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What is Quantitative Research? Definition, Methods, Types, and Examples
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If you’re wondering what is quantitative research and whether this methodology works for your research study, you’re not alone. If you want a simple quantitative research definition , then it’s enough to say that this is a method undertaken by researchers based on their study requirements. However, to select the most appropriate research for their study type, researchers should know all the methods available.
Selecting the right research method depends on a few important criteria, such as the research question, study type, time, costs, data availability, and availability of respondents. There are two main types of research methods— quantitative research and qualitative research. The purpose of quantitative research is to validate or test a theory or hypothesis and that of qualitative research is to understand a subject or event or identify reasons for observed patterns.
Quantitative research methods are used to observe events that affect a particular group of individuals, which is the sample population. In this type of research, diverse numerical data are collected through various methods and then statistically analyzed to aggregate the data, compare them, or show relationships among the data. Quantitative research methods broadly include questionnaires, structured observations, and experiments.
Here are two quantitative research examples:
- Satisfaction surveys sent out by a company regarding their revamped customer service initiatives. Customers are asked to rate their experience on a rating scale of 1 (poor) to 5 (excellent).
- A school has introduced a new after-school program for children, and a few months after commencement, the school sends out feedback questionnaires to the parents of the enrolled children. Such questionnaires usually include close-ended questions that require either definite answers or a Yes/No option. This helps in a quick, overall assessment of the program’s outreach and success.
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Table of Contents
What is quantitative research ? 1,2
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The steps shown in the figure can be grouped into the following broad steps:
- Theory : Define the problem area or area of interest and create a research question.
- Hypothesis : Develop a hypothesis based on the research question. This hypothesis will be tested in the remaining steps.
- Research design : In this step, the most appropriate quantitative research design will be selected, including deciding on the sample size, selecting respondents, identifying research sites, if any, etc.
- Data collection : This process could be extensive based on your research objective and sample size.
- Data analysis : Statistical analysis is used to analyze the data collected. The results from the analysis help in either supporting or rejecting your hypothesis.
- Present results : Based on the data analysis, conclusions are drawn, and results are presented as accurately as possible.
Quantitative research characteristics 4
- Large sample size : This ensures reliability because this sample represents the target population or market. Due to the large sample size, the outcomes can be generalized to the entire population as well, making this one of the important characteristics of quantitative research .
- Structured data and measurable variables: The data are numeric and can be analyzed easily. Quantitative research involves the use of measurable variables such as age, salary range, highest education, etc.
- Easy-to-use data collection methods : The methods include experiments, controlled observations, and questionnaires and surveys with a rating scale or close-ended questions, which require simple and to-the-point answers; are not bound by geographical regions; and are easy to administer.
- Data analysis : Structured and accurate statistical analysis methods using software applications such as Excel, SPSS, R. The analysis is fast, accurate, and less effort intensive.
- Reliable : The respondents answer close-ended questions, their responses are direct without ambiguity and yield numeric outcomes, which are therefore highly reliable.
- Reusable outcomes : This is one of the key characteristics – outcomes of one research can be used and replicated in other research as well and is not exclusive to only one study.
Quantitative research methods 5
Quantitative research methods are classified into two types—primary and secondary.
Primary quantitative research method:
In this type of quantitative research , data are directly collected by the researchers using the following methods.
– Survey research : Surveys are the easiest and most commonly used quantitative research method . They are of two types— cross-sectional and longitudinal.
->Cross-sectional surveys are specifically conducted on a target population for a specified period, that is, these surveys have a specific starting and ending time and researchers study the events during this period to arrive at conclusions. The main purpose of these surveys is to describe and assess the characteristics of a population. There is one independent variable in this study, which is a common factor applicable to all participants in the population, for example, living in a specific city, diagnosed with a specific disease, of a certain age group, etc. An example of a cross-sectional survey is a study to understand why individuals residing in houses built before 1979 in the US are more susceptible to lead contamination.
->Longitudinal surveys are conducted at different time durations. These surveys involve observing the interactions among different variables in the target population, exposing them to various causal factors, and understanding their effects across a longer period. These studies are helpful to analyze a problem in the long term. An example of a longitudinal study is the study of the relationship between smoking and lung cancer over a long period.
– Descriptive research : Explains the current status of an identified and measurable variable. Unlike other types of quantitative research , a hypothesis is not needed at the beginning of the study and can be developed even after data collection. This type of quantitative research describes the characteristics of a problem and answers the what, when, where of a problem. However, it doesn’t answer the why of the problem and doesn’t explore cause-and-effect relationships between variables. Data from this research could be used as preliminary data for another study. Example: A researcher undertakes a study to examine the growth strategy of a company. This sample data can be used by other companies to determine their own growth strategy.
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– Correlational research : This quantitative research method is used to establish a relationship between two variables using statistical analysis and analyze how one affects the other. The research is non-experimental because the researcher doesn’t control or manipulate any of the variables. At least two separate sample groups are needed for this research. Example: Researchers studying a correlation between regular exercise and diabetes.
– Causal-comparative research : This type of quantitative research examines the cause-effect relationships in retrospect between a dependent and independent variable and determines the causes of the already existing differences between groups of people. This is not a true experiment because it doesn’t assign participants to groups randomly. Example: To study the wage differences between men and women in the same role. For this, already existing wage information is analyzed to understand the relationship.
– Experimental research : This quantitative research method uses true experiments or scientific methods for determining a cause-effect relation between variables. It involves testing a hypothesis through experiments, in which one or more independent variables are manipulated and then their effect on dependent variables are studied. Example: A researcher studies the importance of a drug in treating a disease by administering the drug in few patients and not administering in a few.
The following data collection methods are commonly used in primary quantitative research :
- Sampling : The most common type is probability sampling, in which a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are—simple random, systematic, stratified, and cluster sampling.
- Interviews : These are commonly telephonic or face-to-face.
- Observations : Structured observations are most commonly used in quantitative research . In this method, researchers make observations about specific behaviors of individuals in a structured setting.
- Document review : Reviewing existing research or documents to collect evidence for supporting the quantitative research .
- Surveys and questionnaires : Surveys can be administered both online and offline depending on the requirement and sample size.
The data collected can be analyzed in several ways in quantitative research , as listed below:
- Cross-tabulation —Uses a tabular format to draw inferences among collected data
- MaxDiff analysis —Gauges the preferences of the respondents
- TURF analysis —Total Unduplicated Reach and Frequency Analysis; helps in determining the market strategy for a business
- Gap analysis —Identify gaps in attaining the desired results
- SWOT analysis —Helps identify strengths, weaknesses, opportunities, and threats of a product, service, or organization
- Text analysis —Used for interpreting unstructured data
Secondary quantitative research methods :
This method involves conducting research using already existing or secondary data. This method is less effort intensive and requires lesser time. However, researchers should verify the authenticity and recency of the sources being used and ensure their accuracy.
The main sources of secondary data are:
- The Internet
- Government and non-government sources
- Public libraries
- Educational institutions
- Commercial information sources such as newspapers, journals, radio, TV
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When to use quantitative research 6
Here are some simple ways to decide when to use quantitative research . Use quantitative research to:
- recommend a final course of action
- find whether a consensus exists regarding a particular subject
- generalize results to a larger population
- determine a cause-and-effect relationship between variables
- describe characteristics of specific groups of people
- test hypotheses and examine specific relationships
- identify and establish size of market segments
A research case study to understand when to use quantitative research 7
Context: A study was undertaken to evaluate a major innovation in a hospital’s design, in terms of workforce implications and impact on patient and staff experiences of all single-room hospital accommodations. The researchers undertook a mixed methods approach to answer their research questions. Here, we focus on the quantitative research aspect.
Research questions : What are the advantages and disadvantages for the staff as a result of the hospital’s move to the new design with all single-room accommodations? Did the move affect staff experience and well-being and improve their ability to deliver high-quality care?
Method: The researchers obtained quantitative data from three sources:
- Staff activity (task time distribution): Each staff member was shadowed by a researcher who observed each task undertaken by the staff, and logged the time spent on each activity.
- Staff travel distances : The staff were requested to wear pedometers, which recorded the distances covered.
- Staff experience surveys : Staff were surveyed before and after the move to the new hospital design.
Results of quantitative research : The following observations were made based on quantitative data analysis:
- The move to the new design did not result in a significant change in the proportion of time spent on different activities.
- Staff activity events observed per session were higher after the move, and direct care and professional communication events per hour decreased significantly, suggesting fewer interruptions and less fragmented care.
- A significant increase in medication tasks among the recorded events suggests that medication administration was integrated into patient care activities.
- Travel distances increased for all staff, with highest increases for staff in the older people’s ward and surgical wards.
- Ratings for staff toilet facilities, locker facilities, and space at staff bases were higher but those for social interaction and natural light were lower.
Advantages of quantitative research 1,2
When choosing the right research methodology, also consider the advantages of quantitative research and how it can impact your study.
- Quantitative research methods are more scientific and rational. They use quantifiable data leading to objectivity in the results and avoid any chances of ambiguity.
- This type of research uses numeric data so analysis is relatively easier .
- In most cases, a hypothesis is already developed and quantitative research helps in testing and validatin g these constructed theories based on which researchers can make an informed decision about accepting or rejecting their theory.
- The use of statistical analysis software ensures quick analysis of large volumes of data and is less effort intensive.
- Higher levels of control can be applied to the research so the chances of bias can be reduced.
- Quantitative research is based on measured value s, facts, and verifiable information so it can be easily checked or replicated by other researchers leading to continuity in scientific research.
Disadvantages of quantitative research 1,2
Quantitative research may also be limiting; take a look at the disadvantages of quantitative research.
- Experiments are conducted in controlled settings instead of natural settings and it is possible for researchers to either intentionally or unintentionally manipulate the experiment settings to suit the results they desire.
- Participants must necessarily give objective answers (either one- or two-word, or yes or no answers) and the reasons for their selection or the context are not considered.
- Inadequate knowledge of statistical analysis methods may affect the results and their interpretation.
- Although statistical analysis indicates the trends or patterns among variables, the reasons for these observed patterns cannot be interpreted and the research may not give a complete picture.
- Large sample sizes are needed for more accurate and generalizable analysis .
- Quantitative research cannot be used to address complex issues.
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Frequently asked questions on quantitative research
Q: What is the difference between quantitative research and qualitative research? 1
A: The following table lists the key differences between quantitative research and qualitative research, some of which may have been mentioned earlier in the article.
Purpose and design | ||
Research question | ||
Sample size | Large | Small |
Data | ||
Data collection method | Experiments, controlled observations, questionnaires and surveys with a rating scale or close-ended questions. The methods can be experimental, quasi-experimental, descriptive, or correlational. | Semi-structured interviews/surveys with open-ended questions, document study/literature reviews, focus groups, case study research, ethnography |
Data analysis |
Q: What is the difference between reliability and validity? 8,9
A: The term reliability refers to the consistency of a research study. For instance, if a food-measuring weighing scale gives different readings every time the same quantity of food is measured then that weighing scale is not reliable. If the findings in a research study are consistent every time a measurement is made, then the study is considered reliable. However, it is usually unlikely to obtain the exact same results every time because some contributing variables may change. In such cases, a correlation coefficient is used to assess the degree of reliability. A strong positive correlation between the results indicates reliability.
Validity can be defined as the degree to which a tool actually measures what it claims to measure. It helps confirm the credibility of your research and suggests that the results may be generalizable. In other words, it measures the accuracy of the research.
The following table gives the key differences between reliability and validity.
Importance | Refers to the consistency of a measure | Refers to the accuracy of a measure |
Ease of achieving | Easier, yields results faster | Involves more analysis, more difficult to achieve |
Assessment method | By examining the consistency of outcomes over time, between various observers, and within the test | By comparing the accuracy of the results with accepted theories and other measurements of the same idea |
Relationship | Unreliable measurements typically cannot be valid | Valid measurements are also reliable |
Types | Test-retest reliability, internal consistency, inter-rater reliability | Content validity, criterion validity, face validity, construct validity |
Q: What is mixed methods research? 10
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A: A mixed methods approach combines the characteristics of both quantitative research and qualitative research in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method. A mixed methods research design is useful in case of research questions that cannot be answered by either quantitative research or qualitative research alone. However, this method could be more effort- and cost-intensive because of the requirement of more resources. The figure 3 shows some basic mixed methods research designs that could be used.
Thus, quantitative research is the appropriate method for testing your hypotheses and can be used either alone or in combination with qualitative research per your study requirements. We hope this article has provided an insight into the various facets of quantitative research , including its different characteristics, advantages, and disadvantages, and a few tips to quickly understand when to use this research method.
References
- Qualitative vs quantitative research: Differences, examples, & methods. Simply Psychology. Accessed Feb 28, 2023. https://simplypsychology.org/qualitative-quantitative.html#Quantitative-Research
- Your ultimate guide to quantitative research. Qualtrics. Accessed February 28, 2023. https://www.qualtrics.com/uk/experience-management/research/quantitative-research/
- The steps of quantitative research. Revise Sociology. Accessed March 1, 2023. https://revisesociology.com/2017/11/26/the-steps-of-quantitative-research/
- What are the characteristics of quantitative research? Marketing91. Accessed March 1, 2023. https://www.marketing91.com/characteristics-of-quantitative-research/
- Quantitative research: Types, characteristics, methods, & examples. ProProfs Survey Maker. Accessed February 28, 2023. https://www.proprofssurvey.com/blog/quantitative-research/#Characteristics_of_Quantitative_Research
- Qualitative research isn’t as scientific as quantitative methods. Kmusial blog. Accessed March 5, 2023. https://kmusial.wordpress.com/2011/11/25/qualitative-research-isnt-as-scientific-as-quantitative-methods/
- Maben J, Griffiths P, Penfold C, et al. Evaluating a major innovation in hospital design: workforce implications and impact on patient and staff experiences of all single room hospital accommodation. Southampton (UK): NIHR Journals Library; 2015 Feb. (Health Services and Delivery Research, No. 3.3.) Chapter 5, Case study quantitative data findings. Accessed March 6, 2023. https://www.ncbi.nlm.nih.gov/books/NBK274429/
- McLeod, S. A. (2007). What is reliability? Simply Psychology. www.simplypsychology.org/reliability.html
- Reliability vs validity: Differences & examples. Accessed March 5, 2023. https://statisticsbyjim.com/basics/reliability-vs-validity/
- Mixed methods research. Community Engagement Program. Harvard Catalyst. Accessed February 28, 2023. https://catalyst.harvard.edu/community-engagement/mmr
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- What Is Quantitative Research? | Definition & Methods
What Is Quantitative Research? | Definition & Methods
Published on 4 April 2022 by Pritha Bhandari . Revised on 10 October 2022.
Quantitative research is the process of collecting and analysing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalise results to wider populations.
Quantitative research is the opposite of qualitative research , which involves collecting and analysing non-numerical data (e.g. text, video, or audio).
Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.
- What is the demographic makeup of Singapore in 2020?
- How has the average temperature changed globally over the last century?
- Does environmental pollution affect the prevalence of honey bees?
- Does working from home increase productivity for people with long commutes?
Table of contents
Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, frequently asked questions about quantitative research.
You can use quantitative research methods for descriptive, correlational or experimental research.
- In descriptive research , you simply seek an overall summary of your study variables.
- In correlational research , you investigate relationships between your study variables.
- In experimental research , you systematically examine whether there is a cause-and-effect relationship between variables.
Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalised to broader populations based on the sampling method used.
To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).
Research method | How to use | Example |
---|---|---|
Control or manipulate an to measure its effect on a dependent variable. | To test whether an intervention can reduce procrastination in college students, you give equal-sized groups either a procrastination intervention or a comparable task. You compare self-ratings of procrastination behaviors between the groups after the intervention. | |
Ask questions of a group of people in-person, over-the-phone or online. | You distribute with rating scales to first-year international college students to investigate their experiences of culture shock. | |
(Systematic) observation | Identify a behavior or occurrence of interest and monitor it in its natural setting. | To study college classroom participation, you sit in on classes to observe them, counting and recording the prevalence of active and passive behaviors by students from different backgrounds. |
Secondary research | Collect data that has been gathered for other purposes e.g., national surveys or historical records. | To assess whether attitudes towards climate change have changed since the 1980s, you collect relevant questionnaire data from widely available . |
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Once data is collected, you may need to process it before it can be analysed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .
Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualise your data and check for any trends or outliers.
Using inferential statistics , you can make predictions or generalisations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .
You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.
Quantitative research is often used to standardise data collection and generalise findings . Strengths of this approach include:
- Replication
Repeating the study is possible because of standardised data collection protocols and tangible definitions of abstract concepts.
- Direct comparisons of results
The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.
- Large samples
Data from large samples can be processed and analysed using reliable and consistent procedures through quantitative data analysis.
- Hypothesis testing
Using formalised and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.
Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:
- Superficiality
Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.
- Narrow focus
Predetermined variables and measurement procedures can mean that you ignore other relevant observations.
- Structural bias
Despite standardised procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.
- Lack of context
Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.
In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.
Operationalisation means turning abstract conceptual ideas into measurable observations.
For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.
Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.
Reliability and validity are both about how well a method measures something:
- Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions).
- Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).
If you are doing experimental research , you also have to consider the internal and external validity of your experiment.
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.
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Pritha Bhandari
Qualitative vs Quantitative Research Methods & Data Analysis
Saul McLeod, PhD
Editor-in-Chief for Simply Psychology
BSc (Hons) Psychology, MRes, PhD, University of Manchester
Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.
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Olivia Guy-Evans, MSc
Associate Editor for Simply Psychology
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Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.
The main difference between quantitative and qualitative research is the type of data they collect and analyze.
Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.
- Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed numerically. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.
- Qualitative research gathers non-numerical data (words, images, sounds) to explore subjective experiences and attitudes, often via observation and interviews. It aims to produce detailed descriptions and uncover new insights about the studied phenomenon.
On This Page:
What Is Qualitative Research?
Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.
Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.
Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)
Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).
Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human. Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).
Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.
Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.
Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.
Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.
Qualitative Methods
There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography .
The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.
The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)
Here are some examples of qualitative data:
Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.
Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.
Unstructured interviews : generate qualitative data through the use of open questions. This allows the respondent to talk in some depth, choosing their own words. This helps the researcher develop a real sense of a person’s understanding of a situation.
Diaries or journals : Written accounts of personal experiences or reflections.
Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.
Qualitative Data Analysis
Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.
Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis .
For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .
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Key Features
- Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
- Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
- The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
- The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
- The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.
Limitations of Qualitative Research
- Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
- The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
- Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
- The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.
Advantages of Qualitative Research
- Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
- Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
- Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
- Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.
What Is Quantitative Research?
Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.
The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.
Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.
Quantitative Methods
Experiments typically yield quantitative data, as they are concerned with measuring things. However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.
For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).
Experimental methods limit how research participants react to and express appropriate social behavior.
Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.
There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:
Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .
The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.
Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.
This data can be analyzed to identify brain regions involved in specific mental processes or disorders.
For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.
The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms.
Quantitative Data Analysis
Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.
Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).
- Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
- The research aims for objectivity (i.e., without bias) and is separated from the data.
- The design of the study is determined before it begins.
- For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
- Research is used to test a theory and ultimately support or reject it.
Limitations of Quantitative Research
- Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
- Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
- Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
- Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.
Advantages of Quantitative Research
- Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
- Useful for testing and validating already constructed theories.
- Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
- Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
- Hypotheses can also be tested because of statistical analysis (Antonius, 2003).
Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.
Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.
Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.
Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.
Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.
Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.
Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.
Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.
Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage
Further Information
- Mixed methods research
- Designing qualitative research
- Methods of data collection and analysis
- Introduction to quantitative and qualitative research
- Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
- Qualitative research in health care: Analysing qualitative data
- Qualitative data analysis: the framework approach
- Using the framework method for the analysis of
- Qualitative data in multi-disciplinary health research
- Content Analysis
- Grounded Theory
- Thematic Analysis
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Quantitative research methods
a method of research that relies on measuring variables using a numerical system, analyzing these measurements using any of a variety of statistical models, and reporting relationships and associations among the studied variables. For example, these variables may be test scores or measurements of reaction time. The goal of gathering this quantitative data is to understand, describe, and predict the nature of a phenomenon, particularly through the development of models and theories. Quantitative research techniques include experiments and surveys.
SAGE Research Methods Videos
What are the strengths of quantitative research.
Professor Norma T. Mertz briefly discusses qualitative research and how it has changed since she entered the field. She emphasizes the importance of defining a research question before choosing a theoretical approach to research.
This is just one segment in a series about quantitative methods. You can find additional videos in our SAGE database, Research Methods:
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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles
Edward barroga.
1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.
Glafera Janet Matanguihan
2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.
The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.
INTRODUCTION
Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6
It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4
There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.
DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES
A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5
On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4
Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8
Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12
CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES
Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13
There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10
TYPES OF RESEARCH QUESTIONS AND HYPOTHESES
Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .
Quantitative research questions | Quantitative research hypotheses |
---|---|
Descriptive research questions | Simple hypothesis |
Comparative research questions | Complex hypothesis |
Relationship research questions | Directional hypothesis |
Non-directional hypothesis | |
Associative hypothesis | |
Causal hypothesis | |
Null hypothesis | |
Alternative hypothesis | |
Working hypothesis | |
Statistical hypothesis | |
Logical hypothesis | |
Hypothesis-testing | |
Qualitative research questions | Qualitative research hypotheses |
Contextual research questions | Hypothesis-generating |
Descriptive research questions | |
Evaluation research questions | |
Explanatory research questions | |
Exploratory research questions | |
Generative research questions | |
Ideological research questions | |
Ethnographic research questions | |
Phenomenological research questions | |
Grounded theory questions | |
Qualitative case study questions |
Research questions in quantitative research
In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .
Quantitative research questions | |
---|---|
Descriptive research question | |
- Measures responses of subjects to variables | |
- Presents variables to measure, analyze, or assess | |
What is the proportion of resident doctors in the hospital who have mastered ultrasonography (response of subjects to a variable) as a diagnostic technique in their clinical training? | |
Comparative research question | |
- Clarifies difference between one group with outcome variable and another group without outcome variable | |
Is there a difference in the reduction of lung metastasis in osteosarcoma patients who received the vitamin D adjunctive therapy (group with outcome variable) compared with osteosarcoma patients who did not receive the vitamin D adjunctive therapy (group without outcome variable)? | |
- Compares the effects of variables | |
How does the vitamin D analogue 22-Oxacalcitriol (variable 1) mimic the antiproliferative activity of 1,25-Dihydroxyvitamin D (variable 2) in osteosarcoma cells? | |
Relationship research question | |
- Defines trends, association, relationships, or interactions between dependent variable and independent variable | |
Is there a relationship between the number of medical student suicide (dependent variable) and the level of medical student stress (independent variable) in Japan during the first wave of the COVID-19 pandemic? |
Hypotheses in quantitative research
In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .
Quantitative research hypotheses | |
---|---|
Simple hypothesis | |
- Predicts relationship between single dependent variable and single independent variable | |
If the dose of the new medication (single independent variable) is high, blood pressure (single dependent variable) is lowered. | |
Complex hypothesis | |
- Foretells relationship between two or more independent and dependent variables | |
The higher the use of anticancer drugs, radiation therapy, and adjunctive agents (3 independent variables), the higher would be the survival rate (1 dependent variable). | |
Directional hypothesis | |
- Identifies study direction based on theory towards particular outcome to clarify relationship between variables | |
Privately funded research projects will have a larger international scope (study direction) than publicly funded research projects. | |
Non-directional hypothesis | |
- Nature of relationship between two variables or exact study direction is not identified | |
- Does not involve a theory | |
Women and men are different in terms of helpfulness. (Exact study direction is not identified) | |
Associative hypothesis | |
- Describes variable interdependency | |
- Change in one variable causes change in another variable | |
A larger number of people vaccinated against COVID-19 in the region (change in independent variable) will reduce the region’s incidence of COVID-19 infection (change in dependent variable). | |
Causal hypothesis | |
- An effect on dependent variable is predicted from manipulation of independent variable | |
A change into a high-fiber diet (independent variable) will reduce the blood sugar level (dependent variable) of the patient. | |
Null hypothesis | |
- A negative statement indicating no relationship or difference between 2 variables | |
There is no significant difference in the severity of pulmonary metastases between the new drug (variable 1) and the current drug (variable 2). | |
Alternative hypothesis | |
- Following a null hypothesis, an alternative hypothesis predicts a relationship between 2 study variables | |
The new drug (variable 1) is better on average in reducing the level of pain from pulmonary metastasis than the current drug (variable 2). | |
Working hypothesis | |
- A hypothesis that is initially accepted for further research to produce a feasible theory | |
Dairy cows fed with concentrates of different formulations will produce different amounts of milk. | |
Statistical hypothesis | |
- Assumption about the value of population parameter or relationship among several population characteristics | |
- Validity tested by a statistical experiment or analysis | |
The mean recovery rate from COVID-19 infection (value of population parameter) is not significantly different between population 1 and population 2. | |
There is a positive correlation between the level of stress at the workplace and the number of suicides (population characteristics) among working people in Japan. | |
Logical hypothesis | |
- Offers or proposes an explanation with limited or no extensive evidence | |
If healthcare workers provide more educational programs about contraception methods, the number of adolescent pregnancies will be less. | |
Hypothesis-testing (Quantitative hypothesis-testing research) | |
- Quantitative research uses deductive reasoning. | |
- This involves the formation of a hypothesis, collection of data in the investigation of the problem, analysis and use of the data from the investigation, and drawing of conclusions to validate or nullify the hypotheses. |
Research questions in qualitative research
Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15
There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .
Qualitative research questions | |
---|---|
Contextual research question | |
- Ask the nature of what already exists | |
- Individuals or groups function to further clarify and understand the natural context of real-world problems | |
What are the experiences of nurses working night shifts in healthcare during the COVID-19 pandemic? (natural context of real-world problems) | |
Descriptive research question | |
- Aims to describe a phenomenon | |
What are the different forms of disrespect and abuse (phenomenon) experienced by Tanzanian women when giving birth in healthcare facilities? | |
Evaluation research question | |
- Examines the effectiveness of existing practice or accepted frameworks | |
How effective are decision aids (effectiveness of existing practice) in helping decide whether to give birth at home or in a healthcare facility? | |
Explanatory research question | |
- Clarifies a previously studied phenomenon and explains why it occurs | |
Why is there an increase in teenage pregnancy (phenomenon) in Tanzania? | |
Exploratory research question | |
- Explores areas that have not been fully investigated to have a deeper understanding of the research problem | |
What factors affect the mental health of medical students (areas that have not yet been fully investigated) during the COVID-19 pandemic? | |
Generative research question | |
- Develops an in-depth understanding of people’s behavior by asking ‘how would’ or ‘what if’ to identify problems and find solutions | |
How would the extensive research experience of the behavior of new staff impact the success of the novel drug initiative? | |
Ideological research question | |
- Aims to advance specific ideas or ideologies of a position | |
Are Japanese nurses who volunteer in remote African hospitals able to promote humanized care of patients (specific ideas or ideologies) in the areas of safe patient environment, respect of patient privacy, and provision of accurate information related to health and care? | |
Ethnographic research question | |
- Clarifies peoples’ nature, activities, their interactions, and the outcomes of their actions in specific settings | |
What are the demographic characteristics, rehabilitative treatments, community interactions, and disease outcomes (nature, activities, their interactions, and the outcomes) of people in China who are suffering from pneumoconiosis? | |
Phenomenological research question | |
- Knows more about the phenomena that have impacted an individual | |
What are the lived experiences of parents who have been living with and caring for children with a diagnosis of autism? (phenomena that have impacted an individual) | |
Grounded theory question | |
- Focuses on social processes asking about what happens and how people interact, or uncovering social relationships and behaviors of groups | |
What are the problems that pregnant adolescents face in terms of social and cultural norms (social processes), and how can these be addressed? | |
Qualitative case study question | |
- Assesses a phenomenon using different sources of data to answer “why” and “how” questions | |
- Considers how the phenomenon is influenced by its contextual situation. | |
How does quitting work and assuming the role of a full-time mother (phenomenon assessed) change the lives of women in Japan? |
Qualitative research hypotheses | |
---|---|
Hypothesis-generating (Qualitative hypothesis-generating research) | |
- Qualitative research uses inductive reasoning. | |
- This involves data collection from study participants or the literature regarding a phenomenon of interest, using the collected data to develop a formal hypothesis, and using the formal hypothesis as a framework for testing the hypothesis. | |
- Qualitative exploratory studies explore areas deeper, clarifying subjective experience and allowing formulation of a formal hypothesis potentially testable in a future quantitative approach. |
Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15
Hypotheses in qualitative research
Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1
FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES
Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14
The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14
As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.
Variables | Unclear and weak statement (Statement 1) | Clear and good statement (Statement 2) | Points to avoid |
---|---|---|---|
Research question | Which is more effective between smoke moxibustion and smokeless moxibustion? | “Moreover, regarding smoke moxibustion versus smokeless moxibustion, it remains unclear which is more effective, safe, and acceptable to pregnant women, and whether there is any difference in the amount of heat generated.” | 1) Vague and unfocused questions |
2) Closed questions simply answerable by yes or no | |||
3) Questions requiring a simple choice | |||
Hypothesis | The smoke moxibustion group will have higher cephalic presentation. | “Hypothesis 1. The smoke moxibustion stick group (SM group) and smokeless moxibustion stick group (-SLM group) will have higher rates of cephalic presentation after treatment than the control group. | 1) Unverifiable hypotheses |
Hypothesis 2. The SM group and SLM group will have higher rates of cephalic presentation at birth than the control group. | 2) Incompletely stated groups of comparison | ||
Hypothesis 3. There will be no significant differences in the well-being of the mother and child among the three groups in terms of the following outcomes: premature birth, premature rupture of membranes (PROM) at < 37 weeks, Apgar score < 7 at 5 min, umbilical cord blood pH < 7.1, admission to neonatal intensive care unit (NICU), and intrauterine fetal death.” | 3) Insufficiently described variables or outcomes | ||
Research objective | To determine which is more effective between smoke moxibustion and smokeless moxibustion. | “The specific aims of this pilot study were (a) to compare the effects of smoke moxibustion and smokeless moxibustion treatments with the control group as a possible supplement to ECV for converting breech presentation to cephalic presentation and increasing adherence to the newly obtained cephalic position, and (b) to assess the effects of these treatments on the well-being of the mother and child.” | 1) Poor understanding of the research question and hypotheses |
2) Insufficient description of population, variables, or study outcomes |
a These statements were composed for comparison and illustrative purposes only.
b These statements are direct quotes from Higashihara and Horiuchi. 16
Variables | Unclear and weak statement (Statement 1) | Clear and good statement (Statement 2) | Points to avoid |
---|---|---|---|
Research question | Does disrespect and abuse (D&A) occur in childbirth in Tanzania? | How does disrespect and abuse (D&A) occur and what are the types of physical and psychological abuses observed in midwives’ actual care during facility-based childbirth in urban Tanzania? | 1) Ambiguous or oversimplistic questions |
2) Questions unverifiable by data collection and analysis | |||
Hypothesis | Disrespect and abuse (D&A) occur in childbirth in Tanzania. | Hypothesis 1: Several types of physical and psychological abuse by midwives in actual care occur during facility-based childbirth in urban Tanzania. | 1) Statements simply expressing facts |
Hypothesis 2: Weak nursing and midwifery management contribute to the D&A of women during facility-based childbirth in urban Tanzania. | 2) Insufficiently described concepts or variables | ||
Research objective | To describe disrespect and abuse (D&A) in childbirth in Tanzania. | “This study aimed to describe from actual observations the respectful and disrespectful care received by women from midwives during their labor period in two hospitals in urban Tanzania.” | 1) Statements unrelated to the research question and hypotheses |
2) Unattainable or unexplorable objectives |
a This statement is a direct quote from Shimoda et al. 17
The other statements were composed for comparison and illustrative purposes only.
CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES
To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .
![Click on image to zoom An external file that holds a picture, illustration, etc.
Object name is jkms-37-e121-g001.jpg](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039193/bin/jkms-37-e121-g001.jpg)
Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.
Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12
In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.
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EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES
- EXAMPLE 1. Descriptive research question (quantitative research)
- - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
- “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
- RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
- EXAMPLE 2. Relationship research question (quantitative research)
- - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
- “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
- Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
- EXAMPLE 3. Comparative research question (quantitative research)
- - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
- “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
- RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
- STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
- EXAMPLE 4. Exploratory research question (qualitative research)
- - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
- “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
- EXAMPLE 5. Relationship research question (quantitative research)
- - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
- “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23
EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES
- EXAMPLE 1. Working hypothesis (quantitative research)
- - A hypothesis that is initially accepted for further research to produce a feasible theory
- “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
- “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
- EXAMPLE 2. Exploratory hypothesis (qualitative research)
- - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
- “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
- “Conclusion
- Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
- EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
- “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
- Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
- EXAMPLE 4. Statistical hypothesis (quantitative research)
- - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
- “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
- “Statistical Analysis
- ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27
EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS
- EXAMPLE 1. Background, hypotheses, and aims are provided
- “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
- “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
- “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
- EXAMPLE 2. Background, hypotheses, and aims are provided
- “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
- “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
- EXAMPLE 3. Background, aim, and hypothesis are provided
- “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
- “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
- “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30
Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.
Disclosure: The authors have no potential conflicts of interest to disclose.
Author Contributions:
- Conceptualization: Barroga E, Matanguihan GJ.
- Methodology: Barroga E, Matanguihan GJ.
- Writing - original draft: Barroga E, Matanguihan GJ.
- Writing - review & editing: Barroga E, Matanguihan GJ.
Quantitative research: Understanding the approaches and key elements
Quantitative research has many benefits and challenges but understanding how to properly conduct it can lead to a successful marketing research project.
Choosing the right quantitative approach
Editor’s note: Allison Von Borstel is the associate director of creative analytics at The Sound. This is an edited version of an article that originally appeared under the title “ Understanding Quantitative Research Approaches .”
What is quantitative research?
The systematic approaches that ground quantitative research involve hundreds or thousands of data points for one research project. The wonder of quantitative research is that each data point, or row in a spreadsheet, is a person and has a human story to tell.
Quantitative research aggregates voices and distills them into numbers that uncover trends, illuminates relationships and correlations that inform decision-making with solid evidence and clarity.
The benefits of quantitative approach es
Why choose a quantitative approach? Because you want a very clear story grounded in statistical rigor as a guide to making smart, data-backed decisions.
Quantitative approaches shine because they:
Involve a lot of people
Large sample sizes (think hundreds or thousands) enable researchers to generalize findings because the sample is representative of the total population.
They are grounded in statistical rigor
Allowing for precise measurement and analysis of data, providing statistically significant results that bolster confidence in research.
Reduce bias
Structured data collection and analysis methods enhance the reliability of findings.
Boost efficiency
Quantitative methods often follow a qualitative phase, allowing researchers to validate findings by reporting the perspective of hundreds of people in a fraction of the time.
Widen the analysis’ scope
The copious data collected in just a 20-minute (max) survey positions researchers to evaluate a broad spectrum of variables within the data. This thorough comprehension is instrumental when dealing with complex questions that require in-depth analysis.
Quantitative approaches have hurdles, which include:
Limited flexibility
Once a survey is fielded, or data is gathered, there’s no opportunity to ask a live follow-up question. While it is possible to follow-up with the same people for two surveys, the likelihood of sufficient responses is small.
Battling bots
One of the biggest concerns in data quality is making sure data represents people and not bots.
Missing body language cues
Numbers, words and even images lack the cues that a researcher could pick up on during an interview. Unlike in a qualitative focus group, where one might deduce that a person is uncertain of an answer, in quantitative research, a static response is what the researcher works with.
Understanding quantitative research methods
Quantitative approaches approach research from the same starting point as qualitative approaches – grounded in business objectives with a specific group of people to study.
Once research has kicked off, the business objective thoroughly explored and the approach selected, research follows a general outline:
Consider what data is needed
Think about what type of information needs to be gathered, with an approach in mind. While most quantitative research involves numbers, words and images also count.
- Numbers: Yes, the stereotypical rows of numbers in spreadsheets. Rows that capture people’s opinions and attitudes and are coded to numbers for comparative analytics. Numerical analysis is used for everything from descriptive statistics to regression/predictive analysis.
- Words: Text analysis employs a machine learning model to identify sentiment, emotion and meaning of text. Often used for sentiment analysis or content classification, it can be applied to single-word responses, elaborate open-ends, reviews or even social media posts.
- Images: Image analysis extracts meaningful information from images. A computer vision model that takes images as inputs and outputs numerical information (e.g., having a sample upload their favorite bag of chips and yielding the top three brands).
Design a survey
Create a survey to capture the data needed to address the objective. During this process, different pathways could be written to get a dynamic data set (capturing opinions that derive from various lived experiences). Survey logic is also written to provide a smooth UX experience for respondents.
Prepare the data
The quality of quantitative research rests heavily on the quality of data. After data is collected (typically by fielding a survey or collecting already-existing data, more on that in a bit), it’s time to clean the data.
Begin the analysis process
Now that you have a robust database (including numbers, words or images), it’s time to listen to the story that the data tells. Depending on the research approach used, advanced analytics come into play to tease out insights and nuances for the business objective.
Tell the story
Strip the quantitative jargon and convey the insights from the research. Just because it’s quantitative research does not mean the results have to be told in a monotone drone with a monochrome chart. Answer business objectives dynamically, knowing that research is grounded in statistically sound information.
The two options: Primary vs. secondary research
The two methods that encompass quantitative approaches are primary (collecting data oneself) and secondary (relying on already existing data).
Primary research is primarily used
Most research involves primary data collection – where the researcher collects data directly. The main approach in primary research is survey data collection.
The types of survey questions
Span various measurement scales (nominal, ordinal, interval and ratio) using a mix of question types (single and multi-choice, scales, matrix or open-ends).
Analysis methods
Custom surveys yield great data for a variety of methods in market analysis. Here are a couple favorites:
- Crosstabulation : Used to uncover insights that might not be obvious at first glance. This analysis organizes data into categories, revealing trends or patterns between variables.
- Sentiment analysis: Used to sift through text to gauge emotions, opinions and attitudes. This method helps understand perception, fine-tune strategies and effectively respond to feedback.
- Market sizing: Used to map out the dimensions of a market. By calculating the total potential demand for a product or service in a specific market, this method reveals the scope of opportunities needed to make informed decisions about investment and growth strategies.
- Conjoint analysis : Used to uncover what people value most in products or services. It breaks down features into bits and pieces and asks people to choose their ideal combo. By analyzing these preferences, this analysis reveals the hidden recipe for customer satisfaction.
- Job-To-Be-Done : Used to understand the underlying human motivations that drive people to act. People are multifaceted and experience a myriad of situations each day – meaning that a brand’s competition isn’t limited to in-category.
- Segmentation: Used to identify specific cohorts within a greater population. It groups people with similar characteristics, behaviors or needs together. This method helps tailor products or services to specific groups, boosting satisfaction and sales.
Statistical rigor
Regardless of method, a quantitative approach then enables researchers to draw inferences and make predictions based upon the confidence in the data (looking at confidence intervals, margin of error, etc.)
Let’s not forget secondary research
By accessing a wide range of existing information, this research can be a cost-effective way to gain insights or can supplement primary research findings.
Here are popular options:
Government sources
Government sources can be extremely in-depth, can range across multiple industries and markets and reflect millions of people. This type of data is often instrumental for longitudinal or cultural trends analysis.
Educational institutions
Research universities conduct in-depth studies on a variety of topics, often aggregating government data, nonprofit data and primary data.
Client data
This includes any research that was conducted for or by companies before the present research project. Whether it’s data gathered from customer reviews or prior quantitative work, these secondary resources can help extend findings and detect trends by connecting past data to future data.
Quantitative research enhances research projects
Quantitative research approaches are so much more than “how much” or “how many,” they reveal the why behind people’s actions, emotions and behaviors. By using standardized collection methods, like surveys, quant instills confidence and rigor in findings.
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Quantitative Research: What It Is, Practices & Methods
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Quantitative research involves analyzing and gathering numerical data to uncover trends, calculate averages, evaluate relationships, and derive overarching insights. It’s used in various fields, including the natural and social sciences. Quantitative data analysis employs statistical techniques for processing and interpreting numeric data.
Research designs in the quantitative realm outline how data will be collected and analyzed with methods like experiments and surveys. Qualitative methods complement quantitative research by focusing on non-numerical data, adding depth to understanding. Data collection methods can be qualitative or quantitative, depending on research goals. Researchers often use a combination of both approaches to gain a comprehensive understanding of phenomena.
What is Quantitative Research?
Quantitative research is a systematic investigation of phenomena by gathering quantifiable data and performing statistical, mathematical, or computational techniques. Quantitative research collects statistically significant information from existing and potential customers using sampling methods and sending out online surveys , online polls , and questionnaires , for example.
One of the main characteristics of this type of research is that the results can be depicted in numerical form. After carefully collecting structured observations and understanding these numbers, it’s possible to predict the future of a product or service, establish causal relationships or Causal Research , and make changes accordingly. Quantitative research primarily centers on the analysis of numerical data and utilizes inferential statistics to derive conclusions that can be extrapolated to the broader population.
An example of a quantitative research study is the survey conducted to understand how long a doctor takes to tend to a patient when the patient walks into the hospital. A patient satisfaction survey can be administered to ask questions like how long a doctor takes to see a patient, how often a patient walks into a hospital, and other such questions, which are dependent variables in the research. This kind of research method is often employed in the social sciences, and it involves using mathematical frameworks and theories to effectively present data, ensuring that the results are logical, statistically sound, and unbiased.
Data collection in quantitative research uses a structured method and is typically conducted on larger samples representing the entire population. Researchers use quantitative methods to collect numerical data, which is then subjected to statistical analysis to determine statistically significant findings. This approach is valuable in both experimental research and social research, as it helps in making informed decisions and drawing reliable conclusions based on quantitative data.
Quantitative Research Characteristics
Quantitative research has several unique characteristics that make it well-suited for specific projects. Let’s explore the most crucial of these characteristics so that you can consider them when planning your next research project:
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- Structured tools: Quantitative research relies on structured tools such as surveys, polls, or questionnaires to gather quantitative data . Using such structured methods helps collect in-depth and actionable numerical data from the survey respondents, making it easier to perform data analysis.
- Sample size: Quantitative research is conducted on a significant sample size representing the target market . Appropriate Survey Sampling methods, a fundamental aspect of quantitative research methods, must be employed when deriving the sample to fortify the research objective and ensure the reliability of the results.
- Close-ended questions: Closed-ended questions , specifically designed to align with the research objectives, are a cornerstone of quantitative research. These questions facilitate the collection of quantitative data and are extensively used in data collection processes.
- Prior studies: Before collecting feedback from respondents, researchers often delve into previous studies related to the research topic. This preliminary research helps frame the study effectively and ensures the data collection process is well-informed.
- Quantitative data: Typically, quantitative data is represented using tables, charts, graphs, or other numerical forms. This visual representation aids in understanding the collected data and is essential for rigorous data analysis, a key component of quantitative research methods.
- Generalization of results: One of the strengths of quantitative research is its ability to generalize results to the entire population. It means that the findings derived from a sample can be extrapolated to make informed decisions and take appropriate actions for improvement based on numerical data analysis.
Quantitative Research Methods
Quantitative research methods are systematic approaches used to gather and analyze numerical data to understand and draw conclusions about a phenomenon or population. Here are the quantitative research methods:
- Primary quantitative research methods
- Secondary quantitative research methods
Primary Quantitative Research Methods
Primary quantitative research is the most widely used method of conducting market research. The distinct feature of primary research is that the researcher focuses on collecting data directly rather than depending on data collected from previously done research. Primary quantitative research design can be broken down into three further distinctive tracks and the process flow. They are:
A. Techniques and Types of Studies
There are multiple types of primary quantitative research. They can be distinguished into the four following distinctive methods, which are:
01. Survey Research
Survey Research is fundamental for all quantitative outcome research methodologies and studies. Surveys are used to ask questions to a sample of respondents, using various types such as online polls, online surveys, paper questionnaires, web-intercept surveys , etc. Every small and big organization intends to understand what their customers think about their products and services, how well new features are faring in the market, and other such details.
By conducting survey research, an organization can ask multiple survey questions , collect data from a pool of customers, and analyze this collected data to produce numerical results. It is the first step towards collecting data for any research. You can use single ease questions . A single-ease question is a straightforward query that elicits a concise and uncomplicated response.
This type of research can be conducted with a specific target audience group and also can be conducted across multiple groups along with comparative analysis . A prerequisite for this type of research is that the sample of respondents must have randomly selected members. This way, a researcher can easily maintain the accuracy of the obtained results as a huge variety of respondents will be addressed using random selection.
Traditionally, survey research was conducted face-to-face or via phone calls. Still, with the progress made by online mediums such as email or social media, survey research has also spread to online mediums.There are two types of surveys , either of which can be chosen based on the time in hand and the kind of data required:
Cross-sectional surveys: Cross-sectional surveys are observational surveys conducted in situations where the researcher intends to collect data from a sample of the target population at a given point in time. Researchers can evaluate various variables at a particular time. Data gathered using this type of survey is from people who depict similarity in all variables except the variables which are considered for research . Throughout the survey, this one variable will stay constant.
- Cross-sectional surveys are popular with retail, SMEs, and healthcare industries. Information is garnered without modifying any parameters in the variable ecosystem.
- Multiple samples can be analyzed and compared using a cross-sectional survey research method.
- Multiple variables can be evaluated using this type of survey research.
- The only disadvantage of cross-sectional surveys is that the cause-effect relationship of variables cannot be established as it usually evaluates variables at a particular time and not across a continuous time frame.
Longitudinal surveys: Longitudinal surveys are also observational surveys , but unlike cross-sectional surveys, longitudinal surveys are conducted across various time durations to observe a change in respondent behavior and thought processes. This time can be days, months, years, or even decades. For instance, a researcher planning to analyze the change in buying habits of teenagers over 5 years will conduct longitudinal surveys.
- In cross-sectional surveys, the same variables were evaluated at a given time, and in longitudinal surveys, different variables can be analyzed at different intervals.
- Longitudinal surveys are extensively used in the field of medicine and applied sciences. Apart from these two fields, they are also used to observe a change in the market trend analysis , analyze customer satisfaction, or gain feedback on products/services.
- In situations where the sequence of events is highly essential, longitudinal surveys are used.
- Researchers say that when research subjects need to be thoroughly inspected before concluding, they rely on longitudinal surveys.
02. Correlational Research
A comparison between two entities is invariable. Correlation research is conducted to establish a relationship between two closely-knit entities and how one impacts the other, and what changes are eventually observed. This research method is carried out to give value to naturally occurring relationships, and a minimum of two different groups are required to conduct this quantitative research method successfully. Without assuming various aspects, a relationship between two groups or entities must be established.
Researchers use this quantitative research design to correlate two or more variables using mathematical analysis methods. Patterns, relationships, and trends between variables are concluded as they exist in their original setup. The impact of one of these variables on the other is observed, along with how it changes the relationship between the two variables. Researchers tend to manipulate one of the variables to attain the desired results.
Ideally, it is advised not to make conclusions merely based on correlational research. This is because it is not mandatory that if two variables are in sync that they are interrelated.
Example of Correlational Research Questions :
- The relationship between stress and depression.
- The equation between fame and money.
- The relation between activities in a third-grade class and its students.
03. Causal-comparative Research
This research method mainly depends on the factor of comparison. Also called quasi-experimental research , this quantitative research method is used by researchers to conclude the cause-effect equation between two or more variables, where one variable is dependent on the other independent variable. The independent variable is established but not manipulated, and its impact on the dependent variable is observed. These variables or groups must be formed as they exist in the natural setup. As the dependent and independent variables will always exist in a group, it is advised that the conclusions are carefully established by keeping all the factors in mind.
Causal-comparative research is not restricted to the statistical analysis of two variables but extends to analyzing how various variables or groups change under the influence of the same changes. This research is conducted irrespective of the type of relationship that exists between two or more variables. Statistical analysis plan is used to present the outcome using this quantitative research method.
Example of Causal-Comparative Research Questions:
- The impact of drugs on a teenager. The effect of good education on a freshman. The effect of substantial food provision in the villages of Africa.
04. Experimental Research
Also known as true experimentation, this research method relies on a theory. As the name suggests, experimental research is usually based on one or more theories. This theory has yet to be proven before and is merely a supposition. In experimental research, an analysis is done around proving or disproving the statement. This research method is used in natural sciences. Traditional research methods are more effective than modern techniques.
There can be multiple theories in experimental research. A theory is a statement that can be verified or refuted.
After establishing the statement, efforts are made to understand whether it is valid or invalid. This quantitative research method is mainly used in natural or social sciences as various statements must be proved right or wrong.
- Traditional research methods are more effective than modern techniques.
- Systematic teaching schedules help children who struggle to cope with the course.
- It is a boon to have responsible nursing staff for ailing parents.
B. Data Collection Methodologies
The second major step in primary quantitative research is data collection. Data collection can be divided into sampling methods and data collection using surveys and polls.
01. Data Collection Methodologies: Sampling Methods
There are two main sampling methods for quantitative research: Probability and Non-probability sampling .
Probability sampling: A theory of probability is used to filter individuals from a population and create samples in probability sampling . Participants of a sample are chosen by random selection processes. Each target audience member has an equal opportunity to be selected in the sample.
There are four main types of probability sampling:
- Simple random sampling: As the name indicates, simple random sampling is nothing but a random selection of elements for a sample. This sampling technique is implemented where the target population is considerably large.
- Stratified random sampling: In the stratified random sampling method , a large population is divided into groups (strata), and members of a sample are chosen randomly from these strata. The various segregated strata should ideally not overlap one another.
- Cluster sampling: Cluster sampling is a probability sampling method using which the main segment is divided into clusters, usually using geographic segmentation and demographic segmentation parameters.
- Systematic sampling: Systematic sampling is a technique where the starting point of the sample is chosen randomly, and all the other elements are chosen using a fixed interval. This interval is calculated by dividing the population size by the target sample size.
Non-probability sampling: Non-probability sampling is where the researcher’s knowledge and experience are used to create samples. Because of the researcher’s involvement, not all the target population members have an equal probability of being selected to be a part of a sample.
There are five non-probability sampling models:
- Convenience sampling: In convenience sampling , elements of a sample are chosen only due to one prime reason: their proximity to the researcher. These samples are quick and easy to implement as there is no other parameter of selection involved.
- Consecutive sampling: Consecutive sampling is quite similar to convenience sampling, except for the fact that researchers can choose a single element or a group of samples and conduct research consecutively over a significant period and then perform the same process with other samples.
- Quota sampling: Using quota sampling , researchers can select elements using their knowledge of target traits and personalities to form strata. Members of various strata can then be chosen to be a part of the sample as per the researcher’s understanding.
- Snowball sampling: Snowball sampling is conducted with target audiences who are difficult to contact and get information. It is popular in cases where the target audience for analysis research is rare to put together.
- Judgmental sampling: Judgmental sampling is a non-probability sampling method where samples are created only based on the researcher’s experience and research skill .
02. Data collection methodologies: Using surveys & polls
Once the sample is determined, then either surveys or polls can be distributed to collect the data for quantitative research.
Using surveys for primary quantitative research
A survey is defined as a research method used for collecting data from a pre-defined group of respondents to gain information and insights on various topics of interest. The ease of survey distribution and the wide number of people it can reach depending on the research time and objective makes it one of the most important aspects of conducting quantitative research.
Fundamental levels of measurement – nominal, ordinal, interval, and ratio scales
Four measurement scales are fundamental to creating a multiple-choice question in a survey. They are nominal, ordinal, interval, and ratio measurement scales without the fundamentals of which no multiple-choice questions can be created. Hence, it is crucial to understand these measurement levels to develop a robust survey.
Use of different question types
To conduct quantitative research, close-ended questions must be used in a survey. They can be a mix of multiple question types, including multiple-choice questions like semantic differential scale questions , rating scale questions , etc.
Survey Distribution and Survey Data Collection
In the above, we have seen the process of building a survey along with the research design to conduct primary quantitative research. Survey distribution to collect data is the other important aspect of the survey process. There are different ways of survey distribution. Some of the most commonly used methods are:
- Email: Sending a survey via email is the most widely used and effective survey distribution method. This method’s response rate is high because the respondents know your brand. You can use the QuestionPro email management feature to send out and collect survey responses.
- Buy respondents: Another effective way to distribute a survey and conduct primary quantitative research is to use a sample. Since the respondents are knowledgeable and are on the panel by their own will, responses are much higher.
- Embed survey on a website: Embedding a survey on a website increases a high number of responses as the respondent is already in close proximity to the brand when the survey pops up.
- Social distribution: Using social media to distribute the survey aids in collecting a higher number of responses from the people that are aware of the brand.
- QR code: QuestionPro QR codes store the URL for the survey. You can print/publish this code in magazines, signs, business cards, or on just about any object/medium.
- SMS survey: The SMS survey is a quick and time-effective way to collect a high number of responses.
- Offline Survey App: The QuestionPro App allows users to circulate surveys quickly, and the responses can be collected both online and offline.
Survey example
An example of a survey is a short customer satisfaction (CSAT) survey that can quickly be built and deployed to collect feedback about what the customer thinks about a brand and how satisfied and referenceable the brand is.
Using polls for primary quantitative research
Polls are a method to collect feedback using close-ended questions from a sample. The most commonly used types of polls are election polls and exit polls . Both of these are used to collect data from a large sample size but using basic question types like multiple-choice questions.
C. Data Analysis Techniques
The third aspect of primary quantitative research design is data analysis . After collecting raw data, there must be an analysis of this data to derive statistical inferences from this research. It is important to relate the results to the research objective and establish the statistical relevance of the results.
Remember to consider aspects of research that were not considered for the data collection process and report the difference between what was planned vs. what was actually executed.
It is then required to select precise Statistical Analysis Methods , such as SWOT, Conjoint, Cross-tabulation, etc., to analyze the quantitative data.
- SWOT analysis: SWOT Analysis stands for the acronym of Strengths, Weaknesses, Opportunities, and Threat analysis. Organizations use this statistical analysis technique to evaluate their performance internally and externally to develop effective strategies for improvement.
- Conjoint Analysis: Conjoint Analysis is a market analysis method to learn how individuals make complicated purchasing decisions. Trade-offs are involved in an individual’s daily activities, and these reflect their ability to decide from a complex list of product/service options.
- Cross-tabulation: Cross-tabulation is one of the preliminary statistical market analysis methods which establishes relationships, patterns, and trends within the various parameters of the research study.
- TURF Analysis: TURF Analysis , an acronym for Totally Unduplicated Reach and Frequency Analysis, is executed in situations where the reach of a favorable communication source is to be analyzed along with the frequency of this communication. It is used for understanding the potential of a target market.
Inferential statistics methods such as confidence interval, the margin of error, etc., can then be used to provide results.
Secondary Quantitative Research Methods
Secondary quantitative research or desk research is a research method that involves using already existing data or secondary data. Existing data is summarized and collated to increase the overall effectiveness of the research.
This research method involves collecting quantitative data from existing data sources like the internet, government resources, libraries, research reports, etc. Secondary quantitative research helps to validate the data collected from primary quantitative research and aid in strengthening or proving, or disproving previously collected data.
The following are five popularly used secondary quantitative research methods:
- Data available on the internet: With the high penetration of the internet and mobile devices, it has become increasingly easy to conduct quantitative research using the internet. Information about most research topics is available online, and this aids in boosting the validity of primary quantitative data.
- Government and non-government sources: Secondary quantitative research can also be conducted with the help of government and non-government sources that deal with market research reports. This data is highly reliable and in-depth and hence, can be used to increase the validity of quantitative research design.
- Public libraries: Now a sparingly used method of conducting quantitative research, it is still a reliable source of information, though. Public libraries have copies of important research that was conducted earlier. They are a storehouse of valuable information and documents from which information can be extracted.
- Educational institutions: Educational institutions conduct in-depth research on multiple topics, and hence, the reports that they publish are an important source of validation in quantitative research.
- Commercial information sources: Local newspapers, journals, magazines, radio, and TV stations are great sources to obtain data for secondary quantitative research. These commercial information sources have in-depth, first-hand information on market research, demographic segmentation, and similar subjects.
Quantitative Research Examples
Some examples of quantitative research are:
- A customer satisfaction template can be used if any organization would like to conduct a customer satisfaction (CSAT) survey . Through this kind of survey, an organization can collect quantitative data and metrics on the goodwill of the brand or organization in the customer’s mind based on multiple parameters such as product quality, pricing, customer experience, etc. This data can be collected by asking a net promoter score (NPS) question , matrix table questions, etc. that provide data in the form of numbers that can be analyzed and worked upon.
- Another example of quantitative research is an organization that conducts an event, collecting feedback from attendees about the value they see from the event. By using an event survey , the organization can collect actionable feedback about the satisfaction levels of customers during various phases of the event such as the sales, pre and post-event, the likelihood of recommending the organization to their friends and colleagues, hotel preferences for the future events and other such questions.
What are the Advantages of Quantitative Research?
There are many advantages to quantitative research. Some of the major advantages of why researchers use this method in market research are:
![what is quantitative research approaches advantages-of-quantitative-research](https://www.questionpro.com/blog/wp-content/uploads/2018/04/advantages-of-quantitative-research-min.jpg)
Collect Reliable and Accurate Data:
Quantitative research is a powerful method for collecting reliable and accurate quantitative data. Since data is collected, analyzed, and presented in numbers, the results obtained are incredibly reliable and objective. Numbers do not lie and offer an honest and precise picture of the conducted research without discrepancies. In situations where a researcher aims to eliminate bias and predict potential conflicts, quantitative research is the method of choice.
Quick Data Collection:
Quantitative research involves studying a group of people representing a larger population. Researchers use a survey or another quantitative research method to efficiently gather information from these participants, making the process of analyzing the data and identifying patterns faster and more manageable through the use of statistical analysis. This advantage makes quantitative research an attractive option for projects with time constraints.
Wider Scope of Data Analysis:
Quantitative research, thanks to its utilization of statistical methods, offers an extensive range of data collection and analysis. Researchers can delve into a broader spectrum of variables and relationships within the data, enabling a more thorough comprehension of the subject under investigation. This expanded scope is precious when dealing with complex research questions that require in-depth numerical analysis.
Eliminate Bias:
One of the significant advantages of quantitative research is its ability to eliminate bias. This research method leaves no room for personal comments or the biasing of results, as the findings are presented in numerical form. This objectivity makes the results fair and reliable in most cases, reducing the potential for researcher bias or subjectivity.
In summary, quantitative research involves collecting, analyzing, and presenting quantitative data using statistical analysis. It offers numerous advantages, including the collection of reliable and accurate data, quick data collection, a broader scope of data analysis, and the elimination of bias, making it a valuable approach in the field of research. When considering the benefits of quantitative research, it’s essential to recognize its strengths in contrast to qualitative methods and its role in collecting and analyzing numerical data for a more comprehensive understanding of research topics.
Best Practices to Conduct Quantitative Research
Here are some best practices for conducting quantitative research:
![what is quantitative research approaches Tips to conduct quantitative research](https://www.questionpro.com/blog/wp-content/uploads/2023/02/best-practices-to-conduct-quantitative-research.jpg)
- Differentiate between quantitative and qualitative: Understand the difference between the two methodologies and apply the one that suits your needs best.
- Choose a suitable sample size: Ensure that you have a sample representative of your population and large enough to be statistically weighty.
- Keep your research goals clear and concise: Know your research goals before you begin data collection to ensure you collect the right amount and the right quantity of data.
- Keep the questions simple: Remember that you will be reaching out to a demographically wide audience. Pose simple questions for your respondents to understand easily.
Quantitative Research vs Qualitative Research
Quantitative research and qualitative research are two distinct approaches to conducting research, each with its own set of methods and objectives. Here’s a comparison of the two:
![what is quantitative research approaches what is quantitative research approaches](https://www.questionpro.com/blog/wp-content/uploads/2023/11/Quantitative-Research-VS.-Qualitative-Research.jpg)
Quantitative Research
- Objective: The primary goal of quantitative research is to quantify and measure phenomena by collecting numerical data. It aims to test hypotheses, establish patterns, and generalize findings to a larger population.
- Data Collection: Quantitative research employs systematic and standardized approaches for data collection, including techniques like surveys, experiments, and observations that involve predefined variables. It is often collected from a large and representative sample.
- Data Analysis: Data is analyzed using statistical techniques, such as descriptive statistics, inferential statistics, and mathematical modeling. Researchers use statistical tests to draw conclusions and make generalizations based on numerical data.
- Sample Size: Quantitative research often involves larger sample sizes to ensure statistical significance and generalizability.
- Results: The results are typically presented in tables, charts, and statistical summaries, making them highly structured and objective.
- Generalizability: Researchers intentionally structure quantitative research to generate outcomes that can be helpful to a larger population, and they frequently seek to establish causative connections.
- Emphasis on Objectivity: Researchers aim to minimize bias and subjectivity, focusing on replicable and objective findings.
Qualitative Research
- Objective: Qualitative research seeks to gain a deeper understanding of the underlying motivations, behaviors, and experiences of individuals or groups. It explores the context and meaning of phenomena.
- Data Collection: Qualitative research employs adaptable and open-ended techniques for data collection, including methods like interviews, focus groups, observations, and content analysis. It allows participants to express their perspectives in their own words.
- Data Analysis: Data is analyzed through thematic analysis, content analysis, or grounded theory. Researchers focus on identifying patterns, themes, and insights in the data.
- Sample Size: Qualitative research typically involves smaller sample sizes due to the in-depth nature of data collection and analysis.
- Results: Findings are presented in narrative form, often in the participants’ own words. Results are subjective, context-dependent, and provide rich, detailed descriptions.
- Generalizability: Qualitative research does not aim for broad generalizability but focuses on in-depth exploration within a specific context. It provides a detailed understanding of a particular group or situation.
- Emphasis on Subjectivity: Researchers acknowledge the role of subjectivity and the researcher’s influence on the Research Process . Participant perspectives and experiences are central to the findings.
Researchers choose between quantitative and qualitative research methods based on their research objectives and the nature of the research question. Each approach has its advantages and drawbacks, and the decision between them hinges on the particular research objectives and the data needed to address research inquiries effectively.
Quantitative research is a structured way of collecting and analyzing data from various sources. Its purpose is to quantify the problem and understand its extent, seeking results that someone can project to a larger population.
Companies that use quantitative rather than qualitative research typically aim to measure magnitudes and seek objectively interpreted statistical results. So if you want to obtain quantitative data that helps you define the structured cause-and-effect relationship between the research problem and the factors, you should opt for this type of research.
At QuestionPro , we have various Best Data Collection Tools and features to conduct investigations of this type. You can create questionnaires and distribute them through our various methods. We also have sample services or various questions to guarantee the success of your study and the quality of the collected data.
Quantitative research is a systematic and structured approach to studying phenomena that involves the collection of measurable data and the application of statistical, mathematical, or computational techniques for analysis.
Quantitative research is characterized by structured tools like surveys, substantial sample sizes, closed-ended questions, reliance on prior studies, data presented numerically, and the ability to generalize findings to the broader population.
The two main methods of quantitative research are Primary quantitative research methods, involving data collection directly from sources, and Secondary quantitative research methods, which utilize existing data for analysis.
1.Surveying to measure employee engagement with numerical rating scales. 2.Analyzing sales data to identify trends in product demand and market share. 4.Examining test scores to assess the impact of a new teaching method on student performance. 4.Using website analytics to track user behavior and conversion rates for an online store.
1.Differentiate between quantitative and qualitative approaches. 2.Choose a representative sample size. 3.Define clear research goals before data collection. 4.Use simple and easily understandable survey questions.
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Qualitative vs. quantitative research - what’s the difference?
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What is quantitative research?
What is quantitative research used for, how to collect data for quantitative research, what is qualitative research, what is qualitative research used for, how to collect data for qualitative research, when to use which approach, how to analyze qualitative and quantitative research, analyzing quantitative data, analyzing qualitative data, differences between qualitative and quantitative research, frequently asked questions about qualitative vs. quantitative research, related articles.
Both qualitative and quantitative research are valid and effective approaches to study a particular subject. However, it is important to know that these research approaches serve different purposes and provide different results. This guide will help illustrate quantitative and qualitative research, what they are used for, and the difference between them.
Quantitative research focuses on collecting numerical data and using it to measure variables. As such, quantitative research and data are typically expressed in numbers and graphs. Moreover, this type of research is structured and statistical and the returned results are objective.
The simplest way to describe quantitative research is that it answers the questions " what " or " how much ".
To illustrate what quantitative research is used for, let’s look at a simple example. Let’s assume you want to research the reading habits of a specific part of a population.
With this research, you would like to establish what they read. In other words, do they read fiction, non-fiction, magazines, blogs, and so on? Also, you want to establish what they read about. For example, if they read fiction, is it thrillers, romance novels, or period dramas?
With quantitative research, you can gather concrete data about these reading habits. Your research will then, for example, show that 40% of the audience reads fiction and, of that 40%, 60% prefer romance novels.
In other studies and research projects, quantitative research will work in much the same way. That is, you use it to quantify variables, opinions, behaviors, and more.
Now that we've seen what quantitative research is and what it's used for, let's look at how you'll collect data for it. Because quantitative research is structured and statistical, its data collection methods focus on collecting numerical data.
Some methods to collect this data include:
- Surveys . Surveys are one of the most popular and easiest ways to collect quantitative data. These can include anything from online surveys to paper surveys. It’s important to remember that, to collect quantitative data, you won’t be able to ask open-ended questions.
- Interviews . As is the case with qualitative data, you’ll be able to use interviews to collect quantitative data with the proviso that the data will not be based on open-ended questions.
- Observations . You’ll also be able to use observations to collect quantitative data. However, here you’ll need to make observations in an environment where variables can’t be controlled.
- Website interceptors . With website interceptors, you’ll be able to get real-time insights into a specific product, service, or subject. In most cases, these interceptors take the form of surveys displayed on websites or invitations on the website to complete the survey.
- Longitudinal studies . With these studies, you’ll gather data on the same variables over specified time periods. Longitudinal studies are often used in medical sciences and include, for instance, diet studies. It’s important to remember that, for the results to be reliable, you’ll have to collect data from the same subjects.
- Online polls . Similar to website interceptors, online polls allow you to gather data from websites or social media platforms. These polls are short with only a few options and can give you valuable insights into a very specific question or topic.
- Experiments . With experiments, you’ll manipulate some variables (your independent variables) and gather data on causal relationships between others (your dependent variables). You’ll then measure what effect the manipulation of the independent variables has on the dependent variables.
Qualitative research focuses on collecting and analyzing non-numerical data. As such, it's typically unstructured and non-statistical. The main aim of qualitative research is to get a better understanding and insights into concepts, topics, and subjects.
The easiest way to describe qualitative research is that it answers the question " why ".
Considering that qualitative research aims to provide more profound insights and understanding into specific subjects, we’ll use our example mentioned earlier to explain what qualitative research is used for.
Based on this example, you’ve now established that 40% of the population reads fiction. You’ve probably also discovered in what proportion the population consumes other reading materials.
Qualitative research will now enable you to learn the reasons for these reading habits. For example, it will show you why 40% of the readers prefer fiction, while, for instance, only 10% prefer thrillers. It thus gives you an understanding of your participants’ behaviors and actions.
We've now recapped what qualitative research is and what it's used for. Let's now consider some methods to collect data for this type of research.
Some of these data collection methods include:
- Interviews . These include one-on-one interviews with respondents where you ask open-ended questions. You’ll then record the answers from every respondent and analyze these answers later.
- Open-ended survey questions . Open-ended survey questions give you insights into why respondents feel the way they do about a particular aspect.
- Focus groups . Focus groups allow you to have conversations with small groups of people and record their opinions and views about a specific topic.
- Observations . Observations like ethnography require that you participate in a specific organization or group in order to record their routines and interactions. This will, for instance, be the case where you want to establish how customers use a product in real-life scenarios.
- Literature reviews . With literature reviews, you’ll analyze the published works of other authors to analyze the prevailing view regarding a specific subject.
- Diary studies . Diary studies allow you to collect data about peoples’ habits, activities, and experiences over time. This will, for example, show you how customers use a product, when they use it, and what motivates them.
Now, the immediate question is: When should you use qualitative research, and when should you use quantitative research? As mentioned earlier, in its simplest form:
- Quantitative research allows you to confirm or test a hypothesis or theory or quantify a specific problem or quality.
- Qualitative research allows you to understand concepts or experiences.
Let's look at how you'll use these approaches in a research project a bit closer:
- Formulating a hypothesis . As mentioned earlier, qualitative research gives you a deeper understanding of a topic. Apart from learning more profound insights about your research findings, you can also use it to formulate a hypothesis when you start your research.
- Confirming a hypothesis . Once you’ve formulated a hypothesis, you can test it with quantitative research. As mentioned, you can also use it to quantify trends and behavior.
- Finding general answers . Quantitative research can help you answer broad questions. This is because it uses a larger sample size and thus makes it easier to gather simple binary or numeric data on a specific subject.
- Getting a deeper understanding . Once you have the broad answers mentioned above, qualitative research will help you find reasons for these answers. In other words, quantitative research shows you the motives behind actions or behaviors.
Considering the above, why not consider a mixed approach ? You certainly can because these approaches are not mutually exclusive. In other words, using one does not necessarily exclude the other. Moreover, both these approaches are useful for different reasons.
This means you could use both approaches in one project to achieve different goals. For example, you could use qualitative to formulate a hypothesis. Once formulated, quantitative research will allow you to confirm the hypothesis.
So, to answer the initial question, the approach you use is up to you. However, when deciding on the right approach, you should consider the specific research project, the data you'll gather, and what you want to achieve.
No matter what approach you choose, you should design your research in such a way that it delivers results that are objective, reliable, and valid.
Both these research approaches are based on data. Once you have this data, however, you need to analyze it to answer your research questions. The method to do this depends on the research approach you use.
To analyze quantitative data, you'll need to use mathematical or statistical analysis. This can involve anything from calculating simple averages to applying complex and advanced methods to calculate the statistical significance of the results. No matter what analysis methods you use, it will enable you to spot trends and patterns in your data.
Considering the above, you can use tools, applications, and programming languages like R to calculate:
- The average of a set of numbers . This could, for instance, be the case where you calculate the average scores students obtained in a test or the average time people spend on a website.
- The frequency of a specific response . This will be the case where you, for example, use open-ended survey questions during qualitative analysis. You could then calculate the frequency of a specific response for deeper insights.
- Any correlation between different variables . Through mathematical analysis, you can calculate whether two or more variables are directly or indirectly correlated. In turn, this could help you identify trends in the data.
- The statistical significance of your results . By analyzing the data and calculating the statistical significance of the results, you'll be able to see whether certain occurrences happen randomly or because of specific factors.
Analyzing qualitative data is more complex than quantitative data. This is simply because it's not based on numerical values but rather text, images, video, and the like. As such, you won't be able to use mathematical analysis to analyze and interpret your results.
Because of this, it relies on a more interpretive analysis style and a strict analytical framework to analyze data and extract insights from it.
Some of the most common ways to analyze qualitative data include:
- Qualitative content analysis . In a content analysis, you'll analyze the language used in a specific piece of text. This allows you to understand the intentions of the author, who the audience is, and find patterns and correlations in how different concepts are communicated. A major benefit of this approach is that it follows a systematic and transparent process that other researchers will be able to replicate. As such, your research will produce highly reliable results. Keep in mind, however, that content analysis can be time-intensive and difficult to automate. ➡️ Learn how to do a content analysis in the guide.
- Thematic analysis . In a thematic analysis, you'll analyze data with a view of extracting themes, topics, and patterns in the data. Although thematic analysis can encompass a range of diverse approaches, it's usually used to analyze a collection of texts like survey responses, focus group discussions, or transcriptions of interviews. One of the main benefits of thematic analysis is that it's flexible in its approach. However, in some cases, thematic analysis can be highly subjective, which, in turn, impacts the reliability of the results. ➡️ Learn how to do a thematic analysis in this guide.
- Discourse analysis . In a discourse analysis, you'll analyze written or spoken language to understand how language is used in real-life social situations. As such, you'll be able to determine how meaning is given to language in different contexts. This is an especially effective approach if you want to gain a deeper understanding of different social groups and how they communicate with each other. As such, it's commonly used in humanities and social science disciplines.
We’ve now given a broad overview of both qualitative and quantitative research. Based on this, we can summarize the differences between these two approaches as follows:
| Focuses on testing hypotheses. Can also be used to determine general facts about a topic. | Focuses on developing an idea or hypotheses. Can also be used to gain a deeper understanding into specific topics. |
| Analysis is mainly done through mathematical or statistical analytics. | Analysis is more interpretive and involves summarizing and categorizing topics or themes and interpreting data. |
| Data is typically expressed in numbers, graphs, tables, or other numerical formats. | Data is generally expressed in words or text. |
| Requires a reasonably large sample size to be reliable. | Requires smaller sample sizes with only a few respondents. |
| Data collection is focused on closed-ended questions. | Data collection is focused on open-ended questions to extract the opinions and views on a particular subject. |
Qualitative research focuses on collecting and analyzing non-numerical data. As such, it's typically unstructured and non-statistical. The main aim of qualitative research is to get a better understanding and insights into concepts, topics, and subjects. Quantitative research focuses on collecting numerical data and using it to measure variables. As such, quantitative research and data are typically expressed in numbers and graphs. Moreover, this type of research is structured and statistical and the returned results are objective.
3 examples of qualitative research would be:
- Interviews . These include one-on-one interviews with respondents with open-ended questions. You’ll then record the answers and analyze them later.
- Observations . Observations require that you participate in a specific organization or group in order to record their routines and interactions.
3 examples of quantitative research include:
- Surveys . Surveys are one of the most popular and easiest ways to collect quantitative data. To collect quantitative data, you won’t be able to ask open-ended questions.
- Longitudinal studies . With these studies, you’ll gather data on the same variables over specified time periods. Longitudinal studies are often used in medical sciences.
The main purpose of qualitative research is to get a better understanding and insights into concepts, topics, and subjects. The easiest way to describe qualitative research is that it answers the question " why ".
The purpose of quantitative research is to collect numerical data and use it to measure variables. As such, quantitative research and data are typically expressed in numbers and graphs. The simplest way to describe quantitative research is that it answers the questions " what " or " how much ".
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What Is Quantitative Research? Types, Characteristics & Methods
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Market Research Specialist
Emma David, a seasoned market research professional, specializes in employee engagement, survey administration, and data management. Her expertise in leveraging data for informed decisions has positively impacted several brands, enhancing their market position.
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Step into the fascinating world of quantitative research , where numbers reveal extraordinary insights!
By gathering and studying data in a systematic way, quantitative research empowers us to understand our ever-changing world better. It helps understand a problem or an already-formed hypothesis by generating numerical data. The results don’t end here, as you can process these numbers to get actionable insights that aid decision-making.
You can use quantitative research to quantify opinions, behaviors, attitudes, and other definitive variables related to the market, customers, competitors, etc. The research is conducted on a larger sample population to draw predictive, average, and pattern-based insights.
Here, we delve into the intricacies of this research methodology, exploring various quantitative methods, their advantages, and real-life examples that showcase their impact and relevance.
Ready to embark on a journey of discovery and knowledge? Let’s go!
What Is Quantitative Research?
Quantitative research is a method that uses numbers and statistics to test theories about customer attitudes and behaviors. It helps researchers gather and analyze data systematically to gain valuable insights and draw evidence-based conclusions about customer preferences and trends.
Researchers use online surveys, questionnaires , polls , and quizzes to question a large number of people to obtain measurable and bias-free data.
In technical terms, quantitative research is mainly concerned with discovering facts about social phenomena while assuming a fixed and measurable reality.
Offering numbers and stats-based insights, this research methodology is a crucial part of primary research and helps understand how well an organizational decision is going to work out.
Let’s consider an example.
Suppose your qualitative analysis shows that your customers are looking for social media-based customer support. In that case, quantitative analysis will help you see how many of your customers are looking for this support.
If 10% of your customers are looking for such a service, you might or might not consider offering this feature. But, if 40% of your regular customers are seeking support via social media, then it is something you just cannot overlook.
Characteristics of Quantitative Research
Quantitative research clarifies the fuzziness of research data from qualitative research analysis. With numerical insights, you can formulate a better and more profitable business decision.
Hence, quantitative research is more readily contestable, sharpens intelligent discussion, helps you see the rival hypotheses, and dynamically contributes to the research process.
Let us have a quick look at some of its characteristics.
1. Measurable Variables
The data collection methods in quantitative research are structured and contain items requiring measurable variables, such as age, number of family members, salary range, highest education, etc.
These structured data collection methods comprise polls, surveys, questionnaires, etc., and may have questions like the ones shown in the following image:
![what is quantitative research approaches what is quantitative research approaches](https://www.proprofssurvey.com/blog/wp-content/uploads/2023/09/Qualitative-Research-Methods-Types-Examples-and-Analysis-%E2%80%93-9.webp)
As you can see, all the variables are measurable. This ensures that the research is in-depth and provides less erroneous data for reliable, actionable insights.
2. Sample Size
No matter what data analysis methods for quantitative research are being used, the sample size is kept such that it represents the target market.
As the main aim of the research methodology is to get numerical insights, the sample size should be fairly large. Depending on the survey objective and scope, it might span hundreds of thousands of people.
3. Normal Population Distribution
To maintain the reliability of a quantitative research methodology, we assume that the population distribution curve is normal.
![what is quantitative research approaches what is quantitative research approaches](https://www.proprofssurvey.com/blog/wp-content/uploads/2023/09/Qualitative-Research-Methods-Types-Examples-and-Analysis-%E2%80%93-5.webp)
This type of population distribution curve is preferred over a non-normal distribution as the sample size is large, and the characteristics of the sample vary with its size.
This requires adhering to the random sampling principle to avoid the researcher’s bias in result interpretation. Any bias can ruin the fairness of the entire process and defeats the purpose of research.
4. Well-Structured Data Representation
Data analysis in quantitative research produces highly structured results and can form well-defined graphical representations. Some common examples include tables, figures, graphs, etc., that combine large blocks of data.
![what is quantitative research approaches what is quantitative research approaches](https://www.proprofssurvey.com/blog/wp-content/uploads/2023/09/Qualitative-Research-Methods-Types-Examples-and-Analysis-%E2%80%93-8.webp)
This way, you can discover hidden data trends, relationships, and differences among various measurable variables. This can help researchers understand the survey data and formulate actionable insights for decision-making.
5. Predictive Outcomes
Quantitative analysis of data can also be used for estimations and prediction outcomes. You can construct if-then scenarios and analyze the data for the identification of any upcoming trends or events.
However, this requires advanced analytics and involves complex mathematical computations. So, it is mostly done via quantitative research tools that come with advanced analytics capabilities.
Types of Quantitative Research Methods
Quantitative research is usually conducted using two methods. They are-
- Primary quantitative research methods
- Secondary quantitative research methods
1. Primary quantitative research methods
Primary quantitative research is the most popular way of conducting market research. The differentiating factor of this method is that the researcher relies on collecting data firsthand instead of relying on data collected from previous research.
There are multiple types of primary quantitative research. They can be distinguished based on three distinctive aspects, which are:
1.1. Techniques & Types of Studies:
- Survey Research
Surveys are the easiest, most common, and one of the most sought-after quantitative research techniques. The main aim of a survey is to widely gather and describe the characteristics of a target population or customers. Surveys are the foremost quantitative method preferred by both small and large organizations.
They help them understand their customers, products, and other brand offerings in a proper manner.
Surveys can be conducted using various methods, such as online polls, web-based surveys, paper questionnaires, phone calls, or face-to-face interviews. Survey research allows organizations to understand customer opinions, preferences, and behavior, making it crucial for market research and decision-making.
You can watch this quick video to learn more about creating surveys.
Watch: How to Create a Survey Using ProProfs Survey Maker
Surveys are of two types:
- Cross-Sectional Surveys Cross-sectional surveys are used to collect data from a sample of the target population at a specific point in time. Researchers evaluate various variables simultaneously to understand the relationships and patterns within the data.
- Cross-sectional surveys are popular in retail, small and medium-sized enterprises (SMEs), and healthcare industries, where they assess customer satisfaction, market trends, and product feedback.
- Longitudinal Surveys Longitudinal surveys are conducted over an extended period, observing changes in respondent behavior and thought processes.
- Researchers gather data from the same sample multiple times, enabling them to study trends and developments over time. These surveys are valuable in fields such as medicine, applied sciences, and market trend analysis.
Surveys can be distributed via various channels. Some of the most popular ones are listed below:
- Email: Sending surveys via email is a popular and effective method. People recognize your brand, leading to a higher response rate. With ProProfs Survey Maker’s in-mail survey-filling feature, you can easily send out and collect survey responses.
- Embed on a website: Boost your response rate by embedding the survey on your website. When visitors are already engaged with your brand, they are more likely to take the survey.
- Social media: Take advantage of social media platforms to distribute your survey. People familiar with your brand are likely to respond, increasing your response numbers.
- QR codes: QR codes store your survey’s URL, and you can print or publish these codes in magazines, signs, business cards, or any object to make it easy for people to access your survey.
- SMS survey: Collect a high number of responses quickly with SMS surveys. It’s a time-effective way to reach your target audience.
1.2. Correlational Research:
Correlational research aims to establish relationships between two or more variables.
Researchers use statistical analysis to identify patterns and trends in the data, but it does not determine causality between the variables. This method helps understand how changes in one variable may impact another.
Examples of correlational research questions include studying the relationship between stress and depression, fame and money, or classroom activities and student performance.
1.3. Causal-Comparative Research:
Causal-comparative research, also known as quasi-experimental research, seeks to determine cause-and-effect relationships between variables.
Researchers analyze how an independent variable influences a dependent variable, but they do not manipulate the independent variable. Instead, they observe and compare different groups to draw conclusions.
Causal-comparative research is useful in situations where it’s not ethical or feasible to conduct true experiments.
Examples of questions for this type of research include analyzing the effect of training programs on employee performance, studying the influence of customer support on client retention, investigating the impact of supply chain efficiency on cost reduction, etc.
1.4. Experimental Research:
Experimental research is based on testing theories to validate or disprove them. Researchers conduct experiments and manipulate variables to observe their impact on the outcomes.
This type of research is prevalent in natural and social sciences, and it is a powerful method to establish cause-and-effect relationships. By randomly assigning participants to experimental and control groups, researchers can draw more confident conclusions.
Examples of experimental research include studying the effectiveness of a new drug, the impact of teaching methods on student performance, or the outcomes of a marketing campaign.
2. Data collection methodologies
After defining research objectives, the next significant step in primary quantitative research is data collection. This involves using two main methods: sampling and conducting surveys or polls.
2.1Sampling methods:
In quantitative research, there are two primary sampling methods: Probability and Non-probability sampling.
2.2Probability Sampling
In probability sampling, researchers use the concept of probability to create samples from a population. This method ensures that every individual in the target audience has an equal chance of being selected for the sample.
There are four main types of probability sampling:
- Simple random sampling: Here, the elements or participants of a sample are selected randomly, and this technique is used in studies that are conducted over considerably large audiences. It works well for large target populations.
- Stratified random sampling: In this method, the entire population is divided into strata or groups, and the sample members get chosen randomly from these strata only. It is always ensured that different segregated strata do not overlap with each other.
- Cluster sampling: Here, researchers divide the population into clusters, often based on geography or demographics. Then, random clusters are selected for the sample.
- Systematic sampling: In this method, only the starting point of the sample is randomly chosen. All the other participants are chosen using a fixed interval. Researchers calculate this interval by dividing the size of the study population by the target sample size.
2.3Non-probability Sampling
Non-probability sampling is a method where the researcher’s knowledge and experience guide the selection of samples. This approach doesn’t give all members of the target population an equal chance of being included in the sample.
There are five non-probability sampling models:
- Convenience sampling: The elements or participants are chosen on the basis of their nearness to the researcher. The people in close proximity can be studied and analyzed easily and quickly, as there is no other selection criterion involved. Researchers simply choose samples based on what is most convenient for them.
- Consecutive sampling: Similar to convenience sampling, researchers select samples one after another over a significant period. They can opt for a single participant or a group of samples to conduct quantitative research in a consecutive manner for a significant period of time. Once this is over, they can conduct the research from the start.
- Quota sampling: With quota sampling, researchers use their understanding of target traits and personalities to form groups (strata). They then choose samples from each stratum based on their own judgment.
- Snowball sampling: This method is used where the target audiences are difficult to contact and interviewed for data collection. Researchers start with a few participants and then ask them to refer others, creating a snowball effect.
- Judgmental sampling: In judgmental sampling, researchers rely solely on their experience and research skills to handpick samples that they believe will be most relevant to the study.
3. Data analysis techniques
To analyze the quantitative data accurately, you’ll need to use specific statistical methods such as:
- SWOT Analysis: This stands for Strengths, Weaknesses, Opportunities, and Threats analysis. Organizations use SWOT analysis to evaluate their performance internally and externally. It helps develop effective improvement strategies.
- Conjoint Analysis: This market research method uncovers how individuals make complex purchasing decisions. It involves considering trade-offs in their daily activities when choosing from a list of product/service options.
- Cross-tabulation: A preliminary statistical market analysis method that reveals relationships, patterns, and trends within various research study parameters.
- TURF Analysis: Short for Totally Unduplicated Reach and Frequency Analysis, this method helps analyze the reach and frequency of favorable communication sources. It provides insights into the potential of a target market.
- By using these statistical techniques and inferential statistics methods like confidence intervals and margin of error, you can draw meaningful insights from your primary quantitative research that you can use in making informed decisions.
2. Secondary Quantitative Research Methods
- Secondary quantitative research, also known as desk research, is a valuable method that uses existing data, called secondary data.
- Instead of collecting new data, researchers analyze and combine already available information to enhance their research. This approach involves gathering quantitative data from various sources such as the internet, government databases, libraries, and research reports.
- Secondary quantitative research plays a crucial role in validating data collected through primary quantitative research. It helps reinforce or challenge existing findings.
Here are five commonly used secondary quantitative research methods:
A. Data Available on the Internet:
The Internet has become a vast repository of data, making it easier for researchers to access a wealth of information. Online databases, websites, and research repositories provide valuable quantitative data for researchers to analyze and validate their primary research findings.
B. Government and Non-Government Sources:
Government agencies and non-government organizations often conduct extensive research and publish reports. These reports cover a wide range of topics, providing researchers with reliable and comprehensive data for quantitative analysis.
C. Public Libraries:
While less commonly used in the digital age, public libraries still hold valuable research reports, historical data, and publications that can contribute to quantitative research.
D. Educational Institutions:
Educational institutions frequently conduct research on various subjects. Their research reports and publications can serve as valuable sources of information for researchers, validating and supporting primary quantitative research outcomes.
E. Commercial Information Sources:
Commercial sources such as local newspapers, journals, magazines, and media outlets often publish relevant data on economic trends, market research, and demographic analyses. Researchers can access this data to supplement their own findings and draw better conclusions.
Advantages of Quantitative Research Methods
Quantitative research data is often standardized and can be easily used to generalize findings for making crucial business decisions and uncover insights to supplement the qualitative research findings.
Here are some core benefits this research methodology offers.
Direct Result Comparison
As the studies can be replicated for different cultural settings and different times, even with different groups of participants, they tend to be extremely useful. Researchers can compare the results of different studies in a statistical manner and arrive at comprehensive conclusions for a broader understanding.
Replication
Researchers can repeat the study by using standardized data collection protocols over well-structured data sets. They can also apply tangible definitions of abstract concepts to arrive at different conclusions for similar research objectives with minor variations.
Large Samples
As the research data comes from large samples, the researchers can process and analyze the data via highly reliable and consistent analysis procedures. They can arrive at well-defined conclusions that can be used to make the primary research more thorough and reliable.
Hypothesis Testing
This research methodology follows standardized and established hypothesis testing procedures. So, you have to be careful while reporting and analyzing your research data , and the overall quality of results gets improved.
Proven Examples of Quantitative Research Methods
Below, we discuss two excellent examples of quantitative research methods that were used by highly distinguished business and consulting organizations. Both examples show how different types of analysis can be performed with qualitative approaches and how the analysis is done once the data is collected.
1. STEP Project Global Consortium / KPMG 2019 Global Family Business survey
This research utilized quantitative methods to identify ways that kept the family businesses sustainably profitable with time.
The study also identified the ways in which the family business behavior changed with demographic changes and had “why” and “how” questions. Their qualitative research methods allowed the KPMG team to dig deeper into the mindsets and perspectives of the business owners and uncover unexpected research avenues as well.
It was a joint effort in which STEP Project Global Consortium collected 26 cases, and KPMG collected 11 cases.
The research reached the stage of data analysis in 2020, and the analysis process spanned over 4 stages.
The results, which were also the reasons why family businesses tend to lose their strength with time, were found to be:
- Family governance
- Family business legacy
2. EY Seren Teams Research 2020
This is yet another commendable example of qualitative research where the EY Seren Team digs into the unexplored depths of human behavior and how it affected their brand or service expectations.
The research was done across 200+ sources and involved in-depth virtual interviews with people in their homes, exploring their current needs and wishes. It also involved diary studies across the entire UK customer base to analyze human behavior changes and patterns.
The study also included interviews with professionals and design leaders from a wide range of industries to explore how COVID-19 transformed their industries. Finally, quantitative surveys were conducted to gain insights into the EY community after every 15 days.
The insights and results were:
- A culture of fear, daily resilience, and hopes for a better world and a better life – these were the macro trends.
- People felt massive digitization to be a resourceful yet demanding aspect as they have to adapt every day.
- Some people wished to have a new world with lots of possibilities, and some were looking for a new purpose.
8 Best Practices to Conduct Quantitative Research
Here are some best practices to keep in mind while conducting quantitative research:
1. Define Research Objectives
There can be many ways to collect data via quantitative research methods that are chosen as per the research objective and scope. These methods allow you to build your own observations regarding any hypotheses – unknown, entirely new, or unexplained.
You can hypothesize a proof and build a prediction of outcomes supporting the same. You can also create a detailed stepwise plan for data collection, analysis, and testing.
Below, we explore quantitative research methods and discuss some examples to enhance your understanding of them.
2. Keep Your Questions Simple
The surveys are meant to reach people en-masse, and that includes a wide demographic range with recipients from all walks of life. Asking simple questions will ensure that they grasp what’s being asked easily.
3. Develop a Solid Research Design
Choose an appropriate research design that aligns with your objectives, whether it’s experimental, quasi-experimental, or correlational. You also need to pay attention to the sample size and sampling technique such that it represents the target population accurately.
4. Use Reliable & Valid Instruments
It’s crucial to select or develop measurement instruments such as questionnaires, scales, or tests that have been validated and are reliable. Before proceeding with the main study, pilot-test these instruments on a small sample to assess their effectiveness and make any necessary improvements.
5. Ensure Data Quality
Implement data collection protocols to minimize errors and bias during data gathering. Double-check data entries and cleaning procedures to eliminate any inconsistencies or missing values that may affect the accuracy of your results. For instance, you might regularly cross-verify data entries to identify and correct any discrepancies.
6. Employ Appropriate Data Analysis Techniques
Select statistical methods that match the nature of your data and research questions. Whether it’s regression analysis, t-tests, ANOVA, or other techniques, using the right approach is important for drawing meaningful conclusions. Utilize software tools like SPSS or R for data analysis to ensure the accuracy and reproducibility of your findings.
7. Interpret Results Objectively
Present your findings in a clear and unbiased manner. Avoid making unwarranted causal claims, especially in correlational studies. Instead, focus on describing the relationships and patterns observed in your data.
8. Address Ethical Considerations
Prioritize ethical considerations throughout your research process. Obtain informed consent from participants, ensuring their voluntary participation and confidentiality of data. Comply with ethical guidelines and gain approval from a governing body if necessary.
Enhance Your Quantitative Research With Cutting-Edge Software
While no single research methodology can produce 100% reliable results, you can always opt for a hybrid research method by opting for the methods that are most relevant to your objective.
This understanding comes gradually as you learn how to implement the correct combination of qualitative and quantitative research methods for your research projects. For the best results, we recommend investing in smart, efficient, and scalable research tools that come with delightful reporting and advanced analytics to make every research initiative a success.
These software tools, such as ProProfs Survey Maker, come with pre-built survey templates and question libraries and allow you to create a high-converting survey in just a few minutes.
So, choose the best research partner, create the right research plan, and gather insights that drive sustainable growth for your business.
![what is quantitative research approaches Emma David](https://www.proprofssurvey.com/blog/wp-content/uploads/2024/02/Emma-David-150x150.png)
About the author
Emma David is a seasoned market research professional with 8+ years of experience. Having kick-started her journey in research, she has developed rich expertise in employee engagement, survey creation and administration, and data management. Emma believes in the power of data to shape business performance positively. She continues to help brands and businesses make strategic decisions and improve their market standing through her understanding of research methodologies.
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- Qualitative vs. Quantitative Research | Differences, Examples & Methods
Qualitative vs. Quantitative Research | Differences, Examples & Methods
Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.
When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.
Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.
Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.
Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.
Table of contents
The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.
Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.
![what is quantitative research approaches Qualitative vs. quantitative research](https://www.scribbr.com/wp-content/uploads/2023/05/qualitative-vs-quantitative-research.webp)
Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).
Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).
However, some methods are more commonly used in one type or the other.
Quantitative data collection methods
- Surveys : List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
- Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
- Observations : Observing subjects in a natural environment where variables can’t be controlled.
Qualitative data collection methods
- Interviews : Asking open-ended questions verbally to respondents.
- Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
- Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
- Literature review : Survey of published works by other authors.
A rule of thumb for deciding whether to use qualitative or quantitative data is:
- Use quantitative research if you want to confirm or test something (a theory or hypothesis )
- Use qualitative research if you want to understand something (concepts, thoughts, experiences)
For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.
Quantitative research approach
You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”
You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.
Qualitative research approach
You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”
Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.
Mixed methods approach
You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.
It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.
Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.
Analyzing quantitative data
Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.
Applications such as Excel, SPSS, or R can be used to calculate things like:
- Average scores ( means )
- The number of times a particular answer was given
- The correlation or causation between two or more variables
- The reliability and validity of the results
Analyzing qualitative data
Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.
Some common approaches to analyzing qualitative data include:
- Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
- Thematic analysis : Closely examining the data to identify the main themes and patterns
- Discourse analysis : Studying how communication works in social contexts
If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.
- Chi square goodness of fit test
- Degrees of freedom
- Null hypothesis
- Discourse analysis
- Control groups
- Mixed methods research
- Non-probability sampling
- Quantitative research
- Inclusion and exclusion criteria
Research bias
- Rosenthal effect
- Implicit bias
- Cognitive bias
- Selection bias
- Negativity bias
- Status quo bias
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.
In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .
The research methods you use depend on the type of data you need to answer your research question .
- If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
- If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
- If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.
There are various approaches to qualitative data analysis , but they all share five steps in common:
- Prepare and organize your data.
- Review and explore your data.
- Develop a data coding system.
- Assign codes to the data.
- Identify recurring themes.
The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .
A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.
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Quantitative Data Analysis: Everything You Need to Know
11 min read
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Does the thought of quantitative data analysis bring back the horrors of math classes? We get it.
But conducting quantitative data analysis doesn’t have to be hard with the right tools. Want to learn how to turn raw numbers into actionable insights on how to improve your product?
In this article, we explore what quantitative data analysis is, the difference between quantitative and qualitative data analysis, and statistical methods you can apply to your data. We also walk you through the steps you can follow to analyze quantitative information, and how Userpilot can help you streamline the product analytics process. Let’s get started.
- Quantitative data analysis is the process of using statistical methods to define, summarize, and contextualize numerical data.
- Quantitative analysis is different from a qualitative one. The first deals with numerical data and focuses on answering “what,” “when,” and “where.” However, a qualitative analysis relies on text, graphics, or videos and explores “why” and “how” events occur.
- Pros of quantitative data analysis include objectivity, reliability, ease of comparison, and scalability.
- Cons of quantitative metrics include the data’s limited context and inflexibility, and the need for large sample sizes to get statistical significance.
- The methods for analyzing quantitative data are descriptive and inferential statistics.
- Choosing the right analysis method depends on the type of data collected and the specific research questions or hypotheses.
- These are the steps to conduct quantitative data analysis: 1. Defining goals and KPIs . 2. Collecting and cleaning data. 3. Visualizing the data. 4. Identifying patterns . 5. Sharing insights. 6. Acting on findings to improve decision-making.
- With Userpilot , you can auto-capture in-app user interactions and build analytics dashboards . This tool also lets you conduct A/B and multivariate tests, and funnel and cohort analyses .
- Gather and visualize all your product analytics in one place with Userpilot. Get a demo .
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What is quantitative data analysis?
Quantitative data analysis is about applying statistical analysis methods to define, summarize, and contextualize numerical data. In short, it’s about turning raw numbers and data into actionable insights.
The analysis will vary depending on the research questions and the collected data (more on this below).
Quantitative vs qualitative data analysis
The main difference between these forms of analysis lies in the collected data. Quantitative data is numerical or easily quantifiable. For example, the answers to a customer satisfaction score (CSAT) survey are quantitative since you can count the number of people who answered “very satisfied”.
Qualitative feedback , on the other hand, analyzes information that requires interpretation. For instance, evaluating graphics, videos, text-based answers, or impressions.
Another difference between quantitative and qualitative analysis is the questions each seeks to answer. For instance, quantitative data analysis primarily answers what happened, when it happened, and where it happened. However, qualitative data analysis answers why and how an event occurred.
Quantitative data analysis also looks into identifying patterns , drivers, and metrics for different groups. However, qualitative analysis digs deeper into the sample dataset to understand underlying motivations and thinking processes.
Pros of quantitative data analysis
Quantitative or data-driven analysis has advantages such as:
- Objectivity and reliability. Since quantitative analysis is based on numerical data, this reduces biases and allows for more objective conclusions. Also, by relying on statistics, this method ensures the results are consistent and can be replicated by others, making the findings more reliable.
- Easy comparison. Quantitative data is easily comparable because you can identify trends , patterns, correlations, and differences within the same group and KPIs over time. But also, you can compare metrics in different scales by normalizing the data, e.g., bringing ratios and percentages into the same scale for comparison.
- Scalability. Quantitative analysis can handle large volumes of data efficiently, making it suitable for studies involving large populations or datasets. This makes this data analysis method scalable. Plus, researchers can use quantitative analysis to generalize their findings to broader populations.
Cons of quantitative data analysis
These are common disadvantages of data-driven analytics :
- Limited context. Since quantitative data looks at the numbers, it often strips away the data from the context, which can show the underlying reasons behind certain trends. This limitation can lead to a superficial understanding of complex issues, as you often miss the nuances and user motivations behind the data points.
- Inflexibility. When conducting quantitative research, you don’t have room to improvise based on the findings. You need to have predefined hypotheses, follow scientific methods, and select data collection instruments. This makes the process less adaptable to new or unexpected findings.
- Large sample sizes necessary. You need to use large sample sizes to achieve statistical significance and reliable results when doing quantitative analysis. Depending on the type of study you’re conducting, gathering such extensive data can be resource-intensive, time-consuming, and costly.
Quantitative data analysis methods
There are two statistical methods for reviewing quantitative data and user analytics . However, before exploring these in-depth, let’s refresh these key concepts:
- Population. This is the entire group of individuals or entities that are relevant to the research.
- Sample. The sample is a subset of the population that is actually selected for the research since it is often impractical or impossible to study the entire population.
- Statistical significance. The chances that the results gathered after your analysis are realistic and not due to random chance.
Here are methods for analyzing quantitative data:
Descriptive statistics
Descriptive statistics, as the name implies, describe your data and help you understand your sample in more depth. It doesn’t make inferences about the entire population but only focuses on the details of your specific sample.
Descriptive statistics usually include measures like the mean, median, percentage, frequency, skewness, and mode.
Inferential statistics
Inferential statistics aim to make predictions and test hypotheses about the real-world population based on your sample data.
Here, you can use methods such as a T-test, ANOVA, regression analysis, and correlation analysis.
Let’s take a look at this example. Through descriptive statistics, you identify that users under the age of 25 are more likely to skip your onboarding. You’ll need to apply inferential statistics to determine if the result is statistically significant and applicable to your entire ’25 or younger’ population.
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How to choose the right method for your quantitative data analysis
The type of data that you collect and the research questions that you want to answer will impact which quantitative data analysis method you choose. Here’s how to choose the right method:
Determine your data type
Before choosing the quantitative data analysis method, you need to identify which group your data belongs to:
- Nominal —categories with no specific order, e.g., gender, age, or preferred device.
- Ordinal —categories with a specific order, but the intervals between them aren’t equal, e.g., customer satisfaction ratings .
- Interval —categories with an order and equal intervals, but no true zero point, e.g., temperature (where zero doesn’t mean “no temperature”).
- Ratio —categories with a specific order, equal intervals, and a true zero point, e.g., number of sessions per user .
Applying any statistical method to all data types can lead to meaningless results. Instead, identify which statistical analysis method supports your collected data types.
Consider your research questions
The specific research questions you want to answer, and your hypothesis (if you have one) impact the analysis method you choose. This is because they define the type of data you’ll collect and the relationships you’re investigating.
For instance, if you want to understand sample specifics, descriptive statistics—such as tracking NPS —will work. However, if you want to determine if other variables affect the NPS, you’ll need to conduct an inferential analysis.
The overarching questions vary in both of the previous examples. For calculating the NPS, your internal research question might be, “Where do we stand in customer loyalty ?” However, if you’re doing inferential analysis, you may ask, “How do various factors, such as demographics, affect NPS?”
6 steps to do quantitative data analysis and extract meaningful insights
Here’s how to conduct quantitative analysis and extract customer insights :
1. Set goals for your analysis
Before diving into data collection, you need to define clear goals for your analysis as these will guide the process. This is because your objectives determine what to look for and where to find data. These goals should also come with key performance indicators (KPIs) to determine how you’ll measure success.
For example, imagine your goal is to increase user engagement. So, relevant KPIs include product engagement score , feature usage rate , user retention rate, or other relevant product engagement metrics .
2. Collect quantitative data
Once you’ve defined your goals, you need to gather the data you’ll analyze. Quantitative data can come from multiple sources, including user surveys such as NPS, CSAT, and CES, website and application analytics , transaction records, and studies or whitepapers.
Remember: This data should help you reach your goals. So, if you want to increase user engagement , you may need to gather data from a mix of sources.
For instance, product analytics tools can provide insights into how users interact with your tool, click on buttons, or change text. Surveys, on the other hand, can capture user satisfaction levels . Collecting a broad range of data makes your analysis more robust and comprehensive.
![what is quantitative research approaches Raw event auto-tracking in Userpilot](https://images.storychief.com/account_6827/raw-events_8f9c104ca1ae8c6047ec9c64200bff7b_800.png)
3. Clean and visualize your data
Raw data is often messy and contains duplicates, outliers, or missing values that can skew your analysis. Before making any calculations, clean the data by removing these anomalies or outliers to ensure accurate results.
Once cleaned, turn it into visual data by using different types of charts , graphs, or heatmaps . Visualizations and data analytics charts make it easier to spot trends, patterns, and anomalies. If you’re using Userpilot, you can choose your preferred visualizations and organize your dashboard to your liking.
4. Identify patterns and trends
When looking at your dashboards, identify recurring themes, unusual spikes, or consistent declines that might indicate data analytics trends or potential issues.
Picture this: You notice a consistent increase in feature usage whenever you run seasonal marketing campaigns . So, you segment the data based on different promotional strategies. There, you discover that users exposed to email marketing campaigns have a 30% higher engagement rate than those reached through social media ads.
In this example, the pattern suggests that email promotions are more effective in driving feature usage.
If you’re a Userpilot user, you can conduct a trend analysis by tracking how your users perform certain events.
![what is quantitative research approaches Trend analysis report in Userpilot](https://images.storychief.com/account_6827/trend-analysis_3fc243f777c7d77f3fc7134f32c87b31_800.png)
5. Share valuable insights with key stakeholders
Once you’ve discovered meaningful insights, you have to communicate them to your organization’s key stakeholders. Do this by turning your data into a shareable analysis report , one-pager, presentation, or email with clear and actionable next steps.
Your goal at this stage is for others to view and understand the data easily so they can use the insights to make data-led decisions.
Following the previous example, let’s say you’ve found that email campaigns significantly boost feature usage. Your email to other stakeholders should strongly recommend increasing the frequency of these campaigns and adding the supporting data points.
Take a look at how easy it is to share custom dashboards you built in Userpilot with others via email:
6. Act on the insights
Data analysis is only valuable if it leads to actionable steps that improve your product or service. So, make sure to act upon insights by assigning tasks to the right persons.
For example, after analyzing user onboarding data, you may find that users who completed the onboarding checklist were 3x more likely to become paying customers ( like Sked Social did! ).
Now that you have actual data on the checklist’s impact on conversions, you can work on improving it, such as simplifying its steps, adding interactive features, and launching an A/B test to experiment with different versions.
How can Userpilot help with analyzing quantitative data
As you’ve seen throughout this article, using a product analytics tool can simplify your data analysis and help you get insights faster. Here are different ways in which Userpilot can help:
Automatically capture quantitative data
Thanks to Userpilot’s new auto-capture feature, you can automatically track every time your users click, write a text, or fill out a form in your app—no engineers or manual tagging required!
Our customer analytics platform lets you use this data to build segments, trigger personalized in-app events and experiences, or launch surveys.
If you don’t want to auto-capture raw data, you can turn this functionality off in your settings, as seen below:
![what is quantitative research approaches Auto-capture raw data settings in Userpilot](https://images.storychief.com/account_6827/raw-data-settings_3a25122b302ed637b7e69631cde96034_800.png)
Monitor key metrics with customizable dashboards for real-time insights
Userpilot comes with template analytics dashboards , such as new user activation dashboards or customer engagement dashboards . However, you can create custom dashboards and reports to keep track of metrics that are relevant to your business in real time.
For instance, you could build a customer retention analytics dashboard and include all metrics that you find relevant, such as customer stickiness , NPS, or last accessed date.
Analyze experiment data with A/B and multivariate tests
Userpilot lets you conduct A/B and multivariate tests , either by following a controlled or a head-to-head approach. You can track the results on a dashboard.
For example, let’s say you want to test a variation of your onboarding flow to determine which leads to higher user activation .
You can go to Userpilot’s Flows tab and click on Experiments. There, you’ll be able to select the type of test you want to run, for instance, a controlled A/B test , build a new flow, test it, and get the results.
![what is quantitative research approaches Creating new experiments for A/B and multivariate testing in Userpilot](https://images.storychief.com/account_6827/chrome-capture-2024-5-4-1_0b25a89d6190111b9b9547b89e986dfc_800.png)
Use quantitative funnel analysis to increase conversion rates
With Userpilot, you can track your customers’ journey as they complete actions and move through the funnel. Funnel analytics give you insights into your conversion rates and conversion times between two events, helping you identify areas for improvement.
Imagine you want to analyze your free-to-paid conversions and the differences between devices. Just by looking at the graphic, you can draw some insights:
- There’s a significant drop-off between steps one and two, and two and three, indicating potential user friction .
- Users on desktops convert at higher rates than those on mobile or unspecified devices.
- Your average freemium conversion time is almost three days.
![what is quantitative research approaches funnel analysis view in Userpilot](https://images.storychief.com/account_6827/funnel-breakdown-by-device_cf5b3ce3e6e800c0729ae04e7dcf445e_800.png)
Leverage cohort analysis to optimize retention
Another Userpilot functionality that can help you analyze quantitative data is cohort analysis . This powerful tool lets you group users based on shared characteristics or experiences, allowing you to analyze their behavior over time and identify trends, patterns, and the long-term impact of changes on user behavior.
For example, let’s say you recently released a feature and want to measure its impact on user retention. Via a cohort analysis, you can group users who started using your product after the update and compare their retention rates to previous cohorts.
You can do this in Userpilot by creating segments and then tracking user segments ‘ retention rates over time.
![what is quantitative research approaches Retention analysis example in Userpilot](https://images.storychief.com/account_6827/retention-analysis1_c7b75a5890b3832f82bd24b3cd803555_800.png)
Check how many users adopted a feature with a retention table
In Userpilot, you can use retention tables to stay on top of feature adoption . This means you can track how many users continue to use a feature over time and which features are most valuable to your users. The video below shows how to choose the features or events you want to analyze in Userpilot.
As you’ve seen, to conduct quantitative analysis, you first need to identify your business and research goals. Then, collect, clean, and visualize the data to spot trends and patterns. Lastly, analyze the data, share it with stakeholders, and act upon insights to build better products and drive customer satisfaction.
To stay on top of your KPIs, you need a product analytics tool. With Userpilot, you can automate data capture, analyze product analytics, and view results in shareable dashboards. Want to try it for yourself? Get a demo .
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Quantitative Research
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Quantitative research methods are concerned with the planning, design, and implementation of strategies to collect and analyze data. Descartes, the seventeenth-century philosopher, suggested that how the results are achieved is often more important than the results themselves, as the journey taken along the research path is a journey of discovery. High-quality quantitative research is characterized by the attention given to the methods and the reliability of the tools used to collect the data. The ability to critique research in a systematic way is an essential component of a health professional’s role in order to deliver high quality, evidence-based healthcare. This chapter is intended to provide a simple overview of the way new researchers and health practitioners can understand and employ quantitative methods. The chapter offers practical, realistic guidance in a learner-friendly way and uses a logical sequence to understand the process of hypothesis development, study design, data collection and handling, and finally data analysis and interpretation.
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Qualitative Research Methods
Babbie ER. The practice of social research. 14th ed. Belmont: Wadsworth Cengage; 2016.
Google Scholar
Descartes. Cited in Halverston, W. (1976). In: A concise introduction to philosophy, 3rd ed. New York: Random House; 1637.
Doll R, Hill AB. The mortality of doctors in relation to their smoking habits. BMJ. 1954;328(7455):1529–33. https://doi.org/10.1136/bmj.328.7455.1529 .
Article Google Scholar
Liamputtong P. Research methods in health: foundations for evidence-based practice. 3rd ed. Melbourne: Oxford University Press; 2017.
McNabb DE. Research methods in public administration and nonprofit management: quantitative and qualitative approaches. 2nd ed. New York: Armonk; 2007.
Merriam-Webster. Dictionary. http://www.merriam-webster.com . Accessed 20th December 2017.
Olesen Larsen P, von Ins M. The rate of growth in scientific publication and the decline in coverage provided by Science Citation Index. Scientometrics. 2010;84(3):575–603.
Pannucci CJ, Wilkins EG. Identifying and avoiding bias in research. Plast Reconstr Surg. 2010;126(2):619–25. https://doi.org/10.1097/PRS.0b013e3181de24bc .
Petrie A, Sabin C. Medical statistics at a glance. 2nd ed. London: Blackwell Publishing; 2005.
Portney LG, Watkins MP. Foundations of clinical research: applications to practice. 3rd ed. New Jersey: Pearson Publishing; 2009.
Sheehan J. Aspects of research methodology. Nurse Educ Today. 1986;6:193–203.
Wilson LA, Black DA. Health, science research and research methods. Sydney: McGraw Hill; 2013.
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Wilson, L.A. (2019). Quantitative Research. In: Liamputtong, P. (eds) Handbook of Research Methods in Health Social Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-10-5251-4_54
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Unit 6: Qual vs Quant.
27 Quantitative Methods in Communication Research
Quantitative methods in communication research.
In communication research, both quantitative and qualitative methods are essential for understanding different aspects of communication processes and effects. Here’s how quant methods can be applied:
- Collecting data on communication patterns, relationship satisfaction, or conflict resolution strategies among different groups.
- Collecting numerical data on audience demographics, media consumption habits, or attitudes towards specific communication messages.
- Testing hypotheses about the effects of specific communication behaviors (e.g., eye contact, tone of voice) on relationship outcomes.
- Testing the effects of different communication strategies or messages on audience behavior or perception.
- Quantifying the frequency and types of communication behaviors in recorded interactions (e.g., supportive vs. critical comments)
- Quantifying the frequency of certain themes, words, or images in media content to identify patterns or trends.
- Statistical Analysis : Using statistical tools to analyze data from surveys or experiments, such as correlation or regression analysis to explore relationships between variables.
Communication Research in Real Life Copyright © 2023 by Kate Magsamen-Conrad. All Rights Reserved.
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Home » Quantitative Research: Definition, Methods, and Examples
Quantitative Research: Definition, Methods, and Examples
June 13, 2023 max 8min read.
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This article covers:
What Is Quantitative Research?
Quantitative research methods .
- Data Collection and Analysis
Types of Quantitative Research
- Advantages and Disadvantages of Quantitative Research
Examples of Quantitative Research
Picture this: you’re a product or project manager and must make a crucial decision. You need data-driven insights to guide your choices, understand customer preferences, and predict market trends. That’s where quantitative research comes into play. It’s like having a secret weapon that empowers you to make informed decisions confidently.
Quantitative research is all about numbers, statistics, and measurable data. It’s a systematic approach that allows you to gather and analyze numerical information to uncover patterns, trends, and correlations.
Quantitative research provides concrete, objective data to drive your strategies, whether conducting surveys, analyzing large datasets, or crunching numbers.
In this article, we’ll dive and learn all about quantitative research; get ready to uncover the power of numbers.
Quantitative Research Definition:
Quantitative research is a systematic and objective approach to collecting, analyzing, and interpreting numerical data. It measures and quantifies variables, employing statistical methods to uncover patterns, relationships, and trends.
Quantitative research gets utilized across a wide range of fields, including market research, social sciences, psychology, economics, and healthcare. It follows a structured methodology that uses standardized instruments, such as surveys, experiments, or polls, to collect data. This data is then analyzed using statistical techniques to uncover patterns and relationships.
The purpose of quantitative research is to measure and quantify variables, assess the connections between variables, and draw objective and generalizable conclusions. Its benefits are numerous:
- Rigorous and scientific approach : Quantitative research provides a comprehensive and scientific approach to studying phenomena. It enables researchers to gather empirical evidence and draw reliable conclusions based on solid data.
- Evidence-based decision-making : By utilizing quantitative research, researchers can make evidence-based decisions. It helps in developing informed strategies and evaluating the effectiveness of interventions or policies by relying on data-driven insights.
- Advancement of knowledge : Quantitative research contributes to the advancement of knowledge by building upon existing theories. It expands understanding in various fields and informs future research directions, allowing for continued growth and development.
Here are various quantitative research methods:
Survey research : This method involves collecting data from a sample of individuals through questionnaires, interviews, or online surveys. Surveys gather information about people’s attitudes, opinions, behaviors, and characteristics.
Experimentation: It is a research method that allows researchers to determine cause-and-effect relationships. In an experiment, participants randomly get assigned to different groups. While the other group does not receive treatment or intervention, one group does. The outcomes of the two groups then get measured to analyze the effects of the treatment or intervention.
Here are the steps involved in an experiment:
- Define the research question. What do you want to learn about?
- Develop a hypothesis. What do you think the answer to your research question is?
- Design the experiment. How will you manipulate the variables and measure the outcomes?
- Recruit participants. Who will you study?
- Randomly assign participants to groups. This ensures that the groups are as similar as possible.
- Apply the treatments or interventions. This is what the researcher is attempting to test the effects of.
- Measure the outcomes. This is how the researcher will determine whether the treatments or interventions had any effect.
- Analyze the data. This is how the researcher will determine whether the results support the hypothesis.
- Draw conclusions. What do the results mean?
- Content analysis : Content analysis is a systematic approach to analyzing written, verbal, or visual communication. Researchers identify and categorize specific content, themes, or patterns in various forms of media, such as books, articles, speeches, or social media posts.
- Secondary data analysis : It is a research method that involves analyzing data already collected by someone else. This data can be from various sources, such as government reports, previous research studies, or large datasets like surveys or medical records.
Researchers use secondary data analysis to answer new research questions or gain additional insights into a topic.
Data Collection and Analysis for Quantitative Research
Quantitative research is research that uses numbers and statistics to answer questions. It often measures things like attitudes, behaviors, and opinions.
There are three main methods for collecting quantitative data:
- Surveys and questionnaires: These are structured instruments used to gather data from a sample of people.
- Experiments and controlled observations: These are conducted in a controlled setting to measure variables and determine cause-and-effect relationships.
- Existing data sources (secondary data): This data gets collected from databases, archives, or previous studies.
Data preprocessing and cleaning is the first step in data analysis. It involves identifying and correcting errors, removing outliers, and ensuring the data is consistent.
Descriptive statistics is a branch of statistics that deals with the description of the data. It summarizes and describes the data using central tendency, variability, and shape measures.
Inferential statistics again comes under statistics which deals with the inference of properties of a population from a sample. It tests hypotheses, estimates parameters, and makes predictions.
Here are some of the most common inferential statistical techniques:
- Hypothesis testing : This assesses the significance of relationships or differences between variables.
- Confidence intervals : This estimates the range within which population parameters likely fall.
- Correlation and regression analysis : This examines relationships and predicts outcomes based on variables.
- Analysis of variance (ANOVA) : This compare means across multiple groups or conditions.
Statistical software and tools for data analysis can perform complex statistical analyses efficiently. Some of the most popular statistical software packages include SPSS, SAS, and R.
Here are some of the main types of quantitative research methodology:
- Descriptive research describes a particular population’s characteristics, trends, or behaviors. For example, a descriptive study might look at the average height of students in a school, the number of people who voted in an election, or the types of food people eat.
- Correlational research checks the relationship between two or more variables. For example, a correlational study might examine the relationship between income and happiness or stress and weight gain. Correlational research can show that two variables are related but cannot show that one variable causes the other.
- Experimental research is a type of research that investigates cause-and-effect relationships. In an experiment, researchers manipulate one variable (the independent variable) and measure the impact on another variable (the dependent variable). This allows researchers to make inferences about the relationship between the two variables.
- Quasi-experimental research is similar to experimental research. However, it does not involve random assignment of participants to groups. This can be due to practical or ethical considerations, such as when assigning people to receive a new medication randomly is impossible. In quasi-experimental research, researchers try to control for other factors affecting the results, such as the participant’s age, gender, or health status.
- Longitudinal research studies change patterns over an extended time. For example, a longitudinal study might examine how children’s reading skills develop over a few years or how people’s attitudes change as they age. But longitudinal research can be expensive and time-consuming. Still, it can offer valuable insights into how people and things change over time.
Advantages and Disadvantages of Quantitative Research
Here are the advantages and downsides of quantitative research:
Advantages of Quantitative Research:
- Objectivity: Quantitative research aims to be objective and unbiased. This is because it relies on numbers and statistical methods, which reduce the potential for researcher bias and subjective interpretation.
- Generalizability: Quantitative research often involves large sample sizes, which increases the likelihood of obtaining representative data. The study findings are more likely to apply to a wider population.
- Replicability: Using standardized procedures and measurement instruments in quantitative research enhances replicability. This means that other researchers can repeat the study using the same methods to test the reliability of the findings.
- Statistical analysis: Quantitative research employs various statistical techniques for data analysis. This allows researchers to identify data patterns, relationships, and associations. Additionally, statistical analysis can provide precision and help draw objective conclusions.
- Numerical precision: Quantitative research produces numerical data that can be analyzed using mathematical calculations. This numeric precision allows for clear comparisons and quantitative interpretations.
Disadvantages of Quantitative Research :
- Lack of Contextual Understanding : Quantitative research often focuses on measurable variables, which may limit the exploration of complex phenomena. It may overlook the social, cultural, and contextual factors that could influence the research findings.
- Limited Insight : While quantitative research can identify correlations and associations, it may not uncover underlying causes or explanations of these relationships. It may provide answers to “what” and “how much,” but not necessarily “why.”
- Potential for Simplification : The quantification of data can lead to oversimplification, as it may reduce complex phenomena into numerical values. This simplification may overlook nuances and intricacies important to understanding the research topic fully.
- Cost and Time-Intensive : Quantitative research requires significant resources. It includes time, funding, and specialized expertise. Researchers must collect and analyze large amounts of numerical data, which can be lengthy and expensive.
- Limited Flexibility : A systematic and planned strategy typically gets employed in quantitative research. It signifies the researcher’s use of a predetermined data collection and analysis approach. As a result, you may be more confident that your study gets conducted consistently and equitably. But it may also make it more difficult for the researcher to change the research plan or pose additional inquiries while gathering data. This could lead to missing valuable insights.
Here are some real-life examples of quantitative research:
- Market Research : Quantitative market research is a type of market research that uses numerical data to understand consumer preferences, buying behavior, and market trends. This data typically gets gathered through surveys and questionnaires, which are then analyzed to make informed business decisions.
- Health Studies : Quantitative research, such as clinical trials and epidemiological research, is vital in health studies. Researchers collect numerical data on treatment effectiveness, disease prevalence, risk factors, and patient outcomes. This data is then analyzed statistically to draw conclusions and make evidence-based recommendations for healthcare practices.
- Educational Research : Quantitative research is used extensively in educational studies to examine various aspects of learning, teaching methods, and academic achievement. Researchers collect data through standardized tests, surveys, or observations. The reason for this approach is to analyze factors influencing student performance, educational interventions, and educational policy effectiveness.
- Social Science Surveys : Social science researchers often employ quantitative research methods. The aim here is to study social phenomena and gather data on individuals’ or groups’ attitudes, beliefs, and behaviors. Large-scale surveys collect numerical data, then statistically analyze to identify patterns, trends, and associations within the population.
- Opinion Polls : Opinion polls and public opinion research rely heavily on quantitative research techniques. Polling organizations conduct surveys with representative samples of the population. The companies do this intending to gather numerical data on public opinions, political preferences, and social attitudes. The data then gets analyzed to gauge public sentiment and predict election outcomes or public opinion on specific issues.
- Economic Research : Quantitative research is widely used in economic studies to analyze economic indicators, trends, and patterns. Economists collect numerical data on GDP, inflation, employment, and consumer spending. Statistical analysis of this data helps understand economic phenomena, forecast future trends, and inform economic policy decisions.
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Qualitative research is about understanding and exploring something in depth. It uses non-numerical data, like interviews, observations, and open-ended survey responses, to gather rich, descriptive insights. Quantitative research is about measuring and analyzing relationships between variables using numerical data.
Quantitative research gets characterized by the following:
- The collection of numerical information
- The use of statistical analysis
- The goal of measuring and quantifying phenomena
- The purpose of examining relationships between variables
- The purpose of generalizing findings to a larger population
- The use of large sample sizes
- The use of structured surveys or experiments
- The usage of statistical techniques to analyze data objectively
The primary goal of quantitative research is to gather numerical data and analyze it statistically to uncover patterns, relationships, and trends. It aims to provide objective and generalizable insights using systematic data collection methods, standardized instruments, and statistical analysis techniques. Quantitative research seeks to test hypotheses, make predictions, and inform decision-making in various fields.
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Quantitative Market Research: Fundamentals, Methods, and Applications
- by Alice Ananian
- August 16, 2024
![what is quantitative research approaches Quantitative Market Research](https://prelaunch.com/blog/wp-content/uploads/2024/07/quantitative-market-research-800x600.png)
Did you know that 99% of successful businesses use data to drive their decisions? In our increasingly digital world, quantitative market research has become an essential tool. It doesn’t just provide random facts; it offers precise insights into consumer behavior, market trends, and competitive landscapes, giving businesses the edge they need to storm ahead.
This article explores the fundamentals, methods, and applications of quantitative market research, helping business owners, marketing professionals, and entrepreneurs improve their decision-making and drive their businesses forward.
What is Quantitative Market Research?
Quantitative market research is a methodical approach to gather and analyze numerical data, offering businesses a practical understanding of customer behavior and market trends.
This can be part of both primary and secondary market research. Quantitative market research predominantly relies on structured tools like surveys, polls, and questionnaires to collect quantifiable pieces of information such as percentages, frequencies, and ratings. This research is carried out on a large, representative sample of the target audience to ensure accurate reflection of widespread attitudes and behaviors.
Following the data collection, statistical techniques are applied to reveal patterns, track trends, and identify relationships, effectively converting raw data into actionable insights to guide marketing strategies.
Quantitative vs. Qualitative Research
To fully appreciate quantitative research, it’s essential to understand how it differs from qualitative market research:
Data Type | Numerical | Textual, visual |
Sample Size | Large | Small |
Data Collection | Structured surveys, experiments | Interviews, focus groups, observations |
Analysis | Statistical | Interpretive |
Outcome | Generalizable findings | In-depth insights |
Question Types | Closed-ended | Open-ended |
Flexibility | Low (standardized approach) | High (adaptable to responses) |
While quantitative research provides broad, generalizable insights, qualitative research offers deeper, context-rich understanding. Many successful market research strategies combine both approaches to gain a comprehensive view of the market.
Applications of Quantitative Market Research
Quantitative market research finds applications across various business functions and industries. Here are some key areas where this research method proves invaluable:
Product Development
- Measuring consumer preferences for product features: This involves surveying potential customers to rank or rate different product features, helping companies prioritize which features to include or improve.
- Assessing market demand for new products: Researchers can use quantitative methods to estimate the potential market size and gauge consumer interest in a new product concept before investing in development .
- Evaluating pricing strategies: Through techniques like conjoint analysis or price sensitivity meters, companies can determine optimal price points that maximize both sales and profitability.
Brand Management
- Tracking brand awareness and perception: Regular surveys can measure how many consumers recognize a brand and what associations they have with it, allowing companies to monitor their brand’s health over time.
- Measuring brand loyalty and customer satisfaction: Quantitative research can assess how likely customers are to repurchase or recommend a brand, providing insights into customer retention strategies.
- Comparing brand performance against competitors: Competitive benchmarking surveys can reveal a brand’s strengths and weaknesses relative to competitors in various attributes.
Customer Segmentation
- Identifying distinct customer groups: By analyzing survey data on demographics, behaviors, and preferences, researchers can use cluster analysis to group customers with similar characteristics.
- Determining the size and value of different market segments: Once segments are identified, quantitative research can estimate the size of each segment and its potential value to the business.
Advertising Effectiveness
- Measuring ad recall and recognition: Surveys conducted after ad campaigns can quantify how many people remember seeing an ad and can correctly identify the brand associated with it.
- Assessing the impact of advertising on purchase intent: Researchers can measure how exposure to ads influences consumers’ likelihood to buy a product, helping to justify advertising spend.
- Evaluating return on investment for marketing campaigns: By linking advertising exposure data with sales data, companies can calculate the ROI of their marketing efforts.
Market Sizing and Forecasting
- Estimating market size and growth potential: Using survey data and secondary sources, researchers can quantify the current market size and project future growth based on trends and economic factors.
- Projecting future sales and market share: Time series analysis and regression models can be used to forecast a company’s sales and market share based on historical data and market conditions.
Customer Experience
- Measuring customer satisfaction and loyalty: Regular surveys can track customer satisfaction scores and Net Promoter Scores (NPS) to gauge overall customer sentiment and loyalty.
- Identifying pain points in the customer journey: Quantitative analysis of customer feedback can highlight common issues or areas of dissatisfaction in the customer experience.
- Quantifying the impact of service improvements: By measuring customer satisfaction before and after implementing changes, companies can assess the effectiveness of their improvement initiatives.
Competitive Analysis
- Benchmarking product or service performance: Surveys can compare how a company’s offerings stack up against competitors on various attributes, helping identify areas for improvement.
- Assessing market share and competitive positioning: Regular tracking studies can monitor changes in market share and brand positioning relative to competitors, informing strategic decisions.
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Benefits and Challenges of Quantitative Market Research
Quantitative market research offers a range of advantages that make it a valuable tool for businesses seeking data-driven insights. Understanding these benefits can help organizations leverage this research method effectively to inform their strategies and decision-making processes.
Objectivity: Quantitative research provides unbiased, numerical data that can be statistically analyzed. This objectivity ensures that the findings are not influenced by the researcher’s personal biases or perspectives.
Generalizability: Results derived from large sample sizes can be extrapolated to represent the broader population. This means that the findings are more likely to be valid for all individuals within the target group, enhancing the reliability of the study.
Comparability: Standardized data collection methods allow for easy comparison across different time periods or market segments. This comparability is crucial for tracking changes and trends over time, as well as for identifying differences between various subgroups.
Scalability: Quantitative research methods can efficiently gather data from large sample sizes. This scalability makes it possible to conduct studies on a much larger scale, providing more comprehensive insights into the research question.
Hypothesis testing: Quantitative research enables researchers to test specific theories or assumptions about market behavior. By confirming or disproving these hypotheses, researchers can gain a deeper understanding of the factors driving market trends and consumer behaviors.
Decision support: The concrete data obtained from quantitative research provides a solid foundation to support strategic decision-making. This evidence-based approach facilitates more informed and effective decisions, reducing the risk of error and improving outcomes.
While quantitative market research provides numerous advantages, it’s important to recognize that this approach also comes with its own set of limitations and potential pitfalls. Being aware of these challenges can help researchers and businesses plan more effectively and interpret results with appropriate caution.
Limited depth: Quantitative research methods may not capture the nuanced reasons behind consumer behavior or attitudes, often resulting in a superficial understanding of complex issues.
Inflexibility: Structured surveys and experiments may miss unexpected insights that could emerge in more open-ended research methods, limiting the scope of discovery.
Response bias: Respondents may not always provide honest or accurate answers, particularly on sensitive or personal topics, leading to skewed data and unreliable conclusions.
Cost: Conducting large-scale surveys or experiments can be expensive, often requiring significant financial resources for data collection, participant incentives, and analysis.
Time-consuming: The proper design, implementation, and analysis of quantitative research can be time-intensive, potentially delaying the results and impacting project timelines.
Expertise required: Quantitative research requires extensive knowledge of statistical analysis and research methodologies, necessitating skilled professionals to ensure accurate and reliable outcomes.
Examples of Quantitative Market Research
To illustrate the practical applications of quantitative market research, let’s explore some real-world examples:
Netflix A/B Testing Titles
Ever noticed how Netflix displays different titles or artwork for the same movie or show depending on your profile? This is A/B testing, a form of quantitative research. Netflix uses surveys and click-through rates to determine which title or artwork generates the most clicks and engagement.
Spotify Optimizing Playlists
How does Spotify create those eerily perfect playlists that seem to know exactly what you’re in the mood for? Quantitative research plays a role! Spotify analyzes user listening habits, including skip rates, play time, and song popularity, to curate playlists that resonate with different user preferences.
Coca-Cola Testing New Flavors
Developing a new beverage flavor requires understanding consumer preferences. Coca-Cola uses surveys and taste tests to gather quantitative data on sweetness levels, flavor combinations, and overall appeal. This data helps them refine new flavors before a full-scale launch.
Apple gauging iPhone Screen Size Preferences
Before increasing iPhone screen sizes, Apple likely conducted quantitative research. Online surveys and focus groups could have gathered data on user preferences for screen size, one-handed usability, and content viewing experience. This data likely helped Apple determine the optimal screen size for future iPhones.
Dominos Revamping its Pizza Recipe
In 2009, Domino ‘s faced declining sales. Quantitative research came to the rescue. Domino’s conducted customer surveys and taste tests to understand customer dissatisfaction with its pizza crust and sauce. Based on the findings, they revamped the recipe, leading to a significant turnaround in customer satisfaction and sales.
These are just a few examples, but they showcase the power of quantitative research in helping businesses make data-driven decisions that resonate with their target audiences.
Tools and Resources for Quantitative Research
To conduct effective quantitative market research, consider utilizing these tools and resources :
Survey Platforms
Qualtrics : Comprehensive survey software with advanced analytics
Prelaunch : Lets you gather data via a landing page that concisely presents your product
SurveyMonkey : User-friendly platform for creating and distributing surveys
Google Forms : Free tool for basic surveys and data collection
Statistical Analysis Software
SPSS : Powerful software for complex statistical analysis
R : Open-source programming language for statistical computing
Prelaunch : The platform is a comprehensive concept-validating tool that complies and presents the data you gather via your product’s landing page into insightful section that make it easier to make data-driven decisions.
Excel : Suitable for basic data analysis and visualization
Online Panel Providers
Dynata : Large global panel for diverse respondent recruitment
Amazon Mechanical Turk : Platform for crowdsourcing survey participants
Data Visualization Tools
Tableau : Creates interactive data visualizations and dashboards
Power BI : Microsoft’s business analytics tool for data visualization
Datawrapper : User-friendly tool for creating charts and maps
Market Research Associations
ESOMAR : Global voice of the data, research, and insights community
Insights Association : Leading voice, resource, and network of the marketing research and data analytics community
Academic Resources
Journal of Marketing Research : Scholarly journal featuring cutting-edge research methodologies
Market Research Society (MRS) : Provides training, qualifications, and resources for market researchers
Remember to choose tools that align with your research objectives, budget, and level of expertise. Many of these platforms offer free trials or basic versions, allowing you to experiment before committing to a paid solution.
Quantitative market research is a powerful tool for making data-driven decisions. By providing objective, measurable insights into consumer behavior and market trends, it helps businesses develop targeted strategies and stay ahead of the competition.
While it has its limitations, combining quantitative methods with qualitative approaches can offer a comprehensive market understanding. Careful planning, rigorous methodology, and thoughtful interpretation of results are key to successful quantitative research.
Embrace the power of numbers and let data guide your business success.
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Alice Ananian
Alice has over 8 years experience as a strong communicator and creative thinker. She enjoys helping companies refine their branding, deepen their values, and reach their intended audiences through language.
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Quantitative Research
What is Quantitative Research?
Quantitative research is the methodology which researchers use to test theories about people’s attitudes and behaviors based on numerical and statistical evidence. Researchers sample a large number of users (e.g., through surveys) to indirectly obtain measurable, bias-free data about users in relevant situations.
“Quantification clarifies issues which qualitative analysis leaves fuzzy. It is more readily contestable and likely to be contested. It sharpens scholarly discussion, sparks off rival hypotheses, and contributes to the dynamics of the research process.” — Angus Maddison, Notable scholar of quantitative macro-economic history
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See how quantitative research helps reveal cold, hard facts about users which you can interpret and use to improve your designs.
Use Quantitative Research to Find Mathematical Facts about Users
Quantitative research is a subset of user experience (UX) research . Unlike its softer, more individual-oriented “counterpart”, qualitative research , quantitative research means you collect statistical/numerical data to draw generalized conclusions about users’ attitudes and behaviors . Compare and contrast quantitative with qualitative research, below:
Qualitative Research
You Aim to Determine
The “what”, “where” & “when” of the users’ needs & problems – to help keep your project’s focus on track during development
The “why” – to get behind how users approach their problems in their world
Highly structured (e.g., surveys) – to gather data about what users do & find patterns in large user groups
Loosely structured (e.g., contextual inquiries) – to learn why users behave how they do & explore their opinions
Number of Representative Users
Ideally 30+
Often around 5
Level of Contact with Users
Less direct & more remote (e.g., analytics)
More direct & less remote (e.g., usability testing to examine users’ stress levels when they use your design)
Statistically
Reliable – if you have enough test users
Less reliable, with need for great care with handling non-numerical data (e.g., opinions), as your own opinions might influence findings
Quantitative research is often best done from early on in projects since it helps teams to optimally direct product development and avoid costly design mistakes later. As you typically get user data from a distance—i.e., without close physical contact with users—also applying qualitative research will help you investigate why users think and feel the ways they do. Indeed, in an iterative design process quantitative research helps you test the assumptions you and your design team develop from your qualitative research. Regardless of the method you use, with proper care you can gather objective and unbiased data – information which you can complement with qualitative approaches to build a fuller understanding of your target users. From there, you can work towards firmer conclusions and drive your design process towards a more realistic picture of how target users will ultimately receive your product.
![what is quantitative research approaches what is quantitative research approaches](https://public-media.interaction-design.org/images/uploads/user-content/1445/KtwNiUtikPIIOtci0FVIHrUsiD4M58n6rqz4M00Z.png)
Quantitative analysis helps you test your assumptions and establish clearer views of your users in their various contexts.
Quantitative Research Methods You Can Use to Guide Optimal Designs
There are many quantitative research methods, and they help uncover different types of information on users. Some methods, such as A/B testing, are typically done on finished products, while others such as surveys could be done throughout a project’s design process. Here are some of the most helpful methods:
A/B testing – You test two or more versions of your design on users to find the most effective. Each variation differs by just one feature and may or may not affect how users respond. A/B testing is especially valuable for testing assumptions you’ve drawn from qualitative research. The only potential concerns here are scale—in that you’ll typically need to conduct it on thousands of users—and arguably more complexity in terms of considering the statistical significance involved.
Analytics – With tools such as Google Analytics, you measure metrics (e.g., page views, click-through rates) to build a picture (e.g., “How many users take how long to complete a task?”).
Desirability Studies – You measure an aspect of your product (e.g., aesthetic appeal) by typically showing it to participants and asking them to select from a menu of descriptive words. Their responses can reveal powerful insights (e.g., 78% associate the product/brand with “fashionable”).
Surveys and Questionnaires – When you ask for many users’ opinions, you will gain massive amounts of information. Keep in mind that you’ll have data about what users say they do, as opposed to insights into what they do . You can get more reliable results if you incentivize your participants well and use the right format.
Tree Testing – You remove the user interface so users must navigate the site and complete tasks using links alone. This helps you see if an issue is related to the user interface or information architecture.
Another powerful benefit of conducting quantitative research is that you can keep your stakeholders’ support with hard facts and statistics about your design’s performance—which can show what works well and what needs improvement—and prove a good return on investment. You can also produce reports to check statistics against different versions of your product and your competitors’ products.
Most quantitative research methods are relatively cheap. Since no single research method can help you answer all your questions, it’s vital to judge which method suits your project at the time/stage. Remember, it’s best to spend appropriately on a combination of quantitative and qualitative research from early on in development. Design improvements can be costly, and so you can estimate the value of implementing changes when you get the statistics to suggest that these changes will improve usability. Overall, you want to gather measurements objectively, where your personality, presence and theories won’t create bias.
Learn More about Quantitative Research
Take our User Research course to see how to get the most from quantitative research.
See how quantitative research methods fit into your design research landscape .
This insightful piece shows the value of pairing quantitative with qualitative research .
Find helpful tips on combining quantitative research methods in mixed methods research .
Questions related to Quantitative Research
Qualitative and quantitative research differ primarily in the data they produce. Quantitative research yields numerical data to test hypotheses and quantify patterns. It's precise and generalizable. Qualitative research, on the other hand, generates non-numerical data and explores meanings, interpretations, and deeper insights. Watch our video featuring Professor Alan Dix on different types of research methods.
This video elucidates the nuances and applications of both research types in the design field.
In quantitative research, determining a good sample size is crucial for the reliability of the results. William Hudson, CEO of Syntagm, emphasizes the importance of statistical significance with an example in our video.
He illustrates that even with varying results between design choices, we need to discern whether the differences are statistically significant or products of chance. This ensures the validity of the results, allowing for more accurate interpretations. Statistical tools like chi-square tests can aid in analyzing the results effectively. To delve deeper into these concepts, take William Hudson’s Data-Driven Design: Quantitative UX Research Course .
Quantitative research is crucial as it provides precise, numerical data that allows for high levels of statistical inference. Our video from William Hudson, CEO of Syntagm, highlights the importance of analytics in examining existing solutions.
Quantitative methods, like analytics and A/B testing, are pivotal for identifying areas for improvement, understanding user behaviors, and optimizing user experiences based on solid, empirical evidence. This empirical nature ensures that the insights derived are reliable, allowing for practical improvements and innovations. Perhaps most importantly, numerical data is useful to secure stakeholder buy-in and defend design decisions and proposals. Explore this approach in our Data-Driven Design: Quantitative Research for UX Research course and learn from William Hudson’s detailed explanations of when and why to use analytics in the research process.
After establishing initial requirements, statistical data is crucial for informed decisions through quantitative research. William Hudson, CEO of Syntagm, sheds light on the role of quantitative research throughout a typical project lifecycle in this video:
During the analysis and design phases, quantitative research helps validate user requirements and understand user behaviors. Surveys and analytics are standard tools, offering insights into user preferences and design efficacy. Quantitative research can also be used in early design testing, allowing for optimal design modifications based on user interactions and feedback, and it’s fundamental for A/B and multivariate testing once live solutions are available.
To write a compelling quantitative research question:
Create clear, concise, and unambiguous questions that address one aspect at a time.
Use common, short terms and provide explanations for unusual words.
Avoid leading, compound, and overlapping queries and ensure that questions are not vague or broad.
According to our video by William Hudson, CEO of Syntagm, quality and respondent understanding are vital in forming good questions.
He emphasizes the importance of addressing specific aspects and avoiding intimidating and confusing elements, such as extensive question grids or ranking questions, to ensure participant engagement and accurate responses. For more insights, see the article Writing Good Questions for Surveys .
Survey research is typically quantitative, collecting numerical data and statistical analysis to make generalizable conclusions. However, it can also have qualitative elements, mainly when it includes open-ended questions, allowing for expressive responses. Our video featuring the CEO of Syntagm, William Hudson, provides in-depth insights into when and how to effectively utilize surveys in the product or service lifecycle, focusing on user satisfaction and potential improvements.
He emphasizes the importance of surveys in triangulating data to back up qualitative research findings, ensuring we have a complete understanding of the user's requirements and preferences.
Descriptive research focuses on describing the subject being studied and getting answers to questions like what, where, when, and who of the research question. However, it doesn’t include the answers to the underlying reasons, or the “why” behind the answers obtained from the research. We can use both f qualitative and quantitative methods to conduct descriptive research. Descriptive research does not describe the methods, but rather the data gathered through the research (regardless of the methods used).
When we use quantitative research and gather numerical data, we can use statistical analysis to understand relationships between different variables. Here’s William Hudson, CEO of Syntagm with more on correlation and how we can apply tests such as Pearson’s r and Spearman Rank Coefficient to our data.
This helps interpret phenomena such as user experience by analyzing session lengths and conversion values, revealing whether variables like time spent on a page affect checkout values, for example.
Random Sampling: Each individual in the population has an equitable opportunity to be chosen, which minimizes biases and simplifies analysis.
Systematic Sampling: Selecting every k-th item from a list after a random start. It's simpler and faster than random sampling when dealing with large populations.
Stratified Sampling: Segregate the population into subgroups or strata according to comparable characteristics. Then, samples are taken randomly from each stratum.
Cluster Sampling: Divide the population into clusters and choose a random sample.
Multistage Sampling: Various sampling techniques are used at different stages to collect detailed information from diverse populations.
Convenience Sampling: The researcher selects the sample based on availability and willingness to participate, which may only represent part of the population.
Quota Sampling: Segment the population into subgroups, and samples are non-randomly selected to fulfill a predetermined quota from each subset.
These are just a few techniques, and choosing the right one depends on your research question, discipline, resource availability, and the level of accuracy required. In quantitative research, there isn't a one-size-fits-all sampling technique; choosing a method that aligns with your research goals and population is critical. However, a well-planned strategy is essential to avoid wasting resources and time, as highlighted in our video featuring William Hudson, CEO of Syntagm.
He emphasizes the importance of recruiting participants meticulously, ensuring their engagement and the quality of their responses. Accurate and thoughtful participant responses are crucial for obtaining reliable results. William also sheds light on dealing with failing participants and scrutinizing response quality to refine the outcomes.
The 4 types of quantitative research are Descriptive, Correlational, Causal-Comparative/Quasi-Experimental, and Experimental Research. Descriptive research aims to depict ‘what exists’ clearly and precisely. Correlational research examines relationships between variables. Causal-comparative research investigates the cause-effect relationship between variables. Experimental research explores causal relationships by manipulating independent variables. To gain deeper insights into quantitative research methods in UX, consider enrolling in our Data-Driven Design: Quantitative Research for UX course.
The strength of quantitative research is its ability to provide precise numerical data for analyzing target variables.This allows for generalized conclusions and predictions about future occurrences, proving invaluable in various fields, including user experience. William Hudson, CEO of Syntagm, discusses the role of surveys, analytics, and testing in providing objective insights in our video on quantitative research methods, highlighting the significance of structured methodologies in eliciting reliable results.
To master quantitative research methods, enroll in our comprehensive course, Data-Driven Design: Quantitative Research for UX .
This course empowers you to leverage quantitative data to make informed design decisions, providing a deep dive into methods like surveys and analytics. Whether you’re a novice or a seasoned professional, this course at Interaction Design Foundation offers valuable insights and practical knowledge, ensuring you acquire the skills necessary to excel in user experience research. Explore our diverse topics to elevate your understanding of quantitative research methods.
Answer a Short Quiz to Earn a Gift
What is the primary goal of quantitative research in design?
- To analyze numerical data and identify patterns
- To explore abstract design concepts for implementation
- To understand people's subjective experiences and opinions
Which of the following methods is an example of quantitative research?
- Conduct a focus groups to collect detailed user feedback
- Participate in open-ended interviews to explore user experiences
- Run usability tests and measure task completion times
What is one key advantage of quantitative research?
- It allows participants to express their opinions in a flexible manner.
- It provides researchers with detailed narratives of user experiences and perspectives.
- It produces standardized, comparable data that researchers can statistically analyze.
What is a significant challenge of quantitative research?
- It lacks objectivity which makes its results difficult to reproduce.
- It may oversimplify complex user behaviors into numbers and miss contextual insights.
- It often results in biased or misleading conclusions.
How can designers effectively combine qualitative and quantitative research?
- They can collect quantitative data first, followed by qualitative insights to explain the findings.
- They can completely replace quantitative methods with qualitative approaches.
- They can treat them as interchangeable methods to gather similar data.
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Literature on Quantitative Research
Here’s the entire UX literature on Quantitative Research by the Interaction Design Foundation, collated in one place:
Learn more about Quantitative Research
Take a deep dive into Quantitative Research with our course User Research – Methods and Best Practices .
How do you plan to design a product or service that your users will love , if you don't know what they want in the first place? As a user experience designer, you shouldn't leave it to chance to design something outstanding; you should make the effort to understand your users and build on that knowledge from the outset. User research is the way to do this, and it can therefore be thought of as the largest part of user experience design .
In fact, user research is often the first step of a UX design process—after all, you cannot begin to design a product or service without first understanding what your users want! As you gain the skills required, and learn about the best practices in user research, you’ll get first-hand knowledge of your users and be able to design the optimal product—one that’s truly relevant for your users and, subsequently, outperforms your competitors’ .
This course will give you insights into the most essential qualitative research methods around and will teach you how to put them into practice in your design work. You’ll also have the opportunity to embark on three practical projects where you can apply what you’ve learned to carry out user research in the real world . You’ll learn details about how to plan user research projects and fit them into your own work processes in a way that maximizes the impact your research can have on your designs. On top of that, you’ll gain practice with different methods that will help you analyze the results of your research and communicate your findings to your clients and stakeholders—workshops, user journeys and personas, just to name a few!
By the end of the course, you’ll have not only a Course Certificate but also three case studies to add to your portfolio. And remember, a portfolio with engaging case studies is invaluable if you are looking to break into a career in UX design or user research!
We believe you should learn from the best, so we’ve gathered a team of experts to help teach this course alongside our own course instructors. That means you’ll meet a new instructor in each of the lessons on research methods who is an expert in their field—we hope you enjoy what they have in store for you!
All open-source articles on Quantitative Research
Best practices for qualitative user research.
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/articles/heros/article_130935_hero_594b80551a1779.22681546.jpg?tr=w-1000)
- 4 years ago
Card Sorting
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/books/covers/the-encyclopedia-of-human-computer-interaction-2nd-ed.png)
Understand the User’s Perspective through Research for Mobile UX
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7 Simple Ways to Get Better Results From Ethnographic Research
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/articles/heros/582211e8a85ac.jpg?tr=w-1000)
Question Everything
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/articles/heros/582215b5c6fb3.jpg?tr=w-1000)
Tree Testing
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/articles/heros/article_131176_hero_618d1caae69978.43302799.png?tr=w-1000)
- 3 years ago
Adding Quality to Your Design Research with an SSQS Checklist
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/articles/heros/564357f8bbd5d.jpg?tr=w-1000)
- 8 years ago
Rating Scales in UX Research: The Ultimate Guide
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/articles/heros/article_131368_hero_665ec7e8181a15.06131479.png?tr=w-1000)
How to Fit Quantitative Research into the Project Lifecycle
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/articles/heros/article_131166_hero_61765b96319f25.29794910.png?tr=w-1000)
Correlation in User Experience
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/articles/heros/article_131169_hero_61766ccf0906e2.65708525.png?tr=w-1000)
Why and When to Use Surveys
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/articles/heros/article_131170_hero_617670b5aaa324.31427225.png?tr=w-1000)
First-Click Testing
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/articles/heros/article_131177_hero_618d1dba25d615.08534896.png?tr=w-1000)
What to Test
![what is quantitative research approaches what is quantitative research approaches](https://public-images.interaction-design.org/literature/articles/heros/article_131182_hero_618d232f27e369.10387738.png?tr=w-1000)
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Nursing Research (NURS 3321/4325/5366)
- Introduction
- Understand What Quantitative Research Is
- Understand What Qualitative Research Is
- Sage Methods Map
- Step 1: Accessing CINAHL
- Step 2: Create a Keyword Search
- Step 3: Create a Subject Heading Search
- Step 4: Repeat Steps 1-3 for Second Concept
- Step 5: Repeat Steps 1-3 for Quantitative Terms
- Step 6: Combining All Searches
- Step 7: Adding Limiters
- Step 8: Save Your Search!
- What Kind of Article is This?
- PICO Keyword Search Strategy
- PICO Keyword Search
- PICO Subject Heading Search
- Combining Keyword and Subject Heading Searches
- Adding Filters/Limiters
- Finding Health Statistics
- Find Clinical Guidelines This link opens in a new window
- APA Format & Citations This link opens in a new window
What is Quantitative Research?
Quantitative methodology is the dominant research framework in the social sciences. it refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns . quantitative research gathers a range of numeric data. some of the numeric data is intrinsically quantitative (e.g. personal income), while in other cases the numeric structure is imposed (e.g. ‘on a scale from 1 to 10, how depressed did you feel last week’). the collection of quantitative information allows researchers to conduct simple to extremely sophisticated statistical analyses that aggregate the data (e.g. averages, percentages), show relationships among the data (e.g. ‘students with lower grade point averages tend to score lower on a depression scale’) or compare across aggregated data (e.g. the usa has a higher gross domestic product than spain). quantitative research includes methodologies such as questionnaires, structured observations or experiments and stands in contrast to qualitative research. qualitative research involves the collection and analysis of narratives and/or open-ended observations through methodologies such as interviews, focus groups or ethnographies..
Coghlan, D., Brydon-Miller, M. (2014). The SAGE encyclopedia of action research (Vols. 1-2). London, : SAGE Publications Ltd doi: 10.4135/9781446294406
What is the purpose of quantitative research?
The purpose of quantitative research is to generate knowledge and create understanding about the social world. Quantitative research is used by social scientists, including communication researchers, to observe phenomena or occurrences affecting individuals. Social scientists are concerned with the study of people. Quantitative research is a way to learn about a particular group of people, known as a sample population. Using scientific inquiry, quantitative research relies on data that are observed or measured to examine questions about the sample population.
Allen, M. (2017). The SAGE encyclopedia of communication research methods (Vols. 1-4). Thousand Oaks, CA: SAGE Publications, Inc doi: 10.4135/9781483381411
How do I know if the study is a quantitative design? What type of quantitative study is it?
Quantitative Research Designs: Descriptive non-experimental, Quasi-experimental or Experimental?
Studies do not always explicitly state what kind of research design is being used. You will need to know how to decipher which design type is used. The following video will help you determine the quantitative design type.
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Quantitative Research Questionnaire – Types & Examples
Published by Alvin Nicolas at August 20th, 2024 , Revised On August 21, 2024
Research is usually done to provide solutions to an ongoing problem. Wherever the researchers see a gap, they tend to launch research to enhance their knowledge and to provide solutions to the needs of others. If they want to research from a subjective point of view, they consider qualitative research. On the other hand, when they research from an objective point of view, they tend to consider quantitative research.
There’s a fine line between subjectivity and objectivity. Qualitative research, related to subjectivity, assesses individuals’ personal opinions and experiences, while quantitative research, associated with objectivity, collects numerical data to derive results. However, the best medium to collect data in quantitative research is a questionnaire.
Let’s discuss what a quantitative research questionnaire is, its types, methods of writing questions, and types of survey questions. By thoroughly understanding these key essential terms, you can efficiently create a professional and well-organised quantitative research questionnaire.
What is a Quantitative Research Questionnaire?
Quantitative research questionnaires are preferably used during quantitative research. They are a well-structured set of questions designed specifically to gather specific, close-ended participant responses. This allows the researchers to gather numerical data and obtain a deep understanding of a particular event or problem.
As you know, qualitative research questionnaires contain open-ended questions that allow the participants to express themselves freely, while quantitative research questionnaires contain close-ended and specific questions, such as multiple-choice and Likert scales, to assess individuals’ behaviour.
Quantitative research questionnaires are usually used in research in various fields, such as psychology, medicine, chemistry, and economics.
Let’s see how you can write quantitative research questions by going through some examples:
- How much do British people consume fast food per week?
- What is the percentage of students living in hostels in London?
Types of Quantitative Research Questions With Examples
After learning what a quantitative research questionnaire is and what quantitative research questions look like, it’s time to thoroughly discuss the different types of quantitative research questions to explore this topic more.
Dichotomous Questions
Dichotomous questions are those with a margin for only two possible answers. They are usually used when the answers are “Yes/No” or “True/False.” These questions significantly simplify the research process and help collect simple responses.
Example: Have you ever visited Istanbul?
Multiple Choice Questions
Multiple-choice questions have a list of possible answers for the participants to choose from. They help assess people’s general knowledge, and the data gathered by multiple-choice questions can be easily analysed.
Example: Which of the following is the capital of France?
Multiple Answer Questions
Multiple-answer questions are similar to multiple-choice questions. However, there are multiple answers for participants to choose from. They are used when the questions can’t have a single, specific answer.
Example: Which of the following movie genres are your favourite?
Likert Scale Questions
Likert scale questions are used when the preferences and emotions of the participants are measured from one extreme to another. The scales are usually applied to measure likelihood, frequency, satisfaction, and agreement. The Likert scale has only five options to choose from.
Example: How satisfied are you with your job?
Semantic Differential Questions
Similar to Likert scales, semantic differential questions are also used to measure the emotions and attitudes of participants. The only difference is that instead of using extreme options such as strongly agree and strongly disagree, opposites of a particular choice are given to reduce bias.
Example: Please rate the services of our company.
Rank Order Questions
Rank-order questions are usually used to measure the preferences and choices of the participants efficiently. In this, multiple choices are given, and participants are asked to rank them according to their perspective. This helps to create a good participant profile.
Example: Rank the given books according to your interest.
Matrix Questions
Matrix questions are similar to Likert scales. In Likert scales, participants’ responses are measured through separate questions, while in matrix questions, multiple questions are compiled in a single row to simplify the data collection method efficiently.
Example: Rate the following activities that you do in daily life.
How To Write Quantitative Research Questions?
Quantitative research questions allow researchers to gather empirical data to answer their research problems. As we have discussed the different types of quantitative research questions above, it’s time to learn how to write the perfect quantitative research questions for a questionnaire and streamline your research process.
Here are the steps to follow to write quantitative research questions efficiently.
Step 1: Determine the Research Goals
The first step in writing quantitative research questions is to determine your research goals. Determining and confirming your research goals significantly helps you understand what kind of questions you need to create and for what grade. Efficiently determining the research goals also reduces the need for further modifications in the questionnaire.
Step 2: Be Mindful About the Variables
There are two variables in the questions: independent and dependent. It is essential to decide what would be the dependent variable in your questions and what would be the independent. It significantly helps to understand where to emphasise and where not. It also reduces the probability of additional and vague questions.
Step 3: Choose the Right Type of Question
It is also important to determine the right type of questions to add to your questionnaire. Whether you want Likert scales, rank-order questions, or multiple-answer questions, choosing the right type of questions will help you measure individuals’ responses efficiently and accurately.
Step 4: Use Easy and Clear Language
Another thing to keep in mind while writing questions for a quantitative research questionnaire is to use easy and clear language. As you know, quantitative research is done to measure specific and simple responses in empirical form, and using easy and understandable language in questions makes a huge difference.
Step 5: Be Specific About The Topic
Always be mindful and specific about your topic. Avoid writing questions that divert from your topic because they can cause participants to lose interest. Use the basic terms of your selected topic and gradually go deep. Also, remember to align your topic and questions with your research objectives and goals.
Step 6: Appropriately Write Your Questions
When you have considered all the above-discussed things, it’s time to write your questions appropriately. Don’t just haste in writing. Think twice about the result of a question and then consider writing it in the questionnaire. Remember to be precise while writing. Avoid overwriting.
Step 7: Gather Feedback From Peers
When you have finished writing questions, gather feedback from your researcher peers. Write down all the suggestions and feedback given by your peers. Don’t panic over the criticism of your questions. Remember that it’s still time to make necessary changes to the questionnaire before launching your campaign.
Step 8: Refine and Finalise the Questions
After gathering peer feedback, make necessary and appropriate changes to your questions. Be mindful of your research goals and topic. Try to modify your questions according to them. Also, be mindful of the theme and colour scheme of the questionnaire that you decided on. After refining the questions, finalise your questionnaire.
Types of Survey Questionnaires in Quantitative Research
Quantitative research questionnaires have close-ended questions that allow the researchers to measure accurate and specific responses from the participants. They don’t contain open-ended questions like qualitative research, where the response is measured by interviews and focus groups. Good combinations of questions are used in the quantitative research survey .
However, here are the types of surveys in quantitative research:
Descriptive Survey
The descriptive survey is used to obtain information about a particular variable. It is used to associate a quantity and quantify research variables. The questions associated with descriptive surveys mostly start with “What is” and “How much”.
Example: A descriptive survey to measure how much money children spend to buy toys.
Comparative Survey
A comparative survey is used to establish a comparison between one or more dependable variables and two or more comparison groups. This survey aims to form a comparative relation between the variables under study. The structure of the question in a comparative survey is, “What is the difference in [dependable variable] between [two or more groups]?”.
Example: A comparative survey on the difference in political awareness between Eastern and Western citizens.
Relationship-Based Survey
Relationship-based survey is used to understand the relationship or association between two or more independent and dependent variables. Cause and effect between two or more variables is measured in the relationship-based survey. The structure of questions in a relationship-based survey is, “What is the relation [between or among] [independent variable] and [dependable variable]?”.
Example: What is the relationship between education and lifestyle in America?
Advantages & Disadvantages of Questionnaires in Quantitative Research
Quantitative research questionnaires are an excellent tool to collect data and information about the responses of individuals. Quantitative research comes with various advantages, but along with advantages, it also has its disadvantages. Check the table below to learn about the advantages and disadvantages of a quantitative research questionnaire.
It is an efficient source for quickly collecting data. | It restricts the depth of the topic during collection. |
There is less risk of subjectivity and research bias. | There is a high risk of artificial and unreal expectations of research questions. |
It significantly helps to collect extensive insights into the population. | It overemphasises empirical data, avoiding personal opinions. |
It focuses on simplicity and particularity. | There is a risk of over-simplicity. |
There are clear and achievable research objectives. | There is a risk of additional amendments and modifications. |
Quantitative Research Questionnaire Example
Here is an example of a quantitative research questionnaire to help you get the idea and create an efficient and well-developed questionnaire for your research:
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Quantitative research methods. You can use quantitative research methods for descriptive, correlational or experimental research. In descriptive research, you simply seek an overall summary of your study variables.; In correlational research, you investigate relationships between your study variables.; In experimental research, you systematically examine whether there is a cause-and-effect ...
Quantitative research is the process of collecting and analyzing numerical data to describe, predict, or control variables of interest. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations. The purpose of quantitative research is to test a predefined ...
Quantitative Research Methods are as follows: Descriptive Research Design. Descriptive research design is used to describe the characteristics of a population or phenomenon being studied. This research method is used to answer the questions of what, where, when, and how. Descriptive research designs use a variety of methods such as observation ...
Quantitative research is the opposite of qualitative research, which involves collecting and analysing non-numerical data (e.g. text, video, or audio). Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.
What is Quantitative Research? Quantitative methodology is the dominant research framework in the social sciences. It refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns.Quantitative research gathers a range of numeric data.
The necessity, importance, relevance, and urgency of quantitative research are articulated, establishing a strong foundation for the subsequent discussion, which delineates the scope, objectivity, goals, data, and methods that distinguish quantitative research, alongside a balanced inspection of its strengths and shortcomings, particularly in ...
Quantitative research is a type of research that focuses on collecting and analyzing numerical data to answer research questions. There are two main methods used to conduct quantitative research: 1. Primary Method. There are several methods of primary quantitative research, each with its own strengths and limitations.
The main difference between quantitative and qualitative research is the type of data they collect and analyze. Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed numerically. Quantitative research is often used to test ...
Quantitative research is a research strategy that focuses on quantifying the collection and analysis of data. [1] It is formed from a deductive approach where emphasis is placed on the testing of theory, shaped by empiricist and positivist philosophies. [1]Associated with the natural, applied, formal, and social sciences this research strategy promotes the objective empirical investigation of ...
Quantitative research methods. a method of research that relies on measuring variables using a numerical system, analyzing these measurements using any of a variety of statistical models, and reporting relationships and associations among the studied variables. For example, these variables may be test scores or measurements of reaction time.
Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes.2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed ...
These three research approaches are quantitative, qualitative, and mixed methods that are commonly used by researchers in various research studies. However, with many options regarding the ...
The systematic approaches that ground quantitative research involve hundreds or thousands of data points for one research project. The wonder of quantitative research is that each data point, or row in a spreadsheet, is a person and has a human story to tell.
Secondary quantitative research methods; Primary Quantitative Research Methods. Primary quantitative research is the most widely used method of conducting market research. The distinct feature of primary research is that the researcher focuses on collecting data directly rather than depending on data collected from previously done research ...
Quantitative research allows you to confirm or test a hypothesis or theory or quantify a specific problem or quality. Qualitative research allows you to understand concepts or experiences. Let's look at how you'll use these approaches in a research project a bit closer: Formulating a hypothesis.
Secondary quantitative research methods; 1. Primary quantitative research methods. Primary quantitative research is the most popular way of conducting market research. The differentiating factor of this method is that the researcher relies on collecting data firsthand instead of relying on data collected from previous research.
Quantitative research Quantitative research is expressed in numbers and graphs. It is used to test or confirm theories and assumptions. This type of research can be used to establish generalizable facts. about a topic. Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.
quantitative research are: Describing a problem statement by presenting the need for an explanation of a variable's relationship. Offering literature, a significant function by answering research ...
Quantitative research makes use of the scientific method (Chap. 1) through the application of a defined number of specific steps in order to establish new knowledge.These steps involve not only the collection of numerical data but also more importantly the analysis of such data, for the purpose of explaining, predicting, and/or controlling variables relating to the problem being studied.
Quantitative data analysis methods. There are two statistical methods for reviewing quantitative data and user analytics. However, before exploring these in-depth, let's refresh these key concepts: Population. This is the entire group of individuals or entities that are relevant to the research. Sample.
Quantitative research methods are concerned with the planning, design, and implementation of strategies to collect and analyze data. Descartes, the seventeenth-century philosopher, suggested that how the results are achieved is often more important than the results themselves, as the journey taken along the research path is a journey of discovery. . High-quality quantitative research is ...
Quantitative Methods in Communication Research In communication research, both quantitative and qualitative methods are essential for understanding different aspects of communication processes and effects.
Quantitative research is a systematic investigation method that relies on numerical data to answer research questions or test hypotheses. Unlike qualitative research, which deals with subjective experiences and meanings, quantitative research aims to quantify relationships, behaviors, or phenomena through statistical analysis .
Quantitative Research Definition: Quantitative research is a systematic and objective approach to collecting, analyzing, and interpreting numerical data. It measures and quantifies variables, employing statistical methods to uncover patterns, relationships, and trends. Quantitative research gets utilized across a wide range of fields, including ...
Quantitative market research is a methodical approach to gather and analyze numerical data, offering businesses a practical understanding of customer behavior and market trends. This can be part of both primary and secondary market research.
Quantitative research is the methodology which researchers use to test theories about people's attitudes and behaviors based on numerical and statistical evidence. Researchers sample a large number of users (e.g., through surveys) to indirectly obtain measurable, bias-free data about users in relevant situations.
What is Quantitative Research? Quantitative methodology is the dominant research framework in the social sciences. It refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns.Quantitative research gathers a range of numeric data.
1 INTRODUCTION. In August 2021, we issued a call for papers (CfP) with the aim of bringing together information systems (IS) research that transcends the qualitative-quantitative divide using qualitative comparative analysis (QCA) as a configurational, comparative approach.
Types of Survey Questionnaires in Quantitative Research. Quantitative research questionnaires have close-ended questions that allow the researchers to measure accurate and specific responses from the participants. They don't contain open-ended questions like qualitative research, where the response is measured by interviews and focus groups.
Research design, research methods and statistical analysis are critical elements of scientific discovery. Understanding the characteristics of quantitative study design, quantitative data ...