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## Education Standards

Radford university.

Learning Domain: Social Work

Standard: Basic Research Methodology

## Lesson 10: Sampling in Qualitative Research

Lesson 11: qualitative measurement & rigor, lesson 12: qualitative design & data gathering, lesson 1: introduction to research, lesson 2: getting started with your research project, lesson 3: critical information literacy, lesson 4: paradigm, theory, and causality, lesson 5: research questions, lesson 6: ethics, lesson 7: measurement in quantitative research, lesson 8: sampling in quantitative research, lesson 9: quantitative research designs, powerpoint slides: sowk 621.01: research i: basic research methodology.

The twelve lessons for SOWK 621.01: Research I: Basic Research Methodology as previously taught by Dr. Matthew DeCarlo at Radford University. Dr. DeCarlo and his team developed a complete package of materials that includes a textbook, ancillary materials, and a student workbook as part of a VIVA Open Course Grant.

The PowerPoint slides associated with the twelve lessons of the course, SOWK 621.01: Research I: Basic Research Methodology, as previously taught by Dr. Matthew DeCarlo at Radford University.

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Home » Variables in Research – Definition, Types and Examples

## Variables in Research – Definition, Types and Examples

Table of Contents

## Variables in Research

Definition:

In Research, Variables refer to characteristics or attributes that can be measured, manipulated, or controlled. They are the factors that researchers observe or manipulate to understand the relationship between them and the outcomes of interest.

## Types of Variables in Research

Types of Variables in Research are as follows:

## Independent Variable

This is the variable that is manipulated by the researcher. It is also known as the predictor variable, as it is used to predict changes in the dependent variable. Examples of independent variables include age, gender, dosage, and treatment type.

## Dependent Variable

This is the variable that is measured or observed to determine the effects of the independent variable. It is also known as the outcome variable, as it is the variable that is affected by the independent variable. Examples of dependent variables include blood pressure, test scores, and reaction time.

## Confounding Variable

This is a variable that can affect the relationship between the independent variable and the dependent variable. It is a variable that is not being studied but could impact the results of the study. For example, in a study on the effects of a new drug on a disease, a confounding variable could be the patient’s age, as older patients may have more severe symptoms.

## Mediating Variable

This is a variable that explains the relationship between the independent variable and the dependent variable. It is a variable that comes in between the independent and dependent variables and is affected by the independent variable, which then affects the dependent variable. For example, in a study on the relationship between exercise and weight loss, the mediating variable could be metabolism, as exercise can increase metabolism, which can then lead to weight loss.

## Moderator Variable

This is a variable that affects the strength or direction of the relationship between the independent variable and the dependent variable. It is a variable that influences the effect of the independent variable on the dependent variable. For example, in a study on the effects of caffeine on cognitive performance, the moderator variable could be age, as older adults may be more sensitive to the effects of caffeine than younger adults.

## Control Variable

This is a variable that is held constant or controlled by the researcher to ensure that it does not affect the relationship between the independent variable and the dependent variable. Control variables are important to ensure that any observed effects are due to the independent variable and not to other factors. For example, in a study on the effects of a new teaching method on student performance, the control variables could include class size, teacher experience, and student demographics.

## Continuous Variable

This is a variable that can take on any value within a certain range. Continuous variables can be measured on a scale and are often used in statistical analyses. Examples of continuous variables include height, weight, and temperature.

## Categorical Variable

This is a variable that can take on a limited number of values or categories. Categorical variables can be nominal or ordinal. Nominal variables have no inherent order, while ordinal variables have a natural order. Examples of categorical variables include gender, race, and educational level.

## Discrete Variable

This is a variable that can only take on specific values. Discrete variables are often used in counting or frequency analyses. Examples of discrete variables include the number of siblings a person has, the number of times a person exercises in a week, and the number of students in a classroom.

## Dummy Variable

This is a variable that takes on only two values, typically 0 and 1, and is used to represent categorical variables in statistical analyses. Dummy variables are often used when a categorical variable cannot be used directly in an analysis. For example, in a study on the effects of gender on income, a dummy variable could be created, with 0 representing female and 1 representing male.

## Extraneous Variable

This is a variable that has no relationship with the independent or dependent variable but can affect the outcome of the study. Extraneous variables can lead to erroneous conclusions and can be controlled through random assignment or statistical techniques.

## Latent Variable

This is a variable that cannot be directly observed or measured, but is inferred from other variables. Latent variables are often used in psychological or social research to represent constructs such as personality traits, attitudes, or beliefs.

## Moderator-mediator Variable

This is a variable that acts both as a moderator and a mediator. It can moderate the relationship between the independent and dependent variables and also mediate the relationship between the independent and dependent variables. Moderator-mediator variables are often used in complex statistical analyses.

## Variables Analysis Methods

There are different methods to analyze variables in research, including:

- Descriptive statistics: This involves analyzing and summarizing data using measures such as mean, median, mode, range, standard deviation, and frequency distribution. Descriptive statistics are useful for understanding the basic characteristics of a data set.
- Inferential statistics : This involves making inferences about a population based on sample data. Inferential statistics use techniques such as hypothesis testing, confidence intervals, and regression analysis to draw conclusions from data.
- Correlation analysis: This involves examining the relationship between two or more variables. Correlation analysis can determine the strength and direction of the relationship between variables, and can be used to make predictions about future outcomes.
- Regression analysis: This involves examining the relationship between an independent variable and a dependent variable. Regression analysis can be used to predict the value of the dependent variable based on the value of the independent variable, and can also determine the significance of the relationship between the two variables.
- Factor analysis: This involves identifying patterns and relationships among a large number of variables. Factor analysis can be used to reduce the complexity of a data set and identify underlying factors or dimensions.
- Cluster analysis: This involves grouping data into clusters based on similarities between variables. Cluster analysis can be used to identify patterns or segments within a data set, and can be useful for market segmentation or customer profiling.
- Multivariate analysis : This involves analyzing multiple variables simultaneously. Multivariate analysis can be used to understand complex relationships between variables, and can be useful in fields such as social science, finance, and marketing.

## Examples of Variables

- Age : This is a continuous variable that represents the age of an individual in years.
- Gender : This is a categorical variable that represents the biological sex of an individual and can take on values such as male and female.
- Education level: This is a categorical variable that represents the level of education completed by an individual and can take on values such as high school, college, and graduate school.
- Income : This is a continuous variable that represents the amount of money earned by an individual in a year.
- Weight : This is a continuous variable that represents the weight of an individual in kilograms or pounds.
- Ethnicity : This is a categorical variable that represents the ethnic background of an individual and can take on values such as Hispanic, African American, and Asian.
- Time spent on social media : This is a continuous variable that represents the amount of time an individual spends on social media in minutes or hours per day.
- Marital status: This is a categorical variable that represents the marital status of an individual and can take on values such as married, divorced, and single.
- Blood pressure : This is a continuous variable that represents the force of blood against the walls of arteries in millimeters of mercury.
- Job satisfaction : This is a continuous variable that represents an individual’s level of satisfaction with their job and can be measured using a Likert scale.

## Applications of Variables

Variables are used in many different applications across various fields. Here are some examples:

- Scientific research: Variables are used in scientific research to understand the relationships between different factors and to make predictions about future outcomes. For example, scientists may study the effects of different variables on plant growth or the impact of environmental factors on animal behavior.
- Business and marketing: Variables are used in business and marketing to understand customer behavior and to make decisions about product development and marketing strategies. For example, businesses may study variables such as consumer preferences, spending habits, and market trends to identify opportunities for growth.
- Healthcare : Variables are used in healthcare to monitor patient health and to make treatment decisions. For example, doctors may use variables such as blood pressure, heart rate, and cholesterol levels to diagnose and treat cardiovascular disease.
- Education : Variables are used in education to measure student performance and to evaluate the effectiveness of teaching strategies. For example, teachers may use variables such as test scores, attendance, and class participation to assess student learning.
- Social sciences : Variables are used in social sciences to study human behavior and to understand the factors that influence social interactions. For example, sociologists may study variables such as income, education level, and family structure to examine patterns of social inequality.

## Purpose of Variables

Variables serve several purposes in research, including:

- To provide a way of measuring and quantifying concepts: Variables help researchers measure and quantify abstract concepts such as attitudes, behaviors, and perceptions. By assigning numerical values to these concepts, researchers can analyze and compare data to draw meaningful conclusions.
- To help explain relationships between different factors: Variables help researchers identify and explain relationships between different factors. By analyzing how changes in one variable affect another variable, researchers can gain insight into the complex interplay between different factors.
- To make predictions about future outcomes : Variables help researchers make predictions about future outcomes based on past observations. By analyzing patterns and relationships between different variables, researchers can make informed predictions about how different factors may affect future outcomes.
- To test hypotheses: Variables help researchers test hypotheses and theories. By collecting and analyzing data on different variables, researchers can test whether their predictions are accurate and whether their hypotheses are supported by the evidence.

## Characteristics of Variables

Characteristics of Variables are as follows:

- Measurement : Variables can be measured using different scales, such as nominal, ordinal, interval, or ratio scales. The scale used to measure a variable can affect the type of statistical analysis that can be applied.
- Range : Variables have a range of values that they can take on. The range can be finite, such as the number of students in a class, or infinite, such as the range of possible values for a continuous variable like temperature.
- Variability : Variables can have different levels of variability, which refers to the degree to which the values of the variable differ from each other. Highly variable variables have a wide range of values, while low variability variables have values that are more similar to each other.
- Validity and reliability : Variables should be both valid and reliable to ensure accurate and consistent measurement. Validity refers to the extent to which a variable measures what it is intended to measure, while reliability refers to the consistency of the measurement over time.
- Directionality: Some variables have directionality, meaning that the relationship between the variables is not symmetrical. For example, in a study of the relationship between smoking and lung cancer, smoking is the independent variable and lung cancer is the dependent variable.

## Advantages of Variables

Here are some of the advantages of using variables in research:

- Control : Variables allow researchers to control the effects of external factors that could influence the outcome of the study. By manipulating and controlling variables, researchers can isolate the effects of specific factors and measure their impact on the outcome.
- Replicability : Variables make it possible for other researchers to replicate the study and test its findings. By defining and measuring variables consistently, other researchers can conduct similar studies to validate the original findings.
- Accuracy : Variables make it possible to measure phenomena accurately and objectively. By defining and measuring variables precisely, researchers can reduce bias and increase the accuracy of their findings.
- Generalizability : Variables allow researchers to generalize their findings to larger populations. By selecting variables that are representative of the population, researchers can draw conclusions that are applicable to a broader range of individuals.
- Clarity : Variables help researchers to communicate their findings more clearly and effectively. By defining and categorizing variables, researchers can organize and present their findings in a way that is easily understandable to others.

## Disadvantages of Variables

Here are some of the main disadvantages of using variables in research:

- Simplification : Variables may oversimplify the complexity of real-world phenomena. By breaking down a phenomenon into variables, researchers may lose important information and context, which can affect the accuracy and generalizability of their findings.
- Measurement error : Variables rely on accurate and precise measurement, and measurement error can affect the reliability and validity of research findings. The use of subjective or poorly defined variables can also introduce measurement error into the study.
- Confounding variables : Confounding variables are factors that are not measured but that affect the relationship between the variables of interest. If confounding variables are not accounted for, they can distort or obscure the relationship between the variables of interest.
- Limited scope: Variables are defined by the researcher, and the scope of the study is therefore limited by the researcher’s choice of variables. This can lead to a narrow focus that overlooks important aspects of the phenomenon being studied.
- Ethical concerns: The selection and measurement of variables may raise ethical concerns, especially in studies involving human subjects. For example, using variables that are related to sensitive topics, such as race or sexuality, may raise concerns about privacy and discrimination.

## About the author

## Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research Variables

Feb 17, 2014

580 likes | 1.68k Views

Research Variables. Research Definitions. An experiment is a process in which an investigator devises two or more different experiences (treatments) for subjects or participants. Involves a control group and one or more treatment groups. Research Variables.

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## Presentation Transcript

Research Definitions • An experiment is a process in which an investigator devises two or more different experiences (treatments) for subjects or participants. • Involves a control group and one or more treatment groups

Research Variables • Independent Variable (IV): the controlled variable in a study; hypothesized to have an effect on the dependent variable • In a true experiment, this is an experimental (manipulated) variable. • In a quasi-experiment, this is a subject variable (not subject to manipulation). Experimental Subject

Research Variables • Regardless of type, there will always be two or more levels of the independent variable. • Variable: a characteristic or phenomenon that may take on different values; variables must vary! • The levels of the independent variable can be: • Independent of one another: between-subjects design • Dependent on one another: within-subjects design

Research Variables • Dependent Variable (DV): an outcome of interest that is observed and measured by the researcher; hypothesized to be affected by the independent variable

Defining Research Variables • Operational Definition: a definition of a variable in terms of the operations used to manipulate it or measure it • Must be precise enough that anyone reading a review of your research could replicate your experiment exactly.

Problem Variables • Extraneous (Nuisance) Variables: uncontrolled variables which can affect the experimental outcome • Extraneous variables become confounding variables when their values change systematically along with the independent variable in an experiment.

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## introduction to research methodology

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Egesa Romans

According to Mugenda & Mugenda (2010), research is process of carrying out a diligent inquiry or a critical examination of a given phenomenonexhaustive study that follows some logical sequence. Mouly defines research as a process of arriving at effective solutions to problems through systematic collection, analysis and interpretation of data. Research also involves a critical analysis of existing conclusions or theories with regard to newly discovered facts Research is the continued search for knowledge and understanding of the world around us. Clifford Woody argues that research is the process of designing and redefining problems, formulating hypothesis or suggested solutions, collecting, organizing and evaluating data, making deductions and reaching conclusions and carefully testing the conclusions to determine whether they fit the formulated hypothesis.

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In the simplest of terms, the research definition is a process of seeking out knowledge. This knowledge can be new, or it can support an already known fact. The purpose of research is to inform and is based on collected and analyzed data. This exploration occurs systematically, where it is either tested or investigated to add to a body of knowledge. Research is a systematic and scientific approach to understanding the world around us. It is a process of inquiry that involves the collection and analysis of data to answer questions or solve problems.

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Research may be very broadly defined as systematic gathering of data and information and its analysis for advancement of knowledge in any subject. research attempts to find answer intellectual and practical questions through application of systematic methods. Types of research can be classified in many different ways.

Research is any original and systematic investigation undertaken to increase knowledge and understanding and to establish facts and principles. It comprises the creation of ideas and generation of new knowledge that lead to new and improved insights and the development of new material, devices, products and processes. The word " research " perhaps originates from the old French word recerchier that meant to 'search again'. It implicitly assumes that the earlier search was not exhaustive and complete and hence a repeated search is called for.

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In this paper, the author presented how to carry out an appropriate research without any fear. Our intention is to motivated the researcher in such a technique that, they do not feel any difficulties when they start-up their research. After goes through this report, the researcher will never feel anxiety during their research work. Before starting the research work, researchers are fell trepidation but here presented approach will stirred up the researcher for research. The systematic process is presented in this paper for carry on the healthy research.

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## 10 Types of Variables in Research | Examples | PPT

In any research study, there are variables. Variables are any characteristics that can be measured or observed. There are many great uses for these variables, but it is important to know what they are!

In this article, you will learn the basics of variables and will give you a clear picture of the types of variables that exist in the social sciences and statistics and how they can be used.

## What is a Variable?

In research, variables are the factors that are manipulated to measure their effects on an outcome variable.

## Example of Variable

3- For example, if a person’s skin color is the variable in an experiment, its value can range from brown to pale to white, from individual to individual.

## 10 Types of Variables

Independent variable, example of independent variable, dependent variable.

The dependent variable is a variable that represents the experiment’s outcome. The variable that is measured in order to determine the effect of an independent variable. The dependent variable is the variable being measured.

## Example of Dependent Variable

Mediating variable, example of mediating variable.

For example, if income is the independent variable and longevity is the dependent variable, the researcher could postulate that access to quality healthcare is the mediating variable that connects income and longevity.

## Moderating Variable

Control variables.

Control variables are those that remain constant throughout the experiment. Variables that are held constant in order to isolate the effect of a given independent variable.

## Example of Control Variables

Developing conceptual framework with variables.

Organization learning is IV that is independent variable and innovation is DV dependent Variable.

Lets add moderator between organizational learning and innovation. Take leadership as a moderator as it will strengthen the relationship of IV and DV.

The larger firms need to be more innovative as compared to the smaller firms. So, these variables, by default have impact on firm’s innovation. So, we should control these variables in order to see whether IV, mediator and moderator have an effect on the dependent variable.

## Quantitative Variable

Example of quantitative variable, discrete variable, example of discrete variable.

1- As an example, consider the money in your pocket or the funds in your savings account.

## Continuous Variable

Example of continuous variable, qualitative variables.

Qualitative variables, often known as categorical variables, are non-numerical values or categories. You can realistically count any numerical variables.

## Example of Qualitative Variables

Binary variable.

A binary variable is a variable that can take on only two values, usually 0 and 1. In research, binary variables are often used to represent the presence or absence of something,

## Example of Binary Variable

1- To know whether a person has a disease (0 = no, 1 = yes).

## Nominal Variable

Nominal variables are sometimes called categorical variables. Nominal variables are usually coded with numbers, but the numbers do not have any mathematical meaning. In other words, the order of the numbers does not matter.

## Ordinal Variable

In research, an ordinal variable is a variable that is used to rank items. They are the groups that are arranged in a particular order. Ordinal variables are often used in surveys.

## Example of Ordinal Variable

Extraneous variable.

Extraneous variables are factors that affect the dependent variable but were not originally considered by the researcher while designing the experiment. These unexpected variables can alter the outcomes of a study or how a researcher perceives the results.

## Example of Extraneous Variable

Latent variable.

A latent variable is a variable that is not directly observed but is instead inferred from other variables that are observed.

## Example of Latent Variable

Confounding variable.

A variable in your experiment that conceals the true influence of another variable. This can occur when another variable is strongly related to a variable of interest but is not controlled in your experiment.

## Example of Confounding Variable

1- Suppose there is an association between smoking and lung cancer. If age is a confounder, then this means that older people are more likely to get lung cancer, but they are also more likely to smoke. Therefore, the true association between smoking and lung cancer may be underestimated if age is not taken into account.

## Composite Variable

Example of composite variable.

A composite variable could be created by combining the variables “height” and “weight” to create the variable “BMI.”

## Other articles

Methodology

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- How it works

## Types of Variables – A Comprehensive Guide

Published by Carmen Troy at August 14th, 2021 , Revised On October 26, 2023

A variable is any qualitative or quantitative characteristic that can change and have more than one value, such as age, height, weight, gender, etc.

Before conducting research, it’s essential to know what needs to be measured or analysed and choose a suitable statistical test to present your study’s findings.

In most cases, you can do it by identifying the key issues/variables related to your research’s main topic.

Example: If you want to test whether the hybridisation of plants harms the health of people. You can use the key variables like agricultural techniques, type of soil, environmental factors, types of pesticides used, the process of hybridisation, type of yield obtained after hybridisation, type of yield without hybridisation, etc.

Variables are broadly categorised into:

- Independent variables
- Dependent variable
- Control variable

## IMAGES

## VIDEO

## COMMENTS

1 Chapter 5: Variables and measurement IN research. 2 Dependent Variables Dependent/response variable: a variable that is measured or observed from an individual. Reliability: the degree to which the results of a study can be replicated under similar conditions. Operational definition: the definition of an abstract concept used by a researcher ...

Presentation Transcript. Quantitative Research Methodology Session 2 Variables, Population, and Sampling. Variable A characteristic that varies • Independent Variable "the factor that is measured, manipulated, or selected by the experimenter to determine its relationship with an observed phenomenon" (Tuckman, 1999, p.93) Variable (2) 2.

Research Questions, Variables, and Hypotheses: Part 1 PHC 6700/RCS 6740 2/14/06 Happy Valentine's Day!

DeCarlo and his team developed a complete package of materials that includes a textbook, ancillary materials, and a student workbook as part of a VIVA Open Course Grant. The PowerPoint slides associated with the twelve lessons of the course, SOWK 621.01: Research I: Basic Research Methodology, as previously taught by Dr. Matthew DeCarlo at ...

A COURSE IN RESEARCH METHODOLOGY 2018.pptx. Naimi AMARA. This teaching paper is an introdcution to the field of research methodology as it enables beginners (students) to understand basic things about research, research techniques , research design and research procedure. The general aim behind this teaching paper is to facilitate the task of ...

New York: Prentice-Hall, 1960. Download ppt "Lecture Notes on Research Methodology". 1 Research Methodology: An Introduction: MEANING OF RESEARCH: Research in common parlance refers to a search for knowledge. Once can also define research as a scientific & systematic search for pertinent information on a specific topic.

Categorical Variable. This is a variable that can take on a limited number of values or categories. Categorical variables can be nominal or ordinal. Nominal variables have no inherent order, while ordinal variables have a natural order. Examples of categorical variables include gender, race, and educational level.

Presentation on theme: "RESEARCH METHODS Lecture 5. CONCEPTS AND VARIABLES."— ... 1 RESEARCH METHODS Lecture 5 2 CONCEPTS AND VARIABLES 3 Concept Things we observe Observable realities physical or abstract For purposes of identification of a reality we try to give a name to it. By using name we communicate with others. ... Download ppt ...

Presentation Transcript. Research Variables. Research Definitions • An experiment is a process in which an investigator devises two or more different experiences (treatments) for subjects or participants. • Involves a control group and one or more treatment groups. Research Variables • Independent Variable (IV): the controlled variable in ...

Research can be defined as the search for knowledge, or as any systematic investigation, with an open mind, to establish novel facts, solve new or existing problems, prove new ideas, or develop new theories, usually using a scientific method. Egesa Romans. According to Mugenda & Mugenda (2010), research is process of carrying out a diligent ...

Organization is an entity. Name, Size, Type, Learning, Innovation are the attributes of an organization. So all these attributes are the variables. 2- Other example is that Employee is also an entity. Name, Age, Gender, Experience, Stress level, satisfaction, Performance are the attributes of an employee.

You can use the key variables like agricultural techniques, type of soil, environmental factors, types of pesticides used, the process of hybridisation, type of yield obtained after hybridisation, type of yield without hybridisation, etc. Variables are broadly categorised into: Independent Vs. Dependent Vs.

Examples. Discrete variables (aka integer variables) Counts of individual items or values. Number of students in a class. Number of different tree species in a forest. Continuous variables (aka ratio variables) Measurements of continuous or non-finite values. Distance.

Download ppt "Research Methodology Lecture No : 10 (Measurement of Variables/Scales)" Recap Measurement is necessary to give answers or to the research question , or to test our hypotheses. The opeationalizing of certain subjective variables are necessary for measurement. The abstract concepts are broken down to dimensions and its elements.

Template 13: Graph of Primary Research Methodology PPT Template. Experience the power of data-driven insights with this professional and appealing PPT template. Designed for primary research, this template offers a comprehensive framework that includes field trials, observations, interviews, focus groups, and surveys.