chapter 4 of research paper

Research Guide

Chapter 4 research writing, 4.1 structure.

In this section, I focus on the main stages of the research writing process. Most of these concepts have been beautifully explained by Varanya Chaubey (2018) .We will be focusing on the book, but in this section, I compile some of the most interesting ideas and link them to other important aspects to consider when structuring an argument. Some of this material is structured with more detail on Laura Belcher’s book Writing your Journal Article in Twelve Weeks .

4.2 The Three Layer Method

Once we have found our research question and we obtained and processed the data we need to conduct our analysis, we need to write our results.

This method asks us to work from the general ideas to the details, using a descending structure , or a Three layer method .

This method is a 3-step process in which we start working by laying a foundation of the main project and build upon it. The concept is simple: we need to understand what we are doing, why and how before even immersing in the writing process. Otherwise, we will lose sight of the main objective. The process is straightforward and quite intuitive. I introduce the three stages of the process here and explain each of them below.

• Step 1: What are you saying?: This is the main argument that you are making. It is important to figure out if you actually have an argument. But I’ll come back to this point.
• Step 2: Express with an outline. You need to include additional information surrounding your argument, so the readers can answer follow-up questions and have additional details linked to your research question.
• Step 3: Develop your ideas in a draft. Once you have identified your main argument and have an outline, you need to structure the paragraphs in each section.

4.2.1 The Argument

Belcher (2019) defines an argument as: “your article’s most important idea sated in one or two sentences early and clearly in your article […], emerging from a theory and supported with evidence to convince the reader of its validity.”

This may sound trivial, but it is harder than it seems. Many times, we believe we already have an argument, but we really do not. Instead, we have sentences that are tautological or we are simply rephrasing a fact that is accepted by everyone. Therefore, Belcher proposes a set of tests to ensure that you actually have an argument (I am adapting the list for the purposes of this Guide):

Agree/disagree : Do we need evidence to agree or disagree with a particular statement? For instance, we do not need further evidence to the statement ‘The Earth is round’. But we may need evidence on the statement “Prep school is fundamental to children’s cognitive development.”

Dispute test : When a given statement can be the source of disagreement, then it seems that you may indeed have an argument. For instance, “Poorer people are less supportive of redistribution” (AEP, 2021)

Puzzle answer test : If your statement is providing a response to a question that people have about the world or their environment, you may have an argument.

Another important element is to differentiate your argument from your topic. The topic is the major issue you are interested in, whereas your argument explains the main finding (or initially, the hypothesis) of your paper.

Following the research question, an argument needs to be puzzling. It needs to provide relevant information that help us understand the world a little bit more. This is why your argument (as well as your research question) needs to go beyond the basic facts. It needs to provide enough detail as to make it interesting for a larger audience. This also entails that you need to provide more information than naming the main variables in your analysis (x causes Y). You need to specify the conditions and context that make this statement to hold.

Some other elements to consider when structuring your argument is to avoid including normative statements and speculations, More specifically, for quantitative papers:

Avoid including causal claims when the evidence does not allow you to do that . Causal analysis is key in our field, but correlations are important as well and they provide a value to understand our context a little bit more.

4.2.1.1 Finding your RAP

R : Have different versions of your research question to see what is the clearest way to introduce it to your readers.

P : This represents how you position the paper in the literature. This is constructed based on your literature review and the theory behind your question.

These three elements are interconnected. You need to find the best way to bring them all together and work with them to convey your argument.

4.2.2 Express your Ideas using an Outline

An empirical, quantitative, paper in economics (and political science) usually contains the following sections:

• Introduction
• Context (Literature Review) 4a. Theoretical papers contain mathematical models (we will not use those) 4b. Empirical Strategy
• Robustness checks and potential mechanisms (we will not focus on those)
• Final discussion (Conclusion)

We will talk more about each of these sections, but here, the main point to consider is that you need to create an outline that conveys the most important points of each section.

This is, after you have a clear argument, now you need to provide an answer to different questions that the readers may have. This is done by creating the headings and subheadings of each section. For instance, in a paper on mining in the Democratic Republic of the Congo (DRC), readers may be interested in learning why is mining important in the country and what types of mining take place in the country. This means that I need a general section on the context of mining in the DRC and then include subheadings explaining the different types of mining that I analyze.

You will do that for each section. In your outline, include the headings and subheadings, and a short paragraph indicating the main message of the section. This will then be enriched by secondary paragraphs.

Having this structure will allow you to include those sections that add value to your final paper and remove any additional information that is not key to support your main argument.

4.2.2.1 Drafting

Once you have your headings and subheadings, as well as the most important takeaways, it is time for you to start populating your paper. In the next section, I mention some of the elements that you need to include in the research paper. Here again, it is important that you plan the information that you will include and that each paragraph has a purpose, answering a question that is relevant to further your argument. Go for the general to the particular details.

The main thing to consider is that readers have very limited time and span of attention. You need to convey the main message at the beginning of the paper. Then, for each section, the main idea needs to be included in the first paragraph(s). Develop just one idea per paragraph and ensure that the main message is contained at the beginning.

Writing is an iterative process and you probably will spend more time rewriting a section than what you spent writing it for the first time. Don’t despair! We all go through the same process and you will get there. Just ensure that you structure and organize your process.

How To Write The Results/Findings Chapter

For qualitative studies (dissertations & theses).

By: Jenna Crossley (PhD). Expert Reviewed By: Dr. Eunice Rautenbach | August 2021

So, you’ve collected and analysed your qualitative data, and it’s time to write up your results chapter. But where do you start? In this post, we’ll guide you through the qualitative results chapter (also called the findings chapter), step by step. 

Overview: Qualitative Results Chapter

• What (exactly) the qualitative results chapter is
• What to include in your results chapter
• How to write up your results chapter
• A few tips and tricks to help you along the way
• Free results chapter template

What exactly is the results chapter?

The results chapter in a dissertation or thesis (or any formal academic research piece) is where you objectively and neutrally present the findings of your qualitative analysis (or analyses if you used multiple qualitative analysis methods ). This chapter can sometimes be combined with the discussion chapter (where you interpret the data and discuss its meaning), depending on your university’s preference.  We’ll treat the two chapters as separate, as that’s the most common approach.

In contrast to a quantitative results chapter that presents numbers and statistics, a qualitative results chapter presents data primarily in the form of words . But this doesn’t mean that a qualitative study can’t have quantitative elements – you could, for example, present the number of times a theme or topic pops up in your data, depending on the analysis method(s) you adopt.

Adding a quantitative element to your study can add some rigour, which strengthens your results by providing more evidence for your claims. This is particularly common when using qualitative content analysis. Keep in mind though that qualitative research aims to achieve depth, richness and identify nuances , so don’t get tunnel vision by focusing on the numbers. They’re just cream on top in a qualitative analysis.

So, to recap, the results chapter is where you objectively present the findings of your analysis, without interpreting them (you’ll save that for the discussion chapter). With that out the way, let’s take a look at what you should include in your results chapter.

What should you include in the results chapter?

As we’ve mentioned, your qualitative results chapter should purely present and describe your results , not interpret them in relation to the existing literature or your research questions . Any speculations or discussion about the implications of your findings should be reserved for your discussion chapter.

In your results chapter, you’ll want to talk about your analysis findings and whether or not they support your hypotheses (if you have any). Naturally, the exact contents of your results chapter will depend on which qualitative analysis method (or methods) you use. For example, if you were to use thematic analysis, you’d detail the themes identified in your analysis, using extracts from the transcripts or text to support your claims.

While you do need to present your analysis findings in some detail, you should avoid dumping large amounts of raw data in this chapter. Instead, focus on presenting the key findings and using a handful of select quotes or text extracts to support each finding . The reams of data and analysis can be relegated to your appendices.

While it’s tempting to include every last detail you found in your qualitative analysis, it is important to make sure that you report only that which is relevant to your research aims, objectives and research questions .  Always keep these three components, as well as your hypotheses (if you have any) front of mind when writing the chapter and use them as a filter to decide what’s relevant and what’s not.

Need a helping hand?

How do I write the results chapter?

Now that we’ve covered the basics, it’s time to look at how to structure your chapter. Broadly speaking, the results chapter needs to contain three core components – the introduction, the body and the concluding summary. Let’s take a look at each of these.

Section 1: Introduction

The first step is to craft a brief introduction to the chapter. This intro is vital as it provides some context for your findings. In your introduction, you should begin by reiterating your problem statement and research questions and highlight the purpose of your research . Make sure that you spell this out for the reader so that the rest of your chapter is well contextualised.

The next step is to briefly outline the structure of your results chapter. In other words, explain what’s included in the chapter and what the reader can expect. In the results chapter, you want to tell a story that is coherent, flows logically, and is easy to follow , so make sure that you plan your structure out well and convey that structure (at a high level), so that your reader is well oriented.

The introduction section shouldn’t be lengthy. Two or three short paragraphs should be more than adequate. It is merely an introduction and overview, not a summary of the chapter.

Pro Tip – To help you structure your chapter, it can be useful to set up an initial draft with (sub)section headings so that you’re able to easily (re)arrange parts of your chapter. This will also help your reader to follow your results and give your chapter some coherence.  Be sure to use level-based heading styles (e.g. Heading 1, 2, 3 styles) to help the reader differentiate between levels visually. You can find these options in Word (example below).

Section 2: Body

Before we get started on what to include in the body of your chapter, it’s vital to remember that a results section should be completely objective and descriptive, not interpretive . So, be careful not to use words such as, “suggests” or “implies”, as these usually accompany some form of interpretation – that’s reserved for your discussion chapter.

The structure of your body section is very important , so make sure that you plan it out well. When planning out your qualitative results chapter, create sections and subsections so that you can maintain the flow of the story you’re trying to tell. Be sure to systematically and consistently describe each portion of results. Try to adopt a standardised structure for each portion so that you achieve a high level of consistency throughout the chapter.

For qualitative studies, results chapters tend to be structured according to themes , which makes it easier for readers to follow. However, keep in mind that not all results chapters have to be structured in this manner. For example, if you’re conducting a longitudinal study, you may want to structure your chapter chronologically. Similarly, you might structure this chapter based on your theoretical framework . The exact structure of your chapter will depend on the nature of your study , especially your research questions.

As you work through the body of your chapter, make sure that you use quotes to substantiate every one of your claims . You can present these quotes in italics to differentiate them from your own words. A general rule of thumb is to use at least two pieces of evidence per claim, and these should be linked directly to your data. Also, remember that you need to include all relevant results , not just the ones that support your assumptions or initial leanings.

In addition to including quotes, you can also link your claims to the data by using appendices , which you should reference throughout your text. When you reference, make sure that you include both the name/number of the appendix , as well as the line(s) from which you drew your data.

As referencing styles can vary greatly, be sure to look up the appendix referencing conventions of your university’s prescribed style (e.g. APA , Harvard, etc) and keep this consistent throughout your chapter.

Section 3: Concluding summary

The concluding summary is very important because it summarises your key findings and lays the foundation for the discussion chapter . Keep in mind that some readers may skip directly to this section (from the introduction section), so make sure that it can be read and understood well in isolation.

In this section, you need to remind the reader of the key findings. That is, the results that directly relate to your research questions and that you will build upon in your discussion chapter. Remember, your reader has digested a lot of information in this chapter, so you need to use this section to remind them of the most important takeaways.

Importantly, the concluding summary should not present any new information and should only describe what you’ve already presented in your chapter. Keep it concise – you’re not summarising the whole chapter, just the essentials.

Tips for writing an A-grade results chapter

Now that you’ve got a clear picture of what the qualitative results chapter is all about, here are some quick tips and reminders to help you craft a high-quality chapter:

• Your results chapter should be written in the past tense . You’ve done the work already, so you want to tell the reader what you found , not what you are currently finding .
• Make sure that you review your work multiple times and check that every claim is adequately backed up by evidence . Aim for at least two examples per claim, and make use of an appendix to reference these.
• When writing up your results, make sure that you stick to only what is relevant . Don’t waste time on data that are not relevant to your research objectives and research questions.
• Use headings and subheadings to create an intuitive, easy to follow piece of writing. Make use of Microsoft Word’s “heading styles” and be sure to use them consistently.
• When referring to numerical data, tables and figures can provide a useful visual aid. When using these, make sure that they can be read and understood independent of your body text (i.e. that they can stand-alone). To this end, use clear, concise labels for each of your tables or figures and make use of colours to code indicate differences or hierarchy.
• Similarly, when you’re writing up your chapter, it can be useful to highlight topics and themes in different colours . This can help you to differentiate between your data if you get a bit overwhelmed and will also help you to ensure that your results flow logically and coherently.

If you have any questions, leave a comment below and we’ll do our best to help. If you’d like 1-on-1 help with your results chapter (or any chapter of your dissertation or thesis), check out our private dissertation coaching service here or book a free initial consultation to discuss how we can help you.

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This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

22 Comments

This was extremely helpful. Thanks a lot guys

Hi, thanks for the great research support platform created by the gradcoach team!

I wanted to ask- While “suggests” or “implies” are interpretive terms, what terms could we use for the results chapter? Could you share some examples of descriptive terms?

I think that instead of saying, ‘The data suggested, or The data implied,’ you can say, ‘The Data showed or revealed, or illustrated or outlined’…If interview data, you may say Jane Doe illuminated or elaborated, or Jane Doe described… or Jane Doe expressed or stated.

I found this article very useful. Thank you very much for the outstanding work you are doing.

What if i have 3 different interviewees answering the same interview questions? Should i then present the results in form of the table with the division on the 3 perspectives or rather give a results in form of the text and highlight who said what?

I think this tabular representation of results is a great idea. I am doing it too along with the text. Thanks

That was helpful was struggling to separate the discussion from the findings

this was very useful, Thank you.

Very helpful, I am confident to write my results chapter now.

It is so helpful! It is a good job. Thank you very much!

Very useful, well explained. Many thanks.

Hello, I appreciate the way you provided a supportive comments about qualitative results presenting tips

I loved this! It explains everything needed, and it has helped me better organize my thoughts. What words should I not use while writing my results section, other than subjective ones.

Thanks a lot, it is really helpful

Thank you so much dear, i really appropriate your nice explanations about this.

Thank you so much for this! I was wondering if anyone could help with how to prproperly integrate quotations (Excerpts) from interviews in the finding chapter in a qualitative research. Please GradCoach, address this issue and provide examples.

what if I’m not doing any interviews myself and all the information is coming from case studies that have already done the research.

Very helpful thank you.

This was very helpful as I was wondering how to structure this part of my dissertation, to include the quotes… Thanks for this explanation

This is very helpful, thanks! I am required to write up my results chapters with the discussion in each of them – any tips and tricks for this strategy?

For qualitative studies, can the findings be structured according to the Research questions? Thank you.

Do I need to include literature/references in my findings chapter?

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Analysis and Coding Example: Qualitative Data

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Jump to DSE Guide

The following is an example of how to engage in a three step analytic process of coding, categorizing, and identifying themes within the data presented. Note that different researchers would come up with different results based on their specific research questions, literature review findings, and theoretical perspective.

There are many ways cited in the literature to analyze qualitative data. The specific analytic plan in this exercise involved a constant comparative (Glaser & Strauss, 1967) approach that included a three-step process of open coding, categorizing, and synthesizing themes. The constant comparative process involved thinking about how these comments were interrelated. Intertwined within this three step process, this example engages in content analysis techniques as described by Patton (1987) through which coherent and salient themes and patterns are identified throughout the data. This is reflected in the congruencies and incongruencies reflected in the memos and relational matrix.

Step 1: Open Coding

Codes for the qualitative data are created through a line by line analysis of the comments. Codes would be based on the research questions, literature review, and theoretical perspective articulated. Numbering the lines is helpful so that the researcher can make notes regarding which comments they might like to quote in their report.

It is also useful to include memos to remind yourself of what you were thinking and allow you to reflect on the initial interpretations as you engage in the next two analytic steps. In addition, memos will be a reminder of issues that need to be addressed if there is an opportunity for follow up data collection. This technique allows the researcher time to reflect on how his/her biases might affect the analysis. Using different colored text for memos makes it easy to differentiate thoughts from the data.

Many novice researchers forgo this step.  Rather, they move right into arranging the entire statements into the various categories that have been pre-identified. There are two problems with the process. First, since the categories have been listed open coding, it is unclear from where the categories have been derived. Rather, when a researcher uses the open coding process, he/she look at each line of text individually and without consideration for the others. This process of breaking the pieces down and then putting them back together through analysis ensures that the researcher consider all for the data equally and limits the bias that might introduced. In addition, if a researcher is coding interviews or other significant amounts of qualitative data it will likely become overwhelming as the researcher tries to organize and remember from which context each piece of data came.

Step 2: Categorizing

To categorize the codes developed in Step 1 , list the codes and group them by similarity.  Then, identify an appropriate label for each group. The following table reflects the result of this activity.

Step 3: Identification of Themes

In this step, review the categories as well as the memos to determine the themes that emerge.   In the discussion below, three themes emerged from the synthesis of the categories. Relevant quotes from the data are included that exemplify the essence of the themes.These can be used in the discussion of findings. The relational matrix demonstrates the pattern of thinking of the researcher as they engaged in this step in the analysis. This is similar to an axial coding strategy.

Note that this set of data is limited and leaves some questions in mind. In a well-developed study, this would just be a part of the data collected and there would be other data sets and/or opportunities to clarify/verify some of the interpretations made below.  In addition, since there is no literature review or theoretical statement, there are no reference points from which to draw interferences in the data. Some assumptions were made for the purposes of this demonstration in these areas.

T h eme 1:  Professional Standing

Individual participants have articulated issues related to their own professional position. They are concerned about what and when they will teach, their performance, and the respect/prestige that they have within the school. For example, they are concerned about both their physical environment and the steps that they have to take to ensure that they have the up to date tools that they need. They are also concerned that their efforts are being acknowledged, sometimes in relation to their peers and their beliefs that they are more effective.

Selected quotes:

• Some teachers are carrying the weight for other teachers. (demonstrates that they think that some of their peers are not qualified.)
• We need objective observations and feedback from the principal (demonstrates that they are looking for acknowledgement for their efforts.  Or this could be interpreted as a belief that their peers who are less qualified should be acknowledged).
• There is a lack of support for individual teachers

Theme 2:  Group Dynamics and Collegiality

Rationale: There are groups or clicks that have formed. This seems to be the basis for some of the conflict.  This conflict is closely related to the status and professional standing themes. This theme however, has more to do with the group issues while the first theme is an individual perspective. Some teachers and/or subjects are seen as more prestigious than others.  Some of this is related to longevity. This creates jealously and inhibits collegiality. This affects peer-interaction, instruction, and communication.

• Grade level teams work against each other rather than together.
• Each team of teachers has stereotypes about the other teams.
• There is a division between the old and new teachers

Theme 3:  Leadership Issues

Rationale: There seems to be a lack of leadership and shared understanding of the general direction in which the school will go. This is also reflected in a lack of two way communications.  There doesn’t seem to be information being offered by the leadership of the school, nor does there seem to be an opportunity for individuals to share their thoughts, let alone decision making. There seems to be a lack of intervention in the conflict from leadership.

• Decisions are made on inaccurate information.
• We need consistent decisions about school rules

Glaser, B.G., & Strauss, A.  (1967).   The discovery of grounded theory:  Strategies for qualitative research . Chicago, IL: Aldine.

Patton, M. Q.  (1987).   How to use qualitative methods in evaluation .  Newbury Park, CA:  Sage Publications.

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• Chapter Four: Quantitative Methods (Part 3 - Making Sense of Your Study)

After you have designed your study, collected your data, and analyzed it, you have to figure out what it means and communicate that to potential interested audiences. This section of the chapter is about how to make sense of your study, in terms of data interpretation, data write-up, and data presentation, as seen in the above diagram.

• Chapter One: Introduction
• Chapter Two: Understanding the distinctions among research methods
• Chapter Three: Ethical research, writing, and creative work
• Chapter Four: Quantitative Methods (Part 1)
• Chapter Four: Quantitative Methods (Part 2 - Doing Your Study)
• Chapter Five: Qualitative Methods (Part 1)
• Chapter Five: Qualitative Data (Part 2)
• Chapter Six: Critical / Rhetorical Methods (Part 1)
• Chapter Six: Critical / Rhetorical Methods (Part 2)
• Chapter Seven: Presenting Your Results

Data Interpretation

Once you have run your statistics, you have to figure out what your findings mean or interpret your data. To do this, you need to tie back your findings to your research questions and/or hypotheses, think about how your findings relate to what you discovered beforehand about the already existing literature, and determine how your findings take the literature or current theory in the field further. Your interpretation of the data you collected will be found in the last section of your paper, what is commonly called the "discussion" section.

Remember Your RQs/Hs

Your research questions and hypotheses, once developed, should guide your study throughout the research process. As you are choosing your research design, choosing how to operationalize your variables, and choosing/conducting your statistical tests, you should always keep your RQs and Hs in mind.

What were you wanting to discover by your study? What were you wanting to test? Make sure you answer these questions clearly for the reader of your study in both the results and discussion section of the paper. (Specific guidelines for these sections will be covered later in this chapter, including the common practice of placing the data as you present it with each research question in the results section.)

Tie Findings to Your Literature Review

As you have seen in chapter 3 and the Appendix, and will see in chapter 7, the literature review is what you use to set up your quantitative study and to show why there is a need for your study. It should start out broad, with the context for your study, and lead into showing what still needs to be known and studied about your topic area, justifying your focus in the study. It will be brought in again in the last section of the paper you write, i.e., the discussion section.

Your paper is like an hourglass – starting out broad and narrowing down in the middle with your actual study and findings, and then moving to broad implications for the larger context of your study near the end.

Think about Relationship of Findings to Theory

One of the things you will write about in your discussion or last section of your paper is the implications of what you found. These implications are both practical and theoretical. Practical implications are how the research can provide practical applications to real-world people and issues. Theoretical implications are how the research takes the current academic literature further, specifically, in relationship to theory-building.

Did any of the research you reviewed for your literature review mention a theory your findings could expand upon? If so, you should think about how your findings related to this theory. If not, then think about the theories you have already studied in your communication classes. Would any of them provide a possible explanation of what you found? Would your findings help expand that theory to a different context, the context you studied? Does a theory need to be developed in the area of your research? If so, then what aspects of that theory could your findings help explain?

Data Write-Up

All quantitative studies, when written, have four parts. The first part is the introduction and literature review, the second part is the methods section, the third section is the results or findings, and the fourth section is the discussion section. This portion of this chapter will explain what elements you will need to include in each of these sections.

Literature Review

The beginning of your paper and first few pages sets the tone for your study. It tells the reader what the context of your study is and what other people who are also interested in your topic have studied about your topic.

There are many ways to organize a literature review, as can be seen in the following website. Literature Reviews — The Writing Center at UNC-Chapel Hill

After you have done a thorough literature search on your topic, then you have to organize your literature into topics of some kind. Your main goal is to show what has been done and what still needs to be done, to show the need for your study, so at the end of each section of your literature review, you should identify what still needs to be known about that particular area.

For quantitative research, you should do your literature review before coming up with your research questions/hypotheses. Your questions and hypotheses should flow from the literature. This is different from the other two research methods discussed in this book, which do not rely so heavily on a literature review to situation the study before conducting it.

In the methods section, you should tell your reader how you conducted your study, from start to finish, explaining why you made the choices you did along the way. A reader should be able to replicate your study from the descriptions you provide in this section of your write-up. Common headings in the methods section include a description of the participants, procedures, and analysis.

Participants

For the participants' subheading of the methods section, you should minimally report the demographics of your sample in terms of biological sex (frequencies/percentages), age (range of ages and mean), and ethnicity (frequencies/percentages). If you collected data on other demographics, such as socioeconomic status, religious affiliation, type of occupation, etc., then you can report data for that also in the participants' sub-section.

For the procedures sub-section, you report everything you did to collect your data: how you recruited your participants, including what type of sampling you used (probability or non-probability) and informed consent procedures; how you operationalized your variables (including your survey questions, which often are explained in the methods section briefly while the whole survey can be found in an appendix of your paper); the validity and reliability of your survey instrument or methods you used; and what type of study design you had (experimental, quasi-experimental, or non-experimental). For each one of these design issues, in this sub-section of the methods part, you need to explain why you made the decisions you did in order to answer your research questions or test your hypotheses.

In this section, you explain how you converted your data for analysis and how you analyzed your data. You need to explain what statistics you chose to run for each of your research questions/hypotheses and why.

In this section of your paper, you organize the results by your research questions/hypotheses. For each research question/hypothesis, you should present any descriptive statistic results first and then your inferential statistics results. You do not make any interpretation of what your results mean or why you think you got the results you did. You merely report your results.

Reporting Significant Results

For each of the inferential statistics, there is a typical template you can follow when reporting significant results: reporting the test statistic value, the degrees of freedom  3 , and the probability level. Examples follow for each of the statistics we have talked about in this text.

T-test results

"T-tests results show there was a significant difference found between men and women on their levels of self-esteem,  t  (df) = t value,  p  < .05, with men's self-esteem being higher (or lower) (men's mean & standard deviation) than women's self-esteem (women's mean & standard deviation)."

ANOVA results

"ANOVA results indicate there was a significant difference found between [levels of independent variable] on [dependent variable],  F  (df) = F value,  p  < .05."

If doing a factorial ANOVA, you would report the above sentence for all of your independent variables (main effects), as well as for the interaction (interaction effect), with language something like: "ANOVA results indicate a significant main effect for [independent variable] on [dependent variable],  F  (df) = F value,  p  < .05. .... ANOVA results indicate a significant interaction effect between [independent variables] on [dependent variable],  F  (df) = F value,  p  < .05."

See example YouTube tutorial for writing up a two-way ANOVA at the following website.

Factorial Design (Part C): Writing Up Results

Chi-square results

For goodness of fit results, your write-up would look something like: "Using a chi-square goodness of fit test, there was a significant difference found between observed and expected values of [variable], χ2 (df) = chi-square value,  p  < .05." For test of independence results, it would like like: "Using a chi-square test of independence, there was a significant interaction between [your two variables], χ2 (df) = chi-square value,  p  < .05."

Correlation results

"Using Pearson's [or Spearman's] correlation coefficient, there was a significant relationship found between [two variables],  r  (df) = r value,  p  < .05." If there are a lot of significant correlation results, these results are often presented in a table form.

For more information on these types of tables, see the following website:  Correlation Tables .

Regression results

Reporting regression results is more complicated, but generally, you want to inform the reader about how much variance is accounted by the regression model, the significance level of the model, and the significance of the predictor variable. For example:

A regression analysis, predicting GPA scores from GRE scores, was statistically significant,  F (1,8) = 10.34,  p  < .05.

Coefficientsa

The regression equation is: Ŷ = .411 * .005X. For every one unit increase in GRE score, there is a corresponding increase in GPA of .005 (Walen-Frederick, n.d., p. 4).

For more write-up help on regression and other statistics, see the following website location:

Multiple Regression  (pp. 217-220)

Reporting Non-Significant Results

You can follow a similar template when reporting non-significant results for all of the above inferential statistics. It is the same as provided in the above examples, except the word "non-significant" replaces the word "significant," and the  p  values are adjusted to indicate  p > .05.

Many times readers of articles do not read the whole article, especially if they are afraid of the statistical sections. When this happens, they often read the discussion section, which makes this a very important section in your writing. You should include the following elements in your discussion section: (a) a summary of your findings, (b) implications, (c) limitations, and (d) future research ideas.

Summary of Findings

You should summarize the answers to your research questions or what you found when testing your hypotheses in this sub-section of the discussion section. You should not report any statistical data here, but just put your results into narrative form. What did you find out that you did not know before doing your study? Answer that question in this sub- section.

Implications

You need to indicate why your study was important, both theoretically and practically. For the theoretical implications, you should relate what you found to the already existing literature, as discussed earlier when the "hourglass" format was mentioned as a way of conceptualizing your whole paper. If your study added anything to the existing theory on a particular topic, you talk about this here as well.

For practical implications, you need to identify for the reader how this study can help people in their real-world experiences related to your topic. You do not want your study to just be important to academic researchers, but also to other professionals and persons interested in your topic.

Limitations

As you get through conducting your study, you are going to realize there are things you wish you had done differently. Rather than hide these things from the reader, it is better to forthrightly state these for the reader. Explain why your study is limited and what you wish you had done in this sub-section.

Future Research

The limitations sub-section usually is tied directly to the future research sub-section, as your limitations mean that future research should be done to deal with these limitations. There may also be other things that could be studied, however, as a result of what you have found. What would other people say are the "gaps" your study left unstudied on your topic? These should be identified, with some suggestions on how they might be studied.

Other Aspects of the Paper

There are other parts of the academic paper you should include in your final write-up. We have provided useful resources for you to consider when including these aspects as part of your paper. For an example paper that uses the required APA format for a research paper write-up, see the following source:  Varying Definitions of Online Communication .

Abstract & Titles.

Research Abstracts General Format

Tables, References, & Other Materials.

APA Tables and Figures 1 Reference List: Basic Rules

Data Presentation

You will probably be called upon to present your data in other venues besides in writing. Two of the most common venues are oral presentations such as in class or at conferences, and poster presentations, such as what you might find at conferences. You might also be called upon to not write an academic write-up of your study, but rather to provide an executive summary of the results of your study to the "powers that be," who do not have time to read more than 5 pages or so of a summary. There are good resources for doing all of these online, so we have provided these here.

Oral Presentations

Oral Presentations Delivering Presentations

Poster Presentations

Executive Summary

Executive Summaries Complete the Report Good & Poor Examples of Executive Summaries with the following link: http://unilearning.uow.edu.au/report/4bi1.html

Congratulations! You have learned a great deal about how to go about using quantitative methods for your future research projects. You have learned how to design a quantitative study, conduct a quantitative study, and write about a quantitative study. You have some good resources you can take with you when you leave this class. Now, you just have to apply what you have learned to projects that will come your way in the future.

Remember, just because you may not like one method the best does not mean you should not use it. Your research questions/hypotheses should ALWAYS drive your choice of which method you use. And remember also that you can do quantitative methods!

[NOTE: References are not provided for the websites cited in the text, even though if this was an actual research article, they would need to be cited.]

Baker, E., Baker, W., & Tedesco, J. C. (2007). Organizations respond to phishing: Exploring the public relations tackle box.  Communication Research Reports, 24  (4), 327-339.

Benoit, W. L., & Hansen, G. J. (2004). Presidential debate watching, issue knowledge, character evaluation, and vote choice.  Human Communication Research, 30  (1), 121-144.

Chatham, A. (1991).  Home vs. public schooling: What about relationships in adolescence? Doctoral dissertation, University of Oklahoma.

Cousineau, T. M., Rancourt, D., and Green, T. C. (2006). Web chatter before and after the women's health initiative results: A content analysis of on-line menopause message boards.  Journal of Health Communication, 11 (2), 133-147.

Derlega, V., Winstead, B. A., Mathews, A., and Braitman, A. L. (2008). Why does someone reveal highly personal information?: Attributions for and against self-disclosure in close relationships.  Communication Research Reports, 25 , 115-130.

Fischer, J., & Corcoran, K. (2007).  Measures for clinical practice and research: A sourcebook (volumes 1 & 2) . New York: Oxford University Press.

Guay, S., Boisvert, J.-M., & Freeston, M. H. (2003). Validity of three measures of communication for predicting relationship adjustment and stability among a sample of young couples.  Psychological Assessment , 15(3), 392-398.

Holbert, R. L., Tschida, D. A., Dixon, M., Cherry, K., Steuber, K., & Airne, D. (2005). The  West Wing  and depictions of the American Presidency: Expanding the domains of framing in political communication.  Communication Quarterly, 53  (4), 505-522.

Jensen, J. D. (2008). Scientific uncertainty in news coverage of cancer research: Effects of hedging on scientists' and journalists' credibility.  Human Communication Research, 34 , 347- 369.

Keyton, J. (2011).  Communicating research: Asking questions, finding answers . New York: McGraw Hill.

Lenhart, A., Ling, R., Campbell, S., & Purcell, K. (2010, Apr. 10).  Teens and mobile phones . Report from the Pew Internet and American Life Project, retrieved from  http://www.pewinternet.org/Reports/2010/Teens-and-Mobile-Phones.aspx .

Maddy, T. (2008).  Tests: A comprehensive reference for assessments in psychology, education, and business . Austin, TX: Pro-Ed.

McCollum Jr., J. F., & Bryant, J. (2003). Pacing in children's television programming.  Mass Communication and Society, 6  (2), 115-136.

Medved, C. E., Brogan, S. M., McClanahan, A. M., Morris, J. F., & Shepherd, G. J. (2006). Family and work socializing communication: Messages, gender, and ideological implications.  Journal of Family Communication, 6 (3), 161-180.

Moyer-Gusé, E., & Nabi, R. L. (2010). Explaining the effects of narrative in an entertainment television program: Overcoming resistance to persuasion.  Human Communication Research, 36 , 26-52.

Nabi, R. L. (2009). Cosmetic surgery makeover programs and intentions to undergo cosmetic enhancements: A consideration of three models of media effects.  Human Communication Research, 35 , 1-27.

Pearson, J. C., DeWitt, L., Child, J. T., Kahl Jr., D. H., and Dandamudi, V. (2007). Facing the fear: An analysis of speech-anxiety content in public-speaking textbooks.  Communication Research Reports, 24 (2), 159-168.

Rubin. R. B., Rubin, A. M., Graham, E., Perse, E. M., & Seibold, D. (2009).  Communication research measures II: A sourcebook . New York: Routledge.

Serota, K. B., Levine, T. R., and Boster, F. J. (2010). The prevalence of lying in America: Three studies of reported deception.  Human Communication Research, 36 , 1-24.

Sheldon, P. (2008). The relationship between unwillingness-to-communicate and students' facebook use.  Journal of Media Psychology, 20 (2), 67–75.

Trochim, W. M. K. (2006). Reliability and validity.  Research methods data base , retrieved from  http://www.socialresearchmethods.net/kb/relandval.php .

Walen-Frederick, H. (n.d.).  Help sheet for reading SPSS printouts . Retrieved from  http://www.scribd.com/doc/51982223/help-sheet-for-reading-spss-printouts .

Weaver, A. J., & Wilson, B. J. (2009). The role of graphic and sanitized violence in the enjoyment of television dramas.  Human Communication Research, 35 (3), 442-463.

Weber, K., Corrigan, M., Fornash, B., & Neupauer, N. C. (2003). The effect of interest on recall: An experiment.  Communication Research Reports, 20 (2), 116-123.

Witt, P. L., & Schrodt, P. (2006). The influence of instructional technology use and teacher immediacy on student affect for teacher and course.  Communication Reports, 19 (1), 1-15.

3 Degrees of freedom (df) relate to your sample size and to the number of groups being compared. SPSS always computes the df for your statistics. For more information on degrees of freedom, see the following web-based resources:  http://www.youtube.com/watch?v=wsvfasNpU2s  and  http://www.creative-wisdom.com/pub/df/index.htm .

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Chapter 4 – Data Analysis and Discussion (example)

Disclaimer: This is not a sample of our professional work. The paper has been produced by a student. You can view samples of our work here . Opinions, suggestions, recommendations and results in this piece are those of the author and should not be taken as our company views.

Type of Academic Paper – Dissertation Chapter

Academic Subject – Marketing

Word Count – 2964 words

Reliability Analysis

Before conducting any analysis on the data, all the data’s reliability was analyzed based on Cronbach’s Alpha value. The reliability analysis was performed on the complete data of the questionnaire. The reliability of the data was found to be (0.922), as shown in the results of the reliability analysis provided below in table 4.1. However, the complete results output of the reliability analysis is given in the appendix.

Reliability Analysis (N=200)

The Cronbach’s Alpha value between (0.7-1.0) is considered to have excellent reliability. The Cronbach’s Alpha value of the data was found to be (0.922); therefore, this indicated that the questionnaire data had excellent reliability. All of the 29 items of the questionnaire had excellent reliability, and if they are taken for further analysis, they can generate results with 92.2% reliability.

Frequency Distribution Analysis

First of all, the frequency distribution analysis was performed on the demographic variables using SPSS to identify the respondents’ demographic composition. Section 1 of the questionnaire had 5 demographic questions to identify; gender, age group, annual income, marital status, and education level of the research sample. The frequency distribution results shown in table 4.2 below indicated that there were 200 respondents in total, out of which 50% were male, and 50% were female. This shows that the research sample was free from gender-based biases as males and females had equal representation in the sample.

Moreover, the frequency distribution analysis suggested three age groups; ‘20-35’, ‘36-60’ and ‘Above 60’. 39% of the respondents belonged to the ‘20-35’ age group, while 56.5% of the respondents belonged to the ‘36-60’ age group and the remaining 4.5% belonged to the age group of ‘Above 60’.

Furthermore, the annual income level was divided into four categories. The income values were in GBP. It was found that 13% of the respondents had income ‘up to 30000’, 27% had income between ‘31000 to 50000’, 52.5% had income between ‘51000 to 100000’, and 7.5% had income ‘Above 100000’. This suggests that most of the respondents had an annual income between ‘31000 to 50000’ GBP.

The frequency distribution analysis indicated that 61% of respondents were single, while 39% were married, as indicated in table 4.2. This means that most of the respondents were single. Based on frequency distribution, it was also found that the education level of the respondents was analyzed using four categories of education level, namely; diploma, graduate, master, and doctorate. The results depicted that 37% of the respondents were diploma holders, 46% were graduates, 16% had master-level education, while only 2% had a doctorate. This suggests that most of the respondents were either graduate or diploma holders.

Frequency Distribution of the Demographic Characteristics of the respondents (N=200)

Multiple Regression Analysis

The hypotheses were tested using linear multiple regression analysis to determine which of the dependent variables had a significant positive effect on the customer loyalty of the five-star hotel brands. The results of the regression analysis are summarized in the following table 4.3. However, the complete SPSS output of the regression analysis is given in the appendix. Table 4.3

Multiple regression analysis showing the predictive values of dependent variables (Brand image, corporate identity, public relation, perceived quality, and trustworthiness) on customer loyalty (N=200)

Predictors: (Constant), Trustworthiness, Public Relation, Brand Image, Corporate Identity, Perceived Quality Dependent Variable: Customer Loyalty

The significance value (p-value) of ANOVA was found to be (0.000) as shown in the above

table, which was less than 0.05. This suggested that the model equation was significantly fitted

on the data. Moreover, the adjusted R-Square value was (0.897), which indicated that the model’s predictors explained 89.7% variation in customer loyalty.

Furthermore, the presence of the significant effect of the 5 predicting variables on customer loyalty was identified based on their sig. Values. The effect of a predicting variable is significant if its sig. Value is less than 0.05 or if its t-Statistics value is greater than 2. It was found that the variable ‘brand image’ had sig. Value (0.046), the variable ‘corporate identity had sig. Value (0.482), the variable ‘public relation’ had sig. Value (0.400), while the variable ‘perceived quality’ had sig. value (0.000), and the variable ‘trustworthiness’ had sig. value (0.652).

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Hypotheses Assessment

Based on the regression analysis, it was found that brand image and perceived quality have a significant positive effect on customer loyalty. In contrast, corporate identity, public relations, and trustworthiness have an insignificant effect on customer loyalty. Therefore the two hypotheses; H1 and H4 were accepted, however the three hypotheses; H2, H3, and H5 were rejected as indicated in table 4.4.

Hypothesis Assessment Summary Table (N=200)

The insignificant variables (corporate identity, public relation and trustworthiness) were excluded from equation 1. After excluding the insignificant variables from the model equation 1, the final equation becomes as follows;

Customer loyalty                 = α + 0.074 (Brand image) + 0.991 (Perceived quality) + €

The above equation suggests that a 1 unit increase in brand image is likely to result in 0.074 units increase customer loyalty. In comparison, 1 unit increase in perceived quality can result in 0.991 units increase in customer loyalty.

Cross Tabulation Analysis

To further explore the results, the demographic variables’ data were cross-tabulated against the respondents’ responses regarding customer loyalty using SPSS. In this regards the five demographic variables; gender, age group, annual income, marital status and education level were cross-tabulated against the five questions regarding customer loyalty to know the difference between the customer loyalty of five-star hotels of UK based on demographic differences. The results of the cross-tabulation analysis are given in the appendix. The results are graphically presented in bar charts too, which are also given in the appendix.

Cross Tabulation of Gender against Customer Loyalty

The gender was cross-tabulated against question 1 to 5 of the questionnaire to identify the gender differences between male and female respondents’ responses regarding customer loyalty of five-star hotels of the UK. The results indicated that out of 100 males, 57% were extremely agreed that they stay at one hotel, while out of 100 females, 80% were extremely agreed they stay at one hotel. This shows that in comparison with a male, females were more agreed that they stayed at one hotel and were found to be more loyal towards their respective hotel brands.

The cross-tabulation results further indicated that out of 100 males, 53% agreed that they always say positive things about their respective hotel brand to other people. In contrast, out of 100 females, 77% were extremely agreed. Based on the results, the females were found to be in more agreement than males that they always say positive things about their respective hotel brand to other people.

It was further found that out of 100 males, 53% were extremely agreed that they recommend their hotel brand to others, however, out of 100 females, 74% were extremely agreed to this statement. This result also suggested that females were more in agreement than males to recommend their hotel brand to others.

Moreover, it was found that out of 100 males, 54% were extremely agreed that they don’t seek alternative hotel brands, while out of 100 females, 79% were extremely agreed to this statement. This result also suggested that females were more agreed than males that they don’t seek alternative hotel brands, and so were found to be more loyal than males.

Furthermore, it was identified that out of 100 male respondents 56% were extremely agreed that they would continue to go to the same hotel irrespective of the prices, however out of 100 females 79% were extremely agreed. Based on this result, it was clear that females were more agreed than males that they would continue to go to the same hotel irrespective of the prices, so females were found to be more loyal than males.

After cross tabulating ‘gender’ against the response of the 5 questions regarding customer loyalty the females were found to be more loyal customers of the five-star hotel brands than males as they were found to be more in agreement than the man that they stay at one hotel, always say positive things about their hotel brand to other people, recommend their hotel brand to others, don’t seek alternative hotel brands and would continue to go to the same hotel irrespective of the prices.

Cross Tabulation of Age Group against Customer Loyalty

Afterward, the second demographic variable, ‘age groups’ was cross-tabulated against questions 1 to 5 of the questionnaire to identify the difference between the customer loyalty of customers of different age groups. The results indicated that out of 78 respondents between 20 to 35 years of age, 61.5% were extremely agreed that they stayed at one hotel. While out of 113 respondents who were between 36 to 60 years of age, 72.6% were extremely agreed that they always stay at one hotel. However, out of 9 respondents who were above 60 years of age, 77.8% agreed that they always stay at one hotel. This indicated that customers of 36-60 and above 60 age groups were more loyal to their hotel brands as they were keener to stay at a respective hotel brand.

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Cross Tabulation of Annual Income against Customer Loyalty

The third demographic variable, ‘annual income’ was cross-tabulated against questions 1 to 5 of the questionnaire to identify which of the customers were most loyal based on their respective annual income levels. The results indicated that out of 26 respondents who had annual income up to 30000 GBP, 84.6% were extremely agreed that they always stay at one hotel. However, out of 54 respondents who had annual income from 31000 to 50000 GBP, 98.1% agreed that they always stay at one hotel. Although out of 105 respondents had annual income from 50000 to 100000 GBP, 49.5% were extremely agreed that they always stay at one hotel. While out of 10 respondents who had annual income from 50000 to 1000000 GBP, 66.7% agreed that they always stay at one hotel. This indicated that customers of annual income levels from 31000 to 50000 GBP were more loyal to their hotel brands than the customers having other annual income levels.

Cross Tabulation of Marital Status against Customer Loyalty

Furthermore, the fourth demographic variable the ‘marital status’ was cross-tabulated against questions 1 to 5 of the questionnaire to understand the difference between married and unmarried respondents regarding customer loyalty of five-star hotels of the UK. The cross-tabulation analysis results indicated that out of 122 single respondents, 59.8% were extremely agreed that they stay at one hotel. However, out of 78 married respondents, around 82% of respondents agreed that they stay at one hotel. Thus, the married customers were more loyal to their hotel brands than unmarried customers because, in comparison, married customers prefer to stay at one hotel brand.

To proceed with the cross-tabulation results, out of 122 single respondents, 55.7% were extremely agreed upon always saying positive things about their hotel brands to other people. On the other hand, out of 78 married respondents, 79.5% were extremely agreed. Hence, upon evaluating the results, it can be said that married customers have more customer loyalty as they are in more agreement than singles. They always give positive feedback regarding their respective hotel brand to other people.

Cross Tabulation of Education Level against Customer Loyalty

Subsequently, the fifth demographic variable, ‘education level’ was cross-tabulated against questions 1 to 5 of the questionnaire to identify which of the customers were most loyal based on their respective education levels. The results indicated that out of 50 respondents who were diploma holders, 67.6% were extremely agreed that they always stay at one hotel. While out of 64 respondents who were graduates, 69.6% were extremely agreed that they always stay at one hotel. Although out of 22 respondents who were masters, 68.8% were extremely agreed that they always stay at one hotel. However, out of 2 respondents with doctorates, 50% were extremely agreed to always stay at one hotel. This indicated that customers who were graduates were more loyal than the customers with diplomas, masters, or doctorates.

Moreover, 66.2% of the diploma holders were extremely agreed that they always say positive things about their hotel brand to other people. In comparison, 64.1% of the respondents who were graduates were extremely agreed. However, 65.5% of the respondents who had masters were extremely agreed, and 50% of the respondents who had doctorates agreed with the statement. Based on this result customers having masters were the most loyal customers of their respective five-star hotel brands.

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In this subsection, the findings of this study are compared and contrasted with the literature to identify which of the past research supports the present research findings. This present study based on regression analysis suggested that brand image can have a significant positive effect on the customer loyalty of five-star hotels in the UK. This finding was supported by the research of Heung et al. (1996), who also suggested that the hotel’s brand image can play a vital role in preserving a high ratio of customer loyalty.

Moreover, this present study also suggested that perceived quality was the second factor that was found to have a significant positive effect on customer loyalty. The perceived quality was evaluated based on; service quality, comfort, staff courtesy, customer satisfaction, and service quality expectations. In this regard, Tat and Raymond (2000) research supports the findings of this study. The staff service quality was found to affect customer loyalty and the level of satisfaction. Teas (1994) had also found service quality to affect customer loyalty. However, Teas also found that staff empathy (staff courtesy) towards customers can also affect customer loyalty. The research of Rowley and Dawes (1999) also supports the finding of this present study. The users’ expectations about the quality and nature of the services affect customer loyalty. A study by Oberoi and Hales (1990) was found to agree with the present study’s findings, as they had found the quality of staff service to affect customer loyalty.

Summary of the Findings

• The brand image was found to have a significant positive effect on customer loyalty. Therefore customer loyalty is likely to increase with the increase in brand image.
• The corporate identity was found to have an insignificant effect on customer loyalty. Therefore customer loyalty is not likely to increase with the increase in corporate identity.
• Public relations was found to have an insignificant effect on customer loyalty. Therefore customer loyalty is not likely to increase with the increase in public relations.
• Perceived quality was found to have a significant positive effect on customer loyalty. Therefore customer loyalty is likely to increase with the increase in perceived quality.
• Trustworthiness was found to have an insignificant effect on customer loyalty. Therefore customer loyalty is not likely to increase with the increase in trustworthiness.
• The female customers were found to be more loyal customers of the five-star hotel brands than male customers.
• The customers of age from 36 to 60 years were more loyal to their hotel brands than the customers of age from 20 to 35 and above 60.
• The customers who had annual income from 31000 to 50000 were more loyal customers of their respective hotel brands than those who had an annual income level of less than 31000 or more than 50000.
• The married respondents had more customer loyalty than unmarried customers, towards five-star hotel brands of the UK.

The customers who had bachelor degrees and the customers who had master degrees were more loyal to the customers who had a diploma or doctorate.

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How to write the results chapter of a dissertation.

To write the Results chapter of a dissertation:

• Present findings objectively.
• Use tables, graphs, or charts for clarity.
• Refer to research questions/hypotheses.
• Provide sufficient details.
• Avoid interpretation; save that for the Discussion chapter.

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• How to Write a Results Section | Tips & Examples

How to Write a Results Section | Tips & Examples

Published on August 30, 2022 by Tegan George . Revised on July 18, 2023.

A results section is where you report the main findings of the data collection and analysis you conducted for your thesis or dissertation . You should report all relevant results concisely and objectively, in a logical order. Don’t include subjective interpretations of why you found these results or what they mean—any evaluation should be saved for the discussion section .

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Table of contents

How to write a results section, reporting quantitative research results, reporting qualitative research results, results vs. discussion vs. conclusion, checklist: research results, other interesting articles, frequently asked questions about results sections.

When conducting research, it’s important to report the results of your study prior to discussing your interpretations of it. This gives your reader a clear idea of exactly what you found and keeps the data itself separate from your subjective analysis.

Here are a few best practices:

• Your results should always be written in the past tense.
• While the length of this section depends on how much data you collected and analyzed, it should be written as concisely as possible.
• Only include results that are directly relevant to answering your research questions . Avoid speculative or interpretative words like “appears” or “implies.”
• If you have other results you’d like to include, consider adding them to an appendix or footnotes.
• Always start out with your broadest results first, and then flow into your more granular (but still relevant) ones. Think of it like a shoe store: first discuss the shoes as a whole, then the sneakers, boots, sandals, etc.

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If you conducted quantitative research , you’ll likely be working with the results of some sort of statistical analysis .

Your results section should report the results of any statistical tests you used to compare groups or assess relationships between variables . It should also state whether or not each hypothesis was supported.

The most logical way to structure quantitative results is to frame them around your research questions or hypotheses. For each question or hypothesis, share:

• A reminder of the type of analysis you used (e.g., a two-sample t test or simple linear regression ). A more detailed description of your analysis should go in your methodology section.
• A concise summary of each relevant result, both positive and negative. This can include any relevant descriptive statistics (e.g., means and standard deviations ) as well as inferential statistics (e.g., t scores, degrees of freedom , and p values ). Remember, these numbers are often placed in parentheses.
• A brief statement of how each result relates to the question, or whether the hypothesis was supported. You can briefly mention any results that didn’t fit with your expectations and assumptions, but save any speculation on their meaning or consequences for your discussion  and conclusion.

A note on tables and figures

In quantitative research, it’s often helpful to include visual elements such as graphs, charts, and tables , but only if they are directly relevant to your results. Give these elements clear, descriptive titles and labels so that your reader can easily understand what is being shown. If you want to include any other visual elements that are more tangential in nature, consider adding a figure and table list .

As a rule of thumb:

• Tables are used to communicate exact values, giving a concise overview of various results
• Graphs and charts are used to visualize trends and relationships, giving an at-a-glance illustration of key findings

Don’t forget to also mention any tables and figures you used within the text of your results section. Summarize or elaborate on specific aspects you think your reader should know about rather than merely restating the same numbers already shown.

A two-sample t test was used to test the hypothesis that higher social distance from environmental problems would reduce the intent to donate to environmental organizations, with donation intention (recorded as a score from 1 to 10) as the outcome variable and social distance (categorized as either a low or high level of social distance) as the predictor variable.Social distance was found to be positively correlated with donation intention, t (98) = 12.19, p < .001, with the donation intention of the high social distance group 0.28 points higher, on average, than the low social distance group (see figure 1). This contradicts the initial hypothesis that social distance would decrease donation intention, and in fact suggests a small effect in the opposite direction.

Figure 1: Intention to donate to environmental organizations based on social distance from impact of environmental damage.

In qualitative research , your results might not all be directly related to specific hypotheses. In this case, you can structure your results section around key themes or topics that emerged from your analysis of the data.

For each theme, start with general observations about what the data showed. You can mention:

• Recurring points of agreement or disagreement
• Patterns and trends
• Particularly significant snippets from individual responses

Next, clarify and support these points with direct quotations. Be sure to report any relevant demographic information about participants. Further information (such as full transcripts , if appropriate) can be included in an appendix .

When asked about video games as a form of art, the respondents tended to believe that video games themselves are not an art form, but agreed that creativity is involved in their production. The criteria used to identify artistic video games included design, story, music, and creative teams.One respondent (male, 24) noted a difference in creativity between popular video game genres:

“I think that in role-playing games, there’s more attention to character design, to world design, because the whole story is important and more attention is paid to certain game elements […] so that perhaps you do need bigger teams of creative experts than in an average shooter or something.”

Responses suggest that video game consumers consider some types of games to have more artistic potential than others.

Your results section should objectively report your findings, presenting only brief observations in relation to each question, hypothesis, or theme.

It should not  speculate about the meaning of the results or attempt to answer your main research question . Detailed interpretation of your results is more suitable for your discussion section , while synthesis of your results into an overall answer to your main research question is best left for your conclusion .

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I have completed my data collection and analyzed the results.

I have included all results that are relevant to my research questions.

I have concisely and objectively reported each result, including relevant descriptive statistics and inferential statistics .

I have stated whether each hypothesis was supported or refuted.

I have used tables and figures to illustrate my results where appropriate.

All tables and figures are correctly labelled and referred to in the text.

There is no subjective interpretation or speculation on the meaning of the results.

You've finished writing up your results! Use the other checklists to further improve your thesis.

If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

Research bias

• Survivorship bias
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The results chapter of a thesis or dissertation presents your research results concisely and objectively.

In quantitative research , for each question or hypothesis , state:

• The type of analysis used
• Relevant results in the form of descriptive and inferential statistics
• Whether or not the alternative hypothesis was supported

In qualitative research , for each question or theme, describe:

• Recurring patterns
• Significant or representative individual responses
• Relevant quotations from the data

Don’t interpret or speculate in the results chapter.

Results are usually written in the past tense , because they are describing the outcome of completed actions.

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

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Relativity of Education in Technology: Home Based Learning (HBL)

• First Online: 31 August 2024

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• K. P. Jaheer Mukthar 9 &
• Allam Hamdan 10  

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 538))

The present study explore the advantages of home-based learning, which include greater flexibility and cost-effectiveness. This article also look at the disadvantages of home-based learning, such as a lack of face-to-face interaction and the potential for distractions. Most professionals value the added flexibility that home-based learning offers. Not only can they access courses and materials at any time, but they can also tailor their learning to their individual needs and commitments. This makes home-based learning particularly suitable for those with busy professional lives, such as entrepreneurs, freelancers and remote workers.

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Mansor, A.N., Zabarani, N.H., Jamaludin, K.A., Nor, M.Y.M., Alias, B.S., Mansor, A.Z.: Home-based learning (HBL) teacher readiness scale: instrument development and demographic analysis. Sustainability, MDPI, 13 (4), 1–15 (2021)

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Hallgren, K., Paulsell, D., Del Grosso, P.: Better beginnings: developing home-based early learning systems in East Yakima and White Center. Mathematica Policy Research Reports 15e1e3f17e8647348b59140a4, Mathematica Policy Research (undated)

Sivasubramanian, K., Mukthar Kp, J., Raju, V., Srinivas, K.: The impact of digital learning management system on students of higher education institutions during covid-19 pandemic (2022). https://doi.org/10.1007/978-3-030-93921-2_34

Kuger, S., Marcus, J., Katharina Spiess, C.: Does quality of early childhood education and care affect the home learning environment of children? Discussion Papers of DIW Berlin 1687, DIW Berlin, German Institute for Economic Research (2017)

Blaskó, Z., da Costa, P., Schnepf, S.V.: Learning loss and educational inequalities in Europe: mapping the potential consequences of the COVID-19 crisis. IZA Discussion Papers 14298, Institute of Labor Economics (IZA) (2021)

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Cibi, A., Jaheer Mukthar, K.P., Hamdan, A. (2024). Relativity of Education in Technology: Home Based Learning (HBL). In: Hamdan, A., Harraf, A. (eds) Business Development via AI and Digitalization. Studies in Systems, Decision and Control, vol 538. Springer, Cham. https://doi.org/10.1007/978-3-031-62102-4_52

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Online Guide to Writing and Research

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• Online Guide to Writing

Planning and Writing a Research Paper

Collect Evidence

The evidence you collect will shape your research paper tremendously. You will have to decide what evidence is appropriate for your audience, purpose, and thesis. To help you make this decision, consider what kind of appeal you are making to your audience—logical, emotional, or ethical. Click on the tabs below for more information.

• LOGOS OR LOGICAL APPEAL
• PATHOS OR EMOTIONAL APPEAL
• ETHOS OR ETHICAL APPEAL

You appeal to the reader’s intellect through factual or objective evidence. 

You appeal to the reader’s feelings and their heart. 

You appeal to the reader’s sense of justice, fair play or trust.  The writer is seen to have authority regarding what they are writing about.  

EXAMPLE OF A RESEARCH QUESTION AND ARGUMENT

Here is an example that describes research evidence to support an observable trend; this collection of evidence appeals to the readers’ logic and intelligence.

Research Question:  What trends in research led to the computer industry segmentation that has occurred since the 1960s?

Argument Appealing to Logic and Intelligence:   You might learn from early research that the initial phase of the US space program generated much interest in robotics and in programmable machines. That interest led to government funding for research in these areas during the 1960s. This evidence might suggest to you that the government’s role in financing research was instrumental in nurturing the fledgling computer industry of the 1960s. At the same time, you might learn that the government came into conflict with proponents of the growing industry in the 1970s by attempting to curtail domination by a single manufacturer through enforcement of the Sherman Antitrust Act. This evidence, in turn, will help you write about and explain the industry segmentation that has occurred since the 1960s, with its attendant competitive emphasis on constant improvement and innovation, realized in paradigm shifts such as those that occur in object-oriented programming.  

Key Takeaways

• The evidence you collect will shape your research paper tremendously.
• To help you make this decision, consider what kind of appeal you are making to your audience—logical, emotional, or ethical. 

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Table of Contents: Online Guide to Writing

Chapter 1: College Writing

How Does College Writing Differ from Workplace Writing?

What Is College Writing?

Why So Much Emphasis on Writing?

Chapter 2: The Writing Process

Doing Exploratory Research

Getting from Notes to Your Draft

Introduction

Prewriting - Techniques to Get Started - Mining Your Intuition

Prewriting: Targeting Your Audience

Prewriting: Techniques to Get Started

Prewriting: Understanding Your Assignment

Rewriting: Being Your Own Critic

Rewriting: Creating a Revision Strategy

Rewriting: Getting Feedback

Rewriting: The Final Draft

Techniques to Get Started - Outlining

Techniques to Get Started - Using Systematic Techniques

Thesis Statement and Controlling Idea

Writing: Getting from Notes to Your Draft - Freewriting

Writing: Getting from Notes to Your Draft - Summarizing Your Ideas

Writing: Outlining What You Will Write

Chapter 3: Thinking Strategies

A Word About Style, Voice, and Tone

A Word About Style, Voice, and Tone: Style Through Vocabulary and Diction

Critical Strategies and Writing

Critical Strategies and Writing: Analysis

Critical Strategies and Writing: Evaluation

Critical Strategies and Writing: Persuasion

Critical Strategies and Writing: Synthesis

Developing a Paper Using Strategies

Kinds of Assignments You Will Write

Patterns for Presenting Information

Patterns for Presenting Information: Critiques

Patterns for Presenting Information: Discussing Raw Data

Patterns for Presenting Information: General-to-Specific Pattern

Patterns for Presenting Information: Problem-Cause-Solution Pattern

Patterns for Presenting Information: Specific-to-General Pattern

Patterns for Presenting Information: Summaries and Abstracts

Supporting with Research and Examples

Writing Essay Examinations

Writing Essay Examinations: Make Your Answer Relevant and Complete

Writing Essay Examinations: Organize Thinking Before Writing

Writing Essay Examinations: Read and Understand the Question

Chapter 4: The Research Process

Planning and Writing a Research Paper: Ask a Research Question

Planning and Writing a Research Paper: Cite Sources

Planning and Writing a Research Paper: Collect Evidence

Planning and Writing a Research Paper: Decide Your Point of View, or Role, for Your Research

Planning and Writing a Research Paper: Draw Conclusions

Planning and Writing a Research Paper: Find a Topic and Get an Overview

Planning and Writing a Research Paper: Manage Your Resources

Planning and Writing a Research Paper: Outline

Planning and Writing a Research Paper: Survey the Literature

Planning and Writing a Research Paper: Work Your Sources into Your Research Writing

Research Resources: Where Are Research Resources Found? - Human Resources

Research Resources: What Are Research Resources?

Research Resources: Where Are Research Resources Found?

Research Resources: Where Are Research Resources Found? - Electronic Resources

Research Resources: Where Are Research Resources Found? - Print Resources

Structuring the Research Paper: Formal Research Structure

Structuring the Research Paper: Informal Research Structure

The Nature of Research

The Research Assignment: How Should Research Sources Be Evaluated?

The Research Assignment: When Is Research Needed?

The Research Assignment: Why Perform Research?

Chapter 5: Academic Integrity

Academic Integrity

Giving Credit to Sources

Giving Credit to Sources: Copyright Laws

Giving Credit to Sources: Documentation

Giving Credit to Sources: Style Guides

Integrating Sources

Practicing Academic Integrity

Practicing Academic Integrity: Keeping Accurate Records

Practicing Academic Integrity: Managing Source Material

Practicing Academic Integrity: Managing Source Material - Paraphrasing Your Source

Practicing Academic Integrity: Managing Source Material - Quoting Your Source

Practicing Academic Integrity: Managing Source Material - Summarizing Your Sources

Types of Documentation

Types of Documentation: Bibliographies and Source Lists

Types of Documentation: Citing World Wide Web Sources

Types of Documentation: In-Text or Parenthetical Citations

Types of Documentation: In-Text or Parenthetical Citations - APA Style

Types of Documentation: In-Text or Parenthetical Citations - CSE/CBE Style

Types of Documentation: In-Text or Parenthetical Citations - Chicago Style

Types of Documentation: In-Text or Parenthetical Citations - MLA Style

Types of Documentation: Note Citations

Chapter 6: Using Library Resources

Finding Library Resources

Chapter 7: Assessing Your Writing

How Is Writing Graded?

How Is Writing Graded?: A General Assessment Tool

The Draft Stage

The Draft Stage: The First Draft

The Draft Stage: The Revision Process and the Final Draft

The Draft Stage: Using Feedback

The Research Stage

Using Assessment to Improve Your Writing

Chapter 8: Other Frequently Assigned Papers

Reviews and Reaction Papers: Article and Book Reviews

Reviews and Reaction Papers: Reaction Papers

Writing Arguments

Writing Arguments: Adapting the Argument Structure

Writing Arguments: Purposes of Argument

Writing Arguments: References to Consult for Writing Arguments

Writing Arguments: Steps to Writing an Argument - Anticipate Active Opposition

Writing Arguments: Steps to Writing an Argument - Determine Your Organization

Writing Arguments: Steps to Writing an Argument - Develop Your Argument

Writing Arguments: Steps to Writing an Argument - Introduce Your Argument

Writing Arguments: Steps to Writing an Argument - State Your Thesis or Proposition

Writing Arguments: Steps to Writing an Argument - Write Your Conclusion

Writing Arguments: Types of Argument

Appendix A: Books to Help Improve Your Writing

Dictionaries

General Style Manuals

Researching on the Internet

Special Style Manuals

Writing Handbooks

Appendix B: Collaborative Writing and Peer Reviewing

Collaborative Writing: Assignments to Accompany the Group Project

Collaborative Writing: Informal Progress Report

Collaborative Writing: Issues to Resolve

Collaborative Writing: Methodology

Collaborative Writing: Peer Evaluation

Collaborative Writing: Tasks of Collaborative Writing Group Members

Collaborative Writing: Writing Plan

General Introduction

Peer Reviewing

Appendix C: Developing an Improvement Plan

Working with Your Instructor’s Comments and Grades

Appendix D: Writing Plan and Project Schedule

Devising a Writing Project Plan and Schedule

Reviewing Your Plan with Others

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