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Chapter 3 Dissertation

How to Write Chapter 5 Dissertation?| A Beginner’s Guide

Writing a dissertation is a major undertaking. It requires countless hours of research, writing, and editing. One of the most important chapters in your dissertation is Chapter 4. This chapter should provide a detailed explanation of your methodology, results, and analysis.

Here, we'll provide an overview of the chapter 4 dissertation, how to structure it properly, and tips for writing it effectively. Read on to learn more!

Skimming through these dissertations, you can also check out how to craft Chapter 4 and what to discuss.

Example: 1   The Importance of Health and Safety in Construction Industry

Example:2   influence of different socio-physical attributes on individual’s weight.

Keep going through till the end to have a complete idea of how to compose a well-written and structured chapter 4 dissertation.

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What is chapter 4.

In an academic dissertation, chapter 4 is the data analysis chapter—the heart of the research project. That is where you will present the results of your research and analyze them in light of existing literature. In other words, this is where you will explain why your findings are significant and what they mean for the field as a whole.

Structure of Chapter 4

The structure of your chapter 4 should depend on the type of data that you collected during your research process. However, several key elements should be included in chapter 4:

• An introduction that explains the aims and objectives of this chapter.
• A detailed description of the approaches utilized to collect and analyze data.
• Results from both qualitative and quantitative analyses.
• Discussion about the implications for future research; and
• Conclusions about your findings as well as potential limitations or challenges faced in completing this research project.

Keep in mind that these are just general guidelines—your specific dissertation may require additional sections based on its own individual requirements. It's always best to check with your professor before starting work on any section of your dissertation. 

Writing an Effective Chapter 4 Dissertation

i.  Outline Your Goals & Objectives

Before you begin writing this chapter, it's important to think about the goals and objectives you want to achieve with it.

• What are the main points you want to make?
• What do you expect your readers to understand after they've read this chapter?

Having clear goals and objectives before you start writing will help ensure that your chapter is focused and organized.

ii.  Explain Your Methodology

When it comes time to discuss your methodology in Chapter 4, include all relevant details about the methods you used during your research process.

It should include information about what kind of data or materials were collected, how they were analyzed, and why those particular methods were chosen for the study.

It's also important to explain any limitations or challenges encountered during data collection so that readers can fully understand the process.

iii.  Discuss Results & Analysis

In Chapter 4 dissertation, it's also essential to discuss the results of your research and any analysis conducted on those results.

It should include detailed descriptions of any patterns or trends in the data collected as well as a discussion on how those patterns or trends may relate to the existing literature in the field or could potentially lead to further research questions in the future.

Make sure that all data presented here is accurate and reliable; If any differences exist between what was anticipated and what was observed, note them here as well.

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Tips for writing your chapter 4.

Here are some suggestions to make the writing process simpler if you have a clear grasp of what should be in your chapter 4;

• Take notes throughout your entire research process so that it's easier for you to compile all relevant information into one cohesive document later on.
• Utilize headings to make it easier for readers to follow along with your arguments.
• Ensure all references are correctly cited using an accepted academic style such as APA, MLA or Harvard.
• Use diagrams or graphs when necessary to visually demonstrate key points or trends among variables.
• Always proofread and edit carefully before submitting each section, so the content is free from errors or inconsistencies.

Writing a dissertation can seem overwhelming at first glance, but with some guidance, knowledge, and practice, it can become much more manageable. This guide provides an overview of everything you need to know about chapter 4 to write an effective dissertation.

Be sure not to forget to discuss both the methodology used during research and any results or analysis obtained from research; these are both integral components of this section that must not be overlooked if an effective Chapter 4 is desired.

To gain more information and academic assistance, check out the following resources:

• How To Write a Report Introduction: A Step-By-Step Guide
• How To Write a Conclusion Good Paragraph: Examples and strategies for an effective conclusion
• Mastering the Art of Academic Writing: Tips and Tricks on How to Write Academically?

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Best Practice: How to Write a Dissertation or Thesis Quantitative Chapter 4

Statistics Blog

In the first paragraph of your quantitative chapter 4, the results chapter, restate the research questions that will be examined.  This reminds the reader of what you’re going to investigate after having been trough the details of your methodology.  It’s helpful too that the reader knows what the variables are that are going to be analyzed.

Spend a paragraph telling the reader how you’re going to clean the data.  Did you remove univariate or multivariate outlier?  How are you going to treat missing data? What is your final sample size?

The next paragraph should describe the sample using demographics and research variables.  Provide frequencies and percentages for nominal and ordinal level variables and means and standard deviations for the scale level variables.  You can provide this information in figures and tables.

Here’s a sample:

Frequencies and Percentages.  The most frequently observed category of Cardio was Yes ( n  = 41, 72%). The most frequently observed category of Shock was No ( n  = 34, 60%). Frequencies and percentages are presented.

Summary Statistics.  The observations for MiniCog had an average of 25.49 ( SD  = 14.01,  SE M  = 1.87, Min = 2.00, Max = 55.00). The observations for Digital had an average of 29.12 ( SD  = 10.03,  SE M  = 1.33, Min = 15.50, Max = 48.50). Skewness and kurtosis were also calculated. When the skewness is greater than 2 in absolute value, the variable is considered to be asymmetrical about its mean. When the kurtosis is greater than or equal to 3, then the variable’s distribution is markedly different than a normal distribution in its tendency to produce outliers (Westfall & Henning, 2013).

Now that the data is clean and descriptives have been conducted, turn to conducting the statistics and assumptions of those statistics for research question 1.  Provide the assumptions first, then the results of the statistics.  Have a clear accept or reject of the hypothesis statement if you have one.  Here’s an independent samples t-test example:

Introduction.  An two-tailed independent samples  t -test was conducted to examine whether the mean of MiniCog was significantly different between the No and Yes categories of Cardio.

Assumptions.  The assumptions of normality and homogeneity of variance were assessed.

Normality.  A Shapiro-Wilk test was conducted to determine whether MiniCog could have been produced by a normal distribution (Razali & Wah, 2011). The results of the Shapiro-Wilk test were significant,  W  = 0.94,  p  = .007. These results suggest that MiniCog is unlikely to have been produced by a normal distribution; thus normality cannot be assumed. However, the mean of any random variable will be approximately normally distributed as sample size increases according to the Central Limit Theorem (CLT). Therefore, with a sufficiently large sample size ( n  > 50), deviations from normality will have little effect on the results (Stevens, 2009). An alternative way to test the assumption of normality was utilized by plotting the quantiles of the model residuals against the quantiles of a Chi-square distribution, also called a Q-Q scatterplot (DeCarlo, 1997). For the assumption of normality to be met, the quantiles of the residuals must not strongly deviate from the theoretical quantiles. Strong deviations could indicate that the parameter estimates are unreliable. Figure 1 presents a Q-Q scatterplot of MiniCog.

Homogeneity of variance.  Levene’s test for equality of variance was used to assess whether the homogeneity of variance assumption was met (Levene, 1960). The homogeneity of variance assumption requires the variance of the dependent variable be approximately equal in each group. The result of Levene’s test was significant,  F (1, 54) = 18.30,  p  < .001, indicating that the assumption of homogeneity of variance was violated. Consequently, the results may not be reliable or generalizable. Since equal variances cannot be assumed, Welch’s t-test was used instead of the Student’s t-test, which is more reliable when the two samples have unequal variances and unequal sample sizes (Ruxton, 2006).

Results.  The result of the two-tailed independent samples  t -test was significant,  t (46.88) = -4.81,  p  < .001, indicating the null hypothesis can be rejected. This finding suggests the mean of MiniCog was significantly different between the No and Yes categories of Cardio. The mean of MiniCog in the No category of Cardio was significantly lower than the mean of MiniCog in the Yes category. Present the results of the two-tailed independent samples  t -test, and present the means of MiniCog(No) and MiniCog(Yes).

In the next paragraphs, conduct stats and assumptions for your other research questions.  Again, assumptions first, then the results of the statistics with appropriate tables and figures.

Be sure to add all of the in-text citations to your reference section.  Here is a sample of references.

Conover, W. J., & Iman, R. L. (1981). Rank transformations as a bridge between parametric and nonparametric statistics.  The American Statistician, 35 (3), 124-129.

DeCarlo, L. T. (1997). On the meaning and use of kurtosis.  Psychological Methods,  2(3), 292-307.

Levene, H. (1960). Contributions to Probability and Statistics.  Essays in honor of Harold Hotelling,  I. Olkin et al. eds., Stanford University Press, 278-292.

Razali, N. M., & Wah, Y. B. (2011). Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests.  Journal of Statistical Modeling and Analytics, 2 (1), 21-33.

Ruxton, G. D. (2006). The unequal variance t-test is an underused alternative to Student’s t-test and the Mann-Whitney U test.  Behavioral Ecology, 17 (4), 688-690.

Intellectus Statistics [Online computer software]. (2019). Retrieved from  https://analyze.intellectusstatistics.com/

Stevens, J. P. (2009).  Applied multivariate statistics for the social sciences  (5th ed.). Mahwah, NJ: Routledge Academic.

Westfall, P. H., & Henning, K. S. S. (2013).  Texts in statistical science: Understanding advanced statistical methods.  Boca Raton, FL: Taylor & Francis.

Dissertation Chapter 4: How To Write Your Results Chapter

The results chapter , or dissertation chapter 4, is an integral part of any dissertation research.  The professionals at Statistics Solutions have assisted thousands of doctoral candidates with their dissertation results chapter.

The results chapter of your dissertation is one of the most important components of your study, where the accurate statistical analysis must be performed, assumptions examined, and findings reported and clearly explained.  Once you conduct your analyses, you have to present your results in a way that shows clear support or non-support of your hypotheses.  Statistical expertise is needed to effectively present the results and defend your findings.

Discover How We Assist to Edit Your Dissertation Chapters

Aligning theoretical framework, gathering articles, synthesizing gaps, articulating a clear methodology and data plan, and writing about the theoretical and practical implications of your research are part of our comprehensive dissertation editing services.

• Bring dissertation editing expertise to chapters 1-5 in timely manner.
• Track all changes, then work with you to bring about scholarly writing.
• Ongoing support to address committee feedback, reducing revisions.

Statistics Solutions can assist you with your dissertation chapter 4 in the following ways:

Data Management

• Enter, code and clean data: The first step in creating a results chapter is to import your data from Excel to SPSS.  (We also use stat-transfer if the data is in another form).  Once the data is in SPSS, the variables must be labeled and the levels of the variables assigned (e.g., male=1, female=2).  The data cleaning typically entails screening the variables for both univariate and multivariate outliers, normality, addressing missing values, and assessing for linearity.

Statistical Analysis

• Statistical analysis: The actual analyses takes many forms.  Most, if not all, dissertation results chapters include descriptive statistics of the demographic variables (means, standard deviation, frequencies and percentages), as well as the reliabilities of any composite scores.  The analyses should then be focused on addressing the research hypotheses by assessing, addressing and reporting of the assumptions of the particular analysis, and then the conducting and reporting of the relevant statistical output in the results chapter.
• Write results: The results chapter should be presented logically.   First the descriptives and then the results of the analyses that address the hypotheses.  The tables and figures must be in APA 6th edition.  The results chapter should flow smoothly, where the reader does not have to stop to question why an analysis was conducted.  There is an old saying that “hard writing makes for easy reading”–you want the committee to have a very easy time reading your results chapter.

Understanding Your Results

• Explain statistics: You must be able to defend every word of the results chapter.  At Statistics Solutions, we are teachers as well as statisticians and methodologists.  We make sure you completely understand what was conducted, why it was conducted, and the implications of the results.

Presenting Your Results

• Create APA-style tables and figures:  Tables and figures can be a stumbling block for graduate students and is especially important when formulating the results chapter.  APA 6th edition has changed their format a bit from the 5th edition, and Statistics Solutions will make sure it is correct.  For example, there is a greater emphasis on reporting confidence intervals and the regression tables have been substantially modified.
• Dissertation editing:  While the results chapter should be edited properly, we can edit your entire dissertation for both APA and for basic English grammar, style, paragraphing, and punctuation.
• At Statistics Solutions, we use of SPSS, SAS , LISREL, M-Plus, AMOS, statistical packages, and NVIVO for qualitative data.

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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21 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.

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• How to Write a Discussion Section | Tips & Examples

How to Write a Discussion Section | Tips & Examples

Published on August 21, 2022 by Shona McCombes . Revised on July 18, 2023.

The discussion section is where you delve into the meaning, importance, and relevance of your results .

It should focus on explaining and evaluating what you found, showing how it relates to your literature review and paper or dissertation topic , and making an argument in support of your overall conclusion. It should not be a second results section.

There are different ways to write this section, but you can focus your writing around these key elements:

• Summary : A brief recap of your key results
• Interpretations: What do your results mean?
• Implications: Why do your results matter?
• Limitations: What can’t your results tell us?
• Recommendations: Avenues for further studies or analyses

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Table of contents

What not to include in your discussion section, step 1: summarize your key findings, step 2: give your interpretations, step 3: discuss the implications, step 4: acknowledge the limitations, step 5: share your recommendations, discussion section example, other interesting articles, frequently asked questions about discussion sections.

There are a few common mistakes to avoid when writing the discussion section of your paper.

• Don’t introduce new results: You should only discuss the data that you have already reported in your results section .
• Don’t make inflated claims: Avoid overinterpretation and speculation that isn’t directly supported by your data.
• Don’t undermine your research: The discussion of limitations should aim to strengthen your credibility, not emphasize weaknesses or failures.

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Start this section by reiterating your research problem and concisely summarizing your major findings. To speed up the process you can use a summarizer to quickly get an overview of all important findings. Don’t just repeat all the data you have already reported—aim for a clear statement of the overall result that directly answers your main research question . This should be no more than one paragraph.

Many students struggle with the differences between a discussion section and a results section . The crux of the matter is that your results sections should present your results, and your discussion section should subjectively evaluate them. Try not to blend elements of these two sections, in order to keep your paper sharp.

• The results indicate that…
• The study demonstrates a correlation between…
• This analysis supports the theory that…
• The data suggest that…

The meaning of your results may seem obvious to you, but it’s important to spell out their significance for your reader, showing exactly how they answer your research question.

The form of your interpretations will depend on the type of research, but some typical approaches to interpreting the data include:

• Identifying correlations , patterns, and relationships among the data
• Discussing whether the results met your expectations or supported your hypotheses
• Contextualizing your findings within previous research and theory
• Explaining unexpected results and evaluating their significance
• Considering possible alternative explanations and making an argument for your position

You can organize your discussion around key themes, hypotheses, or research questions, following the same structure as your results section. Alternatively, you can also begin by highlighting the most significant or unexpected results.

• In line with the hypothesis…
• Contrary to the hypothesized association…
• The results contradict the claims of Smith (2022) that…
• The results might suggest that x . However, based on the findings of similar studies, a more plausible explanation is y .

As well as giving your own interpretations, make sure to relate your results back to the scholarly work that you surveyed in the literature review . The discussion should show how your findings fit with existing knowledge, what new insights they contribute, and what consequences they have for theory or practice.

Ask yourself these questions:

• Do your results support or challenge existing theories? If they support existing theories, what new information do they contribute? If they challenge existing theories, why do you think that is?
• Are there any practical implications?

Your overall aim is to show the reader exactly what your research has contributed, and why they should care.

• These results build on existing evidence of…
• The results do not fit with the theory that…
• The experiment provides a new insight into the relationship between…
• These results should be taken into account when considering how to…
• The data contribute a clearer understanding of…
• While previous research has focused on  x , these results demonstrate that y .

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Even the best research has its limitations. Acknowledging these is important to demonstrate your credibility. Limitations aren’t about listing your errors, but about providing an accurate picture of what can and cannot be concluded from your study.

Limitations might be due to your overall research design, specific methodological choices , or unanticipated obstacles that emerged during your research process.

Here are a few common possibilities:

• If your sample size was small or limited to a specific group of people, explain how generalizability is limited.
• If you encountered problems when gathering or analyzing data, explain how these influenced the results.
• If there are potential confounding variables that you were unable to control, acknowledge the effect these may have had.

After noting the limitations, you can reiterate why the results are nonetheless valid for the purpose of answering your research question.

• The generalizability of the results is limited by…
• The reliability of these data is impacted by…
• Due to the lack of data on x , the results cannot confirm…
• The methodological choices were constrained by…
• It is beyond the scope of this study to…

Based on the discussion of your results, you can make recommendations for practical implementation or further research. Sometimes, the recommendations are saved for the conclusion .

Suggestions for further research can lead directly from the limitations. Don’t just state that more studies should be done—give concrete ideas for how future work can build on areas that your own research was unable to address.

• Further research is needed to establish…
• Future studies should take into account…
• Avenues for future research include…

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!

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In the discussion , you explore the meaning and relevance of your research results , explaining how they fit with existing research and theory. Discuss:

• Your  interpretations : what do the results tell us?
• The  implications : why do the results matter?
• The  limitation s : what can’t the results tell us?

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.

In a thesis or dissertation, the discussion is an in-depth exploration of the results, going into detail about the meaning of your findings and citing relevant sources to put them in context.

The conclusion is more shorter and more general: it concisely answers your main research question and makes recommendations based on your overall findings.

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Analysis and Coding Example: Qualitative Data

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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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