results chapter dissertation example

How To Write The Results/Findings Chapter

For quantitative studies (dissertations & theses).

By: Derek Jansen (MBA). Expert Reviewed By: Kerryn Warren (PhD) | July 2021

So, you’ve completed your quantitative data analysis and it’s time to report on your findings. But where do you start? In this post, we’ll walk you through the results chapter (also called the findings or analysis chapter), step by step, so that you can craft this section of your dissertation or thesis with confidence. If you’re looking for information regarding the results chapter for qualitative studies, you can find that here .

Overview: Quantitative Results Chapter

• What exactly the results/findings/analysis chapter is
• What you need to include in your results chapter
• How to structure your results chapter
• A few tips and tricks for writing top-notch chapter

What exactly is the results chapter?

The results chapter (also referred to as the findings or analysis chapter) is one of the most important chapters of your dissertation or thesis because it shows the reader what you’ve found in terms of the quantitative data you’ve collected. It presents the data using a clear text narrative, supported by tables, graphs and charts. In doing so, it also highlights any potential issues (such as outliers or unusual findings) you’ve come across.

But how’s that different from the discussion chapter?

Well, in the results chapter, you only present your statistical findings. Only the numbers, so to speak – no more, no less. Contrasted to this, in the discussion chapter , you interpret your findings and link them to prior research (i.e. your literature review), as well as your research objectives and research questions . In other words, the results chapter presents and describes the data, while the discussion chapter interprets the data.

Let’s look at an example.

In your results chapter, you may have a plot that shows how respondents to a survey  responded: the numbers of respondents per category, for instance. You may also state whether this supports a hypothesis by using a p-value from a statistical test. But it is only in the discussion chapter where you will say why this is relevant or how it compares with the literature or the broader picture. So, in your results chapter, make sure that you don’t present anything other than the hard facts – this is not the place for subjectivity.

It’s worth mentioning that some universities prefer you to combine the results and discussion chapters. Even so, it is good practice to separate the results and discussion elements within the chapter, as this ensures your findings are fully described. Typically, though, the results and discussion chapters are split up in quantitative studies. If you’re unsure, chat with your research supervisor or chair to find out what their preference is.

What should you include in the results chapter?

Following your analysis, it’s likely you’ll have far more data than are necessary to include in your chapter. In all likelihood, you’ll have a mountain of SPSS or R output data, and it’s your job to decide what’s most relevant. You’ll need to cut through the noise and focus on the data that matters.

This doesn’t mean that those analyses were a waste of time – on the contrary, those analyses ensure that you have a good understanding of your dataset and how to interpret it. However, that doesn’t mean your reader or examiner needs to see the 165 histograms you created! Relevance is key.

How do I decide what’s relevant?

At this point, it can be difficult to strike a balance between what is and isn’t important. But the most important thing is to ensure your results reflect and align with the purpose of your study .  So, you need to revisit your research aims, objectives and research questions and use these as a litmus test for relevance. Make sure that you refer back to these constantly when writing up your chapter so that you stay on track.

As a general guide, your results chapter will typically include the following:

• Some demographic data about your sample
• Reliability tests (if you used measurement scales)
• Descriptive statistics
• Inferential statistics (if your research objectives and questions require these)
• Hypothesis tests (again, if your research objectives and questions require these)

We’ll discuss each of these points in more detail in the next section.

Importantly, your results chapter needs to lay the foundation for your discussion chapter . This means that, in your results chapter, you need to include all the data that you will use as the basis for your interpretation in the discussion chapter.

For example, if you plan to highlight the strong relationship between Variable X and Variable Y in your discussion chapter, you need to present the respective analysis in your results chapter – perhaps a correlation or regression analysis.

Need a helping hand?

How do I write the results chapter?

There are multiple steps involved in writing up the results chapter for your quantitative research. The exact number of steps applicable to you will vary from study to study and will depend on the nature of the research aims, objectives and research questions . However, we’ll outline the generic steps below.

Step 1 – Revisit your research questions

The first step in writing your results chapter is to revisit your research objectives and research questions . These will be (or at least, should be!) the driving force behind your results and discussion chapters, so you need to review them and then ask yourself which statistical analyses and tests (from your mountain of data) would specifically help you address these . For each research objective and research question, list the specific piece (or pieces) of analysis that address it.

At this stage, it’s also useful to think about the key points that you want to raise in your discussion chapter and note these down so that you have a clear reminder of which data points and analyses you want to highlight in the results chapter. Again, list your points and then list the specific piece of analysis that addresses each point. 

Next, you should draw up a rough outline of how you plan to structure your chapter . Which analyses and statistical tests will you present and in what order? We’ll discuss the “standard structure” in more detail later, but it’s worth mentioning now that it’s always useful to draw up a rough outline before you start writing (this advice applies to any chapter).

Step 2 – Craft an overview introduction

As with all chapters in your dissertation or thesis, you should start your quantitative results chapter by providing a brief overview of what you’ll do in the chapter and why . For example, you’d explain that you will start by presenting demographic data to understand the representativeness of the sample, before moving onto X, Y and Z.

This section shouldn’t be lengthy – a paragraph or two maximum. Also, it’s a good idea to weave the research questions into this section so that there’s a golden thread that runs through the document.

Step 3 – Present the sample demographic data

The first set of data that you’ll present is an overview of the sample demographics – in other words, the demographics of your respondents.

For example:

• What age range are they?
• How is gender distributed?
• How is ethnicity distributed?
• What areas do the participants live in?

The purpose of this is to assess how representative the sample is of the broader population. This is important for the sake of the generalisability of the results. If your sample is not representative of the population, you will not be able to generalise your findings. This is not necessarily the end of the world, but it is a limitation you’ll need to acknowledge.

Of course, to make this representativeness assessment, you’ll need to have a clear view of the demographics of the population. So, make sure that you design your survey to capture the correct demographic information that you will compare your sample to.

But what if I’m not interested in generalisability?

Well, even if your purpose is not necessarily to extrapolate your findings to the broader population, understanding your sample will allow you to interpret your findings appropriately, considering who responded. In other words, it will help you contextualise your findings . For example, if 80% of your sample was aged over 65, this may be a significant contextual factor to consider when interpreting the data. Therefore, it’s important to understand and present the demographic data.

 Step 4 – Review composite measures and the data “shape”.

Before you undertake any statistical analysis, you’ll need to do some checks to ensure that your data are suitable for the analysis methods and techniques you plan to use. If you try to analyse data that doesn’t meet the assumptions of a specific statistical technique, your results will be largely meaningless. Therefore, you may need to show that the methods and techniques you’ll use are “allowed”.

Most commonly, there are two areas you need to pay attention to:

#1: Composite measures

The first is when you have multiple scale-based measures that combine to capture one construct – this is called a composite measure .  For example, you may have four Likert scale-based measures that (should) all measure the same thing, but in different ways. In other words, in a survey, these four scales should all receive similar ratings. This is called “ internal consistency ”.

Internal consistency is not guaranteed though (especially if you developed the measures yourself), so you need to assess the reliability of each composite measure using a test. Typically, Cronbach’s Alpha is a common test used to assess internal consistency – i.e., to show that the items you’re combining are more or less saying the same thing. A high alpha score means that your measure is internally consistent. A low alpha score means you may need to consider scrapping one or more of the measures.

#2: Data shape

The second matter that you should address early on in your results chapter is data shape. In other words, you need to assess whether the data in your set are symmetrical (i.e. normally distributed) or not, as this will directly impact what type of analyses you can use. For many common inferential tests such as T-tests or ANOVAs (we’ll discuss these a bit later), your data needs to be normally distributed. If it’s not, you’ll need to adjust your strategy and use alternative tests.

To assess the shape of the data, you’ll usually assess a variety of descriptive statistics (such as the mean, median and skewness), which is what we’ll look at next.

Step 5 – Present the descriptive statistics

Now that you’ve laid the foundation by discussing the representativeness of your sample, as well as the reliability of your measures and the shape of your data, you can get started with the actual statistical analysis. The first step is to present the descriptive statistics for your variables.

For scaled data, this usually includes statistics such as:

• The mean – this is simply the mathematical average of a range of numbers.
• The median – this is the midpoint in a range of numbers when the numbers are arranged in order.
• The mode – this is the most commonly repeated number in the data set.
• Standard deviation – this metric indicates how dispersed a range of numbers is. In other words, how close all the numbers are to the mean (the average).
• Skewness – this indicates how symmetrical a range of numbers is. In other words, do they tend to cluster into a smooth bell curve shape in the middle of the graph (this is called a normal or parametric distribution), or do they lean to the left or right (this is called a non-normal or non-parametric distribution).
• Kurtosis – this metric indicates whether the data are heavily or lightly-tailed, relative to the normal distribution. In other words, how peaked or flat the distribution is.

A large table that indicates all the above for multiple variables can be a very effective way to present your data economically. You can also use colour coding to help make the data more easily digestible.

For categorical data, where you show the percentage of people who chose or fit into a category, for instance, you can either just plain describe the percentages or numbers of people who responded to something or use graphs and charts (such as bar graphs and pie charts) to present your data in this section of the chapter.

When using figures, make sure that you label them simply and clearly , so that your reader can easily understand them. There’s nothing more frustrating than a graph that’s missing axis labels! Keep in mind that although you’ll be presenting charts and graphs, your text content needs to present a clear narrative that can stand on its own. In other words, don’t rely purely on your figures and tables to convey your key points: highlight the crucial trends and values in the text. Figures and tables should complement the writing, not carry it .

Depending on your research aims, objectives and research questions, you may stop your analysis at this point (i.e. descriptive statistics). However, if your study requires inferential statistics, then it’s time to deep dive into those .

Step 6 – Present the inferential statistics

Inferential statistics are used to make generalisations about a population , whereas descriptive statistics focus purely on the sample . Inferential statistical techniques, broadly speaking, can be broken down into two groups .

First, there are those that compare measurements between groups , such as t-tests (which measure differences between two groups) and ANOVAs (which measure differences between multiple groups). Second, there are techniques that assess the relationships between variables , such as correlation analysis and regression analysis. Within each of these, some tests can be used for normally distributed (parametric) data and some tests are designed specifically for use on non-parametric data.

There are a seemingly endless number of tests that you can use to crunch your data, so it’s easy to run down a rabbit hole and end up with piles of test data. Ultimately, the most important thing is to make sure that you adopt the tests and techniques that allow you to achieve your research objectives and answer your research questions .

In this section of the results chapter, you should try to make use of figures and visual components as effectively as possible. For example, if you present a correlation table, use colour coding to highlight the significance of the correlation values, or scatterplots to visually demonstrate what the trend is. The easier you make it for your reader to digest your findings, the more effectively you’ll be able to make your arguments in the next chapter.

Step 7 – Test your hypotheses

If your study requires it, the next stage is hypothesis testing. A hypothesis is a statement , often indicating a difference between groups or relationship between variables, that can be supported or rejected by a statistical test. However, not all studies will involve hypotheses (again, it depends on the research objectives), so don’t feel like you “must” present and test hypotheses just because you’re undertaking quantitative research.

The basic process for hypothesis testing is as follows:

• Specify your null hypothesis (for example, “The chemical psilocybin has no effect on time perception).
• Specify your alternative hypothesis (e.g., “The chemical psilocybin has an effect on time perception)
• Set your significance level (this is usually 0.05)
• Calculate your statistics and find your p-value (e.g., p=0.01)
• Draw your conclusions (e.g., “The chemical psilocybin does have an effect on time perception”)

Finally, if the aim of your study is to develop and test a conceptual framework , this is the time to present it, following the testing of your hypotheses. While you don’t need to develop or discuss these findings further in the results chapter, indicating whether the tests (and their p-values) support or reject the hypotheses is crucial.

Step 8 – Provide a chapter summary

To wrap up your results chapter and transition to the discussion chapter, you should provide a brief summary of the key findings . “Brief” is the keyword here – much like the chapter introduction, this shouldn’t be lengthy – a paragraph or two maximum. Highlight the findings most relevant to your research objectives and research questions, and wrap it up.

Some final thoughts, tips and tricks

Now that you’ve got the essentials down, here are a few tips and tricks to make your quantitative results chapter shine:

• When writing your results chapter, report your findings in the past tense . You’re talking about what you’ve found in your data, not what you are currently looking for or trying to find.
• Structure your results chapter systematically and sequentially . If you had two experiments where findings from the one generated inputs into the other, report on them in order.
• Make your own tables and graphs rather than copying and pasting them from statistical analysis programmes like SPSS. Check out the DataIsBeautiful reddit for some inspiration.
• Once you’re done writing, review your work to make sure that you have provided enough information to answer your research questions , but also that you didn’t include superfluous information.

If you’ve got any questions about writing up the quantitative results chapter, please leave a comment below. If you’d like 1-on-1 assistance with your quantitative analysis and discussion, check out our hands-on coaching service , or book a free consultation with a friendly coach.

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How to Write the Dissertation Findings or Results – Steps & Tips

Published by Grace Graffin at August 11th, 2021 , Revised On October 9, 2023

Each  part of the dissertation is unique, and some general and specific rules must be followed. The dissertation’s findings section presents the key results of your research without interpreting their meaning .

Theoretically, this is an exciting section of a dissertation because it involves writing what you have observed and found. However, it can be a little tricky if there is too much information to confuse the readers.

The goal is to include only the essential and relevant findings in this section. The results must be presented in an orderly sequence to provide clarity to the readers.

This section of the dissertation should be easy for the readers to follow, so you should avoid going into a lengthy debate over the interpretation of the results.

It is vitally important to focus only on clear and precise observations. The findings chapter of the  dissertation  is theoretically the easiest to write.

It includes  statistical analysis and a brief write-up about whether or not the results emerging from the analysis are significant. This segment should be written in the past sentence as you describe what you have done in the past.

This article will provide detailed information about  how to   write the findings of a dissertation .

When to Write Dissertation Findings Chapter

As soon as you have gathered and analysed your data, you can start to write up the findings chapter of your dissertation paper. Remember that it is your chance to report the most notable findings of your research work and relate them to the research hypothesis  or  research questions set out in  the introduction chapter of the dissertation .

You will be required to separately report your study’s findings before moving on to the discussion chapter  if your dissertation is based on the  collection of primary data  or experimental work.

However, you may not be required to have an independent findings chapter if your dissertation is purely descriptive and focuses on the analysis of case studies or interpretation of texts.

• Always report the findings of your research in the past tense.
• The dissertation findings chapter varies from one project to another, depending on the data collected and analyzed.
• Avoid reporting results that are not relevant to your research questions or research hypothesis.

Does your Dissertation Have the Following?

• Great Research/Sources
• Perfect Language
• Accurate Sources

If not, we can help. Our panel of experts makes sure to keep the 3 pillars of the Dissertation strong.

1. Reporting Quantitative Findings

The best way to present your quantitative findings is to structure them around the research  hypothesis or  questions you intend to address as part of your dissertation project.

Report the relevant findings for each research question or hypothesis, focusing on how you analyzed them.

Analysis of your findings will help you determine how they relate to the different research questions and whether they support the hypothesis you formulated.

While you must highlight meaningful relationships, variances, and tendencies, it is important not to guess their interpretations and implications because this is something to save for the discussion  and  conclusion  chapters.

Any findings not directly relevant to your research questions or explanations concerning the data collection process  should be added to the dissertation paper’s appendix section.

Use of Figures and Tables in Dissertation Findings

Suppose your dissertation is based on quantitative research. In that case, it is important to include charts, graphs, tables, and other visual elements to help your readers understand the emerging trends and relationships in your findings.

Repeating information will give the impression that you are short on ideas. Refer to all charts, illustrations, and tables in your writing but avoid recurrence.

The text should be used only to elaborate and summarize certain parts of your results. On the other hand, illustrations and tables are used to present multifaceted data.

It is recommended to give descriptive labels and captions to all illustrations used so the readers can figure out what each refers to.

How to Report Quantitative Findings

Here is an example of how to report quantitative results in your dissertation findings chapter;

Two hundred seventeen participants completed both the pretest and post-test and a Pairwise T-test was used for the analysis. The quantitative data analysis reveals a statistically significant difference between the mean scores of the pretest and posttest scales from the Teachers Discovering Computers course. The pretest mean was 29.00 with a standard deviation of 7.65, while the posttest mean was 26.50 with a standard deviation of 9.74 (Table 1). These results yield a significance level of .000, indicating a strong treatment effect (see Table 3). With the correlation between the scores being .448, the little relationship is seen between the pretest and posttest scores (Table 2). This leads the researcher to conclude that the impact of the course on the educators’ perception and integration of technology into the curriculum is dramatic.

Paired Samples

Paired samples correlation, paired samples test.

Also Read: How to Write the Abstract for the Dissertation.

2. Reporting Qualitative Findings

A notable issue with reporting qualitative findings is that not all results directly relate to your research questions or hypothesis.

The best way to present the results of qualitative research is to frame your findings around the most critical areas or themes you obtained after you examined the data.

In-depth data analysis will help you observe what the data shows for each theme. Any developments, relationships, patterns, and independent responses directly relevant to your research question or hypothesis should be mentioned to the readers.

Additional information not directly relevant to your research can be included in the appendix .

How to Report Qualitative Findings

Here is an example of how to report qualitative results in your dissertation findings chapter;

How do I report quantitative findings?

The best way to present your quantitative findings is to structure them around the  research hypothesis  or  research questions  you intended to address as part of your dissertation project. Report the relevant findings for each of the research questions or hypotheses, focusing on how you analyzed them.

How do I report qualitative findings?

The best way to present the  qualitative research  results is to frame your findings around the most important areas or themes that you obtained after examining the data.

An in-depth analysis of the data will help you observe what the data is showing for each theme. Any developments, relationships, patterns, and independent responses that are directly relevant to your  research question  or  hypothesis  should be clearly mentioned for the readers.

Can I use interpretive phrases like ‘it confirms’ in the finding chapter?

No, It is highly advisable to avoid using interpretive and subjective phrases in the finding chapter. These terms are more suitable for the  discussion chapter , where you will be expected to provide your interpretation of the results in detail.

Can I report the results from other research papers in my findings chapter?

NO, you must not be presenting results from other research studies in your findings.

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How to Write an Impressive Thesis Results Section

After collecting and analyzing your research data, it’s time to write the results section. This article explains how to write and organize the thesis results section, the differences in reporting qualitative and quantitative data, the differences in the thesis results section across different fields, and the best practices for tables and figures.

What is the thesis results section?

The thesis results section factually and concisely describes what was observed and measured during the study but does not interpret the findings. It presents the findings in a logical order.

What should the thesis results section include?

• Include all relevant results as text, tables, or figures
• Report the results of subject recruitment and data collection
• For qualitative research, present the data from all statistical analyses, whether or not the results are significant
• For quantitative research, present the data by coding or categorizing themes and topics
• Present all secondary findings (e.g., subgroup analyses)
• Include all results, even if they do not fit in with your assumptions or support your hypothesis

What should the thesis results section not include?

• If the study involves the thematic analysis of an interview, don’t include complete transcripts of all interviews. Instead, add these as appendices
• Don’t present raw data. These may be included in appendices
• Don’t include background information (this should be in the introduction section )
• Don’t speculate on the meaning of results that do not support your hypothesis. This will be addressed later in the discussion and conclusion sections.
• Don’t repeat results that have been presented in tables and figures. Only highlight the pertinent points or elaborate on specific aspects

How should the thesis results section be organized?

The opening paragraph of the thesis results section should briefly restate the thesis question. Then, present the results objectively as text, figures, or tables.

Quantitative research presents the results from experiments and  statistical tests , usually in the form of tables and figures (graphs, diagrams, and images), with any pertinent findings emphasized in the text. The results are structured around the thesis question. Demographic data are usually presented first in this section.

For each statistical test used, the following information must be mentioned:

• The type of analysis used (e.g., Mann–Whitney U test or multiple regression analysis)
• A concise summary of each result, including  descriptive statistics   (e.g., means, medians, and modes) and  inferential statistics   (e.g., correlation, regression, and  p  values) and whether the results are significant
• Any trends or differences identified through comparisons
• How the findings relate to your research and if they support or contradict your hypothesis

Qualitative research   presents results around key themes or topics identified from your data analysis and explains how these themes evolved. The data are usually presented as text because it is hard to present the findings as figures.

For each theme presented, describe:

• General trends or patterns observed
• Significant or representative responses
• Relevant quotations from your study subjects

Relevant characteristics about your study subjects

Differences among the results section in different fields of research

Nevertheless, results should be presented logically across all disciplines and reflect the thesis question and any hypotheses that were tested.

The presentation of results varies considerably across disciplines. For example, a thesis documenting how a particular population interprets a specific event and a thesis investigating customer service may both have collected data using interviews and analyzed it using similar methods. Still, the presentation of the results will vastly differ because they are answering different thesis questions. A science thesis may have used experiments to generate data, and these would be presented differently again, probably involving statistics. Nevertheless, results should be presented logically across all disciplines and reflect the thesis question and any  hypotheses that were tested.

Differences between reporting thesis results in the Sciences and the Humanities and Social Sciences (HSS) domains

In the Sciences domain (qualitative and experimental research), the results and discussion sections are considered separate entities, and the results from experiments and statistical tests are presented. In the HSS domain (qualitative research), the results and discussion sections may be combined.

There are two approaches to presenting results in the HSS field:

• If you want to highlight important findings, first present a synopsis of the results and then explain the key findings.
• If you have multiple results of equal significance, present one result and explain it. Then present another result and explain that, and so on. Conclude with an overall synopsis.

Best practices for using tables and figures

The use of figures and tables is highly encouraged because they provide a standalone overview of the research findings that are much easier to understand than wading through dry text mentioning one result after another. The text in the results section should not repeat the information presented in figures and tables. Instead, it should focus on the pertinent findings or elaborate on specific points.

Some popular software programs that can be used for the analysis and presentation of statistical data include  Statistical Package for the Social Sciences (SPSS ) ,  R software ,  MATLAB , Microsoft Excel,  Statistical Analysis Software (SAS) ,  GraphPad Prism , and  Minitab .

The easiest way to construct tables is to use the  Table function in Microsoft Word . Microsoft Excel can also be used; however, Word is the easier option.

General guidelines for figures and tables

• Figures and tables must be interpretable independent from the text
• Number tables and figures consecutively (in separate lists) in the order in which they are mentioned in the text
• All tables and figures must be cited in the text
• Provide clear, descriptive titles for all figures and tables
• Include a legend to concisely describe what is presented in the figure or table

Figure guidelines

• Label figures so that the reader can easily understand what is being shown
• Use a consistent font type and font size for all labels in figure panels
• All abbreviations used in the figure artwork should be defined in the figure legend

Table guidelines

• All table columns should have a heading abbreviation used in tables should be defined in the table footnotes
• All numbers and text presented in tables must correlate with the data presented in the manuscript body

Quantitative results example : Figure 3 presents the characteristics of unemployed subjects and their rate of criminal convictions. A statistically significant association was observed between unemployed people <20 years old, the male sex, and no household income.

Qualitative results example: Table 5 shows the themes identified during the face-to-face interviews about the application that we developed to anonymously report corruption in the workplace. There was positive feedback on the app layout and ease of use. Concerns that emerged from the interviews included breaches of confidentiality and the inability to report incidents because of unstable cellphone network coverage.

Table 5. Themes and selected quotes from the evaluation of our app designed to anonymously report workplace corruption.

Tips for writing the thesis results section

• Do not state that a difference was present between the two groups unless this can be supported by a significant  p-value .
• Present the findings only . Do not comment or speculate on their interpretation.
• Every result included  must have a corresponding method in the methods section. Conversely, all methods  must have associated results presented in the results section.
• Do not explain commonly used methods. Instead, cite a reference.
• Be consistent with the units of measurement used in your thesis study. If you start with kg, then use the same unit all throughout your thesis. Also, be consistent with the capitalization of units of measurement. For example, use either “ml” or “mL” for milliliters, but not both.
• Never manipulate measurement outcomes, even if the result is unexpected. Remain objective.

Results vs. discussion vs. conclusion

Results are presented in three sections of your thesis: the results, discussion, and conclusion.

• In the results section, the data are presented simply and objectively. No speculation or interpretation is given.
• In the discussion section, the meaning of the results is interpreted and put into context (e.g., compared with other findings in the literature ), and its importance is assigned.
• In the conclusion section, the results and the main conclusions are summarized.

A thesis is the most crucial document that you will write during your academic studies. For professional thesis editing and thesis proofreading services , visit Enago Thesis Editing for more information.

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Review Checklist

Have you  completed all data collection procedures and analyzed all results ?

Have you  included all results relevant to your thesis question, even if they do not support your hypothesis?

Have you reported the results  objectively , with no interpretation or speculation?

For quantitative research, have you included both  descriptive and  inferential statistical results and stated whether they support or contradict your hypothesis?

Have you used  tables and figures to present all results?

In your thesis body, have you presented only the pertinent results and elaborated on specific aspects that were presented in the tables and figures?

Are all tables and figures  correctly labeled and cited in numerical order in the text?

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How to Write a Results Section for a Dissertation or Research Paper: Guide & Examples

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A results section is a crucial part of a research paper or dissertation, where you analyze your major findings. This section goes beyond simply presenting study outcomes. You should also include a comprehensive statistical analysis and interpret the collected data in detail.

Without dissertation research results, it is impossible to imagine a scientific work. Your task here is to present your study findings. What are qualitative or quantitative indicators? How to use tables and diagrams? How to describe data? Our article answers all these questions and many more. So, read further to discover how to analyze and describe your research indexes or contact or professionals for dissertation help from StudyCrumb.

What Is a Results Section of Dissertation?

The results section of a dissertation is a data statement from your research. Here you should present the main findings of your study to your readers. This section aims to show information objectively, systematically, concisely. It is allowed using text supplemented with illustrations.  In general, this section's length is not limited but should include all necessary data. Interpretations or conclusions should not be included in this section. Therefore, in theory, this is one of your shortest sections. But it can also be one of the most challenging sections.  The introduction presents a research topic and answers the question "why?". The Methods section explains the data collection process and answers "how?". Meanwhile, the result section shows actual data gained from experiments and tells "what?" Thus, this part plays a critical role in highlighting study's relevance. This chapter gives reader study relevance with novelty. So, you should figure out how to write it correctly. Here are main tasks that you should keep in mind while writing:

• Results answer the question "What was found in your research?"
• Results contain only your study's outcome. They do not include comments or interpretations.
• Results must always be presented accurately & objectively.
• Tables & figures are used to draw readers' attention. But the same data should never be presented in the form of a table and a figure. Don't repeat anything from a table also in text.

Dissertation: Results vs Discussion vs Conclusion

Results and discussion sections of a dissertation are often confused among researchers. Sometimes both these parts are mixed up with a conclusion for thesis . Figured out what is covered in each of these important chapters. Your readers should see that you notice how different they are. A clear understanding of differences will help you write your dissertation more effectively. 5 differences between Results VS Discussion VS Conclusion:

Wanna figure out the actual difference between discussion vs conclusion? Check out our helpful articles about Dissertation Discussion or Dissertation Conclusion.

Present Your Findings When Writing Results Section of Dissertation

Now it's time to understand how to arrange the results section of the dissertation. First, present most general findings, then narrow it down to a more specific one. Describe both qualitative & quantitative results. For example, imagine you are comparing the behavior of hamsters and mice. First, say a few words about the behavioral type of mammals that you studied. Then, mention rodents in general. At end, describe specific species of animals you carried out an experiment on.

Qualitative Results Section in Dissertation

In your dissertation results section, qualitative data may not be directly related to specific sub-questions or hypotheses. You can structure this chapter around main issues that arise when analyzing data. For each question, make a general observation of what data show. For example, you may recall recurring agreements or differences, patterns, trends. Personal answers are the basis of your research. Clarify and support these views with direct quotes. Add more information to the thesis appendix if it's needed.

Quantitative Results Section in a Dissertation

The easiest way to write a quantitative dissertation results section is to build it around a sub-question or hypothesis of your research. For each subquery, provide relevant results and include statistical analysis . Then briefly evaluate importance & reliability. Notice how each result relates to the problem or whether it supports the hypothesis. Focus on key trends, differences, and relationships between data. But don't speculate about their meaning or consequences. This should be put in the discussion vs conclusion section. Suppose your results are not directly related to answering your questions. Maybe there is additional information that helps readers understand how you collect data. In that case, you can include them in the appendix. It is often helpful to include visual elements such as graphs, charts, and tables. But only if they accurately support your results and add value.

Tables and Figures in Results Section in Dissertation

We recommend you use tables or figures in the dissertation results section correctly. Such interpretation can effectively present complex data concisely and visually. It allows readers to quickly gain a statistical overview. On the contrary, poorly designed graphs can confuse readers. That will reduce the effectiveness of your article.  Here are our recommendations that help you understand how to use tables and figures:

• Make sure tables and figures are self-explanatory. Sometimes, your readers may look at tables and figures before reading the entire text. So they should make sense as separate elements.
• Do not repeat the content of tables and figures in text. Text can be used to highlight key points from tables and figures. But do not repeat every element.
• Make sure that values ​​or information in tables and text are consistent. Make sure that abbreviations, group names, interpretations are the same as in text.
• Use clear, informative titles for tables and figures. Do not leave any table or figure without a title or legend. Otherwise, readers will not be able to understand data's meaning. Also, make sure column names, labels, figures are understandable.
• Check accuracy of data presented in tables and figures. Always double-check tables and figures to make sure numbers converge.
• Tables should not contain redundant information. Make sure tables in the article are not too crowded. If you need to provide extensive data, use Appendixes.
• Make sure images are clear. Make sure images and all parts of drawings are precise. Lettering should be in a standard font and legible against the background of the picture.
• Ask for permission to use illustrations. If you use illustrations, be sure to ask copyright holders and indicate them.

Tips on How to Write a Results Section

We have prepared several tips on how to write the results section of the dissertation!  Present data collected during study objectively, logically, and concisely. Highlight most important results and organize them into specific sections. It is an excellent way to show that you have covered all the descriptive information you need. Correct usage of visual elements effectively helps your readers with understanding. So, follow main 3 rules for writing this part:

• State only actual results. Leave explanations and comments for Discussion.
• Use text, tables, and pictures to orderly highlight key results.
• Make sure that contents of tables and figures are not repeated in text.

In case you have questions about a  conceptual framework in research , you will find a blog dedicated to this issue in our database.

What to Avoid When Writing the Results Section of a Dissertation

Here we will discuss how NOT to write the results section of a dissertation. Or simply, what points to avoid:

• Do not make your research too complicated. Your paper, tables, and graphs should be clearly marked and follow order. So that they can exist independently without further explanation.
• Do not include raw data. Remember, you are summarizing relevant results, not reporting them in detail. This chapter should briefly summarize your findings. Avoid complete introduction to each number and calculation.
• Do not contradict errors or false results. Explain these errors and contradictions in conclusions. This often happens when different research methods have been used.
• Do not write a conclusion or discussion. Instead, this part should contain summaries of findings.
• Do not tend to include explanations and inferences from results. Such an approach can make this chapter subjective, unclear, and confusing to the reader.
• Do not forget about novelty. Its lack is one of the main reasons for the paper's rejection.

Dissertation Results Section Example

Let's take a look at some good results section of dissertation examples. Remember that this part shows fundamental research you've done in detail. So, it has to be clear and concise, as you can see in the sample.

Final Thoughts on Writing Results Section of Dissertation

When writing a results section of a dissertation, highlight your achievements by data. The main chapter's task is to convince the reader of conclusions' validity of your research. You should not overload text with too detailed information. Never use words whose meanings you do not understand. Also, oversimplification may seem unconvincing for readers. But on the other hand, writing this part can even be fun. You can directly see your study results, which you'll interpret later. So keep going, and we wish you courage!

Writing any academic paper is long and thorough work. But StudyCrumb got you back! Our professional writers will deliver any type of work quickly and excellently! 

Joe Eckel is an expert on Dissertations writing. He makes sure that each student gets precious insights on composing A-grade academic writing.

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Writing your Dissertation:  Results and Discussion

When writing a dissertation or thesis, the results and discussion sections can be both the most interesting as well as the most challenging sections to write.

You may choose to write these sections separately, or combine them into a single chapter, depending on your university’s guidelines and your own preferences.

There are advantages to both approaches.

Writing the results and discussion as separate sections allows you to focus first on what results you obtained and set out clearly what happened in your experiments and/or investigations without worrying about their implications.This can focus your mind on what the results actually show and help you to sort them in your head.

However, many people find it easier to combine the results with their implications as the two are closely connected.

Check your university’s requirements carefully before combining the results and discussions sections as some specify that they must be kept separate.

Results Section

The Results section should set out your key experimental results, including any statistical analysis and whether or not the results of these are significant.

You should cover any literature supporting your interpretation of significance. It does not have to include everything you did, particularly for a doctorate dissertation. However, for an undergraduate or master's thesis, you will probably find that you need to include most of your work.

You should write your results section in the past tense: you are describing what you have done in the past.

Every result included MUST have a method set out in the methods section. Check back to make sure that you have included all the relevant methods.

Conversely, every method should also have some results given so, if you choose to exclude certain experiments from the results, make sure that you remove mention of the method as well.

If you are unsure whether to include certain results, go back to your research questions and decide whether the results are relevant to them. It doesn’t matter whether they are supportive or not, it’s about relevance. If they are relevant, you should include them.

Having decided what to include, next decide what order to use. You could choose chronological, which should follow the methods, or in order from most to least important in the answering of your research questions, or by research question and/or hypothesis.

You also need to consider how best to present your results: tables, figures, graphs, or text. Try to use a variety of different methods of presentation, and consider your reader: 20 pages of dense tables are hard to understand, as are five pages of graphs, but a single table and well-chosen graph that illustrate your overall findings will make things much clearer.

Make sure that each table and figure has a number and a title. Number tables and figures in separate lists, but consecutively by the order in which you mention them in the text. If you have more than about two or three, it’s often helpful to provide lists of tables and figures alongside the table of contents at the start of your dissertation.

Summarise your results in the text, drawing on the figures and tables to illustrate your points.

The text and figures should be complementary, not repeat the same information. You should refer to every table or figure in the text. Any that you don’t feel the need to refer to can safely be moved to an appendix, or even removed.

Make sure that you including information about the size and direction of any changes, including percentage change if appropriate. Statistical tests should include details of p values or confidence intervals and limits.

While you don’t need to include all your primary evidence in this section, you should as a matter of good practice make it available in an appendix, to which you should refer at the relevant point.

For example:

Details of all the interview participants can be found in Appendix A, with transcripts of each interview in Appendix B.

You will, almost inevitably, find that you need to include some slight discussion of your results during this section. This discussion should evaluate the quality of the results and their reliability, but not stray too far into discussion of how far your results support your hypothesis and/or answer your research questions, as that is for the discussion section.

See our pages: Analysing Qualitative Data and Simple Statistical Analysis for more information on analysing your results.

Discussion Section

This section has four purposes, it should:

• Interpret and explain your results
• Answer your research question
• Justify your approach
• Critically evaluate your study

The discussion section therefore needs to review your findings in the context of the literature and the existing knowledge about the subject.

You also need to demonstrate that you understand the limitations of your research and the implications of your findings for policy and practice. This section should be written in the present tense.

The Discussion section needs to follow from your results and relate back to your literature review . Make sure that everything you discuss is covered in the results section.

Some universities require a separate section on recommendations for policy and practice and/or for future research, while others allow you to include this in your discussion, so check the guidelines carefully.

Starting the Task

Most people are likely to write this section best by preparing an outline, setting out the broad thrust of the argument, and how your results support it.

You may find techniques like mind mapping are helpful in making a first outline; check out our page: Creative Thinking for some ideas about how to think through your ideas. You should start by referring back to your research questions, discuss your results, then set them into the context of the literature, and then into broader theory.

This is likely to be one of the longest sections of your dissertation, and it’s a good idea to break it down into chunks with sub-headings to help your reader to navigate through the detail.

Fleshing Out the Detail

Once you have your outline in front of you, you can start to map out how your results fit into the outline.

This will help you to see whether your results are over-focused in one area, which is why writing up your research as you go along can be a helpful process. For each theme or area, you should discuss how the results help to answer your research question, and whether the results are consistent with your expectations and the literature.

The Importance of Understanding Differences

If your results are controversial and/or unexpected, you should set them fully in context and explain why you think that you obtained them.

Your explanations may include issues such as a non-representative sample for convenience purposes, a response rate skewed towards those with a particular experience, or your own involvement as a participant for sociological research.

You do not need to be apologetic about these, because you made a choice about them, which you should have justified in the methodology section. However, you do need to evaluate your own results against others’ findings, especially if they are different. A full understanding of the limitations of your research is part of a good discussion section.

At this stage, you may want to revisit your literature review, unless you submitted it as a separate submission earlier, and revise it to draw out those studies which have proven more relevant.

Conclude by summarising the implications of your findings in brief, and explain why they are important for researchers and in practice, and provide some suggestions for further work.

You may also wish to make some recommendations for practice. As before, this may be a separate section, or included in your discussion.

The results and discussion, including conclusion and recommendations, are probably the most substantial sections of your dissertation. Once completed, you can begin to relax slightly: you are on to the last stages of writing!

Continue to: Dissertation: Conclusion and Extras Writing your Methodology

See also: Writing a Literature Review Writing a Research Proposal Academic Referencing What Is the Importance of Using a Plagiarism Checker to Check Your Thesis?

Welcome to Student Learning Te Taiako

Writing the results chapter.

The results section describes the data that you gathered and the outcomes of the analysis of that data.

In this section, you will typically find:

• graphs, tables, and charts supported by written descriptions and made identifiable by a title or legend ​
• key findings emphasized—qualitative research often includes historical sources or interview excerpts, while quantitative research will often include measurements or observations from experiments
• in-text citations are infrequent or absent.

This chapter of your thesis lays the foundations for your Discussion chapter where you can elaborate on the implications of your results for theory or practice in your discipline.

Presenting your data will involve making decisions about what is most important for your reader to understand about how you have addressed your research questions. Make decisions about what specific data to present in this section by thinking back to your research question or your research aims.

You might think of the metaphor of the carpenter who has more than enough wood to build with but will only succeed by selecting what is most suitable for the particular task:

“[Data] is a resource you can use to support the claims you want to make. Carpenters don’t try to use all the wood in the woodshed to make a particular table. They don’t see the variety of materials they have available as a problem to be solved... Think of the abundance of your data in the same way.” —from Inframethodology

Video resource

The video below details the features of a good results chapter and the process that goes into preparing it.

Library Guides

Dissertations 5: findings, analysis and discussion: home.

• Results/Findings

Alternative Structures

The time has come to show and discuss the findings of your research. How to structure this part of your dissertation? 

Dissertations can have different structures, as you can see in the dissertation  structure  guide.

Dissertations organised by sections

Many dissertations are organised by sections. In this case, we suggest three options. Note that, if within your course you have been instructed to use a specific structure, you should do that. Also note that sometimes there is considerable freedom on the structure, so you can come up with other structures too. 

A) More common for scientific dissertations and quantitative methods:

- Results chapter 

- Discussion chapter

Example: 

• Introduction
• Literature review
• Methodology
• (Recommendations)

if you write a scientific dissertation, or anyway using quantitative methods, you will have some  objective  results that you will present in the Results chapter. You will then interpret the results in the Discussion chapter.  

B) More common for qualitative methods

- Analysis chapter. This can have more descriptive/thematic subheadings.

- Discussion chapter. This can have more descriptive/thematic subheadings.

• Case study of Company X (fashion brand) environmental strategies 
• Successful elements
• Lessons learnt
• Criticisms of Company X environmental strategies 
• Possible alternatives

C) More common for qualitative methods

- Analysis and discussion chapter. This can have more descriptive/thematic titles.

• Case study of Company X (fashion brand) environmental strategies 

If your dissertation uses qualitative methods, it is harder to identify and report objective data. Instead, it may be more productive and meaningful to present the findings in the same sections where you also analyse, and possibly discuss, them. You will probably have different sections dealing with different themes. The different themes can be subheadings of the Analysis and Discussion (together or separate) chapter(s). 

Thematic dissertations

If the structure of your dissertation is thematic ,  you will have several chapters analysing and discussing the issues raised by your research. The chapters will have descriptive/thematic titles. 

• Background on the conflict in Yemen (2004-present day)
• Classification of the conflict in international law  
• International law violations
• Options for enforcement of international law
• Next: Results/Findings >>
• Last Updated: Aug 4, 2023 2:17 PM
• URL: https://libguides.westminster.ac.uk/c.php?g=696975

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Frequently asked questions

What goes in the results chapter of a dissertation.

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.

Frequently asked questions: Dissertation

Dissertation word counts vary widely across different fields, institutions, and levels of education:

• An undergraduate dissertation is typically 8,000–15,000 words
• A master’s dissertation is typically 12,000–50,000 words
• A PhD thesis is typically book-length: 70,000–100,000 words

However, none of these are strict guidelines – your word count may be lower or higher than the numbers stated here. Always check the guidelines provided by your university to determine how long your own dissertation should be.

A dissertation prospectus or proposal describes what or who you plan to research for your dissertation. It delves into why, when, where, and how you will do your research, as well as helps you choose a type of research to pursue. You should also determine whether you plan to pursue qualitative or quantitative methods and what your research design will look like.

It should outline all of the decisions you have taken about your project, from your dissertation topic to your hypotheses and research objectives , ready to be approved by your supervisor or committee.

Note that some departments require a defense component, where you present your prospectus to your committee orally.

A thesis is typically written by students finishing up a bachelor’s or Master’s degree. Some educational institutions, particularly in the liberal arts, have mandatory theses, but they are often not mandatory to graduate from bachelor’s degrees. It is more common for a thesis to be a graduation requirement from a Master’s degree.

Even if not mandatory, you may want to consider writing a thesis if you:

• Plan to attend graduate school soon
• Have a particular topic you’d like to study more in-depth
• Are considering a career in research
• Would like a capstone experience to tie up your academic experience

The conclusion of your thesis or dissertation should include the following:

• A restatement of your research question
• A summary of your key arguments and/or results
• A short discussion of the implications of your research

The conclusion of your thesis or dissertation shouldn’t take up more than 5–7% of your overall word count.

For a stronger dissertation conclusion , avoid including:

• Important evidence or analysis that wasn’t mentioned in the discussion section and results section
• Generic concluding phrases (e.g. “In conclusion …”)
• Weak statements that undermine your argument (e.g., “There are good points on both sides of this issue.”)

Your conclusion should leave the reader with a strong, decisive impression of your work.

While it may be tempting to present new arguments or evidence in your thesis or disseration conclusion , especially if you have a particularly striking argument you’d like to finish your analysis with, you shouldn’t. Theses and dissertations follow a more formal structure than this.

All your findings and arguments should be presented in the body of the text (more specifically in the discussion section and results section .) The conclusion is meant to summarize and reflect on the evidence and arguments you have already presented, not introduce new ones.

A theoretical framework can sometimes be integrated into a  literature review chapter , but it can also be included as its own chapter or section in your dissertation . As a rule of thumb, if your research involves dealing with a lot of complex theories, it’s a good idea to include a separate theoretical framework chapter.

A literature review and a theoretical framework are not the same thing and cannot be used interchangeably. While a theoretical framework describes the theoretical underpinnings of your work, a literature review critically evaluates existing research relating to your topic. You’ll likely need both in your dissertation .

While a theoretical framework describes the theoretical underpinnings of your work based on existing research, a conceptual framework allows you to draw your own conclusions, mapping out the variables you may use in your study and the interplay between them.

A thesis or dissertation outline is one of the most critical first steps in your writing process. It helps you to lay out and organize your ideas and can provide you with a roadmap for deciding what kind of research you’d like to undertake.

Generally, an outline contains information on the different sections included in your thesis or dissertation , such as:

• Your anticipated title
• Your abstract
• Your chapters (sometimes subdivided into further topics like literature review , research methods , avenues for future research, etc.)

When you mention different chapters within your text, it’s considered best to use Roman numerals for most citation styles. However, the most important thing here is to remain consistent whenever using numbers in your dissertation .

In most styles, the title page is used purely to provide information and doesn’t include any images. Ask your supervisor if you are allowed to include an image on the title page before doing so. If you do decide to include one, make sure to check whether you need permission from the creator of the image.

Include a note directly beneath the image acknowledging where it comes from, beginning with the word “ Note .” (italicized and followed by a period). Include a citation and copyright attribution . Don’t title, number, or label the image as a figure , since it doesn’t appear in your main text.

Definitional terms often fall into the category of common knowledge , meaning that they don’t necessarily have to be cited. This guidance can apply to your thesis or dissertation glossary as well.

However, if you’d prefer to cite your sources , you can follow guidance for citing dictionary entries in MLA or APA style for your glossary.

A glossary is a collection of words pertaining to a specific topic. In your thesis or dissertation, it’s a list of all terms you used that may not immediately be obvious to your reader. In contrast, an index is a list of the contents of your work organized by page number.

The title page of your thesis or dissertation goes first, before all other content or lists that you may choose to include.

The title page of your thesis or dissertation should include your name, department, institution, degree program, and submission date.

Glossaries are not mandatory, but if you use a lot of technical or field-specific terms, it may improve readability to add one to your thesis or dissertation. Your educational institution may also require them, so be sure to check their specific guidelines.

A glossary or “glossary of terms” is a collection of words pertaining to a specific topic. In your thesis or dissertation, it’s a list of all terms you used that may not immediately be obvious to your reader. Your glossary only needs to include terms that your reader may not be familiar with, and is intended to enhance their understanding of your work.

A glossary is a collection of words pertaining to a specific topic. In your thesis or dissertation, it’s a list of all terms you used that may not immediately be obvious to your reader. In contrast, dictionaries are more general collections of words.

An abbreviation is a shortened version of an existing word, such as Dr. for Doctor. In contrast, an acronym uses the first letter of each word to create a wholly new word, such as UNESCO (an acronym for the United Nations Educational, Scientific and Cultural Organization).

As a rule of thumb, write the explanation in full the first time you use an acronym or abbreviation. You can then proceed with the shortened version. However, if the abbreviation is very common (like PC, USA, or DNA), then you can use the abbreviated version from the get-go.

Be sure to add each abbreviation in your list of abbreviations !

If you only used a few abbreviations in your thesis or dissertation , you don’t necessarily need to include a list of abbreviations .

If your abbreviations are numerous, or if you think they won’t be known to your audience, it’s never a bad idea to add one. They can also improve readability, minimizing confusion about abbreviations unfamiliar to your reader.

A list of abbreviations is a list of all the abbreviations that you used in your thesis or dissertation. It should appear at the beginning of your document, with items in alphabetical order, just after your table of contents .

Your list of tables and figures should go directly after your table of contents in your thesis or dissertation.

Lists of figures and tables are often not required, and aren’t particularly common. They specifically aren’t required for APA-Style, though you should be careful to follow their other guidelines for figures and tables .

If you have many figures and tables in your thesis or dissertation, include one may help you stay organized. Your educational institution may require them, so be sure to check their guidelines.

A list of figures and tables compiles all of the figures and tables that you used in your thesis or dissertation and displays them with the page number where they can be found.

The table of contents in a thesis or dissertation always goes between your abstract and your introduction .

You may acknowledge God in your dissertation acknowledgements , but be sure to follow academic convention by also thanking the members of academia, as well as family, colleagues, and friends who helped you.

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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.

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.

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

To automatically insert a table of contents in Microsoft Word, follow these steps:

• Apply heading styles throughout the document.
• In the references section in the ribbon, locate the Table of Contents group.
• Click the arrow next to the Table of Contents icon and select Custom Table of Contents.
• Select which levels of headings you would like to include in the table of contents.

Make sure to update your table of contents if you move text or change headings. To update, simply right click and select Update Field.

All level 1 and 2 headings should be included in your table of contents . That means the titles of your chapters and the main sections within them.

The contents should also include all appendices and the lists of tables and figures, if applicable, as well as your reference list .

Do not include the acknowledgements or abstract in the table of contents.

The abstract appears on its own page in the thesis or dissertation , after the title page and acknowledgements but before the table of contents .

An abstract for a thesis or dissertation is usually around 200–300 words. There’s often a strict word limit, so make sure to check your university’s requirements.

In a thesis or dissertation, the acknowledgements should usually be no longer than one page. There is no minimum length.

The acknowledgements are generally included at the very beginning of your thesis , directly after the title page and before the abstract .

Yes, it’s important to thank your supervisor(s) in the acknowledgements section of your thesis or dissertation .

Even if you feel your supervisor did not contribute greatly to the final product, you must acknowledge them, if only for a very brief thank you. If you do not include your supervisor, it may be seen as a snub.

In the acknowledgements of your thesis or dissertation, you should first thank those who helped you academically or professionally, such as your supervisor, funders, and other academics.

Then you can include personal thanks to friends, family members, or anyone else who supported you during the process.

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How To Write The Results/Findings Chapter

For quantitative graduate (dissertations & theses).

By: Derek Johansen (MBA). Accomplished Reviewed The: Kerryn Warren (PhD) | July 2021

So, you’ve completed your quantitative data analysis and it’s time to report on own findings. But show do him start? In this post, we’ll take you through which results chapter (also labeled the findings or study chapter), step by step, so that you can craft this section of your research conversely thesis with confidence. If you’re looking on information regarding the end chapter for qualitative studies, you can find that here .

Summary: Quantitative Results Chapter

• What exactly the results/findings/analysis chapter is
• What you need to include int your results chapter
• How to structure your results chapter
• AMPERE few tips and tricks for writing top-notch chapter

What exactly is the results chapter?

The results chapter (also referred to as the findings or analysis chapter) shall one of the most important chapters of your dissertation or thesis because it exhibitions the reader what you’ve found in terms of the quantitative data you’ve collected. It presents the date using ampere clear write narrative, supported the charts, diagram and charts. In doing so, it also climax any potential issues (such as irregularities button unusual findings) you’ve come across.

Although how’s that different from to discussion chapter?

Well, by the results chapter, you only present your statistical findings. Only the numbers, so to address – no more, no less. Contrasts to this, in the panel chapters , you interpret your findings and linked yours to prior research (i.e. your literature review), as well as your search objectives also research questions. Stylish other words, the results chapter presents both describes the data, while this discussion chapter interprets the data.

Let’s look at an example.

In your result chapter, you maybe have a design is shows how respondents to a survey  responded: to numbers of respondents per category, for instance. You may other state whether this supports a hypothesis by after a p-value from an statistical exam. Aber it is only in an discussion chapter where you will say why this is relevant or how it compares with which literature or the broader picture. So, in your results chapter, induce certainly that her don’t present anything other than the hard facts – is is not the place in subjectivity.

It’s merit mentioning that some universities prefer you to combine the results or discussion click. Even so, it is goody practical to separate the results and discussion elements within the chapter, as this guarantee choose outcome are fully portrayed. Normal, though, the results and discussion books are split boost in quantitative studies. If you’re unsure, chats with your research supervisor or chair to find out what their preference is.

What should to include in one results section?

Following you analysis, it’s likely you’ll have far more datas from are necessary go include in your chapter. In all likelihood, you’ll have a mountain of SPSS or R output data, and it’s your job to decide what’s most relevant. You’ll need to cut through the noise and focus on the data that matters.

Like doesn’t mean that those analyses was a waste out date – on the contrary, who analyses ensure so they have a good understating the your dataset plus how to schauspieler it. However, that doesn’t mean your reader or researcher needs to see the 165 histograms you created! Relevance is key. Data analysis write-ups

How do I decide what’s relevant?

At this point, it may be difficult to strike a balance between what will and isn’t important. But the bulk important things is to ensure your earnings reflect and orient with the purpose of your study .  Like, you need to revisit your choose aims, objectives and search questions plus use these as a litmus test with relevance. Take sure that you refer back to these constantly while print up your chapter so that you stay on pisten.

As a general guided, your results book will usually include the following:

• Some demographic data about is sample
• Reliability tests (if you used measurement scales)
• Descriptive statistics
• Inferential online (if your choose objectives and questions order these)
• Hypothesis tests (again, if your research your and questions require these)

We’ll explore each off these points in more detailed within the next section.

Importantly, your ergebnisse chapter needed to lay the foundation for your discussion chapter . This means that, in your results chapter, you need to include all the date is she will use more the basis forward your interpretation in who discussion chapter.

For example, if you draft to set the strong relationship between Variable X and Variable UNKNOWN in your discussion chapter, you need to present the respective analysis in your results chapter – perhaps a compare or regressive analysis.

Needing a helping hand?

How execute I write the results chapter?

There are repeatedly steps complicated in writing up who results chapter for owner quantitative research. The exact number of steps applicable toward you will vary from study to investigate and will depend on the nature of the research aims, objectives and research questions . However, we’ll outlines the generic stepping below.

Step 1 – Revisit your choose questions

The first step in writing autochthonous results chapter is to revisit your research objectives additionally research questions . Dieser will been (or at least, should be!) the driving forces behind your results and discussion chapters, to you need to review them and then ask your which statistical tests and tests (from choose mountain for data) would specifically help you address these . For each research objective and exploring go, list the specific part (or pieces) of analysis that address it.

At this stage, it’s also useful to thinks about the key points that her want to raise in your topic chapter press note diesen down so this you can a clear reminder of which data points and analyses you what to highlight int the results chapter. Again, list your points and following list the specific piece of analysis that addresses either point.  The analysis chapter is one of the most important spare of a thesis. Here is a finish guide to dissertation data analysis!

Next, you should pull up a rough outline of method you plan to structure your chapter . Which analyses and statistical tests will you present and in about order? We’ll discussed the “standard structure” in more detail later, not it’s worth mentioning now this it’s always useful to tie up a crude outline before you start writing (this advice applies to any chapter).

Speed 2 – Craft any overview introduction

As with all chapters in thy dissertation or dissertation, you should start your quantitative resultat chapter by providing a brief overview of get you’ll do in the chapters and wherefore . For example, you’d explain that thee will start by presenting statistical intelligence into understand the representativeness of the sample, before moving onto X, Y furthermore Z.

This section shouldn’t be lengthy – a paragraph instead two maximum. Also, it’s a good idea to web the research questions on this section so that there’s a glitter thread that runs trough the documents.

Step 3 – Present one sample demographic dating

The first selected of data that you’ll presence is an overview of the sample demographics – includes other words, the census of your respondents.

In example:

• What age range are they?
• How is sexuality distributed?
• How is race distributed?
• What areas do the participants live in?

The purpose of aforementioned is to assess how spokesperson the sample is of and broader population. This is major required the sake of and generalisability of this results. If your sample is not representative of the population, you will not be able to generalise your findings. Which is not necessarily of end of the world, but a is a limitation you’ll need into acknowledge.

To course, to manufacture this representativeness assessment, you’ll need to have adenine clear view are of demographics of aforementioned population. So, make sure that you design your survey to capture the correct demographic information that you will compare your sample to.

But get if I’m not interested in generalisability?

Okay, even if your purpose is not necessarily until extend autochthonous findings to the broader population, understanding your sample will allow you until ausleger is findings suitably, considering who reply. On other words, is will help you contextualise is findings . For example, are 80% the your sample was senior over 65, this may be a significant contextual factor to consider at interpreting the data. Therefore, it’s essential toward understand and present the demographic file.

 Step 4 – Examination composite measures and the data “shape”.

Before you undertake any statistical analysis, you’ll need to do some inspection to ensure that will details be suitable for the analysis processes also techniques you set toward use. If you try to analyse intelligence ensure doesn’t meet the conjectures a a specific statistical technique, own results will be largely meaningless. Therefore, you may need to show that the processes and abilities you’ll getting are “allowed”.

Most commonly, there are two areas you needed to pay attention to:

#1: Composition measures

The first remains when you have repeatedly scale-based measures that combine to capture one construct – this is called a composite measure .  For example, you may have four Likert scale-based measures that (should) all measure the same thing, but in separate ways. In other words, in a scrutinize, these quad scales should all receive similar ratings. On is called “ internal consistency ”.

Internal consistency is not guaranteed though (especially if you developed the measures yourself), so you need until assess the vertrauen of each composed evaluate by a exam. Typically, Cronbach’s Alpha is a joint check used to assess user consistency – i.e., to shows ensure the product you’re combing are more or less sayings the same thing. ONE height alpha score means that your take is internally consistent. ADENINE low alpha score means you may need to consider scrapping one or find of the measures.

#2: Product shape

The second mattigkeit that you should address early go in your results chapter is data shapes. In other words, you need to assess whether the data at insert set are symmetry (i.e. normally distributed) or not, as this will directly impact what type starting analyses you can use. For loads common inferential testing such than T-tests or ANOVAs (we’ll discuss above-mentioned a bit later), your data needed to is normally distributed. If it’s not, you’ll need into adjust your strategy and use alternative tests.

To assess the shape off the data, you’ll typical assess a choose of descriptive statistics (such as the mean, median and skewness), which exists what we’ll look at next.

Step 5 – Present the descriptive vital

Now that you’ve laid the foundation by discussing the presence of our sample, as well as the reliability of your measures and an shapes of owner data, you can get started the the actual statistical analysis. The first step is to present the descriptive statistics for your variables.

By scaled data, this usually includes statistics such as:

• The mean – this is merely the mathematical average of a range of numbers.
• The median – like is who midpoint in a range of numbers at the numbers are arranged in order.
• Aforementioned run – this is who highest commonly repeated number in the file set.
• Standard variance – this metric indicates how dispersed a range of numbering is. In other words, how close all that numbers can to the mean (the average).
• Skewness – this indicates how symmetrical a range of numbers is. In other words, do it tend to clustering into a smooth bell curve shaped in the median of the graph (this is calls a normal or parametric distribution), either do they lean to the left or right (this is called a non-normal instead non-parametric distribution).
• Kurtosis – this metric points whether the data belong heavily or lightly-tailed, relative to the normal dissemination. In other words, how peaked or flat the distribution is.

A bigger table that indicates all to above for repeated variables can be a very effective way to present thy data economically. It can also use colour coding to help make the product more easily digestible.

For categorical data, location you show the percentage of people who chose or perfect into a choose, for instance, it bottle either simply plain describe this percentages or numbers of people who responded to something or usage graphs additionally schedules (such as bar graphs and pie charts) into present your details in this section by the chapter.

When using numbers, produce sure that you label their single and clear , so that your reader can easily understand them. There’s nothing more frustrating than a graph that’s missing axis labels! Keep in mind that although you’ll be presenting charts and graphs, your theme content needs to present an clear narrative that can stand on seine own. By other words, don’t rely purely on insert numbers and tables to convey your main points: highlight the crucial trends and values in the text. Figures and tables have complement who writing, not portable itp .

Depending on your explore aims, objectives and research questions, your may stop your analysis at this point (i.e. descriptive statistics). However, if your study requires inferential statistics, then it’s time to deep dive into those .

Step 6 – Present the inferential statistischen

Inferential statistiken are used to make generalisations about a population , whereas descriptive zahlen focus purely on the sample . Logical statistical capabilities, broadly speaking, can be broken down into two groups .

First, there are those that comparing measurements with bunches , create as t-tests (which measure differences between two groups) and ANOVAs (which gauge discrepancies between multiple groups). Second, there are techniques that assess the relationships between variables , such as correlation analysis and regression analyzed. Within each of these, certain tests can be previously for normally distributed (parametric) data and certain tests are planned specifically for uses on non-parametric data.

Thither are a seemingly endless number of tests that you ability use to crunch your data, so it’s easily go run down a rabbit hole and end up to piles of test data. Ultimately, the most important thing belongs to create sure that you adopt the tests and techniques that authorize it to realisieren your research objectives and answer your research questions .

In this section in the results chapter, you should try to doing use of figures and visual equipment as effectively as possible. For real, if you presenting a relationship charts, use colour encryption to bright the significance of the correlation principles, or scatterplots to optically demonstrate where the trend remains. The light you make it for your reader to digest your findings, the more effectively you’ll will able to make your arguments in the next chapter.

Level 7 – Test your research

If your study requires it, the upcoming stage is hypothesis test. A hypothesis is a statement , often indicating a gauge between groups or relationship between variables, that can becoming supported or rejected by a statistiken test. However, don see studies will involve conjectures (again, it depends on the investigate objectives), so don’t feelings like you “must” present and test hypotheses just because you’re undertaking quantitive research.

Of basic process for hypothesis testing is because follows:

• Specify your null hypothesis (for example, “The chemical psilocybin has no effect on time perception).
• Specify is alternative hypothesis (e.g., “The synthesized psilocybin has an affect up time perception)
• Set your significance level (this is commonly 0.05)
• Count the statistics and find yours p-value (e.g., p=0.01)
• Draw your conclusions (e.g., “The chemical psilocybin does have an effects on time perception”)

Finally, if the aim of your study is to develop and test an notions framework , this is the time to present thereto, following the testing of your hypotheses. While you don’t need to develop other discuss these findings further in the results branch, indicating whether the tests (and their p-values) support or reject the hypotheses is vital.

Step 8 – Offer a chapter summarized

For wrap up your results chapter and transition to the discussion chapter, you should provide a brief summary of an key findings . “Brief” is the keyword her – much like the chapter preamble, this shouldn’t be extensive – a paragraph instead second maximum. Stress the find most relevant to your research objectives and research frequently, and wrap it up.

Needed a helping hand-held?

Some final my, tip and tricks.

Now that you’ve got the essentials downhill, here are a few tips and trick to perform respective quantify results chapter brilliance:

• Available writing your results chapter, report get what in the past tense . You’re talking around what you’ve found in choose data, not what you are currently find for or trying to find.
• Structure your results chapter systematically both sequentially . Supposing you must two experiments where findings from which one generated inputs into the other, submit on them at command.
• Make your own tables and graphs rather than copied press pasting them from static analysis software like SPSS. Checking out the DataIsBeautiful reddit for several inspiration.
• Once you’re done writing, review thy work to make sure that you had provided enough information to answer your research matter , but additionally that them didn’t include superfluous information.

If you’ve got any questions about writing up the quantitative scores chapter, please walk a commenting below. If you’d like 1-on-1 helps with your quantitative analysis and topic, check out the hands-on coaching service , or book ampere free consultation with a friendly coach.

Psst… there’s better (for free)

This post exists part of our dissertation mini-course, that covers everything you must to get launched with your dissertation, thesis or research project. 

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Writing the Dissertation - Guides for Success: The Results and Discussion

• Writing the Dissertation Homepage
• Overview and Planning
• The Literature Review
• The Methodology
• The Results and Discussion
• The Conclusion
• The Abstract
• The Difference
• What to Avoid

Overview of writing the results and discussion

The results and discussion follow on from the methods or methodology chapter of the dissertation. This creates a natural transition from how you designed your study, to what your study reveals, highlighting your own contribution to the research area.

Disciplinary differences

Please note: this guide is not specific to any one discipline. The results and discussion can vary depending on the nature of the research and the expectations of the school or department, so please adapt the following advice to meet the demands of your project and department. Consult your supervisor for further guidance; you can also peruse our  Writing Across Subjects guide .

Guide contents

As part of the Writing the Dissertation series, this guide covers the most common conventions of the results and discussion chapters, giving you the necessary knowledge, tips and guidance needed to impress your markers! The sections are organised as follows:

• The Difference  - Breaks down the distinctions between the results and discussion chapters.
• Results  - Provides a walk-through of common characteristics of the results chapter.
• Discussion - Provides a walk-through of how to approach writing your discussion chapter, including structure.
• What to Avoid  - Covers a few frequent mistakes you'll want to...avoid!
• FAQs  - Guidance on first- vs. third-person, limitations and more.
• Checklist  - Includes a summary of key points and a self-evaluation checklist.

Training and tools

• The Academic Skills team has recorded a Writing the Dissertation workshop series to help you with each section of a standard dissertation, including a video on writing the results and discussion   (embedded below).
• The dissertation planner tool can help you think through the timeline for planning, research, drafting and editing.
• iSolutions offers training and a Word template to help you digitally format and structure your dissertation.

Introduction

The results of your study are often followed by a separate chapter of discussion. This is certainly the case with scientific writing. Some dissertations, however, might incorporate both the results and discussion in one chapter. This depends on the nature of your dissertation and the conventions within your school or department. Always follow the guidelines given to you and ask your supervisor for further guidance.

As part of the Writing the Dissertation series, this guide covers the essentials of writing your results and discussion, giving you the necesary knowledge, tips and guidance needed to leave a positive impression on your markers! This guide covers the results and discussion as separate – although interrelated – chapters, as you'll see in the next two tabs. However, you can easily adapt the guidance to suit one single chapter – keep an eye out for some hints on how to do this throughout the guide.

Results or discussion - what's the difference?

To understand what the results and discussion sections are about, we need to clearly define the difference between the two.

The results should provide a clear account of the findings . This is written in a dry and direct manner, simply highlighting the findings as they appear once processed. It’s expected to have tables and graphics, where relevant, to contextualise and illustrate the data.

Rather than simply stating the findings of the study, the discussion interprets the findings  to offer a more nuanced understanding of the research. The discussion is similar to the second half of the conclusion because it’s where you consider and formulate a response to the question, ‘what do we now know that we didn’t before?’ (see our Writing the Conclusion   guide for more). The discussion achieves this by answering the research questions and responding to any hypotheses proposed. With this in mind, the discussion should be the most insightful chapter or section of your dissertation because it provides the most original insight.

Across the next two tabs of this guide, we will look at the results and discussion chapters separately in more detail.

Writing the results

The results chapter should provide a direct and factual account of the data collected without any interpretation or interrogation of the findings. As this might suggest, the results chapter can be slightly monotonous, particularly for quantitative data. Nevertheless, it’s crucial that you present your results in a clear and direct manner as it provides the necessary detail for your subsequent discussion.

Note: If you’re writing your results and discussion as one chapter, then you can either:

1) write them as distinctly separate sections in the same chapter, with the discussion following on from the results, or...

2) integrate the two throughout by presenting a subset of the results and then discussing that subset in further detail.

Next, we'll explore some of the most important factors to consider when writing your results chapter.

How you structure your results chapter depends on the design and purpose of your study. Here are some possible options for structuring your results chapter (adapted from Glatthorn and Joyner, 2005):

• Chronological – depending on the nature of the study, it might be important to present your results in order of how you collected the data, such as a pretest-posttest design.
• Research method – if you’ve used a mixed-methods approach, you could isolate each research method and instrument employed in the study.
• Research question and/or hypotheses – you could structure your results around your research questions and/or hypotheses, providing you have more than one. However, keep in mind that the results on their own don’t necessarily answer the questions or respond to the hypotheses in a definitive manner. You need to interpret the findings in the discussion chapter to gain a more rounded understanding.
• Variable – you could isolate each variable in your study (where relevant) and specify how and whether the results changed.

Tables and figures

For your results, you are expected to convert your data into tables and figures, particularly when dealing with quantitative data. Making use of tables and figures is a way of contextualising your results within the study. It also helps to visually reinforce your written account of the data. However, make sure you’re only using tables and figures to supplement , rather than replace, your written account of the results (see the 'What to avoid' tab for more on this).

Figures and tables need to be numbered in order of when they appear in the dissertation, and they should be capitalised. You also need to make direct reference to them in the text, which you can do (with some variation) in one of the following ways:

Figure 1 shows…

The results of the test (see Figure 1) demonstrate…

The actual figures and tables themselves also need to be accompanied by a caption that briefly outlines what is displayed. For example:

Table 1. Variables of the regression model

Table captions normally appear above the table, whilst figures or other such graphical forms appear below, although it’s worth confirming this with your supervisor as the formatting can change depending on the school or discipline. The style guide used for writing in your subject area (e.g., Harvard, MLA, APA, OSCOLA) often dictates correct formatting of tables, graphs and figures, so have a look at your style guide for additional support.

Using quotations

If your qualitative data comes from interviews and focus groups, your data will largely consist of quotations from participants. When presenting this data, you should identify and group the most common and interesting responses and then quote two or three relevant examples to illustrate this point. Here’s a brief example from a qualitative study on the habits of online food shoppers:

Regardless of whether or not participants regularly engage in online food shopping, all but two respondents commented, in some form, on the convenience of online food shopping:

"It’s about convenience for me. I’m at work all week and the weekend doesn’t allow much time for food shopping, so knowing it can be ordered and then delivered in 24 hours is great for me” (Participant A).

"It fits around my schedule, which is important for me and my family” (Participant D).

"In the past, I’ve always gone food shopping after work, which has always been a hassle. Online food shopping, however, frees up some of my time” (Participant E).

As shown in this example, each quotation is attributed to a particular participant, although their anonymity is protected. The details used to identify participants can depend on the relevance of certain factors to the research. For instance, age or gender could be included.

Writing the discussion

The discussion chapter is where “you critically examine your own results in the light of the previous state of the subject as outlined in the background, and make judgments as to what has been learnt in your work” (Evans et al., 2014: 12). Whilst the results chapter is strictly factual, reporting on the data on a surface level, the discussion is rooted in analysis and interpretation , allowing you and your reader to delve beneath the surface.

Next, we will review some of the most important factors to consider when writing your discussion chapter.

Like the results, there is no single way to structure your discussion chapter. As always, it depends on the nature of your dissertation and whether you’re dealing with qualitative, quantitative or mixed-methods research. It’s good to be consistent with the results chapter, so you could structure your discussion chapter, where possible, in the same way as your results.

When it comes to structure, it’s particularly important that you guide your reader through the various points, subtopics or themes of your discussion. You should do this by structuring sections of your discussion, which might incorporate three or four paragraphs around the same theme or issue, in a three-part way that mirrors the typical three-part essay structure of introduction, main body and conclusion.

Figure 1: The three-part cycle that embodies a typical essay structure and reflects how you structure themes or subtopics in your discussion.

This is your topic sentence where you clearly state the focus of this paragraph/section. It’s often a fairly short, declarative statement in order to grab the reader’s attention, and it should be clearly related to your research purpose, such as responding to a research question.

This constitutes your analysis where you explore the theme or focus, outlined in the topic sentence, in further detail by interrogating why this particular theme or finding emerged and the significance of this data. This is also where you bring in the relevant secondary literature.

This is the evaluative stage of the cycle where you explicitly return back to the topic sentence and tell the reader what this means in terms of answering the relevant research question and establishing new knowledge. It could be a single sentence, or a short paragraph, and it doesn’t strictly need to appear at the end of every section or theme. Instead, some prefer to bring the main themes together towards the end of the discussion in a single paragraph or two. Either way, it’s imperative that you evaluate the significance of your discussion and tell the reader what this means.

A note on the three-part structure

This is often how you’re taught to construct a paragraph, but the themes and ideas you engage with at dissertation level are going to extend beyond the confines of a short paragraph. Therefore, this is a structure to guide how you write about particular themes or patterns in your discussion. Think of this structure like a cycle that you can engage in its smallest form to shape a paragraph; in a slightly larger form to shape a subsection of a chapter; and in its largest form to shape the entire chapter. You can 'level up' the same basic structure to accommodate a deeper breadth of thinking and critical engagement.

Using secondary literature

Your discussion chapter should return to the relevant literature (previously identified in your literature review ) in order to contextualise and deepen your reader’s understanding of the findings. This might help to strengthen your findings, or you might find contradictory evidence that serves to counter your results. In the case of the latter, it’s important that you consider why this might be and the implications for this. It’s through your incorporation of secondary literature that you can consider the question, ‘What do we now know that we didn’t before?’

Limitations

You may have included a limitations section in your methodology chapter (see our Writing the Methodology guide ), but it’s also common to have one in your discussion chapter. The difference here is that your limitations are directly associated with your results and the capacity to interpret and analyse those results.

Think of it this way: the limitations in your methodology refer to the issues identified before conducting the research, whilst the limitations in your discussion refer to the issues that emerged after conducting the research. For example, you might only be able to identify a limitation about the external validity or generalisability of your research once you have processed and analysed the data. Try not to overstress the limitations of your work – doing so can undermine the work you’ve done – and try to contextualise them, perhaps by relating them to certain limitations of other studies.

Recommendations

It’s often good to follow your limitations with some recommendations for future research. This creates a neat linearity from what didn’t work, or what could be improved, to how other researchers could address these issues in the future. This helps to reposition your limitations in a positive way by offering an action-oriented response. Try to limit the amount of recommendations you discuss – too many can bring the end of your discussion to a rather negative end as you’re ultimately focusing on what should be done, rather than what you have done. You also don’t need to repeat the recommendations in your conclusion if you’ve included them here.

What to avoid

This portion of the guide will cover some common missteps you should try to avoid in writing your results and discussion.

Over-reliance on tables and figures

It’s very common to produce visual representations of data, such as graphs and tables, and to use these representations in your results chapter. However, the use of these figures should not entirely replace your written account of the data. You don’t need to specify every detail in the data set, but you should provide some written account of what the data shows, drawing your reader’s attention to the most important elements of the data. The figures should support your account and help to contextualise your results. Simply stating, ‘look at Table 1’, without any further detail is not sufficient. Writers often try to do this as a way of saving words, but your markers will know!

Ignoring unexpected or contradictory data

Research can be a complex process with ups and downs, surprises and anomalies. Don’t be tempted to ignore any data that doesn’t meet your expectations, or that perhaps you’re struggling to explain. Failing to report on data for these, and other such reasons, is a problem because it undermines your credibility as a researcher, which inevitably undermines your research in the process. You have to do your best to provide some reason to such data. For instance, there might be some methodological reason behind a particular trend in the data.

Including raw data

You don’t need to include any raw data in your results chapter – raw data meaning unprocessed data that hasn’t undergone any calculations or other such refinement. This can overwhelm your reader and obscure the clarity of the research. You can include raw data in an appendix, providing you feel it’s necessary.

Presenting new results in the discussion

You shouldn’t be stating original findings for the first time in the discussion chapter. The findings of your study should first appear in your results before elaborating on them in the discussion.

Overstressing the significance of your research

It’s important that you clarify what your research demonstrates so you can highlight your own contribution to the research field. However, don’t overstress or inflate the significance of your results. It’s always difficult to provide definitive answers in academic research, especially with qualitative data. You should be confident and authoritative where possible, but don’t claim to reach the absolute truth when perhaps other conclusions could be reached. Where necessary, you should use hedging (see definition) to slightly soften the tone and register of your language.

Definition: Hedging refers to 'the act of expressing your attitude or ideas in tentative or cautious ways' (Singh and Lukkarila, 2017: 101). It’s mostly achieved through a number of verbs or adverbs, such as ‘suggest’ or ‘seemingly.’

Q: What’s the difference between the results and discussion?

A: The results chapter is a factual account of the data collected, whilst the discussion considers the implications of these findings by relating them to relevant literature and answering your research question(s). See the tab 'The Differences' in this guide for more detail.

Q: Should the discussion include recommendations for future research?

A: Your dissertation should include some recommendations for future research, but it can vary where it appears. Recommendations are often featured towards the end of the discussion chapter, but they also regularly appear in the conclusion chapter (see our Writing the Conclusion guide   for more). It simply depends on your dissertation and the conventions of your school or department. It’s worth consulting any specific guidance that you’ve been given, or asking your supervisor directly.

Q: Should the discussion include the limitations of the study?

A: Like the answer above, you should engage with the limitations of your study, but it might appear in the discussion of some dissertations, or the conclusion of others. Consider the narrative flow and whether it makes sense to include the limitations in your discussion chapter, or your conclusion. You should also consult any discipline-specific guidance you’ve been given, or ask your supervisor for more. Be mindful that this is slightly different to the limitations outlined in the methodology or methods chapter (see our Writing the Methodology guide vs. the 'Discussion' tab of this guide).

Q: Should the results and discussion be in the first-person or third?

A: It’s important to be consistent , so you should use whatever you’ve been using throughout your dissertation. Third-person is more commonly accepted, but certain disciplines are happy with the use of first-person. Just remember that the first-person pronoun can be a distracting, but powerful device, so use it sparingly. Consult your lecturer for discipline-specific guidance.

Q: Is there a difference between the discussion and the conclusion of a dissertation?

A: Yes, there is a difference. The discussion chapter is a detailed consideration of how your findings answer your research questions. This includes the use of secondary literature to help contextualise your discussion. Rather than considering the findings in detail, the conclusion briefly summarises and synthesises the main findings of your study before bringing the dissertation to a close. Both are similar, particularly in the way they ‘broaden out’ to consider the wider implications of the research. They are, however, their own distinct chapters, unless otherwise stated by your supervisor.

The results and discussion chapters (or chapter) constitute a large part of your dissertation as it’s here where your original contribution is foregrounded and discussed in detail. Remember, the results chapter simply reports on the data collected, whilst the discussion is where you consider your research questions and/or hypothesis in more detail by interpreting and interrogating the data. You can integrate both into a single chapter and weave the interpretation of your findings throughout the chapter, although it’s common for both the results and discussion to appear as separate chapters. Consult your supervisor for further guidance.

Here’s a final checklist for writing your results and discussion. Remember that not all of these points will be relevant for you, so make sure you cover whatever’s appropriate for your dissertation. The asterisk (*) indicates any content that might not be relevant for your dissertation. To download a copy of the checklist to save and edit, please use the Word document, below.

• Results and discussion self-evaluation checklist

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• Last Updated: Feb 22, 2024 3:43 PM
• URL: https://library.soton.ac.uk/writing_the_dissertation