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• How to Write a Results Section | Tips & Examples

How to Write a Results Section | Tips & Examples

Published on 27 October 2016 by Bas Swaen . Revised on 25 October 2022 by Tegan George.

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

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Table of contents

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

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

Here are a few best practices:

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

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

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

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

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

A note on tables and figures

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

As a rule of thumb:

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

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

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

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

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

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

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

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

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

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

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

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I have completed my data collection and analyzed the results.

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

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

I have stated whether each hypothesis was supported or refuted.

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

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

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

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

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

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

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

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

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

Don’t interpret or speculate in the results chapter.

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

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

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

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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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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 the Dissertation Findings or Results – Tips

Published by Grace Graffin at August 11th, 2021 , Revised On August 13, 2024

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.

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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;

The last question of the interview focused on the need for improvement in Thai ready-to-eat products and the industry at large, emphasizing the need for enhancement in the current products being offered in the market. When asked if there was any particular need for Thai ready-to-eat meals to be improved and how to improve them in case of ‘yes,’ the males replied mainly by saying that the current products need improvement in terms of the use of healthier raw materials and preservatives or additives. There was an agreement amongst all males concerning the need to improve the industry for ready-to-eat meals and the use of more healthy items to prepare such meals. The females were also of the opinion that the fast-food items needed to be improved in the sense that more healthy raw materials such as vegetable oil and unsaturated fats, including whole-wheat products, to overcome risks associated with trans fat leading to obesity and hypertension should be used for the production of RTE products. The frozen RTE meals and packaged snacks included many preservatives and chemical-based flavouring enhancers that harmed human health and needed to be reduced. The industry is said to be aware of this fact and should try to produce RTE products that benefit the community in terms of healthy consumption.

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What to Avoid in Dissertation Findings Chapter

• Avoid using interpretive and subjective phrases and terms such as “confirms,” “reveals,” “suggests,” or “validates.” These terms are more suitable for the discussion chapter , where you will be expected to interpret the results in detail.
• Only briefly explain findings in relation to the key themes, hypothesis, and research questions. You don’t want to write a detailed subjective explanation for any research questions at this stage.

The Do’s of Writing the Findings or Results Section

• Ensure you are not presenting results from other research studies in your findings.
• Observe whether or not your hypothesis is tested or research questions answered.
• Illustrations and tables present data and are labelled to help your readers understand what they relate to.
• Use software such as Excel, STATA, and SPSS to analyse results and important trends.

Essential Guidelines on How to Write Dissertation Findings

The dissertation findings chapter should provide the context for understanding the results. The research problem should be repeated, and the research goals should be stated briefly.

This approach helps to gain the reader’s attention toward the research problem. The first step towards writing the findings is identifying which results will be presented in this section.

The results relevant to the questions must be presented, considering whether the results support the hypothesis. You do not need to include every result in the findings section. The next step is ensuring the data can be appropriately organized and accurate.

You will need to have a basic idea about writing the findings of a dissertation because this will provide you with the knowledge to arrange the data chronologically.

Start each paragraph by writing about the most important results and concluding the section with the most negligible actual results.

A short paragraph can conclude the findings section, summarising the findings so readers will remember as they transition to the next chapter. This is essential if findings are unexpected or unfamiliar or impact the study.

Our writers can help you with all parts of your dissertation, including statistical analysis of your results . To obtain free non-binding quotes, please complete our online quote form here .

Be Impartial in your Writing

When crafting your findings, knowing how you will organize the work is important. The findings are the story that needs to be told in response to the research questions that have been answered.

Therefore, the story needs to be organized to make sense to you and the reader. The findings must be compelling and responsive to be linked to the research questions being answered.

Always ensure that the size and direction of any changes, including percentage change, can be mentioned in the section. The details of p values or confidence intervals and limits should be included.

The findings sections only have the relevant parts of the primary evidence mentioned. Still, it is a good practice to include all the primary evidence in an appendix that can be referred to later.

The results should always be written neutrally without speculation or implication. The statement of the results mustn’t have any form of evaluation or interpretation.

Negative results should be added in the findings section because they validate the results and provide high neutrality levels.

The length of the dissertation findings chapter is an important question that must be addressed. It should be noted that the length of the section is directly related to the total word count of your dissertation paper.

The writer should use their discretion in deciding the length of the findings section or refer to the dissertation handbook or structure guidelines.

It should neither belong nor be short nor concise and comprehensive to highlight the reader’s main findings.

Ethically, you should be confident in the findings and provide counter-evidence. Anything that does not have sufficient evidence should be discarded. The findings should respond to the problem presented and provide a solution to those questions.

Structure of the Findings Chapter

The chapter should use appropriate words and phrases to present the results to the readers. Logical sentences should be used, while paragraphs should be linked to produce cohesive work.

You must ensure all the significant results have been added in the section. Recheck after completing the section to ensure no mistakes have been made.

The structure of the findings section is something you may have to be sure of primarily because it will provide the basis for your research work and ensure that the discussions section can be written clearly and proficiently.

One way to arrange the results is to provide a brief synopsis and then explain the essential findings. However, there should be no speculation or explanation of the results, as this will be done in the discussion section.

Another way to arrange the section is to present and explain a result. This can be done for all the results while the section is concluded with an overall synopsis.

This is the preferred method when you are writing more extended dissertations. It can be helpful when multiple results are equally significant. A brief conclusion should be written to link all the results and transition to the discussion section.

Numerous data analysis dissertation examples are available on the Internet, which will help you improve your understanding of writing the dissertation’s findings.

Problems to Avoid When Writing Dissertation Findings

One of the problems to avoid while writing the dissertation findings is reporting background information or explaining the findings. This should be done in the introduction section .

You can always revise the introduction chapter based on the data you have collected if that seems an appropriate thing to do.

Raw data or intermediate calculations should not be added in the findings section. Always ask your professor if raw data needs to be included.

If the data is to be included, then use an appendix or a set of appendices referred to in the text of the findings chapter.

Do not use vague or non-specific phrases in the findings section. It is important to be factual and concise for the reader’s benefit.

The findings section presents the crucial data collected during the research process. It should be presented concisely and clearly to the reader. There should be no interpretation, speculation, or analysis of the data.

The significant results should be categorized systematically with the text used with charts, figures, and tables. Furthermore, avoiding using vague and non-specific words in this section is essential.

It is essential to label the tables and visual material properly. You should also check and proofread the section to avoid mistakes.

The dissertation findings chapter is a critical part of your overall dissertation paper. If you struggle with presenting your results and statistical analysis, our expert dissertation writers can help you get things right. Whether you need help with the entire dissertation paper or individual chapters, our dissertation experts can provide customized dissertation support .

FAQs About Findings of a Dissertation

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 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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How to Write the Results Section of your Dissertation or Thesis?

Introduction

Organizing your results, providing context, presenting the data in results section, describing statistical analysis, reporting the findings in results section, supporting the findings, visual representation in results section.

As you progress on your journey towards completing your PhD or Post Graduate dissertation, one of the most critical sections that holds immense significance is the results section.

Results section serves as the pinnacle of your research, where you unveil the outcomes of your exhaustive efforts and shed light on the answers to your research questions. In this blog post, we will delve into the intricacies of the results section and explore how to effectively present and interpret your findings to leave a lasting impact.

Whether you’re conducting research in the field of biology, psychology, computer science, or any other discipline, the results section is where your data takes center stage. It is a space where you showcase your meticulous analysis, statistical methods, and the discoveries you’ve made along the way. By understanding the key components and best practices for constructing a compelling results section, you can present your findings in a manner that resonates with both your academic peers and the wider research community.

In this comprehensive guide, we will walk you through the fundamental elements of the results section, from organizing your data to choosing the appropriate visual representations. We will explore the importance of clear and concise reporting, emphasizing the significance of providing contextual information and highlighting any unexpected or groundbreaking discoveries.

Furthermore, we will discuss strategies for effectively interpreting your results, discussing their implications, and connecting them back to your research objectives. By mastering these skills, you will be able to demonstrate the significance of your work, contribute to the existing body of knowledge, and potentially pave the way for further research in your field.

Throughout the blog post, I will provide concrete examples from various disciplines to illustrate the implementation of these techniques. Additionally, I will offer valuable tips on avoiding common pitfalls, ensuring the accuracy and reliability of your results, and seeking feedback from your advisors or peers to enhance the quality of your analysis.

If you are in paucity of time, not confident of your writing skills and in a hurry to complete the writing task then you can think of hiring a research consultant that solves all your problems. Please visit my article on Hiring a Research consultant for your PhD tasks for further details.

Organizing the results of your study in a logical and coherent manner is crucial for effectively communicating your findings. By presenting your results in an organized structure, you enhance the clarity and readability of your dissertation. Here are some key considerations for organizing your results:

• Research studies often involve complex algorithms, software implementations, experimental data, and performance metrics. It is essential to organize these diverse elements in a cohesive manner to make it easier for readers to follow your research. A well-structured results section enables readers to understand the progression of your experiments and the relationship between different findings.
• Begin by reminding readers of the research questions or hypotheses that guided your study. This alignment helps establish a clear connection between the objectives of your research and the subsequent presentation of results. For example, if your research question focuses on evaluating the efficiency of a new sorting algorithm, you would present the experimental data, performance metrics, and comparative analyses specific to that algorithm in relation to the research question.
• Subsubsection 1.1: Experimental Setup
• Subsubsection 1.2: Experimental Results and Analysis
• Subsubsection 2.1: Performance Metrics
• Subsubsection 2.2: Comparative Results and Discussion

Remember to tailor the organization of your results section to the specific requirements of your research. The key is to provide a logical flow and structure that enables readers to easily comprehend and interpret your findings.

Providing context for the results of your study is essential to help readers understand the significance and implications of your findings. By offering background information and study design details, you establish a foundation upon which the results can be properly interpreted. Here are some key considerations for providing context:

• Before delving into the results, it is important to provide readers with relevant background information about the topic or problem being addressed. This may include a literature review of existing research, theories, or methodologies in the field. By doing so, you situate your work within the broader landscape of and demonstrate its relevance. Additionally, explain the design of your study, such as the specific algorithms, software frameworks, datasets, or hardware setups used. This ensures that readers understand the context in which your results were obtained.
• Provide a brief overview of the current state-of-the-art in image recognition algorithms and their limitations.
• Explain the specific challenges or gaps in the existing methods that motivated your research.
• Describe the design of your study, including the choice of machine learning techniques, datasets used for training and evaluation, preprocessing steps, and any hardware or software configurations.

By providing context, you allow readers to understand the background, motivation, and methodology behind your research. This sets the stage for better comprehension and interpretation of your results. Contextualizing your findings, as it helps establish the relevance, novelty, and potential impact of your research within the larger field.

Presenting data in a clear and organized manner is crucial for effectively communicating your results. The way you present your data can greatly impact the reader’s understanding and interpretation of your findings. Here are some key considerations for presenting data:

• Presenting performance metrics of different algorithms using a table to allow for easy comparison.
• Using a line graph to depict the improvement in accuracy over training iterations in a machine learning model.
• Employing a bar chart to compare the execution times of different algorithms on a specific dataset.
• Clear labelling and formatting of your data ensure that readers can easily understand and interpret the information presented. Label each table, figure, chart, or graph with a concise and descriptive title. Ensure that axes, legends, and labels are clearly labelled and units of measurement are specified. Use appropriate fonts, colours, and styles to enhance readability. Consider providing captions or footnotes to provide additional context or explanations where necessary.
• In the text, refer to a specific table presenting the accuracy results of different algorithms and explain how these results support your research hypothesis or contribute to the field.
• Discuss a figure showing the relationship between the number of training examples and the performance of a machine learning model, emphasizing its implications for scalability and generalization.

By presenting data in a visually appealing and well-organized manner, you enhance the clarity and accessibility of your results. Proper labelling, formatting, and referring to each table or figure in the text help readers navigate the information and grasp its significance. Remember to choose the most appropriate format for your data and use visuals to support and reinforce your findings.

The inclusion of statistical analyses in the results section is crucial for providing objective and quantitative evidence to support your findings. Statistical analyses help you draw meaningful conclusions from your data and determine the significance of observed results. Here are some key considerations for describing statistical analyses:

• Statistical analyses play a vital role in determining the reliability and significance of your findings. They provide a systematic and objective framework for interpreting the data and testing hypotheses. Discuss the importance of including statistical analyses in the results section to demonstrate the rigour and validity of your research.
• Describe using a t-test to compare the means of two groups in a user study, as it is appropriate for assessing the statistical significance of differences.
• Explain employing logistic regression to model the relationship between independent variables and a binary outcome in a predictive analytics study.
• Report the p-value as 0.032, indicating a statistically significant difference between the two groups at the 0.05 significance level.
• Interpret an effect size of 0.40 as a medium-sized effect, highlighting its practical importance in the context of the research.

By describing the statistical analyses conducted, explaining the rationale behind the chosen tests, and accurately presenting the statistical values and interpretations, you strengthen the validity and reliability of your findings. Statistical analyses provide an objective framework for drawing conclusions from your data and lend credibility to your research in the computer science domain.

Reporting the findings of your research in an objective, concise, and clear manner is essential for effectively communicating your results. Here are some key considerations for reporting the findings:

• Summarize the key findings of a machine learning study by stating that “the proposed algorithm achieved an average accuracy of 85% on the test dataset, outperforming existing state-of-the-art methods by 10%.”
• For a research question about the impact of different programming languages on software performance, present specific metrics such as execution time or memory usage for each language, along with a comparison and interpretation of the results.
• Instead of using overly technical language, communicate the results in a more accessible way: “The experimental results showed a significant correlation between the number of training samples and the accuracy of the model, indicating that a larger training dataset leads to improved prediction performance.”

By guiding readers on summarizing the results objectively and concisely, addressing each research question or hypothesis, and using clear and concise language, you ensure that your findings are communicated effectively. This approach allows readers to understand the core contributions of your research and how they align with the research questions or hypotheses you set out to investigate.

Providing strong evidence from the data to support your findings, addressing unexpected or contradictory results, and discussing limitations and potential explanations are essential components of reporting research findings. Here are some key considerations for supporting the findings:

• Present empirical evidence from a user study, such as participant feedback or performance metrics, to support the usability and effectiveness of a proposed user interface design.
• If a software system performed unexpectedly poorly in certain scenarios, discuss potential factors such as data bias, implementation issues, or limitations of the evaluation methodology that could have influenced the results.
• Acknowledge limitations such as a small sample size, limited dataset availability, or computational constraints that might affect the generalizability or robustness of the results.
• Discuss potential explanations for unexpected results, such as issues with data quality, algorithmic complexity, or model assumptions.

By providing evidence from the data to support the findings, addressing unexpected or contradictory results, and discussing limitations and potential explanations, you demonstrate a rigorous and reflective approach to your research in the computer science domain. This allows readers to assess the strength and reliability of your findings and gain a deeper understanding of the nuances and implications of your work.

Using visual representations, such as tables, graphs, and figures, alongside the text can greatly enhance the understanding and impact of your findings. Here are some key considerations for visual representation:

Visual representations offer several benefits in presenting research findings. They provide a concise and intuitive way to convey complex information, trends, and patterns. Visuals can help readers grasp key insights at a glance, enhance the overall readability of the document, and make the findings more memorable. Visual representations also facilitate effective comparisons, highlight important relationships, and aid in storytelling. Example:

When creating visual representations, consider the following tips to ensure clarity and effectiveness: a. Choose the appropriate visual format: Select the most suitable format, such as tables, line graphs, scatter plots, or heatmaps, based on the nature of the data and the message you want to convey.

b. Simplify and declutter: Avoid overwhelming the visuals with excessive data points, labels, or unnecessary decorations. Keep the design clean and focused on conveying the essential information.

c. Label and title clearly: Provide descriptive and informative titles for tables, graphs, and figures. Label the axes, data points, or components clearly to facilitate understanding.

d. Use colors and visual cues purposefully: Utilize colors and visual cues to highlight important information or differentiate between categories. Ensure that the chosen colors are distinguishable and accessible. e. Provide legends and captions: Include legends to explain symbols, colors, or abbreviations used in the visuals. Provide informative captions or annotations to guide readers in interpreting the visuals accurately. Example:

By incorporating clear and effective visual representations alongside the text, you enhance the presentation and understanding of your research findings in the computer science domain. Well-designed tables, graphs, and figures can simplify complex information, facilitate comparisons, and enhance the visual appeal of your dissertation. Remember to choose appropriate formats, keep the visuals uncluttered, label clearly, and use colors and visual cues purposefully to maximize their impact.

Writing the results section of a dissertation or thesis is a critical task that requires careful attention to detail, organization, and effective communication. Throughout this blog post, we have explored key elements to consider when crafting this section.

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The main purpose of a dissertation is to contribute knowledge to your field of study. So it goes without saying that a dissertation is rather pointless if you don’t document the results of your research clearly! This is where you document the findings of your research, where you make sense of what you have discovered throughout the research process and explain its relevance to the research question or problem. Let’s explore how to write the results section of your dissertation.

What goes in the results section

Conventionally, the results section is the fourth chapter of your dissertation, written after you present your method of study . How exactly you present your findings differs from study to study, depending on the topic and discipline your research is situated in, the methods you used, and what kind of data you are presenting. 

Here’s what you’ll cover in the results chapter: 

• A brief reminder of the research question and the purpose of your research  
• The results of your experiment or study and what they mean 
• The data that you’ve collected in sentence form, accompanied by visual elements such as tables, graphs, charts, etc. 
• A critical analysis of how they relate to your research question 

Pro-tip: Always check your university’s guidelines for specific details on what you are required to write about in this section.

Results vs discussion

It’s important to note that the results chapter is usually not the same as the discussion . The purpose of the results section is to present findings in a logical, objective, and impartial manner. At this stage, you do not include your interpretation as a researcher or discuss the implications of the research. Observations that you make, as a researcher, are better suited for the next few chapters. In other words, you simply present the data in the results chapter, and you interpret it in the discussion chapter. 

Although, in some cases (for instance, if your university tells you to), you may be asked to combine the two sections. In this case, you’ll have to weave your interpretation and analysis into the segments where you’re presenting data. 

How to write and structure the results section

Regardless of whether your dissertation is qualitative or quantitative in nature, there are certain aspects common to this chapter. It has an introduction that reiterates the aims and purpose of the research, a body that deconstructs the results obtained during the research process, and a conclusion that summarizes the study’s findings and sets the stage for a discussion about its implications for your research area. 

This chapter is written in the simple past tense, as you are reporting a study that has been conducted in the past. 

Reporting qualitative research 

The purpose of qualitative research is to explore the depth and nuances of a particular topic. So you’ll be engaged with uncovering it through words and detailed descriptions, rather than hard numbers. A qualitative study sees data being presented primarily in the form of words , often supplemented with quantitative data that supports relevant claims. You’re likely to resort to this kind of analysis if you’re working in humanities and social sciences. 

The first decision you’ll need to make at this moment is whether you’ll be structuring your data chronologically (in order of how you conducted the research) or thematically (in terms of patterns and trends that you see in your data). 

Ensure that each finding you highlight is directly relevant to your research question. You may have made many discoveries over the course of your research, but your chapter has to be concise and report findings that either support or contradict your hypothesis. There is a lot of raw data that you will need to sift through to decide what’s important. 

Include excerpts and quotations from appropriate sources such as interviews, discussion transcripts, supporting literature, and so on, to back each of your findings. 

Although your chapter is mostly just a barrage of words, it’s useful to have graphs, tables, charts, and other visual elements that illustrate what you’re saying in text. Having such quantitative parameters within the chapter is not mandatory (and may not even apply to certain types of research, like a literary analysis), but is often helpful with establishing a story for your research. 

Commonly used qualitative research methods: in-depth interviews, case studies, focus group discussions, theoretical research , literary analysis, and so forth. 

Reporting quantitative research

Quantitative research, as the name suggests, focuses on studying data through statistical and mathematical techniques. If you’re doing this type of research for your dissertation, your results chapter will be dominated by statistics and numbers (represented through graphs, tables, charts, etc.), explained succinctly through text. 

Here’s what you have to include in the chapter: 

• Statistical analysis, their relevance and relationship with the research question 
• Observations about whether data supports or rejects the hypothesis 
• Trends, patterns, and relationships that can be understood from the data 

Since numerical data can be dense and difficult to understand at the first glance, it’s always advised that you articulate them visually, through graphs, tables, charts, and perhaps even relevant figures. Not only does this allow you to deconstruct data in a more appealing way, but it also allows you to spell out a narrative for your data, which you will support with text that explains your findings. 

Commonly used quantitative research methods: Surveys, polls, simulations and modeling of data 

Tips to write a good results section

• Include tables, figures, and other visual elements to present complex data in a more accessible way. These elements should supplement the words rather than be repetitive. 
• Use a variety of visual elements to illustrate data that might be difficult to interpret solely with words. 
• Be honest in your reporting. This may seem obvious, but it’s easy to forget that results always don’t need to corroborate your hypothesis. In fact, it’s perfectly acceptable for the opposite to happen; this is useful in telling the research community that something doesn’t work! What matters in this section is relevance.
• Be concise and precise in your reporting. You don’t need to delve into every little detail about your data. Simply present data and information that is relevant to your research question. 

Frequently Asked Questions

Are the results and discussion sections the same, do i have to combine the results and discussions sections, where can i document raw data i haven’t been able to include in the chapter, how long should the results section of a dissertation be, what can i include in an appendix.

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Guide to Writing the Results and Discussion Sections of a Scientific Article

A quality research paper has both the qualities of in-depth research and good writing ( Bordage, 2001 ). In addition, a research paper must be clear, concise, and effective when presenting the information in an organized structure with a logical manner ( Sandercock, 2013 ).

In this article, we will take a closer look at the results and discussion section. Composing each of these carefully with sufficient data and well-constructed arguments can help improve your paper overall.

The results section of your research paper contains a description about the main findings of your research, whereas the discussion section interprets the results for readers and provides the significance of the findings. The discussion should not repeat the results.

Let’s dive in a little deeper about how to properly, and clearly organize each part.

How to Organize the Results Section

Since your results follow your methods, you’ll want to provide information about what you discovered from the methods you used, such as your research data. In other words, what were the outcomes of the methods you used?

You may also include information about the measurement of your data, variables, treatments, and statistical analyses.

To start, organize your research data based on how important those are in relation to your research questions. This section should focus on showing major results that support or reject your research hypothesis. Include your least important data as supplemental materials when submitting to the journal.

The next step is to prioritize your research data based on importance – focusing heavily on the information that directly relates to your research questions using the subheadings.

The organization of the subheadings for the results section usually mirrors the methods section. It should follow a logical and chronological order.

Subheading organization

Subheadings within your results section are primarily going to detail major findings within each important experiment. And the first paragraph of your results section should be dedicated to your main findings (findings that answer your overall research question and lead to your conclusion) (Hofmann, 2013).

In the book “Writing in the Biological Sciences,” author Angelika Hofmann recommends you structure your results subsection paragraphs as follows:

• Experimental purpose
• Interpretation

Each subheading may contain a combination of ( Bahadoran, 2019 ; Hofmann, 2013, pg. 62-63):

• Text: to explain about the research data
• Figures: to display the research data and to show trends or relationships, for examples using graphs or gel pictures.
• Tables: to represent a large data and exact value

Decide on the best way to present your data — in the form of text, figures or tables (Hofmann, 2013).

Data or Results?

Sometimes we get confused about how to differentiate between data and results . Data are information (facts or numbers) that you collected from your research ( Bahadoran, 2019 ).

Whereas, results are the texts presenting the meaning of your research data ( Bahadoran, 2019 ).

One mistake that some authors often make is to use text to direct the reader to find a specific table or figure without further explanation. This can confuse readers when they interpret data completely different from what the authors had in mind. So, you should briefly explain your data to make your information clear for the readers.

Common Elements in Figures and Tables

Figures and tables present information about your research data visually. The use of these visual elements is necessary so readers can summarize, compare, and interpret large data at a glance. You can use graphs or figures to compare groups or patterns. Whereas, tables are ideal to present large quantities of data and exact values.

Several components are needed to create your figures and tables. These elements are important to sort your data based on groups (or treatments). It will be easier for the readers to see the similarities and differences among the groups.

When presenting your research data in the form of figures and tables, organize your data based on the steps of the research leading you into a conclusion.

Common elements of the figures (Bahadoran, 2019):

• Figure number
• Figure title
• Figure legend (for example a brief title, experimental/statistical information, or definition of symbols).

Tables in the result section may contain several elements (Bahadoran, 2019):

• Table number
• Table title
• Row headings (for example groups)
• Column headings
• Row subheadings (for example categories or groups)
• Column subheadings (for example categories or variables)
• Footnotes (for example statistical analyses)

Tips to Write the Results Section

• Direct the reader to the research data and explain the meaning of the data.
• Avoid using a repetitive sentence structure to explain a new set of data.
• Write and highlight important findings in your results.
• Use the same order as the subheadings of the methods section.
• Match the results with the research questions from the introduction. Your results should answer your research questions.
• Be sure to mention the figures and tables in the body of your text.
• Make sure there is no mismatch between the table number or the figure number in text and in figure/tables.
• Only present data that support the significance of your study. You can provide additional data in tables and figures as supplementary material.

How to Organize the Discussion Section

It’s not enough to use figures and tables in your results section to convince your readers about the importance of your findings. You need to support your results section by providing more explanation in the discussion section about what you found.

In the discussion section, based on your findings, you defend the answers to your research questions and create arguments to support your conclusions.

Below is a list of questions to guide you when organizing the structure of your discussion section ( Viera et al ., 2018 ):

• What experiments did you conduct and what were the results?
• What do the results mean?
• What were the important results from your study?
• How did the results answer your research questions?
• Did your results support your hypothesis or reject your hypothesis?
• What are the variables or factors that might affect your results?
• What were the strengths and limitations of your study?
• What other published works support your findings?
• What other published works contradict your findings?
• What possible factors might cause your findings different from other findings?
• What is the significance of your research?
• What are new research questions to explore based on your findings?

Organizing the Discussion Section

The structure of the discussion section may be different from one paper to another, but it commonly has a beginning, middle-, and end- to the section.

One way to organize the structure of the discussion section is by dividing it into three parts (Ghasemi, 2019):

• The beginning: The first sentence of the first paragraph should state the importance and the new findings of your research. The first paragraph may also include answers to your research questions mentioned in your introduction section.
• The middle: The middle should contain the interpretations of the results to defend your answers, the strength of the study, the limitations of the study, and an update literature review that validates your findings.
• The end: The end concludes the study and the significance of your research.

Another possible way to organize the discussion section was proposed by Michael Docherty in British Medical Journal: is by using this structure ( Docherty, 1999 ):

• Discussion of important findings
• Comparison of your results with other published works
• Include the strengths and limitations of the study
• Conclusion and possible implications of your study, including the significance of your study – address why and how is it meaningful
• Future research questions based on your findings

Finally, a last option is structuring your discussion this way (Hofmann, 2013, pg. 104):

• First Paragraph: Provide an interpretation based on your key findings. Then support your interpretation with evidence.
• Secondary results
• Limitations
• Unexpected findings
• Comparisons to previous publications
• Last Paragraph: The last paragraph should provide a summarization (conclusion) along with detailing the significance, implications and potential next steps.

Remember, at the heart of the discussion section is presenting an interpretation of your major findings.

Tips to Write the Discussion Section

• Highlight the significance of your findings
• Mention how the study will fill a gap in knowledge.
• Indicate the implication of your research.
• Avoid generalizing, misinterpreting your results, drawing a conclusion with no supportive findings from your results.

Aggarwal, R., & Sahni, P. (2018). The Results Section. In Reporting and Publishing Research in the Biomedical Sciences (pp. 21-38): Springer.

Bahadoran, Z., Mirmiran, P., Zadeh-Vakili, A., Hosseinpanah, F., & Ghasemi, A. (2019). The principles of biomedical scientific writing: Results. International journal of endocrinology and metabolism, 17(2).

Bordage, G. (2001). Reasons reviewers reject and accept manuscripts: the strengths and weaknesses in medical education reports. Academic medicine, 76(9), 889-896.

Cals, J. W., & Kotz, D. (2013). Effective writing and publishing scientific papers, part VI: discussion. Journal of clinical epidemiology, 66(10), 1064.

Docherty, M., & Smith, R. (1999). The case for structuring the discussion of scientific papers: Much the same as that for structuring abstracts. In: British Medical Journal Publishing Group.

Faber, J. (2017). Writing scientific manuscripts: most common mistakes. Dental press journal of orthodontics, 22(5), 113-117.

Fletcher, R. H., & Fletcher, S. W. (2018). The discussion section. In Reporting and Publishing Research in the Biomedical Sciences (pp. 39-48): Springer.

Ghasemi, A., Bahadoran, Z., Mirmiran, P., Hosseinpanah, F., Shiva, N., & Zadeh-Vakili, A. (2019). The Principles of Biomedical Scientific Writing: Discussion. International journal of endocrinology and metabolism, 17(3).

Hofmann, A. H. (2013). Writing in the biological sciences: a comprehensive resource for scientific communication . New York: Oxford University Press.

Kotz, D., & Cals, J. W. (2013). Effective writing and publishing scientific papers, part V: results. Journal of clinical epidemiology, 66(9), 945.

Mack, C. (2014). How to Write a Good Scientific Paper: Structure and Organization. Journal of Micro/ Nanolithography, MEMS, and MOEMS, 13. doi:10.1117/1.JMM.13.4.040101

Moore, A. (2016). What's in a Discussion section? Exploiting 2‐dimensionality in the online world…. Bioessays, 38(12), 1185-1185.

Peat, J., Elliott, E., Baur, L., & Keena, V. (2013). Scientific writing: easy when you know how: John Wiley & Sons.

Sandercock, P. M. L. (2012). How to write and publish a scientific article. Canadian Society of Forensic Science Journal, 45(1), 1-5.

Teo, E. K. (2016). Effective Medical Writing: The Write Way to Get Published. Singapore Medical Journal, 57(9), 523-523. doi:10.11622/smedj.2016156

Van Way III, C. W. (2007). Writing a scientific paper. Nutrition in Clinical Practice, 22(6), 636-640.

Vieira, R. F., Lima, R. C. d., & Mizubuti, E. S. G. (2019). How to write the discussion section of a scientific article. Acta Scientiarum. Agronomy, 41.

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Guide on How to Write the Results Section of a Dissertation

The dissertation results chapter can be written once data has been collected and analyzed. In this section, the main findings of the research are reported and their relation to hypotheses or research questions are observed briefly. This chapter is among the most crucial parts of a study. It is here that statistical analysis is accurately performed, findings reported and explained, and assumptions examined. After this analysis, results are presented in a manner that shows non-support or support of the stated hypothesis.

Writing a thesis results section requires statistical expertise to present and defend the findings effectively. What’s more, the core findings should be presented logically without interpretation or bias from the writer. This section should set up the read for evaluation or interpretation of the findings in the discussion chapter .

When writing the thesis results chapter, the author should break down the findings into simple sentences. Essentially, this section should tell readers what the author found in the research.

What to Include in the Dissertation Results Chapter

The results chapter of a dissertation should include the core findings of a study. Essentially, only the findings of a specific study should be included in this section. These include:

• Data presented in graphs, tables, charts, and figures
• Data collection recruitment, collection, and/or participants
• Secondary findings like subgroup analyses and secondary outcomes
• Contextual data analysis and explanation of the meaning
• Information that corresponds to research questions

It’s crucial to consider the scope of your research when writing up dissertation results. That’s because a study with many variables or a broader scope can yield different results. In that case, only the most relevant results should be stated. Any data that doesn’t present direct outcomes or findings of a study should not be included in this section.

What are the Five Chapters of a Dissertation?

Traditionally, a dissertation has five major chapters. The results section is one of the most important chapters because it summarizes and presents the collected and analyzed data. The major chapters of this paper are:

• Introduction
• Literature review
• Methodology

The methodology section can vary depending on whether the author conducted qualitative research or quantitative research or a mixed study. However, the methodology section is also very important because the used methods can influence how the gathered results will be presented. For instance, you can use a questionnaire to gather information. If you don’t know how to analyze questionnaire results dissertation paper might not impress your readers. Therefore, choose your research methods wisely to make writing the findings or results section easier.

How to Write a Dissertation Results Chapter

Every research project is unique. As such, learners should not take a one-size-fits-all approach when writing results for a dissertation. The layout and content of this chapter should be determined by your research area, study design, and the chosen methodologies. Also, consider the target journal guidelines and editors.

But, when writing the results section dissertation authors can follow certain steps, especially for scientific studies. Those steps are as follows.

• Check the Target Journal’s Instructions or GuidelinesDifferent journals outline the requirements, instructions, or guidelines that authors should follow when writing the findings or results section. A journal can also provide a dissertation results section example to guide authors. It’s crucial that you note the content length limitations, scope, and aims that the journal requires dissertation authors to consider.
• Consider How Your Results Relate to the Catalogue and Requirements of the JournalConsider your findings or experimental results that are relevant to the research objectives or questions. Include even the findings that don’t support your hypothesis or are unexpected. Also, catalog the findings of your research using subheadings to clarify and streamline your report. That way, you can avoid peripheral and excessive details and make your findings easy to understand.It’s important to decide on the results structure. For instance, you can match the hypothesis or research questions to the results. You can also arrange them the way they are ordered in your Methods section. Alternatively, use the importance hierarchy or chronological order. Most importantly, consider your evidence, audience, and objectives of the study when deciding on the dissertation structure for the results section.
• Design Tables and Figures for Illustrating Your DataNumber your figures and tables in the order that you use to mention them in main the paper text. Make sure that your figures have self-explanatory information. Also, include the necessary information, such as definitions in the design to make the findings data easy to understand. Essentially, readers should understand your tables and figures without reading the text.Additionally, make your figures and tables the focal point of this section. Ensure that they tell an informative and clear story about the study without repetition. However, always remember that figures should enhance and clarify your text, not replace it.

Checklist for the Results Chapter

Once you have written this section, go through it carefully to ensure the following:

• All findings that are relevant to the research questions have been included.
• Each result has been reported objectively and concisely, including relevant inferential statistics and descriptive statistics.
• You have stated whether the study findings refuted or supported every hypothesis.
• You have used figures and tables to illustrate your results appropriately.
• All figures and tables are referred to and labeled correctly in the text.
• The presented results do not include speculations or subjective interpretation

You may come across many tips on how to write the results section of a dissertation. However, the most important tip is to ensure that the results that you present in this section are relevant to your study questions or hypotheses. If this sounds too complicated, you can ask us “ do my thesis for me “, and we’ll take care of it. Anyways, you have to remember that relevance is the most important thing regardless of whether the results support or do not support the hypotheses. Also, decide on the order to use when presenting the results of your study. This is very important because it makes it easier for your readers to understand them. Including figures, tables, and graphs makes the information in this section easier to understand.

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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?

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Research Results Template

The fastest (and smartest) way to craft a strong results section for your dissertation, thesis or research project.

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What It Covers

This template covers all the core components required in the results chapter of a typical dissertation, thesis or research project:

• The opening /overview section
• The body section for qualitative studies
• The body section for quantitative studies
• Concluding summary

The purpose of each section is explained in plain language, followed by an overview of the key elements that you need to cover. The template also includes practical examples to help you understand exactly what’s required, along with links to additional free resources (articles, videos, etc.) to help you along your research journey.

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Writing up the results section of your dissertation

(Last updated: 12 May 2021)

Since 2006, Oxbridge Essays has been the UK’s leading paid essay-writing and dissertation service

We have helped 10,000s of undergraduate, Masters and PhD students to maximise their grades in essays, dissertations, model-exam answers, applications and other materials. If you would like a free chat about your project with one of our UK staff, then please just reach out on one of the methods below.

When asked why doing a dissertation can be such a headache, the typical student usually replies with one of two answers. Either, they simply don't like writing enormous volumes of text, or – and you may relate here – they categorically do not enjoy analysing data. "It's so long and boring!", the typical student wails.

Well, students wail, and we answer. We have put together this very comprehensive, very useful guide on how to write up the results section of your dissertation. To help you further, we've broken the information down into both quantitative and qualitative results, so you can focus on what applies to you most.

Writing up your quantitative results

Understanding the basics of your research.

First, you need to recall what you have assessed – or what your main variables are.

All quantitative research has at least one independent and one dependent variable, and, at this point, you should define them explicitly. An independent variable is one that you control to test its effects on the dependent variable. A dependent variable is thus your outcome variable.

Second, you need to determine if your variables were categorical or continuous.

A categorical variable is one with a fixed number of possible values, and a continuous variable is one where final scores have a wide range. Finally, you need to recall if you have used a so-called covariate or confounder variable. This is a variable that could have influenced the relationship between your independent and dependent variable, and that you controlled in order to accurately estimate the relationship between your main variables.

Let’s explain all this with an example. Suppose that your research was to assess whether height is associated with self-esteem. Here, participants’ height is an independent variable and self-esteem is a dependent variable. Because both height and scores on a measure of self-esteem can have a wide range, you have two continuous variables. You might have also wanted to see if the relationship between height and self-esteem exists after controlling for participants’ weight. In this case, weight is a confounding variable that you need to control for.

Here is another example. You might have assessed whether more females than males want to read a specific romantic novel. Here, your independent variable is gender and your dependent variable is the determination to read the book. Since gender has categories (male and female), this is a categorical variable. If you have assessed the determination to read the book on a scale from 1 to 10 (e.g. 1 = no determination at all to read the book, all the way to 10 = extremely strong determination to read it), then this is a continuous variable; however, if you have asked your participants to say whether they do or do not want to read the book, then this is a categorical variable (since there are two categories: “yes” and “no”).

Lastly, you might have wanted to see if the link between gender and the determination to read the book exists after controlling for participants’ current relationship status. Here, relationship status is your confounding variable.

We will return to these examples throughout this blog post. At this point, it is important to remember that outlining your research in this way helps you to write up your results section in the easiest way possible.

Let’s move on to the next step.

Outlining descriptive and frequencies statistics

In order to report descriptive and/or frequencies statistics, you need to outline all variables that you have used in your research and note whether those variables are continuous or categorical.

For continuous variables, you are using descriptive statistics and reporting the measures of central tendency (mean) and measures of variability or spread (standard deviation). For categorical variables, you are using frequencies statistics and reporting the number (or frequency) of participants per category and associated percentages. Both these statistics require you to make a table, and in both cases you also need to comment upon the statistics.

How does all of this look in practice? Recall the two examples that were outlined above. If you have assessed the association between participants’ height and self-esteem, while controlling for participants’ weight, then your research consists of three continuous variables. You need to make a table, as in TABLE 1 below, which identifies means and standard deviations for all these variables. When commenting upon the results, you can say:

Participants were on average 173.50 cm tall (SD = 5.81) and their mean weight was 65.31 kg (SD = 4.44). On average, participants had moderate levels of self-esteem (M = 5.55, SD = 2.67).

Note that, in this example, you are concluding that participants had moderate self-esteem levels if their self-esteem was assessed on a 1 to 10 scale. Since the value of 5 falls within the middle of this range, you are concluding that the mean value of self-esteem is moderate. If the mean value was higher (e.g., M = 8.33), you would conclude that participants’ self-esteem was, on average, high; and if the mean value was lower (e.g., M = 2.44), you would conclude that average self-esteem scores were low.

TABLE 1. Descriptive statistics for all variables used in research:

Let’s now return to our second research example and say that you want to report the degree to which males and females want to read a romantic novel, where this determination was assessed on a 1-10 (continuous) scale. This would look as shown in TABLE 2.

TABLE 2. Descriptive statistics for the determination to read the book, by gender:

We can see how to report frequencies statistics for different groups by referring to our second example about gender, determination to read a romantic novel, and participants’ relationship status.

Here, you have three categorical variables (if determination to read the novel was assessed by having participants reply with “yes” or “no”). Thus, you are not reporting means and standard deviations, but frequencies and percentages.

To put this another way, you are noting how many males versus females wanted to read the book and how many of them were in a relationship, as shown in TABLE 3. You can report these statistics in this way:

Twenty (40%) male participants wanted to read the book and 35 (70%) female participants wanted to read the book. Moreover, 22 (44%) males and 26 (52%) females indicated that they are currently in a relationship.

TABLE 3. Frequencies statistics for all variables used in research:

Reporting the results of a correlation analysis

The first of these is correlation, which you use when you want to establish if one or more (continuous, independent) variables relate to another (continuous, dependent) variable. For instance, you may want to see if participants’ height correlates with their self-esteem levels.

The first step here is to report whether your variables are normally distributed. You do this by looking at a histogram that describes your data. If the histogram has a bell-shaped curve (see purple graph below), your data is normally distributed and you need to rely on a Pearson correlation analysis. Here, you need to report the obtained r value (correlation coefficient) and p value (which needs to be lower than .05 in order to establish significance). If you find a correlation, you need to say something like:

The results of the Pearson correlation analysis revealed that there was a positive correlation between people’s height and their self-esteem levels ( r = .44, p < .001).

One final thing to note, which is important for all analyses, is that when your p value is indicated to be .000, you never report it by saying “ p = .000”, but by noting “ p p = .011”.

If your data is skewed rather than normally distributed (see red graphs), then you need to rely on a Spearman correlation analysis. Here, you report the results by saying:

Spearman correlation analysis revealed a positive relationship between people’s height and their self-esteem (r s = .44, p There has been a significant positive correlation between height and self-esteem after controlling for participants’ weight ( r = .39, p = .034).

You also need to make a table that will summarise your main results. If you didn’t use a covariate, you will have a fairly simple table, such as that shown in TABLE 4. If you have used a covariate, your table is slightly more complex, such as that shown in TABLE 5. Note that both tables use “-” to indicate correlations that have already been noted within the table. Also note how “*”, “**”, and “***” are used to annotate correlations that are significant at different levels.

TABLE 4. Correlations between all variables used in research:

Reporting the results of a regression

These are the specific points that you need to address in order to make sure that all assumptions have been met:

(1) for the assumption of no multicollinearity (i.e., a lack of high correlation between your independent variables), you need to establish that none of your Tolerance statistics are below .01 and none of the VIF statistics are above 10;

(2) for the assumption of no autocorrelation of residuals (i.e., a lack of correlation between the residuals of two observations), you need to look at this table and see whether your Durbin-Watson statistic falls within a desirable range, depending on your number of participants and the number of predictors (independent variables); and,

(3) for the assumptions of linearity (i.e., a linear relationship between independent and dependent variables) and homoscedasticity (i.e., a variance of error terms that should be similar across the independent variables), you need to look at the scatterplot of standardised residual on standardised predicted value and conclude that your graph doesn’t funnel out or curve.

All of this may sound quite complex. But in reality it is not: you just need to look at your results output to note the Tolerance and VIF values, Durbin-Watson value, and the scatterplot. Once you conclude that your assumptions have been met, you write something like:

Since none of the VIF values were below 0.1 and none of the Tolerance values were above 10, the assumption of no multicollinearity has been met. Durbin-Watson statistics fell within an expected range, thus indicating that the assumption of no autocorrelation of residuals has been met as well. Finally, the scatterplot of standardised residual on standardised predicted value did not funnel out or curve, and thus the assumptions of linearity and homoscedasticity have been met as well.

If your assumptions have not been met, you need to dig a bit deeper and understand what this means. A good idea would be to read the chapter on regression (and especially the part about assumptions) written by Andy Field. You can access his book here . This will help you understand all you need to know about the assumptions of a regression analysis, how to test them, and what to do if they have not been met.

Now let’s focus on reporting the results of the actual regression analysis. Let’s say that you wanted to see if participants’ height predicts their self-esteem, after controlling for participants’ weight. You have entered height and weight as predictors in the model and self-esteem as a dependent variable.

First, you need to report whether the model reached significance in predicting self-esteem scores. Look at the results of an ANOVA analysis in your output and note the F value, degrees of freedom for the model and for residuals, and significance level. These values are shown in PICTURE 2.

PICTURE 2. Results of ANOVA for regression:

PICTURE 3. Model summary for regression:

Significance value tells you if your predictor reached significance – such as whether participants’ height predicted self-esteem scores. You also need to comment upon the β value. This value represents the change in the outcome associated with a unit change in the predictor . Thus, if your β value is .351 for participants’ height (predictor/independent variable), then this means that for every increase in height by 1 cm, self-esteem increases by .35. You need to report the same thing for your other predictor – that is, participants’ weight.

Finally, since your model included both height and weight as predictors, and height acted as a significant predictor, you can conclude that participants’ height influences their self-esteem after controlling for weight.

PICTURE 4. Regression coefficients:

The model reached significance, meaning that it successfully predicted self-esteem scores (F (1,40) = 99.59, p The model explained 33.5% of variance in self-esteem scores. Participants’ self-esteem was predicted by their weight (β = .35, t = -8.13, p For every increase in weight by 1 kg, self-esteem decreased by 35. Participants’ self-esteem was also predicted by their height (β = .58, t = 17.80, p after controlling for their weight. For every increase in height by 1 cm, self-esteem increased by .58.

Reporting the results of a chi-square analysis

For instance, you would do a chi-square analysis when you want to see whether gender (categorical independent variable with two levels: males/females) affects the determination to read a book, when this variable is measured with yes/no answers (categorical dependent variable with two levels: yes/no).

When reporting your results, you should first make a table as shown in TABLE 3 above. Then you need to report the results of a chi-square test, by noting the Pearson chi-square value, degrees of freedom, and significance value. You can see all these in your output.

Finally, you need to report the strength of the association, for which you need to look at the Phi and Cramer’s V values. When each of your variables has only two categories, as in the present example, Phi and Cramer’s V values are identical and it doesn’t matter which one you will report. However, when one of your variables has more than two categories, it is better to report the Cramer’s V value. You report these values by indicating the actual value and the associated significance level.

Note that Cramer’s V value can range from 0 to 1. The closer the value is to 1, the higher the strength of the association. You can report the results of the chi-square analysis in the following way:

There was a significant association between gender and the determination to read the romantic novel (x 2 (1) = 25.36, p Cramer’s V value was significant (Cramer’s V = .75, p and it indicated a high strength of the association.

Reporting the results of a t-test analysis

Recall that you have previously outlined descriptive statistics for these variables, where you have noted means and standard deviations for males’ and females’ scores on the determination to read the novel (see TABLE 2 above). Now you need to report the obtained t value, degrees of freedom, and significance level – all of which you can see in your results output.

You can say something like:

Males reported a lower determination to read the novel (M = 3.20, SD = .43) when compared to females (M = 6.33, SD = 1.36). The results of a t-test analysis revealed that this difference reached significance (t (54) = 4.47, p < .001).

Reporting the results of one-way ANOVA

In the t-test example, you had two conditions of a categorical independent variable, which corresponded to whether a participant was male or female. You would have three conditions of an independent variable when assessing whether relationship status (independent variable with three levels: single, in a relationship, and divorced) affects the determination to read a romantic novel (as assessed on a 1-10 scale).

Here, you would report the results in a similar manner to that of a t -test. You first report the means and standard deviations on the determination to read the book for all three groups of participants, by saying who had the highest and lowest mean. Then you report the results of the ANOVA test by reporting the F value, degrees of freedom (for within-subjects and between-subjects comparisons), and the significance value.

There are two things to note here. First, before reporting your results, you need to look at your output to see whether the so-called Levene’s test is significant. This test assesses the homogeneity of variance – the assumption being that all comparison groups should have the same variance. If the test is non-significant, the assumption has been met and you are reporting the standard F value.

However, if the test is significant, the assumption has been violated and you need to report instead the Welch statistic, associated degrees of freedom, and significance value (which you will see in your output; for example, see PICTURE 3 above).

The second thing to note is that ANOVA tells you only whether there were significant differences between groups – but if there are differences, it doesn’t tell you where these differences lie. For this, you need to conduct a post-hoc comparison (Tukey’s HSD test). The output will tell you which comparisons are significant.

You can report your results in the following manner:

Single participants were most determined to read the book (M = 7.11, SD = .45), followed by divorced participants (M = 5.11, SD = .55) and participants who are in a relationship (M = 4.95, SD = .44). ANOVA revealed significant between-groups differences (F (2,12) = 5.12, p = .004). Post-hoc comparisons revealed that significant differences occurred between participants who were single and in a relationship ( p = .003) and between single and divorced participants ( p = .004). There were no significant differences between divorced and in-a-relationship participants (p = .067).

Reporting the results of ANCOVA

For instance, you will use ANCOVA when you want to test whether relationship status (categorical independent variable with three levels: single, in a relationship, divorced) affects the determination to read a romantic novel (continuous dependent variable, assessed on a 1-10 scale) after controlling for participants’ general interest in books (continuous covariate, assessed on a 1-10 scale).

To report the results, you need to look at the “test of between-subjects effects” table in your output. You need to report the F values, degrees of freedom (for each variable and error), and significance values for both the covariate and the main independent variable. As with ANOVA, a significant ANCOVA doesn’t tell you where the differences lie. For this, you need to conduct planned contrasts and report the associated significance values for different comparisons.

You can report the results in the following manner:

The covariate, general interest in books, was significantly related to the determination to read the romantic novel (F (1,26) = 4.96, p There was also a significant effect of relationship status on the determination to read the romantic novel, after controlling for the effect of the general interest in books (F (2,26) = 4.14, p Planned contrasts revealed that being single significantly increased the determination to read the book when compared to being in a relationship (t (26) = 2.77, p = .004) and when compared to being divorced (t (26) = 1.89, p = .003).

Reporting the results of MANOVA

For instance, you would use MANOVA when testing whether male versus female participants (independent variable) show a different determination to read a romantic novel (dependent variable) and a determination to read a crime novel (dependent variable).

When reporting the results, you first need to notice whether the so-called Box’s test and Levene’s test are significant. These tests assess two assumptions: that there is an equality of covariance matrices (Box’s test) and that there is an equality of variances for each dependent variable (Levene’s test).

Both tests need to be non-significant in order to assess whether your assumptions are met. If the tests are significant, you need to dig deeper and understand what this means. Once again, you may find it helpful to read the chapter by Andy Field on MANOVA, which can be accessed here .

Following this, you need to report your descriptive statistics, as outlined previously. Here, you are reporting the means and standard deviations for each dependent variable, separately for each group of participants. Then you need to look at the results of “multivariate analyses”.

You will notice that you are presented with four statistic values and associated F and significance values. These are labelled as Pillai’s Trace, Wilks’ Lambda, Hotelling’s Trace, and Roy’s Largest Root. These statistics test whether your independent variable has an effect on the dependent variables. The most common practice is to report only the Pillai’s Trace. You report the results in the same manner as reporting ANOVA, by noting the F value, degrees of freedom (for hypothesis and error), and significance value.

However, you also need to report the statistic value of one of the four statistics mentioned above. You can label the Pillai’s Trace statistic with V, the Wilks’ Lambda statistic with A, the Hotelling’s Trace statistic with T, and Roy’s Largest Root statistic with Θ (but you need report only one of them).

Finally, you need to look at the results of the Tests of Between-Subjects Effects (which you will see in your output). These tests tell you how your independent variable affected each dependent variable separately. You report these results in exactly the same way as in ANOVA.

Here’s how you can report all results from MANOVA:

Males were less determined to read the romantic novel (M = 4.11, SD = .58) when compared to females (M = 7.11, SD = .43). Males were also more determined to read the crime novel (M = 8.12. SD = .55) than females (M = 5.22, SD = .49). Using Pillai’s Trace, there was a significant effect of gender on the determination to read the romantic and crime novel (V = 0.32, F (4,54) = 2.56, p = .004). Separate univariate ANOVAs on the outcome variables revealed that gender had a significant effect on both the determination to read the romantic novel (F (2,27) = 9.73, p = .003) and the determination to read the crime novel (F (2,27) = 5.23, p = .038).

Writing up your qualitative results

Before reporting the results of your qualitative research, you need to recall what type of research you have conducted. The most common types of qualitative research are interviews, observations, and focus groups – and your research is likely to fall into one of these types.

All three types of research are reported in a similar manner. Still, it may be useful if we focus on each of them separately.

Reporting the results of interviews

For example, let’s say that your qualitative research focused on young people’s reasons for smoking. You have asked your participants questions that explored why they started smoking, why they continue to smoke, and why they wish to quit smoking. Since your research was organised in this manner, you already have three major themes: (1) reasons for starting to smoke, (2) reasons for continuing to smoke, and (3) reasons for quitting smoking. You then explore particular reasons why your participants started to smoke, why they continue to smoke, and why they want to quit. Each reason that you identify will act as a subtheme.

When reporting the results, you should organise your text in subsections. Each section should refer to one theme. Then, within each section, you need to discuss the subthemes that you discovered in your data.

Let’s say that you found that young people started smoking because: (1) they thought smoking was cool, (2) they experienced peer pressure, (3) their parents modelled smoking behaviour, (4) they thought smoking reduces stress, and (5) they wanted to try something new. Now you have five subthemes within your “reasons for starting to smoke” theme. What you need to do now is to present the findings for each subtheme, while also reporting quotes that best describe your subtheme. You do that for each theme and subtheme.

It is also good practice to make a table that lists all your themes, subthemes, and associated quotes.

Here’s an example of how to report a quote within a text:

Several participants noted that they started smoking because they thought smoking was cool. One participant said: “I was only 15 at the time and I was looking at these older boys whom everybody considered as cool. I was shy and I always wanted to be more noticed. So I thought that, if I start smoking, I will be more like these older boys” (interview 1, male).

Reporting the results of observations

For instance, you might have noticed that the therapist finds it important to discuss: (1) the origin of the problem, (2) the lack of a patient’s medical difficulties, (3) the experience of stress, (4) the link of stress to the problem, and (5) the new understanding of the problem. You can consider these as themes in your observations.

Accordingly, you will want to report each theme separately. You do this by outlining your observation first (this can be a conversation or a behaviour that you observed), and then commenting upon it.

Here’s an example:

Therapist: Was there something that stressed you out during the last few months?

Patient: Yes, of course. I thought I would lose my job, but that passed. After that, I was breaking up with my girlfriend. But between those things, I was fine.

Therapist: And was there any difference in your symptoms while you were and while you were not stressed?

Patient: Hmmm. Actually yes. Now that I think of it, they were mostly present when I went through those periods.

Therapist: Could it be that stress intensifies your symptoms?

Patient: I never thought of it. I guess it seems logical. Is it?

In this example, the therapist has tried to make a connection between the patient’s symptoms and stress. She did not explicitly tell the patient “your symptoms are caused by stress”. Instead, she has guided him, through questions, to connect his symptoms to stress. This seems beneficial because the patient has arrived at the link between stress and symptoms himself.

Reporting the results of focus groups

As an example, let’s say that your focus group dealt with identifying reasons why some people prefer Coca-Cola over Schweppes, and vice versa. You have transcribed your focus group sessions and have extracted themes from the data. You have discovered a wide variety of reasons why people prefer one of the two drinks.

When reporting your results, you should have two sections: one listing reasons for favouring Coca-Cola, and the other listing reasons for favouring Schweppes. Within each section, you need to identify specific reasons for these preferences. You should connect these specific reasons to particular quotes.

Here’s an example of how this may look:

The first reason why some participants favoured Schweppes over Coca-Cola is that Schweppes is considered as less sweet. Several participants agreed on this notion. One said: “I don’t like Coca-Cola because it is simply too sweet. Schweppes has a much more bitter taste, and I don’t feel like I am getting stuffed with sugar” (participant 2, female). Another participant agreed by noting: “I completely agree with what she said. Because Coca-Cola is sweet, I feel like I have taken a candy, and this doesn’t refresh me. A glass of cold Schweppes is much more refreshing. I don’t feel like needing water after it” (participant 4, male).

In conclusion…

As we have seen, writing up qualitative results is easier than writing quantitative results. Yet, even reporting statistics is not that hard, especially if you have a good guide to help you.

Hopefully, this guide has reduced your worries and increased your confidence that you can write up the results section of your dissertation without too many difficulties.

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Degree In Sight

Writing up your results

Be open to surprising findings, but don't lose track of your dissertation's main research questions, experts advise.

By ETIENNE S. BENSON

If you wait until you finish data collection to start thinking about your analysis, you've waited too long, says Randy Larsen, PhD, head of the psychology department at Washington University in St. Louis. Rather, before you begin, establish a "road map" that matches your hypotheses to specific analyses that will best test those hypotheses, he recommends. Moreover, try to meet with your dissertation committee to go over the road map, even if your department doesn't require it.

When presenting complex relationships or numerous variables, a good chart, table or graph can make all the difference.

Not having a road map--and failing to tap the resources you have--are among the common pitfalls students face in finishing their dissertations. Some students get hung up on data analysis, struggling with complex statistical procedures or wasting time on analyses that are tangential to their main research questions. Others have difficulty writing up their analyses in a clear and concise manner that meets professional standards.

The good news is that there are resources that can help you resolve such issues. From statistics workshops to style guides, such resources can help you get your dissertation done on schedule.

After all, says Larsen, "A dissertation is a project; it's got to have an end."

STATISTICALLY SPEAKING

One of the trickiest dissertation challenges is sorting out your data. For particularly thorny statistical challenges, the expertise you need may not be available in your home department. Karen Kaczynski, a fifth-year doctoral student at the University of Miami, began planning a dissertation on gender differences in substance abuse among inner-city Hispanic-American adolescents. Although she was familiar with longitudinal data-analysis techniques, she worried that they might not be appropriate for her small sample size of 20 female participants.

So, she attended several workshops, including the APA-sponsored Advanced Training Institute on longitudinal methods, supervised by Jack McArdle, PhD, a professor of psychology at the University of Virginia.

"I was able to ask him specifically about my concerns with using complex analytic techniques with a limited sample size," says Kaczynski. "It was really wonderful to be able to discuss my analyses with someone with his expertise." Back at her home department, she refined her analysis with the help of Maria Llabre, PhD, her department's resident statistics expert.

If you plan to continue in academia after your doctorate, delving into the details of complex statistical methods can be a wise investment, experts say. For her dissertation at Washington University, Nicole Speer, PhD, studied event perception using behavioral measures and functional brain imaging. She says that learning logistic regression, Monte Carlo simulations, brain-imaging analysis and other techniques--with the help of her adviser, other faculty members and fellow students--was well worth the effort.

"Even though it definitely ends up taking you more time to learn, in the long run it's really worth it because if you're continuing in research, you'll most likely be using similar techniques in the future," says Speer.

For computationally intensive analyses, invest in--or have access to--the hardware and software you need. Speer used an APA dissertation grant to buy a powerful computer that shaved weeks off her data analysis, she says. Even so, the analysis took three or four months longer than she had anticipated, in part because she expanded her original plans to address new questions that arose after her data were collected--a move her adviser Jeffrey Zacks, PhD, supported.

"Many data are expensive, so spending time to really digest a dataset is often a wise investment," says Zacks. As Sharon Foster, PhD, and John Cone, PhD, point out in "Dissertations and Theses From Start to Finish" (APA, 1993), adventitious findings are sometimes the most interesting ones.

At the same time, graduate students often lose valuable time exploring issues that are tangential to their main interests, says Larsen. While such meanderings can lead to real breakthroughs, graduate school may not be the ideal time to pursue them. Conduct your planned analyses, write up your results and record unexpected findings for future exploration, suggests Larsen.

FORMAT AND DESIGN

While the results you report may be groundbreaking, the formatting you use should be anything but. Consult style guides and follow professional guidelines, advises Stephen Hinshaw, PhD, chair of the psychology department at the University of California, Berkeley. The fifth edition of the APA Style Manual (APA, 2001) details how to prepare the results section, format text and figures, organize your dissertation, and convert it to one or more journal articles. (Check with your department for local variations from APA style.)

That said, proper formatting can only do so much. The key to good data presentation is viable, testable hypotheses, says Hinshaw. "If these are well-specified, and if a coherent data analytic plan is conceptualized and written," he explains, "the data analyses should be relatively straightforward."

When presenting complex relationships or numerous variables, a good chart, table or graph can make all the difference. For guidance on how to pick the right graphic, Zacks recommends psychologically informed books such as Stephen Kosslyn's "Elements of Graph Design" (W.H. Freeman, 1994) and William Cleveland's "The Elements of Graphing Data" (AT&T Bell Laboratories, 1994). More than just effective means of presenting your results, plots can also help you understand your own data, adds Hinshaw.

Not all psychological studies depend on quantitative measurements and statistical significance tests. For the results sections of qualitative studies, careful description and contextualization are most important, says Sue Morrow, PhD, an associate professor of counseling psychology at the University of Utah. As in quantitative studies, charts and graphs can make your results easier for readers to grasp.

Because qualitative methods tend to be less familiar to readers than quantitative methods, as well as harder to summarize with charts or statistics, one of the biggest challenges is conveying your data in a way that readers will understand. To build trust in your analysis, Morrow recommends keeping your results section separate from your discussion, as in quantitative studies, so that readers can distinguish "data-based interpretations" from your own conclusions.

STAY FOCUSED

While complex analyses and formatting guidelines can seem like formidable barriers to writing up your results, nonacademic factors sometimes pose even greater challenges. At this stage in your graduate career, you may have to contend with romantic breakups, family crises and the stresses of finding a job and planning a move--not to mention the ever-present temptation to procrastinate. With all of these distractions, it's important to keeping moving toward the finish line, says Larsen.

Amy L. Conrad, PhD, recently completed her doctorate in counseling psychology at the University of Iowa. When it came time to write up the results of her study on summer camps for children with cancer, she was also finishing her predoctoral internship, applying for postdocs and in her third trimester of pregnancy.

"I knew that it would be extremely difficult to get any work done after my daughter was born, and I wanted to have guilt-free time to enjoy my maternity leave," says Conrad. With the help of strict goal deadlines, constructive feedback and a lot of late-night milkshakes, she says, she finished and defended her dissertation two weeks before her daughter was born.

Etienne Benson is a writer in Cambridge, Mass.

The dissertation, start to finish

This article is the fourth in a six-part gradPSYCH guide to starting, researching, writing and defending your dissertation.

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Home » Research Results Section – Writing Guide and Examples

Research Results Section – Writing Guide and Examples

Table of Contents

Research Results

Research results refer to the findings and conclusions derived from a systematic investigation or study conducted to answer a specific question or hypothesis. These results are typically presented in a written report or paper and can include various forms of data such as numerical data, qualitative data, statistics, charts, graphs, and visual aids.

Results Section in Research

The results section of the research paper presents the findings of the study. It is the part of the paper where the researcher reports the data collected during the study and analyzes it to draw conclusions.

In the results section, the researcher should describe the data that was collected, the statistical analysis performed, and the findings of the study. It is important to be objective and not interpret the data in this section. Instead, the researcher should report the data as accurately and objectively as possible.

Structure of Research Results Section

The structure of the research results section can vary depending on the type of research conducted, but in general, it should contain the following components:

• Introduction: The introduction should provide an overview of the study, its aims, and its research questions. It should also briefly explain the methodology used to conduct the study.
• Data presentation : This section presents the data collected during the study. It may include tables, graphs, or other visual aids to help readers better understand the data. The data presented should be organized in a logical and coherent way, with headings and subheadings used to help guide the reader.
• Data analysis: In this section, the data presented in the previous section are analyzed and interpreted. The statistical tests used to analyze the data should be clearly explained, and the results of the tests should be presented in a way that is easy to understand.
• Discussion of results : This section should provide an interpretation of the results of the study, including a discussion of any unexpected findings. The discussion should also address the study’s research questions and explain how the results contribute to the field of study.
• Limitations: This section should acknowledge any limitations of the study, such as sample size, data collection methods, or other factors that may have influenced the results.
• Conclusions: The conclusions should summarize the main findings of the study and provide a final interpretation of the results. The conclusions should also address the study’s research questions and explain how the results contribute to the field of study.
• Recommendations : This section may provide recommendations for future research based on the study’s findings. It may also suggest practical applications for the study’s results in real-world settings.

Outline of Research Results Section

The following is an outline of the key components typically included in the Results section:

I. Introduction

• A brief overview of the research objectives and hypotheses
• A statement of the research question

II. Descriptive statistics

• Summary statistics (e.g., mean, standard deviation) for each variable analyzed
• Frequencies and percentages for categorical variables

III. Inferential statistics

• Results of statistical analyses, including tests of hypotheses
• Tables or figures to display statistical results

IV. Effect sizes and confidence intervals

• Effect sizes (e.g., Cohen’s d, odds ratio) to quantify the strength of the relationship between variables
• Confidence intervals to estimate the range of plausible values for the effect size

V. Subgroup analyses

• Results of analyses that examined differences between subgroups (e.g., by gender, age, treatment group)

VI. Limitations and assumptions

• Discussion of any limitations of the study and potential sources of bias
• Assumptions made in the statistical analyses

VII. Conclusions

• A summary of the key findings and their implications
• A statement of whether the hypotheses were supported or not
• Suggestions for future research

Example of Research Results Section

An Example of a Research Results Section could be:

• This study sought to examine the relationship between sleep quality and academic performance in college students.
• Hypothesis : College students who report better sleep quality will have higher GPAs than those who report poor sleep quality.
• Methodology : Participants completed a survey about their sleep habits and academic performance.

II. Participants

• Participants were college students (N=200) from a mid-sized public university in the United States.
• The sample was evenly split by gender (50% female, 50% male) and predominantly white (85%).
• Participants were recruited through flyers and online advertisements.

III. Results

• Participants who reported better sleep quality had significantly higher GPAs (M=3.5, SD=0.5) than those who reported poor sleep quality (M=2.9, SD=0.6).
• See Table 1 for a summary of the results.
• Participants who reported consistent sleep schedules had higher GPAs than those with irregular sleep schedules.

IV. Discussion

• The results support the hypothesis that better sleep quality is associated with higher academic performance in college students.
• These findings have implications for college students, as prioritizing sleep could lead to better academic outcomes.
• Limitations of the study include self-reported data and the lack of control for other variables that could impact academic performance.

V. Conclusion

• College students who prioritize sleep may see a positive impact on their academic performance.
• These findings highlight the importance of sleep in academic success.
• Future research could explore interventions to improve sleep quality in college students.

Example of Research Results in Research Paper :

Our study aimed to compare the performance of three different machine learning algorithms (Random Forest, Support Vector Machine, and Neural Network) in predicting customer churn in a telecommunications company. We collected a dataset of 10,000 customer records, with 20 predictor variables and a binary churn outcome variable.

Our analysis revealed that all three algorithms performed well in predicting customer churn, with an overall accuracy of 85%. However, the Random Forest algorithm showed the highest accuracy (88%), followed by the Support Vector Machine (86%) and the Neural Network (84%).

Furthermore, we found that the most important predictor variables for customer churn were monthly charges, contract type, and tenure. Random Forest identified monthly charges as the most important variable, while Support Vector Machine and Neural Network identified contract type as the most important.

Overall, our results suggest that machine learning algorithms can be effective in predicting customer churn in a telecommunications company, and that Random Forest is the most accurate algorithm for this task.

Example 3 :

Title : The Impact of Social Media on Body Image and Self-Esteem

Abstract : This study aimed to investigate the relationship between social media use, body image, and self-esteem among young adults. A total of 200 participants were recruited from a university and completed self-report measures of social media use, body image satisfaction, and self-esteem.

Results: The results showed that social media use was significantly associated with body image dissatisfaction and lower self-esteem. Specifically, participants who reported spending more time on social media platforms had lower levels of body image satisfaction and self-esteem compared to those who reported less social media use. Moreover, the study found that comparing oneself to others on social media was a significant predictor of body image dissatisfaction and lower self-esteem.

Conclusion : These results suggest that social media use can have negative effects on body image satisfaction and self-esteem among young adults. It is important for individuals to be mindful of their social media use and to recognize the potential negative impact it can have on their mental health. Furthermore, interventions aimed at promoting positive body image and self-esteem should take into account the role of social media in shaping these attitudes and behaviors.

Importance of Research Results

Research results are important for several reasons, including:

• Advancing knowledge: Research results can contribute to the advancement of knowledge in a particular field, whether it be in science, technology, medicine, social sciences, or humanities.
• Developing theories: Research results can help to develop or modify existing theories and create new ones.
• Improving practices: Research results can inform and improve practices in various fields, such as education, healthcare, business, and public policy.
• Identifying problems and solutions: Research results can identify problems and provide solutions to complex issues in society, including issues related to health, environment, social justice, and economics.
• Validating claims : Research results can validate or refute claims made by individuals or groups in society, such as politicians, corporations, or activists.
• Providing evidence: Research results can provide evidence to support decision-making, policy-making, and resource allocation in various fields.

How to Write Results in A Research Paper

Here are some general guidelines on how to write results in a research paper:

• Organize the results section: Start by organizing the results section in a logical and coherent manner. Divide the section into subsections if necessary, based on the research questions or hypotheses.
• Present the findings: Present the findings in a clear and concise manner. Use tables, graphs, and figures to illustrate the data and make the presentation more engaging.
• Describe the data: Describe the data in detail, including the sample size, response rate, and any missing data. Provide relevant descriptive statistics such as means, standard deviations, and ranges.
• Interpret the findings: Interpret the findings in light of the research questions or hypotheses. Discuss the implications of the findings and the extent to which they support or contradict existing theories or previous research.
• Discuss the limitations : Discuss the limitations of the study, including any potential sources of bias or confounding factors that may have affected the results.
• Compare the results : Compare the results with those of previous studies or theoretical predictions. Discuss any similarities, differences, or inconsistencies.
• Avoid redundancy: Avoid repeating information that has already been presented in the introduction or methods sections. Instead, focus on presenting new and relevant information.
• Be objective: Be objective in presenting the results, avoiding any personal biases or interpretations.

When to Write Research Results

Here are situations When to Write Research Results”

• After conducting research on the chosen topic and obtaining relevant data, organize the findings in a structured format that accurately represents the information gathered.
• Once the data has been analyzed and interpreted, and conclusions have been drawn, begin the writing process.
• Before starting to write, ensure that the research results adhere to the guidelines and requirements of the intended audience, such as a scientific journal or academic conference.
• Begin by writing an abstract that briefly summarizes the research question, methodology, findings, and conclusions.
• Follow the abstract with an introduction that provides context for the research, explains its significance, and outlines the research question and objectives.
• The next section should be a literature review that provides an overview of existing research on the topic and highlights the gaps in knowledge that the current research seeks to address.
• The methodology section should provide a detailed explanation of the research design, including the sample size, data collection methods, and analytical techniques used.
• Present the research results in a clear and concise manner, using graphs, tables, and figures to illustrate the findings.
• Discuss the implications of the research results, including how they contribute to the existing body of knowledge on the topic and what further research is needed.
• Conclude the paper by summarizing the main findings, reiterating the significance of the research, and offering suggestions for future research.

Purpose of Research Results

The purposes of Research Results are as follows:

• Informing policy and practice: Research results can provide evidence-based information to inform policy decisions, such as in the fields of healthcare, education, and environmental regulation. They can also inform best practices in fields such as business, engineering, and social work.
• Addressing societal problems : Research results can be used to help address societal problems, such as reducing poverty, improving public health, and promoting social justice.
• Generating economic benefits : Research results can lead to the development of new products, services, and technologies that can create economic value and improve quality of life.
• Supporting academic and professional development : Research results can be used to support academic and professional development by providing opportunities for students, researchers, and practitioners to learn about new findings and methodologies in their field.
• Enhancing public understanding: Research results can help to educate the public about important issues and promote scientific literacy, leading to more informed decision-making and better public policy.
• Evaluating interventions: Research results can be used to evaluate the effectiveness of interventions, such as treatments, educational programs, and social policies. This can help to identify areas where improvements are needed and guide future interventions.
• Contributing to scientific progress: Research results can contribute to the advancement of science by providing new insights and discoveries that can lead to new theories, methods, and techniques.
• Informing decision-making : Research results can provide decision-makers with the information they need to make informed decisions. This can include decision-making at the individual, organizational, or governmental levels.
• Fostering collaboration : Research results can facilitate collaboration between researchers and practitioners, leading to new partnerships, interdisciplinary approaches, and innovative solutions to complex problems.

Advantages of Research Results

Some Advantages of Research Results are as follows:

• Improved decision-making: Research results can help inform decision-making in various fields, including medicine, business, and government. For example, research on the effectiveness of different treatments for a particular disease can help doctors make informed decisions about the best course of treatment for their patients.
• Innovation : Research results can lead to the development of new technologies, products, and services. For example, research on renewable energy sources can lead to the development of new and more efficient ways to harness renewable energy.
• Economic benefits: Research results can stimulate economic growth by providing new opportunities for businesses and entrepreneurs. For example, research on new materials or manufacturing techniques can lead to the development of new products and processes that can create new jobs and boost economic activity.
• Improved quality of life: Research results can contribute to improving the quality of life for individuals and society as a whole. For example, research on the causes of a particular disease can lead to the development of new treatments and cures, improving the health and well-being of millions of people.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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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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