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How to Write Dissertation Results Section

Posted on Thursday, June 27th, 2024. Last updated on Thursday, June 27th, 2024

How to Write Dissertation Results Section

Once you’ve written your research methodology, the next step is to write the dissertation results section. However, you cannot write this section without the data. So, you’ve to collect the appropriate data to address the research questions. After collecting and analyzing the data using the best statistical software, the next step is to write the results section of a dissertation. This article explains how to write the dissertation results section. Specifically, you’ll learn how to write and organize thesis results and the best practices for formatting the tables and figures.

What is the Dissertation Results Section?

The dissertation results section is a critical part of a dissertation or thesis that presents the results & findings of your research study. The main aim of the results and findings section is to implement the proposed data analysis methodology by performing the right statistical tests, describing the data collected, and reporting the results derived from the analysis. In other words, the thesis results section mainly focuses on presenting the factual outcomes of your study without interpreting their meaning or significance. The interpretation of the meaning and significance of the findings is mainly reserved for the discussion section.

What Should be Included in the Results Section of a Dissertation?

Are you done analyzing your dissertation data and wondering what to include in the results section? Here are some of the main components that should be included in your thesis results section:

  1. Presentation of Data Summary – You should present the summary of the data used in your analysis. This may involve using tables, figures, charts, or graphs to present the distributions and composition of the data.
  2. Statistical Analysis – If you adopted a quantitative research methodology, then you need to perform appropriate statistical analysis tests to address the research questions. You may need to perform descriptive statistics such as means, standard deviations, etc., or inferential statistics such as t-tests, chi-square tests, ANOVA tests, etc., to draw conclusions from the data.
  3. Findings – The results section of a dissertation also needs to include the key findings of the research in a clear and organized manner. In particular, it should thoroughly address the proposed research questions/hypotheses.
  4. Contextual Information – Based on the nature of the study, you may also include the demographic composition of the study and any other relevant information that enhances understanding of the findings.
  5. Negative or Unexpected Results: Transparency is key when it comes to dissertation writing. So, you should include any unexpected or negative results alongside the positive results. This helps to provide valuable insights into the limitations of the study.

What should Not Be Included in a Thesis Results Section?

When writing a thesis results section, it is important to be concise and precise when presenting the findings. In other words, you should avoid certain pitfalls that can detract from the clarity and effectiveness of your presentation. Below are some things that you should avoid when writing the results and findings section of a dissertation:

  1. Do not include interpretations or discussions about the meaning or implications of the findings. Instead, save interpretations for the discussion section of your dissertation.
  2. Avoid introducing new literature or theoretical discussions that are not directly related to the findings presented. Instead, it would be best if you kept the results section focused solely on the data and outcomes of your research.
  3. Avoid inserting personal opinions, biases, or speculative statements about the results.
  4. While presenting data is essential, you should avoid dumping large amounts of raw data without proper context or explanation.
  5. Detailed descriptions of research methods, procedures, or techniques should be kept to a minimum in the results section. Instead, any such information should be moved to the methodology chapter of your dissertation.
  6. While it’s important to acknowledge the limitations of your study, detailed discussions about limitations should be reserved for the discussion section.
  7. The results section typically does not include citations or references to external sources unless you are citing specific statistical methods or previously published data that are directly relevant to your findings.
  8. Maintain a professional and objective tone throughout the results section. Avoid using emotional language, speculative statements, or exaggerated claims about the significance of your findings.

How to Write The Results Section of a Dissertation: 8 Steps Guide

Writing the results chapter of a dissertation involves following various steps tailored to meet the specific research objectives/questions. Here are some of the steps you need to follow to effectively organize and present the results & findings of your dissertation:

Step 1 – Revisit Your Research Questions

Begin by revisiting your research questions/hypotheses and if possible, restate them in the dissertation results section. The research questions/hypotheses act as a steering by providing guidance on how to organize the results and discussion chapters. Specifically, they help you identify which statistical analyses are necessary to effectively address each research question.

Step 2 – Craft an Overview Introduction

The results section of a dissertation should start with a concise introduction. This should provide a brief summary of what the readers should expect to find in the results & findings chapter. More importantly, you need to bring to the attention of the reader, the order in which the findings will be presented.

Example:

This chapter presents the findings of [Title of Your Study], focusing on [briefly summarize the specific research objectives or questions]. Through a comprehensive analysis of collected data, this section provides insights into [mention key themes or variables studied].

The chapter presents the results of the demographic composition of the sample, and then proceeds to detailed presentations of descriptive and inferential statistics. This provides a comprehensive understanding of [specific aspects or measures analyzed]. These findings are pivotal in understanding [briefly mention the implications or significance of the findings]. They serve as a foundation for the ensuing discussion chapter, where implications, limitations, and broader theoretical insights will be explored further.

Step 3 – Present Sample Demographic Data

You need to start by presenting the demographics results and findings. This includes analysis of major demographic variables such as age, gender, ethnicity, educational background, etc. Analysis of the demographic variables helps in understanding the generalizability of the findings. It also helps contextualize the results within the target population.

Step 4 – Review Composite Measures and Data “Shape”

Before conducting statistical analyses, ensure your data meets the necessary assumptions for each statistical test. For instance, you can start by assessing the internal consistency of composite measures using reliability tests like Cronbach’s Alpha. You may also need to assess the distribution of the data. In this case, conduct normality tests using either the Shapiri-Wilk test or the Kolmogorov-Smirnov test to determine if it’s symmetrical (normally distributed) or skewed. Testing the normality assumptions helps you to determine the most appropriate statistical analysis tests to use.

Step 5 – Present Descriptive Statistics

Begin your data presentation with descriptive statistics that summarize key variables. Include measures such as mean, median, mode, standard deviation, skewness, and kurtosis for quantitative data. Use clear and labeled tables and graphs to present these statistics effectively. Clear and effective presentations of descriptive statistics act as the foundation for inferential statistics.

Step 6 – Dive into Inferential Statistics

If your research requires inferential statistics to draw conclusions beyond the sample, proceed with analyses like t-tests, ANOVAs, correlations, or regressions. Differentiate between parametric (normally distributed data) and non-parametric tests based on your data’s characteristics. Use visual aids such as correlation matrices or scatterplots to illustrate relationships and significant findings.

Step 7 – Test Your Hypotheses (If Applicable)

If your study involves hypotheses, outline and test each hypothesis according to predetermined significance levels (e.g., p < 0.05). Clearly state your null and alternative hypotheses, calculate relevant statistics, interpret p-values, and draw conclusions based on the results. Ensure each hypothesis test aligns with your research objectives and contributes to answering your primary research questions. You should also provide a clear rationale behind each statistical test.

Step 8 – Provide a Chapter Summary

Conclude your results chapter with a concise summary highlighting the key findings and their implications. Emphasize results that directly address your research questions or hypotheses. Avoid introducing new discussions or interpretations in this section—save these for the subsequent discussion chapter.

Final Take Away

  • Preparation: Collect and analyze your data thoroughly before writing the results section using appropriate statistical tools.
  • Purpose: The results section presents factual outcomes without interpreting their meaning; save interpretations for the discussion section.
  • Components to Include: Focus on data summaries, statistical analyses (descriptive and inferential), key findings, and contextual information (demographics).
  • What to Avoid: Do not include interpretations, new literature discussions, personal opinions, data dumping without context, or detailed methodological descriptions.
  • Organizational Steps: Start with revisiting research questions, craft a brief introduction, present demographic data, review data suitability, present statistics clearly, test hypotheses (if applicable), and provide a concise chapter summary.
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