Writing the results (the section) is where you report the main findings from the data collection and analysis you carried out for your thesis or dissertation. You must report all relevant information concisely and objectively, in a logical order. Do not include subjective interpretations of why you found these results or what they mean – any evaluation should be saved for the discussion section.
The objectives of your Results section are:
- Describe and explain the data you obtained with your methods, as objectively as possible and in a narrative form, and
- To communicate a take-home message based on this data.
While your figures give your readers the opportunity to directly examine your data and draw their own conclusions, the section offers more support for the data interpretation process by explaining the experimental logic, highlighting important features of the data and stating your conclusions.
Section success criteria:
- The data and conclusions drawn from them are described clearly and without speculation.
- Data is presented in a narrative flow without logical breaks.
- The story is based on a take-home message.
Maintain a narrative framework
A great way to find a narrative order for your results is to first organize your numbers. Before'to write your results, you should have decided on the set of figures that will be included in your article. Each figure should support a specific conclusion and provide the data the reader needs to evaluate that conclusion (see figures).
Rearrange your numbers until you have found an order that creates the most logical series of conclusions possible, leading to your final result. Use this series of figures/conclusions as an outline of your results.
Each major conclusion (which can correspond to one or more numbers) can become the title of a subsection. This modular organization will help readers navigate your article by quickly matching numbers to results and vice versa.
Example
If you have conducted quantitative research, you will likely be working with elements of some sort of statistical analysis.
Your section should report the results of any statistical tests you used to compare groups or assess relationships between variables. It must also indicate whether or not each hypothesis was supported.
The most logical way to structure quantitative results is to frame them around your questions or research hypotheses. For each question or hypothesis, share:
A reminder of the type of analysis you used (for example, a two-sample t test or a regression simple linear). A more detailed description of your analysis should be included in your section methodology.
A summary concisely of each relevant result, both positive and negative. This can include all 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 that 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 did not match your expectations and assumptions, but keep any speculation about their meaning or consequences for your discussion and conclusion.
In quantitative research, it is 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 displayed. If you want to include other visual elements that are more tangential in nature, consider adding a list of figures and tables.
Generally :
- Tables are used to communicate exact values, giving a concise overview of different results
- Graphs and charts are used to visualize trends and relationships, giving an at-a-glance illustration of key findings
Be sure to also mention any tables and figures you used in your section text. Summarize or expand on specific aspects that you think your reader should know rather than just repeating the same numbers already stated.
The discussion
The discussion section is where you delve deeper into the meaning, importance, and relevance of your findings. Writing the discussion allows you to focus on explaining and evaluating what you found, showing how it relates to your review of the literature and presenting an argument to support your overall conclusion. This should not be a second results section.
There are different ways to write this section, but you can focus your writing around these key elements:
- Summary: a brief summary of your main results
- Interpretations: What do your results mean?
- Implications: Why are your results important?
- Limitations: What can't your results tell us?
- Recommendations: Areas for further study or analysis
There is often overlap between your discussion and your conclusion, but they are usually separate sections. However, in some cases these two sections are combined.
If you are unsure of best practices in your field, consult sample essays in your field or your department's guidelines.
There are some common mistakes to avoid when writing the discussion section of your article.
- Do not introduce new results: you should only discuss data that you have already reported in your results section.
- Don't make exaggerated claims: Avoid overinterpretation and speculation that are not directly supported by your data.
- Don't undermine your research: discussion of limitations should be aimed at building credibility, not emphasizing weaknesses or failures.
Summarize and interpret the results
Begin this section by reiterating your research problem and concisely summarizing your main findings. Don't just repeat all the data you've already reported, aim for a clear statement of the overall result that directly answers your main research question. This should be no more than one paragraph.
Many researchers are unaware of the differences between a discussion section and a results section. The crux of the matter is that your results sections should present your results, and your discussion section should evaluate them subjectively. Try not to mix elements of these two sections, in order to keep your paper neat.
The meaning of your results may seem obvious to you, but it is important to clarify what they mean to your reader, showing exactly how they answer your research question.
The form of your interpretations will depend on the type of research, but some typical approaches to data interpretation include:
- Identify correlations, patterns and relationships between data
- Discuss whether the results met your expectations or supported your hypotheses
- Contextualize your findings within previous research and theories
- Explain unexpected results and assess their importance
- Consider other possible explanations and argue your position
You can organize your discussion around key themes, hypotheses or research questions, following the same structure as the results section. Alternatively, you can also start by highlighting the most significant or unexpected results.
In addition to giving your own interpretations, be sure to relate your findings to the academic work you examined in the literature review. The discussion should show how your findings correspond to existing knowledge, what new ideas they provide, and what consequences they have for theory or practice.
Ask yourself these questions:
- Do your results support or challenge existing theories?
- If they support existing theories, what new information do they provide?
- If they challenge existing theories, why do you think this is the case?
- Are there any practical implications?
Your overall goal is to show the reader exactly what your research yielded and why they should care.
Give the limits
Even the best research has its limits. Recognizing them is important to demonstrate your credibility. Limitations are not about listing your errors, but about providing an accurate picture of what can and cannot be concluded from your study.
Limitations may be due to your overall research design, specific methodological choices, or unforeseen obstacles that emerged during your research process.
You should only mention limitations directly related to your research objectives. Then, share the impact they had on achieving your research objectives.
Here are some common possibilities:
- If your sample size was small or limited to a specific group of people, explain how generalizability is limited.
- If you encountered any problems during data collection or analysis, explain how these influenced the results.
- If there are potential confounding variables that you were unable to control, recognize the effect they may have had.
After noting the limitations, you can reiterate why the results are nonetheless valid in an effort to answer your research question.
Give an opening
Based on the discussion of your results, you can make recommendations for practical implementation or further research. Sometimes the recommendations are saved for conclusion.
Suggestions for further research may arise directly from the limitations. Don't just say that more studies should be done, give concrete ideas for how future work can build on areas that your own research has not been able to address.
EN 
FR