In quantitative research papers, the results section summarizes the collected data and reports the outcomes of relevant statistical analyses. This section allows researchers to address their research questions and share their data analyses in a thorough and transparent manner.
The American Psychological Association (APA) manual offers strict guidelines outlining what should be included when reporting quantitative research in psychology, education, and other social sciences. Adhering to these standards ensures that the results section is comprehensive and clear.
What goes in your results section?
The results section should encompass several key components when writing a quantitative research paper in APA style. Begin by providing preliminary information about the participants and data, followed by descriptive and inferential statistics and the outcomes of any exploratory analyses.
To ensure a comprehensive results section, incorporate the following elements:
- Participant flow and recruitment period: Specify the number of participants at each study stage and the recruitment dates.
- Missing data: Report the proportion of data excluded from your final analysis and explain the reasons for the exclusion.
- Adverse events (if applicable): Disclose any unanticipated events or side effects during the research for clinical studies.
- Descriptive statistics: Summarize the study’s primary and secondary outcomes.
- Inferential statistics: Address the main research questions by reporting the detailed results of your primary analyses, including confidence intervals and effect sizes.
- Subgroup or exploratory analyses (if relevant): Present the results of any additional analyses, with comprehensive results placed in supplementary materials.
Remember to use the past tense when reporting the findings of a completed research study.
Introduce your data
Begin your results section by describing the participant flow throughout the study, including any excluded data, before presenting your main research findings.
Participant flow and recruitment period
Provide details about the number of participants at each stage of your study, from initial recruitment to final analysis. Specify the dates during which recruitment took place.
Example: Reporting participant flow
150 participants were recruited for the study between January 2020 and March 2020. Of these, 15 participants were excluded due to not meeting the inclusion criteria, and 5 withdrew from the study before completion. The final sample comprised 130 participants (85 females, 45 males) aged 18-65 (M = 35.2, SD = 12.1).
Missing data
Identify the proportion of data excluded from your final analysis and explain the reasons for the exclusion.
Example: Reporting missing data
Of the 130 participants, 3 (2.3%) had missing data on the primary outcome measure due to technical issues with the online survey platform. These participants were excluded from the primary outcome analysis but were included in analyses of other variables for which they had complete data.
Adverse events
In clinical studies, report any unexpected events or side effects during the research.
Summarize your data
Use descriptive statistics to provide an overview of your data for the reader. Include descriptive statistics for each primary, secondary, and subgroup analysis conducted in your study.
When presenting commonly used statistics, such as means or standard deviations, there is no need to provide formulas or citations. However, include the appropriate formulas and citations if you use new or uncommon equations.
Descriptive statistics
The specific descriptive statistics you report in your results section will depend on the nature of your study data. For categorical variables, use proportions to summarize the data. Quantitative data can be described using means and standard deviations. When dealing with a large dataset, presenting the data in a table is often the most effective approach.
In your results section, include the sample sizes (overall and for each group) and appropriate central tendency and variability measures for the study outcomes. Whenever you present a point estimate, include a clearly labeled measure of variability.
If you combined data to create variables of interest, clearly explain how you did so. For each variable of interest, provide details on how it was operationalized in your study.
Example: Reporting descriptive statistics
In a study examining the relationship between sleep quality and academic performance, participants completed the Pittsburgh Sleep Quality Index (PSQI). They provided their Grade Point Average (GPA) for the previous semester. The PSQI scores range from 0 to 21, with higher scores indicating poorer sleep quality. GPA was measured on a 4.0 scale.
The sample consisted of 250 undergraduate students (150 females, 100 males) with a mean age of 20.5 years (SD = 1.8). The average PSQI score for the sample was 6.2 (SD = 2.9), suggesting relatively good sleep quality. The mean GPA was 3.2 (SD = 0.6). Table 1 presents the descriptive statistics for PSQI scores and GPA by gender.
Table 1
Descriptive statistics for PSQI scores and GPA by gender
| PSQI Score | GPA | |||
| Gender | Mean | SD | Mean | SD |
| Male | 6.5 | 3.1 | 3.1 | 0.7 |
| Female | 5.8 | 2.6 | 3.3 | 0.5 |
Note. PSQI = Pittsburgh Sleep Quality Index; GPA = Grade Point Average.
Report statistical results
APA journal standards require researchers to report all relevant hypothesis tests, effect size estimates, and confidence intervals. When presenting statistical results, address primary research questions first, followed by secondary research questions and any exploratory or subgroup analyses. Report test results in the order they were conducted, with main test outcomes preceding post-hoc tests. Include all relevant results, even if they do not support your hypothesis.
Inferential statistics
For each statistical test:
- Restate the hypothesis
- State whether the hypothesis was supported
- Provide the outcomes that led to your conclusion
Include the following information for each hypothesis test:
- Test statistic value
- Degrees of freedom
- Exact p-value (unless < 0.001)
- Effect magnitude and direction
Example: Reporting the results of a statistical test
We hypothesized that sleep quality would be negatively associated with academic performance. A Pearson correlation analysis revealed a significant negative correlation between PSQI scores and GPA, r(248) = –0.38, p < .001, indicating that poorer sleep quality was associated with lower academic performance. The magnitude of the effect was moderate, suggesting that sleep quality explains a substantial portion of the variance in academic performance.
When reporting complex data analyses (e.g., factor analysis, multivariate analysis):
- Present estimated models in detail
- Specify the statistical software used
- Report any violations of statistical assumptions or estimation issues
Effect sizes and confidence intervals
When reporting the results of hypothesis tests, it’s important to include both confidence intervals and effect size estimates. Confidence intervals demonstrate the variability around point estimates and should be reported whenever population parameter estimates are presented.
Example: Reporting a confidence interval
The intervention had a moderate effect on reducing symptoms of depression, as measured by the Beck Depression Inventory, Cohen’s d = 0.65, 95% CI [0.42, 0.88].
Effect sizes provide information about the magnitude of the study outcomes. However, since effect sizes are estimates, it is recommended that they be reported along with their confidence intervals.
Example: Reporting effect size and confidence interval
The correlation between job satisfaction and employee turnover was strong, r = -0.78, 95% CI [-0.85, -0.71].
Subgroup or exploratory analyses
In your results section, concisely present the findings of any additional planned or exploratory analyses, including subgroup analyses.
It’s important to note that subgroup analyses carry a higher risk of false positive results. This is because conducting multiple comparison or correlation tests increases the likelihood of obtaining significant results by chance.
If you discover significant results through these analyses, report them appropriately as exploratory rather than confirmatory findings to prevent overstating their significance.
While you can briefly summarize these analyses in the main text, consider including the detailed analyses in supplementary materials.
Presenting numbers effectively
To effectively present numbers, use a combination of text, tables, and figures as appropriate:
- For three or fewer numbers, consider using a sentence.
- For four to twenty numbers, a table might be more suitable.
- For more than twenty numbers, a figure may be the best choice.
However, these are general guidelines, so use your judgment and seek feedback from others to determine the most effective way to present numbers in your specific case.
When using tables and figures, number them and provide titles and relevant notes. Present data only once throughout the paper and refer to any tables and figures in the text.
Formatting statistics and numbers
When referring to statistics in your paper, adhering to capitalization, italicization, and abbreviation rules is crucial. APA provides specific guidelines for reporting statistics and general rules for writing numbers.
If you are uncertain about presenting specific symbols, consult the detailed APA guidelines or refer to other papers in your field for guidance.
What doesn’t belong in your results section?
When writing your results section, presenting a comprehensive yet concise overview of your data analyses and findings is crucial. To achieve this, certain elements should be omitted from the results section:
Raw data
Avoid presenting raw data in your results section. Instead, summarize the data using appropriate descriptive statistics, such as means, standard deviations, or frequencies. You can include the raw data in an appendix or supplementary materials if necessary.
Interpretation or discussion of results
The results section should focus on presenting the findings objectively, without interpretation or discussion. Save the interpretation and discussion of the results for the discussion section of your paper. In the results section, simply report the outcomes of your analyses without speculating on their meaning or implications.
Explanation of how statistics tests work
Avoid providing detailed explanations of how statistical tests work in your results section. Assume that your readers have a basic understanding of the statistical methods used in your study. If you need to provide more information about a specific statistical test, do so in the methods section or refer readers to appropriate references. The results section should focus on reporting the outcomes of the tests, not on explaining the tests themselves.