How to Present and Report Results from Quantitative Analysis in Research Papers

Introduction

Presenting results from quantitative analysis is more than just showing numbers; it’s about communicating findings clearly, accurately, and logically so that readers can interpret them in the context of the research question. Proper reporting follows academic standards, ensures transparency, and facilitates replication.

1. Follow a Structured Format

Most research papers follow the IMRaD structure (Introduction, Methods, Results, and Discussion). In the Results section:

Present only the findings — interpretation belongs in the Discussion section.
Organize results according to the order of research questions or hypotheses.

2. Use Clear Descriptive Statistics

Report measures of central tendency (mean, median) and variability (standard deviation, range).
Always provide the sample size (n).
Example: “The mean score was 82.4 (SD = 6.5) for Group A (n = 50).”

3. Include Inferential Statistics

Present test statistics, degrees of freedom, p-values, and effect sizes.
Follow APA or relevant style guidelines.
Example: “An independent samples t-test showed a significant difference between groups, t(98) = 2.45, p = .016, Cohen’s d = 0.50.”

4. Use Tables and Figures Effectively

Tables

Summarize large amounts of data compactly.
Include a descriptive title and clear labels.
Avoid repeating all table data in the text — highlight key points instead.

Figures

Graphs, bar charts, scatterplots for visual clarity.
Ensure figures are high-quality, labeled, and follow journal formatting.

5. Report Confidence Intervals and Effect Sizes

Confidence intervals provide precision estimates.
Effect sizes add context about the practical significance of findings.
Example: “The difference in mean scores was 5.2 (95% CI [2.1, 8.3], d = 0.55).”

6. Maintain Transparency and Reproducibility

Specify statistical tests used and any data transformations.
Report missing data handling procedures.
Include software and version (e.g., “Analyses were conducted in SPSS v28”).

7. Avoid Common Reporting Errors

Do not interpret results in the Results section — save that for Discussion.
Avoid selective reporting — present all analyses that were planned.
Do not round excessively — keep p-values to three decimal places unless p < .001.

Example Layout

Results

Demographics: Mean age 32.5 years (SD = 8.2), 55% female.
Primary Analysis: A significant difference was found between the intervention and control groups in post-test scores, t(118) = 3.02, p = .003, d = 0.55.
Secondary Analysis: No significant correlation between age and test performance, r(118) = .12, p = .19.

Conclusion

Presenting and reporting quantitative analysis results requires a balance of clarity, completeness, and adherence to academic guidelines. By combining well-organized text with effective visuals, precise statistics, and transparent reporting, researchers can ensure their findings are both credible and understandable.