The results section of a research paper is where you present and report the findings of your study. This is not the section to interpret the results or discuss their implications. The purpose of this section is to concisely and objectively communicate your research results without bias or embellishment. This section should provide a clear, to-the-point presentation of the evidentiary results from your study in an easy-to-understand, logical flow. Often researchers will include tables, figures, charts, or graphs in this section to visually display or summarize complex data. The results section should be written in the past tense since you have already conducted the research.
It is helpful to think of the results section as visual and data-driven, letting your numbers, charts and visual aids tell the story rather than flowery language. The results section is written to objectively establish evidence to either support or reject your hypotheses. Therefore, speculation, inferences and explanations have no place here and belong instead in the discussion section. The tone should be strictly factual and impartial. The goal is to give the reader a clear picture of exactly what you found in your study without adding your own commentary or bias.
Structure the results section by first presenting the overall demographic characteristics, descriptive statistics or basic analyses on your full dataset. This helps orient the reader. Then present results by individual research questions, hypotheses tests or experiments in a logical sequence. Organize subsections around each analysis or hypothesis test rather than random groupings of results. Break analyses into subsections with clear headings to guide the reader through your evidentiary results in a coherent, step-by-step manner.
Start result subsections with a brief description of what analyses you conducted and what results are being reported in that subsection. Never bury the main findings in paragraphs of context. Place primary results upfront and center each subsection around clearly communicating your central empirical findings for that part of the study. Summarize key results in clear, declarative sentences using numeric values rather than vague descriptions like “a significant difference”. Always include precise statistics such as t values, F values, p values, correlation coefficients, etc. unless the analysis was strictly descriptive.
Use a combination of complete sentences and fragments to convey results concisely. For example, “An independent samples t-test revealed a statistically significant difference between the control and experimental groups in post-test scores, t(78) = 3.14, p = .002.” Tables are especially helpful for presenting organized numeric results in a readable format. Place large tables inline in the text while relocating smaller tables to an appendix to avoid disrupting readability and flow. Ensure table columns and rows align properly and include clear labeling on all elements leaving no ambiguity for the reader.
Figures like bar charts, line graphs or plots provide a clear visual depiction of trends or relationships in the data that may be difficult to grasp from numbers alone. Appropriately label all axes on graphs with units of measurement. Include a brief caption underneath to concisely indicate what is being shown but leave interpretation for the discussion section. The reader should be able to understand a figure independently without referring back to the surrounding text. Always cite figures and tables sequentially in the text by number (e.g. “As shown in Figure 1…”). Never include interpretive analysis, such as statements of cause and effect, here.
The results section should be a cohesive, logical presentation of all core findings supported by evidence from analytical tests, graphs and tables formatted for reader-friendly assimilation of results. While thorough, stay focused only on what is pertinent. Leave out extraneous details, analyses that did not yield significant results and discussions of why findings do or do not support hypotheses. The tone remains strictly objective and the language is concise yet precise in communicating numeric values, trends and relationships revealed through the study. Well-written results establish the bedrock facts to allow informed contextualization and interpretation in the discussion.
Here is a sample results section for a hypothetical research study:
Results
Participant Demographics
A total of 120 college students participated in this study. The average age was 21 years (SD = 2.1). There were 60 females and 60 males. Most participants were in their third year of undergraduate studies.
Spatial Ability Test
An independent samples t-test was conducted to examine whether males scored differently than females on the spatial ability pre-test. There was a significant difference in spatial ability pre-test scores between males (M=15.4, SD=3.2) and females (M=12.1, SD=2.8); t(118) = 4.57, p < .001.
Learning Game Performance
A 2 (Gender) x 2 (Condition) between-subjects ANOVA was performed on post-test scores. There was a significant main effect of condition, F(1, 116) = 15.41, p < .001, with participants in the experimental group (M=18.2, SD=4.1) scoring higher than those in the control group (M=14.3, SD=3.5). The main effect of gender was also significant, F(1, 116) = 9.72, p = .002, with males scoring higher (M=16.8, SD=4.1) than females (M=15.4, SD=3.8) on average. The interaction effect was not significant, F(1, 116) = 1.14, p = .289.
Andrew Stroud