Gathering data is only the first step — selecting which data to present and how to present it are analytical and rhetorical decisions that shape how your findings are received. Effective data presentation supports your argument; poor presentation obscures findings or misleads.
Not all data you collect needs to appear in your report. Data selection should be:
- Purposeful: Include data that directly addresses the research question
- Representative: Include data that fairly represents the range of your findings — not only data that supports your hypothesis
- Proportionate: The most important findings should receive the most attention
- Honest: Do not omit contradictory or inconvenient data
KEY TAKEAWAY: Selective data presentation that excludes unfavourable findings is both an ethical breach and a reasoning error. Your report must represent your data faithfully. Include negative or null results — they are findings too.
| Data Type | Best Visual Format |
|---|---|
| Comparison across categories | Bar chart |
| Changes over time | Line graph |
| Part-to-whole relationships | Pie chart (use sparingly) |
| Correlations between variables | Scatter plot |
| Distribution of values | Histogram |
| Precise values in multiple categories | Table |
When reporting statistical findings:
- State the statistical test used
- Report the test statistic, degrees of freedom and p-value: t(48) = 2.34, p = .023
- Report effect sizes (Cohen’s d, r, η²) — these quantify the practical importance of a finding
- Include confidence intervals where possible
EXAM TIP: If given a graph or table and asked to evaluate its quality, check: Does it have a title? Are axes labelled with units? Does the scale distort the data? Is a misleading zero-truncated y-axis used? These are standard evaluation points.
Direct quotation: Present the participant’s exact words (in quotation marks, with anonymisation) to illustrate a theme. Quotes should be representative — not cherry-picked for dramatic effect.
Paraphrase and summary: Describe the substance of responses without quoting — useful for common patterns across multiple participants.
Thematic tables: Organise quotes or paraphrases by theme, showing how each theme is evidenced across participants.
Case descriptions: Detailed narrative accounts of individual cases — useful when a case is analytically significant.
In a mixed-methods investigation, data types should triangulate and complement each other:
- Use quantitative data to establish patterns and frequencies
- Use qualitative data to explain why those patterns exist
- Where they converge, confidence in the finding increases
- Where they diverge, investigate and report the discrepancy
Every figure, table and quote in your report is an argument — it is evidence offered in support of a claim. Ensure:
- Each visual or quoted passage is explicitly connected to your argument with analytical commentary
- You do not present data without interpreting it
- You do not present an interpretation without pointing to the specific data supporting it
APPLICATION: For every figure or table in your report, write at least one sentence of analysis that (1) describes the key finding the figure shows and (2) connects it to your research question or hypothesis. Never let a figure “speak for itself” — explain what you want the reader to take from it.
COMMON MISTAKE: Presenting data in the results section and then repeating the same points in the discussion without adding new analytical value. The discussion should interpret, contextualise and evaluate — not merely restate what the results showed.
