The Temptation to Overstate Research Findings
After years of work on a Malaysian postgraduate thesis, the temptation to present findings in their most impressive light is understandable. A modest correlation becomes “a strong relationship.” A finding that held in two of three tests becomes evidence of a “consistent pattern.” A qualitative theme expressed by a majority of participants becomes representative of “all participants.” These overstated findings feel like minor rhetorical improvements but they are factual misrepresentations — and experienced examiners recognise them immediately. Writing your findings accurately without overstating means presenting results at the strength the evidence actually warrants, neither more nor less.
Matching Language to Evidence Strength
The language you use to present findings should match the actual strength of the evidence. For quantitative findings, the statistical outputs determine the appropriate claim strength. A significant result at p < .001 with a large effect size warrants stronger language than a significant result at p = .04 with a small effect size. "Strongly predicted" is appropriate for large effects; "significantly predicted" is appropriate for results that are statistically significant but practically modest. Use Cohen's conventions for effect sizes when evaluating practical significance: a correlation of r = .10 is small, r = .30 is medium, and r = .50 is large. Do not describe a small effect as a "significant finding" in the colloquial sense — the statistical significance of a result and its practical magnitude are separate claims requiring separate language.
For qualitative findings, claim strength should match participant representation. “All participants described…” is appropriate only when all participants genuinely did. “Most participants expressed…” means more than half. “Several participants noted…” means more than two but not a majority. “One participant suggested…” is accurate for a single instance. Using these quantifiers accurately rather than inflating them prevents the impression that your analysis found more consensus than it actually did.
Keeping Findings Separate From Interpretation
Overstating findings often happens at the boundary between reporting and interpreting — where the writer slides from describing what the data showed to claiming what it proves. “Table 4 shows that intrinsic motivation significantly predicted completion intention” is a finding. “Table 4 proves that motivation drives doctoral completion” is an overstatement — the cross-sectional design does not support causal claims, and “proves” is almost never appropriate for empirical social science findings. Keep the findings section to what the data shows; save interpretation for the discussion chapter where hedged, evidence-grounded interpretation belongs.
During proofreading, read your findings chapter and flag every instance of strong certainty language — “proves”, “demonstrates conclusively”, “clearly shows”, “definitively establishes”. Then evaluate whether the evidence actually supports that level of certainty. In most cases, “suggests”, “indicates”, or “provides evidence that” is more accurate. Writing your findings accurately without overstating is both an ethical responsibility and a strategic one — findings presented at the right strength are more credible than overstated ones, and credible findings are the foundation of a thesis that holds up throughout the viva.
