Key points at a glance
- State the null model and test assumptions.
- Report the actual p-value with effect and uncertainty.
- Separate statistical evidence from practical importance.
Keep the condition in the sentence
Example: In a suitable test, p = .03 means that data at least this extreme would occur about three percent of the time if the null model held. It does not mean “97% chance my hypothesis is true.” Interpretation also depends on design and assumptions.
Do not overread a threshold
p = .049 and p = .051 do not represent wholly different realities. Set the significance level before analysis and report the actual value where useful. Testing many hypotheses increases the chance of a striking result by coincidence.
Add magnitude and precision
A small p-value can accompany a tiny effect in a large sample. Give the estimated difference or association with a confidence interval and discuss whether it matters. A large p-value does not establish no effect either.
Return to the study design
A significance test cannot repair biased recruitment, weak measurement or unobserved confounding. Say which population and comparison the result concerns. Avoid a causal conclusion unsupported by the design.
Final submission context
Formal details can feel like a separate writing task, but they matter just as much for a printed submission. Anything missing, misplaced or inconsistently formatted in the document will also appear in the bound copy.
Use this guide together with your cover page, table of contents, page numbers, source notes and appendices. Prepare the final PDF for printing and binding only after the complete file has been checked.
Practical check before PDF export
- Do headings, chapter structure and page numbers match?
- Are sources, figures and tables included completely?
- Are required elements such as declarations, appendices or the cover page included where required?
- Did you open and check the final PDF after exporting it?
Checklist
- Null model and test named.
- Actual p-value reported.
- Effect and interval included.
- Design limits discussed.
Common mistakes
- Treating p as a probability that the hypothesis is true.
- Taking p > .05 as proof of equality.
- Equating significance with importance.
Prepare the finished thesis for submission
Once the content and university requirements are checked, review your PDF and the available printing and binding options.
Review printing optionsRelated content
Explore related guidance on thesis structure, sources, formatting and final submission.
Frequently asked questions
What does p < .05 mean?
Under the test assumptions and null model, data at least this extreme would be relatively uncommon.
Is p = .051 no result?
No. Report the estimate, uncertainty and context.
Do I always need p-values?
No. The question and design determine whether estimates and intervals are more useful.