Mann-Whitney U
Two groups, without assuming normality.
What your data needs to look like
Two sets of measurements.
What Chavery does with it
It checks the assumptions first — normality where the test assumes it, and equality of variance where that matters — and says whether each one held. When an assumption fails it names the alternative test rather than running this one anyway.
Then it reports the statistic, the p-value, a confidence interval and an effect size, and writes the sentence you would put in your results chapter. The same numbers always give the same answer; nothing is generated by a language model.
Reporting it
A p-value on its own is not a result. Chavery reports the effect size beside it, because a difference can be statistically significant and too small to matter, and an examiner will ask which yours is. More on effect size.
Related tests
- Independent t-test — Do two separate groups differ on average?
- Kruskal-Wallis — Three or more groups, without assuming normality.
- One-sample t-test — Is this group's mean different from a known value?
- One-way ANOVA — Three or more groups.
- Paired t-test — Before and after, in the same people.
- Welch's t-test — Two groups with unequal spread.
- Wilcoxon signed-rank — Before and after, without assuming normality.
Run it on your own data. Paste your numbers and Chavery runs Mann-Whitney U with the assumption checks and the reported sentence — no project needed. Open the analysis tool, or let Chavery choose the test for you.