Kruskal-Wallis

Three or more groups, without assuming normality.

What your data needs to look like

Three or more groups 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?
• Mann-Whitney U — Two 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.