📊 Kruskal-Wallis H Test Calculator
Paste your groups (one per line) to run a Kruskal-Wallis test, the rank-based alternative to ANOVA that doesn't assume normal data.
H statistic
9.981
Degrees of freedom
2
p-value
0.0068
Rank sums: 34 · 64.5 · 21.5 · N = 15, 3 groups
At least one group differs (significant at α = 0.05)
p = 0.0068 < 0.05, so you reject the null hypothesis that all 3 groups have the same distribution. Like ANOVA, it doesn't say which groups differ, use a post-hoc test (e.g. Dunn's test).
The Kruskal-Wallis H test is the non-parametric alternative to one-way ANOVA: it compares three or more groups by ranking all values together, so it doesn't assume the data are normally distributed, useful for skewed data, ordinal ratings or outliers. The H statistic is compared to a chi-square distribution (with a tie correction). A significant result means the groups aren't all alike but not which ones differ. 🔒 In your browser.
How the kruskal-wallis h test calculator works
The Kruskal-Wallis test ranks every value across all groups together, sums the ranks within each group, and forms the H statistic from those rank sums. H is compared to a chi-square distribution with k − 1 degrees of freedom (k = number of groups), and the tool applies a tie correction for repeated values. Enter one group per line, values separated by commas or spaces.
This is the test to reach for when you'd use one-way ANOVA but the data isn't normally distributed, skewed measurements, ordinal ratings or small samples with outliers, because it works on ranks. Like ANOVA, a significant H tells you the groups are not all alike but not which ones differ; a post-hoc procedure such as Dunn's test locates the differences. For exactly two groups it reduces to the Mann-Whitney U test. It all runs locally in your browser.
Frequently asked questions
When should I use the Kruskal-Wallis test?
When comparing three or more independent groups but the normality assumption of ANOVA is doubtful, skewed data, ordinal scales, small samples or outliers. It's the non-parametric alternative to one-way ANOVA and works on ranks.
How does it relate to ANOVA and Mann-Whitney?
It generalises the Mann-Whitney U test (two groups) to three or more, and it plays the role ANOVA plays for normal data. Use ANOVA when the groups are roughly normal, Kruskal-Wallis when they're not.
What does a significant H mean?
That the groups don't all come from the same distribution, at least one differs. It doesn't identify which; follow up with a post-hoc test like Dunn's test with a multiple-comparison correction.
Does it handle tied values?
Yes, tied values receive average ranks and the H statistic is adjusted with a tie correction, so repeated numbers are handled correctly.
Is my data uploaded?
No, the test is computed entirely in your browser and works offline, so your data never leaves your device.