Kruskal–Wallis test
Purpose
Compare samples using ranks for ordinal outcomes or when a conventional mean model is unsuitable.
Data and assumptions
Rank tests still require an appropriate design and independence assumptions. Some tests admit a median-difference interpretation only under additional distribution-shape assumptions.
Configure this method
Specify a factor containing multiple independent groups. Optional post-hoc testing uses Dunn rank comparisons with Holm or Bonferroni adjustment.
Variables
| Control | Input |
|---|---|
| Analysis variables | Select variables |
| Group Variable | Select one variable |
Analysis settings
| Parameter | Choices | Default |
|---|---|---|
| Perform post hoc pairwise comparisons | Set as needed | Disabled |
| Multiple-comparison adjustment | Holm, Bonferroni | holm |
Analysis parameters remain visible in the main configuration area. Advanced formatting contains only the table title and numeric decimals. Methods that calculate intervals also show the significance level; 0.05 corresponds to 95% intervals.
Read the results
Report group medians and quartiles, the test statistic and p-value. Interpret adjusted post-hoc results separately from the overall test.
Workflow and exports
- Upload the dataset and choose the method from the sidebar or search.
- Select the variables above, set the design-specific options, then run the analysis.
- Inspect the paper-style result. Reconfigure from the result area, or open raw output for diagnostics and sample details.
- Rename and keep result tabs as needed. Export Word, Excel, CSV or TXT; batch export can include the selected AI interpretation. Word retains figures. AI text should be checked against the estimates.