Wilcoxon signed-rank 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
Set two measurements on the same participant for each pair. Wilcoxon uses signs and ranks of paired differences. A location-shift interpretation depends on symmetry of differences; zero handling is recorded in raw output.
Variables
| Control | Input |
|---|---|
| Paired variables | Add ordered variable pairs |
Analysis settings
| Parameter | Choices | Default |
|---|---|---|
| Alternative hypothesis | Two-tailed, Greater Than, Less Than | two-sided |
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.