The Kruskal-Wallis test is a non-parametric test that is used to determine whether three or more groups are in some way the same, in terms of their mean ranks, where the smallest sample has rank 1, then the next smallest sample has rank 2, and so on, for all samples across all the groups. The Null Hypothesis is that all groups have similar mean ranks. The Kruskal-Wallis test can be regarded as the non-parametric counterpart to the one-way ANOVA test, or as the extension of the Mann-Whitney U test to three or more groups. As it is a non-parametric test, it will be more robust than the one-way ANOVA test to deviations from the Normal distribution.
Simply click on the link near the top to add text boxes. Each text box stores a single group/dataset and needs to be filled in with comma separated numbers. Alternatively, you can choose two file entry methods:-
- Select multiple single column CSV files to populate the text boxes by repeatedly pressing the Choose File button - there must be one distinct (and differently named) file for each text box i.e. one file per group. Each file can have a different number of samples.
- Select a single multi-column CSV file by pressing the Choose File button once, where the number of columns equals the number of groups - all groups need to have the same number of samples.
There is a graph at the bottom which will display scatter plots for the ranks of all the groups, once the calculate button is pressed.
Results pending...
| Scatter plot of all the group ranks | ||
| Rank values | ||
| Group number |