# scipy.stats.mstats.kruskalwallis¶

scipy.stats.mstats.kruskalwallis(*args)[source]

Compute the Kruskal-Wallis H-test for independent samples

Parameters
sample1, sample2, …array_like

Two or more arrays with the sample measurements can be given as arguments.

Returns
statisticfloat

The Kruskal-Wallis H statistic, corrected for ties

pvaluefloat

The p-value for the test using the assumption that H has a chi square distribution

Notes

For more details on kruskal, see stats.kruskal.

Examples

>>> from scipy.stats.mstats import kruskal


Random samples from three different brands of batteries were tested to see how long the charge lasted. Results were as follows:

>>> a = [6.3, 5.4, 5.7, 5.2, 5.0]
>>> b = [6.9, 7.0, 6.1, 7.9]
>>> c = [7.2, 6.9, 6.1, 6.5]


Test the hypotesis that the distribution functions for all of the brands’ durations are identical. Use 5% level of significance.

>>> kruskal(a, b, c)
KruskalResult(statistic=7.113812154696133, pvalue=0.028526948491942164)


The null hypothesis is rejected at the 5% level of significance because the returned p-value is less than the critical value of 5%.

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