scipy.stats.mstats.
kruskal#
- scipy.stats.mstats.kruskal(*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- scipy.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 hypothesis 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%.