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This paper describes the methodology and application of the very popular nonparametric test which is a rank based test named as Kruskal-Wallis. This test is useful as a general nonparametric test for comparing more than two independent samples. It can be used to test whether such samples come from the same distribution. This test is powerful alternative to the one-way analysis of variance. Nonparametric ANOVA has no assumption of normality of random error but the independence of random error is required. If the Kruskal-Wallis statistic is significant, the nonparametric multiple comparison tests are useful methods for further analysis. The statistical analysis of the application data in this paper was performed with software MATLAB.
Ostertagová et al. (Fri,) studied this question.