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Kruskal-Wallis Test

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Kruskal-Wallis Test - definitions

Kruskal-Wallis Test - A nonparametric test to compare three or more samples. It tests the null hypothesis that all populations have identical distribution functions against the alternative hypothesis that at least one of the samples differs only with respect to location (median), if at all. It is the analogue to the F-test used in analysis of variance. While analysis of variance tests depend on the assumption that all populations under comparison are normally distributed, the Kruskal-Wallis test places no such restriction on the comparison. It is a logical extension of the Wilcoxon Mann-Whitney Test .

[Category=Quality ]

Source: American Society for Quality, 01 October 2010 08:47:15, External

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Kruskal-Wallis - Kruskal-Wallis performs a hypothesis test of the equality of population medians for a one-way design (two or more populations). This test is a generalization of the procedure used by the Mann-Whitney test and, like Mood's median test, offers a nonparametric alternative to the one-way analysis of variance. The Kruskal-Wallis test looks for differences among the populations medians.

[Category=Data Quality ]

Source: iSixSigma, 30 January 2011 09:52:09, External

Kruskal-Wallis Test - Non-parametric test equivalent to ANOVA. Samples should have same shape and distribution. If not, then use Moods Median Test.

[Category=Quality ]

Source: The Quality Portal, 14 April 2011 07:35:33, External

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