The Kruskal-Wallis test is a non-parametric alternative of the one way ANOVA. By parametric the test doesn’t assumes that data comes from one particular distribution ( McKight & Najab, 2010) . The Kruskal Wallis test and one way Anova are used to assess for significant differences on a continuous dependent variable by a categorical independent variable. However there is difference between the two tests in that the ANOVA tests assumes that the independent variable is normally distributed and there is approximately equal variance to the scores across groups. On the contrary the Kruskal Wallis test does not follow these assumptions.
Kruskal Wallis is used a test of equality for medians and means. When used to measure mean, the observations are assumed to be distributed. It is preferred when the original observations are identically distributed and in this case it is used to show the difference between medians. When the observations represent very different distributions Kruskal Wallis is viewed as a test of dominance ( McKight & Najab, 2010) .
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Moreover, the Kruskal Wallis test works assumes that the observations in each group are identically and independently distributed apart for location. Additional assumptions state that one independent variable with two or more levels should be used in the test. The test is more applicable if one is working with three or more levels. When using two levels the Mann Whitney U test would be more applicable to use. The variables used should have ordinal scale, ratio scale or interval scale ( McKight & Najab, 2010) . The observation should be dependent- there should be no relationship between the members in each group or between the groups. Lastly all groups should have the same shape distribution
The Kruskal Wallis and Mann-Whitney U tests are similar in the sense that they are non-parametric tests used to measure whether two or more samples come from the same distribution ( McKight & Najab, 2010) . They are also used to measure whether medians between comparison groups are different- in both test the distribution of the shapes is assumed to be similar. The major difference between the two tests is that the Kruskal Wallis H can accommodate more than two groups.
References
McKight, P. E., & Najab, J. (2010). Kruskal ‐ Wallis Test. Corsini encyclopedia of psychology .
