How Do You Spell KRUSKAL WALLIS H STATISTIC?

Pronunciation: [kɹˈʌskə͡l wˈɒliz ˈe͡ɪt͡ʃ stɐtˈɪstɪk] (IPA)

The Kruskal Wallis H Statistic is a non-parametric test used to analyze differences among three or more groups. The spelling of "Kruskal" is [ˈkrʌskəl], with the stress on the first syllable and the "s" pronounced as /sk/ sound. "Wallis" is pronounced [ˈwɒlɪs], with the stress on the first syllable and the "ll" pronounced as /l/ sound, not the typical /j/ sound in English. "H" is simply pronounced as "aitch" or /eɪtʃ/. Together, this term is pronounced [ˈkrʌskəl ˈwɒlɪs eɪtʃ stəˈtɪstɪk].

KRUSKAL WALLIS H STATISTIC Meaning and Definition

  1. The Kruskal-Wallis H statistic is a non-parametric statistical test used to determine if there are significant differences between the medians of three or more independent groups. It is an extension of the Mann-Whitney U test, which is used to compare the medians of two independent groups.

    The Kruskal-Wallis H statistic is calculated by ranking the values from all groups together, regardless of which group they belong to. The ranks are then used to calculate the sum of the ranks for each group. The test statistic, H, is calculated by summing the squared deviations of the group sums of ranks from what would be expected if all groups had the same median. The resulting H value follows a chi-square distribution with degrees of freedom equal to the number of groups minus 1.

    The test assumes that the groups are independent and that the populations from which the samples are drawn have similar shapes and dispersion. It is robust to violations of normality assumptions, making it preferable when the data is not normally distributed.

    The null hypothesis of the Kruskal-Wallis test is that the medians of all groups are equal, while the alternative hypothesis is that at least one pair of groups has different medians. By comparing the obtained H statistic to the critical value from the chi-square distribution table, one can determine whether the observed difference in medians is statistically significant, providing evidence for rejecting the null hypothesis.

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