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  2. Kruskal–Wallis test - Wikipedia

    en.wikipedia.org/wiki/KruskalWallis_test

    The parametric equivalent of the Kruskal–Wallis test is the one-way analysis of variance (ANOVA). A significant Kruskal–Wallis test indicates that at least one sample stochastically dominates one other sample. The test does not identify where this stochastic dominance occurs or for how many pairs of groups stochastic dominance obtains.

  3. Jonckheere's trend test - Wikipedia

    en.wikipedia.org/wiki/Jonckheere's_Trend_Test

    In statistics, the Jonckheere trend test [1] (sometimes called the Jonckheere–Terpstra [2] test) is a test for an ordered alternative hypothesis within an independent samples (between-participants) design. It is similar to the Kruskal-Wallis test in that the null hypothesis is that several independent samples are from the same population ...

  4. One-way analysis of variance - Wikipedia

    en.wikipedia.org/wiki/One-way_analysis_of_variance

    Responses for a given group are independent and identically distributed normal random variables (not a simple random sample (SRS)). If data are ordinal, a non-parametric alternative to this test should be used such as Kruskal–Wallis one-way analysis of variance.

  5. List of statistical tests - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_tests

    Kruskal-Wallis test [11] Wilcoxon signed-rank test: interval: non-parametric: paired: ≥1: Location test: Sign test: ordinal: non-parametric: paired: 2: Friedman test: ordinal: non-parametric: paired >2: Location test: test: nominal [1] non-parametric [12] No: Contingency table, sample size > ca. 60, [1] any cell content ≥ 5, [13] marginal ...

  6. Goodman and Kruskal's lambda - Wikipedia

    en.wikipedia.org/wiki/Goodman_and_Kruskal's_lambda

    Although Goodman and Kruskal's lambda is a simple way to assess the association between variables, it yields a value of 0 (no association) whenever two variables are in accord—that is, when the modal category is the same for all values of the independent variable, even if the modal frequencies or percentages vary. As an example, consider the ...

  7. Van der Waerden test - Wikipedia

    en.wikipedia.org/wiki/Van_der_Waerden_test

    The most common non-parametric test for the one-factor model is the Kruskal-Wallis test. The Kruskal-Wallis test is based on the ranks of the data. The advantage of the Van Der Waerden test is that it provides the high efficiency of the standard ANOVA analysis when the normality assumptions are in fact satisfied, but it also provides the ...

  8. ANOVA on ranks - Wikipedia

    en.wikipedia.org/wiki/ANOVA_on_ranks

    The F statistic is a ratio of a numerator to a denominator. Consider randomly selected subjects that are subsequently randomly assigned to groups A, B, and C. Under the truth of the null hypothesis, the variability (or sum of squares) of scores on some dependent variable will be the same within each group.

  9. Talk:Kruskal–Wallis test - Wikipedia

    en.wikipedia.org/wiki/Talk:KruskalWallis_test

    The Kruskal-Wallis test is designed to detect stochastic dominance, so the null hypothesis is the absence of stochastic dominance. Using multi-modal distributions you can quickly generate counter examples to the claim "the null hypothesis of the Kruskal-Wallis is equal distribution of the samples".