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  2. Kruskal–Wallis test - Wikipedia

    en.wikipedia.org/wiki/KruskalWallis_test

    Then, a researcher might use sample contrasts between individual sample pairs, or post hoc tests using Dunn's test, which (1) properly employs the same rankings as the KruskalWallis test, and (2) properly employs the pooled variance implied by the null hypothesis of the KruskalWallis test in order to determine which of the sample pairs ...

  3. Exact test - Wikipedia

    en.wikipedia.org/wiki/Exact_test

    T(y) is the value of the test statistic for an outcome y, with larger values of T representing cases which notionally represent greater departures from the null hypothesis, and where the sum ranges over all outcomes y (including the observed one) that have the same value of the test statistic obtained for the observed sample x , or a larger one.

  4. 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 ...

  5. 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 ...

  6. 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".

  7. Null hypothesis - Wikipedia

    en.wikipedia.org/wiki/Null_hypothesis

    A possible null hypothesis is that the mean male score is the same as the mean female score: H 0: μ 1 = μ 2. where H 0 = the null hypothesis, μ 1 = the mean of population 1, and μ 2 = the mean of population 2. A stronger null hypothesis is that the two samples have equal variances and shapes of their respective distributions.

  8. One-way analysis of variance - Wikipedia

    en.wikipedia.org/wiki/One-way_analysis_of_variance

    The ANOVA tests the null hypothesis, which states that samples in all groups are drawn from populations with the same mean values. To do this, two estimates are made of the population variance. These estimates rely on various assumptions . The ANOVA produces an F-statistic, the ratio of the variance calculated among the means to the variance ...

  9. Test statistic - Wikipedia

    en.wikipedia.org/wiki/Test_statistic

    the exact sampling distribution of T under the null hypothesis is the binomial distribution with parameters 0.5 and 100. the value of T can be compared with its expected value under the null hypothesis of 50, and since the sample size is large, a normal distribution can be used as an approximation to the sampling distribution either for T or ...