In this template Rapporter will present you Kruskal Wallis test.
Kruskal-Wallis test is a non-parametric statistical test that assesses hypothesis of equality of two independent sample's/variabels' variances. Most of the time it's being used beacuse the normality assumptions didn't meet for the samples/variables, but we need the assumption of the equal variances, so it can be an alternative of the Two-sample t-test. Significant result means difference between the samples/variables.
| Test statistic | df | P value |
|---|---|---|
| 1010 | 1 | 1.056e-221 * * * |
As you can see in the table the test's degrees of freedom is 1, the joint test-statistic is 1010, so the p-value of the Kruskal-Wallis test is 1.056e-221. Thus we can reject the assumption of the equal variances.
In this template Rapporter will present you Kruskal Wallis test.
Kruskal-Wallis test is a non-parametric statistical test that assesses hypothesis of equality of two independent sample's/variabels' variances. Most of the time it's being used beacuse the normality assumptions didn't meet for the samples/variables, but we need the assumption of the equal variances, so it can be an alternative of the Two-sample t-test. Significant result means difference between the samples/variables.
| Test statistic | df | P value |
|---|---|---|
| 47.28 | 1 | 6.14e-12 * * * |
As you can see in the table the test's degrees of freedom is 1, the joint test-statistic is 47.28, so the p-value of the Kruskal-Wallis test is 6.14e-12. Thus we can reject the assumption of the equal variances.
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