h2(#description). Description In this template Rapporter will present you Kruskal Wallis test. h3(#introduction). Introduction "Kruskal-Wallis test":http://en.wikipedia.org/wiki/Kruskal-Wallis 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.
Kruskal-Wallis test for _Age_ and _Internet usage for educational purposes (hours per day)_
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. h2(#description-1). Description In this template Rapporter will present you Kruskal Wallis test. h3(#introduction-1). Introduction "Kruskal-Wallis test":http://en.wikipedia.org/wiki/Kruskal-Wallis 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.
Kruskal-Wallis test for _mpg_ and _drat_
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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