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.

This report was generated with R (3.0.1) and rapport (0.51) in *0.267* sec on x86_64-unknown-linux-gnu platform.