The Kruskal-Wallis Test

  • Kruskal-Wallis Test assumes that each of our samples is an independent SRS and will give trustworthy conclusions only if this condition is met.

  • Kruskal-Wallis Test assumes that your data come from a continuous distribution.

  • Kruskal-Wallis Test is an alternative to One-Way ANOVA when the guidelines for its use are not met (such as when the largest sample standard deviation is more than twice as large as the smallest).

Variable Names (optional):
Sample data goes here (enter numbers in columns):
Null Hypothesis:$H_0:$ All groups have the same distribution.
Alternative Hypothesis:$H_a:$ Values are systematically higher in some groups than in others.
Level of Significance: $\alpha=$