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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).

Group/Treatment Names (optional):
Sample data goes here (enter numbers in columns):
Use labels to group data (in Beta):
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: $\alpha=$