- 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: | $\alpha=$ |