The Kruskal-Wallis statistic measures how much the group ranks differ from the average rank of all groups. The chi-square value is obtained by squaring each group's distance from the average of all ranks, weighting by its sample size, summing across groups, and multiplying by a constant.

- The degrees of freedom for the chi-square statistic are equal to the number of groups minus one.

- The asymptotic significance estimates the probability of obtaining a chi-square statistic greater than or equal to the one displayed, if there truly are no differences between the group ranks. A chi-square of 9.751 with 2 degrees of freedom should occur only about 8 times per 1,000.

The table tells us the ratings of the strawberries differed by type of mulch used for cultivation. Like the F test in standard ANOVA, Kruskal-Wallis does not tell us how the groups differed, only that they are different in some way. The Mann-Whitney test could be used for pairwise comparisons.