The Family-Wise Error RateĪs mentioned before, post hoc tests allow us to test for difference between multiple group means while also controlling for the family-wise error rate. If the p-value is not statistically significant, this indicates that the means for all of the groups are not different from each other, so there is no need to conduct a post hoc test to find out which groups are different from each other. Technical Note: It’s important to note that we only need to conduct a post hoc test when the p-value for the ANOVA is statistically significant. In order to find out exactly which groups are different from each other, we must conduct a post hoc test (also known as a multiple comparison test), which will allow us to explore the difference between multiple group means while also controlling for the family-wise error rate. It simply tells us that not all of the group means are equal. However, this doesn’t tell us which groups are different from each other. If the p-value from the ANOVA is less than the significance level, we can reject the null hypothesis and conclude that we have sufficient evidence to say that at least one of the means of the groups is different from the others. The alternative hypothesis: (Ha): at least one of the means is different from the others The null hypothesis (H 0): µ 1 = µ 2 = µ 3 = … = µ k (the means are equal for each group) The hypotheses used in an ANOVA are as follows: An ANOVA is a statistical test that is used to determine whether or not there is a statistically significant difference between the means of three or more independent groups.

Sigmaplot 11 do not test bonferroni