Multiple/Post Hoc Group Comparisons in ANOVA

Multiple/Post Hoc Group Comparisons in ANOVA Note: We may just go over this quickly in class. The key thing to understand is that, when trying to identify where differences are between groups, there are different ways of adjusting the probability estimates to reflect the fact that multiple Comparisons are being made. Introduction. In a one-way ANOVA , the F statistic tests whether the treatment effects are all equal, that there are no differences among the means of the J groups. A significant F value indicates that there are differences in the means, but it does not tell you where those differences are, Group 1 s mean might be different than Group 2 s mean but not different from Group 3 s mean. To isolate where the differences are, you could do a series of pairwise T-tests. The problem with this is that the significance levels can be misleading.

group 1’s mean is 11.8, group 2’s mean is 8.8, so the difference is 3. An asterisk by the value indicates whether the difference is statistically significant given the method of multiple

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  Comparison, Multiple, Group, Post, Differences, Anova, The differences, Multiple post hoc group comparisons in anova

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