The tests of between-subjects effects help you to determine the significance of a factor. However, they do not indicate how the levels of a factor differ. The post hoc tests show the differences in model-predicted means for each pair of factor levels. The first column displays the different post hoc tests. The next two columns display the pair of factor levels being tested. When significance value for the difference in Amount spent for a pair of factor levels is less than 0.05, an asterisk (*) is printed by the difference. In this case, "biweekly" customers spend significantly less than other customers. "Weekly" and "sale" customers do not spend significantly different amounts from each other. Tamhane's T2 is generally more appropriate than Tukey's HSD when there are unequal cell sizes, but the results in this case are largely the same. The confidence intervals for Tamhane's T2 are only slightly wider than those for Tukey's HSD. Since the results of these two tests are not very different, it is safe for you to look at the results of the homogenous subsets, which are available for Tukey's HSD but not for Tamhane's T2. The homogenous subsets table takes the results of the post hoc tests and shows them in a more easily interpretable form. In the subset columns the factor levels that do not have significantly different effects are displayed in the same column. In this example, the first subset contains the "biweekly" customers. The second subset contains the "weekly" and "often" customers. The post hoc tests suggest that customers who shop more often than once every other week will spend more, but effort at enticing customers to shop more than once a week is wasted because they will not spend significantly more. However, the post hoc test results do not account for the levels of other factors, thus ignoring the possibility of an interaction effect with Gender seen in the descriptive statistics table. See the estimated marginal means to see how this might change your conclusions.