Comparing more than two means
Two factor ANOVA with independent samples: the important role of interaction
Abstract
This chapter considers the effect of two factors on any kind of metric you collect, including ease-of-use of a task, time it takes to complete a task, or the sophistication of a design. For each of the two factors, we separately test the null hypothesis that the mean for each level of the factor is the same, vs. the alternate hypothesis that the means are not the same. We also bring to bear the Student-Newman-Keuls (S-N-K) test for each factor to further determine what the differences are, if, indeed, we find that there are differences in the means. The chapter also introduces interaction effects, an important and often overlooked ...
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