![]() ![]() ![]() The only restriction is that the number of observations in each cell has to be equal (there is no such restriction in the case of one-way ANOVA). ![]() One can also test for independence of the factors provided there are more than one observation in each cell. Unlike One-Way ANOVA, it enables us to test the effect of two factors at the same time. It can also be used to analyze the mean responses in an experiment with two factors. Two-way ANOVA (factorial) can be used to, for instance, compare the means of populations that are different in two ways. There are two assignable sources of variation – supp and dose in our example – and this helps to reduce error variation thereby making this design more efficient. An important advantage of the two-way ANOVA is that it is more efficient compared to the one-way. ![]()
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