1.Can you explain how the ANOVA technique avoids the problem of the inflated probability of making Type I error that would arise using the alternative method of comparing groups two at a time using the t-test for independent groups.
2.Can you explain the major differences between analyzing a one-way ANOVA versus a two-factor ANOVA, and explain why factorial designs with two or more independent variables (or factors) can become very difficult to interpret.
Answer 1: We know that when we use t test for independent groups, it only works for two independent groups. But ANOVA can be used to test for more than two independent groups. This means, when we use t test, we need to repeat the procedure many times. Since there are type I error for each t test, probability of making Type I error from each t test will arise. However, when we perform ANOVA, we only use F test once. ANOVA is used to test the equality of means for different groups. Since only test is only ...
The solution discusses how the ANOVA technique avoids the problem of the inflated probability of making Type I error and then explains the major differences between analyzing a one-way ANOVA versus a two-factor ANOVA. 350+ words.