# How ANOVA avoids type 1 errors

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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.

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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.

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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 ...

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