Question

Part a: If the interaction in a two-way factorial ANOVA is significant, then

A.	we need to test for all main effects.

B. we need to test for simple effects.

C.	we need to test for one of the main effects.

D. None of above.

Part B: When testing for significant mean differences among three groups means, doing independent t tests on all possible pairwise comparisons will

A.not change the probability of a Type I error.

B. increase the probability of a Type II error.

C. decrease the probability of a Type I error.

D. increase the probability of a Type I error.

Answer 1

Ans:

1)

we need to test for one of the main effects.

if you have a statistically significant interaction, you will also need to report main effects. Alternately, if you do not have a statistically significant interaction, there are other procedures you will have to follow.

2)

decrease the probability of a Type I error.

One such method is the Bonferroni correction, which resets the P-value to α/k where k represents the number of comparisons made. For example, if 10 hypotheses are tested, then only results with a P-value of less than 0.05/10 or 0.005 would be considered statistically significant. The Bonferroni correction therefore results in fewer statistically significant results.