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. |
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.
Get Answers For Free
Most questions answered within 1 hours.