Comparing Means Pt2

Question 1

Why can’t we use multiple t-tests instead of a One-Way ANOVA?

Answer 1

Because multiple t-tests increase the risk of a Type I error.

Question 2

What is a Type I error?

Answer 2

In statistical hypothesis testing, a type I error, or a false positive, is the erroneous rejection of a true null hypothesis.

Question 3

What is a Type II error?

Answer 3

A type II error, or a false negative, is the erroneous failure in bringing about appropriate rejection of a false null hypothesis.

Question 4

What is the null hypothesis in a One-Way ANOVA?

Answer 4

That all group means are equal.

Question 5

What is the basic idea of ANOVA

Answer 5

The basic idea behind ANOVA is a comparison of the variance between the groups and the
variance within the groups

Question 6

What is the null hypothesis for an ANOVA

Answer 6

No significant differences among the groups

Question 7

What is the alterntive hypothesis

Answer 7

At least one significant difference among groups

Question 8

What is the F statistic?

Answer 8

The ration of the between group variation to within group variation.

If the Between Group Variation is significantly greater than the Within Group Variation, then it is likely that there is a statistically significant difference between the groups.

Question 9

What is the rationale of the F statistic

Answer 9

variability between groups/ variability within groups