Know for Quiz #3 on G&W Chapter 10-11 & 13 (note: knowledge of Ch. 9 also presumed)

1. MATCHING UP DATA & TEST: If I describe a set of data (for example, we have scores for marital happiness of 12 couples both 2 weeks and 2 years after they were married) you should know which type of test is appropriate-a single sample, related samples, or independent measures t, or an ANOVA. Know why we would use an ANOVA instead of t-tests. If I identify a type of test, be able to describe a set of data that would be appropriate for this test. The last page of the independent/related t handout has an exercise for practicing this kind of problem.

2. DIFFERENCES & SIMILARITIES: You should also be able to list several differences between different kinds of tests (for example, how many samples does each test use? Are there differences in what we know about the populations?) and also be able to identify similarities (for example, what is similar about the structure of the t statistic equation for each t-test?).

3. SAMPLING DISTRIBUTIONS: Be able to describe the differences between a normal curve and a t-distribution, and the differences between a t-distribution with small or large degrees of freedom. Be able to draw a comparison picture showing the differences between a normal curve and a t distribution. Know what the appropriate sampling distribution is for each of the t-tests. If you are algebraically inclined, the formula should make this obvious. Be able to describe and draw an F-distribution, and know how it is different from both normal curve and t distributions.

4. ANOVA NOTATION & F-RATIO: Know what the following stand for: SS_{B}, SS_{W, }df_{B}, df_{W},
MS_{B}, MS_{W,} k, *n*, N. Know how they come together to produce the F-ratio. Know what the basic
logic is behind the F-ratio-why are we using a ratio of variances, and why is variance-between on
top of the ratio, variance-within on the bottom? (NOTE: the logic is the same as with t
statistics).