1. ONE-WAY REPEATED MEASURES ANOVA What is the Purpose? What are the Assumptions? How Does it Work? What is the Non-Parametric Replacement?

2. What is the Purpose? Determine whether there is a difference among two or more condition means. Use for a within-subjects or matched- groups design. Normally used with three or more conditions. Ho is equal condition means.

3. What are the Assumptions? Interval or ratio scale data Normal distribution on DV Homogeneity of variance Sphericity: variance of difference scores is equal for any two conditions

4. How Does it Work? Like any ANOVA, variance is divided into parts and then compared. Within-conditions variance is separated into between-subjects variance and error (or residual) variance. Individual differences are systematic and removed from the denominator of F.

5. What is the Non-Parametric Replacement? Friedman ANOVA The Friedman ANOVA requires ordinal data and is similar to the Wilcoxon Matched-Pairs T Test.