1. D. Wayne Mitchell, Ph.D. Kayla N. Jordan – Statistical Analyst Rstats Institute Psychology Department Missouri State University

2. Review of Statistical Terms I. Type I Error II. Type II Error III. Power IV.Effect Size

3. Four Common Effect Size Indices I. (r-squared) r 2 II. (omega-squared) ω 2 III. (eta-squared) η 2 IV. Cohen’s d

4. Size! Small, Medium, Large? Cohen’s d =.20; r 2 =.01 (small) Cohen’s d =.50; r 2 =.06 (medium) Cohen’s d =.80; r 2 =.14 (large)

5. I.Given the correlation result: (r (98) =.40, p <.05); r 2 =.16 II.Given the t-test result: (t (22) = 4.16, p <.05) ω 2 = (t 2 -1)/ (t 2 + df +1) =.40 r 2 or η 2 = t 2 / (t 2 + df ) =.44 Cohen’s d = 2t / = 1.77

6. One-Way ANOVA Results: See Pages 4 and 5 I.Omega-Squared II.Eta-Squared III.Glasses Delta

7. To do a Power Analysis See Suggestions; Page 7 I.Have to Estimate an Effect Size II.Estimate the Smallest Effect that You Want to Detect III.Realize the Complexity of the Design Requires Study to do Appropriate Power Analysis

8. Some Rules of Thumb with Correlation – Regression I. N > 50 + 8m (m = # IVs) II. N > 50 + m (for individual predictions) III. The effect one might expect… r xy = est. r xy √ r xx r yy

9. Some Needed Formulas f 2 = eta 2 / 1 - eta 2 d = Mean1 – Mean2 √ s 1 2 + s 2 2 / 2