Q We have seen that elbow sleeves improve basketball shooting performance. We are interested in whether that effect is going to be the same regardless of a players skill level. We think that sleeves will make a bigger difference for performance (“Shots”) of novices compared to experts. In other words, we hypothesize that there will be an interaction between Sleeves and Skill level. Open the ANOVA basketball.sav data in SPSS. We will do a factorial ANOVA examining the main effects of Skill (Expert vs Novice) and Sleeves (Sleeves vs No Sleeves), and the interaction between the two factors. 1. Go to Analyze ? General Linear Model ? Univariate. 2. In Dependent Variable enter Shots per minute 3. In Fixed Factors, enter Basketball Skills and Elbow Sleeves. 4. It’s helpful to see plots. I typically put the primary effect I am interested in (Sleeves) on the horizontal axis, and my variable that influences my primary effect on separate lines (Skills). Click “Add” to add this plot to the output. 5. Go to EM Means and “Display Means For” Skill, Sleeves and Skill*Sleeves. This will show you the means by your different model factors. 6. Click on “Options” and choose “Estimates of Effect Sizes” and Continue. 7. With all that done, Click OK to run the model. The first section of the output shows you the main effects factors, and the N for each level of the factors, that are in the model. Note that it doesn’t do a full factorial breakdown (i.e., N for each of the 4 cells). GO to the “Test of Between-Subject Effects” Ignore the first two rows (they are relevant to GLM approach, but uninformative for interpreting the effects that we are interested in here). 1. What is the F ratio for the effects of Skill? 2. What are the dfs for that F ratio? 3. Is this effect significant (i.e., is that ratio significantly larger than 1)? What does that mean for the main effect of Skill? 4. What are the means by each level of Basketball Skills? 5. What is the F ratio for the effects of Sleeve?

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