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lecture 11-30 - Review Buch 1910 Dec.8 5-7pm Factorial...

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November 30, 2004 Review: Buch 1910- Dec.8, 5-7pm Factorial Design (cont) Identifying effects To see if there are main effects, compare “marginal means” of DV Data: M=50 (Music & Caffeine) M= 60 (No Music & Caffeine) M= 70 (Music & No Caffeine) M= 60 (None) - take average of 50 & 60= 55 (Caffeine average) - take average of 70 & 60= 65 (No Caffeine average) - Main effect for caffeine: greater learning without caffeine than with - Compare music average (60) to no music average (60) no music effect - If marginal means differ, then there is a main effect for that factor (IV) But, main effects may not tell the whole story… -To see if there is an interaction effect, graph the cell means -X-axis= one IV variable (ex: Music/ No music) -Y-axis= DV variable scores (ex: 50, 60, etc.) Concl: There is an interaction effect if the lines are not parallel -Caffeine w/ music is bad but music w/o caffeine is ok Data: M=90 (M & C) M=70 (C & no M) M=70 (N.C & M) M=50 (None) Avg of caff= 80; avg of no caff= 60 Avg of music= 80; avg of no music= 60 -Conclusion: Main effect for caffeine: better scores w/ caffeine
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