# Notes8(1) - depending on df for denominator. Example 1: 2...

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1 2-Way ANOVA Learning Objectives ± Compute 2-Way ANOVA by hand ± Calculate sums of squares for main effects and interaction ± Complete ANOVA source table ± Correctly interpret results ± Compute 2-Way ANOVA using SPSS ± Correctly interpret output ANOVA Partitions Variance ± Total variance is divided into ± Within groups – individual differences, nuisance variance, error ± Between groups – treatment effects & random error ± With 2-Way ANOVA, you have 2 IVs instead of 1. Variance between groups is partitioned into 2 Main Effects and an Interaction.

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2 ANOVA Significance Test ± ANOVA with 1 IV has 1 F test ± ANOVA with multiple IVs has multiple F tests, one for each Main Effect and one for each Interaction. ± With 2-Way ANOVA, there are two main effects and 1 interaction, so there are 3 F tests. All, some, or none may be significant. Critical values change
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Unformatted text preview: depending on df for denominator. Example 1: 2 kinds of Therapies ± Treatment of panic attacks. ± IV1: psychotherapy. 3 levels: conventional, experimental, and control (wait list). ± IV2: Anti-anxiety drug. 2 levels: drug vs. control. ± DV is number of panic attacks during 1 week after 6 wks therapy. ± See handout for data. Work thru example. Example 2: Types of training ± Military electronic troubleshooters fix radar, missile guidance systems, etc. ± Standard training is experience with common problems. ± New training. ± on top of standard training. ± IV1: Theory of electronics (new module). ± IV2: Practice of troubleshooting (new module). ± Work thru handout. 3 SPSS ± Download file. ± Run SPSS & match to hand computations. ± Produce a graph of the cell means....
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## This note was uploaded on 05/21/2011 for the course PSY 3213 taught by Professor Staff during the Fall '08 term at University of South Florida.

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Notes8(1) - depending on df for denominator. Example 1: 2...

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