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Two-Way Between Groups ANOVA Chapter 14
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Two-Way ANOVAs Are used to evaluate effects of more than one IV on a DV Can determine individual and combined effects of the IVs
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The basic 2 WayANOVA situation 2 or more Nominal Independent Variable with two or more levels 1 Scale Dependent Variable Effects of Drug and Age on recovery time Effects of Exercise and Diet on number of friends Effects of Toy Color and Gender on toy popularity
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One Way ANOVA is Limited Previous data, hour of exercise by relationship status. If I want to look at sex differences for hours of exercise, I have to do a second one-way ANOVA, and it will not tell me if there is a connection between sex and relationship status on hours of exercise.
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Testing for Interactions An interaction occurs when two IVs have an effect in combination that we do not see when looking at each IV individually Two-Way ANOVAs include to nominal IVs and a scale DV Factorial ANOVA uses one scale DV and at least two nominal IVs (factors) –Factor: IV in a study with more than one IV
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Why Use Two-Way ANOVAs To evaluate effects of two IVs, it is more efficient to do a single study than two studies with one IV each. Can explore interactions between variables
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More ANOVA Vocabulary Cell: box depicting a unique combination of levels of IVs in a factorial design Main effect: When one IV influences the DV
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Two Types of Interactions in ANOVA Quantitative: interaction in which one IV exhibits strengthening or weakening of its effects at one or more levels of the other IV, but the direction of the effect does not change Qualitative: interaction of two or more IVs in which one IV reverses its effect depending on the level of the other IV
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What if both IVs influence the DV? This is an interaction
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Understanding Graphs Main Effects: distance between lines Quantitative
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Understanding Graphs Interactions: slopes of lines Qualitative
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Six Steps for Two-Way Between- Groups ANOVA Step 1. Identify the populations, distribution, and assumptions. Step 2. State the null and research hypotheses. Step 3. Determine the characteristics of the comparison distribution. Step 4. Determine critical values, or cutoffs. Step 5. Calculate the test statistic. Step 6. Make a decision.
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df Formulae for ANOVAs
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Determining the Cutoff Point
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Effect Size for Two-Way ANOVA
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Variations on ANOVA
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