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# Two-Way Between Groups ANOVA - PowerPoint PPT Presentation

Two-Way Between Groups ANOVA. Chapter 14. 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. The basic 2 WayANOVA situation. 2 or more Nominal Independent Variable with two or more levels

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### Two-Way Between Groups ANOVA

Chapter 14

• Are used to evaluate effects of more than one IV on a DV

• Can determine individual and combined effects of the IVs

• 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

• 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.

• 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

• 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

• Cell: box depicting a unique combination of levels of IVs in a factorial design

• Main effect: When one IV influences the DV

• 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

• This is an interaction

• Main Effects: distance between lines

• Quantitative

• Interactions: slopes of lines

• Qualitative

• 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.

df Formulae for ANOVAs