1 / 34

# 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. Testing for Interactions.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.

## PowerPoint Slideshow about 'Two-Way Between Groups ANOVA' - donkor

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

### 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

• 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

• 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