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| 1 | |
Discuss the advantages of using a multivariate analysis strategy over separate univariate analyses. |
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| 2 | |
Outline the major assumptions of multivariate statistics, and show how violations of each might affect the outcome of a multivariate analysis. |
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| 3 | |
Discuss the applications of factor analysis. Under what conditions would you use the different types of factor analysis and why would you rotate factors? |
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| 4 | |
Compare and contrast partial and part correlations. What does each do with a third variable? |
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| 5 | |
Discuss why stepwise multiple regression is the least preferred regression method. |
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| 6 | |
Compare and contrast using unstandardized and standardized regression weights to evaluate the degree of contribution of a predictor to accounting for variance in the dependent variable. Is there a better alternative? Explain. |
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| 7 | |
Discuss when you would use discriminant analysis and canonical correlation. |
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| 8 | |
Briefly discuss the strategies that you could use to help interpret a significant main effect found with a MANOVA. |
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| 9 | |
Discuss why it is a good idea to use MANOVA to analyze data from a univariate within-subjects experiment. |
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| 10 | |
Describe several applications for loglinear analysis. |
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| 11 | |
Draw diagrams of the various causal relationships discussed in the path analysis section of the text. |
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| 12 | |
When would you use structural equation modeling (SEM)? In your answer, be sure to discuss the issue of latent variables and the role they play in SEM. |
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