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Chapter 7 Using Multivariate Statistics P173PowerPoint Presentation

Chapter 7 Using Multivariate Statistics P173

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Chapter 7 Using Multivariate Statistics P173

- Multiple Regression
- Multiple Correlation
- What’s the difference between regression and correlation?

- Validity Generalization

Chap 7 Multivariate Statistics

COMPENSATORY PREDICTION MODELS

- Regression Equations
- Y = a + b1X1 + b2X2
- what’s the difference between b and β weights?
- Why use one or the other?

- Multiple Correlation
- How are the correlations among the predictors related to the multiple R?
- Would you want high correlations among predictors?

- Suppressors and Moderator Variables
- Examples of suppressor variables
- Suppressor variables explained
- Suppressors
- How could reading ability act as a suppressor for security guard performance?

- Moderators
- How could social skills moderate the conscientiousness-performance relationship?

- Other Additive Composites
- Unit weighting is usually sufficient
- Could you add veterans’ preference or religious preference?

Chap 7 Multivariate Statistics

NONCOMPENSATORY PREDITION MODELS

- Multiple Cutoff Models
- Two situations warrant it:
- 1. vital trait
- 2. if variance is too low (small) to yield sig r.

- What can happen if cutoffs are all very low?
- What can happen if cutoffs are all very high?

- Two situations warrant it:
- Sequential Hurdles
- When could this be useful?

Chap 7 Multivariate Statistics

REPLICATION AND CROSS-VALIDATION

- What IS cross validation?
- Why is it necessary?

Chap 7 Multivariate Statistics

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