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Chapter 7 Using Multivariate Statistics P173

Chapter 7 Using Multivariate Statistics P173. Multiple Regression Multiple Correlation What’s the difference between regression and correlation? Validity Generalization. COMPENSATORY PREDICTION MODELS. Regression Equations Y = a + b 1 X 1 + b 2 X 2

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Chapter 7 Using Multivariate Statistics P173

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  1. Chapter 7 Using Multivariate Statistics P173 • Multiple Regression • Multiple Correlation • What’s the difference between regression and correlation? • Validity Generalization Chap 7 Multivariate Statistics

  2. 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

  3. 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? • Sequential Hurdles • When could this be useful? Chap 7 Multivariate Statistics

  4. REPLICATION AND CROSS-VALIDATION • What IS cross validation? • Why is it necessary? Chap 7 Multivariate Statistics

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