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Chapter 6 (p153) Predicting Future Performance

Chapter 6 (p153) Predicting Future Performance. Criterion-Related Validation Kind of relation between X and Y (regression) Degree of relation (validity coefficient) Strength? Significant? How accurate are predictions? Regression & Correlation What’s the difference between the two?

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Chapter 6 (p153) Predicting Future Performance

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  1. Chapter 6 (p153)Predicting Future Performance • Criterion-Related Validation • Kind of relation between X and Y (regression) • Degree of relation (validity coefficient) • Strength? • Significant? • How accurate are predictions? • Regression & Correlation • What’s the difference between the two? • Significance Testing Chapter 6 Predicting Future Performance

  2. VALIDATION AS HYPOTHESIS TESTING • BIVARIATE REGRESSION • Linear Functions • MEASURES OF CORRELATION • Basic Concepts in Correlation • Residual and Error of Estimate • Generalized Definition of Correlation • Coefficient of Determination • Third Variables • Null Hypothesis and its Rejection Chapter 6 Predicting Future Performance

  3. The Product-Moment Coefficient of Correlation • What are these? Explain each • Non-linearity • Homoscedasticity and Equality of Prediction Error • Correlated Error • Unreliability • Reduced Variance • Group Heterogeneity • Questionable Data Points • A summary Caveat • Don’t over-estimate what you have • Sometimes you can’t control everything • You may need to get more data • Work with what you have Chapter 6 Predicting Future Performance

  4. Statistical Significance • The Logic of Significance Testing • Under what conditions could a low validity coefficient of .20 be useful? • Type I and Type II Errors and Statistical Power • Which is more important I or II? • How can you control power? • What are the three things power is affected by? • Explain why for each Chapter 6 Predicting Future Performance

  5. COMMENT ON STATISTICAL PREDICTION • What is the standard error of estimate? • Why is it an important consideration for prediction? • What is a problem with restriction range restriction in • The predictor • The criterion • What could be done about it? • Give an example of a curvilinear relationship between a predictor and creiterion Chapter 6 Predicting Future Performance

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