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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? - PowerPoint PPT Presentation
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Chapter 6 Predicting Future Performance 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