EXERCISE 17.1: DETECTING VALID PREDICTORS (REVISITED)

OBJECTIVE: To reexamine the validity of predictors in a data set using multiple regression.

PROLOGUE: Exercise 8.2 examined a number of possible predictors of bus driver job performance. Using the entire set of predictors identified in Exercise 8.2, perform the following procedures to further examine the predictability of bus driver job performance, as indicated by the criterion of overall performance evaluation score (the variable pescore ). As before, the relevant data set is titled “Bus Driver.sav” (see Appendix B).

Perform a multiple regression analysis using pescore as the dependent variable and each of the six predictors identified in Exercise 8.2 as the independent variables.

Choose “enter” as the method.

1. What is the sample size analyzed?

2. What is the magnitude of the estimated multiple correlation coefficient ( R )

obtained in this analysis?

3. What is the magnitude of the estimated squared multiple correlation coefficient

( R 2 ) obtained in this analysis?

4. What is the magnitude of the standard error of estimate obtained in this analysis?

5. Write out the unstandardized regression equation.

6. Write out the standardized regression equation.

7. What predictors have significant regression weights?