Exercises 6 through 10 are based on the data set named Lesson 34 Exercise File 2 on the Web at http://www.prenhiacomigreensalkind. The data are from the following research study.

Sally is interested in predicting the number of relapses that occur after participation in an intensive inpatient substance abuse program. She has data from 120 women who are at least five years beyond their initial admission to the program. Upon entry into the treatment program, the women were evaluated with respect to their psychological state and, in particular, on depression propensity for substance abuse, and daily life stress. In addition, they completed two measures of social support—amount of social support

available to them (number of close relationships) and perceptions of the quality of their social support. She also has records that indicate the number of relapses that each woman has had in the first five years after entry into the treatment program. The SPSS file contains six variables: three psychological state variables (named depress for depression, subst for substance abuse, and stress for daily life stress.), two social support predictors named amt_ss for amount of social support and per_ss for perception of social support), and the number of relapses (named relapses).

6. Conduct a regression analysis to evaluate the relative importance of the psychological state predictors and the social support predictors in predicting the number

of substance abuse relapses.

7. What is the contribution of the set of social support predictors? Report the appropriate statistics.

8. What is the contribution of the psychological state predictors? Report the appropriate statistics.

9. Which variables in each set are the hest predictors of the number of relapses?

How did you arrive at your answer?

10. Write a Results section reporting the analyses you conducted.

LESSON 35

Exercises l through 5 are based on data found in the data file named Lesson 35 Exercise File 1 on the Web at http://www.prenhall.corn/greensalkind. The data are from the following study.

Dave wants to classify college professors into two groups—research scientists and teaching moguls. He obtains scores on four variables from 50 college professors: number of publications in last two years, amount of grant funding generated in last five years, mean teaching evaluation score for the last three semesters, and number of student committees served on during last five years. Dave then has three university administrators evaluate ail 50 professors as one of two types, research scientists and teaching moguls. The SPSS data file has 50 cases and five variables. The five variables are the four predictors and a grouping variable distinguishing research scientists and teaching moguls based on the judgments of the university administrators.

1. Conduct a discriminant analysis to distinguish professors who are research scientists from professors who are teaching moguls. From the output, identify the following:
   1. Research scientist group mean for number of publications
   2. Univariate ANOVA F value for grant money
   3. x2 associated with the discriminant function
2. What percent of research scientists are correctly classified? What is the overall percent of professors correctly classified as teaching moguls and research scientists?
3. Which predictor variables contribute the most to discriminating between research scientists and teaching moguls?
4. Create a combined groups plot to show the classification of the two groups.
5. Write a Results section based on your analyses.

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