This exercise utilizes the SPSS data set profile-e.sav, which can be downloaded from this Web site:

www.routledge.com/9781138289734

Conduct a Forward:LR logistic regression analysis with the following variables:

IV-age, educ, hrsl, sibs, rincom91, life2 (categorical)

DV-satjob2

Note:The variable life 2 is categorical such that dull=1, routine/exciting=2, and all other values are system missing.

1.Develop a research question for the following scenario.

2.Conduct a preliminary Linear Regressiontoidentify outliers and evaluate mulitcollinearity among the five continuous variables.Complete the following:

a.Using Chi-Square table in Appendix B, identify the critical value at p<.001 for identifying outliers.Use Explore to determine if there are outliers.Which cases should be eliminated?

b.Is multicollinearity a problem among the five continuous variables?

3.Conduct a Binary Logistic Regression using the Forward:LR method.

IV- age, educ, hrsl, sibs, rincom91, life2 (categorical;last is the reference category)

DV-satjob2

Note:Make sure that any outliers identified in Exercise 2a are removed from data before running the logisticregression.Also, designating life2 as a categorical covariate with the last category as the reference, essentially makes "routine/exciting"=0 and "dull"=1 , so interpret the results accordingly.

a.Which variables were entered into the model?

b.To what degree does the model fit the data?Explain.

c.Is the generated model significantly different from the constant-only model?

d.How accurate is the model in predicting job satisfaction?

e.What are the odds ratios for the model variables? Explain.