A sales director for a chain of appliance stores wants to find out what circumstances encourage customers to purchase extended warranties after a major appliance purchase. The response variable is an indicator of whether or not a warranty is purchased. The predictor variables they want to consider are
Customer gender
Age of the customer
Whether a gift is offered with the warranty
Price of the appliance
Race of customer
There are several strategies you can take to develop the “best” model for the data. It is recommended that you examine several models before determining which one is best for your analysis. (In this example we allow the computer to help specify important variables, but it is inadvisable to accept a computer designated model without examining alternatives.) Begin by examining the significance of each variable in a fully populated model.
1. Open the data set named WARRANTY.SAV (downloadable from the data section) and choose Analyze/Regression/Binary Logistic.
2. Select Bought as the dependent variable and Gender, Gift, Age, Price, and Race as the covariates (i.e. the independent or predictor) variables.
3. Click on the Categorical checkbox (It is a button in SPSS version 16) and specify Race as a categorical variable. Click Continue and then OK. This produces the following SPSS output table.