A technology firm wants to determine the characteristics of potential customers for a new voice-activated home entertainment system.
Data set: Ch 12 – Exercise 06A.sav
Codebook
Variable: Purchase
Definition: [Outcome] Will the person buy this within 6 months?
Type: Continuous (0 = Will not buy it . . . 100 = Will buy it)
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical (0 = Female, 1 = Male)
Variable: Race
Definition: [Predictor] Race
Type: Categorical (0 = African American, 1 = Asian, 2 = Caucasian, 3 = Latino, 4 = Other)
Variable: Partner
Definition: [Predictor] Relational status
Type: Categorical (0 = Single, 1 = Partner)
Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Income
Definition: [Predictor] Annual income
Type: Continuous
Variable: Brand_ownership
Definition: [Predictor] Does the person already own any other product(s) of this brand
Type: Categorical (0 = Does not own this brand, 1 = Owns this brand)

This data set contains a polychotomous predictor variable (Race), which is represented by the corresponding dummy-coded variables.
Follow this load procedure:
1. Move Purchase into the Dependent box.
2. Move Gender, Partner, Age, Income, and Brand_ownership into the Independent(s) box.
3. Set Method to Forward.
4. Click Next.
5. Move Race.1, Race.2, Race.3, and Race.4 into the Independent(s) box.
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the multiple regression analysis and document your findings (overall R², R² change of statistically significant predictors, hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the multiple regression analysis results, hypothesis resolution, and implications of your findings.