A public opinion consultant is interested in the demographics of those who are in favor of capital punishment (death penalty).
Data set: Ch 13 – Exercise 03B.sav
Codebook
Variable: Death_penalty
Definition: [Outcome] Are you in favor of the death penalty?
Type: Categorical 0 = Anti-death penalty
1 = Pro-death penalty [←BASIS FOR MODEL]

Variable: Age
Definition: [Predictor] Age
Type: Continuous
Variable: Gender
Definition: [Predictor] Gender
Type: Categorical 0 = Female [←REFERENCE]
1 = Male
Variable: Race
Definition: [Predictor] Race
Type: Categorical
0 = African American [←REFERENCE]
1 = Asian
2 = Caucasian
3 = Latino
4 = Other
Variable: Religion
Definition: [Predictor] Religion
Type: Categorical
0 = Atheist [←REFERENCE]
1 = Buddhist
2 = Catholic

3 = Hindu
4 = Jewish
5 = Other
Variable: Education
Definition: [Predictor] Years of education
Type: Continuous (High school = 12, Associate’s = 14,
Bachelor’s = 16, Master’s = 18, Doctorate > 18)
a. Write the hypotheses.
b. Run each criterion of the pretest checklist (sample size, normality, multicollinearity) and discuss your findings.
c. Run the logistic regression analysis and document your findings (odds ratios and Sig. [p value], hypotheses resolution).
d. Write an abstract under 200 words detailing a summary of the study, the logistic regression analysis results, hypothesis resolution, and implications of your findings.

The B data set is the same as the A data set with the following modifications:

The Race variable has been recoded so that Other is now the reference category:
Categorical
0 = Other [←REFERENCE]
1 = Asian
2 = Caucasian
3 = Latino
4 = African American
The Religion variable has been recoded so that Other is now the reference category:
Categorical
0 = Other [←REFERENCE]
1 = Buddhist
2 = Catholic
3 = Hindu
4 = Jewish
5 = Atheist