Question: (Q7) [Regression] Let's Conduct a regression analysis to understand what explains the differences in One-year Revenue ($) [revenue] among different members. Potential predictors that

$(Q7) [Regression] Lets Conduct a regression analysis to understand what explains the differences in One-year Revenue (\$) [$

(Q7) [Regression] Let's Conduct a regression analysis to understand what explains the differences in "One-year Revenue ($) [revenue]" among different members. Potential predictors that we are considering are "Age in Years [age]", "number of visits [visits]", "Gender [gender]", and "Work Status [status]". (7-a) Attach the SPSS output of the regression analysis. (When you run SPSS on a virtual desktop, you might not be able to copy an SPSS output and paste it to an MS Word doc in your local computer. An easy solution is to take a screenshot.) (7-b) What percentage of the total variation of [Revenue] is explained by the estimated regression equation? (7-c) With alpha=0.10, which of the independent variables have a significant impact on the dependent variable(=revenue)? (i.e., list all of the independent variables that have a significant impact on the dependent variable) (7-d) Given the estimated regression equation, what is the predicted revenue from an AFC member with the following profile: - [Age]: 65 years old - [Number of Visits]: 12 times per month - [Gender]: Female (1-Male / 2-Female) - [Work Status]: Retired (1-Employed/2=Retired)

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