4. Run a linear regression analysis to examine what are the important factors that determine the revenue. More specifically, consider the following equation:

[Revenue] = 0

+ 1 * [status]

+ 2 * [number of visits]

+ 3 * [Gender]

paste the Excel output below. (See lecture 11 materials for regression.)

Based on the regression, please answer question 4.1 and 4.2 . (Please highlight your choice.)

4.1. Among the independent variables, what is(are) the variable(s) whose impact(s) on the dependent variable(=revenue) is significantly different from zero (with = .05)? [16 points]

a) status

b) visit

c) visit and status

d) visit, status, and gender

4.2. Given the estimated regression equation, what is the predicted revenue ($) from an AFC member with the following profile: [16 points]

- [status]: retired (=1)

- [number of visits]: 10 times

-[Gender]: Female (=1)

a) 716.0

b) 448.6

c) 482.6

d) 617.6

[Hint for 4.1: conduct the regression and read the 'P-value' for each coefficient. If P-value < , thevariablehassignificant impact; if P-value > , thevariabledoes not have significant impact.]

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