Use the following information to answer the question(s) below. Ford would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on the employee's number of years of sales experience (Exp), the employee's weekly base salary before commissions (Salary), and the education level of the employee. There are three levels of education in the sales force-high school degree, associate's degree, and bachelor's degree. The following dummy variables have been defined. Degree ED1 High School o Associate's o Bachelor's 1 ED2 0 1 0 The following Excel output shows the partially completed regression output from a random sample of employees from the previous month. SUMMARY OUTPUT Regression Statistics Multiple R 0.9035 R Square Adjusted R Square Standard Error 1.7353 Observations ANOVA SS MS F Significance 1.7353 Standard Error Observations ANOVA SS MS F Significance 4.0112E-07 Regression Residual Total 60.23 327.84 24 tStat Lower 95% Upper 95% Intercept Exp Salary ED1 ED2 Coefficients Standard Error 1.6448 1.6352 0.2393 0.1254 0.0127 0.0044 2.9845 1.3553 2.5638 1.0705 P-volue 0.3265 0.0709 0.0097 0.0396 0.0265 An employee with a bachelor's degree will average month than an employee with a high school degree. more cars sales per OA) 2.9845 B) 0.4207 C) 1.3553 D) 2.5638