Print Questions 6. 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 throe lovels of education in the sales forco-high school degree, associate's degree, and bachelor's degree. The dummy variables have been defined as shown in the accompanying table. The accompanying Excel output shows the partially completed regression output from a random sample of employoes from the previous month. What is the predicted number of cars sold in a month for an employee with five years of sales experience, a base salary of $550, and an associate's degree? Round to one decimal place. Click here to view the dummy variables,? Click hore to view the Excel regression outrut, A. 12.0 B. 12.4 C. 13.6 D. 11,3 21PM Print Questions \begin{tabular}{|l|l|} \hline \multicolumn{2}{|l|}{ Predicted Y (niat) 11.37451} \\ \hline \multicolumn{2}{|c|}{ For Average Predicted Y (VHat) } \\ \hline Interval Half Width & 1.967459 \\ \hline Confldence Interval Lower Umit & 9.507054 \\ \hline Confidence Interval Upper Limit & 13.24197 \\ \hline \end{tabular} \begin{tabular}{|l|l|} \hline \multicolumn{2}{|c|}{ For Individual Response Y } \\ \hline Interval Half Width & 4.073127 \\ \hline Prediction Interval Lower Limlt & 7.301287 \\ \hline Prediction Interval Upper Limit & 15.97764 \\ \hline \end{tabular}