can you explain how to run the mutiple regression.

\begin{tabular}{|l|c|c|c|} \hline D35 & B & \\ \hline & A & Bx & \\ \hline \end{tabular} \begin{tabular}{|c|cccc} \hline 1 & WC premium in thousands & Payroll in thousands & Manufacturing & Metropolitan \\ \hline 2 & 7 & 380 & 0 & 0 \\ \hline 3 & 7.3 & 410 & 0 & 0 \\ \hline 4 & 7.8 & 443 & 0 & 1 \\ \hline 5 & 8.2 & 480 & 0 & 0 \\ \hline 6 & 8.5 & 520 & 0 & 1 \\ \hline 7 & 9.2 & 566 & 0 & 0 \\ \hline 8 & 9.9 & 616 & 1 & 0 \\ \hline 9 & 10.6 & 672 & 0 & 0 \\ \hline 10 & 11.4 & 733 & 1 & 1 \\ \hline 11 & 12.2 & 802 & 0 & 1 \\ \hline 12 & 12.9 & 878 & 1 & 0 \\ \hline 13 & 13.5 & 963 & 0 & 1 \\ \hline 14 & 14.5 & 1057 & 1 & 1 \\ \hline 15 & 15.6 & 1161 & 1 & 0 \\ \hline 16 & 16.8 & 1277 & 1 & 1 \\ \hline 17 & 17.3 & 1405 & 1 & 0 \\ 18 & 18.2 & 1548 & 1 & 0 \\ 19 & 19.8 & 1706 & 1 & 1 \\ 20 & 20.5 & 1882 & 1 & 1 \\ \hline 21 & 21.5 & 2077 & 0 & 0 \\ \hline 22 & 23 & 2293 & 1 & 1 \\ \hline 23 & 24.1 & 2534 & 1 & 1 \end{tabular} In the simple regression, interpret the relationship between the independent variable and the dependent variable in terms of the coefficients. When a company's amount of payroll increases by $1.000, how much would you expect the amount of workers compensation premium to go up by? A) $0.0082 B) $8.2 C) $8,200 D) 28.5619 Run a multiple regression using both number of payroll in thousands and the indicator variable manufacturing to predict workers compensation premiums. What statistic in the regression would you use to explain to the risk manager how useful this model is in general? A) R Square 0.9831 B) R Square 0.9952 C) Adjusted R Square 0.9756 D) Adjusted R Square 0.9813 This question is related to Question 3. What are the estimated coefficients for Payroll in thousands and Manufacturing, respectively? A) 4.9789 and 0.3168 B) 0.0003 and 0.4430 C) 0.0075 and 1.2448 D) 0.0149 and 1.3842