The following table contains 25 observations by year of these variables: Year Revenue Per Dollar Number of Offices Profit Margin 1 3.92 7298 0.75 2 3.61 6855 0.71 3 3.32 6636 0.66 4 3.07 6506 0.61 5 3.06 6450 0.7 6 3.11 6402 0.72 7 3.21 6368 0.77 8 3.26 6340 0.74 9 3.42 6349 0.9 10 3.42 6352 0.82 11 3.45 6361 0.75 12 3.58 6369 0.77 13 3.66 6546 0.78 14 3.78 6672 0.84 15 3.82 6890 0.79 16 3.97 7115 0.7 17 4.07 7327 0.68 18 4.25 7546 0.72 19 4.41 7931 0.55 20 4.49 8097 0.63 21 4.7 8468 0.56 22 4.58 8717 0.41 23 4.69 8991 0.51 24 4.71 9179 0.47 25 4.78 9318 0.32 a. Develop an estimated regression equation that can be used to predict the annual profit margin using the information about revenue per dollar and number of offices. b. Interpret coefficients. How profit margin will change when the number of offices increase by 100? c. Compute the coefficent of determination and interpret it. d. At 95% confidence, determine which variable are significant and which are not. e. At 95% confidence, is the regression model significant? f. If in a given year, the number of offices is 9000 and revenue per dollar is $5, what would you expect the profit margin to be?