Question 4 [5 marks]

FCI owns 10 apartment buildings in a college town, which it rents exclusively to students. Each apartment building contains 100 rental units, but the owner is having cash flow problems due to an average vacancy rate of nearly 50 percent. The apartments in each building have comparable floor plans, but some buildings are closer to campus than others. The owner of FCI has data from last year on the number of apartments rented, the rental price (in dollars), and the amount spent on advertising (in hundreds of dollars) at each of the 10 apartments. These data, along with the distance (in miles) from each apartment building to campus, are presented in rows 1 through 11 of Table 3-9. The owner regressed the quantity demanded of apartments on price, advertising, and distance. The results of the regression are reported in rows 16 through 35 of Table 3-9.

A.What is the estimated demand function for FCI's rental units?

B.If FCI raised rents at one complex by $120, what would you expect to happen to the number of units rented?

C.If FCI raised rents at an average apartment building, what would happen to FCI's total revenues?

D.What inferences should be drawn from this analysis?

*See attachment for Data*

D. What inferences should be drawn from this analysis? D m G No A B C Observation Quantity Price Advertising Distance 12 2 28 250 11 70 400 24 16 4 43 450 15 UI 4 32 550 31 18 UT 42 576 34 6 73 376 23 66 375 13 15 O 49 450 24 10 70 400 22 4 e ESC OX F2 F3 F4 O- F5 F6 F7 F8 F9 A & 5 6 7 Q W E R T Y A S D F G H J Z X C V B N- A moodle.sus.edu/mod/assign/view.php?id=491276 E in 400 4 10 70 22 12 10 60 375 10 13 Average 53.30 420.20 20.70 5.90 14 15 16 Regression Statistic 17 18 Multiple R 0.89 9 R-square 10.79 20 Adjusted R- 10.69 square 21 Standard Error 9.18 22 Observations 10.00 23 24 Analysis of Variance 9 DEAL ESC F1 F2 Ox F3 F4 F5 F7 F8 & 2 B 4 5 tab Q W E R T Y U 4 ps lock A S D F G H3 24 Analysis of Variance Significance 25 df Sum of Mean SquareF Squares F 26 Regression 3.00 1920.99 640.33 7.59 0.0182 27 Residual 6.00 505.91 184.32 28 Total 9.00 2426.90 29 30 Coefficients Standard t-statitsic p-value Lower 95% Upper 95% Error 31 32 Intercept 135.15 20.65 6.54 0.0006 84.61 185.68 33 Price 0. 14 0.06 -2.41 0.0500 -0.29 0.00 34 Advertising 0.54 0.64 0.85 0.4296 -1.02 2.09 35 Distance 5.78 1.28 4.61 0.0037 8.86 -2.71 e w ESC F1 F2 F3 F4 F5 F6 F7 F8 FO @ 2 A 5 8 Q W E R T Y U A A S D F G H