Answer these questions directly on this document. You will submit two files for your assignment: this document, plus your regression results in Excel 1. The Hospital Data tab of the Chapter 4 Assignment Data spreadsheet contains information on the total expenses of hospitals and the number of admissions in those hospitals. Perform a regression on this data with total expenses as the Y variable, and answer the following questions. (a) Find the equation that relates total expenses (Y) to number of admissions (X). ?= 1.41+.67X (b) Predict the total expenses of a hospital with 90,000 admissions. (c) Find SST: SSE: SSR: and MSE: (d) Find the coefficient of determination, and interpret what this value means in the context of this hospital data. (e) Find the significance of F. Based on this value, is our model statistically significant at the 5% level? Is there a relationship between total expenses and number of admissions? 2. The Housing Data tab of the Chapter 4 Assignment Data spreadsheet contains information on the sales prices of houses, their square footage, and their age. Perform a regression on this data with sales price as the Y variable, and answer the following questions. (a) Find the equation that relates sales price (Y) to square footage (X1) and age (X2). (b) Estimate the sales price of a home with square footage 2,000 and age 20. (c) Find the coefficient of determination, and interpret what this value means in the context of this housing data. (d) Find the significance of F. Based on this value, is our model statistically significant at the 5% level? (e) Find the p-value for square footage and the p-value for age. At the 5% level, is square footage alone a statistically significant variable in determining sales price? Is age alone a statistically significant variable in determining sales price? Explain how you know.

(X-X) (X-X) (Y-Y) X: Admissions (thousands) 57 77 (77-77)= 0 (77-77)(57-53) = 0 127 160 (160-77)= 6889 (160-77)(127-53)= 6142 157 230 (230-77)= 23409 (230-77)(157-53) = 15912 24 43 (43-77)= 1156 (43-77)(24-53)= 986 14 9 (9-77)= 4624 (9-77)(14-53)= 2652 93 155 (155-77)= 6084 (155-77)(93-53) = 3120 45 53 (53-77)= 576 (53-77)(45-53) = 192 6 6 (6-77)= 5041 (6-77)(6-53) = 3337 99 159 (159-77)= 6724 (159-77)(99-53) = 3772 12 18 (18-77)= 3481 (18-77)(12-53) = 2419 11 16 (16-77)= 3721 (16-77)(11-53) = 2562 15 29 (29-77)= 2304 (29-77)(15-53) = 1824 21 28 (28-77)= 2401 (28-77)(21-53) = 1519 63 98 (98-77)= 441 (98-77)(63-53)= 210 X = 77 (X-X)= 4775 (X-X)(Y-Y)= 3189 Y: Total Expenses (millions) Y = 53 b = 0.67 b = 1.41 = 1.41+.67X Y X1 X2 Selling Price ($) Square Feet Age (Years) 64000 1670 30 59000 1339 25 61500 1712 30 79000 1840 40 87500 2300 18 92500 2234 30 95000 2311 19 113000 2377 7