Chapter 14 Solutions of Essentials of Business Statistics, 4th Edition

CHAPTER 14— Multiple Regression and Model Building

14.1 SSE

LO1

14.2 Insert x values into the least squares equation and solve for .

LO1

14.3 a. b1 = -0.900, For every 1 degree increase in average temperature estimate fuel usage goes down by 0.900 MMcf. b2 = 0.0825, For every 1 unit of increase in the chill index estimate average fuel usage goes up by 0.0825 MMcf.

b. Both the estimate and the prediction = 10.334 MMcf = 13.1087 – 0.900*40 + 0.0825*10.

LO1

14.4 a. bl = 5.6128, b2 = 3.8344

b1 = 5.6128 implies that we estimate that mean sales price increases by $5,612.80 for each increase of 100 square feet in house size, when the niceness rating stays constant.

b2 = 3.8344 implies that we estimate that mean sales price increases by $3,834.40 for each increase in niceness rating of 1, when the square footage remains constant.

b. 172.28. From = 29.347 + 5.6128(20) + 3.8344(8)

LO1

14.5 a. bl = –2.3577, b2 = 1.6122, b3 = 0.5012

b. = 8.41099, = 7.5891 – 2.3577(3.70) + 1.6122(3.90) + .5012(6.50)

LO1

14.6 a. b1 = 0.0386, b2 = 1.0394, b3 = –413.7578

b1: As x-ray exposures go up by 1 monthly labor hours go up by 0.0386.

b2: As bed days go up by 1 monthly labor hours go up by 1.0394.

b3: As length of stay goes up by 1 monthly labor hours go down by 413.7578.

b. = 15896.24725, from = 1946.802 + .03858 (56194) + 1.0394 (14077.88) – 413.7578 (6.89) = 15896.25.

c. Therefore, actual hours were 17207.31 – 15896.25 = 1311.06 hours greater than predicted.

LO1

14.7 (Variance and standard deviation of the populations of potential error term values)

LO2

14.8 a. The proportion of the total variation in the observed values of the dependent variable explained by the multiple regression model.

b. The adjusted Rsquared differs from Rsquared by taking into consideration the number of independent variables in the model.

LO3

14.9 Overall F-test used to determine if at least...