ELEMENTARY STATISTICS-W/ACCESS >CUSTOM<
3rd Edition
ISBN: 9781323594889
Author: Triola
Publisher: PEARSON C
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Textbook Question
Chapter 10.4, Problem 10BSC
City Fuel Consumption: Finding the Best Multiple Regression Equation. In Exercises 9-12, refer to the accompanying table, which was obtained using the data from 21 cars listed in Data Set 20 “Car Measurements" in Appendix B. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal).
10. If exactly two predictor (x) variables are to be used to predict the city fuel consumption, which two variables should be chosen? Why?
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Demand Estimation for The San Francisco Bread Company
Consider the hypothetical example of The San Francisco Bread Company, a San Francisco-based chain of bakery/cafes. San Francisco Bread Company has initiated an empirical estimation of customer traffic at 30 regional locations to help the firm formulate pricing and promotional plans for the coming year. Annual operating data for the 30 outlets appear in the attached Table 1.
The following regression equation was fit to these data:
Qi = b0 + b1Pi + b2Pxi + b3Adi + b4Ii + uit.
Where: Q is the number of meals served,
P is the average price per meal (customer ticket amount, in dollars),
Px is the average price charged by competitors (in dollars),
Ad is the local advertising budget for each outlet (in dollars),
I is the average income per household in each outlet’s service area,
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Demand Estimation for The San Francisco Bread Company
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Where: Q is the number of meals served,
P is the average price per meal (customer ticket amount, in dollars),
Px is the average price charged by competitors (in dollars),
Ad is the local advertising budget for each outlet (in dollars),
I is the average income per household in each outlet’s service area,
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Chapter 10 Solutions
ELEMENTARY STATISTICS-W/ACCESS >CUSTOM<
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