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TABLE 13-1 A Large National Bank Charges Local Companies for Using Their

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TABLE 13-1
A large national bank charges local companies for using their services.A bank official reported the results of a regression analysis designed to predict the bank's charges (Y) -measured in dollars per month-for services rendered to local companies.One independent variable used to predict service charges to a company is the company's sales revenue (X) -measured in millions of dollars.Data for 21 companies who use the bank's services were used to fit the model:
Yi = β0 + β1Xi + εi
The results of the simple linear regression are provided below. TABLE 13-1 A large national bank charges local companies for using their services.A bank official reported the results of a regression analysis designed to predict the bank's charges (Y) -measured in dollars per month-for services rendered to local companies.One independent variable used to predict service charges to a company is the company's sales revenue (X) -measured in millions of dollars.Data for 21 companies who use the bank's services were used to fit the model: Y<sub>i</sub> = β<sub>0</sub> + β<sub>1</sub>X<sub>i</sub> + ε<sub>i</sub> The results of the simple linear regression are provided below.   -Referring to Table 13-1,interpret the p-value for testing whether β<sub>1</sub>exceeds 0. A) There is sufficient evidence (at the α = 0.05) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y) . B) There is insufficient evidence (at the α = 0.10) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y) . C) Sales revenue (X) is a poor predictor of service charge (Y) . D) For every $1 million increase in sales revenue,you expect a service charge to increase $0.034.
-Referring to Table 13-1,interpret the p-value for testing whether β1exceeds 0.


A) There is sufficient evidence (at the α = 0.05) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y) .
B) There is insufficient evidence (at the α = 0.10) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y) .
C) Sales revenue (X) is a poor predictor of service charge (Y) .
D) For every $1 million increase in sales revenue,you expect a service charge to increase $0.034.

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