TABLE 13-01
a Large National Bank Charges Local Companies $E(Y)=\beta_{0}+\beta_{1} X$

TABLE 13-01
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 charge 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:
$E(Y) =\beta_{0}+\beta_{1} X$
The results of the simple linear regression are provided below.
$\hat{Y}=-2,700+20 X, \mathrm{~S}_{Y X}=65, \text { two-tailed } p \text { value }=0.034\left(\text { for testing } \beta_{1}\right)$

-Referring to Table 13-1, interpret the p-value for testing whether þ1 exceeds 0.

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