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

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

(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:


-Referring to Table 13-1, interpret the estimate of a, the standard deviation of the random error term (standard error of the estimate) in the model.

A) About 95% of the observed service charges fall within $130 of the least squares line.
B) For every $1 million increase in sales revenue, we expect a service charge to increase $65.
C) About 95% of the observed service charges fall within $65 of the least squares line.
D) About 95% of the observed service charges equal their corresponding predicted values.