A large national bank charges local companies for using theirservices. A bank official reported the results of a regressionanalysis designed to predict the bank's charges(Y)—measured in dollars per month—for servicesrendered to local companies. One independent variable used topredict the service charge to a company is the company's salesrevenue (X)—measured in millions of dollars. Datafor 21 companies who use the bank's services were used to fit themodel:

E(Y) = β0 +β1X

The results of the simple linear regression are provided below.

= -2,700 + 20X, SYX = 65, two-tailed p value = 0.034(for testing β1)

Interpret the estimate of σ, thestandard deviation of the random error term (standard error of theestimate) in the model.
A)About 95% of the observed service charges equal their correspondingpredicted values.
B)About 95% of the observed service charges fall within $65 of theleast squares line.
C)For every $1 million increase in sales revenue, we expect a servicecharge to increase $65.
D)About 95% of the observed service charges fall within $130 of theleast squares line.