SCENARIO 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_i=

\beta

₀ +

\beta

₁ X_i+

\varepsilon

_i
The results of the simple linear regression are provided below. $SCENARIO 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 = \beta 0 + \beta 1 Xi + \varepsilon i The results of the simple linear regression are provided below. ? = -2,700 +20 X ,SYX = 65,two-tail p value = 0.034 (for testing \beta 1) -Referring to Scenario 13-1,interpret the estimate of ?,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 $65 of the least squares line. B)About 95% of the observed service charges equal their corresponding predicted values. C)About 95% of the observed service charges fall within $130 of the least squares line. D)For every $1 million increase in sales revenue,we expect a service charge to increase $65.$
? = -2,700 +20 X ,S_Y_X= 65,two-tail p value = 0.034 (for testing

\beta

₁)
11eb129a_22de_eb6b_935a_932306595b21_TB6723_00
-Referring to Scenario 13-1,interpret the estimate of ?,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 $65 of the least squares line.
B)About 95% of the observed service charges equal their corresponding predicted values.
C)About 95% of the observed service charges fall within $130 of the least squares line.
D)For every $1 million increase in sales revenue,we expect a service charge to increase $65.

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