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SCENARIO 13-1 a Large National Bank Charges Local Companies for Using

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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: 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: The results of the simple linear regression are provided below. two-tail p value =0.034 (for testing -Referring to Scenario 13-1, interpret the estimate of the Y-intercept of the line. A) All companies will be charged at least $2,700 by the bank. B) There is no practical interpretation since a sales revenue of $0 is a nonsensical value. C) About 95% of the observed service charges fall within $2,700 of the least squares line. D) For every $1 million increase in sales revenue, we expect a service charge to decrease $2,700. 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: The results of the simple linear regression are provided below. two-tail p value =0.034 (for testing -Referring to Scenario 13-1, interpret the estimate of the Y-intercept of the line. A) All companies will be charged at least $2,700 by the bank. B) There is no practical interpretation since a sales revenue of $0 is a nonsensical value. C) About 95% of the observed service charges fall within $2,700 of the least squares line. D) For every $1 million increase in sales revenue, we expect a service charge to decrease $2,700. 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: The results of the simple linear regression are provided below. two-tail p value =0.034 (for testing -Referring to Scenario 13-1, interpret the estimate of the Y-intercept of the line. A) All companies will be charged at least $2,700 by the bank. B) There is no practical interpretation since a sales revenue of $0 is a nonsensical value. C) About 95% of the observed service charges fall within $2,700 of the least squares line. D) For every $1 million increase in sales revenue, we expect a service charge to decrease $2,700. two-tail p value =0.034 (for testing 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: The results of the simple linear regression are provided below. two-tail p value =0.034 (for testing -Referring to Scenario 13-1, interpret the estimate of the Y-intercept of the line. A) All companies will be charged at least $2,700 by the bank. B) There is no practical interpretation since a sales revenue of $0 is a nonsensical value. C) About 95% of the observed service charges fall within $2,700 of the least squares line. D) For every $1 million increase in sales revenue, we expect a service charge to decrease $2,700.
-Referring to Scenario 13-1, interpret the estimate of 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: The results of the simple linear regression are provided below. two-tail p value =0.034 (for testing -Referring to Scenario 13-1, interpret the estimate of the Y-intercept of the line. A) All companies will be charged at least $2,700 by the bank. B) There is no practical interpretation since a sales revenue of $0 is a nonsensical value. C) About 95% of the observed service charges fall within $2,700 of the least squares line. D) For every $1 million increase in sales revenue, we expect a service charge to decrease $2,700. the Y-intercept of the line.


A) All companies will be charged at least $2,700 by the bank.
B) There is no practical interpretation since a sales revenue of $0 is a nonsensical value.
C) About 95% of the observed service charges fall within $2,700 of the least squares line.
D) For every $1 million increase in sales revenue, we expect a service charge to decrease $2,700.

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