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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 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. 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 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. 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 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. 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 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.
-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 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. the standard deviation of the random error term (standard error of the estimate) in the model.


Definitions:

Direct Controls

Government policies that directly constrain activities that generate negative externalities. Examples include maximum emissions limits for factory smokestacks and laws mandating the proper disposal of toxic wastes.

Economic Efficiency

A situation where resources are allocated in a way that maximizes the net benefit to society or achieves the desired output with the least waste.

Negative Externalities

Costs suffered by a third party as a result of an economic transaction or activity, not reflected in the transaction's price.

Traffic Congestion

A condition on road networks that occurs as use increases, and is characterized by slower speeds, longer trip times, and increased vehicular queueing.

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