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A Large National Bank Charges Local Companies for Using Its

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A large national bank charges local companies for using its 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 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, A large national bank charges local companies for using its 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 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,   The results of the simple linear regression are provided below.   = 2,700 + 20x, s = 65, 2-tailed p-value = 0.064 (for testing   ) Interpret the estimate of   , the y-intercept of the line. A)  All companies will be charged at least $2,700 by the bank. B)  About 95% of the observed service charges fall within $2,700 of the least squares line. C)  There is no practical interpretation since a sales revenue of $0 is a nonsensical value. D)  For every $1 million increase in sales revenue, we expect a service charge to increase $2,700. The results of the simple linear regression are provided below. A large national bank charges local companies for using its 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 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,   The results of the simple linear regression are provided below.   = 2,700 + 20x, s = 65, 2-tailed p-value = 0.064 (for testing   ) Interpret the estimate of   , the y-intercept of the line. A)  All companies will be charged at least $2,700 by the bank. B)  About 95% of the observed service charges fall within $2,700 of the least squares line. C)  There is no practical interpretation since a sales revenue of $0 is a nonsensical value. D)  For every $1 million increase in sales revenue, we expect a service charge to increase $2,700. = 2,700 + 20x, s = 65, 2-tailed p-value = 0.064 (for testing A large national bank charges local companies for using its 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 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,   The results of the simple linear regression are provided below.   = 2,700 + 20x, s = 65, 2-tailed p-value = 0.064 (for testing   ) Interpret the estimate of   , the y-intercept of the line. A)  All companies will be charged at least $2,700 by the bank. B)  About 95% of the observed service charges fall within $2,700 of the least squares line. C)  There is no practical interpretation since a sales revenue of $0 is a nonsensical value. D)  For every $1 million increase in sales revenue, we expect a service charge to increase $2,700. ) Interpret the estimate of A large national bank charges local companies for using its 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 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,   The results of the simple linear regression are provided below.   = 2,700 + 20x, s = 65, 2-tailed p-value = 0.064 (for testing   ) Interpret the estimate of   , the y-intercept of the line. A)  All companies will be charged at least $2,700 by the bank. B)  About 95% of the observed service charges fall within $2,700 of the least squares line. C)  There is no practical interpretation since a sales revenue of $0 is a nonsensical value. D)  For every $1 million increase in sales revenue, we expect a service charge to increase $2,700. , the y-intercept of the line.


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

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