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A Large National Bank Charges Local Companies for Using Their E(y)=β0+β1x.E ( y ) = \beta _ { 0 } + \beta _ { 1 } x .

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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 charge to a company is the company's sales revenue (x), measured in $ million. Data for 21 companies who use the bank's services were used to fit the model E(y)=β0+β1x.E ( y ) = \beta _ { 0 } + \beta _ { 1 } x .
The results of the simple linear regression are provided below.
y^=2,700+20x,s=65,2-tailed p-value =.064 (for testing β1 ) \hat { y } = 2,700 + 20 x , s = 65,2 \text {-tailed } p \text {-value } = .064 \text { (for testing } \beta _ { 1 } \text { ) }
Interpret the pp -value for testing whether β1\beta _ { 1 } exceeds 0 .
A) There is sufficient evidence (at α=.05\alpha = .05 ) to conclude that service charge (y)( y ) is positively linearly related to sales revenue (x)( x ) .
B) For every $1\$ 1 million increase in sales revenue (x)( x ) , we expect a service charge (y)( y ) to increase $.064\$ .064 .
C) There is insufficient evidence (at α=.05\alpha = .05 ) to conclude that service charge ( yy ) is positively linearly related to sales revenue (x)( x ) .
D) Sales revenue (x)( x ) is a poor predictor of service charge (y)( y ) .

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