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.
The results of the simple linear regression are provided below.
= 2,700 + 20
x,
s = 65, 2-tailed
p-value = .064 (for testing
β1)
Interpret the
p-value for testing whether
β1 exceeds 0.
◦ For every $1 million increase in sales revenue (
x), we expect a service charge (
y) to increase $.064.
◦ There is insufficient evidence (at
α = .05) to conclude that service charge (
y) is positively linearly related to sales revenue (
x).
◦ Sales revenue (
x) is a poor predictor of service charge (
y).
◦ There is sufficient evidence (at
α = .05) to conclude that service charge (
y) is positively linearly related to sales revenue (
x) .
National Results of the Scholastic Assessment Test (SAT)
Industrial and transport sources are responsible for a large proportion of global GHG emission
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