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 the 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: E(Y) = ß0 + ß1X
The results of the simple linear regression are provided below.
= -2,700 + 20X, SYX = 65, two-tailed p value = 0.034 (for testing ß1)
Referring to Table 13-1, interpret the p value for testing whetherß1 exceeds 0.
A) For every $1 million increase in sales revenue, we expect a service charge to increase $0.034.
B) Sales revenue (X) is a poor predictor of service charge (Y).
C) There is sufficient evidence (at the a = 0.05) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y).
D) There is insufficient evidence (at the a = 0.10) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y).