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