A simple linear regression model was used to describe the relationship between sales revenue y (in thousands of dollars) and advertising expenditure x (also in thousands of dollars) for fast-food outlets during a 3-month period. A sample of 15 outlets yielded the accompanying summary quantities.

a x 514.10 a y 5 1438.50 a x2 5 13.92 a y2 5 140,354 a xy 5 1387.20 a 1y 2 y2 2 5 2401.85 a 1y 2 y^2 2 5 561.46

a. What proportion of observed variation in sales revenue can be attributed to the linear relationship between revenue and advertising expenditure?

b. Calculate se and sb.

c. Obtain a 90% confidence interval for

b, the average change in revenue associated with a $1000 (that is, 1-unit) increase in advertising expenditure.