Boiler drum production. In a production facility, an accurate estimate of man-hours needed to complete a task is required. A manufacturer of boiler drums used regression to predict the number of man-hours needed to erect the drums in future projects. To accomplish this, data for 35 boilers were collected. In addition to man-hours (y), the variables measured were boiler capacity 1x1 = lb/hr2, boiler design pressure (x2 = pounds per square inch or psi), boiler type (x3 = 1 if industry field erected, 0 if utility field erected), and drum type (x4 = 1 if steam, 0 if mud). The data are saved in the file. (The first five and last five observations are listed in the accompanying table.)

a. Fit the model E1y2 = b0 + b1x1 + b2x2 + b3x3 + b4x4 to the data. Give the estimates of the b’s.

b. Conduct a test for the global utility of the model. Use a = .01.

c. Find a 95% confidence interval for E1y2 whenx1 = 150,000, x2 = 500, x3 = 1, and x4 = 0. Interpret the result. Man-Hours, y Boiler Capacity, x1 Design Pressure, x2 Boiler Type, x3 Drum Type, x4 3,137 120,000 375 1 1 3,590 65,000 750 1 1 4,526 150,000 500 1 1 10,825 1,073,877 2,170 0 1 4,023 150,000 325 1 1 f f f f f 4,206 441,000 410 1 0 4,006 441,000 410 1 0 3,728 627,000 1,525 0 0 3,211 610,000 1,500 0 0 1,200 30,000 325 1 0