Concept explainers
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 (x1 = lb/hr) , 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 E(y) = β0 + β1x1 + β2x2 + β3x3 + β4x4 to the data. Give the estimates of the β’.
- b. Conduct a test for the global utility of the model. Use α=.01.
- c. Find a 95% confidence interval for E(y) when x1 = 150,000, x2 = 500, x3 = 1, and x4 = 0. Interpret the result.
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