The electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature (x1), the number of days in the month (x2), the average product purity (x3), and the tons of product produced (x4). The past year’s historical data are available and are presented in the following table:
(a) Fit a multiple linear regression model to these data.
(b) Estimate s2.
(c) Compute the standard errors of the regression coefficients.
(d) Predict power consumption for a month in which X1 =75OF, x2 = 24 days, x3 = 90%, and x4 = 98 tons.
y: Miles/gallon
x1: Displacement (cubic inches)
x2: Horsepower (foot-pounds)
x3: Torque (foot-pounds)
x4: Compression ratio
x5: Rear axle ratio
x6: Carburetor (barrels)
x7: No. of transmission speeds
x8: Overall length (inches)
x9: Width (inches)
x10: Weight (pounds)
x11: Type of transmission (A—automatic, M—manual)
