Author Question: A manufacturer of boiler drums wants to use regression to predict the number of man-hours needed to ... (Read 61 times)

Wadzanai · **on:** Jan 16, 2020

A manufacturer of boiler drums wants to use regression to predict the number of man-hours needed to erect drums in the future. The manufacturer collected a random sample of 35 boilers and measured the following two variables:
MANHRS: y = Number of man-hours required to erect the drum
PRESSURE: x₁= Boiler design pressure (pounds per square inch, i.e., psi)
Initially, the simple linear model E(y) = β₀ + β_1x1 was fit to the data. A printout for the analysis appears below:

UNWEIGHTED LEAST SQUARES LINEAR REGRESSION OF MANHRS

Give a practical interpretation of the coefficient of determination, R². Express R² to the nearest whole percent.
◦ About 43% of the sample variation in number of man-hours can be explained by the simple linear model.
◦ About 2.06% of the sample variation in number of man-hours can be explained by the simple linear model.
◦

= 1.88 + 0.00321x will be correct 43% of the time.
◦ Man hours needed to erect drums will be associated with boiler design pressure 43% of the time.

Gabe · **Reply #1 on:** Jan 16, 2020

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