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Author Question: A manufacturer of boiler drums wants to use regression to predict the number of man-hours needed to ... (Read 56 times)

Wadzanai

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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 + β1x1 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.


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Marked as best answer by Wadzanai on Jan 16, 2020

Gabe

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Wadzanai

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Reply 2 on: Jan 16, 2020
Great answer, keep it coming :)


meow1234

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Reply 3 on: Yesterday
Excellent

 

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