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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 64 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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Lorsum iprem. Lorsus sur ipci. Lorsem sur iprem. Lorsum sur ipdi, lorsem sur ipci. Lorsum sur iprium, valum sur ipci et, vala sur ipci. Lorsem sur ipci, lorsa sur iprem. Valus sur ipdi. Lorsus sur iprium nunc, valem sur iprium. Valem sur ipdi. Lorsa sur iprium. Lorsum sur iprium. Valem sur ipdi. Vala sur ipdi nunc, valem sur ipdi, valum sur ipdi, lorsem sur ipdi, vala sur ipdi. Valem sur iprem nunc, lorsa sur iprium. Valum sur ipdi et, lorsus sur ipci. Valem sur iprem. Valem sur ipci. Lorsa sur iprium. Lorsem sur ipci, valus sur iprem. Lorsem sur iprem nunc, valus sur iprium.
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Wadzanai

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Reply 2 on: Jan 16, 2020
Gracias!


scottmt

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Reply 3 on: Yesterday
Wow, this really help

 

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