Cellulon, a manufacturer of home insulation, wants to develop guidelines for builders and consumers on how the thickness of the insulation in the attic of a home and the outdoor temperature affect natural gas consumption. In the laboratory, it varied the insulation thickness and temperature. A few of the findings are: Monthly Natural Gas Consumption (cubic feet), Thickness of Insulation (inches), Outdoor Temperature (ºF),
y x1 x2
30.3 6.0 32.0
25.2 12 40
30.5 8 49
On the basis of the sample results, the regression equation is:
yˆ y⁢^⁢  = 57.25 − 1.07x1 − 0.64x2

ŷ = -1.02674X1 + 0.13256X2 + 32.2186

Step-by-step explanation:

Given the data:

y x1 ___ x2

30.3__6.0__ 32.0

25.2__ 12___ 40

30.5__ 8 ___49

Using the multiple regression calculator ; the obtained regression model is :

ŷ = -1.02674X1 + 0.13256X2 + 32.2186

X1 = predictor variable 1 = Thickness of Insulation (inches)

X2 = predictor variable 2 = Outdoor Temperature (ºF),

Y = predicted variable = monthly Natural gas consumption.

12.4, 12.387, 12.26, 12.252, 6.241, 6.2, 6.015, 6.009, 1.411, 1.2, 1.056, 1.007, 0.31,   0.13, 0.5, 0.04

step-by-step explanation:

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