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The following data give the selling price, square footage, number of bedrooms, a

ID: 3442209 • Letter: T

Question

The following data give the selling price, square footage, number of bedrooms, and age of houses that have sold in a neighborhood in the past 6 months. Develop three regressions models to predict the selling price based upon each of the other factors individually. Which is best?

SELLING PRICE ($) SQUARE FOOTAGE BEDROOMS AGE (YEARS) 84000 1670 2 30 79000 1339 2 25 91500 1712 3 30 120000 1840 3 40 127500 2300 3 18 132500 2234 3 30 145000 2311 3 19 164000 2377 3 7 155000 2736 4 10 168000 2500 3 1 172500 2500 4 3 174000 2479 3 3 175000 2400 3 1 177500 3124 4 0 184000 2500 3 2 195500 4062 4 10 195000 2854 3 3

Explanation / Answer

Model 1 is better than others because the R-squared value is higher than others.

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Model 1:

price= 91,446.493 +29.8579*Square Footage+2,116.8554*Bedrooms-1,504.7659*Age (Years)

R-squared= 0.86777

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Model 2:

Price = 26,532.2361 + 51.0272*Square Footage

R-squared= 0.69996

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Model 3:

Price=20,331.6327 + 41,403.0612*Bedrooms

R-squared=0.4332

Regression output confidence interval variables coefficients std. error    t (df=13) p-value 95% lower 95% upper Intercept 91,446.4930 26,076.8905 3.507 .0039 35,110.7962 147,782.1897 Square Footage 29.8579 10.8609 2.749 .0166 6.3943 53.3214 Bedrooms 2,116.8554 10,003.0092 0.212 .8357 -19,493.3321 23,727.0430 Age (Years) -1,504.7659 370.8204 -4.058 .0014 -2,305.8746 -703.6572
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