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Useful application of multiple regression analysis

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A useful application of multiple regression analysis is Hedonic modeling. Hedonic models seek to explain the price of a good-such as a house-in terms of its attributes (e.g., number of bedrooms, square footage, or distance from the nearest toxic waste dump). Consider the following Hedonic model of home sale prices: Pricei = β0 + β1(Square footage)i + β2Bathroomsi + β3Bedroomsi + ui. Using data from 37 home sales, you estimate the model and obtain βˆ0 = 90000, βˆ1 = 1100,βˆ2 = 16000, βˆ3 = 35000, SE(βˆ1) = 650.

(a) Interpret each coefficient.

(b) What is the model's forecasted sale price for a 2500-square-foot home with 3 bedrooms and 2.5 bathrooms?

(c) In a remodeling frenzy, a homeowner adds an additional bedroom and an additional bath-room by splitting up existing rooms. What is the forecasted change in the price of her home?

(d) A homeowner adds a 450-square-foot bedroom and a 75-square-foot bathroom by extending the footprint of his home into an area that used to be a driveway. What is the forecasted change in the price of his home?

(e) Conduct two-sided tests of the hypothesis that square footage has no effect on sale price at the 10, 5, and 1 percent levels.

(f) Construct a 95 percent confidence interval for β1.

Reference no: EM132460731

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