Problem # 1.

The data set for this problem was collected from home sales in Blowing Rock, North Carolina (which islocated in the mountains of NC). The price that people are willing to pay for a house isdetermined by a variety of characteristics of the house and available amenities (e.g., closeness to schoolsorshopping).Theprovideddatasetcontainssomeofthesevariables.Usingthedatasetin the spreadsheet, estimate the following model and answer thefollowing questions:(10)

Price = o + 1*Bedrooms + 2*Fullbath + 3*Halfbath + 4*Miles + 5*Sqft + 6*Garage + 7*Acres + 8*View + 9*Days

The variables are defined as follows:

Price = the price at which the house sold in year t(indollars);Bedrooms = the number of bedrooms in thehouse;

Fullbath = the number of full bathrooms inthehouse; Halfbath = the number of half bathrooms in thehouse;

Miles = the number of miles to the nearestshoppingcenter;Sqft =the number of square feet in thehouse;

Garage =the number of cars that can be parked in the garage

Acres = the number of acres of property that comes withthehouse

View = the quality of the view of the mountains form the house (1= good view and0= poor or noview)

Days = the number of days the house was on the market before it wassold

1. Which variables are significant at a critical value of +/-1.96.
2. How much of the variation in the sale price of the house isexplained by thismodel?
3. Interpret the coefficient estimate onMiles.
4. Interpret the coefficient estimate onBedrooms.
5. Forecast the price of a house if the variables take on the following values:

Bedrooms =3; Fullbath = 2; Halfbath = 2; Miles = 4.5; Sqft =2,250;Garage = 3;Acres = 3.75; and Days = 225. The house has a good view of the mountains.