Answer questions (a) through (e) using the following information and output for multiple regression. A real estate investor has devised a model to estimate home prices in a new suburban development. Data for a random sample of 30 homes were gathered on the selling price of the home (in units of $1,000), the home size (square feet), the lot size (in units of 1,000 square feet), and the number of bedrooms. The following multiple regression output was generated: Regression Statistics Multiple R 0.9647 R Square 0.9307 Adjusted R Square 0.9227 Standard Error 26.0389 Observations 30 Coefficients Standard Error t Stat P-value Intercept -34.6165 38.3735 -0.9021 0.3753 X1 (Sq ft) 0.1532 0.0184 8.3122 0.0000 X2 (Lot size) 9.0024 1.7120 5.2583 0.0002 X3 (Bedrooms) 17.3903 6.8905 2.5238 0.1259 a. Why is the coefficient for lot size appositive number? b. Which is the most statistically significant variable? What evidence shows this? c. Which is the least statistically significant variable? What evidence shows this? d. For a 0.05 level of significance, should any variable be dropped from this model? Why or why not? e. Predict the sales price of a 2,134-square foot home with a lot size of 13,400 square feet and three bedrooms.
Paper#13291 | Written in 18-Jul-2015Price : $25