V Empirical 5. Following is the regression output for a data from a random sample of house prices and the attributes that drive the prices. In the model below, price is the house price in $1000s, sqrft is size of house in square feet, and bdrms is number of bedrooms Dependent Variable: PRICE Method: Least Squares Variable C SQRFT BDRMS R-squared Adjusted R-squared Coefficient -19.315 31.04662 0.128436 0.013824 15.19819 9.483517 0.631918 0.623258 63.04484 337845.4 -487.999 72.96353 S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0 (a) Write estimated regression equation model. Sample: 188 Included observations: 88 Std. Error Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion (d) What does 0.631918 mean here? Hannan-Quinn criter. Durbin-Watson stat (c) Does having an additional bedroom significantly impact house prices? t-Statistic Prob. -0.62213 0.5355 9.290506 0.000 1.60259 0.1127 (b) What is the estimated increase in price for a house in $ with one more bedroom, holding everything else constant? 293.546 102.7134 11.15907 11.24352 11.19309 1.858074 (e) The first house in the sample has sqrft of 2,438 and bdrms 5. Find the predicted selling price for this house from the OLS regression line.
V Empirical 5. Following is the regression output for a data from a random sample of house prices and the attributes that drive the prices. In the model below, price is the house price in $1000s, sqrft is size of house in square feet, and bdrms is number of bedrooms Dependent Variable: PRICE Method: Least Squares Variable C SQRFT BDRMS R-squared Adjusted R-squared Coefficient -19.315 31.04662 0.128436 0.013824 15.19819 9.483517 0.631918 0.623258 63.04484 337845.4 -487.999 72.96353 S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0 (a) Write estimated regression equation model. Sample: 188 Included observations: 88 Std. Error Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion (d) What does 0.631918 mean here? Hannan-Quinn criter. Durbin-Watson stat (c) Does having an additional bedroom significantly impact house prices? t-Statistic Prob. -0.62213 0.5355 9.290506 0.000 1.60259 0.1127 (b) What is the estimated increase in price for a house in $ with one more bedroom, holding everything else constant? 293.546 102.7134 11.15907 11.24352 11.19309 1.858074 (e) The first house in the sample has sqrft of 2,438 and bdrms 5. Find the predicted selling price for this house from the OLS regression line.
Chapter3: Polynomial Functions
Section: Chapter Questions
Problem 18T
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