Information for a random sample of homes for sale in a certain region was obtain
ID: 3067350 • Letter: I
Question
Information for a random sample of homes for sale in a certain region was obtained from the Internet. Regression output modeling the Asking Price with Square Footage and number of Bathrooms gave the following result. Complet arts a through d Click to see the regression output along with the ANOVA table Dependent Variable is: Asking Price s-64889 R-Sq-71.4% R-Sq (adj)-65.0% T P-value 0.094 0.822 0.011 Coeff SE(Coeff) Predictor Intercept Baths Sq ft 159546 9502 134.83 85244 -1.87 40905 42.58 0.23 3.17 Analysis of Variance DF MS F P-value Source Regression Residual Total 2 94502821585 47251410793 11.22 0.004 9 37895483400 4210609267 11 1.32398E+11Explanation / Answer
a) The regression model is Y = a + b*Baths + c*Sq. ft
The intercept a is -159546, the coefficient for variable Baths is 9502 and the coefficient for Sq.ft is 134.83. Finally, the regression model is
Price = -159546 + 9502 Baths + 134.83 Sq. ft
So, option B is correct.
b) The variation in home asking prices is accounted for the model is explained by R-Square and the value is 71.4%.
c) For this, I think some more information required
d) As the p-value for Baths is much more than 0.05, we accept the null hypothesis. Hence there is no significant relationship between the Price and Baths in the linear regression model. Hence Option A is correct i.e. Since the model says that the number of bathrooms is significant, this must be true.