Question

Suppose that a researcher collects data on houses that have sold in a particular neighborhood over the past year and obtains the regression results in the table shown below. Dependent variable: In(Price) Regressor Size In(Size) In(Size)2 Bedrooms Pool View Pool x View Condition Intercept 0.00052 (0.000038) 0.774 (0.056) (0.089) (2.05) (0.055) 0.69 0.69 0.65 0.0081 (0.16) 0.0037 (0.038) 0.084 (0.035) 0.035) 0.039) 0.037) 0.036) 0.027 0.027 0.027 (0.032)0.032 (0.031) (0.033 0.028) 0.091 0.077 0.085 0.089 0.046 0027 0.0032 (0.14) 0.16 0.17 (0.049) 0.037) 0.036 0.039) 0.038) 6.63 0.19 0.18 0.21 6.65 6.66 (0.073) 0.39) 0.56) (7.54) 0.42) 12.26 7.02 Summary Statistics SER 0.103 0.73 0.098 0.75 0.102 0.107 0.72 0.101 R2 Variable definitions: Price sale price (); Sizehouse size (in square feet), Bedroomsnumber of bedrooms; Pool- binary variable (1 if house has a swimming pool, 0 otherwise): View binary variable (1 if house has a nice view, 0 otherwise): Conditionbinary variable (1 if real estate agent reports house is in excellent condition, 0 otherwise). 0.74 0.76

Answer 1

As given in the table: The mean size ř= 0.00052 The margin of error E = 0.000038 At 95% confidence level, the critical value of z-test =+1.96 (By using the standard normal table for a two-tailed test.) The 95% confidence interval for the percentage change in price is: CI = F-E = 0.00052 +(1.96x0.000038) = 0.000520.00007448 =(0.00044552,0.00059448) =(0.044552%,0.059448%) (rounded to the two decimal places)