W REGRESSION 1 Dependent Variab Value Independent Varia Size Regression Statistics R Square Adj.RSqr Std.Err.Reg. # Cases # Missing 5%,285) 0.175 0.149 0.695 287 0 1.968 The government plans to build a new subway and rail terminal, and is offering compensation to the land property owner where the terminal is to be developed. The government claims that the offered compensation amount is based on market prices. The property owner believes that the new development would add substantial value to the properties around it, and that she should be compensated for that as well. She obtained results of two simple regressions; both regression outputs are in the worksheet Property Valuation of the Excel Workbook Outputs. Regression 1 has the current market value of properties (variable name Value, in hundreds of thousands of dollars, i.e., measured in units of $100,000) as the dependent variable, and the size of the property (variable name Size, measured in acres; 1 acre (4,047 square meters) as the independent variable. Regression 2 uses the same independent variable Size, but it uses percentage increase in the property value based on the size of the property after similar government developments occurred (variable name IncrValue, in percentage points, i.e., a decrease in value of 12% would correspond to IncrValue = -12). Summary Table Variable Coeff Std.Emr. Intercept 1.784 0.382 Size 2.103 0.112 t-Stat. P-value 4.6700.000 18.777 0.000 Forecasted : Value Size Forecast Fcst#1 1 3.887 Fcst#2 2 5.990 Fcst#3 3 8.093 (Property valuation, 2 points) 1) Using Regression 2, what is a 99.7% confidence interval for the change in IncrValue when Size increases by three acres? Select the confidence interval closest to the one you computed from the choices below. StErrFst 1.033 1.000 0.953 0 (-3.004,-1.198] 1 22 (-7.206,-5.400) REGRESSION 2 24 [-9.012, -3.594) 25 Dependent Variab IncrValue Independent Varis Size 26 [1.668, 14.928) 27 28 [-0.768, 17.364] 29 Regression Statistics R Square Adj.RSqr Std.Err.Reg. # Cases # Missing 5%,490) 0.273 0.252 2.210 492 0 1.965 30 (-15.369, 2.763] 31 32 33 Summary Table Variable Coeff Intercept 14.601 Size -2.101 Std.Emr. 34 2)(Property valuation, 0 points) If the government decides not to develop the terminal in the area, what is the probability that the value of a three acre property value will exceed one million dollars? 35 t-Stat. P-value 35.439 0.000 -6.980 0.000 0.412 0.301 36 (Property valuation, 4 points) What is the point estimate of the value of a three acre property after the government develops the terminal? (Hint: use both Regression 1 and Regression 2.) 38 39 Forecasted : IncrValue Size Forecast Fcst#1 3 8.298 Fcst#2 2 10.399 Fcst#3 1 12.500 20 StErrest 3.022 2.873 2.788 41 42 W REGRESSION 1 Dependent Variab Value Independent Varia Size Regression Statistics R Square Adj.RSqr Std.Err.Reg. # Cases # Missing 5%,285) 0.175 0.149 0.695 287 0 1.968 The government plans to build a new subway and rail terminal, and is offering compensation to the land property owner where the terminal is to be developed. The government claims that the offered compensation amount is based on market prices. The property owner believes that the new development would add substantial value to the properties around it, and that she should be compensated for that as well. She obtained results of two simple regressions; both regression outputs are in the worksheet Property Valuation of the Excel Workbook Outputs. Regression 1 has the current market value of properties (variable name Value, in hundreds of thousands of dollars, i.e., measured in units of $100,000) as the dependent variable, and the size of the property (variable name Size, measured in acres; 1 acre (4,047 square meters) as the independent variable. Regression 2 uses the same independent variable Size, but it uses percentage increase in the property value based on the size of the property after similar government developments occurred (variable name IncrValue, in percentage points, i.e., a decrease in value of 12% would correspond to IncrValue = -12). Summary Table Variable Coeff Std.Emr. Intercept 1.784 0.382 Size 2.103 0.112 t-Stat. P-value 4.6700.000 18.777 0.000 Forecasted : Value Size Forecast Fcst#1 1 3.887 Fcst#2 2 5.990 Fcst#3 3 8.093 (Property valuation, 2 points) 1) Using Regression 2, what is a 99.7% confidence interval for the change in IncrValue when Size increases by three acres? Select the confidence interval closest to the one you computed from the choices below. StErrFst 1.033 1.000 0.953 0 (-3.004,-1.198] 1 22 (-7.206,-5.400) REGRESSION 2 24 [-9.012, -3.594) 25 Dependent Variab IncrValue Independent Varis Size 26 [1.668, 14.928) 27 28 [-0.768, 17.364] 29 Regression Statistics R Square Adj.RSqr Std.Err.Reg. # Cases # Missing 5%,490) 0.273 0.252 2.210 492 0 1.965 30 (-15.369, 2.763] 31 32 33 Summary Table Variable Coeff Intercept 14.601 Size -2.101 Std.Emr. 34 2)(Property valuation, 0 points) If the government decides not to develop the terminal in the area, what is the probability that the value of a three acre property value will exceed one million dollars? 35 t-Stat. P-value 35.439 0.000 -6.980 0.000 0.412 0.301 36 (Property valuation, 4 points) What is the point estimate of the value of a three acre property after the government develops the terminal? (Hint: use both Regression 1 and Regression 2.) 38 39 Forecasted : IncrValue Size Forecast Fcst#1 3 8.298 Fcst#2 2 10.399 Fcst#3 1 12.500 20 StErrest 3.022 2.873 2.788 41 42