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TABLE 15-3 In Hawaii, condemnation proceedings are under way to enable private citizens to own the property that their homes are built on. Until recently, only estates were permitted to own land, and homeowners leased the land from the estate. In order to comply with the new law, a large Hawaiian estate wants to use regression analysis to estimate the fair market value of the land. The following model was fit to data collected for n = 20 properties, 10 of which are located near a cove. where Y = Sale price of property in thousands of dollars XI = Size of property in thousands of square feet X2= 1 if property located near cove, 0 if not Using the data collected for the 20 properties, the following partial output obtained from Microsoft Excel is shown: SUMMARY OUTPUT Regression Statistics Multiple R R Square Standard Error Observations 20 ANOVA F Signif F df SS MS Regression 5 28324 5664 62.2 0.0001 Residual 14 1279 91 Total 19 29063 Coeff StdErrort Stat P-value Intercept -32.1 35.7 -0.90 0.3834 Size 12.2 Cove - 104.3 Size*Cove 17.0 SizeSq -0.3 5.9 2.05 0.0594 53.5 -1.95 0.0715 8.5 1.99 0.0661 0.2 - 1.28 0.2204 SizeSq Cove -0.3 0.3 -1.13 0.2749 What is the correlation between Y and the predicted-Y? 5 0.987 0..974 9.5 0.92 0.8464 O.987 9.5

TABLE 15-3 In Hawaii, condemnation proceedings are under way to enable private citizens to own the property that their homes are built on. Until recently, only estates were permitted to own land, and homeowners leased the land from the estate. In order to comply with the new law, a large Hawaiian estate wants to use regression analysis to estimate the fair market value of the land. The following model was fit to data collected for n = 20 properties, 10 of which are located near a cove. where Y = Sale price of property in thousands of dollars XI = Size of property in thousands of square feet X2= 1 if property located near cove, 0 if not Using the data collected for the 20 properties, the following partial output obtained from Microsoft Excel is shown: SUMMARY OUTPUT Regression Statistics Multiple R R Square Standard Error Observations 20 ANOVA F Signif F df SS MS Regression 5 28324 5664 62.2 0.0001 Residual 14 1279 91 Total 19 29063 Coeff StdErrort Stat P-value Intercept -32.1 35.7 -0.90 0.3834 Size 12.2 Cove - 104.3 Size*Cove 17.0 SizeSq -0.3 5.9 2.05 0.0594 53.5 -1.95 0.0715 8.5 1.99 0.0661 0.2 - 1.28 0.2204 SizeSq Cove -0.3 0.3 -1.13 0.2749 What is the correlation between Y and the predicted-Y? 5 0.987 0..974 9.5 0.92 0.8464 O.987 9.5

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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TABLE 15-3 In Hawaii, condemnation proceedings are under way to enable private citizens to own the property that their homes are built on. Until recently, only estates were permitted to own land, and homeowners leased the land from the estate. In order to comply with the new law, a large Hawaiian estate wants to use regression analysis to estimate the fair market value of the land. The following model was fit to data collected for n = 20 properties, 10 of which are located near a cove. where Y = Sale price of property in thousands of dollars X1 = Size of property in thousands of square feet X2 = 1 if property located near cove, 0 if not Using the data collected for the 20 properties, the following partial output obtained from Microsoft Excel is shown: SUMMARY OUTPUT Regression Statistics Multiple R 0.987 R Square 0..974 Standard Error 9.5 Observations 20 ANOVA df SS MS F Signif F Regression 5 28324 5664 62.2 0.0001 Residual 14 1279 91 Total 19 29063 Intercept Size Cove Size*Cove SizeSq SizeSq*Cove -0.3 17.0 - 0.3 .92 Coeff - 32.1 12.2 - 104.3 .8464 O .987 What is the correlation between Y and the predicted-Y? StdError t Stat 35.7 - 0.90 5.9 2.05 53.5 - 1.95 8.5 1.99 0.2 - 1.28 0.3 - 1.13 9.5 P-value 0.3834 0.0594 0.0715 0.0661 0.2204 0.2749
Transcribed Image Text:TABLE 15-3 In Hawaii, condemnation proceedings are under way to enable private citizens to own the property that their homes are built on. Until recently, only estates were permitted to own land, and homeowners leased the land from the estate. In order to comply with the new law, a large Hawaiian estate wants to use regression analysis to estimate the fair market value of the land. The following model was fit to data collected for n = 20 properties, 10 of which are located near a cove. where Y = Sale price of property in thousands of dollars X1 = Size of property in thousands of square feet X2 = 1 if property located near cove, 0 if not Using the data collected for the 20 properties, the following partial output obtained from Microsoft Excel is shown: SUMMARY OUTPUT Regression Statistics Multiple R 0.987 R Square 0..974 Standard Error 9.5 Observations 20 ANOVA df SS MS F Signif F Regression 5 28324 5664 62.2 0.0001 Residual 14 1279 91 Total 19 29063 Intercept Size Cove Size*Cove SizeSq SizeSq*Cove -0.3 17.0 - 0.3 .92 Coeff - 32.1 12.2 - 104.3 .8464 O .987 What is the correlation between Y and the predicted-Y? StdError t Stat 35.7 - 0.90 5.9 2.05 53.5 - 1.95 8.5 1.99 0.2 - 1.28 0.3 - 1.13 9.5 P-value 0.3834 0.0594 0.0715 0.0661 0.2204 0.2749
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