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 th 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 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 0.985 R Square 0.970 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
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 th 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 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 0.985 R Square 0.970 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
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![### Regression Analysis for Property Valuation in Hawaii
**TABLE 15-3**
In Hawaii, condemnation proceedings are underway 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.
**Model:**
\[ Y = \text{Sale price of property in thousands of dollars} \]
\[ X1 = \text{Size of property in thousands of square feet} \]
\[ X2 = 1 \text{ if property located near cove, 0 if not} \]
Using the data collected for the 20 properties, the following partial output obtained from Microsoft Excel is shown:
**SUMMARY OUTPUT**
**Regression Statistics:**
- Multiple R: 0.985
- R Square: 0.970
- Standard Error: 9.5
- Observations: 20
**ANOVA Table:**
| | df | SS | MS | F | Signif F |
|---------------|-----|---------|---------|-----------|----------|
| Regression | 5 | 28234 | 5664 | 62.2 | 0.0001 |
| Residual | 14 | 1279 | 91 | | |
| Total | 19 | 29063 | | | |
**Coefficients:**
| | Coeff | StdError | t Stat | P-value |
|----------------|-------|----------|--------|---------|
| Intercept | -32.1 | 35.7 | -0.90 | 0.3834 |
| Size | 12.2 | 5.9 | 2.05 | 0.0594 |
| Cove | -104.3| 53.5 | -1.95 | 0.0715 |
| Size*Cove | 17.0 | 8.5 | 1.99 | 0.104](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fe9045e4c-214a-4ed5-8350-6a40e5f22583%2Fad3dbd96-e539-4aad-8674-629aef69a748%2F15bxyik_processed.png&w=3840&q=75)
Transcribed Image Text:### Regression Analysis for Property Valuation in Hawaii
**TABLE 15-3**
In Hawaii, condemnation proceedings are underway 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.
**Model:**
\[ Y = \text{Sale price of property in thousands of dollars} \]
\[ X1 = \text{Size of property in thousands of square feet} \]
\[ X2 = 1 \text{ if property located near cove, 0 if not} \]
Using the data collected for the 20 properties, the following partial output obtained from Microsoft Excel is shown:
**SUMMARY OUTPUT**
**Regression Statistics:**
- Multiple R: 0.985
- R Square: 0.970
- Standard Error: 9.5
- Observations: 20
**ANOVA Table:**
| | df | SS | MS | F | Signif F |
|---------------|-----|---------|---------|-----------|----------|
| Regression | 5 | 28234 | 5664 | 62.2 | 0.0001 |
| Residual | 14 | 1279 | 91 | | |
| Total | 19 | 29063 | | | |
**Coefficients:**
| | Coeff | StdError | t Stat | P-value |
|----------------|-------|----------|--------|---------|
| Intercept | -32.1 | 35.7 | -0.90 | 0.3834 |
| Size | 12.2 | 5.9 | 2.05 | 0.0594 |
| Cove | -104.3| 53.5 | -1.95 | 0.0715 |
| Size*Cove | 17.0 | 8.5 | 1.99 | 0.104
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