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 0.985 0.970 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 Coeff StdError 1 Stat P-value Intercept -32.1 35.7 -0.90 0.3834 Size 12.2 5.9 2.05 0.1394 53.5 -1.95 0.0715 Cove - 104.3 Size*Cove 17.0 0.0661 -0.3 SizeSq SizeSq*Cove -0.3 12.2, yes O2.05, no O 12.2, no 8.5 1.99 - 1.28 - 1.13 O2.05, yes 0.2 What is the slope for the independent variable Size and is it significant at an alpha of .05? 0.3 0.2204 0.2749
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 0.985 0.970 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 Coeff StdError 1 Stat P-value Intercept -32.1 35.7 -0.90 0.3834 Size 12.2 5.9 2.05 0.1394 53.5 -1.95 0.0715 Cove - 104.3 Size*Cove 17.0 0.0661 -0.3 SizeSq SizeSq*Cove -0.3 12.2, yes O2.05, no O 12.2, no 8.5 1.99 - 1.28 - 1.13 O2.05, yes 0.2 What is the slope for the independent variable Size and is it significant at an alpha of .05? 0.3 0.2204 0.2749
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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![## Understanding Regression Analysis in Real Estate
### Background
In Hawaii, condemnation proceedings are being introduced to enable private citizens to own the property that their homes are built on. Previously, only estates were allowed to own land, while homeowners leased the land from the estate. To comply with this new regulation, a large Hawaiian estate wants to use regression analysis to estimate the fair market value of the land. The following model is based on data collected for 20 properties, with 10 of these properties located near a cove.
The regression model is specified as follows:
\[ Y = \text{Sale price of property in thousands of dollars} \]
\[ X1 = \text{Size of property in thousands of square feet} \]
\[ X2 = 1 \text{ if property is located near a cove, } 0 \text{ if not} \]
### Regression Analysis Results
Using data collected from the 20 properties, the partial output obtained from Microsoft Excel is shown below:
#### 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 | 28324 | 5664 | 62.2 | 0.0001 |
| Residual | 14 | 1279 | 91 | | |
| Total | 19 | 29063 | | | |
#### Coefficients Table
| | Coeff | StdError | t Stat | P-value |
|--------------|-------|----------|--------|---------|
| **Intercept** | -32.1 | 35.7 | -0.90 | 0.3834 |
| **Size** | 12.2 | 5.9 | 2.05 | 0.1394 |
| **Cove** | -104.3| 53.5 | -1.95 | 0.0715 |
| **Size*Cove** | 17.0 | 8.5 | 1.99 | 0.0661](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fe9045e4c-214a-4ed5-8350-6a40e5f22583%2F06e212e2-417d-4c52-92b5-966261245f23%2Fgpmeko_processed.png&w=3840&q=75)
Transcribed Image Text:## Understanding Regression Analysis in Real Estate
### Background
In Hawaii, condemnation proceedings are being introduced to enable private citizens to own the property that their homes are built on. Previously, only estates were allowed to own land, while homeowners leased the land from the estate. To comply with this new regulation, a large Hawaiian estate wants to use regression analysis to estimate the fair market value of the land. The following model is based on data collected for 20 properties, with 10 of these properties located near a cove.
The regression model is specified as follows:
\[ Y = \text{Sale price of property in thousands of dollars} \]
\[ X1 = \text{Size of property in thousands of square feet} \]
\[ X2 = 1 \text{ if property is located near a cove, } 0 \text{ if not} \]
### Regression Analysis Results
Using data collected from the 20 properties, the partial output obtained from Microsoft Excel is shown below:
#### 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 | 28324 | 5664 | 62.2 | 0.0001 |
| Residual | 14 | 1279 | 91 | | |
| Total | 19 | 29063 | | | |
#### Coefficients Table
| | Coeff | StdError | t Stat | P-value |
|--------------|-------|----------|--------|---------|
| **Intercept** | -32.1 | 35.7 | -0.90 | 0.3834 |
| **Size** | 12.2 | 5.9 | 2.05 | 0.1394 |
| **Cove** | -104.3| 53.5 | -1.95 | 0.0715 |
| **Size*Cove** | 17.0 | 8.5 | 1.99 | 0.0661
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