Using the regression table I created, how should I perform a T-test for the predictors and assuming the Normality, Homoscedasticity, Independence of observations are satisfied?

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Using the regression table I created, how should I perform a T-test for the predictors and assuming the Normality, Homoscedasticity, Independence of observations are satisfied?

## Regression Analysis

### Regression Statistics
- **Multiple R**: 0.9915
- **R Square**: 0.9830
- **Adjusted R Square**: 0.9824
- **Standard Error**: 108.8113
- **Observations**: 61

### ANOVA (Analysis of Variance)
|          | **df** | **SS**           | **MS**            | **F**      | **Significance F** |
|----------|--------|------------------|-------------------|------------|--------------------|
| Regression | 2      | 39731441.7245   | 19865720.8622     | 1677.8619  | 0.0000             |
| Residual   | 58     | 686714.3411     | 11839.9024        |            |                    |
| Total      | 60     | 40418156.0656   |                   |            |                    |

### Coefficients Analysis
|                | **Coefficients** | **Standard Error** | **t Stat** | **P-value** | **Lower 95%** | **Upper 95%** |
|----------------|------------------|--------------------|------------|-------------|---------------|---------------|
| Intercept      | -90.2166         | 113.1013           | -0.7977    | 0.4283      | -316.6134     | 136.1802      |
| Asking Price   | 9.2169           | 0.1716             | 53.7184    | 0.0000      | 8.8735        | 9.5604        |
| Age            | 2.5069           | 0.8994             | 2.7873     | 0.0072      | 0.7065        | 4.3073        |

### Calculations
- **b2, b1, b0 Intercepts**: 2.5069, 9.2169, -90.2166
- **b2, b1, b0 Standard Error**: 0.8994, 0.1716, 113.1013
- **R Square, Standard Error**: 0.9830, 108.8113
Transcribed Image Text:## Regression Analysis ### Regression Statistics - **Multiple R**: 0.9915 - **R Square**: 0.9830 - **Adjusted R Square**: 0.9824 - **Standard Error**: 108.8113 - **Observations**: 61 ### ANOVA (Analysis of Variance) | | **df** | **SS** | **MS** | **F** | **Significance F** | |----------|--------|------------------|-------------------|------------|--------------------| | Regression | 2 | 39731441.7245 | 19865720.8622 | 1677.8619 | 0.0000 | | Residual | 58 | 686714.3411 | 11839.9024 | | | | Total | 60 | 40418156.0656 | | | | ### Coefficients Analysis | | **Coefficients** | **Standard Error** | **t Stat** | **P-value** | **Lower 95%** | **Upper 95%** | |----------------|------------------|--------------------|------------|-------------|---------------|---------------| | Intercept | -90.2166 | 113.1013 | -0.7977 | 0.4283 | -316.6134 | 136.1802 | | Asking Price | 9.2169 | 0.1716 | 53.7184 | 0.0000 | 8.8735 | 9.5604 | | Age | 2.5069 | 0.8994 | 2.7873 | 0.0072 | 0.7065 | 4.3073 | ### Calculations - **b2, b1, b0 Intercepts**: 2.5069, 9.2169, -90.2166 - **b2, b1, b0 Standard Error**: 0.8994, 0.1716, 113.1013 - **R Square, Standard Error**: 0.9830, 108.8113
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