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?
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?
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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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](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fbfd92378-ff54-49ec-a5cd-cf2154b29b1a%2Fae5d1f20-3ab3-479c-8c10-9044181c3f46%2Fioyoisb_processed.jpeg&w=3840&q=75)
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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