Linear Regression Model | ||||
Y ~ X | ||||
coefficients: | ||||
Estimate | Std. Error | t value | Pr(>|t|) | (Intercept) | 135.163 | 4.782 | 28.264 | 0 | X | -0.667 | 0.089 | -7.505 | 0 |
- - - | ||||
Residual Std. Err. | 9.969 on 86 df | |||
Multiple R-sq. | 0.396 | |||
Adjusted R-sq. | 0.389 |
ANOVA Statistics | |||||
Df | Sum Sq | Mean Sq | F value | Pr(>F) | |
Grade | 1 | 5597.714 | 5597.714 | 56.326 | 0 |
Residuals | 86 | 8546.73 | 99.381 |