Linear Regression Model | ||||
Y ~ X | ||||
coefficients: | ||||
Estimate | Std. Error | t value | Pr(>|t|) | (Intercept) | 81.297 | 3.525 | 23.063 | 0 | X | 0.38 | 0.067 | 5.674 | 0 |
- - - | ||||
Residual Std. Err. | 10.939 on 86 df | |||
Multiple R-sq. | 0.272 | |||
Adjusted R-sq. | 0.264 |
ANOVA Statistics | |||||
Df | Sum Sq | Mean Sq | F value | Pr(>F) | |
Grade | 1 | 3852.596 | 3852.596 | 32.193 | 0 |
Residuals | 86 | 10291.847 | 119.673 |