Linear Regression Model | ||||
Y ~ X | ||||
coefficients: | ||||
Estimate | Std. Error | t value | Pr(>|t|) | (Intercept) | 64.466 | 0.656 | 98.24 | 0 | X | 0.718 | 0.012 | 57.658 | 0 |
- - - | ||||
Residual Std. Err. | 2.037 on 86 df | |||
Multiple R-sq. | 0.975 | |||
Adjusted R-sq. | 0.974 |
ANOVA Statistics | |||||
Df | Sum Sq | Mean Sq | F value | Pr(>F) | |
Grade | 1 | 13787.769 | 13787.769 | 3324.461 | 0 |
Residuals | 86 | 356.674 | 4.147 |