Linear Regression Model | ||||
Y ~ X | ||||
coefficients: | ||||
Estimate | Std. Error | t value | Pr(>|t|) | (Intercept) | 84.897 | 7.104 | 11.95 | 0 | X | 0.358 | 0.168 | 2.128 | 0.055 |
- - - | ||||
Residual Std. Err. | 10.206 on 12 df | |||
Multiple R-sq. | 0.274 | |||
Adjusted R-sq. | 0.214 |
ANOVA Statistics | |||||
Df | Sum Sq | Mean Sq | F value | Pr(>F) | |
Grade | 1 | 471.788 | 471.788 | 4.529 | 0.055 |
Residuals | 12 | 1249.926 | 104.161 |