Linear Regression Model | ||||
Y ~ X | ||||
coefficients: | ||||
Estimate | Std. Error | t value | Pr(>|t|) | (Intercept) | 22.698 | 2.394 | 9.482 | 0 | X | 0.35 | 0.07 | 5.009 | 0 |
- - - | ||||
Residual Std. Err. | 3.148 on 160 df | |||
Multiple R-sq. | 0.136 | |||
Adjusted R-sq. | 0.13 |
ANOVA Statistics | |||||
Df | Sum Sq | Mean Sq | F value | Pr(>F) | |
separate | 1 | 248.581 | 248.581 | 25.086 | 0 |
Residuals | 160 | 1585.449 | 9.909 |