Linear Regression Model | ||||
Y ~ X | ||||
coefficients: | ||||
Estimate | Std. Error | t value | Pr(>|t|) | (Intercept) | 19.228 | 0.651 | 29.525 | 0 | X | -0.402 | 0.049 | -8.206 | 0 |
- - - | ||||
Residual Std. Err. | 1.967 on 160 df | |||
Multiple R-sq. | 0.296 | |||
Adjusted R-sq. | 0.292 |
ANOVA Statistics | |||||
Df | Sum Sq | Mean Sq | F value | Pr(>F) | |
Depression | 1 | 260.587 | 260.587 | 67.336 | 0 |
Residuals | 160 | 619.191 | 3.87 |