| Multiple Linear Regression - Estimated Regression Equation |
| Y [t] = + 1717.75147928994 -396.055827116028 X + e[t] |
| Multiple Linear Regression - Ordinary Least Squares | |||||
| Variable | Parameter | S.D. | T-STAT H0: parameter = 0 | 2-tail p-value | 1-tail p-value |
| (Intercept) | 1717.75147928994 | 20.0003335628486 | 85.8861415431958 | 5.68074202608117e-154 | 2.84037101304058e-154 |
| X | -396.055827116028 | 57.7861732311232 | -6.85381649225935 | 9.76295455223808e-11 | 4.88147727611904e-11 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.445226892939612 |
| R-squared | 0.198226986196661 |
| Adjusted R-squared | 0.194007128229275 |
| F-TEST (value) | 46.9748005095663 |
| F-TEST (DF numerator) | 1 |
| F-TEST (DF denominator) | 190 |
| p-value | 9.762957109416e-11 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 260.004336317031 |
| Sum Squared Residuals | 12844428.4316954 |
