| Multiple Linear Regression - Estimated Regression Equation |
| Brussel[t] = + 5603.29951051044 -0.0828922353186576Vlaanderen[t] + 0.334221860800385Wallonie[t] + 460.19148005847t + 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) | 5603.29951051044 | 4101.090973 | 1.3663 | 0.220835 | 0.110418 |
| Vlaanderen | -0.0828922353186576 | 0.05483 | -1.5118 | 0.181341 | 0.09067 |
| Wallonie | 0.334221860800385 | 0.144869 | 2.3071 | 0.060511 | 0.030256 |
| t | 460.19148005847 | 31.43784 | 14.6381 | 6e-06 | 3e-06 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.992512303481 |
| R-squared | 0.98508067256116 |
| Adjusted R-squared | 0.97762100884174 |
| F-TEST (value) | 132.054300249039 |
| F-TEST (DF numerator) | 3 |
| F-TEST (DF denominator) | 6 |
| p-value | 7.22356976368133e-06 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 203.974359588487 |
| Sum Squared Residuals | 249633.236217201 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 13509 | 13522.8080956065 | -13.8080956064645 |
| 2 | 14142 | 14079.5538100235 | 62.4461899765145 |
| 3 | 14755 | 14855.2719960332 | -100.271996033169 |
| 4 | 15495 | 15322.36927109 | 172.630728910009 |
| 5 | 15096 | 15438.0296755948 | -342.029675594849 |
| 6 | 15930 | 15823.1804121448 | 106.819587855223 |
| 7 | 16436 | 16241.1354805219 | 194.864519478088 |
| 8 | 16705 | 16773.0780301397 | -68.0780301397485 |
| 9 | 17415 | 17289.7445321832 | 125.25546781678 |
| 10 | 17613 | 17750.8286966624 | -137.828696662384 |
