| Multiple Linear Regression - Estimated Regression Equation |
| Jaar[t] = + 1997 + 2.35126663653879e-17Brussel[t] -4.90901356254143e-17Vlaanderen[t] + 8.50318798793082e-17Wallonie[t] + 1.00000000000003t + 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) | 1997 | 0 | 1275809351795235 | 0 | 0 |
| Brussel | 2.35126663653879e-17 | 0 | 0.1914 | 0.854542 | 0.427271 |
| Vlaanderen | -4.90901356254143e-17 | 0 | -2.1857 | 0.071496 | 0.035748 |
| Wallonie | 8.50318798793082e-17 | 0 | 2.2018 | 0.069933 | 0.034966 |
| t | 1.00000000000003 | 0 | 16842314272903.4 | 0 | 0 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 1 |
| R-squared | 1 |
| Adjusted R-squared | 1 |
| F-TEST (value) | 4.8597805716885e+27 |
| F-TEST (DF numerator) | 4 |
| F-TEST (DF denominator) | 6 |
| p-value | 0 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 7.52242760225754e-14 |
| Sum Squared Residuals | 3.39521502187236e-26 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 1998 | 1998 | -1.03686890570325e-13 |
| 2 | 1999 | 1999 | 1.35816347662537e-13 |
| 3 | 2000 | 2000 | 3.04791081881196e-14 |
| 4 | 2001 | 2001 | -5.47007809094785e-14 |
| 5 | 2002 | 2002 | -2.24884362093282e-15 |
| 6 | 2003 | 2003 | -2.1784121544186e-14 |
| 7 | 2004 | 2004 | 1.63822927801474e-14 |
| 8 | 2005 | 2005 | 7.41551553501074e-15 |
| 9 | 2006 | 2006 | -3.90211963247621e-15 |
| 10 | 2007 | 2007 | -3.9634314123264e-15 |
| 11 | 2008 | 2008 | 1.92923523910857e-16 |
