Multiple Linear Regression - Estimated Regression Equation |
Antwerpen[t] = + 81.87106520292 + 0.570789115514044`Vlaams-Brabant`[t] + 0.102967541561667`West-Vlaanderen`[t] + 0.311320329226794`Oost-Vlaanderen`[t] + 0.649695044606708Limburg[t] + 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) | 81.87106520292 | 222.133065 | 0.3686 | 0.723344 | 0.361672 |
`Vlaams-Brabant` | 0.570789115514044 | 0.55185 | 1.0343 | 0.335391 | 0.167696 |
`West-Vlaanderen` | 0.102967541561667 | 0.421953 | 0.244 | 0.814209 | 0.407104 |
`Oost-Vlaanderen` | 0.311320329226794 | 0.384422 | 0.8098 | 0.444686 | 0.222343 |
Limburg | 0.649695044606708 | 0.801335 | 0.8108 | 0.444187 | 0.222094 |
Multiple Linear Regression - Regression Statistics | |
Multiple R | 0.92074199655236 |
R-squared | 0.847765824215226 |
Adjusted R-squared | 0.760774866623927 |
F-TEST (value) | 9.74544766133277 |
F-TEST (DF numerator) | 4 |
F-TEST (DF denominator) | 7 |
p-value | 0.00546102932726655 |
Multiple Linear Regression - Residual Statistics | |
Residual Standard Deviation | 49.4856716881503 |
Sum Squared Residuals | 17141.8219169918 |
Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
1 | 1424 | 1460.25934622717 | -36.2593462271704 |
2 | 1445 | 1380.71453825577 | 64.285461744226 |
3 | 1398 | 1385.87482871039 | 12.1251712896113 |
4 | 1302 | 1314.95565077084 | -12.9556507708355 |
5 | 1232 | 1265.26165491074 | -33.2616549107406 |
6 | 1238 | 1207.06121122844 | 30.9387887715626 |
7 | 1171 | 1181.53749714593 | -10.5374971459317 |
8 | 1155 | 1194.12611313099 | -39.1261131309888 |
9 | 1184 | 1189.87129628408 | -5.87129628407832 |
10 | 1363 | 1283.78631055694 | 79.2136894430572 |
11 | 1339 | 1372.92583348926 | -33.9258334892601 |
12 | 1339 | 1353.62571928945 | -14.6257192894517 |