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