Multiple Linear Regression - Estimated Regression Equation

Sociale_uitkeringen_(in_%_van_BBP)[t] = + 24.7864921233454 + 2.11578501819898e-05`#_werklozen_Vl`[t] + 0.000139357402800176`#_werklozen_Br`[t] -7.45316458655826e-05`#_werklozen_Wa`[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)	24.7864921233454	3.419049	7.2495	0.00035	0.000175
`#_werklozen_Vl`	2.11578501819898e-05	1.1e-05	1.8702	0.110641	0.055321
`#_werklozen_Br`	0.000139357402800176	2.2e-05	6.3515	0.000714	0.000357
`#_werklozen_Wa`	-7.45316458655826e-05	1.9e-05	-3.9627	0.007429	0.003714

Multiple Linear Regression - Regression Statistics
Multiple R	0.935919717283761
R-squared	0.875945717200515
Adjusted R-squared	0.813918575800772
F-TEST (value)	14.1219746297086
F-TEST (DF numerator)	3
F-TEST (DF denominator)	6
p-value	0.00397685325272923
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.533460893357722
Sum Squared Residuals	1.70748314845211

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	22.3	22.6337032878497	-0.333703287849747
2	22.9	22.5848864527849	0.315113547215093
3	22.8	22.7201709211448	0.0798290788552228
4	22.7	22.9776031351007	-0.277603135100659
5	22.3	22.4526908734723	-0.152690873472303
6	22.2	22.3987244356172	-0.198724435617173
7	23.1	23.0212475496902	0.0787524503097615
8	25.2	24.1187803768229	1.08121962317709
9	24.9	25.1949667650425	-0.294966765042513
10	25.2	25.4972262024748	-0.297226202474773