Multiple Linear Regression - Estimated Regression Equation
Sociale_uitkeringen_in_$[t] = -38599575982.5991 -470382.573571658`#_werklozen_Vl.`[t] + 2401209.16313856`#_werklozen_Br.`[t] + 19099.8681407211`#_werklozen_Wa.`[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)-38599575982.599154829386160.9031-0.7040.5078240.253912
`#_werklozen_Vl.`-470382.573571658181418.290428-2.59280.0410570.020528
`#_werklozen_Br.`2401209.16313856351853.1828036.82450.0004860.000243
`#_werklozen_Wa.`19099.8681407211301618.0843620.06330.9515650.475782


Multiple Linear Regression - Regression Statistics
Multiple R0.955316369344932
R-squared0.912629365538382
Adjusted R-squared0.868944048307573
F-TEST (value)20.8909863402514
F-TEST (DF numerator)3
F-TEST (DF denominator)6
p-value0.00141029517107305
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation8554816353.43077
Sum Squared Residuals4.39109297045559e+20


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
15637328500063918576818.6991-7545291818.69912
27137666650070675604963.2572701061536.742793
38246376960077127140257.53245336629342.46764
48565854080081691704241.48643966836558.51363
58919232880097835368954.2664-8643040154.26638
6102035085000106404186824.47-4369101824.46951
7117207944700107800204964.8949407739735.10641
8119301814800109447775167.8039854039632.19679
9116206980300123735521695.624-7528541395.62395
10128906391600130086723211.968-1180331611.96832