Multiple Linear Regression - Estimated Regression Equation
Consumentenvertrouwen[t] = + 286.241461028523 -0.114324430024428Arbeidsleeftijd[t] -0.091455857160081Beroepsbevolking[t] + 0.2095290101299Werkgelegenheid[t] -1.0432590054381Werkzoekenden[t] -2.57186368277774WZMannen[t] + 6.80724314893742WZVrouwen[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)286.241461028523126.7393872.25850.0538480.026924
Arbeidsleeftijd-0.1143244300244280.04872-2.34660.0469320.023466
Beroepsbevolking-0.0914558571600810.071495-1.27920.2366830.118341
Werkgelegenheid0.20952901012990.1017472.05930.0734390.03672
Werkzoekenden-1.04325900543814.358383-0.23940.8168390.408419
WZMannen-2.571863682777743.245711-0.79240.450990.225495
WZVrouwen6.807243148937423.7469121.81680.106780.05339


Multiple Linear Regression - Regression Statistics
Multiple R0.812762858605011
R-squared0.660583464327789
Adjusted R-squared0.406021062573631
F-TEST (value)2.59497655496566
F-TEST (DF numerator)6
F-TEST (DF denominator)8
p-value0.106255076074694
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation5.85645293071471
Sum Squared Residuals274.384327437415


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1-12-7.99412386704778-4.00587613295222
2-12-9.26690074155389-2.73309925844611
32-1.382470301845013.38247030184501
42-3.717045950435785.71704595043578
5136.014743563998636.98525643600137
604.24940254548692-4.24940254548692
7-21.38652691024043-3.38652691024043
8-11-9.02781938981838-1.97218061018162
9-4-4.021868840184910.021868840184906
10-8-4.51252856861059-3.48747143138941
11-3-8.271783615099525.27178361509952
12-1-2.533625549048151.53362554904815
13-11-3.13133940602638-7.86866059397362
14-17-17.29411509707970.294115097079652
15-8-12.49705169297594.49705169297593