| Multiple Linear Regression - Estimated Regression Equation |
| CVI[t] = -0.309576849250441 + 0.852934418541301Econ.Sit.[t] -0.441067887961009Werkloos[t] -0.766757187222168Fin.Sit.[t] + 3.44462990943047Spaarverm.[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) | -0.309576849250441 | 0.740794 | -0.4179 | 0.687013 | 0.343506 |
| Econ.Sit. | 0.852934418541301 | 0.137322 | 6.2112 | 0.000256 | 0.000128 |
| Werkloos | -0.441067887961009 | 0.256834 | -1.7173 | 0.124248 | 0.062124 |
| Fin.Sit. | -0.766757187222168 | 0.183561 | -4.1771 | 0.003092 | 0.001546 |
| Spaarverm. | 3.44462990943047 | 0.307384 | 11.2063 | 4e-06 | 2e-06 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.994514375778772 |
| R-squared | 0.98905884363064 |
| Adjusted R-squared | 0.983588265445959 |
| F-TEST (value) | 180.796034759251 |
| F-TEST (DF numerator) | 4 |
| F-TEST (DF denominator) | 8 |
| p-value | 7.10239501655607e-08 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 1.07369415989597 |
| Sum Squared Residuals | 9.22255319195777 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 8 | 8.70762936669665 | -0.707629366696651 |
| 2 | 3 | 1.84757090521642 | 1.15242909478358 |
| 3 | -3 | -2.44999342275535 | -0.550006577244646 |
| 4 | 4 | 4.0347816212944 | -0.0347816212944039 |
| 5 | -5 | -4.56261107171068 | -0.43738892828932 |
| 6 | -1 | -0.170114621877445 | -0.829885378122555 |
| 7 | 5 | 5.42514289048119 | -0.425142890481193 |
| 8 | 0 | -2.26745722875174 | 2.26745722875174 |
| 9 | -6 | -5.61572817549774 | -0.384271824502262 |
| 10 | -13 | -13.3032642820729 | 0.303264282072895 |
| 11 | -15 | -15.1726496871437 | 0.172649687143737 |
| 12 | -8 | -8.22641399434437 | 0.226413994344372 |
| 13 | -20 | -19.2468922995347 | -0.753107700465293 |
