| Multiple Linear Regression - Estimated Regression Equation |
| Vrouw[t] = + 8.82857142857143 + 0.125988700564972x[t] + 0.171428571428568M1[t] + 0.0714285714285723M2[t] -0.103571428571428M3[t] -0.55682001614205M4[t] -0.666071428571428M5[t] -0.591071428571429M6[t] + 0.408928571428572M7[t] + 0.658928571428573M8[t] + 0.508928571428572M9[t] + 0.310573042776433M10[t] -0.0359967715899913M11[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) | 8.82857142857143 | 0.293449 | 30.0855 | 0 | 0 |
| x | 0.125988700564972 | 0.436707 | 0.2885 | 0.773712 | 0.386856 |
| M1 | 0.171428571428568 | 0.401822 | 0.4266 | 0.670796 | 0.335398 |
| M2 | 0.0714285714285723 | 0.401822 | 0.1778 | 0.85936 | 0.42968 |
| M3 | -0.103571428571428 | 0.401822 | -0.2578 | 0.797258 | 0.398629 |
| M4 | -0.55682001614205 | 0.405513 | -1.3731 | 0.17355 | 0.086775 |
| M5 | -0.666071428571428 | 0.401822 | -1.6576 | 0.101309 | 0.050655 |
| M6 | -0.591071428571429 | 0.401822 | -1.471 | 0.14522 | 0.07261 |
| M7 | 0.408928571428572 | 0.401822 | 1.0177 | 0.311895 | 0.155948 |
| M8 | 0.658928571428573 | 0.401822 | 1.6399 | 0.104963 | 0.052481 |
| M9 | 0.508928571428572 | 0.401822 | 1.2666 | 0.208991 | 0.104495 |
| M10 | 0.310573042776433 | 0.419663 | 0.7401 | 0.461434 | 0.230717 |
| M11 | -0.0359967715899913 | 0.433352 | -0.0831 | 0.934007 | 0.467003 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.507267902262373 |
| R-squared | 0.257320724665668 |
| Adjusted R-squared | 0.145918833365518 |
| F-TEST (value) | 2.30984161635434 |
| F-TEST (DF numerator) | 12 |
| F-TEST (DF denominator) | 80 |
| p-value | 0.0137721805425719 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 0.776394260228902 |
| Sum Squared Residuals | 48.2230437853107 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 8.7 | 9.00000000000002 | -0.300000000000019 |
| 2 | 8.5 | 8.9 | -0.399999999999999 |
| 3 | 8.2 | 8.725 | -0.524999999999999 |
| 4 | 8.3 | 8.27175141242938 | 0.028248587570621 |
| 5 | 8 | 8.1625 | -0.1625 |
| 6 | 8.1 | 8.2375 | -0.137499999999999 |
| 7 | 8.7 | 9.2375 | -0.537500000000001 |
| 8 | 9.3 | 9.4875 | -0.187499999999997 |
| 9 | 8.9 | 9.3375 | -0.4375 |
| 10 | 8.8 | 9.13914447134786 | -0.339144471347862 |
| 11 | 8.4 | 8.79257465698144 | -0.392574656981437 |
| 12 | 8.4 | 8.82857142857143 | -0.428571428571428 |
| 13 | 7.3 | 9 | -1.70000000000000 |
| 14 | 7.2 | 8.9 | -1.7 |
| 15 | 7 | 8.725 | -1.725 |
| 16 | 7 | 8.27175141242938 | -1.27175141242938 |
| 17 | 6.9 | 8.1625 | -1.2625 |
| 18 | 6.9 | 8.2375 | -1.3375 |
| 19 | 7.1 | 9.2375 | -2.1375 |
| 20 | 7.5 | 9.4875 | -1.9875 |
| 21 | 7.4 | 9.3375 | -1.9375 |
| 22 | 8.9 | 9.13914447134786 | -0.239144471347861 |
| 23 | 8.3 | 8.9185633575464 | -0.618563357546409 |
| 24 | 8.3 | 8.82857142857143 | -0.528571428571428 |
| 25 | 9 | 9 | 2.49106291150269e-15 |
| 26 | 8.9 | 8.9 | 1.52655665885959e-16 |
| 27 | 8.8 | 8.725 | 0.0750000000000004 |
| 28 | 7.8 | 8.27175141242938 | -0.471751412429379 |
| 29 | 7.8 | 8.1625 | -0.3625 |
| 30 | 7.8 | 8.2375 | -0.4375 |
| 31 | 9.2 | 9.2375 | -0.0375000000000007 |
| 32 | 9.3 | 9.4875 | -0.1875 |
| 33 | 9.2 | 9.3375 | -0.137500000000001 |
| 34 | 8.6 | 9.13914447134786 | -0.539144471347861 |
| 35 | 8.5 | 8.79257465698144 | -0.292574656981437 |
| 36 | 8.5 | 8.82857142857143 | -0.328571428571428 |
| 37 | 9 | 9 | 2.49106291150269e-15 |
| 38 | 9 | 8.9 | 0.0999999999999998 |
| 39 | 8.8 | 8.725 | 0.0750000000000004 |
| 40 | 8 | 8.27175141242938 | -0.271751412429379 |
| 41 | 7.9 | 8.1625 | -0.262500000000000 |
| 42 | 8.1 | 8.2375 | -0.137500000000000 |
| 43 | 9.3 | 9.2375 | 0.0625000000000007 |
| 44 | 9.4 | 9.4875 | -0.0875000000000004 |
| 45 | 9.4 | 9.3375 | 0.0625000000000001 |
| 46 | 9.3 | 9.26513317191283 | 0.0348668280871676 |
| 47 | 9 | 8.79257465698144 | 0.207425343018563 |
| 48 | 9.1 | 8.82857142857143 | 0.271428571428572 |
| 49 | 9.7 | 9 | 0.700000000000002 |
| 50 | 9.7 | 8.9 | 0.799999999999999 |
| 51 | 9.6 | 8.725 | 0.875 |
| 52 | 8.3 | 8.27175141242938 | 0.0282485875706221 |
| 53 | 8.2 | 8.1625 | 0.0374999999999993 |
| 54 | 8.4 | 8.2375 | 0.162500000000000 |
| 55 | 10.6 | 9.2375 | 1.3625 |
| 56 | 10.9 | 9.4875 | 1.4125 |
| 57 | 10.9 | 9.3375 | 1.5625 |
| 58 | 9.6 | 9.13914447134786 | 0.460855528652139 |
| 59 | 9.3 | 8.79257465698144 | 0.507425343018564 |
| 60 | 9.3 | 8.82857142857143 | 0.471428571428573 |
| 61 | 9.6 | 9 | 0.600000000000002 |
| 62 | 9.5 | 8.9 | 0.6 |
| 63 | 9.5 | 8.725 | 0.775 |
| 64 | 9 | 8.27175141242938 | 0.728248587570621 |
| 65 | 8.9 | 8.1625 | 0.7375 |
| 66 | 9 | 8.2375 | 0.7625 |
| 67 | 10.1 | 9.2375 | 0.8625 |
| 68 | 10.2 | 9.4875 | 0.712499999999999 |
| 69 | 10.2 | 9.3375 | 0.8625 |
| 70 | 9.5 | 9.13914447134786 | 0.360855528652139 |
| 71 | 9.3 | 8.79257465698144 | 0.507425343018564 |
| 72 | 9.3 | 8.82857142857143 | 0.471428571428573 |
| 73 | 9.4 | 9 | 0.400000000000003 |
| 74 | 9.3 | 8.9 | 0.400000000000000 |
| 75 | 9.1 | 8.725 | 0.374999999999999 |
| 76 | 9 | 8.27175141242938 | 0.728248587570621 |
| 77 | 8.9 | 8.1625 | 0.7375 |
| 78 | 9 | 8.2375 | 0.7625 |
| 79 | 9.8 | 9.2375 | 0.562500000000001 |
| 80 | 10 | 9.4875 | 0.512500000000000 |
| 81 | 9.8 | 9.3375 | 0.4625 |
| 82 | 9.4 | 9.13914447134786 | 0.260855528652139 |
| 83 | 9 | 8.9185633575464 | 0.0814366424535907 |
| 84 | 8.9 | 8.82857142857143 | 0.0714285714285721 |
| 85 | 9.3 | 9 | 0.300000000000003 |
| 86 | 9.1 | 8.9 | 0.199999999999999 |
| 87 | 8.8 | 8.725 | 0.0750000000000004 |
| 88 | 8.9 | 8.39774011299435 | 0.50225988700565 |
| 89 | 8.7 | 8.1625 | 0.537499999999999 |
| 90 | 8.6 | 8.2375 | 0.362499999999999 |
| 91 | 9.1 | 9.2375 | -0.137500000000000 |
| 92 | 9.3 | 9.4875 | -0.1875 |
| 93 | 8.9 | 9.3375 | -0.4375 |
