| Multiple Linear Regression - Estimated Regression Equation |
| figures[t] = + 7.1954030122476 + 0.287859980139027dienstencheques[t] -0.0968676605034594M1[t] -0.000589130057849045M2[t] + 0.120934115950253M3[t] + 0.109124028625022M4[t] + 0.0973139412997902M5[t] + 0.418837187307892M6[t] + 0.390360433315994M7[t] + 0.361883679324096M8[t] + 0.268763595309027M9[t] + 0.256953507983796M10[t] + 0.228476753991898M11[t] + 0.0118100873252313t + 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) | 7.1954030122476 | 0.236411 | 30.436 | 0 | 0 |
| dienstencheques | 0.287859980139027 | 0.230913 | 1.2466 | 0.217464 | 0.108732 |
| M1 | -0.0968676605034594 | 0.274892 | -0.3524 | 0.725806 | 0.362903 |
| M2 | -0.000589130057849045 | 0.286364 | -0.0021 | 0.998365 | 0.499183 |
| M3 | 0.120934115950253 | 0.286013 | 0.4228 | 0.673959 | 0.336979 |
| M4 | 0.109124028625022 | 0.285766 | 0.3819 | 0.703933 | 0.351967 |
| M5 | 0.0973139412997902 | 0.285621 | 0.3407 | 0.734532 | 0.367266 |
| M6 | 0.418837187307892 | 0.28558 | 1.4666 | 0.147789 | 0.073895 |
| M7 | 0.390360433315994 | 0.285641 | 1.3666 | 0.176933 | 0.088466 |
| M8 | 0.361883679324096 | 0.285806 | 1.2662 | 0.210423 | 0.105212 |
| M9 | 0.268763595309027 | 0.285368 | 0.9418 | 0.350129 | 0.175065 |
| M10 | 0.256953507983796 | 0.28511 | 0.9012 | 0.371124 | 0.185562 |
| M11 | 0.228476753991898 | 0.284955 | 0.8018 | 0.425887 | 0.212943 |
| t | 0.0118100873252313 | 0.005428 | 2.1756 | 0.033602 | 0.016801 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.682191331962567 |
| R-squared | 0.465385013404862 |
| Adjusted R-squared | 0.347588490934747 |
| F-TEST (value) | 3.95075341483811 |
| F-TEST (DF numerator) | 13 |
| F-TEST (DF denominator) | 59 |
| p-value | 0.000131017632757580 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 0.493467187323147 |
| Sum Squared Residuals | 14.3670820329125 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 6.5 | 7.11034543906937 | -0.610345439069368 |
| 2 | 6.4 | 7.21843405684021 | -0.818434056840214 |
| 3 | 6.2 | 7.35176739017355 | -1.15176739017355 |
| 4 | 6.2 | 7.35176739017355 | -1.15176739017355 |
| 5 | 6.3 | 7.35176739017355 | -1.05176739017355 |
| 6 | 7.5 | 7.68510072350688 | -0.185100723506881 |
| 7 | 7.4 | 7.66843405684021 | -0.268434056840214 |
| 8 | 7.4 | 7.65176739017355 | -0.251767390173547 |
| 9 | 7.4 | 7.57045739348371 | -0.170457393483709 |
| 10 | 7.4 | 7.57045739348371 | -0.170457393483709 |
| 11 | 7.4 | 7.55379072681704 | -0.153790726817042 |
| 12 | 7.2 | 7.33712406015038 | -0.137124060150376 |
| 13 | 7.2 | 7.25206648697215 | -0.0520664869721483 |
| 14 | 7.2 | 7.36015510474299 | -0.160155104742990 |
| 15 | 7.5 | 7.49348843807632 | 0.00651156192367716 |
| 16 | 7.4 | 7.49348843807632 | -0.0934884380763228 |
| 17 | 7.4 | 7.49348843807632 | -0.0934884380763225 |
| 18 | 8 | 7.82682177140966 | 0.173178228590344 |
| 19 | 8.1 | 7.81015510474299 | 0.28984489525701 |
| 20 | 8.1 | 7.79348843807632 | 0.306511561923677 |
| 21 | 8.1 | 7.71217844138649 | 0.387821558613514 |
| 22 | 8.1 | 7.71217844138649 | 0.387821558613515 |
| 23 | 8.1 | 7.69551177471982 | 0.404488225280181 |
| 24 | 7.9 | 7.47884510805315 | 0.421154891946849 |
| 25 | 7.9 | 7.39378753487492 | 0.506212465125077 |
| 26 | 8 | 7.50187615264577 | 0.498123847354235 |
| 27 | 8.1 | 7.6352094859791 | 0.464790514020901 |
| 28 | 8.1 | 7.6352094859791 | 0.464790514020901 |
| 29 | 8.1 | 7.6352094859791 | 0.464790514020901 |
| 30 | 8.5 | 7.96854281931243 | 0.531457180687568 |
| 31 | 8.5 | 7.95187615264576 | 0.548123847354235 |
| 32 | 8.6 | 7.9352094859791 | 0.664790514020901 |
| 33 | 8.4 | 8.14175946942829 | 0.258240530571712 |
| 34 | 8.4 | 8.14175946942829 | 0.258240530571712 |
| 35 | 8.4 | 8.12509280276162 | 0.274907197238379 |
| 36 | 7.7 | 7.90842613609496 | -0.208426136094955 |
| 37 | 7.8 | 7.82336856291673 | -0.023368562916727 |
| 38 | 7.9 | 7.93145718068757 | -0.0314571806875681 |
| 39 | 8.7 | 8.0647905140209 | 0.635209485979098 |
| 40 | 8.8 | 8.0647905140209 | 0.7352094859791 |
| 41 | 8.8 | 8.0647905140209 | 0.735209485979099 |
| 42 | 8.5 | 8.39812384735423 | 0.101876152645765 |
| 43 | 8.5 | 8.38145718068757 | 0.118542819312432 |
| 44 | 8.5 | 8.3647905140209 | 0.135209485979099 |
| 45 | 8.4 | 8.28348051733106 | 0.116519482668937 |
| 46 | 8.5 | 8.28348051733106 | 0.216519482668936 |
| 47 | 8.5 | 8.2668138506644 | 0.233186149335603 |
| 48 | 8.3 | 8.05014718399773 | 0.249852816002270 |
| 49 | 8.4 | 7.9650896108195 | 0.434910389180498 |
| 50 | 8.4 | 8.07317822859034 | 0.326821771409656 |
| 51 | 8.4 | 8.20651156192368 | 0.193488438076323 |
| 52 | 8.4 | 8.20651156192368 | 0.193488438076323 |
| 53 | 8.4 | 8.20651156192368 | 0.193488438076323 |
| 54 | 8.5 | 8.53984489525701 | -0.0398448952570104 |
| 55 | 8.5 | 8.52317822859034 | -0.0231782285903437 |
| 56 | 8.5 | 8.50651156192368 | -0.006511561923677 |
| 57 | 8.5 | 8.42520156523384 | 0.0747984347661607 |
| 58 | 8.5 | 8.42520156523384 | 0.0747984347661608 |
| 59 | 8.5 | 8.40853489856717 | 0.0914651014328275 |
| 60 | 8.3 | 8.1918682319005 | 0.108131768099495 |
| 61 | 8.3 | 8.10681065872228 | 0.193189341277723 |
| 62 | 8.4 | 8.21489927649312 | 0.185100723506881 |
| 63 | 8.2 | 8.34823260982645 | -0.148232609826453 |
| 64 | 8.2 | 8.34823260982645 | -0.148232609826453 |
| 65 | 8.1 | 8.34823260982645 | -0.248232609826453 |
| 66 | 8.1 | 8.68156594315979 | -0.581565943159786 |
| 67 | 8 | 8.66489927649312 | -0.664899276493119 |
| 68 | 7.8 | 8.64823260982645 | -0.848232609826453 |
| 69 | 7.9 | 8.56692261313662 | -0.666922613136614 |
| 70 | 7.8 | 8.56692261313662 | -0.766922613136615 |
| 71 | 7.7 | 8.55025594646995 | -0.850255946469948 |
| 72 | 7.9 | 8.33358927980328 | -0.433589279803281 |
| 73 | 7.8 | 8.24853170662505 | -0.448531706625054 |
