| Multiple Linear Regression - Estimated Regression Equation |
| y[t] = + 100.760435897436 + 0.370153846153844x[t] + 0.925943223443265M1[t] + 1.01766300366300M2[t] + 1.52430952380953M3[t] + 1.16364835164835M4[t] + 4.31965384615384M5[t] + 3.77565934065934M6[t] + 2.46499816849817M7[t] + 1.43767032967033M8[t] + 1.86034249084249M9[t] + 2.54968131868131M10[t] + 1.51066117216118M11[t] + 0.393994505494505t + 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) | 100.760435897436 | 1.650305 | 61.0556 | 0 | 0 |
| x | 0.370153846153844 | 1.475439 | 0.2509 | 0.802766 | 0.401383 |
| M1 | 0.925943223443265 | 1.950324 | 0.4748 | 0.636679 | 0.318339 |
| M2 | 1.01766300366300 | 1.950283 | 0.5218 | 0.603729 | 0.301864 |
| M3 | 1.52430952380953 | 2.028288 | 0.7515 | 0.455275 | 0.227637 |
| M4 | 1.16364835164835 | 2.027155 | 0.574 | 0.568093 | 0.284047 |
| M5 | 4.31965384615384 | 2.026511 | 2.1316 | 0.037147 | 0.018574 |
| M6 | 3.77565934065934 | 2.026358 | 1.8633 | 0.06732 | 0.03366 |
| M7 | 2.46499816849817 | 2.026696 | 1.2163 | 0.228648 | 0.114324 |
| M8 | 1.43767032967033 | 2.027524 | 0.7091 | 0.481023 | 0.240512 |
| M9 | 1.86034249084249 | 2.028841 | 0.9169 | 0.362841 | 0.18142 |
| M10 | 2.54968131868131 | 2.030648 | 1.2556 | 0.214129 | 0.107064 |
| M11 | 1.51066117216118 | 2.02106 | 0.7475 | 0.457706 | 0.228853 |
| t | 0.393994505494505 | 0.03153 | 12.496 | 0 | 0 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.938648554720468 |
| R-squared | 0.881061109278824 |
| Adjusted R-squared | 0.855291016289236 |
| F-TEST (value) | 34.1892871568139 |
| F-TEST (DF numerator) | 13 |
| F-TEST (DF denominator) | 60 |
| p-value | 0 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 3.50015320700787 |
| Sum Squared Residuals | 735.06434835165 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 104.3 | 102.080373626373 | 2.2196263736266 |
| 2 | 103.9 | 102.566087912088 | 1.33391208791204 |
| 3 | 103.9 | 103.466728937729 | 0.43327106227106 |
| 4 | 103.9 | 103.500062271062 | 0.399937728937729 |
| 5 | 108 | 107.050062271062 | 0.949937728937706 |
| 6 | 108 | 106.900062271062 | 1.09993772893772 |
| 7 | 108 | 105.983395604396 | 2.01660439560439 |
| 8 | 108 | 105.350062271062 | 2.64993772893773 |
| 9 | 108 | 106.166728937729 | 1.83327106227105 |
| 10 | 108 | 107.250062271062 | 0.749937728937722 |
| 11 | 108 | 106.605036630037 | 1.39496336996336 |
| 12 | 108 | 105.48836996337 | 2.51163003663002 |
| 13 | 108 | 106.808307692308 | 1.19169230769226 |
| 14 | 108 | 107.294021978022 | 0.705978021978036 |
| 15 | 108 | 108.194663003663 | -0.194663003663008 |
| 16 | 108 | 108.227996336996 | -0.227996336996346 |
| 17 | 108 | 111.777996336996 | -3.77799633699634 |
| 18 | 108 | 111.627996336996 | -3.62799633699635 |
| 19 | 108 | 110.711329670330 | -2.71132967032968 |
| 20 | 108 | 110.077996336996 | -2.07799633699634 |
| 21 | 108 | 110.894663003663 | -2.89466300366301 |
| 22 | 108 | 111.977996336996 | -3.97799633699634 |
| 23 | 108 | 111.703124542125 | -3.70312454212455 |
| 24 | 108 | 110.586457875458 | -2.58645787545788 |
| 25 | 108 | 111.906395604396 | -3.90639560439564 |
| 26 | 108 | 112.392109890110 | -4.39210989010988 |
| 27 | 108 | 113.292750915751 | -5.29275091575092 |
| 28 | 108.2 | 113.326084249084 | -5.12608424908424 |
| 29 | 112.3 | 116.876084249084 | -4.57608424908425 |
| 30 | 111.3 | 116.726084249084 | -5.42608424908425 |
| 31 | 111.3 | 115.809417582418 | -4.50941758241758 |
| 32 | 115.3 | 115.176084249084 | 0.123915750915748 |
| 33 | 117.2 | 115.992750915751 | 1.20724908424909 |
| 34 | 118.3 | 117.076084249084 | 1.22391575091575 |
| 35 | 118.3 | 116.431058608059 | 1.86894139194139 |
| 36 | 118.3 | 115.314391941392 | 2.98560805860806 |
| 37 | 119 | 116.634329670330 | 2.36567032967029 |
| 38 | 120.6 | 117.120043956044 | 3.47995604395604 |
| 39 | 122.6 | 118.020684981685 | 4.57931501831502 |
| 40 | 122.6 | 118.054018315018 | 4.54598168498168 |
| 41 | 127.4 | 121.604018315018 | 5.7959816849817 |
| 42 | 125.9 | 121.454018315018 | 4.44598168498169 |
| 43 | 121.5 | 120.537351648352 | 0.962648351648354 |
| 44 | 118.8 | 119.904018315018 | -1.10401831501831 |
| 45 | 121.6 | 120.720684981685 | 0.879315018315018 |
| 46 | 122.3 | 121.804018315018 | 0.495981684981688 |
| 47 | 122.7 | 121.158992673993 | 1.54100732600733 |
| 48 | 120.8 | 120.042326007326 | 0.757673992673993 |
| 49 | 120.1 | 121.362263736264 | -1.26226373626378 |
| 50 | 120.1 | 121.847978021978 | -1.74797802197802 |
| 51 | 120.1 | 122.748619047619 | -2.64861904761905 |
| 52 | 120.1 | 122.781952380952 | -2.68195238095238 |
| 53 | 128.4 | 126.331952380952 | 2.06804761904763 |
| 54 | 129.8 | 126.181952380952 | 3.61804761904763 |
| 55 | 129.8 | 125.265285714286 | 4.5347142857143 |
| 56 | 128.6 | 124.631952380952 | 3.96804761904762 |
| 57 | 128.6 | 125.448619047619 | 3.15138095238096 |
| 58 | 133.7 | 126.531952380952 | 7.16804761904762 |
| 59 | 130 | 125.886926739927 | 4.11307326007327 |
| 60 | 125.9 | 124.77026007326 | 1.12973992673994 |
| 61 | 129.4 | 126.090197802198 | 3.30980219780217 |
| 62 | 129.4 | 126.575912087912 | 2.82408791208793 |
| 63 | 130.6 | 127.476553113553 | 3.12344688644689 |
| 64 | 130.6 | 127.509886446886 | 3.09011355311356 |
| 65 | 130.6 | 131.059886446886 | -0.459886446886443 |
| 66 | 130.8 | 130.909886446886 | -0.109886446886432 |
| 67 | 129.7 | 129.993219780220 | -0.293219780219784 |
| 68 | 125.8 | 129.359886446886 | -3.55988644688644 |
| 69 | 126 | 130.176553113553 | -4.17655311355311 |
| 70 | 125.6 | 131.259886446886 | -5.65988644688644 |
| 71 | 125.4 | 130.614860805861 | -5.21486080586079 |
| 72 | 124.7 | 129.498194139194 | -4.79819413919413 |
| 73 | 126.9 | 130.818131868132 | -3.9181318681319 |
| 74 | 129.1 | 131.303846153846 | -2.20384615384615 |
