| Multiple Linear Regression - Estimated Regression Equation |
| status[t] = + 1.58337 -0.00239461`MDVP:Fo(Hz)`[t] -0.000138695`MDVP:Fhi(Hz)`[t] -0.00159563`MDVP:Flo(Hz)`[t] -168.038`MDVP:Jitter(%)`[t] -4462.28`MDVP:Jitter(Abs)`[t] -16.7296`MDVP:PPQ`[t] + 103.68`Jitter:DDP`[t] + 32.8725`MDVP:Shimmer`[t] -1635.56`Shimmer:APQ3`[t] -26.0714`Shimmer:APQ5`[t] -3.55789`MDVP:APQ`[t] + 539.3`Shimmer:DDA`[t] -2.25465NHR[t] -0.771266RPDE[t] + 0.403792DFA[t] + 0.128479spread1[t] + 1.1317spread2[t] + 0.103034D2[t] + 1.23075PPE[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) | 1.58337 | 0.955813 | 1.657 | 0.0993995 | 0.0496997 |
| `MDVP:Fo(Hz)` | -0.00239461 | 0.00149401 | -1.603 | 0.110781 | 0.0553907 |
| `MDVP:Fhi(Hz)` | -0.000138695 | 0.000316545 | -0.4382 | 0.661816 | 0.330908 |
| `MDVP:Flo(Hz)` | -0.00159563 | 0.000794803 | -2.008 | 0.0462265 | 0.0231133 |
| `MDVP:Jitter(%)` | -168.038 | 66.2983 | -2.535 | 0.0121352 | 0.00606758 |
| `MDVP:Jitter(Abs)` | -4462.28 | 4514.26 | -0.9885 | 0.32428 | 0.16214 |
| `MDVP:PPQ` | -16.7296 | 82.0259 | -0.204 | 0.838625 | 0.419313 |
| `Jitter:DDP` | 103.68 | 26.4823 | 3.915 | 0.000129327 | 6.46633e-05 |
| `MDVP:Shimmer` | 32.8725 | 29.2664 | 1.123 | 0.262884 | 0.131442 |
| `Shimmer:APQ3` | -1635.56 | 8870.09 | -0.1844 | 0.85392 | 0.42696 |
| `Shimmer:APQ5` | -26.0714 | 19.3875 | -1.345 | 0.180445 | 0.0902227 |
| `MDVP:APQ` | -3.55789 | 10.6889 | -0.3329 | 0.739639 | 0.36982 |
| `Shimmer:DDA` | 539.3 | 2956.16 | 0.1824 | 0.855454 | 0.427727 |
| NHR | -2.25465 | 1.95588 | -1.153 | 0.250583 | 0.125291 |
| RPDE | -0.771266 | 0.357178 | -2.159 | 0.0321856 | 0.0160928 |
| DFA | 0.403792 | 0.725173 | 0.5568 | 0.578361 | 0.28918 |
| spread1 | 0.128479 | 0.0967595 | 1.328 | 0.185969 | 0.0929844 |
| spread2 | 1.1317 | 0.45852 | 2.468 | 0.0145419 | 0.00727096 |
| D2 | 0.103034 | 0.104534 | 0.9857 | 0.325662 | 0.162831 |
| PPE | 1.23075 | 1.31587 | 0.9353 | 0.350916 | 0.175458 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.698609 |
| R-squared | 0.488055 |
| Adjusted R-squared | 0.432472 |
| F-TEST (value) | 8.78071 |
| F-TEST (DF numerator) | 19 |
| F-TEST (DF denominator) | 175 |
| p-value | 0 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 0.325353 |
| Sum Squared Residuals | 18.5245 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 1 | 0.937356 | 0.0626441 |
| 2 | 1 | 1.06837 | -0.0683717 |
| 3 | 1 | 1.00273 | -0.00273208 |
| 4 | 1 | 1.09493 | -0.0949321 |
| 5 | 1 | 0.926169 | 0.0738307 |
| 6 | 1 | 0.97407 | 0.0259301 |
| 7 | 1 | 0.802304 | 0.197696 |
| 8 | 1 | 0.655331 | 0.344669 |
| 9 | 1 | 0.95399 | 0.0460098 |
| 10 | 1 | 1.14307 | -0.143069 |
| 11 | 1 | 1.07755 | -0.0775508 |
| 12 | 1 | 1.23016 | -0.230155 |
| 13 | 1 | 0.460638 | 0.539362 |
| 14 | 1 | 0.878178 | 0.121822 |
| 15 | 1 | 0.711382 | 0.288618 |
| 16 | 1 | 0.736528 | 0.263472 |
| 17 | 1 | 0.546932 | 0.453068 |
| 18 | 1 | 1.32614 | -0.326136 |
| 19 | 1 | 1.30228 | -0.302279 |
| 20 | 1 | 0.96455 | 0.0354499 |
| 21 | 1 | 1.08731 | -0.0873105 |
| 22 | 1 | 0.904967 | 0.0950334 |
| 23 | 1 | 1.18543 | -0.185426 |
| 24 | 1 | 0.891819 | 0.108181 |
| 25 | 1 | 0.830366 | 0.169634 |
| 26 | 1 | 0.932469 | 0.0675309 |
| 27 | 1 | 0.830335 | 0.169665 |
| 28 | 1 | 0.794593 | 0.205407 |
| 29 | 1 | 0.673193 | 0.326807 |
| 30 | 1 | 0.698497 | 0.301503 |
| 31 | 0 | 0.297847 | -0.297847 |
| 32 | 0 | 0.243088 | -0.243088 |
| 33 | 0 | 0.246969 | -0.246969 |
| 34 | 0 | 0.185468 | -0.185468 |
| 35 | 0 | 0.131913 | -0.131913 |
| 36 | 0 | 0.292967 | -0.292967 |
| 37 | 1 | 0.799527 | 0.200473 |
| 38 | 1 | 0.825493 | 0.174507 |
| 39 | 1 | 0.606112 | 0.393888 |
| 40 | 1 | 0.764863 | 0.235137 |
| 41 | 1 | 0.612889 | 0.387111 |
| 42 | 1 | 0.451997 | 0.548003 |
| 43 | 0 | 0.202459 | -0.202459 |
| 44 | 0 | 0.192905 | -0.192905 |
| 45 | 0 | 0.0286343 | -0.0286343 |
| 46 | 0 | 0.107352 | -0.107352 |
| 47 | 0 | 0.0723385 | -0.0723385 |
| 48 | 0 | -0.00173365 | 0.00173365 |
| 49 | 0 | 0.335743 | -0.335743 |
| 50 | 0 | 0.4356 | -0.4356 |
| 51 | 0 | 0.434401 | -0.434401 |
| 52 | 0 | 0.446055 | -0.446055 |
| 53 | 0 | 0.411825 | -0.411825 |
| 54 | 0 | 0.553046 | -0.553046 |
| 55 | 1 | 0.820007 | 0.179993 |
| 56 | 1 | 0.791408 | 0.208592 |
| 57 | 1 | 0.884677 | 0.115323 |
| 58 | 1 | 0.766185 | 0.233815 |
| 59 | 1 | 0.768513 | 0.231487 |
| 60 | 1 | 0.61424 | 0.38576 |
| 61 | 0 | 0.392463 | -0.392463 |
| 62 | 0 | 0.330412 | -0.330412 |
| 63 | 0 | 0.276768 | -0.276768 |
| 64 | 0 | 0.224138 | -0.224138 |
| 65 | 0 | 0.109977 | -0.109977 |
| 66 | 0 | 0.271188 | -0.271188 |
| 67 | 1 | 0.88042 | 0.11958 |
| 68 | 1 | 0.857702 | 0.142298 |
| 69 | 1 | 0.948804 | 0.0511955 |
| 70 | 1 | 0.98425 | 0.0157502 |
| 71 | 1 | 0.819281 | 0.180719 |
| 72 | 1 | 1.09632 | -0.0963242 |
| 73 | 1 | 0.904691 | 0.0953095 |
| 74 | 1 | 0.906043 | 0.0939569 |
| 75 | 1 | 1.07332 | -0.0733189 |
| 76 | 1 | 1.05775 | -0.0577489 |
| 77 | 1 | 1.11024 | -0.110238 |
| 78 | 1 | 1.00579 | -0.00578513 |
| 79 | 1 | 0.97858 | 0.0214202 |
| 80 | 1 | 1.0827 | -0.0826968 |
| 81 | 1 | 1.18395 | -0.183945 |
| 82 | 1 | 1.10303 | -0.103033 |
| 83 | 1 | 1.00903 | -0.00902578 |
| 84 | 1 | 0.705473 | 0.294527 |
| 85 | 1 | 1.06574 | -0.0657364 |
| 86 | 1 | 0.864408 | 0.135592 |
| 87 | 1 | 0.657385 | 0.342615 |
| 88 | 1 | 0.949762 | 0.0502382 |
| 89 | 1 | 0.970458 | 0.0295418 |
| 90 | 1 | 1.17029 | -0.170294 |
| 91 | 1 | 1.13832 | -0.138322 |
| 92 | 1 | 0.798749 | 0.201251 |
| 93 | 1 | 0.712751 | 0.287249 |
| 94 | 1 | 0.800903 | 0.199097 |
| 95 | 1 | 0.815211 | 0.184789 |
| 96 | 1 | 0.756302 | 0.243698 |
| 97 | 1 | 0.782813 | 0.217187 |
| 98 | 1 | 1.01377 | -0.0137686 |
| 99 | 1 | 0.768441 | 0.231559 |
| 100 | 1 | 0.885742 | 0.114258 |
| 101 | 1 | 0.98303 | 0.0169702 |
| 102 | 1 | 0.995343 | 0.00465713 |
| 103 | 1 | 1.0445 | -0.044495 |
| 104 | 1 | 0.572582 | 0.427418 |
| 105 | 1 | 0.571395 | 0.428605 |
| 106 | 1 | 0.556544 | 0.443456 |
| 107 | 1 | 0.56724 | 0.43276 |
| 108 | 1 | 0.694327 | 0.305673 |
| 109 | 1 | 0.653011 | 0.346989 |
| 110 | 1 | 0.924769 | 0.0752305 |
| 111 | 1 | 1.05296 | -0.0529555 |
| 112 | 1 | 0.561793 | 0.438207 |
| 113 | 1 | 0.820787 | 0.179213 |
| 114 | 1 | 0.692369 | 0.307631 |
| 115 | 1 | 0.781774 | 0.218226 |
| 116 | 1 | 0.863072 | 0.136928 |
| 117 | 1 | 0.750949 | 0.249051 |
| 118 | 1 | 1.09169 | -0.0916941 |
| 119 | 1 | 0.883727 | 0.116273 |
| 120 | 1 | 0.764318 | 0.235682 |
| 121 | 1 | 0.560996 | 0.439004 |
| 122 | 1 | 1.00151 | -0.00151382 |
| 123 | 1 | 0.936607 | 0.0633929 |
| 124 | 1 | 0.698999 | 0.301001 |
| 125 | 1 | 0.601461 | 0.398539 |
| 126 | 1 | 0.591827 | 0.408173 |
| 127 | 1 | 0.577916 | 0.422084 |
| 128 | 1 | 0.599845 | 0.400155 |
| 129 | 1 | 0.445568 | 0.554432 |
| 130 | 1 | 0.780751 | 0.219249 |
| 131 | 1 | 0.80822 | 0.19178 |
| 132 | 1 | 0.914989 | 0.0850111 |
| 133 | 1 | 1.03045 | -0.0304476 |
| 134 | 1 | 0.644294 | 0.355706 |
| 135 | 1 | 0.935496 | 0.0645043 |
| 136 | 1 | 0.960039 | 0.0399609 |
| 137 | 1 | 1.14962 | -0.149623 |
| 138 | 1 | 1.14918 | -0.149177 |
| 139 | 1 | 0.950337 | 0.0496629 |
| 140 | 1 | 0.770222 | 0.229778 |
| 141 | 1 | 0.934059 | 0.0659409 |
| 142 | 1 | 0.904439 | 0.0955609 |
| 143 | 1 | 0.72179 | 0.27821 |
| 144 | 1 | 0.631468 | 0.368532 |
| 145 | 1 | 0.534794 | 0.465206 |
| 146 | 1 | 0.851266 | 0.148734 |
| 147 | 1 | 1.34772 | -0.347719 |
| 148 | 1 | 1.1218 | -0.121804 |
| 149 | 1 | 1.25968 | -0.259677 |
| 150 | 1 | 0.848108 | 0.151892 |
| 151 | 1 | 0.82481 | 0.17519 |
| 152 | 1 | 1.0221 | -0.0221015 |
| 153 | 1 | 0.9684 | 0.0316001 |
| 154 | 1 | 0.811903 | 0.188097 |
| 155 | 1 | 0.927261 | 0.0727394 |
| 156 | 1 | 1.04201 | -0.0420136 |
| 157 | 1 | 0.827394 | 0.172606 |
| 158 | 1 | 1.30659 | -0.306587 |
| 159 | 1 | 1.00281 | -0.00280667 |
| 160 | 1 | 0.810082 | 0.189918 |
| 161 | 1 | 1.09388 | -0.0938775 |
| 162 | 1 | 1.02161 | -0.0216139 |
| 163 | 1 | 0.907336 | 0.0926637 |
| 164 | 1 | 0.74898 | 0.25102 |
| 165 | 1 | 1.3308 | -0.330799 |
| 166 | 0 | 0.469862 | -0.469862 |
| 167 | 0 | 0.18347 | -0.18347 |
| 168 | 0 | 0.0170754 | -0.0170754 |
| 169 | 0 | 0.92948 | -0.92948 |
| 170 | 0 | 0.176408 | -0.176408 |
| 171 | 0 | 0.0827605 | -0.0827605 |
| 172 | 0 | 0.801143 | -0.801143 |
| 173 | 0 | 0.825604 | -0.825604 |
| 174 | 0 | 0.870676 | -0.870676 |
| 175 | 0 | 0.84701 | -0.84701 |
| 176 | 0 | 0.829027 | -0.829027 |
| 177 | 0 | 0.784236 | -0.784236 |
| 178 | 1 | 0.631718 | 0.368282 |
| 179 | 1 | 0.706528 | 0.293472 |
| 180 | 1 | 0.934038 | 0.0659616 |
| 181 | 1 | 0.73146 | 0.26854 |
| 182 | 1 | 0.863711 | 0.136289 |
| 183 | 1 | 0.68647 | 0.31353 |
| 184 | 0 | 0.608799 | -0.608799 |
| 185 | 0 | 0.65261 | -0.65261 |
| 186 | 0 | 0.622751 | -0.622751 |
| 187 | 0 | 0.4327 | -0.4327 |
| 188 | 0 | 0.485684 | -0.485684 |
| 189 | 0 | 0.44128 | -0.44128 |
| 190 | 0 | 0.424169 | -0.424169 |
| 191 | 0 | 0.629371 | -0.629371 |
| 192 | 0 | 0.673334 | -0.673334 |
| 193 | 0 | -0.207555 | 0.207555 |
| 194 | 0 | 0.209971 | -0.209971 |
| 195 | 0 | 0.512846 | -0.512846 |
| Goldfeld-Quandt test for Heteroskedasticity | |||
| p-values | Alternative Hypothesis | ||
| breakpoint index | greater | 2-sided | less |
| 23 | 2.73957e-48 | 5.47913e-48 | 1 |
| 24 | 6.90507e-65 | 1.38101e-64 | 1 |
| 25 | 1.87082e-81 | 3.74164e-81 | 1 |
| 26 | 2.49543e-104 | 4.99086e-104 | 1 |
| 27 | 5.17981e-111 | 1.03596e-110 | 1 |
| 28 | 5.68538e-124 | 1.13708e-123 | 1 |
| 29 | 5.31694e-141 | 1.06339e-140 | 1 |
| 30 | 4.71827e-157 | 9.43655e-157 | 1 |
| 31 | 3.79993e-05 | 7.59986e-05 | 0.999962 |
| 32 | 1.14904e-05 | 2.29809e-05 | 0.999989 |
| 33 | 3.42147e-06 | 6.84295e-06 | 0.999997 |
| 34 | 9.5923e-07 | 1.91846e-06 | 0.999999 |
| 35 | 2.55572e-07 | 5.11143e-07 | 1 |
| 36 | 9.60775e-08 | 1.92155e-07 | 1 |
| 37 | 4.06466e-05 | 8.12931e-05 | 0.999959 |
| 38 | 5.0708e-05 | 0.000101416 | 0.999949 |
| 39 | 0.000971919 | 0.00194384 | 0.999028 |
| 40 | 0.00175896 | 0.00351793 | 0.998241 |
| 41 | 0.00311709 | 0.00623417 | 0.996883 |
| 42 | 0.00262488 | 0.00524976 | 0.997375 |
| 43 | 0.00147638 | 0.00295276 | 0.998524 |
| 44 | 0.00102343 | 0.00204686 | 0.998977 |
| 45 | 0.000653565 | 0.00130713 | 0.999346 |
| 46 | 0.000379441 | 0.000758883 | 0.999621 |
| 47 | 0.000272417 | 0.000544834 | 0.999728 |
| 48 | 0.000567082 | 0.00113416 | 0.999433 |
| 49 | 0.000540018 | 0.00108004 | 0.99946 |
| 50 | 0.000444011 | 0.000888022 | 0.999556 |
| 51 | 0.000300532 | 0.000601065 | 0.999699 |
| 52 | 0.000230971 | 0.000461941 | 0.999769 |
| 53 | 0.000180013 | 0.000360027 | 0.99982 |
| 54 | 0.000207582 | 0.000415164 | 0.999792 |
| 55 | 0.000173703 | 0.000347405 | 0.999826 |
| 56 | 0.000139476 | 0.000278952 | 0.999861 |
| 57 | 8.64433e-05 | 0.000172887 | 0.999914 |
| 58 | 6.7632e-05 | 0.000135264 | 0.999932 |
| 59 | 4.38016e-05 | 8.76032e-05 | 0.999956 |
| 60 | 2.74365e-05 | 5.48731e-05 | 0.999973 |
| 61 | 0.000336279 | 0.000672557 | 0.999664 |
| 62 | 0.000348741 | 0.000697481 | 0.999651 |
| 63 | 0.000424512 | 0.000849024 | 0.999575 |
| 64 | 0.000427311 | 0.000854621 | 0.999573 |
| 65 | 0.000274395 | 0.000548791 | 0.999726 |
| 66 | 0.000230974 | 0.000461949 | 0.999769 |
| 67 | 0.00015278 | 0.00030556 | 0.999847 |
| 68 | 9.88365e-05 | 0.000197673 | 0.999901 |
| 69 | 9.79202e-05 | 0.00019584 | 0.999902 |
| 70 | 7.69336e-05 | 0.000153867 | 0.999923 |
| 71 | 4.57046e-05 | 9.14093e-05 | 0.999954 |
| 72 | 3.13527e-05 | 6.27054e-05 | 0.999969 |
| 73 | 1.81742e-05 | 3.63483e-05 | 0.999982 |
| 74 | 5.38999e-05 | 0.0001078 | 0.999946 |
| 75 | 6.85188e-05 | 0.000137038 | 0.999931 |
| 76 | 4.96331e-05 | 9.92661e-05 | 0.99995 |
| 77 | 3.18618e-05 | 6.37235e-05 | 0.999968 |
| 78 | 2.49912e-05 | 4.99823e-05 | 0.999975 |
| 79 | 1.4627e-05 | 2.9254e-05 | 0.999985 |
| 80 | 1.08439e-05 | 2.16879e-05 | 0.999989 |
| 81 | 8.20208e-06 | 1.64042e-05 | 0.999992 |
| 82 | 4.72675e-06 | 9.45349e-06 | 0.999995 |
| 83 | 3.11238e-06 | 6.22476e-06 | 0.999997 |
| 84 | 2.03735e-06 | 4.0747e-06 | 0.999998 |
| 85 | 1.22853e-06 | 2.45706e-06 | 0.999999 |
| 86 | 1.59644e-06 | 3.19288e-06 | 0.999998 |
| 87 | 3.2911e-06 | 6.58221e-06 | 0.999997 |
| 88 | 1.9799e-06 | 3.95981e-06 | 0.999998 |
| 89 | 1.48741e-06 | 2.97481e-06 | 0.999999 |
| 90 | 2.66063e-06 | 5.32125e-06 | 0.999997 |
| 91 | 3.68841e-06 | 7.37681e-06 | 0.999996 |
| 92 | 4.85549e-06 | 9.71099e-06 | 0.999995 |
| 93 | 3.40973e-06 | 6.81945e-06 | 0.999997 |
| 94 | 2.89175e-06 | 5.7835e-06 | 0.999997 |
| 95 | 1.99973e-06 | 3.99946e-06 | 0.999998 |
| 96 | 1.3527e-06 | 2.70539e-06 | 0.999999 |
| 97 | 9.09721e-07 | 1.81944e-06 | 0.999999 |
| 98 | 5.23976e-07 | 1.04795e-06 | 0.999999 |
| 99 | 3.14876e-07 | 6.29752e-07 | 1 |
| 100 | 2.34998e-07 | 4.69996e-07 | 1 |
| 101 | 1.43424e-07 | 2.86848e-07 | 1 |
| 102 | 1.28829e-07 | 2.57658e-07 | 1 |
| 103 | 1.66596e-07 | 3.33191e-07 | 1 |
| 104 | 3.38582e-07 | 6.77165e-07 | 1 |
| 105 | 5.10738e-07 | 1.02148e-06 | 0.999999 |
| 106 | 1.0102e-06 | 2.0204e-06 | 0.999999 |
| 107 | 1.78272e-06 | 3.56545e-06 | 0.999998 |
| 108 | 1.25506e-06 | 2.51011e-06 | 0.999999 |
| 109 | 2.35223e-06 | 4.70446e-06 | 0.999998 |
| 110 | 1.7448e-06 | 3.4896e-06 | 0.999998 |
| 111 | 1.05971e-06 | 2.11941e-06 | 0.999999 |
| 112 | 2.11007e-06 | 4.22014e-06 | 0.999998 |
| 113 | 1.26807e-06 | 2.53614e-06 | 0.999999 |
| 114 | 1.38667e-06 | 2.77335e-06 | 0.999999 |
| 115 | 1.60602e-06 | 3.21205e-06 | 0.999998 |
| 116 | 1.39162e-06 | 2.78324e-06 | 0.999999 |
| 117 | 1.59088e-06 | 3.18176e-06 | 0.999998 |
| 118 | 1.10206e-06 | 2.20413e-06 | 0.999999 |
| 119 | 7.59898e-07 | 1.5198e-06 | 0.999999 |
| 120 | 1.44388e-06 | 2.88776e-06 | 0.999999 |
| 121 | 4.67124e-06 | 9.34247e-06 | 0.999995 |
| 122 | 1.03229e-05 | 2.06458e-05 | 0.99999 |
| 123 | 6.83269e-06 | 1.36654e-05 | 0.999993 |
| 124 | 4.97023e-06 | 9.94045e-06 | 0.999995 |
| 125 | 3.83734e-06 | 7.67469e-06 | 0.999996 |
| 126 | 5.43476e-06 | 1.08695e-05 | 0.999995 |
| 127 | 1.05404e-05 | 2.10809e-05 | 0.999989 |
| 128 | 0.000181318 | 0.000362635 | 0.999819 |
| 129 | 0.000328731 | 0.000657461 | 0.999671 |
| 130 | 0.00032942 | 0.00065884 | 0.999671 |
| 131 | 0.000274486 | 0.000548972 | 0.999726 |
| 132 | 0.000183796 | 0.000367592 | 0.999816 |
| 133 | 0.000152565 | 0.00030513 | 0.999847 |
| 134 | 0.000492361 | 0.000984722 | 0.999508 |
| 135 | 0.000652928 | 0.00130586 | 0.999347 |
| 136 | 0.00046553 | 0.000931061 | 0.999534 |
| 137 | 0.000555043 | 0.00111009 | 0.999445 |
| 138 | 0.000510186 | 0.00102037 | 0.99949 |
| 139 | 0.000324689 | 0.000649379 | 0.999675 |
| 140 | 0.000207914 | 0.000415828 | 0.999792 |
| 141 | 0.000211177 | 0.000422354 | 0.999789 |
| 142 | 0.000149602 | 0.000299204 | 0.99985 |
| 143 | 0.000149353 | 0.000298706 | 0.999851 |
| 144 | 0.000470318 | 0.000940635 | 0.99953 |
| 145 | 0.00045973 | 0.000919461 | 0.99954 |
| 146 | 0.000406078 | 0.000812156 | 0.999594 |
| 147 | 0.000345622 | 0.000691244 | 0.999654 |
| 148 | 0.00027451 | 0.00054902 | 0.999725 |
| 149 | 0.000176392 | 0.000352783 | 0.999824 |
| 150 | 0.000164869 | 0.000329738 | 0.999835 |
| 151 | 9.67803e-05 | 0.000193561 | 0.999903 |
| 152 | 0.00067965 | 0.0013593 | 0.99932 |
| 153 | 0.000511057 | 0.00102211 | 0.999489 |
| 154 | 0.000362237 | 0.000724474 | 0.999638 |
| 155 | 0.000263215 | 0.000526429 | 0.999737 |
| 156 | 0.000271598 | 0.000543195 | 0.999728 |
| 157 | 0.000248637 | 0.000497274 | 0.999751 |
| 158 | 0.000240882 | 0.000481765 | 0.999759 |
| 159 | 0.000147707 | 0.000295415 | 0.999852 |
| 160 | 0.000141854 | 0.000283708 | 0.999858 |
| 161 | 0.000622814 | 0.00124563 | 0.999377 |
| 162 | 0.00054238 | 0.00108476 | 0.999458 |
| 163 | 0.000529872 | 0.00105974 | 0.99947 |
| 164 | 0.125691 | 0.251381 | 0.874309 |
| 165 | 0.329114 | 0.658228 | 0.670886 |
| 166 | 0.28567 | 0.571341 | 0.71433 |
| 167 | 0.265485 | 0.530971 | 0.734515 |
| 168 | 0.199434 | 0.398867 | 0.800566 |
| 169 | 0.255218 | 0.510436 | 0.744782 |
| 170 | 0.223172 | 0.446345 | 0.776828 |
| 171 | 0.786459 | 0.427082 | 0.213541 |
| 172 | 0.866425 | 0.26715 | 0.133575 |
| Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
| Description | # significant tests | % significant tests | OK/NOK |
| 1% type I error level | 141 | 0.94 | NOK |
| 5% type I error level | 141 | 0.94 | NOK |
| 10% type I error level | 141 | 0.94 | NOK |
