| Multiple Linear Regression - Estimated Regression Equation |
| status[t] = + 2.22086 -0.00166542`MDVP:Fo(Hz)`[t] -9.24141e-05`MDVP:Fhi(Hz)`[t] -0.001652`MDVP:Flo(Hz)`[t] -198.749`MDVP:Jitter(%)`[t] -1002.65`MDVP:RAP`[t] -25.6859`MDVP:PPQ`[t] + 438.531`Jitter:DDP`[t] + 22.4255`MDVP:Shimmer`[t] + 0.609317`MDVP:Shimmer(dB)`[t] -227.898`Shimmer:APQ3`[t] -27.8488`Shimmer:APQ5`[t] + 1.0568`MDVP:APQ`[t] + 70.7339`Shimmer:DDA`[t] -2.56541NHR[t] -0.0176013HNR[t] -1.06253RPDE[t] + 0.441091DFA[t] + 0.139239spread1[t] + 1.26289spread2[t] + 0.058223D2[t] + 0.962396PPE[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) | 2.22086 | 1.15675 | 1.92 | 0.0565129 | 0.0282565 |
| `MDVP:Fo(Hz)` | -0.00166542 | 0.00112881 | -1.475 | 0.141927 | 0.0709635 |
| `MDVP:Fhi(Hz)` | -9.24141e-05 | 0.000319035 | -0.2897 | 0.772417 | 0.386209 |
| `MDVP:Flo(Hz)` | -0.001652 | 0.000784526 | -2.106 | 0.0366708 | 0.0183354 |
| `MDVP:Jitter(%)` | -198.749 | 59.6504 | -3.332 | 0.00105468 | 0.000527339 |
| `MDVP:RAP` | -1002.65 | 9312.65 | -0.1077 | 0.914386 | 0.457193 |
| `MDVP:PPQ` | -25.6859 | 87.0557 | -0.2951 | 0.768309 | 0.384154 |
| `Jitter:DDP` | 438.531 | 3105.23 | 0.1412 | 0.887858 | 0.443929 |
| `MDVP:Shimmer` | 22.4255 | 33.5145 | 0.6691 | 0.504305 | 0.252153 |
| `MDVP:Shimmer(dB)` | 0.609317 | 1.19645 | 0.5093 | 0.611212 | 0.305606 |
| `Shimmer:APQ3` | -227.898 | 8914.82 | -0.02556 | 0.979635 | 0.489817 |
| `Shimmer:APQ5` | -27.8488 | 19.9929 | -1.393 | 0.165428 | 0.082714 |
| `MDVP:APQ` | 1.0568 | 9.23433 | 0.1144 | 0.909019 | 0.45451 |
| `Shimmer:DDA` | 70.7339 | 2971.04 | 0.02381 | 0.981033 | 0.490517 |
| NHR | -2.56541 | 1.97706 | -1.298 | 0.196156 | 0.098078 |
| HNR | -0.0176013 | 0.0140749 | -1.251 | 0.21279 | 0.106395 |
| RPDE | -1.06253 | 0.433804 | -2.449 | 0.0153089 | 0.00765447 |
| DFA | 0.441091 | 0.728609 | 0.6054 | 0.545714 | 0.272857 |
| spread1 | 0.139239 | 0.0963406 | 1.445 | 0.150188 | 0.0750938 |
| spread2 | 1.26289 | 0.477321 | 2.646 | 0.00890123 | 0.00445062 |
| D2 | 0.058223 | 0.113512 | 0.5129 | 0.608658 | 0.304329 |
| PPE | 0.962396 | 1.31644 | 0.7311 | 0.465733 | 0.232866 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.700873 |
| R-squared | 0.491223 |
| Adjusted R-squared | 0.429464 |
| F-TEST (value) | 7.95385 |
| F-TEST (DF numerator) | 21 |
| F-TEST (DF denominator) | 173 |
| p-value | 2.22045e-16 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 0.326214 |
| Sum Squared Residuals | 18.4099 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 1 | 0.958879 | 0.0411208 |
| 2 | 1 | 1.06218 | -0.0621753 |
| 3 | 1 | 0.987743 | 0.0122572 |
| 4 | 1 | 1.09203 | -0.0920253 |
| 5 | 1 | 0.886712 | 0.113288 |
| 6 | 1 | 0.941099 | 0.0589013 |
| 7 | 1 | 0.773718 | 0.226282 |
| 8 | 1 | 0.563437 | 0.436563 |
| 9 | 1 | 0.999905 | 9.47239e-05 |
| 10 | 1 | 1.18078 | -0.180781 |
| 11 | 1 | 1.14753 | -0.147533 |
| 12 | 1 | 1.26191 | -0.261909 |
| 13 | 1 | 0.435312 | 0.564688 |
| 14 | 1 | 0.890283 | 0.109717 |
| 15 | 1 | 0.691669 | 0.308331 |
| 16 | 1 | 0.692597 | 0.307403 |
| 17 | 1 | 0.551696 | 0.448304 |
| 18 | 1 | 1.29349 | -0.293492 |
| 19 | 1 | 1.30714 | -0.307136 |
| 20 | 1 | 0.961114 | 0.0388859 |
| 21 | 1 | 1.04418 | -0.0441791 |
| 22 | 1 | 0.910695 | 0.0893049 |
| 23 | 1 | 1.1245 | -0.124502 |
| 24 | 1 | 0.874154 | 0.125846 |
| 25 | 1 | 0.830066 | 0.169934 |
| 26 | 1 | 0.962052 | 0.0379482 |
| 27 | 1 | 0.824663 | 0.175337 |
| 28 | 1 | 0.786448 | 0.213552 |
| 29 | 1 | 0.65982 | 0.34018 |
| 30 | 1 | 0.694335 | 0.305665 |
| 31 | 0 | 0.277616 | -0.277616 |
| 32 | 0 | 0.146771 | -0.146771 |
| 33 | 0 | 0.183047 | -0.183047 |
| 34 | 0 | 0.127774 | -0.127774 |
| 35 | 0 | 0.0924532 | -0.0924532 |
| 36 | 0 | 0.212884 | -0.212884 |
| 37 | 1 | 0.797529 | 0.202471 |
| 38 | 1 | 0.820611 | 0.179389 |
| 39 | 1 | 0.609843 | 0.390157 |
| 40 | 1 | 0.762335 | 0.237665 |
| 41 | 1 | 0.634035 | 0.365965 |
| 42 | 1 | 0.432905 | 0.567095 |
| 43 | 0 | 0.261246 | -0.261246 |
| 44 | 0 | 0.216908 | -0.216908 |
| 45 | 0 | 0.0430149 | -0.0430149 |
| 46 | 0 | 0.107751 | -0.107751 |
| 47 | 0 | 0.072201 | -0.072201 |
| 48 | 0 | -0.0201599 | 0.0201599 |
| 49 | 0 | 0.332225 | -0.332225 |
| 50 | 0 | 0.41673 | -0.41673 |
| 51 | 0 | 0.394788 | -0.394788 |
| 52 | 0 | 0.451442 | -0.451442 |
| 53 | 0 | 0.39317 | -0.39317 |
| 54 | 0 | 0.553351 | -0.553351 |
| 55 | 1 | 0.842255 | 0.157745 |
| 56 | 1 | 0.811648 | 0.188352 |
| 57 | 1 | 0.874403 | 0.125597 |
| 58 | 1 | 0.756292 | 0.243708 |
| 59 | 1 | 0.794369 | 0.205631 |
| 60 | 1 | 0.692974 | 0.307026 |
| 61 | 0 | 0.376374 | -0.376374 |
| 62 | 0 | 0.282495 | -0.282495 |
| 63 | 0 | 0.267731 | -0.267731 |
| 64 | 0 | 0.217911 | -0.217911 |
| 65 | 0 | 0.145804 | -0.145804 |
| 66 | 0 | 0.309337 | -0.309337 |
| 67 | 1 | 0.925485 | 0.0745148 |
| 68 | 1 | 0.904966 | 0.0950339 |
| 69 | 1 | 0.909659 | 0.0903406 |
| 70 | 1 | 0.936212 | 0.0637881 |
| 71 | 1 | 0.869796 | 0.130204 |
| 72 | 1 | 1.09437 | -0.0943678 |
| 73 | 1 | 0.868072 | 0.131928 |
| 74 | 1 | 0.943874 | 0.0561258 |
| 75 | 1 | 1.02599 | -0.0259891 |
| 76 | 1 | 1.089 | -0.089003 |
| 77 | 1 | 1.08112 | -0.0811183 |
| 78 | 1 | 0.988209 | 0.0117909 |
| 79 | 1 | 0.962208 | 0.0377917 |
| 80 | 1 | 1.18105 | -0.181054 |
| 81 | 1 | 1.18996 | -0.189961 |
| 82 | 1 | 1.14011 | -0.140105 |
| 83 | 1 | 1.02079 | -0.0207864 |
| 84 | 1 | 0.681666 | 0.318334 |
| 85 | 1 | 1.06974 | -0.0697351 |
| 86 | 1 | 0.85878 | 0.14122 |
| 87 | 1 | 0.712019 | 0.287981 |
| 88 | 1 | 0.938589 | 0.0614113 |
| 89 | 1 | 1.00435 | -0.00434516 |
| 90 | 1 | 1.21076 | -0.210762 |
| 91 | 1 | 1.12483 | -0.124827 |
| 92 | 1 | 0.786851 | 0.213149 |
| 93 | 1 | 0.717391 | 0.282609 |
| 94 | 1 | 0.864459 | 0.135541 |
| 95 | 1 | 0.769108 | 0.230892 |
| 96 | 1 | 0.73564 | 0.26436 |
| 97 | 1 | 0.800689 | 0.199311 |
| 98 | 1 | 1.0226 | -0.0226049 |
| 99 | 1 | 0.826408 | 0.173592 |
| 100 | 1 | 0.926716 | 0.0732844 |
| 101 | 1 | 0.987725 | 0.0122753 |
| 102 | 1 | 0.992831 | 0.0071694 |
| 103 | 1 | 0.978183 | 0.0218175 |
| 104 | 1 | 0.598167 | 0.401833 |
| 105 | 1 | 0.572149 | 0.427851 |
| 106 | 1 | 0.563684 | 0.436316 |
| 107 | 1 | 0.517108 | 0.482892 |
| 108 | 1 | 0.699103 | 0.300897 |
| 109 | 1 | 0.6058 | 0.3942 |
| 110 | 1 | 0.882059 | 0.117941 |
| 111 | 1 | 1.01868 | -0.0186822 |
| 112 | 1 | 0.589462 | 0.410538 |
| 113 | 1 | 0.752629 | 0.247371 |
| 114 | 1 | 0.701138 | 0.298862 |
| 115 | 1 | 0.808462 | 0.191538 |
| 116 | 1 | 0.869834 | 0.130166 |
| 117 | 1 | 0.721603 | 0.278397 |
| 118 | 1 | 1.03216 | -0.0321553 |
| 119 | 1 | 0.894272 | 0.105728 |
| 120 | 1 | 0.762287 | 0.237713 |
| 121 | 1 | 0.57745 | 0.42255 |
| 122 | 1 | 0.978441 | 0.0215593 |
| 123 | 1 | 0.963161 | 0.0368388 |
| 124 | 1 | 0.700475 | 0.299525 |
| 125 | 1 | 0.588595 | 0.411405 |
| 126 | 1 | 0.607526 | 0.392474 |
| 127 | 1 | 0.609349 | 0.390651 |
| 128 | 1 | 0.622686 | 0.377314 |
| 129 | 1 | 0.412475 | 0.587525 |
| 130 | 1 | 0.730748 | 0.269252 |
| 131 | 1 | 0.792251 | 0.207749 |
| 132 | 1 | 0.846126 | 0.153874 |
| 133 | 1 | 1.03573 | -0.0357308 |
| 134 | 1 | 0.633873 | 0.366127 |
| 135 | 1 | 0.974722 | 0.0252776 |
| 136 | 1 | 0.945805 | 0.0541946 |
| 137 | 1 | 1.15434 | -0.154342 |
| 138 | 1 | 1.13068 | -0.130677 |
| 139 | 1 | 0.94951 | 0.0504895 |
| 140 | 1 | 0.771337 | 0.228663 |
| 141 | 1 | 0.888567 | 0.111433 |
| 142 | 1 | 0.840928 | 0.159072 |
| 143 | 1 | 0.723894 | 0.276106 |
| 144 | 1 | 0.697984 | 0.302016 |
| 145 | 1 | 0.547833 | 0.452167 |
| 146 | 1 | 0.874166 | 0.125834 |
| 147 | 1 | 1.36837 | -0.368368 |
| 148 | 1 | 1.14904 | -0.149039 |
| 149 | 1 | 1.20523 | -0.205234 |
| 150 | 1 | 0.874841 | 0.125159 |
| 151 | 1 | 0.946296 | 0.0537041 |
| 152 | 1 | 0.957064 | 0.0429361 |
| 153 | 1 | 0.903183 | 0.0968168 |
| 154 | 1 | 0.869914 | 0.130086 |
| 155 | 1 | 0.891486 | 0.108514 |
| 156 | 1 | 0.986354 | 0.013646 |
| 157 | 1 | 0.782298 | 0.217702 |
| 158 | 1 | 1.27236 | -0.272363 |
| 159 | 1 | 0.96157 | 0.03843 |
| 160 | 1 | 0.865991 | 0.134009 |
| 161 | 1 | 1.13908 | -0.139083 |
| 162 | 1 | 1.05207 | -0.0520697 |
| 163 | 1 | 0.948021 | 0.0519792 |
| 164 | 1 | 0.790378 | 0.209622 |
| 165 | 1 | 1.41476 | -0.414764 |
| 166 | 0 | 0.46071 | -0.46071 |
| 167 | 0 | 0.225599 | -0.225599 |
| 168 | 0 | 0.108001 | -0.108001 |
| 169 | 0 | 0.929984 | -0.929984 |
| 170 | 0 | 0.226851 | -0.226851 |
| 171 | 0 | 0.11335 | -0.11335 |
| 172 | 0 | 0.784201 | -0.784201 |
| 173 | 0 | 0.82241 | -0.82241 |
| 174 | 0 | 0.859406 | -0.859406 |
| 175 | 0 | 0.858 | -0.858 |
| 176 | 0 | 0.820521 | -0.820521 |
| 177 | 0 | 0.762932 | -0.762932 |
| 178 | 1 | 0.644063 | 0.355937 |
| 179 | 1 | 0.701982 | 0.298018 |
| 180 | 1 | 0.946503 | 0.0534972 |
| 181 | 1 | 0.780175 | 0.219825 |
| 182 | 1 | 0.883114 | 0.116886 |
| 183 | 1 | 0.709165 | 0.290835 |
| 184 | 0 | 0.60716 | -0.60716 |
| 185 | 0 | 0.654041 | -0.654041 |
| 186 | 0 | 0.596412 | -0.596412 |
| 187 | 0 | 0.428782 | -0.428782 |
| 188 | 0 | 0.458572 | -0.458572 |
| 189 | 0 | 0.424374 | -0.424374 |
| 190 | 0 | 0.404643 | -0.404643 |
| 191 | 0 | 0.657962 | -0.657962 |
| 192 | 0 | 0.713377 | -0.713377 |
| 193 | 0 | -0.189287 | 0.189287 |
| 194 | 0 | 0.273958 | -0.273958 |
| 195 | 0 | 0.545086 | -0.545086 |
| Goldfeld-Quandt test for Heteroskedasticity | |||
| p-values | Alternative Hypothesis | ||
| breakpoint index | greater | 2-sided | less |
| 25 | 6.34187e-48 | 1.26837e-47 | 1 |
| 26 | 1.96153e-69 | 3.92305e-69 | 1 |
| 27 | 2.97047e-79 | 5.94094e-79 | 1 |
| 28 | 3.21255e-93 | 6.4251e-93 | 1 |
| 29 | 7.14024e-110 | 1.42805e-109 | 1 |
| 30 | 9.14376e-126 | 1.82875e-125 | 1 |
| 31 | 0.000116123 | 0.000232247 | 0.999884 |
| 32 | 3.04286e-05 | 6.08572e-05 | 0.99997 |
| 33 | 7.54628e-06 | 1.50926e-05 | 0.999992 |
| 34 | 1.99562e-06 | 3.99125e-06 | 0.999998 |
| 35 | 5.70619e-07 | 1.14124e-06 | 0.999999 |
| 36 | 1.5393e-07 | 3.07859e-07 | 1 |
| 37 | 0.000174323 | 0.000348645 | 0.999826 |
| 38 | 9.81505e-05 | 0.000196301 | 0.999902 |
| 39 | 0.00044151 | 0.000883021 | 0.999558 |
| 40 | 0.000577583 | 0.00115517 | 0.999422 |
| 41 | 0.000638925 | 0.00127785 | 0.999361 |
| 42 | 0.000368738 | 0.000737477 | 0.999631 |
| 43 | 0.000327207 | 0.000654415 | 0.999673 |
| 44 | 0.000168679 | 0.000337358 | 0.999831 |
| 45 | 8.78419e-05 | 0.000175684 | 0.999912 |
| 46 | 4.08291e-05 | 8.16581e-05 | 0.999959 |
| 47 | 2.19698e-05 | 4.39396e-05 | 0.999978 |
| 48 | 2.40184e-05 | 4.80368e-05 | 0.999976 |
| 49 | 0.000115181 | 0.000230363 | 0.999885 |
| 50 | 8.95687e-05 | 0.000179137 | 0.99991 |
| 51 | 6.09298e-05 | 0.00012186 | 0.999939 |
| 52 | 4.12657e-05 | 8.25313e-05 | 0.999959 |
| 53 | 2.84817e-05 | 5.69633e-05 | 0.999972 |
| 54 | 3.14456e-05 | 6.28913e-05 | 0.999969 |
| 55 | 3.24672e-05 | 6.49345e-05 | 0.999968 |
| 56 | 3.96268e-05 | 7.92536e-05 | 0.99996 |
| 57 | 2.2127e-05 | 4.42539e-05 | 0.999978 |
| 58 | 1.53253e-05 | 3.06507e-05 | 0.999985 |
| 59 | 8.45358e-06 | 1.69072e-05 | 0.999992 |
| 60 | 4.52178e-06 | 9.04355e-06 | 0.999995 |
| 61 | 0.000241894 | 0.000483788 | 0.999758 |
| 62 | 0.000343716 | 0.000687433 | 0.999656 |
| 63 | 0.000565095 | 0.00113019 | 0.999435 |
| 64 | 0.00065513 | 0.00131026 | 0.999345 |
| 65 | 0.000569942 | 0.00113988 | 0.99943 |
| 66 | 0.000822559 | 0.00164512 | 0.999177 |
| 67 | 0.000621486 | 0.00124297 | 0.999379 |
| 68 | 0.00039679 | 0.000793579 | 0.999603 |
| 69 | 0.000528627 | 0.00105725 | 0.999471 |
| 70 | 0.000347453 | 0.000694905 | 0.999653 |
| 71 | 0.00021482 | 0.00042964 | 0.999785 |
| 72 | 0.000147226 | 0.000294452 | 0.999853 |
| 73 | 9.00305e-05 | 0.000180061 | 0.99991 |
| 74 | 0.000159196 | 0.000318392 | 0.999841 |
| 75 | 0.000170845 | 0.00034169 | 0.999829 |
| 76 | 0.000139657 | 0.000279314 | 0.99986 |
| 77 | 9.21594e-05 | 0.000184319 | 0.999908 |
| 78 | 7.07322e-05 | 0.000141464 | 0.999929 |
| 79 | 4.30886e-05 | 8.61771e-05 | 0.999957 |
| 80 | 3.37239e-05 | 6.74478e-05 | 0.999966 |
| 81 | 2.61668e-05 | 5.23336e-05 | 0.999974 |
| 82 | 1.56784e-05 | 3.13569e-05 | 0.999984 |
| 83 | 1.01674e-05 | 2.03348e-05 | 0.99999 |
| 84 | 6.95312e-06 | 1.39062e-05 | 0.999993 |
| 85 | 4.875e-06 | 9.75e-06 | 0.999995 |
| 86 | 6.86977e-06 | 1.37395e-05 | 0.999993 |
| 87 | 8.51978e-06 | 1.70396e-05 | 0.999991 |
| 88 | 5.35024e-06 | 1.07005e-05 | 0.999995 |
| 89 | 3.87256e-06 | 7.74511e-06 | 0.999996 |
| 90 | 4.30972e-06 | 8.61943e-06 | 0.999996 |
| 91 | 4.42581e-06 | 8.85163e-06 | 0.999996 |
| 92 | 6.11671e-06 | 1.22334e-05 | 0.999994 |
| 93 | 4.1713e-06 | 8.3426e-06 | 0.999996 |
| 94 | 2.69237e-06 | 5.38475e-06 | 0.999997 |
| 95 | 1.87101e-06 | 3.74202e-06 | 0.999998 |
| 96 | 1.32682e-06 | 2.65364e-06 | 0.999999 |
| 97 | 8.62464e-07 | 1.72493e-06 | 0.999999 |
| 98 | 4.82047e-07 | 9.64094e-07 | 1 |
| 99 | 2.81379e-07 | 5.62758e-07 | 1 |
| 100 | 1.71976e-07 | 3.43951e-07 | 1 |
| 101 | 1.29435e-07 | 2.5887e-07 | 1 |
| 102 | 1.08579e-07 | 2.17158e-07 | 1 |
| 103 | 8.9713e-08 | 1.79426e-07 | 1 |
| 104 | 1.21314e-07 | 2.42627e-07 | 1 |
| 105 | 2.16348e-07 | 4.32696e-07 | 1 |
| 106 | 3.80022e-07 | 7.60044e-07 | 1 |
| 107 | 1.02934e-06 | 2.05868e-06 | 0.999999 |
| 108 | 7.40439e-07 | 1.48088e-06 | 0.999999 |
| 109 | 1.88073e-06 | 3.76147e-06 | 0.999998 |
| 110 | 2.05092e-06 | 4.10184e-06 | 0.999998 |
| 111 | 1.22972e-06 | 2.45943e-06 | 0.999999 |
| 112 | 2.92687e-06 | 5.85374e-06 | 0.999997 |
| 113 | 2.66019e-06 | 5.32039e-06 | 0.999997 |
| 114 | 2.83767e-06 | 5.67533e-06 | 0.999997 |
| 115 | 2.94293e-06 | 5.88585e-06 | 0.999997 |
| 116 | 1.99119e-06 | 3.98238e-06 | 0.999998 |
| 117 | 2.9511e-06 | 5.9022e-06 | 0.999997 |
| 118 | 1.7526e-06 | 3.50521e-06 | 0.999998 |
| 119 | 1.13158e-06 | 2.26315e-06 | 0.999999 |
| 120 | 1.92724e-06 | 3.85447e-06 | 0.999998 |
| 121 | 5.89234e-06 | 1.17847e-05 | 0.999994 |
| 122 | 1.45314e-05 | 2.90628e-05 | 0.999985 |
| 123 | 8.91796e-06 | 1.78359e-05 | 0.999991 |
| 124 | 6.45344e-06 | 1.29069e-05 | 0.999994 |
| 125 | 5.98085e-06 | 1.19617e-05 | 0.999994 |
| 126 | 6.78617e-06 | 1.35723e-05 | 0.999993 |
| 127 | 1.27741e-05 | 2.55481e-05 | 0.999987 |
| 128 | 0.000161823 | 0.000323645 | 0.999838 |
| 129 | 0.000350703 | 0.000701405 | 0.999649 |
| 130 | 0.000686375 | 0.00137275 | 0.999314 |
| 131 | 0.000727576 | 0.00145515 | 0.999272 |
| 132 | 0.000540151 | 0.0010803 | 0.99946 |
| 133 | 0.000547854 | 0.00109571 | 0.999452 |
| 134 | 0.00253211 | 0.00506421 | 0.997468 |
| 135 | 0.0022302 | 0.0044604 | 0.99777 |
| 136 | 0.00217864 | 0.00435728 | 0.997821 |
| 137 | 0.0025809 | 0.0051618 | 0.997419 |
| 138 | 0.00235557 | 0.00471113 | 0.997644 |
| 139 | 0.0016264 | 0.00325281 | 0.998374 |
| 140 | 0.00183262 | 0.00366524 | 0.998167 |
| 141 | 0.00137385 | 0.00274771 | 0.998626 |
| 142 | 0.00192619 | 0.00385238 | 0.998074 |
| 143 | 0.00147989 | 0.00295979 | 0.99852 |
| 144 | 0.00618976 | 0.0123795 | 0.99381 |
| 145 | 0.00530096 | 0.0106019 | 0.994699 |
| 146 | 0.00444486 | 0.00888971 | 0.995555 |
| 147 | 0.00329217 | 0.00658434 | 0.996708 |
| 148 | 0.00212662 | 0.00425324 | 0.997873 |
| 149 | 0.00166162 | 0.00332324 | 0.998338 |
| 150 | 0.00122149 | 0.00244298 | 0.998779 |
| 151 | 0.00165809 | 0.00331618 | 0.998342 |
| 152 | 0.0120001 | 0.0240002 | 0.988 |
| 153 | 0.0494342 | 0.0988685 | 0.950566 |
| 154 | 0.0524753 | 0.104951 | 0.947525 |
| 155 | 0.0455026 | 0.0910052 | 0.954497 |
| 156 | 0.0341488 | 0.0682976 | 0.965851 |
| 157 | 0.126246 | 0.252492 | 0.873754 |
| 158 | 0.115874 | 0.231748 | 0.884126 |
| 159 | 0.376575 | 0.753151 | 0.623425 |
| 160 | 0.311 | 0.622 | 0.689 |
| 161 | 0.247306 | 0.494612 | 0.752694 |
| 162 | 0.191257 | 0.382515 | 0.808743 |
| 163 | 0.197715 | 0.395431 | 0.802285 |
| 164 | 0.209276 | 0.418551 | 0.790724 |
| 165 | 0.542708 | 0.914584 | 0.457292 |
| 166 | 0.628927 | 0.742146 | 0.371073 |
| 167 | 0.924099 | 0.151802 | 0.075901 |
| 168 | 0.976253 | 0.0474931 | 0.0237466 |
| 169 | 0.990715 | 0.0185694 | 0.00928468 |
| 170 | 0.963942 | 0.0721162 | 0.0360581 |
| Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
| Description | # significant tests | % significant tests | OK/NOK |
| 1% type I error level | 125 | 0.856164 | NOK |
| 5% type I error level | 130 | 0.890411 | NOK |
| 10% type I error level | 134 | 0.917808 | NOK |
