| Multiple Linear Regression - Estimated Regression Equation |
| status[t] = + 2.26989 -0.00228582`MDVP:Fo(Hz)`[t] -9.95995e-05`MDVP:Fhi(Hz)`[t] -0.00155827`MDVP:Flo(Hz)`[t] -180.732`MDVP:Jitter(%)`[t] -2631.75`MDVP:Jitter(Abs)`[t] -406.789`MDVP:RAP`[t] -35.1555`MDVP:PPQ`[t] + 242.622`Jitter:DDP`[t] + 21.1817`MDVP:Shimmer`[t] + 0.544875`MDVP:Shimmer(dB)`[t] -673.934`Shimmer:APQ3`[t] -26.0271`Shimmer:APQ5`[t] + 220.359`Shimmer:DDA`[t] -2.58626NHR[t] -0.0160167HNR[t] -1.043RPDE[t] + 0.350495DFA[t] + 0.131831spread1[t] + 1.26673spread2[t] + 0.051304D2[t] + 1.1795PPE[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) | 2.26989 | 1.14425 | 1.984 | 0.0488676 | 0.0244338 |
| `MDVP:Fo(Hz)` | -0.00228582 | 0.00146521 | -1.56 | 0.120573 | 0.0602865 |
| `MDVP:Fhi(Hz)` | -9.95995e-05 | 0.000315406 | -0.3158 | 0.752549 | 0.376274 |
| `MDVP:Flo(Hz)` | -0.00155827 | 0.000795983 | -1.958 | 0.0518779 | 0.0259389 |
| `MDVP:Jitter(%)` | -180.732 | 65.4751 | -2.76 | 0.00639725 | 0.00319862 |
| `MDVP:Jitter(Abs)` | -2631.75 | 3917.04 | -0.6719 | 0.502562 | 0.251281 |
| `MDVP:RAP` | -406.789 | 9223.38 | -0.0441 | 0.964872 | 0.482436 |
| `MDVP:PPQ` | -35.1555 | 88.0805 | -0.3991 | 0.69029 | 0.345145 |
| `Jitter:DDP` | 242.622 | 3075.08 | 0.0789 | 0.937204 | 0.468602 |
| `MDVP:Shimmer` | 21.1817 | 26.0537 | 0.813 | 0.417334 | 0.208667 |
| `MDVP:Shimmer(dB)` | 0.544875 | 1.19255 | 0.4569 | 0.648317 | 0.324158 |
| `Shimmer:APQ3` | -673.934 | 8921.09 | -0.07554 | 0.939869 | 0.469935 |
| `Shimmer:APQ5` | -26.0271 | 20.027 | -1.3 | 0.195468 | 0.0977339 |
| `Shimmer:DDA` | 220.359 | 2973.57 | 0.07411 | 0.941012 | 0.470506 |
| NHR | -2.58626 | 1.96369 | -1.317 | 0.189567 | 0.0947834 |
| HNR | -0.0160167 | 0.014259 | -1.123 | 0.26288 | 0.13144 |
| RPDE | -1.043 | 0.42662 | -2.445 | 0.0154958 | 0.00774791 |
| DFA | 0.350495 | 0.73723 | 0.4754 | 0.635087 | 0.317543 |
| spread1 | 0.131831 | 0.0963158 | 1.369 | 0.172857 | 0.0864284 |
| spread2 | 1.26673 | 0.476715 | 2.657 | 0.00861664 | 0.00430832 |
| D2 | 0.051304 | 0.113833 | 0.4507 | 0.652774 | 0.326387 |
| PPE | 1.1795 | 1.34741 | 0.8754 | 0.382579 | 0.191289 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.701789 |
| R-squared | 0.492508 |
| Adjusted R-squared | 0.430905 |
| F-TEST (value) | 7.99488 |
| F-TEST (DF numerator) | 21 |
| F-TEST (DF denominator) | 173 |
| p-value | 2.22045e-16 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 0.325802 |
| Sum Squared Residuals | 18.3634 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 1 | 0.929874 | 0.0701259 |
| 2 | 1 | 1.05145 | -0.0514529 |
| 3 | 1 | 0.963728 | 0.036272 |
| 4 | 1 | 1.07253 | -0.0725333 |
| 5 | 1 | 0.868484 | 0.131516 |
| 6 | 1 | 0.929332 | 0.0706677 |
| 7 | 1 | 0.783954 | 0.216046 |
| 8 | 1 | 0.577447 | 0.422553 |
| 9 | 1 | 0.977223 | 0.0227767 |
| 10 | 1 | 1.1583 | -0.158303 |
| 11 | 1 | 1.1179 | -0.117903 |
| 12 | 1 | 1.23935 | -0.23935 |
| 13 | 1 | 0.456655 | 0.543345 |
| 14 | 1 | 0.886425 | 0.113575 |
| 15 | 1 | 0.703867 | 0.296133 |
| 16 | 1 | 0.704829 | 0.295171 |
| 17 | 1 | 0.552444 | 0.447556 |
| 18 | 1 | 1.31092 | -0.31092 |
| 19 | 1 | 1.29351 | -0.293513 |
| 20 | 1 | 0.962561 | 0.0374388 |
| 21 | 1 | 1.05841 | -0.0584071 |
| 22 | 1 | 0.908923 | 0.091077 |
| 23 | 1 | 1.11711 | -0.117111 |
| 24 | 1 | 0.87281 | 0.12719 |
| 25 | 1 | 0.81968 | 0.18032 |
| 26 | 1 | 0.926559 | 0.0734407 |
| 27 | 1 | 0.80763 | 0.19237 |
| 28 | 1 | 0.795977 | 0.204023 |
| 29 | 1 | 0.66156 | 0.33844 |
| 30 | 1 | 0.69687 | 0.30313 |
| 31 | 0 | 0.289299 | -0.289299 |
| 32 | 0 | 0.152816 | -0.152816 |
| 33 | 0 | 0.18703 | -0.18703 |
| 34 | 0 | 0.126757 | -0.126757 |
| 35 | 0 | 0.085403 | -0.085403 |
| 36 | 0 | 0.204882 | -0.204882 |
| 37 | 1 | 0.807693 | 0.192307 |
| 38 | 1 | 0.820868 | 0.179132 |
| 39 | 1 | 0.598115 | 0.401885 |
| 40 | 1 | 0.753451 | 0.246549 |
| 41 | 1 | 0.617439 | 0.382561 |
| 42 | 1 | 0.43519 | 0.56481 |
| 43 | 0 | 0.249542 | -0.249542 |
| 44 | 0 | 0.208592 | -0.208592 |
| 45 | 0 | 0.0187574 | -0.0187574 |
| 46 | 0 | 0.0926867 | -0.0926867 |
| 47 | 0 | 0.0557239 | -0.0557239 |
| 48 | 0 | -0.0451516 | 0.0451516 |
| 49 | 0 | 0.339306 | -0.339306 |
| 50 | 0 | 0.429267 | -0.429267 |
| 51 | 0 | 0.410919 | -0.410919 |
| 52 | 0 | 0.4349 | -0.4349 |
| 53 | 0 | 0.409618 | -0.409618 |
| 54 | 0 | 0.552403 | -0.552403 |
| 55 | 1 | 0.830103 | 0.169897 |
| 56 | 1 | 0.798474 | 0.201526 |
| 57 | 1 | 0.867592 | 0.132408 |
| 58 | 1 | 0.757826 | 0.242174 |
| 59 | 1 | 0.779329 | 0.220671 |
| 60 | 1 | 0.661596 | 0.338404 |
| 61 | 0 | 0.369094 | -0.369094 |
| 62 | 0 | 0.273413 | -0.273413 |
| 63 | 0 | 0.262433 | -0.262433 |
| 64 | 0 | 0.213676 | -0.213676 |
| 65 | 0 | 0.130883 | -0.130883 |
| 66 | 0 | 0.286705 | -0.286705 |
| 67 | 1 | 0.924403 | 0.0755974 |
| 68 | 1 | 0.896224 | 0.103776 |
| 69 | 1 | 0.914048 | 0.0859518 |
| 70 | 1 | 0.952344 | 0.0476561 |
| 71 | 1 | 0.858203 | 0.141797 |
| 72 | 1 | 1.09182 | -0.0918238 |
| 73 | 1 | 0.888662 | 0.111338 |
| 74 | 1 | 0.935489 | 0.0645111 |
| 75 | 1 | 1.04581 | -0.0458091 |
| 76 | 1 | 1.08736 | -0.0873647 |
| 77 | 1 | 1.10242 | -0.102416 |
| 78 | 1 | 1.0049 | -0.00489805 |
| 79 | 1 | 0.964035 | 0.0359646 |
| 80 | 1 | 1.1474 | -0.147398 |
| 81 | 1 | 1.18134 | -0.181339 |
| 82 | 1 | 1.13703 | -0.137028 |
| 83 | 1 | 1.01609 | -0.0160901 |
| 84 | 1 | 0.692374 | 0.307626 |
| 85 | 1 | 1.08179 | -0.0817867 |
| 86 | 1 | 0.867243 | 0.132757 |
| 87 | 1 | 0.703127 | 0.296873 |
| 88 | 1 | 0.939603 | 0.0603968 |
| 89 | 1 | 0.989259 | 0.0107407 |
| 90 | 1 | 1.21719 | -0.217189 |
| 91 | 1 | 1.13661 | -0.136606 |
| 92 | 1 | 0.790102 | 0.209898 |
| 93 | 1 | 0.732852 | 0.267148 |
| 94 | 1 | 0.856683 | 0.143317 |
| 95 | 1 | 0.788152 | 0.211848 |
| 96 | 1 | 0.75901 | 0.24099 |
| 97 | 1 | 0.806749 | 0.193251 |
| 98 | 1 | 1.02991 | -0.0299144 |
| 99 | 1 | 0.810621 | 0.189379 |
| 100 | 1 | 0.90978 | 0.0902201 |
| 101 | 1 | 0.961919 | 0.038081 |
| 102 | 1 | 0.9739 | 0.0260996 |
| 103 | 1 | 0.978532 | 0.0214677 |
| 104 | 1 | 0.589158 | 0.410842 |
| 105 | 1 | 0.578945 | 0.421055 |
| 106 | 1 | 0.56436 | 0.43564 |
| 107 | 1 | 0.534642 | 0.465358 |
| 108 | 1 | 0.687627 | 0.312373 |
| 109 | 1 | 0.618443 | 0.381557 |
| 110 | 1 | 0.89597 | 0.10403 |
| 111 | 1 | 1.03388 | -0.0338821 |
| 112 | 1 | 0.590284 | 0.409716 |
| 113 | 1 | 0.790041 | 0.209959 |
| 114 | 1 | 0.69619 | 0.30381 |
| 115 | 1 | 0.804405 | 0.195595 |
| 116 | 1 | 0.87073 | 0.12927 |
| 117 | 1 | 0.725477 | 0.274523 |
| 118 | 1 | 1.04994 | -0.0499362 |
| 119 | 1 | 0.891034 | 0.108966 |
| 120 | 1 | 0.763954 | 0.236046 |
| 121 | 1 | 0.550354 | 0.449646 |
| 122 | 1 | 0.976276 | 0.0237243 |
| 123 | 1 | 0.973585 | 0.0264153 |
| 124 | 1 | 0.710271 | 0.289729 |
| 125 | 1 | 0.609464 | 0.390536 |
| 126 | 1 | 0.619047 | 0.380953 |
| 127 | 1 | 0.610644 | 0.389356 |
| 128 | 1 | 0.627741 | 0.372259 |
| 129 | 1 | 0.417827 | 0.582173 |
| 130 | 1 | 0.756971 | 0.243029 |
| 131 | 1 | 0.800737 | 0.199263 |
| 132 | 1 | 0.869074 | 0.130926 |
| 133 | 1 | 1.05 | -0.0499955 |
| 134 | 1 | 0.6441 | 0.3559 |
| 135 | 1 | 0.961571 | 0.0384285 |
| 136 | 1 | 0.960565 | 0.039435 |
| 137 | 1 | 1.14409 | -0.144093 |
| 138 | 1 | 1.14776 | -0.147757 |
| 139 | 1 | 0.957422 | 0.0425783 |
| 140 | 1 | 0.78158 | 0.21842 |
| 141 | 1 | 0.907265 | 0.0927353 |
| 142 | 1 | 0.857399 | 0.142601 |
| 143 | 1 | 0.73037 | 0.26963 |
| 144 | 1 | 0.68519 | 0.31481 |
| 145 | 1 | 0.548931 | 0.451069 |
| 146 | 1 | 0.863145 | 0.136855 |
| 147 | 1 | 1.36807 | -0.368069 |
| 148 | 1 | 1.16406 | -0.164056 |
| 149 | 1 | 1.23865 | -0.238648 |
| 150 | 1 | 0.882646 | 0.117354 |
| 151 | 1 | 0.935772 | 0.0642282 |
| 152 | 1 | 0.991711 | 0.00828863 |
| 153 | 1 | 0.942801 | 0.0571992 |
| 154 | 1 | 0.853795 | 0.146205 |
| 155 | 1 | 0.89616 | 0.10384 |
| 156 | 1 | 0.999641 | 0.000359222 |
| 157 | 1 | 0.793655 | 0.206345 |
| 158 | 1 | 1.24939 | -0.249391 |
| 159 | 1 | 0.968919 | 0.0310807 |
| 160 | 1 | 0.849081 | 0.150919 |
| 161 | 1 | 1.11266 | -0.112661 |
| 162 | 1 | 1.05531 | -0.0553105 |
| 163 | 1 | 0.929621 | 0.0703789 |
| 164 | 1 | 0.796966 | 0.203034 |
| 165 | 1 | 1.39127 | -0.391266 |
| 166 | 0 | 0.450542 | -0.450542 |
| 167 | 0 | 0.226515 | -0.226515 |
| 168 | 0 | 0.0946885 | -0.0946885 |
| 169 | 0 | 0.942813 | -0.942813 |
| 170 | 0 | 0.22816 | -0.22816 |
| 171 | 0 | 0.110566 | -0.110566 |
| 172 | 0 | 0.795482 | -0.795482 |
| 173 | 0 | 0.837427 | -0.837427 |
| 174 | 0 | 0.873888 | -0.873888 |
| 175 | 0 | 0.868673 | -0.868673 |
| 176 | 0 | 0.834202 | -0.834202 |
| 177 | 0 | 0.773645 | -0.773645 |
| 178 | 1 | 0.643405 | 0.356595 |
| 179 | 1 | 0.712601 | 0.287399 |
| 180 | 1 | 0.938348 | 0.0616521 |
| 181 | 1 | 0.768694 | 0.231306 |
| 182 | 1 | 0.878618 | 0.121382 |
| 183 | 1 | 0.721349 | 0.278651 |
| 184 | 0 | 0.606111 | -0.606111 |
| 185 | 0 | 0.649436 | -0.649436 |
| 186 | 0 | 0.605216 | -0.605216 |
| 187 | 0 | 0.431545 | -0.431545 |
| 188 | 0 | 0.478384 | -0.478384 |
| 189 | 0 | 0.433077 | -0.433077 |
| 190 | 0 | 0.420774 | -0.420774 |
| 191 | 0 | 0.649552 | -0.649552 |
| 192 | 0 | 0.703965 | -0.703965 |
| 193 | 0 | -0.17985 | 0.17985 |
| 194 | 0 | 0.266482 | -0.266482 |
| 195 | 0 | 0.523138 | -0.523138 |
| Goldfeld-Quandt test for Heteroskedasticity | |||
| p-values | Alternative Hypothesis | ||
| breakpoint index | greater | 2-sided | less |
| 25 | 2.54259e-49 | 5.08517e-49 | 1 |
| 26 | 3.20097e-70 | 6.40193e-70 | 1 |
| 27 | 3.24307e-80 | 6.48614e-80 | 1 |
| 28 | 7.67856e-92 | 1.53571e-91 | 1 |
| 29 | 8.3637e-110 | 1.67274e-109 | 1 |
| 30 | 3.06533e-121 | 6.13066e-121 | 1 |
| 31 | 0.000331277 | 0.000662554 | 0.999669 |
| 32 | 9.47603e-05 | 0.000189521 | 0.999905 |
| 33 | 2.7619e-05 | 5.52381e-05 | 0.999972 |
| 34 | 7.24999e-06 | 1.45e-05 | 0.999993 |
| 35 | 2.31883e-06 | 4.63766e-06 | 0.999998 |
| 36 | 6.51016e-07 | 1.30203e-06 | 0.999999 |
| 37 | 4.26307e-05 | 8.52613e-05 | 0.999957 |
| 38 | 3.29666e-05 | 6.59332e-05 | 0.999967 |
| 39 | 0.000538163 | 0.00107633 | 0.999462 |
| 40 | 0.000738298 | 0.0014766 | 0.999262 |
| 41 | 0.000894507 | 0.00178901 | 0.999105 |
| 42 | 0.000558109 | 0.00111622 | 0.999442 |
| 43 | 0.000330434 | 0.000660868 | 0.99967 |
| 44 | 0.000188929 | 0.000377858 | 0.999811 |
| 45 | 9.03929e-05 | 0.000180786 | 0.99991 |
| 46 | 4.60125e-05 | 9.2025e-05 | 0.999954 |
| 47 | 2.88034e-05 | 5.76067e-05 | 0.999971 |
| 48 | 3.68478e-05 | 7.36957e-05 | 0.999963 |
| 49 | 0.000195993 | 0.000391985 | 0.999804 |
| 50 | 0.000155318 | 0.000310635 | 0.999845 |
| 51 | 0.000104049 | 0.000208099 | 0.999896 |
| 52 | 7.09077e-05 | 0.000141815 | 0.999929 |
| 53 | 5.33351e-05 | 0.00010667 | 0.999947 |
| 54 | 5.52967e-05 | 0.000110593 | 0.999945 |
| 55 | 4.33326e-05 | 8.66653e-05 | 0.999957 |
| 56 | 4.39826e-05 | 8.79652e-05 | 0.999956 |
| 57 | 2.46857e-05 | 4.93714e-05 | 0.999975 |
| 58 | 1.58546e-05 | 3.17092e-05 | 0.999984 |
| 59 | 8.85462e-06 | 1.77092e-05 | 0.999991 |
| 60 | 5.04577e-06 | 1.00915e-05 | 0.999995 |
| 61 | 0.00025084 | 0.00050168 | 0.999749 |
| 62 | 0.000382314 | 0.000764628 | 0.999618 |
| 63 | 0.000626025 | 0.00125205 | 0.999374 |
| 64 | 0.000744392 | 0.00148878 | 0.999256 |
| 65 | 0.000532796 | 0.00106559 | 0.999467 |
| 66 | 0.000534793 | 0.00106959 | 0.999465 |
| 67 | 0.000411799 | 0.000823598 | 0.999588 |
| 68 | 0.000264196 | 0.000528392 | 0.999736 |
| 69 | 0.000206695 | 0.00041339 | 0.999793 |
| 70 | 0.000149906 | 0.000299811 | 0.99985 |
| 71 | 9.28655e-05 | 0.000185731 | 0.999907 |
| 72 | 6.39284e-05 | 0.000127857 | 0.999936 |
| 73 | 3.71269e-05 | 7.42538e-05 | 0.999963 |
| 74 | 0.000129627 | 0.000259253 | 0.99987 |
| 75 | 0.000158375 | 0.000316749 | 0.999842 |
| 76 | 0.000109236 | 0.000218472 | 0.999891 |
| 77 | 6.97406e-05 | 0.000139481 | 0.99993 |
| 78 | 5.09313e-05 | 0.000101863 | 0.999949 |
| 79 | 3.0633e-05 | 6.1266e-05 | 0.999969 |
| 80 | 2.22896e-05 | 4.45791e-05 | 0.999978 |
| 81 | 1.81655e-05 | 3.6331e-05 | 0.999982 |
| 82 | 1.0911e-05 | 2.18221e-05 | 0.999989 |
| 83 | 7.68715e-06 | 1.53743e-05 | 0.999992 |
| 84 | 5.02656e-06 | 1.00531e-05 | 0.999995 |
| 85 | 3.62436e-06 | 7.24872e-06 | 0.999996 |
| 86 | 3.7413e-06 | 7.48261e-06 | 0.999996 |
| 87 | 6.09989e-06 | 1.21998e-05 | 0.999994 |
| 88 | 3.89171e-06 | 7.78342e-06 | 0.999996 |
| 89 | 2.91397e-06 | 5.82795e-06 | 0.999997 |
| 90 | 3.10547e-06 | 6.21095e-06 | 0.999997 |
| 91 | 2.86183e-06 | 5.72366e-06 | 0.999997 |
| 92 | 3.33499e-06 | 6.66997e-06 | 0.999997 |
| 93 | 2.13784e-06 | 4.27568e-06 | 0.999998 |
| 94 | 1.43711e-06 | 2.87422e-06 | 0.999999 |
| 95 | 9.09806e-07 | 1.81961e-06 | 0.999999 |
| 96 | 5.75937e-07 | 1.15187e-06 | 0.999999 |
| 97 | 3.68113e-07 | 7.36226e-07 | 1 |
| 98 | 2.13779e-07 | 4.27558e-07 | 1 |
| 99 | 1.47381e-07 | 2.94762e-07 | 1 |
| 100 | 8.48497e-08 | 1.69699e-07 | 1 |
| 101 | 6.18401e-08 | 1.2368e-07 | 1 |
| 102 | 5.59037e-08 | 1.11807e-07 | 1 |
| 103 | 6.76053e-08 | 1.35211e-07 | 1 |
| 104 | 1.3364e-07 | 2.67281e-07 | 1 |
| 105 | 2.01506e-07 | 4.03012e-07 | 1 |
| 106 | 3.42743e-07 | 6.85486e-07 | 1 |
| 107 | 7.95165e-07 | 1.59033e-06 | 0.999999 |
| 108 | 5.58514e-07 | 1.11703e-06 | 0.999999 |
| 109 | 1.23607e-06 | 2.47213e-06 | 0.999999 |
| 110 | 1.03076e-06 | 2.06151e-06 | 0.999999 |
| 111 | 6.03889e-07 | 1.20778e-06 | 0.999999 |
| 112 | 1.26527e-06 | 2.53055e-06 | 0.999999 |
| 113 | 7.78069e-07 | 1.55614e-06 | 0.999999 |
| 114 | 8.47946e-07 | 1.69589e-06 | 0.999999 |
| 115 | 8.39088e-07 | 1.67818e-06 | 0.999999 |
| 116 | 4.96846e-07 | 9.93692e-07 | 1 |
| 117 | 6.1711e-07 | 1.23422e-06 | 0.999999 |
| 118 | 3.50833e-07 | 7.01665e-07 | 1 |
| 119 | 2.47941e-07 | 4.95882e-07 | 1 |
| 120 | 6.22759e-07 | 1.24552e-06 | 0.999999 |
| 121 | 3.22371e-06 | 6.44742e-06 | 0.999997 |
| 122 | 8.05682e-06 | 1.61136e-05 | 0.999992 |
| 123 | 5.47198e-06 | 1.0944e-05 | 0.999995 |
| 124 | 3.85709e-06 | 7.71418e-06 | 0.999996 |
| 125 | 2.66657e-06 | 5.33313e-06 | 0.999997 |
| 126 | 2.7103e-06 | 5.4206e-06 | 0.999997 |
| 127 | 4.72053e-06 | 9.44107e-06 | 0.999995 |
| 128 | 5.73339e-05 | 0.000114668 | 0.999943 |
| 129 | 0.000197139 | 0.000394278 | 0.999803 |
| 130 | 0.000207899 | 0.000415799 | 0.999792 |
| 131 | 0.000201761 | 0.000403523 | 0.999798 |
| 132 | 0.000133507 | 0.000267013 | 0.999866 |
| 133 | 0.000111246 | 0.000222492 | 0.999889 |
| 134 | 0.000420296 | 0.000840592 | 0.99958 |
| 135 | 0.000331848 | 0.000663696 | 0.999668 |
| 136 | 0.000343124 | 0.000686248 | 0.999657 |
| 137 | 0.000437825 | 0.00087565 | 0.999562 |
| 138 | 0.000802004 | 0.00160401 | 0.999198 |
| 139 | 0.000670137 | 0.00134027 | 0.99933 |
| 140 | 0.000889584 | 0.00177917 | 0.99911 |
| 141 | 0.000737848 | 0.0014757 | 0.999262 |
| 142 | 0.000963003 | 0.00192601 | 0.999037 |
| 143 | 0.000792252 | 0.0015845 | 0.999208 |
| 144 | 0.00270296 | 0.00540592 | 0.997297 |
| 145 | 0.00235484 | 0.00470968 | 0.997645 |
| 146 | 0.00186325 | 0.00372651 | 0.998137 |
| 147 | 0.00137699 | 0.00275398 | 0.998623 |
| 148 | 0.000934329 | 0.00186866 | 0.999066 |
| 149 | 0.00177876 | 0.00355752 | 0.998221 |
| 150 | 0.00118949 | 0.00237899 | 0.998811 |
| 151 | 0.00101276 | 0.00202551 | 0.998987 |
| 152 | 0.00101103 | 0.00202206 | 0.998989 |
| 153 | 0.022559 | 0.0451181 | 0.977441 |
| 154 | 0.0289795 | 0.0579591 | 0.97102 |
| 155 | 0.0308511 | 0.0617023 | 0.969149 |
| 156 | 0.0235581 | 0.0471163 | 0.976442 |
| 157 | 0.106348 | 0.212695 | 0.893652 |
| 158 | 0.108646 | 0.217293 | 0.891354 |
| 159 | 0.346034 | 0.692068 | 0.653966 |
| 160 | 0.280628 | 0.561257 | 0.719372 |
| 161 | 0.216829 | 0.433658 | 0.783171 |
| 162 | 0.167785 | 0.335569 | 0.832215 |
| 163 | 0.19117 | 0.38234 | 0.80883 |
| 164 | 0.378336 | 0.756673 | 0.621664 |
| 165 | 0.502062 | 0.995876 | 0.497938 |
| 166 | 0.620964 | 0.758073 | 0.379036 |
| 167 | 0.926357 | 0.147287 | 0.0736433 |
| 168 | 0.90656 | 0.186881 | 0.0934405 |
| 169 | 0.955113 | 0.0897731 | 0.0448866 |
| 170 | 0.915108 | 0.169784 | 0.0848918 |
| Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity | |||
| Description | # significant tests | % significant tests | OK/NOK |
| 1% type I error level | 128 | 0.876712 | NOK |
| 5% type I error level | 130 | 0.890411 | NOK |
| 10% type I error level | 133 | 0.910959 | NOK |
