Free Statistics

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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 11 Dec 2013 11:39:47 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/11/t1386780105tnpy8xlwhie9ro0.htm/, Retrieved Thu, 28 Mar 2024 15:08:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232101, Retrieved Thu, 28 Mar 2024 15:08:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2010-12-05 17:44:33] [b98453cac15ba1066b407e146608df68]
- RMPD    [Multiple Regression] [WS 10 multiple re...] [2013-12-11 16:39:47] [04383c33d6dbded00041500085efb365] [Current]
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Dataseries X:
1 119.992 157.302 74.997 0.00784 0.0037 0.00554 0.01109 0.04374 0.426 0.02182 0.0313 0.02971 0.06545 0.02211 21.033 0.414783 0.815285 -4.813031 0.266482 2.301442 0.284654
1 122.4 148.65 113.819 0.00968 0.00465 0.00696 0.01394 0.06134 0.626 0.03134 0.04518 0.04368 0.09403 0.01929 19.085 0.458359 0.819521 -4.075192 0.33559 2.486855 0.368674
1 116.682 131.111 111.555 0.0105 0.00544 0.00781 0.01633 0.05233 0.482 0.02757 0.03858 0.0359 0.0827 0.01309 20.651 0.429895 0.825288 -4.443179 0.311173 2.342259 0.332634
1 116.676 137.871 111.366 0.00997 0.00502 0.00698 0.01505 0.05492 0.517 0.02924 0.04005 0.03772 0.08771 0.01353 20.644 0.434969 0.819235 -4.117501 0.334147 2.405554 0.368975
1 116.014 141.781 110.655 0.01284 0.00655 0.00908 0.01966 0.06425 0.584 0.0349 0.04825 0.04465 0.1047 0.01767 19.649 0.417356 0.823484 -3.747787 0.234513 2.33218 0.410335
1 120.552 131.162 113.787 0.00968 0.00463 0.0075 0.01388 0.04701 0.456 0.02328 0.03526 0.03243 0.06985 0.01222 21.378 0.415564 0.825069 -4.242867 0.299111 2.18756 0.357775
1 120.267 137.244 114.82 0.00333 0.00155 0.00202 0.00466 0.01608 0.14 0.00779 0.00937 0.01351 0.02337 0.00607 24.886 0.59604 0.764112 -5.634322 0.257682 1.854785 0.211756
1 107.332 113.84 104.315 0.0029 0.00144 0.00182 0.00431 0.01567 0.134 0.00829 0.00946 0.01256 0.02487 0.00344 26.892 0.63742 0.763262 -6.167603 0.183721 2.064693 0.163755
1 95.73 132.068 91.754 0.00551 0.00293 0.00332 0.0088 0.02093 0.191 0.01073 0.01277 0.01717 0.03218 0.0107 21.812 0.615551 0.773587 -5.498678 0.327769 2.322511 0.231571
1 95.056 120.103 91.226 0.00532 0.00268 0.00332 0.00803 0.02838 0.255 0.01441 0.01725 0.02444 0.04324 0.01022 21.862 0.547037 0.798463 -5.011879 0.325996 2.432792 0.271362
1 88.333 112.24 84.072 0.00505 0.00254 0.0033 0.00763 0.02143 0.197 0.01079 0.01342 0.01892 0.03237 0.01166 21.118 0.611137 0.776156 -5.24977 0.391002 2.407313 0.24974
1 91.904 115.871 86.292 0.0054 0.00281 0.00336 0.00844 0.02752 0.249 0.01424 0.01641 0.02214 0.04272 0.01141 21.414 0.58339 0.79252 -4.960234 0.363566 2.642476 0.275931
1 136.926 159.866 131.276 0.00293 0.00118 0.00153 0.00355 0.01259 0.112 0.00656 0.00717 0.0114 0.01968 0.00581 25.703 0.4606 0.646846 -6.547148 0.152813 2.041277 0.138512
1 139.173 179.139 76.556 0.0039 0.00165 0.00208 0.00496 0.01642 0.154 0.00728 0.00932 0.01797 0.02184 0.01041 24.889 0.430166 0.665833 -5.660217 0.254989 2.519422 0.199889
1 152.845 163.305 75.836 0.00294 0.00121 0.00149 0.00364 0.01828 0.158 0.01064 0.00972 0.01246 0.03191 0.00609 24.922 0.474791 0.654027 -6.105098 0.203653 2.125618 0.1701
1 142.167 217.455 83.159 0.00369 0.00157 0.00203 0.00471 0.01503 0.126 0.00772 0.00888 0.01359 0.02316 0.00839 25.175 0.565924 0.658245 -5.340115 0.210185 2.205546 0.234589
1 144.188 349.259 82.764 0.00544 0.00211 0.00292 0.00632 0.02047 0.192 0.00969 0.012 0.02074 0.02908 0.01859 22.333 0.56738 0.644692 -5.44004 0.239764 2.264501 0.218164
1 168.778 232.181 75.603 0.00718 0.00284 0.00387 0.00853 0.03327 0.348 0.01441 0.01893 0.0343 0.04322 0.02919 20.376 0.631099 0.605417 -2.93107 0.434326 3.007463 0.430788
1 153.046 175.829 68.623 0.00742 0.00364 0.00432 0.01092 0.05517 0.542 0.02471 0.03572 0.05767 0.07413 0.0316 17.28 0.665318 0.719467 -3.949079 0.35787 3.10901 0.377429
1 156.405 189.398 142.822 0.00768 0.00372 0.00399 0.01116 0.03995 0.348 0.01721 0.02374 0.0431 0.05164 0.03365 17.153 0.649554 0.68608 -4.554466 0.340176 2.856676 0.322111
1 153.848 165.738 65.782 0.0084 0.00428 0.0045 0.01285 0.0381 0.328 0.01667 0.02383 0.04055 0.05 0.03871 17.536 0.660125 0.704087 -4.095442 0.262564 2.73971 0.365391
1 153.88 172.86 78.128 0.0048 0.00232 0.00267 0.00696 0.04137 0.37 0.02021 0.02591 0.04525 0.06062 0.01849 19.493 0.629017 0.698951 -5.18696 0.237622 2.557536 0.259765
1 167.93 193.221 79.068 0.00442 0.0022 0.00247 0.00661 0.04351 0.377 0.02228 0.0254 0.04246 0.06685 0.0128 22.468 0.61906 0.679834 -4.330956 0.262384 2.916777 0.285695
1 173.917 192.735 86.18 0.00476 0.00221 0.00258 0.00663 0.04192 0.364 0.02187 0.0247 0.03772 0.06562 0.0184 20.422 0.537264 0.686894 -5.248776 0.210279 2.547508 0.253556
1 163.656 200.841 76.779 0.00742 0.0038 0.0039 0.0114 0.01659 0.164 0.00738 0.00948 0.01497 0.02214 0.01778 23.831 0.397937 0.732479 -5.557447 0.22089 2.692176 0.215961
1 104.4 206.002 77.968 0.00633 0.00316 0.00375 0.00948 0.03767 0.381 0.01732 0.02245 0.0378 0.05197 0.02887 22.066 0.522746 0.737948 -5.571843 0.236853 2.846369 0.219514
1 171.041 208.313 75.501 0.00455 0.0025 0.00234 0.0075 0.01966 0.186 0.00889 0.01169 0.01872 0.02666 0.01095 25.908 0.418622 0.720916 -6.18359 0.226278 2.589702 0.147403
1 146.845 208.701 81.737 0.00496 0.0025 0.00275 0.00749 0.01919 0.198 0.00883 0.01144 0.01826 0.0265 0.01328 25.119 0.358773 0.726652 -6.27169 0.196102 2.314209 0.162999
1 155.358 227.383 80.055 0.0031 0.00159 0.00176 0.00476 0.01718 0.161 0.00769 0.01012 0.01661 0.02307 0.00677 25.97 0.470478 0.676258 -7.120925 0.279789 2.241742 0.108514
1 162.568 198.346 77.63 0.00502 0.0028 0.00253 0.00841 0.01791 0.168 0.00793 0.01057 0.01799 0.0238 0.0117 25.678 0.427785 0.723797 -6.635729 0.209866 1.957961 0.135242
0 197.076 206.896 192.055 0.00289 0.00166 0.00168 0.00498 0.01098 0.097 0.00563 0.0068 0.00802 0.01689 0.00339 26.775 0.422229 0.741367 -7.3483 0.177551 1.743867 0.085569
0 199.228 209.512 192.091 0.00241 0.00134 0.00138 0.00402 0.01015 0.089 0.00504 0.00641 0.00762 0.01513 0.00167 30.94 0.432439 0.742055 -7.682587 0.173319 2.103106 0.068501
0 198.383 215.203 193.104 0.00212 0.00113 0.00135 0.00339 0.01263 0.111 0.0064 0.00825 0.00951 0.01919 0.00119 30.775 0.465946 0.738703 -7.067931 0.175181 1.512275 0.09632
0 202.266 211.604 197.079 0.0018 0.00093 0.00107 0.00278 0.00954 0.085 0.00469 0.00606 0.00719 0.01407 0.00072 32.684 0.368535 0.742133 -7.695734 0.17854 1.544609 0.056141
0 203.184 211.526 196.16 0.00178 0.00094 0.00106 0.00283 0.00958 0.085 0.00468 0.0061 0.00726 0.01403 0.00065 33.047 0.340068 0.741899 -7.964984 0.163519 1.423287 0.044539
0 201.464 210.565 195.708 0.00198 0.00105 0.00115 0.00314 0.01194 0.107 0.00586 0.0076 0.00957 0.01758 0.00135 31.732 0.344252 0.742737 -7.777685 0.170183 2.447064 0.05761
1 177.876 192.921 168.013 0.00411 0.00233 0.00241 0.007 0.02126 0.189 0.01154 0.01347 0.01612 0.03463 0.00586 23.216 0.360148 0.778834 -6.149653 0.218037 2.477082 0.165827
1 176.17 185.604 163.564 0.00369 0.00205 0.00218 0.00616 0.01851 0.168 0.00938 0.0116 0.01491 0.02814 0.0034 24.951 0.341435 0.783626 -6.006414 0.196371 2.536527 0.173218
1 180.198 201.249 175.456 0.00284 0.00153 0.00166 0.00459 0.01444 0.131 0.00726 0.00885 0.0119 0.02177 0.00231 26.738 0.403884 0.766209 -6.452058 0.212294 2.269398 0.141929
1 187.733 202.324 173.015 0.00316 0.00168 0.00182 0.00504 0.01663 0.151 0.00829 0.01003 0.01366 0.02488 0.00265 26.31 0.396793 0.758324 -6.006647 0.266892 2.382544 0.160691
1 186.163 197.724 177.584 0.00298 0.00165 0.00175 0.00496 0.01495 0.135 0.00774 0.00941 0.01233 0.02321 0.00231 26.822 0.32648 0.765623 -6.647379 0.201095 2.374073 0.130554
1 184.055 196.537 166.977 0.00258 0.00134 0.00147 0.00403 0.01463 0.132 0.00742 0.00901 0.01234 0.02226 0.00257 26.453 0.306443 0.759203 -7.044105 0.063412 2.361532 0.11573
0 237.226 247.326 225.227 0.00298 0.00169 0.00182 0.00507 0.01752 0.164 0.01035 0.01024 0.01133 0.03104 0.0074 22.736 0.305062 0.654172 -7.31055 0.098648 2.416838 0.095032
0 241.404 248.834 232.483 0.00281 0.00157 0.00173 0.0047 0.0176 0.154 0.01006 0.01038 0.01251 0.03017 0.00675 23.145 0.457702 0.634267 -6.793547 0.158266 2.256699 0.117399
0 243.439 250.912 232.435 0.0021 0.00109 0.00137 0.00327 0.01419 0.126 0.00777 0.00898 0.01033 0.0233 0.00454 25.368 0.438296 0.635285 -7.057869 0.091608 2.330716 0.09147
0 242.852 255.034 227.911 0.00225 0.00117 0.00139 0.0035 0.01494 0.134 0.00847 0.00879 0.01014 0.02542 0.00476 25.032 0.431285 0.638928 -6.99582 0.102083 2.3658 0.102706
0 245.51 262.09 231.848 0.00235 0.00127 0.00148 0.0038 0.01608 0.141 0.00906 0.00977 0.01149 0.02719 0.00476 24.602 0.467489 0.631653 -7.156076 0.127642 2.392122 0.097336
0 252.455 261.487 182.786 0.00185 0.00092 0.00113 0.00276 0.01152 0.103 0.00614 0.0073 0.0086 0.01841 0.00432 26.805 0.610367 0.635204 -7.31951 0.200873 2.028612 0.086398
0 122.188 128.611 115.765 0.00524 0.00169 0.00203 0.00507 0.01613 0.143 0.00855 0.00776 0.01433 0.02566 0.00839 23.162 0.579597 0.733659 -6.439398 0.266392 2.079922 0.133867
0 122.964 130.049 114.676 0.00428 0.00124 0.00155 0.00373 0.01681 0.154 0.0093 0.00802 0.014 0.02789 0.00462 24.971 0.538688 0.754073 -6.482096 0.264967 2.054419 0.128872
0 124.445 135.069 117.495 0.00431 0.00141 0.00167 0.00422 0.02184 0.197 0.01241 0.01024 0.01685 0.03724 0.00479 25.135 0.553134 0.775933 -6.650471 0.254498 1.840198 0.103561
0 126.344 134.231 112.773 0.00448 0.00131 0.00169 0.00393 0.02033 0.185 0.01143 0.00959 0.01614 0.03429 0.00474 25.03 0.507504 0.760361 -6.689151 0.291954 2.431854 0.105993
0 128.001 138.052 122.08 0.00436 0.00137 0.00166 0.00411 0.02297 0.21 0.01323 0.01072 0.01677 0.03969 0.00481 24.692 0.459766 0.766204 -7.072419 0.220434 1.972297 0.119308
0 129.336 139.867 118.604 0.0049 0.00165 0.00183 0.00495 0.02498 0.228 0.01396 0.01219 0.01947 0.04188 0.00484 25.429 0.420383 0.785714 -6.836811 0.269866 2.223719 0.147491
1 108.807 134.656 102.874 0.00761 0.00349 0.00486 0.01046 0.02719 0.255 0.01483 0.01609 0.02067 0.0445 0.01036 21.028 0.536009 0.819032 -4.649573 0.205558 1.986899 0.3167
1 109.86 126.358 104.437 0.00874 0.00398 0.00539 0.01193 0.03209 0.307 0.01789 0.01992 0.02454 0.05368 0.0118 20.767 0.558586 0.811843 -4.333543 0.221727 2.014606 0.344834
1 110.417 131.067 103.37 0.00784 0.00352 0.00514 0.01056 0.03715 0.334 0.02032 0.02302 0.02802 0.06097 0.00969 21.422 0.541781 0.821364 -4.438453 0.238298 1.92294 0.335041
1 117.274 129.916 110.402 0.00752 0.00299 0.00469 0.00898 0.02293 0.221 0.01189 0.01459 0.01948 0.03568 0.00681 22.817 0.530529 0.817756 -4.60826 0.290024 2.021591 0.314464
1 116.879 131.897 108.153 0.00788 0.00334 0.00493 0.01003 0.02645 0.265 0.01394 0.01625 0.02137 0.04183 0.00786 22.603 0.540049 0.813432 -4.476755 0.262633 1.827012 0.326197
1 114.847 271.314 104.68 0.00867 0.00373 0.0052 0.0112 0.03225 0.35 0.01805 0.01974 0.02519 0.05414 0.01143 21.66 0.547975 0.817396 -4.609161 0.221711 1.831691 0.316395
0 209.144 237.494 109.379 0.00282 0.00147 0.00152 0.00442 0.01861 0.17 0.00975 0.01258 0.01382 0.02925 0.00871 25.554 0.341788 0.678874 -7.040508 0.066994 2.460791 0.101516
0 223.365 238.987 98.664 0.00264 0.00154 0.00151 0.00461 0.01906 0.165 0.01013 0.01296 0.0134 0.03039 0.00301 26.138 0.447979 0.686264 -7.293801 0.086372 2.32156 0.098555
0 222.236 231.345 205.495 0.00266 0.00152 0.00144 0.00457 0.01643 0.145 0.00867 0.01108 0.012 0.02602 0.0034 25.856 0.364867 0.694399 -6.966321 0.095882 2.278687 0.103224
0 228.832 234.619 223.634 0.00296 0.00175 0.00155 0.00526 0.01644 0.145 0.00882 0.01075 0.01179 0.02647 0.00351 25.964 0.25657 0.683296 -7.24562 0.018689 2.498224 0.093534
0 229.401 252.221 221.156 0.00205 0.00114 0.00113 0.00342 0.01457 0.129 0.00769 0.00957 0.01016 0.02308 0.003 26.415 0.27685 0.673636 -7.496264 0.056844 2.003032 0.073581
0 228.969 239.541 113.201 0.00238 0.00136 0.0014 0.00408 0.01745 0.154 0.00942 0.0116 0.01234 0.02827 0.0042 24.547 0.305429 0.681811 -7.314237 0.006274 2.118596 0.091546
1 140.341 159.774 67.021 0.00817 0.0043 0.0044 0.01289 0.03198 0.313 0.0183 0.0181 0.02428 0.0549 0.02183 19.56 0.460139 0.720908 -5.409423 0.22685 2.359973 0.226156
1 136.969 166.607 66.004 0.00923 0.00507 0.00463 0.0152 0.03111 0.308 0.01638 0.01759 0.02603 0.04914 0.02659 19.979 0.498133 0.729067 -5.324574 0.20566 2.291558 0.226247
1 143.533 162.215 65.809 0.01101 0.00647 0.00467 0.01941 0.05384 0.478 0.03152 0.02422 0.03392 0.09455 0.04882 20.338 0.513237 0.731444 -5.86975 0.151814 2.118496 0.18558
1 148.09 162.824 67.343 0.00762 0.00467 0.00354 0.014 0.05428 0.497 0.03357 0.02494 0.03635 0.1007 0.02431 21.718 0.487407 0.727313 -6.261141 0.120956 2.137075 0.141958
1 142.729 162.408 65.476 0.00831 0.00469 0.00419 0.01407 0.03485 0.365 0.01868 0.01906 0.02949 0.05605 0.02599 20.264 0.489345 0.730387 -5.720868 0.15883 2.277927 0.180828
1 136.358 176.595 65.75 0.00971 0.00534 0.00478 0.01601 0.04978 0.483 0.02749 0.02466 0.03736 0.08247 0.03361 18.57 0.543299 0.733232 -5.207985 0.224852 2.642276 0.242981
1 120.08 139.71 111.208 0.00405 0.0018 0.0022 0.0054 0.01706 0.152 0.00974 0.00925 0.01345 0.02921 0.00442 25.742 0.495954 0.762959 -5.79182 0.329066 2.205024 0.18818
1 112.014 588.518 107.024 0.00533 0.00268 0.00329 0.00805 0.02448 0.226 0.01373 0.01375 0.01956 0.0412 0.00623 24.178 0.509127 0.789532 -5.389129 0.306636 1.928708 0.225461
1 110.793 128.101 107.316 0.00494 0.0026 0.00283 0.0078 0.02442 0.216 0.01432 0.01325 0.01831 0.04295 0.00479 25.438 0.437031 0.815908 -5.31336 0.201861 2.225815 0.244512
1 110.707 122.611 105.007 0.00516 0.00277 0.00289 0.00831 0.02215 0.206 0.01284 0.01219 0.01715 0.03851 0.00472 25.197 0.463514 0.807217 -5.477592 0.315074 1.862092 0.228624
1 112.876 148.826 106.981 0.005 0.0027 0.00289 0.0081 0.03999 0.35 0.02413 0.02231 0.02704 0.07238 0.00905 23.37 0.489538 0.789977 -5.775966 0.341169 2.007923 0.193918
1 110.568 125.394 106.821 0.00462 0.00226 0.0028 0.00677 0.02199 0.197 0.01284 0.01199 0.01636 0.03852 0.0042 25.82 0.429484 0.81634 -5.391029 0.250572 1.777901 0.232744
1 95.385 102.145 90.264 0.00608 0.00331 0.00332 0.00994 0.03202 0.263 0.01803 0.01886 0.02455 0.05408 0.01062 21.875 0.644954 0.779612 -5.115212 0.249494 2.017753 0.260015
1 100.77 115.697 85.545 0.01038 0.00622 0.00576 0.01865 0.03121 0.361 0.01773 0.01783 0.02139 0.0532 0.0222 19.2 0.594387 0.790117 -4.913885 0.265699 2.398422 0.277948
1 96.106 108.664 84.51 0.00694 0.00389 0.00415 0.01168 0.04024 0.364 0.02266 0.02451 0.02876 0.06799 0.01823 19.055 0.544805 0.770466 -4.441519 0.155097 2.645959 0.327978
1 95.605 107.715 87.549 0.00702 0.00428 0.00371 0.01283 0.03156 0.296 0.01792 0.01841 0.0219 0.05377 0.01825 19.659 0.576084 0.778747 -5.132032 0.210458 2.232576 0.260633
1 100.96 110.019 95.628 0.00606 0.00351 0.00348 0.01053 0.02427 0.216 0.01371 0.01421 0.01751 0.04114 0.01237 20.536 0.55461 0.787896 -5.022288 0.146948 2.428306 0.264666
1 98.804 102.305 87.804 0.00432 0.00247 0.00258 0.00742 0.02223 0.202 0.01277 0.01343 0.01552 0.03831 0.00882 22.244 0.576644 0.772416 -6.025367 0.078202 2.053601 0.177275
1 176.858 205.56 75.344 0.00747 0.00418 0.0042 0.01254 0.04795 0.435 0.02679 0.03022 0.0351 0.08037 0.0547 13.893 0.556494 0.729586 -5.288912 0.343073 3.099301 0.242119
1 180.978 200.125 155.495 0.00406 0.0022 0.00244 0.00659 0.03852 0.331 0.02107 0.02493 0.02877 0.06321 0.02782 16.176 0.583574 0.727747 -5.657899 0.315903 3.098256 0.200423
1 178.222 202.45 141.047 0.00321 0.00163 0.00194 0.00488 0.03759 0.327 0.02073 0.02415 0.02784 0.06219 0.03151 15.924 0.598714 0.712199 -6.366916 0.335753 2.654271 0.144614
1 176.281 227.381 125.61 0.0052 0.00287 0.00312 0.00862 0.06511 0.58 0.03671 0.04159 0.04683 0.11012 0.04824 13.922 0.602874 0.740837 -5.515071 0.299549 3.13655 0.220968
1 173.898 211.35 74.677 0.00448 0.00237 0.00254 0.0071 0.06727 0.65 0.03788 0.04254 0.04802 0.11363 0.04214 14.739 0.599371 0.743937 -5.783272 0.299793 3.007096 0.194052
1 179.711 225.93 144.878 0.00709 0.00391 0.00419 0.01172 0.04313 0.442 0.02297 0.02768 0.03455 0.06892 0.07223 11.866 0.590951 0.745526 -4.379411 0.375531 3.671155 0.332086
1 166.605 206.008 78.032 0.00742 0.00387 0.00453 0.01161 0.0664 0.634 0.0365 0.04282 0.05114 0.10949 0.08725 11.744 0.65341 0.733165 -4.508984 0.389232 3.317586 0.301952
1 151.955 163.335 147.226 0.00419 0.00224 0.00227 0.00672 0.07959 0.772 0.04421 0.04962 0.0569 0.13262 0.01658 19.664 0.501037 0.71436 -6.411497 0.207156 2.344876 0.13412
1 148.272 164.989 142.299 0.00459 0.0025 0.00256 0.0075 0.0419 0.383 0.02383 0.02521 0.03051 0.0715 0.01914 18.78 0.454444 0.734504 -5.952058 0.08784 2.344336 0.186489
1 152.125 161.469 76.596 0.00382 0.00191 0.00226 0.00574 0.05925 0.637 0.03341 0.03794 0.04398 0.10024 0.01211 20.969 0.447456 0.69779 -6.152551 0.17352 2.080121 0.160809
1 157.821 172.975 68.401 0.00358 0.00196 0.00196 0.00587 0.03716 0.307 0.02062 0.02321 0.02764 0.06185 0.0085 22.219 0.50238 0.71217 -6.251425 0.188056 2.143851 0.160812
1 157.447 163.267 149.605 0.00369 0.00201 0.00197 0.00602 0.03272 0.283 0.01813 0.01909 0.02571 0.05439 0.01018 21.693 0.447285 0.705658 -6.247076 0.180528 2.344348 0.164916
1 159.116 168.913 144.811 0.00342 0.00178 0.00184 0.00535 0.03381 0.307 0.01806 0.02024 0.02809 0.05417 0.00852 22.663 0.366329 0.693429 -6.41744 0.194627 2.473239 0.151709
1 125.036 143.946 116.187 0.0128 0.00743 0.00623 0.02228 0.03886 0.342 0.02135 0.02174 0.03088 0.06406 0.08151 15.338 0.629574 0.714485 -4.020042 0.265315 2.671825 0.340623
1 125.791 140.557 96.206 0.01378 0.00826 0.00655 0.02478 0.04689 0.422 0.02542 0.0263 0.03908 0.07625 0.10323 15.433 0.57101 0.690892 -5.159169 0.202146 2.441612 0.260375
1 126.512 141.756 99.77 0.01936 0.01159 0.0099 0.03476 0.06734 0.659 0.03611 0.03963 0.05783 0.10833 0.16744 12.435 0.638545 0.674953 -3.760348 0.242861 2.634633 0.378483
1 125.641 141.068 116.346 0.03316 0.02144 0.01522 0.06433 0.09178 0.891 0.05358 0.04791 0.06196 0.16074 0.31482 8.867 0.671299 0.656846 -3.700544 0.260481 2.991063 0.370961
1 128.451 150.449 75.632 0.01551 0.00905 0.00909 0.02716 0.0617 0.584 0.03223 0.03672 0.05174 0.09669 0.11843 15.06 0.639808 0.643327 -4.20273 0.310163 2.638279 0.356881
1 139.224 586.567 66.157 0.03011 0.01854 0.01628 0.05563 0.09419 0.93 0.05551 0.05005 0.06023 0.16654 0.2593 10.489 0.596362 0.641418 -3.269487 0.270641 2.690917 0.444774
1 150.258 154.609 75.349 0.00248 0.00105 0.00136 0.00315 0.01131 0.107 0.00522 0.00659 0.01009 0.01567 0.00495 26.759 0.296888 0.722356 -6.878393 0.089267 2.004055 0.113942
1 154.003 160.267 128.621 0.00183 0.00076 0.001 0.00229 0.0103 0.094 0.00469 0.00582 0.00871 0.01406 0.00243 28.409 0.263654 0.691483 -7.111576 0.14478 2.065477 0.093193
1 149.689 160.368 133.608 0.00257 0.00116 0.00134 0.00349 0.01346 0.126 0.0066 0.00818 0.01059 0.01979 0.00578 27.421 0.365488 0.719974 -6.997403 0.210279 1.994387 0.112878
1 155.078 163.736 144.148 0.00168 0.00068 0.00092 0.00204 0.01064 0.097 0.00522 0.00632 0.00928 0.01567 0.00233 29.746 0.334171 0.67793 -6.981201 0.18455 2.129924 0.106802
1 151.884 157.765 133.751 0.00258 0.00115 0.00122 0.00346 0.0145 0.137 0.00633 0.00788 0.01267 0.01898 0.00659 26.833 0.393563 0.700246 -6.600023 0.249172 2.499148 0.105306
1 151.989 157.339 132.857 0.00174 0.00075 0.00096 0.00225 0.01024 0.093 0.00455 0.00576 0.00993 0.01364 0.00238 29.928 0.311369 0.676066 -6.739151 0.160686 2.296873 0.11513
1 193.03 208.9 80.297 0.00766 0.0045 0.00389 0.01351 0.03044 0.275 0.01771 0.01815 0.02084 0.05312 0.00947 21.934 0.497554 0.740539 -5.845099 0.278679 2.608749 0.185668
1 200.714 223.982 89.686 0.00621 0.00371 0.00337 0.01112 0.02286 0.207 0.01192 0.01439 0.01852 0.03576 0.00704 23.239 0.436084 0.727863 -5.25832 0.256454 2.550961 0.23252
1 208.519 220.315 199.02 0.00609 0.00368 0.00339 0.01105 0.01761 0.155 0.00952 0.01058 0.01307 0.02855 0.0083 22.407 0.338097 0.712466 -6.471427 0.184378 2.502336 0.13639
1 204.664 221.3 189.621 0.00841 0.00502 0.00485 0.01506 0.02378 0.21 0.01277 0.01483 0.01767 0.03831 0.01316 21.305 0.498877 0.722085 -4.876336 0.212054 2.376749 0.268144
1 210.141 232.706 185.258 0.00534 0.00321 0.0028 0.00964 0.0168 0.149 0.00861 0.01017 0.01301 0.02583 0.0062 23.671 0.441097 0.722254 -5.96304 0.250283 2.489191 0.177807
1 206.327 226.355 92.02 0.00495 0.00302 0.00246 0.00905 0.02105 0.209 0.01107 0.01284 0.01604 0.0332 0.01048 21.864 0.331508 0.715121 -6.729713 0.181701 2.938114 0.115515
1 151.872 492.892 69.085 0.00856 0.00404 0.00385 0.01211 0.01843 0.235 0.00796 0.00832 0.01271 0.02389 0.06051 23.693 0.407701 0.662668 -4.673241 0.261549 2.702355 0.274407
1 158.219 442.557 71.948 0.00476 0.00214 0.00207 0.00642 0.01458 0.148 0.00606 0.00747 0.01312 0.01818 0.01554 26.356 0.450798 0.653823 -6.051233 0.27328 2.640798 0.170106
1 170.756 450.247 79.032 0.00555 0.00244 0.00261 0.00731 0.01725 0.175 0.00757 0.00971 0.01652 0.0227 0.01802 25.69 0.486738 0.676023 -4.597834 0.372114 2.975889 0.28278
1 178.285 442.824 82.063 0.00462 0.00157 0.00194 0.00472 0.01279 0.129 0.00617 0.00744 0.01151 0.01851 0.00856 25.02 0.470422 0.655239 -4.913137 0.393056 2.816781 0.251972
1 217.116 233.481 93.978 0.00404 0.00127 0.00128 0.00381 0.01299 0.124 0.00679 0.00631 0.01075 0.02038 0.00681 24.581 0.462516 0.58271 -5.517173 0.389295 2.925862 0.220657
1 128.94 479.697 88.251 0.00581 0.00241 0.00314 0.00723 0.02008 0.221 0.00849 0.01117 0.01734 0.02548 0.0235 24.743 0.487756 0.68413 -6.186128 0.279933 2.68624 0.152428
1 176.824 215.293 83.961 0.0046 0.00209 0.00221 0.00628 0.01169 0.117 0.00534 0.0063 0.01104 0.01603 0.01161 27.166 0.400088 0.656182 -4.711007 0.281618 2.655744 0.234809
1 138.19 203.522 83.34 0.00704 0.00406 0.00398 0.01218 0.04479 0.441 0.02587 0.02567 0.0322 0.07761 0.01968 18.305 0.538016 0.74148 -5.418787 0.160267 2.090438 0.229892
1 182.018 197.173 79.187 0.00842 0.00506 0.00449 0.01517 0.02503 0.231 0.01372 0.0158 0.01931 0.04115 0.01813 18.784 0.589956 0.732903 -5.44514 0.142466 2.174306 0.215558
1 156.239 195.107 79.82 0.00694 0.00403 0.00395 0.01209 0.02343 0.224 0.01289 0.0142 0.0172 0.03867 0.0202 19.196 0.618663 0.728421 -5.944191 0.143359 1.929715 0.181988
1 145.174 198.109 80.637 0.00733 0.00414 0.00422 0.01242 0.02362 0.233 0.01235 0.01495 0.01944 0.03706 0.01874 18.857 0.637518 0.735546 -5.594275 0.12795 1.765957 0.222716
1 138.145 197.238 81.114 0.00544 0.00294 0.00327 0.00883 0.02791 0.246 0.01484 0.01805 0.02259 0.04451 0.01794 18.178 0.623209 0.738245 -5.540351 0.087165 1.821297 0.214075
1 166.888 198.966 79.512 0.00638 0.00368 0.00351 0.01104 0.02857 0.257 0.01547 0.01859 0.02301 0.04641 0.01796 18.33 0.585169 0.736964 -5.825257 0.115697 1.996146 0.196535
1 119.031 127.533 109.216 0.0044 0.00214 0.00192 0.00641 0.01033 0.098 0.00538 0.0057 0.00811 0.01614 0.01724 26.842 0.457541 0.699787 -6.890021 0.152941 2.328513 0.112856
1 120.078 126.632 105.667 0.0027 0.00116 0.00135 0.00349 0.01022 0.09 0.00476 0.00588 0.00903 0.01428 0.00487 26.369 0.491345 0.718839 -5.892061 0.195976 2.108873 0.183572
1 120.289 128.143 100.209 0.00492 0.00269 0.00238 0.00808 0.01412 0.125 0.00703 0.0082 0.01194 0.0211 0.0161 23.949 0.46716 0.724045 -6.135296 0.20363 2.539724 0.169923
1 120.256 125.306 104.773 0.00407 0.00224 0.00205 0.00671 0.01516 0.138 0.00721 0.00815 0.0131 0.02164 0.01015 26.017 0.468621 0.735136 -6.112667 0.217013 2.527742 0.170633
1 119.056 125.213 86.795 0.00346 0.00169 0.0017 0.00508 0.01201 0.106 0.00633 0.00701 0.00915 0.01898 0.00903 23.389 0.470972 0.721308 -5.436135 0.254909 2.51632 0.232209
1 118.747 123.723 109.836 0.00331 0.00168 0.00171 0.00504 0.01043 0.099 0.0049 0.00621 0.00903 0.01471 0.00504 25.619 0.482296 0.723096 -6.448134 0.178713 2.034827 0.141422
1 106.516 112.777 93.105 0.00589 0.00291 0.00319 0.00873 0.04932 0.441 0.02683 0.03112 0.03651 0.0805 0.03031 17.06 0.637814 0.744064 -5.301321 0.320385 2.375138 0.24308
1 110.453 127.611 105.554 0.00494 0.00244 0.00315 0.00731 0.04128 0.379 0.02229 0.02592 0.03316 0.06688 0.02529 17.707 0.653427 0.706687 -5.333619 0.322044 2.631793 0.228319
1 113.4 133.344 107.816 0.00451 0.00219 0.00283 0.00658 0.04879 0.431 0.02385 0.02973 0.0437 0.07154 0.02278 19.013 0.6479 0.708144 -4.378916 0.300067 2.445502 0.259451
1 113.166 130.27 100.673 0.00502 0.00257 0.00312 0.00772 0.05279 0.476 0.02896 0.03347 0.04134 0.08689 0.0369 16.747 0.625362 0.708617 -4.654894 0.304107 2.672362 0.274387
1 112.239 126.609 104.095 0.00472 0.00238 0.0029 0.00715 0.05643 0.517 0.0307 0.0353 0.04451 0.09211 0.02629 17.366 0.640945 0.701404 -5.634576 0.306014 2.419253 0.209191
1 116.15 131.731 109.815 0.00381 0.00181 0.00232 0.00542 0.03026 0.267 0.01514 0.01812 0.0277 0.04543 0.01827 18.801 0.624811 0.696049 -5.866357 0.23307 2.445646 0.184985
1 170.368 268.796 79.543 0.00571 0.00232 0.00269 0.00696 0.03273 0.281 0.01713 0.01964 0.02824 0.05139 0.02485 18.54 0.677131 0.685057 -4.796845 0.397749 2.963799 0.277227
1 208.083 253.792 91.802 0.00757 0.00428 0.00428 0.01285 0.06725 0.571 0.04016 0.04003 0.04464 0.12047 0.04238 15.648 0.606344 0.665945 -5.410336 0.288917 2.665133 0.231723
1 198.458 219.29 148.691 0.00376 0.00182 0.00215 0.00546 0.03527 0.297 0.02055 0.02076 0.0253 0.06165 0.01728 18.702 0.606273 0.661735 -5.585259 0.310746 2.465528 0.209863
1 202.805 231.508 86.232 0.0037 0.00189 0.00211 0.00568 0.01997 0.18 0.01117 0.01177 0.01506 0.0335 0.0201 18.687 0.536102 0.632631 -5.898673 0.213353 2.470746 0.189032
1 202.544 241.35 164.168 0.00254 0.001 0.00133 0.00301 0.02662 0.228 0.01475 0.01558 0.02006 0.04426 0.01049 20.68 0.49748 0.630409 -6.132663 0.220617 2.576563 0.159777
1 223.361 263.872 87.638 0.00352 0.00169 0.00188 0.00506 0.02536 0.225 0.01379 0.01478 0.01909 0.04137 0.01493 20.366 0.566849 0.574282 -5.456811 0.345238 2.840556 0.232861
1 169.774 191.759 151.451 0.01568 0.00863 0.00946 0.02589 0.08143 0.821 0.03804 0.05426 0.08808 0.11411 0.0753 12.359 0.56161 0.793509 -3.297668 0.414758 3.413649 0.457533
1 183.52 216.814 161.34 0.01466 0.00849 0.00819 0.02546 0.0605 0.618 0.02865 0.04101 0.06359 0.08595 0.06057 14.367 0.478024 0.768974 -4.276605 0.355736 3.142364 0.336085
1 188.62 216.302 165.982 0.01719 0.00996 0.01027 0.02987 0.07118 0.722 0.03474 0.0458 0.06824 0.10422 0.08069 12.298 0.55287 0.764036 -3.377325 0.335357 3.274865 0.418646
1 202.632 565.74 177.258 0.01627 0.00919 0.00963 0.02756 0.0717 0.833 0.03515 0.04265 0.0646 0.10546 0.07889 14.989 0.427627 0.775708 -4.892495 0.262281 2.910213 0.270173
1 186.695 211.961 149.442 0.01872 0.01075 0.01154 0.03225 0.0583 0.784 0.02699 0.03714 0.06259 0.08096 0.10952 12.529 0.507826 0.762726 -4.484303 0.340256 2.958815 0.301487
1 192.818 224.429 168.793 0.03107 0.018 0.01958 0.05401 0.11908 1.302 0.05647 0.0794 0.13778 0.16942 0.21713 8.441 0.625866 0.76832 -2.434031 0.450493 3.079221 0.527367
1 198.116 233.099 174.478 0.02714 0.01568 0.01699 0.04705 0.08684 1.018 0.04284 0.05556 0.08318 0.12851 0.16265 9.449 0.584164 0.754449 -2.839756 0.356224 3.184027 0.454721
1 121.345 139.644 98.25 0.00684 0.00388 0.00332 0.01164 0.02534 0.241 0.0134 0.01399 0.02056 0.04019 0.04179 21.52 0.566867 0.670475 -4.865194 0.246404 2.01353 0.168581
1 119.1 128.442 88.833 0.00692 0.00393 0.003 0.01179 0.02682 0.236 0.01484 0.01405 0.02018 0.04451 0.04611 21.824 0.65168 0.659333 -4.239028 0.175691 2.45113 0.247455
1 117.87 127.349 95.654 0.00647 0.00356 0.003 0.01067 0.03087 0.276 0.01659 0.01804 0.02402 0.04977 0.02631 22.431 0.6283 0.652025 -3.583722 0.207914 2.439597 0.206256
1 122.336 142.369 94.794 0.00727 0.00415 0.00339 0.01246 0.02293 0.223 0.01205 0.01289 0.01771 0.03615 0.03191 22.953 0.611679 0.623731 -5.4351 0.230532 2.699645 0.220546
1 117.963 134.209 100.757 0.01813 0.01117 0.00718 0.03351 0.04912 0.438 0.0261 0.02161 0.02916 0.0783 0.10748 19.075 0.630547 0.646786 -3.444478 0.303214 2.964568 0.261305
1 126.144 154.284 97.543 0.00975 0.00593 0.00454 0.01778 0.02852 0.266 0.015 0.01581 0.02157 0.04499 0.03828 21.534 0.635015 0.627337 -5.070096 0.280091 2.8923 0.249703
1 127.93 138.752 112.173 0.00605 0.00321 0.00318 0.00962 0.03235 0.339 0.0136 0.0165 0.03105 0.04079 0.02663 19.651 0.654945 0.675865 -5.498456 0.234196 2.103014 0.216638
1 114.238 124.393 77.022 0.00581 0.00299 0.00316 0.00896 0.04009 0.406 0.01579 0.01994 0.04114 0.04736 0.02073 20.437 0.653139 0.694571 -5.185987 0.259229 2.151121 0.244948
1 115.322 135.738 107.802 0.00619 0.00352 0.00329 0.01057 0.03273 0.325 0.01644 0.01722 0.02931 0.04933 0.0281 19.388 0.577802 0.684373 -5.283009 0.226528 2.442906 0.238281
1 114.554 126.778 91.121 0.00651 0.00366 0.0034 0.01097 0.03658 0.369 0.01864 0.0194 0.03091 0.05592 0.02707 18.954 0.685151 0.719576 -5.529833 0.24275 2.408689 0.22052
1 112.15 131.669 97.527 0.00519 0.00291 0.00284 0.00873 0.01756 0.155 0.00967 0.01033 0.01363 0.02902 0.01435 21.219 0.557045 0.673086 -5.617124 0.184896 1.871871 0.212386
1 102.273 142.83 85.902 0.00907 0.00493 0.00461 0.0148 0.02814 0.272 0.01579 0.01553 0.02073 0.04736 0.03882 18.447 0.671378 0.674562 -2.929379 0.396746 2.560422 0.367233
0 236.2 244.663 102.137 0.00277 0.00154 0.00153 0.00462 0.02448 0.217 0.0141 0.01426 0.01621 0.04231 0.0062 24.078 0.469928 0.628232 -6.816086 0.17227 2.235197 0.119652
0 237.323 243.709 229.256 0.00303 0.00173 0.00159 0.00519 0.01242 0.116 0.00696 0.00747 0.00882 0.02089 0.00533 24.679 0.384868 0.62671 -7.018057 0.176316 1.852402 0.091604
0 260.105 264.919 237.303 0.00339 0.00205 0.00186 0.00616 0.0203 0.197 0.01186 0.0123 0.01367 0.03557 0.0091 21.083 0.440988 0.628058 -7.517934 0.160414 1.881767 0.075587
0 197.569 217.627 90.794 0.00803 0.0049 0.00448 0.0147 0.02177 0.189 0.01279 0.01272 0.01439 0.03836 0.01337 19.269 0.372222 0.725216 -5.736781 0.164529 2.88245 0.202879
0 240.301 245.135 219.783 0.00517 0.00316 0.00283 0.00949 0.02018 0.212 0.01176 0.01191 0.01344 0.03529 0.00965 21.02 0.371837 0.646167 -7.169701 0.073298 2.266432 0.100881
0 244.99 272.21 239.17 0.00451 0.00279 0.00237 0.00837 0.01897 0.181 0.01084 0.01121 0.01255 0.03253 0.01049 21.528 0.522812 0.646818 -7.3045 0.171088 2.095237 0.09622
0 112.547 133.374 105.715 0.00355 0.00166 0.0019 0.00499 0.01358 0.129 0.00664 0.00786 0.0114 0.01992 0.00435 26.436 0.413295 0.7567 -6.323531 0.218885 2.193412 0.160376
0 110.739 113.597 100.139 0.00356 0.0017 0.002 0.0051 0.01484 0.133 0.00754 0.0095 0.01285 0.02261 0.0043 26.55 0.36909 0.776158 -6.085567 0.192375 1.889002 0.174152
0 113.715 116.443 96.913 0.00349 0.00171 0.00203 0.00514 0.01472 0.133 0.00748 0.00905 0.01148 0.02245 0.00478 26.547 0.380253 0.7667 -5.943501 0.19215 1.852542 0.179677
0 117.004 144.466 99.923 0.00353 0.00176 0.00218 0.00528 0.01657 0.145 0.00881 0.01062 0.01318 0.02643 0.0059 25.445 0.387482 0.756482 -6.012559 0.229298 1.872946 0.163118
0 115.38 123.109 108.634 0.00332 0.0016 0.00199 0.0048 0.01503 0.137 0.00812 0.00933 0.01133 0.02436 0.00401 26.005 0.405991 0.761255 -5.966779 0.197938 1.974857 0.184067
0 116.388 129.038 108.97 0.00346 0.00169 0.00213 0.00507 0.01725 0.155 0.00874 0.01021 0.01331 0.02623 0.00415 26.143 0.361232 0.763242 -6.016891 0.109256 2.004719 0.174429
1 151.737 190.204 129.859 0.00314 0.00135 0.00162 0.00406 0.01469 0.132 0.00728 0.00886 0.0123 0.02184 0.0057 24.151 0.39661 0.745957 -6.486822 0.197919 2.449763 0.132703
1 148.79 158.359 138.99 0.00309 0.00152 0.00186 0.00456 0.01574 0.142 0.00839 0.00956 0.01309 0.02518 0.00488 24.412 0.402591 0.762508 -6.311987 0.182459 2.251553 0.160306
1 148.143 155.982 135.041 0.00392 0.00204 0.00231 0.00612 0.0145 0.131 0.00725 0.00876 0.01263 0.02175 0.0054 23.683 0.398499 0.778349 -5.711205 0.240875 2.845109 0.19273
1 150.44 163.441 144.736 0.00396 0.00206 0.00233 0.00619 0.02551 0.237 0.01321 0.01574 0.02148 0.03964 0.00611 23.133 0.352396 0.75932 -6.261446 0.183218 2.264226 0.144105
1 148.462 161.078 141.998 0.00397 0.00202 0.00235 0.00605 0.01831 0.163 0.0095 0.01103 0.01559 0.02849 0.00639 22.866 0.408598 0.768845 -5.704053 0.216204 2.679185 0.19771
1 149.818 163.417 144.786 0.00336 0.00174 0.00198 0.00521 0.02145 0.198 0.01155 0.01341 0.01666 0.03464 0.00595 23.008 0.329577 0.75718 -6.27717 0.109397 2.209021 0.156368
0 117.226 123.925 106.656 0.00417 0.00186 0.0027 0.00558 0.01909 0.171 0.00864 0.01223 0.01949 0.02592 0.00955 23.079 0.603515 0.669565 -5.61907 0.191576 2.027228 0.215724
0 116.848 217.552 99.503 0.00531 0.0026 0.00346 0.0078 0.01795 0.163 0.0081 0.01144 0.01756 0.02429 0.01179 22.085 0.663842 0.656516 -5.198864 0.206768 2.120412 0.252404
0 116.286 177.291 96.983 0.00314 0.00134 0.00192 0.00403 0.01564 0.136 0.00667 0.0099 0.01691 0.02001 0.00737 24.199 0.598515 0.654331 -5.592584 0.133917 2.058658 0.214346
0 116.556 592.03 86.228 0.00496 0.00254 0.00263 0.00762 0.0166 0.154 0.0082 0.00972 0.01491 0.0246 0.01397 23.958 0.566424 0.667654 -6.431119 0.15331 2.161936 0.120605
0 116.342 581.289 94.246 0.00267 0.00115 0.00148 0.00345 0.013 0.117 0.00631 0.00789 0.01144 0.01892 0.0068 25.023 0.528485 0.663884 -6.359018 0.116636 2.152083 0.138868
0 114.563 119.167 86.647 0.00327 0.00146 0.00184 0.00439 0.01185 0.106 0.00557 0.00721 0.01095 0.01672 0.00703 24.775 0.555303 0.659132 -6.710219 0.149694 1.91399 0.121777
0 201.774 262.707 78.228 0.00694 0.00412 0.00396 0.01235 0.02574 0.255 0.01454 0.01582 0.01758 0.04363 0.04441 19.368 0.508479 0.683761 -6.934474 0.15989 2.316346 0.112838
0 174.188 230.978 94.261 0.00459 0.00263 0.00259 0.0079 0.04087 0.405 0.02336 0.02498 0.02745 0.07008 0.02764 19.517 0.448439 0.657899 -6.538586 0.121952 2.657476 0.13305
0 209.516 253.017 89.488 0.00564 0.00331 0.00292 0.00994 0.02751 0.263 0.01604 0.01657 0.01879 0.04812 0.0181 19.147 0.431674 0.683244 -6.195325 0.129303 2.784312 0.168895
0 174.688 240.005 74.287 0.0136 0.00624 0.00564 0.01873 0.02308 0.256 0.01268 0.01365 0.01667 0.03804 0.10715 17.883 0.407567 0.655683 -6.787197 0.158453 2.679772 0.131728
0 198.764 396.961 74.904 0.0074 0.0037 0.0039 0.01109 0.02296 0.241 0.01265 0.01321 0.01588 0.03794 0.07223 19.02 0.451221 0.643956 -6.744577 0.207454 2.138608 0.123306
0 214.289 260.277 77.973 0.00567 0.00295 0.00317 0.00885 0.01884 0.19 0.01026 0.01161 0.01373 0.03078 0.04398 21.209 0.462803 0.664357 -5.724056 0.190667 2.555477 0.148569




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time31 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 31 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232101&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]31 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232101&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232101&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time31 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







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]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
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] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232101&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]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][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232101&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232101&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

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
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.220861.156751.920.05651290.0282565
`MDVP:Fo(Hz)`-0.001665420.00112881-1.4750.1419270.0709635
`MDVP:Fhi(Hz)`-9.24141e-050.000319035-0.28970.7724170.386209
`MDVP:Flo(Hz)`-0.0016520.000784526-2.1060.03667080.0183354
`MDVP:Jitter(%)`-198.74959.6504-3.3320.001054680.000527339
`MDVP:RAP`-1002.659312.65-0.10770.9143860.457193
`MDVP:PPQ`-25.685987.0557-0.29510.7683090.384154
`Jitter:DDP`438.5313105.230.14120.8878580.443929
`MDVP:Shimmer`22.425533.51450.66910.5043050.252153
`MDVP:Shimmer(dB)`0.6093171.196450.50930.6112120.305606
`Shimmer:APQ3`-227.8988914.82-0.025560.9796350.489817
`Shimmer:APQ5`-27.848819.9929-1.3930.1654280.082714
`MDVP:APQ`1.05689.234330.11440.9090190.45451
`Shimmer:DDA`70.73392971.040.023810.9810330.490517
NHR-2.565411.97706-1.2980.1961560.098078
HNR-0.01760130.0140749-1.2510.212790.106395
RPDE-1.062530.433804-2.4490.01530890.00765447
DFA0.4410910.7286090.60540.5457140.272857
spread10.1392390.09634061.4450.1501880.0750938
spread21.262890.4773212.6460.008901230.00445062
D20.0582230.1135120.51290.6086580.304329
PPE0.9623961.316440.73110.4657330.232866

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 2.22086 & 1.15675 & 1.92 & 0.0565129 & 0.0282565 \tabularnewline
`MDVP:Fo(Hz)` & -0.00166542 & 0.00112881 & -1.475 & 0.141927 & 0.0709635 \tabularnewline
`MDVP:Fhi(Hz)` & -9.24141e-05 & 0.000319035 & -0.2897 & 0.772417 & 0.386209 \tabularnewline
`MDVP:Flo(Hz)` & -0.001652 & 0.000784526 & -2.106 & 0.0366708 & 0.0183354 \tabularnewline
`MDVP:Jitter(%)` & -198.749 & 59.6504 & -3.332 & 0.00105468 & 0.000527339 \tabularnewline
`MDVP:RAP` & -1002.65 & 9312.65 & -0.1077 & 0.914386 & 0.457193 \tabularnewline
`MDVP:PPQ` & -25.6859 & 87.0557 & -0.2951 & 0.768309 & 0.384154 \tabularnewline
`Jitter:DDP` & 438.531 & 3105.23 & 0.1412 & 0.887858 & 0.443929 \tabularnewline
`MDVP:Shimmer` & 22.4255 & 33.5145 & 0.6691 & 0.504305 & 0.252153 \tabularnewline
`MDVP:Shimmer(dB)` & 0.609317 & 1.19645 & 0.5093 & 0.611212 & 0.305606 \tabularnewline
`Shimmer:APQ3` & -227.898 & 8914.82 & -0.02556 & 0.979635 & 0.489817 \tabularnewline
`Shimmer:APQ5` & -27.8488 & 19.9929 & -1.393 & 0.165428 & 0.082714 \tabularnewline
`MDVP:APQ` & 1.0568 & 9.23433 & 0.1144 & 0.909019 & 0.45451 \tabularnewline
`Shimmer:DDA` & 70.7339 & 2971.04 & 0.02381 & 0.981033 & 0.490517 \tabularnewline
NHR & -2.56541 & 1.97706 & -1.298 & 0.196156 & 0.098078 \tabularnewline
HNR & -0.0176013 & 0.0140749 & -1.251 & 0.21279 & 0.106395 \tabularnewline
RPDE & -1.06253 & 0.433804 & -2.449 & 0.0153089 & 0.00765447 \tabularnewline
DFA & 0.441091 & 0.728609 & 0.6054 & 0.545714 & 0.272857 \tabularnewline
spread1 & 0.139239 & 0.0963406 & 1.445 & 0.150188 & 0.0750938 \tabularnewline
spread2 & 1.26289 & 0.477321 & 2.646 & 0.00890123 & 0.00445062 \tabularnewline
D2 & 0.058223 & 0.113512 & 0.5129 & 0.608658 & 0.304329 \tabularnewline
PPE & 0.962396 & 1.31644 & 0.7311 & 0.465733 & 0.232866 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232101&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]2.22086[/C][C]1.15675[/C][C]1.92[/C][C]0.0565129[/C][C]0.0282565[/C][/ROW]
[ROW][C]`MDVP:Fo(Hz)`[/C][C]-0.00166542[/C][C]0.00112881[/C][C]-1.475[/C][C]0.141927[/C][C]0.0709635[/C][/ROW]
[ROW][C]`MDVP:Fhi(Hz)`[/C][C]-9.24141e-05[/C][C]0.000319035[/C][C]-0.2897[/C][C]0.772417[/C][C]0.386209[/C][/ROW]
[ROW][C]`MDVP:Flo(Hz)`[/C][C]-0.001652[/C][C]0.000784526[/C][C]-2.106[/C][C]0.0366708[/C][C]0.0183354[/C][/ROW]
[ROW][C]`MDVP:Jitter(%)`[/C][C]-198.749[/C][C]59.6504[/C][C]-3.332[/C][C]0.00105468[/C][C]0.000527339[/C][/ROW]
[ROW][C]`MDVP:RAP`[/C][C]-1002.65[/C][C]9312.65[/C][C]-0.1077[/C][C]0.914386[/C][C]0.457193[/C][/ROW]
[ROW][C]`MDVP:PPQ`[/C][C]-25.6859[/C][C]87.0557[/C][C]-0.2951[/C][C]0.768309[/C][C]0.384154[/C][/ROW]
[ROW][C]`Jitter:DDP`[/C][C]438.531[/C][C]3105.23[/C][C]0.1412[/C][C]0.887858[/C][C]0.443929[/C][/ROW]
[ROW][C]`MDVP:Shimmer`[/C][C]22.4255[/C][C]33.5145[/C][C]0.6691[/C][C]0.504305[/C][C]0.252153[/C][/ROW]
[ROW][C]`MDVP:Shimmer(dB)`[/C][C]0.609317[/C][C]1.19645[/C][C]0.5093[/C][C]0.611212[/C][C]0.305606[/C][/ROW]
[ROW][C]`Shimmer:APQ3`[/C][C]-227.898[/C][C]8914.82[/C][C]-0.02556[/C][C]0.979635[/C][C]0.489817[/C][/ROW]
[ROW][C]`Shimmer:APQ5`[/C][C]-27.8488[/C][C]19.9929[/C][C]-1.393[/C][C]0.165428[/C][C]0.082714[/C][/ROW]
[ROW][C]`MDVP:APQ`[/C][C]1.0568[/C][C]9.23433[/C][C]0.1144[/C][C]0.909019[/C][C]0.45451[/C][/ROW]
[ROW][C]`Shimmer:DDA`[/C][C]70.7339[/C][C]2971.04[/C][C]0.02381[/C][C]0.981033[/C][C]0.490517[/C][/ROW]
[ROW][C]NHR[/C][C]-2.56541[/C][C]1.97706[/C][C]-1.298[/C][C]0.196156[/C][C]0.098078[/C][/ROW]
[ROW][C]HNR[/C][C]-0.0176013[/C][C]0.0140749[/C][C]-1.251[/C][C]0.21279[/C][C]0.106395[/C][/ROW]
[ROW][C]RPDE[/C][C]-1.06253[/C][C]0.433804[/C][C]-2.449[/C][C]0.0153089[/C][C]0.00765447[/C][/ROW]
[ROW][C]DFA[/C][C]0.441091[/C][C]0.728609[/C][C]0.6054[/C][C]0.545714[/C][C]0.272857[/C][/ROW]
[ROW][C]spread1[/C][C]0.139239[/C][C]0.0963406[/C][C]1.445[/C][C]0.150188[/C][C]0.0750938[/C][/ROW]
[ROW][C]spread2[/C][C]1.26289[/C][C]0.477321[/C][C]2.646[/C][C]0.00890123[/C][C]0.00445062[/C][/ROW]
[ROW][C]D2[/C][C]0.058223[/C][C]0.113512[/C][C]0.5129[/C][C]0.608658[/C][C]0.304329[/C][/ROW]
[ROW][C]PPE[/C][C]0.962396[/C][C]1.31644[/C][C]0.7311[/C][C]0.465733[/C][C]0.232866[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232101&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232101&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.220861.156751.920.05651290.0282565
`MDVP:Fo(Hz)`-0.001665420.00112881-1.4750.1419270.0709635
`MDVP:Fhi(Hz)`-9.24141e-050.000319035-0.28970.7724170.386209
`MDVP:Flo(Hz)`-0.0016520.000784526-2.1060.03667080.0183354
`MDVP:Jitter(%)`-198.74959.6504-3.3320.001054680.000527339
`MDVP:RAP`-1002.659312.65-0.10770.9143860.457193
`MDVP:PPQ`-25.685987.0557-0.29510.7683090.384154
`Jitter:DDP`438.5313105.230.14120.8878580.443929
`MDVP:Shimmer`22.425533.51450.66910.5043050.252153
`MDVP:Shimmer(dB)`0.6093171.196450.50930.6112120.305606
`Shimmer:APQ3`-227.8988914.82-0.025560.9796350.489817
`Shimmer:APQ5`-27.848819.9929-1.3930.1654280.082714
`MDVP:APQ`1.05689.234330.11440.9090190.45451
`Shimmer:DDA`70.73392971.040.023810.9810330.490517
NHR-2.565411.97706-1.2980.1961560.098078
HNR-0.01760130.0140749-1.2510.212790.106395
RPDE-1.062530.433804-2.4490.01530890.00765447
DFA0.4410910.7286090.60540.5457140.272857
spread10.1392390.09634061.4450.1501880.0750938
spread21.262890.4773212.6460.008901230.00445062
D20.0582230.1135120.51290.6086580.304329
PPE0.9623961.316440.73110.4657330.232866







Multiple Linear Regression - Regression Statistics
Multiple R0.700873
R-squared0.491223
Adjusted R-squared0.429464
F-TEST (value)7.95385
F-TEST (DF numerator)21
F-TEST (DF denominator)173
p-value2.22045e-16
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.326214
Sum Squared Residuals18.4099

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.700873 \tabularnewline
R-squared & 0.491223 \tabularnewline
Adjusted R-squared & 0.429464 \tabularnewline
F-TEST (value) & 7.95385 \tabularnewline
F-TEST (DF numerator) & 21 \tabularnewline
F-TEST (DF denominator) & 173 \tabularnewline
p-value & 2.22045e-16 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.326214 \tabularnewline
Sum Squared Residuals & 18.4099 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232101&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.700873[/C][/ROW]
[ROW][C]R-squared[/C][C]0.491223[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.429464[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]7.95385[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]21[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]173[/C][/ROW]
[ROW][C]p-value[/C][C]2.22045e-16[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.326214[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]18.4099[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232101&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232101&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.700873
R-squared0.491223
Adjusted R-squared0.429464
F-TEST (value)7.95385
F-TEST (DF numerator)21
F-TEST (DF denominator)173
p-value2.22045e-16
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.326214
Sum Squared Residuals18.4099







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
110.9588790.0411208
211.06218-0.0621753
310.9877430.0122572
411.09203-0.0920253
510.8867120.113288
610.9410990.0589013
710.7737180.226282
810.5634370.436563
910.9999059.47239e-05
1011.18078-0.180781
1111.14753-0.147533
1211.26191-0.261909
1310.4353120.564688
1410.8902830.109717
1510.6916690.308331
1610.6925970.307403
1710.5516960.448304
1811.29349-0.293492
1911.30714-0.307136
2010.9611140.0388859
2111.04418-0.0441791
2210.9106950.0893049
2311.1245-0.124502
2410.8741540.125846
2510.8300660.169934
2610.9620520.0379482
2710.8246630.175337
2810.7864480.213552
2910.659820.34018
3010.6943350.305665
3100.277616-0.277616
3200.146771-0.146771
3300.183047-0.183047
3400.127774-0.127774
3500.0924532-0.0924532
3600.212884-0.212884
3710.7975290.202471
3810.8206110.179389
3910.6098430.390157
4010.7623350.237665
4110.6340350.365965
4210.4329050.567095
4300.261246-0.261246
4400.216908-0.216908
4500.0430149-0.0430149
4600.107751-0.107751
4700.072201-0.072201
480-0.02015990.0201599
4900.332225-0.332225
5000.41673-0.41673
5100.394788-0.394788
5200.451442-0.451442
5300.39317-0.39317
5400.553351-0.553351
5510.8422550.157745
5610.8116480.188352
5710.8744030.125597
5810.7562920.243708
5910.7943690.205631
6010.6929740.307026
6100.376374-0.376374
6200.282495-0.282495
6300.267731-0.267731
6400.217911-0.217911
6500.145804-0.145804
6600.309337-0.309337
6710.9254850.0745148
6810.9049660.0950339
6910.9096590.0903406
7010.9362120.0637881
7110.8697960.130204
7211.09437-0.0943678
7310.8680720.131928
7410.9438740.0561258
7511.02599-0.0259891
7611.089-0.089003
7711.08112-0.0811183
7810.9882090.0117909
7910.9622080.0377917
8011.18105-0.181054
8111.18996-0.189961
8211.14011-0.140105
8311.02079-0.0207864
8410.6816660.318334
8511.06974-0.0697351
8610.858780.14122
8710.7120190.287981
8810.9385890.0614113
8911.00435-0.00434516
9011.21076-0.210762
9111.12483-0.124827
9210.7868510.213149
9310.7173910.282609
9410.8644590.135541
9510.7691080.230892
9610.735640.26436
9710.8006890.199311
9811.0226-0.0226049
9910.8264080.173592
10010.9267160.0732844
10110.9877250.0122753
10210.9928310.0071694
10310.9781830.0218175
10410.5981670.401833
10510.5721490.427851
10610.5636840.436316
10710.5171080.482892
10810.6991030.300897
10910.60580.3942
11010.8820590.117941
11111.01868-0.0186822
11210.5894620.410538
11310.7526290.247371
11410.7011380.298862
11510.8084620.191538
11610.8698340.130166
11710.7216030.278397
11811.03216-0.0321553
11910.8942720.105728
12010.7622870.237713
12110.577450.42255
12210.9784410.0215593
12310.9631610.0368388
12410.7004750.299525
12510.5885950.411405
12610.6075260.392474
12710.6093490.390651
12810.6226860.377314
12910.4124750.587525
13010.7307480.269252
13110.7922510.207749
13210.8461260.153874
13311.03573-0.0357308
13410.6338730.366127
13510.9747220.0252776
13610.9458050.0541946
13711.15434-0.154342
13811.13068-0.130677
13910.949510.0504895
14010.7713370.228663
14110.8885670.111433
14210.8409280.159072
14310.7238940.276106
14410.6979840.302016
14510.5478330.452167
14610.8741660.125834
14711.36837-0.368368
14811.14904-0.149039
14911.20523-0.205234
15010.8748410.125159
15110.9462960.0537041
15210.9570640.0429361
15310.9031830.0968168
15410.8699140.130086
15510.8914860.108514
15610.9863540.013646
15710.7822980.217702
15811.27236-0.272363
15910.961570.03843
16010.8659910.134009
16111.13908-0.139083
16211.05207-0.0520697
16310.9480210.0519792
16410.7903780.209622
16511.41476-0.414764
16600.46071-0.46071
16700.225599-0.225599
16800.108001-0.108001
16900.929984-0.929984
17000.226851-0.226851
17100.11335-0.11335
17200.784201-0.784201
17300.82241-0.82241
17400.859406-0.859406
17500.858-0.858
17600.820521-0.820521
17700.762932-0.762932
17810.6440630.355937
17910.7019820.298018
18010.9465030.0534972
18110.7801750.219825
18210.8831140.116886
18310.7091650.290835
18400.60716-0.60716
18500.654041-0.654041
18600.596412-0.596412
18700.428782-0.428782
18800.458572-0.458572
18900.424374-0.424374
19000.404643-0.404643
19100.657962-0.657962
19200.713377-0.713377
1930-0.1892870.189287
19400.273958-0.273958
19500.545086-0.545086

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1 & 0.958879 & 0.0411208 \tabularnewline
2 & 1 & 1.06218 & -0.0621753 \tabularnewline
3 & 1 & 0.987743 & 0.0122572 \tabularnewline
4 & 1 & 1.09203 & -0.0920253 \tabularnewline
5 & 1 & 0.886712 & 0.113288 \tabularnewline
6 & 1 & 0.941099 & 0.0589013 \tabularnewline
7 & 1 & 0.773718 & 0.226282 \tabularnewline
8 & 1 & 0.563437 & 0.436563 \tabularnewline
9 & 1 & 0.999905 & 9.47239e-05 \tabularnewline
10 & 1 & 1.18078 & -0.180781 \tabularnewline
11 & 1 & 1.14753 & -0.147533 \tabularnewline
12 & 1 & 1.26191 & -0.261909 \tabularnewline
13 & 1 & 0.435312 & 0.564688 \tabularnewline
14 & 1 & 0.890283 & 0.109717 \tabularnewline
15 & 1 & 0.691669 & 0.308331 \tabularnewline
16 & 1 & 0.692597 & 0.307403 \tabularnewline
17 & 1 & 0.551696 & 0.448304 \tabularnewline
18 & 1 & 1.29349 & -0.293492 \tabularnewline
19 & 1 & 1.30714 & -0.307136 \tabularnewline
20 & 1 & 0.961114 & 0.0388859 \tabularnewline
21 & 1 & 1.04418 & -0.0441791 \tabularnewline
22 & 1 & 0.910695 & 0.0893049 \tabularnewline
23 & 1 & 1.1245 & -0.124502 \tabularnewline
24 & 1 & 0.874154 & 0.125846 \tabularnewline
25 & 1 & 0.830066 & 0.169934 \tabularnewline
26 & 1 & 0.962052 & 0.0379482 \tabularnewline
27 & 1 & 0.824663 & 0.175337 \tabularnewline
28 & 1 & 0.786448 & 0.213552 \tabularnewline
29 & 1 & 0.65982 & 0.34018 \tabularnewline
30 & 1 & 0.694335 & 0.305665 \tabularnewline
31 & 0 & 0.277616 & -0.277616 \tabularnewline
32 & 0 & 0.146771 & -0.146771 \tabularnewline
33 & 0 & 0.183047 & -0.183047 \tabularnewline
34 & 0 & 0.127774 & -0.127774 \tabularnewline
35 & 0 & 0.0924532 & -0.0924532 \tabularnewline
36 & 0 & 0.212884 & -0.212884 \tabularnewline
37 & 1 & 0.797529 & 0.202471 \tabularnewline
38 & 1 & 0.820611 & 0.179389 \tabularnewline
39 & 1 & 0.609843 & 0.390157 \tabularnewline
40 & 1 & 0.762335 & 0.237665 \tabularnewline
41 & 1 & 0.634035 & 0.365965 \tabularnewline
42 & 1 & 0.432905 & 0.567095 \tabularnewline
43 & 0 & 0.261246 & -0.261246 \tabularnewline
44 & 0 & 0.216908 & -0.216908 \tabularnewline
45 & 0 & 0.0430149 & -0.0430149 \tabularnewline
46 & 0 & 0.107751 & -0.107751 \tabularnewline
47 & 0 & 0.072201 & -0.072201 \tabularnewline
48 & 0 & -0.0201599 & 0.0201599 \tabularnewline
49 & 0 & 0.332225 & -0.332225 \tabularnewline
50 & 0 & 0.41673 & -0.41673 \tabularnewline
51 & 0 & 0.394788 & -0.394788 \tabularnewline
52 & 0 & 0.451442 & -0.451442 \tabularnewline
53 & 0 & 0.39317 & -0.39317 \tabularnewline
54 & 0 & 0.553351 & -0.553351 \tabularnewline
55 & 1 & 0.842255 & 0.157745 \tabularnewline
56 & 1 & 0.811648 & 0.188352 \tabularnewline
57 & 1 & 0.874403 & 0.125597 \tabularnewline
58 & 1 & 0.756292 & 0.243708 \tabularnewline
59 & 1 & 0.794369 & 0.205631 \tabularnewline
60 & 1 & 0.692974 & 0.307026 \tabularnewline
61 & 0 & 0.376374 & -0.376374 \tabularnewline
62 & 0 & 0.282495 & -0.282495 \tabularnewline
63 & 0 & 0.267731 & -0.267731 \tabularnewline
64 & 0 & 0.217911 & -0.217911 \tabularnewline
65 & 0 & 0.145804 & -0.145804 \tabularnewline
66 & 0 & 0.309337 & -0.309337 \tabularnewline
67 & 1 & 0.925485 & 0.0745148 \tabularnewline
68 & 1 & 0.904966 & 0.0950339 \tabularnewline
69 & 1 & 0.909659 & 0.0903406 \tabularnewline
70 & 1 & 0.936212 & 0.0637881 \tabularnewline
71 & 1 & 0.869796 & 0.130204 \tabularnewline
72 & 1 & 1.09437 & -0.0943678 \tabularnewline
73 & 1 & 0.868072 & 0.131928 \tabularnewline
74 & 1 & 0.943874 & 0.0561258 \tabularnewline
75 & 1 & 1.02599 & -0.0259891 \tabularnewline
76 & 1 & 1.089 & -0.089003 \tabularnewline
77 & 1 & 1.08112 & -0.0811183 \tabularnewline
78 & 1 & 0.988209 & 0.0117909 \tabularnewline
79 & 1 & 0.962208 & 0.0377917 \tabularnewline
80 & 1 & 1.18105 & -0.181054 \tabularnewline
81 & 1 & 1.18996 & -0.189961 \tabularnewline
82 & 1 & 1.14011 & -0.140105 \tabularnewline
83 & 1 & 1.02079 & -0.0207864 \tabularnewline
84 & 1 & 0.681666 & 0.318334 \tabularnewline
85 & 1 & 1.06974 & -0.0697351 \tabularnewline
86 & 1 & 0.85878 & 0.14122 \tabularnewline
87 & 1 & 0.712019 & 0.287981 \tabularnewline
88 & 1 & 0.938589 & 0.0614113 \tabularnewline
89 & 1 & 1.00435 & -0.00434516 \tabularnewline
90 & 1 & 1.21076 & -0.210762 \tabularnewline
91 & 1 & 1.12483 & -0.124827 \tabularnewline
92 & 1 & 0.786851 & 0.213149 \tabularnewline
93 & 1 & 0.717391 & 0.282609 \tabularnewline
94 & 1 & 0.864459 & 0.135541 \tabularnewline
95 & 1 & 0.769108 & 0.230892 \tabularnewline
96 & 1 & 0.73564 & 0.26436 \tabularnewline
97 & 1 & 0.800689 & 0.199311 \tabularnewline
98 & 1 & 1.0226 & -0.0226049 \tabularnewline
99 & 1 & 0.826408 & 0.173592 \tabularnewline
100 & 1 & 0.926716 & 0.0732844 \tabularnewline
101 & 1 & 0.987725 & 0.0122753 \tabularnewline
102 & 1 & 0.992831 & 0.0071694 \tabularnewline
103 & 1 & 0.978183 & 0.0218175 \tabularnewline
104 & 1 & 0.598167 & 0.401833 \tabularnewline
105 & 1 & 0.572149 & 0.427851 \tabularnewline
106 & 1 & 0.563684 & 0.436316 \tabularnewline
107 & 1 & 0.517108 & 0.482892 \tabularnewline
108 & 1 & 0.699103 & 0.300897 \tabularnewline
109 & 1 & 0.6058 & 0.3942 \tabularnewline
110 & 1 & 0.882059 & 0.117941 \tabularnewline
111 & 1 & 1.01868 & -0.0186822 \tabularnewline
112 & 1 & 0.589462 & 0.410538 \tabularnewline
113 & 1 & 0.752629 & 0.247371 \tabularnewline
114 & 1 & 0.701138 & 0.298862 \tabularnewline
115 & 1 & 0.808462 & 0.191538 \tabularnewline
116 & 1 & 0.869834 & 0.130166 \tabularnewline
117 & 1 & 0.721603 & 0.278397 \tabularnewline
118 & 1 & 1.03216 & -0.0321553 \tabularnewline
119 & 1 & 0.894272 & 0.105728 \tabularnewline
120 & 1 & 0.762287 & 0.237713 \tabularnewline
121 & 1 & 0.57745 & 0.42255 \tabularnewline
122 & 1 & 0.978441 & 0.0215593 \tabularnewline
123 & 1 & 0.963161 & 0.0368388 \tabularnewline
124 & 1 & 0.700475 & 0.299525 \tabularnewline
125 & 1 & 0.588595 & 0.411405 \tabularnewline
126 & 1 & 0.607526 & 0.392474 \tabularnewline
127 & 1 & 0.609349 & 0.390651 \tabularnewline
128 & 1 & 0.622686 & 0.377314 \tabularnewline
129 & 1 & 0.412475 & 0.587525 \tabularnewline
130 & 1 & 0.730748 & 0.269252 \tabularnewline
131 & 1 & 0.792251 & 0.207749 \tabularnewline
132 & 1 & 0.846126 & 0.153874 \tabularnewline
133 & 1 & 1.03573 & -0.0357308 \tabularnewline
134 & 1 & 0.633873 & 0.366127 \tabularnewline
135 & 1 & 0.974722 & 0.0252776 \tabularnewline
136 & 1 & 0.945805 & 0.0541946 \tabularnewline
137 & 1 & 1.15434 & -0.154342 \tabularnewline
138 & 1 & 1.13068 & -0.130677 \tabularnewline
139 & 1 & 0.94951 & 0.0504895 \tabularnewline
140 & 1 & 0.771337 & 0.228663 \tabularnewline
141 & 1 & 0.888567 & 0.111433 \tabularnewline
142 & 1 & 0.840928 & 0.159072 \tabularnewline
143 & 1 & 0.723894 & 0.276106 \tabularnewline
144 & 1 & 0.697984 & 0.302016 \tabularnewline
145 & 1 & 0.547833 & 0.452167 \tabularnewline
146 & 1 & 0.874166 & 0.125834 \tabularnewline
147 & 1 & 1.36837 & -0.368368 \tabularnewline
148 & 1 & 1.14904 & -0.149039 \tabularnewline
149 & 1 & 1.20523 & -0.205234 \tabularnewline
150 & 1 & 0.874841 & 0.125159 \tabularnewline
151 & 1 & 0.946296 & 0.0537041 \tabularnewline
152 & 1 & 0.957064 & 0.0429361 \tabularnewline
153 & 1 & 0.903183 & 0.0968168 \tabularnewline
154 & 1 & 0.869914 & 0.130086 \tabularnewline
155 & 1 & 0.891486 & 0.108514 \tabularnewline
156 & 1 & 0.986354 & 0.013646 \tabularnewline
157 & 1 & 0.782298 & 0.217702 \tabularnewline
158 & 1 & 1.27236 & -0.272363 \tabularnewline
159 & 1 & 0.96157 & 0.03843 \tabularnewline
160 & 1 & 0.865991 & 0.134009 \tabularnewline
161 & 1 & 1.13908 & -0.139083 \tabularnewline
162 & 1 & 1.05207 & -0.0520697 \tabularnewline
163 & 1 & 0.948021 & 0.0519792 \tabularnewline
164 & 1 & 0.790378 & 0.209622 \tabularnewline
165 & 1 & 1.41476 & -0.414764 \tabularnewline
166 & 0 & 0.46071 & -0.46071 \tabularnewline
167 & 0 & 0.225599 & -0.225599 \tabularnewline
168 & 0 & 0.108001 & -0.108001 \tabularnewline
169 & 0 & 0.929984 & -0.929984 \tabularnewline
170 & 0 & 0.226851 & -0.226851 \tabularnewline
171 & 0 & 0.11335 & -0.11335 \tabularnewline
172 & 0 & 0.784201 & -0.784201 \tabularnewline
173 & 0 & 0.82241 & -0.82241 \tabularnewline
174 & 0 & 0.859406 & -0.859406 \tabularnewline
175 & 0 & 0.858 & -0.858 \tabularnewline
176 & 0 & 0.820521 & -0.820521 \tabularnewline
177 & 0 & 0.762932 & -0.762932 \tabularnewline
178 & 1 & 0.644063 & 0.355937 \tabularnewline
179 & 1 & 0.701982 & 0.298018 \tabularnewline
180 & 1 & 0.946503 & 0.0534972 \tabularnewline
181 & 1 & 0.780175 & 0.219825 \tabularnewline
182 & 1 & 0.883114 & 0.116886 \tabularnewline
183 & 1 & 0.709165 & 0.290835 \tabularnewline
184 & 0 & 0.60716 & -0.60716 \tabularnewline
185 & 0 & 0.654041 & -0.654041 \tabularnewline
186 & 0 & 0.596412 & -0.596412 \tabularnewline
187 & 0 & 0.428782 & -0.428782 \tabularnewline
188 & 0 & 0.458572 & -0.458572 \tabularnewline
189 & 0 & 0.424374 & -0.424374 \tabularnewline
190 & 0 & 0.404643 & -0.404643 \tabularnewline
191 & 0 & 0.657962 & -0.657962 \tabularnewline
192 & 0 & 0.713377 & -0.713377 \tabularnewline
193 & 0 & -0.189287 & 0.189287 \tabularnewline
194 & 0 & 0.273958 & -0.273958 \tabularnewline
195 & 0 & 0.545086 & -0.545086 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232101&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]1[/C][C]0.958879[/C][C]0.0411208[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]1.06218[/C][C]-0.0621753[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]0.987743[/C][C]0.0122572[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]1.09203[/C][C]-0.0920253[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]0.886712[/C][C]0.113288[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.941099[/C][C]0.0589013[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.773718[/C][C]0.226282[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.563437[/C][C]0.436563[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.999905[/C][C]9.47239e-05[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]1.18078[/C][C]-0.180781[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]1.14753[/C][C]-0.147533[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]1.26191[/C][C]-0.261909[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.435312[/C][C]0.564688[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]0.890283[/C][C]0.109717[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.691669[/C][C]0.308331[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]0.692597[/C][C]0.307403[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.551696[/C][C]0.448304[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]1.29349[/C][C]-0.293492[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]1.30714[/C][C]-0.307136[/C][/ROW]
[ROW][C]20[/C][C]1[/C][C]0.961114[/C][C]0.0388859[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]1.04418[/C][C]-0.0441791[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.910695[/C][C]0.0893049[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]1.1245[/C][C]-0.124502[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.874154[/C][C]0.125846[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.830066[/C][C]0.169934[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.962052[/C][C]0.0379482[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.824663[/C][C]0.175337[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]0.786448[/C][C]0.213552[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.65982[/C][C]0.34018[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]0.694335[/C][C]0.305665[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0.277616[/C][C]-0.277616[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0.146771[/C][C]-0.146771[/C][/ROW]
[ROW][C]33[/C][C]0[/C][C]0.183047[/C][C]-0.183047[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]0.127774[/C][C]-0.127774[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0.0924532[/C][C]-0.0924532[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0.212884[/C][C]-0.212884[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]0.797529[/C][C]0.202471[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.820611[/C][C]0.179389[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.609843[/C][C]0.390157[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]0.762335[/C][C]0.237665[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.634035[/C][C]0.365965[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.432905[/C][C]0.567095[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0.261246[/C][C]-0.261246[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0.216908[/C][C]-0.216908[/C][/ROW]
[ROW][C]45[/C][C]0[/C][C]0.0430149[/C][C]-0.0430149[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0.107751[/C][C]-0.107751[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0.072201[/C][C]-0.072201[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]-0.0201599[/C][C]0.0201599[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0.332225[/C][C]-0.332225[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0.41673[/C][C]-0.41673[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]0.394788[/C][C]-0.394788[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0.451442[/C][C]-0.451442[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0.39317[/C][C]-0.39317[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0.553351[/C][C]-0.553351[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.842255[/C][C]0.157745[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]0.811648[/C][C]0.188352[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]0.874403[/C][C]0.125597[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.756292[/C][C]0.243708[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]0.794369[/C][C]0.205631[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.692974[/C][C]0.307026[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0.376374[/C][C]-0.376374[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0.282495[/C][C]-0.282495[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0.267731[/C][C]-0.267731[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0.217911[/C][C]-0.217911[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0.145804[/C][C]-0.145804[/C][/ROW]
[ROW][C]66[/C][C]0[/C][C]0.309337[/C][C]-0.309337[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.925485[/C][C]0.0745148[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]0.904966[/C][C]0.0950339[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]0.909659[/C][C]0.0903406[/C][/ROW]
[ROW][C]70[/C][C]1[/C][C]0.936212[/C][C]0.0637881[/C][/ROW]
[ROW][C]71[/C][C]1[/C][C]0.869796[/C][C]0.130204[/C][/ROW]
[ROW][C]72[/C][C]1[/C][C]1.09437[/C][C]-0.0943678[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]0.868072[/C][C]0.131928[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.943874[/C][C]0.0561258[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]1.02599[/C][C]-0.0259891[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]1.089[/C][C]-0.089003[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]1.08112[/C][C]-0.0811183[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]0.988209[/C][C]0.0117909[/C][/ROW]
[ROW][C]79[/C][C]1[/C][C]0.962208[/C][C]0.0377917[/C][/ROW]
[ROW][C]80[/C][C]1[/C][C]1.18105[/C][C]-0.181054[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]1.18996[/C][C]-0.189961[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]1.14011[/C][C]-0.140105[/C][/ROW]
[ROW][C]83[/C][C]1[/C][C]1.02079[/C][C]-0.0207864[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]0.681666[/C][C]0.318334[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]1.06974[/C][C]-0.0697351[/C][/ROW]
[ROW][C]86[/C][C]1[/C][C]0.85878[/C][C]0.14122[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.712019[/C][C]0.287981[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]0.938589[/C][C]0.0614113[/C][/ROW]
[ROW][C]89[/C][C]1[/C][C]1.00435[/C][C]-0.00434516[/C][/ROW]
[ROW][C]90[/C][C]1[/C][C]1.21076[/C][C]-0.210762[/C][/ROW]
[ROW][C]91[/C][C]1[/C][C]1.12483[/C][C]-0.124827[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]0.786851[/C][C]0.213149[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.717391[/C][C]0.282609[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]0.864459[/C][C]0.135541[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]0.769108[/C][C]0.230892[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.73564[/C][C]0.26436[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]0.800689[/C][C]0.199311[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]1.0226[/C][C]-0.0226049[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]0.826408[/C][C]0.173592[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]0.926716[/C][C]0.0732844[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]0.987725[/C][C]0.0122753[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]0.992831[/C][C]0.0071694[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]0.978183[/C][C]0.0218175[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.598167[/C][C]0.401833[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]0.572149[/C][C]0.427851[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]0.563684[/C][C]0.436316[/C][/ROW]
[ROW][C]107[/C][C]1[/C][C]0.517108[/C][C]0.482892[/C][/ROW]
[ROW][C]108[/C][C]1[/C][C]0.699103[/C][C]0.300897[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]0.6058[/C][C]0.3942[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]0.882059[/C][C]0.117941[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]1.01868[/C][C]-0.0186822[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]0.589462[/C][C]0.410538[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.752629[/C][C]0.247371[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.701138[/C][C]0.298862[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.808462[/C][C]0.191538[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.869834[/C][C]0.130166[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.721603[/C][C]0.278397[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]1.03216[/C][C]-0.0321553[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.894272[/C][C]0.105728[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.762287[/C][C]0.237713[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]0.57745[/C][C]0.42255[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]0.978441[/C][C]0.0215593[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]0.963161[/C][C]0.0368388[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.700475[/C][C]0.299525[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.588595[/C][C]0.411405[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.607526[/C][C]0.392474[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.609349[/C][C]0.390651[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.622686[/C][C]0.377314[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.412475[/C][C]0.587525[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.730748[/C][C]0.269252[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.792251[/C][C]0.207749[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]0.846126[/C][C]0.153874[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]1.03573[/C][C]-0.0357308[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.633873[/C][C]0.366127[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]0.974722[/C][C]0.0252776[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]0.945805[/C][C]0.0541946[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]1.15434[/C][C]-0.154342[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]1.13068[/C][C]-0.130677[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]0.94951[/C][C]0.0504895[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.771337[/C][C]0.228663[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.888567[/C][C]0.111433[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.840928[/C][C]0.159072[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.723894[/C][C]0.276106[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.697984[/C][C]0.302016[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.547833[/C][C]0.452167[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]0.874166[/C][C]0.125834[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]1.36837[/C][C]-0.368368[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]1.14904[/C][C]-0.149039[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]1.20523[/C][C]-0.205234[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.874841[/C][C]0.125159[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]0.946296[/C][C]0.0537041[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]0.957064[/C][C]0.0429361[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]0.903183[/C][C]0.0968168[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.869914[/C][C]0.130086[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]0.891486[/C][C]0.108514[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.986354[/C][C]0.013646[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.782298[/C][C]0.217702[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]1.27236[/C][C]-0.272363[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]0.96157[/C][C]0.03843[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]0.865991[/C][C]0.134009[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]1.13908[/C][C]-0.139083[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]1.05207[/C][C]-0.0520697[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0.948021[/C][C]0.0519792[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]0.790378[/C][C]0.209622[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]1.41476[/C][C]-0.414764[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.46071[/C][C]-0.46071[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.225599[/C][C]-0.225599[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.108001[/C][C]-0.108001[/C][/ROW]
[ROW][C]169[/C][C]0[/C][C]0.929984[/C][C]-0.929984[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.226851[/C][C]-0.226851[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.11335[/C][C]-0.11335[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.784201[/C][C]-0.784201[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.82241[/C][C]-0.82241[/C][/ROW]
[ROW][C]174[/C][C]0[/C][C]0.859406[/C][C]-0.859406[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.858[/C][C]-0.858[/C][/ROW]
[ROW][C]176[/C][C]0[/C][C]0.820521[/C][C]-0.820521[/C][/ROW]
[ROW][C]177[/C][C]0[/C][C]0.762932[/C][C]-0.762932[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0.644063[/C][C]0.355937[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]0.701982[/C][C]0.298018[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0.946503[/C][C]0.0534972[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]0.780175[/C][C]0.219825[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]0.883114[/C][C]0.116886[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0.709165[/C][C]0.290835[/C][/ROW]
[ROW][C]184[/C][C]0[/C][C]0.60716[/C][C]-0.60716[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]0.654041[/C][C]-0.654041[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]0.596412[/C][C]-0.596412[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.428782[/C][C]-0.428782[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.458572[/C][C]-0.458572[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.424374[/C][C]-0.424374[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.404643[/C][C]-0.404643[/C][/ROW]
[ROW][C]191[/C][C]0[/C][C]0.657962[/C][C]-0.657962[/C][/ROW]
[ROW][C]192[/C][C]0[/C][C]0.713377[/C][C]-0.713377[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]-0.189287[/C][C]0.189287[/C][/ROW]
[ROW][C]194[/C][C]0[/C][C]0.273958[/C][C]-0.273958[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.545086[/C][C]-0.545086[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232101&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232101&T=4

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
110.9588790.0411208
211.06218-0.0621753
310.9877430.0122572
411.09203-0.0920253
510.8867120.113288
610.9410990.0589013
710.7737180.226282
810.5634370.436563
910.9999059.47239e-05
1011.18078-0.180781
1111.14753-0.147533
1211.26191-0.261909
1310.4353120.564688
1410.8902830.109717
1510.6916690.308331
1610.6925970.307403
1710.5516960.448304
1811.29349-0.293492
1911.30714-0.307136
2010.9611140.0388859
2111.04418-0.0441791
2210.9106950.0893049
2311.1245-0.124502
2410.8741540.125846
2510.8300660.169934
2610.9620520.0379482
2710.8246630.175337
2810.7864480.213552
2910.659820.34018
3010.6943350.305665
3100.277616-0.277616
3200.146771-0.146771
3300.183047-0.183047
3400.127774-0.127774
3500.0924532-0.0924532
3600.212884-0.212884
3710.7975290.202471
3810.8206110.179389
3910.6098430.390157
4010.7623350.237665
4110.6340350.365965
4210.4329050.567095
4300.261246-0.261246
4400.216908-0.216908
4500.0430149-0.0430149
4600.107751-0.107751
4700.072201-0.072201
480-0.02015990.0201599
4900.332225-0.332225
5000.41673-0.41673
5100.394788-0.394788
5200.451442-0.451442
5300.39317-0.39317
5400.553351-0.553351
5510.8422550.157745
5610.8116480.188352
5710.8744030.125597
5810.7562920.243708
5910.7943690.205631
6010.6929740.307026
6100.376374-0.376374
6200.282495-0.282495
6300.267731-0.267731
6400.217911-0.217911
6500.145804-0.145804
6600.309337-0.309337
6710.9254850.0745148
6810.9049660.0950339
6910.9096590.0903406
7010.9362120.0637881
7110.8697960.130204
7211.09437-0.0943678
7310.8680720.131928
7410.9438740.0561258
7511.02599-0.0259891
7611.089-0.089003
7711.08112-0.0811183
7810.9882090.0117909
7910.9622080.0377917
8011.18105-0.181054
8111.18996-0.189961
8211.14011-0.140105
8311.02079-0.0207864
8410.6816660.318334
8511.06974-0.0697351
8610.858780.14122
8710.7120190.287981
8810.9385890.0614113
8911.00435-0.00434516
9011.21076-0.210762
9111.12483-0.124827
9210.7868510.213149
9310.7173910.282609
9410.8644590.135541
9510.7691080.230892
9610.735640.26436
9710.8006890.199311
9811.0226-0.0226049
9910.8264080.173592
10010.9267160.0732844
10110.9877250.0122753
10210.9928310.0071694
10310.9781830.0218175
10410.5981670.401833
10510.5721490.427851
10610.5636840.436316
10710.5171080.482892
10810.6991030.300897
10910.60580.3942
11010.8820590.117941
11111.01868-0.0186822
11210.5894620.410538
11310.7526290.247371
11410.7011380.298862
11510.8084620.191538
11610.8698340.130166
11710.7216030.278397
11811.03216-0.0321553
11910.8942720.105728
12010.7622870.237713
12110.577450.42255
12210.9784410.0215593
12310.9631610.0368388
12410.7004750.299525
12510.5885950.411405
12610.6075260.392474
12710.6093490.390651
12810.6226860.377314
12910.4124750.587525
13010.7307480.269252
13110.7922510.207749
13210.8461260.153874
13311.03573-0.0357308
13410.6338730.366127
13510.9747220.0252776
13610.9458050.0541946
13711.15434-0.154342
13811.13068-0.130677
13910.949510.0504895
14010.7713370.228663
14110.8885670.111433
14210.8409280.159072
14310.7238940.276106
14410.6979840.302016
14510.5478330.452167
14610.8741660.125834
14711.36837-0.368368
14811.14904-0.149039
14911.20523-0.205234
15010.8748410.125159
15110.9462960.0537041
15210.9570640.0429361
15310.9031830.0968168
15410.8699140.130086
15510.8914860.108514
15610.9863540.013646
15710.7822980.217702
15811.27236-0.272363
15910.961570.03843
16010.8659910.134009
16111.13908-0.139083
16211.05207-0.0520697
16310.9480210.0519792
16410.7903780.209622
16511.41476-0.414764
16600.46071-0.46071
16700.225599-0.225599
16800.108001-0.108001
16900.929984-0.929984
17000.226851-0.226851
17100.11335-0.11335
17200.784201-0.784201
17300.82241-0.82241
17400.859406-0.859406
17500.858-0.858
17600.820521-0.820521
17700.762932-0.762932
17810.6440630.355937
17910.7019820.298018
18010.9465030.0534972
18110.7801750.219825
18210.8831140.116886
18310.7091650.290835
18400.60716-0.60716
18500.654041-0.654041
18600.596412-0.596412
18700.428782-0.428782
18800.458572-0.458572
18900.424374-0.424374
19000.404643-0.404643
19100.657962-0.657962
19200.713377-0.713377
1930-0.1892870.189287
19400.273958-0.273958
19500.545086-0.545086







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
256.34187e-481.26837e-471
261.96153e-693.92305e-691
272.97047e-795.94094e-791
283.21255e-936.4251e-931
297.14024e-1101.42805e-1091
309.14376e-1261.82875e-1251
310.0001161230.0002322470.999884
323.04286e-056.08572e-050.99997
337.54628e-061.50926e-050.999992
341.99562e-063.99125e-060.999998
355.70619e-071.14124e-060.999999
361.5393e-073.07859e-071
370.0001743230.0003486450.999826
389.81505e-050.0001963010.999902
390.000441510.0008830210.999558
400.0005775830.001155170.999422
410.0006389250.001277850.999361
420.0003687380.0007374770.999631
430.0003272070.0006544150.999673
440.0001686790.0003373580.999831
458.78419e-050.0001756840.999912
464.08291e-058.16581e-050.999959
472.19698e-054.39396e-050.999978
482.40184e-054.80368e-050.999976
490.0001151810.0002303630.999885
508.95687e-050.0001791370.99991
516.09298e-050.000121860.999939
524.12657e-058.25313e-050.999959
532.84817e-055.69633e-050.999972
543.14456e-056.28913e-050.999969
553.24672e-056.49345e-050.999968
563.96268e-057.92536e-050.99996
572.2127e-054.42539e-050.999978
581.53253e-053.06507e-050.999985
598.45358e-061.69072e-050.999992
604.52178e-069.04355e-060.999995
610.0002418940.0004837880.999758
620.0003437160.0006874330.999656
630.0005650950.001130190.999435
640.000655130.001310260.999345
650.0005699420.001139880.99943
660.0008225590.001645120.999177
670.0006214860.001242970.999379
680.000396790.0007935790.999603
690.0005286270.001057250.999471
700.0003474530.0006949050.999653
710.000214820.000429640.999785
720.0001472260.0002944520.999853
739.00305e-050.0001800610.99991
740.0001591960.0003183920.999841
750.0001708450.000341690.999829
760.0001396570.0002793140.99986
779.21594e-050.0001843190.999908
787.07322e-050.0001414640.999929
794.30886e-058.61771e-050.999957
803.37239e-056.74478e-050.999966
812.61668e-055.23336e-050.999974
821.56784e-053.13569e-050.999984
831.01674e-052.03348e-050.99999
846.95312e-061.39062e-050.999993
854.875e-069.75e-060.999995
866.86977e-061.37395e-050.999993
878.51978e-061.70396e-050.999991
885.35024e-061.07005e-050.999995
893.87256e-067.74511e-060.999996
904.30972e-068.61943e-060.999996
914.42581e-068.85163e-060.999996
926.11671e-061.22334e-050.999994
934.1713e-068.3426e-060.999996
942.69237e-065.38475e-060.999997
951.87101e-063.74202e-060.999998
961.32682e-062.65364e-060.999999
978.62464e-071.72493e-060.999999
984.82047e-079.64094e-071
992.81379e-075.62758e-071
1001.71976e-073.43951e-071
1011.29435e-072.5887e-071
1021.08579e-072.17158e-071
1038.9713e-081.79426e-071
1041.21314e-072.42627e-071
1052.16348e-074.32696e-071
1063.80022e-077.60044e-071
1071.02934e-062.05868e-060.999999
1087.40439e-071.48088e-060.999999
1091.88073e-063.76147e-060.999998
1102.05092e-064.10184e-060.999998
1111.22972e-062.45943e-060.999999
1122.92687e-065.85374e-060.999997
1132.66019e-065.32039e-060.999997
1142.83767e-065.67533e-060.999997
1152.94293e-065.88585e-060.999997
1161.99119e-063.98238e-060.999998
1172.9511e-065.9022e-060.999997
1181.7526e-063.50521e-060.999998
1191.13158e-062.26315e-060.999999
1201.92724e-063.85447e-060.999998
1215.89234e-061.17847e-050.999994
1221.45314e-052.90628e-050.999985
1238.91796e-061.78359e-050.999991
1246.45344e-061.29069e-050.999994
1255.98085e-061.19617e-050.999994
1266.78617e-061.35723e-050.999993
1271.27741e-052.55481e-050.999987
1280.0001618230.0003236450.999838
1290.0003507030.0007014050.999649
1300.0006863750.001372750.999314
1310.0007275760.001455150.999272
1320.0005401510.00108030.99946
1330.0005478540.001095710.999452
1340.002532110.005064210.997468
1350.00223020.00446040.99777
1360.002178640.004357280.997821
1370.00258090.00516180.997419
1380.002355570.004711130.997644
1390.00162640.003252810.998374
1400.001832620.003665240.998167
1410.001373850.002747710.998626
1420.001926190.003852380.998074
1430.001479890.002959790.99852
1440.006189760.01237950.99381
1450.005300960.01060190.994699
1460.004444860.008889710.995555
1470.003292170.006584340.996708
1480.002126620.004253240.997873
1490.001661620.003323240.998338
1500.001221490.002442980.998779
1510.001658090.003316180.998342
1520.01200010.02400020.988
1530.04943420.09886850.950566
1540.05247530.1049510.947525
1550.04550260.09100520.954497
1560.03414880.06829760.965851
1570.1262460.2524920.873754
1580.1158740.2317480.884126
1590.3765750.7531510.623425
1600.3110.6220.689
1610.2473060.4946120.752694
1620.1912570.3825150.808743
1630.1977150.3954310.802285
1640.2092760.4185510.790724
1650.5427080.9145840.457292
1660.6289270.7421460.371073
1670.9240990.1518020.075901
1680.9762530.04749310.0237466
1690.9907150.01856940.00928468
1700.9639420.07211620.0360581

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
25 & 6.34187e-48 & 1.26837e-47 & 1 \tabularnewline
26 & 1.96153e-69 & 3.92305e-69 & 1 \tabularnewline
27 & 2.97047e-79 & 5.94094e-79 & 1 \tabularnewline
28 & 3.21255e-93 & 6.4251e-93 & 1 \tabularnewline
29 & 7.14024e-110 & 1.42805e-109 & 1 \tabularnewline
30 & 9.14376e-126 & 1.82875e-125 & 1 \tabularnewline
31 & 0.000116123 & 0.000232247 & 0.999884 \tabularnewline
32 & 3.04286e-05 & 6.08572e-05 & 0.99997 \tabularnewline
33 & 7.54628e-06 & 1.50926e-05 & 0.999992 \tabularnewline
34 & 1.99562e-06 & 3.99125e-06 & 0.999998 \tabularnewline
35 & 5.70619e-07 & 1.14124e-06 & 0.999999 \tabularnewline
36 & 1.5393e-07 & 3.07859e-07 & 1 \tabularnewline
37 & 0.000174323 & 0.000348645 & 0.999826 \tabularnewline
38 & 9.81505e-05 & 0.000196301 & 0.999902 \tabularnewline
39 & 0.00044151 & 0.000883021 & 0.999558 \tabularnewline
40 & 0.000577583 & 0.00115517 & 0.999422 \tabularnewline
41 & 0.000638925 & 0.00127785 & 0.999361 \tabularnewline
42 & 0.000368738 & 0.000737477 & 0.999631 \tabularnewline
43 & 0.000327207 & 0.000654415 & 0.999673 \tabularnewline
44 & 0.000168679 & 0.000337358 & 0.999831 \tabularnewline
45 & 8.78419e-05 & 0.000175684 & 0.999912 \tabularnewline
46 & 4.08291e-05 & 8.16581e-05 & 0.999959 \tabularnewline
47 & 2.19698e-05 & 4.39396e-05 & 0.999978 \tabularnewline
48 & 2.40184e-05 & 4.80368e-05 & 0.999976 \tabularnewline
49 & 0.000115181 & 0.000230363 & 0.999885 \tabularnewline
50 & 8.95687e-05 & 0.000179137 & 0.99991 \tabularnewline
51 & 6.09298e-05 & 0.00012186 & 0.999939 \tabularnewline
52 & 4.12657e-05 & 8.25313e-05 & 0.999959 \tabularnewline
53 & 2.84817e-05 & 5.69633e-05 & 0.999972 \tabularnewline
54 & 3.14456e-05 & 6.28913e-05 & 0.999969 \tabularnewline
55 & 3.24672e-05 & 6.49345e-05 & 0.999968 \tabularnewline
56 & 3.96268e-05 & 7.92536e-05 & 0.99996 \tabularnewline
57 & 2.2127e-05 & 4.42539e-05 & 0.999978 \tabularnewline
58 & 1.53253e-05 & 3.06507e-05 & 0.999985 \tabularnewline
59 & 8.45358e-06 & 1.69072e-05 & 0.999992 \tabularnewline
60 & 4.52178e-06 & 9.04355e-06 & 0.999995 \tabularnewline
61 & 0.000241894 & 0.000483788 & 0.999758 \tabularnewline
62 & 0.000343716 & 0.000687433 & 0.999656 \tabularnewline
63 & 0.000565095 & 0.00113019 & 0.999435 \tabularnewline
64 & 0.00065513 & 0.00131026 & 0.999345 \tabularnewline
65 & 0.000569942 & 0.00113988 & 0.99943 \tabularnewline
66 & 0.000822559 & 0.00164512 & 0.999177 \tabularnewline
67 & 0.000621486 & 0.00124297 & 0.999379 \tabularnewline
68 & 0.00039679 & 0.000793579 & 0.999603 \tabularnewline
69 & 0.000528627 & 0.00105725 & 0.999471 \tabularnewline
70 & 0.000347453 & 0.000694905 & 0.999653 \tabularnewline
71 & 0.00021482 & 0.00042964 & 0.999785 \tabularnewline
72 & 0.000147226 & 0.000294452 & 0.999853 \tabularnewline
73 & 9.00305e-05 & 0.000180061 & 0.99991 \tabularnewline
74 & 0.000159196 & 0.000318392 & 0.999841 \tabularnewline
75 & 0.000170845 & 0.00034169 & 0.999829 \tabularnewline
76 & 0.000139657 & 0.000279314 & 0.99986 \tabularnewline
77 & 9.21594e-05 & 0.000184319 & 0.999908 \tabularnewline
78 & 7.07322e-05 & 0.000141464 & 0.999929 \tabularnewline
79 & 4.30886e-05 & 8.61771e-05 & 0.999957 \tabularnewline
80 & 3.37239e-05 & 6.74478e-05 & 0.999966 \tabularnewline
81 & 2.61668e-05 & 5.23336e-05 & 0.999974 \tabularnewline
82 & 1.56784e-05 & 3.13569e-05 & 0.999984 \tabularnewline
83 & 1.01674e-05 & 2.03348e-05 & 0.99999 \tabularnewline
84 & 6.95312e-06 & 1.39062e-05 & 0.999993 \tabularnewline
85 & 4.875e-06 & 9.75e-06 & 0.999995 \tabularnewline
86 & 6.86977e-06 & 1.37395e-05 & 0.999993 \tabularnewline
87 & 8.51978e-06 & 1.70396e-05 & 0.999991 \tabularnewline
88 & 5.35024e-06 & 1.07005e-05 & 0.999995 \tabularnewline
89 & 3.87256e-06 & 7.74511e-06 & 0.999996 \tabularnewline
90 & 4.30972e-06 & 8.61943e-06 & 0.999996 \tabularnewline
91 & 4.42581e-06 & 8.85163e-06 & 0.999996 \tabularnewline
92 & 6.11671e-06 & 1.22334e-05 & 0.999994 \tabularnewline
93 & 4.1713e-06 & 8.3426e-06 & 0.999996 \tabularnewline
94 & 2.69237e-06 & 5.38475e-06 & 0.999997 \tabularnewline
95 & 1.87101e-06 & 3.74202e-06 & 0.999998 \tabularnewline
96 & 1.32682e-06 & 2.65364e-06 & 0.999999 \tabularnewline
97 & 8.62464e-07 & 1.72493e-06 & 0.999999 \tabularnewline
98 & 4.82047e-07 & 9.64094e-07 & 1 \tabularnewline
99 & 2.81379e-07 & 5.62758e-07 & 1 \tabularnewline
100 & 1.71976e-07 & 3.43951e-07 & 1 \tabularnewline
101 & 1.29435e-07 & 2.5887e-07 & 1 \tabularnewline
102 & 1.08579e-07 & 2.17158e-07 & 1 \tabularnewline
103 & 8.9713e-08 & 1.79426e-07 & 1 \tabularnewline
104 & 1.21314e-07 & 2.42627e-07 & 1 \tabularnewline
105 & 2.16348e-07 & 4.32696e-07 & 1 \tabularnewline
106 & 3.80022e-07 & 7.60044e-07 & 1 \tabularnewline
107 & 1.02934e-06 & 2.05868e-06 & 0.999999 \tabularnewline
108 & 7.40439e-07 & 1.48088e-06 & 0.999999 \tabularnewline
109 & 1.88073e-06 & 3.76147e-06 & 0.999998 \tabularnewline
110 & 2.05092e-06 & 4.10184e-06 & 0.999998 \tabularnewline
111 & 1.22972e-06 & 2.45943e-06 & 0.999999 \tabularnewline
112 & 2.92687e-06 & 5.85374e-06 & 0.999997 \tabularnewline
113 & 2.66019e-06 & 5.32039e-06 & 0.999997 \tabularnewline
114 & 2.83767e-06 & 5.67533e-06 & 0.999997 \tabularnewline
115 & 2.94293e-06 & 5.88585e-06 & 0.999997 \tabularnewline
116 & 1.99119e-06 & 3.98238e-06 & 0.999998 \tabularnewline
117 & 2.9511e-06 & 5.9022e-06 & 0.999997 \tabularnewline
118 & 1.7526e-06 & 3.50521e-06 & 0.999998 \tabularnewline
119 & 1.13158e-06 & 2.26315e-06 & 0.999999 \tabularnewline
120 & 1.92724e-06 & 3.85447e-06 & 0.999998 \tabularnewline
121 & 5.89234e-06 & 1.17847e-05 & 0.999994 \tabularnewline
122 & 1.45314e-05 & 2.90628e-05 & 0.999985 \tabularnewline
123 & 8.91796e-06 & 1.78359e-05 & 0.999991 \tabularnewline
124 & 6.45344e-06 & 1.29069e-05 & 0.999994 \tabularnewline
125 & 5.98085e-06 & 1.19617e-05 & 0.999994 \tabularnewline
126 & 6.78617e-06 & 1.35723e-05 & 0.999993 \tabularnewline
127 & 1.27741e-05 & 2.55481e-05 & 0.999987 \tabularnewline
128 & 0.000161823 & 0.000323645 & 0.999838 \tabularnewline
129 & 0.000350703 & 0.000701405 & 0.999649 \tabularnewline
130 & 0.000686375 & 0.00137275 & 0.999314 \tabularnewline
131 & 0.000727576 & 0.00145515 & 0.999272 \tabularnewline
132 & 0.000540151 & 0.0010803 & 0.99946 \tabularnewline
133 & 0.000547854 & 0.00109571 & 0.999452 \tabularnewline
134 & 0.00253211 & 0.00506421 & 0.997468 \tabularnewline
135 & 0.0022302 & 0.0044604 & 0.99777 \tabularnewline
136 & 0.00217864 & 0.00435728 & 0.997821 \tabularnewline
137 & 0.0025809 & 0.0051618 & 0.997419 \tabularnewline
138 & 0.00235557 & 0.00471113 & 0.997644 \tabularnewline
139 & 0.0016264 & 0.00325281 & 0.998374 \tabularnewline
140 & 0.00183262 & 0.00366524 & 0.998167 \tabularnewline
141 & 0.00137385 & 0.00274771 & 0.998626 \tabularnewline
142 & 0.00192619 & 0.00385238 & 0.998074 \tabularnewline
143 & 0.00147989 & 0.00295979 & 0.99852 \tabularnewline
144 & 0.00618976 & 0.0123795 & 0.99381 \tabularnewline
145 & 0.00530096 & 0.0106019 & 0.994699 \tabularnewline
146 & 0.00444486 & 0.00888971 & 0.995555 \tabularnewline
147 & 0.00329217 & 0.00658434 & 0.996708 \tabularnewline
148 & 0.00212662 & 0.00425324 & 0.997873 \tabularnewline
149 & 0.00166162 & 0.00332324 & 0.998338 \tabularnewline
150 & 0.00122149 & 0.00244298 & 0.998779 \tabularnewline
151 & 0.00165809 & 0.00331618 & 0.998342 \tabularnewline
152 & 0.0120001 & 0.0240002 & 0.988 \tabularnewline
153 & 0.0494342 & 0.0988685 & 0.950566 \tabularnewline
154 & 0.0524753 & 0.104951 & 0.947525 \tabularnewline
155 & 0.0455026 & 0.0910052 & 0.954497 \tabularnewline
156 & 0.0341488 & 0.0682976 & 0.965851 \tabularnewline
157 & 0.126246 & 0.252492 & 0.873754 \tabularnewline
158 & 0.115874 & 0.231748 & 0.884126 \tabularnewline
159 & 0.376575 & 0.753151 & 0.623425 \tabularnewline
160 & 0.311 & 0.622 & 0.689 \tabularnewline
161 & 0.247306 & 0.494612 & 0.752694 \tabularnewline
162 & 0.191257 & 0.382515 & 0.808743 \tabularnewline
163 & 0.197715 & 0.395431 & 0.802285 \tabularnewline
164 & 0.209276 & 0.418551 & 0.790724 \tabularnewline
165 & 0.542708 & 0.914584 & 0.457292 \tabularnewline
166 & 0.628927 & 0.742146 & 0.371073 \tabularnewline
167 & 0.924099 & 0.151802 & 0.075901 \tabularnewline
168 & 0.976253 & 0.0474931 & 0.0237466 \tabularnewline
169 & 0.990715 & 0.0185694 & 0.00928468 \tabularnewline
170 & 0.963942 & 0.0721162 & 0.0360581 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232101&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]25[/C][C]6.34187e-48[/C][C]1.26837e-47[/C][C]1[/C][/ROW]
[ROW][C]26[/C][C]1.96153e-69[/C][C]3.92305e-69[/C][C]1[/C][/ROW]
[ROW][C]27[/C][C]2.97047e-79[/C][C]5.94094e-79[/C][C]1[/C][/ROW]
[ROW][C]28[/C][C]3.21255e-93[/C][C]6.4251e-93[/C][C]1[/C][/ROW]
[ROW][C]29[/C][C]7.14024e-110[/C][C]1.42805e-109[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]9.14376e-126[/C][C]1.82875e-125[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]0.000116123[/C][C]0.000232247[/C][C]0.999884[/C][/ROW]
[ROW][C]32[/C][C]3.04286e-05[/C][C]6.08572e-05[/C][C]0.99997[/C][/ROW]
[ROW][C]33[/C][C]7.54628e-06[/C][C]1.50926e-05[/C][C]0.999992[/C][/ROW]
[ROW][C]34[/C][C]1.99562e-06[/C][C]3.99125e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]35[/C][C]5.70619e-07[/C][C]1.14124e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]36[/C][C]1.5393e-07[/C][C]3.07859e-07[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]0.000174323[/C][C]0.000348645[/C][C]0.999826[/C][/ROW]
[ROW][C]38[/C][C]9.81505e-05[/C][C]0.000196301[/C][C]0.999902[/C][/ROW]
[ROW][C]39[/C][C]0.00044151[/C][C]0.000883021[/C][C]0.999558[/C][/ROW]
[ROW][C]40[/C][C]0.000577583[/C][C]0.00115517[/C][C]0.999422[/C][/ROW]
[ROW][C]41[/C][C]0.000638925[/C][C]0.00127785[/C][C]0.999361[/C][/ROW]
[ROW][C]42[/C][C]0.000368738[/C][C]0.000737477[/C][C]0.999631[/C][/ROW]
[ROW][C]43[/C][C]0.000327207[/C][C]0.000654415[/C][C]0.999673[/C][/ROW]
[ROW][C]44[/C][C]0.000168679[/C][C]0.000337358[/C][C]0.999831[/C][/ROW]
[ROW][C]45[/C][C]8.78419e-05[/C][C]0.000175684[/C][C]0.999912[/C][/ROW]
[ROW][C]46[/C][C]4.08291e-05[/C][C]8.16581e-05[/C][C]0.999959[/C][/ROW]
[ROW][C]47[/C][C]2.19698e-05[/C][C]4.39396e-05[/C][C]0.999978[/C][/ROW]
[ROW][C]48[/C][C]2.40184e-05[/C][C]4.80368e-05[/C][C]0.999976[/C][/ROW]
[ROW][C]49[/C][C]0.000115181[/C][C]0.000230363[/C][C]0.999885[/C][/ROW]
[ROW][C]50[/C][C]8.95687e-05[/C][C]0.000179137[/C][C]0.99991[/C][/ROW]
[ROW][C]51[/C][C]6.09298e-05[/C][C]0.00012186[/C][C]0.999939[/C][/ROW]
[ROW][C]52[/C][C]4.12657e-05[/C][C]8.25313e-05[/C][C]0.999959[/C][/ROW]
[ROW][C]53[/C][C]2.84817e-05[/C][C]5.69633e-05[/C][C]0.999972[/C][/ROW]
[ROW][C]54[/C][C]3.14456e-05[/C][C]6.28913e-05[/C][C]0.999969[/C][/ROW]
[ROW][C]55[/C][C]3.24672e-05[/C][C]6.49345e-05[/C][C]0.999968[/C][/ROW]
[ROW][C]56[/C][C]3.96268e-05[/C][C]7.92536e-05[/C][C]0.99996[/C][/ROW]
[ROW][C]57[/C][C]2.2127e-05[/C][C]4.42539e-05[/C][C]0.999978[/C][/ROW]
[ROW][C]58[/C][C]1.53253e-05[/C][C]3.06507e-05[/C][C]0.999985[/C][/ROW]
[ROW][C]59[/C][C]8.45358e-06[/C][C]1.69072e-05[/C][C]0.999992[/C][/ROW]
[ROW][C]60[/C][C]4.52178e-06[/C][C]9.04355e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]61[/C][C]0.000241894[/C][C]0.000483788[/C][C]0.999758[/C][/ROW]
[ROW][C]62[/C][C]0.000343716[/C][C]0.000687433[/C][C]0.999656[/C][/ROW]
[ROW][C]63[/C][C]0.000565095[/C][C]0.00113019[/C][C]0.999435[/C][/ROW]
[ROW][C]64[/C][C]0.00065513[/C][C]0.00131026[/C][C]0.999345[/C][/ROW]
[ROW][C]65[/C][C]0.000569942[/C][C]0.00113988[/C][C]0.99943[/C][/ROW]
[ROW][C]66[/C][C]0.000822559[/C][C]0.00164512[/C][C]0.999177[/C][/ROW]
[ROW][C]67[/C][C]0.000621486[/C][C]0.00124297[/C][C]0.999379[/C][/ROW]
[ROW][C]68[/C][C]0.00039679[/C][C]0.000793579[/C][C]0.999603[/C][/ROW]
[ROW][C]69[/C][C]0.000528627[/C][C]0.00105725[/C][C]0.999471[/C][/ROW]
[ROW][C]70[/C][C]0.000347453[/C][C]0.000694905[/C][C]0.999653[/C][/ROW]
[ROW][C]71[/C][C]0.00021482[/C][C]0.00042964[/C][C]0.999785[/C][/ROW]
[ROW][C]72[/C][C]0.000147226[/C][C]0.000294452[/C][C]0.999853[/C][/ROW]
[ROW][C]73[/C][C]9.00305e-05[/C][C]0.000180061[/C][C]0.99991[/C][/ROW]
[ROW][C]74[/C][C]0.000159196[/C][C]0.000318392[/C][C]0.999841[/C][/ROW]
[ROW][C]75[/C][C]0.000170845[/C][C]0.00034169[/C][C]0.999829[/C][/ROW]
[ROW][C]76[/C][C]0.000139657[/C][C]0.000279314[/C][C]0.99986[/C][/ROW]
[ROW][C]77[/C][C]9.21594e-05[/C][C]0.000184319[/C][C]0.999908[/C][/ROW]
[ROW][C]78[/C][C]7.07322e-05[/C][C]0.000141464[/C][C]0.999929[/C][/ROW]
[ROW][C]79[/C][C]4.30886e-05[/C][C]8.61771e-05[/C][C]0.999957[/C][/ROW]
[ROW][C]80[/C][C]3.37239e-05[/C][C]6.74478e-05[/C][C]0.999966[/C][/ROW]
[ROW][C]81[/C][C]2.61668e-05[/C][C]5.23336e-05[/C][C]0.999974[/C][/ROW]
[ROW][C]82[/C][C]1.56784e-05[/C][C]3.13569e-05[/C][C]0.999984[/C][/ROW]
[ROW][C]83[/C][C]1.01674e-05[/C][C]2.03348e-05[/C][C]0.99999[/C][/ROW]
[ROW][C]84[/C][C]6.95312e-06[/C][C]1.39062e-05[/C][C]0.999993[/C][/ROW]
[ROW][C]85[/C][C]4.875e-06[/C][C]9.75e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]86[/C][C]6.86977e-06[/C][C]1.37395e-05[/C][C]0.999993[/C][/ROW]
[ROW][C]87[/C][C]8.51978e-06[/C][C]1.70396e-05[/C][C]0.999991[/C][/ROW]
[ROW][C]88[/C][C]5.35024e-06[/C][C]1.07005e-05[/C][C]0.999995[/C][/ROW]
[ROW][C]89[/C][C]3.87256e-06[/C][C]7.74511e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]90[/C][C]4.30972e-06[/C][C]8.61943e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]91[/C][C]4.42581e-06[/C][C]8.85163e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]92[/C][C]6.11671e-06[/C][C]1.22334e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]93[/C][C]4.1713e-06[/C][C]8.3426e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]94[/C][C]2.69237e-06[/C][C]5.38475e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]95[/C][C]1.87101e-06[/C][C]3.74202e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]96[/C][C]1.32682e-06[/C][C]2.65364e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]97[/C][C]8.62464e-07[/C][C]1.72493e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]98[/C][C]4.82047e-07[/C][C]9.64094e-07[/C][C]1[/C][/ROW]
[ROW][C]99[/C][C]2.81379e-07[/C][C]5.62758e-07[/C][C]1[/C][/ROW]
[ROW][C]100[/C][C]1.71976e-07[/C][C]3.43951e-07[/C][C]1[/C][/ROW]
[ROW][C]101[/C][C]1.29435e-07[/C][C]2.5887e-07[/C][C]1[/C][/ROW]
[ROW][C]102[/C][C]1.08579e-07[/C][C]2.17158e-07[/C][C]1[/C][/ROW]
[ROW][C]103[/C][C]8.9713e-08[/C][C]1.79426e-07[/C][C]1[/C][/ROW]
[ROW][C]104[/C][C]1.21314e-07[/C][C]2.42627e-07[/C][C]1[/C][/ROW]
[ROW][C]105[/C][C]2.16348e-07[/C][C]4.32696e-07[/C][C]1[/C][/ROW]
[ROW][C]106[/C][C]3.80022e-07[/C][C]7.60044e-07[/C][C]1[/C][/ROW]
[ROW][C]107[/C][C]1.02934e-06[/C][C]2.05868e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]108[/C][C]7.40439e-07[/C][C]1.48088e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]109[/C][C]1.88073e-06[/C][C]3.76147e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]110[/C][C]2.05092e-06[/C][C]4.10184e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]111[/C][C]1.22972e-06[/C][C]2.45943e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]112[/C][C]2.92687e-06[/C][C]5.85374e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]113[/C][C]2.66019e-06[/C][C]5.32039e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]114[/C][C]2.83767e-06[/C][C]5.67533e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]115[/C][C]2.94293e-06[/C][C]5.88585e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]116[/C][C]1.99119e-06[/C][C]3.98238e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]117[/C][C]2.9511e-06[/C][C]5.9022e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]118[/C][C]1.7526e-06[/C][C]3.50521e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]119[/C][C]1.13158e-06[/C][C]2.26315e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]120[/C][C]1.92724e-06[/C][C]3.85447e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]121[/C][C]5.89234e-06[/C][C]1.17847e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]122[/C][C]1.45314e-05[/C][C]2.90628e-05[/C][C]0.999985[/C][/ROW]
[ROW][C]123[/C][C]8.91796e-06[/C][C]1.78359e-05[/C][C]0.999991[/C][/ROW]
[ROW][C]124[/C][C]6.45344e-06[/C][C]1.29069e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]125[/C][C]5.98085e-06[/C][C]1.19617e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]126[/C][C]6.78617e-06[/C][C]1.35723e-05[/C][C]0.999993[/C][/ROW]
[ROW][C]127[/C][C]1.27741e-05[/C][C]2.55481e-05[/C][C]0.999987[/C][/ROW]
[ROW][C]128[/C][C]0.000161823[/C][C]0.000323645[/C][C]0.999838[/C][/ROW]
[ROW][C]129[/C][C]0.000350703[/C][C]0.000701405[/C][C]0.999649[/C][/ROW]
[ROW][C]130[/C][C]0.000686375[/C][C]0.00137275[/C][C]0.999314[/C][/ROW]
[ROW][C]131[/C][C]0.000727576[/C][C]0.00145515[/C][C]0.999272[/C][/ROW]
[ROW][C]132[/C][C]0.000540151[/C][C]0.0010803[/C][C]0.99946[/C][/ROW]
[ROW][C]133[/C][C]0.000547854[/C][C]0.00109571[/C][C]0.999452[/C][/ROW]
[ROW][C]134[/C][C]0.00253211[/C][C]0.00506421[/C][C]0.997468[/C][/ROW]
[ROW][C]135[/C][C]0.0022302[/C][C]0.0044604[/C][C]0.99777[/C][/ROW]
[ROW][C]136[/C][C]0.00217864[/C][C]0.00435728[/C][C]0.997821[/C][/ROW]
[ROW][C]137[/C][C]0.0025809[/C][C]0.0051618[/C][C]0.997419[/C][/ROW]
[ROW][C]138[/C][C]0.00235557[/C][C]0.00471113[/C][C]0.997644[/C][/ROW]
[ROW][C]139[/C][C]0.0016264[/C][C]0.00325281[/C][C]0.998374[/C][/ROW]
[ROW][C]140[/C][C]0.00183262[/C][C]0.00366524[/C][C]0.998167[/C][/ROW]
[ROW][C]141[/C][C]0.00137385[/C][C]0.00274771[/C][C]0.998626[/C][/ROW]
[ROW][C]142[/C][C]0.00192619[/C][C]0.00385238[/C][C]0.998074[/C][/ROW]
[ROW][C]143[/C][C]0.00147989[/C][C]0.00295979[/C][C]0.99852[/C][/ROW]
[ROW][C]144[/C][C]0.00618976[/C][C]0.0123795[/C][C]0.99381[/C][/ROW]
[ROW][C]145[/C][C]0.00530096[/C][C]0.0106019[/C][C]0.994699[/C][/ROW]
[ROW][C]146[/C][C]0.00444486[/C][C]0.00888971[/C][C]0.995555[/C][/ROW]
[ROW][C]147[/C][C]0.00329217[/C][C]0.00658434[/C][C]0.996708[/C][/ROW]
[ROW][C]148[/C][C]0.00212662[/C][C]0.00425324[/C][C]0.997873[/C][/ROW]
[ROW][C]149[/C][C]0.00166162[/C][C]0.00332324[/C][C]0.998338[/C][/ROW]
[ROW][C]150[/C][C]0.00122149[/C][C]0.00244298[/C][C]0.998779[/C][/ROW]
[ROW][C]151[/C][C]0.00165809[/C][C]0.00331618[/C][C]0.998342[/C][/ROW]
[ROW][C]152[/C][C]0.0120001[/C][C]0.0240002[/C][C]0.988[/C][/ROW]
[ROW][C]153[/C][C]0.0494342[/C][C]0.0988685[/C][C]0.950566[/C][/ROW]
[ROW][C]154[/C][C]0.0524753[/C][C]0.104951[/C][C]0.947525[/C][/ROW]
[ROW][C]155[/C][C]0.0455026[/C][C]0.0910052[/C][C]0.954497[/C][/ROW]
[ROW][C]156[/C][C]0.0341488[/C][C]0.0682976[/C][C]0.965851[/C][/ROW]
[ROW][C]157[/C][C]0.126246[/C][C]0.252492[/C][C]0.873754[/C][/ROW]
[ROW][C]158[/C][C]0.115874[/C][C]0.231748[/C][C]0.884126[/C][/ROW]
[ROW][C]159[/C][C]0.376575[/C][C]0.753151[/C][C]0.623425[/C][/ROW]
[ROW][C]160[/C][C]0.311[/C][C]0.622[/C][C]0.689[/C][/ROW]
[ROW][C]161[/C][C]0.247306[/C][C]0.494612[/C][C]0.752694[/C][/ROW]
[ROW][C]162[/C][C]0.191257[/C][C]0.382515[/C][C]0.808743[/C][/ROW]
[ROW][C]163[/C][C]0.197715[/C][C]0.395431[/C][C]0.802285[/C][/ROW]
[ROW][C]164[/C][C]0.209276[/C][C]0.418551[/C][C]0.790724[/C][/ROW]
[ROW][C]165[/C][C]0.542708[/C][C]0.914584[/C][C]0.457292[/C][/ROW]
[ROW][C]166[/C][C]0.628927[/C][C]0.742146[/C][C]0.371073[/C][/ROW]
[ROW][C]167[/C][C]0.924099[/C][C]0.151802[/C][C]0.075901[/C][/ROW]
[ROW][C]168[/C][C]0.976253[/C][C]0.0474931[/C][C]0.0237466[/C][/ROW]
[ROW][C]169[/C][C]0.990715[/C][C]0.0185694[/C][C]0.00928468[/C][/ROW]
[ROW][C]170[/C][C]0.963942[/C][C]0.0721162[/C][C]0.0360581[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232101&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232101&T=5

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
256.34187e-481.26837e-471
261.96153e-693.92305e-691
272.97047e-795.94094e-791
283.21255e-936.4251e-931
297.14024e-1101.42805e-1091
309.14376e-1261.82875e-1251
310.0001161230.0002322470.999884
323.04286e-056.08572e-050.99997
337.54628e-061.50926e-050.999992
341.99562e-063.99125e-060.999998
355.70619e-071.14124e-060.999999
361.5393e-073.07859e-071
370.0001743230.0003486450.999826
389.81505e-050.0001963010.999902
390.000441510.0008830210.999558
400.0005775830.001155170.999422
410.0006389250.001277850.999361
420.0003687380.0007374770.999631
430.0003272070.0006544150.999673
440.0001686790.0003373580.999831
458.78419e-050.0001756840.999912
464.08291e-058.16581e-050.999959
472.19698e-054.39396e-050.999978
482.40184e-054.80368e-050.999976
490.0001151810.0002303630.999885
508.95687e-050.0001791370.99991
516.09298e-050.000121860.999939
524.12657e-058.25313e-050.999959
532.84817e-055.69633e-050.999972
543.14456e-056.28913e-050.999969
553.24672e-056.49345e-050.999968
563.96268e-057.92536e-050.99996
572.2127e-054.42539e-050.999978
581.53253e-053.06507e-050.999985
598.45358e-061.69072e-050.999992
604.52178e-069.04355e-060.999995
610.0002418940.0004837880.999758
620.0003437160.0006874330.999656
630.0005650950.001130190.999435
640.000655130.001310260.999345
650.0005699420.001139880.99943
660.0008225590.001645120.999177
670.0006214860.001242970.999379
680.000396790.0007935790.999603
690.0005286270.001057250.999471
700.0003474530.0006949050.999653
710.000214820.000429640.999785
720.0001472260.0002944520.999853
739.00305e-050.0001800610.99991
740.0001591960.0003183920.999841
750.0001708450.000341690.999829
760.0001396570.0002793140.99986
779.21594e-050.0001843190.999908
787.07322e-050.0001414640.999929
794.30886e-058.61771e-050.999957
803.37239e-056.74478e-050.999966
812.61668e-055.23336e-050.999974
821.56784e-053.13569e-050.999984
831.01674e-052.03348e-050.99999
846.95312e-061.39062e-050.999993
854.875e-069.75e-060.999995
866.86977e-061.37395e-050.999993
878.51978e-061.70396e-050.999991
885.35024e-061.07005e-050.999995
893.87256e-067.74511e-060.999996
904.30972e-068.61943e-060.999996
914.42581e-068.85163e-060.999996
926.11671e-061.22334e-050.999994
934.1713e-068.3426e-060.999996
942.69237e-065.38475e-060.999997
951.87101e-063.74202e-060.999998
961.32682e-062.65364e-060.999999
978.62464e-071.72493e-060.999999
984.82047e-079.64094e-071
992.81379e-075.62758e-071
1001.71976e-073.43951e-071
1011.29435e-072.5887e-071
1021.08579e-072.17158e-071
1038.9713e-081.79426e-071
1041.21314e-072.42627e-071
1052.16348e-074.32696e-071
1063.80022e-077.60044e-071
1071.02934e-062.05868e-060.999999
1087.40439e-071.48088e-060.999999
1091.88073e-063.76147e-060.999998
1102.05092e-064.10184e-060.999998
1111.22972e-062.45943e-060.999999
1122.92687e-065.85374e-060.999997
1132.66019e-065.32039e-060.999997
1142.83767e-065.67533e-060.999997
1152.94293e-065.88585e-060.999997
1161.99119e-063.98238e-060.999998
1172.9511e-065.9022e-060.999997
1181.7526e-063.50521e-060.999998
1191.13158e-062.26315e-060.999999
1201.92724e-063.85447e-060.999998
1215.89234e-061.17847e-050.999994
1221.45314e-052.90628e-050.999985
1238.91796e-061.78359e-050.999991
1246.45344e-061.29069e-050.999994
1255.98085e-061.19617e-050.999994
1266.78617e-061.35723e-050.999993
1271.27741e-052.55481e-050.999987
1280.0001618230.0003236450.999838
1290.0003507030.0007014050.999649
1300.0006863750.001372750.999314
1310.0007275760.001455150.999272
1320.0005401510.00108030.99946
1330.0005478540.001095710.999452
1340.002532110.005064210.997468
1350.00223020.00446040.99777
1360.002178640.004357280.997821
1370.00258090.00516180.997419
1380.002355570.004711130.997644
1390.00162640.003252810.998374
1400.001832620.003665240.998167
1410.001373850.002747710.998626
1420.001926190.003852380.998074
1430.001479890.002959790.99852
1440.006189760.01237950.99381
1450.005300960.01060190.994699
1460.004444860.008889710.995555
1470.003292170.006584340.996708
1480.002126620.004253240.997873
1490.001661620.003323240.998338
1500.001221490.002442980.998779
1510.001658090.003316180.998342
1520.01200010.02400020.988
1530.04943420.09886850.950566
1540.05247530.1049510.947525
1550.04550260.09100520.954497
1560.03414880.06829760.965851
1570.1262460.2524920.873754
1580.1158740.2317480.884126
1590.3765750.7531510.623425
1600.3110.6220.689
1610.2473060.4946120.752694
1620.1912570.3825150.808743
1630.1977150.3954310.802285
1640.2092760.4185510.790724
1650.5427080.9145840.457292
1660.6289270.7421460.371073
1670.9240990.1518020.075901
1680.9762530.04749310.0237466
1690.9907150.01856940.00928468
1700.9639420.07211620.0360581







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1250.856164NOK
5% type I error level1300.890411NOK
10% type I error level1340.917808NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 125 & 0.856164 & NOK \tabularnewline
5% type I error level & 130 & 0.890411 & NOK \tabularnewline
10% type I error level & 134 & 0.917808 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232101&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]125[/C][C]0.856164[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]130[/C][C]0.890411[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]134[/C][C]0.917808[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232101&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232101&T=6

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1250.856164NOK
5% type I error level1300.890411NOK
10% type I error level1340.917808NOK



Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}