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 02:26:11 -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/t1386746916o1kuw33zxjhfjq2.htm/, Retrieved Thu, 28 Mar 2024 15:08:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232035, Retrieved Thu, 28 Mar 2024 15:08:52 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ARIMA Backward Selection] [Workshop 9 ARIMA ...] [2013-12-02 12:00:55] [cac6c5fb035463be46c296b46e439cb5]
- RMPD  [Recursive Partitioning (Regression Trees)] [] [2013-12-02 15:58:24] [0307e7a6407eb638caabc417e3a6b260]
- RMP       [Multiple Regression] [] [2013-12-11 07:26:11] [9df62e693988eb4e1e1444ece0578579] [Current]
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Dataseries X:
1 119.992 157.302 74.997 0.00784 0.00007 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 0.00008 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 0.00009 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 0.00009 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 0.00011 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 0.00008 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 0.00003 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 0.00003 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 0.00006 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 0.00006 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 0.00006 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 0.00006 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 0.00002 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 0.00003 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 0.00002 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 0.00003 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 0.00004 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 0.00004 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 0.00005 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 0.00005 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 0.00005 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 0.00003 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 0.00003 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 0.00003 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 0.00005 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 0.00006 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 0.00003 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 0.00003 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 0.00002 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 0.00003 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 0.00001 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 0.00001 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 0.00001 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 0.000009 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 0.000009 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 0.00001 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 0.00002 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 0.00002 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 0.00002 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 0.00002 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 0.00002 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 0.00001 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 0.00001 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 0.00001 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 0.000009 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 0.000009 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 0.00001 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 0.000007 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 0.00004 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 0.00003 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 0.00003 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 0.00004 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 0.00003 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 0.00004 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 0.00007 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 0.00008 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 0.00007 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 0.00006 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 0.00007 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 0.00008 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 0.00001 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 0.00001 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 0.00001 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 0.00001 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 0.000009 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 0.00001 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 0.00006 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 0.00007 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 0.00008 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 0.00005 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 0.00006 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 0.00007 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 0.00003 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 0.00005 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 0.00004 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 0.00005 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 0.00004 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 0.00004 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 0.00006 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 0.0001 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 0.00007 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 0.00007 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 0.00006 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 0.00004 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 0.00004 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 0.00002 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 0.00002 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 0.00003 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 0.00003 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 0.00004 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 0.00004 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 0.00003 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 0.00003 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 0.00003 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 0.00002 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 0.00002 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 0.00002 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 0.0001 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 0.00011 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 0.00015 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 0.00026 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 0.00012 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 0.00022 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 0.00002 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 0.00001 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 0.00002 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 0.00001 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 0.00002 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 0.00001 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 0.00004 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 0.00003 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 0.00003 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 0.00004 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 0.00003 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 0.00002 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 0.00006 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 0.00003 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 0.00003 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 0.00003 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 0.00002 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 0.00005 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 0.00003 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 0.00005 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 0.00005 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 0.00004 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 0.00005 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 0.00004 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 0.00004 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 0.00004 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 0.00002 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 0.00004 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 0.00003 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 0.00003 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 0.00003 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 0.00006 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 0.00004 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 0.00004 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 0.00004 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 0.00004 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 0.00003 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 0.00003 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 0.00004 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 0.00002 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 0.00002 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 0.00001 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 0.00002 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 0.00009 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 0.00008 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 0.00009 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 0.00008 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 0.0001 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 0.00016 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 0.00014 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 0.00006 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 0.00006 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 0.00005 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 0.00006 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 0.00015 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 0.00008 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 0.00005 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 0.00005 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 0.00005 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 0.00006 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 0.00005 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 0.00009 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 0.00001 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 0.00001 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 0.00001 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 0.00004 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 0.00002 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 0.00002 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 0.00003 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 0.00003 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 0.00003 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 0.00003 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 0.00003 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 0.00003 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 0.00002 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 0.00002 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 0.00003 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 0.00003 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 0.00003 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 0.00002 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 0.00004 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 0.00005 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 0.00003 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 0.00004 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 0.00002 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 0.00003 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 0.00003 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 0.00003 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 0.00003 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 0.00008 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 0.00004 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 0.00003 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 time32 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 32 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232035&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]32 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232035&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232035&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 time32 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
status[t] = + 2.22477 -0.00238441`MDVP:Fo(Hz)`[t] -0.00011523`MDVP:Fhi(Hz)`[t] -0.0015351`MDVP:Flo(Hz)`[t] -176.913`MDVP:Jitter(%)`[t] -3321.64`MDVP:Jitter(Abs)`[t] -759.215`MDVP:RAP`[t] -36.1351`MDVP:PPQ`[t] + 360.584`Jitter:DDP`[t] + 27.4496`MDVP:Shimmer`[t] + 0.571023`MDVP:Shimmer(dB)`[t] -871.24`Shimmer:APQ3`[t] -26.3959`Shimmer:APQ5`[t] -3.07476`MDVP:APQ`[t] + 283.748`Shimmer:DDA`[t] -2.52562NHR[t] -0.0156926HNR[t] -1.01446RPDE[t] + 0.355145DFA[t] + 0.127298spread1[t] + 1.26558spread2[t] + 0.0494602D2[t] + 1.26346PPE[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
status[t] =  +  2.22477 -0.00238441`MDVP:Fo(Hz)`[t] -0.00011523`MDVP:Fhi(Hz)`[t] -0.0015351`MDVP:Flo(Hz)`[t] -176.913`MDVP:Jitter(%)`[t] -3321.64`MDVP:Jitter(Abs)`[t] -759.215`MDVP:RAP`[t] -36.1351`MDVP:PPQ`[t] +  360.584`Jitter:DDP`[t] +  27.4496`MDVP:Shimmer`[t] +  0.571023`MDVP:Shimmer(dB)`[t] -871.24`Shimmer:APQ3`[t] -26.3959`Shimmer:APQ5`[t] -3.07476`MDVP:APQ`[t] +  283.748`Shimmer:DDA`[t] -2.52562NHR[t] -0.0156926HNR[t] -1.01446RPDE[t] +  0.355145DFA[t] +  0.127298spread1[t] +  1.26558spread2[t] +  0.0494602D2[t] +  1.26346PPE[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232035&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]status[t] =  +  2.22477 -0.00238441`MDVP:Fo(Hz)`[t] -0.00011523`MDVP:Fhi(Hz)`[t] -0.0015351`MDVP:Flo(Hz)`[t] -176.913`MDVP:Jitter(%)`[t] -3321.64`MDVP:Jitter(Abs)`[t] -759.215`MDVP:RAP`[t] -36.1351`MDVP:PPQ`[t] +  360.584`Jitter:DDP`[t] +  27.4496`MDVP:Shimmer`[t] +  0.571023`MDVP:Shimmer(dB)`[t] -871.24`Shimmer:APQ3`[t] -26.3959`Shimmer:APQ5`[t] -3.07476`MDVP:APQ`[t] +  283.748`Shimmer:DDA`[t] -2.52562NHR[t] -0.0156926HNR[t] -1.01446RPDE[t] +  0.355145DFA[t] +  0.127298spread1[t] +  1.26558spread2[t] +  0.0494602D2[t] +  1.26346PPE[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232035&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232035&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] = + 2.22477 -0.00238441`MDVP:Fo(Hz)`[t] -0.00011523`MDVP:Fhi(Hz)`[t] -0.0015351`MDVP:Flo(Hz)`[t] -176.913`MDVP:Jitter(%)`[t] -3321.64`MDVP:Jitter(Abs)`[t] -759.215`MDVP:RAP`[t] -36.1351`MDVP:PPQ`[t] + 360.584`Jitter:DDP`[t] + 27.4496`MDVP:Shimmer`[t] + 0.571023`MDVP:Shimmer(dB)`[t] -871.24`Shimmer:APQ3`[t] -26.3959`Shimmer:APQ5`[t] -3.07476`MDVP:APQ`[t] + 283.748`Shimmer:DDA`[t] -2.52562NHR[t] -0.0156926HNR[t] -1.01446RPDE[t] + 0.355145DFA[t] + 0.127298spread1[t] + 1.26558spread2[t] + 0.0494602D2[t] + 1.26346PPE[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.224771.158381.9210.0564380.028219
`MDVP:Fo(Hz)`-0.002384410.00151006-1.5790.1161690.0580847
`MDVP:Fhi(Hz)`-0.000115230.000321058-0.35890.7201050.360053
`MDVP:Flo(Hz)`-0.00153510.000802317-1.9130.05736640.0286832
`MDVP:Jitter(%)`-176.91367.0287-2.6390.009069330.00453467
`MDVP:Jitter(Abs)`-3321.644625.65-0.71810.4736760.236838
`MDVP:RAP`-759.2159331.88-0.081360.9352530.467626
`MDVP:PPQ`-36.135188.3839-0.40880.6831630.341582
`Jitter:DDP`360.5843111.480.11590.9078760.453938
`MDVP:Shimmer`27.449634.2830.80070.4244240.212212
`MDVP:Shimmer(dB)`0.5710231.199320.47610.6345910.317295
`Shimmer:APQ3`-871.248972.17-0.09710.9227560.461378
`Shimmer:APQ5`-26.395920.1229-1.3120.1913590.0956797
`MDVP:APQ`-3.0747610.8911-0.28230.7780380.389019
`Shimmer:DDA`283.7482989.960.09490.9245050.462252
NHR-2.525621.98061-1.2750.2039670.101983
HNR-0.01569260.0143431-1.0940.2754440.137722
RPDE-1.014460.439539-2.3080.0221890.0110945
DFA0.3551450.7393820.48030.6316060.315803
spread10.1272980.09789831.30.1952340.0976171
spread21.265580.4780052.6480.008859430.00442971
D20.04946020.1143240.43260.6658240.332912
PPE1.263461.383350.91330.3623460.181173

\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) & 2.22477 & 1.15838 & 1.921 & 0.056438 & 0.028219 \tabularnewline
`MDVP:Fo(Hz)` & -0.00238441 & 0.00151006 & -1.579 & 0.116169 & 0.0580847 \tabularnewline
`MDVP:Fhi(Hz)` & -0.00011523 & 0.000321058 & -0.3589 & 0.720105 & 0.360053 \tabularnewline
`MDVP:Flo(Hz)` & -0.0015351 & 0.000802317 & -1.913 & 0.0573664 & 0.0286832 \tabularnewline
`MDVP:Jitter(%)` & -176.913 & 67.0287 & -2.639 & 0.00906933 & 0.00453467 \tabularnewline
`MDVP:Jitter(Abs)` & -3321.64 & 4625.65 & -0.7181 & 0.473676 & 0.236838 \tabularnewline
`MDVP:RAP` & -759.215 & 9331.88 & -0.08136 & 0.935253 & 0.467626 \tabularnewline
`MDVP:PPQ` & -36.1351 & 88.3839 & -0.4088 & 0.683163 & 0.341582 \tabularnewline
`Jitter:DDP` & 360.584 & 3111.48 & 0.1159 & 0.907876 & 0.453938 \tabularnewline
`MDVP:Shimmer` & 27.4496 & 34.283 & 0.8007 & 0.424424 & 0.212212 \tabularnewline
`MDVP:Shimmer(dB)` & 0.571023 & 1.19932 & 0.4761 & 0.634591 & 0.317295 \tabularnewline
`Shimmer:APQ3` & -871.24 & 8972.17 & -0.0971 & 0.922756 & 0.461378 \tabularnewline
`Shimmer:APQ5` & -26.3959 & 20.1229 & -1.312 & 0.191359 & 0.0956797 \tabularnewline
`MDVP:APQ` & -3.07476 & 10.8911 & -0.2823 & 0.778038 & 0.389019 \tabularnewline
`Shimmer:DDA` & 283.748 & 2989.96 & 0.0949 & 0.924505 & 0.462252 \tabularnewline
NHR & -2.52562 & 1.98061 & -1.275 & 0.203967 & 0.101983 \tabularnewline
HNR & -0.0156926 & 0.0143431 & -1.094 & 0.275444 & 0.137722 \tabularnewline
RPDE & -1.01446 & 0.439539 & -2.308 & 0.022189 & 0.0110945 \tabularnewline
DFA & 0.355145 & 0.739382 & 0.4803 & 0.631606 & 0.315803 \tabularnewline
spread1 & 0.127298 & 0.0978983 & 1.3 & 0.195234 & 0.0976171 \tabularnewline
spread2 & 1.26558 & 0.478005 & 2.648 & 0.00885943 & 0.00442971 \tabularnewline
D2 & 0.0494602 & 0.114324 & 0.4326 & 0.665824 & 0.332912 \tabularnewline
PPE & 1.26346 & 1.38335 & 0.9133 & 0.362346 & 0.181173 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232035&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]2.22477[/C][C]1.15838[/C][C]1.921[/C][C]0.056438[/C][C]0.028219[/C][/ROW]
[ROW][C]`MDVP:Fo(Hz)`[/C][C]-0.00238441[/C][C]0.00151006[/C][C]-1.579[/C][C]0.116169[/C][C]0.0580847[/C][/ROW]
[ROW][C]`MDVP:Fhi(Hz)`[/C][C]-0.00011523[/C][C]0.000321058[/C][C]-0.3589[/C][C]0.720105[/C][C]0.360053[/C][/ROW]
[ROW][C]`MDVP:Flo(Hz)`[/C][C]-0.0015351[/C][C]0.000802317[/C][C]-1.913[/C][C]0.0573664[/C][C]0.0286832[/C][/ROW]
[ROW][C]`MDVP:Jitter(%)`[/C][C]-176.913[/C][C]67.0287[/C][C]-2.639[/C][C]0.00906933[/C][C]0.00453467[/C][/ROW]
[ROW][C]`MDVP:Jitter(Abs)`[/C][C]-3321.64[/C][C]4625.65[/C][C]-0.7181[/C][C]0.473676[/C][C]0.236838[/C][/ROW]
[ROW][C]`MDVP:RAP`[/C][C]-759.215[/C][C]9331.88[/C][C]-0.08136[/C][C]0.935253[/C][C]0.467626[/C][/ROW]
[ROW][C]`MDVP:PPQ`[/C][C]-36.1351[/C][C]88.3839[/C][C]-0.4088[/C][C]0.683163[/C][C]0.341582[/C][/ROW]
[ROW][C]`Jitter:DDP`[/C][C]360.584[/C][C]3111.48[/C][C]0.1159[/C][C]0.907876[/C][C]0.453938[/C][/ROW]
[ROW][C]`MDVP:Shimmer`[/C][C]27.4496[/C][C]34.283[/C][C]0.8007[/C][C]0.424424[/C][C]0.212212[/C][/ROW]
[ROW][C]`MDVP:Shimmer(dB)`[/C][C]0.571023[/C][C]1.19932[/C][C]0.4761[/C][C]0.634591[/C][C]0.317295[/C][/ROW]
[ROW][C]`Shimmer:APQ3`[/C][C]-871.24[/C][C]8972.17[/C][C]-0.0971[/C][C]0.922756[/C][C]0.461378[/C][/ROW]
[ROW][C]`Shimmer:APQ5`[/C][C]-26.3959[/C][C]20.1229[/C][C]-1.312[/C][C]0.191359[/C][C]0.0956797[/C][/ROW]
[ROW][C]`MDVP:APQ`[/C][C]-3.07476[/C][C]10.8911[/C][C]-0.2823[/C][C]0.778038[/C][C]0.389019[/C][/ROW]
[ROW][C]`Shimmer:DDA`[/C][C]283.748[/C][C]2989.96[/C][C]0.0949[/C][C]0.924505[/C][C]0.462252[/C][/ROW]
[ROW][C]NHR[/C][C]-2.52562[/C][C]1.98061[/C][C]-1.275[/C][C]0.203967[/C][C]0.101983[/C][/ROW]
[ROW][C]HNR[/C][C]-0.0156926[/C][C]0.0143431[/C][C]-1.094[/C][C]0.275444[/C][C]0.137722[/C][/ROW]
[ROW][C]RPDE[/C][C]-1.01446[/C][C]0.439539[/C][C]-2.308[/C][C]0.022189[/C][C]0.0110945[/C][/ROW]
[ROW][C]DFA[/C][C]0.355145[/C][C]0.739382[/C][C]0.4803[/C][C]0.631606[/C][C]0.315803[/C][/ROW]
[ROW][C]spread1[/C][C]0.127298[/C][C]0.0978983[/C][C]1.3[/C][C]0.195234[/C][C]0.0976171[/C][/ROW]
[ROW][C]spread2[/C][C]1.26558[/C][C]0.478005[/C][C]2.648[/C][C]0.00885943[/C][C]0.00442971[/C][/ROW]
[ROW][C]D2[/C][C]0.0494602[/C][C]0.114324[/C][C]0.4326[/C][C]0.665824[/C][C]0.332912[/C][/ROW]
[ROW][C]PPE[/C][C]1.26346[/C][C]1.38335[/C][C]0.9133[/C][C]0.362346[/C][C]0.181173[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232035&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232035&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)2.224771.158381.9210.0564380.028219
`MDVP:Fo(Hz)`-0.002384410.00151006-1.5790.1161690.0580847
`MDVP:Fhi(Hz)`-0.000115230.000321058-0.35890.7201050.360053
`MDVP:Flo(Hz)`-0.00153510.000802317-1.9130.05736640.0286832
`MDVP:Jitter(%)`-176.91367.0287-2.6390.009069330.00453467
`MDVP:Jitter(Abs)`-3321.644625.65-0.71810.4736760.236838
`MDVP:RAP`-759.2159331.88-0.081360.9352530.467626
`MDVP:PPQ`-36.135188.3839-0.40880.6831630.341582
`Jitter:DDP`360.5843111.480.11590.9078760.453938
`MDVP:Shimmer`27.449634.2830.80070.4244240.212212
`MDVP:Shimmer(dB)`0.5710231.199320.47610.6345910.317295
`Shimmer:APQ3`-871.248972.17-0.09710.9227560.461378
`Shimmer:APQ5`-26.395920.1229-1.3120.1913590.0956797
`MDVP:APQ`-3.0747610.8911-0.28230.7780380.389019
`Shimmer:DDA`283.7482989.960.09490.9245050.462252
NHR-2.525621.98061-1.2750.2039670.101983
HNR-0.01569260.0143431-1.0940.2754440.137722
RPDE-1.014460.439539-2.3080.0221890.0110945
DFA0.3551450.7393820.48030.6316060.315803
spread10.1272980.09789831.30.1952340.0976171
spread21.265580.4780052.6480.008859430.00442971
D20.04946020.1143240.43260.6658240.332912
PPE1.263461.383350.91330.3623460.181173







Multiple Linear Regression - Regression Statistics
Multiple R0.701957
R-squared0.492744
Adjusted R-squared0.427862
F-TEST (value)7.5945
F-TEST (DF numerator)22
F-TEST (DF denominator)172
p-value4.44089e-16
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.326672
Sum Squared Residuals18.3549

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.701957 \tabularnewline
R-squared & 0.492744 \tabularnewline
Adjusted R-squared & 0.427862 \tabularnewline
F-TEST (value) & 7.5945 \tabularnewline
F-TEST (DF numerator) & 22 \tabularnewline
F-TEST (DF denominator) & 172 \tabularnewline
p-value & 4.44089e-16 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.326672 \tabularnewline
Sum Squared Residuals & 18.3549 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232035&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.701957[/C][/ROW]
[ROW][C]R-squared[/C][C]0.492744[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.427862[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]7.5945[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]22[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]172[/C][/ROW]
[ROW][C]p-value[/C][C]4.44089e-16[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.326672[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]18.3549[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232035&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232035&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 R0.701957
R-squared0.492744
Adjusted R-squared0.427862
F-TEST (value)7.5945
F-TEST (DF numerator)22
F-TEST (DF denominator)172
p-value4.44089e-16
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.326672
Sum Squared Residuals18.3549







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
110.9435720.0564281
211.07059-0.0705872
310.9726110.0273892
411.07778-0.0777826
510.8710340.128966
610.9494550.0505448
710.7934060.206594
810.5806750.419325
910.9746030.0253974
1011.15091-0.15091
1111.1116-0.111599
1211.23811-0.238106
1310.4568820.543118
1410.8801520.119848
1510.7048460.295154
1610.7027110.297289
1710.5444420.455558
1811.32292-0.322915
1911.29341-0.293412
2010.9660640.0339362
2111.06595-0.0659459
2210.8904740.109526
2311.10343-0.103432
2410.8657710.134229
2510.8203590.179641
2610.9174090.0825911
2710.8040190.195981
2810.79590.2041
2910.6613960.338604
3010.6993240.300676
3100.296327-0.296327
3200.159359-0.159359
3300.192351-0.192351
3400.128086-0.128086
3500.0881745-0.0881745
3600.203628-0.203628
3710.8106940.189306
3810.8234620.176538
3910.5960430.403957
4010.7530910.246909
4110.6125960.387404
4210.4365020.563498
4300.244621-0.244621
4400.204235-0.204235
4500.0134396-0.0134396
4600.0888887-0.0888887
4700.0510556-0.0510556
480-0.04546860.0454686
4900.337463-0.337463
5000.429479-0.429479
5100.410612-0.410612
5200.425916-0.425916
5300.411523-0.411523
5400.548472-0.548472
5510.8271240.172876
5610.7915550.208445
5710.8674140.132586
5810.759890.24011
5910.779280.22072
6010.6508120.349188
6100.369771-0.369771
6200.274652-0.274652
6300.264476-0.264476
6400.213607-0.213607
6500.128336-0.128336
6600.282276-0.282276
6710.914780.08522
6810.8891040.110896
6910.922250.0777504
7010.9423690.0576308
7110.8508480.149152
7211.093-0.0929953
7310.8872190.112781
7410.9229350.0770649
7511.04227-0.0422683
7611.07861-0.078614
7711.09858-0.0985769
7811.00048-0.00048325
7910.9611320.0388676
8011.14127-0.141275
8111.18014-0.180144
8211.13522-0.13522
8311.01365-0.0136507
8410.6959870.304013
8511.08754-0.08754
8610.8714690.128531
8710.7031310.296869
8810.9446410.0553591
8910.9903410.00965934
9011.22525-0.22525
9111.14447-0.144466
9210.7974710.202529
9310.7336720.266328
9410.8532560.146744
9510.7885590.211441
9610.7576720.242328
9710.8030070.196993
9811.0269-0.0269041
9910.7997390.200261
10010.8970690.102931
10110.9638530.0361472
10210.9738050.0261952
10310.9889170.011083
10410.5857750.414225
10510.5806650.419335
10610.5672640.432736
10710.5352890.464711
10810.6901040.309896
10910.6173620.382638
11010.8984210.101579
11111.03499-0.0349901
11210.5899890.410011
11310.8016310.198369
11410.6988710.301129
11510.8022250.197775
11610.8850940.114906
11710.7288940.271106
11811.05186-0.051857
11910.8860640.113936
12010.7616010.238399
12110.551530.44847
12210.9736330.0263668
12310.9728490.0271515
12410.7106010.289399
12510.618210.38179
12610.6246210.375379
12710.6126390.387361
12810.6275850.372415
12910.4149320.585068
13010.7652490.234751
13110.8031170.196883
13210.8749580.125042
13311.05332-0.0533167
13410.647040.35296
13510.9632820.0367176
13610.9615150.0384847
13711.14637-0.146369
13811.15063-0.150628
13910.9597530.0402465
14010.781480.21852
14110.9100850.0899151
14210.8582980.141702
14310.7289950.271005
14410.6828260.317174
14510.5493930.450607
14610.8602330.139767
14711.35151-0.351514
14811.15229-0.152285
14911.24477-0.244774
15010.8937020.106298
15110.9342530.065747
15210.9559320.0440683
15310.959080.0409204
15410.8454060.154594
15510.8944390.105561
15610.9948170.00518265
15710.7986840.201316
15811.2687-0.268698
15910.9707470.0292526
16010.86190.1381
16111.12813-0.128132
16211.05871-0.0587125
16310.9308250.0691748
16410.7941760.205824
16511.38244-0.382443
16600.450212-0.450212
16700.225191-0.225191
16800.0938475-0.0938475
16900.941843-0.941843
17000.230278-0.230278
17100.114576-0.114576
17200.799341-0.799341
17300.835874-0.835874
17400.878334-0.878334
17500.86601-0.86601
17600.834631-0.834631
17700.776849-0.776849
17810.644340.35566
17910.7122330.287767
18010.9343240.0656761
18110.7639790.236021
18210.8724260.127574
18310.7191930.280807
18400.604386-0.604386
18500.648463-0.648463
18600.606784-0.606784
18700.423249-0.423249
18800.475362-0.475362
18900.435997-0.435997
19000.428277-0.428277
19100.651129-0.651129
19200.700978-0.700978
1930-0.1745040.174504
19400.267081-0.267081
19500.519415-0.519415

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1 & 0.943572 & 0.0564281 \tabularnewline
2 & 1 & 1.07059 & -0.0705872 \tabularnewline
3 & 1 & 0.972611 & 0.0273892 \tabularnewline
4 & 1 & 1.07778 & -0.0777826 \tabularnewline
5 & 1 & 0.871034 & 0.128966 \tabularnewline
6 & 1 & 0.949455 & 0.0505448 \tabularnewline
7 & 1 & 0.793406 & 0.206594 \tabularnewline
8 & 1 & 0.580675 & 0.419325 \tabularnewline
9 & 1 & 0.974603 & 0.0253974 \tabularnewline
10 & 1 & 1.15091 & -0.15091 \tabularnewline
11 & 1 & 1.1116 & -0.111599 \tabularnewline
12 & 1 & 1.23811 & -0.238106 \tabularnewline
13 & 1 & 0.456882 & 0.543118 \tabularnewline
14 & 1 & 0.880152 & 0.119848 \tabularnewline
15 & 1 & 0.704846 & 0.295154 \tabularnewline
16 & 1 & 0.702711 & 0.297289 \tabularnewline
17 & 1 & 0.544442 & 0.455558 \tabularnewline
18 & 1 & 1.32292 & -0.322915 \tabularnewline
19 & 1 & 1.29341 & -0.293412 \tabularnewline
20 & 1 & 0.966064 & 0.0339362 \tabularnewline
21 & 1 & 1.06595 & -0.0659459 \tabularnewline
22 & 1 & 0.890474 & 0.109526 \tabularnewline
23 & 1 & 1.10343 & -0.103432 \tabularnewline
24 & 1 & 0.865771 & 0.134229 \tabularnewline
25 & 1 & 0.820359 & 0.179641 \tabularnewline
26 & 1 & 0.917409 & 0.0825911 \tabularnewline
27 & 1 & 0.804019 & 0.195981 \tabularnewline
28 & 1 & 0.7959 & 0.2041 \tabularnewline
29 & 1 & 0.661396 & 0.338604 \tabularnewline
30 & 1 & 0.699324 & 0.300676 \tabularnewline
31 & 0 & 0.296327 & -0.296327 \tabularnewline
32 & 0 & 0.159359 & -0.159359 \tabularnewline
33 & 0 & 0.192351 & -0.192351 \tabularnewline
34 & 0 & 0.128086 & -0.128086 \tabularnewline
35 & 0 & 0.0881745 & -0.0881745 \tabularnewline
36 & 0 & 0.203628 & -0.203628 \tabularnewline
37 & 1 & 0.810694 & 0.189306 \tabularnewline
38 & 1 & 0.823462 & 0.176538 \tabularnewline
39 & 1 & 0.596043 & 0.403957 \tabularnewline
40 & 1 & 0.753091 & 0.246909 \tabularnewline
41 & 1 & 0.612596 & 0.387404 \tabularnewline
42 & 1 & 0.436502 & 0.563498 \tabularnewline
43 & 0 & 0.244621 & -0.244621 \tabularnewline
44 & 0 & 0.204235 & -0.204235 \tabularnewline
45 & 0 & 0.0134396 & -0.0134396 \tabularnewline
46 & 0 & 0.0888887 & -0.0888887 \tabularnewline
47 & 0 & 0.0510556 & -0.0510556 \tabularnewline
48 & 0 & -0.0454686 & 0.0454686 \tabularnewline
49 & 0 & 0.337463 & -0.337463 \tabularnewline
50 & 0 & 0.429479 & -0.429479 \tabularnewline
51 & 0 & 0.410612 & -0.410612 \tabularnewline
52 & 0 & 0.425916 & -0.425916 \tabularnewline
53 & 0 & 0.411523 & -0.411523 \tabularnewline
54 & 0 & 0.548472 & -0.548472 \tabularnewline
55 & 1 & 0.827124 & 0.172876 \tabularnewline
56 & 1 & 0.791555 & 0.208445 \tabularnewline
57 & 1 & 0.867414 & 0.132586 \tabularnewline
58 & 1 & 0.75989 & 0.24011 \tabularnewline
59 & 1 & 0.77928 & 0.22072 \tabularnewline
60 & 1 & 0.650812 & 0.349188 \tabularnewline
61 & 0 & 0.369771 & -0.369771 \tabularnewline
62 & 0 & 0.274652 & -0.274652 \tabularnewline
63 & 0 & 0.264476 & -0.264476 \tabularnewline
64 & 0 & 0.213607 & -0.213607 \tabularnewline
65 & 0 & 0.128336 & -0.128336 \tabularnewline
66 & 0 & 0.282276 & -0.282276 \tabularnewline
67 & 1 & 0.91478 & 0.08522 \tabularnewline
68 & 1 & 0.889104 & 0.110896 \tabularnewline
69 & 1 & 0.92225 & 0.0777504 \tabularnewline
70 & 1 & 0.942369 & 0.0576308 \tabularnewline
71 & 1 & 0.850848 & 0.149152 \tabularnewline
72 & 1 & 1.093 & -0.0929953 \tabularnewline
73 & 1 & 0.887219 & 0.112781 \tabularnewline
74 & 1 & 0.922935 & 0.0770649 \tabularnewline
75 & 1 & 1.04227 & -0.0422683 \tabularnewline
76 & 1 & 1.07861 & -0.078614 \tabularnewline
77 & 1 & 1.09858 & -0.0985769 \tabularnewline
78 & 1 & 1.00048 & -0.00048325 \tabularnewline
79 & 1 & 0.961132 & 0.0388676 \tabularnewline
80 & 1 & 1.14127 & -0.141275 \tabularnewline
81 & 1 & 1.18014 & -0.180144 \tabularnewline
82 & 1 & 1.13522 & -0.13522 \tabularnewline
83 & 1 & 1.01365 & -0.0136507 \tabularnewline
84 & 1 & 0.695987 & 0.304013 \tabularnewline
85 & 1 & 1.08754 & -0.08754 \tabularnewline
86 & 1 & 0.871469 & 0.128531 \tabularnewline
87 & 1 & 0.703131 & 0.296869 \tabularnewline
88 & 1 & 0.944641 & 0.0553591 \tabularnewline
89 & 1 & 0.990341 & 0.00965934 \tabularnewline
90 & 1 & 1.22525 & -0.22525 \tabularnewline
91 & 1 & 1.14447 & -0.144466 \tabularnewline
92 & 1 & 0.797471 & 0.202529 \tabularnewline
93 & 1 & 0.733672 & 0.266328 \tabularnewline
94 & 1 & 0.853256 & 0.146744 \tabularnewline
95 & 1 & 0.788559 & 0.211441 \tabularnewline
96 & 1 & 0.757672 & 0.242328 \tabularnewline
97 & 1 & 0.803007 & 0.196993 \tabularnewline
98 & 1 & 1.0269 & -0.0269041 \tabularnewline
99 & 1 & 0.799739 & 0.200261 \tabularnewline
100 & 1 & 0.897069 & 0.102931 \tabularnewline
101 & 1 & 0.963853 & 0.0361472 \tabularnewline
102 & 1 & 0.973805 & 0.0261952 \tabularnewline
103 & 1 & 0.988917 & 0.011083 \tabularnewline
104 & 1 & 0.585775 & 0.414225 \tabularnewline
105 & 1 & 0.580665 & 0.419335 \tabularnewline
106 & 1 & 0.567264 & 0.432736 \tabularnewline
107 & 1 & 0.535289 & 0.464711 \tabularnewline
108 & 1 & 0.690104 & 0.309896 \tabularnewline
109 & 1 & 0.617362 & 0.382638 \tabularnewline
110 & 1 & 0.898421 & 0.101579 \tabularnewline
111 & 1 & 1.03499 & -0.0349901 \tabularnewline
112 & 1 & 0.589989 & 0.410011 \tabularnewline
113 & 1 & 0.801631 & 0.198369 \tabularnewline
114 & 1 & 0.698871 & 0.301129 \tabularnewline
115 & 1 & 0.802225 & 0.197775 \tabularnewline
116 & 1 & 0.885094 & 0.114906 \tabularnewline
117 & 1 & 0.728894 & 0.271106 \tabularnewline
118 & 1 & 1.05186 & -0.051857 \tabularnewline
119 & 1 & 0.886064 & 0.113936 \tabularnewline
120 & 1 & 0.761601 & 0.238399 \tabularnewline
121 & 1 & 0.55153 & 0.44847 \tabularnewline
122 & 1 & 0.973633 & 0.0263668 \tabularnewline
123 & 1 & 0.972849 & 0.0271515 \tabularnewline
124 & 1 & 0.710601 & 0.289399 \tabularnewline
125 & 1 & 0.61821 & 0.38179 \tabularnewline
126 & 1 & 0.624621 & 0.375379 \tabularnewline
127 & 1 & 0.612639 & 0.387361 \tabularnewline
128 & 1 & 0.627585 & 0.372415 \tabularnewline
129 & 1 & 0.414932 & 0.585068 \tabularnewline
130 & 1 & 0.765249 & 0.234751 \tabularnewline
131 & 1 & 0.803117 & 0.196883 \tabularnewline
132 & 1 & 0.874958 & 0.125042 \tabularnewline
133 & 1 & 1.05332 & -0.0533167 \tabularnewline
134 & 1 & 0.64704 & 0.35296 \tabularnewline
135 & 1 & 0.963282 & 0.0367176 \tabularnewline
136 & 1 & 0.961515 & 0.0384847 \tabularnewline
137 & 1 & 1.14637 & -0.146369 \tabularnewline
138 & 1 & 1.15063 & -0.150628 \tabularnewline
139 & 1 & 0.959753 & 0.0402465 \tabularnewline
140 & 1 & 0.78148 & 0.21852 \tabularnewline
141 & 1 & 0.910085 & 0.0899151 \tabularnewline
142 & 1 & 0.858298 & 0.141702 \tabularnewline
143 & 1 & 0.728995 & 0.271005 \tabularnewline
144 & 1 & 0.682826 & 0.317174 \tabularnewline
145 & 1 & 0.549393 & 0.450607 \tabularnewline
146 & 1 & 0.860233 & 0.139767 \tabularnewline
147 & 1 & 1.35151 & -0.351514 \tabularnewline
148 & 1 & 1.15229 & -0.152285 \tabularnewline
149 & 1 & 1.24477 & -0.244774 \tabularnewline
150 & 1 & 0.893702 & 0.106298 \tabularnewline
151 & 1 & 0.934253 & 0.065747 \tabularnewline
152 & 1 & 0.955932 & 0.0440683 \tabularnewline
153 & 1 & 0.95908 & 0.0409204 \tabularnewline
154 & 1 & 0.845406 & 0.154594 \tabularnewline
155 & 1 & 0.894439 & 0.105561 \tabularnewline
156 & 1 & 0.994817 & 0.00518265 \tabularnewline
157 & 1 & 0.798684 & 0.201316 \tabularnewline
158 & 1 & 1.2687 & -0.268698 \tabularnewline
159 & 1 & 0.970747 & 0.0292526 \tabularnewline
160 & 1 & 0.8619 & 0.1381 \tabularnewline
161 & 1 & 1.12813 & -0.128132 \tabularnewline
162 & 1 & 1.05871 & -0.0587125 \tabularnewline
163 & 1 & 0.930825 & 0.0691748 \tabularnewline
164 & 1 & 0.794176 & 0.205824 \tabularnewline
165 & 1 & 1.38244 & -0.382443 \tabularnewline
166 & 0 & 0.450212 & -0.450212 \tabularnewline
167 & 0 & 0.225191 & -0.225191 \tabularnewline
168 & 0 & 0.0938475 & -0.0938475 \tabularnewline
169 & 0 & 0.941843 & -0.941843 \tabularnewline
170 & 0 & 0.230278 & -0.230278 \tabularnewline
171 & 0 & 0.114576 & -0.114576 \tabularnewline
172 & 0 & 0.799341 & -0.799341 \tabularnewline
173 & 0 & 0.835874 & -0.835874 \tabularnewline
174 & 0 & 0.878334 & -0.878334 \tabularnewline
175 & 0 & 0.86601 & -0.86601 \tabularnewline
176 & 0 & 0.834631 & -0.834631 \tabularnewline
177 & 0 & 0.776849 & -0.776849 \tabularnewline
178 & 1 & 0.64434 & 0.35566 \tabularnewline
179 & 1 & 0.712233 & 0.287767 \tabularnewline
180 & 1 & 0.934324 & 0.0656761 \tabularnewline
181 & 1 & 0.763979 & 0.236021 \tabularnewline
182 & 1 & 0.872426 & 0.127574 \tabularnewline
183 & 1 & 0.719193 & 0.280807 \tabularnewline
184 & 0 & 0.604386 & -0.604386 \tabularnewline
185 & 0 & 0.648463 & -0.648463 \tabularnewline
186 & 0 & 0.606784 & -0.606784 \tabularnewline
187 & 0 & 0.423249 & -0.423249 \tabularnewline
188 & 0 & 0.475362 & -0.475362 \tabularnewline
189 & 0 & 0.435997 & -0.435997 \tabularnewline
190 & 0 & 0.428277 & -0.428277 \tabularnewline
191 & 0 & 0.651129 & -0.651129 \tabularnewline
192 & 0 & 0.700978 & -0.700978 \tabularnewline
193 & 0 & -0.174504 & 0.174504 \tabularnewline
194 & 0 & 0.267081 & -0.267081 \tabularnewline
195 & 0 & 0.519415 & -0.519415 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232035&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]0.943572[/C][C]0.0564281[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]1.07059[/C][C]-0.0705872[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]0.972611[/C][C]0.0273892[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]1.07778[/C][C]-0.0777826[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]0.871034[/C][C]0.128966[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.949455[/C][C]0.0505448[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.793406[/C][C]0.206594[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.580675[/C][C]0.419325[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.974603[/C][C]0.0253974[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]1.15091[/C][C]-0.15091[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]1.1116[/C][C]-0.111599[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]1.23811[/C][C]-0.238106[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.456882[/C][C]0.543118[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]0.880152[/C][C]0.119848[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.704846[/C][C]0.295154[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]0.702711[/C][C]0.297289[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.544442[/C][C]0.455558[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]1.32292[/C][C]-0.322915[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]1.29341[/C][C]-0.293412[/C][/ROW]
[ROW][C]20[/C][C]1[/C][C]0.966064[/C][C]0.0339362[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]1.06595[/C][C]-0.0659459[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.890474[/C][C]0.109526[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]1.10343[/C][C]-0.103432[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.865771[/C][C]0.134229[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.820359[/C][C]0.179641[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.917409[/C][C]0.0825911[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.804019[/C][C]0.195981[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]0.7959[/C][C]0.2041[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.661396[/C][C]0.338604[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]0.699324[/C][C]0.300676[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0.296327[/C][C]-0.296327[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0.159359[/C][C]-0.159359[/C][/ROW]
[ROW][C]33[/C][C]0[/C][C]0.192351[/C][C]-0.192351[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]0.128086[/C][C]-0.128086[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0.0881745[/C][C]-0.0881745[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0.203628[/C][C]-0.203628[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]0.810694[/C][C]0.189306[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.823462[/C][C]0.176538[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.596043[/C][C]0.403957[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]0.753091[/C][C]0.246909[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.612596[/C][C]0.387404[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.436502[/C][C]0.563498[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0.244621[/C][C]-0.244621[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0.204235[/C][C]-0.204235[/C][/ROW]
[ROW][C]45[/C][C]0[/C][C]0.0134396[/C][C]-0.0134396[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0.0888887[/C][C]-0.0888887[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0.0510556[/C][C]-0.0510556[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]-0.0454686[/C][C]0.0454686[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0.337463[/C][C]-0.337463[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0.429479[/C][C]-0.429479[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]0.410612[/C][C]-0.410612[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0.425916[/C][C]-0.425916[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0.411523[/C][C]-0.411523[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0.548472[/C][C]-0.548472[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.827124[/C][C]0.172876[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]0.791555[/C][C]0.208445[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]0.867414[/C][C]0.132586[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.75989[/C][C]0.24011[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]0.77928[/C][C]0.22072[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.650812[/C][C]0.349188[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0.369771[/C][C]-0.369771[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0.274652[/C][C]-0.274652[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0.264476[/C][C]-0.264476[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0.213607[/C][C]-0.213607[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0.128336[/C][C]-0.128336[/C][/ROW]
[ROW][C]66[/C][C]0[/C][C]0.282276[/C][C]-0.282276[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.91478[/C][C]0.08522[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]0.889104[/C][C]0.110896[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]0.92225[/C][C]0.0777504[/C][/ROW]
[ROW][C]70[/C][C]1[/C][C]0.942369[/C][C]0.0576308[/C][/ROW]
[ROW][C]71[/C][C]1[/C][C]0.850848[/C][C]0.149152[/C][/ROW]
[ROW][C]72[/C][C]1[/C][C]1.093[/C][C]-0.0929953[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]0.887219[/C][C]0.112781[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.922935[/C][C]0.0770649[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]1.04227[/C][C]-0.0422683[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]1.07861[/C][C]-0.078614[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]1.09858[/C][C]-0.0985769[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]1.00048[/C][C]-0.00048325[/C][/ROW]
[ROW][C]79[/C][C]1[/C][C]0.961132[/C][C]0.0388676[/C][/ROW]
[ROW][C]80[/C][C]1[/C][C]1.14127[/C][C]-0.141275[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]1.18014[/C][C]-0.180144[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]1.13522[/C][C]-0.13522[/C][/ROW]
[ROW][C]83[/C][C]1[/C][C]1.01365[/C][C]-0.0136507[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]0.695987[/C][C]0.304013[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]1.08754[/C][C]-0.08754[/C][/ROW]
[ROW][C]86[/C][C]1[/C][C]0.871469[/C][C]0.128531[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.703131[/C][C]0.296869[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]0.944641[/C][C]0.0553591[/C][/ROW]
[ROW][C]89[/C][C]1[/C][C]0.990341[/C][C]0.00965934[/C][/ROW]
[ROW][C]90[/C][C]1[/C][C]1.22525[/C][C]-0.22525[/C][/ROW]
[ROW][C]91[/C][C]1[/C][C]1.14447[/C][C]-0.144466[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]0.797471[/C][C]0.202529[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.733672[/C][C]0.266328[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]0.853256[/C][C]0.146744[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]0.788559[/C][C]0.211441[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.757672[/C][C]0.242328[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]0.803007[/C][C]0.196993[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]1.0269[/C][C]-0.0269041[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]0.799739[/C][C]0.200261[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]0.897069[/C][C]0.102931[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]0.963853[/C][C]0.0361472[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]0.973805[/C][C]0.0261952[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]0.988917[/C][C]0.011083[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.585775[/C][C]0.414225[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]0.580665[/C][C]0.419335[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]0.567264[/C][C]0.432736[/C][/ROW]
[ROW][C]107[/C][C]1[/C][C]0.535289[/C][C]0.464711[/C][/ROW]
[ROW][C]108[/C][C]1[/C][C]0.690104[/C][C]0.309896[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]0.617362[/C][C]0.382638[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]0.898421[/C][C]0.101579[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]1.03499[/C][C]-0.0349901[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]0.589989[/C][C]0.410011[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.801631[/C][C]0.198369[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.698871[/C][C]0.301129[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.802225[/C][C]0.197775[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.885094[/C][C]0.114906[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.728894[/C][C]0.271106[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]1.05186[/C][C]-0.051857[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.886064[/C][C]0.113936[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.761601[/C][C]0.238399[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]0.55153[/C][C]0.44847[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]0.973633[/C][C]0.0263668[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]0.972849[/C][C]0.0271515[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.710601[/C][C]0.289399[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.61821[/C][C]0.38179[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.624621[/C][C]0.375379[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.612639[/C][C]0.387361[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.627585[/C][C]0.372415[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.414932[/C][C]0.585068[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.765249[/C][C]0.234751[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.803117[/C][C]0.196883[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]0.874958[/C][C]0.125042[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]1.05332[/C][C]-0.0533167[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.64704[/C][C]0.35296[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]0.963282[/C][C]0.0367176[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]0.961515[/C][C]0.0384847[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]1.14637[/C][C]-0.146369[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]1.15063[/C][C]-0.150628[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]0.959753[/C][C]0.0402465[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.78148[/C][C]0.21852[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.910085[/C][C]0.0899151[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.858298[/C][C]0.141702[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.728995[/C][C]0.271005[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.682826[/C][C]0.317174[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.549393[/C][C]0.450607[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]0.860233[/C][C]0.139767[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]1.35151[/C][C]-0.351514[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]1.15229[/C][C]-0.152285[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]1.24477[/C][C]-0.244774[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.893702[/C][C]0.106298[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]0.934253[/C][C]0.065747[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]0.955932[/C][C]0.0440683[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]0.95908[/C][C]0.0409204[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.845406[/C][C]0.154594[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]0.894439[/C][C]0.105561[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.994817[/C][C]0.00518265[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.798684[/C][C]0.201316[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]1.2687[/C][C]-0.268698[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]0.970747[/C][C]0.0292526[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]0.8619[/C][C]0.1381[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]1.12813[/C][C]-0.128132[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]1.05871[/C][C]-0.0587125[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0.930825[/C][C]0.0691748[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]0.794176[/C][C]0.205824[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]1.38244[/C][C]-0.382443[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.450212[/C][C]-0.450212[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.225191[/C][C]-0.225191[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.0938475[/C][C]-0.0938475[/C][/ROW]
[ROW][C]169[/C][C]0[/C][C]0.941843[/C][C]-0.941843[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.230278[/C][C]-0.230278[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.114576[/C][C]-0.114576[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.799341[/C][C]-0.799341[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.835874[/C][C]-0.835874[/C][/ROW]
[ROW][C]174[/C][C]0[/C][C]0.878334[/C][C]-0.878334[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.86601[/C][C]-0.86601[/C][/ROW]
[ROW][C]176[/C][C]0[/C][C]0.834631[/C][C]-0.834631[/C][/ROW]
[ROW][C]177[/C][C]0[/C][C]0.776849[/C][C]-0.776849[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0.64434[/C][C]0.35566[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]0.712233[/C][C]0.287767[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0.934324[/C][C]0.0656761[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]0.763979[/C][C]0.236021[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]0.872426[/C][C]0.127574[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0.719193[/C][C]0.280807[/C][/ROW]
[ROW][C]184[/C][C]0[/C][C]0.604386[/C][C]-0.604386[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]0.648463[/C][C]-0.648463[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]0.606784[/C][C]-0.606784[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.423249[/C][C]-0.423249[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.475362[/C][C]-0.475362[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.435997[/C][C]-0.435997[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.428277[/C][C]-0.428277[/C][/ROW]
[ROW][C]191[/C][C]0[/C][C]0.651129[/C][C]-0.651129[/C][/ROW]
[ROW][C]192[/C][C]0[/C][C]0.700978[/C][C]-0.700978[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]-0.174504[/C][C]0.174504[/C][/ROW]
[ROW][C]194[/C][C]0[/C][C]0.267081[/C][C]-0.267081[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.519415[/C][C]-0.519415[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232035&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232035&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
110.9435720.0564281
211.07059-0.0705872
310.9726110.0273892
411.07778-0.0777826
510.8710340.128966
610.9494550.0505448
710.7934060.206594
810.5806750.419325
910.9746030.0253974
1011.15091-0.15091
1111.1116-0.111599
1211.23811-0.238106
1310.4568820.543118
1410.8801520.119848
1510.7048460.295154
1610.7027110.297289
1710.5444420.455558
1811.32292-0.322915
1911.29341-0.293412
2010.9660640.0339362
2111.06595-0.0659459
2210.8904740.109526
2311.10343-0.103432
2410.8657710.134229
2510.8203590.179641
2610.9174090.0825911
2710.8040190.195981
2810.79590.2041
2910.6613960.338604
3010.6993240.300676
3100.296327-0.296327
3200.159359-0.159359
3300.192351-0.192351
3400.128086-0.128086
3500.0881745-0.0881745
3600.203628-0.203628
3710.8106940.189306
3810.8234620.176538
3910.5960430.403957
4010.7530910.246909
4110.6125960.387404
4210.4365020.563498
4300.244621-0.244621
4400.204235-0.204235
4500.0134396-0.0134396
4600.0888887-0.0888887
4700.0510556-0.0510556
480-0.04546860.0454686
4900.337463-0.337463
5000.429479-0.429479
5100.410612-0.410612
5200.425916-0.425916
5300.411523-0.411523
5400.548472-0.548472
5510.8271240.172876
5610.7915550.208445
5710.8674140.132586
5810.759890.24011
5910.779280.22072
6010.6508120.349188
6100.369771-0.369771
6200.274652-0.274652
6300.264476-0.264476
6400.213607-0.213607
6500.128336-0.128336
6600.282276-0.282276
6710.914780.08522
6810.8891040.110896
6910.922250.0777504
7010.9423690.0576308
7110.8508480.149152
7211.093-0.0929953
7310.8872190.112781
7410.9229350.0770649
7511.04227-0.0422683
7611.07861-0.078614
7711.09858-0.0985769
7811.00048-0.00048325
7910.9611320.0388676
8011.14127-0.141275
8111.18014-0.180144
8211.13522-0.13522
8311.01365-0.0136507
8410.6959870.304013
8511.08754-0.08754
8610.8714690.128531
8710.7031310.296869
8810.9446410.0553591
8910.9903410.00965934
9011.22525-0.22525
9111.14447-0.144466
9210.7974710.202529
9310.7336720.266328
9410.8532560.146744
9510.7885590.211441
9610.7576720.242328
9710.8030070.196993
9811.0269-0.0269041
9910.7997390.200261
10010.8970690.102931
10110.9638530.0361472
10210.9738050.0261952
10310.9889170.011083
10410.5857750.414225
10510.5806650.419335
10610.5672640.432736
10710.5352890.464711
10810.6901040.309896
10910.6173620.382638
11010.8984210.101579
11111.03499-0.0349901
11210.5899890.410011
11310.8016310.198369
11410.6988710.301129
11510.8022250.197775
11610.8850940.114906
11710.7288940.271106
11811.05186-0.051857
11910.8860640.113936
12010.7616010.238399
12110.551530.44847
12210.9736330.0263668
12310.9728490.0271515
12410.7106010.289399
12510.618210.38179
12610.6246210.375379
12710.6126390.387361
12810.6275850.372415
12910.4149320.585068
13010.7652490.234751
13110.8031170.196883
13210.8749580.125042
13311.05332-0.0533167
13410.647040.35296
13510.9632820.0367176
13610.9615150.0384847
13711.14637-0.146369
13811.15063-0.150628
13910.9597530.0402465
14010.781480.21852
14110.9100850.0899151
14210.8582980.141702
14310.7289950.271005
14410.6828260.317174
14510.5493930.450607
14610.8602330.139767
14711.35151-0.351514
14811.15229-0.152285
14911.24477-0.244774
15010.8937020.106298
15110.9342530.065747
15210.9559320.0440683
15310.959080.0409204
15410.8454060.154594
15510.8944390.105561
15610.9948170.00518265
15710.7986840.201316
15811.2687-0.268698
15910.9707470.0292526
16010.86190.1381
16111.12813-0.128132
16211.05871-0.0587125
16310.9308250.0691748
16410.7941760.205824
16511.38244-0.382443
16600.450212-0.450212
16700.225191-0.225191
16800.0938475-0.0938475
16900.941843-0.941843
17000.230278-0.230278
17100.114576-0.114576
17200.799341-0.799341
17300.835874-0.835874
17400.878334-0.878334
17500.86601-0.86601
17600.834631-0.834631
17700.776849-0.776849
17810.644340.35566
17910.7122330.287767
18010.9343240.0656761
18110.7639790.236021
18210.8724260.127574
18310.7191930.280807
18400.604386-0.604386
18500.648463-0.648463
18600.606784-0.606784
18700.423249-0.423249
18800.475362-0.475362
18900.435997-0.435997
19000.428277-0.428277
19100.651129-0.651129
19200.700978-0.700978
1930-0.1745040.174504
19400.267081-0.267081
19500.519415-0.519415







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
261.81438e-533.62877e-531
273.49729e-656.99458e-651
289.12368e-781.82474e-771
293.41667e-946.83333e-941
304.4197e-1108.8394e-1101
310.0002546250.0005092510.999745
326.62847e-050.0001325690.999934
331.63455e-053.2691e-050.999984
344.92124e-069.84249e-060.999995
351.49305e-062.98611e-060.999999
363.66378e-077.32756e-071
375.20394e-050.0001040790.999948
382.99681e-055.99362e-050.99997
390.0005278440.001055690.999472
400.0008676120.001735220.999132
410.001089030.002178050.998911
420.0006345590.001269120.999365
430.000391090.0007821790.999609
440.0002188680.0004377360.999781
450.0001019940.0002039870.999898
465.00692e-050.0001001380.99995
472.99692e-055.99383e-050.99997
483.98807e-057.97614e-050.99996
490.0001743570.0003487140.999826
500.0001438210.0002876420.999856
519.51895e-050.0001903790.999905
526.31252e-050.000126250.999937
534.43579e-058.87159e-050.999956
544.61595e-059.23189e-050.999954
555.31699e-050.000106340.999947
566.6546e-050.0001330920.999933
573.76979e-057.53957e-050.999962
582.59914e-055.19829e-050.999974
591.47526e-052.95051e-050.999985
608.44088e-061.68818e-050.999992
610.0003517340.0007034680.999648
620.000457140.0009142810.999543
630.0006235910.001247180.999376
640.0006232410.001246480.999377
650.0004260820.0008521640.999574
660.0004220820.0008441640.999578
670.0002832620.0005665250.999717
680.0001823970.0003647940.999818
690.0002316280.0004632560.999768
700.0001786080.0003572160.999821
710.0001078650.0002157310.999892
727.36296e-050.0001472590.999926
734.32049e-058.64097e-050.999957
740.0001196080.0002392160.99988
750.0001563980.0003127950.999844
760.0001157690.0002315390.999884
777.49724e-050.0001499450.999925
785.88101e-050.000117620.999941
793.48878e-056.97756e-050.999965
802.49067e-054.98133e-050.999975
811.84899e-053.69798e-050.999982
821.07743e-052.15486e-050.999989
837.13072e-061.42614e-050.999993
844.57944e-069.15887e-060.999995
852.76835e-065.53669e-060.999997
863.23318e-066.46637e-060.999997
875.28066e-061.05613e-050.999995
883.34163e-066.68327e-060.999997
892.59786e-065.19572e-060.999997
903.2149e-066.42979e-060.999997
913.17262e-066.34524e-060.999997
923.96138e-067.92276e-060.999996
932.51952e-065.03904e-060.999997
941.68852e-063.37705e-060.999998
951.0897e-062.17939e-060.999999
966.75617e-071.35123e-060.999999
974.20086e-078.40171e-071
982.39384e-074.78768e-071
991.48975e-072.9795e-071
1008.73995e-081.74799e-071
1016.86125e-081.37225e-071
1026.59206e-081.31841e-071
1037.73713e-081.54743e-071
1041.48816e-072.97633e-071
1052.30966e-074.61932e-071
1064.22015e-078.44031e-071
1079.9405e-071.9881e-060.999999
1087.28182e-071.45636e-060.999999
1091.65514e-063.31029e-060.999998
1101.35674e-062.71347e-060.999999
1118.08882e-071.61776e-060.999999
1121.63893e-063.27786e-060.999998
1131.08425e-062.16849e-060.999999
1141.26298e-062.52596e-060.999999
1151.24807e-062.49613e-060.999999
1168.45062e-071.69012e-060.999999
1171.16203e-062.32406e-060.999999
1186.70629e-071.34126e-060.999999
1194.73737e-079.47475e-071
1201.08744e-062.17488e-060.999999
1216.79345e-061.35869e-050.999993
1221.71457e-053.42914e-050.999983
1231.09449e-052.18899e-050.999989
1247.51178e-061.50236e-050.999992
1255.28317e-061.05663e-050.999995
1265.53159e-061.10632e-050.999994
1271.11081e-052.22162e-050.999989
1280.0001462570.0002925140.999854
1290.0003825560.0007651110.999617
1300.0004874170.0009748330.999513
1310.0005018670.001003730.999498
1320.0003434650.000686930.999657
1330.0003079670.0006159340.999692
1340.001383020.002766050.998617
1350.001606070.003212140.998394
1360.001563280.003126570.998437
1370.001689850.00337970.99831
1380.001735730.003471460.998264
1390.00117250.002344990.998828
1400.001453520.002907050.998546
1410.001228730.002457460.998771
1420.001564040.003128070.998436
1430.001314530.002629060.998685
1440.004516190.009032380.995484
1450.003920270.007840530.99608
1460.003016490.006032980.996984
1470.002145460.004290930.997855
1480.001383530.002767060.998616
1490.0013990.0027980.998601
1500.0009274370.001854870.999073
1510.0008691160.001738230.999131
1520.006385180.01277040.993615
1530.0342770.0685540.965723
1540.03053680.06107360.969463
1550.02584510.05169030.974155
1560.01922080.03844170.980779
1570.08907860.1781570.910921
1580.08425210.1685040.915748
1590.2873580.5747160.712642
1600.2263670.4527330.773633
1610.1699160.3398330.830084
1620.1292570.2585140.870743
1630.1478540.2957090.852146
1640.3161250.632250.683875
1650.4253480.8506960.574652
1660.5208680.9582650.479132
1670.9017520.1964960.0982482
1680.9450030.1099930.0549967
1690.9629540.07409140.0370457

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
26 & 1.81438e-53 & 3.62877e-53 & 1 \tabularnewline
27 & 3.49729e-65 & 6.99458e-65 & 1 \tabularnewline
28 & 9.12368e-78 & 1.82474e-77 & 1 \tabularnewline
29 & 3.41667e-94 & 6.83333e-94 & 1 \tabularnewline
30 & 4.4197e-110 & 8.8394e-110 & 1 \tabularnewline
31 & 0.000254625 & 0.000509251 & 0.999745 \tabularnewline
32 & 6.62847e-05 & 0.000132569 & 0.999934 \tabularnewline
33 & 1.63455e-05 & 3.2691e-05 & 0.999984 \tabularnewline
34 & 4.92124e-06 & 9.84249e-06 & 0.999995 \tabularnewline
35 & 1.49305e-06 & 2.98611e-06 & 0.999999 \tabularnewline
36 & 3.66378e-07 & 7.32756e-07 & 1 \tabularnewline
37 & 5.20394e-05 & 0.000104079 & 0.999948 \tabularnewline
38 & 2.99681e-05 & 5.99362e-05 & 0.99997 \tabularnewline
39 & 0.000527844 & 0.00105569 & 0.999472 \tabularnewline
40 & 0.000867612 & 0.00173522 & 0.999132 \tabularnewline
41 & 0.00108903 & 0.00217805 & 0.998911 \tabularnewline
42 & 0.000634559 & 0.00126912 & 0.999365 \tabularnewline
43 & 0.00039109 & 0.000782179 & 0.999609 \tabularnewline
44 & 0.000218868 & 0.000437736 & 0.999781 \tabularnewline
45 & 0.000101994 & 0.000203987 & 0.999898 \tabularnewline
46 & 5.00692e-05 & 0.000100138 & 0.99995 \tabularnewline
47 & 2.99692e-05 & 5.99383e-05 & 0.99997 \tabularnewline
48 & 3.98807e-05 & 7.97614e-05 & 0.99996 \tabularnewline
49 & 0.000174357 & 0.000348714 & 0.999826 \tabularnewline
50 & 0.000143821 & 0.000287642 & 0.999856 \tabularnewline
51 & 9.51895e-05 & 0.000190379 & 0.999905 \tabularnewline
52 & 6.31252e-05 & 0.00012625 & 0.999937 \tabularnewline
53 & 4.43579e-05 & 8.87159e-05 & 0.999956 \tabularnewline
54 & 4.61595e-05 & 9.23189e-05 & 0.999954 \tabularnewline
55 & 5.31699e-05 & 0.00010634 & 0.999947 \tabularnewline
56 & 6.6546e-05 & 0.000133092 & 0.999933 \tabularnewline
57 & 3.76979e-05 & 7.53957e-05 & 0.999962 \tabularnewline
58 & 2.59914e-05 & 5.19829e-05 & 0.999974 \tabularnewline
59 & 1.47526e-05 & 2.95051e-05 & 0.999985 \tabularnewline
60 & 8.44088e-06 & 1.68818e-05 & 0.999992 \tabularnewline
61 & 0.000351734 & 0.000703468 & 0.999648 \tabularnewline
62 & 0.00045714 & 0.000914281 & 0.999543 \tabularnewline
63 & 0.000623591 & 0.00124718 & 0.999376 \tabularnewline
64 & 0.000623241 & 0.00124648 & 0.999377 \tabularnewline
65 & 0.000426082 & 0.000852164 & 0.999574 \tabularnewline
66 & 0.000422082 & 0.000844164 & 0.999578 \tabularnewline
67 & 0.000283262 & 0.000566525 & 0.999717 \tabularnewline
68 & 0.000182397 & 0.000364794 & 0.999818 \tabularnewline
69 & 0.000231628 & 0.000463256 & 0.999768 \tabularnewline
70 & 0.000178608 & 0.000357216 & 0.999821 \tabularnewline
71 & 0.000107865 & 0.000215731 & 0.999892 \tabularnewline
72 & 7.36296e-05 & 0.000147259 & 0.999926 \tabularnewline
73 & 4.32049e-05 & 8.64097e-05 & 0.999957 \tabularnewline
74 & 0.000119608 & 0.000239216 & 0.99988 \tabularnewline
75 & 0.000156398 & 0.000312795 & 0.999844 \tabularnewline
76 & 0.000115769 & 0.000231539 & 0.999884 \tabularnewline
77 & 7.49724e-05 & 0.000149945 & 0.999925 \tabularnewline
78 & 5.88101e-05 & 0.00011762 & 0.999941 \tabularnewline
79 & 3.48878e-05 & 6.97756e-05 & 0.999965 \tabularnewline
80 & 2.49067e-05 & 4.98133e-05 & 0.999975 \tabularnewline
81 & 1.84899e-05 & 3.69798e-05 & 0.999982 \tabularnewline
82 & 1.07743e-05 & 2.15486e-05 & 0.999989 \tabularnewline
83 & 7.13072e-06 & 1.42614e-05 & 0.999993 \tabularnewline
84 & 4.57944e-06 & 9.15887e-06 & 0.999995 \tabularnewline
85 & 2.76835e-06 & 5.53669e-06 & 0.999997 \tabularnewline
86 & 3.23318e-06 & 6.46637e-06 & 0.999997 \tabularnewline
87 & 5.28066e-06 & 1.05613e-05 & 0.999995 \tabularnewline
88 & 3.34163e-06 & 6.68327e-06 & 0.999997 \tabularnewline
89 & 2.59786e-06 & 5.19572e-06 & 0.999997 \tabularnewline
90 & 3.2149e-06 & 6.42979e-06 & 0.999997 \tabularnewline
91 & 3.17262e-06 & 6.34524e-06 & 0.999997 \tabularnewline
92 & 3.96138e-06 & 7.92276e-06 & 0.999996 \tabularnewline
93 & 2.51952e-06 & 5.03904e-06 & 0.999997 \tabularnewline
94 & 1.68852e-06 & 3.37705e-06 & 0.999998 \tabularnewline
95 & 1.0897e-06 & 2.17939e-06 & 0.999999 \tabularnewline
96 & 6.75617e-07 & 1.35123e-06 & 0.999999 \tabularnewline
97 & 4.20086e-07 & 8.40171e-07 & 1 \tabularnewline
98 & 2.39384e-07 & 4.78768e-07 & 1 \tabularnewline
99 & 1.48975e-07 & 2.9795e-07 & 1 \tabularnewline
100 & 8.73995e-08 & 1.74799e-07 & 1 \tabularnewline
101 & 6.86125e-08 & 1.37225e-07 & 1 \tabularnewline
102 & 6.59206e-08 & 1.31841e-07 & 1 \tabularnewline
103 & 7.73713e-08 & 1.54743e-07 & 1 \tabularnewline
104 & 1.48816e-07 & 2.97633e-07 & 1 \tabularnewline
105 & 2.30966e-07 & 4.61932e-07 & 1 \tabularnewline
106 & 4.22015e-07 & 8.44031e-07 & 1 \tabularnewline
107 & 9.9405e-07 & 1.9881e-06 & 0.999999 \tabularnewline
108 & 7.28182e-07 & 1.45636e-06 & 0.999999 \tabularnewline
109 & 1.65514e-06 & 3.31029e-06 & 0.999998 \tabularnewline
110 & 1.35674e-06 & 2.71347e-06 & 0.999999 \tabularnewline
111 & 8.08882e-07 & 1.61776e-06 & 0.999999 \tabularnewline
112 & 1.63893e-06 & 3.27786e-06 & 0.999998 \tabularnewline
113 & 1.08425e-06 & 2.16849e-06 & 0.999999 \tabularnewline
114 & 1.26298e-06 & 2.52596e-06 & 0.999999 \tabularnewline
115 & 1.24807e-06 & 2.49613e-06 & 0.999999 \tabularnewline
116 & 8.45062e-07 & 1.69012e-06 & 0.999999 \tabularnewline
117 & 1.16203e-06 & 2.32406e-06 & 0.999999 \tabularnewline
118 & 6.70629e-07 & 1.34126e-06 & 0.999999 \tabularnewline
119 & 4.73737e-07 & 9.47475e-07 & 1 \tabularnewline
120 & 1.08744e-06 & 2.17488e-06 & 0.999999 \tabularnewline
121 & 6.79345e-06 & 1.35869e-05 & 0.999993 \tabularnewline
122 & 1.71457e-05 & 3.42914e-05 & 0.999983 \tabularnewline
123 & 1.09449e-05 & 2.18899e-05 & 0.999989 \tabularnewline
124 & 7.51178e-06 & 1.50236e-05 & 0.999992 \tabularnewline
125 & 5.28317e-06 & 1.05663e-05 & 0.999995 \tabularnewline
126 & 5.53159e-06 & 1.10632e-05 & 0.999994 \tabularnewline
127 & 1.11081e-05 & 2.22162e-05 & 0.999989 \tabularnewline
128 & 0.000146257 & 0.000292514 & 0.999854 \tabularnewline
129 & 0.000382556 & 0.000765111 & 0.999617 \tabularnewline
130 & 0.000487417 & 0.000974833 & 0.999513 \tabularnewline
131 & 0.000501867 & 0.00100373 & 0.999498 \tabularnewline
132 & 0.000343465 & 0.00068693 & 0.999657 \tabularnewline
133 & 0.000307967 & 0.000615934 & 0.999692 \tabularnewline
134 & 0.00138302 & 0.00276605 & 0.998617 \tabularnewline
135 & 0.00160607 & 0.00321214 & 0.998394 \tabularnewline
136 & 0.00156328 & 0.00312657 & 0.998437 \tabularnewline
137 & 0.00168985 & 0.0033797 & 0.99831 \tabularnewline
138 & 0.00173573 & 0.00347146 & 0.998264 \tabularnewline
139 & 0.0011725 & 0.00234499 & 0.998828 \tabularnewline
140 & 0.00145352 & 0.00290705 & 0.998546 \tabularnewline
141 & 0.00122873 & 0.00245746 & 0.998771 \tabularnewline
142 & 0.00156404 & 0.00312807 & 0.998436 \tabularnewline
143 & 0.00131453 & 0.00262906 & 0.998685 \tabularnewline
144 & 0.00451619 & 0.00903238 & 0.995484 \tabularnewline
145 & 0.00392027 & 0.00784053 & 0.99608 \tabularnewline
146 & 0.00301649 & 0.00603298 & 0.996984 \tabularnewline
147 & 0.00214546 & 0.00429093 & 0.997855 \tabularnewline
148 & 0.00138353 & 0.00276706 & 0.998616 \tabularnewline
149 & 0.001399 & 0.002798 & 0.998601 \tabularnewline
150 & 0.000927437 & 0.00185487 & 0.999073 \tabularnewline
151 & 0.000869116 & 0.00173823 & 0.999131 \tabularnewline
152 & 0.00638518 & 0.0127704 & 0.993615 \tabularnewline
153 & 0.034277 & 0.068554 & 0.965723 \tabularnewline
154 & 0.0305368 & 0.0610736 & 0.969463 \tabularnewline
155 & 0.0258451 & 0.0516903 & 0.974155 \tabularnewline
156 & 0.0192208 & 0.0384417 & 0.980779 \tabularnewline
157 & 0.0890786 & 0.178157 & 0.910921 \tabularnewline
158 & 0.0842521 & 0.168504 & 0.915748 \tabularnewline
159 & 0.287358 & 0.574716 & 0.712642 \tabularnewline
160 & 0.226367 & 0.452733 & 0.773633 \tabularnewline
161 & 0.169916 & 0.339833 & 0.830084 \tabularnewline
162 & 0.129257 & 0.258514 & 0.870743 \tabularnewline
163 & 0.147854 & 0.295709 & 0.852146 \tabularnewline
164 & 0.316125 & 0.63225 & 0.683875 \tabularnewline
165 & 0.425348 & 0.850696 & 0.574652 \tabularnewline
166 & 0.520868 & 0.958265 & 0.479132 \tabularnewline
167 & 0.901752 & 0.196496 & 0.0982482 \tabularnewline
168 & 0.945003 & 0.109993 & 0.0549967 \tabularnewline
169 & 0.962954 & 0.0740914 & 0.0370457 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232035&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]26[/C][C]1.81438e-53[/C][C]3.62877e-53[/C][C]1[/C][/ROW]
[ROW][C]27[/C][C]3.49729e-65[/C][C]6.99458e-65[/C][C]1[/C][/ROW]
[ROW][C]28[/C][C]9.12368e-78[/C][C]1.82474e-77[/C][C]1[/C][/ROW]
[ROW][C]29[/C][C]3.41667e-94[/C][C]6.83333e-94[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]4.4197e-110[/C][C]8.8394e-110[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]0.000254625[/C][C]0.000509251[/C][C]0.999745[/C][/ROW]
[ROW][C]32[/C][C]6.62847e-05[/C][C]0.000132569[/C][C]0.999934[/C][/ROW]
[ROW][C]33[/C][C]1.63455e-05[/C][C]3.2691e-05[/C][C]0.999984[/C][/ROW]
[ROW][C]34[/C][C]4.92124e-06[/C][C]9.84249e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]35[/C][C]1.49305e-06[/C][C]2.98611e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]36[/C][C]3.66378e-07[/C][C]7.32756e-07[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]5.20394e-05[/C][C]0.000104079[/C][C]0.999948[/C][/ROW]
[ROW][C]38[/C][C]2.99681e-05[/C][C]5.99362e-05[/C][C]0.99997[/C][/ROW]
[ROW][C]39[/C][C]0.000527844[/C][C]0.00105569[/C][C]0.999472[/C][/ROW]
[ROW][C]40[/C][C]0.000867612[/C][C]0.00173522[/C][C]0.999132[/C][/ROW]
[ROW][C]41[/C][C]0.00108903[/C][C]0.00217805[/C][C]0.998911[/C][/ROW]
[ROW][C]42[/C][C]0.000634559[/C][C]0.00126912[/C][C]0.999365[/C][/ROW]
[ROW][C]43[/C][C]0.00039109[/C][C]0.000782179[/C][C]0.999609[/C][/ROW]
[ROW][C]44[/C][C]0.000218868[/C][C]0.000437736[/C][C]0.999781[/C][/ROW]
[ROW][C]45[/C][C]0.000101994[/C][C]0.000203987[/C][C]0.999898[/C][/ROW]
[ROW][C]46[/C][C]5.00692e-05[/C][C]0.000100138[/C][C]0.99995[/C][/ROW]
[ROW][C]47[/C][C]2.99692e-05[/C][C]5.99383e-05[/C][C]0.99997[/C][/ROW]
[ROW][C]48[/C][C]3.98807e-05[/C][C]7.97614e-05[/C][C]0.99996[/C][/ROW]
[ROW][C]49[/C][C]0.000174357[/C][C]0.000348714[/C][C]0.999826[/C][/ROW]
[ROW][C]50[/C][C]0.000143821[/C][C]0.000287642[/C][C]0.999856[/C][/ROW]
[ROW][C]51[/C][C]9.51895e-05[/C][C]0.000190379[/C][C]0.999905[/C][/ROW]
[ROW][C]52[/C][C]6.31252e-05[/C][C]0.00012625[/C][C]0.999937[/C][/ROW]
[ROW][C]53[/C][C]4.43579e-05[/C][C]8.87159e-05[/C][C]0.999956[/C][/ROW]
[ROW][C]54[/C][C]4.61595e-05[/C][C]9.23189e-05[/C][C]0.999954[/C][/ROW]
[ROW][C]55[/C][C]5.31699e-05[/C][C]0.00010634[/C][C]0.999947[/C][/ROW]
[ROW][C]56[/C][C]6.6546e-05[/C][C]0.000133092[/C][C]0.999933[/C][/ROW]
[ROW][C]57[/C][C]3.76979e-05[/C][C]7.53957e-05[/C][C]0.999962[/C][/ROW]
[ROW][C]58[/C][C]2.59914e-05[/C][C]5.19829e-05[/C][C]0.999974[/C][/ROW]
[ROW][C]59[/C][C]1.47526e-05[/C][C]2.95051e-05[/C][C]0.999985[/C][/ROW]
[ROW][C]60[/C][C]8.44088e-06[/C][C]1.68818e-05[/C][C]0.999992[/C][/ROW]
[ROW][C]61[/C][C]0.000351734[/C][C]0.000703468[/C][C]0.999648[/C][/ROW]
[ROW][C]62[/C][C]0.00045714[/C][C]0.000914281[/C][C]0.999543[/C][/ROW]
[ROW][C]63[/C][C]0.000623591[/C][C]0.00124718[/C][C]0.999376[/C][/ROW]
[ROW][C]64[/C][C]0.000623241[/C][C]0.00124648[/C][C]0.999377[/C][/ROW]
[ROW][C]65[/C][C]0.000426082[/C][C]0.000852164[/C][C]0.999574[/C][/ROW]
[ROW][C]66[/C][C]0.000422082[/C][C]0.000844164[/C][C]0.999578[/C][/ROW]
[ROW][C]67[/C][C]0.000283262[/C][C]0.000566525[/C][C]0.999717[/C][/ROW]
[ROW][C]68[/C][C]0.000182397[/C][C]0.000364794[/C][C]0.999818[/C][/ROW]
[ROW][C]69[/C][C]0.000231628[/C][C]0.000463256[/C][C]0.999768[/C][/ROW]
[ROW][C]70[/C][C]0.000178608[/C][C]0.000357216[/C][C]0.999821[/C][/ROW]
[ROW][C]71[/C][C]0.000107865[/C][C]0.000215731[/C][C]0.999892[/C][/ROW]
[ROW][C]72[/C][C]7.36296e-05[/C][C]0.000147259[/C][C]0.999926[/C][/ROW]
[ROW][C]73[/C][C]4.32049e-05[/C][C]8.64097e-05[/C][C]0.999957[/C][/ROW]
[ROW][C]74[/C][C]0.000119608[/C][C]0.000239216[/C][C]0.99988[/C][/ROW]
[ROW][C]75[/C][C]0.000156398[/C][C]0.000312795[/C][C]0.999844[/C][/ROW]
[ROW][C]76[/C][C]0.000115769[/C][C]0.000231539[/C][C]0.999884[/C][/ROW]
[ROW][C]77[/C][C]7.49724e-05[/C][C]0.000149945[/C][C]0.999925[/C][/ROW]
[ROW][C]78[/C][C]5.88101e-05[/C][C]0.00011762[/C][C]0.999941[/C][/ROW]
[ROW][C]79[/C][C]3.48878e-05[/C][C]6.97756e-05[/C][C]0.999965[/C][/ROW]
[ROW][C]80[/C][C]2.49067e-05[/C][C]4.98133e-05[/C][C]0.999975[/C][/ROW]
[ROW][C]81[/C][C]1.84899e-05[/C][C]3.69798e-05[/C][C]0.999982[/C][/ROW]
[ROW][C]82[/C][C]1.07743e-05[/C][C]2.15486e-05[/C][C]0.999989[/C][/ROW]
[ROW][C]83[/C][C]7.13072e-06[/C][C]1.42614e-05[/C][C]0.999993[/C][/ROW]
[ROW][C]84[/C][C]4.57944e-06[/C][C]9.15887e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]85[/C][C]2.76835e-06[/C][C]5.53669e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]86[/C][C]3.23318e-06[/C][C]6.46637e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]87[/C][C]5.28066e-06[/C][C]1.05613e-05[/C][C]0.999995[/C][/ROW]
[ROW][C]88[/C][C]3.34163e-06[/C][C]6.68327e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]89[/C][C]2.59786e-06[/C][C]5.19572e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]90[/C][C]3.2149e-06[/C][C]6.42979e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]91[/C][C]3.17262e-06[/C][C]6.34524e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]92[/C][C]3.96138e-06[/C][C]7.92276e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]93[/C][C]2.51952e-06[/C][C]5.03904e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]94[/C][C]1.68852e-06[/C][C]3.37705e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]95[/C][C]1.0897e-06[/C][C]2.17939e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]96[/C][C]6.75617e-07[/C][C]1.35123e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]97[/C][C]4.20086e-07[/C][C]8.40171e-07[/C][C]1[/C][/ROW]
[ROW][C]98[/C][C]2.39384e-07[/C][C]4.78768e-07[/C][C]1[/C][/ROW]
[ROW][C]99[/C][C]1.48975e-07[/C][C]2.9795e-07[/C][C]1[/C][/ROW]
[ROW][C]100[/C][C]8.73995e-08[/C][C]1.74799e-07[/C][C]1[/C][/ROW]
[ROW][C]101[/C][C]6.86125e-08[/C][C]1.37225e-07[/C][C]1[/C][/ROW]
[ROW][C]102[/C][C]6.59206e-08[/C][C]1.31841e-07[/C][C]1[/C][/ROW]
[ROW][C]103[/C][C]7.73713e-08[/C][C]1.54743e-07[/C][C]1[/C][/ROW]
[ROW][C]104[/C][C]1.48816e-07[/C][C]2.97633e-07[/C][C]1[/C][/ROW]
[ROW][C]105[/C][C]2.30966e-07[/C][C]4.61932e-07[/C][C]1[/C][/ROW]
[ROW][C]106[/C][C]4.22015e-07[/C][C]8.44031e-07[/C][C]1[/C][/ROW]
[ROW][C]107[/C][C]9.9405e-07[/C][C]1.9881e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]108[/C][C]7.28182e-07[/C][C]1.45636e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]109[/C][C]1.65514e-06[/C][C]3.31029e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]110[/C][C]1.35674e-06[/C][C]2.71347e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]111[/C][C]8.08882e-07[/C][C]1.61776e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]112[/C][C]1.63893e-06[/C][C]3.27786e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]113[/C][C]1.08425e-06[/C][C]2.16849e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]114[/C][C]1.26298e-06[/C][C]2.52596e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]115[/C][C]1.24807e-06[/C][C]2.49613e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]116[/C][C]8.45062e-07[/C][C]1.69012e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]117[/C][C]1.16203e-06[/C][C]2.32406e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]118[/C][C]6.70629e-07[/C][C]1.34126e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]119[/C][C]4.73737e-07[/C][C]9.47475e-07[/C][C]1[/C][/ROW]
[ROW][C]120[/C][C]1.08744e-06[/C][C]2.17488e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]121[/C][C]6.79345e-06[/C][C]1.35869e-05[/C][C]0.999993[/C][/ROW]
[ROW][C]122[/C][C]1.71457e-05[/C][C]3.42914e-05[/C][C]0.999983[/C][/ROW]
[ROW][C]123[/C][C]1.09449e-05[/C][C]2.18899e-05[/C][C]0.999989[/C][/ROW]
[ROW][C]124[/C][C]7.51178e-06[/C][C]1.50236e-05[/C][C]0.999992[/C][/ROW]
[ROW][C]125[/C][C]5.28317e-06[/C][C]1.05663e-05[/C][C]0.999995[/C][/ROW]
[ROW][C]126[/C][C]5.53159e-06[/C][C]1.10632e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]127[/C][C]1.11081e-05[/C][C]2.22162e-05[/C][C]0.999989[/C][/ROW]
[ROW][C]128[/C][C]0.000146257[/C][C]0.000292514[/C][C]0.999854[/C][/ROW]
[ROW][C]129[/C][C]0.000382556[/C][C]0.000765111[/C][C]0.999617[/C][/ROW]
[ROW][C]130[/C][C]0.000487417[/C][C]0.000974833[/C][C]0.999513[/C][/ROW]
[ROW][C]131[/C][C]0.000501867[/C][C]0.00100373[/C][C]0.999498[/C][/ROW]
[ROW][C]132[/C][C]0.000343465[/C][C]0.00068693[/C][C]0.999657[/C][/ROW]
[ROW][C]133[/C][C]0.000307967[/C][C]0.000615934[/C][C]0.999692[/C][/ROW]
[ROW][C]134[/C][C]0.00138302[/C][C]0.00276605[/C][C]0.998617[/C][/ROW]
[ROW][C]135[/C][C]0.00160607[/C][C]0.00321214[/C][C]0.998394[/C][/ROW]
[ROW][C]136[/C][C]0.00156328[/C][C]0.00312657[/C][C]0.998437[/C][/ROW]
[ROW][C]137[/C][C]0.00168985[/C][C]0.0033797[/C][C]0.99831[/C][/ROW]
[ROW][C]138[/C][C]0.00173573[/C][C]0.00347146[/C][C]0.998264[/C][/ROW]
[ROW][C]139[/C][C]0.0011725[/C][C]0.00234499[/C][C]0.998828[/C][/ROW]
[ROW][C]140[/C][C]0.00145352[/C][C]0.00290705[/C][C]0.998546[/C][/ROW]
[ROW][C]141[/C][C]0.00122873[/C][C]0.00245746[/C][C]0.998771[/C][/ROW]
[ROW][C]142[/C][C]0.00156404[/C][C]0.00312807[/C][C]0.998436[/C][/ROW]
[ROW][C]143[/C][C]0.00131453[/C][C]0.00262906[/C][C]0.998685[/C][/ROW]
[ROW][C]144[/C][C]0.00451619[/C][C]0.00903238[/C][C]0.995484[/C][/ROW]
[ROW][C]145[/C][C]0.00392027[/C][C]0.00784053[/C][C]0.99608[/C][/ROW]
[ROW][C]146[/C][C]0.00301649[/C][C]0.00603298[/C][C]0.996984[/C][/ROW]
[ROW][C]147[/C][C]0.00214546[/C][C]0.00429093[/C][C]0.997855[/C][/ROW]
[ROW][C]148[/C][C]0.00138353[/C][C]0.00276706[/C][C]0.998616[/C][/ROW]
[ROW][C]149[/C][C]0.001399[/C][C]0.002798[/C][C]0.998601[/C][/ROW]
[ROW][C]150[/C][C]0.000927437[/C][C]0.00185487[/C][C]0.999073[/C][/ROW]
[ROW][C]151[/C][C]0.000869116[/C][C]0.00173823[/C][C]0.999131[/C][/ROW]
[ROW][C]152[/C][C]0.00638518[/C][C]0.0127704[/C][C]0.993615[/C][/ROW]
[ROW][C]153[/C][C]0.034277[/C][C]0.068554[/C][C]0.965723[/C][/ROW]
[ROW][C]154[/C][C]0.0305368[/C][C]0.0610736[/C][C]0.969463[/C][/ROW]
[ROW][C]155[/C][C]0.0258451[/C][C]0.0516903[/C][C]0.974155[/C][/ROW]
[ROW][C]156[/C][C]0.0192208[/C][C]0.0384417[/C][C]0.980779[/C][/ROW]
[ROW][C]157[/C][C]0.0890786[/C][C]0.178157[/C][C]0.910921[/C][/ROW]
[ROW][C]158[/C][C]0.0842521[/C][C]0.168504[/C][C]0.915748[/C][/ROW]
[ROW][C]159[/C][C]0.287358[/C][C]0.574716[/C][C]0.712642[/C][/ROW]
[ROW][C]160[/C][C]0.226367[/C][C]0.452733[/C][C]0.773633[/C][/ROW]
[ROW][C]161[/C][C]0.169916[/C][C]0.339833[/C][C]0.830084[/C][/ROW]
[ROW][C]162[/C][C]0.129257[/C][C]0.258514[/C][C]0.870743[/C][/ROW]
[ROW][C]163[/C][C]0.147854[/C][C]0.295709[/C][C]0.852146[/C][/ROW]
[ROW][C]164[/C][C]0.316125[/C][C]0.63225[/C][C]0.683875[/C][/ROW]
[ROW][C]165[/C][C]0.425348[/C][C]0.850696[/C][C]0.574652[/C][/ROW]
[ROW][C]166[/C][C]0.520868[/C][C]0.958265[/C][C]0.479132[/C][/ROW]
[ROW][C]167[/C][C]0.901752[/C][C]0.196496[/C][C]0.0982482[/C][/ROW]
[ROW][C]168[/C][C]0.945003[/C][C]0.109993[/C][C]0.0549967[/C][/ROW]
[ROW][C]169[/C][C]0.962954[/C][C]0.0740914[/C][C]0.0370457[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232035&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232035&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
261.81438e-533.62877e-531
273.49729e-656.99458e-651
289.12368e-781.82474e-771
293.41667e-946.83333e-941
304.4197e-1108.8394e-1101
310.0002546250.0005092510.999745
326.62847e-050.0001325690.999934
331.63455e-053.2691e-050.999984
344.92124e-069.84249e-060.999995
351.49305e-062.98611e-060.999999
363.66378e-077.32756e-071
375.20394e-050.0001040790.999948
382.99681e-055.99362e-050.99997
390.0005278440.001055690.999472
400.0008676120.001735220.999132
410.001089030.002178050.998911
420.0006345590.001269120.999365
430.000391090.0007821790.999609
440.0002188680.0004377360.999781
450.0001019940.0002039870.999898
465.00692e-050.0001001380.99995
472.99692e-055.99383e-050.99997
483.98807e-057.97614e-050.99996
490.0001743570.0003487140.999826
500.0001438210.0002876420.999856
519.51895e-050.0001903790.999905
526.31252e-050.000126250.999937
534.43579e-058.87159e-050.999956
544.61595e-059.23189e-050.999954
555.31699e-050.000106340.999947
566.6546e-050.0001330920.999933
573.76979e-057.53957e-050.999962
582.59914e-055.19829e-050.999974
591.47526e-052.95051e-050.999985
608.44088e-061.68818e-050.999992
610.0003517340.0007034680.999648
620.000457140.0009142810.999543
630.0006235910.001247180.999376
640.0006232410.001246480.999377
650.0004260820.0008521640.999574
660.0004220820.0008441640.999578
670.0002832620.0005665250.999717
680.0001823970.0003647940.999818
690.0002316280.0004632560.999768
700.0001786080.0003572160.999821
710.0001078650.0002157310.999892
727.36296e-050.0001472590.999926
734.32049e-058.64097e-050.999957
740.0001196080.0002392160.99988
750.0001563980.0003127950.999844
760.0001157690.0002315390.999884
777.49724e-050.0001499450.999925
785.88101e-050.000117620.999941
793.48878e-056.97756e-050.999965
802.49067e-054.98133e-050.999975
811.84899e-053.69798e-050.999982
821.07743e-052.15486e-050.999989
837.13072e-061.42614e-050.999993
844.57944e-069.15887e-060.999995
852.76835e-065.53669e-060.999997
863.23318e-066.46637e-060.999997
875.28066e-061.05613e-050.999995
883.34163e-066.68327e-060.999997
892.59786e-065.19572e-060.999997
903.2149e-066.42979e-060.999997
913.17262e-066.34524e-060.999997
923.96138e-067.92276e-060.999996
932.51952e-065.03904e-060.999997
941.68852e-063.37705e-060.999998
951.0897e-062.17939e-060.999999
966.75617e-071.35123e-060.999999
974.20086e-078.40171e-071
982.39384e-074.78768e-071
991.48975e-072.9795e-071
1008.73995e-081.74799e-071
1016.86125e-081.37225e-071
1026.59206e-081.31841e-071
1037.73713e-081.54743e-071
1041.48816e-072.97633e-071
1052.30966e-074.61932e-071
1064.22015e-078.44031e-071
1079.9405e-071.9881e-060.999999
1087.28182e-071.45636e-060.999999
1091.65514e-063.31029e-060.999998
1101.35674e-062.71347e-060.999999
1118.08882e-071.61776e-060.999999
1121.63893e-063.27786e-060.999998
1131.08425e-062.16849e-060.999999
1141.26298e-062.52596e-060.999999
1151.24807e-062.49613e-060.999999
1168.45062e-071.69012e-060.999999
1171.16203e-062.32406e-060.999999
1186.70629e-071.34126e-060.999999
1194.73737e-079.47475e-071
1201.08744e-062.17488e-060.999999
1216.79345e-061.35869e-050.999993
1221.71457e-053.42914e-050.999983
1231.09449e-052.18899e-050.999989
1247.51178e-061.50236e-050.999992
1255.28317e-061.05663e-050.999995
1265.53159e-061.10632e-050.999994
1271.11081e-052.22162e-050.999989
1280.0001462570.0002925140.999854
1290.0003825560.0007651110.999617
1300.0004874170.0009748330.999513
1310.0005018670.001003730.999498
1320.0003434650.000686930.999657
1330.0003079670.0006159340.999692
1340.001383020.002766050.998617
1350.001606070.003212140.998394
1360.001563280.003126570.998437
1370.001689850.00337970.99831
1380.001735730.003471460.998264
1390.00117250.002344990.998828
1400.001453520.002907050.998546
1410.001228730.002457460.998771
1420.001564040.003128070.998436
1430.001314530.002629060.998685
1440.004516190.009032380.995484
1450.003920270.007840530.99608
1460.003016490.006032980.996984
1470.002145460.004290930.997855
1480.001383530.002767060.998616
1490.0013990.0027980.998601
1500.0009274370.001854870.999073
1510.0008691160.001738230.999131
1520.006385180.01277040.993615
1530.0342770.0685540.965723
1540.03053680.06107360.969463
1550.02584510.05169030.974155
1560.01922080.03844170.980779
1570.08907860.1781570.910921
1580.08425210.1685040.915748
1590.2873580.5747160.712642
1600.2263670.4527330.773633
1610.1699160.3398330.830084
1620.1292570.2585140.870743
1630.1478540.2957090.852146
1640.3161250.632250.683875
1650.4253480.8506960.574652
1660.5208680.9582650.479132
1670.9017520.1964960.0982482
1680.9450030.1099930.0549967
1690.9629540.07409140.0370457







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1260.875NOK
5% type I error level1280.888889NOK
10% type I error level1320.916667NOK

\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 & 126 & 0.875 & NOK \tabularnewline
5% type I error level & 128 & 0.888889 & NOK \tabularnewline
10% type I error level & 132 & 0.916667 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232035&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]126[/C][C]0.875[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]128[/C][C]0.888889[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]132[/C][C]0.916667[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232035&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232035&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 level1260.875NOK
5% type I error level1280.888889NOK
10% type I error level1320.916667NOK



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')
}