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Description of Statistical Computation

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 12:06:58 -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/t1386781680s55rz9sy4pgtvkx.htm/, Retrieved Fri, 19 Apr 2024 08:05:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232117, Retrieved Fri, 19 Apr 2024 08:05:00 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [jgjhg] [2013-12-11 17:06:58] [9c1e2bb2413149fa15098d3e18bf4ebf] [Current]
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Dataset

Dataseries X:
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Histogram
Boxplots 
0.284654 2.301442 0.266482 -4.813031 0.815285 0.414783 1 21.033 0.02211 0.06545 0.02971 0.0313 0.02182 0.426 0.04374 0.01109 0.00554 0.0037 0.00007 0.00784 74.997 157.302 119.992
0.368674 2.486855 0.33559 -4.075192 0.819521 0.458359 1 19.085 0.01929 0.09403 0.04368 0.04518 0.03134 0.626 0.06134 0.01394 0.00696 0.00465 0.00008 0.00968 113.819 148.65 122.4
0.332634 2.342259 0.311173 -4.443179 0.825288 0.429895 1 20.651 0.01309 0.0827 0.0359 0.03858 0.02757 0.482 0.05233 0.01633 0.00781 0.00544 0.00009 0.0105 111.555 131.111 116.682
0.368975 2.405554 0.334147 -4.117501 0.819235 0.434969 1 20.644 0.01353 0.08771 0.03772 0.04005 0.02924 0.517 0.05492 0.01505 0.00698 0.00502 0.00009 0.00997 111.366 137.871 116.676
0.410335 2.33218 0.234513 -3.747787 0.823484 0.417356 1 19.649 0.01767 0.1047 0.04465 0.04825 0.0349 0.584 0.06425 0.01966 0.00908 0.00655 0.00011 0.01284 110.655 141.781 116.014
0.357775 2.18756 0.299111 -4.242867 0.825069 0.415564 1 21.378 0.01222 0.06985 0.03243 0.03526 0.02328 0.456 0.04701 0.01388 0.0075 0.00463 0.00008 0.00968 113.787 131.162 120.552
0.211756 1.854785 0.257682 -5.634322 0.764112 0.59604 1 24.886 0.00607 0.02337 0.01351 0.00937 0.00779 0.14 0.01608 0.00466 0.00202 0.00155 0.00003 0.00333 114.82 137.244 120.267
0.163755 2.064693 0.183721 -6.167603 0.763262 0.63742 1 26.892 0.00344 0.02487 0.01256 0.00946 0.00829 0.134 0.01567 0.00431 0.00182 0.00144 0.00003 0.0029 104.315 113.84 107.332
0.231571 2.322511 0.327769 -5.498678 0.773587 0.615551 1 21.812 0.0107 0.03218 0.01717 0.01277 0.01073 0.191 0.02093 0.0088 0.00332 0.00293 0.00006 0.00551 91.754 132.068 95.73
0.271362 2.432792 0.325996 -5.011879 0.798463 0.547037 1 21.862 0.01022 0.04324 0.02444 0.01725 0.01441 0.255 0.02838 0.00803 0.00332 0.00268 0.00006 0.00532 91.226 120.103 95.056
0.24974 2.407313 0.391002 -5.24977 0.776156 0.611137 1 21.118 0.01166 0.03237 0.01892 0.01342 0.01079 0.197 0.02143 0.00763 0.0033 0.00254 0.00006 0.00505 84.072 112.24 88.333
0.275931 2.642476 0.363566 -4.960234 0.79252 0.58339 1 21.414 0.01141 0.04272 0.02214 0.01641 0.01424 0.249 0.02752 0.00844 0.00336 0.00281 0.00006 0.0054 86.292 115.871 91.904
0.138512 2.041277 0.152813 -6.547148 0.646846 0.4606 1 25.703 0.00581 0.01968 0.0114 0.00717 0.00656 0.112 0.01259 0.00355 0.00153 0.00118 0.00002 0.00293 131.276 159.866 136.926
0.199889 2.519422 0.254989 -5.660217 0.665833 0.430166 1 24.889 0.01041 0.02184 0.01797 0.00932 0.00728 0.154 0.01642 0.00496 0.00208 0.00165 0.00003 0.0039 76.556 179.139 139.173
0.1701 2.125618 0.203653 -6.105098 0.654027 0.474791 1 24.922 0.00609 0.03191 0.01246 0.00972 0.01064 0.158 0.01828 0.00364 0.00149 0.00121 0.00002 0.00294 75.836 163.305 152.845
0.234589 2.205546 0.210185 -5.340115 0.658245 0.565924 1 25.175 0.00839 0.02316 0.01359 0.00888 0.00772 0.126 0.01503 0.00471 0.00203 0.00157 0.00003 0.00369 83.159 217.455 142.167
0.218164 2.264501 0.239764 -5.44004 0.644692 0.56738 1 22.333 0.01859 0.02908 0.02074 0.012 0.00969 0.192 0.02047 0.00632 0.00292 0.00211 0.00004 0.00544 82.764 349.259 144.188
0.430788 3.007463 0.434326 -2.93107 0.605417 0.631099 1 20.376 0.02919 0.04322 0.0343 0.01893 0.01441 0.348 0.03327 0.00853 0.00387 0.00284 0.00004 0.00718 75.603 232.181 168.778
0.377429 3.10901 0.35787 -3.949079 0.719467 0.665318 1 17.28 0.0316 0.07413 0.05767 0.03572 0.02471 0.542 0.05517 0.01092 0.00432 0.00364 0.00005 0.00742 68.623 175.829 153.046
0.322111 2.856676 0.340176 -4.554466 0.68608 0.649554 1 17.153 0.03365 0.05164 0.0431 0.02374 0.01721 0.348 0.03995 0.01116 0.00399 0.00372 0.00005 0.00768 142.822 189.398 156.405
0.365391 2.73971 0.262564 -4.095442 0.704087 0.660125 1 17.536 0.03871 0.05 0.04055 0.02383 0.01667 0.328 0.0381 0.01285 0.0045 0.00428 0.00005 0.0084 65.782 165.738 153.848
0.259765 2.557536 0.237622 -5.18696 0.698951 0.629017 1 19.493 0.01849 0.06062 0.04525 0.02591 0.02021 0.37 0.04137 0.00696 0.00267 0.00232 0.00003 0.0048 78.128 172.86 153.88
0.285695 2.916777 0.262384 -4.330956 0.679834 0.61906 1 22.468 0.0128 0.06685 0.04246 0.0254 0.02228 0.377 0.04351 0.00661 0.00247 0.0022 0.00003 0.00442 79.068 193.221 167.93
0.253556 2.547508 0.210279 -5.248776 0.686894 0.537264 1 20.422 0.0184 0.06562 0.03772 0.0247 0.02187 0.364 0.04192 0.00663 0.00258 0.00221 0.00003 0.00476 86.18 192.735 173.917
0.215961 2.692176 0.22089 -5.557447 0.732479 0.397937 1 23.831 0.01778 0.02214 0.01497 0.00948 0.00738 0.164 0.01659 0.0114 0.0039 0.0038 0.00005 0.00742 76.779 200.841 163.656
0.219514 2.846369 0.236853 -5.571843 0.737948 0.522746 1 22.066 0.02887 0.05197 0.0378 0.02245 0.01732 0.381 0.03767 0.00948 0.00375 0.00316 0.00006 0.00633 77.968 206.002 104.4
0.147403 2.589702 0.226278 -6.18359 0.720916 0.418622 1 25.908 0.01095 0.02666 0.01872 0.01169 0.00889 0.186 0.01966 0.0075 0.00234 0.0025 0.00003 0.00455 75.501 208.313 171.041
0.162999 2.314209 0.196102 -6.27169 0.726652 0.358773 1 25.119 0.01328 0.0265 0.01826 0.01144 0.00883 0.198 0.01919 0.00749 0.00275 0.0025 0.00003 0.00496 81.737 208.701 146.845
0.108514 2.241742 0.279789 -7.120925 0.676258 0.470478 1 25.97 0.00677 0.02307 0.01661 0.01012 0.00769 0.161 0.01718 0.00476 0.00176 0.00159 0.00002 0.0031 80.055 227.383 155.358
0.135242 1.957961 0.209866 -6.635729 0.723797 0.427785 1 25.678 0.0117 0.0238 0.01799 0.01057 0.00793 0.168 0.01791 0.00841 0.00253 0.0028 0.00003 0.00502 77.63 198.346 162.568
0.085569 1.743867 0.177551 -7.3483 0.741367 0.422229 0 26.775 0.00339 0.01689 0.00802 0.0068 0.00563 0.097 0.01098 0.00498 0.00168 0.00166 0.00001 0.00289 192.055 206.896 197.076
0.068501 2.103106 0.173319 -7.682587 0.742055 0.432439 0 30.94 0.00167 0.01513 0.00762 0.00641 0.00504 0.089 0.01015 0.00402 0.00138 0.00134 0.00001 0.00241 192.091 209.512 199.228
0.09632 1.512275 0.175181 -7.067931 0.738703 0.465946 0 30.775 0.00119 0.01919 0.00951 0.00825 0.0064 0.111 0.01263 0.00339 0.00135 0.00113 0.00001 0.00212 193.104 215.203 198.383
0.056141 1.544609 0.17854 -7.695734 0.742133 0.368535 0 32.684 0.00072 0.01407 0.00719 0.00606 0.00469 0.085 0.00954 0.00278 0.00107 0.00093 0.000009 0.0018 197.079 211.604 202.266
0.044539 1.423287 0.163519 -7.964984 0.741899 0.340068 0 33.047 0.00065 0.01403 0.00726 0.0061 0.00468 0.085 0.00958 0.00283 0.00106 0.00094 0.000009 0.00178 196.16 211.526 203.184
0.05761 2.447064 0.170183 -7.777685 0.742737 0.344252 0 31.732 0.00135 0.01758 0.00957 0.0076 0.00586 0.107 0.01194 0.00314 0.00115 0.00105 0.00001 0.00198 195.708 210.565 201.464
0.165827 2.477082 0.218037 -6.149653 0.778834 0.360148 1 23.216 0.00586 0.03463 0.01612 0.01347 0.01154 0.189 0.02126 0.007 0.00241 0.00233 0.00002 0.00411 168.013 192.921 177.876
0.173218 2.536527 0.196371 -6.006414 0.783626 0.341435 1 24.951 0.0034 0.02814 0.01491 0.0116 0.00938 0.168 0.01851 0.00616 0.00218 0.00205 0.00002 0.00369 163.564 185.604 176.17
0.141929 2.269398 0.212294 -6.452058 0.766209 0.403884 1 26.738 0.00231 0.02177 0.0119 0.00885 0.00726 0.131 0.01444 0.00459 0.00166 0.00153 0.00002 0.00284 175.456 201.249 180.198
0.160691 2.382544 0.266892 -6.006647 0.758324 0.396793 1 26.31 0.00265 0.02488 0.01366 0.01003 0.00829 0.151 0.01663 0.00504 0.00182 0.00168 0.00002 0.00316 173.015 202.324 187.733
0.130554 2.374073 0.201095 -6.647379 0.765623 0.32648 1 26.822 0.00231 0.02321 0.01233 0.00941 0.00774 0.135 0.01495 0.00496 0.00175 0.00165 0.00002 0.00298 177.584 197.724 186.163
0.11573 2.361532 0.063412 -7.044105 0.759203 0.306443 1 26.453 0.00257 0.02226 0.01234 0.00901 0.00742 0.132 0.01463 0.00403 0.00147 0.00134 0.00001 0.00258 166.977 196.537 184.055
0.095032 2.416838 0.098648 -7.31055 0.654172 0.305062 0 22.736 0.0074 0.03104 0.01133 0.01024 0.01035 0.164 0.01752 0.00507 0.00182 0.00169 0.00001 0.00298 225.227 247.326 237.226
0.117399 2.256699 0.158266 -6.793547 0.634267 0.457702 0 23.145 0.00675 0.03017 0.01251 0.01038 0.01006 0.154 0.0176 0.0047 0.00173 0.00157 0.00001 0.00281 232.483 248.834 241.404
0.09147 2.330716 0.091608 -7.057869 0.635285 0.438296 0 25.368 0.00454 0.0233 0.01033 0.00898 0.00777 0.126 0.01419 0.00327 0.00137 0.00109 0.000009 0.0021 232.435 250.912 243.439
0.102706 2.3658 0.102083 -6.99582 0.638928 0.431285 0 25.032 0.00476 0.02542 0.01014 0.00879 0.00847 0.134 0.01494 0.0035 0.00139 0.00117 0.000009 0.00225 227.911 255.034 242.852
0.097336 2.392122 0.127642 -7.156076 0.631653 0.467489 0 24.602 0.00476 0.02719 0.01149 0.00977 0.00906 0.141 0.01608 0.0038 0.00148 0.00127 0.00001 0.00235 231.848 262.09 245.51
0.086398 2.028612 0.200873 -7.31951 0.635204 0.610367 0 26.805 0.00432 0.01841 0.0086 0.0073 0.00614 0.103 0.01152 0.00276 0.00113 0.00092 0.000007 0.00185 182.786 261.487 252.455
0.133867 2.079922 0.266392 -6.439398 0.733659 0.579597 0 23.162 0.00839 0.02566 0.01433 0.00776 0.00855 0.143 0.01613 0.00507 0.00203 0.00169 0.00004 0.00524 115.765 128.611 122.188
0.128872 2.054419 0.264967 -6.482096 0.754073 0.538688 0 24.971 0.00462 0.02789 0.014 0.00802 0.0093 0.154 0.01681 0.00373 0.00155 0.00124 0.00003 0.00428 114.676 130.049 122.964
0.103561 1.840198 0.254498 -6.650471 0.775933 0.553134 0 25.135 0.00479 0.03724 0.01685 0.01024 0.01241 0.197 0.02184 0.00422 0.00167 0.00141 0.00003 0.00431 117.495 135.069 124.445
0.105993 2.431854 0.291954 -6.689151 0.760361 0.507504 0 25.03 0.00474 0.03429 0.01614 0.00959 0.01143 0.185 0.02033 0.00393 0.00169 0.00131 0.00004 0.00448 112.773 134.231 126.344
0.119308 1.972297 0.220434 -7.072419 0.766204 0.459766 0 24.692 0.00481 0.03969 0.01677 0.01072 0.01323 0.21 0.02297 0.00411 0.00166 0.00137 0.00003 0.00436 122.08 138.052 128.001
0.147491 2.223719 0.269866 -6.836811 0.785714 0.420383 0 25.429 0.00484 0.04188 0.01947 0.01219 0.01396 0.228 0.02498 0.00495 0.00183 0.00165 0.00004 0.0049 118.604 139.867 129.336
0.3167 1.986899 0.205558 -4.649573 0.819032 0.536009 1 21.028 0.01036 0.0445 0.02067 0.01609 0.01483 0.255 0.02719 0.01046 0.00486 0.00349 0.00007 0.00761 102.874 134.656 108.807
0.344834 2.014606 0.221727 -4.333543 0.811843 0.558586 1 20.767 0.0118 0.05368 0.02454 0.01992 0.01789 0.307 0.03209 0.01193 0.00539 0.00398 0.00008 0.00874 104.437 126.358 109.86
0.335041 1.92294 0.238298 -4.438453 0.821364 0.541781 1 21.422 0.00969 0.06097 0.02802 0.02302 0.02032 0.334 0.03715 0.01056 0.00514 0.00352 0.00007 0.00784 103.37 131.067 110.417
0.314464 2.021591 0.290024 -4.60826 0.817756 0.530529 1 22.817 0.00681 0.03568 0.01948 0.01459 0.01189 0.221 0.02293 0.00898 0.00469 0.00299 0.00006 0.00752 110.402 129.916 117.274
0.326197 1.827012 0.262633 -4.476755 0.813432 0.540049 1 22.603 0.00786 0.04183 0.02137 0.01625 0.01394 0.265 0.02645 0.01003 0.00493 0.00334 0.00007 0.00788 108.153 131.897 116.879
0.316395 1.831691 0.221711 -4.609161 0.817396 0.547975 1 21.66 0.01143 0.05414 0.02519 0.01974 0.01805 0.35 0.03225 0.0112 0.0052 0.00373 0.00008 0.00867 104.68 271.314 114.847
0.101516 2.460791 0.066994 -7.040508 0.678874 0.341788 0 25.554 0.00871 0.02925 0.01382 0.01258 0.00975 0.17 0.01861 0.00442 0.00152 0.00147 0.00001 0.00282 109.379 237.494 209.144
0.098555 2.32156 0.086372 -7.293801 0.686264 0.447979 0 26.138 0.00301 0.03039 0.0134 0.01296 0.01013 0.165 0.01906 0.00461 0.00151 0.00154 0.00001 0.00264 98.664 238.987 223.365
0.103224 2.278687 0.095882 -6.966321 0.694399 0.364867 0 25.856 0.0034 0.02602 0.012 0.01108 0.00867 0.145 0.01643 0.00457 0.00144 0.00152 0.00001 0.00266 205.495 231.345 222.236
0.093534 2.498224 0.018689 -7.24562 0.683296 0.25657 0 25.964 0.00351 0.02647 0.01179 0.01075 0.00882 0.145 0.01644 0.00526 0.00155 0.00175 0.00001 0.00296 223.634 234.619 228.832
0.073581 2.003032 0.056844 -7.496264 0.673636 0.27685 0 26.415 0.003 0.02308 0.01016 0.00957 0.00769 0.129 0.01457 0.00342 0.00113 0.00114 0.000009 0.00205 221.156 252.221 229.401
0.091546 2.118596 0.006274 -7.314237 0.681811 0.305429 0 24.547 0.0042 0.02827 0.01234 0.0116 0.00942 0.154 0.01745 0.00408 0.0014 0.00136 0.00001 0.00238 113.201 239.541 228.969
0.226156 2.359973 0.22685 -5.409423 0.720908 0.460139 1 19.56 0.02183 0.0549 0.02428 0.0181 0.0183 0.313 0.03198 0.01289 0.0044 0.0043 0.00006 0.00817 67.021 159.774 140.341
0.226247 2.291558 0.20566 -5.324574 0.729067 0.498133 1 19.979 0.02659 0.04914 0.02603 0.01759 0.01638 0.308 0.03111 0.0152 0.00463 0.00507 0.00007 0.00923 66.004 166.607 136.969
0.18558 2.118496 0.151814 -5.86975 0.731444 0.513237 1 20.338 0.04882 0.09455 0.03392 0.02422 0.03152 0.478 0.05384 0.01941 0.00467 0.00647 0.00008 0.01101 65.809 162.215 143.533
0.141958 2.137075 0.120956 -6.261141 0.727313 0.487407 1 21.718 0.02431 0.1007 0.03635 0.02494 0.03357 0.497 0.05428 0.014 0.00354 0.00467 0.00005 0.00762 67.343 162.824 148.09
0.180828 2.277927 0.15883 -5.720868 0.730387 0.489345 1 20.264 0.02599 0.05605 0.02949 0.01906 0.01868 0.365 0.03485 0.01407 0.00419 0.00469 0.00006 0.00831 65.476 162.408 142.729
0.242981 2.642276 0.224852 -5.207985 0.733232 0.543299 1 18.57 0.03361 0.08247 0.03736 0.02466 0.02749 0.483 0.04978 0.01601 0.00478 0.00534 0.00007 0.00971 65.75 176.595 136.358
0.18818 2.205024 0.329066 -5.79182 0.762959 0.495954 1 25.742 0.00442 0.02921 0.01345 0.00925 0.00974 0.152 0.01706 0.0054 0.0022 0.0018 0.00003 0.00405 111.208 139.71 120.08
0.225461 1.928708 0.306636 -5.389129 0.789532 0.509127 1 24.178 0.00623 0.0412 0.01956 0.01375 0.01373 0.226 0.02448 0.00805 0.00329 0.00268 0.00005 0.00533 107.024 588.518 112.014
0.244512 2.225815 0.201861 -5.31336 0.815908 0.437031 1 25.438 0.00479 0.04295 0.01831 0.01325 0.01432 0.216 0.02442 0.0078 0.00283 0.0026 0.00004 0.00494 107.316 128.101 110.793
0.228624 1.862092 0.315074 -5.477592 0.807217 0.463514 1 25.197 0.00472 0.03851 0.01715 0.01219 0.01284 0.206 0.02215 0.00831 0.00289 0.00277 0.00005 0.00516 105.007 122.611 110.707
0.193918 2.007923 0.341169 -5.775966 0.789977 0.489538 1 23.37 0.00905 0.07238 0.02704 0.02231 0.02413 0.35 0.03999 0.0081 0.00289 0.0027 0.00004 0.005 106.981 148.826 112.876
0.232744 1.777901 0.250572 -5.391029 0.81634 0.429484 1 25.82 0.0042 0.03852 0.01636 0.01199 0.01284 0.197 0.02199 0.00677 0.0028 0.00226 0.00004 0.00462 106.821 125.394 110.568
0.260015 2.017753 0.249494 -5.115212 0.779612 0.644954 1 21.875 0.01062 0.05408 0.02455 0.01886 0.01803 0.263 0.03202 0.00994 0.00332 0.00331 0.00006 0.00608 90.264 102.145 95.385
0.277948 2.398422 0.265699 -4.913885 0.790117 0.594387 1 19.2 0.0222 0.0532 0.02139 0.01783 0.01773 0.361 0.03121 0.01865 0.00576 0.00622 0.0001 0.01038 85.545 115.697 100.77
0.327978 2.645959 0.155097 -4.441519 0.770466 0.544805 1 19.055 0.01823 0.06799 0.02876 0.02451 0.02266 0.364 0.04024 0.01168 0.00415 0.00389 0.00007 0.00694 84.51 108.664 96.106
0.260633 2.232576 0.210458 -5.132032 0.778747 0.576084 1 19.659 0.01825 0.05377 0.0219 0.01841 0.01792 0.296 0.03156 0.01283 0.00371 0.00428 0.00007 0.00702 87.549 107.715 95.605
0.264666 2.428306 0.146948 -5.022288 0.787896 0.55461 1 20.536 0.01237 0.04114 0.01751 0.01421 0.01371 0.216 0.02427 0.01053 0.00348 0.00351 0.00006 0.00606 95.628 110.019 100.96
0.177275 2.053601 0.078202 -6.025367 0.772416 0.576644 1 22.244 0.00882 0.03831 0.01552 0.01343 0.01277 0.202 0.02223 0.00742 0.00258 0.00247 0.00004 0.00432 87.804 102.305 98.804
0.242119 3.099301 0.343073 -5.288912 0.729586 0.556494 1 13.893 0.0547 0.08037 0.0351 0.03022 0.02679 0.435 0.04795 0.01254 0.0042 0.00418 0.00004 0.00747 75.344 205.56 176.858
0.200423 3.098256 0.315903 -5.657899 0.727747 0.583574 1 16.176 0.02782 0.06321 0.02877 0.02493 0.02107 0.331 0.03852 0.00659 0.00244 0.0022 0.00002 0.00406 155.495 200.125 180.978
0.144614 2.654271 0.335753 -6.366916 0.712199 0.598714 1 15.924 0.03151 0.06219 0.02784 0.02415 0.02073 0.327 0.03759 0.00488 0.00194 0.00163 0.00002 0.00321 141.047 202.45 178.222
0.220968 3.13655 0.299549 -5.515071 0.740837 0.602874 1 13.922 0.04824 0.11012 0.04683 0.04159 0.03671 0.58 0.06511 0.00862 0.00312 0.00287 0.00003 0.0052 125.61 227.381 176.281
0.194052 3.007096 0.299793 -5.783272 0.743937 0.599371 1 14.739 0.04214 0.11363 0.04802 0.04254 0.03788 0.65 0.06727 0.0071 0.00254 0.00237 0.00003 0.00448 74.677 211.35 173.898
0.332086 3.671155 0.375531 -4.379411 0.745526 0.590951 1 11.866 0.07223 0.06892 0.03455 0.02768 0.02297 0.442 0.04313 0.01172 0.00419 0.00391 0.00004 0.00709 144.878 225.93 179.711
0.301952 3.317586 0.389232 -4.508984 0.733165 0.65341 1 11.744 0.08725 0.10949 0.05114 0.04282 0.0365 0.634 0.0664 0.01161 0.00453 0.00387 0.00004 0.00742 78.032 206.008 166.605
0.13412 2.344876 0.207156 -6.411497 0.71436 0.501037 1 19.664 0.01658 0.13262 0.0569 0.04962 0.04421 0.772 0.07959 0.00672 0.00227 0.00224 0.00003 0.00419 147.226 163.335 151.955
0.186489 2.344336 0.08784 -5.952058 0.734504 0.454444 1 18.78 0.01914 0.0715 0.03051 0.02521 0.02383 0.383 0.0419 0.0075 0.00256 0.0025 0.00003 0.00459 142.299 164.989 148.272
0.160809 2.080121 0.17352 -6.152551 0.69779 0.447456 1 20.969 0.01211 0.10024 0.04398 0.03794 0.03341 0.637 0.05925 0.00574 0.00226 0.00191 0.00003 0.00382 76.596 161.469 152.125
0.160812 2.143851 0.188056 -6.251425 0.71217 0.50238 1 22.219 0.0085 0.06185 0.02764 0.02321 0.02062 0.307 0.03716 0.00587 0.00196 0.00196 0.00002 0.00358 68.401 172.975 157.821
0.164916 2.344348 0.180528 -6.247076 0.705658 0.447285 1 21.693 0.01018 0.05439 0.02571 0.01909 0.01813 0.283 0.03272 0.00602 0.00197 0.00201 0.00002 0.00369 149.605 163.267 157.447
0.151709 2.473239 0.194627 -6.41744 0.693429 0.366329 1 22.663 0.00852 0.05417 0.02809 0.02024 0.01806 0.307 0.03381 0.00535 0.00184 0.00178 0.00002 0.00342 144.811 168.913 159.116
0.340623 2.671825 0.265315 -4.020042 0.714485 0.629574 1 15.338 0.08151 0.06406 0.03088 0.02174 0.02135 0.342 0.03886 0.02228 0.00623 0.00743 0.0001 0.0128 116.187 143.946 125.036
0.260375 2.441612 0.202146 -5.159169 0.690892 0.57101 1 15.433 0.10323 0.07625 0.03908 0.0263 0.02542 0.422 0.04689 0.02478 0.00655 0.00826 0.00011 0.01378 96.206 140.557 125.791
0.378483 2.634633 0.242861 -3.760348 0.674953 0.638545 1 12.435 0.16744 0.10833 0.05783 0.03963 0.03611 0.659 0.06734 0.03476 0.0099 0.01159 0.00015 0.01936 99.77 141.756 126.512
0.370961 2.991063 0.260481 -3.700544 0.656846 0.671299 1 8.867 0.31482 0.16074 0.06196 0.04791 0.05358 0.891 0.09178 0.06433 0.01522 0.02144 0.00026 0.03316 116.346 141.068 125.641
0.356881 2.638279 0.310163 -4.20273 0.643327 0.639808 1 15.06 0.11843 0.09669 0.05174 0.03672 0.03223 0.584 0.0617 0.02716 0.00909 0.00905 0.00012 0.01551 75.632 150.449 128.451
0.444774 2.690917 0.270641 -3.269487 0.641418 0.596362 1 10.489 0.2593 0.16654 0.06023 0.05005 0.05551 0.93 0.09419 0.05563 0.01628 0.01854 0.00022 0.03011 66.157 586.567 139.224
0.113942 2.004055 0.089267 -6.878393 0.722356 0.296888 1 26.759 0.00495 0.01567 0.01009 0.00659 0.00522 0.107 0.01131 0.00315 0.00136 0.00105 0.00002 0.00248 75.349 154.609 150.258
0.093193 2.065477 0.14478 -7.111576 0.691483 0.263654 1 28.409 0.00243 0.01406 0.00871 0.00582 0.00469 0.094 0.0103 0.00229 0.001 0.00076 0.00001 0.00183 128.621 160.267 154.003
0.112878 1.994387 0.210279 -6.997403 0.719974 0.365488 1 27.421 0.00578 0.01979 0.01059 0.00818 0.0066 0.126 0.01346 0.00349 0.00134 0.00116 0.00002 0.00257 133.608 160.368 149.689
0.106802 2.129924 0.18455 -6.981201 0.67793 0.334171 1 29.746 0.00233 0.01567 0.00928 0.00632 0.00522 0.097 0.01064 0.00204 0.00092 0.00068 0.00001 0.00168 144.148 163.736 155.078
0.105306 2.499148 0.249172 -6.600023 0.700246 0.393563 1 26.833 0.00659 0.01898 0.01267 0.00788 0.00633 0.137 0.0145 0.00346 0.00122 0.00115 0.00002 0.00258 133.751 157.765 151.884
0.11513 2.296873 0.160686 -6.739151 0.676066 0.311369 1 29.928 0.00238 0.01364 0.00993 0.00576 0.00455 0.093 0.01024 0.00225 0.00096 0.00075 0.00001 0.00174 132.857 157.339 151.989
0.185668 2.608749 0.278679 -5.845099 0.740539 0.497554 1 21.934 0.00947 0.05312 0.02084 0.01815 0.01771 0.275 0.03044 0.01351 0.00389 0.0045 0.00004 0.00766 80.297 208.9 193.03
0.23252 2.550961 0.256454 -5.25832 0.727863 0.436084 1 23.239 0.00704 0.03576 0.01852 0.01439 0.01192 0.207 0.02286 0.01112 0.00337 0.00371 0.00003 0.00621 89.686 223.982 200.714
0.13639 2.502336 0.184378 -6.471427 0.712466 0.338097 1 22.407 0.0083 0.02855 0.01307 0.01058 0.00952 0.155 0.01761 0.01105 0.00339 0.00368 0.00003 0.00609 199.02 220.315 208.519
0.268144 2.376749 0.212054 -4.876336 0.722085 0.498877 1 21.305 0.01316 0.03831 0.01767 0.01483 0.01277 0.21 0.02378 0.01506 0.00485 0.00502 0.00004 0.00841 189.621 221.3 204.664
0.177807 2.489191 0.250283 -5.96304 0.722254 0.441097 1 23.671 0.0062 0.02583 0.01301 0.01017 0.00861 0.149 0.0168 0.00964 0.0028 0.00321 0.00003 0.00534 185.258 232.706 210.141
0.115515 2.938114 0.181701 -6.729713 0.715121 0.331508 1 21.864 0.01048 0.0332 0.01604 0.01284 0.01107 0.209 0.02105 0.00905 0.00246 0.00302 0.00002 0.00495 92.02 226.355 206.327
0.274407 2.702355 0.261549 -4.673241 0.662668 0.407701 1 23.693 0.06051 0.02389 0.01271 0.00832 0.00796 0.235 0.01843 0.01211 0.00385 0.00404 0.00006 0.00856 69.085 492.892 151.872
0.170106 2.640798 0.27328 -6.051233 0.653823 0.450798 1 26.356 0.01554 0.01818 0.01312 0.00747 0.00606 0.148 0.01458 0.00642 0.00207 0.00214 0.00003 0.00476 71.948 442.557 158.219
0.28278 2.975889 0.372114 -4.597834 0.676023 0.486738 1 25.69 0.01802 0.0227 0.01652 0.00971 0.00757 0.175 0.01725 0.00731 0.00261 0.00244 0.00003 0.00555 79.032 450.247 170.756
0.251972 2.816781 0.393056 -4.913137 0.655239 0.470422 1 25.02 0.00856 0.01851 0.01151 0.00744 0.00617 0.129 0.01279 0.00472 0.00194 0.00157 0.00003 0.00462 82.063 442.824 178.285
0.220657 2.925862 0.389295 -5.517173 0.58271 0.462516 1 24.581 0.00681 0.02038 0.01075 0.00631 0.00679 0.124 0.01299 0.00381 0.00128 0.00127 0.00002 0.00404 93.978 233.481 217.116
0.152428 2.68624 0.279933 -6.186128 0.68413 0.487756 1 24.743 0.0235 0.02548 0.01734 0.01117 0.00849 0.221 0.02008 0.00723 0.00314 0.00241 0.00005 0.00581 88.251 479.697 128.94
0.234809 2.655744 0.281618 -4.711007 0.656182 0.400088 1 27.166 0.01161 0.01603 0.01104 0.0063 0.00534 0.117 0.01169 0.00628 0.00221 0.00209 0.00003 0.0046 83.961 215.293 176.824
0.229892 2.090438 0.160267 -5.418787 0.74148 0.538016 1 18.305 0.01968 0.07761 0.0322 0.02567 0.02587 0.441 0.04479 0.01218 0.00398 0.00406 0.00005 0.00704 83.34 203.522 138.19
0.215558 2.174306 0.142466 -5.44514 0.732903 0.589956 1 18.784 0.01813 0.04115 0.01931 0.0158 0.01372 0.231 0.02503 0.01517 0.00449 0.00506 0.00005 0.00842 79.187 197.173 182.018
0.181988 1.929715 0.143359 -5.944191 0.728421 0.618663 1 19.196 0.0202 0.03867 0.0172 0.0142 0.01289 0.224 0.02343 0.01209 0.00395 0.00403 0.00004 0.00694 79.82 195.107 156.239
0.222716 1.765957 0.12795 -5.594275 0.735546 0.637518 1 18.857 0.01874 0.03706 0.01944 0.01495 0.01235 0.233 0.02362 0.01242 0.00422 0.00414 0.00005 0.00733 80.637 198.109 145.174
0.214075 1.821297 0.087165 -5.540351 0.738245 0.623209 1 18.178 0.01794 0.04451 0.02259 0.01805 0.01484 0.246 0.02791 0.00883 0.00327 0.00294 0.00004 0.00544 81.114 197.238 138.145
0.196535 1.996146 0.115697 -5.825257 0.736964 0.585169 1 18.33 0.01796 0.04641 0.02301 0.01859 0.01547 0.257 0.02857 0.01104 0.00351 0.00368 0.00004 0.00638 79.512 198.966 166.888
0.112856 2.328513 0.152941 -6.890021 0.699787 0.457541 1 26.842 0.01724 0.01614 0.00811 0.0057 0.00538 0.098 0.01033 0.00641 0.00192 0.00214 0.00004 0.0044 109.216 127.533 119.031
0.183572 2.108873 0.195976 -5.892061 0.718839 0.491345 1 26.369 0.00487 0.01428 0.00903 0.00588 0.00476 0.09 0.01022 0.00349 0.00135 0.00116 0.00002 0.0027 105.667 126.632 120.078
0.169923 2.539724 0.20363 -6.135296 0.724045 0.46716 1 23.949 0.0161 0.0211 0.01194 0.0082 0.00703 0.125 0.01412 0.00808 0.00238 0.00269 0.00004 0.00492 100.209 128.143 120.289
0.170633 2.527742 0.217013 -6.112667 0.735136 0.468621 1 26.017 0.01015 0.02164 0.0131 0.00815 0.00721 0.138 0.01516 0.00671 0.00205 0.00224 0.00003 0.00407 104.773 125.306 120.256
0.232209 2.51632 0.254909 -5.436135 0.721308 0.470972 1 23.389 0.00903 0.01898 0.00915 0.00701 0.00633 0.106 0.01201 0.00508 0.0017 0.00169 0.00003 0.00346 86.795 125.213 119.056
0.141422 2.034827 0.178713 -6.448134 0.723096 0.482296 1 25.619 0.00504 0.01471 0.00903 0.00621 0.0049 0.099 0.01043 0.00504 0.00171 0.00168 0.00003 0.00331 109.836 123.723 118.747
0.24308 2.375138 0.320385 -5.301321 0.744064 0.637814 1 17.06 0.03031 0.0805 0.03651 0.03112 0.02683 0.441 0.04932 0.00873 0.00319 0.00291 0.00006 0.00589 93.105 112.777 106.516
0.228319 2.631793 0.322044 -5.333619 0.706687 0.653427 1 17.707 0.02529 0.06688 0.03316 0.02592 0.02229 0.379 0.04128 0.00731 0.00315 0.00244 0.00004 0.00494 105.554 127.611 110.453
0.259451 2.445502 0.300067 -4.378916 0.708144 0.6479 1 19.013 0.02278 0.07154 0.0437 0.02973 0.02385 0.431 0.04879 0.00658 0.00283 0.00219 0.00004 0.00451 107.816 133.344 113.4
0.274387 2.672362 0.304107 -4.654894 0.708617 0.625362 1 16.747 0.0369 0.08689 0.04134 0.03347 0.02896 0.476 0.05279 0.00772 0.00312 0.00257 0.00004 0.00502 100.673 130.27 113.166
0.209191 2.419253 0.306014 -5.634576 0.701404 0.640945 1 17.366 0.02629 0.09211 0.04451 0.0353 0.0307 0.517 0.05643 0.00715 0.0029 0.00238 0.00004 0.00472 104.095 126.609 112.239
0.184985 2.445646 0.23307 -5.866357 0.696049 0.624811 1 18.801 0.01827 0.04543 0.0277 0.01812 0.01514 0.267 0.03026 0.00542 0.00232 0.00181 0.00003 0.00381 109.815 131.731 116.15
0.277227 2.963799 0.397749 -4.796845 0.685057 0.677131 1 18.54 0.02485 0.05139 0.02824 0.01964 0.01713 0.281 0.03273 0.00696 0.00269 0.00232 0.00003 0.00571 79.543 268.796 170.368
0.231723 2.665133 0.288917 -5.410336 0.665945 0.606344 1 15.648 0.04238 0.12047 0.04464 0.04003 0.04016 0.571 0.06725 0.01285 0.00428 0.00428 0.00004 0.00757 91.802 253.792 208.083
0.209863 2.465528 0.310746 -5.585259 0.661735 0.606273 1 18.702 0.01728 0.06165 0.0253 0.02076 0.02055 0.297 0.03527 0.00546 0.00215 0.00182 0.00002 0.00376 148.691 219.29 198.458
0.189032 2.470746 0.213353 -5.898673 0.632631 0.536102 1 18.687 0.0201 0.0335 0.01506 0.01177 0.01117 0.18 0.01997 0.00568 0.00211 0.00189 0.00002 0.0037 86.232 231.508 202.805
0.159777 2.576563 0.220617 -6.132663 0.630409 0.49748 1 20.68 0.01049 0.04426 0.02006 0.01558 0.01475 0.228 0.02662 0.00301 0.00133 0.001 0.00001 0.00254 164.168 241.35 202.544
0.232861 2.840556 0.345238 -5.456811 0.574282 0.566849 1 20.366 0.01493 0.04137 0.01909 0.01478 0.01379 0.225 0.02536 0.00506 0.00188 0.00169 0.00002 0.00352 87.638 263.872 223.361
0.457533 3.413649 0.414758 -3.297668 0.793509 0.56161 1 12.359 0.0753 0.11411 0.08808 0.05426 0.03804 0.821 0.08143 0.02589 0.00946 0.00863 0.00009 0.01568 151.451 191.759 169.774
0.336085 3.142364 0.355736 -4.276605 0.768974 0.478024 1 14.367 0.06057 0.08595 0.06359 0.04101 0.02865 0.618 0.0605 0.02546 0.00819 0.00849 0.00008 0.01466 161.34 216.814 183.52
0.418646 3.274865 0.335357 -3.377325 0.764036 0.55287 1 12.298 0.08069 0.10422 0.06824 0.0458 0.03474 0.722 0.07118 0.02987 0.01027 0.00996 0.00009 0.01719 165.982 216.302 188.62
0.270173 2.910213 0.262281 -4.892495 0.775708 0.427627 1 14.989 0.07889 0.10546 0.0646 0.04265 0.03515 0.833 0.0717 0.02756 0.00963 0.00919 0.00008 0.01627 177.258 565.74 202.632
0.301487 2.958815 0.340256 -4.484303 0.762726 0.507826 1 12.529 0.10952 0.08096 0.06259 0.03714 0.02699 0.784 0.0583 0.03225 0.01154 0.01075 0.0001 0.01872 149.442 211.961 186.695
0.527367 3.079221 0.450493 -2.434031 0.76832 0.625866 1 8.441 0.21713 0.16942 0.13778 0.0794 0.05647 1.302 0.11908 0.05401 0.01958 0.018 0.00016 0.03107 168.793 224.429 192.818
0.454721 3.184027 0.356224 -2.839756 0.754449 0.584164 1 9.449 0.16265 0.12851 0.08318 0.05556 0.04284 1.018 0.08684 0.04705 0.01699 0.01568 0.00014 0.02714 174.478 233.099 198.116
0.168581 2.01353 0.246404 -4.865194 0.670475 0.566867 1 21.52 0.04179 0.04019 0.02056 0.01399 0.0134 0.241 0.02534 0.01164 0.00332 0.00388 0.00006 0.00684 98.25 139.644 121.345
0.247455 2.45113 0.175691 -4.239028 0.659333 0.65168 1 21.824 0.04611 0.04451 0.02018 0.01405 0.01484 0.236 0.02682 0.01179 0.003 0.00393 0.00006 0.00692 88.833 128.442 119.1
0.206256 2.439597 0.207914 -3.583722 0.652025 0.6283 1 22.431 0.02631 0.04977 0.02402 0.01804 0.01659 0.276 0.03087 0.01067 0.003 0.00356 0.00005 0.00647 95.654 127.349 117.87
0.220546 2.699645 0.230532 -5.4351 0.623731 0.611679 1 22.953 0.03191 0.03615 0.01771 0.01289 0.01205 0.223 0.02293 0.01246 0.00339 0.00415 0.00006 0.00727 94.794 142.369 122.336
0.261305 2.964568 0.303214 -3.444478 0.646786 0.630547 1 19.075 0.10748 0.0783 0.02916 0.02161 0.0261 0.438 0.04912 0.03351 0.00718 0.01117 0.00015 0.01813 100.757 134.209 117.963
0.249703 2.8923 0.280091 -5.070096 0.627337 0.635015 1 21.534 0.03828 0.04499 0.02157 0.01581 0.015 0.266 0.02852 0.01778 0.00454 0.00593 0.00008 0.00975 97.543 154.284 126.144
0.216638 2.103014 0.234196 -5.498456 0.675865 0.654945 1 19.651 0.02663 0.04079 0.03105 0.0165 0.0136 0.339 0.03235 0.00962 0.00318 0.00321 0.00005 0.00605 112.173 138.752 127.93
0.244948 2.151121 0.259229 -5.185987 0.694571 0.653139 1 20.437 0.02073 0.04736 0.04114 0.01994 0.01579 0.406 0.04009 0.00896 0.00316 0.00299 0.00005 0.00581 77.022 124.393 114.238
0.238281 2.442906 0.226528 -5.283009 0.684373 0.577802 1 19.388 0.0281 0.04933 0.02931 0.01722 0.01644 0.325 0.03273 0.01057 0.00329 0.00352 0.00005 0.00619 107.802 135.738 115.322
0.22052 2.408689 0.24275 -5.529833 0.719576 0.685151 1 18.954 0.02707 0.05592 0.03091 0.0194 0.01864 0.369 0.03658 0.01097 0.0034 0.00366 0.00006 0.00651 91.121 126.778 114.554
0.212386 1.871871 0.184896 -5.617124 0.673086 0.557045 1 21.219 0.01435 0.02902 0.01363 0.01033 0.00967 0.155 0.01756 0.00873 0.00284 0.00291 0.00005 0.00519 97.527 131.669 112.15
0.367233 2.560422 0.396746 -2.929379 0.674562 0.671378 1 18.447 0.03882 0.04736 0.02073 0.01553 0.01579 0.272 0.02814 0.0148 0.00461 0.00493 0.00009 0.00907 85.902 142.83 102.273
0.119652 2.235197 0.17227 -6.816086 0.628232 0.469928 0 24.078 0.0062 0.04231 0.01621 0.01426 0.0141 0.217 0.02448 0.00462 0.00153 0.00154 0.00001 0.00277 102.137 244.663 236.2
0.091604 1.852402 0.176316 -7.018057 0.62671 0.384868 0 24.679 0.00533 0.02089 0.00882 0.00747 0.00696 0.116 0.01242 0.00519 0.00159 0.00173 0.00001 0.00303 229.256 243.709 237.323
0.075587 1.881767 0.160414 -7.517934 0.628058 0.440988 0 21.083 0.0091 0.03557 0.01367 0.0123 0.01186 0.197 0.0203 0.00616 0.00186 0.00205 0.00001 0.00339 237.303 264.919 260.105
0.202879 2.88245 0.164529 -5.736781 0.725216 0.372222 0 19.269 0.01337 0.03836 0.01439 0.01272 0.01279 0.189 0.02177 0.0147 0.00448 0.0049 0.00004 0.00803 90.794 217.627 197.569
0.100881 2.266432 0.073298 -7.169701 0.646167 0.371837 0 21.02 0.00965 0.03529 0.01344 0.01191 0.01176 0.212 0.02018 0.00949 0.00283 0.00316 0.00002 0.00517 219.783 245.135 240.301
0.09622 2.095237 0.171088 -7.3045 0.646818 0.522812 0 21.528 0.01049 0.03253 0.01255 0.01121 0.01084 0.181 0.01897 0.00837 0.00237 0.00279 0.00002 0.00451 239.17 272.21 244.99
0.160376 2.193412 0.218885 -6.323531 0.7567 0.413295 0 26.436 0.00435 0.01992 0.0114 0.00786 0.00664 0.129 0.01358 0.00499 0.0019 0.00166 0.00003 0.00355 105.715 133.374 112.547
0.174152 1.889002 0.192375 -6.085567 0.776158 0.36909 0 26.55 0.0043 0.02261 0.01285 0.0095 0.00754 0.133 0.01484 0.0051 0.002 0.0017 0.00003 0.00356 100.139 113.597 110.739
0.179677 1.852542 0.19215 -5.943501 0.7667 0.380253 0 26.547 0.00478 0.02245 0.01148 0.00905 0.00748 0.133 0.01472 0.00514 0.00203 0.00171 0.00003 0.00349 96.913 116.443 113.715
0.163118 1.872946 0.229298 -6.012559 0.756482 0.387482 0 25.445 0.0059 0.02643 0.01318 0.01062 0.00881 0.145 0.01657 0.00528 0.00218 0.00176 0.00003 0.00353 99.923 144.466 117.004
0.184067 1.974857 0.197938 -5.966779 0.761255 0.405991 0 26.005 0.00401 0.02436 0.01133 0.00933 0.00812 0.137 0.01503 0.0048 0.00199 0.0016 0.00003 0.00332 108.634 123.109 115.38
0.174429 2.004719 0.109256 -6.016891 0.763242 0.361232 0 26.143 0.00415 0.02623 0.01331 0.01021 0.00874 0.155 0.01725 0.00507 0.00213 0.00169 0.00003 0.00346 108.97 129.038 116.388
0.132703 2.449763 0.197919 -6.486822 0.745957 0.39661 1 24.151 0.0057 0.02184 0.0123 0.00886 0.00728 0.132 0.01469 0.00406 0.00162 0.00135 0.00002 0.00314 129.859 190.204 151.737
0.160306 2.251553 0.182459 -6.311987 0.762508 0.402591 1 24.412 0.00488 0.02518 0.01309 0.00956 0.00839 0.142 0.01574 0.00456 0.00186 0.00152 0.00002 0.00309 138.99 158.359 148.79
0.19273 2.845109 0.240875 -5.711205 0.778349 0.398499 1 23.683 0.0054 0.02175 0.01263 0.00876 0.00725 0.131 0.0145 0.00612 0.00231 0.00204 0.00003 0.00392 135.041 155.982 148.143
0.144105 2.264226 0.183218 -6.261446 0.75932 0.352396 1 23.133 0.00611 0.03964 0.02148 0.01574 0.01321 0.237 0.02551 0.00619 0.00233 0.00206 0.00003 0.00396 144.736 163.441 150.44
0.19771 2.679185 0.216204 -5.704053 0.768845 0.408598 1 22.866 0.00639 0.02849 0.01559 0.01103 0.0095 0.163 0.01831 0.00605 0.00235 0.00202 0.00003 0.00397 141.998 161.078 148.462
0.156368 2.209021 0.109397 -6.27717 0.75718 0.329577 1 23.008 0.00595 0.03464 0.01666 0.01341 0.01155 0.198 0.02145 0.00521 0.00198 0.00174 0.00002 0.00336 144.786 163.417 149.818
0.215724 2.027228 0.191576 -5.61907 0.669565 0.603515 0 23.079 0.00955 0.02592 0.01949 0.01223 0.00864 0.171 0.01909 0.00558 0.0027 0.00186 0.00004 0.00417 106.656 123.925 117.226
0.252404 2.120412 0.206768 -5.198864 0.656516 0.663842 0 22.085 0.01179 0.02429 0.01756 0.01144 0.0081 0.163 0.01795 0.0078 0.00346 0.0026 0.00005 0.00531 99.503 217.552 116.848
0.214346 2.058658 0.133917 -5.592584 0.654331 0.598515 0 24.199 0.00737 0.02001 0.01691 0.0099 0.00667 0.136 0.01564 0.00403 0.00192 0.00134 0.00003 0.00314 96.983 177.291 116.286
0.120605 2.161936 0.15331 -6.431119 0.667654 0.566424 0 23.958 0.01397 0.0246 0.01491 0.00972 0.0082 0.154 0.0166 0.00762 0.00263 0.00254 0.00004 0.00496 86.228 592.03 116.556
0.138868 2.152083 0.116636 -6.359018 0.663884 0.528485 0 25.023 0.0068 0.01892 0.01144 0.00789 0.00631 0.117 0.013 0.00345 0.00148 0.00115 0.00002 0.00267 94.246 581.289 116.342
0.121777 1.91399 0.149694 -6.710219 0.659132 0.555303 0 24.775 0.00703 0.01672 0.01095 0.00721 0.00557 0.106 0.01185 0.00439 0.00184 0.00146 0.00003 0.00327 86.647 119.167 114.563
0.112838 2.316346 0.15989 -6.934474 0.683761 0.508479 0 19.368 0.04441 0.04363 0.01758 0.01582 0.01454 0.255 0.02574 0.01235 0.00396 0.00412 0.00003 0.00694 78.228 262.707 201.774
0.13305 2.657476 0.121952 -6.538586 0.657899 0.448439 0 19.517 0.02764 0.07008 0.02745 0.02498 0.02336 0.405 0.04087 0.0079 0.00259 0.00263 0.00003 0.00459 94.261 230.978 174.188
0.168895 2.784312 0.129303 -6.195325 0.683244 0.431674 0 19.147 0.0181 0.04812 0.01879 0.01657 0.01604 0.263 0.02751 0.00994 0.00292 0.00331 0.00003 0.00564 89.488 253.017 209.516
0.131728 2.679772 0.158453 -6.787197 0.655683 0.407567 0 17.883 0.10715 0.03804 0.01667 0.01365 0.01268 0.256 0.02308 0.01873 0.00564 0.00624 0.00008 0.0136 74.287 240.005 174.688
0.123306 2.138608 0.207454 -6.744577 0.643956 0.451221 0 19.02 0.07223 0.03794 0.01588 0.01321 0.01265 0.241 0.02296 0.01109 0.0039 0.0037 0.00004 0.0074 74.904 396.961 198.764
0.148569 2.555477 0.190667 -5.724056 0.664357 0.462803 0 21.209 0.04398 0.03078 0.01373 0.01161 0.01026 0.19 0.01884 0.00885 0.00317 0.00295 0.00003 0.00567 77.973 260.277 214.289

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time34 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 34 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232117&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]34 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232117&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232117&T=0

As an alternative you can also use a QR Code:  
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 time34 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






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

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
status[t] =  +  2.22477 +  1.26346PPE[t] +  0.0494602D2[t] +  1.26558spread2[t] +  0.127298spread1[t] +  0.355145DFA[t] -1.01446RPDE[t] -0.0156926HNR[t] -2.52562NHR[t] +  283.748`Shimmer:DDA`[t] -3.07476`MDVP:APQ`[t] -26.3959`Shimmer:APQ5`[t] -871.24`Shimmer:APQ3`[t] +  0.571023`MDVP:Shimmer(dB)`[t] +  27.4496`MDVP:Shimmer`[t] +  360.584`Jitter:DDP`[t] -36.1351`MDVP:PPQ`[t] -759.215`MDVP:RAP`[t] -3321.64`MDVP:Jitter(Abs)`[t] -176.913`MDVP:Jitter(%)`[t] -0.0015351`MDVP:Flo(Hz)`[t] -0.00011523`MDVP:Fhi(Hz)`[t] -0.00238441`MDVP:Fo(Hz)`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232117&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]status[t] =  +  2.22477 +  1.26346PPE[t] +  0.0494602D2[t] +  1.26558spread2[t] +  0.127298spread1[t] +  0.355145DFA[t] -1.01446RPDE[t] -0.0156926HNR[t] -2.52562NHR[t] +  283.748`Shimmer:DDA`[t] -3.07476`MDVP:APQ`[t] -26.3959`Shimmer:APQ5`[t] -871.24`Shimmer:APQ3`[t] +  0.571023`MDVP:Shimmer(dB)`[t] +  27.4496`MDVP:Shimmer`[t] +  360.584`Jitter:DDP`[t] -36.1351`MDVP:PPQ`[t] -759.215`MDVP:RAP`[t] -3321.64`MDVP:Jitter(Abs)`[t] -176.913`MDVP:Jitter(%)`[t] -0.0015351`MDVP:Flo(Hz)`[t] -0.00011523`MDVP:Fhi(Hz)`[t] -0.00238441`MDVP:Fo(Hz)`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232117&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232117&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Estimated Regression Equation
status[t] = + 2.22477 + 1.26346PPE[t] + 0.0494602D2[t] + 1.26558spread2[t] + 0.127298spread1[t] + 0.355145DFA[t] -1.01446RPDE[t] -0.0156926HNR[t] -2.52562NHR[t] + 283.748`Shimmer:DDA`[t] -3.07476`MDVP:APQ`[t] -26.3959`Shimmer:APQ5`[t] -871.24`Shimmer:APQ3`[t] + 0.571023`MDVP:Shimmer(dB)`[t] + 27.4496`MDVP:Shimmer`[t] + 360.584`Jitter:DDP`[t] -36.1351`MDVP:PPQ`[t] -759.215`MDVP:RAP`[t] -3321.64`MDVP:Jitter(Abs)`[t] -176.913`MDVP:Jitter(%)`[t] -0.0015351`MDVP:Flo(Hz)`[t] -0.00011523`MDVP:Fhi(Hz)`[t] -0.00238441`MDVP:Fo(Hz)`[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
PPE1.263461.383350.91330.3623460.181173
D20.04946020.1143240.43260.6658240.332912
spread21.265580.4780052.6480.008859430.00442971
spread10.1272980.09789831.30.1952340.0976171
DFA0.3551450.7393820.48030.6316060.315803
RPDE-1.014460.439539-2.3080.0221890.0110945
HNR-0.01569260.0143431-1.0940.2754440.137722
NHR-2.525621.98061-1.2750.2039670.101983
`Shimmer:DDA`283.7482989.960.09490.9245050.462252
`MDVP:APQ`-3.0747610.8911-0.28230.7780380.389019
`Shimmer:APQ5`-26.395920.1229-1.3120.1913590.0956797
`Shimmer:APQ3`-871.248972.17-0.09710.9227560.461378
`MDVP:Shimmer(dB)`0.5710231.199320.47610.6345910.317295
`MDVP:Shimmer`27.449634.2830.80070.4244240.212212
`Jitter:DDP`360.5843111.480.11590.9078760.453938
`MDVP:PPQ`-36.135188.3839-0.40880.6831630.341582
`MDVP:RAP`-759.2159331.88-0.081360.9352530.467626
`MDVP:Jitter(Abs)`-3321.644625.65-0.71810.4736760.236838
`MDVP:Jitter(%)`-176.91367.0287-2.6390.009069330.00453467
`MDVP:Flo(Hz)`-0.00153510.000802317-1.9130.05736640.0286832
`MDVP:Fhi(Hz)`-0.000115230.000321058-0.35890.7201050.360053
`MDVP:Fo(Hz)`-0.002384410.00151006-1.5790.1161690.0580847

\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
PPE & 1.26346 & 1.38335 & 0.9133 & 0.362346 & 0.181173 \tabularnewline
D2 & 0.0494602 & 0.114324 & 0.4326 & 0.665824 & 0.332912 \tabularnewline
spread2 & 1.26558 & 0.478005 & 2.648 & 0.00885943 & 0.00442971 \tabularnewline
spread1 & 0.127298 & 0.0978983 & 1.3 & 0.195234 & 0.0976171 \tabularnewline
DFA & 0.355145 & 0.739382 & 0.4803 & 0.631606 & 0.315803 \tabularnewline
RPDE & -1.01446 & 0.439539 & -2.308 & 0.022189 & 0.0110945 \tabularnewline
HNR & -0.0156926 & 0.0143431 & -1.094 & 0.275444 & 0.137722 \tabularnewline
NHR & -2.52562 & 1.98061 & -1.275 & 0.203967 & 0.101983 \tabularnewline
`Shimmer:DDA` & 283.748 & 2989.96 & 0.0949 & 0.924505 & 0.462252 \tabularnewline
`MDVP:APQ` & -3.07476 & 10.8911 & -0.2823 & 0.778038 & 0.389019 \tabularnewline
`Shimmer:APQ5` & -26.3959 & 20.1229 & -1.312 & 0.191359 & 0.0956797 \tabularnewline
`Shimmer:APQ3` & -871.24 & 8972.17 & -0.0971 & 0.922756 & 0.461378 \tabularnewline
`MDVP:Shimmer(dB)` & 0.571023 & 1.19932 & 0.4761 & 0.634591 & 0.317295 \tabularnewline
`MDVP:Shimmer` & 27.4496 & 34.283 & 0.8007 & 0.424424 & 0.212212 \tabularnewline
`Jitter:DDP` & 360.584 & 3111.48 & 0.1159 & 0.907876 & 0.453938 \tabularnewline
`MDVP:PPQ` & -36.1351 & 88.3839 & -0.4088 & 0.683163 & 0.341582 \tabularnewline
`MDVP:RAP` & -759.215 & 9331.88 & -0.08136 & 0.935253 & 0.467626 \tabularnewline
`MDVP:Jitter(Abs)` & -3321.64 & 4625.65 & -0.7181 & 0.473676 & 0.236838 \tabularnewline
`MDVP:Jitter(%)` & -176.913 & 67.0287 & -2.639 & 0.00906933 & 0.00453467 \tabularnewline
`MDVP:Flo(Hz)` & -0.0015351 & 0.000802317 & -1.913 & 0.0573664 & 0.0286832 \tabularnewline
`MDVP:Fhi(Hz)` & -0.00011523 & 0.000321058 & -0.3589 & 0.720105 & 0.360053 \tabularnewline
`MDVP:Fo(Hz)` & -0.00238441 & 0.00151006 & -1.579 & 0.116169 & 0.0580847 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232117&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]PPE[/C][C]1.26346[/C][C]1.38335[/C][C]0.9133[/C][C]0.362346[/C][C]0.181173[/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]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]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]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]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]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]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]`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]`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: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]`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]`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]`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]`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: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]`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: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: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: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: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:Fo(Hz)`[/C][C]-0.00238441[/C][C]0.00151006[/C][C]-1.579[/C][C]0.116169[/C][C]0.0580847[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232117&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232117&T=2

As an alternative you can also use a QR Code:  
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
PPE1.263461.383350.91330.3623460.181173
D20.04946020.1143240.43260.6658240.332912
spread21.265580.4780052.6480.008859430.00442971
spread10.1272980.09789831.30.1952340.0976171
DFA0.3551450.7393820.48030.6316060.315803
RPDE-1.014460.439539-2.3080.0221890.0110945
HNR-0.01569260.0143431-1.0940.2754440.137722
NHR-2.525621.98061-1.2750.2039670.101983
`Shimmer:DDA`283.7482989.960.09490.9245050.462252
`MDVP:APQ`-3.0747610.8911-0.28230.7780380.389019
`Shimmer:APQ5`-26.395920.1229-1.3120.1913590.0956797
`Shimmer:APQ3`-871.248972.17-0.09710.9227560.461378
`MDVP:Shimmer(dB)`0.5710231.199320.47610.6345910.317295
`MDVP:Shimmer`27.449634.2830.80070.4244240.212212
`Jitter:DDP`360.5843111.480.11590.9078760.453938
`MDVP:PPQ`-36.135188.3839-0.40880.6831630.341582
`MDVP:RAP`-759.2159331.88-0.081360.9352530.467626
`MDVP:Jitter(Abs)`-3321.644625.65-0.71810.4736760.236838
`MDVP:Jitter(%)`-176.91367.0287-2.6390.009069330.00453467
`MDVP:Flo(Hz)`-0.00153510.000802317-1.9130.05736640.0286832
`MDVP:Fhi(Hz)`-0.000115230.000321058-0.35890.7201050.360053
`MDVP:Fo(Hz)`-0.002384410.00151006-1.5790.1161690.0580847






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=232117&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=232117&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232117&T=3

As an alternative you can also use a QR Code:  
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=232117&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=232117&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232117&T=4

As an alternative you can also use a QR Code:  
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
281.34606e-762.69212e-761
293.41667e-946.83333e-941
303.72451e-1067.44901e-1061
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 & 1.34606e-76 & 2.69212e-76 & 1 \tabularnewline
29 & 3.41667e-94 & 6.83333e-94 & 1 \tabularnewline
30 & 3.72451e-106 & 7.44901e-106 & 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=232117&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]1.34606e-76[/C][C]2.69212e-76[/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]3.72451e-106[/C][C]7.44901e-106[/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=232117&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232117&T=5

As an alternative you can also use a QR Code:  
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
281.34606e-762.69212e-761
293.41667e-946.83333e-941
303.72451e-1067.44901e-1061
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=232117&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=232117&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232117&T=6

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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


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 7 ; 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')
}