FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationMon, 14 Dec 2015 11:28:34 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Dec/14/t14500925785ikx6e1gjgj7e99.htm/, Retrieved Thu, 16 May 2024 10:39:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=286263, Retrieved Thu, 16 May 2024 10:39:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2015-12-14 11:28:34] [5b06bf1f33fbfa9d6fb3148fdcb0ae6c] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1 119.992 74.997 0.00784 0.00007 0.01109 0.426 0.0313 0.02211 21.033 0.414783 0.815285 -4.813031 0.266482 0.00554
1 122.4 113.819 0.00968 0.00008 0.01394 0.626 0.04518 0.01929 19.085 0.458359 0.819521 -4.075192 0.33559 0.00696
1 116.682 111.555 0.0105 0.00009 0.01633 0.482 0.03858 0.01309 20.651 0.429895 0.825288 -4.443179 0.311173 0.00781
1 116.676 111.366 0.00997 0.00009 0.01505 0.517 0.04005 0.01353 20.644 0.434969 0.819235 -4.117501 0.334147 0.00698
1 116.014 110.655 0.01284 0.00011 0.01966 0.584 0.04825 0.01767 19.649 0.417356 0.823484 -3.747787 0.234513 0.00908
1 120.552 113.787 0.00968 0.00008 0.01388 0.456 0.03526 0.01222 21.378 0.415564 0.825069 -4.242867 0.299111 0.0075
1 120.267 114.82 0.00333 0.00003 0.00466 0.14 0.00937 0.00607 24.886 0.59604 0.764112 -5.634322 0.257682 0.00202
1 107.332 104.315 0.0029 0.00003 0.00431 0.134 0.00946 0.00344 26.892 0.63742 0.763262 -6.167603 0.183721 0.00182
1 95.73 91.754 0.00551 0.00006 0.0088 0.191 0.01277 0.0107 21.812 0.615551 0.773587 -5.498678 0.327769 0.00332
1 95.056 91.226 0.00532 0.00006 0.00803 0.255 0.01725 0.01022 21.862 0.547037 0.798463 -5.011879 0.325996 0.00332
1 88.333 84.072 0.00505 0.00006 0.00763 0.197 0.01342 0.01166 21.118 0.611137 0.776156 -5.24977 0.391002 0.0033
1 91.904 86.292 0.0054 0.00006 0.00844 0.249 0.01641 0.01141 21.414 0.58339 0.79252 -4.960234 0.363566 0.00336
1 136.926 131.276 0.00293 0.00002 0.00355 0.112 0.00717 0.00581 25.703 0.4606 0.646846 -6.547148 0.152813 0.00153
1 139.173 76.556 0.0039 0.00003 0.00496 0.154 0.00932 0.01041 24.889 0.430166 0.665833 -5.660217 0.254989 0.00208
1 152.845 75.836 0.00294 0.00002 0.00364 0.158 0.00972 0.00609 24.922 0.474791 0.654027 -6.105098 0.203653 0.00149
1 142.167 83.159 0.00369 0.00003 0.00471 0.126 0.00888 0.00839 25.175 0.565924 0.658245 -5.340115 0.210185 0.00203
1 144.188 82.764 0.00544 0.00004 0.00632 0.192 0.012 0.01859 22.333 0.56738 0.644692 -5.44004 0.239764 0.00292
1 168.778 75.603 0.00718 0.00004 0.00853 0.348 0.01893 0.02919 20.376 0.631099 0.605417 -2.93107 0.434326 0.00387
1 153.046 68.623 0.00742 0.00005 0.01092 0.542 0.03572 0.0316 17.28 0.665318 0.719467 -3.949079 0.35787 0.00432
1 156.405 142.822 0.00768 0.00005 0.01116 0.348 0.02374 0.03365 17.153 0.649554 0.68608 -4.554466 0.340176 0.00399
1 153.848 65.782 0.0084 0.00005 0.01285 0.328 0.02383 0.03871 17.536 0.660125 0.704087 -4.095442 0.262564 0.0045
1 153.88 78.128 0.0048 0.00003 0.00696 0.37 0.02591 0.01849 19.493 0.629017 0.698951 -5.18696 0.237622 0.00267
1 167.93 79.068 0.00442 0.00003 0.00661 0.377 0.0254 0.0128 22.468 0.61906 0.679834 -4.330956 0.262384 0.00247
1 173.917 86.18 0.00476 0.00003 0.00663 0.364 0.0247 0.0184 20.422 0.537264 0.686894 -5.248776 0.210279 0.00258
1 163.656 76.779 0.00742 0.00005 0.0114 0.164 0.00948 0.01778 23.831 0.397937 0.732479 -5.557447 0.22089 0.0039
1 104.4 77.968 0.00633 0.00006 0.00948 0.381 0.02245 0.02887 22.066 0.522746 0.737948 -5.571843 0.236853 0.00375
1 171.041 75.501 0.00455 0.00003 0.0075 0.186 0.01169 0.01095 25.908 0.418622 0.720916 -6.18359 0.226278 0.00234
1 146.845 81.737 0.00496 0.00003 0.00749 0.198 0.01144 0.01328 25.119 0.358773 0.726652 -6.27169 0.196102 0.00275
1 155.358 80.055 0.0031 0.00002 0.00476 0.161 0.01012 0.00677 25.97 0.470478 0.676258 -7.120925 0.279789 0.00176
1 162.568 77.63 0.00502 0.00003 0.00841 0.168 0.01057 0.0117 25.678 0.427785 0.723797 -6.635729 0.209866 0.00253
0 197.076 192.055 0.00289 0.00001 0.00498 0.097 0.0068 0.00339 26.775 0.422229 0.741367 -7.3483 0.177551 0.00168
0 199.228 192.091 0.00241 0.00001 0.00402 0.089 0.00641 0.00167 30.94 0.432439 0.742055 -7.682587 0.173319 0.00138
0 198.383 193.104 0.00212 0.00001 0.00339 0.111 0.00825 0.00119 30.775 0.465946 0.738703 -7.067931 0.175181 0.00135
0 202.266 197.079 0.0018 0.000009 0.00278 0.085 0.00606 0.00072 32.684 0.368535 0.742133 -7.695734 0.17854 0.00107
0 203.184 196.16 0.00178 0.000009 0.00283 0.085 0.0061 0.00065 33.047 0.340068 0.741899 -7.964984 0.163519 0.00106
0 201.464 195.708 0.00198 0.00001 0.00314 0.107 0.0076 0.00135 31.732 0.344252 0.742737 -7.777685 0.170183 0.00115
1 177.876 168.013 0.00411 0.00002 0.007 0.189 0.01347 0.00586 23.216 0.360148 0.778834 -6.149653 0.218037 0.00241
1 176.17 163.564 0.00369 0.00002 0.00616 0.168 0.0116 0.0034 24.951 0.341435 0.783626 -6.006414 0.196371 0.00218
1 180.198 175.456 0.00284 0.00002 0.00459 0.131 0.00885 0.00231 26.738 0.403884 0.766209 -6.452058 0.212294 0.00166
1 187.733 173.015 0.00316 0.00002 0.00504 0.151 0.01003 0.00265 26.31 0.396793 0.758324 -6.006647 0.266892 0.00182
1 186.163 177.584 0.00298 0.00002 0.00496 0.135 0.00941 0.00231 26.822 0.32648 0.765623 -6.647379 0.201095 0.00175
1 184.055 166.977 0.00258 0.00001 0.00403 0.132 0.00901 0.00257 26.453 0.306443 0.759203 -7.044105 0.063412 0.00147
0 237.226 225.227 0.00298 0.00001 0.00507 0.164 0.01024 0.0074 22.736 0.305062 0.654172 -7.31055 0.098648 0.00182
0 241.404 232.483 0.00281 0.00001 0.0047 0.154 0.01038 0.00675 23.145 0.457702 0.634267 -6.793547 0.158266 0.00173
0 243.439 232.435 0.0021 0.000009 0.00327 0.126 0.00898 0.00454 25.368 0.438296 0.635285 -7.057869 0.091608 0.00137
0 242.852 227.911 0.00225 0.000009 0.0035 0.134 0.00879 0.00476 25.032 0.431285 0.638928 -6.99582 0.102083 0.00139
0 245.51 231.848 0.00235 0.00001 0.0038 0.141 0.00977 0.00476 24.602 0.467489 0.631653 -7.156076 0.127642 0.00148
0 252.455 182.786 0.00185 0.000007 0.00276 0.103 0.0073 0.00432 26.805 0.610367 0.635204 -7.31951 0.200873 0.00113
0 122.188 115.765 0.00524 0.00004 0.00507 0.143 0.00776 0.00839 23.162 0.579597 0.733659 -6.439398 0.266392 0.00203
0 122.964 114.676 0.00428 0.00003 0.00373 0.154 0.00802 0.00462 24.971 0.538688 0.754073 -6.482096 0.264967 0.00155
0 124.445 117.495 0.00431 0.00003 0.00422 0.197 0.01024 0.00479 25.135 0.553134 0.775933 -6.650471 0.254498 0.00167
0 126.344 112.773 0.00448 0.00004 0.00393 0.185 0.00959 0.00474 25.03 0.507504 0.760361 -6.689151 0.291954 0.00169
0 128.001 122.08 0.00436 0.00003 0.00411 0.21 0.01072 0.00481 24.692 0.459766 0.766204 -7.072419 0.220434 0.00166
0 129.336 118.604 0.0049 0.00004 0.00495 0.228 0.01219 0.00484 25.429 0.420383 0.785714 -6.836811 0.269866 0.00183
1 108.807 102.874 0.00761 0.00007 0.01046 0.255 0.01609 0.01036 21.028 0.536009 0.819032 -4.649573 0.205558 0.00486
1 109.86 104.437 0.00874 0.00008 0.01193 0.307 0.01992 0.0118 20.767 0.558586 0.811843 -4.333543 0.221727 0.00539
1 110.417 103.37 0.00784 0.00007 0.01056 0.334 0.02302 0.00969 21.422 0.541781 0.821364 -4.438453 0.238298 0.00514
1 117.274 110.402 0.00752 0.00006 0.00898 0.221 0.01459 0.00681 22.817 0.530529 0.817756 -4.60826 0.290024 0.00469
1 116.879 108.153 0.00788 0.00007 0.01003 0.265 0.01625 0.00786 22.603 0.540049 0.813432 -4.476755 0.262633 0.00493
1 114.847 104.68 0.00867 0.00008 0.0112 0.35 0.01974 0.01143 21.66 0.547975 0.817396 -4.609161 0.221711 0.0052
0 209.144 109.379 0.00282 0.00001 0.00442 0.17 0.01258 0.00871 25.554 0.341788 0.678874 -7.040508 0.066994 0.00152
0 223.365 98.664 0.00264 0.00001 0.00461 0.165 0.01296 0.00301 26.138 0.447979 0.686264 -7.293801 0.086372 0.00151
0 222.236 205.495 0.00266 0.00001 0.00457 0.145 0.01108 0.0034 25.856 0.364867 0.694399 -6.966321 0.095882 0.00144
0 228.832 223.634 0.00296 0.00001 0.00526 0.145 0.01075 0.00351 25.964 0.25657 0.683296 -7.24562 0.018689 0.00155
0 229.401 221.156 0.00205 0.000009 0.00342 0.129 0.00957 0.003 26.415 0.27685 0.673636 -7.496264 0.056844 0.00113
0 228.969 113.201 0.00238 0.00001 0.00408 0.154 0.0116 0.0042 24.547 0.305429 0.681811 -7.314237 0.006274 0.0014
1 140.341 67.021 0.00817 0.00006 0.01289 0.313 0.0181 0.02183 19.56 0.460139 0.720908 -5.409423 0.22685 0.0044
1 136.969 66.004 0.00923 0.00007 0.0152 0.308 0.01759 0.02659 19.979 0.498133 0.729067 -5.324574 0.20566 0.00463
1 143.533 65.809 0.01101 0.00008 0.01941 0.478 0.02422 0.04882 20.338 0.513237 0.731444 -5.86975 0.151814 0.00467
1 148.09 67.343 0.00762 0.00005 0.014 0.497 0.02494 0.02431 21.718 0.487407 0.727313 -6.261141 0.120956 0.00354
1 142.729 65.476 0.00831 0.00006 0.01407 0.365 0.01906 0.02599 20.264 0.489345 0.730387 -5.720868 0.15883 0.00419
1 136.358 65.75 0.00971 0.00007 0.01601 0.483 0.02466 0.03361 18.57 0.543299 0.733232 -5.207985 0.224852 0.00478
1 120.08 111.208 0.00405 0.00003 0.0054 0.152 0.00925 0.00442 25.742 0.495954 0.762959 -5.79182 0.329066 0.0022
1 112.014 107.024 0.00533 0.00005 0.00805 0.226 0.01375 0.00623 24.178 0.509127 0.789532 -5.389129 0.306636 0.00329
1 110.793 107.316 0.00494 0.00004 0.0078 0.216 0.01325 0.00479 25.438 0.437031 0.815908 -5.31336 0.201861 0.00283
1 110.707 105.007 0.00516 0.00005 0.00831 0.206 0.01219 0.00472 25.197 0.463514 0.807217 -5.477592 0.315074 0.00289
1 112.876 106.981 0.005 0.00004 0.0081 0.35 0.02231 0.00905 23.37 0.489538 0.789977 -5.775966 0.341169 0.00289
1 110.568 106.821 0.00462 0.00004 0.00677 0.197 0.01199 0.0042 25.82 0.429484 0.81634 -5.391029 0.250572 0.0028
1 95.385 90.264 0.00608 0.00006 0.00994 0.263 0.01886 0.01062 21.875 0.644954 0.779612 -5.115212 0.249494 0.00332
1 100.77 85.545 0.01038 0.0001 0.01865 0.361 0.01783 0.0222 19.2 0.594387 0.790117 -4.913885 0.265699 0.00576
1 96.106 84.51 0.00694 0.00007 0.01168 0.364 0.02451 0.01823 19.055 0.544805 0.770466 -4.441519 0.155097 0.00415
1 95.605 87.549 0.00702 0.00007 0.01283 0.296 0.01841 0.01825 19.659 0.576084 0.778747 -5.132032 0.210458 0.00371
1 100.96 95.628 0.00606 0.00006 0.01053 0.216 0.01421 0.01237 20.536 0.55461 0.787896 -5.022288 0.146948 0.00348
1 98.804 87.804 0.00432 0.00004 0.00742 0.202 0.01343 0.00882 22.244 0.576644 0.772416 -6.025367 0.078202 0.00258
1 176.858 75.344 0.00747 0.00004 0.01254 0.435 0.03022 0.0547 13.893 0.556494 0.729586 -5.288912 0.343073 0.0042
1 180.978 155.495 0.00406 0.00002 0.00659 0.331 0.02493 0.02782 16.176 0.583574 0.727747 -5.657899 0.315903 0.00244
1 178.222 141.047 0.00321 0.00002 0.00488 0.327 0.02415 0.03151 15.924 0.598714 0.712199 -6.366916 0.335753 0.00194
1 176.281 125.61 0.0052 0.00003 0.00862 0.58 0.04159 0.04824 13.922 0.602874 0.740837 -5.515071 0.299549 0.00312
1 173.898 74.677 0.00448 0.00003 0.0071 0.65 0.04254 0.04214 14.739 0.599371 0.743937 -5.783272 0.299793 0.00254
1 179.711 144.878 0.00709 0.00004 0.01172 0.442 0.02768 0.07223 11.866 0.590951 0.745526 -4.379411 0.375531 0.00419
1 166.605 78.032 0.00742 0.00004 0.01161 0.634 0.04282 0.08725 11.744 0.65341 0.733165 -4.508984 0.389232 0.00453
1 151.955 147.226 0.00419 0.00003 0.00672 0.772 0.04962 0.01658 19.664 0.501037 0.71436 -6.411497 0.207156 0.00227
1 148.272 142.299 0.00459 0.00003 0.0075 0.383 0.02521 0.01914 18.78 0.454444 0.734504 -5.952058 0.08784 0.00256
1 152.125 76.596 0.00382 0.00003 0.00574 0.637 0.03794 0.01211 20.969 0.447456 0.69779 -6.152551 0.17352 0.00226
1 157.821 68.401 0.00358 0.00002 0.00587 0.307 0.02321 0.0085 22.219 0.50238 0.71217 -6.251425 0.188056 0.00196
1 157.447 149.605 0.00369 0.00002 0.00602 0.283 0.01909 0.01018 21.693 0.447285 0.705658 -6.247076 0.180528 0.00197
1 159.116 144.811 0.00342 0.00002 0.00535 0.307 0.02024 0.00852 22.663 0.366329 0.693429 -6.41744 0.194627 0.00184
1 125.036 116.187 0.0128 0.0001 0.02228 0.342 0.02174 0.08151 15.338 0.629574 0.714485 -4.020042 0.265315 0.00623
1 125.791 96.206 0.01378 0.00011 0.02478 0.422 0.0263 0.10323 15.433 0.57101 0.690892 -5.159169 0.202146 0.00655
1 126.512 99.77 0.01936 0.00015 0.03476 0.659 0.03963 0.16744 12.435 0.638545 0.674953 -3.760348 0.242861 0.0099
1 125.641 116.346 0.03316 0.00026 0.06433 0.891 0.04791 0.31482 8.867 0.671299 0.656846 -3.700544 0.260481 0.01522
1 128.451 75.632 0.01551 0.00012 0.02716 0.584 0.03672 0.11843 15.06 0.639808 0.643327 -4.20273 0.310163 0.00909
1 139.224 66.157 0.03011 0.00022 0.05563 0.93 0.05005 0.2593 10.489 0.596362 0.641418 -3.269487 0.270641 0.01628
1 150.258 75.349 0.00248 0.00002 0.00315 0.107 0.00659 0.00495 26.759 0.296888 0.722356 -6.878393 0.089267 0.00136
1 154.003 128.621 0.00183 0.00001 0.00229 0.094 0.00582 0.00243 28.409 0.263654 0.691483 -7.111576 0.14478 0.001
1 149.689 133.608 0.00257 0.00002 0.00349 0.126 0.00818 0.00578 27.421 0.365488 0.719974 -6.997403 0.210279 0.00134
1 155.078 144.148 0.00168 0.00001 0.00204 0.097 0.00632 0.00233 29.746 0.334171 0.67793 -6.981201 0.18455 0.00092
1 151.884 133.751 0.00258 0.00002 0.00346 0.137 0.00788 0.00659 26.833 0.393563 0.700246 -6.600023 0.249172 0.00122
1 151.989 132.857 0.00174 0.00001 0.00225 0.093 0.00576 0.00238 29.928 0.311369 0.676066 -6.739151 0.160686 0.00096
1 193.03 80.297 0.00766 0.00004 0.01351 0.275 0.01815 0.00947 21.934 0.497554 0.740539 -5.845099 0.278679 0.00389
1 200.714 89.686 0.00621 0.00003 0.01112 0.207 0.01439 0.00704 23.239 0.436084 0.727863 -5.25832 0.256454 0.00337
1 208.519 199.02 0.00609 0.00003 0.01105 0.155 0.01058 0.0083 22.407 0.338097 0.712466 -6.471427 0.184378 0.00339
1 204.664 189.621 0.00841 0.00004 0.01506 0.21 0.01483 0.01316 21.305 0.498877 0.722085 -4.876336 0.212054 0.00485
1 210.141 185.258 0.00534 0.00003 0.00964 0.149 0.01017 0.0062 23.671 0.441097 0.722254 -5.96304 0.250283 0.0028
1 206.327 92.02 0.00495 0.00002 0.00905 0.209 0.01284 0.01048 21.864 0.331508 0.715121 -6.729713 0.181701 0.00246
1 151.872 69.085 0.00856 0.00006 0.01211 0.235 0.00832 0.06051 23.693 0.407701 0.662668 -4.673241 0.261549 0.00385
1 158.219 71.948 0.00476 0.00003 0.00642 0.148 0.00747 0.01554 26.356 0.450798 0.653823 -6.051233 0.27328 0.00207
1 170.756 79.032 0.00555 0.00003 0.00731 0.175 0.00971 0.01802 25.69 0.486738 0.676023 -4.597834 0.372114 0.00261
1 178.285 82.063 0.00462 0.00003 0.00472 0.129 0.00744 0.00856 25.02 0.470422 0.655239 -4.913137 0.393056 0.00194
1 217.116 93.978 0.00404 0.00002 0.00381 0.124 0.00631 0.00681 24.581 0.462516 0.58271 -5.517173 0.389295 0.00128
1 128.94 88.251 0.00581 0.00005 0.00723 0.221 0.01117 0.0235 24.743 0.487756 0.68413 -6.186128 0.279933 0.00314
1 176.824 83.961 0.0046 0.00003 0.00628 0.117 0.0063 0.01161 27.166 0.400088 0.656182 -4.711007 0.281618 0.00221
1 138.19 83.34 0.00704 0.00005 0.01218 0.441 0.02567 0.01968 18.305 0.538016 0.74148 -5.418787 0.160267 0.00398
1 182.018 79.187 0.00842 0.00005 0.01517 0.231 0.0158 0.01813 18.784 0.589956 0.732903 -5.44514 0.142466 0.00449
1 156.239 79.82 0.00694 0.00004 0.01209 0.224 0.0142 0.0202 19.196 0.618663 0.728421 -5.944191 0.143359 0.00395
1 145.174 80.637 0.00733 0.00005 0.01242 0.233 0.01495 0.01874 18.857 0.637518 0.735546 -5.594275 0.12795 0.00422
1 138.145 81.114 0.00544 0.00004 0.00883 0.246 0.01805 0.01794 18.178 0.623209 0.738245 -5.540351 0.087165 0.00327
1 166.888 79.512 0.00638 0.00004 0.01104 0.257 0.01859 0.01796 18.33 0.585169 0.736964 -5.825257 0.115697 0.00351
1 119.031 109.216 0.0044 0.00004 0.00641 0.098 0.0057 0.01724 26.842 0.457541 0.699787 -6.890021 0.152941 0.00192
1 120.078 105.667 0.0027 0.00002 0.00349 0.09 0.00588 0.00487 26.369 0.491345 0.718839 -5.892061 0.195976 0.00135
1 120.289 100.209 0.00492 0.00004 0.00808 0.125 0.0082 0.0161 23.949 0.46716 0.724045 -6.135296 0.20363 0.00238
1 120.256 104.773 0.00407 0.00003 0.00671 0.138 0.00815 0.01015 26.017 0.468621 0.735136 -6.112667 0.217013 0.00205
1 119.056 86.795 0.00346 0.00003 0.00508 0.106 0.00701 0.00903 23.389 0.470972 0.721308 -5.436135 0.254909 0.0017
1 118.747 109.836 0.00331 0.00003 0.00504 0.099 0.00621 0.00504 25.619 0.482296 0.723096 -6.448134 0.178713 0.00171
1 106.516 93.105 0.00589 0.00006 0.00873 0.441 0.03112 0.03031 17.06 0.637814 0.744064 -5.301321 0.320385 0.00319
1 110.453 105.554 0.00494 0.00004 0.00731 0.379 0.02592 0.02529 17.707 0.653427 0.706687 -5.333619 0.322044 0.00315
1 113.4 107.816 0.00451 0.00004 0.00658 0.431 0.02973 0.02278 19.013 0.6479 0.708144 -4.378916 0.300067 0.00283
1 113.166 100.673 0.00502 0.00004 0.00772 0.476 0.03347 0.0369 16.747 0.625362 0.708617 -4.654894 0.304107 0.00312
1 112.239 104.095 0.00472 0.00004 0.00715 0.517 0.0353 0.02629 17.366 0.640945 0.701404 -5.634576 0.306014 0.0029
1 116.15 109.815 0.00381 0.00003 0.00542 0.267 0.01812 0.01827 18.801 0.624811 0.696049 -5.866357 0.23307 0.00232
1 170.368 79.543 0.00571 0.00003 0.00696 0.281 0.01964 0.02485 18.54 0.677131 0.685057 -4.796845 0.397749 0.00269
1 208.083 91.802 0.00757 0.00004 0.01285 0.571 0.04003 0.04238 15.648 0.606344 0.665945 -5.410336 0.288917 0.00428
1 198.458 148.691 0.00376 0.00002 0.00546 0.297 0.02076 0.01728 18.702 0.606273 0.661735 -5.585259 0.310746 0.00215
1 202.805 86.232 0.0037 0.00002 0.00568 0.18 0.01177 0.0201 18.687 0.536102 0.632631 -5.898673 0.213353 0.00211
1 202.544 164.168 0.00254 0.00001 0.00301 0.228 0.01558 0.01049 20.68 0.49748 0.630409 -6.132663 0.220617 0.00133
1 223.361 87.638 0.00352 0.00002 0.00506 0.225 0.01478 0.01493 20.366 0.566849 0.574282 -5.456811 0.345238 0.00188
1 169.774 151.451 0.01568 0.00009 0.02589 0.821 0.05426 0.0753 12.359 0.56161 0.793509 -3.297668 0.414758 0.00946
1 183.52 161.34 0.01466 0.00008 0.02546 0.618 0.04101 0.06057 14.367 0.478024 0.768974 -4.276605 0.355736 0.00819
1 188.62 165.982 0.01719 0.00009 0.02987 0.722 0.0458 0.08069 12.298 0.55287 0.764036 -3.377325 0.335357 0.01027
1 202.632 177.258 0.01627 0.00008 0.02756 0.833 0.04265 0.07889 14.989 0.427627 0.775708 -4.892495 0.262281 0.00963
1 186.695 149.442 0.01872 0.0001 0.03225 0.784 0.03714 0.10952 12.529 0.507826 0.762726 -4.484303 0.340256 0.01154
1 192.818 168.793 0.03107 0.00016 0.05401 1.302 0.0794 0.21713 8.441 0.625866 0.76832 -2.434031 0.450493 0.01958
1 198.116 174.478 0.02714 0.00014 0.04705 1.018 0.05556 0.16265 9.449 0.584164 0.754449 -2.839756 0.356224 0.01699
1 121.345 98.25 0.00684 0.00006 0.01164 0.241 0.01399 0.04179 21.52 0.566867 0.670475 -4.865194 0.246404 0.00332
1 119.1 88.833 0.00692 0.00006 0.01179 0.236 0.01405 0.04611 21.824 0.65168 0.659333 -4.239028 0.175691 0.003
1 117.87 95.654 0.00647 0.00005 0.01067 0.276 0.01804 0.02631 22.431 0.6283 0.652025 -3.583722 0.207914 0.003
1 122.336 94.794 0.00727 0.00006 0.01246 0.223 0.01289 0.03191 22.953 0.611679 0.623731 -5.4351 0.230532 0.00339
1 117.963 100.757 0.01813 0.00015 0.03351 0.438 0.02161 0.10748 19.075 0.630547 0.646786 -3.444478 0.303214 0.00718
1 126.144 97.543 0.00975 0.00008 0.01778 0.266 0.01581 0.03828 21.534 0.635015 0.627337 -5.070096 0.280091 0.00454
1 127.93 112.173 0.00605 0.00005 0.00962 0.339 0.0165 0.02663 19.651 0.654945 0.675865 -5.498456 0.234196 0.00318
1 114.238 77.022 0.00581 0.00005 0.00896 0.406 0.01994 0.02073 20.437 0.653139 0.694571 -5.185987 0.259229 0.00316
1 115.322 107.802 0.00619 0.00005 0.01057 0.325 0.01722 0.0281 19.388 0.577802 0.684373 -5.283009 0.226528 0.00329
1 114.554 91.121 0.00651 0.00006 0.01097 0.369 0.0194 0.02707 18.954 0.685151 0.719576 -5.529833 0.24275 0.0034
1 112.15 97.527 0.00519 0.00005 0.00873 0.155 0.01033 0.01435 21.219 0.557045 0.673086 -5.617124 0.184896 0.00284
1 102.273 85.902 0.00907 0.00009 0.0148 0.272 0.01553 0.03882 18.447 0.671378 0.674562 -2.929379 0.396746 0.00461
0 236.2 102.137 0.00277 0.00001 0.00462 0.217 0.01426 0.0062 24.078 0.469928 0.628232 -6.816086 0.17227 0.00153
0 237.323 229.256 0.00303 0.00001 0.00519 0.116 0.00747 0.00533 24.679 0.384868 0.62671 -7.018057 0.176316 0.00159
0 260.105 237.303 0.00339 0.00001 0.00616 0.197 0.0123 0.0091 21.083 0.440988 0.628058 -7.517934 0.160414 0.00186
0 197.569 90.794 0.00803 0.00004 0.0147 0.189 0.01272 0.01337 19.269 0.372222 0.725216 -5.736781 0.164529 0.00448
0 240.301 219.783 0.00517 0.00002 0.00949 0.212 0.01191 0.00965 21.02 0.371837 0.646167 -7.169701 0.073298 0.00283
0 244.99 239.17 0.00451 0.00002 0.00837 0.181 0.01121 0.01049 21.528 0.522812 0.646818 -7.3045 0.171088 0.00237
0 112.547 105.715 0.00355 0.00003 0.00499 0.129 0.00786 0.00435 26.436 0.413295 0.7567 -6.323531 0.218885 0.0019
0 110.739 100.139 0.00356 0.00003 0.0051 0.133 0.0095 0.0043 26.55 0.36909 0.776158 -6.085567 0.192375 0.002
0 113.715 96.913 0.00349 0.00003 0.00514 0.133 0.00905 0.00478 26.547 0.380253 0.7667 -5.943501 0.19215 0.00203
0 117.004 99.923 0.00353 0.00003 0.00528 0.145 0.01062 0.0059 25.445 0.387482 0.756482 -6.012559 0.229298 0.00218
0 115.38 108.634 0.00332 0.00003 0.0048 0.137 0.00933 0.00401 26.005 0.405991 0.761255 -5.966779 0.197938 0.00199
0 116.388 108.97 0.00346 0.00003 0.00507 0.155 0.01021 0.00415 26.143 0.361232 0.763242 -6.016891 0.109256 0.00213
1 151.737 129.859 0.00314 0.00002 0.00406 0.132 0.00886 0.0057 24.151 0.39661 0.745957 -6.486822 0.197919 0.00162
1 148.79 138.99 0.00309 0.00002 0.00456 0.142 0.00956 0.00488 24.412 0.402591 0.762508 -6.311987 0.182459 0.00186
1 148.143 135.041 0.00392 0.00003 0.00612 0.131 0.00876 0.0054 23.683 0.398499 0.778349 -5.711205 0.240875 0.00231
1 150.44 144.736 0.00396 0.00003 0.00619 0.237 0.01574 0.00611 23.133 0.352396 0.75932 -6.261446 0.183218 0.00233
1 148.462 141.998 0.00397 0.00003 0.00605 0.163 0.01103 0.00639 22.866 0.408598 0.768845 -5.704053 0.216204 0.00235
1 149.818 144.786 0.00336 0.00002 0.00521 0.198 0.01341 0.00595 23.008 0.329577 0.75718 -6.27717 0.109397 0.00198
0 117.226 106.656 0.00417 0.00004 0.00558 0.171 0.01223 0.00955 23.079 0.603515 0.669565 -5.61907 0.191576 0.0027
0 116.848 99.503 0.00531 0.00005 0.0078 0.163 0.01144 0.01179 22.085 0.663842 0.656516 -5.198864 0.206768 0.00346
0 116.286 96.983 0.00314 0.00003 0.00403 0.136 0.0099 0.00737 24.199 0.598515 0.654331 -5.592584 0.133917 0.00192
0 116.556 86.228 0.00496 0.00004 0.00762 0.154 0.00972 0.01397 23.958 0.566424 0.667654 -6.431119 0.15331 0.00263
0 116.342 94.246 0.00267 0.00002 0.00345 0.117 0.00789 0.0068 25.023 0.528485 0.663884 -6.359018 0.116636 0.00148
0 114.563 86.647 0.00327 0.00003 0.00439 0.106 0.00721 0.00703 24.775 0.555303 0.659132 -6.710219 0.149694 0.00184
0 201.774 78.228 0.00694 0.00003 0.01235 0.255 0.01582 0.04441 19.368 0.508479 0.683761 -6.934474 0.15989 0.00396
0 174.188 94.261 0.00459 0.00003 0.0079 0.405 0.02498 0.02764 19.517 0.448439 0.657899 -6.538586 0.121952 0.00259
0 209.516 89.488 0.00564 0.00003 0.00994 0.263 0.01657 0.0181 19.147 0.431674 0.683244 -6.195325 0.129303 0.00292
0 174.688 74.287 0.0136 0.00008 0.01873 0.256 0.01365 0.10715 17.883 0.407567 0.655683 -6.787197 0.158453 0.00564
0 198.764 74.904 0.0074 0.00004 0.01109 0.241 0.01321 0.07223 19.02 0.451221 0.643956 -6.744577 0.207454 0.0039
0 214.289 77.973 0.00567 0.00003 0.00885 0.19 0.01161 0.04398 21.209 0.462803 0.664357 -5.724056 0.190667 0.00317

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 8 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286263&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286263&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286263&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 time8 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
status[t] = + 5.37854 -0.00499651`MDVP:Fo(Hz)`[t] -0.00121025`MDVP:Flo(Hz)`[t] -168.799`MDVP:Jitter(%)`[t] -8656.92`MDVP:Jitter(Abs)`[t] + 129.401`Jitter:DDP`[t] + 1.15972`MDVP:Shimmer(dB)`[t] -17.5508`Shimmer:APQ5`[t] -3.19852NHR[t] -0.0401612HNR[t] -1.38051RPDE[t] -0.798879DFA[t] + 0.220223spread1[t] + 1.3259spread2[t] -48.9849`MDVP:PPQ`[t] -0.00244164t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
status[t] =  +  5.37854 -0.00499651`MDVP:Fo(Hz)`[t] -0.00121025`MDVP:Flo(Hz)`[t] -168.799`MDVP:Jitter(%)`[t] -8656.92`MDVP:Jitter(Abs)`[t] +  129.401`Jitter:DDP`[t] +  1.15972`MDVP:Shimmer(dB)`[t] -17.5508`Shimmer:APQ5`[t] -3.19852NHR[t] -0.0401612HNR[t] -1.38051RPDE[t] -0.798879DFA[t] +  0.220223spread1[t] +  1.3259spread2[t] -48.9849`MDVP:PPQ`[t] -0.00244164t  + e[t] \tabularnewline
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286263&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]status[t] =  +  5.37854 -0.00499651`MDVP:Fo(Hz)`[t] -0.00121025`MDVP:Flo(Hz)`[t] -168.799`MDVP:Jitter(%)`[t] -8656.92`MDVP:Jitter(Abs)`[t] +  129.401`Jitter:DDP`[t] +  1.15972`MDVP:Shimmer(dB)`[t] -17.5508`Shimmer:APQ5`[t] -3.19852NHR[t] -0.0401612HNR[t] -1.38051RPDE[t] -0.798879DFA[t] +  0.220223spread1[t] +  1.3259spread2[t] -48.9849`MDVP:PPQ`[t] -0.00244164t  + e[t][/C][/ROW]
[ROW][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286263&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286263&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] = + 5.37854 -0.00499651`MDVP:Fo(Hz)`[t] -0.00121025`MDVP:Flo(Hz)`[t] -168.799`MDVP:Jitter(%)`[t] -8656.92`MDVP:Jitter(Abs)`[t] + 129.401`Jitter:DDP`[t] + 1.15972`MDVP:Shimmer(dB)`[t] -17.5508`Shimmer:APQ5`[t] -3.19852NHR[t] -0.0401612HNR[t] -1.38051RPDE[t] -0.798879DFA[t] + 0.220223spread1[t] + 1.3259spread2[t] -48.9849`MDVP:PPQ`[t] -0.00244164t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)+5.378 0.8699+6.1830e+00 4.142e-09 2.071e-09
`MDVP:Fo(Hz)`-0.004997 0.001336-3.7400e+00 0.0002472 0.0001236
`MDVP:Flo(Hz)`-0.00121 0.0007093-1.7060e+00 0.08968 0.04484
`MDVP:Jitter(%)`-168.8 58.11-2.9050e+00 0.004138 0.002069
`MDVP:Jitter(Abs)`-8657 3391-2.5530e+00 0.01151 0.005753
`Jitter:DDP`+129.4 22.71+5.6980e+00 4.91e-08 2.455e-08
`MDVP:Shimmer(dB)`+1.16 0.7038+1.6480e+00 0.1012 0.05059
`Shimmer:APQ5`-17.55 10.84-1.6190e+00 0.1072 0.05358
NHR-3.199 1.797-1.7800e+00 0.07684 0.03842
HNR-0.04016 0.0124-3.2380e+00 0.001436 0.0007181
RPDE-1.381 0.3563-3.8750e+00 0.0001497 7.484e-05
DFA-0.7989 0.6819-1.1710e+00 0.243 0.1215
spread1+0.2202 0.04602+4.7850e+00 3.565e-06 1.782e-06
spread2+1.326 0.3963+3.3460e+00 0.0009997 0.0004998
`MDVP:PPQ`-48.98 53.37-9.1790e-01 0.3599 0.18
t-0.002442 0.0004857-5.0270e+00 1.203e-06 6.015e-07

\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) & +5.378 &  0.8699 & +6.1830e+00 &  4.142e-09 &  2.071e-09 \tabularnewline
`MDVP:Fo(Hz)` & -0.004997 &  0.001336 & -3.7400e+00 &  0.0002472 &  0.0001236 \tabularnewline
`MDVP:Flo(Hz)` & -0.00121 &  0.0007093 & -1.7060e+00 &  0.08968 &  0.04484 \tabularnewline
`MDVP:Jitter(%)` & -168.8 &  58.11 & -2.9050e+00 &  0.004138 &  0.002069 \tabularnewline
`MDVP:Jitter(Abs)` & -8657 &  3391 & -2.5530e+00 &  0.01151 &  0.005753 \tabularnewline
`Jitter:DDP` & +129.4 &  22.71 & +5.6980e+00 &  4.91e-08 &  2.455e-08 \tabularnewline
`MDVP:Shimmer(dB)` & +1.16 &  0.7038 & +1.6480e+00 &  0.1012 &  0.05059 \tabularnewline
`Shimmer:APQ5` & -17.55 &  10.84 & -1.6190e+00 &  0.1072 &  0.05358 \tabularnewline
NHR & -3.199 &  1.797 & -1.7800e+00 &  0.07684 &  0.03842 \tabularnewline
HNR & -0.04016 &  0.0124 & -3.2380e+00 &  0.001436 &  0.0007181 \tabularnewline
RPDE & -1.381 &  0.3563 & -3.8750e+00 &  0.0001497 &  7.484e-05 \tabularnewline
DFA & -0.7989 &  0.6819 & -1.1710e+00 &  0.243 &  0.1215 \tabularnewline
spread1 & +0.2202 &  0.04602 & +4.7850e+00 &  3.565e-06 &  1.782e-06 \tabularnewline
spread2 & +1.326 &  0.3963 & +3.3460e+00 &  0.0009997 &  0.0004998 \tabularnewline
`MDVP:PPQ` & -48.98 &  53.37 & -9.1790e-01 &  0.3599 &  0.18 \tabularnewline
t & -0.002442 &  0.0004857 & -5.0270e+00 &  1.203e-06 &  6.015e-07 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286263&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]+5.378[/C][C] 0.8699[/C][C]+6.1830e+00[/C][C] 4.142e-09[/C][C] 2.071e-09[/C][/ROW]
[ROW][C]`MDVP:Fo(Hz)`[/C][C]-0.004997[/C][C] 0.001336[/C][C]-3.7400e+00[/C][C] 0.0002472[/C][C] 0.0001236[/C][/ROW]
[ROW][C]`MDVP:Flo(Hz)`[/C][C]-0.00121[/C][C] 0.0007093[/C][C]-1.7060e+00[/C][C] 0.08968[/C][C] 0.04484[/C][/ROW]
[ROW][C]`MDVP:Jitter(%)`[/C][C]-168.8[/C][C] 58.11[/C][C]-2.9050e+00[/C][C] 0.004138[/C][C] 0.002069[/C][/ROW]
[ROW][C]`MDVP:Jitter(Abs)`[/C][C]-8657[/C][C] 3391[/C][C]-2.5530e+00[/C][C] 0.01151[/C][C] 0.005753[/C][/ROW]
[ROW][C]`Jitter:DDP`[/C][C]+129.4[/C][C] 22.71[/C][C]+5.6980e+00[/C][C] 4.91e-08[/C][C] 2.455e-08[/C][/ROW]
[ROW][C]`MDVP:Shimmer(dB)`[/C][C]+1.16[/C][C] 0.7038[/C][C]+1.6480e+00[/C][C] 0.1012[/C][C] 0.05059[/C][/ROW]
[ROW][C]`Shimmer:APQ5`[/C][C]-17.55[/C][C] 10.84[/C][C]-1.6190e+00[/C][C] 0.1072[/C][C] 0.05358[/C][/ROW]
[ROW][C]NHR[/C][C]-3.199[/C][C] 1.797[/C][C]-1.7800e+00[/C][C] 0.07684[/C][C] 0.03842[/C][/ROW]
[ROW][C]HNR[/C][C]-0.04016[/C][C] 0.0124[/C][C]-3.2380e+00[/C][C] 0.001436[/C][C] 0.0007181[/C][/ROW]
[ROW][C]RPDE[/C][C]-1.381[/C][C] 0.3563[/C][C]-3.8750e+00[/C][C] 0.0001497[/C][C] 7.484e-05[/C][/ROW]
[ROW][C]DFA[/C][C]-0.7989[/C][C] 0.6819[/C][C]-1.1710e+00[/C][C] 0.243[/C][C] 0.1215[/C][/ROW]
[ROW][C]spread1[/C][C]+0.2202[/C][C] 0.04602[/C][C]+4.7850e+00[/C][C] 3.565e-06[/C][C] 1.782e-06[/C][/ROW]
[ROW][C]spread2[/C][C]+1.326[/C][C] 0.3963[/C][C]+3.3460e+00[/C][C] 0.0009997[/C][C] 0.0004998[/C][/ROW]
[ROW][C]`MDVP:PPQ`[/C][C]-48.98[/C][C] 53.37[/C][C]-9.1790e-01[/C][C] 0.3599[/C][C] 0.18[/C][/ROW]
[ROW][C]t[/C][C]-0.002442[/C][C] 0.0004857[/C][C]-5.0270e+00[/C][C] 1.203e-06[/C][C] 6.015e-07[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286263&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286263&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)+5.378 0.8699+6.1830e+00 4.142e-09 2.071e-09
`MDVP:Fo(Hz)`-0.004997 0.001336-3.7400e+00 0.0002472 0.0001236
`MDVP:Flo(Hz)`-0.00121 0.0007093-1.7060e+00 0.08968 0.04484
`MDVP:Jitter(%)`-168.8 58.11-2.9050e+00 0.004138 0.002069
`MDVP:Jitter(Abs)`-8657 3391-2.5530e+00 0.01151 0.005753
`Jitter:DDP`+129.4 22.71+5.6980e+00 4.91e-08 2.455e-08
`MDVP:Shimmer(dB)`+1.16 0.7038+1.6480e+00 0.1012 0.05059
`Shimmer:APQ5`-17.55 10.84-1.6190e+00 0.1072 0.05358
NHR-3.199 1.797-1.7800e+00 0.07684 0.03842
HNR-0.04016 0.0124-3.2380e+00 0.001436 0.0007181
RPDE-1.381 0.3563-3.8750e+00 0.0001497 7.484e-05
DFA-0.7989 0.6819-1.1710e+00 0.243 0.1215
spread1+0.2202 0.04602+4.7850e+00 3.565e-06 1.782e-06
spread2+1.326 0.3963+3.3460e+00 0.0009997 0.0004998
`MDVP:PPQ`-48.98 53.37-9.1790e-01 0.3599 0.18
t-0.002442 0.0004857-5.0270e+00 1.203e-06 6.015e-07






Multiple Linear Regression - Regression Statistics
Multiple R 0.741
R-squared 0.5491
Adjusted R-squared 0.5113
F-TEST (value) 14.53
F-TEST (DF numerator)15
F-TEST (DF denominator)179
p-value 0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 0.3019
Sum Squared Residuals 16.31

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R &  0.741 \tabularnewline
R-squared &  0.5491 \tabularnewline
Adjusted R-squared &  0.5113 \tabularnewline
F-TEST (value) &  14.53 \tabularnewline
F-TEST (DF numerator) & 15 \tabularnewline
F-TEST (DF denominator) & 179 \tabularnewline
p-value &  0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation &  0.3019 \tabularnewline
Sum Squared Residuals &  16.31 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286263&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C] 0.741[/C][/ROW]
[ROW][C]R-squared[/C][C] 0.5491[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C] 0.5113[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C] 14.53[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]15[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]179[/C][/ROW]
[ROW][C]p-value[/C][C] 0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C] 0.3019[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C] 16.31[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286263&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286263&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 R 0.741
R-squared 0.5491
Adjusted R-squared 0.5113
F-TEST (value) 14.53
F-TEST (DF numerator)15
F-TEST (DF denominator)179
p-value 0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation 0.3019
Sum Squared Residuals 16.31






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1 1 1.019-0.01883
2 1 1.126-0.1256
3 1 1.024-0.02418
4 1 1.1-0.1002
5 1 0.8687 0.1313
6 1 0.9677 0.03226
7 1 0.9504 0.04955
8 1 0.7098 0.2902
9 1 1.137-0.1368
10 1 1.246-0.2455
11 1 1.268-0.2685
12 1 1.338-0.3377
13 1 0.7818 0.2182
14 1 1.126-0.1262
15 1 0.9549 0.04507
16 1 0.9039 0.09612
17 1 0.8039 0.1961
18 1 1.491-0.4909
19 1 1.319-0.3187
20 1 1.088-0.08846
21 1 1.177-0.1771
22 1 1.04-0.03969
23 1 1.161-0.1607
24 1 0.9571 0.04291
25 1 0.95 0.05
26 1 0.9993 0.0007183
27 1 0.9142 0.08579
28 1 0.9957 0.004305
29 1 0.8254 0.1746
30 1 0.8451 0.1549
31 0 0.4224-0.4224
32 0 0.1226-0.1226
33 0 0.1877-0.1877
34 0 0.08955-0.08955
35 0 0.03919-0.03919
36 0 0.1326-0.1326
37 1 0.964 0.03598
38 1 0.9204 0.07957
39 1 0.637 0.363
40 1 0.8014 0.1986
41 1 0.6605 0.3395
42 1 0.5093 0.4907
43 0 0.4438-0.4438
44 0 0.3666-0.3666
45 0 0.1044-0.1044
46 0 0.1736-0.1736
47 0 0.1246-0.1246
48 0-0.08702 0.08702
49 0 0.4556-0.4556
50 0 0.5258-0.5258
51 0 0.4804-0.4804
52 0 0.4389-0.4389
53 0 0.453-0.453
54 0 0.4923-0.4923
55 1 0.791 0.209
56 1 0.733 0.267
57 1 0.7743 0.2257
58 1 0.7069 0.2931
59 1 0.6961 0.3039
60 1 0.5925 0.4075
61 0 0.4335-0.4335
62 0 0.2282-0.2282
63 0 0.3098-0.3098
64 0 0.2813-0.2813
65 0 0.1846-0.1846
66 0 0.3144-0.3144
67 1 1.075-0.07486
68 1 1.015-0.01537
69 1 0.9172 0.08278
70 1 1.022-0.02161
71 1 0.9896 0.01041
72 1 1.124-0.1239
73 1 0.946 0.05402
74 1 0.9726 0.02738
75 1 1.026-0.02591
76 1 1.067-0.06728
77 1 1.134-0.1337
78 1 0.9867 0.01331
79 1 0.9304 0.06964
80 1 1.172-0.1715
81 1 1.157-0.1572
82 1 1.186-0.1859
83 1 1.036-0.03601
84 1 0.7724 0.2276
85 1 1.186-0.1861
86 1 0.9444 0.05558
87 1 0.789 0.211
88 1 0.9438 0.0562
89 1 0.963 0.03701
90 1 1.295-0.2951
91 1 1.18-0.1795
92 1 0.7899 0.2101
93 1 0.8268 0.1732
94 1 0.9157 0.08427
95 1 0.8007 0.1993
96 1 0.8347 0.1653
97 1 0.8716 0.1284
98 1 1.09-0.09037
99 1 0.8687 0.1313
100 1 0.935 0.06504
101 1 1.002-0.002316
102 1 0.9462 0.05381
103 1 1.018-0.018
104 1 0.5665 0.4335
105 1 0.6165 0.3835
106 1 0.53 0.47
107 1 0.5206 0.4794
108 1 0.6694 0.3306
109 1 0.6122 0.3878
110 1 0.8597 0.1403
111 1 0.9922 0.007768
112 1 0.6495 0.3505
113 1 0.8231 0.1769
114 1 0.6317 0.3683
115 1 0.8327 0.1673
116 1 0.8738 0.1262
117 1 0.6988 0.3012
118 1 0.9751 0.0249
119 1 0.8271 0.1729
120 1 0.6834 0.3166
121 1 0.4806 0.5194
122 1 0.9201 0.07991
123 1 0.9937 0.006284
124 1 0.7274 0.2726
125 1 0.6694 0.3306
126 1 0.6388 0.3612
127 1 0.6243 0.3757
128 1 0.6215 0.3785
129 1 0.3583 0.6417
130 1 0.7261 0.2738
131 1 0.7718 0.2282
132 1 0.7968 0.2032
133 1 1.03-0.03031
134 1 0.6094 0.3906
135 1 0.8294 0.1706
136 1 0.9567 0.04329
137 1 1.067-0.06719
138 1 1.129-0.1295
139 1 0.9107 0.08926
140 1 0.785 0.215
141 1 0.7781 0.2219
142 1 0.7283 0.2717
143 1 0.6413 0.3587
144 1 0.669 0.331
145 1 0.5013 0.4987
146 1 0.7459 0.2541
147 1 1.126-0.126
148 1 1.113-0.113
149 1 1.162-0.1615
150 1 0.8644 0.1356
151 1 1.036-0.03556
152 1 0.9062 0.09378
153 1 1.01-0.01032
154 1 0.92 0.07998
155 1 0.8648 0.1352
156 1 1.118-0.1184
157 1 0.7434 0.2566
158 1 1.182-0.1822
159 1 0.9027 0.09726
160 1 0.7326 0.2674
161 1 0.8914 0.1086
162 1 1.004-0.003894
163 1 0.7556 0.2444
164 1 0.7832 0.2168
165 1 1.333-0.3329
166 0 0.2295-0.2295
167 0 0.1547-0.1547
168 0 0.01204-0.01204
169 0 0.8907-0.8907
170 0 0.1909-0.1909
171 0-0.02519 0.02519
172 0 0.6206-0.6206
173 0 0.6758-0.6758
174 0 0.7075-0.7075
175 0 0.7482-0.7482
176 0 0.6621-0.6621
177 0 0.5897-0.5897
178 1 0.4713 0.5287
179 1 0.5219 0.4781
180 1 0.7123 0.2877
181 1 0.5894 0.4106
182 1 0.6673 0.3327
183 1 0.5988 0.4012
184 0 0.4288-0.4288
185 0 0.4852-0.4852
186 0 0.4492-0.4492
187 0 0.3817-0.3817
188 0 0.4391-0.4391
189 0 0.3125-0.3125
190 0 0.3196-0.3196
191 0 0.5248-0.5248
192 0 0.5387-0.5387
193 0-0.2709 0.2709
194 0 0.1749-0.1749
195 0 0.3572-0.3572

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 &  1 &  1.019 & -0.01883 \tabularnewline
2 &  1 &  1.126 & -0.1256 \tabularnewline
3 &  1 &  1.024 & -0.02418 \tabularnewline
4 &  1 &  1.1 & -0.1002 \tabularnewline
5 &  1 &  0.8687 &  0.1313 \tabularnewline
6 &  1 &  0.9677 &  0.03226 \tabularnewline
7 &  1 &  0.9504 &  0.04955 \tabularnewline
8 &  1 &  0.7098 &  0.2902 \tabularnewline
9 &  1 &  1.137 & -0.1368 \tabularnewline
10 &  1 &  1.246 & -0.2455 \tabularnewline
11 &  1 &  1.268 & -0.2685 \tabularnewline
12 &  1 &  1.338 & -0.3377 \tabularnewline
13 &  1 &  0.7818 &  0.2182 \tabularnewline
14 &  1 &  1.126 & -0.1262 \tabularnewline
15 &  1 &  0.9549 &  0.04507 \tabularnewline
16 &  1 &  0.9039 &  0.09612 \tabularnewline
17 &  1 &  0.8039 &  0.1961 \tabularnewline
18 &  1 &  1.491 & -0.4909 \tabularnewline
19 &  1 &  1.319 & -0.3187 \tabularnewline
20 &  1 &  1.088 & -0.08846 \tabularnewline
21 &  1 &  1.177 & -0.1771 \tabularnewline
22 &  1 &  1.04 & -0.03969 \tabularnewline
23 &  1 &  1.161 & -0.1607 \tabularnewline
24 &  1 &  0.9571 &  0.04291 \tabularnewline
25 &  1 &  0.95 &  0.05 \tabularnewline
26 &  1 &  0.9993 &  0.0007183 \tabularnewline
27 &  1 &  0.9142 &  0.08579 \tabularnewline
28 &  1 &  0.9957 &  0.004305 \tabularnewline
29 &  1 &  0.8254 &  0.1746 \tabularnewline
30 &  1 &  0.8451 &  0.1549 \tabularnewline
31 &  0 &  0.4224 & -0.4224 \tabularnewline
32 &  0 &  0.1226 & -0.1226 \tabularnewline
33 &  0 &  0.1877 & -0.1877 \tabularnewline
34 &  0 &  0.08955 & -0.08955 \tabularnewline
35 &  0 &  0.03919 & -0.03919 \tabularnewline
36 &  0 &  0.1326 & -0.1326 \tabularnewline
37 &  1 &  0.964 &  0.03598 \tabularnewline
38 &  1 &  0.9204 &  0.07957 \tabularnewline
39 &  1 &  0.637 &  0.363 \tabularnewline
40 &  1 &  0.8014 &  0.1986 \tabularnewline
41 &  1 &  0.6605 &  0.3395 \tabularnewline
42 &  1 &  0.5093 &  0.4907 \tabularnewline
43 &  0 &  0.4438 & -0.4438 \tabularnewline
44 &  0 &  0.3666 & -0.3666 \tabularnewline
45 &  0 &  0.1044 & -0.1044 \tabularnewline
46 &  0 &  0.1736 & -0.1736 \tabularnewline
47 &  0 &  0.1246 & -0.1246 \tabularnewline
48 &  0 & -0.08702 &  0.08702 \tabularnewline
49 &  0 &  0.4556 & -0.4556 \tabularnewline
50 &  0 &  0.5258 & -0.5258 \tabularnewline
51 &  0 &  0.4804 & -0.4804 \tabularnewline
52 &  0 &  0.4389 & -0.4389 \tabularnewline
53 &  0 &  0.453 & -0.453 \tabularnewline
54 &  0 &  0.4923 & -0.4923 \tabularnewline
55 &  1 &  0.791 &  0.209 \tabularnewline
56 &  1 &  0.733 &  0.267 \tabularnewline
57 &  1 &  0.7743 &  0.2257 \tabularnewline
58 &  1 &  0.7069 &  0.2931 \tabularnewline
59 &  1 &  0.6961 &  0.3039 \tabularnewline
60 &  1 &  0.5925 &  0.4075 \tabularnewline
61 &  0 &  0.4335 & -0.4335 \tabularnewline
62 &  0 &  0.2282 & -0.2282 \tabularnewline
63 &  0 &  0.3098 & -0.3098 \tabularnewline
64 &  0 &  0.2813 & -0.2813 \tabularnewline
65 &  0 &  0.1846 & -0.1846 \tabularnewline
66 &  0 &  0.3144 & -0.3144 \tabularnewline
67 &  1 &  1.075 & -0.07486 \tabularnewline
68 &  1 &  1.015 & -0.01537 \tabularnewline
69 &  1 &  0.9172 &  0.08278 \tabularnewline
70 &  1 &  1.022 & -0.02161 \tabularnewline
71 &  1 &  0.9896 &  0.01041 \tabularnewline
72 &  1 &  1.124 & -0.1239 \tabularnewline
73 &  1 &  0.946 &  0.05402 \tabularnewline
74 &  1 &  0.9726 &  0.02738 \tabularnewline
75 &  1 &  1.026 & -0.02591 \tabularnewline
76 &  1 &  1.067 & -0.06728 \tabularnewline
77 &  1 &  1.134 & -0.1337 \tabularnewline
78 &  1 &  0.9867 &  0.01331 \tabularnewline
79 &  1 &  0.9304 &  0.06964 \tabularnewline
80 &  1 &  1.172 & -0.1715 \tabularnewline
81 &  1 &  1.157 & -0.1572 \tabularnewline
82 &  1 &  1.186 & -0.1859 \tabularnewline
83 &  1 &  1.036 & -0.03601 \tabularnewline
84 &  1 &  0.7724 &  0.2276 \tabularnewline
85 &  1 &  1.186 & -0.1861 \tabularnewline
86 &  1 &  0.9444 &  0.05558 \tabularnewline
87 &  1 &  0.789 &  0.211 \tabularnewline
88 &  1 &  0.9438 &  0.0562 \tabularnewline
89 &  1 &  0.963 &  0.03701 \tabularnewline
90 &  1 &  1.295 & -0.2951 \tabularnewline
91 &  1 &  1.18 & -0.1795 \tabularnewline
92 &  1 &  0.7899 &  0.2101 \tabularnewline
93 &  1 &  0.8268 &  0.1732 \tabularnewline
94 &  1 &  0.9157 &  0.08427 \tabularnewline
95 &  1 &  0.8007 &  0.1993 \tabularnewline
96 &  1 &  0.8347 &  0.1653 \tabularnewline
97 &  1 &  0.8716 &  0.1284 \tabularnewline
98 &  1 &  1.09 & -0.09037 \tabularnewline
99 &  1 &  0.8687 &  0.1313 \tabularnewline
100 &  1 &  0.935 &  0.06504 \tabularnewline
101 &  1 &  1.002 & -0.002316 \tabularnewline
102 &  1 &  0.9462 &  0.05381 \tabularnewline
103 &  1 &  1.018 & -0.018 \tabularnewline
104 &  1 &  0.5665 &  0.4335 \tabularnewline
105 &  1 &  0.6165 &  0.3835 \tabularnewline
106 &  1 &  0.53 &  0.47 \tabularnewline
107 &  1 &  0.5206 &  0.4794 \tabularnewline
108 &  1 &  0.6694 &  0.3306 \tabularnewline
109 &  1 &  0.6122 &  0.3878 \tabularnewline
110 &  1 &  0.8597 &  0.1403 \tabularnewline
111 &  1 &  0.9922 &  0.007768 \tabularnewline
112 &  1 &  0.6495 &  0.3505 \tabularnewline
113 &  1 &  0.8231 &  0.1769 \tabularnewline
114 &  1 &  0.6317 &  0.3683 \tabularnewline
115 &  1 &  0.8327 &  0.1673 \tabularnewline
116 &  1 &  0.8738 &  0.1262 \tabularnewline
117 &  1 &  0.6988 &  0.3012 \tabularnewline
118 &  1 &  0.9751 &  0.0249 \tabularnewline
119 &  1 &  0.8271 &  0.1729 \tabularnewline
120 &  1 &  0.6834 &  0.3166 \tabularnewline
121 &  1 &  0.4806 &  0.5194 \tabularnewline
122 &  1 &  0.9201 &  0.07991 \tabularnewline
123 &  1 &  0.9937 &  0.006284 \tabularnewline
124 &  1 &  0.7274 &  0.2726 \tabularnewline
125 &  1 &  0.6694 &  0.3306 \tabularnewline
126 &  1 &  0.6388 &  0.3612 \tabularnewline
127 &  1 &  0.6243 &  0.3757 \tabularnewline
128 &  1 &  0.6215 &  0.3785 \tabularnewline
129 &  1 &  0.3583 &  0.6417 \tabularnewline
130 &  1 &  0.7261 &  0.2738 \tabularnewline
131 &  1 &  0.7718 &  0.2282 \tabularnewline
132 &  1 &  0.7968 &  0.2032 \tabularnewline
133 &  1 &  1.03 & -0.03031 \tabularnewline
134 &  1 &  0.6094 &  0.3906 \tabularnewline
135 &  1 &  0.8294 &  0.1706 \tabularnewline
136 &  1 &  0.9567 &  0.04329 \tabularnewline
137 &  1 &  1.067 & -0.06719 \tabularnewline
138 &  1 &  1.129 & -0.1295 \tabularnewline
139 &  1 &  0.9107 &  0.08926 \tabularnewline
140 &  1 &  0.785 &  0.215 \tabularnewline
141 &  1 &  0.7781 &  0.2219 \tabularnewline
142 &  1 &  0.7283 &  0.2717 \tabularnewline
143 &  1 &  0.6413 &  0.3587 \tabularnewline
144 &  1 &  0.669 &  0.331 \tabularnewline
145 &  1 &  0.5013 &  0.4987 \tabularnewline
146 &  1 &  0.7459 &  0.2541 \tabularnewline
147 &  1 &  1.126 & -0.126 \tabularnewline
148 &  1 &  1.113 & -0.113 \tabularnewline
149 &  1 &  1.162 & -0.1615 \tabularnewline
150 &  1 &  0.8644 &  0.1356 \tabularnewline
151 &  1 &  1.036 & -0.03556 \tabularnewline
152 &  1 &  0.9062 &  0.09378 \tabularnewline
153 &  1 &  1.01 & -0.01032 \tabularnewline
154 &  1 &  0.92 &  0.07998 \tabularnewline
155 &  1 &  0.8648 &  0.1352 \tabularnewline
156 &  1 &  1.118 & -0.1184 \tabularnewline
157 &  1 &  0.7434 &  0.2566 \tabularnewline
158 &  1 &  1.182 & -0.1822 \tabularnewline
159 &  1 &  0.9027 &  0.09726 \tabularnewline
160 &  1 &  0.7326 &  0.2674 \tabularnewline
161 &  1 &  0.8914 &  0.1086 \tabularnewline
162 &  1 &  1.004 & -0.003894 \tabularnewline
163 &  1 &  0.7556 &  0.2444 \tabularnewline
164 &  1 &  0.7832 &  0.2168 \tabularnewline
165 &  1 &  1.333 & -0.3329 \tabularnewline
166 &  0 &  0.2295 & -0.2295 \tabularnewline
167 &  0 &  0.1547 & -0.1547 \tabularnewline
168 &  0 &  0.01204 & -0.01204 \tabularnewline
169 &  0 &  0.8907 & -0.8907 \tabularnewline
170 &  0 &  0.1909 & -0.1909 \tabularnewline
171 &  0 & -0.02519 &  0.02519 \tabularnewline
172 &  0 &  0.6206 & -0.6206 \tabularnewline
173 &  0 &  0.6758 & -0.6758 \tabularnewline
174 &  0 &  0.7075 & -0.7075 \tabularnewline
175 &  0 &  0.7482 & -0.7482 \tabularnewline
176 &  0 &  0.6621 & -0.6621 \tabularnewline
177 &  0 &  0.5897 & -0.5897 \tabularnewline
178 &  1 &  0.4713 &  0.5287 \tabularnewline
179 &  1 &  0.5219 &  0.4781 \tabularnewline
180 &  1 &  0.7123 &  0.2877 \tabularnewline
181 &  1 &  0.5894 &  0.4106 \tabularnewline
182 &  1 &  0.6673 &  0.3327 \tabularnewline
183 &  1 &  0.5988 &  0.4012 \tabularnewline
184 &  0 &  0.4288 & -0.4288 \tabularnewline
185 &  0 &  0.4852 & -0.4852 \tabularnewline
186 &  0 &  0.4492 & -0.4492 \tabularnewline
187 &  0 &  0.3817 & -0.3817 \tabularnewline
188 &  0 &  0.4391 & -0.4391 \tabularnewline
189 &  0 &  0.3125 & -0.3125 \tabularnewline
190 &  0 &  0.3196 & -0.3196 \tabularnewline
191 &  0 &  0.5248 & -0.5248 \tabularnewline
192 &  0 &  0.5387 & -0.5387 \tabularnewline
193 &  0 & -0.2709 &  0.2709 \tabularnewline
194 &  0 &  0.1749 & -0.1749 \tabularnewline
195 &  0 &  0.3572 & -0.3572 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286263&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] 1.019[/C][C]-0.01883[/C][/ROW]
[ROW][C]2[/C][C] 1[/C][C] 1.126[/C][C]-0.1256[/C][/ROW]
[ROW][C]3[/C][C] 1[/C][C] 1.024[/C][C]-0.02418[/C][/ROW]
[ROW][C]4[/C][C] 1[/C][C] 1.1[/C][C]-0.1002[/C][/ROW]
[ROW][C]5[/C][C] 1[/C][C] 0.8687[/C][C] 0.1313[/C][/ROW]
[ROW][C]6[/C][C] 1[/C][C] 0.9677[/C][C] 0.03226[/C][/ROW]
[ROW][C]7[/C][C] 1[/C][C] 0.9504[/C][C] 0.04955[/C][/ROW]
[ROW][C]8[/C][C] 1[/C][C] 0.7098[/C][C] 0.2902[/C][/ROW]
[ROW][C]9[/C][C] 1[/C][C] 1.137[/C][C]-0.1368[/C][/ROW]
[ROW][C]10[/C][C] 1[/C][C] 1.246[/C][C]-0.2455[/C][/ROW]
[ROW][C]11[/C][C] 1[/C][C] 1.268[/C][C]-0.2685[/C][/ROW]
[ROW][C]12[/C][C] 1[/C][C] 1.338[/C][C]-0.3377[/C][/ROW]
[ROW][C]13[/C][C] 1[/C][C] 0.7818[/C][C] 0.2182[/C][/ROW]
[ROW][C]14[/C][C] 1[/C][C] 1.126[/C][C]-0.1262[/C][/ROW]
[ROW][C]15[/C][C] 1[/C][C] 0.9549[/C][C] 0.04507[/C][/ROW]
[ROW][C]16[/C][C] 1[/C][C] 0.9039[/C][C] 0.09612[/C][/ROW]
[ROW][C]17[/C][C] 1[/C][C] 0.8039[/C][C] 0.1961[/C][/ROW]
[ROW][C]18[/C][C] 1[/C][C] 1.491[/C][C]-0.4909[/C][/ROW]
[ROW][C]19[/C][C] 1[/C][C] 1.319[/C][C]-0.3187[/C][/ROW]
[ROW][C]20[/C][C] 1[/C][C] 1.088[/C][C]-0.08846[/C][/ROW]
[ROW][C]21[/C][C] 1[/C][C] 1.177[/C][C]-0.1771[/C][/ROW]
[ROW][C]22[/C][C] 1[/C][C] 1.04[/C][C]-0.03969[/C][/ROW]
[ROW][C]23[/C][C] 1[/C][C] 1.161[/C][C]-0.1607[/C][/ROW]
[ROW][C]24[/C][C] 1[/C][C] 0.9571[/C][C] 0.04291[/C][/ROW]
[ROW][C]25[/C][C] 1[/C][C] 0.95[/C][C] 0.05[/C][/ROW]
[ROW][C]26[/C][C] 1[/C][C] 0.9993[/C][C] 0.0007183[/C][/ROW]
[ROW][C]27[/C][C] 1[/C][C] 0.9142[/C][C] 0.08579[/C][/ROW]
[ROW][C]28[/C][C] 1[/C][C] 0.9957[/C][C] 0.004305[/C][/ROW]
[ROW][C]29[/C][C] 1[/C][C] 0.8254[/C][C] 0.1746[/C][/ROW]
[ROW][C]30[/C][C] 1[/C][C] 0.8451[/C][C] 0.1549[/C][/ROW]
[ROW][C]31[/C][C] 0[/C][C] 0.4224[/C][C]-0.4224[/C][/ROW]
[ROW][C]32[/C][C] 0[/C][C] 0.1226[/C][C]-0.1226[/C][/ROW]
[ROW][C]33[/C][C] 0[/C][C] 0.1877[/C][C]-0.1877[/C][/ROW]
[ROW][C]34[/C][C] 0[/C][C] 0.08955[/C][C]-0.08955[/C][/ROW]
[ROW][C]35[/C][C] 0[/C][C] 0.03919[/C][C]-0.03919[/C][/ROW]
[ROW][C]36[/C][C] 0[/C][C] 0.1326[/C][C]-0.1326[/C][/ROW]
[ROW][C]37[/C][C] 1[/C][C] 0.964[/C][C] 0.03598[/C][/ROW]
[ROW][C]38[/C][C] 1[/C][C] 0.9204[/C][C] 0.07957[/C][/ROW]
[ROW][C]39[/C][C] 1[/C][C] 0.637[/C][C] 0.363[/C][/ROW]
[ROW][C]40[/C][C] 1[/C][C] 0.8014[/C][C] 0.1986[/C][/ROW]
[ROW][C]41[/C][C] 1[/C][C] 0.6605[/C][C] 0.3395[/C][/ROW]
[ROW][C]42[/C][C] 1[/C][C] 0.5093[/C][C] 0.4907[/C][/ROW]
[ROW][C]43[/C][C] 0[/C][C] 0.4438[/C][C]-0.4438[/C][/ROW]
[ROW][C]44[/C][C] 0[/C][C] 0.3666[/C][C]-0.3666[/C][/ROW]
[ROW][C]45[/C][C] 0[/C][C] 0.1044[/C][C]-0.1044[/C][/ROW]
[ROW][C]46[/C][C] 0[/C][C] 0.1736[/C][C]-0.1736[/C][/ROW]
[ROW][C]47[/C][C] 0[/C][C] 0.1246[/C][C]-0.1246[/C][/ROW]
[ROW][C]48[/C][C] 0[/C][C]-0.08702[/C][C] 0.08702[/C][/ROW]
[ROW][C]49[/C][C] 0[/C][C] 0.4556[/C][C]-0.4556[/C][/ROW]
[ROW][C]50[/C][C] 0[/C][C] 0.5258[/C][C]-0.5258[/C][/ROW]
[ROW][C]51[/C][C] 0[/C][C] 0.4804[/C][C]-0.4804[/C][/ROW]
[ROW][C]52[/C][C] 0[/C][C] 0.4389[/C][C]-0.4389[/C][/ROW]
[ROW][C]53[/C][C] 0[/C][C] 0.453[/C][C]-0.453[/C][/ROW]
[ROW][C]54[/C][C] 0[/C][C] 0.4923[/C][C]-0.4923[/C][/ROW]
[ROW][C]55[/C][C] 1[/C][C] 0.791[/C][C] 0.209[/C][/ROW]
[ROW][C]56[/C][C] 1[/C][C] 0.733[/C][C] 0.267[/C][/ROW]
[ROW][C]57[/C][C] 1[/C][C] 0.7743[/C][C] 0.2257[/C][/ROW]
[ROW][C]58[/C][C] 1[/C][C] 0.7069[/C][C] 0.2931[/C][/ROW]
[ROW][C]59[/C][C] 1[/C][C] 0.6961[/C][C] 0.3039[/C][/ROW]
[ROW][C]60[/C][C] 1[/C][C] 0.5925[/C][C] 0.4075[/C][/ROW]
[ROW][C]61[/C][C] 0[/C][C] 0.4335[/C][C]-0.4335[/C][/ROW]
[ROW][C]62[/C][C] 0[/C][C] 0.2282[/C][C]-0.2282[/C][/ROW]
[ROW][C]63[/C][C] 0[/C][C] 0.3098[/C][C]-0.3098[/C][/ROW]
[ROW][C]64[/C][C] 0[/C][C] 0.2813[/C][C]-0.2813[/C][/ROW]
[ROW][C]65[/C][C] 0[/C][C] 0.1846[/C][C]-0.1846[/C][/ROW]
[ROW][C]66[/C][C] 0[/C][C] 0.3144[/C][C]-0.3144[/C][/ROW]
[ROW][C]67[/C][C] 1[/C][C] 1.075[/C][C]-0.07486[/C][/ROW]
[ROW][C]68[/C][C] 1[/C][C] 1.015[/C][C]-0.01537[/C][/ROW]
[ROW][C]69[/C][C] 1[/C][C] 0.9172[/C][C] 0.08278[/C][/ROW]
[ROW][C]70[/C][C] 1[/C][C] 1.022[/C][C]-0.02161[/C][/ROW]
[ROW][C]71[/C][C] 1[/C][C] 0.9896[/C][C] 0.01041[/C][/ROW]
[ROW][C]72[/C][C] 1[/C][C] 1.124[/C][C]-0.1239[/C][/ROW]
[ROW][C]73[/C][C] 1[/C][C] 0.946[/C][C] 0.05402[/C][/ROW]
[ROW][C]74[/C][C] 1[/C][C] 0.9726[/C][C] 0.02738[/C][/ROW]
[ROW][C]75[/C][C] 1[/C][C] 1.026[/C][C]-0.02591[/C][/ROW]
[ROW][C]76[/C][C] 1[/C][C] 1.067[/C][C]-0.06728[/C][/ROW]
[ROW][C]77[/C][C] 1[/C][C] 1.134[/C][C]-0.1337[/C][/ROW]
[ROW][C]78[/C][C] 1[/C][C] 0.9867[/C][C] 0.01331[/C][/ROW]
[ROW][C]79[/C][C] 1[/C][C] 0.9304[/C][C] 0.06964[/C][/ROW]
[ROW][C]80[/C][C] 1[/C][C] 1.172[/C][C]-0.1715[/C][/ROW]
[ROW][C]81[/C][C] 1[/C][C] 1.157[/C][C]-0.1572[/C][/ROW]
[ROW][C]82[/C][C] 1[/C][C] 1.186[/C][C]-0.1859[/C][/ROW]
[ROW][C]83[/C][C] 1[/C][C] 1.036[/C][C]-0.03601[/C][/ROW]
[ROW][C]84[/C][C] 1[/C][C] 0.7724[/C][C] 0.2276[/C][/ROW]
[ROW][C]85[/C][C] 1[/C][C] 1.186[/C][C]-0.1861[/C][/ROW]
[ROW][C]86[/C][C] 1[/C][C] 0.9444[/C][C] 0.05558[/C][/ROW]
[ROW][C]87[/C][C] 1[/C][C] 0.789[/C][C] 0.211[/C][/ROW]
[ROW][C]88[/C][C] 1[/C][C] 0.9438[/C][C] 0.0562[/C][/ROW]
[ROW][C]89[/C][C] 1[/C][C] 0.963[/C][C] 0.03701[/C][/ROW]
[ROW][C]90[/C][C] 1[/C][C] 1.295[/C][C]-0.2951[/C][/ROW]
[ROW][C]91[/C][C] 1[/C][C] 1.18[/C][C]-0.1795[/C][/ROW]
[ROW][C]92[/C][C] 1[/C][C] 0.7899[/C][C] 0.2101[/C][/ROW]
[ROW][C]93[/C][C] 1[/C][C] 0.8268[/C][C] 0.1732[/C][/ROW]
[ROW][C]94[/C][C] 1[/C][C] 0.9157[/C][C] 0.08427[/C][/ROW]
[ROW][C]95[/C][C] 1[/C][C] 0.8007[/C][C] 0.1993[/C][/ROW]
[ROW][C]96[/C][C] 1[/C][C] 0.8347[/C][C] 0.1653[/C][/ROW]
[ROW][C]97[/C][C] 1[/C][C] 0.8716[/C][C] 0.1284[/C][/ROW]
[ROW][C]98[/C][C] 1[/C][C] 1.09[/C][C]-0.09037[/C][/ROW]
[ROW][C]99[/C][C] 1[/C][C] 0.8687[/C][C] 0.1313[/C][/ROW]
[ROW][C]100[/C][C] 1[/C][C] 0.935[/C][C] 0.06504[/C][/ROW]
[ROW][C]101[/C][C] 1[/C][C] 1.002[/C][C]-0.002316[/C][/ROW]
[ROW][C]102[/C][C] 1[/C][C] 0.9462[/C][C] 0.05381[/C][/ROW]
[ROW][C]103[/C][C] 1[/C][C] 1.018[/C][C]-0.018[/C][/ROW]
[ROW][C]104[/C][C] 1[/C][C] 0.5665[/C][C] 0.4335[/C][/ROW]
[ROW][C]105[/C][C] 1[/C][C] 0.6165[/C][C] 0.3835[/C][/ROW]
[ROW][C]106[/C][C] 1[/C][C] 0.53[/C][C] 0.47[/C][/ROW]
[ROW][C]107[/C][C] 1[/C][C] 0.5206[/C][C] 0.4794[/C][/ROW]
[ROW][C]108[/C][C] 1[/C][C] 0.6694[/C][C] 0.3306[/C][/ROW]
[ROW][C]109[/C][C] 1[/C][C] 0.6122[/C][C] 0.3878[/C][/ROW]
[ROW][C]110[/C][C] 1[/C][C] 0.8597[/C][C] 0.1403[/C][/ROW]
[ROW][C]111[/C][C] 1[/C][C] 0.9922[/C][C] 0.007768[/C][/ROW]
[ROW][C]112[/C][C] 1[/C][C] 0.6495[/C][C] 0.3505[/C][/ROW]
[ROW][C]113[/C][C] 1[/C][C] 0.8231[/C][C] 0.1769[/C][/ROW]
[ROW][C]114[/C][C] 1[/C][C] 0.6317[/C][C] 0.3683[/C][/ROW]
[ROW][C]115[/C][C] 1[/C][C] 0.8327[/C][C] 0.1673[/C][/ROW]
[ROW][C]116[/C][C] 1[/C][C] 0.8738[/C][C] 0.1262[/C][/ROW]
[ROW][C]117[/C][C] 1[/C][C] 0.6988[/C][C] 0.3012[/C][/ROW]
[ROW][C]118[/C][C] 1[/C][C] 0.9751[/C][C] 0.0249[/C][/ROW]
[ROW][C]119[/C][C] 1[/C][C] 0.8271[/C][C] 0.1729[/C][/ROW]
[ROW][C]120[/C][C] 1[/C][C] 0.6834[/C][C] 0.3166[/C][/ROW]
[ROW][C]121[/C][C] 1[/C][C] 0.4806[/C][C] 0.5194[/C][/ROW]
[ROW][C]122[/C][C] 1[/C][C] 0.9201[/C][C] 0.07991[/C][/ROW]
[ROW][C]123[/C][C] 1[/C][C] 0.9937[/C][C] 0.006284[/C][/ROW]
[ROW][C]124[/C][C] 1[/C][C] 0.7274[/C][C] 0.2726[/C][/ROW]
[ROW][C]125[/C][C] 1[/C][C] 0.6694[/C][C] 0.3306[/C][/ROW]
[ROW][C]126[/C][C] 1[/C][C] 0.6388[/C][C] 0.3612[/C][/ROW]
[ROW][C]127[/C][C] 1[/C][C] 0.6243[/C][C] 0.3757[/C][/ROW]
[ROW][C]128[/C][C] 1[/C][C] 0.6215[/C][C] 0.3785[/C][/ROW]
[ROW][C]129[/C][C] 1[/C][C] 0.3583[/C][C] 0.6417[/C][/ROW]
[ROW][C]130[/C][C] 1[/C][C] 0.7261[/C][C] 0.2738[/C][/ROW]
[ROW][C]131[/C][C] 1[/C][C] 0.7718[/C][C] 0.2282[/C][/ROW]
[ROW][C]132[/C][C] 1[/C][C] 0.7968[/C][C] 0.2032[/C][/ROW]
[ROW][C]133[/C][C] 1[/C][C] 1.03[/C][C]-0.03031[/C][/ROW]
[ROW][C]134[/C][C] 1[/C][C] 0.6094[/C][C] 0.3906[/C][/ROW]
[ROW][C]135[/C][C] 1[/C][C] 0.8294[/C][C] 0.1706[/C][/ROW]
[ROW][C]136[/C][C] 1[/C][C] 0.9567[/C][C] 0.04329[/C][/ROW]
[ROW][C]137[/C][C] 1[/C][C] 1.067[/C][C]-0.06719[/C][/ROW]
[ROW][C]138[/C][C] 1[/C][C] 1.129[/C][C]-0.1295[/C][/ROW]
[ROW][C]139[/C][C] 1[/C][C] 0.9107[/C][C] 0.08926[/C][/ROW]
[ROW][C]140[/C][C] 1[/C][C] 0.785[/C][C] 0.215[/C][/ROW]
[ROW][C]141[/C][C] 1[/C][C] 0.7781[/C][C] 0.2219[/C][/ROW]
[ROW][C]142[/C][C] 1[/C][C] 0.7283[/C][C] 0.2717[/C][/ROW]
[ROW][C]143[/C][C] 1[/C][C] 0.6413[/C][C] 0.3587[/C][/ROW]
[ROW][C]144[/C][C] 1[/C][C] 0.669[/C][C] 0.331[/C][/ROW]
[ROW][C]145[/C][C] 1[/C][C] 0.5013[/C][C] 0.4987[/C][/ROW]
[ROW][C]146[/C][C] 1[/C][C] 0.7459[/C][C] 0.2541[/C][/ROW]
[ROW][C]147[/C][C] 1[/C][C] 1.126[/C][C]-0.126[/C][/ROW]
[ROW][C]148[/C][C] 1[/C][C] 1.113[/C][C]-0.113[/C][/ROW]
[ROW][C]149[/C][C] 1[/C][C] 1.162[/C][C]-0.1615[/C][/ROW]
[ROW][C]150[/C][C] 1[/C][C] 0.8644[/C][C] 0.1356[/C][/ROW]
[ROW][C]151[/C][C] 1[/C][C] 1.036[/C][C]-0.03556[/C][/ROW]
[ROW][C]152[/C][C] 1[/C][C] 0.9062[/C][C] 0.09378[/C][/ROW]
[ROW][C]153[/C][C] 1[/C][C] 1.01[/C][C]-0.01032[/C][/ROW]
[ROW][C]154[/C][C] 1[/C][C] 0.92[/C][C] 0.07998[/C][/ROW]
[ROW][C]155[/C][C] 1[/C][C] 0.8648[/C][C] 0.1352[/C][/ROW]
[ROW][C]156[/C][C] 1[/C][C] 1.118[/C][C]-0.1184[/C][/ROW]
[ROW][C]157[/C][C] 1[/C][C] 0.7434[/C][C] 0.2566[/C][/ROW]
[ROW][C]158[/C][C] 1[/C][C] 1.182[/C][C]-0.1822[/C][/ROW]
[ROW][C]159[/C][C] 1[/C][C] 0.9027[/C][C] 0.09726[/C][/ROW]
[ROW][C]160[/C][C] 1[/C][C] 0.7326[/C][C] 0.2674[/C][/ROW]
[ROW][C]161[/C][C] 1[/C][C] 0.8914[/C][C] 0.1086[/C][/ROW]
[ROW][C]162[/C][C] 1[/C][C] 1.004[/C][C]-0.003894[/C][/ROW]
[ROW][C]163[/C][C] 1[/C][C] 0.7556[/C][C] 0.2444[/C][/ROW]
[ROW][C]164[/C][C] 1[/C][C] 0.7832[/C][C] 0.2168[/C][/ROW]
[ROW][C]165[/C][C] 1[/C][C] 1.333[/C][C]-0.3329[/C][/ROW]
[ROW][C]166[/C][C] 0[/C][C] 0.2295[/C][C]-0.2295[/C][/ROW]
[ROW][C]167[/C][C] 0[/C][C] 0.1547[/C][C]-0.1547[/C][/ROW]
[ROW][C]168[/C][C] 0[/C][C] 0.01204[/C][C]-0.01204[/C][/ROW]
[ROW][C]169[/C][C] 0[/C][C] 0.8907[/C][C]-0.8907[/C][/ROW]
[ROW][C]170[/C][C] 0[/C][C] 0.1909[/C][C]-0.1909[/C][/ROW]
[ROW][C]171[/C][C] 0[/C][C]-0.02519[/C][C] 0.02519[/C][/ROW]
[ROW][C]172[/C][C] 0[/C][C] 0.6206[/C][C]-0.6206[/C][/ROW]
[ROW][C]173[/C][C] 0[/C][C] 0.6758[/C][C]-0.6758[/C][/ROW]
[ROW][C]174[/C][C] 0[/C][C] 0.7075[/C][C]-0.7075[/C][/ROW]
[ROW][C]175[/C][C] 0[/C][C] 0.7482[/C][C]-0.7482[/C][/ROW]
[ROW][C]176[/C][C] 0[/C][C] 0.6621[/C][C]-0.6621[/C][/ROW]
[ROW][C]177[/C][C] 0[/C][C] 0.5897[/C][C]-0.5897[/C][/ROW]
[ROW][C]178[/C][C] 1[/C][C] 0.4713[/C][C] 0.5287[/C][/ROW]
[ROW][C]179[/C][C] 1[/C][C] 0.5219[/C][C] 0.4781[/C][/ROW]
[ROW][C]180[/C][C] 1[/C][C] 0.7123[/C][C] 0.2877[/C][/ROW]
[ROW][C]181[/C][C] 1[/C][C] 0.5894[/C][C] 0.4106[/C][/ROW]
[ROW][C]182[/C][C] 1[/C][C] 0.6673[/C][C] 0.3327[/C][/ROW]
[ROW][C]183[/C][C] 1[/C][C] 0.5988[/C][C] 0.4012[/C][/ROW]
[ROW][C]184[/C][C] 0[/C][C] 0.4288[/C][C]-0.4288[/C][/ROW]
[ROW][C]185[/C][C] 0[/C][C] 0.4852[/C][C]-0.4852[/C][/ROW]
[ROW][C]186[/C][C] 0[/C][C] 0.4492[/C][C]-0.4492[/C][/ROW]
[ROW][C]187[/C][C] 0[/C][C] 0.3817[/C][C]-0.3817[/C][/ROW]
[ROW][C]188[/C][C] 0[/C][C] 0.4391[/C][C]-0.4391[/C][/ROW]
[ROW][C]189[/C][C] 0[/C][C] 0.3125[/C][C]-0.3125[/C][/ROW]
[ROW][C]190[/C][C] 0[/C][C] 0.3196[/C][C]-0.3196[/C][/ROW]
[ROW][C]191[/C][C] 0[/C][C] 0.5248[/C][C]-0.5248[/C][/ROW]
[ROW][C]192[/C][C] 0[/C][C] 0.5387[/C][C]-0.5387[/C][/ROW]
[ROW][C]193[/C][C] 0[/C][C]-0.2709[/C][C] 0.2709[/C][/ROW]
[ROW][C]194[/C][C] 0[/C][C] 0.1749[/C][C]-0.1749[/C][/ROW]
[ROW][C]195[/C][C] 0[/C][C] 0.3572[/C][C]-0.3572[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286263&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286263&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
1 1 1.019-0.01883
2 1 1.126-0.1256
3 1 1.024-0.02418
4 1 1.1-0.1002
5 1 0.8687 0.1313
6 1 0.9677 0.03226
7 1 0.9504 0.04955
8 1 0.7098 0.2902
9 1 1.137-0.1368
10 1 1.246-0.2455
11 1 1.268-0.2685
12 1 1.338-0.3377
13 1 0.7818 0.2182
14 1 1.126-0.1262
15 1 0.9549 0.04507
16 1 0.9039 0.09612
17 1 0.8039 0.1961
18 1 1.491-0.4909
19 1 1.319-0.3187
20 1 1.088-0.08846
21 1 1.177-0.1771
22 1 1.04-0.03969
23 1 1.161-0.1607
24 1 0.9571 0.04291
25 1 0.95 0.05
26 1 0.9993 0.0007183
27 1 0.9142 0.08579
28 1 0.9957 0.004305
29 1 0.8254 0.1746
30 1 0.8451 0.1549
31 0 0.4224-0.4224
32 0 0.1226-0.1226
33 0 0.1877-0.1877
34 0 0.08955-0.08955
35 0 0.03919-0.03919
36 0 0.1326-0.1326
37 1 0.964 0.03598
38 1 0.9204 0.07957
39 1 0.637 0.363
40 1 0.8014 0.1986
41 1 0.6605 0.3395
42 1 0.5093 0.4907
43 0 0.4438-0.4438
44 0 0.3666-0.3666
45 0 0.1044-0.1044
46 0 0.1736-0.1736
47 0 0.1246-0.1246
48 0-0.08702 0.08702
49 0 0.4556-0.4556
50 0 0.5258-0.5258
51 0 0.4804-0.4804
52 0 0.4389-0.4389
53 0 0.453-0.453
54 0 0.4923-0.4923
55 1 0.791 0.209
56 1 0.733 0.267
57 1 0.7743 0.2257
58 1 0.7069 0.2931
59 1 0.6961 0.3039
60 1 0.5925 0.4075
61 0 0.4335-0.4335
62 0 0.2282-0.2282
63 0 0.3098-0.3098
64 0 0.2813-0.2813
65 0 0.1846-0.1846
66 0 0.3144-0.3144
67 1 1.075-0.07486
68 1 1.015-0.01537
69 1 0.9172 0.08278
70 1 1.022-0.02161
71 1 0.9896 0.01041
72 1 1.124-0.1239
73 1 0.946 0.05402
74 1 0.9726 0.02738
75 1 1.026-0.02591
76 1 1.067-0.06728
77 1 1.134-0.1337
78 1 0.9867 0.01331
79 1 0.9304 0.06964
80 1 1.172-0.1715
81 1 1.157-0.1572
82 1 1.186-0.1859
83 1 1.036-0.03601
84 1 0.7724 0.2276
85 1 1.186-0.1861
86 1 0.9444 0.05558
87 1 0.789 0.211
88 1 0.9438 0.0562
89 1 0.963 0.03701
90 1 1.295-0.2951
91 1 1.18-0.1795
92 1 0.7899 0.2101
93 1 0.8268 0.1732
94 1 0.9157 0.08427
95 1 0.8007 0.1993
96 1 0.8347 0.1653
97 1 0.8716 0.1284
98 1 1.09-0.09037
99 1 0.8687 0.1313
100 1 0.935 0.06504
101 1 1.002-0.002316
102 1 0.9462 0.05381
103 1 1.018-0.018
104 1 0.5665 0.4335
105 1 0.6165 0.3835
106 1 0.53 0.47
107 1 0.5206 0.4794
108 1 0.6694 0.3306
109 1 0.6122 0.3878
110 1 0.8597 0.1403
111 1 0.9922 0.007768
112 1 0.6495 0.3505
113 1 0.8231 0.1769
114 1 0.6317 0.3683
115 1 0.8327 0.1673
116 1 0.8738 0.1262
117 1 0.6988 0.3012
118 1 0.9751 0.0249
119 1 0.8271 0.1729
120 1 0.6834 0.3166
121 1 0.4806 0.5194
122 1 0.9201 0.07991
123 1 0.9937 0.006284
124 1 0.7274 0.2726
125 1 0.6694 0.3306
126 1 0.6388 0.3612
127 1 0.6243 0.3757
128 1 0.6215 0.3785
129 1 0.3583 0.6417
130 1 0.7261 0.2738
131 1 0.7718 0.2282
132 1 0.7968 0.2032
133 1 1.03-0.03031
134 1 0.6094 0.3906
135 1 0.8294 0.1706
136 1 0.9567 0.04329
137 1 1.067-0.06719
138 1 1.129-0.1295
139 1 0.9107 0.08926
140 1 0.785 0.215
141 1 0.7781 0.2219
142 1 0.7283 0.2717
143 1 0.6413 0.3587
144 1 0.669 0.331
145 1 0.5013 0.4987
146 1 0.7459 0.2541
147 1 1.126-0.126
148 1 1.113-0.113
149 1 1.162-0.1615
150 1 0.8644 0.1356
151 1 1.036-0.03556
152 1 0.9062 0.09378
153 1 1.01-0.01032
154 1 0.92 0.07998
155 1 0.8648 0.1352
156 1 1.118-0.1184
157 1 0.7434 0.2566
158 1 1.182-0.1822
159 1 0.9027 0.09726
160 1 0.7326 0.2674
161 1 0.8914 0.1086
162 1 1.004-0.003894
163 1 0.7556 0.2444
164 1 0.7832 0.2168
165 1 1.333-0.3329
166 0 0.2295-0.2295
167 0 0.1547-0.1547
168 0 0.01204-0.01204
169 0 0.8907-0.8907
170 0 0.1909-0.1909
171 0-0.02519 0.02519
172 0 0.6206-0.6206
173 0 0.6758-0.6758
174 0 0.7075-0.7075
175 0 0.7482-0.7482
176 0 0.6621-0.6621
177 0 0.5897-0.5897
178 1 0.4713 0.5287
179 1 0.5219 0.4781
180 1 0.7123 0.2877
181 1 0.5894 0.4106
182 1 0.6673 0.3327
183 1 0.5988 0.4012
184 0 0.4288-0.4288
185 0 0.4852-0.4852
186 0 0.4492-0.4492
187 0 0.3817-0.3817
188 0 0.4391-0.4391
189 0 0.3125-0.3125
190 0 0.3196-0.3196
191 0 0.5248-0.5248
192 0 0.5387-0.5387
193 0-0.2709 0.2709
194 0 0.1749-0.1749
195 0 0.3572-0.3572






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
19 5.474e-47 1.095e-46 1
20 1.497e-60 2.994e-60 1
21 1.711e-75 3.423e-75 1
22 3.891e-89 7.782e-89 1
23 5.911e-104 1.182e-103 1
24 2.228e-122 4.456e-122 1
25 4.953e-133 9.905e-133 1
26 2.309e-149 4.618e-149 1
27 2.651e-164 5.301e-164 1
28 1.778e-176 3.556e-176 1
29 5.119e-190 1.024e-189 1
30 1.794e-205 3.589e-205 1
31 3.258e-05 6.517e-05 1
32 1.411e-05 2.821e-05 1
33 4.9e-06 9.8e-06 1
34 1.847e-06 3.693e-06 1
35 6.218e-07 1.244e-06 1
36 1.981e-07 3.961e-07 1
37 2.474e-06 4.949e-06 1
38 1.803e-06 3.606e-06 1
39 3.244e-05 6.487e-05 1
40 4.656e-05 9.312e-05 1
41 5.436e-05 0.0001087 0.9999
42 3.069e-05 6.137e-05 1
43 1.736e-05 3.471e-05 1
44 1.062e-05 2.124e-05 1
45 6.183e-06 1.237e-05 1
46 2.999e-06 5.999e-06 1
47 1.647e-06 3.295e-06 1
48 1.035e-06 2.07e-06 1
49 0.0007077 0.001415 0.9993
50 0.00116 0.002321 0.9988
51 0.001095 0.002189 0.9989
52 0.001046 0.002093 0.999
53 0.001225 0.002449 0.9988
54 0.0019 0.0038 0.9981
55 0.001258 0.002515 0.9987
56 0.001026 0.002052 0.999
57 0.0006508 0.001302 0.9993
58 0.0004961 0.0009921 0.9995
59 0.000396 0.0007921 0.9996
60 0.0009069 0.001814 0.9991
61 0.01546 0.03092 0.9845
62 0.01774 0.03548 0.9823
63 0.02291 0.04581 0.9771
64 0.02802 0.05604 0.972
65 0.02971 0.05941 0.9703
66 0.04299 0.08598 0.957
67 0.03419 0.06837 0.9658
68 0.02682 0.05364 0.9732
69 0.02185 0.0437 0.9781
70 0.01844 0.03687 0.9816
71 0.01452 0.02905 0.9855
72 0.01346 0.02693 0.9865
73 0.01253 0.02507 0.9875
74 0.009547 0.0191 0.9905
75 0.009814 0.01963 0.9902
76 0.007768 0.01554 0.9922
77 0.007451 0.0149 0.9925
78 0.006211 0.01242 0.9938
79 0.00503 0.01006 0.995
80 0.007221 0.01444 0.9928
81 0.007233 0.01447 0.9928
82 0.007245 0.01449 0.9928
83 0.006972 0.01394 0.993
84 0.005588 0.01118 0.9944
85 0.005196 0.01039 0.9948
86 0.008363 0.01673 0.9916
87 0.01647 0.03294 0.9835
88 0.01421 0.02842 0.9858
89 0.0127 0.02539 0.9873
90 0.03522 0.07044 0.9648
91 0.05268 0.1054 0.9473
92 0.0654 0.1308 0.9346
93 0.05944 0.1189 0.9406
94 0.0506 0.1012 0.9494
95 0.04341 0.08682 0.9566
96 0.04239 0.08479 0.9576
97 0.03962 0.07923 0.9604
98 0.0499 0.09979 0.9501
99 0.05138 0.1028 0.9486
100 0.04738 0.09477 0.9526
101 0.052 0.104 0.948
102 0.04449 0.08898 0.9555
103 0.05006 0.1001 0.9499
104 0.04836 0.09671 0.9516
105 0.04358 0.08715 0.9564
106 0.04565 0.0913 0.9544
107 0.04142 0.08283 0.9586
108 0.03639 0.07277 0.9636
109 0.02961 0.05921 0.9704
110 0.02446 0.04892 0.9755
111 0.01946 0.03892 0.9805
112 0.01919 0.03837 0.9808
113 0.01525 0.0305 0.9847
114 0.01517 0.03033 0.9848
115 0.01157 0.02315 0.9884
116 0.01108 0.02216 0.9889
117 0.008576 0.01715 0.9914
118 0.007419 0.01484 0.9926
119 0.005733 0.01147 0.9943
120 0.005314 0.01063 0.9947
121 0.004972 0.009944 0.995
122 0.004242 0.008484 0.9958
123 0.003598 0.007197 0.9964
124 0.002627 0.005255 0.9974
125 0.001873 0.003746 0.9981
126 0.001321 0.002642 0.9987
127 0.0009113 0.001823 0.9991
128 0.0006551 0.00131 0.9993
129 0.0007913 0.001583 0.9992
130 0.0005691 0.001138 0.9994
131 0.0004039 0.0008078 0.9996
132 0.0002992 0.0005984 0.9997
133 0.0003066 0.0006133 0.9997
134 0.0002763 0.0005526 0.9997
135 0.0001794 0.0003589 0.9998
136 0.0001569 0.0003138 0.9998
137 0.0001887 0.0003773 0.9998
138 0.0004452 0.0008903 0.9996
139 0.0004355 0.000871 0.9996
140 0.000432 0.0008639 0.9996
141 0.0003419 0.0006839 0.9997
142 0.0002341 0.0004683 0.9998
143 0.0002118 0.0004236 0.9998
144 0.0001389 0.0002778 0.9999
145 0.0001136 0.0002272 0.9999
146 0.0001595 0.0003189 0.9998
147 0.0001596 0.0003192 0.9998
148 0.0001397 0.0002795 0.9999
149 0.0002852 0.0005704 0.9997
150 0.000194 0.000388 0.9998
151 0.000118 0.0002359 0.9999
152 8.876e-05 0.0001775 0.9999
153 0.0001491 0.0002981 0.9999
154 0.0001007 0.0002015 0.9999
155 7.19e-05 0.0001438 0.9999
156 7.932e-05 0.0001586 0.9999
157 0.0002071 0.0004142 0.9998
158 0.0001354 0.0002708 0.9999
159 0.02281 0.04561 0.9772
160 0.01578 0.03155 0.9842
161 0.01316 0.02631 0.9868
162 0.009816 0.01963 0.9902
163 0.006545 0.01309 0.9935
164 0.01615 0.0323 0.9838
165 0.2355 0.471 0.7645
166 0.7583 0.4835 0.2417
167 0.7545 0.4909 0.2455
168 0.6775 0.645 0.3225
169 0.8917 0.2167 0.1083
170 0.8778 0.2444 0.1222
171 0.9663 0.06731 0.03366
172 0.9797 0.04052 0.02026
173 0.9668 0.06646 0.03323
174 0.9585 0.08309 0.04155
175 0.9483 0.1033 0.05166
176 0.9188 0.1624 0.08121

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
19 &  5.474e-47 &  1.095e-46 &  1 \tabularnewline
20 &  1.497e-60 &  2.994e-60 &  1 \tabularnewline
21 &  1.711e-75 &  3.423e-75 &  1 \tabularnewline
22 &  3.891e-89 &  7.782e-89 &  1 \tabularnewline
23 &  5.911e-104 &  1.182e-103 &  1 \tabularnewline
24 &  2.228e-122 &  4.456e-122 &  1 \tabularnewline
25 &  4.953e-133 &  9.905e-133 &  1 \tabularnewline
26 &  2.309e-149 &  4.618e-149 &  1 \tabularnewline
27 &  2.651e-164 &  5.301e-164 &  1 \tabularnewline
28 &  1.778e-176 &  3.556e-176 &  1 \tabularnewline
29 &  5.119e-190 &  1.024e-189 &  1 \tabularnewline
30 &  1.794e-205 &  3.589e-205 &  1 \tabularnewline
31 &  3.258e-05 &  6.517e-05 &  1 \tabularnewline
32 &  1.411e-05 &  2.821e-05 &  1 \tabularnewline
33 &  4.9e-06 &  9.8e-06 &  1 \tabularnewline
34 &  1.847e-06 &  3.693e-06 &  1 \tabularnewline
35 &  6.218e-07 &  1.244e-06 &  1 \tabularnewline
36 &  1.981e-07 &  3.961e-07 &  1 \tabularnewline
37 &  2.474e-06 &  4.949e-06 &  1 \tabularnewline
38 &  1.803e-06 &  3.606e-06 &  1 \tabularnewline
39 &  3.244e-05 &  6.487e-05 &  1 \tabularnewline
40 &  4.656e-05 &  9.312e-05 &  1 \tabularnewline
41 &  5.436e-05 &  0.0001087 &  0.9999 \tabularnewline
42 &  3.069e-05 &  6.137e-05 &  1 \tabularnewline
43 &  1.736e-05 &  3.471e-05 &  1 \tabularnewline
44 &  1.062e-05 &  2.124e-05 &  1 \tabularnewline
45 &  6.183e-06 &  1.237e-05 &  1 \tabularnewline
46 &  2.999e-06 &  5.999e-06 &  1 \tabularnewline
47 &  1.647e-06 &  3.295e-06 &  1 \tabularnewline
48 &  1.035e-06 &  2.07e-06 &  1 \tabularnewline
49 &  0.0007077 &  0.001415 &  0.9993 \tabularnewline
50 &  0.00116 &  0.002321 &  0.9988 \tabularnewline
51 &  0.001095 &  0.002189 &  0.9989 \tabularnewline
52 &  0.001046 &  0.002093 &  0.999 \tabularnewline
53 &  0.001225 &  0.002449 &  0.9988 \tabularnewline
54 &  0.0019 &  0.0038 &  0.9981 \tabularnewline
55 &  0.001258 &  0.002515 &  0.9987 \tabularnewline
56 &  0.001026 &  0.002052 &  0.999 \tabularnewline
57 &  0.0006508 &  0.001302 &  0.9993 \tabularnewline
58 &  0.0004961 &  0.0009921 &  0.9995 \tabularnewline
59 &  0.000396 &  0.0007921 &  0.9996 \tabularnewline
60 &  0.0009069 &  0.001814 &  0.9991 \tabularnewline
61 &  0.01546 &  0.03092 &  0.9845 \tabularnewline
62 &  0.01774 &  0.03548 &  0.9823 \tabularnewline
63 &  0.02291 &  0.04581 &  0.9771 \tabularnewline
64 &  0.02802 &  0.05604 &  0.972 \tabularnewline
65 &  0.02971 &  0.05941 &  0.9703 \tabularnewline
66 &  0.04299 &  0.08598 &  0.957 \tabularnewline
67 &  0.03419 &  0.06837 &  0.9658 \tabularnewline
68 &  0.02682 &  0.05364 &  0.9732 \tabularnewline
69 &  0.02185 &  0.0437 &  0.9781 \tabularnewline
70 &  0.01844 &  0.03687 &  0.9816 \tabularnewline
71 &  0.01452 &  0.02905 &  0.9855 \tabularnewline
72 &  0.01346 &  0.02693 &  0.9865 \tabularnewline
73 &  0.01253 &  0.02507 &  0.9875 \tabularnewline
74 &  0.009547 &  0.0191 &  0.9905 \tabularnewline
75 &  0.009814 &  0.01963 &  0.9902 \tabularnewline
76 &  0.007768 &  0.01554 &  0.9922 \tabularnewline
77 &  0.007451 &  0.0149 &  0.9925 \tabularnewline
78 &  0.006211 &  0.01242 &  0.9938 \tabularnewline
79 &  0.00503 &  0.01006 &  0.995 \tabularnewline
80 &  0.007221 &  0.01444 &  0.9928 \tabularnewline
81 &  0.007233 &  0.01447 &  0.9928 \tabularnewline
82 &  0.007245 &  0.01449 &  0.9928 \tabularnewline
83 &  0.006972 &  0.01394 &  0.993 \tabularnewline
84 &  0.005588 &  0.01118 &  0.9944 \tabularnewline
85 &  0.005196 &  0.01039 &  0.9948 \tabularnewline
86 &  0.008363 &  0.01673 &  0.9916 \tabularnewline
87 &  0.01647 &  0.03294 &  0.9835 \tabularnewline
88 &  0.01421 &  0.02842 &  0.9858 \tabularnewline
89 &  0.0127 &  0.02539 &  0.9873 \tabularnewline
90 &  0.03522 &  0.07044 &  0.9648 \tabularnewline
91 &  0.05268 &  0.1054 &  0.9473 \tabularnewline
92 &  0.0654 &  0.1308 &  0.9346 \tabularnewline
93 &  0.05944 &  0.1189 &  0.9406 \tabularnewline
94 &  0.0506 &  0.1012 &  0.9494 \tabularnewline
95 &  0.04341 &  0.08682 &  0.9566 \tabularnewline
96 &  0.04239 &  0.08479 &  0.9576 \tabularnewline
97 &  0.03962 &  0.07923 &  0.9604 \tabularnewline
98 &  0.0499 &  0.09979 &  0.9501 \tabularnewline
99 &  0.05138 &  0.1028 &  0.9486 \tabularnewline
100 &  0.04738 &  0.09477 &  0.9526 \tabularnewline
101 &  0.052 &  0.104 &  0.948 \tabularnewline
102 &  0.04449 &  0.08898 &  0.9555 \tabularnewline
103 &  0.05006 &  0.1001 &  0.9499 \tabularnewline
104 &  0.04836 &  0.09671 &  0.9516 \tabularnewline
105 &  0.04358 &  0.08715 &  0.9564 \tabularnewline
106 &  0.04565 &  0.0913 &  0.9544 \tabularnewline
107 &  0.04142 &  0.08283 &  0.9586 \tabularnewline
108 &  0.03639 &  0.07277 &  0.9636 \tabularnewline
109 &  0.02961 &  0.05921 &  0.9704 \tabularnewline
110 &  0.02446 &  0.04892 &  0.9755 \tabularnewline
111 &  0.01946 &  0.03892 &  0.9805 \tabularnewline
112 &  0.01919 &  0.03837 &  0.9808 \tabularnewline
113 &  0.01525 &  0.0305 &  0.9847 \tabularnewline
114 &  0.01517 &  0.03033 &  0.9848 \tabularnewline
115 &  0.01157 &  0.02315 &  0.9884 \tabularnewline
116 &  0.01108 &  0.02216 &  0.9889 \tabularnewline
117 &  0.008576 &  0.01715 &  0.9914 \tabularnewline
118 &  0.007419 &  0.01484 &  0.9926 \tabularnewline
119 &  0.005733 &  0.01147 &  0.9943 \tabularnewline
120 &  0.005314 &  0.01063 &  0.9947 \tabularnewline
121 &  0.004972 &  0.009944 &  0.995 \tabularnewline
122 &  0.004242 &  0.008484 &  0.9958 \tabularnewline
123 &  0.003598 &  0.007197 &  0.9964 \tabularnewline
124 &  0.002627 &  0.005255 &  0.9974 \tabularnewline
125 &  0.001873 &  0.003746 &  0.9981 \tabularnewline
126 &  0.001321 &  0.002642 &  0.9987 \tabularnewline
127 &  0.0009113 &  0.001823 &  0.9991 \tabularnewline
128 &  0.0006551 &  0.00131 &  0.9993 \tabularnewline
129 &  0.0007913 &  0.001583 &  0.9992 \tabularnewline
130 &  0.0005691 &  0.001138 &  0.9994 \tabularnewline
131 &  0.0004039 &  0.0008078 &  0.9996 \tabularnewline
132 &  0.0002992 &  0.0005984 &  0.9997 \tabularnewline
133 &  0.0003066 &  0.0006133 &  0.9997 \tabularnewline
134 &  0.0002763 &  0.0005526 &  0.9997 \tabularnewline
135 &  0.0001794 &  0.0003589 &  0.9998 \tabularnewline
136 &  0.0001569 &  0.0003138 &  0.9998 \tabularnewline
137 &  0.0001887 &  0.0003773 &  0.9998 \tabularnewline
138 &  0.0004452 &  0.0008903 &  0.9996 \tabularnewline
139 &  0.0004355 &  0.000871 &  0.9996 \tabularnewline
140 &  0.000432 &  0.0008639 &  0.9996 \tabularnewline
141 &  0.0003419 &  0.0006839 &  0.9997 \tabularnewline
142 &  0.0002341 &  0.0004683 &  0.9998 \tabularnewline
143 &  0.0002118 &  0.0004236 &  0.9998 \tabularnewline
144 &  0.0001389 &  0.0002778 &  0.9999 \tabularnewline
145 &  0.0001136 &  0.0002272 &  0.9999 \tabularnewline
146 &  0.0001595 &  0.0003189 &  0.9998 \tabularnewline
147 &  0.0001596 &  0.0003192 &  0.9998 \tabularnewline
148 &  0.0001397 &  0.0002795 &  0.9999 \tabularnewline
149 &  0.0002852 &  0.0005704 &  0.9997 \tabularnewline
150 &  0.000194 &  0.000388 &  0.9998 \tabularnewline
151 &  0.000118 &  0.0002359 &  0.9999 \tabularnewline
152 &  8.876e-05 &  0.0001775 &  0.9999 \tabularnewline
153 &  0.0001491 &  0.0002981 &  0.9999 \tabularnewline
154 &  0.0001007 &  0.0002015 &  0.9999 \tabularnewline
155 &  7.19e-05 &  0.0001438 &  0.9999 \tabularnewline
156 &  7.932e-05 &  0.0001586 &  0.9999 \tabularnewline
157 &  0.0002071 &  0.0004142 &  0.9998 \tabularnewline
158 &  0.0001354 &  0.0002708 &  0.9999 \tabularnewline
159 &  0.02281 &  0.04561 &  0.9772 \tabularnewline
160 &  0.01578 &  0.03155 &  0.9842 \tabularnewline
161 &  0.01316 &  0.02631 &  0.9868 \tabularnewline
162 &  0.009816 &  0.01963 &  0.9902 \tabularnewline
163 &  0.006545 &  0.01309 &  0.9935 \tabularnewline
164 &  0.01615 &  0.0323 &  0.9838 \tabularnewline
165 &  0.2355 &  0.471 &  0.7645 \tabularnewline
166 &  0.7583 &  0.4835 &  0.2417 \tabularnewline
167 &  0.7545 &  0.4909 &  0.2455 \tabularnewline
168 &  0.6775 &  0.645 &  0.3225 \tabularnewline
169 &  0.8917 &  0.2167 &  0.1083 \tabularnewline
170 &  0.8778 &  0.2444 &  0.1222 \tabularnewline
171 &  0.9663 &  0.06731 &  0.03366 \tabularnewline
172 &  0.9797 &  0.04052 &  0.02026 \tabularnewline
173 &  0.9668 &  0.06646 &  0.03323 \tabularnewline
174 &  0.9585 &  0.08309 &  0.04155 \tabularnewline
175 &  0.9483 &  0.1033 &  0.05166 \tabularnewline
176 &  0.9188 &  0.1624 &  0.08121 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286263&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]19[/C][C] 5.474e-47[/C][C] 1.095e-46[/C][C] 1[/C][/ROW]
[ROW][C]20[/C][C] 1.497e-60[/C][C] 2.994e-60[/C][C] 1[/C][/ROW]
[ROW][C]21[/C][C] 1.711e-75[/C][C] 3.423e-75[/C][C] 1[/C][/ROW]
[ROW][C]22[/C][C] 3.891e-89[/C][C] 7.782e-89[/C][C] 1[/C][/ROW]
[ROW][C]23[/C][C] 5.911e-104[/C][C] 1.182e-103[/C][C] 1[/C][/ROW]
[ROW][C]24[/C][C] 2.228e-122[/C][C] 4.456e-122[/C][C] 1[/C][/ROW]
[ROW][C]25[/C][C] 4.953e-133[/C][C] 9.905e-133[/C][C] 1[/C][/ROW]
[ROW][C]26[/C][C] 2.309e-149[/C][C] 4.618e-149[/C][C] 1[/C][/ROW]
[ROW][C]27[/C][C] 2.651e-164[/C][C] 5.301e-164[/C][C] 1[/C][/ROW]
[ROW][C]28[/C][C] 1.778e-176[/C][C] 3.556e-176[/C][C] 1[/C][/ROW]
[ROW][C]29[/C][C] 5.119e-190[/C][C] 1.024e-189[/C][C] 1[/C][/ROW]
[ROW][C]30[/C][C] 1.794e-205[/C][C] 3.589e-205[/C][C] 1[/C][/ROW]
[ROW][C]31[/C][C] 3.258e-05[/C][C] 6.517e-05[/C][C] 1[/C][/ROW]
[ROW][C]32[/C][C] 1.411e-05[/C][C] 2.821e-05[/C][C] 1[/C][/ROW]
[ROW][C]33[/C][C] 4.9e-06[/C][C] 9.8e-06[/C][C] 1[/C][/ROW]
[ROW][C]34[/C][C] 1.847e-06[/C][C] 3.693e-06[/C][C] 1[/C][/ROW]
[ROW][C]35[/C][C] 6.218e-07[/C][C] 1.244e-06[/C][C] 1[/C][/ROW]
[ROW][C]36[/C][C] 1.981e-07[/C][C] 3.961e-07[/C][C] 1[/C][/ROW]
[ROW][C]37[/C][C] 2.474e-06[/C][C] 4.949e-06[/C][C] 1[/C][/ROW]
[ROW][C]38[/C][C] 1.803e-06[/C][C] 3.606e-06[/C][C] 1[/C][/ROW]
[ROW][C]39[/C][C] 3.244e-05[/C][C] 6.487e-05[/C][C] 1[/C][/ROW]
[ROW][C]40[/C][C] 4.656e-05[/C][C] 9.312e-05[/C][C] 1[/C][/ROW]
[ROW][C]41[/C][C] 5.436e-05[/C][C] 0.0001087[/C][C] 0.9999[/C][/ROW]
[ROW][C]42[/C][C] 3.069e-05[/C][C] 6.137e-05[/C][C] 1[/C][/ROW]
[ROW][C]43[/C][C] 1.736e-05[/C][C] 3.471e-05[/C][C] 1[/C][/ROW]
[ROW][C]44[/C][C] 1.062e-05[/C][C] 2.124e-05[/C][C] 1[/C][/ROW]
[ROW][C]45[/C][C] 6.183e-06[/C][C] 1.237e-05[/C][C] 1[/C][/ROW]
[ROW][C]46[/C][C] 2.999e-06[/C][C] 5.999e-06[/C][C] 1[/C][/ROW]
[ROW][C]47[/C][C] 1.647e-06[/C][C] 3.295e-06[/C][C] 1[/C][/ROW]
[ROW][C]48[/C][C] 1.035e-06[/C][C] 2.07e-06[/C][C] 1[/C][/ROW]
[ROW][C]49[/C][C] 0.0007077[/C][C] 0.001415[/C][C] 0.9993[/C][/ROW]
[ROW][C]50[/C][C] 0.00116[/C][C] 0.002321[/C][C] 0.9988[/C][/ROW]
[ROW][C]51[/C][C] 0.001095[/C][C] 0.002189[/C][C] 0.9989[/C][/ROW]
[ROW][C]52[/C][C] 0.001046[/C][C] 0.002093[/C][C] 0.999[/C][/ROW]
[ROW][C]53[/C][C] 0.001225[/C][C] 0.002449[/C][C] 0.9988[/C][/ROW]
[ROW][C]54[/C][C] 0.0019[/C][C] 0.0038[/C][C] 0.9981[/C][/ROW]
[ROW][C]55[/C][C] 0.001258[/C][C] 0.002515[/C][C] 0.9987[/C][/ROW]
[ROW][C]56[/C][C] 0.001026[/C][C] 0.002052[/C][C] 0.999[/C][/ROW]
[ROW][C]57[/C][C] 0.0006508[/C][C] 0.001302[/C][C] 0.9993[/C][/ROW]
[ROW][C]58[/C][C] 0.0004961[/C][C] 0.0009921[/C][C] 0.9995[/C][/ROW]
[ROW][C]59[/C][C] 0.000396[/C][C] 0.0007921[/C][C] 0.9996[/C][/ROW]
[ROW][C]60[/C][C] 0.0009069[/C][C] 0.001814[/C][C] 0.9991[/C][/ROW]
[ROW][C]61[/C][C] 0.01546[/C][C] 0.03092[/C][C] 0.9845[/C][/ROW]
[ROW][C]62[/C][C] 0.01774[/C][C] 0.03548[/C][C] 0.9823[/C][/ROW]
[ROW][C]63[/C][C] 0.02291[/C][C] 0.04581[/C][C] 0.9771[/C][/ROW]
[ROW][C]64[/C][C] 0.02802[/C][C] 0.05604[/C][C] 0.972[/C][/ROW]
[ROW][C]65[/C][C] 0.02971[/C][C] 0.05941[/C][C] 0.9703[/C][/ROW]
[ROW][C]66[/C][C] 0.04299[/C][C] 0.08598[/C][C] 0.957[/C][/ROW]
[ROW][C]67[/C][C] 0.03419[/C][C] 0.06837[/C][C] 0.9658[/C][/ROW]
[ROW][C]68[/C][C] 0.02682[/C][C] 0.05364[/C][C] 0.9732[/C][/ROW]
[ROW][C]69[/C][C] 0.02185[/C][C] 0.0437[/C][C] 0.9781[/C][/ROW]
[ROW][C]70[/C][C] 0.01844[/C][C] 0.03687[/C][C] 0.9816[/C][/ROW]
[ROW][C]71[/C][C] 0.01452[/C][C] 0.02905[/C][C] 0.9855[/C][/ROW]
[ROW][C]72[/C][C] 0.01346[/C][C] 0.02693[/C][C] 0.9865[/C][/ROW]
[ROW][C]73[/C][C] 0.01253[/C][C] 0.02507[/C][C] 0.9875[/C][/ROW]
[ROW][C]74[/C][C] 0.009547[/C][C] 0.0191[/C][C] 0.9905[/C][/ROW]
[ROW][C]75[/C][C] 0.009814[/C][C] 0.01963[/C][C] 0.9902[/C][/ROW]
[ROW][C]76[/C][C] 0.007768[/C][C] 0.01554[/C][C] 0.9922[/C][/ROW]
[ROW][C]77[/C][C] 0.007451[/C][C] 0.0149[/C][C] 0.9925[/C][/ROW]
[ROW][C]78[/C][C] 0.006211[/C][C] 0.01242[/C][C] 0.9938[/C][/ROW]
[ROW][C]79[/C][C] 0.00503[/C][C] 0.01006[/C][C] 0.995[/C][/ROW]
[ROW][C]80[/C][C] 0.007221[/C][C] 0.01444[/C][C] 0.9928[/C][/ROW]
[ROW][C]81[/C][C] 0.007233[/C][C] 0.01447[/C][C] 0.9928[/C][/ROW]
[ROW][C]82[/C][C] 0.007245[/C][C] 0.01449[/C][C] 0.9928[/C][/ROW]
[ROW][C]83[/C][C] 0.006972[/C][C] 0.01394[/C][C] 0.993[/C][/ROW]
[ROW][C]84[/C][C] 0.005588[/C][C] 0.01118[/C][C] 0.9944[/C][/ROW]
[ROW][C]85[/C][C] 0.005196[/C][C] 0.01039[/C][C] 0.9948[/C][/ROW]
[ROW][C]86[/C][C] 0.008363[/C][C] 0.01673[/C][C] 0.9916[/C][/ROW]
[ROW][C]87[/C][C] 0.01647[/C][C] 0.03294[/C][C] 0.9835[/C][/ROW]
[ROW][C]88[/C][C] 0.01421[/C][C] 0.02842[/C][C] 0.9858[/C][/ROW]
[ROW][C]89[/C][C] 0.0127[/C][C] 0.02539[/C][C] 0.9873[/C][/ROW]
[ROW][C]90[/C][C] 0.03522[/C][C] 0.07044[/C][C] 0.9648[/C][/ROW]
[ROW][C]91[/C][C] 0.05268[/C][C] 0.1054[/C][C] 0.9473[/C][/ROW]
[ROW][C]92[/C][C] 0.0654[/C][C] 0.1308[/C][C] 0.9346[/C][/ROW]
[ROW][C]93[/C][C] 0.05944[/C][C] 0.1189[/C][C] 0.9406[/C][/ROW]
[ROW][C]94[/C][C] 0.0506[/C][C] 0.1012[/C][C] 0.9494[/C][/ROW]
[ROW][C]95[/C][C] 0.04341[/C][C] 0.08682[/C][C] 0.9566[/C][/ROW]
[ROW][C]96[/C][C] 0.04239[/C][C] 0.08479[/C][C] 0.9576[/C][/ROW]
[ROW][C]97[/C][C] 0.03962[/C][C] 0.07923[/C][C] 0.9604[/C][/ROW]
[ROW][C]98[/C][C] 0.0499[/C][C] 0.09979[/C][C] 0.9501[/C][/ROW]
[ROW][C]99[/C][C] 0.05138[/C][C] 0.1028[/C][C] 0.9486[/C][/ROW]
[ROW][C]100[/C][C] 0.04738[/C][C] 0.09477[/C][C] 0.9526[/C][/ROW]
[ROW][C]101[/C][C] 0.052[/C][C] 0.104[/C][C] 0.948[/C][/ROW]
[ROW][C]102[/C][C] 0.04449[/C][C] 0.08898[/C][C] 0.9555[/C][/ROW]
[ROW][C]103[/C][C] 0.05006[/C][C] 0.1001[/C][C] 0.9499[/C][/ROW]
[ROW][C]104[/C][C] 0.04836[/C][C] 0.09671[/C][C] 0.9516[/C][/ROW]
[ROW][C]105[/C][C] 0.04358[/C][C] 0.08715[/C][C] 0.9564[/C][/ROW]
[ROW][C]106[/C][C] 0.04565[/C][C] 0.0913[/C][C] 0.9544[/C][/ROW]
[ROW][C]107[/C][C] 0.04142[/C][C] 0.08283[/C][C] 0.9586[/C][/ROW]
[ROW][C]108[/C][C] 0.03639[/C][C] 0.07277[/C][C] 0.9636[/C][/ROW]
[ROW][C]109[/C][C] 0.02961[/C][C] 0.05921[/C][C] 0.9704[/C][/ROW]
[ROW][C]110[/C][C] 0.02446[/C][C] 0.04892[/C][C] 0.9755[/C][/ROW]
[ROW][C]111[/C][C] 0.01946[/C][C] 0.03892[/C][C] 0.9805[/C][/ROW]
[ROW][C]112[/C][C] 0.01919[/C][C] 0.03837[/C][C] 0.9808[/C][/ROW]
[ROW][C]113[/C][C] 0.01525[/C][C] 0.0305[/C][C] 0.9847[/C][/ROW]
[ROW][C]114[/C][C] 0.01517[/C][C] 0.03033[/C][C] 0.9848[/C][/ROW]
[ROW][C]115[/C][C] 0.01157[/C][C] 0.02315[/C][C] 0.9884[/C][/ROW]
[ROW][C]116[/C][C] 0.01108[/C][C] 0.02216[/C][C] 0.9889[/C][/ROW]
[ROW][C]117[/C][C] 0.008576[/C][C] 0.01715[/C][C] 0.9914[/C][/ROW]
[ROW][C]118[/C][C] 0.007419[/C][C] 0.01484[/C][C] 0.9926[/C][/ROW]
[ROW][C]119[/C][C] 0.005733[/C][C] 0.01147[/C][C] 0.9943[/C][/ROW]
[ROW][C]120[/C][C] 0.005314[/C][C] 0.01063[/C][C] 0.9947[/C][/ROW]
[ROW][C]121[/C][C] 0.004972[/C][C] 0.009944[/C][C] 0.995[/C][/ROW]
[ROW][C]122[/C][C] 0.004242[/C][C] 0.008484[/C][C] 0.9958[/C][/ROW]
[ROW][C]123[/C][C] 0.003598[/C][C] 0.007197[/C][C] 0.9964[/C][/ROW]
[ROW][C]124[/C][C] 0.002627[/C][C] 0.005255[/C][C] 0.9974[/C][/ROW]
[ROW][C]125[/C][C] 0.001873[/C][C] 0.003746[/C][C] 0.9981[/C][/ROW]
[ROW][C]126[/C][C] 0.001321[/C][C] 0.002642[/C][C] 0.9987[/C][/ROW]
[ROW][C]127[/C][C] 0.0009113[/C][C] 0.001823[/C][C] 0.9991[/C][/ROW]
[ROW][C]128[/C][C] 0.0006551[/C][C] 0.00131[/C][C] 0.9993[/C][/ROW]
[ROW][C]129[/C][C] 0.0007913[/C][C] 0.001583[/C][C] 0.9992[/C][/ROW]
[ROW][C]130[/C][C] 0.0005691[/C][C] 0.001138[/C][C] 0.9994[/C][/ROW]
[ROW][C]131[/C][C] 0.0004039[/C][C] 0.0008078[/C][C] 0.9996[/C][/ROW]
[ROW][C]132[/C][C] 0.0002992[/C][C] 0.0005984[/C][C] 0.9997[/C][/ROW]
[ROW][C]133[/C][C] 0.0003066[/C][C] 0.0006133[/C][C] 0.9997[/C][/ROW]
[ROW][C]134[/C][C] 0.0002763[/C][C] 0.0005526[/C][C] 0.9997[/C][/ROW]
[ROW][C]135[/C][C] 0.0001794[/C][C] 0.0003589[/C][C] 0.9998[/C][/ROW]
[ROW][C]136[/C][C] 0.0001569[/C][C] 0.0003138[/C][C] 0.9998[/C][/ROW]
[ROW][C]137[/C][C] 0.0001887[/C][C] 0.0003773[/C][C] 0.9998[/C][/ROW]
[ROW][C]138[/C][C] 0.0004452[/C][C] 0.0008903[/C][C] 0.9996[/C][/ROW]
[ROW][C]139[/C][C] 0.0004355[/C][C] 0.000871[/C][C] 0.9996[/C][/ROW]
[ROW][C]140[/C][C] 0.000432[/C][C] 0.0008639[/C][C] 0.9996[/C][/ROW]
[ROW][C]141[/C][C] 0.0003419[/C][C] 0.0006839[/C][C] 0.9997[/C][/ROW]
[ROW][C]142[/C][C] 0.0002341[/C][C] 0.0004683[/C][C] 0.9998[/C][/ROW]
[ROW][C]143[/C][C] 0.0002118[/C][C] 0.0004236[/C][C] 0.9998[/C][/ROW]
[ROW][C]144[/C][C] 0.0001389[/C][C] 0.0002778[/C][C] 0.9999[/C][/ROW]
[ROW][C]145[/C][C] 0.0001136[/C][C] 0.0002272[/C][C] 0.9999[/C][/ROW]
[ROW][C]146[/C][C] 0.0001595[/C][C] 0.0003189[/C][C] 0.9998[/C][/ROW]
[ROW][C]147[/C][C] 0.0001596[/C][C] 0.0003192[/C][C] 0.9998[/C][/ROW]
[ROW][C]148[/C][C] 0.0001397[/C][C] 0.0002795[/C][C] 0.9999[/C][/ROW]
[ROW][C]149[/C][C] 0.0002852[/C][C] 0.0005704[/C][C] 0.9997[/C][/ROW]
[ROW][C]150[/C][C] 0.000194[/C][C] 0.000388[/C][C] 0.9998[/C][/ROW]
[ROW][C]151[/C][C] 0.000118[/C][C] 0.0002359[/C][C] 0.9999[/C][/ROW]
[ROW][C]152[/C][C] 8.876e-05[/C][C] 0.0001775[/C][C] 0.9999[/C][/ROW]
[ROW][C]153[/C][C] 0.0001491[/C][C] 0.0002981[/C][C] 0.9999[/C][/ROW]
[ROW][C]154[/C][C] 0.0001007[/C][C] 0.0002015[/C][C] 0.9999[/C][/ROW]
[ROW][C]155[/C][C] 7.19e-05[/C][C] 0.0001438[/C][C] 0.9999[/C][/ROW]
[ROW][C]156[/C][C] 7.932e-05[/C][C] 0.0001586[/C][C] 0.9999[/C][/ROW]
[ROW][C]157[/C][C] 0.0002071[/C][C] 0.0004142[/C][C] 0.9998[/C][/ROW]
[ROW][C]158[/C][C] 0.0001354[/C][C] 0.0002708[/C][C] 0.9999[/C][/ROW]
[ROW][C]159[/C][C] 0.02281[/C][C] 0.04561[/C][C] 0.9772[/C][/ROW]
[ROW][C]160[/C][C] 0.01578[/C][C] 0.03155[/C][C] 0.9842[/C][/ROW]
[ROW][C]161[/C][C] 0.01316[/C][C] 0.02631[/C][C] 0.9868[/C][/ROW]
[ROW][C]162[/C][C] 0.009816[/C][C] 0.01963[/C][C] 0.9902[/C][/ROW]
[ROW][C]163[/C][C] 0.006545[/C][C] 0.01309[/C][C] 0.9935[/C][/ROW]
[ROW][C]164[/C][C] 0.01615[/C][C] 0.0323[/C][C] 0.9838[/C][/ROW]
[ROW][C]165[/C][C] 0.2355[/C][C] 0.471[/C][C] 0.7645[/C][/ROW]
[ROW][C]166[/C][C] 0.7583[/C][C] 0.4835[/C][C] 0.2417[/C][/ROW]
[ROW][C]167[/C][C] 0.7545[/C][C] 0.4909[/C][C] 0.2455[/C][/ROW]
[ROW][C]168[/C][C] 0.6775[/C][C] 0.645[/C][C] 0.3225[/C][/ROW]
[ROW][C]169[/C][C] 0.8917[/C][C] 0.2167[/C][C] 0.1083[/C][/ROW]
[ROW][C]170[/C][C] 0.8778[/C][C] 0.2444[/C][C] 0.1222[/C][/ROW]
[ROW][C]171[/C][C] 0.9663[/C][C] 0.06731[/C][C] 0.03366[/C][/ROW]
[ROW][C]172[/C][C] 0.9797[/C][C] 0.04052[/C][C] 0.02026[/C][/ROW]
[ROW][C]173[/C][C] 0.9668[/C][C] 0.06646[/C][C] 0.03323[/C][/ROW]
[ROW][C]174[/C][C] 0.9585[/C][C] 0.08309[/C][C] 0.04155[/C][/ROW]
[ROW][C]175[/C][C] 0.9483[/C][C] 0.1033[/C][C] 0.05166[/C][/ROW]
[ROW][C]176[/C][C] 0.9188[/C][C] 0.1624[/C][C] 0.08121[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286263&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286263&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
19 5.474e-47 1.095e-46 1
20 1.497e-60 2.994e-60 1
21 1.711e-75 3.423e-75 1
22 3.891e-89 7.782e-89 1
23 5.911e-104 1.182e-103 1
24 2.228e-122 4.456e-122 1
25 4.953e-133 9.905e-133 1
26 2.309e-149 4.618e-149 1
27 2.651e-164 5.301e-164 1
28 1.778e-176 3.556e-176 1
29 5.119e-190 1.024e-189 1
30 1.794e-205 3.589e-205 1
31 3.258e-05 6.517e-05 1
32 1.411e-05 2.821e-05 1
33 4.9e-06 9.8e-06 1
34 1.847e-06 3.693e-06 1
35 6.218e-07 1.244e-06 1
36 1.981e-07 3.961e-07 1
37 2.474e-06 4.949e-06 1
38 1.803e-06 3.606e-06 1
39 3.244e-05 6.487e-05 1
40 4.656e-05 9.312e-05 1
41 5.436e-05 0.0001087 0.9999
42 3.069e-05 6.137e-05 1
43 1.736e-05 3.471e-05 1
44 1.062e-05 2.124e-05 1
45 6.183e-06 1.237e-05 1
46 2.999e-06 5.999e-06 1
47 1.647e-06 3.295e-06 1
48 1.035e-06 2.07e-06 1
49 0.0007077 0.001415 0.9993
50 0.00116 0.002321 0.9988
51 0.001095 0.002189 0.9989
52 0.001046 0.002093 0.999
53 0.001225 0.002449 0.9988
54 0.0019 0.0038 0.9981
55 0.001258 0.002515 0.9987
56 0.001026 0.002052 0.999
57 0.0006508 0.001302 0.9993
58 0.0004961 0.0009921 0.9995
59 0.000396 0.0007921 0.9996
60 0.0009069 0.001814 0.9991
61 0.01546 0.03092 0.9845
62 0.01774 0.03548 0.9823
63 0.02291 0.04581 0.9771
64 0.02802 0.05604 0.972
65 0.02971 0.05941 0.9703
66 0.04299 0.08598 0.957
67 0.03419 0.06837 0.9658
68 0.02682 0.05364 0.9732
69 0.02185 0.0437 0.9781
70 0.01844 0.03687 0.9816
71 0.01452 0.02905 0.9855
72 0.01346 0.02693 0.9865
73 0.01253 0.02507 0.9875
74 0.009547 0.0191 0.9905
75 0.009814 0.01963 0.9902
76 0.007768 0.01554 0.9922
77 0.007451 0.0149 0.9925
78 0.006211 0.01242 0.9938
79 0.00503 0.01006 0.995
80 0.007221 0.01444 0.9928
81 0.007233 0.01447 0.9928
82 0.007245 0.01449 0.9928
83 0.006972 0.01394 0.993
84 0.005588 0.01118 0.9944
85 0.005196 0.01039 0.9948
86 0.008363 0.01673 0.9916
87 0.01647 0.03294 0.9835
88 0.01421 0.02842 0.9858
89 0.0127 0.02539 0.9873
90 0.03522 0.07044 0.9648
91 0.05268 0.1054 0.9473
92 0.0654 0.1308 0.9346
93 0.05944 0.1189 0.9406
94 0.0506 0.1012 0.9494
95 0.04341 0.08682 0.9566
96 0.04239 0.08479 0.9576
97 0.03962 0.07923 0.9604
98 0.0499 0.09979 0.9501
99 0.05138 0.1028 0.9486
100 0.04738 0.09477 0.9526
101 0.052 0.104 0.948
102 0.04449 0.08898 0.9555
103 0.05006 0.1001 0.9499
104 0.04836 0.09671 0.9516
105 0.04358 0.08715 0.9564
106 0.04565 0.0913 0.9544
107 0.04142 0.08283 0.9586
108 0.03639 0.07277 0.9636
109 0.02961 0.05921 0.9704
110 0.02446 0.04892 0.9755
111 0.01946 0.03892 0.9805
112 0.01919 0.03837 0.9808
113 0.01525 0.0305 0.9847
114 0.01517 0.03033 0.9848
115 0.01157 0.02315 0.9884
116 0.01108 0.02216 0.9889
117 0.008576 0.01715 0.9914
118 0.007419 0.01484 0.9926
119 0.005733 0.01147 0.9943
120 0.005314 0.01063 0.9947
121 0.004972 0.009944 0.995
122 0.004242 0.008484 0.9958
123 0.003598 0.007197 0.9964
124 0.002627 0.005255 0.9974
125 0.001873 0.003746 0.9981
126 0.001321 0.002642 0.9987
127 0.0009113 0.001823 0.9991
128 0.0006551 0.00131 0.9993
129 0.0007913 0.001583 0.9992
130 0.0005691 0.001138 0.9994
131 0.0004039 0.0008078 0.9996
132 0.0002992 0.0005984 0.9997
133 0.0003066 0.0006133 0.9997
134 0.0002763 0.0005526 0.9997
135 0.0001794 0.0003589 0.9998
136 0.0001569 0.0003138 0.9998
137 0.0001887 0.0003773 0.9998
138 0.0004452 0.0008903 0.9996
139 0.0004355 0.000871 0.9996
140 0.000432 0.0008639 0.9996
141 0.0003419 0.0006839 0.9997
142 0.0002341 0.0004683 0.9998
143 0.0002118 0.0004236 0.9998
144 0.0001389 0.0002778 0.9999
145 0.0001136 0.0002272 0.9999
146 0.0001595 0.0003189 0.9998
147 0.0001596 0.0003192 0.9998
148 0.0001397 0.0002795 0.9999
149 0.0002852 0.0005704 0.9997
150 0.000194 0.000388 0.9998
151 0.000118 0.0002359 0.9999
152 8.876e-05 0.0001775 0.9999
153 0.0001491 0.0002981 0.9999
154 0.0001007 0.0002015 0.9999
155 7.19e-05 0.0001438 0.9999
156 7.932e-05 0.0001586 0.9999
157 0.0002071 0.0004142 0.9998
158 0.0001354 0.0002708 0.9999
159 0.02281 0.04561 0.9772
160 0.01578 0.03155 0.9842
161 0.01316 0.02631 0.9868
162 0.009816 0.01963 0.9902
163 0.006545 0.01309 0.9935
164 0.01615 0.0323 0.9838
165 0.2355 0.471 0.7645
166 0.7583 0.4835 0.2417
167 0.7545 0.4909 0.2455
168 0.6775 0.645 0.3225
169 0.8917 0.2167 0.1083
170 0.8778 0.2444 0.1222
171 0.9663 0.06731 0.03366
172 0.9797 0.04052 0.02026
173 0.9668 0.06646 0.03323
174 0.9585 0.08309 0.04155
175 0.9483 0.1033 0.05166
176 0.9188 0.1624 0.08121






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level80 0.5063NOK
5% type I error level1220.772152NOK
10% type I error level1430.905063NOK

\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 & 80 &  0.5063 & NOK \tabularnewline
5% type I error level & 122 & 0.772152 & NOK \tabularnewline
10% type I error level & 143 & 0.905063 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=286263&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]80[/C][C] 0.5063[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]122[/C][C]0.772152[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]143[/C][C]0.905063[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=286263&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=286263&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level80 0.5063NOK
5% type I error level1220.772152NOK
10% type I error level1430.905063NOK


Figures (Output of Computation)

Figure 1
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 2
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 3
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 4
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 5
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 6
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 7
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 8
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 9
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 10
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ; par4 = ; par5 = ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
mywarning <- ''
par1 <- as.numeric(par1)
if(is.na(par1)) {
par1 <- 1
mywarning = 'Warning: you did not specify the column number of the endogenous series! The first column was selected by default.'
}
if (par4=='') par4 <- 0
par4 <- as.numeric(par4)
if (par5=='') par5 <- 0
par5 <- as.numeric(par5)
x <- na.omit(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'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'Seasonal Differences (s=12)'){
(n <- n - 12)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+12,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'First and Seasonal Differences (s=12)'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
(n <- n - 12)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+12,j] - x[i,j]
}
}
x <- x2
}
if(par4 > 0) {
x2 <- array(0, dim=c(n-par4,par4), dimnames=list(1:(n-par4), paste(colnames(x)[par1],'(t-',1:par4,')',sep='')))
for (i in 1:(n-par4)) {
for (j in 1:par4) {
x2[i,j] <- x[i+par4-j,par1]
}
}
x <- cbind(x[(par4+1):n,], x2)
n <- n - par4
}
if(par5 > 0) {
x2 <- array(0, dim=c(n-par5*12,par5), dimnames=list(1:(n-par5*12), paste(colnames(x)[par1],'(t-',1:par5,'s)',sep='')))
for (i in 1:(n-par5*12)) {
for (j in 1:par5) {
x2[i,j] <- x[i+par5*12-j*12,par1]
}
}
x <- cbind(x[(par5*12+1):n,], x2)
n <- n - par5*12
}
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[n,]))
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
(k <- length(x[n,]))
head(x)
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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, mywarning)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,formatC(signif(mysum$coefficients[i,1],5),format='g',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,2],5),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,3],4),format='e',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4],4),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4]/2,4),format='g',flag=' '))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a,formatC(signif(sqrt(mysum$r.squared),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$adj.r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a,formatC(signif(mysum$fstatistic[1],6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$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$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a,formatC(signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6),format='g',flag=' '))
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,formatC(signif(mysum$sigma,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a,formatC(signif(sum(myerror*myerror),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
if(n < 200) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,formatC(signif(x[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(x[i]-mysum$resid[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$resid[i],6),format='g',flag=' '))
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,formatC(signif(gqarr[mypoint-kp3+1,1],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,2],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,3],6),format='g',flag=' '))
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,formatC(signif(numsignificant1/numgqtests,6),format='g',flag=' '))
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')
}
}