Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSat, 07 Dec 2013 07:58:23 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/07/t1386421175qsng8eodjyfemyn.htm/, Retrieved Fri, 29 Mar 2024 13:28:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231380, Retrieved Fri, 29 Mar 2024 13:28:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact94
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [ws10 3] [2013-12-07 12:58:23] [d36997adcafcba0a4d18dd87f1a174ea] [Current]
Feedback Forum

Post a new message
Dataseries X:
1 119.992 157.302 74.997 0.00784 0.00007 0.0037 0.00554 0.04374 0.426 0.02971
1 122.4 148.65 113.819 0.00968 0.00008 0.00465 0.00696 0.06134 0.626 0.04368
1 116.682 131.111 111.555 0.0105 0.00009 0.00544 0.00781 0.05233 0.482 0.0359
1 116.676 137.871 111.366 0.00997 0.00009 0.00502 0.00698 0.05492 0.517 0.03772
1 116.014 141.781 110.655 0.01284 0.00011 0.00655 0.00908 0.06425 0.584 0.04465
1 120.552 131.162 113.787 0.00968 0.00008 0.00463 0.0075 0.04701 0.456 0.03243
1 120.267 137.244 114.82 0.00333 0.00003 0.00155 0.00202 0.01608 0.14 0.01351
1 107.332 113.84 104.315 0.0029 0.00003 0.00144 0.00182 0.01567 0.134 0.01256
1 95.73 132.068 91.754 0.00551 0.00006 0.00293 0.00332 0.02093 0.191 0.01717
1 95.056 120.103 91.226 0.00532 0.00006 0.00268 0.00332 0.02838 0.255 0.02444
1 88.333 112.24 84.072 0.00505 0.00006 0.00254 0.0033 0.02143 0.197 0.01892
1 91.904 115.871 86.292 0.0054 0.00006 0.00281 0.00336 0.02752 0.249 0.02214
1 136.926 159.866 131.276 0.00293 0.00002 0.00118 0.00153 0.01259 0.112 0.0114
1 139.173 179.139 76.556 0.0039 0.00003 0.00165 0.00208 0.01642 0.154 0.01797
1 152.845 163.305 75.836 0.00294 0.00002 0.00121 0.00149 0.01828 0.158 0.01246
1 142.167 217.455 83.159 0.00369 0.00003 0.00157 0.00203 0.01503 0.126 0.01359
1 144.188 349.259 82.764 0.00544 0.00004 0.00211 0.00292 0.02047 0.192 0.02074
1 168.778 232.181 75.603 0.00718 0.00004 0.00284 0.00387 0.03327 0.348 0.0343
1 153.046 175.829 68.623 0.00742 0.00005 0.00364 0.00432 0.05517 0.542 0.05767
1 156.405 189.398 142.822 0.00768 0.00005 0.00372 0.00399 0.03995 0.348 0.0431
1 153.848 165.738 65.782 0.0084 0.00005 0.00428 0.0045 0.0381 0.328 0.04055
1 153.88 172.86 78.128 0.0048 0.00003 0.00232 0.00267 0.04137 0.37 0.04525
1 167.93 193.221 79.068 0.00442 0.00003 0.0022 0.00247 0.04351 0.377 0.04246
1 173.917 192.735 86.18 0.00476 0.00003 0.00221 0.00258 0.04192 0.364 0.03772
1 163.656 200.841 76.779 0.00742 0.00005 0.0038 0.0039 0.01659 0.164 0.01497
1 104.4 206.002 77.968 0.00633 0.00006 0.00316 0.00375 0.03767 0.381 0.0378
1 171.041 208.313 75.501 0.00455 0.00003 0.0025 0.00234 0.01966 0.186 0.01872
1 146.845 208.701 81.737 0.00496 0.00003 0.0025 0.00275 0.01919 0.198 0.01826
1 155.358 227.383 80.055 0.0031 0.00002 0.00159 0.00176 0.01718 0.161 0.01661
1 162.568 198.346 77.63 0.00502 0.00003 0.0028 0.00253 0.01791 0.168 0.01799
0 197.076 206.896 192.055 0.00289 0.00001 0.00166 0.00168 0.01098 0.097 0.00802
0 199.228 209.512 192.091 0.00241 0.00001 0.00134 0.00138 0.01015 0.089 0.00762
0 198.383 215.203 193.104 0.00212 0.00001 0.00113 0.00135 0.01263 0.111 0.00951
0 202.266 211.604 197.079 0.0018 0.000009 0.00093 0.00107 0.00954 0.085 0.00719
0 203.184 211.526 196.16 0.00178 0.000009 0.00094 0.00106 0.00958 0.085 0.00726
0 201.464 210.565 195.708 0.00198 0.00001 0.00105 0.00115 0.01194 0.107 0.00957
1 177.876 192.921 168.013 0.00411 0.00002 0.00233 0.00241 0.02126 0.189 0.01612
1 176.17 185.604 163.564 0.00369 0.00002 0.00205 0.00218 0.01851 0.168 0.01491
1 180.198 201.249 175.456 0.00284 0.00002 0.00153 0.00166 0.01444 0.131 0.0119
1 187.733 202.324 173.015 0.00316 0.00002 0.00168 0.00182 0.01663 0.151 0.01366
1 186.163 197.724 177.584 0.00298 0.00002 0.00165 0.00175 0.01495 0.135 0.01233
1 184.055 196.537 166.977 0.00258 0.00001 0.00134 0.00147 0.01463 0.132 0.01234
0 237.226 247.326 225.227 0.00298 0.00001 0.00169 0.00182 0.01752 0.164 0.01133
0 241.404 248.834 232.483 0.00281 0.00001 0.00157 0.00173 0.0176 0.154 0.01251
0 243.439 250.912 232.435 0.0021 0.000009 0.00109 0.00137 0.01419 0.126 0.01033
0 242.852 255.034 227.911 0.00225 0.000009 0.00117 0.00139 0.01494 0.134 0.01014
0 245.51 262.09 231.848 0.00235 0.00001 0.00127 0.00148 0.01608 0.141 0.01149
0 252.455 261.487 182.786 0.00185 0.000007 0.00092 0.00113 0.01152 0.103 0.0086
0 122.188 128.611 115.765 0.00524 0.00004 0.00169 0.00203 0.01613 0.143 0.01433
0 122.964 130.049 114.676 0.00428 0.00003 0.00124 0.00155 0.01681 0.154 0.014
0 124.445 135.069 117.495 0.00431 0.00003 0.00141 0.00167 0.02184 0.197 0.01685
0 126.344 134.231 112.773 0.00448 0.00004 0.00131 0.00169 0.02033 0.185 0.01614
0 128.001 138.052 122.08 0.00436 0.00003 0.00137 0.00166 0.02297 0.21 0.01677
0 129.336 139.867 118.604 0.0049 0.00004 0.00165 0.00183 0.02498 0.228 0.01947
1 108.807 134.656 102.874 0.00761 0.00007 0.00349 0.00486 0.02719 0.255 0.02067
1 109.86 126.358 104.437 0.00874 0.00008 0.00398 0.00539 0.03209 0.307 0.02454
1 110.417 131.067 103.37 0.00784 0.00007 0.00352 0.00514 0.03715 0.334 0.02802
1 117.274 129.916 110.402 0.00752 0.00006 0.00299 0.00469 0.02293 0.221 0.01948
1 116.879 131.897 108.153 0.00788 0.00007 0.00334 0.00493 0.02645 0.265 0.02137
1 114.847 271.314 104.68 0.00867 0.00008 0.00373 0.0052 0.03225 0.35 0.02519
0 209.144 237.494 109.379 0.00282 0.00001 0.00147 0.00152 0.01861 0.17 0.01382
0 223.365 238.987 98.664 0.00264 0.00001 0.00154 0.00151 0.01906 0.165 0.0134
0 222.236 231.345 205.495 0.00266 0.00001 0.00152 0.00144 0.01643 0.145 0.012
0 228.832 234.619 223.634 0.00296 0.00001 0.00175 0.00155 0.01644 0.145 0.01179
0 229.401 252.221 221.156 0.00205 0.000009 0.00114 0.00113 0.01457 0.129 0.01016
0 228.969 239.541 113.201 0.00238 0.00001 0.00136 0.0014 0.01745 0.154 0.01234
1 140.341 159.774 67.021 0.00817 0.00006 0.0043 0.0044 0.03198 0.313 0.02428
1 136.969 166.607 66.004 0.00923 0.00007 0.00507 0.00463 0.03111 0.308 0.02603
1 143.533 162.215 65.809 0.01101 0.00008 0.00647 0.00467 0.05384 0.478 0.03392
1 148.09 162.824 67.343 0.00762 0.00005 0.00467 0.00354 0.05428 0.497 0.03635
1 142.729 162.408 65.476 0.00831 0.00006 0.00469 0.00419 0.03485 0.365 0.02949
1 136.358 176.595 65.75 0.00971 0.00007 0.00534 0.00478 0.04978 0.483 0.03736
1 120.08 139.71 111.208 0.00405 0.00003 0.0018 0.0022 0.01706 0.152 0.01345
1 112.014 588.518 107.024 0.00533 0.00005 0.00268 0.00329 0.02448 0.226 0.01956
1 110.793 128.101 107.316 0.00494 0.00004 0.0026 0.00283 0.02442 0.216 0.01831
1 110.707 122.611 105.007 0.00516 0.00005 0.00277 0.00289 0.02215 0.206 0.01715
1 112.876 148.826 106.981 0.005 0.00004 0.0027 0.00289 0.03999 0.35 0.02704
1 110.568 125.394 106.821 0.00462 0.00004 0.00226 0.0028 0.02199 0.197 0.01636
1 95.385 102.145 90.264 0.00608 0.00006 0.00331 0.00332 0.03202 0.263 0.02455
1 100.77 115.697 85.545 0.01038 0.0001 0.00622 0.00576 0.03121 0.361 0.02139
1 96.106 108.664 84.51 0.00694 0.00007 0.00389 0.00415 0.04024 0.364 0.02876
1 95.605 107.715 87.549 0.00702 0.00007 0.00428 0.00371 0.03156 0.296 0.0219
1 100.96 110.019 95.628 0.00606 0.00006 0.00351 0.00348 0.02427 0.216 0.01751
1 98.804 102.305 87.804 0.00432 0.00004 0.00247 0.00258 0.02223 0.202 0.01552
1 176.858 205.56 75.344 0.00747 0.00004 0.00418 0.0042 0.04795 0.435 0.0351
1 180.978 200.125 155.495 0.00406 0.00002 0.0022 0.00244 0.03852 0.331 0.02877
1 178.222 202.45 141.047 0.00321 0.00002 0.00163 0.00194 0.03759 0.327 0.02784
1 176.281 227.381 125.61 0.0052 0.00003 0.00287 0.00312 0.06511 0.58 0.04683
1 173.898 211.35 74.677 0.00448 0.00003 0.00237 0.00254 0.06727 0.65 0.04802
1 179.711 225.93 144.878 0.00709 0.00004 0.00391 0.00419 0.04313 0.442 0.03455
1 166.605 206.008 78.032 0.00742 0.00004 0.00387 0.00453 0.0664 0.634 0.05114
1 151.955 163.335 147.226 0.00419 0.00003 0.00224 0.00227 0.07959 0.772 0.0569
1 148.272 164.989 142.299 0.00459 0.00003 0.0025 0.00256 0.0419 0.383 0.03051
1 152.125 161.469 76.596 0.00382 0.00003 0.00191 0.00226 0.05925 0.637 0.04398
1 157.821 172.975 68.401 0.00358 0.00002 0.00196 0.00196 0.03716 0.307 0.02764
1 157.447 163.267 149.605 0.00369 0.00002 0.00201 0.00197 0.03272 0.283 0.02571
1 159.116 168.913 144.811 0.00342 0.00002 0.00178 0.00184 0.03381 0.307 0.02809
1 125.036 143.946 116.187 0.0128 0.0001 0.00743 0.00623 0.03886 0.342 0.03088
1 125.791 140.557 96.206 0.01378 0.00011 0.00826 0.00655 0.04689 0.422 0.03908
1 126.512 141.756 99.77 0.01936 0.00015 0.01159 0.0099 0.06734 0.659 0.05783
1 125.641 141.068 116.346 0.03316 0.00026 0.02144 0.01522 0.09178 0.891 0.06196
1 128.451 150.449 75.632 0.01551 0.00012 0.00905 0.00909 0.0617 0.584 0.05174
1 139.224 586.567 66.157 0.03011 0.00022 0.01854 0.01628 0.09419 0.93 0.06023
1 150.258 154.609 75.349 0.00248 0.00002 0.00105 0.00136 0.01131 0.107 0.01009
1 154.003 160.267 128.621 0.00183 0.00001 0.00076 0.001 0.0103 0.094 0.00871
1 149.689 160.368 133.608 0.00257 0.00002 0.00116 0.00134 0.01346 0.126 0.01059
1 155.078 163.736 144.148 0.00168 0.00001 0.00068 0.00092 0.01064 0.097 0.00928
1 151.884 157.765 133.751 0.00258 0.00002 0.00115 0.00122 0.0145 0.137 0.01267
1 151.989 157.339 132.857 0.00174 0.00001 0.00075 0.00096 0.01024 0.093 0.00993
1 193.03 208.9 80.297 0.00766 0.00004 0.0045 0.00389 0.03044 0.275 0.02084
1 200.714 223.982 89.686 0.00621 0.00003 0.00371 0.00337 0.02286 0.207 0.01852
1 208.519 220.315 199.02 0.00609 0.00003 0.00368 0.00339 0.01761 0.155 0.01307
1 204.664 221.3 189.621 0.00841 0.00004 0.00502 0.00485 0.02378 0.21 0.01767
1 210.141 232.706 185.258 0.00534 0.00003 0.00321 0.0028 0.0168 0.149 0.01301
1 206.327 226.355 92.02 0.00495 0.00002 0.00302 0.00246 0.02105 0.209 0.01604
1 151.872 492.892 69.085 0.00856 0.00006 0.00404 0.00385 0.01843 0.235 0.01271
1 158.219 442.557 71.948 0.00476 0.00003 0.00214 0.00207 0.01458 0.148 0.01312
1 170.756 450.247 79.032 0.00555 0.00003 0.00244 0.00261 0.01725 0.175 0.01652
1 178.285 442.824 82.063 0.00462 0.00003 0.00157 0.00194 0.01279 0.129 0.01151
1 217.116 233.481 93.978 0.00404 0.00002 0.00127 0.00128 0.01299 0.124 0.01075
1 128.94 479.697 88.251 0.00581 0.00005 0.00241 0.00314 0.02008 0.221 0.01734
1 176.824 215.293 83.961 0.0046 0.00003 0.00209 0.00221 0.01169 0.117 0.01104
1 138.19 203.522 83.34 0.00704 0.00005 0.00406 0.00398 0.04479 0.441 0.0322
1 182.018 197.173 79.187 0.00842 0.00005 0.00506 0.00449 0.02503 0.231 0.01931
1 156.239 195.107 79.82 0.00694 0.00004 0.00403 0.00395 0.02343 0.224 0.0172
1 145.174 198.109 80.637 0.00733 0.00005 0.00414 0.00422 0.02362 0.233 0.01944
1 138.145 197.238 81.114 0.00544 0.00004 0.00294 0.00327 0.02791 0.246 0.02259
1 166.888 198.966 79.512 0.00638 0.00004 0.00368 0.00351 0.02857 0.257 0.02301
1 119.031 127.533 109.216 0.0044 0.00004 0.00214 0.00192 0.01033 0.098 0.00811
1 120.078 126.632 105.667 0.0027 0.00002 0.00116 0.00135 0.01022 0.09 0.00903
1 120.289 128.143 100.209 0.00492 0.00004 0.00269 0.00238 0.01412 0.125 0.01194
1 120.256 125.306 104.773 0.00407 0.00003 0.00224 0.00205 0.01516 0.138 0.0131
1 119.056 125.213 86.795 0.00346 0.00003 0.00169 0.0017 0.01201 0.106 0.00915
1 118.747 123.723 109.836 0.00331 0.00003 0.00168 0.00171 0.01043 0.099 0.00903
1 106.516 112.777 93.105 0.00589 0.00006 0.00291 0.00319 0.04932 0.441 0.03651
1 110.453 127.611 105.554 0.00494 0.00004 0.00244 0.00315 0.04128 0.379 0.03316
1 113.4 133.344 107.816 0.00451 0.00004 0.00219 0.00283 0.04879 0.431 0.0437
1 113.166 130.27 100.673 0.00502 0.00004 0.00257 0.00312 0.05279 0.476 0.04134
1 112.239 126.609 104.095 0.00472 0.00004 0.00238 0.0029 0.05643 0.517 0.04451
1 116.15 131.731 109.815 0.00381 0.00003 0.00181 0.00232 0.03026 0.267 0.0277
1 170.368 268.796 79.543 0.00571 0.00003 0.00232 0.00269 0.03273 0.281 0.02824
1 208.083 253.792 91.802 0.00757 0.00004 0.00428 0.00428 0.06725 0.571 0.04464
1 198.458 219.29 148.691 0.00376 0.00002 0.00182 0.00215 0.03527 0.297 0.0253
1 202.805 231.508 86.232 0.0037 0.00002 0.00189 0.00211 0.01997 0.18 0.01506
1 202.544 241.35 164.168 0.00254 0.00001 0.001 0.00133 0.02662 0.228 0.02006
1 223.361 263.872 87.638 0.00352 0.00002 0.00169 0.00188 0.02536 0.225 0.01909
1 169.774 191.759 151.451 0.01568 0.00009 0.00863 0.00946 0.08143 0.821 0.08808
1 183.52 216.814 161.34 0.01466 0.00008 0.00849 0.00819 0.0605 0.618 0.06359
1 188.62 216.302 165.982 0.01719 0.00009 0.00996 0.01027 0.07118 0.722 0.06824
1 202.632 565.74 177.258 0.01627 0.00008 0.00919 0.00963 0.0717 0.833 0.0646
1 186.695 211.961 149.442 0.01872 0.0001 0.01075 0.01154 0.0583 0.784 0.06259
1 192.818 224.429 168.793 0.03107 0.00016 0.018 0.01958 0.11908 1.302 0.13778
1 198.116 233.099 174.478 0.02714 0.00014 0.01568 0.01699 0.08684 1.018 0.08318
1 121.345 139.644 98.25 0.00684 0.00006 0.00388 0.00332 0.02534 0.241 0.02056
1 119.1 128.442 88.833 0.00692 0.00006 0.00393 0.003 0.02682 0.236 0.02018
1 117.87 127.349 95.654 0.00647 0.00005 0.00356 0.003 0.03087 0.276 0.02402
1 122.336 142.369 94.794 0.00727 0.00006 0.00415 0.00339 0.02293 0.223 0.01771
1 117.963 134.209 100.757 0.01813 0.00015 0.01117 0.00718 0.04912 0.438 0.02916
1 126.144 154.284 97.543 0.00975 0.00008 0.00593 0.00454 0.02852 0.266 0.02157
1 127.93 138.752 112.173 0.00605 0.00005 0.00321 0.00318 0.03235 0.339 0.03105
1 114.238 124.393 77.022 0.00581 0.00005 0.00299 0.00316 0.04009 0.406 0.04114
1 115.322 135.738 107.802 0.00619 0.00005 0.00352 0.00329 0.03273 0.325 0.02931
1 114.554 126.778 91.121 0.00651 0.00006 0.00366 0.0034 0.03658 0.369 0.03091
1 112.15 131.669 97.527 0.00519 0.00005 0.00291 0.00284 0.01756 0.155 0.01363
1 102.273 142.83 85.902 0.00907 0.00009 0.00493 0.00461 0.02814 0.272 0.02073
0 236.2 244.663 102.137 0.00277 0.00001 0.00154 0.00153 0.02448 0.217 0.01621
0 237.323 243.709 229.256 0.00303 0.00001 0.00173 0.00159 0.01242 0.116 0.00882
0 260.105 264.919 237.303 0.00339 0.00001 0.00205 0.00186 0.0203 0.197 0.01367
0 197.569 217.627 90.794 0.00803 0.00004 0.0049 0.00448 0.02177 0.189 0.01439
0 240.301 245.135 219.783 0.00517 0.00002 0.00316 0.00283 0.02018 0.212 0.01344
0 244.99 272.21 239.17 0.00451 0.00002 0.00279 0.00237 0.01897 0.181 0.01255
0 112.547 133.374 105.715 0.00355 0.00003 0.00166 0.0019 0.01358 0.129 0.0114
0 110.739 113.597 100.139 0.00356 0.00003 0.0017 0.002 0.01484 0.133 0.01285
0 113.715 116.443 96.913 0.00349 0.00003 0.00171 0.00203 0.01472 0.133 0.01148
0 117.004 144.466 99.923 0.00353 0.00003 0.00176 0.00218 0.01657 0.145 0.01318
0 115.38 123.109 108.634 0.00332 0.00003 0.0016 0.00199 0.01503 0.137 0.01133
0 116.388 129.038 108.97 0.00346 0.00003 0.00169 0.00213 0.01725 0.155 0.01331
1 151.737 190.204 129.859 0.00314 0.00002 0.00135 0.00162 0.01469 0.132 0.0123
1 148.79 158.359 138.99 0.00309 0.00002 0.00152 0.00186 0.01574 0.142 0.01309
1 148.143 155.982 135.041 0.00392 0.00003 0.00204 0.00231 0.0145 0.131 0.01263
1 150.44 163.441 144.736 0.00396 0.00003 0.00206 0.00233 0.02551 0.237 0.02148
1 148.462 161.078 141.998 0.00397 0.00003 0.00202 0.00235 0.01831 0.163 0.01559
1 149.818 163.417 144.786 0.00336 0.00002 0.00174 0.00198 0.02145 0.198 0.01666
0 117.226 123.925 106.656 0.00417 0.00004 0.00186 0.0027 0.01909 0.171 0.01949
0 116.848 217.552 99.503 0.00531 0.00005 0.0026 0.00346 0.01795 0.163 0.01756
0 116.286 177.291 96.983 0.00314 0.00003 0.00134 0.00192 0.01564 0.136 0.01691
0 116.556 592.03 86.228 0.00496 0.00004 0.00254 0.00263 0.0166 0.154 0.01491
0 116.342 581.289 94.246 0.00267 0.00002 0.00115 0.00148 0.013 0.117 0.01144
0 114.563 119.167 86.647 0.00327 0.00003 0.00146 0.00184 0.01185 0.106 0.01095
0 201.774 262.707 78.228 0.00694 0.00003 0.00412 0.00396 0.02574 0.255 0.01758
0 174.188 230.978 94.261 0.00459 0.00003 0.00263 0.00259 0.04087 0.405 0.02745
0 209.516 253.017 89.488 0.00564 0.00003 0.00331 0.00292 0.02751 0.263 0.01879
0 174.688 240.005 74.287 0.0136 0.00008 0.00624 0.00564 0.02308 0.256 0.01667
0 198.764 396.961 74.904 0.0074 0.00004 0.0037 0.0039 0.02296 0.241 0.01588
0 214.289 260.277 77.973 0.00567 0.00003 0.00295 0.00317 0.01884 0.19 0.01373










Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time23 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 & 23 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=231380&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]23 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=231380&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231380&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time23 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] = + 1.29477 -0.00238094`MDVP:Fo(Hz)`[t] -0.000185002`MDVP:Fhi(Hz)`[t] -0.00244012`MDVP:Flo(Hz)`[t] -94.729`MDVP:Jitter(%)`[t] -85.0461`MDVP:Jitter(Abs)`[t] + 116.985`MDVP:RAP`[t] + 40.7796`MDVP:PPQ`[t] + 4.45967`MDVP:Shimmer`[t] -0.527263`MDVP:Shimmer(dB)`[t] + 9.49206`MDVP:APQ`[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
status[t] =  +  1.29477 -0.00238094`MDVP:Fo(Hz)`[t] -0.000185002`MDVP:Fhi(Hz)`[t] -0.00244012`MDVP:Flo(Hz)`[t] -94.729`MDVP:Jitter(%)`[t] -85.0461`MDVP:Jitter(Abs)`[t] +  116.985`MDVP:RAP`[t] +  40.7796`MDVP:PPQ`[t] +  4.45967`MDVP:Shimmer`[t] -0.527263`MDVP:Shimmer(dB)`[t] +  9.49206`MDVP:APQ`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231380&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]status[t] =  +  1.29477 -0.00238094`MDVP:Fo(Hz)`[t] -0.000185002`MDVP:Fhi(Hz)`[t] -0.00244012`MDVP:Flo(Hz)`[t] -94.729`MDVP:Jitter(%)`[t] -85.0461`MDVP:Jitter(Abs)`[t] +  116.985`MDVP:RAP`[t] +  40.7796`MDVP:PPQ`[t] +  4.45967`MDVP:Shimmer`[t] -0.527263`MDVP:Shimmer(dB)`[t] +  9.49206`MDVP:APQ`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231380&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231380&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
status[t] = + 1.29477 -0.00238094`MDVP:Fo(Hz)`[t] -0.000185002`MDVP:Fhi(Hz)`[t] -0.00244012`MDVP:Flo(Hz)`[t] -94.729`MDVP:Jitter(%)`[t] -85.0461`MDVP:Jitter(Abs)`[t] + 116.985`MDVP:RAP`[t] + 40.7796`MDVP:PPQ`[t] + 4.45967`MDVP:Shimmer`[t] -0.527263`MDVP:Shimmer(dB)`[t] + 9.49206`MDVP:APQ`[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.294770.2215455.8442.27283e-081.13642e-08
`MDVP:Fo(Hz)`-0.002380940.0014057-1.6940.09199860.0459993
`MDVP:Fhi(Hz)`-0.0001850020.000342546-0.54010.5897960.294898
`MDVP:Flo(Hz)`-0.002440120.000833719-2.9270.003856730.00192837
`MDVP:Jitter(%)`-94.72966.2705-1.4290.1545770.0772884
`MDVP:Jitter(Abs)`-85.04614517.35-0.018830.9850.4925
`MDVP:RAP`116.98574.98061.560.1204310.0602156
`MDVP:PPQ`40.779652.67050.77420.4397830.219892
`MDVP:Shimmer`4.4596711.35560.39270.6949740.347487
`MDVP:Shimmer(dB)`-0.5272631.19847-0.43990.6604910.330246
`MDVP:APQ`9.492066.867751.3820.168610.084305

\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) & 1.29477 & 0.221545 & 5.844 & 2.27283e-08 & 1.13642e-08 \tabularnewline
`MDVP:Fo(Hz)` & -0.00238094 & 0.0014057 & -1.694 & 0.0919986 & 0.0459993 \tabularnewline
`MDVP:Fhi(Hz)` & -0.000185002 & 0.000342546 & -0.5401 & 0.589796 & 0.294898 \tabularnewline
`MDVP:Flo(Hz)` & -0.00244012 & 0.000833719 & -2.927 & 0.00385673 & 0.00192837 \tabularnewline
`MDVP:Jitter(%)` & -94.729 & 66.2705 & -1.429 & 0.154577 & 0.0772884 \tabularnewline
`MDVP:Jitter(Abs)` & -85.0461 & 4517.35 & -0.01883 & 0.985 & 0.4925 \tabularnewline
`MDVP:RAP` & 116.985 & 74.9806 & 1.56 & 0.120431 & 0.0602156 \tabularnewline
`MDVP:PPQ` & 40.7796 & 52.6705 & 0.7742 & 0.439783 & 0.219892 \tabularnewline
`MDVP:Shimmer` & 4.45967 & 11.3556 & 0.3927 & 0.694974 & 0.347487 \tabularnewline
`MDVP:Shimmer(dB)` & -0.527263 & 1.19847 & -0.4399 & 0.660491 & 0.330246 \tabularnewline
`MDVP:APQ` & 9.49206 & 6.86775 & 1.382 & 0.16861 & 0.084305 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231380&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]1.29477[/C][C]0.221545[/C][C]5.844[/C][C]2.27283e-08[/C][C]1.13642e-08[/C][/ROW]
[ROW][C]`MDVP:Fo(Hz)`[/C][C]-0.00238094[/C][C]0.0014057[/C][C]-1.694[/C][C]0.0919986[/C][C]0.0459993[/C][/ROW]
[ROW][C]`MDVP:Fhi(Hz)`[/C][C]-0.000185002[/C][C]0.000342546[/C][C]-0.5401[/C][C]0.589796[/C][C]0.294898[/C][/ROW]
[ROW][C]`MDVP:Flo(Hz)`[/C][C]-0.00244012[/C][C]0.000833719[/C][C]-2.927[/C][C]0.00385673[/C][C]0.00192837[/C][/ROW]
[ROW][C]`MDVP:Jitter(%)`[/C][C]-94.729[/C][C]66.2705[/C][C]-1.429[/C][C]0.154577[/C][C]0.0772884[/C][/ROW]
[ROW][C]`MDVP:Jitter(Abs)`[/C][C]-85.0461[/C][C]4517.35[/C][C]-0.01883[/C][C]0.985[/C][C]0.4925[/C][/ROW]
[ROW][C]`MDVP:RAP`[/C][C]116.985[/C][C]74.9806[/C][C]1.56[/C][C]0.120431[/C][C]0.0602156[/C][/ROW]
[ROW][C]`MDVP:PPQ`[/C][C]40.7796[/C][C]52.6705[/C][C]0.7742[/C][C]0.439783[/C][C]0.219892[/C][/ROW]
[ROW][C]`MDVP:Shimmer`[/C][C]4.45967[/C][C]11.3556[/C][C]0.3927[/C][C]0.694974[/C][C]0.347487[/C][/ROW]
[ROW][C]`MDVP:Shimmer(dB)`[/C][C]-0.527263[/C][C]1.19847[/C][C]-0.4399[/C][C]0.660491[/C][C]0.330246[/C][/ROW]
[ROW][C]`MDVP:APQ`[/C][C]9.49206[/C][C]6.86775[/C][C]1.382[/C][C]0.16861[/C][C]0.084305[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231380&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231380&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.294770.2215455.8442.27283e-081.13642e-08
`MDVP:Fo(Hz)`-0.002380940.0014057-1.6940.09199860.0459993
`MDVP:Fhi(Hz)`-0.0001850020.000342546-0.54010.5897960.294898
`MDVP:Flo(Hz)`-0.002440120.000833719-2.9270.003856730.00192837
`MDVP:Jitter(%)`-94.72966.2705-1.4290.1545770.0772884
`MDVP:Jitter(Abs)`-85.04614517.35-0.018830.9850.4925
`MDVP:RAP`116.98574.98061.560.1204310.0602156
`MDVP:PPQ`40.779652.67050.77420.4397830.219892
`MDVP:Shimmer`4.4596711.35560.39270.6949740.347487
`MDVP:Shimmer(dB)`-0.5272631.19847-0.43990.6604910.330246
`MDVP:APQ`9.492066.867751.3820.168610.084305







Multiple Linear Regression - Regression Statistics
Multiple R0.550203
R-squared0.302723
Adjusted R-squared0.264828
F-TEST (value)7.98837
F-TEST (DF numerator)10
F-TEST (DF denominator)184
p-value1.2103e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.370302
Sum Squared Residuals25.2307

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.550203 \tabularnewline
R-squared & 0.302723 \tabularnewline
Adjusted R-squared & 0.264828 \tabularnewline
F-TEST (value) & 7.98837 \tabularnewline
F-TEST (DF numerator) & 10 \tabularnewline
F-TEST (DF denominator) & 184 \tabularnewline
p-value & 1.2103e-10 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.370302 \tabularnewline
Sum Squared Residuals & 25.2307 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231380&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.550203[/C][/ROW]
[ROW][C]R-squared[/C][C]0.302723[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.264828[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]7.98837[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]10[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]184[/C][/ROW]
[ROW][C]p-value[/C][C]1.2103e-10[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.370302[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]25.2307[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231380&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231380&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.550203
R-squared0.302723
Adjusted R-squared0.264828
F-TEST (value)7.98837
F-TEST (DF numerator)10
F-TEST (DF denominator)184
p-value1.2103e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.370302
Sum Squared Residuals25.2307







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
110.9595650.0404346
210.9602350.0397654
310.9930660.00693369
410.9698890.0301112
511.03559-0.0355892
610.9065710.0934288
710.7746880.225312
810.8474760.152524
910.9252230.0747775
1010.9875690.0124314
1110.9780610.0219393
1210.9946530.00534682
1310.6453310.354669
1410.8119110.188089
1510.7541870.245813
1610.7570670.242933
1710.7190030.280997
1810.7624430.237557
1911.13292-0.132918
2010.8087410.191259
2111.00339-0.00338749
2211.04773-0.0477274
2311.00139-0.0013876
2410.8980880.101912
2510.7066580.293342
2611.0616-0.0616014
2710.7863740.213626
2810.7937860.206214
2910.7992670.200733
3010.7962750.203725
3100.380663-0.380663
3200.367488-0.367488
3300.385057-0.385057
3400.340268-0.340268
3500.343839-0.343839
3600.367574-0.367574
3710.553580.44642
3810.5548260.445174
3910.4845920.515408
4010.4820960.517904
4110.4745430.525457
4210.4969720.503028
4300.222596-0.222596
4400.20989-0.20989
4500.18015-0.18015
4600.185112-0.185112
4700.18789-0.18789
4800.255853-0.255853
4900.610833-0.610833
5000.62505-0.62505
5100.662468-0.662468
5200.63464-0.63464
5300.629863-0.629863
5400.647617-0.647617
5510.82240.1776
5610.8198240.180176
5710.8836910.116309
5810.7163320.283668
5910.7486110.251389
6010.7343880.265612
6100.576479-0.576479
6200.593978-0.593978
6300.315838-0.315838
6400.256291-0.256291
6500.240151-0.240151
6600.532706-0.532706
6710.8790060.120994
6810.9018140.0981863
6910.9700410.0299588
7011.03737-0.0373747
7110.9352360.0647637
7210.9928090.00719062
7310.7493460.250654
7410.7722420.227758
7510.8624320.137568
7610.8540690.145931
7710.9445670.055433
7810.8346630.165337
7911.00722-0.00722043
8010.9473190.0526811
8111.06109-0.0610855
8211.00717-0.00716948
8310.9346120.0653878
8410.9478230.0521774
8510.9186970.0813026
8610.6883360.311664
8710.7123050.287695
8810.9233890.0766109
8911.02639-0.0263919
9010.7120610.287939
9111.048-0.0480039
9210.9866510.0133492
9310.7980120.201988
9411.01281-0.0128075
9510.9546970.045303
9610.7296060.270394
9710.7444530.255547
9810.8752340.124766
9911.01075-0.0107467
10011.13851-0.138508
10111.17876-0.178764
10211.18485-0.184853
10311.15653-0.156532
10410.756010.24399
10510.6191260.380874
10610.6219840.378016
10710.584970.41503
10810.6284610.371539
10910.6316910.368309
11010.74520.2548
11110.7058170.294183
11210.382070.61793
11310.4518570.548143
11410.4004820.599518
11510.6560320.343968
11610.5659730.434027
11710.6534440.346556
11810.617110.38289
11910.5089690.491031
12010.4162670.583733
12110.6766520.323348
12210.6206080.379392
12310.963720.0362803
12410.7779820.222018
12510.8132590.186741
12610.8405040.159496
12710.899180.10082
12810.8427750.157225
12910.7010790.298921
13010.7447240.255276
13110.7928110.207189
13210.8063420.193658
13310.7975860.202414
13410.7513270.248673
13511.03455-0.0345466
13610.9921670.00783291
13711.08313-0.0831289
13811.08136-0.0813636
13911.09782-0.0978232
14010.9258710.0741286
14110.7488160.251184
14210.9056760.0943241
14310.6024080.397592
14410.6507050.349295
14510.4859530.514047
14610.6151830.384817
14711.15419-0.154187
14810.9032320.0967677
14910.9330630.0669366
15010.6886060.311394
15110.8334710.166529
15211.48201-0.482012
15310.938580.0614196
15410.857610.14239
15510.8788570.121143
15610.8989590.101041
15710.8285770.171423
15810.8774450.122555
15910.8679950.132005
16010.8788820.121118
16111.09106-0.0910604
16210.9401740.0598261
16310.9832210.0167789
16410.8517150.148285
16510.8919590.108041
16600.565822-0.565822
16700.182506-0.182506
16800.157518-0.157518
16900.688424-0.688424
17000.240395-0.240395
17100.179894-0.179894
17200.777759-0.777759
17300.824413-0.824413
17400.820157-0.820157
17500.826034-0.826034
17600.785813-0.785813
17700.803676-0.803676
17810.6189390.381061
17910.6508860.349114
18010.6581130.341887
18110.7041890.295811
18210.6622060.337794
18310.6682380.331762
18400.841727-0.841727
18500.832294-0.832294
18600.842056-0.842056
18700.762814-0.762814
18800.725387-0.725387
18900.822937-0.822937
19000.705572-0.705572
19100.81251-0.81251
19200.662596-0.662596
19300.444221-0.444221
19400.578854-0.578854
19500.59502-0.59502

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1 & 0.959565 & 0.0404346 \tabularnewline
2 & 1 & 0.960235 & 0.0397654 \tabularnewline
3 & 1 & 0.993066 & 0.00693369 \tabularnewline
4 & 1 & 0.969889 & 0.0301112 \tabularnewline
5 & 1 & 1.03559 & -0.0355892 \tabularnewline
6 & 1 & 0.906571 & 0.0934288 \tabularnewline
7 & 1 & 0.774688 & 0.225312 \tabularnewline
8 & 1 & 0.847476 & 0.152524 \tabularnewline
9 & 1 & 0.925223 & 0.0747775 \tabularnewline
10 & 1 & 0.987569 & 0.0124314 \tabularnewline
11 & 1 & 0.978061 & 0.0219393 \tabularnewline
12 & 1 & 0.994653 & 0.00534682 \tabularnewline
13 & 1 & 0.645331 & 0.354669 \tabularnewline
14 & 1 & 0.811911 & 0.188089 \tabularnewline
15 & 1 & 0.754187 & 0.245813 \tabularnewline
16 & 1 & 0.757067 & 0.242933 \tabularnewline
17 & 1 & 0.719003 & 0.280997 \tabularnewline
18 & 1 & 0.762443 & 0.237557 \tabularnewline
19 & 1 & 1.13292 & -0.132918 \tabularnewline
20 & 1 & 0.808741 & 0.191259 \tabularnewline
21 & 1 & 1.00339 & -0.00338749 \tabularnewline
22 & 1 & 1.04773 & -0.0477274 \tabularnewline
23 & 1 & 1.00139 & -0.0013876 \tabularnewline
24 & 1 & 0.898088 & 0.101912 \tabularnewline
25 & 1 & 0.706658 & 0.293342 \tabularnewline
26 & 1 & 1.0616 & -0.0616014 \tabularnewline
27 & 1 & 0.786374 & 0.213626 \tabularnewline
28 & 1 & 0.793786 & 0.206214 \tabularnewline
29 & 1 & 0.799267 & 0.200733 \tabularnewline
30 & 1 & 0.796275 & 0.203725 \tabularnewline
31 & 0 & 0.380663 & -0.380663 \tabularnewline
32 & 0 & 0.367488 & -0.367488 \tabularnewline
33 & 0 & 0.385057 & -0.385057 \tabularnewline
34 & 0 & 0.340268 & -0.340268 \tabularnewline
35 & 0 & 0.343839 & -0.343839 \tabularnewline
36 & 0 & 0.367574 & -0.367574 \tabularnewline
37 & 1 & 0.55358 & 0.44642 \tabularnewline
38 & 1 & 0.554826 & 0.445174 \tabularnewline
39 & 1 & 0.484592 & 0.515408 \tabularnewline
40 & 1 & 0.482096 & 0.517904 \tabularnewline
41 & 1 & 0.474543 & 0.525457 \tabularnewline
42 & 1 & 0.496972 & 0.503028 \tabularnewline
43 & 0 & 0.222596 & -0.222596 \tabularnewline
44 & 0 & 0.20989 & -0.20989 \tabularnewline
45 & 0 & 0.18015 & -0.18015 \tabularnewline
46 & 0 & 0.185112 & -0.185112 \tabularnewline
47 & 0 & 0.18789 & -0.18789 \tabularnewline
48 & 0 & 0.255853 & -0.255853 \tabularnewline
49 & 0 & 0.610833 & -0.610833 \tabularnewline
50 & 0 & 0.62505 & -0.62505 \tabularnewline
51 & 0 & 0.662468 & -0.662468 \tabularnewline
52 & 0 & 0.63464 & -0.63464 \tabularnewline
53 & 0 & 0.629863 & -0.629863 \tabularnewline
54 & 0 & 0.647617 & -0.647617 \tabularnewline
55 & 1 & 0.8224 & 0.1776 \tabularnewline
56 & 1 & 0.819824 & 0.180176 \tabularnewline
57 & 1 & 0.883691 & 0.116309 \tabularnewline
58 & 1 & 0.716332 & 0.283668 \tabularnewline
59 & 1 & 0.748611 & 0.251389 \tabularnewline
60 & 1 & 0.734388 & 0.265612 \tabularnewline
61 & 0 & 0.576479 & -0.576479 \tabularnewline
62 & 0 & 0.593978 & -0.593978 \tabularnewline
63 & 0 & 0.315838 & -0.315838 \tabularnewline
64 & 0 & 0.256291 & -0.256291 \tabularnewline
65 & 0 & 0.240151 & -0.240151 \tabularnewline
66 & 0 & 0.532706 & -0.532706 \tabularnewline
67 & 1 & 0.879006 & 0.120994 \tabularnewline
68 & 1 & 0.901814 & 0.0981863 \tabularnewline
69 & 1 & 0.970041 & 0.0299588 \tabularnewline
70 & 1 & 1.03737 & -0.0373747 \tabularnewline
71 & 1 & 0.935236 & 0.0647637 \tabularnewline
72 & 1 & 0.992809 & 0.00719062 \tabularnewline
73 & 1 & 0.749346 & 0.250654 \tabularnewline
74 & 1 & 0.772242 & 0.227758 \tabularnewline
75 & 1 & 0.862432 & 0.137568 \tabularnewline
76 & 1 & 0.854069 & 0.145931 \tabularnewline
77 & 1 & 0.944567 & 0.055433 \tabularnewline
78 & 1 & 0.834663 & 0.165337 \tabularnewline
79 & 1 & 1.00722 & -0.00722043 \tabularnewline
80 & 1 & 0.947319 & 0.0526811 \tabularnewline
81 & 1 & 1.06109 & -0.0610855 \tabularnewline
82 & 1 & 1.00717 & -0.00716948 \tabularnewline
83 & 1 & 0.934612 & 0.0653878 \tabularnewline
84 & 1 & 0.947823 & 0.0521774 \tabularnewline
85 & 1 & 0.918697 & 0.0813026 \tabularnewline
86 & 1 & 0.688336 & 0.311664 \tabularnewline
87 & 1 & 0.712305 & 0.287695 \tabularnewline
88 & 1 & 0.923389 & 0.0766109 \tabularnewline
89 & 1 & 1.02639 & -0.0263919 \tabularnewline
90 & 1 & 0.712061 & 0.287939 \tabularnewline
91 & 1 & 1.048 & -0.0480039 \tabularnewline
92 & 1 & 0.986651 & 0.0133492 \tabularnewline
93 & 1 & 0.798012 & 0.201988 \tabularnewline
94 & 1 & 1.01281 & -0.0128075 \tabularnewline
95 & 1 & 0.954697 & 0.045303 \tabularnewline
96 & 1 & 0.729606 & 0.270394 \tabularnewline
97 & 1 & 0.744453 & 0.255547 \tabularnewline
98 & 1 & 0.875234 & 0.124766 \tabularnewline
99 & 1 & 1.01075 & -0.0107467 \tabularnewline
100 & 1 & 1.13851 & -0.138508 \tabularnewline
101 & 1 & 1.17876 & -0.178764 \tabularnewline
102 & 1 & 1.18485 & -0.184853 \tabularnewline
103 & 1 & 1.15653 & -0.156532 \tabularnewline
104 & 1 & 0.75601 & 0.24399 \tabularnewline
105 & 1 & 0.619126 & 0.380874 \tabularnewline
106 & 1 & 0.621984 & 0.378016 \tabularnewline
107 & 1 & 0.58497 & 0.41503 \tabularnewline
108 & 1 & 0.628461 & 0.371539 \tabularnewline
109 & 1 & 0.631691 & 0.368309 \tabularnewline
110 & 1 & 0.7452 & 0.2548 \tabularnewline
111 & 1 & 0.705817 & 0.294183 \tabularnewline
112 & 1 & 0.38207 & 0.61793 \tabularnewline
113 & 1 & 0.451857 & 0.548143 \tabularnewline
114 & 1 & 0.400482 & 0.599518 \tabularnewline
115 & 1 & 0.656032 & 0.343968 \tabularnewline
116 & 1 & 0.565973 & 0.434027 \tabularnewline
117 & 1 & 0.653444 & 0.346556 \tabularnewline
118 & 1 & 0.61711 & 0.38289 \tabularnewline
119 & 1 & 0.508969 & 0.491031 \tabularnewline
120 & 1 & 0.416267 & 0.583733 \tabularnewline
121 & 1 & 0.676652 & 0.323348 \tabularnewline
122 & 1 & 0.620608 & 0.379392 \tabularnewline
123 & 1 & 0.96372 & 0.0362803 \tabularnewline
124 & 1 & 0.777982 & 0.222018 \tabularnewline
125 & 1 & 0.813259 & 0.186741 \tabularnewline
126 & 1 & 0.840504 & 0.159496 \tabularnewline
127 & 1 & 0.89918 & 0.10082 \tabularnewline
128 & 1 & 0.842775 & 0.157225 \tabularnewline
129 & 1 & 0.701079 & 0.298921 \tabularnewline
130 & 1 & 0.744724 & 0.255276 \tabularnewline
131 & 1 & 0.792811 & 0.207189 \tabularnewline
132 & 1 & 0.806342 & 0.193658 \tabularnewline
133 & 1 & 0.797586 & 0.202414 \tabularnewline
134 & 1 & 0.751327 & 0.248673 \tabularnewline
135 & 1 & 1.03455 & -0.0345466 \tabularnewline
136 & 1 & 0.992167 & 0.00783291 \tabularnewline
137 & 1 & 1.08313 & -0.0831289 \tabularnewline
138 & 1 & 1.08136 & -0.0813636 \tabularnewline
139 & 1 & 1.09782 & -0.0978232 \tabularnewline
140 & 1 & 0.925871 & 0.0741286 \tabularnewline
141 & 1 & 0.748816 & 0.251184 \tabularnewline
142 & 1 & 0.905676 & 0.0943241 \tabularnewline
143 & 1 & 0.602408 & 0.397592 \tabularnewline
144 & 1 & 0.650705 & 0.349295 \tabularnewline
145 & 1 & 0.485953 & 0.514047 \tabularnewline
146 & 1 & 0.615183 & 0.384817 \tabularnewline
147 & 1 & 1.15419 & -0.154187 \tabularnewline
148 & 1 & 0.903232 & 0.0967677 \tabularnewline
149 & 1 & 0.933063 & 0.0669366 \tabularnewline
150 & 1 & 0.688606 & 0.311394 \tabularnewline
151 & 1 & 0.833471 & 0.166529 \tabularnewline
152 & 1 & 1.48201 & -0.482012 \tabularnewline
153 & 1 & 0.93858 & 0.0614196 \tabularnewline
154 & 1 & 0.85761 & 0.14239 \tabularnewline
155 & 1 & 0.878857 & 0.121143 \tabularnewline
156 & 1 & 0.898959 & 0.101041 \tabularnewline
157 & 1 & 0.828577 & 0.171423 \tabularnewline
158 & 1 & 0.877445 & 0.122555 \tabularnewline
159 & 1 & 0.867995 & 0.132005 \tabularnewline
160 & 1 & 0.878882 & 0.121118 \tabularnewline
161 & 1 & 1.09106 & -0.0910604 \tabularnewline
162 & 1 & 0.940174 & 0.0598261 \tabularnewline
163 & 1 & 0.983221 & 0.0167789 \tabularnewline
164 & 1 & 0.851715 & 0.148285 \tabularnewline
165 & 1 & 0.891959 & 0.108041 \tabularnewline
166 & 0 & 0.565822 & -0.565822 \tabularnewline
167 & 0 & 0.182506 & -0.182506 \tabularnewline
168 & 0 & 0.157518 & -0.157518 \tabularnewline
169 & 0 & 0.688424 & -0.688424 \tabularnewline
170 & 0 & 0.240395 & -0.240395 \tabularnewline
171 & 0 & 0.179894 & -0.179894 \tabularnewline
172 & 0 & 0.777759 & -0.777759 \tabularnewline
173 & 0 & 0.824413 & -0.824413 \tabularnewline
174 & 0 & 0.820157 & -0.820157 \tabularnewline
175 & 0 & 0.826034 & -0.826034 \tabularnewline
176 & 0 & 0.785813 & -0.785813 \tabularnewline
177 & 0 & 0.803676 & -0.803676 \tabularnewline
178 & 1 & 0.618939 & 0.381061 \tabularnewline
179 & 1 & 0.650886 & 0.349114 \tabularnewline
180 & 1 & 0.658113 & 0.341887 \tabularnewline
181 & 1 & 0.704189 & 0.295811 \tabularnewline
182 & 1 & 0.662206 & 0.337794 \tabularnewline
183 & 1 & 0.668238 & 0.331762 \tabularnewline
184 & 0 & 0.841727 & -0.841727 \tabularnewline
185 & 0 & 0.832294 & -0.832294 \tabularnewline
186 & 0 & 0.842056 & -0.842056 \tabularnewline
187 & 0 & 0.762814 & -0.762814 \tabularnewline
188 & 0 & 0.725387 & -0.725387 \tabularnewline
189 & 0 & 0.822937 & -0.822937 \tabularnewline
190 & 0 & 0.705572 & -0.705572 \tabularnewline
191 & 0 & 0.81251 & -0.81251 \tabularnewline
192 & 0 & 0.662596 & -0.662596 \tabularnewline
193 & 0 & 0.444221 & -0.444221 \tabularnewline
194 & 0 & 0.578854 & -0.578854 \tabularnewline
195 & 0 & 0.59502 & -0.59502 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231380&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]1[/C][C]0.959565[/C][C]0.0404346[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]0.960235[/C][C]0.0397654[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]0.993066[/C][C]0.00693369[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]0.969889[/C][C]0.0301112[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]1.03559[/C][C]-0.0355892[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.906571[/C][C]0.0934288[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.774688[/C][C]0.225312[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.847476[/C][C]0.152524[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.925223[/C][C]0.0747775[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]0.987569[/C][C]0.0124314[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]0.978061[/C][C]0.0219393[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]0.994653[/C][C]0.00534682[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.645331[/C][C]0.354669[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]0.811911[/C][C]0.188089[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.754187[/C][C]0.245813[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]0.757067[/C][C]0.242933[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.719003[/C][C]0.280997[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]0.762443[/C][C]0.237557[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]1.13292[/C][C]-0.132918[/C][/ROW]
[ROW][C]20[/C][C]1[/C][C]0.808741[/C][C]0.191259[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]1.00339[/C][C]-0.00338749[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]1.04773[/C][C]-0.0477274[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]1.00139[/C][C]-0.0013876[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.898088[/C][C]0.101912[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.706658[/C][C]0.293342[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]1.0616[/C][C]-0.0616014[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.786374[/C][C]0.213626[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]0.793786[/C][C]0.206214[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.799267[/C][C]0.200733[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]0.796275[/C][C]0.203725[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0.380663[/C][C]-0.380663[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0.367488[/C][C]-0.367488[/C][/ROW]
[ROW][C]33[/C][C]0[/C][C]0.385057[/C][C]-0.385057[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]0.340268[/C][C]-0.340268[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0.343839[/C][C]-0.343839[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0.367574[/C][C]-0.367574[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]0.55358[/C][C]0.44642[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.554826[/C][C]0.445174[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.484592[/C][C]0.515408[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]0.482096[/C][C]0.517904[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.474543[/C][C]0.525457[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.496972[/C][C]0.503028[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0.222596[/C][C]-0.222596[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0.20989[/C][C]-0.20989[/C][/ROW]
[ROW][C]45[/C][C]0[/C][C]0.18015[/C][C]-0.18015[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0.185112[/C][C]-0.185112[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0.18789[/C][C]-0.18789[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]0.255853[/C][C]-0.255853[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0.610833[/C][C]-0.610833[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0.62505[/C][C]-0.62505[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]0.662468[/C][C]-0.662468[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0.63464[/C][C]-0.63464[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0.629863[/C][C]-0.629863[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0.647617[/C][C]-0.647617[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.8224[/C][C]0.1776[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]0.819824[/C][C]0.180176[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]0.883691[/C][C]0.116309[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.716332[/C][C]0.283668[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]0.748611[/C][C]0.251389[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.734388[/C][C]0.265612[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0.576479[/C][C]-0.576479[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0.593978[/C][C]-0.593978[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0.315838[/C][C]-0.315838[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0.256291[/C][C]-0.256291[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0.240151[/C][C]-0.240151[/C][/ROW]
[ROW][C]66[/C][C]0[/C][C]0.532706[/C][C]-0.532706[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.879006[/C][C]0.120994[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]0.901814[/C][C]0.0981863[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]0.970041[/C][C]0.0299588[/C][/ROW]
[ROW][C]70[/C][C]1[/C][C]1.03737[/C][C]-0.0373747[/C][/ROW]
[ROW][C]71[/C][C]1[/C][C]0.935236[/C][C]0.0647637[/C][/ROW]
[ROW][C]72[/C][C]1[/C][C]0.992809[/C][C]0.00719062[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]0.749346[/C][C]0.250654[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.772242[/C][C]0.227758[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]0.862432[/C][C]0.137568[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]0.854069[/C][C]0.145931[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]0.944567[/C][C]0.055433[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]0.834663[/C][C]0.165337[/C][/ROW]
[ROW][C]79[/C][C]1[/C][C]1.00722[/C][C]-0.00722043[/C][/ROW]
[ROW][C]80[/C][C]1[/C][C]0.947319[/C][C]0.0526811[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]1.06109[/C][C]-0.0610855[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]1.00717[/C][C]-0.00716948[/C][/ROW]
[ROW][C]83[/C][C]1[/C][C]0.934612[/C][C]0.0653878[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]0.947823[/C][C]0.0521774[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]0.918697[/C][C]0.0813026[/C][/ROW]
[ROW][C]86[/C][C]1[/C][C]0.688336[/C][C]0.311664[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.712305[/C][C]0.287695[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]0.923389[/C][C]0.0766109[/C][/ROW]
[ROW][C]89[/C][C]1[/C][C]1.02639[/C][C]-0.0263919[/C][/ROW]
[ROW][C]90[/C][C]1[/C][C]0.712061[/C][C]0.287939[/C][/ROW]
[ROW][C]91[/C][C]1[/C][C]1.048[/C][C]-0.0480039[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]0.986651[/C][C]0.0133492[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.798012[/C][C]0.201988[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]1.01281[/C][C]-0.0128075[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]0.954697[/C][C]0.045303[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.729606[/C][C]0.270394[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]0.744453[/C][C]0.255547[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]0.875234[/C][C]0.124766[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]1.01075[/C][C]-0.0107467[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]1.13851[/C][C]-0.138508[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]1.17876[/C][C]-0.178764[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]1.18485[/C][C]-0.184853[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]1.15653[/C][C]-0.156532[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.75601[/C][C]0.24399[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]0.619126[/C][C]0.380874[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]0.621984[/C][C]0.378016[/C][/ROW]
[ROW][C]107[/C][C]1[/C][C]0.58497[/C][C]0.41503[/C][/ROW]
[ROW][C]108[/C][C]1[/C][C]0.628461[/C][C]0.371539[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]0.631691[/C][C]0.368309[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]0.7452[/C][C]0.2548[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]0.705817[/C][C]0.294183[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]0.38207[/C][C]0.61793[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.451857[/C][C]0.548143[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.400482[/C][C]0.599518[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.656032[/C][C]0.343968[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.565973[/C][C]0.434027[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.653444[/C][C]0.346556[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]0.61711[/C][C]0.38289[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.508969[/C][C]0.491031[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.416267[/C][C]0.583733[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]0.676652[/C][C]0.323348[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]0.620608[/C][C]0.379392[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]0.96372[/C][C]0.0362803[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.777982[/C][C]0.222018[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.813259[/C][C]0.186741[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.840504[/C][C]0.159496[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.89918[/C][C]0.10082[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.842775[/C][C]0.157225[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.701079[/C][C]0.298921[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.744724[/C][C]0.255276[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.792811[/C][C]0.207189[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]0.806342[/C][C]0.193658[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]0.797586[/C][C]0.202414[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.751327[/C][C]0.248673[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]1.03455[/C][C]-0.0345466[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]0.992167[/C][C]0.00783291[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]1.08313[/C][C]-0.0831289[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]1.08136[/C][C]-0.0813636[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]1.09782[/C][C]-0.0978232[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.925871[/C][C]0.0741286[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.748816[/C][C]0.251184[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.905676[/C][C]0.0943241[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.602408[/C][C]0.397592[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.650705[/C][C]0.349295[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.485953[/C][C]0.514047[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]0.615183[/C][C]0.384817[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]1.15419[/C][C]-0.154187[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]0.903232[/C][C]0.0967677[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]0.933063[/C][C]0.0669366[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.688606[/C][C]0.311394[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]0.833471[/C][C]0.166529[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]1.48201[/C][C]-0.482012[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]0.93858[/C][C]0.0614196[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.85761[/C][C]0.14239[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]0.878857[/C][C]0.121143[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.898959[/C][C]0.101041[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.828577[/C][C]0.171423[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]0.877445[/C][C]0.122555[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]0.867995[/C][C]0.132005[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]0.878882[/C][C]0.121118[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]1.09106[/C][C]-0.0910604[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]0.940174[/C][C]0.0598261[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0.983221[/C][C]0.0167789[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]0.851715[/C][C]0.148285[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]0.891959[/C][C]0.108041[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.565822[/C][C]-0.565822[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.182506[/C][C]-0.182506[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.157518[/C][C]-0.157518[/C][/ROW]
[ROW][C]169[/C][C]0[/C][C]0.688424[/C][C]-0.688424[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.240395[/C][C]-0.240395[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.179894[/C][C]-0.179894[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.777759[/C][C]-0.777759[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.824413[/C][C]-0.824413[/C][/ROW]
[ROW][C]174[/C][C]0[/C][C]0.820157[/C][C]-0.820157[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.826034[/C][C]-0.826034[/C][/ROW]
[ROW][C]176[/C][C]0[/C][C]0.785813[/C][C]-0.785813[/C][/ROW]
[ROW][C]177[/C][C]0[/C][C]0.803676[/C][C]-0.803676[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0.618939[/C][C]0.381061[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]0.650886[/C][C]0.349114[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0.658113[/C][C]0.341887[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]0.704189[/C][C]0.295811[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]0.662206[/C][C]0.337794[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0.668238[/C][C]0.331762[/C][/ROW]
[ROW][C]184[/C][C]0[/C][C]0.841727[/C][C]-0.841727[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]0.832294[/C][C]-0.832294[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]0.842056[/C][C]-0.842056[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.762814[/C][C]-0.762814[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.725387[/C][C]-0.725387[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.822937[/C][C]-0.822937[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.705572[/C][C]-0.705572[/C][/ROW]
[ROW][C]191[/C][C]0[/C][C]0.81251[/C][C]-0.81251[/C][/ROW]
[ROW][C]192[/C][C]0[/C][C]0.662596[/C][C]-0.662596[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]0.444221[/C][C]-0.444221[/C][/ROW]
[ROW][C]194[/C][C]0[/C][C]0.578854[/C][C]-0.578854[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.59502[/C][C]-0.59502[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231380&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231380&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
110.9595650.0404346
210.9602350.0397654
310.9930660.00693369
410.9698890.0301112
511.03559-0.0355892
610.9065710.0934288
710.7746880.225312
810.8474760.152524
910.9252230.0747775
1010.9875690.0124314
1110.9780610.0219393
1210.9946530.00534682
1310.6453310.354669
1410.8119110.188089
1510.7541870.245813
1610.7570670.242933
1710.7190030.280997
1810.7624430.237557
1911.13292-0.132918
2010.8087410.191259
2111.00339-0.00338749
2211.04773-0.0477274
2311.00139-0.0013876
2410.8980880.101912
2510.7066580.293342
2611.0616-0.0616014
2710.7863740.213626
2810.7937860.206214
2910.7992670.200733
3010.7962750.203725
3100.380663-0.380663
3200.367488-0.367488
3300.385057-0.385057
3400.340268-0.340268
3500.343839-0.343839
3600.367574-0.367574
3710.553580.44642
3810.5548260.445174
3910.4845920.515408
4010.4820960.517904
4110.4745430.525457
4210.4969720.503028
4300.222596-0.222596
4400.20989-0.20989
4500.18015-0.18015
4600.185112-0.185112
4700.18789-0.18789
4800.255853-0.255853
4900.610833-0.610833
5000.62505-0.62505
5100.662468-0.662468
5200.63464-0.63464
5300.629863-0.629863
5400.647617-0.647617
5510.82240.1776
5610.8198240.180176
5710.8836910.116309
5810.7163320.283668
5910.7486110.251389
6010.7343880.265612
6100.576479-0.576479
6200.593978-0.593978
6300.315838-0.315838
6400.256291-0.256291
6500.240151-0.240151
6600.532706-0.532706
6710.8790060.120994
6810.9018140.0981863
6910.9700410.0299588
7011.03737-0.0373747
7110.9352360.0647637
7210.9928090.00719062
7310.7493460.250654
7410.7722420.227758
7510.8624320.137568
7610.8540690.145931
7710.9445670.055433
7810.8346630.165337
7911.00722-0.00722043
8010.9473190.0526811
8111.06109-0.0610855
8211.00717-0.00716948
8310.9346120.0653878
8410.9478230.0521774
8510.9186970.0813026
8610.6883360.311664
8710.7123050.287695
8810.9233890.0766109
8911.02639-0.0263919
9010.7120610.287939
9111.048-0.0480039
9210.9866510.0133492
9310.7980120.201988
9411.01281-0.0128075
9510.9546970.045303
9610.7296060.270394
9710.7444530.255547
9810.8752340.124766
9911.01075-0.0107467
10011.13851-0.138508
10111.17876-0.178764
10211.18485-0.184853
10311.15653-0.156532
10410.756010.24399
10510.6191260.380874
10610.6219840.378016
10710.584970.41503
10810.6284610.371539
10910.6316910.368309
11010.74520.2548
11110.7058170.294183
11210.382070.61793
11310.4518570.548143
11410.4004820.599518
11510.6560320.343968
11610.5659730.434027
11710.6534440.346556
11810.617110.38289
11910.5089690.491031
12010.4162670.583733
12110.6766520.323348
12210.6206080.379392
12310.963720.0362803
12410.7779820.222018
12510.8132590.186741
12610.8405040.159496
12710.899180.10082
12810.8427750.157225
12910.7010790.298921
13010.7447240.255276
13110.7928110.207189
13210.8063420.193658
13310.7975860.202414
13410.7513270.248673
13511.03455-0.0345466
13610.9921670.00783291
13711.08313-0.0831289
13811.08136-0.0813636
13911.09782-0.0978232
14010.9258710.0741286
14110.7488160.251184
14210.9056760.0943241
14310.6024080.397592
14410.6507050.349295
14510.4859530.514047
14610.6151830.384817
14711.15419-0.154187
14810.9032320.0967677
14910.9330630.0669366
15010.6886060.311394
15110.8334710.166529
15211.48201-0.482012
15310.938580.0614196
15410.857610.14239
15510.8788570.121143
15610.8989590.101041
15710.8285770.171423
15810.8774450.122555
15910.8679950.132005
16010.8788820.121118
16111.09106-0.0910604
16210.9401740.0598261
16310.9832210.0167789
16410.8517150.148285
16510.8919590.108041
16600.565822-0.565822
16700.182506-0.182506
16800.157518-0.157518
16900.688424-0.688424
17000.240395-0.240395
17100.179894-0.179894
17200.777759-0.777759
17300.824413-0.824413
17400.820157-0.820157
17500.826034-0.826034
17600.785813-0.785813
17700.803676-0.803676
17810.6189390.381061
17910.6508860.349114
18010.6581130.341887
18110.7041890.295811
18210.6622060.337794
18310.6682380.331762
18400.841727-0.841727
18500.832294-0.832294
18600.842056-0.842056
18700.762814-0.762814
18800.725387-0.725387
18900.822937-0.822937
19000.705572-0.705572
19100.81251-0.81251
19200.662596-0.662596
19300.444221-0.444221
19400.578854-0.578854
19500.59502-0.59502







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
144.7356e-499.47119e-491
152.68502e-655.37004e-651
16001
171.87572e-993.75144e-991
187.14952e-1091.4299e-1081
193.75272e-1237.50543e-1231
201.16139e-1442.32278e-1441
211.64045e-1733.2809e-1731
224.81422e-1719.62844e-1711
231.39281e-1832.78561e-1831
242.51861e-2015.03721e-2011
252.09059e-2194.18118e-2191
262.23523e-2564.47046e-2561
271.45847e-2492.91694e-2491
285.72857e-2611.14571e-2601
291.35955e-2802.71911e-2801
306.60487e-2971.32097e-2961
312.75795e-085.5159e-081
321.67541e-083.35082e-081
335.74689e-091.14938e-081
341.72909e-093.45817e-091
355.12366e-101.02473e-091
361.47665e-102.9533e-101
371.71754e-083.43508e-081
383.27028e-076.54056e-071
395.18932e-050.0001037860.999948
400.0005439350.001087870.999456
410.002566750.00513350.997433
420.003490530.006981060.996509
430.002386870.004773740.997613
440.001503050.00300610.998497
450.001045020.002090050.998955
460.0006532270.001306450.999347
470.0004121510.0008243010.999588
480.0002613750.0005227510.999739
490.001510180.003020350.99849
500.002254790.004509590.997745
510.003198230.006396460.996802
520.002893450.005786890.997107
530.003261920.006523840.996738
540.00376230.00752460.996238
550.003257750.006515490.996742
560.003625450.007250890.996375
570.002775860.005551730.997224
580.002481650.004963290.997518
590.002216010.004432030.997784
600.001853350.003706710.998147
610.004314910.008629810.995685
620.006134060.01226810.993866
630.005167720.01033540.994832
640.00422010.008440190.99578
650.00341280.006825590.996587
660.003549780.007099550.99645
670.002813970.005627950.997186
680.001976170.003952340.998024
690.002486310.004972610.997514
700.001762660.003525320.998237
710.001253940.002507890.998746
720.0008419770.001683950.999158
730.0006274030.001254810.999373
740.001029390.002058790.998971
750.000714830.001429660.999285
760.0004955620.0009911240.999504
770.0003428240.0006856480.999657
780.0002374040.0004748090.999763
790.0001570010.0003140020.999843
800.0001428930.0002857860.999857
819.55231e-050.0001910460.999904
826.52647e-050.0001305290.999935
834.6604e-059.3208e-050.999953
843.36395e-056.72789e-050.999966
852.11615e-054.2323e-050.999979
862.57997e-055.15995e-050.999974
874.34293e-058.68586e-050.999957
883.39227e-056.78455e-050.999966
892.82322e-055.64644e-050.999972
901.88561e-053.77123e-050.999981
911.30534e-052.61069e-050.999987
921.08329e-052.16658e-050.999989
937.21095e-061.44219e-050.999993
944.46064e-068.92129e-060.999996
952.70091e-065.40181e-060.999997
961.86953e-063.73906e-060.999998
971.29521e-062.59042e-060.999999
987.73041e-071.54608e-060.999999
994.54999e-079.09998e-071
1004.16395e-078.32791e-071
1013.35789e-076.71579e-071
1024.64821e-079.29642e-071
1039.15229e-071.83046e-060.999999
1047.36472e-071.47294e-060.999999
1056.40897e-071.28179e-060.999999
1066.49936e-071.29987e-060.999999
1076.1223e-071.22446e-060.999999
1085.95995e-071.19199e-060.999999
1094.70156e-079.40312e-071
1103.64947e-077.29895e-071
1112.86066e-075.72132e-071
1126.17628e-071.23526e-060.999999
1139.18216e-071.83643e-060.999999
1142.91818e-065.83635e-060.999997
1152.36704e-064.73408e-060.999998
1163.31461e-066.62922e-060.999997
1172.95613e-065.91226e-060.999997
1182.94526e-065.89052e-060.999997
1197.80625e-061.56125e-050.999992
1205.05026e-050.0001010050.999949
1218.2059e-050.0001641180.999918
1220.0001174210.0002348420.999883
1238.04971e-050.0001609940.99992
1247.47631e-050.0001495260.999925
1257.86012e-050.0001572020.999921
1268.93897e-050.0001787790.999911
1278.92048e-050.000178410.999911
1288.9409e-050.0001788180.999911
1298.6164e-050.0001723280.999914
1308.10847e-050.0001621690.999919
1317.68401e-050.000153680.999923
1327.30889e-050.0001461780.999927
1338.61903e-050.0001723810.999914
1340.000109540.0002190810.99989
1358.06056e-050.0001612110.999919
1365.36543e-050.0001073090.999946
1373.51551e-057.03101e-050.999965
1382.33422e-054.66844e-050.999977
1391.97197e-053.94394e-050.99998
1401.38938e-052.77875e-050.999986
1411.73453e-053.46905e-050.999983
1421.16789e-052.33578e-050.999988
1431.64767e-053.29535e-050.999984
1446.345e-050.00012690.999937
1450.0001726110.0003452220.999827
1460.001342250.00268450.998658
1470.00102210.002044190.998978
1480.0006819280.001363860.999318
1490.0005315420.001063080.999468
1500.0003973070.0007946150.999603
1510.0002681050.000536210.999732
1520.0007823540.001564710.999218
1530.0005003840.001000770.9995
1540.0003947430.0007894860.999605
1550.000296430.000592860.999704
1560.0002285440.0004570890.999771
1570.000226340.0004526810.999774
1580.0004433540.0008867070.999557
1590.0002839830.0005679660.999716
1600.0001954090.0003908180.999805
1610.0001199160.0002398330.99988
1626.79448e-050.000135890.999932
1633.98612e-057.97223e-050.99996
1646.80406e-050.0001360810.999932
1650.003833380.007666760.996167
1660.004357820.008715640.995642
1670.004461330.008922660.995539
1680.01159210.02318420.988408
1690.01670530.03341070.983295
1700.01248860.02497720.987511
1710.997080.005839030.00291951
1720.9992440.001512370.000756184
1730.9988290.002341250.00117062
1740.9978190.004362160.00218108
1750.9978370.00432570.00216285
1760.9986610.002677630.00133882
1770.9989560.002087830.00104392
1780.9999050.000189269.46301e-05
1790.9994170.001166940.000583472
1800.9987920.002416040.00120802
1810.9931870.01362660.00681331

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
14 & 4.7356e-49 & 9.47119e-49 & 1 \tabularnewline
15 & 2.68502e-65 & 5.37004e-65 & 1 \tabularnewline
16 & 0 & 0 & 1 \tabularnewline
17 & 1.87572e-99 & 3.75144e-99 & 1 \tabularnewline
18 & 7.14952e-109 & 1.4299e-108 & 1 \tabularnewline
19 & 3.75272e-123 & 7.50543e-123 & 1 \tabularnewline
20 & 1.16139e-144 & 2.32278e-144 & 1 \tabularnewline
21 & 1.64045e-173 & 3.2809e-173 & 1 \tabularnewline
22 & 4.81422e-171 & 9.62844e-171 & 1 \tabularnewline
23 & 1.39281e-183 & 2.78561e-183 & 1 \tabularnewline
24 & 2.51861e-201 & 5.03721e-201 & 1 \tabularnewline
25 & 2.09059e-219 & 4.18118e-219 & 1 \tabularnewline
26 & 2.23523e-256 & 4.47046e-256 & 1 \tabularnewline
27 & 1.45847e-249 & 2.91694e-249 & 1 \tabularnewline
28 & 5.72857e-261 & 1.14571e-260 & 1 \tabularnewline
29 & 1.35955e-280 & 2.71911e-280 & 1 \tabularnewline
30 & 6.60487e-297 & 1.32097e-296 & 1 \tabularnewline
31 & 2.75795e-08 & 5.5159e-08 & 1 \tabularnewline
32 & 1.67541e-08 & 3.35082e-08 & 1 \tabularnewline
33 & 5.74689e-09 & 1.14938e-08 & 1 \tabularnewline
34 & 1.72909e-09 & 3.45817e-09 & 1 \tabularnewline
35 & 5.12366e-10 & 1.02473e-09 & 1 \tabularnewline
36 & 1.47665e-10 & 2.9533e-10 & 1 \tabularnewline
37 & 1.71754e-08 & 3.43508e-08 & 1 \tabularnewline
38 & 3.27028e-07 & 6.54056e-07 & 1 \tabularnewline
39 & 5.18932e-05 & 0.000103786 & 0.999948 \tabularnewline
40 & 0.000543935 & 0.00108787 & 0.999456 \tabularnewline
41 & 0.00256675 & 0.0051335 & 0.997433 \tabularnewline
42 & 0.00349053 & 0.00698106 & 0.996509 \tabularnewline
43 & 0.00238687 & 0.00477374 & 0.997613 \tabularnewline
44 & 0.00150305 & 0.0030061 & 0.998497 \tabularnewline
45 & 0.00104502 & 0.00209005 & 0.998955 \tabularnewline
46 & 0.000653227 & 0.00130645 & 0.999347 \tabularnewline
47 & 0.000412151 & 0.000824301 & 0.999588 \tabularnewline
48 & 0.000261375 & 0.000522751 & 0.999739 \tabularnewline
49 & 0.00151018 & 0.00302035 & 0.99849 \tabularnewline
50 & 0.00225479 & 0.00450959 & 0.997745 \tabularnewline
51 & 0.00319823 & 0.00639646 & 0.996802 \tabularnewline
52 & 0.00289345 & 0.00578689 & 0.997107 \tabularnewline
53 & 0.00326192 & 0.00652384 & 0.996738 \tabularnewline
54 & 0.0037623 & 0.0075246 & 0.996238 \tabularnewline
55 & 0.00325775 & 0.00651549 & 0.996742 \tabularnewline
56 & 0.00362545 & 0.00725089 & 0.996375 \tabularnewline
57 & 0.00277586 & 0.00555173 & 0.997224 \tabularnewline
58 & 0.00248165 & 0.00496329 & 0.997518 \tabularnewline
59 & 0.00221601 & 0.00443203 & 0.997784 \tabularnewline
60 & 0.00185335 & 0.00370671 & 0.998147 \tabularnewline
61 & 0.00431491 & 0.00862981 & 0.995685 \tabularnewline
62 & 0.00613406 & 0.0122681 & 0.993866 \tabularnewline
63 & 0.00516772 & 0.0103354 & 0.994832 \tabularnewline
64 & 0.0042201 & 0.00844019 & 0.99578 \tabularnewline
65 & 0.0034128 & 0.00682559 & 0.996587 \tabularnewline
66 & 0.00354978 & 0.00709955 & 0.99645 \tabularnewline
67 & 0.00281397 & 0.00562795 & 0.997186 \tabularnewline
68 & 0.00197617 & 0.00395234 & 0.998024 \tabularnewline
69 & 0.00248631 & 0.00497261 & 0.997514 \tabularnewline
70 & 0.00176266 & 0.00352532 & 0.998237 \tabularnewline
71 & 0.00125394 & 0.00250789 & 0.998746 \tabularnewline
72 & 0.000841977 & 0.00168395 & 0.999158 \tabularnewline
73 & 0.000627403 & 0.00125481 & 0.999373 \tabularnewline
74 & 0.00102939 & 0.00205879 & 0.998971 \tabularnewline
75 & 0.00071483 & 0.00142966 & 0.999285 \tabularnewline
76 & 0.000495562 & 0.000991124 & 0.999504 \tabularnewline
77 & 0.000342824 & 0.000685648 & 0.999657 \tabularnewline
78 & 0.000237404 & 0.000474809 & 0.999763 \tabularnewline
79 & 0.000157001 & 0.000314002 & 0.999843 \tabularnewline
80 & 0.000142893 & 0.000285786 & 0.999857 \tabularnewline
81 & 9.55231e-05 & 0.000191046 & 0.999904 \tabularnewline
82 & 6.52647e-05 & 0.000130529 & 0.999935 \tabularnewline
83 & 4.6604e-05 & 9.3208e-05 & 0.999953 \tabularnewline
84 & 3.36395e-05 & 6.72789e-05 & 0.999966 \tabularnewline
85 & 2.11615e-05 & 4.2323e-05 & 0.999979 \tabularnewline
86 & 2.57997e-05 & 5.15995e-05 & 0.999974 \tabularnewline
87 & 4.34293e-05 & 8.68586e-05 & 0.999957 \tabularnewline
88 & 3.39227e-05 & 6.78455e-05 & 0.999966 \tabularnewline
89 & 2.82322e-05 & 5.64644e-05 & 0.999972 \tabularnewline
90 & 1.88561e-05 & 3.77123e-05 & 0.999981 \tabularnewline
91 & 1.30534e-05 & 2.61069e-05 & 0.999987 \tabularnewline
92 & 1.08329e-05 & 2.16658e-05 & 0.999989 \tabularnewline
93 & 7.21095e-06 & 1.44219e-05 & 0.999993 \tabularnewline
94 & 4.46064e-06 & 8.92129e-06 & 0.999996 \tabularnewline
95 & 2.70091e-06 & 5.40181e-06 & 0.999997 \tabularnewline
96 & 1.86953e-06 & 3.73906e-06 & 0.999998 \tabularnewline
97 & 1.29521e-06 & 2.59042e-06 & 0.999999 \tabularnewline
98 & 7.73041e-07 & 1.54608e-06 & 0.999999 \tabularnewline
99 & 4.54999e-07 & 9.09998e-07 & 1 \tabularnewline
100 & 4.16395e-07 & 8.32791e-07 & 1 \tabularnewline
101 & 3.35789e-07 & 6.71579e-07 & 1 \tabularnewline
102 & 4.64821e-07 & 9.29642e-07 & 1 \tabularnewline
103 & 9.15229e-07 & 1.83046e-06 & 0.999999 \tabularnewline
104 & 7.36472e-07 & 1.47294e-06 & 0.999999 \tabularnewline
105 & 6.40897e-07 & 1.28179e-06 & 0.999999 \tabularnewline
106 & 6.49936e-07 & 1.29987e-06 & 0.999999 \tabularnewline
107 & 6.1223e-07 & 1.22446e-06 & 0.999999 \tabularnewline
108 & 5.95995e-07 & 1.19199e-06 & 0.999999 \tabularnewline
109 & 4.70156e-07 & 9.40312e-07 & 1 \tabularnewline
110 & 3.64947e-07 & 7.29895e-07 & 1 \tabularnewline
111 & 2.86066e-07 & 5.72132e-07 & 1 \tabularnewline
112 & 6.17628e-07 & 1.23526e-06 & 0.999999 \tabularnewline
113 & 9.18216e-07 & 1.83643e-06 & 0.999999 \tabularnewline
114 & 2.91818e-06 & 5.83635e-06 & 0.999997 \tabularnewline
115 & 2.36704e-06 & 4.73408e-06 & 0.999998 \tabularnewline
116 & 3.31461e-06 & 6.62922e-06 & 0.999997 \tabularnewline
117 & 2.95613e-06 & 5.91226e-06 & 0.999997 \tabularnewline
118 & 2.94526e-06 & 5.89052e-06 & 0.999997 \tabularnewline
119 & 7.80625e-06 & 1.56125e-05 & 0.999992 \tabularnewline
120 & 5.05026e-05 & 0.000101005 & 0.999949 \tabularnewline
121 & 8.2059e-05 & 0.000164118 & 0.999918 \tabularnewline
122 & 0.000117421 & 0.000234842 & 0.999883 \tabularnewline
123 & 8.04971e-05 & 0.000160994 & 0.99992 \tabularnewline
124 & 7.47631e-05 & 0.000149526 & 0.999925 \tabularnewline
125 & 7.86012e-05 & 0.000157202 & 0.999921 \tabularnewline
126 & 8.93897e-05 & 0.000178779 & 0.999911 \tabularnewline
127 & 8.92048e-05 & 0.00017841 & 0.999911 \tabularnewline
128 & 8.9409e-05 & 0.000178818 & 0.999911 \tabularnewline
129 & 8.6164e-05 & 0.000172328 & 0.999914 \tabularnewline
130 & 8.10847e-05 & 0.000162169 & 0.999919 \tabularnewline
131 & 7.68401e-05 & 0.00015368 & 0.999923 \tabularnewline
132 & 7.30889e-05 & 0.000146178 & 0.999927 \tabularnewline
133 & 8.61903e-05 & 0.000172381 & 0.999914 \tabularnewline
134 & 0.00010954 & 0.000219081 & 0.99989 \tabularnewline
135 & 8.06056e-05 & 0.000161211 & 0.999919 \tabularnewline
136 & 5.36543e-05 & 0.000107309 & 0.999946 \tabularnewline
137 & 3.51551e-05 & 7.03101e-05 & 0.999965 \tabularnewline
138 & 2.33422e-05 & 4.66844e-05 & 0.999977 \tabularnewline
139 & 1.97197e-05 & 3.94394e-05 & 0.99998 \tabularnewline
140 & 1.38938e-05 & 2.77875e-05 & 0.999986 \tabularnewline
141 & 1.73453e-05 & 3.46905e-05 & 0.999983 \tabularnewline
142 & 1.16789e-05 & 2.33578e-05 & 0.999988 \tabularnewline
143 & 1.64767e-05 & 3.29535e-05 & 0.999984 \tabularnewline
144 & 6.345e-05 & 0.0001269 & 0.999937 \tabularnewline
145 & 0.000172611 & 0.000345222 & 0.999827 \tabularnewline
146 & 0.00134225 & 0.0026845 & 0.998658 \tabularnewline
147 & 0.0010221 & 0.00204419 & 0.998978 \tabularnewline
148 & 0.000681928 & 0.00136386 & 0.999318 \tabularnewline
149 & 0.000531542 & 0.00106308 & 0.999468 \tabularnewline
150 & 0.000397307 & 0.000794615 & 0.999603 \tabularnewline
151 & 0.000268105 & 0.00053621 & 0.999732 \tabularnewline
152 & 0.000782354 & 0.00156471 & 0.999218 \tabularnewline
153 & 0.000500384 & 0.00100077 & 0.9995 \tabularnewline
154 & 0.000394743 & 0.000789486 & 0.999605 \tabularnewline
155 & 0.00029643 & 0.00059286 & 0.999704 \tabularnewline
156 & 0.000228544 & 0.000457089 & 0.999771 \tabularnewline
157 & 0.00022634 & 0.000452681 & 0.999774 \tabularnewline
158 & 0.000443354 & 0.000886707 & 0.999557 \tabularnewline
159 & 0.000283983 & 0.000567966 & 0.999716 \tabularnewline
160 & 0.000195409 & 0.000390818 & 0.999805 \tabularnewline
161 & 0.000119916 & 0.000239833 & 0.99988 \tabularnewline
162 & 6.79448e-05 & 0.00013589 & 0.999932 \tabularnewline
163 & 3.98612e-05 & 7.97223e-05 & 0.99996 \tabularnewline
164 & 6.80406e-05 & 0.000136081 & 0.999932 \tabularnewline
165 & 0.00383338 & 0.00766676 & 0.996167 \tabularnewline
166 & 0.00435782 & 0.00871564 & 0.995642 \tabularnewline
167 & 0.00446133 & 0.00892266 & 0.995539 \tabularnewline
168 & 0.0115921 & 0.0231842 & 0.988408 \tabularnewline
169 & 0.0167053 & 0.0334107 & 0.983295 \tabularnewline
170 & 0.0124886 & 0.0249772 & 0.987511 \tabularnewline
171 & 0.99708 & 0.00583903 & 0.00291951 \tabularnewline
172 & 0.999244 & 0.00151237 & 0.000756184 \tabularnewline
173 & 0.998829 & 0.00234125 & 0.00117062 \tabularnewline
174 & 0.997819 & 0.00436216 & 0.00218108 \tabularnewline
175 & 0.997837 & 0.0043257 & 0.00216285 \tabularnewline
176 & 0.998661 & 0.00267763 & 0.00133882 \tabularnewline
177 & 0.998956 & 0.00208783 & 0.00104392 \tabularnewline
178 & 0.999905 & 0.00018926 & 9.46301e-05 \tabularnewline
179 & 0.999417 & 0.00116694 & 0.000583472 \tabularnewline
180 & 0.998792 & 0.00241604 & 0.00120802 \tabularnewline
181 & 0.993187 & 0.0136266 & 0.00681331 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231380&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]14[/C][C]4.7356e-49[/C][C]9.47119e-49[/C][C]1[/C][/ROW]
[ROW][C]15[/C][C]2.68502e-65[/C][C]5.37004e-65[/C][C]1[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]17[/C][C]1.87572e-99[/C][C]3.75144e-99[/C][C]1[/C][/ROW]
[ROW][C]18[/C][C]7.14952e-109[/C][C]1.4299e-108[/C][C]1[/C][/ROW]
[ROW][C]19[/C][C]3.75272e-123[/C][C]7.50543e-123[/C][C]1[/C][/ROW]
[ROW][C]20[/C][C]1.16139e-144[/C][C]2.32278e-144[/C][C]1[/C][/ROW]
[ROW][C]21[/C][C]1.64045e-173[/C][C]3.2809e-173[/C][C]1[/C][/ROW]
[ROW][C]22[/C][C]4.81422e-171[/C][C]9.62844e-171[/C][C]1[/C][/ROW]
[ROW][C]23[/C][C]1.39281e-183[/C][C]2.78561e-183[/C][C]1[/C][/ROW]
[ROW][C]24[/C][C]2.51861e-201[/C][C]5.03721e-201[/C][C]1[/C][/ROW]
[ROW][C]25[/C][C]2.09059e-219[/C][C]4.18118e-219[/C][C]1[/C][/ROW]
[ROW][C]26[/C][C]2.23523e-256[/C][C]4.47046e-256[/C][C]1[/C][/ROW]
[ROW][C]27[/C][C]1.45847e-249[/C][C]2.91694e-249[/C][C]1[/C][/ROW]
[ROW][C]28[/C][C]5.72857e-261[/C][C]1.14571e-260[/C][C]1[/C][/ROW]
[ROW][C]29[/C][C]1.35955e-280[/C][C]2.71911e-280[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]6.60487e-297[/C][C]1.32097e-296[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]2.75795e-08[/C][C]5.5159e-08[/C][C]1[/C][/ROW]
[ROW][C]32[/C][C]1.67541e-08[/C][C]3.35082e-08[/C][C]1[/C][/ROW]
[ROW][C]33[/C][C]5.74689e-09[/C][C]1.14938e-08[/C][C]1[/C][/ROW]
[ROW][C]34[/C][C]1.72909e-09[/C][C]3.45817e-09[/C][C]1[/C][/ROW]
[ROW][C]35[/C][C]5.12366e-10[/C][C]1.02473e-09[/C][C]1[/C][/ROW]
[ROW][C]36[/C][C]1.47665e-10[/C][C]2.9533e-10[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]1.71754e-08[/C][C]3.43508e-08[/C][C]1[/C][/ROW]
[ROW][C]38[/C][C]3.27028e-07[/C][C]6.54056e-07[/C][C]1[/C][/ROW]
[ROW][C]39[/C][C]5.18932e-05[/C][C]0.000103786[/C][C]0.999948[/C][/ROW]
[ROW][C]40[/C][C]0.000543935[/C][C]0.00108787[/C][C]0.999456[/C][/ROW]
[ROW][C]41[/C][C]0.00256675[/C][C]0.0051335[/C][C]0.997433[/C][/ROW]
[ROW][C]42[/C][C]0.00349053[/C][C]0.00698106[/C][C]0.996509[/C][/ROW]
[ROW][C]43[/C][C]0.00238687[/C][C]0.00477374[/C][C]0.997613[/C][/ROW]
[ROW][C]44[/C][C]0.00150305[/C][C]0.0030061[/C][C]0.998497[/C][/ROW]
[ROW][C]45[/C][C]0.00104502[/C][C]0.00209005[/C][C]0.998955[/C][/ROW]
[ROW][C]46[/C][C]0.000653227[/C][C]0.00130645[/C][C]0.999347[/C][/ROW]
[ROW][C]47[/C][C]0.000412151[/C][C]0.000824301[/C][C]0.999588[/C][/ROW]
[ROW][C]48[/C][C]0.000261375[/C][C]0.000522751[/C][C]0.999739[/C][/ROW]
[ROW][C]49[/C][C]0.00151018[/C][C]0.00302035[/C][C]0.99849[/C][/ROW]
[ROW][C]50[/C][C]0.00225479[/C][C]0.00450959[/C][C]0.997745[/C][/ROW]
[ROW][C]51[/C][C]0.00319823[/C][C]0.00639646[/C][C]0.996802[/C][/ROW]
[ROW][C]52[/C][C]0.00289345[/C][C]0.00578689[/C][C]0.997107[/C][/ROW]
[ROW][C]53[/C][C]0.00326192[/C][C]0.00652384[/C][C]0.996738[/C][/ROW]
[ROW][C]54[/C][C]0.0037623[/C][C]0.0075246[/C][C]0.996238[/C][/ROW]
[ROW][C]55[/C][C]0.00325775[/C][C]0.00651549[/C][C]0.996742[/C][/ROW]
[ROW][C]56[/C][C]0.00362545[/C][C]0.00725089[/C][C]0.996375[/C][/ROW]
[ROW][C]57[/C][C]0.00277586[/C][C]0.00555173[/C][C]0.997224[/C][/ROW]
[ROW][C]58[/C][C]0.00248165[/C][C]0.00496329[/C][C]0.997518[/C][/ROW]
[ROW][C]59[/C][C]0.00221601[/C][C]0.00443203[/C][C]0.997784[/C][/ROW]
[ROW][C]60[/C][C]0.00185335[/C][C]0.00370671[/C][C]0.998147[/C][/ROW]
[ROW][C]61[/C][C]0.00431491[/C][C]0.00862981[/C][C]0.995685[/C][/ROW]
[ROW][C]62[/C][C]0.00613406[/C][C]0.0122681[/C][C]0.993866[/C][/ROW]
[ROW][C]63[/C][C]0.00516772[/C][C]0.0103354[/C][C]0.994832[/C][/ROW]
[ROW][C]64[/C][C]0.0042201[/C][C]0.00844019[/C][C]0.99578[/C][/ROW]
[ROW][C]65[/C][C]0.0034128[/C][C]0.00682559[/C][C]0.996587[/C][/ROW]
[ROW][C]66[/C][C]0.00354978[/C][C]0.00709955[/C][C]0.99645[/C][/ROW]
[ROW][C]67[/C][C]0.00281397[/C][C]0.00562795[/C][C]0.997186[/C][/ROW]
[ROW][C]68[/C][C]0.00197617[/C][C]0.00395234[/C][C]0.998024[/C][/ROW]
[ROW][C]69[/C][C]0.00248631[/C][C]0.00497261[/C][C]0.997514[/C][/ROW]
[ROW][C]70[/C][C]0.00176266[/C][C]0.00352532[/C][C]0.998237[/C][/ROW]
[ROW][C]71[/C][C]0.00125394[/C][C]0.00250789[/C][C]0.998746[/C][/ROW]
[ROW][C]72[/C][C]0.000841977[/C][C]0.00168395[/C][C]0.999158[/C][/ROW]
[ROW][C]73[/C][C]0.000627403[/C][C]0.00125481[/C][C]0.999373[/C][/ROW]
[ROW][C]74[/C][C]0.00102939[/C][C]0.00205879[/C][C]0.998971[/C][/ROW]
[ROW][C]75[/C][C]0.00071483[/C][C]0.00142966[/C][C]0.999285[/C][/ROW]
[ROW][C]76[/C][C]0.000495562[/C][C]0.000991124[/C][C]0.999504[/C][/ROW]
[ROW][C]77[/C][C]0.000342824[/C][C]0.000685648[/C][C]0.999657[/C][/ROW]
[ROW][C]78[/C][C]0.000237404[/C][C]0.000474809[/C][C]0.999763[/C][/ROW]
[ROW][C]79[/C][C]0.000157001[/C][C]0.000314002[/C][C]0.999843[/C][/ROW]
[ROW][C]80[/C][C]0.000142893[/C][C]0.000285786[/C][C]0.999857[/C][/ROW]
[ROW][C]81[/C][C]9.55231e-05[/C][C]0.000191046[/C][C]0.999904[/C][/ROW]
[ROW][C]82[/C][C]6.52647e-05[/C][C]0.000130529[/C][C]0.999935[/C][/ROW]
[ROW][C]83[/C][C]4.6604e-05[/C][C]9.3208e-05[/C][C]0.999953[/C][/ROW]
[ROW][C]84[/C][C]3.36395e-05[/C][C]6.72789e-05[/C][C]0.999966[/C][/ROW]
[ROW][C]85[/C][C]2.11615e-05[/C][C]4.2323e-05[/C][C]0.999979[/C][/ROW]
[ROW][C]86[/C][C]2.57997e-05[/C][C]5.15995e-05[/C][C]0.999974[/C][/ROW]
[ROW][C]87[/C][C]4.34293e-05[/C][C]8.68586e-05[/C][C]0.999957[/C][/ROW]
[ROW][C]88[/C][C]3.39227e-05[/C][C]6.78455e-05[/C][C]0.999966[/C][/ROW]
[ROW][C]89[/C][C]2.82322e-05[/C][C]5.64644e-05[/C][C]0.999972[/C][/ROW]
[ROW][C]90[/C][C]1.88561e-05[/C][C]3.77123e-05[/C][C]0.999981[/C][/ROW]
[ROW][C]91[/C][C]1.30534e-05[/C][C]2.61069e-05[/C][C]0.999987[/C][/ROW]
[ROW][C]92[/C][C]1.08329e-05[/C][C]2.16658e-05[/C][C]0.999989[/C][/ROW]
[ROW][C]93[/C][C]7.21095e-06[/C][C]1.44219e-05[/C][C]0.999993[/C][/ROW]
[ROW][C]94[/C][C]4.46064e-06[/C][C]8.92129e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]95[/C][C]2.70091e-06[/C][C]5.40181e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]96[/C][C]1.86953e-06[/C][C]3.73906e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]97[/C][C]1.29521e-06[/C][C]2.59042e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]98[/C][C]7.73041e-07[/C][C]1.54608e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]99[/C][C]4.54999e-07[/C][C]9.09998e-07[/C][C]1[/C][/ROW]
[ROW][C]100[/C][C]4.16395e-07[/C][C]8.32791e-07[/C][C]1[/C][/ROW]
[ROW][C]101[/C][C]3.35789e-07[/C][C]6.71579e-07[/C][C]1[/C][/ROW]
[ROW][C]102[/C][C]4.64821e-07[/C][C]9.29642e-07[/C][C]1[/C][/ROW]
[ROW][C]103[/C][C]9.15229e-07[/C][C]1.83046e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]104[/C][C]7.36472e-07[/C][C]1.47294e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]105[/C][C]6.40897e-07[/C][C]1.28179e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]106[/C][C]6.49936e-07[/C][C]1.29987e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]107[/C][C]6.1223e-07[/C][C]1.22446e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]108[/C][C]5.95995e-07[/C][C]1.19199e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]109[/C][C]4.70156e-07[/C][C]9.40312e-07[/C][C]1[/C][/ROW]
[ROW][C]110[/C][C]3.64947e-07[/C][C]7.29895e-07[/C][C]1[/C][/ROW]
[ROW][C]111[/C][C]2.86066e-07[/C][C]5.72132e-07[/C][C]1[/C][/ROW]
[ROW][C]112[/C][C]6.17628e-07[/C][C]1.23526e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]113[/C][C]9.18216e-07[/C][C]1.83643e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]114[/C][C]2.91818e-06[/C][C]5.83635e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]115[/C][C]2.36704e-06[/C][C]4.73408e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]116[/C][C]3.31461e-06[/C][C]6.62922e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]117[/C][C]2.95613e-06[/C][C]5.91226e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]118[/C][C]2.94526e-06[/C][C]5.89052e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]119[/C][C]7.80625e-06[/C][C]1.56125e-05[/C][C]0.999992[/C][/ROW]
[ROW][C]120[/C][C]5.05026e-05[/C][C]0.000101005[/C][C]0.999949[/C][/ROW]
[ROW][C]121[/C][C]8.2059e-05[/C][C]0.000164118[/C][C]0.999918[/C][/ROW]
[ROW][C]122[/C][C]0.000117421[/C][C]0.000234842[/C][C]0.999883[/C][/ROW]
[ROW][C]123[/C][C]8.04971e-05[/C][C]0.000160994[/C][C]0.99992[/C][/ROW]
[ROW][C]124[/C][C]7.47631e-05[/C][C]0.000149526[/C][C]0.999925[/C][/ROW]
[ROW][C]125[/C][C]7.86012e-05[/C][C]0.000157202[/C][C]0.999921[/C][/ROW]
[ROW][C]126[/C][C]8.93897e-05[/C][C]0.000178779[/C][C]0.999911[/C][/ROW]
[ROW][C]127[/C][C]8.92048e-05[/C][C]0.00017841[/C][C]0.999911[/C][/ROW]
[ROW][C]128[/C][C]8.9409e-05[/C][C]0.000178818[/C][C]0.999911[/C][/ROW]
[ROW][C]129[/C][C]8.6164e-05[/C][C]0.000172328[/C][C]0.999914[/C][/ROW]
[ROW][C]130[/C][C]8.10847e-05[/C][C]0.000162169[/C][C]0.999919[/C][/ROW]
[ROW][C]131[/C][C]7.68401e-05[/C][C]0.00015368[/C][C]0.999923[/C][/ROW]
[ROW][C]132[/C][C]7.30889e-05[/C][C]0.000146178[/C][C]0.999927[/C][/ROW]
[ROW][C]133[/C][C]8.61903e-05[/C][C]0.000172381[/C][C]0.999914[/C][/ROW]
[ROW][C]134[/C][C]0.00010954[/C][C]0.000219081[/C][C]0.99989[/C][/ROW]
[ROW][C]135[/C][C]8.06056e-05[/C][C]0.000161211[/C][C]0.999919[/C][/ROW]
[ROW][C]136[/C][C]5.36543e-05[/C][C]0.000107309[/C][C]0.999946[/C][/ROW]
[ROW][C]137[/C][C]3.51551e-05[/C][C]7.03101e-05[/C][C]0.999965[/C][/ROW]
[ROW][C]138[/C][C]2.33422e-05[/C][C]4.66844e-05[/C][C]0.999977[/C][/ROW]
[ROW][C]139[/C][C]1.97197e-05[/C][C]3.94394e-05[/C][C]0.99998[/C][/ROW]
[ROW][C]140[/C][C]1.38938e-05[/C][C]2.77875e-05[/C][C]0.999986[/C][/ROW]
[ROW][C]141[/C][C]1.73453e-05[/C][C]3.46905e-05[/C][C]0.999983[/C][/ROW]
[ROW][C]142[/C][C]1.16789e-05[/C][C]2.33578e-05[/C][C]0.999988[/C][/ROW]
[ROW][C]143[/C][C]1.64767e-05[/C][C]3.29535e-05[/C][C]0.999984[/C][/ROW]
[ROW][C]144[/C][C]6.345e-05[/C][C]0.0001269[/C][C]0.999937[/C][/ROW]
[ROW][C]145[/C][C]0.000172611[/C][C]0.000345222[/C][C]0.999827[/C][/ROW]
[ROW][C]146[/C][C]0.00134225[/C][C]0.0026845[/C][C]0.998658[/C][/ROW]
[ROW][C]147[/C][C]0.0010221[/C][C]0.00204419[/C][C]0.998978[/C][/ROW]
[ROW][C]148[/C][C]0.000681928[/C][C]0.00136386[/C][C]0.999318[/C][/ROW]
[ROW][C]149[/C][C]0.000531542[/C][C]0.00106308[/C][C]0.999468[/C][/ROW]
[ROW][C]150[/C][C]0.000397307[/C][C]0.000794615[/C][C]0.999603[/C][/ROW]
[ROW][C]151[/C][C]0.000268105[/C][C]0.00053621[/C][C]0.999732[/C][/ROW]
[ROW][C]152[/C][C]0.000782354[/C][C]0.00156471[/C][C]0.999218[/C][/ROW]
[ROW][C]153[/C][C]0.000500384[/C][C]0.00100077[/C][C]0.9995[/C][/ROW]
[ROW][C]154[/C][C]0.000394743[/C][C]0.000789486[/C][C]0.999605[/C][/ROW]
[ROW][C]155[/C][C]0.00029643[/C][C]0.00059286[/C][C]0.999704[/C][/ROW]
[ROW][C]156[/C][C]0.000228544[/C][C]0.000457089[/C][C]0.999771[/C][/ROW]
[ROW][C]157[/C][C]0.00022634[/C][C]0.000452681[/C][C]0.999774[/C][/ROW]
[ROW][C]158[/C][C]0.000443354[/C][C]0.000886707[/C][C]0.999557[/C][/ROW]
[ROW][C]159[/C][C]0.000283983[/C][C]0.000567966[/C][C]0.999716[/C][/ROW]
[ROW][C]160[/C][C]0.000195409[/C][C]0.000390818[/C][C]0.999805[/C][/ROW]
[ROW][C]161[/C][C]0.000119916[/C][C]0.000239833[/C][C]0.99988[/C][/ROW]
[ROW][C]162[/C][C]6.79448e-05[/C][C]0.00013589[/C][C]0.999932[/C][/ROW]
[ROW][C]163[/C][C]3.98612e-05[/C][C]7.97223e-05[/C][C]0.99996[/C][/ROW]
[ROW][C]164[/C][C]6.80406e-05[/C][C]0.000136081[/C][C]0.999932[/C][/ROW]
[ROW][C]165[/C][C]0.00383338[/C][C]0.00766676[/C][C]0.996167[/C][/ROW]
[ROW][C]166[/C][C]0.00435782[/C][C]0.00871564[/C][C]0.995642[/C][/ROW]
[ROW][C]167[/C][C]0.00446133[/C][C]0.00892266[/C][C]0.995539[/C][/ROW]
[ROW][C]168[/C][C]0.0115921[/C][C]0.0231842[/C][C]0.988408[/C][/ROW]
[ROW][C]169[/C][C]0.0167053[/C][C]0.0334107[/C][C]0.983295[/C][/ROW]
[ROW][C]170[/C][C]0.0124886[/C][C]0.0249772[/C][C]0.987511[/C][/ROW]
[ROW][C]171[/C][C]0.99708[/C][C]0.00583903[/C][C]0.00291951[/C][/ROW]
[ROW][C]172[/C][C]0.999244[/C][C]0.00151237[/C][C]0.000756184[/C][/ROW]
[ROW][C]173[/C][C]0.998829[/C][C]0.00234125[/C][C]0.00117062[/C][/ROW]
[ROW][C]174[/C][C]0.997819[/C][C]0.00436216[/C][C]0.00218108[/C][/ROW]
[ROW][C]175[/C][C]0.997837[/C][C]0.0043257[/C][C]0.00216285[/C][/ROW]
[ROW][C]176[/C][C]0.998661[/C][C]0.00267763[/C][C]0.00133882[/C][/ROW]
[ROW][C]177[/C][C]0.998956[/C][C]0.00208783[/C][C]0.00104392[/C][/ROW]
[ROW][C]178[/C][C]0.999905[/C][C]0.00018926[/C][C]9.46301e-05[/C][/ROW]
[ROW][C]179[/C][C]0.999417[/C][C]0.00116694[/C][C]0.000583472[/C][/ROW]
[ROW][C]180[/C][C]0.998792[/C][C]0.00241604[/C][C]0.00120802[/C][/ROW]
[ROW][C]181[/C][C]0.993187[/C][C]0.0136266[/C][C]0.00681331[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231380&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231380&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
144.7356e-499.47119e-491
152.68502e-655.37004e-651
16001
171.87572e-993.75144e-991
187.14952e-1091.4299e-1081
193.75272e-1237.50543e-1231
201.16139e-1442.32278e-1441
211.64045e-1733.2809e-1731
224.81422e-1719.62844e-1711
231.39281e-1832.78561e-1831
242.51861e-2015.03721e-2011
252.09059e-2194.18118e-2191
262.23523e-2564.47046e-2561
271.45847e-2492.91694e-2491
285.72857e-2611.14571e-2601
291.35955e-2802.71911e-2801
306.60487e-2971.32097e-2961
312.75795e-085.5159e-081
321.67541e-083.35082e-081
335.74689e-091.14938e-081
341.72909e-093.45817e-091
355.12366e-101.02473e-091
361.47665e-102.9533e-101
371.71754e-083.43508e-081
383.27028e-076.54056e-071
395.18932e-050.0001037860.999948
400.0005439350.001087870.999456
410.002566750.00513350.997433
420.003490530.006981060.996509
430.002386870.004773740.997613
440.001503050.00300610.998497
450.001045020.002090050.998955
460.0006532270.001306450.999347
470.0004121510.0008243010.999588
480.0002613750.0005227510.999739
490.001510180.003020350.99849
500.002254790.004509590.997745
510.003198230.006396460.996802
520.002893450.005786890.997107
530.003261920.006523840.996738
540.00376230.00752460.996238
550.003257750.006515490.996742
560.003625450.007250890.996375
570.002775860.005551730.997224
580.002481650.004963290.997518
590.002216010.004432030.997784
600.001853350.003706710.998147
610.004314910.008629810.995685
620.006134060.01226810.993866
630.005167720.01033540.994832
640.00422010.008440190.99578
650.00341280.006825590.996587
660.003549780.007099550.99645
670.002813970.005627950.997186
680.001976170.003952340.998024
690.002486310.004972610.997514
700.001762660.003525320.998237
710.001253940.002507890.998746
720.0008419770.001683950.999158
730.0006274030.001254810.999373
740.001029390.002058790.998971
750.000714830.001429660.999285
760.0004955620.0009911240.999504
770.0003428240.0006856480.999657
780.0002374040.0004748090.999763
790.0001570010.0003140020.999843
800.0001428930.0002857860.999857
819.55231e-050.0001910460.999904
826.52647e-050.0001305290.999935
834.6604e-059.3208e-050.999953
843.36395e-056.72789e-050.999966
852.11615e-054.2323e-050.999979
862.57997e-055.15995e-050.999974
874.34293e-058.68586e-050.999957
883.39227e-056.78455e-050.999966
892.82322e-055.64644e-050.999972
901.88561e-053.77123e-050.999981
911.30534e-052.61069e-050.999987
921.08329e-052.16658e-050.999989
937.21095e-061.44219e-050.999993
944.46064e-068.92129e-060.999996
952.70091e-065.40181e-060.999997
961.86953e-063.73906e-060.999998
971.29521e-062.59042e-060.999999
987.73041e-071.54608e-060.999999
994.54999e-079.09998e-071
1004.16395e-078.32791e-071
1013.35789e-076.71579e-071
1024.64821e-079.29642e-071
1039.15229e-071.83046e-060.999999
1047.36472e-071.47294e-060.999999
1056.40897e-071.28179e-060.999999
1066.49936e-071.29987e-060.999999
1076.1223e-071.22446e-060.999999
1085.95995e-071.19199e-060.999999
1094.70156e-079.40312e-071
1103.64947e-077.29895e-071
1112.86066e-075.72132e-071
1126.17628e-071.23526e-060.999999
1139.18216e-071.83643e-060.999999
1142.91818e-065.83635e-060.999997
1152.36704e-064.73408e-060.999998
1163.31461e-066.62922e-060.999997
1172.95613e-065.91226e-060.999997
1182.94526e-065.89052e-060.999997
1197.80625e-061.56125e-050.999992
1205.05026e-050.0001010050.999949
1218.2059e-050.0001641180.999918
1220.0001174210.0002348420.999883
1238.04971e-050.0001609940.99992
1247.47631e-050.0001495260.999925
1257.86012e-050.0001572020.999921
1268.93897e-050.0001787790.999911
1278.92048e-050.000178410.999911
1288.9409e-050.0001788180.999911
1298.6164e-050.0001723280.999914
1308.10847e-050.0001621690.999919
1317.68401e-050.000153680.999923
1327.30889e-050.0001461780.999927
1338.61903e-050.0001723810.999914
1340.000109540.0002190810.99989
1358.06056e-050.0001612110.999919
1365.36543e-050.0001073090.999946
1373.51551e-057.03101e-050.999965
1382.33422e-054.66844e-050.999977
1391.97197e-053.94394e-050.99998
1401.38938e-052.77875e-050.999986
1411.73453e-053.46905e-050.999983
1421.16789e-052.33578e-050.999988
1431.64767e-053.29535e-050.999984
1446.345e-050.00012690.999937
1450.0001726110.0003452220.999827
1460.001342250.00268450.998658
1470.00102210.002044190.998978
1480.0006819280.001363860.999318
1490.0005315420.001063080.999468
1500.0003973070.0007946150.999603
1510.0002681050.000536210.999732
1520.0007823540.001564710.999218
1530.0005003840.001000770.9995
1540.0003947430.0007894860.999605
1550.000296430.000592860.999704
1560.0002285440.0004570890.999771
1570.000226340.0004526810.999774
1580.0004433540.0008867070.999557
1590.0002839830.0005679660.999716
1600.0001954090.0003908180.999805
1610.0001199160.0002398330.99988
1626.79448e-050.000135890.999932
1633.98612e-057.97223e-050.99996
1646.80406e-050.0001360810.999932
1650.003833380.007666760.996167
1660.004357820.008715640.995642
1670.004461330.008922660.995539
1680.01159210.02318420.988408
1690.01670530.03341070.983295
1700.01248860.02497720.987511
1710.997080.005839030.00291951
1720.9992440.001512370.000756184
1730.9988290.002341250.00117062
1740.9978190.004362160.00218108
1750.9978370.00432570.00216285
1760.9986610.002677630.00133882
1770.9989560.002087830.00104392
1780.9999050.000189269.46301e-05
1790.9994170.001166940.000583472
1800.9987920.002416040.00120802
1810.9931870.01362660.00681331







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1620.964286NOK
5% type I error level1681NOK
10% type I error level1681NOK

\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 & 162 & 0.964286 & NOK \tabularnewline
5% type I error level & 168 & 1 & NOK \tabularnewline
10% type I error level & 168 & 1 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231380&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]162[/C][C]0.964286[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]168[/C][C]1[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]168[/C][C]1[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231380&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231380&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1620.964286NOK
5% type I error level1681NOK
10% type I error level1681NOK



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