Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareMultiple Regression
Date of computationWed, 11 Dec 2013 12:02:44 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/11/t13867814064f47r8tayjjdxq8.htm/, Retrieved Fri, 29 Mar 2024 08:43:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232113, Retrieved Fri, 29 Mar 2024 08:43:29 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [Kendall] [2013-12-11 15:55:33] [947cbe24e101527daf12b807d6a22f40]
- RMP   [Multiple Regression] [Multiple regression] [2013-12-11 17:01:14] [947cbe24e101527daf12b807d6a22f40]
- RM        [Multiple Regression] [Multiple regression] [2013-12-11 17:02:44] [46d3d8bfbaf7691f7408e38ca0da8f78] [Current]
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Dataseries X:
1 119.992 157.302 74.997 0.00784 0.00007 0.0037 0.00554 0.01109 0.04374 0.426
1 122.4 148.65 113.819 0.00968 0.00008 0.00465 0.00696 0.01394 0.06134 0.626
1 116.682 131.111 111.555 0.0105 0.00009 0.00544 0.00781 0.01633 0.05233 0.482
1 116.676 137.871 111.366 0.00997 0.00009 0.00502 0.00698 0.01505 0.05492 0.517
1 116.014 141.781 110.655 0.01284 0.00011 0.00655 0.00908 0.01966 0.06425 0.584
1 120.552 131.162 113.787 0.00968 0.00008 0.00463 0.0075 0.01388 0.04701 0.456
1 120.267 137.244 114.82 0.00333 0.00003 0.00155 0.00202 0.00466 0.01608 0.14
1 107.332 113.84 104.315 0.0029 0.00003 0.00144 0.00182 0.00431 0.01567 0.134
1 95.73 132.068 91.754 0.00551 0.00006 0.00293 0.00332 0.0088 0.02093 0.191
1 95.056 120.103 91.226 0.00532 0.00006 0.00268 0.00332 0.00803 0.02838 0.255
1 88.333 112.24 84.072 0.00505 0.00006 0.00254 0.0033 0.00763 0.02143 0.197
1 91.904 115.871 86.292 0.0054 0.00006 0.00281 0.00336 0.00844 0.02752 0.249
1 136.926 159.866 131.276 0.00293 0.00002 0.00118 0.00153 0.00355 0.01259 0.112
1 139.173 179.139 76.556 0.0039 0.00003 0.00165 0.00208 0.00496 0.01642 0.154
1 152.845 163.305 75.836 0.00294 0.00002 0.00121 0.00149 0.00364 0.01828 0.158
1 142.167 217.455 83.159 0.00369 0.00003 0.00157 0.00203 0.00471 0.01503 0.126
1 144.188 349.259 82.764 0.00544 0.00004 0.00211 0.00292 0.00632 0.02047 0.192
1 168.778 232.181 75.603 0.00718 0.00004 0.00284 0.00387 0.00853 0.03327 0.348
1 153.046 175.829 68.623 0.00742 0.00005 0.00364 0.00432 0.01092 0.05517 0.542
1 156.405 189.398 142.822 0.00768 0.00005 0.00372 0.00399 0.01116 0.03995 0.348
1 153.848 165.738 65.782 0.0084 0.00005 0.00428 0.0045 0.01285 0.0381 0.328
1 153.88 172.86 78.128 0.0048 0.00003 0.00232 0.00267 0.00696 0.04137 0.37
1 167.93 193.221 79.068 0.00442 0.00003 0.0022 0.00247 0.00661 0.04351 0.377
1 173.917 192.735 86.18 0.00476 0.00003 0.00221 0.00258 0.00663 0.04192 0.364
1 163.656 200.841 76.779 0.00742 0.00005 0.0038 0.0039 0.0114 0.01659 0.164
1 104.4 206.002 77.968 0.00633 0.00006 0.00316 0.00375 0.00948 0.03767 0.381
1 171.041 208.313 75.501 0.00455 0.00003 0.0025 0.00234 0.0075 0.01966 0.186
1 146.845 208.701 81.737 0.00496 0.00003 0.0025 0.00275 0.00749 0.01919 0.198
1 155.358 227.383 80.055 0.0031 0.00002 0.00159 0.00176 0.00476 0.01718 0.161
1 162.568 198.346 77.63 0.00502 0.00003 0.0028 0.00253 0.00841 0.01791 0.168
0 197.076 206.896 192.055 0.00289 0.00001 0.00166 0.00168 0.00498 0.01098 0.097
0 199.228 209.512 192.091 0.00241 0.00001 0.00134 0.00138 0.00402 0.01015 0.089
0 198.383 215.203 193.104 0.00212 0.00001 0.00113 0.00135 0.00339 0.01263 0.111
0 202.266 211.604 197.079 0.0018 0.000009 0.00093 0.00107 0.00278 0.00954 0.085
0 203.184 211.526 196.16 0.00178 0.000009 0.00094 0.00106 0.00283 0.00958 0.085
0 201.464 210.565 195.708 0.00198 0.00001 0.00105 0.00115 0.00314 0.01194 0.107
1 177.876 192.921 168.013 0.00411 0.00002 0.00233 0.00241 0.007 0.02126 0.189
1 176.17 185.604 163.564 0.00369 0.00002 0.00205 0.00218 0.00616 0.01851 0.168
1 180.198 201.249 175.456 0.00284 0.00002 0.00153 0.00166 0.00459 0.01444 0.131
1 187.733 202.324 173.015 0.00316 0.00002 0.00168 0.00182 0.00504 0.01663 0.151
1 186.163 197.724 177.584 0.00298 0.00002 0.00165 0.00175 0.00496 0.01495 0.135
1 184.055 196.537 166.977 0.00258 0.00001 0.00134 0.00147 0.00403 0.01463 0.132
0 237.226 247.326 225.227 0.00298 0.00001 0.00169 0.00182 0.00507 0.01752 0.164
0 241.404 248.834 232.483 0.00281 0.00001 0.00157 0.00173 0.0047 0.0176 0.154
0 243.439 250.912 232.435 0.0021 0.000009 0.00109 0.00137 0.00327 0.01419 0.126
0 242.852 255.034 227.911 0.00225 0.000009 0.00117 0.00139 0.0035 0.01494 0.134
0 245.51 262.09 231.848 0.00235 0.00001 0.00127 0.00148 0.0038 0.01608 0.141
0 252.455 261.487 182.786 0.00185 0.000007 0.00092 0.00113 0.00276 0.01152 0.103
0 122.188 128.611 115.765 0.00524 0.00004 0.00169 0.00203 0.00507 0.01613 0.143
0 122.964 130.049 114.676 0.00428 0.00003 0.00124 0.00155 0.00373 0.01681 0.154
0 124.445 135.069 117.495 0.00431 0.00003 0.00141 0.00167 0.00422 0.02184 0.197
0 126.344 134.231 112.773 0.00448 0.00004 0.00131 0.00169 0.00393 0.02033 0.185
0 128.001 138.052 122.08 0.00436 0.00003 0.00137 0.00166 0.00411 0.02297 0.21
0 129.336 139.867 118.604 0.0049 0.00004 0.00165 0.00183 0.00495 0.02498 0.228
1 108.807 134.656 102.874 0.00761 0.00007 0.00349 0.00486 0.01046 0.02719 0.255
1 109.86 126.358 104.437 0.00874 0.00008 0.00398 0.00539 0.01193 0.03209 0.307
1 110.417 131.067 103.37 0.00784 0.00007 0.00352 0.00514 0.01056 0.03715 0.334
1 117.274 129.916 110.402 0.00752 0.00006 0.00299 0.00469 0.00898 0.02293 0.221
1 116.879 131.897 108.153 0.00788 0.00007 0.00334 0.00493 0.01003 0.02645 0.265
1 114.847 271.314 104.68 0.00867 0.00008 0.00373 0.0052 0.0112 0.03225 0.35
0 209.144 237.494 109.379 0.00282 0.00001 0.00147 0.00152 0.00442 0.01861 0.17
0 223.365 238.987 98.664 0.00264 0.00001 0.00154 0.00151 0.00461 0.01906 0.165
0 222.236 231.345 205.495 0.00266 0.00001 0.00152 0.00144 0.00457 0.01643 0.145
0 228.832 234.619 223.634 0.00296 0.00001 0.00175 0.00155 0.00526 0.01644 0.145
0 229.401 252.221 221.156 0.00205 0.000009 0.00114 0.00113 0.00342 0.01457 0.129
0 228.969 239.541 113.201 0.00238 0.00001 0.00136 0.0014 0.00408 0.01745 0.154
1 140.341 159.774 67.021 0.00817 0.00006 0.0043 0.0044 0.01289 0.03198 0.313
1 136.969 166.607 66.004 0.00923 0.00007 0.00507 0.00463 0.0152 0.03111 0.308
1 143.533 162.215 65.809 0.01101 0.00008 0.00647 0.00467 0.01941 0.05384 0.478
1 148.09 162.824 67.343 0.00762 0.00005 0.00467 0.00354 0.014 0.05428 0.497
1 142.729 162.408 65.476 0.00831 0.00006 0.00469 0.00419 0.01407 0.03485 0.365
1 136.358 176.595 65.75 0.00971 0.00007 0.00534 0.00478 0.01601 0.04978 0.483
1 120.08 139.71 111.208 0.00405 0.00003 0.0018 0.0022 0.0054 0.01706 0.152
1 112.014 588.518 107.024 0.00533 0.00005 0.00268 0.00329 0.00805 0.02448 0.226
1 110.793 128.101 107.316 0.00494 0.00004 0.0026 0.00283 0.0078 0.02442 0.216
1 110.707 122.611 105.007 0.00516 0.00005 0.00277 0.00289 0.00831 0.02215 0.206
1 112.876 148.826 106.981 0.005 0.00004 0.0027 0.00289 0.0081 0.03999 0.35
1 110.568 125.394 106.821 0.00462 0.00004 0.00226 0.0028 0.00677 0.02199 0.197
1 95.385 102.145 90.264 0.00608 0.00006 0.00331 0.00332 0.00994 0.03202 0.263
1 100.77 115.697 85.545 0.01038 0.0001 0.00622 0.00576 0.01865 0.03121 0.361
1 96.106 108.664 84.51 0.00694 0.00007 0.00389 0.00415 0.01168 0.04024 0.364
1 95.605 107.715 87.549 0.00702 0.00007 0.00428 0.00371 0.01283 0.03156 0.296
1 100.96 110.019 95.628 0.00606 0.00006 0.00351 0.00348 0.01053 0.02427 0.216
1 98.804 102.305 87.804 0.00432 0.00004 0.00247 0.00258 0.00742 0.02223 0.202
1 176.858 205.56 75.344 0.00747 0.00004 0.00418 0.0042 0.01254 0.04795 0.435
1 180.978 200.125 155.495 0.00406 0.00002 0.0022 0.00244 0.00659 0.03852 0.331
1 178.222 202.45 141.047 0.00321 0.00002 0.00163 0.00194 0.00488 0.03759 0.327
1 176.281 227.381 125.61 0.0052 0.00003 0.00287 0.00312 0.00862 0.06511 0.58
1 173.898 211.35 74.677 0.00448 0.00003 0.00237 0.00254 0.0071 0.06727 0.65
1 179.711 225.93 144.878 0.00709 0.00004 0.00391 0.00419 0.01172 0.04313 0.442
1 166.605 206.008 78.032 0.00742 0.00004 0.00387 0.00453 0.01161 0.0664 0.634
1 151.955 163.335 147.226 0.00419 0.00003 0.00224 0.00227 0.00672 0.07959 0.772
1 148.272 164.989 142.299 0.00459 0.00003 0.0025 0.00256 0.0075 0.0419 0.383
1 152.125 161.469 76.596 0.00382 0.00003 0.00191 0.00226 0.00574 0.05925 0.637
1 157.821 172.975 68.401 0.00358 0.00002 0.00196 0.00196 0.00587 0.03716 0.307
1 157.447 163.267 149.605 0.00369 0.00002 0.00201 0.00197 0.00602 0.03272 0.283
1 159.116 168.913 144.811 0.00342 0.00002 0.00178 0.00184 0.00535 0.03381 0.307
1 125.036 143.946 116.187 0.0128 0.0001 0.00743 0.00623 0.02228 0.03886 0.342
1 125.791 140.557 96.206 0.01378 0.00011 0.00826 0.00655 0.02478 0.04689 0.422
1 126.512 141.756 99.77 0.01936 0.00015 0.01159 0.0099 0.03476 0.06734 0.659
1 125.641 141.068 116.346 0.03316 0.00026 0.02144 0.01522 0.06433 0.09178 0.891
1 128.451 150.449 75.632 0.01551 0.00012 0.00905 0.00909 0.02716 0.0617 0.584
1 139.224 586.567 66.157 0.03011 0.00022 0.01854 0.01628 0.05563 0.09419 0.93
1 150.258 154.609 75.349 0.00248 0.00002 0.00105 0.00136 0.00315 0.01131 0.107
1 154.003 160.267 128.621 0.00183 0.00001 0.00076 0.001 0.00229 0.0103 0.094
1 149.689 160.368 133.608 0.00257 0.00002 0.00116 0.00134 0.00349 0.01346 0.126
1 155.078 163.736 144.148 0.00168 0.00001 0.00068 0.00092 0.00204 0.01064 0.097
1 151.884 157.765 133.751 0.00258 0.00002 0.00115 0.00122 0.00346 0.0145 0.137
1 151.989 157.339 132.857 0.00174 0.00001 0.00075 0.00096 0.00225 0.01024 0.093
1 193.03 208.9 80.297 0.00766 0.00004 0.0045 0.00389 0.01351 0.03044 0.275
1 200.714 223.982 89.686 0.00621 0.00003 0.00371 0.00337 0.01112 0.02286 0.207
1 208.519 220.315 199.02 0.00609 0.00003 0.00368 0.00339 0.01105 0.01761 0.155
1 204.664 221.3 189.621 0.00841 0.00004 0.00502 0.00485 0.01506 0.02378 0.21
1 210.141 232.706 185.258 0.00534 0.00003 0.00321 0.0028 0.00964 0.0168 0.149
1 206.327 226.355 92.02 0.00495 0.00002 0.00302 0.00246 0.00905 0.02105 0.209
1 151.872 492.892 69.085 0.00856 0.00006 0.00404 0.00385 0.01211 0.01843 0.235
1 158.219 442.557 71.948 0.00476 0.00003 0.00214 0.00207 0.00642 0.01458 0.148
1 170.756 450.247 79.032 0.00555 0.00003 0.00244 0.00261 0.00731 0.01725 0.175
1 178.285 442.824 82.063 0.00462 0.00003 0.00157 0.00194 0.00472 0.01279 0.129
1 217.116 233.481 93.978 0.00404 0.00002 0.00127 0.00128 0.00381 0.01299 0.124
1 128.94 479.697 88.251 0.00581 0.00005 0.00241 0.00314 0.00723 0.02008 0.221
1 176.824 215.293 83.961 0.0046 0.00003 0.00209 0.00221 0.00628 0.01169 0.117
1 138.19 203.522 83.34 0.00704 0.00005 0.00406 0.00398 0.01218 0.04479 0.441
1 182.018 197.173 79.187 0.00842 0.00005 0.00506 0.00449 0.01517 0.02503 0.231
1 156.239 195.107 79.82 0.00694 0.00004 0.00403 0.00395 0.01209 0.02343 0.224
1 145.174 198.109 80.637 0.00733 0.00005 0.00414 0.00422 0.01242 0.02362 0.233
1 138.145 197.238 81.114 0.00544 0.00004 0.00294 0.00327 0.00883 0.02791 0.246
1 166.888 198.966 79.512 0.00638 0.00004 0.00368 0.00351 0.01104 0.02857 0.257
1 119.031 127.533 109.216 0.0044 0.00004 0.00214 0.00192 0.00641 0.01033 0.098
1 120.078 126.632 105.667 0.0027 0.00002 0.00116 0.00135 0.00349 0.01022 0.09
1 120.289 128.143 100.209 0.00492 0.00004 0.00269 0.00238 0.00808 0.01412 0.125
1 120.256 125.306 104.773 0.00407 0.00003 0.00224 0.00205 0.00671 0.01516 0.138
1 119.056 125.213 86.795 0.00346 0.00003 0.00169 0.0017 0.00508 0.01201 0.106
1 118.747 123.723 109.836 0.00331 0.00003 0.00168 0.00171 0.00504 0.01043 0.099
1 106.516 112.777 93.105 0.00589 0.00006 0.00291 0.00319 0.00873 0.04932 0.441
1 110.453 127.611 105.554 0.00494 0.00004 0.00244 0.00315 0.00731 0.04128 0.379
1 113.4 133.344 107.816 0.00451 0.00004 0.00219 0.00283 0.00658 0.04879 0.431
1 113.166 130.27 100.673 0.00502 0.00004 0.00257 0.00312 0.00772 0.05279 0.476
1 112.239 126.609 104.095 0.00472 0.00004 0.00238 0.0029 0.00715 0.05643 0.517
1 116.15 131.731 109.815 0.00381 0.00003 0.00181 0.00232 0.00542 0.03026 0.267
1 170.368 268.796 79.543 0.00571 0.00003 0.00232 0.00269 0.00696 0.03273 0.281
1 208.083 253.792 91.802 0.00757 0.00004 0.00428 0.00428 0.01285 0.06725 0.571
1 198.458 219.29 148.691 0.00376 0.00002 0.00182 0.00215 0.00546 0.03527 0.297
1 202.805 231.508 86.232 0.0037 0.00002 0.00189 0.00211 0.00568 0.01997 0.18
1 202.544 241.35 164.168 0.00254 0.00001 0.001 0.00133 0.00301 0.02662 0.228
1 223.361 263.872 87.638 0.00352 0.00002 0.00169 0.00188 0.00506 0.02536 0.225
1 169.774 191.759 151.451 0.01568 0.00009 0.00863 0.00946 0.02589 0.08143 0.821
1 183.52 216.814 161.34 0.01466 0.00008 0.00849 0.00819 0.02546 0.0605 0.618
1 188.62 216.302 165.982 0.01719 0.00009 0.00996 0.01027 0.02987 0.07118 0.722
1 202.632 565.74 177.258 0.01627 0.00008 0.00919 0.00963 0.02756 0.0717 0.833
1 186.695 211.961 149.442 0.01872 0.0001 0.01075 0.01154 0.03225 0.0583 0.784
1 192.818 224.429 168.793 0.03107 0.00016 0.018 0.01958 0.05401 0.11908 1.302
1 198.116 233.099 174.478 0.02714 0.00014 0.01568 0.01699 0.04705 0.08684 1.018
1 121.345 139.644 98.25 0.00684 0.00006 0.00388 0.00332 0.01164 0.02534 0.241
1 119.1 128.442 88.833 0.00692 0.00006 0.00393 0.003 0.01179 0.02682 0.236
1 117.87 127.349 95.654 0.00647 0.00005 0.00356 0.003 0.01067 0.03087 0.276
1 122.336 142.369 94.794 0.00727 0.00006 0.00415 0.00339 0.01246 0.02293 0.223
1 117.963 134.209 100.757 0.01813 0.00015 0.01117 0.00718 0.03351 0.04912 0.438
1 126.144 154.284 97.543 0.00975 0.00008 0.00593 0.00454 0.01778 0.02852 0.266
1 127.93 138.752 112.173 0.00605 0.00005 0.00321 0.00318 0.00962 0.03235 0.339
1 114.238 124.393 77.022 0.00581 0.00005 0.00299 0.00316 0.00896 0.04009 0.406
1 115.322 135.738 107.802 0.00619 0.00005 0.00352 0.00329 0.01057 0.03273 0.325
1 114.554 126.778 91.121 0.00651 0.00006 0.00366 0.0034 0.01097 0.03658 0.369
1 112.15 131.669 97.527 0.00519 0.00005 0.00291 0.00284 0.00873 0.01756 0.155
1 102.273 142.83 85.902 0.00907 0.00009 0.00493 0.00461 0.0148 0.02814 0.272
0 236.2 244.663 102.137 0.00277 0.00001 0.00154 0.00153 0.00462 0.02448 0.217
0 237.323 243.709 229.256 0.00303 0.00001 0.00173 0.00159 0.00519 0.01242 0.116
0 260.105 264.919 237.303 0.00339 0.00001 0.00205 0.00186 0.00616 0.0203 0.197
0 197.569 217.627 90.794 0.00803 0.00004 0.0049 0.00448 0.0147 0.02177 0.189
0 240.301 245.135 219.783 0.00517 0.00002 0.00316 0.00283 0.00949 0.02018 0.212
0 244.99 272.21 239.17 0.00451 0.00002 0.00279 0.00237 0.00837 0.01897 0.181
0 112.547 133.374 105.715 0.00355 0.00003 0.00166 0.0019 0.00499 0.01358 0.129
0 110.739 113.597 100.139 0.00356 0.00003 0.0017 0.002 0.0051 0.01484 0.133
0 113.715 116.443 96.913 0.00349 0.00003 0.00171 0.00203 0.00514 0.01472 0.133
0 117.004 144.466 99.923 0.00353 0.00003 0.00176 0.00218 0.00528 0.01657 0.145
0 115.38 123.109 108.634 0.00332 0.00003 0.0016 0.00199 0.0048 0.01503 0.137
0 116.388 129.038 108.97 0.00346 0.00003 0.00169 0.00213 0.00507 0.01725 0.155
1 151.737 190.204 129.859 0.00314 0.00002 0.00135 0.00162 0.00406 0.01469 0.132
1 148.79 158.359 138.99 0.00309 0.00002 0.00152 0.00186 0.00456 0.01574 0.142
1 148.143 155.982 135.041 0.00392 0.00003 0.00204 0.00231 0.00612 0.0145 0.131
1 150.44 163.441 144.736 0.00396 0.00003 0.00206 0.00233 0.00619 0.02551 0.237
1 148.462 161.078 141.998 0.00397 0.00003 0.00202 0.00235 0.00605 0.01831 0.163
1 149.818 163.417 144.786 0.00336 0.00002 0.00174 0.00198 0.00521 0.02145 0.198
0 117.226 123.925 106.656 0.00417 0.00004 0.00186 0.0027 0.00558 0.01909 0.171
0 116.848 217.552 99.503 0.00531 0.00005 0.0026 0.00346 0.0078 0.01795 0.163
0 116.286 177.291 96.983 0.00314 0.00003 0.00134 0.00192 0.00403 0.01564 0.136
0 116.556 592.03 86.228 0.00496 0.00004 0.00254 0.00263 0.00762 0.0166 0.154
0 116.342 581.289 94.246 0.00267 0.00002 0.00115 0.00148 0.00345 0.013 0.117
0 114.563 119.167 86.647 0.00327 0.00003 0.00146 0.00184 0.00439 0.01185 0.106
0 201.774 262.707 78.228 0.00694 0.00003 0.00412 0.00396 0.01235 0.02574 0.255
0 174.188 230.978 94.261 0.00459 0.00003 0.00263 0.00259 0.0079 0.04087 0.405
0 209.516 253.017 89.488 0.00564 0.00003 0.00331 0.00292 0.00994 0.02751 0.263
0 174.688 240.005 74.287 0.0136 0.00008 0.00624 0.00564 0.01873 0.02308 0.256
0 198.764 396.961 74.904 0.0074 0.00004 0.0037 0.0039 0.01109 0.02296 0.241
0 214.289 260.277 77.973 0.00567 0.00003 0.00295 0.00317 0.00885 0.01884 0.19




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time21 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 21 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232113&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]21 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232113&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232113&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 time21 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
status[t] = + 1.39731 -0.00304006`MDVP:Fo(Hz)`[t] -0.000253199`MDVP:Fhi(Hz)`[t] -0.00232691`MDVP:Flo(Hz)`[t] -65.7106`MDVP:Jitter(%)`[t] -3241.38`MDVP:Jitter(Abs)`[t] + 2585.71`MDVP:RAP`[t] + 49.4266`MDVP:PPQ`[t] -828.72`Jitter:DDP`[t] + 8.93725`MDVP:Shimmer`[t] -0.238045`MDVP:Shimmer(dB)`[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
status[t] =  +  1.39731 -0.00304006`MDVP:Fo(Hz)`[t] -0.000253199`MDVP:Fhi(Hz)`[t] -0.00232691`MDVP:Flo(Hz)`[t] -65.7106`MDVP:Jitter(%)`[t] -3241.38`MDVP:Jitter(Abs)`[t] +  2585.71`MDVP:RAP`[t] +  49.4266`MDVP:PPQ`[t] -828.72`Jitter:DDP`[t] +  8.93725`MDVP:Shimmer`[t] -0.238045`MDVP:Shimmer(dB)`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232113&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]status[t] =  +  1.39731 -0.00304006`MDVP:Fo(Hz)`[t] -0.000253199`MDVP:Fhi(Hz)`[t] -0.00232691`MDVP:Flo(Hz)`[t] -65.7106`MDVP:Jitter(%)`[t] -3241.38`MDVP:Jitter(Abs)`[t] +  2585.71`MDVP:RAP`[t] +  49.4266`MDVP:PPQ`[t] -828.72`Jitter:DDP`[t] +  8.93725`MDVP:Shimmer`[t] -0.238045`MDVP:Shimmer(dB)`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232113&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232113&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] = + 1.39731 -0.00304006`MDVP:Fo(Hz)`[t] -0.000253199`MDVP:Fhi(Hz)`[t] -0.00232691`MDVP:Flo(Hz)`[t] -65.7106`MDVP:Jitter(%)`[t] -3241.38`MDVP:Jitter(Abs)`[t] + 2585.71`MDVP:RAP`[t] + 49.4266`MDVP:PPQ`[t] -828.72`Jitter:DDP`[t] + 8.93725`MDVP:Shimmer`[t] -0.238045`MDVP:Shimmer(dB)`[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.397310.2104726.6393.44037e-101.72019e-10
`MDVP:Fo(Hz)`-0.003040060.0013361-2.2750.02403940.0120197
`MDVP:Fhi(Hz)`-0.0002531990.000340751-0.74310.4583920.229196
`MDVP:Flo(Hz)`-0.002326910.000836129-2.7830.005948740.00297437
`MDVP:Jitter(%)`-65.710663.3523-1.0370.3009920.150496
`MDVP:Jitter(Abs)`-3241.383947.06-0.82120.4125880.206294
`MDVP:RAP`2585.7110143.30.25490.7990710.399536
`MDVP:PPQ`49.426652.6120.93950.3487290.174365
`Jitter:DDP`-828.723381.41-0.24510.8066670.403333
`MDVP:Shimmer`8.9372511.01560.81130.4182280.209114
`MDVP:Shimmer(dB)`-0.2380451.18726-0.20050.8413110.420655

\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) & 1.39731 & 0.210472 & 6.639 & 3.44037e-10 & 1.72019e-10 \tabularnewline
`MDVP:Fo(Hz)` & -0.00304006 & 0.0013361 & -2.275 & 0.0240394 & 0.0120197 \tabularnewline
`MDVP:Fhi(Hz)` & -0.000253199 & 0.000340751 & -0.7431 & 0.458392 & 0.229196 \tabularnewline
`MDVP:Flo(Hz)` & -0.00232691 & 0.000836129 & -2.783 & 0.00594874 & 0.00297437 \tabularnewline
`MDVP:Jitter(%)` & -65.7106 & 63.3523 & -1.037 & 0.300992 & 0.150496 \tabularnewline
`MDVP:Jitter(Abs)` & -3241.38 & 3947.06 & -0.8212 & 0.412588 & 0.206294 \tabularnewline
`MDVP:RAP` & 2585.71 & 10143.3 & 0.2549 & 0.799071 & 0.399536 \tabularnewline
`MDVP:PPQ` & 49.4266 & 52.612 & 0.9395 & 0.348729 & 0.174365 \tabularnewline
`Jitter:DDP` & -828.72 & 3381.41 & -0.2451 & 0.806667 & 0.403333 \tabularnewline
`MDVP:Shimmer` & 8.93725 & 11.0156 & 0.8113 & 0.418228 & 0.209114 \tabularnewline
`MDVP:Shimmer(dB)` & -0.238045 & 1.18726 & -0.2005 & 0.841311 & 0.420655 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232113&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]1.39731[/C][C]0.210472[/C][C]6.639[/C][C]3.44037e-10[/C][C]1.72019e-10[/C][/ROW]
[ROW][C]`MDVP:Fo(Hz)`[/C][C]-0.00304006[/C][C]0.0013361[/C][C]-2.275[/C][C]0.0240394[/C][C]0.0120197[/C][/ROW]
[ROW][C]`MDVP:Fhi(Hz)`[/C][C]-0.000253199[/C][C]0.000340751[/C][C]-0.7431[/C][C]0.458392[/C][C]0.229196[/C][/ROW]
[ROW][C]`MDVP:Flo(Hz)`[/C][C]-0.00232691[/C][C]0.000836129[/C][C]-2.783[/C][C]0.00594874[/C][C]0.00297437[/C][/ROW]
[ROW][C]`MDVP:Jitter(%)`[/C][C]-65.7106[/C][C]63.3523[/C][C]-1.037[/C][C]0.300992[/C][C]0.150496[/C][/ROW]
[ROW][C]`MDVP:Jitter(Abs)`[/C][C]-3241.38[/C][C]3947.06[/C][C]-0.8212[/C][C]0.412588[/C][C]0.206294[/C][/ROW]
[ROW][C]`MDVP:RAP`[/C][C]2585.71[/C][C]10143.3[/C][C]0.2549[/C][C]0.799071[/C][C]0.399536[/C][/ROW]
[ROW][C]`MDVP:PPQ`[/C][C]49.4266[/C][C]52.612[/C][C]0.9395[/C][C]0.348729[/C][C]0.174365[/C][/ROW]
[ROW][C]`Jitter:DDP`[/C][C]-828.72[/C][C]3381.41[/C][C]-0.2451[/C][C]0.806667[/C][C]0.403333[/C][/ROW]
[ROW][C]`MDVP:Shimmer`[/C][C]8.93725[/C][C]11.0156[/C][C]0.8113[/C][C]0.418228[/C][C]0.209114[/C][/ROW]
[ROW][C]`MDVP:Shimmer(dB)`[/C][C]-0.238045[/C][C]1.18726[/C][C]-0.2005[/C][C]0.841311[/C][C]0.420655[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232113&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232113&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)1.397310.2104726.6393.44037e-101.72019e-10
`MDVP:Fo(Hz)`-0.003040060.0013361-2.2750.02403940.0120197
`MDVP:Fhi(Hz)`-0.0002531990.000340751-0.74310.4583920.229196
`MDVP:Flo(Hz)`-0.002326910.000836129-2.7830.005948740.00297437
`MDVP:Jitter(%)`-65.710663.3523-1.0370.3009920.150496
`MDVP:Jitter(Abs)`-3241.383947.06-0.82120.4125880.206294
`MDVP:RAP`2585.7110143.30.25490.7990710.399536
`MDVP:PPQ`49.426652.6120.93950.3487290.174365
`Jitter:DDP`-828.723381.41-0.24510.8066670.403333
`MDVP:Shimmer`8.9372511.01560.81130.4182280.209114
`MDVP:Shimmer(dB)`-0.2380451.18726-0.20050.8413110.420655







Multiple Linear Regression - Regression Statistics
Multiple R0.543796
R-squared0.295714
Adjusted R-squared0.257438
F-TEST (value)7.72575
F-TEST (DF numerator)10
F-TEST (DF denominator)184
p-value2.77561e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.372158
Sum Squared Residuals25.4843

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.543796 \tabularnewline
R-squared & 0.295714 \tabularnewline
Adjusted R-squared & 0.257438 \tabularnewline
F-TEST (value) & 7.72575 \tabularnewline
F-TEST (DF numerator) & 10 \tabularnewline
F-TEST (DF denominator) & 184 \tabularnewline
p-value & 2.77561e-10 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.372158 \tabularnewline
Sum Squared Residuals & 25.4843 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232113&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.543796[/C][/ROW]
[ROW][C]R-squared[/C][C]0.295714[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.257438[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]7.72575[/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]2.77561e-10[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.372158[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]25.4843[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232113&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232113&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 R0.543796
R-squared0.295714
Adjusted R-squared0.257438
F-TEST (value)7.72575
F-TEST (DF numerator)10
F-TEST (DF denominator)184
p-value2.77561e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.372158
Sum Squared Residuals25.4843







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
111.01606-0.0160645
211.04172-0.0417199
311.04035-0.0403496
411.02248-0.0224792
511.0787-0.0787028
610.9889370.0110633
710.7699480.230052
810.8613990.138601
910.8918690.108131
1010.9536960.046304
1110.9307070.0692929
1210.962660.0373401
1310.6484050.351595
1410.7660730.233927
1510.7683980.231602
1610.7377980.262202
1710.6907330.309267
1810.7282610.271739
1911.01812-0.0181242
2010.7165470.283453
2110.9231580.076842
2210.9358670.0641334
2310.8981220.101878
2410.8447580.155242
2510.7009080.299092
2610.9818050.0181954
2710.748640.25136
2810.8021420.197858
2910.7814050.218595
3010.7606970.239303
3100.399918-0.399918
3200.371974-0.371974
3300.38434-0.38434
3400.341578-0.341578
3500.326544-0.326544
3600.364512-0.364512
3710.5696530.430347
3810.5558240.444176
3910.4710530.528947
4010.4701790.529821
4110.4513740.548626
4210.4946170.505383
4300.236927-0.236927
4400.213119-0.213119
4500.15874-0.15874
4600.182189-0.182189
4700.176274-0.176274
4800.21992-0.21992
4900.628624-0.628624
5000.650582-0.650582
5100.710425-0.710425
5200.644375-0.644375
5300.679146-0.679146
5400.664773-0.664773
5510.8443270.155673
5610.8393110.160689
5710.9028220.0971782
5810.7358680.264132
5910.753420.24658
6010.7318240.268176
6100.568167-0.568167
6200.589577-0.589577
6300.304275-0.304275
6400.249895-0.249895
6500.226413-0.226413
6600.512246-0.512246
6710.9080440.0919559
6810.8982990.101701
6911.02626-0.0262622
7011.10135-0.101346
7110.9279410.0720588
7211.02617-0.0261692
7310.7789570.221043
7410.7325270.267473
7510.8896090.110391
7610.8517450.148255
7710.9950410.00495852
7810.8689220.131078
7910.9863090.0136914
8010.9615660.0384344
8111.05511-0.0551131
8211.01681-0.0168099
8310.9342290.0657714
8410.9689070.0310934
8510.9604640.0395364
8610.7163830.283617
8710.7248320.275168
8810.9480770.0519227
8911.06598-0.0659837
9010.7459750.254025
9111.09152-0.0915231
9211.04158-0.0415821
9310.8335110.166489
9411.03892-0.0389208
9510.97380.0262003
9610.7527160.247284
9710.7332420.266758
9810.8668970.133103
9910.958020.0419804
10011.08262-0.0826181
10111.17362-0.173623
10211.1389-0.138905
10311.24235-0.242349
10410.7456070.254393
10510.6230740.376926
10610.6207680.379232
10710.5913480.408652
10810.6135130.386487
10910.6310120.368988
11010.7762860.223714
11110.7156270.284373
11210.3931890.606811
11310.497560.50244
11410.3846660.615334
11510.6774230.322577
11610.6026150.397385
11710.637240.36276
11810.6110620.388938
11910.4789050.521095
12010.4054420.594558
12110.6566290.343371
12210.595990.40401
12311.00328-0.00327894
12410.7970610.202939
12510.8540020.145998
12610.8507890.149211
12710.8884230.111577
12810.8396590.160341
12910.7154530.284547
13010.755910.24409
13110.7866210.213379
13210.8267550.173245
13310.8031840.196816
13410.7560740.243926
13511.02994-0.0299372
13611.01492-0.0149239
13711.02497-0.0249681
13811.08676-0.086765
13911.09524-0.0952445
14010.9177470.0822526
14110.7433190.256681
14210.9541950.0458055
14310.6125350.387465
14410.6333210.366679
14510.4797670.520233
14610.5939480.406052
14711.01715-0.0171478
14810.8382890.161711
14910.9332850.0667149
15010.738780.26122
15110.8490280.150972
15211.30694-0.306936
15311.01898-0.0189812
15410.8399360.160064
15510.8698310.130169
15610.9180880.0819119
15710.8208160.179184
15810.894280.10572
15910.8623680.137632
16010.8460640.153936
16111.01922-0.019224
16210.9125780.0874218
16310.9624380.0375621
16410.8430820.156918
16510.8597090.140291
16600.56126-0.56126
16700.183347-0.183347
16800.154395-0.154395
16900.731792-0.731792
17000.264796-0.264796
17100.187227-0.187227
17200.786421-0.786421
17300.836763-0.836763
17400.83222-0.83222
17500.83985-0.83985
17600.806546-0.806546
17700.823434-0.823434
17810.6205740.379426
17910.663710.33629
18010.6540570.345943
18110.6878560.312144
18210.667030.33297
18310.7018960.298104
18400.806229-0.806229
18500.795938-0.795938
18600.797073-0.797073
18700.73139-0.73139
18800.712831-0.712831
18900.813797-0.813797
19000.765582-0.765582
19100.841491-0.841491
19200.669025-0.669025
19300.516632-0.516632
19400.619545-0.619545
19500.602198-0.602198

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1 & 1.01606 & -0.0160645 \tabularnewline
2 & 1 & 1.04172 & -0.0417199 \tabularnewline
3 & 1 & 1.04035 & -0.0403496 \tabularnewline
4 & 1 & 1.02248 & -0.0224792 \tabularnewline
5 & 1 & 1.0787 & -0.0787028 \tabularnewline
6 & 1 & 0.988937 & 0.0110633 \tabularnewline
7 & 1 & 0.769948 & 0.230052 \tabularnewline
8 & 1 & 0.861399 & 0.138601 \tabularnewline
9 & 1 & 0.891869 & 0.108131 \tabularnewline
10 & 1 & 0.953696 & 0.046304 \tabularnewline
11 & 1 & 0.930707 & 0.0692929 \tabularnewline
12 & 1 & 0.96266 & 0.0373401 \tabularnewline
13 & 1 & 0.648405 & 0.351595 \tabularnewline
14 & 1 & 0.766073 & 0.233927 \tabularnewline
15 & 1 & 0.768398 & 0.231602 \tabularnewline
16 & 1 & 0.737798 & 0.262202 \tabularnewline
17 & 1 & 0.690733 & 0.309267 \tabularnewline
18 & 1 & 0.728261 & 0.271739 \tabularnewline
19 & 1 & 1.01812 & -0.0181242 \tabularnewline
20 & 1 & 0.716547 & 0.283453 \tabularnewline
21 & 1 & 0.923158 & 0.076842 \tabularnewline
22 & 1 & 0.935867 & 0.0641334 \tabularnewline
23 & 1 & 0.898122 & 0.101878 \tabularnewline
24 & 1 & 0.844758 & 0.155242 \tabularnewline
25 & 1 & 0.700908 & 0.299092 \tabularnewline
26 & 1 & 0.981805 & 0.0181954 \tabularnewline
27 & 1 & 0.74864 & 0.25136 \tabularnewline
28 & 1 & 0.802142 & 0.197858 \tabularnewline
29 & 1 & 0.781405 & 0.218595 \tabularnewline
30 & 1 & 0.760697 & 0.239303 \tabularnewline
31 & 0 & 0.399918 & -0.399918 \tabularnewline
32 & 0 & 0.371974 & -0.371974 \tabularnewline
33 & 0 & 0.38434 & -0.38434 \tabularnewline
34 & 0 & 0.341578 & -0.341578 \tabularnewline
35 & 0 & 0.326544 & -0.326544 \tabularnewline
36 & 0 & 0.364512 & -0.364512 \tabularnewline
37 & 1 & 0.569653 & 0.430347 \tabularnewline
38 & 1 & 0.555824 & 0.444176 \tabularnewline
39 & 1 & 0.471053 & 0.528947 \tabularnewline
40 & 1 & 0.470179 & 0.529821 \tabularnewline
41 & 1 & 0.451374 & 0.548626 \tabularnewline
42 & 1 & 0.494617 & 0.505383 \tabularnewline
43 & 0 & 0.236927 & -0.236927 \tabularnewline
44 & 0 & 0.213119 & -0.213119 \tabularnewline
45 & 0 & 0.15874 & -0.15874 \tabularnewline
46 & 0 & 0.182189 & -0.182189 \tabularnewline
47 & 0 & 0.176274 & -0.176274 \tabularnewline
48 & 0 & 0.21992 & -0.21992 \tabularnewline
49 & 0 & 0.628624 & -0.628624 \tabularnewline
50 & 0 & 0.650582 & -0.650582 \tabularnewline
51 & 0 & 0.710425 & -0.710425 \tabularnewline
52 & 0 & 0.644375 & -0.644375 \tabularnewline
53 & 0 & 0.679146 & -0.679146 \tabularnewline
54 & 0 & 0.664773 & -0.664773 \tabularnewline
55 & 1 & 0.844327 & 0.155673 \tabularnewline
56 & 1 & 0.839311 & 0.160689 \tabularnewline
57 & 1 & 0.902822 & 0.0971782 \tabularnewline
58 & 1 & 0.735868 & 0.264132 \tabularnewline
59 & 1 & 0.75342 & 0.24658 \tabularnewline
60 & 1 & 0.731824 & 0.268176 \tabularnewline
61 & 0 & 0.568167 & -0.568167 \tabularnewline
62 & 0 & 0.589577 & -0.589577 \tabularnewline
63 & 0 & 0.304275 & -0.304275 \tabularnewline
64 & 0 & 0.249895 & -0.249895 \tabularnewline
65 & 0 & 0.226413 & -0.226413 \tabularnewline
66 & 0 & 0.512246 & -0.512246 \tabularnewline
67 & 1 & 0.908044 & 0.0919559 \tabularnewline
68 & 1 & 0.898299 & 0.101701 \tabularnewline
69 & 1 & 1.02626 & -0.0262622 \tabularnewline
70 & 1 & 1.10135 & -0.101346 \tabularnewline
71 & 1 & 0.927941 & 0.0720588 \tabularnewline
72 & 1 & 1.02617 & -0.0261692 \tabularnewline
73 & 1 & 0.778957 & 0.221043 \tabularnewline
74 & 1 & 0.732527 & 0.267473 \tabularnewline
75 & 1 & 0.889609 & 0.110391 \tabularnewline
76 & 1 & 0.851745 & 0.148255 \tabularnewline
77 & 1 & 0.995041 & 0.00495852 \tabularnewline
78 & 1 & 0.868922 & 0.131078 \tabularnewline
79 & 1 & 0.986309 & 0.0136914 \tabularnewline
80 & 1 & 0.961566 & 0.0384344 \tabularnewline
81 & 1 & 1.05511 & -0.0551131 \tabularnewline
82 & 1 & 1.01681 & -0.0168099 \tabularnewline
83 & 1 & 0.934229 & 0.0657714 \tabularnewline
84 & 1 & 0.968907 & 0.0310934 \tabularnewline
85 & 1 & 0.960464 & 0.0395364 \tabularnewline
86 & 1 & 0.716383 & 0.283617 \tabularnewline
87 & 1 & 0.724832 & 0.275168 \tabularnewline
88 & 1 & 0.948077 & 0.0519227 \tabularnewline
89 & 1 & 1.06598 & -0.0659837 \tabularnewline
90 & 1 & 0.745975 & 0.254025 \tabularnewline
91 & 1 & 1.09152 & -0.0915231 \tabularnewline
92 & 1 & 1.04158 & -0.0415821 \tabularnewline
93 & 1 & 0.833511 & 0.166489 \tabularnewline
94 & 1 & 1.03892 & -0.0389208 \tabularnewline
95 & 1 & 0.9738 & 0.0262003 \tabularnewline
96 & 1 & 0.752716 & 0.247284 \tabularnewline
97 & 1 & 0.733242 & 0.266758 \tabularnewline
98 & 1 & 0.866897 & 0.133103 \tabularnewline
99 & 1 & 0.95802 & 0.0419804 \tabularnewline
100 & 1 & 1.08262 & -0.0826181 \tabularnewline
101 & 1 & 1.17362 & -0.173623 \tabularnewline
102 & 1 & 1.1389 & -0.138905 \tabularnewline
103 & 1 & 1.24235 & -0.242349 \tabularnewline
104 & 1 & 0.745607 & 0.254393 \tabularnewline
105 & 1 & 0.623074 & 0.376926 \tabularnewline
106 & 1 & 0.620768 & 0.379232 \tabularnewline
107 & 1 & 0.591348 & 0.408652 \tabularnewline
108 & 1 & 0.613513 & 0.386487 \tabularnewline
109 & 1 & 0.631012 & 0.368988 \tabularnewline
110 & 1 & 0.776286 & 0.223714 \tabularnewline
111 & 1 & 0.715627 & 0.284373 \tabularnewline
112 & 1 & 0.393189 & 0.606811 \tabularnewline
113 & 1 & 0.49756 & 0.50244 \tabularnewline
114 & 1 & 0.384666 & 0.615334 \tabularnewline
115 & 1 & 0.677423 & 0.322577 \tabularnewline
116 & 1 & 0.602615 & 0.397385 \tabularnewline
117 & 1 & 0.63724 & 0.36276 \tabularnewline
118 & 1 & 0.611062 & 0.388938 \tabularnewline
119 & 1 & 0.478905 & 0.521095 \tabularnewline
120 & 1 & 0.405442 & 0.594558 \tabularnewline
121 & 1 & 0.656629 & 0.343371 \tabularnewline
122 & 1 & 0.59599 & 0.40401 \tabularnewline
123 & 1 & 1.00328 & -0.00327894 \tabularnewline
124 & 1 & 0.797061 & 0.202939 \tabularnewline
125 & 1 & 0.854002 & 0.145998 \tabularnewline
126 & 1 & 0.850789 & 0.149211 \tabularnewline
127 & 1 & 0.888423 & 0.111577 \tabularnewline
128 & 1 & 0.839659 & 0.160341 \tabularnewline
129 & 1 & 0.715453 & 0.284547 \tabularnewline
130 & 1 & 0.75591 & 0.24409 \tabularnewline
131 & 1 & 0.786621 & 0.213379 \tabularnewline
132 & 1 & 0.826755 & 0.173245 \tabularnewline
133 & 1 & 0.803184 & 0.196816 \tabularnewline
134 & 1 & 0.756074 & 0.243926 \tabularnewline
135 & 1 & 1.02994 & -0.0299372 \tabularnewline
136 & 1 & 1.01492 & -0.0149239 \tabularnewline
137 & 1 & 1.02497 & -0.0249681 \tabularnewline
138 & 1 & 1.08676 & -0.086765 \tabularnewline
139 & 1 & 1.09524 & -0.0952445 \tabularnewline
140 & 1 & 0.917747 & 0.0822526 \tabularnewline
141 & 1 & 0.743319 & 0.256681 \tabularnewline
142 & 1 & 0.954195 & 0.0458055 \tabularnewline
143 & 1 & 0.612535 & 0.387465 \tabularnewline
144 & 1 & 0.633321 & 0.366679 \tabularnewline
145 & 1 & 0.479767 & 0.520233 \tabularnewline
146 & 1 & 0.593948 & 0.406052 \tabularnewline
147 & 1 & 1.01715 & -0.0171478 \tabularnewline
148 & 1 & 0.838289 & 0.161711 \tabularnewline
149 & 1 & 0.933285 & 0.0667149 \tabularnewline
150 & 1 & 0.73878 & 0.26122 \tabularnewline
151 & 1 & 0.849028 & 0.150972 \tabularnewline
152 & 1 & 1.30694 & -0.306936 \tabularnewline
153 & 1 & 1.01898 & -0.0189812 \tabularnewline
154 & 1 & 0.839936 & 0.160064 \tabularnewline
155 & 1 & 0.869831 & 0.130169 \tabularnewline
156 & 1 & 0.918088 & 0.0819119 \tabularnewline
157 & 1 & 0.820816 & 0.179184 \tabularnewline
158 & 1 & 0.89428 & 0.10572 \tabularnewline
159 & 1 & 0.862368 & 0.137632 \tabularnewline
160 & 1 & 0.846064 & 0.153936 \tabularnewline
161 & 1 & 1.01922 & -0.019224 \tabularnewline
162 & 1 & 0.912578 & 0.0874218 \tabularnewline
163 & 1 & 0.962438 & 0.0375621 \tabularnewline
164 & 1 & 0.843082 & 0.156918 \tabularnewline
165 & 1 & 0.859709 & 0.140291 \tabularnewline
166 & 0 & 0.56126 & -0.56126 \tabularnewline
167 & 0 & 0.183347 & -0.183347 \tabularnewline
168 & 0 & 0.154395 & -0.154395 \tabularnewline
169 & 0 & 0.731792 & -0.731792 \tabularnewline
170 & 0 & 0.264796 & -0.264796 \tabularnewline
171 & 0 & 0.187227 & -0.187227 \tabularnewline
172 & 0 & 0.786421 & -0.786421 \tabularnewline
173 & 0 & 0.836763 & -0.836763 \tabularnewline
174 & 0 & 0.83222 & -0.83222 \tabularnewline
175 & 0 & 0.83985 & -0.83985 \tabularnewline
176 & 0 & 0.806546 & -0.806546 \tabularnewline
177 & 0 & 0.823434 & -0.823434 \tabularnewline
178 & 1 & 0.620574 & 0.379426 \tabularnewline
179 & 1 & 0.66371 & 0.33629 \tabularnewline
180 & 1 & 0.654057 & 0.345943 \tabularnewline
181 & 1 & 0.687856 & 0.312144 \tabularnewline
182 & 1 & 0.66703 & 0.33297 \tabularnewline
183 & 1 & 0.701896 & 0.298104 \tabularnewline
184 & 0 & 0.806229 & -0.806229 \tabularnewline
185 & 0 & 0.795938 & -0.795938 \tabularnewline
186 & 0 & 0.797073 & -0.797073 \tabularnewline
187 & 0 & 0.73139 & -0.73139 \tabularnewline
188 & 0 & 0.712831 & -0.712831 \tabularnewline
189 & 0 & 0.813797 & -0.813797 \tabularnewline
190 & 0 & 0.765582 & -0.765582 \tabularnewline
191 & 0 & 0.841491 & -0.841491 \tabularnewline
192 & 0 & 0.669025 & -0.669025 \tabularnewline
193 & 0 & 0.516632 & -0.516632 \tabularnewline
194 & 0 & 0.619545 & -0.619545 \tabularnewline
195 & 0 & 0.602198 & -0.602198 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232113&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]1[/C][C]1.01606[/C][C]-0.0160645[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]1.04172[/C][C]-0.0417199[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]1.04035[/C][C]-0.0403496[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]1.02248[/C][C]-0.0224792[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]1.0787[/C][C]-0.0787028[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.988937[/C][C]0.0110633[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.769948[/C][C]0.230052[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.861399[/C][C]0.138601[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.891869[/C][C]0.108131[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]0.953696[/C][C]0.046304[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]0.930707[/C][C]0.0692929[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]0.96266[/C][C]0.0373401[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.648405[/C][C]0.351595[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]0.766073[/C][C]0.233927[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.768398[/C][C]0.231602[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]0.737798[/C][C]0.262202[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.690733[/C][C]0.309267[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]0.728261[/C][C]0.271739[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]1.01812[/C][C]-0.0181242[/C][/ROW]
[ROW][C]20[/C][C]1[/C][C]0.716547[/C][C]0.283453[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]0.923158[/C][C]0.076842[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.935867[/C][C]0.0641334[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]0.898122[/C][C]0.101878[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.844758[/C][C]0.155242[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.700908[/C][C]0.299092[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.981805[/C][C]0.0181954[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.74864[/C][C]0.25136[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]0.802142[/C][C]0.197858[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.781405[/C][C]0.218595[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]0.760697[/C][C]0.239303[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0.399918[/C][C]-0.399918[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0.371974[/C][C]-0.371974[/C][/ROW]
[ROW][C]33[/C][C]0[/C][C]0.38434[/C][C]-0.38434[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]0.341578[/C][C]-0.341578[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0.326544[/C][C]-0.326544[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0.364512[/C][C]-0.364512[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]0.569653[/C][C]0.430347[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.555824[/C][C]0.444176[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.471053[/C][C]0.528947[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]0.470179[/C][C]0.529821[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.451374[/C][C]0.548626[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.494617[/C][C]0.505383[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0.236927[/C][C]-0.236927[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0.213119[/C][C]-0.213119[/C][/ROW]
[ROW][C]45[/C][C]0[/C][C]0.15874[/C][C]-0.15874[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0.182189[/C][C]-0.182189[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0.176274[/C][C]-0.176274[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]0.21992[/C][C]-0.21992[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0.628624[/C][C]-0.628624[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0.650582[/C][C]-0.650582[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]0.710425[/C][C]-0.710425[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0.644375[/C][C]-0.644375[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0.679146[/C][C]-0.679146[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0.664773[/C][C]-0.664773[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.844327[/C][C]0.155673[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]0.839311[/C][C]0.160689[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]0.902822[/C][C]0.0971782[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.735868[/C][C]0.264132[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]0.75342[/C][C]0.24658[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.731824[/C][C]0.268176[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0.568167[/C][C]-0.568167[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0.589577[/C][C]-0.589577[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0.304275[/C][C]-0.304275[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0.249895[/C][C]-0.249895[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0.226413[/C][C]-0.226413[/C][/ROW]
[ROW][C]66[/C][C]0[/C][C]0.512246[/C][C]-0.512246[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.908044[/C][C]0.0919559[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]0.898299[/C][C]0.101701[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]1.02626[/C][C]-0.0262622[/C][/ROW]
[ROW][C]70[/C][C]1[/C][C]1.10135[/C][C]-0.101346[/C][/ROW]
[ROW][C]71[/C][C]1[/C][C]0.927941[/C][C]0.0720588[/C][/ROW]
[ROW][C]72[/C][C]1[/C][C]1.02617[/C][C]-0.0261692[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]0.778957[/C][C]0.221043[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.732527[/C][C]0.267473[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]0.889609[/C][C]0.110391[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]0.851745[/C][C]0.148255[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]0.995041[/C][C]0.00495852[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]0.868922[/C][C]0.131078[/C][/ROW]
[ROW][C]79[/C][C]1[/C][C]0.986309[/C][C]0.0136914[/C][/ROW]
[ROW][C]80[/C][C]1[/C][C]0.961566[/C][C]0.0384344[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]1.05511[/C][C]-0.0551131[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]1.01681[/C][C]-0.0168099[/C][/ROW]
[ROW][C]83[/C][C]1[/C][C]0.934229[/C][C]0.0657714[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]0.968907[/C][C]0.0310934[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]0.960464[/C][C]0.0395364[/C][/ROW]
[ROW][C]86[/C][C]1[/C][C]0.716383[/C][C]0.283617[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.724832[/C][C]0.275168[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]0.948077[/C][C]0.0519227[/C][/ROW]
[ROW][C]89[/C][C]1[/C][C]1.06598[/C][C]-0.0659837[/C][/ROW]
[ROW][C]90[/C][C]1[/C][C]0.745975[/C][C]0.254025[/C][/ROW]
[ROW][C]91[/C][C]1[/C][C]1.09152[/C][C]-0.0915231[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]1.04158[/C][C]-0.0415821[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.833511[/C][C]0.166489[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]1.03892[/C][C]-0.0389208[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]0.9738[/C][C]0.0262003[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.752716[/C][C]0.247284[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]0.733242[/C][C]0.266758[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]0.866897[/C][C]0.133103[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]0.95802[/C][C]0.0419804[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]1.08262[/C][C]-0.0826181[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]1.17362[/C][C]-0.173623[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]1.1389[/C][C]-0.138905[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]1.24235[/C][C]-0.242349[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.745607[/C][C]0.254393[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]0.623074[/C][C]0.376926[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]0.620768[/C][C]0.379232[/C][/ROW]
[ROW][C]107[/C][C]1[/C][C]0.591348[/C][C]0.408652[/C][/ROW]
[ROW][C]108[/C][C]1[/C][C]0.613513[/C][C]0.386487[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]0.631012[/C][C]0.368988[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]0.776286[/C][C]0.223714[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]0.715627[/C][C]0.284373[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]0.393189[/C][C]0.606811[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.49756[/C][C]0.50244[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.384666[/C][C]0.615334[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.677423[/C][C]0.322577[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.602615[/C][C]0.397385[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.63724[/C][C]0.36276[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]0.611062[/C][C]0.388938[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.478905[/C][C]0.521095[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.405442[/C][C]0.594558[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]0.656629[/C][C]0.343371[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]0.59599[/C][C]0.40401[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]1.00328[/C][C]-0.00327894[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.797061[/C][C]0.202939[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.854002[/C][C]0.145998[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.850789[/C][C]0.149211[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.888423[/C][C]0.111577[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.839659[/C][C]0.160341[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.715453[/C][C]0.284547[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.75591[/C][C]0.24409[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.786621[/C][C]0.213379[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]0.826755[/C][C]0.173245[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]0.803184[/C][C]0.196816[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.756074[/C][C]0.243926[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]1.02994[/C][C]-0.0299372[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]1.01492[/C][C]-0.0149239[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]1.02497[/C][C]-0.0249681[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]1.08676[/C][C]-0.086765[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]1.09524[/C][C]-0.0952445[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.917747[/C][C]0.0822526[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.743319[/C][C]0.256681[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.954195[/C][C]0.0458055[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.612535[/C][C]0.387465[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.633321[/C][C]0.366679[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.479767[/C][C]0.520233[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]0.593948[/C][C]0.406052[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]1.01715[/C][C]-0.0171478[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]0.838289[/C][C]0.161711[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]0.933285[/C][C]0.0667149[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.73878[/C][C]0.26122[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]0.849028[/C][C]0.150972[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]1.30694[/C][C]-0.306936[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]1.01898[/C][C]-0.0189812[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.839936[/C][C]0.160064[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]0.869831[/C][C]0.130169[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.918088[/C][C]0.0819119[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.820816[/C][C]0.179184[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]0.89428[/C][C]0.10572[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]0.862368[/C][C]0.137632[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]0.846064[/C][C]0.153936[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]1.01922[/C][C]-0.019224[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]0.912578[/C][C]0.0874218[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]0.962438[/C][C]0.0375621[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]0.843082[/C][C]0.156918[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]0.859709[/C][C]0.140291[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.56126[/C][C]-0.56126[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.183347[/C][C]-0.183347[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.154395[/C][C]-0.154395[/C][/ROW]
[ROW][C]169[/C][C]0[/C][C]0.731792[/C][C]-0.731792[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.264796[/C][C]-0.264796[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.187227[/C][C]-0.187227[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.786421[/C][C]-0.786421[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.836763[/C][C]-0.836763[/C][/ROW]
[ROW][C]174[/C][C]0[/C][C]0.83222[/C][C]-0.83222[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.83985[/C][C]-0.83985[/C][/ROW]
[ROW][C]176[/C][C]0[/C][C]0.806546[/C][C]-0.806546[/C][/ROW]
[ROW][C]177[/C][C]0[/C][C]0.823434[/C][C]-0.823434[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0.620574[/C][C]0.379426[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]0.66371[/C][C]0.33629[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0.654057[/C][C]0.345943[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]0.687856[/C][C]0.312144[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]0.66703[/C][C]0.33297[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0.701896[/C][C]0.298104[/C][/ROW]
[ROW][C]184[/C][C]0[/C][C]0.806229[/C][C]-0.806229[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]0.795938[/C][C]-0.795938[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]0.797073[/C][C]-0.797073[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.73139[/C][C]-0.73139[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.712831[/C][C]-0.712831[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.813797[/C][C]-0.813797[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.765582[/C][C]-0.765582[/C][/ROW]
[ROW][C]191[/C][C]0[/C][C]0.841491[/C][C]-0.841491[/C][/ROW]
[ROW][C]192[/C][C]0[/C][C]0.669025[/C][C]-0.669025[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]0.516632[/C][C]-0.516632[/C][/ROW]
[ROW][C]194[/C][C]0[/C][C]0.619545[/C][C]-0.619545[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.602198[/C][C]-0.602198[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232113&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232113&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
111.01606-0.0160645
211.04172-0.0417199
311.04035-0.0403496
411.02248-0.0224792
511.0787-0.0787028
610.9889370.0110633
710.7699480.230052
810.8613990.138601
910.8918690.108131
1010.9536960.046304
1110.9307070.0692929
1210.962660.0373401
1310.6484050.351595
1410.7660730.233927
1510.7683980.231602
1610.7377980.262202
1710.6907330.309267
1810.7282610.271739
1911.01812-0.0181242
2010.7165470.283453
2110.9231580.076842
2210.9358670.0641334
2310.8981220.101878
2410.8447580.155242
2510.7009080.299092
2610.9818050.0181954
2710.748640.25136
2810.8021420.197858
2910.7814050.218595
3010.7606970.239303
3100.399918-0.399918
3200.371974-0.371974
3300.38434-0.38434
3400.341578-0.341578
3500.326544-0.326544
3600.364512-0.364512
3710.5696530.430347
3810.5558240.444176
3910.4710530.528947
4010.4701790.529821
4110.4513740.548626
4210.4946170.505383
4300.236927-0.236927
4400.213119-0.213119
4500.15874-0.15874
4600.182189-0.182189
4700.176274-0.176274
4800.21992-0.21992
4900.628624-0.628624
5000.650582-0.650582
5100.710425-0.710425
5200.644375-0.644375
5300.679146-0.679146
5400.664773-0.664773
5510.8443270.155673
5610.8393110.160689
5710.9028220.0971782
5810.7358680.264132
5910.753420.24658
6010.7318240.268176
6100.568167-0.568167
6200.589577-0.589577
6300.304275-0.304275
6400.249895-0.249895
6500.226413-0.226413
6600.512246-0.512246
6710.9080440.0919559
6810.8982990.101701
6911.02626-0.0262622
7011.10135-0.101346
7110.9279410.0720588
7211.02617-0.0261692
7310.7789570.221043
7410.7325270.267473
7510.8896090.110391
7610.8517450.148255
7710.9950410.00495852
7810.8689220.131078
7910.9863090.0136914
8010.9615660.0384344
8111.05511-0.0551131
8211.01681-0.0168099
8310.9342290.0657714
8410.9689070.0310934
8510.9604640.0395364
8610.7163830.283617
8710.7248320.275168
8810.9480770.0519227
8911.06598-0.0659837
9010.7459750.254025
9111.09152-0.0915231
9211.04158-0.0415821
9310.8335110.166489
9411.03892-0.0389208
9510.97380.0262003
9610.7527160.247284
9710.7332420.266758
9810.8668970.133103
9910.958020.0419804
10011.08262-0.0826181
10111.17362-0.173623
10211.1389-0.138905
10311.24235-0.242349
10410.7456070.254393
10510.6230740.376926
10610.6207680.379232
10710.5913480.408652
10810.6135130.386487
10910.6310120.368988
11010.7762860.223714
11110.7156270.284373
11210.3931890.606811
11310.497560.50244
11410.3846660.615334
11510.6774230.322577
11610.6026150.397385
11710.637240.36276
11810.6110620.388938
11910.4789050.521095
12010.4054420.594558
12110.6566290.343371
12210.595990.40401
12311.00328-0.00327894
12410.7970610.202939
12510.8540020.145998
12610.8507890.149211
12710.8884230.111577
12810.8396590.160341
12910.7154530.284547
13010.755910.24409
13110.7866210.213379
13210.8267550.173245
13310.8031840.196816
13410.7560740.243926
13511.02994-0.0299372
13611.01492-0.0149239
13711.02497-0.0249681
13811.08676-0.086765
13911.09524-0.0952445
14010.9177470.0822526
14110.7433190.256681
14210.9541950.0458055
14310.6125350.387465
14410.6333210.366679
14510.4797670.520233
14610.5939480.406052
14711.01715-0.0171478
14810.8382890.161711
14910.9332850.0667149
15010.738780.26122
15110.8490280.150972
15211.30694-0.306936
15311.01898-0.0189812
15410.8399360.160064
15510.8698310.130169
15610.9180880.0819119
15710.8208160.179184
15810.894280.10572
15910.8623680.137632
16010.8460640.153936
16111.01922-0.019224
16210.9125780.0874218
16310.9624380.0375621
16410.8430820.156918
16510.8597090.140291
16600.56126-0.56126
16700.183347-0.183347
16800.154395-0.154395
16900.731792-0.731792
17000.264796-0.264796
17100.187227-0.187227
17200.786421-0.786421
17300.836763-0.836763
17400.83222-0.83222
17500.83985-0.83985
17600.806546-0.806546
17700.823434-0.823434
17810.6205740.379426
17910.663710.33629
18010.6540570.345943
18110.6878560.312144
18210.667030.33297
18310.7018960.298104
18400.806229-0.806229
18500.795938-0.795938
18600.797073-0.797073
18700.73139-0.73139
18800.712831-0.712831
18900.813797-0.813797
19000.765582-0.765582
19100.841491-0.841491
19200.669025-0.669025
19300.516632-0.516632
19400.619545-0.619545
19500.602198-0.602198







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
144.24803e-478.49606e-471
152.31342e-624.62684e-621
16001
175.52839e-991.10568e-981
182.63389e-1085.26778e-1081
196.12146e-1231.22429e-1221
201.13176e-1442.26351e-1441
211.60437e-1733.20874e-1731
224.8199e-1719.63981e-1711
231.38927e-1832.77855e-1831
242.49388e-2014.98776e-2011
251.68726e-2193.37451e-2191
261.80594e-2563.61189e-2561
271.12232e-2492.24464e-2491
284.3247e-2618.64939e-2611
299.98255e-2811.99651e-2801
305.75678e-2971.15136e-2961
314.34923e-088.69845e-081
323.4954e-086.99079e-081
331.41026e-082.82052e-081
344.35244e-098.70488e-091
351.31607e-092.63214e-091
364.1287e-108.25739e-101
371.38685e-072.77369e-071
381.69771e-063.39542e-060.999998
390.0001092170.0002184330.999891
400.0009165460.001833090.999083
410.002831060.005662110.997169
420.003410490.006820970.99659
430.002287440.004574880.997713
440.001474350.002948710.998526
450.0009404520.00188090.99906
460.0006116210.001223240.999388
470.000399930.0007998590.9996
480.0002472730.0004945450.999753
490.0007863410.001572680.999214
500.001386060.002772120.998614
510.001735580.003471160.998264
520.001576730.003153470.998423
530.001991060.003982120.998009
540.002388930.004777860.997611
550.003034430.006068860.996966
560.004791730.009583470.995208
570.003850470.007700950.99615
580.004149430.008298860.995851
590.003888510.007777020.996111
600.00272960.00545920.99727
610.01322230.02644460.986778
620.02148610.04297230.978514
630.02099510.04199020.979005
640.0191380.03827590.980862
650.01640450.03280890.983596
660.01903370.03806730.980966
670.01428430.02856870.985716
680.01053340.02106690.989467
690.007706130.01541230.992294
700.00575660.01151320.994243
710.004195820.008391650.995804
720.002965650.005931310.997034
730.002194240.004388470.997806
740.00604160.01208320.993958
750.004448030.008896060.995552
760.00326920.006538410.996731
770.002310820.004621640.997689
780.001645280.003290570.998355
790.00116910.00233820.998831
800.0009080190.001816040.999092
810.000672760.001345520.999327
820.0004576390.0009152790.999542
830.0003269980.0006539970.999673
840.000281740.0005634810.999718
850.0001930120.0003860250.999807
860.0002134150.000426830.999787
870.0002763720.0005527430.999724
880.0001859540.0003719090.999814
890.0001312320.0002624650.999869
908.93365e-050.0001786730.999911
916.94095e-050.0001388190.999931
925.56265e-050.0001112530.999944
933.71787e-057.43573e-050.999963
942.35674e-054.71349e-050.999976
951.46221e-052.92443e-050.999985
961.0985e-052.19699e-050.999989
978.14376e-061.62875e-050.999992
985.26812e-061.05362e-050.999995
993.15984e-066.31969e-060.999997
1002.15551e-064.31101e-060.999998
1011.73047e-063.46093e-060.999998
1021.84789e-063.69578e-060.999998
1036.64959e-061.32992e-050.999993
1045.25234e-061.05047e-050.999995
1054.56698e-069.13396e-060.999995
1064.42506e-068.85012e-060.999996
1074.13297e-068.26593e-060.999996
1084.17627e-068.35253e-060.999996
1093.51253e-067.02506e-060.999996
1102.5682e-065.13639e-060.999997
1111.96948e-063.93896e-060.999998
1123.99737e-067.99473e-060.999996
1134.73941e-069.47883e-060.999995
1141.53905e-053.07809e-050.999985
1151.22937e-052.45873e-050.999988
1161.3083e-052.61659e-050.999987
1171.30368e-052.60737e-050.999987
1181.27812e-052.55623e-050.999987
1193.24615e-056.4923e-050.999968
1200.0001322080.0002644160.999868
1210.0002056490.0004112990.999794
1220.0003483460.0006966920.999652
1230.0002494250.000498850.999751
1240.0002071790.0004143580.999793
1250.0002172190.0004344380.999783
1260.0002375770.0004751540.999762
1270.0002772610.0005545210.999723
1280.000285190.000570380.999715
1290.0002446350.000489270.999755
1300.0002764330.0005528660.999724
1310.0003380670.0006761340.999662
1320.0002782570.0005565130.999722
1330.0004386990.0008773970.999561
1340.0005630220.001126040.999437
1350.0004571950.0009143910.999543
1360.0003092370.0006184740.999691
1370.0002017940.0004035880.999798
1380.0001355850.000271170.999864
1399.98545e-050.0001997090.9999
1406.437e-050.000128740.999936
1417.53571e-050.0001507140.999925
1424.93042e-059.86083e-050.999951
1436.30085e-050.0001260170.999937
1440.000425040.0008500810.999575
1450.001671720.003343450.998328
1460.006416410.01283280.993584
1470.004532370.009064730.995468
1480.003151450.00630290.996849
1490.002166430.004332870.997834
1500.001454940.002909880.998545
1510.001022380.002044770.998978
1520.0009989390.001997880.999001
1530.0007152860.001430570.999285
1540.0005758460.001151690.999424
1550.0004469490.0008938980.999553
1560.0002928370.0005856740.999707
1570.0004572980.0009145960.999543
1580.00115670.00231340.998843
1590.0009926590.001985320.999007
1600.0006639380.001327880.999336
1610.0004011030.0008022070.999599
1620.000405540.000811080.999594
1630.0002417720.0004835440.999758
1640.0002453560.0004907120.999755
1650.00315660.00631320.996843
1660.004687790.009375570.995312
1670.006246760.01249350.993753
1680.01389770.02779550.986102
1690.01881370.03762730.981186
1700.01265010.02530020.98735
1710.996930.006140450.00307023
1720.9987250.002550250.00127512
1730.9978440.00431170.00215585
1740.9961680.0076640.003832
1750.9933590.01328150.00664077
1760.9969570.006085720.00304286
1770.9992620.001475210.000737607
1780.9997370.0005262780.000263139
1790.9986370.002725140.00136257
1800.9950510.009897910.00494896
1810.9838220.03235690.0161784

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
14 & 4.24803e-47 & 8.49606e-47 & 1 \tabularnewline
15 & 2.31342e-62 & 4.62684e-62 & 1 \tabularnewline
16 & 0 & 0 & 1 \tabularnewline
17 & 5.52839e-99 & 1.10568e-98 & 1 \tabularnewline
18 & 2.63389e-108 & 5.26778e-108 & 1 \tabularnewline
19 & 6.12146e-123 & 1.22429e-122 & 1 \tabularnewline
20 & 1.13176e-144 & 2.26351e-144 & 1 \tabularnewline
21 & 1.60437e-173 & 3.20874e-173 & 1 \tabularnewline
22 & 4.8199e-171 & 9.63981e-171 & 1 \tabularnewline
23 & 1.38927e-183 & 2.77855e-183 & 1 \tabularnewline
24 & 2.49388e-201 & 4.98776e-201 & 1 \tabularnewline
25 & 1.68726e-219 & 3.37451e-219 & 1 \tabularnewline
26 & 1.80594e-256 & 3.61189e-256 & 1 \tabularnewline
27 & 1.12232e-249 & 2.24464e-249 & 1 \tabularnewline
28 & 4.3247e-261 & 8.64939e-261 & 1 \tabularnewline
29 & 9.98255e-281 & 1.99651e-280 & 1 \tabularnewline
30 & 5.75678e-297 & 1.15136e-296 & 1 \tabularnewline
31 & 4.34923e-08 & 8.69845e-08 & 1 \tabularnewline
32 & 3.4954e-08 & 6.99079e-08 & 1 \tabularnewline
33 & 1.41026e-08 & 2.82052e-08 & 1 \tabularnewline
34 & 4.35244e-09 & 8.70488e-09 & 1 \tabularnewline
35 & 1.31607e-09 & 2.63214e-09 & 1 \tabularnewline
36 & 4.1287e-10 & 8.25739e-10 & 1 \tabularnewline
37 & 1.38685e-07 & 2.77369e-07 & 1 \tabularnewline
38 & 1.69771e-06 & 3.39542e-06 & 0.999998 \tabularnewline
39 & 0.000109217 & 0.000218433 & 0.999891 \tabularnewline
40 & 0.000916546 & 0.00183309 & 0.999083 \tabularnewline
41 & 0.00283106 & 0.00566211 & 0.997169 \tabularnewline
42 & 0.00341049 & 0.00682097 & 0.99659 \tabularnewline
43 & 0.00228744 & 0.00457488 & 0.997713 \tabularnewline
44 & 0.00147435 & 0.00294871 & 0.998526 \tabularnewline
45 & 0.000940452 & 0.0018809 & 0.99906 \tabularnewline
46 & 0.000611621 & 0.00122324 & 0.999388 \tabularnewline
47 & 0.00039993 & 0.000799859 & 0.9996 \tabularnewline
48 & 0.000247273 & 0.000494545 & 0.999753 \tabularnewline
49 & 0.000786341 & 0.00157268 & 0.999214 \tabularnewline
50 & 0.00138606 & 0.00277212 & 0.998614 \tabularnewline
51 & 0.00173558 & 0.00347116 & 0.998264 \tabularnewline
52 & 0.00157673 & 0.00315347 & 0.998423 \tabularnewline
53 & 0.00199106 & 0.00398212 & 0.998009 \tabularnewline
54 & 0.00238893 & 0.00477786 & 0.997611 \tabularnewline
55 & 0.00303443 & 0.00606886 & 0.996966 \tabularnewline
56 & 0.00479173 & 0.00958347 & 0.995208 \tabularnewline
57 & 0.00385047 & 0.00770095 & 0.99615 \tabularnewline
58 & 0.00414943 & 0.00829886 & 0.995851 \tabularnewline
59 & 0.00388851 & 0.00777702 & 0.996111 \tabularnewline
60 & 0.0027296 & 0.0054592 & 0.99727 \tabularnewline
61 & 0.0132223 & 0.0264446 & 0.986778 \tabularnewline
62 & 0.0214861 & 0.0429723 & 0.978514 \tabularnewline
63 & 0.0209951 & 0.0419902 & 0.979005 \tabularnewline
64 & 0.019138 & 0.0382759 & 0.980862 \tabularnewline
65 & 0.0164045 & 0.0328089 & 0.983596 \tabularnewline
66 & 0.0190337 & 0.0380673 & 0.980966 \tabularnewline
67 & 0.0142843 & 0.0285687 & 0.985716 \tabularnewline
68 & 0.0105334 & 0.0210669 & 0.989467 \tabularnewline
69 & 0.00770613 & 0.0154123 & 0.992294 \tabularnewline
70 & 0.0057566 & 0.0115132 & 0.994243 \tabularnewline
71 & 0.00419582 & 0.00839165 & 0.995804 \tabularnewline
72 & 0.00296565 & 0.00593131 & 0.997034 \tabularnewline
73 & 0.00219424 & 0.00438847 & 0.997806 \tabularnewline
74 & 0.0060416 & 0.0120832 & 0.993958 \tabularnewline
75 & 0.00444803 & 0.00889606 & 0.995552 \tabularnewline
76 & 0.0032692 & 0.00653841 & 0.996731 \tabularnewline
77 & 0.00231082 & 0.00462164 & 0.997689 \tabularnewline
78 & 0.00164528 & 0.00329057 & 0.998355 \tabularnewline
79 & 0.0011691 & 0.0023382 & 0.998831 \tabularnewline
80 & 0.000908019 & 0.00181604 & 0.999092 \tabularnewline
81 & 0.00067276 & 0.00134552 & 0.999327 \tabularnewline
82 & 0.000457639 & 0.000915279 & 0.999542 \tabularnewline
83 & 0.000326998 & 0.000653997 & 0.999673 \tabularnewline
84 & 0.00028174 & 0.000563481 & 0.999718 \tabularnewline
85 & 0.000193012 & 0.000386025 & 0.999807 \tabularnewline
86 & 0.000213415 & 0.00042683 & 0.999787 \tabularnewline
87 & 0.000276372 & 0.000552743 & 0.999724 \tabularnewline
88 & 0.000185954 & 0.000371909 & 0.999814 \tabularnewline
89 & 0.000131232 & 0.000262465 & 0.999869 \tabularnewline
90 & 8.93365e-05 & 0.000178673 & 0.999911 \tabularnewline
91 & 6.94095e-05 & 0.000138819 & 0.999931 \tabularnewline
92 & 5.56265e-05 & 0.000111253 & 0.999944 \tabularnewline
93 & 3.71787e-05 & 7.43573e-05 & 0.999963 \tabularnewline
94 & 2.35674e-05 & 4.71349e-05 & 0.999976 \tabularnewline
95 & 1.46221e-05 & 2.92443e-05 & 0.999985 \tabularnewline
96 & 1.0985e-05 & 2.19699e-05 & 0.999989 \tabularnewline
97 & 8.14376e-06 & 1.62875e-05 & 0.999992 \tabularnewline
98 & 5.26812e-06 & 1.05362e-05 & 0.999995 \tabularnewline
99 & 3.15984e-06 & 6.31969e-06 & 0.999997 \tabularnewline
100 & 2.15551e-06 & 4.31101e-06 & 0.999998 \tabularnewline
101 & 1.73047e-06 & 3.46093e-06 & 0.999998 \tabularnewline
102 & 1.84789e-06 & 3.69578e-06 & 0.999998 \tabularnewline
103 & 6.64959e-06 & 1.32992e-05 & 0.999993 \tabularnewline
104 & 5.25234e-06 & 1.05047e-05 & 0.999995 \tabularnewline
105 & 4.56698e-06 & 9.13396e-06 & 0.999995 \tabularnewline
106 & 4.42506e-06 & 8.85012e-06 & 0.999996 \tabularnewline
107 & 4.13297e-06 & 8.26593e-06 & 0.999996 \tabularnewline
108 & 4.17627e-06 & 8.35253e-06 & 0.999996 \tabularnewline
109 & 3.51253e-06 & 7.02506e-06 & 0.999996 \tabularnewline
110 & 2.5682e-06 & 5.13639e-06 & 0.999997 \tabularnewline
111 & 1.96948e-06 & 3.93896e-06 & 0.999998 \tabularnewline
112 & 3.99737e-06 & 7.99473e-06 & 0.999996 \tabularnewline
113 & 4.73941e-06 & 9.47883e-06 & 0.999995 \tabularnewline
114 & 1.53905e-05 & 3.07809e-05 & 0.999985 \tabularnewline
115 & 1.22937e-05 & 2.45873e-05 & 0.999988 \tabularnewline
116 & 1.3083e-05 & 2.61659e-05 & 0.999987 \tabularnewline
117 & 1.30368e-05 & 2.60737e-05 & 0.999987 \tabularnewline
118 & 1.27812e-05 & 2.55623e-05 & 0.999987 \tabularnewline
119 & 3.24615e-05 & 6.4923e-05 & 0.999968 \tabularnewline
120 & 0.000132208 & 0.000264416 & 0.999868 \tabularnewline
121 & 0.000205649 & 0.000411299 & 0.999794 \tabularnewline
122 & 0.000348346 & 0.000696692 & 0.999652 \tabularnewline
123 & 0.000249425 & 0.00049885 & 0.999751 \tabularnewline
124 & 0.000207179 & 0.000414358 & 0.999793 \tabularnewline
125 & 0.000217219 & 0.000434438 & 0.999783 \tabularnewline
126 & 0.000237577 & 0.000475154 & 0.999762 \tabularnewline
127 & 0.000277261 & 0.000554521 & 0.999723 \tabularnewline
128 & 0.00028519 & 0.00057038 & 0.999715 \tabularnewline
129 & 0.000244635 & 0.00048927 & 0.999755 \tabularnewline
130 & 0.000276433 & 0.000552866 & 0.999724 \tabularnewline
131 & 0.000338067 & 0.000676134 & 0.999662 \tabularnewline
132 & 0.000278257 & 0.000556513 & 0.999722 \tabularnewline
133 & 0.000438699 & 0.000877397 & 0.999561 \tabularnewline
134 & 0.000563022 & 0.00112604 & 0.999437 \tabularnewline
135 & 0.000457195 & 0.000914391 & 0.999543 \tabularnewline
136 & 0.000309237 & 0.000618474 & 0.999691 \tabularnewline
137 & 0.000201794 & 0.000403588 & 0.999798 \tabularnewline
138 & 0.000135585 & 0.00027117 & 0.999864 \tabularnewline
139 & 9.98545e-05 & 0.000199709 & 0.9999 \tabularnewline
140 & 6.437e-05 & 0.00012874 & 0.999936 \tabularnewline
141 & 7.53571e-05 & 0.000150714 & 0.999925 \tabularnewline
142 & 4.93042e-05 & 9.86083e-05 & 0.999951 \tabularnewline
143 & 6.30085e-05 & 0.000126017 & 0.999937 \tabularnewline
144 & 0.00042504 & 0.000850081 & 0.999575 \tabularnewline
145 & 0.00167172 & 0.00334345 & 0.998328 \tabularnewline
146 & 0.00641641 & 0.0128328 & 0.993584 \tabularnewline
147 & 0.00453237 & 0.00906473 & 0.995468 \tabularnewline
148 & 0.00315145 & 0.0063029 & 0.996849 \tabularnewline
149 & 0.00216643 & 0.00433287 & 0.997834 \tabularnewline
150 & 0.00145494 & 0.00290988 & 0.998545 \tabularnewline
151 & 0.00102238 & 0.00204477 & 0.998978 \tabularnewline
152 & 0.000998939 & 0.00199788 & 0.999001 \tabularnewline
153 & 0.000715286 & 0.00143057 & 0.999285 \tabularnewline
154 & 0.000575846 & 0.00115169 & 0.999424 \tabularnewline
155 & 0.000446949 & 0.000893898 & 0.999553 \tabularnewline
156 & 0.000292837 & 0.000585674 & 0.999707 \tabularnewline
157 & 0.000457298 & 0.000914596 & 0.999543 \tabularnewline
158 & 0.0011567 & 0.0023134 & 0.998843 \tabularnewline
159 & 0.000992659 & 0.00198532 & 0.999007 \tabularnewline
160 & 0.000663938 & 0.00132788 & 0.999336 \tabularnewline
161 & 0.000401103 & 0.000802207 & 0.999599 \tabularnewline
162 & 0.00040554 & 0.00081108 & 0.999594 \tabularnewline
163 & 0.000241772 & 0.000483544 & 0.999758 \tabularnewline
164 & 0.000245356 & 0.000490712 & 0.999755 \tabularnewline
165 & 0.0031566 & 0.0063132 & 0.996843 \tabularnewline
166 & 0.00468779 & 0.00937557 & 0.995312 \tabularnewline
167 & 0.00624676 & 0.0124935 & 0.993753 \tabularnewline
168 & 0.0138977 & 0.0277955 & 0.986102 \tabularnewline
169 & 0.0188137 & 0.0376273 & 0.981186 \tabularnewline
170 & 0.0126501 & 0.0253002 & 0.98735 \tabularnewline
171 & 0.99693 & 0.00614045 & 0.00307023 \tabularnewline
172 & 0.998725 & 0.00255025 & 0.00127512 \tabularnewline
173 & 0.997844 & 0.0043117 & 0.00215585 \tabularnewline
174 & 0.996168 & 0.007664 & 0.003832 \tabularnewline
175 & 0.993359 & 0.0132815 & 0.00664077 \tabularnewline
176 & 0.996957 & 0.00608572 & 0.00304286 \tabularnewline
177 & 0.999262 & 0.00147521 & 0.000737607 \tabularnewline
178 & 0.999737 & 0.000526278 & 0.000263139 \tabularnewline
179 & 0.998637 & 0.00272514 & 0.00136257 \tabularnewline
180 & 0.995051 & 0.00989791 & 0.00494896 \tabularnewline
181 & 0.983822 & 0.0323569 & 0.0161784 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232113&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]4.24803e-47[/C][C]8.49606e-47[/C][C]1[/C][/ROW]
[ROW][C]15[/C][C]2.31342e-62[/C][C]4.62684e-62[/C][C]1[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0[/C][C]1[/C][/ROW]
[ROW][C]17[/C][C]5.52839e-99[/C][C]1.10568e-98[/C][C]1[/C][/ROW]
[ROW][C]18[/C][C]2.63389e-108[/C][C]5.26778e-108[/C][C]1[/C][/ROW]
[ROW][C]19[/C][C]6.12146e-123[/C][C]1.22429e-122[/C][C]1[/C][/ROW]
[ROW][C]20[/C][C]1.13176e-144[/C][C]2.26351e-144[/C][C]1[/C][/ROW]
[ROW][C]21[/C][C]1.60437e-173[/C][C]3.20874e-173[/C][C]1[/C][/ROW]
[ROW][C]22[/C][C]4.8199e-171[/C][C]9.63981e-171[/C][C]1[/C][/ROW]
[ROW][C]23[/C][C]1.38927e-183[/C][C]2.77855e-183[/C][C]1[/C][/ROW]
[ROW][C]24[/C][C]2.49388e-201[/C][C]4.98776e-201[/C][C]1[/C][/ROW]
[ROW][C]25[/C][C]1.68726e-219[/C][C]3.37451e-219[/C][C]1[/C][/ROW]
[ROW][C]26[/C][C]1.80594e-256[/C][C]3.61189e-256[/C][C]1[/C][/ROW]
[ROW][C]27[/C][C]1.12232e-249[/C][C]2.24464e-249[/C][C]1[/C][/ROW]
[ROW][C]28[/C][C]4.3247e-261[/C][C]8.64939e-261[/C][C]1[/C][/ROW]
[ROW][C]29[/C][C]9.98255e-281[/C][C]1.99651e-280[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]5.75678e-297[/C][C]1.15136e-296[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]4.34923e-08[/C][C]8.69845e-08[/C][C]1[/C][/ROW]
[ROW][C]32[/C][C]3.4954e-08[/C][C]6.99079e-08[/C][C]1[/C][/ROW]
[ROW][C]33[/C][C]1.41026e-08[/C][C]2.82052e-08[/C][C]1[/C][/ROW]
[ROW][C]34[/C][C]4.35244e-09[/C][C]8.70488e-09[/C][C]1[/C][/ROW]
[ROW][C]35[/C][C]1.31607e-09[/C][C]2.63214e-09[/C][C]1[/C][/ROW]
[ROW][C]36[/C][C]4.1287e-10[/C][C]8.25739e-10[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]1.38685e-07[/C][C]2.77369e-07[/C][C]1[/C][/ROW]
[ROW][C]38[/C][C]1.69771e-06[/C][C]3.39542e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]39[/C][C]0.000109217[/C][C]0.000218433[/C][C]0.999891[/C][/ROW]
[ROW][C]40[/C][C]0.000916546[/C][C]0.00183309[/C][C]0.999083[/C][/ROW]
[ROW][C]41[/C][C]0.00283106[/C][C]0.00566211[/C][C]0.997169[/C][/ROW]
[ROW][C]42[/C][C]0.00341049[/C][C]0.00682097[/C][C]0.99659[/C][/ROW]
[ROW][C]43[/C][C]0.00228744[/C][C]0.00457488[/C][C]0.997713[/C][/ROW]
[ROW][C]44[/C][C]0.00147435[/C][C]0.00294871[/C][C]0.998526[/C][/ROW]
[ROW][C]45[/C][C]0.000940452[/C][C]0.0018809[/C][C]0.99906[/C][/ROW]
[ROW][C]46[/C][C]0.000611621[/C][C]0.00122324[/C][C]0.999388[/C][/ROW]
[ROW][C]47[/C][C]0.00039993[/C][C]0.000799859[/C][C]0.9996[/C][/ROW]
[ROW][C]48[/C][C]0.000247273[/C][C]0.000494545[/C][C]0.999753[/C][/ROW]
[ROW][C]49[/C][C]0.000786341[/C][C]0.00157268[/C][C]0.999214[/C][/ROW]
[ROW][C]50[/C][C]0.00138606[/C][C]0.00277212[/C][C]0.998614[/C][/ROW]
[ROW][C]51[/C][C]0.00173558[/C][C]0.00347116[/C][C]0.998264[/C][/ROW]
[ROW][C]52[/C][C]0.00157673[/C][C]0.00315347[/C][C]0.998423[/C][/ROW]
[ROW][C]53[/C][C]0.00199106[/C][C]0.00398212[/C][C]0.998009[/C][/ROW]
[ROW][C]54[/C][C]0.00238893[/C][C]0.00477786[/C][C]0.997611[/C][/ROW]
[ROW][C]55[/C][C]0.00303443[/C][C]0.00606886[/C][C]0.996966[/C][/ROW]
[ROW][C]56[/C][C]0.00479173[/C][C]0.00958347[/C][C]0.995208[/C][/ROW]
[ROW][C]57[/C][C]0.00385047[/C][C]0.00770095[/C][C]0.99615[/C][/ROW]
[ROW][C]58[/C][C]0.00414943[/C][C]0.00829886[/C][C]0.995851[/C][/ROW]
[ROW][C]59[/C][C]0.00388851[/C][C]0.00777702[/C][C]0.996111[/C][/ROW]
[ROW][C]60[/C][C]0.0027296[/C][C]0.0054592[/C][C]0.99727[/C][/ROW]
[ROW][C]61[/C][C]0.0132223[/C][C]0.0264446[/C][C]0.986778[/C][/ROW]
[ROW][C]62[/C][C]0.0214861[/C][C]0.0429723[/C][C]0.978514[/C][/ROW]
[ROW][C]63[/C][C]0.0209951[/C][C]0.0419902[/C][C]0.979005[/C][/ROW]
[ROW][C]64[/C][C]0.019138[/C][C]0.0382759[/C][C]0.980862[/C][/ROW]
[ROW][C]65[/C][C]0.0164045[/C][C]0.0328089[/C][C]0.983596[/C][/ROW]
[ROW][C]66[/C][C]0.0190337[/C][C]0.0380673[/C][C]0.980966[/C][/ROW]
[ROW][C]67[/C][C]0.0142843[/C][C]0.0285687[/C][C]0.985716[/C][/ROW]
[ROW][C]68[/C][C]0.0105334[/C][C]0.0210669[/C][C]0.989467[/C][/ROW]
[ROW][C]69[/C][C]0.00770613[/C][C]0.0154123[/C][C]0.992294[/C][/ROW]
[ROW][C]70[/C][C]0.0057566[/C][C]0.0115132[/C][C]0.994243[/C][/ROW]
[ROW][C]71[/C][C]0.00419582[/C][C]0.00839165[/C][C]0.995804[/C][/ROW]
[ROW][C]72[/C][C]0.00296565[/C][C]0.00593131[/C][C]0.997034[/C][/ROW]
[ROW][C]73[/C][C]0.00219424[/C][C]0.00438847[/C][C]0.997806[/C][/ROW]
[ROW][C]74[/C][C]0.0060416[/C][C]0.0120832[/C][C]0.993958[/C][/ROW]
[ROW][C]75[/C][C]0.00444803[/C][C]0.00889606[/C][C]0.995552[/C][/ROW]
[ROW][C]76[/C][C]0.0032692[/C][C]0.00653841[/C][C]0.996731[/C][/ROW]
[ROW][C]77[/C][C]0.00231082[/C][C]0.00462164[/C][C]0.997689[/C][/ROW]
[ROW][C]78[/C][C]0.00164528[/C][C]0.00329057[/C][C]0.998355[/C][/ROW]
[ROW][C]79[/C][C]0.0011691[/C][C]0.0023382[/C][C]0.998831[/C][/ROW]
[ROW][C]80[/C][C]0.000908019[/C][C]0.00181604[/C][C]0.999092[/C][/ROW]
[ROW][C]81[/C][C]0.00067276[/C][C]0.00134552[/C][C]0.999327[/C][/ROW]
[ROW][C]82[/C][C]0.000457639[/C][C]0.000915279[/C][C]0.999542[/C][/ROW]
[ROW][C]83[/C][C]0.000326998[/C][C]0.000653997[/C][C]0.999673[/C][/ROW]
[ROW][C]84[/C][C]0.00028174[/C][C]0.000563481[/C][C]0.999718[/C][/ROW]
[ROW][C]85[/C][C]0.000193012[/C][C]0.000386025[/C][C]0.999807[/C][/ROW]
[ROW][C]86[/C][C]0.000213415[/C][C]0.00042683[/C][C]0.999787[/C][/ROW]
[ROW][C]87[/C][C]0.000276372[/C][C]0.000552743[/C][C]0.999724[/C][/ROW]
[ROW][C]88[/C][C]0.000185954[/C][C]0.000371909[/C][C]0.999814[/C][/ROW]
[ROW][C]89[/C][C]0.000131232[/C][C]0.000262465[/C][C]0.999869[/C][/ROW]
[ROW][C]90[/C][C]8.93365e-05[/C][C]0.000178673[/C][C]0.999911[/C][/ROW]
[ROW][C]91[/C][C]6.94095e-05[/C][C]0.000138819[/C][C]0.999931[/C][/ROW]
[ROW][C]92[/C][C]5.56265e-05[/C][C]0.000111253[/C][C]0.999944[/C][/ROW]
[ROW][C]93[/C][C]3.71787e-05[/C][C]7.43573e-05[/C][C]0.999963[/C][/ROW]
[ROW][C]94[/C][C]2.35674e-05[/C][C]4.71349e-05[/C][C]0.999976[/C][/ROW]
[ROW][C]95[/C][C]1.46221e-05[/C][C]2.92443e-05[/C][C]0.999985[/C][/ROW]
[ROW][C]96[/C][C]1.0985e-05[/C][C]2.19699e-05[/C][C]0.999989[/C][/ROW]
[ROW][C]97[/C][C]8.14376e-06[/C][C]1.62875e-05[/C][C]0.999992[/C][/ROW]
[ROW][C]98[/C][C]5.26812e-06[/C][C]1.05362e-05[/C][C]0.999995[/C][/ROW]
[ROW][C]99[/C][C]3.15984e-06[/C][C]6.31969e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]100[/C][C]2.15551e-06[/C][C]4.31101e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]101[/C][C]1.73047e-06[/C][C]3.46093e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]102[/C][C]1.84789e-06[/C][C]3.69578e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]103[/C][C]6.64959e-06[/C][C]1.32992e-05[/C][C]0.999993[/C][/ROW]
[ROW][C]104[/C][C]5.25234e-06[/C][C]1.05047e-05[/C][C]0.999995[/C][/ROW]
[ROW][C]105[/C][C]4.56698e-06[/C][C]9.13396e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]106[/C][C]4.42506e-06[/C][C]8.85012e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]107[/C][C]4.13297e-06[/C][C]8.26593e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]108[/C][C]4.17627e-06[/C][C]8.35253e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]109[/C][C]3.51253e-06[/C][C]7.02506e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]110[/C][C]2.5682e-06[/C][C]5.13639e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]111[/C][C]1.96948e-06[/C][C]3.93896e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]112[/C][C]3.99737e-06[/C][C]7.99473e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]113[/C][C]4.73941e-06[/C][C]9.47883e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]114[/C][C]1.53905e-05[/C][C]3.07809e-05[/C][C]0.999985[/C][/ROW]
[ROW][C]115[/C][C]1.22937e-05[/C][C]2.45873e-05[/C][C]0.999988[/C][/ROW]
[ROW][C]116[/C][C]1.3083e-05[/C][C]2.61659e-05[/C][C]0.999987[/C][/ROW]
[ROW][C]117[/C][C]1.30368e-05[/C][C]2.60737e-05[/C][C]0.999987[/C][/ROW]
[ROW][C]118[/C][C]1.27812e-05[/C][C]2.55623e-05[/C][C]0.999987[/C][/ROW]
[ROW][C]119[/C][C]3.24615e-05[/C][C]6.4923e-05[/C][C]0.999968[/C][/ROW]
[ROW][C]120[/C][C]0.000132208[/C][C]0.000264416[/C][C]0.999868[/C][/ROW]
[ROW][C]121[/C][C]0.000205649[/C][C]0.000411299[/C][C]0.999794[/C][/ROW]
[ROW][C]122[/C][C]0.000348346[/C][C]0.000696692[/C][C]0.999652[/C][/ROW]
[ROW][C]123[/C][C]0.000249425[/C][C]0.00049885[/C][C]0.999751[/C][/ROW]
[ROW][C]124[/C][C]0.000207179[/C][C]0.000414358[/C][C]0.999793[/C][/ROW]
[ROW][C]125[/C][C]0.000217219[/C][C]0.000434438[/C][C]0.999783[/C][/ROW]
[ROW][C]126[/C][C]0.000237577[/C][C]0.000475154[/C][C]0.999762[/C][/ROW]
[ROW][C]127[/C][C]0.000277261[/C][C]0.000554521[/C][C]0.999723[/C][/ROW]
[ROW][C]128[/C][C]0.00028519[/C][C]0.00057038[/C][C]0.999715[/C][/ROW]
[ROW][C]129[/C][C]0.000244635[/C][C]0.00048927[/C][C]0.999755[/C][/ROW]
[ROW][C]130[/C][C]0.000276433[/C][C]0.000552866[/C][C]0.999724[/C][/ROW]
[ROW][C]131[/C][C]0.000338067[/C][C]0.000676134[/C][C]0.999662[/C][/ROW]
[ROW][C]132[/C][C]0.000278257[/C][C]0.000556513[/C][C]0.999722[/C][/ROW]
[ROW][C]133[/C][C]0.000438699[/C][C]0.000877397[/C][C]0.999561[/C][/ROW]
[ROW][C]134[/C][C]0.000563022[/C][C]0.00112604[/C][C]0.999437[/C][/ROW]
[ROW][C]135[/C][C]0.000457195[/C][C]0.000914391[/C][C]0.999543[/C][/ROW]
[ROW][C]136[/C][C]0.000309237[/C][C]0.000618474[/C][C]0.999691[/C][/ROW]
[ROW][C]137[/C][C]0.000201794[/C][C]0.000403588[/C][C]0.999798[/C][/ROW]
[ROW][C]138[/C][C]0.000135585[/C][C]0.00027117[/C][C]0.999864[/C][/ROW]
[ROW][C]139[/C][C]9.98545e-05[/C][C]0.000199709[/C][C]0.9999[/C][/ROW]
[ROW][C]140[/C][C]6.437e-05[/C][C]0.00012874[/C][C]0.999936[/C][/ROW]
[ROW][C]141[/C][C]7.53571e-05[/C][C]0.000150714[/C][C]0.999925[/C][/ROW]
[ROW][C]142[/C][C]4.93042e-05[/C][C]9.86083e-05[/C][C]0.999951[/C][/ROW]
[ROW][C]143[/C][C]6.30085e-05[/C][C]0.000126017[/C][C]0.999937[/C][/ROW]
[ROW][C]144[/C][C]0.00042504[/C][C]0.000850081[/C][C]0.999575[/C][/ROW]
[ROW][C]145[/C][C]0.00167172[/C][C]0.00334345[/C][C]0.998328[/C][/ROW]
[ROW][C]146[/C][C]0.00641641[/C][C]0.0128328[/C][C]0.993584[/C][/ROW]
[ROW][C]147[/C][C]0.00453237[/C][C]0.00906473[/C][C]0.995468[/C][/ROW]
[ROW][C]148[/C][C]0.00315145[/C][C]0.0063029[/C][C]0.996849[/C][/ROW]
[ROW][C]149[/C][C]0.00216643[/C][C]0.00433287[/C][C]0.997834[/C][/ROW]
[ROW][C]150[/C][C]0.00145494[/C][C]0.00290988[/C][C]0.998545[/C][/ROW]
[ROW][C]151[/C][C]0.00102238[/C][C]0.00204477[/C][C]0.998978[/C][/ROW]
[ROW][C]152[/C][C]0.000998939[/C][C]0.00199788[/C][C]0.999001[/C][/ROW]
[ROW][C]153[/C][C]0.000715286[/C][C]0.00143057[/C][C]0.999285[/C][/ROW]
[ROW][C]154[/C][C]0.000575846[/C][C]0.00115169[/C][C]0.999424[/C][/ROW]
[ROW][C]155[/C][C]0.000446949[/C][C]0.000893898[/C][C]0.999553[/C][/ROW]
[ROW][C]156[/C][C]0.000292837[/C][C]0.000585674[/C][C]0.999707[/C][/ROW]
[ROW][C]157[/C][C]0.000457298[/C][C]0.000914596[/C][C]0.999543[/C][/ROW]
[ROW][C]158[/C][C]0.0011567[/C][C]0.0023134[/C][C]0.998843[/C][/ROW]
[ROW][C]159[/C][C]0.000992659[/C][C]0.00198532[/C][C]0.999007[/C][/ROW]
[ROW][C]160[/C][C]0.000663938[/C][C]0.00132788[/C][C]0.999336[/C][/ROW]
[ROW][C]161[/C][C]0.000401103[/C][C]0.000802207[/C][C]0.999599[/C][/ROW]
[ROW][C]162[/C][C]0.00040554[/C][C]0.00081108[/C][C]0.999594[/C][/ROW]
[ROW][C]163[/C][C]0.000241772[/C][C]0.000483544[/C][C]0.999758[/C][/ROW]
[ROW][C]164[/C][C]0.000245356[/C][C]0.000490712[/C][C]0.999755[/C][/ROW]
[ROW][C]165[/C][C]0.0031566[/C][C]0.0063132[/C][C]0.996843[/C][/ROW]
[ROW][C]166[/C][C]0.00468779[/C][C]0.00937557[/C][C]0.995312[/C][/ROW]
[ROW][C]167[/C][C]0.00624676[/C][C]0.0124935[/C][C]0.993753[/C][/ROW]
[ROW][C]168[/C][C]0.0138977[/C][C]0.0277955[/C][C]0.986102[/C][/ROW]
[ROW][C]169[/C][C]0.0188137[/C][C]0.0376273[/C][C]0.981186[/C][/ROW]
[ROW][C]170[/C][C]0.0126501[/C][C]0.0253002[/C][C]0.98735[/C][/ROW]
[ROW][C]171[/C][C]0.99693[/C][C]0.00614045[/C][C]0.00307023[/C][/ROW]
[ROW][C]172[/C][C]0.998725[/C][C]0.00255025[/C][C]0.00127512[/C][/ROW]
[ROW][C]173[/C][C]0.997844[/C][C]0.0043117[/C][C]0.00215585[/C][/ROW]
[ROW][C]174[/C][C]0.996168[/C][C]0.007664[/C][C]0.003832[/C][/ROW]
[ROW][C]175[/C][C]0.993359[/C][C]0.0132815[/C][C]0.00664077[/C][/ROW]
[ROW][C]176[/C][C]0.996957[/C][C]0.00608572[/C][C]0.00304286[/C][/ROW]
[ROW][C]177[/C][C]0.999262[/C][C]0.00147521[/C][C]0.000737607[/C][/ROW]
[ROW][C]178[/C][C]0.999737[/C][C]0.000526278[/C][C]0.000263139[/C][/ROW]
[ROW][C]179[/C][C]0.998637[/C][C]0.00272514[/C][C]0.00136257[/C][/ROW]
[ROW][C]180[/C][C]0.995051[/C][C]0.00989791[/C][C]0.00494896[/C][/ROW]
[ROW][C]181[/C][C]0.983822[/C][C]0.0323569[/C][C]0.0161784[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232113&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232113&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
144.24803e-478.49606e-471
152.31342e-624.62684e-621
16001
175.52839e-991.10568e-981
182.63389e-1085.26778e-1081
196.12146e-1231.22429e-1221
201.13176e-1442.26351e-1441
211.60437e-1733.20874e-1731
224.8199e-1719.63981e-1711
231.38927e-1832.77855e-1831
242.49388e-2014.98776e-2011
251.68726e-2193.37451e-2191
261.80594e-2563.61189e-2561
271.12232e-2492.24464e-2491
284.3247e-2618.64939e-2611
299.98255e-2811.99651e-2801
305.75678e-2971.15136e-2961
314.34923e-088.69845e-081
323.4954e-086.99079e-081
331.41026e-082.82052e-081
344.35244e-098.70488e-091
351.31607e-092.63214e-091
364.1287e-108.25739e-101
371.38685e-072.77369e-071
381.69771e-063.39542e-060.999998
390.0001092170.0002184330.999891
400.0009165460.001833090.999083
410.002831060.005662110.997169
420.003410490.006820970.99659
430.002287440.004574880.997713
440.001474350.002948710.998526
450.0009404520.00188090.99906
460.0006116210.001223240.999388
470.000399930.0007998590.9996
480.0002472730.0004945450.999753
490.0007863410.001572680.999214
500.001386060.002772120.998614
510.001735580.003471160.998264
520.001576730.003153470.998423
530.001991060.003982120.998009
540.002388930.004777860.997611
550.003034430.006068860.996966
560.004791730.009583470.995208
570.003850470.007700950.99615
580.004149430.008298860.995851
590.003888510.007777020.996111
600.00272960.00545920.99727
610.01322230.02644460.986778
620.02148610.04297230.978514
630.02099510.04199020.979005
640.0191380.03827590.980862
650.01640450.03280890.983596
660.01903370.03806730.980966
670.01428430.02856870.985716
680.01053340.02106690.989467
690.007706130.01541230.992294
700.00575660.01151320.994243
710.004195820.008391650.995804
720.002965650.005931310.997034
730.002194240.004388470.997806
740.00604160.01208320.993958
750.004448030.008896060.995552
760.00326920.006538410.996731
770.002310820.004621640.997689
780.001645280.003290570.998355
790.00116910.00233820.998831
800.0009080190.001816040.999092
810.000672760.001345520.999327
820.0004576390.0009152790.999542
830.0003269980.0006539970.999673
840.000281740.0005634810.999718
850.0001930120.0003860250.999807
860.0002134150.000426830.999787
870.0002763720.0005527430.999724
880.0001859540.0003719090.999814
890.0001312320.0002624650.999869
908.93365e-050.0001786730.999911
916.94095e-050.0001388190.999931
925.56265e-050.0001112530.999944
933.71787e-057.43573e-050.999963
942.35674e-054.71349e-050.999976
951.46221e-052.92443e-050.999985
961.0985e-052.19699e-050.999989
978.14376e-061.62875e-050.999992
985.26812e-061.05362e-050.999995
993.15984e-066.31969e-060.999997
1002.15551e-064.31101e-060.999998
1011.73047e-063.46093e-060.999998
1021.84789e-063.69578e-060.999998
1036.64959e-061.32992e-050.999993
1045.25234e-061.05047e-050.999995
1054.56698e-069.13396e-060.999995
1064.42506e-068.85012e-060.999996
1074.13297e-068.26593e-060.999996
1084.17627e-068.35253e-060.999996
1093.51253e-067.02506e-060.999996
1102.5682e-065.13639e-060.999997
1111.96948e-063.93896e-060.999998
1123.99737e-067.99473e-060.999996
1134.73941e-069.47883e-060.999995
1141.53905e-053.07809e-050.999985
1151.22937e-052.45873e-050.999988
1161.3083e-052.61659e-050.999987
1171.30368e-052.60737e-050.999987
1181.27812e-052.55623e-050.999987
1193.24615e-056.4923e-050.999968
1200.0001322080.0002644160.999868
1210.0002056490.0004112990.999794
1220.0003483460.0006966920.999652
1230.0002494250.000498850.999751
1240.0002071790.0004143580.999793
1250.0002172190.0004344380.999783
1260.0002375770.0004751540.999762
1270.0002772610.0005545210.999723
1280.000285190.000570380.999715
1290.0002446350.000489270.999755
1300.0002764330.0005528660.999724
1310.0003380670.0006761340.999662
1320.0002782570.0005565130.999722
1330.0004386990.0008773970.999561
1340.0005630220.001126040.999437
1350.0004571950.0009143910.999543
1360.0003092370.0006184740.999691
1370.0002017940.0004035880.999798
1380.0001355850.000271170.999864
1399.98545e-050.0001997090.9999
1406.437e-050.000128740.999936
1417.53571e-050.0001507140.999925
1424.93042e-059.86083e-050.999951
1436.30085e-050.0001260170.999937
1440.000425040.0008500810.999575
1450.001671720.003343450.998328
1460.006416410.01283280.993584
1470.004532370.009064730.995468
1480.003151450.00630290.996849
1490.002166430.004332870.997834
1500.001454940.002909880.998545
1510.001022380.002044770.998978
1520.0009989390.001997880.999001
1530.0007152860.001430570.999285
1540.0005758460.001151690.999424
1550.0004469490.0008938980.999553
1560.0002928370.0005856740.999707
1570.0004572980.0009145960.999543
1580.00115670.00231340.998843
1590.0009926590.001985320.999007
1600.0006639380.001327880.999336
1610.0004011030.0008022070.999599
1620.000405540.000811080.999594
1630.0002417720.0004835440.999758
1640.0002453560.0004907120.999755
1650.00315660.00631320.996843
1660.004687790.009375570.995312
1670.006246760.01249350.993753
1680.01389770.02779550.986102
1690.01881370.03762730.981186
1700.01265010.02530020.98735
1710.996930.006140450.00307023
1720.9987250.002550250.00127512
1730.9978440.00431170.00215585
1740.9961680.0076640.003832
1750.9933590.01328150.00664077
1760.9969570.006085720.00304286
1770.9992620.001475210.000737607
1780.9997370.0005262780.000263139
1790.9986370.002725140.00136257
1800.9950510.009897910.00494896
1810.9838220.03235690.0161784







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1500.892857NOK
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 & 150 & 0.892857 & 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=232113&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]150[/C][C]0.892857[/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=232113&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232113&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 level1500.892857NOK
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 ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')
}