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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 05 Dec 2013 18:00:07 -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/05/t1386284990giaq8miult4jbri.htm/, Retrieved Wed, 24 Apr 2024 06:05:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231280, Retrieved Wed, 24 Apr 2024 06:05:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [ws10] [2013-12-05 23:00:07] [a17fd0651b2d0a0974784add16174701] [Current]
-   P       [Multiple Regression] [ws10] [2013-12-05 23:19:20] [6e6101806504d86600f236fbba4f8aec]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time48 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 48 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231280&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]48 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231280&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231280&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time48 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
NHR[t] = + 0.0487493917669137 -0.000136978753046717`MDVP:Fo(Hz)`[t] + 1.73418954927947e-05`MDVP:Fhi(Hz)`[t] + 1.99172526816135e-05`MDVP:Flo(Hz)`[t] + 4.10594659431346`MDVP:Jitter(%)`[t] + 52.4052020921706`MDVP:Jitter(Abs)`[t] -320.448136297189`MDVP:RAP`[t] -6.83446350213999`MDVP:PPQ`[t] + 110.339974381334`Jitter:DDP`[t] -1.80077848692351`MDVP:Shimmer`[t] + 0.0066153792944201`MDVP:Shimmer(dB)`[t] -138.08492401749`Shimmer:APQ3`[t] + 0.774564726867889`Shimmer:APQ5`[t] + 0.579265150763743`MDVP:APQ`[t] + 46.669866065569`Shimmer:DDA`[t] -0.000859549620166099HNR[t] -0.00370814388609925status[t] -0.010829661243777RPDE[t] -0.139766502749012DFA[t] -0.00853620172566379spread1[t] + 0.04443828523866spread2[t] + 0.00482148062186504D2[t] + 0.0152185348319237PPE[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
NHR[t] =  +  0.0487493917669137 -0.000136978753046717`MDVP:Fo(Hz)`[t] +  1.73418954927947e-05`MDVP:Fhi(Hz)`[t] +  1.99172526816135e-05`MDVP:Flo(Hz)`[t] +  4.10594659431346`MDVP:Jitter(%)`[t] +  52.4052020921706`MDVP:Jitter(Abs)`[t] -320.448136297189`MDVP:RAP`[t] -6.83446350213999`MDVP:PPQ`[t] +  110.339974381334`Jitter:DDP`[t] -1.80077848692351`MDVP:Shimmer`[t] +  0.0066153792944201`MDVP:Shimmer(dB)`[t] -138.08492401749`Shimmer:APQ3`[t] +  0.774564726867889`Shimmer:APQ5`[t] +  0.579265150763743`MDVP:APQ`[t] +  46.669866065569`Shimmer:DDA`[t] -0.000859549620166099HNR[t] -0.00370814388609925status[t] -0.010829661243777RPDE[t] -0.139766502749012DFA[t] -0.00853620172566379spread1[t] +  0.04443828523866spread2[t] +  0.00482148062186504D2[t] +  0.0152185348319237PPE[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231280&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]NHR[t] =  +  0.0487493917669137 -0.000136978753046717`MDVP:Fo(Hz)`[t] +  1.73418954927947e-05`MDVP:Fhi(Hz)`[t] +  1.99172526816135e-05`MDVP:Flo(Hz)`[t] +  4.10594659431346`MDVP:Jitter(%)`[t] +  52.4052020921706`MDVP:Jitter(Abs)`[t] -320.448136297189`MDVP:RAP`[t] -6.83446350213999`MDVP:PPQ`[t] +  110.339974381334`Jitter:DDP`[t] -1.80077848692351`MDVP:Shimmer`[t] +  0.0066153792944201`MDVP:Shimmer(dB)`[t] -138.08492401749`Shimmer:APQ3`[t] +  0.774564726867889`Shimmer:APQ5`[t] +  0.579265150763743`MDVP:APQ`[t] +  46.669866065569`Shimmer:DDA`[t] -0.000859549620166099HNR[t] -0.00370814388609925status[t] -0.010829661243777RPDE[t] -0.139766502749012DFA[t] -0.00853620172566379spread1[t] +  0.04443828523866spread2[t] +  0.00482148062186504D2[t] +  0.0152185348319237PPE[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231280&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231280&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
NHR[t] = + 0.0487493917669137 -0.000136978753046717`MDVP:Fo(Hz)`[t] + 1.73418954927947e-05`MDVP:Fhi(Hz)`[t] + 1.99172526816135e-05`MDVP:Flo(Hz)`[t] + 4.10594659431346`MDVP:Jitter(%)`[t] + 52.4052020921706`MDVP:Jitter(Abs)`[t] -320.448136297189`MDVP:RAP`[t] -6.83446350213999`MDVP:PPQ`[t] + 110.339974381334`Jitter:DDP`[t] -1.80077848692351`MDVP:Shimmer`[t] + 0.0066153792944201`MDVP:Shimmer(dB)`[t] -138.08492401749`Shimmer:APQ3`[t] + 0.774564726867889`Shimmer:APQ5`[t] + 0.579265150763743`MDVP:APQ`[t] + 46.669866065569`Shimmer:DDA`[t] -0.000859549620166099HNR[t] -0.00370814388609925status[t] -0.010829661243777RPDE[t] -0.139766502749012DFA[t] -0.00853620172566379spread1[t] + 0.04443828523866spread2[t] + 0.00482148062186504D2[t] + 0.0152185348319237PPE[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)0.04874939176691370.0447051.09050.2770330.138516
`MDVP:Fo(Hz)`-0.0001369787530467175.7e-05-2.38910.0179730.008987
`MDVP:Fhi(Hz)`1.73418954927947e-051.2e-051.41740.1581890.079095
`MDVP:Flo(Hz)`1.99172526816135e-053.1e-050.64190.5218230.260911
`MDVP:Jitter(%)`4.105946594313462.6010731.57860.1162750.058137
`MDVP:Jitter(Abs)`52.4052020921706177.4626110.29530.7681190.384059
`MDVP:RAP`-320.448136297189356.742579-0.89830.3703020.185151
`MDVP:PPQ`-6.834463502139993.347954-2.04140.042740.02137
`Jitter:DDP`110.339974381334118.9305670.92780.3548280.177414
`MDVP:Shimmer`-1.800778486923511.308894-1.37580.1706720.085336
`MDVP:Shimmer(dB)`0.00661537929442010.0459820.14390.8857720.442886
`Shimmer:APQ3`-138.08492401749343.636661-0.40180.6883050.344152
`Shimmer:APQ5`0.7745647268678890.7726481.00250.317520.15876
`MDVP:APQ`0.5792651507637430.4150691.39560.1646380.082319
`Shimmer:DDA`46.669866065569114.5145290.40750.6841140.342057
HNR-0.0008595496201660990.000548-1.56970.1183220.059161
status-0.003708143886099250.002908-1.27520.2039670.101983
RPDE-0.0108296612437770.017081-0.6340.5269060.263453
DFA-0.1397665027490120.026271-5.320200
spread1-0.008536201725663790.003713-2.2990.0227060.011353
spread20.044438285238660.0183762.41830.0166350.008317
D20.004821480621865040.0043681.10390.271160.13558
PPE0.01521853483192370.0531220.28650.7748530.387426

\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) & 0.0487493917669137 & 0.044705 & 1.0905 & 0.277033 & 0.138516 \tabularnewline
`MDVP:Fo(Hz)` & -0.000136978753046717 & 5.7e-05 & -2.3891 & 0.017973 & 0.008987 \tabularnewline
`MDVP:Fhi(Hz)` & 1.73418954927947e-05 & 1.2e-05 & 1.4174 & 0.158189 & 0.079095 \tabularnewline
`MDVP:Flo(Hz)` & 1.99172526816135e-05 & 3.1e-05 & 0.6419 & 0.521823 & 0.260911 \tabularnewline
`MDVP:Jitter(%)` & 4.10594659431346 & 2.601073 & 1.5786 & 0.116275 & 0.058137 \tabularnewline
`MDVP:Jitter(Abs)` & 52.4052020921706 & 177.462611 & 0.2953 & 0.768119 & 0.384059 \tabularnewline
`MDVP:RAP` & -320.448136297189 & 356.742579 & -0.8983 & 0.370302 & 0.185151 \tabularnewline
`MDVP:PPQ` & -6.83446350213999 & 3.347954 & -2.0414 & 0.04274 & 0.02137 \tabularnewline
`Jitter:DDP` & 110.339974381334 & 118.930567 & 0.9278 & 0.354828 & 0.177414 \tabularnewline
`MDVP:Shimmer` & -1.80077848692351 & 1.308894 & -1.3758 & 0.170672 & 0.085336 \tabularnewline
`MDVP:Shimmer(dB)` & 0.0066153792944201 & 0.045982 & 0.1439 & 0.885772 & 0.442886 \tabularnewline
`Shimmer:APQ3` & -138.08492401749 & 343.636661 & -0.4018 & 0.688305 & 0.344152 \tabularnewline
`Shimmer:APQ5` & 0.774564726867889 & 0.772648 & 1.0025 & 0.31752 & 0.15876 \tabularnewline
`MDVP:APQ` & 0.579265150763743 & 0.415069 & 1.3956 & 0.164638 & 0.082319 \tabularnewline
`Shimmer:DDA` & 46.669866065569 & 114.514529 & 0.4075 & 0.684114 & 0.342057 \tabularnewline
HNR & -0.000859549620166099 & 0.000548 & -1.5697 & 0.118322 & 0.059161 \tabularnewline
status & -0.00370814388609925 & 0.002908 & -1.2752 & 0.203967 & 0.101983 \tabularnewline
RPDE & -0.010829661243777 & 0.017081 & -0.634 & 0.526906 & 0.263453 \tabularnewline
DFA & -0.139766502749012 & 0.026271 & -5.3202 & 0 & 0 \tabularnewline
spread1 & -0.00853620172566379 & 0.003713 & -2.299 & 0.022706 & 0.011353 \tabularnewline
spread2 & 0.04443828523866 & 0.018376 & 2.4183 & 0.016635 & 0.008317 \tabularnewline
D2 & 0.00482148062186504 & 0.004368 & 1.1039 & 0.27116 & 0.13558 \tabularnewline
PPE & 0.0152185348319237 & 0.053122 & 0.2865 & 0.774853 & 0.387426 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231280&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]0.0487493917669137[/C][C]0.044705[/C][C]1.0905[/C][C]0.277033[/C][C]0.138516[/C][/ROW]
[ROW][C]`MDVP:Fo(Hz)`[/C][C]-0.000136978753046717[/C][C]5.7e-05[/C][C]-2.3891[/C][C]0.017973[/C][C]0.008987[/C][/ROW]
[ROW][C]`MDVP:Fhi(Hz)`[/C][C]1.73418954927947e-05[/C][C]1.2e-05[/C][C]1.4174[/C][C]0.158189[/C][C]0.079095[/C][/ROW]
[ROW][C]`MDVP:Flo(Hz)`[/C][C]1.99172526816135e-05[/C][C]3.1e-05[/C][C]0.6419[/C][C]0.521823[/C][C]0.260911[/C][/ROW]
[ROW][C]`MDVP:Jitter(%)`[/C][C]4.10594659431346[/C][C]2.601073[/C][C]1.5786[/C][C]0.116275[/C][C]0.058137[/C][/ROW]
[ROW][C]`MDVP:Jitter(Abs)`[/C][C]52.4052020921706[/C][C]177.462611[/C][C]0.2953[/C][C]0.768119[/C][C]0.384059[/C][/ROW]
[ROW][C]`MDVP:RAP`[/C][C]-320.448136297189[/C][C]356.742579[/C][C]-0.8983[/C][C]0.370302[/C][C]0.185151[/C][/ROW]
[ROW][C]`MDVP:PPQ`[/C][C]-6.83446350213999[/C][C]3.347954[/C][C]-2.0414[/C][C]0.04274[/C][C]0.02137[/C][/ROW]
[ROW][C]`Jitter:DDP`[/C][C]110.339974381334[/C][C]118.930567[/C][C]0.9278[/C][C]0.354828[/C][C]0.177414[/C][/ROW]
[ROW][C]`MDVP:Shimmer`[/C][C]-1.80077848692351[/C][C]1.308894[/C][C]-1.3758[/C][C]0.170672[/C][C]0.085336[/C][/ROW]
[ROW][C]`MDVP:Shimmer(dB)`[/C][C]0.0066153792944201[/C][C]0.045982[/C][C]0.1439[/C][C]0.885772[/C][C]0.442886[/C][/ROW]
[ROW][C]`Shimmer:APQ3`[/C][C]-138.08492401749[/C][C]343.636661[/C][C]-0.4018[/C][C]0.688305[/C][C]0.344152[/C][/ROW]
[ROW][C]`Shimmer:APQ5`[/C][C]0.774564726867889[/C][C]0.772648[/C][C]1.0025[/C][C]0.31752[/C][C]0.15876[/C][/ROW]
[ROW][C]`MDVP:APQ`[/C][C]0.579265150763743[/C][C]0.415069[/C][C]1.3956[/C][C]0.164638[/C][C]0.082319[/C][/ROW]
[ROW][C]`Shimmer:DDA`[/C][C]46.669866065569[/C][C]114.514529[/C][C]0.4075[/C][C]0.684114[/C][C]0.342057[/C][/ROW]
[ROW][C]HNR[/C][C]-0.000859549620166099[/C][C]0.000548[/C][C]-1.5697[/C][C]0.118322[/C][C]0.059161[/C][/ROW]
[ROW][C]status[/C][C]-0.00370814388609925[/C][C]0.002908[/C][C]-1.2752[/C][C]0.203967[/C][C]0.101983[/C][/ROW]
[ROW][C]RPDE[/C][C]-0.010829661243777[/C][C]0.017081[/C][C]-0.634[/C][C]0.526906[/C][C]0.263453[/C][/ROW]
[ROW][C]DFA[/C][C]-0.139766502749012[/C][C]0.026271[/C][C]-5.3202[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]spread1[/C][C]-0.00853620172566379[/C][C]0.003713[/C][C]-2.299[/C][C]0.022706[/C][C]0.011353[/C][/ROW]
[ROW][C]spread2[/C][C]0.04443828523866[/C][C]0.018376[/C][C]2.4183[/C][C]0.016635[/C][C]0.008317[/C][/ROW]
[ROW][C]D2[/C][C]0.00482148062186504[/C][C]0.004368[/C][C]1.1039[/C][C]0.27116[/C][C]0.13558[/C][/ROW]
[ROW][C]PPE[/C][C]0.0152185348319237[/C][C]0.053122[/C][C]0.2865[/C][C]0.774853[/C][C]0.387426[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231280&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231280&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)0.04874939176691370.0447051.09050.2770330.138516
`MDVP:Fo(Hz)`-0.0001369787530467175.7e-05-2.38910.0179730.008987
`MDVP:Fhi(Hz)`1.73418954927947e-051.2e-051.41740.1581890.079095
`MDVP:Flo(Hz)`1.99172526816135e-053.1e-050.64190.5218230.260911
`MDVP:Jitter(%)`4.105946594313462.6010731.57860.1162750.058137
`MDVP:Jitter(Abs)`52.4052020921706177.4626110.29530.7681190.384059
`MDVP:RAP`-320.448136297189356.742579-0.89830.3703020.185151
`MDVP:PPQ`-6.834463502139993.347954-2.04140.042740.02137
`Jitter:DDP`110.339974381334118.9305670.92780.3548280.177414
`MDVP:Shimmer`-1.800778486923511.308894-1.37580.1706720.085336
`MDVP:Shimmer(dB)`0.00661537929442010.0459820.14390.8857720.442886
`Shimmer:APQ3`-138.08492401749343.636661-0.40180.6883050.344152
`Shimmer:APQ5`0.7745647268678890.7726481.00250.317520.15876
`MDVP:APQ`0.5792651507637430.4150691.39560.1646380.082319
`Shimmer:DDA`46.669866065569114.5145290.40750.6841140.342057
HNR-0.0008595496201660990.000548-1.56970.1183220.059161
status-0.003708143886099250.002908-1.27520.2039670.101983
RPDE-0.0108296612437770.017081-0.6340.5269060.263453
DFA-0.1397665027490120.026271-5.320200
spread1-0.008536201725663790.003713-2.2990.0227060.011353
spread20.044438285238660.0183762.41830.0166350.008317
D20.004821480621865040.0043681.10390.271160.13558
PPE0.01521853483192370.0531220.28650.7748530.387426






Multiple Linear Regression - Regression Statistics
Multiple R0.956540015849278
R-squared0.914968801920937
Adjusted R-squared0.904092718445708
F-TEST (value)84.1266807123021
F-TEST (DF numerator)22
F-TEST (DF denominator)172
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.0125171492302843
Sum Squared Residuals0.0269487922747517

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.956540015849278 \tabularnewline
R-squared & 0.914968801920937 \tabularnewline
Adjusted R-squared & 0.904092718445708 \tabularnewline
F-TEST (value) & 84.1266807123021 \tabularnewline
F-TEST (DF numerator) & 22 \tabularnewline
F-TEST (DF denominator) & 172 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.0125171492302843 \tabularnewline
Sum Squared Residuals & 0.0269487922747517 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231280&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.956540015849278[/C][/ROW]
[ROW][C]R-squared[/C][C]0.914968801920937[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.904092718445708[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]84.1266807123021[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]22[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]172[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.0125171492302843[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]0.0269487922747517[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231280&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231280&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.956540015849278
R-squared0.914968801920937
Adjusted R-squared0.904092718445708
F-TEST (value)84.1266807123021
F-TEST (DF numerator)22
F-TEST (DF denominator)172
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.0125171492302843
Sum Squared Residuals0.0269487922747517






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
10.022110.007705429434074520.0144045705659255
20.019290.0237007491384245-0.00441074913842454
30.013090.0292057435303475-0.0161157435303475
40.013530.0270403141375732-0.0135103141375732
50.017670.0425584071035489-0.0248884071035489
60.012220.01063359482186540.00158640517813456
70.00607-0.008721247575343660.0147912475753437
80.00344-0.01065904506759780.0140990450675978
90.01070.0174871117147491-0.00678711171474914
100.010220.008561887011018670.00165811298898133
110.011660.015022987674505-0.00336298767450498
120.011410.0143215850610098-0.00291158506100981
130.005810.00786437609434905-0.00205437609434904
140.010410.0113397200458806-0.000929720045880637
150.006090.004190987485283580.00189901251471642
160.008390.003178413131165520.00521158686883448
170.018590.0193917021790382-0.000801702179038164
180.029190.02431023479317390.00487976520682612
190.03160.03113659128870160.000463408711298406
200.033650.0382644206596405-0.00461442065964052
210.038710.03275022236658670.00595977763341334
220.018490.0186007966120339-0.00011079661203386
230.01280.01193105595960110.000868944040398881
240.01840.01449836379425030.00390163620574971
250.017780.0220222529508515-0.00424225295085149
260.028870.02793470836694510.000935291633054879
270.010950.00979551043918190.00115448956081809
280.013280.01114701564619910.00213298435380087
290.006770.0128835887521632-0.00611358875216318
300.01170.016154516699354-0.00445451669935398
310.00339-0.001635766831346950.00502576683134695
320.00167-0.004597833088319550.00626783308831955
330.00119-0.0150271512635220.016217151263522
340.00072-0.0146975757357990.015417575735799
350.00065-0.01213235665213650.0127823566521365
360.00135-0.006774137349571450.00812413734957145
370.005860.003910701410261460.00194929858973854
380.0034-0.00488875851210290.0082887585121029
390.00231-0.009835886752682760.0121458867526828
400.00265-0.007052008900616780.00970200890061678
410.00231-0.005276045099643230.00758604509964323
420.00257-0.01023246348561970.0128024634856197
430.00740.0123097150034571-0.00490971500345711
440.006750.00805858854379609-0.00130858854379609
450.00454-4.91215131174288e-050.00458912151311743
460.004760.001091535917572010.00366846408242799
470.004760.0060466549385029-0.0012866549385029
480.00432-0.001694653943597670.00601465394359767
490.008390.0174305224070671-0.00904052240706713
500.004620.00799401683288397-0.00337401683288397
510.004790.004545212964481910.00024478703551809
520.004740.0123254537894798-0.00758545378947979
530.004810.0103598016268912-0.00554980162689115
540.004840.0141786113180199-0.0093386113180199
550.010360.00305314793556350.0073068520644365
560.01180.01170304206263329.69579373668054e-05
570.009690.004906562995777930.00478343700422207
580.006810.0013210023154920.005488997684508
590.007860.003291056845219310.00456894315478069
600.011430.0133300644221592-0.00190006442215923
610.008710.004819416669758880.00389058333024112
620.003010.0001074715495906170.00290252845040938
630.00340.002303514291763770.00109648570823623
640.003510.00711967390408594-0.00360967390408594
650.003-5.7623791752569e-050.00305762379175257
660.0042-0.002153588554704130.00635358855470412
670.021830.0372064935705391-0.0153764935705391
680.026590.0437618634047969-0.0171718634047969
690.048820.0648206258877459-0.0160006258877459
700.024310.0426471317040811-0.0183371317040811
710.025990.0405703506063042-0.0145803506063043
720.033610.0507164353164154-0.0171064353164154
730.004420.002369919886620920.00205008011337908
740.006230.0154893899346897-0.00925938993468972
750.00479-0.0016891331767470.006479133176747
760.004720.00624855048661397-0.00152855048661397
770.009050.0162278598720111-0.00717785987201114
780.0042-0.007576995448888650.0117769954488886
790.010620.0178883830672572-0.0072683830672572
800.02220.0512477496548809-0.0290477496548809
810.018230.0237320312807261-0.00550203128072615
820.018250.0297770983212895-0.0115270983212895
830.012370.01345917443349-0.00108917443348995
840.008820.003908170809771240.00491182919022876
850.05470.04504645586493380.00965354413506618
860.027820.01775216399520550.0100678360047945
870.031510.01780463853403190.0137053614659681
880.048240.03333601649017240.0149039835098276
890.042140.0263043105517840.015835689448216
900.072230.03744496604541220.0347850339545878
910.087250.04379320708082750.0434567929191725
920.016580.0298450383977505-0.0132650383977505
930.019140.01552098026676260.00361901973323738
940.012110.0210961412977804-0.00898614129778045
950.00850.00850467882168488-4.67882168488402e-06
960.010180.0127350087578882-0.00255500875788823
970.008520.0161812972430441-0.00766129724304415
980.081510.07826579910803370.00324420089196628
990.103230.0996310245894340.00359897541056596
1000.167440.1394762397401540.027963760259846
1010.314820.2793929758999430.0354270241000573
1020.118430.1074078831480390.0110221168519607
1030.25930.2305131400131790.028786859986821
1040.00495-0.009617175649982350.0145671756499824
1050.00243-0.005587984095030190.00801798409503019
1060.00578-0.0006569810374328390.00643698103743284
1070.00233-0.00415197539545170.0064819753954517
1080.006590.0020217036674450.004568296332555
1090.00238-0.006781936415058740.00916193641505874
1100.009470.0361517819863741-0.0266817819863741
1110.007040.0160857154032386-0.00904571540323858
1120.00830.0256902495061455-0.0173902495061455
1130.013160.0279890200120197-0.0148290200120197
1140.00620.0167608204154266-0.0105608204154266
1150.010480.0205841186958898-0.0101041186958898
1160.060510.03702761559595160.0234823844040484
1170.015540.0220434722475648-0.00650347224756479
1180.018020.01613276902415640.00188723097584361
1190.008560.0156855703320864-0.00712557033208637
1200.006810.0198935220071478-0.0130835220071478
1210.02350.027103913771914-0.00360391377191397
1220.011610.006233149485377980.00537685051462202
1230.019680.0308960003668624-0.0112160003668624
1240.018130.0314243687027077-0.0132943687027077
1250.02020.0240500621809375-0.00385006218093753
1260.018740.0233501891263376-0.00461018912633762
1270.017940.009602612572342610.00833738742765739
1280.017960.0205639636604175-0.00260396366041755
1290.017240.01591937724568690.00132062275431308
1300.00487-0.006183794039163590.0110537940391636
1310.01610.0204307602634911-0.00433076026349113
1320.010150.007958062712070070.00219193728792992
1330.009030.004662224187963870.00436777581203613
1340.005040.002795262874147370.00224473712585263
1350.030310.0310884592308279-0.000778459230827901
1360.025290.0255297511613829-0.000239751161382864
1370.022780.01238473806115640.0103952619388436
1380.03690.02772554580727710.00917445419272293
1390.026290.0329816808821208-0.00669168088212084
1400.018270.01478526328026670.00348473671973331
1410.024850.02468295902510350.000167040974896478
1420.042380.0517183414688555-0.00933834146885552
1430.017280.01583069944621240.00144930055378757
1440.02010.01433244204018490.00576755795981513
1450.010490.01014059799391950.000349402006080487
1460.014930.0203024195925629-0.00537241959256288
1470.07530.0907885942112931-0.0154885942112931
1480.060570.0903992568735996-0.0298292568735996
1490.080690.096573163989517-0.015883163989517
1500.078890.0924565503040601-0.0135665503040601
1510.109520.1090869296362470.000433070363752782
1520.217130.2063076183661720.0108223816338278
1530.162650.1609516993972570.00169830060274346
1540.041790.03279495972701510.00899504027298489
1550.046110.03086466273629580.0152453372637042
1560.026310.0217929714061550.00451702859384496
1570.031910.0505434656471378-0.0186334656471378
1580.107480.130364895009217-0.0228848950092172
1590.038280.0711144839562132-0.0328344839562132
1600.026630.02351305939314710.00311694060685292
1610.020730.01633183627569660.0043981637243034
1620.02810.0352408480898687-0.00714084808986871
1630.027070.0316417140594275-0.00457171405942749
1640.014350.0236442260955131-0.00929422609551311
1650.038820.0471414460266709-0.0083214460266709
1660.00620.0106314004844427-0.0044314004844427
1670.005330.0136746865118272-0.00834468651182724
1680.00910.022348135877156-0.013248135877156
1690.013370.0392170190900813-0.0258470190900813
1700.009650.0315953759233719-0.0219453759233719
1710.010490.0288104385007105-0.0183204385007105
1720.004350.00519883647322421-0.000848836473224213
1730.0043-0.002003505139916790.00630350513991679
1740.00478-0.001928334284261490.00670833428426149
1750.00590.002156933524344890.00374306647565511
1760.00401-0.002074346091363240.00608434609136324
1770.00415-0.005350948869757290.00950094886975729
1780.0057-0.0005101840758983210.00621018407589832
1790.00488-0.005167843526666720.0100478435266667
1800.0054-0.000952369207952560.00635236920795256
1810.006110.005968921366448060.000141078633551936
1820.00639-0.001424987138083860.00781498713808386
1830.00595-0.004374750962478970.010324750962479
1840.009550.0111200452620646-0.00157004526206463
1850.011790.0193713681610256-0.0075813681610256
1860.007370.005618554572612140.00175144542738786
1870.013970.0331076246645469-0.0191376246645469
1880.00680.0125382876415384-0.00573828764153842
1890.007030.0138669490952836-0.00683694909528358
1900.044410.04036677376711480.00404322623288519
1910.027640.034175305947352-0.00653530594735197
1920.01810.0318785927561223-0.0137785927561223
1930.107150.09226222415345010.0148877758465499
1940.072230.0450375756152890.027192424384711
1950.043980.01968062533025660.0242993746697434

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 0.02211 & 0.00770542943407452 & 0.0144045705659255 \tabularnewline
2 & 0.01929 & 0.0237007491384245 & -0.00441074913842454 \tabularnewline
3 & 0.01309 & 0.0292057435303475 & -0.0161157435303475 \tabularnewline
4 & 0.01353 & 0.0270403141375732 & -0.0135103141375732 \tabularnewline
5 & 0.01767 & 0.0425584071035489 & -0.0248884071035489 \tabularnewline
6 & 0.01222 & 0.0106335948218654 & 0.00158640517813456 \tabularnewline
7 & 0.00607 & -0.00872124757534366 & 0.0147912475753437 \tabularnewline
8 & 0.00344 & -0.0106590450675978 & 0.0140990450675978 \tabularnewline
9 & 0.0107 & 0.0174871117147491 & -0.00678711171474914 \tabularnewline
10 & 0.01022 & 0.00856188701101867 & 0.00165811298898133 \tabularnewline
11 & 0.01166 & 0.015022987674505 & -0.00336298767450498 \tabularnewline
12 & 0.01141 & 0.0143215850610098 & -0.00291158506100981 \tabularnewline
13 & 0.00581 & 0.00786437609434905 & -0.00205437609434904 \tabularnewline
14 & 0.01041 & 0.0113397200458806 & -0.000929720045880637 \tabularnewline
15 & 0.00609 & 0.00419098748528358 & 0.00189901251471642 \tabularnewline
16 & 0.00839 & 0.00317841313116552 & 0.00521158686883448 \tabularnewline
17 & 0.01859 & 0.0193917021790382 & -0.000801702179038164 \tabularnewline
18 & 0.02919 & 0.0243102347931739 & 0.00487976520682612 \tabularnewline
19 & 0.0316 & 0.0311365912887016 & 0.000463408711298406 \tabularnewline
20 & 0.03365 & 0.0382644206596405 & -0.00461442065964052 \tabularnewline
21 & 0.03871 & 0.0327502223665867 & 0.00595977763341334 \tabularnewline
22 & 0.01849 & 0.0186007966120339 & -0.00011079661203386 \tabularnewline
23 & 0.0128 & 0.0119310559596011 & 0.000868944040398881 \tabularnewline
24 & 0.0184 & 0.0144983637942503 & 0.00390163620574971 \tabularnewline
25 & 0.01778 & 0.0220222529508515 & -0.00424225295085149 \tabularnewline
26 & 0.02887 & 0.0279347083669451 & 0.000935291633054879 \tabularnewline
27 & 0.01095 & 0.0097955104391819 & 0.00115448956081809 \tabularnewline
28 & 0.01328 & 0.0111470156461991 & 0.00213298435380087 \tabularnewline
29 & 0.00677 & 0.0128835887521632 & -0.00611358875216318 \tabularnewline
30 & 0.0117 & 0.016154516699354 & -0.00445451669935398 \tabularnewline
31 & 0.00339 & -0.00163576683134695 & 0.00502576683134695 \tabularnewline
32 & 0.00167 & -0.00459783308831955 & 0.00626783308831955 \tabularnewline
33 & 0.00119 & -0.015027151263522 & 0.016217151263522 \tabularnewline
34 & 0.00072 & -0.014697575735799 & 0.015417575735799 \tabularnewline
35 & 0.00065 & -0.0121323566521365 & 0.0127823566521365 \tabularnewline
36 & 0.00135 & -0.00677413734957145 & 0.00812413734957145 \tabularnewline
37 & 0.00586 & 0.00391070141026146 & 0.00194929858973854 \tabularnewline
38 & 0.0034 & -0.0048887585121029 & 0.0082887585121029 \tabularnewline
39 & 0.00231 & -0.00983588675268276 & 0.0121458867526828 \tabularnewline
40 & 0.00265 & -0.00705200890061678 & 0.00970200890061678 \tabularnewline
41 & 0.00231 & -0.00527604509964323 & 0.00758604509964323 \tabularnewline
42 & 0.00257 & -0.0102324634856197 & 0.0128024634856197 \tabularnewline
43 & 0.0074 & 0.0123097150034571 & -0.00490971500345711 \tabularnewline
44 & 0.00675 & 0.00805858854379609 & -0.00130858854379609 \tabularnewline
45 & 0.00454 & -4.91215131174288e-05 & 0.00458912151311743 \tabularnewline
46 & 0.00476 & 0.00109153591757201 & 0.00366846408242799 \tabularnewline
47 & 0.00476 & 0.0060466549385029 & -0.0012866549385029 \tabularnewline
48 & 0.00432 & -0.00169465394359767 & 0.00601465394359767 \tabularnewline
49 & 0.00839 & 0.0174305224070671 & -0.00904052240706713 \tabularnewline
50 & 0.00462 & 0.00799401683288397 & -0.00337401683288397 \tabularnewline
51 & 0.00479 & 0.00454521296448191 & 0.00024478703551809 \tabularnewline
52 & 0.00474 & 0.0123254537894798 & -0.00758545378947979 \tabularnewline
53 & 0.00481 & 0.0103598016268912 & -0.00554980162689115 \tabularnewline
54 & 0.00484 & 0.0141786113180199 & -0.0093386113180199 \tabularnewline
55 & 0.01036 & 0.0030531479355635 & 0.0073068520644365 \tabularnewline
56 & 0.0118 & 0.0117030420626332 & 9.69579373668054e-05 \tabularnewline
57 & 0.00969 & 0.00490656299577793 & 0.00478343700422207 \tabularnewline
58 & 0.00681 & 0.001321002315492 & 0.005488997684508 \tabularnewline
59 & 0.00786 & 0.00329105684521931 & 0.00456894315478069 \tabularnewline
60 & 0.01143 & 0.0133300644221592 & -0.00190006442215923 \tabularnewline
61 & 0.00871 & 0.00481941666975888 & 0.00389058333024112 \tabularnewline
62 & 0.00301 & 0.000107471549590617 & 0.00290252845040938 \tabularnewline
63 & 0.0034 & 0.00230351429176377 & 0.00109648570823623 \tabularnewline
64 & 0.00351 & 0.00711967390408594 & -0.00360967390408594 \tabularnewline
65 & 0.003 & -5.7623791752569e-05 & 0.00305762379175257 \tabularnewline
66 & 0.0042 & -0.00215358855470413 & 0.00635358855470412 \tabularnewline
67 & 0.02183 & 0.0372064935705391 & -0.0153764935705391 \tabularnewline
68 & 0.02659 & 0.0437618634047969 & -0.0171718634047969 \tabularnewline
69 & 0.04882 & 0.0648206258877459 & -0.0160006258877459 \tabularnewline
70 & 0.02431 & 0.0426471317040811 & -0.0183371317040811 \tabularnewline
71 & 0.02599 & 0.0405703506063042 & -0.0145803506063043 \tabularnewline
72 & 0.03361 & 0.0507164353164154 & -0.0171064353164154 \tabularnewline
73 & 0.00442 & 0.00236991988662092 & 0.00205008011337908 \tabularnewline
74 & 0.00623 & 0.0154893899346897 & -0.00925938993468972 \tabularnewline
75 & 0.00479 & -0.001689133176747 & 0.006479133176747 \tabularnewline
76 & 0.00472 & 0.00624855048661397 & -0.00152855048661397 \tabularnewline
77 & 0.00905 & 0.0162278598720111 & -0.00717785987201114 \tabularnewline
78 & 0.0042 & -0.00757699544888865 & 0.0117769954488886 \tabularnewline
79 & 0.01062 & 0.0178883830672572 & -0.0072683830672572 \tabularnewline
80 & 0.0222 & 0.0512477496548809 & -0.0290477496548809 \tabularnewline
81 & 0.01823 & 0.0237320312807261 & -0.00550203128072615 \tabularnewline
82 & 0.01825 & 0.0297770983212895 & -0.0115270983212895 \tabularnewline
83 & 0.01237 & 0.01345917443349 & -0.00108917443348995 \tabularnewline
84 & 0.00882 & 0.00390817080977124 & 0.00491182919022876 \tabularnewline
85 & 0.0547 & 0.0450464558649338 & 0.00965354413506618 \tabularnewline
86 & 0.02782 & 0.0177521639952055 & 0.0100678360047945 \tabularnewline
87 & 0.03151 & 0.0178046385340319 & 0.0137053614659681 \tabularnewline
88 & 0.04824 & 0.0333360164901724 & 0.0149039835098276 \tabularnewline
89 & 0.04214 & 0.026304310551784 & 0.015835689448216 \tabularnewline
90 & 0.07223 & 0.0374449660454122 & 0.0347850339545878 \tabularnewline
91 & 0.08725 & 0.0437932070808275 & 0.0434567929191725 \tabularnewline
92 & 0.01658 & 0.0298450383977505 & -0.0132650383977505 \tabularnewline
93 & 0.01914 & 0.0155209802667626 & 0.00361901973323738 \tabularnewline
94 & 0.01211 & 0.0210961412977804 & -0.00898614129778045 \tabularnewline
95 & 0.0085 & 0.00850467882168488 & -4.67882168488402e-06 \tabularnewline
96 & 0.01018 & 0.0127350087578882 & -0.00255500875788823 \tabularnewline
97 & 0.00852 & 0.0161812972430441 & -0.00766129724304415 \tabularnewline
98 & 0.08151 & 0.0782657991080337 & 0.00324420089196628 \tabularnewline
99 & 0.10323 & 0.099631024589434 & 0.00359897541056596 \tabularnewline
100 & 0.16744 & 0.139476239740154 & 0.027963760259846 \tabularnewline
101 & 0.31482 & 0.279392975899943 & 0.0354270241000573 \tabularnewline
102 & 0.11843 & 0.107407883148039 & 0.0110221168519607 \tabularnewline
103 & 0.2593 & 0.230513140013179 & 0.028786859986821 \tabularnewline
104 & 0.00495 & -0.00961717564998235 & 0.0145671756499824 \tabularnewline
105 & 0.00243 & -0.00558798409503019 & 0.00801798409503019 \tabularnewline
106 & 0.00578 & -0.000656981037432839 & 0.00643698103743284 \tabularnewline
107 & 0.00233 & -0.0041519753954517 & 0.0064819753954517 \tabularnewline
108 & 0.00659 & 0.002021703667445 & 0.004568296332555 \tabularnewline
109 & 0.00238 & -0.00678193641505874 & 0.00916193641505874 \tabularnewline
110 & 0.00947 & 0.0361517819863741 & -0.0266817819863741 \tabularnewline
111 & 0.00704 & 0.0160857154032386 & -0.00904571540323858 \tabularnewline
112 & 0.0083 & 0.0256902495061455 & -0.0173902495061455 \tabularnewline
113 & 0.01316 & 0.0279890200120197 & -0.0148290200120197 \tabularnewline
114 & 0.0062 & 0.0167608204154266 & -0.0105608204154266 \tabularnewline
115 & 0.01048 & 0.0205841186958898 & -0.0101041186958898 \tabularnewline
116 & 0.06051 & 0.0370276155959516 & 0.0234823844040484 \tabularnewline
117 & 0.01554 & 0.0220434722475648 & -0.00650347224756479 \tabularnewline
118 & 0.01802 & 0.0161327690241564 & 0.00188723097584361 \tabularnewline
119 & 0.00856 & 0.0156855703320864 & -0.00712557033208637 \tabularnewline
120 & 0.00681 & 0.0198935220071478 & -0.0130835220071478 \tabularnewline
121 & 0.0235 & 0.027103913771914 & -0.00360391377191397 \tabularnewline
122 & 0.01161 & 0.00623314948537798 & 0.00537685051462202 \tabularnewline
123 & 0.01968 & 0.0308960003668624 & -0.0112160003668624 \tabularnewline
124 & 0.01813 & 0.0314243687027077 & -0.0132943687027077 \tabularnewline
125 & 0.0202 & 0.0240500621809375 & -0.00385006218093753 \tabularnewline
126 & 0.01874 & 0.0233501891263376 & -0.00461018912633762 \tabularnewline
127 & 0.01794 & 0.00960261257234261 & 0.00833738742765739 \tabularnewline
128 & 0.01796 & 0.0205639636604175 & -0.00260396366041755 \tabularnewline
129 & 0.01724 & 0.0159193772456869 & 0.00132062275431308 \tabularnewline
130 & 0.00487 & -0.00618379403916359 & 0.0110537940391636 \tabularnewline
131 & 0.0161 & 0.0204307602634911 & -0.00433076026349113 \tabularnewline
132 & 0.01015 & 0.00795806271207007 & 0.00219193728792992 \tabularnewline
133 & 0.00903 & 0.00466222418796387 & 0.00436777581203613 \tabularnewline
134 & 0.00504 & 0.00279526287414737 & 0.00224473712585263 \tabularnewline
135 & 0.03031 & 0.0310884592308279 & -0.000778459230827901 \tabularnewline
136 & 0.02529 & 0.0255297511613829 & -0.000239751161382864 \tabularnewline
137 & 0.02278 & 0.0123847380611564 & 0.0103952619388436 \tabularnewline
138 & 0.0369 & 0.0277255458072771 & 0.00917445419272293 \tabularnewline
139 & 0.02629 & 0.0329816808821208 & -0.00669168088212084 \tabularnewline
140 & 0.01827 & 0.0147852632802667 & 0.00348473671973331 \tabularnewline
141 & 0.02485 & 0.0246829590251035 & 0.000167040974896478 \tabularnewline
142 & 0.04238 & 0.0517183414688555 & -0.00933834146885552 \tabularnewline
143 & 0.01728 & 0.0158306994462124 & 0.00144930055378757 \tabularnewline
144 & 0.0201 & 0.0143324420401849 & 0.00576755795981513 \tabularnewline
145 & 0.01049 & 0.0101405979939195 & 0.000349402006080487 \tabularnewline
146 & 0.01493 & 0.0203024195925629 & -0.00537241959256288 \tabularnewline
147 & 0.0753 & 0.0907885942112931 & -0.0154885942112931 \tabularnewline
148 & 0.06057 & 0.0903992568735996 & -0.0298292568735996 \tabularnewline
149 & 0.08069 & 0.096573163989517 & -0.015883163989517 \tabularnewline
150 & 0.07889 & 0.0924565503040601 & -0.0135665503040601 \tabularnewline
151 & 0.10952 & 0.109086929636247 & 0.000433070363752782 \tabularnewline
152 & 0.21713 & 0.206307618366172 & 0.0108223816338278 \tabularnewline
153 & 0.16265 & 0.160951699397257 & 0.00169830060274346 \tabularnewline
154 & 0.04179 & 0.0327949597270151 & 0.00899504027298489 \tabularnewline
155 & 0.04611 & 0.0308646627362958 & 0.0152453372637042 \tabularnewline
156 & 0.02631 & 0.021792971406155 & 0.00451702859384496 \tabularnewline
157 & 0.03191 & 0.0505434656471378 & -0.0186334656471378 \tabularnewline
158 & 0.10748 & 0.130364895009217 & -0.0228848950092172 \tabularnewline
159 & 0.03828 & 0.0711144839562132 & -0.0328344839562132 \tabularnewline
160 & 0.02663 & 0.0235130593931471 & 0.00311694060685292 \tabularnewline
161 & 0.02073 & 0.0163318362756966 & 0.0043981637243034 \tabularnewline
162 & 0.0281 & 0.0352408480898687 & -0.00714084808986871 \tabularnewline
163 & 0.02707 & 0.0316417140594275 & -0.00457171405942749 \tabularnewline
164 & 0.01435 & 0.0236442260955131 & -0.00929422609551311 \tabularnewline
165 & 0.03882 & 0.0471414460266709 & -0.0083214460266709 \tabularnewline
166 & 0.0062 & 0.0106314004844427 & -0.0044314004844427 \tabularnewline
167 & 0.00533 & 0.0136746865118272 & -0.00834468651182724 \tabularnewline
168 & 0.0091 & 0.022348135877156 & -0.013248135877156 \tabularnewline
169 & 0.01337 & 0.0392170190900813 & -0.0258470190900813 \tabularnewline
170 & 0.00965 & 0.0315953759233719 & -0.0219453759233719 \tabularnewline
171 & 0.01049 & 0.0288104385007105 & -0.0183204385007105 \tabularnewline
172 & 0.00435 & 0.00519883647322421 & -0.000848836473224213 \tabularnewline
173 & 0.0043 & -0.00200350513991679 & 0.00630350513991679 \tabularnewline
174 & 0.00478 & -0.00192833428426149 & 0.00670833428426149 \tabularnewline
175 & 0.0059 & 0.00215693352434489 & 0.00374306647565511 \tabularnewline
176 & 0.00401 & -0.00207434609136324 & 0.00608434609136324 \tabularnewline
177 & 0.00415 & -0.00535094886975729 & 0.00950094886975729 \tabularnewline
178 & 0.0057 & -0.000510184075898321 & 0.00621018407589832 \tabularnewline
179 & 0.00488 & -0.00516784352666672 & 0.0100478435266667 \tabularnewline
180 & 0.0054 & -0.00095236920795256 & 0.00635236920795256 \tabularnewline
181 & 0.00611 & 0.00596892136644806 & 0.000141078633551936 \tabularnewline
182 & 0.00639 & -0.00142498713808386 & 0.00781498713808386 \tabularnewline
183 & 0.00595 & -0.00437475096247897 & 0.010324750962479 \tabularnewline
184 & 0.00955 & 0.0111200452620646 & -0.00157004526206463 \tabularnewline
185 & 0.01179 & 0.0193713681610256 & -0.0075813681610256 \tabularnewline
186 & 0.00737 & 0.00561855457261214 & 0.00175144542738786 \tabularnewline
187 & 0.01397 & 0.0331076246645469 & -0.0191376246645469 \tabularnewline
188 & 0.0068 & 0.0125382876415384 & -0.00573828764153842 \tabularnewline
189 & 0.00703 & 0.0138669490952836 & -0.00683694909528358 \tabularnewline
190 & 0.04441 & 0.0403667737671148 & 0.00404322623288519 \tabularnewline
191 & 0.02764 & 0.034175305947352 & -0.00653530594735197 \tabularnewline
192 & 0.0181 & 0.0318785927561223 & -0.0137785927561223 \tabularnewline
193 & 0.10715 & 0.0922622241534501 & 0.0148877758465499 \tabularnewline
194 & 0.07223 & 0.045037575615289 & 0.027192424384711 \tabularnewline
195 & 0.04398 & 0.0196806253302566 & 0.0242993746697434 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231280&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]0.02211[/C][C]0.00770542943407452[/C][C]0.0144045705659255[/C][/ROW]
[ROW][C]2[/C][C]0.01929[/C][C]0.0237007491384245[/C][C]-0.00441074913842454[/C][/ROW]
[ROW][C]3[/C][C]0.01309[/C][C]0.0292057435303475[/C][C]-0.0161157435303475[/C][/ROW]
[ROW][C]4[/C][C]0.01353[/C][C]0.0270403141375732[/C][C]-0.0135103141375732[/C][/ROW]
[ROW][C]5[/C][C]0.01767[/C][C]0.0425584071035489[/C][C]-0.0248884071035489[/C][/ROW]
[ROW][C]6[/C][C]0.01222[/C][C]0.0106335948218654[/C][C]0.00158640517813456[/C][/ROW]
[ROW][C]7[/C][C]0.00607[/C][C]-0.00872124757534366[/C][C]0.0147912475753437[/C][/ROW]
[ROW][C]8[/C][C]0.00344[/C][C]-0.0106590450675978[/C][C]0.0140990450675978[/C][/ROW]
[ROW][C]9[/C][C]0.0107[/C][C]0.0174871117147491[/C][C]-0.00678711171474914[/C][/ROW]
[ROW][C]10[/C][C]0.01022[/C][C]0.00856188701101867[/C][C]0.00165811298898133[/C][/ROW]
[ROW][C]11[/C][C]0.01166[/C][C]0.015022987674505[/C][C]-0.00336298767450498[/C][/ROW]
[ROW][C]12[/C][C]0.01141[/C][C]0.0143215850610098[/C][C]-0.00291158506100981[/C][/ROW]
[ROW][C]13[/C][C]0.00581[/C][C]0.00786437609434905[/C][C]-0.00205437609434904[/C][/ROW]
[ROW][C]14[/C][C]0.01041[/C][C]0.0113397200458806[/C][C]-0.000929720045880637[/C][/ROW]
[ROW][C]15[/C][C]0.00609[/C][C]0.00419098748528358[/C][C]0.00189901251471642[/C][/ROW]
[ROW][C]16[/C][C]0.00839[/C][C]0.00317841313116552[/C][C]0.00521158686883448[/C][/ROW]
[ROW][C]17[/C][C]0.01859[/C][C]0.0193917021790382[/C][C]-0.000801702179038164[/C][/ROW]
[ROW][C]18[/C][C]0.02919[/C][C]0.0243102347931739[/C][C]0.00487976520682612[/C][/ROW]
[ROW][C]19[/C][C]0.0316[/C][C]0.0311365912887016[/C][C]0.000463408711298406[/C][/ROW]
[ROW][C]20[/C][C]0.03365[/C][C]0.0382644206596405[/C][C]-0.00461442065964052[/C][/ROW]
[ROW][C]21[/C][C]0.03871[/C][C]0.0327502223665867[/C][C]0.00595977763341334[/C][/ROW]
[ROW][C]22[/C][C]0.01849[/C][C]0.0186007966120339[/C][C]-0.00011079661203386[/C][/ROW]
[ROW][C]23[/C][C]0.0128[/C][C]0.0119310559596011[/C][C]0.000868944040398881[/C][/ROW]
[ROW][C]24[/C][C]0.0184[/C][C]0.0144983637942503[/C][C]0.00390163620574971[/C][/ROW]
[ROW][C]25[/C][C]0.01778[/C][C]0.0220222529508515[/C][C]-0.00424225295085149[/C][/ROW]
[ROW][C]26[/C][C]0.02887[/C][C]0.0279347083669451[/C][C]0.000935291633054879[/C][/ROW]
[ROW][C]27[/C][C]0.01095[/C][C]0.0097955104391819[/C][C]0.00115448956081809[/C][/ROW]
[ROW][C]28[/C][C]0.01328[/C][C]0.0111470156461991[/C][C]0.00213298435380087[/C][/ROW]
[ROW][C]29[/C][C]0.00677[/C][C]0.0128835887521632[/C][C]-0.00611358875216318[/C][/ROW]
[ROW][C]30[/C][C]0.0117[/C][C]0.016154516699354[/C][C]-0.00445451669935398[/C][/ROW]
[ROW][C]31[/C][C]0.00339[/C][C]-0.00163576683134695[/C][C]0.00502576683134695[/C][/ROW]
[ROW][C]32[/C][C]0.00167[/C][C]-0.00459783308831955[/C][C]0.00626783308831955[/C][/ROW]
[ROW][C]33[/C][C]0.00119[/C][C]-0.015027151263522[/C][C]0.016217151263522[/C][/ROW]
[ROW][C]34[/C][C]0.00072[/C][C]-0.014697575735799[/C][C]0.015417575735799[/C][/ROW]
[ROW][C]35[/C][C]0.00065[/C][C]-0.0121323566521365[/C][C]0.0127823566521365[/C][/ROW]
[ROW][C]36[/C][C]0.00135[/C][C]-0.00677413734957145[/C][C]0.00812413734957145[/C][/ROW]
[ROW][C]37[/C][C]0.00586[/C][C]0.00391070141026146[/C][C]0.00194929858973854[/C][/ROW]
[ROW][C]38[/C][C]0.0034[/C][C]-0.0048887585121029[/C][C]0.0082887585121029[/C][/ROW]
[ROW][C]39[/C][C]0.00231[/C][C]-0.00983588675268276[/C][C]0.0121458867526828[/C][/ROW]
[ROW][C]40[/C][C]0.00265[/C][C]-0.00705200890061678[/C][C]0.00970200890061678[/C][/ROW]
[ROW][C]41[/C][C]0.00231[/C][C]-0.00527604509964323[/C][C]0.00758604509964323[/C][/ROW]
[ROW][C]42[/C][C]0.00257[/C][C]-0.0102324634856197[/C][C]0.0128024634856197[/C][/ROW]
[ROW][C]43[/C][C]0.0074[/C][C]0.0123097150034571[/C][C]-0.00490971500345711[/C][/ROW]
[ROW][C]44[/C][C]0.00675[/C][C]0.00805858854379609[/C][C]-0.00130858854379609[/C][/ROW]
[ROW][C]45[/C][C]0.00454[/C][C]-4.91215131174288e-05[/C][C]0.00458912151311743[/C][/ROW]
[ROW][C]46[/C][C]0.00476[/C][C]0.00109153591757201[/C][C]0.00366846408242799[/C][/ROW]
[ROW][C]47[/C][C]0.00476[/C][C]0.0060466549385029[/C][C]-0.0012866549385029[/C][/ROW]
[ROW][C]48[/C][C]0.00432[/C][C]-0.00169465394359767[/C][C]0.00601465394359767[/C][/ROW]
[ROW][C]49[/C][C]0.00839[/C][C]0.0174305224070671[/C][C]-0.00904052240706713[/C][/ROW]
[ROW][C]50[/C][C]0.00462[/C][C]0.00799401683288397[/C][C]-0.00337401683288397[/C][/ROW]
[ROW][C]51[/C][C]0.00479[/C][C]0.00454521296448191[/C][C]0.00024478703551809[/C][/ROW]
[ROW][C]52[/C][C]0.00474[/C][C]0.0123254537894798[/C][C]-0.00758545378947979[/C][/ROW]
[ROW][C]53[/C][C]0.00481[/C][C]0.0103598016268912[/C][C]-0.00554980162689115[/C][/ROW]
[ROW][C]54[/C][C]0.00484[/C][C]0.0141786113180199[/C][C]-0.0093386113180199[/C][/ROW]
[ROW][C]55[/C][C]0.01036[/C][C]0.0030531479355635[/C][C]0.0073068520644365[/C][/ROW]
[ROW][C]56[/C][C]0.0118[/C][C]0.0117030420626332[/C][C]9.69579373668054e-05[/C][/ROW]
[ROW][C]57[/C][C]0.00969[/C][C]0.00490656299577793[/C][C]0.00478343700422207[/C][/ROW]
[ROW][C]58[/C][C]0.00681[/C][C]0.001321002315492[/C][C]0.005488997684508[/C][/ROW]
[ROW][C]59[/C][C]0.00786[/C][C]0.00329105684521931[/C][C]0.00456894315478069[/C][/ROW]
[ROW][C]60[/C][C]0.01143[/C][C]0.0133300644221592[/C][C]-0.00190006442215923[/C][/ROW]
[ROW][C]61[/C][C]0.00871[/C][C]0.00481941666975888[/C][C]0.00389058333024112[/C][/ROW]
[ROW][C]62[/C][C]0.00301[/C][C]0.000107471549590617[/C][C]0.00290252845040938[/C][/ROW]
[ROW][C]63[/C][C]0.0034[/C][C]0.00230351429176377[/C][C]0.00109648570823623[/C][/ROW]
[ROW][C]64[/C][C]0.00351[/C][C]0.00711967390408594[/C][C]-0.00360967390408594[/C][/ROW]
[ROW][C]65[/C][C]0.003[/C][C]-5.7623791752569e-05[/C][C]0.00305762379175257[/C][/ROW]
[ROW][C]66[/C][C]0.0042[/C][C]-0.00215358855470413[/C][C]0.00635358855470412[/C][/ROW]
[ROW][C]67[/C][C]0.02183[/C][C]0.0372064935705391[/C][C]-0.0153764935705391[/C][/ROW]
[ROW][C]68[/C][C]0.02659[/C][C]0.0437618634047969[/C][C]-0.0171718634047969[/C][/ROW]
[ROW][C]69[/C][C]0.04882[/C][C]0.0648206258877459[/C][C]-0.0160006258877459[/C][/ROW]
[ROW][C]70[/C][C]0.02431[/C][C]0.0426471317040811[/C][C]-0.0183371317040811[/C][/ROW]
[ROW][C]71[/C][C]0.02599[/C][C]0.0405703506063042[/C][C]-0.0145803506063043[/C][/ROW]
[ROW][C]72[/C][C]0.03361[/C][C]0.0507164353164154[/C][C]-0.0171064353164154[/C][/ROW]
[ROW][C]73[/C][C]0.00442[/C][C]0.00236991988662092[/C][C]0.00205008011337908[/C][/ROW]
[ROW][C]74[/C][C]0.00623[/C][C]0.0154893899346897[/C][C]-0.00925938993468972[/C][/ROW]
[ROW][C]75[/C][C]0.00479[/C][C]-0.001689133176747[/C][C]0.006479133176747[/C][/ROW]
[ROW][C]76[/C][C]0.00472[/C][C]0.00624855048661397[/C][C]-0.00152855048661397[/C][/ROW]
[ROW][C]77[/C][C]0.00905[/C][C]0.0162278598720111[/C][C]-0.00717785987201114[/C][/ROW]
[ROW][C]78[/C][C]0.0042[/C][C]-0.00757699544888865[/C][C]0.0117769954488886[/C][/ROW]
[ROW][C]79[/C][C]0.01062[/C][C]0.0178883830672572[/C][C]-0.0072683830672572[/C][/ROW]
[ROW][C]80[/C][C]0.0222[/C][C]0.0512477496548809[/C][C]-0.0290477496548809[/C][/ROW]
[ROW][C]81[/C][C]0.01823[/C][C]0.0237320312807261[/C][C]-0.00550203128072615[/C][/ROW]
[ROW][C]82[/C][C]0.01825[/C][C]0.0297770983212895[/C][C]-0.0115270983212895[/C][/ROW]
[ROW][C]83[/C][C]0.01237[/C][C]0.01345917443349[/C][C]-0.00108917443348995[/C][/ROW]
[ROW][C]84[/C][C]0.00882[/C][C]0.00390817080977124[/C][C]0.00491182919022876[/C][/ROW]
[ROW][C]85[/C][C]0.0547[/C][C]0.0450464558649338[/C][C]0.00965354413506618[/C][/ROW]
[ROW][C]86[/C][C]0.02782[/C][C]0.0177521639952055[/C][C]0.0100678360047945[/C][/ROW]
[ROW][C]87[/C][C]0.03151[/C][C]0.0178046385340319[/C][C]0.0137053614659681[/C][/ROW]
[ROW][C]88[/C][C]0.04824[/C][C]0.0333360164901724[/C][C]0.0149039835098276[/C][/ROW]
[ROW][C]89[/C][C]0.04214[/C][C]0.026304310551784[/C][C]0.015835689448216[/C][/ROW]
[ROW][C]90[/C][C]0.07223[/C][C]0.0374449660454122[/C][C]0.0347850339545878[/C][/ROW]
[ROW][C]91[/C][C]0.08725[/C][C]0.0437932070808275[/C][C]0.0434567929191725[/C][/ROW]
[ROW][C]92[/C][C]0.01658[/C][C]0.0298450383977505[/C][C]-0.0132650383977505[/C][/ROW]
[ROW][C]93[/C][C]0.01914[/C][C]0.0155209802667626[/C][C]0.00361901973323738[/C][/ROW]
[ROW][C]94[/C][C]0.01211[/C][C]0.0210961412977804[/C][C]-0.00898614129778045[/C][/ROW]
[ROW][C]95[/C][C]0.0085[/C][C]0.00850467882168488[/C][C]-4.67882168488402e-06[/C][/ROW]
[ROW][C]96[/C][C]0.01018[/C][C]0.0127350087578882[/C][C]-0.00255500875788823[/C][/ROW]
[ROW][C]97[/C][C]0.00852[/C][C]0.0161812972430441[/C][C]-0.00766129724304415[/C][/ROW]
[ROW][C]98[/C][C]0.08151[/C][C]0.0782657991080337[/C][C]0.00324420089196628[/C][/ROW]
[ROW][C]99[/C][C]0.10323[/C][C]0.099631024589434[/C][C]0.00359897541056596[/C][/ROW]
[ROW][C]100[/C][C]0.16744[/C][C]0.139476239740154[/C][C]0.027963760259846[/C][/ROW]
[ROW][C]101[/C][C]0.31482[/C][C]0.279392975899943[/C][C]0.0354270241000573[/C][/ROW]
[ROW][C]102[/C][C]0.11843[/C][C]0.107407883148039[/C][C]0.0110221168519607[/C][/ROW]
[ROW][C]103[/C][C]0.2593[/C][C]0.230513140013179[/C][C]0.028786859986821[/C][/ROW]
[ROW][C]104[/C][C]0.00495[/C][C]-0.00961717564998235[/C][C]0.0145671756499824[/C][/ROW]
[ROW][C]105[/C][C]0.00243[/C][C]-0.00558798409503019[/C][C]0.00801798409503019[/C][/ROW]
[ROW][C]106[/C][C]0.00578[/C][C]-0.000656981037432839[/C][C]0.00643698103743284[/C][/ROW]
[ROW][C]107[/C][C]0.00233[/C][C]-0.0041519753954517[/C][C]0.0064819753954517[/C][/ROW]
[ROW][C]108[/C][C]0.00659[/C][C]0.002021703667445[/C][C]0.004568296332555[/C][/ROW]
[ROW][C]109[/C][C]0.00238[/C][C]-0.00678193641505874[/C][C]0.00916193641505874[/C][/ROW]
[ROW][C]110[/C][C]0.00947[/C][C]0.0361517819863741[/C][C]-0.0266817819863741[/C][/ROW]
[ROW][C]111[/C][C]0.00704[/C][C]0.0160857154032386[/C][C]-0.00904571540323858[/C][/ROW]
[ROW][C]112[/C][C]0.0083[/C][C]0.0256902495061455[/C][C]-0.0173902495061455[/C][/ROW]
[ROW][C]113[/C][C]0.01316[/C][C]0.0279890200120197[/C][C]-0.0148290200120197[/C][/ROW]
[ROW][C]114[/C][C]0.0062[/C][C]0.0167608204154266[/C][C]-0.0105608204154266[/C][/ROW]
[ROW][C]115[/C][C]0.01048[/C][C]0.0205841186958898[/C][C]-0.0101041186958898[/C][/ROW]
[ROW][C]116[/C][C]0.06051[/C][C]0.0370276155959516[/C][C]0.0234823844040484[/C][/ROW]
[ROW][C]117[/C][C]0.01554[/C][C]0.0220434722475648[/C][C]-0.00650347224756479[/C][/ROW]
[ROW][C]118[/C][C]0.01802[/C][C]0.0161327690241564[/C][C]0.00188723097584361[/C][/ROW]
[ROW][C]119[/C][C]0.00856[/C][C]0.0156855703320864[/C][C]-0.00712557033208637[/C][/ROW]
[ROW][C]120[/C][C]0.00681[/C][C]0.0198935220071478[/C][C]-0.0130835220071478[/C][/ROW]
[ROW][C]121[/C][C]0.0235[/C][C]0.027103913771914[/C][C]-0.00360391377191397[/C][/ROW]
[ROW][C]122[/C][C]0.01161[/C][C]0.00623314948537798[/C][C]0.00537685051462202[/C][/ROW]
[ROW][C]123[/C][C]0.01968[/C][C]0.0308960003668624[/C][C]-0.0112160003668624[/C][/ROW]
[ROW][C]124[/C][C]0.01813[/C][C]0.0314243687027077[/C][C]-0.0132943687027077[/C][/ROW]
[ROW][C]125[/C][C]0.0202[/C][C]0.0240500621809375[/C][C]-0.00385006218093753[/C][/ROW]
[ROW][C]126[/C][C]0.01874[/C][C]0.0233501891263376[/C][C]-0.00461018912633762[/C][/ROW]
[ROW][C]127[/C][C]0.01794[/C][C]0.00960261257234261[/C][C]0.00833738742765739[/C][/ROW]
[ROW][C]128[/C][C]0.01796[/C][C]0.0205639636604175[/C][C]-0.00260396366041755[/C][/ROW]
[ROW][C]129[/C][C]0.01724[/C][C]0.0159193772456869[/C][C]0.00132062275431308[/C][/ROW]
[ROW][C]130[/C][C]0.00487[/C][C]-0.00618379403916359[/C][C]0.0110537940391636[/C][/ROW]
[ROW][C]131[/C][C]0.0161[/C][C]0.0204307602634911[/C][C]-0.00433076026349113[/C][/ROW]
[ROW][C]132[/C][C]0.01015[/C][C]0.00795806271207007[/C][C]0.00219193728792992[/C][/ROW]
[ROW][C]133[/C][C]0.00903[/C][C]0.00466222418796387[/C][C]0.00436777581203613[/C][/ROW]
[ROW][C]134[/C][C]0.00504[/C][C]0.00279526287414737[/C][C]0.00224473712585263[/C][/ROW]
[ROW][C]135[/C][C]0.03031[/C][C]0.0310884592308279[/C][C]-0.000778459230827901[/C][/ROW]
[ROW][C]136[/C][C]0.02529[/C][C]0.0255297511613829[/C][C]-0.000239751161382864[/C][/ROW]
[ROW][C]137[/C][C]0.02278[/C][C]0.0123847380611564[/C][C]0.0103952619388436[/C][/ROW]
[ROW][C]138[/C][C]0.0369[/C][C]0.0277255458072771[/C][C]0.00917445419272293[/C][/ROW]
[ROW][C]139[/C][C]0.02629[/C][C]0.0329816808821208[/C][C]-0.00669168088212084[/C][/ROW]
[ROW][C]140[/C][C]0.01827[/C][C]0.0147852632802667[/C][C]0.00348473671973331[/C][/ROW]
[ROW][C]141[/C][C]0.02485[/C][C]0.0246829590251035[/C][C]0.000167040974896478[/C][/ROW]
[ROW][C]142[/C][C]0.04238[/C][C]0.0517183414688555[/C][C]-0.00933834146885552[/C][/ROW]
[ROW][C]143[/C][C]0.01728[/C][C]0.0158306994462124[/C][C]0.00144930055378757[/C][/ROW]
[ROW][C]144[/C][C]0.0201[/C][C]0.0143324420401849[/C][C]0.00576755795981513[/C][/ROW]
[ROW][C]145[/C][C]0.01049[/C][C]0.0101405979939195[/C][C]0.000349402006080487[/C][/ROW]
[ROW][C]146[/C][C]0.01493[/C][C]0.0203024195925629[/C][C]-0.00537241959256288[/C][/ROW]
[ROW][C]147[/C][C]0.0753[/C][C]0.0907885942112931[/C][C]-0.0154885942112931[/C][/ROW]
[ROW][C]148[/C][C]0.06057[/C][C]0.0903992568735996[/C][C]-0.0298292568735996[/C][/ROW]
[ROW][C]149[/C][C]0.08069[/C][C]0.096573163989517[/C][C]-0.015883163989517[/C][/ROW]
[ROW][C]150[/C][C]0.07889[/C][C]0.0924565503040601[/C][C]-0.0135665503040601[/C][/ROW]
[ROW][C]151[/C][C]0.10952[/C][C]0.109086929636247[/C][C]0.000433070363752782[/C][/ROW]
[ROW][C]152[/C][C]0.21713[/C][C]0.206307618366172[/C][C]0.0108223816338278[/C][/ROW]
[ROW][C]153[/C][C]0.16265[/C][C]0.160951699397257[/C][C]0.00169830060274346[/C][/ROW]
[ROW][C]154[/C][C]0.04179[/C][C]0.0327949597270151[/C][C]0.00899504027298489[/C][/ROW]
[ROW][C]155[/C][C]0.04611[/C][C]0.0308646627362958[/C][C]0.0152453372637042[/C][/ROW]
[ROW][C]156[/C][C]0.02631[/C][C]0.021792971406155[/C][C]0.00451702859384496[/C][/ROW]
[ROW][C]157[/C][C]0.03191[/C][C]0.0505434656471378[/C][C]-0.0186334656471378[/C][/ROW]
[ROW][C]158[/C][C]0.10748[/C][C]0.130364895009217[/C][C]-0.0228848950092172[/C][/ROW]
[ROW][C]159[/C][C]0.03828[/C][C]0.0711144839562132[/C][C]-0.0328344839562132[/C][/ROW]
[ROW][C]160[/C][C]0.02663[/C][C]0.0235130593931471[/C][C]0.00311694060685292[/C][/ROW]
[ROW][C]161[/C][C]0.02073[/C][C]0.0163318362756966[/C][C]0.0043981637243034[/C][/ROW]
[ROW][C]162[/C][C]0.0281[/C][C]0.0352408480898687[/C][C]-0.00714084808986871[/C][/ROW]
[ROW][C]163[/C][C]0.02707[/C][C]0.0316417140594275[/C][C]-0.00457171405942749[/C][/ROW]
[ROW][C]164[/C][C]0.01435[/C][C]0.0236442260955131[/C][C]-0.00929422609551311[/C][/ROW]
[ROW][C]165[/C][C]0.03882[/C][C]0.0471414460266709[/C][C]-0.0083214460266709[/C][/ROW]
[ROW][C]166[/C][C]0.0062[/C][C]0.0106314004844427[/C][C]-0.0044314004844427[/C][/ROW]
[ROW][C]167[/C][C]0.00533[/C][C]0.0136746865118272[/C][C]-0.00834468651182724[/C][/ROW]
[ROW][C]168[/C][C]0.0091[/C][C]0.022348135877156[/C][C]-0.013248135877156[/C][/ROW]
[ROW][C]169[/C][C]0.01337[/C][C]0.0392170190900813[/C][C]-0.0258470190900813[/C][/ROW]
[ROW][C]170[/C][C]0.00965[/C][C]0.0315953759233719[/C][C]-0.0219453759233719[/C][/ROW]
[ROW][C]171[/C][C]0.01049[/C][C]0.0288104385007105[/C][C]-0.0183204385007105[/C][/ROW]
[ROW][C]172[/C][C]0.00435[/C][C]0.00519883647322421[/C][C]-0.000848836473224213[/C][/ROW]
[ROW][C]173[/C][C]0.0043[/C][C]-0.00200350513991679[/C][C]0.00630350513991679[/C][/ROW]
[ROW][C]174[/C][C]0.00478[/C][C]-0.00192833428426149[/C][C]0.00670833428426149[/C][/ROW]
[ROW][C]175[/C][C]0.0059[/C][C]0.00215693352434489[/C][C]0.00374306647565511[/C][/ROW]
[ROW][C]176[/C][C]0.00401[/C][C]-0.00207434609136324[/C][C]0.00608434609136324[/C][/ROW]
[ROW][C]177[/C][C]0.00415[/C][C]-0.00535094886975729[/C][C]0.00950094886975729[/C][/ROW]
[ROW][C]178[/C][C]0.0057[/C][C]-0.000510184075898321[/C][C]0.00621018407589832[/C][/ROW]
[ROW][C]179[/C][C]0.00488[/C][C]-0.00516784352666672[/C][C]0.0100478435266667[/C][/ROW]
[ROW][C]180[/C][C]0.0054[/C][C]-0.00095236920795256[/C][C]0.00635236920795256[/C][/ROW]
[ROW][C]181[/C][C]0.00611[/C][C]0.00596892136644806[/C][C]0.000141078633551936[/C][/ROW]
[ROW][C]182[/C][C]0.00639[/C][C]-0.00142498713808386[/C][C]0.00781498713808386[/C][/ROW]
[ROW][C]183[/C][C]0.00595[/C][C]-0.00437475096247897[/C][C]0.010324750962479[/C][/ROW]
[ROW][C]184[/C][C]0.00955[/C][C]0.0111200452620646[/C][C]-0.00157004526206463[/C][/ROW]
[ROW][C]185[/C][C]0.01179[/C][C]0.0193713681610256[/C][C]-0.0075813681610256[/C][/ROW]
[ROW][C]186[/C][C]0.00737[/C][C]0.00561855457261214[/C][C]0.00175144542738786[/C][/ROW]
[ROW][C]187[/C][C]0.01397[/C][C]0.0331076246645469[/C][C]-0.0191376246645469[/C][/ROW]
[ROW][C]188[/C][C]0.0068[/C][C]0.0125382876415384[/C][C]-0.00573828764153842[/C][/ROW]
[ROW][C]189[/C][C]0.00703[/C][C]0.0138669490952836[/C][C]-0.00683694909528358[/C][/ROW]
[ROW][C]190[/C][C]0.04441[/C][C]0.0403667737671148[/C][C]0.00404322623288519[/C][/ROW]
[ROW][C]191[/C][C]0.02764[/C][C]0.034175305947352[/C][C]-0.00653530594735197[/C][/ROW]
[ROW][C]192[/C][C]0.0181[/C][C]0.0318785927561223[/C][C]-0.0137785927561223[/C][/ROW]
[ROW][C]193[/C][C]0.10715[/C][C]0.0922622241534501[/C][C]0.0148877758465499[/C][/ROW]
[ROW][C]194[/C][C]0.07223[/C][C]0.045037575615289[/C][C]0.027192424384711[/C][/ROW]
[ROW][C]195[/C][C]0.04398[/C][C]0.0196806253302566[/C][C]0.0242993746697434[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231280&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231280&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
10.022110.007705429434074520.0144045705659255
20.019290.0237007491384245-0.00441074913842454
30.013090.0292057435303475-0.0161157435303475
40.013530.0270403141375732-0.0135103141375732
50.017670.0425584071035489-0.0248884071035489
60.012220.01063359482186540.00158640517813456
70.00607-0.008721247575343660.0147912475753437
80.00344-0.01065904506759780.0140990450675978
90.01070.0174871117147491-0.00678711171474914
100.010220.008561887011018670.00165811298898133
110.011660.015022987674505-0.00336298767450498
120.011410.0143215850610098-0.00291158506100981
130.005810.00786437609434905-0.00205437609434904
140.010410.0113397200458806-0.000929720045880637
150.006090.004190987485283580.00189901251471642
160.008390.003178413131165520.00521158686883448
170.018590.0193917021790382-0.000801702179038164
180.029190.02431023479317390.00487976520682612
190.03160.03113659128870160.000463408711298406
200.033650.0382644206596405-0.00461442065964052
210.038710.03275022236658670.00595977763341334
220.018490.0186007966120339-0.00011079661203386
230.01280.01193105595960110.000868944040398881
240.01840.01449836379425030.00390163620574971
250.017780.0220222529508515-0.00424225295085149
260.028870.02793470836694510.000935291633054879
270.010950.00979551043918190.00115448956081809
280.013280.01114701564619910.00213298435380087
290.006770.0128835887521632-0.00611358875216318
300.01170.016154516699354-0.00445451669935398
310.00339-0.001635766831346950.00502576683134695
320.00167-0.004597833088319550.00626783308831955
330.00119-0.0150271512635220.016217151263522
340.00072-0.0146975757357990.015417575735799
350.00065-0.01213235665213650.0127823566521365
360.00135-0.006774137349571450.00812413734957145
370.005860.003910701410261460.00194929858973854
380.0034-0.00488875851210290.0082887585121029
390.00231-0.009835886752682760.0121458867526828
400.00265-0.007052008900616780.00970200890061678
410.00231-0.005276045099643230.00758604509964323
420.00257-0.01023246348561970.0128024634856197
430.00740.0123097150034571-0.00490971500345711
440.006750.00805858854379609-0.00130858854379609
450.00454-4.91215131174288e-050.00458912151311743
460.004760.001091535917572010.00366846408242799
470.004760.0060466549385029-0.0012866549385029
480.00432-0.001694653943597670.00601465394359767
490.008390.0174305224070671-0.00904052240706713
500.004620.00799401683288397-0.00337401683288397
510.004790.004545212964481910.00024478703551809
520.004740.0123254537894798-0.00758545378947979
530.004810.0103598016268912-0.00554980162689115
540.004840.0141786113180199-0.0093386113180199
550.010360.00305314793556350.0073068520644365
560.01180.01170304206263329.69579373668054e-05
570.009690.004906562995777930.00478343700422207
580.006810.0013210023154920.005488997684508
590.007860.003291056845219310.00456894315478069
600.011430.0133300644221592-0.00190006442215923
610.008710.004819416669758880.00389058333024112
620.003010.0001074715495906170.00290252845040938
630.00340.002303514291763770.00109648570823623
640.003510.00711967390408594-0.00360967390408594
650.003-5.7623791752569e-050.00305762379175257
660.0042-0.002153588554704130.00635358855470412
670.021830.0372064935705391-0.0153764935705391
680.026590.0437618634047969-0.0171718634047969
690.048820.0648206258877459-0.0160006258877459
700.024310.0426471317040811-0.0183371317040811
710.025990.0405703506063042-0.0145803506063043
720.033610.0507164353164154-0.0171064353164154
730.004420.002369919886620920.00205008011337908
740.006230.0154893899346897-0.00925938993468972
750.00479-0.0016891331767470.006479133176747
760.004720.00624855048661397-0.00152855048661397
770.009050.0162278598720111-0.00717785987201114
780.0042-0.007576995448888650.0117769954488886
790.010620.0178883830672572-0.0072683830672572
800.02220.0512477496548809-0.0290477496548809
810.018230.0237320312807261-0.00550203128072615
820.018250.0297770983212895-0.0115270983212895
830.012370.01345917443349-0.00108917443348995
840.008820.003908170809771240.00491182919022876
850.05470.04504645586493380.00965354413506618
860.027820.01775216399520550.0100678360047945
870.031510.01780463853403190.0137053614659681
880.048240.03333601649017240.0149039835098276
890.042140.0263043105517840.015835689448216
900.072230.03744496604541220.0347850339545878
910.087250.04379320708082750.0434567929191725
920.016580.0298450383977505-0.0132650383977505
930.019140.01552098026676260.00361901973323738
940.012110.0210961412977804-0.00898614129778045
950.00850.00850467882168488-4.67882168488402e-06
960.010180.0127350087578882-0.00255500875788823
970.008520.0161812972430441-0.00766129724304415
980.081510.07826579910803370.00324420089196628
990.103230.0996310245894340.00359897541056596
1000.167440.1394762397401540.027963760259846
1010.314820.2793929758999430.0354270241000573
1020.118430.1074078831480390.0110221168519607
1030.25930.2305131400131790.028786859986821
1040.00495-0.009617175649982350.0145671756499824
1050.00243-0.005587984095030190.00801798409503019
1060.00578-0.0006569810374328390.00643698103743284
1070.00233-0.00415197539545170.0064819753954517
1080.006590.0020217036674450.004568296332555
1090.00238-0.006781936415058740.00916193641505874
1100.009470.0361517819863741-0.0266817819863741
1110.007040.0160857154032386-0.00904571540323858
1120.00830.0256902495061455-0.0173902495061455
1130.013160.0279890200120197-0.0148290200120197
1140.00620.0167608204154266-0.0105608204154266
1150.010480.0205841186958898-0.0101041186958898
1160.060510.03702761559595160.0234823844040484
1170.015540.0220434722475648-0.00650347224756479
1180.018020.01613276902415640.00188723097584361
1190.008560.0156855703320864-0.00712557033208637
1200.006810.0198935220071478-0.0130835220071478
1210.02350.027103913771914-0.00360391377191397
1220.011610.006233149485377980.00537685051462202
1230.019680.0308960003668624-0.0112160003668624
1240.018130.0314243687027077-0.0132943687027077
1250.02020.0240500621809375-0.00385006218093753
1260.018740.0233501891263376-0.00461018912633762
1270.017940.009602612572342610.00833738742765739
1280.017960.0205639636604175-0.00260396366041755
1290.017240.01591937724568690.00132062275431308
1300.00487-0.006183794039163590.0110537940391636
1310.01610.0204307602634911-0.00433076026349113
1320.010150.007958062712070070.00219193728792992
1330.009030.004662224187963870.00436777581203613
1340.005040.002795262874147370.00224473712585263
1350.030310.0310884592308279-0.000778459230827901
1360.025290.0255297511613829-0.000239751161382864
1370.022780.01238473806115640.0103952619388436
1380.03690.02772554580727710.00917445419272293
1390.026290.0329816808821208-0.00669168088212084
1400.018270.01478526328026670.00348473671973331
1410.024850.02468295902510350.000167040974896478
1420.042380.0517183414688555-0.00933834146885552
1430.017280.01583069944621240.00144930055378757
1440.02010.01433244204018490.00576755795981513
1450.010490.01014059799391950.000349402006080487
1460.014930.0203024195925629-0.00537241959256288
1470.07530.0907885942112931-0.0154885942112931
1480.060570.0903992568735996-0.0298292568735996
1490.080690.096573163989517-0.015883163989517
1500.078890.0924565503040601-0.0135665503040601
1510.109520.1090869296362470.000433070363752782
1520.217130.2063076183661720.0108223816338278
1530.162650.1609516993972570.00169830060274346
1540.041790.03279495972701510.00899504027298489
1550.046110.03086466273629580.0152453372637042
1560.026310.0217929714061550.00451702859384496
1570.031910.0505434656471378-0.0186334656471378
1580.107480.130364895009217-0.0228848950092172
1590.038280.0711144839562132-0.0328344839562132
1600.026630.02351305939314710.00311694060685292
1610.020730.01633183627569660.0043981637243034
1620.02810.0352408480898687-0.00714084808986871
1630.027070.0316417140594275-0.00457171405942749
1640.014350.0236442260955131-0.00929422609551311
1650.038820.0471414460266709-0.0083214460266709
1660.00620.0106314004844427-0.0044314004844427
1670.005330.0136746865118272-0.00834468651182724
1680.00910.022348135877156-0.013248135877156
1690.013370.0392170190900813-0.0258470190900813
1700.009650.0315953759233719-0.0219453759233719
1710.010490.0288104385007105-0.0183204385007105
1720.004350.00519883647322421-0.000848836473224213
1730.0043-0.002003505139916790.00630350513991679
1740.00478-0.001928334284261490.00670833428426149
1750.00590.002156933524344890.00374306647565511
1760.00401-0.002074346091363240.00608434609136324
1770.00415-0.005350948869757290.00950094886975729
1780.0057-0.0005101840758983210.00621018407589832
1790.00488-0.005167843526666720.0100478435266667
1800.0054-0.000952369207952560.00635236920795256
1810.006110.005968921366448060.000141078633551936
1820.00639-0.001424987138083860.00781498713808386
1830.00595-0.004374750962478970.010324750962479
1840.009550.0111200452620646-0.00157004526206463
1850.011790.0193713681610256-0.0075813681610256
1860.007370.005618554572612140.00175144542738786
1870.013970.0331076246645469-0.0191376246645469
1880.00680.0125382876415384-0.00573828764153842
1890.007030.0138669490952836-0.00683694909528358
1900.044410.04036677376711480.00404322623288519
1910.027640.034175305947352-0.00653530594735197
1920.01810.0318785927561223-0.0137785927561223
1930.107150.09226222415345010.0148877758465499
1940.072230.0450375756152890.027192424384711
1950.043980.01968062533025660.0242993746697434






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
260.01389812300663880.02779624601327760.986101876993361
270.003218107125499190.006436214250998380.996781892874501
280.0006642388359927950.001328477671985590.999335761164007
290.0001108457412319010.0002216914824638010.999889154258768
301.98638469452729e-053.97276938905458e-050.999980136153055
312.91396073358409e-065.82792146716818e-060.999997086039266
326.50362860836289e-071.30072572167258e-060.999999349637139
331.28961738537196e-072.57923477074391e-070.999999871038261
344.56125644840177e-089.12251289680355e-080.999999954387435
356.9805572954537e-091.39611145909074e-080.999999993019443
361.02283727622706e-092.04567455245413e-090.999999998977163
372.73028757653209e-095.46057515306419e-090.999999997269712
385.82508857865945e-101.16501771573189e-090.999999999417491
391.35823778021515e-102.71647556043031e-100.999999999864176
406.32871651951899e-111.2657433039038e-100.999999999936713
411.10099235017087e-112.20198470034174e-110.99999999998899
425.61112355056668e-121.12222471011334e-110.999999999994389
439.60046743272387e-131.92009348654477e-120.99999999999904
441.67994824414341e-133.35989648828681e-130.999999999999832
452.93004315544637e-145.86008631089275e-140.999999999999971
464.91833747997146e-159.83667495994292e-150.999999999999995
478.12923991076088e-161.62584798215218e-150.999999999999999
481.94007216449807e-163.88014432899614e-161
491.07422015207926e-152.14844030415852e-150.999999999999999
503.11163834050033e-166.22327668100065e-161
515.54222544305213e-171.10844508861043e-161
528.97794174424545e-181.79558834884909e-171
533.9988620032244e-187.99772400644881e-181
541.51866857096274e-183.03733714192547e-181
552.48836740076774e-194.97673480153547e-191
564.84972507488457e-209.69945014976914e-201
577.85170649864049e-211.5703412997281e-201
581.54866332927426e-213.09732665854852e-211
592.97964613527965e-225.9592922705593e-221
607.23974330092515e-231.44794866018503e-221
611.44454062238191e-232.88908124476382e-231
621.86154529718508e-233.72309059437016e-231
638.30554613420661e-241.66110922684132e-231
645.29354939682418e-241.05870987936484e-231
651.28387698891005e-242.56775397782011e-241
662.56360572886677e-255.12721145773353e-251
671.166292306104e-242.33258461220801e-241
683.77689423722362e-257.55378847444725e-251
691.86545770814908e-253.73091541629816e-251
707.85100490966764e-261.57020098193353e-251
711.85219683419735e-263.70439366839471e-261
722.28865085432683e-264.57730170865365e-261
737.5423461534562e-271.50846923069124e-261
742.6215967181089e-275.24319343621779e-271
754.81812714192743e-289.63625428385485e-281
768.34061156128742e-291.66812231225748e-281
777.76734012190267e-291.55346802438053e-281
781.91244734017616e-293.82489468035232e-291
791.21318015959951e-292.42636031919903e-291
802.34733294942427e-294.69466589884853e-291
817.61161614385878e-301.52232322877176e-291
822.67714825474331e-305.35429650948663e-301
835.7185222045786e-311.14370444091572e-301
841.02620099198306e-312.05240198396611e-311
851.57158910946713e-183.14317821893427e-181
866.93511237688941e-191.38702247537788e-181
877.76314912209831e-191.55262982441966e-181
886.58216660124865e-181.31643332024973e-171
893.51692250135586e-187.03384500271171e-181
904.01023940328707e-128.02047880657414e-120.99999999999599
911.05066489315973e-052.10132978631945e-050.999989493351068
921.46347101214336e-052.92694202428672e-050.999985365289879
938.56438771115972e-061.71287754223194e-050.999991435612289
947.9283450560529e-061.58566901121058e-050.999992071654944
956.53810499859279e-061.30762099971856e-050.999993461895001
964.35870803449529e-068.71741606899058e-060.999995641291965
973.07796068390974e-066.15592136781947e-060.999996922039316
980.0002552903429811520.0005105806859623040.999744709657019
990.008753643334472060.01750728666894410.991246356665528
1000.1709438078238530.3418876156477060.829056192176147
1010.8545600642921530.2908798714156930.145439935707847
1020.8602837526155820.2794324947688360.139716247384418
1030.975676156622890.04864768675422060.0243238433771103
1040.9864477511491720.02710449770165590.013552248850828
1050.9855512159975010.02889756800499750.0144487840024988
1060.9821842595464180.03563148090716480.0178157404535824
1070.9773675544560980.04526489108780490.0226324455439024
1080.9719698326389280.05606033472214420.0280301673610721
1090.9670624832918250.06587503341635050.0329375167081753
1100.9953641422562910.009271715487418660.00463585774370933
1110.9951073027938710.00978539441225740.0048926972061287
1120.9970984633089980.005803073382003450.00290153669100172
1130.9980280547490530.003943890501894880.00197194525094744
1140.9979301454399460.004139709120108450.00206985456005423
1150.9974052904605410.0051894190789170.0025947095394585
1160.9996954797244470.0006090405511060330.000304520275553016
1170.9996204922603420.000759015479316250.000379507739658125
1180.99963072564990.0007385487002009190.000369274350100459
1190.9994701746323090.00105965073538140.000529825367690699
1200.9997604518307430.0004790963385132490.000239548169256625
1210.9997238738857570.0005522522284852180.000276126114242609
1220.9997132703318450.0005734593363098980.000286729668154949
1230.99977748326690.000445033466199370.000222516733099685
1240.9997764058309140.0004471883381725020.000223594169086251
1250.9996916430552430.0006167138895143260.000308356944757163
1260.9995906900427740.0008186199144524580.000409309957226229
1270.9994178739621610.001164252075678070.000582126037839036
1280.9991892228293640.001621554341271750.000810777170635874
1290.998786534028610.002426931942780090.00121346597139004
1300.9983282694137970.003343461172405740.00167173058620287
1310.9975144249187330.004971150162533520.00248557508126676
1320.9966032189328390.006793562134321360.00339678106716068
1330.9963137809811450.0073724380377110.0036862190188555
1340.9944150679159460.01116986416810870.00558493208405436
1350.9917313245022440.01653735099551140.00826867549775568
1360.9880384832028520.02392303359429560.0119615167971478
1370.984752224118440.03049555176312030.0152477758815602
1380.9953173149243550.009365370151289950.00468268507564497
1390.9944629492923110.01107410141537730.00553705070768865
1400.9930162662665140.0139674674669730.0069837337334865
1410.9895481741340110.02090365173197830.0104518258659892
1420.9923366138753040.01532677224939120.00766338612469561
1430.9888221304771740.02235573904565260.0111778695228263
1440.9838620696113780.03227586077724330.0161379303886216
1450.9768707346798910.04625853064021780.0231292653201089
1460.9666762445654020.06664751086919660.0333237554345983
1470.9612099946649550.07758001067008960.0387900053350448
1480.9585369865891430.08292602682171320.0414630134108566
1490.9473931321833860.1052137356332270.0526068678166135
1500.961273775899060.07745244820187970.0387262241009398
1510.9557819320268420.08843613594631620.0442180679731581
1520.9851355850049710.02972882999005760.0148644149950288
1530.9782580512263010.04348389754739760.0217419487736988
1540.9672667309816810.06546653803663790.032733269018319
1550.98926143989210.02147712021580010.0107385601079
1560.9937202917459930.01255941650801450.00627970825400727
1570.9911535818767230.0176928362465550.00884641812327748
1580.9991639843927470.001672031214506870.000836015607253434
1590.9999476160053130.0001047679893730615.23839946865307e-05
1600.9998739897847060.0002520204305877570.000126010215293879
1610.9999094172771690.0001811654456622239.05827228311115e-05
1620.9998539751904810.0002920496190385910.000146024809519296
1630.9998431720344820.0003136559310356580.000156827965517829
1640.9996859033983050.0006281932033903430.000314096601695171
1650.9991608834722760.001678233055447060.000839116527723531
1660.9974172938830420.005165412233915840.00258270611695792
1670.9960152560880220.007969487823955590.0039847439119778
1680.9978945958786380.004210808242724310.00210540412136215
1690.9919202003405680.01615959931886430.00807979965943215

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
26 & 0.0138981230066388 & 0.0277962460132776 & 0.986101876993361 \tabularnewline
27 & 0.00321810712549919 & 0.00643621425099838 & 0.996781892874501 \tabularnewline
28 & 0.000664238835992795 & 0.00132847767198559 & 0.999335761164007 \tabularnewline
29 & 0.000110845741231901 & 0.000221691482463801 & 0.999889154258768 \tabularnewline
30 & 1.98638469452729e-05 & 3.97276938905458e-05 & 0.999980136153055 \tabularnewline
31 & 2.91396073358409e-06 & 5.82792146716818e-06 & 0.999997086039266 \tabularnewline
32 & 6.50362860836289e-07 & 1.30072572167258e-06 & 0.999999349637139 \tabularnewline
33 & 1.28961738537196e-07 & 2.57923477074391e-07 & 0.999999871038261 \tabularnewline
34 & 4.56125644840177e-08 & 9.12251289680355e-08 & 0.999999954387435 \tabularnewline
35 & 6.9805572954537e-09 & 1.39611145909074e-08 & 0.999999993019443 \tabularnewline
36 & 1.02283727622706e-09 & 2.04567455245413e-09 & 0.999999998977163 \tabularnewline
37 & 2.73028757653209e-09 & 5.46057515306419e-09 & 0.999999997269712 \tabularnewline
38 & 5.82508857865945e-10 & 1.16501771573189e-09 & 0.999999999417491 \tabularnewline
39 & 1.35823778021515e-10 & 2.71647556043031e-10 & 0.999999999864176 \tabularnewline
40 & 6.32871651951899e-11 & 1.2657433039038e-10 & 0.999999999936713 \tabularnewline
41 & 1.10099235017087e-11 & 2.20198470034174e-11 & 0.99999999998899 \tabularnewline
42 & 5.61112355056668e-12 & 1.12222471011334e-11 & 0.999999999994389 \tabularnewline
43 & 9.60046743272387e-13 & 1.92009348654477e-12 & 0.99999999999904 \tabularnewline
44 & 1.67994824414341e-13 & 3.35989648828681e-13 & 0.999999999999832 \tabularnewline
45 & 2.93004315544637e-14 & 5.86008631089275e-14 & 0.999999999999971 \tabularnewline
46 & 4.91833747997146e-15 & 9.83667495994292e-15 & 0.999999999999995 \tabularnewline
47 & 8.12923991076088e-16 & 1.62584798215218e-15 & 0.999999999999999 \tabularnewline
48 & 1.94007216449807e-16 & 3.88014432899614e-16 & 1 \tabularnewline
49 & 1.07422015207926e-15 & 2.14844030415852e-15 & 0.999999999999999 \tabularnewline
50 & 3.11163834050033e-16 & 6.22327668100065e-16 & 1 \tabularnewline
51 & 5.54222544305213e-17 & 1.10844508861043e-16 & 1 \tabularnewline
52 & 8.97794174424545e-18 & 1.79558834884909e-17 & 1 \tabularnewline
53 & 3.9988620032244e-18 & 7.99772400644881e-18 & 1 \tabularnewline
54 & 1.51866857096274e-18 & 3.03733714192547e-18 & 1 \tabularnewline
55 & 2.48836740076774e-19 & 4.97673480153547e-19 & 1 \tabularnewline
56 & 4.84972507488457e-20 & 9.69945014976914e-20 & 1 \tabularnewline
57 & 7.85170649864049e-21 & 1.5703412997281e-20 & 1 \tabularnewline
58 & 1.54866332927426e-21 & 3.09732665854852e-21 & 1 \tabularnewline
59 & 2.97964613527965e-22 & 5.9592922705593e-22 & 1 \tabularnewline
60 & 7.23974330092515e-23 & 1.44794866018503e-22 & 1 \tabularnewline
61 & 1.44454062238191e-23 & 2.88908124476382e-23 & 1 \tabularnewline
62 & 1.86154529718508e-23 & 3.72309059437016e-23 & 1 \tabularnewline
63 & 8.30554613420661e-24 & 1.66110922684132e-23 & 1 \tabularnewline
64 & 5.29354939682418e-24 & 1.05870987936484e-23 & 1 \tabularnewline
65 & 1.28387698891005e-24 & 2.56775397782011e-24 & 1 \tabularnewline
66 & 2.56360572886677e-25 & 5.12721145773353e-25 & 1 \tabularnewline
67 & 1.166292306104e-24 & 2.33258461220801e-24 & 1 \tabularnewline
68 & 3.77689423722362e-25 & 7.55378847444725e-25 & 1 \tabularnewline
69 & 1.86545770814908e-25 & 3.73091541629816e-25 & 1 \tabularnewline
70 & 7.85100490966764e-26 & 1.57020098193353e-25 & 1 \tabularnewline
71 & 1.85219683419735e-26 & 3.70439366839471e-26 & 1 \tabularnewline
72 & 2.28865085432683e-26 & 4.57730170865365e-26 & 1 \tabularnewline
73 & 7.5423461534562e-27 & 1.50846923069124e-26 & 1 \tabularnewline
74 & 2.6215967181089e-27 & 5.24319343621779e-27 & 1 \tabularnewline
75 & 4.81812714192743e-28 & 9.63625428385485e-28 & 1 \tabularnewline
76 & 8.34061156128742e-29 & 1.66812231225748e-28 & 1 \tabularnewline
77 & 7.76734012190267e-29 & 1.55346802438053e-28 & 1 \tabularnewline
78 & 1.91244734017616e-29 & 3.82489468035232e-29 & 1 \tabularnewline
79 & 1.21318015959951e-29 & 2.42636031919903e-29 & 1 \tabularnewline
80 & 2.34733294942427e-29 & 4.69466589884853e-29 & 1 \tabularnewline
81 & 7.61161614385878e-30 & 1.52232322877176e-29 & 1 \tabularnewline
82 & 2.67714825474331e-30 & 5.35429650948663e-30 & 1 \tabularnewline
83 & 5.7185222045786e-31 & 1.14370444091572e-30 & 1 \tabularnewline
84 & 1.02620099198306e-31 & 2.05240198396611e-31 & 1 \tabularnewline
85 & 1.57158910946713e-18 & 3.14317821893427e-18 & 1 \tabularnewline
86 & 6.93511237688941e-19 & 1.38702247537788e-18 & 1 \tabularnewline
87 & 7.76314912209831e-19 & 1.55262982441966e-18 & 1 \tabularnewline
88 & 6.58216660124865e-18 & 1.31643332024973e-17 & 1 \tabularnewline
89 & 3.51692250135586e-18 & 7.03384500271171e-18 & 1 \tabularnewline
90 & 4.01023940328707e-12 & 8.02047880657414e-12 & 0.99999999999599 \tabularnewline
91 & 1.05066489315973e-05 & 2.10132978631945e-05 & 0.999989493351068 \tabularnewline
92 & 1.46347101214336e-05 & 2.92694202428672e-05 & 0.999985365289879 \tabularnewline
93 & 8.56438771115972e-06 & 1.71287754223194e-05 & 0.999991435612289 \tabularnewline
94 & 7.9283450560529e-06 & 1.58566901121058e-05 & 0.999992071654944 \tabularnewline
95 & 6.53810499859279e-06 & 1.30762099971856e-05 & 0.999993461895001 \tabularnewline
96 & 4.35870803449529e-06 & 8.71741606899058e-06 & 0.999995641291965 \tabularnewline
97 & 3.07796068390974e-06 & 6.15592136781947e-06 & 0.999996922039316 \tabularnewline
98 & 0.000255290342981152 & 0.000510580685962304 & 0.999744709657019 \tabularnewline
99 & 0.00875364333447206 & 0.0175072866689441 & 0.991246356665528 \tabularnewline
100 & 0.170943807823853 & 0.341887615647706 & 0.829056192176147 \tabularnewline
101 & 0.854560064292153 & 0.290879871415693 & 0.145439935707847 \tabularnewline
102 & 0.860283752615582 & 0.279432494768836 & 0.139716247384418 \tabularnewline
103 & 0.97567615662289 & 0.0486476867542206 & 0.0243238433771103 \tabularnewline
104 & 0.986447751149172 & 0.0271044977016559 & 0.013552248850828 \tabularnewline
105 & 0.985551215997501 & 0.0288975680049975 & 0.0144487840024988 \tabularnewline
106 & 0.982184259546418 & 0.0356314809071648 & 0.0178157404535824 \tabularnewline
107 & 0.977367554456098 & 0.0452648910878049 & 0.0226324455439024 \tabularnewline
108 & 0.971969832638928 & 0.0560603347221442 & 0.0280301673610721 \tabularnewline
109 & 0.967062483291825 & 0.0658750334163505 & 0.0329375167081753 \tabularnewline
110 & 0.995364142256291 & 0.00927171548741866 & 0.00463585774370933 \tabularnewline
111 & 0.995107302793871 & 0.0097853944122574 & 0.0048926972061287 \tabularnewline
112 & 0.997098463308998 & 0.00580307338200345 & 0.00290153669100172 \tabularnewline
113 & 0.998028054749053 & 0.00394389050189488 & 0.00197194525094744 \tabularnewline
114 & 0.997930145439946 & 0.00413970912010845 & 0.00206985456005423 \tabularnewline
115 & 0.997405290460541 & 0.005189419078917 & 0.0025947095394585 \tabularnewline
116 & 0.999695479724447 & 0.000609040551106033 & 0.000304520275553016 \tabularnewline
117 & 0.999620492260342 & 0.00075901547931625 & 0.000379507739658125 \tabularnewline
118 & 0.9996307256499 & 0.000738548700200919 & 0.000369274350100459 \tabularnewline
119 & 0.999470174632309 & 0.0010596507353814 & 0.000529825367690699 \tabularnewline
120 & 0.999760451830743 & 0.000479096338513249 & 0.000239548169256625 \tabularnewline
121 & 0.999723873885757 & 0.000552252228485218 & 0.000276126114242609 \tabularnewline
122 & 0.999713270331845 & 0.000573459336309898 & 0.000286729668154949 \tabularnewline
123 & 0.9997774832669 & 0.00044503346619937 & 0.000222516733099685 \tabularnewline
124 & 0.999776405830914 & 0.000447188338172502 & 0.000223594169086251 \tabularnewline
125 & 0.999691643055243 & 0.000616713889514326 & 0.000308356944757163 \tabularnewline
126 & 0.999590690042774 & 0.000818619914452458 & 0.000409309957226229 \tabularnewline
127 & 0.999417873962161 & 0.00116425207567807 & 0.000582126037839036 \tabularnewline
128 & 0.999189222829364 & 0.00162155434127175 & 0.000810777170635874 \tabularnewline
129 & 0.99878653402861 & 0.00242693194278009 & 0.00121346597139004 \tabularnewline
130 & 0.998328269413797 & 0.00334346117240574 & 0.00167173058620287 \tabularnewline
131 & 0.997514424918733 & 0.00497115016253352 & 0.00248557508126676 \tabularnewline
132 & 0.996603218932839 & 0.00679356213432136 & 0.00339678106716068 \tabularnewline
133 & 0.996313780981145 & 0.007372438037711 & 0.0036862190188555 \tabularnewline
134 & 0.994415067915946 & 0.0111698641681087 & 0.00558493208405436 \tabularnewline
135 & 0.991731324502244 & 0.0165373509955114 & 0.00826867549775568 \tabularnewline
136 & 0.988038483202852 & 0.0239230335942956 & 0.0119615167971478 \tabularnewline
137 & 0.98475222411844 & 0.0304955517631203 & 0.0152477758815602 \tabularnewline
138 & 0.995317314924355 & 0.00936537015128995 & 0.00468268507564497 \tabularnewline
139 & 0.994462949292311 & 0.0110741014153773 & 0.00553705070768865 \tabularnewline
140 & 0.993016266266514 & 0.013967467466973 & 0.0069837337334865 \tabularnewline
141 & 0.989548174134011 & 0.0209036517319783 & 0.0104518258659892 \tabularnewline
142 & 0.992336613875304 & 0.0153267722493912 & 0.00766338612469561 \tabularnewline
143 & 0.988822130477174 & 0.0223557390456526 & 0.0111778695228263 \tabularnewline
144 & 0.983862069611378 & 0.0322758607772433 & 0.0161379303886216 \tabularnewline
145 & 0.976870734679891 & 0.0462585306402178 & 0.0231292653201089 \tabularnewline
146 & 0.966676244565402 & 0.0666475108691966 & 0.0333237554345983 \tabularnewline
147 & 0.961209994664955 & 0.0775800106700896 & 0.0387900053350448 \tabularnewline
148 & 0.958536986589143 & 0.0829260268217132 & 0.0414630134108566 \tabularnewline
149 & 0.947393132183386 & 0.105213735633227 & 0.0526068678166135 \tabularnewline
150 & 0.96127377589906 & 0.0774524482018797 & 0.0387262241009398 \tabularnewline
151 & 0.955781932026842 & 0.0884361359463162 & 0.0442180679731581 \tabularnewline
152 & 0.985135585004971 & 0.0297288299900576 & 0.0148644149950288 \tabularnewline
153 & 0.978258051226301 & 0.0434838975473976 & 0.0217419487736988 \tabularnewline
154 & 0.967266730981681 & 0.0654665380366379 & 0.032733269018319 \tabularnewline
155 & 0.9892614398921 & 0.0214771202158001 & 0.0107385601079 \tabularnewline
156 & 0.993720291745993 & 0.0125594165080145 & 0.00627970825400727 \tabularnewline
157 & 0.991153581876723 & 0.017692836246555 & 0.00884641812327748 \tabularnewline
158 & 0.999163984392747 & 0.00167203121450687 & 0.000836015607253434 \tabularnewline
159 & 0.999947616005313 & 0.000104767989373061 & 5.23839946865307e-05 \tabularnewline
160 & 0.999873989784706 & 0.000252020430587757 & 0.000126010215293879 \tabularnewline
161 & 0.999909417277169 & 0.000181165445662223 & 9.05827228311115e-05 \tabularnewline
162 & 0.999853975190481 & 0.000292049619038591 & 0.000146024809519296 \tabularnewline
163 & 0.999843172034482 & 0.000313655931035658 & 0.000156827965517829 \tabularnewline
164 & 0.999685903398305 & 0.000628193203390343 & 0.000314096601695171 \tabularnewline
165 & 0.999160883472276 & 0.00167823305544706 & 0.000839116527723531 \tabularnewline
166 & 0.997417293883042 & 0.00516541223391584 & 0.00258270611695792 \tabularnewline
167 & 0.996015256088022 & 0.00796948782395559 & 0.0039847439119778 \tabularnewline
168 & 0.997894595878638 & 0.00421080824272431 & 0.00210540412136215 \tabularnewline
169 & 0.991920200340568 & 0.0161595993188643 & 0.00807979965943215 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231280&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]26[/C][C]0.0138981230066388[/C][C]0.0277962460132776[/C][C]0.986101876993361[/C][/ROW]
[ROW][C]27[/C][C]0.00321810712549919[/C][C]0.00643621425099838[/C][C]0.996781892874501[/C][/ROW]
[ROW][C]28[/C][C]0.000664238835992795[/C][C]0.00132847767198559[/C][C]0.999335761164007[/C][/ROW]
[ROW][C]29[/C][C]0.000110845741231901[/C][C]0.000221691482463801[/C][C]0.999889154258768[/C][/ROW]
[ROW][C]30[/C][C]1.98638469452729e-05[/C][C]3.97276938905458e-05[/C][C]0.999980136153055[/C][/ROW]
[ROW][C]31[/C][C]2.91396073358409e-06[/C][C]5.82792146716818e-06[/C][C]0.999997086039266[/C][/ROW]
[ROW][C]32[/C][C]6.50362860836289e-07[/C][C]1.30072572167258e-06[/C][C]0.999999349637139[/C][/ROW]
[ROW][C]33[/C][C]1.28961738537196e-07[/C][C]2.57923477074391e-07[/C][C]0.999999871038261[/C][/ROW]
[ROW][C]34[/C][C]4.56125644840177e-08[/C][C]9.12251289680355e-08[/C][C]0.999999954387435[/C][/ROW]
[ROW][C]35[/C][C]6.9805572954537e-09[/C][C]1.39611145909074e-08[/C][C]0.999999993019443[/C][/ROW]
[ROW][C]36[/C][C]1.02283727622706e-09[/C][C]2.04567455245413e-09[/C][C]0.999999998977163[/C][/ROW]
[ROW][C]37[/C][C]2.73028757653209e-09[/C][C]5.46057515306419e-09[/C][C]0.999999997269712[/C][/ROW]
[ROW][C]38[/C][C]5.82508857865945e-10[/C][C]1.16501771573189e-09[/C][C]0.999999999417491[/C][/ROW]
[ROW][C]39[/C][C]1.35823778021515e-10[/C][C]2.71647556043031e-10[/C][C]0.999999999864176[/C][/ROW]
[ROW][C]40[/C][C]6.32871651951899e-11[/C][C]1.2657433039038e-10[/C][C]0.999999999936713[/C][/ROW]
[ROW][C]41[/C][C]1.10099235017087e-11[/C][C]2.20198470034174e-11[/C][C]0.99999999998899[/C][/ROW]
[ROW][C]42[/C][C]5.61112355056668e-12[/C][C]1.12222471011334e-11[/C][C]0.999999999994389[/C][/ROW]
[ROW][C]43[/C][C]9.60046743272387e-13[/C][C]1.92009348654477e-12[/C][C]0.99999999999904[/C][/ROW]
[ROW][C]44[/C][C]1.67994824414341e-13[/C][C]3.35989648828681e-13[/C][C]0.999999999999832[/C][/ROW]
[ROW][C]45[/C][C]2.93004315544637e-14[/C][C]5.86008631089275e-14[/C][C]0.999999999999971[/C][/ROW]
[ROW][C]46[/C][C]4.91833747997146e-15[/C][C]9.83667495994292e-15[/C][C]0.999999999999995[/C][/ROW]
[ROW][C]47[/C][C]8.12923991076088e-16[/C][C]1.62584798215218e-15[/C][C]0.999999999999999[/C][/ROW]
[ROW][C]48[/C][C]1.94007216449807e-16[/C][C]3.88014432899614e-16[/C][C]1[/C][/ROW]
[ROW][C]49[/C][C]1.07422015207926e-15[/C][C]2.14844030415852e-15[/C][C]0.999999999999999[/C][/ROW]
[ROW][C]50[/C][C]3.11163834050033e-16[/C][C]6.22327668100065e-16[/C][C]1[/C][/ROW]
[ROW][C]51[/C][C]5.54222544305213e-17[/C][C]1.10844508861043e-16[/C][C]1[/C][/ROW]
[ROW][C]52[/C][C]8.97794174424545e-18[/C][C]1.79558834884909e-17[/C][C]1[/C][/ROW]
[ROW][C]53[/C][C]3.9988620032244e-18[/C][C]7.99772400644881e-18[/C][C]1[/C][/ROW]
[ROW][C]54[/C][C]1.51866857096274e-18[/C][C]3.03733714192547e-18[/C][C]1[/C][/ROW]
[ROW][C]55[/C][C]2.48836740076774e-19[/C][C]4.97673480153547e-19[/C][C]1[/C][/ROW]
[ROW][C]56[/C][C]4.84972507488457e-20[/C][C]9.69945014976914e-20[/C][C]1[/C][/ROW]
[ROW][C]57[/C][C]7.85170649864049e-21[/C][C]1.5703412997281e-20[/C][C]1[/C][/ROW]
[ROW][C]58[/C][C]1.54866332927426e-21[/C][C]3.09732665854852e-21[/C][C]1[/C][/ROW]
[ROW][C]59[/C][C]2.97964613527965e-22[/C][C]5.9592922705593e-22[/C][C]1[/C][/ROW]
[ROW][C]60[/C][C]7.23974330092515e-23[/C][C]1.44794866018503e-22[/C][C]1[/C][/ROW]
[ROW][C]61[/C][C]1.44454062238191e-23[/C][C]2.88908124476382e-23[/C][C]1[/C][/ROW]
[ROW][C]62[/C][C]1.86154529718508e-23[/C][C]3.72309059437016e-23[/C][C]1[/C][/ROW]
[ROW][C]63[/C][C]8.30554613420661e-24[/C][C]1.66110922684132e-23[/C][C]1[/C][/ROW]
[ROW][C]64[/C][C]5.29354939682418e-24[/C][C]1.05870987936484e-23[/C][C]1[/C][/ROW]
[ROW][C]65[/C][C]1.28387698891005e-24[/C][C]2.56775397782011e-24[/C][C]1[/C][/ROW]
[ROW][C]66[/C][C]2.56360572886677e-25[/C][C]5.12721145773353e-25[/C][C]1[/C][/ROW]
[ROW][C]67[/C][C]1.166292306104e-24[/C][C]2.33258461220801e-24[/C][C]1[/C][/ROW]
[ROW][C]68[/C][C]3.77689423722362e-25[/C][C]7.55378847444725e-25[/C][C]1[/C][/ROW]
[ROW][C]69[/C][C]1.86545770814908e-25[/C][C]3.73091541629816e-25[/C][C]1[/C][/ROW]
[ROW][C]70[/C][C]7.85100490966764e-26[/C][C]1.57020098193353e-25[/C][C]1[/C][/ROW]
[ROW][C]71[/C][C]1.85219683419735e-26[/C][C]3.70439366839471e-26[/C][C]1[/C][/ROW]
[ROW][C]72[/C][C]2.28865085432683e-26[/C][C]4.57730170865365e-26[/C][C]1[/C][/ROW]
[ROW][C]73[/C][C]7.5423461534562e-27[/C][C]1.50846923069124e-26[/C][C]1[/C][/ROW]
[ROW][C]74[/C][C]2.6215967181089e-27[/C][C]5.24319343621779e-27[/C][C]1[/C][/ROW]
[ROW][C]75[/C][C]4.81812714192743e-28[/C][C]9.63625428385485e-28[/C][C]1[/C][/ROW]
[ROW][C]76[/C][C]8.34061156128742e-29[/C][C]1.66812231225748e-28[/C][C]1[/C][/ROW]
[ROW][C]77[/C][C]7.76734012190267e-29[/C][C]1.55346802438053e-28[/C][C]1[/C][/ROW]
[ROW][C]78[/C][C]1.91244734017616e-29[/C][C]3.82489468035232e-29[/C][C]1[/C][/ROW]
[ROW][C]79[/C][C]1.21318015959951e-29[/C][C]2.42636031919903e-29[/C][C]1[/C][/ROW]
[ROW][C]80[/C][C]2.34733294942427e-29[/C][C]4.69466589884853e-29[/C][C]1[/C][/ROW]
[ROW][C]81[/C][C]7.61161614385878e-30[/C][C]1.52232322877176e-29[/C][C]1[/C][/ROW]
[ROW][C]82[/C][C]2.67714825474331e-30[/C][C]5.35429650948663e-30[/C][C]1[/C][/ROW]
[ROW][C]83[/C][C]5.7185222045786e-31[/C][C]1.14370444091572e-30[/C][C]1[/C][/ROW]
[ROW][C]84[/C][C]1.02620099198306e-31[/C][C]2.05240198396611e-31[/C][C]1[/C][/ROW]
[ROW][C]85[/C][C]1.57158910946713e-18[/C][C]3.14317821893427e-18[/C][C]1[/C][/ROW]
[ROW][C]86[/C][C]6.93511237688941e-19[/C][C]1.38702247537788e-18[/C][C]1[/C][/ROW]
[ROW][C]87[/C][C]7.76314912209831e-19[/C][C]1.55262982441966e-18[/C][C]1[/C][/ROW]
[ROW][C]88[/C][C]6.58216660124865e-18[/C][C]1.31643332024973e-17[/C][C]1[/C][/ROW]
[ROW][C]89[/C][C]3.51692250135586e-18[/C][C]7.03384500271171e-18[/C][C]1[/C][/ROW]
[ROW][C]90[/C][C]4.01023940328707e-12[/C][C]8.02047880657414e-12[/C][C]0.99999999999599[/C][/ROW]
[ROW][C]91[/C][C]1.05066489315973e-05[/C][C]2.10132978631945e-05[/C][C]0.999989493351068[/C][/ROW]
[ROW][C]92[/C][C]1.46347101214336e-05[/C][C]2.92694202428672e-05[/C][C]0.999985365289879[/C][/ROW]
[ROW][C]93[/C][C]8.56438771115972e-06[/C][C]1.71287754223194e-05[/C][C]0.999991435612289[/C][/ROW]
[ROW][C]94[/C][C]7.9283450560529e-06[/C][C]1.58566901121058e-05[/C][C]0.999992071654944[/C][/ROW]
[ROW][C]95[/C][C]6.53810499859279e-06[/C][C]1.30762099971856e-05[/C][C]0.999993461895001[/C][/ROW]
[ROW][C]96[/C][C]4.35870803449529e-06[/C][C]8.71741606899058e-06[/C][C]0.999995641291965[/C][/ROW]
[ROW][C]97[/C][C]3.07796068390974e-06[/C][C]6.15592136781947e-06[/C][C]0.999996922039316[/C][/ROW]
[ROW][C]98[/C][C]0.000255290342981152[/C][C]0.000510580685962304[/C][C]0.999744709657019[/C][/ROW]
[ROW][C]99[/C][C]0.00875364333447206[/C][C]0.0175072866689441[/C][C]0.991246356665528[/C][/ROW]
[ROW][C]100[/C][C]0.170943807823853[/C][C]0.341887615647706[/C][C]0.829056192176147[/C][/ROW]
[ROW][C]101[/C][C]0.854560064292153[/C][C]0.290879871415693[/C][C]0.145439935707847[/C][/ROW]
[ROW][C]102[/C][C]0.860283752615582[/C][C]0.279432494768836[/C][C]0.139716247384418[/C][/ROW]
[ROW][C]103[/C][C]0.97567615662289[/C][C]0.0486476867542206[/C][C]0.0243238433771103[/C][/ROW]
[ROW][C]104[/C][C]0.986447751149172[/C][C]0.0271044977016559[/C][C]0.013552248850828[/C][/ROW]
[ROW][C]105[/C][C]0.985551215997501[/C][C]0.0288975680049975[/C][C]0.0144487840024988[/C][/ROW]
[ROW][C]106[/C][C]0.982184259546418[/C][C]0.0356314809071648[/C][C]0.0178157404535824[/C][/ROW]
[ROW][C]107[/C][C]0.977367554456098[/C][C]0.0452648910878049[/C][C]0.0226324455439024[/C][/ROW]
[ROW][C]108[/C][C]0.971969832638928[/C][C]0.0560603347221442[/C][C]0.0280301673610721[/C][/ROW]
[ROW][C]109[/C][C]0.967062483291825[/C][C]0.0658750334163505[/C][C]0.0329375167081753[/C][/ROW]
[ROW][C]110[/C][C]0.995364142256291[/C][C]0.00927171548741866[/C][C]0.00463585774370933[/C][/ROW]
[ROW][C]111[/C][C]0.995107302793871[/C][C]0.0097853944122574[/C][C]0.0048926972061287[/C][/ROW]
[ROW][C]112[/C][C]0.997098463308998[/C][C]0.00580307338200345[/C][C]0.00290153669100172[/C][/ROW]
[ROW][C]113[/C][C]0.998028054749053[/C][C]0.00394389050189488[/C][C]0.00197194525094744[/C][/ROW]
[ROW][C]114[/C][C]0.997930145439946[/C][C]0.00413970912010845[/C][C]0.00206985456005423[/C][/ROW]
[ROW][C]115[/C][C]0.997405290460541[/C][C]0.005189419078917[/C][C]0.0025947095394585[/C][/ROW]
[ROW][C]116[/C][C]0.999695479724447[/C][C]0.000609040551106033[/C][C]0.000304520275553016[/C][/ROW]
[ROW][C]117[/C][C]0.999620492260342[/C][C]0.00075901547931625[/C][C]0.000379507739658125[/C][/ROW]
[ROW][C]118[/C][C]0.9996307256499[/C][C]0.000738548700200919[/C][C]0.000369274350100459[/C][/ROW]
[ROW][C]119[/C][C]0.999470174632309[/C][C]0.0010596507353814[/C][C]0.000529825367690699[/C][/ROW]
[ROW][C]120[/C][C]0.999760451830743[/C][C]0.000479096338513249[/C][C]0.000239548169256625[/C][/ROW]
[ROW][C]121[/C][C]0.999723873885757[/C][C]0.000552252228485218[/C][C]0.000276126114242609[/C][/ROW]
[ROW][C]122[/C][C]0.999713270331845[/C][C]0.000573459336309898[/C][C]0.000286729668154949[/C][/ROW]
[ROW][C]123[/C][C]0.9997774832669[/C][C]0.00044503346619937[/C][C]0.000222516733099685[/C][/ROW]
[ROW][C]124[/C][C]0.999776405830914[/C][C]0.000447188338172502[/C][C]0.000223594169086251[/C][/ROW]
[ROW][C]125[/C][C]0.999691643055243[/C][C]0.000616713889514326[/C][C]0.000308356944757163[/C][/ROW]
[ROW][C]126[/C][C]0.999590690042774[/C][C]0.000818619914452458[/C][C]0.000409309957226229[/C][/ROW]
[ROW][C]127[/C][C]0.999417873962161[/C][C]0.00116425207567807[/C][C]0.000582126037839036[/C][/ROW]
[ROW][C]128[/C][C]0.999189222829364[/C][C]0.00162155434127175[/C][C]0.000810777170635874[/C][/ROW]
[ROW][C]129[/C][C]0.99878653402861[/C][C]0.00242693194278009[/C][C]0.00121346597139004[/C][/ROW]
[ROW][C]130[/C][C]0.998328269413797[/C][C]0.00334346117240574[/C][C]0.00167173058620287[/C][/ROW]
[ROW][C]131[/C][C]0.997514424918733[/C][C]0.00497115016253352[/C][C]0.00248557508126676[/C][/ROW]
[ROW][C]132[/C][C]0.996603218932839[/C][C]0.00679356213432136[/C][C]0.00339678106716068[/C][/ROW]
[ROW][C]133[/C][C]0.996313780981145[/C][C]0.007372438037711[/C][C]0.0036862190188555[/C][/ROW]
[ROW][C]134[/C][C]0.994415067915946[/C][C]0.0111698641681087[/C][C]0.00558493208405436[/C][/ROW]
[ROW][C]135[/C][C]0.991731324502244[/C][C]0.0165373509955114[/C][C]0.00826867549775568[/C][/ROW]
[ROW][C]136[/C][C]0.988038483202852[/C][C]0.0239230335942956[/C][C]0.0119615167971478[/C][/ROW]
[ROW][C]137[/C][C]0.98475222411844[/C][C]0.0304955517631203[/C][C]0.0152477758815602[/C][/ROW]
[ROW][C]138[/C][C]0.995317314924355[/C][C]0.00936537015128995[/C][C]0.00468268507564497[/C][/ROW]
[ROW][C]139[/C][C]0.994462949292311[/C][C]0.0110741014153773[/C][C]0.00553705070768865[/C][/ROW]
[ROW][C]140[/C][C]0.993016266266514[/C][C]0.013967467466973[/C][C]0.0069837337334865[/C][/ROW]
[ROW][C]141[/C][C]0.989548174134011[/C][C]0.0209036517319783[/C][C]0.0104518258659892[/C][/ROW]
[ROW][C]142[/C][C]0.992336613875304[/C][C]0.0153267722493912[/C][C]0.00766338612469561[/C][/ROW]
[ROW][C]143[/C][C]0.988822130477174[/C][C]0.0223557390456526[/C][C]0.0111778695228263[/C][/ROW]
[ROW][C]144[/C][C]0.983862069611378[/C][C]0.0322758607772433[/C][C]0.0161379303886216[/C][/ROW]
[ROW][C]145[/C][C]0.976870734679891[/C][C]0.0462585306402178[/C][C]0.0231292653201089[/C][/ROW]
[ROW][C]146[/C][C]0.966676244565402[/C][C]0.0666475108691966[/C][C]0.0333237554345983[/C][/ROW]
[ROW][C]147[/C][C]0.961209994664955[/C][C]0.0775800106700896[/C][C]0.0387900053350448[/C][/ROW]
[ROW][C]148[/C][C]0.958536986589143[/C][C]0.0829260268217132[/C][C]0.0414630134108566[/C][/ROW]
[ROW][C]149[/C][C]0.947393132183386[/C][C]0.105213735633227[/C][C]0.0526068678166135[/C][/ROW]
[ROW][C]150[/C][C]0.96127377589906[/C][C]0.0774524482018797[/C][C]0.0387262241009398[/C][/ROW]
[ROW][C]151[/C][C]0.955781932026842[/C][C]0.0884361359463162[/C][C]0.0442180679731581[/C][/ROW]
[ROW][C]152[/C][C]0.985135585004971[/C][C]0.0297288299900576[/C][C]0.0148644149950288[/C][/ROW]
[ROW][C]153[/C][C]0.978258051226301[/C][C]0.0434838975473976[/C][C]0.0217419487736988[/C][/ROW]
[ROW][C]154[/C][C]0.967266730981681[/C][C]0.0654665380366379[/C][C]0.032733269018319[/C][/ROW]
[ROW][C]155[/C][C]0.9892614398921[/C][C]0.0214771202158001[/C][C]0.0107385601079[/C][/ROW]
[ROW][C]156[/C][C]0.993720291745993[/C][C]0.0125594165080145[/C][C]0.00627970825400727[/C][/ROW]
[ROW][C]157[/C][C]0.991153581876723[/C][C]0.017692836246555[/C][C]0.00884641812327748[/C][/ROW]
[ROW][C]158[/C][C]0.999163984392747[/C][C]0.00167203121450687[/C][C]0.000836015607253434[/C][/ROW]
[ROW][C]159[/C][C]0.999947616005313[/C][C]0.000104767989373061[/C][C]5.23839946865307e-05[/C][/ROW]
[ROW][C]160[/C][C]0.999873989784706[/C][C]0.000252020430587757[/C][C]0.000126010215293879[/C][/ROW]
[ROW][C]161[/C][C]0.999909417277169[/C][C]0.000181165445662223[/C][C]9.05827228311115e-05[/C][/ROW]
[ROW][C]162[/C][C]0.999853975190481[/C][C]0.000292049619038591[/C][C]0.000146024809519296[/C][/ROW]
[ROW][C]163[/C][C]0.999843172034482[/C][C]0.000313655931035658[/C][C]0.000156827965517829[/C][/ROW]
[ROW][C]164[/C][C]0.999685903398305[/C][C]0.000628193203390343[/C][C]0.000314096601695171[/C][/ROW]
[ROW][C]165[/C][C]0.999160883472276[/C][C]0.00167823305544706[/C][C]0.000839116527723531[/C][/ROW]
[ROW][C]166[/C][C]0.997417293883042[/C][C]0.00516541223391584[/C][C]0.00258270611695792[/C][/ROW]
[ROW][C]167[/C][C]0.996015256088022[/C][C]0.00796948782395559[/C][C]0.0039847439119778[/C][/ROW]
[ROW][C]168[/C][C]0.997894595878638[/C][C]0.00421080824272431[/C][C]0.00210540412136215[/C][/ROW]
[ROW][C]169[/C][C]0.991920200340568[/C][C]0.0161595993188643[/C][C]0.00807979965943215[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231280&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231280&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
260.01389812300663880.02779624601327760.986101876993361
270.003218107125499190.006436214250998380.996781892874501
280.0006642388359927950.001328477671985590.999335761164007
290.0001108457412319010.0002216914824638010.999889154258768
301.98638469452729e-053.97276938905458e-050.999980136153055
312.91396073358409e-065.82792146716818e-060.999997086039266
326.50362860836289e-071.30072572167258e-060.999999349637139
331.28961738537196e-072.57923477074391e-070.999999871038261
344.56125644840177e-089.12251289680355e-080.999999954387435
356.9805572954537e-091.39611145909074e-080.999999993019443
361.02283727622706e-092.04567455245413e-090.999999998977163
372.73028757653209e-095.46057515306419e-090.999999997269712
385.82508857865945e-101.16501771573189e-090.999999999417491
391.35823778021515e-102.71647556043031e-100.999999999864176
406.32871651951899e-111.2657433039038e-100.999999999936713
411.10099235017087e-112.20198470034174e-110.99999999998899
425.61112355056668e-121.12222471011334e-110.999999999994389
439.60046743272387e-131.92009348654477e-120.99999999999904
441.67994824414341e-133.35989648828681e-130.999999999999832
452.93004315544637e-145.86008631089275e-140.999999999999971
464.91833747997146e-159.83667495994292e-150.999999999999995
478.12923991076088e-161.62584798215218e-150.999999999999999
481.94007216449807e-163.88014432899614e-161
491.07422015207926e-152.14844030415852e-150.999999999999999
503.11163834050033e-166.22327668100065e-161
515.54222544305213e-171.10844508861043e-161
528.97794174424545e-181.79558834884909e-171
533.9988620032244e-187.99772400644881e-181
541.51866857096274e-183.03733714192547e-181
552.48836740076774e-194.97673480153547e-191
564.84972507488457e-209.69945014976914e-201
577.85170649864049e-211.5703412997281e-201
581.54866332927426e-213.09732665854852e-211
592.97964613527965e-225.9592922705593e-221
607.23974330092515e-231.44794866018503e-221
611.44454062238191e-232.88908124476382e-231
621.86154529718508e-233.72309059437016e-231
638.30554613420661e-241.66110922684132e-231
645.29354939682418e-241.05870987936484e-231
651.28387698891005e-242.56775397782011e-241
662.56360572886677e-255.12721145773353e-251
671.166292306104e-242.33258461220801e-241
683.77689423722362e-257.55378847444725e-251
691.86545770814908e-253.73091541629816e-251
707.85100490966764e-261.57020098193353e-251
711.85219683419735e-263.70439366839471e-261
722.28865085432683e-264.57730170865365e-261
737.5423461534562e-271.50846923069124e-261
742.6215967181089e-275.24319343621779e-271
754.81812714192743e-289.63625428385485e-281
768.34061156128742e-291.66812231225748e-281
777.76734012190267e-291.55346802438053e-281
781.91244734017616e-293.82489468035232e-291
791.21318015959951e-292.42636031919903e-291
802.34733294942427e-294.69466589884853e-291
817.61161614385878e-301.52232322877176e-291
822.67714825474331e-305.35429650948663e-301
835.7185222045786e-311.14370444091572e-301
841.02620099198306e-312.05240198396611e-311
851.57158910946713e-183.14317821893427e-181
866.93511237688941e-191.38702247537788e-181
877.76314912209831e-191.55262982441966e-181
886.58216660124865e-181.31643332024973e-171
893.51692250135586e-187.03384500271171e-181
904.01023940328707e-128.02047880657414e-120.99999999999599
911.05066489315973e-052.10132978631945e-050.999989493351068
921.46347101214336e-052.92694202428672e-050.999985365289879
938.56438771115972e-061.71287754223194e-050.999991435612289
947.9283450560529e-061.58566901121058e-050.999992071654944
956.53810499859279e-061.30762099971856e-050.999993461895001
964.35870803449529e-068.71741606899058e-060.999995641291965
973.07796068390974e-066.15592136781947e-060.999996922039316
980.0002552903429811520.0005105806859623040.999744709657019
990.008753643334472060.01750728666894410.991246356665528
1000.1709438078238530.3418876156477060.829056192176147
1010.8545600642921530.2908798714156930.145439935707847
1020.8602837526155820.2794324947688360.139716247384418
1030.975676156622890.04864768675422060.0243238433771103
1040.9864477511491720.02710449770165590.013552248850828
1050.9855512159975010.02889756800499750.0144487840024988
1060.9821842595464180.03563148090716480.0178157404535824
1070.9773675544560980.04526489108780490.0226324455439024
1080.9719698326389280.05606033472214420.0280301673610721
1090.9670624832918250.06587503341635050.0329375167081753
1100.9953641422562910.009271715487418660.00463585774370933
1110.9951073027938710.00978539441225740.0048926972061287
1120.9970984633089980.005803073382003450.00290153669100172
1130.9980280547490530.003943890501894880.00197194525094744
1140.9979301454399460.004139709120108450.00206985456005423
1150.9974052904605410.0051894190789170.0025947095394585
1160.9996954797244470.0006090405511060330.000304520275553016
1170.9996204922603420.000759015479316250.000379507739658125
1180.99963072564990.0007385487002009190.000369274350100459
1190.9994701746323090.00105965073538140.000529825367690699
1200.9997604518307430.0004790963385132490.000239548169256625
1210.9997238738857570.0005522522284852180.000276126114242609
1220.9997132703318450.0005734593363098980.000286729668154949
1230.99977748326690.000445033466199370.000222516733099685
1240.9997764058309140.0004471883381725020.000223594169086251
1250.9996916430552430.0006167138895143260.000308356944757163
1260.9995906900427740.0008186199144524580.000409309957226229
1270.9994178739621610.001164252075678070.000582126037839036
1280.9991892228293640.001621554341271750.000810777170635874
1290.998786534028610.002426931942780090.00121346597139004
1300.9983282694137970.003343461172405740.00167173058620287
1310.9975144249187330.004971150162533520.00248557508126676
1320.9966032189328390.006793562134321360.00339678106716068
1330.9963137809811450.0073724380377110.0036862190188555
1340.9944150679159460.01116986416810870.00558493208405436
1350.9917313245022440.01653735099551140.00826867549775568
1360.9880384832028520.02392303359429560.0119615167971478
1370.984752224118440.03049555176312030.0152477758815602
1380.9953173149243550.009365370151289950.00468268507564497
1390.9944629492923110.01107410141537730.00553705070768865
1400.9930162662665140.0139674674669730.0069837337334865
1410.9895481741340110.02090365173197830.0104518258659892
1420.9923366138753040.01532677224939120.00766338612469561
1430.9888221304771740.02235573904565260.0111778695228263
1440.9838620696113780.03227586077724330.0161379303886216
1450.9768707346798910.04625853064021780.0231292653201089
1460.9666762445654020.06664751086919660.0333237554345983
1470.9612099946649550.07758001067008960.0387900053350448
1480.9585369865891430.08292602682171320.0414630134108566
1490.9473931321833860.1052137356332270.0526068678166135
1500.961273775899060.07745244820187970.0387262241009398
1510.9557819320268420.08843613594631620.0442180679731581
1520.9851355850049710.02972882999005760.0148644149950288
1530.9782580512263010.04348389754739760.0217419487736988
1540.9672667309816810.06546653803663790.032733269018319
1550.98926143989210.02147712021580010.0107385601079
1560.9937202917459930.01255941650801450.00627970825400727
1570.9911535818767230.0176928362465550.00884641812327748
1580.9991639843927470.001672031214506870.000836015607253434
1590.9999476160053130.0001047679893730615.23839946865307e-05
1600.9998739897847060.0002520204305877570.000126010215293879
1610.9999094172771690.0001811654456622239.05827228311115e-05
1620.9998539751904810.0002920496190385910.000146024809519296
1630.9998431720344820.0003136559310356580.000156827965517829
1640.9996859033983050.0006281932033903430.000314096601695171
1650.9991608834722760.001678233055447060.000839116527723531
1660.9974172938830420.005165412233915840.00258270611695792
1670.9960152560880220.007969487823955590.0039847439119778
1680.9978945958786380.004210808242724310.00210540412136215
1690.9919202003405680.01615959931886430.00807979965943215






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1080.75NOK
5% type I error level1320.916666666666667NOK
10% type I error level1400.972222222222222NOK

\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 & 108 & 0.75 & NOK \tabularnewline
5% type I error level & 132 & 0.916666666666667 & NOK \tabularnewline
10% type I error level & 140 & 0.972222222222222 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231280&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]108[/C][C]0.75[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]132[/C][C]0.916666666666667[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]140[/C][C]0.972222222222222[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231280&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231280&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1080.75NOK
5% type I error level1320.916666666666667NOK
10% type I error level1400.972222222222222NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 15 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 15 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], 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,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
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, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
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,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
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,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
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,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
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,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
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')
}