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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 14:25:17 -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/t13862715779gegkfvb6kxdgp1.htm/, Retrieved Thu, 18 Apr 2024 19:34:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231227, Retrieved Thu, 18 Apr 2024 19:34:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact58

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [WS10: Multiple Re...] [2013-12-05 19:25:17] [0d4b5c001fcd12491258e86d922016e4] [Current]
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Dataset

Dataseries X:
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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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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
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
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
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
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
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
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 1
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 1
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 1
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 1
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 1
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 1
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
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
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
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
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
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
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
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
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
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
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
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
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 1
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 1
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 1
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 1
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 1
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 1
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
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
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
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
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
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
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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 1
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
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
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
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
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
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
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
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
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
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
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
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
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 1
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 1
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 1
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 1
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 1
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 1
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
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
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
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
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
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
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
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
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
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
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
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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time28 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 & 28 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231227&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]28 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=231227&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231227&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 time28 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
status[t] = + 1.27312 -0.00241584`MDVP:Fo(Hz)`[t] -0.000267953`MDVP:Fhi(Hz)`[t] -0.00238313`MDVP:Flo(Hz)`[t] -107.3`MDVP:Jitter(%)`[t] -1672.44`MDVP:Jitter(Abs)`[t] + 274.896`MDVP:RAP`[t] + 78.9838`MDVP:PPQ`[t] -50.9132`Jitter:DDP`[t] + 66.639`MDVP:Shimmer`[t] -1.02881`MDVP:Shimmer(dB)`[t] + 3104.02`Shimmer:APQ3`[t] -18.9423`Shimmer:APQ5`[t] -5.5773`MDVP:APQ`[t] -1055.27`Shimmer:DDA`[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
status[t] =  +  1.27312 -0.00241584`MDVP:Fo(Hz)`[t] -0.000267953`MDVP:Fhi(Hz)`[t] -0.00238313`MDVP:Flo(Hz)`[t] -107.3`MDVP:Jitter(%)`[t] -1672.44`MDVP:Jitter(Abs)`[t] +  274.896`MDVP:RAP`[t] +  78.9838`MDVP:PPQ`[t] -50.9132`Jitter:DDP`[t] +  66.639`MDVP:Shimmer`[t] -1.02881`MDVP:Shimmer(dB)`[t] +  3104.02`Shimmer:APQ3`[t] -18.9423`Shimmer:APQ5`[t] -5.5773`MDVP:APQ`[t] -1055.27`Shimmer:DDA`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231227&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]status[t] =  +  1.27312 -0.00241584`MDVP:Fo(Hz)`[t] -0.000267953`MDVP:Fhi(Hz)`[t] -0.00238313`MDVP:Flo(Hz)`[t] -107.3`MDVP:Jitter(%)`[t] -1672.44`MDVP:Jitter(Abs)`[t] +  274.896`MDVP:RAP`[t] +  78.9838`MDVP:PPQ`[t] -50.9132`Jitter:DDP`[t] +  66.639`MDVP:Shimmer`[t] -1.02881`MDVP:Shimmer(dB)`[t] +  3104.02`Shimmer:APQ3`[t] -18.9423`Shimmer:APQ5`[t] -5.5773`MDVP:APQ`[t] -1055.27`Shimmer:DDA`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231227&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231227&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
status[t] = + 1.27312 -0.00241584`MDVP:Fo(Hz)`[t] -0.000267953`MDVP:Fhi(Hz)`[t] -0.00238313`MDVP:Flo(Hz)`[t] -107.3`MDVP:Jitter(%)`[t] -1672.44`MDVP:Jitter(Abs)`[t] + 274.896`MDVP:RAP`[t] + 78.9838`MDVP:PPQ`[t] -50.9132`Jitter:DDP`[t] + 66.639`MDVP:Shimmer`[t] -1.02881`MDVP:Shimmer(dB)`[t] + 3104.02`Shimmer:APQ3`[t] -18.9423`Shimmer:APQ5`[t] -5.5773`MDVP:APQ`[t] -1055.27`Shimmer:DDA`[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.273120.228225.5788.78234e-084.39117e-08
`MDVP:Fo(Hz)`-0.002415840.00144702-1.670.09675190.0483759
`MDVP:Fhi(Hz)`-0.0002679530.000349968-0.76560.4448880.222444
`MDVP:Flo(Hz)`-0.002383130.000840033-2.8370.005077060.00253853
`MDVP:Jitter(%)`-107.370.6916-1.5180.1308050.0654023
`MDVP:Jitter(Abs)`-1672.444683-0.35710.7214130.360707
`MDVP:RAP`274.89610272.40.026760.978680.48934
`MDVP:PPQ`78.983879.19370.99730.3199340.159967
`Jitter:DDP`-50.91323424.76-0.014870.9881550.494078
`MDVP:Shimmer`66.63937.47331.7780.07704170.0385209
`MDVP:Shimmer(dB)`-1.028811.24194-0.82840.4085470.204273
`Shimmer:APQ3`3104.029961.460.31160.7557030.377851
`Shimmer:APQ5`-18.942321.7206-0.87210.3843210.192161
`MDVP:APQ`-5.577311.469-0.48630.6273490.313675
`Shimmer:DDA`-1055.273319.5-0.31790.7509280.375464

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 1.27312 & 0.22822 & 5.578 & 8.78234e-08 & 4.39117e-08 \tabularnewline
`MDVP:Fo(Hz)` & -0.00241584 & 0.00144702 & -1.67 & 0.0967519 & 0.0483759 \tabularnewline
`MDVP:Fhi(Hz)` & -0.000267953 & 0.000349968 & -0.7656 & 0.444888 & 0.222444 \tabularnewline
`MDVP:Flo(Hz)` & -0.00238313 & 0.000840033 & -2.837 & 0.00507706 & 0.00253853 \tabularnewline
`MDVP:Jitter(%)` & -107.3 & 70.6916 & -1.518 & 0.130805 & 0.0654023 \tabularnewline
`MDVP:Jitter(Abs)` & -1672.44 & 4683 & -0.3571 & 0.721413 & 0.360707 \tabularnewline
`MDVP:RAP` & 274.896 & 10272.4 & 0.02676 & 0.97868 & 0.48934 \tabularnewline
`MDVP:PPQ` & 78.9838 & 79.1937 & 0.9973 & 0.319934 & 0.159967 \tabularnewline
`Jitter:DDP` & -50.9132 & 3424.76 & -0.01487 & 0.988155 & 0.494078 \tabularnewline
`MDVP:Shimmer` & 66.639 & 37.4733 & 1.778 & 0.0770417 & 0.0385209 \tabularnewline
`MDVP:Shimmer(dB)` & -1.02881 & 1.24194 & -0.8284 & 0.408547 & 0.204273 \tabularnewline
`Shimmer:APQ3` & 3104.02 & 9961.46 & 0.3116 & 0.755703 & 0.377851 \tabularnewline
`Shimmer:APQ5` & -18.9423 & 21.7206 & -0.8721 & 0.384321 & 0.192161 \tabularnewline
`MDVP:APQ` & -5.5773 & 11.469 & -0.4863 & 0.627349 & 0.313675 \tabularnewline
`Shimmer:DDA` & -1055.27 & 3319.5 & -0.3179 & 0.750928 & 0.375464 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231227&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]1.27312[/C][C]0.22822[/C][C]5.578[/C][C]8.78234e-08[/C][C]4.39117e-08[/C][/ROW]
[ROW][C]`MDVP:Fo(Hz)`[/C][C]-0.00241584[/C][C]0.00144702[/C][C]-1.67[/C][C]0.0967519[/C][C]0.0483759[/C][/ROW]
[ROW][C]`MDVP:Fhi(Hz)`[/C][C]-0.000267953[/C][C]0.000349968[/C][C]-0.7656[/C][C]0.444888[/C][C]0.222444[/C][/ROW]
[ROW][C]`MDVP:Flo(Hz)`[/C][C]-0.00238313[/C][C]0.000840033[/C][C]-2.837[/C][C]0.00507706[/C][C]0.00253853[/C][/ROW]
[ROW][C]`MDVP:Jitter(%)`[/C][C]-107.3[/C][C]70.6916[/C][C]-1.518[/C][C]0.130805[/C][C]0.0654023[/C][/ROW]
[ROW][C]`MDVP:Jitter(Abs)`[/C][C]-1672.44[/C][C]4683[/C][C]-0.3571[/C][C]0.721413[/C][C]0.360707[/C][/ROW]
[ROW][C]`MDVP:RAP`[/C][C]274.896[/C][C]10272.4[/C][C]0.02676[/C][C]0.97868[/C][C]0.48934[/C][/ROW]
[ROW][C]`MDVP:PPQ`[/C][C]78.9838[/C][C]79.1937[/C][C]0.9973[/C][C]0.319934[/C][C]0.159967[/C][/ROW]
[ROW][C]`Jitter:DDP`[/C][C]-50.9132[/C][C]3424.76[/C][C]-0.01487[/C][C]0.988155[/C][C]0.494078[/C][/ROW]
[ROW][C]`MDVP:Shimmer`[/C][C]66.639[/C][C]37.4733[/C][C]1.778[/C][C]0.0770417[/C][C]0.0385209[/C][/ROW]
[ROW][C]`MDVP:Shimmer(dB)`[/C][C]-1.02881[/C][C]1.24194[/C][C]-0.8284[/C][C]0.408547[/C][C]0.204273[/C][/ROW]
[ROW][C]`Shimmer:APQ3`[/C][C]3104.02[/C][C]9961.46[/C][C]0.3116[/C][C]0.755703[/C][C]0.377851[/C][/ROW]
[ROW][C]`Shimmer:APQ5`[/C][C]-18.9423[/C][C]21.7206[/C][C]-0.8721[/C][C]0.384321[/C][C]0.192161[/C][/ROW]
[ROW][C]`MDVP:APQ`[/C][C]-5.5773[/C][C]11.469[/C][C]-0.4863[/C][C]0.627349[/C][C]0.313675[/C][/ROW]
[ROW][C]`Shimmer:DDA`[/C][C]-1055.27[/C][C]3319.5[/C][C]-0.3179[/C][C]0.750928[/C][C]0.375464[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231227&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231227&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)1.273120.228225.5788.78234e-084.39117e-08
`MDVP:Fo(Hz)`-0.002415840.00144702-1.670.09675190.0483759
`MDVP:Fhi(Hz)`-0.0002679530.000349968-0.76560.4448880.222444
`MDVP:Flo(Hz)`-0.002383130.000840033-2.8370.005077060.00253853
`MDVP:Jitter(%)`-107.370.6916-1.5180.1308050.0654023
`MDVP:Jitter(Abs)`-1672.444683-0.35710.7214130.360707
`MDVP:RAP`274.89610272.40.026760.978680.48934
`MDVP:PPQ`78.983879.19370.99730.3199340.159967
`Jitter:DDP`-50.91323424.76-0.014870.9881550.494078
`MDVP:Shimmer`66.63937.47331.7780.07704170.0385209
`MDVP:Shimmer(dB)`-1.028811.24194-0.82840.4085470.204273
`Shimmer:APQ3`3104.029961.460.31160.7557030.377851
`Shimmer:APQ5`-18.942321.7206-0.87210.3843210.192161
`MDVP:APQ`-5.577311.469-0.48630.6273490.313675
`Shimmer:DDA`-1055.273319.5-0.31790.7509280.375464






Multiple Linear Regression - Regression Statistics
Multiple R0.561764
R-squared0.315579
Adjusted R-squared0.262346
F-TEST (value)5.92828
F-TEST (DF numerator)14
F-TEST (DF denominator)180
p-value1.60655e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.370926
Sum Squared Residuals24.7655

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.561764 \tabularnewline
R-squared & 0.315579 \tabularnewline
Adjusted R-squared & 0.262346 \tabularnewline
F-TEST (value) & 5.92828 \tabularnewline
F-TEST (DF numerator) & 14 \tabularnewline
F-TEST (DF denominator) & 180 \tabularnewline
p-value & 1.60655e-09 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.370926 \tabularnewline
Sum Squared Residuals & 24.7655 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231227&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.561764[/C][/ROW]
[ROW][C]R-squared[/C][C]0.315579[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.262346[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]5.92828[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]14[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]180[/C][/ROW]
[ROW][C]p-value[/C][C]1.60655e-09[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.370926[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]24.7655[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231227&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231227&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 R0.561764
R-squared0.315579
Adjusted R-squared0.262346
F-TEST (value)5.92828
F-TEST (DF numerator)14
F-TEST (DF denominator)180
p-value1.60655e-09
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.370926
Sum Squared Residuals24.7655






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
111.07415-0.0741475
211.009-0.00900408
311.06105-0.0610518
410.9961180.00388224
511.00721-0.00721396
611.02715-0.0271471
710.8063380.193662
810.8383610.161639
910.9239180.0760822
1010.9775610.0224388
1110.9563580.0436416
1211.00617-0.00616681
1310.6222480.377752
1410.8122630.187737
1510.7504730.249527
1610.7300980.269902
1710.6864510.313549
1810.8669750.133025
1911.19236-0.192361
2010.9060630.0939366
2111.09739-0.0973892
2210.9925720.00742812
2310.9723420.0276583
2410.8874480.112552
2510.7510830.248917
2611.08388-0.0838822
2710.8300740.169926
2810.80870.1913
2910.8334130.166587
3010.8142630.185737
3100.402973-0.402973
3200.374153-0.374153
3300.409645-0.409645
3400.352107-0.352107
3500.366348-0.366348
3600.380132-0.380132
3710.5448560.455144
3810.5787920.421208
3910.500940.49906
4010.4933280.506672
4110.475840.52416
4210.5046950.495305
4300.223286-0.223286
4400.216787-0.216787
4500.183469-0.183469
4600.172374-0.172374
4700.167814-0.167814
4800.255561-0.255561
4900.567142-0.567142
5000.599487-0.599487
5100.6356-0.6356
5200.595488-0.595488
5300.616892-0.616892
5400.621838-0.621838
5510.8085670.191433
5610.7580640.241936
5710.8759620.124038
5810.6901350.309865
5910.7229060.277094
6010.6449680.355032
6100.57071-0.57071
6200.596376-0.596376
6300.303831-0.303831
6400.247204-0.247204
6500.232275-0.232275
6600.513784-0.513784
6710.8277830.172217
6810.8840070.115993
6911.08088-0.0808825
7011.02725-0.027246
7110.896990.10301
7211.05715-0.0571538
7310.728360.27164
7410.6911770.308823
7510.8371530.162847
7610.8065380.193462
7710.9110420.0889577
7810.8038110.196189
7910.9788840.0211163
8010.8741840.125816
8111.02264-0.0226388
8210.9604490.0395513
8310.8953570.104643
8410.9157690.0842314
8510.9091690.0908311
8610.6962170.303783
8710.7018820.298118
8810.9104490.0895513
8910.9882540.0117464
9010.6869170.313083
9111.02809-0.0280874
9210.9952940.00470594
9310.7637320.236268
9410.8848680.115132
9510.9625740.0374261
9610.72860.2714
9710.7518340.248166
9810.8388660.161134
9910.9801270.0198733
10011.06651-0.0665116
10111.11749-0.117487
10211.23521-0.235209
10311.1683-0.168303
10410.7546120.245388
10510.6614050.338595
10610.643940.35606
10710.5744510.425549
10810.6959760.304024
10910.662760.33724
11010.7287190.271281
11110.7157490.284251
11210.412170.58783
11310.4944940.505506
11410.4201690.579831
11510.6753490.324651
11610.6442150.355785
11710.6949910.305009
11810.6467930.353207
11910.4599670.540033
12010.3797960.620204
12110.7253680.274632
12210.6109330.389067
12310.9239190.0760814
12410.7640270.235973
12510.8152920.184708
12610.8149840.185016
12710.8918960.108104
12810.8054190.194581
12910.6675430.332457
13010.7544940.245506
13110.7760570.223943
13210.8332160.166784
13310.790710.20929
13410.738120.26188
13511.01-0.00999714
13610.9679210.0320794
13711.18389-0.183887
13811.04258-0.042583
13911.06976-0.0697632
14010.9392830.0607174
14110.7368260.263174
14210.8803760.119624
14310.5763050.423695
14410.6411160.358884
14510.4756090.524391
14610.6180980.381902
14711.14152-0.141519
14810.8587010.141299
14911.00281-0.00280602
15010.7838140.216186
15110.8263930.173607
15211.31141-0.311412
15311.01317-0.0131718
15410.8537930.146207
15510.8726720.127328
15610.8930410.106959
15710.8182940.181706
15811.08521-0.0852109
15910.8887670.111233
16011.06195-0.0619461
16111.37002-0.370019
16210.9733250.0266745
16311.02875-0.0287536
16410.804640.19536
16510.8455130.154487
16600.554188-0.554188
16700.160159-0.160159
16800.143073-0.143073
16900.700266-0.700266
17000.212776-0.212776
17100.164126-0.164126
17200.784235-0.784235
17300.815043-0.815043
17400.816142-0.816142
17500.807764-0.807764
17600.767632-0.767632
17700.822677-0.822677
17810.6248950.375105
17910.6272530.372747
18010.6595510.340449
18110.6923140.307686
18210.6696670.330333
18310.6733710.326629
18400.850573-0.850573
18500.856737-0.856737
18600.849574-0.849574
18700.720055-0.720055
18800.702413-0.702413
18900.808258-0.808258
19000.696702-0.696702
19100.785412-0.785412
19200.617763-0.617763
19300.363409-0.363409
19400.579766-0.579766
19500.581501-0.581501

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1 & 1.07415 & -0.0741475 \tabularnewline
2 & 1 & 1.009 & -0.00900408 \tabularnewline
3 & 1 & 1.06105 & -0.0610518 \tabularnewline
4 & 1 & 0.996118 & 0.00388224 \tabularnewline
5 & 1 & 1.00721 & -0.00721396 \tabularnewline
6 & 1 & 1.02715 & -0.0271471 \tabularnewline
7 & 1 & 0.806338 & 0.193662 \tabularnewline
8 & 1 & 0.838361 & 0.161639 \tabularnewline
9 & 1 & 0.923918 & 0.0760822 \tabularnewline
10 & 1 & 0.977561 & 0.0224388 \tabularnewline
11 & 1 & 0.956358 & 0.0436416 \tabularnewline
12 & 1 & 1.00617 & -0.00616681 \tabularnewline
13 & 1 & 0.622248 & 0.377752 \tabularnewline
14 & 1 & 0.812263 & 0.187737 \tabularnewline
15 & 1 & 0.750473 & 0.249527 \tabularnewline
16 & 1 & 0.730098 & 0.269902 \tabularnewline
17 & 1 & 0.686451 & 0.313549 \tabularnewline
18 & 1 & 0.866975 & 0.133025 \tabularnewline
19 & 1 & 1.19236 & -0.192361 \tabularnewline
20 & 1 & 0.906063 & 0.0939366 \tabularnewline
21 & 1 & 1.09739 & -0.0973892 \tabularnewline
22 & 1 & 0.992572 & 0.00742812 \tabularnewline
23 & 1 & 0.972342 & 0.0276583 \tabularnewline
24 & 1 & 0.887448 & 0.112552 \tabularnewline
25 & 1 & 0.751083 & 0.248917 \tabularnewline
26 & 1 & 1.08388 & -0.0838822 \tabularnewline
27 & 1 & 0.830074 & 0.169926 \tabularnewline
28 & 1 & 0.8087 & 0.1913 \tabularnewline
29 & 1 & 0.833413 & 0.166587 \tabularnewline
30 & 1 & 0.814263 & 0.185737 \tabularnewline
31 & 0 & 0.402973 & -0.402973 \tabularnewline
32 & 0 & 0.374153 & -0.374153 \tabularnewline
33 & 0 & 0.409645 & -0.409645 \tabularnewline
34 & 0 & 0.352107 & -0.352107 \tabularnewline
35 & 0 & 0.366348 & -0.366348 \tabularnewline
36 & 0 & 0.380132 & -0.380132 \tabularnewline
37 & 1 & 0.544856 & 0.455144 \tabularnewline
38 & 1 & 0.578792 & 0.421208 \tabularnewline
39 & 1 & 0.50094 & 0.49906 \tabularnewline
40 & 1 & 0.493328 & 0.506672 \tabularnewline
41 & 1 & 0.47584 & 0.52416 \tabularnewline
42 & 1 & 0.504695 & 0.495305 \tabularnewline
43 & 0 & 0.223286 & -0.223286 \tabularnewline
44 & 0 & 0.216787 & -0.216787 \tabularnewline
45 & 0 & 0.183469 & -0.183469 \tabularnewline
46 & 0 & 0.172374 & -0.172374 \tabularnewline
47 & 0 & 0.167814 & -0.167814 \tabularnewline
48 & 0 & 0.255561 & -0.255561 \tabularnewline
49 & 0 & 0.567142 & -0.567142 \tabularnewline
50 & 0 & 0.599487 & -0.599487 \tabularnewline
51 & 0 & 0.6356 & -0.6356 \tabularnewline
52 & 0 & 0.595488 & -0.595488 \tabularnewline
53 & 0 & 0.616892 & -0.616892 \tabularnewline
54 & 0 & 0.621838 & -0.621838 \tabularnewline
55 & 1 & 0.808567 & 0.191433 \tabularnewline
56 & 1 & 0.758064 & 0.241936 \tabularnewline
57 & 1 & 0.875962 & 0.124038 \tabularnewline
58 & 1 & 0.690135 & 0.309865 \tabularnewline
59 & 1 & 0.722906 & 0.277094 \tabularnewline
60 & 1 & 0.644968 & 0.355032 \tabularnewline
61 & 0 & 0.57071 & -0.57071 \tabularnewline
62 & 0 & 0.596376 & -0.596376 \tabularnewline
63 & 0 & 0.303831 & -0.303831 \tabularnewline
64 & 0 & 0.247204 & -0.247204 \tabularnewline
65 & 0 & 0.232275 & -0.232275 \tabularnewline
66 & 0 & 0.513784 & -0.513784 \tabularnewline
67 & 1 & 0.827783 & 0.172217 \tabularnewline
68 & 1 & 0.884007 & 0.115993 \tabularnewline
69 & 1 & 1.08088 & -0.0808825 \tabularnewline
70 & 1 & 1.02725 & -0.027246 \tabularnewline
71 & 1 & 0.89699 & 0.10301 \tabularnewline
72 & 1 & 1.05715 & -0.0571538 \tabularnewline
73 & 1 & 0.72836 & 0.27164 \tabularnewline
74 & 1 & 0.691177 & 0.308823 \tabularnewline
75 & 1 & 0.837153 & 0.162847 \tabularnewline
76 & 1 & 0.806538 & 0.193462 \tabularnewline
77 & 1 & 0.911042 & 0.0889577 \tabularnewline
78 & 1 & 0.803811 & 0.196189 \tabularnewline
79 & 1 & 0.978884 & 0.0211163 \tabularnewline
80 & 1 & 0.874184 & 0.125816 \tabularnewline
81 & 1 & 1.02264 & -0.0226388 \tabularnewline
82 & 1 & 0.960449 & 0.0395513 \tabularnewline
83 & 1 & 0.895357 & 0.104643 \tabularnewline
84 & 1 & 0.915769 & 0.0842314 \tabularnewline
85 & 1 & 0.909169 & 0.0908311 \tabularnewline
86 & 1 & 0.696217 & 0.303783 \tabularnewline
87 & 1 & 0.701882 & 0.298118 \tabularnewline
88 & 1 & 0.910449 & 0.0895513 \tabularnewline
89 & 1 & 0.988254 & 0.0117464 \tabularnewline
90 & 1 & 0.686917 & 0.313083 \tabularnewline
91 & 1 & 1.02809 & -0.0280874 \tabularnewline
92 & 1 & 0.995294 & 0.00470594 \tabularnewline
93 & 1 & 0.763732 & 0.236268 \tabularnewline
94 & 1 & 0.884868 & 0.115132 \tabularnewline
95 & 1 & 0.962574 & 0.0374261 \tabularnewline
96 & 1 & 0.7286 & 0.2714 \tabularnewline
97 & 1 & 0.751834 & 0.248166 \tabularnewline
98 & 1 & 0.838866 & 0.161134 \tabularnewline
99 & 1 & 0.980127 & 0.0198733 \tabularnewline
100 & 1 & 1.06651 & -0.0665116 \tabularnewline
101 & 1 & 1.11749 & -0.117487 \tabularnewline
102 & 1 & 1.23521 & -0.235209 \tabularnewline
103 & 1 & 1.1683 & -0.168303 \tabularnewline
104 & 1 & 0.754612 & 0.245388 \tabularnewline
105 & 1 & 0.661405 & 0.338595 \tabularnewline
106 & 1 & 0.64394 & 0.35606 \tabularnewline
107 & 1 & 0.574451 & 0.425549 \tabularnewline
108 & 1 & 0.695976 & 0.304024 \tabularnewline
109 & 1 & 0.66276 & 0.33724 \tabularnewline
110 & 1 & 0.728719 & 0.271281 \tabularnewline
111 & 1 & 0.715749 & 0.284251 \tabularnewline
112 & 1 & 0.41217 & 0.58783 \tabularnewline
113 & 1 & 0.494494 & 0.505506 \tabularnewline
114 & 1 & 0.420169 & 0.579831 \tabularnewline
115 & 1 & 0.675349 & 0.324651 \tabularnewline
116 & 1 & 0.644215 & 0.355785 \tabularnewline
117 & 1 & 0.694991 & 0.305009 \tabularnewline
118 & 1 & 0.646793 & 0.353207 \tabularnewline
119 & 1 & 0.459967 & 0.540033 \tabularnewline
120 & 1 & 0.379796 & 0.620204 \tabularnewline
121 & 1 & 0.725368 & 0.274632 \tabularnewline
122 & 1 & 0.610933 & 0.389067 \tabularnewline
123 & 1 & 0.923919 & 0.0760814 \tabularnewline
124 & 1 & 0.764027 & 0.235973 \tabularnewline
125 & 1 & 0.815292 & 0.184708 \tabularnewline
126 & 1 & 0.814984 & 0.185016 \tabularnewline
127 & 1 & 0.891896 & 0.108104 \tabularnewline
128 & 1 & 0.805419 & 0.194581 \tabularnewline
129 & 1 & 0.667543 & 0.332457 \tabularnewline
130 & 1 & 0.754494 & 0.245506 \tabularnewline
131 & 1 & 0.776057 & 0.223943 \tabularnewline
132 & 1 & 0.833216 & 0.166784 \tabularnewline
133 & 1 & 0.79071 & 0.20929 \tabularnewline
134 & 1 & 0.73812 & 0.26188 \tabularnewline
135 & 1 & 1.01 & -0.00999714 \tabularnewline
136 & 1 & 0.967921 & 0.0320794 \tabularnewline
137 & 1 & 1.18389 & -0.183887 \tabularnewline
138 & 1 & 1.04258 & -0.042583 \tabularnewline
139 & 1 & 1.06976 & -0.0697632 \tabularnewline
140 & 1 & 0.939283 & 0.0607174 \tabularnewline
141 & 1 & 0.736826 & 0.263174 \tabularnewline
142 & 1 & 0.880376 & 0.119624 \tabularnewline
143 & 1 & 0.576305 & 0.423695 \tabularnewline
144 & 1 & 0.641116 & 0.358884 \tabularnewline
145 & 1 & 0.475609 & 0.524391 \tabularnewline
146 & 1 & 0.618098 & 0.381902 \tabularnewline
147 & 1 & 1.14152 & -0.141519 \tabularnewline
148 & 1 & 0.858701 & 0.141299 \tabularnewline
149 & 1 & 1.00281 & -0.00280602 \tabularnewline
150 & 1 & 0.783814 & 0.216186 \tabularnewline
151 & 1 & 0.826393 & 0.173607 \tabularnewline
152 & 1 & 1.31141 & -0.311412 \tabularnewline
153 & 1 & 1.01317 & -0.0131718 \tabularnewline
154 & 1 & 0.853793 & 0.146207 \tabularnewline
155 & 1 & 0.872672 & 0.127328 \tabularnewline
156 & 1 & 0.893041 & 0.106959 \tabularnewline
157 & 1 & 0.818294 & 0.181706 \tabularnewline
158 & 1 & 1.08521 & -0.0852109 \tabularnewline
159 & 1 & 0.888767 & 0.111233 \tabularnewline
160 & 1 & 1.06195 & -0.0619461 \tabularnewline
161 & 1 & 1.37002 & -0.370019 \tabularnewline
162 & 1 & 0.973325 & 0.0266745 \tabularnewline
163 & 1 & 1.02875 & -0.0287536 \tabularnewline
164 & 1 & 0.80464 & 0.19536 \tabularnewline
165 & 1 & 0.845513 & 0.154487 \tabularnewline
166 & 0 & 0.554188 & -0.554188 \tabularnewline
167 & 0 & 0.160159 & -0.160159 \tabularnewline
168 & 0 & 0.143073 & -0.143073 \tabularnewline
169 & 0 & 0.700266 & -0.700266 \tabularnewline
170 & 0 & 0.212776 & -0.212776 \tabularnewline
171 & 0 & 0.164126 & -0.164126 \tabularnewline
172 & 0 & 0.784235 & -0.784235 \tabularnewline
173 & 0 & 0.815043 & -0.815043 \tabularnewline
174 & 0 & 0.816142 & -0.816142 \tabularnewline
175 & 0 & 0.807764 & -0.807764 \tabularnewline
176 & 0 & 0.767632 & -0.767632 \tabularnewline
177 & 0 & 0.822677 & -0.822677 \tabularnewline
178 & 1 & 0.624895 & 0.375105 \tabularnewline
179 & 1 & 0.627253 & 0.372747 \tabularnewline
180 & 1 & 0.659551 & 0.340449 \tabularnewline
181 & 1 & 0.692314 & 0.307686 \tabularnewline
182 & 1 & 0.669667 & 0.330333 \tabularnewline
183 & 1 & 0.673371 & 0.326629 \tabularnewline
184 & 0 & 0.850573 & -0.850573 \tabularnewline
185 & 0 & 0.856737 & -0.856737 \tabularnewline
186 & 0 & 0.849574 & -0.849574 \tabularnewline
187 & 0 & 0.720055 & -0.720055 \tabularnewline
188 & 0 & 0.702413 & -0.702413 \tabularnewline
189 & 0 & 0.808258 & -0.808258 \tabularnewline
190 & 0 & 0.696702 & -0.696702 \tabularnewline
191 & 0 & 0.785412 & -0.785412 \tabularnewline
192 & 0 & 0.617763 & -0.617763 \tabularnewline
193 & 0 & 0.363409 & -0.363409 \tabularnewline
194 & 0 & 0.579766 & -0.579766 \tabularnewline
195 & 0 & 0.581501 & -0.581501 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231227&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]1[/C][C]1.07415[/C][C]-0.0741475[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]1.009[/C][C]-0.00900408[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]1.06105[/C][C]-0.0610518[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]0.996118[/C][C]0.00388224[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]1.00721[/C][C]-0.00721396[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]1.02715[/C][C]-0.0271471[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.806338[/C][C]0.193662[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.838361[/C][C]0.161639[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.923918[/C][C]0.0760822[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]0.977561[/C][C]0.0224388[/C][/ROW]
[ROW][C]11[/C][C]1[/C][C]0.956358[/C][C]0.0436416[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]1.00617[/C][C]-0.00616681[/C][/ROW]
[ROW][C]13[/C][C]1[/C][C]0.622248[/C][C]0.377752[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]0.812263[/C][C]0.187737[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.750473[/C][C]0.249527[/C][/ROW]
[ROW][C]16[/C][C]1[/C][C]0.730098[/C][C]0.269902[/C][/ROW]
[ROW][C]17[/C][C]1[/C][C]0.686451[/C][C]0.313549[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]0.866975[/C][C]0.133025[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]1.19236[/C][C]-0.192361[/C][/ROW]
[ROW][C]20[/C][C]1[/C][C]0.906063[/C][C]0.0939366[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]1.09739[/C][C]-0.0973892[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.992572[/C][C]0.00742812[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]0.972342[/C][C]0.0276583[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.887448[/C][C]0.112552[/C][/ROW]
[ROW][C]25[/C][C]1[/C][C]0.751083[/C][C]0.248917[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]1.08388[/C][C]-0.0838822[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]0.830074[/C][C]0.169926[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]0.8087[/C][C]0.1913[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.833413[/C][C]0.166587[/C][/ROW]
[ROW][C]30[/C][C]1[/C][C]0.814263[/C][C]0.185737[/C][/ROW]
[ROW][C]31[/C][C]0[/C][C]0.402973[/C][C]-0.402973[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0.374153[/C][C]-0.374153[/C][/ROW]
[ROW][C]33[/C][C]0[/C][C]0.409645[/C][C]-0.409645[/C][/ROW]
[ROW][C]34[/C][C]0[/C][C]0.352107[/C][C]-0.352107[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0.366348[/C][C]-0.366348[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0.380132[/C][C]-0.380132[/C][/ROW]
[ROW][C]37[/C][C]1[/C][C]0.544856[/C][C]0.455144[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.578792[/C][C]0.421208[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.50094[/C][C]0.49906[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]0.493328[/C][C]0.506672[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.47584[/C][C]0.52416[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.504695[/C][C]0.495305[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0.223286[/C][C]-0.223286[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0.216787[/C][C]-0.216787[/C][/ROW]
[ROW][C]45[/C][C]0[/C][C]0.183469[/C][C]-0.183469[/C][/ROW]
[ROW][C]46[/C][C]0[/C][C]0.172374[/C][C]-0.172374[/C][/ROW]
[ROW][C]47[/C][C]0[/C][C]0.167814[/C][C]-0.167814[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]0.255561[/C][C]-0.255561[/C][/ROW]
[ROW][C]49[/C][C]0[/C][C]0.567142[/C][C]-0.567142[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0.599487[/C][C]-0.599487[/C][/ROW]
[ROW][C]51[/C][C]0[/C][C]0.6356[/C][C]-0.6356[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0.595488[/C][C]-0.595488[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0.616892[/C][C]-0.616892[/C][/ROW]
[ROW][C]54[/C][C]0[/C][C]0.621838[/C][C]-0.621838[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.808567[/C][C]0.191433[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]0.758064[/C][C]0.241936[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]0.875962[/C][C]0.124038[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.690135[/C][C]0.309865[/C][/ROW]
[ROW][C]59[/C][C]1[/C][C]0.722906[/C][C]0.277094[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.644968[/C][C]0.355032[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0.57071[/C][C]-0.57071[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0.596376[/C][C]-0.596376[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0.303831[/C][C]-0.303831[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0.247204[/C][C]-0.247204[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0.232275[/C][C]-0.232275[/C][/ROW]
[ROW][C]66[/C][C]0[/C][C]0.513784[/C][C]-0.513784[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.827783[/C][C]0.172217[/C][/ROW]
[ROW][C]68[/C][C]1[/C][C]0.884007[/C][C]0.115993[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]1.08088[/C][C]-0.0808825[/C][/ROW]
[ROW][C]70[/C][C]1[/C][C]1.02725[/C][C]-0.027246[/C][/ROW]
[ROW][C]71[/C][C]1[/C][C]0.89699[/C][C]0.10301[/C][/ROW]
[ROW][C]72[/C][C]1[/C][C]1.05715[/C][C]-0.0571538[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]0.72836[/C][C]0.27164[/C][/ROW]
[ROW][C]74[/C][C]1[/C][C]0.691177[/C][C]0.308823[/C][/ROW]
[ROW][C]75[/C][C]1[/C][C]0.837153[/C][C]0.162847[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]0.806538[/C][C]0.193462[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]0.911042[/C][C]0.0889577[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]0.803811[/C][C]0.196189[/C][/ROW]
[ROW][C]79[/C][C]1[/C][C]0.978884[/C][C]0.0211163[/C][/ROW]
[ROW][C]80[/C][C]1[/C][C]0.874184[/C][C]0.125816[/C][/ROW]
[ROW][C]81[/C][C]1[/C][C]1.02264[/C][C]-0.0226388[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]0.960449[/C][C]0.0395513[/C][/ROW]
[ROW][C]83[/C][C]1[/C][C]0.895357[/C][C]0.104643[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]0.915769[/C][C]0.0842314[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]0.909169[/C][C]0.0908311[/C][/ROW]
[ROW][C]86[/C][C]1[/C][C]0.696217[/C][C]0.303783[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.701882[/C][C]0.298118[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]0.910449[/C][C]0.0895513[/C][/ROW]
[ROW][C]89[/C][C]1[/C][C]0.988254[/C][C]0.0117464[/C][/ROW]
[ROW][C]90[/C][C]1[/C][C]0.686917[/C][C]0.313083[/C][/ROW]
[ROW][C]91[/C][C]1[/C][C]1.02809[/C][C]-0.0280874[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]0.995294[/C][C]0.00470594[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.763732[/C][C]0.236268[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]0.884868[/C][C]0.115132[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]0.962574[/C][C]0.0374261[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.7286[/C][C]0.2714[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]0.751834[/C][C]0.248166[/C][/ROW]
[ROW][C]98[/C][C]1[/C][C]0.838866[/C][C]0.161134[/C][/ROW]
[ROW][C]99[/C][C]1[/C][C]0.980127[/C][C]0.0198733[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]1.06651[/C][C]-0.0665116[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]1.11749[/C][C]-0.117487[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]1.23521[/C][C]-0.235209[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]1.1683[/C][C]-0.168303[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.754612[/C][C]0.245388[/C][/ROW]
[ROW][C]105[/C][C]1[/C][C]0.661405[/C][C]0.338595[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]0.64394[/C][C]0.35606[/C][/ROW]
[ROW][C]107[/C][C]1[/C][C]0.574451[/C][C]0.425549[/C][/ROW]
[ROW][C]108[/C][C]1[/C][C]0.695976[/C][C]0.304024[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]0.66276[/C][C]0.33724[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]0.728719[/C][C]0.271281[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]0.715749[/C][C]0.284251[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]0.41217[/C][C]0.58783[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.494494[/C][C]0.505506[/C][/ROW]
[ROW][C]114[/C][C]1[/C][C]0.420169[/C][C]0.579831[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.675349[/C][C]0.324651[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.644215[/C][C]0.355785[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.694991[/C][C]0.305009[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]0.646793[/C][C]0.353207[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]0.459967[/C][C]0.540033[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.379796[/C][C]0.620204[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]0.725368[/C][C]0.274632[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]0.610933[/C][C]0.389067[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]0.923919[/C][C]0.0760814[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.764027[/C][C]0.235973[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]0.815292[/C][C]0.184708[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.814984[/C][C]0.185016[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.891896[/C][C]0.108104[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.805419[/C][C]0.194581[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]0.667543[/C][C]0.332457[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]0.754494[/C][C]0.245506[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.776057[/C][C]0.223943[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]0.833216[/C][C]0.166784[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]0.79071[/C][C]0.20929[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.73812[/C][C]0.26188[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]1.01[/C][C]-0.00999714[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]0.967921[/C][C]0.0320794[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]1.18389[/C][C]-0.183887[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]1.04258[/C][C]-0.042583[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]1.06976[/C][C]-0.0697632[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.939283[/C][C]0.0607174[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]0.736826[/C][C]0.263174[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.880376[/C][C]0.119624[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]0.576305[/C][C]0.423695[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.641116[/C][C]0.358884[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.475609[/C][C]0.524391[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]0.618098[/C][C]0.381902[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]1.14152[/C][C]-0.141519[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]0.858701[/C][C]0.141299[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]1.00281[/C][C]-0.00280602[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.783814[/C][C]0.216186[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]0.826393[/C][C]0.173607[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]1.31141[/C][C]-0.311412[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]1.01317[/C][C]-0.0131718[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.853793[/C][C]0.146207[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]0.872672[/C][C]0.127328[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.893041[/C][C]0.106959[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.818294[/C][C]0.181706[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]1.08521[/C][C]-0.0852109[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]0.888767[/C][C]0.111233[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]1.06195[/C][C]-0.0619461[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]1.37002[/C][C]-0.370019[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]0.973325[/C][C]0.0266745[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]1.02875[/C][C]-0.0287536[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]0.80464[/C][C]0.19536[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]0.845513[/C][C]0.154487[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.554188[/C][C]-0.554188[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.160159[/C][C]-0.160159[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.143073[/C][C]-0.143073[/C][/ROW]
[ROW][C]169[/C][C]0[/C][C]0.700266[/C][C]-0.700266[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.212776[/C][C]-0.212776[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.164126[/C][C]-0.164126[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.784235[/C][C]-0.784235[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.815043[/C][C]-0.815043[/C][/ROW]
[ROW][C]174[/C][C]0[/C][C]0.816142[/C][C]-0.816142[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.807764[/C][C]-0.807764[/C][/ROW]
[ROW][C]176[/C][C]0[/C][C]0.767632[/C][C]-0.767632[/C][/ROW]
[ROW][C]177[/C][C]0[/C][C]0.822677[/C][C]-0.822677[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0.624895[/C][C]0.375105[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]0.627253[/C][C]0.372747[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]0.659551[/C][C]0.340449[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]0.692314[/C][C]0.307686[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]0.669667[/C][C]0.330333[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0.673371[/C][C]0.326629[/C][/ROW]
[ROW][C]184[/C][C]0[/C][C]0.850573[/C][C]-0.850573[/C][/ROW]
[ROW][C]185[/C][C]0[/C][C]0.856737[/C][C]-0.856737[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]0.849574[/C][C]-0.849574[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.720055[/C][C]-0.720055[/C][/ROW]
[ROW][C]188[/C][C]0[/C][C]0.702413[/C][C]-0.702413[/C][/ROW]
[ROW][C]189[/C][C]0[/C][C]0.808258[/C][C]-0.808258[/C][/ROW]
[ROW][C]190[/C][C]0[/C][C]0.696702[/C][C]-0.696702[/C][/ROW]
[ROW][C]191[/C][C]0[/C][C]0.785412[/C][C]-0.785412[/C][/ROW]
[ROW][C]192[/C][C]0[/C][C]0.617763[/C][C]-0.617763[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]0.363409[/C][C]-0.363409[/C][/ROW]
[ROW][C]194[/C][C]0[/C][C]0.579766[/C][C]-0.579766[/C][/ROW]
[ROW][C]195[/C][C]0[/C][C]0.581501[/C][C]-0.581501[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231227&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231227&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
111.07415-0.0741475
211.009-0.00900408
311.06105-0.0610518
410.9961180.00388224
511.00721-0.00721396
611.02715-0.0271471
710.8063380.193662
810.8383610.161639
910.9239180.0760822
1010.9775610.0224388
1110.9563580.0436416
1211.00617-0.00616681
1310.6222480.377752
1410.8122630.187737
1510.7504730.249527
1610.7300980.269902
1710.6864510.313549
1810.8669750.133025
1911.19236-0.192361
2010.9060630.0939366
2111.09739-0.0973892
2210.9925720.00742812
2310.9723420.0276583
2410.8874480.112552
2510.7510830.248917
2611.08388-0.0838822
2710.8300740.169926
2810.80870.1913
2910.8334130.166587
3010.8142630.185737
3100.402973-0.402973
3200.374153-0.374153
3300.409645-0.409645
3400.352107-0.352107
3500.366348-0.366348
3600.380132-0.380132
3710.5448560.455144
3810.5787920.421208
3910.500940.49906
4010.4933280.506672
4110.475840.52416
4210.5046950.495305
4300.223286-0.223286
4400.216787-0.216787
4500.183469-0.183469
4600.172374-0.172374
4700.167814-0.167814
4800.255561-0.255561
4900.567142-0.567142
5000.599487-0.599487
5100.6356-0.6356
5200.595488-0.595488
5300.616892-0.616892
5400.621838-0.621838
5510.8085670.191433
5610.7580640.241936
5710.8759620.124038
5810.6901350.309865
5910.7229060.277094
6010.6449680.355032
6100.57071-0.57071
6200.596376-0.596376
6300.303831-0.303831
6400.247204-0.247204
6500.232275-0.232275
6600.513784-0.513784
6710.8277830.172217
6810.8840070.115993
6911.08088-0.0808825
7011.02725-0.027246
7110.896990.10301
7211.05715-0.0571538
7310.728360.27164
7410.6911770.308823
7510.8371530.162847
7610.8065380.193462
7710.9110420.0889577
7810.8038110.196189
7910.9788840.0211163
8010.8741840.125816
8111.02264-0.0226388
8210.9604490.0395513
8310.8953570.104643
8410.9157690.0842314
8510.9091690.0908311
8610.6962170.303783
8710.7018820.298118
8810.9104490.0895513
8910.9882540.0117464
9010.6869170.313083
9111.02809-0.0280874
9210.9952940.00470594
9310.7637320.236268
9410.8848680.115132
9510.9625740.0374261
9610.72860.2714
9710.7518340.248166
9810.8388660.161134
9910.9801270.0198733
10011.06651-0.0665116
10111.11749-0.117487
10211.23521-0.235209
10311.1683-0.168303
10410.7546120.245388
10510.6614050.338595
10610.643940.35606
10710.5744510.425549
10810.6959760.304024
10910.662760.33724
11010.7287190.271281
11110.7157490.284251
11210.412170.58783
11310.4944940.505506
11410.4201690.579831
11510.6753490.324651
11610.6442150.355785
11710.6949910.305009
11810.6467930.353207
11910.4599670.540033
12010.3797960.620204
12110.7253680.274632
12210.6109330.389067
12310.9239190.0760814
12410.7640270.235973
12510.8152920.184708
12610.8149840.185016
12710.8918960.108104
12810.8054190.194581
12910.6675430.332457
13010.7544940.245506
13110.7760570.223943
13210.8332160.166784
13310.790710.20929
13410.738120.26188
13511.01-0.00999714
13610.9679210.0320794
13711.18389-0.183887
13811.04258-0.042583
13911.06976-0.0697632
14010.9392830.0607174
14110.7368260.263174
14210.8803760.119624
14310.5763050.423695
14410.6411160.358884
14510.4756090.524391
14610.6180980.381902
14711.14152-0.141519
14810.8587010.141299
14911.00281-0.00280602
15010.7838140.216186
15110.8263930.173607
15211.31141-0.311412
15311.01317-0.0131718
15410.8537930.146207
15510.8726720.127328
15610.8930410.106959
15710.8182940.181706
15811.08521-0.0852109
15910.8887670.111233
16011.06195-0.0619461
16111.37002-0.370019
16210.9733250.0266745
16311.02875-0.0287536
16410.804640.19536
16510.8455130.154487
16600.554188-0.554188
16700.160159-0.160159
16800.143073-0.143073
16900.700266-0.700266
17000.212776-0.212776
17100.164126-0.164126
17200.784235-0.784235
17300.815043-0.815043
17400.816142-0.816142
17500.807764-0.807764
17600.767632-0.767632
17700.822677-0.822677
17810.6248950.375105
17910.6272530.372747
18010.6595510.340449
18110.6923140.307686
18210.6696670.330333
18310.6733710.326629
18400.850573-0.850573
18500.856737-0.856737
18600.849574-0.849574
18700.720055-0.720055
18800.702413-0.702413
18900.808258-0.808258
19000.696702-0.696702
19100.785412-0.785412
19200.617763-0.617763
19300.363409-0.363409
19400.579766-0.579766
19500.581501-0.581501






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
181.30916e-472.61833e-471
197.05273e-631.41055e-621
203.33181e-826.66362e-821
215.54596e-1061.10919e-1051
225.50761e-1111.10152e-1101
231.74386e-1243.48772e-1241
249.39641e-1421.87928e-1411
254.10354e-1588.20708e-1581
261.94283e-1893.88566e-1891
271.59177e-1883.18355e-1881
288.24713e-2011.64943e-2001
291.79971e-2193.59942e-2191
301.12989e-2352.25979e-2351
311.36648e-062.73297e-060.999999
329.9873e-071.99746e-060.999999
333.16984e-076.33967e-071
349.80748e-081.9615e-071
353.20453e-086.40906e-081
369.68898e-091.9378e-081
373.88477e-077.76954e-071
384.1741e-068.3482e-060.999996
390.0004223470.0008446940.999578
400.002628540.005257070.997371
410.00853380.01706760.991466
420.009603810.01920760.990396
430.006977650.01395530.993022
440.004631550.00926310.995368
450.003195790.006391580.996804
460.002056180.004112360.997944
470.001331050.002662090.998669
480.0008620240.001724050.999138
490.002763120.005526250.997237
500.00401840.008036790.995982
510.004638180.009276370.995362
520.004116060.008232110.995884
530.004782440.009564890.995218
540.005730450.01146090.99427
550.005447060.01089410.994553
560.005727080.01145420.994273
570.003885080.007770150.996115
580.002838740.005677490.997161
590.001973340.003946680.998027
600.001310170.002620330.99869
610.003640140.007280290.99636
620.004147480.008294970.995853
630.00329810.00659620.996702
640.002552040.005104090.997448
650.002045490.004090970.997955
660.002036480.004072960.997964
670.001371980.002743950.998628
680.0009257110.001851420.999074
690.000630810.001261620.999369
700.0006518860.001303770.999348
710.0004444130.0008888250.999556
720.0003232990.0006465990.999677
730.0002222820.0004445640.999778
740.0004598770.0009197540.99954
750.0003103220.0006206440.99969
760.0002028810.0004057610.999797
770.0001289290.0002578590.999871
788.10562e-050.0001621120.999919
795.11223e-050.0001022450.999949
803.90094e-057.80188e-050.999961
812.54963e-055.09925e-050.999975
821.67048e-053.34095e-050.999983
831.12964e-052.25928e-050.999989
848.26524e-061.65305e-050.999992
855.59944e-061.11989e-050.999994
861.34364e-052.68727e-050.999987
873.8012e-057.60241e-050.999962
883.36463e-056.72927e-050.999966
893.21661e-056.43323e-050.999968
902.22503e-054.45007e-050.999978
911.59445e-053.18889e-050.999984
921.35556e-052.71112e-050.999986
939.15462e-061.83092e-050.999991
945.90536e-061.18107e-050.999994
953.70364e-067.40729e-060.999996
962.55381e-065.10762e-060.999997
971.66184e-063.32368e-060.999998
981.16467e-062.32934e-060.999999
996.64716e-071.32943e-060.999999
1005.41756e-071.08351e-060.999999
1013.38739e-076.77479e-071
1028.95255e-071.79051e-060.999999
1032.27903e-064.55807e-060.999998
1041.95217e-063.90433e-060.999998
1051.58925e-063.17849e-060.999998
1061.56246e-063.12492e-060.999998
1071.54685e-063.09369e-060.999998
1081.3449e-062.6898e-060.999999
1099.66697e-071.93339e-060.999999
1107.89786e-071.57957e-060.999999
1116.185e-071.237e-060.999999
1121.15961e-062.31922e-060.999999
1131.4748e-062.94959e-060.999999
1145.33094e-061.06619e-050.999995
1154.43015e-068.8603e-060.999996
1165.55502e-061.111e-050.999994
1175.03736e-061.00747e-050.999995
1184.277e-068.554e-060.999996
1191.23286e-052.46572e-050.999988
1207.39156e-050.0001478310.999926
1210.0001416770.0002833540.999858
1220.0002699310.0005398630.99973
1230.0001851110.0003702230.999815
1240.0001558620.0003117240.999844
1250.0001641210.0003282420.999836
1260.0002434040.0004868070.999757
1270.0003336260.0006672530.999666
1280.0004746120.0009492240.999525
1290.0003794970.0007589950.999621
1300.0004149710.0008299420.999585
1310.000656940.001313880.999343
1320.0005452080.001090420.999455
1330.0007848110.001569620.999215
1340.001319380.002638760.998681
1350.0009342620.001868520.999066
1360.0006279140.001255830.999372
1370.0004396870.0008793750.99956
1380.0003058560.0006117130.999694
1390.0001973240.0003946490.999803
1400.0001255560.0002511120.999874
1410.0001227490.0002454970.999877
1429.16219e-050.0001832440.999908
1439.2951e-050.0001859020.999907
1440.0004761370.0009522750.999524
1450.001412950.00282590.998587
1460.005217350.01043470.994783
1470.003858480.007716950.996142
1480.003058420.006116830.996942
1490.002919620.005839240.99708
1500.002131240.004262490.997869
1510.001537270.003074540.998463
1520.007461690.01492340.992538
1530.005292060.01058410.994708
1540.003532920.007065840.996467
1550.002662090.005324190.997338
1560.001790730.003581460.998209
1570.002684870.005369740.997315
1580.001926040.003852090.998074
1590.001241770.002483530.998758
1600.001054720.002109430.998945
1610.001185960.002371910.998814
1620.0008033010.00160660.999197
1630.001760460.003520910.99824
1640.002544180.005088370.997456
1650.005630790.01126160.994369
1660.01072680.02145360.989273
1670.01179070.02358130.988209
1680.01387480.02774960.986125
1690.0257620.05152390.974238
1700.02867050.05734110.971329
1710.9640780.07184310.0359215
1720.9862710.02745850.0137293
1730.9770890.04582150.0229108
1740.9570270.08594640.0429732
1750.9657810.06843890.0342194
1760.9528580.09428320.0471416
1770.9909740.01805210.00902606

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
18 & 1.30916e-47 & 2.61833e-47 & 1 \tabularnewline
19 & 7.05273e-63 & 1.41055e-62 & 1 \tabularnewline
20 & 3.33181e-82 & 6.66362e-82 & 1 \tabularnewline
21 & 5.54596e-106 & 1.10919e-105 & 1 \tabularnewline
22 & 5.50761e-111 & 1.10152e-110 & 1 \tabularnewline
23 & 1.74386e-124 & 3.48772e-124 & 1 \tabularnewline
24 & 9.39641e-142 & 1.87928e-141 & 1 \tabularnewline
25 & 4.10354e-158 & 8.20708e-158 & 1 \tabularnewline
26 & 1.94283e-189 & 3.88566e-189 & 1 \tabularnewline
27 & 1.59177e-188 & 3.18355e-188 & 1 \tabularnewline
28 & 8.24713e-201 & 1.64943e-200 & 1 \tabularnewline
29 & 1.79971e-219 & 3.59942e-219 & 1 \tabularnewline
30 & 1.12989e-235 & 2.25979e-235 & 1 \tabularnewline
31 & 1.36648e-06 & 2.73297e-06 & 0.999999 \tabularnewline
32 & 9.9873e-07 & 1.99746e-06 & 0.999999 \tabularnewline
33 & 3.16984e-07 & 6.33967e-07 & 1 \tabularnewline
34 & 9.80748e-08 & 1.9615e-07 & 1 \tabularnewline
35 & 3.20453e-08 & 6.40906e-08 & 1 \tabularnewline
36 & 9.68898e-09 & 1.9378e-08 & 1 \tabularnewline
37 & 3.88477e-07 & 7.76954e-07 & 1 \tabularnewline
38 & 4.1741e-06 & 8.3482e-06 & 0.999996 \tabularnewline
39 & 0.000422347 & 0.000844694 & 0.999578 \tabularnewline
40 & 0.00262854 & 0.00525707 & 0.997371 \tabularnewline
41 & 0.0085338 & 0.0170676 & 0.991466 \tabularnewline
42 & 0.00960381 & 0.0192076 & 0.990396 \tabularnewline
43 & 0.00697765 & 0.0139553 & 0.993022 \tabularnewline
44 & 0.00463155 & 0.0092631 & 0.995368 \tabularnewline
45 & 0.00319579 & 0.00639158 & 0.996804 \tabularnewline
46 & 0.00205618 & 0.00411236 & 0.997944 \tabularnewline
47 & 0.00133105 & 0.00266209 & 0.998669 \tabularnewline
48 & 0.000862024 & 0.00172405 & 0.999138 \tabularnewline
49 & 0.00276312 & 0.00552625 & 0.997237 \tabularnewline
50 & 0.0040184 & 0.00803679 & 0.995982 \tabularnewline
51 & 0.00463818 & 0.00927637 & 0.995362 \tabularnewline
52 & 0.00411606 & 0.00823211 & 0.995884 \tabularnewline
53 & 0.00478244 & 0.00956489 & 0.995218 \tabularnewline
54 & 0.00573045 & 0.0114609 & 0.99427 \tabularnewline
55 & 0.00544706 & 0.0108941 & 0.994553 \tabularnewline
56 & 0.00572708 & 0.0114542 & 0.994273 \tabularnewline
57 & 0.00388508 & 0.00777015 & 0.996115 \tabularnewline
58 & 0.00283874 & 0.00567749 & 0.997161 \tabularnewline
59 & 0.00197334 & 0.00394668 & 0.998027 \tabularnewline
60 & 0.00131017 & 0.00262033 & 0.99869 \tabularnewline
61 & 0.00364014 & 0.00728029 & 0.99636 \tabularnewline
62 & 0.00414748 & 0.00829497 & 0.995853 \tabularnewline
63 & 0.0032981 & 0.0065962 & 0.996702 \tabularnewline
64 & 0.00255204 & 0.00510409 & 0.997448 \tabularnewline
65 & 0.00204549 & 0.00409097 & 0.997955 \tabularnewline
66 & 0.00203648 & 0.00407296 & 0.997964 \tabularnewline
67 & 0.00137198 & 0.00274395 & 0.998628 \tabularnewline
68 & 0.000925711 & 0.00185142 & 0.999074 \tabularnewline
69 & 0.00063081 & 0.00126162 & 0.999369 \tabularnewline
70 & 0.000651886 & 0.00130377 & 0.999348 \tabularnewline
71 & 0.000444413 & 0.000888825 & 0.999556 \tabularnewline
72 & 0.000323299 & 0.000646599 & 0.999677 \tabularnewline
73 & 0.000222282 & 0.000444564 & 0.999778 \tabularnewline
74 & 0.000459877 & 0.000919754 & 0.99954 \tabularnewline
75 & 0.000310322 & 0.000620644 & 0.99969 \tabularnewline
76 & 0.000202881 & 0.000405761 & 0.999797 \tabularnewline
77 & 0.000128929 & 0.000257859 & 0.999871 \tabularnewline
78 & 8.10562e-05 & 0.000162112 & 0.999919 \tabularnewline
79 & 5.11223e-05 & 0.000102245 & 0.999949 \tabularnewline
80 & 3.90094e-05 & 7.80188e-05 & 0.999961 \tabularnewline
81 & 2.54963e-05 & 5.09925e-05 & 0.999975 \tabularnewline
82 & 1.67048e-05 & 3.34095e-05 & 0.999983 \tabularnewline
83 & 1.12964e-05 & 2.25928e-05 & 0.999989 \tabularnewline
84 & 8.26524e-06 & 1.65305e-05 & 0.999992 \tabularnewline
85 & 5.59944e-06 & 1.11989e-05 & 0.999994 \tabularnewline
86 & 1.34364e-05 & 2.68727e-05 & 0.999987 \tabularnewline
87 & 3.8012e-05 & 7.60241e-05 & 0.999962 \tabularnewline
88 & 3.36463e-05 & 6.72927e-05 & 0.999966 \tabularnewline
89 & 3.21661e-05 & 6.43323e-05 & 0.999968 \tabularnewline
90 & 2.22503e-05 & 4.45007e-05 & 0.999978 \tabularnewline
91 & 1.59445e-05 & 3.18889e-05 & 0.999984 \tabularnewline
92 & 1.35556e-05 & 2.71112e-05 & 0.999986 \tabularnewline
93 & 9.15462e-06 & 1.83092e-05 & 0.999991 \tabularnewline
94 & 5.90536e-06 & 1.18107e-05 & 0.999994 \tabularnewline
95 & 3.70364e-06 & 7.40729e-06 & 0.999996 \tabularnewline
96 & 2.55381e-06 & 5.10762e-06 & 0.999997 \tabularnewline
97 & 1.66184e-06 & 3.32368e-06 & 0.999998 \tabularnewline
98 & 1.16467e-06 & 2.32934e-06 & 0.999999 \tabularnewline
99 & 6.64716e-07 & 1.32943e-06 & 0.999999 \tabularnewline
100 & 5.41756e-07 & 1.08351e-06 & 0.999999 \tabularnewline
101 & 3.38739e-07 & 6.77479e-07 & 1 \tabularnewline
102 & 8.95255e-07 & 1.79051e-06 & 0.999999 \tabularnewline
103 & 2.27903e-06 & 4.55807e-06 & 0.999998 \tabularnewline
104 & 1.95217e-06 & 3.90433e-06 & 0.999998 \tabularnewline
105 & 1.58925e-06 & 3.17849e-06 & 0.999998 \tabularnewline
106 & 1.56246e-06 & 3.12492e-06 & 0.999998 \tabularnewline
107 & 1.54685e-06 & 3.09369e-06 & 0.999998 \tabularnewline
108 & 1.3449e-06 & 2.6898e-06 & 0.999999 \tabularnewline
109 & 9.66697e-07 & 1.93339e-06 & 0.999999 \tabularnewline
110 & 7.89786e-07 & 1.57957e-06 & 0.999999 \tabularnewline
111 & 6.185e-07 & 1.237e-06 & 0.999999 \tabularnewline
112 & 1.15961e-06 & 2.31922e-06 & 0.999999 \tabularnewline
113 & 1.4748e-06 & 2.94959e-06 & 0.999999 \tabularnewline
114 & 5.33094e-06 & 1.06619e-05 & 0.999995 \tabularnewline
115 & 4.43015e-06 & 8.8603e-06 & 0.999996 \tabularnewline
116 & 5.55502e-06 & 1.111e-05 & 0.999994 \tabularnewline
117 & 5.03736e-06 & 1.00747e-05 & 0.999995 \tabularnewline
118 & 4.277e-06 & 8.554e-06 & 0.999996 \tabularnewline
119 & 1.23286e-05 & 2.46572e-05 & 0.999988 \tabularnewline
120 & 7.39156e-05 & 0.000147831 & 0.999926 \tabularnewline
121 & 0.000141677 & 0.000283354 & 0.999858 \tabularnewline
122 & 0.000269931 & 0.000539863 & 0.99973 \tabularnewline
123 & 0.000185111 & 0.000370223 & 0.999815 \tabularnewline
124 & 0.000155862 & 0.000311724 & 0.999844 \tabularnewline
125 & 0.000164121 & 0.000328242 & 0.999836 \tabularnewline
126 & 0.000243404 & 0.000486807 & 0.999757 \tabularnewline
127 & 0.000333626 & 0.000667253 & 0.999666 \tabularnewline
128 & 0.000474612 & 0.000949224 & 0.999525 \tabularnewline
129 & 0.000379497 & 0.000758995 & 0.999621 \tabularnewline
130 & 0.000414971 & 0.000829942 & 0.999585 \tabularnewline
131 & 0.00065694 & 0.00131388 & 0.999343 \tabularnewline
132 & 0.000545208 & 0.00109042 & 0.999455 \tabularnewline
133 & 0.000784811 & 0.00156962 & 0.999215 \tabularnewline
134 & 0.00131938 & 0.00263876 & 0.998681 \tabularnewline
135 & 0.000934262 & 0.00186852 & 0.999066 \tabularnewline
136 & 0.000627914 & 0.00125583 & 0.999372 \tabularnewline
137 & 0.000439687 & 0.000879375 & 0.99956 \tabularnewline
138 & 0.000305856 & 0.000611713 & 0.999694 \tabularnewline
139 & 0.000197324 & 0.000394649 & 0.999803 \tabularnewline
140 & 0.000125556 & 0.000251112 & 0.999874 \tabularnewline
141 & 0.000122749 & 0.000245497 & 0.999877 \tabularnewline
142 & 9.16219e-05 & 0.000183244 & 0.999908 \tabularnewline
143 & 9.2951e-05 & 0.000185902 & 0.999907 \tabularnewline
144 & 0.000476137 & 0.000952275 & 0.999524 \tabularnewline
145 & 0.00141295 & 0.0028259 & 0.998587 \tabularnewline
146 & 0.00521735 & 0.0104347 & 0.994783 \tabularnewline
147 & 0.00385848 & 0.00771695 & 0.996142 \tabularnewline
148 & 0.00305842 & 0.00611683 & 0.996942 \tabularnewline
149 & 0.00291962 & 0.00583924 & 0.99708 \tabularnewline
150 & 0.00213124 & 0.00426249 & 0.997869 \tabularnewline
151 & 0.00153727 & 0.00307454 & 0.998463 \tabularnewline
152 & 0.00746169 & 0.0149234 & 0.992538 \tabularnewline
153 & 0.00529206 & 0.0105841 & 0.994708 \tabularnewline
154 & 0.00353292 & 0.00706584 & 0.996467 \tabularnewline
155 & 0.00266209 & 0.00532419 & 0.997338 \tabularnewline
156 & 0.00179073 & 0.00358146 & 0.998209 \tabularnewline
157 & 0.00268487 & 0.00536974 & 0.997315 \tabularnewline
158 & 0.00192604 & 0.00385209 & 0.998074 \tabularnewline
159 & 0.00124177 & 0.00248353 & 0.998758 \tabularnewline
160 & 0.00105472 & 0.00210943 & 0.998945 \tabularnewline
161 & 0.00118596 & 0.00237191 & 0.998814 \tabularnewline
162 & 0.000803301 & 0.0016066 & 0.999197 \tabularnewline
163 & 0.00176046 & 0.00352091 & 0.99824 \tabularnewline
164 & 0.00254418 & 0.00508837 & 0.997456 \tabularnewline
165 & 0.00563079 & 0.0112616 & 0.994369 \tabularnewline
166 & 0.0107268 & 0.0214536 & 0.989273 \tabularnewline
167 & 0.0117907 & 0.0235813 & 0.988209 \tabularnewline
168 & 0.0138748 & 0.0277496 & 0.986125 \tabularnewline
169 & 0.025762 & 0.0515239 & 0.974238 \tabularnewline
170 & 0.0286705 & 0.0573411 & 0.971329 \tabularnewline
171 & 0.964078 & 0.0718431 & 0.0359215 \tabularnewline
172 & 0.986271 & 0.0274585 & 0.0137293 \tabularnewline
173 & 0.977089 & 0.0458215 & 0.0229108 \tabularnewline
174 & 0.957027 & 0.0859464 & 0.0429732 \tabularnewline
175 & 0.965781 & 0.0684389 & 0.0342194 \tabularnewline
176 & 0.952858 & 0.0942832 & 0.0471416 \tabularnewline
177 & 0.990974 & 0.0180521 & 0.00902606 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231227&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]18[/C][C]1.30916e-47[/C][C]2.61833e-47[/C][C]1[/C][/ROW]
[ROW][C]19[/C][C]7.05273e-63[/C][C]1.41055e-62[/C][C]1[/C][/ROW]
[ROW][C]20[/C][C]3.33181e-82[/C][C]6.66362e-82[/C][C]1[/C][/ROW]
[ROW][C]21[/C][C]5.54596e-106[/C][C]1.10919e-105[/C][C]1[/C][/ROW]
[ROW][C]22[/C][C]5.50761e-111[/C][C]1.10152e-110[/C][C]1[/C][/ROW]
[ROW][C]23[/C][C]1.74386e-124[/C][C]3.48772e-124[/C][C]1[/C][/ROW]
[ROW][C]24[/C][C]9.39641e-142[/C][C]1.87928e-141[/C][C]1[/C][/ROW]
[ROW][C]25[/C][C]4.10354e-158[/C][C]8.20708e-158[/C][C]1[/C][/ROW]
[ROW][C]26[/C][C]1.94283e-189[/C][C]3.88566e-189[/C][C]1[/C][/ROW]
[ROW][C]27[/C][C]1.59177e-188[/C][C]3.18355e-188[/C][C]1[/C][/ROW]
[ROW][C]28[/C][C]8.24713e-201[/C][C]1.64943e-200[/C][C]1[/C][/ROW]
[ROW][C]29[/C][C]1.79971e-219[/C][C]3.59942e-219[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]1.12989e-235[/C][C]2.25979e-235[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]1.36648e-06[/C][C]2.73297e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]32[/C][C]9.9873e-07[/C][C]1.99746e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]33[/C][C]3.16984e-07[/C][C]6.33967e-07[/C][C]1[/C][/ROW]
[ROW][C]34[/C][C]9.80748e-08[/C][C]1.9615e-07[/C][C]1[/C][/ROW]
[ROW][C]35[/C][C]3.20453e-08[/C][C]6.40906e-08[/C][C]1[/C][/ROW]
[ROW][C]36[/C][C]9.68898e-09[/C][C]1.9378e-08[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]3.88477e-07[/C][C]7.76954e-07[/C][C]1[/C][/ROW]
[ROW][C]38[/C][C]4.1741e-06[/C][C]8.3482e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]39[/C][C]0.000422347[/C][C]0.000844694[/C][C]0.999578[/C][/ROW]
[ROW][C]40[/C][C]0.00262854[/C][C]0.00525707[/C][C]0.997371[/C][/ROW]
[ROW][C]41[/C][C]0.0085338[/C][C]0.0170676[/C][C]0.991466[/C][/ROW]
[ROW][C]42[/C][C]0.00960381[/C][C]0.0192076[/C][C]0.990396[/C][/ROW]
[ROW][C]43[/C][C]0.00697765[/C][C]0.0139553[/C][C]0.993022[/C][/ROW]
[ROW][C]44[/C][C]0.00463155[/C][C]0.0092631[/C][C]0.995368[/C][/ROW]
[ROW][C]45[/C][C]0.00319579[/C][C]0.00639158[/C][C]0.996804[/C][/ROW]
[ROW][C]46[/C][C]0.00205618[/C][C]0.00411236[/C][C]0.997944[/C][/ROW]
[ROW][C]47[/C][C]0.00133105[/C][C]0.00266209[/C][C]0.998669[/C][/ROW]
[ROW][C]48[/C][C]0.000862024[/C][C]0.00172405[/C][C]0.999138[/C][/ROW]
[ROW][C]49[/C][C]0.00276312[/C][C]0.00552625[/C][C]0.997237[/C][/ROW]
[ROW][C]50[/C][C]0.0040184[/C][C]0.00803679[/C][C]0.995982[/C][/ROW]
[ROW][C]51[/C][C]0.00463818[/C][C]0.00927637[/C][C]0.995362[/C][/ROW]
[ROW][C]52[/C][C]0.00411606[/C][C]0.00823211[/C][C]0.995884[/C][/ROW]
[ROW][C]53[/C][C]0.00478244[/C][C]0.00956489[/C][C]0.995218[/C][/ROW]
[ROW][C]54[/C][C]0.00573045[/C][C]0.0114609[/C][C]0.99427[/C][/ROW]
[ROW][C]55[/C][C]0.00544706[/C][C]0.0108941[/C][C]0.994553[/C][/ROW]
[ROW][C]56[/C][C]0.00572708[/C][C]0.0114542[/C][C]0.994273[/C][/ROW]
[ROW][C]57[/C][C]0.00388508[/C][C]0.00777015[/C][C]0.996115[/C][/ROW]
[ROW][C]58[/C][C]0.00283874[/C][C]0.00567749[/C][C]0.997161[/C][/ROW]
[ROW][C]59[/C][C]0.00197334[/C][C]0.00394668[/C][C]0.998027[/C][/ROW]
[ROW][C]60[/C][C]0.00131017[/C][C]0.00262033[/C][C]0.99869[/C][/ROW]
[ROW][C]61[/C][C]0.00364014[/C][C]0.00728029[/C][C]0.99636[/C][/ROW]
[ROW][C]62[/C][C]0.00414748[/C][C]0.00829497[/C][C]0.995853[/C][/ROW]
[ROW][C]63[/C][C]0.0032981[/C][C]0.0065962[/C][C]0.996702[/C][/ROW]
[ROW][C]64[/C][C]0.00255204[/C][C]0.00510409[/C][C]0.997448[/C][/ROW]
[ROW][C]65[/C][C]0.00204549[/C][C]0.00409097[/C][C]0.997955[/C][/ROW]
[ROW][C]66[/C][C]0.00203648[/C][C]0.00407296[/C][C]0.997964[/C][/ROW]
[ROW][C]67[/C][C]0.00137198[/C][C]0.00274395[/C][C]0.998628[/C][/ROW]
[ROW][C]68[/C][C]0.000925711[/C][C]0.00185142[/C][C]0.999074[/C][/ROW]
[ROW][C]69[/C][C]0.00063081[/C][C]0.00126162[/C][C]0.999369[/C][/ROW]
[ROW][C]70[/C][C]0.000651886[/C][C]0.00130377[/C][C]0.999348[/C][/ROW]
[ROW][C]71[/C][C]0.000444413[/C][C]0.000888825[/C][C]0.999556[/C][/ROW]
[ROW][C]72[/C][C]0.000323299[/C][C]0.000646599[/C][C]0.999677[/C][/ROW]
[ROW][C]73[/C][C]0.000222282[/C][C]0.000444564[/C][C]0.999778[/C][/ROW]
[ROW][C]74[/C][C]0.000459877[/C][C]0.000919754[/C][C]0.99954[/C][/ROW]
[ROW][C]75[/C][C]0.000310322[/C][C]0.000620644[/C][C]0.99969[/C][/ROW]
[ROW][C]76[/C][C]0.000202881[/C][C]0.000405761[/C][C]0.999797[/C][/ROW]
[ROW][C]77[/C][C]0.000128929[/C][C]0.000257859[/C][C]0.999871[/C][/ROW]
[ROW][C]78[/C][C]8.10562e-05[/C][C]0.000162112[/C][C]0.999919[/C][/ROW]
[ROW][C]79[/C][C]5.11223e-05[/C][C]0.000102245[/C][C]0.999949[/C][/ROW]
[ROW][C]80[/C][C]3.90094e-05[/C][C]7.80188e-05[/C][C]0.999961[/C][/ROW]
[ROW][C]81[/C][C]2.54963e-05[/C][C]5.09925e-05[/C][C]0.999975[/C][/ROW]
[ROW][C]82[/C][C]1.67048e-05[/C][C]3.34095e-05[/C][C]0.999983[/C][/ROW]
[ROW][C]83[/C][C]1.12964e-05[/C][C]2.25928e-05[/C][C]0.999989[/C][/ROW]
[ROW][C]84[/C][C]8.26524e-06[/C][C]1.65305e-05[/C][C]0.999992[/C][/ROW]
[ROW][C]85[/C][C]5.59944e-06[/C][C]1.11989e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]86[/C][C]1.34364e-05[/C][C]2.68727e-05[/C][C]0.999987[/C][/ROW]
[ROW][C]87[/C][C]3.8012e-05[/C][C]7.60241e-05[/C][C]0.999962[/C][/ROW]
[ROW][C]88[/C][C]3.36463e-05[/C][C]6.72927e-05[/C][C]0.999966[/C][/ROW]
[ROW][C]89[/C][C]3.21661e-05[/C][C]6.43323e-05[/C][C]0.999968[/C][/ROW]
[ROW][C]90[/C][C]2.22503e-05[/C][C]4.45007e-05[/C][C]0.999978[/C][/ROW]
[ROW][C]91[/C][C]1.59445e-05[/C][C]3.18889e-05[/C][C]0.999984[/C][/ROW]
[ROW][C]92[/C][C]1.35556e-05[/C][C]2.71112e-05[/C][C]0.999986[/C][/ROW]
[ROW][C]93[/C][C]9.15462e-06[/C][C]1.83092e-05[/C][C]0.999991[/C][/ROW]
[ROW][C]94[/C][C]5.90536e-06[/C][C]1.18107e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]95[/C][C]3.70364e-06[/C][C]7.40729e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]96[/C][C]2.55381e-06[/C][C]5.10762e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]97[/C][C]1.66184e-06[/C][C]3.32368e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]98[/C][C]1.16467e-06[/C][C]2.32934e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]99[/C][C]6.64716e-07[/C][C]1.32943e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]100[/C][C]5.41756e-07[/C][C]1.08351e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]101[/C][C]3.38739e-07[/C][C]6.77479e-07[/C][C]1[/C][/ROW]
[ROW][C]102[/C][C]8.95255e-07[/C][C]1.79051e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]103[/C][C]2.27903e-06[/C][C]4.55807e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]104[/C][C]1.95217e-06[/C][C]3.90433e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]105[/C][C]1.58925e-06[/C][C]3.17849e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]106[/C][C]1.56246e-06[/C][C]3.12492e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]107[/C][C]1.54685e-06[/C][C]3.09369e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]108[/C][C]1.3449e-06[/C][C]2.6898e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]109[/C][C]9.66697e-07[/C][C]1.93339e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]110[/C][C]7.89786e-07[/C][C]1.57957e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]111[/C][C]6.185e-07[/C][C]1.237e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]112[/C][C]1.15961e-06[/C][C]2.31922e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]113[/C][C]1.4748e-06[/C][C]2.94959e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]114[/C][C]5.33094e-06[/C][C]1.06619e-05[/C][C]0.999995[/C][/ROW]
[ROW][C]115[/C][C]4.43015e-06[/C][C]8.8603e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]116[/C][C]5.55502e-06[/C][C]1.111e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]117[/C][C]5.03736e-06[/C][C]1.00747e-05[/C][C]0.999995[/C][/ROW]
[ROW][C]118[/C][C]4.277e-06[/C][C]8.554e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]119[/C][C]1.23286e-05[/C][C]2.46572e-05[/C][C]0.999988[/C][/ROW]
[ROW][C]120[/C][C]7.39156e-05[/C][C]0.000147831[/C][C]0.999926[/C][/ROW]
[ROW][C]121[/C][C]0.000141677[/C][C]0.000283354[/C][C]0.999858[/C][/ROW]
[ROW][C]122[/C][C]0.000269931[/C][C]0.000539863[/C][C]0.99973[/C][/ROW]
[ROW][C]123[/C][C]0.000185111[/C][C]0.000370223[/C][C]0.999815[/C][/ROW]
[ROW][C]124[/C][C]0.000155862[/C][C]0.000311724[/C][C]0.999844[/C][/ROW]
[ROW][C]125[/C][C]0.000164121[/C][C]0.000328242[/C][C]0.999836[/C][/ROW]
[ROW][C]126[/C][C]0.000243404[/C][C]0.000486807[/C][C]0.999757[/C][/ROW]
[ROW][C]127[/C][C]0.000333626[/C][C]0.000667253[/C][C]0.999666[/C][/ROW]
[ROW][C]128[/C][C]0.000474612[/C][C]0.000949224[/C][C]0.999525[/C][/ROW]
[ROW][C]129[/C][C]0.000379497[/C][C]0.000758995[/C][C]0.999621[/C][/ROW]
[ROW][C]130[/C][C]0.000414971[/C][C]0.000829942[/C][C]0.999585[/C][/ROW]
[ROW][C]131[/C][C]0.00065694[/C][C]0.00131388[/C][C]0.999343[/C][/ROW]
[ROW][C]132[/C][C]0.000545208[/C][C]0.00109042[/C][C]0.999455[/C][/ROW]
[ROW][C]133[/C][C]0.000784811[/C][C]0.00156962[/C][C]0.999215[/C][/ROW]
[ROW][C]134[/C][C]0.00131938[/C][C]0.00263876[/C][C]0.998681[/C][/ROW]
[ROW][C]135[/C][C]0.000934262[/C][C]0.00186852[/C][C]0.999066[/C][/ROW]
[ROW][C]136[/C][C]0.000627914[/C][C]0.00125583[/C][C]0.999372[/C][/ROW]
[ROW][C]137[/C][C]0.000439687[/C][C]0.000879375[/C][C]0.99956[/C][/ROW]
[ROW][C]138[/C][C]0.000305856[/C][C]0.000611713[/C][C]0.999694[/C][/ROW]
[ROW][C]139[/C][C]0.000197324[/C][C]0.000394649[/C][C]0.999803[/C][/ROW]
[ROW][C]140[/C][C]0.000125556[/C][C]0.000251112[/C][C]0.999874[/C][/ROW]
[ROW][C]141[/C][C]0.000122749[/C][C]0.000245497[/C][C]0.999877[/C][/ROW]
[ROW][C]142[/C][C]9.16219e-05[/C][C]0.000183244[/C][C]0.999908[/C][/ROW]
[ROW][C]143[/C][C]9.2951e-05[/C][C]0.000185902[/C][C]0.999907[/C][/ROW]
[ROW][C]144[/C][C]0.000476137[/C][C]0.000952275[/C][C]0.999524[/C][/ROW]
[ROW][C]145[/C][C]0.00141295[/C][C]0.0028259[/C][C]0.998587[/C][/ROW]
[ROW][C]146[/C][C]0.00521735[/C][C]0.0104347[/C][C]0.994783[/C][/ROW]
[ROW][C]147[/C][C]0.00385848[/C][C]0.00771695[/C][C]0.996142[/C][/ROW]
[ROW][C]148[/C][C]0.00305842[/C][C]0.00611683[/C][C]0.996942[/C][/ROW]
[ROW][C]149[/C][C]0.00291962[/C][C]0.00583924[/C][C]0.99708[/C][/ROW]
[ROW][C]150[/C][C]0.00213124[/C][C]0.00426249[/C][C]0.997869[/C][/ROW]
[ROW][C]151[/C][C]0.00153727[/C][C]0.00307454[/C][C]0.998463[/C][/ROW]
[ROW][C]152[/C][C]0.00746169[/C][C]0.0149234[/C][C]0.992538[/C][/ROW]
[ROW][C]153[/C][C]0.00529206[/C][C]0.0105841[/C][C]0.994708[/C][/ROW]
[ROW][C]154[/C][C]0.00353292[/C][C]0.00706584[/C][C]0.996467[/C][/ROW]
[ROW][C]155[/C][C]0.00266209[/C][C]0.00532419[/C][C]0.997338[/C][/ROW]
[ROW][C]156[/C][C]0.00179073[/C][C]0.00358146[/C][C]0.998209[/C][/ROW]
[ROW][C]157[/C][C]0.00268487[/C][C]0.00536974[/C][C]0.997315[/C][/ROW]
[ROW][C]158[/C][C]0.00192604[/C][C]0.00385209[/C][C]0.998074[/C][/ROW]
[ROW][C]159[/C][C]0.00124177[/C][C]0.00248353[/C][C]0.998758[/C][/ROW]
[ROW][C]160[/C][C]0.00105472[/C][C]0.00210943[/C][C]0.998945[/C][/ROW]
[ROW][C]161[/C][C]0.00118596[/C][C]0.00237191[/C][C]0.998814[/C][/ROW]
[ROW][C]162[/C][C]0.000803301[/C][C]0.0016066[/C][C]0.999197[/C][/ROW]
[ROW][C]163[/C][C]0.00176046[/C][C]0.00352091[/C][C]0.99824[/C][/ROW]
[ROW][C]164[/C][C]0.00254418[/C][C]0.00508837[/C][C]0.997456[/C][/ROW]
[ROW][C]165[/C][C]0.00563079[/C][C]0.0112616[/C][C]0.994369[/C][/ROW]
[ROW][C]166[/C][C]0.0107268[/C][C]0.0214536[/C][C]0.989273[/C][/ROW]
[ROW][C]167[/C][C]0.0117907[/C][C]0.0235813[/C][C]0.988209[/C][/ROW]
[ROW][C]168[/C][C]0.0138748[/C][C]0.0277496[/C][C]0.986125[/C][/ROW]
[ROW][C]169[/C][C]0.025762[/C][C]0.0515239[/C][C]0.974238[/C][/ROW]
[ROW][C]170[/C][C]0.0286705[/C][C]0.0573411[/C][C]0.971329[/C][/ROW]
[ROW][C]171[/C][C]0.964078[/C][C]0.0718431[/C][C]0.0359215[/C][/ROW]
[ROW][C]172[/C][C]0.986271[/C][C]0.0274585[/C][C]0.0137293[/C][/ROW]
[ROW][C]173[/C][C]0.977089[/C][C]0.0458215[/C][C]0.0229108[/C][/ROW]
[ROW][C]174[/C][C]0.957027[/C][C]0.0859464[/C][C]0.0429732[/C][/ROW]
[ROW][C]175[/C][C]0.965781[/C][C]0.0684389[/C][C]0.0342194[/C][/ROW]
[ROW][C]176[/C][C]0.952858[/C][C]0.0942832[/C][C]0.0471416[/C][/ROW]
[ROW][C]177[/C][C]0.990974[/C][C]0.0180521[/C][C]0.00902606[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231227&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231227&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
181.30916e-472.61833e-471
197.05273e-631.41055e-621
203.33181e-826.66362e-821
215.54596e-1061.10919e-1051
225.50761e-1111.10152e-1101
231.74386e-1243.48772e-1241
249.39641e-1421.87928e-1411
254.10354e-1588.20708e-1581
261.94283e-1893.88566e-1891
271.59177e-1883.18355e-1881
288.24713e-2011.64943e-2001
291.79971e-2193.59942e-2191
301.12989e-2352.25979e-2351
311.36648e-062.73297e-060.999999
329.9873e-071.99746e-060.999999
333.16984e-076.33967e-071
349.80748e-081.9615e-071
353.20453e-086.40906e-081
369.68898e-091.9378e-081
373.88477e-077.76954e-071
384.1741e-068.3482e-060.999996
390.0004223470.0008446940.999578
400.002628540.005257070.997371
410.00853380.01706760.991466
420.009603810.01920760.990396
430.006977650.01395530.993022
440.004631550.00926310.995368
450.003195790.006391580.996804
460.002056180.004112360.997944
470.001331050.002662090.998669
480.0008620240.001724050.999138
490.002763120.005526250.997237
500.00401840.008036790.995982
510.004638180.009276370.995362
520.004116060.008232110.995884
530.004782440.009564890.995218
540.005730450.01146090.99427
550.005447060.01089410.994553
560.005727080.01145420.994273
570.003885080.007770150.996115
580.002838740.005677490.997161
590.001973340.003946680.998027
600.001310170.002620330.99869
610.003640140.007280290.99636
620.004147480.008294970.995853
630.00329810.00659620.996702
640.002552040.005104090.997448
650.002045490.004090970.997955
660.002036480.004072960.997964
670.001371980.002743950.998628
680.0009257110.001851420.999074
690.000630810.001261620.999369
700.0006518860.001303770.999348
710.0004444130.0008888250.999556
720.0003232990.0006465990.999677
730.0002222820.0004445640.999778
740.0004598770.0009197540.99954
750.0003103220.0006206440.99969
760.0002028810.0004057610.999797
770.0001289290.0002578590.999871
788.10562e-050.0001621120.999919
795.11223e-050.0001022450.999949
803.90094e-057.80188e-050.999961
812.54963e-055.09925e-050.999975
821.67048e-053.34095e-050.999983
831.12964e-052.25928e-050.999989
848.26524e-061.65305e-050.999992
855.59944e-061.11989e-050.999994
861.34364e-052.68727e-050.999987
873.8012e-057.60241e-050.999962
883.36463e-056.72927e-050.999966
893.21661e-056.43323e-050.999968
902.22503e-054.45007e-050.999978
911.59445e-053.18889e-050.999984
921.35556e-052.71112e-050.999986
939.15462e-061.83092e-050.999991
945.90536e-061.18107e-050.999994
953.70364e-067.40729e-060.999996
962.55381e-065.10762e-060.999997
971.66184e-063.32368e-060.999998
981.16467e-062.32934e-060.999999
996.64716e-071.32943e-060.999999
1005.41756e-071.08351e-060.999999
1013.38739e-076.77479e-071
1028.95255e-071.79051e-060.999999
1032.27903e-064.55807e-060.999998
1041.95217e-063.90433e-060.999998
1051.58925e-063.17849e-060.999998
1061.56246e-063.12492e-060.999998
1071.54685e-063.09369e-060.999998
1081.3449e-062.6898e-060.999999
1099.66697e-071.93339e-060.999999
1107.89786e-071.57957e-060.999999
1116.185e-071.237e-060.999999
1121.15961e-062.31922e-060.999999
1131.4748e-062.94959e-060.999999
1145.33094e-061.06619e-050.999995
1154.43015e-068.8603e-060.999996
1165.55502e-061.111e-050.999994
1175.03736e-061.00747e-050.999995
1184.277e-068.554e-060.999996
1191.23286e-052.46572e-050.999988
1207.39156e-050.0001478310.999926
1210.0001416770.0002833540.999858
1220.0002699310.0005398630.99973
1230.0001851110.0003702230.999815
1240.0001558620.0003117240.999844
1250.0001641210.0003282420.999836
1260.0002434040.0004868070.999757
1270.0003336260.0006672530.999666
1280.0004746120.0009492240.999525
1290.0003794970.0007589950.999621
1300.0004149710.0008299420.999585
1310.000656940.001313880.999343
1320.0005452080.001090420.999455
1330.0007848110.001569620.999215
1340.001319380.002638760.998681
1350.0009342620.001868520.999066
1360.0006279140.001255830.999372
1370.0004396870.0008793750.99956
1380.0003058560.0006117130.999694
1390.0001973240.0003946490.999803
1400.0001255560.0002511120.999874
1410.0001227490.0002454970.999877
1429.16219e-050.0001832440.999908
1439.2951e-050.0001859020.999907
1440.0004761370.0009522750.999524
1450.001412950.00282590.998587
1460.005217350.01043470.994783
1470.003858480.007716950.996142
1480.003058420.006116830.996942
1490.002919620.005839240.99708
1500.002131240.004262490.997869
1510.001537270.003074540.998463
1520.007461690.01492340.992538
1530.005292060.01058410.994708
1540.003532920.007065840.996467
1550.002662090.005324190.997338
1560.001790730.003581460.998209
1570.002684870.005369740.997315
1580.001926040.003852090.998074
1590.001241770.002483530.998758
1600.001054720.002109430.998945
1610.001185960.002371910.998814
1620.0008033010.00160660.999197
1630.001760460.003520910.99824
1640.002544180.005088370.997456
1650.005630790.01126160.994369
1660.01072680.02145360.989273
1670.01179070.02358130.988209
1680.01387480.02774960.986125
1690.0257620.05152390.974238
1700.02867050.05734110.971329
1710.9640780.07184310.0359215
1720.9862710.02745850.0137293
1730.9770890.04582150.0229108
1740.9570270.08594640.0429732
1750.9657810.06843890.0342194
1760.9528580.09428320.0471416
1770.9909740.01805210.00902606






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1380.8625NOK
5% type I error level1540.9625NOK
10% type I error level1601NOK

\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 & 138 & 0.8625 & NOK \tabularnewline
5% type I error level & 154 & 0.9625 & NOK \tabularnewline
10% type I error level & 160 & 1 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231227&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]138[/C][C]0.8625[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]154[/C][C]0.9625[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]160[/C][C]1[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231227&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231227&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 level1380.8625NOK
5% type I error level1540.9625NOK
10% type I error level1601NOK


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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}