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Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 02 Dec 2013 14:12:11 -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/02/t13860115724vvdhvbjazz5rfo.htm/, Retrieved Thu, 28 Mar 2024 13:12:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230071, Retrieved Thu, 28 Mar 2024 13:12:06 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2013-12-02 19:12:11] [fa37975af643c4e4fccca077f5456344] [Current]
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Dataseries X:
119.992 157.302 0.00784 0.00007 0.00554 0.02971
122.4 148.65 0.00968 0.00008 0.00696 0.04368
116.682 131.111 0.0105 0.00009 0.00781 0.0359
116.676 137.871 0.00997 0.00009 0.00698 0.03772
116.014 141.781 0.01284 0.00011 0.00908 0.04465
120.552 131.162 0.00968 0.00008 0.0075 0.03243
120.267 137.244 0.00333 0.00003 0.00202 0.01351
107.332 113.84 0.0029 0.00003 0.00182 0.01256
95.73 132.068 0.00551 0.00006 0.00332 0.01717
95.056 120.103 0.00532 0.00006 0.00332 0.02444
88.333 112.24 0.00505 0.00006 0.0033 0.01892
91.904 115.871 0.0054 0.00006 0.00336 0.02214
136.926 159.866 0.00293 0.00002 0.00153 0.0114
139.173 179.139 0.0039 0.00003 0.00208 0.01797
152.845 163.305 0.00294 0.00002 0.00149 0.01246
142.167 217.455 0.00369 0.00003 0.00203 0.01359
144.188 349.259 0.00544 0.00004 0.00292 0.02074
168.778 232.181 0.00718 0.00004 0.00387 0.0343
153.046 175.829 0.00742 0.00005 0.00432 0.05767
156.405 189.398 0.00768 0.00005 0.00399 0.0431
153.848 165.738 0.0084 0.00005 0.0045 0.04055
153.88 172.86 0.0048 0.00003 0.00267 0.04525
167.93 193.221 0.00442 0.00003 0.00247 0.04246
173.917 192.735 0.00476 0.00003 0.00258 0.03772
163.656 200.841 0.00742 0.00005 0.0039 0.01497
104.4 206.002 0.00633 0.00006 0.00375 0.0378
171.041 208.313 0.00455 0.00003 0.00234 0.01872
146.845 208.701 0.00496 0.00003 0.00275 0.01826
155.358 227.383 0.0031 0.00002 0.00176 0.01661
162.568 198.346 0.00502 0.00003 0.00253 0.01799
197.076 206.896 0.00289 0.00001 0.00168 0.00802
199.228 209.512 0.00241 0.00001 0.00138 0.00762
198.383 215.203 0.00212 0.00001 0.00135 0.00951
202.266 211.604 0.0018 0.000009 0.00107 0.00719
203.184 211.526 0.00178 0.000009 0.00106 0.00726
201.464 210.565 0.00198 0.00001 0.00115 0.00957
177.876 192.921 0.00411 0.00002 0.00241 0.01612
176.17 185.604 0.00369 0.00002 0.00218 0.01491
180.198 201.249 0.00284 0.00002 0.00166 0.0119
187.733 202.324 0.00316 0.00002 0.00182 0.01366
186.163 197.724 0.00298 0.00002 0.00175 0.01233
184.055 196.537 0.00258 0.00001 0.00147 0.01234
237.226 247.326 0.00298 0.00001 0.00182 0.01133
241.404 248.834 0.00281 0.00001 0.00173 0.01251
243.439 250.912 0.0021 0.000009 0.00137 0.01033
242.852 255.034 0.00225 0.000009 0.00139 0.01014
245.51 262.09 0.00235 0.00001 0.00148 0.01149
252.455 261.487 0.00185 0.000007 0.00113 0.0086
122.188 128.611 0.00524 0.00004 0.00203 0.01433
122.964 130.049 0.00428 0.00003 0.00155 0.014
124.445 135.069 0.00431 0.00003 0.00167 0.01685
126.344 134.231 0.00448 0.00004 0.00169 0.01614
128.001 138.052 0.00436 0.00003 0.00166 0.01677
129.336 139.867 0.0049 0.00004 0.00183 0.01947
108.807 134.656 0.00761 0.00007 0.00486 0.02067
109.86 126.358 0.00874 0.00008 0.00539 0.02454
110.417 131.067 0.00784 0.00007 0.00514 0.02802
117.274 129.916 0.00752 0.00006 0.00469 0.01948
116.879 131.897 0.00788 0.00007 0.00493 0.02137
114.847 271.314 0.00867 0.00008 0.0052 0.02519
209.144 237.494 0.00282 0.00001 0.00152 0.01382
223.365 238.987 0.00264 0.00001 0.00151 0.0134
222.236 231.345 0.00266 0.00001 0.00144 0.012
228.832 234.619 0.00296 0.00001 0.00155 0.01179
229.401 252.221 0.00205 0.000009 0.00113 0.01016
228.969 239.541 0.00238 0.00001 0.0014 0.01234
140.341 159.774 0.00817 0.00006 0.0044 0.02428
136.969 166.607 0.00923 0.00007 0.00463 0.02603
143.533 162.215 0.01101 0.00008 0.00467 0.03392
148.09 162.824 0.00762 0.00005 0.00354 0.03635
142.729 162.408 0.00831 0.00006 0.00419 0.02949
136.358 176.595 0.00971 0.00007 0.00478 0.03736
120.08 139.71 0.00405 0.00003 0.0022 0.01345
112.014 588.518 0.00533 0.00005 0.00329 0.01956
110.793 128.101 0.00494 0.00004 0.00283 0.01831
110.707 122.611 0.00516 0.00005 0.00289 0.01715
112.876 148.826 0.005 0.00004 0.00289 0.02704
110.568 125.394 0.00462 0.00004 0.0028 0.01636
95.385 102.145 0.00608 0.00006 0.00332 0.02455
100.77 115.697 0.01038 0.0001 0.00576 0.02139
96.106 108.664 0.00694 0.00007 0.00415 0.02876
95.605 107.715 0.00702 0.00007 0.00371 0.0219
100.96 110.019 0.00606 0.00006 0.00348 0.01751
98.804 102.305 0.00432 0.00004 0.00258 0.01552
176.858 205.56 0.00747 0.00004 0.0042 0.0351
180.978 200.125 0.00406 0.00002 0.00244 0.02877
178.222 202.45 0.00321 0.00002 0.00194 0.02784
176.281 227.381 0.0052 0.00003 0.00312 0.04683
173.898 211.35 0.00448 0.00003 0.00254 0.04802
179.711 225.93 0.00709 0.00004 0.00419 0.03455
166.605 206.008 0.00742 0.00004 0.00453 0.05114
151.955 163.335 0.00419 0.00003 0.00227 0.0569
148.272 164.989 0.00459 0.00003 0.00256 0.03051
152.125 161.469 0.00382 0.00003 0.00226 0.04398
157.821 172.975 0.00358 0.00002 0.00196 0.02764
157.447 163.267 0.00369 0.00002 0.00197 0.02571
159.116 168.913 0.00342 0.00002 0.00184 0.02809
125.036 143.946 0.0128 0.0001 0.00623 0.03088
125.791 140.557 0.01378 0.00011 0.00655 0.03908
126.512 141.756 0.01936 0.00015 0.0099 0.05783
125.641 141.068 0.03316 0.00026 0.01522 0.06196
128.451 150.449 0.01551 0.00012 0.00909 0.05174
139.224 586.567 0.03011 0.00022 0.01628 0.06023
150.258 154.609 0.00248 0.00002 0.00136 0.01009
154.003 160.267 0.00183 0.00001 0.001 0.00871
149.689 160.368 0.00257 0.00002 0.00134 0.01059
155.078 163.736 0.00168 0.00001 0.00092 0.00928
151.884 157.765 0.00258 0.00002 0.00122 0.01267
151.989 157.339 0.00174 0.00001 0.00096 0.00993
193.03 208.9 0.00766 0.00004 0.00389 0.02084
200.714 223.982 0.00621 0.00003 0.00337 0.01852
208.519 220.315 0.00609 0.00003 0.00339 0.01307
204.664 221.3 0.00841 0.00004 0.00485 0.01767
210.141 232.706 0.00534 0.00003 0.0028 0.01301
206.327 226.355 0.00495 0.00002 0.00246 0.01604
151.872 492.892 0.00856 0.00006 0.00385 0.01271
158.219 442.557 0.00476 0.00003 0.00207 0.01312
170.756 450.247 0.00555 0.00003 0.00261 0.01652
178.285 442.824 0.00462 0.00003 0.00194 0.01151
217.116 233.481 0.00404 0.00002 0.00128 0.01075
128.94 479.697 0.00581 0.00005 0.00314 0.01734
176.824 215.293 0.0046 0.00003 0.00221 0.01104
138.19 203.522 0.00704 0.00005 0.00398 0.0322
182.018 197.173 0.00842 0.00005 0.00449 0.01931
156.239 195.107 0.00694 0.00004 0.00395 0.0172
145.174 198.109 0.00733 0.00005 0.00422 0.01944
138.145 197.238 0.00544 0.00004 0.00327 0.02259
166.888 198.966 0.00638 0.00004 0.00351 0.02301
119.031 127.533 0.0044 0.00004 0.00192 0.00811
120.078 126.632 0.0027 0.00002 0.00135 0.00903
120.289 128.143 0.00492 0.00004 0.00238 0.01194
120.256 125.306 0.00407 0.00003 0.00205 0.0131
119.056 125.213 0.00346 0.00003 0.0017 0.00915
118.747 123.723 0.00331 0.00003 0.00171 0.00903
106.516 112.777 0.00589 0.00006 0.00319 0.03651
110.453 127.611 0.00494 0.00004 0.00315 0.03316
113.4 133.344 0.00451 0.00004 0.00283 0.0437
113.166 130.27 0.00502 0.00004 0.00312 0.04134
112.239 126.609 0.00472 0.00004 0.0029 0.04451
116.15 131.731 0.00381 0.00003 0.00232 0.0277
170.368 268.796 0.00571 0.00003 0.00269 0.02824
208.083 253.792 0.00757 0.00004 0.00428 0.04464
198.458 219.29 0.00376 0.00002 0.00215 0.0253
202.805 231.508 0.0037 0.00002 0.00211 0.01506
202.544 241.35 0.00254 0.00001 0.00133 0.02006
223.361 263.872 0.00352 0.00002 0.00188 0.01909
169.774 191.759 0.01568 0.00009 0.00946 0.08808
183.52 216.814 0.01466 0.00008 0.00819 0.06359
188.62 216.302 0.01719 0.00009 0.01027 0.06824
202.632 565.74 0.01627 0.00008 0.00963 0.0646
186.695 211.961 0.01872 0.0001 0.01154 0.06259
192.818 224.429 0.03107 0.00016 0.01958 0.13778
198.116 233.099 0.02714 0.00014 0.01699 0.08318
121.345 139.644 0.00684 0.00006 0.00332 0.02056
119.1 128.442 0.00692 0.00006 0.003 0.02018
117.87 127.349 0.00647 0.00005 0.003 0.02402
122.336 142.369 0.00727 0.00006 0.00339 0.01771
117.963 134.209 0.01813 0.00015 0.00718 0.02916
126.144 154.284 0.00975 0.00008 0.00454 0.02157
127.93 138.752 0.00605 0.00005 0.00318 0.03105
114.238 124.393 0.00581 0.00005 0.00316 0.04114
115.322 135.738 0.00619 0.00005 0.00329 0.02931
114.554 126.778 0.00651 0.00006 0.0034 0.03091
112.15 131.669 0.00519 0.00005 0.00284 0.01363
102.273 142.83 0.00907 0.00009 0.00461 0.02073
236.2 244.663 0.00277 0.00001 0.00153 0.01621
237.323 243.709 0.00303 0.00001 0.00159 0.00882
260.105 264.919 0.00339 0.00001 0.00186 0.01367
197.569 217.627 0.00803 0.00004 0.00448 0.01439
240.301 245.135 0.00517 0.00002 0.00283 0.01344
244.99 272.21 0.00451 0.00002 0.00237 0.01255
112.547 133.374 0.00355 0.00003 0.0019 0.0114
110.739 113.597 0.00356 0.00003 0.002 0.01285
113.715 116.443 0.00349 0.00003 0.00203 0.01148
117.004 144.466 0.00353 0.00003 0.00218 0.01318
115.38 123.109 0.00332 0.00003 0.00199 0.01133
116.388 129.038 0.00346 0.00003 0.00213 0.01331
151.737 190.204 0.00314 0.00002 0.00162 0.0123
148.79 158.359 0.00309 0.00002 0.00186 0.01309
148.143 155.982 0.00392 0.00003 0.00231 0.01263
150.44 163.441 0.00396 0.00003 0.00233 0.02148
148.462 161.078 0.00397 0.00003 0.00235 0.01559
149.818 163.417 0.00336 0.00002 0.00198 0.01666
117.226 123.925 0.00417 0.00004 0.0027 0.01949
116.848 217.552 0.00531 0.00005 0.00346 0.01756
116.286 177.291 0.00314 0.00003 0.00192 0.01691
116.556 592.03 0.00496 0.00004 0.00263 0.01491
116.342 581.289 0.00267 0.00002 0.00148 0.01144
114.563 119.167 0.00327 0.00003 0.00184 0.01095
201.774 262.707 0.00694 0.00003 0.00396 0.01758
174.188 230.978 0.00459 0.00003 0.00259 0.02745
209.516 253.017 0.00564 0.00003 0.00292 0.01879
174.688 240.005 0.0136 0.00008 0.00564 0.01667
198.764 396.961 0.0074 0.00004 0.0039 0.01588
214.289 260.277 0.00567 0.00003 0.00317 0.01373
 




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'George Udny Yule' @ yule.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 & 16 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230071&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]16 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230071&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230071&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time16 seconds
R Server'George Udny Yule' @ yule.wessa.net







Multiple Linear Regression - Estimated Regression Equation
MDVP:Fo(Hz)[t] = + 160.228 + 0.0549271`MDVP:Fhi(Hz)`[t] + 19835.2`MDVP:Jitter(%)`[t] -2613680`MDVP:Jitter(Abs)`[t] -3404.11`MDVP:PPQ`[t] -564.084`MDVP:APQ`[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
MDVP:Fo(Hz)[t] =  +  160.228 +  0.0549271`MDVP:Fhi(Hz)`[t] +  19835.2`MDVP:Jitter(%)`[t] -2613680`MDVP:Jitter(Abs)`[t] -3404.11`MDVP:PPQ`[t] -564.084`MDVP:APQ`[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230071&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]MDVP:Fo(Hz)[t] =  +  160.228 +  0.0549271`MDVP:Fhi(Hz)`[t] +  19835.2`MDVP:Jitter(%)`[t] -2613680`MDVP:Jitter(Abs)`[t] -3404.11`MDVP:PPQ`[t] -564.084`MDVP:APQ`[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230071&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230071&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
MDVP:Fo(Hz)[t] = + 160.228 + 0.0549271`MDVP:Fhi(Hz)`[t] + 19835.2`MDVP:Jitter(%)`[t] -2613680`MDVP:Jitter(Abs)`[t] -3404.11`MDVP:PPQ`[t] -564.084`MDVP:APQ`[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)160.2285.4245829.549.61157e-734.80578e-73
`MDVP:Fhi(Hz)`0.05492710.02125892.5840.01052890.00526444
`MDVP:Jitter(%)`19835.22130.229.3113.26379e-171.63189e-17
`MDVP:Jitter(Abs)`-2613680162618-16.073.32833e-371.66416e-37
`MDVP:PPQ`-3404.113168.08-1.0750.2839670.141983
`MDVP:APQ`-564.084185.928-3.0340.002753910.00137696

\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) & 160.228 & 5.42458 & 29.54 & 9.61157e-73 & 4.80578e-73 \tabularnewline
`MDVP:Fhi(Hz)` & 0.0549271 & 0.0212589 & 2.584 & 0.0105289 & 0.00526444 \tabularnewline
`MDVP:Jitter(%)` & 19835.2 & 2130.22 & 9.311 & 3.26379e-17 & 1.63189e-17 \tabularnewline
`MDVP:Jitter(Abs)` & -2613680 & 162618 & -16.07 & 3.32833e-37 & 1.66416e-37 \tabularnewline
`MDVP:PPQ` & -3404.11 & 3168.08 & -1.075 & 0.283967 & 0.141983 \tabularnewline
`MDVP:APQ` & -564.084 & 185.928 & -3.034 & 0.00275391 & 0.00137696 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230071&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]160.228[/C][C]5.42458[/C][C]29.54[/C][C]9.61157e-73[/C][C]4.80578e-73[/C][/ROW]
[ROW][C]`MDVP:Fhi(Hz)`[/C][C]0.0549271[/C][C]0.0212589[/C][C]2.584[/C][C]0.0105289[/C][C]0.00526444[/C][/ROW]
[ROW][C]`MDVP:Jitter(%)`[/C][C]19835.2[/C][C]2130.22[/C][C]9.311[/C][C]3.26379e-17[/C][C]1.63189e-17[/C][/ROW]
[ROW][C]`MDVP:Jitter(Abs)`[/C][C]-2613680[/C][C]162618[/C][C]-16.07[/C][C]3.32833e-37[/C][C]1.66416e-37[/C][/ROW]
[ROW][C]`MDVP:PPQ`[/C][C]-3404.11[/C][C]3168.08[/C][C]-1.075[/C][C]0.283967[/C][C]0.141983[/C][/ROW]
[ROW][C]`MDVP:APQ`[/C][C]-564.084[/C][C]185.928[/C][C]-3.034[/C][C]0.00275391[/C][C]0.00137696[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230071&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230071&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)160.2285.4245829.549.61157e-734.80578e-73
`MDVP:Fhi(Hz)`0.05492710.02125892.5840.01052890.00526444
`MDVP:Jitter(%)`19835.22130.229.3113.26379e-171.63189e-17
`MDVP:Jitter(Abs)`-2613680162618-16.073.32833e-371.66416e-37
`MDVP:PPQ`-3404.113168.08-1.0750.2839670.141983
`MDVP:APQ`-564.084185.928-3.0340.002753910.00137696







Multiple Linear Regression - Regression Statistics
Multiple R0.811161
R-squared0.657983
Adjusted R-squared0.648935
F-TEST (value)72.7208
F-TEST (DF numerator)5
F-TEST (DF denominator)189
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation24.5239
Sum Squared Residuals113669

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.811161 \tabularnewline
R-squared & 0.657983 \tabularnewline
Adjusted R-squared & 0.648935 \tabularnewline
F-TEST (value) & 72.7208 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 189 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 24.5239 \tabularnewline
Sum Squared Residuals & 113669 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230071&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.811161[/C][/ROW]
[ROW][C]R-squared[/C][C]0.657983[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.648935[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]72.7208[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]189[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]24.5239[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]113669[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230071&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230071&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.811161
R-squared0.657983
Adjusted R-squared0.648935
F-TEST (value)72.7208
F-TEST (DF numerator)5
F-TEST (DF denominator)189
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation24.5239
Sum Squared Residuals113669







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1119.992105.80114.1906
2122.4102.97219.4279
3116.68293.631923.0501
4116.67685.289331.3867
5116.01479.099836.9142
6120.552106.51914.0327
7120.267140.911-20.6437
8107.332132.313-24.9807
995.7398.9668-3.23684
1095.05690.44014.61594
1188.33387.83450.498523
1291.90492.9557-1.05165
13136.926163.214-26.2882
14139.173151.798-12.6249
15152.845163.14-10.2947
16142.167152.378-10.2109
17144.188161.13-16.9415
18168.778178.329-9.55122
19153.046139.14313.9029
20156.405154.3882.01736
21153.848167.072-13.2238
22153.88151.9081.97194
23167.93147.74420.1863
24173.917156.7617.1568
25163.656166.033-2.37706
26104.4106.192-1.7919
27171.041164.9856.05592
28146.845172.003-25.1576
29155.358166.573-11.2149
30162.568173.525-10.9572
31197.076192.5374.53919
32199.228184.40614.8216
33198.383178.00320.3802
34202.266176.33325.9326
35203.184175.92727.2571
36201.464175.61825.8459
37177.876182.777-4.90129
38176.17175.510.659924
39180.198162.97717.2205
40187.733167.84619.8866
41186.163165.01221.1511
42184.055184.097-0.0419146
43237.226194.19943.027
44241.404190.55150.8534
45243.439181.65161.7884
46242.852184.89157.9606
47245.51183.58161.9291
48252.455184.29368.1622
49122.188151.688-29.5004
50122.964160.682-37.7185
51124.445159.537-35.0921
52126.344137.059-10.7147
53128.001160.772-32.7709
54129.336143.344-14.0081
55108.807107.411.39745
56109.8699.243610.6164
57110.417106.6753.74165
58117.274132.751-15.4768
59116.879111.984.89863
60114.847106.0978.74975
61209.144190.10219.042
62223.365186.88536.4804
63222.236187.8934.3465
64228.832193.76435.068
65229.401181.64447.7574
66228.969182.7346.2388
67140.341145.563-5.2223
68136.969139.057-2.08806
69143.533143.3990.134059
70148.09157.077-8.98731
71142.729146.261-3.5319
72136.358142.225-5.8669
73120.08154.749-34.6686
74112.014145.359-33.3447
75110.793140.741-29.9485
76110.707119.117-8.40993
77112.876137.941-25.0652
78110.568135.448-24.8796
7995.385104.466-9.08141
80100.7779.431521.3385
8196.10690.54585.56024
8295.60597.4479-1.84288
83100.96107.929-6.96869
8498.804129.452-30.6475
85176.858181.045-4.1866
86180.978174.9436.03456
87178.222160.43817.7842
88176.281160.41415.8673
89173.898146.55527.3431
90179.711174.974.74064
91166.605169.906-3.30118
92151.955134.07517.8795
93148.272155.999-7.72738
94152.125133.95618.1691
95157.821166.203-8.38164
96157.447168.906-11.4589
97159.116162.961-3.84455
98125.036122.0313.00468
99125.791109.43216.3589
100126.51293.650932.8611
101125.64159.394966.2461
102128.451102.36626.0852
103139.224125.28213.9419
104150.258155.317-5.05923
105154.003170.876-16.8728
106149.689157.205-7.51577
107155.078168.042-12.9639
108151.884156.495-4.61135
109151.989168.378-16.3888
110193.03194.096-1.06586
111200.714195.3795.33519
112208.519195.80312.7157
113204.664208.174-3.50958
114210.141183.6526.4912
115206.327201.155.17676
116151.872179.995-28.123
117158.219186.095-27.8758
118170.756198.431-27.6749
119178.285184.683-6.39824
120217.116190.49226.6236
121128.94150.665-21.7253
122176.824171.1355.68906
123138.19148.651-10.4614
124182.018181.210.807725
125156.239180.906-24.6669
126145.174160.487-15.3131
127138.145150.544-12.3995
128166.888168.231-1.34261
129119.031138.851-19.8196
130120.078158.776-38.6983
131120.289145.472-25.1831
132120.256155.062-34.8062
133119.056146.377-27.3212
134118.747143.354-24.6067
135106.51694.977811.5382
136110.453131.249-20.7956
137113.4118.178-4.7782
138113.166128.469-15.3034
139112.239121.278-9.03947
140116.15141.103-24.9532
141170.368184.755-14.3866
142208.083180.02428.0593
143198.458172.9925.4679
144202.805178.38324.4215
145202.544181.88720.6572
146223.361175.148.2605
147169.774164.6595.11505
148183.52190.078-6.55767
149188.62204.392-15.7723
150202.632235.706-33.0742
151186.695207.229-20.5338
152192.818226.275-33.4574
153198.116240.688-42.5724
154121.345123.852-2.50659
155119.1126.127-7.02679
156117.87141.112-23.2416
157122.336133.9-11.5638
158117.96394.270523.6925
159126.144125.380.764113
160127.93128.829-0.898913
161114.238117.656-3.41823
162115.322132.047-16.7253
163114.554110.4894.06532
164112.15122.365-10.2153
165102.27385.361516.9115
166236.2188.12248.0782
167237.323197.19140.1321
168260.105201.84258.2634
169197.569203.544-5.97516
170240.301206.75333.5484
171244.99197.21647.7736
172112.547146.661-34.1136
173110.739144.614-33.8753
174113.715144.053-30.3378
175117.004144.916-27.9119
176115.38141.268-25.8878
177116.388142.777-26.3889
178151.737168.232-16.4949
179148.79164.228-15.4384
180148.143153.152-5.00889
181150.44149.2951.14522
182148.462152.618-4.15571
183149.818167.439-17.6215
184117.226125.016-7.78987
185116.848125.135-8.28743
186116.286137.764-21.4782
187116.556169.219-52.6631
188116.342181.352-65.0102
189114.563140.784-26.2214
190201.774210.507-8.73339
191174.188161.24812.9401
192209.516187.04722.4689
193174.688205.473-30.7854
194198.764202.032-3.26816
195214.289190.04424.2449

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 119.992 & 105.801 & 14.1906 \tabularnewline
2 & 122.4 & 102.972 & 19.4279 \tabularnewline
3 & 116.682 & 93.6319 & 23.0501 \tabularnewline
4 & 116.676 & 85.2893 & 31.3867 \tabularnewline
5 & 116.014 & 79.0998 & 36.9142 \tabularnewline
6 & 120.552 & 106.519 & 14.0327 \tabularnewline
7 & 120.267 & 140.911 & -20.6437 \tabularnewline
8 & 107.332 & 132.313 & -24.9807 \tabularnewline
9 & 95.73 & 98.9668 & -3.23684 \tabularnewline
10 & 95.056 & 90.4401 & 4.61594 \tabularnewline
11 & 88.333 & 87.8345 & 0.498523 \tabularnewline
12 & 91.904 & 92.9557 & -1.05165 \tabularnewline
13 & 136.926 & 163.214 & -26.2882 \tabularnewline
14 & 139.173 & 151.798 & -12.6249 \tabularnewline
15 & 152.845 & 163.14 & -10.2947 \tabularnewline
16 & 142.167 & 152.378 & -10.2109 \tabularnewline
17 & 144.188 & 161.13 & -16.9415 \tabularnewline
18 & 168.778 & 178.329 & -9.55122 \tabularnewline
19 & 153.046 & 139.143 & 13.9029 \tabularnewline
20 & 156.405 & 154.388 & 2.01736 \tabularnewline
21 & 153.848 & 167.072 & -13.2238 \tabularnewline
22 & 153.88 & 151.908 & 1.97194 \tabularnewline
23 & 167.93 & 147.744 & 20.1863 \tabularnewline
24 & 173.917 & 156.76 & 17.1568 \tabularnewline
25 & 163.656 & 166.033 & -2.37706 \tabularnewline
26 & 104.4 & 106.192 & -1.7919 \tabularnewline
27 & 171.041 & 164.985 & 6.05592 \tabularnewline
28 & 146.845 & 172.003 & -25.1576 \tabularnewline
29 & 155.358 & 166.573 & -11.2149 \tabularnewline
30 & 162.568 & 173.525 & -10.9572 \tabularnewline
31 & 197.076 & 192.537 & 4.53919 \tabularnewline
32 & 199.228 & 184.406 & 14.8216 \tabularnewline
33 & 198.383 & 178.003 & 20.3802 \tabularnewline
34 & 202.266 & 176.333 & 25.9326 \tabularnewline
35 & 203.184 & 175.927 & 27.2571 \tabularnewline
36 & 201.464 & 175.618 & 25.8459 \tabularnewline
37 & 177.876 & 182.777 & -4.90129 \tabularnewline
38 & 176.17 & 175.51 & 0.659924 \tabularnewline
39 & 180.198 & 162.977 & 17.2205 \tabularnewline
40 & 187.733 & 167.846 & 19.8866 \tabularnewline
41 & 186.163 & 165.012 & 21.1511 \tabularnewline
42 & 184.055 & 184.097 & -0.0419146 \tabularnewline
43 & 237.226 & 194.199 & 43.027 \tabularnewline
44 & 241.404 & 190.551 & 50.8534 \tabularnewline
45 & 243.439 & 181.651 & 61.7884 \tabularnewline
46 & 242.852 & 184.891 & 57.9606 \tabularnewline
47 & 245.51 & 183.581 & 61.9291 \tabularnewline
48 & 252.455 & 184.293 & 68.1622 \tabularnewline
49 & 122.188 & 151.688 & -29.5004 \tabularnewline
50 & 122.964 & 160.682 & -37.7185 \tabularnewline
51 & 124.445 & 159.537 & -35.0921 \tabularnewline
52 & 126.344 & 137.059 & -10.7147 \tabularnewline
53 & 128.001 & 160.772 & -32.7709 \tabularnewline
54 & 129.336 & 143.344 & -14.0081 \tabularnewline
55 & 108.807 & 107.41 & 1.39745 \tabularnewline
56 & 109.86 & 99.2436 & 10.6164 \tabularnewline
57 & 110.417 & 106.675 & 3.74165 \tabularnewline
58 & 117.274 & 132.751 & -15.4768 \tabularnewline
59 & 116.879 & 111.98 & 4.89863 \tabularnewline
60 & 114.847 & 106.097 & 8.74975 \tabularnewline
61 & 209.144 & 190.102 & 19.042 \tabularnewline
62 & 223.365 & 186.885 & 36.4804 \tabularnewline
63 & 222.236 & 187.89 & 34.3465 \tabularnewline
64 & 228.832 & 193.764 & 35.068 \tabularnewline
65 & 229.401 & 181.644 & 47.7574 \tabularnewline
66 & 228.969 & 182.73 & 46.2388 \tabularnewline
67 & 140.341 & 145.563 & -5.2223 \tabularnewline
68 & 136.969 & 139.057 & -2.08806 \tabularnewline
69 & 143.533 & 143.399 & 0.134059 \tabularnewline
70 & 148.09 & 157.077 & -8.98731 \tabularnewline
71 & 142.729 & 146.261 & -3.5319 \tabularnewline
72 & 136.358 & 142.225 & -5.8669 \tabularnewline
73 & 120.08 & 154.749 & -34.6686 \tabularnewline
74 & 112.014 & 145.359 & -33.3447 \tabularnewline
75 & 110.793 & 140.741 & -29.9485 \tabularnewline
76 & 110.707 & 119.117 & -8.40993 \tabularnewline
77 & 112.876 & 137.941 & -25.0652 \tabularnewline
78 & 110.568 & 135.448 & -24.8796 \tabularnewline
79 & 95.385 & 104.466 & -9.08141 \tabularnewline
80 & 100.77 & 79.4315 & 21.3385 \tabularnewline
81 & 96.106 & 90.5458 & 5.56024 \tabularnewline
82 & 95.605 & 97.4479 & -1.84288 \tabularnewline
83 & 100.96 & 107.929 & -6.96869 \tabularnewline
84 & 98.804 & 129.452 & -30.6475 \tabularnewline
85 & 176.858 & 181.045 & -4.1866 \tabularnewline
86 & 180.978 & 174.943 & 6.03456 \tabularnewline
87 & 178.222 & 160.438 & 17.7842 \tabularnewline
88 & 176.281 & 160.414 & 15.8673 \tabularnewline
89 & 173.898 & 146.555 & 27.3431 \tabularnewline
90 & 179.711 & 174.97 & 4.74064 \tabularnewline
91 & 166.605 & 169.906 & -3.30118 \tabularnewline
92 & 151.955 & 134.075 & 17.8795 \tabularnewline
93 & 148.272 & 155.999 & -7.72738 \tabularnewline
94 & 152.125 & 133.956 & 18.1691 \tabularnewline
95 & 157.821 & 166.203 & -8.38164 \tabularnewline
96 & 157.447 & 168.906 & -11.4589 \tabularnewline
97 & 159.116 & 162.961 & -3.84455 \tabularnewline
98 & 125.036 & 122.031 & 3.00468 \tabularnewline
99 & 125.791 & 109.432 & 16.3589 \tabularnewline
100 & 126.512 & 93.6509 & 32.8611 \tabularnewline
101 & 125.641 & 59.3949 & 66.2461 \tabularnewline
102 & 128.451 & 102.366 & 26.0852 \tabularnewline
103 & 139.224 & 125.282 & 13.9419 \tabularnewline
104 & 150.258 & 155.317 & -5.05923 \tabularnewline
105 & 154.003 & 170.876 & -16.8728 \tabularnewline
106 & 149.689 & 157.205 & -7.51577 \tabularnewline
107 & 155.078 & 168.042 & -12.9639 \tabularnewline
108 & 151.884 & 156.495 & -4.61135 \tabularnewline
109 & 151.989 & 168.378 & -16.3888 \tabularnewline
110 & 193.03 & 194.096 & -1.06586 \tabularnewline
111 & 200.714 & 195.379 & 5.33519 \tabularnewline
112 & 208.519 & 195.803 & 12.7157 \tabularnewline
113 & 204.664 & 208.174 & -3.50958 \tabularnewline
114 & 210.141 & 183.65 & 26.4912 \tabularnewline
115 & 206.327 & 201.15 & 5.17676 \tabularnewline
116 & 151.872 & 179.995 & -28.123 \tabularnewline
117 & 158.219 & 186.095 & -27.8758 \tabularnewline
118 & 170.756 & 198.431 & -27.6749 \tabularnewline
119 & 178.285 & 184.683 & -6.39824 \tabularnewline
120 & 217.116 & 190.492 & 26.6236 \tabularnewline
121 & 128.94 & 150.665 & -21.7253 \tabularnewline
122 & 176.824 & 171.135 & 5.68906 \tabularnewline
123 & 138.19 & 148.651 & -10.4614 \tabularnewline
124 & 182.018 & 181.21 & 0.807725 \tabularnewline
125 & 156.239 & 180.906 & -24.6669 \tabularnewline
126 & 145.174 & 160.487 & -15.3131 \tabularnewline
127 & 138.145 & 150.544 & -12.3995 \tabularnewline
128 & 166.888 & 168.231 & -1.34261 \tabularnewline
129 & 119.031 & 138.851 & -19.8196 \tabularnewline
130 & 120.078 & 158.776 & -38.6983 \tabularnewline
131 & 120.289 & 145.472 & -25.1831 \tabularnewline
132 & 120.256 & 155.062 & -34.8062 \tabularnewline
133 & 119.056 & 146.377 & -27.3212 \tabularnewline
134 & 118.747 & 143.354 & -24.6067 \tabularnewline
135 & 106.516 & 94.9778 & 11.5382 \tabularnewline
136 & 110.453 & 131.249 & -20.7956 \tabularnewline
137 & 113.4 & 118.178 & -4.7782 \tabularnewline
138 & 113.166 & 128.469 & -15.3034 \tabularnewline
139 & 112.239 & 121.278 & -9.03947 \tabularnewline
140 & 116.15 & 141.103 & -24.9532 \tabularnewline
141 & 170.368 & 184.755 & -14.3866 \tabularnewline
142 & 208.083 & 180.024 & 28.0593 \tabularnewline
143 & 198.458 & 172.99 & 25.4679 \tabularnewline
144 & 202.805 & 178.383 & 24.4215 \tabularnewline
145 & 202.544 & 181.887 & 20.6572 \tabularnewline
146 & 223.361 & 175.1 & 48.2605 \tabularnewline
147 & 169.774 & 164.659 & 5.11505 \tabularnewline
148 & 183.52 & 190.078 & -6.55767 \tabularnewline
149 & 188.62 & 204.392 & -15.7723 \tabularnewline
150 & 202.632 & 235.706 & -33.0742 \tabularnewline
151 & 186.695 & 207.229 & -20.5338 \tabularnewline
152 & 192.818 & 226.275 & -33.4574 \tabularnewline
153 & 198.116 & 240.688 & -42.5724 \tabularnewline
154 & 121.345 & 123.852 & -2.50659 \tabularnewline
155 & 119.1 & 126.127 & -7.02679 \tabularnewline
156 & 117.87 & 141.112 & -23.2416 \tabularnewline
157 & 122.336 & 133.9 & -11.5638 \tabularnewline
158 & 117.963 & 94.2705 & 23.6925 \tabularnewline
159 & 126.144 & 125.38 & 0.764113 \tabularnewline
160 & 127.93 & 128.829 & -0.898913 \tabularnewline
161 & 114.238 & 117.656 & -3.41823 \tabularnewline
162 & 115.322 & 132.047 & -16.7253 \tabularnewline
163 & 114.554 & 110.489 & 4.06532 \tabularnewline
164 & 112.15 & 122.365 & -10.2153 \tabularnewline
165 & 102.273 & 85.3615 & 16.9115 \tabularnewline
166 & 236.2 & 188.122 & 48.0782 \tabularnewline
167 & 237.323 & 197.191 & 40.1321 \tabularnewline
168 & 260.105 & 201.842 & 58.2634 \tabularnewline
169 & 197.569 & 203.544 & -5.97516 \tabularnewline
170 & 240.301 & 206.753 & 33.5484 \tabularnewline
171 & 244.99 & 197.216 & 47.7736 \tabularnewline
172 & 112.547 & 146.661 & -34.1136 \tabularnewline
173 & 110.739 & 144.614 & -33.8753 \tabularnewline
174 & 113.715 & 144.053 & -30.3378 \tabularnewline
175 & 117.004 & 144.916 & -27.9119 \tabularnewline
176 & 115.38 & 141.268 & -25.8878 \tabularnewline
177 & 116.388 & 142.777 & -26.3889 \tabularnewline
178 & 151.737 & 168.232 & -16.4949 \tabularnewline
179 & 148.79 & 164.228 & -15.4384 \tabularnewline
180 & 148.143 & 153.152 & -5.00889 \tabularnewline
181 & 150.44 & 149.295 & 1.14522 \tabularnewline
182 & 148.462 & 152.618 & -4.15571 \tabularnewline
183 & 149.818 & 167.439 & -17.6215 \tabularnewline
184 & 117.226 & 125.016 & -7.78987 \tabularnewline
185 & 116.848 & 125.135 & -8.28743 \tabularnewline
186 & 116.286 & 137.764 & -21.4782 \tabularnewline
187 & 116.556 & 169.219 & -52.6631 \tabularnewline
188 & 116.342 & 181.352 & -65.0102 \tabularnewline
189 & 114.563 & 140.784 & -26.2214 \tabularnewline
190 & 201.774 & 210.507 & -8.73339 \tabularnewline
191 & 174.188 & 161.248 & 12.9401 \tabularnewline
192 & 209.516 & 187.047 & 22.4689 \tabularnewline
193 & 174.688 & 205.473 & -30.7854 \tabularnewline
194 & 198.764 & 202.032 & -3.26816 \tabularnewline
195 & 214.289 & 190.044 & 24.2449 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230071&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]119.992[/C][C]105.801[/C][C]14.1906[/C][/ROW]
[ROW][C]2[/C][C]122.4[/C][C]102.972[/C][C]19.4279[/C][/ROW]
[ROW][C]3[/C][C]116.682[/C][C]93.6319[/C][C]23.0501[/C][/ROW]
[ROW][C]4[/C][C]116.676[/C][C]85.2893[/C][C]31.3867[/C][/ROW]
[ROW][C]5[/C][C]116.014[/C][C]79.0998[/C][C]36.9142[/C][/ROW]
[ROW][C]6[/C][C]120.552[/C][C]106.519[/C][C]14.0327[/C][/ROW]
[ROW][C]7[/C][C]120.267[/C][C]140.911[/C][C]-20.6437[/C][/ROW]
[ROW][C]8[/C][C]107.332[/C][C]132.313[/C][C]-24.9807[/C][/ROW]
[ROW][C]9[/C][C]95.73[/C][C]98.9668[/C][C]-3.23684[/C][/ROW]
[ROW][C]10[/C][C]95.056[/C][C]90.4401[/C][C]4.61594[/C][/ROW]
[ROW][C]11[/C][C]88.333[/C][C]87.8345[/C][C]0.498523[/C][/ROW]
[ROW][C]12[/C][C]91.904[/C][C]92.9557[/C][C]-1.05165[/C][/ROW]
[ROW][C]13[/C][C]136.926[/C][C]163.214[/C][C]-26.2882[/C][/ROW]
[ROW][C]14[/C][C]139.173[/C][C]151.798[/C][C]-12.6249[/C][/ROW]
[ROW][C]15[/C][C]152.845[/C][C]163.14[/C][C]-10.2947[/C][/ROW]
[ROW][C]16[/C][C]142.167[/C][C]152.378[/C][C]-10.2109[/C][/ROW]
[ROW][C]17[/C][C]144.188[/C][C]161.13[/C][C]-16.9415[/C][/ROW]
[ROW][C]18[/C][C]168.778[/C][C]178.329[/C][C]-9.55122[/C][/ROW]
[ROW][C]19[/C][C]153.046[/C][C]139.143[/C][C]13.9029[/C][/ROW]
[ROW][C]20[/C][C]156.405[/C][C]154.388[/C][C]2.01736[/C][/ROW]
[ROW][C]21[/C][C]153.848[/C][C]167.072[/C][C]-13.2238[/C][/ROW]
[ROW][C]22[/C][C]153.88[/C][C]151.908[/C][C]1.97194[/C][/ROW]
[ROW][C]23[/C][C]167.93[/C][C]147.744[/C][C]20.1863[/C][/ROW]
[ROW][C]24[/C][C]173.917[/C][C]156.76[/C][C]17.1568[/C][/ROW]
[ROW][C]25[/C][C]163.656[/C][C]166.033[/C][C]-2.37706[/C][/ROW]
[ROW][C]26[/C][C]104.4[/C][C]106.192[/C][C]-1.7919[/C][/ROW]
[ROW][C]27[/C][C]171.041[/C][C]164.985[/C][C]6.05592[/C][/ROW]
[ROW][C]28[/C][C]146.845[/C][C]172.003[/C][C]-25.1576[/C][/ROW]
[ROW][C]29[/C][C]155.358[/C][C]166.573[/C][C]-11.2149[/C][/ROW]
[ROW][C]30[/C][C]162.568[/C][C]173.525[/C][C]-10.9572[/C][/ROW]
[ROW][C]31[/C][C]197.076[/C][C]192.537[/C][C]4.53919[/C][/ROW]
[ROW][C]32[/C][C]199.228[/C][C]184.406[/C][C]14.8216[/C][/ROW]
[ROW][C]33[/C][C]198.383[/C][C]178.003[/C][C]20.3802[/C][/ROW]
[ROW][C]34[/C][C]202.266[/C][C]176.333[/C][C]25.9326[/C][/ROW]
[ROW][C]35[/C][C]203.184[/C][C]175.927[/C][C]27.2571[/C][/ROW]
[ROW][C]36[/C][C]201.464[/C][C]175.618[/C][C]25.8459[/C][/ROW]
[ROW][C]37[/C][C]177.876[/C][C]182.777[/C][C]-4.90129[/C][/ROW]
[ROW][C]38[/C][C]176.17[/C][C]175.51[/C][C]0.659924[/C][/ROW]
[ROW][C]39[/C][C]180.198[/C][C]162.977[/C][C]17.2205[/C][/ROW]
[ROW][C]40[/C][C]187.733[/C][C]167.846[/C][C]19.8866[/C][/ROW]
[ROW][C]41[/C][C]186.163[/C][C]165.012[/C][C]21.1511[/C][/ROW]
[ROW][C]42[/C][C]184.055[/C][C]184.097[/C][C]-0.0419146[/C][/ROW]
[ROW][C]43[/C][C]237.226[/C][C]194.199[/C][C]43.027[/C][/ROW]
[ROW][C]44[/C][C]241.404[/C][C]190.551[/C][C]50.8534[/C][/ROW]
[ROW][C]45[/C][C]243.439[/C][C]181.651[/C][C]61.7884[/C][/ROW]
[ROW][C]46[/C][C]242.852[/C][C]184.891[/C][C]57.9606[/C][/ROW]
[ROW][C]47[/C][C]245.51[/C][C]183.581[/C][C]61.9291[/C][/ROW]
[ROW][C]48[/C][C]252.455[/C][C]184.293[/C][C]68.1622[/C][/ROW]
[ROW][C]49[/C][C]122.188[/C][C]151.688[/C][C]-29.5004[/C][/ROW]
[ROW][C]50[/C][C]122.964[/C][C]160.682[/C][C]-37.7185[/C][/ROW]
[ROW][C]51[/C][C]124.445[/C][C]159.537[/C][C]-35.0921[/C][/ROW]
[ROW][C]52[/C][C]126.344[/C][C]137.059[/C][C]-10.7147[/C][/ROW]
[ROW][C]53[/C][C]128.001[/C][C]160.772[/C][C]-32.7709[/C][/ROW]
[ROW][C]54[/C][C]129.336[/C][C]143.344[/C][C]-14.0081[/C][/ROW]
[ROW][C]55[/C][C]108.807[/C][C]107.41[/C][C]1.39745[/C][/ROW]
[ROW][C]56[/C][C]109.86[/C][C]99.2436[/C][C]10.6164[/C][/ROW]
[ROW][C]57[/C][C]110.417[/C][C]106.675[/C][C]3.74165[/C][/ROW]
[ROW][C]58[/C][C]117.274[/C][C]132.751[/C][C]-15.4768[/C][/ROW]
[ROW][C]59[/C][C]116.879[/C][C]111.98[/C][C]4.89863[/C][/ROW]
[ROW][C]60[/C][C]114.847[/C][C]106.097[/C][C]8.74975[/C][/ROW]
[ROW][C]61[/C][C]209.144[/C][C]190.102[/C][C]19.042[/C][/ROW]
[ROW][C]62[/C][C]223.365[/C][C]186.885[/C][C]36.4804[/C][/ROW]
[ROW][C]63[/C][C]222.236[/C][C]187.89[/C][C]34.3465[/C][/ROW]
[ROW][C]64[/C][C]228.832[/C][C]193.764[/C][C]35.068[/C][/ROW]
[ROW][C]65[/C][C]229.401[/C][C]181.644[/C][C]47.7574[/C][/ROW]
[ROW][C]66[/C][C]228.969[/C][C]182.73[/C][C]46.2388[/C][/ROW]
[ROW][C]67[/C][C]140.341[/C][C]145.563[/C][C]-5.2223[/C][/ROW]
[ROW][C]68[/C][C]136.969[/C][C]139.057[/C][C]-2.08806[/C][/ROW]
[ROW][C]69[/C][C]143.533[/C][C]143.399[/C][C]0.134059[/C][/ROW]
[ROW][C]70[/C][C]148.09[/C][C]157.077[/C][C]-8.98731[/C][/ROW]
[ROW][C]71[/C][C]142.729[/C][C]146.261[/C][C]-3.5319[/C][/ROW]
[ROW][C]72[/C][C]136.358[/C][C]142.225[/C][C]-5.8669[/C][/ROW]
[ROW][C]73[/C][C]120.08[/C][C]154.749[/C][C]-34.6686[/C][/ROW]
[ROW][C]74[/C][C]112.014[/C][C]145.359[/C][C]-33.3447[/C][/ROW]
[ROW][C]75[/C][C]110.793[/C][C]140.741[/C][C]-29.9485[/C][/ROW]
[ROW][C]76[/C][C]110.707[/C][C]119.117[/C][C]-8.40993[/C][/ROW]
[ROW][C]77[/C][C]112.876[/C][C]137.941[/C][C]-25.0652[/C][/ROW]
[ROW][C]78[/C][C]110.568[/C][C]135.448[/C][C]-24.8796[/C][/ROW]
[ROW][C]79[/C][C]95.385[/C][C]104.466[/C][C]-9.08141[/C][/ROW]
[ROW][C]80[/C][C]100.77[/C][C]79.4315[/C][C]21.3385[/C][/ROW]
[ROW][C]81[/C][C]96.106[/C][C]90.5458[/C][C]5.56024[/C][/ROW]
[ROW][C]82[/C][C]95.605[/C][C]97.4479[/C][C]-1.84288[/C][/ROW]
[ROW][C]83[/C][C]100.96[/C][C]107.929[/C][C]-6.96869[/C][/ROW]
[ROW][C]84[/C][C]98.804[/C][C]129.452[/C][C]-30.6475[/C][/ROW]
[ROW][C]85[/C][C]176.858[/C][C]181.045[/C][C]-4.1866[/C][/ROW]
[ROW][C]86[/C][C]180.978[/C][C]174.943[/C][C]6.03456[/C][/ROW]
[ROW][C]87[/C][C]178.222[/C][C]160.438[/C][C]17.7842[/C][/ROW]
[ROW][C]88[/C][C]176.281[/C][C]160.414[/C][C]15.8673[/C][/ROW]
[ROW][C]89[/C][C]173.898[/C][C]146.555[/C][C]27.3431[/C][/ROW]
[ROW][C]90[/C][C]179.711[/C][C]174.97[/C][C]4.74064[/C][/ROW]
[ROW][C]91[/C][C]166.605[/C][C]169.906[/C][C]-3.30118[/C][/ROW]
[ROW][C]92[/C][C]151.955[/C][C]134.075[/C][C]17.8795[/C][/ROW]
[ROW][C]93[/C][C]148.272[/C][C]155.999[/C][C]-7.72738[/C][/ROW]
[ROW][C]94[/C][C]152.125[/C][C]133.956[/C][C]18.1691[/C][/ROW]
[ROW][C]95[/C][C]157.821[/C][C]166.203[/C][C]-8.38164[/C][/ROW]
[ROW][C]96[/C][C]157.447[/C][C]168.906[/C][C]-11.4589[/C][/ROW]
[ROW][C]97[/C][C]159.116[/C][C]162.961[/C][C]-3.84455[/C][/ROW]
[ROW][C]98[/C][C]125.036[/C][C]122.031[/C][C]3.00468[/C][/ROW]
[ROW][C]99[/C][C]125.791[/C][C]109.432[/C][C]16.3589[/C][/ROW]
[ROW][C]100[/C][C]126.512[/C][C]93.6509[/C][C]32.8611[/C][/ROW]
[ROW][C]101[/C][C]125.641[/C][C]59.3949[/C][C]66.2461[/C][/ROW]
[ROW][C]102[/C][C]128.451[/C][C]102.366[/C][C]26.0852[/C][/ROW]
[ROW][C]103[/C][C]139.224[/C][C]125.282[/C][C]13.9419[/C][/ROW]
[ROW][C]104[/C][C]150.258[/C][C]155.317[/C][C]-5.05923[/C][/ROW]
[ROW][C]105[/C][C]154.003[/C][C]170.876[/C][C]-16.8728[/C][/ROW]
[ROW][C]106[/C][C]149.689[/C][C]157.205[/C][C]-7.51577[/C][/ROW]
[ROW][C]107[/C][C]155.078[/C][C]168.042[/C][C]-12.9639[/C][/ROW]
[ROW][C]108[/C][C]151.884[/C][C]156.495[/C][C]-4.61135[/C][/ROW]
[ROW][C]109[/C][C]151.989[/C][C]168.378[/C][C]-16.3888[/C][/ROW]
[ROW][C]110[/C][C]193.03[/C][C]194.096[/C][C]-1.06586[/C][/ROW]
[ROW][C]111[/C][C]200.714[/C][C]195.379[/C][C]5.33519[/C][/ROW]
[ROW][C]112[/C][C]208.519[/C][C]195.803[/C][C]12.7157[/C][/ROW]
[ROW][C]113[/C][C]204.664[/C][C]208.174[/C][C]-3.50958[/C][/ROW]
[ROW][C]114[/C][C]210.141[/C][C]183.65[/C][C]26.4912[/C][/ROW]
[ROW][C]115[/C][C]206.327[/C][C]201.15[/C][C]5.17676[/C][/ROW]
[ROW][C]116[/C][C]151.872[/C][C]179.995[/C][C]-28.123[/C][/ROW]
[ROW][C]117[/C][C]158.219[/C][C]186.095[/C][C]-27.8758[/C][/ROW]
[ROW][C]118[/C][C]170.756[/C][C]198.431[/C][C]-27.6749[/C][/ROW]
[ROW][C]119[/C][C]178.285[/C][C]184.683[/C][C]-6.39824[/C][/ROW]
[ROW][C]120[/C][C]217.116[/C][C]190.492[/C][C]26.6236[/C][/ROW]
[ROW][C]121[/C][C]128.94[/C][C]150.665[/C][C]-21.7253[/C][/ROW]
[ROW][C]122[/C][C]176.824[/C][C]171.135[/C][C]5.68906[/C][/ROW]
[ROW][C]123[/C][C]138.19[/C][C]148.651[/C][C]-10.4614[/C][/ROW]
[ROW][C]124[/C][C]182.018[/C][C]181.21[/C][C]0.807725[/C][/ROW]
[ROW][C]125[/C][C]156.239[/C][C]180.906[/C][C]-24.6669[/C][/ROW]
[ROW][C]126[/C][C]145.174[/C][C]160.487[/C][C]-15.3131[/C][/ROW]
[ROW][C]127[/C][C]138.145[/C][C]150.544[/C][C]-12.3995[/C][/ROW]
[ROW][C]128[/C][C]166.888[/C][C]168.231[/C][C]-1.34261[/C][/ROW]
[ROW][C]129[/C][C]119.031[/C][C]138.851[/C][C]-19.8196[/C][/ROW]
[ROW][C]130[/C][C]120.078[/C][C]158.776[/C][C]-38.6983[/C][/ROW]
[ROW][C]131[/C][C]120.289[/C][C]145.472[/C][C]-25.1831[/C][/ROW]
[ROW][C]132[/C][C]120.256[/C][C]155.062[/C][C]-34.8062[/C][/ROW]
[ROW][C]133[/C][C]119.056[/C][C]146.377[/C][C]-27.3212[/C][/ROW]
[ROW][C]134[/C][C]118.747[/C][C]143.354[/C][C]-24.6067[/C][/ROW]
[ROW][C]135[/C][C]106.516[/C][C]94.9778[/C][C]11.5382[/C][/ROW]
[ROW][C]136[/C][C]110.453[/C][C]131.249[/C][C]-20.7956[/C][/ROW]
[ROW][C]137[/C][C]113.4[/C][C]118.178[/C][C]-4.7782[/C][/ROW]
[ROW][C]138[/C][C]113.166[/C][C]128.469[/C][C]-15.3034[/C][/ROW]
[ROW][C]139[/C][C]112.239[/C][C]121.278[/C][C]-9.03947[/C][/ROW]
[ROW][C]140[/C][C]116.15[/C][C]141.103[/C][C]-24.9532[/C][/ROW]
[ROW][C]141[/C][C]170.368[/C][C]184.755[/C][C]-14.3866[/C][/ROW]
[ROW][C]142[/C][C]208.083[/C][C]180.024[/C][C]28.0593[/C][/ROW]
[ROW][C]143[/C][C]198.458[/C][C]172.99[/C][C]25.4679[/C][/ROW]
[ROW][C]144[/C][C]202.805[/C][C]178.383[/C][C]24.4215[/C][/ROW]
[ROW][C]145[/C][C]202.544[/C][C]181.887[/C][C]20.6572[/C][/ROW]
[ROW][C]146[/C][C]223.361[/C][C]175.1[/C][C]48.2605[/C][/ROW]
[ROW][C]147[/C][C]169.774[/C][C]164.659[/C][C]5.11505[/C][/ROW]
[ROW][C]148[/C][C]183.52[/C][C]190.078[/C][C]-6.55767[/C][/ROW]
[ROW][C]149[/C][C]188.62[/C][C]204.392[/C][C]-15.7723[/C][/ROW]
[ROW][C]150[/C][C]202.632[/C][C]235.706[/C][C]-33.0742[/C][/ROW]
[ROW][C]151[/C][C]186.695[/C][C]207.229[/C][C]-20.5338[/C][/ROW]
[ROW][C]152[/C][C]192.818[/C][C]226.275[/C][C]-33.4574[/C][/ROW]
[ROW][C]153[/C][C]198.116[/C][C]240.688[/C][C]-42.5724[/C][/ROW]
[ROW][C]154[/C][C]121.345[/C][C]123.852[/C][C]-2.50659[/C][/ROW]
[ROW][C]155[/C][C]119.1[/C][C]126.127[/C][C]-7.02679[/C][/ROW]
[ROW][C]156[/C][C]117.87[/C][C]141.112[/C][C]-23.2416[/C][/ROW]
[ROW][C]157[/C][C]122.336[/C][C]133.9[/C][C]-11.5638[/C][/ROW]
[ROW][C]158[/C][C]117.963[/C][C]94.2705[/C][C]23.6925[/C][/ROW]
[ROW][C]159[/C][C]126.144[/C][C]125.38[/C][C]0.764113[/C][/ROW]
[ROW][C]160[/C][C]127.93[/C][C]128.829[/C][C]-0.898913[/C][/ROW]
[ROW][C]161[/C][C]114.238[/C][C]117.656[/C][C]-3.41823[/C][/ROW]
[ROW][C]162[/C][C]115.322[/C][C]132.047[/C][C]-16.7253[/C][/ROW]
[ROW][C]163[/C][C]114.554[/C][C]110.489[/C][C]4.06532[/C][/ROW]
[ROW][C]164[/C][C]112.15[/C][C]122.365[/C][C]-10.2153[/C][/ROW]
[ROW][C]165[/C][C]102.273[/C][C]85.3615[/C][C]16.9115[/C][/ROW]
[ROW][C]166[/C][C]236.2[/C][C]188.122[/C][C]48.0782[/C][/ROW]
[ROW][C]167[/C][C]237.323[/C][C]197.191[/C][C]40.1321[/C][/ROW]
[ROW][C]168[/C][C]260.105[/C][C]201.842[/C][C]58.2634[/C][/ROW]
[ROW][C]169[/C][C]197.569[/C][C]203.544[/C][C]-5.97516[/C][/ROW]
[ROW][C]170[/C][C]240.301[/C][C]206.753[/C][C]33.5484[/C][/ROW]
[ROW][C]171[/C][C]244.99[/C][C]197.216[/C][C]47.7736[/C][/ROW]
[ROW][C]172[/C][C]112.547[/C][C]146.661[/C][C]-34.1136[/C][/ROW]
[ROW][C]173[/C][C]110.739[/C][C]144.614[/C][C]-33.8753[/C][/ROW]
[ROW][C]174[/C][C]113.715[/C][C]144.053[/C][C]-30.3378[/C][/ROW]
[ROW][C]175[/C][C]117.004[/C][C]144.916[/C][C]-27.9119[/C][/ROW]
[ROW][C]176[/C][C]115.38[/C][C]141.268[/C][C]-25.8878[/C][/ROW]
[ROW][C]177[/C][C]116.388[/C][C]142.777[/C][C]-26.3889[/C][/ROW]
[ROW][C]178[/C][C]151.737[/C][C]168.232[/C][C]-16.4949[/C][/ROW]
[ROW][C]179[/C][C]148.79[/C][C]164.228[/C][C]-15.4384[/C][/ROW]
[ROW][C]180[/C][C]148.143[/C][C]153.152[/C][C]-5.00889[/C][/ROW]
[ROW][C]181[/C][C]150.44[/C][C]149.295[/C][C]1.14522[/C][/ROW]
[ROW][C]182[/C][C]148.462[/C][C]152.618[/C][C]-4.15571[/C][/ROW]
[ROW][C]183[/C][C]149.818[/C][C]167.439[/C][C]-17.6215[/C][/ROW]
[ROW][C]184[/C][C]117.226[/C][C]125.016[/C][C]-7.78987[/C][/ROW]
[ROW][C]185[/C][C]116.848[/C][C]125.135[/C][C]-8.28743[/C][/ROW]
[ROW][C]186[/C][C]116.286[/C][C]137.764[/C][C]-21.4782[/C][/ROW]
[ROW][C]187[/C][C]116.556[/C][C]169.219[/C][C]-52.6631[/C][/ROW]
[ROW][C]188[/C][C]116.342[/C][C]181.352[/C][C]-65.0102[/C][/ROW]
[ROW][C]189[/C][C]114.563[/C][C]140.784[/C][C]-26.2214[/C][/ROW]
[ROW][C]190[/C][C]201.774[/C][C]210.507[/C][C]-8.73339[/C][/ROW]
[ROW][C]191[/C][C]174.188[/C][C]161.248[/C][C]12.9401[/C][/ROW]
[ROW][C]192[/C][C]209.516[/C][C]187.047[/C][C]22.4689[/C][/ROW]
[ROW][C]193[/C][C]174.688[/C][C]205.473[/C][C]-30.7854[/C][/ROW]
[ROW][C]194[/C][C]198.764[/C][C]202.032[/C][C]-3.26816[/C][/ROW]
[ROW][C]195[/C][C]214.289[/C][C]190.044[/C][C]24.2449[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230071&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230071&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1119.992105.80114.1906
2122.4102.97219.4279
3116.68293.631923.0501
4116.67685.289331.3867
5116.01479.099836.9142
6120.552106.51914.0327
7120.267140.911-20.6437
8107.332132.313-24.9807
995.7398.9668-3.23684
1095.05690.44014.61594
1188.33387.83450.498523
1291.90492.9557-1.05165
13136.926163.214-26.2882
14139.173151.798-12.6249
15152.845163.14-10.2947
16142.167152.378-10.2109
17144.188161.13-16.9415
18168.778178.329-9.55122
19153.046139.14313.9029
20156.405154.3882.01736
21153.848167.072-13.2238
22153.88151.9081.97194
23167.93147.74420.1863
24173.917156.7617.1568
25163.656166.033-2.37706
26104.4106.192-1.7919
27171.041164.9856.05592
28146.845172.003-25.1576
29155.358166.573-11.2149
30162.568173.525-10.9572
31197.076192.5374.53919
32199.228184.40614.8216
33198.383178.00320.3802
34202.266176.33325.9326
35203.184175.92727.2571
36201.464175.61825.8459
37177.876182.777-4.90129
38176.17175.510.659924
39180.198162.97717.2205
40187.733167.84619.8866
41186.163165.01221.1511
42184.055184.097-0.0419146
43237.226194.19943.027
44241.404190.55150.8534
45243.439181.65161.7884
46242.852184.89157.9606
47245.51183.58161.9291
48252.455184.29368.1622
49122.188151.688-29.5004
50122.964160.682-37.7185
51124.445159.537-35.0921
52126.344137.059-10.7147
53128.001160.772-32.7709
54129.336143.344-14.0081
55108.807107.411.39745
56109.8699.243610.6164
57110.417106.6753.74165
58117.274132.751-15.4768
59116.879111.984.89863
60114.847106.0978.74975
61209.144190.10219.042
62223.365186.88536.4804
63222.236187.8934.3465
64228.832193.76435.068
65229.401181.64447.7574
66228.969182.7346.2388
67140.341145.563-5.2223
68136.969139.057-2.08806
69143.533143.3990.134059
70148.09157.077-8.98731
71142.729146.261-3.5319
72136.358142.225-5.8669
73120.08154.749-34.6686
74112.014145.359-33.3447
75110.793140.741-29.9485
76110.707119.117-8.40993
77112.876137.941-25.0652
78110.568135.448-24.8796
7995.385104.466-9.08141
80100.7779.431521.3385
8196.10690.54585.56024
8295.60597.4479-1.84288
83100.96107.929-6.96869
8498.804129.452-30.6475
85176.858181.045-4.1866
86180.978174.9436.03456
87178.222160.43817.7842
88176.281160.41415.8673
89173.898146.55527.3431
90179.711174.974.74064
91166.605169.906-3.30118
92151.955134.07517.8795
93148.272155.999-7.72738
94152.125133.95618.1691
95157.821166.203-8.38164
96157.447168.906-11.4589
97159.116162.961-3.84455
98125.036122.0313.00468
99125.791109.43216.3589
100126.51293.650932.8611
101125.64159.394966.2461
102128.451102.36626.0852
103139.224125.28213.9419
104150.258155.317-5.05923
105154.003170.876-16.8728
106149.689157.205-7.51577
107155.078168.042-12.9639
108151.884156.495-4.61135
109151.989168.378-16.3888
110193.03194.096-1.06586
111200.714195.3795.33519
112208.519195.80312.7157
113204.664208.174-3.50958
114210.141183.6526.4912
115206.327201.155.17676
116151.872179.995-28.123
117158.219186.095-27.8758
118170.756198.431-27.6749
119178.285184.683-6.39824
120217.116190.49226.6236
121128.94150.665-21.7253
122176.824171.1355.68906
123138.19148.651-10.4614
124182.018181.210.807725
125156.239180.906-24.6669
126145.174160.487-15.3131
127138.145150.544-12.3995
128166.888168.231-1.34261
129119.031138.851-19.8196
130120.078158.776-38.6983
131120.289145.472-25.1831
132120.256155.062-34.8062
133119.056146.377-27.3212
134118.747143.354-24.6067
135106.51694.977811.5382
136110.453131.249-20.7956
137113.4118.178-4.7782
138113.166128.469-15.3034
139112.239121.278-9.03947
140116.15141.103-24.9532
141170.368184.755-14.3866
142208.083180.02428.0593
143198.458172.9925.4679
144202.805178.38324.4215
145202.544181.88720.6572
146223.361175.148.2605
147169.774164.6595.11505
148183.52190.078-6.55767
149188.62204.392-15.7723
150202.632235.706-33.0742
151186.695207.229-20.5338
152192.818226.275-33.4574
153198.116240.688-42.5724
154121.345123.852-2.50659
155119.1126.127-7.02679
156117.87141.112-23.2416
157122.336133.9-11.5638
158117.96394.270523.6925
159126.144125.380.764113
160127.93128.829-0.898913
161114.238117.656-3.41823
162115.322132.047-16.7253
163114.554110.4894.06532
164112.15122.365-10.2153
165102.27385.361516.9115
166236.2188.12248.0782
167237.323197.19140.1321
168260.105201.84258.2634
169197.569203.544-5.97516
170240.301206.75333.5484
171244.99197.21647.7736
172112.547146.661-34.1136
173110.739144.614-33.8753
174113.715144.053-30.3378
175117.004144.916-27.9119
176115.38141.268-25.8878
177116.388142.777-26.3889
178151.737168.232-16.4949
179148.79164.228-15.4384
180148.143153.152-5.00889
181150.44149.2951.14522
182148.462152.618-4.15571
183149.818167.439-17.6215
184117.226125.016-7.78987
185116.848125.135-8.28743
186116.286137.764-21.4782
187116.556169.219-52.6631
188116.342181.352-65.0102
189114.563140.784-26.2214
190201.774210.507-8.73339
191174.188161.24812.9401
192209.516187.04722.4689
193174.688205.473-30.7854
194198.764202.032-3.26816
195214.289190.04424.2449







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.007742620.01548520.992257
100.001133010.002266010.998867
110.0001554570.0003109140.999845
122.224e-054.44801e-050.999978
133.14729e-066.29459e-060.999997
143.73628e-077.47256e-071
151.01161e-052.02323e-050.99999
162.38333e-064.76665e-060.999998
176.02102e-061.2042e-050.999994
183.72724e-067.45449e-060.999996
199.4808e-071.89616e-060.999999
202.34833e-074.69666e-071
212.70409e-075.40817e-071
226.81152e-081.3623e-071
232.73307e-075.46614e-071
246.95309e-071.39062e-060.999999
252.41779e-064.83557e-060.999998
262.22297e-064.44594e-060.999998
274.89658e-069.79317e-060.999995
283.66762e-067.33524e-060.999996
291.46489e-062.92977e-060.999999
306.12101e-071.2242e-060.999999
312.25369e-064.50737e-060.999998
321.16591e-052.33182e-050.999988
332.84362e-055.68723e-050.999972
349.02657e-050.0001805310.99991
350.0001781690.0003563390.999822
360.0002257630.0004515260.999774
370.0001347140.0002694280.999865
387.18164e-050.0001436330.999928
395.68842e-050.0001137680.999943
405.0848e-050.0001016960.999949
414.65646e-059.31291e-050.999953
422.62102e-055.24204e-050.999974
437.56487e-050.0001512970.999924
440.000271020.000542040.999729
450.001390270.002780540.99861
460.003727360.007454730.996273
470.009025040.01805010.990975
480.0275410.0550820.972459
490.03126590.06253170.968734
500.02841380.05682760.971586
510.025410.050820.97459
520.03054360.06108720.969456
530.02757050.0551410.972429
540.02976920.05953840.970231
550.02381230.04762460.976188
560.02689650.05379310.973103
570.02151440.04302890.978486
580.01664630.03329260.983354
590.01439630.02879270.985604
600.01223250.02446490.987768
610.009567530.01913510.990432
620.01025130.02050260.989749
630.01107460.02214920.988925
640.01270010.02540030.9873
650.02033880.04067750.979661
660.03155460.06310910.968445
670.02759390.05518780.972406
680.03293680.06587350.967063
690.08243490.164870.917565
700.07282850.1456570.927171
710.06124940.1224990.938751
720.05219170.1043830.947808
730.06685740.1337150.933143
740.3506690.7013380.649331
750.3808740.7617470.619126
760.3404150.680830.659585
770.3558340.7116680.644166
780.3594840.7189670.640516
790.3257550.6515110.674245
800.4623150.9246310.537685
810.4487820.8975640.551218
820.4252790.8505570.574721
830.3862140.7724280.613786
840.4033770.8067550.596623
850.3798270.7596550.620173
860.3474730.6949470.652527
870.3268040.6536080.673196
880.2969280.5938550.703072
890.2963850.592770.703615
900.2708280.5416560.729172
910.2561150.512230.743885
920.2350930.4701850.764907
930.2118280.4236560.788172
940.1978950.3957890.802105
950.1807940.3615890.819206
960.1676330.3352660.832367
970.1460350.2920690.853965
980.1515170.3030340.848483
990.1857620.3715230.814238
1000.246190.492380.75381
1010.4318360.8636720.568164
1020.4884750.976950.511525
1030.7601860.4796280.239814
1040.7270360.5459290.272964
1050.717050.5659010.28295
1060.6830280.6339450.316972
1070.6609440.6781120.339056
1080.6236340.7527320.376366
1090.6117010.7765990.388299
1100.5819930.8360150.418007
1110.543760.9124810.45624
1120.5134760.9730490.486524
1130.4934610.9869230.506539
1140.5059750.9880490.494025
1150.4652890.9305780.534711
1160.4837350.9674710.516265
1170.5004150.999170.499585
1180.5291820.9416370.470818
1190.4874220.9748450.512578
1200.4739510.9479020.526049
1210.4435690.8871370.556431
1220.4041040.8082080.595896
1230.3719480.7438960.628052
1240.3385540.6771080.661446
1250.3494630.6989270.650537
1260.3255910.6511820.674409
1270.2948660.5897330.705134
1280.2600830.5201660.739917
1290.2372060.4744120.762794
1300.3021810.6043620.697819
1310.2961980.5923960.703802
1320.3497590.6995180.650241
1330.3553330.7106650.644667
1340.3464850.6929710.653515
1350.3453210.6906420.654679
1360.3262180.6524370.673782
1370.2868480.5736950.713152
1380.2638640.5277270.736136
1390.2330120.4660230.766988
1400.2420310.4840630.757969
1410.2618370.5236730.738163
1420.2413290.4826580.758671
1430.2262570.4525140.773743
1440.222120.4442390.77788
1450.1965450.3930910.803455
1460.3076370.6152740.692363
1470.2935070.5870140.706493
1480.2745170.5490330.725483
1490.2726290.5452590.727371
1500.2937920.5875850.706208
1510.2741550.548310.725845
1520.2684340.5368690.731566
1530.3386080.6772160.661392
1540.2955780.5911550.704422
1550.252380.5047610.74762
1560.2590650.5181310.740935
1570.220130.4402610.77987
1580.2714870.5429750.728513
1590.2584180.5168360.741582
1600.2152690.4305380.784731
1610.1951610.3903210.804839
1620.1993360.3986720.800664
1630.1613170.3226340.838683
1640.1427330.2854670.857267
1650.7165240.5669510.283476
1660.7377490.5245020.262251
1670.786970.4260590.21303
1680.9061280.1877440.0938722
1690.9186150.1627710.0813855
1700.9114640.1770720.0885362
1710.9964770.007046570.00352329
1720.9941990.0116020.00580098
1730.992310.01537910.00768954
1740.9880350.02392940.0119647
1750.9834440.03311160.0165558
1760.9726360.05472720.0273636
1770.9632780.07344430.0367221
1780.9401670.1196660.0598331
1790.9074480.1851050.0925523
1800.8653450.269310.134655
1810.7950620.4098750.204938
1820.7079480.5841040.292052
1830.6612060.6775870.338794
1840.5407260.9185490.459274
1850.4042070.8084150.595793
1860.2767920.5535850.723208

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.00774262 & 0.0154852 & 0.992257 \tabularnewline
10 & 0.00113301 & 0.00226601 & 0.998867 \tabularnewline
11 & 0.000155457 & 0.000310914 & 0.999845 \tabularnewline
12 & 2.224e-05 & 4.44801e-05 & 0.999978 \tabularnewline
13 & 3.14729e-06 & 6.29459e-06 & 0.999997 \tabularnewline
14 & 3.73628e-07 & 7.47256e-07 & 1 \tabularnewline
15 & 1.01161e-05 & 2.02323e-05 & 0.99999 \tabularnewline
16 & 2.38333e-06 & 4.76665e-06 & 0.999998 \tabularnewline
17 & 6.02102e-06 & 1.2042e-05 & 0.999994 \tabularnewline
18 & 3.72724e-06 & 7.45449e-06 & 0.999996 \tabularnewline
19 & 9.4808e-07 & 1.89616e-06 & 0.999999 \tabularnewline
20 & 2.34833e-07 & 4.69666e-07 & 1 \tabularnewline
21 & 2.70409e-07 & 5.40817e-07 & 1 \tabularnewline
22 & 6.81152e-08 & 1.3623e-07 & 1 \tabularnewline
23 & 2.73307e-07 & 5.46614e-07 & 1 \tabularnewline
24 & 6.95309e-07 & 1.39062e-06 & 0.999999 \tabularnewline
25 & 2.41779e-06 & 4.83557e-06 & 0.999998 \tabularnewline
26 & 2.22297e-06 & 4.44594e-06 & 0.999998 \tabularnewline
27 & 4.89658e-06 & 9.79317e-06 & 0.999995 \tabularnewline
28 & 3.66762e-06 & 7.33524e-06 & 0.999996 \tabularnewline
29 & 1.46489e-06 & 2.92977e-06 & 0.999999 \tabularnewline
30 & 6.12101e-07 & 1.2242e-06 & 0.999999 \tabularnewline
31 & 2.25369e-06 & 4.50737e-06 & 0.999998 \tabularnewline
32 & 1.16591e-05 & 2.33182e-05 & 0.999988 \tabularnewline
33 & 2.84362e-05 & 5.68723e-05 & 0.999972 \tabularnewline
34 & 9.02657e-05 & 0.000180531 & 0.99991 \tabularnewline
35 & 0.000178169 & 0.000356339 & 0.999822 \tabularnewline
36 & 0.000225763 & 0.000451526 & 0.999774 \tabularnewline
37 & 0.000134714 & 0.000269428 & 0.999865 \tabularnewline
38 & 7.18164e-05 & 0.000143633 & 0.999928 \tabularnewline
39 & 5.68842e-05 & 0.000113768 & 0.999943 \tabularnewline
40 & 5.0848e-05 & 0.000101696 & 0.999949 \tabularnewline
41 & 4.65646e-05 & 9.31291e-05 & 0.999953 \tabularnewline
42 & 2.62102e-05 & 5.24204e-05 & 0.999974 \tabularnewline
43 & 7.56487e-05 & 0.000151297 & 0.999924 \tabularnewline
44 & 0.00027102 & 0.00054204 & 0.999729 \tabularnewline
45 & 0.00139027 & 0.00278054 & 0.99861 \tabularnewline
46 & 0.00372736 & 0.00745473 & 0.996273 \tabularnewline
47 & 0.00902504 & 0.0180501 & 0.990975 \tabularnewline
48 & 0.027541 & 0.055082 & 0.972459 \tabularnewline
49 & 0.0312659 & 0.0625317 & 0.968734 \tabularnewline
50 & 0.0284138 & 0.0568276 & 0.971586 \tabularnewline
51 & 0.02541 & 0.05082 & 0.97459 \tabularnewline
52 & 0.0305436 & 0.0610872 & 0.969456 \tabularnewline
53 & 0.0275705 & 0.055141 & 0.972429 \tabularnewline
54 & 0.0297692 & 0.0595384 & 0.970231 \tabularnewline
55 & 0.0238123 & 0.0476246 & 0.976188 \tabularnewline
56 & 0.0268965 & 0.0537931 & 0.973103 \tabularnewline
57 & 0.0215144 & 0.0430289 & 0.978486 \tabularnewline
58 & 0.0166463 & 0.0332926 & 0.983354 \tabularnewline
59 & 0.0143963 & 0.0287927 & 0.985604 \tabularnewline
60 & 0.0122325 & 0.0244649 & 0.987768 \tabularnewline
61 & 0.00956753 & 0.0191351 & 0.990432 \tabularnewline
62 & 0.0102513 & 0.0205026 & 0.989749 \tabularnewline
63 & 0.0110746 & 0.0221492 & 0.988925 \tabularnewline
64 & 0.0127001 & 0.0254003 & 0.9873 \tabularnewline
65 & 0.0203388 & 0.0406775 & 0.979661 \tabularnewline
66 & 0.0315546 & 0.0631091 & 0.968445 \tabularnewline
67 & 0.0275939 & 0.0551878 & 0.972406 \tabularnewline
68 & 0.0329368 & 0.0658735 & 0.967063 \tabularnewline
69 & 0.0824349 & 0.16487 & 0.917565 \tabularnewline
70 & 0.0728285 & 0.145657 & 0.927171 \tabularnewline
71 & 0.0612494 & 0.122499 & 0.938751 \tabularnewline
72 & 0.0521917 & 0.104383 & 0.947808 \tabularnewline
73 & 0.0668574 & 0.133715 & 0.933143 \tabularnewline
74 & 0.350669 & 0.701338 & 0.649331 \tabularnewline
75 & 0.380874 & 0.761747 & 0.619126 \tabularnewline
76 & 0.340415 & 0.68083 & 0.659585 \tabularnewline
77 & 0.355834 & 0.711668 & 0.644166 \tabularnewline
78 & 0.359484 & 0.718967 & 0.640516 \tabularnewline
79 & 0.325755 & 0.651511 & 0.674245 \tabularnewline
80 & 0.462315 & 0.924631 & 0.537685 \tabularnewline
81 & 0.448782 & 0.897564 & 0.551218 \tabularnewline
82 & 0.425279 & 0.850557 & 0.574721 \tabularnewline
83 & 0.386214 & 0.772428 & 0.613786 \tabularnewline
84 & 0.403377 & 0.806755 & 0.596623 \tabularnewline
85 & 0.379827 & 0.759655 & 0.620173 \tabularnewline
86 & 0.347473 & 0.694947 & 0.652527 \tabularnewline
87 & 0.326804 & 0.653608 & 0.673196 \tabularnewline
88 & 0.296928 & 0.593855 & 0.703072 \tabularnewline
89 & 0.296385 & 0.59277 & 0.703615 \tabularnewline
90 & 0.270828 & 0.541656 & 0.729172 \tabularnewline
91 & 0.256115 & 0.51223 & 0.743885 \tabularnewline
92 & 0.235093 & 0.470185 & 0.764907 \tabularnewline
93 & 0.211828 & 0.423656 & 0.788172 \tabularnewline
94 & 0.197895 & 0.395789 & 0.802105 \tabularnewline
95 & 0.180794 & 0.361589 & 0.819206 \tabularnewline
96 & 0.167633 & 0.335266 & 0.832367 \tabularnewline
97 & 0.146035 & 0.292069 & 0.853965 \tabularnewline
98 & 0.151517 & 0.303034 & 0.848483 \tabularnewline
99 & 0.185762 & 0.371523 & 0.814238 \tabularnewline
100 & 0.24619 & 0.49238 & 0.75381 \tabularnewline
101 & 0.431836 & 0.863672 & 0.568164 \tabularnewline
102 & 0.488475 & 0.97695 & 0.511525 \tabularnewline
103 & 0.760186 & 0.479628 & 0.239814 \tabularnewline
104 & 0.727036 & 0.545929 & 0.272964 \tabularnewline
105 & 0.71705 & 0.565901 & 0.28295 \tabularnewline
106 & 0.683028 & 0.633945 & 0.316972 \tabularnewline
107 & 0.660944 & 0.678112 & 0.339056 \tabularnewline
108 & 0.623634 & 0.752732 & 0.376366 \tabularnewline
109 & 0.611701 & 0.776599 & 0.388299 \tabularnewline
110 & 0.581993 & 0.836015 & 0.418007 \tabularnewline
111 & 0.54376 & 0.912481 & 0.45624 \tabularnewline
112 & 0.513476 & 0.973049 & 0.486524 \tabularnewline
113 & 0.493461 & 0.986923 & 0.506539 \tabularnewline
114 & 0.505975 & 0.988049 & 0.494025 \tabularnewline
115 & 0.465289 & 0.930578 & 0.534711 \tabularnewline
116 & 0.483735 & 0.967471 & 0.516265 \tabularnewline
117 & 0.500415 & 0.99917 & 0.499585 \tabularnewline
118 & 0.529182 & 0.941637 & 0.470818 \tabularnewline
119 & 0.487422 & 0.974845 & 0.512578 \tabularnewline
120 & 0.473951 & 0.947902 & 0.526049 \tabularnewline
121 & 0.443569 & 0.887137 & 0.556431 \tabularnewline
122 & 0.404104 & 0.808208 & 0.595896 \tabularnewline
123 & 0.371948 & 0.743896 & 0.628052 \tabularnewline
124 & 0.338554 & 0.677108 & 0.661446 \tabularnewline
125 & 0.349463 & 0.698927 & 0.650537 \tabularnewline
126 & 0.325591 & 0.651182 & 0.674409 \tabularnewline
127 & 0.294866 & 0.589733 & 0.705134 \tabularnewline
128 & 0.260083 & 0.520166 & 0.739917 \tabularnewline
129 & 0.237206 & 0.474412 & 0.762794 \tabularnewline
130 & 0.302181 & 0.604362 & 0.697819 \tabularnewline
131 & 0.296198 & 0.592396 & 0.703802 \tabularnewline
132 & 0.349759 & 0.699518 & 0.650241 \tabularnewline
133 & 0.355333 & 0.710665 & 0.644667 \tabularnewline
134 & 0.346485 & 0.692971 & 0.653515 \tabularnewline
135 & 0.345321 & 0.690642 & 0.654679 \tabularnewline
136 & 0.326218 & 0.652437 & 0.673782 \tabularnewline
137 & 0.286848 & 0.573695 & 0.713152 \tabularnewline
138 & 0.263864 & 0.527727 & 0.736136 \tabularnewline
139 & 0.233012 & 0.466023 & 0.766988 \tabularnewline
140 & 0.242031 & 0.484063 & 0.757969 \tabularnewline
141 & 0.261837 & 0.523673 & 0.738163 \tabularnewline
142 & 0.241329 & 0.482658 & 0.758671 \tabularnewline
143 & 0.226257 & 0.452514 & 0.773743 \tabularnewline
144 & 0.22212 & 0.444239 & 0.77788 \tabularnewline
145 & 0.196545 & 0.393091 & 0.803455 \tabularnewline
146 & 0.307637 & 0.615274 & 0.692363 \tabularnewline
147 & 0.293507 & 0.587014 & 0.706493 \tabularnewline
148 & 0.274517 & 0.549033 & 0.725483 \tabularnewline
149 & 0.272629 & 0.545259 & 0.727371 \tabularnewline
150 & 0.293792 & 0.587585 & 0.706208 \tabularnewline
151 & 0.274155 & 0.54831 & 0.725845 \tabularnewline
152 & 0.268434 & 0.536869 & 0.731566 \tabularnewline
153 & 0.338608 & 0.677216 & 0.661392 \tabularnewline
154 & 0.295578 & 0.591155 & 0.704422 \tabularnewline
155 & 0.25238 & 0.504761 & 0.74762 \tabularnewline
156 & 0.259065 & 0.518131 & 0.740935 \tabularnewline
157 & 0.22013 & 0.440261 & 0.77987 \tabularnewline
158 & 0.271487 & 0.542975 & 0.728513 \tabularnewline
159 & 0.258418 & 0.516836 & 0.741582 \tabularnewline
160 & 0.215269 & 0.430538 & 0.784731 \tabularnewline
161 & 0.195161 & 0.390321 & 0.804839 \tabularnewline
162 & 0.199336 & 0.398672 & 0.800664 \tabularnewline
163 & 0.161317 & 0.322634 & 0.838683 \tabularnewline
164 & 0.142733 & 0.285467 & 0.857267 \tabularnewline
165 & 0.716524 & 0.566951 & 0.283476 \tabularnewline
166 & 0.737749 & 0.524502 & 0.262251 \tabularnewline
167 & 0.78697 & 0.426059 & 0.21303 \tabularnewline
168 & 0.906128 & 0.187744 & 0.0938722 \tabularnewline
169 & 0.918615 & 0.162771 & 0.0813855 \tabularnewline
170 & 0.911464 & 0.177072 & 0.0885362 \tabularnewline
171 & 0.996477 & 0.00704657 & 0.00352329 \tabularnewline
172 & 0.994199 & 0.011602 & 0.00580098 \tabularnewline
173 & 0.99231 & 0.0153791 & 0.00768954 \tabularnewline
174 & 0.988035 & 0.0239294 & 0.0119647 \tabularnewline
175 & 0.983444 & 0.0331116 & 0.0165558 \tabularnewline
176 & 0.972636 & 0.0547272 & 0.0273636 \tabularnewline
177 & 0.963278 & 0.0734443 & 0.0367221 \tabularnewline
178 & 0.940167 & 0.119666 & 0.0598331 \tabularnewline
179 & 0.907448 & 0.185105 & 0.0925523 \tabularnewline
180 & 0.865345 & 0.26931 & 0.134655 \tabularnewline
181 & 0.795062 & 0.409875 & 0.204938 \tabularnewline
182 & 0.707948 & 0.584104 & 0.292052 \tabularnewline
183 & 0.661206 & 0.677587 & 0.338794 \tabularnewline
184 & 0.540726 & 0.918549 & 0.459274 \tabularnewline
185 & 0.404207 & 0.808415 & 0.595793 \tabularnewline
186 & 0.276792 & 0.553585 & 0.723208 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230071&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]9[/C][C]0.00774262[/C][C]0.0154852[/C][C]0.992257[/C][/ROW]
[ROW][C]10[/C][C]0.00113301[/C][C]0.00226601[/C][C]0.998867[/C][/ROW]
[ROW][C]11[/C][C]0.000155457[/C][C]0.000310914[/C][C]0.999845[/C][/ROW]
[ROW][C]12[/C][C]2.224e-05[/C][C]4.44801e-05[/C][C]0.999978[/C][/ROW]
[ROW][C]13[/C][C]3.14729e-06[/C][C]6.29459e-06[/C][C]0.999997[/C][/ROW]
[ROW][C]14[/C][C]3.73628e-07[/C][C]7.47256e-07[/C][C]1[/C][/ROW]
[ROW][C]15[/C][C]1.01161e-05[/C][C]2.02323e-05[/C][C]0.99999[/C][/ROW]
[ROW][C]16[/C][C]2.38333e-06[/C][C]4.76665e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]17[/C][C]6.02102e-06[/C][C]1.2042e-05[/C][C]0.999994[/C][/ROW]
[ROW][C]18[/C][C]3.72724e-06[/C][C]7.45449e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]19[/C][C]9.4808e-07[/C][C]1.89616e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]20[/C][C]2.34833e-07[/C][C]4.69666e-07[/C][C]1[/C][/ROW]
[ROW][C]21[/C][C]2.70409e-07[/C][C]5.40817e-07[/C][C]1[/C][/ROW]
[ROW][C]22[/C][C]6.81152e-08[/C][C]1.3623e-07[/C][C]1[/C][/ROW]
[ROW][C]23[/C][C]2.73307e-07[/C][C]5.46614e-07[/C][C]1[/C][/ROW]
[ROW][C]24[/C][C]6.95309e-07[/C][C]1.39062e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]25[/C][C]2.41779e-06[/C][C]4.83557e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]26[/C][C]2.22297e-06[/C][C]4.44594e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]27[/C][C]4.89658e-06[/C][C]9.79317e-06[/C][C]0.999995[/C][/ROW]
[ROW][C]28[/C][C]3.66762e-06[/C][C]7.33524e-06[/C][C]0.999996[/C][/ROW]
[ROW][C]29[/C][C]1.46489e-06[/C][C]2.92977e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]30[/C][C]6.12101e-07[/C][C]1.2242e-06[/C][C]0.999999[/C][/ROW]
[ROW][C]31[/C][C]2.25369e-06[/C][C]4.50737e-06[/C][C]0.999998[/C][/ROW]
[ROW][C]32[/C][C]1.16591e-05[/C][C]2.33182e-05[/C][C]0.999988[/C][/ROW]
[ROW][C]33[/C][C]2.84362e-05[/C][C]5.68723e-05[/C][C]0.999972[/C][/ROW]
[ROW][C]34[/C][C]9.02657e-05[/C][C]0.000180531[/C][C]0.99991[/C][/ROW]
[ROW][C]35[/C][C]0.000178169[/C][C]0.000356339[/C][C]0.999822[/C][/ROW]
[ROW][C]36[/C][C]0.000225763[/C][C]0.000451526[/C][C]0.999774[/C][/ROW]
[ROW][C]37[/C][C]0.000134714[/C][C]0.000269428[/C][C]0.999865[/C][/ROW]
[ROW][C]38[/C][C]7.18164e-05[/C][C]0.000143633[/C][C]0.999928[/C][/ROW]
[ROW][C]39[/C][C]5.68842e-05[/C][C]0.000113768[/C][C]0.999943[/C][/ROW]
[ROW][C]40[/C][C]5.0848e-05[/C][C]0.000101696[/C][C]0.999949[/C][/ROW]
[ROW][C]41[/C][C]4.65646e-05[/C][C]9.31291e-05[/C][C]0.999953[/C][/ROW]
[ROW][C]42[/C][C]2.62102e-05[/C][C]5.24204e-05[/C][C]0.999974[/C][/ROW]
[ROW][C]43[/C][C]7.56487e-05[/C][C]0.000151297[/C][C]0.999924[/C][/ROW]
[ROW][C]44[/C][C]0.00027102[/C][C]0.00054204[/C][C]0.999729[/C][/ROW]
[ROW][C]45[/C][C]0.00139027[/C][C]0.00278054[/C][C]0.99861[/C][/ROW]
[ROW][C]46[/C][C]0.00372736[/C][C]0.00745473[/C][C]0.996273[/C][/ROW]
[ROW][C]47[/C][C]0.00902504[/C][C]0.0180501[/C][C]0.990975[/C][/ROW]
[ROW][C]48[/C][C]0.027541[/C][C]0.055082[/C][C]0.972459[/C][/ROW]
[ROW][C]49[/C][C]0.0312659[/C][C]0.0625317[/C][C]0.968734[/C][/ROW]
[ROW][C]50[/C][C]0.0284138[/C][C]0.0568276[/C][C]0.971586[/C][/ROW]
[ROW][C]51[/C][C]0.02541[/C][C]0.05082[/C][C]0.97459[/C][/ROW]
[ROW][C]52[/C][C]0.0305436[/C][C]0.0610872[/C][C]0.969456[/C][/ROW]
[ROW][C]53[/C][C]0.0275705[/C][C]0.055141[/C][C]0.972429[/C][/ROW]
[ROW][C]54[/C][C]0.0297692[/C][C]0.0595384[/C][C]0.970231[/C][/ROW]
[ROW][C]55[/C][C]0.0238123[/C][C]0.0476246[/C][C]0.976188[/C][/ROW]
[ROW][C]56[/C][C]0.0268965[/C][C]0.0537931[/C][C]0.973103[/C][/ROW]
[ROW][C]57[/C][C]0.0215144[/C][C]0.0430289[/C][C]0.978486[/C][/ROW]
[ROW][C]58[/C][C]0.0166463[/C][C]0.0332926[/C][C]0.983354[/C][/ROW]
[ROW][C]59[/C][C]0.0143963[/C][C]0.0287927[/C][C]0.985604[/C][/ROW]
[ROW][C]60[/C][C]0.0122325[/C][C]0.0244649[/C][C]0.987768[/C][/ROW]
[ROW][C]61[/C][C]0.00956753[/C][C]0.0191351[/C][C]0.990432[/C][/ROW]
[ROW][C]62[/C][C]0.0102513[/C][C]0.0205026[/C][C]0.989749[/C][/ROW]
[ROW][C]63[/C][C]0.0110746[/C][C]0.0221492[/C][C]0.988925[/C][/ROW]
[ROW][C]64[/C][C]0.0127001[/C][C]0.0254003[/C][C]0.9873[/C][/ROW]
[ROW][C]65[/C][C]0.0203388[/C][C]0.0406775[/C][C]0.979661[/C][/ROW]
[ROW][C]66[/C][C]0.0315546[/C][C]0.0631091[/C][C]0.968445[/C][/ROW]
[ROW][C]67[/C][C]0.0275939[/C][C]0.0551878[/C][C]0.972406[/C][/ROW]
[ROW][C]68[/C][C]0.0329368[/C][C]0.0658735[/C][C]0.967063[/C][/ROW]
[ROW][C]69[/C][C]0.0824349[/C][C]0.16487[/C][C]0.917565[/C][/ROW]
[ROW][C]70[/C][C]0.0728285[/C][C]0.145657[/C][C]0.927171[/C][/ROW]
[ROW][C]71[/C][C]0.0612494[/C][C]0.122499[/C][C]0.938751[/C][/ROW]
[ROW][C]72[/C][C]0.0521917[/C][C]0.104383[/C][C]0.947808[/C][/ROW]
[ROW][C]73[/C][C]0.0668574[/C][C]0.133715[/C][C]0.933143[/C][/ROW]
[ROW][C]74[/C][C]0.350669[/C][C]0.701338[/C][C]0.649331[/C][/ROW]
[ROW][C]75[/C][C]0.380874[/C][C]0.761747[/C][C]0.619126[/C][/ROW]
[ROW][C]76[/C][C]0.340415[/C][C]0.68083[/C][C]0.659585[/C][/ROW]
[ROW][C]77[/C][C]0.355834[/C][C]0.711668[/C][C]0.644166[/C][/ROW]
[ROW][C]78[/C][C]0.359484[/C][C]0.718967[/C][C]0.640516[/C][/ROW]
[ROW][C]79[/C][C]0.325755[/C][C]0.651511[/C][C]0.674245[/C][/ROW]
[ROW][C]80[/C][C]0.462315[/C][C]0.924631[/C][C]0.537685[/C][/ROW]
[ROW][C]81[/C][C]0.448782[/C][C]0.897564[/C][C]0.551218[/C][/ROW]
[ROW][C]82[/C][C]0.425279[/C][C]0.850557[/C][C]0.574721[/C][/ROW]
[ROW][C]83[/C][C]0.386214[/C][C]0.772428[/C][C]0.613786[/C][/ROW]
[ROW][C]84[/C][C]0.403377[/C][C]0.806755[/C][C]0.596623[/C][/ROW]
[ROW][C]85[/C][C]0.379827[/C][C]0.759655[/C][C]0.620173[/C][/ROW]
[ROW][C]86[/C][C]0.347473[/C][C]0.694947[/C][C]0.652527[/C][/ROW]
[ROW][C]87[/C][C]0.326804[/C][C]0.653608[/C][C]0.673196[/C][/ROW]
[ROW][C]88[/C][C]0.296928[/C][C]0.593855[/C][C]0.703072[/C][/ROW]
[ROW][C]89[/C][C]0.296385[/C][C]0.59277[/C][C]0.703615[/C][/ROW]
[ROW][C]90[/C][C]0.270828[/C][C]0.541656[/C][C]0.729172[/C][/ROW]
[ROW][C]91[/C][C]0.256115[/C][C]0.51223[/C][C]0.743885[/C][/ROW]
[ROW][C]92[/C][C]0.235093[/C][C]0.470185[/C][C]0.764907[/C][/ROW]
[ROW][C]93[/C][C]0.211828[/C][C]0.423656[/C][C]0.788172[/C][/ROW]
[ROW][C]94[/C][C]0.197895[/C][C]0.395789[/C][C]0.802105[/C][/ROW]
[ROW][C]95[/C][C]0.180794[/C][C]0.361589[/C][C]0.819206[/C][/ROW]
[ROW][C]96[/C][C]0.167633[/C][C]0.335266[/C][C]0.832367[/C][/ROW]
[ROW][C]97[/C][C]0.146035[/C][C]0.292069[/C][C]0.853965[/C][/ROW]
[ROW][C]98[/C][C]0.151517[/C][C]0.303034[/C][C]0.848483[/C][/ROW]
[ROW][C]99[/C][C]0.185762[/C][C]0.371523[/C][C]0.814238[/C][/ROW]
[ROW][C]100[/C][C]0.24619[/C][C]0.49238[/C][C]0.75381[/C][/ROW]
[ROW][C]101[/C][C]0.431836[/C][C]0.863672[/C][C]0.568164[/C][/ROW]
[ROW][C]102[/C][C]0.488475[/C][C]0.97695[/C][C]0.511525[/C][/ROW]
[ROW][C]103[/C][C]0.760186[/C][C]0.479628[/C][C]0.239814[/C][/ROW]
[ROW][C]104[/C][C]0.727036[/C][C]0.545929[/C][C]0.272964[/C][/ROW]
[ROW][C]105[/C][C]0.71705[/C][C]0.565901[/C][C]0.28295[/C][/ROW]
[ROW][C]106[/C][C]0.683028[/C][C]0.633945[/C][C]0.316972[/C][/ROW]
[ROW][C]107[/C][C]0.660944[/C][C]0.678112[/C][C]0.339056[/C][/ROW]
[ROW][C]108[/C][C]0.623634[/C][C]0.752732[/C][C]0.376366[/C][/ROW]
[ROW][C]109[/C][C]0.611701[/C][C]0.776599[/C][C]0.388299[/C][/ROW]
[ROW][C]110[/C][C]0.581993[/C][C]0.836015[/C][C]0.418007[/C][/ROW]
[ROW][C]111[/C][C]0.54376[/C][C]0.912481[/C][C]0.45624[/C][/ROW]
[ROW][C]112[/C][C]0.513476[/C][C]0.973049[/C][C]0.486524[/C][/ROW]
[ROW][C]113[/C][C]0.493461[/C][C]0.986923[/C][C]0.506539[/C][/ROW]
[ROW][C]114[/C][C]0.505975[/C][C]0.988049[/C][C]0.494025[/C][/ROW]
[ROW][C]115[/C][C]0.465289[/C][C]0.930578[/C][C]0.534711[/C][/ROW]
[ROW][C]116[/C][C]0.483735[/C][C]0.967471[/C][C]0.516265[/C][/ROW]
[ROW][C]117[/C][C]0.500415[/C][C]0.99917[/C][C]0.499585[/C][/ROW]
[ROW][C]118[/C][C]0.529182[/C][C]0.941637[/C][C]0.470818[/C][/ROW]
[ROW][C]119[/C][C]0.487422[/C][C]0.974845[/C][C]0.512578[/C][/ROW]
[ROW][C]120[/C][C]0.473951[/C][C]0.947902[/C][C]0.526049[/C][/ROW]
[ROW][C]121[/C][C]0.443569[/C][C]0.887137[/C][C]0.556431[/C][/ROW]
[ROW][C]122[/C][C]0.404104[/C][C]0.808208[/C][C]0.595896[/C][/ROW]
[ROW][C]123[/C][C]0.371948[/C][C]0.743896[/C][C]0.628052[/C][/ROW]
[ROW][C]124[/C][C]0.338554[/C][C]0.677108[/C][C]0.661446[/C][/ROW]
[ROW][C]125[/C][C]0.349463[/C][C]0.698927[/C][C]0.650537[/C][/ROW]
[ROW][C]126[/C][C]0.325591[/C][C]0.651182[/C][C]0.674409[/C][/ROW]
[ROW][C]127[/C][C]0.294866[/C][C]0.589733[/C][C]0.705134[/C][/ROW]
[ROW][C]128[/C][C]0.260083[/C][C]0.520166[/C][C]0.739917[/C][/ROW]
[ROW][C]129[/C][C]0.237206[/C][C]0.474412[/C][C]0.762794[/C][/ROW]
[ROW][C]130[/C][C]0.302181[/C][C]0.604362[/C][C]0.697819[/C][/ROW]
[ROW][C]131[/C][C]0.296198[/C][C]0.592396[/C][C]0.703802[/C][/ROW]
[ROW][C]132[/C][C]0.349759[/C][C]0.699518[/C][C]0.650241[/C][/ROW]
[ROW][C]133[/C][C]0.355333[/C][C]0.710665[/C][C]0.644667[/C][/ROW]
[ROW][C]134[/C][C]0.346485[/C][C]0.692971[/C][C]0.653515[/C][/ROW]
[ROW][C]135[/C][C]0.345321[/C][C]0.690642[/C][C]0.654679[/C][/ROW]
[ROW][C]136[/C][C]0.326218[/C][C]0.652437[/C][C]0.673782[/C][/ROW]
[ROW][C]137[/C][C]0.286848[/C][C]0.573695[/C][C]0.713152[/C][/ROW]
[ROW][C]138[/C][C]0.263864[/C][C]0.527727[/C][C]0.736136[/C][/ROW]
[ROW][C]139[/C][C]0.233012[/C][C]0.466023[/C][C]0.766988[/C][/ROW]
[ROW][C]140[/C][C]0.242031[/C][C]0.484063[/C][C]0.757969[/C][/ROW]
[ROW][C]141[/C][C]0.261837[/C][C]0.523673[/C][C]0.738163[/C][/ROW]
[ROW][C]142[/C][C]0.241329[/C][C]0.482658[/C][C]0.758671[/C][/ROW]
[ROW][C]143[/C][C]0.226257[/C][C]0.452514[/C][C]0.773743[/C][/ROW]
[ROW][C]144[/C][C]0.22212[/C][C]0.444239[/C][C]0.77788[/C][/ROW]
[ROW][C]145[/C][C]0.196545[/C][C]0.393091[/C][C]0.803455[/C][/ROW]
[ROW][C]146[/C][C]0.307637[/C][C]0.615274[/C][C]0.692363[/C][/ROW]
[ROW][C]147[/C][C]0.293507[/C][C]0.587014[/C][C]0.706493[/C][/ROW]
[ROW][C]148[/C][C]0.274517[/C][C]0.549033[/C][C]0.725483[/C][/ROW]
[ROW][C]149[/C][C]0.272629[/C][C]0.545259[/C][C]0.727371[/C][/ROW]
[ROW][C]150[/C][C]0.293792[/C][C]0.587585[/C][C]0.706208[/C][/ROW]
[ROW][C]151[/C][C]0.274155[/C][C]0.54831[/C][C]0.725845[/C][/ROW]
[ROW][C]152[/C][C]0.268434[/C][C]0.536869[/C][C]0.731566[/C][/ROW]
[ROW][C]153[/C][C]0.338608[/C][C]0.677216[/C][C]0.661392[/C][/ROW]
[ROW][C]154[/C][C]0.295578[/C][C]0.591155[/C][C]0.704422[/C][/ROW]
[ROW][C]155[/C][C]0.25238[/C][C]0.504761[/C][C]0.74762[/C][/ROW]
[ROW][C]156[/C][C]0.259065[/C][C]0.518131[/C][C]0.740935[/C][/ROW]
[ROW][C]157[/C][C]0.22013[/C][C]0.440261[/C][C]0.77987[/C][/ROW]
[ROW][C]158[/C][C]0.271487[/C][C]0.542975[/C][C]0.728513[/C][/ROW]
[ROW][C]159[/C][C]0.258418[/C][C]0.516836[/C][C]0.741582[/C][/ROW]
[ROW][C]160[/C][C]0.215269[/C][C]0.430538[/C][C]0.784731[/C][/ROW]
[ROW][C]161[/C][C]0.195161[/C][C]0.390321[/C][C]0.804839[/C][/ROW]
[ROW][C]162[/C][C]0.199336[/C][C]0.398672[/C][C]0.800664[/C][/ROW]
[ROW][C]163[/C][C]0.161317[/C][C]0.322634[/C][C]0.838683[/C][/ROW]
[ROW][C]164[/C][C]0.142733[/C][C]0.285467[/C][C]0.857267[/C][/ROW]
[ROW][C]165[/C][C]0.716524[/C][C]0.566951[/C][C]0.283476[/C][/ROW]
[ROW][C]166[/C][C]0.737749[/C][C]0.524502[/C][C]0.262251[/C][/ROW]
[ROW][C]167[/C][C]0.78697[/C][C]0.426059[/C][C]0.21303[/C][/ROW]
[ROW][C]168[/C][C]0.906128[/C][C]0.187744[/C][C]0.0938722[/C][/ROW]
[ROW][C]169[/C][C]0.918615[/C][C]0.162771[/C][C]0.0813855[/C][/ROW]
[ROW][C]170[/C][C]0.911464[/C][C]0.177072[/C][C]0.0885362[/C][/ROW]
[ROW][C]171[/C][C]0.996477[/C][C]0.00704657[/C][C]0.00352329[/C][/ROW]
[ROW][C]172[/C][C]0.994199[/C][C]0.011602[/C][C]0.00580098[/C][/ROW]
[ROW][C]173[/C][C]0.99231[/C][C]0.0153791[/C][C]0.00768954[/C][/ROW]
[ROW][C]174[/C][C]0.988035[/C][C]0.0239294[/C][C]0.0119647[/C][/ROW]
[ROW][C]175[/C][C]0.983444[/C][C]0.0331116[/C][C]0.0165558[/C][/ROW]
[ROW][C]176[/C][C]0.972636[/C][C]0.0547272[/C][C]0.0273636[/C][/ROW]
[ROW][C]177[/C][C]0.963278[/C][C]0.0734443[/C][C]0.0367221[/C][/ROW]
[ROW][C]178[/C][C]0.940167[/C][C]0.119666[/C][C]0.0598331[/C][/ROW]
[ROW][C]179[/C][C]0.907448[/C][C]0.185105[/C][C]0.0925523[/C][/ROW]
[ROW][C]180[/C][C]0.865345[/C][C]0.26931[/C][C]0.134655[/C][/ROW]
[ROW][C]181[/C][C]0.795062[/C][C]0.409875[/C][C]0.204938[/C][/ROW]
[ROW][C]182[/C][C]0.707948[/C][C]0.584104[/C][C]0.292052[/C][/ROW]
[ROW][C]183[/C][C]0.661206[/C][C]0.677587[/C][C]0.338794[/C][/ROW]
[ROW][C]184[/C][C]0.540726[/C][C]0.918549[/C][C]0.459274[/C][/ROW]
[ROW][C]185[/C][C]0.404207[/C][C]0.808415[/C][C]0.595793[/C][/ROW]
[ROW][C]186[/C][C]0.276792[/C][C]0.553585[/C][C]0.723208[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230071&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230071&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.007742620.01548520.992257
100.001133010.002266010.998867
110.0001554570.0003109140.999845
122.224e-054.44801e-050.999978
133.14729e-066.29459e-060.999997
143.73628e-077.47256e-071
151.01161e-052.02323e-050.99999
162.38333e-064.76665e-060.999998
176.02102e-061.2042e-050.999994
183.72724e-067.45449e-060.999996
199.4808e-071.89616e-060.999999
202.34833e-074.69666e-071
212.70409e-075.40817e-071
226.81152e-081.3623e-071
232.73307e-075.46614e-071
246.95309e-071.39062e-060.999999
252.41779e-064.83557e-060.999998
262.22297e-064.44594e-060.999998
274.89658e-069.79317e-060.999995
283.66762e-067.33524e-060.999996
291.46489e-062.92977e-060.999999
306.12101e-071.2242e-060.999999
312.25369e-064.50737e-060.999998
321.16591e-052.33182e-050.999988
332.84362e-055.68723e-050.999972
349.02657e-050.0001805310.99991
350.0001781690.0003563390.999822
360.0002257630.0004515260.999774
370.0001347140.0002694280.999865
387.18164e-050.0001436330.999928
395.68842e-050.0001137680.999943
405.0848e-050.0001016960.999949
414.65646e-059.31291e-050.999953
422.62102e-055.24204e-050.999974
437.56487e-050.0001512970.999924
440.000271020.000542040.999729
450.001390270.002780540.99861
460.003727360.007454730.996273
470.009025040.01805010.990975
480.0275410.0550820.972459
490.03126590.06253170.968734
500.02841380.05682760.971586
510.025410.050820.97459
520.03054360.06108720.969456
530.02757050.0551410.972429
540.02976920.05953840.970231
550.02381230.04762460.976188
560.02689650.05379310.973103
570.02151440.04302890.978486
580.01664630.03329260.983354
590.01439630.02879270.985604
600.01223250.02446490.987768
610.009567530.01913510.990432
620.01025130.02050260.989749
630.01107460.02214920.988925
640.01270010.02540030.9873
650.02033880.04067750.979661
660.03155460.06310910.968445
670.02759390.05518780.972406
680.03293680.06587350.967063
690.08243490.164870.917565
700.07282850.1456570.927171
710.06124940.1224990.938751
720.05219170.1043830.947808
730.06685740.1337150.933143
740.3506690.7013380.649331
750.3808740.7617470.619126
760.3404150.680830.659585
770.3558340.7116680.644166
780.3594840.7189670.640516
790.3257550.6515110.674245
800.4623150.9246310.537685
810.4487820.8975640.551218
820.4252790.8505570.574721
830.3862140.7724280.613786
840.4033770.8067550.596623
850.3798270.7596550.620173
860.3474730.6949470.652527
870.3268040.6536080.673196
880.2969280.5938550.703072
890.2963850.592770.703615
900.2708280.5416560.729172
910.2561150.512230.743885
920.2350930.4701850.764907
930.2118280.4236560.788172
940.1978950.3957890.802105
950.1807940.3615890.819206
960.1676330.3352660.832367
970.1460350.2920690.853965
980.1515170.3030340.848483
990.1857620.3715230.814238
1000.246190.492380.75381
1010.4318360.8636720.568164
1020.4884750.976950.511525
1030.7601860.4796280.239814
1040.7270360.5459290.272964
1050.717050.5659010.28295
1060.6830280.6339450.316972
1070.6609440.6781120.339056
1080.6236340.7527320.376366
1090.6117010.7765990.388299
1100.5819930.8360150.418007
1110.543760.9124810.45624
1120.5134760.9730490.486524
1130.4934610.9869230.506539
1140.5059750.9880490.494025
1150.4652890.9305780.534711
1160.4837350.9674710.516265
1170.5004150.999170.499585
1180.5291820.9416370.470818
1190.4874220.9748450.512578
1200.4739510.9479020.526049
1210.4435690.8871370.556431
1220.4041040.8082080.595896
1230.3719480.7438960.628052
1240.3385540.6771080.661446
1250.3494630.6989270.650537
1260.3255910.6511820.674409
1270.2948660.5897330.705134
1280.2600830.5201660.739917
1290.2372060.4744120.762794
1300.3021810.6043620.697819
1310.2961980.5923960.703802
1320.3497590.6995180.650241
1330.3553330.7106650.644667
1340.3464850.6929710.653515
1350.3453210.6906420.654679
1360.3262180.6524370.673782
1370.2868480.5736950.713152
1380.2638640.5277270.736136
1390.2330120.4660230.766988
1400.2420310.4840630.757969
1410.2618370.5236730.738163
1420.2413290.4826580.758671
1430.2262570.4525140.773743
1440.222120.4442390.77788
1450.1965450.3930910.803455
1460.3076370.6152740.692363
1470.2935070.5870140.706493
1480.2745170.5490330.725483
1490.2726290.5452590.727371
1500.2937920.5875850.706208
1510.2741550.548310.725845
1520.2684340.5368690.731566
1530.3386080.6772160.661392
1540.2955780.5911550.704422
1550.252380.5047610.74762
1560.2590650.5181310.740935
1570.220130.4402610.77987
1580.2714870.5429750.728513
1590.2584180.5168360.741582
1600.2152690.4305380.784731
1610.1951610.3903210.804839
1620.1993360.3986720.800664
1630.1613170.3226340.838683
1640.1427330.2854670.857267
1650.7165240.5669510.283476
1660.7377490.5245020.262251
1670.786970.4260590.21303
1680.9061280.1877440.0938722
1690.9186150.1627710.0813855
1700.9114640.1770720.0885362
1710.9964770.007046570.00352329
1720.9941990.0116020.00580098
1730.992310.01537910.00768954
1740.9880350.02392940.0119647
1750.9834440.03311160.0165558
1760.9726360.05472720.0273636
1770.9632780.07344430.0367221
1780.9401670.1196660.0598331
1790.9074480.1851050.0925523
1800.8653450.269310.134655
1810.7950620.4098750.204938
1820.7079480.5841040.292052
1830.6612060.6775870.338794
1840.5407260.9185490.459274
1850.4042070.8084150.595793
1860.2767920.5535850.723208







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level380.213483NOK
5% type I error level540.303371NOK
10% type I error level670.376404NOK

\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 & 38 & 0.213483 & NOK \tabularnewline
5% type I error level & 54 & 0.303371 & NOK \tabularnewline
10% type I error level & 67 & 0.376404 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230071&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]38[/C][C]0.213483[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]54[/C][C]0.303371[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]67[/C][C]0.376404[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230071&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230071&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level380.213483NOK
5% type I error level540.303371NOK
10% type I error level670.376404NOK



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