Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareMultiple Regression
Date of computationSat, 03 Nov 2012 10:00:56 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/03/t13519512976ur78ha4bvtoy1g.htm/, Retrieved Sun, 03 Jul 2022 13:56:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185727, Retrieved Sun, 03 Jul 2022 13:56:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Decreasing Compet...] [2010-11-17 09:04:39] [b98453cac15ba1066b407e146608df68]
- R PD  [Multiple Regression] [Month effect Door...] [2011-11-22 17:52:50] [59e9c089bdd600b584669dddc48fbcc3]
-  M        [Multiple Regression] [] [2012-11-03 14:00:56] [f3ca428ef12de0510f6752588dd725b0] [Current]
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Dataseries X:
9	13	38	14
9	16	32	18
9	19	35	11
9	15	33	12
9	14	37	16
9	13	29	18
9	19	31	14
9	15	36	14
9	14	35	15
9	15	38	15
9	16	31	17
9	16	34	19
9	16	35	10
9	16	38	16
9	17	37	18
9	15	33	14
9	15	32	14
9	20	38	17
9	18	38	14
9	16	32	16
9	16	33	18
9	16	31	11
9	19	38	14
9	16	39	12
9	17	32	17
9	17	32	9
9	16	35	16
9	15	37	14
9	16	33	15
9	14	33	11
9	15	31	16
9	12	32	13
9	14	31	17
9	16	37	15
9	14	30	14
9	10	33	16
9	10	31	9
9	14	33	15
9	16	31	17
9	16	33	13
9	16	32	15
9	14	33	16
9	20	32	16
9	14	33	12
9	14	28	15
9	11	35	11
9	14	39	15
9	15	34	15
9	16	38	17
9	14	32	13
9	16	38	16
9	14	30	14
9	12	33	11
9	16	38	12
9	9	32	12
9	14	35	15
9	16	34	16
9	16	34	15
9	15	36	12
9	16	34	12
9	12	28	8
9	16	34	13
9	16	35	11
9	14	35	14
9	16	31	15
9	17	34	9
10	18	37	10
10	18	35	11
10	12	27	12
10	16	40	15
10	10	37	15
10	14	36	14
10	18	38	16
10	18	39	15
10	16	41	15
10	17	27	13
10	16	30	12
10	16	37	17
10	13	31	13
10	16	31	15
10	16	27	13
10	16	36	15
10	15	37	15
10	15	33	16
10	16	34	15
10	14	31	14
10	16	39	15
10	16	34	14
10	15	32	13
10	12	33	7
10	17	36	17
10	16	32	13
10	15	41	15
10	13	28	14
10	16	30	13
10	16	36	16
10	16	35	12
10	16	31	14
10	14	34	17
10	16	36	15
10	16	36	17
10	20	35	12
10	15	37	16
10	16	28	11
10	13	39	15
10	17	32	9
10	16	35	16
10	16	39	15
10	12	35	10
10	16	42	10
10	16	34	15
10	17	33	11
10	13	41	13
10	12	33	14
10	18	34	18
10	14	32	16
10	14	40	14
10	13	40	14
10	16	35	14
10	13	36	14
10	16	37	12
10	13	27	14
10	16	39	15
10	15	38	15
10	16	31	15
10	15	33	13
10	17	32	17
10	15	39	17
10	12	36	19
10	16	33	15
10	10	33	13
10	16	32	9
10	12	37	15
10	14	30	15
10	15	38	15
10	13	29	16
10	15	22	11
10	11	35	14
10	12	35	11
10	11	34	15
10	16	35	13
10	15	34	15
10	17	37	16
10	16	35	14
10	10	23	15
10	18	31	16
10	13	27	16
10	16	36	11
10	13	31	12
10	10	32	9
10	15	39	16
10	16	37	13
10	16	38	16
10	14	39	12
10	10	31	13
10	17	32	13
10	13	37	14
10	15	36	19
10	16	32	13
10	12	38	12
10	13	36	13
11	13	26	10
11	12	26	14
11	17	33	16
11	15	39	10
11	10	30	11
11	14	33	14
11	11	25	12
11	13	38	9
11	16	37	9
11	12	31	11
11	16	37	16
11	12	35	9
11	9	25	13
11	12	28	16
11	15	35	13
11	12	33	9
11	12	30	12
11	14	31	16
11	12	37	11
11	16	36	14
11	11	30	13
11	19	36	15
11	15	32	14
11	8	28	16
11	16	36	13
11	17	34	14
11	12	31	15
11	11	28	13
11	11	36	11
11	14	36	11
11	16	40	14
11	12	33	15
11	16	37	11
11	13	32	15
11	15	38	12
11	16	31	14
11	16	37	14
11	14	33	8
11	16	32	13
11	16	30	9
11	14	30	15
11	11	31	17
11	12	32	13
11	15	34	15
11	15	36	15
11	16	37	14
11	16	36	16
11	11	33	13
11	15	33	16
11	12	33	9
11	12	44	16
11	15	39	11
11	15	32	10
11	16	35	11
11	14	25	15
11	17	35	17
11	14	34	14
11	13	35	8
11	15	39	15
11	13	33	11
11	14	36	16
11	15	32	10
11	12	32	15
11	13	36	9
11	8	36	16
11	14	32	19
11	14	34	12
11	11	33	8
11	12	35	11
11	13	30	14
11	10	38	9
11	16	34	15
11	18	33	13
11	13	32	16
11	11	31	11
11	4	30	12
11	13	27	13
11	16	31	10
11	10	30	11
11	12	32	12
11	12	35	8
11	10	28	12
11	13	33	12
11	15	31	15
11	12	35	11
11	14	35	13
11	10	32	14
11	12	21	10
11	12	20	12
11	11	34	15
11	10	32	13
11	12	34	13
11	16	32	13
11	12	33	12
11	14	33	12
11	16	37	9
11	14	32	9
11	13	34	15
11	4	30	10
11	15	30	14
11	11	38	15
11	11	36	7
11	14	32	14




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 13 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185727&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185727&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185727&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 time13 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Doorzettingsvermogen[t] = + 15.5209862838333 -0.832153398799417month[t] + 0.157157668320555Zelfstandig[t] + 0.14049895036519Stressbestendig[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Doorzettingsvermogen[t] =  +  15.5209862838333 -0.832153398799417month[t] +  0.157157668320555Zelfstandig[t] +  0.14049895036519Stressbestendig[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185727&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Doorzettingsvermogen[t] =  +  15.5209862838333 -0.832153398799417month[t] +  0.157157668320555Zelfstandig[t] +  0.14049895036519Stressbestendig[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185727&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185727&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
Doorzettingsvermogen[t] = + 15.5209862838333 -0.832153398799417month[t] + 0.157157668320555Zelfstandig[t] + 0.14049895036519Stressbestendig[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.52098628383332.5391746.112600
month-0.8321533987994170.18009-4.62086e-063e-06
Zelfstandig0.1571576683205550.0374134.20063.7e-051.8e-05
Stressbestendig0.140498950365190.0568552.47120.0141090.007054

\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) & 15.5209862838333 & 2.539174 & 6.1126 & 0 & 0 \tabularnewline
month & -0.832153398799417 & 0.18009 & -4.6208 & 6e-06 & 3e-06 \tabularnewline
Zelfstandig & 0.157157668320555 & 0.037413 & 4.2006 & 3.7e-05 & 1.8e-05 \tabularnewline
Stressbestendig & 0.14049895036519 & 0.056855 & 2.4712 & 0.014109 & 0.007054 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185727&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]15.5209862838333[/C][C]2.539174[/C][C]6.1126[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]month[/C][C]-0.832153398799417[/C][C]0.18009[/C][C]-4.6208[/C][C]6e-06[/C][C]3e-06[/C][/ROW]
[ROW][C]Zelfstandig[/C][C]0.157157668320555[/C][C]0.037413[/C][C]4.2006[/C][C]3.7e-05[/C][C]1.8e-05[/C][/ROW]
[ROW][C]Stressbestendig[/C][C]0.14049895036519[/C][C]0.056855[/C][C]2.4712[/C][C]0.014109[/C][C]0.007054[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185727&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185727&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)15.52098628383332.5391746.112600
month-0.8321533987994170.18009-4.62086e-063e-06
Zelfstandig0.1571576683205550.0374134.20063.7e-051.8e-05
Stressbestendig0.140498950365190.0568552.47120.0141090.007054







Multiple Linear Regression - Regression Statistics
Multiple R0.434624837311673
R-squared0.188898749208199
Adjusted R-squared0.179539888622139
F-TEST (value)20.1839473375186
F-TEST (DF numerator)3
F-TEST (DF denominator)260
p-value8.61988258549218e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.22460154570965
Sum Squared Residuals1286.70152966518

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.434624837311673 \tabularnewline
R-squared & 0.188898749208199 \tabularnewline
Adjusted R-squared & 0.179539888622139 \tabularnewline
F-TEST (value) & 20.1839473375186 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 260 \tabularnewline
p-value & 8.61988258549218e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.22460154570965 \tabularnewline
Sum Squared Residuals & 1286.70152966518 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185727&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.434624837311673[/C][/ROW]
[ROW][C]R-squared[/C][C]0.188898749208199[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.179539888622139[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]20.1839473375186[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]260[/C][/ROW]
[ROW][C]p-value[/C][C]8.61988258549218e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.22460154570965[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1286.70152966518[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185727&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185727&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 R0.434624837311673
R-squared0.188898749208199
Adjusted R-squared0.179539888622139
F-TEST (value)20.1839473375186
F-TEST (DF numerator)3
F-TEST (DF denominator)260
p-value8.61988258549218e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.22460154570965
Sum Squared Residuals1286.70152966518







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.9705823959323-2.97058239593227
21615.58963218746970.410367812530263
31915.07761253987513.92238746012493
41514.90379615359920.0962038464008496
51416.0944226283421-2.09442262834213
61315.1181591825081-2.11815918250807
71914.87047871768844.12952128231158
81515.6562670592912-0.656267059291195
91415.6396083413358-1.63960834133583
101516.1110813462975-1.11108134629749
111615.2919755687840.708024431216009
121616.044446474476-0.0444464744760357
131614.93711358950991.06288641049012
141616.2515802966627-0.251580296662684
151716.37542052907250.62457947092749
161515.1847940543295-0.18479405432953
171515.027636386009-0.0276363860089756
182016.39207924702793.60792075297213
191815.97058239593232.0294176040677
201615.30863428673940.691365713260644
211615.74678985579030.253210144209709
221614.44898186659291.55101813340715
231915.97058239593233.0294176040677
241615.84674216352250.153257836477521
251715.44913323710451.55086676289545
261714.3251416341832.67485836581697
271615.7801072917010.21989270829898
281515.8134247276117-0.813424727611749
291615.32529300469470.67470699530528
301414.763297203234-0.76329720323396
311515.1514766184188-0.151476618418801
321214.8871374356438-2.88713743564379
331415.291975568784-1.29197556878399
341615.95392367797690.0460763220230606
351414.7133210493679-0.713321049367866
361015.4657919550599-5.46579195505991
371014.1679839658625-4.16798396586247
381415.3252930046947-1.32529300469472
391615.2919755687840.708024431216009
401615.04429510396430.95570489603566
411615.16813533637420.831864663625834
421415.4657919550599-1.46579195505991
432015.30863428673944.69136571326064
441414.9037961535991-0.90379615359915
451414.5395046630919-0.539504663091947
461115.0776125398751-4.07761253987507
471416.2682390146181-2.26823901461805
481515.4824506730153-0.482450673015275
491616.3920792470279-0.392079247027874
501414.8871374356438-0.887137435643785
511616.2515802966627-0.251580296662684
521414.7133210493679-0.713321049367866
531214.763297203234-2.76329720323396
541615.68958449520190.310415504798076
55914.7466384852786-5.74663848527859
561415.6396083413358-1.63960834133583
571615.62294962338050.377050376619535
581615.48245067301530.517549326984725
591515.3752691585608-0.375269158560814
601615.06095382191970.939046178080295
611213.5560120105356-1.55601201053562
621615.20145277228490.798547227715105
631615.07761253987510.922387460124931
641415.4991093909706-1.49910939097064
651615.01097766805360.989022331946389
661714.63945697082412.36054302917587
671814.41927552735163.58072447264843
681814.24545914107573.75454085892435
691213.1286967448764-1.1286967448764
701615.59324328413920.406756715860814
711015.1217702791775-5.12177027917752
721414.8241136604918-0.824113660491777
731815.41942689786332.58057310213673
741815.43608561581862.56391438418137
751615.75040095245970.249599047540259
761713.26919569524163.73080430475841
771613.60016974983812.39983025016193
781615.40276817990790.597231820092098
791313.8978263685238-0.897826368523813
801614.17882426925421.82117573074581
811613.26919569524162.73080430475841
821614.9646126108571.03538738914303
831515.1217702791775-0.121770279177522
841514.63363855626050.366361443739507
851614.65029727421591.34970272578414
861414.038325318889-0.0383253188890034
871615.43608561581860.563914384181368
881614.50979832385071.49020167614933
891514.05498403684440.945015963155632
901213.3691480029738-1.36914800297378
911715.24561051158731.75438948841265
921614.05498403684441.94501596315563
931515.7504009524597-0.750400952459741
941313.5668523139273-0.566852313927339
951613.74066870020332.25933129979674
961615.10511156122220.894888438777843
971614.38595809144081.61404190855916
981614.0383253188891.961674681111
991414.9312951749462-0.931295174946238
1001614.9646126108571.03538738914303
1011615.24561051158730.754389488412653
1022014.38595809144085.61404190855916
1031515.2622692295427-0.262269229542712
1041613.14535546283182.85464453716823
1051315.4360856158186-2.43608561581863
1061713.49298823538363.50701176461639
1071614.94795389290161.0520461070984
1081615.43608561581860.563914384181368
1091214.1049601907105-2.10496019071046
1101615.20506386895430.794936131045655
1111614.65029727421591.34970272578414
1121713.93114380443453.06885619556546
1131315.4694030517294-2.46940305172936
1141214.3526406555301-2.35264065553011
1151815.07179412531142.92820587468857
1161414.4764808879399-0.476480887939938
1171415.452744333774-1.452744333774
1181315.452744333774-2.452744333774
1191614.66695599217121.33304400782878
1201314.8241136604918-1.82411366049178
1211614.7002734280821.29972657191805
1221313.4096946456068-0.409694645606785
1231615.43608561581860.563914384181368
1241515.2789279474981-0.278927947498077
1251614.17882426925421.82117573074581
1261514.21214170516490.787858294835077
1271714.61697983830512.38302016169487
1281515.717083516549-0.717083516549012
1291215.5266084123177-3.52660841231773
1301614.49313960589531.5068603941047
1311014.2121417051649-4.21214170516492
1321613.49298823538362.50701176461639
1331215.1217702791775-3.12177027917752
1341414.0216666009336-0.0216666009336388
1351515.2789279474981-0.278927947498077
1361314.0050078829783-1.00500788297827
1371512.20240945290842.79759054709156
1381114.6669559921712-3.66695599217122
1391214.2454591410757-2.24545914107565
1401114.6502972742159-3.65029727421586
1411614.5264570418061.47354295819397
1421514.65029727421590.349702725784142
1431715.26226922954271.73773077045729
1441614.66695599217121.33304400782878
1451012.9215629226898-2.92156292268976
1461814.31932321961943.68067678038062
1471313.6906925463372-0.690692546337165
1481614.40261680939621.59738319060379
1491313.7573274181586-0.757327418158623
1501013.4929882353836-3.49298823538361
1511515.5765845661838-0.576584566183822
1521614.84077237844711.15922762155286
1531615.41942689786330.580573102136733
1541415.0145887647231-1.01458876472306
1551013.8978263685238-3.89782636852381
1561714.05498403684442.94501596315563
1571314.9812713288123-1.98127132881233
1581515.5266084123177-0.526608412317728
1591614.05498403684441.94501596315563
1601214.8574310964025-2.85743109640251
1611314.6836147101266-1.68361471012659
1621311.85838777702611.14161222297395
1631212.4203835784868-0.420383578486812
1641713.80148515746113.19851484253892
1651513.90143746519331.09856253480674
1661012.6275174006735-2.62751740067346
1671413.52048725673070.479512743269305
1681111.9822280094359-0.982228009435877
1691313.6037808465075-0.603780846507519
1701613.4466231781872.55337682181304
1711212.784675068994-0.784675068994016
1721614.43011583074331.56988416925671
1731213.1323078415459-1.13230784154585
174912.1227269598011-3.12272695980107
1751213.0156968158583-1.0156968158583
1761513.69430364300661.30569635699339
1771212.8179925049047-0.817992504904745
1781212.7680163510387-0.768016351038651
1791413.487169820820.512830179180034
1801213.7276210789173-1.72762107891734
1811613.99196026169242.00803973830764
1821112.9085153014038-1.90851530140384
1831914.13245921205754.86754078794245
1841513.36332958841011.63667041158986
185813.0156968158583-5.0156968158583
1861613.85146131132722.14853868867283
1871713.67764492505133.32235507494875
1881213.3466708704548-1.34667087045478
1891112.5941999647627-1.59419996476273
1901113.5704634105968-2.57046341059679
1911413.57046341059680.429536589403211
1921614.62059093497461.37940906502542
1931213.6609862070959-1.66098620709589
1941613.72762107891732.27237892108266
1951313.5038285387753-0.503828538775331
1961514.02527769760310.974722302396911
1971613.20617192008962.79382807991041
1981614.14911793001291.85088206998709
1991412.67749355453961.32250644546045
2001613.2228306380452.77716936195505
2011612.34651949994313.65348050005692
2021413.18951320213420.810486797865779
2031113.6276687711852-2.62766877118516
2041213.222830638045-1.22283063804495
2051513.81814387541641.18185612458356
2061514.13245921205750.86754078794245
2071614.14911793001291.85088206998709
2081614.27295816242271.72704183757726
2091113.3799883063655-2.37998830636551
2101513.80148515746111.19851484253892
2111212.8179925049047-0.817992504904745
2121215.5302195089872-3.53021950898718
2131514.04193641555850.958063584441546
2141512.80133378694942.19866621305062
2151613.41330574227622.58669425772377
2161412.40372486053141.59627513946855
2171714.25629944446742.74370055553262
2181413.67764492505130.32235507494875
2191312.99180889118070.00819110881933573
2201514.60393221701920.396067782980786
2211313.0989904056351-0.0989904056351251
2221414.2729581624227-0.27295816242274
2231512.80133378694942.19866621305062
2241213.5038285387753-1.50382853877533
2251313.2894655098664-0.289465509866409
226814.2729581624227-6.27295816242274
2271414.0658243402361-0.0658243402360914
2281413.39664702432090.60335297567913
2291112.6774935545396-1.67749355453955
2301213.4133057422762-1.41330574227623
2311313.049014251769-0.0490142517690312
2321013.6037808465075-3.60378084650752
2331613.81814387541642.18185612458356
2341813.37998830636554.6200116936345
2351313.6443274891405-0.644327489140521
2361112.784675068994-1.78467506899402
237412.7680163510386-8.76801635103865
2381312.43704229644220.562957703557823
2391612.64417611862883.35582388137117
2401012.6275174006735-2.62751740067346
2411213.0823316876798-1.08233168767976
2421212.9918088911807-0.991808891180664
2431012.4537010143975-2.45370101439754
2441313.2394893560003-0.239489356000315
2451513.34667087045481.65332912954522
2461213.4133057422762-1.41330574227623
2471413.69430364300660.305696356993385
2481013.3633295884101-3.36332958841014
2491211.07259943542330.927400564576722
2501211.19643966783310.803560332166896
2511113.8181438754164-2.81814387541644
2521013.222830638045-3.22283063804495
2531213.5371459746861-1.53714597468606
2541613.2228306380452.77716936195505
2551213.2394893560003-1.23948935600032
2561413.23948935600030.760510643999685
2571613.4466231781872.55337682181304
2581412.66083483658421.33916516341581
2591313.8181438754164-0.81814387541644
260412.4870184503083-8.48701845030827
2611513.0490142517691.95098574823097
2621114.4467745486987-3.44677454869866
2631113.008467609136-2.00846760913603
2641413.36332958841010.636670411589859

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 15.9705823959323 & -2.97058239593227 \tabularnewline
2 & 16 & 15.5896321874697 & 0.410367812530263 \tabularnewline
3 & 19 & 15.0776125398751 & 3.92238746012493 \tabularnewline
4 & 15 & 14.9037961535992 & 0.0962038464008496 \tabularnewline
5 & 14 & 16.0944226283421 & -2.09442262834213 \tabularnewline
6 & 13 & 15.1181591825081 & -2.11815918250807 \tabularnewline
7 & 19 & 14.8704787176884 & 4.12952128231158 \tabularnewline
8 & 15 & 15.6562670592912 & -0.656267059291195 \tabularnewline
9 & 14 & 15.6396083413358 & -1.63960834133583 \tabularnewline
10 & 15 & 16.1110813462975 & -1.11108134629749 \tabularnewline
11 & 16 & 15.291975568784 & 0.708024431216009 \tabularnewline
12 & 16 & 16.044446474476 & -0.0444464744760357 \tabularnewline
13 & 16 & 14.9371135895099 & 1.06288641049012 \tabularnewline
14 & 16 & 16.2515802966627 & -0.251580296662684 \tabularnewline
15 & 17 & 16.3754205290725 & 0.62457947092749 \tabularnewline
16 & 15 & 15.1847940543295 & -0.18479405432953 \tabularnewline
17 & 15 & 15.027636386009 & -0.0276363860089756 \tabularnewline
18 & 20 & 16.3920792470279 & 3.60792075297213 \tabularnewline
19 & 18 & 15.9705823959323 & 2.0294176040677 \tabularnewline
20 & 16 & 15.3086342867394 & 0.691365713260644 \tabularnewline
21 & 16 & 15.7467898557903 & 0.253210144209709 \tabularnewline
22 & 16 & 14.4489818665929 & 1.55101813340715 \tabularnewline
23 & 19 & 15.9705823959323 & 3.0294176040677 \tabularnewline
24 & 16 & 15.8467421635225 & 0.153257836477521 \tabularnewline
25 & 17 & 15.4491332371045 & 1.55086676289545 \tabularnewline
26 & 17 & 14.325141634183 & 2.67485836581697 \tabularnewline
27 & 16 & 15.780107291701 & 0.21989270829898 \tabularnewline
28 & 15 & 15.8134247276117 & -0.813424727611749 \tabularnewline
29 & 16 & 15.3252930046947 & 0.67470699530528 \tabularnewline
30 & 14 & 14.763297203234 & -0.76329720323396 \tabularnewline
31 & 15 & 15.1514766184188 & -0.151476618418801 \tabularnewline
32 & 12 & 14.8871374356438 & -2.88713743564379 \tabularnewline
33 & 14 & 15.291975568784 & -1.29197556878399 \tabularnewline
34 & 16 & 15.9539236779769 & 0.0460763220230606 \tabularnewline
35 & 14 & 14.7133210493679 & -0.713321049367866 \tabularnewline
36 & 10 & 15.4657919550599 & -5.46579195505991 \tabularnewline
37 & 10 & 14.1679839658625 & -4.16798396586247 \tabularnewline
38 & 14 & 15.3252930046947 & -1.32529300469472 \tabularnewline
39 & 16 & 15.291975568784 & 0.708024431216009 \tabularnewline
40 & 16 & 15.0442951039643 & 0.95570489603566 \tabularnewline
41 & 16 & 15.1681353363742 & 0.831864663625834 \tabularnewline
42 & 14 & 15.4657919550599 & -1.46579195505991 \tabularnewline
43 & 20 & 15.3086342867394 & 4.69136571326064 \tabularnewline
44 & 14 & 14.9037961535991 & -0.90379615359915 \tabularnewline
45 & 14 & 14.5395046630919 & -0.539504663091947 \tabularnewline
46 & 11 & 15.0776125398751 & -4.07761253987507 \tabularnewline
47 & 14 & 16.2682390146181 & -2.26823901461805 \tabularnewline
48 & 15 & 15.4824506730153 & -0.482450673015275 \tabularnewline
49 & 16 & 16.3920792470279 & -0.392079247027874 \tabularnewline
50 & 14 & 14.8871374356438 & -0.887137435643785 \tabularnewline
51 & 16 & 16.2515802966627 & -0.251580296662684 \tabularnewline
52 & 14 & 14.7133210493679 & -0.713321049367866 \tabularnewline
53 & 12 & 14.763297203234 & -2.76329720323396 \tabularnewline
54 & 16 & 15.6895844952019 & 0.310415504798076 \tabularnewline
55 & 9 & 14.7466384852786 & -5.74663848527859 \tabularnewline
56 & 14 & 15.6396083413358 & -1.63960834133583 \tabularnewline
57 & 16 & 15.6229496233805 & 0.377050376619535 \tabularnewline
58 & 16 & 15.4824506730153 & 0.517549326984725 \tabularnewline
59 & 15 & 15.3752691585608 & -0.375269158560814 \tabularnewline
60 & 16 & 15.0609538219197 & 0.939046178080295 \tabularnewline
61 & 12 & 13.5560120105356 & -1.55601201053562 \tabularnewline
62 & 16 & 15.2014527722849 & 0.798547227715105 \tabularnewline
63 & 16 & 15.0776125398751 & 0.922387460124931 \tabularnewline
64 & 14 & 15.4991093909706 & -1.49910939097064 \tabularnewline
65 & 16 & 15.0109776680536 & 0.989022331946389 \tabularnewline
66 & 17 & 14.6394569708241 & 2.36054302917587 \tabularnewline
67 & 18 & 14.4192755273516 & 3.58072447264843 \tabularnewline
68 & 18 & 14.2454591410757 & 3.75454085892435 \tabularnewline
69 & 12 & 13.1286967448764 & -1.1286967448764 \tabularnewline
70 & 16 & 15.5932432841392 & 0.406756715860814 \tabularnewline
71 & 10 & 15.1217702791775 & -5.12177027917752 \tabularnewline
72 & 14 & 14.8241136604918 & -0.824113660491777 \tabularnewline
73 & 18 & 15.4194268978633 & 2.58057310213673 \tabularnewline
74 & 18 & 15.4360856158186 & 2.56391438418137 \tabularnewline
75 & 16 & 15.7504009524597 & 0.249599047540259 \tabularnewline
76 & 17 & 13.2691956952416 & 3.73080430475841 \tabularnewline
77 & 16 & 13.6001697498381 & 2.39983025016193 \tabularnewline
78 & 16 & 15.4027681799079 & 0.597231820092098 \tabularnewline
79 & 13 & 13.8978263685238 & -0.897826368523813 \tabularnewline
80 & 16 & 14.1788242692542 & 1.82117573074581 \tabularnewline
81 & 16 & 13.2691956952416 & 2.73080430475841 \tabularnewline
82 & 16 & 14.964612610857 & 1.03538738914303 \tabularnewline
83 & 15 & 15.1217702791775 & -0.121770279177522 \tabularnewline
84 & 15 & 14.6336385562605 & 0.366361443739507 \tabularnewline
85 & 16 & 14.6502972742159 & 1.34970272578414 \tabularnewline
86 & 14 & 14.038325318889 & -0.0383253188890034 \tabularnewline
87 & 16 & 15.4360856158186 & 0.563914384181368 \tabularnewline
88 & 16 & 14.5097983238507 & 1.49020167614933 \tabularnewline
89 & 15 & 14.0549840368444 & 0.945015963155632 \tabularnewline
90 & 12 & 13.3691480029738 & -1.36914800297378 \tabularnewline
91 & 17 & 15.2456105115873 & 1.75438948841265 \tabularnewline
92 & 16 & 14.0549840368444 & 1.94501596315563 \tabularnewline
93 & 15 & 15.7504009524597 & -0.750400952459741 \tabularnewline
94 & 13 & 13.5668523139273 & -0.566852313927339 \tabularnewline
95 & 16 & 13.7406687002033 & 2.25933129979674 \tabularnewline
96 & 16 & 15.1051115612222 & 0.894888438777843 \tabularnewline
97 & 16 & 14.3859580914408 & 1.61404190855916 \tabularnewline
98 & 16 & 14.038325318889 & 1.961674681111 \tabularnewline
99 & 14 & 14.9312951749462 & -0.931295174946238 \tabularnewline
100 & 16 & 14.964612610857 & 1.03538738914303 \tabularnewline
101 & 16 & 15.2456105115873 & 0.754389488412653 \tabularnewline
102 & 20 & 14.3859580914408 & 5.61404190855916 \tabularnewline
103 & 15 & 15.2622692295427 & -0.262269229542712 \tabularnewline
104 & 16 & 13.1453554628318 & 2.85464453716823 \tabularnewline
105 & 13 & 15.4360856158186 & -2.43608561581863 \tabularnewline
106 & 17 & 13.4929882353836 & 3.50701176461639 \tabularnewline
107 & 16 & 14.9479538929016 & 1.0520461070984 \tabularnewline
108 & 16 & 15.4360856158186 & 0.563914384181368 \tabularnewline
109 & 12 & 14.1049601907105 & -2.10496019071046 \tabularnewline
110 & 16 & 15.2050638689543 & 0.794936131045655 \tabularnewline
111 & 16 & 14.6502972742159 & 1.34970272578414 \tabularnewline
112 & 17 & 13.9311438044345 & 3.06885619556546 \tabularnewline
113 & 13 & 15.4694030517294 & -2.46940305172936 \tabularnewline
114 & 12 & 14.3526406555301 & -2.35264065553011 \tabularnewline
115 & 18 & 15.0717941253114 & 2.92820587468857 \tabularnewline
116 & 14 & 14.4764808879399 & -0.476480887939938 \tabularnewline
117 & 14 & 15.452744333774 & -1.452744333774 \tabularnewline
118 & 13 & 15.452744333774 & -2.452744333774 \tabularnewline
119 & 16 & 14.6669559921712 & 1.33304400782878 \tabularnewline
120 & 13 & 14.8241136604918 & -1.82411366049178 \tabularnewline
121 & 16 & 14.700273428082 & 1.29972657191805 \tabularnewline
122 & 13 & 13.4096946456068 & -0.409694645606785 \tabularnewline
123 & 16 & 15.4360856158186 & 0.563914384181368 \tabularnewline
124 & 15 & 15.2789279474981 & -0.278927947498077 \tabularnewline
125 & 16 & 14.1788242692542 & 1.82117573074581 \tabularnewline
126 & 15 & 14.2121417051649 & 0.787858294835077 \tabularnewline
127 & 17 & 14.6169798383051 & 2.38302016169487 \tabularnewline
128 & 15 & 15.717083516549 & -0.717083516549012 \tabularnewline
129 & 12 & 15.5266084123177 & -3.52660841231773 \tabularnewline
130 & 16 & 14.4931396058953 & 1.5068603941047 \tabularnewline
131 & 10 & 14.2121417051649 & -4.21214170516492 \tabularnewline
132 & 16 & 13.4929882353836 & 2.50701176461639 \tabularnewline
133 & 12 & 15.1217702791775 & -3.12177027917752 \tabularnewline
134 & 14 & 14.0216666009336 & -0.0216666009336388 \tabularnewline
135 & 15 & 15.2789279474981 & -0.278927947498077 \tabularnewline
136 & 13 & 14.0050078829783 & -1.00500788297827 \tabularnewline
137 & 15 & 12.2024094529084 & 2.79759054709156 \tabularnewline
138 & 11 & 14.6669559921712 & -3.66695599217122 \tabularnewline
139 & 12 & 14.2454591410757 & -2.24545914107565 \tabularnewline
140 & 11 & 14.6502972742159 & -3.65029727421586 \tabularnewline
141 & 16 & 14.526457041806 & 1.47354295819397 \tabularnewline
142 & 15 & 14.6502972742159 & 0.349702725784142 \tabularnewline
143 & 17 & 15.2622692295427 & 1.73773077045729 \tabularnewline
144 & 16 & 14.6669559921712 & 1.33304400782878 \tabularnewline
145 & 10 & 12.9215629226898 & -2.92156292268976 \tabularnewline
146 & 18 & 14.3193232196194 & 3.68067678038062 \tabularnewline
147 & 13 & 13.6906925463372 & -0.690692546337165 \tabularnewline
148 & 16 & 14.4026168093962 & 1.59738319060379 \tabularnewline
149 & 13 & 13.7573274181586 & -0.757327418158623 \tabularnewline
150 & 10 & 13.4929882353836 & -3.49298823538361 \tabularnewline
151 & 15 & 15.5765845661838 & -0.576584566183822 \tabularnewline
152 & 16 & 14.8407723784471 & 1.15922762155286 \tabularnewline
153 & 16 & 15.4194268978633 & 0.580573102136733 \tabularnewline
154 & 14 & 15.0145887647231 & -1.01458876472306 \tabularnewline
155 & 10 & 13.8978263685238 & -3.89782636852381 \tabularnewline
156 & 17 & 14.0549840368444 & 2.94501596315563 \tabularnewline
157 & 13 & 14.9812713288123 & -1.98127132881233 \tabularnewline
158 & 15 & 15.5266084123177 & -0.526608412317728 \tabularnewline
159 & 16 & 14.0549840368444 & 1.94501596315563 \tabularnewline
160 & 12 & 14.8574310964025 & -2.85743109640251 \tabularnewline
161 & 13 & 14.6836147101266 & -1.68361471012659 \tabularnewline
162 & 13 & 11.8583877770261 & 1.14161222297395 \tabularnewline
163 & 12 & 12.4203835784868 & -0.420383578486812 \tabularnewline
164 & 17 & 13.8014851574611 & 3.19851484253892 \tabularnewline
165 & 15 & 13.9014374651933 & 1.09856253480674 \tabularnewline
166 & 10 & 12.6275174006735 & -2.62751740067346 \tabularnewline
167 & 14 & 13.5204872567307 & 0.479512743269305 \tabularnewline
168 & 11 & 11.9822280094359 & -0.982228009435877 \tabularnewline
169 & 13 & 13.6037808465075 & -0.603780846507519 \tabularnewline
170 & 16 & 13.446623178187 & 2.55337682181304 \tabularnewline
171 & 12 & 12.784675068994 & -0.784675068994016 \tabularnewline
172 & 16 & 14.4301158307433 & 1.56988416925671 \tabularnewline
173 & 12 & 13.1323078415459 & -1.13230784154585 \tabularnewline
174 & 9 & 12.1227269598011 & -3.12272695980107 \tabularnewline
175 & 12 & 13.0156968158583 & -1.0156968158583 \tabularnewline
176 & 15 & 13.6943036430066 & 1.30569635699339 \tabularnewline
177 & 12 & 12.8179925049047 & -0.817992504904745 \tabularnewline
178 & 12 & 12.7680163510387 & -0.768016351038651 \tabularnewline
179 & 14 & 13.48716982082 & 0.512830179180034 \tabularnewline
180 & 12 & 13.7276210789173 & -1.72762107891734 \tabularnewline
181 & 16 & 13.9919602616924 & 2.00803973830764 \tabularnewline
182 & 11 & 12.9085153014038 & -1.90851530140384 \tabularnewline
183 & 19 & 14.1324592120575 & 4.86754078794245 \tabularnewline
184 & 15 & 13.3633295884101 & 1.63667041158986 \tabularnewline
185 & 8 & 13.0156968158583 & -5.0156968158583 \tabularnewline
186 & 16 & 13.8514613113272 & 2.14853868867283 \tabularnewline
187 & 17 & 13.6776449250513 & 3.32235507494875 \tabularnewline
188 & 12 & 13.3466708704548 & -1.34667087045478 \tabularnewline
189 & 11 & 12.5941999647627 & -1.59419996476273 \tabularnewline
190 & 11 & 13.5704634105968 & -2.57046341059679 \tabularnewline
191 & 14 & 13.5704634105968 & 0.429536589403211 \tabularnewline
192 & 16 & 14.6205909349746 & 1.37940906502542 \tabularnewline
193 & 12 & 13.6609862070959 & -1.66098620709589 \tabularnewline
194 & 16 & 13.7276210789173 & 2.27237892108266 \tabularnewline
195 & 13 & 13.5038285387753 & -0.503828538775331 \tabularnewline
196 & 15 & 14.0252776976031 & 0.974722302396911 \tabularnewline
197 & 16 & 13.2061719200896 & 2.79382807991041 \tabularnewline
198 & 16 & 14.1491179300129 & 1.85088206998709 \tabularnewline
199 & 14 & 12.6774935545396 & 1.32250644546045 \tabularnewline
200 & 16 & 13.222830638045 & 2.77716936195505 \tabularnewline
201 & 16 & 12.3465194999431 & 3.65348050005692 \tabularnewline
202 & 14 & 13.1895132021342 & 0.810486797865779 \tabularnewline
203 & 11 & 13.6276687711852 & -2.62766877118516 \tabularnewline
204 & 12 & 13.222830638045 & -1.22283063804495 \tabularnewline
205 & 15 & 13.8181438754164 & 1.18185612458356 \tabularnewline
206 & 15 & 14.1324592120575 & 0.86754078794245 \tabularnewline
207 & 16 & 14.1491179300129 & 1.85088206998709 \tabularnewline
208 & 16 & 14.2729581624227 & 1.72704183757726 \tabularnewline
209 & 11 & 13.3799883063655 & -2.37998830636551 \tabularnewline
210 & 15 & 13.8014851574611 & 1.19851484253892 \tabularnewline
211 & 12 & 12.8179925049047 & -0.817992504904745 \tabularnewline
212 & 12 & 15.5302195089872 & -3.53021950898718 \tabularnewline
213 & 15 & 14.0419364155585 & 0.958063584441546 \tabularnewline
214 & 15 & 12.8013337869494 & 2.19866621305062 \tabularnewline
215 & 16 & 13.4133057422762 & 2.58669425772377 \tabularnewline
216 & 14 & 12.4037248605314 & 1.59627513946855 \tabularnewline
217 & 17 & 14.2562994444674 & 2.74370055553262 \tabularnewline
218 & 14 & 13.6776449250513 & 0.32235507494875 \tabularnewline
219 & 13 & 12.9918088911807 & 0.00819110881933573 \tabularnewline
220 & 15 & 14.6039322170192 & 0.396067782980786 \tabularnewline
221 & 13 & 13.0989904056351 & -0.0989904056351251 \tabularnewline
222 & 14 & 14.2729581624227 & -0.27295816242274 \tabularnewline
223 & 15 & 12.8013337869494 & 2.19866621305062 \tabularnewline
224 & 12 & 13.5038285387753 & -1.50382853877533 \tabularnewline
225 & 13 & 13.2894655098664 & -0.289465509866409 \tabularnewline
226 & 8 & 14.2729581624227 & -6.27295816242274 \tabularnewline
227 & 14 & 14.0658243402361 & -0.0658243402360914 \tabularnewline
228 & 14 & 13.3966470243209 & 0.60335297567913 \tabularnewline
229 & 11 & 12.6774935545396 & -1.67749355453955 \tabularnewline
230 & 12 & 13.4133057422762 & -1.41330574227623 \tabularnewline
231 & 13 & 13.049014251769 & -0.0490142517690312 \tabularnewline
232 & 10 & 13.6037808465075 & -3.60378084650752 \tabularnewline
233 & 16 & 13.8181438754164 & 2.18185612458356 \tabularnewline
234 & 18 & 13.3799883063655 & 4.6200116936345 \tabularnewline
235 & 13 & 13.6443274891405 & -0.644327489140521 \tabularnewline
236 & 11 & 12.784675068994 & -1.78467506899402 \tabularnewline
237 & 4 & 12.7680163510386 & -8.76801635103865 \tabularnewline
238 & 13 & 12.4370422964422 & 0.562957703557823 \tabularnewline
239 & 16 & 12.6441761186288 & 3.35582388137117 \tabularnewline
240 & 10 & 12.6275174006735 & -2.62751740067346 \tabularnewline
241 & 12 & 13.0823316876798 & -1.08233168767976 \tabularnewline
242 & 12 & 12.9918088911807 & -0.991808891180664 \tabularnewline
243 & 10 & 12.4537010143975 & -2.45370101439754 \tabularnewline
244 & 13 & 13.2394893560003 & -0.239489356000315 \tabularnewline
245 & 15 & 13.3466708704548 & 1.65332912954522 \tabularnewline
246 & 12 & 13.4133057422762 & -1.41330574227623 \tabularnewline
247 & 14 & 13.6943036430066 & 0.305696356993385 \tabularnewline
248 & 10 & 13.3633295884101 & -3.36332958841014 \tabularnewline
249 & 12 & 11.0725994354233 & 0.927400564576722 \tabularnewline
250 & 12 & 11.1964396678331 & 0.803560332166896 \tabularnewline
251 & 11 & 13.8181438754164 & -2.81814387541644 \tabularnewline
252 & 10 & 13.222830638045 & -3.22283063804495 \tabularnewline
253 & 12 & 13.5371459746861 & -1.53714597468606 \tabularnewline
254 & 16 & 13.222830638045 & 2.77716936195505 \tabularnewline
255 & 12 & 13.2394893560003 & -1.23948935600032 \tabularnewline
256 & 14 & 13.2394893560003 & 0.760510643999685 \tabularnewline
257 & 16 & 13.446623178187 & 2.55337682181304 \tabularnewline
258 & 14 & 12.6608348365842 & 1.33916516341581 \tabularnewline
259 & 13 & 13.8181438754164 & -0.81814387541644 \tabularnewline
260 & 4 & 12.4870184503083 & -8.48701845030827 \tabularnewline
261 & 15 & 13.049014251769 & 1.95098574823097 \tabularnewline
262 & 11 & 14.4467745486987 & -3.44677454869866 \tabularnewline
263 & 11 & 13.008467609136 & -2.00846760913603 \tabularnewline
264 & 14 & 13.3633295884101 & 0.636670411589859 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185727&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]13[/C][C]15.9705823959323[/C][C]-2.97058239593227[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.5896321874697[/C][C]0.410367812530263[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]15.0776125398751[/C][C]3.92238746012493[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]14.9037961535992[/C][C]0.0962038464008496[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.0944226283421[/C][C]-2.09442262834213[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]15.1181591825081[/C][C]-2.11815918250807[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]14.8704787176884[/C][C]4.12952128231158[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]15.6562670592912[/C][C]-0.656267059291195[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.6396083413358[/C][C]-1.63960834133583[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]16.1110813462975[/C][C]-1.11108134629749[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]15.291975568784[/C][C]0.708024431216009[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.044446474476[/C][C]-0.0444464744760357[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]14.9371135895099[/C][C]1.06288641049012[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]16.2515802966627[/C][C]-0.251580296662684[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]16.3754205290725[/C][C]0.62457947092749[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.1847940543295[/C][C]-0.18479405432953[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]15.027636386009[/C][C]-0.0276363860089756[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.3920792470279[/C][C]3.60792075297213[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.9705823959323[/C][C]2.0294176040677[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.3086342867394[/C][C]0.691365713260644[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.7467898557903[/C][C]0.253210144209709[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]14.4489818665929[/C][C]1.55101813340715[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]15.9705823959323[/C][C]3.0294176040677[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]15.8467421635225[/C][C]0.153257836477521[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.4491332371045[/C][C]1.55086676289545[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]14.325141634183[/C][C]2.67485836581697[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.780107291701[/C][C]0.21989270829898[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]15.8134247276117[/C][C]-0.813424727611749[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.3252930046947[/C][C]0.67470699530528[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.763297203234[/C][C]-0.76329720323396[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.1514766184188[/C][C]-0.151476618418801[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]14.8871374356438[/C][C]-2.88713743564379[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]15.291975568784[/C][C]-1.29197556878399[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.9539236779769[/C][C]0.0460763220230606[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14.7133210493679[/C][C]-0.713321049367866[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]15.4657919550599[/C][C]-5.46579195505991[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]14.1679839658625[/C][C]-4.16798396586247[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.3252930046947[/C][C]-1.32529300469472[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]15.291975568784[/C][C]0.708024431216009[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]15.0442951039643[/C][C]0.95570489603566[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]15.1681353363742[/C][C]0.831864663625834[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.4657919550599[/C][C]-1.46579195505991[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]15.3086342867394[/C][C]4.69136571326064[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.9037961535991[/C][C]-0.90379615359915[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.5395046630919[/C][C]-0.539504663091947[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.0776125398751[/C][C]-4.07761253987507[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.2682390146181[/C][C]-2.26823901461805[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.4824506730153[/C][C]-0.482450673015275[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]16.3920792470279[/C][C]-0.392079247027874[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]14.8871374356438[/C][C]-0.887137435643785[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.2515802966627[/C][C]-0.251580296662684[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.7133210493679[/C][C]-0.713321049367866[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.763297203234[/C][C]-2.76329720323396[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.6895844952019[/C][C]0.310415504798076[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]14.7466384852786[/C][C]-5.74663848527859[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]15.6396083413358[/C][C]-1.63960834133583[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.6229496233805[/C][C]0.377050376619535[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.4824506730153[/C][C]0.517549326984725[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.3752691585608[/C][C]-0.375269158560814[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]15.0609538219197[/C][C]0.939046178080295[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]13.5560120105356[/C][C]-1.55601201053562[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.2014527722849[/C][C]0.798547227715105[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]15.0776125398751[/C][C]0.922387460124931[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]15.4991093909706[/C][C]-1.49910939097064[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.0109776680536[/C][C]0.989022331946389[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]14.6394569708241[/C][C]2.36054302917587[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]14.4192755273516[/C][C]3.58072447264843[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.2454591410757[/C][C]3.75454085892435[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]13.1286967448764[/C][C]-1.1286967448764[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.5932432841392[/C][C]0.406756715860814[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]15.1217702791775[/C][C]-5.12177027917752[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.8241136604918[/C][C]-0.824113660491777[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]15.4194268978633[/C][C]2.58057310213673[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]15.4360856158186[/C][C]2.56391438418137[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.7504009524597[/C][C]0.249599047540259[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.2691956952416[/C][C]3.73080430475841[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]13.6001697498381[/C][C]2.39983025016193[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]15.4027681799079[/C][C]0.597231820092098[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]13.8978263685238[/C][C]-0.897826368523813[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]14.1788242692542[/C][C]1.82117573074581[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]13.2691956952416[/C][C]2.73080430475841[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]14.964612610857[/C][C]1.03538738914303[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.1217702791775[/C][C]-0.121770279177522[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.6336385562605[/C][C]0.366361443739507[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.6502972742159[/C][C]1.34970272578414[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.038325318889[/C][C]-0.0383253188890034[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.4360856158186[/C][C]0.563914384181368[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.5097983238507[/C][C]1.49020167614933[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.0549840368444[/C][C]0.945015963155632[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.3691480029738[/C][C]-1.36914800297378[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]15.2456105115873[/C][C]1.75438948841265[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]14.0549840368444[/C][C]1.94501596315563[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.7504009524597[/C][C]-0.750400952459741[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.5668523139273[/C][C]-0.566852313927339[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]13.7406687002033[/C][C]2.25933129979674[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.1051115612222[/C][C]0.894888438777843[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]14.3859580914408[/C][C]1.61404190855916[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]14.038325318889[/C][C]1.961674681111[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.9312951749462[/C][C]-0.931295174946238[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]14.964612610857[/C][C]1.03538738914303[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]15.2456105115873[/C][C]0.754389488412653[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]14.3859580914408[/C][C]5.61404190855916[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]15.2622692295427[/C][C]-0.262269229542712[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]13.1453554628318[/C][C]2.85464453716823[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]15.4360856158186[/C][C]-2.43608561581863[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]13.4929882353836[/C][C]3.50701176461639[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]14.9479538929016[/C][C]1.0520461070984[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]15.4360856158186[/C][C]0.563914384181368[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]14.1049601907105[/C][C]-2.10496019071046[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.2050638689543[/C][C]0.794936131045655[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]14.6502972742159[/C][C]1.34970272578414[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]13.9311438044345[/C][C]3.06885619556546[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]15.4694030517294[/C][C]-2.46940305172936[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.3526406555301[/C][C]-2.35264065553011[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]15.0717941253114[/C][C]2.92820587468857[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14.4764808879399[/C][C]-0.476480887939938[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]15.452744333774[/C][C]-1.452744333774[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]15.452744333774[/C][C]-2.452744333774[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]14.6669559921712[/C][C]1.33304400782878[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.8241136604918[/C][C]-1.82411366049178[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]14.700273428082[/C][C]1.29972657191805[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]13.4096946456068[/C][C]-0.409694645606785[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]15.4360856158186[/C][C]0.563914384181368[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.2789279474981[/C][C]-0.278927947498077[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]14.1788242692542[/C][C]1.82117573074581[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.2121417051649[/C][C]0.787858294835077[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]14.6169798383051[/C][C]2.38302016169487[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]15.717083516549[/C][C]-0.717083516549012[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]15.5266084123177[/C][C]-3.52660841231773[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]14.4931396058953[/C][C]1.5068603941047[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]14.2121417051649[/C][C]-4.21214170516492[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4929882353836[/C][C]2.50701176461639[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]15.1217702791775[/C][C]-3.12177027917752[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]14.0216666009336[/C][C]-0.0216666009336388[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.2789279474981[/C][C]-0.278927947498077[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]14.0050078829783[/C][C]-1.00500788297827[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]12.2024094529084[/C][C]2.79759054709156[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]14.6669559921712[/C][C]-3.66695599217122[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]14.2454591410757[/C][C]-2.24545914107565[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]14.6502972742159[/C][C]-3.65029727421586[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]14.526457041806[/C][C]1.47354295819397[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]14.6502972742159[/C][C]0.349702725784142[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]15.2622692295427[/C][C]1.73773077045729[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.6669559921712[/C][C]1.33304400782878[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]12.9215629226898[/C][C]-2.92156292268976[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]14.3193232196194[/C][C]3.68067678038062[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]13.6906925463372[/C][C]-0.690692546337165[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.4026168093962[/C][C]1.59738319060379[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]13.7573274181586[/C][C]-0.757327418158623[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]13.4929882353836[/C][C]-3.49298823538361[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]15.5765845661838[/C][C]-0.576584566183822[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]14.8407723784471[/C][C]1.15922762155286[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]15.4194268978633[/C][C]0.580573102136733[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]15.0145887647231[/C][C]-1.01458876472306[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]13.8978263685238[/C][C]-3.89782636852381[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]14.0549840368444[/C][C]2.94501596315563[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]14.9812713288123[/C][C]-1.98127132881233[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]15.5266084123177[/C][C]-0.526608412317728[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.0549840368444[/C][C]1.94501596315563[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]14.8574310964025[/C][C]-2.85743109640251[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]14.6836147101266[/C][C]-1.68361471012659[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]11.8583877770261[/C][C]1.14161222297395[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.4203835784868[/C][C]-0.420383578486812[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]13.8014851574611[/C][C]3.19851484253892[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.9014374651933[/C][C]1.09856253480674[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]12.6275174006735[/C][C]-2.62751740067346[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]13.5204872567307[/C][C]0.479512743269305[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]11.9822280094359[/C][C]-0.982228009435877[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]13.6037808465075[/C][C]-0.603780846507519[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]13.446623178187[/C][C]2.55337682181304[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]12.784675068994[/C][C]-0.784675068994016[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.4301158307433[/C][C]1.56988416925671[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.1323078415459[/C][C]-1.13230784154585[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]12.1227269598011[/C][C]-3.12272695980107[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]13.0156968158583[/C][C]-1.0156968158583[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]13.6943036430066[/C][C]1.30569635699339[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.8179925049047[/C][C]-0.817992504904745[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.7680163510387[/C][C]-0.768016351038651[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.48716982082[/C][C]0.512830179180034[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.7276210789173[/C][C]-1.72762107891734[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]13.9919602616924[/C][C]2.00803973830764[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]12.9085153014038[/C][C]-1.90851530140384[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]14.1324592120575[/C][C]4.86754078794245[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]13.3633295884101[/C][C]1.63667041158986[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]13.0156968158583[/C][C]-5.0156968158583[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]13.8514613113272[/C][C]2.14853868867283[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]13.6776449250513[/C][C]3.32235507494875[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]13.3466708704548[/C][C]-1.34667087045478[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]12.5941999647627[/C][C]-1.59419996476273[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]13.5704634105968[/C][C]-2.57046341059679[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]13.5704634105968[/C][C]0.429536589403211[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]14.6205909349746[/C][C]1.37940906502542[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]13.6609862070959[/C][C]-1.66098620709589[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]13.7276210789173[/C][C]2.27237892108266[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.5038285387753[/C][C]-0.503828538775331[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]14.0252776976031[/C][C]0.974722302396911[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]13.2061719200896[/C][C]2.79382807991041[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]14.1491179300129[/C][C]1.85088206998709[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.6774935545396[/C][C]1.32250644546045[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]13.222830638045[/C][C]2.77716936195505[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]12.3465194999431[/C][C]3.65348050005692[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.1895132021342[/C][C]0.810486797865779[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.6276687711852[/C][C]-2.62766877118516[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]13.222830638045[/C][C]-1.22283063804495[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]13.8181438754164[/C][C]1.18185612458356[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.1324592120575[/C][C]0.86754078794245[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.1491179300129[/C][C]1.85088206998709[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]14.2729581624227[/C][C]1.72704183757726[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.3799883063655[/C][C]-2.37998830636551[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.8014851574611[/C][C]1.19851484253892[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]12.8179925049047[/C][C]-0.817992504904745[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.5302195089872[/C][C]-3.53021950898718[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.0419364155585[/C][C]0.958063584441546[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.8013337869494[/C][C]2.19866621305062[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]13.4133057422762[/C][C]2.58669425772377[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]12.4037248605314[/C][C]1.59627513946855[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.2562994444674[/C][C]2.74370055553262[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.6776449250513[/C][C]0.32235507494875[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]12.9918088911807[/C][C]0.00819110881933573[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]14.6039322170192[/C][C]0.396067782980786[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]13.0989904056351[/C][C]-0.0989904056351251[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.2729581624227[/C][C]-0.27295816242274[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]12.8013337869494[/C][C]2.19866621305062[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.5038285387753[/C][C]-1.50382853877533[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]13.2894655098664[/C][C]-0.289465509866409[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]14.2729581624227[/C][C]-6.27295816242274[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]14.0658243402361[/C][C]-0.0658243402360914[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]13.3966470243209[/C][C]0.60335297567913[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.6774935545396[/C][C]-1.67749355453955[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]13.4133057422762[/C][C]-1.41330574227623[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]13.049014251769[/C][C]-0.0490142517690312[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.6037808465075[/C][C]-3.60378084650752[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]13.8181438754164[/C][C]2.18185612458356[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]13.3799883063655[/C][C]4.6200116936345[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.6443274891405[/C][C]-0.644327489140521[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.784675068994[/C][C]-1.78467506899402[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]12.7680163510386[/C][C]-8.76801635103865[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]12.4370422964422[/C][C]0.562957703557823[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]12.6441761186288[/C][C]3.35582388137117[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]12.6275174006735[/C][C]-2.62751740067346[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]13.0823316876798[/C][C]-1.08233168767976[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]12.9918088911807[/C][C]-0.991808891180664[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]12.4537010143975[/C][C]-2.45370101439754[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]13.2394893560003[/C][C]-0.239489356000315[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.3466708704548[/C][C]1.65332912954522[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]13.4133057422762[/C][C]-1.41330574227623[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]13.6943036430066[/C][C]0.305696356993385[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]13.3633295884101[/C][C]-3.36332958841014[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]11.0725994354233[/C][C]0.927400564576722[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.1964396678331[/C][C]0.803560332166896[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]13.8181438754164[/C][C]-2.81814387541644[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]13.222830638045[/C][C]-3.22283063804495[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]13.5371459746861[/C][C]-1.53714597468606[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]13.222830638045[/C][C]2.77716936195505[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.2394893560003[/C][C]-1.23948935600032[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.2394893560003[/C][C]0.760510643999685[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]13.446623178187[/C][C]2.55337682181304[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]12.6608348365842[/C][C]1.33916516341581[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]13.8181438754164[/C][C]-0.81814387541644[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]12.4870184503083[/C][C]-8.48701845030827[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.049014251769[/C][C]1.95098574823097[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]14.4467745486987[/C][C]-3.44677454869866[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]13.008467609136[/C][C]-2.00846760913603[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.3633295884101[/C][C]0.636670411589859[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185727&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185727&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
11315.9705823959323-2.97058239593227
21615.58963218746970.410367812530263
31915.07761253987513.92238746012493
41514.90379615359920.0962038464008496
51416.0944226283421-2.09442262834213
61315.1181591825081-2.11815918250807
71914.87047871768844.12952128231158
81515.6562670592912-0.656267059291195
91415.6396083413358-1.63960834133583
101516.1110813462975-1.11108134629749
111615.2919755687840.708024431216009
121616.044446474476-0.0444464744760357
131614.93711358950991.06288641049012
141616.2515802966627-0.251580296662684
151716.37542052907250.62457947092749
161515.1847940543295-0.18479405432953
171515.027636386009-0.0276363860089756
182016.39207924702793.60792075297213
191815.97058239593232.0294176040677
201615.30863428673940.691365713260644
211615.74678985579030.253210144209709
221614.44898186659291.55101813340715
231915.97058239593233.0294176040677
241615.84674216352250.153257836477521
251715.44913323710451.55086676289545
261714.3251416341832.67485836581697
271615.7801072917010.21989270829898
281515.8134247276117-0.813424727611749
291615.32529300469470.67470699530528
301414.763297203234-0.76329720323396
311515.1514766184188-0.151476618418801
321214.8871374356438-2.88713743564379
331415.291975568784-1.29197556878399
341615.95392367797690.0460763220230606
351414.7133210493679-0.713321049367866
361015.4657919550599-5.46579195505991
371014.1679839658625-4.16798396586247
381415.3252930046947-1.32529300469472
391615.2919755687840.708024431216009
401615.04429510396430.95570489603566
411615.16813533637420.831864663625834
421415.4657919550599-1.46579195505991
432015.30863428673944.69136571326064
441414.9037961535991-0.90379615359915
451414.5395046630919-0.539504663091947
461115.0776125398751-4.07761253987507
471416.2682390146181-2.26823901461805
481515.4824506730153-0.482450673015275
491616.3920792470279-0.392079247027874
501414.8871374356438-0.887137435643785
511616.2515802966627-0.251580296662684
521414.7133210493679-0.713321049367866
531214.763297203234-2.76329720323396
541615.68958449520190.310415504798076
55914.7466384852786-5.74663848527859
561415.6396083413358-1.63960834133583
571615.62294962338050.377050376619535
581615.48245067301530.517549326984725
591515.3752691585608-0.375269158560814
601615.06095382191970.939046178080295
611213.5560120105356-1.55601201053562
621615.20145277228490.798547227715105
631615.07761253987510.922387460124931
641415.4991093909706-1.49910939097064
651615.01097766805360.989022331946389
661714.63945697082412.36054302917587
671814.41927552735163.58072447264843
681814.24545914107573.75454085892435
691213.1286967448764-1.1286967448764
701615.59324328413920.406756715860814
711015.1217702791775-5.12177027917752
721414.8241136604918-0.824113660491777
731815.41942689786332.58057310213673
741815.43608561581862.56391438418137
751615.75040095245970.249599047540259
761713.26919569524163.73080430475841
771613.60016974983812.39983025016193
781615.40276817990790.597231820092098
791313.8978263685238-0.897826368523813
801614.17882426925421.82117573074581
811613.26919569524162.73080430475841
821614.9646126108571.03538738914303
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891514.05498403684440.945015963155632
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1001614.9646126108571.03538738914303
1011615.24561051158730.754389488412653
1022014.38595809144085.61404190855916
1031515.2622692295427-0.262269229542712
1041613.14535546283182.85464453716823
1051315.4360856158186-2.43608561581863
1061713.49298823538363.50701176461639
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1081615.43608561581860.563914384181368
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1121713.93114380443453.06885619556546
1131315.4694030517294-2.46940305172936
1141214.3526406555301-2.35264065553011
1151815.07179412531142.92820587468857
1161414.4764808879399-0.476480887939938
1171415.452744333774-1.452744333774
1181315.452744333774-2.452744333774
1191614.66695599217121.33304400782878
1201314.8241136604918-1.82411366049178
1211614.7002734280821.29972657191805
1221313.4096946456068-0.409694645606785
1231615.43608561581860.563914384181368
1241515.2789279474981-0.278927947498077
1251614.17882426925421.82117573074581
1261514.21214170516490.787858294835077
1271714.61697983830512.38302016169487
1281515.717083516549-0.717083516549012
1291215.5266084123177-3.52660841231773
1301614.49313960589531.5068603941047
1311014.2121417051649-4.21214170516492
1321613.49298823538362.50701176461639
1331215.1217702791775-3.12177027917752
1341414.0216666009336-0.0216666009336388
1351515.2789279474981-0.278927947498077
1361314.0050078829783-1.00500788297827
1371512.20240945290842.79759054709156
1381114.6669559921712-3.66695599217122
1391214.2454591410757-2.24545914107565
1401114.6502972742159-3.65029727421586
1411614.5264570418061.47354295819397
1421514.65029727421590.349702725784142
1431715.26226922954271.73773077045729
1441614.66695599217121.33304400782878
1451012.9215629226898-2.92156292268976
1461814.31932321961943.68067678038062
1471313.6906925463372-0.690692546337165
1481614.40261680939621.59738319060379
1491313.7573274181586-0.757327418158623
1501013.4929882353836-3.49298823538361
1511515.5765845661838-0.576584566183822
1521614.84077237844711.15922762155286
1531615.41942689786330.580573102136733
1541415.0145887647231-1.01458876472306
1551013.8978263685238-3.89782636852381
1561714.05498403684442.94501596315563
1571314.9812713288123-1.98127132881233
1581515.5266084123177-0.526608412317728
1591614.05498403684441.94501596315563
1601214.8574310964025-2.85743109640251
1611314.6836147101266-1.68361471012659
1621311.85838777702611.14161222297395
1631212.4203835784868-0.420383578486812
1641713.80148515746113.19851484253892
1651513.90143746519331.09856253480674
1661012.6275174006735-2.62751740067346
1671413.52048725673070.479512743269305
1681111.9822280094359-0.982228009435877
1691313.6037808465075-0.603780846507519
1701613.4466231781872.55337682181304
1711212.784675068994-0.784675068994016
1721614.43011583074331.56988416925671
1731213.1323078415459-1.13230784154585
174912.1227269598011-3.12272695980107
1751213.0156968158583-1.0156968158583
1761513.69430364300661.30569635699339
1771212.8179925049047-0.817992504904745
1781212.7680163510387-0.768016351038651
1791413.487169820820.512830179180034
1801213.7276210789173-1.72762107891734
1811613.99196026169242.00803973830764
1821112.9085153014038-1.90851530140384
1831914.13245921205754.86754078794245
1841513.36332958841011.63667041158986
185813.0156968158583-5.0156968158583
1861613.85146131132722.14853868867283
1871713.67764492505133.32235507494875
1881213.3466708704548-1.34667087045478
1891112.5941999647627-1.59419996476273
1901113.5704634105968-2.57046341059679
1911413.57046341059680.429536589403211
1921614.62059093497461.37940906502542
1931213.6609862070959-1.66098620709589
1941613.72762107891732.27237892108266
1951313.5038285387753-0.503828538775331
1961514.02527769760310.974722302396911
1971613.20617192008962.79382807991041
1981614.14911793001291.85088206998709
1991412.67749355453961.32250644546045
2001613.2228306380452.77716936195505
2011612.34651949994313.65348050005692
2021413.18951320213420.810486797865779
2031113.6276687711852-2.62766877118516
2041213.222830638045-1.22283063804495
2051513.81814387541641.18185612458356
2061514.13245921205750.86754078794245
2071614.14911793001291.85088206998709
2081614.27295816242271.72704183757726
2091113.3799883063655-2.37998830636551
2101513.80148515746111.19851484253892
2111212.8179925049047-0.817992504904745
2121215.5302195089872-3.53021950898718
2131514.04193641555850.958063584441546
2141512.80133378694942.19866621305062
2151613.41330574227622.58669425772377
2161412.40372486053141.59627513946855
2171714.25629944446742.74370055553262
2181413.67764492505130.32235507494875
2191312.99180889118070.00819110881933573
2201514.60393221701920.396067782980786
2211313.0989904056351-0.0989904056351251
2221414.2729581624227-0.27295816242274
2231512.80133378694942.19866621305062
2241213.5038285387753-1.50382853877533
2251313.2894655098664-0.289465509866409
226814.2729581624227-6.27295816242274
2271414.0658243402361-0.0658243402360914
2281413.39664702432090.60335297567913
2291112.6774935545396-1.67749355453955
2301213.4133057422762-1.41330574227623
2311313.049014251769-0.0490142517690312
2321013.6037808465075-3.60378084650752
2331613.81814387541642.18185612458356
2341813.37998830636554.6200116936345
2351313.6443274891405-0.644327489140521
2361112.784675068994-1.78467506899402
237412.7680163510386-8.76801635103865
2381312.43704229644220.562957703557823
2391612.64417611862883.35582388137117
2401012.6275174006735-2.62751740067346
2411213.0823316876798-1.08233168767976
2421212.9918088911807-0.991808891180664
2431012.4537010143975-2.45370101439754
2441313.2394893560003-0.239489356000315
2451513.34667087045481.65332912954522
2461213.4133057422762-1.41330574227623
2471413.69430364300660.305696356993385
2481013.3633295884101-3.36332958841014
2491211.07259943542330.927400564576722
2501211.19643966783310.803560332166896
2511113.8181438754164-2.81814387541644
2521013.222830638045-3.22283063804495
2531213.5371459746861-1.53714597468606
2541613.2228306380452.77716936195505
2551213.2394893560003-1.23948935600032
2561413.23948935600030.760510643999685
2571613.4466231781872.55337682181304
2581412.66083483658421.33916516341581
2591313.8181438754164-0.81814387541644
260412.4870184503083-8.48701845030827
2611513.0490142517691.95098574823097
2621114.4467745486987-3.44677454869866
2631113.008467609136-2.00846760913603
2641413.36332958841010.636670411589859







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.8120228410392120.3759543179215760.187977158960788
80.6899118177659210.6201763644681580.310088182234079
90.5739349111123410.8521301777753180.426065088887659
100.4786860927621880.9573721855243750.521313907237812
110.3809111470650230.7618222941300460.619088852934977
120.4057454829173590.8114909658347180.594254517082641
130.3254052829974670.6508105659949350.674594717002533
140.2915018710940690.5830037421881380.708498128905931
150.319499026345310.638998052690620.68050097365469
160.2562346340289280.5124692680578560.743765365971072
170.2019936825382650.403987365076530.798006317461735
180.4566727841356610.9133455682713220.543327215864339
190.4334325257519530.8668650515039050.566567474248047
200.3622065076228240.7244130152456470.637793492377176
210.2962839489961590.5925678979923180.703716051003841
220.2381216057638320.4762432115276650.761878394236168
230.2672332691291670.5344665382583340.732766730870833
240.219561198110120.4391223962202390.78043880188988
250.1911546019478390.3823092038956770.808845398052161
260.1594459716688090.3188919433376170.840554028331191
270.1224872438557950.244974487711590.877512756144205
280.1040339029027280.2080678058054570.895966097097272
290.07808056304132640.1561611260826530.921919436958674
300.07785443389563780.1557088677912760.922145566104362
310.05909776860749930.1181955372149990.940902231392501
320.1069365615452050.213873123090410.893063438454795
330.09144303807488830.1828860761497770.908556961925112
340.06969663067095260.1393932613419050.930303369329047
350.05651229949113930.1130245989822790.943487700508861
360.2196731136579510.4393462273159010.780326886342049
370.3846997046421980.7693994092843970.615300295357802
380.3494957238986090.6989914477972180.650504276101391
390.3129952257734730.6259904515469450.687004774226527
400.2761751853144780.5523503706289560.723824814685522
410.2422161080184370.4844322160368740.757783891981563
420.2183100201803690.4366200403607370.781689979819631
430.3843669527341270.7687339054682530.615633047265873
440.3473684905513120.6947369811026240.652631509448688
450.3038760442330920.6077520884661850.696123955766908
460.4184297630715980.8368595261431970.581570236928402
470.4235688481073760.8471376962147520.576431151892624
480.379286935176710.7585738703534210.62071306482329
490.3364099263348990.6728198526697980.663590073665101
500.2999801086853790.5999602173707590.700019891314621
510.2610026626158590.5220053252317170.738997337384141
520.2275156321317060.4550312642634110.772484367868294
530.2414813246153030.4829626492306060.758518675384697
540.2087985258181230.4175970516362450.791201474181877
550.4125517599091530.8251035198183070.587448240090847
560.3921848661607120.7843697323214240.607815133839288
570.3521223281324740.7042446562649480.647877671867526
580.3155681607036290.6311363214072570.684431839296371
590.2790050809104880.5580101618209760.720994919089512
600.2549415449903810.5098830899807630.745058455009619
610.2307250672075210.4614501344150430.769274932792479
620.2061008179057580.4122016358115160.793899182094242
630.1857482225675150.3714964451350290.814251777432485
640.1716754806372850.343350961274570.828324519362715
650.1529655330091590.3059310660183170.847034466990841
660.1653715454557720.3307430909115440.834628454544228
670.1520907526316460.3041815052632920.847909247368354
680.1416045714740010.2832091429480030.858395428525998
690.1699205650010370.3398411300020740.830079434998963
700.1611968378472050.3223936756944090.838803162152795
710.3695175719594390.7390351439188780.630482428040561
720.3400076149108590.6800152298217180.659992385089141
730.3417542959537720.6835085919075450.658245704046228
740.3344161230094430.6688322460188860.665583876990557
750.3017141095805140.6034282191610290.698285890419486
760.3450221324924740.6900442649849490.654977867507526
770.3287874705080570.6575749410161150.671212529491943
780.2953961302523840.5907922605047690.704603869747616
790.281341830623840.562683661247680.71865816937616
800.2580726309225920.5161452618451850.741927369077408
810.2518471728788910.5036943457577820.748152827121109
820.223274100666860.446548201333720.77672589933314
830.2007860097343070.4015720194686140.799213990265693
840.1762327431046810.3524654862093620.823767256895319
850.1549112225844090.3098224451688180.845088777415591
860.136465276918470.272930553836940.86353472308153
870.1171667124394450.234333424878890.882833287560555
880.102119106856360.204238213712720.89788089314364
890.08675283806698380.1735056761339680.913247161933016
900.08577318397335430.1715463679467090.914226816026646
910.07569510789219850.1513902157843970.924304892107801
920.06761851559042840.1352370311808570.932381484409572
930.06072921861567980.121458437231360.93927078138432
940.0538620222401160.1077240444802320.946137977759884
950.04977759552966740.09955519105933480.950222404470333
960.04128978892951540.08257957785903080.958710211070485
970.03544300397966460.07088600795932910.964556996020335
980.0313303408354290.06266068167085790.968669659164571
990.02861087882042620.05722175764085230.971389121179574
1000.02346086343949070.04692172687898140.976539136560509
1010.01897988081444910.03795976162889810.981020119185551
1020.04818198589914610.09636397179829220.951818014100854
1030.04130442122469880.08260884244939770.958695578775301
1040.04186019237808410.08372038475616820.958139807621916
1050.04981848670703240.09963697341406470.950181513292968
1060.0577824539875920.1155649079751840.942217546012408
1070.04905899571406750.09811799142813490.950941004285933
1080.04086222897013580.08172445794027150.959137771029864
1090.04640977091348940.09281954182697880.953590229086511
1100.03887145722875480.07774291445750960.961128542771245
1110.03330595399802660.06661190799605320.966694046001973
1120.03664465844407610.07328931688815230.963355341555924
1130.04192917077764780.08385834155529560.958070829222352
1140.04888088981365690.09776177962731390.951119110186343
1150.05273079827031910.1054615965406380.947269201729681
1160.04614348117226230.09228696234452470.953856518827738
1170.04294570759590850.0858914151918170.957054292404091
1180.04703657968863590.09407315937727170.952963420311364
1190.04088395963813450.08176791927626910.959116040361865
1200.04075410864519930.08150821729039860.959245891354801
1210.03537148573877720.07074297147755440.964628514261223
1220.03115572791968630.06231145583937270.968844272080314
1230.02567413196471650.05134826392943290.974325868035284
1240.02108234827156910.04216469654313820.978917651728431
1250.01903618525078590.03807237050157180.980963814749214
1260.01572247765610.03144495531219990.9842775223439
1270.01574436976908630.03148873953817250.984255630230914
1280.01300480758482690.02600961516965380.986995192415173
1290.01965279422712630.03930558845425250.980347205772874
1300.01728376490037880.03456752980075750.982716235099621
1310.03423366217777870.06846732435555750.965766337822221
1320.03528357923746740.07056715847493490.964716420762533
1330.0440093708087030.0880187416174060.955990629191297
1340.03715860350781070.07431720701562140.962841396492189
1350.03068825021846060.06137650043692110.969311749781539
1360.0272842526179040.0545685052358080.972715747382096
1370.03095193957579420.06190387915158830.969048060424206
1380.0451783670265520.0903567340531040.954821632973448
1390.04683322615632250.09366645231264510.953166773843677
1400.06636616157229450.1327323231445890.933633838427706
1410.05972820901333270.1194564180266650.940271790986667
1420.05017168695993170.1003433739198630.949828313040068
1430.0465334063123550.09306681262471010.953466593687645
1440.04138366746984630.08276733493969260.958616332530154
1450.05074373597690260.1014874719538050.949256264023097
1460.07025477436472320.1405095487294460.929745225635277
1470.06128637995531090.1225727599106220.938713620044689
1480.05788862584629730.1157772516925950.942111374153703
1490.05038217116142510.100764342322850.949617828838575
1500.06460107129738030.1292021425947610.93539892870262
1510.05457536232505130.1091507246501030.945424637674949
1520.04877078260169710.09754156520339430.951229217398303
1530.04163812245269130.08327624490538260.958361877547309
1540.03535173688765110.07070347377530220.964648263112349
1550.05029398880970230.1005879776194050.949706011190298
1560.06148693639257570.1229738727851510.938513063607424
1570.05706182895500210.1141236579100040.942938171044998
1580.04778558354494690.09557116708989380.952214416455053
1590.05371611290984240.1074322258196850.946283887090158
1600.05303899046347170.1060779809269430.946961009536528
1610.04677554016001590.09355108032003190.953224459839984
1620.0414022326652090.0828044653304180.958597767334791
1630.03552858612646410.07105717225292830.964471413873536
1640.04068232294523740.08136464589047490.959317677054763
1650.03411119026924820.06822238053849640.965888809730752
1660.03903508515821350.0780701703164270.960964914841786
1670.03223830630217240.06447661260434480.967761693697828
1680.02817127116240160.05634254232480330.971828728837598
1690.02350740238106530.04701480476213050.976492597618935
1700.02385754517134450.04771509034268910.976142454828655
1710.02008583896761190.04017167793522380.979914161032388
1720.01732432081311120.03464864162622240.982675679186889
1730.01491363735660340.02982727471320690.985086362643397
1740.01859590020747990.03719180041495990.98140409979252
1750.01563477552567310.03126955105134620.984365224474327
1760.01320876520398520.02641753040797040.986791234796015
1770.0107998136635930.0215996273271860.989200186336407
1780.008724440284692810.01744888056938560.991275559715307
1790.006846673416004020.0136933468320080.993153326583996
1800.006220333465802980.0124406669316060.993779666534197
1810.005744154665614330.01148830933122870.994255845334386
1820.00531035418583720.01062070837167440.994689645814163
1830.01261449811673390.02522899623346790.987385501883266
1840.01119028002912560.02238056005825110.988809719970874
1850.02686208731596510.05372417463193010.973137912684035
1860.02617584241449470.05235168482898950.973824157585505
1870.03326168594382810.06652337188765630.966738314056172
1880.0289329493145520.05786589862910390.971067050685448
1890.02597423554430060.05194847108860130.974025764455699
1900.02722281229719660.05444562459439330.972777187702803
1910.02192919145778880.04385838291557760.978070808542211
1920.01925954598469130.03851909196938260.980740454015309
1930.01706542138170320.03413084276340630.982934578618297
1940.01738927310982370.03477854621964740.982610726890176
1950.01374552891208970.02749105782417940.98625447108791
1960.01142562909986120.02285125819972240.988574370900139
1970.01277854941557840.02555709883115680.987221450584422
1980.01214876351617780.02429752703235560.987851236483822
1990.01034562538017150.02069125076034290.989654374619829
2000.01181744062504570.02363488125009130.988182559374954
2010.01784724267487670.03569448534975340.982152757325123
2020.01434344691606860.02868689383213720.985656553083931
2030.01546492231553740.03092984463107470.984535077684463
2040.01269326355395520.02538652710791050.987306736446045
2050.01056157891346910.02112315782693820.989438421086531
2060.008536105675257310.01707221135051460.991463894324743
2070.008284340225453930.01656868045090790.991715659774546
2080.007801580390025720.01560316078005140.992198419609974
2090.007500549291628960.01500109858325790.992499450708371
2100.006256963922345210.01251392784469040.993743036077655
2110.00474921660056750.009498433201135010.995250783399433
2120.005638618281076830.01127723656215370.994361381718923
2130.004693943092836650.009387886185673290.995306056907163
2140.004907831943471830.009815663886943660.995092168056528
2150.006109003763976940.01221800752795390.993890996236023
2160.005091288919536420.01018257783907280.994908711080464
2170.006507519222060490.0130150384441210.99349248077794
2180.004983956170050070.009967912340100140.99501604382995
2190.003737636009920270.007475272019840530.99626236399008
2200.002983881506223720.005967763012447440.997016118493776
2210.0021584510249950.004316902049990010.997841548975005
2220.001556089123902430.003112178247804860.998443910876098
2230.001745927731941110.003491855463882220.998254072268059
2240.001292006061598140.002584012123196280.998707993938402
2250.0009302197244673220.001860439448934640.999069780275533
2260.005167628785770290.01033525757154060.99483237121423
2270.003614510113627820.007229020227255640.996385489886372
2280.00277707340453070.005554146809061390.997222926595469
2290.002023835886202020.004047671772404040.997976164113798
2300.001420328493925840.002840656987851690.998579671506074
2310.0009400359748289320.001880071949657860.999059964025171
2320.001019369047656290.002038738095312580.998980630952344
2330.001084751721912250.002169503443824510.998915248278088
2340.00473677102771520.00947354205543040.995263228972285
2350.003227374189491080.006454748378982160.996772625810509
2360.002330721890491960.004661443780983910.997669278109508
2370.08209794177365770.1641958835473150.917902058226342
2380.06402187514509460.1280437502901890.935978124854906
2390.1034971703001830.2069943406003660.896502829699817
2400.09570900003931430.1914180000786290.904290999960686
2410.07227924683937090.1445584936787420.927720753160629
2420.05299383708653410.1059876741730680.947006162913466
2430.04830252157787650.09660504315575310.951697478422123
2440.03422831159674260.06845662319348520.965771688403257
2450.03227823995433780.06455647990867560.967721760045662
2460.0219556543903720.0439113087807440.978044345609628
2470.01614358511592330.03228717023184660.983856414884077
2480.01578104760594290.03156209521188590.984218952394057
2490.009953981384665780.01990796276933160.990046018615334
2500.006625656129353580.01325131225870720.993374343870646
2510.005351826872953590.01070365374590720.994648173127046
2520.004885298374125670.009770596748251350.995114701625874
2530.002787066221415970.005574132442831940.997212933778584
2540.003687643577343880.007375287154687770.996312356422656
2550.001699495919300020.003398991838600040.9983005040807
2560.0008932529158854050.001786505831770810.999106747084115
2570.001660828433249230.003321656866498460.998339171566751

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.812022841039212 & 0.375954317921576 & 0.187977158960788 \tabularnewline
8 & 0.689911817765921 & 0.620176364468158 & 0.310088182234079 \tabularnewline
9 & 0.573934911112341 & 0.852130177775318 & 0.426065088887659 \tabularnewline
10 & 0.478686092762188 & 0.957372185524375 & 0.521313907237812 \tabularnewline
11 & 0.380911147065023 & 0.761822294130046 & 0.619088852934977 \tabularnewline
12 & 0.405745482917359 & 0.811490965834718 & 0.594254517082641 \tabularnewline
13 & 0.325405282997467 & 0.650810565994935 & 0.674594717002533 \tabularnewline
14 & 0.291501871094069 & 0.583003742188138 & 0.708498128905931 \tabularnewline
15 & 0.31949902634531 & 0.63899805269062 & 0.68050097365469 \tabularnewline
16 & 0.256234634028928 & 0.512469268057856 & 0.743765365971072 \tabularnewline
17 & 0.201993682538265 & 0.40398736507653 & 0.798006317461735 \tabularnewline
18 & 0.456672784135661 & 0.913345568271322 & 0.543327215864339 \tabularnewline
19 & 0.433432525751953 & 0.866865051503905 & 0.566567474248047 \tabularnewline
20 & 0.362206507622824 & 0.724413015245647 & 0.637793492377176 \tabularnewline
21 & 0.296283948996159 & 0.592567897992318 & 0.703716051003841 \tabularnewline
22 & 0.238121605763832 & 0.476243211527665 & 0.761878394236168 \tabularnewline
23 & 0.267233269129167 & 0.534466538258334 & 0.732766730870833 \tabularnewline
24 & 0.21956119811012 & 0.439122396220239 & 0.78043880188988 \tabularnewline
25 & 0.191154601947839 & 0.382309203895677 & 0.808845398052161 \tabularnewline
26 & 0.159445971668809 & 0.318891943337617 & 0.840554028331191 \tabularnewline
27 & 0.122487243855795 & 0.24497448771159 & 0.877512756144205 \tabularnewline
28 & 0.104033902902728 & 0.208067805805457 & 0.895966097097272 \tabularnewline
29 & 0.0780805630413264 & 0.156161126082653 & 0.921919436958674 \tabularnewline
30 & 0.0778544338956378 & 0.155708867791276 & 0.922145566104362 \tabularnewline
31 & 0.0590977686074993 & 0.118195537214999 & 0.940902231392501 \tabularnewline
32 & 0.106936561545205 & 0.21387312309041 & 0.893063438454795 \tabularnewline
33 & 0.0914430380748883 & 0.182886076149777 & 0.908556961925112 \tabularnewline
34 & 0.0696966306709526 & 0.139393261341905 & 0.930303369329047 \tabularnewline
35 & 0.0565122994911393 & 0.113024598982279 & 0.943487700508861 \tabularnewline
36 & 0.219673113657951 & 0.439346227315901 & 0.780326886342049 \tabularnewline
37 & 0.384699704642198 & 0.769399409284397 & 0.615300295357802 \tabularnewline
38 & 0.349495723898609 & 0.698991447797218 & 0.650504276101391 \tabularnewline
39 & 0.312995225773473 & 0.625990451546945 & 0.687004774226527 \tabularnewline
40 & 0.276175185314478 & 0.552350370628956 & 0.723824814685522 \tabularnewline
41 & 0.242216108018437 & 0.484432216036874 & 0.757783891981563 \tabularnewline
42 & 0.218310020180369 & 0.436620040360737 & 0.781689979819631 \tabularnewline
43 & 0.384366952734127 & 0.768733905468253 & 0.615633047265873 \tabularnewline
44 & 0.347368490551312 & 0.694736981102624 & 0.652631509448688 \tabularnewline
45 & 0.303876044233092 & 0.607752088466185 & 0.696123955766908 \tabularnewline
46 & 0.418429763071598 & 0.836859526143197 & 0.581570236928402 \tabularnewline
47 & 0.423568848107376 & 0.847137696214752 & 0.576431151892624 \tabularnewline
48 & 0.37928693517671 & 0.758573870353421 & 0.62071306482329 \tabularnewline
49 & 0.336409926334899 & 0.672819852669798 & 0.663590073665101 \tabularnewline
50 & 0.299980108685379 & 0.599960217370759 & 0.700019891314621 \tabularnewline
51 & 0.261002662615859 & 0.522005325231717 & 0.738997337384141 \tabularnewline
52 & 0.227515632131706 & 0.455031264263411 & 0.772484367868294 \tabularnewline
53 & 0.241481324615303 & 0.482962649230606 & 0.758518675384697 \tabularnewline
54 & 0.208798525818123 & 0.417597051636245 & 0.791201474181877 \tabularnewline
55 & 0.412551759909153 & 0.825103519818307 & 0.587448240090847 \tabularnewline
56 & 0.392184866160712 & 0.784369732321424 & 0.607815133839288 \tabularnewline
57 & 0.352122328132474 & 0.704244656264948 & 0.647877671867526 \tabularnewline
58 & 0.315568160703629 & 0.631136321407257 & 0.684431839296371 \tabularnewline
59 & 0.279005080910488 & 0.558010161820976 & 0.720994919089512 \tabularnewline
60 & 0.254941544990381 & 0.509883089980763 & 0.745058455009619 \tabularnewline
61 & 0.230725067207521 & 0.461450134415043 & 0.769274932792479 \tabularnewline
62 & 0.206100817905758 & 0.412201635811516 & 0.793899182094242 \tabularnewline
63 & 0.185748222567515 & 0.371496445135029 & 0.814251777432485 \tabularnewline
64 & 0.171675480637285 & 0.34335096127457 & 0.828324519362715 \tabularnewline
65 & 0.152965533009159 & 0.305931066018317 & 0.847034466990841 \tabularnewline
66 & 0.165371545455772 & 0.330743090911544 & 0.834628454544228 \tabularnewline
67 & 0.152090752631646 & 0.304181505263292 & 0.847909247368354 \tabularnewline
68 & 0.141604571474001 & 0.283209142948003 & 0.858395428525998 \tabularnewline
69 & 0.169920565001037 & 0.339841130002074 & 0.830079434998963 \tabularnewline
70 & 0.161196837847205 & 0.322393675694409 & 0.838803162152795 \tabularnewline
71 & 0.369517571959439 & 0.739035143918878 & 0.630482428040561 \tabularnewline
72 & 0.340007614910859 & 0.680015229821718 & 0.659992385089141 \tabularnewline
73 & 0.341754295953772 & 0.683508591907545 & 0.658245704046228 \tabularnewline
74 & 0.334416123009443 & 0.668832246018886 & 0.665583876990557 \tabularnewline
75 & 0.301714109580514 & 0.603428219161029 & 0.698285890419486 \tabularnewline
76 & 0.345022132492474 & 0.690044264984949 & 0.654977867507526 \tabularnewline
77 & 0.328787470508057 & 0.657574941016115 & 0.671212529491943 \tabularnewline
78 & 0.295396130252384 & 0.590792260504769 & 0.704603869747616 \tabularnewline
79 & 0.28134183062384 & 0.56268366124768 & 0.71865816937616 \tabularnewline
80 & 0.258072630922592 & 0.516145261845185 & 0.741927369077408 \tabularnewline
81 & 0.251847172878891 & 0.503694345757782 & 0.748152827121109 \tabularnewline
82 & 0.22327410066686 & 0.44654820133372 & 0.77672589933314 \tabularnewline
83 & 0.200786009734307 & 0.401572019468614 & 0.799213990265693 \tabularnewline
84 & 0.176232743104681 & 0.352465486209362 & 0.823767256895319 \tabularnewline
85 & 0.154911222584409 & 0.309822445168818 & 0.845088777415591 \tabularnewline
86 & 0.13646527691847 & 0.27293055383694 & 0.86353472308153 \tabularnewline
87 & 0.117166712439445 & 0.23433342487889 & 0.882833287560555 \tabularnewline
88 & 0.10211910685636 & 0.20423821371272 & 0.89788089314364 \tabularnewline
89 & 0.0867528380669838 & 0.173505676133968 & 0.913247161933016 \tabularnewline
90 & 0.0857731839733543 & 0.171546367946709 & 0.914226816026646 \tabularnewline
91 & 0.0756951078921985 & 0.151390215784397 & 0.924304892107801 \tabularnewline
92 & 0.0676185155904284 & 0.135237031180857 & 0.932381484409572 \tabularnewline
93 & 0.0607292186156798 & 0.12145843723136 & 0.93927078138432 \tabularnewline
94 & 0.053862022240116 & 0.107724044480232 & 0.946137977759884 \tabularnewline
95 & 0.0497775955296674 & 0.0995551910593348 & 0.950222404470333 \tabularnewline
96 & 0.0412897889295154 & 0.0825795778590308 & 0.958710211070485 \tabularnewline
97 & 0.0354430039796646 & 0.0708860079593291 & 0.964556996020335 \tabularnewline
98 & 0.031330340835429 & 0.0626606816708579 & 0.968669659164571 \tabularnewline
99 & 0.0286108788204262 & 0.0572217576408523 & 0.971389121179574 \tabularnewline
100 & 0.0234608634394907 & 0.0469217268789814 & 0.976539136560509 \tabularnewline
101 & 0.0189798808144491 & 0.0379597616288981 & 0.981020119185551 \tabularnewline
102 & 0.0481819858991461 & 0.0963639717982922 & 0.951818014100854 \tabularnewline
103 & 0.0413044212246988 & 0.0826088424493977 & 0.958695578775301 \tabularnewline
104 & 0.0418601923780841 & 0.0837203847561682 & 0.958139807621916 \tabularnewline
105 & 0.0498184867070324 & 0.0996369734140647 & 0.950181513292968 \tabularnewline
106 & 0.057782453987592 & 0.115564907975184 & 0.942217546012408 \tabularnewline
107 & 0.0490589957140675 & 0.0981179914281349 & 0.950941004285933 \tabularnewline
108 & 0.0408622289701358 & 0.0817244579402715 & 0.959137771029864 \tabularnewline
109 & 0.0464097709134894 & 0.0928195418269788 & 0.953590229086511 \tabularnewline
110 & 0.0388714572287548 & 0.0777429144575096 & 0.961128542771245 \tabularnewline
111 & 0.0333059539980266 & 0.0666119079960532 & 0.966694046001973 \tabularnewline
112 & 0.0366446584440761 & 0.0732893168881523 & 0.963355341555924 \tabularnewline
113 & 0.0419291707776478 & 0.0838583415552956 & 0.958070829222352 \tabularnewline
114 & 0.0488808898136569 & 0.0977617796273139 & 0.951119110186343 \tabularnewline
115 & 0.0527307982703191 & 0.105461596540638 & 0.947269201729681 \tabularnewline
116 & 0.0461434811722623 & 0.0922869623445247 & 0.953856518827738 \tabularnewline
117 & 0.0429457075959085 & 0.085891415191817 & 0.957054292404091 \tabularnewline
118 & 0.0470365796886359 & 0.0940731593772717 & 0.952963420311364 \tabularnewline
119 & 0.0408839596381345 & 0.0817679192762691 & 0.959116040361865 \tabularnewline
120 & 0.0407541086451993 & 0.0815082172903986 & 0.959245891354801 \tabularnewline
121 & 0.0353714857387772 & 0.0707429714775544 & 0.964628514261223 \tabularnewline
122 & 0.0311557279196863 & 0.0623114558393727 & 0.968844272080314 \tabularnewline
123 & 0.0256741319647165 & 0.0513482639294329 & 0.974325868035284 \tabularnewline
124 & 0.0210823482715691 & 0.0421646965431382 & 0.978917651728431 \tabularnewline
125 & 0.0190361852507859 & 0.0380723705015718 & 0.980963814749214 \tabularnewline
126 & 0.0157224776561 & 0.0314449553121999 & 0.9842775223439 \tabularnewline
127 & 0.0157443697690863 & 0.0314887395381725 & 0.984255630230914 \tabularnewline
128 & 0.0130048075848269 & 0.0260096151696538 & 0.986995192415173 \tabularnewline
129 & 0.0196527942271263 & 0.0393055884542525 & 0.980347205772874 \tabularnewline
130 & 0.0172837649003788 & 0.0345675298007575 & 0.982716235099621 \tabularnewline
131 & 0.0342336621777787 & 0.0684673243555575 & 0.965766337822221 \tabularnewline
132 & 0.0352835792374674 & 0.0705671584749349 & 0.964716420762533 \tabularnewline
133 & 0.044009370808703 & 0.088018741617406 & 0.955990629191297 \tabularnewline
134 & 0.0371586035078107 & 0.0743172070156214 & 0.962841396492189 \tabularnewline
135 & 0.0306882502184606 & 0.0613765004369211 & 0.969311749781539 \tabularnewline
136 & 0.027284252617904 & 0.054568505235808 & 0.972715747382096 \tabularnewline
137 & 0.0309519395757942 & 0.0619038791515883 & 0.969048060424206 \tabularnewline
138 & 0.045178367026552 & 0.090356734053104 & 0.954821632973448 \tabularnewline
139 & 0.0468332261563225 & 0.0936664523126451 & 0.953166773843677 \tabularnewline
140 & 0.0663661615722945 & 0.132732323144589 & 0.933633838427706 \tabularnewline
141 & 0.0597282090133327 & 0.119456418026665 & 0.940271790986667 \tabularnewline
142 & 0.0501716869599317 & 0.100343373919863 & 0.949828313040068 \tabularnewline
143 & 0.046533406312355 & 0.0930668126247101 & 0.953466593687645 \tabularnewline
144 & 0.0413836674698463 & 0.0827673349396926 & 0.958616332530154 \tabularnewline
145 & 0.0507437359769026 & 0.101487471953805 & 0.949256264023097 \tabularnewline
146 & 0.0702547743647232 & 0.140509548729446 & 0.929745225635277 \tabularnewline
147 & 0.0612863799553109 & 0.122572759910622 & 0.938713620044689 \tabularnewline
148 & 0.0578886258462973 & 0.115777251692595 & 0.942111374153703 \tabularnewline
149 & 0.0503821711614251 & 0.10076434232285 & 0.949617828838575 \tabularnewline
150 & 0.0646010712973803 & 0.129202142594761 & 0.93539892870262 \tabularnewline
151 & 0.0545753623250513 & 0.109150724650103 & 0.945424637674949 \tabularnewline
152 & 0.0487707826016971 & 0.0975415652033943 & 0.951229217398303 \tabularnewline
153 & 0.0416381224526913 & 0.0832762449053826 & 0.958361877547309 \tabularnewline
154 & 0.0353517368876511 & 0.0707034737753022 & 0.964648263112349 \tabularnewline
155 & 0.0502939888097023 & 0.100587977619405 & 0.949706011190298 \tabularnewline
156 & 0.0614869363925757 & 0.122973872785151 & 0.938513063607424 \tabularnewline
157 & 0.0570618289550021 & 0.114123657910004 & 0.942938171044998 \tabularnewline
158 & 0.0477855835449469 & 0.0955711670898938 & 0.952214416455053 \tabularnewline
159 & 0.0537161129098424 & 0.107432225819685 & 0.946283887090158 \tabularnewline
160 & 0.0530389904634717 & 0.106077980926943 & 0.946961009536528 \tabularnewline
161 & 0.0467755401600159 & 0.0935510803200319 & 0.953224459839984 \tabularnewline
162 & 0.041402232665209 & 0.082804465330418 & 0.958597767334791 \tabularnewline
163 & 0.0355285861264641 & 0.0710571722529283 & 0.964471413873536 \tabularnewline
164 & 0.0406823229452374 & 0.0813646458904749 & 0.959317677054763 \tabularnewline
165 & 0.0341111902692482 & 0.0682223805384964 & 0.965888809730752 \tabularnewline
166 & 0.0390350851582135 & 0.078070170316427 & 0.960964914841786 \tabularnewline
167 & 0.0322383063021724 & 0.0644766126043448 & 0.967761693697828 \tabularnewline
168 & 0.0281712711624016 & 0.0563425423248033 & 0.971828728837598 \tabularnewline
169 & 0.0235074023810653 & 0.0470148047621305 & 0.976492597618935 \tabularnewline
170 & 0.0238575451713445 & 0.0477150903426891 & 0.976142454828655 \tabularnewline
171 & 0.0200858389676119 & 0.0401716779352238 & 0.979914161032388 \tabularnewline
172 & 0.0173243208131112 & 0.0346486416262224 & 0.982675679186889 \tabularnewline
173 & 0.0149136373566034 & 0.0298272747132069 & 0.985086362643397 \tabularnewline
174 & 0.0185959002074799 & 0.0371918004149599 & 0.98140409979252 \tabularnewline
175 & 0.0156347755256731 & 0.0312695510513462 & 0.984365224474327 \tabularnewline
176 & 0.0132087652039852 & 0.0264175304079704 & 0.986791234796015 \tabularnewline
177 & 0.010799813663593 & 0.021599627327186 & 0.989200186336407 \tabularnewline
178 & 0.00872444028469281 & 0.0174488805693856 & 0.991275559715307 \tabularnewline
179 & 0.00684667341600402 & 0.013693346832008 & 0.993153326583996 \tabularnewline
180 & 0.00622033346580298 & 0.012440666931606 & 0.993779666534197 \tabularnewline
181 & 0.00574415466561433 & 0.0114883093312287 & 0.994255845334386 \tabularnewline
182 & 0.0053103541858372 & 0.0106207083716744 & 0.994689645814163 \tabularnewline
183 & 0.0126144981167339 & 0.0252289962334679 & 0.987385501883266 \tabularnewline
184 & 0.0111902800291256 & 0.0223805600582511 & 0.988809719970874 \tabularnewline
185 & 0.0268620873159651 & 0.0537241746319301 & 0.973137912684035 \tabularnewline
186 & 0.0261758424144947 & 0.0523516848289895 & 0.973824157585505 \tabularnewline
187 & 0.0332616859438281 & 0.0665233718876563 & 0.966738314056172 \tabularnewline
188 & 0.028932949314552 & 0.0578658986291039 & 0.971067050685448 \tabularnewline
189 & 0.0259742355443006 & 0.0519484710886013 & 0.974025764455699 \tabularnewline
190 & 0.0272228122971966 & 0.0544456245943933 & 0.972777187702803 \tabularnewline
191 & 0.0219291914577888 & 0.0438583829155776 & 0.978070808542211 \tabularnewline
192 & 0.0192595459846913 & 0.0385190919693826 & 0.980740454015309 \tabularnewline
193 & 0.0170654213817032 & 0.0341308427634063 & 0.982934578618297 \tabularnewline
194 & 0.0173892731098237 & 0.0347785462196474 & 0.982610726890176 \tabularnewline
195 & 0.0137455289120897 & 0.0274910578241794 & 0.98625447108791 \tabularnewline
196 & 0.0114256290998612 & 0.0228512581997224 & 0.988574370900139 \tabularnewline
197 & 0.0127785494155784 & 0.0255570988311568 & 0.987221450584422 \tabularnewline
198 & 0.0121487635161778 & 0.0242975270323556 & 0.987851236483822 \tabularnewline
199 & 0.0103456253801715 & 0.0206912507603429 & 0.989654374619829 \tabularnewline
200 & 0.0118174406250457 & 0.0236348812500913 & 0.988182559374954 \tabularnewline
201 & 0.0178472426748767 & 0.0356944853497534 & 0.982152757325123 \tabularnewline
202 & 0.0143434469160686 & 0.0286868938321372 & 0.985656553083931 \tabularnewline
203 & 0.0154649223155374 & 0.0309298446310747 & 0.984535077684463 \tabularnewline
204 & 0.0126932635539552 & 0.0253865271079105 & 0.987306736446045 \tabularnewline
205 & 0.0105615789134691 & 0.0211231578269382 & 0.989438421086531 \tabularnewline
206 & 0.00853610567525731 & 0.0170722113505146 & 0.991463894324743 \tabularnewline
207 & 0.00828434022545393 & 0.0165686804509079 & 0.991715659774546 \tabularnewline
208 & 0.00780158039002572 & 0.0156031607800514 & 0.992198419609974 \tabularnewline
209 & 0.00750054929162896 & 0.0150010985832579 & 0.992499450708371 \tabularnewline
210 & 0.00625696392234521 & 0.0125139278446904 & 0.993743036077655 \tabularnewline
211 & 0.0047492166005675 & 0.00949843320113501 & 0.995250783399433 \tabularnewline
212 & 0.00563861828107683 & 0.0112772365621537 & 0.994361381718923 \tabularnewline
213 & 0.00469394309283665 & 0.00938788618567329 & 0.995306056907163 \tabularnewline
214 & 0.00490783194347183 & 0.00981566388694366 & 0.995092168056528 \tabularnewline
215 & 0.00610900376397694 & 0.0122180075279539 & 0.993890996236023 \tabularnewline
216 & 0.00509128891953642 & 0.0101825778390728 & 0.994908711080464 \tabularnewline
217 & 0.00650751922206049 & 0.013015038444121 & 0.99349248077794 \tabularnewline
218 & 0.00498395617005007 & 0.00996791234010014 & 0.99501604382995 \tabularnewline
219 & 0.00373763600992027 & 0.00747527201984053 & 0.99626236399008 \tabularnewline
220 & 0.00298388150622372 & 0.00596776301244744 & 0.997016118493776 \tabularnewline
221 & 0.002158451024995 & 0.00431690204999001 & 0.997841548975005 \tabularnewline
222 & 0.00155608912390243 & 0.00311217824780486 & 0.998443910876098 \tabularnewline
223 & 0.00174592773194111 & 0.00349185546388222 & 0.998254072268059 \tabularnewline
224 & 0.00129200606159814 & 0.00258401212319628 & 0.998707993938402 \tabularnewline
225 & 0.000930219724467322 & 0.00186043944893464 & 0.999069780275533 \tabularnewline
226 & 0.00516762878577029 & 0.0103352575715406 & 0.99483237121423 \tabularnewline
227 & 0.00361451011362782 & 0.00722902022725564 & 0.996385489886372 \tabularnewline
228 & 0.0027770734045307 & 0.00555414680906139 & 0.997222926595469 \tabularnewline
229 & 0.00202383588620202 & 0.00404767177240404 & 0.997976164113798 \tabularnewline
230 & 0.00142032849392584 & 0.00284065698785169 & 0.998579671506074 \tabularnewline
231 & 0.000940035974828932 & 0.00188007194965786 & 0.999059964025171 \tabularnewline
232 & 0.00101936904765629 & 0.00203873809531258 & 0.998980630952344 \tabularnewline
233 & 0.00108475172191225 & 0.00216950344382451 & 0.998915248278088 \tabularnewline
234 & 0.0047367710277152 & 0.0094735420554304 & 0.995263228972285 \tabularnewline
235 & 0.00322737418949108 & 0.00645474837898216 & 0.996772625810509 \tabularnewline
236 & 0.00233072189049196 & 0.00466144378098391 & 0.997669278109508 \tabularnewline
237 & 0.0820979417736577 & 0.164195883547315 & 0.917902058226342 \tabularnewline
238 & 0.0640218751450946 & 0.128043750290189 & 0.935978124854906 \tabularnewline
239 & 0.103497170300183 & 0.206994340600366 & 0.896502829699817 \tabularnewline
240 & 0.0957090000393143 & 0.191418000078629 & 0.904290999960686 \tabularnewline
241 & 0.0722792468393709 & 0.144558493678742 & 0.927720753160629 \tabularnewline
242 & 0.0529938370865341 & 0.105987674173068 & 0.947006162913466 \tabularnewline
243 & 0.0483025215778765 & 0.0966050431557531 & 0.951697478422123 \tabularnewline
244 & 0.0342283115967426 & 0.0684566231934852 & 0.965771688403257 \tabularnewline
245 & 0.0322782399543378 & 0.0645564799086756 & 0.967721760045662 \tabularnewline
246 & 0.021955654390372 & 0.043911308780744 & 0.978044345609628 \tabularnewline
247 & 0.0161435851159233 & 0.0322871702318466 & 0.983856414884077 \tabularnewline
248 & 0.0157810476059429 & 0.0315620952118859 & 0.984218952394057 \tabularnewline
249 & 0.00995398138466578 & 0.0199079627693316 & 0.990046018615334 \tabularnewline
250 & 0.00662565612935358 & 0.0132513122587072 & 0.993374343870646 \tabularnewline
251 & 0.00535182687295359 & 0.0107036537459072 & 0.994648173127046 \tabularnewline
252 & 0.00488529837412567 & 0.00977059674825135 & 0.995114701625874 \tabularnewline
253 & 0.00278706622141597 & 0.00557413244283194 & 0.997212933778584 \tabularnewline
254 & 0.00368764357734388 & 0.00737528715468777 & 0.996312356422656 \tabularnewline
255 & 0.00169949591930002 & 0.00339899183860004 & 0.9983005040807 \tabularnewline
256 & 0.000893252915885405 & 0.00178650583177081 & 0.999106747084115 \tabularnewline
257 & 0.00166082843324923 & 0.00332165686649846 & 0.998339171566751 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185727&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]7[/C][C]0.812022841039212[/C][C]0.375954317921576[/C][C]0.187977158960788[/C][/ROW]
[ROW][C]8[/C][C]0.689911817765921[/C][C]0.620176364468158[/C][C]0.310088182234079[/C][/ROW]
[ROW][C]9[/C][C]0.573934911112341[/C][C]0.852130177775318[/C][C]0.426065088887659[/C][/ROW]
[ROW][C]10[/C][C]0.478686092762188[/C][C]0.957372185524375[/C][C]0.521313907237812[/C][/ROW]
[ROW][C]11[/C][C]0.380911147065023[/C][C]0.761822294130046[/C][C]0.619088852934977[/C][/ROW]
[ROW][C]12[/C][C]0.405745482917359[/C][C]0.811490965834718[/C][C]0.594254517082641[/C][/ROW]
[ROW][C]13[/C][C]0.325405282997467[/C][C]0.650810565994935[/C][C]0.674594717002533[/C][/ROW]
[ROW][C]14[/C][C]0.291501871094069[/C][C]0.583003742188138[/C][C]0.708498128905931[/C][/ROW]
[ROW][C]15[/C][C]0.31949902634531[/C][C]0.63899805269062[/C][C]0.68050097365469[/C][/ROW]
[ROW][C]16[/C][C]0.256234634028928[/C][C]0.512469268057856[/C][C]0.743765365971072[/C][/ROW]
[ROW][C]17[/C][C]0.201993682538265[/C][C]0.40398736507653[/C][C]0.798006317461735[/C][/ROW]
[ROW][C]18[/C][C]0.456672784135661[/C][C]0.913345568271322[/C][C]0.543327215864339[/C][/ROW]
[ROW][C]19[/C][C]0.433432525751953[/C][C]0.866865051503905[/C][C]0.566567474248047[/C][/ROW]
[ROW][C]20[/C][C]0.362206507622824[/C][C]0.724413015245647[/C][C]0.637793492377176[/C][/ROW]
[ROW][C]21[/C][C]0.296283948996159[/C][C]0.592567897992318[/C][C]0.703716051003841[/C][/ROW]
[ROW][C]22[/C][C]0.238121605763832[/C][C]0.476243211527665[/C][C]0.761878394236168[/C][/ROW]
[ROW][C]23[/C][C]0.267233269129167[/C][C]0.534466538258334[/C][C]0.732766730870833[/C][/ROW]
[ROW][C]24[/C][C]0.21956119811012[/C][C]0.439122396220239[/C][C]0.78043880188988[/C][/ROW]
[ROW][C]25[/C][C]0.191154601947839[/C][C]0.382309203895677[/C][C]0.808845398052161[/C][/ROW]
[ROW][C]26[/C][C]0.159445971668809[/C][C]0.318891943337617[/C][C]0.840554028331191[/C][/ROW]
[ROW][C]27[/C][C]0.122487243855795[/C][C]0.24497448771159[/C][C]0.877512756144205[/C][/ROW]
[ROW][C]28[/C][C]0.104033902902728[/C][C]0.208067805805457[/C][C]0.895966097097272[/C][/ROW]
[ROW][C]29[/C][C]0.0780805630413264[/C][C]0.156161126082653[/C][C]0.921919436958674[/C][/ROW]
[ROW][C]30[/C][C]0.0778544338956378[/C][C]0.155708867791276[/C][C]0.922145566104362[/C][/ROW]
[ROW][C]31[/C][C]0.0590977686074993[/C][C]0.118195537214999[/C][C]0.940902231392501[/C][/ROW]
[ROW][C]32[/C][C]0.106936561545205[/C][C]0.21387312309041[/C][C]0.893063438454795[/C][/ROW]
[ROW][C]33[/C][C]0.0914430380748883[/C][C]0.182886076149777[/C][C]0.908556961925112[/C][/ROW]
[ROW][C]34[/C][C]0.0696966306709526[/C][C]0.139393261341905[/C][C]0.930303369329047[/C][/ROW]
[ROW][C]35[/C][C]0.0565122994911393[/C][C]0.113024598982279[/C][C]0.943487700508861[/C][/ROW]
[ROW][C]36[/C][C]0.219673113657951[/C][C]0.439346227315901[/C][C]0.780326886342049[/C][/ROW]
[ROW][C]37[/C][C]0.384699704642198[/C][C]0.769399409284397[/C][C]0.615300295357802[/C][/ROW]
[ROW][C]38[/C][C]0.349495723898609[/C][C]0.698991447797218[/C][C]0.650504276101391[/C][/ROW]
[ROW][C]39[/C][C]0.312995225773473[/C][C]0.625990451546945[/C][C]0.687004774226527[/C][/ROW]
[ROW][C]40[/C][C]0.276175185314478[/C][C]0.552350370628956[/C][C]0.723824814685522[/C][/ROW]
[ROW][C]41[/C][C]0.242216108018437[/C][C]0.484432216036874[/C][C]0.757783891981563[/C][/ROW]
[ROW][C]42[/C][C]0.218310020180369[/C][C]0.436620040360737[/C][C]0.781689979819631[/C][/ROW]
[ROW][C]43[/C][C]0.384366952734127[/C][C]0.768733905468253[/C][C]0.615633047265873[/C][/ROW]
[ROW][C]44[/C][C]0.347368490551312[/C][C]0.694736981102624[/C][C]0.652631509448688[/C][/ROW]
[ROW][C]45[/C][C]0.303876044233092[/C][C]0.607752088466185[/C][C]0.696123955766908[/C][/ROW]
[ROW][C]46[/C][C]0.418429763071598[/C][C]0.836859526143197[/C][C]0.581570236928402[/C][/ROW]
[ROW][C]47[/C][C]0.423568848107376[/C][C]0.847137696214752[/C][C]0.576431151892624[/C][/ROW]
[ROW][C]48[/C][C]0.37928693517671[/C][C]0.758573870353421[/C][C]0.62071306482329[/C][/ROW]
[ROW][C]49[/C][C]0.336409926334899[/C][C]0.672819852669798[/C][C]0.663590073665101[/C][/ROW]
[ROW][C]50[/C][C]0.299980108685379[/C][C]0.599960217370759[/C][C]0.700019891314621[/C][/ROW]
[ROW][C]51[/C][C]0.261002662615859[/C][C]0.522005325231717[/C][C]0.738997337384141[/C][/ROW]
[ROW][C]52[/C][C]0.227515632131706[/C][C]0.455031264263411[/C][C]0.772484367868294[/C][/ROW]
[ROW][C]53[/C][C]0.241481324615303[/C][C]0.482962649230606[/C][C]0.758518675384697[/C][/ROW]
[ROW][C]54[/C][C]0.208798525818123[/C][C]0.417597051636245[/C][C]0.791201474181877[/C][/ROW]
[ROW][C]55[/C][C]0.412551759909153[/C][C]0.825103519818307[/C][C]0.587448240090847[/C][/ROW]
[ROW][C]56[/C][C]0.392184866160712[/C][C]0.784369732321424[/C][C]0.607815133839288[/C][/ROW]
[ROW][C]57[/C][C]0.352122328132474[/C][C]0.704244656264948[/C][C]0.647877671867526[/C][/ROW]
[ROW][C]58[/C][C]0.315568160703629[/C][C]0.631136321407257[/C][C]0.684431839296371[/C][/ROW]
[ROW][C]59[/C][C]0.279005080910488[/C][C]0.558010161820976[/C][C]0.720994919089512[/C][/ROW]
[ROW][C]60[/C][C]0.254941544990381[/C][C]0.509883089980763[/C][C]0.745058455009619[/C][/ROW]
[ROW][C]61[/C][C]0.230725067207521[/C][C]0.461450134415043[/C][C]0.769274932792479[/C][/ROW]
[ROW][C]62[/C][C]0.206100817905758[/C][C]0.412201635811516[/C][C]0.793899182094242[/C][/ROW]
[ROW][C]63[/C][C]0.185748222567515[/C][C]0.371496445135029[/C][C]0.814251777432485[/C][/ROW]
[ROW][C]64[/C][C]0.171675480637285[/C][C]0.34335096127457[/C][C]0.828324519362715[/C][/ROW]
[ROW][C]65[/C][C]0.152965533009159[/C][C]0.305931066018317[/C][C]0.847034466990841[/C][/ROW]
[ROW][C]66[/C][C]0.165371545455772[/C][C]0.330743090911544[/C][C]0.834628454544228[/C][/ROW]
[ROW][C]67[/C][C]0.152090752631646[/C][C]0.304181505263292[/C][C]0.847909247368354[/C][/ROW]
[ROW][C]68[/C][C]0.141604571474001[/C][C]0.283209142948003[/C][C]0.858395428525998[/C][/ROW]
[ROW][C]69[/C][C]0.169920565001037[/C][C]0.339841130002074[/C][C]0.830079434998963[/C][/ROW]
[ROW][C]70[/C][C]0.161196837847205[/C][C]0.322393675694409[/C][C]0.838803162152795[/C][/ROW]
[ROW][C]71[/C][C]0.369517571959439[/C][C]0.739035143918878[/C][C]0.630482428040561[/C][/ROW]
[ROW][C]72[/C][C]0.340007614910859[/C][C]0.680015229821718[/C][C]0.659992385089141[/C][/ROW]
[ROW][C]73[/C][C]0.341754295953772[/C][C]0.683508591907545[/C][C]0.658245704046228[/C][/ROW]
[ROW][C]74[/C][C]0.334416123009443[/C][C]0.668832246018886[/C][C]0.665583876990557[/C][/ROW]
[ROW][C]75[/C][C]0.301714109580514[/C][C]0.603428219161029[/C][C]0.698285890419486[/C][/ROW]
[ROW][C]76[/C][C]0.345022132492474[/C][C]0.690044264984949[/C][C]0.654977867507526[/C][/ROW]
[ROW][C]77[/C][C]0.328787470508057[/C][C]0.657574941016115[/C][C]0.671212529491943[/C][/ROW]
[ROW][C]78[/C][C]0.295396130252384[/C][C]0.590792260504769[/C][C]0.704603869747616[/C][/ROW]
[ROW][C]79[/C][C]0.28134183062384[/C][C]0.56268366124768[/C][C]0.71865816937616[/C][/ROW]
[ROW][C]80[/C][C]0.258072630922592[/C][C]0.516145261845185[/C][C]0.741927369077408[/C][/ROW]
[ROW][C]81[/C][C]0.251847172878891[/C][C]0.503694345757782[/C][C]0.748152827121109[/C][/ROW]
[ROW][C]82[/C][C]0.22327410066686[/C][C]0.44654820133372[/C][C]0.77672589933314[/C][/ROW]
[ROW][C]83[/C][C]0.200786009734307[/C][C]0.401572019468614[/C][C]0.799213990265693[/C][/ROW]
[ROW][C]84[/C][C]0.176232743104681[/C][C]0.352465486209362[/C][C]0.823767256895319[/C][/ROW]
[ROW][C]85[/C][C]0.154911222584409[/C][C]0.309822445168818[/C][C]0.845088777415591[/C][/ROW]
[ROW][C]86[/C][C]0.13646527691847[/C][C]0.27293055383694[/C][C]0.86353472308153[/C][/ROW]
[ROW][C]87[/C][C]0.117166712439445[/C][C]0.23433342487889[/C][C]0.882833287560555[/C][/ROW]
[ROW][C]88[/C][C]0.10211910685636[/C][C]0.20423821371272[/C][C]0.89788089314364[/C][/ROW]
[ROW][C]89[/C][C]0.0867528380669838[/C][C]0.173505676133968[/C][C]0.913247161933016[/C][/ROW]
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[ROW][C]235[/C][C]0.00322737418949108[/C][C]0.00645474837898216[/C][C]0.996772625810509[/C][/ROW]
[ROW][C]236[/C][C]0.00233072189049196[/C][C]0.00466144378098391[/C][C]0.997669278109508[/C][/ROW]
[ROW][C]237[/C][C]0.0820979417736577[/C][C]0.164195883547315[/C][C]0.917902058226342[/C][/ROW]
[ROW][C]238[/C][C]0.0640218751450946[/C][C]0.128043750290189[/C][C]0.935978124854906[/C][/ROW]
[ROW][C]239[/C][C]0.103497170300183[/C][C]0.206994340600366[/C][C]0.896502829699817[/C][/ROW]
[ROW][C]240[/C][C]0.0957090000393143[/C][C]0.191418000078629[/C][C]0.904290999960686[/C][/ROW]
[ROW][C]241[/C][C]0.0722792468393709[/C][C]0.144558493678742[/C][C]0.927720753160629[/C][/ROW]
[ROW][C]242[/C][C]0.0529938370865341[/C][C]0.105987674173068[/C][C]0.947006162913466[/C][/ROW]
[ROW][C]243[/C][C]0.0483025215778765[/C][C]0.0966050431557531[/C][C]0.951697478422123[/C][/ROW]
[ROW][C]244[/C][C]0.0342283115967426[/C][C]0.0684566231934852[/C][C]0.965771688403257[/C][/ROW]
[ROW][C]245[/C][C]0.0322782399543378[/C][C]0.0645564799086756[/C][C]0.967721760045662[/C][/ROW]
[ROW][C]246[/C][C]0.021955654390372[/C][C]0.043911308780744[/C][C]0.978044345609628[/C][/ROW]
[ROW][C]247[/C][C]0.0161435851159233[/C][C]0.0322871702318466[/C][C]0.983856414884077[/C][/ROW]
[ROW][C]248[/C][C]0.0157810476059429[/C][C]0.0315620952118859[/C][C]0.984218952394057[/C][/ROW]
[ROW][C]249[/C][C]0.00995398138466578[/C][C]0.0199079627693316[/C][C]0.990046018615334[/C][/ROW]
[ROW][C]250[/C][C]0.00662565612935358[/C][C]0.0132513122587072[/C][C]0.993374343870646[/C][/ROW]
[ROW][C]251[/C][C]0.00535182687295359[/C][C]0.0107036537459072[/C][C]0.994648173127046[/C][/ROW]
[ROW][C]252[/C][C]0.00488529837412567[/C][C]0.00977059674825135[/C][C]0.995114701625874[/C][/ROW]
[ROW][C]253[/C][C]0.00278706622141597[/C][C]0.00557413244283194[/C][C]0.997212933778584[/C][/ROW]
[ROW][C]254[/C][C]0.00368764357734388[/C][C]0.00737528715468777[/C][C]0.996312356422656[/C][/ROW]
[ROW][C]255[/C][C]0.00169949591930002[/C][C]0.00339899183860004[/C][C]0.9983005040807[/C][/ROW]
[ROW][C]256[/C][C]0.000893252915885405[/C][C]0.00178650583177081[/C][C]0.999106747084115[/C][/ROW]
[ROW][C]257[/C][C]0.00166082843324923[/C][C]0.00332165686649846[/C][C]0.998339171566751[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185727&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185727&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
70.8120228410392120.3759543179215760.187977158960788
80.6899118177659210.6201763644681580.310088182234079
90.5739349111123410.8521301777753180.426065088887659
100.4786860927621880.9573721855243750.521313907237812
110.3809111470650230.7618222941300460.619088852934977
120.4057454829173590.8114909658347180.594254517082641
130.3254052829974670.6508105659949350.674594717002533
140.2915018710940690.5830037421881380.708498128905931
150.319499026345310.638998052690620.68050097365469
160.2562346340289280.5124692680578560.743765365971072
170.2019936825382650.403987365076530.798006317461735
180.4566727841356610.9133455682713220.543327215864339
190.4334325257519530.8668650515039050.566567474248047
200.3622065076228240.7244130152456470.637793492377176
210.2962839489961590.5925678979923180.703716051003841
220.2381216057638320.4762432115276650.761878394236168
230.2672332691291670.5344665382583340.732766730870833
240.219561198110120.4391223962202390.78043880188988
250.1911546019478390.3823092038956770.808845398052161
260.1594459716688090.3188919433376170.840554028331191
270.1224872438557950.244974487711590.877512756144205
280.1040339029027280.2080678058054570.895966097097272
290.07808056304132640.1561611260826530.921919436958674
300.07785443389563780.1557088677912760.922145566104362
310.05909776860749930.1181955372149990.940902231392501
320.1069365615452050.213873123090410.893063438454795
330.09144303807488830.1828860761497770.908556961925112
340.06969663067095260.1393932613419050.930303369329047
350.05651229949113930.1130245989822790.943487700508861
360.2196731136579510.4393462273159010.780326886342049
370.3846997046421980.7693994092843970.615300295357802
380.3494957238986090.6989914477972180.650504276101391
390.3129952257734730.6259904515469450.687004774226527
400.2761751853144780.5523503706289560.723824814685522
410.2422161080184370.4844322160368740.757783891981563
420.2183100201803690.4366200403607370.781689979819631
430.3843669527341270.7687339054682530.615633047265873
440.3473684905513120.6947369811026240.652631509448688
450.3038760442330920.6077520884661850.696123955766908
460.4184297630715980.8368595261431970.581570236928402
470.4235688481073760.8471376962147520.576431151892624
480.379286935176710.7585738703534210.62071306482329
490.3364099263348990.6728198526697980.663590073665101
500.2999801086853790.5999602173707590.700019891314621
510.2610026626158590.5220053252317170.738997337384141
520.2275156321317060.4550312642634110.772484367868294
530.2414813246153030.4829626492306060.758518675384697
540.2087985258181230.4175970516362450.791201474181877
550.4125517599091530.8251035198183070.587448240090847
560.3921848661607120.7843697323214240.607815133839288
570.3521223281324740.7042446562649480.647877671867526
580.3155681607036290.6311363214072570.684431839296371
590.2790050809104880.5580101618209760.720994919089512
600.2549415449903810.5098830899807630.745058455009619
610.2307250672075210.4614501344150430.769274932792479
620.2061008179057580.4122016358115160.793899182094242
630.1857482225675150.3714964451350290.814251777432485
640.1716754806372850.343350961274570.828324519362715
650.1529655330091590.3059310660183170.847034466990841
660.1653715454557720.3307430909115440.834628454544228
670.1520907526316460.3041815052632920.847909247368354
680.1416045714740010.2832091429480030.858395428525998
690.1699205650010370.3398411300020740.830079434998963
700.1611968378472050.3223936756944090.838803162152795
710.3695175719594390.7390351439188780.630482428040561
720.3400076149108590.6800152298217180.659992385089141
730.3417542959537720.6835085919075450.658245704046228
740.3344161230094430.6688322460188860.665583876990557
750.3017141095805140.6034282191610290.698285890419486
760.3450221324924740.6900442649849490.654977867507526
770.3287874705080570.6575749410161150.671212529491943
780.2953961302523840.5907922605047690.704603869747616
790.281341830623840.562683661247680.71865816937616
800.2580726309225920.5161452618451850.741927369077408
810.2518471728788910.5036943457577820.748152827121109
820.223274100666860.446548201333720.77672589933314
830.2007860097343070.4015720194686140.799213990265693
840.1762327431046810.3524654862093620.823767256895319
850.1549112225844090.3098224451688180.845088777415591
860.136465276918470.272930553836940.86353472308153
870.1171667124394450.234333424878890.882833287560555
880.102119106856360.204238213712720.89788089314364
890.08675283806698380.1735056761339680.913247161933016
900.08577318397335430.1715463679467090.914226816026646
910.07569510789219850.1513902157843970.924304892107801
920.06761851559042840.1352370311808570.932381484409572
930.06072921861567980.121458437231360.93927078138432
940.0538620222401160.1077240444802320.946137977759884
950.04977759552966740.09955519105933480.950222404470333
960.04128978892951540.08257957785903080.958710211070485
970.03544300397966460.07088600795932910.964556996020335
980.0313303408354290.06266068167085790.968669659164571
990.02861087882042620.05722175764085230.971389121179574
1000.02346086343949070.04692172687898140.976539136560509
1010.01897988081444910.03795976162889810.981020119185551
1020.04818198589914610.09636397179829220.951818014100854
1030.04130442122469880.08260884244939770.958695578775301
1040.04186019237808410.08372038475616820.958139807621916
1050.04981848670703240.09963697341406470.950181513292968
1060.0577824539875920.1155649079751840.942217546012408
1070.04905899571406750.09811799142813490.950941004285933
1080.04086222897013580.08172445794027150.959137771029864
1090.04640977091348940.09281954182697880.953590229086511
1100.03887145722875480.07774291445750960.961128542771245
1110.03330595399802660.06661190799605320.966694046001973
1120.03664465844407610.07328931688815230.963355341555924
1130.04192917077764780.08385834155529560.958070829222352
1140.04888088981365690.09776177962731390.951119110186343
1150.05273079827031910.1054615965406380.947269201729681
1160.04614348117226230.09228696234452470.953856518827738
1170.04294570759590850.0858914151918170.957054292404091
1180.04703657968863590.09407315937727170.952963420311364
1190.04088395963813450.08176791927626910.959116040361865
1200.04075410864519930.08150821729039860.959245891354801
1210.03537148573877720.07074297147755440.964628514261223
1220.03115572791968630.06231145583937270.968844272080314
1230.02567413196471650.05134826392943290.974325868035284
1240.02108234827156910.04216469654313820.978917651728431
1250.01903618525078590.03807237050157180.980963814749214
1260.01572247765610.03144495531219990.9842775223439
1270.01574436976908630.03148873953817250.984255630230914
1280.01300480758482690.02600961516965380.986995192415173
1290.01965279422712630.03930558845425250.980347205772874
1300.01728376490037880.03456752980075750.982716235099621
1310.03423366217777870.06846732435555750.965766337822221
1320.03528357923746740.07056715847493490.964716420762533
1330.0440093708087030.0880187416174060.955990629191297
1340.03715860350781070.07431720701562140.962841396492189
1350.03068825021846060.06137650043692110.969311749781539
1360.0272842526179040.0545685052358080.972715747382096
1370.03095193957579420.06190387915158830.969048060424206
1380.0451783670265520.0903567340531040.954821632973448
1390.04683322615632250.09366645231264510.953166773843677
1400.06636616157229450.1327323231445890.933633838427706
1410.05972820901333270.1194564180266650.940271790986667
1420.05017168695993170.1003433739198630.949828313040068
1430.0465334063123550.09306681262471010.953466593687645
1440.04138366746984630.08276733493969260.958616332530154
1450.05074373597690260.1014874719538050.949256264023097
1460.07025477436472320.1405095487294460.929745225635277
1470.06128637995531090.1225727599106220.938713620044689
1480.05788862584629730.1157772516925950.942111374153703
1490.05038217116142510.100764342322850.949617828838575
1500.06460107129738030.1292021425947610.93539892870262
1510.05457536232505130.1091507246501030.945424637674949
1520.04877078260169710.09754156520339430.951229217398303
1530.04163812245269130.08327624490538260.958361877547309
1540.03535173688765110.07070347377530220.964648263112349
1550.05029398880970230.1005879776194050.949706011190298
1560.06148693639257570.1229738727851510.938513063607424
1570.05706182895500210.1141236579100040.942938171044998
1580.04778558354494690.09557116708989380.952214416455053
1590.05371611290984240.1074322258196850.946283887090158
1600.05303899046347170.1060779809269430.946961009536528
1610.04677554016001590.09355108032003190.953224459839984
1620.0414022326652090.0828044653304180.958597767334791
1630.03552858612646410.07105717225292830.964471413873536
1640.04068232294523740.08136464589047490.959317677054763
1650.03411119026924820.06822238053849640.965888809730752
1660.03903508515821350.0780701703164270.960964914841786
1670.03223830630217240.06447661260434480.967761693697828
1680.02817127116240160.05634254232480330.971828728837598
1690.02350740238106530.04701480476213050.976492597618935
1700.02385754517134450.04771509034268910.976142454828655
1710.02008583896761190.04017167793522380.979914161032388
1720.01732432081311120.03464864162622240.982675679186889
1730.01491363735660340.02982727471320690.985086362643397
1740.01859590020747990.03719180041495990.98140409979252
1750.01563477552567310.03126955105134620.984365224474327
1760.01320876520398520.02641753040797040.986791234796015
1770.0107998136635930.0215996273271860.989200186336407
1780.008724440284692810.01744888056938560.991275559715307
1790.006846673416004020.0136933468320080.993153326583996
1800.006220333465802980.0124406669316060.993779666534197
1810.005744154665614330.01148830933122870.994255845334386
1820.00531035418583720.01062070837167440.994689645814163
1830.01261449811673390.02522899623346790.987385501883266
1840.01119028002912560.02238056005825110.988809719970874
1850.02686208731596510.05372417463193010.973137912684035
1860.02617584241449470.05235168482898950.973824157585505
1870.03326168594382810.06652337188765630.966738314056172
1880.0289329493145520.05786589862910390.971067050685448
1890.02597423554430060.05194847108860130.974025764455699
1900.02722281229719660.05444562459439330.972777187702803
1910.02192919145778880.04385838291557760.978070808542211
1920.01925954598469130.03851909196938260.980740454015309
1930.01706542138170320.03413084276340630.982934578618297
1940.01738927310982370.03477854621964740.982610726890176
1950.01374552891208970.02749105782417940.98625447108791
1960.01142562909986120.02285125819972240.988574370900139
1970.01277854941557840.02555709883115680.987221450584422
1980.01214876351617780.02429752703235560.987851236483822
1990.01034562538017150.02069125076034290.989654374619829
2000.01181744062504570.02363488125009130.988182559374954
2010.01784724267487670.03569448534975340.982152757325123
2020.01434344691606860.02868689383213720.985656553083931
2030.01546492231553740.03092984463107470.984535077684463
2040.01269326355395520.02538652710791050.987306736446045
2050.01056157891346910.02112315782693820.989438421086531
2060.008536105675257310.01707221135051460.991463894324743
2070.008284340225453930.01656868045090790.991715659774546
2080.007801580390025720.01560316078005140.992198419609974
2090.007500549291628960.01500109858325790.992499450708371
2100.006256963922345210.01251392784469040.993743036077655
2110.00474921660056750.009498433201135010.995250783399433
2120.005638618281076830.01127723656215370.994361381718923
2130.004693943092836650.009387886185673290.995306056907163
2140.004907831943471830.009815663886943660.995092168056528
2150.006109003763976940.01221800752795390.993890996236023
2160.005091288919536420.01018257783907280.994908711080464
2170.006507519222060490.0130150384441210.99349248077794
2180.004983956170050070.009967912340100140.99501604382995
2190.003737636009920270.007475272019840530.99626236399008
2200.002983881506223720.005967763012447440.997016118493776
2210.0021584510249950.004316902049990010.997841548975005
2220.001556089123902430.003112178247804860.998443910876098
2230.001745927731941110.003491855463882220.998254072268059
2240.001292006061598140.002584012123196280.998707993938402
2250.0009302197244673220.001860439448934640.999069780275533
2260.005167628785770290.01033525757154060.99483237121423
2270.003614510113627820.007229020227255640.996385489886372
2280.00277707340453070.005554146809061390.997222926595469
2290.002023835886202020.004047671772404040.997976164113798
2300.001420328493925840.002840656987851690.998579671506074
2310.0009400359748289320.001880071949657860.999059964025171
2320.001019369047656290.002038738095312580.998980630952344
2330.001084751721912250.002169503443824510.998915248278088
2340.00473677102771520.00947354205543040.995263228972285
2350.003227374189491080.006454748378982160.996772625810509
2360.002330721890491960.004661443780983910.997669278109508
2370.08209794177365770.1641958835473150.917902058226342
2380.06402187514509460.1280437502901890.935978124854906
2390.1034971703001830.2069943406003660.896502829699817
2400.09570900003931430.1914180000786290.904290999960686
2410.07227924683937090.1445584936787420.927720753160629
2420.05299383708653410.1059876741730680.947006162913466
2430.04830252157787650.09660504315575310.951697478422123
2440.03422831159674260.06845662319348520.965771688403257
2450.03227823995433780.06455647990867560.967721760045662
2460.0219556543903720.0439113087807440.978044345609628
2470.01614358511592330.03228717023184660.983856414884077
2480.01578104760594290.03156209521188590.984218952394057
2490.009953981384665780.01990796276933160.990046018615334
2500.006625656129353580.01325131225870720.993374343870646
2510.005351826872953590.01070365374590720.994648173127046
2520.004885298374125670.009770596748251350.995114701625874
2530.002787066221415970.005574132442831940.997212933778584
2540.003687643577343880.007375287154687770.996312356422656
2550.001699495919300020.003398991838600040.9983005040807
2560.0008932529158854050.001786505831770810.999106747084115
2570.001660828433249230.003321656866498460.998339171566751







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level270.107569721115538NOK
5% type I error level830.330677290836653NOK
10% type I error level1400.557768924302789NOK

\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 & 27 & 0.107569721115538 & NOK \tabularnewline
5% type I error level & 83 & 0.330677290836653 & NOK \tabularnewline
10% type I error level & 140 & 0.557768924302789 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185727&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]27[/C][C]0.107569721115538[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]83[/C][C]0.330677290836653[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]140[/C][C]0.557768924302789[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185727&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185727&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 level270.107569721115538NOK
5% type I error level830.330677290836653NOK
10% type I error level1400.557768924302789NOK



Parameters (Session):
par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,mysum$coefficients[i,1])
a<-table.element(a, round(mysum$coefficients[i,2],6))
a<-table.element(a, round(mysum$coefficients[i,3],4))
a<-table.element(a, round(mysum$coefficients[i,4],6))
a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, sqrt(mysum$r.squared))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, mysum$r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, mysum$adj.r.squared)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, mysum$fstatistic[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, mysum$fstatistic[3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, mysum$sigma)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, sum(myerror*myerror))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]-mysum$resid[i])
a<-table.element(a,mysum$resid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,gqarr[mypoint-kp3+1,1])
a<-table.element(a,gqarr[mypoint-kp3+1,2])
a<-table.element(a,gqarr[mypoint-kp3+1,3])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,numsignificant1)
a<-table.element(a,numsignificant1/numgqtests)
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,numsignificant5)
a<-table.element(a,numsignificant5/numgqtests)
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,numsignificant10)
a<-table.element(a,numsignificant10/numgqtests)
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}