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 09:23:25 -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/t1351949028oyi2d5vvo8isjrl.htm/, Retrieved Sun, 03 Jul 2022 14:44:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185718, Retrieved Sun, 03 Jul 2022 14:44:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
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Dataseries X:
13	38	14
16	32	18
19	35	11
15	33	12
14	37	16
13	29	18
19	31	14
15	36	14
14	35	15
15	38	15
16	31	17
16	34	19
16	35	10
16	38	16
17	37	18
15	33	14
15	32	14
20	38	17
18	38	14
16	32	16
16	33	18
16	31	11
19	38	14
16	39	12
17	32	17
17	32	9
16	35	16
15	37	14
16	33	15
14	33	11
15	31	16
12	32	13
14	31	17
16	37	15
14	30	14
10	33	16
10	31	9
14	33	15
16	31	17
16	33	13
16	32	15
14	33	16
20	32	16
14	33	12
14	28	15
11	35	11
14	39	15
15	34	15
16	38	17
14	32	13
16	38	16
14	30	14
12	33	11
16	38	12
9	32	12
14	35	15
16	34	16
16	34	15
15	36	12
16	34	12
12	28	8
16	34	13
16	35	11
14	35	14
16	31	15
17	34	9
18	37	10
18	35	11
12	27	12
16	40	15
10	37	15
14	36	14
18	38	16
18	39	15
16	41	15
17	27	13
16	30	12
16	37	17
13	31	13
16	31	15
16	27	13
16	36	15
15	37	15
15	33	16
16	34	15
14	31	14
16	39	15
16	34	14
15	32	13
12	33	7
17	36	17
16	32	13
15	41	15
13	28	14
16	30	13
16	36	16
16	35	12
16	31	14
14	34	17
16	36	15
16	36	17
20	35	12
15	37	16
16	28	11
13	39	15
17	32	9
16	35	16
16	39	15
12	35	10
16	42	10
16	34	15
17	33	11
13	41	13
12	33	14
18	34	18
14	32	16
14	40	14
13	40	14
16	35	14
13	36	14
16	37	12
13	27	14
16	39	15
15	38	15
16	31	15
15	33	13
17	32	17
15	39	17
12	36	19
16	33	15
10	33	13
16	32	9
12	37	15
14	30	15
15	38	15
13	29	16
15	22	11
11	35	14
12	35	11
11	34	15
16	35	13
15	34	15
17	37	16
16	35	14
10	23	15
18	31	16
13	27	16
16	36	11
13	31	12
10	32	9
15	39	16
16	37	13
16	38	16
14	39	12
10	31	13
17	32	13
13	37	14
15	36	19
16	32	13
12	38	12
13	36	13
13	26	10
12	26	14
17	33	16
15	39	10
10	30	11
14	33	14
11	25	12
13	38	9
16	37	9
12	31	11
16	37	16
12	35	9
9	25	13
12	28	16
15	35	13
12	33	9
12	30	12
14	31	16
12	37	11
16	36	14
11	30	13
19	36	15
15	32	14
8	28	16
16	36	13
17	34	14
12	31	15
11	28	13
11	36	11
14	36	11
16	40	14
12	33	15
16	37	11
13	32	15
15	38	12
16	31	14
16	37	14
14	33	8
16	32	13
16	30	9
14	30	15
11	31	17
12	32	13
15	34	15
15	36	15
16	37	14
16	36	16
11	33	13
15	33	16
12	33	9
12	44	16
15	39	11
15	32	10
16	35	11
14	25	15
17	35	17
14	34	14
13	35	8
15	39	15
13	33	11
14	36	16
15	32	10
12	32	15
13	36	9
8	36	16
14	32	19
14	34	12
11	33	8
12	35	11
13	30	14
10	38	9
16	34	15
18	33	13
13	32	16
11	31	11
4	30	12
13	27	13
16	31	10
10	30	11
12	32	12
12	35	8
10	28	12
13	33	12
15	31	15
12	35	11
14	35	13
10	32	14
12	21	10
12	20	12
11	34	15
10	32	13
12	34	13
16	32	13
12	33	12
14	33	12
16	37	9
14	32	9
13	34	15
4	30	10
15	30	14
11	38	15
11	36	7
14	32	14




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 11 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185718&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]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185718&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185718&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 time11 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Doorzettingsvermogen[t] = + 5.71492028571314 + 0.172790536906141Zelfstandig[t] + 0.202782719936373Stressbestendig[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Doorzettingsvermogen[t] =  +  5.71492028571314 +  0.172790536906141Zelfstandig[t] +  0.202782719936373Stressbestendig[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185718&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Doorzettingsvermogen[t] =  +  5.71492028571314 +  0.172790536906141Zelfstandig[t] +  0.202782719936373Stressbestendig[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185718&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185718&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] = + 5.71492028571314 + 0.172790536906141Zelfstandig[t] + 0.202782719936373Stressbestendig[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.714920285713141.447543.9480.0001015.1e-05
Zelfstandig0.1727905369061410.0386854.46661.2e-056e-06
Stressbestendig0.2027827199363730.0573473.5360.000480.00024

\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) & 5.71492028571314 & 1.44754 & 3.948 & 0.000101 & 5.1e-05 \tabularnewline
Zelfstandig & 0.172790536906141 & 0.038685 & 4.4666 & 1.2e-05 & 6e-06 \tabularnewline
Stressbestendig & 0.202782719936373 & 0.057347 & 3.536 & 0.00048 & 0.00024 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185718&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]5.71492028571314[/C][C]1.44754[/C][C]3.948[/C][C]0.000101[/C][C]5.1e-05[/C][/ROW]
[ROW][C]Zelfstandig[/C][C]0.172790536906141[/C][C]0.038685[/C][C]4.4666[/C][C]1.2e-05[/C][C]6e-06[/C][/ROW]
[ROW][C]Stressbestendig[/C][C]0.202782719936373[/C][C]0.057347[/C][C]3.536[/C][C]0.00048[/C][C]0.00024[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185718&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185718&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)5.714920285713141.447543.9480.0001015.1e-05
Zelfstandig0.1727905369061410.0386854.46661.2e-056e-06
Stressbestendig0.2027827199363730.0573473.5360.000480.00024







Multiple Linear Regression - Regression Statistics
Multiple R0.349699844892796
R-squared0.122289981518046
Adjusted R-squared0.115564234249985
F-TEST (value)18.1823634823112
F-TEST (DF numerator)2
F-TEST (DF denominator)261
p-value4.04867347425508e-08
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.30970570564996
Sum Squared Residuals1392.36725659183

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.349699844892796 \tabularnewline
R-squared & 0.122289981518046 \tabularnewline
Adjusted R-squared & 0.115564234249985 \tabularnewline
F-TEST (value) & 18.1823634823112 \tabularnewline
F-TEST (DF numerator) & 2 \tabularnewline
F-TEST (DF denominator) & 261 \tabularnewline
p-value & 4.04867347425508e-08 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.30970570564996 \tabularnewline
Sum Squared Residuals & 1392.36725659183 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185718&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.349699844892796[/C][/ROW]
[ROW][C]R-squared[/C][C]0.122289981518046[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.115564234249985[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]18.1823634823112[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]2[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]261[/C][/ROW]
[ROW][C]p-value[/C][C]4.04867347425508e-08[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.30970570564996[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1392.36725659183[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185718&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185718&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 R0.349699844892796
R-squared0.122289981518046
Adjusted R-squared0.115564234249985
F-TEST (value)18.1823634823112
F-TEST (DF numerator)2
F-TEST (DF denominator)261
p-value4.04867347425508e-08
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.30970570564996
Sum Squared Residuals1392.36725659183







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.1199187672557-2.11991876725571
21614.89430642556441.10569357443563
31913.99319899672825.00680100327182
41513.85040064285231.14959935714773
51415.3526936702223-1.35269367022233
61314.3759348148459-1.37593481484595
71913.91038500891275.08961499108726
81514.77433769344340.225662306556557
91414.8043298764737-0.804329876473675
101515.3227014871921-0.322701487192098
111614.51873316872191.48126683127814
121615.4426702193130.557329780686974
131613.79041627679182.20958372320819
141615.52548420712850.474515792871529
151715.75825911009511.24174088990492
161514.2559660827250.744033917274981
171514.08317554581890.916824454181122
182015.72826692706484.27173307293516
191815.11991876725572.88008123274427
201614.48874098569161.51125901430838
211615.06709696247050.932903037529489
221613.30203684910362.69796315089638
231915.11991876725573.88008123274428
241614.88714386428911.11285613571088
251714.6915237056282.308476294372
261713.0692619461373.93073805386299
271615.007112596410.992887403589952
281514.94712823034960.0528717696504159
291614.45874880266141.54125119733861
301413.64761792291590.352382077084099
311514.31595044878550.684049551214517
321213.8803928258825-1.88039282588251
331414.5187331687219-0.518733168721856
341615.1499109502860.850089049714043
351413.73759447200660.262405527993404
361014.6615315225978-4.66153152259777
371012.8964714092309-2.89647140923087
381414.4587488026614-0.458748802661393
391614.51873316872191.48126683127814
401614.05318336278861.94681663721135
411614.28595826575531.71404173424475
421414.6615315225978-0.661531522597765
432014.48874098569165.51125901430837
441413.85040064285230.149599357147726
451413.59479611813070.405203881869313
461113.9931989967282-2.99319899672818
471415.4954920240982-1.49549202409824
481514.63153933956750.368460660432466
491615.72826692706480.271733072935156
501413.88039282588250.119607174117495
511615.52548420712850.474515792871529
521413.73759447200660.262405527993404
531213.6476179229159-1.6476179229159
541614.7143533273831.28564667261702
55913.6776101059461-4.67761010594613
561414.8043298764737-0.804329876473675
571614.83432205950391.16567794049609
581614.63153933956751.36846066043247
591514.36877225357070.631227746429303
601614.02319117975841.97680882024159
611212.1753170785761-0.175317078576075
621614.22597389969481.77402610030521
631613.99319899672822.00680100327182
641414.6015471565373-0.601547156537302
651614.11316772884911.88683227115089
661713.41484301994933.5851569800507
671814.13599735060413.86400264939591
681813.99319899672824.00680100327182
691212.8136574214154-0.813657421415427
701615.66828256100440.331717438995619
711015.149910950286-5.14991095028596
721414.7743376934434-0.774337693443443
731815.52548420712852.47451579287153
741815.49549202409822.50450797590176
751615.84107309791050.158926902089478
761713.01644014135183.9835598586482
771613.33202903213382.66797096786615
781615.55547639015870.444523609841297
791313.7076022889764-0.707602288976364
801614.11316772884911.88683227115089
811613.01644014135182.9835598586482
821614.97712041337981.02287958662018
831515.149910950286-0.149910950285957
841514.66153152259780.338468477402235
851614.63153933956751.36846066043247
861413.91038500891270.0896149910872628
871615.49549202409820.50450797590176
881614.42875661963121.57124338036884
891513.88039282588251.11960717411749
901212.8364870431704-0.836487043170409
911715.38268585325261.61731414674744
921613.88039282588252.11960717411749
931515.8410730979105-0.841073097910522
941313.3920133981943-0.392013398194314
951613.53481175207022.46518824792978
961615.17990313331620.820096866683811
971614.19598171666461.80401828333544
981613.91038500891272.08961499108726
991415.0371047794403-1.03710477944028
1001614.97712041337981.02287958662018
1011615.38268585325260.617314146747438
1022014.19598171666465.80401828333544
1031515.3526936702223-0.35269367022233
1041612.78366523838523.21633476161481
1051315.4954920240982-2.49549202409824
1061713.0692619461373.93073805386299
1071615.007112596410.992887403589952
1081615.49549202409820.50450797590176
1091213.7904162767918-1.79041627679181
1101614.99995003513481.0000499648652
1111614.63153933956751.36846066043247
1121713.64761792291593.3523820770841
1131315.4355076580378-2.43550765803778
1141214.255966082725-2.25596608272502
1151815.23988749937672.76011250062335
1161414.4887409856916-0.488740985691624
1171415.465499841068-1.46549984106801
1181315.465499841068-2.46549984106801
1191614.60154715653731.3984528434627
1201314.7743376934434-1.77433769344344
1211614.54156279047681.45843720952316
1221313.2192228612882-0.219222861288172
1231615.49549202409820.50450797590176
1241515.3227014871921-0.322701487192098
1251614.11316772884911.88683227115089
1261514.05318336278860.946816637211354
1271714.6915237056282.308476294372
1281515.901057463971-0.901057463970986
1291215.7882512931253-3.78825129312531
1301614.45874880266141.54125119733861
1311014.0531833627886-4.05318336278865
1321613.0692619461372.93073805386299
1331215.149910950286-3.14991095028596
1341413.9403771919430.059622808057031
1351515.3227014871921-0.322701487192098
1361313.9703693749732-0.970369374973201
1371511.74692201694833.25307798305165
1381114.6015471565373-3.6015471565373
1391213.9931989967282-1.99319899672818
1401114.6315393395675-3.63153933956753
1411614.39876443660091.60123556339907
1421514.63153933956750.368460660432466
1431715.35269367022231.64730632977767
1441614.60154715653731.3984528434627
1451012.7308434336-2.73084343359998
1461814.31595044878553.68404955121452
1471313.6247883011609-0.624788301160918
1481614.16598953363431.83401046636568
1491313.50481956904-0.504819569039991
1501013.069261946137-3.06926194613701
1511515.6982747440346-0.698274744034613
1521614.74434551041321.25565448958679
1531615.52548420712850.474515792871529
1541414.8871438642891-0.887143864289121
1551013.7076022889764-3.70760228897636
1561713.88039282588253.11960717411749
1571314.9471282303496-1.94712823034958
1581515.7882512931253-0.788251293125308
1591613.88039282588252.11960717411749
1601214.714353327383-2.71435332738298
1611314.5715549735071-1.57155497350707
1621312.23530144463650.764698555363461
1631213.046432324382-1.04643232438203
1641714.66153152259782.33846847740223
1651514.48157842441640.518421575583625
1661013.1292463121975-3.12924631219748
1671414.255966082725-0.25596608272502
1681112.4680763476031-1.46807634760314
1691314.1060051675739-1.10600516757386
1701613.93321463066772.06678536933228
1711213.3020368491036-1.30203684910362
1721615.35269367022230.64730632977767
1731213.5876335568554-1.58763355685544
174912.6708590675395-3.67085906753952
1751213.7975788380671-1.79757883806706
1761514.39876443660090.601235563399071
1771213.2420524830432-1.24205248304315
1781213.3320290321338-1.33202903213385
1791414.3159504487855-0.315950448785483
1801214.3387800705405-2.33878007054046
1811614.77433769344341.22566230655656
1821113.5348117520702-2.53481175207022
1831914.97712041337984.02287958662018
1841514.08317554581890.916824454181122
185813.7975788380671-5.79757883806706
1861614.57155497350711.42844502649293
1871714.42875661963122.57124338036884
1881214.1131677288491-2.11316772884911
1891113.1892306782579-2.18923067825794
1901114.1659895336343-3.16598953363432
1911414.1659895336343-0.165989533634324
1921615.4654998410680.534500158931992
1931214.4587488026614-2.45874880266139
1941614.33878007054051.66121992945953
1951314.2859582657553-1.28595826575525
1961514.7143533273830.285646672617021
1971613.91038500891272.08961499108726
1981614.94712823034961.05287176965042
1991413.03926976310680.960730236893218
2001613.88039282588252.11960717411749
2011612.72368087232473.27631912767527
2021413.9403771919430.059622808057031
2031114.5187331687219-3.51873316872186
2041213.8803928258825-1.88039282588251
2051514.63153933956750.368460660432466
2061514.97712041337980.022879586620184
2071614.94712823034961.05287176965042
2081615.17990313331620.820096866683811
2091114.0531833627886-3.05318336278865
2101514.66153152259780.338468477402235
2111213.2420524830432-1.24205248304315
2121216.5622274285653-4.56222742856532
2131514.68436114435270.315638855647253
2141513.27204466607341.72795533392661
2151613.99319899672822.00680100327182
2161413.07642450741230.923575492587737
2171715.20989531634641.79010468365358
2181414.4287566196312-0.428756619631161
2191313.3848508369191-0.384850836919064
2201515.4954920240982-0.49549202409824
2211313.6476179229159-0.6476179229159
2221415.1799031333162-1.17990313331619
2231513.27204466607341.72795533392661
2241214.2859582657553-2.28595826575525
2251313.7604240937616-0.760424093761578
226815.1799031333162-7.17990313331619
2271415.0970891455007-1.09708914550074
2281414.0231911797584-0.0231911797584147
2291113.0392697631068-2.03926976310678
2301213.9931989967282-1.99319899672818
2311313.7375944720066-0.737594472006596
2321014.1060051675739-4.10600516757386
2331614.63153933956751.36846066043247
2341814.05318336278863.94681663721135
2351314.4887409856916-1.48874098569162
2361113.3020368491036-2.30203684910362
237413.3320290321338-9.33202903213385
2381313.0164401413518-0.0164401413517994
2391613.09925412916722.90074587083275
2401013.1292463121975-3.12924631219748
2411213.6776101059461-1.67761010594613
2421213.3848508369191-1.38485083691906
2431012.9864479583216-2.98644795832157
2441313.8504006428523-0.850400642852273
2451514.11316772884910.88683227115089
2461213.9931989967282-1.99319899672818
2471414.3987644366009-0.398764436600929
2481014.0831755458189-4.08317554581888
2491211.37134876010580.628651239894167
2501211.60412366307240.395876336927562
2511114.6315393395675-3.63153933956753
2521013.8803928258825-3.88039282588251
2531214.2259738996948-2.22597389969479
2541613.88039282588252.11960717411749
2551213.8504006428523-1.85040064285227
2561413.85040064285230.149599357147726
2571613.93321463066772.06678536933228
2581413.0692619461370.930738053862987
2591314.6315393395675-1.63153933956753
260412.9264635922611-8.9264635922611
2611513.73759447200661.2624055279934
2621115.3227014871921-4.3227014871921
2631113.3548586538888-2.35485865388883
2641414.0831755458189-0.0831755458188784

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 15.1199187672557 & -2.11991876725571 \tabularnewline
2 & 16 & 14.8943064255644 & 1.10569357443563 \tabularnewline
3 & 19 & 13.9931989967282 & 5.00680100327182 \tabularnewline
4 & 15 & 13.8504006428523 & 1.14959935714773 \tabularnewline
5 & 14 & 15.3526936702223 & -1.35269367022233 \tabularnewline
6 & 13 & 14.3759348148459 & -1.37593481484595 \tabularnewline
7 & 19 & 13.9103850089127 & 5.08961499108726 \tabularnewline
8 & 15 & 14.7743376934434 & 0.225662306556557 \tabularnewline
9 & 14 & 14.8043298764737 & -0.804329876473675 \tabularnewline
10 & 15 & 15.3227014871921 & -0.322701487192098 \tabularnewline
11 & 16 & 14.5187331687219 & 1.48126683127814 \tabularnewline
12 & 16 & 15.442670219313 & 0.557329780686974 \tabularnewline
13 & 16 & 13.7904162767918 & 2.20958372320819 \tabularnewline
14 & 16 & 15.5254842071285 & 0.474515792871529 \tabularnewline
15 & 17 & 15.7582591100951 & 1.24174088990492 \tabularnewline
16 & 15 & 14.255966082725 & 0.744033917274981 \tabularnewline
17 & 15 & 14.0831755458189 & 0.916824454181122 \tabularnewline
18 & 20 & 15.7282669270648 & 4.27173307293516 \tabularnewline
19 & 18 & 15.1199187672557 & 2.88008123274427 \tabularnewline
20 & 16 & 14.4887409856916 & 1.51125901430838 \tabularnewline
21 & 16 & 15.0670969624705 & 0.932903037529489 \tabularnewline
22 & 16 & 13.3020368491036 & 2.69796315089638 \tabularnewline
23 & 19 & 15.1199187672557 & 3.88008123274428 \tabularnewline
24 & 16 & 14.8871438642891 & 1.11285613571088 \tabularnewline
25 & 17 & 14.691523705628 & 2.308476294372 \tabularnewline
26 & 17 & 13.069261946137 & 3.93073805386299 \tabularnewline
27 & 16 & 15.00711259641 & 0.992887403589952 \tabularnewline
28 & 15 & 14.9471282303496 & 0.0528717696504159 \tabularnewline
29 & 16 & 14.4587488026614 & 1.54125119733861 \tabularnewline
30 & 14 & 13.6476179229159 & 0.352382077084099 \tabularnewline
31 & 15 & 14.3159504487855 & 0.684049551214517 \tabularnewline
32 & 12 & 13.8803928258825 & -1.88039282588251 \tabularnewline
33 & 14 & 14.5187331687219 & -0.518733168721856 \tabularnewline
34 & 16 & 15.149910950286 & 0.850089049714043 \tabularnewline
35 & 14 & 13.7375944720066 & 0.262405527993404 \tabularnewline
36 & 10 & 14.6615315225978 & -4.66153152259777 \tabularnewline
37 & 10 & 12.8964714092309 & -2.89647140923087 \tabularnewline
38 & 14 & 14.4587488026614 & -0.458748802661393 \tabularnewline
39 & 16 & 14.5187331687219 & 1.48126683127814 \tabularnewline
40 & 16 & 14.0531833627886 & 1.94681663721135 \tabularnewline
41 & 16 & 14.2859582657553 & 1.71404173424475 \tabularnewline
42 & 14 & 14.6615315225978 & -0.661531522597765 \tabularnewline
43 & 20 & 14.4887409856916 & 5.51125901430837 \tabularnewline
44 & 14 & 13.8504006428523 & 0.149599357147726 \tabularnewline
45 & 14 & 13.5947961181307 & 0.405203881869313 \tabularnewline
46 & 11 & 13.9931989967282 & -2.99319899672818 \tabularnewline
47 & 14 & 15.4954920240982 & -1.49549202409824 \tabularnewline
48 & 15 & 14.6315393395675 & 0.368460660432466 \tabularnewline
49 & 16 & 15.7282669270648 & 0.271733072935156 \tabularnewline
50 & 14 & 13.8803928258825 & 0.119607174117495 \tabularnewline
51 & 16 & 15.5254842071285 & 0.474515792871529 \tabularnewline
52 & 14 & 13.7375944720066 & 0.262405527993404 \tabularnewline
53 & 12 & 13.6476179229159 & -1.6476179229159 \tabularnewline
54 & 16 & 14.714353327383 & 1.28564667261702 \tabularnewline
55 & 9 & 13.6776101059461 & -4.67761010594613 \tabularnewline
56 & 14 & 14.8043298764737 & -0.804329876473675 \tabularnewline
57 & 16 & 14.8343220595039 & 1.16567794049609 \tabularnewline
58 & 16 & 14.6315393395675 & 1.36846066043247 \tabularnewline
59 & 15 & 14.3687722535707 & 0.631227746429303 \tabularnewline
60 & 16 & 14.0231911797584 & 1.97680882024159 \tabularnewline
61 & 12 & 12.1753170785761 & -0.175317078576075 \tabularnewline
62 & 16 & 14.2259738996948 & 1.77402610030521 \tabularnewline
63 & 16 & 13.9931989967282 & 2.00680100327182 \tabularnewline
64 & 14 & 14.6015471565373 & -0.601547156537302 \tabularnewline
65 & 16 & 14.1131677288491 & 1.88683227115089 \tabularnewline
66 & 17 & 13.4148430199493 & 3.5851569800507 \tabularnewline
67 & 18 & 14.1359973506041 & 3.86400264939591 \tabularnewline
68 & 18 & 13.9931989967282 & 4.00680100327182 \tabularnewline
69 & 12 & 12.8136574214154 & -0.813657421415427 \tabularnewline
70 & 16 & 15.6682825610044 & 0.331717438995619 \tabularnewline
71 & 10 & 15.149910950286 & -5.14991095028596 \tabularnewline
72 & 14 & 14.7743376934434 & -0.774337693443443 \tabularnewline
73 & 18 & 15.5254842071285 & 2.47451579287153 \tabularnewline
74 & 18 & 15.4954920240982 & 2.50450797590176 \tabularnewline
75 & 16 & 15.8410730979105 & 0.158926902089478 \tabularnewline
76 & 17 & 13.0164401413518 & 3.9835598586482 \tabularnewline
77 & 16 & 13.3320290321338 & 2.66797096786615 \tabularnewline
78 & 16 & 15.5554763901587 & 0.444523609841297 \tabularnewline
79 & 13 & 13.7076022889764 & -0.707602288976364 \tabularnewline
80 & 16 & 14.1131677288491 & 1.88683227115089 \tabularnewline
81 & 16 & 13.0164401413518 & 2.9835598586482 \tabularnewline
82 & 16 & 14.9771204133798 & 1.02287958662018 \tabularnewline
83 & 15 & 15.149910950286 & -0.149910950285957 \tabularnewline
84 & 15 & 14.6615315225978 & 0.338468477402235 \tabularnewline
85 & 16 & 14.6315393395675 & 1.36846066043247 \tabularnewline
86 & 14 & 13.9103850089127 & 0.0896149910872628 \tabularnewline
87 & 16 & 15.4954920240982 & 0.50450797590176 \tabularnewline
88 & 16 & 14.4287566196312 & 1.57124338036884 \tabularnewline
89 & 15 & 13.8803928258825 & 1.11960717411749 \tabularnewline
90 & 12 & 12.8364870431704 & -0.836487043170409 \tabularnewline
91 & 17 & 15.3826858532526 & 1.61731414674744 \tabularnewline
92 & 16 & 13.8803928258825 & 2.11960717411749 \tabularnewline
93 & 15 & 15.8410730979105 & -0.841073097910522 \tabularnewline
94 & 13 & 13.3920133981943 & -0.392013398194314 \tabularnewline
95 & 16 & 13.5348117520702 & 2.46518824792978 \tabularnewline
96 & 16 & 15.1799031333162 & 0.820096866683811 \tabularnewline
97 & 16 & 14.1959817166646 & 1.80401828333544 \tabularnewline
98 & 16 & 13.9103850089127 & 2.08961499108726 \tabularnewline
99 & 14 & 15.0371047794403 & -1.03710477944028 \tabularnewline
100 & 16 & 14.9771204133798 & 1.02287958662018 \tabularnewline
101 & 16 & 15.3826858532526 & 0.617314146747438 \tabularnewline
102 & 20 & 14.1959817166646 & 5.80401828333544 \tabularnewline
103 & 15 & 15.3526936702223 & -0.35269367022233 \tabularnewline
104 & 16 & 12.7836652383852 & 3.21633476161481 \tabularnewline
105 & 13 & 15.4954920240982 & -2.49549202409824 \tabularnewline
106 & 17 & 13.069261946137 & 3.93073805386299 \tabularnewline
107 & 16 & 15.00711259641 & 0.992887403589952 \tabularnewline
108 & 16 & 15.4954920240982 & 0.50450797590176 \tabularnewline
109 & 12 & 13.7904162767918 & -1.79041627679181 \tabularnewline
110 & 16 & 14.9999500351348 & 1.0000499648652 \tabularnewline
111 & 16 & 14.6315393395675 & 1.36846066043247 \tabularnewline
112 & 17 & 13.6476179229159 & 3.3523820770841 \tabularnewline
113 & 13 & 15.4355076580378 & -2.43550765803778 \tabularnewline
114 & 12 & 14.255966082725 & -2.25596608272502 \tabularnewline
115 & 18 & 15.2398874993767 & 2.76011250062335 \tabularnewline
116 & 14 & 14.4887409856916 & -0.488740985691624 \tabularnewline
117 & 14 & 15.465499841068 & -1.46549984106801 \tabularnewline
118 & 13 & 15.465499841068 & -2.46549984106801 \tabularnewline
119 & 16 & 14.6015471565373 & 1.3984528434627 \tabularnewline
120 & 13 & 14.7743376934434 & -1.77433769344344 \tabularnewline
121 & 16 & 14.5415627904768 & 1.45843720952316 \tabularnewline
122 & 13 & 13.2192228612882 & -0.219222861288172 \tabularnewline
123 & 16 & 15.4954920240982 & 0.50450797590176 \tabularnewline
124 & 15 & 15.3227014871921 & -0.322701487192098 \tabularnewline
125 & 16 & 14.1131677288491 & 1.88683227115089 \tabularnewline
126 & 15 & 14.0531833627886 & 0.946816637211354 \tabularnewline
127 & 17 & 14.691523705628 & 2.308476294372 \tabularnewline
128 & 15 & 15.901057463971 & -0.901057463970986 \tabularnewline
129 & 12 & 15.7882512931253 & -3.78825129312531 \tabularnewline
130 & 16 & 14.4587488026614 & 1.54125119733861 \tabularnewline
131 & 10 & 14.0531833627886 & -4.05318336278865 \tabularnewline
132 & 16 & 13.069261946137 & 2.93073805386299 \tabularnewline
133 & 12 & 15.149910950286 & -3.14991095028596 \tabularnewline
134 & 14 & 13.940377191943 & 0.059622808057031 \tabularnewline
135 & 15 & 15.3227014871921 & -0.322701487192098 \tabularnewline
136 & 13 & 13.9703693749732 & -0.970369374973201 \tabularnewline
137 & 15 & 11.7469220169483 & 3.25307798305165 \tabularnewline
138 & 11 & 14.6015471565373 & -3.6015471565373 \tabularnewline
139 & 12 & 13.9931989967282 & -1.99319899672818 \tabularnewline
140 & 11 & 14.6315393395675 & -3.63153933956753 \tabularnewline
141 & 16 & 14.3987644366009 & 1.60123556339907 \tabularnewline
142 & 15 & 14.6315393395675 & 0.368460660432466 \tabularnewline
143 & 17 & 15.3526936702223 & 1.64730632977767 \tabularnewline
144 & 16 & 14.6015471565373 & 1.3984528434627 \tabularnewline
145 & 10 & 12.7308434336 & -2.73084343359998 \tabularnewline
146 & 18 & 14.3159504487855 & 3.68404955121452 \tabularnewline
147 & 13 & 13.6247883011609 & -0.624788301160918 \tabularnewline
148 & 16 & 14.1659895336343 & 1.83401046636568 \tabularnewline
149 & 13 & 13.50481956904 & -0.504819569039991 \tabularnewline
150 & 10 & 13.069261946137 & -3.06926194613701 \tabularnewline
151 & 15 & 15.6982747440346 & -0.698274744034613 \tabularnewline
152 & 16 & 14.7443455104132 & 1.25565448958679 \tabularnewline
153 & 16 & 15.5254842071285 & 0.474515792871529 \tabularnewline
154 & 14 & 14.8871438642891 & -0.887143864289121 \tabularnewline
155 & 10 & 13.7076022889764 & -3.70760228897636 \tabularnewline
156 & 17 & 13.8803928258825 & 3.11960717411749 \tabularnewline
157 & 13 & 14.9471282303496 & -1.94712823034958 \tabularnewline
158 & 15 & 15.7882512931253 & -0.788251293125308 \tabularnewline
159 & 16 & 13.8803928258825 & 2.11960717411749 \tabularnewline
160 & 12 & 14.714353327383 & -2.71435332738298 \tabularnewline
161 & 13 & 14.5715549735071 & -1.57155497350707 \tabularnewline
162 & 13 & 12.2353014446365 & 0.764698555363461 \tabularnewline
163 & 12 & 13.046432324382 & -1.04643232438203 \tabularnewline
164 & 17 & 14.6615315225978 & 2.33846847740223 \tabularnewline
165 & 15 & 14.4815784244164 & 0.518421575583625 \tabularnewline
166 & 10 & 13.1292463121975 & -3.12924631219748 \tabularnewline
167 & 14 & 14.255966082725 & -0.25596608272502 \tabularnewline
168 & 11 & 12.4680763476031 & -1.46807634760314 \tabularnewline
169 & 13 & 14.1060051675739 & -1.10600516757386 \tabularnewline
170 & 16 & 13.9332146306677 & 2.06678536933228 \tabularnewline
171 & 12 & 13.3020368491036 & -1.30203684910362 \tabularnewline
172 & 16 & 15.3526936702223 & 0.64730632977767 \tabularnewline
173 & 12 & 13.5876335568554 & -1.58763355685544 \tabularnewline
174 & 9 & 12.6708590675395 & -3.67085906753952 \tabularnewline
175 & 12 & 13.7975788380671 & -1.79757883806706 \tabularnewline
176 & 15 & 14.3987644366009 & 0.601235563399071 \tabularnewline
177 & 12 & 13.2420524830432 & -1.24205248304315 \tabularnewline
178 & 12 & 13.3320290321338 & -1.33202903213385 \tabularnewline
179 & 14 & 14.3159504487855 & -0.315950448785483 \tabularnewline
180 & 12 & 14.3387800705405 & -2.33878007054046 \tabularnewline
181 & 16 & 14.7743376934434 & 1.22566230655656 \tabularnewline
182 & 11 & 13.5348117520702 & -2.53481175207022 \tabularnewline
183 & 19 & 14.9771204133798 & 4.02287958662018 \tabularnewline
184 & 15 & 14.0831755458189 & 0.916824454181122 \tabularnewline
185 & 8 & 13.7975788380671 & -5.79757883806706 \tabularnewline
186 & 16 & 14.5715549735071 & 1.42844502649293 \tabularnewline
187 & 17 & 14.4287566196312 & 2.57124338036884 \tabularnewline
188 & 12 & 14.1131677288491 & -2.11316772884911 \tabularnewline
189 & 11 & 13.1892306782579 & -2.18923067825794 \tabularnewline
190 & 11 & 14.1659895336343 & -3.16598953363432 \tabularnewline
191 & 14 & 14.1659895336343 & -0.165989533634324 \tabularnewline
192 & 16 & 15.465499841068 & 0.534500158931992 \tabularnewline
193 & 12 & 14.4587488026614 & -2.45874880266139 \tabularnewline
194 & 16 & 14.3387800705405 & 1.66121992945953 \tabularnewline
195 & 13 & 14.2859582657553 & -1.28595826575525 \tabularnewline
196 & 15 & 14.714353327383 & 0.285646672617021 \tabularnewline
197 & 16 & 13.9103850089127 & 2.08961499108726 \tabularnewline
198 & 16 & 14.9471282303496 & 1.05287176965042 \tabularnewline
199 & 14 & 13.0392697631068 & 0.960730236893218 \tabularnewline
200 & 16 & 13.8803928258825 & 2.11960717411749 \tabularnewline
201 & 16 & 12.7236808723247 & 3.27631912767527 \tabularnewline
202 & 14 & 13.940377191943 & 0.059622808057031 \tabularnewline
203 & 11 & 14.5187331687219 & -3.51873316872186 \tabularnewline
204 & 12 & 13.8803928258825 & -1.88039282588251 \tabularnewline
205 & 15 & 14.6315393395675 & 0.368460660432466 \tabularnewline
206 & 15 & 14.9771204133798 & 0.022879586620184 \tabularnewline
207 & 16 & 14.9471282303496 & 1.05287176965042 \tabularnewline
208 & 16 & 15.1799031333162 & 0.820096866683811 \tabularnewline
209 & 11 & 14.0531833627886 & -3.05318336278865 \tabularnewline
210 & 15 & 14.6615315225978 & 0.338468477402235 \tabularnewline
211 & 12 & 13.2420524830432 & -1.24205248304315 \tabularnewline
212 & 12 & 16.5622274285653 & -4.56222742856532 \tabularnewline
213 & 15 & 14.6843611443527 & 0.315638855647253 \tabularnewline
214 & 15 & 13.2720446660734 & 1.72795533392661 \tabularnewline
215 & 16 & 13.9931989967282 & 2.00680100327182 \tabularnewline
216 & 14 & 13.0764245074123 & 0.923575492587737 \tabularnewline
217 & 17 & 15.2098953163464 & 1.79010468365358 \tabularnewline
218 & 14 & 14.4287566196312 & -0.428756619631161 \tabularnewline
219 & 13 & 13.3848508369191 & -0.384850836919064 \tabularnewline
220 & 15 & 15.4954920240982 & -0.49549202409824 \tabularnewline
221 & 13 & 13.6476179229159 & -0.6476179229159 \tabularnewline
222 & 14 & 15.1799031333162 & -1.17990313331619 \tabularnewline
223 & 15 & 13.2720446660734 & 1.72795533392661 \tabularnewline
224 & 12 & 14.2859582657553 & -2.28595826575525 \tabularnewline
225 & 13 & 13.7604240937616 & -0.760424093761578 \tabularnewline
226 & 8 & 15.1799031333162 & -7.17990313331619 \tabularnewline
227 & 14 & 15.0970891455007 & -1.09708914550074 \tabularnewline
228 & 14 & 14.0231911797584 & -0.0231911797584147 \tabularnewline
229 & 11 & 13.0392697631068 & -2.03926976310678 \tabularnewline
230 & 12 & 13.9931989967282 & -1.99319899672818 \tabularnewline
231 & 13 & 13.7375944720066 & -0.737594472006596 \tabularnewline
232 & 10 & 14.1060051675739 & -4.10600516757386 \tabularnewline
233 & 16 & 14.6315393395675 & 1.36846066043247 \tabularnewline
234 & 18 & 14.0531833627886 & 3.94681663721135 \tabularnewline
235 & 13 & 14.4887409856916 & -1.48874098569162 \tabularnewline
236 & 11 & 13.3020368491036 & -2.30203684910362 \tabularnewline
237 & 4 & 13.3320290321338 & -9.33202903213385 \tabularnewline
238 & 13 & 13.0164401413518 & -0.0164401413517994 \tabularnewline
239 & 16 & 13.0992541291672 & 2.90074587083275 \tabularnewline
240 & 10 & 13.1292463121975 & -3.12924631219748 \tabularnewline
241 & 12 & 13.6776101059461 & -1.67761010594613 \tabularnewline
242 & 12 & 13.3848508369191 & -1.38485083691906 \tabularnewline
243 & 10 & 12.9864479583216 & -2.98644795832157 \tabularnewline
244 & 13 & 13.8504006428523 & -0.850400642852273 \tabularnewline
245 & 15 & 14.1131677288491 & 0.88683227115089 \tabularnewline
246 & 12 & 13.9931989967282 & -1.99319899672818 \tabularnewline
247 & 14 & 14.3987644366009 & -0.398764436600929 \tabularnewline
248 & 10 & 14.0831755458189 & -4.08317554581888 \tabularnewline
249 & 12 & 11.3713487601058 & 0.628651239894167 \tabularnewline
250 & 12 & 11.6041236630724 & 0.395876336927562 \tabularnewline
251 & 11 & 14.6315393395675 & -3.63153933956753 \tabularnewline
252 & 10 & 13.8803928258825 & -3.88039282588251 \tabularnewline
253 & 12 & 14.2259738996948 & -2.22597389969479 \tabularnewline
254 & 16 & 13.8803928258825 & 2.11960717411749 \tabularnewline
255 & 12 & 13.8504006428523 & -1.85040064285227 \tabularnewline
256 & 14 & 13.8504006428523 & 0.149599357147726 \tabularnewline
257 & 16 & 13.9332146306677 & 2.06678536933228 \tabularnewline
258 & 14 & 13.069261946137 & 0.930738053862987 \tabularnewline
259 & 13 & 14.6315393395675 & -1.63153933956753 \tabularnewline
260 & 4 & 12.9264635922611 & -8.9264635922611 \tabularnewline
261 & 15 & 13.7375944720066 & 1.2624055279934 \tabularnewline
262 & 11 & 15.3227014871921 & -4.3227014871921 \tabularnewline
263 & 11 & 13.3548586538888 & -2.35485865388883 \tabularnewline
264 & 14 & 14.0831755458189 & -0.0831755458188784 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185718&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]15.1199187672557[/C][C]-2.11991876725571[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]14.8943064255644[/C][C]1.10569357443563[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]13.9931989967282[/C][C]5.00680100327182[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]13.8504006428523[/C][C]1.14959935714773[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]15.3526936702223[/C][C]-1.35269367022233[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.3759348148459[/C][C]-1.37593481484595[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]13.9103850089127[/C][C]5.08961499108726[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]14.7743376934434[/C][C]0.225662306556557[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]14.8043298764737[/C][C]-0.804329876473675[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]15.3227014871921[/C][C]-0.322701487192098[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.5187331687219[/C][C]1.48126683127814[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]15.442670219313[/C][C]0.557329780686974[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]13.7904162767918[/C][C]2.20958372320819[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.5254842071285[/C][C]0.474515792871529[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]15.7582591100951[/C][C]1.24174088990492[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]14.255966082725[/C][C]0.744033917274981[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.0831755458189[/C][C]0.916824454181122[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]15.7282669270648[/C][C]4.27173307293516[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.1199187672557[/C][C]2.88008123274427[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]14.4887409856916[/C][C]1.51125901430838[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.0670969624705[/C][C]0.932903037529489[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]13.3020368491036[/C][C]2.69796315089638[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]15.1199187672557[/C][C]3.88008123274428[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.8871438642891[/C][C]1.11285613571088[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]14.691523705628[/C][C]2.308476294372[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]13.069261946137[/C][C]3.93073805386299[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.00711259641[/C][C]0.992887403589952[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]14.9471282303496[/C][C]0.0528717696504159[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]14.4587488026614[/C][C]1.54125119733861[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]13.6476179229159[/C][C]0.352382077084099[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]14.3159504487855[/C][C]0.684049551214517[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]13.8803928258825[/C][C]-1.88039282588251[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.5187331687219[/C][C]-0.518733168721856[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.149910950286[/C][C]0.850089049714043[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.7375944720066[/C][C]0.262405527993404[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]14.6615315225978[/C][C]-4.66153152259777[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]12.8964714092309[/C][C]-2.89647140923087[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]14.4587488026614[/C][C]-0.458748802661393[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.5187331687219[/C][C]1.48126683127814[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.0531833627886[/C][C]1.94681663721135[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.2859582657553[/C][C]1.71404173424475[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]14.6615315225978[/C][C]-0.661531522597765[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]14.4887409856916[/C][C]5.51125901430837[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]13.8504006428523[/C][C]0.149599357147726[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]13.5947961181307[/C][C]0.405203881869313[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.9931989967282[/C][C]-2.99319899672818[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]15.4954920240982[/C][C]-1.49549202409824[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.6315393395675[/C][C]0.368460660432466[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.7282669270648[/C][C]0.271733072935156[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]13.8803928258825[/C][C]0.119607174117495[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.5254842071285[/C][C]0.474515792871529[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.7375944720066[/C][C]0.262405527993404[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]13.6476179229159[/C][C]-1.6476179229159[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]14.714353327383[/C][C]1.28564667261702[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]13.6776101059461[/C][C]-4.67761010594613[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]14.8043298764737[/C][C]-0.804329876473675[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.8343220595039[/C][C]1.16567794049609[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]14.6315393395675[/C][C]1.36846066043247[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]14.3687722535707[/C][C]0.631227746429303[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.0231911797584[/C][C]1.97680882024159[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]12.1753170785761[/C][C]-0.175317078576075[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]14.2259738996948[/C][C]1.77402610030521[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]13.9931989967282[/C][C]2.00680100327182[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.6015471565373[/C][C]-0.601547156537302[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]14.1131677288491[/C][C]1.88683227115089[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]13.4148430199493[/C][C]3.5851569800507[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]14.1359973506041[/C][C]3.86400264939591[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]13.9931989967282[/C][C]4.00680100327182[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]12.8136574214154[/C][C]-0.813657421415427[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.6682825610044[/C][C]0.331717438995619[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]15.149910950286[/C][C]-5.14991095028596[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.7743376934434[/C][C]-0.774337693443443[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]15.5254842071285[/C][C]2.47451579287153[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]15.4954920240982[/C][C]2.50450797590176[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.8410730979105[/C][C]0.158926902089478[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.0164401413518[/C][C]3.9835598586482[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]13.3320290321338[/C][C]2.66797096786615[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]15.5554763901587[/C][C]0.444523609841297[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]13.7076022889764[/C][C]-0.707602288976364[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]14.1131677288491[/C][C]1.88683227115089[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]13.0164401413518[/C][C]2.9835598586482[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]14.9771204133798[/C][C]1.02287958662018[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.149910950286[/C][C]-0.149910950285957[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.6615315225978[/C][C]0.338468477402235[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.6315393395675[/C][C]1.36846066043247[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]13.9103850089127[/C][C]0.0896149910872628[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.4954920240982[/C][C]0.50450797590176[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.4287566196312[/C][C]1.57124338036884[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]13.8803928258825[/C][C]1.11960717411749[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]12.8364870431704[/C][C]-0.836487043170409[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]15.3826858532526[/C][C]1.61731414674744[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]13.8803928258825[/C][C]2.11960717411749[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.8410730979105[/C][C]-0.841073097910522[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.3920133981943[/C][C]-0.392013398194314[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]13.5348117520702[/C][C]2.46518824792978[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.1799031333162[/C][C]0.820096866683811[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]14.1959817166646[/C][C]1.80401828333544[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]13.9103850089127[/C][C]2.08961499108726[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]15.0371047794403[/C][C]-1.03710477944028[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]14.9771204133798[/C][C]1.02287958662018[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]15.3826858532526[/C][C]0.617314146747438[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]14.1959817166646[/C][C]5.80401828333544[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]15.3526936702223[/C][C]-0.35269367022233[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]12.7836652383852[/C][C]3.21633476161481[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]15.4954920240982[/C][C]-2.49549202409824[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]13.069261946137[/C][C]3.93073805386299[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.00711259641[/C][C]0.992887403589952[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]15.4954920240982[/C][C]0.50450797590176[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]13.7904162767918[/C][C]-1.79041627679181[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]14.9999500351348[/C][C]1.0000499648652[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]14.6315393395675[/C][C]1.36846066043247[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]13.6476179229159[/C][C]3.3523820770841[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]15.4355076580378[/C][C]-2.43550765803778[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.255966082725[/C][C]-2.25596608272502[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]15.2398874993767[/C][C]2.76011250062335[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14.4887409856916[/C][C]-0.488740985691624[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]15.465499841068[/C][C]-1.46549984106801[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]15.465499841068[/C][C]-2.46549984106801[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]14.6015471565373[/C][C]1.3984528434627[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.7743376934434[/C][C]-1.77433769344344[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]14.5415627904768[/C][C]1.45843720952316[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]13.2192228612882[/C][C]-0.219222861288172[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]15.4954920240982[/C][C]0.50450797590176[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.3227014871921[/C][C]-0.322701487192098[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]14.1131677288491[/C][C]1.88683227115089[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.0531833627886[/C][C]0.946816637211354[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]14.691523705628[/C][C]2.308476294372[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]15.901057463971[/C][C]-0.901057463970986[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]15.7882512931253[/C][C]-3.78825129312531[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]14.4587488026614[/C][C]1.54125119733861[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]14.0531833627886[/C][C]-4.05318336278865[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.069261946137[/C][C]2.93073805386299[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]15.149910950286[/C][C]-3.14991095028596[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]13.940377191943[/C][C]0.059622808057031[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.3227014871921[/C][C]-0.322701487192098[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]13.9703693749732[/C][C]-0.970369374973201[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]11.7469220169483[/C][C]3.25307798305165[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]14.6015471565373[/C][C]-3.6015471565373[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]13.9931989967282[/C][C]-1.99319899672818[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]14.6315393395675[/C][C]-3.63153933956753[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]14.3987644366009[/C][C]1.60123556339907[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]14.6315393395675[/C][C]0.368460660432466[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]15.3526936702223[/C][C]1.64730632977767[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.6015471565373[/C][C]1.3984528434627[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]12.7308434336[/C][C]-2.73084343359998[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]14.3159504487855[/C][C]3.68404955121452[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]13.6247883011609[/C][C]-0.624788301160918[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.1659895336343[/C][C]1.83401046636568[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]13.50481956904[/C][C]-0.504819569039991[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]13.069261946137[/C][C]-3.06926194613701[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]15.6982747440346[/C][C]-0.698274744034613[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]14.7443455104132[/C][C]1.25565448958679[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]15.5254842071285[/C][C]0.474515792871529[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]14.8871438642891[/C][C]-0.887143864289121[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]13.7076022889764[/C][C]-3.70760228897636[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]13.8803928258825[/C][C]3.11960717411749[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]14.9471282303496[/C][C]-1.94712823034958[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]15.7882512931253[/C][C]-0.788251293125308[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]13.8803928258825[/C][C]2.11960717411749[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]14.714353327383[/C][C]-2.71435332738298[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]14.5715549735071[/C][C]-1.57155497350707[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.2353014446365[/C][C]0.764698555363461[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]13.046432324382[/C][C]-1.04643232438203[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]14.6615315225978[/C][C]2.33846847740223[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]14.4815784244164[/C][C]0.518421575583625[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]13.1292463121975[/C][C]-3.12924631219748[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.255966082725[/C][C]-0.25596608272502[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]12.4680763476031[/C][C]-1.46807634760314[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.1060051675739[/C][C]-1.10600516757386[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]13.9332146306677[/C][C]2.06678536933228[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]13.3020368491036[/C][C]-1.30203684910362[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.3526936702223[/C][C]0.64730632977767[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.5876335568554[/C][C]-1.58763355685544[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]12.6708590675395[/C][C]-3.67085906753952[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]13.7975788380671[/C][C]-1.79757883806706[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.3987644366009[/C][C]0.601235563399071[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]13.2420524830432[/C][C]-1.24205248304315[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]13.3320290321338[/C][C]-1.33202903213385[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]14.3159504487855[/C][C]-0.315950448785483[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]14.3387800705405[/C][C]-2.33878007054046[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]14.7743376934434[/C][C]1.22566230655656[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]13.5348117520702[/C][C]-2.53481175207022[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]14.9771204133798[/C][C]4.02287958662018[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]14.0831755458189[/C][C]0.916824454181122[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]13.7975788380671[/C][C]-5.79757883806706[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.5715549735071[/C][C]1.42844502649293[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.4287566196312[/C][C]2.57124338036884[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]14.1131677288491[/C][C]-2.11316772884911[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]13.1892306782579[/C][C]-2.18923067825794[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]14.1659895336343[/C][C]-3.16598953363432[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.1659895336343[/C][C]-0.165989533634324[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.465499841068[/C][C]0.534500158931992[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]14.4587488026614[/C][C]-2.45874880266139[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.3387800705405[/C][C]1.66121992945953[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]14.2859582657553[/C][C]-1.28595826575525[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]14.714353327383[/C][C]0.285646672617021[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]13.9103850089127[/C][C]2.08961499108726[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]14.9471282303496[/C][C]1.05287176965042[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]13.0392697631068[/C][C]0.960730236893218[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]13.8803928258825[/C][C]2.11960717411749[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]12.7236808723247[/C][C]3.27631912767527[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.940377191943[/C][C]0.059622808057031[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]14.5187331687219[/C][C]-3.51873316872186[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]13.8803928258825[/C][C]-1.88039282588251[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.6315393395675[/C][C]0.368460660432466[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.9771204133798[/C][C]0.022879586620184[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.9471282303496[/C][C]1.05287176965042[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]15.1799031333162[/C][C]0.820096866683811[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]14.0531833627886[/C][C]-3.05318336278865[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]14.6615315225978[/C][C]0.338468477402235[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]13.2420524830432[/C][C]-1.24205248304315[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]16.5622274285653[/C][C]-4.56222742856532[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.6843611443527[/C][C]0.315638855647253[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]13.2720446660734[/C][C]1.72795533392661[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]13.9931989967282[/C][C]2.00680100327182[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.0764245074123[/C][C]0.923575492587737[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]15.2098953163464[/C][C]1.79010468365358[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.4287566196312[/C][C]-0.428756619631161[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]13.3848508369191[/C][C]-0.384850836919064[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.4954920240982[/C][C]-0.49549202409824[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]13.6476179229159[/C][C]-0.6476179229159[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]15.1799031333162[/C][C]-1.17990313331619[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]13.2720446660734[/C][C]1.72795533392661[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]14.2859582657553[/C][C]-2.28595826575525[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]13.7604240937616[/C][C]-0.760424093761578[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]15.1799031333162[/C][C]-7.17990313331619[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]15.0970891455007[/C][C]-1.09708914550074[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]14.0231911797584[/C][C]-0.0231911797584147[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]13.0392697631068[/C][C]-2.03926976310678[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]13.9931989967282[/C][C]-1.99319899672818[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]13.7375944720066[/C][C]-0.737594472006596[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]14.1060051675739[/C][C]-4.10600516757386[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]14.6315393395675[/C][C]1.36846066043247[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]14.0531833627886[/C][C]3.94681663721135[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]14.4887409856916[/C][C]-1.48874098569162[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.3020368491036[/C][C]-2.30203684910362[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]13.3320290321338[/C][C]-9.33202903213385[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.0164401413518[/C][C]-0.0164401413517994[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]13.0992541291672[/C][C]2.90074587083275[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]13.1292463121975[/C][C]-3.12924631219748[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]13.6776101059461[/C][C]-1.67761010594613[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.3848508369191[/C][C]-1.38485083691906[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]12.9864479583216[/C][C]-2.98644795832157[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]13.8504006428523[/C][C]-0.850400642852273[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]14.1131677288491[/C][C]0.88683227115089[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]13.9931989967282[/C][C]-1.99319899672818[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]14.3987644366009[/C][C]-0.398764436600929[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]14.0831755458189[/C][C]-4.08317554581888[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]11.3713487601058[/C][C]0.628651239894167[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.6041236630724[/C][C]0.395876336927562[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]14.6315393395675[/C][C]-3.63153933956753[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]13.8803928258825[/C][C]-3.88039282588251[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]14.2259738996948[/C][C]-2.22597389969479[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]13.8803928258825[/C][C]2.11960717411749[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.8504006428523[/C][C]-1.85040064285227[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.8504006428523[/C][C]0.149599357147726[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]13.9332146306677[/C][C]2.06678536933228[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]13.069261946137[/C][C]0.930738053862987[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.6315393395675[/C][C]-1.63153933956753[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]12.9264635922611[/C][C]-8.9264635922611[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.7375944720066[/C][C]1.2624055279934[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]15.3227014871921[/C][C]-4.3227014871921[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]13.3548586538888[/C][C]-2.35485865388883[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]14.0831755458189[/C][C]-0.0831755458188784[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185718&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185718&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
11315.1199187672557-2.11991876725571
21614.89430642556441.10569357443563
31913.99319899672825.00680100327182
41513.85040064285231.14959935714773
51415.3526936702223-1.35269367022233
61314.3759348148459-1.37593481484595
71913.91038500891275.08961499108726
81514.77433769344340.225662306556557
91414.8043298764737-0.804329876473675
101515.3227014871921-0.322701487192098
111614.51873316872191.48126683127814
121615.4426702193130.557329780686974
131613.79041627679182.20958372320819
141615.52548420712850.474515792871529
151715.75825911009511.24174088990492
161514.2559660827250.744033917274981
171514.08317554581890.916824454181122
182015.72826692706484.27173307293516
191815.11991876725572.88008123274427
201614.48874098569161.51125901430838
211615.06709696247050.932903037529489
221613.30203684910362.69796315089638
231915.11991876725573.88008123274428
241614.88714386428911.11285613571088
251714.6915237056282.308476294372
261713.0692619461373.93073805386299
271615.007112596410.992887403589952
281514.94712823034960.0528717696504159
291614.45874880266141.54125119733861
301413.64761792291590.352382077084099
311514.31595044878550.684049551214517
321213.8803928258825-1.88039282588251
331414.5187331687219-0.518733168721856
341615.1499109502860.850089049714043
351413.73759447200660.262405527993404
361014.6615315225978-4.66153152259777
371012.8964714092309-2.89647140923087
381414.4587488026614-0.458748802661393
391614.51873316872191.48126683127814
401614.05318336278861.94681663721135
411614.28595826575531.71404173424475
421414.6615315225978-0.661531522597765
432014.48874098569165.51125901430837
441413.85040064285230.149599357147726
451413.59479611813070.405203881869313
461113.9931989967282-2.99319899672818
471415.4954920240982-1.49549202409824
481514.63153933956750.368460660432466
491615.72826692706480.271733072935156
501413.88039282588250.119607174117495
511615.52548420712850.474515792871529
521413.73759447200660.262405527993404
531213.6476179229159-1.6476179229159
541614.7143533273831.28564667261702
55913.6776101059461-4.67761010594613
561414.8043298764737-0.804329876473675
571614.83432205950391.16567794049609
581614.63153933956751.36846066043247
591514.36877225357070.631227746429303
601614.02319117975841.97680882024159
611212.1753170785761-0.175317078576075
621614.22597389969481.77402610030521
631613.99319899672822.00680100327182
641414.6015471565373-0.601547156537302
651614.11316772884911.88683227115089
661713.41484301994933.5851569800507
671814.13599735060413.86400264939591
681813.99319899672824.00680100327182
691212.8136574214154-0.813657421415427
701615.66828256100440.331717438995619
711015.149910950286-5.14991095028596
721414.7743376934434-0.774337693443443
731815.52548420712852.47451579287153
741815.49549202409822.50450797590176
751615.84107309791050.158926902089478
761713.01644014135183.9835598586482
771613.33202903213382.66797096786615
781615.55547639015870.444523609841297
791313.7076022889764-0.707602288976364
801614.11316772884911.88683227115089
811613.01644014135182.9835598586482
821614.97712041337981.02287958662018
831515.149910950286-0.149910950285957
841514.66153152259780.338468477402235
851614.63153933956751.36846066043247
861413.91038500891270.0896149910872628
871615.49549202409820.50450797590176
881614.42875661963121.57124338036884
891513.88039282588251.11960717411749
901212.8364870431704-0.836487043170409
911715.38268585325261.61731414674744
921613.88039282588252.11960717411749
931515.8410730979105-0.841073097910522
941313.3920133981943-0.392013398194314
951613.53481175207022.46518824792978
961615.17990313331620.820096866683811
971614.19598171666461.80401828333544
981613.91038500891272.08961499108726
991415.0371047794403-1.03710477944028
1001614.97712041337981.02287958662018
1011615.38268585325260.617314146747438
1022014.19598171666465.80401828333544
1031515.3526936702223-0.35269367022233
1041612.78366523838523.21633476161481
1051315.4954920240982-2.49549202409824
1061713.0692619461373.93073805386299
1071615.007112596410.992887403589952
1081615.49549202409820.50450797590176
1091213.7904162767918-1.79041627679181
1101614.99995003513481.0000499648652
1111614.63153933956751.36846066043247
1121713.64761792291593.3523820770841
1131315.4355076580378-2.43550765803778
1141214.255966082725-2.25596608272502
1151815.23988749937672.76011250062335
1161414.4887409856916-0.488740985691624
1171415.465499841068-1.46549984106801
1181315.465499841068-2.46549984106801
1191614.60154715653731.3984528434627
1201314.7743376934434-1.77433769344344
1211614.54156279047681.45843720952316
1221313.2192228612882-0.219222861288172
1231615.49549202409820.50450797590176
1241515.3227014871921-0.322701487192098
1251614.11316772884911.88683227115089
1261514.05318336278860.946816637211354
1271714.6915237056282.308476294372
1281515.901057463971-0.901057463970986
1291215.7882512931253-3.78825129312531
1301614.45874880266141.54125119733861
1311014.0531833627886-4.05318336278865
1321613.0692619461372.93073805386299
1331215.149910950286-3.14991095028596
1341413.9403771919430.059622808057031
1351515.3227014871921-0.322701487192098
1361313.9703693749732-0.970369374973201
1371511.74692201694833.25307798305165
1381114.6015471565373-3.6015471565373
1391213.9931989967282-1.99319899672818
1401114.6315393395675-3.63153933956753
1411614.39876443660091.60123556339907
1421514.63153933956750.368460660432466
1431715.35269367022231.64730632977767
1441614.60154715653731.3984528434627
1451012.7308434336-2.73084343359998
1461814.31595044878553.68404955121452
1471313.6247883011609-0.624788301160918
1481614.16598953363431.83401046636568
1491313.50481956904-0.504819569039991
1501013.069261946137-3.06926194613701
1511515.6982747440346-0.698274744034613
1521614.74434551041321.25565448958679
1531615.52548420712850.474515792871529
1541414.8871438642891-0.887143864289121
1551013.7076022889764-3.70760228897636
1561713.88039282588253.11960717411749
1571314.9471282303496-1.94712823034958
1581515.7882512931253-0.788251293125308
1591613.88039282588252.11960717411749
1601214.714353327383-2.71435332738298
1611314.5715549735071-1.57155497350707
1621312.23530144463650.764698555363461
1631213.046432324382-1.04643232438203
1641714.66153152259782.33846847740223
1651514.48157842441640.518421575583625
1661013.1292463121975-3.12924631219748
1671414.255966082725-0.25596608272502
1681112.4680763476031-1.46807634760314
1691314.1060051675739-1.10600516757386
1701613.93321463066772.06678536933228
1711213.3020368491036-1.30203684910362
1721615.35269367022230.64730632977767
1731213.5876335568554-1.58763355685544
174912.6708590675395-3.67085906753952
1751213.7975788380671-1.79757883806706
1761514.39876443660090.601235563399071
1771213.2420524830432-1.24205248304315
1781213.3320290321338-1.33202903213385
1791414.3159504487855-0.315950448785483
1801214.3387800705405-2.33878007054046
1811614.77433769344341.22566230655656
1821113.5348117520702-2.53481175207022
1831914.97712041337984.02287958662018
1841514.08317554581890.916824454181122
185813.7975788380671-5.79757883806706
1861614.57155497350711.42844502649293
1871714.42875661963122.57124338036884
1881214.1131677288491-2.11316772884911
1891113.1892306782579-2.18923067825794
1901114.1659895336343-3.16598953363432
1911414.1659895336343-0.165989533634324
1921615.4654998410680.534500158931992
1931214.4587488026614-2.45874880266139
1941614.33878007054051.66121992945953
1951314.2859582657553-1.28595826575525
1961514.7143533273830.285646672617021
1971613.91038500891272.08961499108726
1981614.94712823034961.05287176965042
1991413.03926976310680.960730236893218
2001613.88039282588252.11960717411749
2011612.72368087232473.27631912767527
2021413.9403771919430.059622808057031
2031114.5187331687219-3.51873316872186
2041213.8803928258825-1.88039282588251
2051514.63153933956750.368460660432466
2061514.97712041337980.022879586620184
2071614.94712823034961.05287176965042
2081615.17990313331620.820096866683811
2091114.0531833627886-3.05318336278865
2101514.66153152259780.338468477402235
2111213.2420524830432-1.24205248304315
2121216.5622274285653-4.56222742856532
2131514.68436114435270.315638855647253
2141513.27204466607341.72795533392661
2151613.99319899672822.00680100327182
2161413.07642450741230.923575492587737
2171715.20989531634641.79010468365358
2181414.4287566196312-0.428756619631161
2191313.3848508369191-0.384850836919064
2201515.4954920240982-0.49549202409824
2211313.6476179229159-0.6476179229159
2221415.1799031333162-1.17990313331619
2231513.27204466607341.72795533392661
2241214.2859582657553-2.28595826575525
2251313.7604240937616-0.760424093761578
226815.1799031333162-7.17990313331619
2271415.0970891455007-1.09708914550074
2281414.0231911797584-0.0231911797584147
2291113.0392697631068-2.03926976310678
2301213.9931989967282-1.99319899672818
2311313.7375944720066-0.737594472006596
2321014.1060051675739-4.10600516757386
2331614.63153933956751.36846066043247
2341814.05318336278863.94681663721135
2351314.4887409856916-1.48874098569162
2361113.3020368491036-2.30203684910362
237413.3320290321338-9.33202903213385
2381313.0164401413518-0.0164401413517994
2391613.09925412916722.90074587083275
2401013.1292463121975-3.12924631219748
2411213.6776101059461-1.67761010594613
2421213.3848508369191-1.38485083691906
2431012.9864479583216-2.98644795832157
2441313.8504006428523-0.850400642852273
2451514.11316772884910.88683227115089
2461213.9931989967282-1.99319899672818
2471414.3987644366009-0.398764436600929
2481014.0831755458189-4.08317554581888
2491211.37134876010580.628651239894167
2501211.60412366307240.395876336927562
2511114.6315393395675-3.63153933956753
2521013.8803928258825-3.88039282588251
2531214.2259738996948-2.22597389969479
2541613.88039282588252.11960717411749
2551213.8504006428523-1.85040064285227
2561413.85040064285230.149599357147726
2571613.93321463066772.06678536933228
2581413.0692619461370.930738053862987
2591314.6315393395675-1.63153933956753
260412.9264635922611-8.9264635922611
2611513.73759447200661.2624055279934
2621115.3227014871921-4.3227014871921
2631113.3548586538888-2.35485865388883
2641414.0831755458189-0.0831755458188784







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.6420861894224930.7158276211550130.357913810577507
70.6548694841128690.6902610317742620.345130515887131
80.5166202487363490.9667595025273030.483379751263651
90.4026186591932010.8052373183864030.597381340806798
100.319033124430520.638066248861040.68096687556948
110.2405285106948310.4810570213896620.759471489305169
120.2648960371682110.5297920743364220.735103962831789
130.2035576096445610.4071152192891220.796442390355439
140.1791973872678610.3583947745357230.820802612732139
150.202823987856630.405647975713260.79717601214337
160.1557731381012560.3115462762025110.844226861898744
170.1178008991005390.2356017982010780.882199100899461
180.3256321815466910.6512643630933820.674367818453309
190.3083509832218570.6167019664437150.691649016778143
200.248576007651470.4971520153029390.75142399234853
210.1956891191857920.3913782383715850.804310880814208
220.1532038749343290.3064077498686580.846796125065671
230.1790523305474690.3581046610949380.820947669452531
240.1431163840379560.2862327680759110.856883615962044
250.1234016953632710.2468033907265420.876598304636729
260.1031378443065710.2062756886131410.896862155693429
270.07701228656774690.1540245731354940.922987713432253
280.06414591452973620.1282918290594720.935854085470264
290.04708357653569330.09416715307138660.952916423464307
300.04706038661982170.09412077323964340.952939613380178
310.034857046926130.06971409385226010.96514295307387
320.06618899411190190.1323779882238040.933811005888098
330.05523356137090080.1104671227418020.944766438629099
340.04105758705449220.08211517410898430.958942412945508
350.03253679957667840.06507359915335690.967463200423322
360.1435006649027830.2870013298055650.856499335097217
370.26874178241990.5374835648397990.7312582175801
380.2370578262413670.4741156524827340.762942173758633
390.2091218801628460.4182437603256920.790878119837154
400.1825878076174860.3651756152349730.817412192382514
410.1583196619383360.3166393238766710.841680338061664
420.1385533845546590.2771067691093180.861446615445341
430.2826499857923640.5652999715847270.717350014207636
440.2498036896780290.4996073793560580.750196310321971
450.2132639394609640.4265278789219270.786736060539036
460.3008971704423970.6017943408847940.699102829557603
470.300167501304790.6003350026095790.69983249869521
480.2616178303081070.5232356606162130.738382169691893
490.2257382558026960.4514765116053930.774261744197304
500.1952108327355670.3904216654711340.804789167264433
510.1652469363206460.3304938726412930.834753063679354
520.1395889596907660.2791779193815320.860411040309234
530.1434458676454680.2868917352909350.856554132354532
540.1217155504929520.2434311009859040.878284449507048
550.2540069517658610.5080139035317210.745993048234139
560.2315623420197480.4631246840394950.768437657980252
570.2027437171515250.4054874343030510.797256282848475
580.1781771079318440.3563542158636880.821822892068156
590.151496194716890.302992389433780.84850380528311
600.1386781006923990.2773562013847980.861321899307601
610.117039428750720.234078857501440.88296057124928
620.1041311247322620.2082622494645240.895868875267738
630.09443210109599820.1888642021919960.905567898904002
640.08224219750839910.1644843950167980.917757802491601
650.07383293399674610.1476658679934920.926167066003254
660.08836144230314270.1767228846062850.911638557696857
670.1070940427608370.2141880855216740.892905957239163
680.1325199708235670.2650399416471340.867480029176433
690.1178079143839930.2356158287679870.882192085616006
700.1008768484709090.2017536969418180.899123151529091
710.242571845224350.4851436904487010.75742815477565
720.2228648259026940.4457296518053870.777135174097306
730.2188944003973090.4377888007946180.781105599602691
740.2133376211889330.4266752423778670.786662378811067
750.1885761331806090.3771522663612190.811423866819391
760.2329714850209980.4659429700419950.767028514979002
770.2298750556537080.4597501113074160.770124944346292
780.2020632316533490.4041264633066980.797936768346651
790.1851807269346810.3703614538693620.814819273065319
800.1716900656521180.3433801313042360.828309934347882
810.1769984484356450.353996896871290.823001551564355
820.1557121341222980.3114242682445960.844287865877702
830.1358830490659620.2717660981319250.864116950934038
840.1167626457383680.2335252914767360.883237354261632
850.1029217396397740.2058434792795490.897078260360226
860.08825612105614550.1765122421122910.911743878943854
870.07454634331139170.1490926866227830.925453656688608
880.06566848095247690.1313369619049540.934331519047523
890.05574331495430440.1114866299086090.944256685045696
900.05256546959111760.1051309391822350.947434530408882
910.04689065000448450.0937813000089690.953109349995516
920.0433322046378030.0866644092756060.956667795362197
930.03770015815339380.07540031630678760.962299841846606
940.03238687187583960.06477374375167920.96761312812416
950.03141026724955480.06282053449910960.968589732750445
960.02597578782073040.05195157564146080.97402421217927
970.0229059757975890.0458119515951780.977094024202411
980.02108797259403550.0421759451880710.978912027405965
990.01858287619042660.03716575238085310.981417123809573
1000.01533426903431310.03066853806862610.984665730965687
1010.01237952385296150.02475904770592310.987620476147039
1020.03794350931371110.07588701862742230.962056490686289
1030.03188807199602650.06377614399205310.968111928003973
1040.0350854336540630.0701708673081260.964914566345937
1050.03970680019146570.07941360038293140.960293199808534
1060.05055598128330590.1011119625666120.949444018716694
1070.04341582275129470.08683164550258930.956584177248705
1080.03624628165071050.07249256330142110.963753718349289
1090.03924609340170010.07849218680340030.9607539065983
1100.0332549014806470.0665098029612940.966745098519353
1110.02907602462265370.05815204924530740.970923975377346
1120.03428743086616130.06857486173232260.965712569133839
1130.03773864983851270.07547729967702540.962261350161487
1140.04220445668404150.08440891336808310.957795543315959
1150.04752600654661240.09505201309322480.952473993453388
1160.04105565450783210.08211130901566430.958944345492168
1170.03743596439842940.07487192879685870.962564035601571
1180.0398087468035690.07961749360713810.960191253196431
1190.03530459052214240.07060918104428490.964695409477858
1200.03433807544696050.0686761508939210.96566192455304
1210.03048412499967380.06096824999934750.969515875000326
1220.02670810253201620.05341620506403250.973291897467984
1230.02215289219777840.04430578439555680.977847107802222
1240.01812289928377580.03624579856755160.981877100716224
1250.01687986431084180.03375972862168360.983120135689158
1260.01415706681892180.02831413363784350.985842933181078
1270.01467563075573730.02935126151147460.985324369244263
1280.01204644819145360.02409289638290730.987953551808546
1290.0177046349800070.03540926996001390.982295365019993
1300.01593706105386580.03187412210773150.984062938946134
1310.03052377037506180.06104754075012350.969476229624938
1320.03298797982266280.06597595964532550.967012020177337
1330.04030696149739670.08061392299479340.959693038502603
1340.03427186050815620.06854372101631240.965728139491844
1350.02829376400026480.05658752800052950.971706235999735
1360.02514519991021850.05029039982043710.974854800089781
1370.03010621993584850.06021243987169710.969893780064152
1380.04330606403697360.08661212807394710.956693935963026
1390.04437846495239390.08875692990478780.955621535047606
1400.06126599632756880.1225319926551380.938734003672431
1410.05660440091969270.1132088018393850.943395599080307
1420.04804328815683530.09608657631367050.951956711843165
1430.04542530825078710.09085061650157420.954574691749213
1440.04117390856076690.08234781712153380.958826091439233
1450.05037424367763220.1007484873552640.949625756322368
1460.07197620051265340.1439524010253070.928023799487347
1470.06338407348831380.1267681469766280.936615926511686
1480.06015298389888490.120305967797770.939847016101115
1490.05273218342800560.1054643668560110.947267816571994
1500.06807505791541440.1361501158308290.931924942084586
1510.05775839841133160.1155167968226630.942241601588668
1520.05200336574424270.1040067314884850.947996634255757
1530.04444179347390060.08888358694780130.955558206526099
1540.03804108582202920.07608217164405830.961958914177971
1550.05388669663777080.1077733932755420.946113303362229
1560.06604964104703320.1320992820940660.933950358952967
1570.06234930160302040.1246986032060410.93765069839698
1580.0525957800779510.1051915601559020.947404219922049
1590.05356950662591290.1071390132518260.946430493374087
1600.05772710200317460.1154542040063490.942272897996825
1610.05238321583225230.1047664316645050.947616784167748
1620.04687562442820240.09375124885640470.953124375571798
1630.04184394683326440.08368789366652880.958156053166736
1640.04591193958479810.09182387916959620.954088060415202
1650.038529862455070.077059724910140.96147013754493
1660.04682579274443670.09365158548887350.953174207255563
1670.03934047606808670.07868095213617350.960659523931913
1680.03614747792801870.07229495585603740.963852522071981
1690.03127884012534550.06255768025069090.968721159874655
1700.03064246566497750.0612849313299550.969357534335022
1710.0269536806990380.0539073613980760.973046319300962
1720.02297158910558820.04594317821117630.977028410894412
1730.0206800945951080.04136018919021610.979319905404892
1740.02799764198160030.05599528396320050.9720023580184
1750.02505460368891060.05010920737782130.974945396311089
1760.02110371774130610.04220743548261220.978896282258694
1770.01811661246056420.03623322492112850.981883387539436
1780.01545695546243650.0309139109248730.984543044537563
1790.0124549265046410.02490985300928210.987545073495359
1800.01214420776911030.02428841553822070.98785579223089
1810.01081720396140270.02163440792280550.989182796038597
1820.01080733175874440.02161466351748880.989192668241256
1830.02108734789956540.04217469579913090.978912652100435
1840.01849032735575590.03698065471151190.981509672644244
1850.04659198101929950.09318396203859890.953408018980701
1860.04410873124665710.08821746249331420.955891268753343
1870.05203195368693020.104063907373860.94796804631307
1880.04758090385972460.09516180771944920.952419096140275
1890.04478232168811750.0895646433762350.955217678311883
1900.04938278196270340.09876556392540670.950617218037297
1910.04084851413675990.08169702827351970.95915148586324
1920.03583220170300010.07166440340600010.964167798297
1930.03373373089969530.06746746179939070.966266269100305
1940.03322235265911460.06644470531822920.966777647340885
1950.02754666343421140.05509332686842280.972453336565789
1960.02320221631043650.04640443262087310.976797783689563
1970.02447389449113230.04894778898226470.975526105508868
1980.02283862915575750.0456772583115150.977161370844242
1990.01953944539234280.03907889078468560.980460554607657
2000.02121647737152050.04243295474304090.97878352262848
2010.02978988481764190.05957976963528370.970210115182358
2020.02432137105395190.04864274210790380.975678628946048
2030.0276120491606090.0552240983212180.972387950839391
2040.02375059701708860.04750119403417720.976249402982911
2050.01990445303465680.03980890606931370.980095546965343
2060.01634595629126690.03269191258253380.983654043708733
2070.0155923141322060.03118462826441210.984407685867794
2080.01448045203985310.02896090407970620.985519547960147
2090.01462318318714410.02924636637428820.985376816812856
2100.01226445229137590.02452890458275190.987735547708624
2110.009712916821074160.01942583364214830.990287083178926
2120.01233378304150260.02466756608300520.987666216958497
2130.01040464194669770.02080928389339550.989595358053302
2140.01059520763128380.02119041526256770.989404792368716
2150.01257134225249630.02514268450499250.987428657747504
2160.01047311125411710.02094622250823410.989526888745883
2170.01260630381592510.02521260763185010.987393696184075
2180.009930993156755150.01986198631351030.990069006843245
2190.007687833821455910.01537566764291180.992312166178544
2200.006287374373525950.01257474874705190.993712625626474
2210.004719642238337590.009439284476675170.995280357761662
2220.003555805028961810.007111610057923610.996444194971038
2230.003878598796099530.007757197592199070.9961214012039
2240.003047216680717490.006094433361434990.996952783319282
2250.002281507643270490.004563015286540990.997718492356729
2260.01199396438672020.02398792877344040.98800603561328
2270.008784024197116830.01756804839423370.991215975802883
2280.006930950022204640.01386190004440930.993069049977795
2290.0053224899039940.0106449798079880.994677510096006
2300.003964674519451650.00792934903890330.996035325480548
2310.002758689740148430.005517379480296850.997241310259852
2320.003084577790040550.006169155580081110.996915422209959
2330.00316096931148640.00632193862297280.996839030688514
2340.01116247241727060.02232494483454120.988837527582729
2350.008046603313676720.01609320662735340.991953396686323
2360.00614275776750830.01228551553501660.993857242232492
2370.1453088334594470.2906176669188930.854691166540553
2380.1176073663376180.2352147326752350.882392633662382
2390.1738992404400120.3477984808800240.826100759559988
2400.1647383552848880.3294767105697770.835261644715112
2410.1309958238372220.2619916476744440.869004176162778
2420.1012086860103520.2024173720207040.898791313989648
2430.09479726564769040.1895945312953810.90520273435231
2440.07099435686507940.1419887137301590.929005643134921
2450.06696278641675760.1339255728335150.933037213583242
2460.04862220434695750.09724440869391490.951377795653043
2470.03740378313504330.07480756627008660.962596216864957
2480.03766520311211820.07533040622423640.962334796887882
2490.02530413371425810.05060826742851610.974695866285742
2500.01780700689265070.03561401378530130.982192993107349
2510.01527631200522520.03055262401045030.984723687994775
2520.01455328612054310.02910657224108620.985446713879457
2530.009171575838865730.01834315167773150.990828424161134
2540.01167674852508970.02335349705017940.98832325147491
2550.006160440393980070.01232088078796010.99383955960602
2560.00364129672057250.0072825934411450.996358703279428
2570.006612088986714110.01322417797342820.993387911013286
2580.01218926596232240.02437853192464490.987810734037678

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
6 & 0.642086189422493 & 0.715827621155013 & 0.357913810577507 \tabularnewline
7 & 0.654869484112869 & 0.690261031774262 & 0.345130515887131 \tabularnewline
8 & 0.516620248736349 & 0.966759502527303 & 0.483379751263651 \tabularnewline
9 & 0.402618659193201 & 0.805237318386403 & 0.597381340806798 \tabularnewline
10 & 0.31903312443052 & 0.63806624886104 & 0.68096687556948 \tabularnewline
11 & 0.240528510694831 & 0.481057021389662 & 0.759471489305169 \tabularnewline
12 & 0.264896037168211 & 0.529792074336422 & 0.735103962831789 \tabularnewline
13 & 0.203557609644561 & 0.407115219289122 & 0.796442390355439 \tabularnewline
14 & 0.179197387267861 & 0.358394774535723 & 0.820802612732139 \tabularnewline
15 & 0.20282398785663 & 0.40564797571326 & 0.79717601214337 \tabularnewline
16 & 0.155773138101256 & 0.311546276202511 & 0.844226861898744 \tabularnewline
17 & 0.117800899100539 & 0.235601798201078 & 0.882199100899461 \tabularnewline
18 & 0.325632181546691 & 0.651264363093382 & 0.674367818453309 \tabularnewline
19 & 0.308350983221857 & 0.616701966443715 & 0.691649016778143 \tabularnewline
20 & 0.24857600765147 & 0.497152015302939 & 0.75142399234853 \tabularnewline
21 & 0.195689119185792 & 0.391378238371585 & 0.804310880814208 \tabularnewline
22 & 0.153203874934329 & 0.306407749868658 & 0.846796125065671 \tabularnewline
23 & 0.179052330547469 & 0.358104661094938 & 0.820947669452531 \tabularnewline
24 & 0.143116384037956 & 0.286232768075911 & 0.856883615962044 \tabularnewline
25 & 0.123401695363271 & 0.246803390726542 & 0.876598304636729 \tabularnewline
26 & 0.103137844306571 & 0.206275688613141 & 0.896862155693429 \tabularnewline
27 & 0.0770122865677469 & 0.154024573135494 & 0.922987713432253 \tabularnewline
28 & 0.0641459145297362 & 0.128291829059472 & 0.935854085470264 \tabularnewline
29 & 0.0470835765356933 & 0.0941671530713866 & 0.952916423464307 \tabularnewline
30 & 0.0470603866198217 & 0.0941207732396434 & 0.952939613380178 \tabularnewline
31 & 0.03485704692613 & 0.0697140938522601 & 0.96514295307387 \tabularnewline
32 & 0.0661889941119019 & 0.132377988223804 & 0.933811005888098 \tabularnewline
33 & 0.0552335613709008 & 0.110467122741802 & 0.944766438629099 \tabularnewline
34 & 0.0410575870544922 & 0.0821151741089843 & 0.958942412945508 \tabularnewline
35 & 0.0325367995766784 & 0.0650735991533569 & 0.967463200423322 \tabularnewline
36 & 0.143500664902783 & 0.287001329805565 & 0.856499335097217 \tabularnewline
37 & 0.2687417824199 & 0.537483564839799 & 0.7312582175801 \tabularnewline
38 & 0.237057826241367 & 0.474115652482734 & 0.762942173758633 \tabularnewline
39 & 0.209121880162846 & 0.418243760325692 & 0.790878119837154 \tabularnewline
40 & 0.182587807617486 & 0.365175615234973 & 0.817412192382514 \tabularnewline
41 & 0.158319661938336 & 0.316639323876671 & 0.841680338061664 \tabularnewline
42 & 0.138553384554659 & 0.277106769109318 & 0.861446615445341 \tabularnewline
43 & 0.282649985792364 & 0.565299971584727 & 0.717350014207636 \tabularnewline
44 & 0.249803689678029 & 0.499607379356058 & 0.750196310321971 \tabularnewline
45 & 0.213263939460964 & 0.426527878921927 & 0.786736060539036 \tabularnewline
46 & 0.300897170442397 & 0.601794340884794 & 0.699102829557603 \tabularnewline
47 & 0.30016750130479 & 0.600335002609579 & 0.69983249869521 \tabularnewline
48 & 0.261617830308107 & 0.523235660616213 & 0.738382169691893 \tabularnewline
49 & 0.225738255802696 & 0.451476511605393 & 0.774261744197304 \tabularnewline
50 & 0.195210832735567 & 0.390421665471134 & 0.804789167264433 \tabularnewline
51 & 0.165246936320646 & 0.330493872641293 & 0.834753063679354 \tabularnewline
52 & 0.139588959690766 & 0.279177919381532 & 0.860411040309234 \tabularnewline
53 & 0.143445867645468 & 0.286891735290935 & 0.856554132354532 \tabularnewline
54 & 0.121715550492952 & 0.243431100985904 & 0.878284449507048 \tabularnewline
55 & 0.254006951765861 & 0.508013903531721 & 0.745993048234139 \tabularnewline
56 & 0.231562342019748 & 0.463124684039495 & 0.768437657980252 \tabularnewline
57 & 0.202743717151525 & 0.405487434303051 & 0.797256282848475 \tabularnewline
58 & 0.178177107931844 & 0.356354215863688 & 0.821822892068156 \tabularnewline
59 & 0.15149619471689 & 0.30299238943378 & 0.84850380528311 \tabularnewline
60 & 0.138678100692399 & 0.277356201384798 & 0.861321899307601 \tabularnewline
61 & 0.11703942875072 & 0.23407885750144 & 0.88296057124928 \tabularnewline
62 & 0.104131124732262 & 0.208262249464524 & 0.895868875267738 \tabularnewline
63 & 0.0944321010959982 & 0.188864202191996 & 0.905567898904002 \tabularnewline
64 & 0.0822421975083991 & 0.164484395016798 & 0.917757802491601 \tabularnewline
65 & 0.0738329339967461 & 0.147665867993492 & 0.926167066003254 \tabularnewline
66 & 0.0883614423031427 & 0.176722884606285 & 0.911638557696857 \tabularnewline
67 & 0.107094042760837 & 0.214188085521674 & 0.892905957239163 \tabularnewline
68 & 0.132519970823567 & 0.265039941647134 & 0.867480029176433 \tabularnewline
69 & 0.117807914383993 & 0.235615828767987 & 0.882192085616006 \tabularnewline
70 & 0.100876848470909 & 0.201753696941818 & 0.899123151529091 \tabularnewline
71 & 0.24257184522435 & 0.485143690448701 & 0.75742815477565 \tabularnewline
72 & 0.222864825902694 & 0.445729651805387 & 0.777135174097306 \tabularnewline
73 & 0.218894400397309 & 0.437788800794618 & 0.781105599602691 \tabularnewline
74 & 0.213337621188933 & 0.426675242377867 & 0.786662378811067 \tabularnewline
75 & 0.188576133180609 & 0.377152266361219 & 0.811423866819391 \tabularnewline
76 & 0.232971485020998 & 0.465942970041995 & 0.767028514979002 \tabularnewline
77 & 0.229875055653708 & 0.459750111307416 & 0.770124944346292 \tabularnewline
78 & 0.202063231653349 & 0.404126463306698 & 0.797936768346651 \tabularnewline
79 & 0.185180726934681 & 0.370361453869362 & 0.814819273065319 \tabularnewline
80 & 0.171690065652118 & 0.343380131304236 & 0.828309934347882 \tabularnewline
81 & 0.176998448435645 & 0.35399689687129 & 0.823001551564355 \tabularnewline
82 & 0.155712134122298 & 0.311424268244596 & 0.844287865877702 \tabularnewline
83 & 0.135883049065962 & 0.271766098131925 & 0.864116950934038 \tabularnewline
84 & 0.116762645738368 & 0.233525291476736 & 0.883237354261632 \tabularnewline
85 & 0.102921739639774 & 0.205843479279549 & 0.897078260360226 \tabularnewline
86 & 0.0882561210561455 & 0.176512242112291 & 0.911743878943854 \tabularnewline
87 & 0.0745463433113917 & 0.149092686622783 & 0.925453656688608 \tabularnewline
88 & 0.0656684809524769 & 0.131336961904954 & 0.934331519047523 \tabularnewline
89 & 0.0557433149543044 & 0.111486629908609 & 0.944256685045696 \tabularnewline
90 & 0.0525654695911176 & 0.105130939182235 & 0.947434530408882 \tabularnewline
91 & 0.0468906500044845 & 0.093781300008969 & 0.953109349995516 \tabularnewline
92 & 0.043332204637803 & 0.086664409275606 & 0.956667795362197 \tabularnewline
93 & 0.0377001581533938 & 0.0754003163067876 & 0.962299841846606 \tabularnewline
94 & 0.0323868718758396 & 0.0647737437516792 & 0.96761312812416 \tabularnewline
95 & 0.0314102672495548 & 0.0628205344991096 & 0.968589732750445 \tabularnewline
96 & 0.0259757878207304 & 0.0519515756414608 & 0.97402421217927 \tabularnewline
97 & 0.022905975797589 & 0.045811951595178 & 0.977094024202411 \tabularnewline
98 & 0.0210879725940355 & 0.042175945188071 & 0.978912027405965 \tabularnewline
99 & 0.0185828761904266 & 0.0371657523808531 & 0.981417123809573 \tabularnewline
100 & 0.0153342690343131 & 0.0306685380686261 & 0.984665730965687 \tabularnewline
101 & 0.0123795238529615 & 0.0247590477059231 & 0.987620476147039 \tabularnewline
102 & 0.0379435093137111 & 0.0758870186274223 & 0.962056490686289 \tabularnewline
103 & 0.0318880719960265 & 0.0637761439920531 & 0.968111928003973 \tabularnewline
104 & 0.035085433654063 & 0.070170867308126 & 0.964914566345937 \tabularnewline
105 & 0.0397068001914657 & 0.0794136003829314 & 0.960293199808534 \tabularnewline
106 & 0.0505559812833059 & 0.101111962566612 & 0.949444018716694 \tabularnewline
107 & 0.0434158227512947 & 0.0868316455025893 & 0.956584177248705 \tabularnewline
108 & 0.0362462816507105 & 0.0724925633014211 & 0.963753718349289 \tabularnewline
109 & 0.0392460934017001 & 0.0784921868034003 & 0.9607539065983 \tabularnewline
110 & 0.033254901480647 & 0.066509802961294 & 0.966745098519353 \tabularnewline
111 & 0.0290760246226537 & 0.0581520492453074 & 0.970923975377346 \tabularnewline
112 & 0.0342874308661613 & 0.0685748617323226 & 0.965712569133839 \tabularnewline
113 & 0.0377386498385127 & 0.0754772996770254 & 0.962261350161487 \tabularnewline
114 & 0.0422044566840415 & 0.0844089133680831 & 0.957795543315959 \tabularnewline
115 & 0.0475260065466124 & 0.0950520130932248 & 0.952473993453388 \tabularnewline
116 & 0.0410556545078321 & 0.0821113090156643 & 0.958944345492168 \tabularnewline
117 & 0.0374359643984294 & 0.0748719287968587 & 0.962564035601571 \tabularnewline
118 & 0.039808746803569 & 0.0796174936071381 & 0.960191253196431 \tabularnewline
119 & 0.0353045905221424 & 0.0706091810442849 & 0.964695409477858 \tabularnewline
120 & 0.0343380754469605 & 0.068676150893921 & 0.96566192455304 \tabularnewline
121 & 0.0304841249996738 & 0.0609682499993475 & 0.969515875000326 \tabularnewline
122 & 0.0267081025320162 & 0.0534162050640325 & 0.973291897467984 \tabularnewline
123 & 0.0221528921977784 & 0.0443057843955568 & 0.977847107802222 \tabularnewline
124 & 0.0181228992837758 & 0.0362457985675516 & 0.981877100716224 \tabularnewline
125 & 0.0168798643108418 & 0.0337597286216836 & 0.983120135689158 \tabularnewline
126 & 0.0141570668189218 & 0.0283141336378435 & 0.985842933181078 \tabularnewline
127 & 0.0146756307557373 & 0.0293512615114746 & 0.985324369244263 \tabularnewline
128 & 0.0120464481914536 & 0.0240928963829073 & 0.987953551808546 \tabularnewline
129 & 0.017704634980007 & 0.0354092699600139 & 0.982295365019993 \tabularnewline
130 & 0.0159370610538658 & 0.0318741221077315 & 0.984062938946134 \tabularnewline
131 & 0.0305237703750618 & 0.0610475407501235 & 0.969476229624938 \tabularnewline
132 & 0.0329879798226628 & 0.0659759596453255 & 0.967012020177337 \tabularnewline
133 & 0.0403069614973967 & 0.0806139229947934 & 0.959693038502603 \tabularnewline
134 & 0.0342718605081562 & 0.0685437210163124 & 0.965728139491844 \tabularnewline
135 & 0.0282937640002648 & 0.0565875280005295 & 0.971706235999735 \tabularnewline
136 & 0.0251451999102185 & 0.0502903998204371 & 0.974854800089781 \tabularnewline
137 & 0.0301062199358485 & 0.0602124398716971 & 0.969893780064152 \tabularnewline
138 & 0.0433060640369736 & 0.0866121280739471 & 0.956693935963026 \tabularnewline
139 & 0.0443784649523939 & 0.0887569299047878 & 0.955621535047606 \tabularnewline
140 & 0.0612659963275688 & 0.122531992655138 & 0.938734003672431 \tabularnewline
141 & 0.0566044009196927 & 0.113208801839385 & 0.943395599080307 \tabularnewline
142 & 0.0480432881568353 & 0.0960865763136705 & 0.951956711843165 \tabularnewline
143 & 0.0454253082507871 & 0.0908506165015742 & 0.954574691749213 \tabularnewline
144 & 0.0411739085607669 & 0.0823478171215338 & 0.958826091439233 \tabularnewline
145 & 0.0503742436776322 & 0.100748487355264 & 0.949625756322368 \tabularnewline
146 & 0.0719762005126534 & 0.143952401025307 & 0.928023799487347 \tabularnewline
147 & 0.0633840734883138 & 0.126768146976628 & 0.936615926511686 \tabularnewline
148 & 0.0601529838988849 & 0.12030596779777 & 0.939847016101115 \tabularnewline
149 & 0.0527321834280056 & 0.105464366856011 & 0.947267816571994 \tabularnewline
150 & 0.0680750579154144 & 0.136150115830829 & 0.931924942084586 \tabularnewline
151 & 0.0577583984113316 & 0.115516796822663 & 0.942241601588668 \tabularnewline
152 & 0.0520033657442427 & 0.104006731488485 & 0.947996634255757 \tabularnewline
153 & 0.0444417934739006 & 0.0888835869478013 & 0.955558206526099 \tabularnewline
154 & 0.0380410858220292 & 0.0760821716440583 & 0.961958914177971 \tabularnewline
155 & 0.0538866966377708 & 0.107773393275542 & 0.946113303362229 \tabularnewline
156 & 0.0660496410470332 & 0.132099282094066 & 0.933950358952967 \tabularnewline
157 & 0.0623493016030204 & 0.124698603206041 & 0.93765069839698 \tabularnewline
158 & 0.052595780077951 & 0.105191560155902 & 0.947404219922049 \tabularnewline
159 & 0.0535695066259129 & 0.107139013251826 & 0.946430493374087 \tabularnewline
160 & 0.0577271020031746 & 0.115454204006349 & 0.942272897996825 \tabularnewline
161 & 0.0523832158322523 & 0.104766431664505 & 0.947616784167748 \tabularnewline
162 & 0.0468756244282024 & 0.0937512488564047 & 0.953124375571798 \tabularnewline
163 & 0.0418439468332644 & 0.0836878936665288 & 0.958156053166736 \tabularnewline
164 & 0.0459119395847981 & 0.0918238791695962 & 0.954088060415202 \tabularnewline
165 & 0.03852986245507 & 0.07705972491014 & 0.96147013754493 \tabularnewline
166 & 0.0468257927444367 & 0.0936515854888735 & 0.953174207255563 \tabularnewline
167 & 0.0393404760680867 & 0.0786809521361735 & 0.960659523931913 \tabularnewline
168 & 0.0361474779280187 & 0.0722949558560374 & 0.963852522071981 \tabularnewline
169 & 0.0312788401253455 & 0.0625576802506909 & 0.968721159874655 \tabularnewline
170 & 0.0306424656649775 & 0.061284931329955 & 0.969357534335022 \tabularnewline
171 & 0.026953680699038 & 0.053907361398076 & 0.973046319300962 \tabularnewline
172 & 0.0229715891055882 & 0.0459431782111763 & 0.977028410894412 \tabularnewline
173 & 0.020680094595108 & 0.0413601891902161 & 0.979319905404892 \tabularnewline
174 & 0.0279976419816003 & 0.0559952839632005 & 0.9720023580184 \tabularnewline
175 & 0.0250546036889106 & 0.0501092073778213 & 0.974945396311089 \tabularnewline
176 & 0.0211037177413061 & 0.0422074354826122 & 0.978896282258694 \tabularnewline
177 & 0.0181166124605642 & 0.0362332249211285 & 0.981883387539436 \tabularnewline
178 & 0.0154569554624365 & 0.030913910924873 & 0.984543044537563 \tabularnewline
179 & 0.012454926504641 & 0.0249098530092821 & 0.987545073495359 \tabularnewline
180 & 0.0121442077691103 & 0.0242884155382207 & 0.98785579223089 \tabularnewline
181 & 0.0108172039614027 & 0.0216344079228055 & 0.989182796038597 \tabularnewline
182 & 0.0108073317587444 & 0.0216146635174888 & 0.989192668241256 \tabularnewline
183 & 0.0210873478995654 & 0.0421746957991309 & 0.978912652100435 \tabularnewline
184 & 0.0184903273557559 & 0.0369806547115119 & 0.981509672644244 \tabularnewline
185 & 0.0465919810192995 & 0.0931839620385989 & 0.953408018980701 \tabularnewline
186 & 0.0441087312466571 & 0.0882174624933142 & 0.955891268753343 \tabularnewline
187 & 0.0520319536869302 & 0.10406390737386 & 0.94796804631307 \tabularnewline
188 & 0.0475809038597246 & 0.0951618077194492 & 0.952419096140275 \tabularnewline
189 & 0.0447823216881175 & 0.089564643376235 & 0.955217678311883 \tabularnewline
190 & 0.0493827819627034 & 0.0987655639254067 & 0.950617218037297 \tabularnewline
191 & 0.0408485141367599 & 0.0816970282735197 & 0.95915148586324 \tabularnewline
192 & 0.0358322017030001 & 0.0716644034060001 & 0.964167798297 \tabularnewline
193 & 0.0337337308996953 & 0.0674674617993907 & 0.966266269100305 \tabularnewline
194 & 0.0332223526591146 & 0.0664447053182292 & 0.966777647340885 \tabularnewline
195 & 0.0275466634342114 & 0.0550933268684228 & 0.972453336565789 \tabularnewline
196 & 0.0232022163104365 & 0.0464044326208731 & 0.976797783689563 \tabularnewline
197 & 0.0244738944911323 & 0.0489477889822647 & 0.975526105508868 \tabularnewline
198 & 0.0228386291557575 & 0.045677258311515 & 0.977161370844242 \tabularnewline
199 & 0.0195394453923428 & 0.0390788907846856 & 0.980460554607657 \tabularnewline
200 & 0.0212164773715205 & 0.0424329547430409 & 0.97878352262848 \tabularnewline
201 & 0.0297898848176419 & 0.0595797696352837 & 0.970210115182358 \tabularnewline
202 & 0.0243213710539519 & 0.0486427421079038 & 0.975678628946048 \tabularnewline
203 & 0.027612049160609 & 0.055224098321218 & 0.972387950839391 \tabularnewline
204 & 0.0237505970170886 & 0.0475011940341772 & 0.976249402982911 \tabularnewline
205 & 0.0199044530346568 & 0.0398089060693137 & 0.980095546965343 \tabularnewline
206 & 0.0163459562912669 & 0.0326919125825338 & 0.983654043708733 \tabularnewline
207 & 0.015592314132206 & 0.0311846282644121 & 0.984407685867794 \tabularnewline
208 & 0.0144804520398531 & 0.0289609040797062 & 0.985519547960147 \tabularnewline
209 & 0.0146231831871441 & 0.0292463663742882 & 0.985376816812856 \tabularnewline
210 & 0.0122644522913759 & 0.0245289045827519 & 0.987735547708624 \tabularnewline
211 & 0.00971291682107416 & 0.0194258336421483 & 0.990287083178926 \tabularnewline
212 & 0.0123337830415026 & 0.0246675660830052 & 0.987666216958497 \tabularnewline
213 & 0.0104046419466977 & 0.0208092838933955 & 0.989595358053302 \tabularnewline
214 & 0.0105952076312838 & 0.0211904152625677 & 0.989404792368716 \tabularnewline
215 & 0.0125713422524963 & 0.0251426845049925 & 0.987428657747504 \tabularnewline
216 & 0.0104731112541171 & 0.0209462225082341 & 0.989526888745883 \tabularnewline
217 & 0.0126063038159251 & 0.0252126076318501 & 0.987393696184075 \tabularnewline
218 & 0.00993099315675515 & 0.0198619863135103 & 0.990069006843245 \tabularnewline
219 & 0.00768783382145591 & 0.0153756676429118 & 0.992312166178544 \tabularnewline
220 & 0.00628737437352595 & 0.0125747487470519 & 0.993712625626474 \tabularnewline
221 & 0.00471964223833759 & 0.00943928447667517 & 0.995280357761662 \tabularnewline
222 & 0.00355580502896181 & 0.00711161005792361 & 0.996444194971038 \tabularnewline
223 & 0.00387859879609953 & 0.00775719759219907 & 0.9961214012039 \tabularnewline
224 & 0.00304721668071749 & 0.00609443336143499 & 0.996952783319282 \tabularnewline
225 & 0.00228150764327049 & 0.00456301528654099 & 0.997718492356729 \tabularnewline
226 & 0.0119939643867202 & 0.0239879287734404 & 0.98800603561328 \tabularnewline
227 & 0.00878402419711683 & 0.0175680483942337 & 0.991215975802883 \tabularnewline
228 & 0.00693095002220464 & 0.0138619000444093 & 0.993069049977795 \tabularnewline
229 & 0.005322489903994 & 0.010644979807988 & 0.994677510096006 \tabularnewline
230 & 0.00396467451945165 & 0.0079293490389033 & 0.996035325480548 \tabularnewline
231 & 0.00275868974014843 & 0.00551737948029685 & 0.997241310259852 \tabularnewline
232 & 0.00308457779004055 & 0.00616915558008111 & 0.996915422209959 \tabularnewline
233 & 0.0031609693114864 & 0.0063219386229728 & 0.996839030688514 \tabularnewline
234 & 0.0111624724172706 & 0.0223249448345412 & 0.988837527582729 \tabularnewline
235 & 0.00804660331367672 & 0.0160932066273534 & 0.991953396686323 \tabularnewline
236 & 0.0061427577675083 & 0.0122855155350166 & 0.993857242232492 \tabularnewline
237 & 0.145308833459447 & 0.290617666918893 & 0.854691166540553 \tabularnewline
238 & 0.117607366337618 & 0.235214732675235 & 0.882392633662382 \tabularnewline
239 & 0.173899240440012 & 0.347798480880024 & 0.826100759559988 \tabularnewline
240 & 0.164738355284888 & 0.329476710569777 & 0.835261644715112 \tabularnewline
241 & 0.130995823837222 & 0.261991647674444 & 0.869004176162778 \tabularnewline
242 & 0.101208686010352 & 0.202417372020704 & 0.898791313989648 \tabularnewline
243 & 0.0947972656476904 & 0.189594531295381 & 0.90520273435231 \tabularnewline
244 & 0.0709943568650794 & 0.141988713730159 & 0.929005643134921 \tabularnewline
245 & 0.0669627864167576 & 0.133925572833515 & 0.933037213583242 \tabularnewline
246 & 0.0486222043469575 & 0.0972444086939149 & 0.951377795653043 \tabularnewline
247 & 0.0374037831350433 & 0.0748075662700866 & 0.962596216864957 \tabularnewline
248 & 0.0376652031121182 & 0.0753304062242364 & 0.962334796887882 \tabularnewline
249 & 0.0253041337142581 & 0.0506082674285161 & 0.974695866285742 \tabularnewline
250 & 0.0178070068926507 & 0.0356140137853013 & 0.982192993107349 \tabularnewline
251 & 0.0152763120052252 & 0.0305526240104503 & 0.984723687994775 \tabularnewline
252 & 0.0145532861205431 & 0.0291065722410862 & 0.985446713879457 \tabularnewline
253 & 0.00917157583886573 & 0.0183431516777315 & 0.990828424161134 \tabularnewline
254 & 0.0116767485250897 & 0.0233534970501794 & 0.98832325147491 \tabularnewline
255 & 0.00616044039398007 & 0.0123208807879601 & 0.99383955960602 \tabularnewline
256 & 0.0036412967205725 & 0.007282593441145 & 0.996358703279428 \tabularnewline
257 & 0.00661208898671411 & 0.0132241779734282 & 0.993387911013286 \tabularnewline
258 & 0.0121892659623224 & 0.0243785319246449 & 0.987810734037678 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185718&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]6[/C][C]0.642086189422493[/C][C]0.715827621155013[/C][C]0.357913810577507[/C][/ROW]
[ROW][C]7[/C][C]0.654869484112869[/C][C]0.690261031774262[/C][C]0.345130515887131[/C][/ROW]
[ROW][C]8[/C][C]0.516620248736349[/C][C]0.966759502527303[/C][C]0.483379751263651[/C][/ROW]
[ROW][C]9[/C][C]0.402618659193201[/C][C]0.805237318386403[/C][C]0.597381340806798[/C][/ROW]
[ROW][C]10[/C][C]0.31903312443052[/C][C]0.63806624886104[/C][C]0.68096687556948[/C][/ROW]
[ROW][C]11[/C][C]0.240528510694831[/C][C]0.481057021389662[/C][C]0.759471489305169[/C][/ROW]
[ROW][C]12[/C][C]0.264896037168211[/C][C]0.529792074336422[/C][C]0.735103962831789[/C][/ROW]
[ROW][C]13[/C][C]0.203557609644561[/C][C]0.407115219289122[/C][C]0.796442390355439[/C][/ROW]
[ROW][C]14[/C][C]0.179197387267861[/C][C]0.358394774535723[/C][C]0.820802612732139[/C][/ROW]
[ROW][C]15[/C][C]0.20282398785663[/C][C]0.40564797571326[/C][C]0.79717601214337[/C][/ROW]
[ROW][C]16[/C][C]0.155773138101256[/C][C]0.311546276202511[/C][C]0.844226861898744[/C][/ROW]
[ROW][C]17[/C][C]0.117800899100539[/C][C]0.235601798201078[/C][C]0.882199100899461[/C][/ROW]
[ROW][C]18[/C][C]0.325632181546691[/C][C]0.651264363093382[/C][C]0.674367818453309[/C][/ROW]
[ROW][C]19[/C][C]0.308350983221857[/C][C]0.616701966443715[/C][C]0.691649016778143[/C][/ROW]
[ROW][C]20[/C][C]0.24857600765147[/C][C]0.497152015302939[/C][C]0.75142399234853[/C][/ROW]
[ROW][C]21[/C][C]0.195689119185792[/C][C]0.391378238371585[/C][C]0.804310880814208[/C][/ROW]
[ROW][C]22[/C][C]0.153203874934329[/C][C]0.306407749868658[/C][C]0.846796125065671[/C][/ROW]
[ROW][C]23[/C][C]0.179052330547469[/C][C]0.358104661094938[/C][C]0.820947669452531[/C][/ROW]
[ROW][C]24[/C][C]0.143116384037956[/C][C]0.286232768075911[/C][C]0.856883615962044[/C][/ROW]
[ROW][C]25[/C][C]0.123401695363271[/C][C]0.246803390726542[/C][C]0.876598304636729[/C][/ROW]
[ROW][C]26[/C][C]0.103137844306571[/C][C]0.206275688613141[/C][C]0.896862155693429[/C][/ROW]
[ROW][C]27[/C][C]0.0770122865677469[/C][C]0.154024573135494[/C][C]0.922987713432253[/C][/ROW]
[ROW][C]28[/C][C]0.0641459145297362[/C][C]0.128291829059472[/C][C]0.935854085470264[/C][/ROW]
[ROW][C]29[/C][C]0.0470835765356933[/C][C]0.0941671530713866[/C][C]0.952916423464307[/C][/ROW]
[ROW][C]30[/C][C]0.0470603866198217[/C][C]0.0941207732396434[/C][C]0.952939613380178[/C][/ROW]
[ROW][C]31[/C][C]0.03485704692613[/C][C]0.0697140938522601[/C][C]0.96514295307387[/C][/ROW]
[ROW][C]32[/C][C]0.0661889941119019[/C][C]0.132377988223804[/C][C]0.933811005888098[/C][/ROW]
[ROW][C]33[/C][C]0.0552335613709008[/C][C]0.110467122741802[/C][C]0.944766438629099[/C][/ROW]
[ROW][C]34[/C][C]0.0410575870544922[/C][C]0.0821151741089843[/C][C]0.958942412945508[/C][/ROW]
[ROW][C]35[/C][C]0.0325367995766784[/C][C]0.0650735991533569[/C][C]0.967463200423322[/C][/ROW]
[ROW][C]36[/C][C]0.143500664902783[/C][C]0.287001329805565[/C][C]0.856499335097217[/C][/ROW]
[ROW][C]37[/C][C]0.2687417824199[/C][C]0.537483564839799[/C][C]0.7312582175801[/C][/ROW]
[ROW][C]38[/C][C]0.237057826241367[/C][C]0.474115652482734[/C][C]0.762942173758633[/C][/ROW]
[ROW][C]39[/C][C]0.209121880162846[/C][C]0.418243760325692[/C][C]0.790878119837154[/C][/ROW]
[ROW][C]40[/C][C]0.182587807617486[/C][C]0.365175615234973[/C][C]0.817412192382514[/C][/ROW]
[ROW][C]41[/C][C]0.158319661938336[/C][C]0.316639323876671[/C][C]0.841680338061664[/C][/ROW]
[ROW][C]42[/C][C]0.138553384554659[/C][C]0.277106769109318[/C][C]0.861446615445341[/C][/ROW]
[ROW][C]43[/C][C]0.282649985792364[/C][C]0.565299971584727[/C][C]0.717350014207636[/C][/ROW]
[ROW][C]44[/C][C]0.249803689678029[/C][C]0.499607379356058[/C][C]0.750196310321971[/C][/ROW]
[ROW][C]45[/C][C]0.213263939460964[/C][C]0.426527878921927[/C][C]0.786736060539036[/C][/ROW]
[ROW][C]46[/C][C]0.300897170442397[/C][C]0.601794340884794[/C][C]0.699102829557603[/C][/ROW]
[ROW][C]47[/C][C]0.30016750130479[/C][C]0.600335002609579[/C][C]0.69983249869521[/C][/ROW]
[ROW][C]48[/C][C]0.261617830308107[/C][C]0.523235660616213[/C][C]0.738382169691893[/C][/ROW]
[ROW][C]49[/C][C]0.225738255802696[/C][C]0.451476511605393[/C][C]0.774261744197304[/C][/ROW]
[ROW][C]50[/C][C]0.195210832735567[/C][C]0.390421665471134[/C][C]0.804789167264433[/C][/ROW]
[ROW][C]51[/C][C]0.165246936320646[/C][C]0.330493872641293[/C][C]0.834753063679354[/C][/ROW]
[ROW][C]52[/C][C]0.139588959690766[/C][C]0.279177919381532[/C][C]0.860411040309234[/C][/ROW]
[ROW][C]53[/C][C]0.143445867645468[/C][C]0.286891735290935[/C][C]0.856554132354532[/C][/ROW]
[ROW][C]54[/C][C]0.121715550492952[/C][C]0.243431100985904[/C][C]0.878284449507048[/C][/ROW]
[ROW][C]55[/C][C]0.254006951765861[/C][C]0.508013903531721[/C][C]0.745993048234139[/C][/ROW]
[ROW][C]56[/C][C]0.231562342019748[/C][C]0.463124684039495[/C][C]0.768437657980252[/C][/ROW]
[ROW][C]57[/C][C]0.202743717151525[/C][C]0.405487434303051[/C][C]0.797256282848475[/C][/ROW]
[ROW][C]58[/C][C]0.178177107931844[/C][C]0.356354215863688[/C][C]0.821822892068156[/C][/ROW]
[ROW][C]59[/C][C]0.15149619471689[/C][C]0.30299238943378[/C][C]0.84850380528311[/C][/ROW]
[ROW][C]60[/C][C]0.138678100692399[/C][C]0.277356201384798[/C][C]0.861321899307601[/C][/ROW]
[ROW][C]61[/C][C]0.11703942875072[/C][C]0.23407885750144[/C][C]0.88296057124928[/C][/ROW]
[ROW][C]62[/C][C]0.104131124732262[/C][C]0.208262249464524[/C][C]0.895868875267738[/C][/ROW]
[ROW][C]63[/C][C]0.0944321010959982[/C][C]0.188864202191996[/C][C]0.905567898904002[/C][/ROW]
[ROW][C]64[/C][C]0.0822421975083991[/C][C]0.164484395016798[/C][C]0.917757802491601[/C][/ROW]
[ROW][C]65[/C][C]0.0738329339967461[/C][C]0.147665867993492[/C][C]0.926167066003254[/C][/ROW]
[ROW][C]66[/C][C]0.0883614423031427[/C][C]0.176722884606285[/C][C]0.911638557696857[/C][/ROW]
[ROW][C]67[/C][C]0.107094042760837[/C][C]0.214188085521674[/C][C]0.892905957239163[/C][/ROW]
[ROW][C]68[/C][C]0.132519970823567[/C][C]0.265039941647134[/C][C]0.867480029176433[/C][/ROW]
[ROW][C]69[/C][C]0.117807914383993[/C][C]0.235615828767987[/C][C]0.882192085616006[/C][/ROW]
[ROW][C]70[/C][C]0.100876848470909[/C][C]0.201753696941818[/C][C]0.899123151529091[/C][/ROW]
[ROW][C]71[/C][C]0.24257184522435[/C][C]0.485143690448701[/C][C]0.75742815477565[/C][/ROW]
[ROW][C]72[/C][C]0.222864825902694[/C][C]0.445729651805387[/C][C]0.777135174097306[/C][/ROW]
[ROW][C]73[/C][C]0.218894400397309[/C][C]0.437788800794618[/C][C]0.781105599602691[/C][/ROW]
[ROW][C]74[/C][C]0.213337621188933[/C][C]0.426675242377867[/C][C]0.786662378811067[/C][/ROW]
[ROW][C]75[/C][C]0.188576133180609[/C][C]0.377152266361219[/C][C]0.811423866819391[/C][/ROW]
[ROW][C]76[/C][C]0.232971485020998[/C][C]0.465942970041995[/C][C]0.767028514979002[/C][/ROW]
[ROW][C]77[/C][C]0.229875055653708[/C][C]0.459750111307416[/C][C]0.770124944346292[/C][/ROW]
[ROW][C]78[/C][C]0.202063231653349[/C][C]0.404126463306698[/C][C]0.797936768346651[/C][/ROW]
[ROW][C]79[/C][C]0.185180726934681[/C][C]0.370361453869362[/C][C]0.814819273065319[/C][/ROW]
[ROW][C]80[/C][C]0.171690065652118[/C][C]0.343380131304236[/C][C]0.828309934347882[/C][/ROW]
[ROW][C]81[/C][C]0.176998448435645[/C][C]0.35399689687129[/C][C]0.823001551564355[/C][/ROW]
[ROW][C]82[/C][C]0.155712134122298[/C][C]0.311424268244596[/C][C]0.844287865877702[/C][/ROW]
[ROW][C]83[/C][C]0.135883049065962[/C][C]0.271766098131925[/C][C]0.864116950934038[/C][/ROW]
[ROW][C]84[/C][C]0.116762645738368[/C][C]0.233525291476736[/C][C]0.883237354261632[/C][/ROW]
[ROW][C]85[/C][C]0.102921739639774[/C][C]0.205843479279549[/C][C]0.897078260360226[/C][/ROW]
[ROW][C]86[/C][C]0.0882561210561455[/C][C]0.176512242112291[/C][C]0.911743878943854[/C][/ROW]
[ROW][C]87[/C][C]0.0745463433113917[/C][C]0.149092686622783[/C][C]0.925453656688608[/C][/ROW]
[ROW][C]88[/C][C]0.0656684809524769[/C][C]0.131336961904954[/C][C]0.934331519047523[/C][/ROW]
[ROW][C]89[/C][C]0.0557433149543044[/C][C]0.111486629908609[/C][C]0.944256685045696[/C][/ROW]
[ROW][C]90[/C][C]0.0525654695911176[/C][C]0.105130939182235[/C][C]0.947434530408882[/C][/ROW]
[ROW][C]91[/C][C]0.0468906500044845[/C][C]0.093781300008969[/C][C]0.953109349995516[/C][/ROW]
[ROW][C]92[/C][C]0.043332204637803[/C][C]0.086664409275606[/C][C]0.956667795362197[/C][/ROW]
[ROW][C]93[/C][C]0.0377001581533938[/C][C]0.0754003163067876[/C][C]0.962299841846606[/C][/ROW]
[ROW][C]94[/C][C]0.0323868718758396[/C][C]0.0647737437516792[/C][C]0.96761312812416[/C][/ROW]
[ROW][C]95[/C][C]0.0314102672495548[/C][C]0.0628205344991096[/C][C]0.968589732750445[/C][/ROW]
[ROW][C]96[/C][C]0.0259757878207304[/C][C]0.0519515756414608[/C][C]0.97402421217927[/C][/ROW]
[ROW][C]97[/C][C]0.022905975797589[/C][C]0.045811951595178[/C][C]0.977094024202411[/C][/ROW]
[ROW][C]98[/C][C]0.0210879725940355[/C][C]0.042175945188071[/C][C]0.978912027405965[/C][/ROW]
[ROW][C]99[/C][C]0.0185828761904266[/C][C]0.0371657523808531[/C][C]0.981417123809573[/C][/ROW]
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[ROW][C]127[/C][C]0.0146756307557373[/C][C]0.0293512615114746[/C][C]0.985324369244263[/C][/ROW]
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[ROW][C]241[/C][C]0.130995823837222[/C][C]0.261991647674444[/C][C]0.869004176162778[/C][/ROW]
[ROW][C]242[/C][C]0.101208686010352[/C][C]0.202417372020704[/C][C]0.898791313989648[/C][/ROW]
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[ROW][C]244[/C][C]0.0709943568650794[/C][C]0.141988713730159[/C][C]0.929005643134921[/C][/ROW]
[ROW][C]245[/C][C]0.0669627864167576[/C][C]0.133925572833515[/C][C]0.933037213583242[/C][/ROW]
[ROW][C]246[/C][C]0.0486222043469575[/C][C]0.0972444086939149[/C][C]0.951377795653043[/C][/ROW]
[ROW][C]247[/C][C]0.0374037831350433[/C][C]0.0748075662700866[/C][C]0.962596216864957[/C][/ROW]
[ROW][C]248[/C][C]0.0376652031121182[/C][C]0.0753304062242364[/C][C]0.962334796887882[/C][/ROW]
[ROW][C]249[/C][C]0.0253041337142581[/C][C]0.0506082674285161[/C][C]0.974695866285742[/C][/ROW]
[ROW][C]250[/C][C]0.0178070068926507[/C][C]0.0356140137853013[/C][C]0.982192993107349[/C][/ROW]
[ROW][C]251[/C][C]0.0152763120052252[/C][C]0.0305526240104503[/C][C]0.984723687994775[/C][/ROW]
[ROW][C]252[/C][C]0.0145532861205431[/C][C]0.0291065722410862[/C][C]0.985446713879457[/C][/ROW]
[ROW][C]253[/C][C]0.00917157583886573[/C][C]0.0183431516777315[/C][C]0.990828424161134[/C][/ROW]
[ROW][C]254[/C][C]0.0116767485250897[/C][C]0.0233534970501794[/C][C]0.98832325147491[/C][/ROW]
[ROW][C]255[/C][C]0.00616044039398007[/C][C]0.0123208807879601[/C][C]0.99383955960602[/C][/ROW]
[ROW][C]256[/C][C]0.0036412967205725[/C][C]0.007282593441145[/C][C]0.996358703279428[/C][/ROW]
[ROW][C]257[/C][C]0.00661208898671411[/C][C]0.0132241779734282[/C][C]0.993387911013286[/C][/ROW]
[ROW][C]258[/C][C]0.0121892659623224[/C][C]0.0243785319246449[/C][C]0.987810734037678[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185718&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185718&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
60.6420861894224930.7158276211550130.357913810577507
70.6548694841128690.6902610317742620.345130515887131
80.5166202487363490.9667595025273030.483379751263651
90.4026186591932010.8052373183864030.597381340806798
100.319033124430520.638066248861040.68096687556948
110.2405285106948310.4810570213896620.759471489305169
120.2648960371682110.5297920743364220.735103962831789
130.2035576096445610.4071152192891220.796442390355439
140.1791973872678610.3583947745357230.820802612732139
150.202823987856630.405647975713260.79717601214337
160.1557731381012560.3115462762025110.844226861898744
170.1178008991005390.2356017982010780.882199100899461
180.3256321815466910.6512643630933820.674367818453309
190.3083509832218570.6167019664437150.691649016778143
200.248576007651470.4971520153029390.75142399234853
210.1956891191857920.3913782383715850.804310880814208
220.1532038749343290.3064077498686580.846796125065671
230.1790523305474690.3581046610949380.820947669452531
240.1431163840379560.2862327680759110.856883615962044
250.1234016953632710.2468033907265420.876598304636729
260.1031378443065710.2062756886131410.896862155693429
270.07701228656774690.1540245731354940.922987713432253
280.06414591452973620.1282918290594720.935854085470264
290.04708357653569330.09416715307138660.952916423464307
300.04706038661982170.09412077323964340.952939613380178
310.034857046926130.06971409385226010.96514295307387
320.06618899411190190.1323779882238040.933811005888098
330.05523356137090080.1104671227418020.944766438629099
340.04105758705449220.08211517410898430.958942412945508
350.03253679957667840.06507359915335690.967463200423322
360.1435006649027830.2870013298055650.856499335097217
370.26874178241990.5374835648397990.7312582175801
380.2370578262413670.4741156524827340.762942173758633
390.2091218801628460.4182437603256920.790878119837154
400.1825878076174860.3651756152349730.817412192382514
410.1583196619383360.3166393238766710.841680338061664
420.1385533845546590.2771067691093180.861446615445341
430.2826499857923640.5652999715847270.717350014207636
440.2498036896780290.4996073793560580.750196310321971
450.2132639394609640.4265278789219270.786736060539036
460.3008971704423970.6017943408847940.699102829557603
470.300167501304790.6003350026095790.69983249869521
480.2616178303081070.5232356606162130.738382169691893
490.2257382558026960.4514765116053930.774261744197304
500.1952108327355670.3904216654711340.804789167264433
510.1652469363206460.3304938726412930.834753063679354
520.1395889596907660.2791779193815320.860411040309234
530.1434458676454680.2868917352909350.856554132354532
540.1217155504929520.2434311009859040.878284449507048
550.2540069517658610.5080139035317210.745993048234139
560.2315623420197480.4631246840394950.768437657980252
570.2027437171515250.4054874343030510.797256282848475
580.1781771079318440.3563542158636880.821822892068156
590.151496194716890.302992389433780.84850380528311
600.1386781006923990.2773562013847980.861321899307601
610.117039428750720.234078857501440.88296057124928
620.1041311247322620.2082622494645240.895868875267738
630.09443210109599820.1888642021919960.905567898904002
640.08224219750839910.1644843950167980.917757802491601
650.07383293399674610.1476658679934920.926167066003254
660.08836144230314270.1767228846062850.911638557696857
670.1070940427608370.2141880855216740.892905957239163
680.1325199708235670.2650399416471340.867480029176433
690.1178079143839930.2356158287679870.882192085616006
700.1008768484709090.2017536969418180.899123151529091
710.242571845224350.4851436904487010.75742815477565
720.2228648259026940.4457296518053870.777135174097306
730.2188944003973090.4377888007946180.781105599602691
740.2133376211889330.4266752423778670.786662378811067
750.1885761331806090.3771522663612190.811423866819391
760.2329714850209980.4659429700419950.767028514979002
770.2298750556537080.4597501113074160.770124944346292
780.2020632316533490.4041264633066980.797936768346651
790.1851807269346810.3703614538693620.814819273065319
800.1716900656521180.3433801313042360.828309934347882
810.1769984484356450.353996896871290.823001551564355
820.1557121341222980.3114242682445960.844287865877702
830.1358830490659620.2717660981319250.864116950934038
840.1167626457383680.2335252914767360.883237354261632
850.1029217396397740.2058434792795490.897078260360226
860.08825612105614550.1765122421122910.911743878943854
870.07454634331139170.1490926866227830.925453656688608
880.06566848095247690.1313369619049540.934331519047523
890.05574331495430440.1114866299086090.944256685045696
900.05256546959111760.1051309391822350.947434530408882
910.04689065000448450.0937813000089690.953109349995516
920.0433322046378030.0866644092756060.956667795362197
930.03770015815339380.07540031630678760.962299841846606
940.03238687187583960.06477374375167920.96761312812416
950.03141026724955480.06282053449910960.968589732750445
960.02597578782073040.05195157564146080.97402421217927
970.0229059757975890.0458119515951780.977094024202411
980.02108797259403550.0421759451880710.978912027405965
990.01858287619042660.03716575238085310.981417123809573
1000.01533426903431310.03066853806862610.984665730965687
1010.01237952385296150.02475904770592310.987620476147039
1020.03794350931371110.07588701862742230.962056490686289
1030.03188807199602650.06377614399205310.968111928003973
1040.0350854336540630.0701708673081260.964914566345937
1050.03970680019146570.07941360038293140.960293199808534
1060.05055598128330590.1011119625666120.949444018716694
1070.04341582275129470.08683164550258930.956584177248705
1080.03624628165071050.07249256330142110.963753718349289
1090.03924609340170010.07849218680340030.9607539065983
1100.0332549014806470.0665098029612940.966745098519353
1110.02907602462265370.05815204924530740.970923975377346
1120.03428743086616130.06857486173232260.965712569133839
1130.03773864983851270.07547729967702540.962261350161487
1140.04220445668404150.08440891336808310.957795543315959
1150.04752600654661240.09505201309322480.952473993453388
1160.04105565450783210.08211130901566430.958944345492168
1170.03743596439842940.07487192879685870.962564035601571
1180.0398087468035690.07961749360713810.960191253196431
1190.03530459052214240.07060918104428490.964695409477858
1200.03433807544696050.0686761508939210.96566192455304
1210.03048412499967380.06096824999934750.969515875000326
1220.02670810253201620.05341620506403250.973291897467984
1230.02215289219777840.04430578439555680.977847107802222
1240.01812289928377580.03624579856755160.981877100716224
1250.01687986431084180.03375972862168360.983120135689158
1260.01415706681892180.02831413363784350.985842933181078
1270.01467563075573730.02935126151147460.985324369244263
1280.01204644819145360.02409289638290730.987953551808546
1290.0177046349800070.03540926996001390.982295365019993
1300.01593706105386580.03187412210773150.984062938946134
1310.03052377037506180.06104754075012350.969476229624938
1320.03298797982266280.06597595964532550.967012020177337
1330.04030696149739670.08061392299479340.959693038502603
1340.03427186050815620.06854372101631240.965728139491844
1350.02829376400026480.05658752800052950.971706235999735
1360.02514519991021850.05029039982043710.974854800089781
1370.03010621993584850.06021243987169710.969893780064152
1380.04330606403697360.08661212807394710.956693935963026
1390.04437846495239390.08875692990478780.955621535047606
1400.06126599632756880.1225319926551380.938734003672431
1410.05660440091969270.1132088018393850.943395599080307
1420.04804328815683530.09608657631367050.951956711843165
1430.04542530825078710.09085061650157420.954574691749213
1440.04117390856076690.08234781712153380.958826091439233
1450.05037424367763220.1007484873552640.949625756322368
1460.07197620051265340.1439524010253070.928023799487347
1470.06338407348831380.1267681469766280.936615926511686
1480.06015298389888490.120305967797770.939847016101115
1490.05273218342800560.1054643668560110.947267816571994
1500.06807505791541440.1361501158308290.931924942084586
1510.05775839841133160.1155167968226630.942241601588668
1520.05200336574424270.1040067314884850.947996634255757
1530.04444179347390060.08888358694780130.955558206526099
1540.03804108582202920.07608217164405830.961958914177971
1550.05388669663777080.1077733932755420.946113303362229
1560.06604964104703320.1320992820940660.933950358952967
1570.06234930160302040.1246986032060410.93765069839698
1580.0525957800779510.1051915601559020.947404219922049
1590.05356950662591290.1071390132518260.946430493374087
1600.05772710200317460.1154542040063490.942272897996825
1610.05238321583225230.1047664316645050.947616784167748
1620.04687562442820240.09375124885640470.953124375571798
1630.04184394683326440.08368789366652880.958156053166736
1640.04591193958479810.09182387916959620.954088060415202
1650.038529862455070.077059724910140.96147013754493
1660.04682579274443670.09365158548887350.953174207255563
1670.03934047606808670.07868095213617350.960659523931913
1680.03614747792801870.07229495585603740.963852522071981
1690.03127884012534550.06255768025069090.968721159874655
1700.03064246566497750.0612849313299550.969357534335022
1710.0269536806990380.0539073613980760.973046319300962
1720.02297158910558820.04594317821117630.977028410894412
1730.0206800945951080.04136018919021610.979319905404892
1740.02799764198160030.05599528396320050.9720023580184
1750.02505460368891060.05010920737782130.974945396311089
1760.02110371774130610.04220743548261220.978896282258694
1770.01811661246056420.03623322492112850.981883387539436
1780.01545695546243650.0309139109248730.984543044537563
1790.0124549265046410.02490985300928210.987545073495359
1800.01214420776911030.02428841553822070.98785579223089
1810.01081720396140270.02163440792280550.989182796038597
1820.01080733175874440.02161466351748880.989192668241256
1830.02108734789956540.04217469579913090.978912652100435
1840.01849032735575590.03698065471151190.981509672644244
1850.04659198101929950.09318396203859890.953408018980701
1860.04410873124665710.08821746249331420.955891268753343
1870.05203195368693020.104063907373860.94796804631307
1880.04758090385972460.09516180771944920.952419096140275
1890.04478232168811750.0895646433762350.955217678311883
1900.04938278196270340.09876556392540670.950617218037297
1910.04084851413675990.08169702827351970.95915148586324
1920.03583220170300010.07166440340600010.964167798297
1930.03373373089969530.06746746179939070.966266269100305
1940.03322235265911460.06644470531822920.966777647340885
1950.02754666343421140.05509332686842280.972453336565789
1960.02320221631043650.04640443262087310.976797783689563
1970.02447389449113230.04894778898226470.975526105508868
1980.02283862915575750.0456772583115150.977161370844242
1990.01953944539234280.03907889078468560.980460554607657
2000.02121647737152050.04243295474304090.97878352262848
2010.02978988481764190.05957976963528370.970210115182358
2020.02432137105395190.04864274210790380.975678628946048
2030.0276120491606090.0552240983212180.972387950839391
2040.02375059701708860.04750119403417720.976249402982911
2050.01990445303465680.03980890606931370.980095546965343
2060.01634595629126690.03269191258253380.983654043708733
2070.0155923141322060.03118462826441210.984407685867794
2080.01448045203985310.02896090407970620.985519547960147
2090.01462318318714410.02924636637428820.985376816812856
2100.01226445229137590.02452890458275190.987735547708624
2110.009712916821074160.01942583364214830.990287083178926
2120.01233378304150260.02466756608300520.987666216958497
2130.01040464194669770.02080928389339550.989595358053302
2140.01059520763128380.02119041526256770.989404792368716
2150.01257134225249630.02514268450499250.987428657747504
2160.01047311125411710.02094622250823410.989526888745883
2170.01260630381592510.02521260763185010.987393696184075
2180.009930993156755150.01986198631351030.990069006843245
2190.007687833821455910.01537566764291180.992312166178544
2200.006287374373525950.01257474874705190.993712625626474
2210.004719642238337590.009439284476675170.995280357761662
2220.003555805028961810.007111610057923610.996444194971038
2230.003878598796099530.007757197592199070.9961214012039
2240.003047216680717490.006094433361434990.996952783319282
2250.002281507643270490.004563015286540990.997718492356729
2260.01199396438672020.02398792877344040.98800603561328
2270.008784024197116830.01756804839423370.991215975802883
2280.006930950022204640.01386190004440930.993069049977795
2290.0053224899039940.0106449798079880.994677510096006
2300.003964674519451650.00792934903890330.996035325480548
2310.002758689740148430.005517379480296850.997241310259852
2320.003084577790040550.006169155580081110.996915422209959
2330.00316096931148640.00632193862297280.996839030688514
2340.01116247241727060.02232494483454120.988837527582729
2350.008046603313676720.01609320662735340.991953396686323
2360.00614275776750830.01228551553501660.993857242232492
2370.1453088334594470.2906176669188930.854691166540553
2380.1176073663376180.2352147326752350.882392633662382
2390.1738992404400120.3477984808800240.826100759559988
2400.1647383552848880.3294767105697770.835261644715112
2410.1309958238372220.2619916476744440.869004176162778
2420.1012086860103520.2024173720207040.898791313989648
2430.09479726564769040.1895945312953810.90520273435231
2440.07099435686507940.1419887137301590.929005643134921
2450.06696278641675760.1339255728335150.933037213583242
2460.04862220434695750.09724440869391490.951377795653043
2470.03740378313504330.07480756627008660.962596216864957
2480.03766520311211820.07533040622423640.962334796887882
2490.02530413371425810.05060826742851610.974695866285742
2500.01780700689265070.03561401378530130.982192993107349
2510.01527631200522520.03055262401045030.984723687994775
2520.01455328612054310.02910657224108620.985446713879457
2530.009171575838865730.01834315167773150.990828424161134
2540.01167674852508970.02335349705017940.98832325147491
2550.006160440393980070.01232088078796010.99383955960602
2560.00364129672057250.0072825934411450.996358703279428
2570.006612088986714110.01322417797342820.993387911013286
2580.01218926596232240.02437853192464490.987810734037678







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.0395256916996047NOK
5% type I error level720.284584980237154NOK
10% type I error level1450.573122529644269NOK

\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 & 10 & 0.0395256916996047 & NOK \tabularnewline
5% type I error level & 72 & 0.284584980237154 & NOK \tabularnewline
10% type I error level & 145 & 0.573122529644269 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185718&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]10[/C][C]0.0395256916996047[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]72[/C][C]0.284584980237154[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]145[/C][C]0.573122529644269[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185718&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185718&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.0395256916996047NOK
5% type I error level720.284584980237154NOK
10% type I error level1450.573122529644269NOK



Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, mysum$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')
}