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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 29 Dec 2010 17:06:25 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/29/t1293642269l23luvup4fvrwu8.htm/, Retrieved Fri, 03 May 2024 07:03:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116970, Retrieved Fri, 03 May 2024 07:03:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [multiple regression] [2010-12-29 17:06:25] [be9f1751361e0e66b042227828c71db5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
347553	0,032500	125,01	0,012257
353245	0,025000	120,96	0,014315
347966	0,025000	117,07	0,012208
364343	0,025000	112,45	0,009063
341713	0,025000	110,23	0,009054
361162	0,025000	107,34	0,009063
354400	0,025000	107,73	0,019270
345183	0,025000	103,71	0,018200
341807	0,017500	105,28	0,015106
348712	0,017500	106,92	0,013078
349011	0,017500	107,8	0,010081
416259	0,017500	109,7	0,011089
360289	0,017500	111,51	0,013118
367557	0,017500	106,21	0,012097
364611	0,017500	105,14	0,013065
378688	0,017500	103,53	0,007984
351763	0,017500	103,99	0,007976
377765	0,017500	102,72	0,004990
373212	0,017500	98,5	-0,001990
365819	0,017500	99,85	0,000000
364686	0,017500	98,81	0,001984
363333	0,017500	98,42	0,007944
362536	0,017500	97,96	0,009980
428803	0,017500	100,13	0,005982
375361	0,017500	99,75	0,004980
377205	0,017500	98,24	0,001992
381266	0,017500	90,79	-0,002976
390516	0,010000	83,67	-0,001980
366117	0,010000	85,1	-0,000989
393928	0,010000	84,53	0,001986
387784	0,010000	87,22	0,000997
385656	0,010000	94,55	-0,001986
385320	0,005000	100,49	0,000990
389053	0,005000	100,65	-0,006897
390595	0,005000	101,92	-0,006917
462440	0,005000	101,85	-0,003964
402532	0,005000	105,84	-0,004955
409070	0,005000	105,73	-0,003976
421329	0,005000	105,85	-0,000995
428841	0,005000	107,46	0,001984
404864	0,005000	106,51	0,001980
432633	0,005000	108,86	0,000000
416886	0,005000	109,32	0,003984
414893	0,005000	107,75	0,001990
417914	0,005000	109,75	0,000000
417518	0,005000	112,36	0,004960
423137	0,005000	112,26	0,004975
506710	0,005000	113,81	0,005970
436264	0,005000	118,02	0,005976
443712	0,005000	123,01	0,005988
452849	0,005000	122,64	0,004980
453009	0,005000	125,51	0,019802
437876	0,005000	118,99	0,019763
460041	0,005000	114,2	0,022795
450426	0,005000	115,16	0,019841
447873	0,005000	117,9	0,021847
444955	0,005000	120,74	0,024728
452043	0,005000	121,06	0,025666
480877	0,005000	125,27	0,021782
546696	0,005000	129,47	0,018793
483668	0,005000	129,45	0,018812
489627	0,005000	126	0,019841
490007	0,005000	128,69	0,022795
496590	0,005000	131,67	0,003883
480846	0,005000	135	0,004845
497677	0,005000	140,57	0,000969
492795	0,005000	140,73	-0,000973
488495	0,005000	144,67	-0,002915
486769	0,005000	134,59	-0,001931
494455	0,005000	121,3	0,001925
498054	0,005000	120,58	0,007752
558648	0,005000	117,54	0,005825
506424	0,005000	113,18	0,001944
512528	0,005000	116,66	-0,000973
512866	0,005000	119,78	-0,003876
529324	0,005000	119,81	-0,000967
508431	0,005000	122,11	-0,003857
523026	0,005000	120,9	-0,002904
521355	0,005000	119,86	-0,000974
514103	0,005000	113,4	0,002924
513885	0,005000	107,57	-0,001934
522150	0,005000	105,97	-0,006724
527384	0,005000	104,96	-0,011538
654047	0,005000	102,68	-0,010618
543115	0,005000	105,16	-0,006790
543200	0,005000	109,34	-0,006816
571201	0,005000	106,71	-0,005837
568892	0,005000	105,48	-0,007744
537223	0,005000	108,11	-0,006776
553186	0,005000	106,23	-0,005825
550954	0,005000	107,9	-0,005848
543433	0,005000	108,07	-0,004859
557195	0,005000	106,75	-0,009690
565522	0,005000	108,36	-0,011605
571691	0,005000	108,89	-0,008755
633972	0,005000	112,21	-0,004878
575265	0,005000	117,1	-0,003906
572364	0,003500	116,04	-0,002941
586744	0,002500	121,12	-0,006849
600389	0,002500	123,83	-0,007805
578540	0,002500	121,93	-0,007797
610778	0,002500	122,15	-0,008789
596577	0,002500	124,68	-0,007843
590558	0,002500	121,61	-0,007813
597294	0,001000	118,98	-0,007828
602384	0,001000	121,28	-0,007828
614190	0,001000	122,31	-0,009814
690042	0,001000	127,36	-0,011765
639497	0,001000	132,66	-0,013725
649304	0,001000	133,52	-0,015733
678762	0,001000	131,2	-0,011823
691885	0,001000	131,07	-0,010816
667973	0,001000	126,48	-0,008841
682032	0,001000	123,6	-0,006897
672651	0,001000	118,07	-0,007905
671865	0,001000	119,01	-0,008858
671463	0,001000	120,5	-0,006903
675917	0,001000	123,86	-0,008876
680952	0,001000	121,49	-0,003964
754718	0,001000	122,27	-0,002976
694413	0,001000	118,65	-0,003976
699390	0,001000	119,27	-0,001998
710573	0,001000	118,57	-0,000997
714217	0,001000	119,79	-0,000994
702996	0,001000	117,26	-0,001982
712370	0,001000	118,26	-0,003968
708445	0,001000	118,69	-0,001992
707083	0,001000	118,83	-0,002979
700632	0,001000	115,19	-0,001986
706309	0,001000	109,58	0,000000
709523	0,001000	109,2	-0,004975
769096	0,001000	107,9	-0,003980
715100	0,001000	106,48	-0,002994
713872	0,001000	106,55	0,000000
714032	0,001000	108,62	-0,000998
732269	0,001000	107,25	-0,003980
711137	0,001000	112,35	-0,004965
715284	0,001000	109,47	0,000000
716888	0,001000	109,36	-0,000998
716426	0,001000	110,35	-0,001992
714726	0,001000	110,01	0,000000
718016	0,001000	108,92	0,004975
725932	0,001000	104,9	0,008000
779564	0,001000	103,84	0,001998
732144	0,001000	103,21	0,002002
730816	0,001000	104,88	-0,001001
746719	0,001000	105,31	0,000000
760065	0,001000	107,36	0,000999
734516	0,001000	106,91	0,000998
740167	0,001000	108,63	-0,004980
740976	0,001000	111,93	-0,002997
735764	0,001000	110,72	-0,002994
734711	0,001000	111,06	-0,002985
737916	0,001000	114,82	-0,007921
739132	0,001000	118,41	-0,009921
792705	0,001000	118,64	-0,003988
747488	0,001000	115,45	-0,000999
746616	0,001000	117,89	-0,001002
749781	0,001000	117,31	-0,001998
760911	0,001000	117,11	-0,000998
739543	0,001000	111,51	0,000997
745626	0,001000	114,53	0,005005
746246	0,004000	115,67	0,003006
744769	0,004000	115,88	0,009009
741388	0,004000	117,01	0,005988
744469	0,004000	118,66	0,003992
745566	0,004000	117,35	0,003006
798367	0,004000	117,3	0,003003
752440	0,004000	120,58	0,000000
756627	0,007500	120,45	-0,002006
758941	0,007500	117,28	-0,001001
771287	0,007500	118,83	0,000000
749858	0,007500	120,73	0,000000
758370	0,007500	122,62	-0,001992
755407	0,007500	121,59	0,000000
752063	0,007500	116,72	-0,001984
756298	0,007500	115,01	-0,001984
755892	0,007500	115,74	0,002982
758486	0,007500	111,21	0,005994
812777	0,007500	112,34	0,006986
762561	0,007500	107,66	0,007000
763579	0,007500	107,16	0,010050
764615	0,007500	100,79	0,012024
773312	0,007500	102,49	0,007992
755697	0,007500	104,14	0,012948
762909	0,007500	106,9	0,019960
760337	0,007500	106,81	0,022977
759270	0,007500	109,28	0,020875
754929	0,007500	106,75	0,020875
766116	0,005000	100,33	0,016848
765945	0,005000	96,81	0,009930
814783	0,003000	91,28	0,003964
768494	0,003000	90,41	0,000000
769222	0,003000	92,5	-0,000995
768977	0,003000	97,87	-0,002970
783341	0,003000	99	-0,000991
764061	0,003000	96,3	-0,010816
767394	0,003000	96,52	-0,017613
763910	0,003000	94,5	-0,022461
761677	0,003000	94,84	-0,022395
759173	0,003000	91,49	-0,022395
762486	0,003000	90,29	-0,025341
762690	0,003000	89,19	-0,018682
809542	0,003000	89,55	-0,016782
769041	0,003000	91,16	-0,012910
770889	0,003000	90,28	-0,010956
773527	0,003000	90,52	-0,010924
789890	0,003000	93,38	-0,011905
768325	0,003000	91,74	-0,008946
772712	0,003000	90,92	-0,006972
772944	0,003000	87,72	-0,008991
769637	0,003000	85,47	-0,008964
768546	0,003000	84,38	-0,005976
775013	0,003000	81,87	0,002000
776635	0,003000	82,48	0,001002

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gwilym Jenkins' @ www.wessa.org
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ www.wessa.org \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116970&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ www.wessa.org[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116970&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116970&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gwilym Jenkins' @ www.wessa.org
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
Banknotes[t] = + 952695.721801893 -17024358.4005245Loan_Interest[t] -2261.87936460689Exchange_Rate_USD[t] -583456.00996409Inflation[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Banknotes[t] =  +  952695.721801893 -17024358.4005245Loan_Interest[t] -2261.87936460689Exchange_Rate_USD[t] -583456.00996409Inflation[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116970&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Banknotes[t] =  +  952695.721801893 -17024358.4005245Loan_Interest[t] -2261.87936460689Exchange_Rate_USD[t] -583456.00996409Inflation[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116970&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116970&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Banknotes[t] = + 952695.721801893 -17024358.4005245Loan_Interest[t] -2261.87936460689Exchange_Rate_USD[t] -583456.00996409Inflation[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)952695.72180189378403.80854412.151100
Loan_Interest-17024358.40052451499128.74551-11.356200
Exchange_Rate_USD-2261.87936460689681.415855-3.31940.0010630.000531
Inflation-583456.00996409944730.073981-0.61760.5375110.268756

\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) & 952695.721801893 & 78403.808544 & 12.1511 & 0 & 0 \tabularnewline
Loan_Interest & -17024358.4005245 & 1499128.74551 & -11.3562 & 0 & 0 \tabularnewline
Exchange_Rate_USD & -2261.87936460689 & 681.415855 & -3.3194 & 0.001063 & 0.000531 \tabularnewline
Inflation & -583456.00996409 & 944730.073981 & -0.6176 & 0.537511 & 0.268756 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116970&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]952695.721801893[/C][C]78403.808544[/C][C]12.1511[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Loan_Interest[/C][C]-17024358.4005245[/C][C]1499128.74551[/C][C]-11.3562[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Exchange_Rate_USD[/C][C]-2261.87936460689[/C][C]681.415855[/C][C]-3.3194[/C][C]0.001063[/C][C]0.000531[/C][/ROW]
[ROW][C]Inflation[/C][C]-583456.00996409[/C][C]944730.073981[/C][C]-0.6176[/C][C]0.537511[/C][C]0.268756[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116970&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116970&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)952695.72180189378403.80854412.151100
Loan_Interest-17024358.40052451499128.74551-11.356200
Exchange_Rate_USD-2261.87936460689681.415855-3.31940.0010630.000531
Inflation-583456.00996409944730.073981-0.61760.5375110.268756






Multiple Linear Regression - Regression Statistics
Multiple R0.680344765580795
R-squared0.462869000053186
Adjusted R-squared0.455232066404654
F-TEST (value)60.6092734800841
F-TEST (DF numerator)3
F-TEST (DF denominator)211
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation113207.900804473
Sum Squared Residuals2704182077761.17

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.680344765580795 \tabularnewline
R-squared & 0.462869000053186 \tabularnewline
Adjusted R-squared & 0.455232066404654 \tabularnewline
F-TEST (value) & 60.6092734800841 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 211 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 113207.900804473 \tabularnewline
Sum Squared Residuals & 2704182077761.17 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116970&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.680344765580795[/C][/ROW]
[ROW][C]R-squared[/C][C]0.462869000053186[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.455232066404654[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]60.6092734800841[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]211[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]113207.900804473[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2704182077761.17[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116970&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116970&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.680344765580795
R-squared0.462869000053186
Adjusted R-squared0.455232066404654
F-TEST (value)60.6092734800841
F-TEST (DF numerator)3
F-TEST (DF denominator)211
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation113207.900804473
Sum Squared Residuals2704182077761.17






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1347553109495.114101206238057.885898794
2353245245137.66106329108107.33893671
3347966255165.71360460892800.2863953919
4364343267450.56542042996892.4345795712
5341713272477.18871394669235.8112860541
6361162279008.7689735782153.2310264298
7354400272171.3005276782228.69947233
8345183281888.35350405163294.6464959486
9341807407825.103800382-66018.1038003816
10348712405298.870430633-56586.8704306334
11349011405057.034251642-56046.0342516418
12416259400171.33980084516087.6601991552
13360289394893.505906689-34604.5059066892
14367557407477.175125279-39920.1751252791
15364611409332.600627763-44721.6006277632
16378688415938.766391408-37250.7663914079
17351763414902.969531768-63139.9695317684
18377765419517.755970572-41752.7559705719
19373212433135.409838762-59923.4098387624
20365819428920.795236715-63101.7952367145
21364686430115.573052137-65429.5730521369
22363333427520.308184948-64187.3081849476
23362536427372.85625638-64836.85625638
24428803424797.2351630194005.76483698057
25375361426241.372243554-50880.372243554
26377205431400.176641883-54195.1766418832
27381266451149.787365706-69883.7873657061
28390516594355.934259717-203839.934259717
29366117590543.241862455-224426.241862455
30393928590096.731470638-196168.731470638
31387784584589.3139737-196805.3139737
32385656569750.187508854-184094.187508854
33385320639700.051000059-254380.051000059
34389053643939.867852308-254886.867852308
35390595641078.950179457-250483.950179457
36462440639514.336137555-177074.336137555
37402532631067.642378648-228535.642378648
38409070630745.245675-221675.245675
39421329628734.537785544-207405.537785544
40428841623354.796554844-194513.796554844
41404864625505.915775261-220641.915775261
42432633621345.742168163-188712.742168163
43416886617980.788916747-201094.788916747
44414893622695.350803049-207802.350803049
45417914619332.669533663-201418.669533663
46417518610535.222582617-193017.222582617
47423137610752.658678929-187615.658678929
48506710606666.206933874-99956.2069338737
49436264597140.194072819-160876.194072819
50443712585846.414571311-142134.414571311
51452849587271.433594259-134422.433594259
52453009572131.85483815-119122.85483815
53437876586902.063079775-149026.063079775
54460041595967.426614031-135926.426614031
55450426595519.551477443-145093.551477443
56447873588151.589262432-140278.589262432
57444955580046.915102242-135091.915102242
58452043578775.831968221-126732.831968221
59480877571519.462985927-90642.4629859266
60546696563763.51966836-17067.5196683603
61483668563797.671591463-80129.6715914631
62489627571000.779165104-81373.7791651038
63490007563192.794620877-73185.7946208774
64496590567486.71417479-70896.7141747897
65480846559393.371209063-78547.3712090632
66497677549056.178642824-51379.1786428236
67492795549827.349515837-57032.3495158368
68488495542048.616390636-53553.6163906359
69486769564274.239672069-77505.2396720687
70494455592084.810053273-97629.8100532728
71498054590313.565025729-92259.565025729
72558648598313.998025335-39665.9980253348
73506424610440.184829691-104016.184829691
74512528604270.785821925-91742.7858219247
75512866598907.495001277-86041.495001277
76529324597142.365087353-67818.3650873532
77508431593626.230417554-85195.2304175536
78523026595807.070871232-72781.0708712321
79521355597033.355311193-75678.3553111926
80514103609370.784479713-95267.7844797131
81513885625391.970471777-111506.970471777
82522150631805.731742876-109655.731742876
83527384636898.987133096-109514.987133096
84654047641519.29255523312527.7074447673
85543115633676.362124865-90561.3621248651
86543200624236.876237067-81036.8762370673
87571201629614.415532229-58413.4155322286
88568892633509.177761697-64617.1777616966
89537223626995.649615135-89772.6496151353
90553186630693.11615512-77507.1161551204
91550954626929.197104456-75975.197104456
92543433625967.639618618-82534.6396186184
93557195631771.996364036-74576.996364036
94565522629247.6888461-63725.6888461001
95571691626386.043154461-54695.0431544608
96633972616614.54471333517357.4552866648
97575265604986.835378722-29721.8353787224
98572364632357.930056377-59993.9300563771
99586744640172.087371638-53428.0873716384
100600389634600.17823908-34211.1782390794
101578540638893.081383753-60353.0813837527
102610778638974.256285424-28196.2562854236
103596577632699.752107542-36122.7521075421
104590558639626.218076586-49068.2180765864
105597294671120.250246439-73826.2502464388
106602384665917.927707843-63533.9277078429
107614190664746.935598086-50556.9355980865
108690042654462.76748226235579.2325177384
109639497643618.380629375-4121.38062937472
110649304642844.744043826459.25595617935
111678762645810.99117074932951.0088292509
112691885645517.49528611446367.5047138858
113667973654747.1959499813225.8040500193
114682032660127.17003667821904.8299633216
115672651673223.486580998-572.486580998309
116671865671653.353555764211.646444236427
117671463667142.496803024320.50319698048
118675917660693.740845615223.2591544005
119680952663188.45901877417763.5409812257
120754718660847.73857653693870.2614234636
121694413669619.19788637724793.8021136226
122699390667062.75669261232327.2433073878
123710573668062.03278186342510.9672181371
124714217665300.78958901348916.2104109874
125702996671599.79891931331396.2010806874
126712370670496.66319049441873.3368095057
127708445668371.14598802440073.8540119756
128707083668630.35395881438452.646041186
129700632676284.22302808924347.7769719113
130706309687814.62262774518494.3773722553
131709523691576.83043586717946.1695641333
132769096693936.73487994175159.2651200587
133715100696573.31595185918526.6840481415
134713872694668.11710250419203.8828974964
135714032690568.31591571123463.6840842885
136732269695406.95646693636862.0435330642
137711137684446.07587725526690.9241227447
138715284688063.42935785227220.5706421485
139716888688894.52518590227993.4748140976
140716426687235.21988884629190.7801111541
141714726686842.01450096427883.9854990363
142718016686404.76935881431611.2306411861
143725932693732.56997439232199.4300256078
144779564699632.0650726879931.93492732
145732144701054.71524834231089.2847516575
146730816699029.49510737131786.5048926288
147746719697472.84751461649246.1524853839
148760065692253.12226321867811.8777367821
149734516693271.55143330141244.4485666991
150740167692869.01895374247297.9810462576
151740976684247.82378278156728.1762172191
152735764686982.94744592548781.0525540747
153734711686208.6573578748502.3426421307
154737916680583.9298121357332.0701878699
155739132673630.6949131265501.3050868804
156792705669648.818152143123056.181847857
157747488675120.26331145672367.7366885436
158746616669603.02802984577012.9719701546
159749781671496.04024724278284.9597527584
160760911671364.96011019989546.039889801
161739543682867.48981211956675.5101878808
162745626673698.1224430771927.8775569297
163746246621212.833329763125033.166670237
164744769617235.352235381127533.647764619
165741388616442.049159477124945.950840523
166744469613874.526403764130594.473596236
167745566617412.875997223128153.124002777
168798367617527.720333484180839.279666516
169752440611860.874415495140579.125584505
170756627553740.077087046202886.922912954
171758941560323.861382836198617.138617164
172771287556233.908901721215053.091098279
173749858551936.338108968197921.661891032
174758370548823.63048171209546.36951829
175755407549991.121855406205415.878144594
176752063562164.05108481189898.948915189
177756298566031.864798288190266.135201712
178755892561483.250316644194408.749683356
179758486569972.194336301188513.805663699
180812777566837.482292411245939.517707589
181762561577414.909334632185146.090665368
182763579576766.308186545186812.691813455
183764615590022.737575421174592.262424579
184773312588530.037287765184781.962712235
185755697581906.328350782173790.671649218
186762909571572.347762598191336.652237402
187760337570015.630123351190321.369876649
188759270565655.212625717193614.787374283
189754929571377.767418172183551.232581828
190766116630809.506292385135306.493707615
191765945642807.670332733123137.329667267
192814783692845.478575504121937.521424496
193768494697126.1332462171367.8667537903
194769222692979.34410409676242.6558959044
195768977681985.37753583686991.6224641644
196783341678274.794410111105066.205589889
197764061690114.32399244773946.6760075533
198767394693582.46103195973811.5389680409
199763910700980.05208477162929.947915229
200761677700172.50500414761504.494995853
201759173707749.8008755851423.19912442
202762486712182.91751846350303.0824815375
203762690710785.75124917951904.2487508207
204809542708862.908258989100679.091741011
205769041702962.14081139166078.859188609
206770889703812.52160877567076.4783912248
207773527703250.9999689570276.0000310493
208789890697354.3953319592535.6046680503
209768325699337.43115642168987.5688435787
210772712700040.4300717372671.5699282702
211772944708456.4417225964487.5582774106
212769637713529.91698068656107.0830193141
213768546714251.99893033554294.0010696653
214775013715275.67100002459737.3289999756
215776635714478.21368555862156.7863144416

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 347553 & 109495.114101206 & 238057.885898794 \tabularnewline
2 & 353245 & 245137.66106329 & 108107.33893671 \tabularnewline
3 & 347966 & 255165.713604608 & 92800.2863953919 \tabularnewline
4 & 364343 & 267450.565420429 & 96892.4345795712 \tabularnewline
5 & 341713 & 272477.188713946 & 69235.8112860541 \tabularnewline
6 & 361162 & 279008.76897357 & 82153.2310264298 \tabularnewline
7 & 354400 & 272171.30052767 & 82228.69947233 \tabularnewline
8 & 345183 & 281888.353504051 & 63294.6464959486 \tabularnewline
9 & 341807 & 407825.103800382 & -66018.1038003816 \tabularnewline
10 & 348712 & 405298.870430633 & -56586.8704306334 \tabularnewline
11 & 349011 & 405057.034251642 & -56046.0342516418 \tabularnewline
12 & 416259 & 400171.339800845 & 16087.6601991552 \tabularnewline
13 & 360289 & 394893.505906689 & -34604.5059066892 \tabularnewline
14 & 367557 & 407477.175125279 & -39920.1751252791 \tabularnewline
15 & 364611 & 409332.600627763 & -44721.6006277632 \tabularnewline
16 & 378688 & 415938.766391408 & -37250.7663914079 \tabularnewline
17 & 351763 & 414902.969531768 & -63139.9695317684 \tabularnewline
18 & 377765 & 419517.755970572 & -41752.7559705719 \tabularnewline
19 & 373212 & 433135.409838762 & -59923.4098387624 \tabularnewline
20 & 365819 & 428920.795236715 & -63101.7952367145 \tabularnewline
21 & 364686 & 430115.573052137 & -65429.5730521369 \tabularnewline
22 & 363333 & 427520.308184948 & -64187.3081849476 \tabularnewline
23 & 362536 & 427372.85625638 & -64836.85625638 \tabularnewline
24 & 428803 & 424797.235163019 & 4005.76483698057 \tabularnewline
25 & 375361 & 426241.372243554 & -50880.372243554 \tabularnewline
26 & 377205 & 431400.176641883 & -54195.1766418832 \tabularnewline
27 & 381266 & 451149.787365706 & -69883.7873657061 \tabularnewline
28 & 390516 & 594355.934259717 & -203839.934259717 \tabularnewline
29 & 366117 & 590543.241862455 & -224426.241862455 \tabularnewline
30 & 393928 & 590096.731470638 & -196168.731470638 \tabularnewline
31 & 387784 & 584589.3139737 & -196805.3139737 \tabularnewline
32 & 385656 & 569750.187508854 & -184094.187508854 \tabularnewline
33 & 385320 & 639700.051000059 & -254380.051000059 \tabularnewline
34 & 389053 & 643939.867852308 & -254886.867852308 \tabularnewline
35 & 390595 & 641078.950179457 & -250483.950179457 \tabularnewline
36 & 462440 & 639514.336137555 & -177074.336137555 \tabularnewline
37 & 402532 & 631067.642378648 & -228535.642378648 \tabularnewline
38 & 409070 & 630745.245675 & -221675.245675 \tabularnewline
39 & 421329 & 628734.537785544 & -207405.537785544 \tabularnewline
40 & 428841 & 623354.796554844 & -194513.796554844 \tabularnewline
41 & 404864 & 625505.915775261 & -220641.915775261 \tabularnewline
42 & 432633 & 621345.742168163 & -188712.742168163 \tabularnewline
43 & 416886 & 617980.788916747 & -201094.788916747 \tabularnewline
44 & 414893 & 622695.350803049 & -207802.350803049 \tabularnewline
45 & 417914 & 619332.669533663 & -201418.669533663 \tabularnewline
46 & 417518 & 610535.222582617 & -193017.222582617 \tabularnewline
47 & 423137 & 610752.658678929 & -187615.658678929 \tabularnewline
48 & 506710 & 606666.206933874 & -99956.2069338737 \tabularnewline
49 & 436264 & 597140.194072819 & -160876.194072819 \tabularnewline
50 & 443712 & 585846.414571311 & -142134.414571311 \tabularnewline
51 & 452849 & 587271.433594259 & -134422.433594259 \tabularnewline
52 & 453009 & 572131.85483815 & -119122.85483815 \tabularnewline
53 & 437876 & 586902.063079775 & -149026.063079775 \tabularnewline
54 & 460041 & 595967.426614031 & -135926.426614031 \tabularnewline
55 & 450426 & 595519.551477443 & -145093.551477443 \tabularnewline
56 & 447873 & 588151.589262432 & -140278.589262432 \tabularnewline
57 & 444955 & 580046.915102242 & -135091.915102242 \tabularnewline
58 & 452043 & 578775.831968221 & -126732.831968221 \tabularnewline
59 & 480877 & 571519.462985927 & -90642.4629859266 \tabularnewline
60 & 546696 & 563763.51966836 & -17067.5196683603 \tabularnewline
61 & 483668 & 563797.671591463 & -80129.6715914631 \tabularnewline
62 & 489627 & 571000.779165104 & -81373.7791651038 \tabularnewline
63 & 490007 & 563192.794620877 & -73185.7946208774 \tabularnewline
64 & 496590 & 567486.71417479 & -70896.7141747897 \tabularnewline
65 & 480846 & 559393.371209063 & -78547.3712090632 \tabularnewline
66 & 497677 & 549056.178642824 & -51379.1786428236 \tabularnewline
67 & 492795 & 549827.349515837 & -57032.3495158368 \tabularnewline
68 & 488495 & 542048.616390636 & -53553.6163906359 \tabularnewline
69 & 486769 & 564274.239672069 & -77505.2396720687 \tabularnewline
70 & 494455 & 592084.810053273 & -97629.8100532728 \tabularnewline
71 & 498054 & 590313.565025729 & -92259.565025729 \tabularnewline
72 & 558648 & 598313.998025335 & -39665.9980253348 \tabularnewline
73 & 506424 & 610440.184829691 & -104016.184829691 \tabularnewline
74 & 512528 & 604270.785821925 & -91742.7858219247 \tabularnewline
75 & 512866 & 598907.495001277 & -86041.495001277 \tabularnewline
76 & 529324 & 597142.365087353 & -67818.3650873532 \tabularnewline
77 & 508431 & 593626.230417554 & -85195.2304175536 \tabularnewline
78 & 523026 & 595807.070871232 & -72781.0708712321 \tabularnewline
79 & 521355 & 597033.355311193 & -75678.3553111926 \tabularnewline
80 & 514103 & 609370.784479713 & -95267.7844797131 \tabularnewline
81 & 513885 & 625391.970471777 & -111506.970471777 \tabularnewline
82 & 522150 & 631805.731742876 & -109655.731742876 \tabularnewline
83 & 527384 & 636898.987133096 & -109514.987133096 \tabularnewline
84 & 654047 & 641519.292555233 & 12527.7074447673 \tabularnewline
85 & 543115 & 633676.362124865 & -90561.3621248651 \tabularnewline
86 & 543200 & 624236.876237067 & -81036.8762370673 \tabularnewline
87 & 571201 & 629614.415532229 & -58413.4155322286 \tabularnewline
88 & 568892 & 633509.177761697 & -64617.1777616966 \tabularnewline
89 & 537223 & 626995.649615135 & -89772.6496151353 \tabularnewline
90 & 553186 & 630693.11615512 & -77507.1161551204 \tabularnewline
91 & 550954 & 626929.197104456 & -75975.197104456 \tabularnewline
92 & 543433 & 625967.639618618 & -82534.6396186184 \tabularnewline
93 & 557195 & 631771.996364036 & -74576.996364036 \tabularnewline
94 & 565522 & 629247.6888461 & -63725.6888461001 \tabularnewline
95 & 571691 & 626386.043154461 & -54695.0431544608 \tabularnewline
96 & 633972 & 616614.544713335 & 17357.4552866648 \tabularnewline
97 & 575265 & 604986.835378722 & -29721.8353787224 \tabularnewline
98 & 572364 & 632357.930056377 & -59993.9300563771 \tabularnewline
99 & 586744 & 640172.087371638 & -53428.0873716384 \tabularnewline
100 & 600389 & 634600.17823908 & -34211.1782390794 \tabularnewline
101 & 578540 & 638893.081383753 & -60353.0813837527 \tabularnewline
102 & 610778 & 638974.256285424 & -28196.2562854236 \tabularnewline
103 & 596577 & 632699.752107542 & -36122.7521075421 \tabularnewline
104 & 590558 & 639626.218076586 & -49068.2180765864 \tabularnewline
105 & 597294 & 671120.250246439 & -73826.2502464388 \tabularnewline
106 & 602384 & 665917.927707843 & -63533.9277078429 \tabularnewline
107 & 614190 & 664746.935598086 & -50556.9355980865 \tabularnewline
108 & 690042 & 654462.767482262 & 35579.2325177384 \tabularnewline
109 & 639497 & 643618.380629375 & -4121.38062937472 \tabularnewline
110 & 649304 & 642844.74404382 & 6459.25595617935 \tabularnewline
111 & 678762 & 645810.991170749 & 32951.0088292509 \tabularnewline
112 & 691885 & 645517.495286114 & 46367.5047138858 \tabularnewline
113 & 667973 & 654747.19594998 & 13225.8040500193 \tabularnewline
114 & 682032 & 660127.170036678 & 21904.8299633216 \tabularnewline
115 & 672651 & 673223.486580998 & -572.486580998309 \tabularnewline
116 & 671865 & 671653.353555764 & 211.646444236427 \tabularnewline
117 & 671463 & 667142.49680302 & 4320.50319698048 \tabularnewline
118 & 675917 & 660693.7408456 & 15223.2591544005 \tabularnewline
119 & 680952 & 663188.459018774 & 17763.5409812257 \tabularnewline
120 & 754718 & 660847.738576536 & 93870.2614234636 \tabularnewline
121 & 694413 & 669619.197886377 & 24793.8021136226 \tabularnewline
122 & 699390 & 667062.756692612 & 32327.2433073878 \tabularnewline
123 & 710573 & 668062.032781863 & 42510.9672181371 \tabularnewline
124 & 714217 & 665300.789589013 & 48916.2104109874 \tabularnewline
125 & 702996 & 671599.798919313 & 31396.2010806874 \tabularnewline
126 & 712370 & 670496.663190494 & 41873.3368095057 \tabularnewline
127 & 708445 & 668371.145988024 & 40073.8540119756 \tabularnewline
128 & 707083 & 668630.353958814 & 38452.646041186 \tabularnewline
129 & 700632 & 676284.223028089 & 24347.7769719113 \tabularnewline
130 & 706309 & 687814.622627745 & 18494.3773722553 \tabularnewline
131 & 709523 & 691576.830435867 & 17946.1695641333 \tabularnewline
132 & 769096 & 693936.734879941 & 75159.2651200587 \tabularnewline
133 & 715100 & 696573.315951859 & 18526.6840481415 \tabularnewline
134 & 713872 & 694668.117102504 & 19203.8828974964 \tabularnewline
135 & 714032 & 690568.315915711 & 23463.6840842885 \tabularnewline
136 & 732269 & 695406.956466936 & 36862.0435330642 \tabularnewline
137 & 711137 & 684446.075877255 & 26690.9241227447 \tabularnewline
138 & 715284 & 688063.429357852 & 27220.5706421485 \tabularnewline
139 & 716888 & 688894.525185902 & 27993.4748140976 \tabularnewline
140 & 716426 & 687235.219888846 & 29190.7801111541 \tabularnewline
141 & 714726 & 686842.014500964 & 27883.9854990363 \tabularnewline
142 & 718016 & 686404.769358814 & 31611.2306411861 \tabularnewline
143 & 725932 & 693732.569974392 & 32199.4300256078 \tabularnewline
144 & 779564 & 699632.06507268 & 79931.93492732 \tabularnewline
145 & 732144 & 701054.715248342 & 31089.2847516575 \tabularnewline
146 & 730816 & 699029.495107371 & 31786.5048926288 \tabularnewline
147 & 746719 & 697472.847514616 & 49246.1524853839 \tabularnewline
148 & 760065 & 692253.122263218 & 67811.8777367821 \tabularnewline
149 & 734516 & 693271.551433301 & 41244.4485666991 \tabularnewline
150 & 740167 & 692869.018953742 & 47297.9810462576 \tabularnewline
151 & 740976 & 684247.823782781 & 56728.1762172191 \tabularnewline
152 & 735764 & 686982.947445925 & 48781.0525540747 \tabularnewline
153 & 734711 & 686208.65735787 & 48502.3426421307 \tabularnewline
154 & 737916 & 680583.92981213 & 57332.0701878699 \tabularnewline
155 & 739132 & 673630.69491312 & 65501.3050868804 \tabularnewline
156 & 792705 & 669648.818152143 & 123056.181847857 \tabularnewline
157 & 747488 & 675120.263311456 & 72367.7366885436 \tabularnewline
158 & 746616 & 669603.028029845 & 77012.9719701546 \tabularnewline
159 & 749781 & 671496.040247242 & 78284.9597527584 \tabularnewline
160 & 760911 & 671364.960110199 & 89546.039889801 \tabularnewline
161 & 739543 & 682867.489812119 & 56675.5101878808 \tabularnewline
162 & 745626 & 673698.12244307 & 71927.8775569297 \tabularnewline
163 & 746246 & 621212.833329763 & 125033.166670237 \tabularnewline
164 & 744769 & 617235.352235381 & 127533.647764619 \tabularnewline
165 & 741388 & 616442.049159477 & 124945.950840523 \tabularnewline
166 & 744469 & 613874.526403764 & 130594.473596236 \tabularnewline
167 & 745566 & 617412.875997223 & 128153.124002777 \tabularnewline
168 & 798367 & 617527.720333484 & 180839.279666516 \tabularnewline
169 & 752440 & 611860.874415495 & 140579.125584505 \tabularnewline
170 & 756627 & 553740.077087046 & 202886.922912954 \tabularnewline
171 & 758941 & 560323.861382836 & 198617.138617164 \tabularnewline
172 & 771287 & 556233.908901721 & 215053.091098279 \tabularnewline
173 & 749858 & 551936.338108968 & 197921.661891032 \tabularnewline
174 & 758370 & 548823.63048171 & 209546.36951829 \tabularnewline
175 & 755407 & 549991.121855406 & 205415.878144594 \tabularnewline
176 & 752063 & 562164.05108481 & 189898.948915189 \tabularnewline
177 & 756298 & 566031.864798288 & 190266.135201712 \tabularnewline
178 & 755892 & 561483.250316644 & 194408.749683356 \tabularnewline
179 & 758486 & 569972.194336301 & 188513.805663699 \tabularnewline
180 & 812777 & 566837.482292411 & 245939.517707589 \tabularnewline
181 & 762561 & 577414.909334632 & 185146.090665368 \tabularnewline
182 & 763579 & 576766.308186545 & 186812.691813455 \tabularnewline
183 & 764615 & 590022.737575421 & 174592.262424579 \tabularnewline
184 & 773312 & 588530.037287765 & 184781.962712235 \tabularnewline
185 & 755697 & 581906.328350782 & 173790.671649218 \tabularnewline
186 & 762909 & 571572.347762598 & 191336.652237402 \tabularnewline
187 & 760337 & 570015.630123351 & 190321.369876649 \tabularnewline
188 & 759270 & 565655.212625717 & 193614.787374283 \tabularnewline
189 & 754929 & 571377.767418172 & 183551.232581828 \tabularnewline
190 & 766116 & 630809.506292385 & 135306.493707615 \tabularnewline
191 & 765945 & 642807.670332733 & 123137.329667267 \tabularnewline
192 & 814783 & 692845.478575504 & 121937.521424496 \tabularnewline
193 & 768494 & 697126.13324621 & 71367.8667537903 \tabularnewline
194 & 769222 & 692979.344104096 & 76242.6558959044 \tabularnewline
195 & 768977 & 681985.377535836 & 86991.6224641644 \tabularnewline
196 & 783341 & 678274.794410111 & 105066.205589889 \tabularnewline
197 & 764061 & 690114.323992447 & 73946.6760075533 \tabularnewline
198 & 767394 & 693582.461031959 & 73811.5389680409 \tabularnewline
199 & 763910 & 700980.052084771 & 62929.947915229 \tabularnewline
200 & 761677 & 700172.505004147 & 61504.494995853 \tabularnewline
201 & 759173 & 707749.80087558 & 51423.19912442 \tabularnewline
202 & 762486 & 712182.917518463 & 50303.0824815375 \tabularnewline
203 & 762690 & 710785.751249179 & 51904.2487508207 \tabularnewline
204 & 809542 & 708862.908258989 & 100679.091741011 \tabularnewline
205 & 769041 & 702962.140811391 & 66078.859188609 \tabularnewline
206 & 770889 & 703812.521608775 & 67076.4783912248 \tabularnewline
207 & 773527 & 703250.99996895 & 70276.0000310493 \tabularnewline
208 & 789890 & 697354.39533195 & 92535.6046680503 \tabularnewline
209 & 768325 & 699337.431156421 & 68987.5688435787 \tabularnewline
210 & 772712 & 700040.43007173 & 72671.5699282702 \tabularnewline
211 & 772944 & 708456.44172259 & 64487.5582774106 \tabularnewline
212 & 769637 & 713529.916980686 & 56107.0830193141 \tabularnewline
213 & 768546 & 714251.998930335 & 54294.0010696653 \tabularnewline
214 & 775013 & 715275.671000024 & 59737.3289999756 \tabularnewline
215 & 776635 & 714478.213685558 & 62156.7863144416 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116970&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]347553[/C][C]109495.114101206[/C][C]238057.885898794[/C][/ROW]
[ROW][C]2[/C][C]353245[/C][C]245137.66106329[/C][C]108107.33893671[/C][/ROW]
[ROW][C]3[/C][C]347966[/C][C]255165.713604608[/C][C]92800.2863953919[/C][/ROW]
[ROW][C]4[/C][C]364343[/C][C]267450.565420429[/C][C]96892.4345795712[/C][/ROW]
[ROW][C]5[/C][C]341713[/C][C]272477.188713946[/C][C]69235.8112860541[/C][/ROW]
[ROW][C]6[/C][C]361162[/C][C]279008.76897357[/C][C]82153.2310264298[/C][/ROW]
[ROW][C]7[/C][C]354400[/C][C]272171.30052767[/C][C]82228.69947233[/C][/ROW]
[ROW][C]8[/C][C]345183[/C][C]281888.353504051[/C][C]63294.6464959486[/C][/ROW]
[ROW][C]9[/C][C]341807[/C][C]407825.103800382[/C][C]-66018.1038003816[/C][/ROW]
[ROW][C]10[/C][C]348712[/C][C]405298.870430633[/C][C]-56586.8704306334[/C][/ROW]
[ROW][C]11[/C][C]349011[/C][C]405057.034251642[/C][C]-56046.0342516418[/C][/ROW]
[ROW][C]12[/C][C]416259[/C][C]400171.339800845[/C][C]16087.6601991552[/C][/ROW]
[ROW][C]13[/C][C]360289[/C][C]394893.505906689[/C][C]-34604.5059066892[/C][/ROW]
[ROW][C]14[/C][C]367557[/C][C]407477.175125279[/C][C]-39920.1751252791[/C][/ROW]
[ROW][C]15[/C][C]364611[/C][C]409332.600627763[/C][C]-44721.6006277632[/C][/ROW]
[ROW][C]16[/C][C]378688[/C][C]415938.766391408[/C][C]-37250.7663914079[/C][/ROW]
[ROW][C]17[/C][C]351763[/C][C]414902.969531768[/C][C]-63139.9695317684[/C][/ROW]
[ROW][C]18[/C][C]377765[/C][C]419517.755970572[/C][C]-41752.7559705719[/C][/ROW]
[ROW][C]19[/C][C]373212[/C][C]433135.409838762[/C][C]-59923.4098387624[/C][/ROW]
[ROW][C]20[/C][C]365819[/C][C]428920.795236715[/C][C]-63101.7952367145[/C][/ROW]
[ROW][C]21[/C][C]364686[/C][C]430115.573052137[/C][C]-65429.5730521369[/C][/ROW]
[ROW][C]22[/C][C]363333[/C][C]427520.308184948[/C][C]-64187.3081849476[/C][/ROW]
[ROW][C]23[/C][C]362536[/C][C]427372.85625638[/C][C]-64836.85625638[/C][/ROW]
[ROW][C]24[/C][C]428803[/C][C]424797.235163019[/C][C]4005.76483698057[/C][/ROW]
[ROW][C]25[/C][C]375361[/C][C]426241.372243554[/C][C]-50880.372243554[/C][/ROW]
[ROW][C]26[/C][C]377205[/C][C]431400.176641883[/C][C]-54195.1766418832[/C][/ROW]
[ROW][C]27[/C][C]381266[/C][C]451149.787365706[/C][C]-69883.7873657061[/C][/ROW]
[ROW][C]28[/C][C]390516[/C][C]594355.934259717[/C][C]-203839.934259717[/C][/ROW]
[ROW][C]29[/C][C]366117[/C][C]590543.241862455[/C][C]-224426.241862455[/C][/ROW]
[ROW][C]30[/C][C]393928[/C][C]590096.731470638[/C][C]-196168.731470638[/C][/ROW]
[ROW][C]31[/C][C]387784[/C][C]584589.3139737[/C][C]-196805.3139737[/C][/ROW]
[ROW][C]32[/C][C]385656[/C][C]569750.187508854[/C][C]-184094.187508854[/C][/ROW]
[ROW][C]33[/C][C]385320[/C][C]639700.051000059[/C][C]-254380.051000059[/C][/ROW]
[ROW][C]34[/C][C]389053[/C][C]643939.867852308[/C][C]-254886.867852308[/C][/ROW]
[ROW][C]35[/C][C]390595[/C][C]641078.950179457[/C][C]-250483.950179457[/C][/ROW]
[ROW][C]36[/C][C]462440[/C][C]639514.336137555[/C][C]-177074.336137555[/C][/ROW]
[ROW][C]37[/C][C]402532[/C][C]631067.642378648[/C][C]-228535.642378648[/C][/ROW]
[ROW][C]38[/C][C]409070[/C][C]630745.245675[/C][C]-221675.245675[/C][/ROW]
[ROW][C]39[/C][C]421329[/C][C]628734.537785544[/C][C]-207405.537785544[/C][/ROW]
[ROW][C]40[/C][C]428841[/C][C]623354.796554844[/C][C]-194513.796554844[/C][/ROW]
[ROW][C]41[/C][C]404864[/C][C]625505.915775261[/C][C]-220641.915775261[/C][/ROW]
[ROW][C]42[/C][C]432633[/C][C]621345.742168163[/C][C]-188712.742168163[/C][/ROW]
[ROW][C]43[/C][C]416886[/C][C]617980.788916747[/C][C]-201094.788916747[/C][/ROW]
[ROW][C]44[/C][C]414893[/C][C]622695.350803049[/C][C]-207802.350803049[/C][/ROW]
[ROW][C]45[/C][C]417914[/C][C]619332.669533663[/C][C]-201418.669533663[/C][/ROW]
[ROW][C]46[/C][C]417518[/C][C]610535.222582617[/C][C]-193017.222582617[/C][/ROW]
[ROW][C]47[/C][C]423137[/C][C]610752.658678929[/C][C]-187615.658678929[/C][/ROW]
[ROW][C]48[/C][C]506710[/C][C]606666.206933874[/C][C]-99956.2069338737[/C][/ROW]
[ROW][C]49[/C][C]436264[/C][C]597140.194072819[/C][C]-160876.194072819[/C][/ROW]
[ROW][C]50[/C][C]443712[/C][C]585846.414571311[/C][C]-142134.414571311[/C][/ROW]
[ROW][C]51[/C][C]452849[/C][C]587271.433594259[/C][C]-134422.433594259[/C][/ROW]
[ROW][C]52[/C][C]453009[/C][C]572131.85483815[/C][C]-119122.85483815[/C][/ROW]
[ROW][C]53[/C][C]437876[/C][C]586902.063079775[/C][C]-149026.063079775[/C][/ROW]
[ROW][C]54[/C][C]460041[/C][C]595967.426614031[/C][C]-135926.426614031[/C][/ROW]
[ROW][C]55[/C][C]450426[/C][C]595519.551477443[/C][C]-145093.551477443[/C][/ROW]
[ROW][C]56[/C][C]447873[/C][C]588151.589262432[/C][C]-140278.589262432[/C][/ROW]
[ROW][C]57[/C][C]444955[/C][C]580046.915102242[/C][C]-135091.915102242[/C][/ROW]
[ROW][C]58[/C][C]452043[/C][C]578775.831968221[/C][C]-126732.831968221[/C][/ROW]
[ROW][C]59[/C][C]480877[/C][C]571519.462985927[/C][C]-90642.4629859266[/C][/ROW]
[ROW][C]60[/C][C]546696[/C][C]563763.51966836[/C][C]-17067.5196683603[/C][/ROW]
[ROW][C]61[/C][C]483668[/C][C]563797.671591463[/C][C]-80129.6715914631[/C][/ROW]
[ROW][C]62[/C][C]489627[/C][C]571000.779165104[/C][C]-81373.7791651038[/C][/ROW]
[ROW][C]63[/C][C]490007[/C][C]563192.794620877[/C][C]-73185.7946208774[/C][/ROW]
[ROW][C]64[/C][C]496590[/C][C]567486.71417479[/C][C]-70896.7141747897[/C][/ROW]
[ROW][C]65[/C][C]480846[/C][C]559393.371209063[/C][C]-78547.3712090632[/C][/ROW]
[ROW][C]66[/C][C]497677[/C][C]549056.178642824[/C][C]-51379.1786428236[/C][/ROW]
[ROW][C]67[/C][C]492795[/C][C]549827.349515837[/C][C]-57032.3495158368[/C][/ROW]
[ROW][C]68[/C][C]488495[/C][C]542048.616390636[/C][C]-53553.6163906359[/C][/ROW]
[ROW][C]69[/C][C]486769[/C][C]564274.239672069[/C][C]-77505.2396720687[/C][/ROW]
[ROW][C]70[/C][C]494455[/C][C]592084.810053273[/C][C]-97629.8100532728[/C][/ROW]
[ROW][C]71[/C][C]498054[/C][C]590313.565025729[/C][C]-92259.565025729[/C][/ROW]
[ROW][C]72[/C][C]558648[/C][C]598313.998025335[/C][C]-39665.9980253348[/C][/ROW]
[ROW][C]73[/C][C]506424[/C][C]610440.184829691[/C][C]-104016.184829691[/C][/ROW]
[ROW][C]74[/C][C]512528[/C][C]604270.785821925[/C][C]-91742.7858219247[/C][/ROW]
[ROW][C]75[/C][C]512866[/C][C]598907.495001277[/C][C]-86041.495001277[/C][/ROW]
[ROW][C]76[/C][C]529324[/C][C]597142.365087353[/C][C]-67818.3650873532[/C][/ROW]
[ROW][C]77[/C][C]508431[/C][C]593626.230417554[/C][C]-85195.2304175536[/C][/ROW]
[ROW][C]78[/C][C]523026[/C][C]595807.070871232[/C][C]-72781.0708712321[/C][/ROW]
[ROW][C]79[/C][C]521355[/C][C]597033.355311193[/C][C]-75678.3553111926[/C][/ROW]
[ROW][C]80[/C][C]514103[/C][C]609370.784479713[/C][C]-95267.7844797131[/C][/ROW]
[ROW][C]81[/C][C]513885[/C][C]625391.970471777[/C][C]-111506.970471777[/C][/ROW]
[ROW][C]82[/C][C]522150[/C][C]631805.731742876[/C][C]-109655.731742876[/C][/ROW]
[ROW][C]83[/C][C]527384[/C][C]636898.987133096[/C][C]-109514.987133096[/C][/ROW]
[ROW][C]84[/C][C]654047[/C][C]641519.292555233[/C][C]12527.7074447673[/C][/ROW]
[ROW][C]85[/C][C]543115[/C][C]633676.362124865[/C][C]-90561.3621248651[/C][/ROW]
[ROW][C]86[/C][C]543200[/C][C]624236.876237067[/C][C]-81036.8762370673[/C][/ROW]
[ROW][C]87[/C][C]571201[/C][C]629614.415532229[/C][C]-58413.4155322286[/C][/ROW]
[ROW][C]88[/C][C]568892[/C][C]633509.177761697[/C][C]-64617.1777616966[/C][/ROW]
[ROW][C]89[/C][C]537223[/C][C]626995.649615135[/C][C]-89772.6496151353[/C][/ROW]
[ROW][C]90[/C][C]553186[/C][C]630693.11615512[/C][C]-77507.1161551204[/C][/ROW]
[ROW][C]91[/C][C]550954[/C][C]626929.197104456[/C][C]-75975.197104456[/C][/ROW]
[ROW][C]92[/C][C]543433[/C][C]625967.639618618[/C][C]-82534.6396186184[/C][/ROW]
[ROW][C]93[/C][C]557195[/C][C]631771.996364036[/C][C]-74576.996364036[/C][/ROW]
[ROW][C]94[/C][C]565522[/C][C]629247.6888461[/C][C]-63725.6888461001[/C][/ROW]
[ROW][C]95[/C][C]571691[/C][C]626386.043154461[/C][C]-54695.0431544608[/C][/ROW]
[ROW][C]96[/C][C]633972[/C][C]616614.544713335[/C][C]17357.4552866648[/C][/ROW]
[ROW][C]97[/C][C]575265[/C][C]604986.835378722[/C][C]-29721.8353787224[/C][/ROW]
[ROW][C]98[/C][C]572364[/C][C]632357.930056377[/C][C]-59993.9300563771[/C][/ROW]
[ROW][C]99[/C][C]586744[/C][C]640172.087371638[/C][C]-53428.0873716384[/C][/ROW]
[ROW][C]100[/C][C]600389[/C][C]634600.17823908[/C][C]-34211.1782390794[/C][/ROW]
[ROW][C]101[/C][C]578540[/C][C]638893.081383753[/C][C]-60353.0813837527[/C][/ROW]
[ROW][C]102[/C][C]610778[/C][C]638974.256285424[/C][C]-28196.2562854236[/C][/ROW]
[ROW][C]103[/C][C]596577[/C][C]632699.752107542[/C][C]-36122.7521075421[/C][/ROW]
[ROW][C]104[/C][C]590558[/C][C]639626.218076586[/C][C]-49068.2180765864[/C][/ROW]
[ROW][C]105[/C][C]597294[/C][C]671120.250246439[/C][C]-73826.2502464388[/C][/ROW]
[ROW][C]106[/C][C]602384[/C][C]665917.927707843[/C][C]-63533.9277078429[/C][/ROW]
[ROW][C]107[/C][C]614190[/C][C]664746.935598086[/C][C]-50556.9355980865[/C][/ROW]
[ROW][C]108[/C][C]690042[/C][C]654462.767482262[/C][C]35579.2325177384[/C][/ROW]
[ROW][C]109[/C][C]639497[/C][C]643618.380629375[/C][C]-4121.38062937472[/C][/ROW]
[ROW][C]110[/C][C]649304[/C][C]642844.74404382[/C][C]6459.25595617935[/C][/ROW]
[ROW][C]111[/C][C]678762[/C][C]645810.991170749[/C][C]32951.0088292509[/C][/ROW]
[ROW][C]112[/C][C]691885[/C][C]645517.495286114[/C][C]46367.5047138858[/C][/ROW]
[ROW][C]113[/C][C]667973[/C][C]654747.19594998[/C][C]13225.8040500193[/C][/ROW]
[ROW][C]114[/C][C]682032[/C][C]660127.170036678[/C][C]21904.8299633216[/C][/ROW]
[ROW][C]115[/C][C]672651[/C][C]673223.486580998[/C][C]-572.486580998309[/C][/ROW]
[ROW][C]116[/C][C]671865[/C][C]671653.353555764[/C][C]211.646444236427[/C][/ROW]
[ROW][C]117[/C][C]671463[/C][C]667142.49680302[/C][C]4320.50319698048[/C][/ROW]
[ROW][C]118[/C][C]675917[/C][C]660693.7408456[/C][C]15223.2591544005[/C][/ROW]
[ROW][C]119[/C][C]680952[/C][C]663188.459018774[/C][C]17763.5409812257[/C][/ROW]
[ROW][C]120[/C][C]754718[/C][C]660847.738576536[/C][C]93870.2614234636[/C][/ROW]
[ROW][C]121[/C][C]694413[/C][C]669619.197886377[/C][C]24793.8021136226[/C][/ROW]
[ROW][C]122[/C][C]699390[/C][C]667062.756692612[/C][C]32327.2433073878[/C][/ROW]
[ROW][C]123[/C][C]710573[/C][C]668062.032781863[/C][C]42510.9672181371[/C][/ROW]
[ROW][C]124[/C][C]714217[/C][C]665300.789589013[/C][C]48916.2104109874[/C][/ROW]
[ROW][C]125[/C][C]702996[/C][C]671599.798919313[/C][C]31396.2010806874[/C][/ROW]
[ROW][C]126[/C][C]712370[/C][C]670496.663190494[/C][C]41873.3368095057[/C][/ROW]
[ROW][C]127[/C][C]708445[/C][C]668371.145988024[/C][C]40073.8540119756[/C][/ROW]
[ROW][C]128[/C][C]707083[/C][C]668630.353958814[/C][C]38452.646041186[/C][/ROW]
[ROW][C]129[/C][C]700632[/C][C]676284.223028089[/C][C]24347.7769719113[/C][/ROW]
[ROW][C]130[/C][C]706309[/C][C]687814.622627745[/C][C]18494.3773722553[/C][/ROW]
[ROW][C]131[/C][C]709523[/C][C]691576.830435867[/C][C]17946.1695641333[/C][/ROW]
[ROW][C]132[/C][C]769096[/C][C]693936.734879941[/C][C]75159.2651200587[/C][/ROW]
[ROW][C]133[/C][C]715100[/C][C]696573.315951859[/C][C]18526.6840481415[/C][/ROW]
[ROW][C]134[/C][C]713872[/C][C]694668.117102504[/C][C]19203.8828974964[/C][/ROW]
[ROW][C]135[/C][C]714032[/C][C]690568.315915711[/C][C]23463.6840842885[/C][/ROW]
[ROW][C]136[/C][C]732269[/C][C]695406.956466936[/C][C]36862.0435330642[/C][/ROW]
[ROW][C]137[/C][C]711137[/C][C]684446.075877255[/C][C]26690.9241227447[/C][/ROW]
[ROW][C]138[/C][C]715284[/C][C]688063.429357852[/C][C]27220.5706421485[/C][/ROW]
[ROW][C]139[/C][C]716888[/C][C]688894.525185902[/C][C]27993.4748140976[/C][/ROW]
[ROW][C]140[/C][C]716426[/C][C]687235.219888846[/C][C]29190.7801111541[/C][/ROW]
[ROW][C]141[/C][C]714726[/C][C]686842.014500964[/C][C]27883.9854990363[/C][/ROW]
[ROW][C]142[/C][C]718016[/C][C]686404.769358814[/C][C]31611.2306411861[/C][/ROW]
[ROW][C]143[/C][C]725932[/C][C]693732.569974392[/C][C]32199.4300256078[/C][/ROW]
[ROW][C]144[/C][C]779564[/C][C]699632.06507268[/C][C]79931.93492732[/C][/ROW]
[ROW][C]145[/C][C]732144[/C][C]701054.715248342[/C][C]31089.2847516575[/C][/ROW]
[ROW][C]146[/C][C]730816[/C][C]699029.495107371[/C][C]31786.5048926288[/C][/ROW]
[ROW][C]147[/C][C]746719[/C][C]697472.847514616[/C][C]49246.1524853839[/C][/ROW]
[ROW][C]148[/C][C]760065[/C][C]692253.122263218[/C][C]67811.8777367821[/C][/ROW]
[ROW][C]149[/C][C]734516[/C][C]693271.551433301[/C][C]41244.4485666991[/C][/ROW]
[ROW][C]150[/C][C]740167[/C][C]692869.018953742[/C][C]47297.9810462576[/C][/ROW]
[ROW][C]151[/C][C]740976[/C][C]684247.823782781[/C][C]56728.1762172191[/C][/ROW]
[ROW][C]152[/C][C]735764[/C][C]686982.947445925[/C][C]48781.0525540747[/C][/ROW]
[ROW][C]153[/C][C]734711[/C][C]686208.65735787[/C][C]48502.3426421307[/C][/ROW]
[ROW][C]154[/C][C]737916[/C][C]680583.92981213[/C][C]57332.0701878699[/C][/ROW]
[ROW][C]155[/C][C]739132[/C][C]673630.69491312[/C][C]65501.3050868804[/C][/ROW]
[ROW][C]156[/C][C]792705[/C][C]669648.818152143[/C][C]123056.181847857[/C][/ROW]
[ROW][C]157[/C][C]747488[/C][C]675120.263311456[/C][C]72367.7366885436[/C][/ROW]
[ROW][C]158[/C][C]746616[/C][C]669603.028029845[/C][C]77012.9719701546[/C][/ROW]
[ROW][C]159[/C][C]749781[/C][C]671496.040247242[/C][C]78284.9597527584[/C][/ROW]
[ROW][C]160[/C][C]760911[/C][C]671364.960110199[/C][C]89546.039889801[/C][/ROW]
[ROW][C]161[/C][C]739543[/C][C]682867.489812119[/C][C]56675.5101878808[/C][/ROW]
[ROW][C]162[/C][C]745626[/C][C]673698.12244307[/C][C]71927.8775569297[/C][/ROW]
[ROW][C]163[/C][C]746246[/C][C]621212.833329763[/C][C]125033.166670237[/C][/ROW]
[ROW][C]164[/C][C]744769[/C][C]617235.352235381[/C][C]127533.647764619[/C][/ROW]
[ROW][C]165[/C][C]741388[/C][C]616442.049159477[/C][C]124945.950840523[/C][/ROW]
[ROW][C]166[/C][C]744469[/C][C]613874.526403764[/C][C]130594.473596236[/C][/ROW]
[ROW][C]167[/C][C]745566[/C][C]617412.875997223[/C][C]128153.124002777[/C][/ROW]
[ROW][C]168[/C][C]798367[/C][C]617527.720333484[/C][C]180839.279666516[/C][/ROW]
[ROW][C]169[/C][C]752440[/C][C]611860.874415495[/C][C]140579.125584505[/C][/ROW]
[ROW][C]170[/C][C]756627[/C][C]553740.077087046[/C][C]202886.922912954[/C][/ROW]
[ROW][C]171[/C][C]758941[/C][C]560323.861382836[/C][C]198617.138617164[/C][/ROW]
[ROW][C]172[/C][C]771287[/C][C]556233.908901721[/C][C]215053.091098279[/C][/ROW]
[ROW][C]173[/C][C]749858[/C][C]551936.338108968[/C][C]197921.661891032[/C][/ROW]
[ROW][C]174[/C][C]758370[/C][C]548823.63048171[/C][C]209546.36951829[/C][/ROW]
[ROW][C]175[/C][C]755407[/C][C]549991.121855406[/C][C]205415.878144594[/C][/ROW]
[ROW][C]176[/C][C]752063[/C][C]562164.05108481[/C][C]189898.948915189[/C][/ROW]
[ROW][C]177[/C][C]756298[/C][C]566031.864798288[/C][C]190266.135201712[/C][/ROW]
[ROW][C]178[/C][C]755892[/C][C]561483.250316644[/C][C]194408.749683356[/C][/ROW]
[ROW][C]179[/C][C]758486[/C][C]569972.194336301[/C][C]188513.805663699[/C][/ROW]
[ROW][C]180[/C][C]812777[/C][C]566837.482292411[/C][C]245939.517707589[/C][/ROW]
[ROW][C]181[/C][C]762561[/C][C]577414.909334632[/C][C]185146.090665368[/C][/ROW]
[ROW][C]182[/C][C]763579[/C][C]576766.308186545[/C][C]186812.691813455[/C][/ROW]
[ROW][C]183[/C][C]764615[/C][C]590022.737575421[/C][C]174592.262424579[/C][/ROW]
[ROW][C]184[/C][C]773312[/C][C]588530.037287765[/C][C]184781.962712235[/C][/ROW]
[ROW][C]185[/C][C]755697[/C][C]581906.328350782[/C][C]173790.671649218[/C][/ROW]
[ROW][C]186[/C][C]762909[/C][C]571572.347762598[/C][C]191336.652237402[/C][/ROW]
[ROW][C]187[/C][C]760337[/C][C]570015.630123351[/C][C]190321.369876649[/C][/ROW]
[ROW][C]188[/C][C]759270[/C][C]565655.212625717[/C][C]193614.787374283[/C][/ROW]
[ROW][C]189[/C][C]754929[/C][C]571377.767418172[/C][C]183551.232581828[/C][/ROW]
[ROW][C]190[/C][C]766116[/C][C]630809.506292385[/C][C]135306.493707615[/C][/ROW]
[ROW][C]191[/C][C]765945[/C][C]642807.670332733[/C][C]123137.329667267[/C][/ROW]
[ROW][C]192[/C][C]814783[/C][C]692845.478575504[/C][C]121937.521424496[/C][/ROW]
[ROW][C]193[/C][C]768494[/C][C]697126.13324621[/C][C]71367.8667537903[/C][/ROW]
[ROW][C]194[/C][C]769222[/C][C]692979.344104096[/C][C]76242.6558959044[/C][/ROW]
[ROW][C]195[/C][C]768977[/C][C]681985.377535836[/C][C]86991.6224641644[/C][/ROW]
[ROW][C]196[/C][C]783341[/C][C]678274.794410111[/C][C]105066.205589889[/C][/ROW]
[ROW][C]197[/C][C]764061[/C][C]690114.323992447[/C][C]73946.6760075533[/C][/ROW]
[ROW][C]198[/C][C]767394[/C][C]693582.461031959[/C][C]73811.5389680409[/C][/ROW]
[ROW][C]199[/C][C]763910[/C][C]700980.052084771[/C][C]62929.947915229[/C][/ROW]
[ROW][C]200[/C][C]761677[/C][C]700172.505004147[/C][C]61504.494995853[/C][/ROW]
[ROW][C]201[/C][C]759173[/C][C]707749.80087558[/C][C]51423.19912442[/C][/ROW]
[ROW][C]202[/C][C]762486[/C][C]712182.917518463[/C][C]50303.0824815375[/C][/ROW]
[ROW][C]203[/C][C]762690[/C][C]710785.751249179[/C][C]51904.2487508207[/C][/ROW]
[ROW][C]204[/C][C]809542[/C][C]708862.908258989[/C][C]100679.091741011[/C][/ROW]
[ROW][C]205[/C][C]769041[/C][C]702962.140811391[/C][C]66078.859188609[/C][/ROW]
[ROW][C]206[/C][C]770889[/C][C]703812.521608775[/C][C]67076.4783912248[/C][/ROW]
[ROW][C]207[/C][C]773527[/C][C]703250.99996895[/C][C]70276.0000310493[/C][/ROW]
[ROW][C]208[/C][C]789890[/C][C]697354.39533195[/C][C]92535.6046680503[/C][/ROW]
[ROW][C]209[/C][C]768325[/C][C]699337.431156421[/C][C]68987.5688435787[/C][/ROW]
[ROW][C]210[/C][C]772712[/C][C]700040.43007173[/C][C]72671.5699282702[/C][/ROW]
[ROW][C]211[/C][C]772944[/C][C]708456.44172259[/C][C]64487.5582774106[/C][/ROW]
[ROW][C]212[/C][C]769637[/C][C]713529.916980686[/C][C]56107.0830193141[/C][/ROW]
[ROW][C]213[/C][C]768546[/C][C]714251.998930335[/C][C]54294.0010696653[/C][/ROW]
[ROW][C]214[/C][C]775013[/C][C]715275.671000024[/C][C]59737.3289999756[/C][/ROW]
[ROW][C]215[/C][C]776635[/C][C]714478.213685558[/C][C]62156.7863144416[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116970&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116970&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1347553109495.114101206238057.885898794
2353245245137.66106329108107.33893671
3347966255165.71360460892800.2863953919
4364343267450.56542042996892.4345795712
5341713272477.18871394669235.8112860541
6361162279008.7689735782153.2310264298
7354400272171.3005276782228.69947233
8345183281888.35350405163294.6464959486
9341807407825.103800382-66018.1038003816
10348712405298.870430633-56586.8704306334
11349011405057.034251642-56046.0342516418
12416259400171.33980084516087.6601991552
13360289394893.505906689-34604.5059066892
14367557407477.175125279-39920.1751252791
15364611409332.600627763-44721.6006277632
16378688415938.766391408-37250.7663914079
17351763414902.969531768-63139.9695317684
18377765419517.755970572-41752.7559705719
19373212433135.409838762-59923.4098387624
20365819428920.795236715-63101.7952367145
21364686430115.573052137-65429.5730521369
22363333427520.308184948-64187.3081849476
23362536427372.85625638-64836.85625638
24428803424797.2351630194005.76483698057
25375361426241.372243554-50880.372243554
26377205431400.176641883-54195.1766418832
27381266451149.787365706-69883.7873657061
28390516594355.934259717-203839.934259717
29366117590543.241862455-224426.241862455
30393928590096.731470638-196168.731470638
31387784584589.3139737-196805.3139737
32385656569750.187508854-184094.187508854
33385320639700.051000059-254380.051000059
34389053643939.867852308-254886.867852308
35390595641078.950179457-250483.950179457
36462440639514.336137555-177074.336137555
37402532631067.642378648-228535.642378648
38409070630745.245675-221675.245675
39421329628734.537785544-207405.537785544
40428841623354.796554844-194513.796554844
41404864625505.915775261-220641.915775261
42432633621345.742168163-188712.742168163
43416886617980.788916747-201094.788916747
44414893622695.350803049-207802.350803049
45417914619332.669533663-201418.669533663
46417518610535.222582617-193017.222582617
47423137610752.658678929-187615.658678929
48506710606666.206933874-99956.2069338737
49436264597140.194072819-160876.194072819
50443712585846.414571311-142134.414571311
51452849587271.433594259-134422.433594259
52453009572131.85483815-119122.85483815
53437876586902.063079775-149026.063079775
54460041595967.426614031-135926.426614031
55450426595519.551477443-145093.551477443
56447873588151.589262432-140278.589262432
57444955580046.915102242-135091.915102242
58452043578775.831968221-126732.831968221
59480877571519.462985927-90642.4629859266
60546696563763.51966836-17067.5196683603
61483668563797.671591463-80129.6715914631
62489627571000.779165104-81373.7791651038
63490007563192.794620877-73185.7946208774
64496590567486.71417479-70896.7141747897
65480846559393.371209063-78547.3712090632
66497677549056.178642824-51379.1786428236
67492795549827.349515837-57032.3495158368
68488495542048.616390636-53553.6163906359
69486769564274.239672069-77505.2396720687
70494455592084.810053273-97629.8100532728
71498054590313.565025729-92259.565025729
72558648598313.998025335-39665.9980253348
73506424610440.184829691-104016.184829691
74512528604270.785821925-91742.7858219247
75512866598907.495001277-86041.495001277
76529324597142.365087353-67818.3650873532
77508431593626.230417554-85195.2304175536
78523026595807.070871232-72781.0708712321
79521355597033.355311193-75678.3553111926
80514103609370.784479713-95267.7844797131
81513885625391.970471777-111506.970471777
82522150631805.731742876-109655.731742876
83527384636898.987133096-109514.987133096
84654047641519.29255523312527.7074447673
85543115633676.362124865-90561.3621248651
86543200624236.876237067-81036.8762370673
87571201629614.415532229-58413.4155322286
88568892633509.177761697-64617.1777616966
89537223626995.649615135-89772.6496151353
90553186630693.11615512-77507.1161551204
91550954626929.197104456-75975.197104456
92543433625967.639618618-82534.6396186184
93557195631771.996364036-74576.996364036
94565522629247.6888461-63725.6888461001
95571691626386.043154461-54695.0431544608
96633972616614.54471333517357.4552866648
97575265604986.835378722-29721.8353787224
98572364632357.930056377-59993.9300563771
99586744640172.087371638-53428.0873716384
100600389634600.17823908-34211.1782390794
101578540638893.081383753-60353.0813837527
102610778638974.256285424-28196.2562854236
103596577632699.752107542-36122.7521075421
104590558639626.218076586-49068.2180765864
105597294671120.250246439-73826.2502464388
106602384665917.927707843-63533.9277078429
107614190664746.935598086-50556.9355980865
108690042654462.76748226235579.2325177384
109639497643618.380629375-4121.38062937472
110649304642844.744043826459.25595617935
111678762645810.99117074932951.0088292509
112691885645517.49528611446367.5047138858
113667973654747.1959499813225.8040500193
114682032660127.17003667821904.8299633216
115672651673223.486580998-572.486580998309
116671865671653.353555764211.646444236427
117671463667142.496803024320.50319698048
118675917660693.740845615223.2591544005
119680952663188.45901877417763.5409812257
120754718660847.73857653693870.2614234636
121694413669619.19788637724793.8021136226
122699390667062.75669261232327.2433073878
123710573668062.03278186342510.9672181371
124714217665300.78958901348916.2104109874
125702996671599.79891931331396.2010806874
126712370670496.66319049441873.3368095057
127708445668371.14598802440073.8540119756
128707083668630.35395881438452.646041186
129700632676284.22302808924347.7769719113
130706309687814.62262774518494.3773722553
131709523691576.83043586717946.1695641333
132769096693936.73487994175159.2651200587
133715100696573.31595185918526.6840481415
134713872694668.11710250419203.8828974964
135714032690568.31591571123463.6840842885
136732269695406.95646693636862.0435330642
137711137684446.07587725526690.9241227447
138715284688063.42935785227220.5706421485
139716888688894.52518590227993.4748140976
140716426687235.21988884629190.7801111541
141714726686842.01450096427883.9854990363
142718016686404.76935881431611.2306411861
143725932693732.56997439232199.4300256078
144779564699632.0650726879931.93492732
145732144701054.71524834231089.2847516575
146730816699029.49510737131786.5048926288
147746719697472.84751461649246.1524853839
148760065692253.12226321867811.8777367821
149734516693271.55143330141244.4485666991
150740167692869.01895374247297.9810462576
151740976684247.82378278156728.1762172191
152735764686982.94744592548781.0525540747
153734711686208.6573578748502.3426421307
154737916680583.9298121357332.0701878699
155739132673630.6949131265501.3050868804
156792705669648.818152143123056.181847857
157747488675120.26331145672367.7366885436
158746616669603.02802984577012.9719701546
159749781671496.04024724278284.9597527584
160760911671364.96011019989546.039889801
161739543682867.48981211956675.5101878808
162745626673698.1224430771927.8775569297
163746246621212.833329763125033.166670237
164744769617235.352235381127533.647764619
165741388616442.049159477124945.950840523
166744469613874.526403764130594.473596236
167745566617412.875997223128153.124002777
168798367617527.720333484180839.279666516
169752440611860.874415495140579.125584505
170756627553740.077087046202886.922912954
171758941560323.861382836198617.138617164
172771287556233.908901721215053.091098279
173749858551936.338108968197921.661891032
174758370548823.63048171209546.36951829
175755407549991.121855406205415.878144594
176752063562164.05108481189898.948915189
177756298566031.864798288190266.135201712
178755892561483.250316644194408.749683356
179758486569972.194336301188513.805663699
180812777566837.482292411245939.517707589
181762561577414.909334632185146.090665368
182763579576766.308186545186812.691813455
183764615590022.737575421174592.262424579
184773312588530.037287765184781.962712235
185755697581906.328350782173790.671649218
186762909571572.347762598191336.652237402
187760337570015.630123351190321.369876649
188759270565655.212625717193614.787374283
189754929571377.767418172183551.232581828
190766116630809.506292385135306.493707615
191765945642807.670332733123137.329667267
192814783692845.478575504121937.521424496
193768494697126.1332462171367.8667537903
194769222692979.34410409676242.6558959044
195768977681985.37753583686991.6224641644
196783341678274.794410111105066.205589889
197764061690114.32399244773946.6760075533
198767394693582.46103195973811.5389680409
199763910700980.05208477162929.947915229
200761677700172.50500414761504.494995853
201759173707749.8008755851423.19912442
202762486712182.91751846350303.0824815375
203762690710785.75124917951904.2487508207
204809542708862.908258989100679.091741011
205769041702962.14081139166078.859188609
206770889703812.52160877567076.4783912248
207773527703250.9999689570276.0000310493
208789890697354.3953319592535.6046680503
209768325699337.43115642168987.5688435787
210772712700040.4300717372671.5699282702
211772944708456.4417225964487.5582774106
212769637713529.91698068656107.0830193141
213768546714251.99893033554294.0010696653
214775013715275.67100002459737.3289999756
215776635714478.21368555862156.7863144416






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.001156714662267690.002313429324535380.998843285337732
80.0001183762598021330.0002367525196042660.999881623740198
91.40840800499684e-052.81681600999367e-050.99998591591995
101.05860664760653e-062.11721329521307e-060.999998941393352
117.42132766925973e-081.48426553385195e-070.999999925786723
122.08019070750409e-054.16038141500819e-050.999979198092925
133.79408043532642e-067.58816087065283e-060.999996205919565
146.58454840120356e-071.31690968024071e-060.99999934154516
151.07491513666429e-072.14983027332858e-070.999999892508486
161.9284979427035e-083.85699588540699e-080.99999998071502
174.46747239400329e-098.93494478800659e-090.999999995532528
187.32217447130169e-101.46443489426034e-090.999999999267783
191.09457521427899e-102.18915042855799e-100.999999999890542
201.69734279672647e-113.39468559345294e-110.999999999983027
212.41909194886914e-124.83818389773827e-120.99999999999758
223.23314235345985e-136.4662847069197e-130.999999999999677
234.215718946365e-148.43143789273001e-140.999999999999958
241.98756080400704e-123.97512160801407e-120.999999999998012
253.36322289219786e-136.72644578439573e-130.999999999999664
265.5164662215849e-141.10329324431698e-130.999999999999945
278.79375690290096e-151.75875138058019e-140.999999999999991
281.58792070398823e-153.17584140797645e-150.999999999999998
295.79571016567398e-161.1591420331348e-151
301.34911449331401e-162.69822898662801e-161
312.70051377423489e-175.40102754846979e-171
325.38967187657891e-181.07793437531578e-171
331.44630465949546e-182.89260931899092e-181
344.08721467269162e-198.17442934538324e-191
351.11187902662134e-192.22375805324268e-191
368.89024846356204e-181.77804969271241e-171
372.83333553605794e-185.66667107211587e-181
389.03862785215871e-191.80772557043174e-181
394.01372774398711e-198.02745548797422e-191
402.44169177149616e-194.88338354299232e-191
418.98990880923735e-201.79798176184747e-191
425.27879359181157e-201.05575871836231e-191
432.02542464633922e-204.05084929267844e-201
448.33989916694203e-211.66797983338841e-201
453.41869036153435e-216.8373807230687e-211
461.37602463763035e-212.75204927526069e-211
476.30335467380133e-221.26067093476027e-211
481.11538885585596e-182.23077771171193e-181
494.75489606468618e-199.50979212937237e-191
501.80610319720834e-193.61220639441668e-191
518.11355597181473e-201.62271119436295e-191
523.24524261161195e-206.4904852232239e-201
531.43890097328965e-202.87780194657929e-201
541.43234919001758e-202.86469838003516e-201
559.2446629706912e-211.84893259413824e-201
565.46771399257409e-211.09354279851482e-201
573.43241416904894e-216.86482833809787e-211
582.46694301515511e-214.93388603031021e-211
592.91928850172571e-215.83857700345142e-211
606.7490120704802e-191.34980241409604e-181
614.4923074132624e-198.9846148265248e-191
624.92716461882829e-199.85432923765658e-191
634.88890794787677e-199.77781589575353e-191
644.13447426791113e-198.26894853582225e-191
651.91529843929122e-193.83059687858243e-191
667.50784500270693e-201.50156900054139e-191
672.67285422645732e-205.34570845291463e-201
688.85741533170073e-211.77148306634015e-201
694.04409949728505e-218.0881989945701e-211
701.004868521998e-202.009737043996e-201
713.83231115686618e-207.66462231373236e-201
724.22156290800205e-178.4431258160041e-171
734.03691479794101e-168.07382959588202e-161
742.32595407021374e-154.65190814042749e-150.999999999999998
756.8137228661236e-151.36274457322472e-140.999999999999993
763.95716586206869e-147.91433172413738e-140.99999999999996
776.69866979815012e-141.33973395963002e-130.999999999999933
781.95900454496285e-133.9180090899257e-130.999999999999804
796.65747560660795e-131.33149512132159e-120.999999999999334
805.86768063494188e-121.17353612698838e-110.999999999994132
817.72486816261642e-111.54497363252328e-100.999999999922751
829.3724004207021e-101.87448008414042e-090.99999999906276
838.09016631986917e-091.61803326397383e-080.999999991909834
841.62515592938862e-053.25031185877724e-050.999983748440706
857.58417939629174e-050.0001516835879258350.999924158206037
860.000241687850280830.0004833757005616610.99975831214972
870.001131179335469610.002262358670939210.99886882066453
880.004068181761875580.008136363523751160.995931818238124
890.01143541042973140.02287082085946290.988564589570269
900.03463690627448420.06927381254896840.965363093725516
910.08886363394338790.1777272678867760.911136366056612
920.2171717849815530.4343435699631060.782828215018447
930.4060691007612030.8121382015224050.593930899238797
940.612586219136920.774827561726160.38741378086308
950.820933021167670.3581339576646590.179066978832329
960.9360229776511940.1279540446976110.0639770223488056
970.9827228469892780.03455430602144310.0172771530107215
980.9971906155145650.005618768970869330.00280938448543467
990.999183769662670.001632460674658950.000816230337329474
1000.9996901775381730.0006196449236530410.00030982246182652
1010.9999597611847568.04776304875783e-054.02388152437892e-05
1020.9999904520525861.90958948283424e-059.54794741417122e-06
1030.9999987556039782.4887920435007e-061.24439602175035e-06
1040.9999999640657277.18685452734227e-083.59342726367114e-08
1050.9999999993072571.38548561503816e-096.92742807519082e-10
1060.999999999991121.77585510956225e-118.87927554781123e-12
1070.9999999999998632.73077171124669e-131.36538585562335e-13
1080.9999999999999161.69011801196534e-138.4505900598267e-14
1090.9999999999999637.43536821461076e-143.71768410730538e-14
1100.9999999999999755.08123937863228e-142.54061968931614e-14
1110.9999999999999745.10492196588177e-142.55246098294088e-14
1120.9999999999999764.8385992617301e-142.41929963086505e-14
1130.999999999999991.99992360699611e-149.99961803498055e-15
1140.9999999999999976.68321817654467e-153.34160908827234e-15
11517.45499100908792e-163.72749550454396e-16
11618.80685948614233e-174.40342974307116e-17
11719.1836893364025e-184.59184466820125e-18
11812.06336807151548e-181.03168403575774e-18
11912.54533674522349e-191.27266837261174e-19
12015.31665543859097e-212.65832771929548e-21
12111.0468610125209e-215.2343050626045e-22
12212.42734964875655e-221.21367482437828e-22
12316.64311476340493e-233.32155738170247e-23
12412.5671189379896e-231.2835594689948e-23
12517.4516867903e-243.72584339515e-24
12614.07913511083245e-242.03956755541623e-24
12712.00355353241414e-241.00177676620707e-24
12811.08291385645351e-245.41456928226756e-25
12912.5711976925677e-251.28559884628385e-25
13013.61121486339497e-261.80560743169749e-26
13118.25882973140404e-274.12941486570202e-27
13219.0227881030398e-284.5113940515199e-28
13312.57086605265084e-281.28543302632542e-28
13416.27846784161761e-293.13923392080881e-29
13512.13489888879702e-291.06744944439851e-29
13611.92240252223203e-299.61201261116016e-30
13718.88152265267611e-304.44076132633806e-30
13813.55395546054912e-301.77697773027456e-30
13911.57322512987554e-307.86612564937772e-31
14017.0361968570965e-313.51809842854825e-31
14112.196836180772e-311.098418090386e-31
14216.73356054126683e-323.36678027063341e-32
14312.43190930595008e-321.21595465297504e-32
14417.42790954609629e-333.71395477304815e-33
14515.79628528001305e-332.89814264000652e-33
14614.69383791322202e-332.34691895661101e-33
14711.0047472469728e-325.02373623486402e-33
14812.16755699971721e-321.0837784998586e-32
14912.90969184330239e-321.4548459216512e-32
15016.76252094954243e-323.38126047477121e-32
15111.81947113058368e-319.09735565291838e-32
15213.30495756121582e-311.65247878060791e-31
15315.19397054102973e-312.59698527051487e-31
15411.27352159220445e-306.36760796102224e-31
15513.77661323723665e-301.88830661861833e-30
15612.30059737283607e-311.15029868641803e-31
15719.2777994710535e-314.63889973552675e-31
15813.88492690362132e-301.94246345181066e-30
15911.68885525935239e-298.44427629676196e-30
16015.320782324996e-292.660391162498e-29
16111.38772801963412e-286.93864009817061e-29
16214.6435076564871e-282.32175382824355e-28
16311.1544497942422e-275.77224897121099e-28
16412.18993432592597e-271.09496716296298e-27
16512.93538997807206e-271.46769498903603e-27
16614.09825651909349e-272.04912825954674e-27
16713.55000444925382e-271.77500222462691e-27
16811.37977060585974e-276.89885302929872e-28
16913.76269094099137e-271.88134547049568e-27
17011.4571453593777e-267.28572679688852e-27
17115.73245234319575e-262.86622617159788e-26
17211.47100939082504e-257.35504695412518e-26
17315.41101603287011e-252.70550801643505e-25
17412.52626829726673e-241.26313414863337e-24
17511.13073808351959e-235.65369041759793e-24
17614.61754388008215e-232.30877194004108e-23
17712.0981887551325e-221.04909437756625e-22
17818.30757897245316e-224.15378948622658e-22
17913.37388196991793e-211.68694098495897e-21
18019.89400356304722e-244.94700178152361e-24
18115.4280859658195e-232.71404298290975e-23
18212.93489101950486e-221.46744550975243e-22
18311.596933187193e-217.98466593596502e-22
18412.89981087397788e-211.44990543698894e-21
18511.97314595924037e-209.86572979620184e-21
18611.18197534046638e-195.9098767023319e-20
18718.0665913970733e-194.03329569853665e-19
18815.40223044059402e-182.70111522029701e-18
18913.64196616420125e-171.82098308210062e-17
19012.79713112165446e-161.39856556082723e-16
1910.9999999999999992.19856343693077e-151.09928171846538e-15
19213.31490062394433e-161.65745031197216e-16
1930.9999999999999992.72010906947575e-151.36005453473788e-15
1940.9999999999999892.24973109566673e-141.12486554783337e-14
1950.9999999999999131.74344134368563e-138.71720671842813e-14
1960.9999999999992761.44715959540582e-127.23579797702911e-13
1970.9999999999947971.04060420895857e-115.20302104479283e-12
1980.9999999999553668.92684653033057e-114.46342326516529e-11
1990.9999999996333867.33227937383966e-103.66613968691983e-10
2000.9999999975113624.97727635000438e-092.48863817500219e-09
2010.9999999854960962.90078082947871e-081.45039041473936e-08
2020.9999999190304971.6193900551732e-078.09695027586602e-08
2030.999999806617313.86765379182889e-071.93382689591444e-07
2040.9999999841355573.17288858334399e-081.586444291672e-08
2050.999999756436844.87126318980227e-072.43563159490114e-07
2060.9999962144248197.5711503623028e-063.7855751811514e-06
2070.999940667922090.0001186641558213225.9332077910661e-05
2080.9999775606684424.48786631150407e-052.24393315575204e-05

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.00115671466226769 & 0.00231342932453538 & 0.998843285337732 \tabularnewline
8 & 0.000118376259802133 & 0.000236752519604266 & 0.999881623740198 \tabularnewline
9 & 1.40840800499684e-05 & 2.81681600999367e-05 & 0.99998591591995 \tabularnewline
10 & 1.05860664760653e-06 & 2.11721329521307e-06 & 0.999998941393352 \tabularnewline
11 & 7.42132766925973e-08 & 1.48426553385195e-07 & 0.999999925786723 \tabularnewline
12 & 2.08019070750409e-05 & 4.16038141500819e-05 & 0.999979198092925 \tabularnewline
13 & 3.79408043532642e-06 & 7.58816087065283e-06 & 0.999996205919565 \tabularnewline
14 & 6.58454840120356e-07 & 1.31690968024071e-06 & 0.99999934154516 \tabularnewline
15 & 1.07491513666429e-07 & 2.14983027332858e-07 & 0.999999892508486 \tabularnewline
16 & 1.9284979427035e-08 & 3.85699588540699e-08 & 0.99999998071502 \tabularnewline
17 & 4.46747239400329e-09 & 8.93494478800659e-09 & 0.999999995532528 \tabularnewline
18 & 7.32217447130169e-10 & 1.46443489426034e-09 & 0.999999999267783 \tabularnewline
19 & 1.09457521427899e-10 & 2.18915042855799e-10 & 0.999999999890542 \tabularnewline
20 & 1.69734279672647e-11 & 3.39468559345294e-11 & 0.999999999983027 \tabularnewline
21 & 2.41909194886914e-12 & 4.83818389773827e-12 & 0.99999999999758 \tabularnewline
22 & 3.23314235345985e-13 & 6.4662847069197e-13 & 0.999999999999677 \tabularnewline
23 & 4.215718946365e-14 & 8.43143789273001e-14 & 0.999999999999958 \tabularnewline
24 & 1.98756080400704e-12 & 3.97512160801407e-12 & 0.999999999998012 \tabularnewline
25 & 3.36322289219786e-13 & 6.72644578439573e-13 & 0.999999999999664 \tabularnewline
26 & 5.5164662215849e-14 & 1.10329324431698e-13 & 0.999999999999945 \tabularnewline
27 & 8.79375690290096e-15 & 1.75875138058019e-14 & 0.999999999999991 \tabularnewline
28 & 1.58792070398823e-15 & 3.17584140797645e-15 & 0.999999999999998 \tabularnewline
29 & 5.79571016567398e-16 & 1.1591420331348e-15 & 1 \tabularnewline
30 & 1.34911449331401e-16 & 2.69822898662801e-16 & 1 \tabularnewline
31 & 2.70051377423489e-17 & 5.40102754846979e-17 & 1 \tabularnewline
32 & 5.38967187657891e-18 & 1.07793437531578e-17 & 1 \tabularnewline
33 & 1.44630465949546e-18 & 2.89260931899092e-18 & 1 \tabularnewline
34 & 4.08721467269162e-19 & 8.17442934538324e-19 & 1 \tabularnewline
35 & 1.11187902662134e-19 & 2.22375805324268e-19 & 1 \tabularnewline
36 & 8.89024846356204e-18 & 1.77804969271241e-17 & 1 \tabularnewline
37 & 2.83333553605794e-18 & 5.66667107211587e-18 & 1 \tabularnewline
38 & 9.03862785215871e-19 & 1.80772557043174e-18 & 1 \tabularnewline
39 & 4.01372774398711e-19 & 8.02745548797422e-19 & 1 \tabularnewline
40 & 2.44169177149616e-19 & 4.88338354299232e-19 & 1 \tabularnewline
41 & 8.98990880923735e-20 & 1.79798176184747e-19 & 1 \tabularnewline
42 & 5.27879359181157e-20 & 1.05575871836231e-19 & 1 \tabularnewline
43 & 2.02542464633922e-20 & 4.05084929267844e-20 & 1 \tabularnewline
44 & 8.33989916694203e-21 & 1.66797983338841e-20 & 1 \tabularnewline
45 & 3.41869036153435e-21 & 6.8373807230687e-21 & 1 \tabularnewline
46 & 1.37602463763035e-21 & 2.75204927526069e-21 & 1 \tabularnewline
47 & 6.30335467380133e-22 & 1.26067093476027e-21 & 1 \tabularnewline
48 & 1.11538885585596e-18 & 2.23077771171193e-18 & 1 \tabularnewline
49 & 4.75489606468618e-19 & 9.50979212937237e-19 & 1 \tabularnewline
50 & 1.80610319720834e-19 & 3.61220639441668e-19 & 1 \tabularnewline
51 & 8.11355597181473e-20 & 1.62271119436295e-19 & 1 \tabularnewline
52 & 3.24524261161195e-20 & 6.4904852232239e-20 & 1 \tabularnewline
53 & 1.43890097328965e-20 & 2.87780194657929e-20 & 1 \tabularnewline
54 & 1.43234919001758e-20 & 2.86469838003516e-20 & 1 \tabularnewline
55 & 9.2446629706912e-21 & 1.84893259413824e-20 & 1 \tabularnewline
56 & 5.46771399257409e-21 & 1.09354279851482e-20 & 1 \tabularnewline
57 & 3.43241416904894e-21 & 6.86482833809787e-21 & 1 \tabularnewline
58 & 2.46694301515511e-21 & 4.93388603031021e-21 & 1 \tabularnewline
59 & 2.91928850172571e-21 & 5.83857700345142e-21 & 1 \tabularnewline
60 & 6.7490120704802e-19 & 1.34980241409604e-18 & 1 \tabularnewline
61 & 4.4923074132624e-19 & 8.9846148265248e-19 & 1 \tabularnewline
62 & 4.92716461882829e-19 & 9.85432923765658e-19 & 1 \tabularnewline
63 & 4.88890794787677e-19 & 9.77781589575353e-19 & 1 \tabularnewline
64 & 4.13447426791113e-19 & 8.26894853582225e-19 & 1 \tabularnewline
65 & 1.91529843929122e-19 & 3.83059687858243e-19 & 1 \tabularnewline
66 & 7.50784500270693e-20 & 1.50156900054139e-19 & 1 \tabularnewline
67 & 2.67285422645732e-20 & 5.34570845291463e-20 & 1 \tabularnewline
68 & 8.85741533170073e-21 & 1.77148306634015e-20 & 1 \tabularnewline
69 & 4.04409949728505e-21 & 8.0881989945701e-21 & 1 \tabularnewline
70 & 1.004868521998e-20 & 2.009737043996e-20 & 1 \tabularnewline
71 & 3.83231115686618e-20 & 7.66462231373236e-20 & 1 \tabularnewline
72 & 4.22156290800205e-17 & 8.4431258160041e-17 & 1 \tabularnewline
73 & 4.03691479794101e-16 & 8.07382959588202e-16 & 1 \tabularnewline
74 & 2.32595407021374e-15 & 4.65190814042749e-15 & 0.999999999999998 \tabularnewline
75 & 6.8137228661236e-15 & 1.36274457322472e-14 & 0.999999999999993 \tabularnewline
76 & 3.95716586206869e-14 & 7.91433172413738e-14 & 0.99999999999996 \tabularnewline
77 & 6.69866979815012e-14 & 1.33973395963002e-13 & 0.999999999999933 \tabularnewline
78 & 1.95900454496285e-13 & 3.9180090899257e-13 & 0.999999999999804 \tabularnewline
79 & 6.65747560660795e-13 & 1.33149512132159e-12 & 0.999999999999334 \tabularnewline
80 & 5.86768063494188e-12 & 1.17353612698838e-11 & 0.999999999994132 \tabularnewline
81 & 7.72486816261642e-11 & 1.54497363252328e-10 & 0.999999999922751 \tabularnewline
82 & 9.3724004207021e-10 & 1.87448008414042e-09 & 0.99999999906276 \tabularnewline
83 & 8.09016631986917e-09 & 1.61803326397383e-08 & 0.999999991909834 \tabularnewline
84 & 1.62515592938862e-05 & 3.25031185877724e-05 & 0.999983748440706 \tabularnewline
85 & 7.58417939629174e-05 & 0.000151683587925835 & 0.999924158206037 \tabularnewline
86 & 0.00024168785028083 & 0.000483375700561661 & 0.99975831214972 \tabularnewline
87 & 0.00113117933546961 & 0.00226235867093921 & 0.99886882066453 \tabularnewline
88 & 0.00406818176187558 & 0.00813636352375116 & 0.995931818238124 \tabularnewline
89 & 0.0114354104297314 & 0.0228708208594629 & 0.988564589570269 \tabularnewline
90 & 0.0346369062744842 & 0.0692738125489684 & 0.965363093725516 \tabularnewline
91 & 0.0888636339433879 & 0.177727267886776 & 0.911136366056612 \tabularnewline
92 & 0.217171784981553 & 0.434343569963106 & 0.782828215018447 \tabularnewline
93 & 0.406069100761203 & 0.812138201522405 & 0.593930899238797 \tabularnewline
94 & 0.61258621913692 & 0.77482756172616 & 0.38741378086308 \tabularnewline
95 & 0.82093302116767 & 0.358133957664659 & 0.179066978832329 \tabularnewline
96 & 0.936022977651194 & 0.127954044697611 & 0.0639770223488056 \tabularnewline
97 & 0.982722846989278 & 0.0345543060214431 & 0.0172771530107215 \tabularnewline
98 & 0.997190615514565 & 0.00561876897086933 & 0.00280938448543467 \tabularnewline
99 & 0.99918376966267 & 0.00163246067465895 & 0.000816230337329474 \tabularnewline
100 & 0.999690177538173 & 0.000619644923653041 & 0.00030982246182652 \tabularnewline
101 & 0.999959761184756 & 8.04776304875783e-05 & 4.02388152437892e-05 \tabularnewline
102 & 0.999990452052586 & 1.90958948283424e-05 & 9.54794741417122e-06 \tabularnewline
103 & 0.999998755603978 & 2.4887920435007e-06 & 1.24439602175035e-06 \tabularnewline
104 & 0.999999964065727 & 7.18685452734227e-08 & 3.59342726367114e-08 \tabularnewline
105 & 0.999999999307257 & 1.38548561503816e-09 & 6.92742807519082e-10 \tabularnewline
106 & 0.99999999999112 & 1.77585510956225e-11 & 8.87927554781123e-12 \tabularnewline
107 & 0.999999999999863 & 2.73077171124669e-13 & 1.36538585562335e-13 \tabularnewline
108 & 0.999999999999916 & 1.69011801196534e-13 & 8.4505900598267e-14 \tabularnewline
109 & 0.999999999999963 & 7.43536821461076e-14 & 3.71768410730538e-14 \tabularnewline
110 & 0.999999999999975 & 5.08123937863228e-14 & 2.54061968931614e-14 \tabularnewline
111 & 0.999999999999974 & 5.10492196588177e-14 & 2.55246098294088e-14 \tabularnewline
112 & 0.999999999999976 & 4.8385992617301e-14 & 2.41929963086505e-14 \tabularnewline
113 & 0.99999999999999 & 1.99992360699611e-14 & 9.99961803498055e-15 \tabularnewline
114 & 0.999999999999997 & 6.68321817654467e-15 & 3.34160908827234e-15 \tabularnewline
115 & 1 & 7.45499100908792e-16 & 3.72749550454396e-16 \tabularnewline
116 & 1 & 8.80685948614233e-17 & 4.40342974307116e-17 \tabularnewline
117 & 1 & 9.1836893364025e-18 & 4.59184466820125e-18 \tabularnewline
118 & 1 & 2.06336807151548e-18 & 1.03168403575774e-18 \tabularnewline
119 & 1 & 2.54533674522349e-19 & 1.27266837261174e-19 \tabularnewline
120 & 1 & 5.31665543859097e-21 & 2.65832771929548e-21 \tabularnewline
121 & 1 & 1.0468610125209e-21 & 5.2343050626045e-22 \tabularnewline
122 & 1 & 2.42734964875655e-22 & 1.21367482437828e-22 \tabularnewline
123 & 1 & 6.64311476340493e-23 & 3.32155738170247e-23 \tabularnewline
124 & 1 & 2.5671189379896e-23 & 1.2835594689948e-23 \tabularnewline
125 & 1 & 7.4516867903e-24 & 3.72584339515e-24 \tabularnewline
126 & 1 & 4.07913511083245e-24 & 2.03956755541623e-24 \tabularnewline
127 & 1 & 2.00355353241414e-24 & 1.00177676620707e-24 \tabularnewline
128 & 1 & 1.08291385645351e-24 & 5.41456928226756e-25 \tabularnewline
129 & 1 & 2.5711976925677e-25 & 1.28559884628385e-25 \tabularnewline
130 & 1 & 3.61121486339497e-26 & 1.80560743169749e-26 \tabularnewline
131 & 1 & 8.25882973140404e-27 & 4.12941486570202e-27 \tabularnewline
132 & 1 & 9.0227881030398e-28 & 4.5113940515199e-28 \tabularnewline
133 & 1 & 2.57086605265084e-28 & 1.28543302632542e-28 \tabularnewline
134 & 1 & 6.27846784161761e-29 & 3.13923392080881e-29 \tabularnewline
135 & 1 & 2.13489888879702e-29 & 1.06744944439851e-29 \tabularnewline
136 & 1 & 1.92240252223203e-29 & 9.61201261116016e-30 \tabularnewline
137 & 1 & 8.88152265267611e-30 & 4.44076132633806e-30 \tabularnewline
138 & 1 & 3.55395546054912e-30 & 1.77697773027456e-30 \tabularnewline
139 & 1 & 1.57322512987554e-30 & 7.86612564937772e-31 \tabularnewline
140 & 1 & 7.0361968570965e-31 & 3.51809842854825e-31 \tabularnewline
141 & 1 & 2.196836180772e-31 & 1.098418090386e-31 \tabularnewline
142 & 1 & 6.73356054126683e-32 & 3.36678027063341e-32 \tabularnewline
143 & 1 & 2.43190930595008e-32 & 1.21595465297504e-32 \tabularnewline
144 & 1 & 7.42790954609629e-33 & 3.71395477304815e-33 \tabularnewline
145 & 1 & 5.79628528001305e-33 & 2.89814264000652e-33 \tabularnewline
146 & 1 & 4.69383791322202e-33 & 2.34691895661101e-33 \tabularnewline
147 & 1 & 1.0047472469728e-32 & 5.02373623486402e-33 \tabularnewline
148 & 1 & 2.16755699971721e-32 & 1.0837784998586e-32 \tabularnewline
149 & 1 & 2.90969184330239e-32 & 1.4548459216512e-32 \tabularnewline
150 & 1 & 6.76252094954243e-32 & 3.38126047477121e-32 \tabularnewline
151 & 1 & 1.81947113058368e-31 & 9.09735565291838e-32 \tabularnewline
152 & 1 & 3.30495756121582e-31 & 1.65247878060791e-31 \tabularnewline
153 & 1 & 5.19397054102973e-31 & 2.59698527051487e-31 \tabularnewline
154 & 1 & 1.27352159220445e-30 & 6.36760796102224e-31 \tabularnewline
155 & 1 & 3.77661323723665e-30 & 1.88830661861833e-30 \tabularnewline
156 & 1 & 2.30059737283607e-31 & 1.15029868641803e-31 \tabularnewline
157 & 1 & 9.2777994710535e-31 & 4.63889973552675e-31 \tabularnewline
158 & 1 & 3.88492690362132e-30 & 1.94246345181066e-30 \tabularnewline
159 & 1 & 1.68885525935239e-29 & 8.44427629676196e-30 \tabularnewline
160 & 1 & 5.320782324996e-29 & 2.660391162498e-29 \tabularnewline
161 & 1 & 1.38772801963412e-28 & 6.93864009817061e-29 \tabularnewline
162 & 1 & 4.6435076564871e-28 & 2.32175382824355e-28 \tabularnewline
163 & 1 & 1.1544497942422e-27 & 5.77224897121099e-28 \tabularnewline
164 & 1 & 2.18993432592597e-27 & 1.09496716296298e-27 \tabularnewline
165 & 1 & 2.93538997807206e-27 & 1.46769498903603e-27 \tabularnewline
166 & 1 & 4.09825651909349e-27 & 2.04912825954674e-27 \tabularnewline
167 & 1 & 3.55000444925382e-27 & 1.77500222462691e-27 \tabularnewline
168 & 1 & 1.37977060585974e-27 & 6.89885302929872e-28 \tabularnewline
169 & 1 & 3.76269094099137e-27 & 1.88134547049568e-27 \tabularnewline
170 & 1 & 1.4571453593777e-26 & 7.28572679688852e-27 \tabularnewline
171 & 1 & 5.73245234319575e-26 & 2.86622617159788e-26 \tabularnewline
172 & 1 & 1.47100939082504e-25 & 7.35504695412518e-26 \tabularnewline
173 & 1 & 5.41101603287011e-25 & 2.70550801643505e-25 \tabularnewline
174 & 1 & 2.52626829726673e-24 & 1.26313414863337e-24 \tabularnewline
175 & 1 & 1.13073808351959e-23 & 5.65369041759793e-24 \tabularnewline
176 & 1 & 4.61754388008215e-23 & 2.30877194004108e-23 \tabularnewline
177 & 1 & 2.0981887551325e-22 & 1.04909437756625e-22 \tabularnewline
178 & 1 & 8.30757897245316e-22 & 4.15378948622658e-22 \tabularnewline
179 & 1 & 3.37388196991793e-21 & 1.68694098495897e-21 \tabularnewline
180 & 1 & 9.89400356304722e-24 & 4.94700178152361e-24 \tabularnewline
181 & 1 & 5.4280859658195e-23 & 2.71404298290975e-23 \tabularnewline
182 & 1 & 2.93489101950486e-22 & 1.46744550975243e-22 \tabularnewline
183 & 1 & 1.596933187193e-21 & 7.98466593596502e-22 \tabularnewline
184 & 1 & 2.89981087397788e-21 & 1.44990543698894e-21 \tabularnewline
185 & 1 & 1.97314595924037e-20 & 9.86572979620184e-21 \tabularnewline
186 & 1 & 1.18197534046638e-19 & 5.9098767023319e-20 \tabularnewline
187 & 1 & 8.0665913970733e-19 & 4.03329569853665e-19 \tabularnewline
188 & 1 & 5.40223044059402e-18 & 2.70111522029701e-18 \tabularnewline
189 & 1 & 3.64196616420125e-17 & 1.82098308210062e-17 \tabularnewline
190 & 1 & 2.79713112165446e-16 & 1.39856556082723e-16 \tabularnewline
191 & 0.999999999999999 & 2.19856343693077e-15 & 1.09928171846538e-15 \tabularnewline
192 & 1 & 3.31490062394433e-16 & 1.65745031197216e-16 \tabularnewline
193 & 0.999999999999999 & 2.72010906947575e-15 & 1.36005453473788e-15 \tabularnewline
194 & 0.999999999999989 & 2.24973109566673e-14 & 1.12486554783337e-14 \tabularnewline
195 & 0.999999999999913 & 1.74344134368563e-13 & 8.71720671842813e-14 \tabularnewline
196 & 0.999999999999276 & 1.44715959540582e-12 & 7.23579797702911e-13 \tabularnewline
197 & 0.999999999994797 & 1.04060420895857e-11 & 5.20302104479283e-12 \tabularnewline
198 & 0.999999999955366 & 8.92684653033057e-11 & 4.46342326516529e-11 \tabularnewline
199 & 0.999999999633386 & 7.33227937383966e-10 & 3.66613968691983e-10 \tabularnewline
200 & 0.999999997511362 & 4.97727635000438e-09 & 2.48863817500219e-09 \tabularnewline
201 & 0.999999985496096 & 2.90078082947871e-08 & 1.45039041473936e-08 \tabularnewline
202 & 0.999999919030497 & 1.6193900551732e-07 & 8.09695027586602e-08 \tabularnewline
203 & 0.99999980661731 & 3.86765379182889e-07 & 1.93382689591444e-07 \tabularnewline
204 & 0.999999984135557 & 3.17288858334399e-08 & 1.586444291672e-08 \tabularnewline
205 & 0.99999975643684 & 4.87126318980227e-07 & 2.43563159490114e-07 \tabularnewline
206 & 0.999996214424819 & 7.5711503623028e-06 & 3.7855751811514e-06 \tabularnewline
207 & 0.99994066792209 & 0.000118664155821322 & 5.9332077910661e-05 \tabularnewline
208 & 0.999977560668442 & 4.48786631150407e-05 & 2.24393315575204e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116970&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]7[/C][C]0.00115671466226769[/C][C]0.00231342932453538[/C][C]0.998843285337732[/C][/ROW]
[ROW][C]8[/C][C]0.000118376259802133[/C][C]0.000236752519604266[/C][C]0.999881623740198[/C][/ROW]
[ROW][C]9[/C][C]1.40840800499684e-05[/C][C]2.81681600999367e-05[/C][C]0.99998591591995[/C][/ROW]
[ROW][C]10[/C][C]1.05860664760653e-06[/C][C]2.11721329521307e-06[/C][C]0.999998941393352[/C][/ROW]
[ROW][C]11[/C][C]7.42132766925973e-08[/C][C]1.48426553385195e-07[/C][C]0.999999925786723[/C][/ROW]
[ROW][C]12[/C][C]2.08019070750409e-05[/C][C]4.16038141500819e-05[/C][C]0.999979198092925[/C][/ROW]
[ROW][C]13[/C][C]3.79408043532642e-06[/C][C]7.58816087065283e-06[/C][C]0.999996205919565[/C][/ROW]
[ROW][C]14[/C][C]6.58454840120356e-07[/C][C]1.31690968024071e-06[/C][C]0.99999934154516[/C][/ROW]
[ROW][C]15[/C][C]1.07491513666429e-07[/C][C]2.14983027332858e-07[/C][C]0.999999892508486[/C][/ROW]
[ROW][C]16[/C][C]1.9284979427035e-08[/C][C]3.85699588540699e-08[/C][C]0.99999998071502[/C][/ROW]
[ROW][C]17[/C][C]4.46747239400329e-09[/C][C]8.93494478800659e-09[/C][C]0.999999995532528[/C][/ROW]
[ROW][C]18[/C][C]7.32217447130169e-10[/C][C]1.46443489426034e-09[/C][C]0.999999999267783[/C][/ROW]
[ROW][C]19[/C][C]1.09457521427899e-10[/C][C]2.18915042855799e-10[/C][C]0.999999999890542[/C][/ROW]
[ROW][C]20[/C][C]1.69734279672647e-11[/C][C]3.39468559345294e-11[/C][C]0.999999999983027[/C][/ROW]
[ROW][C]21[/C][C]2.41909194886914e-12[/C][C]4.83818389773827e-12[/C][C]0.99999999999758[/C][/ROW]
[ROW][C]22[/C][C]3.23314235345985e-13[/C][C]6.4662847069197e-13[/C][C]0.999999999999677[/C][/ROW]
[ROW][C]23[/C][C]4.215718946365e-14[/C][C]8.43143789273001e-14[/C][C]0.999999999999958[/C][/ROW]
[ROW][C]24[/C][C]1.98756080400704e-12[/C][C]3.97512160801407e-12[/C][C]0.999999999998012[/C][/ROW]
[ROW][C]25[/C][C]3.36322289219786e-13[/C][C]6.72644578439573e-13[/C][C]0.999999999999664[/C][/ROW]
[ROW][C]26[/C][C]5.5164662215849e-14[/C][C]1.10329324431698e-13[/C][C]0.999999999999945[/C][/ROW]
[ROW][C]27[/C][C]8.79375690290096e-15[/C][C]1.75875138058019e-14[/C][C]0.999999999999991[/C][/ROW]
[ROW][C]28[/C][C]1.58792070398823e-15[/C][C]3.17584140797645e-15[/C][C]0.999999999999998[/C][/ROW]
[ROW][C]29[/C][C]5.79571016567398e-16[/C][C]1.1591420331348e-15[/C][C]1[/C][/ROW]
[ROW][C]30[/C][C]1.34911449331401e-16[/C][C]2.69822898662801e-16[/C][C]1[/C][/ROW]
[ROW][C]31[/C][C]2.70051377423489e-17[/C][C]5.40102754846979e-17[/C][C]1[/C][/ROW]
[ROW][C]32[/C][C]5.38967187657891e-18[/C][C]1.07793437531578e-17[/C][C]1[/C][/ROW]
[ROW][C]33[/C][C]1.44630465949546e-18[/C][C]2.89260931899092e-18[/C][C]1[/C][/ROW]
[ROW][C]34[/C][C]4.08721467269162e-19[/C][C]8.17442934538324e-19[/C][C]1[/C][/ROW]
[ROW][C]35[/C][C]1.11187902662134e-19[/C][C]2.22375805324268e-19[/C][C]1[/C][/ROW]
[ROW][C]36[/C][C]8.89024846356204e-18[/C][C]1.77804969271241e-17[/C][C]1[/C][/ROW]
[ROW][C]37[/C][C]2.83333553605794e-18[/C][C]5.66667107211587e-18[/C][C]1[/C][/ROW]
[ROW][C]38[/C][C]9.03862785215871e-19[/C][C]1.80772557043174e-18[/C][C]1[/C][/ROW]
[ROW][C]39[/C][C]4.01372774398711e-19[/C][C]8.02745548797422e-19[/C][C]1[/C][/ROW]
[ROW][C]40[/C][C]2.44169177149616e-19[/C][C]4.88338354299232e-19[/C][C]1[/C][/ROW]
[ROW][C]41[/C][C]8.98990880923735e-20[/C][C]1.79798176184747e-19[/C][C]1[/C][/ROW]
[ROW][C]42[/C][C]5.27879359181157e-20[/C][C]1.05575871836231e-19[/C][C]1[/C][/ROW]
[ROW][C]43[/C][C]2.02542464633922e-20[/C][C]4.05084929267844e-20[/C][C]1[/C][/ROW]
[ROW][C]44[/C][C]8.33989916694203e-21[/C][C]1.66797983338841e-20[/C][C]1[/C][/ROW]
[ROW][C]45[/C][C]3.41869036153435e-21[/C][C]6.8373807230687e-21[/C][C]1[/C][/ROW]
[ROW][C]46[/C][C]1.37602463763035e-21[/C][C]2.75204927526069e-21[/C][C]1[/C][/ROW]
[ROW][C]47[/C][C]6.30335467380133e-22[/C][C]1.26067093476027e-21[/C][C]1[/C][/ROW]
[ROW][C]48[/C][C]1.11538885585596e-18[/C][C]2.23077771171193e-18[/C][C]1[/C][/ROW]
[ROW][C]49[/C][C]4.75489606468618e-19[/C][C]9.50979212937237e-19[/C][C]1[/C][/ROW]
[ROW][C]50[/C][C]1.80610319720834e-19[/C][C]3.61220639441668e-19[/C][C]1[/C][/ROW]
[ROW][C]51[/C][C]8.11355597181473e-20[/C][C]1.62271119436295e-19[/C][C]1[/C][/ROW]
[ROW][C]52[/C][C]3.24524261161195e-20[/C][C]6.4904852232239e-20[/C][C]1[/C][/ROW]
[ROW][C]53[/C][C]1.43890097328965e-20[/C][C]2.87780194657929e-20[/C][C]1[/C][/ROW]
[ROW][C]54[/C][C]1.43234919001758e-20[/C][C]2.86469838003516e-20[/C][C]1[/C][/ROW]
[ROW][C]55[/C][C]9.2446629706912e-21[/C][C]1.84893259413824e-20[/C][C]1[/C][/ROW]
[ROW][C]56[/C][C]5.46771399257409e-21[/C][C]1.09354279851482e-20[/C][C]1[/C][/ROW]
[ROW][C]57[/C][C]3.43241416904894e-21[/C][C]6.86482833809787e-21[/C][C]1[/C][/ROW]
[ROW][C]58[/C][C]2.46694301515511e-21[/C][C]4.93388603031021e-21[/C][C]1[/C][/ROW]
[ROW][C]59[/C][C]2.91928850172571e-21[/C][C]5.83857700345142e-21[/C][C]1[/C][/ROW]
[ROW][C]60[/C][C]6.7490120704802e-19[/C][C]1.34980241409604e-18[/C][C]1[/C][/ROW]
[ROW][C]61[/C][C]4.4923074132624e-19[/C][C]8.9846148265248e-19[/C][C]1[/C][/ROW]
[ROW][C]62[/C][C]4.92716461882829e-19[/C][C]9.85432923765658e-19[/C][C]1[/C][/ROW]
[ROW][C]63[/C][C]4.88890794787677e-19[/C][C]9.77781589575353e-19[/C][C]1[/C][/ROW]
[ROW][C]64[/C][C]4.13447426791113e-19[/C][C]8.26894853582225e-19[/C][C]1[/C][/ROW]
[ROW][C]65[/C][C]1.91529843929122e-19[/C][C]3.83059687858243e-19[/C][C]1[/C][/ROW]
[ROW][C]66[/C][C]7.50784500270693e-20[/C][C]1.50156900054139e-19[/C][C]1[/C][/ROW]
[ROW][C]67[/C][C]2.67285422645732e-20[/C][C]5.34570845291463e-20[/C][C]1[/C][/ROW]
[ROW][C]68[/C][C]8.85741533170073e-21[/C][C]1.77148306634015e-20[/C][C]1[/C][/ROW]
[ROW][C]69[/C][C]4.04409949728505e-21[/C][C]8.0881989945701e-21[/C][C]1[/C][/ROW]
[ROW][C]70[/C][C]1.004868521998e-20[/C][C]2.009737043996e-20[/C][C]1[/C][/ROW]
[ROW][C]71[/C][C]3.83231115686618e-20[/C][C]7.66462231373236e-20[/C][C]1[/C][/ROW]
[ROW][C]72[/C][C]4.22156290800205e-17[/C][C]8.4431258160041e-17[/C][C]1[/C][/ROW]
[ROW][C]73[/C][C]4.03691479794101e-16[/C][C]8.07382959588202e-16[/C][C]1[/C][/ROW]
[ROW][C]74[/C][C]2.32595407021374e-15[/C][C]4.65190814042749e-15[/C][C]0.999999999999998[/C][/ROW]
[ROW][C]75[/C][C]6.8137228661236e-15[/C][C]1.36274457322472e-14[/C][C]0.999999999999993[/C][/ROW]
[ROW][C]76[/C][C]3.95716586206869e-14[/C][C]7.91433172413738e-14[/C][C]0.99999999999996[/C][/ROW]
[ROW][C]77[/C][C]6.69866979815012e-14[/C][C]1.33973395963002e-13[/C][C]0.999999999999933[/C][/ROW]
[ROW][C]78[/C][C]1.95900454496285e-13[/C][C]3.9180090899257e-13[/C][C]0.999999999999804[/C][/ROW]
[ROW][C]79[/C][C]6.65747560660795e-13[/C][C]1.33149512132159e-12[/C][C]0.999999999999334[/C][/ROW]
[ROW][C]80[/C][C]5.86768063494188e-12[/C][C]1.17353612698838e-11[/C][C]0.999999999994132[/C][/ROW]
[ROW][C]81[/C][C]7.72486816261642e-11[/C][C]1.54497363252328e-10[/C][C]0.999999999922751[/C][/ROW]
[ROW][C]82[/C][C]9.3724004207021e-10[/C][C]1.87448008414042e-09[/C][C]0.99999999906276[/C][/ROW]
[ROW][C]83[/C][C]8.09016631986917e-09[/C][C]1.61803326397383e-08[/C][C]0.999999991909834[/C][/ROW]
[ROW][C]84[/C][C]1.62515592938862e-05[/C][C]3.25031185877724e-05[/C][C]0.999983748440706[/C][/ROW]
[ROW][C]85[/C][C]7.58417939629174e-05[/C][C]0.000151683587925835[/C][C]0.999924158206037[/C][/ROW]
[ROW][C]86[/C][C]0.00024168785028083[/C][C]0.000483375700561661[/C][C]0.99975831214972[/C][/ROW]
[ROW][C]87[/C][C]0.00113117933546961[/C][C]0.00226235867093921[/C][C]0.99886882066453[/C][/ROW]
[ROW][C]88[/C][C]0.00406818176187558[/C][C]0.00813636352375116[/C][C]0.995931818238124[/C][/ROW]
[ROW][C]89[/C][C]0.0114354104297314[/C][C]0.0228708208594629[/C][C]0.988564589570269[/C][/ROW]
[ROW][C]90[/C][C]0.0346369062744842[/C][C]0.0692738125489684[/C][C]0.965363093725516[/C][/ROW]
[ROW][C]91[/C][C]0.0888636339433879[/C][C]0.177727267886776[/C][C]0.911136366056612[/C][/ROW]
[ROW][C]92[/C][C]0.217171784981553[/C][C]0.434343569963106[/C][C]0.782828215018447[/C][/ROW]
[ROW][C]93[/C][C]0.406069100761203[/C][C]0.812138201522405[/C][C]0.593930899238797[/C][/ROW]
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[ROW][C]97[/C][C]0.982722846989278[/C][C]0.0345543060214431[/C][C]0.0172771530107215[/C][/ROW]
[ROW][C]98[/C][C]0.997190615514565[/C][C]0.00561876897086933[/C][C]0.00280938448543467[/C][/ROW]
[ROW][C]99[/C][C]0.99918376966267[/C][C]0.00163246067465895[/C][C]0.000816230337329474[/C][/ROW]
[ROW][C]100[/C][C]0.999690177538173[/C][C]0.000619644923653041[/C][C]0.00030982246182652[/C][/ROW]
[ROW][C]101[/C][C]0.999959761184756[/C][C]8.04776304875783e-05[/C][C]4.02388152437892e-05[/C][/ROW]
[ROW][C]102[/C][C]0.999990452052586[/C][C]1.90958948283424e-05[/C][C]9.54794741417122e-06[/C][/ROW]
[ROW][C]103[/C][C]0.999998755603978[/C][C]2.4887920435007e-06[/C][C]1.24439602175035e-06[/C][/ROW]
[ROW][C]104[/C][C]0.999999964065727[/C][C]7.18685452734227e-08[/C][C]3.59342726367114e-08[/C][/ROW]
[ROW][C]105[/C][C]0.999999999307257[/C][C]1.38548561503816e-09[/C][C]6.92742807519082e-10[/C][/ROW]
[ROW][C]106[/C][C]0.99999999999112[/C][C]1.77585510956225e-11[/C][C]8.87927554781123e-12[/C][/ROW]
[ROW][C]107[/C][C]0.999999999999863[/C][C]2.73077171124669e-13[/C][C]1.36538585562335e-13[/C][/ROW]
[ROW][C]108[/C][C]0.999999999999916[/C][C]1.69011801196534e-13[/C][C]8.4505900598267e-14[/C][/ROW]
[ROW][C]109[/C][C]0.999999999999963[/C][C]7.43536821461076e-14[/C][C]3.71768410730538e-14[/C][/ROW]
[ROW][C]110[/C][C]0.999999999999975[/C][C]5.08123937863228e-14[/C][C]2.54061968931614e-14[/C][/ROW]
[ROW][C]111[/C][C]0.999999999999974[/C][C]5.10492196588177e-14[/C][C]2.55246098294088e-14[/C][/ROW]
[ROW][C]112[/C][C]0.999999999999976[/C][C]4.8385992617301e-14[/C][C]2.41929963086505e-14[/C][/ROW]
[ROW][C]113[/C][C]0.99999999999999[/C][C]1.99992360699611e-14[/C][C]9.99961803498055e-15[/C][/ROW]
[ROW][C]114[/C][C]0.999999999999997[/C][C]6.68321817654467e-15[/C][C]3.34160908827234e-15[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]7.45499100908792e-16[/C][C]3.72749550454396e-16[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]8.80685948614233e-17[/C][C]4.40342974307116e-17[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]9.1836893364025e-18[/C][C]4.59184466820125e-18[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]2.06336807151548e-18[/C][C]1.03168403575774e-18[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]2.54533674522349e-19[/C][C]1.27266837261174e-19[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]5.31665543859097e-21[/C][C]2.65832771929548e-21[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]1.0468610125209e-21[/C][C]5.2343050626045e-22[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]2.42734964875655e-22[/C][C]1.21367482437828e-22[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]6.64311476340493e-23[/C][C]3.32155738170247e-23[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]2.5671189379896e-23[/C][C]1.2835594689948e-23[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]7.4516867903e-24[/C][C]3.72584339515e-24[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]4.07913511083245e-24[/C][C]2.03956755541623e-24[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]2.00355353241414e-24[/C][C]1.00177676620707e-24[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]1.08291385645351e-24[/C][C]5.41456928226756e-25[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]2.5711976925677e-25[/C][C]1.28559884628385e-25[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]3.61121486339497e-26[/C][C]1.80560743169749e-26[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]8.25882973140404e-27[/C][C]4.12941486570202e-27[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]9.0227881030398e-28[/C][C]4.5113940515199e-28[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]2.57086605265084e-28[/C][C]1.28543302632542e-28[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]6.27846784161761e-29[/C][C]3.13923392080881e-29[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]2.13489888879702e-29[/C][C]1.06744944439851e-29[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]1.92240252223203e-29[/C][C]9.61201261116016e-30[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]8.88152265267611e-30[/C][C]4.44076132633806e-30[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]3.55395546054912e-30[/C][C]1.77697773027456e-30[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]1.57322512987554e-30[/C][C]7.86612564937772e-31[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]7.0361968570965e-31[/C][C]3.51809842854825e-31[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]2.196836180772e-31[/C][C]1.098418090386e-31[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]6.73356054126683e-32[/C][C]3.36678027063341e-32[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]2.43190930595008e-32[/C][C]1.21595465297504e-32[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]7.42790954609629e-33[/C][C]3.71395477304815e-33[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]5.79628528001305e-33[/C][C]2.89814264000652e-33[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]4.69383791322202e-33[/C][C]2.34691895661101e-33[/C][/ROW]
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[ROW][C]149[/C][C]1[/C][C]2.90969184330239e-32[/C][C]1.4548459216512e-32[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]6.76252094954243e-32[/C][C]3.38126047477121e-32[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]1.81947113058368e-31[/C][C]9.09735565291838e-32[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]3.30495756121582e-31[/C][C]1.65247878060791e-31[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]5.19397054102973e-31[/C][C]2.59698527051487e-31[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]1.27352159220445e-30[/C][C]6.36760796102224e-31[/C][/ROW]
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[ROW][C]156[/C][C]1[/C][C]2.30059737283607e-31[/C][C]1.15029868641803e-31[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]9.2777994710535e-31[/C][C]4.63889973552675e-31[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]3.88492690362132e-30[/C][C]1.94246345181066e-30[/C][/ROW]
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[ROW][C]161[/C][C]1[/C][C]1.38772801963412e-28[/C][C]6.93864009817061e-29[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]4.6435076564871e-28[/C][C]2.32175382824355e-28[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]1.1544497942422e-27[/C][C]5.77224897121099e-28[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]2.18993432592597e-27[/C][C]1.09496716296298e-27[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]2.93538997807206e-27[/C][C]1.46769498903603e-27[/C][/ROW]
[ROW][C]166[/C][C]1[/C][C]4.09825651909349e-27[/C][C]2.04912825954674e-27[/C][/ROW]
[ROW][C]167[/C][C]1[/C][C]3.55000444925382e-27[/C][C]1.77500222462691e-27[/C][/ROW]
[ROW][C]168[/C][C]1[/C][C]1.37977060585974e-27[/C][C]6.89885302929872e-28[/C][/ROW]
[ROW][C]169[/C][C]1[/C][C]3.76269094099137e-27[/C][C]1.88134547049568e-27[/C][/ROW]
[ROW][C]170[/C][C]1[/C][C]1.4571453593777e-26[/C][C]7.28572679688852e-27[/C][/ROW]
[ROW][C]171[/C][C]1[/C][C]5.73245234319575e-26[/C][C]2.86622617159788e-26[/C][/ROW]
[ROW][C]172[/C][C]1[/C][C]1.47100939082504e-25[/C][C]7.35504695412518e-26[/C][/ROW]
[ROW][C]173[/C][C]1[/C][C]5.41101603287011e-25[/C][C]2.70550801643505e-25[/C][/ROW]
[ROW][C]174[/C][C]1[/C][C]2.52626829726673e-24[/C][C]1.26313414863337e-24[/C][/ROW]
[ROW][C]175[/C][C]1[/C][C]1.13073808351959e-23[/C][C]5.65369041759793e-24[/C][/ROW]
[ROW][C]176[/C][C]1[/C][C]4.61754388008215e-23[/C][C]2.30877194004108e-23[/C][/ROW]
[ROW][C]177[/C][C]1[/C][C]2.0981887551325e-22[/C][C]1.04909437756625e-22[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]8.30757897245316e-22[/C][C]4.15378948622658e-22[/C][/ROW]
[ROW][C]179[/C][C]1[/C][C]3.37388196991793e-21[/C][C]1.68694098495897e-21[/C][/ROW]
[ROW][C]180[/C][C]1[/C][C]9.89400356304722e-24[/C][C]4.94700178152361e-24[/C][/ROW]
[ROW][C]181[/C][C]1[/C][C]5.4280859658195e-23[/C][C]2.71404298290975e-23[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]2.93489101950486e-22[/C][C]1.46744550975243e-22[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]1.596933187193e-21[/C][C]7.98466593596502e-22[/C][/ROW]
[ROW][C]184[/C][C]1[/C][C]2.89981087397788e-21[/C][C]1.44990543698894e-21[/C][/ROW]
[ROW][C]185[/C][C]1[/C][C]1.97314595924037e-20[/C][C]9.86572979620184e-21[/C][/ROW]
[ROW][C]186[/C][C]1[/C][C]1.18197534046638e-19[/C][C]5.9098767023319e-20[/C][/ROW]
[ROW][C]187[/C][C]1[/C][C]8.0665913970733e-19[/C][C]4.03329569853665e-19[/C][/ROW]
[ROW][C]188[/C][C]1[/C][C]5.40223044059402e-18[/C][C]2.70111522029701e-18[/C][/ROW]
[ROW][C]189[/C][C]1[/C][C]3.64196616420125e-17[/C][C]1.82098308210062e-17[/C][/ROW]
[ROW][C]190[/C][C]1[/C][C]2.79713112165446e-16[/C][C]1.39856556082723e-16[/C][/ROW]
[ROW][C]191[/C][C]0.999999999999999[/C][C]2.19856343693077e-15[/C][C]1.09928171846538e-15[/C][/ROW]
[ROW][C]192[/C][C]1[/C][C]3.31490062394433e-16[/C][C]1.65745031197216e-16[/C][/ROW]
[ROW][C]193[/C][C]0.999999999999999[/C][C]2.72010906947575e-15[/C][C]1.36005453473788e-15[/C][/ROW]
[ROW][C]194[/C][C]0.999999999999989[/C][C]2.24973109566673e-14[/C][C]1.12486554783337e-14[/C][/ROW]
[ROW][C]195[/C][C]0.999999999999913[/C][C]1.74344134368563e-13[/C][C]8.71720671842813e-14[/C][/ROW]
[ROW][C]196[/C][C]0.999999999999276[/C][C]1.44715959540582e-12[/C][C]7.23579797702911e-13[/C][/ROW]
[ROW][C]197[/C][C]0.999999999994797[/C][C]1.04060420895857e-11[/C][C]5.20302104479283e-12[/C][/ROW]
[ROW][C]198[/C][C]0.999999999955366[/C][C]8.92684653033057e-11[/C][C]4.46342326516529e-11[/C][/ROW]
[ROW][C]199[/C][C]0.999999999633386[/C][C]7.33227937383966e-10[/C][C]3.66613968691983e-10[/C][/ROW]
[ROW][C]200[/C][C]0.999999997511362[/C][C]4.97727635000438e-09[/C][C]2.48863817500219e-09[/C][/ROW]
[ROW][C]201[/C][C]0.999999985496096[/C][C]2.90078082947871e-08[/C][C]1.45039041473936e-08[/C][/ROW]
[ROW][C]202[/C][C]0.999999919030497[/C][C]1.6193900551732e-07[/C][C]8.09695027586602e-08[/C][/ROW]
[ROW][C]203[/C][C]0.99999980661731[/C][C]3.86765379182889e-07[/C][C]1.93382689591444e-07[/C][/ROW]
[ROW][C]204[/C][C]0.999999984135557[/C][C]3.17288858334399e-08[/C][C]1.586444291672e-08[/C][/ROW]
[ROW][C]205[/C][C]0.99999975643684[/C][C]4.87126318980227e-07[/C][C]2.43563159490114e-07[/C][/ROW]
[ROW][C]206[/C][C]0.999996214424819[/C][C]7.5711503623028e-06[/C][C]3.7855751811514e-06[/C][/ROW]
[ROW][C]207[/C][C]0.99994066792209[/C][C]0.000118664155821322[/C][C]5.9332077910661e-05[/C][/ROW]
[ROW][C]208[/C][C]0.999977560668442[/C][C]4.48786631150407e-05[/C][C]2.24393315575204e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116970&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116970&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.001156714662267690.002313429324535380.998843285337732
80.0001183762598021330.0002367525196042660.999881623740198
91.40840800499684e-052.81681600999367e-050.99998591591995
101.05860664760653e-062.11721329521307e-060.999998941393352
117.42132766925973e-081.48426553385195e-070.999999925786723
122.08019070750409e-054.16038141500819e-050.999979198092925
133.79408043532642e-067.58816087065283e-060.999996205919565
146.58454840120356e-071.31690968024071e-060.99999934154516
151.07491513666429e-072.14983027332858e-070.999999892508486
161.9284979427035e-083.85699588540699e-080.99999998071502
174.46747239400329e-098.93494478800659e-090.999999995532528
187.32217447130169e-101.46443489426034e-090.999999999267783
191.09457521427899e-102.18915042855799e-100.999999999890542
201.69734279672647e-113.39468559345294e-110.999999999983027
212.41909194886914e-124.83818389773827e-120.99999999999758
223.23314235345985e-136.4662847069197e-130.999999999999677
234.215718946365e-148.43143789273001e-140.999999999999958
241.98756080400704e-123.97512160801407e-120.999999999998012
253.36322289219786e-136.72644578439573e-130.999999999999664
265.5164662215849e-141.10329324431698e-130.999999999999945
278.79375690290096e-151.75875138058019e-140.999999999999991
281.58792070398823e-153.17584140797645e-150.999999999999998
295.79571016567398e-161.1591420331348e-151
301.34911449331401e-162.69822898662801e-161
312.70051377423489e-175.40102754846979e-171
325.38967187657891e-181.07793437531578e-171
331.44630465949546e-182.89260931899092e-181
344.08721467269162e-198.17442934538324e-191
351.11187902662134e-192.22375805324268e-191
368.89024846356204e-181.77804969271241e-171
372.83333553605794e-185.66667107211587e-181
389.03862785215871e-191.80772557043174e-181
394.01372774398711e-198.02745548797422e-191
402.44169177149616e-194.88338354299232e-191
418.98990880923735e-201.79798176184747e-191
425.27879359181157e-201.05575871836231e-191
432.02542464633922e-204.05084929267844e-201
448.33989916694203e-211.66797983338841e-201
453.41869036153435e-216.8373807230687e-211
461.37602463763035e-212.75204927526069e-211
476.30335467380133e-221.26067093476027e-211
481.11538885585596e-182.23077771171193e-181
494.75489606468618e-199.50979212937237e-191
501.80610319720834e-193.61220639441668e-191
518.11355597181473e-201.62271119436295e-191
523.24524261161195e-206.4904852232239e-201
531.43890097328965e-202.87780194657929e-201
541.43234919001758e-202.86469838003516e-201
559.2446629706912e-211.84893259413824e-201
565.46771399257409e-211.09354279851482e-201
573.43241416904894e-216.86482833809787e-211
582.46694301515511e-214.93388603031021e-211
592.91928850172571e-215.83857700345142e-211
606.7490120704802e-191.34980241409604e-181
614.4923074132624e-198.9846148265248e-191
624.92716461882829e-199.85432923765658e-191
634.88890794787677e-199.77781589575353e-191
644.13447426791113e-198.26894853582225e-191
651.91529843929122e-193.83059687858243e-191
667.50784500270693e-201.50156900054139e-191
672.67285422645732e-205.34570845291463e-201
688.85741533170073e-211.77148306634015e-201
694.04409949728505e-218.0881989945701e-211
701.004868521998e-202.009737043996e-201
713.83231115686618e-207.66462231373236e-201
724.22156290800205e-178.4431258160041e-171
734.03691479794101e-168.07382959588202e-161
742.32595407021374e-154.65190814042749e-150.999999999999998
756.8137228661236e-151.36274457322472e-140.999999999999993
763.95716586206869e-147.91433172413738e-140.99999999999996
776.69866979815012e-141.33973395963002e-130.999999999999933
781.95900454496285e-133.9180090899257e-130.999999999999804
796.65747560660795e-131.33149512132159e-120.999999999999334
805.86768063494188e-121.17353612698838e-110.999999999994132
817.72486816261642e-111.54497363252328e-100.999999999922751
829.3724004207021e-101.87448008414042e-090.99999999906276
838.09016631986917e-091.61803326397383e-080.999999991909834
841.62515592938862e-053.25031185877724e-050.999983748440706
857.58417939629174e-050.0001516835879258350.999924158206037
860.000241687850280830.0004833757005616610.99975831214972
870.001131179335469610.002262358670939210.99886882066453
880.004068181761875580.008136363523751160.995931818238124
890.01143541042973140.02287082085946290.988564589570269
900.03463690627448420.06927381254896840.965363093725516
910.08886363394338790.1777272678867760.911136366056612
920.2171717849815530.4343435699631060.782828215018447
930.4060691007612030.8121382015224050.593930899238797
940.612586219136920.774827561726160.38741378086308
950.820933021167670.3581339576646590.179066978832329
960.9360229776511940.1279540446976110.0639770223488056
970.9827228469892780.03455430602144310.0172771530107215
980.9971906155145650.005618768970869330.00280938448543467
990.999183769662670.001632460674658950.000816230337329474
1000.9996901775381730.0006196449236530410.00030982246182652
1010.9999597611847568.04776304875783e-054.02388152437892e-05
1020.9999904520525861.90958948283424e-059.54794741417122e-06
1030.9999987556039782.4887920435007e-061.24439602175035e-06
1040.9999999640657277.18685452734227e-083.59342726367114e-08
1050.9999999993072571.38548561503816e-096.92742807519082e-10
1060.999999999991121.77585510956225e-118.87927554781123e-12
1070.9999999999998632.73077171124669e-131.36538585562335e-13
1080.9999999999999161.69011801196534e-138.4505900598267e-14
1090.9999999999999637.43536821461076e-143.71768410730538e-14
1100.9999999999999755.08123937863228e-142.54061968931614e-14
1110.9999999999999745.10492196588177e-142.55246098294088e-14
1120.9999999999999764.8385992617301e-142.41929963086505e-14
1130.999999999999991.99992360699611e-149.99961803498055e-15
1140.9999999999999976.68321817654467e-153.34160908827234e-15
11517.45499100908792e-163.72749550454396e-16
11618.80685948614233e-174.40342974307116e-17
11719.1836893364025e-184.59184466820125e-18
11812.06336807151548e-181.03168403575774e-18
11912.54533674522349e-191.27266837261174e-19
12015.31665543859097e-212.65832771929548e-21
12111.0468610125209e-215.2343050626045e-22
12212.42734964875655e-221.21367482437828e-22
12316.64311476340493e-233.32155738170247e-23
12412.5671189379896e-231.2835594689948e-23
12517.4516867903e-243.72584339515e-24
12614.07913511083245e-242.03956755541623e-24
12712.00355353241414e-241.00177676620707e-24
12811.08291385645351e-245.41456928226756e-25
12912.5711976925677e-251.28559884628385e-25
13013.61121486339497e-261.80560743169749e-26
13118.25882973140404e-274.12941486570202e-27
13219.0227881030398e-284.5113940515199e-28
13312.57086605265084e-281.28543302632542e-28
13416.27846784161761e-293.13923392080881e-29
13512.13489888879702e-291.06744944439851e-29
13611.92240252223203e-299.61201261116016e-30
13718.88152265267611e-304.44076132633806e-30
13813.55395546054912e-301.77697773027456e-30
13911.57322512987554e-307.86612564937772e-31
14017.0361968570965e-313.51809842854825e-31
14112.196836180772e-311.098418090386e-31
14216.73356054126683e-323.36678027063341e-32
14312.43190930595008e-321.21595465297504e-32
14417.42790954609629e-333.71395477304815e-33
14515.79628528001305e-332.89814264000652e-33
14614.69383791322202e-332.34691895661101e-33
14711.0047472469728e-325.02373623486402e-33
14812.16755699971721e-321.0837784998586e-32
14912.90969184330239e-321.4548459216512e-32
15016.76252094954243e-323.38126047477121e-32
15111.81947113058368e-319.09735565291838e-32
15213.30495756121582e-311.65247878060791e-31
15315.19397054102973e-312.59698527051487e-31
15411.27352159220445e-306.36760796102224e-31
15513.77661323723665e-301.88830661861833e-30
15612.30059737283607e-311.15029868641803e-31
15719.2777994710535e-314.63889973552675e-31
15813.88492690362132e-301.94246345181066e-30
15911.68885525935239e-298.44427629676196e-30
16015.320782324996e-292.660391162498e-29
16111.38772801963412e-286.93864009817061e-29
16214.6435076564871e-282.32175382824355e-28
16311.1544497942422e-275.77224897121099e-28
16412.18993432592597e-271.09496716296298e-27
16512.93538997807206e-271.46769498903603e-27
16614.09825651909349e-272.04912825954674e-27
16713.55000444925382e-271.77500222462691e-27
16811.37977060585974e-276.89885302929872e-28
16913.76269094099137e-271.88134547049568e-27
17011.4571453593777e-267.28572679688852e-27
17115.73245234319575e-262.86622617159788e-26
17211.47100939082504e-257.35504695412518e-26
17315.41101603287011e-252.70550801643505e-25
17412.52626829726673e-241.26313414863337e-24
17511.13073808351959e-235.65369041759793e-24
17614.61754388008215e-232.30877194004108e-23
17712.0981887551325e-221.04909437756625e-22
17818.30757897245316e-224.15378948622658e-22
17913.37388196991793e-211.68694098495897e-21
18019.89400356304722e-244.94700178152361e-24
18115.4280859658195e-232.71404298290975e-23
18212.93489101950486e-221.46744550975243e-22
18311.596933187193e-217.98466593596502e-22
18412.89981087397788e-211.44990543698894e-21
18511.97314595924037e-209.86572979620184e-21
18611.18197534046638e-195.9098767023319e-20
18718.0665913970733e-194.03329569853665e-19
18815.40223044059402e-182.70111522029701e-18
18913.64196616420125e-171.82098308210062e-17
19012.79713112165446e-161.39856556082723e-16
1910.9999999999999992.19856343693077e-151.09928171846538e-15
19213.31490062394433e-161.65745031197216e-16
1930.9999999999999992.72010906947575e-151.36005453473788e-15
1940.9999999999999892.24973109566673e-141.12486554783337e-14
1950.9999999999999131.74344134368563e-138.71720671842813e-14
1960.9999999999992761.44715959540582e-127.23579797702911e-13
1970.9999999999947971.04060420895857e-115.20302104479283e-12
1980.9999999999553668.92684653033057e-114.46342326516529e-11
1990.9999999996333867.33227937383966e-103.66613968691983e-10
2000.9999999975113624.97727635000438e-092.48863817500219e-09
2010.9999999854960962.90078082947871e-081.45039041473936e-08
2020.9999999190304971.6193900551732e-078.09695027586602e-08
2030.999999806617313.86765379182889e-071.93382689591444e-07
2040.9999999841355573.17288858334399e-081.586444291672e-08
2050.999999756436844.87126318980227e-072.43563159490114e-07
2060.9999962144248197.5711503623028e-063.7855751811514e-06
2070.999940667922090.0001186641558213225.9332077910661e-05
2080.9999775606684424.48786631150407e-052.24393315575204e-05






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1930.955445544554455NOK
5% type I error level1950.965346534653465NOK
10% type I error level1960.97029702970297NOK

\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 & 193 & 0.955445544554455 & NOK \tabularnewline
5% type I error level & 195 & 0.965346534653465 & NOK \tabularnewline
10% type I error level & 196 & 0.97029702970297 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116970&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]193[/C][C]0.955445544554455[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]195[/C][C]0.965346534653465[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]196[/C][C]0.97029702970297[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116970&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116970&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1930.955445544554455NOK
5% type I error level1950.965346534653465NOK
10% type I error level1960.97029702970297NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 3
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

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