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Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareMultiple Regression
Date of computationTue, 29 Nov 2011 09:59:15 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/29/t13225789658ueph7398ylcd2f.htm/, Retrieved Fri, 29 Mar 2024 09:28:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148475, Retrieved Fri, 29 Mar 2024 09:28:11 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Q1 The Seatbeltlaw] [2007-11-14 19:27:43] [8cd6641b921d30ebe00b648d1481bba0]
- RMPD  [Multiple Regression] [Seatbelt] [2009-11-12 13:54:52] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [Aantal reizigers ...] [2010-11-26 01:03:33] [97ad38b1c3b35a5feca8b85f7bc7b3ff]
- RMP         [Multiple Regression] [] [2011-11-29 14:59:15] [f15d0acd791188344a5291b640d5aaed] [Current]
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Dataseries X:
1149822
1086979
1276674
1522522
1742117
1737275
1979900
2061036
1867943
1707752
1298756
1281814
1281151
1164976
1454329
1645288
1817743
1895785
2236311
2295951
2087315
1980891
1465446
1445026
1488120
1338333
1715789
1806090
2083316
2092278
2430800
2424894
2299016
2130688
1652221
1608162
1647074
1479691
1884978
2007898
2208954
2217164
2534291
2560312
2429069
2315077
1799608
1772590
1744799
1659093
2099821
2135736
2427894
2468882
2703217
2766841
2655236
2550373
2052097
1998055
1920748
1876694
2380930
2467402
2770771
2781340
3143926
3172235
2952540
2920877
2384552
2248987
2208616
2178756
2632870
2706905
3029745
3015402
3391414
3507805
3177852
3142961
2545815
2414007
2372578
2332664
2825328
2901478
3263955
3226738
3610786
3709274
3467185
3449646
2802951
2462530
2490645
2561520
3067554
3226951
3546493
3492787
3952263
3932072
3720284
3651555
2914972
2713514
2703997
2591373
3163748
3355137
3613702
3686773
4098716
4063517
3551489
3226663
2656842
2597484
2572399
2596631
3165225
3303145
3698247
3668631
4130433
4131400
3864358
3721110
2892532
2843451
2747502
2668775
3018602
3013392
3393657
3544233
4075832
4032923
3734509
3761285
2970090
2847849
2741680
2830639
3257673
3480085
3843271
3796961
4337767
4243630
3927202
3915296
3087396
2963792
2955792
2829925
3281195
3548011
4059648
3941175
4528594
4433151
4145737
4077132
3198519
3078660
3028202
2858642
3398954
3808883
4175961
4227542
4744616
4608012
4295049
4201144
3353276
3286851
3169889
3051720
3695426
3905501
4296458
4246247
4921849
4821446
4425064
4379099
3472889
3359160
3200944
3153170
3741498
3918719
4403449
4400407
4847473
4716136
4297440
4272253
3271834
3168388
2911748
2720999
3199918
3672623
3892013
3850845
4532467
4484739
4014972
3983758
3158459
3100569
2935404
2855719
3465611
3006985
4095110
4104793
4730788
4642726
4246919
4308117




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 7 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148475&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148475&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148475&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Yt[t] = + 2510604.94444444 -127914.944444444M1[t] -203431.312865497M2[t] + 264454.160818713M3[t] + 406908.266081871M4[t] + 771632.108187134M5[t] + 773356.002923977M6[t] + 1222628.89766082M7[t] + 1205610.84502924M8[t] + 918825.529239766M9[t] + 841799.108187134M10[t] + 99298.1111111111M11[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Yt[t] =  +  2510604.94444444 -127914.944444444M1[t] -203431.312865497M2[t] +  264454.160818713M3[t] +  406908.266081871M4[t] +  771632.108187134M5[t] +  773356.002923977M6[t] +  1222628.89766082M7[t] +  1205610.84502924M8[t] +  918825.529239766M9[t] +  841799.108187134M10[t] +  99298.1111111111M11[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148475&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Yt[t] =  +  2510604.94444444 -127914.944444444M1[t] -203431.312865497M2[t] +  264454.160818713M3[t] +  406908.266081871M4[t] +  771632.108187134M5[t] +  773356.002923977M6[t] +  1222628.89766082M7[t] +  1205610.84502924M8[t] +  918825.529239766M9[t] +  841799.108187134M10[t] +  99298.1111111111M11[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148475&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148475&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
Yt[t] = + 2510604.94444444 -127914.944444444M1[t] -203431.312865497M2[t] + 264454.160818713M3[t] + 406908.266081871M4[t] + 771632.108187134M5[t] + 773356.002923977M6[t] + 1222628.89766082M7[t] + 1205610.84502924M8[t] + 918825.529239766M9[t] + 841799.108187134M10[t] + 99298.1111111111M11[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2510604.94444444187597.13206713.38300
M1-127914.944444444261788.314092-0.48860.6256110.312806
M2-203431.312865497261788.314092-0.77710.4379680.218984
M3264454.160818713261788.3140921.01020.3135480.156774
M4406908.266081871261788.3140921.55430.1215810.06079
M5771632.108187134261788.3140922.94750.0035580.001779
M6773356.002923977261788.3140922.95410.0034860.001743
M71222628.89766082261788.3140924.67035e-063e-06
M81205610.84502924261788.3140924.60537e-064e-06
M9918825.529239766261788.3140923.50980.0005470.000273
M10841799.108187134261788.3140923.21560.0015030.000752
M1199298.1111111111265302.4084310.37430.7085650.354282

\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) & 2510604.94444444 & 187597.132067 & 13.383 & 0 & 0 \tabularnewline
M1 & -127914.944444444 & 261788.314092 & -0.4886 & 0.625611 & 0.312806 \tabularnewline
M2 & -203431.312865497 & 261788.314092 & -0.7771 & 0.437968 & 0.218984 \tabularnewline
M3 & 264454.160818713 & 261788.314092 & 1.0102 & 0.313548 & 0.156774 \tabularnewline
M4 & 406908.266081871 & 261788.314092 & 1.5543 & 0.121581 & 0.06079 \tabularnewline
M5 & 771632.108187134 & 261788.314092 & 2.9475 & 0.003558 & 0.001779 \tabularnewline
M6 & 773356.002923977 & 261788.314092 & 2.9541 & 0.003486 & 0.001743 \tabularnewline
M7 & 1222628.89766082 & 261788.314092 & 4.6703 & 5e-06 & 3e-06 \tabularnewline
M8 & 1205610.84502924 & 261788.314092 & 4.6053 & 7e-06 & 4e-06 \tabularnewline
M9 & 918825.529239766 & 261788.314092 & 3.5098 & 0.000547 & 0.000273 \tabularnewline
M10 & 841799.108187134 & 261788.314092 & 3.2156 & 0.001503 & 0.000752 \tabularnewline
M11 & 99298.1111111111 & 265302.408431 & 0.3743 & 0.708565 & 0.354282 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148475&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]2510604.94444444[/C][C]187597.132067[/C][C]13.383[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]M1[/C][C]-127914.944444444[/C][C]261788.314092[/C][C]-0.4886[/C][C]0.625611[/C][C]0.312806[/C][/ROW]
[ROW][C]M2[/C][C]-203431.312865497[/C][C]261788.314092[/C][C]-0.7771[/C][C]0.437968[/C][C]0.218984[/C][/ROW]
[ROW][C]M3[/C][C]264454.160818713[/C][C]261788.314092[/C][C]1.0102[/C][C]0.313548[/C][C]0.156774[/C][/ROW]
[ROW][C]M4[/C][C]406908.266081871[/C][C]261788.314092[/C][C]1.5543[/C][C]0.121581[/C][C]0.06079[/C][/ROW]
[ROW][C]M5[/C][C]771632.108187134[/C][C]261788.314092[/C][C]2.9475[/C][C]0.003558[/C][C]0.001779[/C][/ROW]
[ROW][C]M6[/C][C]773356.002923977[/C][C]261788.314092[/C][C]2.9541[/C][C]0.003486[/C][C]0.001743[/C][/ROW]
[ROW][C]M7[/C][C]1222628.89766082[/C][C]261788.314092[/C][C]4.6703[/C][C]5e-06[/C][C]3e-06[/C][/ROW]
[ROW][C]M8[/C][C]1205610.84502924[/C][C]261788.314092[/C][C]4.6053[/C][C]7e-06[/C][C]4e-06[/C][/ROW]
[ROW][C]M9[/C][C]918825.529239766[/C][C]261788.314092[/C][C]3.5098[/C][C]0.000547[/C][C]0.000273[/C][/ROW]
[ROW][C]M10[/C][C]841799.108187134[/C][C]261788.314092[/C][C]3.2156[/C][C]0.001503[/C][C]0.000752[/C][/ROW]
[ROW][C]M11[/C][C]99298.1111111111[/C][C]265302.408431[/C][C]0.3743[/C][C]0.708565[/C][C]0.354282[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148475&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148475&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2510604.94444444187597.13206713.38300
M1-127914.944444444261788.314092-0.48860.6256110.312806
M2-203431.312865497261788.314092-0.77710.4379680.218984
M3264454.160818713261788.3140921.01020.3135480.156774
M4406908.266081871261788.3140921.55430.1215810.06079
M5771632.108187134261788.3140922.94750.0035580.001779
M6773356.002923977261788.3140922.95410.0034860.001743
M71222628.89766082261788.3140924.67035e-063e-06
M81205610.84502924261788.3140924.60537e-064e-06
M9918825.529239766261788.3140923.50980.0005470.000273
M10841799.108187134261788.3140923.21560.0015030.000752
M1199298.1111111111265302.4084310.37430.7085650.354282







Multiple Linear Regression - Regression Statistics
Multiple R0.530809624094231
R-squared0.281758857031059
Adjusted R-squared0.244839919775646
F-TEST (value)7.63182469424277
F-TEST (DF numerator)11
F-TEST (DF denominator)214
p-value4.52526904837214e-11
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation795907.225293862
Sum Squared Residuals135562218612844

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.530809624094231 \tabularnewline
R-squared & 0.281758857031059 \tabularnewline
Adjusted R-squared & 0.244839919775646 \tabularnewline
F-TEST (value) & 7.63182469424277 \tabularnewline
F-TEST (DF numerator) & 11 \tabularnewline
F-TEST (DF denominator) & 214 \tabularnewline
p-value & 4.52526904837214e-11 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 795907.225293862 \tabularnewline
Sum Squared Residuals & 135562218612844 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148475&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.530809624094231[/C][/ROW]
[ROW][C]R-squared[/C][C]0.281758857031059[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.244839919775646[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]7.63182469424277[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]11[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]214[/C][/ROW]
[ROW][C]p-value[/C][C]4.52526904837214e-11[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]795907.225293862[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]135562218612844[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148475&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148475&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.530809624094231
R-squared0.281758857031059
Adjusted R-squared0.244839919775646
F-TEST (value)7.63182469424277
F-TEST (DF numerator)11
F-TEST (DF denominator)214
p-value4.52526904837214e-11
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation795907.225293862
Sum Squared Residuals135562218612844







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
111498222382690-1232868
210869792307173.63157895-1220194.63157895
312766742775059.10526316-1498385.10526316
415225222917513.21052632-1394991.21052632
517421173282237.05263158-1540120.05263158
617372753283960.94736842-1546685.94736842
719799003733233.84210526-1753333.84210526
820610363716215.78947369-1655179.78947369
918679433429430.47368421-1561487.47368421
1017077523352404.05263158-1644652.05263158
1112987562609903.05555556-1311147.05555556
1212818142510604.94444444-1228790.94444444
1312811512382690-1101539
1411649762307173.63157895-1142197.63157895
1514543292775059.10526316-1320730.10526316
1616452882917513.21052632-1272225.21052632
1718177433282237.05263158-1464494.05263158
1818957853283960.94736842-1388175.94736842
1922363113733233.84210526-1496922.84210526
2022959513716215.78947368-1420264.78947368
2120873153429430.47368421-1342115.47368421
2219808913352404.05263158-1371513.05263158
2314654462609903.05555556-1144457.05555556
2414450262510604.94444444-1065578.94444444
2514881202382690-894570
2613383332307173.63157895-968840.631578948
2717157892775059.10526316-1059270.10526316
2818060902917513.21052632-1111423.21052632
2920833163282237.05263158-1198921.05263158
3020922783283960.94736842-1191682.94736842
3124308003733233.84210526-1302433.84210526
3224248943716215.78947368-1291321.78947368
3322990163429430.47368421-1130414.47368421
3421306883352404.05263158-1221716.05263158
3516522212609903.05555556-957682.055555556
3616081622510604.94444444-902442.944444444
3716470742382690-735616.000000001
3814796912307173.63157895-827482.631578948
3918849782775059.10526316-890081.105263157
4020078982917513.21052632-909615.210526316
4122089543282237.05263158-1073283.05263158
4222171643283960.94736842-1066796.94736842
4325342913733233.84210526-1198942.84210526
4425603123716215.78947368-1155903.78947368
4524290693429430.47368421-1000361.47368421
4623150773352404.05263158-1037327.05263158
4717996082609903.05555556-810295.055555556
4817725902510604.94444444-738014.944444444
4917447992382690-637891.000000001
5016590932307173.63157895-648080.631578947
5120998212775059.10526316-675238.105263158
5221357362917513.21052632-781777.210526316
5324278943282237.05263158-854343.052631579
5424688823283960.94736842-815078.947368421
5527032173733233.84210526-1030016.84210526
5627668413716215.78947368-949374.789473684
5726552363429430.47368421-774194.473684211
5825503733352404.05263158-802031.052631579
5920520972609903.05555556-557806.055555556
6019980552510604.94444444-512549.944444445
6119207482382690-461942.000000001
6218766942307173.63157895-430479.631578947
6323809302775059.10526316-394129.105263158
6424674022917513.21052632-450111.210526316
6527707713282237.05263158-511466.052631579
6627813403283960.94736842-502620.947368421
6731439263733233.84210526-589307.842105263
6831722353716215.78947368-543980.789473684
6929525403429430.47368421-476890.473684211
7029208773352404.05263158-431527.052631579
7123845522609903.05555556-225351.055555556
7222489872510604.94444444-261617.944444445
7322086162382690-174074
7421787562307173.63157895-128417.631578947
7526328702775059.10526316-142189.105263158
7627069052917513.21052632-210608.210526316
7730297453282237.05263158-252492.052631579
7830154023283960.94736842-268558.947368421
7933914143733233.84210526-341819.842105263
8035078053716215.78947368-208410.789473684
8131778523429430.47368421-251578.47368421
8231429613352404.05263158-209443.052631579
8325458152609903.05555556-64088.0555555554
8424140072510604.94444444-96597.9444444445
8523725782382690-10112.0000000004
8623326642307173.6315789525490.3684210526
8728253282775059.1052631650268.8947368421
8829014782917513.21052632-16035.2105263159
8932639553282237.05263158-18282.052631579
9032267383283960.94736842-57222.947368421
9136107863733233.84210526-122447.842105263
9237092743716215.78947368-6941.78947368442
9334671853429430.4736842137754.5263157894
9434496463352404.0526315897241.9473684208
9528029512609903.05555556193047.944444444
9624625302510604.94444444-48074.9444444444
9724906452382690107955
9825615202307173.63157895254346.368421053
9930675542775059.10526316292494.894736842
10032269512917513.21052632309437.789473684
10135464933282237.05263158264255.947368421
10234927873283960.94736842208826.052631579
10339522633733233.84210526219029.157894737
10439320723716215.78947368215856.210526316
10537202843429430.47368421290853.526315789
10636515553352404.05263158299150.947368421
10729149722609903.05555556305068.944444444
10827135142510604.94444444202909.055555555
10927039972382690321307
11025913732307173.63157895284199.368421053
11131637482775059.10526316388688.894736842
11233551372917513.21052632437623.789473684
11336137023282237.05263158331464.947368421
11436867733283960.94736842402812.052631579
11540987163733233.84210526365482.157894737
11640635173716215.78947368347301.210526316
11735514893429430.47368421122058.526315789
11832266633352404.05263158-125741.052631579
11926568422609903.0555555646938.9444444444
12025974842510604.9444444486879.0555555554
12125723992382690189709
12225966312307173.63157895289457.368421053
12331652252775059.10526316390165.894736842
12433031452917513.21052632385631.789473684
12536982473282237.05263158416009.947368421
12636686313283960.94736842384670.052631579
12741304333733233.84210526397199.157894737
12841314003716215.78947368415184.210526316
12938643583429430.47368421434927.526315789
13037211103352404.05263158368705.947368421
13128925322609903.05555556282628.944444444
13228434512510604.94444444332846.055555556
13327475022382690364812
13426687752307173.63157895361601.368421053
13530186022775059.10526316243542.894736842
13630133922917513.2105263295878.7894736841
13733936573282237.05263158111419.947368421
13835442333283960.94736842260272.052631579
13940758323733233.84210526342598.157894737
14040329233716215.78947368316707.210526316
14137345093429430.47368421305078.526315789
14237612853352404.05263158408880.947368421
14329700902609903.05555556360186.944444444
14428478492510604.94444444337244.055555556
14527416802382690358990
14628306392307173.63157895523465.368421053
14732576732775059.10526316482613.894736842
14834800852917513.21052632562571.789473684
14938432713282237.05263158561033.947368421
15037969613283960.94736842513000.052631579
15143377673733233.84210526604533.157894737
15242436303716215.78947368527414.210526316
15339272023429430.47368421497771.526315789
15439152963352404.05263158562891.947368421
15530873962609903.05555556477492.944444444
15629637922510604.94444444453187.055555555
15729557922382690573102
15828299252307173.63157895522751.368421053
15932811952775059.10526316506135.894736842
16035480112917513.21052632630497.789473684
16140596483282237.05263158777410.947368421
16239411753283960.94736842657214.052631579
16345285943733233.84210526795360.157894737
16444331513716215.78947368716935.210526316
16541457373429430.47368421716306.52631579
16640771323352404.05263158724727.947368421
16731985192609903.05555556588615.944444444
16830786602510604.94444444568055.055555556
16930282022382690645512
17028586422307173.63157895551468.368421053
17133989542775059.10526316623894.894736842
17238088832917513.21052632891369.789473684
17341759613282237.05263158893723.947368421
17442275423283960.94736842943581.052631579
17547446163733233.842105261011382.15789474
17646080123716215.78947368891796.210526316
17742950493429430.47368421865618.52631579
17842011443352404.05263158848739.947368421
17933532762609903.05555556743372.944444444
18032868512510604.94444444776246.055555556
18131698892382690787198.999999999
18230517202307173.63157895744546.368421053
18336954262775059.10526316920366.894736842
18439055012917513.21052632987987.789473684
18542964583282237.052631581014220.94736842
18642462473283960.94736842962286.052631579
18749218493733233.842105261188615.15789474
18848214463716215.789473681105230.21052632
18944250643429430.47368421995633.52631579
19043790993352404.052631581026694.94736842
19134728892609903.05555556862985.944444444
19233591602510604.94444444848555.055555556
19332009442382690818253.999999999
19431531702307173.63157895845996.368421053
19537414982775059.10526316966438.894736842
19639187192917513.210526321001205.78947368
19744034493282237.052631581121211.94736842
19844004073283960.947368421116446.05263158
19948474733733233.842105261114239.15789474
20047161363716215.78947368999920.210526316
20142974403429430.47368421868009.52631579
20242722533352404.05263158919848.947368421
20332718342609903.05555556661930.944444444
20431683882510604.94444444657783.055555556
20529117482382690529058
20627209992307173.63157895413825.368421053
20731999182775059.10526316424858.894736842
20836726232917513.21052632755109.789473684
20938920133282237.05263158609775.947368421
21038508453283960.94736842566884.052631579
21145324673733233.84210526799233.157894737
21244847393716215.78947368768523.210526316
21340149723429430.47368421585541.52631579
21439837583352404.05263158631353.947368421
21531584592609903.05555556548555.944444444
21631005692510604.94444444589964.055555556
21729354042382690552714
21828557192307173.63157895548545.368421053
21934656112775059.10526316690551.894736842
22030069852917513.2105263289471.7894736841
22140951103282237.05263158812872.947368421
22241047933283960.94736842820832.052631579
22347307883733233.84210526997554.157894737
22446427263716215.78947368926510.210526316
22542469193429430.47368421817488.52631579
22643081173352404.05263158955712.947368421

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1149822 & 2382690 & -1232868 \tabularnewline
2 & 1086979 & 2307173.63157895 & -1220194.63157895 \tabularnewline
3 & 1276674 & 2775059.10526316 & -1498385.10526316 \tabularnewline
4 & 1522522 & 2917513.21052632 & -1394991.21052632 \tabularnewline
5 & 1742117 & 3282237.05263158 & -1540120.05263158 \tabularnewline
6 & 1737275 & 3283960.94736842 & -1546685.94736842 \tabularnewline
7 & 1979900 & 3733233.84210526 & -1753333.84210526 \tabularnewline
8 & 2061036 & 3716215.78947369 & -1655179.78947369 \tabularnewline
9 & 1867943 & 3429430.47368421 & -1561487.47368421 \tabularnewline
10 & 1707752 & 3352404.05263158 & -1644652.05263158 \tabularnewline
11 & 1298756 & 2609903.05555556 & -1311147.05555556 \tabularnewline
12 & 1281814 & 2510604.94444444 & -1228790.94444444 \tabularnewline
13 & 1281151 & 2382690 & -1101539 \tabularnewline
14 & 1164976 & 2307173.63157895 & -1142197.63157895 \tabularnewline
15 & 1454329 & 2775059.10526316 & -1320730.10526316 \tabularnewline
16 & 1645288 & 2917513.21052632 & -1272225.21052632 \tabularnewline
17 & 1817743 & 3282237.05263158 & -1464494.05263158 \tabularnewline
18 & 1895785 & 3283960.94736842 & -1388175.94736842 \tabularnewline
19 & 2236311 & 3733233.84210526 & -1496922.84210526 \tabularnewline
20 & 2295951 & 3716215.78947368 & -1420264.78947368 \tabularnewline
21 & 2087315 & 3429430.47368421 & -1342115.47368421 \tabularnewline
22 & 1980891 & 3352404.05263158 & -1371513.05263158 \tabularnewline
23 & 1465446 & 2609903.05555556 & -1144457.05555556 \tabularnewline
24 & 1445026 & 2510604.94444444 & -1065578.94444444 \tabularnewline
25 & 1488120 & 2382690 & -894570 \tabularnewline
26 & 1338333 & 2307173.63157895 & -968840.631578948 \tabularnewline
27 & 1715789 & 2775059.10526316 & -1059270.10526316 \tabularnewline
28 & 1806090 & 2917513.21052632 & -1111423.21052632 \tabularnewline
29 & 2083316 & 3282237.05263158 & -1198921.05263158 \tabularnewline
30 & 2092278 & 3283960.94736842 & -1191682.94736842 \tabularnewline
31 & 2430800 & 3733233.84210526 & -1302433.84210526 \tabularnewline
32 & 2424894 & 3716215.78947368 & -1291321.78947368 \tabularnewline
33 & 2299016 & 3429430.47368421 & -1130414.47368421 \tabularnewline
34 & 2130688 & 3352404.05263158 & -1221716.05263158 \tabularnewline
35 & 1652221 & 2609903.05555556 & -957682.055555556 \tabularnewline
36 & 1608162 & 2510604.94444444 & -902442.944444444 \tabularnewline
37 & 1647074 & 2382690 & -735616.000000001 \tabularnewline
38 & 1479691 & 2307173.63157895 & -827482.631578948 \tabularnewline
39 & 1884978 & 2775059.10526316 & -890081.105263157 \tabularnewline
40 & 2007898 & 2917513.21052632 & -909615.210526316 \tabularnewline
41 & 2208954 & 3282237.05263158 & -1073283.05263158 \tabularnewline
42 & 2217164 & 3283960.94736842 & -1066796.94736842 \tabularnewline
43 & 2534291 & 3733233.84210526 & -1198942.84210526 \tabularnewline
44 & 2560312 & 3716215.78947368 & -1155903.78947368 \tabularnewline
45 & 2429069 & 3429430.47368421 & -1000361.47368421 \tabularnewline
46 & 2315077 & 3352404.05263158 & -1037327.05263158 \tabularnewline
47 & 1799608 & 2609903.05555556 & -810295.055555556 \tabularnewline
48 & 1772590 & 2510604.94444444 & -738014.944444444 \tabularnewline
49 & 1744799 & 2382690 & -637891.000000001 \tabularnewline
50 & 1659093 & 2307173.63157895 & -648080.631578947 \tabularnewline
51 & 2099821 & 2775059.10526316 & -675238.105263158 \tabularnewline
52 & 2135736 & 2917513.21052632 & -781777.210526316 \tabularnewline
53 & 2427894 & 3282237.05263158 & -854343.052631579 \tabularnewline
54 & 2468882 & 3283960.94736842 & -815078.947368421 \tabularnewline
55 & 2703217 & 3733233.84210526 & -1030016.84210526 \tabularnewline
56 & 2766841 & 3716215.78947368 & -949374.789473684 \tabularnewline
57 & 2655236 & 3429430.47368421 & -774194.473684211 \tabularnewline
58 & 2550373 & 3352404.05263158 & -802031.052631579 \tabularnewline
59 & 2052097 & 2609903.05555556 & -557806.055555556 \tabularnewline
60 & 1998055 & 2510604.94444444 & -512549.944444445 \tabularnewline
61 & 1920748 & 2382690 & -461942.000000001 \tabularnewline
62 & 1876694 & 2307173.63157895 & -430479.631578947 \tabularnewline
63 & 2380930 & 2775059.10526316 & -394129.105263158 \tabularnewline
64 & 2467402 & 2917513.21052632 & -450111.210526316 \tabularnewline
65 & 2770771 & 3282237.05263158 & -511466.052631579 \tabularnewline
66 & 2781340 & 3283960.94736842 & -502620.947368421 \tabularnewline
67 & 3143926 & 3733233.84210526 & -589307.842105263 \tabularnewline
68 & 3172235 & 3716215.78947368 & -543980.789473684 \tabularnewline
69 & 2952540 & 3429430.47368421 & -476890.473684211 \tabularnewline
70 & 2920877 & 3352404.05263158 & -431527.052631579 \tabularnewline
71 & 2384552 & 2609903.05555556 & -225351.055555556 \tabularnewline
72 & 2248987 & 2510604.94444444 & -261617.944444445 \tabularnewline
73 & 2208616 & 2382690 & -174074 \tabularnewline
74 & 2178756 & 2307173.63157895 & -128417.631578947 \tabularnewline
75 & 2632870 & 2775059.10526316 & -142189.105263158 \tabularnewline
76 & 2706905 & 2917513.21052632 & -210608.210526316 \tabularnewline
77 & 3029745 & 3282237.05263158 & -252492.052631579 \tabularnewline
78 & 3015402 & 3283960.94736842 & -268558.947368421 \tabularnewline
79 & 3391414 & 3733233.84210526 & -341819.842105263 \tabularnewline
80 & 3507805 & 3716215.78947368 & -208410.789473684 \tabularnewline
81 & 3177852 & 3429430.47368421 & -251578.47368421 \tabularnewline
82 & 3142961 & 3352404.05263158 & -209443.052631579 \tabularnewline
83 & 2545815 & 2609903.05555556 & -64088.0555555554 \tabularnewline
84 & 2414007 & 2510604.94444444 & -96597.9444444445 \tabularnewline
85 & 2372578 & 2382690 & -10112.0000000004 \tabularnewline
86 & 2332664 & 2307173.63157895 & 25490.3684210526 \tabularnewline
87 & 2825328 & 2775059.10526316 & 50268.8947368421 \tabularnewline
88 & 2901478 & 2917513.21052632 & -16035.2105263159 \tabularnewline
89 & 3263955 & 3282237.05263158 & -18282.052631579 \tabularnewline
90 & 3226738 & 3283960.94736842 & -57222.947368421 \tabularnewline
91 & 3610786 & 3733233.84210526 & -122447.842105263 \tabularnewline
92 & 3709274 & 3716215.78947368 & -6941.78947368442 \tabularnewline
93 & 3467185 & 3429430.47368421 & 37754.5263157894 \tabularnewline
94 & 3449646 & 3352404.05263158 & 97241.9473684208 \tabularnewline
95 & 2802951 & 2609903.05555556 & 193047.944444444 \tabularnewline
96 & 2462530 & 2510604.94444444 & -48074.9444444444 \tabularnewline
97 & 2490645 & 2382690 & 107955 \tabularnewline
98 & 2561520 & 2307173.63157895 & 254346.368421053 \tabularnewline
99 & 3067554 & 2775059.10526316 & 292494.894736842 \tabularnewline
100 & 3226951 & 2917513.21052632 & 309437.789473684 \tabularnewline
101 & 3546493 & 3282237.05263158 & 264255.947368421 \tabularnewline
102 & 3492787 & 3283960.94736842 & 208826.052631579 \tabularnewline
103 & 3952263 & 3733233.84210526 & 219029.157894737 \tabularnewline
104 & 3932072 & 3716215.78947368 & 215856.210526316 \tabularnewline
105 & 3720284 & 3429430.47368421 & 290853.526315789 \tabularnewline
106 & 3651555 & 3352404.05263158 & 299150.947368421 \tabularnewline
107 & 2914972 & 2609903.05555556 & 305068.944444444 \tabularnewline
108 & 2713514 & 2510604.94444444 & 202909.055555555 \tabularnewline
109 & 2703997 & 2382690 & 321307 \tabularnewline
110 & 2591373 & 2307173.63157895 & 284199.368421053 \tabularnewline
111 & 3163748 & 2775059.10526316 & 388688.894736842 \tabularnewline
112 & 3355137 & 2917513.21052632 & 437623.789473684 \tabularnewline
113 & 3613702 & 3282237.05263158 & 331464.947368421 \tabularnewline
114 & 3686773 & 3283960.94736842 & 402812.052631579 \tabularnewline
115 & 4098716 & 3733233.84210526 & 365482.157894737 \tabularnewline
116 & 4063517 & 3716215.78947368 & 347301.210526316 \tabularnewline
117 & 3551489 & 3429430.47368421 & 122058.526315789 \tabularnewline
118 & 3226663 & 3352404.05263158 & -125741.052631579 \tabularnewline
119 & 2656842 & 2609903.05555556 & 46938.9444444444 \tabularnewline
120 & 2597484 & 2510604.94444444 & 86879.0555555554 \tabularnewline
121 & 2572399 & 2382690 & 189709 \tabularnewline
122 & 2596631 & 2307173.63157895 & 289457.368421053 \tabularnewline
123 & 3165225 & 2775059.10526316 & 390165.894736842 \tabularnewline
124 & 3303145 & 2917513.21052632 & 385631.789473684 \tabularnewline
125 & 3698247 & 3282237.05263158 & 416009.947368421 \tabularnewline
126 & 3668631 & 3283960.94736842 & 384670.052631579 \tabularnewline
127 & 4130433 & 3733233.84210526 & 397199.157894737 \tabularnewline
128 & 4131400 & 3716215.78947368 & 415184.210526316 \tabularnewline
129 & 3864358 & 3429430.47368421 & 434927.526315789 \tabularnewline
130 & 3721110 & 3352404.05263158 & 368705.947368421 \tabularnewline
131 & 2892532 & 2609903.05555556 & 282628.944444444 \tabularnewline
132 & 2843451 & 2510604.94444444 & 332846.055555556 \tabularnewline
133 & 2747502 & 2382690 & 364812 \tabularnewline
134 & 2668775 & 2307173.63157895 & 361601.368421053 \tabularnewline
135 & 3018602 & 2775059.10526316 & 243542.894736842 \tabularnewline
136 & 3013392 & 2917513.21052632 & 95878.7894736841 \tabularnewline
137 & 3393657 & 3282237.05263158 & 111419.947368421 \tabularnewline
138 & 3544233 & 3283960.94736842 & 260272.052631579 \tabularnewline
139 & 4075832 & 3733233.84210526 & 342598.157894737 \tabularnewline
140 & 4032923 & 3716215.78947368 & 316707.210526316 \tabularnewline
141 & 3734509 & 3429430.47368421 & 305078.526315789 \tabularnewline
142 & 3761285 & 3352404.05263158 & 408880.947368421 \tabularnewline
143 & 2970090 & 2609903.05555556 & 360186.944444444 \tabularnewline
144 & 2847849 & 2510604.94444444 & 337244.055555556 \tabularnewline
145 & 2741680 & 2382690 & 358990 \tabularnewline
146 & 2830639 & 2307173.63157895 & 523465.368421053 \tabularnewline
147 & 3257673 & 2775059.10526316 & 482613.894736842 \tabularnewline
148 & 3480085 & 2917513.21052632 & 562571.789473684 \tabularnewline
149 & 3843271 & 3282237.05263158 & 561033.947368421 \tabularnewline
150 & 3796961 & 3283960.94736842 & 513000.052631579 \tabularnewline
151 & 4337767 & 3733233.84210526 & 604533.157894737 \tabularnewline
152 & 4243630 & 3716215.78947368 & 527414.210526316 \tabularnewline
153 & 3927202 & 3429430.47368421 & 497771.526315789 \tabularnewline
154 & 3915296 & 3352404.05263158 & 562891.947368421 \tabularnewline
155 & 3087396 & 2609903.05555556 & 477492.944444444 \tabularnewline
156 & 2963792 & 2510604.94444444 & 453187.055555555 \tabularnewline
157 & 2955792 & 2382690 & 573102 \tabularnewline
158 & 2829925 & 2307173.63157895 & 522751.368421053 \tabularnewline
159 & 3281195 & 2775059.10526316 & 506135.894736842 \tabularnewline
160 & 3548011 & 2917513.21052632 & 630497.789473684 \tabularnewline
161 & 4059648 & 3282237.05263158 & 777410.947368421 \tabularnewline
162 & 3941175 & 3283960.94736842 & 657214.052631579 \tabularnewline
163 & 4528594 & 3733233.84210526 & 795360.157894737 \tabularnewline
164 & 4433151 & 3716215.78947368 & 716935.210526316 \tabularnewline
165 & 4145737 & 3429430.47368421 & 716306.52631579 \tabularnewline
166 & 4077132 & 3352404.05263158 & 724727.947368421 \tabularnewline
167 & 3198519 & 2609903.05555556 & 588615.944444444 \tabularnewline
168 & 3078660 & 2510604.94444444 & 568055.055555556 \tabularnewline
169 & 3028202 & 2382690 & 645512 \tabularnewline
170 & 2858642 & 2307173.63157895 & 551468.368421053 \tabularnewline
171 & 3398954 & 2775059.10526316 & 623894.894736842 \tabularnewline
172 & 3808883 & 2917513.21052632 & 891369.789473684 \tabularnewline
173 & 4175961 & 3282237.05263158 & 893723.947368421 \tabularnewline
174 & 4227542 & 3283960.94736842 & 943581.052631579 \tabularnewline
175 & 4744616 & 3733233.84210526 & 1011382.15789474 \tabularnewline
176 & 4608012 & 3716215.78947368 & 891796.210526316 \tabularnewline
177 & 4295049 & 3429430.47368421 & 865618.52631579 \tabularnewline
178 & 4201144 & 3352404.05263158 & 848739.947368421 \tabularnewline
179 & 3353276 & 2609903.05555556 & 743372.944444444 \tabularnewline
180 & 3286851 & 2510604.94444444 & 776246.055555556 \tabularnewline
181 & 3169889 & 2382690 & 787198.999999999 \tabularnewline
182 & 3051720 & 2307173.63157895 & 744546.368421053 \tabularnewline
183 & 3695426 & 2775059.10526316 & 920366.894736842 \tabularnewline
184 & 3905501 & 2917513.21052632 & 987987.789473684 \tabularnewline
185 & 4296458 & 3282237.05263158 & 1014220.94736842 \tabularnewline
186 & 4246247 & 3283960.94736842 & 962286.052631579 \tabularnewline
187 & 4921849 & 3733233.84210526 & 1188615.15789474 \tabularnewline
188 & 4821446 & 3716215.78947368 & 1105230.21052632 \tabularnewline
189 & 4425064 & 3429430.47368421 & 995633.52631579 \tabularnewline
190 & 4379099 & 3352404.05263158 & 1026694.94736842 \tabularnewline
191 & 3472889 & 2609903.05555556 & 862985.944444444 \tabularnewline
192 & 3359160 & 2510604.94444444 & 848555.055555556 \tabularnewline
193 & 3200944 & 2382690 & 818253.999999999 \tabularnewline
194 & 3153170 & 2307173.63157895 & 845996.368421053 \tabularnewline
195 & 3741498 & 2775059.10526316 & 966438.894736842 \tabularnewline
196 & 3918719 & 2917513.21052632 & 1001205.78947368 \tabularnewline
197 & 4403449 & 3282237.05263158 & 1121211.94736842 \tabularnewline
198 & 4400407 & 3283960.94736842 & 1116446.05263158 \tabularnewline
199 & 4847473 & 3733233.84210526 & 1114239.15789474 \tabularnewline
200 & 4716136 & 3716215.78947368 & 999920.210526316 \tabularnewline
201 & 4297440 & 3429430.47368421 & 868009.52631579 \tabularnewline
202 & 4272253 & 3352404.05263158 & 919848.947368421 \tabularnewline
203 & 3271834 & 2609903.05555556 & 661930.944444444 \tabularnewline
204 & 3168388 & 2510604.94444444 & 657783.055555556 \tabularnewline
205 & 2911748 & 2382690 & 529058 \tabularnewline
206 & 2720999 & 2307173.63157895 & 413825.368421053 \tabularnewline
207 & 3199918 & 2775059.10526316 & 424858.894736842 \tabularnewline
208 & 3672623 & 2917513.21052632 & 755109.789473684 \tabularnewline
209 & 3892013 & 3282237.05263158 & 609775.947368421 \tabularnewline
210 & 3850845 & 3283960.94736842 & 566884.052631579 \tabularnewline
211 & 4532467 & 3733233.84210526 & 799233.157894737 \tabularnewline
212 & 4484739 & 3716215.78947368 & 768523.210526316 \tabularnewline
213 & 4014972 & 3429430.47368421 & 585541.52631579 \tabularnewline
214 & 3983758 & 3352404.05263158 & 631353.947368421 \tabularnewline
215 & 3158459 & 2609903.05555556 & 548555.944444444 \tabularnewline
216 & 3100569 & 2510604.94444444 & 589964.055555556 \tabularnewline
217 & 2935404 & 2382690 & 552714 \tabularnewline
218 & 2855719 & 2307173.63157895 & 548545.368421053 \tabularnewline
219 & 3465611 & 2775059.10526316 & 690551.894736842 \tabularnewline
220 & 3006985 & 2917513.21052632 & 89471.7894736841 \tabularnewline
221 & 4095110 & 3282237.05263158 & 812872.947368421 \tabularnewline
222 & 4104793 & 3283960.94736842 & 820832.052631579 \tabularnewline
223 & 4730788 & 3733233.84210526 & 997554.157894737 \tabularnewline
224 & 4642726 & 3716215.78947368 & 926510.210526316 \tabularnewline
225 & 4246919 & 3429430.47368421 & 817488.52631579 \tabularnewline
226 & 4308117 & 3352404.05263158 & 955712.947368421 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148475&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]1149822[/C][C]2382690[/C][C]-1232868[/C][/ROW]
[ROW][C]2[/C][C]1086979[/C][C]2307173.63157895[/C][C]-1220194.63157895[/C][/ROW]
[ROW][C]3[/C][C]1276674[/C][C]2775059.10526316[/C][C]-1498385.10526316[/C][/ROW]
[ROW][C]4[/C][C]1522522[/C][C]2917513.21052632[/C][C]-1394991.21052632[/C][/ROW]
[ROW][C]5[/C][C]1742117[/C][C]3282237.05263158[/C][C]-1540120.05263158[/C][/ROW]
[ROW][C]6[/C][C]1737275[/C][C]3283960.94736842[/C][C]-1546685.94736842[/C][/ROW]
[ROW][C]7[/C][C]1979900[/C][C]3733233.84210526[/C][C]-1753333.84210526[/C][/ROW]
[ROW][C]8[/C][C]2061036[/C][C]3716215.78947369[/C][C]-1655179.78947369[/C][/ROW]
[ROW][C]9[/C][C]1867943[/C][C]3429430.47368421[/C][C]-1561487.47368421[/C][/ROW]
[ROW][C]10[/C][C]1707752[/C][C]3352404.05263158[/C][C]-1644652.05263158[/C][/ROW]
[ROW][C]11[/C][C]1298756[/C][C]2609903.05555556[/C][C]-1311147.05555556[/C][/ROW]
[ROW][C]12[/C][C]1281814[/C][C]2510604.94444444[/C][C]-1228790.94444444[/C][/ROW]
[ROW][C]13[/C][C]1281151[/C][C]2382690[/C][C]-1101539[/C][/ROW]
[ROW][C]14[/C][C]1164976[/C][C]2307173.63157895[/C][C]-1142197.63157895[/C][/ROW]
[ROW][C]15[/C][C]1454329[/C][C]2775059.10526316[/C][C]-1320730.10526316[/C][/ROW]
[ROW][C]16[/C][C]1645288[/C][C]2917513.21052632[/C][C]-1272225.21052632[/C][/ROW]
[ROW][C]17[/C][C]1817743[/C][C]3282237.05263158[/C][C]-1464494.05263158[/C][/ROW]
[ROW][C]18[/C][C]1895785[/C][C]3283960.94736842[/C][C]-1388175.94736842[/C][/ROW]
[ROW][C]19[/C][C]2236311[/C][C]3733233.84210526[/C][C]-1496922.84210526[/C][/ROW]
[ROW][C]20[/C][C]2295951[/C][C]3716215.78947368[/C][C]-1420264.78947368[/C][/ROW]
[ROW][C]21[/C][C]2087315[/C][C]3429430.47368421[/C][C]-1342115.47368421[/C][/ROW]
[ROW][C]22[/C][C]1980891[/C][C]3352404.05263158[/C][C]-1371513.05263158[/C][/ROW]
[ROW][C]23[/C][C]1465446[/C][C]2609903.05555556[/C][C]-1144457.05555556[/C][/ROW]
[ROW][C]24[/C][C]1445026[/C][C]2510604.94444444[/C][C]-1065578.94444444[/C][/ROW]
[ROW][C]25[/C][C]1488120[/C][C]2382690[/C][C]-894570[/C][/ROW]
[ROW][C]26[/C][C]1338333[/C][C]2307173.63157895[/C][C]-968840.631578948[/C][/ROW]
[ROW][C]27[/C][C]1715789[/C][C]2775059.10526316[/C][C]-1059270.10526316[/C][/ROW]
[ROW][C]28[/C][C]1806090[/C][C]2917513.21052632[/C][C]-1111423.21052632[/C][/ROW]
[ROW][C]29[/C][C]2083316[/C][C]3282237.05263158[/C][C]-1198921.05263158[/C][/ROW]
[ROW][C]30[/C][C]2092278[/C][C]3283960.94736842[/C][C]-1191682.94736842[/C][/ROW]
[ROW][C]31[/C][C]2430800[/C][C]3733233.84210526[/C][C]-1302433.84210526[/C][/ROW]
[ROW][C]32[/C][C]2424894[/C][C]3716215.78947368[/C][C]-1291321.78947368[/C][/ROW]
[ROW][C]33[/C][C]2299016[/C][C]3429430.47368421[/C][C]-1130414.47368421[/C][/ROW]
[ROW][C]34[/C][C]2130688[/C][C]3352404.05263158[/C][C]-1221716.05263158[/C][/ROW]
[ROW][C]35[/C][C]1652221[/C][C]2609903.05555556[/C][C]-957682.055555556[/C][/ROW]
[ROW][C]36[/C][C]1608162[/C][C]2510604.94444444[/C][C]-902442.944444444[/C][/ROW]
[ROW][C]37[/C][C]1647074[/C][C]2382690[/C][C]-735616.000000001[/C][/ROW]
[ROW][C]38[/C][C]1479691[/C][C]2307173.63157895[/C][C]-827482.631578948[/C][/ROW]
[ROW][C]39[/C][C]1884978[/C][C]2775059.10526316[/C][C]-890081.105263157[/C][/ROW]
[ROW][C]40[/C][C]2007898[/C][C]2917513.21052632[/C][C]-909615.210526316[/C][/ROW]
[ROW][C]41[/C][C]2208954[/C][C]3282237.05263158[/C][C]-1073283.05263158[/C][/ROW]
[ROW][C]42[/C][C]2217164[/C][C]3283960.94736842[/C][C]-1066796.94736842[/C][/ROW]
[ROW][C]43[/C][C]2534291[/C][C]3733233.84210526[/C][C]-1198942.84210526[/C][/ROW]
[ROW][C]44[/C][C]2560312[/C][C]3716215.78947368[/C][C]-1155903.78947368[/C][/ROW]
[ROW][C]45[/C][C]2429069[/C][C]3429430.47368421[/C][C]-1000361.47368421[/C][/ROW]
[ROW][C]46[/C][C]2315077[/C][C]3352404.05263158[/C][C]-1037327.05263158[/C][/ROW]
[ROW][C]47[/C][C]1799608[/C][C]2609903.05555556[/C][C]-810295.055555556[/C][/ROW]
[ROW][C]48[/C][C]1772590[/C][C]2510604.94444444[/C][C]-738014.944444444[/C][/ROW]
[ROW][C]49[/C][C]1744799[/C][C]2382690[/C][C]-637891.000000001[/C][/ROW]
[ROW][C]50[/C][C]1659093[/C][C]2307173.63157895[/C][C]-648080.631578947[/C][/ROW]
[ROW][C]51[/C][C]2099821[/C][C]2775059.10526316[/C][C]-675238.105263158[/C][/ROW]
[ROW][C]52[/C][C]2135736[/C][C]2917513.21052632[/C][C]-781777.210526316[/C][/ROW]
[ROW][C]53[/C][C]2427894[/C][C]3282237.05263158[/C][C]-854343.052631579[/C][/ROW]
[ROW][C]54[/C][C]2468882[/C][C]3283960.94736842[/C][C]-815078.947368421[/C][/ROW]
[ROW][C]55[/C][C]2703217[/C][C]3733233.84210526[/C][C]-1030016.84210526[/C][/ROW]
[ROW][C]56[/C][C]2766841[/C][C]3716215.78947368[/C][C]-949374.789473684[/C][/ROW]
[ROW][C]57[/C][C]2655236[/C][C]3429430.47368421[/C][C]-774194.473684211[/C][/ROW]
[ROW][C]58[/C][C]2550373[/C][C]3352404.05263158[/C][C]-802031.052631579[/C][/ROW]
[ROW][C]59[/C][C]2052097[/C][C]2609903.05555556[/C][C]-557806.055555556[/C][/ROW]
[ROW][C]60[/C][C]1998055[/C][C]2510604.94444444[/C][C]-512549.944444445[/C][/ROW]
[ROW][C]61[/C][C]1920748[/C][C]2382690[/C][C]-461942.000000001[/C][/ROW]
[ROW][C]62[/C][C]1876694[/C][C]2307173.63157895[/C][C]-430479.631578947[/C][/ROW]
[ROW][C]63[/C][C]2380930[/C][C]2775059.10526316[/C][C]-394129.105263158[/C][/ROW]
[ROW][C]64[/C][C]2467402[/C][C]2917513.21052632[/C][C]-450111.210526316[/C][/ROW]
[ROW][C]65[/C][C]2770771[/C][C]3282237.05263158[/C][C]-511466.052631579[/C][/ROW]
[ROW][C]66[/C][C]2781340[/C][C]3283960.94736842[/C][C]-502620.947368421[/C][/ROW]
[ROW][C]67[/C][C]3143926[/C][C]3733233.84210526[/C][C]-589307.842105263[/C][/ROW]
[ROW][C]68[/C][C]3172235[/C][C]3716215.78947368[/C][C]-543980.789473684[/C][/ROW]
[ROW][C]69[/C][C]2952540[/C][C]3429430.47368421[/C][C]-476890.473684211[/C][/ROW]
[ROW][C]70[/C][C]2920877[/C][C]3352404.05263158[/C][C]-431527.052631579[/C][/ROW]
[ROW][C]71[/C][C]2384552[/C][C]2609903.05555556[/C][C]-225351.055555556[/C][/ROW]
[ROW][C]72[/C][C]2248987[/C][C]2510604.94444444[/C][C]-261617.944444445[/C][/ROW]
[ROW][C]73[/C][C]2208616[/C][C]2382690[/C][C]-174074[/C][/ROW]
[ROW][C]74[/C][C]2178756[/C][C]2307173.63157895[/C][C]-128417.631578947[/C][/ROW]
[ROW][C]75[/C][C]2632870[/C][C]2775059.10526316[/C][C]-142189.105263158[/C][/ROW]
[ROW][C]76[/C][C]2706905[/C][C]2917513.21052632[/C][C]-210608.210526316[/C][/ROW]
[ROW][C]77[/C][C]3029745[/C][C]3282237.05263158[/C][C]-252492.052631579[/C][/ROW]
[ROW][C]78[/C][C]3015402[/C][C]3283960.94736842[/C][C]-268558.947368421[/C][/ROW]
[ROW][C]79[/C][C]3391414[/C][C]3733233.84210526[/C][C]-341819.842105263[/C][/ROW]
[ROW][C]80[/C][C]3507805[/C][C]3716215.78947368[/C][C]-208410.789473684[/C][/ROW]
[ROW][C]81[/C][C]3177852[/C][C]3429430.47368421[/C][C]-251578.47368421[/C][/ROW]
[ROW][C]82[/C][C]3142961[/C][C]3352404.05263158[/C][C]-209443.052631579[/C][/ROW]
[ROW][C]83[/C][C]2545815[/C][C]2609903.05555556[/C][C]-64088.0555555554[/C][/ROW]
[ROW][C]84[/C][C]2414007[/C][C]2510604.94444444[/C][C]-96597.9444444445[/C][/ROW]
[ROW][C]85[/C][C]2372578[/C][C]2382690[/C][C]-10112.0000000004[/C][/ROW]
[ROW][C]86[/C][C]2332664[/C][C]2307173.63157895[/C][C]25490.3684210526[/C][/ROW]
[ROW][C]87[/C][C]2825328[/C][C]2775059.10526316[/C][C]50268.8947368421[/C][/ROW]
[ROW][C]88[/C][C]2901478[/C][C]2917513.21052632[/C][C]-16035.2105263159[/C][/ROW]
[ROW][C]89[/C][C]3263955[/C][C]3282237.05263158[/C][C]-18282.052631579[/C][/ROW]
[ROW][C]90[/C][C]3226738[/C][C]3283960.94736842[/C][C]-57222.947368421[/C][/ROW]
[ROW][C]91[/C][C]3610786[/C][C]3733233.84210526[/C][C]-122447.842105263[/C][/ROW]
[ROW][C]92[/C][C]3709274[/C][C]3716215.78947368[/C][C]-6941.78947368442[/C][/ROW]
[ROW][C]93[/C][C]3467185[/C][C]3429430.47368421[/C][C]37754.5263157894[/C][/ROW]
[ROW][C]94[/C][C]3449646[/C][C]3352404.05263158[/C][C]97241.9473684208[/C][/ROW]
[ROW][C]95[/C][C]2802951[/C][C]2609903.05555556[/C][C]193047.944444444[/C][/ROW]
[ROW][C]96[/C][C]2462530[/C][C]2510604.94444444[/C][C]-48074.9444444444[/C][/ROW]
[ROW][C]97[/C][C]2490645[/C][C]2382690[/C][C]107955[/C][/ROW]
[ROW][C]98[/C][C]2561520[/C][C]2307173.63157895[/C][C]254346.368421053[/C][/ROW]
[ROW][C]99[/C][C]3067554[/C][C]2775059.10526316[/C][C]292494.894736842[/C][/ROW]
[ROW][C]100[/C][C]3226951[/C][C]2917513.21052632[/C][C]309437.789473684[/C][/ROW]
[ROW][C]101[/C][C]3546493[/C][C]3282237.05263158[/C][C]264255.947368421[/C][/ROW]
[ROW][C]102[/C][C]3492787[/C][C]3283960.94736842[/C][C]208826.052631579[/C][/ROW]
[ROW][C]103[/C][C]3952263[/C][C]3733233.84210526[/C][C]219029.157894737[/C][/ROW]
[ROW][C]104[/C][C]3932072[/C][C]3716215.78947368[/C][C]215856.210526316[/C][/ROW]
[ROW][C]105[/C][C]3720284[/C][C]3429430.47368421[/C][C]290853.526315789[/C][/ROW]
[ROW][C]106[/C][C]3651555[/C][C]3352404.05263158[/C][C]299150.947368421[/C][/ROW]
[ROW][C]107[/C][C]2914972[/C][C]2609903.05555556[/C][C]305068.944444444[/C][/ROW]
[ROW][C]108[/C][C]2713514[/C][C]2510604.94444444[/C][C]202909.055555555[/C][/ROW]
[ROW][C]109[/C][C]2703997[/C][C]2382690[/C][C]321307[/C][/ROW]
[ROW][C]110[/C][C]2591373[/C][C]2307173.63157895[/C][C]284199.368421053[/C][/ROW]
[ROW][C]111[/C][C]3163748[/C][C]2775059.10526316[/C][C]388688.894736842[/C][/ROW]
[ROW][C]112[/C][C]3355137[/C][C]2917513.21052632[/C][C]437623.789473684[/C][/ROW]
[ROW][C]113[/C][C]3613702[/C][C]3282237.05263158[/C][C]331464.947368421[/C][/ROW]
[ROW][C]114[/C][C]3686773[/C][C]3283960.94736842[/C][C]402812.052631579[/C][/ROW]
[ROW][C]115[/C][C]4098716[/C][C]3733233.84210526[/C][C]365482.157894737[/C][/ROW]
[ROW][C]116[/C][C]4063517[/C][C]3716215.78947368[/C][C]347301.210526316[/C][/ROW]
[ROW][C]117[/C][C]3551489[/C][C]3429430.47368421[/C][C]122058.526315789[/C][/ROW]
[ROW][C]118[/C][C]3226663[/C][C]3352404.05263158[/C][C]-125741.052631579[/C][/ROW]
[ROW][C]119[/C][C]2656842[/C][C]2609903.05555556[/C][C]46938.9444444444[/C][/ROW]
[ROW][C]120[/C][C]2597484[/C][C]2510604.94444444[/C][C]86879.0555555554[/C][/ROW]
[ROW][C]121[/C][C]2572399[/C][C]2382690[/C][C]189709[/C][/ROW]
[ROW][C]122[/C][C]2596631[/C][C]2307173.63157895[/C][C]289457.368421053[/C][/ROW]
[ROW][C]123[/C][C]3165225[/C][C]2775059.10526316[/C][C]390165.894736842[/C][/ROW]
[ROW][C]124[/C][C]3303145[/C][C]2917513.21052632[/C][C]385631.789473684[/C][/ROW]
[ROW][C]125[/C][C]3698247[/C][C]3282237.05263158[/C][C]416009.947368421[/C][/ROW]
[ROW][C]126[/C][C]3668631[/C][C]3283960.94736842[/C][C]384670.052631579[/C][/ROW]
[ROW][C]127[/C][C]4130433[/C][C]3733233.84210526[/C][C]397199.157894737[/C][/ROW]
[ROW][C]128[/C][C]4131400[/C][C]3716215.78947368[/C][C]415184.210526316[/C][/ROW]
[ROW][C]129[/C][C]3864358[/C][C]3429430.47368421[/C][C]434927.526315789[/C][/ROW]
[ROW][C]130[/C][C]3721110[/C][C]3352404.05263158[/C][C]368705.947368421[/C][/ROW]
[ROW][C]131[/C][C]2892532[/C][C]2609903.05555556[/C][C]282628.944444444[/C][/ROW]
[ROW][C]132[/C][C]2843451[/C][C]2510604.94444444[/C][C]332846.055555556[/C][/ROW]
[ROW][C]133[/C][C]2747502[/C][C]2382690[/C][C]364812[/C][/ROW]
[ROW][C]134[/C][C]2668775[/C][C]2307173.63157895[/C][C]361601.368421053[/C][/ROW]
[ROW][C]135[/C][C]3018602[/C][C]2775059.10526316[/C][C]243542.894736842[/C][/ROW]
[ROW][C]136[/C][C]3013392[/C][C]2917513.21052632[/C][C]95878.7894736841[/C][/ROW]
[ROW][C]137[/C][C]3393657[/C][C]3282237.05263158[/C][C]111419.947368421[/C][/ROW]
[ROW][C]138[/C][C]3544233[/C][C]3283960.94736842[/C][C]260272.052631579[/C][/ROW]
[ROW][C]139[/C][C]4075832[/C][C]3733233.84210526[/C][C]342598.157894737[/C][/ROW]
[ROW][C]140[/C][C]4032923[/C][C]3716215.78947368[/C][C]316707.210526316[/C][/ROW]
[ROW][C]141[/C][C]3734509[/C][C]3429430.47368421[/C][C]305078.526315789[/C][/ROW]
[ROW][C]142[/C][C]3761285[/C][C]3352404.05263158[/C][C]408880.947368421[/C][/ROW]
[ROW][C]143[/C][C]2970090[/C][C]2609903.05555556[/C][C]360186.944444444[/C][/ROW]
[ROW][C]144[/C][C]2847849[/C][C]2510604.94444444[/C][C]337244.055555556[/C][/ROW]
[ROW][C]145[/C][C]2741680[/C][C]2382690[/C][C]358990[/C][/ROW]
[ROW][C]146[/C][C]2830639[/C][C]2307173.63157895[/C][C]523465.368421053[/C][/ROW]
[ROW][C]147[/C][C]3257673[/C][C]2775059.10526316[/C][C]482613.894736842[/C][/ROW]
[ROW][C]148[/C][C]3480085[/C][C]2917513.21052632[/C][C]562571.789473684[/C][/ROW]
[ROW][C]149[/C][C]3843271[/C][C]3282237.05263158[/C][C]561033.947368421[/C][/ROW]
[ROW][C]150[/C][C]3796961[/C][C]3283960.94736842[/C][C]513000.052631579[/C][/ROW]
[ROW][C]151[/C][C]4337767[/C][C]3733233.84210526[/C][C]604533.157894737[/C][/ROW]
[ROW][C]152[/C][C]4243630[/C][C]3716215.78947368[/C][C]527414.210526316[/C][/ROW]
[ROW][C]153[/C][C]3927202[/C][C]3429430.47368421[/C][C]497771.526315789[/C][/ROW]
[ROW][C]154[/C][C]3915296[/C][C]3352404.05263158[/C][C]562891.947368421[/C][/ROW]
[ROW][C]155[/C][C]3087396[/C][C]2609903.05555556[/C][C]477492.944444444[/C][/ROW]
[ROW][C]156[/C][C]2963792[/C][C]2510604.94444444[/C][C]453187.055555555[/C][/ROW]
[ROW][C]157[/C][C]2955792[/C][C]2382690[/C][C]573102[/C][/ROW]
[ROW][C]158[/C][C]2829925[/C][C]2307173.63157895[/C][C]522751.368421053[/C][/ROW]
[ROW][C]159[/C][C]3281195[/C][C]2775059.10526316[/C][C]506135.894736842[/C][/ROW]
[ROW][C]160[/C][C]3548011[/C][C]2917513.21052632[/C][C]630497.789473684[/C][/ROW]
[ROW][C]161[/C][C]4059648[/C][C]3282237.05263158[/C][C]777410.947368421[/C][/ROW]
[ROW][C]162[/C][C]3941175[/C][C]3283960.94736842[/C][C]657214.052631579[/C][/ROW]
[ROW][C]163[/C][C]4528594[/C][C]3733233.84210526[/C][C]795360.157894737[/C][/ROW]
[ROW][C]164[/C][C]4433151[/C][C]3716215.78947368[/C][C]716935.210526316[/C][/ROW]
[ROW][C]165[/C][C]4145737[/C][C]3429430.47368421[/C][C]716306.52631579[/C][/ROW]
[ROW][C]166[/C][C]4077132[/C][C]3352404.05263158[/C][C]724727.947368421[/C][/ROW]
[ROW][C]167[/C][C]3198519[/C][C]2609903.05555556[/C][C]588615.944444444[/C][/ROW]
[ROW][C]168[/C][C]3078660[/C][C]2510604.94444444[/C][C]568055.055555556[/C][/ROW]
[ROW][C]169[/C][C]3028202[/C][C]2382690[/C][C]645512[/C][/ROW]
[ROW][C]170[/C][C]2858642[/C][C]2307173.63157895[/C][C]551468.368421053[/C][/ROW]
[ROW][C]171[/C][C]3398954[/C][C]2775059.10526316[/C][C]623894.894736842[/C][/ROW]
[ROW][C]172[/C][C]3808883[/C][C]2917513.21052632[/C][C]891369.789473684[/C][/ROW]
[ROW][C]173[/C][C]4175961[/C][C]3282237.05263158[/C][C]893723.947368421[/C][/ROW]
[ROW][C]174[/C][C]4227542[/C][C]3283960.94736842[/C][C]943581.052631579[/C][/ROW]
[ROW][C]175[/C][C]4744616[/C][C]3733233.84210526[/C][C]1011382.15789474[/C][/ROW]
[ROW][C]176[/C][C]4608012[/C][C]3716215.78947368[/C][C]891796.210526316[/C][/ROW]
[ROW][C]177[/C][C]4295049[/C][C]3429430.47368421[/C][C]865618.52631579[/C][/ROW]
[ROW][C]178[/C][C]4201144[/C][C]3352404.05263158[/C][C]848739.947368421[/C][/ROW]
[ROW][C]179[/C][C]3353276[/C][C]2609903.05555556[/C][C]743372.944444444[/C][/ROW]
[ROW][C]180[/C][C]3286851[/C][C]2510604.94444444[/C][C]776246.055555556[/C][/ROW]
[ROW][C]181[/C][C]3169889[/C][C]2382690[/C][C]787198.999999999[/C][/ROW]
[ROW][C]182[/C][C]3051720[/C][C]2307173.63157895[/C][C]744546.368421053[/C][/ROW]
[ROW][C]183[/C][C]3695426[/C][C]2775059.10526316[/C][C]920366.894736842[/C][/ROW]
[ROW][C]184[/C][C]3905501[/C][C]2917513.21052632[/C][C]987987.789473684[/C][/ROW]
[ROW][C]185[/C][C]4296458[/C][C]3282237.05263158[/C][C]1014220.94736842[/C][/ROW]
[ROW][C]186[/C][C]4246247[/C][C]3283960.94736842[/C][C]962286.052631579[/C][/ROW]
[ROW][C]187[/C][C]4921849[/C][C]3733233.84210526[/C][C]1188615.15789474[/C][/ROW]
[ROW][C]188[/C][C]4821446[/C][C]3716215.78947368[/C][C]1105230.21052632[/C][/ROW]
[ROW][C]189[/C][C]4425064[/C][C]3429430.47368421[/C][C]995633.52631579[/C][/ROW]
[ROW][C]190[/C][C]4379099[/C][C]3352404.05263158[/C][C]1026694.94736842[/C][/ROW]
[ROW][C]191[/C][C]3472889[/C][C]2609903.05555556[/C][C]862985.944444444[/C][/ROW]
[ROW][C]192[/C][C]3359160[/C][C]2510604.94444444[/C][C]848555.055555556[/C][/ROW]
[ROW][C]193[/C][C]3200944[/C][C]2382690[/C][C]818253.999999999[/C][/ROW]
[ROW][C]194[/C][C]3153170[/C][C]2307173.63157895[/C][C]845996.368421053[/C][/ROW]
[ROW][C]195[/C][C]3741498[/C][C]2775059.10526316[/C][C]966438.894736842[/C][/ROW]
[ROW][C]196[/C][C]3918719[/C][C]2917513.21052632[/C][C]1001205.78947368[/C][/ROW]
[ROW][C]197[/C][C]4403449[/C][C]3282237.05263158[/C][C]1121211.94736842[/C][/ROW]
[ROW][C]198[/C][C]4400407[/C][C]3283960.94736842[/C][C]1116446.05263158[/C][/ROW]
[ROW][C]199[/C][C]4847473[/C][C]3733233.84210526[/C][C]1114239.15789474[/C][/ROW]
[ROW][C]200[/C][C]4716136[/C][C]3716215.78947368[/C][C]999920.210526316[/C][/ROW]
[ROW][C]201[/C][C]4297440[/C][C]3429430.47368421[/C][C]868009.52631579[/C][/ROW]
[ROW][C]202[/C][C]4272253[/C][C]3352404.05263158[/C][C]919848.947368421[/C][/ROW]
[ROW][C]203[/C][C]3271834[/C][C]2609903.05555556[/C][C]661930.944444444[/C][/ROW]
[ROW][C]204[/C][C]3168388[/C][C]2510604.94444444[/C][C]657783.055555556[/C][/ROW]
[ROW][C]205[/C][C]2911748[/C][C]2382690[/C][C]529058[/C][/ROW]
[ROW][C]206[/C][C]2720999[/C][C]2307173.63157895[/C][C]413825.368421053[/C][/ROW]
[ROW][C]207[/C][C]3199918[/C][C]2775059.10526316[/C][C]424858.894736842[/C][/ROW]
[ROW][C]208[/C][C]3672623[/C][C]2917513.21052632[/C][C]755109.789473684[/C][/ROW]
[ROW][C]209[/C][C]3892013[/C][C]3282237.05263158[/C][C]609775.947368421[/C][/ROW]
[ROW][C]210[/C][C]3850845[/C][C]3283960.94736842[/C][C]566884.052631579[/C][/ROW]
[ROW][C]211[/C][C]4532467[/C][C]3733233.84210526[/C][C]799233.157894737[/C][/ROW]
[ROW][C]212[/C][C]4484739[/C][C]3716215.78947368[/C][C]768523.210526316[/C][/ROW]
[ROW][C]213[/C][C]4014972[/C][C]3429430.47368421[/C][C]585541.52631579[/C][/ROW]
[ROW][C]214[/C][C]3983758[/C][C]3352404.05263158[/C][C]631353.947368421[/C][/ROW]
[ROW][C]215[/C][C]3158459[/C][C]2609903.05555556[/C][C]548555.944444444[/C][/ROW]
[ROW][C]216[/C][C]3100569[/C][C]2510604.94444444[/C][C]589964.055555556[/C][/ROW]
[ROW][C]217[/C][C]2935404[/C][C]2382690[/C][C]552714[/C][/ROW]
[ROW][C]218[/C][C]2855719[/C][C]2307173.63157895[/C][C]548545.368421053[/C][/ROW]
[ROW][C]219[/C][C]3465611[/C][C]2775059.10526316[/C][C]690551.894736842[/C][/ROW]
[ROW][C]220[/C][C]3006985[/C][C]2917513.21052632[/C][C]89471.7894736841[/C][/ROW]
[ROW][C]221[/C][C]4095110[/C][C]3282237.05263158[/C][C]812872.947368421[/C][/ROW]
[ROW][C]222[/C][C]4104793[/C][C]3283960.94736842[/C][C]820832.052631579[/C][/ROW]
[ROW][C]223[/C][C]4730788[/C][C]3733233.84210526[/C][C]997554.157894737[/C][/ROW]
[ROW][C]224[/C][C]4642726[/C][C]3716215.78947368[/C][C]926510.210526316[/C][/ROW]
[ROW][C]225[/C][C]4246919[/C][C]3429430.47368421[/C][C]817488.52631579[/C][/ROW]
[ROW][C]226[/C][C]4308117[/C][C]3352404.05263158[/C][C]955712.947368421[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148475&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148475&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
111498222382690-1232868
210869792307173.63157895-1220194.63157895
312766742775059.10526316-1498385.10526316
415225222917513.21052632-1394991.21052632
517421173282237.05263158-1540120.05263158
617372753283960.94736842-1546685.94736842
719799003733233.84210526-1753333.84210526
820610363716215.78947369-1655179.78947369
918679433429430.47368421-1561487.47368421
1017077523352404.05263158-1644652.05263158
1112987562609903.05555556-1311147.05555556
1212818142510604.94444444-1228790.94444444
1312811512382690-1101539
1411649762307173.63157895-1142197.63157895
1514543292775059.10526316-1320730.10526316
1616452882917513.21052632-1272225.21052632
1718177433282237.05263158-1464494.05263158
1818957853283960.94736842-1388175.94736842
1922363113733233.84210526-1496922.84210526
2022959513716215.78947368-1420264.78947368
2120873153429430.47368421-1342115.47368421
2219808913352404.05263158-1371513.05263158
2314654462609903.05555556-1144457.05555556
2414450262510604.94444444-1065578.94444444
2514881202382690-894570
2613383332307173.63157895-968840.631578948
2717157892775059.10526316-1059270.10526316
2818060902917513.21052632-1111423.21052632
2920833163282237.05263158-1198921.05263158
3020922783283960.94736842-1191682.94736842
3124308003733233.84210526-1302433.84210526
3224248943716215.78947368-1291321.78947368
3322990163429430.47368421-1130414.47368421
3421306883352404.05263158-1221716.05263158
3516522212609903.05555556-957682.055555556
3616081622510604.94444444-902442.944444444
3716470742382690-735616.000000001
3814796912307173.63157895-827482.631578948
3918849782775059.10526316-890081.105263157
4020078982917513.21052632-909615.210526316
4122089543282237.05263158-1073283.05263158
4222171643283960.94736842-1066796.94736842
4325342913733233.84210526-1198942.84210526
4425603123716215.78947368-1155903.78947368
4524290693429430.47368421-1000361.47368421
4623150773352404.05263158-1037327.05263158
4717996082609903.05555556-810295.055555556
4817725902510604.94444444-738014.944444444
4917447992382690-637891.000000001
5016590932307173.63157895-648080.631578947
5120998212775059.10526316-675238.105263158
5221357362917513.21052632-781777.210526316
5324278943282237.05263158-854343.052631579
5424688823283960.94736842-815078.947368421
5527032173733233.84210526-1030016.84210526
5627668413716215.78947368-949374.789473684
5726552363429430.47368421-774194.473684211
5825503733352404.05263158-802031.052631579
5920520972609903.05555556-557806.055555556
6019980552510604.94444444-512549.944444445
6119207482382690-461942.000000001
6218766942307173.63157895-430479.631578947
6323809302775059.10526316-394129.105263158
6424674022917513.21052632-450111.210526316
6527707713282237.05263158-511466.052631579
6627813403283960.94736842-502620.947368421
6731439263733233.84210526-589307.842105263
6831722353716215.78947368-543980.789473684
6929525403429430.47368421-476890.473684211
7029208773352404.05263158-431527.052631579
7123845522609903.05555556-225351.055555556
7222489872510604.94444444-261617.944444445
7322086162382690-174074
7421787562307173.63157895-128417.631578947
7526328702775059.10526316-142189.105263158
7627069052917513.21052632-210608.210526316
7730297453282237.05263158-252492.052631579
7830154023283960.94736842-268558.947368421
7933914143733233.84210526-341819.842105263
8035078053716215.78947368-208410.789473684
8131778523429430.47368421-251578.47368421
8231429613352404.05263158-209443.052631579
8325458152609903.05555556-64088.0555555554
8424140072510604.94444444-96597.9444444445
8523725782382690-10112.0000000004
8623326642307173.6315789525490.3684210526
8728253282775059.1052631650268.8947368421
8829014782917513.21052632-16035.2105263159
8932639553282237.05263158-18282.052631579
9032267383283960.94736842-57222.947368421
9136107863733233.84210526-122447.842105263
9237092743716215.78947368-6941.78947368442
9334671853429430.4736842137754.5263157894
9434496463352404.0526315897241.9473684208
9528029512609903.05555556193047.944444444
9624625302510604.94444444-48074.9444444444
9724906452382690107955
9825615202307173.63157895254346.368421053
9930675542775059.10526316292494.894736842
10032269512917513.21052632309437.789473684
10135464933282237.05263158264255.947368421
10234927873283960.94736842208826.052631579
10339522633733233.84210526219029.157894737
10439320723716215.78947368215856.210526316
10537202843429430.47368421290853.526315789
10636515553352404.05263158299150.947368421
10729149722609903.05555556305068.944444444
10827135142510604.94444444202909.055555555
10927039972382690321307
11025913732307173.63157895284199.368421053
11131637482775059.10526316388688.894736842
11233551372917513.21052632437623.789473684
11336137023282237.05263158331464.947368421
11436867733283960.94736842402812.052631579
11540987163733233.84210526365482.157894737
11640635173716215.78947368347301.210526316
11735514893429430.47368421122058.526315789
11832266633352404.05263158-125741.052631579
11926568422609903.0555555646938.9444444444
12025974842510604.9444444486879.0555555554
12125723992382690189709
12225966312307173.63157895289457.368421053
12331652252775059.10526316390165.894736842
12433031452917513.21052632385631.789473684
12536982473282237.05263158416009.947368421
12636686313283960.94736842384670.052631579
12741304333733233.84210526397199.157894737
12841314003716215.78947368415184.210526316
12938643583429430.47368421434927.526315789
13037211103352404.05263158368705.947368421
13128925322609903.05555556282628.944444444
13228434512510604.94444444332846.055555556
13327475022382690364812
13426687752307173.63157895361601.368421053
13530186022775059.10526316243542.894736842
13630133922917513.2105263295878.7894736841
13733936573282237.05263158111419.947368421
13835442333283960.94736842260272.052631579
13940758323733233.84210526342598.157894737
14040329233716215.78947368316707.210526316
14137345093429430.47368421305078.526315789
14237612853352404.05263158408880.947368421
14329700902609903.05555556360186.944444444
14428478492510604.94444444337244.055555556
14527416802382690358990
14628306392307173.63157895523465.368421053
14732576732775059.10526316482613.894736842
14834800852917513.21052632562571.789473684
14938432713282237.05263158561033.947368421
15037969613283960.94736842513000.052631579
15143377673733233.84210526604533.157894737
15242436303716215.78947368527414.210526316
15339272023429430.47368421497771.526315789
15439152963352404.05263158562891.947368421
15530873962609903.05555556477492.944444444
15629637922510604.94444444453187.055555555
15729557922382690573102
15828299252307173.63157895522751.368421053
15932811952775059.10526316506135.894736842
16035480112917513.21052632630497.789473684
16140596483282237.05263158777410.947368421
16239411753283960.94736842657214.052631579
16345285943733233.84210526795360.157894737
16444331513716215.78947368716935.210526316
16541457373429430.47368421716306.52631579
16640771323352404.05263158724727.947368421
16731985192609903.05555556588615.944444444
16830786602510604.94444444568055.055555556
16930282022382690645512
17028586422307173.63157895551468.368421053
17133989542775059.10526316623894.894736842
17238088832917513.21052632891369.789473684
17341759613282237.05263158893723.947368421
17442275423283960.94736842943581.052631579
17547446163733233.842105261011382.15789474
17646080123716215.78947368891796.210526316
17742950493429430.47368421865618.52631579
17842011443352404.05263158848739.947368421
17933532762609903.05555556743372.944444444
18032868512510604.94444444776246.055555556
18131698892382690787198.999999999
18230517202307173.63157895744546.368421053
18336954262775059.10526316920366.894736842
18439055012917513.21052632987987.789473684
18542964583282237.052631581014220.94736842
18642462473283960.94736842962286.052631579
18749218493733233.842105261188615.15789474
18848214463716215.789473681105230.21052632
18944250643429430.47368421995633.52631579
19043790993352404.052631581026694.94736842
19134728892609903.05555556862985.944444444
19233591602510604.94444444848555.055555556
19332009442382690818253.999999999
19431531702307173.63157895845996.368421053
19537414982775059.10526316966438.894736842
19639187192917513.210526321001205.78947368
19744034493282237.052631581121211.94736842
19844004073283960.947368421116446.05263158
19948474733733233.842105261114239.15789474
20047161363716215.78947368999920.210526316
20142974403429430.47368421868009.52631579
20242722533352404.05263158919848.947368421
20332718342609903.05555556661930.944444444
20431683882510604.94444444657783.055555556
20529117482382690529058
20627209992307173.63157895413825.368421053
20731999182775059.10526316424858.894736842
20836726232917513.21052632755109.789473684
20938920133282237.05263158609775.947368421
21038508453283960.94736842566884.052631579
21145324673733233.84210526799233.157894737
21244847393716215.78947368768523.210526316
21340149723429430.47368421585541.52631579
21439837583352404.05263158631353.947368421
21531584592609903.05555556548555.944444444
21631005692510604.94444444589964.055555556
21729354042382690552714
21828557192307173.63157895548545.368421053
21934656112775059.10526316690551.894736842
22030069852917513.2105263289471.7894736841
22140951103282237.05263158812872.947368421
22241047933283960.94736842820832.052631579
22347307883733233.84210526997554.157894737
22446427263716215.78947368926510.210526316
22542469193429430.47368421817488.52631579
22643081173352404.05263158955712.947368421







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
150.003214082796922460.006428165593844910.996785917203078
160.0005809041241105850.001161808248221170.999419095875889
178.33192906727799e-050.000166638581345560.999916680709327
182.24320391987139e-054.48640783974278e-050.999977567960801
191.62365511298039e-053.24731022596079e-050.99998376344887
207.84017749368523e-061.56803549873705e-050.999992159822506
213.23194055709347e-066.46388111418694e-060.999996768059443
221.98855754924142e-063.97711509848285e-060.999998011442451
236.00182685004751e-071.2003653700095e-060.999999399817315
241.79063813953498e-073.58127627906995e-070.999999820936186
251.42604294813192e-072.85208589626384e-070.999999857395705
266.72516286206954e-081.34503257241391e-070.999999932748371
279.87840118560296e-081.97568023712059e-070.999999901215988
285.07610432865555e-081.01522086573111e-070.999999949238957
294.59364808244541e-089.18729616489083e-080.999999954063519
303.39618745958181e-086.79237491916361e-080.999999966038125
313.55713182729495e-087.1142636545899e-080.999999964428682
322.39768214479008e-084.79536428958016e-080.999999976023179
332.33734809290997e-084.67469618581993e-080.999999976626519
341.96004109947736e-083.92008219895473e-080.999999980399589
351.37506847574094e-082.75013695148188e-080.999999986249315
368.52948808735969e-091.70589761747194e-080.999999991470512
379.32575675986758e-091.86515135197352e-080.999999990674243
387.53229572615374e-091.50645914523075e-080.999999992467704
391.27487697688301e-082.54975395376602e-080.99999998725123
401.5208005162347e-083.04160103246941e-080.999999984791995
411.81097108322167e-083.62194216644334e-080.999999981890289
422.00673743416012e-084.01347486832023e-080.999999979932626
432.6940392770561e-085.3880785541122e-080.999999973059607
443.34348183324675e-086.6869636664935e-080.999999966565182
454.54614575592149e-089.09229151184298e-080.999999954538542
467.546451363033e-081.5092902726066e-070.999999924535486
478.53440109787702e-081.7068802195754e-070.999999914655989
489.24851551011338e-081.84970310202268e-070.999999907514845
491.13561907454175e-072.27123814908351e-070.999999886438093
501.67109035671549e-073.34218071343098e-070.999999832890964
514.65948748126866e-079.31897496253732e-070.999999534051252
527.51150436123761e-071.50230087224752e-060.999999248849564
531.81880909647838e-063.63761819295676e-060.999998181190904
544.46504359604458e-068.93008719208917e-060.999995534956404
551.09236134596432e-052.18472269192864e-050.99998907638654
562.64829264572829e-055.29658529145658e-050.999973517073543
576.10661400723277e-050.0001221322801446550.999938933859928
580.0001605086765720510.0003210173531441030.999839491323428
590.000292807428915550.00058561485783110.999707192571084
600.0004613611387293910.0009227222774587830.999538638861271
610.0007105676021796720.001421135204359340.99928943239782
620.001274923108470080.002549846216940170.99872507689153
630.003431740977893790.006863481955787580.996568259022106
640.007497808076135350.01499561615227070.992502191923865
650.0190895588344310.0381791176688620.980910441165569
660.04110794125434250.0822158825086850.958892058745658
670.09805965372716470.1961193074543290.901940346272835
680.1871767822017750.3743535644035510.812823217798225
690.2812117111746920.5624234223493840.718788288825308
700.4180307407488560.8360614814977110.581969259251144
710.5099439759638290.9801120480723430.490056024036171
720.575270250392860.8494594992142810.42472974960714
730.6444058756613470.7111882486773050.355594124338653
740.720010788421060.5599784231578810.27998921157894
750.8059817201169090.3880365597661810.194018279883091
760.8699026277374640.2601947445250720.130097372262536
770.9298650901567280.1402698196865450.0701349098432724
780.9640367097832590.07192658043348130.0359632902167407
790.9875764563718090.02484708725638170.0124235436281909
800.9958895384608290.008220923078342850.00411046153917142
810.9983493743450140.003301251309971280.00165062565498564
820.9994455971376570.001108805724686220.000554402862343108
830.9996925306569940.0006149386860122570.000307469343006129
840.9998105627987590.0003788744024827320.000189437201241366
850.9998873293941380.0002253412117246020.000112670605862301
860.9999367816051850.0001264367896304166.32183948152081e-05
870.999972431818025.51363639596626e-052.75681819798313e-05
880.9999887553437072.2489312585572e-051.1244656292786e-05
890.9999969099140436.18017191362799e-063.090085956814e-06
900.9999991619638211.67607235733595e-068.38036178667973e-07
910.9999998893574692.2128506214475e-071.10642531072375e-07
920.9999999794813674.10372654921301e-082.0518632746065e-08
930.999999994262091.14758199665729e-085.73790998328647e-09
940.9999999985140742.97185207871158e-091.48592603935579e-09
950.9999999991577341.68453114063648e-098.42265570318242e-10
960.9999999995456489.08703560134523e-104.54351780067262e-10
970.9999999997221025.55795729523788e-102.77897864761894e-10
980.9999999998283873.43225717390878e-101.71612858695439e-10
990.999999999916071.67859663150074e-108.39298315750372e-11
1000.9999999999615427.69157415877485e-113.84578707938743e-11
1010.9999999999874562.50887101722607e-111.25443550861303e-11
1020.9999999999958078.38597348926947e-124.19298674463474e-12
1030.9999999999992191.56259234175527e-127.81296170877635e-13
1040.9999999999997864.28172553011039e-132.14086276505519e-13
1050.9999999999999021.96362715752326e-139.81813578761628e-14
1060.9999999999999568.82731436529324e-144.41365718264662e-14
1070.9999999999999617.84968712351288e-143.92484356175644e-14
1080.9999999999999666.7359441251425e-143.36797206257125e-14
1090.9999999999999696.26598566550148e-143.13299283275074e-14
1100.999999999999975.94897996395914e-142.97448998197957e-14
1110.9999999999999764.87810247705015e-142.43905123852508e-14
1120.9999999999999813.81094098942739e-141.90547049471369e-14
1130.999999999999992.07295489820151e-141.03647744910076e-14
1140.9999999999999941.2673502382123e-146.33675119106151e-15
1150.9999999999999984.57684253707693e-152.28842126853846e-15
1160.9999999999999992.28283452730965e-151.14141726365483e-15
11719.44421835371906e-164.72210917685953e-16
11817.58187545857761e-173.79093772928881e-17
11914.2190333110369e-172.10951665551845e-17
12012.6010703623492e-171.3005351811746e-17
12112.24114128024208e-171.12057064012104e-17
12212.57834784992093e-171.28917392496046e-17
12312.92862486931293e-171.46431243465647e-17
12413.15373070358726e-171.57686535179363e-17
12512.34237913642465e-171.17118956821232e-17
12611.72135211829356e-178.60676059146778e-18
12716.75753674617669e-183.37876837308834e-18
12814.27283169397646e-182.13641584698823e-18
12914.03117147726347e-182.01558573863174e-18
13012.57543154143836e-181.28771577071918e-18
13112.89112799686356e-181.44556399843178e-18
13213.70712059591876e-181.85356029795938e-18
13315.1819039516464e-182.5909519758232e-18
13417.64286114881726e-183.82143057440863e-18
13516.14445427426408e-183.07222713713204e-18
13611.63324146065665e-188.16620730328327e-19
13711.34088724536135e-196.70443622680674e-20
13813.73910958902742e-201.86955479451371e-20
13915.11016310620414e-212.55508155310207e-21
14011.0669169759278e-215.33458487963898e-22
14113.95641087602883e-221.97820543801442e-22
14211.92976726944899e-229.64883634724495e-23
14312.36001247816444e-221.18000623908222e-22
14412.54966017883831e-221.27483008941916e-22
14513.0873657708735e-221.54368288543675e-22
14617.17873863939009e-223.58936931969504e-22
14711.19472137887644e-215.97360689438221e-22
14812.1500439845014e-211.0750219922507e-21
14911.89313141783834e-219.46565708919169e-22
15011.54419111368885e-217.72095556844423e-22
15117.63015120313447e-223.81507560156724e-22
15214.26500346329048e-222.13250173164524e-22
15313.98672550070163e-221.99336275035082e-22
15414.03178846448787e-222.01589423224393e-22
15517.78843257001181e-223.8942162850059e-22
15611.31569153644654e-216.5784576822327e-22
15713.54226728049919e-211.7711336402496e-21
15819.85599898197116e-214.92799949098558e-21
15911.79390441386844e-208.96952206934221e-21
16014.43171983218074e-202.21585991609037e-20
16119.64270916732285e-204.82135458366143e-20
16211.5565131533459e-197.78256576672951e-20
16312.2104968360355e-191.10524841801775e-19
16413.54572894126223e-191.77286447063112e-19
16518.80296453935652e-194.40148226967826e-19
16611.93616282990809e-189.68081414954044e-19
16715.45171275810198e-182.72585637905099e-18
16811.41441020557406e-177.07205102787031e-18
16914.45145574715206e-172.22572787357603e-17
17011.36386312431791e-166.81931562158954e-17
17113.69873483593704e-161.84936741796852e-16
17217.61199039834041e-163.8059951991702e-16
1730.9999999999999992.09581140126466e-151.04790570063233e-15
1740.9999999999999975.38459849970345e-152.69229924985172e-15
1750.9999999999999931.38428280092745e-146.92141400463725e-15
1760.9999999999999813.74937340031499e-141.87468670015749e-14
1770.9999999999999471.05655575083673e-135.28277875418366e-14
1780.999999999999853.00844544881433e-131.50422272440717e-13
1790.9999999999995459.10592424274355e-134.55296212137178e-13
1800.9999999999986752.64976267581224e-121.32488133790612e-12
1810.9999999999965866.82905494067854e-123.41452747033927e-12
1820.9999999999908521.82960237806814e-119.1480118903407e-12
1830.9999999999811733.76533815510012e-111.88266907755006e-11
1840.9999999999787854.24309506734159e-112.1215475336708e-11
1850.9999999999493731.01254525263782e-105.0627262631891e-11
1860.9999999998664282.6714326299691e-101.33571631498455e-10
1870.9999999997337715.32457471815593e-102.66228735907797e-10
1880.9999999994253941.14921183862153e-095.74605919310764e-10
1890.9999999988089762.38204789478232e-091.19102394739116e-09
1900.9999999971914895.61702261838872e-092.80851130919436e-09
1910.9999999938844891.22310225349903e-086.11551126749515e-09
1920.9999999853476622.9304675021176e-081.4652337510588e-08
1930.9999999692372356.15255294710317e-083.07627647355159e-08
1940.9999999525473979.49052052057443e-084.74526026028722e-08
1950.999999941666881.16666239722421e-075.83331198612104e-08
1960.9999999785077844.29844317722309e-082.14922158861154e-08
1970.9999999790717994.18564024557405e-082.09282012278702e-08
1980.999999983516073.2967860557475e-081.64839302787375e-08
1990.9999999563985898.72028211377498e-084.36014105688749e-08
2000.9999998512045662.97590868011708e-071.48795434005854e-07
2010.9999995042162669.91567467050206e-074.95783733525103e-07
2020.9999981807784433.63844311385722e-061.81922155692861e-06
2030.9999928814817131.42370365746042e-057.11851828730211e-06
2040.9999715956891995.68086216012784e-052.84043108006392e-05
2050.9998880158296370.0002239683407269020.000111984170363451
2060.9996089984659930.0007820030680133320.000391001534006666
2070.9989365810439570.002126837912086370.00106341895604319
2080.9996695351249180.0006609297501636180.000330464875081809
2090.9987985459348670.002402908130266040.00120145406513302
2100.9963536021083760.007292795783248450.00364639789162423
2110.9860259575029480.02794808499410390.013974042497052

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
15 & 0.00321408279692246 & 0.00642816559384491 & 0.996785917203078 \tabularnewline
16 & 0.000580904124110585 & 0.00116180824822117 & 0.999419095875889 \tabularnewline
17 & 8.33192906727799e-05 & 0.00016663858134556 & 0.999916680709327 \tabularnewline
18 & 2.24320391987139e-05 & 4.48640783974278e-05 & 0.999977567960801 \tabularnewline
19 & 1.62365511298039e-05 & 3.24731022596079e-05 & 0.99998376344887 \tabularnewline
20 & 7.84017749368523e-06 & 1.56803549873705e-05 & 0.999992159822506 \tabularnewline
21 & 3.23194055709347e-06 & 6.46388111418694e-06 & 0.999996768059443 \tabularnewline
22 & 1.98855754924142e-06 & 3.97711509848285e-06 & 0.999998011442451 \tabularnewline
23 & 6.00182685004751e-07 & 1.2003653700095e-06 & 0.999999399817315 \tabularnewline
24 & 1.79063813953498e-07 & 3.58127627906995e-07 & 0.999999820936186 \tabularnewline
25 & 1.42604294813192e-07 & 2.85208589626384e-07 & 0.999999857395705 \tabularnewline
26 & 6.72516286206954e-08 & 1.34503257241391e-07 & 0.999999932748371 \tabularnewline
27 & 9.87840118560296e-08 & 1.97568023712059e-07 & 0.999999901215988 \tabularnewline
28 & 5.07610432865555e-08 & 1.01522086573111e-07 & 0.999999949238957 \tabularnewline
29 & 4.59364808244541e-08 & 9.18729616489083e-08 & 0.999999954063519 \tabularnewline
30 & 3.39618745958181e-08 & 6.79237491916361e-08 & 0.999999966038125 \tabularnewline
31 & 3.55713182729495e-08 & 7.1142636545899e-08 & 0.999999964428682 \tabularnewline
32 & 2.39768214479008e-08 & 4.79536428958016e-08 & 0.999999976023179 \tabularnewline
33 & 2.33734809290997e-08 & 4.67469618581993e-08 & 0.999999976626519 \tabularnewline
34 & 1.96004109947736e-08 & 3.92008219895473e-08 & 0.999999980399589 \tabularnewline
35 & 1.37506847574094e-08 & 2.75013695148188e-08 & 0.999999986249315 \tabularnewline
36 & 8.52948808735969e-09 & 1.70589761747194e-08 & 0.999999991470512 \tabularnewline
37 & 9.32575675986758e-09 & 1.86515135197352e-08 & 0.999999990674243 \tabularnewline
38 & 7.53229572615374e-09 & 1.50645914523075e-08 & 0.999999992467704 \tabularnewline
39 & 1.27487697688301e-08 & 2.54975395376602e-08 & 0.99999998725123 \tabularnewline
40 & 1.5208005162347e-08 & 3.04160103246941e-08 & 0.999999984791995 \tabularnewline
41 & 1.81097108322167e-08 & 3.62194216644334e-08 & 0.999999981890289 \tabularnewline
42 & 2.00673743416012e-08 & 4.01347486832023e-08 & 0.999999979932626 \tabularnewline
43 & 2.6940392770561e-08 & 5.3880785541122e-08 & 0.999999973059607 \tabularnewline
44 & 3.34348183324675e-08 & 6.6869636664935e-08 & 0.999999966565182 \tabularnewline
45 & 4.54614575592149e-08 & 9.09229151184298e-08 & 0.999999954538542 \tabularnewline
46 & 7.546451363033e-08 & 1.5092902726066e-07 & 0.999999924535486 \tabularnewline
47 & 8.53440109787702e-08 & 1.7068802195754e-07 & 0.999999914655989 \tabularnewline
48 & 9.24851551011338e-08 & 1.84970310202268e-07 & 0.999999907514845 \tabularnewline
49 & 1.13561907454175e-07 & 2.27123814908351e-07 & 0.999999886438093 \tabularnewline
50 & 1.67109035671549e-07 & 3.34218071343098e-07 & 0.999999832890964 \tabularnewline
51 & 4.65948748126866e-07 & 9.31897496253732e-07 & 0.999999534051252 \tabularnewline
52 & 7.51150436123761e-07 & 1.50230087224752e-06 & 0.999999248849564 \tabularnewline
53 & 1.81880909647838e-06 & 3.63761819295676e-06 & 0.999998181190904 \tabularnewline
54 & 4.46504359604458e-06 & 8.93008719208917e-06 & 0.999995534956404 \tabularnewline
55 & 1.09236134596432e-05 & 2.18472269192864e-05 & 0.99998907638654 \tabularnewline
56 & 2.64829264572829e-05 & 5.29658529145658e-05 & 0.999973517073543 \tabularnewline
57 & 6.10661400723277e-05 & 0.000122132280144655 & 0.999938933859928 \tabularnewline
58 & 0.000160508676572051 & 0.000321017353144103 & 0.999839491323428 \tabularnewline
59 & 0.00029280742891555 & 0.0005856148578311 & 0.999707192571084 \tabularnewline
60 & 0.000461361138729391 & 0.000922722277458783 & 0.999538638861271 \tabularnewline
61 & 0.000710567602179672 & 0.00142113520435934 & 0.99928943239782 \tabularnewline
62 & 0.00127492310847008 & 0.00254984621694017 & 0.99872507689153 \tabularnewline
63 & 0.00343174097789379 & 0.00686348195578758 & 0.996568259022106 \tabularnewline
64 & 0.00749780807613535 & 0.0149956161522707 & 0.992502191923865 \tabularnewline
65 & 0.019089558834431 & 0.038179117668862 & 0.980910441165569 \tabularnewline
66 & 0.0411079412543425 & 0.082215882508685 & 0.958892058745658 \tabularnewline
67 & 0.0980596537271647 & 0.196119307454329 & 0.901940346272835 \tabularnewline
68 & 0.187176782201775 & 0.374353564403551 & 0.812823217798225 \tabularnewline
69 & 0.281211711174692 & 0.562423422349384 & 0.718788288825308 \tabularnewline
70 & 0.418030740748856 & 0.836061481497711 & 0.581969259251144 \tabularnewline
71 & 0.509943975963829 & 0.980112048072343 & 0.490056024036171 \tabularnewline
72 & 0.57527025039286 & 0.849459499214281 & 0.42472974960714 \tabularnewline
73 & 0.644405875661347 & 0.711188248677305 & 0.355594124338653 \tabularnewline
74 & 0.72001078842106 & 0.559978423157881 & 0.27998921157894 \tabularnewline
75 & 0.805981720116909 & 0.388036559766181 & 0.194018279883091 \tabularnewline
76 & 0.869902627737464 & 0.260194744525072 & 0.130097372262536 \tabularnewline
77 & 0.929865090156728 & 0.140269819686545 & 0.0701349098432724 \tabularnewline
78 & 0.964036709783259 & 0.0719265804334813 & 0.0359632902167407 \tabularnewline
79 & 0.987576456371809 & 0.0248470872563817 & 0.0124235436281909 \tabularnewline
80 & 0.995889538460829 & 0.00822092307834285 & 0.00411046153917142 \tabularnewline
81 & 0.998349374345014 & 0.00330125130997128 & 0.00165062565498564 \tabularnewline
82 & 0.999445597137657 & 0.00110880572468622 & 0.000554402862343108 \tabularnewline
83 & 0.999692530656994 & 0.000614938686012257 & 0.000307469343006129 \tabularnewline
84 & 0.999810562798759 & 0.000378874402482732 & 0.000189437201241366 \tabularnewline
85 & 0.999887329394138 & 0.000225341211724602 & 0.000112670605862301 \tabularnewline
86 & 0.999936781605185 & 0.000126436789630416 & 6.32183948152081e-05 \tabularnewline
87 & 0.99997243181802 & 5.51363639596626e-05 & 2.75681819798313e-05 \tabularnewline
88 & 0.999988755343707 & 2.2489312585572e-05 & 1.1244656292786e-05 \tabularnewline
89 & 0.999996909914043 & 6.18017191362799e-06 & 3.090085956814e-06 \tabularnewline
90 & 0.999999161963821 & 1.67607235733595e-06 & 8.38036178667973e-07 \tabularnewline
91 & 0.999999889357469 & 2.2128506214475e-07 & 1.10642531072375e-07 \tabularnewline
92 & 0.999999979481367 & 4.10372654921301e-08 & 2.0518632746065e-08 \tabularnewline
93 & 0.99999999426209 & 1.14758199665729e-08 & 5.73790998328647e-09 \tabularnewline
94 & 0.999999998514074 & 2.97185207871158e-09 & 1.48592603935579e-09 \tabularnewline
95 & 0.999999999157734 & 1.68453114063648e-09 & 8.42265570318242e-10 \tabularnewline
96 & 0.999999999545648 & 9.08703560134523e-10 & 4.54351780067262e-10 \tabularnewline
97 & 0.999999999722102 & 5.55795729523788e-10 & 2.77897864761894e-10 \tabularnewline
98 & 0.999999999828387 & 3.43225717390878e-10 & 1.71612858695439e-10 \tabularnewline
99 & 0.99999999991607 & 1.67859663150074e-10 & 8.39298315750372e-11 \tabularnewline
100 & 0.999999999961542 & 7.69157415877485e-11 & 3.84578707938743e-11 \tabularnewline
101 & 0.999999999987456 & 2.50887101722607e-11 & 1.25443550861303e-11 \tabularnewline
102 & 0.999999999995807 & 8.38597348926947e-12 & 4.19298674463474e-12 \tabularnewline
103 & 0.999999999999219 & 1.56259234175527e-12 & 7.81296170877635e-13 \tabularnewline
104 & 0.999999999999786 & 4.28172553011039e-13 & 2.14086276505519e-13 \tabularnewline
105 & 0.999999999999902 & 1.96362715752326e-13 & 9.81813578761628e-14 \tabularnewline
106 & 0.999999999999956 & 8.82731436529324e-14 & 4.41365718264662e-14 \tabularnewline
107 & 0.999999999999961 & 7.84968712351288e-14 & 3.92484356175644e-14 \tabularnewline
108 & 0.999999999999966 & 6.7359441251425e-14 & 3.36797206257125e-14 \tabularnewline
109 & 0.999999999999969 & 6.26598566550148e-14 & 3.13299283275074e-14 \tabularnewline
110 & 0.99999999999997 & 5.94897996395914e-14 & 2.97448998197957e-14 \tabularnewline
111 & 0.999999999999976 & 4.87810247705015e-14 & 2.43905123852508e-14 \tabularnewline
112 & 0.999999999999981 & 3.81094098942739e-14 & 1.90547049471369e-14 \tabularnewline
113 & 0.99999999999999 & 2.07295489820151e-14 & 1.03647744910076e-14 \tabularnewline
114 & 0.999999999999994 & 1.2673502382123e-14 & 6.33675119106151e-15 \tabularnewline
115 & 0.999999999999998 & 4.57684253707693e-15 & 2.28842126853846e-15 \tabularnewline
116 & 0.999999999999999 & 2.28283452730965e-15 & 1.14141726365483e-15 \tabularnewline
117 & 1 & 9.44421835371906e-16 & 4.72210917685953e-16 \tabularnewline
118 & 1 & 7.58187545857761e-17 & 3.79093772928881e-17 \tabularnewline
119 & 1 & 4.2190333110369e-17 & 2.10951665551845e-17 \tabularnewline
120 & 1 & 2.6010703623492e-17 & 1.3005351811746e-17 \tabularnewline
121 & 1 & 2.24114128024208e-17 & 1.12057064012104e-17 \tabularnewline
122 & 1 & 2.57834784992093e-17 & 1.28917392496046e-17 \tabularnewline
123 & 1 & 2.92862486931293e-17 & 1.46431243465647e-17 \tabularnewline
124 & 1 & 3.15373070358726e-17 & 1.57686535179363e-17 \tabularnewline
125 & 1 & 2.34237913642465e-17 & 1.17118956821232e-17 \tabularnewline
126 & 1 & 1.72135211829356e-17 & 8.60676059146778e-18 \tabularnewline
127 & 1 & 6.75753674617669e-18 & 3.37876837308834e-18 \tabularnewline
128 & 1 & 4.27283169397646e-18 & 2.13641584698823e-18 \tabularnewline
129 & 1 & 4.03117147726347e-18 & 2.01558573863174e-18 \tabularnewline
130 & 1 & 2.57543154143836e-18 & 1.28771577071918e-18 \tabularnewline
131 & 1 & 2.89112799686356e-18 & 1.44556399843178e-18 \tabularnewline
132 & 1 & 3.70712059591876e-18 & 1.85356029795938e-18 \tabularnewline
133 & 1 & 5.1819039516464e-18 & 2.5909519758232e-18 \tabularnewline
134 & 1 & 7.64286114881726e-18 & 3.82143057440863e-18 \tabularnewline
135 & 1 & 6.14445427426408e-18 & 3.07222713713204e-18 \tabularnewline
136 & 1 & 1.63324146065665e-18 & 8.16620730328327e-19 \tabularnewline
137 & 1 & 1.34088724536135e-19 & 6.70443622680674e-20 \tabularnewline
138 & 1 & 3.73910958902742e-20 & 1.86955479451371e-20 \tabularnewline
139 & 1 & 5.11016310620414e-21 & 2.55508155310207e-21 \tabularnewline
140 & 1 & 1.0669169759278e-21 & 5.33458487963898e-22 \tabularnewline
141 & 1 & 3.95641087602883e-22 & 1.97820543801442e-22 \tabularnewline
142 & 1 & 1.92976726944899e-22 & 9.64883634724495e-23 \tabularnewline
143 & 1 & 2.36001247816444e-22 & 1.18000623908222e-22 \tabularnewline
144 & 1 & 2.54966017883831e-22 & 1.27483008941916e-22 \tabularnewline
145 & 1 & 3.0873657708735e-22 & 1.54368288543675e-22 \tabularnewline
146 & 1 & 7.17873863939009e-22 & 3.58936931969504e-22 \tabularnewline
147 & 1 & 1.19472137887644e-21 & 5.97360689438221e-22 \tabularnewline
148 & 1 & 2.1500439845014e-21 & 1.0750219922507e-21 \tabularnewline
149 & 1 & 1.89313141783834e-21 & 9.46565708919169e-22 \tabularnewline
150 & 1 & 1.54419111368885e-21 & 7.72095556844423e-22 \tabularnewline
151 & 1 & 7.63015120313447e-22 & 3.81507560156724e-22 \tabularnewline
152 & 1 & 4.26500346329048e-22 & 2.13250173164524e-22 \tabularnewline
153 & 1 & 3.98672550070163e-22 & 1.99336275035082e-22 \tabularnewline
154 & 1 & 4.03178846448787e-22 & 2.01589423224393e-22 \tabularnewline
155 & 1 & 7.78843257001181e-22 & 3.8942162850059e-22 \tabularnewline
156 & 1 & 1.31569153644654e-21 & 6.5784576822327e-22 \tabularnewline
157 & 1 & 3.54226728049919e-21 & 1.7711336402496e-21 \tabularnewline
158 & 1 & 9.85599898197116e-21 & 4.92799949098558e-21 \tabularnewline
159 & 1 & 1.79390441386844e-20 & 8.96952206934221e-21 \tabularnewline
160 & 1 & 4.43171983218074e-20 & 2.21585991609037e-20 \tabularnewline
161 & 1 & 9.64270916732285e-20 & 4.82135458366143e-20 \tabularnewline
162 & 1 & 1.5565131533459e-19 & 7.78256576672951e-20 \tabularnewline
163 & 1 & 2.2104968360355e-19 & 1.10524841801775e-19 \tabularnewline
164 & 1 & 3.54572894126223e-19 & 1.77286447063112e-19 \tabularnewline
165 & 1 & 8.80296453935652e-19 & 4.40148226967826e-19 \tabularnewline
166 & 1 & 1.93616282990809e-18 & 9.68081414954044e-19 \tabularnewline
167 & 1 & 5.45171275810198e-18 & 2.72585637905099e-18 \tabularnewline
168 & 1 & 1.41441020557406e-17 & 7.07205102787031e-18 \tabularnewline
169 & 1 & 4.45145574715206e-17 & 2.22572787357603e-17 \tabularnewline
170 & 1 & 1.36386312431791e-16 & 6.81931562158954e-17 \tabularnewline
171 & 1 & 3.69873483593704e-16 & 1.84936741796852e-16 \tabularnewline
172 & 1 & 7.61199039834041e-16 & 3.8059951991702e-16 \tabularnewline
173 & 0.999999999999999 & 2.09581140126466e-15 & 1.04790570063233e-15 \tabularnewline
174 & 0.999999999999997 & 5.38459849970345e-15 & 2.69229924985172e-15 \tabularnewline
175 & 0.999999999999993 & 1.38428280092745e-14 & 6.92141400463725e-15 \tabularnewline
176 & 0.999999999999981 & 3.74937340031499e-14 & 1.87468670015749e-14 \tabularnewline
177 & 0.999999999999947 & 1.05655575083673e-13 & 5.28277875418366e-14 \tabularnewline
178 & 0.99999999999985 & 3.00844544881433e-13 & 1.50422272440717e-13 \tabularnewline
179 & 0.999999999999545 & 9.10592424274355e-13 & 4.55296212137178e-13 \tabularnewline
180 & 0.999999999998675 & 2.64976267581224e-12 & 1.32488133790612e-12 \tabularnewline
181 & 0.999999999996586 & 6.82905494067854e-12 & 3.41452747033927e-12 \tabularnewline
182 & 0.999999999990852 & 1.82960237806814e-11 & 9.1480118903407e-12 \tabularnewline
183 & 0.999999999981173 & 3.76533815510012e-11 & 1.88266907755006e-11 \tabularnewline
184 & 0.999999999978785 & 4.24309506734159e-11 & 2.1215475336708e-11 \tabularnewline
185 & 0.999999999949373 & 1.01254525263782e-10 & 5.0627262631891e-11 \tabularnewline
186 & 0.999999999866428 & 2.6714326299691e-10 & 1.33571631498455e-10 \tabularnewline
187 & 0.999999999733771 & 5.32457471815593e-10 & 2.66228735907797e-10 \tabularnewline
188 & 0.999999999425394 & 1.14921183862153e-09 & 5.74605919310764e-10 \tabularnewline
189 & 0.999999998808976 & 2.38204789478232e-09 & 1.19102394739116e-09 \tabularnewline
190 & 0.999999997191489 & 5.61702261838872e-09 & 2.80851130919436e-09 \tabularnewline
191 & 0.999999993884489 & 1.22310225349903e-08 & 6.11551126749515e-09 \tabularnewline
192 & 0.999999985347662 & 2.9304675021176e-08 & 1.4652337510588e-08 \tabularnewline
193 & 0.999999969237235 & 6.15255294710317e-08 & 3.07627647355159e-08 \tabularnewline
194 & 0.999999952547397 & 9.49052052057443e-08 & 4.74526026028722e-08 \tabularnewline
195 & 0.99999994166688 & 1.16666239722421e-07 & 5.83331198612104e-08 \tabularnewline
196 & 0.999999978507784 & 4.29844317722309e-08 & 2.14922158861154e-08 \tabularnewline
197 & 0.999999979071799 & 4.18564024557405e-08 & 2.09282012278702e-08 \tabularnewline
198 & 0.99999998351607 & 3.2967860557475e-08 & 1.64839302787375e-08 \tabularnewline
199 & 0.999999956398589 & 8.72028211377498e-08 & 4.36014105688749e-08 \tabularnewline
200 & 0.999999851204566 & 2.97590868011708e-07 & 1.48795434005854e-07 \tabularnewline
201 & 0.999999504216266 & 9.91567467050206e-07 & 4.95783733525103e-07 \tabularnewline
202 & 0.999998180778443 & 3.63844311385722e-06 & 1.81922155692861e-06 \tabularnewline
203 & 0.999992881481713 & 1.42370365746042e-05 & 7.11851828730211e-06 \tabularnewline
204 & 0.999971595689199 & 5.68086216012784e-05 & 2.84043108006392e-05 \tabularnewline
205 & 0.999888015829637 & 0.000223968340726902 & 0.000111984170363451 \tabularnewline
206 & 0.999608998465993 & 0.000782003068013332 & 0.000391001534006666 \tabularnewline
207 & 0.998936581043957 & 0.00212683791208637 & 0.00106341895604319 \tabularnewline
208 & 0.999669535124918 & 0.000660929750163618 & 0.000330464875081809 \tabularnewline
209 & 0.998798545934867 & 0.00240290813026604 & 0.00120145406513302 \tabularnewline
210 & 0.996353602108376 & 0.00729279578324845 & 0.00364639789162423 \tabularnewline
211 & 0.986025957502948 & 0.0279480849941039 & 0.013974042497052 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148475&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]15[/C][C]0.00321408279692246[/C][C]0.00642816559384491[/C][C]0.996785917203078[/C][/ROW]
[ROW][C]16[/C][C]0.000580904124110585[/C][C]0.00116180824822117[/C][C]0.999419095875889[/C][/ROW]
[ROW][C]17[/C][C]8.33192906727799e-05[/C][C]0.00016663858134556[/C][C]0.999916680709327[/C][/ROW]
[ROW][C]18[/C][C]2.24320391987139e-05[/C][C]4.48640783974278e-05[/C][C]0.999977567960801[/C][/ROW]
[ROW][C]19[/C][C]1.62365511298039e-05[/C][C]3.24731022596079e-05[/C][C]0.99998376344887[/C][/ROW]
[ROW][C]20[/C][C]7.84017749368523e-06[/C][C]1.56803549873705e-05[/C][C]0.999992159822506[/C][/ROW]
[ROW][C]21[/C][C]3.23194055709347e-06[/C][C]6.46388111418694e-06[/C][C]0.999996768059443[/C][/ROW]
[ROW][C]22[/C][C]1.98855754924142e-06[/C][C]3.97711509848285e-06[/C][C]0.999998011442451[/C][/ROW]
[ROW][C]23[/C][C]6.00182685004751e-07[/C][C]1.2003653700095e-06[/C][C]0.999999399817315[/C][/ROW]
[ROW][C]24[/C][C]1.79063813953498e-07[/C][C]3.58127627906995e-07[/C][C]0.999999820936186[/C][/ROW]
[ROW][C]25[/C][C]1.42604294813192e-07[/C][C]2.85208589626384e-07[/C][C]0.999999857395705[/C][/ROW]
[ROW][C]26[/C][C]6.72516286206954e-08[/C][C]1.34503257241391e-07[/C][C]0.999999932748371[/C][/ROW]
[ROW][C]27[/C][C]9.87840118560296e-08[/C][C]1.97568023712059e-07[/C][C]0.999999901215988[/C][/ROW]
[ROW][C]28[/C][C]5.07610432865555e-08[/C][C]1.01522086573111e-07[/C][C]0.999999949238957[/C][/ROW]
[ROW][C]29[/C][C]4.59364808244541e-08[/C][C]9.18729616489083e-08[/C][C]0.999999954063519[/C][/ROW]
[ROW][C]30[/C][C]3.39618745958181e-08[/C][C]6.79237491916361e-08[/C][C]0.999999966038125[/C][/ROW]
[ROW][C]31[/C][C]3.55713182729495e-08[/C][C]7.1142636545899e-08[/C][C]0.999999964428682[/C][/ROW]
[ROW][C]32[/C][C]2.39768214479008e-08[/C][C]4.79536428958016e-08[/C][C]0.999999976023179[/C][/ROW]
[ROW][C]33[/C][C]2.33734809290997e-08[/C][C]4.67469618581993e-08[/C][C]0.999999976626519[/C][/ROW]
[ROW][C]34[/C][C]1.96004109947736e-08[/C][C]3.92008219895473e-08[/C][C]0.999999980399589[/C][/ROW]
[ROW][C]35[/C][C]1.37506847574094e-08[/C][C]2.75013695148188e-08[/C][C]0.999999986249315[/C][/ROW]
[ROW][C]36[/C][C]8.52948808735969e-09[/C][C]1.70589761747194e-08[/C][C]0.999999991470512[/C][/ROW]
[ROW][C]37[/C][C]9.32575675986758e-09[/C][C]1.86515135197352e-08[/C][C]0.999999990674243[/C][/ROW]
[ROW][C]38[/C][C]7.53229572615374e-09[/C][C]1.50645914523075e-08[/C][C]0.999999992467704[/C][/ROW]
[ROW][C]39[/C][C]1.27487697688301e-08[/C][C]2.54975395376602e-08[/C][C]0.99999998725123[/C][/ROW]
[ROW][C]40[/C][C]1.5208005162347e-08[/C][C]3.04160103246941e-08[/C][C]0.999999984791995[/C][/ROW]
[ROW][C]41[/C][C]1.81097108322167e-08[/C][C]3.62194216644334e-08[/C][C]0.999999981890289[/C][/ROW]
[ROW][C]42[/C][C]2.00673743416012e-08[/C][C]4.01347486832023e-08[/C][C]0.999999979932626[/C][/ROW]
[ROW][C]43[/C][C]2.6940392770561e-08[/C][C]5.3880785541122e-08[/C][C]0.999999973059607[/C][/ROW]
[ROW][C]44[/C][C]3.34348183324675e-08[/C][C]6.6869636664935e-08[/C][C]0.999999966565182[/C][/ROW]
[ROW][C]45[/C][C]4.54614575592149e-08[/C][C]9.09229151184298e-08[/C][C]0.999999954538542[/C][/ROW]
[ROW][C]46[/C][C]7.546451363033e-08[/C][C]1.5092902726066e-07[/C][C]0.999999924535486[/C][/ROW]
[ROW][C]47[/C][C]8.53440109787702e-08[/C][C]1.7068802195754e-07[/C][C]0.999999914655989[/C][/ROW]
[ROW][C]48[/C][C]9.24851551011338e-08[/C][C]1.84970310202268e-07[/C][C]0.999999907514845[/C][/ROW]
[ROW][C]49[/C][C]1.13561907454175e-07[/C][C]2.27123814908351e-07[/C][C]0.999999886438093[/C][/ROW]
[ROW][C]50[/C][C]1.67109035671549e-07[/C][C]3.34218071343098e-07[/C][C]0.999999832890964[/C][/ROW]
[ROW][C]51[/C][C]4.65948748126866e-07[/C][C]9.31897496253732e-07[/C][C]0.999999534051252[/C][/ROW]
[ROW][C]52[/C][C]7.51150436123761e-07[/C][C]1.50230087224752e-06[/C][C]0.999999248849564[/C][/ROW]
[ROW][C]53[/C][C]1.81880909647838e-06[/C][C]3.63761819295676e-06[/C][C]0.999998181190904[/C][/ROW]
[ROW][C]54[/C][C]4.46504359604458e-06[/C][C]8.93008719208917e-06[/C][C]0.999995534956404[/C][/ROW]
[ROW][C]55[/C][C]1.09236134596432e-05[/C][C]2.18472269192864e-05[/C][C]0.99998907638654[/C][/ROW]
[ROW][C]56[/C][C]2.64829264572829e-05[/C][C]5.29658529145658e-05[/C][C]0.999973517073543[/C][/ROW]
[ROW][C]57[/C][C]6.10661400723277e-05[/C][C]0.000122132280144655[/C][C]0.999938933859928[/C][/ROW]
[ROW][C]58[/C][C]0.000160508676572051[/C][C]0.000321017353144103[/C][C]0.999839491323428[/C][/ROW]
[ROW][C]59[/C][C]0.00029280742891555[/C][C]0.0005856148578311[/C][C]0.999707192571084[/C][/ROW]
[ROW][C]60[/C][C]0.000461361138729391[/C][C]0.000922722277458783[/C][C]0.999538638861271[/C][/ROW]
[ROW][C]61[/C][C]0.000710567602179672[/C][C]0.00142113520435934[/C][C]0.99928943239782[/C][/ROW]
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[ROW][C]63[/C][C]0.00343174097789379[/C][C]0.00686348195578758[/C][C]0.996568259022106[/C][/ROW]
[ROW][C]64[/C][C]0.00749780807613535[/C][C]0.0149956161522707[/C][C]0.992502191923865[/C][/ROW]
[ROW][C]65[/C][C]0.019089558834431[/C][C]0.038179117668862[/C][C]0.980910441165569[/C][/ROW]
[ROW][C]66[/C][C]0.0411079412543425[/C][C]0.082215882508685[/C][C]0.958892058745658[/C][/ROW]
[ROW][C]67[/C][C]0.0980596537271647[/C][C]0.196119307454329[/C][C]0.901940346272835[/C][/ROW]
[ROW][C]68[/C][C]0.187176782201775[/C][C]0.374353564403551[/C][C]0.812823217798225[/C][/ROW]
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[ROW][C]80[/C][C]0.995889538460829[/C][C]0.00822092307834285[/C][C]0.00411046153917142[/C][/ROW]
[ROW][C]81[/C][C]0.998349374345014[/C][C]0.00330125130997128[/C][C]0.00165062565498564[/C][/ROW]
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[ROW][C]83[/C][C]0.999692530656994[/C][C]0.000614938686012257[/C][C]0.000307469343006129[/C][/ROW]
[ROW][C]84[/C][C]0.999810562798759[/C][C]0.000378874402482732[/C][C]0.000189437201241366[/C][/ROW]
[ROW][C]85[/C][C]0.999887329394138[/C][C]0.000225341211724602[/C][C]0.000112670605862301[/C][/ROW]
[ROW][C]86[/C][C]0.999936781605185[/C][C]0.000126436789630416[/C][C]6.32183948152081e-05[/C][/ROW]
[ROW][C]87[/C][C]0.99997243181802[/C][C]5.51363639596626e-05[/C][C]2.75681819798313e-05[/C][/ROW]
[ROW][C]88[/C][C]0.999988755343707[/C][C]2.2489312585572e-05[/C][C]1.1244656292786e-05[/C][/ROW]
[ROW][C]89[/C][C]0.999996909914043[/C][C]6.18017191362799e-06[/C][C]3.090085956814e-06[/C][/ROW]
[ROW][C]90[/C][C]0.999999161963821[/C][C]1.67607235733595e-06[/C][C]8.38036178667973e-07[/C][/ROW]
[ROW][C]91[/C][C]0.999999889357469[/C][C]2.2128506214475e-07[/C][C]1.10642531072375e-07[/C][/ROW]
[ROW][C]92[/C][C]0.999999979481367[/C][C]4.10372654921301e-08[/C][C]2.0518632746065e-08[/C][/ROW]
[ROW][C]93[/C][C]0.99999999426209[/C][C]1.14758199665729e-08[/C][C]5.73790998328647e-09[/C][/ROW]
[ROW][C]94[/C][C]0.999999998514074[/C][C]2.97185207871158e-09[/C][C]1.48592603935579e-09[/C][/ROW]
[ROW][C]95[/C][C]0.999999999157734[/C][C]1.68453114063648e-09[/C][C]8.42265570318242e-10[/C][/ROW]
[ROW][C]96[/C][C]0.999999999545648[/C][C]9.08703560134523e-10[/C][C]4.54351780067262e-10[/C][/ROW]
[ROW][C]97[/C][C]0.999999999722102[/C][C]5.55795729523788e-10[/C][C]2.77897864761894e-10[/C][/ROW]
[ROW][C]98[/C][C]0.999999999828387[/C][C]3.43225717390878e-10[/C][C]1.71612858695439e-10[/C][/ROW]
[ROW][C]99[/C][C]0.99999999991607[/C][C]1.67859663150074e-10[/C][C]8.39298315750372e-11[/C][/ROW]
[ROW][C]100[/C][C]0.999999999961542[/C][C]7.69157415877485e-11[/C][C]3.84578707938743e-11[/C][/ROW]
[ROW][C]101[/C][C]0.999999999987456[/C][C]2.50887101722607e-11[/C][C]1.25443550861303e-11[/C][/ROW]
[ROW][C]102[/C][C]0.999999999995807[/C][C]8.38597348926947e-12[/C][C]4.19298674463474e-12[/C][/ROW]
[ROW][C]103[/C][C]0.999999999999219[/C][C]1.56259234175527e-12[/C][C]7.81296170877635e-13[/C][/ROW]
[ROW][C]104[/C][C]0.999999999999786[/C][C]4.28172553011039e-13[/C][C]2.14086276505519e-13[/C][/ROW]
[ROW][C]105[/C][C]0.999999999999902[/C][C]1.96362715752326e-13[/C][C]9.81813578761628e-14[/C][/ROW]
[ROW][C]106[/C][C]0.999999999999956[/C][C]8.82731436529324e-14[/C][C]4.41365718264662e-14[/C][/ROW]
[ROW][C]107[/C][C]0.999999999999961[/C][C]7.84968712351288e-14[/C][C]3.92484356175644e-14[/C][/ROW]
[ROW][C]108[/C][C]0.999999999999966[/C][C]6.7359441251425e-14[/C][C]3.36797206257125e-14[/C][/ROW]
[ROW][C]109[/C][C]0.999999999999969[/C][C]6.26598566550148e-14[/C][C]3.13299283275074e-14[/C][/ROW]
[ROW][C]110[/C][C]0.99999999999997[/C][C]5.94897996395914e-14[/C][C]2.97448998197957e-14[/C][/ROW]
[ROW][C]111[/C][C]0.999999999999976[/C][C]4.87810247705015e-14[/C][C]2.43905123852508e-14[/C][/ROW]
[ROW][C]112[/C][C]0.999999999999981[/C][C]3.81094098942739e-14[/C][C]1.90547049471369e-14[/C][/ROW]
[ROW][C]113[/C][C]0.99999999999999[/C][C]2.07295489820151e-14[/C][C]1.03647744910076e-14[/C][/ROW]
[ROW][C]114[/C][C]0.999999999999994[/C][C]1.2673502382123e-14[/C][C]6.33675119106151e-15[/C][/ROW]
[ROW][C]115[/C][C]0.999999999999998[/C][C]4.57684253707693e-15[/C][C]2.28842126853846e-15[/C][/ROW]
[ROW][C]116[/C][C]0.999999999999999[/C][C]2.28283452730965e-15[/C][C]1.14141726365483e-15[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]9.44421835371906e-16[/C][C]4.72210917685953e-16[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]7.58187545857761e-17[/C][C]3.79093772928881e-17[/C][/ROW]
[ROW][C]119[/C][C]1[/C][C]4.2190333110369e-17[/C][C]2.10951665551845e-17[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]2.6010703623492e-17[/C][C]1.3005351811746e-17[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]2.24114128024208e-17[/C][C]1.12057064012104e-17[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]2.57834784992093e-17[/C][C]1.28917392496046e-17[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]2.92862486931293e-17[/C][C]1.46431243465647e-17[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]3.15373070358726e-17[/C][C]1.57686535179363e-17[/C][/ROW]
[ROW][C]125[/C][C]1[/C][C]2.34237913642465e-17[/C][C]1.17118956821232e-17[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]1.72135211829356e-17[/C][C]8.60676059146778e-18[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]6.75753674617669e-18[/C][C]3.37876837308834e-18[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]4.27283169397646e-18[/C][C]2.13641584698823e-18[/C][/ROW]
[ROW][C]129[/C][C]1[/C][C]4.03117147726347e-18[/C][C]2.01558573863174e-18[/C][/ROW]
[ROW][C]130[/C][C]1[/C][C]2.57543154143836e-18[/C][C]1.28771577071918e-18[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]2.89112799686356e-18[/C][C]1.44556399843178e-18[/C][/ROW]
[ROW][C]132[/C][C]1[/C][C]3.70712059591876e-18[/C][C]1.85356029795938e-18[/C][/ROW]
[ROW][C]133[/C][C]1[/C][C]5.1819039516464e-18[/C][C]2.5909519758232e-18[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]7.64286114881726e-18[/C][C]3.82143057440863e-18[/C][/ROW]
[ROW][C]135[/C][C]1[/C][C]6.14445427426408e-18[/C][C]3.07222713713204e-18[/C][/ROW]
[ROW][C]136[/C][C]1[/C][C]1.63324146065665e-18[/C][C]8.16620730328327e-19[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]1.34088724536135e-19[/C][C]6.70443622680674e-20[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]3.73910958902742e-20[/C][C]1.86955479451371e-20[/C][/ROW]
[ROW][C]139[/C][C]1[/C][C]5.11016310620414e-21[/C][C]2.55508155310207e-21[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]1.0669169759278e-21[/C][C]5.33458487963898e-22[/C][/ROW]
[ROW][C]141[/C][C]1[/C][C]3.95641087602883e-22[/C][C]1.97820543801442e-22[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]1.92976726944899e-22[/C][C]9.64883634724495e-23[/C][/ROW]
[ROW][C]143[/C][C]1[/C][C]2.36001247816444e-22[/C][C]1.18000623908222e-22[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]2.54966017883831e-22[/C][C]1.27483008941916e-22[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]3.0873657708735e-22[/C][C]1.54368288543675e-22[/C][/ROW]
[ROW][C]146[/C][C]1[/C][C]7.17873863939009e-22[/C][C]3.58936931969504e-22[/C][/ROW]
[ROW][C]147[/C][C]1[/C][C]1.19472137887644e-21[/C][C]5.97360689438221e-22[/C][/ROW]
[ROW][C]148[/C][C]1[/C][C]2.1500439845014e-21[/C][C]1.0750219922507e-21[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]1.89313141783834e-21[/C][C]9.46565708919169e-22[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]1.54419111368885e-21[/C][C]7.72095556844423e-22[/C][/ROW]
[ROW][C]151[/C][C]1[/C][C]7.63015120313447e-22[/C][C]3.81507560156724e-22[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]4.26500346329048e-22[/C][C]2.13250173164524e-22[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]3.98672550070163e-22[/C][C]1.99336275035082e-22[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]4.03178846448787e-22[/C][C]2.01589423224393e-22[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]7.78843257001181e-22[/C][C]3.8942162850059e-22[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]1.31569153644654e-21[/C][C]6.5784576822327e-22[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]3.54226728049919e-21[/C][C]1.7711336402496e-21[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]9.85599898197116e-21[/C][C]4.92799949098558e-21[/C][/ROW]
[ROW][C]159[/C][C]1[/C][C]1.79390441386844e-20[/C][C]8.96952206934221e-21[/C][/ROW]
[ROW][C]160[/C][C]1[/C][C]4.43171983218074e-20[/C][C]2.21585991609037e-20[/C][/ROW]
[ROW][C]161[/C][C]1[/C][C]9.64270916732285e-20[/C][C]4.82135458366143e-20[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]1.5565131533459e-19[/C][C]7.78256576672951e-20[/C][/ROW]
[ROW][C]163[/C][C]1[/C][C]2.2104968360355e-19[/C][C]1.10524841801775e-19[/C][/ROW]
[ROW][C]164[/C][C]1[/C][C]3.54572894126223e-19[/C][C]1.77286447063112e-19[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]8.80296453935652e-19[/C][C]4.40148226967826e-19[/C][/ROW]
[ROW][C]166[/C][C]1[/C][C]1.93616282990809e-18[/C][C]9.68081414954044e-19[/C][/ROW]
[ROW][C]167[/C][C]1[/C][C]5.45171275810198e-18[/C][C]2.72585637905099e-18[/C][/ROW]
[ROW][C]168[/C][C]1[/C][C]1.41441020557406e-17[/C][C]7.07205102787031e-18[/C][/ROW]
[ROW][C]169[/C][C]1[/C][C]4.45145574715206e-17[/C][C]2.22572787357603e-17[/C][/ROW]
[ROW][C]170[/C][C]1[/C][C]1.36386312431791e-16[/C][C]6.81931562158954e-17[/C][/ROW]
[ROW][C]171[/C][C]1[/C][C]3.69873483593704e-16[/C][C]1.84936741796852e-16[/C][/ROW]
[ROW][C]172[/C][C]1[/C][C]7.61199039834041e-16[/C][C]3.8059951991702e-16[/C][/ROW]
[ROW][C]173[/C][C]0.999999999999999[/C][C]2.09581140126466e-15[/C][C]1.04790570063233e-15[/C][/ROW]
[ROW][C]174[/C][C]0.999999999999997[/C][C]5.38459849970345e-15[/C][C]2.69229924985172e-15[/C][/ROW]
[ROW][C]175[/C][C]0.999999999999993[/C][C]1.38428280092745e-14[/C][C]6.92141400463725e-15[/C][/ROW]
[ROW][C]176[/C][C]0.999999999999981[/C][C]3.74937340031499e-14[/C][C]1.87468670015749e-14[/C][/ROW]
[ROW][C]177[/C][C]0.999999999999947[/C][C]1.05655575083673e-13[/C][C]5.28277875418366e-14[/C][/ROW]
[ROW][C]178[/C][C]0.99999999999985[/C][C]3.00844544881433e-13[/C][C]1.50422272440717e-13[/C][/ROW]
[ROW][C]179[/C][C]0.999999999999545[/C][C]9.10592424274355e-13[/C][C]4.55296212137178e-13[/C][/ROW]
[ROW][C]180[/C][C]0.999999999998675[/C][C]2.64976267581224e-12[/C][C]1.32488133790612e-12[/C][/ROW]
[ROW][C]181[/C][C]0.999999999996586[/C][C]6.82905494067854e-12[/C][C]3.41452747033927e-12[/C][/ROW]
[ROW][C]182[/C][C]0.999999999990852[/C][C]1.82960237806814e-11[/C][C]9.1480118903407e-12[/C][/ROW]
[ROW][C]183[/C][C]0.999999999981173[/C][C]3.76533815510012e-11[/C][C]1.88266907755006e-11[/C][/ROW]
[ROW][C]184[/C][C]0.999999999978785[/C][C]4.24309506734159e-11[/C][C]2.1215475336708e-11[/C][/ROW]
[ROW][C]185[/C][C]0.999999999949373[/C][C]1.01254525263782e-10[/C][C]5.0627262631891e-11[/C][/ROW]
[ROW][C]186[/C][C]0.999999999866428[/C][C]2.6714326299691e-10[/C][C]1.33571631498455e-10[/C][/ROW]
[ROW][C]187[/C][C]0.999999999733771[/C][C]5.32457471815593e-10[/C][C]2.66228735907797e-10[/C][/ROW]
[ROW][C]188[/C][C]0.999999999425394[/C][C]1.14921183862153e-09[/C][C]5.74605919310764e-10[/C][/ROW]
[ROW][C]189[/C][C]0.999999998808976[/C][C]2.38204789478232e-09[/C][C]1.19102394739116e-09[/C][/ROW]
[ROW][C]190[/C][C]0.999999997191489[/C][C]5.61702261838872e-09[/C][C]2.80851130919436e-09[/C][/ROW]
[ROW][C]191[/C][C]0.999999993884489[/C][C]1.22310225349903e-08[/C][C]6.11551126749515e-09[/C][/ROW]
[ROW][C]192[/C][C]0.999999985347662[/C][C]2.9304675021176e-08[/C][C]1.4652337510588e-08[/C][/ROW]
[ROW][C]193[/C][C]0.999999969237235[/C][C]6.15255294710317e-08[/C][C]3.07627647355159e-08[/C][/ROW]
[ROW][C]194[/C][C]0.999999952547397[/C][C]9.49052052057443e-08[/C][C]4.74526026028722e-08[/C][/ROW]
[ROW][C]195[/C][C]0.99999994166688[/C][C]1.16666239722421e-07[/C][C]5.83331198612104e-08[/C][/ROW]
[ROW][C]196[/C][C]0.999999978507784[/C][C]4.29844317722309e-08[/C][C]2.14922158861154e-08[/C][/ROW]
[ROW][C]197[/C][C]0.999999979071799[/C][C]4.18564024557405e-08[/C][C]2.09282012278702e-08[/C][/ROW]
[ROW][C]198[/C][C]0.99999998351607[/C][C]3.2967860557475e-08[/C][C]1.64839302787375e-08[/C][/ROW]
[ROW][C]199[/C][C]0.999999956398589[/C][C]8.72028211377498e-08[/C][C]4.36014105688749e-08[/C][/ROW]
[ROW][C]200[/C][C]0.999999851204566[/C][C]2.97590868011708e-07[/C][C]1.48795434005854e-07[/C][/ROW]
[ROW][C]201[/C][C]0.999999504216266[/C][C]9.91567467050206e-07[/C][C]4.95783733525103e-07[/C][/ROW]
[ROW][C]202[/C][C]0.999998180778443[/C][C]3.63844311385722e-06[/C][C]1.81922155692861e-06[/C][/ROW]
[ROW][C]203[/C][C]0.999992881481713[/C][C]1.42370365746042e-05[/C][C]7.11851828730211e-06[/C][/ROW]
[ROW][C]204[/C][C]0.999971595689199[/C][C]5.68086216012784e-05[/C][C]2.84043108006392e-05[/C][/ROW]
[ROW][C]205[/C][C]0.999888015829637[/C][C]0.000223968340726902[/C][C]0.000111984170363451[/C][/ROW]
[ROW][C]206[/C][C]0.999608998465993[/C][C]0.000782003068013332[/C][C]0.000391001534006666[/C][/ROW]
[ROW][C]207[/C][C]0.998936581043957[/C][C]0.00212683791208637[/C][C]0.00106341895604319[/C][/ROW]
[ROW][C]208[/C][C]0.999669535124918[/C][C]0.000660929750163618[/C][C]0.000330464875081809[/C][/ROW]
[ROW][C]209[/C][C]0.998798545934867[/C][C]0.00240290813026604[/C][C]0.00120145406513302[/C][/ROW]
[ROW][C]210[/C][C]0.996353602108376[/C][C]0.00729279578324845[/C][C]0.00364639789162423[/C][/ROW]
[ROW][C]211[/C][C]0.986025957502948[/C][C]0.0279480849941039[/C][C]0.013974042497052[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148475&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148475&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
150.003214082796922460.006428165593844910.996785917203078
160.0005809041241105850.001161808248221170.999419095875889
178.33192906727799e-050.000166638581345560.999916680709327
182.24320391987139e-054.48640783974278e-050.999977567960801
191.62365511298039e-053.24731022596079e-050.99998376344887
207.84017749368523e-061.56803549873705e-050.999992159822506
213.23194055709347e-066.46388111418694e-060.999996768059443
221.98855754924142e-063.97711509848285e-060.999998011442451
236.00182685004751e-071.2003653700095e-060.999999399817315
241.79063813953498e-073.58127627906995e-070.999999820936186
251.42604294813192e-072.85208589626384e-070.999999857395705
266.72516286206954e-081.34503257241391e-070.999999932748371
279.87840118560296e-081.97568023712059e-070.999999901215988
285.07610432865555e-081.01522086573111e-070.999999949238957
294.59364808244541e-089.18729616489083e-080.999999954063519
303.39618745958181e-086.79237491916361e-080.999999966038125
313.55713182729495e-087.1142636545899e-080.999999964428682
322.39768214479008e-084.79536428958016e-080.999999976023179
332.33734809290997e-084.67469618581993e-080.999999976626519
341.96004109947736e-083.92008219895473e-080.999999980399589
351.37506847574094e-082.75013695148188e-080.999999986249315
368.52948808735969e-091.70589761747194e-080.999999991470512
379.32575675986758e-091.86515135197352e-080.999999990674243
387.53229572615374e-091.50645914523075e-080.999999992467704
391.27487697688301e-082.54975395376602e-080.99999998725123
401.5208005162347e-083.04160103246941e-080.999999984791995
411.81097108322167e-083.62194216644334e-080.999999981890289
422.00673743416012e-084.01347486832023e-080.999999979932626
432.6940392770561e-085.3880785541122e-080.999999973059607
443.34348183324675e-086.6869636664935e-080.999999966565182
454.54614575592149e-089.09229151184298e-080.999999954538542
467.546451363033e-081.5092902726066e-070.999999924535486
478.53440109787702e-081.7068802195754e-070.999999914655989
489.24851551011338e-081.84970310202268e-070.999999907514845
491.13561907454175e-072.27123814908351e-070.999999886438093
501.67109035671549e-073.34218071343098e-070.999999832890964
514.65948748126866e-079.31897496253732e-070.999999534051252
527.51150436123761e-071.50230087224752e-060.999999248849564
531.81880909647838e-063.63761819295676e-060.999998181190904
544.46504359604458e-068.93008719208917e-060.999995534956404
551.09236134596432e-052.18472269192864e-050.99998907638654
562.64829264572829e-055.29658529145658e-050.999973517073543
576.10661400723277e-050.0001221322801446550.999938933859928
580.0001605086765720510.0003210173531441030.999839491323428
590.000292807428915550.00058561485783110.999707192571084
600.0004613611387293910.0009227222774587830.999538638861271
610.0007105676021796720.001421135204359340.99928943239782
620.001274923108470080.002549846216940170.99872507689153
630.003431740977893790.006863481955787580.996568259022106
640.007497808076135350.01499561615227070.992502191923865
650.0190895588344310.0381791176688620.980910441165569
660.04110794125434250.0822158825086850.958892058745658
670.09805965372716470.1961193074543290.901940346272835
680.1871767822017750.3743535644035510.812823217798225
690.2812117111746920.5624234223493840.718788288825308
700.4180307407488560.8360614814977110.581969259251144
710.5099439759638290.9801120480723430.490056024036171
720.575270250392860.8494594992142810.42472974960714
730.6444058756613470.7111882486773050.355594124338653
740.720010788421060.5599784231578810.27998921157894
750.8059817201169090.3880365597661810.194018279883091
760.8699026277374640.2601947445250720.130097372262536
770.9298650901567280.1402698196865450.0701349098432724
780.9640367097832590.07192658043348130.0359632902167407
790.9875764563718090.02484708725638170.0124235436281909
800.9958895384608290.008220923078342850.00411046153917142
810.9983493743450140.003301251309971280.00165062565498564
820.9994455971376570.001108805724686220.000554402862343108
830.9996925306569940.0006149386860122570.000307469343006129
840.9998105627987590.0003788744024827320.000189437201241366
850.9998873293941380.0002253412117246020.000112670605862301
860.9999367816051850.0001264367896304166.32183948152081e-05
870.999972431818025.51363639596626e-052.75681819798313e-05
880.9999887553437072.2489312585572e-051.1244656292786e-05
890.9999969099140436.18017191362799e-063.090085956814e-06
900.9999991619638211.67607235733595e-068.38036178667973e-07
910.9999998893574692.2128506214475e-071.10642531072375e-07
920.9999999794813674.10372654921301e-082.0518632746065e-08
930.999999994262091.14758199665729e-085.73790998328647e-09
940.9999999985140742.97185207871158e-091.48592603935579e-09
950.9999999991577341.68453114063648e-098.42265570318242e-10
960.9999999995456489.08703560134523e-104.54351780067262e-10
970.9999999997221025.55795729523788e-102.77897864761894e-10
980.9999999998283873.43225717390878e-101.71612858695439e-10
990.999999999916071.67859663150074e-108.39298315750372e-11
1000.9999999999615427.69157415877485e-113.84578707938743e-11
1010.9999999999874562.50887101722607e-111.25443550861303e-11
1020.9999999999958078.38597348926947e-124.19298674463474e-12
1030.9999999999992191.56259234175527e-127.81296170877635e-13
1040.9999999999997864.28172553011039e-132.14086276505519e-13
1050.9999999999999021.96362715752326e-139.81813578761628e-14
1060.9999999999999568.82731436529324e-144.41365718264662e-14
1070.9999999999999617.84968712351288e-143.92484356175644e-14
1080.9999999999999666.7359441251425e-143.36797206257125e-14
1090.9999999999999696.26598566550148e-143.13299283275074e-14
1100.999999999999975.94897996395914e-142.97448998197957e-14
1110.9999999999999764.87810247705015e-142.43905123852508e-14
1120.9999999999999813.81094098942739e-141.90547049471369e-14
1130.999999999999992.07295489820151e-141.03647744910076e-14
1140.9999999999999941.2673502382123e-146.33675119106151e-15
1150.9999999999999984.57684253707693e-152.28842126853846e-15
1160.9999999999999992.28283452730965e-151.14141726365483e-15
11719.44421835371906e-164.72210917685953e-16
11817.58187545857761e-173.79093772928881e-17
11914.2190333110369e-172.10951665551845e-17
12012.6010703623492e-171.3005351811746e-17
12112.24114128024208e-171.12057064012104e-17
12212.57834784992093e-171.28917392496046e-17
12312.92862486931293e-171.46431243465647e-17
12413.15373070358726e-171.57686535179363e-17
12512.34237913642465e-171.17118956821232e-17
12611.72135211829356e-178.60676059146778e-18
12716.75753674617669e-183.37876837308834e-18
12814.27283169397646e-182.13641584698823e-18
12914.03117147726347e-182.01558573863174e-18
13012.57543154143836e-181.28771577071918e-18
13112.89112799686356e-181.44556399843178e-18
13213.70712059591876e-181.85356029795938e-18
13315.1819039516464e-182.5909519758232e-18
13417.64286114881726e-183.82143057440863e-18
13516.14445427426408e-183.07222713713204e-18
13611.63324146065665e-188.16620730328327e-19
13711.34088724536135e-196.70443622680674e-20
13813.73910958902742e-201.86955479451371e-20
13915.11016310620414e-212.55508155310207e-21
14011.0669169759278e-215.33458487963898e-22
14113.95641087602883e-221.97820543801442e-22
14211.92976726944899e-229.64883634724495e-23
14312.36001247816444e-221.18000623908222e-22
14412.54966017883831e-221.27483008941916e-22
14513.0873657708735e-221.54368288543675e-22
14617.17873863939009e-223.58936931969504e-22
14711.19472137887644e-215.97360689438221e-22
14812.1500439845014e-211.0750219922507e-21
14911.89313141783834e-219.46565708919169e-22
15011.54419111368885e-217.72095556844423e-22
15117.63015120313447e-223.81507560156724e-22
15214.26500346329048e-222.13250173164524e-22
15313.98672550070163e-221.99336275035082e-22
15414.03178846448787e-222.01589423224393e-22
15517.78843257001181e-223.8942162850059e-22
15611.31569153644654e-216.5784576822327e-22
15713.54226728049919e-211.7711336402496e-21
15819.85599898197116e-214.92799949098558e-21
15911.79390441386844e-208.96952206934221e-21
16014.43171983218074e-202.21585991609037e-20
16119.64270916732285e-204.82135458366143e-20
16211.5565131533459e-197.78256576672951e-20
16312.2104968360355e-191.10524841801775e-19
16413.54572894126223e-191.77286447063112e-19
16518.80296453935652e-194.40148226967826e-19
16611.93616282990809e-189.68081414954044e-19
16715.45171275810198e-182.72585637905099e-18
16811.41441020557406e-177.07205102787031e-18
16914.45145574715206e-172.22572787357603e-17
17011.36386312431791e-166.81931562158954e-17
17113.69873483593704e-161.84936741796852e-16
17217.61199039834041e-163.8059951991702e-16
1730.9999999999999992.09581140126466e-151.04790570063233e-15
1740.9999999999999975.38459849970345e-152.69229924985172e-15
1750.9999999999999931.38428280092745e-146.92141400463725e-15
1760.9999999999999813.74937340031499e-141.87468670015749e-14
1770.9999999999999471.05655575083673e-135.28277875418366e-14
1780.999999999999853.00844544881433e-131.50422272440717e-13
1790.9999999999995459.10592424274355e-134.55296212137178e-13
1800.9999999999986752.64976267581224e-121.32488133790612e-12
1810.9999999999965866.82905494067854e-123.41452747033927e-12
1820.9999999999908521.82960237806814e-119.1480118903407e-12
1830.9999999999811733.76533815510012e-111.88266907755006e-11
1840.9999999999787854.24309506734159e-112.1215475336708e-11
1850.9999999999493731.01254525263782e-105.0627262631891e-11
1860.9999999998664282.6714326299691e-101.33571631498455e-10
1870.9999999997337715.32457471815593e-102.66228735907797e-10
1880.9999999994253941.14921183862153e-095.74605919310764e-10
1890.9999999988089762.38204789478232e-091.19102394739116e-09
1900.9999999971914895.61702261838872e-092.80851130919436e-09
1910.9999999938844891.22310225349903e-086.11551126749515e-09
1920.9999999853476622.9304675021176e-081.4652337510588e-08
1930.9999999692372356.15255294710317e-083.07627647355159e-08
1940.9999999525473979.49052052057443e-084.74526026028722e-08
1950.999999941666881.16666239722421e-075.83331198612104e-08
1960.9999999785077844.29844317722309e-082.14922158861154e-08
1970.9999999790717994.18564024557405e-082.09282012278702e-08
1980.999999983516073.2967860557475e-081.64839302787375e-08
1990.9999999563985898.72028211377498e-084.36014105688749e-08
2000.9999998512045662.97590868011708e-071.48795434005854e-07
2010.9999995042162669.91567467050206e-074.95783733525103e-07
2020.9999981807784433.63844311385722e-061.81922155692861e-06
2030.9999928814817131.42370365746042e-057.11851828730211e-06
2040.9999715956891995.68086216012784e-052.84043108006392e-05
2050.9998880158296370.0002239683407269020.000111984170363451
2060.9996089984659930.0007820030680133320.000391001534006666
2070.9989365810439570.002126837912086370.00106341895604319
2080.9996695351249180.0006609297501636180.000330464875081809
2090.9987985459348670.002402908130266040.00120145406513302
2100.9963536021083760.007292795783248450.00364639789162423
2110.9860259575029480.02794808499410390.013974042497052







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1800.913705583756345NOK
5% type I error level1840.934010152284264NOK
10% type I error level1860.944162436548223NOK

\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 & 180 & 0.913705583756345 & NOK \tabularnewline
5% type I error level & 184 & 0.934010152284264 & NOK \tabularnewline
10% type I error level & 186 & 0.944162436548223 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148475&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]180[/C][C]0.913705583756345[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]184[/C][C]0.934010152284264[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]186[/C][C]0.944162436548223[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148475&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148475&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1800.913705583756345NOK
5% type I error level1840.934010152284264NOK
10% type I error level1860.944162436548223NOK



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