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Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 10 Dec 2013 04:21:14 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/10/t1386667342rezhohk49sy255c.htm/, Retrieved Fri, 29 Mar 2024 10:17:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231833, Retrieved Fri, 29 Mar 2024 10:17:54 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Workshop 10] [2013-12-10 09:21:14] [67d37a8f6529c122cc345ef1d65d5ffd] [Current]
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Dataseries X:
1 1 41 38 13 12 14
1 1 39 32 16 11 18
1 1 30 35 19 15 11
1 0 31 33 15 6 12
1 1 34 37 14 13 16
1 1 35 29 13 10 18
1 1 39 31 19 12 14
1 1 34 36 15 14 14
1 1 36 35 14 12 15
1 1 37 38 15 9 15
1 0 38 31 16 10 17
1 1 36 34 16 12 19
1 0 38 35 16 12 10
1 1 39 38 16 11 16
1 1 33 37 17 15 18
1 0 32 33 15 12 14
1 0 36 32 15 10 14
1 1 38 38 20 12 17
1 0 39 38 18 11 14
1 1 32 32 16 12 16
1 0 32 33 16 11 18
1 1 31 31 16 12 11
1 1 39 38 19 13 14
1 1 37 39 16 11 12
1 0 39 32 17 12 17
1 1 41 32 17 13 9
1 0 36 35 16 10 16
1 1 33 37 15 14 14
1 1 33 33 16 12 15
1 0 34 33 14 10 11
1 1 31 31 15 12 16
1 0 27 32 12 8 13
1 1 37 31 14 10 17
1 1 34 37 16 12 15
1 0 34 30 14 12 14
1 0 32 33 10 7 16
1 0 29 31 10 9 9
1 0 36 33 14 12 15
1 1 29 31 16 10 17
1 0 35 33 16 10 13
1 0 37 32 16 10 15
1 1 34 33 14 12 16
1 0 38 32 20 15 16
1 0 35 33 14 10 12
1 1 38 28 14 10 15
1 1 37 35 11 12 11
1 1 38 39 14 13 15
1 1 33 34 15 11 15
1 1 36 38 16 11 17
1 0 38 32 14 12 13
1 1 32 38 16 14 16
1 0 32 30 14 10 14
1 0 32 33 12 12 11
1 1 34 38 16 13 12
1 0 32 32 9 5 12
1 1 37 35 14 6 15
1 1 39 34 16 12 16
1 1 29 34 16 12 15
1 0 37 36 15 11 12
1 1 35 34 16 10 12
1 0 30 28 12 7 8
1 0 38 34 16 12 13
1 1 34 35 16 14 11
1 1 31 35 14 11 14
1 1 34 31 16 12 15
1 0 35 37 17 13 10
1 1 36 35 18 14 11
1 0 30 27 18 11 12
1 1 39 40 12 12 15
1 0 35 37 16 12 15
1 0 38 36 10 8 14
1 1 31 38 14 11 16
1 1 34 39 18 14 15
1 0 38 41 18 14 15
1 0 34 27 16 12 13
1 1 39 30 17 9 12
1 1 37 37 16 13 17
1 1 34 31 16 11 13
1 0 28 31 13 12 15
1 0 37 27 16 12 13
1 0 33 36 16 12 15
1 1 35 37 16 12 15
1 0 37 33 15 12 16
1 1 32 34 15 11 15
1 1 33 31 16 10 14
1 0 38 39 14 9 15
1 1 33 34 16 12 14
1 1 29 32 16 12 13
1 1 33 33 15 12 7
1 1 31 36 12 9 17
1 1 36 32 17 15 13
1 1 35 41 16 12 15
1 1 32 28 15 12 14
1 1 29 30 13 12 13
1 1 39 36 16 10 16
1 1 37 35 16 13 12
1 1 35 31 16 9 14
1 0 37 34 16 12 17
1 0 32 36 14 10 15
1 1 38 36 16 14 17
1 0 37 35 16 11 12
1 1 36 37 20 15 16
1 0 32 28 15 11 11
1 1 33 39 16 11 15
1 0 40 32 13 12 9
1 1 38 35 17 12 16
1 0 41 39 16 12 15
1 0 36 35 16 11 10
1 1 43 42 12 7 10
1 1 30 34 16 12 15
1 1 31 33 16 14 11
1 1 32 41 17 11 13
1 1 37 34 12 10 18
1 0 37 32 18 13 16
1 1 33 40 14 13 14
1 1 34 40 14 8 14
1 1 33 35 13 11 14
1 1 38 36 16 12 14
1 0 33 37 13 11 12
1 1 31 27 16 13 14
1 1 38 39 13 12 15
1 1 37 38 16 14 15
1 1 36 31 15 13 15
1 1 31 33 16 15 13
1 0 39 32 15 10 17
1 1 44 39 17 11 17
1 1 33 36 15 9 19
1 1 35 33 12 11 15
1 0 32 33 16 10 13
1 0 28 32 10 11 9
1 1 40 37 16 8 15
1 0 27 30 12 11 15
1 0 37 38 14 12 15
1 1 32 29 15 12 16
1 0 28 22 13 9 11
1 0 34 35 15 11 14
1 1 30 35 11 10 11
1 1 35 34 12 8 15
1 0 31 35 11 9 13
1 1 32 34 16 8 15
1 0 30 37 15 9 16
1 1 30 35 17 15 14
1 0 31 23 16 11 15
1 1 40 31 10 8 16
1 1 32 27 18 13 16
1 0 36 36 13 12 11
1 0 32 31 16 12 12
1 0 35 32 13 9 9
1 1 38 39 10 7 16
1 1 42 37 15 13 13
1 0 34 38 16 9 16
1 1 35 39 16 6 12
1 1 38 34 14 8 9
1 1 33 31 10 8 13
1 1 32 37 13 6 14
1 1 33 36 15 9 19
1 1 34 32 16 11 13
1 1 32 38 12 8 12
0 0 27 26 13 10 10
0 0 31 26 12 8 14
0 0 38 33 17 14 16
0 1 34 39 15 10 10
0 0 24 30 10 8 11
0 0 30 33 14 11 14
0 1 26 25 11 12 12
0 1 34 38 13 12 9
0 0 27 37 16 12 9
0 0 37 31 12 5 11
0 1 36 37 16 12 16
0 0 41 35 12 10 9
0 1 29 25 9 7 13
0 1 36 28 12 12 16
0 0 32 35 15 11 13
0 1 37 33 12 8 9
0 0 30 30 12 9 12
0 1 31 31 14 10 16
0 1 38 37 12 9 11
0 1 36 36 16 12 14
0 0 35 30 11 6 13
0 0 31 36 19 15 15
0 0 38 32 15 12 14
0 1 22 28 8 12 16
0 1 32 36 16 12 13
0 0 36 34 17 11 14
0 1 39 31 12 7 15
0 0 28 28 11 7 13
0 0 32 36 11 5 11
0 1 32 36 14 12 11
0 1 38 40 16 12 14
0 1 32 33 12 3 15
0 1 35 37 16 11 11
0 1 32 32 13 10 15
0 0 37 38 15 12 12
0 1 34 31 16 9 14
0 1 33 37 16 12 14
0 0 33 33 14 9 8
0 0 30 30 16 12 9
0 0 24 30 14 10 15
0 0 34 31 11 9 17
0 0 34 32 12 12 13
0 1 33 34 15 8 15
0 1 34 36 15 11 15
0 1 35 37 16 11 14
0 0 35 36 16 12 16
0 0 36 33 11 10 13
0 0 34 33 15 10 16
0 1 34 33 12 12 9
0 0 41 44 12 12 16
0 0 32 39 15 11 11
0 0 30 32 15 8 10
0 1 35 35 16 12 11
0 0 28 25 14 10 15
0 1 33 35 17 11 17
0 1 39 34 14 10 14
0 0 36 35 13 8 8
0 1 36 39 15 12 15
0 0 35 33 13 12 11
0 0 38 36 14 10 16
0 1 33 32 15 12 10
0 0 31 32 12 9 15
0 1 32 36 8 6 16
0 0 31 32 14 10 19
0 0 33 34 14 9 12
0 0 34 33 11 9 8
0 0 34 35 12 9 11
0 1 34 30 13 6 14
0 0 33 38 10 10 9
0 0 32 34 16 6 15
0 1 41 33 18 14 13
0 1 34 32 13 10 16
0 0 36 31 11 10 11
0 0 37 30 4 6 12
0 0 36 27 13 12 13
0 1 29 31 16 12 10
0 0 37 30 10 7 11
0 0 27 32 12 8 12
0 0 35 35 12 11 8
0 0 28 28 10 3 12
0 0 35 33 13 6 12
0 0 29 35 12 8 11
0 0 32 35 14 9 13
0 1 36 32 10 9 14
0 1 19 21 12 8 10
0 1 21 20 12 9 12
0 0 31 34 11 7 15
0 0 33 32 10 7 13
0 1 36 34 12 6 13
0 1 33 32 16 9 13
0 0 37 33 12 10 12
0 0 34 33 14 11 12
0 0 35 37 16 12 9
0 1 31 32 14 8 9
0 1 37 34 13 11 15
0 1 35 30 4 3 10
0 1 27 30 15 11 14
0 0 34 38 11 12 15
0 0 40 36 11 7 7
0 0 29 32 14 9 14
0 0 38 34 15 12 8
0 1 34 33 14 8 10
0 0 21 27 13 11 13
0 0 36 32 11 8 13
0 1 38 34 15 10 13
0 0 30 29 11 8 8
0 0 35 35 13 7 12
0 1 30 27 13 8 13
0 1 36 33 16 10 12
0 0 34 38 13 8 10
0 1 35 36 16 12 13
0 0 34 33 16 14 12
0 0 32 39 12 7 9
0 1 33 29 7 6 15
0 0 33 32 16 11 13
0 1 26 34 5 4 13
0 0 35 38 16 9 13
0 0 21 17 4 5 15
0 0 38 35 12 9 15
0 0 35 32 15 11 14
0 1 33 34 14 12 15
0 0 37 36 11 9 11
0 0 38 31 16 12 15
0 1 34 35 15 10 14
0 0 27 29 12 9 13
0 1 16 22 6 6 12
0 0 40 41 16 10 16
0 0 36 36 10 9 16
0 1 42 42 15 13 9
0 1 30 33 14 12 14




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time26 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 26 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231833&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]26 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231833&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231833&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 time26 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Gender[t] = -0.430055 + 0.114625Pop[t] -0.00772106Connected[t] + 0.0151118Separate[t] + 0.00197408Learning[t] + 0.0176182Software[t] + 0.0328699Happiness[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Gender[t] =  -0.430055 +  0.114625Pop[t] -0.00772106Connected[t] +  0.0151118Separate[t] +  0.00197408Learning[t] +  0.0176182Software[t] +  0.0328699Happiness[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231833&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Gender[t] =  -0.430055 +  0.114625Pop[t] -0.00772106Connected[t] +  0.0151118Separate[t] +  0.00197408Learning[t] +  0.0176182Software[t] +  0.0328699Happiness[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231833&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231833&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
Gender[t] = -0.430055 + 0.114625Pop[t] -0.00772106Connected[t] + 0.0151118Separate[t] + 0.00197408Learning[t] + 0.0176182Software[t] + 0.0328699Happiness[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-0.4300550.317311-1.3550.1764060.0882032
Pop0.1146250.06360491.8020.07259570.0362978
Connected-0.007721060.00841701-0.91730.3597630.179882
Separate0.01511180.008715261.7340.08402310.0420116
Learning0.001974080.01517190.13010.8965690.448285
Software0.01761820.01615691.090.276450.138225
Happiness0.03286990.01200662.7380.006582840.00329142

\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) & -0.430055 & 0.317311 & -1.355 & 0.176406 & 0.0882032 \tabularnewline
Pop & 0.114625 & 0.0636049 & 1.802 & 0.0725957 & 0.0362978 \tabularnewline
Connected & -0.00772106 & 0.00841701 & -0.9173 & 0.359763 & 0.179882 \tabularnewline
Separate & 0.0151118 & 0.00871526 & 1.734 & 0.0840231 & 0.0420116 \tabularnewline
Learning & 0.00197408 & 0.0151719 & 0.1301 & 0.896569 & 0.448285 \tabularnewline
Software & 0.0176182 & 0.0161569 & 1.09 & 0.27645 & 0.138225 \tabularnewline
Happiness & 0.0328699 & 0.0120066 & 2.738 & 0.00658284 & 0.00329142 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231833&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]-0.430055[/C][C]0.317311[/C][C]-1.355[/C][C]0.176406[/C][C]0.0882032[/C][/ROW]
[ROW][C]Pop[/C][C]0.114625[/C][C]0.0636049[/C][C]1.802[/C][C]0.0725957[/C][C]0.0362978[/C][/ROW]
[ROW][C]Connected[/C][C]-0.00772106[/C][C]0.00841701[/C][C]-0.9173[/C][C]0.359763[/C][C]0.179882[/C][/ROW]
[ROW][C]Separate[/C][C]0.0151118[/C][C]0.00871526[/C][C]1.734[/C][C]0.0840231[/C][C]0.0420116[/C][/ROW]
[ROW][C]Learning[/C][C]0.00197408[/C][C]0.0151719[/C][C]0.1301[/C][C]0.896569[/C][C]0.448285[/C][/ROW]
[ROW][C]Software[/C][C]0.0176182[/C][C]0.0161569[/C][C]1.09[/C][C]0.27645[/C][C]0.138225[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0328699[/C][C]0.0120066[/C][C]2.738[/C][C]0.00658284[/C][C]0.00329142[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231833&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231833&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)-0.4300550.317311-1.3550.1764060.0882032
Pop0.1146250.06360491.8020.07259570.0362978
Connected-0.007721060.00841701-0.91730.3597630.179882
Separate0.01511180.008715261.7340.08402310.0420116
Learning0.001974080.01517190.13010.8965690.448285
Software0.01761820.01615691.090.276450.138225
Happiness0.03286990.01200662.7380.006582840.00329142







Multiple Linear Regression - Regression Statistics
Multiple R0.29304
R-squared0.0858724
Adjusted R-squared0.0663537
F-TEST (value)4.39949
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0.000286945
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.483022
Sum Squared Residuals65.5601

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.29304 \tabularnewline
R-squared & 0.0858724 \tabularnewline
Adjusted R-squared & 0.0663537 \tabularnewline
F-TEST (value) & 4.39949 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 0.000286945 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 0.483022 \tabularnewline
Sum Squared Residuals & 65.5601 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231833&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.29304[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0858724[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0663537[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]4.39949[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]281[/C][/ROW]
[ROW][C]p-value[/C][C]0.000286945[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]0.483022[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]65.5601[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231833&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231833&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 R0.29304
R-squared0.0858724
Adjusted R-squared0.0663537
F-TEST (value)4.39949
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0.000286945
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation0.483022
Sum Squared Residuals65.5601







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
110.6395160.360484
210.684070.31593
310.6452020.354798
400.473666-0.473666
510.7637840.236216
610.6460790.353921
710.561020.43898
810.7025240.297476
910.667630.33237
1010.6543640.345636
1100.626192-0.626192
1210.7879450.212055
1300.491786-0.491786
1410.7090020.290998
1510.8784030.121597
1600.637394-0.637394
1700.556162-0.556162
1810.7751070.224893
1900.64721-0.64721
2010.6899960.310004
2100.75323-0.75323
2210.5182560.481744
2310.6844210.315579
2410.6080760.391924
2500.670793-0.670793
2610.410010.58999
2700.669211-0.669211
2810.7253570.274643
2910.6645170.335483
3000.486132-0.486132
3110.6806320.319368
3200.551623-0.551623
3310.6299640.370036
3410.7172440.282756
3500.574643-0.574643
3600.605173-0.605173
3700.40326-0.40326
3800.637406-0.637406
3910.6956810.304319
4000.548099-0.548099
4100.583285-0.583285
4210.6857180.314282
4300.704421-0.704421
4400.511281-0.511281
4510.5111680.488832
4610.5225070.477493
4710.7302530.269747
4810.6600370.339963
4910.7650350.234965
5000.541112-0.541112
5110.8159040.184096
5200.554848-0.554848
5300.532863-0.532863
5410.6513640.348636
5500.421371-0.421371
5610.5541990.445801
5710.6661730.333827
5810.7105130.289487
5900.560767-0.560767
6010.5303410.469659
6100.286045-0.286045
6200.575284-0.575284
6310.5907770.409223
6410.6557470.344253
6510.6265730.373427
6600.564766-0.564766
6710.5792830.420717
6800.48473-0.48473
6910.7160780.283922
7000.709523-0.709523
7100.55606-0.55606
7210.7668220.233178
7310.7866520.213348
7400.785991-0.785991
7500.500385-0.500385
7610.4233650.576635
7710.7774380.222562
7810.5432150.456785
7900.666977-0.666977
8000.477222-0.477222
8100.709853-0.709853
8210.7095230.290477
8300.664529-0.664529
8410.6677580.332242
8510.5661870.433813
8600.65978-0.65978
8710.6467590.353241
8810.614550.38545
8910.3995840.600416
9010.7302840.269716
9110.6153310.384669
9210.769970.23003
9310.5618350.438165
9410.5784040.421596
9510.661160.33884
9610.5828650.417135
9710.5331270.466873
9800.714485-0.714485
9900.678389-0.678389
10010.7722240.227776
10100.547629-0.547629
10210.7954220.204578
10300.445607-0.445607
10410.737570.26243
10500.392217-0.392217
10610.690980.30902
10700.69342-0.69342
10800.48961-0.48961
10910.4629770.537023
11010.7027920.297208
11110.5837160.416284
11210.7117490.288251
11310.7042220.295778
11400.672957-0.672957
11510.75110.2489
11610.6552880.344712
11710.6383310.361669
11810.6383780.361622
11900.602815-0.602815
12010.5740370.425963
12110.7106610.289339
12210.7444290.255571
12310.6267750.373225
12410.6670740.332926
12500.631608-0.631608
12610.7203520.279648
12710.7865030.213497
12810.6235610.376439
12900.571262-0.571262
13000.461329-0.461329
13110.6004440.399556
13200.639994-0.639994
13300.705244-0.705244
13410.6426870.357313
13500.346636-0.346636
13600.634558-0.634558
13710.5413180.458682
13810.5858180.414182
13900.581718-0.581718
14010.6168770.383123
14100.726169-0.726169
14210.7398630.260137
14300.511223-0.511223
14410.5307990.469201
14510.6360040.363996
14600.549288-0.549288
14700.543405-0.543405
14800.377967-0.377967
14910.6495170.350483
15010.605380.39462
15100.712371-0.712371
15210.5354270.464573
15310.3693840.630616
15410.4862360.513764
15510.5881840.411816
15610.7865030.213497
15710.5583260.441674
15810.5708190.429181
15900.284928-0.284928
16000.348313-0.348313
16100.581368-0.581368
16210.4312830.568717
16300.36025-0.36025
16400.51862-0.51862
16510.3745650.625435
16610.414590.58541
16700.459447-0.459447
16800.226081-0.226081
16910.6200470.379953
17000.277996-0.277996
17110.2922330.707767
17210.4761440.523856
17300.502505-0.502505
17410.243420.75658
17500.36836-0.36836
17610.5287960.471204
17710.3795040.620496
17810.5391950.460805
17900.307796-0.307796
18000.669447-0.669447
18100.461332-0.461332
18210.5763420.423658
18310.537210.46279
18400.493327-0.493327
18510.3773550.622645
18600.349237-0.349237
18700.338272-0.338272
18810.4675220.532478
18910.5842010.415799
19010.3911530.608847
19110.44580.5542
19210.5013430.498657
19300.493984-0.493984
19410.4262230.573777
19510.577470.42253
19600.263001-0.263001
19700.330501-0.330501
19800.534862-0.534862
19900.514963-0.514963
20000.453424-0.453424
20110.4925580.507442
20210.5679150.432085
20310.544410.45559
20400.612656-0.612656
20500.415883-0.415883
20600.537831-0.537831
20710.3370560.662944
20800.679328-0.679328
20900.497213-0.497213
21000.321148-0.321148
21110.4331950.566805
21200.428419-0.428419
21310.6302120.369788
21410.4466240.553376
21500.250469-0.250469
21610.6154270.384573
21700.397049-0.397049
21800.550308-0.550308
21910.3684580.631542
22000.489472-0.489472
22110.5143170.485683
22200.642518-0.642518
22300.409592-0.409592
22400.249358-0.249358
22500.380165-0.380165
22610.3523350.647665
22700.381152-0.381152
22800.467016-0.467016
22910.4615690.538431
23010.5187710.481229
23100.31992-0.31992
23200.245665-0.245665
23300.364397-0.364397
23410.3862040.613796
23500.242258-0.242258
23600.404128-0.404128
23700.309071-0.309071
23800.243921-0.243921
23900.324209-0.324209
24000.401152-0.401152
24100.465295-0.465295
24210.4140490.585951
24310.2339270.766073
24410.2867310.713269
24500.482485-0.482485
24600.369105-0.369105
24710.3624960.637504
24810.4161860.583814
24900.377266-0.377266
25000.421996-0.421996
25100.397679-0.397679
25210.2785830.721417
25310.510580.48942
25410.1425130.857487
25510.4984210.501579
25600.607861-0.607861
25700.18026-0.18026
25800.475992-0.475992
25900.294336-0.294336
26010.3034010.696599
26100.462594-0.462594
26200.365535-0.365535
26310.4234490.576551
26400.202176-0.202176
26500.372051-0.372051
26610.340250.65975
26710.3928830.607117
26800.376986-0.376986
26910.5140460.485954
27000.478799-0.478799
27100.355078-0.355078
27210.3659690.634031
27300.451423-0.451423
27410.3906520.609348
27500.491415-0.491415
27600.253739-0.253739
27700.48076-0.48076
27800.466877-0.466877
27910.5610560.438944
28000.370139-0.370139
28100.481064-0.481064
28210.5023150.497685
28300.409281-0.409281
28410.2908610.709139
28500.614373-0.614373
28600.540236-0.540236
28710.4348350.565165
28810.5362380.463762

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 1 & 0.639516 & 0.360484 \tabularnewline
2 & 1 & 0.68407 & 0.31593 \tabularnewline
3 & 1 & 0.645202 & 0.354798 \tabularnewline
4 & 0 & 0.473666 & -0.473666 \tabularnewline
5 & 1 & 0.763784 & 0.236216 \tabularnewline
6 & 1 & 0.646079 & 0.353921 \tabularnewline
7 & 1 & 0.56102 & 0.43898 \tabularnewline
8 & 1 & 0.702524 & 0.297476 \tabularnewline
9 & 1 & 0.66763 & 0.33237 \tabularnewline
10 & 1 & 0.654364 & 0.345636 \tabularnewline
11 & 0 & 0.626192 & -0.626192 \tabularnewline
12 & 1 & 0.787945 & 0.212055 \tabularnewline
13 & 0 & 0.491786 & -0.491786 \tabularnewline
14 & 1 & 0.709002 & 0.290998 \tabularnewline
15 & 1 & 0.878403 & 0.121597 \tabularnewline
16 & 0 & 0.637394 & -0.637394 \tabularnewline
17 & 0 & 0.556162 & -0.556162 \tabularnewline
18 & 1 & 0.775107 & 0.224893 \tabularnewline
19 & 0 & 0.64721 & -0.64721 \tabularnewline
20 & 1 & 0.689996 & 0.310004 \tabularnewline
21 & 0 & 0.75323 & -0.75323 \tabularnewline
22 & 1 & 0.518256 & 0.481744 \tabularnewline
23 & 1 & 0.684421 & 0.315579 \tabularnewline
24 & 1 & 0.608076 & 0.391924 \tabularnewline
25 & 0 & 0.670793 & -0.670793 \tabularnewline
26 & 1 & 0.41001 & 0.58999 \tabularnewline
27 & 0 & 0.669211 & -0.669211 \tabularnewline
28 & 1 & 0.725357 & 0.274643 \tabularnewline
29 & 1 & 0.664517 & 0.335483 \tabularnewline
30 & 0 & 0.486132 & -0.486132 \tabularnewline
31 & 1 & 0.680632 & 0.319368 \tabularnewline
32 & 0 & 0.551623 & -0.551623 \tabularnewline
33 & 1 & 0.629964 & 0.370036 \tabularnewline
34 & 1 & 0.717244 & 0.282756 \tabularnewline
35 & 0 & 0.574643 & -0.574643 \tabularnewline
36 & 0 & 0.605173 & -0.605173 \tabularnewline
37 & 0 & 0.40326 & -0.40326 \tabularnewline
38 & 0 & 0.637406 & -0.637406 \tabularnewline
39 & 1 & 0.695681 & 0.304319 \tabularnewline
40 & 0 & 0.548099 & -0.548099 \tabularnewline
41 & 0 & 0.583285 & -0.583285 \tabularnewline
42 & 1 & 0.685718 & 0.314282 \tabularnewline
43 & 0 & 0.704421 & -0.704421 \tabularnewline
44 & 0 & 0.511281 & -0.511281 \tabularnewline
45 & 1 & 0.511168 & 0.488832 \tabularnewline
46 & 1 & 0.522507 & 0.477493 \tabularnewline
47 & 1 & 0.730253 & 0.269747 \tabularnewline
48 & 1 & 0.660037 & 0.339963 \tabularnewline
49 & 1 & 0.765035 & 0.234965 \tabularnewline
50 & 0 & 0.541112 & -0.541112 \tabularnewline
51 & 1 & 0.815904 & 0.184096 \tabularnewline
52 & 0 & 0.554848 & -0.554848 \tabularnewline
53 & 0 & 0.532863 & -0.532863 \tabularnewline
54 & 1 & 0.651364 & 0.348636 \tabularnewline
55 & 0 & 0.421371 & -0.421371 \tabularnewline
56 & 1 & 0.554199 & 0.445801 \tabularnewline
57 & 1 & 0.666173 & 0.333827 \tabularnewline
58 & 1 & 0.710513 & 0.289487 \tabularnewline
59 & 0 & 0.560767 & -0.560767 \tabularnewline
60 & 1 & 0.530341 & 0.469659 \tabularnewline
61 & 0 & 0.286045 & -0.286045 \tabularnewline
62 & 0 & 0.575284 & -0.575284 \tabularnewline
63 & 1 & 0.590777 & 0.409223 \tabularnewline
64 & 1 & 0.655747 & 0.344253 \tabularnewline
65 & 1 & 0.626573 & 0.373427 \tabularnewline
66 & 0 & 0.564766 & -0.564766 \tabularnewline
67 & 1 & 0.579283 & 0.420717 \tabularnewline
68 & 0 & 0.48473 & -0.48473 \tabularnewline
69 & 1 & 0.716078 & 0.283922 \tabularnewline
70 & 0 & 0.709523 & -0.709523 \tabularnewline
71 & 0 & 0.55606 & -0.55606 \tabularnewline
72 & 1 & 0.766822 & 0.233178 \tabularnewline
73 & 1 & 0.786652 & 0.213348 \tabularnewline
74 & 0 & 0.785991 & -0.785991 \tabularnewline
75 & 0 & 0.500385 & -0.500385 \tabularnewline
76 & 1 & 0.423365 & 0.576635 \tabularnewline
77 & 1 & 0.777438 & 0.222562 \tabularnewline
78 & 1 & 0.543215 & 0.456785 \tabularnewline
79 & 0 & 0.666977 & -0.666977 \tabularnewline
80 & 0 & 0.477222 & -0.477222 \tabularnewline
81 & 0 & 0.709853 & -0.709853 \tabularnewline
82 & 1 & 0.709523 & 0.290477 \tabularnewline
83 & 0 & 0.664529 & -0.664529 \tabularnewline
84 & 1 & 0.667758 & 0.332242 \tabularnewline
85 & 1 & 0.566187 & 0.433813 \tabularnewline
86 & 0 & 0.65978 & -0.65978 \tabularnewline
87 & 1 & 0.646759 & 0.353241 \tabularnewline
88 & 1 & 0.61455 & 0.38545 \tabularnewline
89 & 1 & 0.399584 & 0.600416 \tabularnewline
90 & 1 & 0.730284 & 0.269716 \tabularnewline
91 & 1 & 0.615331 & 0.384669 \tabularnewline
92 & 1 & 0.76997 & 0.23003 \tabularnewline
93 & 1 & 0.561835 & 0.438165 \tabularnewline
94 & 1 & 0.578404 & 0.421596 \tabularnewline
95 & 1 & 0.66116 & 0.33884 \tabularnewline
96 & 1 & 0.582865 & 0.417135 \tabularnewline
97 & 1 & 0.533127 & 0.466873 \tabularnewline
98 & 0 & 0.714485 & -0.714485 \tabularnewline
99 & 0 & 0.678389 & -0.678389 \tabularnewline
100 & 1 & 0.772224 & 0.227776 \tabularnewline
101 & 0 & 0.547629 & -0.547629 \tabularnewline
102 & 1 & 0.795422 & 0.204578 \tabularnewline
103 & 0 & 0.445607 & -0.445607 \tabularnewline
104 & 1 & 0.73757 & 0.26243 \tabularnewline
105 & 0 & 0.392217 & -0.392217 \tabularnewline
106 & 1 & 0.69098 & 0.30902 \tabularnewline
107 & 0 & 0.69342 & -0.69342 \tabularnewline
108 & 0 & 0.48961 & -0.48961 \tabularnewline
109 & 1 & 0.462977 & 0.537023 \tabularnewline
110 & 1 & 0.702792 & 0.297208 \tabularnewline
111 & 1 & 0.583716 & 0.416284 \tabularnewline
112 & 1 & 0.711749 & 0.288251 \tabularnewline
113 & 1 & 0.704222 & 0.295778 \tabularnewline
114 & 0 & 0.672957 & -0.672957 \tabularnewline
115 & 1 & 0.7511 & 0.2489 \tabularnewline
116 & 1 & 0.655288 & 0.344712 \tabularnewline
117 & 1 & 0.638331 & 0.361669 \tabularnewline
118 & 1 & 0.638378 & 0.361622 \tabularnewline
119 & 0 & 0.602815 & -0.602815 \tabularnewline
120 & 1 & 0.574037 & 0.425963 \tabularnewline
121 & 1 & 0.710661 & 0.289339 \tabularnewline
122 & 1 & 0.744429 & 0.255571 \tabularnewline
123 & 1 & 0.626775 & 0.373225 \tabularnewline
124 & 1 & 0.667074 & 0.332926 \tabularnewline
125 & 0 & 0.631608 & -0.631608 \tabularnewline
126 & 1 & 0.720352 & 0.279648 \tabularnewline
127 & 1 & 0.786503 & 0.213497 \tabularnewline
128 & 1 & 0.623561 & 0.376439 \tabularnewline
129 & 0 & 0.571262 & -0.571262 \tabularnewline
130 & 0 & 0.461329 & -0.461329 \tabularnewline
131 & 1 & 0.600444 & 0.399556 \tabularnewline
132 & 0 & 0.639994 & -0.639994 \tabularnewline
133 & 0 & 0.705244 & -0.705244 \tabularnewline
134 & 1 & 0.642687 & 0.357313 \tabularnewline
135 & 0 & 0.346636 & -0.346636 \tabularnewline
136 & 0 & 0.634558 & -0.634558 \tabularnewline
137 & 1 & 0.541318 & 0.458682 \tabularnewline
138 & 1 & 0.585818 & 0.414182 \tabularnewline
139 & 0 & 0.581718 & -0.581718 \tabularnewline
140 & 1 & 0.616877 & 0.383123 \tabularnewline
141 & 0 & 0.726169 & -0.726169 \tabularnewline
142 & 1 & 0.739863 & 0.260137 \tabularnewline
143 & 0 & 0.511223 & -0.511223 \tabularnewline
144 & 1 & 0.530799 & 0.469201 \tabularnewline
145 & 1 & 0.636004 & 0.363996 \tabularnewline
146 & 0 & 0.549288 & -0.549288 \tabularnewline
147 & 0 & 0.543405 & -0.543405 \tabularnewline
148 & 0 & 0.377967 & -0.377967 \tabularnewline
149 & 1 & 0.649517 & 0.350483 \tabularnewline
150 & 1 & 0.60538 & 0.39462 \tabularnewline
151 & 0 & 0.712371 & -0.712371 \tabularnewline
152 & 1 & 0.535427 & 0.464573 \tabularnewline
153 & 1 & 0.369384 & 0.630616 \tabularnewline
154 & 1 & 0.486236 & 0.513764 \tabularnewline
155 & 1 & 0.588184 & 0.411816 \tabularnewline
156 & 1 & 0.786503 & 0.213497 \tabularnewline
157 & 1 & 0.558326 & 0.441674 \tabularnewline
158 & 1 & 0.570819 & 0.429181 \tabularnewline
159 & 0 & 0.284928 & -0.284928 \tabularnewline
160 & 0 & 0.348313 & -0.348313 \tabularnewline
161 & 0 & 0.581368 & -0.581368 \tabularnewline
162 & 1 & 0.431283 & 0.568717 \tabularnewline
163 & 0 & 0.36025 & -0.36025 \tabularnewline
164 & 0 & 0.51862 & -0.51862 \tabularnewline
165 & 1 & 0.374565 & 0.625435 \tabularnewline
166 & 1 & 0.41459 & 0.58541 \tabularnewline
167 & 0 & 0.459447 & -0.459447 \tabularnewline
168 & 0 & 0.226081 & -0.226081 \tabularnewline
169 & 1 & 0.620047 & 0.379953 \tabularnewline
170 & 0 & 0.277996 & -0.277996 \tabularnewline
171 & 1 & 0.292233 & 0.707767 \tabularnewline
172 & 1 & 0.476144 & 0.523856 \tabularnewline
173 & 0 & 0.502505 & -0.502505 \tabularnewline
174 & 1 & 0.24342 & 0.75658 \tabularnewline
175 & 0 & 0.36836 & -0.36836 \tabularnewline
176 & 1 & 0.528796 & 0.471204 \tabularnewline
177 & 1 & 0.379504 & 0.620496 \tabularnewline
178 & 1 & 0.539195 & 0.460805 \tabularnewline
179 & 0 & 0.307796 & -0.307796 \tabularnewline
180 & 0 & 0.669447 & -0.669447 \tabularnewline
181 & 0 & 0.461332 & -0.461332 \tabularnewline
182 & 1 & 0.576342 & 0.423658 \tabularnewline
183 & 1 & 0.53721 & 0.46279 \tabularnewline
184 & 0 & 0.493327 & -0.493327 \tabularnewline
185 & 1 & 0.377355 & 0.622645 \tabularnewline
186 & 0 & 0.349237 & -0.349237 \tabularnewline
187 & 0 & 0.338272 & -0.338272 \tabularnewline
188 & 1 & 0.467522 & 0.532478 \tabularnewline
189 & 1 & 0.584201 & 0.415799 \tabularnewline
190 & 1 & 0.391153 & 0.608847 \tabularnewline
191 & 1 & 0.4458 & 0.5542 \tabularnewline
192 & 1 & 0.501343 & 0.498657 \tabularnewline
193 & 0 & 0.493984 & -0.493984 \tabularnewline
194 & 1 & 0.426223 & 0.573777 \tabularnewline
195 & 1 & 0.57747 & 0.42253 \tabularnewline
196 & 0 & 0.263001 & -0.263001 \tabularnewline
197 & 0 & 0.330501 & -0.330501 \tabularnewline
198 & 0 & 0.534862 & -0.534862 \tabularnewline
199 & 0 & 0.514963 & -0.514963 \tabularnewline
200 & 0 & 0.453424 & -0.453424 \tabularnewline
201 & 1 & 0.492558 & 0.507442 \tabularnewline
202 & 1 & 0.567915 & 0.432085 \tabularnewline
203 & 1 & 0.54441 & 0.45559 \tabularnewline
204 & 0 & 0.612656 & -0.612656 \tabularnewline
205 & 0 & 0.415883 & -0.415883 \tabularnewline
206 & 0 & 0.537831 & -0.537831 \tabularnewline
207 & 1 & 0.337056 & 0.662944 \tabularnewline
208 & 0 & 0.679328 & -0.679328 \tabularnewline
209 & 0 & 0.497213 & -0.497213 \tabularnewline
210 & 0 & 0.321148 & -0.321148 \tabularnewline
211 & 1 & 0.433195 & 0.566805 \tabularnewline
212 & 0 & 0.428419 & -0.428419 \tabularnewline
213 & 1 & 0.630212 & 0.369788 \tabularnewline
214 & 1 & 0.446624 & 0.553376 \tabularnewline
215 & 0 & 0.250469 & -0.250469 \tabularnewline
216 & 1 & 0.615427 & 0.384573 \tabularnewline
217 & 0 & 0.397049 & -0.397049 \tabularnewline
218 & 0 & 0.550308 & -0.550308 \tabularnewline
219 & 1 & 0.368458 & 0.631542 \tabularnewline
220 & 0 & 0.489472 & -0.489472 \tabularnewline
221 & 1 & 0.514317 & 0.485683 \tabularnewline
222 & 0 & 0.642518 & -0.642518 \tabularnewline
223 & 0 & 0.409592 & -0.409592 \tabularnewline
224 & 0 & 0.249358 & -0.249358 \tabularnewline
225 & 0 & 0.380165 & -0.380165 \tabularnewline
226 & 1 & 0.352335 & 0.647665 \tabularnewline
227 & 0 & 0.381152 & -0.381152 \tabularnewline
228 & 0 & 0.467016 & -0.467016 \tabularnewline
229 & 1 & 0.461569 & 0.538431 \tabularnewline
230 & 1 & 0.518771 & 0.481229 \tabularnewline
231 & 0 & 0.31992 & -0.31992 \tabularnewline
232 & 0 & 0.245665 & -0.245665 \tabularnewline
233 & 0 & 0.364397 & -0.364397 \tabularnewline
234 & 1 & 0.386204 & 0.613796 \tabularnewline
235 & 0 & 0.242258 & -0.242258 \tabularnewline
236 & 0 & 0.404128 & -0.404128 \tabularnewline
237 & 0 & 0.309071 & -0.309071 \tabularnewline
238 & 0 & 0.243921 & -0.243921 \tabularnewline
239 & 0 & 0.324209 & -0.324209 \tabularnewline
240 & 0 & 0.401152 & -0.401152 \tabularnewline
241 & 0 & 0.465295 & -0.465295 \tabularnewline
242 & 1 & 0.414049 & 0.585951 \tabularnewline
243 & 1 & 0.233927 & 0.766073 \tabularnewline
244 & 1 & 0.286731 & 0.713269 \tabularnewline
245 & 0 & 0.482485 & -0.482485 \tabularnewline
246 & 0 & 0.369105 & -0.369105 \tabularnewline
247 & 1 & 0.362496 & 0.637504 \tabularnewline
248 & 1 & 0.416186 & 0.583814 \tabularnewline
249 & 0 & 0.377266 & -0.377266 \tabularnewline
250 & 0 & 0.421996 & -0.421996 \tabularnewline
251 & 0 & 0.397679 & -0.397679 \tabularnewline
252 & 1 & 0.278583 & 0.721417 \tabularnewline
253 & 1 & 0.51058 & 0.48942 \tabularnewline
254 & 1 & 0.142513 & 0.857487 \tabularnewline
255 & 1 & 0.498421 & 0.501579 \tabularnewline
256 & 0 & 0.607861 & -0.607861 \tabularnewline
257 & 0 & 0.18026 & -0.18026 \tabularnewline
258 & 0 & 0.475992 & -0.475992 \tabularnewline
259 & 0 & 0.294336 & -0.294336 \tabularnewline
260 & 1 & 0.303401 & 0.696599 \tabularnewline
261 & 0 & 0.462594 & -0.462594 \tabularnewline
262 & 0 & 0.365535 & -0.365535 \tabularnewline
263 & 1 & 0.423449 & 0.576551 \tabularnewline
264 & 0 & 0.202176 & -0.202176 \tabularnewline
265 & 0 & 0.372051 & -0.372051 \tabularnewline
266 & 1 & 0.34025 & 0.65975 \tabularnewline
267 & 1 & 0.392883 & 0.607117 \tabularnewline
268 & 0 & 0.376986 & -0.376986 \tabularnewline
269 & 1 & 0.514046 & 0.485954 \tabularnewline
270 & 0 & 0.478799 & -0.478799 \tabularnewline
271 & 0 & 0.355078 & -0.355078 \tabularnewline
272 & 1 & 0.365969 & 0.634031 \tabularnewline
273 & 0 & 0.451423 & -0.451423 \tabularnewline
274 & 1 & 0.390652 & 0.609348 \tabularnewline
275 & 0 & 0.491415 & -0.491415 \tabularnewline
276 & 0 & 0.253739 & -0.253739 \tabularnewline
277 & 0 & 0.48076 & -0.48076 \tabularnewline
278 & 0 & 0.466877 & -0.466877 \tabularnewline
279 & 1 & 0.561056 & 0.438944 \tabularnewline
280 & 0 & 0.370139 & -0.370139 \tabularnewline
281 & 0 & 0.481064 & -0.481064 \tabularnewline
282 & 1 & 0.502315 & 0.497685 \tabularnewline
283 & 0 & 0.409281 & -0.409281 \tabularnewline
284 & 1 & 0.290861 & 0.709139 \tabularnewline
285 & 0 & 0.614373 & -0.614373 \tabularnewline
286 & 0 & 0.540236 & -0.540236 \tabularnewline
287 & 1 & 0.434835 & 0.565165 \tabularnewline
288 & 1 & 0.536238 & 0.463762 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231833&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]1[/C][C]0.639516[/C][C]0.360484[/C][/ROW]
[ROW][C]2[/C][C]1[/C][C]0.68407[/C][C]0.31593[/C][/ROW]
[ROW][C]3[/C][C]1[/C][C]0.645202[/C][C]0.354798[/C][/ROW]
[ROW][C]4[/C][C]0[/C][C]0.473666[/C][C]-0.473666[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]0.763784[/C][C]0.236216[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]0.646079[/C][C]0.353921[/C][/ROW]
[ROW][C]7[/C][C]1[/C][C]0.56102[/C][C]0.43898[/C][/ROW]
[ROW][C]8[/C][C]1[/C][C]0.702524[/C][C]0.297476[/C][/ROW]
[ROW][C]9[/C][C]1[/C][C]0.66763[/C][C]0.33237[/C][/ROW]
[ROW][C]10[/C][C]1[/C][C]0.654364[/C][C]0.345636[/C][/ROW]
[ROW][C]11[/C][C]0[/C][C]0.626192[/C][C]-0.626192[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]0.787945[/C][C]0.212055[/C][/ROW]
[ROW][C]13[/C][C]0[/C][C]0.491786[/C][C]-0.491786[/C][/ROW]
[ROW][C]14[/C][C]1[/C][C]0.709002[/C][C]0.290998[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.878403[/C][C]0.121597[/C][/ROW]
[ROW][C]16[/C][C]0[/C][C]0.637394[/C][C]-0.637394[/C][/ROW]
[ROW][C]17[/C][C]0[/C][C]0.556162[/C][C]-0.556162[/C][/ROW]
[ROW][C]18[/C][C]1[/C][C]0.775107[/C][C]0.224893[/C][/ROW]
[ROW][C]19[/C][C]0[/C][C]0.64721[/C][C]-0.64721[/C][/ROW]
[ROW][C]20[/C][C]1[/C][C]0.689996[/C][C]0.310004[/C][/ROW]
[ROW][C]21[/C][C]0[/C][C]0.75323[/C][C]-0.75323[/C][/ROW]
[ROW][C]22[/C][C]1[/C][C]0.518256[/C][C]0.481744[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]0.684421[/C][C]0.315579[/C][/ROW]
[ROW][C]24[/C][C]1[/C][C]0.608076[/C][C]0.391924[/C][/ROW]
[ROW][C]25[/C][C]0[/C][C]0.670793[/C][C]-0.670793[/C][/ROW]
[ROW][C]26[/C][C]1[/C][C]0.41001[/C][C]0.58999[/C][/ROW]
[ROW][C]27[/C][C]0[/C][C]0.669211[/C][C]-0.669211[/C][/ROW]
[ROW][C]28[/C][C]1[/C][C]0.725357[/C][C]0.274643[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]0.664517[/C][C]0.335483[/C][/ROW]
[ROW][C]30[/C][C]0[/C][C]0.486132[/C][C]-0.486132[/C][/ROW]
[ROW][C]31[/C][C]1[/C][C]0.680632[/C][C]0.319368[/C][/ROW]
[ROW][C]32[/C][C]0[/C][C]0.551623[/C][C]-0.551623[/C][/ROW]
[ROW][C]33[/C][C]1[/C][C]0.629964[/C][C]0.370036[/C][/ROW]
[ROW][C]34[/C][C]1[/C][C]0.717244[/C][C]0.282756[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]0.574643[/C][C]-0.574643[/C][/ROW]
[ROW][C]36[/C][C]0[/C][C]0.605173[/C][C]-0.605173[/C][/ROW]
[ROW][C]37[/C][C]0[/C][C]0.40326[/C][C]-0.40326[/C][/ROW]
[ROW][C]38[/C][C]0[/C][C]0.637406[/C][C]-0.637406[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]0.695681[/C][C]0.304319[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]0.548099[/C][C]-0.548099[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]0.583285[/C][C]-0.583285[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]0.685718[/C][C]0.314282[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]0.704421[/C][C]-0.704421[/C][/ROW]
[ROW][C]44[/C][C]0[/C][C]0.511281[/C][C]-0.511281[/C][/ROW]
[ROW][C]45[/C][C]1[/C][C]0.511168[/C][C]0.488832[/C][/ROW]
[ROW][C]46[/C][C]1[/C][C]0.522507[/C][C]0.477493[/C][/ROW]
[ROW][C]47[/C][C]1[/C][C]0.730253[/C][C]0.269747[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]0.660037[/C][C]0.339963[/C][/ROW]
[ROW][C]49[/C][C]1[/C][C]0.765035[/C][C]0.234965[/C][/ROW]
[ROW][C]50[/C][C]0[/C][C]0.541112[/C][C]-0.541112[/C][/ROW]
[ROW][C]51[/C][C]1[/C][C]0.815904[/C][C]0.184096[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]0.554848[/C][C]-0.554848[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]0.532863[/C][C]-0.532863[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]0.651364[/C][C]0.348636[/C][/ROW]
[ROW][C]55[/C][C]0[/C][C]0.421371[/C][C]-0.421371[/C][/ROW]
[ROW][C]56[/C][C]1[/C][C]0.554199[/C][C]0.445801[/C][/ROW]
[ROW][C]57[/C][C]1[/C][C]0.666173[/C][C]0.333827[/C][/ROW]
[ROW][C]58[/C][C]1[/C][C]0.710513[/C][C]0.289487[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]0.560767[/C][C]-0.560767[/C][/ROW]
[ROW][C]60[/C][C]1[/C][C]0.530341[/C][C]0.469659[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]0.286045[/C][C]-0.286045[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]0.575284[/C][C]-0.575284[/C][/ROW]
[ROW][C]63[/C][C]1[/C][C]0.590777[/C][C]0.409223[/C][/ROW]
[ROW][C]64[/C][C]1[/C][C]0.655747[/C][C]0.344253[/C][/ROW]
[ROW][C]65[/C][C]1[/C][C]0.626573[/C][C]0.373427[/C][/ROW]
[ROW][C]66[/C][C]0[/C][C]0.564766[/C][C]-0.564766[/C][/ROW]
[ROW][C]67[/C][C]1[/C][C]0.579283[/C][C]0.420717[/C][/ROW]
[ROW][C]68[/C][C]0[/C][C]0.48473[/C][C]-0.48473[/C][/ROW]
[ROW][C]69[/C][C]1[/C][C]0.716078[/C][C]0.283922[/C][/ROW]
[ROW][C]70[/C][C]0[/C][C]0.709523[/C][C]-0.709523[/C][/ROW]
[ROW][C]71[/C][C]0[/C][C]0.55606[/C][C]-0.55606[/C][/ROW]
[ROW][C]72[/C][C]1[/C][C]0.766822[/C][C]0.233178[/C][/ROW]
[ROW][C]73[/C][C]1[/C][C]0.786652[/C][C]0.213348[/C][/ROW]
[ROW][C]74[/C][C]0[/C][C]0.785991[/C][C]-0.785991[/C][/ROW]
[ROW][C]75[/C][C]0[/C][C]0.500385[/C][C]-0.500385[/C][/ROW]
[ROW][C]76[/C][C]1[/C][C]0.423365[/C][C]0.576635[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]0.777438[/C][C]0.222562[/C][/ROW]
[ROW][C]78[/C][C]1[/C][C]0.543215[/C][C]0.456785[/C][/ROW]
[ROW][C]79[/C][C]0[/C][C]0.666977[/C][C]-0.666977[/C][/ROW]
[ROW][C]80[/C][C]0[/C][C]0.477222[/C][C]-0.477222[/C][/ROW]
[ROW][C]81[/C][C]0[/C][C]0.709853[/C][C]-0.709853[/C][/ROW]
[ROW][C]82[/C][C]1[/C][C]0.709523[/C][C]0.290477[/C][/ROW]
[ROW][C]83[/C][C]0[/C][C]0.664529[/C][C]-0.664529[/C][/ROW]
[ROW][C]84[/C][C]1[/C][C]0.667758[/C][C]0.332242[/C][/ROW]
[ROW][C]85[/C][C]1[/C][C]0.566187[/C][C]0.433813[/C][/ROW]
[ROW][C]86[/C][C]0[/C][C]0.65978[/C][C]-0.65978[/C][/ROW]
[ROW][C]87[/C][C]1[/C][C]0.646759[/C][C]0.353241[/C][/ROW]
[ROW][C]88[/C][C]1[/C][C]0.61455[/C][C]0.38545[/C][/ROW]
[ROW][C]89[/C][C]1[/C][C]0.399584[/C][C]0.600416[/C][/ROW]
[ROW][C]90[/C][C]1[/C][C]0.730284[/C][C]0.269716[/C][/ROW]
[ROW][C]91[/C][C]1[/C][C]0.615331[/C][C]0.384669[/C][/ROW]
[ROW][C]92[/C][C]1[/C][C]0.76997[/C][C]0.23003[/C][/ROW]
[ROW][C]93[/C][C]1[/C][C]0.561835[/C][C]0.438165[/C][/ROW]
[ROW][C]94[/C][C]1[/C][C]0.578404[/C][C]0.421596[/C][/ROW]
[ROW][C]95[/C][C]1[/C][C]0.66116[/C][C]0.33884[/C][/ROW]
[ROW][C]96[/C][C]1[/C][C]0.582865[/C][C]0.417135[/C][/ROW]
[ROW][C]97[/C][C]1[/C][C]0.533127[/C][C]0.466873[/C][/ROW]
[ROW][C]98[/C][C]0[/C][C]0.714485[/C][C]-0.714485[/C][/ROW]
[ROW][C]99[/C][C]0[/C][C]0.678389[/C][C]-0.678389[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]0.772224[/C][C]0.227776[/C][/ROW]
[ROW][C]101[/C][C]0[/C][C]0.547629[/C][C]-0.547629[/C][/ROW]
[ROW][C]102[/C][C]1[/C][C]0.795422[/C][C]0.204578[/C][/ROW]
[ROW][C]103[/C][C]0[/C][C]0.445607[/C][C]-0.445607[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]0.73757[/C][C]0.26243[/C][/ROW]
[ROW][C]105[/C][C]0[/C][C]0.392217[/C][C]-0.392217[/C][/ROW]
[ROW][C]106[/C][C]1[/C][C]0.69098[/C][C]0.30902[/C][/ROW]
[ROW][C]107[/C][C]0[/C][C]0.69342[/C][C]-0.69342[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]0.48961[/C][C]-0.48961[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]0.462977[/C][C]0.537023[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]0.702792[/C][C]0.297208[/C][/ROW]
[ROW][C]111[/C][C]1[/C][C]0.583716[/C][C]0.416284[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]0.711749[/C][C]0.288251[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]0.704222[/C][C]0.295778[/C][/ROW]
[ROW][C]114[/C][C]0[/C][C]0.672957[/C][C]-0.672957[/C][/ROW]
[ROW][C]115[/C][C]1[/C][C]0.7511[/C][C]0.2489[/C][/ROW]
[ROW][C]116[/C][C]1[/C][C]0.655288[/C][C]0.344712[/C][/ROW]
[ROW][C]117[/C][C]1[/C][C]0.638331[/C][C]0.361669[/C][/ROW]
[ROW][C]118[/C][C]1[/C][C]0.638378[/C][C]0.361622[/C][/ROW]
[ROW][C]119[/C][C]0[/C][C]0.602815[/C][C]-0.602815[/C][/ROW]
[ROW][C]120[/C][C]1[/C][C]0.574037[/C][C]0.425963[/C][/ROW]
[ROW][C]121[/C][C]1[/C][C]0.710661[/C][C]0.289339[/C][/ROW]
[ROW][C]122[/C][C]1[/C][C]0.744429[/C][C]0.255571[/C][/ROW]
[ROW][C]123[/C][C]1[/C][C]0.626775[/C][C]0.373225[/C][/ROW]
[ROW][C]124[/C][C]1[/C][C]0.667074[/C][C]0.332926[/C][/ROW]
[ROW][C]125[/C][C]0[/C][C]0.631608[/C][C]-0.631608[/C][/ROW]
[ROW][C]126[/C][C]1[/C][C]0.720352[/C][C]0.279648[/C][/ROW]
[ROW][C]127[/C][C]1[/C][C]0.786503[/C][C]0.213497[/C][/ROW]
[ROW][C]128[/C][C]1[/C][C]0.623561[/C][C]0.376439[/C][/ROW]
[ROW][C]129[/C][C]0[/C][C]0.571262[/C][C]-0.571262[/C][/ROW]
[ROW][C]130[/C][C]0[/C][C]0.461329[/C][C]-0.461329[/C][/ROW]
[ROW][C]131[/C][C]1[/C][C]0.600444[/C][C]0.399556[/C][/ROW]
[ROW][C]132[/C][C]0[/C][C]0.639994[/C][C]-0.639994[/C][/ROW]
[ROW][C]133[/C][C]0[/C][C]0.705244[/C][C]-0.705244[/C][/ROW]
[ROW][C]134[/C][C]1[/C][C]0.642687[/C][C]0.357313[/C][/ROW]
[ROW][C]135[/C][C]0[/C][C]0.346636[/C][C]-0.346636[/C][/ROW]
[ROW][C]136[/C][C]0[/C][C]0.634558[/C][C]-0.634558[/C][/ROW]
[ROW][C]137[/C][C]1[/C][C]0.541318[/C][C]0.458682[/C][/ROW]
[ROW][C]138[/C][C]1[/C][C]0.585818[/C][C]0.414182[/C][/ROW]
[ROW][C]139[/C][C]0[/C][C]0.581718[/C][C]-0.581718[/C][/ROW]
[ROW][C]140[/C][C]1[/C][C]0.616877[/C][C]0.383123[/C][/ROW]
[ROW][C]141[/C][C]0[/C][C]0.726169[/C][C]-0.726169[/C][/ROW]
[ROW][C]142[/C][C]1[/C][C]0.739863[/C][C]0.260137[/C][/ROW]
[ROW][C]143[/C][C]0[/C][C]0.511223[/C][C]-0.511223[/C][/ROW]
[ROW][C]144[/C][C]1[/C][C]0.530799[/C][C]0.469201[/C][/ROW]
[ROW][C]145[/C][C]1[/C][C]0.636004[/C][C]0.363996[/C][/ROW]
[ROW][C]146[/C][C]0[/C][C]0.549288[/C][C]-0.549288[/C][/ROW]
[ROW][C]147[/C][C]0[/C][C]0.543405[/C][C]-0.543405[/C][/ROW]
[ROW][C]148[/C][C]0[/C][C]0.377967[/C][C]-0.377967[/C][/ROW]
[ROW][C]149[/C][C]1[/C][C]0.649517[/C][C]0.350483[/C][/ROW]
[ROW][C]150[/C][C]1[/C][C]0.60538[/C][C]0.39462[/C][/ROW]
[ROW][C]151[/C][C]0[/C][C]0.712371[/C][C]-0.712371[/C][/ROW]
[ROW][C]152[/C][C]1[/C][C]0.535427[/C][C]0.464573[/C][/ROW]
[ROW][C]153[/C][C]1[/C][C]0.369384[/C][C]0.630616[/C][/ROW]
[ROW][C]154[/C][C]1[/C][C]0.486236[/C][C]0.513764[/C][/ROW]
[ROW][C]155[/C][C]1[/C][C]0.588184[/C][C]0.411816[/C][/ROW]
[ROW][C]156[/C][C]1[/C][C]0.786503[/C][C]0.213497[/C][/ROW]
[ROW][C]157[/C][C]1[/C][C]0.558326[/C][C]0.441674[/C][/ROW]
[ROW][C]158[/C][C]1[/C][C]0.570819[/C][C]0.429181[/C][/ROW]
[ROW][C]159[/C][C]0[/C][C]0.284928[/C][C]-0.284928[/C][/ROW]
[ROW][C]160[/C][C]0[/C][C]0.348313[/C][C]-0.348313[/C][/ROW]
[ROW][C]161[/C][C]0[/C][C]0.581368[/C][C]-0.581368[/C][/ROW]
[ROW][C]162[/C][C]1[/C][C]0.431283[/C][C]0.568717[/C][/ROW]
[ROW][C]163[/C][C]0[/C][C]0.36025[/C][C]-0.36025[/C][/ROW]
[ROW][C]164[/C][C]0[/C][C]0.51862[/C][C]-0.51862[/C][/ROW]
[ROW][C]165[/C][C]1[/C][C]0.374565[/C][C]0.625435[/C][/ROW]
[ROW][C]166[/C][C]1[/C][C]0.41459[/C][C]0.58541[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.459447[/C][C]-0.459447[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.226081[/C][C]-0.226081[/C][/ROW]
[ROW][C]169[/C][C]1[/C][C]0.620047[/C][C]0.379953[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]0.277996[/C][C]-0.277996[/C][/ROW]
[ROW][C]171[/C][C]1[/C][C]0.292233[/C][C]0.707767[/C][/ROW]
[ROW][C]172[/C][C]1[/C][C]0.476144[/C][C]0.523856[/C][/ROW]
[ROW][C]173[/C][C]0[/C][C]0.502505[/C][C]-0.502505[/C][/ROW]
[ROW][C]174[/C][C]1[/C][C]0.24342[/C][C]0.75658[/C][/ROW]
[ROW][C]175[/C][C]0[/C][C]0.36836[/C][C]-0.36836[/C][/ROW]
[ROW][C]176[/C][C]1[/C][C]0.528796[/C][C]0.471204[/C][/ROW]
[ROW][C]177[/C][C]1[/C][C]0.379504[/C][C]0.620496[/C][/ROW]
[ROW][C]178[/C][C]1[/C][C]0.539195[/C][C]0.460805[/C][/ROW]
[ROW][C]179[/C][C]0[/C][C]0.307796[/C][C]-0.307796[/C][/ROW]
[ROW][C]180[/C][C]0[/C][C]0.669447[/C][C]-0.669447[/C][/ROW]
[ROW][C]181[/C][C]0[/C][C]0.461332[/C][C]-0.461332[/C][/ROW]
[ROW][C]182[/C][C]1[/C][C]0.576342[/C][C]0.423658[/C][/ROW]
[ROW][C]183[/C][C]1[/C][C]0.53721[/C][C]0.46279[/C][/ROW]
[ROW][C]184[/C][C]0[/C][C]0.493327[/C][C]-0.493327[/C][/ROW]
[ROW][C]185[/C][C]1[/C][C]0.377355[/C][C]0.622645[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]0.349237[/C][C]-0.349237[/C][/ROW]
[ROW][C]187[/C][C]0[/C][C]0.338272[/C][C]-0.338272[/C][/ROW]
[ROW][C]188[/C][C]1[/C][C]0.467522[/C][C]0.532478[/C][/ROW]
[ROW][C]189[/C][C]1[/C][C]0.584201[/C][C]0.415799[/C][/ROW]
[ROW][C]190[/C][C]1[/C][C]0.391153[/C][C]0.608847[/C][/ROW]
[ROW][C]191[/C][C]1[/C][C]0.4458[/C][C]0.5542[/C][/ROW]
[ROW][C]192[/C][C]1[/C][C]0.501343[/C][C]0.498657[/C][/ROW]
[ROW][C]193[/C][C]0[/C][C]0.493984[/C][C]-0.493984[/C][/ROW]
[ROW][C]194[/C][C]1[/C][C]0.426223[/C][C]0.573777[/C][/ROW]
[ROW][C]195[/C][C]1[/C][C]0.57747[/C][C]0.42253[/C][/ROW]
[ROW][C]196[/C][C]0[/C][C]0.263001[/C][C]-0.263001[/C][/ROW]
[ROW][C]197[/C][C]0[/C][C]0.330501[/C][C]-0.330501[/C][/ROW]
[ROW][C]198[/C][C]0[/C][C]0.534862[/C][C]-0.534862[/C][/ROW]
[ROW][C]199[/C][C]0[/C][C]0.514963[/C][C]-0.514963[/C][/ROW]
[ROW][C]200[/C][C]0[/C][C]0.453424[/C][C]-0.453424[/C][/ROW]
[ROW][C]201[/C][C]1[/C][C]0.492558[/C][C]0.507442[/C][/ROW]
[ROW][C]202[/C][C]1[/C][C]0.567915[/C][C]0.432085[/C][/ROW]
[ROW][C]203[/C][C]1[/C][C]0.54441[/C][C]0.45559[/C][/ROW]
[ROW][C]204[/C][C]0[/C][C]0.612656[/C][C]-0.612656[/C][/ROW]
[ROW][C]205[/C][C]0[/C][C]0.415883[/C][C]-0.415883[/C][/ROW]
[ROW][C]206[/C][C]0[/C][C]0.537831[/C][C]-0.537831[/C][/ROW]
[ROW][C]207[/C][C]1[/C][C]0.337056[/C][C]0.662944[/C][/ROW]
[ROW][C]208[/C][C]0[/C][C]0.679328[/C][C]-0.679328[/C][/ROW]
[ROW][C]209[/C][C]0[/C][C]0.497213[/C][C]-0.497213[/C][/ROW]
[ROW][C]210[/C][C]0[/C][C]0.321148[/C][C]-0.321148[/C][/ROW]
[ROW][C]211[/C][C]1[/C][C]0.433195[/C][C]0.566805[/C][/ROW]
[ROW][C]212[/C][C]0[/C][C]0.428419[/C][C]-0.428419[/C][/ROW]
[ROW][C]213[/C][C]1[/C][C]0.630212[/C][C]0.369788[/C][/ROW]
[ROW][C]214[/C][C]1[/C][C]0.446624[/C][C]0.553376[/C][/ROW]
[ROW][C]215[/C][C]0[/C][C]0.250469[/C][C]-0.250469[/C][/ROW]
[ROW][C]216[/C][C]1[/C][C]0.615427[/C][C]0.384573[/C][/ROW]
[ROW][C]217[/C][C]0[/C][C]0.397049[/C][C]-0.397049[/C][/ROW]
[ROW][C]218[/C][C]0[/C][C]0.550308[/C][C]-0.550308[/C][/ROW]
[ROW][C]219[/C][C]1[/C][C]0.368458[/C][C]0.631542[/C][/ROW]
[ROW][C]220[/C][C]0[/C][C]0.489472[/C][C]-0.489472[/C][/ROW]
[ROW][C]221[/C][C]1[/C][C]0.514317[/C][C]0.485683[/C][/ROW]
[ROW][C]222[/C][C]0[/C][C]0.642518[/C][C]-0.642518[/C][/ROW]
[ROW][C]223[/C][C]0[/C][C]0.409592[/C][C]-0.409592[/C][/ROW]
[ROW][C]224[/C][C]0[/C][C]0.249358[/C][C]-0.249358[/C][/ROW]
[ROW][C]225[/C][C]0[/C][C]0.380165[/C][C]-0.380165[/C][/ROW]
[ROW][C]226[/C][C]1[/C][C]0.352335[/C][C]0.647665[/C][/ROW]
[ROW][C]227[/C][C]0[/C][C]0.381152[/C][C]-0.381152[/C][/ROW]
[ROW][C]228[/C][C]0[/C][C]0.467016[/C][C]-0.467016[/C][/ROW]
[ROW][C]229[/C][C]1[/C][C]0.461569[/C][C]0.538431[/C][/ROW]
[ROW][C]230[/C][C]1[/C][C]0.518771[/C][C]0.481229[/C][/ROW]
[ROW][C]231[/C][C]0[/C][C]0.31992[/C][C]-0.31992[/C][/ROW]
[ROW][C]232[/C][C]0[/C][C]0.245665[/C][C]-0.245665[/C][/ROW]
[ROW][C]233[/C][C]0[/C][C]0.364397[/C][C]-0.364397[/C][/ROW]
[ROW][C]234[/C][C]1[/C][C]0.386204[/C][C]0.613796[/C][/ROW]
[ROW][C]235[/C][C]0[/C][C]0.242258[/C][C]-0.242258[/C][/ROW]
[ROW][C]236[/C][C]0[/C][C]0.404128[/C][C]-0.404128[/C][/ROW]
[ROW][C]237[/C][C]0[/C][C]0.309071[/C][C]-0.309071[/C][/ROW]
[ROW][C]238[/C][C]0[/C][C]0.243921[/C][C]-0.243921[/C][/ROW]
[ROW][C]239[/C][C]0[/C][C]0.324209[/C][C]-0.324209[/C][/ROW]
[ROW][C]240[/C][C]0[/C][C]0.401152[/C][C]-0.401152[/C][/ROW]
[ROW][C]241[/C][C]0[/C][C]0.465295[/C][C]-0.465295[/C][/ROW]
[ROW][C]242[/C][C]1[/C][C]0.414049[/C][C]0.585951[/C][/ROW]
[ROW][C]243[/C][C]1[/C][C]0.233927[/C][C]0.766073[/C][/ROW]
[ROW][C]244[/C][C]1[/C][C]0.286731[/C][C]0.713269[/C][/ROW]
[ROW][C]245[/C][C]0[/C][C]0.482485[/C][C]-0.482485[/C][/ROW]
[ROW][C]246[/C][C]0[/C][C]0.369105[/C][C]-0.369105[/C][/ROW]
[ROW][C]247[/C][C]1[/C][C]0.362496[/C][C]0.637504[/C][/ROW]
[ROW][C]248[/C][C]1[/C][C]0.416186[/C][C]0.583814[/C][/ROW]
[ROW][C]249[/C][C]0[/C][C]0.377266[/C][C]-0.377266[/C][/ROW]
[ROW][C]250[/C][C]0[/C][C]0.421996[/C][C]-0.421996[/C][/ROW]
[ROW][C]251[/C][C]0[/C][C]0.397679[/C][C]-0.397679[/C][/ROW]
[ROW][C]252[/C][C]1[/C][C]0.278583[/C][C]0.721417[/C][/ROW]
[ROW][C]253[/C][C]1[/C][C]0.51058[/C][C]0.48942[/C][/ROW]
[ROW][C]254[/C][C]1[/C][C]0.142513[/C][C]0.857487[/C][/ROW]
[ROW][C]255[/C][C]1[/C][C]0.498421[/C][C]0.501579[/C][/ROW]
[ROW][C]256[/C][C]0[/C][C]0.607861[/C][C]-0.607861[/C][/ROW]
[ROW][C]257[/C][C]0[/C][C]0.18026[/C][C]-0.18026[/C][/ROW]
[ROW][C]258[/C][C]0[/C][C]0.475992[/C][C]-0.475992[/C][/ROW]
[ROW][C]259[/C][C]0[/C][C]0.294336[/C][C]-0.294336[/C][/ROW]
[ROW][C]260[/C][C]1[/C][C]0.303401[/C][C]0.696599[/C][/ROW]
[ROW][C]261[/C][C]0[/C][C]0.462594[/C][C]-0.462594[/C][/ROW]
[ROW][C]262[/C][C]0[/C][C]0.365535[/C][C]-0.365535[/C][/ROW]
[ROW][C]263[/C][C]1[/C][C]0.423449[/C][C]0.576551[/C][/ROW]
[ROW][C]264[/C][C]0[/C][C]0.202176[/C][C]-0.202176[/C][/ROW]
[ROW][C]265[/C][C]0[/C][C]0.372051[/C][C]-0.372051[/C][/ROW]
[ROW][C]266[/C][C]1[/C][C]0.34025[/C][C]0.65975[/C][/ROW]
[ROW][C]267[/C][C]1[/C][C]0.392883[/C][C]0.607117[/C][/ROW]
[ROW][C]268[/C][C]0[/C][C]0.376986[/C][C]-0.376986[/C][/ROW]
[ROW][C]269[/C][C]1[/C][C]0.514046[/C][C]0.485954[/C][/ROW]
[ROW][C]270[/C][C]0[/C][C]0.478799[/C][C]-0.478799[/C][/ROW]
[ROW][C]271[/C][C]0[/C][C]0.355078[/C][C]-0.355078[/C][/ROW]
[ROW][C]272[/C][C]1[/C][C]0.365969[/C][C]0.634031[/C][/ROW]
[ROW][C]273[/C][C]0[/C][C]0.451423[/C][C]-0.451423[/C][/ROW]
[ROW][C]274[/C][C]1[/C][C]0.390652[/C][C]0.609348[/C][/ROW]
[ROW][C]275[/C][C]0[/C][C]0.491415[/C][C]-0.491415[/C][/ROW]
[ROW][C]276[/C][C]0[/C][C]0.253739[/C][C]-0.253739[/C][/ROW]
[ROW][C]277[/C][C]0[/C][C]0.48076[/C][C]-0.48076[/C][/ROW]
[ROW][C]278[/C][C]0[/C][C]0.466877[/C][C]-0.466877[/C][/ROW]
[ROW][C]279[/C][C]1[/C][C]0.561056[/C][C]0.438944[/C][/ROW]
[ROW][C]280[/C][C]0[/C][C]0.370139[/C][C]-0.370139[/C][/ROW]
[ROW][C]281[/C][C]0[/C][C]0.481064[/C][C]-0.481064[/C][/ROW]
[ROW][C]282[/C][C]1[/C][C]0.502315[/C][C]0.497685[/C][/ROW]
[ROW][C]283[/C][C]0[/C][C]0.409281[/C][C]-0.409281[/C][/ROW]
[ROW][C]284[/C][C]1[/C][C]0.290861[/C][C]0.709139[/C][/ROW]
[ROW][C]285[/C][C]0[/C][C]0.614373[/C][C]-0.614373[/C][/ROW]
[ROW][C]286[/C][C]0[/C][C]0.540236[/C][C]-0.540236[/C][/ROW]
[ROW][C]287[/C][C]1[/C][C]0.434835[/C][C]0.565165[/C][/ROW]
[ROW][C]288[/C][C]1[/C][C]0.536238[/C][C]0.463762[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231833&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231833&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
110.6395160.360484
210.684070.31593
310.6452020.354798
400.473666-0.473666
510.7637840.236216
610.6460790.353921
710.561020.43898
810.7025240.297476
910.667630.33237
1010.6543640.345636
1100.626192-0.626192
1210.7879450.212055
1300.491786-0.491786
1410.7090020.290998
1510.8784030.121597
1600.637394-0.637394
1700.556162-0.556162
1810.7751070.224893
1900.64721-0.64721
2010.6899960.310004
2100.75323-0.75323
2210.5182560.481744
2310.6844210.315579
2410.6080760.391924
2500.670793-0.670793
2610.410010.58999
2700.669211-0.669211
2810.7253570.274643
2910.6645170.335483
3000.486132-0.486132
3110.6806320.319368
3200.551623-0.551623
3310.6299640.370036
3410.7172440.282756
3500.574643-0.574643
3600.605173-0.605173
3700.40326-0.40326
3800.637406-0.637406
3910.6956810.304319
4000.548099-0.548099
4100.583285-0.583285
4210.6857180.314282
4300.704421-0.704421
4400.511281-0.511281
4510.5111680.488832
4610.5225070.477493
4710.7302530.269747
4810.6600370.339963
4910.7650350.234965
5000.541112-0.541112
5110.8159040.184096
5200.554848-0.554848
5300.532863-0.532863
5410.6513640.348636
5500.421371-0.421371
5610.5541990.445801
5710.6661730.333827
5810.7105130.289487
5900.560767-0.560767
6010.5303410.469659
6100.286045-0.286045
6200.575284-0.575284
6310.5907770.409223
6410.6557470.344253
6510.6265730.373427
6600.564766-0.564766
6710.5792830.420717
6800.48473-0.48473
6910.7160780.283922
7000.709523-0.709523
7100.55606-0.55606
7210.7668220.233178
7310.7866520.213348
7400.785991-0.785991
7500.500385-0.500385
7610.4233650.576635
7710.7774380.222562
7810.5432150.456785
7900.666977-0.666977
8000.477222-0.477222
8100.709853-0.709853
8210.7095230.290477
8300.664529-0.664529
8410.6677580.332242
8510.5661870.433813
8600.65978-0.65978
8710.6467590.353241
8810.614550.38545
8910.3995840.600416
9010.7302840.269716
9110.6153310.384669
9210.769970.23003
9310.5618350.438165
9410.5784040.421596
9510.661160.33884
9610.5828650.417135
9710.5331270.466873
9800.714485-0.714485
9900.678389-0.678389
10010.7722240.227776
10100.547629-0.547629
10210.7954220.204578
10300.445607-0.445607
10410.737570.26243
10500.392217-0.392217
10610.690980.30902
10700.69342-0.69342
10800.48961-0.48961
10910.4629770.537023
11010.7027920.297208
11110.5837160.416284
11210.7117490.288251
11310.7042220.295778
11400.672957-0.672957
11510.75110.2489
11610.6552880.344712
11710.6383310.361669
11810.6383780.361622
11900.602815-0.602815
12010.5740370.425963
12110.7106610.289339
12210.7444290.255571
12310.6267750.373225
12410.6670740.332926
12500.631608-0.631608
12610.7203520.279648
12710.7865030.213497
12810.6235610.376439
12900.571262-0.571262
13000.461329-0.461329
13110.6004440.399556
13200.639994-0.639994
13300.705244-0.705244
13410.6426870.357313
13500.346636-0.346636
13600.634558-0.634558
13710.5413180.458682
13810.5858180.414182
13900.581718-0.581718
14010.6168770.383123
14100.726169-0.726169
14210.7398630.260137
14300.511223-0.511223
14410.5307990.469201
14510.6360040.363996
14600.549288-0.549288
14700.543405-0.543405
14800.377967-0.377967
14910.6495170.350483
15010.605380.39462
15100.712371-0.712371
15210.5354270.464573
15310.3693840.630616
15410.4862360.513764
15510.5881840.411816
15610.7865030.213497
15710.5583260.441674
15810.5708190.429181
15900.284928-0.284928
16000.348313-0.348313
16100.581368-0.581368
16210.4312830.568717
16300.36025-0.36025
16400.51862-0.51862
16510.3745650.625435
16610.414590.58541
16700.459447-0.459447
16800.226081-0.226081
16910.6200470.379953
17000.277996-0.277996
17110.2922330.707767
17210.4761440.523856
17300.502505-0.502505
17410.243420.75658
17500.36836-0.36836
17610.5287960.471204
17710.3795040.620496
17810.5391950.460805
17900.307796-0.307796
18000.669447-0.669447
18100.461332-0.461332
18210.5763420.423658
18310.537210.46279
18400.493327-0.493327
18510.3773550.622645
18600.349237-0.349237
18700.338272-0.338272
18810.4675220.532478
18910.5842010.415799
19010.3911530.608847
19110.44580.5542
19210.5013430.498657
19300.493984-0.493984
19410.4262230.573777
19510.577470.42253
19600.263001-0.263001
19700.330501-0.330501
19800.534862-0.534862
19900.514963-0.514963
20000.453424-0.453424
20110.4925580.507442
20210.5679150.432085
20310.544410.45559
20400.612656-0.612656
20500.415883-0.415883
20600.537831-0.537831
20710.3370560.662944
20800.679328-0.679328
20900.497213-0.497213
21000.321148-0.321148
21110.4331950.566805
21200.428419-0.428419
21310.6302120.369788
21410.4466240.553376
21500.250469-0.250469
21610.6154270.384573
21700.397049-0.397049
21800.550308-0.550308
21910.3684580.631542
22000.489472-0.489472
22110.5143170.485683
22200.642518-0.642518
22300.409592-0.409592
22400.249358-0.249358
22500.380165-0.380165
22610.3523350.647665
22700.381152-0.381152
22800.467016-0.467016
22910.4615690.538431
23010.5187710.481229
23100.31992-0.31992
23200.245665-0.245665
23300.364397-0.364397
23410.3862040.613796
23500.242258-0.242258
23600.404128-0.404128
23700.309071-0.309071
23800.243921-0.243921
23900.324209-0.324209
24000.401152-0.401152
24100.465295-0.465295
24210.4140490.585951
24310.2339270.766073
24410.2867310.713269
24500.482485-0.482485
24600.369105-0.369105
24710.3624960.637504
24810.4161860.583814
24900.377266-0.377266
25000.421996-0.421996
25100.397679-0.397679
25210.2785830.721417
25310.510580.48942
25410.1425130.857487
25510.4984210.501579
25600.607861-0.607861
25700.18026-0.18026
25800.475992-0.475992
25900.294336-0.294336
26010.3034010.696599
26100.462594-0.462594
26200.365535-0.365535
26310.4234490.576551
26400.202176-0.202176
26500.372051-0.372051
26610.340250.65975
26710.3928830.607117
26800.376986-0.376986
26910.5140460.485954
27000.478799-0.478799
27100.355078-0.355078
27210.3659690.634031
27300.451423-0.451423
27410.3906520.609348
27500.491415-0.491415
27600.253739-0.253739
27700.48076-0.48076
27800.466877-0.466877
27910.5610560.438944
28000.370139-0.370139
28100.481064-0.481064
28210.5023150.497685
28300.409281-0.409281
28410.2908610.709139
28500.614373-0.614373
28600.540236-0.540236
28710.4348350.565165
28810.5362380.463762







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.08223570.1644710.917764
110.4875780.9751550.512422
120.3423720.6847450.657628
130.4028220.8056440.597178
140.290170.580340.70983
150.2803890.5607780.719611
160.3632710.7265430.636729
170.3439990.6879990.656001
180.27070.5414010.7293
190.3776890.7553790.622311
200.324630.649260.67537
210.4509450.901890.549055
220.4973340.9946670.502666
230.4336760.8673520.566324
240.4063640.8127280.593636
250.4881380.9762750.511862
260.4635080.9270160.536492
270.4768570.9537140.523143
280.4133210.8266430.586679
290.3821030.7642060.617897
300.3707850.7415690.629215
310.3418840.6837670.658116
320.2974190.5948370.702581
330.2949890.5899770.705011
340.2581870.5163740.741813
350.3034740.6069480.696526
360.2683360.5366730.731664
370.2279570.4559150.772043
380.2828880.5657750.717112
390.2956170.5912330.704383
400.2836610.5673220.716339
410.276290.552580.72371
420.2496980.4993960.750302
430.3734980.7469960.626502
440.351610.703220.64839
450.4120780.8241570.587922
460.3887530.7775060.611247
470.3447260.6894530.655274
480.331640.663280.66836
490.2973520.5947040.702648
500.3165420.6330830.683458
510.2778210.5556420.722179
520.2630260.5260520.736974
530.2722210.5444410.727779
540.2446990.4893990.755301
550.2174350.4348710.782565
560.2611670.5223330.738833
570.2378470.4756940.762153
580.220380.4407610.77962
590.2340470.4680940.765953
600.2539870.5079740.746013
610.23050.4610010.7695
620.2469140.4938290.753086
630.2314530.4629050.768547
640.2162150.432430.783785
650.2107990.4215980.789201
660.2336610.4673220.766339
670.2219990.4439980.778001
680.2041660.4083320.795834
690.1787370.3574730.821263
700.2319480.4638960.768052
710.2324020.4648040.767598
720.2062520.4125050.793748
730.1800870.3601740.819913
740.2752040.5504080.724796
750.2667170.5334350.733283
760.3231420.6462850.676858
770.2915910.5831820.708409
780.2997030.5994060.700297
790.3218580.6437150.678142
800.3131250.6262490.686875
810.3581890.7163780.641811
820.3330820.6661630.666918
830.3658220.7316450.634178
840.3521860.7043730.647814
850.3592460.7184930.640754
860.3885640.7771280.611436
870.3725090.7450190.627491
880.3621990.7243970.637801
890.3850050.7700110.614995
900.3680480.7360960.631952
910.3486450.6972910.651355
920.3191190.6382390.680881
930.3181210.6362420.681879
940.3113310.6226610.688669
950.2995920.5991830.700408
960.2873920.5747830.712608
970.2962720.5925440.703728
980.3366110.6732210.663389
990.3642240.7284490.635776
1000.3352070.6704150.664793
1010.3446560.6893130.655344
1020.3146080.6292170.685392
1030.3073450.6146890.692655
1040.2842990.5685970.715701
1050.2719480.5438950.728052
1060.2531650.5063310.746835
1070.2882750.576550.711725
1080.2889450.577890.711055
1090.314880.629760.68512
1100.2936890.5873780.706311
1110.2805840.5611680.719416
1120.2584680.5169360.741532
1130.2463140.4926280.753686
1140.2774820.5549650.722518
1150.2543530.5087050.745647
1160.2413180.4826360.758682
1170.2299040.4598090.770096
1180.2172420.4344850.782758
1190.2341030.4682060.765897
1200.2295690.4591370.770431
1210.2124680.4249350.787532
1220.1934560.3869110.806544
1230.1845980.3691960.815402
1240.1716880.3433760.828312
1250.1830440.3660870.816956
1260.1684240.3368470.831576
1270.1529220.3058450.847078
1280.1479790.2959580.852021
1290.1536090.3072190.846391
1300.1489690.2979390.851031
1310.145750.2914990.85425
1320.1555130.3110260.844487
1330.1836460.3672910.816354
1340.174960.349920.82504
1350.16580.33160.8342
1360.1842670.3685340.815733
1370.184710.3694190.81529
1380.1830380.3660750.816962
1390.1912180.3824370.808782
1400.1834770.3669540.816523
1410.2159880.4319760.784012
1420.1957050.391410.804295
1430.2062420.4124840.793758
1440.2087790.4175570.791221
1450.1952260.3904530.804774
1460.2093120.4186250.790688
1470.2315450.4630910.768455
1480.2417270.4834550.758273
1490.2265790.4531570.773421
1500.2076890.4153770.792311
1510.2660330.5320660.733967
1520.2596730.5193460.740327
1530.2655230.5310460.734477
1540.2634610.5269220.736539
1550.2496920.4993840.750308
1560.2263810.4527620.773619
1570.213530.4270610.78647
1580.1987060.3974120.801294
1590.1844350.3688690.815565
1600.173570.347140.82643
1610.1746640.3493280.825336
1620.1969680.3939350.803032
1630.18180.36360.8182
1640.1770670.3541350.822933
1650.2040940.4081880.795906
1660.2211350.4422710.778865
1670.2149270.4298530.785073
1680.1980870.3961750.801913
1690.1925030.3850070.807497
1700.1774420.3548840.822558
1710.2059010.4118010.794099
1720.2065790.4131590.793421
1730.207560.415120.79244
1740.2381940.4763880.761806
1750.2285310.4570630.771469
1760.2256680.4513360.774332
1770.2417640.4835270.758236
1780.238570.4771390.76143
1790.2270520.4541030.772948
1800.2510110.5020220.748989
1810.251830.5036610.74817
1820.2528480.5056950.747152
1830.2530950.506190.746905
1840.25880.5176010.7412
1850.2676880.5353750.732312
1860.257550.5150990.74245
1870.2431170.4862330.756883
1880.2553220.5106440.744678
1890.2568590.5137170.743141
1900.2656060.5312110.734394
1910.2763550.552710.723645
1920.2789960.5579930.721004
1930.2783640.5567290.721636
1940.281030.5620590.71897
1950.2834620.5669230.716538
1960.2666480.5332970.733352
1970.2582630.5165260.741737
1980.2626640.5253290.737336
1990.2644010.5288010.735599
2000.2595310.5190630.740469
2010.2640590.5281190.735941
2020.2677770.5355550.732223
2030.2758940.5517880.724106
2040.2839920.5679840.716008
2050.2747940.5495890.725206
2060.2780660.5561330.721934
2070.305290.610580.69471
2080.3119420.6238840.688058
2090.3009280.6018550.699072
2100.287250.57450.71275
2110.3017790.6035580.698221
2120.3129960.6259930.687004
2130.3048440.6096870.695156
2140.318650.63730.68135
2150.2943250.5886510.705675
2160.3136790.6273580.686321
2170.2988490.5976980.701151
2180.2928230.5856470.707177
2190.3127480.6254960.687252
2200.3065880.6131760.693412
2210.3407420.6814840.659258
2220.3527560.7055120.647244
2230.3386310.6772620.661369
2240.310880.6217590.68912
2250.2898070.5796150.710193
2260.3010680.6021350.698932
2270.2748040.5496070.725196
2280.2726840.5453670.727316
2290.2802650.560530.719735
2300.289420.578840.71058
2310.267850.5357010.73215
2320.2408020.4816050.759198
2330.237380.4747590.76262
2340.2487090.4974180.751291
2350.2365170.4730330.763483
2360.2224880.4449760.777512
2370.2026740.4053470.797326
2380.2013720.4027430.798628
2390.1980560.3961120.801944
2400.1841330.3682660.815867
2410.1768590.3537180.823141
2420.1960970.3921950.803903
2430.1921610.3843220.807839
2440.1895350.3790710.810465
2450.1896280.3792550.810372
2460.1841210.3682420.815879
2470.1813490.3626980.818651
2480.18320.3664010.8168
2490.1663830.3327660.833617
2500.152870.3057390.84713
2510.1373570.2747150.862643
2520.1499570.2999140.850043
2530.1604520.3209040.839548
2540.1929430.3858850.807057
2550.1930350.3860690.806965
2560.1881910.3763830.811809
2570.158780.317560.84122
2580.1479040.2958080.852096
2590.1291110.2582220.870889
2600.1565680.3131370.843432
2610.1791240.3582480.820876
2620.1500370.3000750.849963
2630.1984070.3968130.801593
2640.1701860.3403720.829814
2650.1367950.273590.863205
2660.1923490.3846980.807651
2670.4116490.8232990.588351
2680.3497620.6995230.650238
2690.3792990.7585980.620701
2700.4202840.8405680.579716
2710.3900550.7801090.609945
2720.7557060.4885880.244294
2730.6938610.6122780.306139
2740.7038610.5922780.296139
2750.6105960.7788090.389404
2760.537290.9254210.46271
2770.4386440.8772890.561356
2780.3146060.6292130.685394

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.0822357 & 0.164471 & 0.917764 \tabularnewline
11 & 0.487578 & 0.975155 & 0.512422 \tabularnewline
12 & 0.342372 & 0.684745 & 0.657628 \tabularnewline
13 & 0.402822 & 0.805644 & 0.597178 \tabularnewline
14 & 0.29017 & 0.58034 & 0.70983 \tabularnewline
15 & 0.280389 & 0.560778 & 0.719611 \tabularnewline
16 & 0.363271 & 0.726543 & 0.636729 \tabularnewline
17 & 0.343999 & 0.687999 & 0.656001 \tabularnewline
18 & 0.2707 & 0.541401 & 0.7293 \tabularnewline
19 & 0.377689 & 0.755379 & 0.622311 \tabularnewline
20 & 0.32463 & 0.64926 & 0.67537 \tabularnewline
21 & 0.450945 & 0.90189 & 0.549055 \tabularnewline
22 & 0.497334 & 0.994667 & 0.502666 \tabularnewline
23 & 0.433676 & 0.867352 & 0.566324 \tabularnewline
24 & 0.406364 & 0.812728 & 0.593636 \tabularnewline
25 & 0.488138 & 0.976275 & 0.511862 \tabularnewline
26 & 0.463508 & 0.927016 & 0.536492 \tabularnewline
27 & 0.476857 & 0.953714 & 0.523143 \tabularnewline
28 & 0.413321 & 0.826643 & 0.586679 \tabularnewline
29 & 0.382103 & 0.764206 & 0.617897 \tabularnewline
30 & 0.370785 & 0.741569 & 0.629215 \tabularnewline
31 & 0.341884 & 0.683767 & 0.658116 \tabularnewline
32 & 0.297419 & 0.594837 & 0.702581 \tabularnewline
33 & 0.294989 & 0.589977 & 0.705011 \tabularnewline
34 & 0.258187 & 0.516374 & 0.741813 \tabularnewline
35 & 0.303474 & 0.606948 & 0.696526 \tabularnewline
36 & 0.268336 & 0.536673 & 0.731664 \tabularnewline
37 & 0.227957 & 0.455915 & 0.772043 \tabularnewline
38 & 0.282888 & 0.565775 & 0.717112 \tabularnewline
39 & 0.295617 & 0.591233 & 0.704383 \tabularnewline
40 & 0.283661 & 0.567322 & 0.716339 \tabularnewline
41 & 0.27629 & 0.55258 & 0.72371 \tabularnewline
42 & 0.249698 & 0.499396 & 0.750302 \tabularnewline
43 & 0.373498 & 0.746996 & 0.626502 \tabularnewline
44 & 0.35161 & 0.70322 & 0.64839 \tabularnewline
45 & 0.412078 & 0.824157 & 0.587922 \tabularnewline
46 & 0.388753 & 0.777506 & 0.611247 \tabularnewline
47 & 0.344726 & 0.689453 & 0.655274 \tabularnewline
48 & 0.33164 & 0.66328 & 0.66836 \tabularnewline
49 & 0.297352 & 0.594704 & 0.702648 \tabularnewline
50 & 0.316542 & 0.633083 & 0.683458 \tabularnewline
51 & 0.277821 & 0.555642 & 0.722179 \tabularnewline
52 & 0.263026 & 0.526052 & 0.736974 \tabularnewline
53 & 0.272221 & 0.544441 & 0.727779 \tabularnewline
54 & 0.244699 & 0.489399 & 0.755301 \tabularnewline
55 & 0.217435 & 0.434871 & 0.782565 \tabularnewline
56 & 0.261167 & 0.522333 & 0.738833 \tabularnewline
57 & 0.237847 & 0.475694 & 0.762153 \tabularnewline
58 & 0.22038 & 0.440761 & 0.77962 \tabularnewline
59 & 0.234047 & 0.468094 & 0.765953 \tabularnewline
60 & 0.253987 & 0.507974 & 0.746013 \tabularnewline
61 & 0.2305 & 0.461001 & 0.7695 \tabularnewline
62 & 0.246914 & 0.493829 & 0.753086 \tabularnewline
63 & 0.231453 & 0.462905 & 0.768547 \tabularnewline
64 & 0.216215 & 0.43243 & 0.783785 \tabularnewline
65 & 0.210799 & 0.421598 & 0.789201 \tabularnewline
66 & 0.233661 & 0.467322 & 0.766339 \tabularnewline
67 & 0.221999 & 0.443998 & 0.778001 \tabularnewline
68 & 0.204166 & 0.408332 & 0.795834 \tabularnewline
69 & 0.178737 & 0.357473 & 0.821263 \tabularnewline
70 & 0.231948 & 0.463896 & 0.768052 \tabularnewline
71 & 0.232402 & 0.464804 & 0.767598 \tabularnewline
72 & 0.206252 & 0.412505 & 0.793748 \tabularnewline
73 & 0.180087 & 0.360174 & 0.819913 \tabularnewline
74 & 0.275204 & 0.550408 & 0.724796 \tabularnewline
75 & 0.266717 & 0.533435 & 0.733283 \tabularnewline
76 & 0.323142 & 0.646285 & 0.676858 \tabularnewline
77 & 0.291591 & 0.583182 & 0.708409 \tabularnewline
78 & 0.299703 & 0.599406 & 0.700297 \tabularnewline
79 & 0.321858 & 0.643715 & 0.678142 \tabularnewline
80 & 0.313125 & 0.626249 & 0.686875 \tabularnewline
81 & 0.358189 & 0.716378 & 0.641811 \tabularnewline
82 & 0.333082 & 0.666163 & 0.666918 \tabularnewline
83 & 0.365822 & 0.731645 & 0.634178 \tabularnewline
84 & 0.352186 & 0.704373 & 0.647814 \tabularnewline
85 & 0.359246 & 0.718493 & 0.640754 \tabularnewline
86 & 0.388564 & 0.777128 & 0.611436 \tabularnewline
87 & 0.372509 & 0.745019 & 0.627491 \tabularnewline
88 & 0.362199 & 0.724397 & 0.637801 \tabularnewline
89 & 0.385005 & 0.770011 & 0.614995 \tabularnewline
90 & 0.368048 & 0.736096 & 0.631952 \tabularnewline
91 & 0.348645 & 0.697291 & 0.651355 \tabularnewline
92 & 0.319119 & 0.638239 & 0.680881 \tabularnewline
93 & 0.318121 & 0.636242 & 0.681879 \tabularnewline
94 & 0.311331 & 0.622661 & 0.688669 \tabularnewline
95 & 0.299592 & 0.599183 & 0.700408 \tabularnewline
96 & 0.287392 & 0.574783 & 0.712608 \tabularnewline
97 & 0.296272 & 0.592544 & 0.703728 \tabularnewline
98 & 0.336611 & 0.673221 & 0.663389 \tabularnewline
99 & 0.364224 & 0.728449 & 0.635776 \tabularnewline
100 & 0.335207 & 0.670415 & 0.664793 \tabularnewline
101 & 0.344656 & 0.689313 & 0.655344 \tabularnewline
102 & 0.314608 & 0.629217 & 0.685392 \tabularnewline
103 & 0.307345 & 0.614689 & 0.692655 \tabularnewline
104 & 0.284299 & 0.568597 & 0.715701 \tabularnewline
105 & 0.271948 & 0.543895 & 0.728052 \tabularnewline
106 & 0.253165 & 0.506331 & 0.746835 \tabularnewline
107 & 0.288275 & 0.57655 & 0.711725 \tabularnewline
108 & 0.288945 & 0.57789 & 0.711055 \tabularnewline
109 & 0.31488 & 0.62976 & 0.68512 \tabularnewline
110 & 0.293689 & 0.587378 & 0.706311 \tabularnewline
111 & 0.280584 & 0.561168 & 0.719416 \tabularnewline
112 & 0.258468 & 0.516936 & 0.741532 \tabularnewline
113 & 0.246314 & 0.492628 & 0.753686 \tabularnewline
114 & 0.277482 & 0.554965 & 0.722518 \tabularnewline
115 & 0.254353 & 0.508705 & 0.745647 \tabularnewline
116 & 0.241318 & 0.482636 & 0.758682 \tabularnewline
117 & 0.229904 & 0.459809 & 0.770096 \tabularnewline
118 & 0.217242 & 0.434485 & 0.782758 \tabularnewline
119 & 0.234103 & 0.468206 & 0.765897 \tabularnewline
120 & 0.229569 & 0.459137 & 0.770431 \tabularnewline
121 & 0.212468 & 0.424935 & 0.787532 \tabularnewline
122 & 0.193456 & 0.386911 & 0.806544 \tabularnewline
123 & 0.184598 & 0.369196 & 0.815402 \tabularnewline
124 & 0.171688 & 0.343376 & 0.828312 \tabularnewline
125 & 0.183044 & 0.366087 & 0.816956 \tabularnewline
126 & 0.168424 & 0.336847 & 0.831576 \tabularnewline
127 & 0.152922 & 0.305845 & 0.847078 \tabularnewline
128 & 0.147979 & 0.295958 & 0.852021 \tabularnewline
129 & 0.153609 & 0.307219 & 0.846391 \tabularnewline
130 & 0.148969 & 0.297939 & 0.851031 \tabularnewline
131 & 0.14575 & 0.291499 & 0.85425 \tabularnewline
132 & 0.155513 & 0.311026 & 0.844487 \tabularnewline
133 & 0.183646 & 0.367291 & 0.816354 \tabularnewline
134 & 0.17496 & 0.34992 & 0.82504 \tabularnewline
135 & 0.1658 & 0.3316 & 0.8342 \tabularnewline
136 & 0.184267 & 0.368534 & 0.815733 \tabularnewline
137 & 0.18471 & 0.369419 & 0.81529 \tabularnewline
138 & 0.183038 & 0.366075 & 0.816962 \tabularnewline
139 & 0.191218 & 0.382437 & 0.808782 \tabularnewline
140 & 0.183477 & 0.366954 & 0.816523 \tabularnewline
141 & 0.215988 & 0.431976 & 0.784012 \tabularnewline
142 & 0.195705 & 0.39141 & 0.804295 \tabularnewline
143 & 0.206242 & 0.412484 & 0.793758 \tabularnewline
144 & 0.208779 & 0.417557 & 0.791221 \tabularnewline
145 & 0.195226 & 0.390453 & 0.804774 \tabularnewline
146 & 0.209312 & 0.418625 & 0.790688 \tabularnewline
147 & 0.231545 & 0.463091 & 0.768455 \tabularnewline
148 & 0.241727 & 0.483455 & 0.758273 \tabularnewline
149 & 0.226579 & 0.453157 & 0.773421 \tabularnewline
150 & 0.207689 & 0.415377 & 0.792311 \tabularnewline
151 & 0.266033 & 0.532066 & 0.733967 \tabularnewline
152 & 0.259673 & 0.519346 & 0.740327 \tabularnewline
153 & 0.265523 & 0.531046 & 0.734477 \tabularnewline
154 & 0.263461 & 0.526922 & 0.736539 \tabularnewline
155 & 0.249692 & 0.499384 & 0.750308 \tabularnewline
156 & 0.226381 & 0.452762 & 0.773619 \tabularnewline
157 & 0.21353 & 0.427061 & 0.78647 \tabularnewline
158 & 0.198706 & 0.397412 & 0.801294 \tabularnewline
159 & 0.184435 & 0.368869 & 0.815565 \tabularnewline
160 & 0.17357 & 0.34714 & 0.82643 \tabularnewline
161 & 0.174664 & 0.349328 & 0.825336 \tabularnewline
162 & 0.196968 & 0.393935 & 0.803032 \tabularnewline
163 & 0.1818 & 0.3636 & 0.8182 \tabularnewline
164 & 0.177067 & 0.354135 & 0.822933 \tabularnewline
165 & 0.204094 & 0.408188 & 0.795906 \tabularnewline
166 & 0.221135 & 0.442271 & 0.778865 \tabularnewline
167 & 0.214927 & 0.429853 & 0.785073 \tabularnewline
168 & 0.198087 & 0.396175 & 0.801913 \tabularnewline
169 & 0.192503 & 0.385007 & 0.807497 \tabularnewline
170 & 0.177442 & 0.354884 & 0.822558 \tabularnewline
171 & 0.205901 & 0.411801 & 0.794099 \tabularnewline
172 & 0.206579 & 0.413159 & 0.793421 \tabularnewline
173 & 0.20756 & 0.41512 & 0.79244 \tabularnewline
174 & 0.238194 & 0.476388 & 0.761806 \tabularnewline
175 & 0.228531 & 0.457063 & 0.771469 \tabularnewline
176 & 0.225668 & 0.451336 & 0.774332 \tabularnewline
177 & 0.241764 & 0.483527 & 0.758236 \tabularnewline
178 & 0.23857 & 0.477139 & 0.76143 \tabularnewline
179 & 0.227052 & 0.454103 & 0.772948 \tabularnewline
180 & 0.251011 & 0.502022 & 0.748989 \tabularnewline
181 & 0.25183 & 0.503661 & 0.74817 \tabularnewline
182 & 0.252848 & 0.505695 & 0.747152 \tabularnewline
183 & 0.253095 & 0.50619 & 0.746905 \tabularnewline
184 & 0.2588 & 0.517601 & 0.7412 \tabularnewline
185 & 0.267688 & 0.535375 & 0.732312 \tabularnewline
186 & 0.25755 & 0.515099 & 0.74245 \tabularnewline
187 & 0.243117 & 0.486233 & 0.756883 \tabularnewline
188 & 0.255322 & 0.510644 & 0.744678 \tabularnewline
189 & 0.256859 & 0.513717 & 0.743141 \tabularnewline
190 & 0.265606 & 0.531211 & 0.734394 \tabularnewline
191 & 0.276355 & 0.55271 & 0.723645 \tabularnewline
192 & 0.278996 & 0.557993 & 0.721004 \tabularnewline
193 & 0.278364 & 0.556729 & 0.721636 \tabularnewline
194 & 0.28103 & 0.562059 & 0.71897 \tabularnewline
195 & 0.283462 & 0.566923 & 0.716538 \tabularnewline
196 & 0.266648 & 0.533297 & 0.733352 \tabularnewline
197 & 0.258263 & 0.516526 & 0.741737 \tabularnewline
198 & 0.262664 & 0.525329 & 0.737336 \tabularnewline
199 & 0.264401 & 0.528801 & 0.735599 \tabularnewline
200 & 0.259531 & 0.519063 & 0.740469 \tabularnewline
201 & 0.264059 & 0.528119 & 0.735941 \tabularnewline
202 & 0.267777 & 0.535555 & 0.732223 \tabularnewline
203 & 0.275894 & 0.551788 & 0.724106 \tabularnewline
204 & 0.283992 & 0.567984 & 0.716008 \tabularnewline
205 & 0.274794 & 0.549589 & 0.725206 \tabularnewline
206 & 0.278066 & 0.556133 & 0.721934 \tabularnewline
207 & 0.30529 & 0.61058 & 0.69471 \tabularnewline
208 & 0.311942 & 0.623884 & 0.688058 \tabularnewline
209 & 0.300928 & 0.601855 & 0.699072 \tabularnewline
210 & 0.28725 & 0.5745 & 0.71275 \tabularnewline
211 & 0.301779 & 0.603558 & 0.698221 \tabularnewline
212 & 0.312996 & 0.625993 & 0.687004 \tabularnewline
213 & 0.304844 & 0.609687 & 0.695156 \tabularnewline
214 & 0.31865 & 0.6373 & 0.68135 \tabularnewline
215 & 0.294325 & 0.588651 & 0.705675 \tabularnewline
216 & 0.313679 & 0.627358 & 0.686321 \tabularnewline
217 & 0.298849 & 0.597698 & 0.701151 \tabularnewline
218 & 0.292823 & 0.585647 & 0.707177 \tabularnewline
219 & 0.312748 & 0.625496 & 0.687252 \tabularnewline
220 & 0.306588 & 0.613176 & 0.693412 \tabularnewline
221 & 0.340742 & 0.681484 & 0.659258 \tabularnewline
222 & 0.352756 & 0.705512 & 0.647244 \tabularnewline
223 & 0.338631 & 0.677262 & 0.661369 \tabularnewline
224 & 0.31088 & 0.621759 & 0.68912 \tabularnewline
225 & 0.289807 & 0.579615 & 0.710193 \tabularnewline
226 & 0.301068 & 0.602135 & 0.698932 \tabularnewline
227 & 0.274804 & 0.549607 & 0.725196 \tabularnewline
228 & 0.272684 & 0.545367 & 0.727316 \tabularnewline
229 & 0.280265 & 0.56053 & 0.719735 \tabularnewline
230 & 0.28942 & 0.57884 & 0.71058 \tabularnewline
231 & 0.26785 & 0.535701 & 0.73215 \tabularnewline
232 & 0.240802 & 0.481605 & 0.759198 \tabularnewline
233 & 0.23738 & 0.474759 & 0.76262 \tabularnewline
234 & 0.248709 & 0.497418 & 0.751291 \tabularnewline
235 & 0.236517 & 0.473033 & 0.763483 \tabularnewline
236 & 0.222488 & 0.444976 & 0.777512 \tabularnewline
237 & 0.202674 & 0.405347 & 0.797326 \tabularnewline
238 & 0.201372 & 0.402743 & 0.798628 \tabularnewline
239 & 0.198056 & 0.396112 & 0.801944 \tabularnewline
240 & 0.184133 & 0.368266 & 0.815867 \tabularnewline
241 & 0.176859 & 0.353718 & 0.823141 \tabularnewline
242 & 0.196097 & 0.392195 & 0.803903 \tabularnewline
243 & 0.192161 & 0.384322 & 0.807839 \tabularnewline
244 & 0.189535 & 0.379071 & 0.810465 \tabularnewline
245 & 0.189628 & 0.379255 & 0.810372 \tabularnewline
246 & 0.184121 & 0.368242 & 0.815879 \tabularnewline
247 & 0.181349 & 0.362698 & 0.818651 \tabularnewline
248 & 0.1832 & 0.366401 & 0.8168 \tabularnewline
249 & 0.166383 & 0.332766 & 0.833617 \tabularnewline
250 & 0.15287 & 0.305739 & 0.84713 \tabularnewline
251 & 0.137357 & 0.274715 & 0.862643 \tabularnewline
252 & 0.149957 & 0.299914 & 0.850043 \tabularnewline
253 & 0.160452 & 0.320904 & 0.839548 \tabularnewline
254 & 0.192943 & 0.385885 & 0.807057 \tabularnewline
255 & 0.193035 & 0.386069 & 0.806965 \tabularnewline
256 & 0.188191 & 0.376383 & 0.811809 \tabularnewline
257 & 0.15878 & 0.31756 & 0.84122 \tabularnewline
258 & 0.147904 & 0.295808 & 0.852096 \tabularnewline
259 & 0.129111 & 0.258222 & 0.870889 \tabularnewline
260 & 0.156568 & 0.313137 & 0.843432 \tabularnewline
261 & 0.179124 & 0.358248 & 0.820876 \tabularnewline
262 & 0.150037 & 0.300075 & 0.849963 \tabularnewline
263 & 0.198407 & 0.396813 & 0.801593 \tabularnewline
264 & 0.170186 & 0.340372 & 0.829814 \tabularnewline
265 & 0.136795 & 0.27359 & 0.863205 \tabularnewline
266 & 0.192349 & 0.384698 & 0.807651 \tabularnewline
267 & 0.411649 & 0.823299 & 0.588351 \tabularnewline
268 & 0.349762 & 0.699523 & 0.650238 \tabularnewline
269 & 0.379299 & 0.758598 & 0.620701 \tabularnewline
270 & 0.420284 & 0.840568 & 0.579716 \tabularnewline
271 & 0.390055 & 0.780109 & 0.609945 \tabularnewline
272 & 0.755706 & 0.488588 & 0.244294 \tabularnewline
273 & 0.693861 & 0.612278 & 0.306139 \tabularnewline
274 & 0.703861 & 0.592278 & 0.296139 \tabularnewline
275 & 0.610596 & 0.778809 & 0.389404 \tabularnewline
276 & 0.53729 & 0.925421 & 0.46271 \tabularnewline
277 & 0.438644 & 0.877289 & 0.561356 \tabularnewline
278 & 0.314606 & 0.629213 & 0.685394 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231833&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]10[/C][C]0.0822357[/C][C]0.164471[/C][C]0.917764[/C][/ROW]
[ROW][C]11[/C][C]0.487578[/C][C]0.975155[/C][C]0.512422[/C][/ROW]
[ROW][C]12[/C][C]0.342372[/C][C]0.684745[/C][C]0.657628[/C][/ROW]
[ROW][C]13[/C][C]0.402822[/C][C]0.805644[/C][C]0.597178[/C][/ROW]
[ROW][C]14[/C][C]0.29017[/C][C]0.58034[/C][C]0.70983[/C][/ROW]
[ROW][C]15[/C][C]0.280389[/C][C]0.560778[/C][C]0.719611[/C][/ROW]
[ROW][C]16[/C][C]0.363271[/C][C]0.726543[/C][C]0.636729[/C][/ROW]
[ROW][C]17[/C][C]0.343999[/C][C]0.687999[/C][C]0.656001[/C][/ROW]
[ROW][C]18[/C][C]0.2707[/C][C]0.541401[/C][C]0.7293[/C][/ROW]
[ROW][C]19[/C][C]0.377689[/C][C]0.755379[/C][C]0.622311[/C][/ROW]
[ROW][C]20[/C][C]0.32463[/C][C]0.64926[/C][C]0.67537[/C][/ROW]
[ROW][C]21[/C][C]0.450945[/C][C]0.90189[/C][C]0.549055[/C][/ROW]
[ROW][C]22[/C][C]0.497334[/C][C]0.994667[/C][C]0.502666[/C][/ROW]
[ROW][C]23[/C][C]0.433676[/C][C]0.867352[/C][C]0.566324[/C][/ROW]
[ROW][C]24[/C][C]0.406364[/C][C]0.812728[/C][C]0.593636[/C][/ROW]
[ROW][C]25[/C][C]0.488138[/C][C]0.976275[/C][C]0.511862[/C][/ROW]
[ROW][C]26[/C][C]0.463508[/C][C]0.927016[/C][C]0.536492[/C][/ROW]
[ROW][C]27[/C][C]0.476857[/C][C]0.953714[/C][C]0.523143[/C][/ROW]
[ROW][C]28[/C][C]0.413321[/C][C]0.826643[/C][C]0.586679[/C][/ROW]
[ROW][C]29[/C][C]0.382103[/C][C]0.764206[/C][C]0.617897[/C][/ROW]
[ROW][C]30[/C][C]0.370785[/C][C]0.741569[/C][C]0.629215[/C][/ROW]
[ROW][C]31[/C][C]0.341884[/C][C]0.683767[/C][C]0.658116[/C][/ROW]
[ROW][C]32[/C][C]0.297419[/C][C]0.594837[/C][C]0.702581[/C][/ROW]
[ROW][C]33[/C][C]0.294989[/C][C]0.589977[/C][C]0.705011[/C][/ROW]
[ROW][C]34[/C][C]0.258187[/C][C]0.516374[/C][C]0.741813[/C][/ROW]
[ROW][C]35[/C][C]0.303474[/C][C]0.606948[/C][C]0.696526[/C][/ROW]
[ROW][C]36[/C][C]0.268336[/C][C]0.536673[/C][C]0.731664[/C][/ROW]
[ROW][C]37[/C][C]0.227957[/C][C]0.455915[/C][C]0.772043[/C][/ROW]
[ROW][C]38[/C][C]0.282888[/C][C]0.565775[/C][C]0.717112[/C][/ROW]
[ROW][C]39[/C][C]0.295617[/C][C]0.591233[/C][C]0.704383[/C][/ROW]
[ROW][C]40[/C][C]0.283661[/C][C]0.567322[/C][C]0.716339[/C][/ROW]
[ROW][C]41[/C][C]0.27629[/C][C]0.55258[/C][C]0.72371[/C][/ROW]
[ROW][C]42[/C][C]0.249698[/C][C]0.499396[/C][C]0.750302[/C][/ROW]
[ROW][C]43[/C][C]0.373498[/C][C]0.746996[/C][C]0.626502[/C][/ROW]
[ROW][C]44[/C][C]0.35161[/C][C]0.70322[/C][C]0.64839[/C][/ROW]
[ROW][C]45[/C][C]0.412078[/C][C]0.824157[/C][C]0.587922[/C][/ROW]
[ROW][C]46[/C][C]0.388753[/C][C]0.777506[/C][C]0.611247[/C][/ROW]
[ROW][C]47[/C][C]0.344726[/C][C]0.689453[/C][C]0.655274[/C][/ROW]
[ROW][C]48[/C][C]0.33164[/C][C]0.66328[/C][C]0.66836[/C][/ROW]
[ROW][C]49[/C][C]0.297352[/C][C]0.594704[/C][C]0.702648[/C][/ROW]
[ROW][C]50[/C][C]0.316542[/C][C]0.633083[/C][C]0.683458[/C][/ROW]
[ROW][C]51[/C][C]0.277821[/C][C]0.555642[/C][C]0.722179[/C][/ROW]
[ROW][C]52[/C][C]0.263026[/C][C]0.526052[/C][C]0.736974[/C][/ROW]
[ROW][C]53[/C][C]0.272221[/C][C]0.544441[/C][C]0.727779[/C][/ROW]
[ROW][C]54[/C][C]0.244699[/C][C]0.489399[/C][C]0.755301[/C][/ROW]
[ROW][C]55[/C][C]0.217435[/C][C]0.434871[/C][C]0.782565[/C][/ROW]
[ROW][C]56[/C][C]0.261167[/C][C]0.522333[/C][C]0.738833[/C][/ROW]
[ROW][C]57[/C][C]0.237847[/C][C]0.475694[/C][C]0.762153[/C][/ROW]
[ROW][C]58[/C][C]0.22038[/C][C]0.440761[/C][C]0.77962[/C][/ROW]
[ROW][C]59[/C][C]0.234047[/C][C]0.468094[/C][C]0.765953[/C][/ROW]
[ROW][C]60[/C][C]0.253987[/C][C]0.507974[/C][C]0.746013[/C][/ROW]
[ROW][C]61[/C][C]0.2305[/C][C]0.461001[/C][C]0.7695[/C][/ROW]
[ROW][C]62[/C][C]0.246914[/C][C]0.493829[/C][C]0.753086[/C][/ROW]
[ROW][C]63[/C][C]0.231453[/C][C]0.462905[/C][C]0.768547[/C][/ROW]
[ROW][C]64[/C][C]0.216215[/C][C]0.43243[/C][C]0.783785[/C][/ROW]
[ROW][C]65[/C][C]0.210799[/C][C]0.421598[/C][C]0.789201[/C][/ROW]
[ROW][C]66[/C][C]0.233661[/C][C]0.467322[/C][C]0.766339[/C][/ROW]
[ROW][C]67[/C][C]0.221999[/C][C]0.443998[/C][C]0.778001[/C][/ROW]
[ROW][C]68[/C][C]0.204166[/C][C]0.408332[/C][C]0.795834[/C][/ROW]
[ROW][C]69[/C][C]0.178737[/C][C]0.357473[/C][C]0.821263[/C][/ROW]
[ROW][C]70[/C][C]0.231948[/C][C]0.463896[/C][C]0.768052[/C][/ROW]
[ROW][C]71[/C][C]0.232402[/C][C]0.464804[/C][C]0.767598[/C][/ROW]
[ROW][C]72[/C][C]0.206252[/C][C]0.412505[/C][C]0.793748[/C][/ROW]
[ROW][C]73[/C][C]0.180087[/C][C]0.360174[/C][C]0.819913[/C][/ROW]
[ROW][C]74[/C][C]0.275204[/C][C]0.550408[/C][C]0.724796[/C][/ROW]
[ROW][C]75[/C][C]0.266717[/C][C]0.533435[/C][C]0.733283[/C][/ROW]
[ROW][C]76[/C][C]0.323142[/C][C]0.646285[/C][C]0.676858[/C][/ROW]
[ROW][C]77[/C][C]0.291591[/C][C]0.583182[/C][C]0.708409[/C][/ROW]
[ROW][C]78[/C][C]0.299703[/C][C]0.599406[/C][C]0.700297[/C][/ROW]
[ROW][C]79[/C][C]0.321858[/C][C]0.643715[/C][C]0.678142[/C][/ROW]
[ROW][C]80[/C][C]0.313125[/C][C]0.626249[/C][C]0.686875[/C][/ROW]
[ROW][C]81[/C][C]0.358189[/C][C]0.716378[/C][C]0.641811[/C][/ROW]
[ROW][C]82[/C][C]0.333082[/C][C]0.666163[/C][C]0.666918[/C][/ROW]
[ROW][C]83[/C][C]0.365822[/C][C]0.731645[/C][C]0.634178[/C][/ROW]
[ROW][C]84[/C][C]0.352186[/C][C]0.704373[/C][C]0.647814[/C][/ROW]
[ROW][C]85[/C][C]0.359246[/C][C]0.718493[/C][C]0.640754[/C][/ROW]
[ROW][C]86[/C][C]0.388564[/C][C]0.777128[/C][C]0.611436[/C][/ROW]
[ROW][C]87[/C][C]0.372509[/C][C]0.745019[/C][C]0.627491[/C][/ROW]
[ROW][C]88[/C][C]0.362199[/C][C]0.724397[/C][C]0.637801[/C][/ROW]
[ROW][C]89[/C][C]0.385005[/C][C]0.770011[/C][C]0.614995[/C][/ROW]
[ROW][C]90[/C][C]0.368048[/C][C]0.736096[/C][C]0.631952[/C][/ROW]
[ROW][C]91[/C][C]0.348645[/C][C]0.697291[/C][C]0.651355[/C][/ROW]
[ROW][C]92[/C][C]0.319119[/C][C]0.638239[/C][C]0.680881[/C][/ROW]
[ROW][C]93[/C][C]0.318121[/C][C]0.636242[/C][C]0.681879[/C][/ROW]
[ROW][C]94[/C][C]0.311331[/C][C]0.622661[/C][C]0.688669[/C][/ROW]
[ROW][C]95[/C][C]0.299592[/C][C]0.599183[/C][C]0.700408[/C][/ROW]
[ROW][C]96[/C][C]0.287392[/C][C]0.574783[/C][C]0.712608[/C][/ROW]
[ROW][C]97[/C][C]0.296272[/C][C]0.592544[/C][C]0.703728[/C][/ROW]
[ROW][C]98[/C][C]0.336611[/C][C]0.673221[/C][C]0.663389[/C][/ROW]
[ROW][C]99[/C][C]0.364224[/C][C]0.728449[/C][C]0.635776[/C][/ROW]
[ROW][C]100[/C][C]0.335207[/C][C]0.670415[/C][C]0.664793[/C][/ROW]
[ROW][C]101[/C][C]0.344656[/C][C]0.689313[/C][C]0.655344[/C][/ROW]
[ROW][C]102[/C][C]0.314608[/C][C]0.629217[/C][C]0.685392[/C][/ROW]
[ROW][C]103[/C][C]0.307345[/C][C]0.614689[/C][C]0.692655[/C][/ROW]
[ROW][C]104[/C][C]0.284299[/C][C]0.568597[/C][C]0.715701[/C][/ROW]
[ROW][C]105[/C][C]0.271948[/C][C]0.543895[/C][C]0.728052[/C][/ROW]
[ROW][C]106[/C][C]0.253165[/C][C]0.506331[/C][C]0.746835[/C][/ROW]
[ROW][C]107[/C][C]0.288275[/C][C]0.57655[/C][C]0.711725[/C][/ROW]
[ROW][C]108[/C][C]0.288945[/C][C]0.57789[/C][C]0.711055[/C][/ROW]
[ROW][C]109[/C][C]0.31488[/C][C]0.62976[/C][C]0.68512[/C][/ROW]
[ROW][C]110[/C][C]0.293689[/C][C]0.587378[/C][C]0.706311[/C][/ROW]
[ROW][C]111[/C][C]0.280584[/C][C]0.561168[/C][C]0.719416[/C][/ROW]
[ROW][C]112[/C][C]0.258468[/C][C]0.516936[/C][C]0.741532[/C][/ROW]
[ROW][C]113[/C][C]0.246314[/C][C]0.492628[/C][C]0.753686[/C][/ROW]
[ROW][C]114[/C][C]0.277482[/C][C]0.554965[/C][C]0.722518[/C][/ROW]
[ROW][C]115[/C][C]0.254353[/C][C]0.508705[/C][C]0.745647[/C][/ROW]
[ROW][C]116[/C][C]0.241318[/C][C]0.482636[/C][C]0.758682[/C][/ROW]
[ROW][C]117[/C][C]0.229904[/C][C]0.459809[/C][C]0.770096[/C][/ROW]
[ROW][C]118[/C][C]0.217242[/C][C]0.434485[/C][C]0.782758[/C][/ROW]
[ROW][C]119[/C][C]0.234103[/C][C]0.468206[/C][C]0.765897[/C][/ROW]
[ROW][C]120[/C][C]0.229569[/C][C]0.459137[/C][C]0.770431[/C][/ROW]
[ROW][C]121[/C][C]0.212468[/C][C]0.424935[/C][C]0.787532[/C][/ROW]
[ROW][C]122[/C][C]0.193456[/C][C]0.386911[/C][C]0.806544[/C][/ROW]
[ROW][C]123[/C][C]0.184598[/C][C]0.369196[/C][C]0.815402[/C][/ROW]
[ROW][C]124[/C][C]0.171688[/C][C]0.343376[/C][C]0.828312[/C][/ROW]
[ROW][C]125[/C][C]0.183044[/C][C]0.366087[/C][C]0.816956[/C][/ROW]
[ROW][C]126[/C][C]0.168424[/C][C]0.336847[/C][C]0.831576[/C][/ROW]
[ROW][C]127[/C][C]0.152922[/C][C]0.305845[/C][C]0.847078[/C][/ROW]
[ROW][C]128[/C][C]0.147979[/C][C]0.295958[/C][C]0.852021[/C][/ROW]
[ROW][C]129[/C][C]0.153609[/C][C]0.307219[/C][C]0.846391[/C][/ROW]
[ROW][C]130[/C][C]0.148969[/C][C]0.297939[/C][C]0.851031[/C][/ROW]
[ROW][C]131[/C][C]0.14575[/C][C]0.291499[/C][C]0.85425[/C][/ROW]
[ROW][C]132[/C][C]0.155513[/C][C]0.311026[/C][C]0.844487[/C][/ROW]
[ROW][C]133[/C][C]0.183646[/C][C]0.367291[/C][C]0.816354[/C][/ROW]
[ROW][C]134[/C][C]0.17496[/C][C]0.34992[/C][C]0.82504[/C][/ROW]
[ROW][C]135[/C][C]0.1658[/C][C]0.3316[/C][C]0.8342[/C][/ROW]
[ROW][C]136[/C][C]0.184267[/C][C]0.368534[/C][C]0.815733[/C][/ROW]
[ROW][C]137[/C][C]0.18471[/C][C]0.369419[/C][C]0.81529[/C][/ROW]
[ROW][C]138[/C][C]0.183038[/C][C]0.366075[/C][C]0.816962[/C][/ROW]
[ROW][C]139[/C][C]0.191218[/C][C]0.382437[/C][C]0.808782[/C][/ROW]
[ROW][C]140[/C][C]0.183477[/C][C]0.366954[/C][C]0.816523[/C][/ROW]
[ROW][C]141[/C][C]0.215988[/C][C]0.431976[/C][C]0.784012[/C][/ROW]
[ROW][C]142[/C][C]0.195705[/C][C]0.39141[/C][C]0.804295[/C][/ROW]
[ROW][C]143[/C][C]0.206242[/C][C]0.412484[/C][C]0.793758[/C][/ROW]
[ROW][C]144[/C][C]0.208779[/C][C]0.417557[/C][C]0.791221[/C][/ROW]
[ROW][C]145[/C][C]0.195226[/C][C]0.390453[/C][C]0.804774[/C][/ROW]
[ROW][C]146[/C][C]0.209312[/C][C]0.418625[/C][C]0.790688[/C][/ROW]
[ROW][C]147[/C][C]0.231545[/C][C]0.463091[/C][C]0.768455[/C][/ROW]
[ROW][C]148[/C][C]0.241727[/C][C]0.483455[/C][C]0.758273[/C][/ROW]
[ROW][C]149[/C][C]0.226579[/C][C]0.453157[/C][C]0.773421[/C][/ROW]
[ROW][C]150[/C][C]0.207689[/C][C]0.415377[/C][C]0.792311[/C][/ROW]
[ROW][C]151[/C][C]0.266033[/C][C]0.532066[/C][C]0.733967[/C][/ROW]
[ROW][C]152[/C][C]0.259673[/C][C]0.519346[/C][C]0.740327[/C][/ROW]
[ROW][C]153[/C][C]0.265523[/C][C]0.531046[/C][C]0.734477[/C][/ROW]
[ROW][C]154[/C][C]0.263461[/C][C]0.526922[/C][C]0.736539[/C][/ROW]
[ROW][C]155[/C][C]0.249692[/C][C]0.499384[/C][C]0.750308[/C][/ROW]
[ROW][C]156[/C][C]0.226381[/C][C]0.452762[/C][C]0.773619[/C][/ROW]
[ROW][C]157[/C][C]0.21353[/C][C]0.427061[/C][C]0.78647[/C][/ROW]
[ROW][C]158[/C][C]0.198706[/C][C]0.397412[/C][C]0.801294[/C][/ROW]
[ROW][C]159[/C][C]0.184435[/C][C]0.368869[/C][C]0.815565[/C][/ROW]
[ROW][C]160[/C][C]0.17357[/C][C]0.34714[/C][C]0.82643[/C][/ROW]
[ROW][C]161[/C][C]0.174664[/C][C]0.349328[/C][C]0.825336[/C][/ROW]
[ROW][C]162[/C][C]0.196968[/C][C]0.393935[/C][C]0.803032[/C][/ROW]
[ROW][C]163[/C][C]0.1818[/C][C]0.3636[/C][C]0.8182[/C][/ROW]
[ROW][C]164[/C][C]0.177067[/C][C]0.354135[/C][C]0.822933[/C][/ROW]
[ROW][C]165[/C][C]0.204094[/C][C]0.408188[/C][C]0.795906[/C][/ROW]
[ROW][C]166[/C][C]0.221135[/C][C]0.442271[/C][C]0.778865[/C][/ROW]
[ROW][C]167[/C][C]0.214927[/C][C]0.429853[/C][C]0.785073[/C][/ROW]
[ROW][C]168[/C][C]0.198087[/C][C]0.396175[/C][C]0.801913[/C][/ROW]
[ROW][C]169[/C][C]0.192503[/C][C]0.385007[/C][C]0.807497[/C][/ROW]
[ROW][C]170[/C][C]0.177442[/C][C]0.354884[/C][C]0.822558[/C][/ROW]
[ROW][C]171[/C][C]0.205901[/C][C]0.411801[/C][C]0.794099[/C][/ROW]
[ROW][C]172[/C][C]0.206579[/C][C]0.413159[/C][C]0.793421[/C][/ROW]
[ROW][C]173[/C][C]0.20756[/C][C]0.41512[/C][C]0.79244[/C][/ROW]
[ROW][C]174[/C][C]0.238194[/C][C]0.476388[/C][C]0.761806[/C][/ROW]
[ROW][C]175[/C][C]0.228531[/C][C]0.457063[/C][C]0.771469[/C][/ROW]
[ROW][C]176[/C][C]0.225668[/C][C]0.451336[/C][C]0.774332[/C][/ROW]
[ROW][C]177[/C][C]0.241764[/C][C]0.483527[/C][C]0.758236[/C][/ROW]
[ROW][C]178[/C][C]0.23857[/C][C]0.477139[/C][C]0.76143[/C][/ROW]
[ROW][C]179[/C][C]0.227052[/C][C]0.454103[/C][C]0.772948[/C][/ROW]
[ROW][C]180[/C][C]0.251011[/C][C]0.502022[/C][C]0.748989[/C][/ROW]
[ROW][C]181[/C][C]0.25183[/C][C]0.503661[/C][C]0.74817[/C][/ROW]
[ROW][C]182[/C][C]0.252848[/C][C]0.505695[/C][C]0.747152[/C][/ROW]
[ROW][C]183[/C][C]0.253095[/C][C]0.50619[/C][C]0.746905[/C][/ROW]
[ROW][C]184[/C][C]0.2588[/C][C]0.517601[/C][C]0.7412[/C][/ROW]
[ROW][C]185[/C][C]0.267688[/C][C]0.535375[/C][C]0.732312[/C][/ROW]
[ROW][C]186[/C][C]0.25755[/C][C]0.515099[/C][C]0.74245[/C][/ROW]
[ROW][C]187[/C][C]0.243117[/C][C]0.486233[/C][C]0.756883[/C][/ROW]
[ROW][C]188[/C][C]0.255322[/C][C]0.510644[/C][C]0.744678[/C][/ROW]
[ROW][C]189[/C][C]0.256859[/C][C]0.513717[/C][C]0.743141[/C][/ROW]
[ROW][C]190[/C][C]0.265606[/C][C]0.531211[/C][C]0.734394[/C][/ROW]
[ROW][C]191[/C][C]0.276355[/C][C]0.55271[/C][C]0.723645[/C][/ROW]
[ROW][C]192[/C][C]0.278996[/C][C]0.557993[/C][C]0.721004[/C][/ROW]
[ROW][C]193[/C][C]0.278364[/C][C]0.556729[/C][C]0.721636[/C][/ROW]
[ROW][C]194[/C][C]0.28103[/C][C]0.562059[/C][C]0.71897[/C][/ROW]
[ROW][C]195[/C][C]0.283462[/C][C]0.566923[/C][C]0.716538[/C][/ROW]
[ROW][C]196[/C][C]0.266648[/C][C]0.533297[/C][C]0.733352[/C][/ROW]
[ROW][C]197[/C][C]0.258263[/C][C]0.516526[/C][C]0.741737[/C][/ROW]
[ROW][C]198[/C][C]0.262664[/C][C]0.525329[/C][C]0.737336[/C][/ROW]
[ROW][C]199[/C][C]0.264401[/C][C]0.528801[/C][C]0.735599[/C][/ROW]
[ROW][C]200[/C][C]0.259531[/C][C]0.519063[/C][C]0.740469[/C][/ROW]
[ROW][C]201[/C][C]0.264059[/C][C]0.528119[/C][C]0.735941[/C][/ROW]
[ROW][C]202[/C][C]0.267777[/C][C]0.535555[/C][C]0.732223[/C][/ROW]
[ROW][C]203[/C][C]0.275894[/C][C]0.551788[/C][C]0.724106[/C][/ROW]
[ROW][C]204[/C][C]0.283992[/C][C]0.567984[/C][C]0.716008[/C][/ROW]
[ROW][C]205[/C][C]0.274794[/C][C]0.549589[/C][C]0.725206[/C][/ROW]
[ROW][C]206[/C][C]0.278066[/C][C]0.556133[/C][C]0.721934[/C][/ROW]
[ROW][C]207[/C][C]0.30529[/C][C]0.61058[/C][C]0.69471[/C][/ROW]
[ROW][C]208[/C][C]0.311942[/C][C]0.623884[/C][C]0.688058[/C][/ROW]
[ROW][C]209[/C][C]0.300928[/C][C]0.601855[/C][C]0.699072[/C][/ROW]
[ROW][C]210[/C][C]0.28725[/C][C]0.5745[/C][C]0.71275[/C][/ROW]
[ROW][C]211[/C][C]0.301779[/C][C]0.603558[/C][C]0.698221[/C][/ROW]
[ROW][C]212[/C][C]0.312996[/C][C]0.625993[/C][C]0.687004[/C][/ROW]
[ROW][C]213[/C][C]0.304844[/C][C]0.609687[/C][C]0.695156[/C][/ROW]
[ROW][C]214[/C][C]0.31865[/C][C]0.6373[/C][C]0.68135[/C][/ROW]
[ROW][C]215[/C][C]0.294325[/C][C]0.588651[/C][C]0.705675[/C][/ROW]
[ROW][C]216[/C][C]0.313679[/C][C]0.627358[/C][C]0.686321[/C][/ROW]
[ROW][C]217[/C][C]0.298849[/C][C]0.597698[/C][C]0.701151[/C][/ROW]
[ROW][C]218[/C][C]0.292823[/C][C]0.585647[/C][C]0.707177[/C][/ROW]
[ROW][C]219[/C][C]0.312748[/C][C]0.625496[/C][C]0.687252[/C][/ROW]
[ROW][C]220[/C][C]0.306588[/C][C]0.613176[/C][C]0.693412[/C][/ROW]
[ROW][C]221[/C][C]0.340742[/C][C]0.681484[/C][C]0.659258[/C][/ROW]
[ROW][C]222[/C][C]0.352756[/C][C]0.705512[/C][C]0.647244[/C][/ROW]
[ROW][C]223[/C][C]0.338631[/C][C]0.677262[/C][C]0.661369[/C][/ROW]
[ROW][C]224[/C][C]0.31088[/C][C]0.621759[/C][C]0.68912[/C][/ROW]
[ROW][C]225[/C][C]0.289807[/C][C]0.579615[/C][C]0.710193[/C][/ROW]
[ROW][C]226[/C][C]0.301068[/C][C]0.602135[/C][C]0.698932[/C][/ROW]
[ROW][C]227[/C][C]0.274804[/C][C]0.549607[/C][C]0.725196[/C][/ROW]
[ROW][C]228[/C][C]0.272684[/C][C]0.545367[/C][C]0.727316[/C][/ROW]
[ROW][C]229[/C][C]0.280265[/C][C]0.56053[/C][C]0.719735[/C][/ROW]
[ROW][C]230[/C][C]0.28942[/C][C]0.57884[/C][C]0.71058[/C][/ROW]
[ROW][C]231[/C][C]0.26785[/C][C]0.535701[/C][C]0.73215[/C][/ROW]
[ROW][C]232[/C][C]0.240802[/C][C]0.481605[/C][C]0.759198[/C][/ROW]
[ROW][C]233[/C][C]0.23738[/C][C]0.474759[/C][C]0.76262[/C][/ROW]
[ROW][C]234[/C][C]0.248709[/C][C]0.497418[/C][C]0.751291[/C][/ROW]
[ROW][C]235[/C][C]0.236517[/C][C]0.473033[/C][C]0.763483[/C][/ROW]
[ROW][C]236[/C][C]0.222488[/C][C]0.444976[/C][C]0.777512[/C][/ROW]
[ROW][C]237[/C][C]0.202674[/C][C]0.405347[/C][C]0.797326[/C][/ROW]
[ROW][C]238[/C][C]0.201372[/C][C]0.402743[/C][C]0.798628[/C][/ROW]
[ROW][C]239[/C][C]0.198056[/C][C]0.396112[/C][C]0.801944[/C][/ROW]
[ROW][C]240[/C][C]0.184133[/C][C]0.368266[/C][C]0.815867[/C][/ROW]
[ROW][C]241[/C][C]0.176859[/C][C]0.353718[/C][C]0.823141[/C][/ROW]
[ROW][C]242[/C][C]0.196097[/C][C]0.392195[/C][C]0.803903[/C][/ROW]
[ROW][C]243[/C][C]0.192161[/C][C]0.384322[/C][C]0.807839[/C][/ROW]
[ROW][C]244[/C][C]0.189535[/C][C]0.379071[/C][C]0.810465[/C][/ROW]
[ROW][C]245[/C][C]0.189628[/C][C]0.379255[/C][C]0.810372[/C][/ROW]
[ROW][C]246[/C][C]0.184121[/C][C]0.368242[/C][C]0.815879[/C][/ROW]
[ROW][C]247[/C][C]0.181349[/C][C]0.362698[/C][C]0.818651[/C][/ROW]
[ROW][C]248[/C][C]0.1832[/C][C]0.366401[/C][C]0.8168[/C][/ROW]
[ROW][C]249[/C][C]0.166383[/C][C]0.332766[/C][C]0.833617[/C][/ROW]
[ROW][C]250[/C][C]0.15287[/C][C]0.305739[/C][C]0.84713[/C][/ROW]
[ROW][C]251[/C][C]0.137357[/C][C]0.274715[/C][C]0.862643[/C][/ROW]
[ROW][C]252[/C][C]0.149957[/C][C]0.299914[/C][C]0.850043[/C][/ROW]
[ROW][C]253[/C][C]0.160452[/C][C]0.320904[/C][C]0.839548[/C][/ROW]
[ROW][C]254[/C][C]0.192943[/C][C]0.385885[/C][C]0.807057[/C][/ROW]
[ROW][C]255[/C][C]0.193035[/C][C]0.386069[/C][C]0.806965[/C][/ROW]
[ROW][C]256[/C][C]0.188191[/C][C]0.376383[/C][C]0.811809[/C][/ROW]
[ROW][C]257[/C][C]0.15878[/C][C]0.31756[/C][C]0.84122[/C][/ROW]
[ROW][C]258[/C][C]0.147904[/C][C]0.295808[/C][C]0.852096[/C][/ROW]
[ROW][C]259[/C][C]0.129111[/C][C]0.258222[/C][C]0.870889[/C][/ROW]
[ROW][C]260[/C][C]0.156568[/C][C]0.313137[/C][C]0.843432[/C][/ROW]
[ROW][C]261[/C][C]0.179124[/C][C]0.358248[/C][C]0.820876[/C][/ROW]
[ROW][C]262[/C][C]0.150037[/C][C]0.300075[/C][C]0.849963[/C][/ROW]
[ROW][C]263[/C][C]0.198407[/C][C]0.396813[/C][C]0.801593[/C][/ROW]
[ROW][C]264[/C][C]0.170186[/C][C]0.340372[/C][C]0.829814[/C][/ROW]
[ROW][C]265[/C][C]0.136795[/C][C]0.27359[/C][C]0.863205[/C][/ROW]
[ROW][C]266[/C][C]0.192349[/C][C]0.384698[/C][C]0.807651[/C][/ROW]
[ROW][C]267[/C][C]0.411649[/C][C]0.823299[/C][C]0.588351[/C][/ROW]
[ROW][C]268[/C][C]0.349762[/C][C]0.699523[/C][C]0.650238[/C][/ROW]
[ROW][C]269[/C][C]0.379299[/C][C]0.758598[/C][C]0.620701[/C][/ROW]
[ROW][C]270[/C][C]0.420284[/C][C]0.840568[/C][C]0.579716[/C][/ROW]
[ROW][C]271[/C][C]0.390055[/C][C]0.780109[/C][C]0.609945[/C][/ROW]
[ROW][C]272[/C][C]0.755706[/C][C]0.488588[/C][C]0.244294[/C][/ROW]
[ROW][C]273[/C][C]0.693861[/C][C]0.612278[/C][C]0.306139[/C][/ROW]
[ROW][C]274[/C][C]0.703861[/C][C]0.592278[/C][C]0.296139[/C][/ROW]
[ROW][C]275[/C][C]0.610596[/C][C]0.778809[/C][C]0.389404[/C][/ROW]
[ROW][C]276[/C][C]0.53729[/C][C]0.925421[/C][C]0.46271[/C][/ROW]
[ROW][C]277[/C][C]0.438644[/C][C]0.877289[/C][C]0.561356[/C][/ROW]
[ROW][C]278[/C][C]0.314606[/C][C]0.629213[/C][C]0.685394[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231833&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231833&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
100.08223570.1644710.917764
110.4875780.9751550.512422
120.3423720.6847450.657628
130.4028220.8056440.597178
140.290170.580340.70983
150.2803890.5607780.719611
160.3632710.7265430.636729
170.3439990.6879990.656001
180.27070.5414010.7293
190.3776890.7553790.622311
200.324630.649260.67537
210.4509450.901890.549055
220.4973340.9946670.502666
230.4336760.8673520.566324
240.4063640.8127280.593636
250.4881380.9762750.511862
260.4635080.9270160.536492
270.4768570.9537140.523143
280.4133210.8266430.586679
290.3821030.7642060.617897
300.3707850.7415690.629215
310.3418840.6837670.658116
320.2974190.5948370.702581
330.2949890.5899770.705011
340.2581870.5163740.741813
350.3034740.6069480.696526
360.2683360.5366730.731664
370.2279570.4559150.772043
380.2828880.5657750.717112
390.2956170.5912330.704383
400.2836610.5673220.716339
410.276290.552580.72371
420.2496980.4993960.750302
430.3734980.7469960.626502
440.351610.703220.64839
450.4120780.8241570.587922
460.3887530.7775060.611247
470.3447260.6894530.655274
480.331640.663280.66836
490.2973520.5947040.702648
500.3165420.6330830.683458
510.2778210.5556420.722179
520.2630260.5260520.736974
530.2722210.5444410.727779
540.2446990.4893990.755301
550.2174350.4348710.782565
560.2611670.5223330.738833
570.2378470.4756940.762153
580.220380.4407610.77962
590.2340470.4680940.765953
600.2539870.5079740.746013
610.23050.4610010.7695
620.2469140.4938290.753086
630.2314530.4629050.768547
640.2162150.432430.783785
650.2107990.4215980.789201
660.2336610.4673220.766339
670.2219990.4439980.778001
680.2041660.4083320.795834
690.1787370.3574730.821263
700.2319480.4638960.768052
710.2324020.4648040.767598
720.2062520.4125050.793748
730.1800870.3601740.819913
740.2752040.5504080.724796
750.2667170.5334350.733283
760.3231420.6462850.676858
770.2915910.5831820.708409
780.2997030.5994060.700297
790.3218580.6437150.678142
800.3131250.6262490.686875
810.3581890.7163780.641811
820.3330820.6661630.666918
830.3658220.7316450.634178
840.3521860.7043730.647814
850.3592460.7184930.640754
860.3885640.7771280.611436
870.3725090.7450190.627491
880.3621990.7243970.637801
890.3850050.7700110.614995
900.3680480.7360960.631952
910.3486450.6972910.651355
920.3191190.6382390.680881
930.3181210.6362420.681879
940.3113310.6226610.688669
950.2995920.5991830.700408
960.2873920.5747830.712608
970.2962720.5925440.703728
980.3366110.6732210.663389
990.3642240.7284490.635776
1000.3352070.6704150.664793
1010.3446560.6893130.655344
1020.3146080.6292170.685392
1030.3073450.6146890.692655
1040.2842990.5685970.715701
1050.2719480.5438950.728052
1060.2531650.5063310.746835
1070.2882750.576550.711725
1080.2889450.577890.711055
1090.314880.629760.68512
1100.2936890.5873780.706311
1110.2805840.5611680.719416
1120.2584680.5169360.741532
1130.2463140.4926280.753686
1140.2774820.5549650.722518
1150.2543530.5087050.745647
1160.2413180.4826360.758682
1170.2299040.4598090.770096
1180.2172420.4344850.782758
1190.2341030.4682060.765897
1200.2295690.4591370.770431
1210.2124680.4249350.787532
1220.1934560.3869110.806544
1230.1845980.3691960.815402
1240.1716880.3433760.828312
1250.1830440.3660870.816956
1260.1684240.3368470.831576
1270.1529220.3058450.847078
1280.1479790.2959580.852021
1290.1536090.3072190.846391
1300.1489690.2979390.851031
1310.145750.2914990.85425
1320.1555130.3110260.844487
1330.1836460.3672910.816354
1340.174960.349920.82504
1350.16580.33160.8342
1360.1842670.3685340.815733
1370.184710.3694190.81529
1380.1830380.3660750.816962
1390.1912180.3824370.808782
1400.1834770.3669540.816523
1410.2159880.4319760.784012
1420.1957050.391410.804295
1430.2062420.4124840.793758
1440.2087790.4175570.791221
1450.1952260.3904530.804774
1460.2093120.4186250.790688
1470.2315450.4630910.768455
1480.2417270.4834550.758273
1490.2265790.4531570.773421
1500.2076890.4153770.792311
1510.2660330.5320660.733967
1520.2596730.5193460.740327
1530.2655230.5310460.734477
1540.2634610.5269220.736539
1550.2496920.4993840.750308
1560.2263810.4527620.773619
1570.213530.4270610.78647
1580.1987060.3974120.801294
1590.1844350.3688690.815565
1600.173570.347140.82643
1610.1746640.3493280.825336
1620.1969680.3939350.803032
1630.18180.36360.8182
1640.1770670.3541350.822933
1650.2040940.4081880.795906
1660.2211350.4422710.778865
1670.2149270.4298530.785073
1680.1980870.3961750.801913
1690.1925030.3850070.807497
1700.1774420.3548840.822558
1710.2059010.4118010.794099
1720.2065790.4131590.793421
1730.207560.415120.79244
1740.2381940.4763880.761806
1750.2285310.4570630.771469
1760.2256680.4513360.774332
1770.2417640.4835270.758236
1780.238570.4771390.76143
1790.2270520.4541030.772948
1800.2510110.5020220.748989
1810.251830.5036610.74817
1820.2528480.5056950.747152
1830.2530950.506190.746905
1840.25880.5176010.7412
1850.2676880.5353750.732312
1860.257550.5150990.74245
1870.2431170.4862330.756883
1880.2553220.5106440.744678
1890.2568590.5137170.743141
1900.2656060.5312110.734394
1910.2763550.552710.723645
1920.2789960.5579930.721004
1930.2783640.5567290.721636
1940.281030.5620590.71897
1950.2834620.5669230.716538
1960.2666480.5332970.733352
1970.2582630.5165260.741737
1980.2626640.5253290.737336
1990.2644010.5288010.735599
2000.2595310.5190630.740469
2010.2640590.5281190.735941
2020.2677770.5355550.732223
2030.2758940.5517880.724106
2040.2839920.5679840.716008
2050.2747940.5495890.725206
2060.2780660.5561330.721934
2070.305290.610580.69471
2080.3119420.6238840.688058
2090.3009280.6018550.699072
2100.287250.57450.71275
2110.3017790.6035580.698221
2120.3129960.6259930.687004
2130.3048440.6096870.695156
2140.318650.63730.68135
2150.2943250.5886510.705675
2160.3136790.6273580.686321
2170.2988490.5976980.701151
2180.2928230.5856470.707177
2190.3127480.6254960.687252
2200.3065880.6131760.693412
2210.3407420.6814840.659258
2220.3527560.7055120.647244
2230.3386310.6772620.661369
2240.310880.6217590.68912
2250.2898070.5796150.710193
2260.3010680.6021350.698932
2270.2748040.5496070.725196
2280.2726840.5453670.727316
2290.2802650.560530.719735
2300.289420.578840.71058
2310.267850.5357010.73215
2320.2408020.4816050.759198
2330.237380.4747590.76262
2340.2487090.4974180.751291
2350.2365170.4730330.763483
2360.2224880.4449760.777512
2370.2026740.4053470.797326
2380.2013720.4027430.798628
2390.1980560.3961120.801944
2400.1841330.3682660.815867
2410.1768590.3537180.823141
2420.1960970.3921950.803903
2430.1921610.3843220.807839
2440.1895350.3790710.810465
2450.1896280.3792550.810372
2460.1841210.3682420.815879
2470.1813490.3626980.818651
2480.18320.3664010.8168
2490.1663830.3327660.833617
2500.152870.3057390.84713
2510.1373570.2747150.862643
2520.1499570.2999140.850043
2530.1604520.3209040.839548
2540.1929430.3858850.807057
2550.1930350.3860690.806965
2560.1881910.3763830.811809
2570.158780.317560.84122
2580.1479040.2958080.852096
2590.1291110.2582220.870889
2600.1565680.3131370.843432
2610.1791240.3582480.820876
2620.1500370.3000750.849963
2630.1984070.3968130.801593
2640.1701860.3403720.829814
2650.1367950.273590.863205
2660.1923490.3846980.807651
2670.4116490.8232990.588351
2680.3497620.6995230.650238
2690.3792990.7585980.620701
2700.4202840.8405680.579716
2710.3900550.7801090.609945
2720.7557060.4885880.244294
2730.6938610.6122780.306139
2740.7038610.5922780.296139
2750.6105960.7788090.389404
2760.537290.9254210.46271
2770.4386440.8772890.561356
2780.3146060.6292130.685394







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level00OK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 0 & 0 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231833&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231833&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231833&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 level00OK
5% type I error level00OK
10% type I error level00OK



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