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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 06 Dec 2013 16:07:22 -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/06/t1386364149t5zj059t0sl9an3.htm/, Retrieved Thu, 28 Mar 2024 13:05:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231355, Retrieved Thu, 28 Mar 2024 13:05:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [w10] [2013-12-06 21:07:22] [4c6743e926d608f4adf2160fecf92c6f] [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 time25 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 25 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231355&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]25 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231355&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231355&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 time25 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 1.94933 + 0.653493Pop[t] + 0.0305177Gender[t] + 0.0700025Connected[t] + 0.0563925Separate[t] + 0.623309Software[t] + 0.076475Happiness[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  1.94933 +  0.653493Pop[t] +  0.0305177Gender[t] +  0.0700025Connected[t] +  0.0563925Separate[t] +  0.623309Software[t] +  0.076475Happiness[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231355&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  1.94933 +  0.653493Pop[t] +  0.0305177Gender[t] +  0.0700025Connected[t] +  0.0563925Separate[t] +  0.623309Software[t] +  0.076475Happiness[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231355&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231355&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
Learning[t] = + 1.94933 + 0.653493Pop[t] + 0.0305177Gender[t] + 0.0700025Connected[t] + 0.0563925Separate[t] + 0.623309Software[t] + 0.076475Happiness[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.949331.246271.5640.1189110.0594553
Pop0.6534930.2484842.630.00901130.00450565
Gender0.03051770.2345460.13010.8965690.448285
Connected0.07000250.03287952.1290.03411880.0170594
Separate0.05639250.0342851.6450.1011260.0505631
Software0.6233090.051672212.062.79257e-271.39628e-27
Happiness0.0764750.04761511.6060.1093730.0546867

\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) & 1.94933 & 1.24627 & 1.564 & 0.118911 & 0.0594553 \tabularnewline
Pop & 0.653493 & 0.248484 & 2.63 & 0.0090113 & 0.00450565 \tabularnewline
Gender & 0.0305177 & 0.234546 & 0.1301 & 0.896569 & 0.448285 \tabularnewline
Connected & 0.0700025 & 0.0328795 & 2.129 & 0.0341188 & 0.0170594 \tabularnewline
Separate & 0.0563925 & 0.034285 & 1.645 & 0.101126 & 0.0505631 \tabularnewline
Software & 0.623309 & 0.0516722 & 12.06 & 2.79257e-27 & 1.39628e-27 \tabularnewline
Happiness & 0.076475 & 0.0476151 & 1.606 & 0.109373 & 0.0546867 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231355&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]1.94933[/C][C]1.24627[/C][C]1.564[/C][C]0.118911[/C][C]0.0594553[/C][/ROW]
[ROW][C]Pop[/C][C]0.653493[/C][C]0.248484[/C][C]2.63[/C][C]0.0090113[/C][C]0.00450565[/C][/ROW]
[ROW][C]Gender[/C][C]0.0305177[/C][C]0.234546[/C][C]0.1301[/C][C]0.896569[/C][C]0.448285[/C][/ROW]
[ROW][C]Connected[/C][C]0.0700025[/C][C]0.0328795[/C][C]2.129[/C][C]0.0341188[/C][C]0.0170594[/C][/ROW]
[ROW][C]Separate[/C][C]0.0563925[/C][C]0.034285[/C][C]1.645[/C][C]0.101126[/C][C]0.0505631[/C][/ROW]
[ROW][C]Software[/C][C]0.623309[/C][C]0.0516722[/C][C]12.06[/C][C]2.79257e-27[/C][C]1.39628e-27[/C][/ROW]
[ROW][C]Happiness[/C][C]0.076475[/C][C]0.0476151[/C][C]1.606[/C][C]0.109373[/C][C]0.0546867[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231355&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231355&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)1.949331.246271.5640.1189110.0594553
Pop0.6534930.2484842.630.00901130.00450565
Gender0.03051770.2345460.13010.8965690.448285
Connected0.07000250.03287952.1290.03411880.0170594
Separate0.05639250.0342851.6450.1011260.0505631
Software0.6233090.051672212.062.79257e-271.39628e-27
Happiness0.0764750.04761511.6060.1093730.0546867







Multiple Linear Regression - Regression Statistics
Multiple R0.697111
R-squared0.485963
Adjusted R-squared0.474987
F-TEST (value)44.2756
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.89915
Sum Squared Residuals1013.51

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.697111 \tabularnewline
R-squared & 0.485963 \tabularnewline
Adjusted R-squared & 0.474987 \tabularnewline
F-TEST (value) & 44.2756 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.89915 \tabularnewline
Sum Squared Residuals & 1013.51 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231355&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.697111[/C][/ROW]
[ROW][C]R-squared[/C][C]0.485963[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.474987[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]44.2756[/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[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.89915[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1013.51[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231355&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231355&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 R0.697111
R-squared0.485963
Adjusted R-squared0.474987
F-TEST (value)44.2756
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.89915
Sum Squared Residuals1013.51







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.1967-3.19672
21615.4010.599048
31916.8982.10198
41511.29143.70859
51416.4266-2.42657
61314.3285-1.32845
71915.6623.33803
81516.8405-1.84054
91415.754-1.75401
101514.12330.876742
111614.54431.45575
121616.0035-0.00351307
131615.48110.518882
141615.58640.413644
151717.7561-0.756135
161515.2542-0.254218
171514.23120.768783
182016.21613.78386
191815.40292.59711
201615.38130.618707
211614.93681.06319
221614.87251.12748
231916.682.31998
241615.19680.803156
251715.91731.08273
261716.09930.9007
271614.55331.44666
281516.8269-1.82693
291615.43120.568787
301413.91820.0818206
311515.2549-0.254898
321212.2781-0.278101
331414.5048-0.50477
341615.72680.273215
351415.225-1.22505
361012.2906-2.29062
371012.6791-2.67912
381415.6107-1.6107
391613.94472.05525
401614.14111.85887
411614.37771.62231
421415.5777-1.57769
432017.64072.35928
441414.0647-0.064657
451414.2526-0.252645
461115.5181-4.51811
471416.7429-2.74289
481514.86430.135704
491615.45280.547176
501415.5414-1.54137
511616.9663-0.966266
521413.83840.161578
531215.0248-3.02479
541616.1771-0.177062
55910.6817-1.68171
561412.08421.91585
571615.98410.0159044
581615.20760.792405
591514.99710.00285141
601614.15161.84843
611211.25690.743145
621615.65420.34585
631616.5547-0.554718
641414.7042-0.704209
651615.38840.61157
661716.00720.992796
671816.69471.30528
681813.99964.0004
691216.246-4.24598
701615.76630.23373
711013.3502-3.35017
721415.0263-1.02634
731817.08620.913812
741817.44850.551534
751614.97941.02061
761713.58273.4173
771616.7131-0.713052
781614.61221.38783
791314.9379-1.9379
801615.18940.8106
811615.56990.430127
821615.79680.203212
831515.7572-0.75718
841514.79430.205706
851613.99532.00467
861414.2191-0.219135
871615.41110.58887
881614.94191.05814
891514.81940.180587
901213.7434-1.74341
911717.3018-0.301805
921616.0224-0.0223577
931515.0028-0.00277298
941314.8291-1.82908
951614.85031.14974
961616.2179-0.217892
971613.5122.48797
981615.890.109952
991414.2533-0.253252
1001617.35-1.34997
1011614.94081.05924
1022017.81322.18681
1031514.11950.880479
1041615.14630.853741
1051315.3755-2.37547
1061715.97051.02951
1071616.2991-0.29907
1081614.71781.2822
1091213.1398-1.13985
1101615.27760.722402
1111616.2319-0.231926
1121715.03611.96391
1131214.7504-2.75042
1141816.32411.6759
1151416.3728-2.37279
1161413.32630.673749
1171314.8442-1.84421
1181615.87390.126072
1191314.7735-1.77353
1201615.49970.500313
1211316.1196-3.11958
1221617.2398-1.2398
1231516.1517-1.15174
1241617.0082-1.00819
1251514.67060.32935
1261716.06920.930763
1271514.03640.963637
1281214.9479-2.94791
1291613.93112.06888
1301013.9121-3.91213
1311613.65362.34644
1321214.1882-2.18819
1331415.9627-1.96267
1341515.2121-0.212115
1351312.25450.745462
1361514.88370.116301
1371113.7815-2.78147
1381213.1344-1.13437
1391113.3506-2.3506
1401612.92443.07563
1411513.62281.37719
1421717.1274-0.127443
1431614.07351.92654
1441013.3917-3.39168
1451815.72262.27736
1461315.474-2.47398
1471614.98851.01152
1481313.1555-0.15553
1491013.0795-3.07951
1501516.7572-1.75716
1511613.95922.04079
1521611.94034.05971
1531412.88551.11447
1541012.6722-2.67224
1551311.77051.22955
1561514.03640.963637
1571614.66861.33144
1581212.9205-0.920511
1591312.30340.696554
1601211.64270.357262
1611716.42030.579692
1621513.55711.44292
1631011.1489-1.14887
1641413.83740.16259
1651113.6071-2.60714
1661314.6708-1.67083
1671614.09391.90609
1681210.24541.75464
1691615.28980.710228
1701213.7145-1.71454
171910.7771-1.77707
1721214.7822-2.78224
1731514.01370.986275
1741212.1056-0.105643
1751212.2687-0.268665
1761413.35480.645213
1771213.1775-1.17747
1781615.08040.91957
1791110.82520.174775
1801916.64632.3537
1811514.96430.0356528
182813.8022-5.8022
1831614.72391.27606
1841714.31382.68618
1851211.96840.0315955
1861110.84570.154269
1871110.17730.822687
1881414.571-0.570995
1891615.4460.553995
190129.097942.90206
1911614.21411.78591
1921313.4047-0.404707
1931515.0797-0.0797495
1941612.78853.21146
1951614.92681.07319
1961412.34191.65805
1971613.90922.09083
1981412.70141.29862
1991112.9874-1.98744
2001214.6079-2.60786
2011512.34092.65912
2021514.39360.606409
2031614.44351.55649
2041615.13290.86714
2051113.5576-2.55764
2061513.64711.35294
2071214.3889-2.38887
2081216.004-4.00401
2091514.08630.913655
2101511.60523.39481
2111614.72461.27539
2121412.69941.30057
2131714.42012.57985
2141413.9310.0689658
2151312.04140.958567
2161515.3261-0.326082
2171314.5813-1.58131
2181414.0962-0.096249
2191514.3390.661048
2201212.6809-0.680877
221811.2135-3.21352
2221413.61010.389914
2231412.70421.29576
2241112.412-1.41195
2251212.7542-0.754162
2261310.86222.13778
2271013.3237-3.3237
2281610.99375.00626
2291816.43141.56859
2301313.6212-0.621187
2311113.2919-2.29191
232410.8888-6.88876
2331314.4659-1.4659
2341614.00251.99745
2351011.4356-1.43559
2361211.54810.451867
2371213.8414-1.84136
238108.276021.72398
2391310.91792.08207
2401211.78080.21916
2411412.76711.23289
2421012.9849-2.98493
2431210.24541.75464
2441211.10520.894765
2451111.547-0.547044
2461011.4213-1.42131
2471211.15130.848685
2481612.69843.30155
2491213.5512-1.55117
2501413.96450.0355296
2511614.65391.34607
2521411.62922.37076
2531314.4908-1.49081
25448.75639-4.75639
2551513.48871.51126
2561115.0992-4.09917
2571111.6781-0.678052
2581412.46441.5356
2591514.61830.381718
2601411.97212.02789
2611312.79260.207442
2621112.2546-1.25463
2631513.78461.21544
2641111.2831-0.283063
2651311.6541.34598
2661311.58321.41683
2671613.51172.48832
2681312.22360.776445
2691614.9341.06605
2701615.83440.165602
2711211.44020.559841
272710.8123-3.8123
2731613.91462.08545
27459.20467-4.20467
2751613.14632.85371
27648.64173-4.64173
2771213.3401-1.34007
2781514.1310.868969
2791414.8341-0.834112
2801113.0206-2.02056
2811614.98441.01557
2821513.63741.36259
2831212.0787-0.0787396
28468.99808-2.99808
2851614.51821.48178
2861013.3329-3.33293
2871516.0797-1.07973
2881414.4912-0.491237

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.1967 & -3.19672 \tabularnewline
2 & 16 & 15.401 & 0.599048 \tabularnewline
3 & 19 & 16.898 & 2.10198 \tabularnewline
4 & 15 & 11.2914 & 3.70859 \tabularnewline
5 & 14 & 16.4266 & -2.42657 \tabularnewline
6 & 13 & 14.3285 & -1.32845 \tabularnewline
7 & 19 & 15.662 & 3.33803 \tabularnewline
8 & 15 & 16.8405 & -1.84054 \tabularnewline
9 & 14 & 15.754 & -1.75401 \tabularnewline
10 & 15 & 14.1233 & 0.876742 \tabularnewline
11 & 16 & 14.5443 & 1.45575 \tabularnewline
12 & 16 & 16.0035 & -0.00351307 \tabularnewline
13 & 16 & 15.4811 & 0.518882 \tabularnewline
14 & 16 & 15.5864 & 0.413644 \tabularnewline
15 & 17 & 17.7561 & -0.756135 \tabularnewline
16 & 15 & 15.2542 & -0.254218 \tabularnewline
17 & 15 & 14.2312 & 0.768783 \tabularnewline
18 & 20 & 16.2161 & 3.78386 \tabularnewline
19 & 18 & 15.4029 & 2.59711 \tabularnewline
20 & 16 & 15.3813 & 0.618707 \tabularnewline
21 & 16 & 14.9368 & 1.06319 \tabularnewline
22 & 16 & 14.8725 & 1.12748 \tabularnewline
23 & 19 & 16.68 & 2.31998 \tabularnewline
24 & 16 & 15.1968 & 0.803156 \tabularnewline
25 & 17 & 15.9173 & 1.08273 \tabularnewline
26 & 17 & 16.0993 & 0.9007 \tabularnewline
27 & 16 & 14.5533 & 1.44666 \tabularnewline
28 & 15 & 16.8269 & -1.82693 \tabularnewline
29 & 16 & 15.4312 & 0.568787 \tabularnewline
30 & 14 & 13.9182 & 0.0818206 \tabularnewline
31 & 15 & 15.2549 & -0.254898 \tabularnewline
32 & 12 & 12.2781 & -0.278101 \tabularnewline
33 & 14 & 14.5048 & -0.50477 \tabularnewline
34 & 16 & 15.7268 & 0.273215 \tabularnewline
35 & 14 & 15.225 & -1.22505 \tabularnewline
36 & 10 & 12.2906 & -2.29062 \tabularnewline
37 & 10 & 12.6791 & -2.67912 \tabularnewline
38 & 14 & 15.6107 & -1.6107 \tabularnewline
39 & 16 & 13.9447 & 2.05525 \tabularnewline
40 & 16 & 14.1411 & 1.85887 \tabularnewline
41 & 16 & 14.3777 & 1.62231 \tabularnewline
42 & 14 & 15.5777 & -1.57769 \tabularnewline
43 & 20 & 17.6407 & 2.35928 \tabularnewline
44 & 14 & 14.0647 & -0.064657 \tabularnewline
45 & 14 & 14.2526 & -0.252645 \tabularnewline
46 & 11 & 15.5181 & -4.51811 \tabularnewline
47 & 14 & 16.7429 & -2.74289 \tabularnewline
48 & 15 & 14.8643 & 0.135704 \tabularnewline
49 & 16 & 15.4528 & 0.547176 \tabularnewline
50 & 14 & 15.5414 & -1.54137 \tabularnewline
51 & 16 & 16.9663 & -0.966266 \tabularnewline
52 & 14 & 13.8384 & 0.161578 \tabularnewline
53 & 12 & 15.0248 & -3.02479 \tabularnewline
54 & 16 & 16.1771 & -0.177062 \tabularnewline
55 & 9 & 10.6817 & -1.68171 \tabularnewline
56 & 14 & 12.0842 & 1.91585 \tabularnewline
57 & 16 & 15.9841 & 0.0159044 \tabularnewline
58 & 16 & 15.2076 & 0.792405 \tabularnewline
59 & 15 & 14.9971 & 0.00285141 \tabularnewline
60 & 16 & 14.1516 & 1.84843 \tabularnewline
61 & 12 & 11.2569 & 0.743145 \tabularnewline
62 & 16 & 15.6542 & 0.34585 \tabularnewline
63 & 16 & 16.5547 & -0.554718 \tabularnewline
64 & 14 & 14.7042 & -0.704209 \tabularnewline
65 & 16 & 15.3884 & 0.61157 \tabularnewline
66 & 17 & 16.0072 & 0.992796 \tabularnewline
67 & 18 & 16.6947 & 1.30528 \tabularnewline
68 & 18 & 13.9996 & 4.0004 \tabularnewline
69 & 12 & 16.246 & -4.24598 \tabularnewline
70 & 16 & 15.7663 & 0.23373 \tabularnewline
71 & 10 & 13.3502 & -3.35017 \tabularnewline
72 & 14 & 15.0263 & -1.02634 \tabularnewline
73 & 18 & 17.0862 & 0.913812 \tabularnewline
74 & 18 & 17.4485 & 0.551534 \tabularnewline
75 & 16 & 14.9794 & 1.02061 \tabularnewline
76 & 17 & 13.5827 & 3.4173 \tabularnewline
77 & 16 & 16.7131 & -0.713052 \tabularnewline
78 & 16 & 14.6122 & 1.38783 \tabularnewline
79 & 13 & 14.9379 & -1.9379 \tabularnewline
80 & 16 & 15.1894 & 0.8106 \tabularnewline
81 & 16 & 15.5699 & 0.430127 \tabularnewline
82 & 16 & 15.7968 & 0.203212 \tabularnewline
83 & 15 & 15.7572 & -0.75718 \tabularnewline
84 & 15 & 14.7943 & 0.205706 \tabularnewline
85 & 16 & 13.9953 & 2.00467 \tabularnewline
86 & 14 & 14.2191 & -0.219135 \tabularnewline
87 & 16 & 15.4111 & 0.58887 \tabularnewline
88 & 16 & 14.9419 & 1.05814 \tabularnewline
89 & 15 & 14.8194 & 0.180587 \tabularnewline
90 & 12 & 13.7434 & -1.74341 \tabularnewline
91 & 17 & 17.3018 & -0.301805 \tabularnewline
92 & 16 & 16.0224 & -0.0223577 \tabularnewline
93 & 15 & 15.0028 & -0.00277298 \tabularnewline
94 & 13 & 14.8291 & -1.82908 \tabularnewline
95 & 16 & 14.8503 & 1.14974 \tabularnewline
96 & 16 & 16.2179 & -0.217892 \tabularnewline
97 & 16 & 13.512 & 2.48797 \tabularnewline
98 & 16 & 15.89 & 0.109952 \tabularnewline
99 & 14 & 14.2533 & -0.253252 \tabularnewline
100 & 16 & 17.35 & -1.34997 \tabularnewline
101 & 16 & 14.9408 & 1.05924 \tabularnewline
102 & 20 & 17.8132 & 2.18681 \tabularnewline
103 & 15 & 14.1195 & 0.880479 \tabularnewline
104 & 16 & 15.1463 & 0.853741 \tabularnewline
105 & 13 & 15.3755 & -2.37547 \tabularnewline
106 & 17 & 15.9705 & 1.02951 \tabularnewline
107 & 16 & 16.2991 & -0.29907 \tabularnewline
108 & 16 & 14.7178 & 1.2822 \tabularnewline
109 & 12 & 13.1398 & -1.13985 \tabularnewline
110 & 16 & 15.2776 & 0.722402 \tabularnewline
111 & 16 & 16.2319 & -0.231926 \tabularnewline
112 & 17 & 15.0361 & 1.96391 \tabularnewline
113 & 12 & 14.7504 & -2.75042 \tabularnewline
114 & 18 & 16.3241 & 1.6759 \tabularnewline
115 & 14 & 16.3728 & -2.37279 \tabularnewline
116 & 14 & 13.3263 & 0.673749 \tabularnewline
117 & 13 & 14.8442 & -1.84421 \tabularnewline
118 & 16 & 15.8739 & 0.126072 \tabularnewline
119 & 13 & 14.7735 & -1.77353 \tabularnewline
120 & 16 & 15.4997 & 0.500313 \tabularnewline
121 & 13 & 16.1196 & -3.11958 \tabularnewline
122 & 16 & 17.2398 & -1.2398 \tabularnewline
123 & 15 & 16.1517 & -1.15174 \tabularnewline
124 & 16 & 17.0082 & -1.00819 \tabularnewline
125 & 15 & 14.6706 & 0.32935 \tabularnewline
126 & 17 & 16.0692 & 0.930763 \tabularnewline
127 & 15 & 14.0364 & 0.963637 \tabularnewline
128 & 12 & 14.9479 & -2.94791 \tabularnewline
129 & 16 & 13.9311 & 2.06888 \tabularnewline
130 & 10 & 13.9121 & -3.91213 \tabularnewline
131 & 16 & 13.6536 & 2.34644 \tabularnewline
132 & 12 & 14.1882 & -2.18819 \tabularnewline
133 & 14 & 15.9627 & -1.96267 \tabularnewline
134 & 15 & 15.2121 & -0.212115 \tabularnewline
135 & 13 & 12.2545 & 0.745462 \tabularnewline
136 & 15 & 14.8837 & 0.116301 \tabularnewline
137 & 11 & 13.7815 & -2.78147 \tabularnewline
138 & 12 & 13.1344 & -1.13437 \tabularnewline
139 & 11 & 13.3506 & -2.3506 \tabularnewline
140 & 16 & 12.9244 & 3.07563 \tabularnewline
141 & 15 & 13.6228 & 1.37719 \tabularnewline
142 & 17 & 17.1274 & -0.127443 \tabularnewline
143 & 16 & 14.0735 & 1.92654 \tabularnewline
144 & 10 & 13.3917 & -3.39168 \tabularnewline
145 & 18 & 15.7226 & 2.27736 \tabularnewline
146 & 13 & 15.474 & -2.47398 \tabularnewline
147 & 16 & 14.9885 & 1.01152 \tabularnewline
148 & 13 & 13.1555 & -0.15553 \tabularnewline
149 & 10 & 13.0795 & -3.07951 \tabularnewline
150 & 15 & 16.7572 & -1.75716 \tabularnewline
151 & 16 & 13.9592 & 2.04079 \tabularnewline
152 & 16 & 11.9403 & 4.05971 \tabularnewline
153 & 14 & 12.8855 & 1.11447 \tabularnewline
154 & 10 & 12.6722 & -2.67224 \tabularnewline
155 & 13 & 11.7705 & 1.22955 \tabularnewline
156 & 15 & 14.0364 & 0.963637 \tabularnewline
157 & 16 & 14.6686 & 1.33144 \tabularnewline
158 & 12 & 12.9205 & -0.920511 \tabularnewline
159 & 13 & 12.3034 & 0.696554 \tabularnewline
160 & 12 & 11.6427 & 0.357262 \tabularnewline
161 & 17 & 16.4203 & 0.579692 \tabularnewline
162 & 15 & 13.5571 & 1.44292 \tabularnewline
163 & 10 & 11.1489 & -1.14887 \tabularnewline
164 & 14 & 13.8374 & 0.16259 \tabularnewline
165 & 11 & 13.6071 & -2.60714 \tabularnewline
166 & 13 & 14.6708 & -1.67083 \tabularnewline
167 & 16 & 14.0939 & 1.90609 \tabularnewline
168 & 12 & 10.2454 & 1.75464 \tabularnewline
169 & 16 & 15.2898 & 0.710228 \tabularnewline
170 & 12 & 13.7145 & -1.71454 \tabularnewline
171 & 9 & 10.7771 & -1.77707 \tabularnewline
172 & 12 & 14.7822 & -2.78224 \tabularnewline
173 & 15 & 14.0137 & 0.986275 \tabularnewline
174 & 12 & 12.1056 & -0.105643 \tabularnewline
175 & 12 & 12.2687 & -0.268665 \tabularnewline
176 & 14 & 13.3548 & 0.645213 \tabularnewline
177 & 12 & 13.1775 & -1.17747 \tabularnewline
178 & 16 & 15.0804 & 0.91957 \tabularnewline
179 & 11 & 10.8252 & 0.174775 \tabularnewline
180 & 19 & 16.6463 & 2.3537 \tabularnewline
181 & 15 & 14.9643 & 0.0356528 \tabularnewline
182 & 8 & 13.8022 & -5.8022 \tabularnewline
183 & 16 & 14.7239 & 1.27606 \tabularnewline
184 & 17 & 14.3138 & 2.68618 \tabularnewline
185 & 12 & 11.9684 & 0.0315955 \tabularnewline
186 & 11 & 10.8457 & 0.154269 \tabularnewline
187 & 11 & 10.1773 & 0.822687 \tabularnewline
188 & 14 & 14.571 & -0.570995 \tabularnewline
189 & 16 & 15.446 & 0.553995 \tabularnewline
190 & 12 & 9.09794 & 2.90206 \tabularnewline
191 & 16 & 14.2141 & 1.78591 \tabularnewline
192 & 13 & 13.4047 & -0.404707 \tabularnewline
193 & 15 & 15.0797 & -0.0797495 \tabularnewline
194 & 16 & 12.7885 & 3.21146 \tabularnewline
195 & 16 & 14.9268 & 1.07319 \tabularnewline
196 & 14 & 12.3419 & 1.65805 \tabularnewline
197 & 16 & 13.9092 & 2.09083 \tabularnewline
198 & 14 & 12.7014 & 1.29862 \tabularnewline
199 & 11 & 12.9874 & -1.98744 \tabularnewline
200 & 12 & 14.6079 & -2.60786 \tabularnewline
201 & 15 & 12.3409 & 2.65912 \tabularnewline
202 & 15 & 14.3936 & 0.606409 \tabularnewline
203 & 16 & 14.4435 & 1.55649 \tabularnewline
204 & 16 & 15.1329 & 0.86714 \tabularnewline
205 & 11 & 13.5576 & -2.55764 \tabularnewline
206 & 15 & 13.6471 & 1.35294 \tabularnewline
207 & 12 & 14.3889 & -2.38887 \tabularnewline
208 & 12 & 16.004 & -4.00401 \tabularnewline
209 & 15 & 14.0863 & 0.913655 \tabularnewline
210 & 15 & 11.6052 & 3.39481 \tabularnewline
211 & 16 & 14.7246 & 1.27539 \tabularnewline
212 & 14 & 12.6994 & 1.30057 \tabularnewline
213 & 17 & 14.4201 & 2.57985 \tabularnewline
214 & 14 & 13.931 & 0.0689658 \tabularnewline
215 & 13 & 12.0414 & 0.958567 \tabularnewline
216 & 15 & 15.3261 & -0.326082 \tabularnewline
217 & 13 & 14.5813 & -1.58131 \tabularnewline
218 & 14 & 14.0962 & -0.096249 \tabularnewline
219 & 15 & 14.339 & 0.661048 \tabularnewline
220 & 12 & 12.6809 & -0.680877 \tabularnewline
221 & 8 & 11.2135 & -3.21352 \tabularnewline
222 & 14 & 13.6101 & 0.389914 \tabularnewline
223 & 14 & 12.7042 & 1.29576 \tabularnewline
224 & 11 & 12.412 & -1.41195 \tabularnewline
225 & 12 & 12.7542 & -0.754162 \tabularnewline
226 & 13 & 10.8622 & 2.13778 \tabularnewline
227 & 10 & 13.3237 & -3.3237 \tabularnewline
228 & 16 & 10.9937 & 5.00626 \tabularnewline
229 & 18 & 16.4314 & 1.56859 \tabularnewline
230 & 13 & 13.6212 & -0.621187 \tabularnewline
231 & 11 & 13.2919 & -2.29191 \tabularnewline
232 & 4 & 10.8888 & -6.88876 \tabularnewline
233 & 13 & 14.4659 & -1.4659 \tabularnewline
234 & 16 & 14.0025 & 1.99745 \tabularnewline
235 & 10 & 11.4356 & -1.43559 \tabularnewline
236 & 12 & 11.5481 & 0.451867 \tabularnewline
237 & 12 & 13.8414 & -1.84136 \tabularnewline
238 & 10 & 8.27602 & 1.72398 \tabularnewline
239 & 13 & 10.9179 & 2.08207 \tabularnewline
240 & 12 & 11.7808 & 0.21916 \tabularnewline
241 & 14 & 12.7671 & 1.23289 \tabularnewline
242 & 10 & 12.9849 & -2.98493 \tabularnewline
243 & 12 & 10.2454 & 1.75464 \tabularnewline
244 & 12 & 11.1052 & 0.894765 \tabularnewline
245 & 11 & 11.547 & -0.547044 \tabularnewline
246 & 10 & 11.4213 & -1.42131 \tabularnewline
247 & 12 & 11.1513 & 0.848685 \tabularnewline
248 & 16 & 12.6984 & 3.30155 \tabularnewline
249 & 12 & 13.5512 & -1.55117 \tabularnewline
250 & 14 & 13.9645 & 0.0355296 \tabularnewline
251 & 16 & 14.6539 & 1.34607 \tabularnewline
252 & 14 & 11.6292 & 2.37076 \tabularnewline
253 & 13 & 14.4908 & -1.49081 \tabularnewline
254 & 4 & 8.75639 & -4.75639 \tabularnewline
255 & 15 & 13.4887 & 1.51126 \tabularnewline
256 & 11 & 15.0992 & -4.09917 \tabularnewline
257 & 11 & 11.6781 & -0.678052 \tabularnewline
258 & 14 & 12.4644 & 1.5356 \tabularnewline
259 & 15 & 14.6183 & 0.381718 \tabularnewline
260 & 14 & 11.9721 & 2.02789 \tabularnewline
261 & 13 & 12.7926 & 0.207442 \tabularnewline
262 & 11 & 12.2546 & -1.25463 \tabularnewline
263 & 15 & 13.7846 & 1.21544 \tabularnewline
264 & 11 & 11.2831 & -0.283063 \tabularnewline
265 & 13 & 11.654 & 1.34598 \tabularnewline
266 & 13 & 11.5832 & 1.41683 \tabularnewline
267 & 16 & 13.5117 & 2.48832 \tabularnewline
268 & 13 & 12.2236 & 0.776445 \tabularnewline
269 & 16 & 14.934 & 1.06605 \tabularnewline
270 & 16 & 15.8344 & 0.165602 \tabularnewline
271 & 12 & 11.4402 & 0.559841 \tabularnewline
272 & 7 & 10.8123 & -3.8123 \tabularnewline
273 & 16 & 13.9146 & 2.08545 \tabularnewline
274 & 5 & 9.20467 & -4.20467 \tabularnewline
275 & 16 & 13.1463 & 2.85371 \tabularnewline
276 & 4 & 8.64173 & -4.64173 \tabularnewline
277 & 12 & 13.3401 & -1.34007 \tabularnewline
278 & 15 & 14.131 & 0.868969 \tabularnewline
279 & 14 & 14.8341 & -0.834112 \tabularnewline
280 & 11 & 13.0206 & -2.02056 \tabularnewline
281 & 16 & 14.9844 & 1.01557 \tabularnewline
282 & 15 & 13.6374 & 1.36259 \tabularnewline
283 & 12 & 12.0787 & -0.0787396 \tabularnewline
284 & 6 & 8.99808 & -2.99808 \tabularnewline
285 & 16 & 14.5182 & 1.48178 \tabularnewline
286 & 10 & 13.3329 & -3.33293 \tabularnewline
287 & 15 & 16.0797 & -1.07973 \tabularnewline
288 & 14 & 14.4912 & -0.491237 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231355&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]13[/C][C]16.1967[/C][C]-3.19672[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.401[/C][C]0.599048[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]16.898[/C][C]2.10198[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]11.2914[/C][C]3.70859[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.4266[/C][C]-2.42657[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.3285[/C][C]-1.32845[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.662[/C][C]3.33803[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]16.8405[/C][C]-1.84054[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.754[/C][C]-1.75401[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.1233[/C][C]0.876742[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.5443[/C][C]1.45575[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.0035[/C][C]-0.00351307[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.4811[/C][C]0.518882[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.5864[/C][C]0.413644[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.7561[/C][C]-0.756135[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.2542[/C][C]-0.254218[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.2312[/C][C]0.768783[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.2161[/C][C]3.78386[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.4029[/C][C]2.59711[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.3813[/C][C]0.618707[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]14.9368[/C][C]1.06319[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]14.8725[/C][C]1.12748[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.68[/C][C]2.31998[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]15.1968[/C][C]0.803156[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.9173[/C][C]1.08273[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.0993[/C][C]0.9007[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.5533[/C][C]1.44666[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.8269[/C][C]-1.82693[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.4312[/C][C]0.568787[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]13.9182[/C][C]0.0818206[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.2549[/C][C]-0.254898[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.2781[/C][C]-0.278101[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.5048[/C][C]-0.50477[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.7268[/C][C]0.273215[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.225[/C][C]-1.22505[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.2906[/C][C]-2.29062[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]12.6791[/C][C]-2.67912[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.6107[/C][C]-1.6107[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]13.9447[/C][C]2.05525[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.1411[/C][C]1.85887[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.3777[/C][C]1.62231[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.5777[/C][C]-1.57769[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.6407[/C][C]2.35928[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.0647[/C][C]-0.064657[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.2526[/C][C]-0.252645[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.5181[/C][C]-4.51811[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.7429[/C][C]-2.74289[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.8643[/C][C]0.135704[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.4528[/C][C]0.547176[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.5414[/C][C]-1.54137[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.9663[/C][C]-0.966266[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.8384[/C][C]0.161578[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]15.0248[/C][C]-3.02479[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]16.1771[/C][C]-0.177062[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]10.6817[/C][C]-1.68171[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.0842[/C][C]1.91585[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.9841[/C][C]0.0159044[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.2076[/C][C]0.792405[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]14.9971[/C][C]0.00285141[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.1516[/C][C]1.84843[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.2569[/C][C]0.743145[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.6542[/C][C]0.34585[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.5547[/C][C]-0.554718[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.7042[/C][C]-0.704209[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.3884[/C][C]0.61157[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.0072[/C][C]0.992796[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.6947[/C][C]1.30528[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]13.9996[/C][C]4.0004[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]16.246[/C][C]-4.24598[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.7663[/C][C]0.23373[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.3502[/C][C]-3.35017[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]15.0263[/C][C]-1.02634[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]17.0862[/C][C]0.913812[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.4485[/C][C]0.551534[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]14.9794[/C][C]1.02061[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.5827[/C][C]3.4173[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.7131[/C][C]-0.713052[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.6122[/C][C]1.38783[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]14.9379[/C][C]-1.9379[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.1894[/C][C]0.8106[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.5699[/C][C]0.430127[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.7968[/C][C]0.203212[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.7572[/C][C]-0.75718[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.7943[/C][C]0.205706[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]13.9953[/C][C]2.00467[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.2191[/C][C]-0.219135[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.4111[/C][C]0.58887[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.9419[/C][C]1.05814[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.8194[/C][C]0.180587[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.7434[/C][C]-1.74341[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]17.3018[/C][C]-0.301805[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]16.0224[/C][C]-0.0223577[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.0028[/C][C]-0.00277298[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.8291[/C][C]-1.82908[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.8503[/C][C]1.14974[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]16.2179[/C][C]-0.217892[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.512[/C][C]2.48797[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.89[/C][C]0.109952[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.2533[/C][C]-0.253252[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.35[/C][C]-1.34997[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.9408[/C][C]1.05924[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.8132[/C][C]2.18681[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.1195[/C][C]0.880479[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]15.1463[/C][C]0.853741[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]15.3755[/C][C]-2.37547[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.9705[/C][C]1.02951[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]16.2991[/C][C]-0.29907[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.7178[/C][C]1.2822[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]13.1398[/C][C]-1.13985[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.2776[/C][C]0.722402[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.2319[/C][C]-0.231926[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.0361[/C][C]1.96391[/C][/ROW]
[ROW][C]113[/C][C]12[/C][C]14.7504[/C][C]-2.75042[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]16.3241[/C][C]1.6759[/C][/ROW]
[ROW][C]115[/C][C]14[/C][C]16.3728[/C][C]-2.37279[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.3263[/C][C]0.673749[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]14.8442[/C][C]-1.84421[/C][/ROW]
[ROW][C]118[/C][C]16[/C][C]15.8739[/C][C]0.126072[/C][/ROW]
[ROW][C]119[/C][C]13[/C][C]14.7735[/C][C]-1.77353[/C][/ROW]
[ROW][C]120[/C][C]16[/C][C]15.4997[/C][C]0.500313[/C][/ROW]
[ROW][C]121[/C][C]13[/C][C]16.1196[/C][C]-3.11958[/C][/ROW]
[ROW][C]122[/C][C]16[/C][C]17.2398[/C][C]-1.2398[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]16.1517[/C][C]-1.15174[/C][/ROW]
[ROW][C]124[/C][C]16[/C][C]17.0082[/C][C]-1.00819[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]14.6706[/C][C]0.32935[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.0692[/C][C]0.930763[/C][/ROW]
[ROW][C]127[/C][C]15[/C][C]14.0364[/C][C]0.963637[/C][/ROW]
[ROW][C]128[/C][C]12[/C][C]14.9479[/C][C]-2.94791[/C][/ROW]
[ROW][C]129[/C][C]16[/C][C]13.9311[/C][C]2.06888[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]13.9121[/C][C]-3.91213[/C][/ROW]
[ROW][C]131[/C][C]16[/C][C]13.6536[/C][C]2.34644[/C][/ROW]
[ROW][C]132[/C][C]12[/C][C]14.1882[/C][C]-2.18819[/C][/ROW]
[ROW][C]133[/C][C]14[/C][C]15.9627[/C][C]-1.96267[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]15.2121[/C][C]-0.212115[/C][/ROW]
[ROW][C]135[/C][C]13[/C][C]12.2545[/C][C]0.745462[/C][/ROW]
[ROW][C]136[/C][C]15[/C][C]14.8837[/C][C]0.116301[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]13.7815[/C][C]-2.78147[/C][/ROW]
[ROW][C]138[/C][C]12[/C][C]13.1344[/C][C]-1.13437[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]13.3506[/C][C]-2.3506[/C][/ROW]
[ROW][C]140[/C][C]16[/C][C]12.9244[/C][C]3.07563[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]13.6228[/C][C]1.37719[/C][/ROW]
[ROW][C]142[/C][C]17[/C][C]17.1274[/C][C]-0.127443[/C][/ROW]
[ROW][C]143[/C][C]16[/C][C]14.0735[/C][C]1.92654[/C][/ROW]
[ROW][C]144[/C][C]10[/C][C]13.3917[/C][C]-3.39168[/C][/ROW]
[ROW][C]145[/C][C]18[/C][C]15.7226[/C][C]2.27736[/C][/ROW]
[ROW][C]146[/C][C]13[/C][C]15.474[/C][C]-2.47398[/C][/ROW]
[ROW][C]147[/C][C]16[/C][C]14.9885[/C][C]1.01152[/C][/ROW]
[ROW][C]148[/C][C]13[/C][C]13.1555[/C][C]-0.15553[/C][/ROW]
[ROW][C]149[/C][C]10[/C][C]13.0795[/C][C]-3.07951[/C][/ROW]
[ROW][C]150[/C][C]15[/C][C]16.7572[/C][C]-1.75716[/C][/ROW]
[ROW][C]151[/C][C]16[/C][C]13.9592[/C][C]2.04079[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]11.9403[/C][C]4.05971[/C][/ROW]
[ROW][C]153[/C][C]14[/C][C]12.8855[/C][C]1.11447[/C][/ROW]
[ROW][C]154[/C][C]10[/C][C]12.6722[/C][C]-2.67224[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.7705[/C][C]1.22955[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]14.0364[/C][C]0.963637[/C][/ROW]
[ROW][C]157[/C][C]16[/C][C]14.6686[/C][C]1.33144[/C][/ROW]
[ROW][C]158[/C][C]12[/C][C]12.9205[/C][C]-0.920511[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]12.3034[/C][C]0.696554[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.6427[/C][C]0.357262[/C][/ROW]
[ROW][C]161[/C][C]17[/C][C]16.4203[/C][C]0.579692[/C][/ROW]
[ROW][C]162[/C][C]15[/C][C]13.5571[/C][C]1.44292[/C][/ROW]
[ROW][C]163[/C][C]10[/C][C]11.1489[/C][C]-1.14887[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]13.8374[/C][C]0.16259[/C][/ROW]
[ROW][C]165[/C][C]11[/C][C]13.6071[/C][C]-2.60714[/C][/ROW]
[ROW][C]166[/C][C]13[/C][C]14.6708[/C][C]-1.67083[/C][/ROW]
[ROW][C]167[/C][C]16[/C][C]14.0939[/C][C]1.90609[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]10.2454[/C][C]1.75464[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]15.2898[/C][C]0.710228[/C][/ROW]
[ROW][C]170[/C][C]12[/C][C]13.7145[/C][C]-1.71454[/C][/ROW]
[ROW][C]171[/C][C]9[/C][C]10.7771[/C][C]-1.77707[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]14.7822[/C][C]-2.78224[/C][/ROW]
[ROW][C]173[/C][C]15[/C][C]14.0137[/C][C]0.986275[/C][/ROW]
[ROW][C]174[/C][C]12[/C][C]12.1056[/C][C]-0.105643[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]12.2687[/C][C]-0.268665[/C][/ROW]
[ROW][C]176[/C][C]14[/C][C]13.3548[/C][C]0.645213[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]13.1775[/C][C]-1.17747[/C][/ROW]
[ROW][C]178[/C][C]16[/C][C]15.0804[/C][C]0.91957[/C][/ROW]
[ROW][C]179[/C][C]11[/C][C]10.8252[/C][C]0.174775[/C][/ROW]
[ROW][C]180[/C][C]19[/C][C]16.6463[/C][C]2.3537[/C][/ROW]
[ROW][C]181[/C][C]15[/C][C]14.9643[/C][C]0.0356528[/C][/ROW]
[ROW][C]182[/C][C]8[/C][C]13.8022[/C][C]-5.8022[/C][/ROW]
[ROW][C]183[/C][C]16[/C][C]14.7239[/C][C]1.27606[/C][/ROW]
[ROW][C]184[/C][C]17[/C][C]14.3138[/C][C]2.68618[/C][/ROW]
[ROW][C]185[/C][C]12[/C][C]11.9684[/C][C]0.0315955[/C][/ROW]
[ROW][C]186[/C][C]11[/C][C]10.8457[/C][C]0.154269[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]10.1773[/C][C]0.822687[/C][/ROW]
[ROW][C]188[/C][C]14[/C][C]14.571[/C][C]-0.570995[/C][/ROW]
[ROW][C]189[/C][C]16[/C][C]15.446[/C][C]0.553995[/C][/ROW]
[ROW][C]190[/C][C]12[/C][C]9.09794[/C][C]2.90206[/C][/ROW]
[ROW][C]191[/C][C]16[/C][C]14.2141[/C][C]1.78591[/C][/ROW]
[ROW][C]192[/C][C]13[/C][C]13.4047[/C][C]-0.404707[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]15.0797[/C][C]-0.0797495[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]12.7885[/C][C]3.21146[/C][/ROW]
[ROW][C]195[/C][C]16[/C][C]14.9268[/C][C]1.07319[/C][/ROW]
[ROW][C]196[/C][C]14[/C][C]12.3419[/C][C]1.65805[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]13.9092[/C][C]2.09083[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]12.7014[/C][C]1.29862[/C][/ROW]
[ROW][C]199[/C][C]11[/C][C]12.9874[/C][C]-1.98744[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]14.6079[/C][C]-2.60786[/C][/ROW]
[ROW][C]201[/C][C]15[/C][C]12.3409[/C][C]2.65912[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]14.3936[/C][C]0.606409[/C][/ROW]
[ROW][C]203[/C][C]16[/C][C]14.4435[/C][C]1.55649[/C][/ROW]
[ROW][C]204[/C][C]16[/C][C]15.1329[/C][C]0.86714[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]13.5576[/C][C]-2.55764[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.6471[/C][C]1.35294[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]14.3889[/C][C]-2.38887[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]16.004[/C][C]-4.00401[/C][/ROW]
[ROW][C]209[/C][C]15[/C][C]14.0863[/C][C]0.913655[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]11.6052[/C][C]3.39481[/C][/ROW]
[ROW][C]211[/C][C]16[/C][C]14.7246[/C][C]1.27539[/C][/ROW]
[ROW][C]212[/C][C]14[/C][C]12.6994[/C][C]1.30057[/C][/ROW]
[ROW][C]213[/C][C]17[/C][C]14.4201[/C][C]2.57985[/C][/ROW]
[ROW][C]214[/C][C]14[/C][C]13.931[/C][C]0.0689658[/C][/ROW]
[ROW][C]215[/C][C]13[/C][C]12.0414[/C][C]0.958567[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]15.3261[/C][C]-0.326082[/C][/ROW]
[ROW][C]217[/C][C]13[/C][C]14.5813[/C][C]-1.58131[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.0962[/C][C]-0.096249[/C][/ROW]
[ROW][C]219[/C][C]15[/C][C]14.339[/C][C]0.661048[/C][/ROW]
[ROW][C]220[/C][C]12[/C][C]12.6809[/C][C]-0.680877[/C][/ROW]
[ROW][C]221[/C][C]8[/C][C]11.2135[/C][C]-3.21352[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]13.6101[/C][C]0.389914[/C][/ROW]
[ROW][C]223[/C][C]14[/C][C]12.7042[/C][C]1.29576[/C][/ROW]
[ROW][C]224[/C][C]11[/C][C]12.412[/C][C]-1.41195[/C][/ROW]
[ROW][C]225[/C][C]12[/C][C]12.7542[/C][C]-0.754162[/C][/ROW]
[ROW][C]226[/C][C]13[/C][C]10.8622[/C][C]2.13778[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]13.3237[/C][C]-3.3237[/C][/ROW]
[ROW][C]228[/C][C]16[/C][C]10.9937[/C][C]5.00626[/C][/ROW]
[ROW][C]229[/C][C]18[/C][C]16.4314[/C][C]1.56859[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]13.6212[/C][C]-0.621187[/C][/ROW]
[ROW][C]231[/C][C]11[/C][C]13.2919[/C][C]-2.29191[/C][/ROW]
[ROW][C]232[/C][C]4[/C][C]10.8888[/C][C]-6.88876[/C][/ROW]
[ROW][C]233[/C][C]13[/C][C]14.4659[/C][C]-1.4659[/C][/ROW]
[ROW][C]234[/C][C]16[/C][C]14.0025[/C][C]1.99745[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]11.4356[/C][C]-1.43559[/C][/ROW]
[ROW][C]236[/C][C]12[/C][C]11.5481[/C][C]0.451867[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]13.8414[/C][C]-1.84136[/C][/ROW]
[ROW][C]238[/C][C]10[/C][C]8.27602[/C][C]1.72398[/C][/ROW]
[ROW][C]239[/C][C]13[/C][C]10.9179[/C][C]2.08207[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]11.7808[/C][C]0.21916[/C][/ROW]
[ROW][C]241[/C][C]14[/C][C]12.7671[/C][C]1.23289[/C][/ROW]
[ROW][C]242[/C][C]10[/C][C]12.9849[/C][C]-2.98493[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]10.2454[/C][C]1.75464[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]11.1052[/C][C]0.894765[/C][/ROW]
[ROW][C]245[/C][C]11[/C][C]11.547[/C][C]-0.547044[/C][/ROW]
[ROW][C]246[/C][C]10[/C][C]11.4213[/C][C]-1.42131[/C][/ROW]
[ROW][C]247[/C][C]12[/C][C]11.1513[/C][C]0.848685[/C][/ROW]
[ROW][C]248[/C][C]16[/C][C]12.6984[/C][C]3.30155[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]13.5512[/C][C]-1.55117[/C][/ROW]
[ROW][C]250[/C][C]14[/C][C]13.9645[/C][C]0.0355296[/C][/ROW]
[ROW][C]251[/C][C]16[/C][C]14.6539[/C][C]1.34607[/C][/ROW]
[ROW][C]252[/C][C]14[/C][C]11.6292[/C][C]2.37076[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.4908[/C][C]-1.49081[/C][/ROW]
[ROW][C]254[/C][C]4[/C][C]8.75639[/C][C]-4.75639[/C][/ROW]
[ROW][C]255[/C][C]15[/C][C]13.4887[/C][C]1.51126[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]15.0992[/C][C]-4.09917[/C][/ROW]
[ROW][C]257[/C][C]11[/C][C]11.6781[/C][C]-0.678052[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]12.4644[/C][C]1.5356[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]14.6183[/C][C]0.381718[/C][/ROW]
[ROW][C]260[/C][C]14[/C][C]11.9721[/C][C]2.02789[/C][/ROW]
[ROW][C]261[/C][C]13[/C][C]12.7926[/C][C]0.207442[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]12.2546[/C][C]-1.25463[/C][/ROW]
[ROW][C]263[/C][C]15[/C][C]13.7846[/C][C]1.21544[/C][/ROW]
[ROW][C]264[/C][C]11[/C][C]11.2831[/C][C]-0.283063[/C][/ROW]
[ROW][C]265[/C][C]13[/C][C]11.654[/C][C]1.34598[/C][/ROW]
[ROW][C]266[/C][C]13[/C][C]11.5832[/C][C]1.41683[/C][/ROW]
[ROW][C]267[/C][C]16[/C][C]13.5117[/C][C]2.48832[/C][/ROW]
[ROW][C]268[/C][C]13[/C][C]12.2236[/C][C]0.776445[/C][/ROW]
[ROW][C]269[/C][C]16[/C][C]14.934[/C][C]1.06605[/C][/ROW]
[ROW][C]270[/C][C]16[/C][C]15.8344[/C][C]0.165602[/C][/ROW]
[ROW][C]271[/C][C]12[/C][C]11.4402[/C][C]0.559841[/C][/ROW]
[ROW][C]272[/C][C]7[/C][C]10.8123[/C][C]-3.8123[/C][/ROW]
[ROW][C]273[/C][C]16[/C][C]13.9146[/C][C]2.08545[/C][/ROW]
[ROW][C]274[/C][C]5[/C][C]9.20467[/C][C]-4.20467[/C][/ROW]
[ROW][C]275[/C][C]16[/C][C]13.1463[/C][C]2.85371[/C][/ROW]
[ROW][C]276[/C][C]4[/C][C]8.64173[/C][C]-4.64173[/C][/ROW]
[ROW][C]277[/C][C]12[/C][C]13.3401[/C][C]-1.34007[/C][/ROW]
[ROW][C]278[/C][C]15[/C][C]14.131[/C][C]0.868969[/C][/ROW]
[ROW][C]279[/C][C]14[/C][C]14.8341[/C][C]-0.834112[/C][/ROW]
[ROW][C]280[/C][C]11[/C][C]13.0206[/C][C]-2.02056[/C][/ROW]
[ROW][C]281[/C][C]16[/C][C]14.9844[/C][C]1.01557[/C][/ROW]
[ROW][C]282[/C][C]15[/C][C]13.6374[/C][C]1.36259[/C][/ROW]
[ROW][C]283[/C][C]12[/C][C]12.0787[/C][C]-0.0787396[/C][/ROW]
[ROW][C]284[/C][C]6[/C][C]8.99808[/C][C]-2.99808[/C][/ROW]
[ROW][C]285[/C][C]16[/C][C]14.5182[/C][C]1.48178[/C][/ROW]
[ROW][C]286[/C][C]10[/C][C]13.3329[/C][C]-3.33293[/C][/ROW]
[ROW][C]287[/C][C]15[/C][C]16.0797[/C][C]-1.07973[/C][/ROW]
[ROW][C]288[/C][C]14[/C][C]14.4912[/C][C]-0.491237[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231355&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231355&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
11316.1967-3.19672
21615.4010.599048
31916.8982.10198
41511.29143.70859
51416.4266-2.42657
61314.3285-1.32845
71915.6623.33803
81516.8405-1.84054
91415.754-1.75401
101514.12330.876742
111614.54431.45575
121616.0035-0.00351307
131615.48110.518882
141615.58640.413644
151717.7561-0.756135
161515.2542-0.254218
171514.23120.768783
182016.21613.78386
191815.40292.59711
201615.38130.618707
211614.93681.06319
221614.87251.12748
231916.682.31998
241615.19680.803156
251715.91731.08273
261716.09930.9007
271614.55331.44666
281516.8269-1.82693
291615.43120.568787
301413.91820.0818206
311515.2549-0.254898
321212.2781-0.278101
331414.5048-0.50477
341615.72680.273215
351415.225-1.22505
361012.2906-2.29062
371012.6791-2.67912
381415.6107-1.6107
391613.94472.05525
401614.14111.85887
411614.37771.62231
421415.5777-1.57769
432017.64072.35928
441414.0647-0.064657
451414.2526-0.252645
461115.5181-4.51811
471416.7429-2.74289
481514.86430.135704
491615.45280.547176
501415.5414-1.54137
511616.9663-0.966266
521413.83840.161578
531215.0248-3.02479
541616.1771-0.177062
55910.6817-1.68171
561412.08421.91585
571615.98410.0159044
581615.20760.792405
591514.99710.00285141
601614.15161.84843
611211.25690.743145
621615.65420.34585
631616.5547-0.554718
641414.7042-0.704209
651615.38840.61157
661716.00720.992796
671816.69471.30528
681813.99964.0004
691216.246-4.24598
701615.76630.23373
711013.3502-3.35017
721415.0263-1.02634
731817.08620.913812
741817.44850.551534
751614.97941.02061
761713.58273.4173
771616.7131-0.713052
781614.61221.38783
791314.9379-1.9379
801615.18940.8106
811615.56990.430127
821615.79680.203212
831515.7572-0.75718
841514.79430.205706
851613.99532.00467
861414.2191-0.219135
871615.41110.58887
881614.94191.05814
891514.81940.180587
901213.7434-1.74341
911717.3018-0.301805
921616.0224-0.0223577
931515.0028-0.00277298
941314.8291-1.82908
951614.85031.14974
961616.2179-0.217892
971613.5122.48797
981615.890.109952
991414.2533-0.253252
1001617.35-1.34997
1011614.94081.05924
1022017.81322.18681
1031514.11950.880479
1041615.14630.853741
1051315.3755-2.37547
1061715.97051.02951
1071616.2991-0.29907
1081614.71781.2822
1091213.1398-1.13985
1101615.27760.722402
1111616.2319-0.231926
1121715.03611.96391
1131214.7504-2.75042
1141816.32411.6759
1151416.3728-2.37279
1161413.32630.673749
1171314.8442-1.84421
1181615.87390.126072
1191314.7735-1.77353
1201615.49970.500313
1211316.1196-3.11958
1221617.2398-1.2398
1231516.1517-1.15174
1241617.0082-1.00819
1251514.67060.32935
1261716.06920.930763
1271514.03640.963637
1281214.9479-2.94791
1291613.93112.06888
1301013.9121-3.91213
1311613.65362.34644
1321214.1882-2.18819
1331415.9627-1.96267
1341515.2121-0.212115
1351312.25450.745462
1361514.88370.116301
1371113.7815-2.78147
1381213.1344-1.13437
1391113.3506-2.3506
1401612.92443.07563
1411513.62281.37719
1421717.1274-0.127443
1431614.07351.92654
1441013.3917-3.39168
1451815.72262.27736
1461315.474-2.47398
1471614.98851.01152
1481313.1555-0.15553
1491013.0795-3.07951
1501516.7572-1.75716
1511613.95922.04079
1521611.94034.05971
1531412.88551.11447
1541012.6722-2.67224
1551311.77051.22955
1561514.03640.963637
1571614.66861.33144
1581212.9205-0.920511
1591312.30340.696554
1601211.64270.357262
1611716.42030.579692
1621513.55711.44292
1631011.1489-1.14887
1641413.83740.16259
1651113.6071-2.60714
1661314.6708-1.67083
1671614.09391.90609
1681210.24541.75464
1691615.28980.710228
1701213.7145-1.71454
171910.7771-1.77707
1721214.7822-2.78224
1731514.01370.986275
1741212.1056-0.105643
1751212.2687-0.268665
1761413.35480.645213
1771213.1775-1.17747
1781615.08040.91957
1791110.82520.174775
1801916.64632.3537
1811514.96430.0356528
182813.8022-5.8022
1831614.72391.27606
1841714.31382.68618
1851211.96840.0315955
1861110.84570.154269
1871110.17730.822687
1881414.571-0.570995
1891615.4460.553995
190129.097942.90206
1911614.21411.78591
1921313.4047-0.404707
1931515.0797-0.0797495
1941612.78853.21146
1951614.92681.07319
1961412.34191.65805
1971613.90922.09083
1981412.70141.29862
1991112.9874-1.98744
2001214.6079-2.60786
2011512.34092.65912
2021514.39360.606409
2031614.44351.55649
2041615.13290.86714
2051113.5576-2.55764
2061513.64711.35294
2071214.3889-2.38887
2081216.004-4.00401
2091514.08630.913655
2101511.60523.39481
2111614.72461.27539
2121412.69941.30057
2131714.42012.57985
2141413.9310.0689658
2151312.04140.958567
2161515.3261-0.326082
2171314.5813-1.58131
2181414.0962-0.096249
2191514.3390.661048
2201212.6809-0.680877
221811.2135-3.21352
2221413.61010.389914
2231412.70421.29576
2241112.412-1.41195
2251212.7542-0.754162
2261310.86222.13778
2271013.3237-3.3237
2281610.99375.00626
2291816.43141.56859
2301313.6212-0.621187
2311113.2919-2.29191
232410.8888-6.88876
2331314.4659-1.4659
2341614.00251.99745
2351011.4356-1.43559
2361211.54810.451867
2371213.8414-1.84136
238108.276021.72398
2391310.91792.08207
2401211.78080.21916
2411412.76711.23289
2421012.9849-2.98493
2431210.24541.75464
2441211.10520.894765
2451111.547-0.547044
2461011.4213-1.42131
2471211.15130.848685
2481612.69843.30155
2491213.5512-1.55117
2501413.96450.0355296
2511614.65391.34607
2521411.62922.37076
2531314.4908-1.49081
25448.75639-4.75639
2551513.48871.51126
2561115.0992-4.09917
2571111.6781-0.678052
2581412.46441.5356
2591514.61830.381718
2601411.97212.02789
2611312.79260.207442
2621112.2546-1.25463
2631513.78461.21544
2641111.2831-0.283063
2651311.6541.34598
2661311.58321.41683
2671613.51172.48832
2681312.22360.776445
2691614.9341.06605
2701615.83440.165602
2711211.44020.559841
272710.8123-3.8123
2731613.91462.08545
27459.20467-4.20467
2751613.14632.85371
27648.64173-4.64173
2771213.3401-1.34007
2781514.1310.868969
2791414.8341-0.834112
2801113.0206-2.02056
2811614.98441.01557
2821513.63741.36259
2831212.0787-0.0787396
28468.99808-2.99808
2851614.51821.48178
2861013.3329-3.33293
2871516.0797-1.07973
2881414.4912-0.491237







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.8140860.3718270.185914
110.7612290.4775410.238771
120.7841450.4317110.215855
130.7191610.5616770.280839
140.7124120.5751760.287588
150.6690450.6619110.330955
160.61260.7747990.3874
170.5248230.9503540.475177
180.8557410.2885180.144259
190.8499990.3000020.150001
200.8020030.3959940.197997
210.7458980.5082040.254102
220.6840990.6318020.315901
230.7037920.5924160.296208
240.6406160.7187690.359384
250.5774830.8450340.422517
260.510840.978320.48916
270.4471860.8943720.552814
280.4304030.8608050.569597
290.3698740.7397480.630126
300.356280.712560.64372
310.3008570.6017140.699143
320.2852030.5704060.714797
330.251840.503680.74816
340.207050.4140990.79295
350.2059320.4118640.794068
360.2941920.5883830.705808
370.3817230.7634460.618277
380.383990.767980.61601
390.4124450.8248890.587555
400.3916940.7833870.608306
410.3579920.7159830.642008
420.3449280.6898550.655072
430.3579080.7158160.642092
440.3171950.6343910.682805
450.2811120.5622240.718888
460.5164210.9671580.483579
470.5678740.8642520.432126
480.5214010.9571970.478599
490.4771550.9543110.522845
500.4806790.9613580.519321
510.4385740.8771480.561426
520.3933250.786650.606675
530.4469610.8939230.553039
540.4044710.8089430.595529
550.4064750.812950.593525
560.3908130.7816250.609187
570.3495170.6990330.650483
580.3267120.6534240.673288
590.2876530.5753070.712347
600.2897040.5794090.710296
610.2602930.5205860.739707
620.2266810.4533620.773319
630.1959690.3919380.804031
640.1694480.3388960.830552
650.1463510.2927020.853649
660.1341390.2682770.865861
670.1275040.2550080.872496
680.2180350.4360710.781965
690.3421890.6843770.657811
700.3062360.6124720.693764
710.3901940.7803880.609806
720.3563340.7126680.643666
730.3388850.677770.661115
740.3113930.6227860.688607
750.2807090.5614180.719291
760.3356880.6713750.664312
770.303570.607140.69643
780.2815180.5630360.718482
790.2851270.5702540.714873
800.2575860.5151730.742414
810.2311650.462330.768835
820.2038980.4077960.796102
830.184080.3681590.81592
840.1598010.3196020.840199
850.1567520.3135040.843248
860.1348760.2697510.865124
870.1169090.2338170.883091
880.1039360.2078710.896064
890.08798260.1759650.912017
900.0835260.1670520.916474
910.07159430.1431890.928406
920.06096380.1219280.939036
930.0517020.1034040.948298
940.05324090.1064820.946759
950.04673480.09346950.953265
960.03851270.07702540.961487
970.04173630.08347250.958264
980.0341720.06834390.965828
990.02775030.05550060.97225
1000.02487830.04975660.975122
1010.02149310.04298630.978507
1020.02541590.05083170.974584
1030.02132310.04264630.978677
1040.01884410.03768820.981156
1050.02390950.04781890.976091
1060.02047790.04095580.979522
1070.01639390.03278780.983606
1080.01492520.02985040.985075
1090.01273970.02547940.98726
1100.01050520.02101030.989495
1110.008264610.01652920.991735
1120.009715280.01943060.990285
1130.01363490.02726980.986365
1140.01317660.02635310.986823
1150.01399430.02798870.986006
1160.01173480.02346970.988265
1170.01162590.02325190.988374
1180.009221130.01844230.990779
1190.008611330.01722270.991389
1200.006928220.01385640.993072
1210.00999640.01999280.990004
1220.008508090.01701620.991492
1230.007583090.01516620.992417
1240.006323850.01264770.993676
1250.005013060.01002610.994987
1260.00420040.008400810.9958
1270.003470470.006940950.99653
1280.005358240.01071650.994642
1290.005686990.0113740.994313
1300.0124270.02485410.987573
1310.01378150.0275630.986218
1320.01481810.02963620.985182
1330.01464180.02928350.985358
1340.01187160.02374330.988128
1350.009855850.01971170.990144
1360.007829470.01565890.992171
1370.01043670.02087340.989563
1380.009335760.01867150.990664
1390.01073090.02146180.989269
1400.01479960.02959920.9852
1410.01373720.02747440.986263
1420.01136870.02273750.988631
1430.01139010.02278010.98861
1440.0214370.04287410.978563
1450.02303780.04607560.976962
1460.02610280.05220550.973897
1470.02257790.04515570.977422
1480.01837780.03675560.981622
1490.0270910.0541820.972909
1500.0273860.05477210.972614
1510.02749570.05499130.972504
1520.05087320.1017460.949127
1530.04523350.09046710.954766
1540.05664350.1132870.943356
1550.04976130.09952260.950239
1560.0427690.08553810.957231
1570.04065710.08131410.959343
1580.03418250.0683650.965818
1590.02887220.05774430.971128
1600.02461360.04922730.975386
1610.0206410.0412820.979359
1620.01812050.0362410.981879
1630.01673820.03347640.983262
1640.01347010.02694010.98653
1650.01678350.0335670.983216
1660.01663280.03326550.983367
1670.01705090.03410170.982949
1680.01712040.03424090.98288
1690.01402730.02805450.985973
1700.01332670.02665340.986673
1710.01315860.02631710.986841
1720.01581470.03162940.984185
1730.01362030.02724070.98638
1740.01088080.02176160.989119
1750.008641520.0172830.991358
1760.007006760.01401350.992993
1770.006047190.01209440.993953
1780.005039130.01007830.994961
1790.004017470.008034950.995983
1800.004510270.009020550.99549
1810.00350850.0070170.996492
1820.02756010.05512020.97244
1830.02449280.04898560.975507
1840.03084060.06168120.969159
1850.02566010.05132020.97434
1860.0209850.04197010.979015
1870.01770050.0354010.9823
1880.01554640.03109290.984454
1890.01260410.02520830.987396
1900.01784870.03569740.982151
1910.0163610.03272210.983639
1920.01332260.02664520.986677
1930.01058180.02116360.989418
1940.01601910.03203830.983981
1950.01320840.02641680.986792
1960.01225950.02451910.98774
1970.01201940.02403890.987981
1980.01004510.02009030.989955
1990.009926720.01985340.990073
2000.01226260.02452520.987737
2010.01470890.02941790.985291
2020.01169190.02338380.988308
2030.01015830.02031650.989842
2040.008182880.01636580.991817
2050.009555560.01911110.990444
2060.008558420.01711680.991442
2070.01122620.02245240.988774
2080.02552480.05104960.974475
2090.02084210.04168430.979158
2100.0326170.06523390.967383
2110.0274510.05490190.972549
2120.0252540.05050810.974746
2130.02708970.05417930.97291
2140.02171580.04343150.978284
2150.01858010.03716030.98142
2160.01544260.03088530.984557
2170.0145420.0290840.985458
2180.01138230.02276450.988618
2190.008832450.01766490.991168
2200.006945920.01389180.993054
2210.01107960.02215920.98892
2220.008605180.01721040.991395
2230.007446690.01489340.992553
2240.00633980.01267960.99366
2250.004940180.009880360.99506
2260.006294580.01258920.993705
2270.01425490.02850980.985745
2280.07864570.1572910.921354
2290.07104670.1420930.928953
2300.05842340.1168470.941577
2310.05909080.1181820.940909
2320.2424190.4848370.757581
2330.223150.44630.77685
2340.2030240.4060490.796976
2350.1801260.3602520.819874
2360.153650.3073010.84635
2370.1842170.3684330.815783
2380.2364590.4729180.763541
2390.2981290.5962580.701871
2400.258940.5178810.74106
2410.2437320.4874650.756268
2420.2789340.5578670.721066
2430.2672750.5345490.732725
2440.2429770.4859550.757023
2450.214090.428180.78591
2460.1834890.3669780.816511
2470.182160.364320.81784
2480.2786690.5573390.721331
2490.2622320.5244650.737768
2500.2226570.4453130.777343
2510.1892860.3785730.810714
2520.2123380.4246750.787662
2530.1940960.3881920.805904
2540.2589860.5179710.741014
2550.2482790.4965580.751721
2560.5008680.9982650.499132
2570.4531960.9063930.546804
2580.4617610.9235220.538239
2590.4406940.8813870.559306
2600.4630870.9261740.536913
2610.4035090.8070190.596491
2620.3541890.7083780.645811
2630.316610.633220.68339
2640.2595670.5191340.740433
2650.2570810.5141610.742919
2660.3685860.7371720.631414
2670.6137510.7724980.386249
2680.5520440.8959120.447956
2690.5030510.9938980.496949
2700.5136610.9726770.486339
2710.4419420.8838840.558058
2720.418640.8372790.58136
2730.3648650.7297290.635135
2740.2889470.5778940.711053
2750.4255950.851190.574405
2760.3767770.7535550.623223
2770.2666060.5332110.733394
2780.1710920.3421850.828908

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.814086 & 0.371827 & 0.185914 \tabularnewline
11 & 0.761229 & 0.477541 & 0.238771 \tabularnewline
12 & 0.784145 & 0.431711 & 0.215855 \tabularnewline
13 & 0.719161 & 0.561677 & 0.280839 \tabularnewline
14 & 0.712412 & 0.575176 & 0.287588 \tabularnewline
15 & 0.669045 & 0.661911 & 0.330955 \tabularnewline
16 & 0.6126 & 0.774799 & 0.3874 \tabularnewline
17 & 0.524823 & 0.950354 & 0.475177 \tabularnewline
18 & 0.855741 & 0.288518 & 0.144259 \tabularnewline
19 & 0.849999 & 0.300002 & 0.150001 \tabularnewline
20 & 0.802003 & 0.395994 & 0.197997 \tabularnewline
21 & 0.745898 & 0.508204 & 0.254102 \tabularnewline
22 & 0.684099 & 0.631802 & 0.315901 \tabularnewline
23 & 0.703792 & 0.592416 & 0.296208 \tabularnewline
24 & 0.640616 & 0.718769 & 0.359384 \tabularnewline
25 & 0.577483 & 0.845034 & 0.422517 \tabularnewline
26 & 0.51084 & 0.97832 & 0.48916 \tabularnewline
27 & 0.447186 & 0.894372 & 0.552814 \tabularnewline
28 & 0.430403 & 0.860805 & 0.569597 \tabularnewline
29 & 0.369874 & 0.739748 & 0.630126 \tabularnewline
30 & 0.35628 & 0.71256 & 0.64372 \tabularnewline
31 & 0.300857 & 0.601714 & 0.699143 \tabularnewline
32 & 0.285203 & 0.570406 & 0.714797 \tabularnewline
33 & 0.25184 & 0.50368 & 0.74816 \tabularnewline
34 & 0.20705 & 0.414099 & 0.79295 \tabularnewline
35 & 0.205932 & 0.411864 & 0.794068 \tabularnewline
36 & 0.294192 & 0.588383 & 0.705808 \tabularnewline
37 & 0.381723 & 0.763446 & 0.618277 \tabularnewline
38 & 0.38399 & 0.76798 & 0.61601 \tabularnewline
39 & 0.412445 & 0.824889 & 0.587555 \tabularnewline
40 & 0.391694 & 0.783387 & 0.608306 \tabularnewline
41 & 0.357992 & 0.715983 & 0.642008 \tabularnewline
42 & 0.344928 & 0.689855 & 0.655072 \tabularnewline
43 & 0.357908 & 0.715816 & 0.642092 \tabularnewline
44 & 0.317195 & 0.634391 & 0.682805 \tabularnewline
45 & 0.281112 & 0.562224 & 0.718888 \tabularnewline
46 & 0.516421 & 0.967158 & 0.483579 \tabularnewline
47 & 0.567874 & 0.864252 & 0.432126 \tabularnewline
48 & 0.521401 & 0.957197 & 0.478599 \tabularnewline
49 & 0.477155 & 0.954311 & 0.522845 \tabularnewline
50 & 0.480679 & 0.961358 & 0.519321 \tabularnewline
51 & 0.438574 & 0.877148 & 0.561426 \tabularnewline
52 & 0.393325 & 0.78665 & 0.606675 \tabularnewline
53 & 0.446961 & 0.893923 & 0.553039 \tabularnewline
54 & 0.404471 & 0.808943 & 0.595529 \tabularnewline
55 & 0.406475 & 0.81295 & 0.593525 \tabularnewline
56 & 0.390813 & 0.781625 & 0.609187 \tabularnewline
57 & 0.349517 & 0.699033 & 0.650483 \tabularnewline
58 & 0.326712 & 0.653424 & 0.673288 \tabularnewline
59 & 0.287653 & 0.575307 & 0.712347 \tabularnewline
60 & 0.289704 & 0.579409 & 0.710296 \tabularnewline
61 & 0.260293 & 0.520586 & 0.739707 \tabularnewline
62 & 0.226681 & 0.453362 & 0.773319 \tabularnewline
63 & 0.195969 & 0.391938 & 0.804031 \tabularnewline
64 & 0.169448 & 0.338896 & 0.830552 \tabularnewline
65 & 0.146351 & 0.292702 & 0.853649 \tabularnewline
66 & 0.134139 & 0.268277 & 0.865861 \tabularnewline
67 & 0.127504 & 0.255008 & 0.872496 \tabularnewline
68 & 0.218035 & 0.436071 & 0.781965 \tabularnewline
69 & 0.342189 & 0.684377 & 0.657811 \tabularnewline
70 & 0.306236 & 0.612472 & 0.693764 \tabularnewline
71 & 0.390194 & 0.780388 & 0.609806 \tabularnewline
72 & 0.356334 & 0.712668 & 0.643666 \tabularnewline
73 & 0.338885 & 0.67777 & 0.661115 \tabularnewline
74 & 0.311393 & 0.622786 & 0.688607 \tabularnewline
75 & 0.280709 & 0.561418 & 0.719291 \tabularnewline
76 & 0.335688 & 0.671375 & 0.664312 \tabularnewline
77 & 0.30357 & 0.60714 & 0.69643 \tabularnewline
78 & 0.281518 & 0.563036 & 0.718482 \tabularnewline
79 & 0.285127 & 0.570254 & 0.714873 \tabularnewline
80 & 0.257586 & 0.515173 & 0.742414 \tabularnewline
81 & 0.231165 & 0.46233 & 0.768835 \tabularnewline
82 & 0.203898 & 0.407796 & 0.796102 \tabularnewline
83 & 0.18408 & 0.368159 & 0.81592 \tabularnewline
84 & 0.159801 & 0.319602 & 0.840199 \tabularnewline
85 & 0.156752 & 0.313504 & 0.843248 \tabularnewline
86 & 0.134876 & 0.269751 & 0.865124 \tabularnewline
87 & 0.116909 & 0.233817 & 0.883091 \tabularnewline
88 & 0.103936 & 0.207871 & 0.896064 \tabularnewline
89 & 0.0879826 & 0.175965 & 0.912017 \tabularnewline
90 & 0.083526 & 0.167052 & 0.916474 \tabularnewline
91 & 0.0715943 & 0.143189 & 0.928406 \tabularnewline
92 & 0.0609638 & 0.121928 & 0.939036 \tabularnewline
93 & 0.051702 & 0.103404 & 0.948298 \tabularnewline
94 & 0.0532409 & 0.106482 & 0.946759 \tabularnewline
95 & 0.0467348 & 0.0934695 & 0.953265 \tabularnewline
96 & 0.0385127 & 0.0770254 & 0.961487 \tabularnewline
97 & 0.0417363 & 0.0834725 & 0.958264 \tabularnewline
98 & 0.034172 & 0.0683439 & 0.965828 \tabularnewline
99 & 0.0277503 & 0.0555006 & 0.97225 \tabularnewline
100 & 0.0248783 & 0.0497566 & 0.975122 \tabularnewline
101 & 0.0214931 & 0.0429863 & 0.978507 \tabularnewline
102 & 0.0254159 & 0.0508317 & 0.974584 \tabularnewline
103 & 0.0213231 & 0.0426463 & 0.978677 \tabularnewline
104 & 0.0188441 & 0.0376882 & 0.981156 \tabularnewline
105 & 0.0239095 & 0.0478189 & 0.976091 \tabularnewline
106 & 0.0204779 & 0.0409558 & 0.979522 \tabularnewline
107 & 0.0163939 & 0.0327878 & 0.983606 \tabularnewline
108 & 0.0149252 & 0.0298504 & 0.985075 \tabularnewline
109 & 0.0127397 & 0.0254794 & 0.98726 \tabularnewline
110 & 0.0105052 & 0.0210103 & 0.989495 \tabularnewline
111 & 0.00826461 & 0.0165292 & 0.991735 \tabularnewline
112 & 0.00971528 & 0.0194306 & 0.990285 \tabularnewline
113 & 0.0136349 & 0.0272698 & 0.986365 \tabularnewline
114 & 0.0131766 & 0.0263531 & 0.986823 \tabularnewline
115 & 0.0139943 & 0.0279887 & 0.986006 \tabularnewline
116 & 0.0117348 & 0.0234697 & 0.988265 \tabularnewline
117 & 0.0116259 & 0.0232519 & 0.988374 \tabularnewline
118 & 0.00922113 & 0.0184423 & 0.990779 \tabularnewline
119 & 0.00861133 & 0.0172227 & 0.991389 \tabularnewline
120 & 0.00692822 & 0.0138564 & 0.993072 \tabularnewline
121 & 0.0099964 & 0.0199928 & 0.990004 \tabularnewline
122 & 0.00850809 & 0.0170162 & 0.991492 \tabularnewline
123 & 0.00758309 & 0.0151662 & 0.992417 \tabularnewline
124 & 0.00632385 & 0.0126477 & 0.993676 \tabularnewline
125 & 0.00501306 & 0.0100261 & 0.994987 \tabularnewline
126 & 0.0042004 & 0.00840081 & 0.9958 \tabularnewline
127 & 0.00347047 & 0.00694095 & 0.99653 \tabularnewline
128 & 0.00535824 & 0.0107165 & 0.994642 \tabularnewline
129 & 0.00568699 & 0.011374 & 0.994313 \tabularnewline
130 & 0.012427 & 0.0248541 & 0.987573 \tabularnewline
131 & 0.0137815 & 0.027563 & 0.986218 \tabularnewline
132 & 0.0148181 & 0.0296362 & 0.985182 \tabularnewline
133 & 0.0146418 & 0.0292835 & 0.985358 \tabularnewline
134 & 0.0118716 & 0.0237433 & 0.988128 \tabularnewline
135 & 0.00985585 & 0.0197117 & 0.990144 \tabularnewline
136 & 0.00782947 & 0.0156589 & 0.992171 \tabularnewline
137 & 0.0104367 & 0.0208734 & 0.989563 \tabularnewline
138 & 0.00933576 & 0.0186715 & 0.990664 \tabularnewline
139 & 0.0107309 & 0.0214618 & 0.989269 \tabularnewline
140 & 0.0147996 & 0.0295992 & 0.9852 \tabularnewline
141 & 0.0137372 & 0.0274744 & 0.986263 \tabularnewline
142 & 0.0113687 & 0.0227375 & 0.988631 \tabularnewline
143 & 0.0113901 & 0.0227801 & 0.98861 \tabularnewline
144 & 0.021437 & 0.0428741 & 0.978563 \tabularnewline
145 & 0.0230378 & 0.0460756 & 0.976962 \tabularnewline
146 & 0.0261028 & 0.0522055 & 0.973897 \tabularnewline
147 & 0.0225779 & 0.0451557 & 0.977422 \tabularnewline
148 & 0.0183778 & 0.0367556 & 0.981622 \tabularnewline
149 & 0.027091 & 0.054182 & 0.972909 \tabularnewline
150 & 0.027386 & 0.0547721 & 0.972614 \tabularnewline
151 & 0.0274957 & 0.0549913 & 0.972504 \tabularnewline
152 & 0.0508732 & 0.101746 & 0.949127 \tabularnewline
153 & 0.0452335 & 0.0904671 & 0.954766 \tabularnewline
154 & 0.0566435 & 0.113287 & 0.943356 \tabularnewline
155 & 0.0497613 & 0.0995226 & 0.950239 \tabularnewline
156 & 0.042769 & 0.0855381 & 0.957231 \tabularnewline
157 & 0.0406571 & 0.0813141 & 0.959343 \tabularnewline
158 & 0.0341825 & 0.068365 & 0.965818 \tabularnewline
159 & 0.0288722 & 0.0577443 & 0.971128 \tabularnewline
160 & 0.0246136 & 0.0492273 & 0.975386 \tabularnewline
161 & 0.020641 & 0.041282 & 0.979359 \tabularnewline
162 & 0.0181205 & 0.036241 & 0.981879 \tabularnewline
163 & 0.0167382 & 0.0334764 & 0.983262 \tabularnewline
164 & 0.0134701 & 0.0269401 & 0.98653 \tabularnewline
165 & 0.0167835 & 0.033567 & 0.983216 \tabularnewline
166 & 0.0166328 & 0.0332655 & 0.983367 \tabularnewline
167 & 0.0170509 & 0.0341017 & 0.982949 \tabularnewline
168 & 0.0171204 & 0.0342409 & 0.98288 \tabularnewline
169 & 0.0140273 & 0.0280545 & 0.985973 \tabularnewline
170 & 0.0133267 & 0.0266534 & 0.986673 \tabularnewline
171 & 0.0131586 & 0.0263171 & 0.986841 \tabularnewline
172 & 0.0158147 & 0.0316294 & 0.984185 \tabularnewline
173 & 0.0136203 & 0.0272407 & 0.98638 \tabularnewline
174 & 0.0108808 & 0.0217616 & 0.989119 \tabularnewline
175 & 0.00864152 & 0.017283 & 0.991358 \tabularnewline
176 & 0.00700676 & 0.0140135 & 0.992993 \tabularnewline
177 & 0.00604719 & 0.0120944 & 0.993953 \tabularnewline
178 & 0.00503913 & 0.0100783 & 0.994961 \tabularnewline
179 & 0.00401747 & 0.00803495 & 0.995983 \tabularnewline
180 & 0.00451027 & 0.00902055 & 0.99549 \tabularnewline
181 & 0.0035085 & 0.007017 & 0.996492 \tabularnewline
182 & 0.0275601 & 0.0551202 & 0.97244 \tabularnewline
183 & 0.0244928 & 0.0489856 & 0.975507 \tabularnewline
184 & 0.0308406 & 0.0616812 & 0.969159 \tabularnewline
185 & 0.0256601 & 0.0513202 & 0.97434 \tabularnewline
186 & 0.020985 & 0.0419701 & 0.979015 \tabularnewline
187 & 0.0177005 & 0.035401 & 0.9823 \tabularnewline
188 & 0.0155464 & 0.0310929 & 0.984454 \tabularnewline
189 & 0.0126041 & 0.0252083 & 0.987396 \tabularnewline
190 & 0.0178487 & 0.0356974 & 0.982151 \tabularnewline
191 & 0.016361 & 0.0327221 & 0.983639 \tabularnewline
192 & 0.0133226 & 0.0266452 & 0.986677 \tabularnewline
193 & 0.0105818 & 0.0211636 & 0.989418 \tabularnewline
194 & 0.0160191 & 0.0320383 & 0.983981 \tabularnewline
195 & 0.0132084 & 0.0264168 & 0.986792 \tabularnewline
196 & 0.0122595 & 0.0245191 & 0.98774 \tabularnewline
197 & 0.0120194 & 0.0240389 & 0.987981 \tabularnewline
198 & 0.0100451 & 0.0200903 & 0.989955 \tabularnewline
199 & 0.00992672 & 0.0198534 & 0.990073 \tabularnewline
200 & 0.0122626 & 0.0245252 & 0.987737 \tabularnewline
201 & 0.0147089 & 0.0294179 & 0.985291 \tabularnewline
202 & 0.0116919 & 0.0233838 & 0.988308 \tabularnewline
203 & 0.0101583 & 0.0203165 & 0.989842 \tabularnewline
204 & 0.00818288 & 0.0163658 & 0.991817 \tabularnewline
205 & 0.00955556 & 0.0191111 & 0.990444 \tabularnewline
206 & 0.00855842 & 0.0171168 & 0.991442 \tabularnewline
207 & 0.0112262 & 0.0224524 & 0.988774 \tabularnewline
208 & 0.0255248 & 0.0510496 & 0.974475 \tabularnewline
209 & 0.0208421 & 0.0416843 & 0.979158 \tabularnewline
210 & 0.032617 & 0.0652339 & 0.967383 \tabularnewline
211 & 0.027451 & 0.0549019 & 0.972549 \tabularnewline
212 & 0.025254 & 0.0505081 & 0.974746 \tabularnewline
213 & 0.0270897 & 0.0541793 & 0.97291 \tabularnewline
214 & 0.0217158 & 0.0434315 & 0.978284 \tabularnewline
215 & 0.0185801 & 0.0371603 & 0.98142 \tabularnewline
216 & 0.0154426 & 0.0308853 & 0.984557 \tabularnewline
217 & 0.014542 & 0.029084 & 0.985458 \tabularnewline
218 & 0.0113823 & 0.0227645 & 0.988618 \tabularnewline
219 & 0.00883245 & 0.0176649 & 0.991168 \tabularnewline
220 & 0.00694592 & 0.0138918 & 0.993054 \tabularnewline
221 & 0.0110796 & 0.0221592 & 0.98892 \tabularnewline
222 & 0.00860518 & 0.0172104 & 0.991395 \tabularnewline
223 & 0.00744669 & 0.0148934 & 0.992553 \tabularnewline
224 & 0.0063398 & 0.0126796 & 0.99366 \tabularnewline
225 & 0.00494018 & 0.00988036 & 0.99506 \tabularnewline
226 & 0.00629458 & 0.0125892 & 0.993705 \tabularnewline
227 & 0.0142549 & 0.0285098 & 0.985745 \tabularnewline
228 & 0.0786457 & 0.157291 & 0.921354 \tabularnewline
229 & 0.0710467 & 0.142093 & 0.928953 \tabularnewline
230 & 0.0584234 & 0.116847 & 0.941577 \tabularnewline
231 & 0.0590908 & 0.118182 & 0.940909 \tabularnewline
232 & 0.242419 & 0.484837 & 0.757581 \tabularnewline
233 & 0.22315 & 0.4463 & 0.77685 \tabularnewline
234 & 0.203024 & 0.406049 & 0.796976 \tabularnewline
235 & 0.180126 & 0.360252 & 0.819874 \tabularnewline
236 & 0.15365 & 0.307301 & 0.84635 \tabularnewline
237 & 0.184217 & 0.368433 & 0.815783 \tabularnewline
238 & 0.236459 & 0.472918 & 0.763541 \tabularnewline
239 & 0.298129 & 0.596258 & 0.701871 \tabularnewline
240 & 0.25894 & 0.517881 & 0.74106 \tabularnewline
241 & 0.243732 & 0.487465 & 0.756268 \tabularnewline
242 & 0.278934 & 0.557867 & 0.721066 \tabularnewline
243 & 0.267275 & 0.534549 & 0.732725 \tabularnewline
244 & 0.242977 & 0.485955 & 0.757023 \tabularnewline
245 & 0.21409 & 0.42818 & 0.78591 \tabularnewline
246 & 0.183489 & 0.366978 & 0.816511 \tabularnewline
247 & 0.18216 & 0.36432 & 0.81784 \tabularnewline
248 & 0.278669 & 0.557339 & 0.721331 \tabularnewline
249 & 0.262232 & 0.524465 & 0.737768 \tabularnewline
250 & 0.222657 & 0.445313 & 0.777343 \tabularnewline
251 & 0.189286 & 0.378573 & 0.810714 \tabularnewline
252 & 0.212338 & 0.424675 & 0.787662 \tabularnewline
253 & 0.194096 & 0.388192 & 0.805904 \tabularnewline
254 & 0.258986 & 0.517971 & 0.741014 \tabularnewline
255 & 0.248279 & 0.496558 & 0.751721 \tabularnewline
256 & 0.500868 & 0.998265 & 0.499132 \tabularnewline
257 & 0.453196 & 0.906393 & 0.546804 \tabularnewline
258 & 0.461761 & 0.923522 & 0.538239 \tabularnewline
259 & 0.440694 & 0.881387 & 0.559306 \tabularnewline
260 & 0.463087 & 0.926174 & 0.536913 \tabularnewline
261 & 0.403509 & 0.807019 & 0.596491 \tabularnewline
262 & 0.354189 & 0.708378 & 0.645811 \tabularnewline
263 & 0.31661 & 0.63322 & 0.68339 \tabularnewline
264 & 0.259567 & 0.519134 & 0.740433 \tabularnewline
265 & 0.257081 & 0.514161 & 0.742919 \tabularnewline
266 & 0.368586 & 0.737172 & 0.631414 \tabularnewline
267 & 0.613751 & 0.772498 & 0.386249 \tabularnewline
268 & 0.552044 & 0.895912 & 0.447956 \tabularnewline
269 & 0.503051 & 0.993898 & 0.496949 \tabularnewline
270 & 0.513661 & 0.972677 & 0.486339 \tabularnewline
271 & 0.441942 & 0.883884 & 0.558058 \tabularnewline
272 & 0.41864 & 0.837279 & 0.58136 \tabularnewline
273 & 0.364865 & 0.729729 & 0.635135 \tabularnewline
274 & 0.288947 & 0.577894 & 0.711053 \tabularnewline
275 & 0.425595 & 0.85119 & 0.574405 \tabularnewline
276 & 0.376777 & 0.753555 & 0.623223 \tabularnewline
277 & 0.266606 & 0.533211 & 0.733394 \tabularnewline
278 & 0.171092 & 0.342185 & 0.828908 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231355&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]0.814086[/C][C]0.371827[/C][C]0.185914[/C][/ROW]
[ROW][C]11[/C][C]0.761229[/C][C]0.477541[/C][C]0.238771[/C][/ROW]
[ROW][C]12[/C][C]0.784145[/C][C]0.431711[/C][C]0.215855[/C][/ROW]
[ROW][C]13[/C][C]0.719161[/C][C]0.561677[/C][C]0.280839[/C][/ROW]
[ROW][C]14[/C][C]0.712412[/C][C]0.575176[/C][C]0.287588[/C][/ROW]
[ROW][C]15[/C][C]0.669045[/C][C]0.661911[/C][C]0.330955[/C][/ROW]
[ROW][C]16[/C][C]0.6126[/C][C]0.774799[/C][C]0.3874[/C][/ROW]
[ROW][C]17[/C][C]0.524823[/C][C]0.950354[/C][C]0.475177[/C][/ROW]
[ROW][C]18[/C][C]0.855741[/C][C]0.288518[/C][C]0.144259[/C][/ROW]
[ROW][C]19[/C][C]0.849999[/C][C]0.300002[/C][C]0.150001[/C][/ROW]
[ROW][C]20[/C][C]0.802003[/C][C]0.395994[/C][C]0.197997[/C][/ROW]
[ROW][C]21[/C][C]0.745898[/C][C]0.508204[/C][C]0.254102[/C][/ROW]
[ROW][C]22[/C][C]0.684099[/C][C]0.631802[/C][C]0.315901[/C][/ROW]
[ROW][C]23[/C][C]0.703792[/C][C]0.592416[/C][C]0.296208[/C][/ROW]
[ROW][C]24[/C][C]0.640616[/C][C]0.718769[/C][C]0.359384[/C][/ROW]
[ROW][C]25[/C][C]0.577483[/C][C]0.845034[/C][C]0.422517[/C][/ROW]
[ROW][C]26[/C][C]0.51084[/C][C]0.97832[/C][C]0.48916[/C][/ROW]
[ROW][C]27[/C][C]0.447186[/C][C]0.894372[/C][C]0.552814[/C][/ROW]
[ROW][C]28[/C][C]0.430403[/C][C]0.860805[/C][C]0.569597[/C][/ROW]
[ROW][C]29[/C][C]0.369874[/C][C]0.739748[/C][C]0.630126[/C][/ROW]
[ROW][C]30[/C][C]0.35628[/C][C]0.71256[/C][C]0.64372[/C][/ROW]
[ROW][C]31[/C][C]0.300857[/C][C]0.601714[/C][C]0.699143[/C][/ROW]
[ROW][C]32[/C][C]0.285203[/C][C]0.570406[/C][C]0.714797[/C][/ROW]
[ROW][C]33[/C][C]0.25184[/C][C]0.50368[/C][C]0.74816[/C][/ROW]
[ROW][C]34[/C][C]0.20705[/C][C]0.414099[/C][C]0.79295[/C][/ROW]
[ROW][C]35[/C][C]0.205932[/C][C]0.411864[/C][C]0.794068[/C][/ROW]
[ROW][C]36[/C][C]0.294192[/C][C]0.588383[/C][C]0.705808[/C][/ROW]
[ROW][C]37[/C][C]0.381723[/C][C]0.763446[/C][C]0.618277[/C][/ROW]
[ROW][C]38[/C][C]0.38399[/C][C]0.76798[/C][C]0.61601[/C][/ROW]
[ROW][C]39[/C][C]0.412445[/C][C]0.824889[/C][C]0.587555[/C][/ROW]
[ROW][C]40[/C][C]0.391694[/C][C]0.783387[/C][C]0.608306[/C][/ROW]
[ROW][C]41[/C][C]0.357992[/C][C]0.715983[/C][C]0.642008[/C][/ROW]
[ROW][C]42[/C][C]0.344928[/C][C]0.689855[/C][C]0.655072[/C][/ROW]
[ROW][C]43[/C][C]0.357908[/C][C]0.715816[/C][C]0.642092[/C][/ROW]
[ROW][C]44[/C][C]0.317195[/C][C]0.634391[/C][C]0.682805[/C][/ROW]
[ROW][C]45[/C][C]0.281112[/C][C]0.562224[/C][C]0.718888[/C][/ROW]
[ROW][C]46[/C][C]0.516421[/C][C]0.967158[/C][C]0.483579[/C][/ROW]
[ROW][C]47[/C][C]0.567874[/C][C]0.864252[/C][C]0.432126[/C][/ROW]
[ROW][C]48[/C][C]0.521401[/C][C]0.957197[/C][C]0.478599[/C][/ROW]
[ROW][C]49[/C][C]0.477155[/C][C]0.954311[/C][C]0.522845[/C][/ROW]
[ROW][C]50[/C][C]0.480679[/C][C]0.961358[/C][C]0.519321[/C][/ROW]
[ROW][C]51[/C][C]0.438574[/C][C]0.877148[/C][C]0.561426[/C][/ROW]
[ROW][C]52[/C][C]0.393325[/C][C]0.78665[/C][C]0.606675[/C][/ROW]
[ROW][C]53[/C][C]0.446961[/C][C]0.893923[/C][C]0.553039[/C][/ROW]
[ROW][C]54[/C][C]0.404471[/C][C]0.808943[/C][C]0.595529[/C][/ROW]
[ROW][C]55[/C][C]0.406475[/C][C]0.81295[/C][C]0.593525[/C][/ROW]
[ROW][C]56[/C][C]0.390813[/C][C]0.781625[/C][C]0.609187[/C][/ROW]
[ROW][C]57[/C][C]0.349517[/C][C]0.699033[/C][C]0.650483[/C][/ROW]
[ROW][C]58[/C][C]0.326712[/C][C]0.653424[/C][C]0.673288[/C][/ROW]
[ROW][C]59[/C][C]0.287653[/C][C]0.575307[/C][C]0.712347[/C][/ROW]
[ROW][C]60[/C][C]0.289704[/C][C]0.579409[/C][C]0.710296[/C][/ROW]
[ROW][C]61[/C][C]0.260293[/C][C]0.520586[/C][C]0.739707[/C][/ROW]
[ROW][C]62[/C][C]0.226681[/C][C]0.453362[/C][C]0.773319[/C][/ROW]
[ROW][C]63[/C][C]0.195969[/C][C]0.391938[/C][C]0.804031[/C][/ROW]
[ROW][C]64[/C][C]0.169448[/C][C]0.338896[/C][C]0.830552[/C][/ROW]
[ROW][C]65[/C][C]0.146351[/C][C]0.292702[/C][C]0.853649[/C][/ROW]
[ROW][C]66[/C][C]0.134139[/C][C]0.268277[/C][C]0.865861[/C][/ROW]
[ROW][C]67[/C][C]0.127504[/C][C]0.255008[/C][C]0.872496[/C][/ROW]
[ROW][C]68[/C][C]0.218035[/C][C]0.436071[/C][C]0.781965[/C][/ROW]
[ROW][C]69[/C][C]0.342189[/C][C]0.684377[/C][C]0.657811[/C][/ROW]
[ROW][C]70[/C][C]0.306236[/C][C]0.612472[/C][C]0.693764[/C][/ROW]
[ROW][C]71[/C][C]0.390194[/C][C]0.780388[/C][C]0.609806[/C][/ROW]
[ROW][C]72[/C][C]0.356334[/C][C]0.712668[/C][C]0.643666[/C][/ROW]
[ROW][C]73[/C][C]0.338885[/C][C]0.67777[/C][C]0.661115[/C][/ROW]
[ROW][C]74[/C][C]0.311393[/C][C]0.622786[/C][C]0.688607[/C][/ROW]
[ROW][C]75[/C][C]0.280709[/C][C]0.561418[/C][C]0.719291[/C][/ROW]
[ROW][C]76[/C][C]0.335688[/C][C]0.671375[/C][C]0.664312[/C][/ROW]
[ROW][C]77[/C][C]0.30357[/C][C]0.60714[/C][C]0.69643[/C][/ROW]
[ROW][C]78[/C][C]0.281518[/C][C]0.563036[/C][C]0.718482[/C][/ROW]
[ROW][C]79[/C][C]0.285127[/C][C]0.570254[/C][C]0.714873[/C][/ROW]
[ROW][C]80[/C][C]0.257586[/C][C]0.515173[/C][C]0.742414[/C][/ROW]
[ROW][C]81[/C][C]0.231165[/C][C]0.46233[/C][C]0.768835[/C][/ROW]
[ROW][C]82[/C][C]0.203898[/C][C]0.407796[/C][C]0.796102[/C][/ROW]
[ROW][C]83[/C][C]0.18408[/C][C]0.368159[/C][C]0.81592[/C][/ROW]
[ROW][C]84[/C][C]0.159801[/C][C]0.319602[/C][C]0.840199[/C][/ROW]
[ROW][C]85[/C][C]0.156752[/C][C]0.313504[/C][C]0.843248[/C][/ROW]
[ROW][C]86[/C][C]0.134876[/C][C]0.269751[/C][C]0.865124[/C][/ROW]
[ROW][C]87[/C][C]0.116909[/C][C]0.233817[/C][C]0.883091[/C][/ROW]
[ROW][C]88[/C][C]0.103936[/C][C]0.207871[/C][C]0.896064[/C][/ROW]
[ROW][C]89[/C][C]0.0879826[/C][C]0.175965[/C][C]0.912017[/C][/ROW]
[ROW][C]90[/C][C]0.083526[/C][C]0.167052[/C][C]0.916474[/C][/ROW]
[ROW][C]91[/C][C]0.0715943[/C][C]0.143189[/C][C]0.928406[/C][/ROW]
[ROW][C]92[/C][C]0.0609638[/C][C]0.121928[/C][C]0.939036[/C][/ROW]
[ROW][C]93[/C][C]0.051702[/C][C]0.103404[/C][C]0.948298[/C][/ROW]
[ROW][C]94[/C][C]0.0532409[/C][C]0.106482[/C][C]0.946759[/C][/ROW]
[ROW][C]95[/C][C]0.0467348[/C][C]0.0934695[/C][C]0.953265[/C][/ROW]
[ROW][C]96[/C][C]0.0385127[/C][C]0.0770254[/C][C]0.961487[/C][/ROW]
[ROW][C]97[/C][C]0.0417363[/C][C]0.0834725[/C][C]0.958264[/C][/ROW]
[ROW][C]98[/C][C]0.034172[/C][C]0.0683439[/C][C]0.965828[/C][/ROW]
[ROW][C]99[/C][C]0.0277503[/C][C]0.0555006[/C][C]0.97225[/C][/ROW]
[ROW][C]100[/C][C]0.0248783[/C][C]0.0497566[/C][C]0.975122[/C][/ROW]
[ROW][C]101[/C][C]0.0214931[/C][C]0.0429863[/C][C]0.978507[/C][/ROW]
[ROW][C]102[/C][C]0.0254159[/C][C]0.0508317[/C][C]0.974584[/C][/ROW]
[ROW][C]103[/C][C]0.0213231[/C][C]0.0426463[/C][C]0.978677[/C][/ROW]
[ROW][C]104[/C][C]0.0188441[/C][C]0.0376882[/C][C]0.981156[/C][/ROW]
[ROW][C]105[/C][C]0.0239095[/C][C]0.0478189[/C][C]0.976091[/C][/ROW]
[ROW][C]106[/C][C]0.0204779[/C][C]0.0409558[/C][C]0.979522[/C][/ROW]
[ROW][C]107[/C][C]0.0163939[/C][C]0.0327878[/C][C]0.983606[/C][/ROW]
[ROW][C]108[/C][C]0.0149252[/C][C]0.0298504[/C][C]0.985075[/C][/ROW]
[ROW][C]109[/C][C]0.0127397[/C][C]0.0254794[/C][C]0.98726[/C][/ROW]
[ROW][C]110[/C][C]0.0105052[/C][C]0.0210103[/C][C]0.989495[/C][/ROW]
[ROW][C]111[/C][C]0.00826461[/C][C]0.0165292[/C][C]0.991735[/C][/ROW]
[ROW][C]112[/C][C]0.00971528[/C][C]0.0194306[/C][C]0.990285[/C][/ROW]
[ROW][C]113[/C][C]0.0136349[/C][C]0.0272698[/C][C]0.986365[/C][/ROW]
[ROW][C]114[/C][C]0.0131766[/C][C]0.0263531[/C][C]0.986823[/C][/ROW]
[ROW][C]115[/C][C]0.0139943[/C][C]0.0279887[/C][C]0.986006[/C][/ROW]
[ROW][C]116[/C][C]0.0117348[/C][C]0.0234697[/C][C]0.988265[/C][/ROW]
[ROW][C]117[/C][C]0.0116259[/C][C]0.0232519[/C][C]0.988374[/C][/ROW]
[ROW][C]118[/C][C]0.00922113[/C][C]0.0184423[/C][C]0.990779[/C][/ROW]
[ROW][C]119[/C][C]0.00861133[/C][C]0.0172227[/C][C]0.991389[/C][/ROW]
[ROW][C]120[/C][C]0.00692822[/C][C]0.0138564[/C][C]0.993072[/C][/ROW]
[ROW][C]121[/C][C]0.0099964[/C][C]0.0199928[/C][C]0.990004[/C][/ROW]
[ROW][C]122[/C][C]0.00850809[/C][C]0.0170162[/C][C]0.991492[/C][/ROW]
[ROW][C]123[/C][C]0.00758309[/C][C]0.0151662[/C][C]0.992417[/C][/ROW]
[ROW][C]124[/C][C]0.00632385[/C][C]0.0126477[/C][C]0.993676[/C][/ROW]
[ROW][C]125[/C][C]0.00501306[/C][C]0.0100261[/C][C]0.994987[/C][/ROW]
[ROW][C]126[/C][C]0.0042004[/C][C]0.00840081[/C][C]0.9958[/C][/ROW]
[ROW][C]127[/C][C]0.00347047[/C][C]0.00694095[/C][C]0.99653[/C][/ROW]
[ROW][C]128[/C][C]0.00535824[/C][C]0.0107165[/C][C]0.994642[/C][/ROW]
[ROW][C]129[/C][C]0.00568699[/C][C]0.011374[/C][C]0.994313[/C][/ROW]
[ROW][C]130[/C][C]0.012427[/C][C]0.0248541[/C][C]0.987573[/C][/ROW]
[ROW][C]131[/C][C]0.0137815[/C][C]0.027563[/C][C]0.986218[/C][/ROW]
[ROW][C]132[/C][C]0.0148181[/C][C]0.0296362[/C][C]0.985182[/C][/ROW]
[ROW][C]133[/C][C]0.0146418[/C][C]0.0292835[/C][C]0.985358[/C][/ROW]
[ROW][C]134[/C][C]0.0118716[/C][C]0.0237433[/C][C]0.988128[/C][/ROW]
[ROW][C]135[/C][C]0.00985585[/C][C]0.0197117[/C][C]0.990144[/C][/ROW]
[ROW][C]136[/C][C]0.00782947[/C][C]0.0156589[/C][C]0.992171[/C][/ROW]
[ROW][C]137[/C][C]0.0104367[/C][C]0.0208734[/C][C]0.989563[/C][/ROW]
[ROW][C]138[/C][C]0.00933576[/C][C]0.0186715[/C][C]0.990664[/C][/ROW]
[ROW][C]139[/C][C]0.0107309[/C][C]0.0214618[/C][C]0.989269[/C][/ROW]
[ROW][C]140[/C][C]0.0147996[/C][C]0.0295992[/C][C]0.9852[/C][/ROW]
[ROW][C]141[/C][C]0.0137372[/C][C]0.0274744[/C][C]0.986263[/C][/ROW]
[ROW][C]142[/C][C]0.0113687[/C][C]0.0227375[/C][C]0.988631[/C][/ROW]
[ROW][C]143[/C][C]0.0113901[/C][C]0.0227801[/C][C]0.98861[/C][/ROW]
[ROW][C]144[/C][C]0.021437[/C][C]0.0428741[/C][C]0.978563[/C][/ROW]
[ROW][C]145[/C][C]0.0230378[/C][C]0.0460756[/C][C]0.976962[/C][/ROW]
[ROW][C]146[/C][C]0.0261028[/C][C]0.0522055[/C][C]0.973897[/C][/ROW]
[ROW][C]147[/C][C]0.0225779[/C][C]0.0451557[/C][C]0.977422[/C][/ROW]
[ROW][C]148[/C][C]0.0183778[/C][C]0.0367556[/C][C]0.981622[/C][/ROW]
[ROW][C]149[/C][C]0.027091[/C][C]0.054182[/C][C]0.972909[/C][/ROW]
[ROW][C]150[/C][C]0.027386[/C][C]0.0547721[/C][C]0.972614[/C][/ROW]
[ROW][C]151[/C][C]0.0274957[/C][C]0.0549913[/C][C]0.972504[/C][/ROW]
[ROW][C]152[/C][C]0.0508732[/C][C]0.101746[/C][C]0.949127[/C][/ROW]
[ROW][C]153[/C][C]0.0452335[/C][C]0.0904671[/C][C]0.954766[/C][/ROW]
[ROW][C]154[/C][C]0.0566435[/C][C]0.113287[/C][C]0.943356[/C][/ROW]
[ROW][C]155[/C][C]0.0497613[/C][C]0.0995226[/C][C]0.950239[/C][/ROW]
[ROW][C]156[/C][C]0.042769[/C][C]0.0855381[/C][C]0.957231[/C][/ROW]
[ROW][C]157[/C][C]0.0406571[/C][C]0.0813141[/C][C]0.959343[/C][/ROW]
[ROW][C]158[/C][C]0.0341825[/C][C]0.068365[/C][C]0.965818[/C][/ROW]
[ROW][C]159[/C][C]0.0288722[/C][C]0.0577443[/C][C]0.971128[/C][/ROW]
[ROW][C]160[/C][C]0.0246136[/C][C]0.0492273[/C][C]0.975386[/C][/ROW]
[ROW][C]161[/C][C]0.020641[/C][C]0.041282[/C][C]0.979359[/C][/ROW]
[ROW][C]162[/C][C]0.0181205[/C][C]0.036241[/C][C]0.981879[/C][/ROW]
[ROW][C]163[/C][C]0.0167382[/C][C]0.0334764[/C][C]0.983262[/C][/ROW]
[ROW][C]164[/C][C]0.0134701[/C][C]0.0269401[/C][C]0.98653[/C][/ROW]
[ROW][C]165[/C][C]0.0167835[/C][C]0.033567[/C][C]0.983216[/C][/ROW]
[ROW][C]166[/C][C]0.0166328[/C][C]0.0332655[/C][C]0.983367[/C][/ROW]
[ROW][C]167[/C][C]0.0170509[/C][C]0.0341017[/C][C]0.982949[/C][/ROW]
[ROW][C]168[/C][C]0.0171204[/C][C]0.0342409[/C][C]0.98288[/C][/ROW]
[ROW][C]169[/C][C]0.0140273[/C][C]0.0280545[/C][C]0.985973[/C][/ROW]
[ROW][C]170[/C][C]0.0133267[/C][C]0.0266534[/C][C]0.986673[/C][/ROW]
[ROW][C]171[/C][C]0.0131586[/C][C]0.0263171[/C][C]0.986841[/C][/ROW]
[ROW][C]172[/C][C]0.0158147[/C][C]0.0316294[/C][C]0.984185[/C][/ROW]
[ROW][C]173[/C][C]0.0136203[/C][C]0.0272407[/C][C]0.98638[/C][/ROW]
[ROW][C]174[/C][C]0.0108808[/C][C]0.0217616[/C][C]0.989119[/C][/ROW]
[ROW][C]175[/C][C]0.00864152[/C][C]0.017283[/C][C]0.991358[/C][/ROW]
[ROW][C]176[/C][C]0.00700676[/C][C]0.0140135[/C][C]0.992993[/C][/ROW]
[ROW][C]177[/C][C]0.00604719[/C][C]0.0120944[/C][C]0.993953[/C][/ROW]
[ROW][C]178[/C][C]0.00503913[/C][C]0.0100783[/C][C]0.994961[/C][/ROW]
[ROW][C]179[/C][C]0.00401747[/C][C]0.00803495[/C][C]0.995983[/C][/ROW]
[ROW][C]180[/C][C]0.00451027[/C][C]0.00902055[/C][C]0.99549[/C][/ROW]
[ROW][C]181[/C][C]0.0035085[/C][C]0.007017[/C][C]0.996492[/C][/ROW]
[ROW][C]182[/C][C]0.0275601[/C][C]0.0551202[/C][C]0.97244[/C][/ROW]
[ROW][C]183[/C][C]0.0244928[/C][C]0.0489856[/C][C]0.975507[/C][/ROW]
[ROW][C]184[/C][C]0.0308406[/C][C]0.0616812[/C][C]0.969159[/C][/ROW]
[ROW][C]185[/C][C]0.0256601[/C][C]0.0513202[/C][C]0.97434[/C][/ROW]
[ROW][C]186[/C][C]0.020985[/C][C]0.0419701[/C][C]0.979015[/C][/ROW]
[ROW][C]187[/C][C]0.0177005[/C][C]0.035401[/C][C]0.9823[/C][/ROW]
[ROW][C]188[/C][C]0.0155464[/C][C]0.0310929[/C][C]0.984454[/C][/ROW]
[ROW][C]189[/C][C]0.0126041[/C][C]0.0252083[/C][C]0.987396[/C][/ROW]
[ROW][C]190[/C][C]0.0178487[/C][C]0.0356974[/C][C]0.982151[/C][/ROW]
[ROW][C]191[/C][C]0.016361[/C][C]0.0327221[/C][C]0.983639[/C][/ROW]
[ROW][C]192[/C][C]0.0133226[/C][C]0.0266452[/C][C]0.986677[/C][/ROW]
[ROW][C]193[/C][C]0.0105818[/C][C]0.0211636[/C][C]0.989418[/C][/ROW]
[ROW][C]194[/C][C]0.0160191[/C][C]0.0320383[/C][C]0.983981[/C][/ROW]
[ROW][C]195[/C][C]0.0132084[/C][C]0.0264168[/C][C]0.986792[/C][/ROW]
[ROW][C]196[/C][C]0.0122595[/C][C]0.0245191[/C][C]0.98774[/C][/ROW]
[ROW][C]197[/C][C]0.0120194[/C][C]0.0240389[/C][C]0.987981[/C][/ROW]
[ROW][C]198[/C][C]0.0100451[/C][C]0.0200903[/C][C]0.989955[/C][/ROW]
[ROW][C]199[/C][C]0.00992672[/C][C]0.0198534[/C][C]0.990073[/C][/ROW]
[ROW][C]200[/C][C]0.0122626[/C][C]0.0245252[/C][C]0.987737[/C][/ROW]
[ROW][C]201[/C][C]0.0147089[/C][C]0.0294179[/C][C]0.985291[/C][/ROW]
[ROW][C]202[/C][C]0.0116919[/C][C]0.0233838[/C][C]0.988308[/C][/ROW]
[ROW][C]203[/C][C]0.0101583[/C][C]0.0203165[/C][C]0.989842[/C][/ROW]
[ROW][C]204[/C][C]0.00818288[/C][C]0.0163658[/C][C]0.991817[/C][/ROW]
[ROW][C]205[/C][C]0.00955556[/C][C]0.0191111[/C][C]0.990444[/C][/ROW]
[ROW][C]206[/C][C]0.00855842[/C][C]0.0171168[/C][C]0.991442[/C][/ROW]
[ROW][C]207[/C][C]0.0112262[/C][C]0.0224524[/C][C]0.988774[/C][/ROW]
[ROW][C]208[/C][C]0.0255248[/C][C]0.0510496[/C][C]0.974475[/C][/ROW]
[ROW][C]209[/C][C]0.0208421[/C][C]0.0416843[/C][C]0.979158[/C][/ROW]
[ROW][C]210[/C][C]0.032617[/C][C]0.0652339[/C][C]0.967383[/C][/ROW]
[ROW][C]211[/C][C]0.027451[/C][C]0.0549019[/C][C]0.972549[/C][/ROW]
[ROW][C]212[/C][C]0.025254[/C][C]0.0505081[/C][C]0.974746[/C][/ROW]
[ROW][C]213[/C][C]0.0270897[/C][C]0.0541793[/C][C]0.97291[/C][/ROW]
[ROW][C]214[/C][C]0.0217158[/C][C]0.0434315[/C][C]0.978284[/C][/ROW]
[ROW][C]215[/C][C]0.0185801[/C][C]0.0371603[/C][C]0.98142[/C][/ROW]
[ROW][C]216[/C][C]0.0154426[/C][C]0.0308853[/C][C]0.984557[/C][/ROW]
[ROW][C]217[/C][C]0.014542[/C][C]0.029084[/C][C]0.985458[/C][/ROW]
[ROW][C]218[/C][C]0.0113823[/C][C]0.0227645[/C][C]0.988618[/C][/ROW]
[ROW][C]219[/C][C]0.00883245[/C][C]0.0176649[/C][C]0.991168[/C][/ROW]
[ROW][C]220[/C][C]0.00694592[/C][C]0.0138918[/C][C]0.993054[/C][/ROW]
[ROW][C]221[/C][C]0.0110796[/C][C]0.0221592[/C][C]0.98892[/C][/ROW]
[ROW][C]222[/C][C]0.00860518[/C][C]0.0172104[/C][C]0.991395[/C][/ROW]
[ROW][C]223[/C][C]0.00744669[/C][C]0.0148934[/C][C]0.992553[/C][/ROW]
[ROW][C]224[/C][C]0.0063398[/C][C]0.0126796[/C][C]0.99366[/C][/ROW]
[ROW][C]225[/C][C]0.00494018[/C][C]0.00988036[/C][C]0.99506[/C][/ROW]
[ROW][C]226[/C][C]0.00629458[/C][C]0.0125892[/C][C]0.993705[/C][/ROW]
[ROW][C]227[/C][C]0.0142549[/C][C]0.0285098[/C][C]0.985745[/C][/ROW]
[ROW][C]228[/C][C]0.0786457[/C][C]0.157291[/C][C]0.921354[/C][/ROW]
[ROW][C]229[/C][C]0.0710467[/C][C]0.142093[/C][C]0.928953[/C][/ROW]
[ROW][C]230[/C][C]0.0584234[/C][C]0.116847[/C][C]0.941577[/C][/ROW]
[ROW][C]231[/C][C]0.0590908[/C][C]0.118182[/C][C]0.940909[/C][/ROW]
[ROW][C]232[/C][C]0.242419[/C][C]0.484837[/C][C]0.757581[/C][/ROW]
[ROW][C]233[/C][C]0.22315[/C][C]0.4463[/C][C]0.77685[/C][/ROW]
[ROW][C]234[/C][C]0.203024[/C][C]0.406049[/C][C]0.796976[/C][/ROW]
[ROW][C]235[/C][C]0.180126[/C][C]0.360252[/C][C]0.819874[/C][/ROW]
[ROW][C]236[/C][C]0.15365[/C][C]0.307301[/C][C]0.84635[/C][/ROW]
[ROW][C]237[/C][C]0.184217[/C][C]0.368433[/C][C]0.815783[/C][/ROW]
[ROW][C]238[/C][C]0.236459[/C][C]0.472918[/C][C]0.763541[/C][/ROW]
[ROW][C]239[/C][C]0.298129[/C][C]0.596258[/C][C]0.701871[/C][/ROW]
[ROW][C]240[/C][C]0.25894[/C][C]0.517881[/C][C]0.74106[/C][/ROW]
[ROW][C]241[/C][C]0.243732[/C][C]0.487465[/C][C]0.756268[/C][/ROW]
[ROW][C]242[/C][C]0.278934[/C][C]0.557867[/C][C]0.721066[/C][/ROW]
[ROW][C]243[/C][C]0.267275[/C][C]0.534549[/C][C]0.732725[/C][/ROW]
[ROW][C]244[/C][C]0.242977[/C][C]0.485955[/C][C]0.757023[/C][/ROW]
[ROW][C]245[/C][C]0.21409[/C][C]0.42818[/C][C]0.78591[/C][/ROW]
[ROW][C]246[/C][C]0.183489[/C][C]0.366978[/C][C]0.816511[/C][/ROW]
[ROW][C]247[/C][C]0.18216[/C][C]0.36432[/C][C]0.81784[/C][/ROW]
[ROW][C]248[/C][C]0.278669[/C][C]0.557339[/C][C]0.721331[/C][/ROW]
[ROW][C]249[/C][C]0.262232[/C][C]0.524465[/C][C]0.737768[/C][/ROW]
[ROW][C]250[/C][C]0.222657[/C][C]0.445313[/C][C]0.777343[/C][/ROW]
[ROW][C]251[/C][C]0.189286[/C][C]0.378573[/C][C]0.810714[/C][/ROW]
[ROW][C]252[/C][C]0.212338[/C][C]0.424675[/C][C]0.787662[/C][/ROW]
[ROW][C]253[/C][C]0.194096[/C][C]0.388192[/C][C]0.805904[/C][/ROW]
[ROW][C]254[/C][C]0.258986[/C][C]0.517971[/C][C]0.741014[/C][/ROW]
[ROW][C]255[/C][C]0.248279[/C][C]0.496558[/C][C]0.751721[/C][/ROW]
[ROW][C]256[/C][C]0.500868[/C][C]0.998265[/C][C]0.499132[/C][/ROW]
[ROW][C]257[/C][C]0.453196[/C][C]0.906393[/C][C]0.546804[/C][/ROW]
[ROW][C]258[/C][C]0.461761[/C][C]0.923522[/C][C]0.538239[/C][/ROW]
[ROW][C]259[/C][C]0.440694[/C][C]0.881387[/C][C]0.559306[/C][/ROW]
[ROW][C]260[/C][C]0.463087[/C][C]0.926174[/C][C]0.536913[/C][/ROW]
[ROW][C]261[/C][C]0.403509[/C][C]0.807019[/C][C]0.596491[/C][/ROW]
[ROW][C]262[/C][C]0.354189[/C][C]0.708378[/C][C]0.645811[/C][/ROW]
[ROW][C]263[/C][C]0.31661[/C][C]0.63322[/C][C]0.68339[/C][/ROW]
[ROW][C]264[/C][C]0.259567[/C][C]0.519134[/C][C]0.740433[/C][/ROW]
[ROW][C]265[/C][C]0.257081[/C][C]0.514161[/C][C]0.742919[/C][/ROW]
[ROW][C]266[/C][C]0.368586[/C][C]0.737172[/C][C]0.631414[/C][/ROW]
[ROW][C]267[/C][C]0.613751[/C][C]0.772498[/C][C]0.386249[/C][/ROW]
[ROW][C]268[/C][C]0.552044[/C][C]0.895912[/C][C]0.447956[/C][/ROW]
[ROW][C]269[/C][C]0.503051[/C][C]0.993898[/C][C]0.496949[/C][/ROW]
[ROW][C]270[/C][C]0.513661[/C][C]0.972677[/C][C]0.486339[/C][/ROW]
[ROW][C]271[/C][C]0.441942[/C][C]0.883884[/C][C]0.558058[/C][/ROW]
[ROW][C]272[/C][C]0.41864[/C][C]0.837279[/C][C]0.58136[/C][/ROW]
[ROW][C]273[/C][C]0.364865[/C][C]0.729729[/C][C]0.635135[/C][/ROW]
[ROW][C]274[/C][C]0.288947[/C][C]0.577894[/C][C]0.711053[/C][/ROW]
[ROW][C]275[/C][C]0.425595[/C][C]0.85119[/C][C]0.574405[/C][/ROW]
[ROW][C]276[/C][C]0.376777[/C][C]0.753555[/C][C]0.623223[/C][/ROW]
[ROW][C]277[/C][C]0.266606[/C][C]0.533211[/C][C]0.733394[/C][/ROW]
[ROW][C]278[/C][C]0.171092[/C][C]0.342185[/C][C]0.828908[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231355&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231355&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
100.8140860.3718270.185914
110.7612290.4775410.238771
120.7841450.4317110.215855
130.7191610.5616770.280839
140.7124120.5751760.287588
150.6690450.6619110.330955
160.61260.7747990.3874
170.5248230.9503540.475177
180.8557410.2885180.144259
190.8499990.3000020.150001
200.8020030.3959940.197997
210.7458980.5082040.254102
220.6840990.6318020.315901
230.7037920.5924160.296208
240.6406160.7187690.359384
250.5774830.8450340.422517
260.510840.978320.48916
270.4471860.8943720.552814
280.4304030.8608050.569597
290.3698740.7397480.630126
300.356280.712560.64372
310.3008570.6017140.699143
320.2852030.5704060.714797
330.251840.503680.74816
340.207050.4140990.79295
350.2059320.4118640.794068
360.2941920.5883830.705808
370.3817230.7634460.618277
380.383990.767980.61601
390.4124450.8248890.587555
400.3916940.7833870.608306
410.3579920.7159830.642008
420.3449280.6898550.655072
430.3579080.7158160.642092
440.3171950.6343910.682805
450.2811120.5622240.718888
460.5164210.9671580.483579
470.5678740.8642520.432126
480.5214010.9571970.478599
490.4771550.9543110.522845
500.4806790.9613580.519321
510.4385740.8771480.561426
520.3933250.786650.606675
530.4469610.8939230.553039
540.4044710.8089430.595529
550.4064750.812950.593525
560.3908130.7816250.609187
570.3495170.6990330.650483
580.3267120.6534240.673288
590.2876530.5753070.712347
600.2897040.5794090.710296
610.2602930.5205860.739707
620.2266810.4533620.773319
630.1959690.3919380.804031
640.1694480.3388960.830552
650.1463510.2927020.853649
660.1341390.2682770.865861
670.1275040.2550080.872496
680.2180350.4360710.781965
690.3421890.6843770.657811
700.3062360.6124720.693764
710.3901940.7803880.609806
720.3563340.7126680.643666
730.3388850.677770.661115
740.3113930.6227860.688607
750.2807090.5614180.719291
760.3356880.6713750.664312
770.303570.607140.69643
780.2815180.5630360.718482
790.2851270.5702540.714873
800.2575860.5151730.742414
810.2311650.462330.768835
820.2038980.4077960.796102
830.184080.3681590.81592
840.1598010.3196020.840199
850.1567520.3135040.843248
860.1348760.2697510.865124
870.1169090.2338170.883091
880.1039360.2078710.896064
890.08798260.1759650.912017
900.0835260.1670520.916474
910.07159430.1431890.928406
920.06096380.1219280.939036
930.0517020.1034040.948298
940.05324090.1064820.946759
950.04673480.09346950.953265
960.03851270.07702540.961487
970.04173630.08347250.958264
980.0341720.06834390.965828
990.02775030.05550060.97225
1000.02487830.04975660.975122
1010.02149310.04298630.978507
1020.02541590.05083170.974584
1030.02132310.04264630.978677
1040.01884410.03768820.981156
1050.02390950.04781890.976091
1060.02047790.04095580.979522
1070.01639390.03278780.983606
1080.01492520.02985040.985075
1090.01273970.02547940.98726
1100.01050520.02101030.989495
1110.008264610.01652920.991735
1120.009715280.01943060.990285
1130.01363490.02726980.986365
1140.01317660.02635310.986823
1150.01399430.02798870.986006
1160.01173480.02346970.988265
1170.01162590.02325190.988374
1180.009221130.01844230.990779
1190.008611330.01722270.991389
1200.006928220.01385640.993072
1210.00999640.01999280.990004
1220.008508090.01701620.991492
1230.007583090.01516620.992417
1240.006323850.01264770.993676
1250.005013060.01002610.994987
1260.00420040.008400810.9958
1270.003470470.006940950.99653
1280.005358240.01071650.994642
1290.005686990.0113740.994313
1300.0124270.02485410.987573
1310.01378150.0275630.986218
1320.01481810.02963620.985182
1330.01464180.02928350.985358
1340.01187160.02374330.988128
1350.009855850.01971170.990144
1360.007829470.01565890.992171
1370.01043670.02087340.989563
1380.009335760.01867150.990664
1390.01073090.02146180.989269
1400.01479960.02959920.9852
1410.01373720.02747440.986263
1420.01136870.02273750.988631
1430.01139010.02278010.98861
1440.0214370.04287410.978563
1450.02303780.04607560.976962
1460.02610280.05220550.973897
1470.02257790.04515570.977422
1480.01837780.03675560.981622
1490.0270910.0541820.972909
1500.0273860.05477210.972614
1510.02749570.05499130.972504
1520.05087320.1017460.949127
1530.04523350.09046710.954766
1540.05664350.1132870.943356
1550.04976130.09952260.950239
1560.0427690.08553810.957231
1570.04065710.08131410.959343
1580.03418250.0683650.965818
1590.02887220.05774430.971128
1600.02461360.04922730.975386
1610.0206410.0412820.979359
1620.01812050.0362410.981879
1630.01673820.03347640.983262
1640.01347010.02694010.98653
1650.01678350.0335670.983216
1660.01663280.03326550.983367
1670.01705090.03410170.982949
1680.01712040.03424090.98288
1690.01402730.02805450.985973
1700.01332670.02665340.986673
1710.01315860.02631710.986841
1720.01581470.03162940.984185
1730.01362030.02724070.98638
1740.01088080.02176160.989119
1750.008641520.0172830.991358
1760.007006760.01401350.992993
1770.006047190.01209440.993953
1780.005039130.01007830.994961
1790.004017470.008034950.995983
1800.004510270.009020550.99549
1810.00350850.0070170.996492
1820.02756010.05512020.97244
1830.02449280.04898560.975507
1840.03084060.06168120.969159
1850.02566010.05132020.97434
1860.0209850.04197010.979015
1870.01770050.0354010.9823
1880.01554640.03109290.984454
1890.01260410.02520830.987396
1900.01784870.03569740.982151
1910.0163610.03272210.983639
1920.01332260.02664520.986677
1930.01058180.02116360.989418
1940.01601910.03203830.983981
1950.01320840.02641680.986792
1960.01225950.02451910.98774
1970.01201940.02403890.987981
1980.01004510.02009030.989955
1990.009926720.01985340.990073
2000.01226260.02452520.987737
2010.01470890.02941790.985291
2020.01169190.02338380.988308
2030.01015830.02031650.989842
2040.008182880.01636580.991817
2050.009555560.01911110.990444
2060.008558420.01711680.991442
2070.01122620.02245240.988774
2080.02552480.05104960.974475
2090.02084210.04168430.979158
2100.0326170.06523390.967383
2110.0274510.05490190.972549
2120.0252540.05050810.974746
2130.02708970.05417930.97291
2140.02171580.04343150.978284
2150.01858010.03716030.98142
2160.01544260.03088530.984557
2170.0145420.0290840.985458
2180.01138230.02276450.988618
2190.008832450.01766490.991168
2200.006945920.01389180.993054
2210.01107960.02215920.98892
2220.008605180.01721040.991395
2230.007446690.01489340.992553
2240.00633980.01267960.99366
2250.004940180.009880360.99506
2260.006294580.01258920.993705
2270.01425490.02850980.985745
2280.07864570.1572910.921354
2290.07104670.1420930.928953
2300.05842340.1168470.941577
2310.05909080.1181820.940909
2320.2424190.4848370.757581
2330.223150.44630.77685
2340.2030240.4060490.796976
2350.1801260.3602520.819874
2360.153650.3073010.84635
2370.1842170.3684330.815783
2380.2364590.4729180.763541
2390.2981290.5962580.701871
2400.258940.5178810.74106
2410.2437320.4874650.756268
2420.2789340.5578670.721066
2430.2672750.5345490.732725
2440.2429770.4859550.757023
2450.214090.428180.78591
2460.1834890.3669780.816511
2470.182160.364320.81784
2480.2786690.5573390.721331
2490.2622320.5244650.737768
2500.2226570.4453130.777343
2510.1892860.3785730.810714
2520.2123380.4246750.787662
2530.1940960.3881920.805904
2540.2589860.5179710.741014
2550.2482790.4965580.751721
2560.5008680.9982650.499132
2570.4531960.9063930.546804
2580.4617610.9235220.538239
2590.4406940.8813870.559306
2600.4630870.9261740.536913
2610.4035090.8070190.596491
2620.3541890.7083780.645811
2630.316610.633220.68339
2640.2595670.5191340.740433
2650.2570810.5141610.742919
2660.3685860.7371720.631414
2670.6137510.7724980.386249
2680.5520440.8959120.447956
2690.5030510.9938980.496949
2700.5136610.9726770.486339
2710.4419420.8838840.558058
2720.418640.8372790.58136
2730.3648650.7297290.635135
2740.2889470.5778940.711053
2750.4255950.851190.574405
2760.3767770.7535550.623223
2770.2666060.5332110.733394
2780.1710920.3421850.828908







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level60.0223048NOK
5% type I error level1070.39777NOK
10% type I error level1310.486989NOK

\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 & 6 & 0.0223048 & NOK \tabularnewline
5% type I error level & 107 & 0.39777 & NOK \tabularnewline
10% type I error level & 131 & 0.486989 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231355&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]6[/C][C]0.0223048[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]107[/C][C]0.39777[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]131[/C][C]0.486989[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231355&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231355&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 level60.0223048NOK
5% type I error level1070.39777NOK
10% type I error level1310.486989NOK



Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 5 ; 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')
}