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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSat, 07 Dec 2013 16:24:58 -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/07/t1386451526ux9xh2y4kqqmqq7.htm/, Retrieved Thu, 18 Apr 2024 20:16:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231417, Retrieved Thu, 18 Apr 2024 20:16:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [WS 10 - Multiple ...] [2013-12-07 21:24:58] [e5eda3cc50f4d89e40bb52bce43bc7fc] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
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0 0 38 33 17 14 16
0 1 34 39 15 10 10
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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
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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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time25 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231417&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231417&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231417&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time25 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 2.06285 + 0.452576Pop[t] + 0.23917Gender[t] -0.0132556Connected[t] + 0.0243562Separate[t] + 0.547343Learning[t] -0.00908693Happiness[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Software[t] =  +  2.06285 +  0.452576Pop[t] +  0.23917Gender[t] -0.0132556Connected[t] +  0.0243562Separate[t] +  0.547343Learning[t] -0.00908693Happiness[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231417&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Software[t] =  +  2.06285 +  0.452576Pop[t] +  0.23917Gender[t] -0.0132556Connected[t] +  0.0243562Separate[t] +  0.547343Learning[t] -0.00908693Happiness[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231417&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231417&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 2.06285 + 0.452576Pop[t] + 0.23917Gender[t] -0.0132556Connected[t] + 0.0243562Separate[t] + 0.547343Learning[t] -0.00908693Happiness[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.062851.166461.7680.07806580.0390329
Pop0.4525760.2341481.9330.05425720.0271286
Gender0.239170.2193321.090.276450.138225
Connected-0.01325560.0310483-0.42690.6697550.334878
Separate0.02435620.03224950.75520.4507360.225368
Learning0.5473430.045374712.062.79257e-271.39628e-27
Happiness-0.009086930.0448204-0.20270.8394840.419742

\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) & 2.06285 & 1.16646 & 1.768 & 0.0780658 & 0.0390329 \tabularnewline
Pop & 0.452576 & 0.234148 & 1.933 & 0.0542572 & 0.0271286 \tabularnewline
Gender & 0.23917 & 0.219332 & 1.09 & 0.27645 & 0.138225 \tabularnewline
Connected & -0.0132556 & 0.0310483 & -0.4269 & 0.669755 & 0.334878 \tabularnewline
Separate & 0.0243562 & 0.0322495 & 0.7552 & 0.450736 & 0.225368 \tabularnewline
Learning & 0.547343 & 0.0453747 & 12.06 & 2.79257e-27 & 1.39628e-27 \tabularnewline
Happiness & -0.00908693 & 0.0448204 & -0.2027 & 0.839484 & 0.419742 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231417&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]2.06285[/C][C]1.16646[/C][C]1.768[/C][C]0.0780658[/C][C]0.0390329[/C][/ROW]
[ROW][C]Pop[/C][C]0.452576[/C][C]0.234148[/C][C]1.933[/C][C]0.0542572[/C][C]0.0271286[/C][/ROW]
[ROW][C]Gender[/C][C]0.23917[/C][C]0.219332[/C][C]1.09[/C][C]0.27645[/C][C]0.138225[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0132556[/C][C]0.0310483[/C][C]-0.4269[/C][C]0.669755[/C][C]0.334878[/C][/ROW]
[ROW][C]Separate[/C][C]0.0243562[/C][C]0.0322495[/C][C]0.7552[/C][C]0.450736[/C][C]0.225368[/C][/ROW]
[ROW][C]Learning[/C][C]0.547343[/C][C]0.0453747[/C][C]12.06[/C][C]2.79257e-27[/C][C]1.39628e-27[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.00908693[/C][C]0.0448204[/C][C]-0.2027[/C][C]0.839484[/C][C]0.419742[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231417&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231417&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)2.062851.166461.7680.07806580.0390329
Pop0.4525760.2341481.9330.05425720.0271286
Gender0.239170.2193321.090.276450.138225
Connected-0.01325560.0310483-0.42690.6697550.334878
Separate0.02435620.03224950.75520.4507360.225368
Learning0.5473430.045374712.062.79257e-271.39628e-27
Happiness-0.009086930.0448204-0.20270.8394840.419742






Multiple Linear Regression - Regression Statistics
Multiple R0.664439
R-squared0.441479
Adjusted R-squared0.429553
F-TEST (value)37.019
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.77967
Sum Squared Residuals889.986

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.664439 \tabularnewline
R-squared & 0.441479 \tabularnewline
Adjusted R-squared & 0.429553 \tabularnewline
F-TEST (value) & 37.019 \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 & 1.77967 \tabularnewline
Sum Squared Residuals & 889.986 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231417&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.664439[/C][/ROW]
[ROW][C]R-squared[/C][C]0.441479[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.429553[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]37.019[/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]1.77967[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]889.986[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231417&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231417&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.664439
R-squared0.441479
Adjusted R-squared0.429553
F-TEST (value)37.019
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.77967
Sum Squared Residuals889.986






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.12491.8751
21111.611-0.610959
31513.5091.49103
4611.0094-5.00937
51310.72252.27749
6109.948880.0511173
71213.265-1.26498
81411.26372.73633
91210.65641.34363
10911.2635-2.26353
111011.3698-1.36978
121211.69040.309648
131211.53080.469191
141111.7753-0.775271
151512.35962.64038
161210.97791.02206
171010.9006-0.900561
181213.9688-1.96881
191112.649-1.64896
201211.72190.278078
211111.4889-0.488935
221211.75630.243744
231313.4355-0.435475
241111.8625-0.862486
251211.92820.07178
261312.21360.786426
271011.5028-1.5028
281411.30132.69872
291211.74210.25789
301010.4313-0.431345
311211.16350.836522
3289.38692-1.38692
331010.5275-0.527514
341211.82630.173721
351210.3311.66898
3678.22305-1.22305
3798.277710.722289
381210.36851.63151
391011.7282-1.72825
401011.4946-1.4946
411011.4256-1.42556
421210.62511.37492
431513.59261.40741
441010.409-0.409003
451010.4594-0.459364
46129.037432.96257
471310.72732.27272
481111.2191-0.219123
491111.806-0.80595
501210.33581.66421
511411.86812.13194
521010.3575-0.357527
53129.363172.63683
541311.87791.1221
5557.6877-2.6877
56610.6431-4.64311
571211.67780.322154
581211.81950.180512
591111.0029-0.00290371
601011.7672-1.76722
6179.29516-2.29516
621211.47920.520808
631411.81392.18609
641110.73170.268267
651211.68010.319858
661312.16660.833368
671412.88211.11791
681112.5185-1.51852
69129.64372.3563
701211.57390.426146
7188.23476-0.234757
721110.78660.213372
731412.96971.03032
741412.72621.2738
751211.36170.638279
76912.1641-3.16411
771311.76831.23166
781111.6983-0.698316
79129.878472.12153
801211.3220.678046
811211.5760.423991
821211.8130.186977
831210.89351.10651
841111.2324-0.232378
851011.7025-1.70248
86910.4881-1.48811
871211.77560.224447
881211.78890.21105
891211.26750.732538
9099.63414-0.634142
911512.24352.7565
921211.91040.0895517
931211.09530.904672
941210.09821.90179
951011.7266-1.72656
961311.76511.23494
97911.676-2.67597
981211.45610.5439
991010.4946-0.494577
1001411.73072.26927
1011111.5259-0.525891
1021513.98011.01995
1031110.88340.116581
1041111.8882-0.888247
105129.798292.20171
1061212.2628-0.262801
1071211.5430.456967
1081111.5573-0.55732
10979.68482-2.68482
1101211.80620.193767
1111411.8052.19503
1121112.5157-1.51573
113109.496810.503191
1141312.51120.488839
1151310.8272.173
116810.8137-2.81375
1171110.15790.842121
1181211.7580.242012
119119.98561.0144
1201311.63161.36843
1211210.17991.82006
1221411.81092.18913
1231311.10631.89371
1241511.78683.21321
1251010.8335-0.833533
1261112.2716-1.27161
127911.2315-2.23149
128119.526221.47378
1291011.5344-1.53437
130118.315322.68468
131811.7467-3.74675
132119.320031.67997
1331210.4771.52299
1341211.10150.89849
13599.69562-0.695617
1361111.0001-0.000140293
137109.130220.869781
13889.55058-1.55058
13998.859620.14038
140811.7797-3.77972
141911.0837-2.0837
1421512.3872.61298
1431111.2859-0.285889
14488.30746-0.307461
1451312.69480.305172
146129.930562.06944
1471211.49470.505256
14899.86456-0.864564
14978.52882-1.52882
1501311.19111.80893
151911.6024-2.60238
152611.889-5.889
153810.66-2.66002
15488.42751-0.427511
155610.2198-4.21985
156911.2315-2.23149
1571111.7227-0.722672
15889.71503-1.71503
159109.362810.637192
16088.72609-0.726095
1611411.52232.47766
1621010.9205-0.920507
16387.848880.151118
1641110.00450.995469
165128.478023.52198
166129.810552.18945
1671211.28180.718156
16858.7956-3.7956
1691211.33810.661895
170108.858181.14182
17177.33448-0.334476
172128.929533.07047
1731110.58320.416838
17489.10166-1.10166
17598.854950.145051
1761010.1636-0.163559
17799.16765-0.167655
1781211.33190.668077
17968.23224-2.23224
1801512.7922.20803
1811210.42151.57853
182126.925735.07427
1831211.3940.605968
1841111.5914-0.591384
18578.97191-1.97191
18678.27632-1.27632
18758.43632-3.43632
1881210.31751.68248
1891211.40280.597164
19039.11342-6.11342
1911111.3968-0.396795
192109.63640.363597
1931210.5991.40096
194911.2367-2.23665
1951211.3960.603955
196910.0193-1.01929
1971211.07160.928416
1981010.0019-0.00190838
19998.23350.766495
200128.841553.15845
201810.7665-2.76655
2021110.8020.197997
2031111.3695-0.369534
2041211.08780.912166
205108.292051.70795
2061010.4807-0.480678
207129.141432.85857
208129.013782.98622
2091110.69880.301239
210810.5639-2.56387
2111211.34810.651917
212109.827110.172895
2131111.8674-0.867416
2141010.1488-0.148757
21589.48089-1.48089
2161210.84861.15144
217129.418172.58183
218109.953380.0466191
2191210.76331.23673
22098.863150.136855
22166.98802-0.988023
222109.921480.0785158
223910.0073-1.00729
22498.3640.636
22598.932790.0672053
22669.57027-3.57027
227107.942612.05739
228611.088-5.08798
2291412.29641.70365
230109.60080.399195
231108.261521.73848
23264.383411.61659
233129.24062.7594
2341211.33930.660722
23577.67656-0.67656
23688.94343-0.943428
237118.94682.0532
23837.73806-4.73806
23969.40908-3.40908
24088.99907-0.999072
241910.0358-1.03582
24297.950441.04956
24389.0389-1.0389
24498.969860.0301433
24578.36451-1.36451
24677.76012-0.760121
24769.10292-3.10292
248911.2834-2.28335
249108.835231.16477
250119.969681.03032
2511211.17580.824201
252810.2515-2.25152
253119.618841.38116
25434.66727-1.66727
2551110.75770.242258
256128.422173.57783
25778.36662-1.36662
25899.99343-0.99343
2591210.52471.47529
260810.227-2.22703
261119.439441.56056
26288.2677-0.267698
2631010.7184-0.718443
26488.3196-0.319597
26579.4578-2.4578
26689.55931-1.55931
2671011.277-1.27703
26889.56229-1.56229
2691211.35430.645735
2701411.06442.93563
27179.0749-2.0749
27266.26602-0.266018
2731111.0442-0.0441816
27445.40407-1.40407
275911.1638-2.16381
27654.251610.74839
27798.843420.156575
2781110.46120.53876
2791210.21921.7808
28098.370040.629959
2811210.93541.06463
2821010.7867-0.786734
28398.861270.138727
28465.800790.199214
2851011.1433-1.14334
28697.790521.20948
2871310.89662.10338
2881210.24371.7563

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 10.1249 & 1.8751 \tabularnewline
2 & 11 & 11.611 & -0.610959 \tabularnewline
3 & 15 & 13.509 & 1.49103 \tabularnewline
4 & 6 & 11.0094 & -5.00937 \tabularnewline
5 & 13 & 10.7225 & 2.27749 \tabularnewline
6 & 10 & 9.94888 & 0.0511173 \tabularnewline
7 & 12 & 13.265 & -1.26498 \tabularnewline
8 & 14 & 11.2637 & 2.73633 \tabularnewline
9 & 12 & 10.6564 & 1.34363 \tabularnewline
10 & 9 & 11.2635 & -2.26353 \tabularnewline
11 & 10 & 11.3698 & -1.36978 \tabularnewline
12 & 12 & 11.6904 & 0.309648 \tabularnewline
13 & 12 & 11.5308 & 0.469191 \tabularnewline
14 & 11 & 11.7753 & -0.775271 \tabularnewline
15 & 15 & 12.3596 & 2.64038 \tabularnewline
16 & 12 & 10.9779 & 1.02206 \tabularnewline
17 & 10 & 10.9006 & -0.900561 \tabularnewline
18 & 12 & 13.9688 & -1.96881 \tabularnewline
19 & 11 & 12.649 & -1.64896 \tabularnewline
20 & 12 & 11.7219 & 0.278078 \tabularnewline
21 & 11 & 11.4889 & -0.488935 \tabularnewline
22 & 12 & 11.7563 & 0.243744 \tabularnewline
23 & 13 & 13.4355 & -0.435475 \tabularnewline
24 & 11 & 11.8625 & -0.862486 \tabularnewline
25 & 12 & 11.9282 & 0.07178 \tabularnewline
26 & 13 & 12.2136 & 0.786426 \tabularnewline
27 & 10 & 11.5028 & -1.5028 \tabularnewline
28 & 14 & 11.3013 & 2.69872 \tabularnewline
29 & 12 & 11.7421 & 0.25789 \tabularnewline
30 & 10 & 10.4313 & -0.431345 \tabularnewline
31 & 12 & 11.1635 & 0.836522 \tabularnewline
32 & 8 & 9.38692 & -1.38692 \tabularnewline
33 & 10 & 10.5275 & -0.527514 \tabularnewline
34 & 12 & 11.8263 & 0.173721 \tabularnewline
35 & 12 & 10.331 & 1.66898 \tabularnewline
36 & 7 & 8.22305 & -1.22305 \tabularnewline
37 & 9 & 8.27771 & 0.722289 \tabularnewline
38 & 12 & 10.3685 & 1.63151 \tabularnewline
39 & 10 & 11.7282 & -1.72825 \tabularnewline
40 & 10 & 11.4946 & -1.4946 \tabularnewline
41 & 10 & 11.4256 & -1.42556 \tabularnewline
42 & 12 & 10.6251 & 1.37492 \tabularnewline
43 & 15 & 13.5926 & 1.40741 \tabularnewline
44 & 10 & 10.409 & -0.409003 \tabularnewline
45 & 10 & 10.4594 & -0.459364 \tabularnewline
46 & 12 & 9.03743 & 2.96257 \tabularnewline
47 & 13 & 10.7273 & 2.27272 \tabularnewline
48 & 11 & 11.2191 & -0.219123 \tabularnewline
49 & 11 & 11.806 & -0.80595 \tabularnewline
50 & 12 & 10.3358 & 1.66421 \tabularnewline
51 & 14 & 11.8681 & 2.13194 \tabularnewline
52 & 10 & 10.3575 & -0.357527 \tabularnewline
53 & 12 & 9.36317 & 2.63683 \tabularnewline
54 & 13 & 11.8779 & 1.1221 \tabularnewline
55 & 5 & 7.6877 & -2.6877 \tabularnewline
56 & 6 & 10.6431 & -4.64311 \tabularnewline
57 & 12 & 11.6778 & 0.322154 \tabularnewline
58 & 12 & 11.8195 & 0.180512 \tabularnewline
59 & 11 & 11.0029 & -0.00290371 \tabularnewline
60 & 10 & 11.7672 & -1.76722 \tabularnewline
61 & 7 & 9.29516 & -2.29516 \tabularnewline
62 & 12 & 11.4792 & 0.520808 \tabularnewline
63 & 14 & 11.8139 & 2.18609 \tabularnewline
64 & 11 & 10.7317 & 0.268267 \tabularnewline
65 & 12 & 11.6801 & 0.319858 \tabularnewline
66 & 13 & 12.1666 & 0.833368 \tabularnewline
67 & 14 & 12.8821 & 1.11791 \tabularnewline
68 & 11 & 12.5185 & -1.51852 \tabularnewline
69 & 12 & 9.6437 & 2.3563 \tabularnewline
70 & 12 & 11.5739 & 0.426146 \tabularnewline
71 & 8 & 8.23476 & -0.234757 \tabularnewline
72 & 11 & 10.7866 & 0.213372 \tabularnewline
73 & 14 & 12.9697 & 1.03032 \tabularnewline
74 & 14 & 12.7262 & 1.2738 \tabularnewline
75 & 12 & 11.3617 & 0.638279 \tabularnewline
76 & 9 & 12.1641 & -3.16411 \tabularnewline
77 & 13 & 11.7683 & 1.23166 \tabularnewline
78 & 11 & 11.6983 & -0.698316 \tabularnewline
79 & 12 & 9.87847 & 2.12153 \tabularnewline
80 & 12 & 11.322 & 0.678046 \tabularnewline
81 & 12 & 11.576 & 0.423991 \tabularnewline
82 & 12 & 11.813 & 0.186977 \tabularnewline
83 & 12 & 10.8935 & 1.10651 \tabularnewline
84 & 11 & 11.2324 & -0.232378 \tabularnewline
85 & 10 & 11.7025 & -1.70248 \tabularnewline
86 & 9 & 10.4881 & -1.48811 \tabularnewline
87 & 12 & 11.7756 & 0.224447 \tabularnewline
88 & 12 & 11.7889 & 0.21105 \tabularnewline
89 & 12 & 11.2675 & 0.732538 \tabularnewline
90 & 9 & 9.63414 & -0.634142 \tabularnewline
91 & 15 & 12.2435 & 2.7565 \tabularnewline
92 & 12 & 11.9104 & 0.0895517 \tabularnewline
93 & 12 & 11.0953 & 0.904672 \tabularnewline
94 & 12 & 10.0982 & 1.90179 \tabularnewline
95 & 10 & 11.7266 & -1.72656 \tabularnewline
96 & 13 & 11.7651 & 1.23494 \tabularnewline
97 & 9 & 11.676 & -2.67597 \tabularnewline
98 & 12 & 11.4561 & 0.5439 \tabularnewline
99 & 10 & 10.4946 & -0.494577 \tabularnewline
100 & 14 & 11.7307 & 2.26927 \tabularnewline
101 & 11 & 11.5259 & -0.525891 \tabularnewline
102 & 15 & 13.9801 & 1.01995 \tabularnewline
103 & 11 & 10.8834 & 0.116581 \tabularnewline
104 & 11 & 11.8882 & -0.888247 \tabularnewline
105 & 12 & 9.79829 & 2.20171 \tabularnewline
106 & 12 & 12.2628 & -0.262801 \tabularnewline
107 & 12 & 11.543 & 0.456967 \tabularnewline
108 & 11 & 11.5573 & -0.55732 \tabularnewline
109 & 7 & 9.68482 & -2.68482 \tabularnewline
110 & 12 & 11.8062 & 0.193767 \tabularnewline
111 & 14 & 11.805 & 2.19503 \tabularnewline
112 & 11 & 12.5157 & -1.51573 \tabularnewline
113 & 10 & 9.49681 & 0.503191 \tabularnewline
114 & 13 & 12.5112 & 0.488839 \tabularnewline
115 & 13 & 10.827 & 2.173 \tabularnewline
116 & 8 & 10.8137 & -2.81375 \tabularnewline
117 & 11 & 10.1579 & 0.842121 \tabularnewline
118 & 12 & 11.758 & 0.242012 \tabularnewline
119 & 11 & 9.9856 & 1.0144 \tabularnewline
120 & 13 & 11.6316 & 1.36843 \tabularnewline
121 & 12 & 10.1799 & 1.82006 \tabularnewline
122 & 14 & 11.8109 & 2.18913 \tabularnewline
123 & 13 & 11.1063 & 1.89371 \tabularnewline
124 & 15 & 11.7868 & 3.21321 \tabularnewline
125 & 10 & 10.8335 & -0.833533 \tabularnewline
126 & 11 & 12.2716 & -1.27161 \tabularnewline
127 & 9 & 11.2315 & -2.23149 \tabularnewline
128 & 11 & 9.52622 & 1.47378 \tabularnewline
129 & 10 & 11.5344 & -1.53437 \tabularnewline
130 & 11 & 8.31532 & 2.68468 \tabularnewline
131 & 8 & 11.7467 & -3.74675 \tabularnewline
132 & 11 & 9.32003 & 1.67997 \tabularnewline
133 & 12 & 10.477 & 1.52299 \tabularnewline
134 & 12 & 11.1015 & 0.89849 \tabularnewline
135 & 9 & 9.69562 & -0.695617 \tabularnewline
136 & 11 & 11.0001 & -0.000140293 \tabularnewline
137 & 10 & 9.13022 & 0.869781 \tabularnewline
138 & 8 & 9.55058 & -1.55058 \tabularnewline
139 & 9 & 8.85962 & 0.14038 \tabularnewline
140 & 8 & 11.7797 & -3.77972 \tabularnewline
141 & 9 & 11.0837 & -2.0837 \tabularnewline
142 & 15 & 12.387 & 2.61298 \tabularnewline
143 & 11 & 11.2859 & -0.285889 \tabularnewline
144 & 8 & 8.30746 & -0.307461 \tabularnewline
145 & 13 & 12.6948 & 0.305172 \tabularnewline
146 & 12 & 9.93056 & 2.06944 \tabularnewline
147 & 12 & 11.4947 & 0.505256 \tabularnewline
148 & 9 & 9.86456 & -0.864564 \tabularnewline
149 & 7 & 8.52882 & -1.52882 \tabularnewline
150 & 13 & 11.1911 & 1.80893 \tabularnewline
151 & 9 & 11.6024 & -2.60238 \tabularnewline
152 & 6 & 11.889 & -5.889 \tabularnewline
153 & 8 & 10.66 & -2.66002 \tabularnewline
154 & 8 & 8.42751 & -0.427511 \tabularnewline
155 & 6 & 10.2198 & -4.21985 \tabularnewline
156 & 9 & 11.2315 & -2.23149 \tabularnewline
157 & 11 & 11.7227 & -0.722672 \tabularnewline
158 & 8 & 9.71503 & -1.71503 \tabularnewline
159 & 10 & 9.36281 & 0.637192 \tabularnewline
160 & 8 & 8.72609 & -0.726095 \tabularnewline
161 & 14 & 11.5223 & 2.47766 \tabularnewline
162 & 10 & 10.9205 & -0.920507 \tabularnewline
163 & 8 & 7.84888 & 0.151118 \tabularnewline
164 & 11 & 10.0045 & 0.995469 \tabularnewline
165 & 12 & 8.47802 & 3.52198 \tabularnewline
166 & 12 & 9.81055 & 2.18945 \tabularnewline
167 & 12 & 11.2818 & 0.718156 \tabularnewline
168 & 5 & 8.7956 & -3.7956 \tabularnewline
169 & 12 & 11.3381 & 0.661895 \tabularnewline
170 & 10 & 8.85818 & 1.14182 \tabularnewline
171 & 7 & 7.33448 & -0.334476 \tabularnewline
172 & 12 & 8.92953 & 3.07047 \tabularnewline
173 & 11 & 10.5832 & 0.416838 \tabularnewline
174 & 8 & 9.10166 & -1.10166 \tabularnewline
175 & 9 & 8.85495 & 0.145051 \tabularnewline
176 & 10 & 10.1636 & -0.163559 \tabularnewline
177 & 9 & 9.16765 & -0.167655 \tabularnewline
178 & 12 & 11.3319 & 0.668077 \tabularnewline
179 & 6 & 8.23224 & -2.23224 \tabularnewline
180 & 15 & 12.792 & 2.20803 \tabularnewline
181 & 12 & 10.4215 & 1.57853 \tabularnewline
182 & 12 & 6.92573 & 5.07427 \tabularnewline
183 & 12 & 11.394 & 0.605968 \tabularnewline
184 & 11 & 11.5914 & -0.591384 \tabularnewline
185 & 7 & 8.97191 & -1.97191 \tabularnewline
186 & 7 & 8.27632 & -1.27632 \tabularnewline
187 & 5 & 8.43632 & -3.43632 \tabularnewline
188 & 12 & 10.3175 & 1.68248 \tabularnewline
189 & 12 & 11.4028 & 0.597164 \tabularnewline
190 & 3 & 9.11342 & -6.11342 \tabularnewline
191 & 11 & 11.3968 & -0.396795 \tabularnewline
192 & 10 & 9.6364 & 0.363597 \tabularnewline
193 & 12 & 10.599 & 1.40096 \tabularnewline
194 & 9 & 11.2367 & -2.23665 \tabularnewline
195 & 12 & 11.396 & 0.603955 \tabularnewline
196 & 9 & 10.0193 & -1.01929 \tabularnewline
197 & 12 & 11.0716 & 0.928416 \tabularnewline
198 & 10 & 10.0019 & -0.00190838 \tabularnewline
199 & 9 & 8.2335 & 0.766495 \tabularnewline
200 & 12 & 8.84155 & 3.15845 \tabularnewline
201 & 8 & 10.7665 & -2.76655 \tabularnewline
202 & 11 & 10.802 & 0.197997 \tabularnewline
203 & 11 & 11.3695 & -0.369534 \tabularnewline
204 & 12 & 11.0878 & 0.912166 \tabularnewline
205 & 10 & 8.29205 & 1.70795 \tabularnewline
206 & 10 & 10.4807 & -0.480678 \tabularnewline
207 & 12 & 9.14143 & 2.85857 \tabularnewline
208 & 12 & 9.01378 & 2.98622 \tabularnewline
209 & 11 & 10.6988 & 0.301239 \tabularnewline
210 & 8 & 10.5639 & -2.56387 \tabularnewline
211 & 12 & 11.3481 & 0.651917 \tabularnewline
212 & 10 & 9.82711 & 0.172895 \tabularnewline
213 & 11 & 11.8674 & -0.867416 \tabularnewline
214 & 10 & 10.1488 & -0.148757 \tabularnewline
215 & 8 & 9.48089 & -1.48089 \tabularnewline
216 & 12 & 10.8486 & 1.15144 \tabularnewline
217 & 12 & 9.41817 & 2.58183 \tabularnewline
218 & 10 & 9.95338 & 0.0466191 \tabularnewline
219 & 12 & 10.7633 & 1.23673 \tabularnewline
220 & 9 & 8.86315 & 0.136855 \tabularnewline
221 & 6 & 6.98802 & -0.988023 \tabularnewline
222 & 10 & 9.92148 & 0.0785158 \tabularnewline
223 & 9 & 10.0073 & -1.00729 \tabularnewline
224 & 9 & 8.364 & 0.636 \tabularnewline
225 & 9 & 8.93279 & 0.0672053 \tabularnewline
226 & 6 & 9.57027 & -3.57027 \tabularnewline
227 & 10 & 7.94261 & 2.05739 \tabularnewline
228 & 6 & 11.088 & -5.08798 \tabularnewline
229 & 14 & 12.2964 & 1.70365 \tabularnewline
230 & 10 & 9.6008 & 0.399195 \tabularnewline
231 & 10 & 8.26152 & 1.73848 \tabularnewline
232 & 6 & 4.38341 & 1.61659 \tabularnewline
233 & 12 & 9.2406 & 2.7594 \tabularnewline
234 & 12 & 11.3393 & 0.660722 \tabularnewline
235 & 7 & 7.67656 & -0.67656 \tabularnewline
236 & 8 & 8.94343 & -0.943428 \tabularnewline
237 & 11 & 8.9468 & 2.0532 \tabularnewline
238 & 3 & 7.73806 & -4.73806 \tabularnewline
239 & 6 & 9.40908 & -3.40908 \tabularnewline
240 & 8 & 8.99907 & -0.999072 \tabularnewline
241 & 9 & 10.0358 & -1.03582 \tabularnewline
242 & 9 & 7.95044 & 1.04956 \tabularnewline
243 & 8 & 9.0389 & -1.0389 \tabularnewline
244 & 9 & 8.96986 & 0.0301433 \tabularnewline
245 & 7 & 8.36451 & -1.36451 \tabularnewline
246 & 7 & 7.76012 & -0.760121 \tabularnewline
247 & 6 & 9.10292 & -3.10292 \tabularnewline
248 & 9 & 11.2834 & -2.28335 \tabularnewline
249 & 10 & 8.83523 & 1.16477 \tabularnewline
250 & 11 & 9.96968 & 1.03032 \tabularnewline
251 & 12 & 11.1758 & 0.824201 \tabularnewline
252 & 8 & 10.2515 & -2.25152 \tabularnewline
253 & 11 & 9.61884 & 1.38116 \tabularnewline
254 & 3 & 4.66727 & -1.66727 \tabularnewline
255 & 11 & 10.7577 & 0.242258 \tabularnewline
256 & 12 & 8.42217 & 3.57783 \tabularnewline
257 & 7 & 8.36662 & -1.36662 \tabularnewline
258 & 9 & 9.99343 & -0.99343 \tabularnewline
259 & 12 & 10.5247 & 1.47529 \tabularnewline
260 & 8 & 10.227 & -2.22703 \tabularnewline
261 & 11 & 9.43944 & 1.56056 \tabularnewline
262 & 8 & 8.2677 & -0.267698 \tabularnewline
263 & 10 & 10.7184 & -0.718443 \tabularnewline
264 & 8 & 8.3196 & -0.319597 \tabularnewline
265 & 7 & 9.4578 & -2.4578 \tabularnewline
266 & 8 & 9.55931 & -1.55931 \tabularnewline
267 & 10 & 11.277 & -1.27703 \tabularnewline
268 & 8 & 9.56229 & -1.56229 \tabularnewline
269 & 12 & 11.3543 & 0.645735 \tabularnewline
270 & 14 & 11.0644 & 2.93563 \tabularnewline
271 & 7 & 9.0749 & -2.0749 \tabularnewline
272 & 6 & 6.26602 & -0.266018 \tabularnewline
273 & 11 & 11.0442 & -0.0441816 \tabularnewline
274 & 4 & 5.40407 & -1.40407 \tabularnewline
275 & 9 & 11.1638 & -2.16381 \tabularnewline
276 & 5 & 4.25161 & 0.74839 \tabularnewline
277 & 9 & 8.84342 & 0.156575 \tabularnewline
278 & 11 & 10.4612 & 0.53876 \tabularnewline
279 & 12 & 10.2192 & 1.7808 \tabularnewline
280 & 9 & 8.37004 & 0.629959 \tabularnewline
281 & 12 & 10.9354 & 1.06463 \tabularnewline
282 & 10 & 10.7867 & -0.786734 \tabularnewline
283 & 9 & 8.86127 & 0.138727 \tabularnewline
284 & 6 & 5.80079 & 0.199214 \tabularnewline
285 & 10 & 11.1433 & -1.14334 \tabularnewline
286 & 9 & 7.79052 & 1.20948 \tabularnewline
287 & 13 & 10.8966 & 2.10338 \tabularnewline
288 & 12 & 10.2437 & 1.7563 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231417&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]12[/C][C]10.1249[/C][C]1.8751[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]11.611[/C][C]-0.610959[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]13.509[/C][C]1.49103[/C][/ROW]
[ROW][C]4[/C][C]6[/C][C]11.0094[/C][C]-5.00937[/C][/ROW]
[ROW][C]5[/C][C]13[/C][C]10.7225[/C][C]2.27749[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]9.94888[/C][C]0.0511173[/C][/ROW]
[ROW][C]7[/C][C]12[/C][C]13.265[/C][C]-1.26498[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]11.2637[/C][C]2.73633[/C][/ROW]
[ROW][C]9[/C][C]12[/C][C]10.6564[/C][C]1.34363[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]11.2635[/C][C]-2.26353[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]11.3698[/C][C]-1.36978[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]11.6904[/C][C]0.309648[/C][/ROW]
[ROW][C]13[/C][C]12[/C][C]11.5308[/C][C]0.469191[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]11.7753[/C][C]-0.775271[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]12.3596[/C][C]2.64038[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]10.9779[/C][C]1.02206[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]10.9006[/C][C]-0.900561[/C][/ROW]
[ROW][C]18[/C][C]12[/C][C]13.9688[/C][C]-1.96881[/C][/ROW]
[ROW][C]19[/C][C]11[/C][C]12.649[/C][C]-1.64896[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]11.7219[/C][C]0.278078[/C][/ROW]
[ROW][C]21[/C][C]11[/C][C]11.4889[/C][C]-0.488935[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]11.7563[/C][C]0.243744[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]13.4355[/C][C]-0.435475[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]11.8625[/C][C]-0.862486[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]11.9282[/C][C]0.07178[/C][/ROW]
[ROW][C]26[/C][C]13[/C][C]12.2136[/C][C]0.786426[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]11.5028[/C][C]-1.5028[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]11.3013[/C][C]2.69872[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]11.7421[/C][C]0.25789[/C][/ROW]
[ROW][C]30[/C][C]10[/C][C]10.4313[/C][C]-0.431345[/C][/ROW]
[ROW][C]31[/C][C]12[/C][C]11.1635[/C][C]0.836522[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]9.38692[/C][C]-1.38692[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.5275[/C][C]-0.527514[/C][/ROW]
[ROW][C]34[/C][C]12[/C][C]11.8263[/C][C]0.173721[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.331[/C][C]1.66898[/C][/ROW]
[ROW][C]36[/C][C]7[/C][C]8.22305[/C][C]-1.22305[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]8.27771[/C][C]0.722289[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]10.3685[/C][C]1.63151[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]11.7282[/C][C]-1.72825[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]11.4946[/C][C]-1.4946[/C][/ROW]
[ROW][C]41[/C][C]10[/C][C]11.4256[/C][C]-1.42556[/C][/ROW]
[ROW][C]42[/C][C]12[/C][C]10.6251[/C][C]1.37492[/C][/ROW]
[ROW][C]43[/C][C]15[/C][C]13.5926[/C][C]1.40741[/C][/ROW]
[ROW][C]44[/C][C]10[/C][C]10.409[/C][C]-0.409003[/C][/ROW]
[ROW][C]45[/C][C]10[/C][C]10.4594[/C][C]-0.459364[/C][/ROW]
[ROW][C]46[/C][C]12[/C][C]9.03743[/C][C]2.96257[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]10.7273[/C][C]2.27272[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.2191[/C][C]-0.219123[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]11.806[/C][C]-0.80595[/C][/ROW]
[ROW][C]50[/C][C]12[/C][C]10.3358[/C][C]1.66421[/C][/ROW]
[ROW][C]51[/C][C]14[/C][C]11.8681[/C][C]2.13194[/C][/ROW]
[ROW][C]52[/C][C]10[/C][C]10.3575[/C][C]-0.357527[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]9.36317[/C][C]2.63683[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.8779[/C][C]1.1221[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]7.6877[/C][C]-2.6877[/C][/ROW]
[ROW][C]56[/C][C]6[/C][C]10.6431[/C][C]-4.64311[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]11.6778[/C][C]0.322154[/C][/ROW]
[ROW][C]58[/C][C]12[/C][C]11.8195[/C][C]0.180512[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]11.0029[/C][C]-0.00290371[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]11.7672[/C][C]-1.76722[/C][/ROW]
[ROW][C]61[/C][C]7[/C][C]9.29516[/C][C]-2.29516[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]11.4792[/C][C]0.520808[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]11.8139[/C][C]2.18609[/C][/ROW]
[ROW][C]64[/C][C]11[/C][C]10.7317[/C][C]0.268267[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]11.6801[/C][C]0.319858[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]12.1666[/C][C]0.833368[/C][/ROW]
[ROW][C]67[/C][C]14[/C][C]12.8821[/C][C]1.11791[/C][/ROW]
[ROW][C]68[/C][C]11[/C][C]12.5185[/C][C]-1.51852[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]9.6437[/C][C]2.3563[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]11.5739[/C][C]0.426146[/C][/ROW]
[ROW][C]71[/C][C]8[/C][C]8.23476[/C][C]-0.234757[/C][/ROW]
[ROW][C]72[/C][C]11[/C][C]10.7866[/C][C]0.213372[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]12.9697[/C][C]1.03032[/C][/ROW]
[ROW][C]74[/C][C]14[/C][C]12.7262[/C][C]1.2738[/C][/ROW]
[ROW][C]75[/C][C]12[/C][C]11.3617[/C][C]0.638279[/C][/ROW]
[ROW][C]76[/C][C]9[/C][C]12.1641[/C][C]-3.16411[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.7683[/C][C]1.23166[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]11.6983[/C][C]-0.698316[/C][/ROW]
[ROW][C]79[/C][C]12[/C][C]9.87847[/C][C]2.12153[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]11.322[/C][C]0.678046[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]11.576[/C][C]0.423991[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]11.813[/C][C]0.186977[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]10.8935[/C][C]1.10651[/C][/ROW]
[ROW][C]84[/C][C]11[/C][C]11.2324[/C][C]-0.232378[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]11.7025[/C][C]-1.70248[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]10.4881[/C][C]-1.48811[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]11.7756[/C][C]0.224447[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.7889[/C][C]0.21105[/C][/ROW]
[ROW][C]89[/C][C]12[/C][C]11.2675[/C][C]0.732538[/C][/ROW]
[ROW][C]90[/C][C]9[/C][C]9.63414[/C][C]-0.634142[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]12.2435[/C][C]2.7565[/C][/ROW]
[ROW][C]92[/C][C]12[/C][C]11.9104[/C][C]0.0895517[/C][/ROW]
[ROW][C]93[/C][C]12[/C][C]11.0953[/C][C]0.904672[/C][/ROW]
[ROW][C]94[/C][C]12[/C][C]10.0982[/C][C]1.90179[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]11.7266[/C][C]-1.72656[/C][/ROW]
[ROW][C]96[/C][C]13[/C][C]11.7651[/C][C]1.23494[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]11.676[/C][C]-2.67597[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]11.4561[/C][C]0.5439[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]10.4946[/C][C]-0.494577[/C][/ROW]
[ROW][C]100[/C][C]14[/C][C]11.7307[/C][C]2.26927[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]11.5259[/C][C]-0.525891[/C][/ROW]
[ROW][C]102[/C][C]15[/C][C]13.9801[/C][C]1.01995[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]10.8834[/C][C]0.116581[/C][/ROW]
[ROW][C]104[/C][C]11[/C][C]11.8882[/C][C]-0.888247[/C][/ROW]
[ROW][C]105[/C][C]12[/C][C]9.79829[/C][C]2.20171[/C][/ROW]
[ROW][C]106[/C][C]12[/C][C]12.2628[/C][C]-0.262801[/C][/ROW]
[ROW][C]107[/C][C]12[/C][C]11.543[/C][C]0.456967[/C][/ROW]
[ROW][C]108[/C][C]11[/C][C]11.5573[/C][C]-0.55732[/C][/ROW]
[ROW][C]109[/C][C]7[/C][C]9.68482[/C][C]-2.68482[/C][/ROW]
[ROW][C]110[/C][C]12[/C][C]11.8062[/C][C]0.193767[/C][/ROW]
[ROW][C]111[/C][C]14[/C][C]11.805[/C][C]2.19503[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.5157[/C][C]-1.51573[/C][/ROW]
[ROW][C]113[/C][C]10[/C][C]9.49681[/C][C]0.503191[/C][/ROW]
[ROW][C]114[/C][C]13[/C][C]12.5112[/C][C]0.488839[/C][/ROW]
[ROW][C]115[/C][C]13[/C][C]10.827[/C][C]2.173[/C][/ROW]
[ROW][C]116[/C][C]8[/C][C]10.8137[/C][C]-2.81375[/C][/ROW]
[ROW][C]117[/C][C]11[/C][C]10.1579[/C][C]0.842121[/C][/ROW]
[ROW][C]118[/C][C]12[/C][C]11.758[/C][C]0.242012[/C][/ROW]
[ROW][C]119[/C][C]11[/C][C]9.9856[/C][C]1.0144[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]11.6316[/C][C]1.36843[/C][/ROW]
[ROW][C]121[/C][C]12[/C][C]10.1799[/C][C]1.82006[/C][/ROW]
[ROW][C]122[/C][C]14[/C][C]11.8109[/C][C]2.18913[/C][/ROW]
[ROW][C]123[/C][C]13[/C][C]11.1063[/C][C]1.89371[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]11.7868[/C][C]3.21321[/C][/ROW]
[ROW][C]125[/C][C]10[/C][C]10.8335[/C][C]-0.833533[/C][/ROW]
[ROW][C]126[/C][C]11[/C][C]12.2716[/C][C]-1.27161[/C][/ROW]
[ROW][C]127[/C][C]9[/C][C]11.2315[/C][C]-2.23149[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]9.52622[/C][C]1.47378[/C][/ROW]
[ROW][C]129[/C][C]10[/C][C]11.5344[/C][C]-1.53437[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]8.31532[/C][C]2.68468[/C][/ROW]
[ROW][C]131[/C][C]8[/C][C]11.7467[/C][C]-3.74675[/C][/ROW]
[ROW][C]132[/C][C]11[/C][C]9.32003[/C][C]1.67997[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]10.477[/C][C]1.52299[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]11.1015[/C][C]0.89849[/C][/ROW]
[ROW][C]135[/C][C]9[/C][C]9.69562[/C][C]-0.695617[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]11.0001[/C][C]-0.000140293[/C][/ROW]
[ROW][C]137[/C][C]10[/C][C]9.13022[/C][C]0.869781[/C][/ROW]
[ROW][C]138[/C][C]8[/C][C]9.55058[/C][C]-1.55058[/C][/ROW]
[ROW][C]139[/C][C]9[/C][C]8.85962[/C][C]0.14038[/C][/ROW]
[ROW][C]140[/C][C]8[/C][C]11.7797[/C][C]-3.77972[/C][/ROW]
[ROW][C]141[/C][C]9[/C][C]11.0837[/C][C]-2.0837[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]12.387[/C][C]2.61298[/C][/ROW]
[ROW][C]143[/C][C]11[/C][C]11.2859[/C][C]-0.285889[/C][/ROW]
[ROW][C]144[/C][C]8[/C][C]8.30746[/C][C]-0.307461[/C][/ROW]
[ROW][C]145[/C][C]13[/C][C]12.6948[/C][C]0.305172[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]9.93056[/C][C]2.06944[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]11.4947[/C][C]0.505256[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]9.86456[/C][C]-0.864564[/C][/ROW]
[ROW][C]149[/C][C]7[/C][C]8.52882[/C][C]-1.52882[/C][/ROW]
[ROW][C]150[/C][C]13[/C][C]11.1911[/C][C]1.80893[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]11.6024[/C][C]-2.60238[/C][/ROW]
[ROW][C]152[/C][C]6[/C][C]11.889[/C][C]-5.889[/C][/ROW]
[ROW][C]153[/C][C]8[/C][C]10.66[/C][C]-2.66002[/C][/ROW]
[ROW][C]154[/C][C]8[/C][C]8.42751[/C][C]-0.427511[/C][/ROW]
[ROW][C]155[/C][C]6[/C][C]10.2198[/C][C]-4.21985[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]11.2315[/C][C]-2.23149[/C][/ROW]
[ROW][C]157[/C][C]11[/C][C]11.7227[/C][C]-0.722672[/C][/ROW]
[ROW][C]158[/C][C]8[/C][C]9.71503[/C][C]-1.71503[/C][/ROW]
[ROW][C]159[/C][C]10[/C][C]9.36281[/C][C]0.637192[/C][/ROW]
[ROW][C]160[/C][C]8[/C][C]8.72609[/C][C]-0.726095[/C][/ROW]
[ROW][C]161[/C][C]14[/C][C]11.5223[/C][C]2.47766[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]10.9205[/C][C]-0.920507[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]7.84888[/C][C]0.151118[/C][/ROW]
[ROW][C]164[/C][C]11[/C][C]10.0045[/C][C]0.995469[/C][/ROW]
[ROW][C]165[/C][C]12[/C][C]8.47802[/C][C]3.52198[/C][/ROW]
[ROW][C]166[/C][C]12[/C][C]9.81055[/C][C]2.18945[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]11.2818[/C][C]0.718156[/C][/ROW]
[ROW][C]168[/C][C]5[/C][C]8.7956[/C][C]-3.7956[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]11.3381[/C][C]0.661895[/C][/ROW]
[ROW][C]170[/C][C]10[/C][C]8.85818[/C][C]1.14182[/C][/ROW]
[ROW][C]171[/C][C]7[/C][C]7.33448[/C][C]-0.334476[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]8.92953[/C][C]3.07047[/C][/ROW]
[ROW][C]173[/C][C]11[/C][C]10.5832[/C][C]0.416838[/C][/ROW]
[ROW][C]174[/C][C]8[/C][C]9.10166[/C][C]-1.10166[/C][/ROW]
[ROW][C]175[/C][C]9[/C][C]8.85495[/C][C]0.145051[/C][/ROW]
[ROW][C]176[/C][C]10[/C][C]10.1636[/C][C]-0.163559[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]9.16765[/C][C]-0.167655[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.3319[/C][C]0.668077[/C][/ROW]
[ROW][C]179[/C][C]6[/C][C]8.23224[/C][C]-2.23224[/C][/ROW]
[ROW][C]180[/C][C]15[/C][C]12.792[/C][C]2.20803[/C][/ROW]
[ROW][C]181[/C][C]12[/C][C]10.4215[/C][C]1.57853[/C][/ROW]
[ROW][C]182[/C][C]12[/C][C]6.92573[/C][C]5.07427[/C][/ROW]
[ROW][C]183[/C][C]12[/C][C]11.394[/C][C]0.605968[/C][/ROW]
[ROW][C]184[/C][C]11[/C][C]11.5914[/C][C]-0.591384[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]8.97191[/C][C]-1.97191[/C][/ROW]
[ROW][C]186[/C][C]7[/C][C]8.27632[/C][C]-1.27632[/C][/ROW]
[ROW][C]187[/C][C]5[/C][C]8.43632[/C][C]-3.43632[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]10.3175[/C][C]1.68248[/C][/ROW]
[ROW][C]189[/C][C]12[/C][C]11.4028[/C][C]0.597164[/C][/ROW]
[ROW][C]190[/C][C]3[/C][C]9.11342[/C][C]-6.11342[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]11.3968[/C][C]-0.396795[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]9.6364[/C][C]0.363597[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]10.599[/C][C]1.40096[/C][/ROW]
[ROW][C]194[/C][C]9[/C][C]11.2367[/C][C]-2.23665[/C][/ROW]
[ROW][C]195[/C][C]12[/C][C]11.396[/C][C]0.603955[/C][/ROW]
[ROW][C]196[/C][C]9[/C][C]10.0193[/C][C]-1.01929[/C][/ROW]
[ROW][C]197[/C][C]12[/C][C]11.0716[/C][C]0.928416[/C][/ROW]
[ROW][C]198[/C][C]10[/C][C]10.0019[/C][C]-0.00190838[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]8.2335[/C][C]0.766495[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]8.84155[/C][C]3.15845[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]10.7665[/C][C]-2.76655[/C][/ROW]
[ROW][C]202[/C][C]11[/C][C]10.802[/C][C]0.197997[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]11.3695[/C][C]-0.369534[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]11.0878[/C][C]0.912166[/C][/ROW]
[ROW][C]205[/C][C]10[/C][C]8.29205[/C][C]1.70795[/C][/ROW]
[ROW][C]206[/C][C]10[/C][C]10.4807[/C][C]-0.480678[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]9.14143[/C][C]2.85857[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]9.01378[/C][C]2.98622[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]10.6988[/C][C]0.301239[/C][/ROW]
[ROW][C]210[/C][C]8[/C][C]10.5639[/C][C]-2.56387[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]11.3481[/C][C]0.651917[/C][/ROW]
[ROW][C]212[/C][C]10[/C][C]9.82711[/C][C]0.172895[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.8674[/C][C]-0.867416[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]10.1488[/C][C]-0.148757[/C][/ROW]
[ROW][C]215[/C][C]8[/C][C]9.48089[/C][C]-1.48089[/C][/ROW]
[ROW][C]216[/C][C]12[/C][C]10.8486[/C][C]1.15144[/C][/ROW]
[ROW][C]217[/C][C]12[/C][C]9.41817[/C][C]2.58183[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]9.95338[/C][C]0.0466191[/C][/ROW]
[ROW][C]219[/C][C]12[/C][C]10.7633[/C][C]1.23673[/C][/ROW]
[ROW][C]220[/C][C]9[/C][C]8.86315[/C][C]0.136855[/C][/ROW]
[ROW][C]221[/C][C]6[/C][C]6.98802[/C][C]-0.988023[/C][/ROW]
[ROW][C]222[/C][C]10[/C][C]9.92148[/C][C]0.0785158[/C][/ROW]
[ROW][C]223[/C][C]9[/C][C]10.0073[/C][C]-1.00729[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]8.364[/C][C]0.636[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]8.93279[/C][C]0.0672053[/C][/ROW]
[ROW][C]226[/C][C]6[/C][C]9.57027[/C][C]-3.57027[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]7.94261[/C][C]2.05739[/C][/ROW]
[ROW][C]228[/C][C]6[/C][C]11.088[/C][C]-5.08798[/C][/ROW]
[ROW][C]229[/C][C]14[/C][C]12.2964[/C][C]1.70365[/C][/ROW]
[ROW][C]230[/C][C]10[/C][C]9.6008[/C][C]0.399195[/C][/ROW]
[ROW][C]231[/C][C]10[/C][C]8.26152[/C][C]1.73848[/C][/ROW]
[ROW][C]232[/C][C]6[/C][C]4.38341[/C][C]1.61659[/C][/ROW]
[ROW][C]233[/C][C]12[/C][C]9.2406[/C][C]2.7594[/C][/ROW]
[ROW][C]234[/C][C]12[/C][C]11.3393[/C][C]0.660722[/C][/ROW]
[ROW][C]235[/C][C]7[/C][C]7.67656[/C][C]-0.67656[/C][/ROW]
[ROW][C]236[/C][C]8[/C][C]8.94343[/C][C]-0.943428[/C][/ROW]
[ROW][C]237[/C][C]11[/C][C]8.9468[/C][C]2.0532[/C][/ROW]
[ROW][C]238[/C][C]3[/C][C]7.73806[/C][C]-4.73806[/C][/ROW]
[ROW][C]239[/C][C]6[/C][C]9.40908[/C][C]-3.40908[/C][/ROW]
[ROW][C]240[/C][C]8[/C][C]8.99907[/C][C]-0.999072[/C][/ROW]
[ROW][C]241[/C][C]9[/C][C]10.0358[/C][C]-1.03582[/C][/ROW]
[ROW][C]242[/C][C]9[/C][C]7.95044[/C][C]1.04956[/C][/ROW]
[ROW][C]243[/C][C]8[/C][C]9.0389[/C][C]-1.0389[/C][/ROW]
[ROW][C]244[/C][C]9[/C][C]8.96986[/C][C]0.0301433[/C][/ROW]
[ROW][C]245[/C][C]7[/C][C]8.36451[/C][C]-1.36451[/C][/ROW]
[ROW][C]246[/C][C]7[/C][C]7.76012[/C][C]-0.760121[/C][/ROW]
[ROW][C]247[/C][C]6[/C][C]9.10292[/C][C]-3.10292[/C][/ROW]
[ROW][C]248[/C][C]9[/C][C]11.2834[/C][C]-2.28335[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]8.83523[/C][C]1.16477[/C][/ROW]
[ROW][C]250[/C][C]11[/C][C]9.96968[/C][C]1.03032[/C][/ROW]
[ROW][C]251[/C][C]12[/C][C]11.1758[/C][C]0.824201[/C][/ROW]
[ROW][C]252[/C][C]8[/C][C]10.2515[/C][C]-2.25152[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]9.61884[/C][C]1.38116[/C][/ROW]
[ROW][C]254[/C][C]3[/C][C]4.66727[/C][C]-1.66727[/C][/ROW]
[ROW][C]255[/C][C]11[/C][C]10.7577[/C][C]0.242258[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]8.42217[/C][C]3.57783[/C][/ROW]
[ROW][C]257[/C][C]7[/C][C]8.36662[/C][C]-1.36662[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]9.99343[/C][C]-0.99343[/C][/ROW]
[ROW][C]259[/C][C]12[/C][C]10.5247[/C][C]1.47529[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]10.227[/C][C]-2.22703[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]9.43944[/C][C]1.56056[/C][/ROW]
[ROW][C]262[/C][C]8[/C][C]8.2677[/C][C]-0.267698[/C][/ROW]
[ROW][C]263[/C][C]10[/C][C]10.7184[/C][C]-0.718443[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]8.3196[/C][C]-0.319597[/C][/ROW]
[ROW][C]265[/C][C]7[/C][C]9.4578[/C][C]-2.4578[/C][/ROW]
[ROW][C]266[/C][C]8[/C][C]9.55931[/C][C]-1.55931[/C][/ROW]
[ROW][C]267[/C][C]10[/C][C]11.277[/C][C]-1.27703[/C][/ROW]
[ROW][C]268[/C][C]8[/C][C]9.56229[/C][C]-1.56229[/C][/ROW]
[ROW][C]269[/C][C]12[/C][C]11.3543[/C][C]0.645735[/C][/ROW]
[ROW][C]270[/C][C]14[/C][C]11.0644[/C][C]2.93563[/C][/ROW]
[ROW][C]271[/C][C]7[/C][C]9.0749[/C][C]-2.0749[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]6.26602[/C][C]-0.266018[/C][/ROW]
[ROW][C]273[/C][C]11[/C][C]11.0442[/C][C]-0.0441816[/C][/ROW]
[ROW][C]274[/C][C]4[/C][C]5.40407[/C][C]-1.40407[/C][/ROW]
[ROW][C]275[/C][C]9[/C][C]11.1638[/C][C]-2.16381[/C][/ROW]
[ROW][C]276[/C][C]5[/C][C]4.25161[/C][C]0.74839[/C][/ROW]
[ROW][C]277[/C][C]9[/C][C]8.84342[/C][C]0.156575[/C][/ROW]
[ROW][C]278[/C][C]11[/C][C]10.4612[/C][C]0.53876[/C][/ROW]
[ROW][C]279[/C][C]12[/C][C]10.2192[/C][C]1.7808[/C][/ROW]
[ROW][C]280[/C][C]9[/C][C]8.37004[/C][C]0.629959[/C][/ROW]
[ROW][C]281[/C][C]12[/C][C]10.9354[/C][C]1.06463[/C][/ROW]
[ROW][C]282[/C][C]10[/C][C]10.7867[/C][C]-0.786734[/C][/ROW]
[ROW][C]283[/C][C]9[/C][C]8.86127[/C][C]0.138727[/C][/ROW]
[ROW][C]284[/C][C]6[/C][C]5.80079[/C][C]0.199214[/C][/ROW]
[ROW][C]285[/C][C]10[/C][C]11.1433[/C][C]-1.14334[/C][/ROW]
[ROW][C]286[/C][C]9[/C][C]7.79052[/C][C]1.20948[/C][/ROW]
[ROW][C]287[/C][C]13[/C][C]10.8966[/C][C]2.10338[/C][/ROW]
[ROW][C]288[/C][C]12[/C][C]10.2437[/C][C]1.7563[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231417&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231417&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.12491.8751
21111.611-0.610959
31513.5091.49103
4611.0094-5.00937
51310.72252.27749
6109.948880.0511173
71213.265-1.26498
81411.26372.73633
91210.65641.34363
10911.2635-2.26353
111011.3698-1.36978
121211.69040.309648
131211.53080.469191
141111.7753-0.775271
151512.35962.64038
161210.97791.02206
171010.9006-0.900561
181213.9688-1.96881
191112.649-1.64896
201211.72190.278078
211111.4889-0.488935
221211.75630.243744
231313.4355-0.435475
241111.8625-0.862486
251211.92820.07178
261312.21360.786426
271011.5028-1.5028
281411.30132.69872
291211.74210.25789
301010.4313-0.431345
311211.16350.836522
3289.38692-1.38692
331010.5275-0.527514
341211.82630.173721
351210.3311.66898
3678.22305-1.22305
3798.277710.722289
381210.36851.63151
391011.7282-1.72825
401011.4946-1.4946
411011.4256-1.42556
421210.62511.37492
431513.59261.40741
441010.409-0.409003
451010.4594-0.459364
46129.037432.96257
471310.72732.27272
481111.2191-0.219123
491111.806-0.80595
501210.33581.66421
511411.86812.13194
521010.3575-0.357527
53129.363172.63683
541311.87791.1221
5557.6877-2.6877
56610.6431-4.64311
571211.67780.322154
581211.81950.180512
591111.0029-0.00290371
601011.7672-1.76722
6179.29516-2.29516
621211.47920.520808
631411.81392.18609
641110.73170.268267
651211.68010.319858
661312.16660.833368
671412.88211.11791
681112.5185-1.51852
69129.64372.3563
701211.57390.426146
7188.23476-0.234757
721110.78660.213372
731412.96971.03032
741412.72621.2738
751211.36170.638279
76912.1641-3.16411
771311.76831.23166
781111.6983-0.698316
79129.878472.12153
801211.3220.678046
811211.5760.423991
821211.8130.186977
831210.89351.10651
841111.2324-0.232378
851011.7025-1.70248
86910.4881-1.48811
871211.77560.224447
881211.78890.21105
891211.26750.732538
9099.63414-0.634142
911512.24352.7565
921211.91040.0895517
931211.09530.904672
941210.09821.90179
951011.7266-1.72656
961311.76511.23494
97911.676-2.67597
981211.45610.5439
991010.4946-0.494577
1001411.73072.26927
1011111.5259-0.525891
1021513.98011.01995
1031110.88340.116581
1041111.8882-0.888247
105129.798292.20171
1061212.2628-0.262801
1071211.5430.456967
1081111.5573-0.55732
10979.68482-2.68482
1101211.80620.193767
1111411.8052.19503
1121112.5157-1.51573
113109.496810.503191
1141312.51120.488839
1151310.8272.173
116810.8137-2.81375
1171110.15790.842121
1181211.7580.242012
119119.98561.0144
1201311.63161.36843
1211210.17991.82006
1221411.81092.18913
1231311.10631.89371
1241511.78683.21321
1251010.8335-0.833533
1261112.2716-1.27161
127911.2315-2.23149
128119.526221.47378
1291011.5344-1.53437
130118.315322.68468
131811.7467-3.74675
132119.320031.67997
1331210.4771.52299
1341211.10150.89849
13599.69562-0.695617
1361111.0001-0.000140293
137109.130220.869781
13889.55058-1.55058
13998.859620.14038
140811.7797-3.77972
141911.0837-2.0837
1421512.3872.61298
1431111.2859-0.285889
14488.30746-0.307461
1451312.69480.305172
146129.930562.06944
1471211.49470.505256
14899.86456-0.864564
14978.52882-1.52882
1501311.19111.80893
151911.6024-2.60238
152611.889-5.889
153810.66-2.66002
15488.42751-0.427511
155610.2198-4.21985
156911.2315-2.23149
1571111.7227-0.722672
15889.71503-1.71503
159109.362810.637192
16088.72609-0.726095
1611411.52232.47766
1621010.9205-0.920507
16387.848880.151118
1641110.00450.995469
165128.478023.52198
166129.810552.18945
1671211.28180.718156
16858.7956-3.7956
1691211.33810.661895
170108.858181.14182
17177.33448-0.334476
172128.929533.07047
1731110.58320.416838
17489.10166-1.10166
17598.854950.145051
1761010.1636-0.163559
17799.16765-0.167655
1781211.33190.668077
17968.23224-2.23224
1801512.7922.20803
1811210.42151.57853
182126.925735.07427
1831211.3940.605968
1841111.5914-0.591384
18578.97191-1.97191
18678.27632-1.27632
18758.43632-3.43632
1881210.31751.68248
1891211.40280.597164
19039.11342-6.11342
1911111.3968-0.396795
192109.63640.363597
1931210.5991.40096
194911.2367-2.23665
1951211.3960.603955
196910.0193-1.01929
1971211.07160.928416
1981010.0019-0.00190838
19998.23350.766495
200128.841553.15845
201810.7665-2.76655
2021110.8020.197997
2031111.3695-0.369534
2041211.08780.912166
205108.292051.70795
2061010.4807-0.480678
207129.141432.85857
208129.013782.98622
2091110.69880.301239
210810.5639-2.56387
2111211.34810.651917
212109.827110.172895
2131111.8674-0.867416
2141010.1488-0.148757
21589.48089-1.48089
2161210.84861.15144
217129.418172.58183
218109.953380.0466191
2191210.76331.23673
22098.863150.136855
22166.98802-0.988023
222109.921480.0785158
223910.0073-1.00729
22498.3640.636
22598.932790.0672053
22669.57027-3.57027
227107.942612.05739
228611.088-5.08798
2291412.29641.70365
230109.60080.399195
231108.261521.73848
23264.383411.61659
233129.24062.7594
2341211.33930.660722
23577.67656-0.67656
23688.94343-0.943428
237118.94682.0532
23837.73806-4.73806
23969.40908-3.40908
24088.99907-0.999072
241910.0358-1.03582
24297.950441.04956
24389.0389-1.0389
24498.969860.0301433
24578.36451-1.36451
24677.76012-0.760121
24769.10292-3.10292
248911.2834-2.28335
249108.835231.16477
250119.969681.03032
2511211.17580.824201
252810.2515-2.25152
253119.618841.38116
25434.66727-1.66727
2551110.75770.242258
256128.422173.57783
25778.36662-1.36662
25899.99343-0.99343
2591210.52471.47529
260810.227-2.22703
261119.439441.56056
26288.2677-0.267698
2631010.7184-0.718443
26488.3196-0.319597
26579.4578-2.4578
26689.55931-1.55931
2671011.277-1.27703
26889.56229-1.56229
2691211.35430.645735
2701411.06442.93563
27179.0749-2.0749
27266.26602-0.266018
2731111.0442-0.0441816
27445.40407-1.40407
275911.1638-2.16381
27654.251610.74839
27798.843420.156575
2781110.46120.53876
2791210.21921.7808
28098.370040.629959
2811210.93541.06463
2821010.7867-0.786734
28398.861270.138727
28465.800790.199214
2851011.1433-1.14334
28697.790521.20948
2871310.89662.10338
2881210.24371.7563






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.7284270.5431470.271573
110.9321110.1357770.0678887
120.8839280.2321450.116072
130.9079960.1840080.0920039
140.8829190.2341630.117081
150.8933720.2132550.106628
160.9014440.1971110.0985557
170.8604780.2790440.139522
180.8508820.2982350.149118
190.8008760.3982490.199124
200.7415270.5169460.258473
210.6800450.6399090.319955
220.611980.7760390.38802
230.5389480.9221040.461052
240.514660.9706810.48534
250.5131780.9736450.486822
260.4799910.9599820.520009
270.4213960.8427920.578604
280.425690.8513810.57431
290.3650840.7301690.634916
300.3068020.6136040.693198
310.2543550.5087090.745645
320.2489590.4979180.751041
330.2174210.4348420.782579
340.1783690.3567380.821631
350.2178680.4357360.782132
360.2012150.402430.798785
370.1653560.3307130.834644
380.1934590.3869190.806541
390.2068940.4137880.793106
400.1779290.3558590.822071
410.1490260.2980530.850974
420.1266550.2533110.873345
430.1835680.3671370.816432
440.1511760.3023520.848824
450.1286760.2573510.871324
460.1375590.2751180.862441
470.1306730.2613470.869327
480.1097710.2195430.890229
490.09880390.1976080.901196
500.1031240.2062470.896876
510.106560.2131190.89344
520.08622550.1724510.913774
530.1044730.2089460.895527
540.0864560.1729120.913544
550.1477580.2955160.852242
560.4314090.8628180.568591
570.3884690.7769380.611531
580.346870.693740.65313
590.3069520.6139050.693048
600.3247170.6494340.675283
610.3406010.6812010.659399
620.3115220.6230440.688478
630.3157660.6315320.684234
640.2796190.5592390.720381
650.2461530.4923060.753847
660.2211430.4422870.778857
670.1974210.3948410.802579
680.1761920.3523850.823808
690.1710670.3421350.828933
700.1480450.296090.851955
710.1272340.2544680.872766
720.1088180.2176370.891182
730.09329550.1865910.906704
740.08339930.1667990.916601
750.08025020.16050.91975
760.1171980.2343950.882802
770.1037490.2074980.896251
780.08868640.1773730.911314
790.1029250.205850.897075
800.1004370.2008750.899563
810.08471860.1694370.915281
820.07110770.1422150.928892
830.06551420.1310280.934486
840.05481050.1096210.94519
850.05322570.1064510.946774
860.05546620.1109320.944534
870.04552810.09105630.954472
880.03710960.07421920.96289
890.03063070.06126140.969369
900.02707870.05415730.972921
910.0385910.07718210.961409
920.03249880.06499760.967501
930.02851540.05703080.971485
940.02915940.05831880.970841
950.03035280.06070560.969647
960.02653630.05307260.973464
970.03546020.07092030.96454
980.03017690.06035390.969823
990.02498090.04996180.975019
1000.02841730.05683460.971583
1010.02330880.04661750.976691
1020.01999880.03999760.980001
1030.01626980.03253970.98373
1040.01491520.02983040.985085
1050.01714310.03428620.982857
1060.01375870.02751740.986241
1070.01100710.02201410.988993
1080.008928290.01785660.991072
1090.01632970.03265940.98367
1100.01308720.02617430.986913
1110.01447510.02895010.985525
1120.01505950.03011890.984941
1130.01219390.02438780.987806
1140.01004770.02009540.989952
1150.01097870.02195740.989021
1160.01744740.03489470.982553
1170.01469630.02939270.985304
1180.01180980.02361960.98819
1190.01018430.02036860.989816
1200.009407330.01881470.990593
1210.0096390.0192780.990361
1220.01129730.02259460.988703
1230.01215870.02431740.987841
1240.02165530.04331060.978345
1250.01785970.03571940.98214
1260.01577010.03154010.98423
1270.01789480.03578950.982105
1280.01734960.03469910.98265
1290.01588220.03176450.984118
1300.02153160.04306320.978468
1310.04016090.08032190.959839
1320.04063120.08126240.959369
1330.04156730.08313470.958433
1340.03768290.07536580.962317
1350.03223860.06447720.967761
1360.0269830.05396590.973017
1370.02533680.05067360.974663
1380.02425740.04851470.975743
1390.02081260.04162520.979187
1400.03878950.0775790.961211
1410.03910490.07820980.960895
1420.05659350.1131870.943407
1430.04764980.09529960.95235
1440.04029570.08059150.959704
1450.03549570.07099150.964504
1460.04603640.09207280.953964
1470.04405060.08810110.955949
1480.03952910.07905820.960471
1490.03679150.0735830.963208
1500.05132580.1026520.948674
1510.05222280.1044460.947777
1520.1660170.3320340.833983
1530.1769690.3539380.823031
1540.1668290.3336590.833171
1550.237590.475180.76241
1560.2350140.4700280.764986
1570.2139870.4279740.786013
1580.2030380.4060770.796962
1590.1822090.3644180.817791
1600.1643310.3286630.835669
1610.178340.356680.82166
1620.1665360.3330720.833464
1630.1464960.2929920.853504
1640.13170.26340.8683
1650.1808650.3617290.819135
1660.1847550.3695090.815245
1670.1667640.3335280.833236
1680.2725310.5450630.727469
1690.246580.4931590.75342
1700.2272650.454530.772735
1710.2061480.4122970.793852
1720.2444810.4889610.755519
1730.2186760.4373530.781324
1740.2068460.4136920.793154
1750.1835310.3670620.816469
1760.1630160.3260330.836984
1770.1431490.2862980.856851
1780.1263450.2526910.873655
1790.1406250.2812490.859375
1800.1485180.2970370.851482
1810.1404460.2808910.859554
1820.3303910.6607820.669609
1830.3066850.613370.693315
1840.2826070.5652140.717393
1850.299880.5997590.70012
1860.2887430.5774860.711257
1870.3784820.7569650.621518
1880.3837470.7674940.616253
1890.3550260.7100520.644974
1900.7196950.560610.280305
1910.6893070.6213850.310693
1920.6592340.6815320.340766
1930.6444710.7110580.355529
1940.6632970.6734070.336703
1950.6376650.724670.362335
1960.6136210.7727580.386379
1970.5907380.8185240.409262
1980.5586690.8826630.441331
1990.5257580.9484840.474242
2000.5976390.8047220.402361
2010.6420670.7158660.357933
2020.6073080.7853840.392692
2030.5712960.8574090.428704
2040.5434230.9131530.456577
2050.5340260.9319480.465974
2060.4987890.9975780.501211
2070.5671490.8657010.432851
2080.626170.7476610.37383
2090.5957750.808450.404225
2100.6267980.7464050.373202
2110.5978610.8042790.402139
2120.559450.8811010.44055
2130.5257770.9484460.474223
2140.4868230.9736450.513177
2150.4750730.9501460.524927
2160.463330.926660.53667
2170.5010020.9979950.498998
2180.4605160.9210310.539484
2190.4480830.8961660.551917
2200.4088730.8177450.591127
2210.3757270.7514540.624273
2220.3377520.6755030.662248
2230.3097830.6195670.690217
2240.2786930.5573860.721307
2250.2451360.4902710.754864
2260.3488110.6976230.651189
2270.394250.7884990.60575
2280.6983740.6032530.301626
2290.680.6399990.32
2300.6401460.7197090.359854
2310.6343180.7313650.365682
2320.6314470.7371050.368553
2330.6728830.6542350.327117
2340.6486880.7026240.351312
2350.6088170.7823660.391183
2360.5707390.8585230.429261
2370.6373060.7253880.362694
2380.8518330.2963330.148167
2390.9221310.1557380.077869
2400.9055630.1888740.0944372
2410.8934750.2130490.106525
2420.8842910.2314180.115709
2430.8606710.2786570.139329
2440.8308840.3382330.169116
2450.8325450.3349110.167455
2460.8084980.3830040.191502
2470.8625890.2748220.137411
2480.8835310.2329380.116469
2490.8662660.2674680.133734
2500.8433030.3133940.156697
2510.8278090.3443830.172191
2520.8219110.3561780.178089
2530.8015430.3969150.198457
2540.7700860.4598270.229914
2550.7221550.555690.277845
2560.8759560.2480880.124044
2570.8494590.3010820.150541
2580.8263460.3473080.173654
2590.8319230.3361540.168077
2600.8486360.3027280.151364
2610.8451630.3096750.154837
2620.8013960.3972080.198604
2630.778310.4433790.22169
2640.7197150.5605690.280285
2650.7723810.4552380.227619
2660.8399230.3201550.160077
2670.9269180.1461640.0730822
2680.9066720.1866570.0933285
2690.8650080.2699840.134992
2700.9266590.1466820.0733408
2710.9045380.1909240.0954618
2720.9434210.1131570.0565786
2730.9020430.1959150.0979573
2740.9030720.1938570.0969283
2750.8899340.2201320.110066
2760.8117620.3764760.188238
2770.7199780.5600450.280022
2780.5555160.8889680.444484

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.728427 & 0.543147 & 0.271573 \tabularnewline
11 & 0.932111 & 0.135777 & 0.0678887 \tabularnewline
12 & 0.883928 & 0.232145 & 0.116072 \tabularnewline
13 & 0.907996 & 0.184008 & 0.0920039 \tabularnewline
14 & 0.882919 & 0.234163 & 0.117081 \tabularnewline
15 & 0.893372 & 0.213255 & 0.106628 \tabularnewline
16 & 0.901444 & 0.197111 & 0.0985557 \tabularnewline
17 & 0.860478 & 0.279044 & 0.139522 \tabularnewline
18 & 0.850882 & 0.298235 & 0.149118 \tabularnewline
19 & 0.800876 & 0.398249 & 0.199124 \tabularnewline
20 & 0.741527 & 0.516946 & 0.258473 \tabularnewline
21 & 0.680045 & 0.639909 & 0.319955 \tabularnewline
22 & 0.61198 & 0.776039 & 0.38802 \tabularnewline
23 & 0.538948 & 0.922104 & 0.461052 \tabularnewline
24 & 0.51466 & 0.970681 & 0.48534 \tabularnewline
25 & 0.513178 & 0.973645 & 0.486822 \tabularnewline
26 & 0.479991 & 0.959982 & 0.520009 \tabularnewline
27 & 0.421396 & 0.842792 & 0.578604 \tabularnewline
28 & 0.42569 & 0.851381 & 0.57431 \tabularnewline
29 & 0.365084 & 0.730169 & 0.634916 \tabularnewline
30 & 0.306802 & 0.613604 & 0.693198 \tabularnewline
31 & 0.254355 & 0.508709 & 0.745645 \tabularnewline
32 & 0.248959 & 0.497918 & 0.751041 \tabularnewline
33 & 0.217421 & 0.434842 & 0.782579 \tabularnewline
34 & 0.178369 & 0.356738 & 0.821631 \tabularnewline
35 & 0.217868 & 0.435736 & 0.782132 \tabularnewline
36 & 0.201215 & 0.40243 & 0.798785 \tabularnewline
37 & 0.165356 & 0.330713 & 0.834644 \tabularnewline
38 & 0.193459 & 0.386919 & 0.806541 \tabularnewline
39 & 0.206894 & 0.413788 & 0.793106 \tabularnewline
40 & 0.177929 & 0.355859 & 0.822071 \tabularnewline
41 & 0.149026 & 0.298053 & 0.850974 \tabularnewline
42 & 0.126655 & 0.253311 & 0.873345 \tabularnewline
43 & 0.183568 & 0.367137 & 0.816432 \tabularnewline
44 & 0.151176 & 0.302352 & 0.848824 \tabularnewline
45 & 0.128676 & 0.257351 & 0.871324 \tabularnewline
46 & 0.137559 & 0.275118 & 0.862441 \tabularnewline
47 & 0.130673 & 0.261347 & 0.869327 \tabularnewline
48 & 0.109771 & 0.219543 & 0.890229 \tabularnewline
49 & 0.0988039 & 0.197608 & 0.901196 \tabularnewline
50 & 0.103124 & 0.206247 & 0.896876 \tabularnewline
51 & 0.10656 & 0.213119 & 0.89344 \tabularnewline
52 & 0.0862255 & 0.172451 & 0.913774 \tabularnewline
53 & 0.104473 & 0.208946 & 0.895527 \tabularnewline
54 & 0.086456 & 0.172912 & 0.913544 \tabularnewline
55 & 0.147758 & 0.295516 & 0.852242 \tabularnewline
56 & 0.431409 & 0.862818 & 0.568591 \tabularnewline
57 & 0.388469 & 0.776938 & 0.611531 \tabularnewline
58 & 0.34687 & 0.69374 & 0.65313 \tabularnewline
59 & 0.306952 & 0.613905 & 0.693048 \tabularnewline
60 & 0.324717 & 0.649434 & 0.675283 \tabularnewline
61 & 0.340601 & 0.681201 & 0.659399 \tabularnewline
62 & 0.311522 & 0.623044 & 0.688478 \tabularnewline
63 & 0.315766 & 0.631532 & 0.684234 \tabularnewline
64 & 0.279619 & 0.559239 & 0.720381 \tabularnewline
65 & 0.246153 & 0.492306 & 0.753847 \tabularnewline
66 & 0.221143 & 0.442287 & 0.778857 \tabularnewline
67 & 0.197421 & 0.394841 & 0.802579 \tabularnewline
68 & 0.176192 & 0.352385 & 0.823808 \tabularnewline
69 & 0.171067 & 0.342135 & 0.828933 \tabularnewline
70 & 0.148045 & 0.29609 & 0.851955 \tabularnewline
71 & 0.127234 & 0.254468 & 0.872766 \tabularnewline
72 & 0.108818 & 0.217637 & 0.891182 \tabularnewline
73 & 0.0932955 & 0.186591 & 0.906704 \tabularnewline
74 & 0.0833993 & 0.166799 & 0.916601 \tabularnewline
75 & 0.0802502 & 0.1605 & 0.91975 \tabularnewline
76 & 0.117198 & 0.234395 & 0.882802 \tabularnewline
77 & 0.103749 & 0.207498 & 0.896251 \tabularnewline
78 & 0.0886864 & 0.177373 & 0.911314 \tabularnewline
79 & 0.102925 & 0.20585 & 0.897075 \tabularnewline
80 & 0.100437 & 0.200875 & 0.899563 \tabularnewline
81 & 0.0847186 & 0.169437 & 0.915281 \tabularnewline
82 & 0.0711077 & 0.142215 & 0.928892 \tabularnewline
83 & 0.0655142 & 0.131028 & 0.934486 \tabularnewline
84 & 0.0548105 & 0.109621 & 0.94519 \tabularnewline
85 & 0.0532257 & 0.106451 & 0.946774 \tabularnewline
86 & 0.0554662 & 0.110932 & 0.944534 \tabularnewline
87 & 0.0455281 & 0.0910563 & 0.954472 \tabularnewline
88 & 0.0371096 & 0.0742192 & 0.96289 \tabularnewline
89 & 0.0306307 & 0.0612614 & 0.969369 \tabularnewline
90 & 0.0270787 & 0.0541573 & 0.972921 \tabularnewline
91 & 0.038591 & 0.0771821 & 0.961409 \tabularnewline
92 & 0.0324988 & 0.0649976 & 0.967501 \tabularnewline
93 & 0.0285154 & 0.0570308 & 0.971485 \tabularnewline
94 & 0.0291594 & 0.0583188 & 0.970841 \tabularnewline
95 & 0.0303528 & 0.0607056 & 0.969647 \tabularnewline
96 & 0.0265363 & 0.0530726 & 0.973464 \tabularnewline
97 & 0.0354602 & 0.0709203 & 0.96454 \tabularnewline
98 & 0.0301769 & 0.0603539 & 0.969823 \tabularnewline
99 & 0.0249809 & 0.0499618 & 0.975019 \tabularnewline
100 & 0.0284173 & 0.0568346 & 0.971583 \tabularnewline
101 & 0.0233088 & 0.0466175 & 0.976691 \tabularnewline
102 & 0.0199988 & 0.0399976 & 0.980001 \tabularnewline
103 & 0.0162698 & 0.0325397 & 0.98373 \tabularnewline
104 & 0.0149152 & 0.0298304 & 0.985085 \tabularnewline
105 & 0.0171431 & 0.0342862 & 0.982857 \tabularnewline
106 & 0.0137587 & 0.0275174 & 0.986241 \tabularnewline
107 & 0.0110071 & 0.0220141 & 0.988993 \tabularnewline
108 & 0.00892829 & 0.0178566 & 0.991072 \tabularnewline
109 & 0.0163297 & 0.0326594 & 0.98367 \tabularnewline
110 & 0.0130872 & 0.0261743 & 0.986913 \tabularnewline
111 & 0.0144751 & 0.0289501 & 0.985525 \tabularnewline
112 & 0.0150595 & 0.0301189 & 0.984941 \tabularnewline
113 & 0.0121939 & 0.0243878 & 0.987806 \tabularnewline
114 & 0.0100477 & 0.0200954 & 0.989952 \tabularnewline
115 & 0.0109787 & 0.0219574 & 0.989021 \tabularnewline
116 & 0.0174474 & 0.0348947 & 0.982553 \tabularnewline
117 & 0.0146963 & 0.0293927 & 0.985304 \tabularnewline
118 & 0.0118098 & 0.0236196 & 0.98819 \tabularnewline
119 & 0.0101843 & 0.0203686 & 0.989816 \tabularnewline
120 & 0.00940733 & 0.0188147 & 0.990593 \tabularnewline
121 & 0.009639 & 0.019278 & 0.990361 \tabularnewline
122 & 0.0112973 & 0.0225946 & 0.988703 \tabularnewline
123 & 0.0121587 & 0.0243174 & 0.987841 \tabularnewline
124 & 0.0216553 & 0.0433106 & 0.978345 \tabularnewline
125 & 0.0178597 & 0.0357194 & 0.98214 \tabularnewline
126 & 0.0157701 & 0.0315401 & 0.98423 \tabularnewline
127 & 0.0178948 & 0.0357895 & 0.982105 \tabularnewline
128 & 0.0173496 & 0.0346991 & 0.98265 \tabularnewline
129 & 0.0158822 & 0.0317645 & 0.984118 \tabularnewline
130 & 0.0215316 & 0.0430632 & 0.978468 \tabularnewline
131 & 0.0401609 & 0.0803219 & 0.959839 \tabularnewline
132 & 0.0406312 & 0.0812624 & 0.959369 \tabularnewline
133 & 0.0415673 & 0.0831347 & 0.958433 \tabularnewline
134 & 0.0376829 & 0.0753658 & 0.962317 \tabularnewline
135 & 0.0322386 & 0.0644772 & 0.967761 \tabularnewline
136 & 0.026983 & 0.0539659 & 0.973017 \tabularnewline
137 & 0.0253368 & 0.0506736 & 0.974663 \tabularnewline
138 & 0.0242574 & 0.0485147 & 0.975743 \tabularnewline
139 & 0.0208126 & 0.0416252 & 0.979187 \tabularnewline
140 & 0.0387895 & 0.077579 & 0.961211 \tabularnewline
141 & 0.0391049 & 0.0782098 & 0.960895 \tabularnewline
142 & 0.0565935 & 0.113187 & 0.943407 \tabularnewline
143 & 0.0476498 & 0.0952996 & 0.95235 \tabularnewline
144 & 0.0402957 & 0.0805915 & 0.959704 \tabularnewline
145 & 0.0354957 & 0.0709915 & 0.964504 \tabularnewline
146 & 0.0460364 & 0.0920728 & 0.953964 \tabularnewline
147 & 0.0440506 & 0.0881011 & 0.955949 \tabularnewline
148 & 0.0395291 & 0.0790582 & 0.960471 \tabularnewline
149 & 0.0367915 & 0.073583 & 0.963208 \tabularnewline
150 & 0.0513258 & 0.102652 & 0.948674 \tabularnewline
151 & 0.0522228 & 0.104446 & 0.947777 \tabularnewline
152 & 0.166017 & 0.332034 & 0.833983 \tabularnewline
153 & 0.176969 & 0.353938 & 0.823031 \tabularnewline
154 & 0.166829 & 0.333659 & 0.833171 \tabularnewline
155 & 0.23759 & 0.47518 & 0.76241 \tabularnewline
156 & 0.235014 & 0.470028 & 0.764986 \tabularnewline
157 & 0.213987 & 0.427974 & 0.786013 \tabularnewline
158 & 0.203038 & 0.406077 & 0.796962 \tabularnewline
159 & 0.182209 & 0.364418 & 0.817791 \tabularnewline
160 & 0.164331 & 0.328663 & 0.835669 \tabularnewline
161 & 0.17834 & 0.35668 & 0.82166 \tabularnewline
162 & 0.166536 & 0.333072 & 0.833464 \tabularnewline
163 & 0.146496 & 0.292992 & 0.853504 \tabularnewline
164 & 0.1317 & 0.2634 & 0.8683 \tabularnewline
165 & 0.180865 & 0.361729 & 0.819135 \tabularnewline
166 & 0.184755 & 0.369509 & 0.815245 \tabularnewline
167 & 0.166764 & 0.333528 & 0.833236 \tabularnewline
168 & 0.272531 & 0.545063 & 0.727469 \tabularnewline
169 & 0.24658 & 0.493159 & 0.75342 \tabularnewline
170 & 0.227265 & 0.45453 & 0.772735 \tabularnewline
171 & 0.206148 & 0.412297 & 0.793852 \tabularnewline
172 & 0.244481 & 0.488961 & 0.755519 \tabularnewline
173 & 0.218676 & 0.437353 & 0.781324 \tabularnewline
174 & 0.206846 & 0.413692 & 0.793154 \tabularnewline
175 & 0.183531 & 0.367062 & 0.816469 \tabularnewline
176 & 0.163016 & 0.326033 & 0.836984 \tabularnewline
177 & 0.143149 & 0.286298 & 0.856851 \tabularnewline
178 & 0.126345 & 0.252691 & 0.873655 \tabularnewline
179 & 0.140625 & 0.281249 & 0.859375 \tabularnewline
180 & 0.148518 & 0.297037 & 0.851482 \tabularnewline
181 & 0.140446 & 0.280891 & 0.859554 \tabularnewline
182 & 0.330391 & 0.660782 & 0.669609 \tabularnewline
183 & 0.306685 & 0.61337 & 0.693315 \tabularnewline
184 & 0.282607 & 0.565214 & 0.717393 \tabularnewline
185 & 0.29988 & 0.599759 & 0.70012 \tabularnewline
186 & 0.288743 & 0.577486 & 0.711257 \tabularnewline
187 & 0.378482 & 0.756965 & 0.621518 \tabularnewline
188 & 0.383747 & 0.767494 & 0.616253 \tabularnewline
189 & 0.355026 & 0.710052 & 0.644974 \tabularnewline
190 & 0.719695 & 0.56061 & 0.280305 \tabularnewline
191 & 0.689307 & 0.621385 & 0.310693 \tabularnewline
192 & 0.659234 & 0.681532 & 0.340766 \tabularnewline
193 & 0.644471 & 0.711058 & 0.355529 \tabularnewline
194 & 0.663297 & 0.673407 & 0.336703 \tabularnewline
195 & 0.637665 & 0.72467 & 0.362335 \tabularnewline
196 & 0.613621 & 0.772758 & 0.386379 \tabularnewline
197 & 0.590738 & 0.818524 & 0.409262 \tabularnewline
198 & 0.558669 & 0.882663 & 0.441331 \tabularnewline
199 & 0.525758 & 0.948484 & 0.474242 \tabularnewline
200 & 0.597639 & 0.804722 & 0.402361 \tabularnewline
201 & 0.642067 & 0.715866 & 0.357933 \tabularnewline
202 & 0.607308 & 0.785384 & 0.392692 \tabularnewline
203 & 0.571296 & 0.857409 & 0.428704 \tabularnewline
204 & 0.543423 & 0.913153 & 0.456577 \tabularnewline
205 & 0.534026 & 0.931948 & 0.465974 \tabularnewline
206 & 0.498789 & 0.997578 & 0.501211 \tabularnewline
207 & 0.567149 & 0.865701 & 0.432851 \tabularnewline
208 & 0.62617 & 0.747661 & 0.37383 \tabularnewline
209 & 0.595775 & 0.80845 & 0.404225 \tabularnewline
210 & 0.626798 & 0.746405 & 0.373202 \tabularnewline
211 & 0.597861 & 0.804279 & 0.402139 \tabularnewline
212 & 0.55945 & 0.881101 & 0.44055 \tabularnewline
213 & 0.525777 & 0.948446 & 0.474223 \tabularnewline
214 & 0.486823 & 0.973645 & 0.513177 \tabularnewline
215 & 0.475073 & 0.950146 & 0.524927 \tabularnewline
216 & 0.46333 & 0.92666 & 0.53667 \tabularnewline
217 & 0.501002 & 0.997995 & 0.498998 \tabularnewline
218 & 0.460516 & 0.921031 & 0.539484 \tabularnewline
219 & 0.448083 & 0.896166 & 0.551917 \tabularnewline
220 & 0.408873 & 0.817745 & 0.591127 \tabularnewline
221 & 0.375727 & 0.751454 & 0.624273 \tabularnewline
222 & 0.337752 & 0.675503 & 0.662248 \tabularnewline
223 & 0.309783 & 0.619567 & 0.690217 \tabularnewline
224 & 0.278693 & 0.557386 & 0.721307 \tabularnewline
225 & 0.245136 & 0.490271 & 0.754864 \tabularnewline
226 & 0.348811 & 0.697623 & 0.651189 \tabularnewline
227 & 0.39425 & 0.788499 & 0.60575 \tabularnewline
228 & 0.698374 & 0.603253 & 0.301626 \tabularnewline
229 & 0.68 & 0.639999 & 0.32 \tabularnewline
230 & 0.640146 & 0.719709 & 0.359854 \tabularnewline
231 & 0.634318 & 0.731365 & 0.365682 \tabularnewline
232 & 0.631447 & 0.737105 & 0.368553 \tabularnewline
233 & 0.672883 & 0.654235 & 0.327117 \tabularnewline
234 & 0.648688 & 0.702624 & 0.351312 \tabularnewline
235 & 0.608817 & 0.782366 & 0.391183 \tabularnewline
236 & 0.570739 & 0.858523 & 0.429261 \tabularnewline
237 & 0.637306 & 0.725388 & 0.362694 \tabularnewline
238 & 0.851833 & 0.296333 & 0.148167 \tabularnewline
239 & 0.922131 & 0.155738 & 0.077869 \tabularnewline
240 & 0.905563 & 0.188874 & 0.0944372 \tabularnewline
241 & 0.893475 & 0.213049 & 0.106525 \tabularnewline
242 & 0.884291 & 0.231418 & 0.115709 \tabularnewline
243 & 0.860671 & 0.278657 & 0.139329 \tabularnewline
244 & 0.830884 & 0.338233 & 0.169116 \tabularnewline
245 & 0.832545 & 0.334911 & 0.167455 \tabularnewline
246 & 0.808498 & 0.383004 & 0.191502 \tabularnewline
247 & 0.862589 & 0.274822 & 0.137411 \tabularnewline
248 & 0.883531 & 0.232938 & 0.116469 \tabularnewline
249 & 0.866266 & 0.267468 & 0.133734 \tabularnewline
250 & 0.843303 & 0.313394 & 0.156697 \tabularnewline
251 & 0.827809 & 0.344383 & 0.172191 \tabularnewline
252 & 0.821911 & 0.356178 & 0.178089 \tabularnewline
253 & 0.801543 & 0.396915 & 0.198457 \tabularnewline
254 & 0.770086 & 0.459827 & 0.229914 \tabularnewline
255 & 0.722155 & 0.55569 & 0.277845 \tabularnewline
256 & 0.875956 & 0.248088 & 0.124044 \tabularnewline
257 & 0.849459 & 0.301082 & 0.150541 \tabularnewline
258 & 0.826346 & 0.347308 & 0.173654 \tabularnewline
259 & 0.831923 & 0.336154 & 0.168077 \tabularnewline
260 & 0.848636 & 0.302728 & 0.151364 \tabularnewline
261 & 0.845163 & 0.309675 & 0.154837 \tabularnewline
262 & 0.801396 & 0.397208 & 0.198604 \tabularnewline
263 & 0.77831 & 0.443379 & 0.22169 \tabularnewline
264 & 0.719715 & 0.560569 & 0.280285 \tabularnewline
265 & 0.772381 & 0.455238 & 0.227619 \tabularnewline
266 & 0.839923 & 0.320155 & 0.160077 \tabularnewline
267 & 0.926918 & 0.146164 & 0.0730822 \tabularnewline
268 & 0.906672 & 0.186657 & 0.0933285 \tabularnewline
269 & 0.865008 & 0.269984 & 0.134992 \tabularnewline
270 & 0.926659 & 0.146682 & 0.0733408 \tabularnewline
271 & 0.904538 & 0.190924 & 0.0954618 \tabularnewline
272 & 0.943421 & 0.113157 & 0.0565786 \tabularnewline
273 & 0.902043 & 0.195915 & 0.0979573 \tabularnewline
274 & 0.903072 & 0.193857 & 0.0969283 \tabularnewline
275 & 0.889934 & 0.220132 & 0.110066 \tabularnewline
276 & 0.811762 & 0.376476 & 0.188238 \tabularnewline
277 & 0.719978 & 0.560045 & 0.280022 \tabularnewline
278 & 0.555516 & 0.888968 & 0.444484 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231417&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]0.728427[/C][C]0.543147[/C][C]0.271573[/C][/ROW]
[ROW][C]11[/C][C]0.932111[/C][C]0.135777[/C][C]0.0678887[/C][/ROW]
[ROW][C]12[/C][C]0.883928[/C][C]0.232145[/C][C]0.116072[/C][/ROW]
[ROW][C]13[/C][C]0.907996[/C][C]0.184008[/C][C]0.0920039[/C][/ROW]
[ROW][C]14[/C][C]0.882919[/C][C]0.234163[/C][C]0.117081[/C][/ROW]
[ROW][C]15[/C][C]0.893372[/C][C]0.213255[/C][C]0.106628[/C][/ROW]
[ROW][C]16[/C][C]0.901444[/C][C]0.197111[/C][C]0.0985557[/C][/ROW]
[ROW][C]17[/C][C]0.860478[/C][C]0.279044[/C][C]0.139522[/C][/ROW]
[ROW][C]18[/C][C]0.850882[/C][C]0.298235[/C][C]0.149118[/C][/ROW]
[ROW][C]19[/C][C]0.800876[/C][C]0.398249[/C][C]0.199124[/C][/ROW]
[ROW][C]20[/C][C]0.741527[/C][C]0.516946[/C][C]0.258473[/C][/ROW]
[ROW][C]21[/C][C]0.680045[/C][C]0.639909[/C][C]0.319955[/C][/ROW]
[ROW][C]22[/C][C]0.61198[/C][C]0.776039[/C][C]0.38802[/C][/ROW]
[ROW][C]23[/C][C]0.538948[/C][C]0.922104[/C][C]0.461052[/C][/ROW]
[ROW][C]24[/C][C]0.51466[/C][C]0.970681[/C][C]0.48534[/C][/ROW]
[ROW][C]25[/C][C]0.513178[/C][C]0.973645[/C][C]0.486822[/C][/ROW]
[ROW][C]26[/C][C]0.479991[/C][C]0.959982[/C][C]0.520009[/C][/ROW]
[ROW][C]27[/C][C]0.421396[/C][C]0.842792[/C][C]0.578604[/C][/ROW]
[ROW][C]28[/C][C]0.42569[/C][C]0.851381[/C][C]0.57431[/C][/ROW]
[ROW][C]29[/C][C]0.365084[/C][C]0.730169[/C][C]0.634916[/C][/ROW]
[ROW][C]30[/C][C]0.306802[/C][C]0.613604[/C][C]0.693198[/C][/ROW]
[ROW][C]31[/C][C]0.254355[/C][C]0.508709[/C][C]0.745645[/C][/ROW]
[ROW][C]32[/C][C]0.248959[/C][C]0.497918[/C][C]0.751041[/C][/ROW]
[ROW][C]33[/C][C]0.217421[/C][C]0.434842[/C][C]0.782579[/C][/ROW]
[ROW][C]34[/C][C]0.178369[/C][C]0.356738[/C][C]0.821631[/C][/ROW]
[ROW][C]35[/C][C]0.217868[/C][C]0.435736[/C][C]0.782132[/C][/ROW]
[ROW][C]36[/C][C]0.201215[/C][C]0.40243[/C][C]0.798785[/C][/ROW]
[ROW][C]37[/C][C]0.165356[/C][C]0.330713[/C][C]0.834644[/C][/ROW]
[ROW][C]38[/C][C]0.193459[/C][C]0.386919[/C][C]0.806541[/C][/ROW]
[ROW][C]39[/C][C]0.206894[/C][C]0.413788[/C][C]0.793106[/C][/ROW]
[ROW][C]40[/C][C]0.177929[/C][C]0.355859[/C][C]0.822071[/C][/ROW]
[ROW][C]41[/C][C]0.149026[/C][C]0.298053[/C][C]0.850974[/C][/ROW]
[ROW][C]42[/C][C]0.126655[/C][C]0.253311[/C][C]0.873345[/C][/ROW]
[ROW][C]43[/C][C]0.183568[/C][C]0.367137[/C][C]0.816432[/C][/ROW]
[ROW][C]44[/C][C]0.151176[/C][C]0.302352[/C][C]0.848824[/C][/ROW]
[ROW][C]45[/C][C]0.128676[/C][C]0.257351[/C][C]0.871324[/C][/ROW]
[ROW][C]46[/C][C]0.137559[/C][C]0.275118[/C][C]0.862441[/C][/ROW]
[ROW][C]47[/C][C]0.130673[/C][C]0.261347[/C][C]0.869327[/C][/ROW]
[ROW][C]48[/C][C]0.109771[/C][C]0.219543[/C][C]0.890229[/C][/ROW]
[ROW][C]49[/C][C]0.0988039[/C][C]0.197608[/C][C]0.901196[/C][/ROW]
[ROW][C]50[/C][C]0.103124[/C][C]0.206247[/C][C]0.896876[/C][/ROW]
[ROW][C]51[/C][C]0.10656[/C][C]0.213119[/C][C]0.89344[/C][/ROW]
[ROW][C]52[/C][C]0.0862255[/C][C]0.172451[/C][C]0.913774[/C][/ROW]
[ROW][C]53[/C][C]0.104473[/C][C]0.208946[/C][C]0.895527[/C][/ROW]
[ROW][C]54[/C][C]0.086456[/C][C]0.172912[/C][C]0.913544[/C][/ROW]
[ROW][C]55[/C][C]0.147758[/C][C]0.295516[/C][C]0.852242[/C][/ROW]
[ROW][C]56[/C][C]0.431409[/C][C]0.862818[/C][C]0.568591[/C][/ROW]
[ROW][C]57[/C][C]0.388469[/C][C]0.776938[/C][C]0.611531[/C][/ROW]
[ROW][C]58[/C][C]0.34687[/C][C]0.69374[/C][C]0.65313[/C][/ROW]
[ROW][C]59[/C][C]0.306952[/C][C]0.613905[/C][C]0.693048[/C][/ROW]
[ROW][C]60[/C][C]0.324717[/C][C]0.649434[/C][C]0.675283[/C][/ROW]
[ROW][C]61[/C][C]0.340601[/C][C]0.681201[/C][C]0.659399[/C][/ROW]
[ROW][C]62[/C][C]0.311522[/C][C]0.623044[/C][C]0.688478[/C][/ROW]
[ROW][C]63[/C][C]0.315766[/C][C]0.631532[/C][C]0.684234[/C][/ROW]
[ROW][C]64[/C][C]0.279619[/C][C]0.559239[/C][C]0.720381[/C][/ROW]
[ROW][C]65[/C][C]0.246153[/C][C]0.492306[/C][C]0.753847[/C][/ROW]
[ROW][C]66[/C][C]0.221143[/C][C]0.442287[/C][C]0.778857[/C][/ROW]
[ROW][C]67[/C][C]0.197421[/C][C]0.394841[/C][C]0.802579[/C][/ROW]
[ROW][C]68[/C][C]0.176192[/C][C]0.352385[/C][C]0.823808[/C][/ROW]
[ROW][C]69[/C][C]0.171067[/C][C]0.342135[/C][C]0.828933[/C][/ROW]
[ROW][C]70[/C][C]0.148045[/C][C]0.29609[/C][C]0.851955[/C][/ROW]
[ROW][C]71[/C][C]0.127234[/C][C]0.254468[/C][C]0.872766[/C][/ROW]
[ROW][C]72[/C][C]0.108818[/C][C]0.217637[/C][C]0.891182[/C][/ROW]
[ROW][C]73[/C][C]0.0932955[/C][C]0.186591[/C][C]0.906704[/C][/ROW]
[ROW][C]74[/C][C]0.0833993[/C][C]0.166799[/C][C]0.916601[/C][/ROW]
[ROW][C]75[/C][C]0.0802502[/C][C]0.1605[/C][C]0.91975[/C][/ROW]
[ROW][C]76[/C][C]0.117198[/C][C]0.234395[/C][C]0.882802[/C][/ROW]
[ROW][C]77[/C][C]0.103749[/C][C]0.207498[/C][C]0.896251[/C][/ROW]
[ROW][C]78[/C][C]0.0886864[/C][C]0.177373[/C][C]0.911314[/C][/ROW]
[ROW][C]79[/C][C]0.102925[/C][C]0.20585[/C][C]0.897075[/C][/ROW]
[ROW][C]80[/C][C]0.100437[/C][C]0.200875[/C][C]0.899563[/C][/ROW]
[ROW][C]81[/C][C]0.0847186[/C][C]0.169437[/C][C]0.915281[/C][/ROW]
[ROW][C]82[/C][C]0.0711077[/C][C]0.142215[/C][C]0.928892[/C][/ROW]
[ROW][C]83[/C][C]0.0655142[/C][C]0.131028[/C][C]0.934486[/C][/ROW]
[ROW][C]84[/C][C]0.0548105[/C][C]0.109621[/C][C]0.94519[/C][/ROW]
[ROW][C]85[/C][C]0.0532257[/C][C]0.106451[/C][C]0.946774[/C][/ROW]
[ROW][C]86[/C][C]0.0554662[/C][C]0.110932[/C][C]0.944534[/C][/ROW]
[ROW][C]87[/C][C]0.0455281[/C][C]0.0910563[/C][C]0.954472[/C][/ROW]
[ROW][C]88[/C][C]0.0371096[/C][C]0.0742192[/C][C]0.96289[/C][/ROW]
[ROW][C]89[/C][C]0.0306307[/C][C]0.0612614[/C][C]0.969369[/C][/ROW]
[ROW][C]90[/C][C]0.0270787[/C][C]0.0541573[/C][C]0.972921[/C][/ROW]
[ROW][C]91[/C][C]0.038591[/C][C]0.0771821[/C][C]0.961409[/C][/ROW]
[ROW][C]92[/C][C]0.0324988[/C][C]0.0649976[/C][C]0.967501[/C][/ROW]
[ROW][C]93[/C][C]0.0285154[/C][C]0.0570308[/C][C]0.971485[/C][/ROW]
[ROW][C]94[/C][C]0.0291594[/C][C]0.0583188[/C][C]0.970841[/C][/ROW]
[ROW][C]95[/C][C]0.0303528[/C][C]0.0607056[/C][C]0.969647[/C][/ROW]
[ROW][C]96[/C][C]0.0265363[/C][C]0.0530726[/C][C]0.973464[/C][/ROW]
[ROW][C]97[/C][C]0.0354602[/C][C]0.0709203[/C][C]0.96454[/C][/ROW]
[ROW][C]98[/C][C]0.0301769[/C][C]0.0603539[/C][C]0.969823[/C][/ROW]
[ROW][C]99[/C][C]0.0249809[/C][C]0.0499618[/C][C]0.975019[/C][/ROW]
[ROW][C]100[/C][C]0.0284173[/C][C]0.0568346[/C][C]0.971583[/C][/ROW]
[ROW][C]101[/C][C]0.0233088[/C][C]0.0466175[/C][C]0.976691[/C][/ROW]
[ROW][C]102[/C][C]0.0199988[/C][C]0.0399976[/C][C]0.980001[/C][/ROW]
[ROW][C]103[/C][C]0.0162698[/C][C]0.0325397[/C][C]0.98373[/C][/ROW]
[ROW][C]104[/C][C]0.0149152[/C][C]0.0298304[/C][C]0.985085[/C][/ROW]
[ROW][C]105[/C][C]0.0171431[/C][C]0.0342862[/C][C]0.982857[/C][/ROW]
[ROW][C]106[/C][C]0.0137587[/C][C]0.0275174[/C][C]0.986241[/C][/ROW]
[ROW][C]107[/C][C]0.0110071[/C][C]0.0220141[/C][C]0.988993[/C][/ROW]
[ROW][C]108[/C][C]0.00892829[/C][C]0.0178566[/C][C]0.991072[/C][/ROW]
[ROW][C]109[/C][C]0.0163297[/C][C]0.0326594[/C][C]0.98367[/C][/ROW]
[ROW][C]110[/C][C]0.0130872[/C][C]0.0261743[/C][C]0.986913[/C][/ROW]
[ROW][C]111[/C][C]0.0144751[/C][C]0.0289501[/C][C]0.985525[/C][/ROW]
[ROW][C]112[/C][C]0.0150595[/C][C]0.0301189[/C][C]0.984941[/C][/ROW]
[ROW][C]113[/C][C]0.0121939[/C][C]0.0243878[/C][C]0.987806[/C][/ROW]
[ROW][C]114[/C][C]0.0100477[/C][C]0.0200954[/C][C]0.989952[/C][/ROW]
[ROW][C]115[/C][C]0.0109787[/C][C]0.0219574[/C][C]0.989021[/C][/ROW]
[ROW][C]116[/C][C]0.0174474[/C][C]0.0348947[/C][C]0.982553[/C][/ROW]
[ROW][C]117[/C][C]0.0146963[/C][C]0.0293927[/C][C]0.985304[/C][/ROW]
[ROW][C]118[/C][C]0.0118098[/C][C]0.0236196[/C][C]0.98819[/C][/ROW]
[ROW][C]119[/C][C]0.0101843[/C][C]0.0203686[/C][C]0.989816[/C][/ROW]
[ROW][C]120[/C][C]0.00940733[/C][C]0.0188147[/C][C]0.990593[/C][/ROW]
[ROW][C]121[/C][C]0.009639[/C][C]0.019278[/C][C]0.990361[/C][/ROW]
[ROW][C]122[/C][C]0.0112973[/C][C]0.0225946[/C][C]0.988703[/C][/ROW]
[ROW][C]123[/C][C]0.0121587[/C][C]0.0243174[/C][C]0.987841[/C][/ROW]
[ROW][C]124[/C][C]0.0216553[/C][C]0.0433106[/C][C]0.978345[/C][/ROW]
[ROW][C]125[/C][C]0.0178597[/C][C]0.0357194[/C][C]0.98214[/C][/ROW]
[ROW][C]126[/C][C]0.0157701[/C][C]0.0315401[/C][C]0.98423[/C][/ROW]
[ROW][C]127[/C][C]0.0178948[/C][C]0.0357895[/C][C]0.982105[/C][/ROW]
[ROW][C]128[/C][C]0.0173496[/C][C]0.0346991[/C][C]0.98265[/C][/ROW]
[ROW][C]129[/C][C]0.0158822[/C][C]0.0317645[/C][C]0.984118[/C][/ROW]
[ROW][C]130[/C][C]0.0215316[/C][C]0.0430632[/C][C]0.978468[/C][/ROW]
[ROW][C]131[/C][C]0.0401609[/C][C]0.0803219[/C][C]0.959839[/C][/ROW]
[ROW][C]132[/C][C]0.0406312[/C][C]0.0812624[/C][C]0.959369[/C][/ROW]
[ROW][C]133[/C][C]0.0415673[/C][C]0.0831347[/C][C]0.958433[/C][/ROW]
[ROW][C]134[/C][C]0.0376829[/C][C]0.0753658[/C][C]0.962317[/C][/ROW]
[ROW][C]135[/C][C]0.0322386[/C][C]0.0644772[/C][C]0.967761[/C][/ROW]
[ROW][C]136[/C][C]0.026983[/C][C]0.0539659[/C][C]0.973017[/C][/ROW]
[ROW][C]137[/C][C]0.0253368[/C][C]0.0506736[/C][C]0.974663[/C][/ROW]
[ROW][C]138[/C][C]0.0242574[/C][C]0.0485147[/C][C]0.975743[/C][/ROW]
[ROW][C]139[/C][C]0.0208126[/C][C]0.0416252[/C][C]0.979187[/C][/ROW]
[ROW][C]140[/C][C]0.0387895[/C][C]0.077579[/C][C]0.961211[/C][/ROW]
[ROW][C]141[/C][C]0.0391049[/C][C]0.0782098[/C][C]0.960895[/C][/ROW]
[ROW][C]142[/C][C]0.0565935[/C][C]0.113187[/C][C]0.943407[/C][/ROW]
[ROW][C]143[/C][C]0.0476498[/C][C]0.0952996[/C][C]0.95235[/C][/ROW]
[ROW][C]144[/C][C]0.0402957[/C][C]0.0805915[/C][C]0.959704[/C][/ROW]
[ROW][C]145[/C][C]0.0354957[/C][C]0.0709915[/C][C]0.964504[/C][/ROW]
[ROW][C]146[/C][C]0.0460364[/C][C]0.0920728[/C][C]0.953964[/C][/ROW]
[ROW][C]147[/C][C]0.0440506[/C][C]0.0881011[/C][C]0.955949[/C][/ROW]
[ROW][C]148[/C][C]0.0395291[/C][C]0.0790582[/C][C]0.960471[/C][/ROW]
[ROW][C]149[/C][C]0.0367915[/C][C]0.073583[/C][C]0.963208[/C][/ROW]
[ROW][C]150[/C][C]0.0513258[/C][C]0.102652[/C][C]0.948674[/C][/ROW]
[ROW][C]151[/C][C]0.0522228[/C][C]0.104446[/C][C]0.947777[/C][/ROW]
[ROW][C]152[/C][C]0.166017[/C][C]0.332034[/C][C]0.833983[/C][/ROW]
[ROW][C]153[/C][C]0.176969[/C][C]0.353938[/C][C]0.823031[/C][/ROW]
[ROW][C]154[/C][C]0.166829[/C][C]0.333659[/C][C]0.833171[/C][/ROW]
[ROW][C]155[/C][C]0.23759[/C][C]0.47518[/C][C]0.76241[/C][/ROW]
[ROW][C]156[/C][C]0.235014[/C][C]0.470028[/C][C]0.764986[/C][/ROW]
[ROW][C]157[/C][C]0.213987[/C][C]0.427974[/C][C]0.786013[/C][/ROW]
[ROW][C]158[/C][C]0.203038[/C][C]0.406077[/C][C]0.796962[/C][/ROW]
[ROW][C]159[/C][C]0.182209[/C][C]0.364418[/C][C]0.817791[/C][/ROW]
[ROW][C]160[/C][C]0.164331[/C][C]0.328663[/C][C]0.835669[/C][/ROW]
[ROW][C]161[/C][C]0.17834[/C][C]0.35668[/C][C]0.82166[/C][/ROW]
[ROW][C]162[/C][C]0.166536[/C][C]0.333072[/C][C]0.833464[/C][/ROW]
[ROW][C]163[/C][C]0.146496[/C][C]0.292992[/C][C]0.853504[/C][/ROW]
[ROW][C]164[/C][C]0.1317[/C][C]0.2634[/C][C]0.8683[/C][/ROW]
[ROW][C]165[/C][C]0.180865[/C][C]0.361729[/C][C]0.819135[/C][/ROW]
[ROW][C]166[/C][C]0.184755[/C][C]0.369509[/C][C]0.815245[/C][/ROW]
[ROW][C]167[/C][C]0.166764[/C][C]0.333528[/C][C]0.833236[/C][/ROW]
[ROW][C]168[/C][C]0.272531[/C][C]0.545063[/C][C]0.727469[/C][/ROW]
[ROW][C]169[/C][C]0.24658[/C][C]0.493159[/C][C]0.75342[/C][/ROW]
[ROW][C]170[/C][C]0.227265[/C][C]0.45453[/C][C]0.772735[/C][/ROW]
[ROW][C]171[/C][C]0.206148[/C][C]0.412297[/C][C]0.793852[/C][/ROW]
[ROW][C]172[/C][C]0.244481[/C][C]0.488961[/C][C]0.755519[/C][/ROW]
[ROW][C]173[/C][C]0.218676[/C][C]0.437353[/C][C]0.781324[/C][/ROW]
[ROW][C]174[/C][C]0.206846[/C][C]0.413692[/C][C]0.793154[/C][/ROW]
[ROW][C]175[/C][C]0.183531[/C][C]0.367062[/C][C]0.816469[/C][/ROW]
[ROW][C]176[/C][C]0.163016[/C][C]0.326033[/C][C]0.836984[/C][/ROW]
[ROW][C]177[/C][C]0.143149[/C][C]0.286298[/C][C]0.856851[/C][/ROW]
[ROW][C]178[/C][C]0.126345[/C][C]0.252691[/C][C]0.873655[/C][/ROW]
[ROW][C]179[/C][C]0.140625[/C][C]0.281249[/C][C]0.859375[/C][/ROW]
[ROW][C]180[/C][C]0.148518[/C][C]0.297037[/C][C]0.851482[/C][/ROW]
[ROW][C]181[/C][C]0.140446[/C][C]0.280891[/C][C]0.859554[/C][/ROW]
[ROW][C]182[/C][C]0.330391[/C][C]0.660782[/C][C]0.669609[/C][/ROW]
[ROW][C]183[/C][C]0.306685[/C][C]0.61337[/C][C]0.693315[/C][/ROW]
[ROW][C]184[/C][C]0.282607[/C][C]0.565214[/C][C]0.717393[/C][/ROW]
[ROW][C]185[/C][C]0.29988[/C][C]0.599759[/C][C]0.70012[/C][/ROW]
[ROW][C]186[/C][C]0.288743[/C][C]0.577486[/C][C]0.711257[/C][/ROW]
[ROW][C]187[/C][C]0.378482[/C][C]0.756965[/C][C]0.621518[/C][/ROW]
[ROW][C]188[/C][C]0.383747[/C][C]0.767494[/C][C]0.616253[/C][/ROW]
[ROW][C]189[/C][C]0.355026[/C][C]0.710052[/C][C]0.644974[/C][/ROW]
[ROW][C]190[/C][C]0.719695[/C][C]0.56061[/C][C]0.280305[/C][/ROW]
[ROW][C]191[/C][C]0.689307[/C][C]0.621385[/C][C]0.310693[/C][/ROW]
[ROW][C]192[/C][C]0.659234[/C][C]0.681532[/C][C]0.340766[/C][/ROW]
[ROW][C]193[/C][C]0.644471[/C][C]0.711058[/C][C]0.355529[/C][/ROW]
[ROW][C]194[/C][C]0.663297[/C][C]0.673407[/C][C]0.336703[/C][/ROW]
[ROW][C]195[/C][C]0.637665[/C][C]0.72467[/C][C]0.362335[/C][/ROW]
[ROW][C]196[/C][C]0.613621[/C][C]0.772758[/C][C]0.386379[/C][/ROW]
[ROW][C]197[/C][C]0.590738[/C][C]0.818524[/C][C]0.409262[/C][/ROW]
[ROW][C]198[/C][C]0.558669[/C][C]0.882663[/C][C]0.441331[/C][/ROW]
[ROW][C]199[/C][C]0.525758[/C][C]0.948484[/C][C]0.474242[/C][/ROW]
[ROW][C]200[/C][C]0.597639[/C][C]0.804722[/C][C]0.402361[/C][/ROW]
[ROW][C]201[/C][C]0.642067[/C][C]0.715866[/C][C]0.357933[/C][/ROW]
[ROW][C]202[/C][C]0.607308[/C][C]0.785384[/C][C]0.392692[/C][/ROW]
[ROW][C]203[/C][C]0.571296[/C][C]0.857409[/C][C]0.428704[/C][/ROW]
[ROW][C]204[/C][C]0.543423[/C][C]0.913153[/C][C]0.456577[/C][/ROW]
[ROW][C]205[/C][C]0.534026[/C][C]0.931948[/C][C]0.465974[/C][/ROW]
[ROW][C]206[/C][C]0.498789[/C][C]0.997578[/C][C]0.501211[/C][/ROW]
[ROW][C]207[/C][C]0.567149[/C][C]0.865701[/C][C]0.432851[/C][/ROW]
[ROW][C]208[/C][C]0.62617[/C][C]0.747661[/C][C]0.37383[/C][/ROW]
[ROW][C]209[/C][C]0.595775[/C][C]0.80845[/C][C]0.404225[/C][/ROW]
[ROW][C]210[/C][C]0.626798[/C][C]0.746405[/C][C]0.373202[/C][/ROW]
[ROW][C]211[/C][C]0.597861[/C][C]0.804279[/C][C]0.402139[/C][/ROW]
[ROW][C]212[/C][C]0.55945[/C][C]0.881101[/C][C]0.44055[/C][/ROW]
[ROW][C]213[/C][C]0.525777[/C][C]0.948446[/C][C]0.474223[/C][/ROW]
[ROW][C]214[/C][C]0.486823[/C][C]0.973645[/C][C]0.513177[/C][/ROW]
[ROW][C]215[/C][C]0.475073[/C][C]0.950146[/C][C]0.524927[/C][/ROW]
[ROW][C]216[/C][C]0.46333[/C][C]0.92666[/C][C]0.53667[/C][/ROW]
[ROW][C]217[/C][C]0.501002[/C][C]0.997995[/C][C]0.498998[/C][/ROW]
[ROW][C]218[/C][C]0.460516[/C][C]0.921031[/C][C]0.539484[/C][/ROW]
[ROW][C]219[/C][C]0.448083[/C][C]0.896166[/C][C]0.551917[/C][/ROW]
[ROW][C]220[/C][C]0.408873[/C][C]0.817745[/C][C]0.591127[/C][/ROW]
[ROW][C]221[/C][C]0.375727[/C][C]0.751454[/C][C]0.624273[/C][/ROW]
[ROW][C]222[/C][C]0.337752[/C][C]0.675503[/C][C]0.662248[/C][/ROW]
[ROW][C]223[/C][C]0.309783[/C][C]0.619567[/C][C]0.690217[/C][/ROW]
[ROW][C]224[/C][C]0.278693[/C][C]0.557386[/C][C]0.721307[/C][/ROW]
[ROW][C]225[/C][C]0.245136[/C][C]0.490271[/C][C]0.754864[/C][/ROW]
[ROW][C]226[/C][C]0.348811[/C][C]0.697623[/C][C]0.651189[/C][/ROW]
[ROW][C]227[/C][C]0.39425[/C][C]0.788499[/C][C]0.60575[/C][/ROW]
[ROW][C]228[/C][C]0.698374[/C][C]0.603253[/C][C]0.301626[/C][/ROW]
[ROW][C]229[/C][C]0.68[/C][C]0.639999[/C][C]0.32[/C][/ROW]
[ROW][C]230[/C][C]0.640146[/C][C]0.719709[/C][C]0.359854[/C][/ROW]
[ROW][C]231[/C][C]0.634318[/C][C]0.731365[/C][C]0.365682[/C][/ROW]
[ROW][C]232[/C][C]0.631447[/C][C]0.737105[/C][C]0.368553[/C][/ROW]
[ROW][C]233[/C][C]0.672883[/C][C]0.654235[/C][C]0.327117[/C][/ROW]
[ROW][C]234[/C][C]0.648688[/C][C]0.702624[/C][C]0.351312[/C][/ROW]
[ROW][C]235[/C][C]0.608817[/C][C]0.782366[/C][C]0.391183[/C][/ROW]
[ROW][C]236[/C][C]0.570739[/C][C]0.858523[/C][C]0.429261[/C][/ROW]
[ROW][C]237[/C][C]0.637306[/C][C]0.725388[/C][C]0.362694[/C][/ROW]
[ROW][C]238[/C][C]0.851833[/C][C]0.296333[/C][C]0.148167[/C][/ROW]
[ROW][C]239[/C][C]0.922131[/C][C]0.155738[/C][C]0.077869[/C][/ROW]
[ROW][C]240[/C][C]0.905563[/C][C]0.188874[/C][C]0.0944372[/C][/ROW]
[ROW][C]241[/C][C]0.893475[/C][C]0.213049[/C][C]0.106525[/C][/ROW]
[ROW][C]242[/C][C]0.884291[/C][C]0.231418[/C][C]0.115709[/C][/ROW]
[ROW][C]243[/C][C]0.860671[/C][C]0.278657[/C][C]0.139329[/C][/ROW]
[ROW][C]244[/C][C]0.830884[/C][C]0.338233[/C][C]0.169116[/C][/ROW]
[ROW][C]245[/C][C]0.832545[/C][C]0.334911[/C][C]0.167455[/C][/ROW]
[ROW][C]246[/C][C]0.808498[/C][C]0.383004[/C][C]0.191502[/C][/ROW]
[ROW][C]247[/C][C]0.862589[/C][C]0.274822[/C][C]0.137411[/C][/ROW]
[ROW][C]248[/C][C]0.883531[/C][C]0.232938[/C][C]0.116469[/C][/ROW]
[ROW][C]249[/C][C]0.866266[/C][C]0.267468[/C][C]0.133734[/C][/ROW]
[ROW][C]250[/C][C]0.843303[/C][C]0.313394[/C][C]0.156697[/C][/ROW]
[ROW][C]251[/C][C]0.827809[/C][C]0.344383[/C][C]0.172191[/C][/ROW]
[ROW][C]252[/C][C]0.821911[/C][C]0.356178[/C][C]0.178089[/C][/ROW]
[ROW][C]253[/C][C]0.801543[/C][C]0.396915[/C][C]0.198457[/C][/ROW]
[ROW][C]254[/C][C]0.770086[/C][C]0.459827[/C][C]0.229914[/C][/ROW]
[ROW][C]255[/C][C]0.722155[/C][C]0.55569[/C][C]0.277845[/C][/ROW]
[ROW][C]256[/C][C]0.875956[/C][C]0.248088[/C][C]0.124044[/C][/ROW]
[ROW][C]257[/C][C]0.849459[/C][C]0.301082[/C][C]0.150541[/C][/ROW]
[ROW][C]258[/C][C]0.826346[/C][C]0.347308[/C][C]0.173654[/C][/ROW]
[ROW][C]259[/C][C]0.831923[/C][C]0.336154[/C][C]0.168077[/C][/ROW]
[ROW][C]260[/C][C]0.848636[/C][C]0.302728[/C][C]0.151364[/C][/ROW]
[ROW][C]261[/C][C]0.845163[/C][C]0.309675[/C][C]0.154837[/C][/ROW]
[ROW][C]262[/C][C]0.801396[/C][C]0.397208[/C][C]0.198604[/C][/ROW]
[ROW][C]263[/C][C]0.77831[/C][C]0.443379[/C][C]0.22169[/C][/ROW]
[ROW][C]264[/C][C]0.719715[/C][C]0.560569[/C][C]0.280285[/C][/ROW]
[ROW][C]265[/C][C]0.772381[/C][C]0.455238[/C][C]0.227619[/C][/ROW]
[ROW][C]266[/C][C]0.839923[/C][C]0.320155[/C][C]0.160077[/C][/ROW]
[ROW][C]267[/C][C]0.926918[/C][C]0.146164[/C][C]0.0730822[/C][/ROW]
[ROW][C]268[/C][C]0.906672[/C][C]0.186657[/C][C]0.0933285[/C][/ROW]
[ROW][C]269[/C][C]0.865008[/C][C]0.269984[/C][C]0.134992[/C][/ROW]
[ROW][C]270[/C][C]0.926659[/C][C]0.146682[/C][C]0.0733408[/C][/ROW]
[ROW][C]271[/C][C]0.904538[/C][C]0.190924[/C][C]0.0954618[/C][/ROW]
[ROW][C]272[/C][C]0.943421[/C][C]0.113157[/C][C]0.0565786[/C][/ROW]
[ROW][C]273[/C][C]0.902043[/C][C]0.195915[/C][C]0.0979573[/C][/ROW]
[ROW][C]274[/C][C]0.903072[/C][C]0.193857[/C][C]0.0969283[/C][/ROW]
[ROW][C]275[/C][C]0.889934[/C][C]0.220132[/C][C]0.110066[/C][/ROW]
[ROW][C]276[/C][C]0.811762[/C][C]0.376476[/C][C]0.188238[/C][/ROW]
[ROW][C]277[/C][C]0.719978[/C][C]0.560045[/C][C]0.280022[/C][/ROW]
[ROW][C]278[/C][C]0.555516[/C][C]0.888968[/C][C]0.444484[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231417&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231417&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.7284270.5431470.271573
110.9321110.1357770.0678887
120.8839280.2321450.116072
130.9079960.1840080.0920039
140.8829190.2341630.117081
150.8933720.2132550.106628
160.9014440.1971110.0985557
170.8604780.2790440.139522
180.8508820.2982350.149118
190.8008760.3982490.199124
200.7415270.5169460.258473
210.6800450.6399090.319955
220.611980.7760390.38802
230.5389480.9221040.461052
240.514660.9706810.48534
250.5131780.9736450.486822
260.4799910.9599820.520009
270.4213960.8427920.578604
280.425690.8513810.57431
290.3650840.7301690.634916
300.3068020.6136040.693198
310.2543550.5087090.745645
320.2489590.4979180.751041
330.2174210.4348420.782579
340.1783690.3567380.821631
350.2178680.4357360.782132
360.2012150.402430.798785
370.1653560.3307130.834644
380.1934590.3869190.806541
390.2068940.4137880.793106
400.1779290.3558590.822071
410.1490260.2980530.850974
420.1266550.2533110.873345
430.1835680.3671370.816432
440.1511760.3023520.848824
450.1286760.2573510.871324
460.1375590.2751180.862441
470.1306730.2613470.869327
480.1097710.2195430.890229
490.09880390.1976080.901196
500.1031240.2062470.896876
510.106560.2131190.89344
520.08622550.1724510.913774
530.1044730.2089460.895527
540.0864560.1729120.913544
550.1477580.2955160.852242
560.4314090.8628180.568591
570.3884690.7769380.611531
580.346870.693740.65313
590.3069520.6139050.693048
600.3247170.6494340.675283
610.3406010.6812010.659399
620.3115220.6230440.688478
630.3157660.6315320.684234
640.2796190.5592390.720381
650.2461530.4923060.753847
660.2211430.4422870.778857
670.1974210.3948410.802579
680.1761920.3523850.823808
690.1710670.3421350.828933
700.1480450.296090.851955
710.1272340.2544680.872766
720.1088180.2176370.891182
730.09329550.1865910.906704
740.08339930.1667990.916601
750.08025020.16050.91975
760.1171980.2343950.882802
770.1037490.2074980.896251
780.08868640.1773730.911314
790.1029250.205850.897075
800.1004370.2008750.899563
810.08471860.1694370.915281
820.07110770.1422150.928892
830.06551420.1310280.934486
840.05481050.1096210.94519
850.05322570.1064510.946774
860.05546620.1109320.944534
870.04552810.09105630.954472
880.03710960.07421920.96289
890.03063070.06126140.969369
900.02707870.05415730.972921
910.0385910.07718210.961409
920.03249880.06499760.967501
930.02851540.05703080.971485
940.02915940.05831880.970841
950.03035280.06070560.969647
960.02653630.05307260.973464
970.03546020.07092030.96454
980.03017690.06035390.969823
990.02498090.04996180.975019
1000.02841730.05683460.971583
1010.02330880.04661750.976691
1020.01999880.03999760.980001
1030.01626980.03253970.98373
1040.01491520.02983040.985085
1050.01714310.03428620.982857
1060.01375870.02751740.986241
1070.01100710.02201410.988993
1080.008928290.01785660.991072
1090.01632970.03265940.98367
1100.01308720.02617430.986913
1110.01447510.02895010.985525
1120.01505950.03011890.984941
1130.01219390.02438780.987806
1140.01004770.02009540.989952
1150.01097870.02195740.989021
1160.01744740.03489470.982553
1170.01469630.02939270.985304
1180.01180980.02361960.98819
1190.01018430.02036860.989816
1200.009407330.01881470.990593
1210.0096390.0192780.990361
1220.01129730.02259460.988703
1230.01215870.02431740.987841
1240.02165530.04331060.978345
1250.01785970.03571940.98214
1260.01577010.03154010.98423
1270.01789480.03578950.982105
1280.01734960.03469910.98265
1290.01588220.03176450.984118
1300.02153160.04306320.978468
1310.04016090.08032190.959839
1320.04063120.08126240.959369
1330.04156730.08313470.958433
1340.03768290.07536580.962317
1350.03223860.06447720.967761
1360.0269830.05396590.973017
1370.02533680.05067360.974663
1380.02425740.04851470.975743
1390.02081260.04162520.979187
1400.03878950.0775790.961211
1410.03910490.07820980.960895
1420.05659350.1131870.943407
1430.04764980.09529960.95235
1440.04029570.08059150.959704
1450.03549570.07099150.964504
1460.04603640.09207280.953964
1470.04405060.08810110.955949
1480.03952910.07905820.960471
1490.03679150.0735830.963208
1500.05132580.1026520.948674
1510.05222280.1044460.947777
1520.1660170.3320340.833983
1530.1769690.3539380.823031
1540.1668290.3336590.833171
1550.237590.475180.76241
1560.2350140.4700280.764986
1570.2139870.4279740.786013
1580.2030380.4060770.796962
1590.1822090.3644180.817791
1600.1643310.3286630.835669
1610.178340.356680.82166
1620.1665360.3330720.833464
1630.1464960.2929920.853504
1640.13170.26340.8683
1650.1808650.3617290.819135
1660.1847550.3695090.815245
1670.1667640.3335280.833236
1680.2725310.5450630.727469
1690.246580.4931590.75342
1700.2272650.454530.772735
1710.2061480.4122970.793852
1720.2444810.4889610.755519
1730.2186760.4373530.781324
1740.2068460.4136920.793154
1750.1835310.3670620.816469
1760.1630160.3260330.836984
1770.1431490.2862980.856851
1780.1263450.2526910.873655
1790.1406250.2812490.859375
1800.1485180.2970370.851482
1810.1404460.2808910.859554
1820.3303910.6607820.669609
1830.3066850.613370.693315
1840.2826070.5652140.717393
1850.299880.5997590.70012
1860.2887430.5774860.711257
1870.3784820.7569650.621518
1880.3837470.7674940.616253
1890.3550260.7100520.644974
1900.7196950.560610.280305
1910.6893070.6213850.310693
1920.6592340.6815320.340766
1930.6444710.7110580.355529
1940.6632970.6734070.336703
1950.6376650.724670.362335
1960.6136210.7727580.386379
1970.5907380.8185240.409262
1980.5586690.8826630.441331
1990.5257580.9484840.474242
2000.5976390.8047220.402361
2010.6420670.7158660.357933
2020.6073080.7853840.392692
2030.5712960.8574090.428704
2040.5434230.9131530.456577
2050.5340260.9319480.465974
2060.4987890.9975780.501211
2070.5671490.8657010.432851
2080.626170.7476610.37383
2090.5957750.808450.404225
2100.6267980.7464050.373202
2110.5978610.8042790.402139
2120.559450.8811010.44055
2130.5257770.9484460.474223
2140.4868230.9736450.513177
2150.4750730.9501460.524927
2160.463330.926660.53667
2170.5010020.9979950.498998
2180.4605160.9210310.539484
2190.4480830.8961660.551917
2200.4088730.8177450.591127
2210.3757270.7514540.624273
2220.3377520.6755030.662248
2230.3097830.6195670.690217
2240.2786930.5573860.721307
2250.2451360.4902710.754864
2260.3488110.6976230.651189
2270.394250.7884990.60575
2280.6983740.6032530.301626
2290.680.6399990.32
2300.6401460.7197090.359854
2310.6343180.7313650.365682
2320.6314470.7371050.368553
2330.6728830.6542350.327117
2340.6486880.7026240.351312
2350.6088170.7823660.391183
2360.5707390.8585230.429261
2370.6373060.7253880.362694
2380.8518330.2963330.148167
2390.9221310.1557380.077869
2400.9055630.1888740.0944372
2410.8934750.2130490.106525
2420.8842910.2314180.115709
2430.8606710.2786570.139329
2440.8308840.3382330.169116
2450.8325450.3349110.167455
2460.8084980.3830040.191502
2470.8625890.2748220.137411
2480.8835310.2329380.116469
2490.8662660.2674680.133734
2500.8433030.3133940.156697
2510.8278090.3443830.172191
2520.8219110.3561780.178089
2530.8015430.3969150.198457
2540.7700860.4598270.229914
2550.7221550.555690.277845
2560.8759560.2480880.124044
2570.8494590.3010820.150541
2580.8263460.3473080.173654
2590.8319230.3361540.168077
2600.8486360.3027280.151364
2610.8451630.3096750.154837
2620.8013960.3972080.198604
2630.778310.4433790.22169
2640.7197150.5605690.280285
2650.7723810.4552380.227619
2660.8399230.3201550.160077
2670.9269180.1461640.0730822
2680.9066720.1866570.0933285
2690.8650080.2699840.134992
2700.9266590.1466820.0733408
2710.9045380.1909240.0954618
2720.9434210.1131570.0565786
2730.9020430.1959150.0979573
2740.9030720.1938570.0969283
2750.8899340.2201320.110066
2760.8117620.3764760.188238
2770.7199780.5600450.280022
2780.5555160.8889680.444484






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level330.122677NOK
10% type I error level620.230483NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 33 & 0.122677 & NOK \tabularnewline
10% type I error level & 62 & 0.230483 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231417&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]33[/C][C]0.122677[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]62[/C][C]0.230483[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231417&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231417&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level330.122677NOK
10% type I error level620.230483NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 6 ; par2 = equal ; par3 = 2 ; par4 = no ;
Parameters (R input):
par1 = 6 ; 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')
}