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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 computationTue, 09 Dec 2014 09:22:06 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/09/t14181170492pqwlsjpt82n396.htm/, Retrieved Thu, 16 May 2024 21:28:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264345, Retrieved Thu, 16 May 2024 21:28:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [Univariate Data Series] [WS8: Data Baby] [2014-11-19 13:06:54] [bcf5edf18529a33bd1494456d2c6cb9a]
- RMPD            [Multiple Regression] [Voorspelling exam...] [2014-12-09 09:22:06] [ddb851b9ced255c1d64c58a7ca49fb28] [Current]
- R  D              [Multiple Regression] [Multiple Regression] [2014-12-09 09:28:59] [bcf5edf18529a33bd1494456d2c6cb9a]
- RMPD              [Classical Decomposition] [CD] [2014-12-09 10:50:13] [bcf5edf18529a33bd1494456d2c6cb9a]
- R P                 [Classical Decomposition] [Expon.Smoothing o...] [2014-12-09 12:59:31] [bcf5edf18529a33bd1494456d2c6cb9a]
- RMPD              [Exponential Smoothing] [Expon.Smoothing] [2014-12-09 10:58:26] [bcf5edf18529a33bd1494456d2c6cb9a]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.5 2.1 1.8 7.5
2.1 2.0 2.1 6.0
2.1 2.0 2.2 6.5
1.9 2.1 2.3 1.0
1.6 2.0 2.1 1.0
2.1 2.3 2.7 5.5
2.1 2.1 2.1 8.5
2.2 2.1 2.4 6.5
1.5 2.2 2.9 4.5
1.9 2.1 2.2 2.0
2.2 2.1 2.1 5.0
1.6 2.1 2.2 0.5
1.5 2.0 2.2 5.0
1.9 2.3 2.7 5.0
0.1 1.8 1.9 2.5
2.2 2.0 2.0 5.0
1.8 2.2 2.5 5.5
1.6 2.0 2.2 3.5
2.2 2.1 2.3 3.0
2.1 2.0 1.9 4.0
1.9 1.8 2.1 0.5
1.6 2.2 3.5 6.5
1.9 2.2 2.1 4.5
2.2 1.7 2.3 7.5
1.8 2.1 2.3 5.5
2.4 2.3 2.2 4.0
2.4 2.7 3.5 7.5
2.5 1.9 1.9 7.0
1.9 2.0 1.9 4.0
2.1 2.0 1.9 5.5
1.9 1.9 1.9 2.5
2.1 2.0 2.1 5.5
1.5 2.0 2.0 3.5
1.9 2.1 3.2 2.5
2.1 2.0 2.3 4.5
1.5 1.8 2.5 4.5
2.1 2.0 1.8 4.5
2.1 2.2 2.4 6.0
1.8 2.2 2.8 2.5
2.4 2.1 2.3 5.0
2.1 1.8 2.0 0.0
1.9 1.9 2.5 5.0
2.1 2.1 2.3 6.5
1.9 2.0 1.8 5.0
2.4 1.9 1.9 6.0
2.1 2.2 2.6 4.5
2.2 2.0 2.0 5.5
2.2 2.0 2.6 1.0
1.8 1.7 1.6 7.5
2.1 2.0 2.2 6.0
2.4 2.2 2.1 5.0
2.2 1.7 1.8 1.0
2.1 2.0 1.8 5.0
1.5 2.2 1.9 6.5
1.9 2.0 2.4 7.0
1.8 1.9 1.9 4.5
1.8 2.0 2.0 0.0
1.6 2.0 2.1 8.5
1.2 1.6 1.7 3.5
1.8 2.1 1.9 7.5
1.5 2.1 2.1 3.5
2.1 2.0 2.4 6.0
2.4 1.9 1.8 1.5
2.4 2.2 2.3 9.0
1.5 2.1 2.1 3.5
1.8 1.8 2.0 3.5
2.1 2.3 2.8 4.0
2.2 2.3 2.0 6.5
2.1 2.2 2.7 7.5
1.9 2.1 2.1 6.0
2.1 2.2 2.9 5.0
1.9 1.9 2.0 5.5
1.6 1.8 1.8 3.5
2.4 2.1 2.6 7.5
1.9 2.0 2.1 6.5
1.9 1.7 2.3 NA
2.1 2.1 2.3 6.5
1.8 2.1 2.2 6.5
2.1 2.1 2.0 7.0
2.4 1.8 2.2 3.5
2.1 2.0 2.1 1.5
2.2 2.1 2.1 4.0
2.1 1.9 1.9 7.5
2.2 2.1 2.0 4.5
1.6 1.0 1.7 0.0
2.4 2.2 2.2 3.5
2.1 2.1 2.2 5.5
1.9 1.9 2.3 5.0
2.4 2.0 2.4 4.5
2.1 1.9 2.1 2.5
1.8 2.0 1.9 7.5
2.1 1.8 1.7 7.0
1.8 2.0 1.8 0.0
1.9 2.0 1.5 4.5
1.9 2.0 1.9 3.0
2.4 1.8 1.9 1.5
1.8 2.0 1.7 3.5
1.8 1.1 1.9 2.5
2.1 1.8 1.9 5.5
2.1 1.8 1.8 8.0
2.4 2.0 2.4 1.0
1.9 1.9 1.8 5.0
1.8 2.1 1.9 4.5
1.8 1.6 1.8 3.0
2.2 2.2 2.1 3.0
2.4 1.9 1.9 8.0
1.8 2.0 2.2 2.5
2.4 2.1 2.0 7.0
1.8 1.3 1.7 0.0
1.9 1.8 1.7 1.0
2.4 1.9 1.8 3.5
2.1 2.1 1.9 5.5
1.9 1.8 1.8 5.5
2.1 0.75 1 0.5
2.7 1.5 1 7.5
2.1 3 4 9
2.1 2.25 4 9.5
2.1 3 3 8.5
2.1 1.5 2 7
2.1 3 4 8
2.1 3 4 10
2.1 3 4 7
2.1 0.75 2 8.5
2.4 3 4 9
1.95 2.25 1 9.5
2.1 1.5 3 4
2.1 1.5 3 6
1.95 2.25 4 8
2.1 3 3 5.5
2.4 3 4 9.5
2.1 1.5 3 7.5
2.25 2.25 3 7
2.4 2.25 4 7.5
2.25 1.5 3 8
2.55 2.25 3 7
1.95 1.5 2 7
2.4 2.25 2 6
2.1 2.25 3 10
2.1 3 1 2.5
2.4 3 4 9
2.1 3 3 8
2.1 1.5 2 6
2.25 3 4 8.5
2.25 3 4 6
2.4 2.25 4 9
2.1 2.25 4 8
2.4 2.25 4 9
2.1 3 3 5.5
2.1 2.25 3 7
2.25 3 4 5.5
2.25 3 4 9
2.4 1.5 4 2
2.25 2.25 3 8.5
2.25 3 4 9
2.1 2.25 4 8.5
2.1 1.5 2 9
2.1 2.25 2 7.5
2.7 2.25 4 10
2.1 1.5 3 9
2.1 2.25 3 7.5
2.25 1.5 2 6
2.7 2.25 3 10.5
2.4 3 2 8.5
2.1 3 4 8
2.1 3 1 10
2.4 3 4 10.5
1.95 1.5 1 6.5
2.7 2.25 4 9.5
2.1 1.5 3 8.5
2.25 2.25 3 7.5
2.1 2.25 2 5
2.7 2.25 3 8
2.1 3 3 10
2.1 1.5 4 7
1.65 2.25 4 7.5
1.65 2.25 4 7.5
2.1 3 3 9.5
2.1 2.25 3 6
2.1 3 4 10
2.1 2.25 4 7
2.1 1.5 1 3
2.4 3 2 6
2.4 1.5 3 7
2.1 3 4 10
2.25 3 3 7
2.4 3 4 3.5
2.1 3 3 8
2.1 2.25 3 10
2.4 2.25 3 5.5
2.4 0.75 3 6
2.1 3 1 6.5
2.1 0.75 1 6.5
2.4 1.5 3 8.5
2.1 1.5 2 4
2.7 3 3 9.5
2.1 1.5 2 8
2.1 2.25 2 8.5
2.25 3 4 5.5
2.1 3 2 7
2.4 1.5 2 9
2.25 3 3 8
2.25 3 4 10
2.1 1.5 2 8
2.1 1.5 4 6
2.4 2.25 3 8
2.25 1.5 4 5
2.1 1.5 2 9
2.1 2.25 1 4.5
1.65 1.5 1 8.5
2.7 3 4 9.5
2.1 3 3 8.5
1.95 0.75 1 7.5
2.25 1.5 4 7.5
2.4 1.5 3 5
1.95 2.25 2 7
2.1 2.25 4 8
2.4 1.5 3 5.5
2.1 2.25 3 8.5
2.4 2.25 4 9.5
2.4 0.75 1 7
2.4 2.25 3 8
2.25 3 4 8.5
2.4 0.75 1 3.5
2.1 0.75 3 6.5
2.1 3 4 6.5
1.8 3 4 10.5
2.7 3 1 8.5
2.1 3 4 8
2.1 1.5 2 10
2.4 3 3 10
2.55 3 4 9.5
2.55 3 4 9
2.1 3 4 10
2.1 1.5 2 7.5
2.1 2.25 4 4.5
2.25 0.75 2 4.5
2.25 0.75 1 0.5
2.1 2.25 1 6.5
2.1 3 4 4.5
1.95 2.25 2 5.5
2.4 3 2 5
2.1 2.25 3 6
2.4 3 2 4
2.4 1.5 3 8
2.4 3 4 10.5
1.95 0.75 2 6.5
2.1 1.5 3 8
2.1 3 4 8.5
2.55 3 3 5.5
2.1 3 4 7
2.1 2.25 4 5
2.1 2.25 4 3.5
1.95 3 2 5
2.25 1.5 2 9
2.4 2.25 2 8.5
1.95 2.25 4 5
2.1 2.25 3 9.5
2.1 0.75 2 3
1.95 2.25 2 1.5
2.1 1.5 3 6
2.1 2.25 3 0.5
1.95 1.5 1 6.5
2.1 0.75 2 7.5
1.95 1.5 2 4.5
2.4 1.5 3 8
2.4 2.25 3 9
2.4 1.5 2 7.5
1.95 1.5 2 8.5
2.7 3 3 7
2.1 2.25 3 9.5
1.95 1.5 1 6.5
2.1 0.75 3 9.5
1.95 2.25 2 6
2.1 3 2 8
2.25 3 3 9.5
2.7 1.5 3 8
2.1 1.5 3 8
2.4 2.25 3 9
1.35 0.75 1 5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 8 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264345&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264345&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264345&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 time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = -1.49982 + 2.13795PA[t] + 0.533129PE[t] + 0.799039PR[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  -1.49982 +  2.13795PA[t] +  0.533129PE[t] +  0.799039PR[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264345&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  -1.49982 +  2.13795PA[t] +  0.533129PE[t] +  0.799039PR[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264345&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264345&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
Ex[t] = -1.49982 + 2.13795PA[t] + 0.533129PE[t] + 0.799039PR[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-1.499821.03119-1.4540.1469640.0734818
PA2.137950.4835454.4211.4151e-057.0755e-06
PE0.5331290.2594772.0550.04086340.0204317
PR0.7990390.1762624.5338.68728e-064.34364e-06

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & -1.49982 & 1.03119 & -1.454 & 0.146964 & 0.0734818 \tabularnewline
PA & 2.13795 & 0.483545 & 4.421 & 1.4151e-05 & 7.0755e-06 \tabularnewline
PE & 0.533129 & 0.259477 & 2.055 & 0.0408634 & 0.0204317 \tabularnewline
PR & 0.799039 & 0.176262 & 4.533 & 8.68728e-06 & 4.34364e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264345&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]-1.49982[/C][C]1.03119[/C][C]-1.454[/C][C]0.146964[/C][C]0.0734818[/C][/ROW]
[ROW][C]PA[/C][C]2.13795[/C][C]0.483545[/C][C]4.421[/C][C]1.4151e-05[/C][C]7.0755e-06[/C][/ROW]
[ROW][C]PE[/C][C]0.533129[/C][C]0.259477[/C][C]2.055[/C][C]0.0408634[/C][C]0.0204317[/C][/ROW]
[ROW][C]PR[/C][C]0.799039[/C][C]0.176262[/C][C]4.533[/C][C]8.68728e-06[/C][C]4.34364e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264345&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264345&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)-1.499821.03119-1.4540.1469640.0734818
PA2.137950.4835454.4211.4151e-057.0755e-06
PE0.5331290.2594772.0550.04086340.0204317
PR0.7990390.1762624.5338.68728e-064.34364e-06






Multiple Linear Regression - Regression Statistics
Multiple R0.48386
R-squared0.23412
Adjusted R-squared0.225735
F-TEST (value)27.9195
F-TEST (DF numerator)3
F-TEST (DF denominator)274
p-value8.88178e-16
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.2294
Sum Squared Residuals1361.84

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.48386 \tabularnewline
R-squared & 0.23412 \tabularnewline
Adjusted R-squared & 0.225735 \tabularnewline
F-TEST (value) & 27.9195 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 274 \tabularnewline
p-value & 8.88178e-16 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.2294 \tabularnewline
Sum Squared Residuals & 1361.84 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264345&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.48386[/C][/ROW]
[ROW][C]R-squared[/C][C]0.23412[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.225735[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]27.9195[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]274[/C][/ROW]
[ROW][C]p-value[/C][C]8.88178e-16[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.2294[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1361.84[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264345&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264345&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 R0.48386
R-squared0.23412
Adjusted R-squared0.225735
F-TEST (value)27.9195
F-TEST (DF numerator)3
F-TEST (DF denominator)274
p-value8.88178e-16
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.2294
Sum Squared Residuals1361.84






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.54.264933.23507
265.73410.265899
36.55.8140.685995
415.51963-4.51963
514.66513-3.66513
65.56.37346-0.873463
78.55.787412.71259
86.56.240920.25908
94.55.19719-0.69719
1025.43973-3.43973
1156.00121-1.00121
120.54.79834-4.29834
1354.531240.468763
1455.94587-0.945874
152.51.191781.30822
1655.86799-0.867992
175.55.51896-0.0189584
183.54.74503-1.24503
1936.16102-3.16102
2045.57429-1.57429
210.55.19989-4.69989
226.55.890410.609592
234.55.41314-0.913137
247.55.947761.55224
255.55.305840.194162
2646.61533-2.61533
277.57.86733-0.367329
2876.376160.623841
2945.1467-1.1467
305.55.57429-0.0742932
312.55.09339-2.59339
325.55.7341-0.234101
333.54.37143-0.87143
342.56.23877-3.73877
354.55.89391-1.39391
364.54.66432-0.164323
374.55.49439-0.994389
3866.08044-0.0804383
392.55.75867-3.25867
4056.58861-1.58861
4105.54757-5.54757
4255.57281-0.572814
436.55.947220.552778
4455.0668-0.0668002
4566.16236-0.162364
464.56.24025-1.74025
475.55.86799-0.367992
4816.34741-5.34741
497.54.533262.96674
5065.8140.185995
5156.48211-1.48211
5215.54825-4.54825
5355.49439-0.494389
546.54.398152.10185
5575.546221.45378
564.54.8796-0.379597
5705.01281-5.01281
588.54.665133.83487
593.53.277080.222917
607.54.986222.51378
613.54.50465-1.00465
6265.973810.0261874
631.56.08246-4.58246
6496.641922.35808
653.54.50465-1.00465
663.54.90619-1.40619
6746.45337-2.45337
686.56.027930.47207
697.56.320151.17985
7065.359820.640175
7156.47996-1.47996
725.55.17330.326705
733.54.31879-0.818791
747.56.828320.671683
756.55.306511.19349
76NANA0.552778
776.55.225931.27407
786.55.207511.29249
7979.84876-2.84876
803.57.7341-4.2341
811.53.50121-2.00121
8242.020981.97902
837.58.9213-1.4213
844.58.31238-3.81238
8503.06201-3.06201
863.53.86732-0.367318
875.55.91301-0.413007
8857.1152-2.1152
894.57.68079-3.18079
902.5-0.06709052.56709
917.55.807861.69214
92711.853-4.85301
9300.327089-0.327089
944.56.6467-2.1467
9537.60905-4.60905
961.52.7731-1.2731
973.55.45309-1.95309
982.52.467670.0323325
995.52.887762.61224
100813.6152-5.6152
10111.01349-0.0134873
10255.48622-0.486222
1034.56.13975-1.63975
10436.05452-3.05452
10531.162361.83764
106810.6726-2.67262
1072.51.848890.651106
108711.3999-4.39991
10903.88027-3.88027
11013.58246-2.58246
1113.53.62761-0.127606
1125.54.960170.539826
1135.59.18875-3.68875
1140.5-1.128641.62864
1157.56.28541.2146
11696.885562.11444
1179.57.986361.51364
1188.56.887631.61237
11976.78540.214597
12085.78542.2146
1211010.7854-0.785403
12273.487793.51221
1238.57.926790.573213
12494.167754.83225
1259.511.6867-2.18667
12644.18667-0.186672
12765.064860.935135
12889.48636-1.48636
1295.54.426791.07321
1309.58.186671.31333
1317.57.407210.0927902
13277.52694-0.52694
1337.56.007361.49264
13488.54859-0.548594
13575.066941.93306
13677.42886-0.428863
13762.586523.41348
1381012.8883-2.88829
1392.51.926790.573213
14097.986361.01364
14187.387630.612367
14265.606090.393905
1438.510.6061-2.10609
14465.026940.97306
14598.385560.614443
14687.026940.97306
147910.4864-1.48636
1485.55.086520.413482
14979.60609-2.60609
1505.54.606090.893905
151914.6271-5.62709
15220.407211.59279
1538.57.606090.893905
15497.885561.11444
1558.54.887633.61237
15697.287481.71252
1577.56.168321.33168
158107.186672.81333
15998.086520.913482
1607.57.208320.291675
16163.369292.63071
16210.58.828711.67129
1638.58.28540.214597
16483.388294.61171
165107.926792.07321
16610.58.26792.2321
1676.55.668320.831676
1689.57.186672.31333
1698.57.907210.59279
1707.58.28748-0.787479
17154.869290.130715
17284.986363.01364
173109.985710.0142898
17475.923481.07652
1757.56.423481.07652
1767.54.986362.51364
1779.510.0865-0.586518
17863.78542.2146
1791010.3856-0.385557
18078.58859-1.58859
18133.82871-0.828709
18265.828060.171945
18374.78542.2146
1841010.3071-0.307056
185711.9268-4.92679
1863.52.486361.01364
18784.586523.41348
1881011.7279-1.7279
1895.55.92821-0.428209
19064.888291.11171
1916.54.188752.31125
1926.54.828061.67194
1938.59.88763-1.38763
19442.769131.23087
1959.56.887632.61237
19685.287482.71252
1978.511.1061-2.60609
1985.54.687330.812674
19974.029022.97098
20098.307060.692944
20186.106091.89391
202107.387632.61237
20388.98571-0.98571
20465.22790.772098
205810.3064-2.3064
20651.387633.61237
20799.48844-0.488441
2084.5-0.3734824.87348
2098.58.068170.431829
2109.57.986361.51364
2118.54.868063.63194
2127.57.30640.193598
2137.59.32806-1.82806
21453.466791.53321
21576.385560.614443
21689.32806-1.32806
2175.53.586521.91348
2188.57.026941.47306
2199.57.330132.16987
22076.22790.772098
22187.606090.393905
2228.59.83013-1.33013
2233.52.786830.713175
2246.57.7854-1.2854
2256.53.144023.35598
22610.58.671051.82895
2278.58.28540.214597
22883.387634.61237
229107.627752.37225
230109.247480.752521
2319.59.247480.252521
23296.78542.2146
233107.887632.11237
2347.510.3856-2.88556
2354.55.30848-0.808478
2364.58.50944-4.00944
2370.5-1.011561.51156
2386.59.7854-3.2854
2394.54.466790.0332126
2405.57.32871-1.82871
24155.58652-0.586518
24268.82871-2.82871
24342.828061.17194
24485.926792.07321
24510.58.667091.83291
2466.54.686671.81333
24787.28540.714597
2488.510.9484-2.44844
2495.56.2854-0.785403
25079.38556-2.38556
25158.88556-3.88556
2523.54.36663-0.866634
25351.708323.29168
25496.928862.07114
2558.510.5649-2.06486
25652.086522.91348
2579.511.4878-1.98779
25836.96679-3.96679
2591.51.68667-0.186672
260612.0865-6.08652
2610.5-1.73212.2321
2626.53.987792.51221
2637.58.06694-0.566941
2644.53.328061.17194
26586.22791.7721
26697.529021.47098
2677.54.066943.43306
2688.59.76913-1.26913
26974.086522.91348
2709.57.26792.2321
2716.52.786833.71317
2729.58.966790.533213
27364.187331.81267
27485.807062.19294
2759.58.969440.530561
27686.186671.81333
27786.22791.7721
27896.585292.41471
2795NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 4.26493 & 3.23507 \tabularnewline
2 & 6 & 5.7341 & 0.265899 \tabularnewline
3 & 6.5 & 5.814 & 0.685995 \tabularnewline
4 & 1 & 5.51963 & -4.51963 \tabularnewline
5 & 1 & 4.66513 & -3.66513 \tabularnewline
6 & 5.5 & 6.37346 & -0.873463 \tabularnewline
7 & 8.5 & 5.78741 & 2.71259 \tabularnewline
8 & 6.5 & 6.24092 & 0.25908 \tabularnewline
9 & 4.5 & 5.19719 & -0.69719 \tabularnewline
10 & 2 & 5.43973 & -3.43973 \tabularnewline
11 & 5 & 6.00121 & -1.00121 \tabularnewline
12 & 0.5 & 4.79834 & -4.29834 \tabularnewline
13 & 5 & 4.53124 & 0.468763 \tabularnewline
14 & 5 & 5.94587 & -0.945874 \tabularnewline
15 & 2.5 & 1.19178 & 1.30822 \tabularnewline
16 & 5 & 5.86799 & -0.867992 \tabularnewline
17 & 5.5 & 5.51896 & -0.0189584 \tabularnewline
18 & 3.5 & 4.74503 & -1.24503 \tabularnewline
19 & 3 & 6.16102 & -3.16102 \tabularnewline
20 & 4 & 5.57429 & -1.57429 \tabularnewline
21 & 0.5 & 5.19989 & -4.69989 \tabularnewline
22 & 6.5 & 5.89041 & 0.609592 \tabularnewline
23 & 4.5 & 5.41314 & -0.913137 \tabularnewline
24 & 7.5 & 5.94776 & 1.55224 \tabularnewline
25 & 5.5 & 5.30584 & 0.194162 \tabularnewline
26 & 4 & 6.61533 & -2.61533 \tabularnewline
27 & 7.5 & 7.86733 & -0.367329 \tabularnewline
28 & 7 & 6.37616 & 0.623841 \tabularnewline
29 & 4 & 5.1467 & -1.1467 \tabularnewline
30 & 5.5 & 5.57429 & -0.0742932 \tabularnewline
31 & 2.5 & 5.09339 & -2.59339 \tabularnewline
32 & 5.5 & 5.7341 & -0.234101 \tabularnewline
33 & 3.5 & 4.37143 & -0.87143 \tabularnewline
34 & 2.5 & 6.23877 & -3.73877 \tabularnewline
35 & 4.5 & 5.89391 & -1.39391 \tabularnewline
36 & 4.5 & 4.66432 & -0.164323 \tabularnewline
37 & 4.5 & 5.49439 & -0.994389 \tabularnewline
38 & 6 & 6.08044 & -0.0804383 \tabularnewline
39 & 2.5 & 5.75867 & -3.25867 \tabularnewline
40 & 5 & 6.58861 & -1.58861 \tabularnewline
41 & 0 & 5.54757 & -5.54757 \tabularnewline
42 & 5 & 5.57281 & -0.572814 \tabularnewline
43 & 6.5 & 5.94722 & 0.552778 \tabularnewline
44 & 5 & 5.0668 & -0.0668002 \tabularnewline
45 & 6 & 6.16236 & -0.162364 \tabularnewline
46 & 4.5 & 6.24025 & -1.74025 \tabularnewline
47 & 5.5 & 5.86799 & -0.367992 \tabularnewline
48 & 1 & 6.34741 & -5.34741 \tabularnewline
49 & 7.5 & 4.53326 & 2.96674 \tabularnewline
50 & 6 & 5.814 & 0.185995 \tabularnewline
51 & 5 & 6.48211 & -1.48211 \tabularnewline
52 & 1 & 5.54825 & -4.54825 \tabularnewline
53 & 5 & 5.49439 & -0.494389 \tabularnewline
54 & 6.5 & 4.39815 & 2.10185 \tabularnewline
55 & 7 & 5.54622 & 1.45378 \tabularnewline
56 & 4.5 & 4.8796 & -0.379597 \tabularnewline
57 & 0 & 5.01281 & -5.01281 \tabularnewline
58 & 8.5 & 4.66513 & 3.83487 \tabularnewline
59 & 3.5 & 3.27708 & 0.222917 \tabularnewline
60 & 7.5 & 4.98622 & 2.51378 \tabularnewline
61 & 3.5 & 4.50465 & -1.00465 \tabularnewline
62 & 6 & 5.97381 & 0.0261874 \tabularnewline
63 & 1.5 & 6.08246 & -4.58246 \tabularnewline
64 & 9 & 6.64192 & 2.35808 \tabularnewline
65 & 3.5 & 4.50465 & -1.00465 \tabularnewline
66 & 3.5 & 4.90619 & -1.40619 \tabularnewline
67 & 4 & 6.45337 & -2.45337 \tabularnewline
68 & 6.5 & 6.02793 & 0.47207 \tabularnewline
69 & 7.5 & 6.32015 & 1.17985 \tabularnewline
70 & 6 & 5.35982 & 0.640175 \tabularnewline
71 & 5 & 6.47996 & -1.47996 \tabularnewline
72 & 5.5 & 5.1733 & 0.326705 \tabularnewline
73 & 3.5 & 4.31879 & -0.818791 \tabularnewline
74 & 7.5 & 6.82832 & 0.671683 \tabularnewline
75 & 6.5 & 5.30651 & 1.19349 \tabularnewline
76 & NA & NA & 0.552778 \tabularnewline
77 & 6.5 & 5.22593 & 1.27407 \tabularnewline
78 & 6.5 & 5.20751 & 1.29249 \tabularnewline
79 & 7 & 9.84876 & -2.84876 \tabularnewline
80 & 3.5 & 7.7341 & -4.2341 \tabularnewline
81 & 1.5 & 3.50121 & -2.00121 \tabularnewline
82 & 4 & 2.02098 & 1.97902 \tabularnewline
83 & 7.5 & 8.9213 & -1.4213 \tabularnewline
84 & 4.5 & 8.31238 & -3.81238 \tabularnewline
85 & 0 & 3.06201 & -3.06201 \tabularnewline
86 & 3.5 & 3.86732 & -0.367318 \tabularnewline
87 & 5.5 & 5.91301 & -0.413007 \tabularnewline
88 & 5 & 7.1152 & -2.1152 \tabularnewline
89 & 4.5 & 7.68079 & -3.18079 \tabularnewline
90 & 2.5 & -0.0670905 & 2.56709 \tabularnewline
91 & 7.5 & 5.80786 & 1.69214 \tabularnewline
92 & 7 & 11.853 & -4.85301 \tabularnewline
93 & 0 & 0.327089 & -0.327089 \tabularnewline
94 & 4.5 & 6.6467 & -2.1467 \tabularnewline
95 & 3 & 7.60905 & -4.60905 \tabularnewline
96 & 1.5 & 2.7731 & -1.2731 \tabularnewline
97 & 3.5 & 5.45309 & -1.95309 \tabularnewline
98 & 2.5 & 2.46767 & 0.0323325 \tabularnewline
99 & 5.5 & 2.88776 & 2.61224 \tabularnewline
100 & 8 & 13.6152 & -5.6152 \tabularnewline
101 & 1 & 1.01349 & -0.0134873 \tabularnewline
102 & 5 & 5.48622 & -0.486222 \tabularnewline
103 & 4.5 & 6.13975 & -1.63975 \tabularnewline
104 & 3 & 6.05452 & -3.05452 \tabularnewline
105 & 3 & 1.16236 & 1.83764 \tabularnewline
106 & 8 & 10.6726 & -2.67262 \tabularnewline
107 & 2.5 & 1.84889 & 0.651106 \tabularnewline
108 & 7 & 11.3999 & -4.39991 \tabularnewline
109 & 0 & 3.88027 & -3.88027 \tabularnewline
110 & 1 & 3.58246 & -2.58246 \tabularnewline
111 & 3.5 & 3.62761 & -0.127606 \tabularnewline
112 & 5.5 & 4.96017 & 0.539826 \tabularnewline
113 & 5.5 & 9.18875 & -3.68875 \tabularnewline
114 & 0.5 & -1.12864 & 1.62864 \tabularnewline
115 & 7.5 & 6.2854 & 1.2146 \tabularnewline
116 & 9 & 6.88556 & 2.11444 \tabularnewline
117 & 9.5 & 7.98636 & 1.51364 \tabularnewline
118 & 8.5 & 6.88763 & 1.61237 \tabularnewline
119 & 7 & 6.7854 & 0.214597 \tabularnewline
120 & 8 & 5.7854 & 2.2146 \tabularnewline
121 & 10 & 10.7854 & -0.785403 \tabularnewline
122 & 7 & 3.48779 & 3.51221 \tabularnewline
123 & 8.5 & 7.92679 & 0.573213 \tabularnewline
124 & 9 & 4.16775 & 4.83225 \tabularnewline
125 & 9.5 & 11.6867 & -2.18667 \tabularnewline
126 & 4 & 4.18667 & -0.186672 \tabularnewline
127 & 6 & 5.06486 & 0.935135 \tabularnewline
128 & 8 & 9.48636 & -1.48636 \tabularnewline
129 & 5.5 & 4.42679 & 1.07321 \tabularnewline
130 & 9.5 & 8.18667 & 1.31333 \tabularnewline
131 & 7.5 & 7.40721 & 0.0927902 \tabularnewline
132 & 7 & 7.52694 & -0.52694 \tabularnewline
133 & 7.5 & 6.00736 & 1.49264 \tabularnewline
134 & 8 & 8.54859 & -0.548594 \tabularnewline
135 & 7 & 5.06694 & 1.93306 \tabularnewline
136 & 7 & 7.42886 & -0.428863 \tabularnewline
137 & 6 & 2.58652 & 3.41348 \tabularnewline
138 & 10 & 12.8883 & -2.88829 \tabularnewline
139 & 2.5 & 1.92679 & 0.573213 \tabularnewline
140 & 9 & 7.98636 & 1.01364 \tabularnewline
141 & 8 & 7.38763 & 0.612367 \tabularnewline
142 & 6 & 5.60609 & 0.393905 \tabularnewline
143 & 8.5 & 10.6061 & -2.10609 \tabularnewline
144 & 6 & 5.02694 & 0.97306 \tabularnewline
145 & 9 & 8.38556 & 0.614443 \tabularnewline
146 & 8 & 7.02694 & 0.97306 \tabularnewline
147 & 9 & 10.4864 & -1.48636 \tabularnewline
148 & 5.5 & 5.08652 & 0.413482 \tabularnewline
149 & 7 & 9.60609 & -2.60609 \tabularnewline
150 & 5.5 & 4.60609 & 0.893905 \tabularnewline
151 & 9 & 14.6271 & -5.62709 \tabularnewline
152 & 2 & 0.40721 & 1.59279 \tabularnewline
153 & 8.5 & 7.60609 & 0.893905 \tabularnewline
154 & 9 & 7.88556 & 1.11444 \tabularnewline
155 & 8.5 & 4.88763 & 3.61237 \tabularnewline
156 & 9 & 7.28748 & 1.71252 \tabularnewline
157 & 7.5 & 6.16832 & 1.33168 \tabularnewline
158 & 10 & 7.18667 & 2.81333 \tabularnewline
159 & 9 & 8.08652 & 0.913482 \tabularnewline
160 & 7.5 & 7.20832 & 0.291675 \tabularnewline
161 & 6 & 3.36929 & 2.63071 \tabularnewline
162 & 10.5 & 8.82871 & 1.67129 \tabularnewline
163 & 8.5 & 8.2854 & 0.214597 \tabularnewline
164 & 8 & 3.38829 & 4.61171 \tabularnewline
165 & 10 & 7.92679 & 2.07321 \tabularnewline
166 & 10.5 & 8.2679 & 2.2321 \tabularnewline
167 & 6.5 & 5.66832 & 0.831676 \tabularnewline
168 & 9.5 & 7.18667 & 2.31333 \tabularnewline
169 & 8.5 & 7.90721 & 0.59279 \tabularnewline
170 & 7.5 & 8.28748 & -0.787479 \tabularnewline
171 & 5 & 4.86929 & 0.130715 \tabularnewline
172 & 8 & 4.98636 & 3.01364 \tabularnewline
173 & 10 & 9.98571 & 0.0142898 \tabularnewline
174 & 7 & 5.92348 & 1.07652 \tabularnewline
175 & 7.5 & 6.42348 & 1.07652 \tabularnewline
176 & 7.5 & 4.98636 & 2.51364 \tabularnewline
177 & 9.5 & 10.0865 & -0.586518 \tabularnewline
178 & 6 & 3.7854 & 2.2146 \tabularnewline
179 & 10 & 10.3856 & -0.385557 \tabularnewline
180 & 7 & 8.58859 & -1.58859 \tabularnewline
181 & 3 & 3.82871 & -0.828709 \tabularnewline
182 & 6 & 5.82806 & 0.171945 \tabularnewline
183 & 7 & 4.7854 & 2.2146 \tabularnewline
184 & 10 & 10.3071 & -0.307056 \tabularnewline
185 & 7 & 11.9268 & -4.92679 \tabularnewline
186 & 3.5 & 2.48636 & 1.01364 \tabularnewline
187 & 8 & 4.58652 & 3.41348 \tabularnewline
188 & 10 & 11.7279 & -1.7279 \tabularnewline
189 & 5.5 & 5.92821 & -0.428209 \tabularnewline
190 & 6 & 4.88829 & 1.11171 \tabularnewline
191 & 6.5 & 4.18875 & 2.31125 \tabularnewline
192 & 6.5 & 4.82806 & 1.67194 \tabularnewline
193 & 8.5 & 9.88763 & -1.38763 \tabularnewline
194 & 4 & 2.76913 & 1.23087 \tabularnewline
195 & 9.5 & 6.88763 & 2.61237 \tabularnewline
196 & 8 & 5.28748 & 2.71252 \tabularnewline
197 & 8.5 & 11.1061 & -2.60609 \tabularnewline
198 & 5.5 & 4.68733 & 0.812674 \tabularnewline
199 & 7 & 4.02902 & 2.97098 \tabularnewline
200 & 9 & 8.30706 & 0.692944 \tabularnewline
201 & 8 & 6.10609 & 1.89391 \tabularnewline
202 & 10 & 7.38763 & 2.61237 \tabularnewline
203 & 8 & 8.98571 & -0.98571 \tabularnewline
204 & 6 & 5.2279 & 0.772098 \tabularnewline
205 & 8 & 10.3064 & -2.3064 \tabularnewline
206 & 5 & 1.38763 & 3.61237 \tabularnewline
207 & 9 & 9.48844 & -0.488441 \tabularnewline
208 & 4.5 & -0.373482 & 4.87348 \tabularnewline
209 & 8.5 & 8.06817 & 0.431829 \tabularnewline
210 & 9.5 & 7.98636 & 1.51364 \tabularnewline
211 & 8.5 & 4.86806 & 3.63194 \tabularnewline
212 & 7.5 & 7.3064 & 0.193598 \tabularnewline
213 & 7.5 & 9.32806 & -1.82806 \tabularnewline
214 & 5 & 3.46679 & 1.53321 \tabularnewline
215 & 7 & 6.38556 & 0.614443 \tabularnewline
216 & 8 & 9.32806 & -1.32806 \tabularnewline
217 & 5.5 & 3.58652 & 1.91348 \tabularnewline
218 & 8.5 & 7.02694 & 1.47306 \tabularnewline
219 & 9.5 & 7.33013 & 2.16987 \tabularnewline
220 & 7 & 6.2279 & 0.772098 \tabularnewline
221 & 8 & 7.60609 & 0.393905 \tabularnewline
222 & 8.5 & 9.83013 & -1.33013 \tabularnewline
223 & 3.5 & 2.78683 & 0.713175 \tabularnewline
224 & 6.5 & 7.7854 & -1.2854 \tabularnewline
225 & 6.5 & 3.14402 & 3.35598 \tabularnewline
226 & 10.5 & 8.67105 & 1.82895 \tabularnewline
227 & 8.5 & 8.2854 & 0.214597 \tabularnewline
228 & 8 & 3.38763 & 4.61237 \tabularnewline
229 & 10 & 7.62775 & 2.37225 \tabularnewline
230 & 10 & 9.24748 & 0.752521 \tabularnewline
231 & 9.5 & 9.24748 & 0.252521 \tabularnewline
232 & 9 & 6.7854 & 2.2146 \tabularnewline
233 & 10 & 7.88763 & 2.11237 \tabularnewline
234 & 7.5 & 10.3856 & -2.88556 \tabularnewline
235 & 4.5 & 5.30848 & -0.808478 \tabularnewline
236 & 4.5 & 8.50944 & -4.00944 \tabularnewline
237 & 0.5 & -1.01156 & 1.51156 \tabularnewline
238 & 6.5 & 9.7854 & -3.2854 \tabularnewline
239 & 4.5 & 4.46679 & 0.0332126 \tabularnewline
240 & 5.5 & 7.32871 & -1.82871 \tabularnewline
241 & 5 & 5.58652 & -0.586518 \tabularnewline
242 & 6 & 8.82871 & -2.82871 \tabularnewline
243 & 4 & 2.82806 & 1.17194 \tabularnewline
244 & 8 & 5.92679 & 2.07321 \tabularnewline
245 & 10.5 & 8.66709 & 1.83291 \tabularnewline
246 & 6.5 & 4.68667 & 1.81333 \tabularnewline
247 & 8 & 7.2854 & 0.714597 \tabularnewline
248 & 8.5 & 10.9484 & -2.44844 \tabularnewline
249 & 5.5 & 6.2854 & -0.785403 \tabularnewline
250 & 7 & 9.38556 & -2.38556 \tabularnewline
251 & 5 & 8.88556 & -3.88556 \tabularnewline
252 & 3.5 & 4.36663 & -0.866634 \tabularnewline
253 & 5 & 1.70832 & 3.29168 \tabularnewline
254 & 9 & 6.92886 & 2.07114 \tabularnewline
255 & 8.5 & 10.5649 & -2.06486 \tabularnewline
256 & 5 & 2.08652 & 2.91348 \tabularnewline
257 & 9.5 & 11.4878 & -1.98779 \tabularnewline
258 & 3 & 6.96679 & -3.96679 \tabularnewline
259 & 1.5 & 1.68667 & -0.186672 \tabularnewline
260 & 6 & 12.0865 & -6.08652 \tabularnewline
261 & 0.5 & -1.7321 & 2.2321 \tabularnewline
262 & 6.5 & 3.98779 & 2.51221 \tabularnewline
263 & 7.5 & 8.06694 & -0.566941 \tabularnewline
264 & 4.5 & 3.32806 & 1.17194 \tabularnewline
265 & 8 & 6.2279 & 1.7721 \tabularnewline
266 & 9 & 7.52902 & 1.47098 \tabularnewline
267 & 7.5 & 4.06694 & 3.43306 \tabularnewline
268 & 8.5 & 9.76913 & -1.26913 \tabularnewline
269 & 7 & 4.08652 & 2.91348 \tabularnewline
270 & 9.5 & 7.2679 & 2.2321 \tabularnewline
271 & 6.5 & 2.78683 & 3.71317 \tabularnewline
272 & 9.5 & 8.96679 & 0.533213 \tabularnewline
273 & 6 & 4.18733 & 1.81267 \tabularnewline
274 & 8 & 5.80706 & 2.19294 \tabularnewline
275 & 9.5 & 8.96944 & 0.530561 \tabularnewline
276 & 8 & 6.18667 & 1.81333 \tabularnewline
277 & 8 & 6.2279 & 1.7721 \tabularnewline
278 & 9 & 6.58529 & 2.41471 \tabularnewline
279 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264345&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]7.5[/C][C]4.26493[/C][C]3.23507[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]5.7341[/C][C]0.265899[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]5.814[/C][C]0.685995[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]5.51963[/C][C]-4.51963[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]4.66513[/C][C]-3.66513[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]6.37346[/C][C]-0.873463[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]5.78741[/C][C]2.71259[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]6.24092[/C][C]0.25908[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]5.19719[/C][C]-0.69719[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]5.43973[/C][C]-3.43973[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]6.00121[/C][C]-1.00121[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]4.79834[/C][C]-4.29834[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]4.53124[/C][C]0.468763[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]5.94587[/C][C]-0.945874[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]1.19178[/C][C]1.30822[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]5.86799[/C][C]-0.867992[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]5.51896[/C][C]-0.0189584[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]4.74503[/C][C]-1.24503[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]6.16102[/C][C]-3.16102[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]5.57429[/C][C]-1.57429[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]5.19989[/C][C]-4.69989[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]5.89041[/C][C]0.609592[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]5.41314[/C][C]-0.913137[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]5.94776[/C][C]1.55224[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]5.30584[/C][C]0.194162[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]6.61533[/C][C]-2.61533[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]7.86733[/C][C]-0.367329[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]6.37616[/C][C]0.623841[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]5.1467[/C][C]-1.1467[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]5.57429[/C][C]-0.0742932[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]5.09339[/C][C]-2.59339[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]5.7341[/C][C]-0.234101[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]4.37143[/C][C]-0.87143[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]6.23877[/C][C]-3.73877[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]5.89391[/C][C]-1.39391[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]4.66432[/C][C]-0.164323[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.49439[/C][C]-0.994389[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]6.08044[/C][C]-0.0804383[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]5.75867[/C][C]-3.25867[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]6.58861[/C][C]-1.58861[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]5.54757[/C][C]-5.54757[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]5.57281[/C][C]-0.572814[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]5.94722[/C][C]0.552778[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]5.0668[/C][C]-0.0668002[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]6.16236[/C][C]-0.162364[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]6.24025[/C][C]-1.74025[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]5.86799[/C][C]-0.367992[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]6.34741[/C][C]-5.34741[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]4.53326[/C][C]2.96674[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]5.814[/C][C]0.185995[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]6.48211[/C][C]-1.48211[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]5.54825[/C][C]-4.54825[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]5.49439[/C][C]-0.494389[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]4.39815[/C][C]2.10185[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]5.54622[/C][C]1.45378[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]4.8796[/C][C]-0.379597[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]5.01281[/C][C]-5.01281[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]4.66513[/C][C]3.83487[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]3.27708[/C][C]0.222917[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]4.98622[/C][C]2.51378[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]4.50465[/C][C]-1.00465[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]5.97381[/C][C]0.0261874[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]6.08246[/C][C]-4.58246[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]6.64192[/C][C]2.35808[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]4.50465[/C][C]-1.00465[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]4.90619[/C][C]-1.40619[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]6.45337[/C][C]-2.45337[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]6.02793[/C][C]0.47207[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]6.32015[/C][C]1.17985[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]5.35982[/C][C]0.640175[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]6.47996[/C][C]-1.47996[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]5.1733[/C][C]0.326705[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]4.31879[/C][C]-0.818791[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]6.82832[/C][C]0.671683[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]5.30651[/C][C]1.19349[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.552778[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]5.22593[/C][C]1.27407[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]5.20751[/C][C]1.29249[/C][/ROW]
[ROW][C]79[/C][C]7[/C][C]9.84876[/C][C]-2.84876[/C][/ROW]
[ROW][C]80[/C][C]3.5[/C][C]7.7341[/C][C]-4.2341[/C][/ROW]
[ROW][C]81[/C][C]1.5[/C][C]3.50121[/C][C]-2.00121[/C][/ROW]
[ROW][C]82[/C][C]4[/C][C]2.02098[/C][C]1.97902[/C][/ROW]
[ROW][C]83[/C][C]7.5[/C][C]8.9213[/C][C]-1.4213[/C][/ROW]
[ROW][C]84[/C][C]4.5[/C][C]8.31238[/C][C]-3.81238[/C][/ROW]
[ROW][C]85[/C][C]0[/C][C]3.06201[/C][C]-3.06201[/C][/ROW]
[ROW][C]86[/C][C]3.5[/C][C]3.86732[/C][C]-0.367318[/C][/ROW]
[ROW][C]87[/C][C]5.5[/C][C]5.91301[/C][C]-0.413007[/C][/ROW]
[ROW][C]88[/C][C]5[/C][C]7.1152[/C][C]-2.1152[/C][/ROW]
[ROW][C]89[/C][C]4.5[/C][C]7.68079[/C][C]-3.18079[/C][/ROW]
[ROW][C]90[/C][C]2.5[/C][C]-0.0670905[/C][C]2.56709[/C][/ROW]
[ROW][C]91[/C][C]7.5[/C][C]5.80786[/C][C]1.69214[/C][/ROW]
[ROW][C]92[/C][C]7[/C][C]11.853[/C][C]-4.85301[/C][/ROW]
[ROW][C]93[/C][C]0[/C][C]0.327089[/C][C]-0.327089[/C][/ROW]
[ROW][C]94[/C][C]4.5[/C][C]6.6467[/C][C]-2.1467[/C][/ROW]
[ROW][C]95[/C][C]3[/C][C]7.60905[/C][C]-4.60905[/C][/ROW]
[ROW][C]96[/C][C]1.5[/C][C]2.7731[/C][C]-1.2731[/C][/ROW]
[ROW][C]97[/C][C]3.5[/C][C]5.45309[/C][C]-1.95309[/C][/ROW]
[ROW][C]98[/C][C]2.5[/C][C]2.46767[/C][C]0.0323325[/C][/ROW]
[ROW][C]99[/C][C]5.5[/C][C]2.88776[/C][C]2.61224[/C][/ROW]
[ROW][C]100[/C][C]8[/C][C]13.6152[/C][C]-5.6152[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]1.01349[/C][C]-0.0134873[/C][/ROW]
[ROW][C]102[/C][C]5[/C][C]5.48622[/C][C]-0.486222[/C][/ROW]
[ROW][C]103[/C][C]4.5[/C][C]6.13975[/C][C]-1.63975[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]6.05452[/C][C]-3.05452[/C][/ROW]
[ROW][C]105[/C][C]3[/C][C]1.16236[/C][C]1.83764[/C][/ROW]
[ROW][C]106[/C][C]8[/C][C]10.6726[/C][C]-2.67262[/C][/ROW]
[ROW][C]107[/C][C]2.5[/C][C]1.84889[/C][C]0.651106[/C][/ROW]
[ROW][C]108[/C][C]7[/C][C]11.3999[/C][C]-4.39991[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]3.88027[/C][C]-3.88027[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]3.58246[/C][C]-2.58246[/C][/ROW]
[ROW][C]111[/C][C]3.5[/C][C]3.62761[/C][C]-0.127606[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]4.96017[/C][C]0.539826[/C][/ROW]
[ROW][C]113[/C][C]5.5[/C][C]9.18875[/C][C]-3.68875[/C][/ROW]
[ROW][C]114[/C][C]0.5[/C][C]-1.12864[/C][C]1.62864[/C][/ROW]
[ROW][C]115[/C][C]7.5[/C][C]6.2854[/C][C]1.2146[/C][/ROW]
[ROW][C]116[/C][C]9[/C][C]6.88556[/C][C]2.11444[/C][/ROW]
[ROW][C]117[/C][C]9.5[/C][C]7.98636[/C][C]1.51364[/C][/ROW]
[ROW][C]118[/C][C]8.5[/C][C]6.88763[/C][C]1.61237[/C][/ROW]
[ROW][C]119[/C][C]7[/C][C]6.7854[/C][C]0.214597[/C][/ROW]
[ROW][C]120[/C][C]8[/C][C]5.7854[/C][C]2.2146[/C][/ROW]
[ROW][C]121[/C][C]10[/C][C]10.7854[/C][C]-0.785403[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]3.48779[/C][C]3.51221[/C][/ROW]
[ROW][C]123[/C][C]8.5[/C][C]7.92679[/C][C]0.573213[/C][/ROW]
[ROW][C]124[/C][C]9[/C][C]4.16775[/C][C]4.83225[/C][/ROW]
[ROW][C]125[/C][C]9.5[/C][C]11.6867[/C][C]-2.18667[/C][/ROW]
[ROW][C]126[/C][C]4[/C][C]4.18667[/C][C]-0.186672[/C][/ROW]
[ROW][C]127[/C][C]6[/C][C]5.06486[/C][C]0.935135[/C][/ROW]
[ROW][C]128[/C][C]8[/C][C]9.48636[/C][C]-1.48636[/C][/ROW]
[ROW][C]129[/C][C]5.5[/C][C]4.42679[/C][C]1.07321[/C][/ROW]
[ROW][C]130[/C][C]9.5[/C][C]8.18667[/C][C]1.31333[/C][/ROW]
[ROW][C]131[/C][C]7.5[/C][C]7.40721[/C][C]0.0927902[/C][/ROW]
[ROW][C]132[/C][C]7[/C][C]7.52694[/C][C]-0.52694[/C][/ROW]
[ROW][C]133[/C][C]7.5[/C][C]6.00736[/C][C]1.49264[/C][/ROW]
[ROW][C]134[/C][C]8[/C][C]8.54859[/C][C]-0.548594[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]5.06694[/C][C]1.93306[/C][/ROW]
[ROW][C]136[/C][C]7[/C][C]7.42886[/C][C]-0.428863[/C][/ROW]
[ROW][C]137[/C][C]6[/C][C]2.58652[/C][C]3.41348[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]12.8883[/C][C]-2.88829[/C][/ROW]
[ROW][C]139[/C][C]2.5[/C][C]1.92679[/C][C]0.573213[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]7.98636[/C][C]1.01364[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]7.38763[/C][C]0.612367[/C][/ROW]
[ROW][C]142[/C][C]6[/C][C]5.60609[/C][C]0.393905[/C][/ROW]
[ROW][C]143[/C][C]8.5[/C][C]10.6061[/C][C]-2.10609[/C][/ROW]
[ROW][C]144[/C][C]6[/C][C]5.02694[/C][C]0.97306[/C][/ROW]
[ROW][C]145[/C][C]9[/C][C]8.38556[/C][C]0.614443[/C][/ROW]
[ROW][C]146[/C][C]8[/C][C]7.02694[/C][C]0.97306[/C][/ROW]
[ROW][C]147[/C][C]9[/C][C]10.4864[/C][C]-1.48636[/C][/ROW]
[ROW][C]148[/C][C]5.5[/C][C]5.08652[/C][C]0.413482[/C][/ROW]
[ROW][C]149[/C][C]7[/C][C]9.60609[/C][C]-2.60609[/C][/ROW]
[ROW][C]150[/C][C]5.5[/C][C]4.60609[/C][C]0.893905[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]14.6271[/C][C]-5.62709[/C][/ROW]
[ROW][C]152[/C][C]2[/C][C]0.40721[/C][C]1.59279[/C][/ROW]
[ROW][C]153[/C][C]8.5[/C][C]7.60609[/C][C]0.893905[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]7.88556[/C][C]1.11444[/C][/ROW]
[ROW][C]155[/C][C]8.5[/C][C]4.88763[/C][C]3.61237[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]7.28748[/C][C]1.71252[/C][/ROW]
[ROW][C]157[/C][C]7.5[/C][C]6.16832[/C][C]1.33168[/C][/ROW]
[ROW][C]158[/C][C]10[/C][C]7.18667[/C][C]2.81333[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]8.08652[/C][C]0.913482[/C][/ROW]
[ROW][C]160[/C][C]7.5[/C][C]7.20832[/C][C]0.291675[/C][/ROW]
[ROW][C]161[/C][C]6[/C][C]3.36929[/C][C]2.63071[/C][/ROW]
[ROW][C]162[/C][C]10.5[/C][C]8.82871[/C][C]1.67129[/C][/ROW]
[ROW][C]163[/C][C]8.5[/C][C]8.2854[/C][C]0.214597[/C][/ROW]
[ROW][C]164[/C][C]8[/C][C]3.38829[/C][C]4.61171[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]7.92679[/C][C]2.07321[/C][/ROW]
[ROW][C]166[/C][C]10.5[/C][C]8.2679[/C][C]2.2321[/C][/ROW]
[ROW][C]167[/C][C]6.5[/C][C]5.66832[/C][C]0.831676[/C][/ROW]
[ROW][C]168[/C][C]9.5[/C][C]7.18667[/C][C]2.31333[/C][/ROW]
[ROW][C]169[/C][C]8.5[/C][C]7.90721[/C][C]0.59279[/C][/ROW]
[ROW][C]170[/C][C]7.5[/C][C]8.28748[/C][C]-0.787479[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]4.86929[/C][C]0.130715[/C][/ROW]
[ROW][C]172[/C][C]8[/C][C]4.98636[/C][C]3.01364[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]9.98571[/C][C]0.0142898[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]5.92348[/C][C]1.07652[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]6.42348[/C][C]1.07652[/C][/ROW]
[ROW][C]176[/C][C]7.5[/C][C]4.98636[/C][C]2.51364[/C][/ROW]
[ROW][C]177[/C][C]9.5[/C][C]10.0865[/C][C]-0.586518[/C][/ROW]
[ROW][C]178[/C][C]6[/C][C]3.7854[/C][C]2.2146[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]10.3856[/C][C]-0.385557[/C][/ROW]
[ROW][C]180[/C][C]7[/C][C]8.58859[/C][C]-1.58859[/C][/ROW]
[ROW][C]181[/C][C]3[/C][C]3.82871[/C][C]-0.828709[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]5.82806[/C][C]0.171945[/C][/ROW]
[ROW][C]183[/C][C]7[/C][C]4.7854[/C][C]2.2146[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]10.3071[/C][C]-0.307056[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]11.9268[/C][C]-4.92679[/C][/ROW]
[ROW][C]186[/C][C]3.5[/C][C]2.48636[/C][C]1.01364[/C][/ROW]
[ROW][C]187[/C][C]8[/C][C]4.58652[/C][C]3.41348[/C][/ROW]
[ROW][C]188[/C][C]10[/C][C]11.7279[/C][C]-1.7279[/C][/ROW]
[ROW][C]189[/C][C]5.5[/C][C]5.92821[/C][C]-0.428209[/C][/ROW]
[ROW][C]190[/C][C]6[/C][C]4.88829[/C][C]1.11171[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]4.18875[/C][C]2.31125[/C][/ROW]
[ROW][C]192[/C][C]6.5[/C][C]4.82806[/C][C]1.67194[/C][/ROW]
[ROW][C]193[/C][C]8.5[/C][C]9.88763[/C][C]-1.38763[/C][/ROW]
[ROW][C]194[/C][C]4[/C][C]2.76913[/C][C]1.23087[/C][/ROW]
[ROW][C]195[/C][C]9.5[/C][C]6.88763[/C][C]2.61237[/C][/ROW]
[ROW][C]196[/C][C]8[/C][C]5.28748[/C][C]2.71252[/C][/ROW]
[ROW][C]197[/C][C]8.5[/C][C]11.1061[/C][C]-2.60609[/C][/ROW]
[ROW][C]198[/C][C]5.5[/C][C]4.68733[/C][C]0.812674[/C][/ROW]
[ROW][C]199[/C][C]7[/C][C]4.02902[/C][C]2.97098[/C][/ROW]
[ROW][C]200[/C][C]9[/C][C]8.30706[/C][C]0.692944[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]6.10609[/C][C]1.89391[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]7.38763[/C][C]2.61237[/C][/ROW]
[ROW][C]203[/C][C]8[/C][C]8.98571[/C][C]-0.98571[/C][/ROW]
[ROW][C]204[/C][C]6[/C][C]5.2279[/C][C]0.772098[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]10.3064[/C][C]-2.3064[/C][/ROW]
[ROW][C]206[/C][C]5[/C][C]1.38763[/C][C]3.61237[/C][/ROW]
[ROW][C]207[/C][C]9[/C][C]9.48844[/C][C]-0.488441[/C][/ROW]
[ROW][C]208[/C][C]4.5[/C][C]-0.373482[/C][C]4.87348[/C][/ROW]
[ROW][C]209[/C][C]8.5[/C][C]8.06817[/C][C]0.431829[/C][/ROW]
[ROW][C]210[/C][C]9.5[/C][C]7.98636[/C][C]1.51364[/C][/ROW]
[ROW][C]211[/C][C]8.5[/C][C]4.86806[/C][C]3.63194[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]7.3064[/C][C]0.193598[/C][/ROW]
[ROW][C]213[/C][C]7.5[/C][C]9.32806[/C][C]-1.82806[/C][/ROW]
[ROW][C]214[/C][C]5[/C][C]3.46679[/C][C]1.53321[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]6.38556[/C][C]0.614443[/C][/ROW]
[ROW][C]216[/C][C]8[/C][C]9.32806[/C][C]-1.32806[/C][/ROW]
[ROW][C]217[/C][C]5.5[/C][C]3.58652[/C][C]1.91348[/C][/ROW]
[ROW][C]218[/C][C]8.5[/C][C]7.02694[/C][C]1.47306[/C][/ROW]
[ROW][C]219[/C][C]9.5[/C][C]7.33013[/C][C]2.16987[/C][/ROW]
[ROW][C]220[/C][C]7[/C][C]6.2279[/C][C]0.772098[/C][/ROW]
[ROW][C]221[/C][C]8[/C][C]7.60609[/C][C]0.393905[/C][/ROW]
[ROW][C]222[/C][C]8.5[/C][C]9.83013[/C][C]-1.33013[/C][/ROW]
[ROW][C]223[/C][C]3.5[/C][C]2.78683[/C][C]0.713175[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]7.7854[/C][C]-1.2854[/C][/ROW]
[ROW][C]225[/C][C]6.5[/C][C]3.14402[/C][C]3.35598[/C][/ROW]
[ROW][C]226[/C][C]10.5[/C][C]8.67105[/C][C]1.82895[/C][/ROW]
[ROW][C]227[/C][C]8.5[/C][C]8.2854[/C][C]0.214597[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]3.38763[/C][C]4.61237[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]7.62775[/C][C]2.37225[/C][/ROW]
[ROW][C]230[/C][C]10[/C][C]9.24748[/C][C]0.752521[/C][/ROW]
[ROW][C]231[/C][C]9.5[/C][C]9.24748[/C][C]0.252521[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]6.7854[/C][C]2.2146[/C][/ROW]
[ROW][C]233[/C][C]10[/C][C]7.88763[/C][C]2.11237[/C][/ROW]
[ROW][C]234[/C][C]7.5[/C][C]10.3856[/C][C]-2.88556[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]5.30848[/C][C]-0.808478[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]8.50944[/C][C]-4.00944[/C][/ROW]
[ROW][C]237[/C][C]0.5[/C][C]-1.01156[/C][C]1.51156[/C][/ROW]
[ROW][C]238[/C][C]6.5[/C][C]9.7854[/C][C]-3.2854[/C][/ROW]
[ROW][C]239[/C][C]4.5[/C][C]4.46679[/C][C]0.0332126[/C][/ROW]
[ROW][C]240[/C][C]5.5[/C][C]7.32871[/C][C]-1.82871[/C][/ROW]
[ROW][C]241[/C][C]5[/C][C]5.58652[/C][C]-0.586518[/C][/ROW]
[ROW][C]242[/C][C]6[/C][C]8.82871[/C][C]-2.82871[/C][/ROW]
[ROW][C]243[/C][C]4[/C][C]2.82806[/C][C]1.17194[/C][/ROW]
[ROW][C]244[/C][C]8[/C][C]5.92679[/C][C]2.07321[/C][/ROW]
[ROW][C]245[/C][C]10.5[/C][C]8.66709[/C][C]1.83291[/C][/ROW]
[ROW][C]246[/C][C]6.5[/C][C]4.68667[/C][C]1.81333[/C][/ROW]
[ROW][C]247[/C][C]8[/C][C]7.2854[/C][C]0.714597[/C][/ROW]
[ROW][C]248[/C][C]8.5[/C][C]10.9484[/C][C]-2.44844[/C][/ROW]
[ROW][C]249[/C][C]5.5[/C][C]6.2854[/C][C]-0.785403[/C][/ROW]
[ROW][C]250[/C][C]7[/C][C]9.38556[/C][C]-2.38556[/C][/ROW]
[ROW][C]251[/C][C]5[/C][C]8.88556[/C][C]-3.88556[/C][/ROW]
[ROW][C]252[/C][C]3.5[/C][C]4.36663[/C][C]-0.866634[/C][/ROW]
[ROW][C]253[/C][C]5[/C][C]1.70832[/C][C]3.29168[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]6.92886[/C][C]2.07114[/C][/ROW]
[ROW][C]255[/C][C]8.5[/C][C]10.5649[/C][C]-2.06486[/C][/ROW]
[ROW][C]256[/C][C]5[/C][C]2.08652[/C][C]2.91348[/C][/ROW]
[ROW][C]257[/C][C]9.5[/C][C]11.4878[/C][C]-1.98779[/C][/ROW]
[ROW][C]258[/C][C]3[/C][C]6.96679[/C][C]-3.96679[/C][/ROW]
[ROW][C]259[/C][C]1.5[/C][C]1.68667[/C][C]-0.186672[/C][/ROW]
[ROW][C]260[/C][C]6[/C][C]12.0865[/C][C]-6.08652[/C][/ROW]
[ROW][C]261[/C][C]0.5[/C][C]-1.7321[/C][C]2.2321[/C][/ROW]
[ROW][C]262[/C][C]6.5[/C][C]3.98779[/C][C]2.51221[/C][/ROW]
[ROW][C]263[/C][C]7.5[/C][C]8.06694[/C][C]-0.566941[/C][/ROW]
[ROW][C]264[/C][C]4.5[/C][C]3.32806[/C][C]1.17194[/C][/ROW]
[ROW][C]265[/C][C]8[/C][C]6.2279[/C][C]1.7721[/C][/ROW]
[ROW][C]266[/C][C]9[/C][C]7.52902[/C][C]1.47098[/C][/ROW]
[ROW][C]267[/C][C]7.5[/C][C]4.06694[/C][C]3.43306[/C][/ROW]
[ROW][C]268[/C][C]8.5[/C][C]9.76913[/C][C]-1.26913[/C][/ROW]
[ROW][C]269[/C][C]7[/C][C]4.08652[/C][C]2.91348[/C][/ROW]
[ROW][C]270[/C][C]9.5[/C][C]7.2679[/C][C]2.2321[/C][/ROW]
[ROW][C]271[/C][C]6.5[/C][C]2.78683[/C][C]3.71317[/C][/ROW]
[ROW][C]272[/C][C]9.5[/C][C]8.96679[/C][C]0.533213[/C][/ROW]
[ROW][C]273[/C][C]6[/C][C]4.18733[/C][C]1.81267[/C][/ROW]
[ROW][C]274[/C][C]8[/C][C]5.80706[/C][C]2.19294[/C][/ROW]
[ROW][C]275[/C][C]9.5[/C][C]8.96944[/C][C]0.530561[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]6.18667[/C][C]1.81333[/C][/ROW]
[ROW][C]277[/C][C]8[/C][C]6.2279[/C][C]1.7721[/C][/ROW]
[ROW][C]278[/C][C]9[/C][C]6.58529[/C][C]2.41471[/C][/ROW]
[ROW][C]279[/C][C]5[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264345&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264345&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
17.54.264933.23507
265.73410.265899
36.55.8140.685995
415.51963-4.51963
514.66513-3.66513
65.56.37346-0.873463
78.55.787412.71259
86.56.240920.25908
94.55.19719-0.69719
1025.43973-3.43973
1156.00121-1.00121
120.54.79834-4.29834
1354.531240.468763
1455.94587-0.945874
152.51.191781.30822
1655.86799-0.867992
175.55.51896-0.0189584
183.54.74503-1.24503
1936.16102-3.16102
2045.57429-1.57429
210.55.19989-4.69989
226.55.890410.609592
234.55.41314-0.913137
247.55.947761.55224
255.55.305840.194162
2646.61533-2.61533
277.57.86733-0.367329
2876.376160.623841
2945.1467-1.1467
305.55.57429-0.0742932
312.55.09339-2.59339
325.55.7341-0.234101
333.54.37143-0.87143
342.56.23877-3.73877
354.55.89391-1.39391
364.54.66432-0.164323
374.55.49439-0.994389
3866.08044-0.0804383
392.55.75867-3.25867
4056.58861-1.58861
4105.54757-5.54757
4255.57281-0.572814
436.55.947220.552778
4455.0668-0.0668002
4566.16236-0.162364
464.56.24025-1.74025
475.55.86799-0.367992
4816.34741-5.34741
497.54.533262.96674
5065.8140.185995
5156.48211-1.48211
5215.54825-4.54825
5355.49439-0.494389
546.54.398152.10185
5575.546221.45378
564.54.8796-0.379597
5705.01281-5.01281
588.54.665133.83487
593.53.277080.222917
607.54.986222.51378
613.54.50465-1.00465
6265.973810.0261874
631.56.08246-4.58246
6496.641922.35808
653.54.50465-1.00465
663.54.90619-1.40619
6746.45337-2.45337
686.56.027930.47207
697.56.320151.17985
7065.359820.640175
7156.47996-1.47996
725.55.17330.326705
733.54.31879-0.818791
747.56.828320.671683
756.55.306511.19349
76NANA0.552778
776.55.225931.27407
786.55.207511.29249
7979.84876-2.84876
803.57.7341-4.2341
811.53.50121-2.00121
8242.020981.97902
837.58.9213-1.4213
844.58.31238-3.81238
8503.06201-3.06201
863.53.86732-0.367318
875.55.91301-0.413007
8857.1152-2.1152
894.57.68079-3.18079
902.5-0.06709052.56709
917.55.807861.69214
92711.853-4.85301
9300.327089-0.327089
944.56.6467-2.1467
9537.60905-4.60905
961.52.7731-1.2731
973.55.45309-1.95309
982.52.467670.0323325
995.52.887762.61224
100813.6152-5.6152
10111.01349-0.0134873
10255.48622-0.486222
1034.56.13975-1.63975
10436.05452-3.05452
10531.162361.83764
106810.6726-2.67262
1072.51.848890.651106
108711.3999-4.39991
10903.88027-3.88027
11013.58246-2.58246
1113.53.62761-0.127606
1125.54.960170.539826
1135.59.18875-3.68875
1140.5-1.128641.62864
1157.56.28541.2146
11696.885562.11444
1179.57.986361.51364
1188.56.887631.61237
11976.78540.214597
12085.78542.2146
1211010.7854-0.785403
12273.487793.51221
1238.57.926790.573213
12494.167754.83225
1259.511.6867-2.18667
12644.18667-0.186672
12765.064860.935135
12889.48636-1.48636
1295.54.426791.07321
1309.58.186671.31333
1317.57.407210.0927902
13277.52694-0.52694
1337.56.007361.49264
13488.54859-0.548594
13575.066941.93306
13677.42886-0.428863
13762.586523.41348
1381012.8883-2.88829
1392.51.926790.573213
14097.986361.01364
14187.387630.612367
14265.606090.393905
1438.510.6061-2.10609
14465.026940.97306
14598.385560.614443
14687.026940.97306
147910.4864-1.48636
1485.55.086520.413482
14979.60609-2.60609
1505.54.606090.893905
151914.6271-5.62709
15220.407211.59279
1538.57.606090.893905
15497.885561.11444
1558.54.887633.61237
15697.287481.71252
1577.56.168321.33168
158107.186672.81333
15998.086520.913482
1607.57.208320.291675
16163.369292.63071
16210.58.828711.67129
1638.58.28540.214597
16483.388294.61171
165107.926792.07321
16610.58.26792.2321
1676.55.668320.831676
1689.57.186672.31333
1698.57.907210.59279
1707.58.28748-0.787479
17154.869290.130715
17284.986363.01364
173109.985710.0142898
17475.923481.07652
1757.56.423481.07652
1767.54.986362.51364
1779.510.0865-0.586518
17863.78542.2146
1791010.3856-0.385557
18078.58859-1.58859
18133.82871-0.828709
18265.828060.171945
18374.78542.2146
1841010.3071-0.307056
185711.9268-4.92679
1863.52.486361.01364
18784.586523.41348
1881011.7279-1.7279
1895.55.92821-0.428209
19064.888291.11171
1916.54.188752.31125
1926.54.828061.67194
1938.59.88763-1.38763
19442.769131.23087
1959.56.887632.61237
19685.287482.71252
1978.511.1061-2.60609
1985.54.687330.812674
19974.029022.97098
20098.307060.692944
20186.106091.89391
202107.387632.61237
20388.98571-0.98571
20465.22790.772098
205810.3064-2.3064
20651.387633.61237
20799.48844-0.488441
2084.5-0.3734824.87348
2098.58.068170.431829
2109.57.986361.51364
2118.54.868063.63194
2127.57.30640.193598
2137.59.32806-1.82806
21453.466791.53321
21576.385560.614443
21689.32806-1.32806
2175.53.586521.91348
2188.57.026941.47306
2199.57.330132.16987
22076.22790.772098
22187.606090.393905
2228.59.83013-1.33013
2233.52.786830.713175
2246.57.7854-1.2854
2256.53.144023.35598
22610.58.671051.82895
2278.58.28540.214597
22883.387634.61237
229107.627752.37225
230109.247480.752521
2319.59.247480.252521
23296.78542.2146
233107.887632.11237
2347.510.3856-2.88556
2354.55.30848-0.808478
2364.58.50944-4.00944
2370.5-1.011561.51156
2386.59.7854-3.2854
2394.54.466790.0332126
2405.57.32871-1.82871
24155.58652-0.586518
24268.82871-2.82871
24342.828061.17194
24485.926792.07321
24510.58.667091.83291
2466.54.686671.81333
24787.28540.714597
2488.510.9484-2.44844
2495.56.2854-0.785403
25079.38556-2.38556
25158.88556-3.88556
2523.54.36663-0.866634
25351.708323.29168
25496.928862.07114
2558.510.5649-2.06486
25652.086522.91348
2579.511.4878-1.98779
25836.96679-3.96679
2591.51.68667-0.186672
260612.0865-6.08652
2610.5-1.73212.2321
2626.53.987792.51221
2637.58.06694-0.566941
2644.53.328061.17194
26586.22791.7721
26697.529021.47098
2677.54.066943.43306
2688.59.76913-1.26913
26974.086522.91348
2709.57.26792.2321
2716.52.786833.71317
2729.58.966790.533213
27364.187331.81267
27485.807062.19294
2759.58.969440.530561
27686.186671.81333
27786.22791.7721
27896.585292.41471
2795NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.4690880.9381760.530912
80.33620.67240.6638
90.832070.3358610.16793
100.8822270.2355450.117773
110.8422430.3155140.157757
120.882730.2345410.11727
130.8788170.2423670.121183
140.8278920.3442150.172108
150.8115050.3769890.188495
160.7516720.4966560.248328
170.6942940.6114110.305706
180.6265390.7469220.373461
190.6140320.7719350.385968
200.556770.8864590.44323
210.5583670.8832670.441633
220.6100490.7799010.389951
230.5504820.8990370.449518
240.6433850.713230.356615
250.59290.8141990.4071
260.5529480.8941040.447052
270.4977030.9954070.502297
280.4785130.9570260.521487
290.4204010.8408020.579599
300.3717130.7434260.628287
310.3564060.7128130.643594
320.3088360.6176730.691164
330.2611480.5222960.738852
340.3035420.6070830.696458
350.25940.51880.7406
360.221170.4423410.77883
370.183620.3672390.81638
380.1554420.3108830.844558
390.1650380.3300760.834962
400.1368360.2736720.863164
410.2610750.522150.738925
420.2275630.4551260.772437
430.2112890.4225790.788711
440.180620.361240.81938
450.1576320.3152640.842368
460.134420.268840.86558
470.1120780.2241550.887922
480.1873510.3747020.812649
490.2555950.511190.744405
500.2303440.4606880.769656
510.2007310.4014610.799269
520.2633270.5266550.736673
530.2284950.4569910.771505
540.2189610.4379220.781039
550.2328260.4656520.767174
560.201050.4021010.79895
570.3313120.6626250.668688
580.4466790.8933590.553321
590.4065180.8130360.593482
600.4228680.8457370.577132
610.3925020.7850030.607498
620.3665910.7331820.633409
630.4416440.8832880.558356
640.495480.9909590.50452
650.4652710.9305410.534729
660.4313710.8627430.568629
670.4175720.8351440.582428
680.3810390.7620790.618961
690.3812790.7625580.618721
700.3509150.701830.649085
710.3197240.6394480.680276
720.2933390.5866780.706661
730.2632140.5264280.736786
740.260230.520460.73977
750.2482910.4965820.751709
760.2278760.4557510.772124
770.2129910.4259820.787009
780.2001090.4002180.799891
790.1905310.3810620.809469
800.2477880.4955770.752212
810.2350620.4701240.764938
820.2515660.5031310.748434
830.2307060.4614120.769294
840.2388260.4776530.761174
850.2547540.5095080.745246
860.2271820.4543640.772818
870.204340.408680.79566
880.1885860.3771710.811414
890.2000330.4000670.799967
900.2146650.4293310.785335
910.2215680.4431370.778432
920.3656450.731290.634355
930.3350620.6701240.664938
940.3353940.6707880.664606
950.4080.8160.592
960.3915080.7830160.608492
970.3846490.7692980.615351
980.3617950.7235910.638205
990.4114780.8229560.588522
1000.5592230.8815550.440777
1010.5278630.9442740.472137
1020.4989370.9978740.501063
1030.484650.9692990.51535
1040.5226230.9547530.477377
1050.5463480.9073030.453652
1060.5717090.8565820.428291
1070.5498890.9002220.450111
1080.6428020.7143960.357198
1090.7319930.5360140.268007
1100.7409060.5181880.259094
1110.7166450.566710.283355
1120.6987590.6024810.301241
1130.7526390.4947210.247361
1140.7692730.4614540.230727
1150.756660.486680.24334
1160.8042790.3914410.195721
1170.7822960.4354090.217704
1180.8026990.3946030.197301
1190.7776370.4447250.222363
1200.7754570.4490850.224543
1210.7559140.4881710.244086
1220.8660170.2679660.133983
1230.8487280.3025440.151272
1240.9008950.198210.0991049
1250.9003740.1992510.0996257
1260.891850.21630.10815
1270.8819080.2361850.118092
1280.8796370.2407270.120363
1290.8676510.2646980.132349
1300.8660360.2679280.133964
1310.8481760.3036470.151824
1320.8277330.3445350.172267
1330.8270170.3459660.172983
1340.8055790.3888420.194421
1350.8060640.3878720.193936
1360.7857860.4284280.214214
1370.8210510.3578980.178949
1380.8620620.2758750.137938
1390.8438270.3123460.156173
1400.8248940.3502120.175106
1410.8090820.3818360.190918
1420.7851730.4296530.214827
1430.7879160.4241670.212084
1440.769940.4601190.23006
1450.7445710.5108570.255429
1460.7242310.5515370.275769
1470.7183940.5632130.281606
1480.6903980.6192050.309602
1490.7104530.5790930.289547
1500.6845920.6308150.315408
1510.8301080.3397840.169892
1520.8205630.3588730.179437
1530.8002920.3994170.199708
1540.7816960.4366070.218304
1550.8245930.3508140.175407
1560.8138690.3722630.186131
1570.8061170.3877670.193883
1580.8214990.3570030.178501
1590.8010880.3978250.198912
1600.7804470.4391070.219553
1610.8013460.3973090.198654
1620.7888210.4223570.211179
1630.7624880.4750230.237512
1640.8220720.3558560.177928
1650.8215540.3568920.178446
1660.8181830.3636350.181817
1670.8031920.3936150.196808
1680.805620.388760.19438
1690.7817780.4364440.218222
1700.767480.465040.23252
1710.7403540.5192930.259646
1720.7532760.4934490.246724
1730.7249580.5500830.275042
1740.6969530.6060950.303047
1750.6675420.6649160.332458
1760.6659870.6680250.334013
1770.6391220.7217550.360878
1780.6356360.7287280.364364
1790.602740.7945190.39726
1800.6174570.7650860.382543
1810.5946570.8106850.405343
1820.5610210.8779570.438979
1830.5598630.8802740.440137
1840.526220.9475610.47378
1850.6713690.6572620.328631
1860.6400850.7198290.359915
1870.6779770.6440470.322023
1880.6697480.6605030.330252
1890.6409120.7181760.359088
1900.6093570.7812850.390643
1910.6063010.7873980.393699
1920.590760.818480.40924
1930.5898820.8202350.410118
1940.5654680.8690630.434532
1950.5652470.8695060.434753
1960.5650430.8699140.434957
1970.5809370.8381270.419063
1980.5443670.9112650.455633
1990.5632590.8734830.436741
2000.5263450.9473110.473655
2010.51820.9635990.4818
2020.5160160.9679690.483984
2030.4858370.9716750.514163
2040.4506040.9012070.549396
2050.4546350.9092710.545365
2060.492380.9847610.50762
2070.470330.940660.52967
2080.55170.8965990.4483
2090.5164370.9671270.483563
2100.489240.978480.51076
2110.5164650.9670710.483535
2120.4760290.9520580.523971
2130.4708010.9416030.529199
2140.439290.878580.56071
2150.4008450.8016890.599155
2160.3832620.7665250.616738
2170.3651080.7302160.634892
2180.3423850.6847690.657615
2190.3230490.6460980.676951
2200.2885910.5771810.711409
2210.2549510.5099010.745049
2220.256440.5128790.74356
2230.2247310.4494620.775269
2240.2010430.4020860.798957
2250.2529760.5059520.747024
2260.2296250.459250.770375
2270.1999190.3998370.800081
2280.2736490.5472970.726351
2290.2835260.5670520.716474
2300.2571060.5142130.742894
2310.2265440.4530870.773456
2320.2506660.5013330.749334
2330.2317250.4634490.768275
2340.2400480.4800970.759952
2350.2310240.4620470.768976
2360.4978620.9957240.502138
2370.4547070.9094130.545293
2380.4543180.9086360.545682
2390.4045450.809090.595455
2400.3874180.7748350.612582
2410.3418680.6837370.658132
2420.3906110.7812230.609389
2430.3430140.6860280.656986
2440.377960.7559190.62204
2450.3328350.6656710.667165
2460.3023490.6046980.697651
2470.3055820.6111640.694418
2480.3118440.6236890.688156
2490.2747340.5494670.725266
2500.2403740.4807490.759626
2510.2764250.552850.723575
2520.2354480.4708950.764552
2530.2229490.4458980.777051
2540.1884140.3768280.811586
2550.1764440.3528880.823556
2560.1825010.3650020.817499
2570.2697360.5394720.730264
2580.486790.973580.51321
2590.4390470.8780940.560953
2600.9960040.007992950.00399648
2610.993520.01295970.00647984
2620.9886010.02279850.0113992
2630.9976310.004738770.00236939
2640.9952750.009450820.00472541
2650.9896920.02061570.0103078
2660.9795670.04086590.020433
2670.9741580.05168420.0258421
2680.9810740.03785150.0189258
2690.9607130.0785730.0392865
2700.950260.09948040.0497402
2710.9474220.1051560.052578
2720.989430.02114010.0105701

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.469088 & 0.938176 & 0.530912 \tabularnewline
8 & 0.3362 & 0.6724 & 0.6638 \tabularnewline
9 & 0.83207 & 0.335861 & 0.16793 \tabularnewline
10 & 0.882227 & 0.235545 & 0.117773 \tabularnewline
11 & 0.842243 & 0.315514 & 0.157757 \tabularnewline
12 & 0.88273 & 0.234541 & 0.11727 \tabularnewline
13 & 0.878817 & 0.242367 & 0.121183 \tabularnewline
14 & 0.827892 & 0.344215 & 0.172108 \tabularnewline
15 & 0.811505 & 0.376989 & 0.188495 \tabularnewline
16 & 0.751672 & 0.496656 & 0.248328 \tabularnewline
17 & 0.694294 & 0.611411 & 0.305706 \tabularnewline
18 & 0.626539 & 0.746922 & 0.373461 \tabularnewline
19 & 0.614032 & 0.771935 & 0.385968 \tabularnewline
20 & 0.55677 & 0.886459 & 0.44323 \tabularnewline
21 & 0.558367 & 0.883267 & 0.441633 \tabularnewline
22 & 0.610049 & 0.779901 & 0.389951 \tabularnewline
23 & 0.550482 & 0.899037 & 0.449518 \tabularnewline
24 & 0.643385 & 0.71323 & 0.356615 \tabularnewline
25 & 0.5929 & 0.814199 & 0.4071 \tabularnewline
26 & 0.552948 & 0.894104 & 0.447052 \tabularnewline
27 & 0.497703 & 0.995407 & 0.502297 \tabularnewline
28 & 0.478513 & 0.957026 & 0.521487 \tabularnewline
29 & 0.420401 & 0.840802 & 0.579599 \tabularnewline
30 & 0.371713 & 0.743426 & 0.628287 \tabularnewline
31 & 0.356406 & 0.712813 & 0.643594 \tabularnewline
32 & 0.308836 & 0.617673 & 0.691164 \tabularnewline
33 & 0.261148 & 0.522296 & 0.738852 \tabularnewline
34 & 0.303542 & 0.607083 & 0.696458 \tabularnewline
35 & 0.2594 & 0.5188 & 0.7406 \tabularnewline
36 & 0.22117 & 0.442341 & 0.77883 \tabularnewline
37 & 0.18362 & 0.367239 & 0.81638 \tabularnewline
38 & 0.155442 & 0.310883 & 0.844558 \tabularnewline
39 & 0.165038 & 0.330076 & 0.834962 \tabularnewline
40 & 0.136836 & 0.273672 & 0.863164 \tabularnewline
41 & 0.261075 & 0.52215 & 0.738925 \tabularnewline
42 & 0.227563 & 0.455126 & 0.772437 \tabularnewline
43 & 0.211289 & 0.422579 & 0.788711 \tabularnewline
44 & 0.18062 & 0.36124 & 0.81938 \tabularnewline
45 & 0.157632 & 0.315264 & 0.842368 \tabularnewline
46 & 0.13442 & 0.26884 & 0.86558 \tabularnewline
47 & 0.112078 & 0.224155 & 0.887922 \tabularnewline
48 & 0.187351 & 0.374702 & 0.812649 \tabularnewline
49 & 0.255595 & 0.51119 & 0.744405 \tabularnewline
50 & 0.230344 & 0.460688 & 0.769656 \tabularnewline
51 & 0.200731 & 0.401461 & 0.799269 \tabularnewline
52 & 0.263327 & 0.526655 & 0.736673 \tabularnewline
53 & 0.228495 & 0.456991 & 0.771505 \tabularnewline
54 & 0.218961 & 0.437922 & 0.781039 \tabularnewline
55 & 0.232826 & 0.465652 & 0.767174 \tabularnewline
56 & 0.20105 & 0.402101 & 0.79895 \tabularnewline
57 & 0.331312 & 0.662625 & 0.668688 \tabularnewline
58 & 0.446679 & 0.893359 & 0.553321 \tabularnewline
59 & 0.406518 & 0.813036 & 0.593482 \tabularnewline
60 & 0.422868 & 0.845737 & 0.577132 \tabularnewline
61 & 0.392502 & 0.785003 & 0.607498 \tabularnewline
62 & 0.366591 & 0.733182 & 0.633409 \tabularnewline
63 & 0.441644 & 0.883288 & 0.558356 \tabularnewline
64 & 0.49548 & 0.990959 & 0.50452 \tabularnewline
65 & 0.465271 & 0.930541 & 0.534729 \tabularnewline
66 & 0.431371 & 0.862743 & 0.568629 \tabularnewline
67 & 0.417572 & 0.835144 & 0.582428 \tabularnewline
68 & 0.381039 & 0.762079 & 0.618961 \tabularnewline
69 & 0.381279 & 0.762558 & 0.618721 \tabularnewline
70 & 0.350915 & 0.70183 & 0.649085 \tabularnewline
71 & 0.319724 & 0.639448 & 0.680276 \tabularnewline
72 & 0.293339 & 0.586678 & 0.706661 \tabularnewline
73 & 0.263214 & 0.526428 & 0.736786 \tabularnewline
74 & 0.26023 & 0.52046 & 0.73977 \tabularnewline
75 & 0.248291 & 0.496582 & 0.751709 \tabularnewline
76 & 0.227876 & 0.455751 & 0.772124 \tabularnewline
77 & 0.212991 & 0.425982 & 0.787009 \tabularnewline
78 & 0.200109 & 0.400218 & 0.799891 \tabularnewline
79 & 0.190531 & 0.381062 & 0.809469 \tabularnewline
80 & 0.247788 & 0.495577 & 0.752212 \tabularnewline
81 & 0.235062 & 0.470124 & 0.764938 \tabularnewline
82 & 0.251566 & 0.503131 & 0.748434 \tabularnewline
83 & 0.230706 & 0.461412 & 0.769294 \tabularnewline
84 & 0.238826 & 0.477653 & 0.761174 \tabularnewline
85 & 0.254754 & 0.509508 & 0.745246 \tabularnewline
86 & 0.227182 & 0.454364 & 0.772818 \tabularnewline
87 & 0.20434 & 0.40868 & 0.79566 \tabularnewline
88 & 0.188586 & 0.377171 & 0.811414 \tabularnewline
89 & 0.200033 & 0.400067 & 0.799967 \tabularnewline
90 & 0.214665 & 0.429331 & 0.785335 \tabularnewline
91 & 0.221568 & 0.443137 & 0.778432 \tabularnewline
92 & 0.365645 & 0.73129 & 0.634355 \tabularnewline
93 & 0.335062 & 0.670124 & 0.664938 \tabularnewline
94 & 0.335394 & 0.670788 & 0.664606 \tabularnewline
95 & 0.408 & 0.816 & 0.592 \tabularnewline
96 & 0.391508 & 0.783016 & 0.608492 \tabularnewline
97 & 0.384649 & 0.769298 & 0.615351 \tabularnewline
98 & 0.361795 & 0.723591 & 0.638205 \tabularnewline
99 & 0.411478 & 0.822956 & 0.588522 \tabularnewline
100 & 0.559223 & 0.881555 & 0.440777 \tabularnewline
101 & 0.527863 & 0.944274 & 0.472137 \tabularnewline
102 & 0.498937 & 0.997874 & 0.501063 \tabularnewline
103 & 0.48465 & 0.969299 & 0.51535 \tabularnewline
104 & 0.522623 & 0.954753 & 0.477377 \tabularnewline
105 & 0.546348 & 0.907303 & 0.453652 \tabularnewline
106 & 0.571709 & 0.856582 & 0.428291 \tabularnewline
107 & 0.549889 & 0.900222 & 0.450111 \tabularnewline
108 & 0.642802 & 0.714396 & 0.357198 \tabularnewline
109 & 0.731993 & 0.536014 & 0.268007 \tabularnewline
110 & 0.740906 & 0.518188 & 0.259094 \tabularnewline
111 & 0.716645 & 0.56671 & 0.283355 \tabularnewline
112 & 0.698759 & 0.602481 & 0.301241 \tabularnewline
113 & 0.752639 & 0.494721 & 0.247361 \tabularnewline
114 & 0.769273 & 0.461454 & 0.230727 \tabularnewline
115 & 0.75666 & 0.48668 & 0.24334 \tabularnewline
116 & 0.804279 & 0.391441 & 0.195721 \tabularnewline
117 & 0.782296 & 0.435409 & 0.217704 \tabularnewline
118 & 0.802699 & 0.394603 & 0.197301 \tabularnewline
119 & 0.777637 & 0.444725 & 0.222363 \tabularnewline
120 & 0.775457 & 0.449085 & 0.224543 \tabularnewline
121 & 0.755914 & 0.488171 & 0.244086 \tabularnewline
122 & 0.866017 & 0.267966 & 0.133983 \tabularnewline
123 & 0.848728 & 0.302544 & 0.151272 \tabularnewline
124 & 0.900895 & 0.19821 & 0.0991049 \tabularnewline
125 & 0.900374 & 0.199251 & 0.0996257 \tabularnewline
126 & 0.89185 & 0.2163 & 0.10815 \tabularnewline
127 & 0.881908 & 0.236185 & 0.118092 \tabularnewline
128 & 0.879637 & 0.240727 & 0.120363 \tabularnewline
129 & 0.867651 & 0.264698 & 0.132349 \tabularnewline
130 & 0.866036 & 0.267928 & 0.133964 \tabularnewline
131 & 0.848176 & 0.303647 & 0.151824 \tabularnewline
132 & 0.827733 & 0.344535 & 0.172267 \tabularnewline
133 & 0.827017 & 0.345966 & 0.172983 \tabularnewline
134 & 0.805579 & 0.388842 & 0.194421 \tabularnewline
135 & 0.806064 & 0.387872 & 0.193936 \tabularnewline
136 & 0.785786 & 0.428428 & 0.214214 \tabularnewline
137 & 0.821051 & 0.357898 & 0.178949 \tabularnewline
138 & 0.862062 & 0.275875 & 0.137938 \tabularnewline
139 & 0.843827 & 0.312346 & 0.156173 \tabularnewline
140 & 0.824894 & 0.350212 & 0.175106 \tabularnewline
141 & 0.809082 & 0.381836 & 0.190918 \tabularnewline
142 & 0.785173 & 0.429653 & 0.214827 \tabularnewline
143 & 0.787916 & 0.424167 & 0.212084 \tabularnewline
144 & 0.76994 & 0.460119 & 0.23006 \tabularnewline
145 & 0.744571 & 0.510857 & 0.255429 \tabularnewline
146 & 0.724231 & 0.551537 & 0.275769 \tabularnewline
147 & 0.718394 & 0.563213 & 0.281606 \tabularnewline
148 & 0.690398 & 0.619205 & 0.309602 \tabularnewline
149 & 0.710453 & 0.579093 & 0.289547 \tabularnewline
150 & 0.684592 & 0.630815 & 0.315408 \tabularnewline
151 & 0.830108 & 0.339784 & 0.169892 \tabularnewline
152 & 0.820563 & 0.358873 & 0.179437 \tabularnewline
153 & 0.800292 & 0.399417 & 0.199708 \tabularnewline
154 & 0.781696 & 0.436607 & 0.218304 \tabularnewline
155 & 0.824593 & 0.350814 & 0.175407 \tabularnewline
156 & 0.813869 & 0.372263 & 0.186131 \tabularnewline
157 & 0.806117 & 0.387767 & 0.193883 \tabularnewline
158 & 0.821499 & 0.357003 & 0.178501 \tabularnewline
159 & 0.801088 & 0.397825 & 0.198912 \tabularnewline
160 & 0.780447 & 0.439107 & 0.219553 \tabularnewline
161 & 0.801346 & 0.397309 & 0.198654 \tabularnewline
162 & 0.788821 & 0.422357 & 0.211179 \tabularnewline
163 & 0.762488 & 0.475023 & 0.237512 \tabularnewline
164 & 0.822072 & 0.355856 & 0.177928 \tabularnewline
165 & 0.821554 & 0.356892 & 0.178446 \tabularnewline
166 & 0.818183 & 0.363635 & 0.181817 \tabularnewline
167 & 0.803192 & 0.393615 & 0.196808 \tabularnewline
168 & 0.80562 & 0.38876 & 0.19438 \tabularnewline
169 & 0.781778 & 0.436444 & 0.218222 \tabularnewline
170 & 0.76748 & 0.46504 & 0.23252 \tabularnewline
171 & 0.740354 & 0.519293 & 0.259646 \tabularnewline
172 & 0.753276 & 0.493449 & 0.246724 \tabularnewline
173 & 0.724958 & 0.550083 & 0.275042 \tabularnewline
174 & 0.696953 & 0.606095 & 0.303047 \tabularnewline
175 & 0.667542 & 0.664916 & 0.332458 \tabularnewline
176 & 0.665987 & 0.668025 & 0.334013 \tabularnewline
177 & 0.639122 & 0.721755 & 0.360878 \tabularnewline
178 & 0.635636 & 0.728728 & 0.364364 \tabularnewline
179 & 0.60274 & 0.794519 & 0.39726 \tabularnewline
180 & 0.617457 & 0.765086 & 0.382543 \tabularnewline
181 & 0.594657 & 0.810685 & 0.405343 \tabularnewline
182 & 0.561021 & 0.877957 & 0.438979 \tabularnewline
183 & 0.559863 & 0.880274 & 0.440137 \tabularnewline
184 & 0.52622 & 0.947561 & 0.47378 \tabularnewline
185 & 0.671369 & 0.657262 & 0.328631 \tabularnewline
186 & 0.640085 & 0.719829 & 0.359915 \tabularnewline
187 & 0.677977 & 0.644047 & 0.322023 \tabularnewline
188 & 0.669748 & 0.660503 & 0.330252 \tabularnewline
189 & 0.640912 & 0.718176 & 0.359088 \tabularnewline
190 & 0.609357 & 0.781285 & 0.390643 \tabularnewline
191 & 0.606301 & 0.787398 & 0.393699 \tabularnewline
192 & 0.59076 & 0.81848 & 0.40924 \tabularnewline
193 & 0.589882 & 0.820235 & 0.410118 \tabularnewline
194 & 0.565468 & 0.869063 & 0.434532 \tabularnewline
195 & 0.565247 & 0.869506 & 0.434753 \tabularnewline
196 & 0.565043 & 0.869914 & 0.434957 \tabularnewline
197 & 0.580937 & 0.838127 & 0.419063 \tabularnewline
198 & 0.544367 & 0.911265 & 0.455633 \tabularnewline
199 & 0.563259 & 0.873483 & 0.436741 \tabularnewline
200 & 0.526345 & 0.947311 & 0.473655 \tabularnewline
201 & 0.5182 & 0.963599 & 0.4818 \tabularnewline
202 & 0.516016 & 0.967969 & 0.483984 \tabularnewline
203 & 0.485837 & 0.971675 & 0.514163 \tabularnewline
204 & 0.450604 & 0.901207 & 0.549396 \tabularnewline
205 & 0.454635 & 0.909271 & 0.545365 \tabularnewline
206 & 0.49238 & 0.984761 & 0.50762 \tabularnewline
207 & 0.47033 & 0.94066 & 0.52967 \tabularnewline
208 & 0.5517 & 0.896599 & 0.4483 \tabularnewline
209 & 0.516437 & 0.967127 & 0.483563 \tabularnewline
210 & 0.48924 & 0.97848 & 0.51076 \tabularnewline
211 & 0.516465 & 0.967071 & 0.483535 \tabularnewline
212 & 0.476029 & 0.952058 & 0.523971 \tabularnewline
213 & 0.470801 & 0.941603 & 0.529199 \tabularnewline
214 & 0.43929 & 0.87858 & 0.56071 \tabularnewline
215 & 0.400845 & 0.801689 & 0.599155 \tabularnewline
216 & 0.383262 & 0.766525 & 0.616738 \tabularnewline
217 & 0.365108 & 0.730216 & 0.634892 \tabularnewline
218 & 0.342385 & 0.684769 & 0.657615 \tabularnewline
219 & 0.323049 & 0.646098 & 0.676951 \tabularnewline
220 & 0.288591 & 0.577181 & 0.711409 \tabularnewline
221 & 0.254951 & 0.509901 & 0.745049 \tabularnewline
222 & 0.25644 & 0.512879 & 0.74356 \tabularnewline
223 & 0.224731 & 0.449462 & 0.775269 \tabularnewline
224 & 0.201043 & 0.402086 & 0.798957 \tabularnewline
225 & 0.252976 & 0.505952 & 0.747024 \tabularnewline
226 & 0.229625 & 0.45925 & 0.770375 \tabularnewline
227 & 0.199919 & 0.399837 & 0.800081 \tabularnewline
228 & 0.273649 & 0.547297 & 0.726351 \tabularnewline
229 & 0.283526 & 0.567052 & 0.716474 \tabularnewline
230 & 0.257106 & 0.514213 & 0.742894 \tabularnewline
231 & 0.226544 & 0.453087 & 0.773456 \tabularnewline
232 & 0.250666 & 0.501333 & 0.749334 \tabularnewline
233 & 0.231725 & 0.463449 & 0.768275 \tabularnewline
234 & 0.240048 & 0.480097 & 0.759952 \tabularnewline
235 & 0.231024 & 0.462047 & 0.768976 \tabularnewline
236 & 0.497862 & 0.995724 & 0.502138 \tabularnewline
237 & 0.454707 & 0.909413 & 0.545293 \tabularnewline
238 & 0.454318 & 0.908636 & 0.545682 \tabularnewline
239 & 0.404545 & 0.80909 & 0.595455 \tabularnewline
240 & 0.387418 & 0.774835 & 0.612582 \tabularnewline
241 & 0.341868 & 0.683737 & 0.658132 \tabularnewline
242 & 0.390611 & 0.781223 & 0.609389 \tabularnewline
243 & 0.343014 & 0.686028 & 0.656986 \tabularnewline
244 & 0.37796 & 0.755919 & 0.62204 \tabularnewline
245 & 0.332835 & 0.665671 & 0.667165 \tabularnewline
246 & 0.302349 & 0.604698 & 0.697651 \tabularnewline
247 & 0.305582 & 0.611164 & 0.694418 \tabularnewline
248 & 0.311844 & 0.623689 & 0.688156 \tabularnewline
249 & 0.274734 & 0.549467 & 0.725266 \tabularnewline
250 & 0.240374 & 0.480749 & 0.759626 \tabularnewline
251 & 0.276425 & 0.55285 & 0.723575 \tabularnewline
252 & 0.235448 & 0.470895 & 0.764552 \tabularnewline
253 & 0.222949 & 0.445898 & 0.777051 \tabularnewline
254 & 0.188414 & 0.376828 & 0.811586 \tabularnewline
255 & 0.176444 & 0.352888 & 0.823556 \tabularnewline
256 & 0.182501 & 0.365002 & 0.817499 \tabularnewline
257 & 0.269736 & 0.539472 & 0.730264 \tabularnewline
258 & 0.48679 & 0.97358 & 0.51321 \tabularnewline
259 & 0.439047 & 0.878094 & 0.560953 \tabularnewline
260 & 0.996004 & 0.00799295 & 0.00399648 \tabularnewline
261 & 0.99352 & 0.0129597 & 0.00647984 \tabularnewline
262 & 0.988601 & 0.0227985 & 0.0113992 \tabularnewline
263 & 0.997631 & 0.00473877 & 0.00236939 \tabularnewline
264 & 0.995275 & 0.00945082 & 0.00472541 \tabularnewline
265 & 0.989692 & 0.0206157 & 0.0103078 \tabularnewline
266 & 0.979567 & 0.0408659 & 0.020433 \tabularnewline
267 & 0.974158 & 0.0516842 & 0.0258421 \tabularnewline
268 & 0.981074 & 0.0378515 & 0.0189258 \tabularnewline
269 & 0.960713 & 0.078573 & 0.0392865 \tabularnewline
270 & 0.95026 & 0.0994804 & 0.0497402 \tabularnewline
271 & 0.947422 & 0.105156 & 0.052578 \tabularnewline
272 & 0.98943 & 0.0211401 & 0.0105701 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264345&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]7[/C][C]0.469088[/C][C]0.938176[/C][C]0.530912[/C][/ROW]
[ROW][C]8[/C][C]0.3362[/C][C]0.6724[/C][C]0.6638[/C][/ROW]
[ROW][C]9[/C][C]0.83207[/C][C]0.335861[/C][C]0.16793[/C][/ROW]
[ROW][C]10[/C][C]0.882227[/C][C]0.235545[/C][C]0.117773[/C][/ROW]
[ROW][C]11[/C][C]0.842243[/C][C]0.315514[/C][C]0.157757[/C][/ROW]
[ROW][C]12[/C][C]0.88273[/C][C]0.234541[/C][C]0.11727[/C][/ROW]
[ROW][C]13[/C][C]0.878817[/C][C]0.242367[/C][C]0.121183[/C][/ROW]
[ROW][C]14[/C][C]0.827892[/C][C]0.344215[/C][C]0.172108[/C][/ROW]
[ROW][C]15[/C][C]0.811505[/C][C]0.376989[/C][C]0.188495[/C][/ROW]
[ROW][C]16[/C][C]0.751672[/C][C]0.496656[/C][C]0.248328[/C][/ROW]
[ROW][C]17[/C][C]0.694294[/C][C]0.611411[/C][C]0.305706[/C][/ROW]
[ROW][C]18[/C][C]0.626539[/C][C]0.746922[/C][C]0.373461[/C][/ROW]
[ROW][C]19[/C][C]0.614032[/C][C]0.771935[/C][C]0.385968[/C][/ROW]
[ROW][C]20[/C][C]0.55677[/C][C]0.886459[/C][C]0.44323[/C][/ROW]
[ROW][C]21[/C][C]0.558367[/C][C]0.883267[/C][C]0.441633[/C][/ROW]
[ROW][C]22[/C][C]0.610049[/C][C]0.779901[/C][C]0.389951[/C][/ROW]
[ROW][C]23[/C][C]0.550482[/C][C]0.899037[/C][C]0.449518[/C][/ROW]
[ROW][C]24[/C][C]0.643385[/C][C]0.71323[/C][C]0.356615[/C][/ROW]
[ROW][C]25[/C][C]0.5929[/C][C]0.814199[/C][C]0.4071[/C][/ROW]
[ROW][C]26[/C][C]0.552948[/C][C]0.894104[/C][C]0.447052[/C][/ROW]
[ROW][C]27[/C][C]0.497703[/C][C]0.995407[/C][C]0.502297[/C][/ROW]
[ROW][C]28[/C][C]0.478513[/C][C]0.957026[/C][C]0.521487[/C][/ROW]
[ROW][C]29[/C][C]0.420401[/C][C]0.840802[/C][C]0.579599[/C][/ROW]
[ROW][C]30[/C][C]0.371713[/C][C]0.743426[/C][C]0.628287[/C][/ROW]
[ROW][C]31[/C][C]0.356406[/C][C]0.712813[/C][C]0.643594[/C][/ROW]
[ROW][C]32[/C][C]0.308836[/C][C]0.617673[/C][C]0.691164[/C][/ROW]
[ROW][C]33[/C][C]0.261148[/C][C]0.522296[/C][C]0.738852[/C][/ROW]
[ROW][C]34[/C][C]0.303542[/C][C]0.607083[/C][C]0.696458[/C][/ROW]
[ROW][C]35[/C][C]0.2594[/C][C]0.5188[/C][C]0.7406[/C][/ROW]
[ROW][C]36[/C][C]0.22117[/C][C]0.442341[/C][C]0.77883[/C][/ROW]
[ROW][C]37[/C][C]0.18362[/C][C]0.367239[/C][C]0.81638[/C][/ROW]
[ROW][C]38[/C][C]0.155442[/C][C]0.310883[/C][C]0.844558[/C][/ROW]
[ROW][C]39[/C][C]0.165038[/C][C]0.330076[/C][C]0.834962[/C][/ROW]
[ROW][C]40[/C][C]0.136836[/C][C]0.273672[/C][C]0.863164[/C][/ROW]
[ROW][C]41[/C][C]0.261075[/C][C]0.52215[/C][C]0.738925[/C][/ROW]
[ROW][C]42[/C][C]0.227563[/C][C]0.455126[/C][C]0.772437[/C][/ROW]
[ROW][C]43[/C][C]0.211289[/C][C]0.422579[/C][C]0.788711[/C][/ROW]
[ROW][C]44[/C][C]0.18062[/C][C]0.36124[/C][C]0.81938[/C][/ROW]
[ROW][C]45[/C][C]0.157632[/C][C]0.315264[/C][C]0.842368[/C][/ROW]
[ROW][C]46[/C][C]0.13442[/C][C]0.26884[/C][C]0.86558[/C][/ROW]
[ROW][C]47[/C][C]0.112078[/C][C]0.224155[/C][C]0.887922[/C][/ROW]
[ROW][C]48[/C][C]0.187351[/C][C]0.374702[/C][C]0.812649[/C][/ROW]
[ROW][C]49[/C][C]0.255595[/C][C]0.51119[/C][C]0.744405[/C][/ROW]
[ROW][C]50[/C][C]0.230344[/C][C]0.460688[/C][C]0.769656[/C][/ROW]
[ROW][C]51[/C][C]0.200731[/C][C]0.401461[/C][C]0.799269[/C][/ROW]
[ROW][C]52[/C][C]0.263327[/C][C]0.526655[/C][C]0.736673[/C][/ROW]
[ROW][C]53[/C][C]0.228495[/C][C]0.456991[/C][C]0.771505[/C][/ROW]
[ROW][C]54[/C][C]0.218961[/C][C]0.437922[/C][C]0.781039[/C][/ROW]
[ROW][C]55[/C][C]0.232826[/C][C]0.465652[/C][C]0.767174[/C][/ROW]
[ROW][C]56[/C][C]0.20105[/C][C]0.402101[/C][C]0.79895[/C][/ROW]
[ROW][C]57[/C][C]0.331312[/C][C]0.662625[/C][C]0.668688[/C][/ROW]
[ROW][C]58[/C][C]0.446679[/C][C]0.893359[/C][C]0.553321[/C][/ROW]
[ROW][C]59[/C][C]0.406518[/C][C]0.813036[/C][C]0.593482[/C][/ROW]
[ROW][C]60[/C][C]0.422868[/C][C]0.845737[/C][C]0.577132[/C][/ROW]
[ROW][C]61[/C][C]0.392502[/C][C]0.785003[/C][C]0.607498[/C][/ROW]
[ROW][C]62[/C][C]0.366591[/C][C]0.733182[/C][C]0.633409[/C][/ROW]
[ROW][C]63[/C][C]0.441644[/C][C]0.883288[/C][C]0.558356[/C][/ROW]
[ROW][C]64[/C][C]0.49548[/C][C]0.990959[/C][C]0.50452[/C][/ROW]
[ROW][C]65[/C][C]0.465271[/C][C]0.930541[/C][C]0.534729[/C][/ROW]
[ROW][C]66[/C][C]0.431371[/C][C]0.862743[/C][C]0.568629[/C][/ROW]
[ROW][C]67[/C][C]0.417572[/C][C]0.835144[/C][C]0.582428[/C][/ROW]
[ROW][C]68[/C][C]0.381039[/C][C]0.762079[/C][C]0.618961[/C][/ROW]
[ROW][C]69[/C][C]0.381279[/C][C]0.762558[/C][C]0.618721[/C][/ROW]
[ROW][C]70[/C][C]0.350915[/C][C]0.70183[/C][C]0.649085[/C][/ROW]
[ROW][C]71[/C][C]0.319724[/C][C]0.639448[/C][C]0.680276[/C][/ROW]
[ROW][C]72[/C][C]0.293339[/C][C]0.586678[/C][C]0.706661[/C][/ROW]
[ROW][C]73[/C][C]0.263214[/C][C]0.526428[/C][C]0.736786[/C][/ROW]
[ROW][C]74[/C][C]0.26023[/C][C]0.52046[/C][C]0.73977[/C][/ROW]
[ROW][C]75[/C][C]0.248291[/C][C]0.496582[/C][C]0.751709[/C][/ROW]
[ROW][C]76[/C][C]0.227876[/C][C]0.455751[/C][C]0.772124[/C][/ROW]
[ROW][C]77[/C][C]0.212991[/C][C]0.425982[/C][C]0.787009[/C][/ROW]
[ROW][C]78[/C][C]0.200109[/C][C]0.400218[/C][C]0.799891[/C][/ROW]
[ROW][C]79[/C][C]0.190531[/C][C]0.381062[/C][C]0.809469[/C][/ROW]
[ROW][C]80[/C][C]0.247788[/C][C]0.495577[/C][C]0.752212[/C][/ROW]
[ROW][C]81[/C][C]0.235062[/C][C]0.470124[/C][C]0.764938[/C][/ROW]
[ROW][C]82[/C][C]0.251566[/C][C]0.503131[/C][C]0.748434[/C][/ROW]
[ROW][C]83[/C][C]0.230706[/C][C]0.461412[/C][C]0.769294[/C][/ROW]
[ROW][C]84[/C][C]0.238826[/C][C]0.477653[/C][C]0.761174[/C][/ROW]
[ROW][C]85[/C][C]0.254754[/C][C]0.509508[/C][C]0.745246[/C][/ROW]
[ROW][C]86[/C][C]0.227182[/C][C]0.454364[/C][C]0.772818[/C][/ROW]
[ROW][C]87[/C][C]0.20434[/C][C]0.40868[/C][C]0.79566[/C][/ROW]
[ROW][C]88[/C][C]0.188586[/C][C]0.377171[/C][C]0.811414[/C][/ROW]
[ROW][C]89[/C][C]0.200033[/C][C]0.400067[/C][C]0.799967[/C][/ROW]
[ROW][C]90[/C][C]0.214665[/C][C]0.429331[/C][C]0.785335[/C][/ROW]
[ROW][C]91[/C][C]0.221568[/C][C]0.443137[/C][C]0.778432[/C][/ROW]
[ROW][C]92[/C][C]0.365645[/C][C]0.73129[/C][C]0.634355[/C][/ROW]
[ROW][C]93[/C][C]0.335062[/C][C]0.670124[/C][C]0.664938[/C][/ROW]
[ROW][C]94[/C][C]0.335394[/C][C]0.670788[/C][C]0.664606[/C][/ROW]
[ROW][C]95[/C][C]0.408[/C][C]0.816[/C][C]0.592[/C][/ROW]
[ROW][C]96[/C][C]0.391508[/C][C]0.783016[/C][C]0.608492[/C][/ROW]
[ROW][C]97[/C][C]0.384649[/C][C]0.769298[/C][C]0.615351[/C][/ROW]
[ROW][C]98[/C][C]0.361795[/C][C]0.723591[/C][C]0.638205[/C][/ROW]
[ROW][C]99[/C][C]0.411478[/C][C]0.822956[/C][C]0.588522[/C][/ROW]
[ROW][C]100[/C][C]0.559223[/C][C]0.881555[/C][C]0.440777[/C][/ROW]
[ROW][C]101[/C][C]0.527863[/C][C]0.944274[/C][C]0.472137[/C][/ROW]
[ROW][C]102[/C][C]0.498937[/C][C]0.997874[/C][C]0.501063[/C][/ROW]
[ROW][C]103[/C][C]0.48465[/C][C]0.969299[/C][C]0.51535[/C][/ROW]
[ROW][C]104[/C][C]0.522623[/C][C]0.954753[/C][C]0.477377[/C][/ROW]
[ROW][C]105[/C][C]0.546348[/C][C]0.907303[/C][C]0.453652[/C][/ROW]
[ROW][C]106[/C][C]0.571709[/C][C]0.856582[/C][C]0.428291[/C][/ROW]
[ROW][C]107[/C][C]0.549889[/C][C]0.900222[/C][C]0.450111[/C][/ROW]
[ROW][C]108[/C][C]0.642802[/C][C]0.714396[/C][C]0.357198[/C][/ROW]
[ROW][C]109[/C][C]0.731993[/C][C]0.536014[/C][C]0.268007[/C][/ROW]
[ROW][C]110[/C][C]0.740906[/C][C]0.518188[/C][C]0.259094[/C][/ROW]
[ROW][C]111[/C][C]0.716645[/C][C]0.56671[/C][C]0.283355[/C][/ROW]
[ROW][C]112[/C][C]0.698759[/C][C]0.602481[/C][C]0.301241[/C][/ROW]
[ROW][C]113[/C][C]0.752639[/C][C]0.494721[/C][C]0.247361[/C][/ROW]
[ROW][C]114[/C][C]0.769273[/C][C]0.461454[/C][C]0.230727[/C][/ROW]
[ROW][C]115[/C][C]0.75666[/C][C]0.48668[/C][C]0.24334[/C][/ROW]
[ROW][C]116[/C][C]0.804279[/C][C]0.391441[/C][C]0.195721[/C][/ROW]
[ROW][C]117[/C][C]0.782296[/C][C]0.435409[/C][C]0.217704[/C][/ROW]
[ROW][C]118[/C][C]0.802699[/C][C]0.394603[/C][C]0.197301[/C][/ROW]
[ROW][C]119[/C][C]0.777637[/C][C]0.444725[/C][C]0.222363[/C][/ROW]
[ROW][C]120[/C][C]0.775457[/C][C]0.449085[/C][C]0.224543[/C][/ROW]
[ROW][C]121[/C][C]0.755914[/C][C]0.488171[/C][C]0.244086[/C][/ROW]
[ROW][C]122[/C][C]0.866017[/C][C]0.267966[/C][C]0.133983[/C][/ROW]
[ROW][C]123[/C][C]0.848728[/C][C]0.302544[/C][C]0.151272[/C][/ROW]
[ROW][C]124[/C][C]0.900895[/C][C]0.19821[/C][C]0.0991049[/C][/ROW]
[ROW][C]125[/C][C]0.900374[/C][C]0.199251[/C][C]0.0996257[/C][/ROW]
[ROW][C]126[/C][C]0.89185[/C][C]0.2163[/C][C]0.10815[/C][/ROW]
[ROW][C]127[/C][C]0.881908[/C][C]0.236185[/C][C]0.118092[/C][/ROW]
[ROW][C]128[/C][C]0.879637[/C][C]0.240727[/C][C]0.120363[/C][/ROW]
[ROW][C]129[/C][C]0.867651[/C][C]0.264698[/C][C]0.132349[/C][/ROW]
[ROW][C]130[/C][C]0.866036[/C][C]0.267928[/C][C]0.133964[/C][/ROW]
[ROW][C]131[/C][C]0.848176[/C][C]0.303647[/C][C]0.151824[/C][/ROW]
[ROW][C]132[/C][C]0.827733[/C][C]0.344535[/C][C]0.172267[/C][/ROW]
[ROW][C]133[/C][C]0.827017[/C][C]0.345966[/C][C]0.172983[/C][/ROW]
[ROW][C]134[/C][C]0.805579[/C][C]0.388842[/C][C]0.194421[/C][/ROW]
[ROW][C]135[/C][C]0.806064[/C][C]0.387872[/C][C]0.193936[/C][/ROW]
[ROW][C]136[/C][C]0.785786[/C][C]0.428428[/C][C]0.214214[/C][/ROW]
[ROW][C]137[/C][C]0.821051[/C][C]0.357898[/C][C]0.178949[/C][/ROW]
[ROW][C]138[/C][C]0.862062[/C][C]0.275875[/C][C]0.137938[/C][/ROW]
[ROW][C]139[/C][C]0.843827[/C][C]0.312346[/C][C]0.156173[/C][/ROW]
[ROW][C]140[/C][C]0.824894[/C][C]0.350212[/C][C]0.175106[/C][/ROW]
[ROW][C]141[/C][C]0.809082[/C][C]0.381836[/C][C]0.190918[/C][/ROW]
[ROW][C]142[/C][C]0.785173[/C][C]0.429653[/C][C]0.214827[/C][/ROW]
[ROW][C]143[/C][C]0.787916[/C][C]0.424167[/C][C]0.212084[/C][/ROW]
[ROW][C]144[/C][C]0.76994[/C][C]0.460119[/C][C]0.23006[/C][/ROW]
[ROW][C]145[/C][C]0.744571[/C][C]0.510857[/C][C]0.255429[/C][/ROW]
[ROW][C]146[/C][C]0.724231[/C][C]0.551537[/C][C]0.275769[/C][/ROW]
[ROW][C]147[/C][C]0.718394[/C][C]0.563213[/C][C]0.281606[/C][/ROW]
[ROW][C]148[/C][C]0.690398[/C][C]0.619205[/C][C]0.309602[/C][/ROW]
[ROW][C]149[/C][C]0.710453[/C][C]0.579093[/C][C]0.289547[/C][/ROW]
[ROW][C]150[/C][C]0.684592[/C][C]0.630815[/C][C]0.315408[/C][/ROW]
[ROW][C]151[/C][C]0.830108[/C][C]0.339784[/C][C]0.169892[/C][/ROW]
[ROW][C]152[/C][C]0.820563[/C][C]0.358873[/C][C]0.179437[/C][/ROW]
[ROW][C]153[/C][C]0.800292[/C][C]0.399417[/C][C]0.199708[/C][/ROW]
[ROW][C]154[/C][C]0.781696[/C][C]0.436607[/C][C]0.218304[/C][/ROW]
[ROW][C]155[/C][C]0.824593[/C][C]0.350814[/C][C]0.175407[/C][/ROW]
[ROW][C]156[/C][C]0.813869[/C][C]0.372263[/C][C]0.186131[/C][/ROW]
[ROW][C]157[/C][C]0.806117[/C][C]0.387767[/C][C]0.193883[/C][/ROW]
[ROW][C]158[/C][C]0.821499[/C][C]0.357003[/C][C]0.178501[/C][/ROW]
[ROW][C]159[/C][C]0.801088[/C][C]0.397825[/C][C]0.198912[/C][/ROW]
[ROW][C]160[/C][C]0.780447[/C][C]0.439107[/C][C]0.219553[/C][/ROW]
[ROW][C]161[/C][C]0.801346[/C][C]0.397309[/C][C]0.198654[/C][/ROW]
[ROW][C]162[/C][C]0.788821[/C][C]0.422357[/C][C]0.211179[/C][/ROW]
[ROW][C]163[/C][C]0.762488[/C][C]0.475023[/C][C]0.237512[/C][/ROW]
[ROW][C]164[/C][C]0.822072[/C][C]0.355856[/C][C]0.177928[/C][/ROW]
[ROW][C]165[/C][C]0.821554[/C][C]0.356892[/C][C]0.178446[/C][/ROW]
[ROW][C]166[/C][C]0.818183[/C][C]0.363635[/C][C]0.181817[/C][/ROW]
[ROW][C]167[/C][C]0.803192[/C][C]0.393615[/C][C]0.196808[/C][/ROW]
[ROW][C]168[/C][C]0.80562[/C][C]0.38876[/C][C]0.19438[/C][/ROW]
[ROW][C]169[/C][C]0.781778[/C][C]0.436444[/C][C]0.218222[/C][/ROW]
[ROW][C]170[/C][C]0.76748[/C][C]0.46504[/C][C]0.23252[/C][/ROW]
[ROW][C]171[/C][C]0.740354[/C][C]0.519293[/C][C]0.259646[/C][/ROW]
[ROW][C]172[/C][C]0.753276[/C][C]0.493449[/C][C]0.246724[/C][/ROW]
[ROW][C]173[/C][C]0.724958[/C][C]0.550083[/C][C]0.275042[/C][/ROW]
[ROW][C]174[/C][C]0.696953[/C][C]0.606095[/C][C]0.303047[/C][/ROW]
[ROW][C]175[/C][C]0.667542[/C][C]0.664916[/C][C]0.332458[/C][/ROW]
[ROW][C]176[/C][C]0.665987[/C][C]0.668025[/C][C]0.334013[/C][/ROW]
[ROW][C]177[/C][C]0.639122[/C][C]0.721755[/C][C]0.360878[/C][/ROW]
[ROW][C]178[/C][C]0.635636[/C][C]0.728728[/C][C]0.364364[/C][/ROW]
[ROW][C]179[/C][C]0.60274[/C][C]0.794519[/C][C]0.39726[/C][/ROW]
[ROW][C]180[/C][C]0.617457[/C][C]0.765086[/C][C]0.382543[/C][/ROW]
[ROW][C]181[/C][C]0.594657[/C][C]0.810685[/C][C]0.405343[/C][/ROW]
[ROW][C]182[/C][C]0.561021[/C][C]0.877957[/C][C]0.438979[/C][/ROW]
[ROW][C]183[/C][C]0.559863[/C][C]0.880274[/C][C]0.440137[/C][/ROW]
[ROW][C]184[/C][C]0.52622[/C][C]0.947561[/C][C]0.47378[/C][/ROW]
[ROW][C]185[/C][C]0.671369[/C][C]0.657262[/C][C]0.328631[/C][/ROW]
[ROW][C]186[/C][C]0.640085[/C][C]0.719829[/C][C]0.359915[/C][/ROW]
[ROW][C]187[/C][C]0.677977[/C][C]0.644047[/C][C]0.322023[/C][/ROW]
[ROW][C]188[/C][C]0.669748[/C][C]0.660503[/C][C]0.330252[/C][/ROW]
[ROW][C]189[/C][C]0.640912[/C][C]0.718176[/C][C]0.359088[/C][/ROW]
[ROW][C]190[/C][C]0.609357[/C][C]0.781285[/C][C]0.390643[/C][/ROW]
[ROW][C]191[/C][C]0.606301[/C][C]0.787398[/C][C]0.393699[/C][/ROW]
[ROW][C]192[/C][C]0.59076[/C][C]0.81848[/C][C]0.40924[/C][/ROW]
[ROW][C]193[/C][C]0.589882[/C][C]0.820235[/C][C]0.410118[/C][/ROW]
[ROW][C]194[/C][C]0.565468[/C][C]0.869063[/C][C]0.434532[/C][/ROW]
[ROW][C]195[/C][C]0.565247[/C][C]0.869506[/C][C]0.434753[/C][/ROW]
[ROW][C]196[/C][C]0.565043[/C][C]0.869914[/C][C]0.434957[/C][/ROW]
[ROW][C]197[/C][C]0.580937[/C][C]0.838127[/C][C]0.419063[/C][/ROW]
[ROW][C]198[/C][C]0.544367[/C][C]0.911265[/C][C]0.455633[/C][/ROW]
[ROW][C]199[/C][C]0.563259[/C][C]0.873483[/C][C]0.436741[/C][/ROW]
[ROW][C]200[/C][C]0.526345[/C][C]0.947311[/C][C]0.473655[/C][/ROW]
[ROW][C]201[/C][C]0.5182[/C][C]0.963599[/C][C]0.4818[/C][/ROW]
[ROW][C]202[/C][C]0.516016[/C][C]0.967969[/C][C]0.483984[/C][/ROW]
[ROW][C]203[/C][C]0.485837[/C][C]0.971675[/C][C]0.514163[/C][/ROW]
[ROW][C]204[/C][C]0.450604[/C][C]0.901207[/C][C]0.549396[/C][/ROW]
[ROW][C]205[/C][C]0.454635[/C][C]0.909271[/C][C]0.545365[/C][/ROW]
[ROW][C]206[/C][C]0.49238[/C][C]0.984761[/C][C]0.50762[/C][/ROW]
[ROW][C]207[/C][C]0.47033[/C][C]0.94066[/C][C]0.52967[/C][/ROW]
[ROW][C]208[/C][C]0.5517[/C][C]0.896599[/C][C]0.4483[/C][/ROW]
[ROW][C]209[/C][C]0.516437[/C][C]0.967127[/C][C]0.483563[/C][/ROW]
[ROW][C]210[/C][C]0.48924[/C][C]0.97848[/C][C]0.51076[/C][/ROW]
[ROW][C]211[/C][C]0.516465[/C][C]0.967071[/C][C]0.483535[/C][/ROW]
[ROW][C]212[/C][C]0.476029[/C][C]0.952058[/C][C]0.523971[/C][/ROW]
[ROW][C]213[/C][C]0.470801[/C][C]0.941603[/C][C]0.529199[/C][/ROW]
[ROW][C]214[/C][C]0.43929[/C][C]0.87858[/C][C]0.56071[/C][/ROW]
[ROW][C]215[/C][C]0.400845[/C][C]0.801689[/C][C]0.599155[/C][/ROW]
[ROW][C]216[/C][C]0.383262[/C][C]0.766525[/C][C]0.616738[/C][/ROW]
[ROW][C]217[/C][C]0.365108[/C][C]0.730216[/C][C]0.634892[/C][/ROW]
[ROW][C]218[/C][C]0.342385[/C][C]0.684769[/C][C]0.657615[/C][/ROW]
[ROW][C]219[/C][C]0.323049[/C][C]0.646098[/C][C]0.676951[/C][/ROW]
[ROW][C]220[/C][C]0.288591[/C][C]0.577181[/C][C]0.711409[/C][/ROW]
[ROW][C]221[/C][C]0.254951[/C][C]0.509901[/C][C]0.745049[/C][/ROW]
[ROW][C]222[/C][C]0.25644[/C][C]0.512879[/C][C]0.74356[/C][/ROW]
[ROW][C]223[/C][C]0.224731[/C][C]0.449462[/C][C]0.775269[/C][/ROW]
[ROW][C]224[/C][C]0.201043[/C][C]0.402086[/C][C]0.798957[/C][/ROW]
[ROW][C]225[/C][C]0.252976[/C][C]0.505952[/C][C]0.747024[/C][/ROW]
[ROW][C]226[/C][C]0.229625[/C][C]0.45925[/C][C]0.770375[/C][/ROW]
[ROW][C]227[/C][C]0.199919[/C][C]0.399837[/C][C]0.800081[/C][/ROW]
[ROW][C]228[/C][C]0.273649[/C][C]0.547297[/C][C]0.726351[/C][/ROW]
[ROW][C]229[/C][C]0.283526[/C][C]0.567052[/C][C]0.716474[/C][/ROW]
[ROW][C]230[/C][C]0.257106[/C][C]0.514213[/C][C]0.742894[/C][/ROW]
[ROW][C]231[/C][C]0.226544[/C][C]0.453087[/C][C]0.773456[/C][/ROW]
[ROW][C]232[/C][C]0.250666[/C][C]0.501333[/C][C]0.749334[/C][/ROW]
[ROW][C]233[/C][C]0.231725[/C][C]0.463449[/C][C]0.768275[/C][/ROW]
[ROW][C]234[/C][C]0.240048[/C][C]0.480097[/C][C]0.759952[/C][/ROW]
[ROW][C]235[/C][C]0.231024[/C][C]0.462047[/C][C]0.768976[/C][/ROW]
[ROW][C]236[/C][C]0.497862[/C][C]0.995724[/C][C]0.502138[/C][/ROW]
[ROW][C]237[/C][C]0.454707[/C][C]0.909413[/C][C]0.545293[/C][/ROW]
[ROW][C]238[/C][C]0.454318[/C][C]0.908636[/C][C]0.545682[/C][/ROW]
[ROW][C]239[/C][C]0.404545[/C][C]0.80909[/C][C]0.595455[/C][/ROW]
[ROW][C]240[/C][C]0.387418[/C][C]0.774835[/C][C]0.612582[/C][/ROW]
[ROW][C]241[/C][C]0.341868[/C][C]0.683737[/C][C]0.658132[/C][/ROW]
[ROW][C]242[/C][C]0.390611[/C][C]0.781223[/C][C]0.609389[/C][/ROW]
[ROW][C]243[/C][C]0.343014[/C][C]0.686028[/C][C]0.656986[/C][/ROW]
[ROW][C]244[/C][C]0.37796[/C][C]0.755919[/C][C]0.62204[/C][/ROW]
[ROW][C]245[/C][C]0.332835[/C][C]0.665671[/C][C]0.667165[/C][/ROW]
[ROW][C]246[/C][C]0.302349[/C][C]0.604698[/C][C]0.697651[/C][/ROW]
[ROW][C]247[/C][C]0.305582[/C][C]0.611164[/C][C]0.694418[/C][/ROW]
[ROW][C]248[/C][C]0.311844[/C][C]0.623689[/C][C]0.688156[/C][/ROW]
[ROW][C]249[/C][C]0.274734[/C][C]0.549467[/C][C]0.725266[/C][/ROW]
[ROW][C]250[/C][C]0.240374[/C][C]0.480749[/C][C]0.759626[/C][/ROW]
[ROW][C]251[/C][C]0.276425[/C][C]0.55285[/C][C]0.723575[/C][/ROW]
[ROW][C]252[/C][C]0.235448[/C][C]0.470895[/C][C]0.764552[/C][/ROW]
[ROW][C]253[/C][C]0.222949[/C][C]0.445898[/C][C]0.777051[/C][/ROW]
[ROW][C]254[/C][C]0.188414[/C][C]0.376828[/C][C]0.811586[/C][/ROW]
[ROW][C]255[/C][C]0.176444[/C][C]0.352888[/C][C]0.823556[/C][/ROW]
[ROW][C]256[/C][C]0.182501[/C][C]0.365002[/C][C]0.817499[/C][/ROW]
[ROW][C]257[/C][C]0.269736[/C][C]0.539472[/C][C]0.730264[/C][/ROW]
[ROW][C]258[/C][C]0.48679[/C][C]0.97358[/C][C]0.51321[/C][/ROW]
[ROW][C]259[/C][C]0.439047[/C][C]0.878094[/C][C]0.560953[/C][/ROW]
[ROW][C]260[/C][C]0.996004[/C][C]0.00799295[/C][C]0.00399648[/C][/ROW]
[ROW][C]261[/C][C]0.99352[/C][C]0.0129597[/C][C]0.00647984[/C][/ROW]
[ROW][C]262[/C][C]0.988601[/C][C]0.0227985[/C][C]0.0113992[/C][/ROW]
[ROW][C]263[/C][C]0.997631[/C][C]0.00473877[/C][C]0.00236939[/C][/ROW]
[ROW][C]264[/C][C]0.995275[/C][C]0.00945082[/C][C]0.00472541[/C][/ROW]
[ROW][C]265[/C][C]0.989692[/C][C]0.0206157[/C][C]0.0103078[/C][/ROW]
[ROW][C]266[/C][C]0.979567[/C][C]0.0408659[/C][C]0.020433[/C][/ROW]
[ROW][C]267[/C][C]0.974158[/C][C]0.0516842[/C][C]0.0258421[/C][/ROW]
[ROW][C]268[/C][C]0.981074[/C][C]0.0378515[/C][C]0.0189258[/C][/ROW]
[ROW][C]269[/C][C]0.960713[/C][C]0.078573[/C][C]0.0392865[/C][/ROW]
[ROW][C]270[/C][C]0.95026[/C][C]0.0994804[/C][C]0.0497402[/C][/ROW]
[ROW][C]271[/C][C]0.947422[/C][C]0.105156[/C][C]0.052578[/C][/ROW]
[ROW][C]272[/C][C]0.98943[/C][C]0.0211401[/C][C]0.0105701[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264345&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264345&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.4690880.9381760.530912
80.33620.67240.6638
90.832070.3358610.16793
100.8822270.2355450.117773
110.8422430.3155140.157757
120.882730.2345410.11727
130.8788170.2423670.121183
140.8278920.3442150.172108
150.8115050.3769890.188495
160.7516720.4966560.248328
170.6942940.6114110.305706
180.6265390.7469220.373461
190.6140320.7719350.385968
200.556770.8864590.44323
210.5583670.8832670.441633
220.6100490.7799010.389951
230.5504820.8990370.449518
240.6433850.713230.356615
250.59290.8141990.4071
260.5529480.8941040.447052
270.4977030.9954070.502297
280.4785130.9570260.521487
290.4204010.8408020.579599
300.3717130.7434260.628287
310.3564060.7128130.643594
320.3088360.6176730.691164
330.2611480.5222960.738852
340.3035420.6070830.696458
350.25940.51880.7406
360.221170.4423410.77883
370.183620.3672390.81638
380.1554420.3108830.844558
390.1650380.3300760.834962
400.1368360.2736720.863164
410.2610750.522150.738925
420.2275630.4551260.772437
430.2112890.4225790.788711
440.180620.361240.81938
450.1576320.3152640.842368
460.134420.268840.86558
470.1120780.2241550.887922
480.1873510.3747020.812649
490.2555950.511190.744405
500.2303440.4606880.769656
510.2007310.4014610.799269
520.2633270.5266550.736673
530.2284950.4569910.771505
540.2189610.4379220.781039
550.2328260.4656520.767174
560.201050.4021010.79895
570.3313120.6626250.668688
580.4466790.8933590.553321
590.4065180.8130360.593482
600.4228680.8457370.577132
610.3925020.7850030.607498
620.3665910.7331820.633409
630.4416440.8832880.558356
640.495480.9909590.50452
650.4652710.9305410.534729
660.4313710.8627430.568629
670.4175720.8351440.582428
680.3810390.7620790.618961
690.3812790.7625580.618721
700.3509150.701830.649085
710.3197240.6394480.680276
720.2933390.5866780.706661
730.2632140.5264280.736786
740.260230.520460.73977
750.2482910.4965820.751709
760.2278760.4557510.772124
770.2129910.4259820.787009
780.2001090.4002180.799891
790.1905310.3810620.809469
800.2477880.4955770.752212
810.2350620.4701240.764938
820.2515660.5031310.748434
830.2307060.4614120.769294
840.2388260.4776530.761174
850.2547540.5095080.745246
860.2271820.4543640.772818
870.204340.408680.79566
880.1885860.3771710.811414
890.2000330.4000670.799967
900.2146650.4293310.785335
910.2215680.4431370.778432
920.3656450.731290.634355
930.3350620.6701240.664938
940.3353940.6707880.664606
950.4080.8160.592
960.3915080.7830160.608492
970.3846490.7692980.615351
980.3617950.7235910.638205
990.4114780.8229560.588522
1000.5592230.8815550.440777
1010.5278630.9442740.472137
1020.4989370.9978740.501063
1030.484650.9692990.51535
1040.5226230.9547530.477377
1050.5463480.9073030.453652
1060.5717090.8565820.428291
1070.5498890.9002220.450111
1080.6428020.7143960.357198
1090.7319930.5360140.268007
1100.7409060.5181880.259094
1110.7166450.566710.283355
1120.6987590.6024810.301241
1130.7526390.4947210.247361
1140.7692730.4614540.230727
1150.756660.486680.24334
1160.8042790.3914410.195721
1170.7822960.4354090.217704
1180.8026990.3946030.197301
1190.7776370.4447250.222363
1200.7754570.4490850.224543
1210.7559140.4881710.244086
1220.8660170.2679660.133983
1230.8487280.3025440.151272
1240.9008950.198210.0991049
1250.9003740.1992510.0996257
1260.891850.21630.10815
1270.8819080.2361850.118092
1280.8796370.2407270.120363
1290.8676510.2646980.132349
1300.8660360.2679280.133964
1310.8481760.3036470.151824
1320.8277330.3445350.172267
1330.8270170.3459660.172983
1340.8055790.3888420.194421
1350.8060640.3878720.193936
1360.7857860.4284280.214214
1370.8210510.3578980.178949
1380.8620620.2758750.137938
1390.8438270.3123460.156173
1400.8248940.3502120.175106
1410.8090820.3818360.190918
1420.7851730.4296530.214827
1430.7879160.4241670.212084
1440.769940.4601190.23006
1450.7445710.5108570.255429
1460.7242310.5515370.275769
1470.7183940.5632130.281606
1480.6903980.6192050.309602
1490.7104530.5790930.289547
1500.6845920.6308150.315408
1510.8301080.3397840.169892
1520.8205630.3588730.179437
1530.8002920.3994170.199708
1540.7816960.4366070.218304
1550.8245930.3508140.175407
1560.8138690.3722630.186131
1570.8061170.3877670.193883
1580.8214990.3570030.178501
1590.8010880.3978250.198912
1600.7804470.4391070.219553
1610.8013460.3973090.198654
1620.7888210.4223570.211179
1630.7624880.4750230.237512
1640.8220720.3558560.177928
1650.8215540.3568920.178446
1660.8181830.3636350.181817
1670.8031920.3936150.196808
1680.805620.388760.19438
1690.7817780.4364440.218222
1700.767480.465040.23252
1710.7403540.5192930.259646
1720.7532760.4934490.246724
1730.7249580.5500830.275042
1740.6969530.6060950.303047
1750.6675420.6649160.332458
1760.6659870.6680250.334013
1770.6391220.7217550.360878
1780.6356360.7287280.364364
1790.602740.7945190.39726
1800.6174570.7650860.382543
1810.5946570.8106850.405343
1820.5610210.8779570.438979
1830.5598630.8802740.440137
1840.526220.9475610.47378
1850.6713690.6572620.328631
1860.6400850.7198290.359915
1870.6779770.6440470.322023
1880.6697480.6605030.330252
1890.6409120.7181760.359088
1900.6093570.7812850.390643
1910.6063010.7873980.393699
1920.590760.818480.40924
1930.5898820.8202350.410118
1940.5654680.8690630.434532
1950.5652470.8695060.434753
1960.5650430.8699140.434957
1970.5809370.8381270.419063
1980.5443670.9112650.455633
1990.5632590.8734830.436741
2000.5263450.9473110.473655
2010.51820.9635990.4818
2020.5160160.9679690.483984
2030.4858370.9716750.514163
2040.4506040.9012070.549396
2050.4546350.9092710.545365
2060.492380.9847610.50762
2070.470330.940660.52967
2080.55170.8965990.4483
2090.5164370.9671270.483563
2100.489240.978480.51076
2110.5164650.9670710.483535
2120.4760290.9520580.523971
2130.4708010.9416030.529199
2140.439290.878580.56071
2150.4008450.8016890.599155
2160.3832620.7665250.616738
2170.3651080.7302160.634892
2180.3423850.6847690.657615
2190.3230490.6460980.676951
2200.2885910.5771810.711409
2210.2549510.5099010.745049
2220.256440.5128790.74356
2230.2247310.4494620.775269
2240.2010430.4020860.798957
2250.2529760.5059520.747024
2260.2296250.459250.770375
2270.1999190.3998370.800081
2280.2736490.5472970.726351
2290.2835260.5670520.716474
2300.2571060.5142130.742894
2310.2265440.4530870.773456
2320.2506660.5013330.749334
2330.2317250.4634490.768275
2340.2400480.4800970.759952
2350.2310240.4620470.768976
2360.4978620.9957240.502138
2370.4547070.9094130.545293
2380.4543180.9086360.545682
2390.4045450.809090.595455
2400.3874180.7748350.612582
2410.3418680.6837370.658132
2420.3906110.7812230.609389
2430.3430140.6860280.656986
2440.377960.7559190.62204
2450.3328350.6656710.667165
2460.3023490.6046980.697651
2470.3055820.6111640.694418
2480.3118440.6236890.688156
2490.2747340.5494670.725266
2500.2403740.4807490.759626
2510.2764250.552850.723575
2520.2354480.4708950.764552
2530.2229490.4458980.777051
2540.1884140.3768280.811586
2550.1764440.3528880.823556
2560.1825010.3650020.817499
2570.2697360.5394720.730264
2580.486790.973580.51321
2590.4390470.8780940.560953
2600.9960040.007992950.00399648
2610.993520.01295970.00647984
2620.9886010.02279850.0113992
2630.9976310.004738770.00236939
2640.9952750.009450820.00472541
2650.9896920.02061570.0103078
2660.9795670.04086590.020433
2670.9741580.05168420.0258421
2680.9810740.03785150.0189258
2690.9607130.0785730.0392865
2700.950260.09948040.0497402
2710.9474220.1051560.052578
2720.989430.02114010.0105701






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level30.0112782NOK
5% type I error level90.0338346OK
10% type I error level120.0451128OK

\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 & 3 & 0.0112782 & NOK \tabularnewline
5% type I error level & 9 & 0.0338346 & OK \tabularnewline
10% type I error level & 12 & 0.0451128 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264345&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]3[/C][C]0.0112782[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]9[/C][C]0.0338346[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]12[/C][C]0.0451128[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264345&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264345&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 level30.0112782NOK
5% type I error level90.0338346OK
10% type I error level120.0451128OK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 4 ; 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')
}