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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 computationThu, 11 Dec 2014 09:07:14 +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/11/t1418288915crhjmq9nky4py4y.htm/, Retrieved Thu, 16 May 2024 06:47:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265643, Retrieved Thu, 16 May 2024 06:47:32 +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)
-       [Multiple Regression] [] [2014-12-11 09:07:14] [6398a3f6f1f2f5e55f0ec79c736f94f8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.00 0.50 0.67 0.67 0.00 7.5
0.89 0.50 0.83 0.33 0.50 6.0
0.89 0.40 1.00 0.67 0.00 6.5
0.89 0.50 0.83 0.00 0.00 1.0
0.89 0.70 0.67 0.00 1.00 1.0
0.78 0.30 0.00 0.00 0.50 5.5
0.89 0.40 0.83 0.67 0.50 8.5
1.00 0.40 0.50 0.67 1.00 6.5
0.89 0.70 0.83 0.00 0.50 4.5
0.78 0.60 0.33 0.67 0.50 2.0
1.00 0.60 0.50 1.00 0.00 5.0
0.78 0.20 0.67 0.00 0.50 0.5
0.89 0.40 1.00 0.00 0.50 5.0
0.89 0.40 0.50 0.67 0.00 5.0
0.89 0.50 0.67 0.33 0.00 2.5
0.89 0.30 0.17 0.67 0.00 5.0
0.89 0.40 0.83 0.33 0.50 5.5
0.67 0.70 0.67 0.33 0.50 3.5
1.00 0.50 0.67 0.33 0.00 3.0
0.78 0.20 0.67 0.00 0.00 4.0
0.78 0.30 0.50 0.67 0.00 0.5
0.89 0.60 1.00 0.33 0.00 6.5
0.78 0.60 0.83 0.33 0.00 4.5
0.89 0.20 0.83 0.33 0.00 7.5
0.89 0.70 1.00 0.67 1.00 5.5
0.33 0.20 0.67 0.00 0.00 4.0
1.00 1.00 1.00 0.33 1.00 7.5
0.89 0.40 0.83 0.67 0.00 7.0
0.89 0.40 1.00 1.00 0.00 4.0
0.67 0.20 0.83 0.67 0.00 5.5
0.56 0.40 0.67 0.33 0.00 2.5
0.89 0.40 0.67 0.00 0.50 5.5
0.89 0.70 1.00 0.67 0.50 3.5
1.00 0.20 0.67 0.67 0.00 2.5
0.78 0.60 1.00 1.00 0.00 4.5
0.78 0.30 1.00 1.00 0.50 4.5
0.33 0.30 0.50 0.33 0.00 4.5
0.78 0.20 0.67 0.00 0.50 6.0
0.89 0.50 0.83 0.67 0.50 2.5
0.89 0.70 1.00 0.67 0.50 5.0
0.78 0.60 1.00 0.67 0.50 0.0
0.89 0.40 1.00 0.67 0.50 5.0
0.89 0.60 1.00 0.33 0.50 6.5
1.00 0.40 1.00 1.00 0.00 5.0
0.67 0.30 0.83 0.67 0.00 6.0
1.00 0.50 0.83 0.67 0.50 4.5
0.89 0.20 0.50 0.00 0.00 5.5
0.89 0.30 0.83 0.00 0.50 1.0
0.89 0.50 0.17 0.00 0.00 7.5
0.78 0.70 0.83 1.00 0.50 6.0
0.89 0.40 1.00 0.67 1.00 5.0
0.78 0.30 1.00 0.00 0.00 1.0
0.78 0.20 0.67 0.67 1.00 5.0
1.00 0.50 1.00 0.00 0.00 6.5
0.78 0.40 1.00 0.00 0.50 7.0
1.00 0.60 1.00 0.67 1.00 4.5
0.78 0.40 0.83 1.00 0.00 0.0
0.67 0.40 0.33 0.00 0.00 8.5
0.33 0.20 0.33 0.33 0.00 3.5
1.00 0.90 1.00 0.67 0.50 7.5
1.00 0.80 1.00 0.67 1.00 3.5
0.78 0.80 0.83 0.00 0.50 6.0
0.67 0.30 1.00 1.00 0.50 1.5
1.00 0.20 0.83 0.67 0.00 9.0
0.89 0.40 0.67 0.00 0.50 3.5
0.89 0.20 0.83 1.00 0.00 3.5
0.78 0.20 0.67 0.67 0.50 4.0
1.00 0.10 0.83 0.67 0.00 6.5
0.56 0.40 0.67 1.00 0.50 7.5
0.67 0.50 1.00 0.00 0.50 6.0
0.89 0.80 0.83 0.33 0.50 5.0
0.89 0.40 0.67 0.67 0.00 5.5
0.89 0.60 0.83 0.33 0.50 3.5
0.89 0.50 0.83 0.67 0.50 7.5
0.78 0.30 0.67 0.00 0.00 6.5
0.89 0.80 1.00 1.00 0.50 NA
1.00 0.40 0.33 0.00 0.50 6.5
1.00 0.60 0.83 0.67 0.50 6.5
0.89 0.40 1.00 0.33 0.00 7.0
0.44 0.30 0.83 0.00 0.00 3.5
0.78 0.80 0.83 0.00 1.00 1.5
0.89 0.60 0.50 0.33 1.00 4.0
0.67 0.30 0.50 0.00 0.00 7.5
0.78 0.50 0.83 0.67 0.50 4.5
0.78 0.40 1.00 0.33 0.00 0.0
0.33 0.30 0.33 0.67 0.00 3.5
0.89 0.70 1.00 0.33 0.00 5.5
0.89 0.20 0.67 0.33 0.50 5.0
0.89 0.40 0.83 1.00 0.00 4.5
0.89 0.60 1.00 0.67 0.50 2.5
0.56 0.60 0.83 0.00 0.00 7.5
0.67 0.60 0.83 0.67 0.50 7.0
0.67 0.40 1.00 0.33 0.50 0.0
0.78 0.60 0.83 0.00 0.00 4.5
0.78 0.50 1.00 0.33 0.50 3.0
0.78 0.50 0.83 0.00 0.00 1.5
0.89 0.60 0.67 0.00 0.00 3.5
1.00 0.80 0.83 0.33 0.50 2.5
0.89 0.50 0.83 0.67 1.00 5.5
0.89 0.60 0.83 0.67 0.50 8.0
0.78 0.40 0.83 0.67 0.50 1.0
1.00 0.30 0.67 0.67 0.50 5.0
0.78 0.30 0.83 1.00 0.00 4.5
0.67 0.20 0.00 0.00 0.00 3.0
0.78 0.40 0.83 0.00 0.00 3.0
0.89 0.50 1.00 0.00 0.00 8.0
0.67 0.30 0.17 0.00 0.50 2.5
0.22 0.40 0.17 0.00 0.50 7.0
0.44 0.50 0.50 1.00 0.00 0.0
0.89 0.30 0.50 0.67 0.00 1.0
0.67 0.50 1.00 0.00 0.00 3.5
0.89 0.40 0.67 0.67 0.00 5.5
0.67 0.40 0.83 0.67 0.00 5.5
0.78 0.60 1.00 0.00 1.00 0.5
0.78 0.30 1.00 0.67 1.00 7.5
0.78 0.40 1.00 0.33 1.00 9
1.00 0.30 1.00 1.00 1.00 9.5
0.78 1.00 1.00 1.00 1.00 8.5
0.67 0.40 1.00 0.00 0.00 7
0.89 0.80 0.83 1.00 0.50 8
0.89 0.30 1.00 0.67 1.00 10
1.00 0.50 0.83 0.67 0.00 7
0.78 0.40 1.00 0.00 0.00 8.5
0.67 0.30 0.83 0.67 0.00 9
0.89 0.50 0.83 1.00 0.00 9.5
0.67 0.30 1.00 0.67 0.00 4
0.67 0.30 0.67 0.00 0.00 6
1.00 0.40 0.83 0.00 0.00 8
0.67 0.30 1.00 0.00 0.00 5.5
1.00 0.60 1.00 0.33 0.50 9.5
0.89 0.60 0.83 0.67 1.00 7.5
0.89 0.40 1.00 1.00 1.00 7
1.00 0.40 1.00 0.00 0.00 7.5
0.67 0.40 1.00 0.67 0.00 8
0.44 0.30 0.67 0.67 0.50 7
0.89 0.20 1.00 0.33 1.00 7
0.56 0.50 0.83 0.67 0.00 6
0.78 0.40 1.00 0.67 1.00 10
1.00 0.40 1.00 0.67 0.00 2.5
1.00 0.40 0.83 0.67 0.00 9
0.89 0.30 0.67 0.67 0.50 8
0.67 0.40 0.83 0.67 1.00 6
0.89 0.20 1.00 0.33 0.50 8.5
0.33 0.00 0.00 0.00 0.00 6
0.89 0.40 1.00 0.67 0.50 9
0.78 0.60 1.00 0.00 1.00 8
1.00 0.40 0.67 0.67 0.00 9
0.44 0.40 1.00 0.00 0.00 5.5
0.67 0.40 0.83 0.00 0.50 7
0.33 0.20 0.17 0.00 0.50 5.5
0.89 0.40 0.83 1.00 1.00 9
0.89 0.30 0.83 0.00 0.00 2
1.00 0.60 0.83 0.67 1.00 8.5
0.89 0.60 0.83 1.00 0.00 9
0.89 0.40 0.83 0.00 0.00 8.5
1.00 0.50 1.00 0.67 1.00 9
0.89 0.40 0.83 0.00 0.50 7.5
1.00 0.60 1.00 1.00 1.00 10
0.78 0.60 0.83 0.67 0.50 9
0.78 0.90 1.00 0.67 0.50 7.5
0.67 0.40 0.83 0.67 0.50 6
0.89 0.80 1.00 1.00 0.50 10.5
0.67 0.50 0.83 1.00 0.00 8.5
0.78 0.40 0.83 1.00 0.00 8
0.89 0.40 1.00 0.67 1.00 10
0.89 0.70 1.00 1.00 1.00 10.5
0.78 0.40 1.00 0.33 1.00 6.5
1.00 0.80 1.00 0.67 0.50 9.5
1.00 0.40 1.00 1.00 1.00 8.5
1.00 0.30 1.00 0.67 0.00 7.5
0.67 0.50 1.00 0.67 0.50 5
0.89 0.80 1.00 0.67 1.00 8
1.00 0.40 0.83 0.33 0.00 10
1.00 1.00 1.00 1.00 0.50 7
0.89 0.50 1.00 0.67 1.00 7.5
0.89 0.50 1.00 0.67 1.00 7.5
0.89 0.30 1.00 0.33 0.00 9.5
0.89 0.30 0.83 0.33 0.50 6
0.89 0.30 0.50 0.00 0.00 10
1.00 0.40 0.67 0.33 0.50 7
0.67 0.50 1.00 0.33 0.00 3
1.00 0.50 0.67 0.67 0.50 6
0.89 0.40 1.00 0.00 0.00 7
0.89 0.70 1.00 1.00 0.50 10
0.89 0.50 0.50 0.33 0.00 7
0.89 0.40 0.67 0.33 1.00 3.5
1.00 0.70 0.67 1.00 0.00 8
1.00 0.70 0.67 1.00 0.00 10
1.00 0.70 0.67 1.00 0.00 5.5
0.89 0.70 0.67 1.00 0.00 6
0.89 0.70 0.67 0.00 0.00 6.5
0.89 0.70 1.00 0.67 0.50 6.5
0.33 0.10 0.67 0.33 0.50 8.5
0.67 0.20 0.67 0.67 0.50 4
0.56 0.30 0.33 0.33 0.00 9.5
0.44 0.60 0.83 0.33 0.00 8
1.00 0.80 1.00 1.00 1.00 8.5
0.89 0.80 1.00 0.33 0.50 5.5
0.33 0.00 0.17 0.00 0.00 7
0.67 0.30 0.67 0.33 0.00 9
0.67 0.60 0.83 0.33 0.50 8
1.00 0.50 0.83 0.67 0.00 10
0.78 0.70 1.00 0.33 0.00 8
0.67 0.30 0.83 0.00 0.50 6
1.00 0.30 1.00 0.67 0.00 8
0.78 0.40 1.00 0.67 0.00 5
0.89 0.40 0.83 1.00 0.00 9
0.89 0.10 0.83 0.00 0.00 4.5
0.89 0.50 1.00 0.67 0.00 8.5
0.00 0.00 0.00 0.00 0.00 9.5
0.67 0.40 1.00 0.33 0.50 8.5
1.00 0.60 0.83 0.67 1.00 7.5
1.00 0.40 1.00 0.33 0.50 7.5
0.67 0.10 0.33 0.00 0.50 5
0.89 0.30 0.83 0.00 0.00 7
0.89 0.70 0.83 0.67 0.00 8
0.56 0.30 0.17 0.00 0.00 5.5
0.67 0.50 0.83 0.33 0.50 8.5
1.00 0.30 0.83 0.67 1.00 9.5
1.00 0.60 0.67 0.67 0.50 7
1.00 0.90 1.00 1.00 0.00 8
0.67 0.40 0.83 0.00 0.50 8.5
0.44 0.30 1.00 0.00 0.50 3.5
0.89 0.90 1.00 0.67 1.00 6.5
0.44 0.50 1.00 0.00 0.50 6.5
0.56 0.30 1.00 1.00 0.50 10.5
0.89 0.60 0.83 0.67 0.00 8.5
0.67 0.20 1.00 0.33 0.00 8
0.89 0.40 0.83 1.00 0.50 10
1.00 0.50 0.83 0.67 0.50 10
0.78 0.40 0.83 0.67 0.00 9.5
0.44 0.00 0.00 0.00 0.00 9
0.89 0.20 1.00 0.33 0.50 10
0.89 0.50 1.00 0.67 0.50 7.5
0.89 0.30 1.00 0.67 0.00 4.5
0.44 0.00 0.00 0.00 0.00 4.5
1.00 0.50 0.83 1.00 0.00 0.5
0.89 0.60 0.83 0.33 0.00 6.5
0.67 0.30 0.83 0.00 0.50 4.5
0.33 0.00 0.00 0.00 0.00 5.5
0.78 0.30 0.67 0.00 0.50 5
0.89 0.50 1.00 0.67 0.50 6
0.78 0.40 0.67 0.00 0.00 4
0.78 0.50 0.83 0.67 0.00 8
0.89 0.70 1.00 1.00 1.00 10.5
0.78 0.80 1.00 0.67 0.50 6.5
0.78 0.60 1.00 0.33 0.50 8
0.67 0.40 0.83 0.33 0.00 8.5
0.89 0.50 0.83 0.33 0.50 5.5
0.89 0.50 1.00 0.00 0.50 7
0.78 0.30 1.00 0.33 0.00 5
1.00 0.60 1.00 0.00 0.50 3.5
1.00 0.30 0.67 0.67 0.00 5
0.78 0.60 0.83 1.00 0.50 9
0.78 0.30 0.33 0.33 0.00 8.5
0.89 0.70 1.00 0.67 1.00 5
0.89 0.70 1.00 1.00 0.00 9.5
0.67 0.60 0.67 1.00 0.50 3
1.00 0.50 1.00 0.33 0.50 1.5
0.67 0.50 0.83 0.33 0.00 6
0.56 0.40 0.67 0.00 0.00 0.5
0.78 0.40 1.00 0.33 1.00 6.5
1.00 0.70 1.00 1.00 0.00 7.5
0.67 0.20 0.17 0.00 0.50 4.5
0.78 0.50 0.83 0.67 0.00 8
0.56 0.40 0.83 0.67 0.50 9
1.00 0.20 1.00 0.67 1.00 7.5
0.89 0.50 0.67 0.67 0.00 8.5
0.44 0.40 0.50 0.00 0.00 7
1.00 0.70 0.67 1.00 1.00 9.5
0.89 0.60 0.83 0.67 1.00 6.5
0.78 0.40 0.83 0.00 0.00 9.5
0.89 0.50 1.00 0.67 1.00 6
0.11 0.00 0.17 0.00 0.00 8
0.89 0.70 1.00 0.67 0.50 9.5
0.89 0.40 0.67 0.67 0.00 8
1.00 0.50 0.67 1.00 0.00 8
0.89 0.60 0.83 0.67 0.00 9
1.00 0.80 0.50 0.67 0.50 5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265643&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265643&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265643&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 time9 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 4.8738 + 0.281126Calculation[t] -0.330574Algebraic_Reasoning[t] + 0.566447Graphical_Interpretation[t] + 1.39892Proportionality_and_Ratio[t] + 0.357192Probability_and_Sampling[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  4.8738 +  0.281126Calculation[t] -0.330574Algebraic_Reasoning[t] +  0.566447Graphical_Interpretation[t] +  1.39892Proportionality_and_Ratio[t] +  0.357192Probability_and_Sampling[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265643&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  4.8738 +  0.281126Calculation[t] -0.330574Algebraic_Reasoning[t] +  0.566447Graphical_Interpretation[t] +  1.39892Proportionality_and_Ratio[t] +  0.357192Probability_and_Sampling[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265643&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265643&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] = + 4.8738 + 0.281126Calculation[t] -0.330574Algebraic_Reasoning[t] + 0.566447Graphical_Interpretation[t] + 1.39892Proportionality_and_Ratio[t] + 0.357192Probability_and_Sampling[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.87380.7257366.7161.08973e-105.44865e-11
Calculation0.2811260.9884870.28440.776320.38816
Algebraic_Reasoning-0.3305740.92055-0.35910.7197950.359897
Graphical_Interpretation0.5664470.7356240.770.4419550.220978
Proportionality_and_Ratio1.398920.4660873.0010.00293680.0014684
Probability_and_Sampling0.3571920.4287440.83310.4055120.202756

\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) & 4.8738 & 0.725736 & 6.716 & 1.08973e-10 & 5.44865e-11 \tabularnewline
Calculation & 0.281126 & 0.988487 & 0.2844 & 0.77632 & 0.38816 \tabularnewline
Algebraic_Reasoning & -0.330574 & 0.92055 & -0.3591 & 0.719795 & 0.359897 \tabularnewline
Graphical_Interpretation & 0.566447 & 0.735624 & 0.77 & 0.441955 & 0.220978 \tabularnewline
Proportionality_and_Ratio & 1.39892 & 0.466087 & 3.001 & 0.0029368 & 0.0014684 \tabularnewline
Probability_and_Sampling & 0.357192 & 0.428744 & 0.8331 & 0.405512 & 0.202756 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265643&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]4.8738[/C][C]0.725736[/C][C]6.716[/C][C]1.08973e-10[/C][C]5.44865e-11[/C][/ROW]
[ROW][C]Calculation[/C][C]0.281126[/C][C]0.988487[/C][C]0.2844[/C][C]0.77632[/C][C]0.38816[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-0.330574[/C][C]0.92055[/C][C]-0.3591[/C][C]0.719795[/C][C]0.359897[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]0.566447[/C][C]0.735624[/C][C]0.77[/C][C]0.441955[/C][C]0.220978[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]1.39892[/C][C]0.466087[/C][C]3.001[/C][C]0.0029368[/C][C]0.0014684[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.357192[/C][C]0.428744[/C][C]0.8331[/C][C]0.405512[/C][C]0.202756[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265643&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265643&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)4.87380.7257366.7161.08973e-105.44865e-11
Calculation0.2811260.9884870.28440.776320.38816
Algebraic_Reasoning-0.3305740.92055-0.35910.7197950.359897
Graphical_Interpretation0.5664470.7356240.770.4419550.220978
Proportionality_and_Ratio1.398920.4660873.0010.00293680.0014684
Probability_and_Sampling0.3571920.4287440.83310.4055120.202756






Multiple Linear Regression - Regression Statistics
Multiple R0.233543
R-squared0.0545421
Adjusted R-squared0.0371624
F-TEST (value)3.13826
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value0.00900818
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.48611
Sum Squared Residuals1681.16

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.233543 \tabularnewline
R-squared & 0.0545421 \tabularnewline
Adjusted R-squared & 0.0371624 \tabularnewline
F-TEST (value) & 3.13826 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 272 \tabularnewline
p-value & 0.00900818 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.48611 \tabularnewline
Sum Squared Residuals & 1681.16 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265643&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.233543[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0545421[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0371624[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]3.13826[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]272[/C][/ROW]
[ROW][C]p-value[/C][C]0.00900818[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.48611[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1681.16[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265643&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265643&T=3

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.233543
R-squared0.0545421
Adjusted R-squared0.0371624
F-TEST (value)3.13826
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value0.00900818
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.48611
Sum Squared Residuals1681.16






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.56.306441.19356
266.06911-0.0691076
36.56.49550.00450103
415.42887-4.42887
515.62931-4.62931
65.55.17250.327497
78.56.57781.9222
86.56.60039-0.100392
94.55.54135-1.04135
1026.19754-4.19754
1156.63873-1.63873
120.55.58508-5.08508
1355.73682-0.736816
1456.21228-1.21228
152.55.79988-3.29988
1656.05841-1.05841
175.56.10217-0.602165
183.55.85051-2.35051
1935.8308-2.8308
2045.40648-1.40648
210.56.21441-5.71441
226.55.953750.54625
234.55.82653-1.32653
247.55.989681.51032
255.56.75352-1.25352
2645.27998-1.27998
277.56.209641.29036
2876.39920.600797
2946.95714-2.95714
305.56.40347-0.90347
312.55.74017-3.24017
325.55.54989-0.0498886
333.56.57492-3.07492
342.56.40561-3.90561
354.56.86011-2.36011
364.57.13787-2.63787
374.55.61227-1.11227
3865.585080.41492
392.56.54474-4.04474
4056.57492-1.57492
4106.57706-6.57706
4256.6741-1.6741
436.56.132350.367654
4456.98807-1.98807
4566.37041-0.370413
464.56.57567-2.07567
475.55.341110.158889
4815.67358-4.67358
497.55.055012.44499
5066.90935-0.909348
5156.85269-1.85269
5215.56035-4.56035
5356.70095-1.70095
546.55.556090.943914
5575.705891.29411
564.56.8175-2.3175
5706.82992-6.82992
588.55.116853.38315
593.55.54903-2.04903
607.56.539730.960268
613.56.75139-3.25139
6265.477370.522634
631.57.10695-5.60695
6496.496242.50376
653.55.54989-2.04989
663.56.92696-3.42696
6746.52236-2.52236
686.56.5293-0.0292993
697.56.856040.643959
7065.641910.358089
7155.96994-0.969935
725.56.30857-0.808572
733.56.03605-2.53605
747.56.544740.955258
756.55.373431.12657
76NANA1.11178
776.56.54261-0.0426082
786.55.519860.980135
7978.86847-1.86847
803.57.65596-4.15596
811.53.52772-2.02772
8241.746212.25379
837.59.51382-2.01382
844.510.4889-5.98894
8502.49161-2.49161
863.53.92069-0.420692
875.56.57765-1.07765
8857.36085-2.36085
894.58.60798-4.10798
902.50.3030372.19696
917.56.949840.550163
92713.1366-6.13661
9300.864885-0.864885
944.57.63448-3.13448
9536.89794-3.89794
961.53.30518-1.80518
973.57.00086-3.50086
982.53.72334-1.22334
995.54.011681.48832
100813.5469-5.54688
10112.55115-1.55115
10257.36298-2.36298
1034.56.49604-1.99604
10435.431-2.431
10530.5251622.47484
106810.7379-2.73787
1072.50.5783111.92169
108713.5144-6.51436
10905.24533-5.24533
11012.96331-1.96331
1113.54.30857-0.808572
1125.56.33736-0.837355
1135.510.8184-5.31837
1140.5-0.1451750.645175
1157.54.846132.65387
11696.878322.12168
1179.58.085071.41493
1188.56.996371.50363
11975.907211.09279
12084.885753.11425
121109.397070.602931
12274.02732.9727
1238.55.870412.62959
12496.327792.67221
1259.511.9667-2.46671
12643.34250.657498
12763.492852.50715
12888.02943-0.0294295
1295.52.163273.33673
1309.58.690280.809719
1317.57.81434-0.314336
13275.089141.91086
1337.55.933651.56635
13487.393720.606282
13576.443170.556828
13677.27337-0.273374
13762.821773.17823
1381014.0264-4.02642
1392.5-0.06987312.56987
14097.520231.47977
14188.69455-0.694548
14263.764582.23542
1438.57.466571.03343
14463.67412.3259
14596.818372.18163
14685.33952.6605
14798.931710.068287
1485.54.078671.42133
14976.675350.32465
1505.53.718041.78196
151912.495-3.49498
15220.2212041.7788
1538.56.294732.20527
15495.961923.03808
1558.56.350562.14944
15697.140521.85948
1577.54.779152.72085
158107.480762.51924
15997.977881.02212
1607.58.01595-0.515951
16162.503513.49649
16210.58.765941.73406
1638.57.329921.17008
16484.852693.14731
165106.715163.28484
16610.510.34610.153867
1676.53.572792.92721
1689.58.345261.15474
1698.57.559480.94052
1707.59.07919-1.57919
17153.720461.27954
17283.954494.04551
173109.968320.0316807
17476.319630.680366
1757.56.819630.680366
1767.54.052923.44708
1779.59.63522-0.135222
17861.308054.69195
179109.042460.957543
18079.92496-2.92496
18133.48503-0.485034
18264.558221.44178
18374.036572.96343
184108.703581.29642
18579.69013-2.69013
1863.52.201971.29803
18784.701973.29803
1881011.202-1.20197
1895.56.17104-0.671044
19064.772121.22788
1916.56.57492-0.0749228
1926.53.953282.54672
1938.510.9914-2.49143
19440.08063133.91937
1959.57.230952.26905
19686.713031.28697
1978.59.06623-0.566231
1985.53.562871.93713
19973.804153.19585
20096.97422.0258
20184.397073.60293
202107.889772.11023
20387.611730.38827
20464.559481.44052
20589.46458-1.46458
20652.860852.13915
207910.0611-1.0611
2084.52.462442.03756
2098.53.87384.6262
2109.57.136612.36339
2118.57.72120.778796
2127.56.229381.27062
2137.57.89462-0.394621
21453.494981.50502
21575.300031.69997
21687.528350.471645
2175.53.007262.49274
2188.55.820382.67962
2199.58.951980.548023
22075.822781.17722
22185.078672.92133
2228.510.6434-2.14337
2233.53.6874-0.187404
2246.55.577250.922748
2256.53.076033.42397
22610.58.333092.16691
2278.56.524131.97587
22885.039442.96056
229106.575673.42433
230106.868283.13172
2319.55.49754.0025
23295.264583.73542
233109.141040.858962
2347.59.52856-2.02856
2354.54.9975-0.497496
2364.510.8587-6.35871
2370.5-0.1425460.642546
2386.57.61173-1.11173
2394.53.966570.533428
2405.56.05202-0.552022
24155.64104-0.641038
24267.34037-1.34037
24342.335221.66478
24484.715163.28484
24510.510.5109-0.0109415
2466.54.601421.89858
24785.361722.63828
2488.59.06911-0.569108
2495.54.203761.29624
25078.022-1.022
25157.20162-2.20162
2523.54.87255-1.37255
25352.942412.05759
25496.142482.85752
2558.510.2535-1.75352
25652.357972.64203
2579.513.3209-3.82085
25837.69633-4.69633
2591.51.328660.171336
260610.7785-4.77852
2610.50.3461330.153867
2626.55.88890.611105
2637.58.27093-0.770932
2644.52.835221.66478
26585.485032.51497
26698.449730.55027
2677.55.275512.22449
2688.56.648491.85151
26974.559162.44084
2709.59.69028-0.190281
2716.52.4314.069
2729.510.3196-0.819634
27363.001022.99898
27485.074922.92508
2759.57.808571.69143
27686.768081.23192
27785.333092.66691
278910.2896-1.28957
2795NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 6.30644 & 1.19356 \tabularnewline
2 & 6 & 6.06911 & -0.0691076 \tabularnewline
3 & 6.5 & 6.4955 & 0.00450103 \tabularnewline
4 & 1 & 5.42887 & -4.42887 \tabularnewline
5 & 1 & 5.62931 & -4.62931 \tabularnewline
6 & 5.5 & 5.1725 & 0.327497 \tabularnewline
7 & 8.5 & 6.5778 & 1.9222 \tabularnewline
8 & 6.5 & 6.60039 & -0.100392 \tabularnewline
9 & 4.5 & 5.54135 & -1.04135 \tabularnewline
10 & 2 & 6.19754 & -4.19754 \tabularnewline
11 & 5 & 6.63873 & -1.63873 \tabularnewline
12 & 0.5 & 5.58508 & -5.08508 \tabularnewline
13 & 5 & 5.73682 & -0.736816 \tabularnewline
14 & 5 & 6.21228 & -1.21228 \tabularnewline
15 & 2.5 & 5.79988 & -3.29988 \tabularnewline
16 & 5 & 6.05841 & -1.05841 \tabularnewline
17 & 5.5 & 6.10217 & -0.602165 \tabularnewline
18 & 3.5 & 5.85051 & -2.35051 \tabularnewline
19 & 3 & 5.8308 & -2.8308 \tabularnewline
20 & 4 & 5.40648 & -1.40648 \tabularnewline
21 & 0.5 & 6.21441 & -5.71441 \tabularnewline
22 & 6.5 & 5.95375 & 0.54625 \tabularnewline
23 & 4.5 & 5.82653 & -1.32653 \tabularnewline
24 & 7.5 & 5.98968 & 1.51032 \tabularnewline
25 & 5.5 & 6.75352 & -1.25352 \tabularnewline
26 & 4 & 5.27998 & -1.27998 \tabularnewline
27 & 7.5 & 6.20964 & 1.29036 \tabularnewline
28 & 7 & 6.3992 & 0.600797 \tabularnewline
29 & 4 & 6.95714 & -2.95714 \tabularnewline
30 & 5.5 & 6.40347 & -0.90347 \tabularnewline
31 & 2.5 & 5.74017 & -3.24017 \tabularnewline
32 & 5.5 & 5.54989 & -0.0498886 \tabularnewline
33 & 3.5 & 6.57492 & -3.07492 \tabularnewline
34 & 2.5 & 6.40561 & -3.90561 \tabularnewline
35 & 4.5 & 6.86011 & -2.36011 \tabularnewline
36 & 4.5 & 7.13787 & -2.63787 \tabularnewline
37 & 4.5 & 5.61227 & -1.11227 \tabularnewline
38 & 6 & 5.58508 & 0.41492 \tabularnewline
39 & 2.5 & 6.54474 & -4.04474 \tabularnewline
40 & 5 & 6.57492 & -1.57492 \tabularnewline
41 & 0 & 6.57706 & -6.57706 \tabularnewline
42 & 5 & 6.6741 & -1.6741 \tabularnewline
43 & 6.5 & 6.13235 & 0.367654 \tabularnewline
44 & 5 & 6.98807 & -1.98807 \tabularnewline
45 & 6 & 6.37041 & -0.370413 \tabularnewline
46 & 4.5 & 6.57567 & -2.07567 \tabularnewline
47 & 5.5 & 5.34111 & 0.158889 \tabularnewline
48 & 1 & 5.67358 & -4.67358 \tabularnewline
49 & 7.5 & 5.05501 & 2.44499 \tabularnewline
50 & 6 & 6.90935 & -0.909348 \tabularnewline
51 & 5 & 6.85269 & -1.85269 \tabularnewline
52 & 1 & 5.56035 & -4.56035 \tabularnewline
53 & 5 & 6.70095 & -1.70095 \tabularnewline
54 & 6.5 & 5.55609 & 0.943914 \tabularnewline
55 & 7 & 5.70589 & 1.29411 \tabularnewline
56 & 4.5 & 6.8175 & -2.3175 \tabularnewline
57 & 0 & 6.82992 & -6.82992 \tabularnewline
58 & 8.5 & 5.11685 & 3.38315 \tabularnewline
59 & 3.5 & 5.54903 & -2.04903 \tabularnewline
60 & 7.5 & 6.53973 & 0.960268 \tabularnewline
61 & 3.5 & 6.75139 & -3.25139 \tabularnewline
62 & 6 & 5.47737 & 0.522634 \tabularnewline
63 & 1.5 & 7.10695 & -5.60695 \tabularnewline
64 & 9 & 6.49624 & 2.50376 \tabularnewline
65 & 3.5 & 5.54989 & -2.04989 \tabularnewline
66 & 3.5 & 6.92696 & -3.42696 \tabularnewline
67 & 4 & 6.52236 & -2.52236 \tabularnewline
68 & 6.5 & 6.5293 & -0.0292993 \tabularnewline
69 & 7.5 & 6.85604 & 0.643959 \tabularnewline
70 & 6 & 5.64191 & 0.358089 \tabularnewline
71 & 5 & 5.96994 & -0.969935 \tabularnewline
72 & 5.5 & 6.30857 & -0.808572 \tabularnewline
73 & 3.5 & 6.03605 & -2.53605 \tabularnewline
74 & 7.5 & 6.54474 & 0.955258 \tabularnewline
75 & 6.5 & 5.37343 & 1.12657 \tabularnewline
76 & NA & NA & 1.11178 \tabularnewline
77 & 6.5 & 6.54261 & -0.0426082 \tabularnewline
78 & 6.5 & 5.51986 & 0.980135 \tabularnewline
79 & 7 & 8.86847 & -1.86847 \tabularnewline
80 & 3.5 & 7.65596 & -4.15596 \tabularnewline
81 & 1.5 & 3.52772 & -2.02772 \tabularnewline
82 & 4 & 1.74621 & 2.25379 \tabularnewline
83 & 7.5 & 9.51382 & -2.01382 \tabularnewline
84 & 4.5 & 10.4889 & -5.98894 \tabularnewline
85 & 0 & 2.49161 & -2.49161 \tabularnewline
86 & 3.5 & 3.92069 & -0.420692 \tabularnewline
87 & 5.5 & 6.57765 & -1.07765 \tabularnewline
88 & 5 & 7.36085 & -2.36085 \tabularnewline
89 & 4.5 & 8.60798 & -4.10798 \tabularnewline
90 & 2.5 & 0.303037 & 2.19696 \tabularnewline
91 & 7.5 & 6.94984 & 0.550163 \tabularnewline
92 & 7 & 13.1366 & -6.13661 \tabularnewline
93 & 0 & 0.864885 & -0.864885 \tabularnewline
94 & 4.5 & 7.63448 & -3.13448 \tabularnewline
95 & 3 & 6.89794 & -3.89794 \tabularnewline
96 & 1.5 & 3.30518 & -1.80518 \tabularnewline
97 & 3.5 & 7.00086 & -3.50086 \tabularnewline
98 & 2.5 & 3.72334 & -1.22334 \tabularnewline
99 & 5.5 & 4.01168 & 1.48832 \tabularnewline
100 & 8 & 13.5469 & -5.54688 \tabularnewline
101 & 1 & 2.55115 & -1.55115 \tabularnewline
102 & 5 & 7.36298 & -2.36298 \tabularnewline
103 & 4.5 & 6.49604 & -1.99604 \tabularnewline
104 & 3 & 5.431 & -2.431 \tabularnewline
105 & 3 & 0.525162 & 2.47484 \tabularnewline
106 & 8 & 10.7379 & -2.73787 \tabularnewline
107 & 2.5 & 0.578311 & 1.92169 \tabularnewline
108 & 7 & 13.5144 & -6.51436 \tabularnewline
109 & 0 & 5.24533 & -5.24533 \tabularnewline
110 & 1 & 2.96331 & -1.96331 \tabularnewline
111 & 3.5 & 4.30857 & -0.808572 \tabularnewline
112 & 5.5 & 6.33736 & -0.837355 \tabularnewline
113 & 5.5 & 10.8184 & -5.31837 \tabularnewline
114 & 0.5 & -0.145175 & 0.645175 \tabularnewline
115 & 7.5 & 4.84613 & 2.65387 \tabularnewline
116 & 9 & 6.87832 & 2.12168 \tabularnewline
117 & 9.5 & 8.08507 & 1.41493 \tabularnewline
118 & 8.5 & 6.99637 & 1.50363 \tabularnewline
119 & 7 & 5.90721 & 1.09279 \tabularnewline
120 & 8 & 4.88575 & 3.11425 \tabularnewline
121 & 10 & 9.39707 & 0.602931 \tabularnewline
122 & 7 & 4.0273 & 2.9727 \tabularnewline
123 & 8.5 & 5.87041 & 2.62959 \tabularnewline
124 & 9 & 6.32779 & 2.67221 \tabularnewline
125 & 9.5 & 11.9667 & -2.46671 \tabularnewline
126 & 4 & 3.3425 & 0.657498 \tabularnewline
127 & 6 & 3.49285 & 2.50715 \tabularnewline
128 & 8 & 8.02943 & -0.0294295 \tabularnewline
129 & 5.5 & 2.16327 & 3.33673 \tabularnewline
130 & 9.5 & 8.69028 & 0.809719 \tabularnewline
131 & 7.5 & 7.81434 & -0.314336 \tabularnewline
132 & 7 & 5.08914 & 1.91086 \tabularnewline
133 & 7.5 & 5.93365 & 1.56635 \tabularnewline
134 & 8 & 7.39372 & 0.606282 \tabularnewline
135 & 7 & 6.44317 & 0.556828 \tabularnewline
136 & 7 & 7.27337 & -0.273374 \tabularnewline
137 & 6 & 2.82177 & 3.17823 \tabularnewline
138 & 10 & 14.0264 & -4.02642 \tabularnewline
139 & 2.5 & -0.0698731 & 2.56987 \tabularnewline
140 & 9 & 7.52023 & 1.47977 \tabularnewline
141 & 8 & 8.69455 & -0.694548 \tabularnewline
142 & 6 & 3.76458 & 2.23542 \tabularnewline
143 & 8.5 & 7.46657 & 1.03343 \tabularnewline
144 & 6 & 3.6741 & 2.3259 \tabularnewline
145 & 9 & 6.81837 & 2.18163 \tabularnewline
146 & 8 & 5.3395 & 2.6605 \tabularnewline
147 & 9 & 8.93171 & 0.068287 \tabularnewline
148 & 5.5 & 4.07867 & 1.42133 \tabularnewline
149 & 7 & 6.67535 & 0.32465 \tabularnewline
150 & 5.5 & 3.71804 & 1.78196 \tabularnewline
151 & 9 & 12.495 & -3.49498 \tabularnewline
152 & 2 & 0.221204 & 1.7788 \tabularnewline
153 & 8.5 & 6.29473 & 2.20527 \tabularnewline
154 & 9 & 5.96192 & 3.03808 \tabularnewline
155 & 8.5 & 6.35056 & 2.14944 \tabularnewline
156 & 9 & 7.14052 & 1.85948 \tabularnewline
157 & 7.5 & 4.77915 & 2.72085 \tabularnewline
158 & 10 & 7.48076 & 2.51924 \tabularnewline
159 & 9 & 7.97788 & 1.02212 \tabularnewline
160 & 7.5 & 8.01595 & -0.515951 \tabularnewline
161 & 6 & 2.50351 & 3.49649 \tabularnewline
162 & 10.5 & 8.76594 & 1.73406 \tabularnewline
163 & 8.5 & 7.32992 & 1.17008 \tabularnewline
164 & 8 & 4.85269 & 3.14731 \tabularnewline
165 & 10 & 6.71516 & 3.28484 \tabularnewline
166 & 10.5 & 10.3461 & 0.153867 \tabularnewline
167 & 6.5 & 3.57279 & 2.92721 \tabularnewline
168 & 9.5 & 8.34526 & 1.15474 \tabularnewline
169 & 8.5 & 7.55948 & 0.94052 \tabularnewline
170 & 7.5 & 9.07919 & -1.57919 \tabularnewline
171 & 5 & 3.72046 & 1.27954 \tabularnewline
172 & 8 & 3.95449 & 4.04551 \tabularnewline
173 & 10 & 9.96832 & 0.0316807 \tabularnewline
174 & 7 & 6.31963 & 0.680366 \tabularnewline
175 & 7.5 & 6.81963 & 0.680366 \tabularnewline
176 & 7.5 & 4.05292 & 3.44708 \tabularnewline
177 & 9.5 & 9.63522 & -0.135222 \tabularnewline
178 & 6 & 1.30805 & 4.69195 \tabularnewline
179 & 10 & 9.04246 & 0.957543 \tabularnewline
180 & 7 & 9.92496 & -2.92496 \tabularnewline
181 & 3 & 3.48503 & -0.485034 \tabularnewline
182 & 6 & 4.55822 & 1.44178 \tabularnewline
183 & 7 & 4.03657 & 2.96343 \tabularnewline
184 & 10 & 8.70358 & 1.29642 \tabularnewline
185 & 7 & 9.69013 & -2.69013 \tabularnewline
186 & 3.5 & 2.20197 & 1.29803 \tabularnewline
187 & 8 & 4.70197 & 3.29803 \tabularnewline
188 & 10 & 11.202 & -1.20197 \tabularnewline
189 & 5.5 & 6.17104 & -0.671044 \tabularnewline
190 & 6 & 4.77212 & 1.22788 \tabularnewline
191 & 6.5 & 6.57492 & -0.0749228 \tabularnewline
192 & 6.5 & 3.95328 & 2.54672 \tabularnewline
193 & 8.5 & 10.9914 & -2.49143 \tabularnewline
194 & 4 & 0.0806313 & 3.91937 \tabularnewline
195 & 9.5 & 7.23095 & 2.26905 \tabularnewline
196 & 8 & 6.71303 & 1.28697 \tabularnewline
197 & 8.5 & 9.06623 & -0.566231 \tabularnewline
198 & 5.5 & 3.56287 & 1.93713 \tabularnewline
199 & 7 & 3.80415 & 3.19585 \tabularnewline
200 & 9 & 6.9742 & 2.0258 \tabularnewline
201 & 8 & 4.39707 & 3.60293 \tabularnewline
202 & 10 & 7.88977 & 2.11023 \tabularnewline
203 & 8 & 7.61173 & 0.38827 \tabularnewline
204 & 6 & 4.55948 & 1.44052 \tabularnewline
205 & 8 & 9.46458 & -1.46458 \tabularnewline
206 & 5 & 2.86085 & 2.13915 \tabularnewline
207 & 9 & 10.0611 & -1.0611 \tabularnewline
208 & 4.5 & 2.46244 & 2.03756 \tabularnewline
209 & 8.5 & 3.8738 & 4.6262 \tabularnewline
210 & 9.5 & 7.13661 & 2.36339 \tabularnewline
211 & 8.5 & 7.7212 & 0.778796 \tabularnewline
212 & 7.5 & 6.22938 & 1.27062 \tabularnewline
213 & 7.5 & 7.89462 & -0.394621 \tabularnewline
214 & 5 & 3.49498 & 1.50502 \tabularnewline
215 & 7 & 5.30003 & 1.69997 \tabularnewline
216 & 8 & 7.52835 & 0.471645 \tabularnewline
217 & 5.5 & 3.00726 & 2.49274 \tabularnewline
218 & 8.5 & 5.82038 & 2.67962 \tabularnewline
219 & 9.5 & 8.95198 & 0.548023 \tabularnewline
220 & 7 & 5.82278 & 1.17722 \tabularnewline
221 & 8 & 5.07867 & 2.92133 \tabularnewline
222 & 8.5 & 10.6434 & -2.14337 \tabularnewline
223 & 3.5 & 3.6874 & -0.187404 \tabularnewline
224 & 6.5 & 5.57725 & 0.922748 \tabularnewline
225 & 6.5 & 3.07603 & 3.42397 \tabularnewline
226 & 10.5 & 8.33309 & 2.16691 \tabularnewline
227 & 8.5 & 6.52413 & 1.97587 \tabularnewline
228 & 8 & 5.03944 & 2.96056 \tabularnewline
229 & 10 & 6.57567 & 3.42433 \tabularnewline
230 & 10 & 6.86828 & 3.13172 \tabularnewline
231 & 9.5 & 5.4975 & 4.0025 \tabularnewline
232 & 9 & 5.26458 & 3.73542 \tabularnewline
233 & 10 & 9.14104 & 0.858962 \tabularnewline
234 & 7.5 & 9.52856 & -2.02856 \tabularnewline
235 & 4.5 & 4.9975 & -0.497496 \tabularnewline
236 & 4.5 & 10.8587 & -6.35871 \tabularnewline
237 & 0.5 & -0.142546 & 0.642546 \tabularnewline
238 & 6.5 & 7.61173 & -1.11173 \tabularnewline
239 & 4.5 & 3.96657 & 0.533428 \tabularnewline
240 & 5.5 & 6.05202 & -0.552022 \tabularnewline
241 & 5 & 5.64104 & -0.641038 \tabularnewline
242 & 6 & 7.34037 & -1.34037 \tabularnewline
243 & 4 & 2.33522 & 1.66478 \tabularnewline
244 & 8 & 4.71516 & 3.28484 \tabularnewline
245 & 10.5 & 10.5109 & -0.0109415 \tabularnewline
246 & 6.5 & 4.60142 & 1.89858 \tabularnewline
247 & 8 & 5.36172 & 2.63828 \tabularnewline
248 & 8.5 & 9.06911 & -0.569108 \tabularnewline
249 & 5.5 & 4.20376 & 1.29624 \tabularnewline
250 & 7 & 8.022 & -1.022 \tabularnewline
251 & 5 & 7.20162 & -2.20162 \tabularnewline
252 & 3.5 & 4.87255 & -1.37255 \tabularnewline
253 & 5 & 2.94241 & 2.05759 \tabularnewline
254 & 9 & 6.14248 & 2.85752 \tabularnewline
255 & 8.5 & 10.2535 & -1.75352 \tabularnewline
256 & 5 & 2.35797 & 2.64203 \tabularnewline
257 & 9.5 & 13.3209 & -3.82085 \tabularnewline
258 & 3 & 7.69633 & -4.69633 \tabularnewline
259 & 1.5 & 1.32866 & 0.171336 \tabularnewline
260 & 6 & 10.7785 & -4.77852 \tabularnewline
261 & 0.5 & 0.346133 & 0.153867 \tabularnewline
262 & 6.5 & 5.8889 & 0.611105 \tabularnewline
263 & 7.5 & 8.27093 & -0.770932 \tabularnewline
264 & 4.5 & 2.83522 & 1.66478 \tabularnewline
265 & 8 & 5.48503 & 2.51497 \tabularnewline
266 & 9 & 8.44973 & 0.55027 \tabularnewline
267 & 7.5 & 5.27551 & 2.22449 \tabularnewline
268 & 8.5 & 6.64849 & 1.85151 \tabularnewline
269 & 7 & 4.55916 & 2.44084 \tabularnewline
270 & 9.5 & 9.69028 & -0.190281 \tabularnewline
271 & 6.5 & 2.431 & 4.069 \tabularnewline
272 & 9.5 & 10.3196 & -0.819634 \tabularnewline
273 & 6 & 3.00102 & 2.99898 \tabularnewline
274 & 8 & 5.07492 & 2.92508 \tabularnewline
275 & 9.5 & 7.80857 & 1.69143 \tabularnewline
276 & 8 & 6.76808 & 1.23192 \tabularnewline
277 & 8 & 5.33309 & 2.66691 \tabularnewline
278 & 9 & 10.2896 & -1.28957 \tabularnewline
279 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265643&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]6.30644[/C][C]1.19356[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]6.06911[/C][C]-0.0691076[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]6.4955[/C][C]0.00450103[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]5.42887[/C][C]-4.42887[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.62931[/C][C]-4.62931[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]5.1725[/C][C]0.327497[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]6.5778[/C][C]1.9222[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]6.60039[/C][C]-0.100392[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]5.54135[/C][C]-1.04135[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]6.19754[/C][C]-4.19754[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]6.63873[/C][C]-1.63873[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]5.58508[/C][C]-5.08508[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]5.73682[/C][C]-0.736816[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]6.21228[/C][C]-1.21228[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]5.79988[/C][C]-3.29988[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]6.05841[/C][C]-1.05841[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]6.10217[/C][C]-0.602165[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]5.85051[/C][C]-2.35051[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]5.8308[/C][C]-2.8308[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]5.40648[/C][C]-1.40648[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]6.21441[/C][C]-5.71441[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]5.95375[/C][C]0.54625[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]5.82653[/C][C]-1.32653[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]5.98968[/C][C]1.51032[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]6.75352[/C][C]-1.25352[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]5.27998[/C][C]-1.27998[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]6.20964[/C][C]1.29036[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]6.3992[/C][C]0.600797[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]6.95714[/C][C]-2.95714[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]6.40347[/C][C]-0.90347[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]5.74017[/C][C]-3.24017[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]5.54989[/C][C]-0.0498886[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]6.57492[/C][C]-3.07492[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]6.40561[/C][C]-3.90561[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]6.86011[/C][C]-2.36011[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]7.13787[/C][C]-2.63787[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.61227[/C][C]-1.11227[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]5.58508[/C][C]0.41492[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]6.54474[/C][C]-4.04474[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]6.57492[/C][C]-1.57492[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]6.57706[/C][C]-6.57706[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.6741[/C][C]-1.6741[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]6.13235[/C][C]0.367654[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]6.98807[/C][C]-1.98807[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]6.37041[/C][C]-0.370413[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]6.57567[/C][C]-2.07567[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]5.34111[/C][C]0.158889[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]5.67358[/C][C]-4.67358[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]5.05501[/C][C]2.44499[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]6.90935[/C][C]-0.909348[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]6.85269[/C][C]-1.85269[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]5.56035[/C][C]-4.56035[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]6.70095[/C][C]-1.70095[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]5.55609[/C][C]0.943914[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]5.70589[/C][C]1.29411[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]6.8175[/C][C]-2.3175[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]6.82992[/C][C]-6.82992[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]5.11685[/C][C]3.38315[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]5.54903[/C][C]-2.04903[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]6.53973[/C][C]0.960268[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]6.75139[/C][C]-3.25139[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]5.47737[/C][C]0.522634[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]7.10695[/C][C]-5.60695[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]6.49624[/C][C]2.50376[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]5.54989[/C][C]-2.04989[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]6.92696[/C][C]-3.42696[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]6.52236[/C][C]-2.52236[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]6.5293[/C][C]-0.0292993[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]6.85604[/C][C]0.643959[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]5.64191[/C][C]0.358089[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]5.96994[/C][C]-0.969935[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]6.30857[/C][C]-0.808572[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]6.03605[/C][C]-2.53605[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]6.54474[/C][C]0.955258[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]5.37343[/C][C]1.12657[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]1.11178[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]6.54261[/C][C]-0.0426082[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]5.51986[/C][C]0.980135[/C][/ROW]
[ROW][C]79[/C][C]7[/C][C]8.86847[/C][C]-1.86847[/C][/ROW]
[ROW][C]80[/C][C]3.5[/C][C]7.65596[/C][C]-4.15596[/C][/ROW]
[ROW][C]81[/C][C]1.5[/C][C]3.52772[/C][C]-2.02772[/C][/ROW]
[ROW][C]82[/C][C]4[/C][C]1.74621[/C][C]2.25379[/C][/ROW]
[ROW][C]83[/C][C]7.5[/C][C]9.51382[/C][C]-2.01382[/C][/ROW]
[ROW][C]84[/C][C]4.5[/C][C]10.4889[/C][C]-5.98894[/C][/ROW]
[ROW][C]85[/C][C]0[/C][C]2.49161[/C][C]-2.49161[/C][/ROW]
[ROW][C]86[/C][C]3.5[/C][C]3.92069[/C][C]-0.420692[/C][/ROW]
[ROW][C]87[/C][C]5.5[/C][C]6.57765[/C][C]-1.07765[/C][/ROW]
[ROW][C]88[/C][C]5[/C][C]7.36085[/C][C]-2.36085[/C][/ROW]
[ROW][C]89[/C][C]4.5[/C][C]8.60798[/C][C]-4.10798[/C][/ROW]
[ROW][C]90[/C][C]2.5[/C][C]0.303037[/C][C]2.19696[/C][/ROW]
[ROW][C]91[/C][C]7.5[/C][C]6.94984[/C][C]0.550163[/C][/ROW]
[ROW][C]92[/C][C]7[/C][C]13.1366[/C][C]-6.13661[/C][/ROW]
[ROW][C]93[/C][C]0[/C][C]0.864885[/C][C]-0.864885[/C][/ROW]
[ROW][C]94[/C][C]4.5[/C][C]7.63448[/C][C]-3.13448[/C][/ROW]
[ROW][C]95[/C][C]3[/C][C]6.89794[/C][C]-3.89794[/C][/ROW]
[ROW][C]96[/C][C]1.5[/C][C]3.30518[/C][C]-1.80518[/C][/ROW]
[ROW][C]97[/C][C]3.5[/C][C]7.00086[/C][C]-3.50086[/C][/ROW]
[ROW][C]98[/C][C]2.5[/C][C]3.72334[/C][C]-1.22334[/C][/ROW]
[ROW][C]99[/C][C]5.5[/C][C]4.01168[/C][C]1.48832[/C][/ROW]
[ROW][C]100[/C][C]8[/C][C]13.5469[/C][C]-5.54688[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]2.55115[/C][C]-1.55115[/C][/ROW]
[ROW][C]102[/C][C]5[/C][C]7.36298[/C][C]-2.36298[/C][/ROW]
[ROW][C]103[/C][C]4.5[/C][C]6.49604[/C][C]-1.99604[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]5.431[/C][C]-2.431[/C][/ROW]
[ROW][C]105[/C][C]3[/C][C]0.525162[/C][C]2.47484[/C][/ROW]
[ROW][C]106[/C][C]8[/C][C]10.7379[/C][C]-2.73787[/C][/ROW]
[ROW][C]107[/C][C]2.5[/C][C]0.578311[/C][C]1.92169[/C][/ROW]
[ROW][C]108[/C][C]7[/C][C]13.5144[/C][C]-6.51436[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]5.24533[/C][C]-5.24533[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]2.96331[/C][C]-1.96331[/C][/ROW]
[ROW][C]111[/C][C]3.5[/C][C]4.30857[/C][C]-0.808572[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]6.33736[/C][C]-0.837355[/C][/ROW]
[ROW][C]113[/C][C]5.5[/C][C]10.8184[/C][C]-5.31837[/C][/ROW]
[ROW][C]114[/C][C]0.5[/C][C]-0.145175[/C][C]0.645175[/C][/ROW]
[ROW][C]115[/C][C]7.5[/C][C]4.84613[/C][C]2.65387[/C][/ROW]
[ROW][C]116[/C][C]9[/C][C]6.87832[/C][C]2.12168[/C][/ROW]
[ROW][C]117[/C][C]9.5[/C][C]8.08507[/C][C]1.41493[/C][/ROW]
[ROW][C]118[/C][C]8.5[/C][C]6.99637[/C][C]1.50363[/C][/ROW]
[ROW][C]119[/C][C]7[/C][C]5.90721[/C][C]1.09279[/C][/ROW]
[ROW][C]120[/C][C]8[/C][C]4.88575[/C][C]3.11425[/C][/ROW]
[ROW][C]121[/C][C]10[/C][C]9.39707[/C][C]0.602931[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]4.0273[/C][C]2.9727[/C][/ROW]
[ROW][C]123[/C][C]8.5[/C][C]5.87041[/C][C]2.62959[/C][/ROW]
[ROW][C]124[/C][C]9[/C][C]6.32779[/C][C]2.67221[/C][/ROW]
[ROW][C]125[/C][C]9.5[/C][C]11.9667[/C][C]-2.46671[/C][/ROW]
[ROW][C]126[/C][C]4[/C][C]3.3425[/C][C]0.657498[/C][/ROW]
[ROW][C]127[/C][C]6[/C][C]3.49285[/C][C]2.50715[/C][/ROW]
[ROW][C]128[/C][C]8[/C][C]8.02943[/C][C]-0.0294295[/C][/ROW]
[ROW][C]129[/C][C]5.5[/C][C]2.16327[/C][C]3.33673[/C][/ROW]
[ROW][C]130[/C][C]9.5[/C][C]8.69028[/C][C]0.809719[/C][/ROW]
[ROW][C]131[/C][C]7.5[/C][C]7.81434[/C][C]-0.314336[/C][/ROW]
[ROW][C]132[/C][C]7[/C][C]5.08914[/C][C]1.91086[/C][/ROW]
[ROW][C]133[/C][C]7.5[/C][C]5.93365[/C][C]1.56635[/C][/ROW]
[ROW][C]134[/C][C]8[/C][C]7.39372[/C][C]0.606282[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]6.44317[/C][C]0.556828[/C][/ROW]
[ROW][C]136[/C][C]7[/C][C]7.27337[/C][C]-0.273374[/C][/ROW]
[ROW][C]137[/C][C]6[/C][C]2.82177[/C][C]3.17823[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]14.0264[/C][C]-4.02642[/C][/ROW]
[ROW][C]139[/C][C]2.5[/C][C]-0.0698731[/C][C]2.56987[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]7.52023[/C][C]1.47977[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]8.69455[/C][C]-0.694548[/C][/ROW]
[ROW][C]142[/C][C]6[/C][C]3.76458[/C][C]2.23542[/C][/ROW]
[ROW][C]143[/C][C]8.5[/C][C]7.46657[/C][C]1.03343[/C][/ROW]
[ROW][C]144[/C][C]6[/C][C]3.6741[/C][C]2.3259[/C][/ROW]
[ROW][C]145[/C][C]9[/C][C]6.81837[/C][C]2.18163[/C][/ROW]
[ROW][C]146[/C][C]8[/C][C]5.3395[/C][C]2.6605[/C][/ROW]
[ROW][C]147[/C][C]9[/C][C]8.93171[/C][C]0.068287[/C][/ROW]
[ROW][C]148[/C][C]5.5[/C][C]4.07867[/C][C]1.42133[/C][/ROW]
[ROW][C]149[/C][C]7[/C][C]6.67535[/C][C]0.32465[/C][/ROW]
[ROW][C]150[/C][C]5.5[/C][C]3.71804[/C][C]1.78196[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]12.495[/C][C]-3.49498[/C][/ROW]
[ROW][C]152[/C][C]2[/C][C]0.221204[/C][C]1.7788[/C][/ROW]
[ROW][C]153[/C][C]8.5[/C][C]6.29473[/C][C]2.20527[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]5.96192[/C][C]3.03808[/C][/ROW]
[ROW][C]155[/C][C]8.5[/C][C]6.35056[/C][C]2.14944[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]7.14052[/C][C]1.85948[/C][/ROW]
[ROW][C]157[/C][C]7.5[/C][C]4.77915[/C][C]2.72085[/C][/ROW]
[ROW][C]158[/C][C]10[/C][C]7.48076[/C][C]2.51924[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]7.97788[/C][C]1.02212[/C][/ROW]
[ROW][C]160[/C][C]7.5[/C][C]8.01595[/C][C]-0.515951[/C][/ROW]
[ROW][C]161[/C][C]6[/C][C]2.50351[/C][C]3.49649[/C][/ROW]
[ROW][C]162[/C][C]10.5[/C][C]8.76594[/C][C]1.73406[/C][/ROW]
[ROW][C]163[/C][C]8.5[/C][C]7.32992[/C][C]1.17008[/C][/ROW]
[ROW][C]164[/C][C]8[/C][C]4.85269[/C][C]3.14731[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]6.71516[/C][C]3.28484[/C][/ROW]
[ROW][C]166[/C][C]10.5[/C][C]10.3461[/C][C]0.153867[/C][/ROW]
[ROW][C]167[/C][C]6.5[/C][C]3.57279[/C][C]2.92721[/C][/ROW]
[ROW][C]168[/C][C]9.5[/C][C]8.34526[/C][C]1.15474[/C][/ROW]
[ROW][C]169[/C][C]8.5[/C][C]7.55948[/C][C]0.94052[/C][/ROW]
[ROW][C]170[/C][C]7.5[/C][C]9.07919[/C][C]-1.57919[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]3.72046[/C][C]1.27954[/C][/ROW]
[ROW][C]172[/C][C]8[/C][C]3.95449[/C][C]4.04551[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]9.96832[/C][C]0.0316807[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]6.31963[/C][C]0.680366[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]6.81963[/C][C]0.680366[/C][/ROW]
[ROW][C]176[/C][C]7.5[/C][C]4.05292[/C][C]3.44708[/C][/ROW]
[ROW][C]177[/C][C]9.5[/C][C]9.63522[/C][C]-0.135222[/C][/ROW]
[ROW][C]178[/C][C]6[/C][C]1.30805[/C][C]4.69195[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]9.04246[/C][C]0.957543[/C][/ROW]
[ROW][C]180[/C][C]7[/C][C]9.92496[/C][C]-2.92496[/C][/ROW]
[ROW][C]181[/C][C]3[/C][C]3.48503[/C][C]-0.485034[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]4.55822[/C][C]1.44178[/C][/ROW]
[ROW][C]183[/C][C]7[/C][C]4.03657[/C][C]2.96343[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]8.70358[/C][C]1.29642[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]9.69013[/C][C]-2.69013[/C][/ROW]
[ROW][C]186[/C][C]3.5[/C][C]2.20197[/C][C]1.29803[/C][/ROW]
[ROW][C]187[/C][C]8[/C][C]4.70197[/C][C]3.29803[/C][/ROW]
[ROW][C]188[/C][C]10[/C][C]11.202[/C][C]-1.20197[/C][/ROW]
[ROW][C]189[/C][C]5.5[/C][C]6.17104[/C][C]-0.671044[/C][/ROW]
[ROW][C]190[/C][C]6[/C][C]4.77212[/C][C]1.22788[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]6.57492[/C][C]-0.0749228[/C][/ROW]
[ROW][C]192[/C][C]6.5[/C][C]3.95328[/C][C]2.54672[/C][/ROW]
[ROW][C]193[/C][C]8.5[/C][C]10.9914[/C][C]-2.49143[/C][/ROW]
[ROW][C]194[/C][C]4[/C][C]0.0806313[/C][C]3.91937[/C][/ROW]
[ROW][C]195[/C][C]9.5[/C][C]7.23095[/C][C]2.26905[/C][/ROW]
[ROW][C]196[/C][C]8[/C][C]6.71303[/C][C]1.28697[/C][/ROW]
[ROW][C]197[/C][C]8.5[/C][C]9.06623[/C][C]-0.566231[/C][/ROW]
[ROW][C]198[/C][C]5.5[/C][C]3.56287[/C][C]1.93713[/C][/ROW]
[ROW][C]199[/C][C]7[/C][C]3.80415[/C][C]3.19585[/C][/ROW]
[ROW][C]200[/C][C]9[/C][C]6.9742[/C][C]2.0258[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]4.39707[/C][C]3.60293[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]7.88977[/C][C]2.11023[/C][/ROW]
[ROW][C]203[/C][C]8[/C][C]7.61173[/C][C]0.38827[/C][/ROW]
[ROW][C]204[/C][C]6[/C][C]4.55948[/C][C]1.44052[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]9.46458[/C][C]-1.46458[/C][/ROW]
[ROW][C]206[/C][C]5[/C][C]2.86085[/C][C]2.13915[/C][/ROW]
[ROW][C]207[/C][C]9[/C][C]10.0611[/C][C]-1.0611[/C][/ROW]
[ROW][C]208[/C][C]4.5[/C][C]2.46244[/C][C]2.03756[/C][/ROW]
[ROW][C]209[/C][C]8.5[/C][C]3.8738[/C][C]4.6262[/C][/ROW]
[ROW][C]210[/C][C]9.5[/C][C]7.13661[/C][C]2.36339[/C][/ROW]
[ROW][C]211[/C][C]8.5[/C][C]7.7212[/C][C]0.778796[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]6.22938[/C][C]1.27062[/C][/ROW]
[ROW][C]213[/C][C]7.5[/C][C]7.89462[/C][C]-0.394621[/C][/ROW]
[ROW][C]214[/C][C]5[/C][C]3.49498[/C][C]1.50502[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]5.30003[/C][C]1.69997[/C][/ROW]
[ROW][C]216[/C][C]8[/C][C]7.52835[/C][C]0.471645[/C][/ROW]
[ROW][C]217[/C][C]5.5[/C][C]3.00726[/C][C]2.49274[/C][/ROW]
[ROW][C]218[/C][C]8.5[/C][C]5.82038[/C][C]2.67962[/C][/ROW]
[ROW][C]219[/C][C]9.5[/C][C]8.95198[/C][C]0.548023[/C][/ROW]
[ROW][C]220[/C][C]7[/C][C]5.82278[/C][C]1.17722[/C][/ROW]
[ROW][C]221[/C][C]8[/C][C]5.07867[/C][C]2.92133[/C][/ROW]
[ROW][C]222[/C][C]8.5[/C][C]10.6434[/C][C]-2.14337[/C][/ROW]
[ROW][C]223[/C][C]3.5[/C][C]3.6874[/C][C]-0.187404[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]5.57725[/C][C]0.922748[/C][/ROW]
[ROW][C]225[/C][C]6.5[/C][C]3.07603[/C][C]3.42397[/C][/ROW]
[ROW][C]226[/C][C]10.5[/C][C]8.33309[/C][C]2.16691[/C][/ROW]
[ROW][C]227[/C][C]8.5[/C][C]6.52413[/C][C]1.97587[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]5.03944[/C][C]2.96056[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]6.57567[/C][C]3.42433[/C][/ROW]
[ROW][C]230[/C][C]10[/C][C]6.86828[/C][C]3.13172[/C][/ROW]
[ROW][C]231[/C][C]9.5[/C][C]5.4975[/C][C]4.0025[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]5.26458[/C][C]3.73542[/C][/ROW]
[ROW][C]233[/C][C]10[/C][C]9.14104[/C][C]0.858962[/C][/ROW]
[ROW][C]234[/C][C]7.5[/C][C]9.52856[/C][C]-2.02856[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]4.9975[/C][C]-0.497496[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]10.8587[/C][C]-6.35871[/C][/ROW]
[ROW][C]237[/C][C]0.5[/C][C]-0.142546[/C][C]0.642546[/C][/ROW]
[ROW][C]238[/C][C]6.5[/C][C]7.61173[/C][C]-1.11173[/C][/ROW]
[ROW][C]239[/C][C]4.5[/C][C]3.96657[/C][C]0.533428[/C][/ROW]
[ROW][C]240[/C][C]5.5[/C][C]6.05202[/C][C]-0.552022[/C][/ROW]
[ROW][C]241[/C][C]5[/C][C]5.64104[/C][C]-0.641038[/C][/ROW]
[ROW][C]242[/C][C]6[/C][C]7.34037[/C][C]-1.34037[/C][/ROW]
[ROW][C]243[/C][C]4[/C][C]2.33522[/C][C]1.66478[/C][/ROW]
[ROW][C]244[/C][C]8[/C][C]4.71516[/C][C]3.28484[/C][/ROW]
[ROW][C]245[/C][C]10.5[/C][C]10.5109[/C][C]-0.0109415[/C][/ROW]
[ROW][C]246[/C][C]6.5[/C][C]4.60142[/C][C]1.89858[/C][/ROW]
[ROW][C]247[/C][C]8[/C][C]5.36172[/C][C]2.63828[/C][/ROW]
[ROW][C]248[/C][C]8.5[/C][C]9.06911[/C][C]-0.569108[/C][/ROW]
[ROW][C]249[/C][C]5.5[/C][C]4.20376[/C][C]1.29624[/C][/ROW]
[ROW][C]250[/C][C]7[/C][C]8.022[/C][C]-1.022[/C][/ROW]
[ROW][C]251[/C][C]5[/C][C]7.20162[/C][C]-2.20162[/C][/ROW]
[ROW][C]252[/C][C]3.5[/C][C]4.87255[/C][C]-1.37255[/C][/ROW]
[ROW][C]253[/C][C]5[/C][C]2.94241[/C][C]2.05759[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]6.14248[/C][C]2.85752[/C][/ROW]
[ROW][C]255[/C][C]8.5[/C][C]10.2535[/C][C]-1.75352[/C][/ROW]
[ROW][C]256[/C][C]5[/C][C]2.35797[/C][C]2.64203[/C][/ROW]
[ROW][C]257[/C][C]9.5[/C][C]13.3209[/C][C]-3.82085[/C][/ROW]
[ROW][C]258[/C][C]3[/C][C]7.69633[/C][C]-4.69633[/C][/ROW]
[ROW][C]259[/C][C]1.5[/C][C]1.32866[/C][C]0.171336[/C][/ROW]
[ROW][C]260[/C][C]6[/C][C]10.7785[/C][C]-4.77852[/C][/ROW]
[ROW][C]261[/C][C]0.5[/C][C]0.346133[/C][C]0.153867[/C][/ROW]
[ROW][C]262[/C][C]6.5[/C][C]5.8889[/C][C]0.611105[/C][/ROW]
[ROW][C]263[/C][C]7.5[/C][C]8.27093[/C][C]-0.770932[/C][/ROW]
[ROW][C]264[/C][C]4.5[/C][C]2.83522[/C][C]1.66478[/C][/ROW]
[ROW][C]265[/C][C]8[/C][C]5.48503[/C][C]2.51497[/C][/ROW]
[ROW][C]266[/C][C]9[/C][C]8.44973[/C][C]0.55027[/C][/ROW]
[ROW][C]267[/C][C]7.5[/C][C]5.27551[/C][C]2.22449[/C][/ROW]
[ROW][C]268[/C][C]8.5[/C][C]6.64849[/C][C]1.85151[/C][/ROW]
[ROW][C]269[/C][C]7[/C][C]4.55916[/C][C]2.44084[/C][/ROW]
[ROW][C]270[/C][C]9.5[/C][C]9.69028[/C][C]-0.190281[/C][/ROW]
[ROW][C]271[/C][C]6.5[/C][C]2.431[/C][C]4.069[/C][/ROW]
[ROW][C]272[/C][C]9.5[/C][C]10.3196[/C][C]-0.819634[/C][/ROW]
[ROW][C]273[/C][C]6[/C][C]3.00102[/C][C]2.99898[/C][/ROW]
[ROW][C]274[/C][C]8[/C][C]5.07492[/C][C]2.92508[/C][/ROW]
[ROW][C]275[/C][C]9.5[/C][C]7.80857[/C][C]1.69143[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]6.76808[/C][C]1.23192[/C][/ROW]
[ROW][C]277[/C][C]8[/C][C]5.33309[/C][C]2.66691[/C][/ROW]
[ROW][C]278[/C][C]9[/C][C]10.2896[/C][C]-1.28957[/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=265643&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265643&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
17.56.306441.19356
266.06911-0.0691076
36.56.49550.00450103
415.42887-4.42887
515.62931-4.62931
65.55.17250.327497
78.56.57781.9222
86.56.60039-0.100392
94.55.54135-1.04135
1026.19754-4.19754
1156.63873-1.63873
120.55.58508-5.08508
1355.73682-0.736816
1456.21228-1.21228
152.55.79988-3.29988
1656.05841-1.05841
175.56.10217-0.602165
183.55.85051-2.35051
1935.8308-2.8308
2045.40648-1.40648
210.56.21441-5.71441
226.55.953750.54625
234.55.82653-1.32653
247.55.989681.51032
255.56.75352-1.25352
2645.27998-1.27998
277.56.209641.29036
2876.39920.600797
2946.95714-2.95714
305.56.40347-0.90347
312.55.74017-3.24017
325.55.54989-0.0498886
333.56.57492-3.07492
342.56.40561-3.90561
354.56.86011-2.36011
364.57.13787-2.63787
374.55.61227-1.11227
3865.585080.41492
392.56.54474-4.04474
4056.57492-1.57492
4106.57706-6.57706
4256.6741-1.6741
436.56.132350.367654
4456.98807-1.98807
4566.37041-0.370413
464.56.57567-2.07567
475.55.341110.158889
4815.67358-4.67358
497.55.055012.44499
5066.90935-0.909348
5156.85269-1.85269
5215.56035-4.56035
5356.70095-1.70095
546.55.556090.943914
5575.705891.29411
564.56.8175-2.3175
5706.82992-6.82992
588.55.116853.38315
593.55.54903-2.04903
607.56.539730.960268
613.56.75139-3.25139
6265.477370.522634
631.57.10695-5.60695
6496.496242.50376
653.55.54989-2.04989
663.56.92696-3.42696
6746.52236-2.52236
686.56.5293-0.0292993
697.56.856040.643959
7065.641910.358089
7155.96994-0.969935
725.56.30857-0.808572
733.56.03605-2.53605
747.56.544740.955258
756.55.373431.12657
76NANA1.11178
776.56.54261-0.0426082
786.55.519860.980135
7978.86847-1.86847
803.57.65596-4.15596
811.53.52772-2.02772
8241.746212.25379
837.59.51382-2.01382
844.510.4889-5.98894
8502.49161-2.49161
863.53.92069-0.420692
875.56.57765-1.07765
8857.36085-2.36085
894.58.60798-4.10798
902.50.3030372.19696
917.56.949840.550163
92713.1366-6.13661
9300.864885-0.864885
944.57.63448-3.13448
9536.89794-3.89794
961.53.30518-1.80518
973.57.00086-3.50086
982.53.72334-1.22334
995.54.011681.48832
100813.5469-5.54688
10112.55115-1.55115
10257.36298-2.36298
1034.56.49604-1.99604
10435.431-2.431
10530.5251622.47484
106810.7379-2.73787
1072.50.5783111.92169
108713.5144-6.51436
10905.24533-5.24533
11012.96331-1.96331
1113.54.30857-0.808572
1125.56.33736-0.837355
1135.510.8184-5.31837
1140.5-0.1451750.645175
1157.54.846132.65387
11696.878322.12168
1179.58.085071.41493
1188.56.996371.50363
11975.907211.09279
12084.885753.11425
121109.397070.602931
12274.02732.9727
1238.55.870412.62959
12496.327792.67221
1259.511.9667-2.46671
12643.34250.657498
12763.492852.50715
12888.02943-0.0294295
1295.52.163273.33673
1309.58.690280.809719
1317.57.81434-0.314336
13275.089141.91086
1337.55.933651.56635
13487.393720.606282
13576.443170.556828
13677.27337-0.273374
13762.821773.17823
1381014.0264-4.02642
1392.5-0.06987312.56987
14097.520231.47977
14188.69455-0.694548
14263.764582.23542
1438.57.466571.03343
14463.67412.3259
14596.818372.18163
14685.33952.6605
14798.931710.068287
1485.54.078671.42133
14976.675350.32465
1505.53.718041.78196
151912.495-3.49498
15220.2212041.7788
1538.56.294732.20527
15495.961923.03808
1558.56.350562.14944
15697.140521.85948
1577.54.779152.72085
158107.480762.51924
15997.977881.02212
1607.58.01595-0.515951
16162.503513.49649
16210.58.765941.73406
1638.57.329921.17008
16484.852693.14731
165106.715163.28484
16610.510.34610.153867
1676.53.572792.92721
1689.58.345261.15474
1698.57.559480.94052
1707.59.07919-1.57919
17153.720461.27954
17283.954494.04551
173109.968320.0316807
17476.319630.680366
1757.56.819630.680366
1767.54.052923.44708
1779.59.63522-0.135222
17861.308054.69195
179109.042460.957543
18079.92496-2.92496
18133.48503-0.485034
18264.558221.44178
18374.036572.96343
184108.703581.29642
18579.69013-2.69013
1863.52.201971.29803
18784.701973.29803
1881011.202-1.20197
1895.56.17104-0.671044
19064.772121.22788
1916.56.57492-0.0749228
1926.53.953282.54672
1938.510.9914-2.49143
19440.08063133.91937
1959.57.230952.26905
19686.713031.28697
1978.59.06623-0.566231
1985.53.562871.93713
19973.804153.19585
20096.97422.0258
20184.397073.60293
202107.889772.11023
20387.611730.38827
20464.559481.44052
20589.46458-1.46458
20652.860852.13915
207910.0611-1.0611
2084.52.462442.03756
2098.53.87384.6262
2109.57.136612.36339
2118.57.72120.778796
2127.56.229381.27062
2137.57.89462-0.394621
21453.494981.50502
21575.300031.69997
21687.528350.471645
2175.53.007262.49274
2188.55.820382.67962
2199.58.951980.548023
22075.822781.17722
22185.078672.92133
2228.510.6434-2.14337
2233.53.6874-0.187404
2246.55.577250.922748
2256.53.076033.42397
22610.58.333092.16691
2278.56.524131.97587
22885.039442.96056
229106.575673.42433
230106.868283.13172
2319.55.49754.0025
23295.264583.73542
233109.141040.858962
2347.59.52856-2.02856
2354.54.9975-0.497496
2364.510.8587-6.35871
2370.5-0.1425460.642546
2386.57.61173-1.11173
2394.53.966570.533428
2405.56.05202-0.552022
24155.64104-0.641038
24267.34037-1.34037
24342.335221.66478
24484.715163.28484
24510.510.5109-0.0109415
2466.54.601421.89858
24785.361722.63828
2488.59.06911-0.569108
2495.54.203761.29624
25078.022-1.022
25157.20162-2.20162
2523.54.87255-1.37255
25352.942412.05759
25496.142482.85752
2558.510.2535-1.75352
25652.357972.64203
2579.513.3209-3.82085
25837.69633-4.69633
2591.51.328660.171336
260610.7785-4.77852
2610.50.3461330.153867
2626.55.88890.611105
2637.58.27093-0.770932
2644.52.835221.66478
26585.485032.51497
26698.449730.55027
2677.55.275512.22449
2688.56.648491.85151
26974.559162.44084
2709.59.69028-0.190281
2716.52.4314.069
2729.510.3196-0.819634
27363.001022.99898
27485.074922.92508
2759.57.808571.69143
27686.768081.23192
27785.333092.66691
278910.2896-1.28957
2795NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.3502610.7005230.649739
100.5991570.8016860.400843
110.4603730.9207460.539627
120.7131190.5737610.286881
130.6200890.7598210.379911
140.5185610.9628790.481439
150.4544860.9089720.545514
160.3624910.7249820.637509
170.2798340.5596680.720166
180.2541660.5083320.745834
190.2099980.4199960.790002
200.1586190.3172380.841381
210.3121350.624270.687865
220.3171260.6342510.682874
230.2715210.5430420.728479
240.2621410.5242820.737859
250.2106990.4213980.789301
260.1988050.397610.801195
270.221590.4431790.77841
280.1842030.3684050.815797
290.2165550.433110.783445
300.1732990.3465980.826701
310.1444670.2889330.855533
320.1203870.2407740.879613
330.1174690.2349380.882531
340.1550080.3100160.844992
350.1281220.2562430.871878
360.1135090.2270180.886491
370.1051430.2102860.894857
380.09173910.1834780.908261
390.1059960.2119920.894004
400.08402620.1680520.915974
410.1921860.3843710.807814
420.1604770.3209540.839523
430.1464240.2928490.853576
440.1225990.2451970.877401
450.1096120.2192230.890388
460.09174990.18350.90825
470.07573740.1514750.924263
480.1185120.2370240.881488
490.1462540.2925080.853746
500.1299240.2598480.870076
510.1088780.2177560.891122
520.1373160.2746320.862684
530.1159490.2318990.884051
540.1085650.2171310.891435
550.1172150.2344290.882785
560.1014990.2029970.898501
570.2047960.4095930.795204
580.2838470.5676940.716153
590.2544210.5088410.745579
600.2503440.5006890.749656
610.2440020.4880040.755998
620.2186130.4372270.781387
630.2566940.5133880.743306
640.3182670.6365340.681733
650.2991310.5982630.700869
660.295450.5908990.70455
670.2753020.5506040.724698
680.2540870.5081740.745913
690.2975190.5950390.702481
700.2804850.560970.719515
710.2484380.4968760.751562
720.2215730.4431460.778427
730.2101370.4202740.789863
740.2133490.4266980.786651
750.199510.3990190.80049
760.1783280.3566550.821672
770.1599210.3198430.840079
780.1513030.3026060.848697
790.1341320.2682640.865868
800.158650.3173010.84135
810.143880.287760.85612
820.1533790.3067590.846621
830.1386250.2772510.861375
840.2503160.5006320.749684
850.2370870.4741730.762913
860.2107510.4215030.789249
870.1882140.3764280.811786
880.1785940.3571870.821406
890.2025750.4051490.797425
900.2240780.4481550.775922
910.2270960.4541930.772904
920.3546640.7093280.645336
930.3243270.6486550.675673
940.3288360.6576710.671164
950.3875560.7751120.612444
960.3774910.7549810.622509
970.4137420.8274830.586258
980.393350.7866990.60665
990.4091360.8182710.590864
1000.5351610.9296770.464839
1010.5147110.9705790.485289
1020.5118360.9763270.488164
1030.5120810.9758380.487919
1040.5142280.9715440.485772
1050.5381670.9236660.461833
1060.5534010.8931980.446599
1070.5827540.8344920.417246
1080.7776630.4446730.222337
1090.8837390.2325230.116261
1100.8786050.2427910.121395
1110.8692670.2614650.130733
1120.8628740.2742530.137126
1130.9264950.147010.0735051
1140.9321320.1357350.0678676
1150.9510530.09789380.0489469
1160.9606130.07877340.0393867
1170.9651520.06969540.0348477
1180.96460.0708010.0354005
1190.964150.07169910.0358496
1200.9750550.04989070.0249453
1210.9719170.05616510.0280826
1220.9777060.04458840.0222942
1230.9825550.034890.017445
1240.9860310.02793710.0139686
1250.9875040.02499230.0124961
1260.9852980.02940460.0147023
1270.9857420.02851530.0142576
1280.9828470.03430570.0171528
1290.9872190.0255610.0127805
1300.9855280.02894440.0144722
1310.9835650.03287010.016435
1320.9821780.03564450.0178222
1330.9817660.03646840.0182342
1340.9807820.03843630.0192181
1350.977040.04591930.0229597
1360.9747190.05056230.0252811
1370.9802280.03954370.0197718
1380.9895620.02087580.0104379
1390.9902250.01954930.00977467
1400.9891230.02175410.010877
1410.9876890.02462180.0123109
1420.9871890.02562240.0128112
1430.9855230.02895410.014477
1440.9856130.02877430.0143871
1450.9855620.02887610.0144381
1460.986440.027120.01356
1470.9837920.03241610.0162081
1480.9813870.03722510.0186125
1490.9782530.04349360.0217468
1500.9765440.04691240.0234562
1510.984320.03135940.0156797
1520.9828750.03425070.0171253
1530.9831390.03372240.0168612
1540.9851090.02978280.0148914
1550.9843330.03133450.0156673
1560.9827670.03446660.0172333
1570.9837860.03242840.0162142
1580.9842370.03152570.0157629
1590.9816630.03667480.0183374
1600.979240.04151960.0207598
1610.9836170.0327660.016383
1620.9821950.03561070.0178053
1630.979580.04084020.0204201
1640.9819260.03614770.0180738
1650.9846630.03067450.0153372
1660.9808520.03829680.0191484
1670.9826610.03467770.0173389
1680.9790190.04196210.020981
1690.9746710.05065750.0253287
1700.974590.0508210.0254105
1710.9704450.05911040.0295552
1720.9791220.04175530.0208777
1730.9743580.05128490.0256424
1740.9686550.06268980.0313449
1750.9619280.07614310.0380716
1760.9673070.06538690.0326935
1770.9603090.07938130.0396906
1780.9787110.0425790.0212895
1790.9744760.05104750.0255237
1800.9823980.03520350.0176017
1810.9784050.04318920.0215946
1820.9749840.05003230.0250162
1830.9754130.04917440.0245872
1840.9710440.05791240.0289562
1850.9732410.05351720.0267586
1860.9679780.06404470.0320223
1870.9708170.05836510.0291826
1880.9688840.06223290.0311165
1890.966350.06730030.0336502
1900.9609090.0781830.0390915
1910.9529010.09419830.0470992
1920.9506360.09872860.0493643
1930.9644480.07110450.0355523
1940.9708560.05828890.0291445
1950.9674990.06500180.0325009
1960.9607190.07856260.0392813
1970.9521810.09563820.0478191
1980.9459250.1081510.0540753
1990.9476750.104650.0523248
2000.9416390.1167210.0583607
2010.9510150.09797080.0489854
2020.9470370.1059260.0529629
2030.9353570.1292870.0646433
2040.9238930.1522140.0761069
2050.9266470.1467060.0733528
2060.9157070.1685860.0842929
2070.9034850.193030.096515
2080.8913890.2172220.108611
2090.9072250.185550.0927749
2100.8988980.2022040.101102
2110.8802050.239590.119795
2120.8632460.2735090.136754
2130.8416730.3166540.158327
2140.8258930.3482140.174107
2150.8059390.3881210.194061
2160.7754660.4490680.224534
2170.7659780.4680450.234022
2180.7624750.475050.237525
2190.7281370.5437260.271863
2200.6937270.6125460.306273
2210.7097510.5804990.290249
2220.7278820.5442370.272118
2230.6891550.6216890.310845
2240.6494620.7010750.350538
2250.6289330.7421340.371067
2260.6070050.7859890.392995
2270.571340.8573210.42866
2280.5598840.8802320.440116
2290.6024820.7950350.397518
2300.602080.7958410.39792
2310.6444880.7110240.355512
2320.7230380.5539240.276962
2330.6840950.6318090.315905
2340.6714260.6571480.328574
2350.6309030.7381940.369097
2360.915320.169360.0846799
2370.8934830.2130340.106517
2380.8707880.2584240.129212
2390.8422220.3155550.157778
2400.8068450.3863090.193155
2410.7772050.445590.222795
2420.7462480.5075040.253752
2430.7017960.5964080.298204
2440.7255290.5489430.274471
2450.6761980.6476040.323802
2460.655810.6883810.34419
2470.6294580.7410840.370542
2480.5711570.8576850.428843
2490.5675220.8649570.432478
2500.5358280.9283430.464172
2510.4789930.9579860.521007
2520.5094940.9810120.490506
2530.4560070.9120140.543993
2540.4186510.8373020.581349
2550.3607410.7214820.639259
2560.3124890.6249790.687511
2570.6086010.7827990.391399
2580.7427830.5144350.257217
2590.6855870.6288250.314413
2600.9882720.02345650.0117282
2610.98090.03819970.0190999
2620.9810910.03781860.0189093
2630.9656580.06868460.0343423
2640.9483440.1033120.0516561
2650.9067160.1865690.0932844
2660.8384060.3231870.161594
2670.7385480.5229030.261452
2680.6376980.7246030.362302
2690.9668490.06630210.0331511
2700.9334820.1330370.0665183

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.350261 & 0.700523 & 0.649739 \tabularnewline
10 & 0.599157 & 0.801686 & 0.400843 \tabularnewline
11 & 0.460373 & 0.920746 & 0.539627 \tabularnewline
12 & 0.713119 & 0.573761 & 0.286881 \tabularnewline
13 & 0.620089 & 0.759821 & 0.379911 \tabularnewline
14 & 0.518561 & 0.962879 & 0.481439 \tabularnewline
15 & 0.454486 & 0.908972 & 0.545514 \tabularnewline
16 & 0.362491 & 0.724982 & 0.637509 \tabularnewline
17 & 0.279834 & 0.559668 & 0.720166 \tabularnewline
18 & 0.254166 & 0.508332 & 0.745834 \tabularnewline
19 & 0.209998 & 0.419996 & 0.790002 \tabularnewline
20 & 0.158619 & 0.317238 & 0.841381 \tabularnewline
21 & 0.312135 & 0.62427 & 0.687865 \tabularnewline
22 & 0.317126 & 0.634251 & 0.682874 \tabularnewline
23 & 0.271521 & 0.543042 & 0.728479 \tabularnewline
24 & 0.262141 & 0.524282 & 0.737859 \tabularnewline
25 & 0.210699 & 0.421398 & 0.789301 \tabularnewline
26 & 0.198805 & 0.39761 & 0.801195 \tabularnewline
27 & 0.22159 & 0.443179 & 0.77841 \tabularnewline
28 & 0.184203 & 0.368405 & 0.815797 \tabularnewline
29 & 0.216555 & 0.43311 & 0.783445 \tabularnewline
30 & 0.173299 & 0.346598 & 0.826701 \tabularnewline
31 & 0.144467 & 0.288933 & 0.855533 \tabularnewline
32 & 0.120387 & 0.240774 & 0.879613 \tabularnewline
33 & 0.117469 & 0.234938 & 0.882531 \tabularnewline
34 & 0.155008 & 0.310016 & 0.844992 \tabularnewline
35 & 0.128122 & 0.256243 & 0.871878 \tabularnewline
36 & 0.113509 & 0.227018 & 0.886491 \tabularnewline
37 & 0.105143 & 0.210286 & 0.894857 \tabularnewline
38 & 0.0917391 & 0.183478 & 0.908261 \tabularnewline
39 & 0.105996 & 0.211992 & 0.894004 \tabularnewline
40 & 0.0840262 & 0.168052 & 0.915974 \tabularnewline
41 & 0.192186 & 0.384371 & 0.807814 \tabularnewline
42 & 0.160477 & 0.320954 & 0.839523 \tabularnewline
43 & 0.146424 & 0.292849 & 0.853576 \tabularnewline
44 & 0.122599 & 0.245197 & 0.877401 \tabularnewline
45 & 0.109612 & 0.219223 & 0.890388 \tabularnewline
46 & 0.0917499 & 0.1835 & 0.90825 \tabularnewline
47 & 0.0757374 & 0.151475 & 0.924263 \tabularnewline
48 & 0.118512 & 0.237024 & 0.881488 \tabularnewline
49 & 0.146254 & 0.292508 & 0.853746 \tabularnewline
50 & 0.129924 & 0.259848 & 0.870076 \tabularnewline
51 & 0.108878 & 0.217756 & 0.891122 \tabularnewline
52 & 0.137316 & 0.274632 & 0.862684 \tabularnewline
53 & 0.115949 & 0.231899 & 0.884051 \tabularnewline
54 & 0.108565 & 0.217131 & 0.891435 \tabularnewline
55 & 0.117215 & 0.234429 & 0.882785 \tabularnewline
56 & 0.101499 & 0.202997 & 0.898501 \tabularnewline
57 & 0.204796 & 0.409593 & 0.795204 \tabularnewline
58 & 0.283847 & 0.567694 & 0.716153 \tabularnewline
59 & 0.254421 & 0.508841 & 0.745579 \tabularnewline
60 & 0.250344 & 0.500689 & 0.749656 \tabularnewline
61 & 0.244002 & 0.488004 & 0.755998 \tabularnewline
62 & 0.218613 & 0.437227 & 0.781387 \tabularnewline
63 & 0.256694 & 0.513388 & 0.743306 \tabularnewline
64 & 0.318267 & 0.636534 & 0.681733 \tabularnewline
65 & 0.299131 & 0.598263 & 0.700869 \tabularnewline
66 & 0.29545 & 0.590899 & 0.70455 \tabularnewline
67 & 0.275302 & 0.550604 & 0.724698 \tabularnewline
68 & 0.254087 & 0.508174 & 0.745913 \tabularnewline
69 & 0.297519 & 0.595039 & 0.702481 \tabularnewline
70 & 0.280485 & 0.56097 & 0.719515 \tabularnewline
71 & 0.248438 & 0.496876 & 0.751562 \tabularnewline
72 & 0.221573 & 0.443146 & 0.778427 \tabularnewline
73 & 0.210137 & 0.420274 & 0.789863 \tabularnewline
74 & 0.213349 & 0.426698 & 0.786651 \tabularnewline
75 & 0.19951 & 0.399019 & 0.80049 \tabularnewline
76 & 0.178328 & 0.356655 & 0.821672 \tabularnewline
77 & 0.159921 & 0.319843 & 0.840079 \tabularnewline
78 & 0.151303 & 0.302606 & 0.848697 \tabularnewline
79 & 0.134132 & 0.268264 & 0.865868 \tabularnewline
80 & 0.15865 & 0.317301 & 0.84135 \tabularnewline
81 & 0.14388 & 0.28776 & 0.85612 \tabularnewline
82 & 0.153379 & 0.306759 & 0.846621 \tabularnewline
83 & 0.138625 & 0.277251 & 0.861375 \tabularnewline
84 & 0.250316 & 0.500632 & 0.749684 \tabularnewline
85 & 0.237087 & 0.474173 & 0.762913 \tabularnewline
86 & 0.210751 & 0.421503 & 0.789249 \tabularnewline
87 & 0.188214 & 0.376428 & 0.811786 \tabularnewline
88 & 0.178594 & 0.357187 & 0.821406 \tabularnewline
89 & 0.202575 & 0.405149 & 0.797425 \tabularnewline
90 & 0.224078 & 0.448155 & 0.775922 \tabularnewline
91 & 0.227096 & 0.454193 & 0.772904 \tabularnewline
92 & 0.354664 & 0.709328 & 0.645336 \tabularnewline
93 & 0.324327 & 0.648655 & 0.675673 \tabularnewline
94 & 0.328836 & 0.657671 & 0.671164 \tabularnewline
95 & 0.387556 & 0.775112 & 0.612444 \tabularnewline
96 & 0.377491 & 0.754981 & 0.622509 \tabularnewline
97 & 0.413742 & 0.827483 & 0.586258 \tabularnewline
98 & 0.39335 & 0.786699 & 0.60665 \tabularnewline
99 & 0.409136 & 0.818271 & 0.590864 \tabularnewline
100 & 0.535161 & 0.929677 & 0.464839 \tabularnewline
101 & 0.514711 & 0.970579 & 0.485289 \tabularnewline
102 & 0.511836 & 0.976327 & 0.488164 \tabularnewline
103 & 0.512081 & 0.975838 & 0.487919 \tabularnewline
104 & 0.514228 & 0.971544 & 0.485772 \tabularnewline
105 & 0.538167 & 0.923666 & 0.461833 \tabularnewline
106 & 0.553401 & 0.893198 & 0.446599 \tabularnewline
107 & 0.582754 & 0.834492 & 0.417246 \tabularnewline
108 & 0.777663 & 0.444673 & 0.222337 \tabularnewline
109 & 0.883739 & 0.232523 & 0.116261 \tabularnewline
110 & 0.878605 & 0.242791 & 0.121395 \tabularnewline
111 & 0.869267 & 0.261465 & 0.130733 \tabularnewline
112 & 0.862874 & 0.274253 & 0.137126 \tabularnewline
113 & 0.926495 & 0.14701 & 0.0735051 \tabularnewline
114 & 0.932132 & 0.135735 & 0.0678676 \tabularnewline
115 & 0.951053 & 0.0978938 & 0.0489469 \tabularnewline
116 & 0.960613 & 0.0787734 & 0.0393867 \tabularnewline
117 & 0.965152 & 0.0696954 & 0.0348477 \tabularnewline
118 & 0.9646 & 0.070801 & 0.0354005 \tabularnewline
119 & 0.96415 & 0.0716991 & 0.0358496 \tabularnewline
120 & 0.975055 & 0.0498907 & 0.0249453 \tabularnewline
121 & 0.971917 & 0.0561651 & 0.0280826 \tabularnewline
122 & 0.977706 & 0.0445884 & 0.0222942 \tabularnewline
123 & 0.982555 & 0.03489 & 0.017445 \tabularnewline
124 & 0.986031 & 0.0279371 & 0.0139686 \tabularnewline
125 & 0.987504 & 0.0249923 & 0.0124961 \tabularnewline
126 & 0.985298 & 0.0294046 & 0.0147023 \tabularnewline
127 & 0.985742 & 0.0285153 & 0.0142576 \tabularnewline
128 & 0.982847 & 0.0343057 & 0.0171528 \tabularnewline
129 & 0.987219 & 0.025561 & 0.0127805 \tabularnewline
130 & 0.985528 & 0.0289444 & 0.0144722 \tabularnewline
131 & 0.983565 & 0.0328701 & 0.016435 \tabularnewline
132 & 0.982178 & 0.0356445 & 0.0178222 \tabularnewline
133 & 0.981766 & 0.0364684 & 0.0182342 \tabularnewline
134 & 0.980782 & 0.0384363 & 0.0192181 \tabularnewline
135 & 0.97704 & 0.0459193 & 0.0229597 \tabularnewline
136 & 0.974719 & 0.0505623 & 0.0252811 \tabularnewline
137 & 0.980228 & 0.0395437 & 0.0197718 \tabularnewline
138 & 0.989562 & 0.0208758 & 0.0104379 \tabularnewline
139 & 0.990225 & 0.0195493 & 0.00977467 \tabularnewline
140 & 0.989123 & 0.0217541 & 0.010877 \tabularnewline
141 & 0.987689 & 0.0246218 & 0.0123109 \tabularnewline
142 & 0.987189 & 0.0256224 & 0.0128112 \tabularnewline
143 & 0.985523 & 0.0289541 & 0.014477 \tabularnewline
144 & 0.985613 & 0.0287743 & 0.0143871 \tabularnewline
145 & 0.985562 & 0.0288761 & 0.0144381 \tabularnewline
146 & 0.98644 & 0.02712 & 0.01356 \tabularnewline
147 & 0.983792 & 0.0324161 & 0.0162081 \tabularnewline
148 & 0.981387 & 0.0372251 & 0.0186125 \tabularnewline
149 & 0.978253 & 0.0434936 & 0.0217468 \tabularnewline
150 & 0.976544 & 0.0469124 & 0.0234562 \tabularnewline
151 & 0.98432 & 0.0313594 & 0.0156797 \tabularnewline
152 & 0.982875 & 0.0342507 & 0.0171253 \tabularnewline
153 & 0.983139 & 0.0337224 & 0.0168612 \tabularnewline
154 & 0.985109 & 0.0297828 & 0.0148914 \tabularnewline
155 & 0.984333 & 0.0313345 & 0.0156673 \tabularnewline
156 & 0.982767 & 0.0344666 & 0.0172333 \tabularnewline
157 & 0.983786 & 0.0324284 & 0.0162142 \tabularnewline
158 & 0.984237 & 0.0315257 & 0.0157629 \tabularnewline
159 & 0.981663 & 0.0366748 & 0.0183374 \tabularnewline
160 & 0.97924 & 0.0415196 & 0.0207598 \tabularnewline
161 & 0.983617 & 0.032766 & 0.016383 \tabularnewline
162 & 0.982195 & 0.0356107 & 0.0178053 \tabularnewline
163 & 0.97958 & 0.0408402 & 0.0204201 \tabularnewline
164 & 0.981926 & 0.0361477 & 0.0180738 \tabularnewline
165 & 0.984663 & 0.0306745 & 0.0153372 \tabularnewline
166 & 0.980852 & 0.0382968 & 0.0191484 \tabularnewline
167 & 0.982661 & 0.0346777 & 0.0173389 \tabularnewline
168 & 0.979019 & 0.0419621 & 0.020981 \tabularnewline
169 & 0.974671 & 0.0506575 & 0.0253287 \tabularnewline
170 & 0.97459 & 0.050821 & 0.0254105 \tabularnewline
171 & 0.970445 & 0.0591104 & 0.0295552 \tabularnewline
172 & 0.979122 & 0.0417553 & 0.0208777 \tabularnewline
173 & 0.974358 & 0.0512849 & 0.0256424 \tabularnewline
174 & 0.968655 & 0.0626898 & 0.0313449 \tabularnewline
175 & 0.961928 & 0.0761431 & 0.0380716 \tabularnewline
176 & 0.967307 & 0.0653869 & 0.0326935 \tabularnewline
177 & 0.960309 & 0.0793813 & 0.0396906 \tabularnewline
178 & 0.978711 & 0.042579 & 0.0212895 \tabularnewline
179 & 0.974476 & 0.0510475 & 0.0255237 \tabularnewline
180 & 0.982398 & 0.0352035 & 0.0176017 \tabularnewline
181 & 0.978405 & 0.0431892 & 0.0215946 \tabularnewline
182 & 0.974984 & 0.0500323 & 0.0250162 \tabularnewline
183 & 0.975413 & 0.0491744 & 0.0245872 \tabularnewline
184 & 0.971044 & 0.0579124 & 0.0289562 \tabularnewline
185 & 0.973241 & 0.0535172 & 0.0267586 \tabularnewline
186 & 0.967978 & 0.0640447 & 0.0320223 \tabularnewline
187 & 0.970817 & 0.0583651 & 0.0291826 \tabularnewline
188 & 0.968884 & 0.0622329 & 0.0311165 \tabularnewline
189 & 0.96635 & 0.0673003 & 0.0336502 \tabularnewline
190 & 0.960909 & 0.078183 & 0.0390915 \tabularnewline
191 & 0.952901 & 0.0941983 & 0.0470992 \tabularnewline
192 & 0.950636 & 0.0987286 & 0.0493643 \tabularnewline
193 & 0.964448 & 0.0711045 & 0.0355523 \tabularnewline
194 & 0.970856 & 0.0582889 & 0.0291445 \tabularnewline
195 & 0.967499 & 0.0650018 & 0.0325009 \tabularnewline
196 & 0.960719 & 0.0785626 & 0.0392813 \tabularnewline
197 & 0.952181 & 0.0956382 & 0.0478191 \tabularnewline
198 & 0.945925 & 0.108151 & 0.0540753 \tabularnewline
199 & 0.947675 & 0.10465 & 0.0523248 \tabularnewline
200 & 0.941639 & 0.116721 & 0.0583607 \tabularnewline
201 & 0.951015 & 0.0979708 & 0.0489854 \tabularnewline
202 & 0.947037 & 0.105926 & 0.0529629 \tabularnewline
203 & 0.935357 & 0.129287 & 0.0646433 \tabularnewline
204 & 0.923893 & 0.152214 & 0.0761069 \tabularnewline
205 & 0.926647 & 0.146706 & 0.0733528 \tabularnewline
206 & 0.915707 & 0.168586 & 0.0842929 \tabularnewline
207 & 0.903485 & 0.19303 & 0.096515 \tabularnewline
208 & 0.891389 & 0.217222 & 0.108611 \tabularnewline
209 & 0.907225 & 0.18555 & 0.0927749 \tabularnewline
210 & 0.898898 & 0.202204 & 0.101102 \tabularnewline
211 & 0.880205 & 0.23959 & 0.119795 \tabularnewline
212 & 0.863246 & 0.273509 & 0.136754 \tabularnewline
213 & 0.841673 & 0.316654 & 0.158327 \tabularnewline
214 & 0.825893 & 0.348214 & 0.174107 \tabularnewline
215 & 0.805939 & 0.388121 & 0.194061 \tabularnewline
216 & 0.775466 & 0.449068 & 0.224534 \tabularnewline
217 & 0.765978 & 0.468045 & 0.234022 \tabularnewline
218 & 0.762475 & 0.47505 & 0.237525 \tabularnewline
219 & 0.728137 & 0.543726 & 0.271863 \tabularnewline
220 & 0.693727 & 0.612546 & 0.306273 \tabularnewline
221 & 0.709751 & 0.580499 & 0.290249 \tabularnewline
222 & 0.727882 & 0.544237 & 0.272118 \tabularnewline
223 & 0.689155 & 0.621689 & 0.310845 \tabularnewline
224 & 0.649462 & 0.701075 & 0.350538 \tabularnewline
225 & 0.628933 & 0.742134 & 0.371067 \tabularnewline
226 & 0.607005 & 0.785989 & 0.392995 \tabularnewline
227 & 0.57134 & 0.857321 & 0.42866 \tabularnewline
228 & 0.559884 & 0.880232 & 0.440116 \tabularnewline
229 & 0.602482 & 0.795035 & 0.397518 \tabularnewline
230 & 0.60208 & 0.795841 & 0.39792 \tabularnewline
231 & 0.644488 & 0.711024 & 0.355512 \tabularnewline
232 & 0.723038 & 0.553924 & 0.276962 \tabularnewline
233 & 0.684095 & 0.631809 & 0.315905 \tabularnewline
234 & 0.671426 & 0.657148 & 0.328574 \tabularnewline
235 & 0.630903 & 0.738194 & 0.369097 \tabularnewline
236 & 0.91532 & 0.16936 & 0.0846799 \tabularnewline
237 & 0.893483 & 0.213034 & 0.106517 \tabularnewline
238 & 0.870788 & 0.258424 & 0.129212 \tabularnewline
239 & 0.842222 & 0.315555 & 0.157778 \tabularnewline
240 & 0.806845 & 0.386309 & 0.193155 \tabularnewline
241 & 0.777205 & 0.44559 & 0.222795 \tabularnewline
242 & 0.746248 & 0.507504 & 0.253752 \tabularnewline
243 & 0.701796 & 0.596408 & 0.298204 \tabularnewline
244 & 0.725529 & 0.548943 & 0.274471 \tabularnewline
245 & 0.676198 & 0.647604 & 0.323802 \tabularnewline
246 & 0.65581 & 0.688381 & 0.34419 \tabularnewline
247 & 0.629458 & 0.741084 & 0.370542 \tabularnewline
248 & 0.571157 & 0.857685 & 0.428843 \tabularnewline
249 & 0.567522 & 0.864957 & 0.432478 \tabularnewline
250 & 0.535828 & 0.928343 & 0.464172 \tabularnewline
251 & 0.478993 & 0.957986 & 0.521007 \tabularnewline
252 & 0.509494 & 0.981012 & 0.490506 \tabularnewline
253 & 0.456007 & 0.912014 & 0.543993 \tabularnewline
254 & 0.418651 & 0.837302 & 0.581349 \tabularnewline
255 & 0.360741 & 0.721482 & 0.639259 \tabularnewline
256 & 0.312489 & 0.624979 & 0.687511 \tabularnewline
257 & 0.608601 & 0.782799 & 0.391399 \tabularnewline
258 & 0.742783 & 0.514435 & 0.257217 \tabularnewline
259 & 0.685587 & 0.628825 & 0.314413 \tabularnewline
260 & 0.988272 & 0.0234565 & 0.0117282 \tabularnewline
261 & 0.9809 & 0.0381997 & 0.0190999 \tabularnewline
262 & 0.981091 & 0.0378186 & 0.0189093 \tabularnewline
263 & 0.965658 & 0.0686846 & 0.0343423 \tabularnewline
264 & 0.948344 & 0.103312 & 0.0516561 \tabularnewline
265 & 0.906716 & 0.186569 & 0.0932844 \tabularnewline
266 & 0.838406 & 0.323187 & 0.161594 \tabularnewline
267 & 0.738548 & 0.522903 & 0.261452 \tabularnewline
268 & 0.637698 & 0.724603 & 0.362302 \tabularnewline
269 & 0.966849 & 0.0663021 & 0.0331511 \tabularnewline
270 & 0.933482 & 0.133037 & 0.0665183 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265643&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]9[/C][C]0.350261[/C][C]0.700523[/C][C]0.649739[/C][/ROW]
[ROW][C]10[/C][C]0.599157[/C][C]0.801686[/C][C]0.400843[/C][/ROW]
[ROW][C]11[/C][C]0.460373[/C][C]0.920746[/C][C]0.539627[/C][/ROW]
[ROW][C]12[/C][C]0.713119[/C][C]0.573761[/C][C]0.286881[/C][/ROW]
[ROW][C]13[/C][C]0.620089[/C][C]0.759821[/C][C]0.379911[/C][/ROW]
[ROW][C]14[/C][C]0.518561[/C][C]0.962879[/C][C]0.481439[/C][/ROW]
[ROW][C]15[/C][C]0.454486[/C][C]0.908972[/C][C]0.545514[/C][/ROW]
[ROW][C]16[/C][C]0.362491[/C][C]0.724982[/C][C]0.637509[/C][/ROW]
[ROW][C]17[/C][C]0.279834[/C][C]0.559668[/C][C]0.720166[/C][/ROW]
[ROW][C]18[/C][C]0.254166[/C][C]0.508332[/C][C]0.745834[/C][/ROW]
[ROW][C]19[/C][C]0.209998[/C][C]0.419996[/C][C]0.790002[/C][/ROW]
[ROW][C]20[/C][C]0.158619[/C][C]0.317238[/C][C]0.841381[/C][/ROW]
[ROW][C]21[/C][C]0.312135[/C][C]0.62427[/C][C]0.687865[/C][/ROW]
[ROW][C]22[/C][C]0.317126[/C][C]0.634251[/C][C]0.682874[/C][/ROW]
[ROW][C]23[/C][C]0.271521[/C][C]0.543042[/C][C]0.728479[/C][/ROW]
[ROW][C]24[/C][C]0.262141[/C][C]0.524282[/C][C]0.737859[/C][/ROW]
[ROW][C]25[/C][C]0.210699[/C][C]0.421398[/C][C]0.789301[/C][/ROW]
[ROW][C]26[/C][C]0.198805[/C][C]0.39761[/C][C]0.801195[/C][/ROW]
[ROW][C]27[/C][C]0.22159[/C][C]0.443179[/C][C]0.77841[/C][/ROW]
[ROW][C]28[/C][C]0.184203[/C][C]0.368405[/C][C]0.815797[/C][/ROW]
[ROW][C]29[/C][C]0.216555[/C][C]0.43311[/C][C]0.783445[/C][/ROW]
[ROW][C]30[/C][C]0.173299[/C][C]0.346598[/C][C]0.826701[/C][/ROW]
[ROW][C]31[/C][C]0.144467[/C][C]0.288933[/C][C]0.855533[/C][/ROW]
[ROW][C]32[/C][C]0.120387[/C][C]0.240774[/C][C]0.879613[/C][/ROW]
[ROW][C]33[/C][C]0.117469[/C][C]0.234938[/C][C]0.882531[/C][/ROW]
[ROW][C]34[/C][C]0.155008[/C][C]0.310016[/C][C]0.844992[/C][/ROW]
[ROW][C]35[/C][C]0.128122[/C][C]0.256243[/C][C]0.871878[/C][/ROW]
[ROW][C]36[/C][C]0.113509[/C][C]0.227018[/C][C]0.886491[/C][/ROW]
[ROW][C]37[/C][C]0.105143[/C][C]0.210286[/C][C]0.894857[/C][/ROW]
[ROW][C]38[/C][C]0.0917391[/C][C]0.183478[/C][C]0.908261[/C][/ROW]
[ROW][C]39[/C][C]0.105996[/C][C]0.211992[/C][C]0.894004[/C][/ROW]
[ROW][C]40[/C][C]0.0840262[/C][C]0.168052[/C][C]0.915974[/C][/ROW]
[ROW][C]41[/C][C]0.192186[/C][C]0.384371[/C][C]0.807814[/C][/ROW]
[ROW][C]42[/C][C]0.160477[/C][C]0.320954[/C][C]0.839523[/C][/ROW]
[ROW][C]43[/C][C]0.146424[/C][C]0.292849[/C][C]0.853576[/C][/ROW]
[ROW][C]44[/C][C]0.122599[/C][C]0.245197[/C][C]0.877401[/C][/ROW]
[ROW][C]45[/C][C]0.109612[/C][C]0.219223[/C][C]0.890388[/C][/ROW]
[ROW][C]46[/C][C]0.0917499[/C][C]0.1835[/C][C]0.90825[/C][/ROW]
[ROW][C]47[/C][C]0.0757374[/C][C]0.151475[/C][C]0.924263[/C][/ROW]
[ROW][C]48[/C][C]0.118512[/C][C]0.237024[/C][C]0.881488[/C][/ROW]
[ROW][C]49[/C][C]0.146254[/C][C]0.292508[/C][C]0.853746[/C][/ROW]
[ROW][C]50[/C][C]0.129924[/C][C]0.259848[/C][C]0.870076[/C][/ROW]
[ROW][C]51[/C][C]0.108878[/C][C]0.217756[/C][C]0.891122[/C][/ROW]
[ROW][C]52[/C][C]0.137316[/C][C]0.274632[/C][C]0.862684[/C][/ROW]
[ROW][C]53[/C][C]0.115949[/C][C]0.231899[/C][C]0.884051[/C][/ROW]
[ROW][C]54[/C][C]0.108565[/C][C]0.217131[/C][C]0.891435[/C][/ROW]
[ROW][C]55[/C][C]0.117215[/C][C]0.234429[/C][C]0.882785[/C][/ROW]
[ROW][C]56[/C][C]0.101499[/C][C]0.202997[/C][C]0.898501[/C][/ROW]
[ROW][C]57[/C][C]0.204796[/C][C]0.409593[/C][C]0.795204[/C][/ROW]
[ROW][C]58[/C][C]0.283847[/C][C]0.567694[/C][C]0.716153[/C][/ROW]
[ROW][C]59[/C][C]0.254421[/C][C]0.508841[/C][C]0.745579[/C][/ROW]
[ROW][C]60[/C][C]0.250344[/C][C]0.500689[/C][C]0.749656[/C][/ROW]
[ROW][C]61[/C][C]0.244002[/C][C]0.488004[/C][C]0.755998[/C][/ROW]
[ROW][C]62[/C][C]0.218613[/C][C]0.437227[/C][C]0.781387[/C][/ROW]
[ROW][C]63[/C][C]0.256694[/C][C]0.513388[/C][C]0.743306[/C][/ROW]
[ROW][C]64[/C][C]0.318267[/C][C]0.636534[/C][C]0.681733[/C][/ROW]
[ROW][C]65[/C][C]0.299131[/C][C]0.598263[/C][C]0.700869[/C][/ROW]
[ROW][C]66[/C][C]0.29545[/C][C]0.590899[/C][C]0.70455[/C][/ROW]
[ROW][C]67[/C][C]0.275302[/C][C]0.550604[/C][C]0.724698[/C][/ROW]
[ROW][C]68[/C][C]0.254087[/C][C]0.508174[/C][C]0.745913[/C][/ROW]
[ROW][C]69[/C][C]0.297519[/C][C]0.595039[/C][C]0.702481[/C][/ROW]
[ROW][C]70[/C][C]0.280485[/C][C]0.56097[/C][C]0.719515[/C][/ROW]
[ROW][C]71[/C][C]0.248438[/C][C]0.496876[/C][C]0.751562[/C][/ROW]
[ROW][C]72[/C][C]0.221573[/C][C]0.443146[/C][C]0.778427[/C][/ROW]
[ROW][C]73[/C][C]0.210137[/C][C]0.420274[/C][C]0.789863[/C][/ROW]
[ROW][C]74[/C][C]0.213349[/C][C]0.426698[/C][C]0.786651[/C][/ROW]
[ROW][C]75[/C][C]0.19951[/C][C]0.399019[/C][C]0.80049[/C][/ROW]
[ROW][C]76[/C][C]0.178328[/C][C]0.356655[/C][C]0.821672[/C][/ROW]
[ROW][C]77[/C][C]0.159921[/C][C]0.319843[/C][C]0.840079[/C][/ROW]
[ROW][C]78[/C][C]0.151303[/C][C]0.302606[/C][C]0.848697[/C][/ROW]
[ROW][C]79[/C][C]0.134132[/C][C]0.268264[/C][C]0.865868[/C][/ROW]
[ROW][C]80[/C][C]0.15865[/C][C]0.317301[/C][C]0.84135[/C][/ROW]
[ROW][C]81[/C][C]0.14388[/C][C]0.28776[/C][C]0.85612[/C][/ROW]
[ROW][C]82[/C][C]0.153379[/C][C]0.306759[/C][C]0.846621[/C][/ROW]
[ROW][C]83[/C][C]0.138625[/C][C]0.277251[/C][C]0.861375[/C][/ROW]
[ROW][C]84[/C][C]0.250316[/C][C]0.500632[/C][C]0.749684[/C][/ROW]
[ROW][C]85[/C][C]0.237087[/C][C]0.474173[/C][C]0.762913[/C][/ROW]
[ROW][C]86[/C][C]0.210751[/C][C]0.421503[/C][C]0.789249[/C][/ROW]
[ROW][C]87[/C][C]0.188214[/C][C]0.376428[/C][C]0.811786[/C][/ROW]
[ROW][C]88[/C][C]0.178594[/C][C]0.357187[/C][C]0.821406[/C][/ROW]
[ROW][C]89[/C][C]0.202575[/C][C]0.405149[/C][C]0.797425[/C][/ROW]
[ROW][C]90[/C][C]0.224078[/C][C]0.448155[/C][C]0.775922[/C][/ROW]
[ROW][C]91[/C][C]0.227096[/C][C]0.454193[/C][C]0.772904[/C][/ROW]
[ROW][C]92[/C][C]0.354664[/C][C]0.709328[/C][C]0.645336[/C][/ROW]
[ROW][C]93[/C][C]0.324327[/C][C]0.648655[/C][C]0.675673[/C][/ROW]
[ROW][C]94[/C][C]0.328836[/C][C]0.657671[/C][C]0.671164[/C][/ROW]
[ROW][C]95[/C][C]0.387556[/C][C]0.775112[/C][C]0.612444[/C][/ROW]
[ROW][C]96[/C][C]0.377491[/C][C]0.754981[/C][C]0.622509[/C][/ROW]
[ROW][C]97[/C][C]0.413742[/C][C]0.827483[/C][C]0.586258[/C][/ROW]
[ROW][C]98[/C][C]0.39335[/C][C]0.786699[/C][C]0.60665[/C][/ROW]
[ROW][C]99[/C][C]0.409136[/C][C]0.818271[/C][C]0.590864[/C][/ROW]
[ROW][C]100[/C][C]0.535161[/C][C]0.929677[/C][C]0.464839[/C][/ROW]
[ROW][C]101[/C][C]0.514711[/C][C]0.970579[/C][C]0.485289[/C][/ROW]
[ROW][C]102[/C][C]0.511836[/C][C]0.976327[/C][C]0.488164[/C][/ROW]
[ROW][C]103[/C][C]0.512081[/C][C]0.975838[/C][C]0.487919[/C][/ROW]
[ROW][C]104[/C][C]0.514228[/C][C]0.971544[/C][C]0.485772[/C][/ROW]
[ROW][C]105[/C][C]0.538167[/C][C]0.923666[/C][C]0.461833[/C][/ROW]
[ROW][C]106[/C][C]0.553401[/C][C]0.893198[/C][C]0.446599[/C][/ROW]
[ROW][C]107[/C][C]0.582754[/C][C]0.834492[/C][C]0.417246[/C][/ROW]
[ROW][C]108[/C][C]0.777663[/C][C]0.444673[/C][C]0.222337[/C][/ROW]
[ROW][C]109[/C][C]0.883739[/C][C]0.232523[/C][C]0.116261[/C][/ROW]
[ROW][C]110[/C][C]0.878605[/C][C]0.242791[/C][C]0.121395[/C][/ROW]
[ROW][C]111[/C][C]0.869267[/C][C]0.261465[/C][C]0.130733[/C][/ROW]
[ROW][C]112[/C][C]0.862874[/C][C]0.274253[/C][C]0.137126[/C][/ROW]
[ROW][C]113[/C][C]0.926495[/C][C]0.14701[/C][C]0.0735051[/C][/ROW]
[ROW][C]114[/C][C]0.932132[/C][C]0.135735[/C][C]0.0678676[/C][/ROW]
[ROW][C]115[/C][C]0.951053[/C][C]0.0978938[/C][C]0.0489469[/C][/ROW]
[ROW][C]116[/C][C]0.960613[/C][C]0.0787734[/C][C]0.0393867[/C][/ROW]
[ROW][C]117[/C][C]0.965152[/C][C]0.0696954[/C][C]0.0348477[/C][/ROW]
[ROW][C]118[/C][C]0.9646[/C][C]0.070801[/C][C]0.0354005[/C][/ROW]
[ROW][C]119[/C][C]0.96415[/C][C]0.0716991[/C][C]0.0358496[/C][/ROW]
[ROW][C]120[/C][C]0.975055[/C][C]0.0498907[/C][C]0.0249453[/C][/ROW]
[ROW][C]121[/C][C]0.971917[/C][C]0.0561651[/C][C]0.0280826[/C][/ROW]
[ROW][C]122[/C][C]0.977706[/C][C]0.0445884[/C][C]0.0222942[/C][/ROW]
[ROW][C]123[/C][C]0.982555[/C][C]0.03489[/C][C]0.017445[/C][/ROW]
[ROW][C]124[/C][C]0.986031[/C][C]0.0279371[/C][C]0.0139686[/C][/ROW]
[ROW][C]125[/C][C]0.987504[/C][C]0.0249923[/C][C]0.0124961[/C][/ROW]
[ROW][C]126[/C][C]0.985298[/C][C]0.0294046[/C][C]0.0147023[/C][/ROW]
[ROW][C]127[/C][C]0.985742[/C][C]0.0285153[/C][C]0.0142576[/C][/ROW]
[ROW][C]128[/C][C]0.982847[/C][C]0.0343057[/C][C]0.0171528[/C][/ROW]
[ROW][C]129[/C][C]0.987219[/C][C]0.025561[/C][C]0.0127805[/C][/ROW]
[ROW][C]130[/C][C]0.985528[/C][C]0.0289444[/C][C]0.0144722[/C][/ROW]
[ROW][C]131[/C][C]0.983565[/C][C]0.0328701[/C][C]0.016435[/C][/ROW]
[ROW][C]132[/C][C]0.982178[/C][C]0.0356445[/C][C]0.0178222[/C][/ROW]
[ROW][C]133[/C][C]0.981766[/C][C]0.0364684[/C][C]0.0182342[/C][/ROW]
[ROW][C]134[/C][C]0.980782[/C][C]0.0384363[/C][C]0.0192181[/C][/ROW]
[ROW][C]135[/C][C]0.97704[/C][C]0.0459193[/C][C]0.0229597[/C][/ROW]
[ROW][C]136[/C][C]0.974719[/C][C]0.0505623[/C][C]0.0252811[/C][/ROW]
[ROW][C]137[/C][C]0.980228[/C][C]0.0395437[/C][C]0.0197718[/C][/ROW]
[ROW][C]138[/C][C]0.989562[/C][C]0.0208758[/C][C]0.0104379[/C][/ROW]
[ROW][C]139[/C][C]0.990225[/C][C]0.0195493[/C][C]0.00977467[/C][/ROW]
[ROW][C]140[/C][C]0.989123[/C][C]0.0217541[/C][C]0.010877[/C][/ROW]
[ROW][C]141[/C][C]0.987689[/C][C]0.0246218[/C][C]0.0123109[/C][/ROW]
[ROW][C]142[/C][C]0.987189[/C][C]0.0256224[/C][C]0.0128112[/C][/ROW]
[ROW][C]143[/C][C]0.985523[/C][C]0.0289541[/C][C]0.014477[/C][/ROW]
[ROW][C]144[/C][C]0.985613[/C][C]0.0287743[/C][C]0.0143871[/C][/ROW]
[ROW][C]145[/C][C]0.985562[/C][C]0.0288761[/C][C]0.0144381[/C][/ROW]
[ROW][C]146[/C][C]0.98644[/C][C]0.02712[/C][C]0.01356[/C][/ROW]
[ROW][C]147[/C][C]0.983792[/C][C]0.0324161[/C][C]0.0162081[/C][/ROW]
[ROW][C]148[/C][C]0.981387[/C][C]0.0372251[/C][C]0.0186125[/C][/ROW]
[ROW][C]149[/C][C]0.978253[/C][C]0.0434936[/C][C]0.0217468[/C][/ROW]
[ROW][C]150[/C][C]0.976544[/C][C]0.0469124[/C][C]0.0234562[/C][/ROW]
[ROW][C]151[/C][C]0.98432[/C][C]0.0313594[/C][C]0.0156797[/C][/ROW]
[ROW][C]152[/C][C]0.982875[/C][C]0.0342507[/C][C]0.0171253[/C][/ROW]
[ROW][C]153[/C][C]0.983139[/C][C]0.0337224[/C][C]0.0168612[/C][/ROW]
[ROW][C]154[/C][C]0.985109[/C][C]0.0297828[/C][C]0.0148914[/C][/ROW]
[ROW][C]155[/C][C]0.984333[/C][C]0.0313345[/C][C]0.0156673[/C][/ROW]
[ROW][C]156[/C][C]0.982767[/C][C]0.0344666[/C][C]0.0172333[/C][/ROW]
[ROW][C]157[/C][C]0.983786[/C][C]0.0324284[/C][C]0.0162142[/C][/ROW]
[ROW][C]158[/C][C]0.984237[/C][C]0.0315257[/C][C]0.0157629[/C][/ROW]
[ROW][C]159[/C][C]0.981663[/C][C]0.0366748[/C][C]0.0183374[/C][/ROW]
[ROW][C]160[/C][C]0.97924[/C][C]0.0415196[/C][C]0.0207598[/C][/ROW]
[ROW][C]161[/C][C]0.983617[/C][C]0.032766[/C][C]0.016383[/C][/ROW]
[ROW][C]162[/C][C]0.982195[/C][C]0.0356107[/C][C]0.0178053[/C][/ROW]
[ROW][C]163[/C][C]0.97958[/C][C]0.0408402[/C][C]0.0204201[/C][/ROW]
[ROW][C]164[/C][C]0.981926[/C][C]0.0361477[/C][C]0.0180738[/C][/ROW]
[ROW][C]165[/C][C]0.984663[/C][C]0.0306745[/C][C]0.0153372[/C][/ROW]
[ROW][C]166[/C][C]0.980852[/C][C]0.0382968[/C][C]0.0191484[/C][/ROW]
[ROW][C]167[/C][C]0.982661[/C][C]0.0346777[/C][C]0.0173389[/C][/ROW]
[ROW][C]168[/C][C]0.979019[/C][C]0.0419621[/C][C]0.020981[/C][/ROW]
[ROW][C]169[/C][C]0.974671[/C][C]0.0506575[/C][C]0.0253287[/C][/ROW]
[ROW][C]170[/C][C]0.97459[/C][C]0.050821[/C][C]0.0254105[/C][/ROW]
[ROW][C]171[/C][C]0.970445[/C][C]0.0591104[/C][C]0.0295552[/C][/ROW]
[ROW][C]172[/C][C]0.979122[/C][C]0.0417553[/C][C]0.0208777[/C][/ROW]
[ROW][C]173[/C][C]0.974358[/C][C]0.0512849[/C][C]0.0256424[/C][/ROW]
[ROW][C]174[/C][C]0.968655[/C][C]0.0626898[/C][C]0.0313449[/C][/ROW]
[ROW][C]175[/C][C]0.961928[/C][C]0.0761431[/C][C]0.0380716[/C][/ROW]
[ROW][C]176[/C][C]0.967307[/C][C]0.0653869[/C][C]0.0326935[/C][/ROW]
[ROW][C]177[/C][C]0.960309[/C][C]0.0793813[/C][C]0.0396906[/C][/ROW]
[ROW][C]178[/C][C]0.978711[/C][C]0.042579[/C][C]0.0212895[/C][/ROW]
[ROW][C]179[/C][C]0.974476[/C][C]0.0510475[/C][C]0.0255237[/C][/ROW]
[ROW][C]180[/C][C]0.982398[/C][C]0.0352035[/C][C]0.0176017[/C][/ROW]
[ROW][C]181[/C][C]0.978405[/C][C]0.0431892[/C][C]0.0215946[/C][/ROW]
[ROW][C]182[/C][C]0.974984[/C][C]0.0500323[/C][C]0.0250162[/C][/ROW]
[ROW][C]183[/C][C]0.975413[/C][C]0.0491744[/C][C]0.0245872[/C][/ROW]
[ROW][C]184[/C][C]0.971044[/C][C]0.0579124[/C][C]0.0289562[/C][/ROW]
[ROW][C]185[/C][C]0.973241[/C][C]0.0535172[/C][C]0.0267586[/C][/ROW]
[ROW][C]186[/C][C]0.967978[/C][C]0.0640447[/C][C]0.0320223[/C][/ROW]
[ROW][C]187[/C][C]0.970817[/C][C]0.0583651[/C][C]0.0291826[/C][/ROW]
[ROW][C]188[/C][C]0.968884[/C][C]0.0622329[/C][C]0.0311165[/C][/ROW]
[ROW][C]189[/C][C]0.96635[/C][C]0.0673003[/C][C]0.0336502[/C][/ROW]
[ROW][C]190[/C][C]0.960909[/C][C]0.078183[/C][C]0.0390915[/C][/ROW]
[ROW][C]191[/C][C]0.952901[/C][C]0.0941983[/C][C]0.0470992[/C][/ROW]
[ROW][C]192[/C][C]0.950636[/C][C]0.0987286[/C][C]0.0493643[/C][/ROW]
[ROW][C]193[/C][C]0.964448[/C][C]0.0711045[/C][C]0.0355523[/C][/ROW]
[ROW][C]194[/C][C]0.970856[/C][C]0.0582889[/C][C]0.0291445[/C][/ROW]
[ROW][C]195[/C][C]0.967499[/C][C]0.0650018[/C][C]0.0325009[/C][/ROW]
[ROW][C]196[/C][C]0.960719[/C][C]0.0785626[/C][C]0.0392813[/C][/ROW]
[ROW][C]197[/C][C]0.952181[/C][C]0.0956382[/C][C]0.0478191[/C][/ROW]
[ROW][C]198[/C][C]0.945925[/C][C]0.108151[/C][C]0.0540753[/C][/ROW]
[ROW][C]199[/C][C]0.947675[/C][C]0.10465[/C][C]0.0523248[/C][/ROW]
[ROW][C]200[/C][C]0.941639[/C][C]0.116721[/C][C]0.0583607[/C][/ROW]
[ROW][C]201[/C][C]0.951015[/C][C]0.0979708[/C][C]0.0489854[/C][/ROW]
[ROW][C]202[/C][C]0.947037[/C][C]0.105926[/C][C]0.0529629[/C][/ROW]
[ROW][C]203[/C][C]0.935357[/C][C]0.129287[/C][C]0.0646433[/C][/ROW]
[ROW][C]204[/C][C]0.923893[/C][C]0.152214[/C][C]0.0761069[/C][/ROW]
[ROW][C]205[/C][C]0.926647[/C][C]0.146706[/C][C]0.0733528[/C][/ROW]
[ROW][C]206[/C][C]0.915707[/C][C]0.168586[/C][C]0.0842929[/C][/ROW]
[ROW][C]207[/C][C]0.903485[/C][C]0.19303[/C][C]0.096515[/C][/ROW]
[ROW][C]208[/C][C]0.891389[/C][C]0.217222[/C][C]0.108611[/C][/ROW]
[ROW][C]209[/C][C]0.907225[/C][C]0.18555[/C][C]0.0927749[/C][/ROW]
[ROW][C]210[/C][C]0.898898[/C][C]0.202204[/C][C]0.101102[/C][/ROW]
[ROW][C]211[/C][C]0.880205[/C][C]0.23959[/C][C]0.119795[/C][/ROW]
[ROW][C]212[/C][C]0.863246[/C][C]0.273509[/C][C]0.136754[/C][/ROW]
[ROW][C]213[/C][C]0.841673[/C][C]0.316654[/C][C]0.158327[/C][/ROW]
[ROW][C]214[/C][C]0.825893[/C][C]0.348214[/C][C]0.174107[/C][/ROW]
[ROW][C]215[/C][C]0.805939[/C][C]0.388121[/C][C]0.194061[/C][/ROW]
[ROW][C]216[/C][C]0.775466[/C][C]0.449068[/C][C]0.224534[/C][/ROW]
[ROW][C]217[/C][C]0.765978[/C][C]0.468045[/C][C]0.234022[/C][/ROW]
[ROW][C]218[/C][C]0.762475[/C][C]0.47505[/C][C]0.237525[/C][/ROW]
[ROW][C]219[/C][C]0.728137[/C][C]0.543726[/C][C]0.271863[/C][/ROW]
[ROW][C]220[/C][C]0.693727[/C][C]0.612546[/C][C]0.306273[/C][/ROW]
[ROW][C]221[/C][C]0.709751[/C][C]0.580499[/C][C]0.290249[/C][/ROW]
[ROW][C]222[/C][C]0.727882[/C][C]0.544237[/C][C]0.272118[/C][/ROW]
[ROW][C]223[/C][C]0.689155[/C][C]0.621689[/C][C]0.310845[/C][/ROW]
[ROW][C]224[/C][C]0.649462[/C][C]0.701075[/C][C]0.350538[/C][/ROW]
[ROW][C]225[/C][C]0.628933[/C][C]0.742134[/C][C]0.371067[/C][/ROW]
[ROW][C]226[/C][C]0.607005[/C][C]0.785989[/C][C]0.392995[/C][/ROW]
[ROW][C]227[/C][C]0.57134[/C][C]0.857321[/C][C]0.42866[/C][/ROW]
[ROW][C]228[/C][C]0.559884[/C][C]0.880232[/C][C]0.440116[/C][/ROW]
[ROW][C]229[/C][C]0.602482[/C][C]0.795035[/C][C]0.397518[/C][/ROW]
[ROW][C]230[/C][C]0.60208[/C][C]0.795841[/C][C]0.39792[/C][/ROW]
[ROW][C]231[/C][C]0.644488[/C][C]0.711024[/C][C]0.355512[/C][/ROW]
[ROW][C]232[/C][C]0.723038[/C][C]0.553924[/C][C]0.276962[/C][/ROW]
[ROW][C]233[/C][C]0.684095[/C][C]0.631809[/C][C]0.315905[/C][/ROW]
[ROW][C]234[/C][C]0.671426[/C][C]0.657148[/C][C]0.328574[/C][/ROW]
[ROW][C]235[/C][C]0.630903[/C][C]0.738194[/C][C]0.369097[/C][/ROW]
[ROW][C]236[/C][C]0.91532[/C][C]0.16936[/C][C]0.0846799[/C][/ROW]
[ROW][C]237[/C][C]0.893483[/C][C]0.213034[/C][C]0.106517[/C][/ROW]
[ROW][C]238[/C][C]0.870788[/C][C]0.258424[/C][C]0.129212[/C][/ROW]
[ROW][C]239[/C][C]0.842222[/C][C]0.315555[/C][C]0.157778[/C][/ROW]
[ROW][C]240[/C][C]0.806845[/C][C]0.386309[/C][C]0.193155[/C][/ROW]
[ROW][C]241[/C][C]0.777205[/C][C]0.44559[/C][C]0.222795[/C][/ROW]
[ROW][C]242[/C][C]0.746248[/C][C]0.507504[/C][C]0.253752[/C][/ROW]
[ROW][C]243[/C][C]0.701796[/C][C]0.596408[/C][C]0.298204[/C][/ROW]
[ROW][C]244[/C][C]0.725529[/C][C]0.548943[/C][C]0.274471[/C][/ROW]
[ROW][C]245[/C][C]0.676198[/C][C]0.647604[/C][C]0.323802[/C][/ROW]
[ROW][C]246[/C][C]0.65581[/C][C]0.688381[/C][C]0.34419[/C][/ROW]
[ROW][C]247[/C][C]0.629458[/C][C]0.741084[/C][C]0.370542[/C][/ROW]
[ROW][C]248[/C][C]0.571157[/C][C]0.857685[/C][C]0.428843[/C][/ROW]
[ROW][C]249[/C][C]0.567522[/C][C]0.864957[/C][C]0.432478[/C][/ROW]
[ROW][C]250[/C][C]0.535828[/C][C]0.928343[/C][C]0.464172[/C][/ROW]
[ROW][C]251[/C][C]0.478993[/C][C]0.957986[/C][C]0.521007[/C][/ROW]
[ROW][C]252[/C][C]0.509494[/C][C]0.981012[/C][C]0.490506[/C][/ROW]
[ROW][C]253[/C][C]0.456007[/C][C]0.912014[/C][C]0.543993[/C][/ROW]
[ROW][C]254[/C][C]0.418651[/C][C]0.837302[/C][C]0.581349[/C][/ROW]
[ROW][C]255[/C][C]0.360741[/C][C]0.721482[/C][C]0.639259[/C][/ROW]
[ROW][C]256[/C][C]0.312489[/C][C]0.624979[/C][C]0.687511[/C][/ROW]
[ROW][C]257[/C][C]0.608601[/C][C]0.782799[/C][C]0.391399[/C][/ROW]
[ROW][C]258[/C][C]0.742783[/C][C]0.514435[/C][C]0.257217[/C][/ROW]
[ROW][C]259[/C][C]0.685587[/C][C]0.628825[/C][C]0.314413[/C][/ROW]
[ROW][C]260[/C][C]0.988272[/C][C]0.0234565[/C][C]0.0117282[/C][/ROW]
[ROW][C]261[/C][C]0.9809[/C][C]0.0381997[/C][C]0.0190999[/C][/ROW]
[ROW][C]262[/C][C]0.981091[/C][C]0.0378186[/C][C]0.0189093[/C][/ROW]
[ROW][C]263[/C][C]0.965658[/C][C]0.0686846[/C][C]0.0343423[/C][/ROW]
[ROW][C]264[/C][C]0.948344[/C][C]0.103312[/C][C]0.0516561[/C][/ROW]
[ROW][C]265[/C][C]0.906716[/C][C]0.186569[/C][C]0.0932844[/C][/ROW]
[ROW][C]266[/C][C]0.838406[/C][C]0.323187[/C][C]0.161594[/C][/ROW]
[ROW][C]267[/C][C]0.738548[/C][C]0.522903[/C][C]0.261452[/C][/ROW]
[ROW][C]268[/C][C]0.637698[/C][C]0.724603[/C][C]0.362302[/C][/ROW]
[ROW][C]269[/C][C]0.966849[/C][C]0.0663021[/C][C]0.0331511[/C][/ROW]
[ROW][C]270[/C][C]0.933482[/C][C]0.133037[/C][C]0.0665183[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265643&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265643&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
90.3502610.7005230.649739
100.5991570.8016860.400843
110.4603730.9207460.539627
120.7131190.5737610.286881
130.6200890.7598210.379911
140.5185610.9628790.481439
150.4544860.9089720.545514
160.3624910.7249820.637509
170.2798340.5596680.720166
180.2541660.5083320.745834
190.2099980.4199960.790002
200.1586190.3172380.841381
210.3121350.624270.687865
220.3171260.6342510.682874
230.2715210.5430420.728479
240.2621410.5242820.737859
250.2106990.4213980.789301
260.1988050.397610.801195
270.221590.4431790.77841
280.1842030.3684050.815797
290.2165550.433110.783445
300.1732990.3465980.826701
310.1444670.2889330.855533
320.1203870.2407740.879613
330.1174690.2349380.882531
340.1550080.3100160.844992
350.1281220.2562430.871878
360.1135090.2270180.886491
370.1051430.2102860.894857
380.09173910.1834780.908261
390.1059960.2119920.894004
400.08402620.1680520.915974
410.1921860.3843710.807814
420.1604770.3209540.839523
430.1464240.2928490.853576
440.1225990.2451970.877401
450.1096120.2192230.890388
460.09174990.18350.90825
470.07573740.1514750.924263
480.1185120.2370240.881488
490.1462540.2925080.853746
500.1299240.2598480.870076
510.1088780.2177560.891122
520.1373160.2746320.862684
530.1159490.2318990.884051
540.1085650.2171310.891435
550.1172150.2344290.882785
560.1014990.2029970.898501
570.2047960.4095930.795204
580.2838470.5676940.716153
590.2544210.5088410.745579
600.2503440.5006890.749656
610.2440020.4880040.755998
620.2186130.4372270.781387
630.2566940.5133880.743306
640.3182670.6365340.681733
650.2991310.5982630.700869
660.295450.5908990.70455
670.2753020.5506040.724698
680.2540870.5081740.745913
690.2975190.5950390.702481
700.2804850.560970.719515
710.2484380.4968760.751562
720.2215730.4431460.778427
730.2101370.4202740.789863
740.2133490.4266980.786651
750.199510.3990190.80049
760.1783280.3566550.821672
770.1599210.3198430.840079
780.1513030.3026060.848697
790.1341320.2682640.865868
800.158650.3173010.84135
810.143880.287760.85612
820.1533790.3067590.846621
830.1386250.2772510.861375
840.2503160.5006320.749684
850.2370870.4741730.762913
860.2107510.4215030.789249
870.1882140.3764280.811786
880.1785940.3571870.821406
890.2025750.4051490.797425
900.2240780.4481550.775922
910.2270960.4541930.772904
920.3546640.7093280.645336
930.3243270.6486550.675673
940.3288360.6576710.671164
950.3875560.7751120.612444
960.3774910.7549810.622509
970.4137420.8274830.586258
980.393350.7866990.60665
990.4091360.8182710.590864
1000.5351610.9296770.464839
1010.5147110.9705790.485289
1020.5118360.9763270.488164
1030.5120810.9758380.487919
1040.5142280.9715440.485772
1050.5381670.9236660.461833
1060.5534010.8931980.446599
1070.5827540.8344920.417246
1080.7776630.4446730.222337
1090.8837390.2325230.116261
1100.8786050.2427910.121395
1110.8692670.2614650.130733
1120.8628740.2742530.137126
1130.9264950.147010.0735051
1140.9321320.1357350.0678676
1150.9510530.09789380.0489469
1160.9606130.07877340.0393867
1170.9651520.06969540.0348477
1180.96460.0708010.0354005
1190.964150.07169910.0358496
1200.9750550.04989070.0249453
1210.9719170.05616510.0280826
1220.9777060.04458840.0222942
1230.9825550.034890.017445
1240.9860310.02793710.0139686
1250.9875040.02499230.0124961
1260.9852980.02940460.0147023
1270.9857420.02851530.0142576
1280.9828470.03430570.0171528
1290.9872190.0255610.0127805
1300.9855280.02894440.0144722
1310.9835650.03287010.016435
1320.9821780.03564450.0178222
1330.9817660.03646840.0182342
1340.9807820.03843630.0192181
1350.977040.04591930.0229597
1360.9747190.05056230.0252811
1370.9802280.03954370.0197718
1380.9895620.02087580.0104379
1390.9902250.01954930.00977467
1400.9891230.02175410.010877
1410.9876890.02462180.0123109
1420.9871890.02562240.0128112
1430.9855230.02895410.014477
1440.9856130.02877430.0143871
1450.9855620.02887610.0144381
1460.986440.027120.01356
1470.9837920.03241610.0162081
1480.9813870.03722510.0186125
1490.9782530.04349360.0217468
1500.9765440.04691240.0234562
1510.984320.03135940.0156797
1520.9828750.03425070.0171253
1530.9831390.03372240.0168612
1540.9851090.02978280.0148914
1550.9843330.03133450.0156673
1560.9827670.03446660.0172333
1570.9837860.03242840.0162142
1580.9842370.03152570.0157629
1590.9816630.03667480.0183374
1600.979240.04151960.0207598
1610.9836170.0327660.016383
1620.9821950.03561070.0178053
1630.979580.04084020.0204201
1640.9819260.03614770.0180738
1650.9846630.03067450.0153372
1660.9808520.03829680.0191484
1670.9826610.03467770.0173389
1680.9790190.04196210.020981
1690.9746710.05065750.0253287
1700.974590.0508210.0254105
1710.9704450.05911040.0295552
1720.9791220.04175530.0208777
1730.9743580.05128490.0256424
1740.9686550.06268980.0313449
1750.9619280.07614310.0380716
1760.9673070.06538690.0326935
1770.9603090.07938130.0396906
1780.9787110.0425790.0212895
1790.9744760.05104750.0255237
1800.9823980.03520350.0176017
1810.9784050.04318920.0215946
1820.9749840.05003230.0250162
1830.9754130.04917440.0245872
1840.9710440.05791240.0289562
1850.9732410.05351720.0267586
1860.9679780.06404470.0320223
1870.9708170.05836510.0291826
1880.9688840.06223290.0311165
1890.966350.06730030.0336502
1900.9609090.0781830.0390915
1910.9529010.09419830.0470992
1920.9506360.09872860.0493643
1930.9644480.07110450.0355523
1940.9708560.05828890.0291445
1950.9674990.06500180.0325009
1960.9607190.07856260.0392813
1970.9521810.09563820.0478191
1980.9459250.1081510.0540753
1990.9476750.104650.0523248
2000.9416390.1167210.0583607
2010.9510150.09797080.0489854
2020.9470370.1059260.0529629
2030.9353570.1292870.0646433
2040.9238930.1522140.0761069
2050.9266470.1467060.0733528
2060.9157070.1685860.0842929
2070.9034850.193030.096515
2080.8913890.2172220.108611
2090.9072250.185550.0927749
2100.8988980.2022040.101102
2110.8802050.239590.119795
2120.8632460.2735090.136754
2130.8416730.3166540.158327
2140.8258930.3482140.174107
2150.8059390.3881210.194061
2160.7754660.4490680.224534
2170.7659780.4680450.234022
2180.7624750.475050.237525
2190.7281370.5437260.271863
2200.6937270.6125460.306273
2210.7097510.5804990.290249
2220.7278820.5442370.272118
2230.6891550.6216890.310845
2240.6494620.7010750.350538
2250.6289330.7421340.371067
2260.6070050.7859890.392995
2270.571340.8573210.42866
2280.5598840.8802320.440116
2290.6024820.7950350.397518
2300.602080.7958410.39792
2310.6444880.7110240.355512
2320.7230380.5539240.276962
2330.6840950.6318090.315905
2340.6714260.6571480.328574
2350.6309030.7381940.369097
2360.915320.169360.0846799
2370.8934830.2130340.106517
2380.8707880.2584240.129212
2390.8422220.3155550.157778
2400.8068450.3863090.193155
2410.7772050.445590.222795
2420.7462480.5075040.253752
2430.7017960.5964080.298204
2440.7255290.5489430.274471
2450.6761980.6476040.323802
2460.655810.6883810.34419
2470.6294580.7410840.370542
2480.5711570.8576850.428843
2490.5675220.8649570.432478
2500.5358280.9283430.464172
2510.4789930.9579860.521007
2520.5094940.9810120.490506
2530.4560070.9120140.543993
2540.4186510.8373020.581349
2550.3607410.7214820.639259
2560.3124890.6249790.687511
2570.6086010.7827990.391399
2580.7427830.5144350.257217
2590.6855870.6288250.314413
2600.9882720.02345650.0117282
2610.98090.03819970.0190999
2620.9810910.03781860.0189093
2630.9656580.06868460.0343423
2640.9483440.1033120.0516561
2650.9067160.1865690.0932844
2660.8384060.3231870.161594
2670.7385480.5229030.261452
2680.6376980.7246030.362302
2690.9668490.06630210.0331511
2700.9334820.1330370.0665183






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level550.209924NOK
10% type I error level890.339695NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 55 & 0.209924 & NOK \tabularnewline
10% type I error level & 89 & 0.339695 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265643&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]55[/C][C]0.209924[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]89[/C][C]0.339695[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265643&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265643&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level550.209924NOK
10% type I error level890.339695NOK


Figures (Output of Computation)

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Input Parameters & R Code

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