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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 19 Nov 2013 14:17:33 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/19/t1384889029za759f1rsh82j5s.htm/, Retrieved Sat, 04 May 2024 05:24:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226550, Retrieved Sat, 04 May 2024 05:24:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact55

Tree of Dependent Computations

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14 41 38 13 12 53 32 9
18 39 32 16 11 83 51 9
11 30 35 19 14 66 42 9
12 31 33 15 12 67 41 9
16 34 37 14 21 76 46 9
18 35 29 13 12 78 47 9
14 39 31 19 22 53 37 9
14 34 36 15 11 80 49 9
15 36 35 14 10 74 45 9
15 37 38 15 13 76 47 9
17 38 31 16 10 79 49 9
19 36 34 16 8 54 33 9
10 38 35 16 15 67 42 9
16 39 38 16 14 54 33 9
18 33 37 17 10 87 53 9
14 32 33 15 14 58 36 9
14 36 32 15 14 75 45 9
17 38 38 20 11 88 54 9
14 39 38 18 10 64 41 9
16 32 32 16 13 57 36 9
18 32 33 16 9.5 66 41 9
11 31 31 16 14 68 44 9
14 39 38 19 12 54 33 9
12 37 39 16 14 56 37 9
17 39 32 17 11 86 52 9
9 41 32 17 9 80 47 9
16 36 35 16 11 76 43 9
14 33 37 15 15 69 44 9
15 33 33 16 14 78 45 9
11 34 33 14 13 67 44 9
16 31 31 15 9 80 49 9
13 27 32 12 15 54 33 9
17 37 31 14 10 71 43 9
15 34 37 16 11 84 54 9
14 34 30 14 13 74 42 9
16 32 33 10 8 71 44 9
9 29 31 10 20 63 37 9
15 36 33 14 12 71 43 9
17 29 31 16 10 76 46 9
13 35 33 16 10 69 42 9
15 37 32 16 9 74 45 9
16 34 33 14 14 75 44 9
16 38 32 20 8 54 33 9
12 35 33 14 14 52 31 9
15 38 28 14 11 69 42 9
11 37 35 11 13 68 40 9
15 38 39 14 9 65 43 9
15 33 34 15 11 75 46 9
17 36 38 16 15 74 42 9
13 38 32 14 11 75 45 9
16 32 38 16 10 72 44 9
14 32 30 14 14 67 40 9
11 32 33 12 18 63 37 9
12 34 38 16 14 62 46 9
12 32 32 9 11 63 36 9
15 37 35 14 14.5 76 47 9
16 39 34 16 13 74 45 9
15 29 34 16 9 67 42 9
12 37 36 15 10 73 43 9
12 35 34 16 15 70 43 9
8 30 28 12 20 53 32 9
13 38 34 16 12 77 45 9
11 34 35 16 12 80 48 9
14 31 35 14 14 52 31 9
15 34 31 16 13 54 33 9
10 35 37 17 11 80 49 10
11 36 35 18 17 66 42 10
12 30 27 18 12 73 41 10
15 39 40 12 13 63 38 10
15 35 37 16 14 69 42 10
14 38 36 10 13 67 44 10
16 31 38 14 15 54 33 10
15 34 39 18 13 81 48 10
15 38 41 18 10 69 40 10
13 34 27 16 11 84 50 10
12 39 30 17 19 80 49 10
17 37 37 16 13 70 43 10
13 34 31 16 17 69 44 10
15 28 31 13 13 77 47 10
13 37 27 16 9 54 33 10
15 33 36 16 11 79 46 10
15 35 37 16 9 71 45 10
16 37 33 15 12 73 43 10
15 32 34 15 12 72 44 10
14 33 31 16 13 77 47 10
15 38 39 14 13 75 45 10
14 33 34 16 12 69 42 10
13 29 32 16 15 54 33 10
7 33 33 15 22 70 43 10
17 31 36 12 13 73 46 10
13 36 32 17 15 54 33 10
15 35 41 16 13 77 46 10
14 32 28 15 15 82 48 10
13 29 30 13 12.5 80 47 10
16 39 36 16 11 80 47 10
12 37 35 16 16 69 43 10
14 35 31 16 11 78 46 10
17 37 34 16 11 81 48 10
15 32 36 14 10 76 46 10
17 38 36 16 10 76 45 10
12 37 35 16 16 73 45 10
16 36 37 20 12 85 52 10
11 32 28 15 11 66 42 10
15 33 39 16 16 79 47 10
9 40 32 13 19 68 41 10
16 38 35 17 11 76 47 10
15 41 39 16 16 71 43 10
10 36 35 16 15 54 33 10
10 43 42 12 24 46 30 10
15 30 34 16 14 85 52 10
11 31 33 16 15 74 44 10
13 32 41 17 11 88 55 10
14 32 33 13 15 38 11 10
18 37 34 12 12 76 47 10
16 37 32 18 10 86 53 10
14 33 40 14 14 54 33 10
14 34 40 14 13 67 44 10
14 33 35 13 9 69 42 10
14 38 36 16 15 90 55 10
12 33 37 13 15 54 33 10
14 31 27 16 14 76 46 10
15 38 39 13 11 89 54 10
15 37 38 16 8 76 47 10
15 36 31 15 11 73 45 10
13 31 33 16 11 79 47 10
17 39 32 15 8 90 55 10
17 44 39 17 10 74 44 10
19 33 36 15 11 81 53 10
15 35 33 12 13 72 44 10
13 32 33 16 11 71 42 10
9 28 32 10 20 66 40 10
15 40 37 16 10 77 46 10
15 27 30 12 15 65 40 10
15 37 38 14 12 74 46 10
16 32 29 15 14 85 53 10
11 28 22 13 23 54 33 10
14 34 35 15 14 63 42 10
11 30 35 11 16 54 35 10
15 35 34 12 11 64 40 10
13 31 35 11 12 69 41 10
15 32 34 16 10 54 33 10
16 30 37 15 14 84 51 10
14 30 35 17 12 86 53 10
15 31 23 16 12 77 46 10
16 40 31 10 11 89 55 10
16 32 27 18 12 76 47 10
11 36 36 13 13 60 38 10
12 32 31 16 11 75 46 10
9 35 32 13 19 73 46 10
16 38 39 10 12 85 53 10
13 42 37 15 17 79 47 10
16 34 38 16 9 71 41 10
12 35 39 16 12 72 44 10
9 38 34 14 19 69 43 9
13 33 31 10 18 78 51 10
13 36 32 17 15 54 33 10
14 32 37 13 14 69 43 10
19 33 36 15 11 81 53 10
13 34 32 16 9 84 51 10
12 32 38 12 18 84 50 10
13 34 36 13 16 69 46 10
10 27 26 13 24 66 43 11
14 31 26 12 14 81 47 11
16 38 33 17 20 82 50 11
10 34 39 15 18 72 43 11
11 24 30 10 23 54 33 11
14 30 33 14 12 78 48 11
12 26 25 11 14 74 44 11
9 34 38 13 16 82 50 11
9 27 37 16 18 73 41 11
11 37 31 12 20 55 34 11
16 36 37 16 12 72 44 11
9 41 35 12 12 78 47 11
13 29 25 9 17 59 35 11
16 36 28 12 13 72 44 11
13 32 35 15 9 78 44 11
9 37 33 12 16 68 43 11
12 30 30 12 18 69 41 11
16 31 31 14 10 67 41 11
11 38 37 12 14 74 42 11
14 36 36 16 11 54 33 11
13 35 30 11 9 67 41 11
15 31 36 19 11 70 44 11
14 38 32 15 10 80 48 11
16 22 28 8 11 89 55 11
13 32 36 16 19 76 44 11
14 36 34 17 14 74 43 11
15 39 31 12 12 87 52 11
13 28 28 11 14 54 30 11
11 32 36 11 21 61 39 11
11 32 36 14 13 38 11 11
14 38 40 16 10 75 44 11
15 32 33 12 15 69 42 11
11 35 37 16 16 62 41 11
15 32 32 13 14 72 44 11
12 37 38 15 12 70 44 11
14 34 31 16 19 79 48 11
14 33 37 16 15 87 53 11
8 33 33 14 19 62 37 11
13 26 32 16 13 77 44 11
9 30 30 16 17 69 44 11
15 24 30 14 12 69 40 11
17 34 31 11 11 75 42 11
13 34 32 12 14 54 35 11
15 33 34 15 11 72 43 11
15 34 36 15 13 74 45 11
14 35 37 16 12 85 55 11
16 35 36 16 15 52 31 11
13 36 33 11 14 70 44 11
16 34 33 15 12 84 50 11
9 34 33 12 17 64 40 11
16 41 44 12 11 84 53 11
11 32 39 15 18 87 54 11
10 30 32 15 13 79 49 11
11 35 35 16 17 67 40 11
15 28 25 14 13 65 41 11
17 33 35 17 11 85 52 11
14 39 34 14 12 83 52 11
8 36 35 13 22 61 36 11
15 36 39 15 14 82 52 11
11 35 33 13 12 76 46 11
16 38 36 14 12 58 31 11
10 33 32 15 17 72 44 11
15 31 32 12 9 72 44 11
9 34 36 13 21 38 11 11
16 32 36 8 10 78 46 11
19 31 32 14 11 54 33 11
12 33 34 14 12 63 34 11
8 34 33 11 23 66 42 11
11 34 35 12 13 70 43 11
14 34 30 13 12 71 43 11
9 33 38 10 16 67 44 11
15 32 34 16 9 58 36 11
13 41 33 18 17 72 46 11
16 34 32 13 9 72 44 11
11 36 31 11 14 70 43 11
12 37 30 4 17 76 50 11
13 36 27 13 13 50 33 11
10 29 31 16 11 72 43 11
11 37 30 10 12 72 44 11
12 27 32 12 10 88 53 11
8 35 35 12 19 53 34 11
12 28 28 10 16 58 35 11
12 35 33 13 16 66 40 11
15 37 31 15 14 82 53 11
11 29 35 12 20 69 42 11
13 32 35 14 15 68 43 11
14 36 32 10 23 44 29 11
10 19 21 12 20 56 36 11
12 21 20 12 16 53 30 11
15 31 34 11 14 70 42 11
13 33 32 10 17 78 47 11
13 36 34 12 11 71 44 11
13 33 32 16 13 72 45 11
12 37 33 12 17 68 44 11
12 34 33 14 15 67 43 11
9 35 37 16 21 75 43 11
9 31 32 14 18 62 40 11
15 37 34 13 15 67 41 11
10 35 30 4 8 83 52 11
14 27 30 15 12 64 38 11
15 34 38 11 12 68 41 11
7 40 36 11 22 62 39 11
14 29 32 14 12 72 43 11

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 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 & 14 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226550&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]14 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=226550&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226550&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 time14 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 18.1535 + 0.00435118Connected[t] + 0.0110693Separate[t] + 0.0816438Learning[t] -0.363622Depression[t] + 0.01612Sport1[t] + 0.0151722Sport2[t] -0.312112Month[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  18.1535 +  0.00435118Connected[t] +  0.0110693Separate[t] +  0.0816438Learning[t] -0.363622Depression[t] +  0.01612Sport1[t] +  0.0151722Sport2[t] -0.312112Month[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226550&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  18.1535 +  0.00435118Connected[t] +  0.0110693Separate[t] +  0.0816438Learning[t] -0.363622Depression[t] +  0.01612Sport1[t] +  0.0151722Sport2[t] -0.312112Month[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226550&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226550&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
Happiness[t] = + 18.1535 + 0.00435118Connected[t] + 0.0110693Separate[t] + 0.0816438Learning[t] -0.363622Depression[t] + 0.01612Sport1[t] + 0.0151722Sport2[t] -0.312112Month[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)18.15352.623216.923.6042e-111.8021e-11
Connected0.004351180.03747350.11610.9076530.453827
Separate0.01106930.03799760.29130.7710460.385523
Learning0.08164380.0554261.4730.1419740.0709868
Depression-0.3636220.0396756-9.1651.66825e-178.34126e-18
Sport10.016120.04066720.39640.6921490.346075
Sport20.01517220.06041040.25120.8018990.400949
Month-0.3121120.171881-1.8160.07056110.0352805

\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) & 18.1535 & 2.62321 & 6.92 & 3.6042e-11 & 1.8021e-11 \tabularnewline
Connected & 0.00435118 & 0.0374735 & 0.1161 & 0.907653 & 0.453827 \tabularnewline
Separate & 0.0110693 & 0.0379976 & 0.2913 & 0.771046 & 0.385523 \tabularnewline
Learning & 0.0816438 & 0.055426 & 1.473 & 0.141974 & 0.0709868 \tabularnewline
Depression & -0.363622 & 0.0396756 & -9.165 & 1.66825e-17 & 8.34126e-18 \tabularnewline
Sport1 & 0.01612 & 0.0406672 & 0.3964 & 0.692149 & 0.346075 \tabularnewline
Sport2 & 0.0151722 & 0.0604104 & 0.2512 & 0.801899 & 0.400949 \tabularnewline
Month & -0.312112 & 0.171881 & -1.816 & 0.0705611 & 0.0352805 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226550&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]18.1535[/C][C]2.62321[/C][C]6.92[/C][C]3.6042e-11[/C][C]1.8021e-11[/C][/ROW]
[ROW][C]Connected[/C][C]0.00435118[/C][C]0.0374735[/C][C]0.1161[/C][C]0.907653[/C][C]0.453827[/C][/ROW]
[ROW][C]Separate[/C][C]0.0110693[/C][C]0.0379976[/C][C]0.2913[/C][C]0.771046[/C][C]0.385523[/C][/ROW]
[ROW][C]Learning[/C][C]0.0816438[/C][C]0.055426[/C][C]1.473[/C][C]0.141974[/C][C]0.0709868[/C][/ROW]
[ROW][C]Depression[/C][C]-0.363622[/C][C]0.0396756[/C][C]-9.165[/C][C]1.66825e-17[/C][C]8.34126e-18[/C][/ROW]
[ROW][C]Sport1[/C][C]0.01612[/C][C]0.0406672[/C][C]0.3964[/C][C]0.692149[/C][C]0.346075[/C][/ROW]
[ROW][C]Sport2[/C][C]0.0151722[/C][C]0.0604104[/C][C]0.2512[/C][C]0.801899[/C][C]0.400949[/C][/ROW]
[ROW][C]Month[/C][C]-0.312112[/C][C]0.171881[/C][C]-1.816[/C][C]0.0705611[/C][C]0.0352805[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226550&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226550&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)18.15352.623216.923.6042e-111.8021e-11
Connected0.004351180.03747350.11610.9076530.453827
Separate0.01106930.03799760.29130.7710460.385523
Learning0.08164380.0554261.4730.1419740.0709868
Depression-0.3636220.0396756-9.1651.66825e-178.34126e-18
Sport10.016120.04066720.39640.6921490.346075
Sport20.01517220.06041040.25120.8018990.400949
Month-0.3121120.171881-1.8160.07056110.0352805






Multiple Linear Regression - Regression Statistics
Multiple R0.60953
R-squared0.371526
Adjusted R-squared0.354341
F-TEST (value)21.6194
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.00773
Sum Squared Residuals1031.93

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.60953 \tabularnewline
R-squared & 0.371526 \tabularnewline
Adjusted R-squared & 0.354341 \tabularnewline
F-TEST (value) & 21.6194 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.00773 \tabularnewline
Sum Squared Residuals & 1031.93 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226550&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.60953[/C][/ROW]
[ROW][C]R-squared[/C][C]0.371526[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.354341[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]21.6194[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.00773[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1031.93[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226550&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226550&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.60953
R-squared0.371526
Adjusted R-squared0.354341
F-TEST (value)21.6194
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.00773
Sum Squared Residuals1031.93






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.98130.0186593
21815.28662.71335
31114.0242-3.02417
41214.408-2.408
51611.3324.66797
61814.48623.51381
71410.82473.17534
81415.1488-1.14882
91515.271-0.271022
101514.36190.638056
111715.541.45998
121915.6463.35398
131013.4665-3.46655
141613.52162.47838
151815.8562.14402
161413.46420.535834
171413.88110.118909
181715.80141.1986
191415.422-1.42197
201613.88222.11776
211815.38692.61307
221113.8019-2.8019
231414.4938-0.493793
241213.6169-1.61691
251715.43181.56818
26915.9952-6.99519
271615.07260.927416
281413.44790.55213
291514.00910.99089
301114.0213-3.0213
311615.80770.192337
321312.71280.287209
331715.15241.84761
341515.3819-0.381873
351414.0706-0.0705913
361615.56860.431385
37910.9348-1.9348
381514.44290.557064
391715.4071.59301
401315.2817-2.2817
411515.7691-0.769075
421613.78662.21336
431615.95920.0408427
441213.223-1.223
451514.71250.287499
461113.767-2.767
471515.5122-0.512199
481514.99620.00378661
491713.60393.39611
501314.899-1.89901
511615.40270.597299
521413.55510.444917
531111.8605-0.860519
541213.8261-1.82606
551214.1347-2.1347
561513.70171.29834
571614.34541.65457
581515.598-0.598048
591215.3216-3.32162
601213.506-1.50596
61810.8322-2.83217
621314.7531-1.75306
631114.8406-3.8406
641413.22770.772271
651513.7861.214
661015.0154-5.01542
671112.5657-1.56566
681214.3668-2.36677
691513.48961.51037
701513.55941.44062
711413.43320.566771
721612.64783.35221
731514.38860.611449
741515.2041-0.204143
751314.8984-1.89838
761212.0464-0.0463606
771713.9633.037
781312.42810.571907
791513.7861.21398
801314.8972-1.89715
811514.85240.147636
821515.4552-0.455247
831614.24911.75094
841514.23740.762576
851414.0527-0.0527058
861513.93711.06286
871414.2447-0.244715
881312.7360.264043
89710.5471-3.54708
901713.69313.30688
911312.84810.151941
921514.15690.843071
931413.3020.697969
941314.0095-1.00947
951614.90981.09024
961212.8339-0.833874
971414.7896-0.7896
981714.91022.08979
9915151.31151e-05
1001715.17421.82579
1011212.9287-0.928698
1021615.02720.972807
1031114.4076-3.40757
1041513.08261.91737
105911.4315-2.43146
1061614.91151.08849
1071512.92782.0722
1081012.7996-2.79962
109109.133920.866082
1101513.91411.08594
1111113.245-2.24502
1121315.2666-2.26663
1131411.92342.07656
1141814.12423.87575
1151615.57140.428554
1161413.04230.95775
1171413.78670.213323
1181415.1017-1.10172
1191413.73350.266498
1201212.5638-0.563777
1211413.60480.395188
1221514.9450.0550266
1231515.9496-0.949585
1241514.61650.383465
1251314.8256-1.82563
1261716.15730.842715
1271715.26781.73224
1281914.90924.09083
1291513.63091.36914
1301314.6252-1.62516
131910.7233-1.72328
1321515.2253-0.225273
1331512.66212.33793
1341514.28440.715602
1351613.80092.19906
136119.467011.53299
1371413.35450.645472
1381112.032-1.03202
1391514.17950.82048
1401313.8237-0.823691
1411514.58930.410742
1421613.83432.16567
1431414.7653-0.765308
1441514.30390.696101
1451614.63541.36464
1461614.51491.48513
1471113.4656-2.46559
1481214.7282-2.72819
149911.5662-2.56616
1501614.25681.74323
1511312.65440.345609
1521615.40130.598723
1531214.3875-2.38747
154911.8851-2.88511
1551311.82151.17846
1561312.84810.151941
1571413.31660.683431
1581914.90924.09083
1591315.6961-2.69614
1601212.1395-0.139512
1611312.63250.367525
162109.176360.82364
1631413.05080.949172
1641611.44694.5531
1651011.7925-1.79246
166118.981112.01889
1671413.98130.0186947
1681212.778-0.778002
169912.6127-3.61275
170911.8073-2.80728
1711110.33420.665807
1721614.05761.94243
173913.8728-4.87285
1741311.15861.84145
1751613.26772.73225
1761315.124-2.12397
177912.1569-3.15693
1781211.35180.648206
1791614.40721.59276
1801113.0143-2.01435
1811413.95310.0469324
1821314.5323-1.53226
1831514.60110.398943
1841414.8462-0.846173
1851614.04841.95157
1861311.54821.45178
1871413.39580.604171
1881514.04080.959192
1891312.28510.714897
1901110.09510.904902
1911112.4534-1.45342
1921414.8751-0.875082
1931512.49972.50026
1941112.392-1.39201
1951513.01261.98736
1961213.9591-1.95911
1971411.61062.38937
1981413.3320.668001
199811.0242-3.02419
2001313.6757-0.675688
201912.0875-3.08751
2021513.65551.34447
2031713.95593.04413
2041312.5130.487008
2051514.27810.721887
2061513.63991.36006
2071414.4297-0.429671
2081612.43163.56836
2091312.84560.154411
2101614.20741.79258
211911.6703-2.67026
2121614.52381.47615
2131112.1924-1.19245
2141013.7196-3.71955
2151112.0717-1.07168
2161513.20471.79534
2171714.79862.20142
2181414.1728-0.172824
21989.85558-1.85558
2201513.55341.4466
2211113.8588-2.85883
2221613.4692.531
2231012.0894-2.08942
2241514.74480.255243
22599.47151-0.471508
2261614.23031.76975
2271913.72375.27625
2281213.5512-1.55122
22989.46947-1.46947
2301113.2891-2.28912
2311413.69520.304842
232912.0306-3.03063
2331514.75080.249236
2341312.41060.58943
2351614.83951.16055
2361112.8083-1.80828
2371211.34210.657887
2381312.81680.183211
2391014.3091-4.30914
2401113.4946-2.49457
2411214.7582-2.7582
242810.7011-2.70115
2431211.61660.383444
2441212.1521-0.152113
2451513.48441.51563
2461110.69070.309282
2471312.68420.31578
248148.833585.16642
2491010.1916-0.191643
2501211.50440.49563
2511512.80462.19544
2521311.82341.17657
2531314.0453-1.04529
2541313.6407-0.640719
2551211.80850.191522
2561212.6547-0.654664
257910.8138-1.81381
258911.4136-2.41356
2591512.56682.4332
2601014.7492-4.74919
2611413.63930.360714
2621513.54171.45828
26379.78241-2.78241
2641413.79330.206696

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 13.9813 & 0.0186593 \tabularnewline
2 & 18 & 15.2866 & 2.71335 \tabularnewline
3 & 11 & 14.0242 & -3.02417 \tabularnewline
4 & 12 & 14.408 & -2.408 \tabularnewline
5 & 16 & 11.332 & 4.66797 \tabularnewline
6 & 18 & 14.4862 & 3.51381 \tabularnewline
7 & 14 & 10.8247 & 3.17534 \tabularnewline
8 & 14 & 15.1488 & -1.14882 \tabularnewline
9 & 15 & 15.271 & -0.271022 \tabularnewline
10 & 15 & 14.3619 & 0.638056 \tabularnewline
11 & 17 & 15.54 & 1.45998 \tabularnewline
12 & 19 & 15.646 & 3.35398 \tabularnewline
13 & 10 & 13.4665 & -3.46655 \tabularnewline
14 & 16 & 13.5216 & 2.47838 \tabularnewline
15 & 18 & 15.856 & 2.14402 \tabularnewline
16 & 14 & 13.4642 & 0.535834 \tabularnewline
17 & 14 & 13.8811 & 0.118909 \tabularnewline
18 & 17 & 15.8014 & 1.1986 \tabularnewline
19 & 14 & 15.422 & -1.42197 \tabularnewline
20 & 16 & 13.8822 & 2.11776 \tabularnewline
21 & 18 & 15.3869 & 2.61307 \tabularnewline
22 & 11 & 13.8019 & -2.8019 \tabularnewline
23 & 14 & 14.4938 & -0.493793 \tabularnewline
24 & 12 & 13.6169 & -1.61691 \tabularnewline
25 & 17 & 15.4318 & 1.56818 \tabularnewline
26 & 9 & 15.9952 & -6.99519 \tabularnewline
27 & 16 & 15.0726 & 0.927416 \tabularnewline
28 & 14 & 13.4479 & 0.55213 \tabularnewline
29 & 15 & 14.0091 & 0.99089 \tabularnewline
30 & 11 & 14.0213 & -3.0213 \tabularnewline
31 & 16 & 15.8077 & 0.192337 \tabularnewline
32 & 13 & 12.7128 & 0.287209 \tabularnewline
33 & 17 & 15.1524 & 1.84761 \tabularnewline
34 & 15 & 15.3819 & -0.381873 \tabularnewline
35 & 14 & 14.0706 & -0.0705913 \tabularnewline
36 & 16 & 15.5686 & 0.431385 \tabularnewline
37 & 9 & 10.9348 & -1.9348 \tabularnewline
38 & 15 & 14.4429 & 0.557064 \tabularnewline
39 & 17 & 15.407 & 1.59301 \tabularnewline
40 & 13 & 15.2817 & -2.2817 \tabularnewline
41 & 15 & 15.7691 & -0.769075 \tabularnewline
42 & 16 & 13.7866 & 2.21336 \tabularnewline
43 & 16 & 15.9592 & 0.0408427 \tabularnewline
44 & 12 & 13.223 & -1.223 \tabularnewline
45 & 15 & 14.7125 & 0.287499 \tabularnewline
46 & 11 & 13.767 & -2.767 \tabularnewline
47 & 15 & 15.5122 & -0.512199 \tabularnewline
48 & 15 & 14.9962 & 0.00378661 \tabularnewline
49 & 17 & 13.6039 & 3.39611 \tabularnewline
50 & 13 & 14.899 & -1.89901 \tabularnewline
51 & 16 & 15.4027 & 0.597299 \tabularnewline
52 & 14 & 13.5551 & 0.444917 \tabularnewline
53 & 11 & 11.8605 & -0.860519 \tabularnewline
54 & 12 & 13.8261 & -1.82606 \tabularnewline
55 & 12 & 14.1347 & -2.1347 \tabularnewline
56 & 15 & 13.7017 & 1.29834 \tabularnewline
57 & 16 & 14.3454 & 1.65457 \tabularnewline
58 & 15 & 15.598 & -0.598048 \tabularnewline
59 & 12 & 15.3216 & -3.32162 \tabularnewline
60 & 12 & 13.506 & -1.50596 \tabularnewline
61 & 8 & 10.8322 & -2.83217 \tabularnewline
62 & 13 & 14.7531 & -1.75306 \tabularnewline
63 & 11 & 14.8406 & -3.8406 \tabularnewline
64 & 14 & 13.2277 & 0.772271 \tabularnewline
65 & 15 & 13.786 & 1.214 \tabularnewline
66 & 10 & 15.0154 & -5.01542 \tabularnewline
67 & 11 & 12.5657 & -1.56566 \tabularnewline
68 & 12 & 14.3668 & -2.36677 \tabularnewline
69 & 15 & 13.4896 & 1.51037 \tabularnewline
70 & 15 & 13.5594 & 1.44062 \tabularnewline
71 & 14 & 13.4332 & 0.566771 \tabularnewline
72 & 16 & 12.6478 & 3.35221 \tabularnewline
73 & 15 & 14.3886 & 0.611449 \tabularnewline
74 & 15 & 15.2041 & -0.204143 \tabularnewline
75 & 13 & 14.8984 & -1.89838 \tabularnewline
76 & 12 & 12.0464 & -0.0463606 \tabularnewline
77 & 17 & 13.963 & 3.037 \tabularnewline
78 & 13 & 12.4281 & 0.571907 \tabularnewline
79 & 15 & 13.786 & 1.21398 \tabularnewline
80 & 13 & 14.8972 & -1.89715 \tabularnewline
81 & 15 & 14.8524 & 0.147636 \tabularnewline
82 & 15 & 15.4552 & -0.455247 \tabularnewline
83 & 16 & 14.2491 & 1.75094 \tabularnewline
84 & 15 & 14.2374 & 0.762576 \tabularnewline
85 & 14 & 14.0527 & -0.0527058 \tabularnewline
86 & 15 & 13.9371 & 1.06286 \tabularnewline
87 & 14 & 14.2447 & -0.244715 \tabularnewline
88 & 13 & 12.736 & 0.264043 \tabularnewline
89 & 7 & 10.5471 & -3.54708 \tabularnewline
90 & 17 & 13.6931 & 3.30688 \tabularnewline
91 & 13 & 12.8481 & 0.151941 \tabularnewline
92 & 15 & 14.1569 & 0.843071 \tabularnewline
93 & 14 & 13.302 & 0.697969 \tabularnewline
94 & 13 & 14.0095 & -1.00947 \tabularnewline
95 & 16 & 14.9098 & 1.09024 \tabularnewline
96 & 12 & 12.8339 & -0.833874 \tabularnewline
97 & 14 & 14.7896 & -0.7896 \tabularnewline
98 & 17 & 14.9102 & 2.08979 \tabularnewline
99 & 15 & 15 & 1.31151e-05 \tabularnewline
100 & 17 & 15.1742 & 1.82579 \tabularnewline
101 & 12 & 12.9287 & -0.928698 \tabularnewline
102 & 16 & 15.0272 & 0.972807 \tabularnewline
103 & 11 & 14.4076 & -3.40757 \tabularnewline
104 & 15 & 13.0826 & 1.91737 \tabularnewline
105 & 9 & 11.4315 & -2.43146 \tabularnewline
106 & 16 & 14.9115 & 1.08849 \tabularnewline
107 & 15 & 12.9278 & 2.0722 \tabularnewline
108 & 10 & 12.7996 & -2.79962 \tabularnewline
109 & 10 & 9.13392 & 0.866082 \tabularnewline
110 & 15 & 13.9141 & 1.08594 \tabularnewline
111 & 11 & 13.245 & -2.24502 \tabularnewline
112 & 13 & 15.2666 & -2.26663 \tabularnewline
113 & 14 & 11.9234 & 2.07656 \tabularnewline
114 & 18 & 14.1242 & 3.87575 \tabularnewline
115 & 16 & 15.5714 & 0.428554 \tabularnewline
116 & 14 & 13.0423 & 0.95775 \tabularnewline
117 & 14 & 13.7867 & 0.213323 \tabularnewline
118 & 14 & 15.1017 & -1.10172 \tabularnewline
119 & 14 & 13.7335 & 0.266498 \tabularnewline
120 & 12 & 12.5638 & -0.563777 \tabularnewline
121 & 14 & 13.6048 & 0.395188 \tabularnewline
122 & 15 & 14.945 & 0.0550266 \tabularnewline
123 & 15 & 15.9496 & -0.949585 \tabularnewline
124 & 15 & 14.6165 & 0.383465 \tabularnewline
125 & 13 & 14.8256 & -1.82563 \tabularnewline
126 & 17 & 16.1573 & 0.842715 \tabularnewline
127 & 17 & 15.2678 & 1.73224 \tabularnewline
128 & 19 & 14.9092 & 4.09083 \tabularnewline
129 & 15 & 13.6309 & 1.36914 \tabularnewline
130 & 13 & 14.6252 & -1.62516 \tabularnewline
131 & 9 & 10.7233 & -1.72328 \tabularnewline
132 & 15 & 15.2253 & -0.225273 \tabularnewline
133 & 15 & 12.6621 & 2.33793 \tabularnewline
134 & 15 & 14.2844 & 0.715602 \tabularnewline
135 & 16 & 13.8009 & 2.19906 \tabularnewline
136 & 11 & 9.46701 & 1.53299 \tabularnewline
137 & 14 & 13.3545 & 0.645472 \tabularnewline
138 & 11 & 12.032 & -1.03202 \tabularnewline
139 & 15 & 14.1795 & 0.82048 \tabularnewline
140 & 13 & 13.8237 & -0.823691 \tabularnewline
141 & 15 & 14.5893 & 0.410742 \tabularnewline
142 & 16 & 13.8343 & 2.16567 \tabularnewline
143 & 14 & 14.7653 & -0.765308 \tabularnewline
144 & 15 & 14.3039 & 0.696101 \tabularnewline
145 & 16 & 14.6354 & 1.36464 \tabularnewline
146 & 16 & 14.5149 & 1.48513 \tabularnewline
147 & 11 & 13.4656 & -2.46559 \tabularnewline
148 & 12 & 14.7282 & -2.72819 \tabularnewline
149 & 9 & 11.5662 & -2.56616 \tabularnewline
150 & 16 & 14.2568 & 1.74323 \tabularnewline
151 & 13 & 12.6544 & 0.345609 \tabularnewline
152 & 16 & 15.4013 & 0.598723 \tabularnewline
153 & 12 & 14.3875 & -2.38747 \tabularnewline
154 & 9 & 11.8851 & -2.88511 \tabularnewline
155 & 13 & 11.8215 & 1.17846 \tabularnewline
156 & 13 & 12.8481 & 0.151941 \tabularnewline
157 & 14 & 13.3166 & 0.683431 \tabularnewline
158 & 19 & 14.9092 & 4.09083 \tabularnewline
159 & 13 & 15.6961 & -2.69614 \tabularnewline
160 & 12 & 12.1395 & -0.139512 \tabularnewline
161 & 13 & 12.6325 & 0.367525 \tabularnewline
162 & 10 & 9.17636 & 0.82364 \tabularnewline
163 & 14 & 13.0508 & 0.949172 \tabularnewline
164 & 16 & 11.4469 & 4.5531 \tabularnewline
165 & 10 & 11.7925 & -1.79246 \tabularnewline
166 & 11 & 8.98111 & 2.01889 \tabularnewline
167 & 14 & 13.9813 & 0.0186947 \tabularnewline
168 & 12 & 12.778 & -0.778002 \tabularnewline
169 & 9 & 12.6127 & -3.61275 \tabularnewline
170 & 9 & 11.8073 & -2.80728 \tabularnewline
171 & 11 & 10.3342 & 0.665807 \tabularnewline
172 & 16 & 14.0576 & 1.94243 \tabularnewline
173 & 9 & 13.8728 & -4.87285 \tabularnewline
174 & 13 & 11.1586 & 1.84145 \tabularnewline
175 & 16 & 13.2677 & 2.73225 \tabularnewline
176 & 13 & 15.124 & -2.12397 \tabularnewline
177 & 9 & 12.1569 & -3.15693 \tabularnewline
178 & 12 & 11.3518 & 0.648206 \tabularnewline
179 & 16 & 14.4072 & 1.59276 \tabularnewline
180 & 11 & 13.0143 & -2.01435 \tabularnewline
181 & 14 & 13.9531 & 0.0469324 \tabularnewline
182 & 13 & 14.5323 & -1.53226 \tabularnewline
183 & 15 & 14.6011 & 0.398943 \tabularnewline
184 & 14 & 14.8462 & -0.846173 \tabularnewline
185 & 16 & 14.0484 & 1.95157 \tabularnewline
186 & 13 & 11.5482 & 1.45178 \tabularnewline
187 & 14 & 13.3958 & 0.604171 \tabularnewline
188 & 15 & 14.0408 & 0.959192 \tabularnewline
189 & 13 & 12.2851 & 0.714897 \tabularnewline
190 & 11 & 10.0951 & 0.904902 \tabularnewline
191 & 11 & 12.4534 & -1.45342 \tabularnewline
192 & 14 & 14.8751 & -0.875082 \tabularnewline
193 & 15 & 12.4997 & 2.50026 \tabularnewline
194 & 11 & 12.392 & -1.39201 \tabularnewline
195 & 15 & 13.0126 & 1.98736 \tabularnewline
196 & 12 & 13.9591 & -1.95911 \tabularnewline
197 & 14 & 11.6106 & 2.38937 \tabularnewline
198 & 14 & 13.332 & 0.668001 \tabularnewline
199 & 8 & 11.0242 & -3.02419 \tabularnewline
200 & 13 & 13.6757 & -0.675688 \tabularnewline
201 & 9 & 12.0875 & -3.08751 \tabularnewline
202 & 15 & 13.6555 & 1.34447 \tabularnewline
203 & 17 & 13.9559 & 3.04413 \tabularnewline
204 & 13 & 12.513 & 0.487008 \tabularnewline
205 & 15 & 14.2781 & 0.721887 \tabularnewline
206 & 15 & 13.6399 & 1.36006 \tabularnewline
207 & 14 & 14.4297 & -0.429671 \tabularnewline
208 & 16 & 12.4316 & 3.56836 \tabularnewline
209 & 13 & 12.8456 & 0.154411 \tabularnewline
210 & 16 & 14.2074 & 1.79258 \tabularnewline
211 & 9 & 11.6703 & -2.67026 \tabularnewline
212 & 16 & 14.5238 & 1.47615 \tabularnewline
213 & 11 & 12.1924 & -1.19245 \tabularnewline
214 & 10 & 13.7196 & -3.71955 \tabularnewline
215 & 11 & 12.0717 & -1.07168 \tabularnewline
216 & 15 & 13.2047 & 1.79534 \tabularnewline
217 & 17 & 14.7986 & 2.20142 \tabularnewline
218 & 14 & 14.1728 & -0.172824 \tabularnewline
219 & 8 & 9.85558 & -1.85558 \tabularnewline
220 & 15 & 13.5534 & 1.4466 \tabularnewline
221 & 11 & 13.8588 & -2.85883 \tabularnewline
222 & 16 & 13.469 & 2.531 \tabularnewline
223 & 10 & 12.0894 & -2.08942 \tabularnewline
224 & 15 & 14.7448 & 0.255243 \tabularnewline
225 & 9 & 9.47151 & -0.471508 \tabularnewline
226 & 16 & 14.2303 & 1.76975 \tabularnewline
227 & 19 & 13.7237 & 5.27625 \tabularnewline
228 & 12 & 13.5512 & -1.55122 \tabularnewline
229 & 8 & 9.46947 & -1.46947 \tabularnewline
230 & 11 & 13.2891 & -2.28912 \tabularnewline
231 & 14 & 13.6952 & 0.304842 \tabularnewline
232 & 9 & 12.0306 & -3.03063 \tabularnewline
233 & 15 & 14.7508 & 0.249236 \tabularnewline
234 & 13 & 12.4106 & 0.58943 \tabularnewline
235 & 16 & 14.8395 & 1.16055 \tabularnewline
236 & 11 & 12.8083 & -1.80828 \tabularnewline
237 & 12 & 11.3421 & 0.657887 \tabularnewline
238 & 13 & 12.8168 & 0.183211 \tabularnewline
239 & 10 & 14.3091 & -4.30914 \tabularnewline
240 & 11 & 13.4946 & -2.49457 \tabularnewline
241 & 12 & 14.7582 & -2.7582 \tabularnewline
242 & 8 & 10.7011 & -2.70115 \tabularnewline
243 & 12 & 11.6166 & 0.383444 \tabularnewline
244 & 12 & 12.1521 & -0.152113 \tabularnewline
245 & 15 & 13.4844 & 1.51563 \tabularnewline
246 & 11 & 10.6907 & 0.309282 \tabularnewline
247 & 13 & 12.6842 & 0.31578 \tabularnewline
248 & 14 & 8.83358 & 5.16642 \tabularnewline
249 & 10 & 10.1916 & -0.191643 \tabularnewline
250 & 12 & 11.5044 & 0.49563 \tabularnewline
251 & 15 & 12.8046 & 2.19544 \tabularnewline
252 & 13 & 11.8234 & 1.17657 \tabularnewline
253 & 13 & 14.0453 & -1.04529 \tabularnewline
254 & 13 & 13.6407 & -0.640719 \tabularnewline
255 & 12 & 11.8085 & 0.191522 \tabularnewline
256 & 12 & 12.6547 & -0.654664 \tabularnewline
257 & 9 & 10.8138 & -1.81381 \tabularnewline
258 & 9 & 11.4136 & -2.41356 \tabularnewline
259 & 15 & 12.5668 & 2.4332 \tabularnewline
260 & 10 & 14.7492 & -4.74919 \tabularnewline
261 & 14 & 13.6393 & 0.360714 \tabularnewline
262 & 15 & 13.5417 & 1.45828 \tabularnewline
263 & 7 & 9.78241 & -2.78241 \tabularnewline
264 & 14 & 13.7933 & 0.206696 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226550&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]14[/C][C]13.9813[/C][C]0.0186593[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.2866[/C][C]2.71335[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]14.0242[/C][C]-3.02417[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.408[/C][C]-2.408[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]11.332[/C][C]4.66797[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.4862[/C][C]3.51381[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.8247[/C][C]3.17534[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]15.1488[/C][C]-1.14882[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.271[/C][C]-0.271022[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.3619[/C][C]0.638056[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.54[/C][C]1.45998[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.646[/C][C]3.35398[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.4665[/C][C]-3.46655[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.5216[/C][C]2.47838[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.856[/C][C]2.14402[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.4642[/C][C]0.535834[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.8811[/C][C]0.118909[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.8014[/C][C]1.1986[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.422[/C][C]-1.42197[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.8822[/C][C]2.11776[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.3869[/C][C]2.61307[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.8019[/C][C]-2.8019[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.4938[/C][C]-0.493793[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.6169[/C][C]-1.61691[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.4318[/C][C]1.56818[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.9952[/C][C]-6.99519[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.0726[/C][C]0.927416[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.4479[/C][C]0.55213[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]14.0091[/C][C]0.99089[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]14.0213[/C][C]-3.0213[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.8077[/C][C]0.192337[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.7128[/C][C]0.287209[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]15.1524[/C][C]1.84761[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.3819[/C][C]-0.381873[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14.0706[/C][C]-0.0705913[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.5686[/C][C]0.431385[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.9348[/C][C]-1.9348[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.4429[/C][C]0.557064[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.407[/C][C]1.59301[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.2817[/C][C]-2.2817[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.7691[/C][C]-0.769075[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.7866[/C][C]2.21336[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.9592[/C][C]0.0408427[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.223[/C][C]-1.223[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.7125[/C][C]0.287499[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.767[/C][C]-2.767[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.5122[/C][C]-0.512199[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.9962[/C][C]0.00378661[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.6039[/C][C]3.39611[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.899[/C][C]-1.89901[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.4027[/C][C]0.597299[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.5551[/C][C]0.444917[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.8605[/C][C]-0.860519[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.8261[/C][C]-1.82606[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.1347[/C][C]-2.1347[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.7017[/C][C]1.29834[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.3454[/C][C]1.65457[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.598[/C][C]-0.598048[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.3216[/C][C]-3.32162[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.506[/C][C]-1.50596[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.8322[/C][C]-2.83217[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.7531[/C][C]-1.75306[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.8406[/C][C]-3.8406[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.2277[/C][C]0.772271[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.786[/C][C]1.214[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.0154[/C][C]-5.01542[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.5657[/C][C]-1.56566[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.3668[/C][C]-2.36677[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.4896[/C][C]1.51037[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.5594[/C][C]1.44062[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.4332[/C][C]0.566771[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.6478[/C][C]3.35221[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.3886[/C][C]0.611449[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.2041[/C][C]-0.204143[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.8984[/C][C]-1.89838[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.0464[/C][C]-0.0463606[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]13.963[/C][C]3.037[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.4281[/C][C]0.571907[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.786[/C][C]1.21398[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]14.8972[/C][C]-1.89715[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.8524[/C][C]0.147636[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.4552[/C][C]-0.455247[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.2491[/C][C]1.75094[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2374[/C][C]0.762576[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.0527[/C][C]-0.0527058[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.9371[/C][C]1.06286[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.2447[/C][C]-0.244715[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.736[/C][C]0.264043[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.5471[/C][C]-3.54708[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.6931[/C][C]3.30688[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.8481[/C][C]0.151941[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.1569[/C][C]0.843071[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.302[/C][C]0.697969[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.0095[/C][C]-1.00947[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.9098[/C][C]1.09024[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.8339[/C][C]-0.833874[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.7896[/C][C]-0.7896[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.9102[/C][C]2.08979[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]15[/C][C]1.31151e-05[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.1742[/C][C]1.82579[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.9287[/C][C]-0.928698[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]15.0272[/C][C]0.972807[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.4076[/C][C]-3.40757[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.0826[/C][C]1.91737[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.4315[/C][C]-2.43146[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.9115[/C][C]1.08849[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9278[/C][C]2.0722[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.7996[/C][C]-2.79962[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.13392[/C][C]0.866082[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.9141[/C][C]1.08594[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.245[/C][C]-2.24502[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.2666[/C][C]-2.26663[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]11.9234[/C][C]2.07656[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.1242[/C][C]3.87575[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.5714[/C][C]0.428554[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.0423[/C][C]0.95775[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.7867[/C][C]0.213323[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.1017[/C][C]-1.10172[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.7335[/C][C]0.266498[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.5638[/C][C]-0.563777[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.6048[/C][C]0.395188[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.945[/C][C]0.0550266[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.9496[/C][C]-0.949585[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.6165[/C][C]0.383465[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.8256[/C][C]-1.82563[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.1573[/C][C]0.842715[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.2678[/C][C]1.73224[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.9092[/C][C]4.09083[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.6309[/C][C]1.36914[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.6252[/C][C]-1.62516[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.7233[/C][C]-1.72328[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.2253[/C][C]-0.225273[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.6621[/C][C]2.33793[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.2844[/C][C]0.715602[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.8009[/C][C]2.19906[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.46701[/C][C]1.53299[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.3545[/C][C]0.645472[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]12.032[/C][C]-1.03202[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.1795[/C][C]0.82048[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.8237[/C][C]-0.823691[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.5893[/C][C]0.410742[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.8343[/C][C]2.16567[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.7653[/C][C]-0.765308[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.3039[/C][C]0.696101[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.6354[/C][C]1.36464[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.5149[/C][C]1.48513[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.4656[/C][C]-2.46559[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.7282[/C][C]-2.72819[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.5662[/C][C]-2.56616[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.2568[/C][C]1.74323[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.6544[/C][C]0.345609[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.4013[/C][C]0.598723[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.3875[/C][C]-2.38747[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.8851[/C][C]-2.88511[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.8215[/C][C]1.17846[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.8481[/C][C]0.151941[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.3166[/C][C]0.683431[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.9092[/C][C]4.09083[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.6961[/C][C]-2.69614[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.1395[/C][C]-0.139512[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6325[/C][C]0.367525[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.17636[/C][C]0.82364[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.0508[/C][C]0.949172[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.4469[/C][C]4.5531[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.7925[/C][C]-1.79246[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]8.98111[/C][C]2.01889[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]13.9813[/C][C]0.0186947[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.778[/C][C]-0.778002[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.6127[/C][C]-3.61275[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.8073[/C][C]-2.80728[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.3342[/C][C]0.665807[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.0576[/C][C]1.94243[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]13.8728[/C][C]-4.87285[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.1586[/C][C]1.84145[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.2677[/C][C]2.73225[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.124[/C][C]-2.12397[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.1569[/C][C]-3.15693[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.3518[/C][C]0.648206[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.4072[/C][C]1.59276[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.0143[/C][C]-2.01435[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]13.9531[/C][C]0.0469324[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.5323[/C][C]-1.53226[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.6011[/C][C]0.398943[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.8462[/C][C]-0.846173[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]14.0484[/C][C]1.95157[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.5482[/C][C]1.45178[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.3958[/C][C]0.604171[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.0408[/C][C]0.959192[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.2851[/C][C]0.714897[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.0951[/C][C]0.904902[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.4534[/C][C]-1.45342[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.8751[/C][C]-0.875082[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.4997[/C][C]2.50026[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.392[/C][C]-1.39201[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.0126[/C][C]1.98736[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]13.9591[/C][C]-1.95911[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.6106[/C][C]2.38937[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.332[/C][C]0.668001[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.0242[/C][C]-3.02419[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.6757[/C][C]-0.675688[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.0875[/C][C]-3.08751[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.6555[/C][C]1.34447[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]13.9559[/C][C]3.04413[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.513[/C][C]0.487008[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.2781[/C][C]0.721887[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.6399[/C][C]1.36006[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.4297[/C][C]-0.429671[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.4316[/C][C]3.56836[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.8456[/C][C]0.154411[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.2074[/C][C]1.79258[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.6703[/C][C]-2.67026[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.5238[/C][C]1.47615[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.1924[/C][C]-1.19245[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.7196[/C][C]-3.71955[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.0717[/C][C]-1.07168[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.2047[/C][C]1.79534[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.7986[/C][C]2.20142[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.1728[/C][C]-0.172824[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.85558[/C][C]-1.85558[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.5534[/C][C]1.4466[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.8588[/C][C]-2.85883[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.469[/C][C]2.531[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.0894[/C][C]-2.08942[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.7448[/C][C]0.255243[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.47151[/C][C]-0.471508[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.2303[/C][C]1.76975[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]13.7237[/C][C]5.27625[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.5512[/C][C]-1.55122[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.46947[/C][C]-1.46947[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.2891[/C][C]-2.28912[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.6952[/C][C]0.304842[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]12.0306[/C][C]-3.03063[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]14.7508[/C][C]0.249236[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.4106[/C][C]0.58943[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]14.8395[/C][C]1.16055[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.8083[/C][C]-1.80828[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.3421[/C][C]0.657887[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]12.8168[/C][C]0.183211[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.3091[/C][C]-4.30914[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.4946[/C][C]-2.49457[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.7582[/C][C]-2.7582[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.7011[/C][C]-2.70115[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.6166[/C][C]0.383444[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.1521[/C][C]-0.152113[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.4844[/C][C]1.51563[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.6907[/C][C]0.309282[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.6842[/C][C]0.31578[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.83358[/C][C]5.16642[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.1916[/C][C]-0.191643[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5044[/C][C]0.49563[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.8046[/C][C]2.19544[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.8234[/C][C]1.17657[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.0453[/C][C]-1.04529[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.6407[/C][C]-0.640719[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.8085[/C][C]0.191522[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.6547[/C][C]-0.654664[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.8138[/C][C]-1.81381[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.4136[/C][C]-2.41356[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.5668[/C][C]2.4332[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.7492[/C][C]-4.74919[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.6393[/C][C]0.360714[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.5417[/C][C]1.45828[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.78241[/C][C]-2.78241[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.7933[/C][C]0.206696[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226550&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226550&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
11413.98130.0186593
21815.28662.71335
31114.0242-3.02417
41214.408-2.408
51611.3324.66797
61814.48623.51381
71410.82473.17534
81415.1488-1.14882
91515.271-0.271022
101514.36190.638056
111715.541.45998
121915.6463.35398
131013.4665-3.46655
141613.52162.47838
151815.8562.14402
161413.46420.535834
171413.88110.118909
181715.80141.1986
191415.422-1.42197
201613.88222.11776
211815.38692.61307
221113.8019-2.8019
231414.4938-0.493793
241213.6169-1.61691
251715.43181.56818
26915.9952-6.99519
271615.07260.927416
281413.44790.55213
291514.00910.99089
301114.0213-3.0213
311615.80770.192337
321312.71280.287209
331715.15241.84761
341515.3819-0.381873
351414.0706-0.0705913
361615.56860.431385
37910.9348-1.9348
381514.44290.557064
391715.4071.59301
401315.2817-2.2817
411515.7691-0.769075
421613.78662.21336
431615.95920.0408427
441213.223-1.223
451514.71250.287499
461113.767-2.767
471515.5122-0.512199
481514.99620.00378661
491713.60393.39611
501314.899-1.89901
511615.40270.597299
521413.55510.444917
531111.8605-0.860519
541213.8261-1.82606
551214.1347-2.1347
561513.70171.29834
571614.34541.65457
581515.598-0.598048
591215.3216-3.32162
601213.506-1.50596
61810.8322-2.83217
621314.7531-1.75306
631114.8406-3.8406
641413.22770.772271
651513.7861.214
661015.0154-5.01542
671112.5657-1.56566
681214.3668-2.36677
691513.48961.51037
701513.55941.44062
711413.43320.566771
721612.64783.35221
731514.38860.611449
741515.2041-0.204143
751314.8984-1.89838
761212.0464-0.0463606
771713.9633.037
781312.42810.571907
791513.7861.21398
801314.8972-1.89715
811514.85240.147636
821515.4552-0.455247
831614.24911.75094
841514.23740.762576
851414.0527-0.0527058
861513.93711.06286
871414.2447-0.244715
881312.7360.264043
89710.5471-3.54708
901713.69313.30688
911312.84810.151941
921514.15690.843071
931413.3020.697969
941314.0095-1.00947
951614.90981.09024
961212.8339-0.833874
971414.7896-0.7896
981714.91022.08979
9915151.31151e-05
1001715.17421.82579
1011212.9287-0.928698
1021615.02720.972807
1031114.4076-3.40757
1041513.08261.91737
105911.4315-2.43146
1061614.91151.08849
1071512.92782.0722
1081012.7996-2.79962
109109.133920.866082
1101513.91411.08594
1111113.245-2.24502
1121315.2666-2.26663
1131411.92342.07656
1141814.12423.87575
1151615.57140.428554
1161413.04230.95775
1171413.78670.213323
1181415.1017-1.10172
1191413.73350.266498
1201212.5638-0.563777
1211413.60480.395188
1221514.9450.0550266
1231515.9496-0.949585
1241514.61650.383465
1251314.8256-1.82563
1261716.15730.842715
1271715.26781.73224
1281914.90924.09083
1291513.63091.36914
1301314.6252-1.62516
131910.7233-1.72328
1321515.2253-0.225273
1331512.66212.33793
1341514.28440.715602
1351613.80092.19906
136119.467011.53299
1371413.35450.645472
1381112.032-1.03202
1391514.17950.82048
1401313.8237-0.823691
1411514.58930.410742
1421613.83432.16567
1431414.7653-0.765308
1441514.30390.696101
1451614.63541.36464
1461614.51491.48513
1471113.4656-2.46559
1481214.7282-2.72819
149911.5662-2.56616
1501614.25681.74323
1511312.65440.345609
1521615.40130.598723
1531214.3875-2.38747
154911.8851-2.88511
1551311.82151.17846
1561312.84810.151941
1571413.31660.683431
1581914.90924.09083
1591315.6961-2.69614
1601212.1395-0.139512
1611312.63250.367525
162109.176360.82364
1631413.05080.949172
1641611.44694.5531
1651011.7925-1.79246
166118.981112.01889
1671413.98130.0186947
1681212.778-0.778002
169912.6127-3.61275
170911.8073-2.80728
1711110.33420.665807
1721614.05761.94243
173913.8728-4.87285
1741311.15861.84145
1751613.26772.73225
1761315.124-2.12397
177912.1569-3.15693
1781211.35180.648206
1791614.40721.59276
1801113.0143-2.01435
1811413.95310.0469324
1821314.5323-1.53226
1831514.60110.398943
1841414.8462-0.846173
1851614.04841.95157
1861311.54821.45178
1871413.39580.604171
1881514.04080.959192
1891312.28510.714897
1901110.09510.904902
1911112.4534-1.45342
1921414.8751-0.875082
1931512.49972.50026
1941112.392-1.39201
1951513.01261.98736
1961213.9591-1.95911
1971411.61062.38937
1981413.3320.668001
199811.0242-3.02419
2001313.6757-0.675688
201912.0875-3.08751
2021513.65551.34447
2031713.95593.04413
2041312.5130.487008
2051514.27810.721887
2061513.63991.36006
2071414.4297-0.429671
2081612.43163.56836
2091312.84560.154411
2101614.20741.79258
211911.6703-2.67026
2121614.52381.47615
2131112.1924-1.19245
2141013.7196-3.71955
2151112.0717-1.07168
2161513.20471.79534
2171714.79862.20142
2181414.1728-0.172824
21989.85558-1.85558
2201513.55341.4466
2211113.8588-2.85883
2221613.4692.531
2231012.0894-2.08942
2241514.74480.255243
22599.47151-0.471508
2261614.23031.76975
2271913.72375.27625
2281213.5512-1.55122
22989.46947-1.46947
2301113.2891-2.28912
2311413.69520.304842
232912.0306-3.03063
2331514.75080.249236
2341312.41060.58943
2351614.83951.16055
2361112.8083-1.80828
2371211.34210.657887
2381312.81680.183211
2391014.3091-4.30914
2401113.4946-2.49457
2411214.7582-2.7582
242810.7011-2.70115
2431211.61660.383444
2441212.1521-0.152113
2451513.48441.51563
2461110.69070.309282
2471312.68420.31578
248148.833585.16642
2491010.1916-0.191643
2501211.50440.49563
2511512.80462.19544
2521311.82341.17657
2531314.0453-1.04529
2541313.6407-0.640719
2551211.80850.191522
2561212.6547-0.654664
257910.8138-1.81381
258911.4136-2.41356
2591512.56682.4332
2601014.7492-4.74919
2611413.63930.360714
2621513.54171.45828
26379.78241-2.78241
2641413.79330.206696






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.02798450.05596890.972016
120.7167330.5665350.283267
130.9662860.06742790.033714
140.9413320.1173350.0586676
150.9482890.1034210.0517105
160.9227610.1544780.0772392
170.9599850.08002970.0400148
180.9392740.1214520.0607258
190.9118780.1762430.0881216
200.9126220.1747550.0873776
210.9318470.1363050.0681527
220.928510.142980.0714899
230.9260180.1479630.0739817
240.8995910.2008170.100409
250.876080.2478390.12392
260.9989420.002115490.00105775
270.9983280.003343590.00167179
280.9973490.00530190.00265095
290.9959340.008131890.00406595
300.9972350.00552980.0027649
310.9958140.008372360.00418618
320.9940010.01199760.00599882
330.9927120.01457580.00728791
340.9894940.02101240.0105062
350.9870050.02598980.0129949
360.9819990.03600240.0180012
370.9878880.0242230.0121115
380.9832660.03346770.0167339
390.9807610.03847750.0192387
400.9812220.03755570.0187779
410.9755040.04899140.0244957
420.9727840.05443240.0272162
430.9643710.07125720.0356286
440.9584190.08316120.0415806
450.9465260.1069480.0534739
460.9560740.08785230.0439261
470.944150.1116990.0558496
480.9294780.1410440.0705221
490.9399820.1200370.0600184
500.937360.125280.06264
510.922960.1540810.0770403
520.9054350.1891290.0945645
530.8931750.2136490.106825
540.8779610.2440790.122039
550.8698390.2603230.130161
560.852870.294260.14713
570.8381430.3237140.161857
580.8102610.3794780.189739
590.8536870.2926260.146313
600.8492770.3014460.150723
610.8705280.2589440.129472
620.8717350.2565310.128265
630.9254320.1491360.0745681
640.9131780.1736450.0868223
650.9018390.1963230.0981614
660.9139920.1720160.0860082
670.9130140.1739710.0869856
680.9037970.1924060.0962028
690.9362520.1274960.0637478
700.9413520.1172950.0586476
710.9361110.1277770.0638887
720.957840.08432040.0421602
730.9488370.1023250.0511626
740.9376910.1246180.0623088
750.9307650.138470.069235
760.9166490.1667030.0833513
770.9329080.1341830.0670915
780.9207950.158410.0792048
790.9135090.1729820.0864911
800.9068720.1862560.093128
810.8896020.2207950.110398
820.8709670.2580650.129033
830.8649380.2701240.135062
840.8460850.307830.153915
850.8222930.3554140.177707
860.7996090.4007810.200391
870.772220.455560.22778
880.7426520.5146970.257348
890.8150950.3698090.184905
900.8486740.3026530.151326
910.8257590.3484820.174241
920.8027250.3945510.197275
930.7796510.4406990.220349
940.7580940.4838120.241906
950.7334580.5330850.266542
960.7098460.5803080.290154
970.6822240.6355510.317776
980.6798460.6403090.320154
990.6460860.7078270.353914
1000.6329540.7340910.367046
1010.6087030.7825950.391297
1020.5785380.8429240.421462
1030.6306160.7387680.369384
1040.6173050.7653890.382695
1050.6392560.7214880.360744
1060.6130180.7739640.386982
1070.6032670.7934670.396733
1080.6420740.7158530.357926
1090.6114030.7771940.388597
1100.5844880.8310250.415512
1110.5963260.8073490.403674
1120.6195360.7609270.380464
1130.6071150.7857710.392885
1140.6933750.6132490.306625
1150.6634720.6730570.336528
1160.6358020.7283970.364198
1170.6018610.7962790.398139
1180.5786710.8426570.421329
1190.5436870.9126260.456313
1200.5121630.9756750.487837
1210.4824760.9649520.517524
1220.4499320.8998650.550068
1230.424440.8488810.57556
1240.3920620.7841240.607938
1250.387160.7743210.61284
1260.3582450.716490.641755
1270.3430190.6860370.656981
1280.4533670.9067330.546633
1290.4327270.8654540.567273
1300.420480.8409590.57952
1310.4111040.8222080.588896
1320.3791380.7582770.620862
1330.3951020.7902050.604898
1340.3654280.7308570.634572
1350.3734790.7469590.626521
1360.3631950.726390.636805
1370.3333170.6666350.666683
1380.3101530.6203060.689847
1390.2839110.5678220.716089
1400.2600630.5201250.739937
1410.2334490.4668990.766551
1420.2402380.4804760.759762
1430.2162390.4324780.783761
1440.195440.390880.80456
1450.1830810.3661630.816919
1460.1751370.3502740.824863
1470.1855470.3710940.814453
1480.2036220.4072450.796378
1490.2218890.4437770.778111
1500.2194580.4389150.780542
1510.1978510.3957010.802149
1520.1775350.3550690.822465
1530.1849150.3698310.815085
1540.219620.439240.78038
1550.1981170.3962340.801883
1560.1775190.3550370.822481
1570.1553110.3106220.844689
1580.2286550.457310.771345
1590.2541660.5083320.745834
1600.2277830.4555650.772217
1610.200960.401920.79904
1620.1781370.3562730.821863
1630.157850.3157010.84215
1640.2634260.5268510.736574
1650.2596860.5193710.740314
1660.2557450.511490.744255
1670.2275090.4550190.772491
1680.2060710.4121430.793929
1690.2629610.5259220.737039
1700.2853590.5707180.714641
1710.2571660.5143310.742834
1720.253870.5077390.74613
1730.4104940.8209890.589506
1740.3998320.7996640.600168
1750.4263460.8526910.573654
1760.4320360.8640710.567964
1770.4831640.9663280.516836
1780.4501960.9003920.549804
1790.430810.861620.56919
1800.426680.8533610.57332
1810.3894510.7789030.610549
1820.3779850.7559710.622015
1830.341970.683940.65803
1840.3140890.6281780.685911
1850.3223610.6447230.677639
1860.314190.628380.68581
1870.2821520.5643040.717848
1880.2585140.5170280.741486
1890.2298980.4597960.770102
1900.2116220.4232430.788378
1910.216960.4339210.78304
1920.1982720.3965440.801728
1930.2170890.4341780.782911
1940.2037930.4075870.796207
1950.2055740.4111490.794426
1960.2133810.4267620.786619
1970.2570890.5141790.742911
1980.2408890.4817780.759111
1990.2717950.5435910.728205
2000.2388580.4777170.761142
2010.2683980.5367950.731602
2020.2511380.5022750.748862
2030.3179340.6358680.682066
2040.2823120.5646240.717688
2050.2491030.4982050.750897
2060.2298660.4597320.770134
2070.1984690.3969380.801531
2080.2218840.4437690.778116
2090.1907340.3814670.809266
2100.2082630.4165260.791737
2110.22910.4582010.7709
2120.2176340.4352670.782366
2130.1903750.3807510.809625
2140.2374270.4748540.762573
2150.2095950.419190.790405
2160.1986990.3973970.801301
2170.2326230.4652470.767377
2180.2020430.4040870.797957
2190.1878640.3757290.812136
2200.195910.391820.80409
2210.2016560.4033110.798344
2220.2052340.4104680.794766
2230.1875040.3750070.812496
2240.156780.313560.84322
2250.1414170.2828350.858583
2260.1701710.3403410.829829
2270.366060.732120.63394
2280.3413310.6826610.658669
2290.3141320.6282650.685868
2300.2973030.5946060.702697
2310.2537780.5075560.746222
2320.2821530.5643070.717847
2330.2336570.4673130.766343
2340.1967380.3934760.803262
2350.1987610.3975230.801239
2360.1704580.3409170.829542
2370.148370.296740.85163
2380.1138640.2277270.886136
2390.205320.410640.79468
2400.196550.3930990.80345
2410.1647750.3295490.835225
2420.2834350.566870.716565
2430.2217890.4435790.778211
2440.1711630.3423270.828837
2450.3412890.6825780.658711
2460.2637560.5275110.736244
2470.1950370.3900740.804963
2480.3029280.6058550.697072
2490.2305830.4611670.769417
2500.1556290.3112590.844371
2510.1548510.3097020.845149
2520.4840370.9680750.515963
2530.5504630.8990730.449537

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.0279845 & 0.0559689 & 0.972016 \tabularnewline
12 & 0.716733 & 0.566535 & 0.283267 \tabularnewline
13 & 0.966286 & 0.0674279 & 0.033714 \tabularnewline
14 & 0.941332 & 0.117335 & 0.0586676 \tabularnewline
15 & 0.948289 & 0.103421 & 0.0517105 \tabularnewline
16 & 0.922761 & 0.154478 & 0.0772392 \tabularnewline
17 & 0.959985 & 0.0800297 & 0.0400148 \tabularnewline
18 & 0.939274 & 0.121452 & 0.0607258 \tabularnewline
19 & 0.911878 & 0.176243 & 0.0881216 \tabularnewline
20 & 0.912622 & 0.174755 & 0.0873776 \tabularnewline
21 & 0.931847 & 0.136305 & 0.0681527 \tabularnewline
22 & 0.92851 & 0.14298 & 0.0714899 \tabularnewline
23 & 0.926018 & 0.147963 & 0.0739817 \tabularnewline
24 & 0.899591 & 0.200817 & 0.100409 \tabularnewline
25 & 0.87608 & 0.247839 & 0.12392 \tabularnewline
26 & 0.998942 & 0.00211549 & 0.00105775 \tabularnewline
27 & 0.998328 & 0.00334359 & 0.00167179 \tabularnewline
28 & 0.997349 & 0.0053019 & 0.00265095 \tabularnewline
29 & 0.995934 & 0.00813189 & 0.00406595 \tabularnewline
30 & 0.997235 & 0.0055298 & 0.0027649 \tabularnewline
31 & 0.995814 & 0.00837236 & 0.00418618 \tabularnewline
32 & 0.994001 & 0.0119976 & 0.00599882 \tabularnewline
33 & 0.992712 & 0.0145758 & 0.00728791 \tabularnewline
34 & 0.989494 & 0.0210124 & 0.0105062 \tabularnewline
35 & 0.987005 & 0.0259898 & 0.0129949 \tabularnewline
36 & 0.981999 & 0.0360024 & 0.0180012 \tabularnewline
37 & 0.987888 & 0.024223 & 0.0121115 \tabularnewline
38 & 0.983266 & 0.0334677 & 0.0167339 \tabularnewline
39 & 0.980761 & 0.0384775 & 0.0192387 \tabularnewline
40 & 0.981222 & 0.0375557 & 0.0187779 \tabularnewline
41 & 0.975504 & 0.0489914 & 0.0244957 \tabularnewline
42 & 0.972784 & 0.0544324 & 0.0272162 \tabularnewline
43 & 0.964371 & 0.0712572 & 0.0356286 \tabularnewline
44 & 0.958419 & 0.0831612 & 0.0415806 \tabularnewline
45 & 0.946526 & 0.106948 & 0.0534739 \tabularnewline
46 & 0.956074 & 0.0878523 & 0.0439261 \tabularnewline
47 & 0.94415 & 0.111699 & 0.0558496 \tabularnewline
48 & 0.929478 & 0.141044 & 0.0705221 \tabularnewline
49 & 0.939982 & 0.120037 & 0.0600184 \tabularnewline
50 & 0.93736 & 0.12528 & 0.06264 \tabularnewline
51 & 0.92296 & 0.154081 & 0.0770403 \tabularnewline
52 & 0.905435 & 0.189129 & 0.0945645 \tabularnewline
53 & 0.893175 & 0.213649 & 0.106825 \tabularnewline
54 & 0.877961 & 0.244079 & 0.122039 \tabularnewline
55 & 0.869839 & 0.260323 & 0.130161 \tabularnewline
56 & 0.85287 & 0.29426 & 0.14713 \tabularnewline
57 & 0.838143 & 0.323714 & 0.161857 \tabularnewline
58 & 0.810261 & 0.379478 & 0.189739 \tabularnewline
59 & 0.853687 & 0.292626 & 0.146313 \tabularnewline
60 & 0.849277 & 0.301446 & 0.150723 \tabularnewline
61 & 0.870528 & 0.258944 & 0.129472 \tabularnewline
62 & 0.871735 & 0.256531 & 0.128265 \tabularnewline
63 & 0.925432 & 0.149136 & 0.0745681 \tabularnewline
64 & 0.913178 & 0.173645 & 0.0868223 \tabularnewline
65 & 0.901839 & 0.196323 & 0.0981614 \tabularnewline
66 & 0.913992 & 0.172016 & 0.0860082 \tabularnewline
67 & 0.913014 & 0.173971 & 0.0869856 \tabularnewline
68 & 0.903797 & 0.192406 & 0.0962028 \tabularnewline
69 & 0.936252 & 0.127496 & 0.0637478 \tabularnewline
70 & 0.941352 & 0.117295 & 0.0586476 \tabularnewline
71 & 0.936111 & 0.127777 & 0.0638887 \tabularnewline
72 & 0.95784 & 0.0843204 & 0.0421602 \tabularnewline
73 & 0.948837 & 0.102325 & 0.0511626 \tabularnewline
74 & 0.937691 & 0.124618 & 0.0623088 \tabularnewline
75 & 0.930765 & 0.13847 & 0.069235 \tabularnewline
76 & 0.916649 & 0.166703 & 0.0833513 \tabularnewline
77 & 0.932908 & 0.134183 & 0.0670915 \tabularnewline
78 & 0.920795 & 0.15841 & 0.0792048 \tabularnewline
79 & 0.913509 & 0.172982 & 0.0864911 \tabularnewline
80 & 0.906872 & 0.186256 & 0.093128 \tabularnewline
81 & 0.889602 & 0.220795 & 0.110398 \tabularnewline
82 & 0.870967 & 0.258065 & 0.129033 \tabularnewline
83 & 0.864938 & 0.270124 & 0.135062 \tabularnewline
84 & 0.846085 & 0.30783 & 0.153915 \tabularnewline
85 & 0.822293 & 0.355414 & 0.177707 \tabularnewline
86 & 0.799609 & 0.400781 & 0.200391 \tabularnewline
87 & 0.77222 & 0.45556 & 0.22778 \tabularnewline
88 & 0.742652 & 0.514697 & 0.257348 \tabularnewline
89 & 0.815095 & 0.369809 & 0.184905 \tabularnewline
90 & 0.848674 & 0.302653 & 0.151326 \tabularnewline
91 & 0.825759 & 0.348482 & 0.174241 \tabularnewline
92 & 0.802725 & 0.394551 & 0.197275 \tabularnewline
93 & 0.779651 & 0.440699 & 0.220349 \tabularnewline
94 & 0.758094 & 0.483812 & 0.241906 \tabularnewline
95 & 0.733458 & 0.533085 & 0.266542 \tabularnewline
96 & 0.709846 & 0.580308 & 0.290154 \tabularnewline
97 & 0.682224 & 0.635551 & 0.317776 \tabularnewline
98 & 0.679846 & 0.640309 & 0.320154 \tabularnewline
99 & 0.646086 & 0.707827 & 0.353914 \tabularnewline
100 & 0.632954 & 0.734091 & 0.367046 \tabularnewline
101 & 0.608703 & 0.782595 & 0.391297 \tabularnewline
102 & 0.578538 & 0.842924 & 0.421462 \tabularnewline
103 & 0.630616 & 0.738768 & 0.369384 \tabularnewline
104 & 0.617305 & 0.765389 & 0.382695 \tabularnewline
105 & 0.639256 & 0.721488 & 0.360744 \tabularnewline
106 & 0.613018 & 0.773964 & 0.386982 \tabularnewline
107 & 0.603267 & 0.793467 & 0.396733 \tabularnewline
108 & 0.642074 & 0.715853 & 0.357926 \tabularnewline
109 & 0.611403 & 0.777194 & 0.388597 \tabularnewline
110 & 0.584488 & 0.831025 & 0.415512 \tabularnewline
111 & 0.596326 & 0.807349 & 0.403674 \tabularnewline
112 & 0.619536 & 0.760927 & 0.380464 \tabularnewline
113 & 0.607115 & 0.785771 & 0.392885 \tabularnewline
114 & 0.693375 & 0.613249 & 0.306625 \tabularnewline
115 & 0.663472 & 0.673057 & 0.336528 \tabularnewline
116 & 0.635802 & 0.728397 & 0.364198 \tabularnewline
117 & 0.601861 & 0.796279 & 0.398139 \tabularnewline
118 & 0.578671 & 0.842657 & 0.421329 \tabularnewline
119 & 0.543687 & 0.912626 & 0.456313 \tabularnewline
120 & 0.512163 & 0.975675 & 0.487837 \tabularnewline
121 & 0.482476 & 0.964952 & 0.517524 \tabularnewline
122 & 0.449932 & 0.899865 & 0.550068 \tabularnewline
123 & 0.42444 & 0.848881 & 0.57556 \tabularnewline
124 & 0.392062 & 0.784124 & 0.607938 \tabularnewline
125 & 0.38716 & 0.774321 & 0.61284 \tabularnewline
126 & 0.358245 & 0.71649 & 0.641755 \tabularnewline
127 & 0.343019 & 0.686037 & 0.656981 \tabularnewline
128 & 0.453367 & 0.906733 & 0.546633 \tabularnewline
129 & 0.432727 & 0.865454 & 0.567273 \tabularnewline
130 & 0.42048 & 0.840959 & 0.57952 \tabularnewline
131 & 0.411104 & 0.822208 & 0.588896 \tabularnewline
132 & 0.379138 & 0.758277 & 0.620862 \tabularnewline
133 & 0.395102 & 0.790205 & 0.604898 \tabularnewline
134 & 0.365428 & 0.730857 & 0.634572 \tabularnewline
135 & 0.373479 & 0.746959 & 0.626521 \tabularnewline
136 & 0.363195 & 0.72639 & 0.636805 \tabularnewline
137 & 0.333317 & 0.666635 & 0.666683 \tabularnewline
138 & 0.310153 & 0.620306 & 0.689847 \tabularnewline
139 & 0.283911 & 0.567822 & 0.716089 \tabularnewline
140 & 0.260063 & 0.520125 & 0.739937 \tabularnewline
141 & 0.233449 & 0.466899 & 0.766551 \tabularnewline
142 & 0.240238 & 0.480476 & 0.759762 \tabularnewline
143 & 0.216239 & 0.432478 & 0.783761 \tabularnewline
144 & 0.19544 & 0.39088 & 0.80456 \tabularnewline
145 & 0.183081 & 0.366163 & 0.816919 \tabularnewline
146 & 0.175137 & 0.350274 & 0.824863 \tabularnewline
147 & 0.185547 & 0.371094 & 0.814453 \tabularnewline
148 & 0.203622 & 0.407245 & 0.796378 \tabularnewline
149 & 0.221889 & 0.443777 & 0.778111 \tabularnewline
150 & 0.219458 & 0.438915 & 0.780542 \tabularnewline
151 & 0.197851 & 0.395701 & 0.802149 \tabularnewline
152 & 0.177535 & 0.355069 & 0.822465 \tabularnewline
153 & 0.184915 & 0.369831 & 0.815085 \tabularnewline
154 & 0.21962 & 0.43924 & 0.78038 \tabularnewline
155 & 0.198117 & 0.396234 & 0.801883 \tabularnewline
156 & 0.177519 & 0.355037 & 0.822481 \tabularnewline
157 & 0.155311 & 0.310622 & 0.844689 \tabularnewline
158 & 0.228655 & 0.45731 & 0.771345 \tabularnewline
159 & 0.254166 & 0.508332 & 0.745834 \tabularnewline
160 & 0.227783 & 0.455565 & 0.772217 \tabularnewline
161 & 0.20096 & 0.40192 & 0.79904 \tabularnewline
162 & 0.178137 & 0.356273 & 0.821863 \tabularnewline
163 & 0.15785 & 0.315701 & 0.84215 \tabularnewline
164 & 0.263426 & 0.526851 & 0.736574 \tabularnewline
165 & 0.259686 & 0.519371 & 0.740314 \tabularnewline
166 & 0.255745 & 0.51149 & 0.744255 \tabularnewline
167 & 0.227509 & 0.455019 & 0.772491 \tabularnewline
168 & 0.206071 & 0.412143 & 0.793929 \tabularnewline
169 & 0.262961 & 0.525922 & 0.737039 \tabularnewline
170 & 0.285359 & 0.570718 & 0.714641 \tabularnewline
171 & 0.257166 & 0.514331 & 0.742834 \tabularnewline
172 & 0.25387 & 0.507739 & 0.74613 \tabularnewline
173 & 0.410494 & 0.820989 & 0.589506 \tabularnewline
174 & 0.399832 & 0.799664 & 0.600168 \tabularnewline
175 & 0.426346 & 0.852691 & 0.573654 \tabularnewline
176 & 0.432036 & 0.864071 & 0.567964 \tabularnewline
177 & 0.483164 & 0.966328 & 0.516836 \tabularnewline
178 & 0.450196 & 0.900392 & 0.549804 \tabularnewline
179 & 0.43081 & 0.86162 & 0.56919 \tabularnewline
180 & 0.42668 & 0.853361 & 0.57332 \tabularnewline
181 & 0.389451 & 0.778903 & 0.610549 \tabularnewline
182 & 0.377985 & 0.755971 & 0.622015 \tabularnewline
183 & 0.34197 & 0.68394 & 0.65803 \tabularnewline
184 & 0.314089 & 0.628178 & 0.685911 \tabularnewline
185 & 0.322361 & 0.644723 & 0.677639 \tabularnewline
186 & 0.31419 & 0.62838 & 0.68581 \tabularnewline
187 & 0.282152 & 0.564304 & 0.717848 \tabularnewline
188 & 0.258514 & 0.517028 & 0.741486 \tabularnewline
189 & 0.229898 & 0.459796 & 0.770102 \tabularnewline
190 & 0.211622 & 0.423243 & 0.788378 \tabularnewline
191 & 0.21696 & 0.433921 & 0.78304 \tabularnewline
192 & 0.198272 & 0.396544 & 0.801728 \tabularnewline
193 & 0.217089 & 0.434178 & 0.782911 \tabularnewline
194 & 0.203793 & 0.407587 & 0.796207 \tabularnewline
195 & 0.205574 & 0.411149 & 0.794426 \tabularnewline
196 & 0.213381 & 0.426762 & 0.786619 \tabularnewline
197 & 0.257089 & 0.514179 & 0.742911 \tabularnewline
198 & 0.240889 & 0.481778 & 0.759111 \tabularnewline
199 & 0.271795 & 0.543591 & 0.728205 \tabularnewline
200 & 0.238858 & 0.477717 & 0.761142 \tabularnewline
201 & 0.268398 & 0.536795 & 0.731602 \tabularnewline
202 & 0.251138 & 0.502275 & 0.748862 \tabularnewline
203 & 0.317934 & 0.635868 & 0.682066 \tabularnewline
204 & 0.282312 & 0.564624 & 0.717688 \tabularnewline
205 & 0.249103 & 0.498205 & 0.750897 \tabularnewline
206 & 0.229866 & 0.459732 & 0.770134 \tabularnewline
207 & 0.198469 & 0.396938 & 0.801531 \tabularnewline
208 & 0.221884 & 0.443769 & 0.778116 \tabularnewline
209 & 0.190734 & 0.381467 & 0.809266 \tabularnewline
210 & 0.208263 & 0.416526 & 0.791737 \tabularnewline
211 & 0.2291 & 0.458201 & 0.7709 \tabularnewline
212 & 0.217634 & 0.435267 & 0.782366 \tabularnewline
213 & 0.190375 & 0.380751 & 0.809625 \tabularnewline
214 & 0.237427 & 0.474854 & 0.762573 \tabularnewline
215 & 0.209595 & 0.41919 & 0.790405 \tabularnewline
216 & 0.198699 & 0.397397 & 0.801301 \tabularnewline
217 & 0.232623 & 0.465247 & 0.767377 \tabularnewline
218 & 0.202043 & 0.404087 & 0.797957 \tabularnewline
219 & 0.187864 & 0.375729 & 0.812136 \tabularnewline
220 & 0.19591 & 0.39182 & 0.80409 \tabularnewline
221 & 0.201656 & 0.403311 & 0.798344 \tabularnewline
222 & 0.205234 & 0.410468 & 0.794766 \tabularnewline
223 & 0.187504 & 0.375007 & 0.812496 \tabularnewline
224 & 0.15678 & 0.31356 & 0.84322 \tabularnewline
225 & 0.141417 & 0.282835 & 0.858583 \tabularnewline
226 & 0.170171 & 0.340341 & 0.829829 \tabularnewline
227 & 0.36606 & 0.73212 & 0.63394 \tabularnewline
228 & 0.341331 & 0.682661 & 0.658669 \tabularnewline
229 & 0.314132 & 0.628265 & 0.685868 \tabularnewline
230 & 0.297303 & 0.594606 & 0.702697 \tabularnewline
231 & 0.253778 & 0.507556 & 0.746222 \tabularnewline
232 & 0.282153 & 0.564307 & 0.717847 \tabularnewline
233 & 0.233657 & 0.467313 & 0.766343 \tabularnewline
234 & 0.196738 & 0.393476 & 0.803262 \tabularnewline
235 & 0.198761 & 0.397523 & 0.801239 \tabularnewline
236 & 0.170458 & 0.340917 & 0.829542 \tabularnewline
237 & 0.14837 & 0.29674 & 0.85163 \tabularnewline
238 & 0.113864 & 0.227727 & 0.886136 \tabularnewline
239 & 0.20532 & 0.41064 & 0.79468 \tabularnewline
240 & 0.19655 & 0.393099 & 0.80345 \tabularnewline
241 & 0.164775 & 0.329549 & 0.835225 \tabularnewline
242 & 0.283435 & 0.56687 & 0.716565 \tabularnewline
243 & 0.221789 & 0.443579 & 0.778211 \tabularnewline
244 & 0.171163 & 0.342327 & 0.828837 \tabularnewline
245 & 0.341289 & 0.682578 & 0.658711 \tabularnewline
246 & 0.263756 & 0.527511 & 0.736244 \tabularnewline
247 & 0.195037 & 0.390074 & 0.804963 \tabularnewline
248 & 0.302928 & 0.605855 & 0.697072 \tabularnewline
249 & 0.230583 & 0.461167 & 0.769417 \tabularnewline
250 & 0.155629 & 0.311259 & 0.844371 \tabularnewline
251 & 0.154851 & 0.309702 & 0.845149 \tabularnewline
252 & 0.484037 & 0.968075 & 0.515963 \tabularnewline
253 & 0.550463 & 0.899073 & 0.449537 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226550&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]11[/C][C]0.0279845[/C][C]0.0559689[/C][C]0.972016[/C][/ROW]
[ROW][C]12[/C][C]0.716733[/C][C]0.566535[/C][C]0.283267[/C][/ROW]
[ROW][C]13[/C][C]0.966286[/C][C]0.0674279[/C][C]0.033714[/C][/ROW]
[ROW][C]14[/C][C]0.941332[/C][C]0.117335[/C][C]0.0586676[/C][/ROW]
[ROW][C]15[/C][C]0.948289[/C][C]0.103421[/C][C]0.0517105[/C][/ROW]
[ROW][C]16[/C][C]0.922761[/C][C]0.154478[/C][C]0.0772392[/C][/ROW]
[ROW][C]17[/C][C]0.959985[/C][C]0.0800297[/C][C]0.0400148[/C][/ROW]
[ROW][C]18[/C][C]0.939274[/C][C]0.121452[/C][C]0.0607258[/C][/ROW]
[ROW][C]19[/C][C]0.911878[/C][C]0.176243[/C][C]0.0881216[/C][/ROW]
[ROW][C]20[/C][C]0.912622[/C][C]0.174755[/C][C]0.0873776[/C][/ROW]
[ROW][C]21[/C][C]0.931847[/C][C]0.136305[/C][C]0.0681527[/C][/ROW]
[ROW][C]22[/C][C]0.92851[/C][C]0.14298[/C][C]0.0714899[/C][/ROW]
[ROW][C]23[/C][C]0.926018[/C][C]0.147963[/C][C]0.0739817[/C][/ROW]
[ROW][C]24[/C][C]0.899591[/C][C]0.200817[/C][C]0.100409[/C][/ROW]
[ROW][C]25[/C][C]0.87608[/C][C]0.247839[/C][C]0.12392[/C][/ROW]
[ROW][C]26[/C][C]0.998942[/C][C]0.00211549[/C][C]0.00105775[/C][/ROW]
[ROW][C]27[/C][C]0.998328[/C][C]0.00334359[/C][C]0.00167179[/C][/ROW]
[ROW][C]28[/C][C]0.997349[/C][C]0.0053019[/C][C]0.00265095[/C][/ROW]
[ROW][C]29[/C][C]0.995934[/C][C]0.00813189[/C][C]0.00406595[/C][/ROW]
[ROW][C]30[/C][C]0.997235[/C][C]0.0055298[/C][C]0.0027649[/C][/ROW]
[ROW][C]31[/C][C]0.995814[/C][C]0.00837236[/C][C]0.00418618[/C][/ROW]
[ROW][C]32[/C][C]0.994001[/C][C]0.0119976[/C][C]0.00599882[/C][/ROW]
[ROW][C]33[/C][C]0.992712[/C][C]0.0145758[/C][C]0.00728791[/C][/ROW]
[ROW][C]34[/C][C]0.989494[/C][C]0.0210124[/C][C]0.0105062[/C][/ROW]
[ROW][C]35[/C][C]0.987005[/C][C]0.0259898[/C][C]0.0129949[/C][/ROW]
[ROW][C]36[/C][C]0.981999[/C][C]0.0360024[/C][C]0.0180012[/C][/ROW]
[ROW][C]37[/C][C]0.987888[/C][C]0.024223[/C][C]0.0121115[/C][/ROW]
[ROW][C]38[/C][C]0.983266[/C][C]0.0334677[/C][C]0.0167339[/C][/ROW]
[ROW][C]39[/C][C]0.980761[/C][C]0.0384775[/C][C]0.0192387[/C][/ROW]
[ROW][C]40[/C][C]0.981222[/C][C]0.0375557[/C][C]0.0187779[/C][/ROW]
[ROW][C]41[/C][C]0.975504[/C][C]0.0489914[/C][C]0.0244957[/C][/ROW]
[ROW][C]42[/C][C]0.972784[/C][C]0.0544324[/C][C]0.0272162[/C][/ROW]
[ROW][C]43[/C][C]0.964371[/C][C]0.0712572[/C][C]0.0356286[/C][/ROW]
[ROW][C]44[/C][C]0.958419[/C][C]0.0831612[/C][C]0.0415806[/C][/ROW]
[ROW][C]45[/C][C]0.946526[/C][C]0.106948[/C][C]0.0534739[/C][/ROW]
[ROW][C]46[/C][C]0.956074[/C][C]0.0878523[/C][C]0.0439261[/C][/ROW]
[ROW][C]47[/C][C]0.94415[/C][C]0.111699[/C][C]0.0558496[/C][/ROW]
[ROW][C]48[/C][C]0.929478[/C][C]0.141044[/C][C]0.0705221[/C][/ROW]
[ROW][C]49[/C][C]0.939982[/C][C]0.120037[/C][C]0.0600184[/C][/ROW]
[ROW][C]50[/C][C]0.93736[/C][C]0.12528[/C][C]0.06264[/C][/ROW]
[ROW][C]51[/C][C]0.92296[/C][C]0.154081[/C][C]0.0770403[/C][/ROW]
[ROW][C]52[/C][C]0.905435[/C][C]0.189129[/C][C]0.0945645[/C][/ROW]
[ROW][C]53[/C][C]0.893175[/C][C]0.213649[/C][C]0.106825[/C][/ROW]
[ROW][C]54[/C][C]0.877961[/C][C]0.244079[/C][C]0.122039[/C][/ROW]
[ROW][C]55[/C][C]0.869839[/C][C]0.260323[/C][C]0.130161[/C][/ROW]
[ROW][C]56[/C][C]0.85287[/C][C]0.29426[/C][C]0.14713[/C][/ROW]
[ROW][C]57[/C][C]0.838143[/C][C]0.323714[/C][C]0.161857[/C][/ROW]
[ROW][C]58[/C][C]0.810261[/C][C]0.379478[/C][C]0.189739[/C][/ROW]
[ROW][C]59[/C][C]0.853687[/C][C]0.292626[/C][C]0.146313[/C][/ROW]
[ROW][C]60[/C][C]0.849277[/C][C]0.301446[/C][C]0.150723[/C][/ROW]
[ROW][C]61[/C][C]0.870528[/C][C]0.258944[/C][C]0.129472[/C][/ROW]
[ROW][C]62[/C][C]0.871735[/C][C]0.256531[/C][C]0.128265[/C][/ROW]
[ROW][C]63[/C][C]0.925432[/C][C]0.149136[/C][C]0.0745681[/C][/ROW]
[ROW][C]64[/C][C]0.913178[/C][C]0.173645[/C][C]0.0868223[/C][/ROW]
[ROW][C]65[/C][C]0.901839[/C][C]0.196323[/C][C]0.0981614[/C][/ROW]
[ROW][C]66[/C][C]0.913992[/C][C]0.172016[/C][C]0.0860082[/C][/ROW]
[ROW][C]67[/C][C]0.913014[/C][C]0.173971[/C][C]0.0869856[/C][/ROW]
[ROW][C]68[/C][C]0.903797[/C][C]0.192406[/C][C]0.0962028[/C][/ROW]
[ROW][C]69[/C][C]0.936252[/C][C]0.127496[/C][C]0.0637478[/C][/ROW]
[ROW][C]70[/C][C]0.941352[/C][C]0.117295[/C][C]0.0586476[/C][/ROW]
[ROW][C]71[/C][C]0.936111[/C][C]0.127777[/C][C]0.0638887[/C][/ROW]
[ROW][C]72[/C][C]0.95784[/C][C]0.0843204[/C][C]0.0421602[/C][/ROW]
[ROW][C]73[/C][C]0.948837[/C][C]0.102325[/C][C]0.0511626[/C][/ROW]
[ROW][C]74[/C][C]0.937691[/C][C]0.124618[/C][C]0.0623088[/C][/ROW]
[ROW][C]75[/C][C]0.930765[/C][C]0.13847[/C][C]0.069235[/C][/ROW]
[ROW][C]76[/C][C]0.916649[/C][C]0.166703[/C][C]0.0833513[/C][/ROW]
[ROW][C]77[/C][C]0.932908[/C][C]0.134183[/C][C]0.0670915[/C][/ROW]
[ROW][C]78[/C][C]0.920795[/C][C]0.15841[/C][C]0.0792048[/C][/ROW]
[ROW][C]79[/C][C]0.913509[/C][C]0.172982[/C][C]0.0864911[/C][/ROW]
[ROW][C]80[/C][C]0.906872[/C][C]0.186256[/C][C]0.093128[/C][/ROW]
[ROW][C]81[/C][C]0.889602[/C][C]0.220795[/C][C]0.110398[/C][/ROW]
[ROW][C]82[/C][C]0.870967[/C][C]0.258065[/C][C]0.129033[/C][/ROW]
[ROW][C]83[/C][C]0.864938[/C][C]0.270124[/C][C]0.135062[/C][/ROW]
[ROW][C]84[/C][C]0.846085[/C][C]0.30783[/C][C]0.153915[/C][/ROW]
[ROW][C]85[/C][C]0.822293[/C][C]0.355414[/C][C]0.177707[/C][/ROW]
[ROW][C]86[/C][C]0.799609[/C][C]0.400781[/C][C]0.200391[/C][/ROW]
[ROW][C]87[/C][C]0.77222[/C][C]0.45556[/C][C]0.22778[/C][/ROW]
[ROW][C]88[/C][C]0.742652[/C][C]0.514697[/C][C]0.257348[/C][/ROW]
[ROW][C]89[/C][C]0.815095[/C][C]0.369809[/C][C]0.184905[/C][/ROW]
[ROW][C]90[/C][C]0.848674[/C][C]0.302653[/C][C]0.151326[/C][/ROW]
[ROW][C]91[/C][C]0.825759[/C][C]0.348482[/C][C]0.174241[/C][/ROW]
[ROW][C]92[/C][C]0.802725[/C][C]0.394551[/C][C]0.197275[/C][/ROW]
[ROW][C]93[/C][C]0.779651[/C][C]0.440699[/C][C]0.220349[/C][/ROW]
[ROW][C]94[/C][C]0.758094[/C][C]0.483812[/C][C]0.241906[/C][/ROW]
[ROW][C]95[/C][C]0.733458[/C][C]0.533085[/C][C]0.266542[/C][/ROW]
[ROW][C]96[/C][C]0.709846[/C][C]0.580308[/C][C]0.290154[/C][/ROW]
[ROW][C]97[/C][C]0.682224[/C][C]0.635551[/C][C]0.317776[/C][/ROW]
[ROW][C]98[/C][C]0.679846[/C][C]0.640309[/C][C]0.320154[/C][/ROW]
[ROW][C]99[/C][C]0.646086[/C][C]0.707827[/C][C]0.353914[/C][/ROW]
[ROW][C]100[/C][C]0.632954[/C][C]0.734091[/C][C]0.367046[/C][/ROW]
[ROW][C]101[/C][C]0.608703[/C][C]0.782595[/C][C]0.391297[/C][/ROW]
[ROW][C]102[/C][C]0.578538[/C][C]0.842924[/C][C]0.421462[/C][/ROW]
[ROW][C]103[/C][C]0.630616[/C][C]0.738768[/C][C]0.369384[/C][/ROW]
[ROW][C]104[/C][C]0.617305[/C][C]0.765389[/C][C]0.382695[/C][/ROW]
[ROW][C]105[/C][C]0.639256[/C][C]0.721488[/C][C]0.360744[/C][/ROW]
[ROW][C]106[/C][C]0.613018[/C][C]0.773964[/C][C]0.386982[/C][/ROW]
[ROW][C]107[/C][C]0.603267[/C][C]0.793467[/C][C]0.396733[/C][/ROW]
[ROW][C]108[/C][C]0.642074[/C][C]0.715853[/C][C]0.357926[/C][/ROW]
[ROW][C]109[/C][C]0.611403[/C][C]0.777194[/C][C]0.388597[/C][/ROW]
[ROW][C]110[/C][C]0.584488[/C][C]0.831025[/C][C]0.415512[/C][/ROW]
[ROW][C]111[/C][C]0.596326[/C][C]0.807349[/C][C]0.403674[/C][/ROW]
[ROW][C]112[/C][C]0.619536[/C][C]0.760927[/C][C]0.380464[/C][/ROW]
[ROW][C]113[/C][C]0.607115[/C][C]0.785771[/C][C]0.392885[/C][/ROW]
[ROW][C]114[/C][C]0.693375[/C][C]0.613249[/C][C]0.306625[/C][/ROW]
[ROW][C]115[/C][C]0.663472[/C][C]0.673057[/C][C]0.336528[/C][/ROW]
[ROW][C]116[/C][C]0.635802[/C][C]0.728397[/C][C]0.364198[/C][/ROW]
[ROW][C]117[/C][C]0.601861[/C][C]0.796279[/C][C]0.398139[/C][/ROW]
[ROW][C]118[/C][C]0.578671[/C][C]0.842657[/C][C]0.421329[/C][/ROW]
[ROW][C]119[/C][C]0.543687[/C][C]0.912626[/C][C]0.456313[/C][/ROW]
[ROW][C]120[/C][C]0.512163[/C][C]0.975675[/C][C]0.487837[/C][/ROW]
[ROW][C]121[/C][C]0.482476[/C][C]0.964952[/C][C]0.517524[/C][/ROW]
[ROW][C]122[/C][C]0.449932[/C][C]0.899865[/C][C]0.550068[/C][/ROW]
[ROW][C]123[/C][C]0.42444[/C][C]0.848881[/C][C]0.57556[/C][/ROW]
[ROW][C]124[/C][C]0.392062[/C][C]0.784124[/C][C]0.607938[/C][/ROW]
[ROW][C]125[/C][C]0.38716[/C][C]0.774321[/C][C]0.61284[/C][/ROW]
[ROW][C]126[/C][C]0.358245[/C][C]0.71649[/C][C]0.641755[/C][/ROW]
[ROW][C]127[/C][C]0.343019[/C][C]0.686037[/C][C]0.656981[/C][/ROW]
[ROW][C]128[/C][C]0.453367[/C][C]0.906733[/C][C]0.546633[/C][/ROW]
[ROW][C]129[/C][C]0.432727[/C][C]0.865454[/C][C]0.567273[/C][/ROW]
[ROW][C]130[/C][C]0.42048[/C][C]0.840959[/C][C]0.57952[/C][/ROW]
[ROW][C]131[/C][C]0.411104[/C][C]0.822208[/C][C]0.588896[/C][/ROW]
[ROW][C]132[/C][C]0.379138[/C][C]0.758277[/C][C]0.620862[/C][/ROW]
[ROW][C]133[/C][C]0.395102[/C][C]0.790205[/C][C]0.604898[/C][/ROW]
[ROW][C]134[/C][C]0.365428[/C][C]0.730857[/C][C]0.634572[/C][/ROW]
[ROW][C]135[/C][C]0.373479[/C][C]0.746959[/C][C]0.626521[/C][/ROW]
[ROW][C]136[/C][C]0.363195[/C][C]0.72639[/C][C]0.636805[/C][/ROW]
[ROW][C]137[/C][C]0.333317[/C][C]0.666635[/C][C]0.666683[/C][/ROW]
[ROW][C]138[/C][C]0.310153[/C][C]0.620306[/C][C]0.689847[/C][/ROW]
[ROW][C]139[/C][C]0.283911[/C][C]0.567822[/C][C]0.716089[/C][/ROW]
[ROW][C]140[/C][C]0.260063[/C][C]0.520125[/C][C]0.739937[/C][/ROW]
[ROW][C]141[/C][C]0.233449[/C][C]0.466899[/C][C]0.766551[/C][/ROW]
[ROW][C]142[/C][C]0.240238[/C][C]0.480476[/C][C]0.759762[/C][/ROW]
[ROW][C]143[/C][C]0.216239[/C][C]0.432478[/C][C]0.783761[/C][/ROW]
[ROW][C]144[/C][C]0.19544[/C][C]0.39088[/C][C]0.80456[/C][/ROW]
[ROW][C]145[/C][C]0.183081[/C][C]0.366163[/C][C]0.816919[/C][/ROW]
[ROW][C]146[/C][C]0.175137[/C][C]0.350274[/C][C]0.824863[/C][/ROW]
[ROW][C]147[/C][C]0.185547[/C][C]0.371094[/C][C]0.814453[/C][/ROW]
[ROW][C]148[/C][C]0.203622[/C][C]0.407245[/C][C]0.796378[/C][/ROW]
[ROW][C]149[/C][C]0.221889[/C][C]0.443777[/C][C]0.778111[/C][/ROW]
[ROW][C]150[/C][C]0.219458[/C][C]0.438915[/C][C]0.780542[/C][/ROW]
[ROW][C]151[/C][C]0.197851[/C][C]0.395701[/C][C]0.802149[/C][/ROW]
[ROW][C]152[/C][C]0.177535[/C][C]0.355069[/C][C]0.822465[/C][/ROW]
[ROW][C]153[/C][C]0.184915[/C][C]0.369831[/C][C]0.815085[/C][/ROW]
[ROW][C]154[/C][C]0.21962[/C][C]0.43924[/C][C]0.78038[/C][/ROW]
[ROW][C]155[/C][C]0.198117[/C][C]0.396234[/C][C]0.801883[/C][/ROW]
[ROW][C]156[/C][C]0.177519[/C][C]0.355037[/C][C]0.822481[/C][/ROW]
[ROW][C]157[/C][C]0.155311[/C][C]0.310622[/C][C]0.844689[/C][/ROW]
[ROW][C]158[/C][C]0.228655[/C][C]0.45731[/C][C]0.771345[/C][/ROW]
[ROW][C]159[/C][C]0.254166[/C][C]0.508332[/C][C]0.745834[/C][/ROW]
[ROW][C]160[/C][C]0.227783[/C][C]0.455565[/C][C]0.772217[/C][/ROW]
[ROW][C]161[/C][C]0.20096[/C][C]0.40192[/C][C]0.79904[/C][/ROW]
[ROW][C]162[/C][C]0.178137[/C][C]0.356273[/C][C]0.821863[/C][/ROW]
[ROW][C]163[/C][C]0.15785[/C][C]0.315701[/C][C]0.84215[/C][/ROW]
[ROW][C]164[/C][C]0.263426[/C][C]0.526851[/C][C]0.736574[/C][/ROW]
[ROW][C]165[/C][C]0.259686[/C][C]0.519371[/C][C]0.740314[/C][/ROW]
[ROW][C]166[/C][C]0.255745[/C][C]0.51149[/C][C]0.744255[/C][/ROW]
[ROW][C]167[/C][C]0.227509[/C][C]0.455019[/C][C]0.772491[/C][/ROW]
[ROW][C]168[/C][C]0.206071[/C][C]0.412143[/C][C]0.793929[/C][/ROW]
[ROW][C]169[/C][C]0.262961[/C][C]0.525922[/C][C]0.737039[/C][/ROW]
[ROW][C]170[/C][C]0.285359[/C][C]0.570718[/C][C]0.714641[/C][/ROW]
[ROW][C]171[/C][C]0.257166[/C][C]0.514331[/C][C]0.742834[/C][/ROW]
[ROW][C]172[/C][C]0.25387[/C][C]0.507739[/C][C]0.74613[/C][/ROW]
[ROW][C]173[/C][C]0.410494[/C][C]0.820989[/C][C]0.589506[/C][/ROW]
[ROW][C]174[/C][C]0.399832[/C][C]0.799664[/C][C]0.600168[/C][/ROW]
[ROW][C]175[/C][C]0.426346[/C][C]0.852691[/C][C]0.573654[/C][/ROW]
[ROW][C]176[/C][C]0.432036[/C][C]0.864071[/C][C]0.567964[/C][/ROW]
[ROW][C]177[/C][C]0.483164[/C][C]0.966328[/C][C]0.516836[/C][/ROW]
[ROW][C]178[/C][C]0.450196[/C][C]0.900392[/C][C]0.549804[/C][/ROW]
[ROW][C]179[/C][C]0.43081[/C][C]0.86162[/C][C]0.56919[/C][/ROW]
[ROW][C]180[/C][C]0.42668[/C][C]0.853361[/C][C]0.57332[/C][/ROW]
[ROW][C]181[/C][C]0.389451[/C][C]0.778903[/C][C]0.610549[/C][/ROW]
[ROW][C]182[/C][C]0.377985[/C][C]0.755971[/C][C]0.622015[/C][/ROW]
[ROW][C]183[/C][C]0.34197[/C][C]0.68394[/C][C]0.65803[/C][/ROW]
[ROW][C]184[/C][C]0.314089[/C][C]0.628178[/C][C]0.685911[/C][/ROW]
[ROW][C]185[/C][C]0.322361[/C][C]0.644723[/C][C]0.677639[/C][/ROW]
[ROW][C]186[/C][C]0.31419[/C][C]0.62838[/C][C]0.68581[/C][/ROW]
[ROW][C]187[/C][C]0.282152[/C][C]0.564304[/C][C]0.717848[/C][/ROW]
[ROW][C]188[/C][C]0.258514[/C][C]0.517028[/C][C]0.741486[/C][/ROW]
[ROW][C]189[/C][C]0.229898[/C][C]0.459796[/C][C]0.770102[/C][/ROW]
[ROW][C]190[/C][C]0.211622[/C][C]0.423243[/C][C]0.788378[/C][/ROW]
[ROW][C]191[/C][C]0.21696[/C][C]0.433921[/C][C]0.78304[/C][/ROW]
[ROW][C]192[/C][C]0.198272[/C][C]0.396544[/C][C]0.801728[/C][/ROW]
[ROW][C]193[/C][C]0.217089[/C][C]0.434178[/C][C]0.782911[/C][/ROW]
[ROW][C]194[/C][C]0.203793[/C][C]0.407587[/C][C]0.796207[/C][/ROW]
[ROW][C]195[/C][C]0.205574[/C][C]0.411149[/C][C]0.794426[/C][/ROW]
[ROW][C]196[/C][C]0.213381[/C][C]0.426762[/C][C]0.786619[/C][/ROW]
[ROW][C]197[/C][C]0.257089[/C][C]0.514179[/C][C]0.742911[/C][/ROW]
[ROW][C]198[/C][C]0.240889[/C][C]0.481778[/C][C]0.759111[/C][/ROW]
[ROW][C]199[/C][C]0.271795[/C][C]0.543591[/C][C]0.728205[/C][/ROW]
[ROW][C]200[/C][C]0.238858[/C][C]0.477717[/C][C]0.761142[/C][/ROW]
[ROW][C]201[/C][C]0.268398[/C][C]0.536795[/C][C]0.731602[/C][/ROW]
[ROW][C]202[/C][C]0.251138[/C][C]0.502275[/C][C]0.748862[/C][/ROW]
[ROW][C]203[/C][C]0.317934[/C][C]0.635868[/C][C]0.682066[/C][/ROW]
[ROW][C]204[/C][C]0.282312[/C][C]0.564624[/C][C]0.717688[/C][/ROW]
[ROW][C]205[/C][C]0.249103[/C][C]0.498205[/C][C]0.750897[/C][/ROW]
[ROW][C]206[/C][C]0.229866[/C][C]0.459732[/C][C]0.770134[/C][/ROW]
[ROW][C]207[/C][C]0.198469[/C][C]0.396938[/C][C]0.801531[/C][/ROW]
[ROW][C]208[/C][C]0.221884[/C][C]0.443769[/C][C]0.778116[/C][/ROW]
[ROW][C]209[/C][C]0.190734[/C][C]0.381467[/C][C]0.809266[/C][/ROW]
[ROW][C]210[/C][C]0.208263[/C][C]0.416526[/C][C]0.791737[/C][/ROW]
[ROW][C]211[/C][C]0.2291[/C][C]0.458201[/C][C]0.7709[/C][/ROW]
[ROW][C]212[/C][C]0.217634[/C][C]0.435267[/C][C]0.782366[/C][/ROW]
[ROW][C]213[/C][C]0.190375[/C][C]0.380751[/C][C]0.809625[/C][/ROW]
[ROW][C]214[/C][C]0.237427[/C][C]0.474854[/C][C]0.762573[/C][/ROW]
[ROW][C]215[/C][C]0.209595[/C][C]0.41919[/C][C]0.790405[/C][/ROW]
[ROW][C]216[/C][C]0.198699[/C][C]0.397397[/C][C]0.801301[/C][/ROW]
[ROW][C]217[/C][C]0.232623[/C][C]0.465247[/C][C]0.767377[/C][/ROW]
[ROW][C]218[/C][C]0.202043[/C][C]0.404087[/C][C]0.797957[/C][/ROW]
[ROW][C]219[/C][C]0.187864[/C][C]0.375729[/C][C]0.812136[/C][/ROW]
[ROW][C]220[/C][C]0.19591[/C][C]0.39182[/C][C]0.80409[/C][/ROW]
[ROW][C]221[/C][C]0.201656[/C][C]0.403311[/C][C]0.798344[/C][/ROW]
[ROW][C]222[/C][C]0.205234[/C][C]0.410468[/C][C]0.794766[/C][/ROW]
[ROW][C]223[/C][C]0.187504[/C][C]0.375007[/C][C]0.812496[/C][/ROW]
[ROW][C]224[/C][C]0.15678[/C][C]0.31356[/C][C]0.84322[/C][/ROW]
[ROW][C]225[/C][C]0.141417[/C][C]0.282835[/C][C]0.858583[/C][/ROW]
[ROW][C]226[/C][C]0.170171[/C][C]0.340341[/C][C]0.829829[/C][/ROW]
[ROW][C]227[/C][C]0.36606[/C][C]0.73212[/C][C]0.63394[/C][/ROW]
[ROW][C]228[/C][C]0.341331[/C][C]0.682661[/C][C]0.658669[/C][/ROW]
[ROW][C]229[/C][C]0.314132[/C][C]0.628265[/C][C]0.685868[/C][/ROW]
[ROW][C]230[/C][C]0.297303[/C][C]0.594606[/C][C]0.702697[/C][/ROW]
[ROW][C]231[/C][C]0.253778[/C][C]0.507556[/C][C]0.746222[/C][/ROW]
[ROW][C]232[/C][C]0.282153[/C][C]0.564307[/C][C]0.717847[/C][/ROW]
[ROW][C]233[/C][C]0.233657[/C][C]0.467313[/C][C]0.766343[/C][/ROW]
[ROW][C]234[/C][C]0.196738[/C][C]0.393476[/C][C]0.803262[/C][/ROW]
[ROW][C]235[/C][C]0.198761[/C][C]0.397523[/C][C]0.801239[/C][/ROW]
[ROW][C]236[/C][C]0.170458[/C][C]0.340917[/C][C]0.829542[/C][/ROW]
[ROW][C]237[/C][C]0.14837[/C][C]0.29674[/C][C]0.85163[/C][/ROW]
[ROW][C]238[/C][C]0.113864[/C][C]0.227727[/C][C]0.886136[/C][/ROW]
[ROW][C]239[/C][C]0.20532[/C][C]0.41064[/C][C]0.79468[/C][/ROW]
[ROW][C]240[/C][C]0.19655[/C][C]0.393099[/C][C]0.80345[/C][/ROW]
[ROW][C]241[/C][C]0.164775[/C][C]0.329549[/C][C]0.835225[/C][/ROW]
[ROW][C]242[/C][C]0.283435[/C][C]0.56687[/C][C]0.716565[/C][/ROW]
[ROW][C]243[/C][C]0.221789[/C][C]0.443579[/C][C]0.778211[/C][/ROW]
[ROW][C]244[/C][C]0.171163[/C][C]0.342327[/C][C]0.828837[/C][/ROW]
[ROW][C]245[/C][C]0.341289[/C][C]0.682578[/C][C]0.658711[/C][/ROW]
[ROW][C]246[/C][C]0.263756[/C][C]0.527511[/C][C]0.736244[/C][/ROW]
[ROW][C]247[/C][C]0.195037[/C][C]0.390074[/C][C]0.804963[/C][/ROW]
[ROW][C]248[/C][C]0.302928[/C][C]0.605855[/C][C]0.697072[/C][/ROW]
[ROW][C]249[/C][C]0.230583[/C][C]0.461167[/C][C]0.769417[/C][/ROW]
[ROW][C]250[/C][C]0.155629[/C][C]0.311259[/C][C]0.844371[/C][/ROW]
[ROW][C]251[/C][C]0.154851[/C][C]0.309702[/C][C]0.845149[/C][/ROW]
[ROW][C]252[/C][C]0.484037[/C][C]0.968075[/C][C]0.515963[/C][/ROW]
[ROW][C]253[/C][C]0.550463[/C][C]0.899073[/C][C]0.449537[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226550&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226550&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
110.02798450.05596890.972016
120.7167330.5665350.283267
130.9662860.06742790.033714
140.9413320.1173350.0586676
150.9482890.1034210.0517105
160.9227610.1544780.0772392
170.9599850.08002970.0400148
180.9392740.1214520.0607258
190.9118780.1762430.0881216
200.9126220.1747550.0873776
210.9318470.1363050.0681527
220.928510.142980.0714899
230.9260180.1479630.0739817
240.8995910.2008170.100409
250.876080.2478390.12392
260.9989420.002115490.00105775
270.9983280.003343590.00167179
280.9973490.00530190.00265095
290.9959340.008131890.00406595
300.9972350.00552980.0027649
310.9958140.008372360.00418618
320.9940010.01199760.00599882
330.9927120.01457580.00728791
340.9894940.02101240.0105062
350.9870050.02598980.0129949
360.9819990.03600240.0180012
370.9878880.0242230.0121115
380.9832660.03346770.0167339
390.9807610.03847750.0192387
400.9812220.03755570.0187779
410.9755040.04899140.0244957
420.9727840.05443240.0272162
430.9643710.07125720.0356286
440.9584190.08316120.0415806
450.9465260.1069480.0534739
460.9560740.08785230.0439261
470.944150.1116990.0558496
480.9294780.1410440.0705221
490.9399820.1200370.0600184
500.937360.125280.06264
510.922960.1540810.0770403
520.9054350.1891290.0945645
530.8931750.2136490.106825
540.8779610.2440790.122039
550.8698390.2603230.130161
560.852870.294260.14713
570.8381430.3237140.161857
580.8102610.3794780.189739
590.8536870.2926260.146313
600.8492770.3014460.150723
610.8705280.2589440.129472
620.8717350.2565310.128265
630.9254320.1491360.0745681
640.9131780.1736450.0868223
650.9018390.1963230.0981614
660.9139920.1720160.0860082
670.9130140.1739710.0869856
680.9037970.1924060.0962028
690.9362520.1274960.0637478
700.9413520.1172950.0586476
710.9361110.1277770.0638887
720.957840.08432040.0421602
730.9488370.1023250.0511626
740.9376910.1246180.0623088
750.9307650.138470.069235
760.9166490.1667030.0833513
770.9329080.1341830.0670915
780.9207950.158410.0792048
790.9135090.1729820.0864911
800.9068720.1862560.093128
810.8896020.2207950.110398
820.8709670.2580650.129033
830.8649380.2701240.135062
840.8460850.307830.153915
850.8222930.3554140.177707
860.7996090.4007810.200391
870.772220.455560.22778
880.7426520.5146970.257348
890.8150950.3698090.184905
900.8486740.3026530.151326
910.8257590.3484820.174241
920.8027250.3945510.197275
930.7796510.4406990.220349
940.7580940.4838120.241906
950.7334580.5330850.266542
960.7098460.5803080.290154
970.6822240.6355510.317776
980.6798460.6403090.320154
990.6460860.7078270.353914
1000.6329540.7340910.367046
1010.6087030.7825950.391297
1020.5785380.8429240.421462
1030.6306160.7387680.369384
1040.6173050.7653890.382695
1050.6392560.7214880.360744
1060.6130180.7739640.386982
1070.6032670.7934670.396733
1080.6420740.7158530.357926
1090.6114030.7771940.388597
1100.5844880.8310250.415512
1110.5963260.8073490.403674
1120.6195360.7609270.380464
1130.6071150.7857710.392885
1140.6933750.6132490.306625
1150.6634720.6730570.336528
1160.6358020.7283970.364198
1170.6018610.7962790.398139
1180.5786710.8426570.421329
1190.5436870.9126260.456313
1200.5121630.9756750.487837
1210.4824760.9649520.517524
1220.4499320.8998650.550068
1230.424440.8488810.57556
1240.3920620.7841240.607938
1250.387160.7743210.61284
1260.3582450.716490.641755
1270.3430190.6860370.656981
1280.4533670.9067330.546633
1290.4327270.8654540.567273
1300.420480.8409590.57952
1310.4111040.8222080.588896
1320.3791380.7582770.620862
1330.3951020.7902050.604898
1340.3654280.7308570.634572
1350.3734790.7469590.626521
1360.3631950.726390.636805
1370.3333170.6666350.666683
1380.3101530.6203060.689847
1390.2839110.5678220.716089
1400.2600630.5201250.739937
1410.2334490.4668990.766551
1420.2402380.4804760.759762
1430.2162390.4324780.783761
1440.195440.390880.80456
1450.1830810.3661630.816919
1460.1751370.3502740.824863
1470.1855470.3710940.814453
1480.2036220.4072450.796378
1490.2218890.4437770.778111
1500.2194580.4389150.780542
1510.1978510.3957010.802149
1520.1775350.3550690.822465
1530.1849150.3698310.815085
1540.219620.439240.78038
1550.1981170.3962340.801883
1560.1775190.3550370.822481
1570.1553110.3106220.844689
1580.2286550.457310.771345
1590.2541660.5083320.745834
1600.2277830.4555650.772217
1610.200960.401920.79904
1620.1781370.3562730.821863
1630.157850.3157010.84215
1640.2634260.5268510.736574
1650.2596860.5193710.740314
1660.2557450.511490.744255
1670.2275090.4550190.772491
1680.2060710.4121430.793929
1690.2629610.5259220.737039
1700.2853590.5707180.714641
1710.2571660.5143310.742834
1720.253870.5077390.74613
1730.4104940.8209890.589506
1740.3998320.7996640.600168
1750.4263460.8526910.573654
1760.4320360.8640710.567964
1770.4831640.9663280.516836
1780.4501960.9003920.549804
1790.430810.861620.56919
1800.426680.8533610.57332
1810.3894510.7789030.610549
1820.3779850.7559710.622015
1830.341970.683940.65803
1840.3140890.6281780.685911
1850.3223610.6447230.677639
1860.314190.628380.68581
1870.2821520.5643040.717848
1880.2585140.5170280.741486
1890.2298980.4597960.770102
1900.2116220.4232430.788378
1910.216960.4339210.78304
1920.1982720.3965440.801728
1930.2170890.4341780.782911
1940.2037930.4075870.796207
1950.2055740.4111490.794426
1960.2133810.4267620.786619
1970.2570890.5141790.742911
1980.2408890.4817780.759111
1990.2717950.5435910.728205
2000.2388580.4777170.761142
2010.2683980.5367950.731602
2020.2511380.5022750.748862
2030.3179340.6358680.682066
2040.2823120.5646240.717688
2050.2491030.4982050.750897
2060.2298660.4597320.770134
2070.1984690.3969380.801531
2080.2218840.4437690.778116
2090.1907340.3814670.809266
2100.2082630.4165260.791737
2110.22910.4582010.7709
2120.2176340.4352670.782366
2130.1903750.3807510.809625
2140.2374270.4748540.762573
2150.2095950.419190.790405
2160.1986990.3973970.801301
2170.2326230.4652470.767377
2180.2020430.4040870.797957
2190.1878640.3757290.812136
2200.195910.391820.80409
2210.2016560.4033110.798344
2220.2052340.4104680.794766
2230.1875040.3750070.812496
2240.156780.313560.84322
2250.1414170.2828350.858583
2260.1701710.3403410.829829
2270.366060.732120.63394
2280.3413310.6826610.658669
2290.3141320.6282650.685868
2300.2973030.5946060.702697
2310.2537780.5075560.746222
2320.2821530.5643070.717847
2330.2336570.4673130.766343
2340.1967380.3934760.803262
2350.1987610.3975230.801239
2360.1704580.3409170.829542
2370.148370.296740.85163
2380.1138640.2277270.886136
2390.205320.410640.79468
2400.196550.3930990.80345
2410.1647750.3295490.835225
2420.2834350.566870.716565
2430.2217890.4435790.778211
2440.1711630.3423270.828837
2450.3412890.6825780.658711
2460.2637560.5275110.736244
2470.1950370.3900740.804963
2480.3029280.6058550.697072
2490.2305830.4611670.769417
2500.1556290.3112590.844371
2510.1548510.3097020.845149
2520.4840370.9680750.515963
2530.5504630.8990730.449537






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level60.0246914NOK
5% type I error level160.0658436NOK
10% type I error level240.0987654OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 6 & 0.0246914 & NOK \tabularnewline
5% type I error level & 16 & 0.0658436 & NOK \tabularnewline
10% type I error level & 24 & 0.0987654 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226550&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]6[/C][C]0.0246914[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]16[/C][C]0.0658436[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]24[/C][C]0.0987654[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226550&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226550&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level60.0246914NOK
5% type I error level160.0658436NOK
10% type I error level240.0987654OK


Figures (Output of Computation)

Figure 1
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; 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')
}