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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 computationMon, 18 Nov 2013 06:34:41 -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/18/t1384774499wejv5mai960ty44.htm/, Retrieved Sat, 27 Apr 2024 10:22:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226044, Retrieved Sat, 27 Apr 2024 10:22:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Workshop 71] [2013-11-18 11:34:41] [249761a82d67c41cbe9b5c486860cdc6] [Current]
-    D    [Multiple Regression] [workshop 7 ] [2013-11-20 11:35:52] [4e6b221caf797a012ce5465db674848b]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12 41 38 13 14 12 53 32
11 39 32 16 18 11 83 51
15 30 35 19 11 14 66 42
6 31 33 15 12 12 67 41
13 34 37 14 16 21 76 46
10 35 29 13 18 12 78 47
12 39 31 19 14 22 53 37
14 34 36 15 14 11 80 49
12 36 35 14 15 10 74 45
9 37 38 15 15 13 76 47
10 38 31 16 17 10 79 49
12 36 34 16 19 8 54 33
12 38 35 16 10 15 67 42
11 39 38 16 16 14 54 33
15 33 37 17 18 10 87 53
12 32 33 15 14 14 58 36
10 36 32 15 14 14 75 45
12 38 38 20 17 11 88 54
11 39 38 18 14 10 64 41
12 32 32 16 16 13 57 36
11 32 33 16 18 9.5 66 41
12 31 31 16 11 14 68 44
13 39 38 19 14 12 54 33
11 37 39 16 12 14 56 37
12 39 32 17 17 11 86 52
13 41 32 17 9 9 80 47
10 36 35 16 16 11 76 43
14 33 37 15 14 15 69 44
12 33 33 16 15 14 78 45
10 34 33 14 11 13 67 44
12 31 31 15 16 9 80 49
8 27 32 12 13 15 54 33
10 37 31 14 17 10 71 43
12 34 37 16 15 11 84 54
12 34 30 14 14 13 74 42
7 32 33 10 16 8 71 44
9 29 31 10 9 20 63 37
12 36 33 14 15 12 71 43
10 29 31 16 17 10 76 46
10 35 33 16 13 10 69 42
10 37 32 16 15 9 74 45
12 34 33 14 16 14 75 44
15 38 32 20 16 8 54 33
10 35 33 14 12 14 52 31
10 38 28 14 15 11 69 42
12 37 35 11 11 13 68 40
13 38 39 14 15 9 65 43
11 33 34 15 15 11 75 46
11 36 38 16 17 15 74 42
12 38 32 14 13 11 75 45
14 32 38 16 16 10 72 44
10 32 30 14 14 14 67 40
12 32 33 12 11 18 63 37
13 34 38 16 12 14 62 46
5 32 32 9 12 11 63 36
6 37 35 14 15 14.5 76 47
12 39 34 16 16 13 74 45
12 29 34 16 15 9 67 42
11 37 36 15 12 10 73 43
10 35 34 16 12 15 70 43
7 30 28 12 8 20 53 32
12 38 34 16 13 12 77 45
14 34 35 16 11 12 80 48
11 31 35 14 14 14 52 31
12 34 31 16 15 13 54 33
13 35 37 17 10 11 80 49
14 36 35 18 11 17 66 42
11 30 27 18 12 12 73 41
12 39 40 12 15 13 63 38
12 35 37 16 15 14 69 42
8 38 36 10 14 13 67 44
11 31 38 14 16 15 54 33
14 34 39 18 15 13 81 48
14 38 41 18 15 10 69 40
12 34 27 16 13 11 84 50
9 39 30 17 12 19 80 49
13 37 37 16 17 13 70 43
11 34 31 16 13 17 69 44
12 28 31 13 15 13 77 47
12 37 27 16 13 9 54 33
12 33 36 16 15 11 79 46
12 35 37 16 15 9 71 45
12 37 33 15 16 12 73 43
11 32 34 15 15 12 72 44
10 33 31 16 14 13 77 47
9 38 39 14 15 13 75 45
12 33 34 16 14 12 69 42
12 29 32 16 13 15 54 33
12 33 33 15 7 22 70 43
9 31 36 12 17 13 73 46
15 36 32 17 13 15 54 33
12 35 41 16 15 13 77 46
12 32 28 15 14 15 82 48
12 29 30 13 13 12.5 80 47
10 39 36 16 16 11 80 47
13 37 35 16 12 16 69 43
9 35 31 16 14 11 78 46
12 37 34 16 17 11 81 48
10 32 36 14 15 10 76 46
14 38 36 16 17 10 76 45
11 37 35 16 12 16 73 45
15 36 37 20 16 12 85 52
11 32 28 15 11 11 66 42
11 33 39 16 15 16 79 47
12 40 32 13 9 19 68 41
12 38 35 17 16 11 76 47
12 41 39 16 15 16 71 43
11 36 35 16 10 15 54 33
7 43 42 12 10 24 46 30
12 30 34 16 15 14 85 52
14 31 33 16 11 15 74 44
11 32 41 17 13 11 88 55
11 32 33 13 14 15 38 11
10 37 34 12 18 12 76 47
13 37 32 18 16 10 86 53
13 33 40 14 14 14 54 33
8 34 40 14 14 13 67 44
11 33 35 13 14 9 69 42
12 38 36 16 14 15 90 55
11 33 37 13 12 15 54 33
13 31 27 16 14 14 76 46
12 38 39 13 15 11 89 54
14 37 38 16 15 8 76 47
13 36 31 15 15 11 73 45
15 31 33 16 13 11 79 47
10 39 32 15 17 8 90 55
11 44 39 17 17 10 74 44
9 33 36 15 19 11 81 53
11 35 33 12 15 13 72 44
10 32 33 16 13 11 71 42
11 28 32 10 9 20 66 40
8 40 37 16 15 10 77 46
11 27 30 12 15 15 65 40
12 37 38 14 15 12 74 46
12 32 29 15 16 14 85 53
9 28 22 13 11 23 54 33
11 34 35 15 14 14 63 42
10 30 35 11 11 16 54 35
8 35 34 12 15 11 64 40
9 31 35 11 13 12 69 41
8 32 34 16 15 10 54 33
9 30 37 15 16 14 84 51
15 30 35 17 14 12 86 53
11 31 23 16 15 12 77 46
8 40 31 10 16 11 89 55
13 32 27 18 16 12 76 47
12 36 36 13 11 13 60 38
12 32 31 16 12 11 75 46
9 35 32 13 9 19 73 46
7 38 39 10 16 12 85 53
13 42 37 15 13 17 79 47
9 34 38 16 16 9 71 41
6 35 39 16 12 12 72 44
8 38 34 14 9 19 69 43
8 33 31 10 13 18 78 51
15 36 32 17 13 15 54 33
6 32 37 13 14 14 69 43
9 33 36 15 19 11 81 53
11 34 32 16 13 9 84 51
8 32 38 12 12 18 84 50
8 34 36 13 13 16 69 46
10 27 26 13 10 24 66 43
8 31 26 12 14 14 81 47
14 38 33 17 16 20 82 50
10 34 39 15 10 18 72 43
8 24 30 10 11 23 54 33
11 30 33 14 14 12 78 48
12 26 25 11 12 14 74 44
12 34 38 13 9 16 82 50
12 27 37 16 9 18 73 41
5 37 31 12 11 20 55 34
12 36 37 16 16 12 72 44
10 41 35 12 9 12 78 47
7 29 25 9 13 17 59 35
12 36 28 12 16 13 72 44
11 32 35 15 13 9 78 44
8 37 33 12 9 16 68 43
9 30 30 12 12 18 69 41
10 31 31 14 16 10 67 41
9 38 37 12 11 14 74 42
12 36 36 16 14 11 54 33
6 35 30 11 13 9 67 41
15 31 36 19 15 11 70 44
12 38 32 15 14 10 80 48
12 22 28 8 16 11 89 55
12 32 36 16 13 19 76 44
11 36 34 17 14 14 74 43
7 39 31 12 15 12 87 52
7 28 28 11 13 14 54 30
5 32 36 11 11 21 61 39
12 32 36 14 11 13 38 11
12 38 40 16 14 10 75 44
3 32 33 12 15 15 69 42
11 35 37 16 11 16 62 41
10 32 32 13 15 14 72 44
12 37 38 15 12 12 70 44
9 34 31 16 14 19 79 48
12 33 37 16 14 15 87 53
9 33 33 14 8 19 62 37
12 26 32 16 13 13 77 44
12 30 30 16 9 17 69 44
10 24 30 14 15 12 69 40
9 34 31 11 17 11 75 42
12 34 32 12 13 14 54 35
8 33 34 15 15 11 72 43
11 34 36 15 15 13 74 45
11 35 37 16 14 12 85 55
12 35 36 16 16 15 52 31
10 36 33 11 13 14 70 44
10 34 33 15 16 12 84 50
12 34 33 12 9 17 64 40
12 41 44 12 16 11 84 53
11 32 39 15 11 18 87 54
8 30 32 15 10 13 79 49
12 35 35 16 11 17 67 40
10 28 25 14 15 13 65 41
11 33 35 17 17 11 85 52
10 39 34 14 14 12 83 52
8 36 35 13 8 22 61 36
12 36 39 15 15 14 82 52
12 35 33 13 11 12 76 46
10 38 36 14 16 12 58 31
12 33 32 15 10 17 72 44
9 31 32 12 15 9 72 44
9 34 36 13 9 21 38 11
6 32 36 8 16 10 78 46
10 31 32 14 19 11 54 33
9 33 34 14 12 12 63 34
9 34 33 11 8 23 66 42
9 34 35 12 11 13 70 43
6 34 30 13 14 12 71 43
10 33 38 10 9 16 67 44
6 32 34 16 15 9 58 36
14 41 33 18 13 17 72 46
10 34 32 13 16 9 72 44
10 36 31 11 11 14 70 43
6 37 30 4 12 17 76 50
12 36 27 13 13 13 50 33
12 29 31 16 10 11 72 43
7 37 30 10 11 12 72 44
8 27 32 12 12 10 88 53
11 35 35 12 8 19 53 34
3 28 28 10 12 16 58 35
6 35 33 13 12 16 66 40
10 37 31 15 15 14 82 53
8 29 35 12 11 20 69 42
9 32 35 14 13 15 68 43
9 36 32 10 14 23 44 29
8 19 21 12 10 20 56 36
9 21 20 12 12 16 53 30
7 31 34 11 15 14 70 42
7 33 32 10 13 17 78 47
6 36 34 12 13 11 71 44
9 33 32 16 13 13 72 45
10 37 33 12 12 17 68 44
11 34 33 14 12 15 67 43
12 35 37 16 9 21 75 43
8 31 32 14 9 18 62 40
11 37 34 13 15 15 67 41
3 35 30 4 10 8 83 52
11 27 30 15 14 12 64 38
12 34 38 11 15 12 68 41
7 40 36 11 7 22 62 39
9 29 32 14 14 12 72 43

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time19 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 & 19 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226044&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]19 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=226044&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226044&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 time19 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 1.32525 -0.0106467Connected[t] + 0.0375201Separate[t] + 0.574624Learning[t] -0.00589175Happiness[t] -0.0103371Depression[t] + 0.0133695Sport1[t] -0.0142351Sport2[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Software[t] =  +  1.32525 -0.0106467Connected[t] +  0.0375201Separate[t] +  0.574624Learning[t] -0.00589175Happiness[t] -0.0103371Depression[t] +  0.0133695Sport1[t] -0.0142351Sport2[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226044&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Software[t] =  +  1.32525 -0.0106467Connected[t] +  0.0375201Separate[t] +  0.574624Learning[t] -0.00589175Happiness[t] -0.0103371Depression[t] +  0.0133695Sport1[t] -0.0142351Sport2[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226044&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226044&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 1.32525 -0.0106467Connected[t] + 0.0375201Separate[t] + 0.574624Learning[t] -0.00589175Happiness[t] -0.0103371Depression[t] + 0.0133695Sport1[t] -0.0142351Sport2[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.325251.877460.70590.4809090.240455
Connected-0.01064670.0339491-0.31360.7540750.377037
Separate0.03752010.03468791.0820.2804270.140213
Learning0.5746240.049047111.721.14473e-255.72366e-26
Happiness-0.005891750.0566938-0.10390.9173120.458656
Depression-0.01033710.041457-0.24930.8032930.401647
Sport10.01336950.03681060.36320.7167570.358378
Sport2-0.01423510.0549054-0.25930.7956380.397819

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 1.32525 & 1.87746 & 0.7059 & 0.480909 & 0.240455 \tabularnewline
Connected & -0.0106467 & 0.0339491 & -0.3136 & 0.754075 & 0.377037 \tabularnewline
Separate & 0.0375201 & 0.0346879 & 1.082 & 0.280427 & 0.140213 \tabularnewline
Learning & 0.574624 & 0.0490471 & 11.72 & 1.14473e-25 & 5.72366e-26 \tabularnewline
Happiness & -0.00589175 & 0.0566938 & -0.1039 & 0.917312 & 0.458656 \tabularnewline
Depression & -0.0103371 & 0.041457 & -0.2493 & 0.803293 & 0.401647 \tabularnewline
Sport1 & 0.0133695 & 0.0368106 & 0.3632 & 0.716757 & 0.358378 \tabularnewline
Sport2 & -0.0142351 & 0.0549054 & -0.2593 & 0.795638 & 0.397819 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226044&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]1.32525[/C][C]1.87746[/C][C]0.7059[/C][C]0.480909[/C][C]0.240455[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0106467[/C][C]0.0339491[/C][C]-0.3136[/C][C]0.754075[/C][C]0.377037[/C][/ROW]
[ROW][C]Separate[/C][C]0.0375201[/C][C]0.0346879[/C][C]1.082[/C][C]0.280427[/C][C]0.140213[/C][/ROW]
[ROW][C]Learning[/C][C]0.574624[/C][C]0.0490471[/C][C]11.72[/C][C]1.14473e-25[/C][C]5.72366e-26[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.00589175[/C][C]0.0566938[/C][C]-0.1039[/C][C]0.917312[/C][C]0.458656[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0103371[/C][C]0.041457[/C][C]-0.2493[/C][C]0.803293[/C][C]0.401647[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0133695[/C][C]0.0368106[/C][C]0.3632[/C][C]0.716757[/C][C]0.358378[/C][/ROW]
[ROW][C]Sport2[/C][C]-0.0142351[/C][C]0.0549054[/C][C]-0.2593[/C][C]0.795638[/C][C]0.397819[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226044&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226044&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.325251.877460.70590.4809090.240455
Connected-0.01064670.0339491-0.31360.7540750.377037
Separate0.03752010.03468791.0820.2804270.140213
Learning0.5746240.049047111.721.14473e-255.72366e-26
Happiness-0.005891750.0566938-0.10390.9173120.458656
Depression-0.01033710.041457-0.24930.8032930.401647
Sport10.01336950.03681060.36320.7167570.358378
Sport2-0.01423510.0549054-0.25930.7956380.397819






Multiple Linear Regression - Regression Statistics
Multiple R0.626468
R-squared0.392462
Adjusted R-squared0.37585
F-TEST (value)23.6247
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.83291
Sum Squared Residuals860.044

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.626468 \tabularnewline
R-squared & 0.392462 \tabularnewline
Adjusted R-squared & 0.37585 \tabularnewline
F-TEST (value) & 23.6247 \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 & 1.83291 \tabularnewline
Sum Squared Residuals & 860.044 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226044&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.626468[/C][/ROW]
[ROW][C]R-squared[/C][C]0.392462[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.37585[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]23.6247[/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]1.83291[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]860.044[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226044&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226044&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 R0.626468
R-squared0.392462
Adjusted R-squared0.37585
F-TEST (value)23.6247
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.83291
Sum Squared Residuals860.044






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1129.831152.16885
21111.4686-0.46858
31513.31191.6881
4610.9701-4.9701
51310.44622.55383
6109.654490.345511
71212.863-0.862997
81411.10922.8908
91210.45691.54307
10911.1007-2.10072
111011.4329-1.43293
121211.46920.530804
131211.51180.488224
141111.543-0.542989
151512.332.66997
161210.87781.12215
171010.8969-0.896906
181214.0329-2.03288
191112.7652-1.76518
201211.40010.599865
211111.5112-0.511202
221211.42560.574433
231313.2993-0.29932
241111.5952-0.595168
251212.075-0.0749699
261312.11240.887557
271011.6452-1.64516
281411.04012.95987
291211.57520.424792
301010.3164-0.316387
311210.96241.03757
3289.15447-1.15447
331010.2728-0.27278
341211.69780.302246
351210.30821.69179
3678.11489-1.11489
3797.981671.01833
381210.34961.65042
391011.5313-1.53134
401011.5294-1.52943
411011.4933-1.49331
421210.38351.61645
431513.6891.31097
441010.274-0.274025
451010.1385-0.138516
46128.705923.29408
471310.50422.4958
481111.0148-0.014771
491111.698-0.697975
501210.33791.66211
511411.74292.25707
521010.254-0.254048
53129.182912.81709
541311.54171.45831
5557.50222-2.50222
56610.398-4.39803
571211.49980.500185
581211.60260.39736
591111.0912-0.0912031
601011.5203-1.52029
6178.95109-1.95109
621211.57860.421418
631411.66792.33212
641110.37990.620132
651211.34980.65019
661312.30890.691112
671412.64241.35762
681112.5597-1.55972
69129.384912.61509
701211.62640.373626
7188.07019-0.0701876
721110.46860.531423
731412.94671.05333
741412.96361.03642
751211.39130.608723
76911.9092-2.90918
771311.60281.39723
781111.3642-0.364202
79129.798032.20197
801211.22090.779078
811211.71790.282086
821211.66210.337907
831210.93441.0656
841111.0034-0.00344218
851011.4746-1.47456
86910.5681-1.56807
871211.56170.438327
881211.43170.568327
891210.88651.11347
9099.32803-0.328035
911511.93183.06823
921211.83680.163192
931210.831.17004
94129.806922.19308
951011.6473-1.64728
961311.51281.48719
97911.5015-2.50154
981211.58680.413228
991010.5495-0.54954
1001411.63742.36264
1011111.5378-0.537814
1021514.00060.999431
1031110.76050.239521
1041111.7646-0.764553
105129.64622.3538
1061212.1415-0.141549
1071211.62940.370636
1081111.4874-0.487382
10979.21971-2.21971
1101211.63860.361391
1111411.57052.42951
1121112.4948-1.49478
113119.806751.19325
114109.219430.780567
1151312.67290.327119
1161310.54442.45556
117810.5614-2.56135
118119.906331.09367
1191211.64820.351828
120119.858711.14129
1211311.33631.6637
1221210.07321.92682
1231411.7272.27297
1241310.85782.14223
1251511.62423.3758
1261010.9675-0.967505
1271112.2482-1.24816
128911.0468-2.04682
129119.199771.80023
1301011.5778-1.57777
131118.027242.97276
132811.6645-3.66451
133119.115061.88494
1341210.52391.47607
1351210.8351.16504
13699.27233-0.272332
1371110.9130.0869692
138108.633441.36656
13989.20795-1.20795
14098.767490.232508
141811.5147-3.51468
142911.1715-2.17152
1431512.27652.72355
1441111.2144-0.214369
14588.00773-0.00772786
1461312.46960.530445
147129.824852.17515
1481211.50520.494843
14999.6951-0.695103
15078.29384-1.29384
1511311.02051.97949
152911.7613-2.76131
153611.7514-5.7514
154810.3021-2.30205
15587.937450.0625544
1561511.93183.06823
15769.9261-3.9261
158911.0468-2.04682
1591111.5853-0.585316
16089.46033-1.46033
16189.8098-1.8098
162109.44670.553303
16389.05289-1.05289
1641412.0111.98901
1651011.1514-1.15142
16687.891210.108793
1671110.44180.55824
168128.454883.54512
1691210.02531.97473
1701211.77330.226737
17158.96971-3.96971
1721211.64210.357852
173109.294130.705868
17477.16437-0.164365
175128.995633.00437
1761111.164-0.163974
17789.14357-1.14357
17899.10903-0.109031
1791010.3175-0.317544
18099.38635-0.386352
1811211.54270.457316
18268.54158-2.54158
1831513.37121.62878
1841210.94111.0589
185126.937565.06244
1861211.6460.353991
1871112.1363-1.1363
18879.17914-2.17914
18978.47216-1.47216
19058.63463-3.63463
1911210.53231.46772
1921211.8060.194018
19339.1994-6.1994
1941111.5499-0.549915
195109.758480.241521
1961211.09120.908775
197911.4144-2.41439
1981211.72730.272713
199910.3155-1.31548
2001211.63520.3648
2011211.39280.607164
2021010.3807-0.380743
20398.638220.361776
204129.061812.93819
205811.0174-3.01737
2061111.0594-0.0593559
2071111.6818-0.681796
2081211.50190.498071
209108.589211.41079
2101011.0138-1.01376
211129.15442.8456
212129.595712.40429
2131111.2108-0.210779
214810.9912-2.99123
2151211.54560.454379
2161010.0725-0.072505
2171112.238-1.23804
2181010.3934-0.393367
21989.75381-1.75381
2201211.14760.852404
221129.833312.16669
2221010.432-0.431969
2231210.89551.10447
22499.24619-0.246187
22599.86545-0.865452
22667.12264-1.12264
2271010.2671-0.267129
228910.4579-1.45787
22998.521920.478082
23099.29652-0.296522
23169.68958-3.68958
232108.196911.80309
233611.5358-5.53579
2341412.52561.4744
235109.782980.21702
236108.540191.45981
23764.413321.58668
238129.412872.58713
2391211.55150.448523
24077.95057-0.950574
24189.38191-1.38191
242119.142361.85764
24337.86506-4.86506
24469.73778-3.73778
2451010.8226-0.822553
24689.27826-1.27826
247910.4079-1.40787
24897.744061.25594
24988.77694-0.776945
25098.7930.207001
25178.69665-1.69665
25278.04224-1.04224
25369.24573-3.24573
254911.4796-2.47959
255109.101330.898673
2561110.30410.695944
2571211.65530.344653
258810.261-2.261
259119.745811.25419
26034.60455-1.60455
2611110.89090.109059
262128.822963.17704
26378.57605-1.57605
264910.4058-1.40584

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 9.83115 & 2.16885 \tabularnewline
2 & 11 & 11.4686 & -0.46858 \tabularnewline
3 & 15 & 13.3119 & 1.6881 \tabularnewline
4 & 6 & 10.9701 & -4.9701 \tabularnewline
5 & 13 & 10.4462 & 2.55383 \tabularnewline
6 & 10 & 9.65449 & 0.345511 \tabularnewline
7 & 12 & 12.863 & -0.862997 \tabularnewline
8 & 14 & 11.1092 & 2.8908 \tabularnewline
9 & 12 & 10.4569 & 1.54307 \tabularnewline
10 & 9 & 11.1007 & -2.10072 \tabularnewline
11 & 10 & 11.4329 & -1.43293 \tabularnewline
12 & 12 & 11.4692 & 0.530804 \tabularnewline
13 & 12 & 11.5118 & 0.488224 \tabularnewline
14 & 11 & 11.543 & -0.542989 \tabularnewline
15 & 15 & 12.33 & 2.66997 \tabularnewline
16 & 12 & 10.8778 & 1.12215 \tabularnewline
17 & 10 & 10.8969 & -0.896906 \tabularnewline
18 & 12 & 14.0329 & -2.03288 \tabularnewline
19 & 11 & 12.7652 & -1.76518 \tabularnewline
20 & 12 & 11.4001 & 0.599865 \tabularnewline
21 & 11 & 11.5112 & -0.511202 \tabularnewline
22 & 12 & 11.4256 & 0.574433 \tabularnewline
23 & 13 & 13.2993 & -0.29932 \tabularnewline
24 & 11 & 11.5952 & -0.595168 \tabularnewline
25 & 12 & 12.075 & -0.0749699 \tabularnewline
26 & 13 & 12.1124 & 0.887557 \tabularnewline
27 & 10 & 11.6452 & -1.64516 \tabularnewline
28 & 14 & 11.0401 & 2.95987 \tabularnewline
29 & 12 & 11.5752 & 0.424792 \tabularnewline
30 & 10 & 10.3164 & -0.316387 \tabularnewline
31 & 12 & 10.9624 & 1.03757 \tabularnewline
32 & 8 & 9.15447 & -1.15447 \tabularnewline
33 & 10 & 10.2728 & -0.27278 \tabularnewline
34 & 12 & 11.6978 & 0.302246 \tabularnewline
35 & 12 & 10.3082 & 1.69179 \tabularnewline
36 & 7 & 8.11489 & -1.11489 \tabularnewline
37 & 9 & 7.98167 & 1.01833 \tabularnewline
38 & 12 & 10.3496 & 1.65042 \tabularnewline
39 & 10 & 11.5313 & -1.53134 \tabularnewline
40 & 10 & 11.5294 & -1.52943 \tabularnewline
41 & 10 & 11.4933 & -1.49331 \tabularnewline
42 & 12 & 10.3835 & 1.61645 \tabularnewline
43 & 15 & 13.689 & 1.31097 \tabularnewline
44 & 10 & 10.274 & -0.274025 \tabularnewline
45 & 10 & 10.1385 & -0.138516 \tabularnewline
46 & 12 & 8.70592 & 3.29408 \tabularnewline
47 & 13 & 10.5042 & 2.4958 \tabularnewline
48 & 11 & 11.0148 & -0.014771 \tabularnewline
49 & 11 & 11.698 & -0.697975 \tabularnewline
50 & 12 & 10.3379 & 1.66211 \tabularnewline
51 & 14 & 11.7429 & 2.25707 \tabularnewline
52 & 10 & 10.254 & -0.254048 \tabularnewline
53 & 12 & 9.18291 & 2.81709 \tabularnewline
54 & 13 & 11.5417 & 1.45831 \tabularnewline
55 & 5 & 7.50222 & -2.50222 \tabularnewline
56 & 6 & 10.398 & -4.39803 \tabularnewline
57 & 12 & 11.4998 & 0.500185 \tabularnewline
58 & 12 & 11.6026 & 0.39736 \tabularnewline
59 & 11 & 11.0912 & -0.0912031 \tabularnewline
60 & 10 & 11.5203 & -1.52029 \tabularnewline
61 & 7 & 8.95109 & -1.95109 \tabularnewline
62 & 12 & 11.5786 & 0.421418 \tabularnewline
63 & 14 & 11.6679 & 2.33212 \tabularnewline
64 & 11 & 10.3799 & 0.620132 \tabularnewline
65 & 12 & 11.3498 & 0.65019 \tabularnewline
66 & 13 & 12.3089 & 0.691112 \tabularnewline
67 & 14 & 12.6424 & 1.35762 \tabularnewline
68 & 11 & 12.5597 & -1.55972 \tabularnewline
69 & 12 & 9.38491 & 2.61509 \tabularnewline
70 & 12 & 11.6264 & 0.373626 \tabularnewline
71 & 8 & 8.07019 & -0.0701876 \tabularnewline
72 & 11 & 10.4686 & 0.531423 \tabularnewline
73 & 14 & 12.9467 & 1.05333 \tabularnewline
74 & 14 & 12.9636 & 1.03642 \tabularnewline
75 & 12 & 11.3913 & 0.608723 \tabularnewline
76 & 9 & 11.9092 & -2.90918 \tabularnewline
77 & 13 & 11.6028 & 1.39723 \tabularnewline
78 & 11 & 11.3642 & -0.364202 \tabularnewline
79 & 12 & 9.79803 & 2.20197 \tabularnewline
80 & 12 & 11.2209 & 0.779078 \tabularnewline
81 & 12 & 11.7179 & 0.282086 \tabularnewline
82 & 12 & 11.6621 & 0.337907 \tabularnewline
83 & 12 & 10.9344 & 1.0656 \tabularnewline
84 & 11 & 11.0034 & -0.00344218 \tabularnewline
85 & 10 & 11.4746 & -1.47456 \tabularnewline
86 & 9 & 10.5681 & -1.56807 \tabularnewline
87 & 12 & 11.5617 & 0.438327 \tabularnewline
88 & 12 & 11.4317 & 0.568327 \tabularnewline
89 & 12 & 10.8865 & 1.11347 \tabularnewline
90 & 9 & 9.32803 & -0.328035 \tabularnewline
91 & 15 & 11.9318 & 3.06823 \tabularnewline
92 & 12 & 11.8368 & 0.163192 \tabularnewline
93 & 12 & 10.83 & 1.17004 \tabularnewline
94 & 12 & 9.80692 & 2.19308 \tabularnewline
95 & 10 & 11.6473 & -1.64728 \tabularnewline
96 & 13 & 11.5128 & 1.48719 \tabularnewline
97 & 9 & 11.5015 & -2.50154 \tabularnewline
98 & 12 & 11.5868 & 0.413228 \tabularnewline
99 & 10 & 10.5495 & -0.54954 \tabularnewline
100 & 14 & 11.6374 & 2.36264 \tabularnewline
101 & 11 & 11.5378 & -0.537814 \tabularnewline
102 & 15 & 14.0006 & 0.999431 \tabularnewline
103 & 11 & 10.7605 & 0.239521 \tabularnewline
104 & 11 & 11.7646 & -0.764553 \tabularnewline
105 & 12 & 9.6462 & 2.3538 \tabularnewline
106 & 12 & 12.1415 & -0.141549 \tabularnewline
107 & 12 & 11.6294 & 0.370636 \tabularnewline
108 & 11 & 11.4874 & -0.487382 \tabularnewline
109 & 7 & 9.21971 & -2.21971 \tabularnewline
110 & 12 & 11.6386 & 0.361391 \tabularnewline
111 & 14 & 11.5705 & 2.42951 \tabularnewline
112 & 11 & 12.4948 & -1.49478 \tabularnewline
113 & 11 & 9.80675 & 1.19325 \tabularnewline
114 & 10 & 9.21943 & 0.780567 \tabularnewline
115 & 13 & 12.6729 & 0.327119 \tabularnewline
116 & 13 & 10.5444 & 2.45556 \tabularnewline
117 & 8 & 10.5614 & -2.56135 \tabularnewline
118 & 11 & 9.90633 & 1.09367 \tabularnewline
119 & 12 & 11.6482 & 0.351828 \tabularnewline
120 & 11 & 9.85871 & 1.14129 \tabularnewline
121 & 13 & 11.3363 & 1.6637 \tabularnewline
122 & 12 & 10.0732 & 1.92682 \tabularnewline
123 & 14 & 11.727 & 2.27297 \tabularnewline
124 & 13 & 10.8578 & 2.14223 \tabularnewline
125 & 15 & 11.6242 & 3.3758 \tabularnewline
126 & 10 & 10.9675 & -0.967505 \tabularnewline
127 & 11 & 12.2482 & -1.24816 \tabularnewline
128 & 9 & 11.0468 & -2.04682 \tabularnewline
129 & 11 & 9.19977 & 1.80023 \tabularnewline
130 & 10 & 11.5778 & -1.57777 \tabularnewline
131 & 11 & 8.02724 & 2.97276 \tabularnewline
132 & 8 & 11.6645 & -3.66451 \tabularnewline
133 & 11 & 9.11506 & 1.88494 \tabularnewline
134 & 12 & 10.5239 & 1.47607 \tabularnewline
135 & 12 & 10.835 & 1.16504 \tabularnewline
136 & 9 & 9.27233 & -0.272332 \tabularnewline
137 & 11 & 10.913 & 0.0869692 \tabularnewline
138 & 10 & 8.63344 & 1.36656 \tabularnewline
139 & 8 & 9.20795 & -1.20795 \tabularnewline
140 & 9 & 8.76749 & 0.232508 \tabularnewline
141 & 8 & 11.5147 & -3.51468 \tabularnewline
142 & 9 & 11.1715 & -2.17152 \tabularnewline
143 & 15 & 12.2765 & 2.72355 \tabularnewline
144 & 11 & 11.2144 & -0.214369 \tabularnewline
145 & 8 & 8.00773 & -0.00772786 \tabularnewline
146 & 13 & 12.4696 & 0.530445 \tabularnewline
147 & 12 & 9.82485 & 2.17515 \tabularnewline
148 & 12 & 11.5052 & 0.494843 \tabularnewline
149 & 9 & 9.6951 & -0.695103 \tabularnewline
150 & 7 & 8.29384 & -1.29384 \tabularnewline
151 & 13 & 11.0205 & 1.97949 \tabularnewline
152 & 9 & 11.7613 & -2.76131 \tabularnewline
153 & 6 & 11.7514 & -5.7514 \tabularnewline
154 & 8 & 10.3021 & -2.30205 \tabularnewline
155 & 8 & 7.93745 & 0.0625544 \tabularnewline
156 & 15 & 11.9318 & 3.06823 \tabularnewline
157 & 6 & 9.9261 & -3.9261 \tabularnewline
158 & 9 & 11.0468 & -2.04682 \tabularnewline
159 & 11 & 11.5853 & -0.585316 \tabularnewline
160 & 8 & 9.46033 & -1.46033 \tabularnewline
161 & 8 & 9.8098 & -1.8098 \tabularnewline
162 & 10 & 9.4467 & 0.553303 \tabularnewline
163 & 8 & 9.05289 & -1.05289 \tabularnewline
164 & 14 & 12.011 & 1.98901 \tabularnewline
165 & 10 & 11.1514 & -1.15142 \tabularnewline
166 & 8 & 7.89121 & 0.108793 \tabularnewline
167 & 11 & 10.4418 & 0.55824 \tabularnewline
168 & 12 & 8.45488 & 3.54512 \tabularnewline
169 & 12 & 10.0253 & 1.97473 \tabularnewline
170 & 12 & 11.7733 & 0.226737 \tabularnewline
171 & 5 & 8.96971 & -3.96971 \tabularnewline
172 & 12 & 11.6421 & 0.357852 \tabularnewline
173 & 10 & 9.29413 & 0.705868 \tabularnewline
174 & 7 & 7.16437 & -0.164365 \tabularnewline
175 & 12 & 8.99563 & 3.00437 \tabularnewline
176 & 11 & 11.164 & -0.163974 \tabularnewline
177 & 8 & 9.14357 & -1.14357 \tabularnewline
178 & 9 & 9.10903 & -0.109031 \tabularnewline
179 & 10 & 10.3175 & -0.317544 \tabularnewline
180 & 9 & 9.38635 & -0.386352 \tabularnewline
181 & 12 & 11.5427 & 0.457316 \tabularnewline
182 & 6 & 8.54158 & -2.54158 \tabularnewline
183 & 15 & 13.3712 & 1.62878 \tabularnewline
184 & 12 & 10.9411 & 1.0589 \tabularnewline
185 & 12 & 6.93756 & 5.06244 \tabularnewline
186 & 12 & 11.646 & 0.353991 \tabularnewline
187 & 11 & 12.1363 & -1.1363 \tabularnewline
188 & 7 & 9.17914 & -2.17914 \tabularnewline
189 & 7 & 8.47216 & -1.47216 \tabularnewline
190 & 5 & 8.63463 & -3.63463 \tabularnewline
191 & 12 & 10.5323 & 1.46772 \tabularnewline
192 & 12 & 11.806 & 0.194018 \tabularnewline
193 & 3 & 9.1994 & -6.1994 \tabularnewline
194 & 11 & 11.5499 & -0.549915 \tabularnewline
195 & 10 & 9.75848 & 0.241521 \tabularnewline
196 & 12 & 11.0912 & 0.908775 \tabularnewline
197 & 9 & 11.4144 & -2.41439 \tabularnewline
198 & 12 & 11.7273 & 0.272713 \tabularnewline
199 & 9 & 10.3155 & -1.31548 \tabularnewline
200 & 12 & 11.6352 & 0.3648 \tabularnewline
201 & 12 & 11.3928 & 0.607164 \tabularnewline
202 & 10 & 10.3807 & -0.380743 \tabularnewline
203 & 9 & 8.63822 & 0.361776 \tabularnewline
204 & 12 & 9.06181 & 2.93819 \tabularnewline
205 & 8 & 11.0174 & -3.01737 \tabularnewline
206 & 11 & 11.0594 & -0.0593559 \tabularnewline
207 & 11 & 11.6818 & -0.681796 \tabularnewline
208 & 12 & 11.5019 & 0.498071 \tabularnewline
209 & 10 & 8.58921 & 1.41079 \tabularnewline
210 & 10 & 11.0138 & -1.01376 \tabularnewline
211 & 12 & 9.1544 & 2.8456 \tabularnewline
212 & 12 & 9.59571 & 2.40429 \tabularnewline
213 & 11 & 11.2108 & -0.210779 \tabularnewline
214 & 8 & 10.9912 & -2.99123 \tabularnewline
215 & 12 & 11.5456 & 0.454379 \tabularnewline
216 & 10 & 10.0725 & -0.072505 \tabularnewline
217 & 11 & 12.238 & -1.23804 \tabularnewline
218 & 10 & 10.3934 & -0.393367 \tabularnewline
219 & 8 & 9.75381 & -1.75381 \tabularnewline
220 & 12 & 11.1476 & 0.852404 \tabularnewline
221 & 12 & 9.83331 & 2.16669 \tabularnewline
222 & 10 & 10.432 & -0.431969 \tabularnewline
223 & 12 & 10.8955 & 1.10447 \tabularnewline
224 & 9 & 9.24619 & -0.246187 \tabularnewline
225 & 9 & 9.86545 & -0.865452 \tabularnewline
226 & 6 & 7.12264 & -1.12264 \tabularnewline
227 & 10 & 10.2671 & -0.267129 \tabularnewline
228 & 9 & 10.4579 & -1.45787 \tabularnewline
229 & 9 & 8.52192 & 0.478082 \tabularnewline
230 & 9 & 9.29652 & -0.296522 \tabularnewline
231 & 6 & 9.68958 & -3.68958 \tabularnewline
232 & 10 & 8.19691 & 1.80309 \tabularnewline
233 & 6 & 11.5358 & -5.53579 \tabularnewline
234 & 14 & 12.5256 & 1.4744 \tabularnewline
235 & 10 & 9.78298 & 0.21702 \tabularnewline
236 & 10 & 8.54019 & 1.45981 \tabularnewline
237 & 6 & 4.41332 & 1.58668 \tabularnewline
238 & 12 & 9.41287 & 2.58713 \tabularnewline
239 & 12 & 11.5515 & 0.448523 \tabularnewline
240 & 7 & 7.95057 & -0.950574 \tabularnewline
241 & 8 & 9.38191 & -1.38191 \tabularnewline
242 & 11 & 9.14236 & 1.85764 \tabularnewline
243 & 3 & 7.86506 & -4.86506 \tabularnewline
244 & 6 & 9.73778 & -3.73778 \tabularnewline
245 & 10 & 10.8226 & -0.822553 \tabularnewline
246 & 8 & 9.27826 & -1.27826 \tabularnewline
247 & 9 & 10.4079 & -1.40787 \tabularnewline
248 & 9 & 7.74406 & 1.25594 \tabularnewline
249 & 8 & 8.77694 & -0.776945 \tabularnewline
250 & 9 & 8.793 & 0.207001 \tabularnewline
251 & 7 & 8.69665 & -1.69665 \tabularnewline
252 & 7 & 8.04224 & -1.04224 \tabularnewline
253 & 6 & 9.24573 & -3.24573 \tabularnewline
254 & 9 & 11.4796 & -2.47959 \tabularnewline
255 & 10 & 9.10133 & 0.898673 \tabularnewline
256 & 11 & 10.3041 & 0.695944 \tabularnewline
257 & 12 & 11.6553 & 0.344653 \tabularnewline
258 & 8 & 10.261 & -2.261 \tabularnewline
259 & 11 & 9.74581 & 1.25419 \tabularnewline
260 & 3 & 4.60455 & -1.60455 \tabularnewline
261 & 11 & 10.8909 & 0.109059 \tabularnewline
262 & 12 & 8.82296 & 3.17704 \tabularnewline
263 & 7 & 8.57605 & -1.57605 \tabularnewline
264 & 9 & 10.4058 & -1.40584 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226044&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]9.83115[/C][C]2.16885[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]11.4686[/C][C]-0.46858[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]13.3119[/C][C]1.6881[/C][/ROW]
[ROW][C]4[/C][C]6[/C][C]10.9701[/C][C]-4.9701[/C][/ROW]
[ROW][C]5[/C][C]13[/C][C]10.4462[/C][C]2.55383[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]9.65449[/C][C]0.345511[/C][/ROW]
[ROW][C]7[/C][C]12[/C][C]12.863[/C][C]-0.862997[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]11.1092[/C][C]2.8908[/C][/ROW]
[ROW][C]9[/C][C]12[/C][C]10.4569[/C][C]1.54307[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]11.1007[/C][C]-2.10072[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]11.4329[/C][C]-1.43293[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]11.4692[/C][C]0.530804[/C][/ROW]
[ROW][C]13[/C][C]12[/C][C]11.5118[/C][C]0.488224[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]11.543[/C][C]-0.542989[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]12.33[/C][C]2.66997[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]10.8778[/C][C]1.12215[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]10.8969[/C][C]-0.896906[/C][/ROW]
[ROW][C]18[/C][C]12[/C][C]14.0329[/C][C]-2.03288[/C][/ROW]
[ROW][C]19[/C][C]11[/C][C]12.7652[/C][C]-1.76518[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]11.4001[/C][C]0.599865[/C][/ROW]
[ROW][C]21[/C][C]11[/C][C]11.5112[/C][C]-0.511202[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]11.4256[/C][C]0.574433[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]13.2993[/C][C]-0.29932[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]11.5952[/C][C]-0.595168[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]12.075[/C][C]-0.0749699[/C][/ROW]
[ROW][C]26[/C][C]13[/C][C]12.1124[/C][C]0.887557[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]11.6452[/C][C]-1.64516[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]11.0401[/C][C]2.95987[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]11.5752[/C][C]0.424792[/C][/ROW]
[ROW][C]30[/C][C]10[/C][C]10.3164[/C][C]-0.316387[/C][/ROW]
[ROW][C]31[/C][C]12[/C][C]10.9624[/C][C]1.03757[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]9.15447[/C][C]-1.15447[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.2728[/C][C]-0.27278[/C][/ROW]
[ROW][C]34[/C][C]12[/C][C]11.6978[/C][C]0.302246[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.3082[/C][C]1.69179[/C][/ROW]
[ROW][C]36[/C][C]7[/C][C]8.11489[/C][C]-1.11489[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]7.98167[/C][C]1.01833[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]10.3496[/C][C]1.65042[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]11.5313[/C][C]-1.53134[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]11.5294[/C][C]-1.52943[/C][/ROW]
[ROW][C]41[/C][C]10[/C][C]11.4933[/C][C]-1.49331[/C][/ROW]
[ROW][C]42[/C][C]12[/C][C]10.3835[/C][C]1.61645[/C][/ROW]
[ROW][C]43[/C][C]15[/C][C]13.689[/C][C]1.31097[/C][/ROW]
[ROW][C]44[/C][C]10[/C][C]10.274[/C][C]-0.274025[/C][/ROW]
[ROW][C]45[/C][C]10[/C][C]10.1385[/C][C]-0.138516[/C][/ROW]
[ROW][C]46[/C][C]12[/C][C]8.70592[/C][C]3.29408[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]10.5042[/C][C]2.4958[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.0148[/C][C]-0.014771[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]11.698[/C][C]-0.697975[/C][/ROW]
[ROW][C]50[/C][C]12[/C][C]10.3379[/C][C]1.66211[/C][/ROW]
[ROW][C]51[/C][C]14[/C][C]11.7429[/C][C]2.25707[/C][/ROW]
[ROW][C]52[/C][C]10[/C][C]10.254[/C][C]-0.254048[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]9.18291[/C][C]2.81709[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.5417[/C][C]1.45831[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]7.50222[/C][C]-2.50222[/C][/ROW]
[ROW][C]56[/C][C]6[/C][C]10.398[/C][C]-4.39803[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]11.4998[/C][C]0.500185[/C][/ROW]
[ROW][C]58[/C][C]12[/C][C]11.6026[/C][C]0.39736[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]11.0912[/C][C]-0.0912031[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]11.5203[/C][C]-1.52029[/C][/ROW]
[ROW][C]61[/C][C]7[/C][C]8.95109[/C][C]-1.95109[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]11.5786[/C][C]0.421418[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]11.6679[/C][C]2.33212[/C][/ROW]
[ROW][C]64[/C][C]11[/C][C]10.3799[/C][C]0.620132[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]11.3498[/C][C]0.65019[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]12.3089[/C][C]0.691112[/C][/ROW]
[ROW][C]67[/C][C]14[/C][C]12.6424[/C][C]1.35762[/C][/ROW]
[ROW][C]68[/C][C]11[/C][C]12.5597[/C][C]-1.55972[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]9.38491[/C][C]2.61509[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]11.6264[/C][C]0.373626[/C][/ROW]
[ROW][C]71[/C][C]8[/C][C]8.07019[/C][C]-0.0701876[/C][/ROW]
[ROW][C]72[/C][C]11[/C][C]10.4686[/C][C]0.531423[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]12.9467[/C][C]1.05333[/C][/ROW]
[ROW][C]74[/C][C]14[/C][C]12.9636[/C][C]1.03642[/C][/ROW]
[ROW][C]75[/C][C]12[/C][C]11.3913[/C][C]0.608723[/C][/ROW]
[ROW][C]76[/C][C]9[/C][C]11.9092[/C][C]-2.90918[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.6028[/C][C]1.39723[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]11.3642[/C][C]-0.364202[/C][/ROW]
[ROW][C]79[/C][C]12[/C][C]9.79803[/C][C]2.20197[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]11.2209[/C][C]0.779078[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]11.7179[/C][C]0.282086[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]11.6621[/C][C]0.337907[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]10.9344[/C][C]1.0656[/C][/ROW]
[ROW][C]84[/C][C]11[/C][C]11.0034[/C][C]-0.00344218[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]11.4746[/C][C]-1.47456[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]10.5681[/C][C]-1.56807[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]11.5617[/C][C]0.438327[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.4317[/C][C]0.568327[/C][/ROW]
[ROW][C]89[/C][C]12[/C][C]10.8865[/C][C]1.11347[/C][/ROW]
[ROW][C]90[/C][C]9[/C][C]9.32803[/C][C]-0.328035[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]11.9318[/C][C]3.06823[/C][/ROW]
[ROW][C]92[/C][C]12[/C][C]11.8368[/C][C]0.163192[/C][/ROW]
[ROW][C]93[/C][C]12[/C][C]10.83[/C][C]1.17004[/C][/ROW]
[ROW][C]94[/C][C]12[/C][C]9.80692[/C][C]2.19308[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]11.6473[/C][C]-1.64728[/C][/ROW]
[ROW][C]96[/C][C]13[/C][C]11.5128[/C][C]1.48719[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]11.5015[/C][C]-2.50154[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]11.5868[/C][C]0.413228[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]10.5495[/C][C]-0.54954[/C][/ROW]
[ROW][C]100[/C][C]14[/C][C]11.6374[/C][C]2.36264[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]11.5378[/C][C]-0.537814[/C][/ROW]
[ROW][C]102[/C][C]15[/C][C]14.0006[/C][C]0.999431[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]10.7605[/C][C]0.239521[/C][/ROW]
[ROW][C]104[/C][C]11[/C][C]11.7646[/C][C]-0.764553[/C][/ROW]
[ROW][C]105[/C][C]12[/C][C]9.6462[/C][C]2.3538[/C][/ROW]
[ROW][C]106[/C][C]12[/C][C]12.1415[/C][C]-0.141549[/C][/ROW]
[ROW][C]107[/C][C]12[/C][C]11.6294[/C][C]0.370636[/C][/ROW]
[ROW][C]108[/C][C]11[/C][C]11.4874[/C][C]-0.487382[/C][/ROW]
[ROW][C]109[/C][C]7[/C][C]9.21971[/C][C]-2.21971[/C][/ROW]
[ROW][C]110[/C][C]12[/C][C]11.6386[/C][C]0.361391[/C][/ROW]
[ROW][C]111[/C][C]14[/C][C]11.5705[/C][C]2.42951[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.4948[/C][C]-1.49478[/C][/ROW]
[ROW][C]113[/C][C]11[/C][C]9.80675[/C][C]1.19325[/C][/ROW]
[ROW][C]114[/C][C]10[/C][C]9.21943[/C][C]0.780567[/C][/ROW]
[ROW][C]115[/C][C]13[/C][C]12.6729[/C][C]0.327119[/C][/ROW]
[ROW][C]116[/C][C]13[/C][C]10.5444[/C][C]2.45556[/C][/ROW]
[ROW][C]117[/C][C]8[/C][C]10.5614[/C][C]-2.56135[/C][/ROW]
[ROW][C]118[/C][C]11[/C][C]9.90633[/C][C]1.09367[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]11.6482[/C][C]0.351828[/C][/ROW]
[ROW][C]120[/C][C]11[/C][C]9.85871[/C][C]1.14129[/C][/ROW]
[ROW][C]121[/C][C]13[/C][C]11.3363[/C][C]1.6637[/C][/ROW]
[ROW][C]122[/C][C]12[/C][C]10.0732[/C][C]1.92682[/C][/ROW]
[ROW][C]123[/C][C]14[/C][C]11.727[/C][C]2.27297[/C][/ROW]
[ROW][C]124[/C][C]13[/C][C]10.8578[/C][C]2.14223[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]11.6242[/C][C]3.3758[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]10.9675[/C][C]-0.967505[/C][/ROW]
[ROW][C]127[/C][C]11[/C][C]12.2482[/C][C]-1.24816[/C][/ROW]
[ROW][C]128[/C][C]9[/C][C]11.0468[/C][C]-2.04682[/C][/ROW]
[ROW][C]129[/C][C]11[/C][C]9.19977[/C][C]1.80023[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]11.5778[/C][C]-1.57777[/C][/ROW]
[ROW][C]131[/C][C]11[/C][C]8.02724[/C][C]2.97276[/C][/ROW]
[ROW][C]132[/C][C]8[/C][C]11.6645[/C][C]-3.66451[/C][/ROW]
[ROW][C]133[/C][C]11[/C][C]9.11506[/C][C]1.88494[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]10.5239[/C][C]1.47607[/C][/ROW]
[ROW][C]135[/C][C]12[/C][C]10.835[/C][C]1.16504[/C][/ROW]
[ROW][C]136[/C][C]9[/C][C]9.27233[/C][C]-0.272332[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]10.913[/C][C]0.0869692[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]8.63344[/C][C]1.36656[/C][/ROW]
[ROW][C]139[/C][C]8[/C][C]9.20795[/C][C]-1.20795[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]8.76749[/C][C]0.232508[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]11.5147[/C][C]-3.51468[/C][/ROW]
[ROW][C]142[/C][C]9[/C][C]11.1715[/C][C]-2.17152[/C][/ROW]
[ROW][C]143[/C][C]15[/C][C]12.2765[/C][C]2.72355[/C][/ROW]
[ROW][C]144[/C][C]11[/C][C]11.2144[/C][C]-0.214369[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]8.00773[/C][C]-0.00772786[/C][/ROW]
[ROW][C]146[/C][C]13[/C][C]12.4696[/C][C]0.530445[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]9.82485[/C][C]2.17515[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]11.5052[/C][C]0.494843[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]9.6951[/C][C]-0.695103[/C][/ROW]
[ROW][C]150[/C][C]7[/C][C]8.29384[/C][C]-1.29384[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]11.0205[/C][C]1.97949[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.7613[/C][C]-2.76131[/C][/ROW]
[ROW][C]153[/C][C]6[/C][C]11.7514[/C][C]-5.7514[/C][/ROW]
[ROW][C]154[/C][C]8[/C][C]10.3021[/C][C]-2.30205[/C][/ROW]
[ROW][C]155[/C][C]8[/C][C]7.93745[/C][C]0.0625544[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]11.9318[/C][C]3.06823[/C][/ROW]
[ROW][C]157[/C][C]6[/C][C]9.9261[/C][C]-3.9261[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]11.0468[/C][C]-2.04682[/C][/ROW]
[ROW][C]159[/C][C]11[/C][C]11.5853[/C][C]-0.585316[/C][/ROW]
[ROW][C]160[/C][C]8[/C][C]9.46033[/C][C]-1.46033[/C][/ROW]
[ROW][C]161[/C][C]8[/C][C]9.8098[/C][C]-1.8098[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.4467[/C][C]0.553303[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]9.05289[/C][C]-1.05289[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]12.011[/C][C]1.98901[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.1514[/C][C]-1.15142[/C][/ROW]
[ROW][C]166[/C][C]8[/C][C]7.89121[/C][C]0.108793[/C][/ROW]
[ROW][C]167[/C][C]11[/C][C]10.4418[/C][C]0.55824[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]8.45488[/C][C]3.54512[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]10.0253[/C][C]1.97473[/C][/ROW]
[ROW][C]170[/C][C]12[/C][C]11.7733[/C][C]0.226737[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]8.96971[/C][C]-3.96971[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.6421[/C][C]0.357852[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]9.29413[/C][C]0.705868[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]7.16437[/C][C]-0.164365[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]8.99563[/C][C]3.00437[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]11.164[/C][C]-0.163974[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]9.14357[/C][C]-1.14357[/C][/ROW]
[ROW][C]178[/C][C]9[/C][C]9.10903[/C][C]-0.109031[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]10.3175[/C][C]-0.317544[/C][/ROW]
[ROW][C]180[/C][C]9[/C][C]9.38635[/C][C]-0.386352[/C][/ROW]
[ROW][C]181[/C][C]12[/C][C]11.5427[/C][C]0.457316[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]8.54158[/C][C]-2.54158[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]13.3712[/C][C]1.62878[/C][/ROW]
[ROW][C]184[/C][C]12[/C][C]10.9411[/C][C]1.0589[/C][/ROW]
[ROW][C]185[/C][C]12[/C][C]6.93756[/C][C]5.06244[/C][/ROW]
[ROW][C]186[/C][C]12[/C][C]11.646[/C][C]0.353991[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]12.1363[/C][C]-1.1363[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]9.17914[/C][C]-2.17914[/C][/ROW]
[ROW][C]189[/C][C]7[/C][C]8.47216[/C][C]-1.47216[/C][/ROW]
[ROW][C]190[/C][C]5[/C][C]8.63463[/C][C]-3.63463[/C][/ROW]
[ROW][C]191[/C][C]12[/C][C]10.5323[/C][C]1.46772[/C][/ROW]
[ROW][C]192[/C][C]12[/C][C]11.806[/C][C]0.194018[/C][/ROW]
[ROW][C]193[/C][C]3[/C][C]9.1994[/C][C]-6.1994[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]11.5499[/C][C]-0.549915[/C][/ROW]
[ROW][C]195[/C][C]10[/C][C]9.75848[/C][C]0.241521[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]11.0912[/C][C]0.908775[/C][/ROW]
[ROW][C]197[/C][C]9[/C][C]11.4144[/C][C]-2.41439[/C][/ROW]
[ROW][C]198[/C][C]12[/C][C]11.7273[/C][C]0.272713[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]10.3155[/C][C]-1.31548[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]11.6352[/C][C]0.3648[/C][/ROW]
[ROW][C]201[/C][C]12[/C][C]11.3928[/C][C]0.607164[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]10.3807[/C][C]-0.380743[/C][/ROW]
[ROW][C]203[/C][C]9[/C][C]8.63822[/C][C]0.361776[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]9.06181[/C][C]2.93819[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]11.0174[/C][C]-3.01737[/C][/ROW]
[ROW][C]206[/C][C]11[/C][C]11.0594[/C][C]-0.0593559[/C][/ROW]
[ROW][C]207[/C][C]11[/C][C]11.6818[/C][C]-0.681796[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]11.5019[/C][C]0.498071[/C][/ROW]
[ROW][C]209[/C][C]10[/C][C]8.58921[/C][C]1.41079[/C][/ROW]
[ROW][C]210[/C][C]10[/C][C]11.0138[/C][C]-1.01376[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]9.1544[/C][C]2.8456[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]9.59571[/C][C]2.40429[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.2108[/C][C]-0.210779[/C][/ROW]
[ROW][C]214[/C][C]8[/C][C]10.9912[/C][C]-2.99123[/C][/ROW]
[ROW][C]215[/C][C]12[/C][C]11.5456[/C][C]0.454379[/C][/ROW]
[ROW][C]216[/C][C]10[/C][C]10.0725[/C][C]-0.072505[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]12.238[/C][C]-1.23804[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]10.3934[/C][C]-0.393367[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.75381[/C][C]-1.75381[/C][/ROW]
[ROW][C]220[/C][C]12[/C][C]11.1476[/C][C]0.852404[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]9.83331[/C][C]2.16669[/C][/ROW]
[ROW][C]222[/C][C]10[/C][C]10.432[/C][C]-0.431969[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]10.8955[/C][C]1.10447[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]9.24619[/C][C]-0.246187[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.86545[/C][C]-0.865452[/C][/ROW]
[ROW][C]226[/C][C]6[/C][C]7.12264[/C][C]-1.12264[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]10.2671[/C][C]-0.267129[/C][/ROW]
[ROW][C]228[/C][C]9[/C][C]10.4579[/C][C]-1.45787[/C][/ROW]
[ROW][C]229[/C][C]9[/C][C]8.52192[/C][C]0.478082[/C][/ROW]
[ROW][C]230[/C][C]9[/C][C]9.29652[/C][C]-0.296522[/C][/ROW]
[ROW][C]231[/C][C]6[/C][C]9.68958[/C][C]-3.68958[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]8.19691[/C][C]1.80309[/C][/ROW]
[ROW][C]233[/C][C]6[/C][C]11.5358[/C][C]-5.53579[/C][/ROW]
[ROW][C]234[/C][C]14[/C][C]12.5256[/C][C]1.4744[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]9.78298[/C][C]0.21702[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]8.54019[/C][C]1.45981[/C][/ROW]
[ROW][C]237[/C][C]6[/C][C]4.41332[/C][C]1.58668[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]9.41287[/C][C]2.58713[/C][/ROW]
[ROW][C]239[/C][C]12[/C][C]11.5515[/C][C]0.448523[/C][/ROW]
[ROW][C]240[/C][C]7[/C][C]7.95057[/C][C]-0.950574[/C][/ROW]
[ROW][C]241[/C][C]8[/C][C]9.38191[/C][C]-1.38191[/C][/ROW]
[ROW][C]242[/C][C]11[/C][C]9.14236[/C][C]1.85764[/C][/ROW]
[ROW][C]243[/C][C]3[/C][C]7.86506[/C][C]-4.86506[/C][/ROW]
[ROW][C]244[/C][C]6[/C][C]9.73778[/C][C]-3.73778[/C][/ROW]
[ROW][C]245[/C][C]10[/C][C]10.8226[/C][C]-0.822553[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]9.27826[/C][C]-1.27826[/C][/ROW]
[ROW][C]247[/C][C]9[/C][C]10.4079[/C][C]-1.40787[/C][/ROW]
[ROW][C]248[/C][C]9[/C][C]7.74406[/C][C]1.25594[/C][/ROW]
[ROW][C]249[/C][C]8[/C][C]8.77694[/C][C]-0.776945[/C][/ROW]
[ROW][C]250[/C][C]9[/C][C]8.793[/C][C]0.207001[/C][/ROW]
[ROW][C]251[/C][C]7[/C][C]8.69665[/C][C]-1.69665[/C][/ROW]
[ROW][C]252[/C][C]7[/C][C]8.04224[/C][C]-1.04224[/C][/ROW]
[ROW][C]253[/C][C]6[/C][C]9.24573[/C][C]-3.24573[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]11.4796[/C][C]-2.47959[/C][/ROW]
[ROW][C]255[/C][C]10[/C][C]9.10133[/C][C]0.898673[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]10.3041[/C][C]0.695944[/C][/ROW]
[ROW][C]257[/C][C]12[/C][C]11.6553[/C][C]0.344653[/C][/ROW]
[ROW][C]258[/C][C]8[/C][C]10.261[/C][C]-2.261[/C][/ROW]
[ROW][C]259[/C][C]11[/C][C]9.74581[/C][C]1.25419[/C][/ROW]
[ROW][C]260[/C][C]3[/C][C]4.60455[/C][C]-1.60455[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]10.8909[/C][C]0.109059[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]8.82296[/C][C]3.17704[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]8.57605[/C][C]-1.57605[/C][/ROW]
[ROW][C]264[/C][C]9[/C][C]10.4058[/C][C]-1.40584[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226044&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226044&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
1129.831152.16885
21111.4686-0.46858
31513.31191.6881
4610.9701-4.9701
51310.44622.55383
6109.654490.345511
71212.863-0.862997
81411.10922.8908
91210.45691.54307
10911.1007-2.10072
111011.4329-1.43293
121211.46920.530804
131211.51180.488224
141111.543-0.542989
151512.332.66997
161210.87781.12215
171010.8969-0.896906
181214.0329-2.03288
191112.7652-1.76518
201211.40010.599865
211111.5112-0.511202
221211.42560.574433
231313.2993-0.29932
241111.5952-0.595168
251212.075-0.0749699
261312.11240.887557
271011.6452-1.64516
281411.04012.95987
291211.57520.424792
301010.3164-0.316387
311210.96241.03757
3289.15447-1.15447
331010.2728-0.27278
341211.69780.302246
351210.30821.69179
3678.11489-1.11489
3797.981671.01833
381210.34961.65042
391011.5313-1.53134
401011.5294-1.52943
411011.4933-1.49331
421210.38351.61645
431513.6891.31097
441010.274-0.274025
451010.1385-0.138516
46128.705923.29408
471310.50422.4958
481111.0148-0.014771
491111.698-0.697975
501210.33791.66211
511411.74292.25707
521010.254-0.254048
53129.182912.81709
541311.54171.45831
5557.50222-2.50222
56610.398-4.39803
571211.49980.500185
581211.60260.39736
591111.0912-0.0912031
601011.5203-1.52029
6178.95109-1.95109
621211.57860.421418
631411.66792.33212
641110.37990.620132
651211.34980.65019
661312.30890.691112
671412.64241.35762
681112.5597-1.55972
69129.384912.61509
701211.62640.373626
7188.07019-0.0701876
721110.46860.531423
731412.94671.05333
741412.96361.03642
751211.39130.608723
76911.9092-2.90918
771311.60281.39723
781111.3642-0.364202
79129.798032.20197
801211.22090.779078
811211.71790.282086
821211.66210.337907
831210.93441.0656
841111.0034-0.00344218
851011.4746-1.47456
86910.5681-1.56807
871211.56170.438327
881211.43170.568327
891210.88651.11347
9099.32803-0.328035
911511.93183.06823
921211.83680.163192
931210.831.17004
94129.806922.19308
951011.6473-1.64728
961311.51281.48719
97911.5015-2.50154
981211.58680.413228
991010.5495-0.54954
1001411.63742.36264
1011111.5378-0.537814
1021514.00060.999431
1031110.76050.239521
1041111.7646-0.764553
105129.64622.3538
1061212.1415-0.141549
1071211.62940.370636
1081111.4874-0.487382
10979.21971-2.21971
1101211.63860.361391
1111411.57052.42951
1121112.4948-1.49478
113119.806751.19325
114109.219430.780567
1151312.67290.327119
1161310.54442.45556
117810.5614-2.56135
118119.906331.09367
1191211.64820.351828
120119.858711.14129
1211311.33631.6637
1221210.07321.92682
1231411.7272.27297
1241310.85782.14223
1251511.62423.3758
1261010.9675-0.967505
1271112.2482-1.24816
128911.0468-2.04682
129119.199771.80023
1301011.5778-1.57777
131118.027242.97276
132811.6645-3.66451
133119.115061.88494
1341210.52391.47607
1351210.8351.16504
13699.27233-0.272332
1371110.9130.0869692
138108.633441.36656
13989.20795-1.20795
14098.767490.232508
141811.5147-3.51468
142911.1715-2.17152
1431512.27652.72355
1441111.2144-0.214369
14588.00773-0.00772786
1461312.46960.530445
147129.824852.17515
1481211.50520.494843
14999.6951-0.695103
15078.29384-1.29384
1511311.02051.97949
152911.7613-2.76131
153611.7514-5.7514
154810.3021-2.30205
15587.937450.0625544
1561511.93183.06823
15769.9261-3.9261
158911.0468-2.04682
1591111.5853-0.585316
16089.46033-1.46033
16189.8098-1.8098
162109.44670.553303
16389.05289-1.05289
1641412.0111.98901
1651011.1514-1.15142
16687.891210.108793
1671110.44180.55824
168128.454883.54512
1691210.02531.97473
1701211.77330.226737
17158.96971-3.96971
1721211.64210.357852
173109.294130.705868
17477.16437-0.164365
175128.995633.00437
1761111.164-0.163974
17789.14357-1.14357
17899.10903-0.109031
1791010.3175-0.317544
18099.38635-0.386352
1811211.54270.457316
18268.54158-2.54158
1831513.37121.62878
1841210.94111.0589
185126.937565.06244
1861211.6460.353991
1871112.1363-1.1363
18879.17914-2.17914
18978.47216-1.47216
19058.63463-3.63463
1911210.53231.46772
1921211.8060.194018
19339.1994-6.1994
1941111.5499-0.549915
195109.758480.241521
1961211.09120.908775
197911.4144-2.41439
1981211.72730.272713
199910.3155-1.31548
2001211.63520.3648
2011211.39280.607164
2021010.3807-0.380743
20398.638220.361776
204129.061812.93819
205811.0174-3.01737
2061111.0594-0.0593559
2071111.6818-0.681796
2081211.50190.498071
209108.589211.41079
2101011.0138-1.01376
211129.15442.8456
212129.595712.40429
2131111.2108-0.210779
214810.9912-2.99123
2151211.54560.454379
2161010.0725-0.072505
2171112.238-1.23804
2181010.3934-0.393367
21989.75381-1.75381
2201211.14760.852404
221129.833312.16669
2221010.432-0.431969
2231210.89551.10447
22499.24619-0.246187
22599.86545-0.865452
22667.12264-1.12264
2271010.2671-0.267129
228910.4579-1.45787
22998.521920.478082
23099.29652-0.296522
23169.68958-3.68958
232108.196911.80309
233611.5358-5.53579
2341412.52561.4744
235109.782980.21702
236108.540191.45981
23764.413321.58668
238129.412872.58713
2391211.55150.448523
24077.95057-0.950574
24189.38191-1.38191
242119.142361.85764
24337.86506-4.86506
24469.73778-3.73778
2451010.8226-0.822553
24689.27826-1.27826
247910.4079-1.40787
24897.744061.25594
24988.77694-0.776945
25098.7930.207001
25178.69665-1.69665
25278.04224-1.04224
25369.24573-3.24573
254911.4796-2.47959
255109.101330.898673
2561110.30410.695944
2571211.65530.344653
258810.261-2.261
259119.745811.25419
26034.60455-1.60455
2611110.89090.109059
262128.822963.17704
26378.57605-1.57605
264910.4058-1.40584






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.991740.01651990.00825995
120.9882950.02340980.0117049
130.9759730.04805420.0240271
140.9752410.04951840.0247592
150.96250.07500080.0375004
160.9493960.1012080.0506041
170.9216210.1567580.078379
180.9182380.1635250.0817624
190.9014250.197150.0985752
200.8613710.2772580.138629
210.827180.345640.17282
220.7794010.4411970.220599
230.7339990.5320030.266001
240.6948520.6102950.305148
250.6429950.7140090.357005
260.6418980.7162040.358102
270.6598730.6802530.340127
280.6702570.6594860.329743
290.6101760.7796480.389824
300.5620020.8759950.437998
310.5116450.9767110.488355
320.5278140.9443720.472186
330.4672260.9344520.532774
340.412190.824380.58781
350.3948280.7896570.605172
360.3816490.7632980.618351
370.3314460.6628910.668554
380.3154670.6309340.684533
390.2960560.5921120.703944
400.2709090.5418170.729091
410.241490.482980.75851
420.2146010.4292010.785399
430.2531670.5063350.746833
440.2151920.4303850.784808
450.1796090.3592190.820391
460.2173220.4346440.782678
470.2363090.4726180.763691
480.1995870.3991750.800413
490.1887010.3774010.811299
500.1744030.3488060.825597
510.1816270.3632530.818373
520.1520430.3040860.847957
530.1582470.3164930.841753
540.139250.2784990.86075
550.2105380.4210770.789462
560.4752610.9505220.524739
570.4326040.8652080.567396
580.3903760.7807510.609624
590.350020.7000390.64998
600.3461280.6922560.653872
610.3499460.6998930.650054
620.3115060.6230120.688494
630.321420.6428390.67858
640.2853650.570730.714635
650.2602470.5204930.739753
660.2277910.4555830.772209
670.2092940.4185880.790706
680.1891530.3783060.810847
690.1884310.3768620.811569
700.1620310.3240620.837969
710.1429060.2858130.857094
720.1220290.2440580.877971
730.1041750.208350.895825
740.08858690.1771740.911413
750.07953690.1590740.920463
760.1006380.2012760.899362
770.09005320.1801060.909947
780.07468940.1493790.925311
790.07993070.1598610.920069
800.07671220.1534240.923288
810.06367410.1273480.936326
820.05263360.1052670.947366
830.04578320.09156650.954217
840.03722550.07445090.962775
850.03410670.06821330.965893
860.03880020.07760040.9612
870.0314260.0628520.968574
880.0256130.0512260.974387
890.02173120.04346240.978269
900.01819210.03638420.981808
910.03000140.06000280.969999
920.02487260.04974520.975127
930.02269470.04538950.977305
940.02440790.04881580.975592
950.0244150.04883010.975585
960.0221560.0443120.977844
970.02725750.0545150.972743
980.02209150.04418310.977908
990.01869520.03739030.981305
1000.02186680.04373370.978133
1010.0180530.03610590.981947
1020.01532290.03064590.984677
1030.01216390.02432780.987836
1040.01075450.02150910.989245
1050.01205950.02411890.987941
1060.009432810.01886560.990567
1070.007411170.01482230.992589
1080.00607660.01215320.993923
1090.008539390.01707880.991461
1100.006654240.01330850.993346
1110.007673860.01534770.992326
1120.008027640.01605530.991972
1130.006654810.01330960.993345
1140.005377910.01075580.994622
1150.004186610.008373210.995813
1160.00492560.009851210.995074
1170.007096660.01419330.992903
1180.005933370.01186670.994067
1190.004602450.009204890.995398
1200.00386210.00772420.996138
1210.003714530.007429070.996285
1220.003740030.007480050.99626
1230.004433010.008866010.995567
1240.005072840.01014570.994927
1250.009115850.01823170.990884
1260.00758380.01516760.992416
1270.006505670.01301130.993494
1280.006762550.01352510.993237
1290.006667210.01333440.993333
1300.006666250.01333250.993334
1310.008469750.01693950.99153
1320.01718880.03437760.982811
1330.01677550.03355110.983224
1340.01570690.03141380.984293
1350.01365340.02730680.986347
1360.01111010.02222010.98889
1370.008812590.01762520.991187
1380.007903890.01580780.992096
1390.007044320.01408860.992956
1400.005720240.01144050.99428
1410.01087720.02175440.989123
1420.01273610.02547220.987264
1430.01698010.03396020.98302
1440.01358820.02717630.986412
1450.01076190.02152380.989238
1460.008721010.0174420.991279
1470.009740070.01948010.99026
1480.007848220.01569640.992152
1490.006593310.01318660.993407
1500.005954090.01190820.994046
1510.006176190.01235240.993824
1520.008288420.01657680.991712
1530.05326920.1065380.946731
1540.06052230.1210450.939478
1550.05064190.1012840.949358
1560.07289170.1457830.927108
1570.1280920.2561840.871908
1580.1294470.2588950.870553
1590.1125470.2250930.887453
1600.1087990.2175970.891201
1610.1079180.2158360.892082
1620.09369090.1873820.906309
1630.08436260.1687250.915637
1640.08956180.1791240.910438
1650.08112490.162250.918875
1660.06902470.1380490.930975
1670.05871240.1174250.941288
1680.09761090.1952220.902389
1690.09912030.1982410.90088
1700.08622590.1724520.913774
1710.1497440.2994880.850256
1720.1299940.2599880.870006
1730.1144770.2289530.885523
1740.09844540.1968910.901555
1750.1358830.2717660.864117
1760.1177880.2355760.882212
1770.1058770.2117540.894123
1780.09080550.1816110.909195
1790.07670850.1534170.923292
1800.0643620.1287240.935638
1810.05378810.1075760.946212
1820.06151110.1230220.938489
1830.06156140.1231230.938439
1840.05705590.1141120.942944
1850.2271330.4542660.772867
1860.209260.418520.79074
1870.1874610.3749220.812539
1880.1870410.3740830.812959
1890.173830.3476610.82617
1900.2573560.5147130.742644
1910.2624980.5249970.737502
1920.2321680.4643360.767832
1930.6079060.7841880.392094
1940.577320.8453590.42268
1950.5406290.9187410.459371
1960.507890.9842210.49211
1970.5225290.9549420.477471
1980.486520.973040.51348
1990.460350.92070.53965
2000.4622560.9245130.537744
2010.4361790.8723580.563821
2020.4156460.8312930.584354
2030.3938790.7877590.606121
2040.4449690.8899380.555031
2050.4790810.9581620.520919
2060.4363010.8726020.563699
2070.3961970.7923940.603803
2080.3562350.7124690.643765
2090.3373580.6747160.662642
2100.2997630.5995260.700237
2110.3655920.7311840.634408
2120.3825130.7650250.617487
2130.3404110.6808210.659589
2140.3613030.7226060.638697
2150.3253370.6506730.674663
2160.2888970.5777930.711103
2170.2531510.5063020.746849
2180.2163340.4326680.783666
2190.2147520.4295030.785248
2200.1905690.3811380.809431
2210.2333580.4667160.766642
2220.1973580.3947170.802642
2230.1894160.3788330.810584
2240.1641750.328350.835825
2250.135710.271420.86429
2260.1111140.2222270.888886
2270.0894340.1788680.910566
2280.0718010.1436020.928199
2290.05497170.1099430.945028
2300.04199270.08398540.958007
2310.06143840.1228770.938562
2320.07508720.1501740.924913
2330.2750540.5501080.724946
2340.2440760.4881530.755924
2350.1987240.3974470.801276
2360.1976420.3952840.802358
2370.2355540.4711080.764446
2380.2526360.5052730.747364
2390.2439440.4878890.756056
2400.1995150.399030.800485
2410.1619430.3238850.838057
2420.2022050.4044090.797795
2430.4862340.9724670.513766
2440.6802440.6395110.319756
2450.6041630.7916740.395837
2460.5339020.9321960.466098
2470.4588970.9177940.541103
2480.3933580.7867150.606642
2490.3018590.6037180.698141
2500.2447890.4895790.755211
2510.3570070.7140130.642993
2520.5801070.8397860.419893
2530.5216260.9567470.478374

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.99174 & 0.0165199 & 0.00825995 \tabularnewline
12 & 0.988295 & 0.0234098 & 0.0117049 \tabularnewline
13 & 0.975973 & 0.0480542 & 0.0240271 \tabularnewline
14 & 0.975241 & 0.0495184 & 0.0247592 \tabularnewline
15 & 0.9625 & 0.0750008 & 0.0375004 \tabularnewline
16 & 0.949396 & 0.101208 & 0.0506041 \tabularnewline
17 & 0.921621 & 0.156758 & 0.078379 \tabularnewline
18 & 0.918238 & 0.163525 & 0.0817624 \tabularnewline
19 & 0.901425 & 0.19715 & 0.0985752 \tabularnewline
20 & 0.861371 & 0.277258 & 0.138629 \tabularnewline
21 & 0.82718 & 0.34564 & 0.17282 \tabularnewline
22 & 0.779401 & 0.441197 & 0.220599 \tabularnewline
23 & 0.733999 & 0.532003 & 0.266001 \tabularnewline
24 & 0.694852 & 0.610295 & 0.305148 \tabularnewline
25 & 0.642995 & 0.714009 & 0.357005 \tabularnewline
26 & 0.641898 & 0.716204 & 0.358102 \tabularnewline
27 & 0.659873 & 0.680253 & 0.340127 \tabularnewline
28 & 0.670257 & 0.659486 & 0.329743 \tabularnewline
29 & 0.610176 & 0.779648 & 0.389824 \tabularnewline
30 & 0.562002 & 0.875995 & 0.437998 \tabularnewline
31 & 0.511645 & 0.976711 & 0.488355 \tabularnewline
32 & 0.527814 & 0.944372 & 0.472186 \tabularnewline
33 & 0.467226 & 0.934452 & 0.532774 \tabularnewline
34 & 0.41219 & 0.82438 & 0.58781 \tabularnewline
35 & 0.394828 & 0.789657 & 0.605172 \tabularnewline
36 & 0.381649 & 0.763298 & 0.618351 \tabularnewline
37 & 0.331446 & 0.662891 & 0.668554 \tabularnewline
38 & 0.315467 & 0.630934 & 0.684533 \tabularnewline
39 & 0.296056 & 0.592112 & 0.703944 \tabularnewline
40 & 0.270909 & 0.541817 & 0.729091 \tabularnewline
41 & 0.24149 & 0.48298 & 0.75851 \tabularnewline
42 & 0.214601 & 0.429201 & 0.785399 \tabularnewline
43 & 0.253167 & 0.506335 & 0.746833 \tabularnewline
44 & 0.215192 & 0.430385 & 0.784808 \tabularnewline
45 & 0.179609 & 0.359219 & 0.820391 \tabularnewline
46 & 0.217322 & 0.434644 & 0.782678 \tabularnewline
47 & 0.236309 & 0.472618 & 0.763691 \tabularnewline
48 & 0.199587 & 0.399175 & 0.800413 \tabularnewline
49 & 0.188701 & 0.377401 & 0.811299 \tabularnewline
50 & 0.174403 & 0.348806 & 0.825597 \tabularnewline
51 & 0.181627 & 0.363253 & 0.818373 \tabularnewline
52 & 0.152043 & 0.304086 & 0.847957 \tabularnewline
53 & 0.158247 & 0.316493 & 0.841753 \tabularnewline
54 & 0.13925 & 0.278499 & 0.86075 \tabularnewline
55 & 0.210538 & 0.421077 & 0.789462 \tabularnewline
56 & 0.475261 & 0.950522 & 0.524739 \tabularnewline
57 & 0.432604 & 0.865208 & 0.567396 \tabularnewline
58 & 0.390376 & 0.780751 & 0.609624 \tabularnewline
59 & 0.35002 & 0.700039 & 0.64998 \tabularnewline
60 & 0.346128 & 0.692256 & 0.653872 \tabularnewline
61 & 0.349946 & 0.699893 & 0.650054 \tabularnewline
62 & 0.311506 & 0.623012 & 0.688494 \tabularnewline
63 & 0.32142 & 0.642839 & 0.67858 \tabularnewline
64 & 0.285365 & 0.57073 & 0.714635 \tabularnewline
65 & 0.260247 & 0.520493 & 0.739753 \tabularnewline
66 & 0.227791 & 0.455583 & 0.772209 \tabularnewline
67 & 0.209294 & 0.418588 & 0.790706 \tabularnewline
68 & 0.189153 & 0.378306 & 0.810847 \tabularnewline
69 & 0.188431 & 0.376862 & 0.811569 \tabularnewline
70 & 0.162031 & 0.324062 & 0.837969 \tabularnewline
71 & 0.142906 & 0.285813 & 0.857094 \tabularnewline
72 & 0.122029 & 0.244058 & 0.877971 \tabularnewline
73 & 0.104175 & 0.20835 & 0.895825 \tabularnewline
74 & 0.0885869 & 0.177174 & 0.911413 \tabularnewline
75 & 0.0795369 & 0.159074 & 0.920463 \tabularnewline
76 & 0.100638 & 0.201276 & 0.899362 \tabularnewline
77 & 0.0900532 & 0.180106 & 0.909947 \tabularnewline
78 & 0.0746894 & 0.149379 & 0.925311 \tabularnewline
79 & 0.0799307 & 0.159861 & 0.920069 \tabularnewline
80 & 0.0767122 & 0.153424 & 0.923288 \tabularnewline
81 & 0.0636741 & 0.127348 & 0.936326 \tabularnewline
82 & 0.0526336 & 0.105267 & 0.947366 \tabularnewline
83 & 0.0457832 & 0.0915665 & 0.954217 \tabularnewline
84 & 0.0372255 & 0.0744509 & 0.962775 \tabularnewline
85 & 0.0341067 & 0.0682133 & 0.965893 \tabularnewline
86 & 0.0388002 & 0.0776004 & 0.9612 \tabularnewline
87 & 0.031426 & 0.062852 & 0.968574 \tabularnewline
88 & 0.025613 & 0.051226 & 0.974387 \tabularnewline
89 & 0.0217312 & 0.0434624 & 0.978269 \tabularnewline
90 & 0.0181921 & 0.0363842 & 0.981808 \tabularnewline
91 & 0.0300014 & 0.0600028 & 0.969999 \tabularnewline
92 & 0.0248726 & 0.0497452 & 0.975127 \tabularnewline
93 & 0.0226947 & 0.0453895 & 0.977305 \tabularnewline
94 & 0.0244079 & 0.0488158 & 0.975592 \tabularnewline
95 & 0.024415 & 0.0488301 & 0.975585 \tabularnewline
96 & 0.022156 & 0.044312 & 0.977844 \tabularnewline
97 & 0.0272575 & 0.054515 & 0.972743 \tabularnewline
98 & 0.0220915 & 0.0441831 & 0.977908 \tabularnewline
99 & 0.0186952 & 0.0373903 & 0.981305 \tabularnewline
100 & 0.0218668 & 0.0437337 & 0.978133 \tabularnewline
101 & 0.018053 & 0.0361059 & 0.981947 \tabularnewline
102 & 0.0153229 & 0.0306459 & 0.984677 \tabularnewline
103 & 0.0121639 & 0.0243278 & 0.987836 \tabularnewline
104 & 0.0107545 & 0.0215091 & 0.989245 \tabularnewline
105 & 0.0120595 & 0.0241189 & 0.987941 \tabularnewline
106 & 0.00943281 & 0.0188656 & 0.990567 \tabularnewline
107 & 0.00741117 & 0.0148223 & 0.992589 \tabularnewline
108 & 0.0060766 & 0.0121532 & 0.993923 \tabularnewline
109 & 0.00853939 & 0.0170788 & 0.991461 \tabularnewline
110 & 0.00665424 & 0.0133085 & 0.993346 \tabularnewline
111 & 0.00767386 & 0.0153477 & 0.992326 \tabularnewline
112 & 0.00802764 & 0.0160553 & 0.991972 \tabularnewline
113 & 0.00665481 & 0.0133096 & 0.993345 \tabularnewline
114 & 0.00537791 & 0.0107558 & 0.994622 \tabularnewline
115 & 0.00418661 & 0.00837321 & 0.995813 \tabularnewline
116 & 0.0049256 & 0.00985121 & 0.995074 \tabularnewline
117 & 0.00709666 & 0.0141933 & 0.992903 \tabularnewline
118 & 0.00593337 & 0.0118667 & 0.994067 \tabularnewline
119 & 0.00460245 & 0.00920489 & 0.995398 \tabularnewline
120 & 0.0038621 & 0.0077242 & 0.996138 \tabularnewline
121 & 0.00371453 & 0.00742907 & 0.996285 \tabularnewline
122 & 0.00374003 & 0.00748005 & 0.99626 \tabularnewline
123 & 0.00443301 & 0.00886601 & 0.995567 \tabularnewline
124 & 0.00507284 & 0.0101457 & 0.994927 \tabularnewline
125 & 0.00911585 & 0.0182317 & 0.990884 \tabularnewline
126 & 0.0075838 & 0.0151676 & 0.992416 \tabularnewline
127 & 0.00650567 & 0.0130113 & 0.993494 \tabularnewline
128 & 0.00676255 & 0.0135251 & 0.993237 \tabularnewline
129 & 0.00666721 & 0.0133344 & 0.993333 \tabularnewline
130 & 0.00666625 & 0.0133325 & 0.993334 \tabularnewline
131 & 0.00846975 & 0.0169395 & 0.99153 \tabularnewline
132 & 0.0171888 & 0.0343776 & 0.982811 \tabularnewline
133 & 0.0167755 & 0.0335511 & 0.983224 \tabularnewline
134 & 0.0157069 & 0.0314138 & 0.984293 \tabularnewline
135 & 0.0136534 & 0.0273068 & 0.986347 \tabularnewline
136 & 0.0111101 & 0.0222201 & 0.98889 \tabularnewline
137 & 0.00881259 & 0.0176252 & 0.991187 \tabularnewline
138 & 0.00790389 & 0.0158078 & 0.992096 \tabularnewline
139 & 0.00704432 & 0.0140886 & 0.992956 \tabularnewline
140 & 0.00572024 & 0.0114405 & 0.99428 \tabularnewline
141 & 0.0108772 & 0.0217544 & 0.989123 \tabularnewline
142 & 0.0127361 & 0.0254722 & 0.987264 \tabularnewline
143 & 0.0169801 & 0.0339602 & 0.98302 \tabularnewline
144 & 0.0135882 & 0.0271763 & 0.986412 \tabularnewline
145 & 0.0107619 & 0.0215238 & 0.989238 \tabularnewline
146 & 0.00872101 & 0.017442 & 0.991279 \tabularnewline
147 & 0.00974007 & 0.0194801 & 0.99026 \tabularnewline
148 & 0.00784822 & 0.0156964 & 0.992152 \tabularnewline
149 & 0.00659331 & 0.0131866 & 0.993407 \tabularnewline
150 & 0.00595409 & 0.0119082 & 0.994046 \tabularnewline
151 & 0.00617619 & 0.0123524 & 0.993824 \tabularnewline
152 & 0.00828842 & 0.0165768 & 0.991712 \tabularnewline
153 & 0.0532692 & 0.106538 & 0.946731 \tabularnewline
154 & 0.0605223 & 0.121045 & 0.939478 \tabularnewline
155 & 0.0506419 & 0.101284 & 0.949358 \tabularnewline
156 & 0.0728917 & 0.145783 & 0.927108 \tabularnewline
157 & 0.128092 & 0.256184 & 0.871908 \tabularnewline
158 & 0.129447 & 0.258895 & 0.870553 \tabularnewline
159 & 0.112547 & 0.225093 & 0.887453 \tabularnewline
160 & 0.108799 & 0.217597 & 0.891201 \tabularnewline
161 & 0.107918 & 0.215836 & 0.892082 \tabularnewline
162 & 0.0936909 & 0.187382 & 0.906309 \tabularnewline
163 & 0.0843626 & 0.168725 & 0.915637 \tabularnewline
164 & 0.0895618 & 0.179124 & 0.910438 \tabularnewline
165 & 0.0811249 & 0.16225 & 0.918875 \tabularnewline
166 & 0.0690247 & 0.138049 & 0.930975 \tabularnewline
167 & 0.0587124 & 0.117425 & 0.941288 \tabularnewline
168 & 0.0976109 & 0.195222 & 0.902389 \tabularnewline
169 & 0.0991203 & 0.198241 & 0.90088 \tabularnewline
170 & 0.0862259 & 0.172452 & 0.913774 \tabularnewline
171 & 0.149744 & 0.299488 & 0.850256 \tabularnewline
172 & 0.129994 & 0.259988 & 0.870006 \tabularnewline
173 & 0.114477 & 0.228953 & 0.885523 \tabularnewline
174 & 0.0984454 & 0.196891 & 0.901555 \tabularnewline
175 & 0.135883 & 0.271766 & 0.864117 \tabularnewline
176 & 0.117788 & 0.235576 & 0.882212 \tabularnewline
177 & 0.105877 & 0.211754 & 0.894123 \tabularnewline
178 & 0.0908055 & 0.181611 & 0.909195 \tabularnewline
179 & 0.0767085 & 0.153417 & 0.923292 \tabularnewline
180 & 0.064362 & 0.128724 & 0.935638 \tabularnewline
181 & 0.0537881 & 0.107576 & 0.946212 \tabularnewline
182 & 0.0615111 & 0.123022 & 0.938489 \tabularnewline
183 & 0.0615614 & 0.123123 & 0.938439 \tabularnewline
184 & 0.0570559 & 0.114112 & 0.942944 \tabularnewline
185 & 0.227133 & 0.454266 & 0.772867 \tabularnewline
186 & 0.20926 & 0.41852 & 0.79074 \tabularnewline
187 & 0.187461 & 0.374922 & 0.812539 \tabularnewline
188 & 0.187041 & 0.374083 & 0.812959 \tabularnewline
189 & 0.17383 & 0.347661 & 0.82617 \tabularnewline
190 & 0.257356 & 0.514713 & 0.742644 \tabularnewline
191 & 0.262498 & 0.524997 & 0.737502 \tabularnewline
192 & 0.232168 & 0.464336 & 0.767832 \tabularnewline
193 & 0.607906 & 0.784188 & 0.392094 \tabularnewline
194 & 0.57732 & 0.845359 & 0.42268 \tabularnewline
195 & 0.540629 & 0.918741 & 0.459371 \tabularnewline
196 & 0.50789 & 0.984221 & 0.49211 \tabularnewline
197 & 0.522529 & 0.954942 & 0.477471 \tabularnewline
198 & 0.48652 & 0.97304 & 0.51348 \tabularnewline
199 & 0.46035 & 0.9207 & 0.53965 \tabularnewline
200 & 0.462256 & 0.924513 & 0.537744 \tabularnewline
201 & 0.436179 & 0.872358 & 0.563821 \tabularnewline
202 & 0.415646 & 0.831293 & 0.584354 \tabularnewline
203 & 0.393879 & 0.787759 & 0.606121 \tabularnewline
204 & 0.444969 & 0.889938 & 0.555031 \tabularnewline
205 & 0.479081 & 0.958162 & 0.520919 \tabularnewline
206 & 0.436301 & 0.872602 & 0.563699 \tabularnewline
207 & 0.396197 & 0.792394 & 0.603803 \tabularnewline
208 & 0.356235 & 0.712469 & 0.643765 \tabularnewline
209 & 0.337358 & 0.674716 & 0.662642 \tabularnewline
210 & 0.299763 & 0.599526 & 0.700237 \tabularnewline
211 & 0.365592 & 0.731184 & 0.634408 \tabularnewline
212 & 0.382513 & 0.765025 & 0.617487 \tabularnewline
213 & 0.340411 & 0.680821 & 0.659589 \tabularnewline
214 & 0.361303 & 0.722606 & 0.638697 \tabularnewline
215 & 0.325337 & 0.650673 & 0.674663 \tabularnewline
216 & 0.288897 & 0.577793 & 0.711103 \tabularnewline
217 & 0.253151 & 0.506302 & 0.746849 \tabularnewline
218 & 0.216334 & 0.432668 & 0.783666 \tabularnewline
219 & 0.214752 & 0.429503 & 0.785248 \tabularnewline
220 & 0.190569 & 0.381138 & 0.809431 \tabularnewline
221 & 0.233358 & 0.466716 & 0.766642 \tabularnewline
222 & 0.197358 & 0.394717 & 0.802642 \tabularnewline
223 & 0.189416 & 0.378833 & 0.810584 \tabularnewline
224 & 0.164175 & 0.32835 & 0.835825 \tabularnewline
225 & 0.13571 & 0.27142 & 0.86429 \tabularnewline
226 & 0.111114 & 0.222227 & 0.888886 \tabularnewline
227 & 0.089434 & 0.178868 & 0.910566 \tabularnewline
228 & 0.071801 & 0.143602 & 0.928199 \tabularnewline
229 & 0.0549717 & 0.109943 & 0.945028 \tabularnewline
230 & 0.0419927 & 0.0839854 & 0.958007 \tabularnewline
231 & 0.0614384 & 0.122877 & 0.938562 \tabularnewline
232 & 0.0750872 & 0.150174 & 0.924913 \tabularnewline
233 & 0.275054 & 0.550108 & 0.724946 \tabularnewline
234 & 0.244076 & 0.488153 & 0.755924 \tabularnewline
235 & 0.198724 & 0.397447 & 0.801276 \tabularnewline
236 & 0.197642 & 0.395284 & 0.802358 \tabularnewline
237 & 0.235554 & 0.471108 & 0.764446 \tabularnewline
238 & 0.252636 & 0.505273 & 0.747364 \tabularnewline
239 & 0.243944 & 0.487889 & 0.756056 \tabularnewline
240 & 0.199515 & 0.39903 & 0.800485 \tabularnewline
241 & 0.161943 & 0.323885 & 0.838057 \tabularnewline
242 & 0.202205 & 0.404409 & 0.797795 \tabularnewline
243 & 0.486234 & 0.972467 & 0.513766 \tabularnewline
244 & 0.680244 & 0.639511 & 0.319756 \tabularnewline
245 & 0.604163 & 0.791674 & 0.395837 \tabularnewline
246 & 0.533902 & 0.932196 & 0.466098 \tabularnewline
247 & 0.458897 & 0.917794 & 0.541103 \tabularnewline
248 & 0.393358 & 0.786715 & 0.606642 \tabularnewline
249 & 0.301859 & 0.603718 & 0.698141 \tabularnewline
250 & 0.244789 & 0.489579 & 0.755211 \tabularnewline
251 & 0.357007 & 0.714013 & 0.642993 \tabularnewline
252 & 0.580107 & 0.839786 & 0.419893 \tabularnewline
253 & 0.521626 & 0.956747 & 0.478374 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226044&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]0.99174[/C][C]0.0165199[/C][C]0.00825995[/C][/ROW]
[ROW][C]12[/C][C]0.988295[/C][C]0.0234098[/C][C]0.0117049[/C][/ROW]
[ROW][C]13[/C][C]0.975973[/C][C]0.0480542[/C][C]0.0240271[/C][/ROW]
[ROW][C]14[/C][C]0.975241[/C][C]0.0495184[/C][C]0.0247592[/C][/ROW]
[ROW][C]15[/C][C]0.9625[/C][C]0.0750008[/C][C]0.0375004[/C][/ROW]
[ROW][C]16[/C][C]0.949396[/C][C]0.101208[/C][C]0.0506041[/C][/ROW]
[ROW][C]17[/C][C]0.921621[/C][C]0.156758[/C][C]0.078379[/C][/ROW]
[ROW][C]18[/C][C]0.918238[/C][C]0.163525[/C][C]0.0817624[/C][/ROW]
[ROW][C]19[/C][C]0.901425[/C][C]0.19715[/C][C]0.0985752[/C][/ROW]
[ROW][C]20[/C][C]0.861371[/C][C]0.277258[/C][C]0.138629[/C][/ROW]
[ROW][C]21[/C][C]0.82718[/C][C]0.34564[/C][C]0.17282[/C][/ROW]
[ROW][C]22[/C][C]0.779401[/C][C]0.441197[/C][C]0.220599[/C][/ROW]
[ROW][C]23[/C][C]0.733999[/C][C]0.532003[/C][C]0.266001[/C][/ROW]
[ROW][C]24[/C][C]0.694852[/C][C]0.610295[/C][C]0.305148[/C][/ROW]
[ROW][C]25[/C][C]0.642995[/C][C]0.714009[/C][C]0.357005[/C][/ROW]
[ROW][C]26[/C][C]0.641898[/C][C]0.716204[/C][C]0.358102[/C][/ROW]
[ROW][C]27[/C][C]0.659873[/C][C]0.680253[/C][C]0.340127[/C][/ROW]
[ROW][C]28[/C][C]0.670257[/C][C]0.659486[/C][C]0.329743[/C][/ROW]
[ROW][C]29[/C][C]0.610176[/C][C]0.779648[/C][C]0.389824[/C][/ROW]
[ROW][C]30[/C][C]0.562002[/C][C]0.875995[/C][C]0.437998[/C][/ROW]
[ROW][C]31[/C][C]0.511645[/C][C]0.976711[/C][C]0.488355[/C][/ROW]
[ROW][C]32[/C][C]0.527814[/C][C]0.944372[/C][C]0.472186[/C][/ROW]
[ROW][C]33[/C][C]0.467226[/C][C]0.934452[/C][C]0.532774[/C][/ROW]
[ROW][C]34[/C][C]0.41219[/C][C]0.82438[/C][C]0.58781[/C][/ROW]
[ROW][C]35[/C][C]0.394828[/C][C]0.789657[/C][C]0.605172[/C][/ROW]
[ROW][C]36[/C][C]0.381649[/C][C]0.763298[/C][C]0.618351[/C][/ROW]
[ROW][C]37[/C][C]0.331446[/C][C]0.662891[/C][C]0.668554[/C][/ROW]
[ROW][C]38[/C][C]0.315467[/C][C]0.630934[/C][C]0.684533[/C][/ROW]
[ROW][C]39[/C][C]0.296056[/C][C]0.592112[/C][C]0.703944[/C][/ROW]
[ROW][C]40[/C][C]0.270909[/C][C]0.541817[/C][C]0.729091[/C][/ROW]
[ROW][C]41[/C][C]0.24149[/C][C]0.48298[/C][C]0.75851[/C][/ROW]
[ROW][C]42[/C][C]0.214601[/C][C]0.429201[/C][C]0.785399[/C][/ROW]
[ROW][C]43[/C][C]0.253167[/C][C]0.506335[/C][C]0.746833[/C][/ROW]
[ROW][C]44[/C][C]0.215192[/C][C]0.430385[/C][C]0.784808[/C][/ROW]
[ROW][C]45[/C][C]0.179609[/C][C]0.359219[/C][C]0.820391[/C][/ROW]
[ROW][C]46[/C][C]0.217322[/C][C]0.434644[/C][C]0.782678[/C][/ROW]
[ROW][C]47[/C][C]0.236309[/C][C]0.472618[/C][C]0.763691[/C][/ROW]
[ROW][C]48[/C][C]0.199587[/C][C]0.399175[/C][C]0.800413[/C][/ROW]
[ROW][C]49[/C][C]0.188701[/C][C]0.377401[/C][C]0.811299[/C][/ROW]
[ROW][C]50[/C][C]0.174403[/C][C]0.348806[/C][C]0.825597[/C][/ROW]
[ROW][C]51[/C][C]0.181627[/C][C]0.363253[/C][C]0.818373[/C][/ROW]
[ROW][C]52[/C][C]0.152043[/C][C]0.304086[/C][C]0.847957[/C][/ROW]
[ROW][C]53[/C][C]0.158247[/C][C]0.316493[/C][C]0.841753[/C][/ROW]
[ROW][C]54[/C][C]0.13925[/C][C]0.278499[/C][C]0.86075[/C][/ROW]
[ROW][C]55[/C][C]0.210538[/C][C]0.421077[/C][C]0.789462[/C][/ROW]
[ROW][C]56[/C][C]0.475261[/C][C]0.950522[/C][C]0.524739[/C][/ROW]
[ROW][C]57[/C][C]0.432604[/C][C]0.865208[/C][C]0.567396[/C][/ROW]
[ROW][C]58[/C][C]0.390376[/C][C]0.780751[/C][C]0.609624[/C][/ROW]
[ROW][C]59[/C][C]0.35002[/C][C]0.700039[/C][C]0.64998[/C][/ROW]
[ROW][C]60[/C][C]0.346128[/C][C]0.692256[/C][C]0.653872[/C][/ROW]
[ROW][C]61[/C][C]0.349946[/C][C]0.699893[/C][C]0.650054[/C][/ROW]
[ROW][C]62[/C][C]0.311506[/C][C]0.623012[/C][C]0.688494[/C][/ROW]
[ROW][C]63[/C][C]0.32142[/C][C]0.642839[/C][C]0.67858[/C][/ROW]
[ROW][C]64[/C][C]0.285365[/C][C]0.57073[/C][C]0.714635[/C][/ROW]
[ROW][C]65[/C][C]0.260247[/C][C]0.520493[/C][C]0.739753[/C][/ROW]
[ROW][C]66[/C][C]0.227791[/C][C]0.455583[/C][C]0.772209[/C][/ROW]
[ROW][C]67[/C][C]0.209294[/C][C]0.418588[/C][C]0.790706[/C][/ROW]
[ROW][C]68[/C][C]0.189153[/C][C]0.378306[/C][C]0.810847[/C][/ROW]
[ROW][C]69[/C][C]0.188431[/C][C]0.376862[/C][C]0.811569[/C][/ROW]
[ROW][C]70[/C][C]0.162031[/C][C]0.324062[/C][C]0.837969[/C][/ROW]
[ROW][C]71[/C][C]0.142906[/C][C]0.285813[/C][C]0.857094[/C][/ROW]
[ROW][C]72[/C][C]0.122029[/C][C]0.244058[/C][C]0.877971[/C][/ROW]
[ROW][C]73[/C][C]0.104175[/C][C]0.20835[/C][C]0.895825[/C][/ROW]
[ROW][C]74[/C][C]0.0885869[/C][C]0.177174[/C][C]0.911413[/C][/ROW]
[ROW][C]75[/C][C]0.0795369[/C][C]0.159074[/C][C]0.920463[/C][/ROW]
[ROW][C]76[/C][C]0.100638[/C][C]0.201276[/C][C]0.899362[/C][/ROW]
[ROW][C]77[/C][C]0.0900532[/C][C]0.180106[/C][C]0.909947[/C][/ROW]
[ROW][C]78[/C][C]0.0746894[/C][C]0.149379[/C][C]0.925311[/C][/ROW]
[ROW][C]79[/C][C]0.0799307[/C][C]0.159861[/C][C]0.920069[/C][/ROW]
[ROW][C]80[/C][C]0.0767122[/C][C]0.153424[/C][C]0.923288[/C][/ROW]
[ROW][C]81[/C][C]0.0636741[/C][C]0.127348[/C][C]0.936326[/C][/ROW]
[ROW][C]82[/C][C]0.0526336[/C][C]0.105267[/C][C]0.947366[/C][/ROW]
[ROW][C]83[/C][C]0.0457832[/C][C]0.0915665[/C][C]0.954217[/C][/ROW]
[ROW][C]84[/C][C]0.0372255[/C][C]0.0744509[/C][C]0.962775[/C][/ROW]
[ROW][C]85[/C][C]0.0341067[/C][C]0.0682133[/C][C]0.965893[/C][/ROW]
[ROW][C]86[/C][C]0.0388002[/C][C]0.0776004[/C][C]0.9612[/C][/ROW]
[ROW][C]87[/C][C]0.031426[/C][C]0.062852[/C][C]0.968574[/C][/ROW]
[ROW][C]88[/C][C]0.025613[/C][C]0.051226[/C][C]0.974387[/C][/ROW]
[ROW][C]89[/C][C]0.0217312[/C][C]0.0434624[/C][C]0.978269[/C][/ROW]
[ROW][C]90[/C][C]0.0181921[/C][C]0.0363842[/C][C]0.981808[/C][/ROW]
[ROW][C]91[/C][C]0.0300014[/C][C]0.0600028[/C][C]0.969999[/C][/ROW]
[ROW][C]92[/C][C]0.0248726[/C][C]0.0497452[/C][C]0.975127[/C][/ROW]
[ROW][C]93[/C][C]0.0226947[/C][C]0.0453895[/C][C]0.977305[/C][/ROW]
[ROW][C]94[/C][C]0.0244079[/C][C]0.0488158[/C][C]0.975592[/C][/ROW]
[ROW][C]95[/C][C]0.024415[/C][C]0.0488301[/C][C]0.975585[/C][/ROW]
[ROW][C]96[/C][C]0.022156[/C][C]0.044312[/C][C]0.977844[/C][/ROW]
[ROW][C]97[/C][C]0.0272575[/C][C]0.054515[/C][C]0.972743[/C][/ROW]
[ROW][C]98[/C][C]0.0220915[/C][C]0.0441831[/C][C]0.977908[/C][/ROW]
[ROW][C]99[/C][C]0.0186952[/C][C]0.0373903[/C][C]0.981305[/C][/ROW]
[ROW][C]100[/C][C]0.0218668[/C][C]0.0437337[/C][C]0.978133[/C][/ROW]
[ROW][C]101[/C][C]0.018053[/C][C]0.0361059[/C][C]0.981947[/C][/ROW]
[ROW][C]102[/C][C]0.0153229[/C][C]0.0306459[/C][C]0.984677[/C][/ROW]
[ROW][C]103[/C][C]0.0121639[/C][C]0.0243278[/C][C]0.987836[/C][/ROW]
[ROW][C]104[/C][C]0.0107545[/C][C]0.0215091[/C][C]0.989245[/C][/ROW]
[ROW][C]105[/C][C]0.0120595[/C][C]0.0241189[/C][C]0.987941[/C][/ROW]
[ROW][C]106[/C][C]0.00943281[/C][C]0.0188656[/C][C]0.990567[/C][/ROW]
[ROW][C]107[/C][C]0.00741117[/C][C]0.0148223[/C][C]0.992589[/C][/ROW]
[ROW][C]108[/C][C]0.0060766[/C][C]0.0121532[/C][C]0.993923[/C][/ROW]
[ROW][C]109[/C][C]0.00853939[/C][C]0.0170788[/C][C]0.991461[/C][/ROW]
[ROW][C]110[/C][C]0.00665424[/C][C]0.0133085[/C][C]0.993346[/C][/ROW]
[ROW][C]111[/C][C]0.00767386[/C][C]0.0153477[/C][C]0.992326[/C][/ROW]
[ROW][C]112[/C][C]0.00802764[/C][C]0.0160553[/C][C]0.991972[/C][/ROW]
[ROW][C]113[/C][C]0.00665481[/C][C]0.0133096[/C][C]0.993345[/C][/ROW]
[ROW][C]114[/C][C]0.00537791[/C][C]0.0107558[/C][C]0.994622[/C][/ROW]
[ROW][C]115[/C][C]0.00418661[/C][C]0.00837321[/C][C]0.995813[/C][/ROW]
[ROW][C]116[/C][C]0.0049256[/C][C]0.00985121[/C][C]0.995074[/C][/ROW]
[ROW][C]117[/C][C]0.00709666[/C][C]0.0141933[/C][C]0.992903[/C][/ROW]
[ROW][C]118[/C][C]0.00593337[/C][C]0.0118667[/C][C]0.994067[/C][/ROW]
[ROW][C]119[/C][C]0.00460245[/C][C]0.00920489[/C][C]0.995398[/C][/ROW]
[ROW][C]120[/C][C]0.0038621[/C][C]0.0077242[/C][C]0.996138[/C][/ROW]
[ROW][C]121[/C][C]0.00371453[/C][C]0.00742907[/C][C]0.996285[/C][/ROW]
[ROW][C]122[/C][C]0.00374003[/C][C]0.00748005[/C][C]0.99626[/C][/ROW]
[ROW][C]123[/C][C]0.00443301[/C][C]0.00886601[/C][C]0.995567[/C][/ROW]
[ROW][C]124[/C][C]0.00507284[/C][C]0.0101457[/C][C]0.994927[/C][/ROW]
[ROW][C]125[/C][C]0.00911585[/C][C]0.0182317[/C][C]0.990884[/C][/ROW]
[ROW][C]126[/C][C]0.0075838[/C][C]0.0151676[/C][C]0.992416[/C][/ROW]
[ROW][C]127[/C][C]0.00650567[/C][C]0.0130113[/C][C]0.993494[/C][/ROW]
[ROW][C]128[/C][C]0.00676255[/C][C]0.0135251[/C][C]0.993237[/C][/ROW]
[ROW][C]129[/C][C]0.00666721[/C][C]0.0133344[/C][C]0.993333[/C][/ROW]
[ROW][C]130[/C][C]0.00666625[/C][C]0.0133325[/C][C]0.993334[/C][/ROW]
[ROW][C]131[/C][C]0.00846975[/C][C]0.0169395[/C][C]0.99153[/C][/ROW]
[ROW][C]132[/C][C]0.0171888[/C][C]0.0343776[/C][C]0.982811[/C][/ROW]
[ROW][C]133[/C][C]0.0167755[/C][C]0.0335511[/C][C]0.983224[/C][/ROW]
[ROW][C]134[/C][C]0.0157069[/C][C]0.0314138[/C][C]0.984293[/C][/ROW]
[ROW][C]135[/C][C]0.0136534[/C][C]0.0273068[/C][C]0.986347[/C][/ROW]
[ROW][C]136[/C][C]0.0111101[/C][C]0.0222201[/C][C]0.98889[/C][/ROW]
[ROW][C]137[/C][C]0.00881259[/C][C]0.0176252[/C][C]0.991187[/C][/ROW]
[ROW][C]138[/C][C]0.00790389[/C][C]0.0158078[/C][C]0.992096[/C][/ROW]
[ROW][C]139[/C][C]0.00704432[/C][C]0.0140886[/C][C]0.992956[/C][/ROW]
[ROW][C]140[/C][C]0.00572024[/C][C]0.0114405[/C][C]0.99428[/C][/ROW]
[ROW][C]141[/C][C]0.0108772[/C][C]0.0217544[/C][C]0.989123[/C][/ROW]
[ROW][C]142[/C][C]0.0127361[/C][C]0.0254722[/C][C]0.987264[/C][/ROW]
[ROW][C]143[/C][C]0.0169801[/C][C]0.0339602[/C][C]0.98302[/C][/ROW]
[ROW][C]144[/C][C]0.0135882[/C][C]0.0271763[/C][C]0.986412[/C][/ROW]
[ROW][C]145[/C][C]0.0107619[/C][C]0.0215238[/C][C]0.989238[/C][/ROW]
[ROW][C]146[/C][C]0.00872101[/C][C]0.017442[/C][C]0.991279[/C][/ROW]
[ROW][C]147[/C][C]0.00974007[/C][C]0.0194801[/C][C]0.99026[/C][/ROW]
[ROW][C]148[/C][C]0.00784822[/C][C]0.0156964[/C][C]0.992152[/C][/ROW]
[ROW][C]149[/C][C]0.00659331[/C][C]0.0131866[/C][C]0.993407[/C][/ROW]
[ROW][C]150[/C][C]0.00595409[/C][C]0.0119082[/C][C]0.994046[/C][/ROW]
[ROW][C]151[/C][C]0.00617619[/C][C]0.0123524[/C][C]0.993824[/C][/ROW]
[ROW][C]152[/C][C]0.00828842[/C][C]0.0165768[/C][C]0.991712[/C][/ROW]
[ROW][C]153[/C][C]0.0532692[/C][C]0.106538[/C][C]0.946731[/C][/ROW]
[ROW][C]154[/C][C]0.0605223[/C][C]0.121045[/C][C]0.939478[/C][/ROW]
[ROW][C]155[/C][C]0.0506419[/C][C]0.101284[/C][C]0.949358[/C][/ROW]
[ROW][C]156[/C][C]0.0728917[/C][C]0.145783[/C][C]0.927108[/C][/ROW]
[ROW][C]157[/C][C]0.128092[/C][C]0.256184[/C][C]0.871908[/C][/ROW]
[ROW][C]158[/C][C]0.129447[/C][C]0.258895[/C][C]0.870553[/C][/ROW]
[ROW][C]159[/C][C]0.112547[/C][C]0.225093[/C][C]0.887453[/C][/ROW]
[ROW][C]160[/C][C]0.108799[/C][C]0.217597[/C][C]0.891201[/C][/ROW]
[ROW][C]161[/C][C]0.107918[/C][C]0.215836[/C][C]0.892082[/C][/ROW]
[ROW][C]162[/C][C]0.0936909[/C][C]0.187382[/C][C]0.906309[/C][/ROW]
[ROW][C]163[/C][C]0.0843626[/C][C]0.168725[/C][C]0.915637[/C][/ROW]
[ROW][C]164[/C][C]0.0895618[/C][C]0.179124[/C][C]0.910438[/C][/ROW]
[ROW][C]165[/C][C]0.0811249[/C][C]0.16225[/C][C]0.918875[/C][/ROW]
[ROW][C]166[/C][C]0.0690247[/C][C]0.138049[/C][C]0.930975[/C][/ROW]
[ROW][C]167[/C][C]0.0587124[/C][C]0.117425[/C][C]0.941288[/C][/ROW]
[ROW][C]168[/C][C]0.0976109[/C][C]0.195222[/C][C]0.902389[/C][/ROW]
[ROW][C]169[/C][C]0.0991203[/C][C]0.198241[/C][C]0.90088[/C][/ROW]
[ROW][C]170[/C][C]0.0862259[/C][C]0.172452[/C][C]0.913774[/C][/ROW]
[ROW][C]171[/C][C]0.149744[/C][C]0.299488[/C][C]0.850256[/C][/ROW]
[ROW][C]172[/C][C]0.129994[/C][C]0.259988[/C][C]0.870006[/C][/ROW]
[ROW][C]173[/C][C]0.114477[/C][C]0.228953[/C][C]0.885523[/C][/ROW]
[ROW][C]174[/C][C]0.0984454[/C][C]0.196891[/C][C]0.901555[/C][/ROW]
[ROW][C]175[/C][C]0.135883[/C][C]0.271766[/C][C]0.864117[/C][/ROW]
[ROW][C]176[/C][C]0.117788[/C][C]0.235576[/C][C]0.882212[/C][/ROW]
[ROW][C]177[/C][C]0.105877[/C][C]0.211754[/C][C]0.894123[/C][/ROW]
[ROW][C]178[/C][C]0.0908055[/C][C]0.181611[/C][C]0.909195[/C][/ROW]
[ROW][C]179[/C][C]0.0767085[/C][C]0.153417[/C][C]0.923292[/C][/ROW]
[ROW][C]180[/C][C]0.064362[/C][C]0.128724[/C][C]0.935638[/C][/ROW]
[ROW][C]181[/C][C]0.0537881[/C][C]0.107576[/C][C]0.946212[/C][/ROW]
[ROW][C]182[/C][C]0.0615111[/C][C]0.123022[/C][C]0.938489[/C][/ROW]
[ROW][C]183[/C][C]0.0615614[/C][C]0.123123[/C][C]0.938439[/C][/ROW]
[ROW][C]184[/C][C]0.0570559[/C][C]0.114112[/C][C]0.942944[/C][/ROW]
[ROW][C]185[/C][C]0.227133[/C][C]0.454266[/C][C]0.772867[/C][/ROW]
[ROW][C]186[/C][C]0.20926[/C][C]0.41852[/C][C]0.79074[/C][/ROW]
[ROW][C]187[/C][C]0.187461[/C][C]0.374922[/C][C]0.812539[/C][/ROW]
[ROW][C]188[/C][C]0.187041[/C][C]0.374083[/C][C]0.812959[/C][/ROW]
[ROW][C]189[/C][C]0.17383[/C][C]0.347661[/C][C]0.82617[/C][/ROW]
[ROW][C]190[/C][C]0.257356[/C][C]0.514713[/C][C]0.742644[/C][/ROW]
[ROW][C]191[/C][C]0.262498[/C][C]0.524997[/C][C]0.737502[/C][/ROW]
[ROW][C]192[/C][C]0.232168[/C][C]0.464336[/C][C]0.767832[/C][/ROW]
[ROW][C]193[/C][C]0.607906[/C][C]0.784188[/C][C]0.392094[/C][/ROW]
[ROW][C]194[/C][C]0.57732[/C][C]0.845359[/C][C]0.42268[/C][/ROW]
[ROW][C]195[/C][C]0.540629[/C][C]0.918741[/C][C]0.459371[/C][/ROW]
[ROW][C]196[/C][C]0.50789[/C][C]0.984221[/C][C]0.49211[/C][/ROW]
[ROW][C]197[/C][C]0.522529[/C][C]0.954942[/C][C]0.477471[/C][/ROW]
[ROW][C]198[/C][C]0.48652[/C][C]0.97304[/C][C]0.51348[/C][/ROW]
[ROW][C]199[/C][C]0.46035[/C][C]0.9207[/C][C]0.53965[/C][/ROW]
[ROW][C]200[/C][C]0.462256[/C][C]0.924513[/C][C]0.537744[/C][/ROW]
[ROW][C]201[/C][C]0.436179[/C][C]0.872358[/C][C]0.563821[/C][/ROW]
[ROW][C]202[/C][C]0.415646[/C][C]0.831293[/C][C]0.584354[/C][/ROW]
[ROW][C]203[/C][C]0.393879[/C][C]0.787759[/C][C]0.606121[/C][/ROW]
[ROW][C]204[/C][C]0.444969[/C][C]0.889938[/C][C]0.555031[/C][/ROW]
[ROW][C]205[/C][C]0.479081[/C][C]0.958162[/C][C]0.520919[/C][/ROW]
[ROW][C]206[/C][C]0.436301[/C][C]0.872602[/C][C]0.563699[/C][/ROW]
[ROW][C]207[/C][C]0.396197[/C][C]0.792394[/C][C]0.603803[/C][/ROW]
[ROW][C]208[/C][C]0.356235[/C][C]0.712469[/C][C]0.643765[/C][/ROW]
[ROW][C]209[/C][C]0.337358[/C][C]0.674716[/C][C]0.662642[/C][/ROW]
[ROW][C]210[/C][C]0.299763[/C][C]0.599526[/C][C]0.700237[/C][/ROW]
[ROW][C]211[/C][C]0.365592[/C][C]0.731184[/C][C]0.634408[/C][/ROW]
[ROW][C]212[/C][C]0.382513[/C][C]0.765025[/C][C]0.617487[/C][/ROW]
[ROW][C]213[/C][C]0.340411[/C][C]0.680821[/C][C]0.659589[/C][/ROW]
[ROW][C]214[/C][C]0.361303[/C][C]0.722606[/C][C]0.638697[/C][/ROW]
[ROW][C]215[/C][C]0.325337[/C][C]0.650673[/C][C]0.674663[/C][/ROW]
[ROW][C]216[/C][C]0.288897[/C][C]0.577793[/C][C]0.711103[/C][/ROW]
[ROW][C]217[/C][C]0.253151[/C][C]0.506302[/C][C]0.746849[/C][/ROW]
[ROW][C]218[/C][C]0.216334[/C][C]0.432668[/C][C]0.783666[/C][/ROW]
[ROW][C]219[/C][C]0.214752[/C][C]0.429503[/C][C]0.785248[/C][/ROW]
[ROW][C]220[/C][C]0.190569[/C][C]0.381138[/C][C]0.809431[/C][/ROW]
[ROW][C]221[/C][C]0.233358[/C][C]0.466716[/C][C]0.766642[/C][/ROW]
[ROW][C]222[/C][C]0.197358[/C][C]0.394717[/C][C]0.802642[/C][/ROW]
[ROW][C]223[/C][C]0.189416[/C][C]0.378833[/C][C]0.810584[/C][/ROW]
[ROW][C]224[/C][C]0.164175[/C][C]0.32835[/C][C]0.835825[/C][/ROW]
[ROW][C]225[/C][C]0.13571[/C][C]0.27142[/C][C]0.86429[/C][/ROW]
[ROW][C]226[/C][C]0.111114[/C][C]0.222227[/C][C]0.888886[/C][/ROW]
[ROW][C]227[/C][C]0.089434[/C][C]0.178868[/C][C]0.910566[/C][/ROW]
[ROW][C]228[/C][C]0.071801[/C][C]0.143602[/C][C]0.928199[/C][/ROW]
[ROW][C]229[/C][C]0.0549717[/C][C]0.109943[/C][C]0.945028[/C][/ROW]
[ROW][C]230[/C][C]0.0419927[/C][C]0.0839854[/C][C]0.958007[/C][/ROW]
[ROW][C]231[/C][C]0.0614384[/C][C]0.122877[/C][C]0.938562[/C][/ROW]
[ROW][C]232[/C][C]0.0750872[/C][C]0.150174[/C][C]0.924913[/C][/ROW]
[ROW][C]233[/C][C]0.275054[/C][C]0.550108[/C][C]0.724946[/C][/ROW]
[ROW][C]234[/C][C]0.244076[/C][C]0.488153[/C][C]0.755924[/C][/ROW]
[ROW][C]235[/C][C]0.198724[/C][C]0.397447[/C][C]0.801276[/C][/ROW]
[ROW][C]236[/C][C]0.197642[/C][C]0.395284[/C][C]0.802358[/C][/ROW]
[ROW][C]237[/C][C]0.235554[/C][C]0.471108[/C][C]0.764446[/C][/ROW]
[ROW][C]238[/C][C]0.252636[/C][C]0.505273[/C][C]0.747364[/C][/ROW]
[ROW][C]239[/C][C]0.243944[/C][C]0.487889[/C][C]0.756056[/C][/ROW]
[ROW][C]240[/C][C]0.199515[/C][C]0.39903[/C][C]0.800485[/C][/ROW]
[ROW][C]241[/C][C]0.161943[/C][C]0.323885[/C][C]0.838057[/C][/ROW]
[ROW][C]242[/C][C]0.202205[/C][C]0.404409[/C][C]0.797795[/C][/ROW]
[ROW][C]243[/C][C]0.486234[/C][C]0.972467[/C][C]0.513766[/C][/ROW]
[ROW][C]244[/C][C]0.680244[/C][C]0.639511[/C][C]0.319756[/C][/ROW]
[ROW][C]245[/C][C]0.604163[/C][C]0.791674[/C][C]0.395837[/C][/ROW]
[ROW][C]246[/C][C]0.533902[/C][C]0.932196[/C][C]0.466098[/C][/ROW]
[ROW][C]247[/C][C]0.458897[/C][C]0.917794[/C][C]0.541103[/C][/ROW]
[ROW][C]248[/C][C]0.393358[/C][C]0.786715[/C][C]0.606642[/C][/ROW]
[ROW][C]249[/C][C]0.301859[/C][C]0.603718[/C][C]0.698141[/C][/ROW]
[ROW][C]250[/C][C]0.244789[/C][C]0.489579[/C][C]0.755211[/C][/ROW]
[ROW][C]251[/C][C]0.357007[/C][C]0.714013[/C][C]0.642993[/C][/ROW]
[ROW][C]252[/C][C]0.580107[/C][C]0.839786[/C][C]0.419893[/C][/ROW]
[ROW][C]253[/C][C]0.521626[/C][C]0.956747[/C][C]0.478374[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226044&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226044&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
110.991740.01651990.00825995
120.9882950.02340980.0117049
130.9759730.04805420.0240271
140.9752410.04951840.0247592
150.96250.07500080.0375004
160.9493960.1012080.0506041
170.9216210.1567580.078379
180.9182380.1635250.0817624
190.9014250.197150.0985752
200.8613710.2772580.138629
210.827180.345640.17282
220.7794010.4411970.220599
230.7339990.5320030.266001
240.6948520.6102950.305148
250.6429950.7140090.357005
260.6418980.7162040.358102
270.6598730.6802530.340127
280.6702570.6594860.329743
290.6101760.7796480.389824
300.5620020.8759950.437998
310.5116450.9767110.488355
320.5278140.9443720.472186
330.4672260.9344520.532774
340.412190.824380.58781
350.3948280.7896570.605172
360.3816490.7632980.618351
370.3314460.6628910.668554
380.3154670.6309340.684533
390.2960560.5921120.703944
400.2709090.5418170.729091
410.241490.482980.75851
420.2146010.4292010.785399
430.2531670.5063350.746833
440.2151920.4303850.784808
450.1796090.3592190.820391
460.2173220.4346440.782678
470.2363090.4726180.763691
480.1995870.3991750.800413
490.1887010.3774010.811299
500.1744030.3488060.825597
510.1816270.3632530.818373
520.1520430.3040860.847957
530.1582470.3164930.841753
540.139250.2784990.86075
550.2105380.4210770.789462
560.4752610.9505220.524739
570.4326040.8652080.567396
580.3903760.7807510.609624
590.350020.7000390.64998
600.3461280.6922560.653872
610.3499460.6998930.650054
620.3115060.6230120.688494
630.321420.6428390.67858
640.2853650.570730.714635
650.2602470.5204930.739753
660.2277910.4555830.772209
670.2092940.4185880.790706
680.1891530.3783060.810847
690.1884310.3768620.811569
700.1620310.3240620.837969
710.1429060.2858130.857094
720.1220290.2440580.877971
730.1041750.208350.895825
740.08858690.1771740.911413
750.07953690.1590740.920463
760.1006380.2012760.899362
770.09005320.1801060.909947
780.07468940.1493790.925311
790.07993070.1598610.920069
800.07671220.1534240.923288
810.06367410.1273480.936326
820.05263360.1052670.947366
830.04578320.09156650.954217
840.03722550.07445090.962775
850.03410670.06821330.965893
860.03880020.07760040.9612
870.0314260.0628520.968574
880.0256130.0512260.974387
890.02173120.04346240.978269
900.01819210.03638420.981808
910.03000140.06000280.969999
920.02487260.04974520.975127
930.02269470.04538950.977305
940.02440790.04881580.975592
950.0244150.04883010.975585
960.0221560.0443120.977844
970.02725750.0545150.972743
980.02209150.04418310.977908
990.01869520.03739030.981305
1000.02186680.04373370.978133
1010.0180530.03610590.981947
1020.01532290.03064590.984677
1030.01216390.02432780.987836
1040.01075450.02150910.989245
1050.01205950.02411890.987941
1060.009432810.01886560.990567
1070.007411170.01482230.992589
1080.00607660.01215320.993923
1090.008539390.01707880.991461
1100.006654240.01330850.993346
1110.007673860.01534770.992326
1120.008027640.01605530.991972
1130.006654810.01330960.993345
1140.005377910.01075580.994622
1150.004186610.008373210.995813
1160.00492560.009851210.995074
1170.007096660.01419330.992903
1180.005933370.01186670.994067
1190.004602450.009204890.995398
1200.00386210.00772420.996138
1210.003714530.007429070.996285
1220.003740030.007480050.99626
1230.004433010.008866010.995567
1240.005072840.01014570.994927
1250.009115850.01823170.990884
1260.00758380.01516760.992416
1270.006505670.01301130.993494
1280.006762550.01352510.993237
1290.006667210.01333440.993333
1300.006666250.01333250.993334
1310.008469750.01693950.99153
1320.01718880.03437760.982811
1330.01677550.03355110.983224
1340.01570690.03141380.984293
1350.01365340.02730680.986347
1360.01111010.02222010.98889
1370.008812590.01762520.991187
1380.007903890.01580780.992096
1390.007044320.01408860.992956
1400.005720240.01144050.99428
1410.01087720.02175440.989123
1420.01273610.02547220.987264
1430.01698010.03396020.98302
1440.01358820.02717630.986412
1450.01076190.02152380.989238
1460.008721010.0174420.991279
1470.009740070.01948010.99026
1480.007848220.01569640.992152
1490.006593310.01318660.993407
1500.005954090.01190820.994046
1510.006176190.01235240.993824
1520.008288420.01657680.991712
1530.05326920.1065380.946731
1540.06052230.1210450.939478
1550.05064190.1012840.949358
1560.07289170.1457830.927108
1570.1280920.2561840.871908
1580.1294470.2588950.870553
1590.1125470.2250930.887453
1600.1087990.2175970.891201
1610.1079180.2158360.892082
1620.09369090.1873820.906309
1630.08436260.1687250.915637
1640.08956180.1791240.910438
1650.08112490.162250.918875
1660.06902470.1380490.930975
1670.05871240.1174250.941288
1680.09761090.1952220.902389
1690.09912030.1982410.90088
1700.08622590.1724520.913774
1710.1497440.2994880.850256
1720.1299940.2599880.870006
1730.1144770.2289530.885523
1740.09844540.1968910.901555
1750.1358830.2717660.864117
1760.1177880.2355760.882212
1770.1058770.2117540.894123
1780.09080550.1816110.909195
1790.07670850.1534170.923292
1800.0643620.1287240.935638
1810.05378810.1075760.946212
1820.06151110.1230220.938489
1830.06156140.1231230.938439
1840.05705590.1141120.942944
1850.2271330.4542660.772867
1860.209260.418520.79074
1870.1874610.3749220.812539
1880.1870410.3740830.812959
1890.173830.3476610.82617
1900.2573560.5147130.742644
1910.2624980.5249970.737502
1920.2321680.4643360.767832
1930.6079060.7841880.392094
1940.577320.8453590.42268
1950.5406290.9187410.459371
1960.507890.9842210.49211
1970.5225290.9549420.477471
1980.486520.973040.51348
1990.460350.92070.53965
2000.4622560.9245130.537744
2010.4361790.8723580.563821
2020.4156460.8312930.584354
2030.3938790.7877590.606121
2040.4449690.8899380.555031
2050.4790810.9581620.520919
2060.4363010.8726020.563699
2070.3961970.7923940.603803
2080.3562350.7124690.643765
2090.3373580.6747160.662642
2100.2997630.5995260.700237
2110.3655920.7311840.634408
2120.3825130.7650250.617487
2130.3404110.6808210.659589
2140.3613030.7226060.638697
2150.3253370.6506730.674663
2160.2888970.5777930.711103
2170.2531510.5063020.746849
2180.2163340.4326680.783666
2190.2147520.4295030.785248
2200.1905690.3811380.809431
2210.2333580.4667160.766642
2220.1973580.3947170.802642
2230.1894160.3788330.810584
2240.1641750.328350.835825
2250.135710.271420.86429
2260.1111140.2222270.888886
2270.0894340.1788680.910566
2280.0718010.1436020.928199
2290.05497170.1099430.945028
2300.04199270.08398540.958007
2310.06143840.1228770.938562
2320.07508720.1501740.924913
2330.2750540.5501080.724946
2340.2440760.4881530.755924
2350.1987240.3974470.801276
2360.1976420.3952840.802358
2370.2355540.4711080.764446
2380.2526360.5052730.747364
2390.2439440.4878890.756056
2400.1995150.399030.800485
2410.1619430.3238850.838057
2420.2022050.4044090.797795
2430.4862340.9724670.513766
2440.6802440.6395110.319756
2450.6041630.7916740.395837
2460.5339020.9321960.466098
2470.4588970.9177940.541103
2480.3933580.7867150.606642
2490.3018590.6037180.698141
2500.2447890.4895790.755211
2510.3570070.7140130.642993
2520.5801070.8397860.419893
2530.5216260.9567470.478374






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level70.0288066NOK
5% type I error level660.271605NOK
10% type I error level760.312757NOK

\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 & 7 & 0.0288066 & NOK \tabularnewline
5% type I error level & 66 & 0.271605 & NOK \tabularnewline
10% type I error level & 76 & 0.312757 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226044&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]7[/C][C]0.0288066[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]66[/C][C]0.271605[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]76[/C][C]0.312757[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226044&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226044&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 level70.0288066NOK
5% type I error level660.271605NOK
10% type I error level760.312757NOK


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')
}