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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, 02 Dec 2013 13:19:19 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/02/t13860088805n5nupj8nmno241.htm/, Retrieved Thu, 28 Mar 2024 16:40:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230053, Retrieved Thu, 28 Mar 2024 16:40:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2013-12-02 18:19:19] [55c2cace1b2f0b23d7a5ea0032d37b7d] [Current]
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Dataseries X:
41 38 13 12 14 12 53 32 9
39 32 16 11 18 11 83 51 9
30 35 19 15 11 14 66 42 9
31 33 15 6 12 12 67 41 9
34 37 14 13 16 21 76 46 9
35 29 13 10 18 12 78 47 9
39 31 19 12 14 22 53 37 9
34 36 15 14 14 11 80 49 9
36 35 14 12 15 10 74 45 9
37 38 15 9 15 13 76 47 9
38 31 16 10 17 10 79 49 9
36 34 16 12 19 8 54 33 9
38 35 16 12 10 15 67 42 9
39 38 16 11 16 14 54 33 9
33 37 17 15 18 10 87 53 9
32 33 15 12 14 14 58 36 9
36 32 15 10 14 14 75 45 9
38 38 20 12 17 11 88 54 9
39 38 18 11 14 10 64 41 9
32 32 16 12 16 13 57 36 9
32 33 16 11 18 9.5 66 41 9
31 31 16 12 11 14 68 44 9
39 38 19 13 14 12 54 33 9
37 39 16 11 12 14 56 37 9
39 32 17 12 17 11 86 52 9
41 32 17 13 9 9 80 47 9
36 35 16 10 16 11 76 43 9
33 37 15 14 14 15 69 44 9
33 33 16 12 15 14 78 45 9
34 33 14 10 11 13 67 44 9
31 31 15 12 16 9 80 49 9
27 32 12 8 13 15 54 33 9
37 31 14 10 17 10 71 43 9
34 37 16 12 15 11 84 54 9
34 30 14 12 14 13 74 42 9
32 33 10 7 16 8 71 44 9
29 31 10 9 9 20 63 37 9
36 33 14 12 15 12 71 43 9
29 31 16 10 17 10 76 46 9
35 33 16 10 13 10 69 42 9
37 32 16 10 15 9 74 45 9
34 33 14 12 16 14 75 44 9
38 32 20 15 16 8 54 33 9
35 33 14 10 12 14 52 31 9
38 28 14 10 15 11 69 42 9
37 35 11 12 11 13 68 40 9
38 39 14 13 15 9 65 43 9
33 34 15 11 15 11 75 46 9
36 38 16 11 17 15 74 42 9
38 32 14 12 13 11 75 45 9
32 38 16 14 16 10 72 44 9
32 30 14 10 14 14 67 40 9
32 33 12 12 11 18 63 37 9
34 38 16 13 12 14 62 46 9
32 32 9 5 12 11 63 36 9
37 35 14 6 15 14.5 76 47 9
39 34 16 12 16 13 74 45 9
29 34 16 12 15 9 67 42 9
37 36 15 11 12 10 73 43 9
35 34 16 10 12 15 70 43 9
30 28 12 7 8 20 53 32 9
38 34 16 12 13 12 77 45 9
34 35 16 14 11 12 80 48 9
31 35 14 11 14 14 52 31 9
34 31 16 12 15 13 54 33 9
35 37 17 13 10 11 80 49 10
36 35 18 14 11 17 66 42 10
30 27 18 11 12 12 73 41 10
39 40 12 12 15 13 63 38 10
35 37 16 12 15 14 69 42 10
38 36 10 8 14 13 67 44 10
31 38 14 11 16 15 54 33 10
34 39 18 14 15 13 81 48 10
38 41 18 14 15 10 69 40 10
34 27 16 12 13 11 84 50 10
39 30 17 9 12 19 80 49 10
37 37 16 13 17 13 70 43 10
34 31 16 11 13 17 69 44 10
28 31 13 12 15 13 77 47 10
37 27 16 12 13 9 54 33 10
33 36 16 12 15 11 79 46 10
35 37 16 12 15 9 71 45 10
37 33 15 12 16 12 73 43 10
32 34 15 11 15 12 72 44 10
33 31 16 10 14 13 77 47 10
38 39 14 9 15 13 75 45 10
33 34 16 12 14 12 69 42 10
29 32 16 12 13 15 54 33 10
33 33 15 12 7 22 70 43 10
31 36 12 9 17 13 73 46 10
36 32 17 15 13 15 54 33 10
35 41 16 12 15 13 77 46 10
32 28 15 12 14 15 82 48 10
29 30 13 12 13 12.5 80 47 10
39 36 16 10 16 11 80 47 10
37 35 16 13 12 16 69 43 10
35 31 16 9 14 11 78 46 10
37 34 16 12 17 11 81 48 10
32 36 14 10 15 10 76 46 10
38 36 16 14 17 10 76 45 10
37 35 16 11 12 16 73 45 10
36 37 20 15 16 12 85 52 10
32 28 15 11 11 11 66 42 10
33 39 16 11 15 16 79 47 10
40 32 13 12 9 19 68 41 10
38 35 17 12 16 11 76 47 10
41 39 16 12 15 16 71 43 10
36 35 16 11 10 15 54 33 10
43 42 12 7 10 24 46 30 10
30 34 16 12 15 14 85 52 10
31 33 16 14 11 15 74 44 10
32 41 17 11 13 11 88 55 10
32 33 13 11 14 15 38 11 10
37 34 12 10 18 12 76 47 10
37 32 18 13 16 10 86 53 10
33 40 14 13 14 14 54 33 10
34 40 14 8 14 13 67 44 10
33 35 13 11 14 9 69 42 10
38 36 16 12 14 15 90 55 10
33 37 13 11 12 15 54 33 10
31 27 16 13 14 14 76 46 10
38 39 13 12 15 11 89 54 10
37 38 16 14 15 8 76 47 10
36 31 15 13 15 11 73 45 10
31 33 16 15 13 11 79 47 10
39 32 15 10 17 8 90 55 10
44 39 17 11 17 10 74 44 10
33 36 15 9 19 11 81 53 10
35 33 12 11 15 13 72 44 10
32 33 16 10 13 11 71 42 10
28 32 10 11 9 20 66 40 10
40 37 16 8 15 10 77 46 10
27 30 12 11 15 15 65 40 10
37 38 14 12 15 12 74 46 10
32 29 15 12 16 14 85 53 10
28 22 13 9 11 23 54 33 10
34 35 15 11 14 14 63 42 10
30 35 11 10 11 16 54 35 10
35 34 12 8 15 11 64 40 10
31 35 11 9 13 12 69 41 10
32 34 16 8 15 10 54 33 10
30 37 15 9 16 14 84 51 10
30 35 17 15 14 12 86 53 10
31 23 16 11 15 12 77 46 10
40 31 10 8 16 11 89 55 10
32 27 18 13 16 12 76 47 10
36 36 13 12 11 13 60 38 10
32 31 16 12 12 11 75 46 10
35 32 13 9 9 19 73 46 10
38 39 10 7 16 12 85 53 10
42 37 15 13 13 17 79 47 10
34 38 16 9 16 9 71 41 10
35 39 16 6 12 12 72 44 10
38 34 14 8 9 19 69 43 9
33 31 10 8 13 18 78 51 10
36 32 17 15 13 15 54 33 10
32 37 13 6 14 14 69 43 10
33 36 15 9 19 11 81 53 10
34 32 16 11 13 9 84 51 10
32 38 12 8 12 18 84 50 10
34 36 13 8 13 16 69 46 10
27 26 13 10 10 24 66 43 11
31 26 12 8 14 14 81 47 11
38 33 17 14 16 20 82 50 11
34 39 15 10 10 18 72 43 11
24 30 10 8 11 23 54 33 11
30 33 14 11 14 12 78 48 11
26 25 11 12 12 14 74 44 11
34 38 13 12 9 16 82 50 11
27 37 16 12 9 18 73 41 11
37 31 12 5 11 20 55 34 11
36 37 16 12 16 12 72 44 11
41 35 12 10 9 12 78 47 11
29 25 9 7 13 17 59 35 11
36 28 12 12 16 13 72 44 11
32 35 15 11 13 9 78 44 11
37 33 12 8 9 16 68 43 11
30 30 12 9 12 18 69 41 11
31 31 14 10 16 10 67 41 11
38 37 12 9 11 14 74 42 11
36 36 16 12 14 11 54 33 11
35 30 11 6 13 9 67 41 11
31 36 19 15 15 11 70 44 11
38 32 15 12 14 10 80 48 11
22 28 8 12 16 11 89 55 11
32 36 16 12 13 19 76 44 11
36 34 17 11 14 14 74 43 11
39 31 12 7 15 12 87 52 11
28 28 11 7 13 14 54 30 11
32 36 11 5 11 21 61 39 11
32 36 14 12 11 13 38 11 11
38 40 16 12 14 10 75 44 11
32 33 12 3 15 15 69 42 11
35 37 16 11 11 16 62 41 11
32 32 13 10 15 14 72 44 11
37 38 15 12 12 12 70 44 11
34 31 16 9 14 19 79 48 11
33 37 16 12 14 15 87 53 11
33 33 14 9 8 19 62 37 11
26 32 16 12 13 13 77 44 11
30 30 16 12 9 17 69 44 11
24 30 14 10 15 12 69 40 11
34 31 11 9 17 11 75 42 11
34 32 12 12 13 14 54 35 11
33 34 15 8 15 11 72 43 11
34 36 15 11 15 13 74 45 11
35 37 16 11 14 12 85 55 11
35 36 16 12 16 15 52 31 11
36 33 11 10 13 14 70 44 11
34 33 15 10 16 12 84 50 11
34 33 12 12 9 17 64 40 11
41 44 12 12 16 11 84 53 11
32 39 15 11 11 18 87 54 11
30 32 15 8 10 13 79 49 11
35 35 16 12 11 17 67 40 11
28 25 14 10 15 13 65 41 11
33 35 17 11 17 11 85 52 11
39 34 14 10 14 12 83 52 11
36 35 13 8 8 22 61 36 11
36 39 15 12 15 14 82 52 11
35 33 13 12 11 12 76 46 11
38 36 14 10 16 12 58 31 11
33 32 15 12 10 17 72 44 11
31 32 12 9 15 9 72 44 11
34 36 13 9 9 21 38 11 11
32 36 8 6 16 10 78 46 11
31 32 14 10 19 11 54 33 11
33 34 14 9 12 12 63 34 11
34 33 11 9 8 23 66 42 11
34 35 12 9 11 13 70 43 11
34 30 13 6 14 12 71 43 11
33 38 10 10 9 16 67 44 11
32 34 16 6 15 9 58 36 11
41 33 18 14 13 17 72 46 11
34 32 13 10 16 9 72 44 11
36 31 11 10 11 14 70 43 11
37 30 4 6 12 17 76 50 11
36 27 13 12 13 13 50 33 11
29 31 16 12 10 11 72 43 11
37 30 10 7 11 12 72 44 11
27 32 12 8 12 10 88 53 11
35 35 12 11 8 19 53 34 11
28 28 10 3 12 16 58 35 11
35 33 13 6 12 16 66 40 11
37 31 15 10 15 14 82 53 11
29 35 12 8 11 20 69 42 11
32 35 14 9 13 15 68 43 11
36 32 10 9 14 23 44 29 11
19 21 12 8 10 20 56 36 11
21 20 12 9 12 16 53 30 11
31 34 11 7 15 14 70 42 11
33 32 10 7 13 17 78 47 11
36 34 12 6 13 11 71 44 11
33 32 16 9 13 13 72 45 11
37 33 12 10 12 17 68 44 11
34 33 14 11 12 15 67 43 11
35 37 16 12 9 21 75 43 11
31 32 14 8 9 18 62 40 11
37 34 13 11 15 15 67 41 11
35 30 4 3 10 8 83 52 11
27 30 15 11 14 12 64 38 11
34 38 11 12 15 12 68 41 11
40 36 11 7 7 22 62 39 11
29 32 14 9 14 12 72 43 11
    




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time21 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 21 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230053&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]21 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230053&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230053&T=0

As an alternative you can also use a 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 time21 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 18.2331 + 0.00399972Connected[t] + 0.0118355Separate[t] + 0.0926299Learning[t] -0.0199196Software[t] -0.36355Depression[t] + 0.0165415Sport1[t] + 0.0147119Sport2[t] -0.317163Month[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  18.2331 +  0.00399972Connected[t] +  0.0118355Separate[t] +  0.0926299Learning[t] -0.0199196Software[t] -0.36355Depression[t] +  0.0165415Sport1[t] +  0.0147119Sport2[t] -0.317163Month[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230053&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  18.2331 +  0.00399972Connected[t] +  0.0118355Separate[t] +  0.0926299Learning[t] -0.0199196Software[t] -0.36355Depression[t] +  0.0165415Sport1[t] +  0.0147119Sport2[t] -0.317163Month[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230053&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230053&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 18.2331 + 0.00399972Connected[t] + 0.0118355Separate[t] + 0.0926299Learning[t] -0.0199196Software[t] -0.36355Depression[t] + 0.0165415Sport1[t] + 0.0147119Sport2[t] -0.317163Month[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)18.23312.642316.94.08604e-112.04302e-11
Connected0.003999720.03756040.10650.9152790.45764
Separate0.01183550.03815810.31020.7566850.378342
Learning0.09262990.06729461.3760.1698790.0849396
Software-0.01991960.0689353-0.2890.7728460.386423
Depression-0.363550.0397476-9.1461.93288e-179.66442e-18
Sport10.01654150.04076630.40580.6852570.342628
Sport20.01471190.06053980.2430.8081910.404096
Month-0.3171630.173074-1.8330.0680390.0340195

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 18.2331 & 2.64231 & 6.9 & 4.08604e-11 & 2.04302e-11 \tabularnewline
Connected & 0.00399972 & 0.0375604 & 0.1065 & 0.915279 & 0.45764 \tabularnewline
Separate & 0.0118355 & 0.0381581 & 0.3102 & 0.756685 & 0.378342 \tabularnewline
Learning & 0.0926299 & 0.0672946 & 1.376 & 0.169879 & 0.0849396 \tabularnewline
Software & -0.0199196 & 0.0689353 & -0.289 & 0.772846 & 0.386423 \tabularnewline
Depression & -0.36355 & 0.0397476 & -9.146 & 1.93288e-17 & 9.66442e-18 \tabularnewline
Sport1 & 0.0165415 & 0.0407663 & 0.4058 & 0.685257 & 0.342628 \tabularnewline
Sport2 & 0.0147119 & 0.0605398 & 0.243 & 0.808191 & 0.404096 \tabularnewline
Month & -0.317163 & 0.173074 & -1.833 & 0.068039 & 0.0340195 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230053&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]18.2331[/C][C]2.64231[/C][C]6.9[/C][C]4.08604e-11[/C][C]2.04302e-11[/C][/ROW]
[ROW][C]Connected[/C][C]0.00399972[/C][C]0.0375604[/C][C]0.1065[/C][C]0.915279[/C][C]0.45764[/C][/ROW]
[ROW][C]Separate[/C][C]0.0118355[/C][C]0.0381581[/C][C]0.3102[/C][C]0.756685[/C][C]0.378342[/C][/ROW]
[ROW][C]Learning[/C][C]0.0926299[/C][C]0.0672946[/C][C]1.376[/C][C]0.169879[/C][C]0.0849396[/C][/ROW]
[ROW][C]Software[/C][C]-0.0199196[/C][C]0.0689353[/C][C]-0.289[/C][C]0.772846[/C][C]0.386423[/C][/ROW]
[ROW][C]Depression[/C][C]-0.36355[/C][C]0.0397476[/C][C]-9.146[/C][C]1.93288e-17[/C][C]9.66442e-18[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0165415[/C][C]0.0407663[/C][C]0.4058[/C][C]0.685257[/C][C]0.342628[/C][/ROW]
[ROW][C]Sport2[/C][C]0.0147119[/C][C]0.0605398[/C][C]0.243[/C][C]0.808191[/C][C]0.404096[/C][/ROW]
[ROW][C]Month[/C][C]-0.317163[/C][C]0.173074[/C][C]-1.833[/C][C]0.068039[/C][C]0.0340195[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230053&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230053&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)18.23312.642316.94.08604e-112.04302e-11
Connected0.003999720.03756040.10650.9152790.45764
Separate0.01183550.03815810.31020.7566850.378342
Learning0.09262990.06729461.3760.1698790.0849396
Software-0.01991960.0689353-0.2890.7728460.386423
Depression-0.363550.0397476-9.1461.93288e-179.66442e-18
Sport10.01654150.04076630.40580.6852570.342628
Sport20.01471190.06053980.2430.8081910.404096
Month-0.3171630.173074-1.8330.0680390.0340195







Multiple Linear Regression - Regression Statistics
Multiple R0.609698
R-squared0.371732
Adjusted R-squared0.352022
F-TEST (value)18.8597
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01134
Sum Squared Residuals1031.59

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.609698 \tabularnewline
R-squared & 0.371732 \tabularnewline
Adjusted R-squared & 0.352022 \tabularnewline
F-TEST (value) & 18.8597 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.01134 \tabularnewline
Sum Squared Residuals & 1031.59 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230053&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.609698[/C][/ROW]
[ROW][C]R-squared[/C][C]0.371732[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.352022[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]18.8597[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.01134[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1031.59[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230053&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230053&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.609698
R-squared0.371732
Adjusted R-squared0.352022
F-TEST (value)18.8597
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01134
Sum Squared Residuals1031.59







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.94240.0575709
21815.30052.69945
31113.994-2.994
41214.512-2.51202
51611.28984.71022
61814.4863.51403
71410.84543.15458
81415.0965-1.09645
91515.2453-0.245279
101514.4090.590968
111715.57261.42741
121915.63843.36157
131013.4609-3.46086
141613.53642.46361
151815.80782.19218
161413.4470.553031
171413.90460.0954157
181715.8451.155
191415.459-1.45896
201613.87482.12523
211815.40142.59862
221113.795-2.79504
231414.5015-0.501543
241213.6322-1.63216
251715.43761.56241
26915.98-6.97996
271615.11050.889512
281413.39460.605426
291514.00680.993164
301114.0323-3.0323
311615.79220.207785
321312.74310.256927
331715.16271.83727
341515.3805-0.380483
351414.0433-0.0433172
361615.59750.402549
37910.924-1.92403
381514.41550.58454
391715.44281.55717
401315.3159-2.31586
411515.8024-0.802421
421613.76122.23876
431615.93350.0664801
441213.2334-1.23337
451514.71990.280123
461113.7079-2.70793
471515.466-0.465954
481515.0017-0.00169777
491713.62413.37592
501314.8708-1.87076
511615.36240.637587
521413.56640.433607
531111.8123-0.8123
541213.8001-1.80014
551214.1921-2.19215
561513.79531.20467
571614.34011.65995
581515.5943-0.594329
591215.3277-3.3277
601213.5412-1.5412
61810.8786-2.87865
621314.7492-1.74923
631114.799-3.79899
641413.22110.778878
651513.77721.22282
661015.0003-5.0003
671112.5375-1.53748
681214.3974-2.39738
691513.43841.56156
701513.5521.448
711413.4360.564042
721612.63843.36158
731514.36740.632585
741515.1815-0.181542
751314.8861-1.88612
761212.1047-0.104735
771713.93493.06511
781312.43570.564314
791513.74451.25545
801314.8789-1.87887
811514.84710.152919
821515.447-0.446972
831614.2281.77199
841514.23790.762063
851414.0823-0.0822727
861513.96911.03089
871414.2356-0.235598
881312.72470.27525
89710.5269-3.52689
901713.7023.29803
911312.78560.214381
921514.15410.845924
931413.28060.719383
941313.9681-0.968109
951614.94221.05783
961212.804-0.804026
971414.8391-0.839121
981714.90192.09808
991515.0116-0.0115866
1001715.12651.87355
1011212.9395-0.939455
1021615.00560.994353
1031114.4018-3.4018
1041513.09951.90053
105911.3859-2.38593
1061614.9131.08704
1071512.92042.07963
1081012.8082-2.80817
109109.179760.820236
1101513.90831.09172
1111113.1974-2.19741
1121315.2961-2.29609
1131411.90232.09771
1141814.11033.88973
1151615.56340.436598
1161412.99381.0062
1171413.83780.162179
1181415.0801-1.08011
1191413.72720.272756
1201212.542-0.541956
1211413.57240.427631
1221514.90780.092193
1231515.9026-0.902649
1241514.57340.426607
1251314.7585-1.75853
1261716.1760.82404
1271715.29061.70945
1281914.95034.04972
1291513.59671.40334
1301314.6562-1.65624
131910.6686-1.66862
1321515.2971-0.29706
1331512.62742.37258
1341514.25520.744766
1351613.77922.22081
136119.475871.52413
1371413.35240.647625
1381112.0068-1.00682
1391514.20420.795825
1401313.8213-0.821332
1411514.65780.342153
1421613.87972.12034
1431414.7113-0.711342
1441514.30850.691493
1451614.63761.36238
1461614.50341.49656
1471113.4221-2.42211
1481214.7177-2.71774
149911.582-2.58196
1501614.28511.71491
1511312.61580.384222
1521615.45570.544281
1531214.5013-2.50134
154911.937-2.93704
1551311.8241.17603
1561312.78560.214381
1571413.39630.603654
1581914.95034.04972
1591315.707-2.70703
1601212.1726-0.172618
1611312.66970.330294
162109.164190.835808
1631413.06990.930132
1641611.40374.59628
1651011.8119-1.81186
166118.979422.02058
1671413.96640.0335952
1681212.7058-0.705799
169912.5704-3.57042
170911.8001-2.8001
1711110.41020.589829
1721614.0451.95501
173913.854-4.85402
1741311.1611.83904
1751613.20442.7956
1761315.1225-2.12251
177912.1757-3.17573
1781211.35230.647678
1791614.40881.59119
1801113.0188-2.01879
1811413.93710.0628745
1821314.5783-1.57832
1831514.56180.438248
1841414.8195-0.81946
1851613.9482.05198
1861311.53851.46153
1871413.41330.586697
1881514.08090.919129
1891312.31210.687893
1901110.1660.834021
1911112.4204-1.42044
1921414.8652-0.865219
1931512.62072.37929
1941112.3972-1.39716
1951513.00471.99534
1961213.9351-1.93511
1971411.65552.34448
1981413.32290.67713
199811.0469-3.0469
2001313.665-0.664972
201912.0708-3.07077
2021513.66031.33975
2031713.94633.05366
2041312.450.549961
2051514.33340.66663
2061513.63671.36331
2071414.4378-0.437779
2081612.41643.58358
2091312.81420.185846
2101614.22361.77637
211911.6102-2.6102
2121614.47181.52823
2131112.1939-1.19389
2141013.7747-3.77466
2151112.058-1.05801
2161513.20211.79793
2171714.81822.18185
2181414.1757-0.175713
21989.88796-1.88796
2201513.5321.46796
2211113.8113-2.81135
2221613.47292.5271
2231012.0634-2.06343
2241514.74570.254299
22599.48717-0.487171
2261614.25141.74859
2271913.72445.27564
2281213.576-1.57599
22989.45854-1.45854
2301113.2912-2.29121
2311413.76450.235484
232911.992-2.99198
2331514.85440.145625
2341312.37470.625259
2351614.83041.16959
2361112.7758-1.77577
2371211.31080.689212
2381312.75950.240549
2391014.2948-4.29482
2401113.51-2.50996
2411214.7831-2.78314
242810.6605-2.66046
2431211.71180.288218
2441212.223-0.22298
2451513.49591.50409
2461110.7150.284968
2471312.70830.291709
248148.80695.1931
2491010.206-0.206027
2501211.49860.501425
2511512.83632.16367
2521311.84331.15673
2531314.1055-1.10549
2541313.6847-0.684733
2551211.78710.212949
2561212.6362-0.636239
257910.804-1.80395
258911.4547-2.45467
2591512.5382.46198
2601014.7797-4.77971
2611413.63280.367171
2621513.47541.52463
26379.81113-2.81113
2641413.81760.1824

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 13.9424 & 0.0575709 \tabularnewline
2 & 18 & 15.3005 & 2.69945 \tabularnewline
3 & 11 & 13.994 & -2.994 \tabularnewline
4 & 12 & 14.512 & -2.51202 \tabularnewline
5 & 16 & 11.2898 & 4.71022 \tabularnewline
6 & 18 & 14.486 & 3.51403 \tabularnewline
7 & 14 & 10.8454 & 3.15458 \tabularnewline
8 & 14 & 15.0965 & -1.09645 \tabularnewline
9 & 15 & 15.2453 & -0.245279 \tabularnewline
10 & 15 & 14.409 & 0.590968 \tabularnewline
11 & 17 & 15.5726 & 1.42741 \tabularnewline
12 & 19 & 15.6384 & 3.36157 \tabularnewline
13 & 10 & 13.4609 & -3.46086 \tabularnewline
14 & 16 & 13.5364 & 2.46361 \tabularnewline
15 & 18 & 15.8078 & 2.19218 \tabularnewline
16 & 14 & 13.447 & 0.553031 \tabularnewline
17 & 14 & 13.9046 & 0.0954157 \tabularnewline
18 & 17 & 15.845 & 1.155 \tabularnewline
19 & 14 & 15.459 & -1.45896 \tabularnewline
20 & 16 & 13.8748 & 2.12523 \tabularnewline
21 & 18 & 15.4014 & 2.59862 \tabularnewline
22 & 11 & 13.795 & -2.79504 \tabularnewline
23 & 14 & 14.5015 & -0.501543 \tabularnewline
24 & 12 & 13.6322 & -1.63216 \tabularnewline
25 & 17 & 15.4376 & 1.56241 \tabularnewline
26 & 9 & 15.98 & -6.97996 \tabularnewline
27 & 16 & 15.1105 & 0.889512 \tabularnewline
28 & 14 & 13.3946 & 0.605426 \tabularnewline
29 & 15 & 14.0068 & 0.993164 \tabularnewline
30 & 11 & 14.0323 & -3.0323 \tabularnewline
31 & 16 & 15.7922 & 0.207785 \tabularnewline
32 & 13 & 12.7431 & 0.256927 \tabularnewline
33 & 17 & 15.1627 & 1.83727 \tabularnewline
34 & 15 & 15.3805 & -0.380483 \tabularnewline
35 & 14 & 14.0433 & -0.0433172 \tabularnewline
36 & 16 & 15.5975 & 0.402549 \tabularnewline
37 & 9 & 10.924 & -1.92403 \tabularnewline
38 & 15 & 14.4155 & 0.58454 \tabularnewline
39 & 17 & 15.4428 & 1.55717 \tabularnewline
40 & 13 & 15.3159 & -2.31586 \tabularnewline
41 & 15 & 15.8024 & -0.802421 \tabularnewline
42 & 16 & 13.7612 & 2.23876 \tabularnewline
43 & 16 & 15.9335 & 0.0664801 \tabularnewline
44 & 12 & 13.2334 & -1.23337 \tabularnewline
45 & 15 & 14.7199 & 0.280123 \tabularnewline
46 & 11 & 13.7079 & -2.70793 \tabularnewline
47 & 15 & 15.466 & -0.465954 \tabularnewline
48 & 15 & 15.0017 & -0.00169777 \tabularnewline
49 & 17 & 13.6241 & 3.37592 \tabularnewline
50 & 13 & 14.8708 & -1.87076 \tabularnewline
51 & 16 & 15.3624 & 0.637587 \tabularnewline
52 & 14 & 13.5664 & 0.433607 \tabularnewline
53 & 11 & 11.8123 & -0.8123 \tabularnewline
54 & 12 & 13.8001 & -1.80014 \tabularnewline
55 & 12 & 14.1921 & -2.19215 \tabularnewline
56 & 15 & 13.7953 & 1.20467 \tabularnewline
57 & 16 & 14.3401 & 1.65995 \tabularnewline
58 & 15 & 15.5943 & -0.594329 \tabularnewline
59 & 12 & 15.3277 & -3.3277 \tabularnewline
60 & 12 & 13.5412 & -1.5412 \tabularnewline
61 & 8 & 10.8786 & -2.87865 \tabularnewline
62 & 13 & 14.7492 & -1.74923 \tabularnewline
63 & 11 & 14.799 & -3.79899 \tabularnewline
64 & 14 & 13.2211 & 0.778878 \tabularnewline
65 & 15 & 13.7772 & 1.22282 \tabularnewline
66 & 10 & 15.0003 & -5.0003 \tabularnewline
67 & 11 & 12.5375 & -1.53748 \tabularnewline
68 & 12 & 14.3974 & -2.39738 \tabularnewline
69 & 15 & 13.4384 & 1.56156 \tabularnewline
70 & 15 & 13.552 & 1.448 \tabularnewline
71 & 14 & 13.436 & 0.564042 \tabularnewline
72 & 16 & 12.6384 & 3.36158 \tabularnewline
73 & 15 & 14.3674 & 0.632585 \tabularnewline
74 & 15 & 15.1815 & -0.181542 \tabularnewline
75 & 13 & 14.8861 & -1.88612 \tabularnewline
76 & 12 & 12.1047 & -0.104735 \tabularnewline
77 & 17 & 13.9349 & 3.06511 \tabularnewline
78 & 13 & 12.4357 & 0.564314 \tabularnewline
79 & 15 & 13.7445 & 1.25545 \tabularnewline
80 & 13 & 14.8789 & -1.87887 \tabularnewline
81 & 15 & 14.8471 & 0.152919 \tabularnewline
82 & 15 & 15.447 & -0.446972 \tabularnewline
83 & 16 & 14.228 & 1.77199 \tabularnewline
84 & 15 & 14.2379 & 0.762063 \tabularnewline
85 & 14 & 14.0823 & -0.0822727 \tabularnewline
86 & 15 & 13.9691 & 1.03089 \tabularnewline
87 & 14 & 14.2356 & -0.235598 \tabularnewline
88 & 13 & 12.7247 & 0.27525 \tabularnewline
89 & 7 & 10.5269 & -3.52689 \tabularnewline
90 & 17 & 13.702 & 3.29803 \tabularnewline
91 & 13 & 12.7856 & 0.214381 \tabularnewline
92 & 15 & 14.1541 & 0.845924 \tabularnewline
93 & 14 & 13.2806 & 0.719383 \tabularnewline
94 & 13 & 13.9681 & -0.968109 \tabularnewline
95 & 16 & 14.9422 & 1.05783 \tabularnewline
96 & 12 & 12.804 & -0.804026 \tabularnewline
97 & 14 & 14.8391 & -0.839121 \tabularnewline
98 & 17 & 14.9019 & 2.09808 \tabularnewline
99 & 15 & 15.0116 & -0.0115866 \tabularnewline
100 & 17 & 15.1265 & 1.87355 \tabularnewline
101 & 12 & 12.9395 & -0.939455 \tabularnewline
102 & 16 & 15.0056 & 0.994353 \tabularnewline
103 & 11 & 14.4018 & -3.4018 \tabularnewline
104 & 15 & 13.0995 & 1.90053 \tabularnewline
105 & 9 & 11.3859 & -2.38593 \tabularnewline
106 & 16 & 14.913 & 1.08704 \tabularnewline
107 & 15 & 12.9204 & 2.07963 \tabularnewline
108 & 10 & 12.8082 & -2.80817 \tabularnewline
109 & 10 & 9.17976 & 0.820236 \tabularnewline
110 & 15 & 13.9083 & 1.09172 \tabularnewline
111 & 11 & 13.1974 & -2.19741 \tabularnewline
112 & 13 & 15.2961 & -2.29609 \tabularnewline
113 & 14 & 11.9023 & 2.09771 \tabularnewline
114 & 18 & 14.1103 & 3.88973 \tabularnewline
115 & 16 & 15.5634 & 0.436598 \tabularnewline
116 & 14 & 12.9938 & 1.0062 \tabularnewline
117 & 14 & 13.8378 & 0.162179 \tabularnewline
118 & 14 & 15.0801 & -1.08011 \tabularnewline
119 & 14 & 13.7272 & 0.272756 \tabularnewline
120 & 12 & 12.542 & -0.541956 \tabularnewline
121 & 14 & 13.5724 & 0.427631 \tabularnewline
122 & 15 & 14.9078 & 0.092193 \tabularnewline
123 & 15 & 15.9026 & -0.902649 \tabularnewline
124 & 15 & 14.5734 & 0.426607 \tabularnewline
125 & 13 & 14.7585 & -1.75853 \tabularnewline
126 & 17 & 16.176 & 0.82404 \tabularnewline
127 & 17 & 15.2906 & 1.70945 \tabularnewline
128 & 19 & 14.9503 & 4.04972 \tabularnewline
129 & 15 & 13.5967 & 1.40334 \tabularnewline
130 & 13 & 14.6562 & -1.65624 \tabularnewline
131 & 9 & 10.6686 & -1.66862 \tabularnewline
132 & 15 & 15.2971 & -0.29706 \tabularnewline
133 & 15 & 12.6274 & 2.37258 \tabularnewline
134 & 15 & 14.2552 & 0.744766 \tabularnewline
135 & 16 & 13.7792 & 2.22081 \tabularnewline
136 & 11 & 9.47587 & 1.52413 \tabularnewline
137 & 14 & 13.3524 & 0.647625 \tabularnewline
138 & 11 & 12.0068 & -1.00682 \tabularnewline
139 & 15 & 14.2042 & 0.795825 \tabularnewline
140 & 13 & 13.8213 & -0.821332 \tabularnewline
141 & 15 & 14.6578 & 0.342153 \tabularnewline
142 & 16 & 13.8797 & 2.12034 \tabularnewline
143 & 14 & 14.7113 & -0.711342 \tabularnewline
144 & 15 & 14.3085 & 0.691493 \tabularnewline
145 & 16 & 14.6376 & 1.36238 \tabularnewline
146 & 16 & 14.5034 & 1.49656 \tabularnewline
147 & 11 & 13.4221 & -2.42211 \tabularnewline
148 & 12 & 14.7177 & -2.71774 \tabularnewline
149 & 9 & 11.582 & -2.58196 \tabularnewline
150 & 16 & 14.2851 & 1.71491 \tabularnewline
151 & 13 & 12.6158 & 0.384222 \tabularnewline
152 & 16 & 15.4557 & 0.544281 \tabularnewline
153 & 12 & 14.5013 & -2.50134 \tabularnewline
154 & 9 & 11.937 & -2.93704 \tabularnewline
155 & 13 & 11.824 & 1.17603 \tabularnewline
156 & 13 & 12.7856 & 0.214381 \tabularnewline
157 & 14 & 13.3963 & 0.603654 \tabularnewline
158 & 19 & 14.9503 & 4.04972 \tabularnewline
159 & 13 & 15.707 & -2.70703 \tabularnewline
160 & 12 & 12.1726 & -0.172618 \tabularnewline
161 & 13 & 12.6697 & 0.330294 \tabularnewline
162 & 10 & 9.16419 & 0.835808 \tabularnewline
163 & 14 & 13.0699 & 0.930132 \tabularnewline
164 & 16 & 11.4037 & 4.59628 \tabularnewline
165 & 10 & 11.8119 & -1.81186 \tabularnewline
166 & 11 & 8.97942 & 2.02058 \tabularnewline
167 & 14 & 13.9664 & 0.0335952 \tabularnewline
168 & 12 & 12.7058 & -0.705799 \tabularnewline
169 & 9 & 12.5704 & -3.57042 \tabularnewline
170 & 9 & 11.8001 & -2.8001 \tabularnewline
171 & 11 & 10.4102 & 0.589829 \tabularnewline
172 & 16 & 14.045 & 1.95501 \tabularnewline
173 & 9 & 13.854 & -4.85402 \tabularnewline
174 & 13 & 11.161 & 1.83904 \tabularnewline
175 & 16 & 13.2044 & 2.7956 \tabularnewline
176 & 13 & 15.1225 & -2.12251 \tabularnewline
177 & 9 & 12.1757 & -3.17573 \tabularnewline
178 & 12 & 11.3523 & 0.647678 \tabularnewline
179 & 16 & 14.4088 & 1.59119 \tabularnewline
180 & 11 & 13.0188 & -2.01879 \tabularnewline
181 & 14 & 13.9371 & 0.0628745 \tabularnewline
182 & 13 & 14.5783 & -1.57832 \tabularnewline
183 & 15 & 14.5618 & 0.438248 \tabularnewline
184 & 14 & 14.8195 & -0.81946 \tabularnewline
185 & 16 & 13.948 & 2.05198 \tabularnewline
186 & 13 & 11.5385 & 1.46153 \tabularnewline
187 & 14 & 13.4133 & 0.586697 \tabularnewline
188 & 15 & 14.0809 & 0.919129 \tabularnewline
189 & 13 & 12.3121 & 0.687893 \tabularnewline
190 & 11 & 10.166 & 0.834021 \tabularnewline
191 & 11 & 12.4204 & -1.42044 \tabularnewline
192 & 14 & 14.8652 & -0.865219 \tabularnewline
193 & 15 & 12.6207 & 2.37929 \tabularnewline
194 & 11 & 12.3972 & -1.39716 \tabularnewline
195 & 15 & 13.0047 & 1.99534 \tabularnewline
196 & 12 & 13.9351 & -1.93511 \tabularnewline
197 & 14 & 11.6555 & 2.34448 \tabularnewline
198 & 14 & 13.3229 & 0.67713 \tabularnewline
199 & 8 & 11.0469 & -3.0469 \tabularnewline
200 & 13 & 13.665 & -0.664972 \tabularnewline
201 & 9 & 12.0708 & -3.07077 \tabularnewline
202 & 15 & 13.6603 & 1.33975 \tabularnewline
203 & 17 & 13.9463 & 3.05366 \tabularnewline
204 & 13 & 12.45 & 0.549961 \tabularnewline
205 & 15 & 14.3334 & 0.66663 \tabularnewline
206 & 15 & 13.6367 & 1.36331 \tabularnewline
207 & 14 & 14.4378 & -0.437779 \tabularnewline
208 & 16 & 12.4164 & 3.58358 \tabularnewline
209 & 13 & 12.8142 & 0.185846 \tabularnewline
210 & 16 & 14.2236 & 1.77637 \tabularnewline
211 & 9 & 11.6102 & -2.6102 \tabularnewline
212 & 16 & 14.4718 & 1.52823 \tabularnewline
213 & 11 & 12.1939 & -1.19389 \tabularnewline
214 & 10 & 13.7747 & -3.77466 \tabularnewline
215 & 11 & 12.058 & -1.05801 \tabularnewline
216 & 15 & 13.2021 & 1.79793 \tabularnewline
217 & 17 & 14.8182 & 2.18185 \tabularnewline
218 & 14 & 14.1757 & -0.175713 \tabularnewline
219 & 8 & 9.88796 & -1.88796 \tabularnewline
220 & 15 & 13.532 & 1.46796 \tabularnewline
221 & 11 & 13.8113 & -2.81135 \tabularnewline
222 & 16 & 13.4729 & 2.5271 \tabularnewline
223 & 10 & 12.0634 & -2.06343 \tabularnewline
224 & 15 & 14.7457 & 0.254299 \tabularnewline
225 & 9 & 9.48717 & -0.487171 \tabularnewline
226 & 16 & 14.2514 & 1.74859 \tabularnewline
227 & 19 & 13.7244 & 5.27564 \tabularnewline
228 & 12 & 13.576 & -1.57599 \tabularnewline
229 & 8 & 9.45854 & -1.45854 \tabularnewline
230 & 11 & 13.2912 & -2.29121 \tabularnewline
231 & 14 & 13.7645 & 0.235484 \tabularnewline
232 & 9 & 11.992 & -2.99198 \tabularnewline
233 & 15 & 14.8544 & 0.145625 \tabularnewline
234 & 13 & 12.3747 & 0.625259 \tabularnewline
235 & 16 & 14.8304 & 1.16959 \tabularnewline
236 & 11 & 12.7758 & -1.77577 \tabularnewline
237 & 12 & 11.3108 & 0.689212 \tabularnewline
238 & 13 & 12.7595 & 0.240549 \tabularnewline
239 & 10 & 14.2948 & -4.29482 \tabularnewline
240 & 11 & 13.51 & -2.50996 \tabularnewline
241 & 12 & 14.7831 & -2.78314 \tabularnewline
242 & 8 & 10.6605 & -2.66046 \tabularnewline
243 & 12 & 11.7118 & 0.288218 \tabularnewline
244 & 12 & 12.223 & -0.22298 \tabularnewline
245 & 15 & 13.4959 & 1.50409 \tabularnewline
246 & 11 & 10.715 & 0.284968 \tabularnewline
247 & 13 & 12.7083 & 0.291709 \tabularnewline
248 & 14 & 8.8069 & 5.1931 \tabularnewline
249 & 10 & 10.206 & -0.206027 \tabularnewline
250 & 12 & 11.4986 & 0.501425 \tabularnewline
251 & 15 & 12.8363 & 2.16367 \tabularnewline
252 & 13 & 11.8433 & 1.15673 \tabularnewline
253 & 13 & 14.1055 & -1.10549 \tabularnewline
254 & 13 & 13.6847 & -0.684733 \tabularnewline
255 & 12 & 11.7871 & 0.212949 \tabularnewline
256 & 12 & 12.6362 & -0.636239 \tabularnewline
257 & 9 & 10.804 & -1.80395 \tabularnewline
258 & 9 & 11.4547 & -2.45467 \tabularnewline
259 & 15 & 12.538 & 2.46198 \tabularnewline
260 & 10 & 14.7797 & -4.77971 \tabularnewline
261 & 14 & 13.6328 & 0.367171 \tabularnewline
262 & 15 & 13.4754 & 1.52463 \tabularnewline
263 & 7 & 9.81113 & -2.81113 \tabularnewline
264 & 14 & 13.8176 & 0.1824 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230053&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]14[/C][C]13.9424[/C][C]0.0575709[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.3005[/C][C]2.69945[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.994[/C][C]-2.994[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.512[/C][C]-2.51202[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]11.2898[/C][C]4.71022[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.486[/C][C]3.51403[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.8454[/C][C]3.15458[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]15.0965[/C][C]-1.09645[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.2453[/C][C]-0.245279[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.409[/C][C]0.590968[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.5726[/C][C]1.42741[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.6384[/C][C]3.36157[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.4609[/C][C]-3.46086[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.5364[/C][C]2.46361[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.8078[/C][C]2.19218[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.447[/C][C]0.553031[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.9046[/C][C]0.0954157[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.845[/C][C]1.155[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.459[/C][C]-1.45896[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.8748[/C][C]2.12523[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.4014[/C][C]2.59862[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.795[/C][C]-2.79504[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.5015[/C][C]-0.501543[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.6322[/C][C]-1.63216[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.4376[/C][C]1.56241[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.98[/C][C]-6.97996[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.1105[/C][C]0.889512[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.3946[/C][C]0.605426[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]14.0068[/C][C]0.993164[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]14.0323[/C][C]-3.0323[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.7922[/C][C]0.207785[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.7431[/C][C]0.256927[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]15.1627[/C][C]1.83727[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.3805[/C][C]-0.380483[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14.0433[/C][C]-0.0433172[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.5975[/C][C]0.402549[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.924[/C][C]-1.92403[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.4155[/C][C]0.58454[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.4428[/C][C]1.55717[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.3159[/C][C]-2.31586[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.8024[/C][C]-0.802421[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.7612[/C][C]2.23876[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.9335[/C][C]0.0664801[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.2334[/C][C]-1.23337[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.7199[/C][C]0.280123[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.7079[/C][C]-2.70793[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.466[/C][C]-0.465954[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.0017[/C][C]-0.00169777[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.6241[/C][C]3.37592[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.8708[/C][C]-1.87076[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.3624[/C][C]0.637587[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.5664[/C][C]0.433607[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.8123[/C][C]-0.8123[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.8001[/C][C]-1.80014[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.1921[/C][C]-2.19215[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.7953[/C][C]1.20467[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.3401[/C][C]1.65995[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.5943[/C][C]-0.594329[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.3277[/C][C]-3.3277[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.5412[/C][C]-1.5412[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.8786[/C][C]-2.87865[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.7492[/C][C]-1.74923[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.799[/C][C]-3.79899[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.2211[/C][C]0.778878[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.7772[/C][C]1.22282[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.0003[/C][C]-5.0003[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.5375[/C][C]-1.53748[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.3974[/C][C]-2.39738[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.4384[/C][C]1.56156[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.552[/C][C]1.448[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.436[/C][C]0.564042[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.6384[/C][C]3.36158[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.3674[/C][C]0.632585[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.1815[/C][C]-0.181542[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.8861[/C][C]-1.88612[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.1047[/C][C]-0.104735[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]13.9349[/C][C]3.06511[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.4357[/C][C]0.564314[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.7445[/C][C]1.25545[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]14.8789[/C][C]-1.87887[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.8471[/C][C]0.152919[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.447[/C][C]-0.446972[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.228[/C][C]1.77199[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2379[/C][C]0.762063[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.0823[/C][C]-0.0822727[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.9691[/C][C]1.03089[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.2356[/C][C]-0.235598[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.7247[/C][C]0.27525[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.5269[/C][C]-3.52689[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.702[/C][C]3.29803[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.7856[/C][C]0.214381[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.1541[/C][C]0.845924[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.2806[/C][C]0.719383[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.9681[/C][C]-0.968109[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.9422[/C][C]1.05783[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.804[/C][C]-0.804026[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.8391[/C][C]-0.839121[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.9019[/C][C]2.09808[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]15.0116[/C][C]-0.0115866[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.1265[/C][C]1.87355[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.9395[/C][C]-0.939455[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]15.0056[/C][C]0.994353[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.4018[/C][C]-3.4018[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.0995[/C][C]1.90053[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.3859[/C][C]-2.38593[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.913[/C][C]1.08704[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9204[/C][C]2.07963[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.8082[/C][C]-2.80817[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.17976[/C][C]0.820236[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.9083[/C][C]1.09172[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.1974[/C][C]-2.19741[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.2961[/C][C]-2.29609[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]11.9023[/C][C]2.09771[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.1103[/C][C]3.88973[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.5634[/C][C]0.436598[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]12.9938[/C][C]1.0062[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.8378[/C][C]0.162179[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.0801[/C][C]-1.08011[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.7272[/C][C]0.272756[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.542[/C][C]-0.541956[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.5724[/C][C]0.427631[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.9078[/C][C]0.092193[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.9026[/C][C]-0.902649[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.5734[/C][C]0.426607[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.7585[/C][C]-1.75853[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.176[/C][C]0.82404[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.2906[/C][C]1.70945[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.9503[/C][C]4.04972[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5967[/C][C]1.40334[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.6562[/C][C]-1.65624[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.6686[/C][C]-1.66862[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.2971[/C][C]-0.29706[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.6274[/C][C]2.37258[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.2552[/C][C]0.744766[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.7792[/C][C]2.22081[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.47587[/C][C]1.52413[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.3524[/C][C]0.647625[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]12.0068[/C][C]-1.00682[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.2042[/C][C]0.795825[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.8213[/C][C]-0.821332[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.6578[/C][C]0.342153[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.8797[/C][C]2.12034[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.7113[/C][C]-0.711342[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.3085[/C][C]0.691493[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.6376[/C][C]1.36238[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.5034[/C][C]1.49656[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.4221[/C][C]-2.42211[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.7177[/C][C]-2.71774[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.582[/C][C]-2.58196[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.2851[/C][C]1.71491[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.6158[/C][C]0.384222[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.4557[/C][C]0.544281[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.5013[/C][C]-2.50134[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.937[/C][C]-2.93704[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.824[/C][C]1.17603[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.7856[/C][C]0.214381[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.3963[/C][C]0.603654[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.9503[/C][C]4.04972[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.707[/C][C]-2.70703[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.1726[/C][C]-0.172618[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6697[/C][C]0.330294[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.16419[/C][C]0.835808[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.0699[/C][C]0.930132[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.4037[/C][C]4.59628[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.8119[/C][C]-1.81186[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]8.97942[/C][C]2.02058[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]13.9664[/C][C]0.0335952[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.7058[/C][C]-0.705799[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.5704[/C][C]-3.57042[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.8001[/C][C]-2.8001[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.4102[/C][C]0.589829[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.045[/C][C]1.95501[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]13.854[/C][C]-4.85402[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.161[/C][C]1.83904[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.2044[/C][C]2.7956[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.1225[/C][C]-2.12251[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.1757[/C][C]-3.17573[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.3523[/C][C]0.647678[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.4088[/C][C]1.59119[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.0188[/C][C]-2.01879[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]13.9371[/C][C]0.0628745[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.5783[/C][C]-1.57832[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.5618[/C][C]0.438248[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.8195[/C][C]-0.81946[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]13.948[/C][C]2.05198[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.5385[/C][C]1.46153[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.4133[/C][C]0.586697[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.0809[/C][C]0.919129[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.3121[/C][C]0.687893[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.166[/C][C]0.834021[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.4204[/C][C]-1.42044[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.8652[/C][C]-0.865219[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.6207[/C][C]2.37929[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.3972[/C][C]-1.39716[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.0047[/C][C]1.99534[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]13.9351[/C][C]-1.93511[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.6555[/C][C]2.34448[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.3229[/C][C]0.67713[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.0469[/C][C]-3.0469[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.665[/C][C]-0.664972[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.0708[/C][C]-3.07077[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.6603[/C][C]1.33975[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]13.9463[/C][C]3.05366[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.45[/C][C]0.549961[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.3334[/C][C]0.66663[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.6367[/C][C]1.36331[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.4378[/C][C]-0.437779[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.4164[/C][C]3.58358[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.8142[/C][C]0.185846[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.2236[/C][C]1.77637[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.6102[/C][C]-2.6102[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.4718[/C][C]1.52823[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.1939[/C][C]-1.19389[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.7747[/C][C]-3.77466[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.058[/C][C]-1.05801[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.2021[/C][C]1.79793[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.8182[/C][C]2.18185[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.1757[/C][C]-0.175713[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.88796[/C][C]-1.88796[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.532[/C][C]1.46796[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.8113[/C][C]-2.81135[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.4729[/C][C]2.5271[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.0634[/C][C]-2.06343[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.7457[/C][C]0.254299[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.48717[/C][C]-0.487171[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.2514[/C][C]1.74859[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]13.7244[/C][C]5.27564[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.576[/C][C]-1.57599[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.45854[/C][C]-1.45854[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.2912[/C][C]-2.29121[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.7645[/C][C]0.235484[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]11.992[/C][C]-2.99198[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]14.8544[/C][C]0.145625[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.3747[/C][C]0.625259[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]14.8304[/C][C]1.16959[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.7758[/C][C]-1.77577[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.3108[/C][C]0.689212[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]12.7595[/C][C]0.240549[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.2948[/C][C]-4.29482[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.51[/C][C]-2.50996[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.7831[/C][C]-2.78314[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.6605[/C][C]-2.66046[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.7118[/C][C]0.288218[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.223[/C][C]-0.22298[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.4959[/C][C]1.50409[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.715[/C][C]0.284968[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.7083[/C][C]0.291709[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.8069[/C][C]5.1931[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.206[/C][C]-0.206027[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.4986[/C][C]0.501425[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.8363[/C][C]2.16367[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.8433[/C][C]1.15673[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.1055[/C][C]-1.10549[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.6847[/C][C]-0.684733[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.7871[/C][C]0.212949[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.6362[/C][C]-0.636239[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.804[/C][C]-1.80395[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.4547[/C][C]-2.45467[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.538[/C][C]2.46198[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.7797[/C][C]-4.77971[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.6328[/C][C]0.367171[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.4754[/C][C]1.52463[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.81113[/C][C]-2.81113[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.8176[/C][C]0.1824[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230053&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230053&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.94240.0575709
21815.30052.69945
31113.994-2.994
41214.512-2.51202
51611.28984.71022
61814.4863.51403
71410.84543.15458
81415.0965-1.09645
91515.2453-0.245279
101514.4090.590968
111715.57261.42741
121915.63843.36157
131013.4609-3.46086
141613.53642.46361
151815.80782.19218
161413.4470.553031
171413.90460.0954157
181715.8451.155
191415.459-1.45896
201613.87482.12523
211815.40142.59862
221113.795-2.79504
231414.5015-0.501543
241213.6322-1.63216
251715.43761.56241
26915.98-6.97996
271615.11050.889512
281413.39460.605426
291514.00680.993164
301114.0323-3.0323
311615.79220.207785
321312.74310.256927
331715.16271.83727
341515.3805-0.380483
351414.0433-0.0433172
361615.59750.402549
37910.924-1.92403
381514.41550.58454
391715.44281.55717
401315.3159-2.31586
411515.8024-0.802421
421613.76122.23876
431615.93350.0664801
441213.2334-1.23337
451514.71990.280123
461113.7079-2.70793
471515.466-0.465954
481515.0017-0.00169777
491713.62413.37592
501314.8708-1.87076
511615.36240.637587
521413.56640.433607
531111.8123-0.8123
541213.8001-1.80014
551214.1921-2.19215
561513.79531.20467
571614.34011.65995
581515.5943-0.594329
591215.3277-3.3277
601213.5412-1.5412
61810.8786-2.87865
621314.7492-1.74923
631114.799-3.79899
641413.22110.778878
651513.77721.22282
661015.0003-5.0003
671112.5375-1.53748
681214.3974-2.39738
691513.43841.56156
701513.5521.448
711413.4360.564042
721612.63843.36158
731514.36740.632585
741515.1815-0.181542
751314.8861-1.88612
761212.1047-0.104735
771713.93493.06511
781312.43570.564314
791513.74451.25545
801314.8789-1.87887
811514.84710.152919
821515.447-0.446972
831614.2281.77199
841514.23790.762063
851414.0823-0.0822727
861513.96911.03089
871414.2356-0.235598
881312.72470.27525
89710.5269-3.52689
901713.7023.29803
911312.78560.214381
921514.15410.845924
931413.28060.719383
941313.9681-0.968109
951614.94221.05783
961212.804-0.804026
971414.8391-0.839121
981714.90192.09808
991515.0116-0.0115866
1001715.12651.87355
1011212.9395-0.939455
1021615.00560.994353
1031114.4018-3.4018
1041513.09951.90053
105911.3859-2.38593
1061614.9131.08704
1071512.92042.07963
1081012.8082-2.80817
109109.179760.820236
1101513.90831.09172
1111113.1974-2.19741
1121315.2961-2.29609
1131411.90232.09771
1141814.11033.88973
1151615.56340.436598
1161412.99381.0062
1171413.83780.162179
1181415.0801-1.08011
1191413.72720.272756
1201212.542-0.541956
1211413.57240.427631
1221514.90780.092193
1231515.9026-0.902649
1241514.57340.426607
1251314.7585-1.75853
1261716.1760.82404
1271715.29061.70945
1281914.95034.04972
1291513.59671.40334
1301314.6562-1.65624
131910.6686-1.66862
1321515.2971-0.29706
1331512.62742.37258
1341514.25520.744766
1351613.77922.22081
136119.475871.52413
1371413.35240.647625
1381112.0068-1.00682
1391514.20420.795825
1401313.8213-0.821332
1411514.65780.342153
1421613.87972.12034
1431414.7113-0.711342
1441514.30850.691493
1451614.63761.36238
1461614.50341.49656
1471113.4221-2.42211
1481214.7177-2.71774
149911.582-2.58196
1501614.28511.71491
1511312.61580.384222
1521615.45570.544281
1531214.5013-2.50134
154911.937-2.93704
1551311.8241.17603
1561312.78560.214381
1571413.39630.603654
1581914.95034.04972
1591315.707-2.70703
1601212.1726-0.172618
1611312.66970.330294
162109.164190.835808
1631413.06990.930132
1641611.40374.59628
1651011.8119-1.81186
166118.979422.02058
1671413.96640.0335952
1681212.7058-0.705799
169912.5704-3.57042
170911.8001-2.8001
1711110.41020.589829
1721614.0451.95501
173913.854-4.85402
1741311.1611.83904
1751613.20442.7956
1761315.1225-2.12251
177912.1757-3.17573
1781211.35230.647678
1791614.40881.59119
1801113.0188-2.01879
1811413.93710.0628745
1821314.5783-1.57832
1831514.56180.438248
1841414.8195-0.81946
1851613.9482.05198
1861311.53851.46153
1871413.41330.586697
1881514.08090.919129
1891312.31210.687893
1901110.1660.834021
1911112.4204-1.42044
1921414.8652-0.865219
1931512.62072.37929
1941112.3972-1.39716
1951513.00471.99534
1961213.9351-1.93511
1971411.65552.34448
1981413.32290.67713
199811.0469-3.0469
2001313.665-0.664972
201912.0708-3.07077
2021513.66031.33975
2031713.94633.05366
2041312.450.549961
2051514.33340.66663
2061513.63671.36331
2071414.4378-0.437779
2081612.41643.58358
2091312.81420.185846
2101614.22361.77637
211911.6102-2.6102
2121614.47181.52823
2131112.1939-1.19389
2141013.7747-3.77466
2151112.058-1.05801
2161513.20211.79793
2171714.81822.18185
2181414.1757-0.175713
21989.88796-1.88796
2201513.5321.46796
2211113.8113-2.81135
2221613.47292.5271
2231012.0634-2.06343
2241514.74570.254299
22599.48717-0.487171
2261614.25141.74859
2271913.72445.27564
2281213.576-1.57599
22989.45854-1.45854
2301113.2912-2.29121
2311413.76450.235484
232911.992-2.99198
2331514.85440.145625
2341312.37470.625259
2351614.83041.16959
2361112.7758-1.77577
2371211.31080.689212
2381312.75950.240549
2391014.2948-4.29482
2401113.51-2.50996
2411214.7831-2.78314
242810.6605-2.66046
2431211.71180.288218
2441212.223-0.22298
2451513.49591.50409
2461110.7150.284968
2471312.70830.291709
248148.80695.1931
2491010.206-0.206027
2501211.49860.501425
2511512.83632.16367
2521311.84331.15673
2531314.1055-1.10549
2541313.6847-0.684733
2551211.78710.212949
2561212.6362-0.636239
257910.804-1.80395
258911.4547-2.45467
2591512.5382.46198
2601014.7797-4.77971
2611413.63280.367171
2621513.47541.52463
26379.81113-2.81113
2641413.81760.1824







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.8246030.3507950.175397
130.9817790.03644260.0182213
140.9650410.0699170.0349585
150.9654160.06916860.0345843
160.9429830.1140340.0570171
170.9668570.06628540.0331427
180.9467110.1065780.0532888
190.9191380.1617230.0808616
200.9153090.1693830.0846913
210.9374250.1251510.0625755
220.9350620.1298770.0649384
230.9350480.1299040.0649519
240.9112740.1774510.0887255
250.8909140.2181720.109086
260.9993050.001389070.000694537
270.9988680.002264940.00113247
280.9981580.003683980.00184199
290.997110.005780210.00289011
300.9980490.00390120.0019506
310.9969850.006030890.00301545
320.9955760.008848460.00442423
330.9945480.01090340.00545172
340.9920050.01598930.00799464
350.9900160.01996770.00998386
360.9859340.02813190.0140659
370.9905730.01885330.00942663
380.9867890.02642220.0132111
390.9846130.03077360.0153868
400.984960.03008020.0150401
410.9801320.0397360.019868
420.977720.04455940.0222797
430.9703720.05925670.0296284
440.9650380.06992370.0349618
450.954540.09091930.0454597
460.9629170.07416630.0370832
470.9523810.09523790.0476189
480.9392690.1214630.0607313
490.9478160.1043690.0521843
500.9446170.1107660.055383
510.9317380.1365250.0682624
520.9155390.1689220.0844609
530.9028650.1942690.0971346
540.8879380.2241250.112062
550.8828110.2343770.117189
560.8644380.2711240.135562
570.8505110.2989780.149489
580.8237210.3525580.176279
590.8652140.2695720.134786
600.8622150.2755690.137785
610.8828830.2342350.117117
620.8837590.2324830.116241
630.9316620.1366760.0683378
640.920160.1596810.0798404
650.9097640.1804720.0902362
660.9208390.1583220.0791609
670.9200250.159950.0799752
680.9112330.1775330.0887666
690.9419330.1161330.0580665
700.9463850.107230.053615
710.941090.1178190.0589097
720.9610690.07786280.0389314
730.9525880.09482340.0474117
740.9419990.1160020.0580011
750.9351440.1297130.0648565
760.9215830.1568350.0784173
770.9376190.1247620.0623809
780.9260440.1479110.0739557
790.9196730.1606540.0803271
800.9129940.1740120.087006
810.8964430.2071150.103557
820.8784860.2430280.121514
830.872940.254120.12706
840.8546150.2907690.145385
850.8315740.3368510.168426
860.8089790.3820410.191021
870.7821550.435690.217845
880.7531750.493650.246825
890.821660.356680.17834
900.8525550.2948890.147445
910.8304490.3391030.169551
920.8076860.3846290.192314
930.7855130.4289750.214487
940.7629790.4740430.237021
950.7373130.5253740.262687
960.7127450.574510.287255
970.6866170.6267670.313383
980.6844390.6311210.315561
990.6509310.6981390.349069
1000.640280.719440.35972
1010.6166550.766690.383345
1020.5869790.8260420.413021
1030.6377640.7244710.362236
1040.6232520.7534970.376748
1050.6406180.7187630.359382
1060.6139060.7721880.386094
1070.6038050.792390.396195
1080.6444250.711150.355575
1090.6135760.7728470.386424
1100.5865530.8268940.413447
1110.5941820.8116360.405818
1120.6216040.7567920.378396
1130.6094310.7811390.390569
1140.6962030.6075950.303797
1150.6663780.6672450.333622
1160.6396920.7206170.360308
1170.6057960.7884070.394204
1180.5818410.8363180.418159
1190.5467660.9064670.453234
1200.5147750.970450.485225
1210.4855580.9711150.514442
1220.4526750.905350.547325
1230.4255570.8511150.574443
1240.3936190.7872390.606381
1250.3853070.7706140.614693
1260.3556510.7113030.644349
1270.3394170.6788350.660583
1280.441320.8826410.55868
1290.421960.843920.57804
1300.4123350.824670.587665
1310.4002160.8004320.599784
1320.3710180.7420350.628982
1330.388190.776380.61181
1340.3587910.7175820.641209
1350.3679910.7359820.632009
1360.356430.7128610.64357
1370.3266030.6532060.673397
1380.3029970.6059940.697003
1390.2763370.5526740.723663
1400.2530760.5061520.746924
1410.2257350.4514690.774265
1420.2295530.4591070.770447
1430.2050450.410090.794955
1440.1845740.3691480.815426
1450.1724350.344870.827565
1460.1651670.3303340.834833
1470.1727370.3454730.827263
1480.1901570.3803140.809843
1490.2096530.4193050.790347
1500.2062890.4125780.793711
1510.18460.3691990.8154
1520.1650020.3300030.834998
1530.1784310.3568620.821569
1540.214110.428220.78589
1550.1927420.3854830.807258
1560.1726680.3453360.827332
1570.1505630.3011270.849437
1580.2204380.4408750.779562
1590.2462640.4925290.753736
1600.2206640.4413280.779336
1610.1942110.3884210.805789
1620.1717110.3434220.828289
1630.1517180.3034360.848282
1640.2549860.5099720.745014
1650.2517760.5035510.748224
1660.247590.4951810.75241
1670.2197230.4394460.780277
1680.1979810.3959620.802019
1690.2518550.503710.748145
1700.2741970.5483930.725803
1710.2470320.4940640.752968
1720.2434020.4868050.756598
1730.397040.7940790.60296
1740.3854990.7709980.614501
1750.4108130.8216250.589187
1760.416560.833120.58344
1770.4676120.9352240.532388
1780.4345040.8690080.565496
1790.4147880.8295760.585212
1800.4106070.8212140.589393
1810.3735850.747170.626415
1820.3628930.7257850.637107
1830.3273770.6547540.672623
1840.2994870.5989740.700513
1850.3151790.6303590.684821
1860.3091120.6182230.690888
1870.2768250.5536510.723175
1880.2515650.5031310.748435
1890.2228530.4457070.777147
1900.2016450.403290.798355
1910.204160.4083210.79584
1920.1857670.3715350.814233
1930.2038210.4076410.796179
1940.1901280.3802550.809872
1950.190950.3819010.80905
1960.1984250.396850.801575
1970.2436980.4873970.756302
1980.2264930.4529870.773507
1990.2545530.5091050.745447
2000.2228830.4457660.777117
2010.2531560.5063110.746844
2020.2341570.4683140.765843
2030.2944760.5889530.705524
2040.2610280.5220560.738972
2050.2293370.4586750.770663
2060.2103620.4207240.789638
2070.1804220.3608440.819578
2080.2018750.4037490.798125
2090.1720510.3441010.827949
2100.1878750.375750.812125
2110.2113670.4227340.788633
2120.1973060.3946120.802694
2130.1713030.3426060.828697
2140.2135030.4270060.786497
2150.1872640.3745280.812736
2160.1762940.3525890.823706
2170.2072520.4145040.792748
2180.1785210.3570420.821479
2190.1647660.3295310.835234
2200.1717880.3435760.828212
2210.1767010.3534030.823299
2220.179020.3580390.82098
2230.1630870.3261740.836913
2240.1345190.2690390.865481
2250.1205510.2411030.879449
2260.1453520.2907040.854648
2270.3235970.6471940.676403
2280.299790.599580.70021
2290.2732570.5465150.726743
2300.2570740.5141480.742926
2310.2174470.4348950.782553
2320.2507670.5015350.749233
2330.2094740.4189480.790526
2340.1723610.3447220.827639
2350.1711930.3423870.828807
2360.1487350.2974690.851265
2370.1220280.2440570.877972
2380.09261160.1852230.907388
2390.1870830.3741650.812917
2400.1808890.3617790.819111
2410.1521370.3042740.847863
2420.3229730.6459460.677027
2430.2805910.5611830.719409
2440.2256340.4512670.774366
2450.3382820.6765640.661718
2460.2589170.5178340.741083
2470.1904930.3809850.809507
2480.3093070.6186140.690693
2490.2234960.4469910.776504
2500.1481990.2963980.851801
2510.235890.4717790.76411
2520.7436690.5126630.256331

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.824603 & 0.350795 & 0.175397 \tabularnewline
13 & 0.981779 & 0.0364426 & 0.0182213 \tabularnewline
14 & 0.965041 & 0.069917 & 0.0349585 \tabularnewline
15 & 0.965416 & 0.0691686 & 0.0345843 \tabularnewline
16 & 0.942983 & 0.114034 & 0.0570171 \tabularnewline
17 & 0.966857 & 0.0662854 & 0.0331427 \tabularnewline
18 & 0.946711 & 0.106578 & 0.0532888 \tabularnewline
19 & 0.919138 & 0.161723 & 0.0808616 \tabularnewline
20 & 0.915309 & 0.169383 & 0.0846913 \tabularnewline
21 & 0.937425 & 0.125151 & 0.0625755 \tabularnewline
22 & 0.935062 & 0.129877 & 0.0649384 \tabularnewline
23 & 0.935048 & 0.129904 & 0.0649519 \tabularnewline
24 & 0.911274 & 0.177451 & 0.0887255 \tabularnewline
25 & 0.890914 & 0.218172 & 0.109086 \tabularnewline
26 & 0.999305 & 0.00138907 & 0.000694537 \tabularnewline
27 & 0.998868 & 0.00226494 & 0.00113247 \tabularnewline
28 & 0.998158 & 0.00368398 & 0.00184199 \tabularnewline
29 & 0.99711 & 0.00578021 & 0.00289011 \tabularnewline
30 & 0.998049 & 0.0039012 & 0.0019506 \tabularnewline
31 & 0.996985 & 0.00603089 & 0.00301545 \tabularnewline
32 & 0.995576 & 0.00884846 & 0.00442423 \tabularnewline
33 & 0.994548 & 0.0109034 & 0.00545172 \tabularnewline
34 & 0.992005 & 0.0159893 & 0.00799464 \tabularnewline
35 & 0.990016 & 0.0199677 & 0.00998386 \tabularnewline
36 & 0.985934 & 0.0281319 & 0.0140659 \tabularnewline
37 & 0.990573 & 0.0188533 & 0.00942663 \tabularnewline
38 & 0.986789 & 0.0264222 & 0.0132111 \tabularnewline
39 & 0.984613 & 0.0307736 & 0.0153868 \tabularnewline
40 & 0.98496 & 0.0300802 & 0.0150401 \tabularnewline
41 & 0.980132 & 0.039736 & 0.019868 \tabularnewline
42 & 0.97772 & 0.0445594 & 0.0222797 \tabularnewline
43 & 0.970372 & 0.0592567 & 0.0296284 \tabularnewline
44 & 0.965038 & 0.0699237 & 0.0349618 \tabularnewline
45 & 0.95454 & 0.0909193 & 0.0454597 \tabularnewline
46 & 0.962917 & 0.0741663 & 0.0370832 \tabularnewline
47 & 0.952381 & 0.0952379 & 0.0476189 \tabularnewline
48 & 0.939269 & 0.121463 & 0.0607313 \tabularnewline
49 & 0.947816 & 0.104369 & 0.0521843 \tabularnewline
50 & 0.944617 & 0.110766 & 0.055383 \tabularnewline
51 & 0.931738 & 0.136525 & 0.0682624 \tabularnewline
52 & 0.915539 & 0.168922 & 0.0844609 \tabularnewline
53 & 0.902865 & 0.194269 & 0.0971346 \tabularnewline
54 & 0.887938 & 0.224125 & 0.112062 \tabularnewline
55 & 0.882811 & 0.234377 & 0.117189 \tabularnewline
56 & 0.864438 & 0.271124 & 0.135562 \tabularnewline
57 & 0.850511 & 0.298978 & 0.149489 \tabularnewline
58 & 0.823721 & 0.352558 & 0.176279 \tabularnewline
59 & 0.865214 & 0.269572 & 0.134786 \tabularnewline
60 & 0.862215 & 0.275569 & 0.137785 \tabularnewline
61 & 0.882883 & 0.234235 & 0.117117 \tabularnewline
62 & 0.883759 & 0.232483 & 0.116241 \tabularnewline
63 & 0.931662 & 0.136676 & 0.0683378 \tabularnewline
64 & 0.92016 & 0.159681 & 0.0798404 \tabularnewline
65 & 0.909764 & 0.180472 & 0.0902362 \tabularnewline
66 & 0.920839 & 0.158322 & 0.0791609 \tabularnewline
67 & 0.920025 & 0.15995 & 0.0799752 \tabularnewline
68 & 0.911233 & 0.177533 & 0.0887666 \tabularnewline
69 & 0.941933 & 0.116133 & 0.0580665 \tabularnewline
70 & 0.946385 & 0.10723 & 0.053615 \tabularnewline
71 & 0.94109 & 0.117819 & 0.0589097 \tabularnewline
72 & 0.961069 & 0.0778628 & 0.0389314 \tabularnewline
73 & 0.952588 & 0.0948234 & 0.0474117 \tabularnewline
74 & 0.941999 & 0.116002 & 0.0580011 \tabularnewline
75 & 0.935144 & 0.129713 & 0.0648565 \tabularnewline
76 & 0.921583 & 0.156835 & 0.0784173 \tabularnewline
77 & 0.937619 & 0.124762 & 0.0623809 \tabularnewline
78 & 0.926044 & 0.147911 & 0.0739557 \tabularnewline
79 & 0.919673 & 0.160654 & 0.0803271 \tabularnewline
80 & 0.912994 & 0.174012 & 0.087006 \tabularnewline
81 & 0.896443 & 0.207115 & 0.103557 \tabularnewline
82 & 0.878486 & 0.243028 & 0.121514 \tabularnewline
83 & 0.87294 & 0.25412 & 0.12706 \tabularnewline
84 & 0.854615 & 0.290769 & 0.145385 \tabularnewline
85 & 0.831574 & 0.336851 & 0.168426 \tabularnewline
86 & 0.808979 & 0.382041 & 0.191021 \tabularnewline
87 & 0.782155 & 0.43569 & 0.217845 \tabularnewline
88 & 0.753175 & 0.49365 & 0.246825 \tabularnewline
89 & 0.82166 & 0.35668 & 0.17834 \tabularnewline
90 & 0.852555 & 0.294889 & 0.147445 \tabularnewline
91 & 0.830449 & 0.339103 & 0.169551 \tabularnewline
92 & 0.807686 & 0.384629 & 0.192314 \tabularnewline
93 & 0.785513 & 0.428975 & 0.214487 \tabularnewline
94 & 0.762979 & 0.474043 & 0.237021 \tabularnewline
95 & 0.737313 & 0.525374 & 0.262687 \tabularnewline
96 & 0.712745 & 0.57451 & 0.287255 \tabularnewline
97 & 0.686617 & 0.626767 & 0.313383 \tabularnewline
98 & 0.684439 & 0.631121 & 0.315561 \tabularnewline
99 & 0.650931 & 0.698139 & 0.349069 \tabularnewline
100 & 0.64028 & 0.71944 & 0.35972 \tabularnewline
101 & 0.616655 & 0.76669 & 0.383345 \tabularnewline
102 & 0.586979 & 0.826042 & 0.413021 \tabularnewline
103 & 0.637764 & 0.724471 & 0.362236 \tabularnewline
104 & 0.623252 & 0.753497 & 0.376748 \tabularnewline
105 & 0.640618 & 0.718763 & 0.359382 \tabularnewline
106 & 0.613906 & 0.772188 & 0.386094 \tabularnewline
107 & 0.603805 & 0.79239 & 0.396195 \tabularnewline
108 & 0.644425 & 0.71115 & 0.355575 \tabularnewline
109 & 0.613576 & 0.772847 & 0.386424 \tabularnewline
110 & 0.586553 & 0.826894 & 0.413447 \tabularnewline
111 & 0.594182 & 0.811636 & 0.405818 \tabularnewline
112 & 0.621604 & 0.756792 & 0.378396 \tabularnewline
113 & 0.609431 & 0.781139 & 0.390569 \tabularnewline
114 & 0.696203 & 0.607595 & 0.303797 \tabularnewline
115 & 0.666378 & 0.667245 & 0.333622 \tabularnewline
116 & 0.639692 & 0.720617 & 0.360308 \tabularnewline
117 & 0.605796 & 0.788407 & 0.394204 \tabularnewline
118 & 0.581841 & 0.836318 & 0.418159 \tabularnewline
119 & 0.546766 & 0.906467 & 0.453234 \tabularnewline
120 & 0.514775 & 0.97045 & 0.485225 \tabularnewline
121 & 0.485558 & 0.971115 & 0.514442 \tabularnewline
122 & 0.452675 & 0.90535 & 0.547325 \tabularnewline
123 & 0.425557 & 0.851115 & 0.574443 \tabularnewline
124 & 0.393619 & 0.787239 & 0.606381 \tabularnewline
125 & 0.385307 & 0.770614 & 0.614693 \tabularnewline
126 & 0.355651 & 0.711303 & 0.644349 \tabularnewline
127 & 0.339417 & 0.678835 & 0.660583 \tabularnewline
128 & 0.44132 & 0.882641 & 0.55868 \tabularnewline
129 & 0.42196 & 0.84392 & 0.57804 \tabularnewline
130 & 0.412335 & 0.82467 & 0.587665 \tabularnewline
131 & 0.400216 & 0.800432 & 0.599784 \tabularnewline
132 & 0.371018 & 0.742035 & 0.628982 \tabularnewline
133 & 0.38819 & 0.77638 & 0.61181 \tabularnewline
134 & 0.358791 & 0.717582 & 0.641209 \tabularnewline
135 & 0.367991 & 0.735982 & 0.632009 \tabularnewline
136 & 0.35643 & 0.712861 & 0.64357 \tabularnewline
137 & 0.326603 & 0.653206 & 0.673397 \tabularnewline
138 & 0.302997 & 0.605994 & 0.697003 \tabularnewline
139 & 0.276337 & 0.552674 & 0.723663 \tabularnewline
140 & 0.253076 & 0.506152 & 0.746924 \tabularnewline
141 & 0.225735 & 0.451469 & 0.774265 \tabularnewline
142 & 0.229553 & 0.459107 & 0.770447 \tabularnewline
143 & 0.205045 & 0.41009 & 0.794955 \tabularnewline
144 & 0.184574 & 0.369148 & 0.815426 \tabularnewline
145 & 0.172435 & 0.34487 & 0.827565 \tabularnewline
146 & 0.165167 & 0.330334 & 0.834833 \tabularnewline
147 & 0.172737 & 0.345473 & 0.827263 \tabularnewline
148 & 0.190157 & 0.380314 & 0.809843 \tabularnewline
149 & 0.209653 & 0.419305 & 0.790347 \tabularnewline
150 & 0.206289 & 0.412578 & 0.793711 \tabularnewline
151 & 0.1846 & 0.369199 & 0.8154 \tabularnewline
152 & 0.165002 & 0.330003 & 0.834998 \tabularnewline
153 & 0.178431 & 0.356862 & 0.821569 \tabularnewline
154 & 0.21411 & 0.42822 & 0.78589 \tabularnewline
155 & 0.192742 & 0.385483 & 0.807258 \tabularnewline
156 & 0.172668 & 0.345336 & 0.827332 \tabularnewline
157 & 0.150563 & 0.301127 & 0.849437 \tabularnewline
158 & 0.220438 & 0.440875 & 0.779562 \tabularnewline
159 & 0.246264 & 0.492529 & 0.753736 \tabularnewline
160 & 0.220664 & 0.441328 & 0.779336 \tabularnewline
161 & 0.194211 & 0.388421 & 0.805789 \tabularnewline
162 & 0.171711 & 0.343422 & 0.828289 \tabularnewline
163 & 0.151718 & 0.303436 & 0.848282 \tabularnewline
164 & 0.254986 & 0.509972 & 0.745014 \tabularnewline
165 & 0.251776 & 0.503551 & 0.748224 \tabularnewline
166 & 0.24759 & 0.495181 & 0.75241 \tabularnewline
167 & 0.219723 & 0.439446 & 0.780277 \tabularnewline
168 & 0.197981 & 0.395962 & 0.802019 \tabularnewline
169 & 0.251855 & 0.50371 & 0.748145 \tabularnewline
170 & 0.274197 & 0.548393 & 0.725803 \tabularnewline
171 & 0.247032 & 0.494064 & 0.752968 \tabularnewline
172 & 0.243402 & 0.486805 & 0.756598 \tabularnewline
173 & 0.39704 & 0.794079 & 0.60296 \tabularnewline
174 & 0.385499 & 0.770998 & 0.614501 \tabularnewline
175 & 0.410813 & 0.821625 & 0.589187 \tabularnewline
176 & 0.41656 & 0.83312 & 0.58344 \tabularnewline
177 & 0.467612 & 0.935224 & 0.532388 \tabularnewline
178 & 0.434504 & 0.869008 & 0.565496 \tabularnewline
179 & 0.414788 & 0.829576 & 0.585212 \tabularnewline
180 & 0.410607 & 0.821214 & 0.589393 \tabularnewline
181 & 0.373585 & 0.74717 & 0.626415 \tabularnewline
182 & 0.362893 & 0.725785 & 0.637107 \tabularnewline
183 & 0.327377 & 0.654754 & 0.672623 \tabularnewline
184 & 0.299487 & 0.598974 & 0.700513 \tabularnewline
185 & 0.315179 & 0.630359 & 0.684821 \tabularnewline
186 & 0.309112 & 0.618223 & 0.690888 \tabularnewline
187 & 0.276825 & 0.553651 & 0.723175 \tabularnewline
188 & 0.251565 & 0.503131 & 0.748435 \tabularnewline
189 & 0.222853 & 0.445707 & 0.777147 \tabularnewline
190 & 0.201645 & 0.40329 & 0.798355 \tabularnewline
191 & 0.20416 & 0.408321 & 0.79584 \tabularnewline
192 & 0.185767 & 0.371535 & 0.814233 \tabularnewline
193 & 0.203821 & 0.407641 & 0.796179 \tabularnewline
194 & 0.190128 & 0.380255 & 0.809872 \tabularnewline
195 & 0.19095 & 0.381901 & 0.80905 \tabularnewline
196 & 0.198425 & 0.39685 & 0.801575 \tabularnewline
197 & 0.243698 & 0.487397 & 0.756302 \tabularnewline
198 & 0.226493 & 0.452987 & 0.773507 \tabularnewline
199 & 0.254553 & 0.509105 & 0.745447 \tabularnewline
200 & 0.222883 & 0.445766 & 0.777117 \tabularnewline
201 & 0.253156 & 0.506311 & 0.746844 \tabularnewline
202 & 0.234157 & 0.468314 & 0.765843 \tabularnewline
203 & 0.294476 & 0.588953 & 0.705524 \tabularnewline
204 & 0.261028 & 0.522056 & 0.738972 \tabularnewline
205 & 0.229337 & 0.458675 & 0.770663 \tabularnewline
206 & 0.210362 & 0.420724 & 0.789638 \tabularnewline
207 & 0.180422 & 0.360844 & 0.819578 \tabularnewline
208 & 0.201875 & 0.403749 & 0.798125 \tabularnewline
209 & 0.172051 & 0.344101 & 0.827949 \tabularnewline
210 & 0.187875 & 0.37575 & 0.812125 \tabularnewline
211 & 0.211367 & 0.422734 & 0.788633 \tabularnewline
212 & 0.197306 & 0.394612 & 0.802694 \tabularnewline
213 & 0.171303 & 0.342606 & 0.828697 \tabularnewline
214 & 0.213503 & 0.427006 & 0.786497 \tabularnewline
215 & 0.187264 & 0.374528 & 0.812736 \tabularnewline
216 & 0.176294 & 0.352589 & 0.823706 \tabularnewline
217 & 0.207252 & 0.414504 & 0.792748 \tabularnewline
218 & 0.178521 & 0.357042 & 0.821479 \tabularnewline
219 & 0.164766 & 0.329531 & 0.835234 \tabularnewline
220 & 0.171788 & 0.343576 & 0.828212 \tabularnewline
221 & 0.176701 & 0.353403 & 0.823299 \tabularnewline
222 & 0.17902 & 0.358039 & 0.82098 \tabularnewline
223 & 0.163087 & 0.326174 & 0.836913 \tabularnewline
224 & 0.134519 & 0.269039 & 0.865481 \tabularnewline
225 & 0.120551 & 0.241103 & 0.879449 \tabularnewline
226 & 0.145352 & 0.290704 & 0.854648 \tabularnewline
227 & 0.323597 & 0.647194 & 0.676403 \tabularnewline
228 & 0.29979 & 0.59958 & 0.70021 \tabularnewline
229 & 0.273257 & 0.546515 & 0.726743 \tabularnewline
230 & 0.257074 & 0.514148 & 0.742926 \tabularnewline
231 & 0.217447 & 0.434895 & 0.782553 \tabularnewline
232 & 0.250767 & 0.501535 & 0.749233 \tabularnewline
233 & 0.209474 & 0.418948 & 0.790526 \tabularnewline
234 & 0.172361 & 0.344722 & 0.827639 \tabularnewline
235 & 0.171193 & 0.342387 & 0.828807 \tabularnewline
236 & 0.148735 & 0.297469 & 0.851265 \tabularnewline
237 & 0.122028 & 0.244057 & 0.877972 \tabularnewline
238 & 0.0926116 & 0.185223 & 0.907388 \tabularnewline
239 & 0.187083 & 0.374165 & 0.812917 \tabularnewline
240 & 0.180889 & 0.361779 & 0.819111 \tabularnewline
241 & 0.152137 & 0.304274 & 0.847863 \tabularnewline
242 & 0.322973 & 0.645946 & 0.677027 \tabularnewline
243 & 0.280591 & 0.561183 & 0.719409 \tabularnewline
244 & 0.225634 & 0.451267 & 0.774366 \tabularnewline
245 & 0.338282 & 0.676564 & 0.661718 \tabularnewline
246 & 0.258917 & 0.517834 & 0.741083 \tabularnewline
247 & 0.190493 & 0.380985 & 0.809507 \tabularnewline
248 & 0.309307 & 0.618614 & 0.690693 \tabularnewline
249 & 0.223496 & 0.446991 & 0.776504 \tabularnewline
250 & 0.148199 & 0.296398 & 0.851801 \tabularnewline
251 & 0.23589 & 0.471779 & 0.76411 \tabularnewline
252 & 0.743669 & 0.512663 & 0.256331 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230053&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]12[/C][C]0.824603[/C][C]0.350795[/C][C]0.175397[/C][/ROW]
[ROW][C]13[/C][C]0.981779[/C][C]0.0364426[/C][C]0.0182213[/C][/ROW]
[ROW][C]14[/C][C]0.965041[/C][C]0.069917[/C][C]0.0349585[/C][/ROW]
[ROW][C]15[/C][C]0.965416[/C][C]0.0691686[/C][C]0.0345843[/C][/ROW]
[ROW][C]16[/C][C]0.942983[/C][C]0.114034[/C][C]0.0570171[/C][/ROW]
[ROW][C]17[/C][C]0.966857[/C][C]0.0662854[/C][C]0.0331427[/C][/ROW]
[ROW][C]18[/C][C]0.946711[/C][C]0.106578[/C][C]0.0532888[/C][/ROW]
[ROW][C]19[/C][C]0.919138[/C][C]0.161723[/C][C]0.0808616[/C][/ROW]
[ROW][C]20[/C][C]0.915309[/C][C]0.169383[/C][C]0.0846913[/C][/ROW]
[ROW][C]21[/C][C]0.937425[/C][C]0.125151[/C][C]0.0625755[/C][/ROW]
[ROW][C]22[/C][C]0.935062[/C][C]0.129877[/C][C]0.0649384[/C][/ROW]
[ROW][C]23[/C][C]0.935048[/C][C]0.129904[/C][C]0.0649519[/C][/ROW]
[ROW][C]24[/C][C]0.911274[/C][C]0.177451[/C][C]0.0887255[/C][/ROW]
[ROW][C]25[/C][C]0.890914[/C][C]0.218172[/C][C]0.109086[/C][/ROW]
[ROW][C]26[/C][C]0.999305[/C][C]0.00138907[/C][C]0.000694537[/C][/ROW]
[ROW][C]27[/C][C]0.998868[/C][C]0.00226494[/C][C]0.00113247[/C][/ROW]
[ROW][C]28[/C][C]0.998158[/C][C]0.00368398[/C][C]0.00184199[/C][/ROW]
[ROW][C]29[/C][C]0.99711[/C][C]0.00578021[/C][C]0.00289011[/C][/ROW]
[ROW][C]30[/C][C]0.998049[/C][C]0.0039012[/C][C]0.0019506[/C][/ROW]
[ROW][C]31[/C][C]0.996985[/C][C]0.00603089[/C][C]0.00301545[/C][/ROW]
[ROW][C]32[/C][C]0.995576[/C][C]0.00884846[/C][C]0.00442423[/C][/ROW]
[ROW][C]33[/C][C]0.994548[/C][C]0.0109034[/C][C]0.00545172[/C][/ROW]
[ROW][C]34[/C][C]0.992005[/C][C]0.0159893[/C][C]0.00799464[/C][/ROW]
[ROW][C]35[/C][C]0.990016[/C][C]0.0199677[/C][C]0.00998386[/C][/ROW]
[ROW][C]36[/C][C]0.985934[/C][C]0.0281319[/C][C]0.0140659[/C][/ROW]
[ROW][C]37[/C][C]0.990573[/C][C]0.0188533[/C][C]0.00942663[/C][/ROW]
[ROW][C]38[/C][C]0.986789[/C][C]0.0264222[/C][C]0.0132111[/C][/ROW]
[ROW][C]39[/C][C]0.984613[/C][C]0.0307736[/C][C]0.0153868[/C][/ROW]
[ROW][C]40[/C][C]0.98496[/C][C]0.0300802[/C][C]0.0150401[/C][/ROW]
[ROW][C]41[/C][C]0.980132[/C][C]0.039736[/C][C]0.019868[/C][/ROW]
[ROW][C]42[/C][C]0.97772[/C][C]0.0445594[/C][C]0.0222797[/C][/ROW]
[ROW][C]43[/C][C]0.970372[/C][C]0.0592567[/C][C]0.0296284[/C][/ROW]
[ROW][C]44[/C][C]0.965038[/C][C]0.0699237[/C][C]0.0349618[/C][/ROW]
[ROW][C]45[/C][C]0.95454[/C][C]0.0909193[/C][C]0.0454597[/C][/ROW]
[ROW][C]46[/C][C]0.962917[/C][C]0.0741663[/C][C]0.0370832[/C][/ROW]
[ROW][C]47[/C][C]0.952381[/C][C]0.0952379[/C][C]0.0476189[/C][/ROW]
[ROW][C]48[/C][C]0.939269[/C][C]0.121463[/C][C]0.0607313[/C][/ROW]
[ROW][C]49[/C][C]0.947816[/C][C]0.104369[/C][C]0.0521843[/C][/ROW]
[ROW][C]50[/C][C]0.944617[/C][C]0.110766[/C][C]0.055383[/C][/ROW]
[ROW][C]51[/C][C]0.931738[/C][C]0.136525[/C][C]0.0682624[/C][/ROW]
[ROW][C]52[/C][C]0.915539[/C][C]0.168922[/C][C]0.0844609[/C][/ROW]
[ROW][C]53[/C][C]0.902865[/C][C]0.194269[/C][C]0.0971346[/C][/ROW]
[ROW][C]54[/C][C]0.887938[/C][C]0.224125[/C][C]0.112062[/C][/ROW]
[ROW][C]55[/C][C]0.882811[/C][C]0.234377[/C][C]0.117189[/C][/ROW]
[ROW][C]56[/C][C]0.864438[/C][C]0.271124[/C][C]0.135562[/C][/ROW]
[ROW][C]57[/C][C]0.850511[/C][C]0.298978[/C][C]0.149489[/C][/ROW]
[ROW][C]58[/C][C]0.823721[/C][C]0.352558[/C][C]0.176279[/C][/ROW]
[ROW][C]59[/C][C]0.865214[/C][C]0.269572[/C][C]0.134786[/C][/ROW]
[ROW][C]60[/C][C]0.862215[/C][C]0.275569[/C][C]0.137785[/C][/ROW]
[ROW][C]61[/C][C]0.882883[/C][C]0.234235[/C][C]0.117117[/C][/ROW]
[ROW][C]62[/C][C]0.883759[/C][C]0.232483[/C][C]0.116241[/C][/ROW]
[ROW][C]63[/C][C]0.931662[/C][C]0.136676[/C][C]0.0683378[/C][/ROW]
[ROW][C]64[/C][C]0.92016[/C][C]0.159681[/C][C]0.0798404[/C][/ROW]
[ROW][C]65[/C][C]0.909764[/C][C]0.180472[/C][C]0.0902362[/C][/ROW]
[ROW][C]66[/C][C]0.920839[/C][C]0.158322[/C][C]0.0791609[/C][/ROW]
[ROW][C]67[/C][C]0.920025[/C][C]0.15995[/C][C]0.0799752[/C][/ROW]
[ROW][C]68[/C][C]0.911233[/C][C]0.177533[/C][C]0.0887666[/C][/ROW]
[ROW][C]69[/C][C]0.941933[/C][C]0.116133[/C][C]0.0580665[/C][/ROW]
[ROW][C]70[/C][C]0.946385[/C][C]0.10723[/C][C]0.053615[/C][/ROW]
[ROW][C]71[/C][C]0.94109[/C][C]0.117819[/C][C]0.0589097[/C][/ROW]
[ROW][C]72[/C][C]0.961069[/C][C]0.0778628[/C][C]0.0389314[/C][/ROW]
[ROW][C]73[/C][C]0.952588[/C][C]0.0948234[/C][C]0.0474117[/C][/ROW]
[ROW][C]74[/C][C]0.941999[/C][C]0.116002[/C][C]0.0580011[/C][/ROW]
[ROW][C]75[/C][C]0.935144[/C][C]0.129713[/C][C]0.0648565[/C][/ROW]
[ROW][C]76[/C][C]0.921583[/C][C]0.156835[/C][C]0.0784173[/C][/ROW]
[ROW][C]77[/C][C]0.937619[/C][C]0.124762[/C][C]0.0623809[/C][/ROW]
[ROW][C]78[/C][C]0.926044[/C][C]0.147911[/C][C]0.0739557[/C][/ROW]
[ROW][C]79[/C][C]0.919673[/C][C]0.160654[/C][C]0.0803271[/C][/ROW]
[ROW][C]80[/C][C]0.912994[/C][C]0.174012[/C][C]0.087006[/C][/ROW]
[ROW][C]81[/C][C]0.896443[/C][C]0.207115[/C][C]0.103557[/C][/ROW]
[ROW][C]82[/C][C]0.878486[/C][C]0.243028[/C][C]0.121514[/C][/ROW]
[ROW][C]83[/C][C]0.87294[/C][C]0.25412[/C][C]0.12706[/C][/ROW]
[ROW][C]84[/C][C]0.854615[/C][C]0.290769[/C][C]0.145385[/C][/ROW]
[ROW][C]85[/C][C]0.831574[/C][C]0.336851[/C][C]0.168426[/C][/ROW]
[ROW][C]86[/C][C]0.808979[/C][C]0.382041[/C][C]0.191021[/C][/ROW]
[ROW][C]87[/C][C]0.782155[/C][C]0.43569[/C][C]0.217845[/C][/ROW]
[ROW][C]88[/C][C]0.753175[/C][C]0.49365[/C][C]0.246825[/C][/ROW]
[ROW][C]89[/C][C]0.82166[/C][C]0.35668[/C][C]0.17834[/C][/ROW]
[ROW][C]90[/C][C]0.852555[/C][C]0.294889[/C][C]0.147445[/C][/ROW]
[ROW][C]91[/C][C]0.830449[/C][C]0.339103[/C][C]0.169551[/C][/ROW]
[ROW][C]92[/C][C]0.807686[/C][C]0.384629[/C][C]0.192314[/C][/ROW]
[ROW][C]93[/C][C]0.785513[/C][C]0.428975[/C][C]0.214487[/C][/ROW]
[ROW][C]94[/C][C]0.762979[/C][C]0.474043[/C][C]0.237021[/C][/ROW]
[ROW][C]95[/C][C]0.737313[/C][C]0.525374[/C][C]0.262687[/C][/ROW]
[ROW][C]96[/C][C]0.712745[/C][C]0.57451[/C][C]0.287255[/C][/ROW]
[ROW][C]97[/C][C]0.686617[/C][C]0.626767[/C][C]0.313383[/C][/ROW]
[ROW][C]98[/C][C]0.684439[/C][C]0.631121[/C][C]0.315561[/C][/ROW]
[ROW][C]99[/C][C]0.650931[/C][C]0.698139[/C][C]0.349069[/C][/ROW]
[ROW][C]100[/C][C]0.64028[/C][C]0.71944[/C][C]0.35972[/C][/ROW]
[ROW][C]101[/C][C]0.616655[/C][C]0.76669[/C][C]0.383345[/C][/ROW]
[ROW][C]102[/C][C]0.586979[/C][C]0.826042[/C][C]0.413021[/C][/ROW]
[ROW][C]103[/C][C]0.637764[/C][C]0.724471[/C][C]0.362236[/C][/ROW]
[ROW][C]104[/C][C]0.623252[/C][C]0.753497[/C][C]0.376748[/C][/ROW]
[ROW][C]105[/C][C]0.640618[/C][C]0.718763[/C][C]0.359382[/C][/ROW]
[ROW][C]106[/C][C]0.613906[/C][C]0.772188[/C][C]0.386094[/C][/ROW]
[ROW][C]107[/C][C]0.603805[/C][C]0.79239[/C][C]0.396195[/C][/ROW]
[ROW][C]108[/C][C]0.644425[/C][C]0.71115[/C][C]0.355575[/C][/ROW]
[ROW][C]109[/C][C]0.613576[/C][C]0.772847[/C][C]0.386424[/C][/ROW]
[ROW][C]110[/C][C]0.586553[/C][C]0.826894[/C][C]0.413447[/C][/ROW]
[ROW][C]111[/C][C]0.594182[/C][C]0.811636[/C][C]0.405818[/C][/ROW]
[ROW][C]112[/C][C]0.621604[/C][C]0.756792[/C][C]0.378396[/C][/ROW]
[ROW][C]113[/C][C]0.609431[/C][C]0.781139[/C][C]0.390569[/C][/ROW]
[ROW][C]114[/C][C]0.696203[/C][C]0.607595[/C][C]0.303797[/C][/ROW]
[ROW][C]115[/C][C]0.666378[/C][C]0.667245[/C][C]0.333622[/C][/ROW]
[ROW][C]116[/C][C]0.639692[/C][C]0.720617[/C][C]0.360308[/C][/ROW]
[ROW][C]117[/C][C]0.605796[/C][C]0.788407[/C][C]0.394204[/C][/ROW]
[ROW][C]118[/C][C]0.581841[/C][C]0.836318[/C][C]0.418159[/C][/ROW]
[ROW][C]119[/C][C]0.546766[/C][C]0.906467[/C][C]0.453234[/C][/ROW]
[ROW][C]120[/C][C]0.514775[/C][C]0.97045[/C][C]0.485225[/C][/ROW]
[ROW][C]121[/C][C]0.485558[/C][C]0.971115[/C][C]0.514442[/C][/ROW]
[ROW][C]122[/C][C]0.452675[/C][C]0.90535[/C][C]0.547325[/C][/ROW]
[ROW][C]123[/C][C]0.425557[/C][C]0.851115[/C][C]0.574443[/C][/ROW]
[ROW][C]124[/C][C]0.393619[/C][C]0.787239[/C][C]0.606381[/C][/ROW]
[ROW][C]125[/C][C]0.385307[/C][C]0.770614[/C][C]0.614693[/C][/ROW]
[ROW][C]126[/C][C]0.355651[/C][C]0.711303[/C][C]0.644349[/C][/ROW]
[ROW][C]127[/C][C]0.339417[/C][C]0.678835[/C][C]0.660583[/C][/ROW]
[ROW][C]128[/C][C]0.44132[/C][C]0.882641[/C][C]0.55868[/C][/ROW]
[ROW][C]129[/C][C]0.42196[/C][C]0.84392[/C][C]0.57804[/C][/ROW]
[ROW][C]130[/C][C]0.412335[/C][C]0.82467[/C][C]0.587665[/C][/ROW]
[ROW][C]131[/C][C]0.400216[/C][C]0.800432[/C][C]0.599784[/C][/ROW]
[ROW][C]132[/C][C]0.371018[/C][C]0.742035[/C][C]0.628982[/C][/ROW]
[ROW][C]133[/C][C]0.38819[/C][C]0.77638[/C][C]0.61181[/C][/ROW]
[ROW][C]134[/C][C]0.358791[/C][C]0.717582[/C][C]0.641209[/C][/ROW]
[ROW][C]135[/C][C]0.367991[/C][C]0.735982[/C][C]0.632009[/C][/ROW]
[ROW][C]136[/C][C]0.35643[/C][C]0.712861[/C][C]0.64357[/C][/ROW]
[ROW][C]137[/C][C]0.326603[/C][C]0.653206[/C][C]0.673397[/C][/ROW]
[ROW][C]138[/C][C]0.302997[/C][C]0.605994[/C][C]0.697003[/C][/ROW]
[ROW][C]139[/C][C]0.276337[/C][C]0.552674[/C][C]0.723663[/C][/ROW]
[ROW][C]140[/C][C]0.253076[/C][C]0.506152[/C][C]0.746924[/C][/ROW]
[ROW][C]141[/C][C]0.225735[/C][C]0.451469[/C][C]0.774265[/C][/ROW]
[ROW][C]142[/C][C]0.229553[/C][C]0.459107[/C][C]0.770447[/C][/ROW]
[ROW][C]143[/C][C]0.205045[/C][C]0.41009[/C][C]0.794955[/C][/ROW]
[ROW][C]144[/C][C]0.184574[/C][C]0.369148[/C][C]0.815426[/C][/ROW]
[ROW][C]145[/C][C]0.172435[/C][C]0.34487[/C][C]0.827565[/C][/ROW]
[ROW][C]146[/C][C]0.165167[/C][C]0.330334[/C][C]0.834833[/C][/ROW]
[ROW][C]147[/C][C]0.172737[/C][C]0.345473[/C][C]0.827263[/C][/ROW]
[ROW][C]148[/C][C]0.190157[/C][C]0.380314[/C][C]0.809843[/C][/ROW]
[ROW][C]149[/C][C]0.209653[/C][C]0.419305[/C][C]0.790347[/C][/ROW]
[ROW][C]150[/C][C]0.206289[/C][C]0.412578[/C][C]0.793711[/C][/ROW]
[ROW][C]151[/C][C]0.1846[/C][C]0.369199[/C][C]0.8154[/C][/ROW]
[ROW][C]152[/C][C]0.165002[/C][C]0.330003[/C][C]0.834998[/C][/ROW]
[ROW][C]153[/C][C]0.178431[/C][C]0.356862[/C][C]0.821569[/C][/ROW]
[ROW][C]154[/C][C]0.21411[/C][C]0.42822[/C][C]0.78589[/C][/ROW]
[ROW][C]155[/C][C]0.192742[/C][C]0.385483[/C][C]0.807258[/C][/ROW]
[ROW][C]156[/C][C]0.172668[/C][C]0.345336[/C][C]0.827332[/C][/ROW]
[ROW][C]157[/C][C]0.150563[/C][C]0.301127[/C][C]0.849437[/C][/ROW]
[ROW][C]158[/C][C]0.220438[/C][C]0.440875[/C][C]0.779562[/C][/ROW]
[ROW][C]159[/C][C]0.246264[/C][C]0.492529[/C][C]0.753736[/C][/ROW]
[ROW][C]160[/C][C]0.220664[/C][C]0.441328[/C][C]0.779336[/C][/ROW]
[ROW][C]161[/C][C]0.194211[/C][C]0.388421[/C][C]0.805789[/C][/ROW]
[ROW][C]162[/C][C]0.171711[/C][C]0.343422[/C][C]0.828289[/C][/ROW]
[ROW][C]163[/C][C]0.151718[/C][C]0.303436[/C][C]0.848282[/C][/ROW]
[ROW][C]164[/C][C]0.254986[/C][C]0.509972[/C][C]0.745014[/C][/ROW]
[ROW][C]165[/C][C]0.251776[/C][C]0.503551[/C][C]0.748224[/C][/ROW]
[ROW][C]166[/C][C]0.24759[/C][C]0.495181[/C][C]0.75241[/C][/ROW]
[ROW][C]167[/C][C]0.219723[/C][C]0.439446[/C][C]0.780277[/C][/ROW]
[ROW][C]168[/C][C]0.197981[/C][C]0.395962[/C][C]0.802019[/C][/ROW]
[ROW][C]169[/C][C]0.251855[/C][C]0.50371[/C][C]0.748145[/C][/ROW]
[ROW][C]170[/C][C]0.274197[/C][C]0.548393[/C][C]0.725803[/C][/ROW]
[ROW][C]171[/C][C]0.247032[/C][C]0.494064[/C][C]0.752968[/C][/ROW]
[ROW][C]172[/C][C]0.243402[/C][C]0.486805[/C][C]0.756598[/C][/ROW]
[ROW][C]173[/C][C]0.39704[/C][C]0.794079[/C][C]0.60296[/C][/ROW]
[ROW][C]174[/C][C]0.385499[/C][C]0.770998[/C][C]0.614501[/C][/ROW]
[ROW][C]175[/C][C]0.410813[/C][C]0.821625[/C][C]0.589187[/C][/ROW]
[ROW][C]176[/C][C]0.41656[/C][C]0.83312[/C][C]0.58344[/C][/ROW]
[ROW][C]177[/C][C]0.467612[/C][C]0.935224[/C][C]0.532388[/C][/ROW]
[ROW][C]178[/C][C]0.434504[/C][C]0.869008[/C][C]0.565496[/C][/ROW]
[ROW][C]179[/C][C]0.414788[/C][C]0.829576[/C][C]0.585212[/C][/ROW]
[ROW][C]180[/C][C]0.410607[/C][C]0.821214[/C][C]0.589393[/C][/ROW]
[ROW][C]181[/C][C]0.373585[/C][C]0.74717[/C][C]0.626415[/C][/ROW]
[ROW][C]182[/C][C]0.362893[/C][C]0.725785[/C][C]0.637107[/C][/ROW]
[ROW][C]183[/C][C]0.327377[/C][C]0.654754[/C][C]0.672623[/C][/ROW]
[ROW][C]184[/C][C]0.299487[/C][C]0.598974[/C][C]0.700513[/C][/ROW]
[ROW][C]185[/C][C]0.315179[/C][C]0.630359[/C][C]0.684821[/C][/ROW]
[ROW][C]186[/C][C]0.309112[/C][C]0.618223[/C][C]0.690888[/C][/ROW]
[ROW][C]187[/C][C]0.276825[/C][C]0.553651[/C][C]0.723175[/C][/ROW]
[ROW][C]188[/C][C]0.251565[/C][C]0.503131[/C][C]0.748435[/C][/ROW]
[ROW][C]189[/C][C]0.222853[/C][C]0.445707[/C][C]0.777147[/C][/ROW]
[ROW][C]190[/C][C]0.201645[/C][C]0.40329[/C][C]0.798355[/C][/ROW]
[ROW][C]191[/C][C]0.20416[/C][C]0.408321[/C][C]0.79584[/C][/ROW]
[ROW][C]192[/C][C]0.185767[/C][C]0.371535[/C][C]0.814233[/C][/ROW]
[ROW][C]193[/C][C]0.203821[/C][C]0.407641[/C][C]0.796179[/C][/ROW]
[ROW][C]194[/C][C]0.190128[/C][C]0.380255[/C][C]0.809872[/C][/ROW]
[ROW][C]195[/C][C]0.19095[/C][C]0.381901[/C][C]0.80905[/C][/ROW]
[ROW][C]196[/C][C]0.198425[/C][C]0.39685[/C][C]0.801575[/C][/ROW]
[ROW][C]197[/C][C]0.243698[/C][C]0.487397[/C][C]0.756302[/C][/ROW]
[ROW][C]198[/C][C]0.226493[/C][C]0.452987[/C][C]0.773507[/C][/ROW]
[ROW][C]199[/C][C]0.254553[/C][C]0.509105[/C][C]0.745447[/C][/ROW]
[ROW][C]200[/C][C]0.222883[/C][C]0.445766[/C][C]0.777117[/C][/ROW]
[ROW][C]201[/C][C]0.253156[/C][C]0.506311[/C][C]0.746844[/C][/ROW]
[ROW][C]202[/C][C]0.234157[/C][C]0.468314[/C][C]0.765843[/C][/ROW]
[ROW][C]203[/C][C]0.294476[/C][C]0.588953[/C][C]0.705524[/C][/ROW]
[ROW][C]204[/C][C]0.261028[/C][C]0.522056[/C][C]0.738972[/C][/ROW]
[ROW][C]205[/C][C]0.229337[/C][C]0.458675[/C][C]0.770663[/C][/ROW]
[ROW][C]206[/C][C]0.210362[/C][C]0.420724[/C][C]0.789638[/C][/ROW]
[ROW][C]207[/C][C]0.180422[/C][C]0.360844[/C][C]0.819578[/C][/ROW]
[ROW][C]208[/C][C]0.201875[/C][C]0.403749[/C][C]0.798125[/C][/ROW]
[ROW][C]209[/C][C]0.172051[/C][C]0.344101[/C][C]0.827949[/C][/ROW]
[ROW][C]210[/C][C]0.187875[/C][C]0.37575[/C][C]0.812125[/C][/ROW]
[ROW][C]211[/C][C]0.211367[/C][C]0.422734[/C][C]0.788633[/C][/ROW]
[ROW][C]212[/C][C]0.197306[/C][C]0.394612[/C][C]0.802694[/C][/ROW]
[ROW][C]213[/C][C]0.171303[/C][C]0.342606[/C][C]0.828697[/C][/ROW]
[ROW][C]214[/C][C]0.213503[/C][C]0.427006[/C][C]0.786497[/C][/ROW]
[ROW][C]215[/C][C]0.187264[/C][C]0.374528[/C][C]0.812736[/C][/ROW]
[ROW][C]216[/C][C]0.176294[/C][C]0.352589[/C][C]0.823706[/C][/ROW]
[ROW][C]217[/C][C]0.207252[/C][C]0.414504[/C][C]0.792748[/C][/ROW]
[ROW][C]218[/C][C]0.178521[/C][C]0.357042[/C][C]0.821479[/C][/ROW]
[ROW][C]219[/C][C]0.164766[/C][C]0.329531[/C][C]0.835234[/C][/ROW]
[ROW][C]220[/C][C]0.171788[/C][C]0.343576[/C][C]0.828212[/C][/ROW]
[ROW][C]221[/C][C]0.176701[/C][C]0.353403[/C][C]0.823299[/C][/ROW]
[ROW][C]222[/C][C]0.17902[/C][C]0.358039[/C][C]0.82098[/C][/ROW]
[ROW][C]223[/C][C]0.163087[/C][C]0.326174[/C][C]0.836913[/C][/ROW]
[ROW][C]224[/C][C]0.134519[/C][C]0.269039[/C][C]0.865481[/C][/ROW]
[ROW][C]225[/C][C]0.120551[/C][C]0.241103[/C][C]0.879449[/C][/ROW]
[ROW][C]226[/C][C]0.145352[/C][C]0.290704[/C][C]0.854648[/C][/ROW]
[ROW][C]227[/C][C]0.323597[/C][C]0.647194[/C][C]0.676403[/C][/ROW]
[ROW][C]228[/C][C]0.29979[/C][C]0.59958[/C][C]0.70021[/C][/ROW]
[ROW][C]229[/C][C]0.273257[/C][C]0.546515[/C][C]0.726743[/C][/ROW]
[ROW][C]230[/C][C]0.257074[/C][C]0.514148[/C][C]0.742926[/C][/ROW]
[ROW][C]231[/C][C]0.217447[/C][C]0.434895[/C][C]0.782553[/C][/ROW]
[ROW][C]232[/C][C]0.250767[/C][C]0.501535[/C][C]0.749233[/C][/ROW]
[ROW][C]233[/C][C]0.209474[/C][C]0.418948[/C][C]0.790526[/C][/ROW]
[ROW][C]234[/C][C]0.172361[/C][C]0.344722[/C][C]0.827639[/C][/ROW]
[ROW][C]235[/C][C]0.171193[/C][C]0.342387[/C][C]0.828807[/C][/ROW]
[ROW][C]236[/C][C]0.148735[/C][C]0.297469[/C][C]0.851265[/C][/ROW]
[ROW][C]237[/C][C]0.122028[/C][C]0.244057[/C][C]0.877972[/C][/ROW]
[ROW][C]238[/C][C]0.0926116[/C][C]0.185223[/C][C]0.907388[/C][/ROW]
[ROW][C]239[/C][C]0.187083[/C][C]0.374165[/C][C]0.812917[/C][/ROW]
[ROW][C]240[/C][C]0.180889[/C][C]0.361779[/C][C]0.819111[/C][/ROW]
[ROW][C]241[/C][C]0.152137[/C][C]0.304274[/C][C]0.847863[/C][/ROW]
[ROW][C]242[/C][C]0.322973[/C][C]0.645946[/C][C]0.677027[/C][/ROW]
[ROW][C]243[/C][C]0.280591[/C][C]0.561183[/C][C]0.719409[/C][/ROW]
[ROW][C]244[/C][C]0.225634[/C][C]0.451267[/C][C]0.774366[/C][/ROW]
[ROW][C]245[/C][C]0.338282[/C][C]0.676564[/C][C]0.661718[/C][/ROW]
[ROW][C]246[/C][C]0.258917[/C][C]0.517834[/C][C]0.741083[/C][/ROW]
[ROW][C]247[/C][C]0.190493[/C][C]0.380985[/C][C]0.809507[/C][/ROW]
[ROW][C]248[/C][C]0.309307[/C][C]0.618614[/C][C]0.690693[/C][/ROW]
[ROW][C]249[/C][C]0.223496[/C][C]0.446991[/C][C]0.776504[/C][/ROW]
[ROW][C]250[/C][C]0.148199[/C][C]0.296398[/C][C]0.851801[/C][/ROW]
[ROW][C]251[/C][C]0.23589[/C][C]0.471779[/C][C]0.76411[/C][/ROW]
[ROW][C]252[/C][C]0.743669[/C][C]0.512663[/C][C]0.256331[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230053&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230053&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.8246030.3507950.175397
130.9817790.03644260.0182213
140.9650410.0699170.0349585
150.9654160.06916860.0345843
160.9429830.1140340.0570171
170.9668570.06628540.0331427
180.9467110.1065780.0532888
190.9191380.1617230.0808616
200.9153090.1693830.0846913
210.9374250.1251510.0625755
220.9350620.1298770.0649384
230.9350480.1299040.0649519
240.9112740.1774510.0887255
250.8909140.2181720.109086
260.9993050.001389070.000694537
270.9988680.002264940.00113247
280.9981580.003683980.00184199
290.997110.005780210.00289011
300.9980490.00390120.0019506
310.9969850.006030890.00301545
320.9955760.008848460.00442423
330.9945480.01090340.00545172
340.9920050.01598930.00799464
350.9900160.01996770.00998386
360.9859340.02813190.0140659
370.9905730.01885330.00942663
380.9867890.02642220.0132111
390.9846130.03077360.0153868
400.984960.03008020.0150401
410.9801320.0397360.019868
420.977720.04455940.0222797
430.9703720.05925670.0296284
440.9650380.06992370.0349618
450.954540.09091930.0454597
460.9629170.07416630.0370832
470.9523810.09523790.0476189
480.9392690.1214630.0607313
490.9478160.1043690.0521843
500.9446170.1107660.055383
510.9317380.1365250.0682624
520.9155390.1689220.0844609
530.9028650.1942690.0971346
540.8879380.2241250.112062
550.8828110.2343770.117189
560.8644380.2711240.135562
570.8505110.2989780.149489
580.8237210.3525580.176279
590.8652140.2695720.134786
600.8622150.2755690.137785
610.8828830.2342350.117117
620.8837590.2324830.116241
630.9316620.1366760.0683378
640.920160.1596810.0798404
650.9097640.1804720.0902362
660.9208390.1583220.0791609
670.9200250.159950.0799752
680.9112330.1775330.0887666
690.9419330.1161330.0580665
700.9463850.107230.053615
710.941090.1178190.0589097
720.9610690.07786280.0389314
730.9525880.09482340.0474117
740.9419990.1160020.0580011
750.9351440.1297130.0648565
760.9215830.1568350.0784173
770.9376190.1247620.0623809
780.9260440.1479110.0739557
790.9196730.1606540.0803271
800.9129940.1740120.087006
810.8964430.2071150.103557
820.8784860.2430280.121514
830.872940.254120.12706
840.8546150.2907690.145385
850.8315740.3368510.168426
860.8089790.3820410.191021
870.7821550.435690.217845
880.7531750.493650.246825
890.821660.356680.17834
900.8525550.2948890.147445
910.8304490.3391030.169551
920.8076860.3846290.192314
930.7855130.4289750.214487
940.7629790.4740430.237021
950.7373130.5253740.262687
960.7127450.574510.287255
970.6866170.6267670.313383
980.6844390.6311210.315561
990.6509310.6981390.349069
1000.640280.719440.35972
1010.6166550.766690.383345
1020.5869790.8260420.413021
1030.6377640.7244710.362236
1040.6232520.7534970.376748
1050.6406180.7187630.359382
1060.6139060.7721880.386094
1070.6038050.792390.396195
1080.6444250.711150.355575
1090.6135760.7728470.386424
1100.5865530.8268940.413447
1110.5941820.8116360.405818
1120.6216040.7567920.378396
1130.6094310.7811390.390569
1140.6962030.6075950.303797
1150.6663780.6672450.333622
1160.6396920.7206170.360308
1170.6057960.7884070.394204
1180.5818410.8363180.418159
1190.5467660.9064670.453234
1200.5147750.970450.485225
1210.4855580.9711150.514442
1220.4526750.905350.547325
1230.4255570.8511150.574443
1240.3936190.7872390.606381
1250.3853070.7706140.614693
1260.3556510.7113030.644349
1270.3394170.6788350.660583
1280.441320.8826410.55868
1290.421960.843920.57804
1300.4123350.824670.587665
1310.4002160.8004320.599784
1320.3710180.7420350.628982
1330.388190.776380.61181
1340.3587910.7175820.641209
1350.3679910.7359820.632009
1360.356430.7128610.64357
1370.3266030.6532060.673397
1380.3029970.6059940.697003
1390.2763370.5526740.723663
1400.2530760.5061520.746924
1410.2257350.4514690.774265
1420.2295530.4591070.770447
1430.2050450.410090.794955
1440.1845740.3691480.815426
1450.1724350.344870.827565
1460.1651670.3303340.834833
1470.1727370.3454730.827263
1480.1901570.3803140.809843
1490.2096530.4193050.790347
1500.2062890.4125780.793711
1510.18460.3691990.8154
1520.1650020.3300030.834998
1530.1784310.3568620.821569
1540.214110.428220.78589
1550.1927420.3854830.807258
1560.1726680.3453360.827332
1570.1505630.3011270.849437
1580.2204380.4408750.779562
1590.2462640.4925290.753736
1600.2206640.4413280.779336
1610.1942110.3884210.805789
1620.1717110.3434220.828289
1630.1517180.3034360.848282
1640.2549860.5099720.745014
1650.2517760.5035510.748224
1660.247590.4951810.75241
1670.2197230.4394460.780277
1680.1979810.3959620.802019
1690.2518550.503710.748145
1700.2741970.5483930.725803
1710.2470320.4940640.752968
1720.2434020.4868050.756598
1730.397040.7940790.60296
1740.3854990.7709980.614501
1750.4108130.8216250.589187
1760.416560.833120.58344
1770.4676120.9352240.532388
1780.4345040.8690080.565496
1790.4147880.8295760.585212
1800.4106070.8212140.589393
1810.3735850.747170.626415
1820.3628930.7257850.637107
1830.3273770.6547540.672623
1840.2994870.5989740.700513
1850.3151790.6303590.684821
1860.3091120.6182230.690888
1870.2768250.5536510.723175
1880.2515650.5031310.748435
1890.2228530.4457070.777147
1900.2016450.403290.798355
1910.204160.4083210.79584
1920.1857670.3715350.814233
1930.2038210.4076410.796179
1940.1901280.3802550.809872
1950.190950.3819010.80905
1960.1984250.396850.801575
1970.2436980.4873970.756302
1980.2264930.4529870.773507
1990.2545530.5091050.745447
2000.2228830.4457660.777117
2010.2531560.5063110.746844
2020.2341570.4683140.765843
2030.2944760.5889530.705524
2040.2610280.5220560.738972
2050.2293370.4586750.770663
2060.2103620.4207240.789638
2070.1804220.3608440.819578
2080.2018750.4037490.798125
2090.1720510.3441010.827949
2100.1878750.375750.812125
2110.2113670.4227340.788633
2120.1973060.3946120.802694
2130.1713030.3426060.828697
2140.2135030.4270060.786497
2150.1872640.3745280.812736
2160.1762940.3525890.823706
2170.2072520.4145040.792748
2180.1785210.3570420.821479
2190.1647660.3295310.835234
2200.1717880.3435760.828212
2210.1767010.3534030.823299
2220.179020.3580390.82098
2230.1630870.3261740.836913
2240.1345190.2690390.865481
2250.1205510.2411030.879449
2260.1453520.2907040.854648
2270.3235970.6471940.676403
2280.299790.599580.70021
2290.2732570.5465150.726743
2300.2570740.5141480.742926
2310.2174470.4348950.782553
2320.2507670.5015350.749233
2330.2094740.4189480.790526
2340.1723610.3447220.827639
2350.1711930.3423870.828807
2360.1487350.2974690.851265
2370.1220280.2440570.877972
2380.09261160.1852230.907388
2390.1870830.3741650.812917
2400.1808890.3617790.819111
2410.1521370.3042740.847863
2420.3229730.6459460.677027
2430.2805910.5611830.719409
2440.2256340.4512670.774366
2450.3382820.6765640.661718
2460.2589170.5178340.741083
2470.1904930.3809850.809507
2480.3093070.6186140.690693
2490.2234960.4469910.776504
2500.1481990.2963980.851801
2510.235890.4717790.76411
2520.7436690.5126630.256331







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level70.0290456NOK
5% type I error level180.0746888NOK
10% type I error level280.116183NOK

\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 & 0.0290456 & NOK \tabularnewline
5% type I error level & 18 & 0.0746888 & NOK \tabularnewline
10% type I error level & 28 & 0.116183 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230053&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]0.0290456[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]18[/C][C]0.0746888[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]28[/C][C]0.116183[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230053&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230053&T=6

As an alternative you can also use a 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 level70.0290456NOK
5% type I error level180.0746888NOK
10% type I error level280.116183NOK



Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 5 ; 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')
}