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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 01 Nov 2013 05:12:06 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/01/t13832971557sfswjufkqb6t5f.htm/, Retrieved Mon, 29 Apr 2024 07:32:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221586, Retrieved Mon, 29 Apr 2024 07:32:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2013-11-01 09:12:06] [55c2cace1b2f0b23d7a5ea0032d37b7d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 14 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221586&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221586&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221586&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 23.5546 + 0.429002Separate[t] + 0.112478Learning[t] -0.0592071Software[t] + 0.0111176Happiness[t] -0.041336Depression[t] -0.0530615Sport1[t] + 0.119664Sport2[t] -0.585108Month[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Connected[t] =  +  23.5546 +  0.429002Separate[t] +  0.112478Learning[t] -0.0592071Software[t] +  0.0111176Happiness[t] -0.041336Depression[t] -0.0530615Sport1[t] +  0.119664Sport2[t] -0.585108Month[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221586&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Connected[t] =  +  23.5546 +  0.429002Separate[t] +  0.112478Learning[t] -0.0592071Software[t] +  0.0111176Happiness[t] -0.041336Depression[t] -0.0530615Sport1[t] +  0.119664Sport2[t] -0.585108Month[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221586&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221586&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 23.5546 + 0.429002Separate[t] + 0.112478Learning[t] -0.0592071Software[t] + 0.0111176Happiness[t] -0.041336Depression[t] -0.0530615Sport1[t] + 0.119664Sport2[t] -0.585108Month[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)23.55464.566675.1585.01828e-072.50914e-07
Separate0.4290020.05767997.4381.56186e-127.80928e-13
Learning0.1124780.112391.0010.3178790.15894
Software-0.05920710.114889-0.51530.6067590.30338
Happiness0.01111760.1044020.10650.9152790.45764
Depression-0.0413360.076324-0.54160.5885770.294288
Sport1-0.05306150.0679066-0.78140.4352980.217649
Sport20.1196640.1006661.1890.2356530.117827
Month-0.5851080.288124-2.0310.04331790.021659

\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) & 23.5546 & 4.56667 & 5.158 & 5.01828e-07 & 2.50914e-07 \tabularnewline
Separate & 0.429002 & 0.0576799 & 7.438 & 1.56186e-12 & 7.80928e-13 \tabularnewline
Learning & 0.112478 & 0.11239 & 1.001 & 0.317879 & 0.15894 \tabularnewline
Software & -0.0592071 & 0.114889 & -0.5153 & 0.606759 & 0.30338 \tabularnewline
Happiness & 0.0111176 & 0.104402 & 0.1065 & 0.915279 & 0.45764 \tabularnewline
Depression & -0.041336 & 0.076324 & -0.5416 & 0.588577 & 0.294288 \tabularnewline
Sport1 & -0.0530615 & 0.0679066 & -0.7814 & 0.435298 & 0.217649 \tabularnewline
Sport2 & 0.119664 & 0.100666 & 1.189 & 0.235653 & 0.117827 \tabularnewline
Month & -0.585108 & 0.288124 & -2.031 & 0.0433179 & 0.021659 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221586&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]23.5546[/C][C]4.56667[/C][C]5.158[/C][C]5.01828e-07[/C][C]2.50914e-07[/C][/ROW]
[ROW][C]Separate[/C][C]0.429002[/C][C]0.0576799[/C][C]7.438[/C][C]1.56186e-12[/C][C]7.80928e-13[/C][/ROW]
[ROW][C]Learning[/C][C]0.112478[/C][C]0.11239[/C][C]1.001[/C][C]0.317879[/C][C]0.15894[/C][/ROW]
[ROW][C]Software[/C][C]-0.0592071[/C][C]0.114889[/C][C]-0.5153[/C][C]0.606759[/C][C]0.30338[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0111176[/C][C]0.104402[/C][C]0.1065[/C][C]0.915279[/C][C]0.45764[/C][/ROW]
[ROW][C]Depression[/C][C]-0.041336[/C][C]0.076324[/C][C]-0.5416[/C][C]0.588577[/C][C]0.294288[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.0530615[/C][C]0.0679066[/C][C]-0.7814[/C][C]0.435298[/C][C]0.217649[/C][/ROW]
[ROW][C]Sport2[/C][C]0.119664[/C][C]0.100666[/C][C]1.189[/C][C]0.235653[/C][C]0.117827[/C][/ROW]
[ROW][C]Month[/C][C]-0.585108[/C][C]0.288124[/C][C]-2.031[/C][C]0.0433179[/C][C]0.021659[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221586&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221586&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)23.55464.566675.1585.01828e-072.50914e-07
Separate0.4290020.05767997.4381.56186e-127.80928e-13
Learning0.1124780.112391.0010.3178790.15894
Software-0.05920710.114889-0.51530.6067590.30338
Happiness0.01111760.1044020.10650.9152790.45764
Depression-0.0413360.076324-0.54160.5885770.294288
Sport1-0.05306150.0679066-0.78140.4352980.217649
Sport20.1196640.1006661.1890.2356530.117827
Month-0.5851080.288124-2.0310.04331790.021659






Multiple Linear Regression - Regression Statistics
Multiple R0.493526
R-squared0.243568
Adjusted R-squared0.219837
F-TEST (value)10.2636
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value1.96565e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.35331
Sum Squared Residuals2867.4

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.493526 \tabularnewline
R-squared & 0.243568 \tabularnewline
Adjusted R-squared & 0.219837 \tabularnewline
F-TEST (value) & 10.2636 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 1.96565e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.35331 \tabularnewline
Sum Squared Residuals & 2867.4 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221586&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.493526[/C][/ROW]
[ROW][C]R-squared[/C][C]0.243568[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.219837[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]10.2636[/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]1.96565e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.35331[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2867.4[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221586&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221586&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.493526
R-squared0.243568
Adjusted R-squared0.219837
F-TEST (value)10.2636
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value1.96565e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.35331
Sum Squared Residuals2867.4






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14136.0194.981
23934.60924.3908
33035.6201-5.62005
43134.7661-3.76606
53435.7484-1.74836
63532.78932.21072
73933.87585.12419
83435.9105-1.9105
93635.37960.620402
103736.96590.0340998
113834.24253.75746
123634.9281.07204
133835.35472.64528
143936.42182.5782
153336.6983-3.69828
163234.2296-2.22962
173634.0941.90604
183837.65650.343516
193937.21661.78344
203234.0297-2.02973
213234.8056-2.80561
223133.8774-2.87743
233936.70132.29874
243737.1789-0.178869
253934.61184.38817
264134.26646.73359
273635.34730.652702
283336.1595-3.15951
293334.369-1.36896
303434.7233-0.723295
313133.9888-2.98881
322733.5008-6.50081
333733.72413.27591
343436.9676-2.96758
353432.74051.25953
363234.501-2.50103
372932.5376-3.5376
383634.35881.64122
392934.0427-5.04273
403534.7490.250956
413734.47732.5227
423434.1946-0.194641
433834.30893.69111
443533.93341.06663
453832.365.64002
463734.59372.40626
473837.3160.684039
483335.1475-2.14755
493636.4073-0.407331
503833.9764.02404
513236.7707-4.77072
523232.9496-0.94965
533233.5478-1.54784
543437.3901-3.39006
553233.3767-1.37666
563735.6821.31797
573935.06273.93734
582935.2293-6.22933
593735.76071.23933
603535.0269-0.0268506
613031.5151-1.51514
623834.91153.08854
633435.3996-1.39962
643134.7544-3.7544
653433.38980.6102
663535.9941-0.994083
673634.85771.14234
683031.33-1.32997
693936.33662.66343
703535.6184-0.618421
713835.1272.87295
723135.5704-4.5704
733436.7055-2.70555
743837.3670.633012
753431.59162.40844
763932.91946.08056
773735.68941.31061
783433.19670.803301
792832.9221-4.92214
803731.23185.76821
813335.2615-2.26147
823536.078-1.07797
833733.79113.20886
843234.441-2.44096
853333.3669-0.366867
863836.51111.48895
873334.403-1.40297
882933.1288-4.12879
893333.4369-0.436908
903135.2471-4.24711
913633.06362.93636
923537.4299-2.42993
933231.62070.379347
942932.3324-3.33238
953935.45763.5424
963734.70482.29515
973533.3361.66398
983734.55892.4411
993235.3554-3.35545
1003835.24612.75385
1013734.85032.14966
1023636.3322-0.332156
1033231.94290.057148
1043336.5207-3.52067
1054032.7967.20401
1063835.23492.76509
1074136.40734.59271
1083634.44161.55835
1094336.92516.07494
1103034.6791-4.67907
1113133.6722-2.67221
1123238.1554-6.15535
1133231.50710.492941
1143734.34282.65717
1153734.22992.77012
1163336.3291-3.3291
1173437.293-3.29297
1183334.6778-1.67775
1193835.57832.4217
1203334.9845-1.98445
1213131.3653-0.365299
1223836.63771.36226
1233736.40390.596086
1243633.14352.85652
1253133.8943-2.89427
1263934.19094.80906
1274436.80977.19029
1283336.1026-3.10261
1293533.63321.36681
1303234.0165-2.01648
1312832.4629-4.46289
1324036.07483.92524
1332732.1563-5.15628
1343736.11850.881512
1353232.5524-0.552361
1362828.326-0.326028
1373435.0144-1.0144
1383034.1476-4.14757
1393534.26830.731681
1403134.3164-3.31642
1413234.4525-2.45253
1423035.9757-5.97573
1433035.1811-5.18108
1443129.80841.19157
1454033.23596.76411
1463231.81480.185175
1473634.84771.15225
1483233.2953-1.29535
1493533.30661.69338
1503836.65871.3413
1514235.36826.6318
1523436.2171-2.21706
1533536.9611-1.96113
1543834.77473.22533
1553333.0182-0.0182108
1563633.06362.93636
1573235.7448-3.74478
1583336.1026-3.10261
1593433.99810.00188586
1603235.797-3.79703
1613435.4626-1.46256
1622729.9052-2.90517
1633130.05170.948332
1643833.3424.65802
1653435.6368-1.6368
1662430.8947-6.89471
1673033.4635-3.46354
1682629.2636-3.26356
1693435.243-1.24302
1702734.4694-7.46935
1713731.91695.0831
1723635.20720.792754
1734133.98057.01946
1742928.94070.0592995
1753630.8555.14502
1763234.0683-2.06826
1773733.12763.87243
1783031.4396-1.43965
1793132.5157-1.51568
1803834.45123.54876
1813634.43611.56385
1823531.99413.00595
1833135.0744-4.0744
1843833.06444.93564
1852230.902-8.902
1863234.2433-2.24329
1873633.76122.23877
1883932.62966.37037
1892830.2437-2.24366
1903234.188-2.18805
1913232.3115-0.311547
1923836.39551.6045
1933233.3589-1.35892
1943535.2171-0.217144
1953232.7494-0.749425
1963735.58541.41458
1973432.60651.39351
1983335.3421-2.34205
1993332.75860.241423
2002632.7222-6.72224
2013032.0789-2.07891
2022431.7671-7.7671
2033431.90242.09759
2043432.37441.62557
2053333.9551-0.955144
2063434.6861-0.68606
2073535.8707-0.870721
2083534.15980.840165
2093633.03742.96264
2103433.57840.421582
2113432.70271.29734
2124138.24192.75808
2133236.1091-4.10909
2143033.3054-3.30543
2153533.87361.12637
2162829.9127-1.91266
2173334.8409-1.84089
2183934.16514.8349
2193633.37272.6273
2203636.2857-0.285679
2213533.12531.8747
2223833.85894.14107
2233332.67640.323629
2243132.9028-1.90283
2253432.02381.97623
2263234.2373-2.23729
2273132.6692-1.66919
2283333.1093-0.109349
2293432.64191.35813
2303433.96650.0335138
2313432.13321.8668
2323335.1019-2.10194
2333234.1739-2.17392
2344133.59717.40293
2353432.96721.03278
2363632.03753.96254
2373731.46435.53568
2383630.35625.64385
2392932.4882-3.4882
2403731.76985.23019
2412733.1153-6.11534
2423533.39181.60823
2432830.6603-2.66029
2443533.13891.86106
2453733.09173.90826
2462933.6697-4.66974
2473234.2371-2.23713
2483631.77884.22118
2491927.6244-8.62441
2502126.765-5.76498
2513133.4269-2.42689
2523332.4840.516008
2533633.88662.11339
2543333.2848-0.284831
2553733.12083.87917
2563433.30270.697347
2573534.47860.52145
2583132.8002-1.80023
2593733.41323.5868
2603531.85963.14037
2612731.8352-4.83523
2623434.916-0.915996
2634033.93086.06923
2642932.873-3.873

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 41 & 36.019 & 4.981 \tabularnewline
2 & 39 & 34.6092 & 4.3908 \tabularnewline
3 & 30 & 35.6201 & -5.62005 \tabularnewline
4 & 31 & 34.7661 & -3.76606 \tabularnewline
5 & 34 & 35.7484 & -1.74836 \tabularnewline
6 & 35 & 32.7893 & 2.21072 \tabularnewline
7 & 39 & 33.8758 & 5.12419 \tabularnewline
8 & 34 & 35.9105 & -1.9105 \tabularnewline
9 & 36 & 35.3796 & 0.620402 \tabularnewline
10 & 37 & 36.9659 & 0.0340998 \tabularnewline
11 & 38 & 34.2425 & 3.75746 \tabularnewline
12 & 36 & 34.928 & 1.07204 \tabularnewline
13 & 38 & 35.3547 & 2.64528 \tabularnewline
14 & 39 & 36.4218 & 2.5782 \tabularnewline
15 & 33 & 36.6983 & -3.69828 \tabularnewline
16 & 32 & 34.2296 & -2.22962 \tabularnewline
17 & 36 & 34.094 & 1.90604 \tabularnewline
18 & 38 & 37.6565 & 0.343516 \tabularnewline
19 & 39 & 37.2166 & 1.78344 \tabularnewline
20 & 32 & 34.0297 & -2.02973 \tabularnewline
21 & 32 & 34.8056 & -2.80561 \tabularnewline
22 & 31 & 33.8774 & -2.87743 \tabularnewline
23 & 39 & 36.7013 & 2.29874 \tabularnewline
24 & 37 & 37.1789 & -0.178869 \tabularnewline
25 & 39 & 34.6118 & 4.38817 \tabularnewline
26 & 41 & 34.2664 & 6.73359 \tabularnewline
27 & 36 & 35.3473 & 0.652702 \tabularnewline
28 & 33 & 36.1595 & -3.15951 \tabularnewline
29 & 33 & 34.369 & -1.36896 \tabularnewline
30 & 34 & 34.7233 & -0.723295 \tabularnewline
31 & 31 & 33.9888 & -2.98881 \tabularnewline
32 & 27 & 33.5008 & -6.50081 \tabularnewline
33 & 37 & 33.7241 & 3.27591 \tabularnewline
34 & 34 & 36.9676 & -2.96758 \tabularnewline
35 & 34 & 32.7405 & 1.25953 \tabularnewline
36 & 32 & 34.501 & -2.50103 \tabularnewline
37 & 29 & 32.5376 & -3.5376 \tabularnewline
38 & 36 & 34.3588 & 1.64122 \tabularnewline
39 & 29 & 34.0427 & -5.04273 \tabularnewline
40 & 35 & 34.749 & 0.250956 \tabularnewline
41 & 37 & 34.4773 & 2.5227 \tabularnewline
42 & 34 & 34.1946 & -0.194641 \tabularnewline
43 & 38 & 34.3089 & 3.69111 \tabularnewline
44 & 35 & 33.9334 & 1.06663 \tabularnewline
45 & 38 & 32.36 & 5.64002 \tabularnewline
46 & 37 & 34.5937 & 2.40626 \tabularnewline
47 & 38 & 37.316 & 0.684039 \tabularnewline
48 & 33 & 35.1475 & -2.14755 \tabularnewline
49 & 36 & 36.4073 & -0.407331 \tabularnewline
50 & 38 & 33.976 & 4.02404 \tabularnewline
51 & 32 & 36.7707 & -4.77072 \tabularnewline
52 & 32 & 32.9496 & -0.94965 \tabularnewline
53 & 32 & 33.5478 & -1.54784 \tabularnewline
54 & 34 & 37.3901 & -3.39006 \tabularnewline
55 & 32 & 33.3767 & -1.37666 \tabularnewline
56 & 37 & 35.682 & 1.31797 \tabularnewline
57 & 39 & 35.0627 & 3.93734 \tabularnewline
58 & 29 & 35.2293 & -6.22933 \tabularnewline
59 & 37 & 35.7607 & 1.23933 \tabularnewline
60 & 35 & 35.0269 & -0.0268506 \tabularnewline
61 & 30 & 31.5151 & -1.51514 \tabularnewline
62 & 38 & 34.9115 & 3.08854 \tabularnewline
63 & 34 & 35.3996 & -1.39962 \tabularnewline
64 & 31 & 34.7544 & -3.7544 \tabularnewline
65 & 34 & 33.3898 & 0.6102 \tabularnewline
66 & 35 & 35.9941 & -0.994083 \tabularnewline
67 & 36 & 34.8577 & 1.14234 \tabularnewline
68 & 30 & 31.33 & -1.32997 \tabularnewline
69 & 39 & 36.3366 & 2.66343 \tabularnewline
70 & 35 & 35.6184 & -0.618421 \tabularnewline
71 & 38 & 35.127 & 2.87295 \tabularnewline
72 & 31 & 35.5704 & -4.5704 \tabularnewline
73 & 34 & 36.7055 & -2.70555 \tabularnewline
74 & 38 & 37.367 & 0.633012 \tabularnewline
75 & 34 & 31.5916 & 2.40844 \tabularnewline
76 & 39 & 32.9194 & 6.08056 \tabularnewline
77 & 37 & 35.6894 & 1.31061 \tabularnewline
78 & 34 & 33.1967 & 0.803301 \tabularnewline
79 & 28 & 32.9221 & -4.92214 \tabularnewline
80 & 37 & 31.2318 & 5.76821 \tabularnewline
81 & 33 & 35.2615 & -2.26147 \tabularnewline
82 & 35 & 36.078 & -1.07797 \tabularnewline
83 & 37 & 33.7911 & 3.20886 \tabularnewline
84 & 32 & 34.441 & -2.44096 \tabularnewline
85 & 33 & 33.3669 & -0.366867 \tabularnewline
86 & 38 & 36.5111 & 1.48895 \tabularnewline
87 & 33 & 34.403 & -1.40297 \tabularnewline
88 & 29 & 33.1288 & -4.12879 \tabularnewline
89 & 33 & 33.4369 & -0.436908 \tabularnewline
90 & 31 & 35.2471 & -4.24711 \tabularnewline
91 & 36 & 33.0636 & 2.93636 \tabularnewline
92 & 35 & 37.4299 & -2.42993 \tabularnewline
93 & 32 & 31.6207 & 0.379347 \tabularnewline
94 & 29 & 32.3324 & -3.33238 \tabularnewline
95 & 39 & 35.4576 & 3.5424 \tabularnewline
96 & 37 & 34.7048 & 2.29515 \tabularnewline
97 & 35 & 33.336 & 1.66398 \tabularnewline
98 & 37 & 34.5589 & 2.4411 \tabularnewline
99 & 32 & 35.3554 & -3.35545 \tabularnewline
100 & 38 & 35.2461 & 2.75385 \tabularnewline
101 & 37 & 34.8503 & 2.14966 \tabularnewline
102 & 36 & 36.3322 & -0.332156 \tabularnewline
103 & 32 & 31.9429 & 0.057148 \tabularnewline
104 & 33 & 36.5207 & -3.52067 \tabularnewline
105 & 40 & 32.796 & 7.20401 \tabularnewline
106 & 38 & 35.2349 & 2.76509 \tabularnewline
107 & 41 & 36.4073 & 4.59271 \tabularnewline
108 & 36 & 34.4416 & 1.55835 \tabularnewline
109 & 43 & 36.9251 & 6.07494 \tabularnewline
110 & 30 & 34.6791 & -4.67907 \tabularnewline
111 & 31 & 33.6722 & -2.67221 \tabularnewline
112 & 32 & 38.1554 & -6.15535 \tabularnewline
113 & 32 & 31.5071 & 0.492941 \tabularnewline
114 & 37 & 34.3428 & 2.65717 \tabularnewline
115 & 37 & 34.2299 & 2.77012 \tabularnewline
116 & 33 & 36.3291 & -3.3291 \tabularnewline
117 & 34 & 37.293 & -3.29297 \tabularnewline
118 & 33 & 34.6778 & -1.67775 \tabularnewline
119 & 38 & 35.5783 & 2.4217 \tabularnewline
120 & 33 & 34.9845 & -1.98445 \tabularnewline
121 & 31 & 31.3653 & -0.365299 \tabularnewline
122 & 38 & 36.6377 & 1.36226 \tabularnewline
123 & 37 & 36.4039 & 0.596086 \tabularnewline
124 & 36 & 33.1435 & 2.85652 \tabularnewline
125 & 31 & 33.8943 & -2.89427 \tabularnewline
126 & 39 & 34.1909 & 4.80906 \tabularnewline
127 & 44 & 36.8097 & 7.19029 \tabularnewline
128 & 33 & 36.1026 & -3.10261 \tabularnewline
129 & 35 & 33.6332 & 1.36681 \tabularnewline
130 & 32 & 34.0165 & -2.01648 \tabularnewline
131 & 28 & 32.4629 & -4.46289 \tabularnewline
132 & 40 & 36.0748 & 3.92524 \tabularnewline
133 & 27 & 32.1563 & -5.15628 \tabularnewline
134 & 37 & 36.1185 & 0.881512 \tabularnewline
135 & 32 & 32.5524 & -0.552361 \tabularnewline
136 & 28 & 28.326 & -0.326028 \tabularnewline
137 & 34 & 35.0144 & -1.0144 \tabularnewline
138 & 30 & 34.1476 & -4.14757 \tabularnewline
139 & 35 & 34.2683 & 0.731681 \tabularnewline
140 & 31 & 34.3164 & -3.31642 \tabularnewline
141 & 32 & 34.4525 & -2.45253 \tabularnewline
142 & 30 & 35.9757 & -5.97573 \tabularnewline
143 & 30 & 35.1811 & -5.18108 \tabularnewline
144 & 31 & 29.8084 & 1.19157 \tabularnewline
145 & 40 & 33.2359 & 6.76411 \tabularnewline
146 & 32 & 31.8148 & 0.185175 \tabularnewline
147 & 36 & 34.8477 & 1.15225 \tabularnewline
148 & 32 & 33.2953 & -1.29535 \tabularnewline
149 & 35 & 33.3066 & 1.69338 \tabularnewline
150 & 38 & 36.6587 & 1.3413 \tabularnewline
151 & 42 & 35.3682 & 6.6318 \tabularnewline
152 & 34 & 36.2171 & -2.21706 \tabularnewline
153 & 35 & 36.9611 & -1.96113 \tabularnewline
154 & 38 & 34.7747 & 3.22533 \tabularnewline
155 & 33 & 33.0182 & -0.0182108 \tabularnewline
156 & 36 & 33.0636 & 2.93636 \tabularnewline
157 & 32 & 35.7448 & -3.74478 \tabularnewline
158 & 33 & 36.1026 & -3.10261 \tabularnewline
159 & 34 & 33.9981 & 0.00188586 \tabularnewline
160 & 32 & 35.797 & -3.79703 \tabularnewline
161 & 34 & 35.4626 & -1.46256 \tabularnewline
162 & 27 & 29.9052 & -2.90517 \tabularnewline
163 & 31 & 30.0517 & 0.948332 \tabularnewline
164 & 38 & 33.342 & 4.65802 \tabularnewline
165 & 34 & 35.6368 & -1.6368 \tabularnewline
166 & 24 & 30.8947 & -6.89471 \tabularnewline
167 & 30 & 33.4635 & -3.46354 \tabularnewline
168 & 26 & 29.2636 & -3.26356 \tabularnewline
169 & 34 & 35.243 & -1.24302 \tabularnewline
170 & 27 & 34.4694 & -7.46935 \tabularnewline
171 & 37 & 31.9169 & 5.0831 \tabularnewline
172 & 36 & 35.2072 & 0.792754 \tabularnewline
173 & 41 & 33.9805 & 7.01946 \tabularnewline
174 & 29 & 28.9407 & 0.0592995 \tabularnewline
175 & 36 & 30.855 & 5.14502 \tabularnewline
176 & 32 & 34.0683 & -2.06826 \tabularnewline
177 & 37 & 33.1276 & 3.87243 \tabularnewline
178 & 30 & 31.4396 & -1.43965 \tabularnewline
179 & 31 & 32.5157 & -1.51568 \tabularnewline
180 & 38 & 34.4512 & 3.54876 \tabularnewline
181 & 36 & 34.4361 & 1.56385 \tabularnewline
182 & 35 & 31.9941 & 3.00595 \tabularnewline
183 & 31 & 35.0744 & -4.0744 \tabularnewline
184 & 38 & 33.0644 & 4.93564 \tabularnewline
185 & 22 & 30.902 & -8.902 \tabularnewline
186 & 32 & 34.2433 & -2.24329 \tabularnewline
187 & 36 & 33.7612 & 2.23877 \tabularnewline
188 & 39 & 32.6296 & 6.37037 \tabularnewline
189 & 28 & 30.2437 & -2.24366 \tabularnewline
190 & 32 & 34.188 & -2.18805 \tabularnewline
191 & 32 & 32.3115 & -0.311547 \tabularnewline
192 & 38 & 36.3955 & 1.6045 \tabularnewline
193 & 32 & 33.3589 & -1.35892 \tabularnewline
194 & 35 & 35.2171 & -0.217144 \tabularnewline
195 & 32 & 32.7494 & -0.749425 \tabularnewline
196 & 37 & 35.5854 & 1.41458 \tabularnewline
197 & 34 & 32.6065 & 1.39351 \tabularnewline
198 & 33 & 35.3421 & -2.34205 \tabularnewline
199 & 33 & 32.7586 & 0.241423 \tabularnewline
200 & 26 & 32.7222 & -6.72224 \tabularnewline
201 & 30 & 32.0789 & -2.07891 \tabularnewline
202 & 24 & 31.7671 & -7.7671 \tabularnewline
203 & 34 & 31.9024 & 2.09759 \tabularnewline
204 & 34 & 32.3744 & 1.62557 \tabularnewline
205 & 33 & 33.9551 & -0.955144 \tabularnewline
206 & 34 & 34.6861 & -0.68606 \tabularnewline
207 & 35 & 35.8707 & -0.870721 \tabularnewline
208 & 35 & 34.1598 & 0.840165 \tabularnewline
209 & 36 & 33.0374 & 2.96264 \tabularnewline
210 & 34 & 33.5784 & 0.421582 \tabularnewline
211 & 34 & 32.7027 & 1.29734 \tabularnewline
212 & 41 & 38.2419 & 2.75808 \tabularnewline
213 & 32 & 36.1091 & -4.10909 \tabularnewline
214 & 30 & 33.3054 & -3.30543 \tabularnewline
215 & 35 & 33.8736 & 1.12637 \tabularnewline
216 & 28 & 29.9127 & -1.91266 \tabularnewline
217 & 33 & 34.8409 & -1.84089 \tabularnewline
218 & 39 & 34.1651 & 4.8349 \tabularnewline
219 & 36 & 33.3727 & 2.6273 \tabularnewline
220 & 36 & 36.2857 & -0.285679 \tabularnewline
221 & 35 & 33.1253 & 1.8747 \tabularnewline
222 & 38 & 33.8589 & 4.14107 \tabularnewline
223 & 33 & 32.6764 & 0.323629 \tabularnewline
224 & 31 & 32.9028 & -1.90283 \tabularnewline
225 & 34 & 32.0238 & 1.97623 \tabularnewline
226 & 32 & 34.2373 & -2.23729 \tabularnewline
227 & 31 & 32.6692 & -1.66919 \tabularnewline
228 & 33 & 33.1093 & -0.109349 \tabularnewline
229 & 34 & 32.6419 & 1.35813 \tabularnewline
230 & 34 & 33.9665 & 0.0335138 \tabularnewline
231 & 34 & 32.1332 & 1.8668 \tabularnewline
232 & 33 & 35.1019 & -2.10194 \tabularnewline
233 & 32 & 34.1739 & -2.17392 \tabularnewline
234 & 41 & 33.5971 & 7.40293 \tabularnewline
235 & 34 & 32.9672 & 1.03278 \tabularnewline
236 & 36 & 32.0375 & 3.96254 \tabularnewline
237 & 37 & 31.4643 & 5.53568 \tabularnewline
238 & 36 & 30.3562 & 5.64385 \tabularnewline
239 & 29 & 32.4882 & -3.4882 \tabularnewline
240 & 37 & 31.7698 & 5.23019 \tabularnewline
241 & 27 & 33.1153 & -6.11534 \tabularnewline
242 & 35 & 33.3918 & 1.60823 \tabularnewline
243 & 28 & 30.6603 & -2.66029 \tabularnewline
244 & 35 & 33.1389 & 1.86106 \tabularnewline
245 & 37 & 33.0917 & 3.90826 \tabularnewline
246 & 29 & 33.6697 & -4.66974 \tabularnewline
247 & 32 & 34.2371 & -2.23713 \tabularnewline
248 & 36 & 31.7788 & 4.22118 \tabularnewline
249 & 19 & 27.6244 & -8.62441 \tabularnewline
250 & 21 & 26.765 & -5.76498 \tabularnewline
251 & 31 & 33.4269 & -2.42689 \tabularnewline
252 & 33 & 32.484 & 0.516008 \tabularnewline
253 & 36 & 33.8866 & 2.11339 \tabularnewline
254 & 33 & 33.2848 & -0.284831 \tabularnewline
255 & 37 & 33.1208 & 3.87917 \tabularnewline
256 & 34 & 33.3027 & 0.697347 \tabularnewline
257 & 35 & 34.4786 & 0.52145 \tabularnewline
258 & 31 & 32.8002 & -1.80023 \tabularnewline
259 & 37 & 33.4132 & 3.5868 \tabularnewline
260 & 35 & 31.8596 & 3.14037 \tabularnewline
261 & 27 & 31.8352 & -4.83523 \tabularnewline
262 & 34 & 34.916 & -0.915996 \tabularnewline
263 & 40 & 33.9308 & 6.06923 \tabularnewline
264 & 29 & 32.873 & -3.873 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221586&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]41[/C][C]36.019[/C][C]4.981[/C][/ROW]
[ROW][C]2[/C][C]39[/C][C]34.6092[/C][C]4.3908[/C][/ROW]
[ROW][C]3[/C][C]30[/C][C]35.6201[/C][C]-5.62005[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]34.7661[/C][C]-3.76606[/C][/ROW]
[ROW][C]5[/C][C]34[/C][C]35.7484[/C][C]-1.74836[/C][/ROW]
[ROW][C]6[/C][C]35[/C][C]32.7893[/C][C]2.21072[/C][/ROW]
[ROW][C]7[/C][C]39[/C][C]33.8758[/C][C]5.12419[/C][/ROW]
[ROW][C]8[/C][C]34[/C][C]35.9105[/C][C]-1.9105[/C][/ROW]
[ROW][C]9[/C][C]36[/C][C]35.3796[/C][C]0.620402[/C][/ROW]
[ROW][C]10[/C][C]37[/C][C]36.9659[/C][C]0.0340998[/C][/ROW]
[ROW][C]11[/C][C]38[/C][C]34.2425[/C][C]3.75746[/C][/ROW]
[ROW][C]12[/C][C]36[/C][C]34.928[/C][C]1.07204[/C][/ROW]
[ROW][C]13[/C][C]38[/C][C]35.3547[/C][C]2.64528[/C][/ROW]
[ROW][C]14[/C][C]39[/C][C]36.4218[/C][C]2.5782[/C][/ROW]
[ROW][C]15[/C][C]33[/C][C]36.6983[/C][C]-3.69828[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]34.2296[/C][C]-2.22962[/C][/ROW]
[ROW][C]17[/C][C]36[/C][C]34.094[/C][C]1.90604[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]37.6565[/C][C]0.343516[/C][/ROW]
[ROW][C]19[/C][C]39[/C][C]37.2166[/C][C]1.78344[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]34.0297[/C][C]-2.02973[/C][/ROW]
[ROW][C]21[/C][C]32[/C][C]34.8056[/C][C]-2.80561[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]33.8774[/C][C]-2.87743[/C][/ROW]
[ROW][C]23[/C][C]39[/C][C]36.7013[/C][C]2.29874[/C][/ROW]
[ROW][C]24[/C][C]37[/C][C]37.1789[/C][C]-0.178869[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]34.6118[/C][C]4.38817[/C][/ROW]
[ROW][C]26[/C][C]41[/C][C]34.2664[/C][C]6.73359[/C][/ROW]
[ROW][C]27[/C][C]36[/C][C]35.3473[/C][C]0.652702[/C][/ROW]
[ROW][C]28[/C][C]33[/C][C]36.1595[/C][C]-3.15951[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]34.369[/C][C]-1.36896[/C][/ROW]
[ROW][C]30[/C][C]34[/C][C]34.7233[/C][C]-0.723295[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]33.9888[/C][C]-2.98881[/C][/ROW]
[ROW][C]32[/C][C]27[/C][C]33.5008[/C][C]-6.50081[/C][/ROW]
[ROW][C]33[/C][C]37[/C][C]33.7241[/C][C]3.27591[/C][/ROW]
[ROW][C]34[/C][C]34[/C][C]36.9676[/C][C]-2.96758[/C][/ROW]
[ROW][C]35[/C][C]34[/C][C]32.7405[/C][C]1.25953[/C][/ROW]
[ROW][C]36[/C][C]32[/C][C]34.501[/C][C]-2.50103[/C][/ROW]
[ROW][C]37[/C][C]29[/C][C]32.5376[/C][C]-3.5376[/C][/ROW]
[ROW][C]38[/C][C]36[/C][C]34.3588[/C][C]1.64122[/C][/ROW]
[ROW][C]39[/C][C]29[/C][C]34.0427[/C][C]-5.04273[/C][/ROW]
[ROW][C]40[/C][C]35[/C][C]34.749[/C][C]0.250956[/C][/ROW]
[ROW][C]41[/C][C]37[/C][C]34.4773[/C][C]2.5227[/C][/ROW]
[ROW][C]42[/C][C]34[/C][C]34.1946[/C][C]-0.194641[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]34.3089[/C][C]3.69111[/C][/ROW]
[ROW][C]44[/C][C]35[/C][C]33.9334[/C][C]1.06663[/C][/ROW]
[ROW][C]45[/C][C]38[/C][C]32.36[/C][C]5.64002[/C][/ROW]
[ROW][C]46[/C][C]37[/C][C]34.5937[/C][C]2.40626[/C][/ROW]
[ROW][C]47[/C][C]38[/C][C]37.316[/C][C]0.684039[/C][/ROW]
[ROW][C]48[/C][C]33[/C][C]35.1475[/C][C]-2.14755[/C][/ROW]
[ROW][C]49[/C][C]36[/C][C]36.4073[/C][C]-0.407331[/C][/ROW]
[ROW][C]50[/C][C]38[/C][C]33.976[/C][C]4.02404[/C][/ROW]
[ROW][C]51[/C][C]32[/C][C]36.7707[/C][C]-4.77072[/C][/ROW]
[ROW][C]52[/C][C]32[/C][C]32.9496[/C][C]-0.94965[/C][/ROW]
[ROW][C]53[/C][C]32[/C][C]33.5478[/C][C]-1.54784[/C][/ROW]
[ROW][C]54[/C][C]34[/C][C]37.3901[/C][C]-3.39006[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]33.3767[/C][C]-1.37666[/C][/ROW]
[ROW][C]56[/C][C]37[/C][C]35.682[/C][C]1.31797[/C][/ROW]
[ROW][C]57[/C][C]39[/C][C]35.0627[/C][C]3.93734[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]35.2293[/C][C]-6.22933[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]35.7607[/C][C]1.23933[/C][/ROW]
[ROW][C]60[/C][C]35[/C][C]35.0269[/C][C]-0.0268506[/C][/ROW]
[ROW][C]61[/C][C]30[/C][C]31.5151[/C][C]-1.51514[/C][/ROW]
[ROW][C]62[/C][C]38[/C][C]34.9115[/C][C]3.08854[/C][/ROW]
[ROW][C]63[/C][C]34[/C][C]35.3996[/C][C]-1.39962[/C][/ROW]
[ROW][C]64[/C][C]31[/C][C]34.7544[/C][C]-3.7544[/C][/ROW]
[ROW][C]65[/C][C]34[/C][C]33.3898[/C][C]0.6102[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]35.9941[/C][C]-0.994083[/C][/ROW]
[ROW][C]67[/C][C]36[/C][C]34.8577[/C][C]1.14234[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]31.33[/C][C]-1.32997[/C][/ROW]
[ROW][C]69[/C][C]39[/C][C]36.3366[/C][C]2.66343[/C][/ROW]
[ROW][C]70[/C][C]35[/C][C]35.6184[/C][C]-0.618421[/C][/ROW]
[ROW][C]71[/C][C]38[/C][C]35.127[/C][C]2.87295[/C][/ROW]
[ROW][C]72[/C][C]31[/C][C]35.5704[/C][C]-4.5704[/C][/ROW]
[ROW][C]73[/C][C]34[/C][C]36.7055[/C][C]-2.70555[/C][/ROW]
[ROW][C]74[/C][C]38[/C][C]37.367[/C][C]0.633012[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]31.5916[/C][C]2.40844[/C][/ROW]
[ROW][C]76[/C][C]39[/C][C]32.9194[/C][C]6.08056[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.6894[/C][C]1.31061[/C][/ROW]
[ROW][C]78[/C][C]34[/C][C]33.1967[/C][C]0.803301[/C][/ROW]
[ROW][C]79[/C][C]28[/C][C]32.9221[/C][C]-4.92214[/C][/ROW]
[ROW][C]80[/C][C]37[/C][C]31.2318[/C][C]5.76821[/C][/ROW]
[ROW][C]81[/C][C]33[/C][C]35.2615[/C][C]-2.26147[/C][/ROW]
[ROW][C]82[/C][C]35[/C][C]36.078[/C][C]-1.07797[/C][/ROW]
[ROW][C]83[/C][C]37[/C][C]33.7911[/C][C]3.20886[/C][/ROW]
[ROW][C]84[/C][C]32[/C][C]34.441[/C][C]-2.44096[/C][/ROW]
[ROW][C]85[/C][C]33[/C][C]33.3669[/C][C]-0.366867[/C][/ROW]
[ROW][C]86[/C][C]38[/C][C]36.5111[/C][C]1.48895[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]34.403[/C][C]-1.40297[/C][/ROW]
[ROW][C]88[/C][C]29[/C][C]33.1288[/C][C]-4.12879[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.4369[/C][C]-0.436908[/C][/ROW]
[ROW][C]90[/C][C]31[/C][C]35.2471[/C][C]-4.24711[/C][/ROW]
[ROW][C]91[/C][C]36[/C][C]33.0636[/C][C]2.93636[/C][/ROW]
[ROW][C]92[/C][C]35[/C][C]37.4299[/C][C]-2.42993[/C][/ROW]
[ROW][C]93[/C][C]32[/C][C]31.6207[/C][C]0.379347[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]32.3324[/C][C]-3.33238[/C][/ROW]
[ROW][C]95[/C][C]39[/C][C]35.4576[/C][C]3.5424[/C][/ROW]
[ROW][C]96[/C][C]37[/C][C]34.7048[/C][C]2.29515[/C][/ROW]
[ROW][C]97[/C][C]35[/C][C]33.336[/C][C]1.66398[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]34.5589[/C][C]2.4411[/C][/ROW]
[ROW][C]99[/C][C]32[/C][C]35.3554[/C][C]-3.35545[/C][/ROW]
[ROW][C]100[/C][C]38[/C][C]35.2461[/C][C]2.75385[/C][/ROW]
[ROW][C]101[/C][C]37[/C][C]34.8503[/C][C]2.14966[/C][/ROW]
[ROW][C]102[/C][C]36[/C][C]36.3322[/C][C]-0.332156[/C][/ROW]
[ROW][C]103[/C][C]32[/C][C]31.9429[/C][C]0.057148[/C][/ROW]
[ROW][C]104[/C][C]33[/C][C]36.5207[/C][C]-3.52067[/C][/ROW]
[ROW][C]105[/C][C]40[/C][C]32.796[/C][C]7.20401[/C][/ROW]
[ROW][C]106[/C][C]38[/C][C]35.2349[/C][C]2.76509[/C][/ROW]
[ROW][C]107[/C][C]41[/C][C]36.4073[/C][C]4.59271[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]34.4416[/C][C]1.55835[/C][/ROW]
[ROW][C]109[/C][C]43[/C][C]36.9251[/C][C]6.07494[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]34.6791[/C][C]-4.67907[/C][/ROW]
[ROW][C]111[/C][C]31[/C][C]33.6722[/C][C]-2.67221[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]38.1554[/C][C]-6.15535[/C][/ROW]
[ROW][C]113[/C][C]32[/C][C]31.5071[/C][C]0.492941[/C][/ROW]
[ROW][C]114[/C][C]37[/C][C]34.3428[/C][C]2.65717[/C][/ROW]
[ROW][C]115[/C][C]37[/C][C]34.2299[/C][C]2.77012[/C][/ROW]
[ROW][C]116[/C][C]33[/C][C]36.3291[/C][C]-3.3291[/C][/ROW]
[ROW][C]117[/C][C]34[/C][C]37.293[/C][C]-3.29297[/C][/ROW]
[ROW][C]118[/C][C]33[/C][C]34.6778[/C][C]-1.67775[/C][/ROW]
[ROW][C]119[/C][C]38[/C][C]35.5783[/C][C]2.4217[/C][/ROW]
[ROW][C]120[/C][C]33[/C][C]34.9845[/C][C]-1.98445[/C][/ROW]
[ROW][C]121[/C][C]31[/C][C]31.3653[/C][C]-0.365299[/C][/ROW]
[ROW][C]122[/C][C]38[/C][C]36.6377[/C][C]1.36226[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]36.4039[/C][C]0.596086[/C][/ROW]
[ROW][C]124[/C][C]36[/C][C]33.1435[/C][C]2.85652[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]33.8943[/C][C]-2.89427[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]34.1909[/C][C]4.80906[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]36.8097[/C][C]7.19029[/C][/ROW]
[ROW][C]128[/C][C]33[/C][C]36.1026[/C][C]-3.10261[/C][/ROW]
[ROW][C]129[/C][C]35[/C][C]33.6332[/C][C]1.36681[/C][/ROW]
[ROW][C]130[/C][C]32[/C][C]34.0165[/C][C]-2.01648[/C][/ROW]
[ROW][C]131[/C][C]28[/C][C]32.4629[/C][C]-4.46289[/C][/ROW]
[ROW][C]132[/C][C]40[/C][C]36.0748[/C][C]3.92524[/C][/ROW]
[ROW][C]133[/C][C]27[/C][C]32.1563[/C][C]-5.15628[/C][/ROW]
[ROW][C]134[/C][C]37[/C][C]36.1185[/C][C]0.881512[/C][/ROW]
[ROW][C]135[/C][C]32[/C][C]32.5524[/C][C]-0.552361[/C][/ROW]
[ROW][C]136[/C][C]28[/C][C]28.326[/C][C]-0.326028[/C][/ROW]
[ROW][C]137[/C][C]34[/C][C]35.0144[/C][C]-1.0144[/C][/ROW]
[ROW][C]138[/C][C]30[/C][C]34.1476[/C][C]-4.14757[/C][/ROW]
[ROW][C]139[/C][C]35[/C][C]34.2683[/C][C]0.731681[/C][/ROW]
[ROW][C]140[/C][C]31[/C][C]34.3164[/C][C]-3.31642[/C][/ROW]
[ROW][C]141[/C][C]32[/C][C]34.4525[/C][C]-2.45253[/C][/ROW]
[ROW][C]142[/C][C]30[/C][C]35.9757[/C][C]-5.97573[/C][/ROW]
[ROW][C]143[/C][C]30[/C][C]35.1811[/C][C]-5.18108[/C][/ROW]
[ROW][C]144[/C][C]31[/C][C]29.8084[/C][C]1.19157[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]33.2359[/C][C]6.76411[/C][/ROW]
[ROW][C]146[/C][C]32[/C][C]31.8148[/C][C]0.185175[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]34.8477[/C][C]1.15225[/C][/ROW]
[ROW][C]148[/C][C]32[/C][C]33.2953[/C][C]-1.29535[/C][/ROW]
[ROW][C]149[/C][C]35[/C][C]33.3066[/C][C]1.69338[/C][/ROW]
[ROW][C]150[/C][C]38[/C][C]36.6587[/C][C]1.3413[/C][/ROW]
[ROW][C]151[/C][C]42[/C][C]35.3682[/C][C]6.6318[/C][/ROW]
[ROW][C]152[/C][C]34[/C][C]36.2171[/C][C]-2.21706[/C][/ROW]
[ROW][C]153[/C][C]35[/C][C]36.9611[/C][C]-1.96113[/C][/ROW]
[ROW][C]154[/C][C]38[/C][C]34.7747[/C][C]3.22533[/C][/ROW]
[ROW][C]155[/C][C]33[/C][C]33.0182[/C][C]-0.0182108[/C][/ROW]
[ROW][C]156[/C][C]36[/C][C]33.0636[/C][C]2.93636[/C][/ROW]
[ROW][C]157[/C][C]32[/C][C]35.7448[/C][C]-3.74478[/C][/ROW]
[ROW][C]158[/C][C]33[/C][C]36.1026[/C][C]-3.10261[/C][/ROW]
[ROW][C]159[/C][C]34[/C][C]33.9981[/C][C]0.00188586[/C][/ROW]
[ROW][C]160[/C][C]32[/C][C]35.797[/C][C]-3.79703[/C][/ROW]
[ROW][C]161[/C][C]34[/C][C]35.4626[/C][C]-1.46256[/C][/ROW]
[ROW][C]162[/C][C]27[/C][C]29.9052[/C][C]-2.90517[/C][/ROW]
[ROW][C]163[/C][C]31[/C][C]30.0517[/C][C]0.948332[/C][/ROW]
[ROW][C]164[/C][C]38[/C][C]33.342[/C][C]4.65802[/C][/ROW]
[ROW][C]165[/C][C]34[/C][C]35.6368[/C][C]-1.6368[/C][/ROW]
[ROW][C]166[/C][C]24[/C][C]30.8947[/C][C]-6.89471[/C][/ROW]
[ROW][C]167[/C][C]30[/C][C]33.4635[/C][C]-3.46354[/C][/ROW]
[ROW][C]168[/C][C]26[/C][C]29.2636[/C][C]-3.26356[/C][/ROW]
[ROW][C]169[/C][C]34[/C][C]35.243[/C][C]-1.24302[/C][/ROW]
[ROW][C]170[/C][C]27[/C][C]34.4694[/C][C]-7.46935[/C][/ROW]
[ROW][C]171[/C][C]37[/C][C]31.9169[/C][C]5.0831[/C][/ROW]
[ROW][C]172[/C][C]36[/C][C]35.2072[/C][C]0.792754[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]33.9805[/C][C]7.01946[/C][/ROW]
[ROW][C]174[/C][C]29[/C][C]28.9407[/C][C]0.0592995[/C][/ROW]
[ROW][C]175[/C][C]36[/C][C]30.855[/C][C]5.14502[/C][/ROW]
[ROW][C]176[/C][C]32[/C][C]34.0683[/C][C]-2.06826[/C][/ROW]
[ROW][C]177[/C][C]37[/C][C]33.1276[/C][C]3.87243[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.4396[/C][C]-1.43965[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]32.5157[/C][C]-1.51568[/C][/ROW]
[ROW][C]180[/C][C]38[/C][C]34.4512[/C][C]3.54876[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]34.4361[/C][C]1.56385[/C][/ROW]
[ROW][C]182[/C][C]35[/C][C]31.9941[/C][C]3.00595[/C][/ROW]
[ROW][C]183[/C][C]31[/C][C]35.0744[/C][C]-4.0744[/C][/ROW]
[ROW][C]184[/C][C]38[/C][C]33.0644[/C][C]4.93564[/C][/ROW]
[ROW][C]185[/C][C]22[/C][C]30.902[/C][C]-8.902[/C][/ROW]
[ROW][C]186[/C][C]32[/C][C]34.2433[/C][C]-2.24329[/C][/ROW]
[ROW][C]187[/C][C]36[/C][C]33.7612[/C][C]2.23877[/C][/ROW]
[ROW][C]188[/C][C]39[/C][C]32.6296[/C][C]6.37037[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.2437[/C][C]-2.24366[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]34.188[/C][C]-2.18805[/C][/ROW]
[ROW][C]191[/C][C]32[/C][C]32.3115[/C][C]-0.311547[/C][/ROW]
[ROW][C]192[/C][C]38[/C][C]36.3955[/C][C]1.6045[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]33.3589[/C][C]-1.35892[/C][/ROW]
[ROW][C]194[/C][C]35[/C][C]35.2171[/C][C]-0.217144[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]32.7494[/C][C]-0.749425[/C][/ROW]
[ROW][C]196[/C][C]37[/C][C]35.5854[/C][C]1.41458[/C][/ROW]
[ROW][C]197[/C][C]34[/C][C]32.6065[/C][C]1.39351[/C][/ROW]
[ROW][C]198[/C][C]33[/C][C]35.3421[/C][C]-2.34205[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]32.7586[/C][C]0.241423[/C][/ROW]
[ROW][C]200[/C][C]26[/C][C]32.7222[/C][C]-6.72224[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]32.0789[/C][C]-2.07891[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]31.7671[/C][C]-7.7671[/C][/ROW]
[ROW][C]203[/C][C]34[/C][C]31.9024[/C][C]2.09759[/C][/ROW]
[ROW][C]204[/C][C]34[/C][C]32.3744[/C][C]1.62557[/C][/ROW]
[ROW][C]205[/C][C]33[/C][C]33.9551[/C][C]-0.955144[/C][/ROW]
[ROW][C]206[/C][C]34[/C][C]34.6861[/C][C]-0.68606[/C][/ROW]
[ROW][C]207[/C][C]35[/C][C]35.8707[/C][C]-0.870721[/C][/ROW]
[ROW][C]208[/C][C]35[/C][C]34.1598[/C][C]0.840165[/C][/ROW]
[ROW][C]209[/C][C]36[/C][C]33.0374[/C][C]2.96264[/C][/ROW]
[ROW][C]210[/C][C]34[/C][C]33.5784[/C][C]0.421582[/C][/ROW]
[ROW][C]211[/C][C]34[/C][C]32.7027[/C][C]1.29734[/C][/ROW]
[ROW][C]212[/C][C]41[/C][C]38.2419[/C][C]2.75808[/C][/ROW]
[ROW][C]213[/C][C]32[/C][C]36.1091[/C][C]-4.10909[/C][/ROW]
[ROW][C]214[/C][C]30[/C][C]33.3054[/C][C]-3.30543[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]33.8736[/C][C]1.12637[/C][/ROW]
[ROW][C]216[/C][C]28[/C][C]29.9127[/C][C]-1.91266[/C][/ROW]
[ROW][C]217[/C][C]33[/C][C]34.8409[/C][C]-1.84089[/C][/ROW]
[ROW][C]218[/C][C]39[/C][C]34.1651[/C][C]4.8349[/C][/ROW]
[ROW][C]219[/C][C]36[/C][C]33.3727[/C][C]2.6273[/C][/ROW]
[ROW][C]220[/C][C]36[/C][C]36.2857[/C][C]-0.285679[/C][/ROW]
[ROW][C]221[/C][C]35[/C][C]33.1253[/C][C]1.8747[/C][/ROW]
[ROW][C]222[/C][C]38[/C][C]33.8589[/C][C]4.14107[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]32.6764[/C][C]0.323629[/C][/ROW]
[ROW][C]224[/C][C]31[/C][C]32.9028[/C][C]-1.90283[/C][/ROW]
[ROW][C]225[/C][C]34[/C][C]32.0238[/C][C]1.97623[/C][/ROW]
[ROW][C]226[/C][C]32[/C][C]34.2373[/C][C]-2.23729[/C][/ROW]
[ROW][C]227[/C][C]31[/C][C]32.6692[/C][C]-1.66919[/C][/ROW]
[ROW][C]228[/C][C]33[/C][C]33.1093[/C][C]-0.109349[/C][/ROW]
[ROW][C]229[/C][C]34[/C][C]32.6419[/C][C]1.35813[/C][/ROW]
[ROW][C]230[/C][C]34[/C][C]33.9665[/C][C]0.0335138[/C][/ROW]
[ROW][C]231[/C][C]34[/C][C]32.1332[/C][C]1.8668[/C][/ROW]
[ROW][C]232[/C][C]33[/C][C]35.1019[/C][C]-2.10194[/C][/ROW]
[ROW][C]233[/C][C]32[/C][C]34.1739[/C][C]-2.17392[/C][/ROW]
[ROW][C]234[/C][C]41[/C][C]33.5971[/C][C]7.40293[/C][/ROW]
[ROW][C]235[/C][C]34[/C][C]32.9672[/C][C]1.03278[/C][/ROW]
[ROW][C]236[/C][C]36[/C][C]32.0375[/C][C]3.96254[/C][/ROW]
[ROW][C]237[/C][C]37[/C][C]31.4643[/C][C]5.53568[/C][/ROW]
[ROW][C]238[/C][C]36[/C][C]30.3562[/C][C]5.64385[/C][/ROW]
[ROW][C]239[/C][C]29[/C][C]32.4882[/C][C]-3.4882[/C][/ROW]
[ROW][C]240[/C][C]37[/C][C]31.7698[/C][C]5.23019[/C][/ROW]
[ROW][C]241[/C][C]27[/C][C]33.1153[/C][C]-6.11534[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.3918[/C][C]1.60823[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]30.6603[/C][C]-2.66029[/C][/ROW]
[ROW][C]244[/C][C]35[/C][C]33.1389[/C][C]1.86106[/C][/ROW]
[ROW][C]245[/C][C]37[/C][C]33.0917[/C][C]3.90826[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]33.6697[/C][C]-4.66974[/C][/ROW]
[ROW][C]247[/C][C]32[/C][C]34.2371[/C][C]-2.23713[/C][/ROW]
[ROW][C]248[/C][C]36[/C][C]31.7788[/C][C]4.22118[/C][/ROW]
[ROW][C]249[/C][C]19[/C][C]27.6244[/C][C]-8.62441[/C][/ROW]
[ROW][C]250[/C][C]21[/C][C]26.765[/C][C]-5.76498[/C][/ROW]
[ROW][C]251[/C][C]31[/C][C]33.4269[/C][C]-2.42689[/C][/ROW]
[ROW][C]252[/C][C]33[/C][C]32.484[/C][C]0.516008[/C][/ROW]
[ROW][C]253[/C][C]36[/C][C]33.8866[/C][C]2.11339[/C][/ROW]
[ROW][C]254[/C][C]33[/C][C]33.2848[/C][C]-0.284831[/C][/ROW]
[ROW][C]255[/C][C]37[/C][C]33.1208[/C][C]3.87917[/C][/ROW]
[ROW][C]256[/C][C]34[/C][C]33.3027[/C][C]0.697347[/C][/ROW]
[ROW][C]257[/C][C]35[/C][C]34.4786[/C][C]0.52145[/C][/ROW]
[ROW][C]258[/C][C]31[/C][C]32.8002[/C][C]-1.80023[/C][/ROW]
[ROW][C]259[/C][C]37[/C][C]33.4132[/C][C]3.5868[/C][/ROW]
[ROW][C]260[/C][C]35[/C][C]31.8596[/C][C]3.14037[/C][/ROW]
[ROW][C]261[/C][C]27[/C][C]31.8352[/C][C]-4.83523[/C][/ROW]
[ROW][C]262[/C][C]34[/C][C]34.916[/C][C]-0.915996[/C][/ROW]
[ROW][C]263[/C][C]40[/C][C]33.9308[/C][C]6.06923[/C][/ROW]
[ROW][C]264[/C][C]29[/C][C]32.873[/C][C]-3.873[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221586&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221586&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14136.0194.981
23934.60924.3908
33035.6201-5.62005
43134.7661-3.76606
53435.7484-1.74836
63532.78932.21072
73933.87585.12419
83435.9105-1.9105
93635.37960.620402
103736.96590.0340998
113834.24253.75746
123634.9281.07204
133835.35472.64528
143936.42182.5782
153336.6983-3.69828
163234.2296-2.22962
173634.0941.90604
183837.65650.343516
193937.21661.78344
203234.0297-2.02973
213234.8056-2.80561
223133.8774-2.87743
233936.70132.29874
243737.1789-0.178869
253934.61184.38817
264134.26646.73359
273635.34730.652702
283336.1595-3.15951
293334.369-1.36896
303434.7233-0.723295
313133.9888-2.98881
322733.5008-6.50081
333733.72413.27591
343436.9676-2.96758
353432.74051.25953
363234.501-2.50103
372932.5376-3.5376
383634.35881.64122
392934.0427-5.04273
403534.7490.250956
413734.47732.5227
423434.1946-0.194641
433834.30893.69111
443533.93341.06663
453832.365.64002
463734.59372.40626
473837.3160.684039
483335.1475-2.14755
493636.4073-0.407331
503833.9764.02404
513236.7707-4.77072
523232.9496-0.94965
533233.5478-1.54784
543437.3901-3.39006
553233.3767-1.37666
563735.6821.31797
573935.06273.93734
582935.2293-6.22933
593735.76071.23933
603535.0269-0.0268506
613031.5151-1.51514
623834.91153.08854
633435.3996-1.39962
643134.7544-3.7544
653433.38980.6102
663535.9941-0.994083
673634.85771.14234
683031.33-1.32997
693936.33662.66343
703535.6184-0.618421
713835.1272.87295
723135.5704-4.5704
733436.7055-2.70555
743837.3670.633012
753431.59162.40844
763932.91946.08056
773735.68941.31061
783433.19670.803301
792832.9221-4.92214
803731.23185.76821
813335.2615-2.26147
823536.078-1.07797
833733.79113.20886
843234.441-2.44096
853333.3669-0.366867
863836.51111.48895
873334.403-1.40297
882933.1288-4.12879
893333.4369-0.436908
903135.2471-4.24711
913633.06362.93636
923537.4299-2.42993
933231.62070.379347
942932.3324-3.33238
953935.45763.5424
963734.70482.29515
973533.3361.66398
983734.55892.4411
993235.3554-3.35545
1003835.24612.75385
1013734.85032.14966
1023636.3322-0.332156
1033231.94290.057148
1043336.5207-3.52067
1054032.7967.20401
1063835.23492.76509
1074136.40734.59271
1083634.44161.55835
1094336.92516.07494
1103034.6791-4.67907
1113133.6722-2.67221
1123238.1554-6.15535
1133231.50710.492941
1143734.34282.65717
1153734.22992.77012
1163336.3291-3.3291
1173437.293-3.29297
1183334.6778-1.67775
1193835.57832.4217
1203334.9845-1.98445
1213131.3653-0.365299
1223836.63771.36226
1233736.40390.596086
1243633.14352.85652
1253133.8943-2.89427
1263934.19094.80906
1274436.80977.19029
1283336.1026-3.10261
1293533.63321.36681
1303234.0165-2.01648
1312832.4629-4.46289
1324036.07483.92524
1332732.1563-5.15628
1343736.11850.881512
1353232.5524-0.552361
1362828.326-0.326028
1373435.0144-1.0144
1383034.1476-4.14757
1393534.26830.731681
1403134.3164-3.31642
1413234.4525-2.45253
1423035.9757-5.97573
1433035.1811-5.18108
1443129.80841.19157
1454033.23596.76411
1463231.81480.185175
1473634.84771.15225
1483233.2953-1.29535
1493533.30661.69338
1503836.65871.3413
1514235.36826.6318
1523436.2171-2.21706
1533536.9611-1.96113
1543834.77473.22533
1553333.0182-0.0182108
1563633.06362.93636
1573235.7448-3.74478
1583336.1026-3.10261
1593433.99810.00188586
1603235.797-3.79703
1613435.4626-1.46256
1622729.9052-2.90517
1633130.05170.948332
1643833.3424.65802
1653435.6368-1.6368
1662430.8947-6.89471
1673033.4635-3.46354
1682629.2636-3.26356
1693435.243-1.24302
1702734.4694-7.46935
1713731.91695.0831
1723635.20720.792754
1734133.98057.01946
1742928.94070.0592995
1753630.8555.14502
1763234.0683-2.06826
1773733.12763.87243
1783031.4396-1.43965
1793132.5157-1.51568
1803834.45123.54876
1813634.43611.56385
1823531.99413.00595
1833135.0744-4.0744
1843833.06444.93564
1852230.902-8.902
1863234.2433-2.24329
1873633.76122.23877
1883932.62966.37037
1892830.2437-2.24366
1903234.188-2.18805
1913232.3115-0.311547
1923836.39551.6045
1933233.3589-1.35892
1943535.2171-0.217144
1953232.7494-0.749425
1963735.58541.41458
1973432.60651.39351
1983335.3421-2.34205
1993332.75860.241423
2002632.7222-6.72224
2013032.0789-2.07891
2022431.7671-7.7671
2033431.90242.09759
2043432.37441.62557
2053333.9551-0.955144
2063434.6861-0.68606
2073535.8707-0.870721
2083534.15980.840165
2093633.03742.96264
2103433.57840.421582
2113432.70271.29734
2124138.24192.75808
2133236.1091-4.10909
2143033.3054-3.30543
2153533.87361.12637
2162829.9127-1.91266
2173334.8409-1.84089
2183934.16514.8349
2193633.37272.6273
2203636.2857-0.285679
2213533.12531.8747
2223833.85894.14107
2233332.67640.323629
2243132.9028-1.90283
2253432.02381.97623
2263234.2373-2.23729
2273132.6692-1.66919
2283333.1093-0.109349
2293432.64191.35813
2303433.96650.0335138
2313432.13321.8668
2323335.1019-2.10194
2333234.1739-2.17392
2344133.59717.40293
2353432.96721.03278
2363632.03753.96254
2373731.46435.53568
2383630.35625.64385
2392932.4882-3.4882
2403731.76985.23019
2412733.1153-6.11534
2423533.39181.60823
2432830.6603-2.66029
2443533.13891.86106
2453733.09173.90826
2462933.6697-4.66974
2473234.2371-2.23713
2483631.77884.22118
2491927.6244-8.62441
2502126.765-5.76498
2513133.4269-2.42689
2523332.4840.516008
2533633.88662.11339
2543333.2848-0.284831
2553733.12083.87917
2563433.30270.697347
2573534.47860.52145
2583132.8002-1.80023
2593733.41323.5868
2603531.85963.14037
2612731.8352-4.83523
2623434.916-0.915996
2634033.93086.06923
2642932.873-3.873






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.5599360.8801270.440064
130.6962150.607570.303785
140.6798830.6402340.320117
150.5781690.8436630.421831
160.6040.7920.396
170.6603010.6793980.339699
180.6561080.6877830.343892
190.5679010.8641980.432099
200.5947040.8105930.405296
210.6511470.6977070.348853
220.6206130.7587740.379387
230.6062190.7875630.393781
240.5390470.9219070.460953
250.5879870.8240270.412013
260.7464170.5071660.253583
270.7194550.5610890.280545
280.6763360.6473280.323664
290.6663930.6672140.333607
300.6055120.7889750.394488
310.5962610.8074790.403739
320.7363060.5273870.263694
330.7236280.5527440.276372
340.6861010.6277970.313899
350.6330960.7338090.366904
360.5812080.8375840.418792
370.5416670.9166660.458333
380.504970.990060.49503
390.6222530.7554940.377747
400.5694160.8611680.430584
410.5331340.9337330.466866
420.4796320.9592650.520368
430.4377980.8755960.562202
440.389840.7796810.61016
450.457760.9155210.54224
460.464530.9290610.53547
470.4339980.8679960.566002
480.4039170.8078340.596083
490.3577970.7155930.642203
500.3665790.7331570.633421
510.4142380.8284760.585762
520.3779330.7558650.622067
530.3378820.6757640.662118
540.3044280.6088560.695572
550.2667370.5334730.733263
560.2508040.5016080.749196
570.2621210.5242420.737879
580.3787590.7575190.621241
590.3403150.680630.659685
600.2999240.5998490.700076
610.27030.54060.7297
620.2526610.5053220.747339
630.2264680.4529350.773532
640.2344420.4688830.765558
650.2023770.4047530.797623
660.1734230.3468460.826577
670.1518540.3037080.848146
680.1529270.3058540.847073
690.1687860.3375710.831214
700.1442680.2885370.855732
710.1537760.3075520.846224
720.1793760.3587530.820624
730.1709890.3419770.829011
740.1465060.2930120.853494
750.1296240.2592480.870376
760.1723590.3447180.827641
770.1497620.2995250.850238
780.127620.2552410.87238
790.1614370.3228730.838563
800.186880.3737590.81312
810.1777020.3554040.822298
820.1553430.3106850.844657
830.148360.2967190.85164
840.1409650.281930.859035
850.12260.24520.8774
860.1099720.2199440.890028
870.09719150.1943830.902808
880.1124910.2249810.887509
890.09494320.1898860.905057
900.09836090.1967220.901639
910.09254940.1850990.907451
920.08256180.1651240.917438
930.06933460.1386690.930665
940.06939320.1387860.930607
950.07057110.1411420.929429
960.06584170.1316830.934158
970.05633770.1126750.943662
980.05074540.1014910.949255
990.04974530.09949060.950255
1000.04669150.0933830.953308
1010.04204350.08408710.957956
1020.03484680.06969350.965153
1030.0283930.0567860.971607
1040.02828830.05657670.971712
1050.06559610.1311920.934404
1060.06173340.1234670.938267
1070.07556480.151130.924435
1080.06535350.1307070.934646
1090.1036750.2073510.896325
1100.1205590.2411190.879441
1110.1157180.2314370.884282
1120.1521360.3042720.847864
1130.1406870.2813740.859313
1140.1365760.2731520.863424
1150.1301640.2603290.869836
1160.1276740.2553480.872326
1170.1245220.2490450.875478
1180.1097750.2195510.890225
1190.1035850.2071690.896415
1200.09300710.1860140.906993
1210.08114920.1622980.918851
1220.07415340.1483070.925847
1230.06344730.1268950.936553
1240.0605520.1211040.939448
1250.0572220.1144440.942778
1260.07054880.1410980.929451
1270.1268050.2536110.873195
1280.124070.248140.87593
1290.1104340.2208690.889566
1300.1017260.2034520.898274
1310.1104510.2209020.889549
1320.1180640.2361280.881936
1330.1421170.2842330.857883
1340.1255070.2510140.874493
1350.1084410.2168810.891559
1360.0943060.1886120.905694
1370.0809990.1619980.919001
1380.08946780.1789360.910532
1390.07648440.1529690.923516
1400.07638980.152780.92361
1410.07402650.1480530.925974
1420.1058330.2116650.894167
1430.1316450.2632890.868355
1440.1194580.2389150.880542
1450.1953360.3906710.804664
1460.1763420.3526850.823658
1470.1591760.3183520.840824
1480.1407470.2814940.859253
1490.1273090.2546170.872691
1500.1130940.2261870.886906
1510.1783720.3567450.821628
1520.1654580.3309160.834542
1530.1509350.301870.849065
1540.1651590.3303190.834841
1550.1451710.2903410.854829
1560.1593640.3187280.840636
1570.1531080.3062160.846892
1580.1408950.2817890.859105
1590.1358330.2716660.864167
1600.1261580.2523160.873842
1610.1082250.2164490.891775
1620.1004190.2008380.899581
1630.09209180.1841840.907908
1640.1213840.2427670.878616
1650.1088580.2177150.891142
1660.1806910.3613820.819309
1670.1760030.3520060.823997
1680.1620790.3241580.837921
1690.1453340.2906680.854666
1700.2353860.4707730.764614
1710.2780920.5561840.721908
1720.2492720.4985450.750728
1730.362280.724560.63772
1740.327680.6553590.67232
1750.3998090.7996170.600191
1760.3721270.7442530.627873
1770.3783520.7567050.621648
1780.3456160.6912320.654384
1790.315210.6304210.68479
1800.3140350.6280690.685965
1810.2836170.5672350.716383
1820.279780.5595590.72022
1830.2949510.5899010.705049
1840.3648640.7297280.635136
1850.6022120.7955760.397788
1860.5822550.835490.417745
1870.578770.842460.42123
1880.7288820.5422360.271118
1890.7054590.5890810.294541
1900.7098960.5802080.290104
1910.6744060.6511870.325594
1920.6451650.709670.354835
1930.6105960.7788080.389404
1940.576550.8468990.42345
1950.5367480.9265040.463252
1960.4985760.9971520.501424
1970.4913130.9826260.508687
1980.462490.924980.53751
1990.4209910.8419820.579009
2000.4926050.9852090.507395
2010.458080.916160.54192
2020.6074750.7850510.392525
2030.5877060.8245880.412294
2040.5516710.8966580.448329
2050.5086210.9827580.491379
2060.4670590.9341170.532941
2070.4266590.8533190.573341
2080.384610.769220.61539
2090.3593960.7187910.640604
2100.3271420.6542830.672858
2110.2908130.5816260.709187
2120.2653780.5307550.734622
2130.3133060.6266130.686694
2140.2910870.5821750.708913
2150.2527960.5055920.747204
2160.21830.43660.7817
2170.1900030.3800060.809997
2180.2203130.4406260.779687
2190.1965620.3931240.803438
2200.1769670.3539330.823033
2210.1514040.3028080.848596
2220.1644350.328870.835565
2230.1343870.2687740.865613
2240.1133190.2266390.886681
2250.1699860.3399720.830014
2260.1544230.3088450.845577
2270.1338560.2677120.866144
2280.1413790.2827580.858621
2290.1137460.2274920.886254
2300.08879970.1775990.9112
2310.08843340.1768670.911567
2320.2094660.4189310.790534
2330.1715250.343050.828475
2340.2814280.5628550.718572
2350.2361750.472350.763825
2360.2406180.4812360.759382
2370.2065070.4130150.793493
2380.2884680.5769350.711532
2390.2370710.4741420.762929
2400.396220.792440.60378
2410.4648060.9296120.535194
2420.3872040.7744080.612796
2430.3142850.628570.685715
2440.301190.602380.69881
2450.323090.646180.67691
2460.5342080.9315840.465792
2470.5266320.9467350.473368
2480.4576510.9153020.542349
2490.6720790.6558420.327921
2500.6007710.7984570.399229
2510.561180.877640.43882
2520.6634790.6730420.336521

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.559936 & 0.880127 & 0.440064 \tabularnewline
13 & 0.696215 & 0.60757 & 0.303785 \tabularnewline
14 & 0.679883 & 0.640234 & 0.320117 \tabularnewline
15 & 0.578169 & 0.843663 & 0.421831 \tabularnewline
16 & 0.604 & 0.792 & 0.396 \tabularnewline
17 & 0.660301 & 0.679398 & 0.339699 \tabularnewline
18 & 0.656108 & 0.687783 & 0.343892 \tabularnewline
19 & 0.567901 & 0.864198 & 0.432099 \tabularnewline
20 & 0.594704 & 0.810593 & 0.405296 \tabularnewline
21 & 0.651147 & 0.697707 & 0.348853 \tabularnewline
22 & 0.620613 & 0.758774 & 0.379387 \tabularnewline
23 & 0.606219 & 0.787563 & 0.393781 \tabularnewline
24 & 0.539047 & 0.921907 & 0.460953 \tabularnewline
25 & 0.587987 & 0.824027 & 0.412013 \tabularnewline
26 & 0.746417 & 0.507166 & 0.253583 \tabularnewline
27 & 0.719455 & 0.561089 & 0.280545 \tabularnewline
28 & 0.676336 & 0.647328 & 0.323664 \tabularnewline
29 & 0.666393 & 0.667214 & 0.333607 \tabularnewline
30 & 0.605512 & 0.788975 & 0.394488 \tabularnewline
31 & 0.596261 & 0.807479 & 0.403739 \tabularnewline
32 & 0.736306 & 0.527387 & 0.263694 \tabularnewline
33 & 0.723628 & 0.552744 & 0.276372 \tabularnewline
34 & 0.686101 & 0.627797 & 0.313899 \tabularnewline
35 & 0.633096 & 0.733809 & 0.366904 \tabularnewline
36 & 0.581208 & 0.837584 & 0.418792 \tabularnewline
37 & 0.541667 & 0.916666 & 0.458333 \tabularnewline
38 & 0.50497 & 0.99006 & 0.49503 \tabularnewline
39 & 0.622253 & 0.755494 & 0.377747 \tabularnewline
40 & 0.569416 & 0.861168 & 0.430584 \tabularnewline
41 & 0.533134 & 0.933733 & 0.466866 \tabularnewline
42 & 0.479632 & 0.959265 & 0.520368 \tabularnewline
43 & 0.437798 & 0.875596 & 0.562202 \tabularnewline
44 & 0.38984 & 0.779681 & 0.61016 \tabularnewline
45 & 0.45776 & 0.915521 & 0.54224 \tabularnewline
46 & 0.46453 & 0.929061 & 0.53547 \tabularnewline
47 & 0.433998 & 0.867996 & 0.566002 \tabularnewline
48 & 0.403917 & 0.807834 & 0.596083 \tabularnewline
49 & 0.357797 & 0.715593 & 0.642203 \tabularnewline
50 & 0.366579 & 0.733157 & 0.633421 \tabularnewline
51 & 0.414238 & 0.828476 & 0.585762 \tabularnewline
52 & 0.377933 & 0.755865 & 0.622067 \tabularnewline
53 & 0.337882 & 0.675764 & 0.662118 \tabularnewline
54 & 0.304428 & 0.608856 & 0.695572 \tabularnewline
55 & 0.266737 & 0.533473 & 0.733263 \tabularnewline
56 & 0.250804 & 0.501608 & 0.749196 \tabularnewline
57 & 0.262121 & 0.524242 & 0.737879 \tabularnewline
58 & 0.378759 & 0.757519 & 0.621241 \tabularnewline
59 & 0.340315 & 0.68063 & 0.659685 \tabularnewline
60 & 0.299924 & 0.599849 & 0.700076 \tabularnewline
61 & 0.2703 & 0.5406 & 0.7297 \tabularnewline
62 & 0.252661 & 0.505322 & 0.747339 \tabularnewline
63 & 0.226468 & 0.452935 & 0.773532 \tabularnewline
64 & 0.234442 & 0.468883 & 0.765558 \tabularnewline
65 & 0.202377 & 0.404753 & 0.797623 \tabularnewline
66 & 0.173423 & 0.346846 & 0.826577 \tabularnewline
67 & 0.151854 & 0.303708 & 0.848146 \tabularnewline
68 & 0.152927 & 0.305854 & 0.847073 \tabularnewline
69 & 0.168786 & 0.337571 & 0.831214 \tabularnewline
70 & 0.144268 & 0.288537 & 0.855732 \tabularnewline
71 & 0.153776 & 0.307552 & 0.846224 \tabularnewline
72 & 0.179376 & 0.358753 & 0.820624 \tabularnewline
73 & 0.170989 & 0.341977 & 0.829011 \tabularnewline
74 & 0.146506 & 0.293012 & 0.853494 \tabularnewline
75 & 0.129624 & 0.259248 & 0.870376 \tabularnewline
76 & 0.172359 & 0.344718 & 0.827641 \tabularnewline
77 & 0.149762 & 0.299525 & 0.850238 \tabularnewline
78 & 0.12762 & 0.255241 & 0.87238 \tabularnewline
79 & 0.161437 & 0.322873 & 0.838563 \tabularnewline
80 & 0.18688 & 0.373759 & 0.81312 \tabularnewline
81 & 0.177702 & 0.355404 & 0.822298 \tabularnewline
82 & 0.155343 & 0.310685 & 0.844657 \tabularnewline
83 & 0.14836 & 0.296719 & 0.85164 \tabularnewline
84 & 0.140965 & 0.28193 & 0.859035 \tabularnewline
85 & 0.1226 & 0.2452 & 0.8774 \tabularnewline
86 & 0.109972 & 0.219944 & 0.890028 \tabularnewline
87 & 0.0971915 & 0.194383 & 0.902808 \tabularnewline
88 & 0.112491 & 0.224981 & 0.887509 \tabularnewline
89 & 0.0949432 & 0.189886 & 0.905057 \tabularnewline
90 & 0.0983609 & 0.196722 & 0.901639 \tabularnewline
91 & 0.0925494 & 0.185099 & 0.907451 \tabularnewline
92 & 0.0825618 & 0.165124 & 0.917438 \tabularnewline
93 & 0.0693346 & 0.138669 & 0.930665 \tabularnewline
94 & 0.0693932 & 0.138786 & 0.930607 \tabularnewline
95 & 0.0705711 & 0.141142 & 0.929429 \tabularnewline
96 & 0.0658417 & 0.131683 & 0.934158 \tabularnewline
97 & 0.0563377 & 0.112675 & 0.943662 \tabularnewline
98 & 0.0507454 & 0.101491 & 0.949255 \tabularnewline
99 & 0.0497453 & 0.0994906 & 0.950255 \tabularnewline
100 & 0.0466915 & 0.093383 & 0.953308 \tabularnewline
101 & 0.0420435 & 0.0840871 & 0.957956 \tabularnewline
102 & 0.0348468 & 0.0696935 & 0.965153 \tabularnewline
103 & 0.028393 & 0.056786 & 0.971607 \tabularnewline
104 & 0.0282883 & 0.0565767 & 0.971712 \tabularnewline
105 & 0.0655961 & 0.131192 & 0.934404 \tabularnewline
106 & 0.0617334 & 0.123467 & 0.938267 \tabularnewline
107 & 0.0755648 & 0.15113 & 0.924435 \tabularnewline
108 & 0.0653535 & 0.130707 & 0.934646 \tabularnewline
109 & 0.103675 & 0.207351 & 0.896325 \tabularnewline
110 & 0.120559 & 0.241119 & 0.879441 \tabularnewline
111 & 0.115718 & 0.231437 & 0.884282 \tabularnewline
112 & 0.152136 & 0.304272 & 0.847864 \tabularnewline
113 & 0.140687 & 0.281374 & 0.859313 \tabularnewline
114 & 0.136576 & 0.273152 & 0.863424 \tabularnewline
115 & 0.130164 & 0.260329 & 0.869836 \tabularnewline
116 & 0.127674 & 0.255348 & 0.872326 \tabularnewline
117 & 0.124522 & 0.249045 & 0.875478 \tabularnewline
118 & 0.109775 & 0.219551 & 0.890225 \tabularnewline
119 & 0.103585 & 0.207169 & 0.896415 \tabularnewline
120 & 0.0930071 & 0.186014 & 0.906993 \tabularnewline
121 & 0.0811492 & 0.162298 & 0.918851 \tabularnewline
122 & 0.0741534 & 0.148307 & 0.925847 \tabularnewline
123 & 0.0634473 & 0.126895 & 0.936553 \tabularnewline
124 & 0.060552 & 0.121104 & 0.939448 \tabularnewline
125 & 0.057222 & 0.114444 & 0.942778 \tabularnewline
126 & 0.0705488 & 0.141098 & 0.929451 \tabularnewline
127 & 0.126805 & 0.253611 & 0.873195 \tabularnewline
128 & 0.12407 & 0.24814 & 0.87593 \tabularnewline
129 & 0.110434 & 0.220869 & 0.889566 \tabularnewline
130 & 0.101726 & 0.203452 & 0.898274 \tabularnewline
131 & 0.110451 & 0.220902 & 0.889549 \tabularnewline
132 & 0.118064 & 0.236128 & 0.881936 \tabularnewline
133 & 0.142117 & 0.284233 & 0.857883 \tabularnewline
134 & 0.125507 & 0.251014 & 0.874493 \tabularnewline
135 & 0.108441 & 0.216881 & 0.891559 \tabularnewline
136 & 0.094306 & 0.188612 & 0.905694 \tabularnewline
137 & 0.080999 & 0.161998 & 0.919001 \tabularnewline
138 & 0.0894678 & 0.178936 & 0.910532 \tabularnewline
139 & 0.0764844 & 0.152969 & 0.923516 \tabularnewline
140 & 0.0763898 & 0.15278 & 0.92361 \tabularnewline
141 & 0.0740265 & 0.148053 & 0.925974 \tabularnewline
142 & 0.105833 & 0.211665 & 0.894167 \tabularnewline
143 & 0.131645 & 0.263289 & 0.868355 \tabularnewline
144 & 0.119458 & 0.238915 & 0.880542 \tabularnewline
145 & 0.195336 & 0.390671 & 0.804664 \tabularnewline
146 & 0.176342 & 0.352685 & 0.823658 \tabularnewline
147 & 0.159176 & 0.318352 & 0.840824 \tabularnewline
148 & 0.140747 & 0.281494 & 0.859253 \tabularnewline
149 & 0.127309 & 0.254617 & 0.872691 \tabularnewline
150 & 0.113094 & 0.226187 & 0.886906 \tabularnewline
151 & 0.178372 & 0.356745 & 0.821628 \tabularnewline
152 & 0.165458 & 0.330916 & 0.834542 \tabularnewline
153 & 0.150935 & 0.30187 & 0.849065 \tabularnewline
154 & 0.165159 & 0.330319 & 0.834841 \tabularnewline
155 & 0.145171 & 0.290341 & 0.854829 \tabularnewline
156 & 0.159364 & 0.318728 & 0.840636 \tabularnewline
157 & 0.153108 & 0.306216 & 0.846892 \tabularnewline
158 & 0.140895 & 0.281789 & 0.859105 \tabularnewline
159 & 0.135833 & 0.271666 & 0.864167 \tabularnewline
160 & 0.126158 & 0.252316 & 0.873842 \tabularnewline
161 & 0.108225 & 0.216449 & 0.891775 \tabularnewline
162 & 0.100419 & 0.200838 & 0.899581 \tabularnewline
163 & 0.0920918 & 0.184184 & 0.907908 \tabularnewline
164 & 0.121384 & 0.242767 & 0.878616 \tabularnewline
165 & 0.108858 & 0.217715 & 0.891142 \tabularnewline
166 & 0.180691 & 0.361382 & 0.819309 \tabularnewline
167 & 0.176003 & 0.352006 & 0.823997 \tabularnewline
168 & 0.162079 & 0.324158 & 0.837921 \tabularnewline
169 & 0.145334 & 0.290668 & 0.854666 \tabularnewline
170 & 0.235386 & 0.470773 & 0.764614 \tabularnewline
171 & 0.278092 & 0.556184 & 0.721908 \tabularnewline
172 & 0.249272 & 0.498545 & 0.750728 \tabularnewline
173 & 0.36228 & 0.72456 & 0.63772 \tabularnewline
174 & 0.32768 & 0.655359 & 0.67232 \tabularnewline
175 & 0.399809 & 0.799617 & 0.600191 \tabularnewline
176 & 0.372127 & 0.744253 & 0.627873 \tabularnewline
177 & 0.378352 & 0.756705 & 0.621648 \tabularnewline
178 & 0.345616 & 0.691232 & 0.654384 \tabularnewline
179 & 0.31521 & 0.630421 & 0.68479 \tabularnewline
180 & 0.314035 & 0.628069 & 0.685965 \tabularnewline
181 & 0.283617 & 0.567235 & 0.716383 \tabularnewline
182 & 0.27978 & 0.559559 & 0.72022 \tabularnewline
183 & 0.294951 & 0.589901 & 0.705049 \tabularnewline
184 & 0.364864 & 0.729728 & 0.635136 \tabularnewline
185 & 0.602212 & 0.795576 & 0.397788 \tabularnewline
186 & 0.582255 & 0.83549 & 0.417745 \tabularnewline
187 & 0.57877 & 0.84246 & 0.42123 \tabularnewline
188 & 0.728882 & 0.542236 & 0.271118 \tabularnewline
189 & 0.705459 & 0.589081 & 0.294541 \tabularnewline
190 & 0.709896 & 0.580208 & 0.290104 \tabularnewline
191 & 0.674406 & 0.651187 & 0.325594 \tabularnewline
192 & 0.645165 & 0.70967 & 0.354835 \tabularnewline
193 & 0.610596 & 0.778808 & 0.389404 \tabularnewline
194 & 0.57655 & 0.846899 & 0.42345 \tabularnewline
195 & 0.536748 & 0.926504 & 0.463252 \tabularnewline
196 & 0.498576 & 0.997152 & 0.501424 \tabularnewline
197 & 0.491313 & 0.982626 & 0.508687 \tabularnewline
198 & 0.46249 & 0.92498 & 0.53751 \tabularnewline
199 & 0.420991 & 0.841982 & 0.579009 \tabularnewline
200 & 0.492605 & 0.985209 & 0.507395 \tabularnewline
201 & 0.45808 & 0.91616 & 0.54192 \tabularnewline
202 & 0.607475 & 0.785051 & 0.392525 \tabularnewline
203 & 0.587706 & 0.824588 & 0.412294 \tabularnewline
204 & 0.551671 & 0.896658 & 0.448329 \tabularnewline
205 & 0.508621 & 0.982758 & 0.491379 \tabularnewline
206 & 0.467059 & 0.934117 & 0.532941 \tabularnewline
207 & 0.426659 & 0.853319 & 0.573341 \tabularnewline
208 & 0.38461 & 0.76922 & 0.61539 \tabularnewline
209 & 0.359396 & 0.718791 & 0.640604 \tabularnewline
210 & 0.327142 & 0.654283 & 0.672858 \tabularnewline
211 & 0.290813 & 0.581626 & 0.709187 \tabularnewline
212 & 0.265378 & 0.530755 & 0.734622 \tabularnewline
213 & 0.313306 & 0.626613 & 0.686694 \tabularnewline
214 & 0.291087 & 0.582175 & 0.708913 \tabularnewline
215 & 0.252796 & 0.505592 & 0.747204 \tabularnewline
216 & 0.2183 & 0.4366 & 0.7817 \tabularnewline
217 & 0.190003 & 0.380006 & 0.809997 \tabularnewline
218 & 0.220313 & 0.440626 & 0.779687 \tabularnewline
219 & 0.196562 & 0.393124 & 0.803438 \tabularnewline
220 & 0.176967 & 0.353933 & 0.823033 \tabularnewline
221 & 0.151404 & 0.302808 & 0.848596 \tabularnewline
222 & 0.164435 & 0.32887 & 0.835565 \tabularnewline
223 & 0.134387 & 0.268774 & 0.865613 \tabularnewline
224 & 0.113319 & 0.226639 & 0.886681 \tabularnewline
225 & 0.169986 & 0.339972 & 0.830014 \tabularnewline
226 & 0.154423 & 0.308845 & 0.845577 \tabularnewline
227 & 0.133856 & 0.267712 & 0.866144 \tabularnewline
228 & 0.141379 & 0.282758 & 0.858621 \tabularnewline
229 & 0.113746 & 0.227492 & 0.886254 \tabularnewline
230 & 0.0887997 & 0.177599 & 0.9112 \tabularnewline
231 & 0.0884334 & 0.176867 & 0.911567 \tabularnewline
232 & 0.209466 & 0.418931 & 0.790534 \tabularnewline
233 & 0.171525 & 0.34305 & 0.828475 \tabularnewline
234 & 0.281428 & 0.562855 & 0.718572 \tabularnewline
235 & 0.236175 & 0.47235 & 0.763825 \tabularnewline
236 & 0.240618 & 0.481236 & 0.759382 \tabularnewline
237 & 0.206507 & 0.413015 & 0.793493 \tabularnewline
238 & 0.288468 & 0.576935 & 0.711532 \tabularnewline
239 & 0.237071 & 0.474142 & 0.762929 \tabularnewline
240 & 0.39622 & 0.79244 & 0.60378 \tabularnewline
241 & 0.464806 & 0.929612 & 0.535194 \tabularnewline
242 & 0.387204 & 0.774408 & 0.612796 \tabularnewline
243 & 0.314285 & 0.62857 & 0.685715 \tabularnewline
244 & 0.30119 & 0.60238 & 0.69881 \tabularnewline
245 & 0.32309 & 0.64618 & 0.67691 \tabularnewline
246 & 0.534208 & 0.931584 & 0.465792 \tabularnewline
247 & 0.526632 & 0.946735 & 0.473368 \tabularnewline
248 & 0.457651 & 0.915302 & 0.542349 \tabularnewline
249 & 0.672079 & 0.655842 & 0.327921 \tabularnewline
250 & 0.600771 & 0.798457 & 0.399229 \tabularnewline
251 & 0.56118 & 0.87764 & 0.43882 \tabularnewline
252 & 0.663479 & 0.673042 & 0.336521 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221586&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]0.559936[/C][C]0.880127[/C][C]0.440064[/C][/ROW]
[ROW][C]13[/C][C]0.696215[/C][C]0.60757[/C][C]0.303785[/C][/ROW]
[ROW][C]14[/C][C]0.679883[/C][C]0.640234[/C][C]0.320117[/C][/ROW]
[ROW][C]15[/C][C]0.578169[/C][C]0.843663[/C][C]0.421831[/C][/ROW]
[ROW][C]16[/C][C]0.604[/C][C]0.792[/C][C]0.396[/C][/ROW]
[ROW][C]17[/C][C]0.660301[/C][C]0.679398[/C][C]0.339699[/C][/ROW]
[ROW][C]18[/C][C]0.656108[/C][C]0.687783[/C][C]0.343892[/C][/ROW]
[ROW][C]19[/C][C]0.567901[/C][C]0.864198[/C][C]0.432099[/C][/ROW]
[ROW][C]20[/C][C]0.594704[/C][C]0.810593[/C][C]0.405296[/C][/ROW]
[ROW][C]21[/C][C]0.651147[/C][C]0.697707[/C][C]0.348853[/C][/ROW]
[ROW][C]22[/C][C]0.620613[/C][C]0.758774[/C][C]0.379387[/C][/ROW]
[ROW][C]23[/C][C]0.606219[/C][C]0.787563[/C][C]0.393781[/C][/ROW]
[ROW][C]24[/C][C]0.539047[/C][C]0.921907[/C][C]0.460953[/C][/ROW]
[ROW][C]25[/C][C]0.587987[/C][C]0.824027[/C][C]0.412013[/C][/ROW]
[ROW][C]26[/C][C]0.746417[/C][C]0.507166[/C][C]0.253583[/C][/ROW]
[ROW][C]27[/C][C]0.719455[/C][C]0.561089[/C][C]0.280545[/C][/ROW]
[ROW][C]28[/C][C]0.676336[/C][C]0.647328[/C][C]0.323664[/C][/ROW]
[ROW][C]29[/C][C]0.666393[/C][C]0.667214[/C][C]0.333607[/C][/ROW]
[ROW][C]30[/C][C]0.605512[/C][C]0.788975[/C][C]0.394488[/C][/ROW]
[ROW][C]31[/C][C]0.596261[/C][C]0.807479[/C][C]0.403739[/C][/ROW]
[ROW][C]32[/C][C]0.736306[/C][C]0.527387[/C][C]0.263694[/C][/ROW]
[ROW][C]33[/C][C]0.723628[/C][C]0.552744[/C][C]0.276372[/C][/ROW]
[ROW][C]34[/C][C]0.686101[/C][C]0.627797[/C][C]0.313899[/C][/ROW]
[ROW][C]35[/C][C]0.633096[/C][C]0.733809[/C][C]0.366904[/C][/ROW]
[ROW][C]36[/C][C]0.581208[/C][C]0.837584[/C][C]0.418792[/C][/ROW]
[ROW][C]37[/C][C]0.541667[/C][C]0.916666[/C][C]0.458333[/C][/ROW]
[ROW][C]38[/C][C]0.50497[/C][C]0.99006[/C][C]0.49503[/C][/ROW]
[ROW][C]39[/C][C]0.622253[/C][C]0.755494[/C][C]0.377747[/C][/ROW]
[ROW][C]40[/C][C]0.569416[/C][C]0.861168[/C][C]0.430584[/C][/ROW]
[ROW][C]41[/C][C]0.533134[/C][C]0.933733[/C][C]0.466866[/C][/ROW]
[ROW][C]42[/C][C]0.479632[/C][C]0.959265[/C][C]0.520368[/C][/ROW]
[ROW][C]43[/C][C]0.437798[/C][C]0.875596[/C][C]0.562202[/C][/ROW]
[ROW][C]44[/C][C]0.38984[/C][C]0.779681[/C][C]0.61016[/C][/ROW]
[ROW][C]45[/C][C]0.45776[/C][C]0.915521[/C][C]0.54224[/C][/ROW]
[ROW][C]46[/C][C]0.46453[/C][C]0.929061[/C][C]0.53547[/C][/ROW]
[ROW][C]47[/C][C]0.433998[/C][C]0.867996[/C][C]0.566002[/C][/ROW]
[ROW][C]48[/C][C]0.403917[/C][C]0.807834[/C][C]0.596083[/C][/ROW]
[ROW][C]49[/C][C]0.357797[/C][C]0.715593[/C][C]0.642203[/C][/ROW]
[ROW][C]50[/C][C]0.366579[/C][C]0.733157[/C][C]0.633421[/C][/ROW]
[ROW][C]51[/C][C]0.414238[/C][C]0.828476[/C][C]0.585762[/C][/ROW]
[ROW][C]52[/C][C]0.377933[/C][C]0.755865[/C][C]0.622067[/C][/ROW]
[ROW][C]53[/C][C]0.337882[/C][C]0.675764[/C][C]0.662118[/C][/ROW]
[ROW][C]54[/C][C]0.304428[/C][C]0.608856[/C][C]0.695572[/C][/ROW]
[ROW][C]55[/C][C]0.266737[/C][C]0.533473[/C][C]0.733263[/C][/ROW]
[ROW][C]56[/C][C]0.250804[/C][C]0.501608[/C][C]0.749196[/C][/ROW]
[ROW][C]57[/C][C]0.262121[/C][C]0.524242[/C][C]0.737879[/C][/ROW]
[ROW][C]58[/C][C]0.378759[/C][C]0.757519[/C][C]0.621241[/C][/ROW]
[ROW][C]59[/C][C]0.340315[/C][C]0.68063[/C][C]0.659685[/C][/ROW]
[ROW][C]60[/C][C]0.299924[/C][C]0.599849[/C][C]0.700076[/C][/ROW]
[ROW][C]61[/C][C]0.2703[/C][C]0.5406[/C][C]0.7297[/C][/ROW]
[ROW][C]62[/C][C]0.252661[/C][C]0.505322[/C][C]0.747339[/C][/ROW]
[ROW][C]63[/C][C]0.226468[/C][C]0.452935[/C][C]0.773532[/C][/ROW]
[ROW][C]64[/C][C]0.234442[/C][C]0.468883[/C][C]0.765558[/C][/ROW]
[ROW][C]65[/C][C]0.202377[/C][C]0.404753[/C][C]0.797623[/C][/ROW]
[ROW][C]66[/C][C]0.173423[/C][C]0.346846[/C][C]0.826577[/C][/ROW]
[ROW][C]67[/C][C]0.151854[/C][C]0.303708[/C][C]0.848146[/C][/ROW]
[ROW][C]68[/C][C]0.152927[/C][C]0.305854[/C][C]0.847073[/C][/ROW]
[ROW][C]69[/C][C]0.168786[/C][C]0.337571[/C][C]0.831214[/C][/ROW]
[ROW][C]70[/C][C]0.144268[/C][C]0.288537[/C][C]0.855732[/C][/ROW]
[ROW][C]71[/C][C]0.153776[/C][C]0.307552[/C][C]0.846224[/C][/ROW]
[ROW][C]72[/C][C]0.179376[/C][C]0.358753[/C][C]0.820624[/C][/ROW]
[ROW][C]73[/C][C]0.170989[/C][C]0.341977[/C][C]0.829011[/C][/ROW]
[ROW][C]74[/C][C]0.146506[/C][C]0.293012[/C][C]0.853494[/C][/ROW]
[ROW][C]75[/C][C]0.129624[/C][C]0.259248[/C][C]0.870376[/C][/ROW]
[ROW][C]76[/C][C]0.172359[/C][C]0.344718[/C][C]0.827641[/C][/ROW]
[ROW][C]77[/C][C]0.149762[/C][C]0.299525[/C][C]0.850238[/C][/ROW]
[ROW][C]78[/C][C]0.12762[/C][C]0.255241[/C][C]0.87238[/C][/ROW]
[ROW][C]79[/C][C]0.161437[/C][C]0.322873[/C][C]0.838563[/C][/ROW]
[ROW][C]80[/C][C]0.18688[/C][C]0.373759[/C][C]0.81312[/C][/ROW]
[ROW][C]81[/C][C]0.177702[/C][C]0.355404[/C][C]0.822298[/C][/ROW]
[ROW][C]82[/C][C]0.155343[/C][C]0.310685[/C][C]0.844657[/C][/ROW]
[ROW][C]83[/C][C]0.14836[/C][C]0.296719[/C][C]0.85164[/C][/ROW]
[ROW][C]84[/C][C]0.140965[/C][C]0.28193[/C][C]0.859035[/C][/ROW]
[ROW][C]85[/C][C]0.1226[/C][C]0.2452[/C][C]0.8774[/C][/ROW]
[ROW][C]86[/C][C]0.109972[/C][C]0.219944[/C][C]0.890028[/C][/ROW]
[ROW][C]87[/C][C]0.0971915[/C][C]0.194383[/C][C]0.902808[/C][/ROW]
[ROW][C]88[/C][C]0.112491[/C][C]0.224981[/C][C]0.887509[/C][/ROW]
[ROW][C]89[/C][C]0.0949432[/C][C]0.189886[/C][C]0.905057[/C][/ROW]
[ROW][C]90[/C][C]0.0983609[/C][C]0.196722[/C][C]0.901639[/C][/ROW]
[ROW][C]91[/C][C]0.0925494[/C][C]0.185099[/C][C]0.907451[/C][/ROW]
[ROW][C]92[/C][C]0.0825618[/C][C]0.165124[/C][C]0.917438[/C][/ROW]
[ROW][C]93[/C][C]0.0693346[/C][C]0.138669[/C][C]0.930665[/C][/ROW]
[ROW][C]94[/C][C]0.0693932[/C][C]0.138786[/C][C]0.930607[/C][/ROW]
[ROW][C]95[/C][C]0.0705711[/C][C]0.141142[/C][C]0.929429[/C][/ROW]
[ROW][C]96[/C][C]0.0658417[/C][C]0.131683[/C][C]0.934158[/C][/ROW]
[ROW][C]97[/C][C]0.0563377[/C][C]0.112675[/C][C]0.943662[/C][/ROW]
[ROW][C]98[/C][C]0.0507454[/C][C]0.101491[/C][C]0.949255[/C][/ROW]
[ROW][C]99[/C][C]0.0497453[/C][C]0.0994906[/C][C]0.950255[/C][/ROW]
[ROW][C]100[/C][C]0.0466915[/C][C]0.093383[/C][C]0.953308[/C][/ROW]
[ROW][C]101[/C][C]0.0420435[/C][C]0.0840871[/C][C]0.957956[/C][/ROW]
[ROW][C]102[/C][C]0.0348468[/C][C]0.0696935[/C][C]0.965153[/C][/ROW]
[ROW][C]103[/C][C]0.028393[/C][C]0.056786[/C][C]0.971607[/C][/ROW]
[ROW][C]104[/C][C]0.0282883[/C][C]0.0565767[/C][C]0.971712[/C][/ROW]
[ROW][C]105[/C][C]0.0655961[/C][C]0.131192[/C][C]0.934404[/C][/ROW]
[ROW][C]106[/C][C]0.0617334[/C][C]0.123467[/C][C]0.938267[/C][/ROW]
[ROW][C]107[/C][C]0.0755648[/C][C]0.15113[/C][C]0.924435[/C][/ROW]
[ROW][C]108[/C][C]0.0653535[/C][C]0.130707[/C][C]0.934646[/C][/ROW]
[ROW][C]109[/C][C]0.103675[/C][C]0.207351[/C][C]0.896325[/C][/ROW]
[ROW][C]110[/C][C]0.120559[/C][C]0.241119[/C][C]0.879441[/C][/ROW]
[ROW][C]111[/C][C]0.115718[/C][C]0.231437[/C][C]0.884282[/C][/ROW]
[ROW][C]112[/C][C]0.152136[/C][C]0.304272[/C][C]0.847864[/C][/ROW]
[ROW][C]113[/C][C]0.140687[/C][C]0.281374[/C][C]0.859313[/C][/ROW]
[ROW][C]114[/C][C]0.136576[/C][C]0.273152[/C][C]0.863424[/C][/ROW]
[ROW][C]115[/C][C]0.130164[/C][C]0.260329[/C][C]0.869836[/C][/ROW]
[ROW][C]116[/C][C]0.127674[/C][C]0.255348[/C][C]0.872326[/C][/ROW]
[ROW][C]117[/C][C]0.124522[/C][C]0.249045[/C][C]0.875478[/C][/ROW]
[ROW][C]118[/C][C]0.109775[/C][C]0.219551[/C][C]0.890225[/C][/ROW]
[ROW][C]119[/C][C]0.103585[/C][C]0.207169[/C][C]0.896415[/C][/ROW]
[ROW][C]120[/C][C]0.0930071[/C][C]0.186014[/C][C]0.906993[/C][/ROW]
[ROW][C]121[/C][C]0.0811492[/C][C]0.162298[/C][C]0.918851[/C][/ROW]
[ROW][C]122[/C][C]0.0741534[/C][C]0.148307[/C][C]0.925847[/C][/ROW]
[ROW][C]123[/C][C]0.0634473[/C][C]0.126895[/C][C]0.936553[/C][/ROW]
[ROW][C]124[/C][C]0.060552[/C][C]0.121104[/C][C]0.939448[/C][/ROW]
[ROW][C]125[/C][C]0.057222[/C][C]0.114444[/C][C]0.942778[/C][/ROW]
[ROW][C]126[/C][C]0.0705488[/C][C]0.141098[/C][C]0.929451[/C][/ROW]
[ROW][C]127[/C][C]0.126805[/C][C]0.253611[/C][C]0.873195[/C][/ROW]
[ROW][C]128[/C][C]0.12407[/C][C]0.24814[/C][C]0.87593[/C][/ROW]
[ROW][C]129[/C][C]0.110434[/C][C]0.220869[/C][C]0.889566[/C][/ROW]
[ROW][C]130[/C][C]0.101726[/C][C]0.203452[/C][C]0.898274[/C][/ROW]
[ROW][C]131[/C][C]0.110451[/C][C]0.220902[/C][C]0.889549[/C][/ROW]
[ROW][C]132[/C][C]0.118064[/C][C]0.236128[/C][C]0.881936[/C][/ROW]
[ROW][C]133[/C][C]0.142117[/C][C]0.284233[/C][C]0.857883[/C][/ROW]
[ROW][C]134[/C][C]0.125507[/C][C]0.251014[/C][C]0.874493[/C][/ROW]
[ROW][C]135[/C][C]0.108441[/C][C]0.216881[/C][C]0.891559[/C][/ROW]
[ROW][C]136[/C][C]0.094306[/C][C]0.188612[/C][C]0.905694[/C][/ROW]
[ROW][C]137[/C][C]0.080999[/C][C]0.161998[/C][C]0.919001[/C][/ROW]
[ROW][C]138[/C][C]0.0894678[/C][C]0.178936[/C][C]0.910532[/C][/ROW]
[ROW][C]139[/C][C]0.0764844[/C][C]0.152969[/C][C]0.923516[/C][/ROW]
[ROW][C]140[/C][C]0.0763898[/C][C]0.15278[/C][C]0.92361[/C][/ROW]
[ROW][C]141[/C][C]0.0740265[/C][C]0.148053[/C][C]0.925974[/C][/ROW]
[ROW][C]142[/C][C]0.105833[/C][C]0.211665[/C][C]0.894167[/C][/ROW]
[ROW][C]143[/C][C]0.131645[/C][C]0.263289[/C][C]0.868355[/C][/ROW]
[ROW][C]144[/C][C]0.119458[/C][C]0.238915[/C][C]0.880542[/C][/ROW]
[ROW][C]145[/C][C]0.195336[/C][C]0.390671[/C][C]0.804664[/C][/ROW]
[ROW][C]146[/C][C]0.176342[/C][C]0.352685[/C][C]0.823658[/C][/ROW]
[ROW][C]147[/C][C]0.159176[/C][C]0.318352[/C][C]0.840824[/C][/ROW]
[ROW][C]148[/C][C]0.140747[/C][C]0.281494[/C][C]0.859253[/C][/ROW]
[ROW][C]149[/C][C]0.127309[/C][C]0.254617[/C][C]0.872691[/C][/ROW]
[ROW][C]150[/C][C]0.113094[/C][C]0.226187[/C][C]0.886906[/C][/ROW]
[ROW][C]151[/C][C]0.178372[/C][C]0.356745[/C][C]0.821628[/C][/ROW]
[ROW][C]152[/C][C]0.165458[/C][C]0.330916[/C][C]0.834542[/C][/ROW]
[ROW][C]153[/C][C]0.150935[/C][C]0.30187[/C][C]0.849065[/C][/ROW]
[ROW][C]154[/C][C]0.165159[/C][C]0.330319[/C][C]0.834841[/C][/ROW]
[ROW][C]155[/C][C]0.145171[/C][C]0.290341[/C][C]0.854829[/C][/ROW]
[ROW][C]156[/C][C]0.159364[/C][C]0.318728[/C][C]0.840636[/C][/ROW]
[ROW][C]157[/C][C]0.153108[/C][C]0.306216[/C][C]0.846892[/C][/ROW]
[ROW][C]158[/C][C]0.140895[/C][C]0.281789[/C][C]0.859105[/C][/ROW]
[ROW][C]159[/C][C]0.135833[/C][C]0.271666[/C][C]0.864167[/C][/ROW]
[ROW][C]160[/C][C]0.126158[/C][C]0.252316[/C][C]0.873842[/C][/ROW]
[ROW][C]161[/C][C]0.108225[/C][C]0.216449[/C][C]0.891775[/C][/ROW]
[ROW][C]162[/C][C]0.100419[/C][C]0.200838[/C][C]0.899581[/C][/ROW]
[ROW][C]163[/C][C]0.0920918[/C][C]0.184184[/C][C]0.907908[/C][/ROW]
[ROW][C]164[/C][C]0.121384[/C][C]0.242767[/C][C]0.878616[/C][/ROW]
[ROW][C]165[/C][C]0.108858[/C][C]0.217715[/C][C]0.891142[/C][/ROW]
[ROW][C]166[/C][C]0.180691[/C][C]0.361382[/C][C]0.819309[/C][/ROW]
[ROW][C]167[/C][C]0.176003[/C][C]0.352006[/C][C]0.823997[/C][/ROW]
[ROW][C]168[/C][C]0.162079[/C][C]0.324158[/C][C]0.837921[/C][/ROW]
[ROW][C]169[/C][C]0.145334[/C][C]0.290668[/C][C]0.854666[/C][/ROW]
[ROW][C]170[/C][C]0.235386[/C][C]0.470773[/C][C]0.764614[/C][/ROW]
[ROW][C]171[/C][C]0.278092[/C][C]0.556184[/C][C]0.721908[/C][/ROW]
[ROW][C]172[/C][C]0.249272[/C][C]0.498545[/C][C]0.750728[/C][/ROW]
[ROW][C]173[/C][C]0.36228[/C][C]0.72456[/C][C]0.63772[/C][/ROW]
[ROW][C]174[/C][C]0.32768[/C][C]0.655359[/C][C]0.67232[/C][/ROW]
[ROW][C]175[/C][C]0.399809[/C][C]0.799617[/C][C]0.600191[/C][/ROW]
[ROW][C]176[/C][C]0.372127[/C][C]0.744253[/C][C]0.627873[/C][/ROW]
[ROW][C]177[/C][C]0.378352[/C][C]0.756705[/C][C]0.621648[/C][/ROW]
[ROW][C]178[/C][C]0.345616[/C][C]0.691232[/C][C]0.654384[/C][/ROW]
[ROW][C]179[/C][C]0.31521[/C][C]0.630421[/C][C]0.68479[/C][/ROW]
[ROW][C]180[/C][C]0.314035[/C][C]0.628069[/C][C]0.685965[/C][/ROW]
[ROW][C]181[/C][C]0.283617[/C][C]0.567235[/C][C]0.716383[/C][/ROW]
[ROW][C]182[/C][C]0.27978[/C][C]0.559559[/C][C]0.72022[/C][/ROW]
[ROW][C]183[/C][C]0.294951[/C][C]0.589901[/C][C]0.705049[/C][/ROW]
[ROW][C]184[/C][C]0.364864[/C][C]0.729728[/C][C]0.635136[/C][/ROW]
[ROW][C]185[/C][C]0.602212[/C][C]0.795576[/C][C]0.397788[/C][/ROW]
[ROW][C]186[/C][C]0.582255[/C][C]0.83549[/C][C]0.417745[/C][/ROW]
[ROW][C]187[/C][C]0.57877[/C][C]0.84246[/C][C]0.42123[/C][/ROW]
[ROW][C]188[/C][C]0.728882[/C][C]0.542236[/C][C]0.271118[/C][/ROW]
[ROW][C]189[/C][C]0.705459[/C][C]0.589081[/C][C]0.294541[/C][/ROW]
[ROW][C]190[/C][C]0.709896[/C][C]0.580208[/C][C]0.290104[/C][/ROW]
[ROW][C]191[/C][C]0.674406[/C][C]0.651187[/C][C]0.325594[/C][/ROW]
[ROW][C]192[/C][C]0.645165[/C][C]0.70967[/C][C]0.354835[/C][/ROW]
[ROW][C]193[/C][C]0.610596[/C][C]0.778808[/C][C]0.389404[/C][/ROW]
[ROW][C]194[/C][C]0.57655[/C][C]0.846899[/C][C]0.42345[/C][/ROW]
[ROW][C]195[/C][C]0.536748[/C][C]0.926504[/C][C]0.463252[/C][/ROW]
[ROW][C]196[/C][C]0.498576[/C][C]0.997152[/C][C]0.501424[/C][/ROW]
[ROW][C]197[/C][C]0.491313[/C][C]0.982626[/C][C]0.508687[/C][/ROW]
[ROW][C]198[/C][C]0.46249[/C][C]0.92498[/C][C]0.53751[/C][/ROW]
[ROW][C]199[/C][C]0.420991[/C][C]0.841982[/C][C]0.579009[/C][/ROW]
[ROW][C]200[/C][C]0.492605[/C][C]0.985209[/C][C]0.507395[/C][/ROW]
[ROW][C]201[/C][C]0.45808[/C][C]0.91616[/C][C]0.54192[/C][/ROW]
[ROW][C]202[/C][C]0.607475[/C][C]0.785051[/C][C]0.392525[/C][/ROW]
[ROW][C]203[/C][C]0.587706[/C][C]0.824588[/C][C]0.412294[/C][/ROW]
[ROW][C]204[/C][C]0.551671[/C][C]0.896658[/C][C]0.448329[/C][/ROW]
[ROW][C]205[/C][C]0.508621[/C][C]0.982758[/C][C]0.491379[/C][/ROW]
[ROW][C]206[/C][C]0.467059[/C][C]0.934117[/C][C]0.532941[/C][/ROW]
[ROW][C]207[/C][C]0.426659[/C][C]0.853319[/C][C]0.573341[/C][/ROW]
[ROW][C]208[/C][C]0.38461[/C][C]0.76922[/C][C]0.61539[/C][/ROW]
[ROW][C]209[/C][C]0.359396[/C][C]0.718791[/C][C]0.640604[/C][/ROW]
[ROW][C]210[/C][C]0.327142[/C][C]0.654283[/C][C]0.672858[/C][/ROW]
[ROW][C]211[/C][C]0.290813[/C][C]0.581626[/C][C]0.709187[/C][/ROW]
[ROW][C]212[/C][C]0.265378[/C][C]0.530755[/C][C]0.734622[/C][/ROW]
[ROW][C]213[/C][C]0.313306[/C][C]0.626613[/C][C]0.686694[/C][/ROW]
[ROW][C]214[/C][C]0.291087[/C][C]0.582175[/C][C]0.708913[/C][/ROW]
[ROW][C]215[/C][C]0.252796[/C][C]0.505592[/C][C]0.747204[/C][/ROW]
[ROW][C]216[/C][C]0.2183[/C][C]0.4366[/C][C]0.7817[/C][/ROW]
[ROW][C]217[/C][C]0.190003[/C][C]0.380006[/C][C]0.809997[/C][/ROW]
[ROW][C]218[/C][C]0.220313[/C][C]0.440626[/C][C]0.779687[/C][/ROW]
[ROW][C]219[/C][C]0.196562[/C][C]0.393124[/C][C]0.803438[/C][/ROW]
[ROW][C]220[/C][C]0.176967[/C][C]0.353933[/C][C]0.823033[/C][/ROW]
[ROW][C]221[/C][C]0.151404[/C][C]0.302808[/C][C]0.848596[/C][/ROW]
[ROW][C]222[/C][C]0.164435[/C][C]0.32887[/C][C]0.835565[/C][/ROW]
[ROW][C]223[/C][C]0.134387[/C][C]0.268774[/C][C]0.865613[/C][/ROW]
[ROW][C]224[/C][C]0.113319[/C][C]0.226639[/C][C]0.886681[/C][/ROW]
[ROW][C]225[/C][C]0.169986[/C][C]0.339972[/C][C]0.830014[/C][/ROW]
[ROW][C]226[/C][C]0.154423[/C][C]0.308845[/C][C]0.845577[/C][/ROW]
[ROW][C]227[/C][C]0.133856[/C][C]0.267712[/C][C]0.866144[/C][/ROW]
[ROW][C]228[/C][C]0.141379[/C][C]0.282758[/C][C]0.858621[/C][/ROW]
[ROW][C]229[/C][C]0.113746[/C][C]0.227492[/C][C]0.886254[/C][/ROW]
[ROW][C]230[/C][C]0.0887997[/C][C]0.177599[/C][C]0.9112[/C][/ROW]
[ROW][C]231[/C][C]0.0884334[/C][C]0.176867[/C][C]0.911567[/C][/ROW]
[ROW][C]232[/C][C]0.209466[/C][C]0.418931[/C][C]0.790534[/C][/ROW]
[ROW][C]233[/C][C]0.171525[/C][C]0.34305[/C][C]0.828475[/C][/ROW]
[ROW][C]234[/C][C]0.281428[/C][C]0.562855[/C][C]0.718572[/C][/ROW]
[ROW][C]235[/C][C]0.236175[/C][C]0.47235[/C][C]0.763825[/C][/ROW]
[ROW][C]236[/C][C]0.240618[/C][C]0.481236[/C][C]0.759382[/C][/ROW]
[ROW][C]237[/C][C]0.206507[/C][C]0.413015[/C][C]0.793493[/C][/ROW]
[ROW][C]238[/C][C]0.288468[/C][C]0.576935[/C][C]0.711532[/C][/ROW]
[ROW][C]239[/C][C]0.237071[/C][C]0.474142[/C][C]0.762929[/C][/ROW]
[ROW][C]240[/C][C]0.39622[/C][C]0.79244[/C][C]0.60378[/C][/ROW]
[ROW][C]241[/C][C]0.464806[/C][C]0.929612[/C][C]0.535194[/C][/ROW]
[ROW][C]242[/C][C]0.387204[/C][C]0.774408[/C][C]0.612796[/C][/ROW]
[ROW][C]243[/C][C]0.314285[/C][C]0.62857[/C][C]0.685715[/C][/ROW]
[ROW][C]244[/C][C]0.30119[/C][C]0.60238[/C][C]0.69881[/C][/ROW]
[ROW][C]245[/C][C]0.32309[/C][C]0.64618[/C][C]0.67691[/C][/ROW]
[ROW][C]246[/C][C]0.534208[/C][C]0.931584[/C][C]0.465792[/C][/ROW]
[ROW][C]247[/C][C]0.526632[/C][C]0.946735[/C][C]0.473368[/C][/ROW]
[ROW][C]248[/C][C]0.457651[/C][C]0.915302[/C][C]0.542349[/C][/ROW]
[ROW][C]249[/C][C]0.672079[/C][C]0.655842[/C][C]0.327921[/C][/ROW]
[ROW][C]250[/C][C]0.600771[/C][C]0.798457[/C][C]0.399229[/C][/ROW]
[ROW][C]251[/C][C]0.56118[/C][C]0.87764[/C][C]0.43882[/C][/ROW]
[ROW][C]252[/C][C]0.663479[/C][C]0.673042[/C][C]0.336521[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221586&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221586&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.5599360.8801270.440064
130.6962150.607570.303785
140.6798830.6402340.320117
150.5781690.8436630.421831
160.6040.7920.396
170.6603010.6793980.339699
180.6561080.6877830.343892
190.5679010.8641980.432099
200.5947040.8105930.405296
210.6511470.6977070.348853
220.6206130.7587740.379387
230.6062190.7875630.393781
240.5390470.9219070.460953
250.5879870.8240270.412013
260.7464170.5071660.253583
270.7194550.5610890.280545
280.6763360.6473280.323664
290.6663930.6672140.333607
300.6055120.7889750.394488
310.5962610.8074790.403739
320.7363060.5273870.263694
330.7236280.5527440.276372
340.6861010.6277970.313899
350.6330960.7338090.366904
360.5812080.8375840.418792
370.5416670.9166660.458333
380.504970.990060.49503
390.6222530.7554940.377747
400.5694160.8611680.430584
410.5331340.9337330.466866
420.4796320.9592650.520368
430.4377980.8755960.562202
440.389840.7796810.61016
450.457760.9155210.54224
460.464530.9290610.53547
470.4339980.8679960.566002
480.4039170.8078340.596083
490.3577970.7155930.642203
500.3665790.7331570.633421
510.4142380.8284760.585762
520.3779330.7558650.622067
530.3378820.6757640.662118
540.3044280.6088560.695572
550.2667370.5334730.733263
560.2508040.5016080.749196
570.2621210.5242420.737879
580.3787590.7575190.621241
590.3403150.680630.659685
600.2999240.5998490.700076
610.27030.54060.7297
620.2526610.5053220.747339
630.2264680.4529350.773532
640.2344420.4688830.765558
650.2023770.4047530.797623
660.1734230.3468460.826577
670.1518540.3037080.848146
680.1529270.3058540.847073
690.1687860.3375710.831214
700.1442680.2885370.855732
710.1537760.3075520.846224
720.1793760.3587530.820624
730.1709890.3419770.829011
740.1465060.2930120.853494
750.1296240.2592480.870376
760.1723590.3447180.827641
770.1497620.2995250.850238
780.127620.2552410.87238
790.1614370.3228730.838563
800.186880.3737590.81312
810.1777020.3554040.822298
820.1553430.3106850.844657
830.148360.2967190.85164
840.1409650.281930.859035
850.12260.24520.8774
860.1099720.2199440.890028
870.09719150.1943830.902808
880.1124910.2249810.887509
890.09494320.1898860.905057
900.09836090.1967220.901639
910.09254940.1850990.907451
920.08256180.1651240.917438
930.06933460.1386690.930665
940.06939320.1387860.930607
950.07057110.1411420.929429
960.06584170.1316830.934158
970.05633770.1126750.943662
980.05074540.1014910.949255
990.04974530.09949060.950255
1000.04669150.0933830.953308
1010.04204350.08408710.957956
1020.03484680.06969350.965153
1030.0283930.0567860.971607
1040.02828830.05657670.971712
1050.06559610.1311920.934404
1060.06173340.1234670.938267
1070.07556480.151130.924435
1080.06535350.1307070.934646
1090.1036750.2073510.896325
1100.1205590.2411190.879441
1110.1157180.2314370.884282
1120.1521360.3042720.847864
1130.1406870.2813740.859313
1140.1365760.2731520.863424
1150.1301640.2603290.869836
1160.1276740.2553480.872326
1170.1245220.2490450.875478
1180.1097750.2195510.890225
1190.1035850.2071690.896415
1200.09300710.1860140.906993
1210.08114920.1622980.918851
1220.07415340.1483070.925847
1230.06344730.1268950.936553
1240.0605520.1211040.939448
1250.0572220.1144440.942778
1260.07054880.1410980.929451
1270.1268050.2536110.873195
1280.124070.248140.87593
1290.1104340.2208690.889566
1300.1017260.2034520.898274
1310.1104510.2209020.889549
1320.1180640.2361280.881936
1330.1421170.2842330.857883
1340.1255070.2510140.874493
1350.1084410.2168810.891559
1360.0943060.1886120.905694
1370.0809990.1619980.919001
1380.08946780.1789360.910532
1390.07648440.1529690.923516
1400.07638980.152780.92361
1410.07402650.1480530.925974
1420.1058330.2116650.894167
1430.1316450.2632890.868355
1440.1194580.2389150.880542
1450.1953360.3906710.804664
1460.1763420.3526850.823658
1470.1591760.3183520.840824
1480.1407470.2814940.859253
1490.1273090.2546170.872691
1500.1130940.2261870.886906
1510.1783720.3567450.821628
1520.1654580.3309160.834542
1530.1509350.301870.849065
1540.1651590.3303190.834841
1550.1451710.2903410.854829
1560.1593640.3187280.840636
1570.1531080.3062160.846892
1580.1408950.2817890.859105
1590.1358330.2716660.864167
1600.1261580.2523160.873842
1610.1082250.2164490.891775
1620.1004190.2008380.899581
1630.09209180.1841840.907908
1640.1213840.2427670.878616
1650.1088580.2177150.891142
1660.1806910.3613820.819309
1670.1760030.3520060.823997
1680.1620790.3241580.837921
1690.1453340.2906680.854666
1700.2353860.4707730.764614
1710.2780920.5561840.721908
1720.2492720.4985450.750728
1730.362280.724560.63772
1740.327680.6553590.67232
1750.3998090.7996170.600191
1760.3721270.7442530.627873
1770.3783520.7567050.621648
1780.3456160.6912320.654384
1790.315210.6304210.68479
1800.3140350.6280690.685965
1810.2836170.5672350.716383
1820.279780.5595590.72022
1830.2949510.5899010.705049
1840.3648640.7297280.635136
1850.6022120.7955760.397788
1860.5822550.835490.417745
1870.578770.842460.42123
1880.7288820.5422360.271118
1890.7054590.5890810.294541
1900.7098960.5802080.290104
1910.6744060.6511870.325594
1920.6451650.709670.354835
1930.6105960.7788080.389404
1940.576550.8468990.42345
1950.5367480.9265040.463252
1960.4985760.9971520.501424
1970.4913130.9826260.508687
1980.462490.924980.53751
1990.4209910.8419820.579009
2000.4926050.9852090.507395
2010.458080.916160.54192
2020.6074750.7850510.392525
2030.5877060.8245880.412294
2040.5516710.8966580.448329
2050.5086210.9827580.491379
2060.4670590.9341170.532941
2070.4266590.8533190.573341
2080.384610.769220.61539
2090.3593960.7187910.640604
2100.3271420.6542830.672858
2110.2908130.5816260.709187
2120.2653780.5307550.734622
2130.3133060.6266130.686694
2140.2910870.5821750.708913
2150.2527960.5055920.747204
2160.21830.43660.7817
2170.1900030.3800060.809997
2180.2203130.4406260.779687
2190.1965620.3931240.803438
2200.1769670.3539330.823033
2210.1514040.3028080.848596
2220.1644350.328870.835565
2230.1343870.2687740.865613
2240.1133190.2266390.886681
2250.1699860.3399720.830014
2260.1544230.3088450.845577
2270.1338560.2677120.866144
2280.1413790.2827580.858621
2290.1137460.2274920.886254
2300.08879970.1775990.9112
2310.08843340.1768670.911567
2320.2094660.4189310.790534
2330.1715250.343050.828475
2340.2814280.5628550.718572
2350.2361750.472350.763825
2360.2406180.4812360.759382
2370.2065070.4130150.793493
2380.2884680.5769350.711532
2390.2370710.4741420.762929
2400.396220.792440.60378
2410.4648060.9296120.535194
2420.3872040.7744080.612796
2430.3142850.628570.685715
2440.301190.602380.69881
2450.323090.646180.67691
2460.5342080.9315840.465792
2470.5266320.9467350.473368
2480.4576510.9153020.542349
2490.6720790.6558420.327921
2500.6007710.7984570.399229
2510.561180.877640.43882
2520.6634790.6730420.336521






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level60.0248963OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 6 & 0.0248963 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221586&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]6[/C][C]0.0248963[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221586&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221586&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level60.0248963OK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

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