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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 computationSun, 14 Dec 2014 12:51:09 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/14/t1418561633vxei217xcklkfjz.htm/, Retrieved Fri, 01 Nov 2024 00:04:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267527, Retrieved Fri, 01 Nov 2024 00:04:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact122

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-14 12:51:09] [0a6fc2c777821367d2239c664b701a36] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13 41 38 12 14 12 53 32 9
16 39 32 11 18 11 83 51 9
19 30 35 15 11 14 66 42 9
15 31 33 6 12 12 67 41 9
14 34 37 13 16 21 76 46 9
13 35 29 10 18 12 78 47 9
19 39 31 12 14 22 53 37 9
15 34 36 14 14 11 80 49 9
14 36 35 12 15 10 74 45 9
15 37 38 9 15 13 76 47 9
16 38 31 10 17 10 79 49 9
16 36 34 12 19 8 54 33 9
16 38 35 12 10 15 67 42 9
16 39 38 11 16 14 54 33 9
17 33 37 15 18 10 87 53 9
15 32 33 12 14 14 58 36 9
15 36 32 10 14 14 75 45 9
20 38 38 12 17 11 88 54 9
18 39 38 11 14 10 64 41 9
16 32 32 12 16 13 57 36 9
16 32 33 11 18 9.5 66 41 9
16 31 31 12 11 14 68 44 9
19 39 38 13 14 12 54 33 9
16 37 39 11 12 14 56 37 9
17 39 32 12 17 11 86 52 9
17 41 32 13 9 9 80 47 9
16 36 35 10 16 11 76 43 9
15 33 37 14 14 15 69 44 9
16 33 33 12 15 14 78 45 9
14 34 33 10 11 13 67 44 9
15 31 31 12 16 9 80 49 9
12 27 32 8 13 15 54 33 9
14 37 31 10 17 10 71 43 9
16 34 37 12 15 11 84 54 9
14 34 30 12 14 13 74 42 9
10 32 33 7 16 8 71 44 9
10 29 31 9 9 20 63 37 9
14 36 33 12 15 12 71 43 9
16 29 31 10 17 10 76 46 9
16 35 33 10 13 10 69 42 9
16 37 32 10 15 9 74 45 9
14 34 33 12 16 14 75 44 9
20 38 32 15 16 8 54 33 9
14 35 33 10 12 14 52 31 9
14 38 28 10 15 11 69 42 9
11 37 35 12 11 13 68 40 9
14 38 39 13 15 9 65 43 9
15 33 34 11 15 11 75 46 9
16 36 38 11 17 15 74 42 9
14 38 32 12 13 11 75 45 9
16 32 38 14 16 10 72 44 9
14 32 30 10 14 14 67 40 9
12 32 33 12 11 18 63 37 9
16 34 38 13 12 14 62 46 9
9 32 32 5 12 11 63 36 9
14 37 35 6 15 14.5 76 47 9
16 39 34 12 16 13 74 45 9
16 29 34 12 15 9 67 42 9
15 37 36 11 12 10 73 43 9
16 35 34 10 12 15 70 43 9
12 30 28 7 8 20 53 32 9
16 38 34 12 13 12 77 45 9
16 34 35 14 11 12 80 48 9
14 31 35 11 14 14 52 31 9
16 34 31 12 15 13 54 33 9
17 35 37 13 10 11 80 49 10
18 36 35 14 11 17 66 42 10
18 30 27 11 12 12 73 41 10
12 39 40 12 15 13 63 38 10
16 35 37 12 15 14 69 42 10
10 38 36 8 14 13 67 44 10
14 31 38 11 16 15 54 33 10
18 34 39 14 15 13 81 48 10
18 38 41 14 15 10 69 40 10
16 34 27 12 13 11 84 50 10
17 39 30 9 12 19 80 49 10
16 37 37 13 17 13 70 43 10
16 34 31 11 13 17 69 44 10
13 28 31 12 15 13 77 47 10
16 37 27 12 13 9 54 33 10
16 33 36 12 15 11 79 46 10
16 35 37 12 15 9 71 45 10
15 37 33 12 16 12 73 43 10
15 32 34 11 15 12 72 44 10
16 33 31 10 14 13 77 47 10
14 38 39 9 15 13 75 45 10
16 33 34 12 14 12 69 42 10
16 29 32 12 13 15 54 33 10
15 33 33 12 7 22 70 43 10
12 31 36 9 17 13 73 46 10
17 36 32 15 13 15 54 33 10
16 35 41 12 15 13 77 46 10
15 32 28 12 14 15 82 48 10
13 29 30 12 13 12.5 80 47 10
16 39 36 10 16 11 80 47 10
16 37 35 13 12 16 69 43 10
16 35 31 9 14 11 78 46 10
16 37 34 12 17 11 81 48 10
14 32 36 10 15 10 76 46 10
16 38 36 14 17 10 76 45 10
16 37 35 11 12 16 73 45 10
20 36 37 15 16 12 85 52 10
15 32 28 11 11 11 66 42 10
16 33 39 11 15 16 79 47 10
13 40 32 12 9 19 68 41 10
17 38 35 12 16 11 76 47 10
16 41 39 12 15 16 71 43 10
16 36 35 11 10 15 54 33 10
12 43 42 7 10 24 46 30 10
16 30 34 12 15 14 85 52 10
16 31 33 14 11 15 74 44 10
17 32 41 11 13 11 88 55 10
13 32 33 11 14 15 38 11 10
12 37 34 10 18 12 76 47 10
18 37 32 13 16 10 86 53 10
14 33 40 13 14 14 54 33 10
14 34 40 8 14 13 67 44 10
13 33 35 11 14 9 69 42 10
16 38 36 12 14 15 90 55 10
13 33 37 11 12 15 54 33 10
16 31 27 13 14 14 76 46 10
13 38 39 12 15 11 89 54 10
16 37 38 14 15 8 76 47 10
15 36 31 13 15 11 73 45 10
16 31 33 15 13 11 79 47 10
15 39 32 10 17 8 90 55 10
17 44 39 11 17 10 74 44 10
15 33 36 9 19 11 81 53 10
12 35 33 11 15 13 72 44 10
16 32 33 10 13 11 71 42 10
10 28 32 11 9 20 66 40 10
16 40 37 8 15 10 77 46 10
12 27 30 11 15 15 65 40 10
14 37 38 12 15 12 74 46 10
15 32 29 12 16 14 85 53 10
13 28 22 9 11 23 54 33 10
15 34 35 11 14 14 63 42 10
11 30 35 10 11 16 54 35 10
12 35 34 8 15 11 64 40 10
11 31 35 9 13 12 69 41 10
16 32 34 8 15 10 54 33 10
15 30 37 9 16 14 84 51 10
17 30 35 15 14 12 86 53 10
16 31 23 11 15 12 77 46 10
10 40 31 8 16 11 89 55 10
18 32 27 13 16 12 76 47 10
13 36 36 12 11 13 60 38 10
16 32 31 12 12 11 75 46 10
13 35 32 9 9 19 73 46 10
10 38 39 7 16 12 85 53 10
15 42 37 13 13 17 79 47 10
16 34 38 9 16 9 71 41 10
16 35 39 6 12 12 72 44 10
14 38 34 8 9 19 69 43 9
10 33 31 8 13 18 78 51 10
17 36 32 15 13 15 54 33 10
13 32 37 6 14 14 69 43 10
15 33 36 9 19 11 81 53 10
16 34 32 11 13 9 84 51 10
12 32 38 8 12 18 84 50 10
13 34 36 8 13 16 69 46 10
13 27 26 10 10 24 66 43 11
12 31 26 8 14 14 81 47 11
17 38 33 14 16 20 82 50 11
15 34 39 10 10 18 72 43 11
10 24 30 8 11 23 54 33 11
14 30 33 11 14 12 78 48 11
11 26 25 12 12 14 74 44 11
13 34 38 12 9 16 82 50 11
16 27 37 12 9 18 73 41 11
12 37 31 5 11 20 55 34 11
16 36 37 12 16 12 72 44 11
12 41 35 10 9 12 78 47 11
9 29 25 7 13 17 59 35 11
12 36 28 12 16 13 72 44 11
15 32 35 11 13 9 78 44 11
12 37 33 8 9 16 68 43 11
12 30 30 9 12 18 69 41 11
14 31 31 10 16 10 67 41 11
12 38 37 9 11 14 74 42 11
16 36 36 12 14 11 54 33 11
11 35 30 6 13 9 67 41 11
19 31 36 15 15 11 70 44 11
15 38 32 12 14 10 80 48 11
8 22 28 12 16 11 89 55 11
16 32 36 12 13 19 76 44 11
17 36 34 11 14 14 74 43 11
12 39 31 7 15 12 87 52 11
11 28 28 7 13 14 54 30 11
11 32 36 5 11 21 61 39 11
14 32 36 12 11 13 38 11 11
16 38 40 12 14 10 75 44 11
12 32 33 3 15 15 69 42 11
16 35 37 11 11 16 62 41 11
13 32 32 10 15 14 72 44 11
15 37 38 12 12 12 70 44 11
16 34 31 9 14 19 79 48 11
16 33 37 12 14 15 87 53 11
14 33 33 9 8 19 62 37 11
16 26 32 12 13 13 77 44 11
16 30 30 12 9 17 69 44 11
14 24 30 10 15 12 69 40 11
11 34 31 9 17 11 75 42 11
12 34 32 12 13 14 54 35 11
15 33 34 8 15 11 72 43 11
15 34 36 11 15 13 74 45 11
16 35 37 11 14 12 85 55 11
16 35 36 12 16 15 52 31 11
11 36 33 10 13 14 70 44 11
15 34 33 10 16 12 84 50 11
12 34 33 12 9 17 64 40 11
12 41 44 12 16 11 84 53 11
15 32 39 11 11 18 87 54 11
15 30 32 8 10 13 79 49 11
16 35 35 12 11 17 67 40 11
14 28 25 10 15 13 65 41 11
17 33 35 11 17 11 85 52 11
14 39 34 10 14 12 83 52 11
13 36 35 8 8 22 61 36 11
15 36 39 12 15 14 82 52 11
13 35 33 12 11 12 76 46 11
14 38 36 10 16 12 58 31 11
15 33 32 12 10 17 72 44 11
12 31 32 9 15 9 72 44 11
13 34 36 9 9 21 38 11 11
8 32 36 6 16 10 78 46 11
14 31 32 10 19 11 54 33 11
14 33 34 9 12 12 63 34 11
11 34 33 9 8 23 66 42 11
12 34 35 9 11 13 70 43 11
13 34 30 6 14 12 71 43 11
10 33 38 10 9 16 67 44 11
16 32 34 6 15 9 58 36 11
18 41 33 14 13 17 72 46 11
13 34 32 10 16 9 72 44 11
11 36 31 10 11 14 70 43 11
4 37 30 6 12 17 76 50 11
13 36 27 12 13 13 50 33 11
16 29 31 12 10 11 72 43 11
10 37 30 7 11 12 72 44 11
12 27 32 8 12 10 88 53 11
12 35 35 11 8 19 53 34 11
10 28 28 3 12 16 58 35 11
13 35 33 6 12 16 66 40 11
15 37 31 10 15 14 82 53 11
12 29 35 8 11 20 69 42 11
14 32 35 9 13 15 68 43 11
10 36 32 9 14 23 44 29 11
12 19 21 8 10 20 56 36 11
12 21 20 9 12 16 53 30 11
11 31 34 7 15 14 70 42 11
10 33 32 7 13 17 78 47 11
12 36 34 6 13 11 71 44 11
16 33 32 9 13 13 72 45 11
12 37 33 10 12 17 68 44 11
14 34 33 11 12 15 67 43 11
16 35 37 12 9 21 75 43 11
14 31 32 8 9 18 62 40 11
13 37 34 11 15 15 67 41 11
4 35 30 3 10 8 83 52 11
15 27 30 11 14 12 64 38 11
11 34 38 12 15 12 68 41 11
11 40 36 7 7 22 62 39 11
14 29 32 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 time9 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 & 9 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267527&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267527&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267527&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 8.35047 + 0.0347834Connected[t] + 0.0433406Separate[t] + 0.576062Software[t] + 0.0796226Happiness[t] -0.026102Depression[t] + 0.0282903Sport1[t] -0.0326512Sport2[t] -0.404599Month[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  8.35047 +  0.0347834Connected[t] +  0.0433406Separate[t] +  0.576062Software[t] +  0.0796226Happiness[t] -0.026102Depression[t] +  0.0282903Sport1[t] -0.0326512Sport2[t] -0.404599Month[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267527&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  8.35047 +  0.0347834Connected[t] +  0.0433406Separate[t] +  0.576062Software[t] +  0.0796226Happiness[t] -0.026102Depression[t] +  0.0282903Sport1[t] -0.0326512Sport2[t] -0.404599Month[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267527&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267527&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
Learning[t] = + 8.35047 + 0.0347834Connected[t] + 0.0433406Separate[t] + 0.576062Software[t] + 0.0796226Happiness[t] -0.026102Depression[t] + 0.0282903Sport1[t] -0.0326512Sport2[t] -0.404599Month[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.350472.616983.1910.001596130.000798065
Connected0.03478340.03475611.0010.3178790.15894
Separate0.04334060.03528011.2280.2204020.110201
Software0.5760620.052770810.925.1445e-232.57225e-23
Happiness0.07962260.05784491.3760.1698790.0849396
Depression-0.0261020.0424367-0.61510.539050.269525
Sport10.02829030.03776650.74910.4544970.227248
Sport2-0.03265120.0560978-0.5820.5610530.280527
Month-0.4045990.159517-2.5360.01179690.00589846

\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) & 8.35047 & 2.61698 & 3.191 & 0.00159613 & 0.000798065 \tabularnewline
Connected & 0.0347834 & 0.0347561 & 1.001 & 0.317879 & 0.15894 \tabularnewline
Separate & 0.0433406 & 0.0352801 & 1.228 & 0.220402 & 0.110201 \tabularnewline
Software & 0.576062 & 0.0527708 & 10.92 & 5.1445e-23 & 2.57225e-23 \tabularnewline
Happiness & 0.0796226 & 0.0578449 & 1.376 & 0.169879 & 0.0849396 \tabularnewline
Depression & -0.026102 & 0.0424367 & -0.6151 & 0.53905 & 0.269525 \tabularnewline
Sport1 & 0.0282903 & 0.0377665 & 0.7491 & 0.454497 & 0.227248 \tabularnewline
Sport2 & -0.0326512 & 0.0560978 & -0.582 & 0.561053 & 0.280527 \tabularnewline
Month & -0.404599 & 0.159517 & -2.536 & 0.0117969 & 0.00589846 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267527&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]8.35047[/C][C]2.61698[/C][C]3.191[/C][C]0.00159613[/C][C]0.000798065[/C][/ROW]
[ROW][C]Connected[/C][C]0.0347834[/C][C]0.0347561[/C][C]1.001[/C][C]0.317879[/C][C]0.15894[/C][/ROW]
[ROW][C]Separate[/C][C]0.0433406[/C][C]0.0352801[/C][C]1.228[/C][C]0.220402[/C][C]0.110201[/C][/ROW]
[ROW][C]Software[/C][C]0.576062[/C][C]0.0527708[/C][C]10.92[/C][C]5.1445e-23[/C][C]2.57225e-23[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0796226[/C][C]0.0578449[/C][C]1.376[/C][C]0.169879[/C][C]0.0849396[/C][/ROW]
[ROW][C]Depression[/C][C]-0.026102[/C][C]0.0424367[/C][C]-0.6151[/C][C]0.53905[/C][C]0.269525[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0282903[/C][C]0.0377665[/C][C]0.7491[/C][C]0.454497[/C][C]0.227248[/C][/ROW]
[ROW][C]Sport2[/C][C]-0.0326512[/C][C]0.0560978[/C][C]-0.582[/C][C]0.561053[/C][C]0.280527[/C][/ROW]
[ROW][C]Month[/C][C]-0.404599[/C][C]0.159517[/C][C]-2.536[/C][C]0.0117969[/C][C]0.00589846[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267527&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267527&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)8.350472.616983.1910.001596130.000798065
Connected0.03478340.03475611.0010.3178790.15894
Separate0.04334060.03528011.2280.2204020.110201
Software0.5760620.052770810.925.1445e-232.57225e-23
Happiness0.07962260.05784491.3760.1698790.0849396
Depression-0.0261020.0424367-0.61510.539050.269525
Sport10.02829030.03776650.74910.4544970.227248
Sport2-0.03265120.0560978-0.5820.5610530.280527
Month-0.4045990.159517-2.5360.01179690.00589846






Multiple Linear Regression - Regression Statistics
Multiple R0.664098
R-squared0.441026
Adjusted R-squared0.42349
F-TEST (value)25.1492
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.86478
Sum Squared Residuals886.735

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.664098 \tabularnewline
R-squared & 0.441026 \tabularnewline
Adjusted R-squared & 0.42349 \tabularnewline
F-TEST (value) & 25.1492 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.86478 \tabularnewline
Sum Squared Residuals & 886.735 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267527&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.664098[/C][/ROW]
[ROW][C]R-squared[/C][C]0.441026[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.42349[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]25.1492[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.86478[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]886.735[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267527&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267527&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 R0.664098
R-squared0.441026
Adjusted R-squared0.42349
F-TEST (value)25.1492
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.86478
Sum Squared Residuals886.735






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.9509-2.95093
21615.61820.381817
31916.91672.08334
41511.8733.12703
51416.3581-2.35805
61314.736-1.73602
71915.15373.8463
81517.0078-2.00776
91415.9484-1.94845
101514.2980.701964
111614.86261.13738
121616.1018-0.101808
131615.38930.610689
141615.4080.592021
151718.0044-1.0044
161515.3798-0.379816
171514.51060.489441
182016.38343.61662
191815.37482.62517
201615.49350.506468
211615.30280.697231
221615.04120.958823
231916.45312.54694
241614.98921.01076
251716.16680.833158
261716.22120.778791
271614.97171.02828
281516.764-1.76397
291615.76620.233833
301414.0779-0.0778958
311515.746-0.746027
321212.7374-0.737377
331414.7974-0.797419
341615.92850.0714999
351415.6022-1.6022
361012.9219-2.92193
371013.0147-3.01467
381415.79-1.78999
391614.56261.43735
401614.47211.52789
411614.72721.27282
421415.8284-1.82835
432017.5742.42599
441414.1663-0.166311
451414.4929-0.492904
461115.5799-4.57995
471416.6042-2.60423
481515.1942-0.194229
491615.62910.370906
501415.7309-1.73093
511617.1472-1.14715
521414.2217-0.221677
531215.1453-3.14534
541615.86960.130448
55911.3646-2.36455
561412.40071.59933
571616.0108-0.0107717
581615.58760.412356
591515.2487-0.248652
601614.3011.69904
611211.5680.431959
621615.84810.151907
631616.7321-0.732097
641414.8492-0.849166
651615.45320.546782
661715.78671.21327
671816.06641.9336
681814.22363.7764
691215.704-3.70396
701615.44780.552162
711013.0292-3.0292
721414.699-0.69901
731816.82151.17846
741817.04740.952614
751615.06190.938146
761713.26873.73134
771616.2745-0.274453
781614.27411.7259
791315.0335-2.03348
801614.92481.07523
811615.56550.434465
821615.5370.463025
831515.5564-0.556379
841514.70920.290824
851613.97562.02435
861414.0086-0.00857332
871615.22080.779169
881614.70661.29341
891514.35480.645249
901213.7051-1.70508
911716.67830.321736
921615.7430.25698
931515.0196-0.019564
941314.9636-1.9636
951614.69741.30263
961615.68310.316937
971613.58232.4177
981615.76850.231489
991414.3199-0.319858
1001617.0247-1.0247
1011614.57881.4212
1022017.46882.53123
1031514.05230.947695
1041614.95631.04367
1051314.8012-1.80117
1061715.65821.34179
1071615.71490.285055
1081614.26521.73483
1091212.1445-0.144503
1101615.270.729968
1111616.019-0.0190229
1121714.97292.0271
1131314.6235-1.62353
1141214.5611-2.56111
1151816.18261.81743
1161415.8742-1.87424
1171413.06340.936576
1181314.7664-1.76642
1191615.57280.427246
1201314.4067-1.40675
1211615.43920.560835
1221315.8912-2.89117
1231616.9043-0.904258
1241515.8922-0.892153
1251616.9022-0.902236
1261514.70360.296368
1271715.61131.38869
1281513.98391.01614
1291214.7441-2.74408
1301613.99362.00636
1311013.7577-3.75767
1321613.51762.48237
1331214.2162-2.21616
1341415.6238-1.6238
1351515.1699-0.169867
1361312.14220.857844
1371514.50090.499053
1381113.4686-2.46862
1391213.0157-1.01572
1401113.4194-2.41945
1411612.88313.11687
1421513.75591.24415
1431717.0098-0.00977951
1441614.27381.72621
1451013.3567-3.35673
1461815.65272.34725
1471315.0229-2.02288
1481614.9621.03798
1491312.87730.122741
1501012.9839-2.98387
1511516.1495-1.14948
1521614.02761.97243
1531611.91114.08895
1541412.88161.11838
1551012.5111-2.51108
1561716.67830.321736
1571311.77481.22516
1581513.98391.01614
1591614.7221.27795
1601212.9024-0.902449
1611312.72340.276589
1621312.35940.640555
1631212.2197-0.219714
1641716.15590.844074
1651513.49271.50729
1661011.3691-1.36909
1671414.1512-0.151184
1681114.0474-3.04738
1691314.6284-1.62842
1701614.32861.67136
1711210.21041.78963
1721615.22940.770583
1731213.679-1.67896
174911.1422-2.14224
1751214.8132-2.81325
1761514.43670.56328
1771212.0443-0.0443133
1781212.5271-0.527126
1791413.6520.347962
1801213.2424-1.24236
1811614.90291.09713
1821111.2308-0.230817
1831916.63022.36976
1841515.071-0.0709574
185814.5003-6.50026
1861614.73851.26148
1871714.40112.59888
1881212.2769-0.276935
1891111.3376-0.337593
1901110.23350.766461
1911414.7383-0.738347
1921615.40680.593164
193129.554862.44514
1941613.93112.0689
1951313.5896-0.589629
1961514.93250.0675295
1971612.89713.10291
1981615.0180.981991
1991412.34951.65052
2001614.54141.45864
2011613.94462.05541
2021413.32260.677382
2031113.4275-2.42752
2041214.4367-2.43671
2051512.66992.33007
2061514.45870.541348
2071614.46791.53206
2081614.93161.06835
2091113.5563-2.55628
2101513.97791.02206
2111214.2029-2.2029
2121215.7784-3.77844
2131514.1440.85598
2141512.03072.9693
2151614.56851.43152
2161413.07310.926865
2171714.67462.32539
2181413.94240.0576402
2191311.89051.1095
2201515.206-0.205965
2211314.671-1.67102
2221414.1319-0.131921
2231514.30010.699882
2241213.1093-1.10929
2251312.71170.288334
226811.7472-3.74721
2271413.80160.19842
2281413.02030.979733
2291112.2298-1.22976
2301212.8968-0.896838
2311311.24521.75479
2321013.2131-3.21307
2331611.36774.63228
2341815.94742.05258
2351313.8693-0.869329
2361113.343-2.343
237410.9727-6.9727
2381314.2678-1.26782
2391614.30691.69309
2401011.6824-1.68239
2411212.2879-0.287912
2421213.5012-1.50119
243108.851421.14858
2441311.10291.89714
2451513.70921.29075
2461211.96850.0314943
2471412.87771.12227
2481012.5358-2.5358
2491210.76241.23759
2501211.73940.260609
2511111.9221-0.922062
2521011.7305-1.73046
2531211.4020.598034
2541612.88263.11744
2551213.3766-1.37655
2561413.90480.0951709
2571614.51991.48012
2581411.66832.33172
2591314.3567-1.35669
26049.38335-5.38335
2611513.84731.15274
2621115.1084-4.10836
2631111.3476-0.347629
2641412.91441.08555

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 15.9509 & -2.95093 \tabularnewline
2 & 16 & 15.6182 & 0.381817 \tabularnewline
3 & 19 & 16.9167 & 2.08334 \tabularnewline
4 & 15 & 11.873 & 3.12703 \tabularnewline
5 & 14 & 16.3581 & -2.35805 \tabularnewline
6 & 13 & 14.736 & -1.73602 \tabularnewline
7 & 19 & 15.1537 & 3.8463 \tabularnewline
8 & 15 & 17.0078 & -2.00776 \tabularnewline
9 & 14 & 15.9484 & -1.94845 \tabularnewline
10 & 15 & 14.298 & 0.701964 \tabularnewline
11 & 16 & 14.8626 & 1.13738 \tabularnewline
12 & 16 & 16.1018 & -0.101808 \tabularnewline
13 & 16 & 15.3893 & 0.610689 \tabularnewline
14 & 16 & 15.408 & 0.592021 \tabularnewline
15 & 17 & 18.0044 & -1.0044 \tabularnewline
16 & 15 & 15.3798 & -0.379816 \tabularnewline
17 & 15 & 14.5106 & 0.489441 \tabularnewline
18 & 20 & 16.3834 & 3.61662 \tabularnewline
19 & 18 & 15.3748 & 2.62517 \tabularnewline
20 & 16 & 15.4935 & 0.506468 \tabularnewline
21 & 16 & 15.3028 & 0.697231 \tabularnewline
22 & 16 & 15.0412 & 0.958823 \tabularnewline
23 & 19 & 16.4531 & 2.54694 \tabularnewline
24 & 16 & 14.9892 & 1.01076 \tabularnewline
25 & 17 & 16.1668 & 0.833158 \tabularnewline
26 & 17 & 16.2212 & 0.778791 \tabularnewline
27 & 16 & 14.9717 & 1.02828 \tabularnewline
28 & 15 & 16.764 & -1.76397 \tabularnewline
29 & 16 & 15.7662 & 0.233833 \tabularnewline
30 & 14 & 14.0779 & -0.0778958 \tabularnewline
31 & 15 & 15.746 & -0.746027 \tabularnewline
32 & 12 & 12.7374 & -0.737377 \tabularnewline
33 & 14 & 14.7974 & -0.797419 \tabularnewline
34 & 16 & 15.9285 & 0.0714999 \tabularnewline
35 & 14 & 15.6022 & -1.6022 \tabularnewline
36 & 10 & 12.9219 & -2.92193 \tabularnewline
37 & 10 & 13.0147 & -3.01467 \tabularnewline
38 & 14 & 15.79 & -1.78999 \tabularnewline
39 & 16 & 14.5626 & 1.43735 \tabularnewline
40 & 16 & 14.4721 & 1.52789 \tabularnewline
41 & 16 & 14.7272 & 1.27282 \tabularnewline
42 & 14 & 15.8284 & -1.82835 \tabularnewline
43 & 20 & 17.574 & 2.42599 \tabularnewline
44 & 14 & 14.1663 & -0.166311 \tabularnewline
45 & 14 & 14.4929 & -0.492904 \tabularnewline
46 & 11 & 15.5799 & -4.57995 \tabularnewline
47 & 14 & 16.6042 & -2.60423 \tabularnewline
48 & 15 & 15.1942 & -0.194229 \tabularnewline
49 & 16 & 15.6291 & 0.370906 \tabularnewline
50 & 14 & 15.7309 & -1.73093 \tabularnewline
51 & 16 & 17.1472 & -1.14715 \tabularnewline
52 & 14 & 14.2217 & -0.221677 \tabularnewline
53 & 12 & 15.1453 & -3.14534 \tabularnewline
54 & 16 & 15.8696 & 0.130448 \tabularnewline
55 & 9 & 11.3646 & -2.36455 \tabularnewline
56 & 14 & 12.4007 & 1.59933 \tabularnewline
57 & 16 & 16.0108 & -0.0107717 \tabularnewline
58 & 16 & 15.5876 & 0.412356 \tabularnewline
59 & 15 & 15.2487 & -0.248652 \tabularnewline
60 & 16 & 14.301 & 1.69904 \tabularnewline
61 & 12 & 11.568 & 0.431959 \tabularnewline
62 & 16 & 15.8481 & 0.151907 \tabularnewline
63 & 16 & 16.7321 & -0.732097 \tabularnewline
64 & 14 & 14.8492 & -0.849166 \tabularnewline
65 & 16 & 15.4532 & 0.546782 \tabularnewline
66 & 17 & 15.7867 & 1.21327 \tabularnewline
67 & 18 & 16.0664 & 1.9336 \tabularnewline
68 & 18 & 14.2236 & 3.7764 \tabularnewline
69 & 12 & 15.704 & -3.70396 \tabularnewline
70 & 16 & 15.4478 & 0.552162 \tabularnewline
71 & 10 & 13.0292 & -3.0292 \tabularnewline
72 & 14 & 14.699 & -0.69901 \tabularnewline
73 & 18 & 16.8215 & 1.17846 \tabularnewline
74 & 18 & 17.0474 & 0.952614 \tabularnewline
75 & 16 & 15.0619 & 0.938146 \tabularnewline
76 & 17 & 13.2687 & 3.73134 \tabularnewline
77 & 16 & 16.2745 & -0.274453 \tabularnewline
78 & 16 & 14.2741 & 1.7259 \tabularnewline
79 & 13 & 15.0335 & -2.03348 \tabularnewline
80 & 16 & 14.9248 & 1.07523 \tabularnewline
81 & 16 & 15.5655 & 0.434465 \tabularnewline
82 & 16 & 15.537 & 0.463025 \tabularnewline
83 & 15 & 15.5564 & -0.556379 \tabularnewline
84 & 15 & 14.7092 & 0.290824 \tabularnewline
85 & 16 & 13.9756 & 2.02435 \tabularnewline
86 & 14 & 14.0086 & -0.00857332 \tabularnewline
87 & 16 & 15.2208 & 0.779169 \tabularnewline
88 & 16 & 14.7066 & 1.29341 \tabularnewline
89 & 15 & 14.3548 & 0.645249 \tabularnewline
90 & 12 & 13.7051 & -1.70508 \tabularnewline
91 & 17 & 16.6783 & 0.321736 \tabularnewline
92 & 16 & 15.743 & 0.25698 \tabularnewline
93 & 15 & 15.0196 & -0.019564 \tabularnewline
94 & 13 & 14.9636 & -1.9636 \tabularnewline
95 & 16 & 14.6974 & 1.30263 \tabularnewline
96 & 16 & 15.6831 & 0.316937 \tabularnewline
97 & 16 & 13.5823 & 2.4177 \tabularnewline
98 & 16 & 15.7685 & 0.231489 \tabularnewline
99 & 14 & 14.3199 & -0.319858 \tabularnewline
100 & 16 & 17.0247 & -1.0247 \tabularnewline
101 & 16 & 14.5788 & 1.4212 \tabularnewline
102 & 20 & 17.4688 & 2.53123 \tabularnewline
103 & 15 & 14.0523 & 0.947695 \tabularnewline
104 & 16 & 14.9563 & 1.04367 \tabularnewline
105 & 13 & 14.8012 & -1.80117 \tabularnewline
106 & 17 & 15.6582 & 1.34179 \tabularnewline
107 & 16 & 15.7149 & 0.285055 \tabularnewline
108 & 16 & 14.2652 & 1.73483 \tabularnewline
109 & 12 & 12.1445 & -0.144503 \tabularnewline
110 & 16 & 15.27 & 0.729968 \tabularnewline
111 & 16 & 16.019 & -0.0190229 \tabularnewline
112 & 17 & 14.9729 & 2.0271 \tabularnewline
113 & 13 & 14.6235 & -1.62353 \tabularnewline
114 & 12 & 14.5611 & -2.56111 \tabularnewline
115 & 18 & 16.1826 & 1.81743 \tabularnewline
116 & 14 & 15.8742 & -1.87424 \tabularnewline
117 & 14 & 13.0634 & 0.936576 \tabularnewline
118 & 13 & 14.7664 & -1.76642 \tabularnewline
119 & 16 & 15.5728 & 0.427246 \tabularnewline
120 & 13 & 14.4067 & -1.40675 \tabularnewline
121 & 16 & 15.4392 & 0.560835 \tabularnewline
122 & 13 & 15.8912 & -2.89117 \tabularnewline
123 & 16 & 16.9043 & -0.904258 \tabularnewline
124 & 15 & 15.8922 & -0.892153 \tabularnewline
125 & 16 & 16.9022 & -0.902236 \tabularnewline
126 & 15 & 14.7036 & 0.296368 \tabularnewline
127 & 17 & 15.6113 & 1.38869 \tabularnewline
128 & 15 & 13.9839 & 1.01614 \tabularnewline
129 & 12 & 14.7441 & -2.74408 \tabularnewline
130 & 16 & 13.9936 & 2.00636 \tabularnewline
131 & 10 & 13.7577 & -3.75767 \tabularnewline
132 & 16 & 13.5176 & 2.48237 \tabularnewline
133 & 12 & 14.2162 & -2.21616 \tabularnewline
134 & 14 & 15.6238 & -1.6238 \tabularnewline
135 & 15 & 15.1699 & -0.169867 \tabularnewline
136 & 13 & 12.1422 & 0.857844 \tabularnewline
137 & 15 & 14.5009 & 0.499053 \tabularnewline
138 & 11 & 13.4686 & -2.46862 \tabularnewline
139 & 12 & 13.0157 & -1.01572 \tabularnewline
140 & 11 & 13.4194 & -2.41945 \tabularnewline
141 & 16 & 12.8831 & 3.11687 \tabularnewline
142 & 15 & 13.7559 & 1.24415 \tabularnewline
143 & 17 & 17.0098 & -0.00977951 \tabularnewline
144 & 16 & 14.2738 & 1.72621 \tabularnewline
145 & 10 & 13.3567 & -3.35673 \tabularnewline
146 & 18 & 15.6527 & 2.34725 \tabularnewline
147 & 13 & 15.0229 & -2.02288 \tabularnewline
148 & 16 & 14.962 & 1.03798 \tabularnewline
149 & 13 & 12.8773 & 0.122741 \tabularnewline
150 & 10 & 12.9839 & -2.98387 \tabularnewline
151 & 15 & 16.1495 & -1.14948 \tabularnewline
152 & 16 & 14.0276 & 1.97243 \tabularnewline
153 & 16 & 11.9111 & 4.08895 \tabularnewline
154 & 14 & 12.8816 & 1.11838 \tabularnewline
155 & 10 & 12.5111 & -2.51108 \tabularnewline
156 & 17 & 16.6783 & 0.321736 \tabularnewline
157 & 13 & 11.7748 & 1.22516 \tabularnewline
158 & 15 & 13.9839 & 1.01614 \tabularnewline
159 & 16 & 14.722 & 1.27795 \tabularnewline
160 & 12 & 12.9024 & -0.902449 \tabularnewline
161 & 13 & 12.7234 & 0.276589 \tabularnewline
162 & 13 & 12.3594 & 0.640555 \tabularnewline
163 & 12 & 12.2197 & -0.219714 \tabularnewline
164 & 17 & 16.1559 & 0.844074 \tabularnewline
165 & 15 & 13.4927 & 1.50729 \tabularnewline
166 & 10 & 11.3691 & -1.36909 \tabularnewline
167 & 14 & 14.1512 & -0.151184 \tabularnewline
168 & 11 & 14.0474 & -3.04738 \tabularnewline
169 & 13 & 14.6284 & -1.62842 \tabularnewline
170 & 16 & 14.3286 & 1.67136 \tabularnewline
171 & 12 & 10.2104 & 1.78963 \tabularnewline
172 & 16 & 15.2294 & 0.770583 \tabularnewline
173 & 12 & 13.679 & -1.67896 \tabularnewline
174 & 9 & 11.1422 & -2.14224 \tabularnewline
175 & 12 & 14.8132 & -2.81325 \tabularnewline
176 & 15 & 14.4367 & 0.56328 \tabularnewline
177 & 12 & 12.0443 & -0.0443133 \tabularnewline
178 & 12 & 12.5271 & -0.527126 \tabularnewline
179 & 14 & 13.652 & 0.347962 \tabularnewline
180 & 12 & 13.2424 & -1.24236 \tabularnewline
181 & 16 & 14.9029 & 1.09713 \tabularnewline
182 & 11 & 11.2308 & -0.230817 \tabularnewline
183 & 19 & 16.6302 & 2.36976 \tabularnewline
184 & 15 & 15.071 & -0.0709574 \tabularnewline
185 & 8 & 14.5003 & -6.50026 \tabularnewline
186 & 16 & 14.7385 & 1.26148 \tabularnewline
187 & 17 & 14.4011 & 2.59888 \tabularnewline
188 & 12 & 12.2769 & -0.276935 \tabularnewline
189 & 11 & 11.3376 & -0.337593 \tabularnewline
190 & 11 & 10.2335 & 0.766461 \tabularnewline
191 & 14 & 14.7383 & -0.738347 \tabularnewline
192 & 16 & 15.4068 & 0.593164 \tabularnewline
193 & 12 & 9.55486 & 2.44514 \tabularnewline
194 & 16 & 13.9311 & 2.0689 \tabularnewline
195 & 13 & 13.5896 & -0.589629 \tabularnewline
196 & 15 & 14.9325 & 0.0675295 \tabularnewline
197 & 16 & 12.8971 & 3.10291 \tabularnewline
198 & 16 & 15.018 & 0.981991 \tabularnewline
199 & 14 & 12.3495 & 1.65052 \tabularnewline
200 & 16 & 14.5414 & 1.45864 \tabularnewline
201 & 16 & 13.9446 & 2.05541 \tabularnewline
202 & 14 & 13.3226 & 0.677382 \tabularnewline
203 & 11 & 13.4275 & -2.42752 \tabularnewline
204 & 12 & 14.4367 & -2.43671 \tabularnewline
205 & 15 & 12.6699 & 2.33007 \tabularnewline
206 & 15 & 14.4587 & 0.541348 \tabularnewline
207 & 16 & 14.4679 & 1.53206 \tabularnewline
208 & 16 & 14.9316 & 1.06835 \tabularnewline
209 & 11 & 13.5563 & -2.55628 \tabularnewline
210 & 15 & 13.9779 & 1.02206 \tabularnewline
211 & 12 & 14.2029 & -2.2029 \tabularnewline
212 & 12 & 15.7784 & -3.77844 \tabularnewline
213 & 15 & 14.144 & 0.85598 \tabularnewline
214 & 15 & 12.0307 & 2.9693 \tabularnewline
215 & 16 & 14.5685 & 1.43152 \tabularnewline
216 & 14 & 13.0731 & 0.926865 \tabularnewline
217 & 17 & 14.6746 & 2.32539 \tabularnewline
218 & 14 & 13.9424 & 0.0576402 \tabularnewline
219 & 13 & 11.8905 & 1.1095 \tabularnewline
220 & 15 & 15.206 & -0.205965 \tabularnewline
221 & 13 & 14.671 & -1.67102 \tabularnewline
222 & 14 & 14.1319 & -0.131921 \tabularnewline
223 & 15 & 14.3001 & 0.699882 \tabularnewline
224 & 12 & 13.1093 & -1.10929 \tabularnewline
225 & 13 & 12.7117 & 0.288334 \tabularnewline
226 & 8 & 11.7472 & -3.74721 \tabularnewline
227 & 14 & 13.8016 & 0.19842 \tabularnewline
228 & 14 & 13.0203 & 0.979733 \tabularnewline
229 & 11 & 12.2298 & -1.22976 \tabularnewline
230 & 12 & 12.8968 & -0.896838 \tabularnewline
231 & 13 & 11.2452 & 1.75479 \tabularnewline
232 & 10 & 13.2131 & -3.21307 \tabularnewline
233 & 16 & 11.3677 & 4.63228 \tabularnewline
234 & 18 & 15.9474 & 2.05258 \tabularnewline
235 & 13 & 13.8693 & -0.869329 \tabularnewline
236 & 11 & 13.343 & -2.343 \tabularnewline
237 & 4 & 10.9727 & -6.9727 \tabularnewline
238 & 13 & 14.2678 & -1.26782 \tabularnewline
239 & 16 & 14.3069 & 1.69309 \tabularnewline
240 & 10 & 11.6824 & -1.68239 \tabularnewline
241 & 12 & 12.2879 & -0.287912 \tabularnewline
242 & 12 & 13.5012 & -1.50119 \tabularnewline
243 & 10 & 8.85142 & 1.14858 \tabularnewline
244 & 13 & 11.1029 & 1.89714 \tabularnewline
245 & 15 & 13.7092 & 1.29075 \tabularnewline
246 & 12 & 11.9685 & 0.0314943 \tabularnewline
247 & 14 & 12.8777 & 1.12227 \tabularnewline
248 & 10 & 12.5358 & -2.5358 \tabularnewline
249 & 12 & 10.7624 & 1.23759 \tabularnewline
250 & 12 & 11.7394 & 0.260609 \tabularnewline
251 & 11 & 11.9221 & -0.922062 \tabularnewline
252 & 10 & 11.7305 & -1.73046 \tabularnewline
253 & 12 & 11.402 & 0.598034 \tabularnewline
254 & 16 & 12.8826 & 3.11744 \tabularnewline
255 & 12 & 13.3766 & -1.37655 \tabularnewline
256 & 14 & 13.9048 & 0.0951709 \tabularnewline
257 & 16 & 14.5199 & 1.48012 \tabularnewline
258 & 14 & 11.6683 & 2.33172 \tabularnewline
259 & 13 & 14.3567 & -1.35669 \tabularnewline
260 & 4 & 9.38335 & -5.38335 \tabularnewline
261 & 15 & 13.8473 & 1.15274 \tabularnewline
262 & 11 & 15.1084 & -4.10836 \tabularnewline
263 & 11 & 11.3476 & -0.347629 \tabularnewline
264 & 14 & 12.9144 & 1.08555 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267527&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]13[/C][C]15.9509[/C][C]-2.95093[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.6182[/C][C]0.381817[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]16.9167[/C][C]2.08334[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]11.873[/C][C]3.12703[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.3581[/C][C]-2.35805[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.736[/C][C]-1.73602[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.1537[/C][C]3.8463[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]17.0078[/C][C]-2.00776[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.9484[/C][C]-1.94845[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.298[/C][C]0.701964[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.8626[/C][C]1.13738[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1018[/C][C]-0.101808[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.3893[/C][C]0.610689[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.408[/C][C]0.592021[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]18.0044[/C][C]-1.0044[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.3798[/C][C]-0.379816[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.5106[/C][C]0.489441[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.3834[/C][C]3.61662[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.3748[/C][C]2.62517[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.4935[/C][C]0.506468[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.3028[/C][C]0.697231[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.0412[/C][C]0.958823[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.4531[/C][C]2.54694[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.9892[/C][C]1.01076[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.1668[/C][C]0.833158[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.2212[/C][C]0.778791[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.9717[/C][C]1.02828[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.764[/C][C]-1.76397[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.7662[/C][C]0.233833[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.0779[/C][C]-0.0778958[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.746[/C][C]-0.746027[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.7374[/C][C]-0.737377[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.7974[/C][C]-0.797419[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.9285[/C][C]0.0714999[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.6022[/C][C]-1.6022[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.9219[/C][C]-2.92193[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]13.0147[/C][C]-3.01467[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.79[/C][C]-1.78999[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.5626[/C][C]1.43735[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.4721[/C][C]1.52789[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.7272[/C][C]1.27282[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.8284[/C][C]-1.82835[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.574[/C][C]2.42599[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.1663[/C][C]-0.166311[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.4929[/C][C]-0.492904[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.5799[/C][C]-4.57995[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.6042[/C][C]-2.60423[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.1942[/C][C]-0.194229[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.6291[/C][C]0.370906[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.7309[/C][C]-1.73093[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]17.1472[/C][C]-1.14715[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.2217[/C][C]-0.221677[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]15.1453[/C][C]-3.14534[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.8696[/C][C]0.130448[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.3646[/C][C]-2.36455[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.4007[/C][C]1.59933[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]16.0108[/C][C]-0.0107717[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.5876[/C][C]0.412356[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.2487[/C][C]-0.248652[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.301[/C][C]1.69904[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.568[/C][C]0.431959[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.8481[/C][C]0.151907[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.7321[/C][C]-0.732097[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.8492[/C][C]-0.849166[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.4532[/C][C]0.546782[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]15.7867[/C][C]1.21327[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.0664[/C][C]1.9336[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.2236[/C][C]3.7764[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.704[/C][C]-3.70396[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.4478[/C][C]0.552162[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.0292[/C][C]-3.0292[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.699[/C][C]-0.69901[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.8215[/C][C]1.17846[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.0474[/C][C]0.952614[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.0619[/C][C]0.938146[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.2687[/C][C]3.73134[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.2745[/C][C]-0.274453[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.2741[/C][C]1.7259[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.0335[/C][C]-2.03348[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]14.9248[/C][C]1.07523[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.5655[/C][C]0.434465[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.537[/C][C]0.463025[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.5564[/C][C]-0.556379[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.7092[/C][C]0.290824[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]13.9756[/C][C]2.02435[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.0086[/C][C]-0.00857332[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.2208[/C][C]0.779169[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.7066[/C][C]1.29341[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.3548[/C][C]0.645249[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.7051[/C][C]-1.70508[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.6783[/C][C]0.321736[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.743[/C][C]0.25698[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.0196[/C][C]-0.019564[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.9636[/C][C]-1.9636[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.6974[/C][C]1.30263[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.6831[/C][C]0.316937[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.5823[/C][C]2.4177[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.7685[/C][C]0.231489[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.3199[/C][C]-0.319858[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.0247[/C][C]-1.0247[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.5788[/C][C]1.4212[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.4688[/C][C]2.53123[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.0523[/C][C]0.947695[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.9563[/C][C]1.04367[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.8012[/C][C]-1.80117[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.6582[/C][C]1.34179[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7149[/C][C]0.285055[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.2652[/C][C]1.73483[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.1445[/C][C]-0.144503[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.27[/C][C]0.729968[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.019[/C][C]-0.0190229[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]14.9729[/C][C]2.0271[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.6235[/C][C]-1.62353[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.5611[/C][C]-2.56111[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.1826[/C][C]1.81743[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.8742[/C][C]-1.87424[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.0634[/C][C]0.936576[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7664[/C][C]-1.76642[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5728[/C][C]0.427246[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.4067[/C][C]-1.40675[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.4392[/C][C]0.560835[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.8912[/C][C]-2.89117[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.9043[/C][C]-0.904258[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.8922[/C][C]-0.892153[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.9022[/C][C]-0.902236[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.7036[/C][C]0.296368[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.6113[/C][C]1.38869[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]13.9839[/C][C]1.01614[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.7441[/C][C]-2.74408[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9936[/C][C]2.00636[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.7577[/C][C]-3.75767[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.5176[/C][C]2.48237[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.2162[/C][C]-2.21616[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.6238[/C][C]-1.6238[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.1699[/C][C]-0.169867[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.1422[/C][C]0.857844[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.5009[/C][C]0.499053[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.4686[/C][C]-2.46862[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]13.0157[/C][C]-1.01572[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.4194[/C][C]-2.41945[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8831[/C][C]3.11687[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.7559[/C][C]1.24415[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]17.0098[/C][C]-0.00977951[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.2738[/C][C]1.72621[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.3567[/C][C]-3.35673[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.6527[/C][C]2.34725[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.0229[/C][C]-2.02288[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.962[/C][C]1.03798[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.8773[/C][C]0.122741[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.9839[/C][C]-2.98387[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]16.1495[/C][C]-1.14948[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]14.0276[/C][C]1.97243[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.9111[/C][C]4.08895[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.8816[/C][C]1.11838[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.5111[/C][C]-2.51108[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.6783[/C][C]0.321736[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.7748[/C][C]1.22516[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.9839[/C][C]1.01614[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.722[/C][C]1.27795[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.9024[/C][C]-0.902449[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.7234[/C][C]0.276589[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.3594[/C][C]0.640555[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.2197[/C][C]-0.219714[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.1559[/C][C]0.844074[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.4927[/C][C]1.50729[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.3691[/C][C]-1.36909[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.1512[/C][C]-0.151184[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.0474[/C][C]-3.04738[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.6284[/C][C]-1.62842[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.3286[/C][C]1.67136[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.2104[/C][C]1.78963[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.2294[/C][C]0.770583[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.679[/C][C]-1.67896[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.1422[/C][C]-2.14224[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.8132[/C][C]-2.81325[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.4367[/C][C]0.56328[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.0443[/C][C]-0.0443133[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.5271[/C][C]-0.527126[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.652[/C][C]0.347962[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.2424[/C][C]-1.24236[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]14.9029[/C][C]1.09713[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.2308[/C][C]-0.230817[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]16.6302[/C][C]2.36976[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.071[/C][C]-0.0709574[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.5003[/C][C]-6.50026[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.7385[/C][C]1.26148[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.4011[/C][C]2.59888[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.2769[/C][C]-0.276935[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.3376[/C][C]-0.337593[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.2335[/C][C]0.766461[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.7383[/C][C]-0.738347[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.4068[/C][C]0.593164[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.55486[/C][C]2.44514[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]13.9311[/C][C]2.0689[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.5896[/C][C]-0.589629[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]14.9325[/C][C]0.0675295[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.8971[/C][C]3.10291[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.018[/C][C]0.981991[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.3495[/C][C]1.65052[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.5414[/C][C]1.45864[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]13.9446[/C][C]2.05541[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.3226[/C][C]0.677382[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.4275[/C][C]-2.42752[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.4367[/C][C]-2.43671[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.6699[/C][C]2.33007[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.4587[/C][C]0.541348[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.4679[/C][C]1.53206[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]14.9316[/C][C]1.06835[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.5563[/C][C]-2.55628[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.9779[/C][C]1.02206[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.2029[/C][C]-2.2029[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.7784[/C][C]-3.77844[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.144[/C][C]0.85598[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.0307[/C][C]2.9693[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.5685[/C][C]1.43152[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.0731[/C][C]0.926865[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.6746[/C][C]2.32539[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.9424[/C][C]0.0576402[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.8905[/C][C]1.1095[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.206[/C][C]-0.205965[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.671[/C][C]-1.67102[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.1319[/C][C]-0.131921[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.3001[/C][C]0.699882[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.1093[/C][C]-1.10929[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.7117[/C][C]0.288334[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.7472[/C][C]-3.74721[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.8016[/C][C]0.19842[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]13.0203[/C][C]0.979733[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.2298[/C][C]-1.22976[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.8968[/C][C]-0.896838[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.2452[/C][C]1.75479[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.2131[/C][C]-3.21307[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.3677[/C][C]4.63228[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.9474[/C][C]2.05258[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.8693[/C][C]-0.869329[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.343[/C][C]-2.343[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.9727[/C][C]-6.9727[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.2678[/C][C]-1.26782[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.3069[/C][C]1.69309[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.6824[/C][C]-1.68239[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.2879[/C][C]-0.287912[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.5012[/C][C]-1.50119[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.85142[/C][C]1.14858[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]11.1029[/C][C]1.89714[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.7092[/C][C]1.29075[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]11.9685[/C][C]0.0314943[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]12.8777[/C][C]1.12227[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.5358[/C][C]-2.5358[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.7624[/C][C]1.23759[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.7394[/C][C]0.260609[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.9221[/C][C]-0.922062[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.7305[/C][C]-1.73046[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.402[/C][C]0.598034[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.8826[/C][C]3.11744[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.3766[/C][C]-1.37655[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.9048[/C][C]0.0951709[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.5199[/C][C]1.48012[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.6683[/C][C]2.33172[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.3567[/C][C]-1.35669[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.38335[/C][C]-5.38335[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.8473[/C][C]1.15274[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]15.1084[/C][C]-4.10836[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.3476[/C][C]-0.347629[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.9144[/C][C]1.08555[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267527&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267527&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
11315.9509-2.95093
21615.61820.381817
31916.91672.08334
41511.8733.12703
51416.3581-2.35805
61314.736-1.73602
71915.15373.8463
81517.0078-2.00776
91415.9484-1.94845
101514.2980.701964
111614.86261.13738
121616.1018-0.101808
131615.38930.610689
141615.4080.592021
151718.0044-1.0044
161515.3798-0.379816
171514.51060.489441
182016.38343.61662
191815.37482.62517
201615.49350.506468
211615.30280.697231
221615.04120.958823
231916.45312.54694
241614.98921.01076
251716.16680.833158
261716.22120.778791
271614.97171.02828
281516.764-1.76397
291615.76620.233833
301414.0779-0.0778958
311515.746-0.746027
321212.7374-0.737377
331414.7974-0.797419
341615.92850.0714999
351415.6022-1.6022
361012.9219-2.92193
371013.0147-3.01467
381415.79-1.78999
391614.56261.43735
401614.47211.52789
411614.72721.27282
421415.8284-1.82835
432017.5742.42599
441414.1663-0.166311
451414.4929-0.492904
461115.5799-4.57995
471416.6042-2.60423
481515.1942-0.194229
491615.62910.370906
501415.7309-1.73093
511617.1472-1.14715
521414.2217-0.221677
531215.1453-3.14534
541615.86960.130448
55911.3646-2.36455
561412.40071.59933
571616.0108-0.0107717
581615.58760.412356
591515.2487-0.248652
601614.3011.69904
611211.5680.431959
621615.84810.151907
631616.7321-0.732097
641414.8492-0.849166
651615.45320.546782
661715.78671.21327
671816.06641.9336
681814.22363.7764
691215.704-3.70396
701615.44780.552162
711013.0292-3.0292
721414.699-0.69901
731816.82151.17846
741817.04740.952614
751615.06190.938146
761713.26873.73134
771616.2745-0.274453
781614.27411.7259
791315.0335-2.03348
801614.92481.07523
811615.56550.434465
821615.5370.463025
831515.5564-0.556379
841514.70920.290824
851613.97562.02435
861414.0086-0.00857332
871615.22080.779169
881614.70661.29341
891514.35480.645249
901213.7051-1.70508
911716.67830.321736
921615.7430.25698
931515.0196-0.019564
941314.9636-1.9636
951614.69741.30263
961615.68310.316937
971613.58232.4177
981615.76850.231489
991414.3199-0.319858
1001617.0247-1.0247
1011614.57881.4212
1022017.46882.53123
1031514.05230.947695
1041614.95631.04367
1051314.8012-1.80117
1061715.65821.34179
1071615.71490.285055
1081614.26521.73483
1091212.1445-0.144503
1101615.270.729968
1111616.019-0.0190229
1121714.97292.0271
1131314.6235-1.62353
1141214.5611-2.56111
1151816.18261.81743
1161415.8742-1.87424
1171413.06340.936576
1181314.7664-1.76642
1191615.57280.427246
1201314.4067-1.40675
1211615.43920.560835
1221315.8912-2.89117
1231616.9043-0.904258
1241515.8922-0.892153
1251616.9022-0.902236
1261514.70360.296368
1271715.61131.38869
1281513.98391.01614
1291214.7441-2.74408
1301613.99362.00636
1311013.7577-3.75767
1321613.51762.48237
1331214.2162-2.21616
1341415.6238-1.6238
1351515.1699-0.169867
1361312.14220.857844
1371514.50090.499053
1381113.4686-2.46862
1391213.0157-1.01572
1401113.4194-2.41945
1411612.88313.11687
1421513.75591.24415
1431717.0098-0.00977951
1441614.27381.72621
1451013.3567-3.35673
1461815.65272.34725
1471315.0229-2.02288
1481614.9621.03798
1491312.87730.122741
1501012.9839-2.98387
1511516.1495-1.14948
1521614.02761.97243
1531611.91114.08895
1541412.88161.11838
1551012.5111-2.51108
1561716.67830.321736
1571311.77481.22516
1581513.98391.01614
1591614.7221.27795
1601212.9024-0.902449
1611312.72340.276589
1621312.35940.640555
1631212.2197-0.219714
1641716.15590.844074
1651513.49271.50729
1661011.3691-1.36909
1671414.1512-0.151184
1681114.0474-3.04738
1691314.6284-1.62842
1701614.32861.67136
1711210.21041.78963
1721615.22940.770583
1731213.679-1.67896
174911.1422-2.14224
1751214.8132-2.81325
1761514.43670.56328
1771212.0443-0.0443133
1781212.5271-0.527126
1791413.6520.347962
1801213.2424-1.24236
1811614.90291.09713
1821111.2308-0.230817
1831916.63022.36976
1841515.071-0.0709574
185814.5003-6.50026
1861614.73851.26148
1871714.40112.59888
1881212.2769-0.276935
1891111.3376-0.337593
1901110.23350.766461
1911414.7383-0.738347
1921615.40680.593164
193129.554862.44514
1941613.93112.0689
1951313.5896-0.589629
1961514.93250.0675295
1971612.89713.10291
1981615.0180.981991
1991412.34951.65052
2001614.54141.45864
2011613.94462.05541
2021413.32260.677382
2031113.4275-2.42752
2041214.4367-2.43671
2051512.66992.33007
2061514.45870.541348
2071614.46791.53206
2081614.93161.06835
2091113.5563-2.55628
2101513.97791.02206
2111214.2029-2.2029
2121215.7784-3.77844
2131514.1440.85598
2141512.03072.9693
2151614.56851.43152
2161413.07310.926865
2171714.67462.32539
2181413.94240.0576402
2191311.89051.1095
2201515.206-0.205965
2211314.671-1.67102
2221414.1319-0.131921
2231514.30010.699882
2241213.1093-1.10929
2251312.71170.288334
226811.7472-3.74721
2271413.80160.19842
2281413.02030.979733
2291112.2298-1.22976
2301212.8968-0.896838
2311311.24521.75479
2321013.2131-3.21307
2331611.36774.63228
2341815.94742.05258
2351313.8693-0.869329
2361113.343-2.343
237410.9727-6.9727
2381314.2678-1.26782
2391614.30691.69309
2401011.6824-1.68239
2411212.2879-0.287912
2421213.5012-1.50119
243108.851421.14858
2441311.10291.89714
2451513.70921.29075
2461211.96850.0314943
2471412.87771.12227
2481012.5358-2.5358
2491210.76241.23759
2501211.73940.260609
2511111.9221-0.922062
2521011.7305-1.73046
2531211.4020.598034
2541612.88263.11744
2551213.3766-1.37655
2561413.90480.0951709
2571614.51991.48012
2581411.66832.33172
2591314.3567-1.35669
26049.38335-5.38335
2611513.84731.15274
2621115.1084-4.10836
2631111.3476-0.347629
2641412.91441.08555






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.2492720.4985450.750728
130.1689540.3379080.831046
140.1886520.3773050.811348
150.1138220.2276440.886178
160.07735820.1547160.922642
170.111090.222180.88891
180.3502970.7005940.649703
190.2730760.5461520.726924
200.2003650.400730.799635
210.1473290.2946580.852671
220.142430.284860.85757
230.3296140.6592270.670386
240.3961080.7922160.603892
250.3646440.7292880.635356
260.3430140.6860280.656986
270.4195220.8390440.580478
280.4310390.8620790.568961
290.4111780.8223570.588822
300.4445630.8891260.555437
310.3891820.7783640.610818
320.3466210.6932420.653379
330.3166770.6333540.683323
340.2756750.551350.724325
350.233140.4662790.76686
360.3636240.7272480.636376
370.400480.800960.59952
380.3925180.7850370.607482
390.4206470.8412940.579353
400.3940370.7880730.605963
410.3526090.7052170.647391
420.3178160.6356310.682184
430.3306030.6612060.669397
440.2841930.5683860.715807
450.2593070.5186150.740693
460.4573730.9147460.542627
470.6130150.773970.386985
480.5647910.8704180.435209
490.5501160.8997680.449884
500.5388870.9222260.461113
510.4960290.9920580.503971
520.4489770.8979530.551023
530.469410.938820.53059
540.4498340.8996680.550166
550.4520660.9041320.547934
560.4207090.8414170.579291
570.3771220.7542440.622878
580.3435040.6870090.656496
590.3053820.6107630.694618
600.3047160.6094310.695284
610.2748850.5497710.725115
620.2433920.4867830.756608
630.2132060.4264110.786794
640.184850.3697010.81515
650.1596120.3192240.840388
660.1357020.2714030.864298
670.1180790.2361570.881921
680.1474920.2949830.852508
690.3472560.6945110.652744
700.3093840.6187670.690616
710.4660180.9320370.533982
720.4276950.855390.572305
730.4157560.8315130.584244
740.3945460.7890920.605454
750.3594440.7188890.640556
760.4070740.8141480.592926
770.3743010.7486010.625699
780.3465910.6931830.653409
790.3751240.7502480.624876
800.3445240.6890480.655476
810.3118930.6237860.688107
820.2778010.5556020.722199
830.2541370.5082740.745863
840.2233820.4467640.776618
850.2136240.4272490.786376
860.1860950.372190.813905
870.1627840.3255690.837216
880.1479690.2959390.852031
890.1275370.2550740.872463
900.1293260.2586530.870674
910.1115350.2230710.888465
920.09612840.1922570.903872
930.08255030.1651010.91745
940.08774250.1754850.912257
950.0780880.1561760.921912
960.06582940.1316590.934171
970.06890680.1378140.931093
980.0573580.1147160.942642
990.04759060.09518130.952409
1000.04254390.08508770.957456
1010.03698590.07397190.963014
1020.04200020.08400050.958
1030.03566540.07133080.964335
1040.03166650.0633330.968333
1050.03880950.0776190.961191
1060.03358010.06716020.96642
1070.02729040.05458080.97271
1080.02601340.05202680.973987
1090.02122210.04244430.978778
1100.01720380.03440760.982796
1110.01363220.02726440.986368
1120.01362280.02724550.986377
1130.01248730.02497460.987513
1140.01914620.03829240.980854
1150.01776170.03552340.982238
1160.01760360.03520730.982396
1170.01436510.02873020.985635
1180.01493330.02986660.985067
1190.01206910.02413820.987931
1200.01101720.02203440.988983
1210.008849280.01769860.991151
1220.0140520.0281040.985948
1230.01204310.02408620.987957
1240.0108230.02164610.989177
1250.009037310.01807460.990963
1260.007284510.0145690.992715
1270.006399140.01279830.993601
1280.005106590.01021320.994893
1290.007833750.01566750.992166
1300.008079630.01615930.99192
1310.01809490.03618990.981905
1320.0203690.04073790.979631
1330.02326180.04652350.976738
1340.02325620.04651240.976744
1350.0190360.03807210.980964
1360.01563720.03127450.984363
1370.0124430.0248860.987557
1380.01657730.03315450.983423
1390.01492410.02984810.985076
1400.01903120.03806230.980969
1410.02611290.05222590.973887
1420.02329660.04659320.976703
1430.01901340.03802680.980987
1440.01807750.03615490.981923
1450.03550260.07100520.964497
1460.03842220.07684440.961578
1470.04319880.08639750.956801
1480.03696460.07392920.963035
1490.03032680.06065370.969673
1500.04572930.09145870.954271
1510.04138110.08276220.958619
1520.04108710.08217420.958913
1530.07170820.1434160.928292
1540.06315970.1263190.93684
1550.07711280.1542260.922887
1560.06481480.129630.935185
1570.05642130.1128430.943579
1580.04785030.09570060.95215
1590.0454570.0909140.954543
1600.03903550.07807110.960964
1610.03186880.06373760.968131
1620.02618790.05237590.973812
1630.02158130.04316270.978419
1640.01825240.03650480.981748
1650.01613830.03227670.983862
1660.01625170.03250330.983748
1670.01295680.02591360.987043
1680.01847940.03695880.981521
1690.01789430.03578850.982106
1700.01701890.03403780.982981
1710.01656170.03312330.983438
1720.0134360.02687210.986564
1730.01295840.02591670.987042
1740.01387740.02775490.986123
1750.01724080.03448150.982759
1760.01389520.02779030.986105
1770.0110520.0221040.988948
1780.008870740.01774150.991129
1790.006883220.01376640.993117
1800.005774440.01154890.994226
1810.004853940.009707870.995146
1820.00378880.00757760.996211
1830.00424150.0084830.995759
1840.003270550.006541090.996729
1850.07284070.1456810.927159
1860.06383690.1276740.936163
1870.07555140.1511030.924449
1880.06403710.1280740.935963
1890.05365420.1073080.946346
1900.04430830.08861670.955692
1910.03873350.07746710.961266
1920.03248040.06496090.96752
1930.0387770.0775540.961223
1940.04258040.08516070.95742
1950.03554150.0710830.964459
1960.0291430.0582860.970857
1970.03934320.07868640.960657
1980.03217520.06435030.967825
1990.02996920.05993830.970031
2000.02546850.05093710.974531
2010.02420990.04841990.97579
2020.0201830.0403660.979817
2030.02552710.05105430.974473
2040.02805990.05611970.97194
2050.03122240.06244490.968778
2060.02457160.04914320.975428
2070.02426990.04853980.97573
2080.01996930.03993860.980031
2090.02167280.04334570.978327
2100.01745630.03491270.982544
2110.01892930.03785860.981071
2120.02927030.05854060.97073
2130.02286940.04573870.977131
2140.0330240.0660480.966976
2150.02845690.05691370.971543
2160.0220850.044170.977915
2170.02435910.04871820.975641
2180.02048960.04097920.97951
2190.01832060.03664110.981679
2200.01375480.02750960.986245
2210.01192720.02385450.988073
2220.008581220.01716240.991419
2230.006346570.01269310.993653
2240.004964720.009929430.995035
2250.004294650.008589290.995705
2260.009946290.01989260.990054
2270.007534380.01506880.992466
2280.005373390.01074680.994627
2290.003807180.007614360.996193
2300.002664710.005329420.997335
2310.002671580.005343160.997328
2320.004943360.009886730.995057
2330.02594670.05189350.974053
2340.03845790.07691590.961542
2350.02771880.05543760.972281
2360.02396180.04792360.976038
2370.1877710.3755420.812229
2380.1470450.294090.852955
2390.1302160.2604320.869784
2400.09886840.1977370.901132
2410.07660010.15320.9234
2420.06146340.1229270.938537
2430.05620980.112420.94379
2440.1035630.2071250.896437
2450.09078380.1815680.909216
2460.06963830.1392770.930362
2470.04652960.09305930.95347
2480.0378060.0756120.962194
2490.03407470.06814950.965925
2500.04144890.08289770.958551
2510.02182240.04364490.978178
2520.05474270.1094850.945257

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.249272 & 0.498545 & 0.750728 \tabularnewline
13 & 0.168954 & 0.337908 & 0.831046 \tabularnewline
14 & 0.188652 & 0.377305 & 0.811348 \tabularnewline
15 & 0.113822 & 0.227644 & 0.886178 \tabularnewline
16 & 0.0773582 & 0.154716 & 0.922642 \tabularnewline
17 & 0.11109 & 0.22218 & 0.88891 \tabularnewline
18 & 0.350297 & 0.700594 & 0.649703 \tabularnewline
19 & 0.273076 & 0.546152 & 0.726924 \tabularnewline
20 & 0.200365 & 0.40073 & 0.799635 \tabularnewline
21 & 0.147329 & 0.294658 & 0.852671 \tabularnewline
22 & 0.14243 & 0.28486 & 0.85757 \tabularnewline
23 & 0.329614 & 0.659227 & 0.670386 \tabularnewline
24 & 0.396108 & 0.792216 & 0.603892 \tabularnewline
25 & 0.364644 & 0.729288 & 0.635356 \tabularnewline
26 & 0.343014 & 0.686028 & 0.656986 \tabularnewline
27 & 0.419522 & 0.839044 & 0.580478 \tabularnewline
28 & 0.431039 & 0.862079 & 0.568961 \tabularnewline
29 & 0.411178 & 0.822357 & 0.588822 \tabularnewline
30 & 0.444563 & 0.889126 & 0.555437 \tabularnewline
31 & 0.389182 & 0.778364 & 0.610818 \tabularnewline
32 & 0.346621 & 0.693242 & 0.653379 \tabularnewline
33 & 0.316677 & 0.633354 & 0.683323 \tabularnewline
34 & 0.275675 & 0.55135 & 0.724325 \tabularnewline
35 & 0.23314 & 0.466279 & 0.76686 \tabularnewline
36 & 0.363624 & 0.727248 & 0.636376 \tabularnewline
37 & 0.40048 & 0.80096 & 0.59952 \tabularnewline
38 & 0.392518 & 0.785037 & 0.607482 \tabularnewline
39 & 0.420647 & 0.841294 & 0.579353 \tabularnewline
40 & 0.394037 & 0.788073 & 0.605963 \tabularnewline
41 & 0.352609 & 0.705217 & 0.647391 \tabularnewline
42 & 0.317816 & 0.635631 & 0.682184 \tabularnewline
43 & 0.330603 & 0.661206 & 0.669397 \tabularnewline
44 & 0.284193 & 0.568386 & 0.715807 \tabularnewline
45 & 0.259307 & 0.518615 & 0.740693 \tabularnewline
46 & 0.457373 & 0.914746 & 0.542627 \tabularnewline
47 & 0.613015 & 0.77397 & 0.386985 \tabularnewline
48 & 0.564791 & 0.870418 & 0.435209 \tabularnewline
49 & 0.550116 & 0.899768 & 0.449884 \tabularnewline
50 & 0.538887 & 0.922226 & 0.461113 \tabularnewline
51 & 0.496029 & 0.992058 & 0.503971 \tabularnewline
52 & 0.448977 & 0.897953 & 0.551023 \tabularnewline
53 & 0.46941 & 0.93882 & 0.53059 \tabularnewline
54 & 0.449834 & 0.899668 & 0.550166 \tabularnewline
55 & 0.452066 & 0.904132 & 0.547934 \tabularnewline
56 & 0.420709 & 0.841417 & 0.579291 \tabularnewline
57 & 0.377122 & 0.754244 & 0.622878 \tabularnewline
58 & 0.343504 & 0.687009 & 0.656496 \tabularnewline
59 & 0.305382 & 0.610763 & 0.694618 \tabularnewline
60 & 0.304716 & 0.609431 & 0.695284 \tabularnewline
61 & 0.274885 & 0.549771 & 0.725115 \tabularnewline
62 & 0.243392 & 0.486783 & 0.756608 \tabularnewline
63 & 0.213206 & 0.426411 & 0.786794 \tabularnewline
64 & 0.18485 & 0.369701 & 0.81515 \tabularnewline
65 & 0.159612 & 0.319224 & 0.840388 \tabularnewline
66 & 0.135702 & 0.271403 & 0.864298 \tabularnewline
67 & 0.118079 & 0.236157 & 0.881921 \tabularnewline
68 & 0.147492 & 0.294983 & 0.852508 \tabularnewline
69 & 0.347256 & 0.694511 & 0.652744 \tabularnewline
70 & 0.309384 & 0.618767 & 0.690616 \tabularnewline
71 & 0.466018 & 0.932037 & 0.533982 \tabularnewline
72 & 0.427695 & 0.85539 & 0.572305 \tabularnewline
73 & 0.415756 & 0.831513 & 0.584244 \tabularnewline
74 & 0.394546 & 0.789092 & 0.605454 \tabularnewline
75 & 0.359444 & 0.718889 & 0.640556 \tabularnewline
76 & 0.407074 & 0.814148 & 0.592926 \tabularnewline
77 & 0.374301 & 0.748601 & 0.625699 \tabularnewline
78 & 0.346591 & 0.693183 & 0.653409 \tabularnewline
79 & 0.375124 & 0.750248 & 0.624876 \tabularnewline
80 & 0.344524 & 0.689048 & 0.655476 \tabularnewline
81 & 0.311893 & 0.623786 & 0.688107 \tabularnewline
82 & 0.277801 & 0.555602 & 0.722199 \tabularnewline
83 & 0.254137 & 0.508274 & 0.745863 \tabularnewline
84 & 0.223382 & 0.446764 & 0.776618 \tabularnewline
85 & 0.213624 & 0.427249 & 0.786376 \tabularnewline
86 & 0.186095 & 0.37219 & 0.813905 \tabularnewline
87 & 0.162784 & 0.325569 & 0.837216 \tabularnewline
88 & 0.147969 & 0.295939 & 0.852031 \tabularnewline
89 & 0.127537 & 0.255074 & 0.872463 \tabularnewline
90 & 0.129326 & 0.258653 & 0.870674 \tabularnewline
91 & 0.111535 & 0.223071 & 0.888465 \tabularnewline
92 & 0.0961284 & 0.192257 & 0.903872 \tabularnewline
93 & 0.0825503 & 0.165101 & 0.91745 \tabularnewline
94 & 0.0877425 & 0.175485 & 0.912257 \tabularnewline
95 & 0.078088 & 0.156176 & 0.921912 \tabularnewline
96 & 0.0658294 & 0.131659 & 0.934171 \tabularnewline
97 & 0.0689068 & 0.137814 & 0.931093 \tabularnewline
98 & 0.057358 & 0.114716 & 0.942642 \tabularnewline
99 & 0.0475906 & 0.0951813 & 0.952409 \tabularnewline
100 & 0.0425439 & 0.0850877 & 0.957456 \tabularnewline
101 & 0.0369859 & 0.0739719 & 0.963014 \tabularnewline
102 & 0.0420002 & 0.0840005 & 0.958 \tabularnewline
103 & 0.0356654 & 0.0713308 & 0.964335 \tabularnewline
104 & 0.0316665 & 0.063333 & 0.968333 \tabularnewline
105 & 0.0388095 & 0.077619 & 0.961191 \tabularnewline
106 & 0.0335801 & 0.0671602 & 0.96642 \tabularnewline
107 & 0.0272904 & 0.0545808 & 0.97271 \tabularnewline
108 & 0.0260134 & 0.0520268 & 0.973987 \tabularnewline
109 & 0.0212221 & 0.0424443 & 0.978778 \tabularnewline
110 & 0.0172038 & 0.0344076 & 0.982796 \tabularnewline
111 & 0.0136322 & 0.0272644 & 0.986368 \tabularnewline
112 & 0.0136228 & 0.0272455 & 0.986377 \tabularnewline
113 & 0.0124873 & 0.0249746 & 0.987513 \tabularnewline
114 & 0.0191462 & 0.0382924 & 0.980854 \tabularnewline
115 & 0.0177617 & 0.0355234 & 0.982238 \tabularnewline
116 & 0.0176036 & 0.0352073 & 0.982396 \tabularnewline
117 & 0.0143651 & 0.0287302 & 0.985635 \tabularnewline
118 & 0.0149333 & 0.0298666 & 0.985067 \tabularnewline
119 & 0.0120691 & 0.0241382 & 0.987931 \tabularnewline
120 & 0.0110172 & 0.0220344 & 0.988983 \tabularnewline
121 & 0.00884928 & 0.0176986 & 0.991151 \tabularnewline
122 & 0.014052 & 0.028104 & 0.985948 \tabularnewline
123 & 0.0120431 & 0.0240862 & 0.987957 \tabularnewline
124 & 0.010823 & 0.0216461 & 0.989177 \tabularnewline
125 & 0.00903731 & 0.0180746 & 0.990963 \tabularnewline
126 & 0.00728451 & 0.014569 & 0.992715 \tabularnewline
127 & 0.00639914 & 0.0127983 & 0.993601 \tabularnewline
128 & 0.00510659 & 0.0102132 & 0.994893 \tabularnewline
129 & 0.00783375 & 0.0156675 & 0.992166 \tabularnewline
130 & 0.00807963 & 0.0161593 & 0.99192 \tabularnewline
131 & 0.0180949 & 0.0361899 & 0.981905 \tabularnewline
132 & 0.020369 & 0.0407379 & 0.979631 \tabularnewline
133 & 0.0232618 & 0.0465235 & 0.976738 \tabularnewline
134 & 0.0232562 & 0.0465124 & 0.976744 \tabularnewline
135 & 0.019036 & 0.0380721 & 0.980964 \tabularnewline
136 & 0.0156372 & 0.0312745 & 0.984363 \tabularnewline
137 & 0.012443 & 0.024886 & 0.987557 \tabularnewline
138 & 0.0165773 & 0.0331545 & 0.983423 \tabularnewline
139 & 0.0149241 & 0.0298481 & 0.985076 \tabularnewline
140 & 0.0190312 & 0.0380623 & 0.980969 \tabularnewline
141 & 0.0261129 & 0.0522259 & 0.973887 \tabularnewline
142 & 0.0232966 & 0.0465932 & 0.976703 \tabularnewline
143 & 0.0190134 & 0.0380268 & 0.980987 \tabularnewline
144 & 0.0180775 & 0.0361549 & 0.981923 \tabularnewline
145 & 0.0355026 & 0.0710052 & 0.964497 \tabularnewline
146 & 0.0384222 & 0.0768444 & 0.961578 \tabularnewline
147 & 0.0431988 & 0.0863975 & 0.956801 \tabularnewline
148 & 0.0369646 & 0.0739292 & 0.963035 \tabularnewline
149 & 0.0303268 & 0.0606537 & 0.969673 \tabularnewline
150 & 0.0457293 & 0.0914587 & 0.954271 \tabularnewline
151 & 0.0413811 & 0.0827622 & 0.958619 \tabularnewline
152 & 0.0410871 & 0.0821742 & 0.958913 \tabularnewline
153 & 0.0717082 & 0.143416 & 0.928292 \tabularnewline
154 & 0.0631597 & 0.126319 & 0.93684 \tabularnewline
155 & 0.0771128 & 0.154226 & 0.922887 \tabularnewline
156 & 0.0648148 & 0.12963 & 0.935185 \tabularnewline
157 & 0.0564213 & 0.112843 & 0.943579 \tabularnewline
158 & 0.0478503 & 0.0957006 & 0.95215 \tabularnewline
159 & 0.045457 & 0.090914 & 0.954543 \tabularnewline
160 & 0.0390355 & 0.0780711 & 0.960964 \tabularnewline
161 & 0.0318688 & 0.0637376 & 0.968131 \tabularnewline
162 & 0.0261879 & 0.0523759 & 0.973812 \tabularnewline
163 & 0.0215813 & 0.0431627 & 0.978419 \tabularnewline
164 & 0.0182524 & 0.0365048 & 0.981748 \tabularnewline
165 & 0.0161383 & 0.0322767 & 0.983862 \tabularnewline
166 & 0.0162517 & 0.0325033 & 0.983748 \tabularnewline
167 & 0.0129568 & 0.0259136 & 0.987043 \tabularnewline
168 & 0.0184794 & 0.0369588 & 0.981521 \tabularnewline
169 & 0.0178943 & 0.0357885 & 0.982106 \tabularnewline
170 & 0.0170189 & 0.0340378 & 0.982981 \tabularnewline
171 & 0.0165617 & 0.0331233 & 0.983438 \tabularnewline
172 & 0.013436 & 0.0268721 & 0.986564 \tabularnewline
173 & 0.0129584 & 0.0259167 & 0.987042 \tabularnewline
174 & 0.0138774 & 0.0277549 & 0.986123 \tabularnewline
175 & 0.0172408 & 0.0344815 & 0.982759 \tabularnewline
176 & 0.0138952 & 0.0277903 & 0.986105 \tabularnewline
177 & 0.011052 & 0.022104 & 0.988948 \tabularnewline
178 & 0.00887074 & 0.0177415 & 0.991129 \tabularnewline
179 & 0.00688322 & 0.0137664 & 0.993117 \tabularnewline
180 & 0.00577444 & 0.0115489 & 0.994226 \tabularnewline
181 & 0.00485394 & 0.00970787 & 0.995146 \tabularnewline
182 & 0.0037888 & 0.0075776 & 0.996211 \tabularnewline
183 & 0.0042415 & 0.008483 & 0.995759 \tabularnewline
184 & 0.00327055 & 0.00654109 & 0.996729 \tabularnewline
185 & 0.0728407 & 0.145681 & 0.927159 \tabularnewline
186 & 0.0638369 & 0.127674 & 0.936163 \tabularnewline
187 & 0.0755514 & 0.151103 & 0.924449 \tabularnewline
188 & 0.0640371 & 0.128074 & 0.935963 \tabularnewline
189 & 0.0536542 & 0.107308 & 0.946346 \tabularnewline
190 & 0.0443083 & 0.0886167 & 0.955692 \tabularnewline
191 & 0.0387335 & 0.0774671 & 0.961266 \tabularnewline
192 & 0.0324804 & 0.0649609 & 0.96752 \tabularnewline
193 & 0.038777 & 0.077554 & 0.961223 \tabularnewline
194 & 0.0425804 & 0.0851607 & 0.95742 \tabularnewline
195 & 0.0355415 & 0.071083 & 0.964459 \tabularnewline
196 & 0.029143 & 0.058286 & 0.970857 \tabularnewline
197 & 0.0393432 & 0.0786864 & 0.960657 \tabularnewline
198 & 0.0321752 & 0.0643503 & 0.967825 \tabularnewline
199 & 0.0299692 & 0.0599383 & 0.970031 \tabularnewline
200 & 0.0254685 & 0.0509371 & 0.974531 \tabularnewline
201 & 0.0242099 & 0.0484199 & 0.97579 \tabularnewline
202 & 0.020183 & 0.040366 & 0.979817 \tabularnewline
203 & 0.0255271 & 0.0510543 & 0.974473 \tabularnewline
204 & 0.0280599 & 0.0561197 & 0.97194 \tabularnewline
205 & 0.0312224 & 0.0624449 & 0.968778 \tabularnewline
206 & 0.0245716 & 0.0491432 & 0.975428 \tabularnewline
207 & 0.0242699 & 0.0485398 & 0.97573 \tabularnewline
208 & 0.0199693 & 0.0399386 & 0.980031 \tabularnewline
209 & 0.0216728 & 0.0433457 & 0.978327 \tabularnewline
210 & 0.0174563 & 0.0349127 & 0.982544 \tabularnewline
211 & 0.0189293 & 0.0378586 & 0.981071 \tabularnewline
212 & 0.0292703 & 0.0585406 & 0.97073 \tabularnewline
213 & 0.0228694 & 0.0457387 & 0.977131 \tabularnewline
214 & 0.033024 & 0.066048 & 0.966976 \tabularnewline
215 & 0.0284569 & 0.0569137 & 0.971543 \tabularnewline
216 & 0.022085 & 0.04417 & 0.977915 \tabularnewline
217 & 0.0243591 & 0.0487182 & 0.975641 \tabularnewline
218 & 0.0204896 & 0.0409792 & 0.97951 \tabularnewline
219 & 0.0183206 & 0.0366411 & 0.981679 \tabularnewline
220 & 0.0137548 & 0.0275096 & 0.986245 \tabularnewline
221 & 0.0119272 & 0.0238545 & 0.988073 \tabularnewline
222 & 0.00858122 & 0.0171624 & 0.991419 \tabularnewline
223 & 0.00634657 & 0.0126931 & 0.993653 \tabularnewline
224 & 0.00496472 & 0.00992943 & 0.995035 \tabularnewline
225 & 0.00429465 & 0.00858929 & 0.995705 \tabularnewline
226 & 0.00994629 & 0.0198926 & 0.990054 \tabularnewline
227 & 0.00753438 & 0.0150688 & 0.992466 \tabularnewline
228 & 0.00537339 & 0.0107468 & 0.994627 \tabularnewline
229 & 0.00380718 & 0.00761436 & 0.996193 \tabularnewline
230 & 0.00266471 & 0.00532942 & 0.997335 \tabularnewline
231 & 0.00267158 & 0.00534316 & 0.997328 \tabularnewline
232 & 0.00494336 & 0.00988673 & 0.995057 \tabularnewline
233 & 0.0259467 & 0.0518935 & 0.974053 \tabularnewline
234 & 0.0384579 & 0.0769159 & 0.961542 \tabularnewline
235 & 0.0277188 & 0.0554376 & 0.972281 \tabularnewline
236 & 0.0239618 & 0.0479236 & 0.976038 \tabularnewline
237 & 0.187771 & 0.375542 & 0.812229 \tabularnewline
238 & 0.147045 & 0.29409 & 0.852955 \tabularnewline
239 & 0.130216 & 0.260432 & 0.869784 \tabularnewline
240 & 0.0988684 & 0.197737 & 0.901132 \tabularnewline
241 & 0.0766001 & 0.1532 & 0.9234 \tabularnewline
242 & 0.0614634 & 0.122927 & 0.938537 \tabularnewline
243 & 0.0562098 & 0.11242 & 0.94379 \tabularnewline
244 & 0.103563 & 0.207125 & 0.896437 \tabularnewline
245 & 0.0907838 & 0.181568 & 0.909216 \tabularnewline
246 & 0.0696383 & 0.139277 & 0.930362 \tabularnewline
247 & 0.0465296 & 0.0930593 & 0.95347 \tabularnewline
248 & 0.037806 & 0.075612 & 0.962194 \tabularnewline
249 & 0.0340747 & 0.0681495 & 0.965925 \tabularnewline
250 & 0.0414489 & 0.0828977 & 0.958551 \tabularnewline
251 & 0.0218224 & 0.0436449 & 0.978178 \tabularnewline
252 & 0.0547427 & 0.109485 & 0.945257 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267527&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]0.249272[/C][C]0.498545[/C][C]0.750728[/C][/ROW]
[ROW][C]13[/C][C]0.168954[/C][C]0.337908[/C][C]0.831046[/C][/ROW]
[ROW][C]14[/C][C]0.188652[/C][C]0.377305[/C][C]0.811348[/C][/ROW]
[ROW][C]15[/C][C]0.113822[/C][C]0.227644[/C][C]0.886178[/C][/ROW]
[ROW][C]16[/C][C]0.0773582[/C][C]0.154716[/C][C]0.922642[/C][/ROW]
[ROW][C]17[/C][C]0.11109[/C][C]0.22218[/C][C]0.88891[/C][/ROW]
[ROW][C]18[/C][C]0.350297[/C][C]0.700594[/C][C]0.649703[/C][/ROW]
[ROW][C]19[/C][C]0.273076[/C][C]0.546152[/C][C]0.726924[/C][/ROW]
[ROW][C]20[/C][C]0.200365[/C][C]0.40073[/C][C]0.799635[/C][/ROW]
[ROW][C]21[/C][C]0.147329[/C][C]0.294658[/C][C]0.852671[/C][/ROW]
[ROW][C]22[/C][C]0.14243[/C][C]0.28486[/C][C]0.85757[/C][/ROW]
[ROW][C]23[/C][C]0.329614[/C][C]0.659227[/C][C]0.670386[/C][/ROW]
[ROW][C]24[/C][C]0.396108[/C][C]0.792216[/C][C]0.603892[/C][/ROW]
[ROW][C]25[/C][C]0.364644[/C][C]0.729288[/C][C]0.635356[/C][/ROW]
[ROW][C]26[/C][C]0.343014[/C][C]0.686028[/C][C]0.656986[/C][/ROW]
[ROW][C]27[/C][C]0.419522[/C][C]0.839044[/C][C]0.580478[/C][/ROW]
[ROW][C]28[/C][C]0.431039[/C][C]0.862079[/C][C]0.568961[/C][/ROW]
[ROW][C]29[/C][C]0.411178[/C][C]0.822357[/C][C]0.588822[/C][/ROW]
[ROW][C]30[/C][C]0.444563[/C][C]0.889126[/C][C]0.555437[/C][/ROW]
[ROW][C]31[/C][C]0.389182[/C][C]0.778364[/C][C]0.610818[/C][/ROW]
[ROW][C]32[/C][C]0.346621[/C][C]0.693242[/C][C]0.653379[/C][/ROW]
[ROW][C]33[/C][C]0.316677[/C][C]0.633354[/C][C]0.683323[/C][/ROW]
[ROW][C]34[/C][C]0.275675[/C][C]0.55135[/C][C]0.724325[/C][/ROW]
[ROW][C]35[/C][C]0.23314[/C][C]0.466279[/C][C]0.76686[/C][/ROW]
[ROW][C]36[/C][C]0.363624[/C][C]0.727248[/C][C]0.636376[/C][/ROW]
[ROW][C]37[/C][C]0.40048[/C][C]0.80096[/C][C]0.59952[/C][/ROW]
[ROW][C]38[/C][C]0.392518[/C][C]0.785037[/C][C]0.607482[/C][/ROW]
[ROW][C]39[/C][C]0.420647[/C][C]0.841294[/C][C]0.579353[/C][/ROW]
[ROW][C]40[/C][C]0.394037[/C][C]0.788073[/C][C]0.605963[/C][/ROW]
[ROW][C]41[/C][C]0.352609[/C][C]0.705217[/C][C]0.647391[/C][/ROW]
[ROW][C]42[/C][C]0.317816[/C][C]0.635631[/C][C]0.682184[/C][/ROW]
[ROW][C]43[/C][C]0.330603[/C][C]0.661206[/C][C]0.669397[/C][/ROW]
[ROW][C]44[/C][C]0.284193[/C][C]0.568386[/C][C]0.715807[/C][/ROW]
[ROW][C]45[/C][C]0.259307[/C][C]0.518615[/C][C]0.740693[/C][/ROW]
[ROW][C]46[/C][C]0.457373[/C][C]0.914746[/C][C]0.542627[/C][/ROW]
[ROW][C]47[/C][C]0.613015[/C][C]0.77397[/C][C]0.386985[/C][/ROW]
[ROW][C]48[/C][C]0.564791[/C][C]0.870418[/C][C]0.435209[/C][/ROW]
[ROW][C]49[/C][C]0.550116[/C][C]0.899768[/C][C]0.449884[/C][/ROW]
[ROW][C]50[/C][C]0.538887[/C][C]0.922226[/C][C]0.461113[/C][/ROW]
[ROW][C]51[/C][C]0.496029[/C][C]0.992058[/C][C]0.503971[/C][/ROW]
[ROW][C]52[/C][C]0.448977[/C][C]0.897953[/C][C]0.551023[/C][/ROW]
[ROW][C]53[/C][C]0.46941[/C][C]0.93882[/C][C]0.53059[/C][/ROW]
[ROW][C]54[/C][C]0.449834[/C][C]0.899668[/C][C]0.550166[/C][/ROW]
[ROW][C]55[/C][C]0.452066[/C][C]0.904132[/C][C]0.547934[/C][/ROW]
[ROW][C]56[/C][C]0.420709[/C][C]0.841417[/C][C]0.579291[/C][/ROW]
[ROW][C]57[/C][C]0.377122[/C][C]0.754244[/C][C]0.622878[/C][/ROW]
[ROW][C]58[/C][C]0.343504[/C][C]0.687009[/C][C]0.656496[/C][/ROW]
[ROW][C]59[/C][C]0.305382[/C][C]0.610763[/C][C]0.694618[/C][/ROW]
[ROW][C]60[/C][C]0.304716[/C][C]0.609431[/C][C]0.695284[/C][/ROW]
[ROW][C]61[/C][C]0.274885[/C][C]0.549771[/C][C]0.725115[/C][/ROW]
[ROW][C]62[/C][C]0.243392[/C][C]0.486783[/C][C]0.756608[/C][/ROW]
[ROW][C]63[/C][C]0.213206[/C][C]0.426411[/C][C]0.786794[/C][/ROW]
[ROW][C]64[/C][C]0.18485[/C][C]0.369701[/C][C]0.81515[/C][/ROW]
[ROW][C]65[/C][C]0.159612[/C][C]0.319224[/C][C]0.840388[/C][/ROW]
[ROW][C]66[/C][C]0.135702[/C][C]0.271403[/C][C]0.864298[/C][/ROW]
[ROW][C]67[/C][C]0.118079[/C][C]0.236157[/C][C]0.881921[/C][/ROW]
[ROW][C]68[/C][C]0.147492[/C][C]0.294983[/C][C]0.852508[/C][/ROW]
[ROW][C]69[/C][C]0.347256[/C][C]0.694511[/C][C]0.652744[/C][/ROW]
[ROW][C]70[/C][C]0.309384[/C][C]0.618767[/C][C]0.690616[/C][/ROW]
[ROW][C]71[/C][C]0.466018[/C][C]0.932037[/C][C]0.533982[/C][/ROW]
[ROW][C]72[/C][C]0.427695[/C][C]0.85539[/C][C]0.572305[/C][/ROW]
[ROW][C]73[/C][C]0.415756[/C][C]0.831513[/C][C]0.584244[/C][/ROW]
[ROW][C]74[/C][C]0.394546[/C][C]0.789092[/C][C]0.605454[/C][/ROW]
[ROW][C]75[/C][C]0.359444[/C][C]0.718889[/C][C]0.640556[/C][/ROW]
[ROW][C]76[/C][C]0.407074[/C][C]0.814148[/C][C]0.592926[/C][/ROW]
[ROW][C]77[/C][C]0.374301[/C][C]0.748601[/C][C]0.625699[/C][/ROW]
[ROW][C]78[/C][C]0.346591[/C][C]0.693183[/C][C]0.653409[/C][/ROW]
[ROW][C]79[/C][C]0.375124[/C][C]0.750248[/C][C]0.624876[/C][/ROW]
[ROW][C]80[/C][C]0.344524[/C][C]0.689048[/C][C]0.655476[/C][/ROW]
[ROW][C]81[/C][C]0.311893[/C][C]0.623786[/C][C]0.688107[/C][/ROW]
[ROW][C]82[/C][C]0.277801[/C][C]0.555602[/C][C]0.722199[/C][/ROW]
[ROW][C]83[/C][C]0.254137[/C][C]0.508274[/C][C]0.745863[/C][/ROW]
[ROW][C]84[/C][C]0.223382[/C][C]0.446764[/C][C]0.776618[/C][/ROW]
[ROW][C]85[/C][C]0.213624[/C][C]0.427249[/C][C]0.786376[/C][/ROW]
[ROW][C]86[/C][C]0.186095[/C][C]0.37219[/C][C]0.813905[/C][/ROW]
[ROW][C]87[/C][C]0.162784[/C][C]0.325569[/C][C]0.837216[/C][/ROW]
[ROW][C]88[/C][C]0.147969[/C][C]0.295939[/C][C]0.852031[/C][/ROW]
[ROW][C]89[/C][C]0.127537[/C][C]0.255074[/C][C]0.872463[/C][/ROW]
[ROW][C]90[/C][C]0.129326[/C][C]0.258653[/C][C]0.870674[/C][/ROW]
[ROW][C]91[/C][C]0.111535[/C][C]0.223071[/C][C]0.888465[/C][/ROW]
[ROW][C]92[/C][C]0.0961284[/C][C]0.192257[/C][C]0.903872[/C][/ROW]
[ROW][C]93[/C][C]0.0825503[/C][C]0.165101[/C][C]0.91745[/C][/ROW]
[ROW][C]94[/C][C]0.0877425[/C][C]0.175485[/C][C]0.912257[/C][/ROW]
[ROW][C]95[/C][C]0.078088[/C][C]0.156176[/C][C]0.921912[/C][/ROW]
[ROW][C]96[/C][C]0.0658294[/C][C]0.131659[/C][C]0.934171[/C][/ROW]
[ROW][C]97[/C][C]0.0689068[/C][C]0.137814[/C][C]0.931093[/C][/ROW]
[ROW][C]98[/C][C]0.057358[/C][C]0.114716[/C][C]0.942642[/C][/ROW]
[ROW][C]99[/C][C]0.0475906[/C][C]0.0951813[/C][C]0.952409[/C][/ROW]
[ROW][C]100[/C][C]0.0425439[/C][C]0.0850877[/C][C]0.957456[/C][/ROW]
[ROW][C]101[/C][C]0.0369859[/C][C]0.0739719[/C][C]0.963014[/C][/ROW]
[ROW][C]102[/C][C]0.0420002[/C][C]0.0840005[/C][C]0.958[/C][/ROW]
[ROW][C]103[/C][C]0.0356654[/C][C]0.0713308[/C][C]0.964335[/C][/ROW]
[ROW][C]104[/C][C]0.0316665[/C][C]0.063333[/C][C]0.968333[/C][/ROW]
[ROW][C]105[/C][C]0.0388095[/C][C]0.077619[/C][C]0.961191[/C][/ROW]
[ROW][C]106[/C][C]0.0335801[/C][C]0.0671602[/C][C]0.96642[/C][/ROW]
[ROW][C]107[/C][C]0.0272904[/C][C]0.0545808[/C][C]0.97271[/C][/ROW]
[ROW][C]108[/C][C]0.0260134[/C][C]0.0520268[/C][C]0.973987[/C][/ROW]
[ROW][C]109[/C][C]0.0212221[/C][C]0.0424443[/C][C]0.978778[/C][/ROW]
[ROW][C]110[/C][C]0.0172038[/C][C]0.0344076[/C][C]0.982796[/C][/ROW]
[ROW][C]111[/C][C]0.0136322[/C][C]0.0272644[/C][C]0.986368[/C][/ROW]
[ROW][C]112[/C][C]0.0136228[/C][C]0.0272455[/C][C]0.986377[/C][/ROW]
[ROW][C]113[/C][C]0.0124873[/C][C]0.0249746[/C][C]0.987513[/C][/ROW]
[ROW][C]114[/C][C]0.0191462[/C][C]0.0382924[/C][C]0.980854[/C][/ROW]
[ROW][C]115[/C][C]0.0177617[/C][C]0.0355234[/C][C]0.982238[/C][/ROW]
[ROW][C]116[/C][C]0.0176036[/C][C]0.0352073[/C][C]0.982396[/C][/ROW]
[ROW][C]117[/C][C]0.0143651[/C][C]0.0287302[/C][C]0.985635[/C][/ROW]
[ROW][C]118[/C][C]0.0149333[/C][C]0.0298666[/C][C]0.985067[/C][/ROW]
[ROW][C]119[/C][C]0.0120691[/C][C]0.0241382[/C][C]0.987931[/C][/ROW]
[ROW][C]120[/C][C]0.0110172[/C][C]0.0220344[/C][C]0.988983[/C][/ROW]
[ROW][C]121[/C][C]0.00884928[/C][C]0.0176986[/C][C]0.991151[/C][/ROW]
[ROW][C]122[/C][C]0.014052[/C][C]0.028104[/C][C]0.985948[/C][/ROW]
[ROW][C]123[/C][C]0.0120431[/C][C]0.0240862[/C][C]0.987957[/C][/ROW]
[ROW][C]124[/C][C]0.010823[/C][C]0.0216461[/C][C]0.989177[/C][/ROW]
[ROW][C]125[/C][C]0.00903731[/C][C]0.0180746[/C][C]0.990963[/C][/ROW]
[ROW][C]126[/C][C]0.00728451[/C][C]0.014569[/C][C]0.992715[/C][/ROW]
[ROW][C]127[/C][C]0.00639914[/C][C]0.0127983[/C][C]0.993601[/C][/ROW]
[ROW][C]128[/C][C]0.00510659[/C][C]0.0102132[/C][C]0.994893[/C][/ROW]
[ROW][C]129[/C][C]0.00783375[/C][C]0.0156675[/C][C]0.992166[/C][/ROW]
[ROW][C]130[/C][C]0.00807963[/C][C]0.0161593[/C][C]0.99192[/C][/ROW]
[ROW][C]131[/C][C]0.0180949[/C][C]0.0361899[/C][C]0.981905[/C][/ROW]
[ROW][C]132[/C][C]0.020369[/C][C]0.0407379[/C][C]0.979631[/C][/ROW]
[ROW][C]133[/C][C]0.0232618[/C][C]0.0465235[/C][C]0.976738[/C][/ROW]
[ROW][C]134[/C][C]0.0232562[/C][C]0.0465124[/C][C]0.976744[/C][/ROW]
[ROW][C]135[/C][C]0.019036[/C][C]0.0380721[/C][C]0.980964[/C][/ROW]
[ROW][C]136[/C][C]0.0156372[/C][C]0.0312745[/C][C]0.984363[/C][/ROW]
[ROW][C]137[/C][C]0.012443[/C][C]0.024886[/C][C]0.987557[/C][/ROW]
[ROW][C]138[/C][C]0.0165773[/C][C]0.0331545[/C][C]0.983423[/C][/ROW]
[ROW][C]139[/C][C]0.0149241[/C][C]0.0298481[/C][C]0.985076[/C][/ROW]
[ROW][C]140[/C][C]0.0190312[/C][C]0.0380623[/C][C]0.980969[/C][/ROW]
[ROW][C]141[/C][C]0.0261129[/C][C]0.0522259[/C][C]0.973887[/C][/ROW]
[ROW][C]142[/C][C]0.0232966[/C][C]0.0465932[/C][C]0.976703[/C][/ROW]
[ROW][C]143[/C][C]0.0190134[/C][C]0.0380268[/C][C]0.980987[/C][/ROW]
[ROW][C]144[/C][C]0.0180775[/C][C]0.0361549[/C][C]0.981923[/C][/ROW]
[ROW][C]145[/C][C]0.0355026[/C][C]0.0710052[/C][C]0.964497[/C][/ROW]
[ROW][C]146[/C][C]0.0384222[/C][C]0.0768444[/C][C]0.961578[/C][/ROW]
[ROW][C]147[/C][C]0.0431988[/C][C]0.0863975[/C][C]0.956801[/C][/ROW]
[ROW][C]148[/C][C]0.0369646[/C][C]0.0739292[/C][C]0.963035[/C][/ROW]
[ROW][C]149[/C][C]0.0303268[/C][C]0.0606537[/C][C]0.969673[/C][/ROW]
[ROW][C]150[/C][C]0.0457293[/C][C]0.0914587[/C][C]0.954271[/C][/ROW]
[ROW][C]151[/C][C]0.0413811[/C][C]0.0827622[/C][C]0.958619[/C][/ROW]
[ROW][C]152[/C][C]0.0410871[/C][C]0.0821742[/C][C]0.958913[/C][/ROW]
[ROW][C]153[/C][C]0.0717082[/C][C]0.143416[/C][C]0.928292[/C][/ROW]
[ROW][C]154[/C][C]0.0631597[/C][C]0.126319[/C][C]0.93684[/C][/ROW]
[ROW][C]155[/C][C]0.0771128[/C][C]0.154226[/C][C]0.922887[/C][/ROW]
[ROW][C]156[/C][C]0.0648148[/C][C]0.12963[/C][C]0.935185[/C][/ROW]
[ROW][C]157[/C][C]0.0564213[/C][C]0.112843[/C][C]0.943579[/C][/ROW]
[ROW][C]158[/C][C]0.0478503[/C][C]0.0957006[/C][C]0.95215[/C][/ROW]
[ROW][C]159[/C][C]0.045457[/C][C]0.090914[/C][C]0.954543[/C][/ROW]
[ROW][C]160[/C][C]0.0390355[/C][C]0.0780711[/C][C]0.960964[/C][/ROW]
[ROW][C]161[/C][C]0.0318688[/C][C]0.0637376[/C][C]0.968131[/C][/ROW]
[ROW][C]162[/C][C]0.0261879[/C][C]0.0523759[/C][C]0.973812[/C][/ROW]
[ROW][C]163[/C][C]0.0215813[/C][C]0.0431627[/C][C]0.978419[/C][/ROW]
[ROW][C]164[/C][C]0.0182524[/C][C]0.0365048[/C][C]0.981748[/C][/ROW]
[ROW][C]165[/C][C]0.0161383[/C][C]0.0322767[/C][C]0.983862[/C][/ROW]
[ROW][C]166[/C][C]0.0162517[/C][C]0.0325033[/C][C]0.983748[/C][/ROW]
[ROW][C]167[/C][C]0.0129568[/C][C]0.0259136[/C][C]0.987043[/C][/ROW]
[ROW][C]168[/C][C]0.0184794[/C][C]0.0369588[/C][C]0.981521[/C][/ROW]
[ROW][C]169[/C][C]0.0178943[/C][C]0.0357885[/C][C]0.982106[/C][/ROW]
[ROW][C]170[/C][C]0.0170189[/C][C]0.0340378[/C][C]0.982981[/C][/ROW]
[ROW][C]171[/C][C]0.0165617[/C][C]0.0331233[/C][C]0.983438[/C][/ROW]
[ROW][C]172[/C][C]0.013436[/C][C]0.0268721[/C][C]0.986564[/C][/ROW]
[ROW][C]173[/C][C]0.0129584[/C][C]0.0259167[/C][C]0.987042[/C][/ROW]
[ROW][C]174[/C][C]0.0138774[/C][C]0.0277549[/C][C]0.986123[/C][/ROW]
[ROW][C]175[/C][C]0.0172408[/C][C]0.0344815[/C][C]0.982759[/C][/ROW]
[ROW][C]176[/C][C]0.0138952[/C][C]0.0277903[/C][C]0.986105[/C][/ROW]
[ROW][C]177[/C][C]0.011052[/C][C]0.022104[/C][C]0.988948[/C][/ROW]
[ROW][C]178[/C][C]0.00887074[/C][C]0.0177415[/C][C]0.991129[/C][/ROW]
[ROW][C]179[/C][C]0.00688322[/C][C]0.0137664[/C][C]0.993117[/C][/ROW]
[ROW][C]180[/C][C]0.00577444[/C][C]0.0115489[/C][C]0.994226[/C][/ROW]
[ROW][C]181[/C][C]0.00485394[/C][C]0.00970787[/C][C]0.995146[/C][/ROW]
[ROW][C]182[/C][C]0.0037888[/C][C]0.0075776[/C][C]0.996211[/C][/ROW]
[ROW][C]183[/C][C]0.0042415[/C][C]0.008483[/C][C]0.995759[/C][/ROW]
[ROW][C]184[/C][C]0.00327055[/C][C]0.00654109[/C][C]0.996729[/C][/ROW]
[ROW][C]185[/C][C]0.0728407[/C][C]0.145681[/C][C]0.927159[/C][/ROW]
[ROW][C]186[/C][C]0.0638369[/C][C]0.127674[/C][C]0.936163[/C][/ROW]
[ROW][C]187[/C][C]0.0755514[/C][C]0.151103[/C][C]0.924449[/C][/ROW]
[ROW][C]188[/C][C]0.0640371[/C][C]0.128074[/C][C]0.935963[/C][/ROW]
[ROW][C]189[/C][C]0.0536542[/C][C]0.107308[/C][C]0.946346[/C][/ROW]
[ROW][C]190[/C][C]0.0443083[/C][C]0.0886167[/C][C]0.955692[/C][/ROW]
[ROW][C]191[/C][C]0.0387335[/C][C]0.0774671[/C][C]0.961266[/C][/ROW]
[ROW][C]192[/C][C]0.0324804[/C][C]0.0649609[/C][C]0.96752[/C][/ROW]
[ROW][C]193[/C][C]0.038777[/C][C]0.077554[/C][C]0.961223[/C][/ROW]
[ROW][C]194[/C][C]0.0425804[/C][C]0.0851607[/C][C]0.95742[/C][/ROW]
[ROW][C]195[/C][C]0.0355415[/C][C]0.071083[/C][C]0.964459[/C][/ROW]
[ROW][C]196[/C][C]0.029143[/C][C]0.058286[/C][C]0.970857[/C][/ROW]
[ROW][C]197[/C][C]0.0393432[/C][C]0.0786864[/C][C]0.960657[/C][/ROW]
[ROW][C]198[/C][C]0.0321752[/C][C]0.0643503[/C][C]0.967825[/C][/ROW]
[ROW][C]199[/C][C]0.0299692[/C][C]0.0599383[/C][C]0.970031[/C][/ROW]
[ROW][C]200[/C][C]0.0254685[/C][C]0.0509371[/C][C]0.974531[/C][/ROW]
[ROW][C]201[/C][C]0.0242099[/C][C]0.0484199[/C][C]0.97579[/C][/ROW]
[ROW][C]202[/C][C]0.020183[/C][C]0.040366[/C][C]0.979817[/C][/ROW]
[ROW][C]203[/C][C]0.0255271[/C][C]0.0510543[/C][C]0.974473[/C][/ROW]
[ROW][C]204[/C][C]0.0280599[/C][C]0.0561197[/C][C]0.97194[/C][/ROW]
[ROW][C]205[/C][C]0.0312224[/C][C]0.0624449[/C][C]0.968778[/C][/ROW]
[ROW][C]206[/C][C]0.0245716[/C][C]0.0491432[/C][C]0.975428[/C][/ROW]
[ROW][C]207[/C][C]0.0242699[/C][C]0.0485398[/C][C]0.97573[/C][/ROW]
[ROW][C]208[/C][C]0.0199693[/C][C]0.0399386[/C][C]0.980031[/C][/ROW]
[ROW][C]209[/C][C]0.0216728[/C][C]0.0433457[/C][C]0.978327[/C][/ROW]
[ROW][C]210[/C][C]0.0174563[/C][C]0.0349127[/C][C]0.982544[/C][/ROW]
[ROW][C]211[/C][C]0.0189293[/C][C]0.0378586[/C][C]0.981071[/C][/ROW]
[ROW][C]212[/C][C]0.0292703[/C][C]0.0585406[/C][C]0.97073[/C][/ROW]
[ROW][C]213[/C][C]0.0228694[/C][C]0.0457387[/C][C]0.977131[/C][/ROW]
[ROW][C]214[/C][C]0.033024[/C][C]0.066048[/C][C]0.966976[/C][/ROW]
[ROW][C]215[/C][C]0.0284569[/C][C]0.0569137[/C][C]0.971543[/C][/ROW]
[ROW][C]216[/C][C]0.022085[/C][C]0.04417[/C][C]0.977915[/C][/ROW]
[ROW][C]217[/C][C]0.0243591[/C][C]0.0487182[/C][C]0.975641[/C][/ROW]
[ROW][C]218[/C][C]0.0204896[/C][C]0.0409792[/C][C]0.97951[/C][/ROW]
[ROW][C]219[/C][C]0.0183206[/C][C]0.0366411[/C][C]0.981679[/C][/ROW]
[ROW][C]220[/C][C]0.0137548[/C][C]0.0275096[/C][C]0.986245[/C][/ROW]
[ROW][C]221[/C][C]0.0119272[/C][C]0.0238545[/C][C]0.988073[/C][/ROW]
[ROW][C]222[/C][C]0.00858122[/C][C]0.0171624[/C][C]0.991419[/C][/ROW]
[ROW][C]223[/C][C]0.00634657[/C][C]0.0126931[/C][C]0.993653[/C][/ROW]
[ROW][C]224[/C][C]0.00496472[/C][C]0.00992943[/C][C]0.995035[/C][/ROW]
[ROW][C]225[/C][C]0.00429465[/C][C]0.00858929[/C][C]0.995705[/C][/ROW]
[ROW][C]226[/C][C]0.00994629[/C][C]0.0198926[/C][C]0.990054[/C][/ROW]
[ROW][C]227[/C][C]0.00753438[/C][C]0.0150688[/C][C]0.992466[/C][/ROW]
[ROW][C]228[/C][C]0.00537339[/C][C]0.0107468[/C][C]0.994627[/C][/ROW]
[ROW][C]229[/C][C]0.00380718[/C][C]0.00761436[/C][C]0.996193[/C][/ROW]
[ROW][C]230[/C][C]0.00266471[/C][C]0.00532942[/C][C]0.997335[/C][/ROW]
[ROW][C]231[/C][C]0.00267158[/C][C]0.00534316[/C][C]0.997328[/C][/ROW]
[ROW][C]232[/C][C]0.00494336[/C][C]0.00988673[/C][C]0.995057[/C][/ROW]
[ROW][C]233[/C][C]0.0259467[/C][C]0.0518935[/C][C]0.974053[/C][/ROW]
[ROW][C]234[/C][C]0.0384579[/C][C]0.0769159[/C][C]0.961542[/C][/ROW]
[ROW][C]235[/C][C]0.0277188[/C][C]0.0554376[/C][C]0.972281[/C][/ROW]
[ROW][C]236[/C][C]0.0239618[/C][C]0.0479236[/C][C]0.976038[/C][/ROW]
[ROW][C]237[/C][C]0.187771[/C][C]0.375542[/C][C]0.812229[/C][/ROW]
[ROW][C]238[/C][C]0.147045[/C][C]0.29409[/C][C]0.852955[/C][/ROW]
[ROW][C]239[/C][C]0.130216[/C][C]0.260432[/C][C]0.869784[/C][/ROW]
[ROW][C]240[/C][C]0.0988684[/C][C]0.197737[/C][C]0.901132[/C][/ROW]
[ROW][C]241[/C][C]0.0766001[/C][C]0.1532[/C][C]0.9234[/C][/ROW]
[ROW][C]242[/C][C]0.0614634[/C][C]0.122927[/C][C]0.938537[/C][/ROW]
[ROW][C]243[/C][C]0.0562098[/C][C]0.11242[/C][C]0.94379[/C][/ROW]
[ROW][C]244[/C][C]0.103563[/C][C]0.207125[/C][C]0.896437[/C][/ROW]
[ROW][C]245[/C][C]0.0907838[/C][C]0.181568[/C][C]0.909216[/C][/ROW]
[ROW][C]246[/C][C]0.0696383[/C][C]0.139277[/C][C]0.930362[/C][/ROW]
[ROW][C]247[/C][C]0.0465296[/C][C]0.0930593[/C][C]0.95347[/C][/ROW]
[ROW][C]248[/C][C]0.037806[/C][C]0.075612[/C][C]0.962194[/C][/ROW]
[ROW][C]249[/C][C]0.0340747[/C][C]0.0681495[/C][C]0.965925[/C][/ROW]
[ROW][C]250[/C][C]0.0414489[/C][C]0.0828977[/C][C]0.958551[/C][/ROW]
[ROW][C]251[/C][C]0.0218224[/C][C]0.0436449[/C][C]0.978178[/C][/ROW]
[ROW][C]252[/C][C]0.0547427[/C][C]0.109485[/C][C]0.945257[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267527&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267527&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
120.2492720.4985450.750728
130.1689540.3379080.831046
140.1886520.3773050.811348
150.1138220.2276440.886178
160.07735820.1547160.922642
170.111090.222180.88891
180.3502970.7005940.649703
190.2730760.5461520.726924
200.2003650.400730.799635
210.1473290.2946580.852671
220.142430.284860.85757
230.3296140.6592270.670386
240.3961080.7922160.603892
250.3646440.7292880.635356
260.3430140.6860280.656986
270.4195220.8390440.580478
280.4310390.8620790.568961
290.4111780.8223570.588822
300.4445630.8891260.555437
310.3891820.7783640.610818
320.3466210.6932420.653379
330.3166770.6333540.683323
340.2756750.551350.724325
350.233140.4662790.76686
360.3636240.7272480.636376
370.400480.800960.59952
380.3925180.7850370.607482
390.4206470.8412940.579353
400.3940370.7880730.605963
410.3526090.7052170.647391
420.3178160.6356310.682184
430.3306030.6612060.669397
440.2841930.5683860.715807
450.2593070.5186150.740693
460.4573730.9147460.542627
470.6130150.773970.386985
480.5647910.8704180.435209
490.5501160.8997680.449884
500.5388870.9222260.461113
510.4960290.9920580.503971
520.4489770.8979530.551023
530.469410.938820.53059
540.4498340.8996680.550166
550.4520660.9041320.547934
560.4207090.8414170.579291
570.3771220.7542440.622878
580.3435040.6870090.656496
590.3053820.6107630.694618
600.3047160.6094310.695284
610.2748850.5497710.725115
620.2433920.4867830.756608
630.2132060.4264110.786794
640.184850.3697010.81515
650.1596120.3192240.840388
660.1357020.2714030.864298
670.1180790.2361570.881921
680.1474920.2949830.852508
690.3472560.6945110.652744
700.3093840.6187670.690616
710.4660180.9320370.533982
720.4276950.855390.572305
730.4157560.8315130.584244
740.3945460.7890920.605454
750.3594440.7188890.640556
760.4070740.8141480.592926
770.3743010.7486010.625699
780.3465910.6931830.653409
790.3751240.7502480.624876
800.3445240.6890480.655476
810.3118930.6237860.688107
820.2778010.5556020.722199
830.2541370.5082740.745863
840.2233820.4467640.776618
850.2136240.4272490.786376
860.1860950.372190.813905
870.1627840.3255690.837216
880.1479690.2959390.852031
890.1275370.2550740.872463
900.1293260.2586530.870674
910.1115350.2230710.888465
920.09612840.1922570.903872
930.08255030.1651010.91745
940.08774250.1754850.912257
950.0780880.1561760.921912
960.06582940.1316590.934171
970.06890680.1378140.931093
980.0573580.1147160.942642
990.04759060.09518130.952409
1000.04254390.08508770.957456
1010.03698590.07397190.963014
1020.04200020.08400050.958
1030.03566540.07133080.964335
1040.03166650.0633330.968333
1050.03880950.0776190.961191
1060.03358010.06716020.96642
1070.02729040.05458080.97271
1080.02601340.05202680.973987
1090.02122210.04244430.978778
1100.01720380.03440760.982796
1110.01363220.02726440.986368
1120.01362280.02724550.986377
1130.01248730.02497460.987513
1140.01914620.03829240.980854
1150.01776170.03552340.982238
1160.01760360.03520730.982396
1170.01436510.02873020.985635
1180.01493330.02986660.985067
1190.01206910.02413820.987931
1200.01101720.02203440.988983
1210.008849280.01769860.991151
1220.0140520.0281040.985948
1230.01204310.02408620.987957
1240.0108230.02164610.989177
1250.009037310.01807460.990963
1260.007284510.0145690.992715
1270.006399140.01279830.993601
1280.005106590.01021320.994893
1290.007833750.01566750.992166
1300.008079630.01615930.99192
1310.01809490.03618990.981905
1320.0203690.04073790.979631
1330.02326180.04652350.976738
1340.02325620.04651240.976744
1350.0190360.03807210.980964
1360.01563720.03127450.984363
1370.0124430.0248860.987557
1380.01657730.03315450.983423
1390.01492410.02984810.985076
1400.01903120.03806230.980969
1410.02611290.05222590.973887
1420.02329660.04659320.976703
1430.01901340.03802680.980987
1440.01807750.03615490.981923
1450.03550260.07100520.964497
1460.03842220.07684440.961578
1470.04319880.08639750.956801
1480.03696460.07392920.963035
1490.03032680.06065370.969673
1500.04572930.09145870.954271
1510.04138110.08276220.958619
1520.04108710.08217420.958913
1530.07170820.1434160.928292
1540.06315970.1263190.93684
1550.07711280.1542260.922887
1560.06481480.129630.935185
1570.05642130.1128430.943579
1580.04785030.09570060.95215
1590.0454570.0909140.954543
1600.03903550.07807110.960964
1610.03186880.06373760.968131
1620.02618790.05237590.973812
1630.02158130.04316270.978419
1640.01825240.03650480.981748
1650.01613830.03227670.983862
1660.01625170.03250330.983748
1670.01295680.02591360.987043
1680.01847940.03695880.981521
1690.01789430.03578850.982106
1700.01701890.03403780.982981
1710.01656170.03312330.983438
1720.0134360.02687210.986564
1730.01295840.02591670.987042
1740.01387740.02775490.986123
1750.01724080.03448150.982759
1760.01389520.02779030.986105
1770.0110520.0221040.988948
1780.008870740.01774150.991129
1790.006883220.01376640.993117
1800.005774440.01154890.994226
1810.004853940.009707870.995146
1820.00378880.00757760.996211
1830.00424150.0084830.995759
1840.003270550.006541090.996729
1850.07284070.1456810.927159
1860.06383690.1276740.936163
1870.07555140.1511030.924449
1880.06403710.1280740.935963
1890.05365420.1073080.946346
1900.04430830.08861670.955692
1910.03873350.07746710.961266
1920.03248040.06496090.96752
1930.0387770.0775540.961223
1940.04258040.08516070.95742
1950.03554150.0710830.964459
1960.0291430.0582860.970857
1970.03934320.07868640.960657
1980.03217520.06435030.967825
1990.02996920.05993830.970031
2000.02546850.05093710.974531
2010.02420990.04841990.97579
2020.0201830.0403660.979817
2030.02552710.05105430.974473
2040.02805990.05611970.97194
2050.03122240.06244490.968778
2060.02457160.04914320.975428
2070.02426990.04853980.97573
2080.01996930.03993860.980031
2090.02167280.04334570.978327
2100.01745630.03491270.982544
2110.01892930.03785860.981071
2120.02927030.05854060.97073
2130.02286940.04573870.977131
2140.0330240.0660480.966976
2150.02845690.05691370.971543
2160.0220850.044170.977915
2170.02435910.04871820.975641
2180.02048960.04097920.97951
2190.01832060.03664110.981679
2200.01375480.02750960.986245
2210.01192720.02385450.988073
2220.008581220.01716240.991419
2230.006346570.01269310.993653
2240.004964720.009929430.995035
2250.004294650.008589290.995705
2260.009946290.01989260.990054
2270.007534380.01506880.992466
2280.005373390.01074680.994627
2290.003807180.007614360.996193
2300.002664710.005329420.997335
2310.002671580.005343160.997328
2320.004943360.009886730.995057
2330.02594670.05189350.974053
2340.03845790.07691590.961542
2350.02771880.05543760.972281
2360.02396180.04792360.976038
2370.1877710.3755420.812229
2380.1470450.294090.852955
2390.1302160.2604320.869784
2400.09886840.1977370.901132
2410.07660010.15320.9234
2420.06146340.1229270.938537
2430.05620980.112420.94379
2440.1035630.2071250.896437
2450.09078380.1815680.909216
2460.06963830.1392770.930362
2470.04652960.09305930.95347
2480.0378060.0756120.962194
2490.03407470.06814950.965925
2500.04144890.08289770.958551
2510.02182240.04364490.978178
2520.05474270.1094850.945257






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.0414938NOK
5% type I error level850.352697NOK
10% type I error level1330.551867NOK

\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 & 10 & 0.0414938 & NOK \tabularnewline
5% type I error level & 85 & 0.352697 & NOK \tabularnewline
10% type I error level & 133 & 0.551867 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267527&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]10[/C][C]0.0414938[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]85[/C][C]0.352697[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]133[/C][C]0.551867[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267527&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267527&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 level100.0414938NOK
5% type I error level850.352697NOK
10% type I error level1330.551867NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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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 = 2 ; par3 = Pearson Chi-Squared ;
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')
}