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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, 03 Nov 2013 09:55:17 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/03/t1383490796r9wbd592pnbqrr0.htm/, Retrieved Mon, 29 Apr 2024 15:09:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221929, Retrieved Mon, 29 Apr 2024 15:09:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact53

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Ws7 met tijdsvari...] [2013-11-03 14:55:17] [113c22c9ed50e819fac395000376f96b] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time24 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 24 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221929&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]24 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221929&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221929&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 time24 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 4.29369 -0.0175723Connected[t] + 0.0386463Separate[t] + 0.552864Learning[t] -0.0164329Happiness[t] -0.00235835Depression[t] + 0.0214237Sport1[t] -0.022855Sport2[t] -0.258721Month[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Software[t] =  +  4.29369 -0.0175723Connected[t] +  0.0386463Separate[t] +  0.552864Learning[t] -0.0164329Happiness[t] -0.00235835Depression[t] +  0.0214237Sport1[t] -0.022855Sport2[t] -0.258721Month[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221929&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Software[t] =  +  4.29369 -0.0175723Connected[t] +  0.0386463Separate[t] +  0.552864Learning[t] -0.0164329Happiness[t] -0.00235835Depression[t] +  0.0214237Sport1[t] -0.022855Sport2[t] -0.258721Month[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221929&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221929&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 4.29369 -0.0175723Connected[t] + 0.0386463Separate[t] + 0.552864Learning[t] -0.0164329Happiness[t] -0.00235835Depression[t] + 0.0214237Sport1[t] -0.022855Sport2[t] -0.258721Month[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.293692.600561.6510.0999570.0499785
Connected-0.01757230.0340982-0.51530.6067590.30338
Separate0.03864630.034581.1180.2647930.132397
Learning0.5528640.050645710.925.1445e-232.57225e-23
Happiness-0.01643290.056869-0.2890.7728460.386423
Depression-0.002358350.041604-0.056690.954840.47742
Sport10.02142370.03701460.57880.5632420.281621
Sport2-0.0228550.0549745-0.41570.6779510.338976
Month-0.2587210.157399-1.6440.1014650.0507325

\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) & 4.29369 & 2.60056 & 1.651 & 0.099957 & 0.0499785 \tabularnewline
Connected & -0.0175723 & 0.0340982 & -0.5153 & 0.606759 & 0.30338 \tabularnewline
Separate & 0.0386463 & 0.03458 & 1.118 & 0.264793 & 0.132397 \tabularnewline
Learning & 0.552864 & 0.0506457 & 10.92 & 5.1445e-23 & 2.57225e-23 \tabularnewline
Happiness & -0.0164329 & 0.056869 & -0.289 & 0.772846 & 0.386423 \tabularnewline
Depression & -0.00235835 & 0.041604 & -0.05669 & 0.95484 & 0.47742 \tabularnewline
Sport1 & 0.0214237 & 0.0370146 & 0.5788 & 0.563242 & 0.281621 \tabularnewline
Sport2 & -0.022855 & 0.0549745 & -0.4157 & 0.677951 & 0.338976 \tabularnewline
Month & -0.258721 & 0.157399 & -1.644 & 0.101465 & 0.0507325 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221929&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]4.29369[/C][C]2.60056[/C][C]1.651[/C][C]0.099957[/C][C]0.0499785[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0175723[/C][C]0.0340982[/C][C]-0.5153[/C][C]0.606759[/C][C]0.30338[/C][/ROW]
[ROW][C]Separate[/C][C]0.0386463[/C][C]0.03458[/C][C]1.118[/C][C]0.264793[/C][C]0.132397[/C][/ROW]
[ROW][C]Learning[/C][C]0.552864[/C][C]0.0506457[/C][C]10.92[/C][C]5.1445e-23[/C][C]2.57225e-23[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.0164329[/C][C]0.056869[/C][C]-0.289[/C][C]0.772846[/C][C]0.386423[/C][/ROW]
[ROW][C]Depression[/C][C]-0.00235835[/C][C]0.041604[/C][C]-0.05669[/C][C]0.95484[/C][C]0.47742[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0214237[/C][C]0.0370146[/C][C]0.5788[/C][C]0.563242[/C][C]0.281621[/C][/ROW]
[ROW][C]Sport2[/C][C]-0.022855[/C][C]0.0549745[/C][C]-0.4157[/C][C]0.677951[/C][C]0.338976[/C][/ROW]
[ROW][C]Month[/C][C]-0.258721[/C][C]0.157399[/C][C]-1.644[/C][C]0.101465[/C][C]0.0507325[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221929&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221929&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)4.293692.600561.6510.0999570.0499785
Connected-0.01757230.0340982-0.51530.6067590.30338
Separate0.03864630.034581.1180.2647930.132397
Learning0.5528640.050645710.925.1445e-232.57225e-23
Happiness-0.01643290.056869-0.2890.7728460.386423
Depression-0.002358350.041604-0.056690.954840.47742
Sport10.02142370.03701460.57880.5632420.281621
Sport2-0.0228550.0549745-0.41570.6779510.338976
Month-0.2587210.157399-1.6440.1014650.0507325






Multiple Linear Regression - Regression Statistics
Multiple R0.631531
R-squared0.398832
Adjusted R-squared0.379972
F-TEST (value)21.1468
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.82684
Sum Squared Residuals851.027

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.631531 \tabularnewline
R-squared & 0.398832 \tabularnewline
Adjusted R-squared & 0.379972 \tabularnewline
F-TEST (value) & 21.1468 \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 & 1.82684 \tabularnewline
Sum Squared Residuals & 851.027 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221929&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.631531[/C][/ROW]
[ROW][C]R-squared[/C][C]0.398832[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.379972[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]21.1468[/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]1.82684[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]851.027[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221929&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221929&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 R0.631531
R-squared0.398832
Adjusted R-squared0.379972
F-TEST (value)21.1468
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.82684
Sum Squared Residuals851.027






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.04631.95373
21111.6532-0.653217
31513.53531.46465
4611.2616-5.26159
51310.80222.19783
6109.930920.0690816
71212.9902-0.990212
81411.392.61003
91210.71211.28788
10911.3534-2.35341
111011.6109-1.61095
121211.5640.436028
131211.77170.228326
141111.701-0.700989
151512.54712.45291
161211.12790.872105
171011.1775-1.17747
181214.1691-2.16911
191112.8804-1.88041
201211.59020.409819
211111.6828-0.682754
221211.70170.298266
231313.3972-0.397163
241111.7919-0.791938
251212.2639-0.26393
261312.35070.649301
271011.8876-1.88761
281411.31542.68463
291211.86950.130467
301010.6015-0.601516
311211.22130.778693
3289.51546-1.51546
331010.4885-0.488534
341211.93650.0635324
351210.6321.36805
3678.44053-1.44053
3798.491280.508724
381210.61151.38845
391011.7734-1.77339
401011.7524-1.75244
411011.6867-1.68669
421210.68841.31162
431513.71231.28771
441010.5409-0.540912
451010.3655-0.365538
46129.080342.91966
471310.68682.31319
481111.2753-0.275264
491111.9577-0.957693
501210.6131.38703
511411.96762.03235
521010.5605-0.560485
53129.593432.40657
541311.72891.27114
5557.91912-2.91912
56610.6811-4.68107
571211.7030.297024
581211.82320.176836
591111.3596-0.359642
601011.7943-1.7943
6179.37996-2.37996
621211.83650.163524
631411.9742.02602
641110.65560.344372
651211.53710.462883
661312.32380.676217
671412.61131.38875
681112.5757-1.5757
69129.405432.59457
701211.6060.393996
7188.12769-0.12769
721110.47480.525241
731412.92891.07109
741412.86871.13126
751211.41560.58443
76911.9312-2.93124
771311.53891.46108
781111.3718-0.371779
79129.898012.10199
801211.11340.886606
811211.73240.267606
821211.59210.407922
831210.91451.08547
841111.0132-0.0131955
851011.4852-1.48518
86910.5872-1.58719
871211.54640.453641
881211.43310.566947
891211.04490.955135
9099.38996-0.389957
911511.86293.13709
921211.84290.157083
931210.91351.08651
94129.940112.05989
951011.6091-1.6091
961311.51531.48471
97911.499-2.49903
981211.54910.450916
991010.5823-0.582325
1001411.57262.42739
1011111.5553-0.555279
1021513.90241.0976
1031110.76660.233424
1041111.8137-0.813686
105129.754562.24544
1061212.0552-0.0551915
1071211.59310.406862
1081111.4753-0.475285
10979.2873-2.2873
1101211.69220.307844
1111411.64652.35351
1121112.516-1.51605
113119.903991.09601
114109.234570.765427
1151312.58920.410846
1161310.55212.44787
117810.564-2.56402
118119.933491.06651
1191211.68150.318502
120119.913841.08616
1211311.36481.63519
1221210.13331.86672
1231411.65932.34065
1241310.82792.17211
1251511.66163.33839
1261010.9237-0.923686
1271112.116-1.11599
128910.9967-1.99666
129119.260881.73912
1301011.5869-1.58692
131118.284482.71552
132811.6075-3.60755
133119.222261.77774
1341210.52421.47581
1351210.87161.12837
13699.41957-0.419569
1371110.88130.11869
138108.75191.2481
13989.22428-1.22428
14098.895120.104883
141811.4366-3.43655
142911.2402-2.24023
1431512.30342.69662
1441111.2199-0.219931
14588.09108-0.0910811
1461312.4020.598039
147129.857892.14211
1481211.52030.479661
14999.83526-0.835261
15078.39305-1.39305
1511311.05591.94411
152911.7233-2.72328
153611.7559-5.75587
154810.6543-2.65429
15588.10264-0.102637
1561511.86293.13709
15769.99371-3.99371
158910.9967-1.99666
1591111.5907-0.590663
16089.66429-1.66429
16189.86307-1.86307
162109.375610.624385
16388.94025-0.940249
1641411.75792.24207
1651011.0034-1.00343
16687.881720.118285
1671110.25170.748336
168128.388063.61194
169129.934462.06554
1701211.68560.314425
17158.80329-3.80329
1721211.33660.663445
173109.134950.865047
17477.09045-0.0904512
175128.774923.22508
1761110.96160.0383961
17788.9957-0.995699
17899.01588-0.0158842
1791010.053-0.0529741
18099.25596-0.25596
1811211.19890.801088
18268.3371-2.3371
1831513.02031.97969
1841210.67291.32713
185126.926995.07301
1861211.48670.513317
1871111.8673-0.867332
18878.99545-1.99545
18978.34392-1.34392
19058.54343-3.54343
1911210.36811.63191
1921211.51920.480797
19339.0316-6.0316
1941111.2812-0.281187
195109.566740.433263
1961210.82761.17235
197911.2147-2.21473
1981211.53070.469277
199910.1897-1.18966
2001211.47310.526894
2011211.21040.789567
2021010.2148-0.214752
20398.471410.528592
204128.831663.16834
205810.7621-2.76212
2061110.81430.185743
2071111.4141-0.414097
2081211.1770.822953
209108.419381.58062
2101010.7842-0.784205
211129.028932.97107
212129.361512.63849
2131111.0921-0.0920929
214810.8278-2.82782
2151211.33150.66849
216109.840320.159676
2171111.9464-0.946437
2181010.1479-0.147858
21989.65573-1.65573
2201210.90411.0959
221129.66312.3369
2221010.1542-0.15422
2231210.731.27002
22499.04324-0.0432369
22599.79408-0.794076
22667.03283-1.03283
227109.94430.0557049
228910.2691-1.26907
22998.475480.524516
23099.14276-0.142765
23169.47688-3.47688
232108.109211.89079
233611.1973-5.19732
2341412.19161.80837
235109.526950.473049
236108.397811.60219
23764.416591.58341
238129.118522.88148
2391211.35150.648505
24077.81344-0.813439
24189.29755-1.29755
242119.001831.99817
24337.77419-4.77419
24469.56013-3.56013
2451010.5545-0.5545
24689.21555-1.21555
247910.2032-1.20321
24897.576021.42398
24988.72528-0.725279
25098.700910.299085
25178.55874-1.55874
25277.97634-0.97634
25369.03939-3.03939
254911.2201-2.22013
255108.921191.07881
2561110.08580.91422
2571211.53510.464941
258810.1035-2.10352
259119.515261.48474
26034.61009-1.61009
2611110.66990.330076
262128.645333.35467
26378.48765-1.48765
264910.2163-1.21632

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 10.0463 & 1.95373 \tabularnewline
2 & 11 & 11.6532 & -0.653217 \tabularnewline
3 & 15 & 13.5353 & 1.46465 \tabularnewline
4 & 6 & 11.2616 & -5.26159 \tabularnewline
5 & 13 & 10.8022 & 2.19783 \tabularnewline
6 & 10 & 9.93092 & 0.0690816 \tabularnewline
7 & 12 & 12.9902 & -0.990212 \tabularnewline
8 & 14 & 11.39 & 2.61003 \tabularnewline
9 & 12 & 10.7121 & 1.28788 \tabularnewline
10 & 9 & 11.3534 & -2.35341 \tabularnewline
11 & 10 & 11.6109 & -1.61095 \tabularnewline
12 & 12 & 11.564 & 0.436028 \tabularnewline
13 & 12 & 11.7717 & 0.228326 \tabularnewline
14 & 11 & 11.701 & -0.700989 \tabularnewline
15 & 15 & 12.5471 & 2.45291 \tabularnewline
16 & 12 & 11.1279 & 0.872105 \tabularnewline
17 & 10 & 11.1775 & -1.17747 \tabularnewline
18 & 12 & 14.1691 & -2.16911 \tabularnewline
19 & 11 & 12.8804 & -1.88041 \tabularnewline
20 & 12 & 11.5902 & 0.409819 \tabularnewline
21 & 11 & 11.6828 & -0.682754 \tabularnewline
22 & 12 & 11.7017 & 0.298266 \tabularnewline
23 & 13 & 13.3972 & -0.397163 \tabularnewline
24 & 11 & 11.7919 & -0.791938 \tabularnewline
25 & 12 & 12.2639 & -0.26393 \tabularnewline
26 & 13 & 12.3507 & 0.649301 \tabularnewline
27 & 10 & 11.8876 & -1.88761 \tabularnewline
28 & 14 & 11.3154 & 2.68463 \tabularnewline
29 & 12 & 11.8695 & 0.130467 \tabularnewline
30 & 10 & 10.6015 & -0.601516 \tabularnewline
31 & 12 & 11.2213 & 0.778693 \tabularnewline
32 & 8 & 9.51546 & -1.51546 \tabularnewline
33 & 10 & 10.4885 & -0.488534 \tabularnewline
34 & 12 & 11.9365 & 0.0635324 \tabularnewline
35 & 12 & 10.632 & 1.36805 \tabularnewline
36 & 7 & 8.44053 & -1.44053 \tabularnewline
37 & 9 & 8.49128 & 0.508724 \tabularnewline
38 & 12 & 10.6115 & 1.38845 \tabularnewline
39 & 10 & 11.7734 & -1.77339 \tabularnewline
40 & 10 & 11.7524 & -1.75244 \tabularnewline
41 & 10 & 11.6867 & -1.68669 \tabularnewline
42 & 12 & 10.6884 & 1.31162 \tabularnewline
43 & 15 & 13.7123 & 1.28771 \tabularnewline
44 & 10 & 10.5409 & -0.540912 \tabularnewline
45 & 10 & 10.3655 & -0.365538 \tabularnewline
46 & 12 & 9.08034 & 2.91966 \tabularnewline
47 & 13 & 10.6868 & 2.31319 \tabularnewline
48 & 11 & 11.2753 & -0.275264 \tabularnewline
49 & 11 & 11.9577 & -0.957693 \tabularnewline
50 & 12 & 10.613 & 1.38703 \tabularnewline
51 & 14 & 11.9676 & 2.03235 \tabularnewline
52 & 10 & 10.5605 & -0.560485 \tabularnewline
53 & 12 & 9.59343 & 2.40657 \tabularnewline
54 & 13 & 11.7289 & 1.27114 \tabularnewline
55 & 5 & 7.91912 & -2.91912 \tabularnewline
56 & 6 & 10.6811 & -4.68107 \tabularnewline
57 & 12 & 11.703 & 0.297024 \tabularnewline
58 & 12 & 11.8232 & 0.176836 \tabularnewline
59 & 11 & 11.3596 & -0.359642 \tabularnewline
60 & 10 & 11.7943 & -1.7943 \tabularnewline
61 & 7 & 9.37996 & -2.37996 \tabularnewline
62 & 12 & 11.8365 & 0.163524 \tabularnewline
63 & 14 & 11.974 & 2.02602 \tabularnewline
64 & 11 & 10.6556 & 0.344372 \tabularnewline
65 & 12 & 11.5371 & 0.462883 \tabularnewline
66 & 13 & 12.3238 & 0.676217 \tabularnewline
67 & 14 & 12.6113 & 1.38875 \tabularnewline
68 & 11 & 12.5757 & -1.5757 \tabularnewline
69 & 12 & 9.40543 & 2.59457 \tabularnewline
70 & 12 & 11.606 & 0.393996 \tabularnewline
71 & 8 & 8.12769 & -0.12769 \tabularnewline
72 & 11 & 10.4748 & 0.525241 \tabularnewline
73 & 14 & 12.9289 & 1.07109 \tabularnewline
74 & 14 & 12.8687 & 1.13126 \tabularnewline
75 & 12 & 11.4156 & 0.58443 \tabularnewline
76 & 9 & 11.9312 & -2.93124 \tabularnewline
77 & 13 & 11.5389 & 1.46108 \tabularnewline
78 & 11 & 11.3718 & -0.371779 \tabularnewline
79 & 12 & 9.89801 & 2.10199 \tabularnewline
80 & 12 & 11.1134 & 0.886606 \tabularnewline
81 & 12 & 11.7324 & 0.267606 \tabularnewline
82 & 12 & 11.5921 & 0.407922 \tabularnewline
83 & 12 & 10.9145 & 1.08547 \tabularnewline
84 & 11 & 11.0132 & -0.0131955 \tabularnewline
85 & 10 & 11.4852 & -1.48518 \tabularnewline
86 & 9 & 10.5872 & -1.58719 \tabularnewline
87 & 12 & 11.5464 & 0.453641 \tabularnewline
88 & 12 & 11.4331 & 0.566947 \tabularnewline
89 & 12 & 11.0449 & 0.955135 \tabularnewline
90 & 9 & 9.38996 & -0.389957 \tabularnewline
91 & 15 & 11.8629 & 3.13709 \tabularnewline
92 & 12 & 11.8429 & 0.157083 \tabularnewline
93 & 12 & 10.9135 & 1.08651 \tabularnewline
94 & 12 & 9.94011 & 2.05989 \tabularnewline
95 & 10 & 11.6091 & -1.6091 \tabularnewline
96 & 13 & 11.5153 & 1.48471 \tabularnewline
97 & 9 & 11.499 & -2.49903 \tabularnewline
98 & 12 & 11.5491 & 0.450916 \tabularnewline
99 & 10 & 10.5823 & -0.582325 \tabularnewline
100 & 14 & 11.5726 & 2.42739 \tabularnewline
101 & 11 & 11.5553 & -0.555279 \tabularnewline
102 & 15 & 13.9024 & 1.0976 \tabularnewline
103 & 11 & 10.7666 & 0.233424 \tabularnewline
104 & 11 & 11.8137 & -0.813686 \tabularnewline
105 & 12 & 9.75456 & 2.24544 \tabularnewline
106 & 12 & 12.0552 & -0.0551915 \tabularnewline
107 & 12 & 11.5931 & 0.406862 \tabularnewline
108 & 11 & 11.4753 & -0.475285 \tabularnewline
109 & 7 & 9.2873 & -2.2873 \tabularnewline
110 & 12 & 11.6922 & 0.307844 \tabularnewline
111 & 14 & 11.6465 & 2.35351 \tabularnewline
112 & 11 & 12.516 & -1.51605 \tabularnewline
113 & 11 & 9.90399 & 1.09601 \tabularnewline
114 & 10 & 9.23457 & 0.765427 \tabularnewline
115 & 13 & 12.5892 & 0.410846 \tabularnewline
116 & 13 & 10.5521 & 2.44787 \tabularnewline
117 & 8 & 10.564 & -2.56402 \tabularnewline
118 & 11 & 9.93349 & 1.06651 \tabularnewline
119 & 12 & 11.6815 & 0.318502 \tabularnewline
120 & 11 & 9.91384 & 1.08616 \tabularnewline
121 & 13 & 11.3648 & 1.63519 \tabularnewline
122 & 12 & 10.1333 & 1.86672 \tabularnewline
123 & 14 & 11.6593 & 2.34065 \tabularnewline
124 & 13 & 10.8279 & 2.17211 \tabularnewline
125 & 15 & 11.6616 & 3.33839 \tabularnewline
126 & 10 & 10.9237 & -0.923686 \tabularnewline
127 & 11 & 12.116 & -1.11599 \tabularnewline
128 & 9 & 10.9967 & -1.99666 \tabularnewline
129 & 11 & 9.26088 & 1.73912 \tabularnewline
130 & 10 & 11.5869 & -1.58692 \tabularnewline
131 & 11 & 8.28448 & 2.71552 \tabularnewline
132 & 8 & 11.6075 & -3.60755 \tabularnewline
133 & 11 & 9.22226 & 1.77774 \tabularnewline
134 & 12 & 10.5242 & 1.47581 \tabularnewline
135 & 12 & 10.8716 & 1.12837 \tabularnewline
136 & 9 & 9.41957 & -0.419569 \tabularnewline
137 & 11 & 10.8813 & 0.11869 \tabularnewline
138 & 10 & 8.7519 & 1.2481 \tabularnewline
139 & 8 & 9.22428 & -1.22428 \tabularnewline
140 & 9 & 8.89512 & 0.104883 \tabularnewline
141 & 8 & 11.4366 & -3.43655 \tabularnewline
142 & 9 & 11.2402 & -2.24023 \tabularnewline
143 & 15 & 12.3034 & 2.69662 \tabularnewline
144 & 11 & 11.2199 & -0.219931 \tabularnewline
145 & 8 & 8.09108 & -0.0910811 \tabularnewline
146 & 13 & 12.402 & 0.598039 \tabularnewline
147 & 12 & 9.85789 & 2.14211 \tabularnewline
148 & 12 & 11.5203 & 0.479661 \tabularnewline
149 & 9 & 9.83526 & -0.835261 \tabularnewline
150 & 7 & 8.39305 & -1.39305 \tabularnewline
151 & 13 & 11.0559 & 1.94411 \tabularnewline
152 & 9 & 11.7233 & -2.72328 \tabularnewline
153 & 6 & 11.7559 & -5.75587 \tabularnewline
154 & 8 & 10.6543 & -2.65429 \tabularnewline
155 & 8 & 8.10264 & -0.102637 \tabularnewline
156 & 15 & 11.8629 & 3.13709 \tabularnewline
157 & 6 & 9.99371 & -3.99371 \tabularnewline
158 & 9 & 10.9967 & -1.99666 \tabularnewline
159 & 11 & 11.5907 & -0.590663 \tabularnewline
160 & 8 & 9.66429 & -1.66429 \tabularnewline
161 & 8 & 9.86307 & -1.86307 \tabularnewline
162 & 10 & 9.37561 & 0.624385 \tabularnewline
163 & 8 & 8.94025 & -0.940249 \tabularnewline
164 & 14 & 11.7579 & 2.24207 \tabularnewline
165 & 10 & 11.0034 & -1.00343 \tabularnewline
166 & 8 & 7.88172 & 0.118285 \tabularnewline
167 & 11 & 10.2517 & 0.748336 \tabularnewline
168 & 12 & 8.38806 & 3.61194 \tabularnewline
169 & 12 & 9.93446 & 2.06554 \tabularnewline
170 & 12 & 11.6856 & 0.314425 \tabularnewline
171 & 5 & 8.80329 & -3.80329 \tabularnewline
172 & 12 & 11.3366 & 0.663445 \tabularnewline
173 & 10 & 9.13495 & 0.865047 \tabularnewline
174 & 7 & 7.09045 & -0.0904512 \tabularnewline
175 & 12 & 8.77492 & 3.22508 \tabularnewline
176 & 11 & 10.9616 & 0.0383961 \tabularnewline
177 & 8 & 8.9957 & -0.995699 \tabularnewline
178 & 9 & 9.01588 & -0.0158842 \tabularnewline
179 & 10 & 10.053 & -0.0529741 \tabularnewline
180 & 9 & 9.25596 & -0.25596 \tabularnewline
181 & 12 & 11.1989 & 0.801088 \tabularnewline
182 & 6 & 8.3371 & -2.3371 \tabularnewline
183 & 15 & 13.0203 & 1.97969 \tabularnewline
184 & 12 & 10.6729 & 1.32713 \tabularnewline
185 & 12 & 6.92699 & 5.07301 \tabularnewline
186 & 12 & 11.4867 & 0.513317 \tabularnewline
187 & 11 & 11.8673 & -0.867332 \tabularnewline
188 & 7 & 8.99545 & -1.99545 \tabularnewline
189 & 7 & 8.34392 & -1.34392 \tabularnewline
190 & 5 & 8.54343 & -3.54343 \tabularnewline
191 & 12 & 10.3681 & 1.63191 \tabularnewline
192 & 12 & 11.5192 & 0.480797 \tabularnewline
193 & 3 & 9.0316 & -6.0316 \tabularnewline
194 & 11 & 11.2812 & -0.281187 \tabularnewline
195 & 10 & 9.56674 & 0.433263 \tabularnewline
196 & 12 & 10.8276 & 1.17235 \tabularnewline
197 & 9 & 11.2147 & -2.21473 \tabularnewline
198 & 12 & 11.5307 & 0.469277 \tabularnewline
199 & 9 & 10.1897 & -1.18966 \tabularnewline
200 & 12 & 11.4731 & 0.526894 \tabularnewline
201 & 12 & 11.2104 & 0.789567 \tabularnewline
202 & 10 & 10.2148 & -0.214752 \tabularnewline
203 & 9 & 8.47141 & 0.528592 \tabularnewline
204 & 12 & 8.83166 & 3.16834 \tabularnewline
205 & 8 & 10.7621 & -2.76212 \tabularnewline
206 & 11 & 10.8143 & 0.185743 \tabularnewline
207 & 11 & 11.4141 & -0.414097 \tabularnewline
208 & 12 & 11.177 & 0.822953 \tabularnewline
209 & 10 & 8.41938 & 1.58062 \tabularnewline
210 & 10 & 10.7842 & -0.784205 \tabularnewline
211 & 12 & 9.02893 & 2.97107 \tabularnewline
212 & 12 & 9.36151 & 2.63849 \tabularnewline
213 & 11 & 11.0921 & -0.0920929 \tabularnewline
214 & 8 & 10.8278 & -2.82782 \tabularnewline
215 & 12 & 11.3315 & 0.66849 \tabularnewline
216 & 10 & 9.84032 & 0.159676 \tabularnewline
217 & 11 & 11.9464 & -0.946437 \tabularnewline
218 & 10 & 10.1479 & -0.147858 \tabularnewline
219 & 8 & 9.65573 & -1.65573 \tabularnewline
220 & 12 & 10.9041 & 1.0959 \tabularnewline
221 & 12 & 9.6631 & 2.3369 \tabularnewline
222 & 10 & 10.1542 & -0.15422 \tabularnewline
223 & 12 & 10.73 & 1.27002 \tabularnewline
224 & 9 & 9.04324 & -0.0432369 \tabularnewline
225 & 9 & 9.79408 & -0.794076 \tabularnewline
226 & 6 & 7.03283 & -1.03283 \tabularnewline
227 & 10 & 9.9443 & 0.0557049 \tabularnewline
228 & 9 & 10.2691 & -1.26907 \tabularnewline
229 & 9 & 8.47548 & 0.524516 \tabularnewline
230 & 9 & 9.14276 & -0.142765 \tabularnewline
231 & 6 & 9.47688 & -3.47688 \tabularnewline
232 & 10 & 8.10921 & 1.89079 \tabularnewline
233 & 6 & 11.1973 & -5.19732 \tabularnewline
234 & 14 & 12.1916 & 1.80837 \tabularnewline
235 & 10 & 9.52695 & 0.473049 \tabularnewline
236 & 10 & 8.39781 & 1.60219 \tabularnewline
237 & 6 & 4.41659 & 1.58341 \tabularnewline
238 & 12 & 9.11852 & 2.88148 \tabularnewline
239 & 12 & 11.3515 & 0.648505 \tabularnewline
240 & 7 & 7.81344 & -0.813439 \tabularnewline
241 & 8 & 9.29755 & -1.29755 \tabularnewline
242 & 11 & 9.00183 & 1.99817 \tabularnewline
243 & 3 & 7.77419 & -4.77419 \tabularnewline
244 & 6 & 9.56013 & -3.56013 \tabularnewline
245 & 10 & 10.5545 & -0.5545 \tabularnewline
246 & 8 & 9.21555 & -1.21555 \tabularnewline
247 & 9 & 10.2032 & -1.20321 \tabularnewline
248 & 9 & 7.57602 & 1.42398 \tabularnewline
249 & 8 & 8.72528 & -0.725279 \tabularnewline
250 & 9 & 8.70091 & 0.299085 \tabularnewline
251 & 7 & 8.55874 & -1.55874 \tabularnewline
252 & 7 & 7.97634 & -0.97634 \tabularnewline
253 & 6 & 9.03939 & -3.03939 \tabularnewline
254 & 9 & 11.2201 & -2.22013 \tabularnewline
255 & 10 & 8.92119 & 1.07881 \tabularnewline
256 & 11 & 10.0858 & 0.91422 \tabularnewline
257 & 12 & 11.5351 & 0.464941 \tabularnewline
258 & 8 & 10.1035 & -2.10352 \tabularnewline
259 & 11 & 9.51526 & 1.48474 \tabularnewline
260 & 3 & 4.61009 & -1.61009 \tabularnewline
261 & 11 & 10.6699 & 0.330076 \tabularnewline
262 & 12 & 8.64533 & 3.35467 \tabularnewline
263 & 7 & 8.48765 & -1.48765 \tabularnewline
264 & 9 & 10.2163 & -1.21632 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221929&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]10.0463[/C][C]1.95373[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]11.6532[/C][C]-0.653217[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]13.5353[/C][C]1.46465[/C][/ROW]
[ROW][C]4[/C][C]6[/C][C]11.2616[/C][C]-5.26159[/C][/ROW]
[ROW][C]5[/C][C]13[/C][C]10.8022[/C][C]2.19783[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]9.93092[/C][C]0.0690816[/C][/ROW]
[ROW][C]7[/C][C]12[/C][C]12.9902[/C][C]-0.990212[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]11.39[/C][C]2.61003[/C][/ROW]
[ROW][C]9[/C][C]12[/C][C]10.7121[/C][C]1.28788[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]11.3534[/C][C]-2.35341[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]11.6109[/C][C]-1.61095[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]11.564[/C][C]0.436028[/C][/ROW]
[ROW][C]13[/C][C]12[/C][C]11.7717[/C][C]0.228326[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]11.701[/C][C]-0.700989[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]12.5471[/C][C]2.45291[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]11.1279[/C][C]0.872105[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]11.1775[/C][C]-1.17747[/C][/ROW]
[ROW][C]18[/C][C]12[/C][C]14.1691[/C][C]-2.16911[/C][/ROW]
[ROW][C]19[/C][C]11[/C][C]12.8804[/C][C]-1.88041[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]11.5902[/C][C]0.409819[/C][/ROW]
[ROW][C]21[/C][C]11[/C][C]11.6828[/C][C]-0.682754[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]11.7017[/C][C]0.298266[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]13.3972[/C][C]-0.397163[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]11.7919[/C][C]-0.791938[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]12.2639[/C][C]-0.26393[/C][/ROW]
[ROW][C]26[/C][C]13[/C][C]12.3507[/C][C]0.649301[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]11.8876[/C][C]-1.88761[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]11.3154[/C][C]2.68463[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]11.8695[/C][C]0.130467[/C][/ROW]
[ROW][C]30[/C][C]10[/C][C]10.6015[/C][C]-0.601516[/C][/ROW]
[ROW][C]31[/C][C]12[/C][C]11.2213[/C][C]0.778693[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]9.51546[/C][C]-1.51546[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.4885[/C][C]-0.488534[/C][/ROW]
[ROW][C]34[/C][C]12[/C][C]11.9365[/C][C]0.0635324[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.632[/C][C]1.36805[/C][/ROW]
[ROW][C]36[/C][C]7[/C][C]8.44053[/C][C]-1.44053[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]8.49128[/C][C]0.508724[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]10.6115[/C][C]1.38845[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]11.7734[/C][C]-1.77339[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]11.7524[/C][C]-1.75244[/C][/ROW]
[ROW][C]41[/C][C]10[/C][C]11.6867[/C][C]-1.68669[/C][/ROW]
[ROW][C]42[/C][C]12[/C][C]10.6884[/C][C]1.31162[/C][/ROW]
[ROW][C]43[/C][C]15[/C][C]13.7123[/C][C]1.28771[/C][/ROW]
[ROW][C]44[/C][C]10[/C][C]10.5409[/C][C]-0.540912[/C][/ROW]
[ROW][C]45[/C][C]10[/C][C]10.3655[/C][C]-0.365538[/C][/ROW]
[ROW][C]46[/C][C]12[/C][C]9.08034[/C][C]2.91966[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]10.6868[/C][C]2.31319[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.2753[/C][C]-0.275264[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]11.9577[/C][C]-0.957693[/C][/ROW]
[ROW][C]50[/C][C]12[/C][C]10.613[/C][C]1.38703[/C][/ROW]
[ROW][C]51[/C][C]14[/C][C]11.9676[/C][C]2.03235[/C][/ROW]
[ROW][C]52[/C][C]10[/C][C]10.5605[/C][C]-0.560485[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]9.59343[/C][C]2.40657[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.7289[/C][C]1.27114[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]7.91912[/C][C]-2.91912[/C][/ROW]
[ROW][C]56[/C][C]6[/C][C]10.6811[/C][C]-4.68107[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]11.703[/C][C]0.297024[/C][/ROW]
[ROW][C]58[/C][C]12[/C][C]11.8232[/C][C]0.176836[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]11.3596[/C][C]-0.359642[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]11.7943[/C][C]-1.7943[/C][/ROW]
[ROW][C]61[/C][C]7[/C][C]9.37996[/C][C]-2.37996[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]11.8365[/C][C]0.163524[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]11.974[/C][C]2.02602[/C][/ROW]
[ROW][C]64[/C][C]11[/C][C]10.6556[/C][C]0.344372[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]11.5371[/C][C]0.462883[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]12.3238[/C][C]0.676217[/C][/ROW]
[ROW][C]67[/C][C]14[/C][C]12.6113[/C][C]1.38875[/C][/ROW]
[ROW][C]68[/C][C]11[/C][C]12.5757[/C][C]-1.5757[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]9.40543[/C][C]2.59457[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]11.606[/C][C]0.393996[/C][/ROW]
[ROW][C]71[/C][C]8[/C][C]8.12769[/C][C]-0.12769[/C][/ROW]
[ROW][C]72[/C][C]11[/C][C]10.4748[/C][C]0.525241[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]12.9289[/C][C]1.07109[/C][/ROW]
[ROW][C]74[/C][C]14[/C][C]12.8687[/C][C]1.13126[/C][/ROW]
[ROW][C]75[/C][C]12[/C][C]11.4156[/C][C]0.58443[/C][/ROW]
[ROW][C]76[/C][C]9[/C][C]11.9312[/C][C]-2.93124[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.5389[/C][C]1.46108[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]11.3718[/C][C]-0.371779[/C][/ROW]
[ROW][C]79[/C][C]12[/C][C]9.89801[/C][C]2.10199[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]11.1134[/C][C]0.886606[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]11.7324[/C][C]0.267606[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]11.5921[/C][C]0.407922[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]10.9145[/C][C]1.08547[/C][/ROW]
[ROW][C]84[/C][C]11[/C][C]11.0132[/C][C]-0.0131955[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]11.4852[/C][C]-1.48518[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]10.5872[/C][C]-1.58719[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]11.5464[/C][C]0.453641[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.4331[/C][C]0.566947[/C][/ROW]
[ROW][C]89[/C][C]12[/C][C]11.0449[/C][C]0.955135[/C][/ROW]
[ROW][C]90[/C][C]9[/C][C]9.38996[/C][C]-0.389957[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]11.8629[/C][C]3.13709[/C][/ROW]
[ROW][C]92[/C][C]12[/C][C]11.8429[/C][C]0.157083[/C][/ROW]
[ROW][C]93[/C][C]12[/C][C]10.9135[/C][C]1.08651[/C][/ROW]
[ROW][C]94[/C][C]12[/C][C]9.94011[/C][C]2.05989[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]11.6091[/C][C]-1.6091[/C][/ROW]
[ROW][C]96[/C][C]13[/C][C]11.5153[/C][C]1.48471[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]11.499[/C][C]-2.49903[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]11.5491[/C][C]0.450916[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]10.5823[/C][C]-0.582325[/C][/ROW]
[ROW][C]100[/C][C]14[/C][C]11.5726[/C][C]2.42739[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]11.5553[/C][C]-0.555279[/C][/ROW]
[ROW][C]102[/C][C]15[/C][C]13.9024[/C][C]1.0976[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]10.7666[/C][C]0.233424[/C][/ROW]
[ROW][C]104[/C][C]11[/C][C]11.8137[/C][C]-0.813686[/C][/ROW]
[ROW][C]105[/C][C]12[/C][C]9.75456[/C][C]2.24544[/C][/ROW]
[ROW][C]106[/C][C]12[/C][C]12.0552[/C][C]-0.0551915[/C][/ROW]
[ROW][C]107[/C][C]12[/C][C]11.5931[/C][C]0.406862[/C][/ROW]
[ROW][C]108[/C][C]11[/C][C]11.4753[/C][C]-0.475285[/C][/ROW]
[ROW][C]109[/C][C]7[/C][C]9.2873[/C][C]-2.2873[/C][/ROW]
[ROW][C]110[/C][C]12[/C][C]11.6922[/C][C]0.307844[/C][/ROW]
[ROW][C]111[/C][C]14[/C][C]11.6465[/C][C]2.35351[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.516[/C][C]-1.51605[/C][/ROW]
[ROW][C]113[/C][C]11[/C][C]9.90399[/C][C]1.09601[/C][/ROW]
[ROW][C]114[/C][C]10[/C][C]9.23457[/C][C]0.765427[/C][/ROW]
[ROW][C]115[/C][C]13[/C][C]12.5892[/C][C]0.410846[/C][/ROW]
[ROW][C]116[/C][C]13[/C][C]10.5521[/C][C]2.44787[/C][/ROW]
[ROW][C]117[/C][C]8[/C][C]10.564[/C][C]-2.56402[/C][/ROW]
[ROW][C]118[/C][C]11[/C][C]9.93349[/C][C]1.06651[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]11.6815[/C][C]0.318502[/C][/ROW]
[ROW][C]120[/C][C]11[/C][C]9.91384[/C][C]1.08616[/C][/ROW]
[ROW][C]121[/C][C]13[/C][C]11.3648[/C][C]1.63519[/C][/ROW]
[ROW][C]122[/C][C]12[/C][C]10.1333[/C][C]1.86672[/C][/ROW]
[ROW][C]123[/C][C]14[/C][C]11.6593[/C][C]2.34065[/C][/ROW]
[ROW][C]124[/C][C]13[/C][C]10.8279[/C][C]2.17211[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]11.6616[/C][C]3.33839[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]10.9237[/C][C]-0.923686[/C][/ROW]
[ROW][C]127[/C][C]11[/C][C]12.116[/C][C]-1.11599[/C][/ROW]
[ROW][C]128[/C][C]9[/C][C]10.9967[/C][C]-1.99666[/C][/ROW]
[ROW][C]129[/C][C]11[/C][C]9.26088[/C][C]1.73912[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]11.5869[/C][C]-1.58692[/C][/ROW]
[ROW][C]131[/C][C]11[/C][C]8.28448[/C][C]2.71552[/C][/ROW]
[ROW][C]132[/C][C]8[/C][C]11.6075[/C][C]-3.60755[/C][/ROW]
[ROW][C]133[/C][C]11[/C][C]9.22226[/C][C]1.77774[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]10.5242[/C][C]1.47581[/C][/ROW]
[ROW][C]135[/C][C]12[/C][C]10.8716[/C][C]1.12837[/C][/ROW]
[ROW][C]136[/C][C]9[/C][C]9.41957[/C][C]-0.419569[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]10.8813[/C][C]0.11869[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]8.7519[/C][C]1.2481[/C][/ROW]
[ROW][C]139[/C][C]8[/C][C]9.22428[/C][C]-1.22428[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]8.89512[/C][C]0.104883[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]11.4366[/C][C]-3.43655[/C][/ROW]
[ROW][C]142[/C][C]9[/C][C]11.2402[/C][C]-2.24023[/C][/ROW]
[ROW][C]143[/C][C]15[/C][C]12.3034[/C][C]2.69662[/C][/ROW]
[ROW][C]144[/C][C]11[/C][C]11.2199[/C][C]-0.219931[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]8.09108[/C][C]-0.0910811[/C][/ROW]
[ROW][C]146[/C][C]13[/C][C]12.402[/C][C]0.598039[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]9.85789[/C][C]2.14211[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]11.5203[/C][C]0.479661[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]9.83526[/C][C]-0.835261[/C][/ROW]
[ROW][C]150[/C][C]7[/C][C]8.39305[/C][C]-1.39305[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]11.0559[/C][C]1.94411[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.7233[/C][C]-2.72328[/C][/ROW]
[ROW][C]153[/C][C]6[/C][C]11.7559[/C][C]-5.75587[/C][/ROW]
[ROW][C]154[/C][C]8[/C][C]10.6543[/C][C]-2.65429[/C][/ROW]
[ROW][C]155[/C][C]8[/C][C]8.10264[/C][C]-0.102637[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]11.8629[/C][C]3.13709[/C][/ROW]
[ROW][C]157[/C][C]6[/C][C]9.99371[/C][C]-3.99371[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]10.9967[/C][C]-1.99666[/C][/ROW]
[ROW][C]159[/C][C]11[/C][C]11.5907[/C][C]-0.590663[/C][/ROW]
[ROW][C]160[/C][C]8[/C][C]9.66429[/C][C]-1.66429[/C][/ROW]
[ROW][C]161[/C][C]8[/C][C]9.86307[/C][C]-1.86307[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.37561[/C][C]0.624385[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]8.94025[/C][C]-0.940249[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]11.7579[/C][C]2.24207[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.0034[/C][C]-1.00343[/C][/ROW]
[ROW][C]166[/C][C]8[/C][C]7.88172[/C][C]0.118285[/C][/ROW]
[ROW][C]167[/C][C]11[/C][C]10.2517[/C][C]0.748336[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]8.38806[/C][C]3.61194[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]9.93446[/C][C]2.06554[/C][/ROW]
[ROW][C]170[/C][C]12[/C][C]11.6856[/C][C]0.314425[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]8.80329[/C][C]-3.80329[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.3366[/C][C]0.663445[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]9.13495[/C][C]0.865047[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]7.09045[/C][C]-0.0904512[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]8.77492[/C][C]3.22508[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]10.9616[/C][C]0.0383961[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]8.9957[/C][C]-0.995699[/C][/ROW]
[ROW][C]178[/C][C]9[/C][C]9.01588[/C][C]-0.0158842[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]10.053[/C][C]-0.0529741[/C][/ROW]
[ROW][C]180[/C][C]9[/C][C]9.25596[/C][C]-0.25596[/C][/ROW]
[ROW][C]181[/C][C]12[/C][C]11.1989[/C][C]0.801088[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]8.3371[/C][C]-2.3371[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]13.0203[/C][C]1.97969[/C][/ROW]
[ROW][C]184[/C][C]12[/C][C]10.6729[/C][C]1.32713[/C][/ROW]
[ROW][C]185[/C][C]12[/C][C]6.92699[/C][C]5.07301[/C][/ROW]
[ROW][C]186[/C][C]12[/C][C]11.4867[/C][C]0.513317[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]11.8673[/C][C]-0.867332[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]8.99545[/C][C]-1.99545[/C][/ROW]
[ROW][C]189[/C][C]7[/C][C]8.34392[/C][C]-1.34392[/C][/ROW]
[ROW][C]190[/C][C]5[/C][C]8.54343[/C][C]-3.54343[/C][/ROW]
[ROW][C]191[/C][C]12[/C][C]10.3681[/C][C]1.63191[/C][/ROW]
[ROW][C]192[/C][C]12[/C][C]11.5192[/C][C]0.480797[/C][/ROW]
[ROW][C]193[/C][C]3[/C][C]9.0316[/C][C]-6.0316[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]11.2812[/C][C]-0.281187[/C][/ROW]
[ROW][C]195[/C][C]10[/C][C]9.56674[/C][C]0.433263[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]10.8276[/C][C]1.17235[/C][/ROW]
[ROW][C]197[/C][C]9[/C][C]11.2147[/C][C]-2.21473[/C][/ROW]
[ROW][C]198[/C][C]12[/C][C]11.5307[/C][C]0.469277[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]10.1897[/C][C]-1.18966[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]11.4731[/C][C]0.526894[/C][/ROW]
[ROW][C]201[/C][C]12[/C][C]11.2104[/C][C]0.789567[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]10.2148[/C][C]-0.214752[/C][/ROW]
[ROW][C]203[/C][C]9[/C][C]8.47141[/C][C]0.528592[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]8.83166[/C][C]3.16834[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]10.7621[/C][C]-2.76212[/C][/ROW]
[ROW][C]206[/C][C]11[/C][C]10.8143[/C][C]0.185743[/C][/ROW]
[ROW][C]207[/C][C]11[/C][C]11.4141[/C][C]-0.414097[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]11.177[/C][C]0.822953[/C][/ROW]
[ROW][C]209[/C][C]10[/C][C]8.41938[/C][C]1.58062[/C][/ROW]
[ROW][C]210[/C][C]10[/C][C]10.7842[/C][C]-0.784205[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]9.02893[/C][C]2.97107[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]9.36151[/C][C]2.63849[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.0921[/C][C]-0.0920929[/C][/ROW]
[ROW][C]214[/C][C]8[/C][C]10.8278[/C][C]-2.82782[/C][/ROW]
[ROW][C]215[/C][C]12[/C][C]11.3315[/C][C]0.66849[/C][/ROW]
[ROW][C]216[/C][C]10[/C][C]9.84032[/C][C]0.159676[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]11.9464[/C][C]-0.946437[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]10.1479[/C][C]-0.147858[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.65573[/C][C]-1.65573[/C][/ROW]
[ROW][C]220[/C][C]12[/C][C]10.9041[/C][C]1.0959[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]9.6631[/C][C]2.3369[/C][/ROW]
[ROW][C]222[/C][C]10[/C][C]10.1542[/C][C]-0.15422[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]10.73[/C][C]1.27002[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]9.04324[/C][C]-0.0432369[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.79408[/C][C]-0.794076[/C][/ROW]
[ROW][C]226[/C][C]6[/C][C]7.03283[/C][C]-1.03283[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]9.9443[/C][C]0.0557049[/C][/ROW]
[ROW][C]228[/C][C]9[/C][C]10.2691[/C][C]-1.26907[/C][/ROW]
[ROW][C]229[/C][C]9[/C][C]8.47548[/C][C]0.524516[/C][/ROW]
[ROW][C]230[/C][C]9[/C][C]9.14276[/C][C]-0.142765[/C][/ROW]
[ROW][C]231[/C][C]6[/C][C]9.47688[/C][C]-3.47688[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]8.10921[/C][C]1.89079[/C][/ROW]
[ROW][C]233[/C][C]6[/C][C]11.1973[/C][C]-5.19732[/C][/ROW]
[ROW][C]234[/C][C]14[/C][C]12.1916[/C][C]1.80837[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]9.52695[/C][C]0.473049[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]8.39781[/C][C]1.60219[/C][/ROW]
[ROW][C]237[/C][C]6[/C][C]4.41659[/C][C]1.58341[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]9.11852[/C][C]2.88148[/C][/ROW]
[ROW][C]239[/C][C]12[/C][C]11.3515[/C][C]0.648505[/C][/ROW]
[ROW][C]240[/C][C]7[/C][C]7.81344[/C][C]-0.813439[/C][/ROW]
[ROW][C]241[/C][C]8[/C][C]9.29755[/C][C]-1.29755[/C][/ROW]
[ROW][C]242[/C][C]11[/C][C]9.00183[/C][C]1.99817[/C][/ROW]
[ROW][C]243[/C][C]3[/C][C]7.77419[/C][C]-4.77419[/C][/ROW]
[ROW][C]244[/C][C]6[/C][C]9.56013[/C][C]-3.56013[/C][/ROW]
[ROW][C]245[/C][C]10[/C][C]10.5545[/C][C]-0.5545[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]9.21555[/C][C]-1.21555[/C][/ROW]
[ROW][C]247[/C][C]9[/C][C]10.2032[/C][C]-1.20321[/C][/ROW]
[ROW][C]248[/C][C]9[/C][C]7.57602[/C][C]1.42398[/C][/ROW]
[ROW][C]249[/C][C]8[/C][C]8.72528[/C][C]-0.725279[/C][/ROW]
[ROW][C]250[/C][C]9[/C][C]8.70091[/C][C]0.299085[/C][/ROW]
[ROW][C]251[/C][C]7[/C][C]8.55874[/C][C]-1.55874[/C][/ROW]
[ROW][C]252[/C][C]7[/C][C]7.97634[/C][C]-0.97634[/C][/ROW]
[ROW][C]253[/C][C]6[/C][C]9.03939[/C][C]-3.03939[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]11.2201[/C][C]-2.22013[/C][/ROW]
[ROW][C]255[/C][C]10[/C][C]8.92119[/C][C]1.07881[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]10.0858[/C][C]0.91422[/C][/ROW]
[ROW][C]257[/C][C]12[/C][C]11.5351[/C][C]0.464941[/C][/ROW]
[ROW][C]258[/C][C]8[/C][C]10.1035[/C][C]-2.10352[/C][/ROW]
[ROW][C]259[/C][C]11[/C][C]9.51526[/C][C]1.48474[/C][/ROW]
[ROW][C]260[/C][C]3[/C][C]4.61009[/C][C]-1.61009[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]10.6699[/C][C]0.330076[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]8.64533[/C][C]3.35467[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]8.48765[/C][C]-1.48765[/C][/ROW]
[ROW][C]264[/C][C]9[/C][C]10.2163[/C][C]-1.21632[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221929&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221929&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
11210.04631.95373
21111.6532-0.653217
31513.53531.46465
4611.2616-5.26159
51310.80222.19783
6109.930920.0690816
71212.9902-0.990212
81411.392.61003
91210.71211.28788
10911.3534-2.35341
111011.6109-1.61095
121211.5640.436028
131211.77170.228326
141111.701-0.700989
151512.54712.45291
161211.12790.872105
171011.1775-1.17747
181214.1691-2.16911
191112.8804-1.88041
201211.59020.409819
211111.6828-0.682754
221211.70170.298266
231313.3972-0.397163
241111.7919-0.791938
251212.2639-0.26393
261312.35070.649301
271011.8876-1.88761
281411.31542.68463
291211.86950.130467
301010.6015-0.601516
311211.22130.778693
3289.51546-1.51546
331010.4885-0.488534
341211.93650.0635324
351210.6321.36805
3678.44053-1.44053
3798.491280.508724
381210.61151.38845
391011.7734-1.77339
401011.7524-1.75244
411011.6867-1.68669
421210.68841.31162
431513.71231.28771
441010.5409-0.540912
451010.3655-0.365538
46129.080342.91966
471310.68682.31319
481111.2753-0.275264
491111.9577-0.957693
501210.6131.38703
511411.96762.03235
521010.5605-0.560485
53129.593432.40657
541311.72891.27114
5557.91912-2.91912
56610.6811-4.68107
571211.7030.297024
581211.82320.176836
591111.3596-0.359642
601011.7943-1.7943
6179.37996-2.37996
621211.83650.163524
631411.9742.02602
641110.65560.344372
651211.53710.462883
661312.32380.676217
671412.61131.38875
681112.5757-1.5757
69129.405432.59457
701211.6060.393996
7188.12769-0.12769
721110.47480.525241
731412.92891.07109
741412.86871.13126
751211.41560.58443
76911.9312-2.93124
771311.53891.46108
781111.3718-0.371779
79129.898012.10199
801211.11340.886606
811211.73240.267606
821211.59210.407922
831210.91451.08547
841111.0132-0.0131955
851011.4852-1.48518
86910.5872-1.58719
871211.54640.453641
881211.43310.566947
891211.04490.955135
9099.38996-0.389957
911511.86293.13709
921211.84290.157083
931210.91351.08651
94129.940112.05989
951011.6091-1.6091
961311.51531.48471
97911.499-2.49903
981211.54910.450916
991010.5823-0.582325
1001411.57262.42739
1011111.5553-0.555279
1021513.90241.0976
1031110.76660.233424
1041111.8137-0.813686
105129.754562.24544
1061212.0552-0.0551915
1071211.59310.406862
1081111.4753-0.475285
10979.2873-2.2873
1101211.69220.307844
1111411.64652.35351
1121112.516-1.51605
113119.903991.09601
114109.234570.765427
1151312.58920.410846
1161310.55212.44787
117810.564-2.56402
118119.933491.06651
1191211.68150.318502
120119.913841.08616
1211311.36481.63519
1221210.13331.86672
1231411.65932.34065
1241310.82792.17211
1251511.66163.33839
1261010.9237-0.923686
1271112.116-1.11599
128910.9967-1.99666
129119.260881.73912
1301011.5869-1.58692
131118.284482.71552
132811.6075-3.60755
133119.222261.77774
1341210.52421.47581
1351210.87161.12837
13699.41957-0.419569
1371110.88130.11869
138108.75191.2481
13989.22428-1.22428
14098.895120.104883
141811.4366-3.43655
142911.2402-2.24023
1431512.30342.69662
1441111.2199-0.219931
14588.09108-0.0910811
1461312.4020.598039
147129.857892.14211
1481211.52030.479661
14999.83526-0.835261
15078.39305-1.39305
1511311.05591.94411
152911.7233-2.72328
153611.7559-5.75587
154810.6543-2.65429
15588.10264-0.102637
1561511.86293.13709
15769.99371-3.99371
158910.9967-1.99666
1591111.5907-0.590663
16089.66429-1.66429
16189.86307-1.86307
162109.375610.624385
16388.94025-0.940249
1641411.75792.24207
1651011.0034-1.00343
16687.881720.118285
1671110.25170.748336
168128.388063.61194
169129.934462.06554
1701211.68560.314425
17158.80329-3.80329
1721211.33660.663445
173109.134950.865047
17477.09045-0.0904512
175128.774923.22508
1761110.96160.0383961
17788.9957-0.995699
17899.01588-0.0158842
1791010.053-0.0529741
18099.25596-0.25596
1811211.19890.801088
18268.3371-2.3371
1831513.02031.97969
1841210.67291.32713
185126.926995.07301
1861211.48670.513317
1871111.8673-0.867332
18878.99545-1.99545
18978.34392-1.34392
19058.54343-3.54343
1911210.36811.63191
1921211.51920.480797
19339.0316-6.0316
1941111.2812-0.281187
195109.566740.433263
1961210.82761.17235
197911.2147-2.21473
1981211.53070.469277
199910.1897-1.18966
2001211.47310.526894
2011211.21040.789567
2021010.2148-0.214752
20398.471410.528592
204128.831663.16834
205810.7621-2.76212
2061110.81430.185743
2071111.4141-0.414097
2081211.1770.822953
209108.419381.58062
2101010.7842-0.784205
211129.028932.97107
212129.361512.63849
2131111.0921-0.0920929
214810.8278-2.82782
2151211.33150.66849
216109.840320.159676
2171111.9464-0.946437
2181010.1479-0.147858
21989.65573-1.65573
2201210.90411.0959
221129.66312.3369
2221010.1542-0.15422
2231210.731.27002
22499.04324-0.0432369
22599.79408-0.794076
22667.03283-1.03283
227109.94430.0557049
228910.2691-1.26907
22998.475480.524516
23099.14276-0.142765
23169.47688-3.47688
232108.109211.89079
233611.1973-5.19732
2341412.19161.80837
235109.526950.473049
236108.397811.60219
23764.416591.58341
238129.118522.88148
2391211.35150.648505
24077.81344-0.813439
24189.29755-1.29755
242119.001831.99817
24337.77419-4.77419
24469.56013-3.56013
2451010.5545-0.5545
24689.21555-1.21555
247910.2032-1.20321
24897.576021.42398
24988.72528-0.725279
25098.700910.299085
25178.55874-1.55874
25277.97634-0.97634
25369.03939-3.03939
254911.2201-2.22013
255108.921191.07881
2561110.08580.91422
2571211.53510.464941
258810.1035-2.10352
259119.515261.48474
26034.61009-1.61009
2611110.66990.330076
262128.645333.35467
26378.48765-1.48765
264910.2163-1.21632






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.9952880.009423760.00471188
130.9886290.02274210.0113711
140.9874440.02511240.0125562
150.9791370.04172580.0208629
160.9699140.06017260.0300863
170.9503540.09929250.0496463
180.9470330.1059340.0529668
190.9340560.1318880.0659441
200.9026080.1947850.0973923
210.8745120.2509760.125488
220.8337870.3324250.166213
230.7938050.4123890.206195
240.7584270.4831450.241573
250.7104040.5791910.289596
260.7073450.5853090.292655
270.7236980.5526030.276302
280.7293440.5413110.270656
290.6724180.6551640.327582
300.6261130.7477740.373887
310.5753350.8493290.424665
320.5915770.8168460.408423
330.53140.9371990.4686
340.4747420.9494830.525258
350.4540070.9080140.545993
360.4412810.8825610.558719
370.3865540.7731070.613446
380.367180.734360.63282
390.3477790.6955580.652221
400.3221610.6443210.677839
410.2915940.5831870.708406
420.2592890.5185780.740711
430.3002760.6005520.699724
440.258930.5178610.74107
450.2193710.4387420.780629
460.2561130.5122270.743887
470.2739090.5478180.726091
480.2337860.4675720.766214
490.2221780.4443560.777822
500.204410.4088210.79559
510.2100210.4200410.789979
520.1776270.3552540.822373
530.1814030.3628070.818597
540.1596590.3193180.840341
550.2387880.4775750.761212
560.5193530.9612930.480647
570.4755450.9510890.524455
580.4316810.8633620.568319
590.3904070.7808130.609593
600.3900240.7800480.609976
610.4027330.8054650.597267
620.3618240.7236480.638176
630.3653310.7306620.634669
640.3258250.6516510.674175
650.2979060.5958120.702094
660.2622640.5245280.737736
670.2362430.4724870.763757
680.2202190.4404370.779781
690.2101570.4203140.789843
700.1841680.3683360.815832
710.166640.333280.83336
720.1432120.2864240.856788
730.1226920.2453850.877308
740.1047330.2094670.895267
750.09253770.1850750.907462
760.119420.238840.88058
770.1067530.2135060.893247
780.08941050.1788210.91059
790.09206340.1841270.907937
800.08445990.168920.91554
810.07094590.1418920.929054
820.05932410.1186480.940676
830.05039870.1007970.949601
840.0415890.08317810.958411
850.03957010.07914010.96043
860.04639170.09278340.953608
870.03764130.07528250.962359
880.03058370.06116730.969416
890.02566330.05132670.974337
900.02180770.04361550.978192
910.03358010.06716030.96642
920.02810960.05621920.97189
930.02500890.05001780.974991
940.02556050.0511210.97444
950.02661260.05322520.973387
960.02354140.04708280.976459
970.03035580.06071150.969644
980.02451160.04902320.975488
990.02109860.04219720.978901
1000.02370170.04740340.976298
1010.01984770.03969530.980152
1020.01669530.03339060.983305
1030.01317350.02634690.986827
1040.0118110.0236220.988189
1050.01262020.02524040.98738
1060.009919130.01983830.990081
1070.007793090.01558620.992207
1080.006504460.01300890.993496
1090.009465830.01893170.990534
1100.007367110.01473420.992633
1110.008197940.01639590.991802
1120.008699170.01739830.991301
1130.007100270.01420050.9929
1140.005670650.01134130.994329
1150.004388910.008777820.995611
1160.004986210.009972410.995014
1170.007449120.01489820.992551
1180.006154550.01230910.993845
1190.00476210.00952420.995238
1200.003956610.007913220.996043
1210.003725210.007450410.996275
1220.003700960.007401910.996299
1230.004291390.008582780.995709
1240.004770370.009540730.99523
1250.008568540.01713710.991431
1260.007237090.01447420.992763
1270.006294190.01258840.993706
1280.0066980.0133960.993302
1290.006612230.01322450.993388
1300.006704050.01340810.993296
1310.008853810.01770760.991146
1320.01774140.03548280.982259
1330.01773920.03547840.982261
1340.01699910.03399810.983001
1350.01505090.03010190.984949
1360.01236140.02472280.987639
1370.009989880.01997980.99001
1380.009595930.01919190.990404
1390.008605340.01721070.991395
1400.007371290.01474260.992629
1410.01303520.02607040.986965
1420.0147060.02941190.985294
1430.02128860.04257730.978711
1440.01717470.03434940.982825
1450.01375330.02750650.986247
1460.01164350.0232870.988356
1470.01487450.02974910.985125
1480.01321060.02642110.986789
1490.01118970.02237950.98881
1500.009866580.01973320.990133
1510.0122080.02441610.987792
1520.01443040.02886070.98557
1530.06496710.1299340.935033
1540.06511040.1302210.93489
1550.05598350.1119670.944017
1560.106070.212140.89393
1570.14770.29540.8523
1580.1387830.2775670.861217
1590.1246550.249310.875345
1600.1147220.2294450.885278
1610.1047860.2095710.895214
1620.09079040.1815810.90921
1630.08163350.1632670.918366
1640.08650150.1730030.913499
1650.07827570.1565510.921724
1660.06642880.1328580.933571
1670.05639060.1127810.943609
1680.09353710.1870740.906463
1690.09439220.1887840.905608
1700.08200530.1640110.917995
1710.143740.2874810.85626
1720.1245080.2490160.875492
1730.10940.21880.8906
1740.09378270.1875650.906217
1750.1294150.2588290.870585
1760.1119760.2239520.888024
1770.1004980.2009960.899502
1780.08593030.1718610.91407
1790.07232990.144660.92767
1800.060450.12090.93955
1810.05037050.1007410.949629
1820.05723130.1144630.942769
1830.05743620.1148720.942564
1840.05315620.1063120.946844
1850.2152850.430570.784715
1860.1977820.3955630.802218
1870.176640.353280.82336
1880.1757940.3515880.824206
1890.1624640.3249290.837536
1900.2408440.4816880.759156
1910.2458530.4917070.754147
1920.2165740.4331470.783426
1930.5807230.8385540.419277
1940.5489820.9020360.451018
1950.5118990.9762020.488101
1960.4801580.9603160.519842
1970.4921110.9842210.507889
1980.4560780.9121550.543922
1990.4286480.8572950.571352
2000.4298160.8596310.570184
2010.4041880.8083760.595812
2020.3827510.7655020.617249
2030.3613520.7227050.638648
2040.4144830.8289660.585517
2050.444380.8887590.55562
2060.4018350.803670.598165
2070.3617090.7234190.638291
2080.3235880.6471770.676412
2090.3062890.6125770.693711
2100.2692890.5385770.730711
2110.3332810.6665620.666719
2120.350850.7016990.64915
2130.3097140.6194270.690286
2140.3276250.655250.672375
2150.2930040.5860080.706996
2160.2578120.5156240.742188
2170.2231430.4462850.776857
2180.1885510.3771020.811449
2190.186130.372260.81387
2200.1641810.3283620.835819
2210.2034660.4069330.796534
2220.1698610.3397210.830139
2230.1624840.3249680.837516
2240.139150.27830.86085
2250.1134350.226870.886565
2260.0914340.1828680.908566
2270.07244140.1448830.927559
2280.05705170.1141030.942948
2290.04297090.08594180.957029
2300.03221770.06443550.967782
2310.04700990.09401970.95299
2320.0579240.1158480.942076
2330.225140.4502790.77486
2340.1982990.3965990.801701
2350.158050.31610.84195
2360.1566710.3133420.843329
2370.1885080.3770170.811492
2380.2037180.4074350.796282
2390.1947670.3895340.805233
2400.1549970.3099940.845003
2410.1222740.2445470.877726
2420.1544170.3088350.845583
2430.4055150.811030.594485
2440.5963070.8073860.403693
2450.5123120.9753760.487688
2460.4372120.8744230.562788
2470.3599990.7199970.640001
2480.2953320.5906640.704668
2490.2115140.4230280.788486
2500.1602210.3204410.839779
2510.2375610.4751220.762439
2520.4109210.8218430.589079

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.995288 & 0.00942376 & 0.00471188 \tabularnewline
13 & 0.988629 & 0.0227421 & 0.0113711 \tabularnewline
14 & 0.987444 & 0.0251124 & 0.0125562 \tabularnewline
15 & 0.979137 & 0.0417258 & 0.0208629 \tabularnewline
16 & 0.969914 & 0.0601726 & 0.0300863 \tabularnewline
17 & 0.950354 & 0.0992925 & 0.0496463 \tabularnewline
18 & 0.947033 & 0.105934 & 0.0529668 \tabularnewline
19 & 0.934056 & 0.131888 & 0.0659441 \tabularnewline
20 & 0.902608 & 0.194785 & 0.0973923 \tabularnewline
21 & 0.874512 & 0.250976 & 0.125488 \tabularnewline
22 & 0.833787 & 0.332425 & 0.166213 \tabularnewline
23 & 0.793805 & 0.412389 & 0.206195 \tabularnewline
24 & 0.758427 & 0.483145 & 0.241573 \tabularnewline
25 & 0.710404 & 0.579191 & 0.289596 \tabularnewline
26 & 0.707345 & 0.585309 & 0.292655 \tabularnewline
27 & 0.723698 & 0.552603 & 0.276302 \tabularnewline
28 & 0.729344 & 0.541311 & 0.270656 \tabularnewline
29 & 0.672418 & 0.655164 & 0.327582 \tabularnewline
30 & 0.626113 & 0.747774 & 0.373887 \tabularnewline
31 & 0.575335 & 0.849329 & 0.424665 \tabularnewline
32 & 0.591577 & 0.816846 & 0.408423 \tabularnewline
33 & 0.5314 & 0.937199 & 0.4686 \tabularnewline
34 & 0.474742 & 0.949483 & 0.525258 \tabularnewline
35 & 0.454007 & 0.908014 & 0.545993 \tabularnewline
36 & 0.441281 & 0.882561 & 0.558719 \tabularnewline
37 & 0.386554 & 0.773107 & 0.613446 \tabularnewline
38 & 0.36718 & 0.73436 & 0.63282 \tabularnewline
39 & 0.347779 & 0.695558 & 0.652221 \tabularnewline
40 & 0.322161 & 0.644321 & 0.677839 \tabularnewline
41 & 0.291594 & 0.583187 & 0.708406 \tabularnewline
42 & 0.259289 & 0.518578 & 0.740711 \tabularnewline
43 & 0.300276 & 0.600552 & 0.699724 \tabularnewline
44 & 0.25893 & 0.517861 & 0.74107 \tabularnewline
45 & 0.219371 & 0.438742 & 0.780629 \tabularnewline
46 & 0.256113 & 0.512227 & 0.743887 \tabularnewline
47 & 0.273909 & 0.547818 & 0.726091 \tabularnewline
48 & 0.233786 & 0.467572 & 0.766214 \tabularnewline
49 & 0.222178 & 0.444356 & 0.777822 \tabularnewline
50 & 0.20441 & 0.408821 & 0.79559 \tabularnewline
51 & 0.210021 & 0.420041 & 0.789979 \tabularnewline
52 & 0.177627 & 0.355254 & 0.822373 \tabularnewline
53 & 0.181403 & 0.362807 & 0.818597 \tabularnewline
54 & 0.159659 & 0.319318 & 0.840341 \tabularnewline
55 & 0.238788 & 0.477575 & 0.761212 \tabularnewline
56 & 0.519353 & 0.961293 & 0.480647 \tabularnewline
57 & 0.475545 & 0.951089 & 0.524455 \tabularnewline
58 & 0.431681 & 0.863362 & 0.568319 \tabularnewline
59 & 0.390407 & 0.780813 & 0.609593 \tabularnewline
60 & 0.390024 & 0.780048 & 0.609976 \tabularnewline
61 & 0.402733 & 0.805465 & 0.597267 \tabularnewline
62 & 0.361824 & 0.723648 & 0.638176 \tabularnewline
63 & 0.365331 & 0.730662 & 0.634669 \tabularnewline
64 & 0.325825 & 0.651651 & 0.674175 \tabularnewline
65 & 0.297906 & 0.595812 & 0.702094 \tabularnewline
66 & 0.262264 & 0.524528 & 0.737736 \tabularnewline
67 & 0.236243 & 0.472487 & 0.763757 \tabularnewline
68 & 0.220219 & 0.440437 & 0.779781 \tabularnewline
69 & 0.210157 & 0.420314 & 0.789843 \tabularnewline
70 & 0.184168 & 0.368336 & 0.815832 \tabularnewline
71 & 0.16664 & 0.33328 & 0.83336 \tabularnewline
72 & 0.143212 & 0.286424 & 0.856788 \tabularnewline
73 & 0.122692 & 0.245385 & 0.877308 \tabularnewline
74 & 0.104733 & 0.209467 & 0.895267 \tabularnewline
75 & 0.0925377 & 0.185075 & 0.907462 \tabularnewline
76 & 0.11942 & 0.23884 & 0.88058 \tabularnewline
77 & 0.106753 & 0.213506 & 0.893247 \tabularnewline
78 & 0.0894105 & 0.178821 & 0.91059 \tabularnewline
79 & 0.0920634 & 0.184127 & 0.907937 \tabularnewline
80 & 0.0844599 & 0.16892 & 0.91554 \tabularnewline
81 & 0.0709459 & 0.141892 & 0.929054 \tabularnewline
82 & 0.0593241 & 0.118648 & 0.940676 \tabularnewline
83 & 0.0503987 & 0.100797 & 0.949601 \tabularnewline
84 & 0.041589 & 0.0831781 & 0.958411 \tabularnewline
85 & 0.0395701 & 0.0791401 & 0.96043 \tabularnewline
86 & 0.0463917 & 0.0927834 & 0.953608 \tabularnewline
87 & 0.0376413 & 0.0752825 & 0.962359 \tabularnewline
88 & 0.0305837 & 0.0611673 & 0.969416 \tabularnewline
89 & 0.0256633 & 0.0513267 & 0.974337 \tabularnewline
90 & 0.0218077 & 0.0436155 & 0.978192 \tabularnewline
91 & 0.0335801 & 0.0671603 & 0.96642 \tabularnewline
92 & 0.0281096 & 0.0562192 & 0.97189 \tabularnewline
93 & 0.0250089 & 0.0500178 & 0.974991 \tabularnewline
94 & 0.0255605 & 0.051121 & 0.97444 \tabularnewline
95 & 0.0266126 & 0.0532252 & 0.973387 \tabularnewline
96 & 0.0235414 & 0.0470828 & 0.976459 \tabularnewline
97 & 0.0303558 & 0.0607115 & 0.969644 \tabularnewline
98 & 0.0245116 & 0.0490232 & 0.975488 \tabularnewline
99 & 0.0210986 & 0.0421972 & 0.978901 \tabularnewline
100 & 0.0237017 & 0.0474034 & 0.976298 \tabularnewline
101 & 0.0198477 & 0.0396953 & 0.980152 \tabularnewline
102 & 0.0166953 & 0.0333906 & 0.983305 \tabularnewline
103 & 0.0131735 & 0.0263469 & 0.986827 \tabularnewline
104 & 0.011811 & 0.023622 & 0.988189 \tabularnewline
105 & 0.0126202 & 0.0252404 & 0.98738 \tabularnewline
106 & 0.00991913 & 0.0198383 & 0.990081 \tabularnewline
107 & 0.00779309 & 0.0155862 & 0.992207 \tabularnewline
108 & 0.00650446 & 0.0130089 & 0.993496 \tabularnewline
109 & 0.00946583 & 0.0189317 & 0.990534 \tabularnewline
110 & 0.00736711 & 0.0147342 & 0.992633 \tabularnewline
111 & 0.00819794 & 0.0163959 & 0.991802 \tabularnewline
112 & 0.00869917 & 0.0173983 & 0.991301 \tabularnewline
113 & 0.00710027 & 0.0142005 & 0.9929 \tabularnewline
114 & 0.00567065 & 0.0113413 & 0.994329 \tabularnewline
115 & 0.00438891 & 0.00877782 & 0.995611 \tabularnewline
116 & 0.00498621 & 0.00997241 & 0.995014 \tabularnewline
117 & 0.00744912 & 0.0148982 & 0.992551 \tabularnewline
118 & 0.00615455 & 0.0123091 & 0.993845 \tabularnewline
119 & 0.0047621 & 0.0095242 & 0.995238 \tabularnewline
120 & 0.00395661 & 0.00791322 & 0.996043 \tabularnewline
121 & 0.00372521 & 0.00745041 & 0.996275 \tabularnewline
122 & 0.00370096 & 0.00740191 & 0.996299 \tabularnewline
123 & 0.00429139 & 0.00858278 & 0.995709 \tabularnewline
124 & 0.00477037 & 0.00954073 & 0.99523 \tabularnewline
125 & 0.00856854 & 0.0171371 & 0.991431 \tabularnewline
126 & 0.00723709 & 0.0144742 & 0.992763 \tabularnewline
127 & 0.00629419 & 0.0125884 & 0.993706 \tabularnewline
128 & 0.006698 & 0.013396 & 0.993302 \tabularnewline
129 & 0.00661223 & 0.0132245 & 0.993388 \tabularnewline
130 & 0.00670405 & 0.0134081 & 0.993296 \tabularnewline
131 & 0.00885381 & 0.0177076 & 0.991146 \tabularnewline
132 & 0.0177414 & 0.0354828 & 0.982259 \tabularnewline
133 & 0.0177392 & 0.0354784 & 0.982261 \tabularnewline
134 & 0.0169991 & 0.0339981 & 0.983001 \tabularnewline
135 & 0.0150509 & 0.0301019 & 0.984949 \tabularnewline
136 & 0.0123614 & 0.0247228 & 0.987639 \tabularnewline
137 & 0.00998988 & 0.0199798 & 0.99001 \tabularnewline
138 & 0.00959593 & 0.0191919 & 0.990404 \tabularnewline
139 & 0.00860534 & 0.0172107 & 0.991395 \tabularnewline
140 & 0.00737129 & 0.0147426 & 0.992629 \tabularnewline
141 & 0.0130352 & 0.0260704 & 0.986965 \tabularnewline
142 & 0.014706 & 0.0294119 & 0.985294 \tabularnewline
143 & 0.0212886 & 0.0425773 & 0.978711 \tabularnewline
144 & 0.0171747 & 0.0343494 & 0.982825 \tabularnewline
145 & 0.0137533 & 0.0275065 & 0.986247 \tabularnewline
146 & 0.0116435 & 0.023287 & 0.988356 \tabularnewline
147 & 0.0148745 & 0.0297491 & 0.985125 \tabularnewline
148 & 0.0132106 & 0.0264211 & 0.986789 \tabularnewline
149 & 0.0111897 & 0.0223795 & 0.98881 \tabularnewline
150 & 0.00986658 & 0.0197332 & 0.990133 \tabularnewline
151 & 0.012208 & 0.0244161 & 0.987792 \tabularnewline
152 & 0.0144304 & 0.0288607 & 0.98557 \tabularnewline
153 & 0.0649671 & 0.129934 & 0.935033 \tabularnewline
154 & 0.0651104 & 0.130221 & 0.93489 \tabularnewline
155 & 0.0559835 & 0.111967 & 0.944017 \tabularnewline
156 & 0.10607 & 0.21214 & 0.89393 \tabularnewline
157 & 0.1477 & 0.2954 & 0.8523 \tabularnewline
158 & 0.138783 & 0.277567 & 0.861217 \tabularnewline
159 & 0.124655 & 0.24931 & 0.875345 \tabularnewline
160 & 0.114722 & 0.229445 & 0.885278 \tabularnewline
161 & 0.104786 & 0.209571 & 0.895214 \tabularnewline
162 & 0.0907904 & 0.181581 & 0.90921 \tabularnewline
163 & 0.0816335 & 0.163267 & 0.918366 \tabularnewline
164 & 0.0865015 & 0.173003 & 0.913499 \tabularnewline
165 & 0.0782757 & 0.156551 & 0.921724 \tabularnewline
166 & 0.0664288 & 0.132858 & 0.933571 \tabularnewline
167 & 0.0563906 & 0.112781 & 0.943609 \tabularnewline
168 & 0.0935371 & 0.187074 & 0.906463 \tabularnewline
169 & 0.0943922 & 0.188784 & 0.905608 \tabularnewline
170 & 0.0820053 & 0.164011 & 0.917995 \tabularnewline
171 & 0.14374 & 0.287481 & 0.85626 \tabularnewline
172 & 0.124508 & 0.249016 & 0.875492 \tabularnewline
173 & 0.1094 & 0.2188 & 0.8906 \tabularnewline
174 & 0.0937827 & 0.187565 & 0.906217 \tabularnewline
175 & 0.129415 & 0.258829 & 0.870585 \tabularnewline
176 & 0.111976 & 0.223952 & 0.888024 \tabularnewline
177 & 0.100498 & 0.200996 & 0.899502 \tabularnewline
178 & 0.0859303 & 0.171861 & 0.91407 \tabularnewline
179 & 0.0723299 & 0.14466 & 0.92767 \tabularnewline
180 & 0.06045 & 0.1209 & 0.93955 \tabularnewline
181 & 0.0503705 & 0.100741 & 0.949629 \tabularnewline
182 & 0.0572313 & 0.114463 & 0.942769 \tabularnewline
183 & 0.0574362 & 0.114872 & 0.942564 \tabularnewline
184 & 0.0531562 & 0.106312 & 0.946844 \tabularnewline
185 & 0.215285 & 0.43057 & 0.784715 \tabularnewline
186 & 0.197782 & 0.395563 & 0.802218 \tabularnewline
187 & 0.17664 & 0.35328 & 0.82336 \tabularnewline
188 & 0.175794 & 0.351588 & 0.824206 \tabularnewline
189 & 0.162464 & 0.324929 & 0.837536 \tabularnewline
190 & 0.240844 & 0.481688 & 0.759156 \tabularnewline
191 & 0.245853 & 0.491707 & 0.754147 \tabularnewline
192 & 0.216574 & 0.433147 & 0.783426 \tabularnewline
193 & 0.580723 & 0.838554 & 0.419277 \tabularnewline
194 & 0.548982 & 0.902036 & 0.451018 \tabularnewline
195 & 0.511899 & 0.976202 & 0.488101 \tabularnewline
196 & 0.480158 & 0.960316 & 0.519842 \tabularnewline
197 & 0.492111 & 0.984221 & 0.507889 \tabularnewline
198 & 0.456078 & 0.912155 & 0.543922 \tabularnewline
199 & 0.428648 & 0.857295 & 0.571352 \tabularnewline
200 & 0.429816 & 0.859631 & 0.570184 \tabularnewline
201 & 0.404188 & 0.808376 & 0.595812 \tabularnewline
202 & 0.382751 & 0.765502 & 0.617249 \tabularnewline
203 & 0.361352 & 0.722705 & 0.638648 \tabularnewline
204 & 0.414483 & 0.828966 & 0.585517 \tabularnewline
205 & 0.44438 & 0.888759 & 0.55562 \tabularnewline
206 & 0.401835 & 0.80367 & 0.598165 \tabularnewline
207 & 0.361709 & 0.723419 & 0.638291 \tabularnewline
208 & 0.323588 & 0.647177 & 0.676412 \tabularnewline
209 & 0.306289 & 0.612577 & 0.693711 \tabularnewline
210 & 0.269289 & 0.538577 & 0.730711 \tabularnewline
211 & 0.333281 & 0.666562 & 0.666719 \tabularnewline
212 & 0.35085 & 0.701699 & 0.64915 \tabularnewline
213 & 0.309714 & 0.619427 & 0.690286 \tabularnewline
214 & 0.327625 & 0.65525 & 0.672375 \tabularnewline
215 & 0.293004 & 0.586008 & 0.706996 \tabularnewline
216 & 0.257812 & 0.515624 & 0.742188 \tabularnewline
217 & 0.223143 & 0.446285 & 0.776857 \tabularnewline
218 & 0.188551 & 0.377102 & 0.811449 \tabularnewline
219 & 0.18613 & 0.37226 & 0.81387 \tabularnewline
220 & 0.164181 & 0.328362 & 0.835819 \tabularnewline
221 & 0.203466 & 0.406933 & 0.796534 \tabularnewline
222 & 0.169861 & 0.339721 & 0.830139 \tabularnewline
223 & 0.162484 & 0.324968 & 0.837516 \tabularnewline
224 & 0.13915 & 0.2783 & 0.86085 \tabularnewline
225 & 0.113435 & 0.22687 & 0.886565 \tabularnewline
226 & 0.091434 & 0.182868 & 0.908566 \tabularnewline
227 & 0.0724414 & 0.144883 & 0.927559 \tabularnewline
228 & 0.0570517 & 0.114103 & 0.942948 \tabularnewline
229 & 0.0429709 & 0.0859418 & 0.957029 \tabularnewline
230 & 0.0322177 & 0.0644355 & 0.967782 \tabularnewline
231 & 0.0470099 & 0.0940197 & 0.95299 \tabularnewline
232 & 0.057924 & 0.115848 & 0.942076 \tabularnewline
233 & 0.22514 & 0.450279 & 0.77486 \tabularnewline
234 & 0.198299 & 0.396599 & 0.801701 \tabularnewline
235 & 0.15805 & 0.3161 & 0.84195 \tabularnewline
236 & 0.156671 & 0.313342 & 0.843329 \tabularnewline
237 & 0.188508 & 0.377017 & 0.811492 \tabularnewline
238 & 0.203718 & 0.407435 & 0.796282 \tabularnewline
239 & 0.194767 & 0.389534 & 0.805233 \tabularnewline
240 & 0.154997 & 0.309994 & 0.845003 \tabularnewline
241 & 0.122274 & 0.244547 & 0.877726 \tabularnewline
242 & 0.154417 & 0.308835 & 0.845583 \tabularnewline
243 & 0.405515 & 0.81103 & 0.594485 \tabularnewline
244 & 0.596307 & 0.807386 & 0.403693 \tabularnewline
245 & 0.512312 & 0.975376 & 0.487688 \tabularnewline
246 & 0.437212 & 0.874423 & 0.562788 \tabularnewline
247 & 0.359999 & 0.719997 & 0.640001 \tabularnewline
248 & 0.295332 & 0.590664 & 0.704668 \tabularnewline
249 & 0.211514 & 0.423028 & 0.788486 \tabularnewline
250 & 0.160221 & 0.320441 & 0.839779 \tabularnewline
251 & 0.237561 & 0.475122 & 0.762439 \tabularnewline
252 & 0.410921 & 0.821843 & 0.589079 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221929&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]0.995288[/C][C]0.00942376[/C][C]0.00471188[/C][/ROW]
[ROW][C]13[/C][C]0.988629[/C][C]0.0227421[/C][C]0.0113711[/C][/ROW]
[ROW][C]14[/C][C]0.987444[/C][C]0.0251124[/C][C]0.0125562[/C][/ROW]
[ROW][C]15[/C][C]0.979137[/C][C]0.0417258[/C][C]0.0208629[/C][/ROW]
[ROW][C]16[/C][C]0.969914[/C][C]0.0601726[/C][C]0.0300863[/C][/ROW]
[ROW][C]17[/C][C]0.950354[/C][C]0.0992925[/C][C]0.0496463[/C][/ROW]
[ROW][C]18[/C][C]0.947033[/C][C]0.105934[/C][C]0.0529668[/C][/ROW]
[ROW][C]19[/C][C]0.934056[/C][C]0.131888[/C][C]0.0659441[/C][/ROW]
[ROW][C]20[/C][C]0.902608[/C][C]0.194785[/C][C]0.0973923[/C][/ROW]
[ROW][C]21[/C][C]0.874512[/C][C]0.250976[/C][C]0.125488[/C][/ROW]
[ROW][C]22[/C][C]0.833787[/C][C]0.332425[/C][C]0.166213[/C][/ROW]
[ROW][C]23[/C][C]0.793805[/C][C]0.412389[/C][C]0.206195[/C][/ROW]
[ROW][C]24[/C][C]0.758427[/C][C]0.483145[/C][C]0.241573[/C][/ROW]
[ROW][C]25[/C][C]0.710404[/C][C]0.579191[/C][C]0.289596[/C][/ROW]
[ROW][C]26[/C][C]0.707345[/C][C]0.585309[/C][C]0.292655[/C][/ROW]
[ROW][C]27[/C][C]0.723698[/C][C]0.552603[/C][C]0.276302[/C][/ROW]
[ROW][C]28[/C][C]0.729344[/C][C]0.541311[/C][C]0.270656[/C][/ROW]
[ROW][C]29[/C][C]0.672418[/C][C]0.655164[/C][C]0.327582[/C][/ROW]
[ROW][C]30[/C][C]0.626113[/C][C]0.747774[/C][C]0.373887[/C][/ROW]
[ROW][C]31[/C][C]0.575335[/C][C]0.849329[/C][C]0.424665[/C][/ROW]
[ROW][C]32[/C][C]0.591577[/C][C]0.816846[/C][C]0.408423[/C][/ROW]
[ROW][C]33[/C][C]0.5314[/C][C]0.937199[/C][C]0.4686[/C][/ROW]
[ROW][C]34[/C][C]0.474742[/C][C]0.949483[/C][C]0.525258[/C][/ROW]
[ROW][C]35[/C][C]0.454007[/C][C]0.908014[/C][C]0.545993[/C][/ROW]
[ROW][C]36[/C][C]0.441281[/C][C]0.882561[/C][C]0.558719[/C][/ROW]
[ROW][C]37[/C][C]0.386554[/C][C]0.773107[/C][C]0.613446[/C][/ROW]
[ROW][C]38[/C][C]0.36718[/C][C]0.73436[/C][C]0.63282[/C][/ROW]
[ROW][C]39[/C][C]0.347779[/C][C]0.695558[/C][C]0.652221[/C][/ROW]
[ROW][C]40[/C][C]0.322161[/C][C]0.644321[/C][C]0.677839[/C][/ROW]
[ROW][C]41[/C][C]0.291594[/C][C]0.583187[/C][C]0.708406[/C][/ROW]
[ROW][C]42[/C][C]0.259289[/C][C]0.518578[/C][C]0.740711[/C][/ROW]
[ROW][C]43[/C][C]0.300276[/C][C]0.600552[/C][C]0.699724[/C][/ROW]
[ROW][C]44[/C][C]0.25893[/C][C]0.517861[/C][C]0.74107[/C][/ROW]
[ROW][C]45[/C][C]0.219371[/C][C]0.438742[/C][C]0.780629[/C][/ROW]
[ROW][C]46[/C][C]0.256113[/C][C]0.512227[/C][C]0.743887[/C][/ROW]
[ROW][C]47[/C][C]0.273909[/C][C]0.547818[/C][C]0.726091[/C][/ROW]
[ROW][C]48[/C][C]0.233786[/C][C]0.467572[/C][C]0.766214[/C][/ROW]
[ROW][C]49[/C][C]0.222178[/C][C]0.444356[/C][C]0.777822[/C][/ROW]
[ROW][C]50[/C][C]0.20441[/C][C]0.408821[/C][C]0.79559[/C][/ROW]
[ROW][C]51[/C][C]0.210021[/C][C]0.420041[/C][C]0.789979[/C][/ROW]
[ROW][C]52[/C][C]0.177627[/C][C]0.355254[/C][C]0.822373[/C][/ROW]
[ROW][C]53[/C][C]0.181403[/C][C]0.362807[/C][C]0.818597[/C][/ROW]
[ROW][C]54[/C][C]0.159659[/C][C]0.319318[/C][C]0.840341[/C][/ROW]
[ROW][C]55[/C][C]0.238788[/C][C]0.477575[/C][C]0.761212[/C][/ROW]
[ROW][C]56[/C][C]0.519353[/C][C]0.961293[/C][C]0.480647[/C][/ROW]
[ROW][C]57[/C][C]0.475545[/C][C]0.951089[/C][C]0.524455[/C][/ROW]
[ROW][C]58[/C][C]0.431681[/C][C]0.863362[/C][C]0.568319[/C][/ROW]
[ROW][C]59[/C][C]0.390407[/C][C]0.780813[/C][C]0.609593[/C][/ROW]
[ROW][C]60[/C][C]0.390024[/C][C]0.780048[/C][C]0.609976[/C][/ROW]
[ROW][C]61[/C][C]0.402733[/C][C]0.805465[/C][C]0.597267[/C][/ROW]
[ROW][C]62[/C][C]0.361824[/C][C]0.723648[/C][C]0.638176[/C][/ROW]
[ROW][C]63[/C][C]0.365331[/C][C]0.730662[/C][C]0.634669[/C][/ROW]
[ROW][C]64[/C][C]0.325825[/C][C]0.651651[/C][C]0.674175[/C][/ROW]
[ROW][C]65[/C][C]0.297906[/C][C]0.595812[/C][C]0.702094[/C][/ROW]
[ROW][C]66[/C][C]0.262264[/C][C]0.524528[/C][C]0.737736[/C][/ROW]
[ROW][C]67[/C][C]0.236243[/C][C]0.472487[/C][C]0.763757[/C][/ROW]
[ROW][C]68[/C][C]0.220219[/C][C]0.440437[/C][C]0.779781[/C][/ROW]
[ROW][C]69[/C][C]0.210157[/C][C]0.420314[/C][C]0.789843[/C][/ROW]
[ROW][C]70[/C][C]0.184168[/C][C]0.368336[/C][C]0.815832[/C][/ROW]
[ROW][C]71[/C][C]0.16664[/C][C]0.33328[/C][C]0.83336[/C][/ROW]
[ROW][C]72[/C][C]0.143212[/C][C]0.286424[/C][C]0.856788[/C][/ROW]
[ROW][C]73[/C][C]0.122692[/C][C]0.245385[/C][C]0.877308[/C][/ROW]
[ROW][C]74[/C][C]0.104733[/C][C]0.209467[/C][C]0.895267[/C][/ROW]
[ROW][C]75[/C][C]0.0925377[/C][C]0.185075[/C][C]0.907462[/C][/ROW]
[ROW][C]76[/C][C]0.11942[/C][C]0.23884[/C][C]0.88058[/C][/ROW]
[ROW][C]77[/C][C]0.106753[/C][C]0.213506[/C][C]0.893247[/C][/ROW]
[ROW][C]78[/C][C]0.0894105[/C][C]0.178821[/C][C]0.91059[/C][/ROW]
[ROW][C]79[/C][C]0.0920634[/C][C]0.184127[/C][C]0.907937[/C][/ROW]
[ROW][C]80[/C][C]0.0844599[/C][C]0.16892[/C][C]0.91554[/C][/ROW]
[ROW][C]81[/C][C]0.0709459[/C][C]0.141892[/C][C]0.929054[/C][/ROW]
[ROW][C]82[/C][C]0.0593241[/C][C]0.118648[/C][C]0.940676[/C][/ROW]
[ROW][C]83[/C][C]0.0503987[/C][C]0.100797[/C][C]0.949601[/C][/ROW]
[ROW][C]84[/C][C]0.041589[/C][C]0.0831781[/C][C]0.958411[/C][/ROW]
[ROW][C]85[/C][C]0.0395701[/C][C]0.0791401[/C][C]0.96043[/C][/ROW]
[ROW][C]86[/C][C]0.0463917[/C][C]0.0927834[/C][C]0.953608[/C][/ROW]
[ROW][C]87[/C][C]0.0376413[/C][C]0.0752825[/C][C]0.962359[/C][/ROW]
[ROW][C]88[/C][C]0.0305837[/C][C]0.0611673[/C][C]0.969416[/C][/ROW]
[ROW][C]89[/C][C]0.0256633[/C][C]0.0513267[/C][C]0.974337[/C][/ROW]
[ROW][C]90[/C][C]0.0218077[/C][C]0.0436155[/C][C]0.978192[/C][/ROW]
[ROW][C]91[/C][C]0.0335801[/C][C]0.0671603[/C][C]0.96642[/C][/ROW]
[ROW][C]92[/C][C]0.0281096[/C][C]0.0562192[/C][C]0.97189[/C][/ROW]
[ROW][C]93[/C][C]0.0250089[/C][C]0.0500178[/C][C]0.974991[/C][/ROW]
[ROW][C]94[/C][C]0.0255605[/C][C]0.051121[/C][C]0.97444[/C][/ROW]
[ROW][C]95[/C][C]0.0266126[/C][C]0.0532252[/C][C]0.973387[/C][/ROW]
[ROW][C]96[/C][C]0.0235414[/C][C]0.0470828[/C][C]0.976459[/C][/ROW]
[ROW][C]97[/C][C]0.0303558[/C][C]0.0607115[/C][C]0.969644[/C][/ROW]
[ROW][C]98[/C][C]0.0245116[/C][C]0.0490232[/C][C]0.975488[/C][/ROW]
[ROW][C]99[/C][C]0.0210986[/C][C]0.0421972[/C][C]0.978901[/C][/ROW]
[ROW][C]100[/C][C]0.0237017[/C][C]0.0474034[/C][C]0.976298[/C][/ROW]
[ROW][C]101[/C][C]0.0198477[/C][C]0.0396953[/C][C]0.980152[/C][/ROW]
[ROW][C]102[/C][C]0.0166953[/C][C]0.0333906[/C][C]0.983305[/C][/ROW]
[ROW][C]103[/C][C]0.0131735[/C][C]0.0263469[/C][C]0.986827[/C][/ROW]
[ROW][C]104[/C][C]0.011811[/C][C]0.023622[/C][C]0.988189[/C][/ROW]
[ROW][C]105[/C][C]0.0126202[/C][C]0.0252404[/C][C]0.98738[/C][/ROW]
[ROW][C]106[/C][C]0.00991913[/C][C]0.0198383[/C][C]0.990081[/C][/ROW]
[ROW][C]107[/C][C]0.00779309[/C][C]0.0155862[/C][C]0.992207[/C][/ROW]
[ROW][C]108[/C][C]0.00650446[/C][C]0.0130089[/C][C]0.993496[/C][/ROW]
[ROW][C]109[/C][C]0.00946583[/C][C]0.0189317[/C][C]0.990534[/C][/ROW]
[ROW][C]110[/C][C]0.00736711[/C][C]0.0147342[/C][C]0.992633[/C][/ROW]
[ROW][C]111[/C][C]0.00819794[/C][C]0.0163959[/C][C]0.991802[/C][/ROW]
[ROW][C]112[/C][C]0.00869917[/C][C]0.0173983[/C][C]0.991301[/C][/ROW]
[ROW][C]113[/C][C]0.00710027[/C][C]0.0142005[/C][C]0.9929[/C][/ROW]
[ROW][C]114[/C][C]0.00567065[/C][C]0.0113413[/C][C]0.994329[/C][/ROW]
[ROW][C]115[/C][C]0.00438891[/C][C]0.00877782[/C][C]0.995611[/C][/ROW]
[ROW][C]116[/C][C]0.00498621[/C][C]0.00997241[/C][C]0.995014[/C][/ROW]
[ROW][C]117[/C][C]0.00744912[/C][C]0.0148982[/C][C]0.992551[/C][/ROW]
[ROW][C]118[/C][C]0.00615455[/C][C]0.0123091[/C][C]0.993845[/C][/ROW]
[ROW][C]119[/C][C]0.0047621[/C][C]0.0095242[/C][C]0.995238[/C][/ROW]
[ROW][C]120[/C][C]0.00395661[/C][C]0.00791322[/C][C]0.996043[/C][/ROW]
[ROW][C]121[/C][C]0.00372521[/C][C]0.00745041[/C][C]0.996275[/C][/ROW]
[ROW][C]122[/C][C]0.00370096[/C][C]0.00740191[/C][C]0.996299[/C][/ROW]
[ROW][C]123[/C][C]0.00429139[/C][C]0.00858278[/C][C]0.995709[/C][/ROW]
[ROW][C]124[/C][C]0.00477037[/C][C]0.00954073[/C][C]0.99523[/C][/ROW]
[ROW][C]125[/C][C]0.00856854[/C][C]0.0171371[/C][C]0.991431[/C][/ROW]
[ROW][C]126[/C][C]0.00723709[/C][C]0.0144742[/C][C]0.992763[/C][/ROW]
[ROW][C]127[/C][C]0.00629419[/C][C]0.0125884[/C][C]0.993706[/C][/ROW]
[ROW][C]128[/C][C]0.006698[/C][C]0.013396[/C][C]0.993302[/C][/ROW]
[ROW][C]129[/C][C]0.00661223[/C][C]0.0132245[/C][C]0.993388[/C][/ROW]
[ROW][C]130[/C][C]0.00670405[/C][C]0.0134081[/C][C]0.993296[/C][/ROW]
[ROW][C]131[/C][C]0.00885381[/C][C]0.0177076[/C][C]0.991146[/C][/ROW]
[ROW][C]132[/C][C]0.0177414[/C][C]0.0354828[/C][C]0.982259[/C][/ROW]
[ROW][C]133[/C][C]0.0177392[/C][C]0.0354784[/C][C]0.982261[/C][/ROW]
[ROW][C]134[/C][C]0.0169991[/C][C]0.0339981[/C][C]0.983001[/C][/ROW]
[ROW][C]135[/C][C]0.0150509[/C][C]0.0301019[/C][C]0.984949[/C][/ROW]
[ROW][C]136[/C][C]0.0123614[/C][C]0.0247228[/C][C]0.987639[/C][/ROW]
[ROW][C]137[/C][C]0.00998988[/C][C]0.0199798[/C][C]0.99001[/C][/ROW]
[ROW][C]138[/C][C]0.00959593[/C][C]0.0191919[/C][C]0.990404[/C][/ROW]
[ROW][C]139[/C][C]0.00860534[/C][C]0.0172107[/C][C]0.991395[/C][/ROW]
[ROW][C]140[/C][C]0.00737129[/C][C]0.0147426[/C][C]0.992629[/C][/ROW]
[ROW][C]141[/C][C]0.0130352[/C][C]0.0260704[/C][C]0.986965[/C][/ROW]
[ROW][C]142[/C][C]0.014706[/C][C]0.0294119[/C][C]0.985294[/C][/ROW]
[ROW][C]143[/C][C]0.0212886[/C][C]0.0425773[/C][C]0.978711[/C][/ROW]
[ROW][C]144[/C][C]0.0171747[/C][C]0.0343494[/C][C]0.982825[/C][/ROW]
[ROW][C]145[/C][C]0.0137533[/C][C]0.0275065[/C][C]0.986247[/C][/ROW]
[ROW][C]146[/C][C]0.0116435[/C][C]0.023287[/C][C]0.988356[/C][/ROW]
[ROW][C]147[/C][C]0.0148745[/C][C]0.0297491[/C][C]0.985125[/C][/ROW]
[ROW][C]148[/C][C]0.0132106[/C][C]0.0264211[/C][C]0.986789[/C][/ROW]
[ROW][C]149[/C][C]0.0111897[/C][C]0.0223795[/C][C]0.98881[/C][/ROW]
[ROW][C]150[/C][C]0.00986658[/C][C]0.0197332[/C][C]0.990133[/C][/ROW]
[ROW][C]151[/C][C]0.012208[/C][C]0.0244161[/C][C]0.987792[/C][/ROW]
[ROW][C]152[/C][C]0.0144304[/C][C]0.0288607[/C][C]0.98557[/C][/ROW]
[ROW][C]153[/C][C]0.0649671[/C][C]0.129934[/C][C]0.935033[/C][/ROW]
[ROW][C]154[/C][C]0.0651104[/C][C]0.130221[/C][C]0.93489[/C][/ROW]
[ROW][C]155[/C][C]0.0559835[/C][C]0.111967[/C][C]0.944017[/C][/ROW]
[ROW][C]156[/C][C]0.10607[/C][C]0.21214[/C][C]0.89393[/C][/ROW]
[ROW][C]157[/C][C]0.1477[/C][C]0.2954[/C][C]0.8523[/C][/ROW]
[ROW][C]158[/C][C]0.138783[/C][C]0.277567[/C][C]0.861217[/C][/ROW]
[ROW][C]159[/C][C]0.124655[/C][C]0.24931[/C][C]0.875345[/C][/ROW]
[ROW][C]160[/C][C]0.114722[/C][C]0.229445[/C][C]0.885278[/C][/ROW]
[ROW][C]161[/C][C]0.104786[/C][C]0.209571[/C][C]0.895214[/C][/ROW]
[ROW][C]162[/C][C]0.0907904[/C][C]0.181581[/C][C]0.90921[/C][/ROW]
[ROW][C]163[/C][C]0.0816335[/C][C]0.163267[/C][C]0.918366[/C][/ROW]
[ROW][C]164[/C][C]0.0865015[/C][C]0.173003[/C][C]0.913499[/C][/ROW]
[ROW][C]165[/C][C]0.0782757[/C][C]0.156551[/C][C]0.921724[/C][/ROW]
[ROW][C]166[/C][C]0.0664288[/C][C]0.132858[/C][C]0.933571[/C][/ROW]
[ROW][C]167[/C][C]0.0563906[/C][C]0.112781[/C][C]0.943609[/C][/ROW]
[ROW][C]168[/C][C]0.0935371[/C][C]0.187074[/C][C]0.906463[/C][/ROW]
[ROW][C]169[/C][C]0.0943922[/C][C]0.188784[/C][C]0.905608[/C][/ROW]
[ROW][C]170[/C][C]0.0820053[/C][C]0.164011[/C][C]0.917995[/C][/ROW]
[ROW][C]171[/C][C]0.14374[/C][C]0.287481[/C][C]0.85626[/C][/ROW]
[ROW][C]172[/C][C]0.124508[/C][C]0.249016[/C][C]0.875492[/C][/ROW]
[ROW][C]173[/C][C]0.1094[/C][C]0.2188[/C][C]0.8906[/C][/ROW]
[ROW][C]174[/C][C]0.0937827[/C][C]0.187565[/C][C]0.906217[/C][/ROW]
[ROW][C]175[/C][C]0.129415[/C][C]0.258829[/C][C]0.870585[/C][/ROW]
[ROW][C]176[/C][C]0.111976[/C][C]0.223952[/C][C]0.888024[/C][/ROW]
[ROW][C]177[/C][C]0.100498[/C][C]0.200996[/C][C]0.899502[/C][/ROW]
[ROW][C]178[/C][C]0.0859303[/C][C]0.171861[/C][C]0.91407[/C][/ROW]
[ROW][C]179[/C][C]0.0723299[/C][C]0.14466[/C][C]0.92767[/C][/ROW]
[ROW][C]180[/C][C]0.06045[/C][C]0.1209[/C][C]0.93955[/C][/ROW]
[ROW][C]181[/C][C]0.0503705[/C][C]0.100741[/C][C]0.949629[/C][/ROW]
[ROW][C]182[/C][C]0.0572313[/C][C]0.114463[/C][C]0.942769[/C][/ROW]
[ROW][C]183[/C][C]0.0574362[/C][C]0.114872[/C][C]0.942564[/C][/ROW]
[ROW][C]184[/C][C]0.0531562[/C][C]0.106312[/C][C]0.946844[/C][/ROW]
[ROW][C]185[/C][C]0.215285[/C][C]0.43057[/C][C]0.784715[/C][/ROW]
[ROW][C]186[/C][C]0.197782[/C][C]0.395563[/C][C]0.802218[/C][/ROW]
[ROW][C]187[/C][C]0.17664[/C][C]0.35328[/C][C]0.82336[/C][/ROW]
[ROW][C]188[/C][C]0.175794[/C][C]0.351588[/C][C]0.824206[/C][/ROW]
[ROW][C]189[/C][C]0.162464[/C][C]0.324929[/C][C]0.837536[/C][/ROW]
[ROW][C]190[/C][C]0.240844[/C][C]0.481688[/C][C]0.759156[/C][/ROW]
[ROW][C]191[/C][C]0.245853[/C][C]0.491707[/C][C]0.754147[/C][/ROW]
[ROW][C]192[/C][C]0.216574[/C][C]0.433147[/C][C]0.783426[/C][/ROW]
[ROW][C]193[/C][C]0.580723[/C][C]0.838554[/C][C]0.419277[/C][/ROW]
[ROW][C]194[/C][C]0.548982[/C][C]0.902036[/C][C]0.451018[/C][/ROW]
[ROW][C]195[/C][C]0.511899[/C][C]0.976202[/C][C]0.488101[/C][/ROW]
[ROW][C]196[/C][C]0.480158[/C][C]0.960316[/C][C]0.519842[/C][/ROW]
[ROW][C]197[/C][C]0.492111[/C][C]0.984221[/C][C]0.507889[/C][/ROW]
[ROW][C]198[/C][C]0.456078[/C][C]0.912155[/C][C]0.543922[/C][/ROW]
[ROW][C]199[/C][C]0.428648[/C][C]0.857295[/C][C]0.571352[/C][/ROW]
[ROW][C]200[/C][C]0.429816[/C][C]0.859631[/C][C]0.570184[/C][/ROW]
[ROW][C]201[/C][C]0.404188[/C][C]0.808376[/C][C]0.595812[/C][/ROW]
[ROW][C]202[/C][C]0.382751[/C][C]0.765502[/C][C]0.617249[/C][/ROW]
[ROW][C]203[/C][C]0.361352[/C][C]0.722705[/C][C]0.638648[/C][/ROW]
[ROW][C]204[/C][C]0.414483[/C][C]0.828966[/C][C]0.585517[/C][/ROW]
[ROW][C]205[/C][C]0.44438[/C][C]0.888759[/C][C]0.55562[/C][/ROW]
[ROW][C]206[/C][C]0.401835[/C][C]0.80367[/C][C]0.598165[/C][/ROW]
[ROW][C]207[/C][C]0.361709[/C][C]0.723419[/C][C]0.638291[/C][/ROW]
[ROW][C]208[/C][C]0.323588[/C][C]0.647177[/C][C]0.676412[/C][/ROW]
[ROW][C]209[/C][C]0.306289[/C][C]0.612577[/C][C]0.693711[/C][/ROW]
[ROW][C]210[/C][C]0.269289[/C][C]0.538577[/C][C]0.730711[/C][/ROW]
[ROW][C]211[/C][C]0.333281[/C][C]0.666562[/C][C]0.666719[/C][/ROW]
[ROW][C]212[/C][C]0.35085[/C][C]0.701699[/C][C]0.64915[/C][/ROW]
[ROW][C]213[/C][C]0.309714[/C][C]0.619427[/C][C]0.690286[/C][/ROW]
[ROW][C]214[/C][C]0.327625[/C][C]0.65525[/C][C]0.672375[/C][/ROW]
[ROW][C]215[/C][C]0.293004[/C][C]0.586008[/C][C]0.706996[/C][/ROW]
[ROW][C]216[/C][C]0.257812[/C][C]0.515624[/C][C]0.742188[/C][/ROW]
[ROW][C]217[/C][C]0.223143[/C][C]0.446285[/C][C]0.776857[/C][/ROW]
[ROW][C]218[/C][C]0.188551[/C][C]0.377102[/C][C]0.811449[/C][/ROW]
[ROW][C]219[/C][C]0.18613[/C][C]0.37226[/C][C]0.81387[/C][/ROW]
[ROW][C]220[/C][C]0.164181[/C][C]0.328362[/C][C]0.835819[/C][/ROW]
[ROW][C]221[/C][C]0.203466[/C][C]0.406933[/C][C]0.796534[/C][/ROW]
[ROW][C]222[/C][C]0.169861[/C][C]0.339721[/C][C]0.830139[/C][/ROW]
[ROW][C]223[/C][C]0.162484[/C][C]0.324968[/C][C]0.837516[/C][/ROW]
[ROW][C]224[/C][C]0.13915[/C][C]0.2783[/C][C]0.86085[/C][/ROW]
[ROW][C]225[/C][C]0.113435[/C][C]0.22687[/C][C]0.886565[/C][/ROW]
[ROW][C]226[/C][C]0.091434[/C][C]0.182868[/C][C]0.908566[/C][/ROW]
[ROW][C]227[/C][C]0.0724414[/C][C]0.144883[/C][C]0.927559[/C][/ROW]
[ROW][C]228[/C][C]0.0570517[/C][C]0.114103[/C][C]0.942948[/C][/ROW]
[ROW][C]229[/C][C]0.0429709[/C][C]0.0859418[/C][C]0.957029[/C][/ROW]
[ROW][C]230[/C][C]0.0322177[/C][C]0.0644355[/C][C]0.967782[/C][/ROW]
[ROW][C]231[/C][C]0.0470099[/C][C]0.0940197[/C][C]0.95299[/C][/ROW]
[ROW][C]232[/C][C]0.057924[/C][C]0.115848[/C][C]0.942076[/C][/ROW]
[ROW][C]233[/C][C]0.22514[/C][C]0.450279[/C][C]0.77486[/C][/ROW]
[ROW][C]234[/C][C]0.198299[/C][C]0.396599[/C][C]0.801701[/C][/ROW]
[ROW][C]235[/C][C]0.15805[/C][C]0.3161[/C][C]0.84195[/C][/ROW]
[ROW][C]236[/C][C]0.156671[/C][C]0.313342[/C][C]0.843329[/C][/ROW]
[ROW][C]237[/C][C]0.188508[/C][C]0.377017[/C][C]0.811492[/C][/ROW]
[ROW][C]238[/C][C]0.203718[/C][C]0.407435[/C][C]0.796282[/C][/ROW]
[ROW][C]239[/C][C]0.194767[/C][C]0.389534[/C][C]0.805233[/C][/ROW]
[ROW][C]240[/C][C]0.154997[/C][C]0.309994[/C][C]0.845003[/C][/ROW]
[ROW][C]241[/C][C]0.122274[/C][C]0.244547[/C][C]0.877726[/C][/ROW]
[ROW][C]242[/C][C]0.154417[/C][C]0.308835[/C][C]0.845583[/C][/ROW]
[ROW][C]243[/C][C]0.405515[/C][C]0.81103[/C][C]0.594485[/C][/ROW]
[ROW][C]244[/C][C]0.596307[/C][C]0.807386[/C][C]0.403693[/C][/ROW]
[ROW][C]245[/C][C]0.512312[/C][C]0.975376[/C][C]0.487688[/C][/ROW]
[ROW][C]246[/C][C]0.437212[/C][C]0.874423[/C][C]0.562788[/C][/ROW]
[ROW][C]247[/C][C]0.359999[/C][C]0.719997[/C][C]0.640001[/C][/ROW]
[ROW][C]248[/C][C]0.295332[/C][C]0.590664[/C][C]0.704668[/C][/ROW]
[ROW][C]249[/C][C]0.211514[/C][C]0.423028[/C][C]0.788486[/C][/ROW]
[ROW][C]250[/C][C]0.160221[/C][C]0.320441[/C][C]0.839779[/C][/ROW]
[ROW][C]251[/C][C]0.237561[/C][C]0.475122[/C][C]0.762439[/C][/ROW]
[ROW][C]252[/C][C]0.410921[/C][C]0.821843[/C][C]0.589079[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221929&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221929&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
120.9952880.009423760.00471188
130.9886290.02274210.0113711
140.9874440.02511240.0125562
150.9791370.04172580.0208629
160.9699140.06017260.0300863
170.9503540.09929250.0496463
180.9470330.1059340.0529668
190.9340560.1318880.0659441
200.9026080.1947850.0973923
210.8745120.2509760.125488
220.8337870.3324250.166213
230.7938050.4123890.206195
240.7584270.4831450.241573
250.7104040.5791910.289596
260.7073450.5853090.292655
270.7236980.5526030.276302
280.7293440.5413110.270656
290.6724180.6551640.327582
300.6261130.7477740.373887
310.5753350.8493290.424665
320.5915770.8168460.408423
330.53140.9371990.4686
340.4747420.9494830.525258
350.4540070.9080140.545993
360.4412810.8825610.558719
370.3865540.7731070.613446
380.367180.734360.63282
390.3477790.6955580.652221
400.3221610.6443210.677839
410.2915940.5831870.708406
420.2592890.5185780.740711
430.3002760.6005520.699724
440.258930.5178610.74107
450.2193710.4387420.780629
460.2561130.5122270.743887
470.2739090.5478180.726091
480.2337860.4675720.766214
490.2221780.4443560.777822
500.204410.4088210.79559
510.2100210.4200410.789979
520.1776270.3552540.822373
530.1814030.3628070.818597
540.1596590.3193180.840341
550.2387880.4775750.761212
560.5193530.9612930.480647
570.4755450.9510890.524455
580.4316810.8633620.568319
590.3904070.7808130.609593
600.3900240.7800480.609976
610.4027330.8054650.597267
620.3618240.7236480.638176
630.3653310.7306620.634669
640.3258250.6516510.674175
650.2979060.5958120.702094
660.2622640.5245280.737736
670.2362430.4724870.763757
680.2202190.4404370.779781
690.2101570.4203140.789843
700.1841680.3683360.815832
710.166640.333280.83336
720.1432120.2864240.856788
730.1226920.2453850.877308
740.1047330.2094670.895267
750.09253770.1850750.907462
760.119420.238840.88058
770.1067530.2135060.893247
780.08941050.1788210.91059
790.09206340.1841270.907937
800.08445990.168920.91554
810.07094590.1418920.929054
820.05932410.1186480.940676
830.05039870.1007970.949601
840.0415890.08317810.958411
850.03957010.07914010.96043
860.04639170.09278340.953608
870.03764130.07528250.962359
880.03058370.06116730.969416
890.02566330.05132670.974337
900.02180770.04361550.978192
910.03358010.06716030.96642
920.02810960.05621920.97189
930.02500890.05001780.974991
940.02556050.0511210.97444
950.02661260.05322520.973387
960.02354140.04708280.976459
970.03035580.06071150.969644
980.02451160.04902320.975488
990.02109860.04219720.978901
1000.02370170.04740340.976298
1010.01984770.03969530.980152
1020.01669530.03339060.983305
1030.01317350.02634690.986827
1040.0118110.0236220.988189
1050.01262020.02524040.98738
1060.009919130.01983830.990081
1070.007793090.01558620.992207
1080.006504460.01300890.993496
1090.009465830.01893170.990534
1100.007367110.01473420.992633
1110.008197940.01639590.991802
1120.008699170.01739830.991301
1130.007100270.01420050.9929
1140.005670650.01134130.994329
1150.004388910.008777820.995611
1160.004986210.009972410.995014
1170.007449120.01489820.992551
1180.006154550.01230910.993845
1190.00476210.00952420.995238
1200.003956610.007913220.996043
1210.003725210.007450410.996275
1220.003700960.007401910.996299
1230.004291390.008582780.995709
1240.004770370.009540730.99523
1250.008568540.01713710.991431
1260.007237090.01447420.992763
1270.006294190.01258840.993706
1280.0066980.0133960.993302
1290.006612230.01322450.993388
1300.006704050.01340810.993296
1310.008853810.01770760.991146
1320.01774140.03548280.982259
1330.01773920.03547840.982261
1340.01699910.03399810.983001
1350.01505090.03010190.984949
1360.01236140.02472280.987639
1370.009989880.01997980.99001
1380.009595930.01919190.990404
1390.008605340.01721070.991395
1400.007371290.01474260.992629
1410.01303520.02607040.986965
1420.0147060.02941190.985294
1430.02128860.04257730.978711
1440.01717470.03434940.982825
1450.01375330.02750650.986247
1460.01164350.0232870.988356
1470.01487450.02974910.985125
1480.01321060.02642110.986789
1490.01118970.02237950.98881
1500.009866580.01973320.990133
1510.0122080.02441610.987792
1520.01443040.02886070.98557
1530.06496710.1299340.935033
1540.06511040.1302210.93489
1550.05598350.1119670.944017
1560.106070.212140.89393
1570.14770.29540.8523
1580.1387830.2775670.861217
1590.1246550.249310.875345
1600.1147220.2294450.885278
1610.1047860.2095710.895214
1620.09079040.1815810.90921
1630.08163350.1632670.918366
1640.08650150.1730030.913499
1650.07827570.1565510.921724
1660.06642880.1328580.933571
1670.05639060.1127810.943609
1680.09353710.1870740.906463
1690.09439220.1887840.905608
1700.08200530.1640110.917995
1710.143740.2874810.85626
1720.1245080.2490160.875492
1730.10940.21880.8906
1740.09378270.1875650.906217
1750.1294150.2588290.870585
1760.1119760.2239520.888024
1770.1004980.2009960.899502
1780.08593030.1718610.91407
1790.07232990.144660.92767
1800.060450.12090.93955
1810.05037050.1007410.949629
1820.05723130.1144630.942769
1830.05743620.1148720.942564
1840.05315620.1063120.946844
1850.2152850.430570.784715
1860.1977820.3955630.802218
1870.176640.353280.82336
1880.1757940.3515880.824206
1890.1624640.3249290.837536
1900.2408440.4816880.759156
1910.2458530.4917070.754147
1920.2165740.4331470.783426
1930.5807230.8385540.419277
1940.5489820.9020360.451018
1950.5118990.9762020.488101
1960.4801580.9603160.519842
1970.4921110.9842210.507889
1980.4560780.9121550.543922
1990.4286480.8572950.571352
2000.4298160.8596310.570184
2010.4041880.8083760.595812
2020.3827510.7655020.617249
2030.3613520.7227050.638648
2040.4144830.8289660.585517
2050.444380.8887590.55562
2060.4018350.803670.598165
2070.3617090.7234190.638291
2080.3235880.6471770.676412
2090.3062890.6125770.693711
2100.2692890.5385770.730711
2110.3332810.6665620.666719
2120.350850.7016990.64915
2130.3097140.6194270.690286
2140.3276250.655250.672375
2150.2930040.5860080.706996
2160.2578120.5156240.742188
2170.2231430.4462850.776857
2180.1885510.3771020.811449
2190.186130.372260.81387
2200.1641810.3283620.835819
2210.2034660.4069330.796534
2220.1698610.3397210.830139
2230.1624840.3249680.837516
2240.139150.27830.86085
2250.1134350.226870.886565
2260.0914340.1828680.908566
2270.07244140.1448830.927559
2280.05705170.1141030.942948
2290.04297090.08594180.957029
2300.03221770.06443550.967782
2310.04700990.09401970.95299
2320.0579240.1158480.942076
2330.225140.4502790.77486
2340.1982990.3965990.801701
2350.158050.31610.84195
2360.1566710.3133420.843329
2370.1885080.3770170.811492
2380.2037180.4074350.796282
2390.1947670.3895340.805233
2400.1549970.3099940.845003
2410.1222740.2445470.877726
2420.1544170.3088350.845583
2430.4055150.811030.594485
2440.5963070.8073860.403693
2450.5123120.9753760.487688
2460.4372120.8744230.562788
2470.3599990.7199970.640001
2480.2953320.5906640.704668
2490.2115140.4230280.788486
2500.1602210.3204410.839779
2510.2375610.4751220.762439
2520.4109210.8218430.589079






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level90.0373444NOK
5% type I error level610.253112NOK
10% type I error level780.323651NOK

\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 & 9 & 0.0373444 & NOK \tabularnewline
5% type I error level & 61 & 0.253112 & NOK \tabularnewline
10% type I error level & 78 & 0.323651 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221929&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]9[/C][C]0.0373444[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]61[/C][C]0.253112[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]78[/C][C]0.323651[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221929&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221929&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 level90.0373444NOK
5% type I error level610.253112NOK
10% type I error level780.323651NOK


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 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 4 ; 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')
}