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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 computationSat, 02 Nov 2013 16:57:07 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/02/t1383425856jwr5avfkybyfsbs.htm/, Retrieved Tue, 07 May 2024 08:26:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221814, Retrieved Tue, 07 May 2024 08:26:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [WORKSHOP 7 ] [2013-11-02 19:41:02] [69bf0eb8b9b38defaaf4848d8c317571]
- R PD    [Multiple Regression] [ws7 1] [2013-11-02 20:57:07] [4c6743e926d608f4adf2160fecf92c6f] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 13 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221814&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221814&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221814&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 time13 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 3.78198 + 0.0469471Connected[t] + 0.0420052Separate[t] + 0.607446Software[t] + 0.0985621Happiness[t] -0.0394659Depression[t] + 0.0158262Sport1[t] -0.0193788Sport2[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  3.78198 +  0.0469471Connected[t] +  0.0420052Separate[t] +  0.607446Software[t] +  0.0985621Happiness[t] -0.0394659Depression[t] +  0.0158262Sport1[t] -0.0193788Sport2[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221814&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  3.78198 +  0.0469471Connected[t] +  0.0420052Separate[t] +  0.607446Software[t] +  0.0985621Happiness[t] -0.0394659Depression[t] +  0.0158262Sport1[t] -0.0193788Sport2[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221814&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221814&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 3.78198 + 0.0469471Connected[t] + 0.0420052Separate[t] + 0.607446Software[t] + 0.0985621Happiness[t] -0.0394659Depression[t] + 0.0158262Sport1[t] -0.0193788Sport2[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)3.781981.917671.9720.04966660.0248333
Connected0.04694710.03478661.350.1783450.0891725
Separate0.04200520.03564831.1780.2397620.119881
Software0.6074460.051841711.721.13111e-255.65557e-26
Happiness0.09856210.05796931.70.0902990.0451495
Depression-0.03946590.0425648-0.92720.3546980.177349
Sport10.01582620.03784760.41820.6761840.338092
Sport2-0.01937880.0564467-0.34330.7316470.365823

\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) & 3.78198 & 1.91767 & 1.972 & 0.0496666 & 0.0248333 \tabularnewline
Connected & 0.0469471 & 0.0347866 & 1.35 & 0.178345 & 0.0891725 \tabularnewline
Separate & 0.0420052 & 0.0356483 & 1.178 & 0.239762 & 0.119881 \tabularnewline
Software & 0.607446 & 0.0518417 & 11.72 & 1.13111e-25 & 5.65557e-26 \tabularnewline
Happiness & 0.0985621 & 0.0579693 & 1.7 & 0.090299 & 0.0451495 \tabularnewline
Depression & -0.0394659 & 0.0425648 & -0.9272 & 0.354698 & 0.177349 \tabularnewline
Sport1 & 0.0158262 & 0.0378476 & 0.4182 & 0.676184 & 0.338092 \tabularnewline
Sport2 & -0.0193788 & 0.0564467 & -0.3433 & 0.731647 & 0.365823 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221814&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]3.78198[/C][C]1.91767[/C][C]1.972[/C][C]0.0496666[/C][C]0.0248333[/C][/ROW]
[ROW][C]Connected[/C][C]0.0469471[/C][C]0.0347866[/C][C]1.35[/C][C]0.178345[/C][C]0.0891725[/C][/ROW]
[ROW][C]Separate[/C][C]0.0420052[/C][C]0.0356483[/C][C]1.178[/C][C]0.239762[/C][C]0.119881[/C][/ROW]
[ROW][C]Software[/C][C]0.607446[/C][C]0.0518417[/C][C]11.72[/C][C]1.13111e-25[/C][C]5.65557e-26[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0985621[/C][C]0.0579693[/C][C]1.7[/C][C]0.090299[/C][C]0.0451495[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0394659[/C][C]0.0425648[/C][C]-0.9272[/C][C]0.354698[/C][C]0.177349[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0158262[/C][C]0.0378476[/C][C]0.4182[/C][C]0.676184[/C][C]0.338092[/C][/ROW]
[ROW][C]Sport2[/C][C]-0.0193788[/C][C]0.0564467[/C][C]-0.3433[/C][C]0.731647[/C][C]0.365823[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221814&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221814&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)3.781981.917671.9720.04966660.0248333
Connected0.04694710.03478661.350.1783450.0891725
Separate0.04200520.03564831.1780.2397620.119881
Software0.6074460.051841711.721.13111e-255.65557e-26
Happiness0.09856210.05796931.70.0902990.0451495
Depression-0.03946590.0425648-0.92720.3546980.177349
Sport10.01582620.03784760.41820.6761840.338092
Sport2-0.01937880.0564467-0.34330.7316470.365823






Multiple Linear Regression - Regression Statistics
Multiple R0.6534
R-squared0.426932
Adjusted R-squared0.411262
F-TEST (value)27.2455
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.88445
Sum Squared Residuals909.095

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.6534 \tabularnewline
R-squared & 0.426932 \tabularnewline
Adjusted R-squared & 0.411262 \tabularnewline
F-TEST (value) & 27.2455 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.88445 \tabularnewline
Sum Squared Residuals & 909.095 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221814&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.6534[/C][/ROW]
[ROW][C]R-squared[/C][C]0.426932[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.411262[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]27.2455[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.88445[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]909.095[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221814&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221814&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 R0.6534
R-squared0.426932
Adjusted R-squared0.411262
F-TEST (value)27.2455
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.88445
Sum Squared Residuals909.095






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.7173-2.7173
21615.30420.695769
31916.53452.46546
41511.24323.75684
51415.8887-1.88874
61314.3419-1.3419
71914.83784.16219
81516.6569-1.65688
91415.6145-1.61447
101513.83961.16041
111614.52421.47581
121615.96170.0383365
131614.96561.03443
141615.13060.869402
151717.7264-0.72637
161515.0074-0.00743243
171514.0330.96704
182016.03923.96081
191815.09462.90543
201615.18620.813809
211615.00150.998453
221614.5841.41598
231916.22732.7727
241614.63861.3614
251715.84121.15879
261715.83491.16507
271614.52911.47092
281516.4169-1.41688
291615.29510.704944
301413.61760.382379
311515.3672-0.367181
321212.1577-0.157712
331414.4669-0.466905
341615.5490.45103
351415.1517-1.15172
361012.4548-2.45483
371012.2904-2.29039
381415.4428-1.4428
391614.11231.88768
401614.05051.9495
411614.361.64003
421415.4125-1.41247
432017.49822.5018
441413.73820.261805
451414.139-0.138973
461115.1507-4.1507
471416.4196-2.41962
481514.78120.218844
491615.1910.809032
501415.3616-1.36158
511616.8539-0.853874
521413.73140.268554
531214.6136-2.61363
541615.59120.408809
55910.7137-1.71371
561411.85182.14823
571615.69350.306532
581615.23070.769349
591514.82320.176781
601613.79312.20694
611210.83651.1635
621615.43780.562221
631616.2991-0.299105
641414.439-0.438987
651615.15020.849824
661715.74411.25586
671816.09041.90962
681814.07643.92363
691215.8085-3.8085
701615.47270.527328
711013.0122-3.01222
721414.7156-0.715555
731816.83771.16227
741817.1930.806953
751615.00930.99069
761713.08953.91049
771616.407-0.407049
781614.2121.78803
791314.9612-1.96119
801615.08370.916264
811615.53590.464083
821615.64350.356482
831515.62-0.619965
841514.6860.313978
851613.88252.11753
861413.95150.0485269
871615.23310.766868
881614.68141.31861
891514.1030.897019
901213.6429-1.64292
911716.83240.167643
921615.72930.270747
931514.90520.094776
941314.856-1.85596
951614.69771.30228
961615.6960.303995
971613.48312.51694
981615.82970.170286
991414.2661-0.266066
1001617.194-1.19403
1011614.50571.49434
1022017.57892.42112
1031514.0230.976991
1041614.83781.16222
1051314.7122-1.71223
1061715.76041.23965
1071615.77170.228293
1081614.23291.7671
1091212.0021-0.00211891
1101615.17140.828648
1111615.93840.0615863
1121714.86252.13755
1131314.5285-1.52847
1141214.6142-2.61417
1151816.27631.72371
1161415.9507-1.95069
1171412.99251.00755
1181314.7861-1.78609
1191615.51390.486094
1201314.3732-1.3732
1211615.4070.593016
1221315.8999-2.8999
1231617.0741-1.07415
1241515.9986-0.9986
1251616.9218-0.921842
1261514.74990.250111
1271715.76711.23288
1281514.00380.996171
1291214.7454-2.74539
1301613.90182.09816
1311013.4897-3.48968
1321613.48462.51542
1331214.1316-2.1316
1341415.6891-1.68912
1351515.1344-0.134404
1361311.87921.1208
1371514.54070.45925
1381113.3641-2.36411
1391212.9949-0.994898
1401113.2797-2.27972
1411612.87093.12909
1421513.57711.42285
1431717.0125-0.0125121
1441614.21741.78261
1451013.3072-3.30715
1461815.71062.28939
1471315.0579-2.05791
1481614.921.08005
1491312.63740.362604
1501012.8778-2.87784
1511516.1546-1.15459
1521613.99232.00768
1531611.7044.29603
1541412.24961.75037
1551012.31-2.31
1561716.83240.167643
1571311.56921.43078
1581514.00380.996171
1591614.67141.32856
1601212.5729-0.572865
1611312.60040.399634
1621312.46580.53418
1631212.3875-0.387502
1641716.57290.427139
1651513.67231.32773
1661011.42-1.42001
1671414.469-0.469003
1681114.2908-3.29077
1691314.8481-1.84814
1701614.43051.56946
1711210.36481.63517
1721615.70580.294166
1731213.9886-1.98855
174911.3116-2.31157
1751215.2883-3.28832
1761514.74430.255742
1771212.2633-0.263253
1781212.6874-0.687392
1791414.0621-0.0621132
1801213.4761-1.47606
1811615.43450.565534
1821111.5219-0.521893
1831917.16071.83932
1841515.5206-0.520605
185814.7659-6.76587
1861614.96741.0326
1871714.74732.25265
1881212.5412-0.541216
1891111.5268-0.526795
1901110.29870.701278
1911415.0452-1.04517
1921615.8550.14497
193129.657332.34267
1941614.30061.69936
1951313.9156-0.915634
1961515.3689-0.368886
1971613.09752.90255
1981615.31250.687545
1991412.48731.51273
2001614.77031.22968
2011614.19541.80463
2021413.5650.434985
2031113.7618-2.76184
2041214.9168-2.91683
2051512.96952.03052
2061514.83670.163265
2071614.84691.15311
2081615.43390.566116
2091113.9167-2.91665
2101514.30270.697331
2111214.5076-2.50756
2121216.2896-4.28958
2131514.30860.691391
2141512.16742.83261
2151614.88311.11688
2161413.42060.579371
2171715.06231.93773
2181414.3277-0.327702
2191311.98981.01017
2201515.6156-0.615582
2211315.0226-2.0226
2221414.5732-0.573189
2231514.56630.433735
2241213.4586-1.45857
2251312.80390.196122
226811.9665-3.9665
2271414.3096-0.309628
2281413.27370.726256
2291112.3428-1.34276
2301213.161-1.16104
2311311.47971.52034
2321013.4652-3.46518
2331611.70074.29935
2341816.45571.54433
2351314.3054-1.30542
2361113.6549-2.6549
237411.1695-7.16952
2381314.8156-1.81562
2391614.59261.40735
2401011.9287-1.92871
2411212.407-0.406995
2421213.7958-1.79576
243108.885931.11407
2441311.27661.72336
2451514.09220.907782
2461212.0462-0.0461519
2471413.15370.846312
2481012.8898-2.88977
2491210.80061.19942
2501211.88370.116305
2511112.1375-1.13747
2521011.8615-1.86154
2531211.66310.336903
2541613.17812.8219
2551213.715-1.71499
2561414.2641-0.264075
2571614.68061.31938
2581411.82382.17619
2591314.7814-1.78137
26049.48339-5.48339
2611514.17440.825633
2621115.5502-4.55021
2631111.4713-0.471302
2641413.16710.832904

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 15.7173 & -2.7173 \tabularnewline
2 & 16 & 15.3042 & 0.695769 \tabularnewline
3 & 19 & 16.5345 & 2.46546 \tabularnewline
4 & 15 & 11.2432 & 3.75684 \tabularnewline
5 & 14 & 15.8887 & -1.88874 \tabularnewline
6 & 13 & 14.3419 & -1.3419 \tabularnewline
7 & 19 & 14.8378 & 4.16219 \tabularnewline
8 & 15 & 16.6569 & -1.65688 \tabularnewline
9 & 14 & 15.6145 & -1.61447 \tabularnewline
10 & 15 & 13.8396 & 1.16041 \tabularnewline
11 & 16 & 14.5242 & 1.47581 \tabularnewline
12 & 16 & 15.9617 & 0.0383365 \tabularnewline
13 & 16 & 14.9656 & 1.03443 \tabularnewline
14 & 16 & 15.1306 & 0.869402 \tabularnewline
15 & 17 & 17.7264 & -0.72637 \tabularnewline
16 & 15 & 15.0074 & -0.00743243 \tabularnewline
17 & 15 & 14.033 & 0.96704 \tabularnewline
18 & 20 & 16.0392 & 3.96081 \tabularnewline
19 & 18 & 15.0946 & 2.90543 \tabularnewline
20 & 16 & 15.1862 & 0.813809 \tabularnewline
21 & 16 & 15.0015 & 0.998453 \tabularnewline
22 & 16 & 14.584 & 1.41598 \tabularnewline
23 & 19 & 16.2273 & 2.7727 \tabularnewline
24 & 16 & 14.6386 & 1.3614 \tabularnewline
25 & 17 & 15.8412 & 1.15879 \tabularnewline
26 & 17 & 15.8349 & 1.16507 \tabularnewline
27 & 16 & 14.5291 & 1.47092 \tabularnewline
28 & 15 & 16.4169 & -1.41688 \tabularnewline
29 & 16 & 15.2951 & 0.704944 \tabularnewline
30 & 14 & 13.6176 & 0.382379 \tabularnewline
31 & 15 & 15.3672 & -0.367181 \tabularnewline
32 & 12 & 12.1577 & -0.157712 \tabularnewline
33 & 14 & 14.4669 & -0.466905 \tabularnewline
34 & 16 & 15.549 & 0.45103 \tabularnewline
35 & 14 & 15.1517 & -1.15172 \tabularnewline
36 & 10 & 12.4548 & -2.45483 \tabularnewline
37 & 10 & 12.2904 & -2.29039 \tabularnewline
38 & 14 & 15.4428 & -1.4428 \tabularnewline
39 & 16 & 14.1123 & 1.88768 \tabularnewline
40 & 16 & 14.0505 & 1.9495 \tabularnewline
41 & 16 & 14.36 & 1.64003 \tabularnewline
42 & 14 & 15.4125 & -1.41247 \tabularnewline
43 & 20 & 17.4982 & 2.5018 \tabularnewline
44 & 14 & 13.7382 & 0.261805 \tabularnewline
45 & 14 & 14.139 & -0.138973 \tabularnewline
46 & 11 & 15.1507 & -4.1507 \tabularnewline
47 & 14 & 16.4196 & -2.41962 \tabularnewline
48 & 15 & 14.7812 & 0.218844 \tabularnewline
49 & 16 & 15.191 & 0.809032 \tabularnewline
50 & 14 & 15.3616 & -1.36158 \tabularnewline
51 & 16 & 16.8539 & -0.853874 \tabularnewline
52 & 14 & 13.7314 & 0.268554 \tabularnewline
53 & 12 & 14.6136 & -2.61363 \tabularnewline
54 & 16 & 15.5912 & 0.408809 \tabularnewline
55 & 9 & 10.7137 & -1.71371 \tabularnewline
56 & 14 & 11.8518 & 2.14823 \tabularnewline
57 & 16 & 15.6935 & 0.306532 \tabularnewline
58 & 16 & 15.2307 & 0.769349 \tabularnewline
59 & 15 & 14.8232 & 0.176781 \tabularnewline
60 & 16 & 13.7931 & 2.20694 \tabularnewline
61 & 12 & 10.8365 & 1.1635 \tabularnewline
62 & 16 & 15.4378 & 0.562221 \tabularnewline
63 & 16 & 16.2991 & -0.299105 \tabularnewline
64 & 14 & 14.439 & -0.438987 \tabularnewline
65 & 16 & 15.1502 & 0.849824 \tabularnewline
66 & 17 & 15.7441 & 1.25586 \tabularnewline
67 & 18 & 16.0904 & 1.90962 \tabularnewline
68 & 18 & 14.0764 & 3.92363 \tabularnewline
69 & 12 & 15.8085 & -3.8085 \tabularnewline
70 & 16 & 15.4727 & 0.527328 \tabularnewline
71 & 10 & 13.0122 & -3.01222 \tabularnewline
72 & 14 & 14.7156 & -0.715555 \tabularnewline
73 & 18 & 16.8377 & 1.16227 \tabularnewline
74 & 18 & 17.193 & 0.806953 \tabularnewline
75 & 16 & 15.0093 & 0.99069 \tabularnewline
76 & 17 & 13.0895 & 3.91049 \tabularnewline
77 & 16 & 16.407 & -0.407049 \tabularnewline
78 & 16 & 14.212 & 1.78803 \tabularnewline
79 & 13 & 14.9612 & -1.96119 \tabularnewline
80 & 16 & 15.0837 & 0.916264 \tabularnewline
81 & 16 & 15.5359 & 0.464083 \tabularnewline
82 & 16 & 15.6435 & 0.356482 \tabularnewline
83 & 15 & 15.62 & -0.619965 \tabularnewline
84 & 15 & 14.686 & 0.313978 \tabularnewline
85 & 16 & 13.8825 & 2.11753 \tabularnewline
86 & 14 & 13.9515 & 0.0485269 \tabularnewline
87 & 16 & 15.2331 & 0.766868 \tabularnewline
88 & 16 & 14.6814 & 1.31861 \tabularnewline
89 & 15 & 14.103 & 0.897019 \tabularnewline
90 & 12 & 13.6429 & -1.64292 \tabularnewline
91 & 17 & 16.8324 & 0.167643 \tabularnewline
92 & 16 & 15.7293 & 0.270747 \tabularnewline
93 & 15 & 14.9052 & 0.094776 \tabularnewline
94 & 13 & 14.856 & -1.85596 \tabularnewline
95 & 16 & 14.6977 & 1.30228 \tabularnewline
96 & 16 & 15.696 & 0.303995 \tabularnewline
97 & 16 & 13.4831 & 2.51694 \tabularnewline
98 & 16 & 15.8297 & 0.170286 \tabularnewline
99 & 14 & 14.2661 & -0.266066 \tabularnewline
100 & 16 & 17.194 & -1.19403 \tabularnewline
101 & 16 & 14.5057 & 1.49434 \tabularnewline
102 & 20 & 17.5789 & 2.42112 \tabularnewline
103 & 15 & 14.023 & 0.976991 \tabularnewline
104 & 16 & 14.8378 & 1.16222 \tabularnewline
105 & 13 & 14.7122 & -1.71223 \tabularnewline
106 & 17 & 15.7604 & 1.23965 \tabularnewline
107 & 16 & 15.7717 & 0.228293 \tabularnewline
108 & 16 & 14.2329 & 1.7671 \tabularnewline
109 & 12 & 12.0021 & -0.00211891 \tabularnewline
110 & 16 & 15.1714 & 0.828648 \tabularnewline
111 & 16 & 15.9384 & 0.0615863 \tabularnewline
112 & 17 & 14.8625 & 2.13755 \tabularnewline
113 & 13 & 14.5285 & -1.52847 \tabularnewline
114 & 12 & 14.6142 & -2.61417 \tabularnewline
115 & 18 & 16.2763 & 1.72371 \tabularnewline
116 & 14 & 15.9507 & -1.95069 \tabularnewline
117 & 14 & 12.9925 & 1.00755 \tabularnewline
118 & 13 & 14.7861 & -1.78609 \tabularnewline
119 & 16 & 15.5139 & 0.486094 \tabularnewline
120 & 13 & 14.3732 & -1.3732 \tabularnewline
121 & 16 & 15.407 & 0.593016 \tabularnewline
122 & 13 & 15.8999 & -2.8999 \tabularnewline
123 & 16 & 17.0741 & -1.07415 \tabularnewline
124 & 15 & 15.9986 & -0.9986 \tabularnewline
125 & 16 & 16.9218 & -0.921842 \tabularnewline
126 & 15 & 14.7499 & 0.250111 \tabularnewline
127 & 17 & 15.7671 & 1.23288 \tabularnewline
128 & 15 & 14.0038 & 0.996171 \tabularnewline
129 & 12 & 14.7454 & -2.74539 \tabularnewline
130 & 16 & 13.9018 & 2.09816 \tabularnewline
131 & 10 & 13.4897 & -3.48968 \tabularnewline
132 & 16 & 13.4846 & 2.51542 \tabularnewline
133 & 12 & 14.1316 & -2.1316 \tabularnewline
134 & 14 & 15.6891 & -1.68912 \tabularnewline
135 & 15 & 15.1344 & -0.134404 \tabularnewline
136 & 13 & 11.8792 & 1.1208 \tabularnewline
137 & 15 & 14.5407 & 0.45925 \tabularnewline
138 & 11 & 13.3641 & -2.36411 \tabularnewline
139 & 12 & 12.9949 & -0.994898 \tabularnewline
140 & 11 & 13.2797 & -2.27972 \tabularnewline
141 & 16 & 12.8709 & 3.12909 \tabularnewline
142 & 15 & 13.5771 & 1.42285 \tabularnewline
143 & 17 & 17.0125 & -0.0125121 \tabularnewline
144 & 16 & 14.2174 & 1.78261 \tabularnewline
145 & 10 & 13.3072 & -3.30715 \tabularnewline
146 & 18 & 15.7106 & 2.28939 \tabularnewline
147 & 13 & 15.0579 & -2.05791 \tabularnewline
148 & 16 & 14.92 & 1.08005 \tabularnewline
149 & 13 & 12.6374 & 0.362604 \tabularnewline
150 & 10 & 12.8778 & -2.87784 \tabularnewline
151 & 15 & 16.1546 & -1.15459 \tabularnewline
152 & 16 & 13.9923 & 2.00768 \tabularnewline
153 & 16 & 11.704 & 4.29603 \tabularnewline
154 & 14 & 12.2496 & 1.75037 \tabularnewline
155 & 10 & 12.31 & -2.31 \tabularnewline
156 & 17 & 16.8324 & 0.167643 \tabularnewline
157 & 13 & 11.5692 & 1.43078 \tabularnewline
158 & 15 & 14.0038 & 0.996171 \tabularnewline
159 & 16 & 14.6714 & 1.32856 \tabularnewline
160 & 12 & 12.5729 & -0.572865 \tabularnewline
161 & 13 & 12.6004 & 0.399634 \tabularnewline
162 & 13 & 12.4658 & 0.53418 \tabularnewline
163 & 12 & 12.3875 & -0.387502 \tabularnewline
164 & 17 & 16.5729 & 0.427139 \tabularnewline
165 & 15 & 13.6723 & 1.32773 \tabularnewline
166 & 10 & 11.42 & -1.42001 \tabularnewline
167 & 14 & 14.469 & -0.469003 \tabularnewline
168 & 11 & 14.2908 & -3.29077 \tabularnewline
169 & 13 & 14.8481 & -1.84814 \tabularnewline
170 & 16 & 14.4305 & 1.56946 \tabularnewline
171 & 12 & 10.3648 & 1.63517 \tabularnewline
172 & 16 & 15.7058 & 0.294166 \tabularnewline
173 & 12 & 13.9886 & -1.98855 \tabularnewline
174 & 9 & 11.3116 & -2.31157 \tabularnewline
175 & 12 & 15.2883 & -3.28832 \tabularnewline
176 & 15 & 14.7443 & 0.255742 \tabularnewline
177 & 12 & 12.2633 & -0.263253 \tabularnewline
178 & 12 & 12.6874 & -0.687392 \tabularnewline
179 & 14 & 14.0621 & -0.0621132 \tabularnewline
180 & 12 & 13.4761 & -1.47606 \tabularnewline
181 & 16 & 15.4345 & 0.565534 \tabularnewline
182 & 11 & 11.5219 & -0.521893 \tabularnewline
183 & 19 & 17.1607 & 1.83932 \tabularnewline
184 & 15 & 15.5206 & -0.520605 \tabularnewline
185 & 8 & 14.7659 & -6.76587 \tabularnewline
186 & 16 & 14.9674 & 1.0326 \tabularnewline
187 & 17 & 14.7473 & 2.25265 \tabularnewline
188 & 12 & 12.5412 & -0.541216 \tabularnewline
189 & 11 & 11.5268 & -0.526795 \tabularnewline
190 & 11 & 10.2987 & 0.701278 \tabularnewline
191 & 14 & 15.0452 & -1.04517 \tabularnewline
192 & 16 & 15.855 & 0.14497 \tabularnewline
193 & 12 & 9.65733 & 2.34267 \tabularnewline
194 & 16 & 14.3006 & 1.69936 \tabularnewline
195 & 13 & 13.9156 & -0.915634 \tabularnewline
196 & 15 & 15.3689 & -0.368886 \tabularnewline
197 & 16 & 13.0975 & 2.90255 \tabularnewline
198 & 16 & 15.3125 & 0.687545 \tabularnewline
199 & 14 & 12.4873 & 1.51273 \tabularnewline
200 & 16 & 14.7703 & 1.22968 \tabularnewline
201 & 16 & 14.1954 & 1.80463 \tabularnewline
202 & 14 & 13.565 & 0.434985 \tabularnewline
203 & 11 & 13.7618 & -2.76184 \tabularnewline
204 & 12 & 14.9168 & -2.91683 \tabularnewline
205 & 15 & 12.9695 & 2.03052 \tabularnewline
206 & 15 & 14.8367 & 0.163265 \tabularnewline
207 & 16 & 14.8469 & 1.15311 \tabularnewline
208 & 16 & 15.4339 & 0.566116 \tabularnewline
209 & 11 & 13.9167 & -2.91665 \tabularnewline
210 & 15 & 14.3027 & 0.697331 \tabularnewline
211 & 12 & 14.5076 & -2.50756 \tabularnewline
212 & 12 & 16.2896 & -4.28958 \tabularnewline
213 & 15 & 14.3086 & 0.691391 \tabularnewline
214 & 15 & 12.1674 & 2.83261 \tabularnewline
215 & 16 & 14.8831 & 1.11688 \tabularnewline
216 & 14 & 13.4206 & 0.579371 \tabularnewline
217 & 17 & 15.0623 & 1.93773 \tabularnewline
218 & 14 & 14.3277 & -0.327702 \tabularnewline
219 & 13 & 11.9898 & 1.01017 \tabularnewline
220 & 15 & 15.6156 & -0.615582 \tabularnewline
221 & 13 & 15.0226 & -2.0226 \tabularnewline
222 & 14 & 14.5732 & -0.573189 \tabularnewline
223 & 15 & 14.5663 & 0.433735 \tabularnewline
224 & 12 & 13.4586 & -1.45857 \tabularnewline
225 & 13 & 12.8039 & 0.196122 \tabularnewline
226 & 8 & 11.9665 & -3.9665 \tabularnewline
227 & 14 & 14.3096 & -0.309628 \tabularnewline
228 & 14 & 13.2737 & 0.726256 \tabularnewline
229 & 11 & 12.3428 & -1.34276 \tabularnewline
230 & 12 & 13.161 & -1.16104 \tabularnewline
231 & 13 & 11.4797 & 1.52034 \tabularnewline
232 & 10 & 13.4652 & -3.46518 \tabularnewline
233 & 16 & 11.7007 & 4.29935 \tabularnewline
234 & 18 & 16.4557 & 1.54433 \tabularnewline
235 & 13 & 14.3054 & -1.30542 \tabularnewline
236 & 11 & 13.6549 & -2.6549 \tabularnewline
237 & 4 & 11.1695 & -7.16952 \tabularnewline
238 & 13 & 14.8156 & -1.81562 \tabularnewline
239 & 16 & 14.5926 & 1.40735 \tabularnewline
240 & 10 & 11.9287 & -1.92871 \tabularnewline
241 & 12 & 12.407 & -0.406995 \tabularnewline
242 & 12 & 13.7958 & -1.79576 \tabularnewline
243 & 10 & 8.88593 & 1.11407 \tabularnewline
244 & 13 & 11.2766 & 1.72336 \tabularnewline
245 & 15 & 14.0922 & 0.907782 \tabularnewline
246 & 12 & 12.0462 & -0.0461519 \tabularnewline
247 & 14 & 13.1537 & 0.846312 \tabularnewline
248 & 10 & 12.8898 & -2.88977 \tabularnewline
249 & 12 & 10.8006 & 1.19942 \tabularnewline
250 & 12 & 11.8837 & 0.116305 \tabularnewline
251 & 11 & 12.1375 & -1.13747 \tabularnewline
252 & 10 & 11.8615 & -1.86154 \tabularnewline
253 & 12 & 11.6631 & 0.336903 \tabularnewline
254 & 16 & 13.1781 & 2.8219 \tabularnewline
255 & 12 & 13.715 & -1.71499 \tabularnewline
256 & 14 & 14.2641 & -0.264075 \tabularnewline
257 & 16 & 14.6806 & 1.31938 \tabularnewline
258 & 14 & 11.8238 & 2.17619 \tabularnewline
259 & 13 & 14.7814 & -1.78137 \tabularnewline
260 & 4 & 9.48339 & -5.48339 \tabularnewline
261 & 15 & 14.1744 & 0.825633 \tabularnewline
262 & 11 & 15.5502 & -4.55021 \tabularnewline
263 & 11 & 11.4713 & -0.471302 \tabularnewline
264 & 14 & 13.1671 & 0.832904 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221814&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]13[/C][C]15.7173[/C][C]-2.7173[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.3042[/C][C]0.695769[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]16.5345[/C][C]2.46546[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]11.2432[/C][C]3.75684[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]15.8887[/C][C]-1.88874[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.3419[/C][C]-1.3419[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]14.8378[/C][C]4.16219[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]16.6569[/C][C]-1.65688[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.6145[/C][C]-1.61447[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]13.8396[/C][C]1.16041[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.5242[/C][C]1.47581[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]15.9617[/C][C]0.0383365[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]14.9656[/C][C]1.03443[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.1306[/C][C]0.869402[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.7264[/C][C]-0.72637[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.0074[/C][C]-0.00743243[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.033[/C][C]0.96704[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.0392[/C][C]3.96081[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.0946[/C][C]2.90543[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.1862[/C][C]0.813809[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.0015[/C][C]0.998453[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]14.584[/C][C]1.41598[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.2273[/C][C]2.7727[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.6386[/C][C]1.3614[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.8412[/C][C]1.15879[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]15.8349[/C][C]1.16507[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.5291[/C][C]1.47092[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.4169[/C][C]-1.41688[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.2951[/C][C]0.704944[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]13.6176[/C][C]0.382379[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.3672[/C][C]-0.367181[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.1577[/C][C]-0.157712[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.4669[/C][C]-0.466905[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.549[/C][C]0.45103[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.1517[/C][C]-1.15172[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.4548[/C][C]-2.45483[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]12.2904[/C][C]-2.29039[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.4428[/C][C]-1.4428[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.1123[/C][C]1.88768[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.0505[/C][C]1.9495[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.36[/C][C]1.64003[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.4125[/C][C]-1.41247[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.4982[/C][C]2.5018[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]13.7382[/C][C]0.261805[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.139[/C][C]-0.138973[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.1507[/C][C]-4.1507[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.4196[/C][C]-2.41962[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.7812[/C][C]0.218844[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.191[/C][C]0.809032[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.3616[/C][C]-1.36158[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.8539[/C][C]-0.853874[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.7314[/C][C]0.268554[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.6136[/C][C]-2.61363[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.5912[/C][C]0.408809[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]10.7137[/C][C]-1.71371[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]11.8518[/C][C]2.14823[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.6935[/C][C]0.306532[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.2307[/C][C]0.769349[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]14.8232[/C][C]0.176781[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]13.7931[/C][C]2.20694[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]10.8365[/C][C]1.1635[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.4378[/C][C]0.562221[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.2991[/C][C]-0.299105[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.439[/C][C]-0.438987[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.1502[/C][C]0.849824[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]15.7441[/C][C]1.25586[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.0904[/C][C]1.90962[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.0764[/C][C]3.92363[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.8085[/C][C]-3.8085[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.4727[/C][C]0.527328[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.0122[/C][C]-3.01222[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.7156[/C][C]-0.715555[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.8377[/C][C]1.16227[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.193[/C][C]0.806953[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.0093[/C][C]0.99069[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.0895[/C][C]3.91049[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.407[/C][C]-0.407049[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.212[/C][C]1.78803[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]14.9612[/C][C]-1.96119[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.0837[/C][C]0.916264[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.5359[/C][C]0.464083[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.6435[/C][C]0.356482[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.62[/C][C]-0.619965[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.686[/C][C]0.313978[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]13.8825[/C][C]2.11753[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]13.9515[/C][C]0.0485269[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.2331[/C][C]0.766868[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.6814[/C][C]1.31861[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.103[/C][C]0.897019[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.6429[/C][C]-1.64292[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.8324[/C][C]0.167643[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.7293[/C][C]0.270747[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]14.9052[/C][C]0.094776[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.856[/C][C]-1.85596[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.6977[/C][C]1.30228[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.696[/C][C]0.303995[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.4831[/C][C]2.51694[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.8297[/C][C]0.170286[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.2661[/C][C]-0.266066[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.194[/C][C]-1.19403[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.5057[/C][C]1.49434[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.5789[/C][C]2.42112[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.023[/C][C]0.976991[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.8378[/C][C]1.16222[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.7122[/C][C]-1.71223[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.7604[/C][C]1.23965[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7717[/C][C]0.228293[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.2329[/C][C]1.7671[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.0021[/C][C]-0.00211891[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.1714[/C][C]0.828648[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]15.9384[/C][C]0.0615863[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]14.8625[/C][C]2.13755[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.5285[/C][C]-1.52847[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.6142[/C][C]-2.61417[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.2763[/C][C]1.72371[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.9507[/C][C]-1.95069[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]12.9925[/C][C]1.00755[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7861[/C][C]-1.78609[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5139[/C][C]0.486094[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.3732[/C][C]-1.3732[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.407[/C][C]0.593016[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.8999[/C][C]-2.8999[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]17.0741[/C][C]-1.07415[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.9986[/C][C]-0.9986[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.9218[/C][C]-0.921842[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.7499[/C][C]0.250111[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.7671[/C][C]1.23288[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]14.0038[/C][C]0.996171[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.7454[/C][C]-2.74539[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9018[/C][C]2.09816[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.4897[/C][C]-3.48968[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4846[/C][C]2.51542[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.1316[/C][C]-2.1316[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.6891[/C][C]-1.68912[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.1344[/C][C]-0.134404[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]11.8792[/C][C]1.1208[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.5407[/C][C]0.45925[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.3641[/C][C]-2.36411[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]12.9949[/C][C]-0.994898[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.2797[/C][C]-2.27972[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8709[/C][C]3.12909[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.5771[/C][C]1.42285[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]17.0125[/C][C]-0.0125121[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.2174[/C][C]1.78261[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.3072[/C][C]-3.30715[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.7106[/C][C]2.28939[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.0579[/C][C]-2.05791[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.92[/C][C]1.08005[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.6374[/C][C]0.362604[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.8778[/C][C]-2.87784[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]16.1546[/C][C]-1.15459[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.9923[/C][C]2.00768[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.704[/C][C]4.29603[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.2496[/C][C]1.75037[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.31[/C][C]-2.31[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.8324[/C][C]0.167643[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.5692[/C][C]1.43078[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]14.0038[/C][C]0.996171[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.6714[/C][C]1.32856[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.5729[/C][C]-0.572865[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6004[/C][C]0.399634[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.4658[/C][C]0.53418[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.3875[/C][C]-0.387502[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.5729[/C][C]0.427139[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.6723[/C][C]1.32773[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.42[/C][C]-1.42001[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.469[/C][C]-0.469003[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.2908[/C][C]-3.29077[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.8481[/C][C]-1.84814[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.4305[/C][C]1.56946[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.3648[/C][C]1.63517[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.7058[/C][C]0.294166[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.9886[/C][C]-1.98855[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.3116[/C][C]-2.31157[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]15.2883[/C][C]-3.28832[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.7443[/C][C]0.255742[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.2633[/C][C]-0.263253[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6874[/C][C]-0.687392[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]14.0621[/C][C]-0.0621132[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.4761[/C][C]-1.47606[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.4345[/C][C]0.565534[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.5219[/C][C]-0.521893[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]17.1607[/C][C]1.83932[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.5206[/C][C]-0.520605[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.7659[/C][C]-6.76587[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.9674[/C][C]1.0326[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.7473[/C][C]2.25265[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.5412[/C][C]-0.541216[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.5268[/C][C]-0.526795[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.2987[/C][C]0.701278[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]15.0452[/C][C]-1.04517[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.855[/C][C]0.14497[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.65733[/C][C]2.34267[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.3006[/C][C]1.69936[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.9156[/C][C]-0.915634[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15.3689[/C][C]-0.368886[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]13.0975[/C][C]2.90255[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.3125[/C][C]0.687545[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4873[/C][C]1.51273[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.7703[/C][C]1.22968[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]14.1954[/C][C]1.80463[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.565[/C][C]0.434985[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.7618[/C][C]-2.76184[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.9168[/C][C]-2.91683[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.9695[/C][C]2.03052[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.8367[/C][C]0.163265[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.8469[/C][C]1.15311[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]15.4339[/C][C]0.566116[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.9167[/C][C]-2.91665[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]14.3027[/C][C]0.697331[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.5076[/C][C]-2.50756[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]16.2896[/C][C]-4.28958[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.3086[/C][C]0.691391[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.1674[/C][C]2.83261[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.8831[/C][C]1.11688[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.4206[/C][C]0.579371[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]15.0623[/C][C]1.93773[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.3277[/C][C]-0.327702[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.9898[/C][C]1.01017[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.6156[/C][C]-0.615582[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]15.0226[/C][C]-2.0226[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.5732[/C][C]-0.573189[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.5663[/C][C]0.433735[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.4586[/C][C]-1.45857[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.8039[/C][C]0.196122[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.9665[/C][C]-3.9665[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]14.3096[/C][C]-0.309628[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]13.2737[/C][C]0.726256[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.3428[/C][C]-1.34276[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]13.161[/C][C]-1.16104[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.4797[/C][C]1.52034[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.4652[/C][C]-3.46518[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.7007[/C][C]4.29935[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]16.4557[/C][C]1.54433[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]14.3054[/C][C]-1.30542[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.6549[/C][C]-2.6549[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]11.1695[/C][C]-7.16952[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.8156[/C][C]-1.81562[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.5926[/C][C]1.40735[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.9287[/C][C]-1.92871[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.407[/C][C]-0.406995[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.7958[/C][C]-1.79576[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.88593[/C][C]1.11407[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]11.2766[/C][C]1.72336[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]14.0922[/C][C]0.907782[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]12.0462[/C][C]-0.0461519[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]13.1537[/C][C]0.846312[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.8898[/C][C]-2.88977[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.8006[/C][C]1.19942[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.8837[/C][C]0.116305[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]12.1375[/C][C]-1.13747[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.8615[/C][C]-1.86154[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.6631[/C][C]0.336903[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]13.1781[/C][C]2.8219[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.715[/C][C]-1.71499[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]14.2641[/C][C]-0.264075[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.6806[/C][C]1.31938[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.8238[/C][C]2.17619[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.7814[/C][C]-1.78137[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.48339[/C][C]-5.48339[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]14.1744[/C][C]0.825633[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]15.5502[/C][C]-4.55021[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.4713[/C][C]-0.471302[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.1671[/C][C]0.832904[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221814&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221814&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.7173-2.7173
21615.30420.695769
31916.53452.46546
41511.24323.75684
51415.8887-1.88874
61314.3419-1.3419
71914.83784.16219
81516.6569-1.65688
91415.6145-1.61447
101513.83961.16041
111614.52421.47581
121615.96170.0383365
131614.96561.03443
141615.13060.869402
151717.7264-0.72637
161515.0074-0.00743243
171514.0330.96704
182016.03923.96081
191815.09462.90543
201615.18620.813809
211615.00150.998453
221614.5841.41598
231916.22732.7727
241614.63861.3614
251715.84121.15879
261715.83491.16507
271614.52911.47092
281516.4169-1.41688
291615.29510.704944
301413.61760.382379
311515.3672-0.367181
321212.1577-0.157712
331414.4669-0.466905
341615.5490.45103
351415.1517-1.15172
361012.4548-2.45483
371012.2904-2.29039
381415.4428-1.4428
391614.11231.88768
401614.05051.9495
411614.361.64003
421415.4125-1.41247
432017.49822.5018
441413.73820.261805
451414.139-0.138973
461115.1507-4.1507
471416.4196-2.41962
481514.78120.218844
491615.1910.809032
501415.3616-1.36158
511616.8539-0.853874
521413.73140.268554
531214.6136-2.61363
541615.59120.408809
55910.7137-1.71371
561411.85182.14823
571615.69350.306532
581615.23070.769349
591514.82320.176781
601613.79312.20694
611210.83651.1635
621615.43780.562221
631616.2991-0.299105
641414.439-0.438987
651615.15020.849824
661715.74411.25586
671816.09041.90962
681814.07643.92363
691215.8085-3.8085
701615.47270.527328
711013.0122-3.01222
721414.7156-0.715555
731816.83771.16227
741817.1930.806953
751615.00930.99069
761713.08953.91049
771616.407-0.407049
781614.2121.78803
791314.9612-1.96119
801615.08370.916264
811615.53590.464083
821615.64350.356482
831515.62-0.619965
841514.6860.313978
851613.88252.11753
861413.95150.0485269
871615.23310.766868
881614.68141.31861
891514.1030.897019
901213.6429-1.64292
911716.83240.167643
921615.72930.270747
931514.90520.094776
941314.856-1.85596
951614.69771.30228
961615.6960.303995
971613.48312.51694
981615.82970.170286
991414.2661-0.266066
1001617.194-1.19403
1011614.50571.49434
1022017.57892.42112
1031514.0230.976991
1041614.83781.16222
1051314.7122-1.71223
1061715.76041.23965
1071615.77170.228293
1081614.23291.7671
1091212.0021-0.00211891
1101615.17140.828648
1111615.93840.0615863
1121714.86252.13755
1131314.5285-1.52847
1141214.6142-2.61417
1151816.27631.72371
1161415.9507-1.95069
1171412.99251.00755
1181314.7861-1.78609
1191615.51390.486094
1201314.3732-1.3732
1211615.4070.593016
1221315.8999-2.8999
1231617.0741-1.07415
1241515.9986-0.9986
1251616.9218-0.921842
1261514.74990.250111
1271715.76711.23288
1281514.00380.996171
1291214.7454-2.74539
1301613.90182.09816
1311013.4897-3.48968
1321613.48462.51542
1331214.1316-2.1316
1341415.6891-1.68912
1351515.1344-0.134404
1361311.87921.1208
1371514.54070.45925
1381113.3641-2.36411
1391212.9949-0.994898
1401113.2797-2.27972
1411612.87093.12909
1421513.57711.42285
1431717.0125-0.0125121
1441614.21741.78261
1451013.3072-3.30715
1461815.71062.28939
1471315.0579-2.05791
1481614.921.08005
1491312.63740.362604
1501012.8778-2.87784
1511516.1546-1.15459
1521613.99232.00768
1531611.7044.29603
1541412.24961.75037
1551012.31-2.31
1561716.83240.167643
1571311.56921.43078
1581514.00380.996171
1591614.67141.32856
1601212.5729-0.572865
1611312.60040.399634
1621312.46580.53418
1631212.3875-0.387502
1641716.57290.427139
1651513.67231.32773
1661011.42-1.42001
1671414.469-0.469003
1681114.2908-3.29077
1691314.8481-1.84814
1701614.43051.56946
1711210.36481.63517
1721615.70580.294166
1731213.9886-1.98855
174911.3116-2.31157
1751215.2883-3.28832
1761514.74430.255742
1771212.2633-0.263253
1781212.6874-0.687392
1791414.0621-0.0621132
1801213.4761-1.47606
1811615.43450.565534
1821111.5219-0.521893
1831917.16071.83932
1841515.5206-0.520605
185814.7659-6.76587
1861614.96741.0326
1871714.74732.25265
1881212.5412-0.541216
1891111.5268-0.526795
1901110.29870.701278
1911415.0452-1.04517
1921615.8550.14497
193129.657332.34267
1941614.30061.69936
1951313.9156-0.915634
1961515.3689-0.368886
1971613.09752.90255
1981615.31250.687545
1991412.48731.51273
2001614.77031.22968
2011614.19541.80463
2021413.5650.434985
2031113.7618-2.76184
2041214.9168-2.91683
2051512.96952.03052
2061514.83670.163265
2071614.84691.15311
2081615.43390.566116
2091113.9167-2.91665
2101514.30270.697331
2111214.5076-2.50756
2121216.2896-4.28958
2131514.30860.691391
2141512.16742.83261
2151614.88311.11688
2161413.42060.579371
2171715.06231.93773
2181414.3277-0.327702
2191311.98981.01017
2201515.6156-0.615582
2211315.0226-2.0226
2221414.5732-0.573189
2231514.56630.433735
2241213.4586-1.45857
2251312.80390.196122
226811.9665-3.9665
2271414.3096-0.309628
2281413.27370.726256
2291112.3428-1.34276
2301213.161-1.16104
2311311.47971.52034
2321013.4652-3.46518
2331611.70074.29935
2341816.45571.54433
2351314.3054-1.30542
2361113.6549-2.6549
237411.1695-7.16952
2381314.8156-1.81562
2391614.59261.40735
2401011.9287-1.92871
2411212.407-0.406995
2421213.7958-1.79576
243108.885931.11407
2441311.27661.72336
2451514.09220.907782
2461212.0462-0.0461519
2471413.15370.846312
2481012.8898-2.88977
2491210.80061.19942
2501211.88370.116305
2511112.1375-1.13747
2521011.8615-1.86154
2531211.66310.336903
2541613.17812.8219
2551213.715-1.71499
2561414.2641-0.264075
2571614.68061.31938
2581411.82382.17619
2591314.7814-1.78137
26049.48339-5.48339
2611514.17440.825633
2621115.5502-4.55021
2631111.4713-0.471302
2641413.16710.832904






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.2344540.4689080.765546
120.1202970.2405930.879703
130.08155670.1631130.918443
140.1028780.2057570.897122
150.05875430.1175090.941246
160.03917040.07834090.96083
170.06302220.1260440.936978
180.2558770.5117540.744123
190.1942260.3884520.805774
200.1377730.2755450.862227
210.09861240.1972250.901388
220.09685940.1937190.903141
230.2570650.514130.742935
240.3215060.6430130.678494
250.2948810.5897630.705119
260.2774580.5549160.722542
270.3521120.7042240.647888
280.3638630.7277260.636137
290.34680.6935990.6532
300.3809130.7618250.619087
310.3286890.6573790.671311
320.2895060.5790120.710494
330.2625030.5250070.737497
340.2263160.4526320.773684
350.1878910.3757810.812109
360.3049450.6098890.695055
370.3349840.6699680.665016
380.3259770.6519530.674023
390.3560380.7120750.643962
400.3342220.6684440.665778
410.2980120.5960240.701988
420.2638440.5276880.736156
430.2782780.5565560.721722
440.236540.4730790.76346
450.2144450.428890.785555
460.3926970.7853940.607303
470.5455310.9089380.454469
480.4965610.9931220.503439
490.483230.9664610.51677
500.4684060.9368110.531594
510.4236880.8473750.576312
520.3781850.756370.621815
530.3866170.7732340.613383
540.3697210.7394410.630279
550.360950.72190.63905
560.3389910.6779820.661009
570.2993840.5987680.700616
580.2706990.5413970.729301
590.2362450.4724910.763755
600.2421080.4842160.757892
610.2183810.4367610.781619
620.1914860.3829710.808514
630.1634940.3269880.836506
640.1377650.2755310.862235
650.1188750.2377510.881125
660.1100170.2200330.889983
670.1058130.2116270.894187
680.2226160.4452330.777384
690.3124110.6248220.687589
700.281580.563160.71842
710.3970160.7940320.602984
720.3590440.7180880.640956
730.3507980.7015970.649202
740.3353430.6706860.664657
750.3032170.6064330.696783
760.369170.7383410.63083
770.3334370.6668730.666563
780.3126420.6252840.687358
790.3256930.6513850.674307
800.2981840.5963680.701816
810.2700510.5401020.729949
820.2391680.4783370.760832
830.2148660.4297320.785134
840.1876610.3753220.812339
850.1843740.3687480.815626
860.1593620.3187230.840638
870.1401260.2802530.859874
880.1305620.2611240.869438
890.112810.225620.88719
900.1100170.2200340.889983
910.09412310.1882460.905877
920.08128190.1625640.918718
930.06902290.1380460.930977
940.07107850.1421570.928922
950.06423330.1284670.935767
960.0538240.1076480.946176
970.05947350.1189470.940527
980.04926320.09852640.950737
990.04039380.08078750.959606
1000.03534170.07068340.964658
1010.03135240.06270470.968648
1020.03690320.07380640.963097
1030.03166920.06333840.968331
1040.02859590.05719180.971404
1050.0338460.06769210.966154
1060.02974360.05948730.970256
1070.02415560.04831120.975844
1080.02403120.04806240.975969
1090.01947380.03894760.980526
1100.01593220.03186450.984068
1110.01262990.02525980.98737
1120.01305950.0261190.986941
1130.01166380.02332770.988336
1140.01674560.03349120.983254
1150.01599580.03199170.984004
1160.0153060.0306120.984694
1170.01266140.02532280.987339
1180.01263820.02527650.987362
1190.01027510.02055020.989725
1200.009050320.01810060.99095
1210.00736390.01472780.992636
1220.01133130.02266260.988669
1230.009547080.01909420.990453
1240.008480390.01696080.99152
1250.006941240.01388250.993059
1260.005654640.01130930.994345
1270.005091280.01018260.994909
1280.004102210.008204430.995898
1290.006053680.01210740.993946
1300.006560280.01312060.99344
1310.01355550.0271110.986444
1320.01632150.03264310.983678
1330.01760620.03521240.982394
1340.01700580.03401160.982994
1350.01389920.02779830.986101
1360.01172810.02345610.988272
1370.00938760.01877520.990612
1380.0114310.0228620.988569
1390.009947720.01989540.990052
1400.01130140.02260290.988699
1410.01753490.03506980.982465
1420.0159480.03189610.984052
1430.01269890.02539780.987301
1440.01346340.02692680.986537
1450.02565640.05131290.974344
1460.03143770.06287540.968562
1470.03299860.06599730.967001
1480.02979220.05958440.970208
1490.02482850.0496570.975172
1500.03444650.06889290.965554
1510.02972220.05944450.970278
1520.03129680.06259360.968703
1530.06394010.127880.93606
1540.06282270.1256450.937177
1550.07223020.144460.92777
1560.06179630.1235930.938204
1570.05521390.1104280.944786
1580.04831790.09663570.951682
1590.04727620.09455230.952724
1600.04053550.0810710.959464
1610.03344860.06689720.966551
1620.02749750.0549950.972502
1630.02289880.04579760.977101
1640.01931550.0386310.980684
1650.01695320.03390650.983047
1660.01720190.03440370.982798
1670.01382150.02764290.986179
1680.02038720.04077430.979613
1690.02020470.04040930.979795
1700.01887090.03774180.981129
1710.01814830.03629660.981852
1720.01470530.02941060.985295
1730.01475050.0295010.985249
1740.01642860.03285730.983571
1750.0219560.0439120.978044
1760.01765890.03531780.982341
1770.01438690.02877370.985613
1780.01174580.02349160.988254
1790.009194540.01838910.990805
1800.008006690.01601340.991993
1810.006604640.01320930.993395
1820.005345520.0106910.994654
1830.005609450.01121890.994391
1840.004436430.008872860.995564
1850.09406080.1881220.905939
1860.08166580.1633320.918334
1870.09282760.1856550.907172
1880.08019420.1603880.919806
1890.06794280.1358860.932057
1900.05634290.1126860.943657
1910.04969930.09939860.950301
1920.04195090.08390180.958049
1930.04870950.09741910.95129
1940.05228250.1045650.947718
1950.04437450.08874910.955625
1960.03702080.07404150.962979
1970.04831330.09662650.951687
1980.03958480.07916950.960415
1990.03670030.07340060.9633
2000.03104020.06208040.96896
2010.02922250.05844510.970777
2020.02438160.04876310.975618
2030.03130460.06260920.968695
2040.03568040.07136090.96432
2050.0389080.07781590.961092
2060.03088050.0617610.969119
2070.03034380.06068770.969656
2080.0249510.04990210.975049
2090.02786860.05573720.972131
2100.02254240.04508490.977458
2110.02497830.04995660.975022
2120.03997410.07994820.960026
2130.03158780.06317570.968412
2140.04416240.08832490.955838
2150.03806240.07612470.961938
2160.02975350.0595070.970246
2170.03219920.06439850.967801
2180.02753240.05506480.972468
2190.02474450.0494890.975255
2200.01896550.0379310.981035
2210.01689620.03379250.983104
2220.01242180.02484350.987578
2230.009312620.01862520.990687
2240.00750260.01500520.992497
2250.006547480.0130950.993453
2260.01499480.02998960.985005
2270.01154130.02308260.988459
2280.008350130.01670030.99165
2290.006096590.01219320.993903
2300.004410140.008820270.99559
2310.004394480.008788970.995606
2320.008144730.01628950.991855
2330.03775670.07551340.962243
2340.05429420.1085880.945706
2350.04050630.08101250.959494
2360.03610940.07221870.963891
2370.2464920.4929830.753508
2380.2007720.4015430.799228
2390.1800340.3600690.819966
2400.1421190.2842380.857881
2410.1136990.2273980.886301
2420.09452350.1890470.905477
2430.08789690.1757940.912103
2440.1535440.3070880.846456
2450.1376250.275250.862375
2460.1101050.220210.889895
2470.07776740.1555350.922233
2480.06669170.1333830.933308
2490.06248650.1249730.937514
2500.07737850.1547570.922622
2510.0460530.0921060.953947
2520.1122810.2245620.887719
2530.2349930.4699850.765007

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.234454 & 0.468908 & 0.765546 \tabularnewline
12 & 0.120297 & 0.240593 & 0.879703 \tabularnewline
13 & 0.0815567 & 0.163113 & 0.918443 \tabularnewline
14 & 0.102878 & 0.205757 & 0.897122 \tabularnewline
15 & 0.0587543 & 0.117509 & 0.941246 \tabularnewline
16 & 0.0391704 & 0.0783409 & 0.96083 \tabularnewline
17 & 0.0630222 & 0.126044 & 0.936978 \tabularnewline
18 & 0.255877 & 0.511754 & 0.744123 \tabularnewline
19 & 0.194226 & 0.388452 & 0.805774 \tabularnewline
20 & 0.137773 & 0.275545 & 0.862227 \tabularnewline
21 & 0.0986124 & 0.197225 & 0.901388 \tabularnewline
22 & 0.0968594 & 0.193719 & 0.903141 \tabularnewline
23 & 0.257065 & 0.51413 & 0.742935 \tabularnewline
24 & 0.321506 & 0.643013 & 0.678494 \tabularnewline
25 & 0.294881 & 0.589763 & 0.705119 \tabularnewline
26 & 0.277458 & 0.554916 & 0.722542 \tabularnewline
27 & 0.352112 & 0.704224 & 0.647888 \tabularnewline
28 & 0.363863 & 0.727726 & 0.636137 \tabularnewline
29 & 0.3468 & 0.693599 & 0.6532 \tabularnewline
30 & 0.380913 & 0.761825 & 0.619087 \tabularnewline
31 & 0.328689 & 0.657379 & 0.671311 \tabularnewline
32 & 0.289506 & 0.579012 & 0.710494 \tabularnewline
33 & 0.262503 & 0.525007 & 0.737497 \tabularnewline
34 & 0.226316 & 0.452632 & 0.773684 \tabularnewline
35 & 0.187891 & 0.375781 & 0.812109 \tabularnewline
36 & 0.304945 & 0.609889 & 0.695055 \tabularnewline
37 & 0.334984 & 0.669968 & 0.665016 \tabularnewline
38 & 0.325977 & 0.651953 & 0.674023 \tabularnewline
39 & 0.356038 & 0.712075 & 0.643962 \tabularnewline
40 & 0.334222 & 0.668444 & 0.665778 \tabularnewline
41 & 0.298012 & 0.596024 & 0.701988 \tabularnewline
42 & 0.263844 & 0.527688 & 0.736156 \tabularnewline
43 & 0.278278 & 0.556556 & 0.721722 \tabularnewline
44 & 0.23654 & 0.473079 & 0.76346 \tabularnewline
45 & 0.214445 & 0.42889 & 0.785555 \tabularnewline
46 & 0.392697 & 0.785394 & 0.607303 \tabularnewline
47 & 0.545531 & 0.908938 & 0.454469 \tabularnewline
48 & 0.496561 & 0.993122 & 0.503439 \tabularnewline
49 & 0.48323 & 0.966461 & 0.51677 \tabularnewline
50 & 0.468406 & 0.936811 & 0.531594 \tabularnewline
51 & 0.423688 & 0.847375 & 0.576312 \tabularnewline
52 & 0.378185 & 0.75637 & 0.621815 \tabularnewline
53 & 0.386617 & 0.773234 & 0.613383 \tabularnewline
54 & 0.369721 & 0.739441 & 0.630279 \tabularnewline
55 & 0.36095 & 0.7219 & 0.63905 \tabularnewline
56 & 0.338991 & 0.677982 & 0.661009 \tabularnewline
57 & 0.299384 & 0.598768 & 0.700616 \tabularnewline
58 & 0.270699 & 0.541397 & 0.729301 \tabularnewline
59 & 0.236245 & 0.472491 & 0.763755 \tabularnewline
60 & 0.242108 & 0.484216 & 0.757892 \tabularnewline
61 & 0.218381 & 0.436761 & 0.781619 \tabularnewline
62 & 0.191486 & 0.382971 & 0.808514 \tabularnewline
63 & 0.163494 & 0.326988 & 0.836506 \tabularnewline
64 & 0.137765 & 0.275531 & 0.862235 \tabularnewline
65 & 0.118875 & 0.237751 & 0.881125 \tabularnewline
66 & 0.110017 & 0.220033 & 0.889983 \tabularnewline
67 & 0.105813 & 0.211627 & 0.894187 \tabularnewline
68 & 0.222616 & 0.445233 & 0.777384 \tabularnewline
69 & 0.312411 & 0.624822 & 0.687589 \tabularnewline
70 & 0.28158 & 0.56316 & 0.71842 \tabularnewline
71 & 0.397016 & 0.794032 & 0.602984 \tabularnewline
72 & 0.359044 & 0.718088 & 0.640956 \tabularnewline
73 & 0.350798 & 0.701597 & 0.649202 \tabularnewline
74 & 0.335343 & 0.670686 & 0.664657 \tabularnewline
75 & 0.303217 & 0.606433 & 0.696783 \tabularnewline
76 & 0.36917 & 0.738341 & 0.63083 \tabularnewline
77 & 0.333437 & 0.666873 & 0.666563 \tabularnewline
78 & 0.312642 & 0.625284 & 0.687358 \tabularnewline
79 & 0.325693 & 0.651385 & 0.674307 \tabularnewline
80 & 0.298184 & 0.596368 & 0.701816 \tabularnewline
81 & 0.270051 & 0.540102 & 0.729949 \tabularnewline
82 & 0.239168 & 0.478337 & 0.760832 \tabularnewline
83 & 0.214866 & 0.429732 & 0.785134 \tabularnewline
84 & 0.187661 & 0.375322 & 0.812339 \tabularnewline
85 & 0.184374 & 0.368748 & 0.815626 \tabularnewline
86 & 0.159362 & 0.318723 & 0.840638 \tabularnewline
87 & 0.140126 & 0.280253 & 0.859874 \tabularnewline
88 & 0.130562 & 0.261124 & 0.869438 \tabularnewline
89 & 0.11281 & 0.22562 & 0.88719 \tabularnewline
90 & 0.110017 & 0.220034 & 0.889983 \tabularnewline
91 & 0.0941231 & 0.188246 & 0.905877 \tabularnewline
92 & 0.0812819 & 0.162564 & 0.918718 \tabularnewline
93 & 0.0690229 & 0.138046 & 0.930977 \tabularnewline
94 & 0.0710785 & 0.142157 & 0.928922 \tabularnewline
95 & 0.0642333 & 0.128467 & 0.935767 \tabularnewline
96 & 0.053824 & 0.107648 & 0.946176 \tabularnewline
97 & 0.0594735 & 0.118947 & 0.940527 \tabularnewline
98 & 0.0492632 & 0.0985264 & 0.950737 \tabularnewline
99 & 0.0403938 & 0.0807875 & 0.959606 \tabularnewline
100 & 0.0353417 & 0.0706834 & 0.964658 \tabularnewline
101 & 0.0313524 & 0.0627047 & 0.968648 \tabularnewline
102 & 0.0369032 & 0.0738064 & 0.963097 \tabularnewline
103 & 0.0316692 & 0.0633384 & 0.968331 \tabularnewline
104 & 0.0285959 & 0.0571918 & 0.971404 \tabularnewline
105 & 0.033846 & 0.0676921 & 0.966154 \tabularnewline
106 & 0.0297436 & 0.0594873 & 0.970256 \tabularnewline
107 & 0.0241556 & 0.0483112 & 0.975844 \tabularnewline
108 & 0.0240312 & 0.0480624 & 0.975969 \tabularnewline
109 & 0.0194738 & 0.0389476 & 0.980526 \tabularnewline
110 & 0.0159322 & 0.0318645 & 0.984068 \tabularnewline
111 & 0.0126299 & 0.0252598 & 0.98737 \tabularnewline
112 & 0.0130595 & 0.026119 & 0.986941 \tabularnewline
113 & 0.0116638 & 0.0233277 & 0.988336 \tabularnewline
114 & 0.0167456 & 0.0334912 & 0.983254 \tabularnewline
115 & 0.0159958 & 0.0319917 & 0.984004 \tabularnewline
116 & 0.015306 & 0.030612 & 0.984694 \tabularnewline
117 & 0.0126614 & 0.0253228 & 0.987339 \tabularnewline
118 & 0.0126382 & 0.0252765 & 0.987362 \tabularnewline
119 & 0.0102751 & 0.0205502 & 0.989725 \tabularnewline
120 & 0.00905032 & 0.0181006 & 0.99095 \tabularnewline
121 & 0.0073639 & 0.0147278 & 0.992636 \tabularnewline
122 & 0.0113313 & 0.0226626 & 0.988669 \tabularnewline
123 & 0.00954708 & 0.0190942 & 0.990453 \tabularnewline
124 & 0.00848039 & 0.0169608 & 0.99152 \tabularnewline
125 & 0.00694124 & 0.0138825 & 0.993059 \tabularnewline
126 & 0.00565464 & 0.0113093 & 0.994345 \tabularnewline
127 & 0.00509128 & 0.0101826 & 0.994909 \tabularnewline
128 & 0.00410221 & 0.00820443 & 0.995898 \tabularnewline
129 & 0.00605368 & 0.0121074 & 0.993946 \tabularnewline
130 & 0.00656028 & 0.0131206 & 0.99344 \tabularnewline
131 & 0.0135555 & 0.027111 & 0.986444 \tabularnewline
132 & 0.0163215 & 0.0326431 & 0.983678 \tabularnewline
133 & 0.0176062 & 0.0352124 & 0.982394 \tabularnewline
134 & 0.0170058 & 0.0340116 & 0.982994 \tabularnewline
135 & 0.0138992 & 0.0277983 & 0.986101 \tabularnewline
136 & 0.0117281 & 0.0234561 & 0.988272 \tabularnewline
137 & 0.0093876 & 0.0187752 & 0.990612 \tabularnewline
138 & 0.011431 & 0.022862 & 0.988569 \tabularnewline
139 & 0.00994772 & 0.0198954 & 0.990052 \tabularnewline
140 & 0.0113014 & 0.0226029 & 0.988699 \tabularnewline
141 & 0.0175349 & 0.0350698 & 0.982465 \tabularnewline
142 & 0.015948 & 0.0318961 & 0.984052 \tabularnewline
143 & 0.0126989 & 0.0253978 & 0.987301 \tabularnewline
144 & 0.0134634 & 0.0269268 & 0.986537 \tabularnewline
145 & 0.0256564 & 0.0513129 & 0.974344 \tabularnewline
146 & 0.0314377 & 0.0628754 & 0.968562 \tabularnewline
147 & 0.0329986 & 0.0659973 & 0.967001 \tabularnewline
148 & 0.0297922 & 0.0595844 & 0.970208 \tabularnewline
149 & 0.0248285 & 0.049657 & 0.975172 \tabularnewline
150 & 0.0344465 & 0.0688929 & 0.965554 \tabularnewline
151 & 0.0297222 & 0.0594445 & 0.970278 \tabularnewline
152 & 0.0312968 & 0.0625936 & 0.968703 \tabularnewline
153 & 0.0639401 & 0.12788 & 0.93606 \tabularnewline
154 & 0.0628227 & 0.125645 & 0.937177 \tabularnewline
155 & 0.0722302 & 0.14446 & 0.92777 \tabularnewline
156 & 0.0617963 & 0.123593 & 0.938204 \tabularnewline
157 & 0.0552139 & 0.110428 & 0.944786 \tabularnewline
158 & 0.0483179 & 0.0966357 & 0.951682 \tabularnewline
159 & 0.0472762 & 0.0945523 & 0.952724 \tabularnewline
160 & 0.0405355 & 0.081071 & 0.959464 \tabularnewline
161 & 0.0334486 & 0.0668972 & 0.966551 \tabularnewline
162 & 0.0274975 & 0.054995 & 0.972502 \tabularnewline
163 & 0.0228988 & 0.0457976 & 0.977101 \tabularnewline
164 & 0.0193155 & 0.038631 & 0.980684 \tabularnewline
165 & 0.0169532 & 0.0339065 & 0.983047 \tabularnewline
166 & 0.0172019 & 0.0344037 & 0.982798 \tabularnewline
167 & 0.0138215 & 0.0276429 & 0.986179 \tabularnewline
168 & 0.0203872 & 0.0407743 & 0.979613 \tabularnewline
169 & 0.0202047 & 0.0404093 & 0.979795 \tabularnewline
170 & 0.0188709 & 0.0377418 & 0.981129 \tabularnewline
171 & 0.0181483 & 0.0362966 & 0.981852 \tabularnewline
172 & 0.0147053 & 0.0294106 & 0.985295 \tabularnewline
173 & 0.0147505 & 0.029501 & 0.985249 \tabularnewline
174 & 0.0164286 & 0.0328573 & 0.983571 \tabularnewline
175 & 0.021956 & 0.043912 & 0.978044 \tabularnewline
176 & 0.0176589 & 0.0353178 & 0.982341 \tabularnewline
177 & 0.0143869 & 0.0287737 & 0.985613 \tabularnewline
178 & 0.0117458 & 0.0234916 & 0.988254 \tabularnewline
179 & 0.00919454 & 0.0183891 & 0.990805 \tabularnewline
180 & 0.00800669 & 0.0160134 & 0.991993 \tabularnewline
181 & 0.00660464 & 0.0132093 & 0.993395 \tabularnewline
182 & 0.00534552 & 0.010691 & 0.994654 \tabularnewline
183 & 0.00560945 & 0.0112189 & 0.994391 \tabularnewline
184 & 0.00443643 & 0.00887286 & 0.995564 \tabularnewline
185 & 0.0940608 & 0.188122 & 0.905939 \tabularnewline
186 & 0.0816658 & 0.163332 & 0.918334 \tabularnewline
187 & 0.0928276 & 0.185655 & 0.907172 \tabularnewline
188 & 0.0801942 & 0.160388 & 0.919806 \tabularnewline
189 & 0.0679428 & 0.135886 & 0.932057 \tabularnewline
190 & 0.0563429 & 0.112686 & 0.943657 \tabularnewline
191 & 0.0496993 & 0.0993986 & 0.950301 \tabularnewline
192 & 0.0419509 & 0.0839018 & 0.958049 \tabularnewline
193 & 0.0487095 & 0.0974191 & 0.95129 \tabularnewline
194 & 0.0522825 & 0.104565 & 0.947718 \tabularnewline
195 & 0.0443745 & 0.0887491 & 0.955625 \tabularnewline
196 & 0.0370208 & 0.0740415 & 0.962979 \tabularnewline
197 & 0.0483133 & 0.0966265 & 0.951687 \tabularnewline
198 & 0.0395848 & 0.0791695 & 0.960415 \tabularnewline
199 & 0.0367003 & 0.0734006 & 0.9633 \tabularnewline
200 & 0.0310402 & 0.0620804 & 0.96896 \tabularnewline
201 & 0.0292225 & 0.0584451 & 0.970777 \tabularnewline
202 & 0.0243816 & 0.0487631 & 0.975618 \tabularnewline
203 & 0.0313046 & 0.0626092 & 0.968695 \tabularnewline
204 & 0.0356804 & 0.0713609 & 0.96432 \tabularnewline
205 & 0.038908 & 0.0778159 & 0.961092 \tabularnewline
206 & 0.0308805 & 0.061761 & 0.969119 \tabularnewline
207 & 0.0303438 & 0.0606877 & 0.969656 \tabularnewline
208 & 0.024951 & 0.0499021 & 0.975049 \tabularnewline
209 & 0.0278686 & 0.0557372 & 0.972131 \tabularnewline
210 & 0.0225424 & 0.0450849 & 0.977458 \tabularnewline
211 & 0.0249783 & 0.0499566 & 0.975022 \tabularnewline
212 & 0.0399741 & 0.0799482 & 0.960026 \tabularnewline
213 & 0.0315878 & 0.0631757 & 0.968412 \tabularnewline
214 & 0.0441624 & 0.0883249 & 0.955838 \tabularnewline
215 & 0.0380624 & 0.0761247 & 0.961938 \tabularnewline
216 & 0.0297535 & 0.059507 & 0.970246 \tabularnewline
217 & 0.0321992 & 0.0643985 & 0.967801 \tabularnewline
218 & 0.0275324 & 0.0550648 & 0.972468 \tabularnewline
219 & 0.0247445 & 0.049489 & 0.975255 \tabularnewline
220 & 0.0189655 & 0.037931 & 0.981035 \tabularnewline
221 & 0.0168962 & 0.0337925 & 0.983104 \tabularnewline
222 & 0.0124218 & 0.0248435 & 0.987578 \tabularnewline
223 & 0.00931262 & 0.0186252 & 0.990687 \tabularnewline
224 & 0.0075026 & 0.0150052 & 0.992497 \tabularnewline
225 & 0.00654748 & 0.013095 & 0.993453 \tabularnewline
226 & 0.0149948 & 0.0299896 & 0.985005 \tabularnewline
227 & 0.0115413 & 0.0230826 & 0.988459 \tabularnewline
228 & 0.00835013 & 0.0167003 & 0.99165 \tabularnewline
229 & 0.00609659 & 0.0121932 & 0.993903 \tabularnewline
230 & 0.00441014 & 0.00882027 & 0.99559 \tabularnewline
231 & 0.00439448 & 0.00878897 & 0.995606 \tabularnewline
232 & 0.00814473 & 0.0162895 & 0.991855 \tabularnewline
233 & 0.0377567 & 0.0755134 & 0.962243 \tabularnewline
234 & 0.0542942 & 0.108588 & 0.945706 \tabularnewline
235 & 0.0405063 & 0.0810125 & 0.959494 \tabularnewline
236 & 0.0361094 & 0.0722187 & 0.963891 \tabularnewline
237 & 0.246492 & 0.492983 & 0.753508 \tabularnewline
238 & 0.200772 & 0.401543 & 0.799228 \tabularnewline
239 & 0.180034 & 0.360069 & 0.819966 \tabularnewline
240 & 0.142119 & 0.284238 & 0.857881 \tabularnewline
241 & 0.113699 & 0.227398 & 0.886301 \tabularnewline
242 & 0.0945235 & 0.189047 & 0.905477 \tabularnewline
243 & 0.0878969 & 0.175794 & 0.912103 \tabularnewline
244 & 0.153544 & 0.307088 & 0.846456 \tabularnewline
245 & 0.137625 & 0.27525 & 0.862375 \tabularnewline
246 & 0.110105 & 0.22021 & 0.889895 \tabularnewline
247 & 0.0777674 & 0.155535 & 0.922233 \tabularnewline
248 & 0.0666917 & 0.133383 & 0.933308 \tabularnewline
249 & 0.0624865 & 0.124973 & 0.937514 \tabularnewline
250 & 0.0773785 & 0.154757 & 0.922622 \tabularnewline
251 & 0.046053 & 0.092106 & 0.953947 \tabularnewline
252 & 0.112281 & 0.224562 & 0.887719 \tabularnewline
253 & 0.234993 & 0.469985 & 0.765007 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221814&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.234454[/C][C]0.468908[/C][C]0.765546[/C][/ROW]
[ROW][C]12[/C][C]0.120297[/C][C]0.240593[/C][C]0.879703[/C][/ROW]
[ROW][C]13[/C][C]0.0815567[/C][C]0.163113[/C][C]0.918443[/C][/ROW]
[ROW][C]14[/C][C]0.102878[/C][C]0.205757[/C][C]0.897122[/C][/ROW]
[ROW][C]15[/C][C]0.0587543[/C][C]0.117509[/C][C]0.941246[/C][/ROW]
[ROW][C]16[/C][C]0.0391704[/C][C]0.0783409[/C][C]0.96083[/C][/ROW]
[ROW][C]17[/C][C]0.0630222[/C][C]0.126044[/C][C]0.936978[/C][/ROW]
[ROW][C]18[/C][C]0.255877[/C][C]0.511754[/C][C]0.744123[/C][/ROW]
[ROW][C]19[/C][C]0.194226[/C][C]0.388452[/C][C]0.805774[/C][/ROW]
[ROW][C]20[/C][C]0.137773[/C][C]0.275545[/C][C]0.862227[/C][/ROW]
[ROW][C]21[/C][C]0.0986124[/C][C]0.197225[/C][C]0.901388[/C][/ROW]
[ROW][C]22[/C][C]0.0968594[/C][C]0.193719[/C][C]0.903141[/C][/ROW]
[ROW][C]23[/C][C]0.257065[/C][C]0.51413[/C][C]0.742935[/C][/ROW]
[ROW][C]24[/C][C]0.321506[/C][C]0.643013[/C][C]0.678494[/C][/ROW]
[ROW][C]25[/C][C]0.294881[/C][C]0.589763[/C][C]0.705119[/C][/ROW]
[ROW][C]26[/C][C]0.277458[/C][C]0.554916[/C][C]0.722542[/C][/ROW]
[ROW][C]27[/C][C]0.352112[/C][C]0.704224[/C][C]0.647888[/C][/ROW]
[ROW][C]28[/C][C]0.363863[/C][C]0.727726[/C][C]0.636137[/C][/ROW]
[ROW][C]29[/C][C]0.3468[/C][C]0.693599[/C][C]0.6532[/C][/ROW]
[ROW][C]30[/C][C]0.380913[/C][C]0.761825[/C][C]0.619087[/C][/ROW]
[ROW][C]31[/C][C]0.328689[/C][C]0.657379[/C][C]0.671311[/C][/ROW]
[ROW][C]32[/C][C]0.289506[/C][C]0.579012[/C][C]0.710494[/C][/ROW]
[ROW][C]33[/C][C]0.262503[/C][C]0.525007[/C][C]0.737497[/C][/ROW]
[ROW][C]34[/C][C]0.226316[/C][C]0.452632[/C][C]0.773684[/C][/ROW]
[ROW][C]35[/C][C]0.187891[/C][C]0.375781[/C][C]0.812109[/C][/ROW]
[ROW][C]36[/C][C]0.304945[/C][C]0.609889[/C][C]0.695055[/C][/ROW]
[ROW][C]37[/C][C]0.334984[/C][C]0.669968[/C][C]0.665016[/C][/ROW]
[ROW][C]38[/C][C]0.325977[/C][C]0.651953[/C][C]0.674023[/C][/ROW]
[ROW][C]39[/C][C]0.356038[/C][C]0.712075[/C][C]0.643962[/C][/ROW]
[ROW][C]40[/C][C]0.334222[/C][C]0.668444[/C][C]0.665778[/C][/ROW]
[ROW][C]41[/C][C]0.298012[/C][C]0.596024[/C][C]0.701988[/C][/ROW]
[ROW][C]42[/C][C]0.263844[/C][C]0.527688[/C][C]0.736156[/C][/ROW]
[ROW][C]43[/C][C]0.278278[/C][C]0.556556[/C][C]0.721722[/C][/ROW]
[ROW][C]44[/C][C]0.23654[/C][C]0.473079[/C][C]0.76346[/C][/ROW]
[ROW][C]45[/C][C]0.214445[/C][C]0.42889[/C][C]0.785555[/C][/ROW]
[ROW][C]46[/C][C]0.392697[/C][C]0.785394[/C][C]0.607303[/C][/ROW]
[ROW][C]47[/C][C]0.545531[/C][C]0.908938[/C][C]0.454469[/C][/ROW]
[ROW][C]48[/C][C]0.496561[/C][C]0.993122[/C][C]0.503439[/C][/ROW]
[ROW][C]49[/C][C]0.48323[/C][C]0.966461[/C][C]0.51677[/C][/ROW]
[ROW][C]50[/C][C]0.468406[/C][C]0.936811[/C][C]0.531594[/C][/ROW]
[ROW][C]51[/C][C]0.423688[/C][C]0.847375[/C][C]0.576312[/C][/ROW]
[ROW][C]52[/C][C]0.378185[/C][C]0.75637[/C][C]0.621815[/C][/ROW]
[ROW][C]53[/C][C]0.386617[/C][C]0.773234[/C][C]0.613383[/C][/ROW]
[ROW][C]54[/C][C]0.369721[/C][C]0.739441[/C][C]0.630279[/C][/ROW]
[ROW][C]55[/C][C]0.36095[/C][C]0.7219[/C][C]0.63905[/C][/ROW]
[ROW][C]56[/C][C]0.338991[/C][C]0.677982[/C][C]0.661009[/C][/ROW]
[ROW][C]57[/C][C]0.299384[/C][C]0.598768[/C][C]0.700616[/C][/ROW]
[ROW][C]58[/C][C]0.270699[/C][C]0.541397[/C][C]0.729301[/C][/ROW]
[ROW][C]59[/C][C]0.236245[/C][C]0.472491[/C][C]0.763755[/C][/ROW]
[ROW][C]60[/C][C]0.242108[/C][C]0.484216[/C][C]0.757892[/C][/ROW]
[ROW][C]61[/C][C]0.218381[/C][C]0.436761[/C][C]0.781619[/C][/ROW]
[ROW][C]62[/C][C]0.191486[/C][C]0.382971[/C][C]0.808514[/C][/ROW]
[ROW][C]63[/C][C]0.163494[/C][C]0.326988[/C][C]0.836506[/C][/ROW]
[ROW][C]64[/C][C]0.137765[/C][C]0.275531[/C][C]0.862235[/C][/ROW]
[ROW][C]65[/C][C]0.118875[/C][C]0.237751[/C][C]0.881125[/C][/ROW]
[ROW][C]66[/C][C]0.110017[/C][C]0.220033[/C][C]0.889983[/C][/ROW]
[ROW][C]67[/C][C]0.105813[/C][C]0.211627[/C][C]0.894187[/C][/ROW]
[ROW][C]68[/C][C]0.222616[/C][C]0.445233[/C][C]0.777384[/C][/ROW]
[ROW][C]69[/C][C]0.312411[/C][C]0.624822[/C][C]0.687589[/C][/ROW]
[ROW][C]70[/C][C]0.28158[/C][C]0.56316[/C][C]0.71842[/C][/ROW]
[ROW][C]71[/C][C]0.397016[/C][C]0.794032[/C][C]0.602984[/C][/ROW]
[ROW][C]72[/C][C]0.359044[/C][C]0.718088[/C][C]0.640956[/C][/ROW]
[ROW][C]73[/C][C]0.350798[/C][C]0.701597[/C][C]0.649202[/C][/ROW]
[ROW][C]74[/C][C]0.335343[/C][C]0.670686[/C][C]0.664657[/C][/ROW]
[ROW][C]75[/C][C]0.303217[/C][C]0.606433[/C][C]0.696783[/C][/ROW]
[ROW][C]76[/C][C]0.36917[/C][C]0.738341[/C][C]0.63083[/C][/ROW]
[ROW][C]77[/C][C]0.333437[/C][C]0.666873[/C][C]0.666563[/C][/ROW]
[ROW][C]78[/C][C]0.312642[/C][C]0.625284[/C][C]0.687358[/C][/ROW]
[ROW][C]79[/C][C]0.325693[/C][C]0.651385[/C][C]0.674307[/C][/ROW]
[ROW][C]80[/C][C]0.298184[/C][C]0.596368[/C][C]0.701816[/C][/ROW]
[ROW][C]81[/C][C]0.270051[/C][C]0.540102[/C][C]0.729949[/C][/ROW]
[ROW][C]82[/C][C]0.239168[/C][C]0.478337[/C][C]0.760832[/C][/ROW]
[ROW][C]83[/C][C]0.214866[/C][C]0.429732[/C][C]0.785134[/C][/ROW]
[ROW][C]84[/C][C]0.187661[/C][C]0.375322[/C][C]0.812339[/C][/ROW]
[ROW][C]85[/C][C]0.184374[/C][C]0.368748[/C][C]0.815626[/C][/ROW]
[ROW][C]86[/C][C]0.159362[/C][C]0.318723[/C][C]0.840638[/C][/ROW]
[ROW][C]87[/C][C]0.140126[/C][C]0.280253[/C][C]0.859874[/C][/ROW]
[ROW][C]88[/C][C]0.130562[/C][C]0.261124[/C][C]0.869438[/C][/ROW]
[ROW][C]89[/C][C]0.11281[/C][C]0.22562[/C][C]0.88719[/C][/ROW]
[ROW][C]90[/C][C]0.110017[/C][C]0.220034[/C][C]0.889983[/C][/ROW]
[ROW][C]91[/C][C]0.0941231[/C][C]0.188246[/C][C]0.905877[/C][/ROW]
[ROW][C]92[/C][C]0.0812819[/C][C]0.162564[/C][C]0.918718[/C][/ROW]
[ROW][C]93[/C][C]0.0690229[/C][C]0.138046[/C][C]0.930977[/C][/ROW]
[ROW][C]94[/C][C]0.0710785[/C][C]0.142157[/C][C]0.928922[/C][/ROW]
[ROW][C]95[/C][C]0.0642333[/C][C]0.128467[/C][C]0.935767[/C][/ROW]
[ROW][C]96[/C][C]0.053824[/C][C]0.107648[/C][C]0.946176[/C][/ROW]
[ROW][C]97[/C][C]0.0594735[/C][C]0.118947[/C][C]0.940527[/C][/ROW]
[ROW][C]98[/C][C]0.0492632[/C][C]0.0985264[/C][C]0.950737[/C][/ROW]
[ROW][C]99[/C][C]0.0403938[/C][C]0.0807875[/C][C]0.959606[/C][/ROW]
[ROW][C]100[/C][C]0.0353417[/C][C]0.0706834[/C][C]0.964658[/C][/ROW]
[ROW][C]101[/C][C]0.0313524[/C][C]0.0627047[/C][C]0.968648[/C][/ROW]
[ROW][C]102[/C][C]0.0369032[/C][C]0.0738064[/C][C]0.963097[/C][/ROW]
[ROW][C]103[/C][C]0.0316692[/C][C]0.0633384[/C][C]0.968331[/C][/ROW]
[ROW][C]104[/C][C]0.0285959[/C][C]0.0571918[/C][C]0.971404[/C][/ROW]
[ROW][C]105[/C][C]0.033846[/C][C]0.0676921[/C][C]0.966154[/C][/ROW]
[ROW][C]106[/C][C]0.0297436[/C][C]0.0594873[/C][C]0.970256[/C][/ROW]
[ROW][C]107[/C][C]0.0241556[/C][C]0.0483112[/C][C]0.975844[/C][/ROW]
[ROW][C]108[/C][C]0.0240312[/C][C]0.0480624[/C][C]0.975969[/C][/ROW]
[ROW][C]109[/C][C]0.0194738[/C][C]0.0389476[/C][C]0.980526[/C][/ROW]
[ROW][C]110[/C][C]0.0159322[/C][C]0.0318645[/C][C]0.984068[/C][/ROW]
[ROW][C]111[/C][C]0.0126299[/C][C]0.0252598[/C][C]0.98737[/C][/ROW]
[ROW][C]112[/C][C]0.0130595[/C][C]0.026119[/C][C]0.986941[/C][/ROW]
[ROW][C]113[/C][C]0.0116638[/C][C]0.0233277[/C][C]0.988336[/C][/ROW]
[ROW][C]114[/C][C]0.0167456[/C][C]0.0334912[/C][C]0.983254[/C][/ROW]
[ROW][C]115[/C][C]0.0159958[/C][C]0.0319917[/C][C]0.984004[/C][/ROW]
[ROW][C]116[/C][C]0.015306[/C][C]0.030612[/C][C]0.984694[/C][/ROW]
[ROW][C]117[/C][C]0.0126614[/C][C]0.0253228[/C][C]0.987339[/C][/ROW]
[ROW][C]118[/C][C]0.0126382[/C][C]0.0252765[/C][C]0.987362[/C][/ROW]
[ROW][C]119[/C][C]0.0102751[/C][C]0.0205502[/C][C]0.989725[/C][/ROW]
[ROW][C]120[/C][C]0.00905032[/C][C]0.0181006[/C][C]0.99095[/C][/ROW]
[ROW][C]121[/C][C]0.0073639[/C][C]0.0147278[/C][C]0.992636[/C][/ROW]
[ROW][C]122[/C][C]0.0113313[/C][C]0.0226626[/C][C]0.988669[/C][/ROW]
[ROW][C]123[/C][C]0.00954708[/C][C]0.0190942[/C][C]0.990453[/C][/ROW]
[ROW][C]124[/C][C]0.00848039[/C][C]0.0169608[/C][C]0.99152[/C][/ROW]
[ROW][C]125[/C][C]0.00694124[/C][C]0.0138825[/C][C]0.993059[/C][/ROW]
[ROW][C]126[/C][C]0.00565464[/C][C]0.0113093[/C][C]0.994345[/C][/ROW]
[ROW][C]127[/C][C]0.00509128[/C][C]0.0101826[/C][C]0.994909[/C][/ROW]
[ROW][C]128[/C][C]0.00410221[/C][C]0.00820443[/C][C]0.995898[/C][/ROW]
[ROW][C]129[/C][C]0.00605368[/C][C]0.0121074[/C][C]0.993946[/C][/ROW]
[ROW][C]130[/C][C]0.00656028[/C][C]0.0131206[/C][C]0.99344[/C][/ROW]
[ROW][C]131[/C][C]0.0135555[/C][C]0.027111[/C][C]0.986444[/C][/ROW]
[ROW][C]132[/C][C]0.0163215[/C][C]0.0326431[/C][C]0.983678[/C][/ROW]
[ROW][C]133[/C][C]0.0176062[/C][C]0.0352124[/C][C]0.982394[/C][/ROW]
[ROW][C]134[/C][C]0.0170058[/C][C]0.0340116[/C][C]0.982994[/C][/ROW]
[ROW][C]135[/C][C]0.0138992[/C][C]0.0277983[/C][C]0.986101[/C][/ROW]
[ROW][C]136[/C][C]0.0117281[/C][C]0.0234561[/C][C]0.988272[/C][/ROW]
[ROW][C]137[/C][C]0.0093876[/C][C]0.0187752[/C][C]0.990612[/C][/ROW]
[ROW][C]138[/C][C]0.011431[/C][C]0.022862[/C][C]0.988569[/C][/ROW]
[ROW][C]139[/C][C]0.00994772[/C][C]0.0198954[/C][C]0.990052[/C][/ROW]
[ROW][C]140[/C][C]0.0113014[/C][C]0.0226029[/C][C]0.988699[/C][/ROW]
[ROW][C]141[/C][C]0.0175349[/C][C]0.0350698[/C][C]0.982465[/C][/ROW]
[ROW][C]142[/C][C]0.015948[/C][C]0.0318961[/C][C]0.984052[/C][/ROW]
[ROW][C]143[/C][C]0.0126989[/C][C]0.0253978[/C][C]0.987301[/C][/ROW]
[ROW][C]144[/C][C]0.0134634[/C][C]0.0269268[/C][C]0.986537[/C][/ROW]
[ROW][C]145[/C][C]0.0256564[/C][C]0.0513129[/C][C]0.974344[/C][/ROW]
[ROW][C]146[/C][C]0.0314377[/C][C]0.0628754[/C][C]0.968562[/C][/ROW]
[ROW][C]147[/C][C]0.0329986[/C][C]0.0659973[/C][C]0.967001[/C][/ROW]
[ROW][C]148[/C][C]0.0297922[/C][C]0.0595844[/C][C]0.970208[/C][/ROW]
[ROW][C]149[/C][C]0.0248285[/C][C]0.049657[/C][C]0.975172[/C][/ROW]
[ROW][C]150[/C][C]0.0344465[/C][C]0.0688929[/C][C]0.965554[/C][/ROW]
[ROW][C]151[/C][C]0.0297222[/C][C]0.0594445[/C][C]0.970278[/C][/ROW]
[ROW][C]152[/C][C]0.0312968[/C][C]0.0625936[/C][C]0.968703[/C][/ROW]
[ROW][C]153[/C][C]0.0639401[/C][C]0.12788[/C][C]0.93606[/C][/ROW]
[ROW][C]154[/C][C]0.0628227[/C][C]0.125645[/C][C]0.937177[/C][/ROW]
[ROW][C]155[/C][C]0.0722302[/C][C]0.14446[/C][C]0.92777[/C][/ROW]
[ROW][C]156[/C][C]0.0617963[/C][C]0.123593[/C][C]0.938204[/C][/ROW]
[ROW][C]157[/C][C]0.0552139[/C][C]0.110428[/C][C]0.944786[/C][/ROW]
[ROW][C]158[/C][C]0.0483179[/C][C]0.0966357[/C][C]0.951682[/C][/ROW]
[ROW][C]159[/C][C]0.0472762[/C][C]0.0945523[/C][C]0.952724[/C][/ROW]
[ROW][C]160[/C][C]0.0405355[/C][C]0.081071[/C][C]0.959464[/C][/ROW]
[ROW][C]161[/C][C]0.0334486[/C][C]0.0668972[/C][C]0.966551[/C][/ROW]
[ROW][C]162[/C][C]0.0274975[/C][C]0.054995[/C][C]0.972502[/C][/ROW]
[ROW][C]163[/C][C]0.0228988[/C][C]0.0457976[/C][C]0.977101[/C][/ROW]
[ROW][C]164[/C][C]0.0193155[/C][C]0.038631[/C][C]0.980684[/C][/ROW]
[ROW][C]165[/C][C]0.0169532[/C][C]0.0339065[/C][C]0.983047[/C][/ROW]
[ROW][C]166[/C][C]0.0172019[/C][C]0.0344037[/C][C]0.982798[/C][/ROW]
[ROW][C]167[/C][C]0.0138215[/C][C]0.0276429[/C][C]0.986179[/C][/ROW]
[ROW][C]168[/C][C]0.0203872[/C][C]0.0407743[/C][C]0.979613[/C][/ROW]
[ROW][C]169[/C][C]0.0202047[/C][C]0.0404093[/C][C]0.979795[/C][/ROW]
[ROW][C]170[/C][C]0.0188709[/C][C]0.0377418[/C][C]0.981129[/C][/ROW]
[ROW][C]171[/C][C]0.0181483[/C][C]0.0362966[/C][C]0.981852[/C][/ROW]
[ROW][C]172[/C][C]0.0147053[/C][C]0.0294106[/C][C]0.985295[/C][/ROW]
[ROW][C]173[/C][C]0.0147505[/C][C]0.029501[/C][C]0.985249[/C][/ROW]
[ROW][C]174[/C][C]0.0164286[/C][C]0.0328573[/C][C]0.983571[/C][/ROW]
[ROW][C]175[/C][C]0.021956[/C][C]0.043912[/C][C]0.978044[/C][/ROW]
[ROW][C]176[/C][C]0.0176589[/C][C]0.0353178[/C][C]0.982341[/C][/ROW]
[ROW][C]177[/C][C]0.0143869[/C][C]0.0287737[/C][C]0.985613[/C][/ROW]
[ROW][C]178[/C][C]0.0117458[/C][C]0.0234916[/C][C]0.988254[/C][/ROW]
[ROW][C]179[/C][C]0.00919454[/C][C]0.0183891[/C][C]0.990805[/C][/ROW]
[ROW][C]180[/C][C]0.00800669[/C][C]0.0160134[/C][C]0.991993[/C][/ROW]
[ROW][C]181[/C][C]0.00660464[/C][C]0.0132093[/C][C]0.993395[/C][/ROW]
[ROW][C]182[/C][C]0.00534552[/C][C]0.010691[/C][C]0.994654[/C][/ROW]
[ROW][C]183[/C][C]0.00560945[/C][C]0.0112189[/C][C]0.994391[/C][/ROW]
[ROW][C]184[/C][C]0.00443643[/C][C]0.00887286[/C][C]0.995564[/C][/ROW]
[ROW][C]185[/C][C]0.0940608[/C][C]0.188122[/C][C]0.905939[/C][/ROW]
[ROW][C]186[/C][C]0.0816658[/C][C]0.163332[/C][C]0.918334[/C][/ROW]
[ROW][C]187[/C][C]0.0928276[/C][C]0.185655[/C][C]0.907172[/C][/ROW]
[ROW][C]188[/C][C]0.0801942[/C][C]0.160388[/C][C]0.919806[/C][/ROW]
[ROW][C]189[/C][C]0.0679428[/C][C]0.135886[/C][C]0.932057[/C][/ROW]
[ROW][C]190[/C][C]0.0563429[/C][C]0.112686[/C][C]0.943657[/C][/ROW]
[ROW][C]191[/C][C]0.0496993[/C][C]0.0993986[/C][C]0.950301[/C][/ROW]
[ROW][C]192[/C][C]0.0419509[/C][C]0.0839018[/C][C]0.958049[/C][/ROW]
[ROW][C]193[/C][C]0.0487095[/C][C]0.0974191[/C][C]0.95129[/C][/ROW]
[ROW][C]194[/C][C]0.0522825[/C][C]0.104565[/C][C]0.947718[/C][/ROW]
[ROW][C]195[/C][C]0.0443745[/C][C]0.0887491[/C][C]0.955625[/C][/ROW]
[ROW][C]196[/C][C]0.0370208[/C][C]0.0740415[/C][C]0.962979[/C][/ROW]
[ROW][C]197[/C][C]0.0483133[/C][C]0.0966265[/C][C]0.951687[/C][/ROW]
[ROW][C]198[/C][C]0.0395848[/C][C]0.0791695[/C][C]0.960415[/C][/ROW]
[ROW][C]199[/C][C]0.0367003[/C][C]0.0734006[/C][C]0.9633[/C][/ROW]
[ROW][C]200[/C][C]0.0310402[/C][C]0.0620804[/C][C]0.96896[/C][/ROW]
[ROW][C]201[/C][C]0.0292225[/C][C]0.0584451[/C][C]0.970777[/C][/ROW]
[ROW][C]202[/C][C]0.0243816[/C][C]0.0487631[/C][C]0.975618[/C][/ROW]
[ROW][C]203[/C][C]0.0313046[/C][C]0.0626092[/C][C]0.968695[/C][/ROW]
[ROW][C]204[/C][C]0.0356804[/C][C]0.0713609[/C][C]0.96432[/C][/ROW]
[ROW][C]205[/C][C]0.038908[/C][C]0.0778159[/C][C]0.961092[/C][/ROW]
[ROW][C]206[/C][C]0.0308805[/C][C]0.061761[/C][C]0.969119[/C][/ROW]
[ROW][C]207[/C][C]0.0303438[/C][C]0.0606877[/C][C]0.969656[/C][/ROW]
[ROW][C]208[/C][C]0.024951[/C][C]0.0499021[/C][C]0.975049[/C][/ROW]
[ROW][C]209[/C][C]0.0278686[/C][C]0.0557372[/C][C]0.972131[/C][/ROW]
[ROW][C]210[/C][C]0.0225424[/C][C]0.0450849[/C][C]0.977458[/C][/ROW]
[ROW][C]211[/C][C]0.0249783[/C][C]0.0499566[/C][C]0.975022[/C][/ROW]
[ROW][C]212[/C][C]0.0399741[/C][C]0.0799482[/C][C]0.960026[/C][/ROW]
[ROW][C]213[/C][C]0.0315878[/C][C]0.0631757[/C][C]0.968412[/C][/ROW]
[ROW][C]214[/C][C]0.0441624[/C][C]0.0883249[/C][C]0.955838[/C][/ROW]
[ROW][C]215[/C][C]0.0380624[/C][C]0.0761247[/C][C]0.961938[/C][/ROW]
[ROW][C]216[/C][C]0.0297535[/C][C]0.059507[/C][C]0.970246[/C][/ROW]
[ROW][C]217[/C][C]0.0321992[/C][C]0.0643985[/C][C]0.967801[/C][/ROW]
[ROW][C]218[/C][C]0.0275324[/C][C]0.0550648[/C][C]0.972468[/C][/ROW]
[ROW][C]219[/C][C]0.0247445[/C][C]0.049489[/C][C]0.975255[/C][/ROW]
[ROW][C]220[/C][C]0.0189655[/C][C]0.037931[/C][C]0.981035[/C][/ROW]
[ROW][C]221[/C][C]0.0168962[/C][C]0.0337925[/C][C]0.983104[/C][/ROW]
[ROW][C]222[/C][C]0.0124218[/C][C]0.0248435[/C][C]0.987578[/C][/ROW]
[ROW][C]223[/C][C]0.00931262[/C][C]0.0186252[/C][C]0.990687[/C][/ROW]
[ROW][C]224[/C][C]0.0075026[/C][C]0.0150052[/C][C]0.992497[/C][/ROW]
[ROW][C]225[/C][C]0.00654748[/C][C]0.013095[/C][C]0.993453[/C][/ROW]
[ROW][C]226[/C][C]0.0149948[/C][C]0.0299896[/C][C]0.985005[/C][/ROW]
[ROW][C]227[/C][C]0.0115413[/C][C]0.0230826[/C][C]0.988459[/C][/ROW]
[ROW][C]228[/C][C]0.00835013[/C][C]0.0167003[/C][C]0.99165[/C][/ROW]
[ROW][C]229[/C][C]0.00609659[/C][C]0.0121932[/C][C]0.993903[/C][/ROW]
[ROW][C]230[/C][C]0.00441014[/C][C]0.00882027[/C][C]0.99559[/C][/ROW]
[ROW][C]231[/C][C]0.00439448[/C][C]0.00878897[/C][C]0.995606[/C][/ROW]
[ROW][C]232[/C][C]0.00814473[/C][C]0.0162895[/C][C]0.991855[/C][/ROW]
[ROW][C]233[/C][C]0.0377567[/C][C]0.0755134[/C][C]0.962243[/C][/ROW]
[ROW][C]234[/C][C]0.0542942[/C][C]0.108588[/C][C]0.945706[/C][/ROW]
[ROW][C]235[/C][C]0.0405063[/C][C]0.0810125[/C][C]0.959494[/C][/ROW]
[ROW][C]236[/C][C]0.0361094[/C][C]0.0722187[/C][C]0.963891[/C][/ROW]
[ROW][C]237[/C][C]0.246492[/C][C]0.492983[/C][C]0.753508[/C][/ROW]
[ROW][C]238[/C][C]0.200772[/C][C]0.401543[/C][C]0.799228[/C][/ROW]
[ROW][C]239[/C][C]0.180034[/C][C]0.360069[/C][C]0.819966[/C][/ROW]
[ROW][C]240[/C][C]0.142119[/C][C]0.284238[/C][C]0.857881[/C][/ROW]
[ROW][C]241[/C][C]0.113699[/C][C]0.227398[/C][C]0.886301[/C][/ROW]
[ROW][C]242[/C][C]0.0945235[/C][C]0.189047[/C][C]0.905477[/C][/ROW]
[ROW][C]243[/C][C]0.0878969[/C][C]0.175794[/C][C]0.912103[/C][/ROW]
[ROW][C]244[/C][C]0.153544[/C][C]0.307088[/C][C]0.846456[/C][/ROW]
[ROW][C]245[/C][C]0.137625[/C][C]0.27525[/C][C]0.862375[/C][/ROW]
[ROW][C]246[/C][C]0.110105[/C][C]0.22021[/C][C]0.889895[/C][/ROW]
[ROW][C]247[/C][C]0.0777674[/C][C]0.155535[/C][C]0.922233[/C][/ROW]
[ROW][C]248[/C][C]0.0666917[/C][C]0.133383[/C][C]0.933308[/C][/ROW]
[ROW][C]249[/C][C]0.0624865[/C][C]0.124973[/C][C]0.937514[/C][/ROW]
[ROW][C]250[/C][C]0.0773785[/C][C]0.154757[/C][C]0.922622[/C][/ROW]
[ROW][C]251[/C][C]0.046053[/C][C]0.092106[/C][C]0.953947[/C][/ROW]
[ROW][C]252[/C][C]0.112281[/C][C]0.224562[/C][C]0.887719[/C][/ROW]
[ROW][C]253[/C][C]0.234993[/C][C]0.469985[/C][C]0.765007[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221814&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221814&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.2344540.4689080.765546
120.1202970.2405930.879703
130.08155670.1631130.918443
140.1028780.2057570.897122
150.05875430.1175090.941246
160.03917040.07834090.96083
170.06302220.1260440.936978
180.2558770.5117540.744123
190.1942260.3884520.805774
200.1377730.2755450.862227
210.09861240.1972250.901388
220.09685940.1937190.903141
230.2570650.514130.742935
240.3215060.6430130.678494
250.2948810.5897630.705119
260.2774580.5549160.722542
270.3521120.7042240.647888
280.3638630.7277260.636137
290.34680.6935990.6532
300.3809130.7618250.619087
310.3286890.6573790.671311
320.2895060.5790120.710494
330.2625030.5250070.737497
340.2263160.4526320.773684
350.1878910.3757810.812109
360.3049450.6098890.695055
370.3349840.6699680.665016
380.3259770.6519530.674023
390.3560380.7120750.643962
400.3342220.6684440.665778
410.2980120.5960240.701988
420.2638440.5276880.736156
430.2782780.5565560.721722
440.236540.4730790.76346
450.2144450.428890.785555
460.3926970.7853940.607303
470.5455310.9089380.454469
480.4965610.9931220.503439
490.483230.9664610.51677
500.4684060.9368110.531594
510.4236880.8473750.576312
520.3781850.756370.621815
530.3866170.7732340.613383
540.3697210.7394410.630279
550.360950.72190.63905
560.3389910.6779820.661009
570.2993840.5987680.700616
580.2706990.5413970.729301
590.2362450.4724910.763755
600.2421080.4842160.757892
610.2183810.4367610.781619
620.1914860.3829710.808514
630.1634940.3269880.836506
640.1377650.2755310.862235
650.1188750.2377510.881125
660.1100170.2200330.889983
670.1058130.2116270.894187
680.2226160.4452330.777384
690.3124110.6248220.687589
700.281580.563160.71842
710.3970160.7940320.602984
720.3590440.7180880.640956
730.3507980.7015970.649202
740.3353430.6706860.664657
750.3032170.6064330.696783
760.369170.7383410.63083
770.3334370.6668730.666563
780.3126420.6252840.687358
790.3256930.6513850.674307
800.2981840.5963680.701816
810.2700510.5401020.729949
820.2391680.4783370.760832
830.2148660.4297320.785134
840.1876610.3753220.812339
850.1843740.3687480.815626
860.1593620.3187230.840638
870.1401260.2802530.859874
880.1305620.2611240.869438
890.112810.225620.88719
900.1100170.2200340.889983
910.09412310.1882460.905877
920.08128190.1625640.918718
930.06902290.1380460.930977
940.07107850.1421570.928922
950.06423330.1284670.935767
960.0538240.1076480.946176
970.05947350.1189470.940527
980.04926320.09852640.950737
990.04039380.08078750.959606
1000.03534170.07068340.964658
1010.03135240.06270470.968648
1020.03690320.07380640.963097
1030.03166920.06333840.968331
1040.02859590.05719180.971404
1050.0338460.06769210.966154
1060.02974360.05948730.970256
1070.02415560.04831120.975844
1080.02403120.04806240.975969
1090.01947380.03894760.980526
1100.01593220.03186450.984068
1110.01262990.02525980.98737
1120.01305950.0261190.986941
1130.01166380.02332770.988336
1140.01674560.03349120.983254
1150.01599580.03199170.984004
1160.0153060.0306120.984694
1170.01266140.02532280.987339
1180.01263820.02527650.987362
1190.01027510.02055020.989725
1200.009050320.01810060.99095
1210.00736390.01472780.992636
1220.01133130.02266260.988669
1230.009547080.01909420.990453
1240.008480390.01696080.99152
1250.006941240.01388250.993059
1260.005654640.01130930.994345
1270.005091280.01018260.994909
1280.004102210.008204430.995898
1290.006053680.01210740.993946
1300.006560280.01312060.99344
1310.01355550.0271110.986444
1320.01632150.03264310.983678
1330.01760620.03521240.982394
1340.01700580.03401160.982994
1350.01389920.02779830.986101
1360.01172810.02345610.988272
1370.00938760.01877520.990612
1380.0114310.0228620.988569
1390.009947720.01989540.990052
1400.01130140.02260290.988699
1410.01753490.03506980.982465
1420.0159480.03189610.984052
1430.01269890.02539780.987301
1440.01346340.02692680.986537
1450.02565640.05131290.974344
1460.03143770.06287540.968562
1470.03299860.06599730.967001
1480.02979220.05958440.970208
1490.02482850.0496570.975172
1500.03444650.06889290.965554
1510.02972220.05944450.970278
1520.03129680.06259360.968703
1530.06394010.127880.93606
1540.06282270.1256450.937177
1550.07223020.144460.92777
1560.06179630.1235930.938204
1570.05521390.1104280.944786
1580.04831790.09663570.951682
1590.04727620.09455230.952724
1600.04053550.0810710.959464
1610.03344860.06689720.966551
1620.02749750.0549950.972502
1630.02289880.04579760.977101
1640.01931550.0386310.980684
1650.01695320.03390650.983047
1660.01720190.03440370.982798
1670.01382150.02764290.986179
1680.02038720.04077430.979613
1690.02020470.04040930.979795
1700.01887090.03774180.981129
1710.01814830.03629660.981852
1720.01470530.02941060.985295
1730.01475050.0295010.985249
1740.01642860.03285730.983571
1750.0219560.0439120.978044
1760.01765890.03531780.982341
1770.01438690.02877370.985613
1780.01174580.02349160.988254
1790.009194540.01838910.990805
1800.008006690.01601340.991993
1810.006604640.01320930.993395
1820.005345520.0106910.994654
1830.005609450.01121890.994391
1840.004436430.008872860.995564
1850.09406080.1881220.905939
1860.08166580.1633320.918334
1870.09282760.1856550.907172
1880.08019420.1603880.919806
1890.06794280.1358860.932057
1900.05634290.1126860.943657
1910.04969930.09939860.950301
1920.04195090.08390180.958049
1930.04870950.09741910.95129
1940.05228250.1045650.947718
1950.04437450.08874910.955625
1960.03702080.07404150.962979
1970.04831330.09662650.951687
1980.03958480.07916950.960415
1990.03670030.07340060.9633
2000.03104020.06208040.96896
2010.02922250.05844510.970777
2020.02438160.04876310.975618
2030.03130460.06260920.968695
2040.03568040.07136090.96432
2050.0389080.07781590.961092
2060.03088050.0617610.969119
2070.03034380.06068770.969656
2080.0249510.04990210.975049
2090.02786860.05573720.972131
2100.02254240.04508490.977458
2110.02497830.04995660.975022
2120.03997410.07994820.960026
2130.03158780.06317570.968412
2140.04416240.08832490.955838
2150.03806240.07612470.961938
2160.02975350.0595070.970246
2170.03219920.06439850.967801
2180.02753240.05506480.972468
2190.02474450.0494890.975255
2200.01896550.0379310.981035
2210.01689620.03379250.983104
2220.01242180.02484350.987578
2230.009312620.01862520.990687
2240.00750260.01500520.992497
2250.006547480.0130950.993453
2260.01499480.02998960.985005
2270.01154130.02308260.988459
2280.008350130.01670030.99165
2290.006096590.01219320.993903
2300.004410140.008820270.99559
2310.004394480.008788970.995606
2320.008144730.01628950.991855
2330.03775670.07551340.962243
2340.05429420.1085880.945706
2350.04050630.08101250.959494
2360.03610940.07221870.963891
2370.2464920.4929830.753508
2380.2007720.4015430.799228
2390.1800340.3600690.819966
2400.1421190.2842380.857881
2410.1136990.2273980.886301
2420.09452350.1890470.905477
2430.08789690.1757940.912103
2440.1535440.3070880.846456
2450.1376250.275250.862375
2460.1101050.220210.889895
2470.07776740.1555350.922233
2480.06669170.1333830.933308
2490.06248650.1249730.937514
2500.07737850.1547570.922622
2510.0460530.0921060.953947
2520.1122810.2245620.887719
2530.2349930.4699850.765007






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0164609NOK
5% type I error level790.325103NOK
10% type I error level1280.526749NOK

\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 & 4 & 0.0164609 & NOK \tabularnewline
5% type I error level & 79 & 0.325103 & NOK \tabularnewline
10% type I error level & 128 & 0.526749 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221814&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]4[/C][C]0.0164609[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]79[/C][C]0.325103[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]128[/C][C]0.526749[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221814&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221814&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 level40.0164609NOK
5% type I error level790.325103NOK
10% type I error level1280.526749NOK


Figures (Output of Computation)

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

Parameters (Session):
Parameters (R input):
par1 = 3 ; 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')
}