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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 03 Nov 2013 09:52:36 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/03/t1383490690kclr7wu4l92fsie.htm/, Retrieved Mon, 29 Apr 2024 10:32:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221927, Retrieved Mon, 29 Apr 2024 10:32:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2013-11-03 14:52:36] [0e9124696d12fe9c83a0561864c9b933] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time21 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 21 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221927&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]21 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221927&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221927&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 time21 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 5.45153 + 0.0321669Connected[t] + 0.0427654Separate[t] + 0.55849Software[t] + 0.0702335Happiness[t] -0.0311264Depression[t] + 0.00747851Sport1[t] -0.00491058t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  5.45153 +  0.0321669Connected[t] +  0.0427654Separate[t] +  0.55849Software[t] +  0.0702335Happiness[t] -0.0311264Depression[t] +  0.00747851Sport1[t] -0.00491058t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221927&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  5.45153 +  0.0321669Connected[t] +  0.0427654Separate[t] +  0.55849Software[t] +  0.0702335Happiness[t] -0.0311264Depression[t] +  0.00747851Sport1[t] -0.00491058t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221927&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221927&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] = + 5.45153 + 0.0321669Connected[t] + 0.0427654Separate[t] + 0.55849Software[t] + 0.0702335Happiness[t] -0.0311264Depression[t] + 0.00747851Sport1[t] -0.00491058t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)5.451531.942792.8060.005400970.00270048
Connected0.03216690.03442440.93440.3509670.175483
Separate0.04276540.03507621.2190.2238860.111943
Software0.558490.053725710.42.40853e-211.20426e-21
Happiness0.07023350.05780951.2150.2255180.112759
Depression-0.03112640.041759-0.74540.4567250.228362
Sport10.007478510.01186880.63010.5291910.264595
t-0.004910580.00168013-2.9230.003779910.00188996

\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) & 5.45153 & 1.94279 & 2.806 & 0.00540097 & 0.00270048 \tabularnewline
Connected & 0.0321669 & 0.0344244 & 0.9344 & 0.350967 & 0.175483 \tabularnewline
Separate & 0.0427654 & 0.0350762 & 1.219 & 0.223886 & 0.111943 \tabularnewline
Software & 0.55849 & 0.0537257 & 10.4 & 2.40853e-21 & 1.20426e-21 \tabularnewline
Happiness & 0.0702335 & 0.0578095 & 1.215 & 0.225518 & 0.112759 \tabularnewline
Depression & -0.0311264 & 0.041759 & -0.7454 & 0.456725 & 0.228362 \tabularnewline
Sport1 & 0.00747851 & 0.0118688 & 0.6301 & 0.529191 & 0.264595 \tabularnewline
t & -0.00491058 & 0.00168013 & -2.923 & 0.00377991 & 0.00188996 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221927&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]5.45153[/C][C]1.94279[/C][C]2.806[/C][C]0.00540097[/C][C]0.00270048[/C][/ROW]
[ROW][C]Connected[/C][C]0.0321669[/C][C]0.0344244[/C][C]0.9344[/C][C]0.350967[/C][C]0.175483[/C][/ROW]
[ROW][C]Separate[/C][C]0.0427654[/C][C]0.0350762[/C][C]1.219[/C][C]0.223886[/C][C]0.111943[/C][/ROW]
[ROW][C]Software[/C][C]0.55849[/C][C]0.0537257[/C][C]10.4[/C][C]2.40853e-21[/C][C]1.20426e-21[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0702335[/C][C]0.0578095[/C][C]1.215[/C][C]0.225518[/C][C]0.112759[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0311264[/C][C]0.041759[/C][C]-0.7454[/C][C]0.456725[/C][C]0.228362[/C][/ROW]
[ROW][C]Sport1[/C][C]0.00747851[/C][C]0.0118688[/C][C]0.6301[/C][C]0.529191[/C][C]0.264595[/C][/ROW]
[ROW][C]t[/C][C]-0.00491058[/C][C]0.00168013[/C][C]-2.923[/C][C]0.00377991[/C][C]0.00188996[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221927&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221927&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)5.451531.942792.8060.005400970.00270048
Connected0.03216690.03442440.93440.3509670.175483
Separate0.04276540.03507621.2190.2238860.111943
Software0.558490.053725710.42.40853e-211.20426e-21
Happiness0.07023350.05780951.2150.2255180.112759
Depression-0.03112640.041759-0.74540.4567250.228362
Sport10.007478510.01186880.63010.5291910.264595
t-0.004910580.00168013-2.9230.003779910.00188996






Multiple Linear Regression - Regression Statistics
Multiple R0.667213
R-squared0.445173
Adjusted R-squared0.430002
F-TEST (value)29.3436
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.85422
Sum Squared Residuals880.157

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.667213 \tabularnewline
R-squared & 0.445173 \tabularnewline
Adjusted R-squared & 0.430002 \tabularnewline
F-TEST (value) & 29.3436 \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 & 1.85422 \tabularnewline
Sum Squared Residuals & 880.157 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221927&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.667213[/C][/ROW]
[ROW][C]R-squared[/C][C]0.445173[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.430002[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]29.3436[/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]1.85422[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]880.157[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221927&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221927&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 R0.667213
R-squared0.445173
Adjusted R-squared0.430002
F-TEST (value)29.3436
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.85422
Sum Squared Residuals880.157






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.0985-3.09854
21615.75060.249372
31917.10631.89368
41512.16162.83839
51416.4018-2.40179
61314.847-1.84701
71915.39413.60588
81517.1035-2.10349
91416.0597-2.05966
101514.46130.53868
111615.0040.99601
121616.1958-0.195778
131615.54520.454799
141615.49760.50243
151718.0026-1.00262
161515.4967-0.496691
171514.58780.412162
182016.42213.57787
191815.53182.46816
201615.59840.401602
211615.39450.605521
221615.21360.786386
231916.49212.50786
241615.16090.839081
251716.14840.851624
261716.22180.778197
271614.90841.09165
281516.8091-1.80911
291615.68480.315176
301414.263-0.26303
311515.766-0.765961
321212.8493-0.849289
331414.804-0.803962
341616.0017-0.00174961
351415.4902-1.49021
361013.0305-3.03048
371013.0355-3.03553
381415.747-1.74703
391614.55461.44544
401614.49491.50511
411614.72051.27946
421415.701-1.70095
432017.48712.51288
441414.1534-0.153378
451414.4624-0.462355
461115.4909-4.49095
471416.6308-2.63076
481515.1467-0.146742
491615.41790.582123
501415.6302-1.63025
511617.0253-1.0253
521414.1419-0.141941
531215.0172-3.01719
541616.0362-0.0361861
55911.3433-2.34329
561412.3851.61502
571615.85450.14546
581615.52990.470117
591515.1124-0.112393
601614.22111.77894
611211.55960.440447
621615.64070.359318
631616.5488-0.548817
641414.711-0.710986
651615.30630.693679
661716.05420.945814
671816.33321.66682
681814.39593.60411
691215.8997-3.89971
701615.65160.348421
711013.4124-3.41238
721414.9243-0.924295
731816.92811.07194
741817.1410.859016
751615.23230.767705
761713.49193.50811
771616.4191-0.4191
781614.53121.4688
791315.2166-2.21658
801615.14210.85786
811615.65860.341373
821615.76320.236759
831515.6434-0.643414
841514.88420.115768
851614.16071.83926
861414.1556-0.155569
871615.36750.632512
881614.87261.12741
891514.51950.480519
901213.908-1.90797
911716.75850.241506
921615.80560.194438
931515.0531-0.0531068
941315.0299-2.02985
951614.74361.25639
961615.78820.211757
971613.67742.32262
981615.77370.226292
991414.4298-0.429782
1001616.9923-0.992298
1011614.67661.32338
1022017.45422.54578
1031514.23970.76034
1041614.95991.04014
1051314.8422-1.8422
1061715.70171.29827
1071615.70110.298877
1081614.35871.64135
1091212.3043-0.304342
1101615.28570.714319
1111615.99280.00717285
1121715.05641.94359
1131314.2812-1.28118
1141214.5799-2.57987
1151816.16151.83853
1161415.8657-1.86573
1171413.22890.771112
1181314.7929-1.79292
1191615.52040.479616
1201314.4292-1.42922
1211615.38540.614577
1221315.8212-2.82121
1231616.8545-0.854504
1241515.8438-0.843765
1251616.7849-0.784934
1261514.65870.341278
1271715.49061.50942
1281514.04830.951748
1291214.6859-2.68587
1301613.94032.05973
1311013.724-3.72395
1321613.45832.54167
1331214.166-2.16599
1341415.544-1.54405
1351515.0837-0.0836567
1361312.11210.887887
1371514.53130.468722
1381113.499-2.49895
1391213.0065-1.00648
1401113.34-2.33996
1411612.85653.1435
1421513.64411.35588
1431716.84140.158636
1441614.12441.8756
1451013.2668-3.26675
1461815.49752.50245
1471314.9458-1.94575
1481614.8431.15699
1491312.82720.172772
1501012.9005-2.90046
1511515.8784-0.878418
1521613.82492.17514
1531611.85264.14742
1541412.39631.6037
1551012.4816-2.48163
1561716.43930.560693
1571311.70671.29331
1581513.90091.09907
1591614.53741.4626
1601212.6989-0.698904
1611312.69310.306895
1621312.67020.329796
1631212.3814-0.381358
1641716.21310.786902
1651513.66821.33178
1661011.6198-1.61976
1671414.3442-0.344192
1681114.1943-3.19435
1691314.7896-1.7896
1701614.38721.61281
1711210.48151.51847
1721615.33780.662212
1731213.8444-1.84444
174911.3336-2.33361
1751214.907-2.90704
1761514.4730.526992
1771212.2943-0.294328
1781212.6504-0.650368
1791413.79390.206132
1801213.2889-1.2889
1811615.00690.993126
1821111.4515-0.451506
1831916.70162.29842
1841515.111-0.110982
185814.597-6.59699
1861614.69891.30106
1871714.38962.61042
1881212.3486-0.348623
1891111.4121-0.41207
1901110.4550.545032
1911414.4365-0.436491
1921615.37640.623572
193129.722482.27752
1941614.08861.91136
1951313.6329-0.632885
1961514.9990.00102459
1971612.91263.08737
1981614.99191.00806
1991412.40761.59237
2001614.46041.53964
2011614.03331.96668
2021413.29550.704538
2031113.313-2.31296
2041214.4949-2.49492
2051512.67792.32212
2061514.41880.581163
2071614.5321.46799
2081614.84311.15687
2091113.5801-2.58015
2101513.88861.11145
2111214.2038-2.20379
2121215.7224-3.72243
2131514.10910.890921
2141512.09062.90942
2151614.46471.53526
2161413.08050.919486
2171714.57492.42513
2181413.90490.0950769
2191311.83211.16789
2201515.1299-0.12991
2211314.5727-1.57269
2221413.89210.107851
2231514.20.800012
2241213.0555-1.05545
2251312.26890.731083
226811.6574-3.65737
2271413.68330.316721
2281412.81431.18571
2291112.1979-1.19789
2301212.8304-0.83039
2311311.18551.81451
2321013.2189-3.21891
2331611.34884.65121
2341815.77382.22625
2351313.7267-0.726661
2361113.2216-2.22156
237410.9938-6.99382
2381314.1797-1.17968
2391614.13671.86326
2401011.5931-1.59306
2411212.1626-0.162645
2421213.396-1.39602
243108.810371.18963
2441310.97972.02025
2451513.58021.41979
2461211.80710.192867
2471412.74581.25417
2481012.383-2.38303
2491210.70461.29544
2501211.52220.477753
2511111.7208-0.72083
2521011.5207-1.5207
2531211.27370.726256
2541612.70753.2925
2551213.2079-1.20786
2561413.71970.280292
2571614.13891.86112
2581411.55372.44632
2591314.0549-1.05494
26049.33309-5.33309
2611513.55311.4469
2621114.7741-3.77412
2631111.1662-0.166228
2641412.63111.36892

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.0985 & -3.09854 \tabularnewline
2 & 16 & 15.7506 & 0.249372 \tabularnewline
3 & 19 & 17.1063 & 1.89368 \tabularnewline
4 & 15 & 12.1616 & 2.83839 \tabularnewline
5 & 14 & 16.4018 & -2.40179 \tabularnewline
6 & 13 & 14.847 & -1.84701 \tabularnewline
7 & 19 & 15.3941 & 3.60588 \tabularnewline
8 & 15 & 17.1035 & -2.10349 \tabularnewline
9 & 14 & 16.0597 & -2.05966 \tabularnewline
10 & 15 & 14.4613 & 0.53868 \tabularnewline
11 & 16 & 15.004 & 0.99601 \tabularnewline
12 & 16 & 16.1958 & -0.195778 \tabularnewline
13 & 16 & 15.5452 & 0.454799 \tabularnewline
14 & 16 & 15.4976 & 0.50243 \tabularnewline
15 & 17 & 18.0026 & -1.00262 \tabularnewline
16 & 15 & 15.4967 & -0.496691 \tabularnewline
17 & 15 & 14.5878 & 0.412162 \tabularnewline
18 & 20 & 16.4221 & 3.57787 \tabularnewline
19 & 18 & 15.5318 & 2.46816 \tabularnewline
20 & 16 & 15.5984 & 0.401602 \tabularnewline
21 & 16 & 15.3945 & 0.605521 \tabularnewline
22 & 16 & 15.2136 & 0.786386 \tabularnewline
23 & 19 & 16.4921 & 2.50786 \tabularnewline
24 & 16 & 15.1609 & 0.839081 \tabularnewline
25 & 17 & 16.1484 & 0.851624 \tabularnewline
26 & 17 & 16.2218 & 0.778197 \tabularnewline
27 & 16 & 14.9084 & 1.09165 \tabularnewline
28 & 15 & 16.8091 & -1.80911 \tabularnewline
29 & 16 & 15.6848 & 0.315176 \tabularnewline
30 & 14 & 14.263 & -0.26303 \tabularnewline
31 & 15 & 15.766 & -0.765961 \tabularnewline
32 & 12 & 12.8493 & -0.849289 \tabularnewline
33 & 14 & 14.804 & -0.803962 \tabularnewline
34 & 16 & 16.0017 & -0.00174961 \tabularnewline
35 & 14 & 15.4902 & -1.49021 \tabularnewline
36 & 10 & 13.0305 & -3.03048 \tabularnewline
37 & 10 & 13.0355 & -3.03553 \tabularnewline
38 & 14 & 15.747 & -1.74703 \tabularnewline
39 & 16 & 14.5546 & 1.44544 \tabularnewline
40 & 16 & 14.4949 & 1.50511 \tabularnewline
41 & 16 & 14.7205 & 1.27946 \tabularnewline
42 & 14 & 15.701 & -1.70095 \tabularnewline
43 & 20 & 17.4871 & 2.51288 \tabularnewline
44 & 14 & 14.1534 & -0.153378 \tabularnewline
45 & 14 & 14.4624 & -0.462355 \tabularnewline
46 & 11 & 15.4909 & -4.49095 \tabularnewline
47 & 14 & 16.6308 & -2.63076 \tabularnewline
48 & 15 & 15.1467 & -0.146742 \tabularnewline
49 & 16 & 15.4179 & 0.582123 \tabularnewline
50 & 14 & 15.6302 & -1.63025 \tabularnewline
51 & 16 & 17.0253 & -1.0253 \tabularnewline
52 & 14 & 14.1419 & -0.141941 \tabularnewline
53 & 12 & 15.0172 & -3.01719 \tabularnewline
54 & 16 & 16.0362 & -0.0361861 \tabularnewline
55 & 9 & 11.3433 & -2.34329 \tabularnewline
56 & 14 & 12.385 & 1.61502 \tabularnewline
57 & 16 & 15.8545 & 0.14546 \tabularnewline
58 & 16 & 15.5299 & 0.470117 \tabularnewline
59 & 15 & 15.1124 & -0.112393 \tabularnewline
60 & 16 & 14.2211 & 1.77894 \tabularnewline
61 & 12 & 11.5596 & 0.440447 \tabularnewline
62 & 16 & 15.6407 & 0.359318 \tabularnewline
63 & 16 & 16.5488 & -0.548817 \tabularnewline
64 & 14 & 14.711 & -0.710986 \tabularnewline
65 & 16 & 15.3063 & 0.693679 \tabularnewline
66 & 17 & 16.0542 & 0.945814 \tabularnewline
67 & 18 & 16.3332 & 1.66682 \tabularnewline
68 & 18 & 14.3959 & 3.60411 \tabularnewline
69 & 12 & 15.8997 & -3.89971 \tabularnewline
70 & 16 & 15.6516 & 0.348421 \tabularnewline
71 & 10 & 13.4124 & -3.41238 \tabularnewline
72 & 14 & 14.9243 & -0.924295 \tabularnewline
73 & 18 & 16.9281 & 1.07194 \tabularnewline
74 & 18 & 17.141 & 0.859016 \tabularnewline
75 & 16 & 15.2323 & 0.767705 \tabularnewline
76 & 17 & 13.4919 & 3.50811 \tabularnewline
77 & 16 & 16.4191 & -0.4191 \tabularnewline
78 & 16 & 14.5312 & 1.4688 \tabularnewline
79 & 13 & 15.2166 & -2.21658 \tabularnewline
80 & 16 & 15.1421 & 0.85786 \tabularnewline
81 & 16 & 15.6586 & 0.341373 \tabularnewline
82 & 16 & 15.7632 & 0.236759 \tabularnewline
83 & 15 & 15.6434 & -0.643414 \tabularnewline
84 & 15 & 14.8842 & 0.115768 \tabularnewline
85 & 16 & 14.1607 & 1.83926 \tabularnewline
86 & 14 & 14.1556 & -0.155569 \tabularnewline
87 & 16 & 15.3675 & 0.632512 \tabularnewline
88 & 16 & 14.8726 & 1.12741 \tabularnewline
89 & 15 & 14.5195 & 0.480519 \tabularnewline
90 & 12 & 13.908 & -1.90797 \tabularnewline
91 & 17 & 16.7585 & 0.241506 \tabularnewline
92 & 16 & 15.8056 & 0.194438 \tabularnewline
93 & 15 & 15.0531 & -0.0531068 \tabularnewline
94 & 13 & 15.0299 & -2.02985 \tabularnewline
95 & 16 & 14.7436 & 1.25639 \tabularnewline
96 & 16 & 15.7882 & 0.211757 \tabularnewline
97 & 16 & 13.6774 & 2.32262 \tabularnewline
98 & 16 & 15.7737 & 0.226292 \tabularnewline
99 & 14 & 14.4298 & -0.429782 \tabularnewline
100 & 16 & 16.9923 & -0.992298 \tabularnewline
101 & 16 & 14.6766 & 1.32338 \tabularnewline
102 & 20 & 17.4542 & 2.54578 \tabularnewline
103 & 15 & 14.2397 & 0.76034 \tabularnewline
104 & 16 & 14.9599 & 1.04014 \tabularnewline
105 & 13 & 14.8422 & -1.8422 \tabularnewline
106 & 17 & 15.7017 & 1.29827 \tabularnewline
107 & 16 & 15.7011 & 0.298877 \tabularnewline
108 & 16 & 14.3587 & 1.64135 \tabularnewline
109 & 12 & 12.3043 & -0.304342 \tabularnewline
110 & 16 & 15.2857 & 0.714319 \tabularnewline
111 & 16 & 15.9928 & 0.00717285 \tabularnewline
112 & 17 & 15.0564 & 1.94359 \tabularnewline
113 & 13 & 14.2812 & -1.28118 \tabularnewline
114 & 12 & 14.5799 & -2.57987 \tabularnewline
115 & 18 & 16.1615 & 1.83853 \tabularnewline
116 & 14 & 15.8657 & -1.86573 \tabularnewline
117 & 14 & 13.2289 & 0.771112 \tabularnewline
118 & 13 & 14.7929 & -1.79292 \tabularnewline
119 & 16 & 15.5204 & 0.479616 \tabularnewline
120 & 13 & 14.4292 & -1.42922 \tabularnewline
121 & 16 & 15.3854 & 0.614577 \tabularnewline
122 & 13 & 15.8212 & -2.82121 \tabularnewline
123 & 16 & 16.8545 & -0.854504 \tabularnewline
124 & 15 & 15.8438 & -0.843765 \tabularnewline
125 & 16 & 16.7849 & -0.784934 \tabularnewline
126 & 15 & 14.6587 & 0.341278 \tabularnewline
127 & 17 & 15.4906 & 1.50942 \tabularnewline
128 & 15 & 14.0483 & 0.951748 \tabularnewline
129 & 12 & 14.6859 & -2.68587 \tabularnewline
130 & 16 & 13.9403 & 2.05973 \tabularnewline
131 & 10 & 13.724 & -3.72395 \tabularnewline
132 & 16 & 13.4583 & 2.54167 \tabularnewline
133 & 12 & 14.166 & -2.16599 \tabularnewline
134 & 14 & 15.544 & -1.54405 \tabularnewline
135 & 15 & 15.0837 & -0.0836567 \tabularnewline
136 & 13 & 12.1121 & 0.887887 \tabularnewline
137 & 15 & 14.5313 & 0.468722 \tabularnewline
138 & 11 & 13.499 & -2.49895 \tabularnewline
139 & 12 & 13.0065 & -1.00648 \tabularnewline
140 & 11 & 13.34 & -2.33996 \tabularnewline
141 & 16 & 12.8565 & 3.1435 \tabularnewline
142 & 15 & 13.6441 & 1.35588 \tabularnewline
143 & 17 & 16.8414 & 0.158636 \tabularnewline
144 & 16 & 14.1244 & 1.8756 \tabularnewline
145 & 10 & 13.2668 & -3.26675 \tabularnewline
146 & 18 & 15.4975 & 2.50245 \tabularnewline
147 & 13 & 14.9458 & -1.94575 \tabularnewline
148 & 16 & 14.843 & 1.15699 \tabularnewline
149 & 13 & 12.8272 & 0.172772 \tabularnewline
150 & 10 & 12.9005 & -2.90046 \tabularnewline
151 & 15 & 15.8784 & -0.878418 \tabularnewline
152 & 16 & 13.8249 & 2.17514 \tabularnewline
153 & 16 & 11.8526 & 4.14742 \tabularnewline
154 & 14 & 12.3963 & 1.6037 \tabularnewline
155 & 10 & 12.4816 & -2.48163 \tabularnewline
156 & 17 & 16.4393 & 0.560693 \tabularnewline
157 & 13 & 11.7067 & 1.29331 \tabularnewline
158 & 15 & 13.9009 & 1.09907 \tabularnewline
159 & 16 & 14.5374 & 1.4626 \tabularnewline
160 & 12 & 12.6989 & -0.698904 \tabularnewline
161 & 13 & 12.6931 & 0.306895 \tabularnewline
162 & 13 & 12.6702 & 0.329796 \tabularnewline
163 & 12 & 12.3814 & -0.381358 \tabularnewline
164 & 17 & 16.2131 & 0.786902 \tabularnewline
165 & 15 & 13.6682 & 1.33178 \tabularnewline
166 & 10 & 11.6198 & -1.61976 \tabularnewline
167 & 14 & 14.3442 & -0.344192 \tabularnewline
168 & 11 & 14.1943 & -3.19435 \tabularnewline
169 & 13 & 14.7896 & -1.7896 \tabularnewline
170 & 16 & 14.3872 & 1.61281 \tabularnewline
171 & 12 & 10.4815 & 1.51847 \tabularnewline
172 & 16 & 15.3378 & 0.662212 \tabularnewline
173 & 12 & 13.8444 & -1.84444 \tabularnewline
174 & 9 & 11.3336 & -2.33361 \tabularnewline
175 & 12 & 14.907 & -2.90704 \tabularnewline
176 & 15 & 14.473 & 0.526992 \tabularnewline
177 & 12 & 12.2943 & -0.294328 \tabularnewline
178 & 12 & 12.6504 & -0.650368 \tabularnewline
179 & 14 & 13.7939 & 0.206132 \tabularnewline
180 & 12 & 13.2889 & -1.2889 \tabularnewline
181 & 16 & 15.0069 & 0.993126 \tabularnewline
182 & 11 & 11.4515 & -0.451506 \tabularnewline
183 & 19 & 16.7016 & 2.29842 \tabularnewline
184 & 15 & 15.111 & -0.110982 \tabularnewline
185 & 8 & 14.597 & -6.59699 \tabularnewline
186 & 16 & 14.6989 & 1.30106 \tabularnewline
187 & 17 & 14.3896 & 2.61042 \tabularnewline
188 & 12 & 12.3486 & -0.348623 \tabularnewline
189 & 11 & 11.4121 & -0.41207 \tabularnewline
190 & 11 & 10.455 & 0.545032 \tabularnewline
191 & 14 & 14.4365 & -0.436491 \tabularnewline
192 & 16 & 15.3764 & 0.623572 \tabularnewline
193 & 12 & 9.72248 & 2.27752 \tabularnewline
194 & 16 & 14.0886 & 1.91136 \tabularnewline
195 & 13 & 13.6329 & -0.632885 \tabularnewline
196 & 15 & 14.999 & 0.00102459 \tabularnewline
197 & 16 & 12.9126 & 3.08737 \tabularnewline
198 & 16 & 14.9919 & 1.00806 \tabularnewline
199 & 14 & 12.4076 & 1.59237 \tabularnewline
200 & 16 & 14.4604 & 1.53964 \tabularnewline
201 & 16 & 14.0333 & 1.96668 \tabularnewline
202 & 14 & 13.2955 & 0.704538 \tabularnewline
203 & 11 & 13.313 & -2.31296 \tabularnewline
204 & 12 & 14.4949 & -2.49492 \tabularnewline
205 & 15 & 12.6779 & 2.32212 \tabularnewline
206 & 15 & 14.4188 & 0.581163 \tabularnewline
207 & 16 & 14.532 & 1.46799 \tabularnewline
208 & 16 & 14.8431 & 1.15687 \tabularnewline
209 & 11 & 13.5801 & -2.58015 \tabularnewline
210 & 15 & 13.8886 & 1.11145 \tabularnewline
211 & 12 & 14.2038 & -2.20379 \tabularnewline
212 & 12 & 15.7224 & -3.72243 \tabularnewline
213 & 15 & 14.1091 & 0.890921 \tabularnewline
214 & 15 & 12.0906 & 2.90942 \tabularnewline
215 & 16 & 14.4647 & 1.53526 \tabularnewline
216 & 14 & 13.0805 & 0.919486 \tabularnewline
217 & 17 & 14.5749 & 2.42513 \tabularnewline
218 & 14 & 13.9049 & 0.0950769 \tabularnewline
219 & 13 & 11.8321 & 1.16789 \tabularnewline
220 & 15 & 15.1299 & -0.12991 \tabularnewline
221 & 13 & 14.5727 & -1.57269 \tabularnewline
222 & 14 & 13.8921 & 0.107851 \tabularnewline
223 & 15 & 14.2 & 0.800012 \tabularnewline
224 & 12 & 13.0555 & -1.05545 \tabularnewline
225 & 13 & 12.2689 & 0.731083 \tabularnewline
226 & 8 & 11.6574 & -3.65737 \tabularnewline
227 & 14 & 13.6833 & 0.316721 \tabularnewline
228 & 14 & 12.8143 & 1.18571 \tabularnewline
229 & 11 & 12.1979 & -1.19789 \tabularnewline
230 & 12 & 12.8304 & -0.83039 \tabularnewline
231 & 13 & 11.1855 & 1.81451 \tabularnewline
232 & 10 & 13.2189 & -3.21891 \tabularnewline
233 & 16 & 11.3488 & 4.65121 \tabularnewline
234 & 18 & 15.7738 & 2.22625 \tabularnewline
235 & 13 & 13.7267 & -0.726661 \tabularnewline
236 & 11 & 13.2216 & -2.22156 \tabularnewline
237 & 4 & 10.9938 & -6.99382 \tabularnewline
238 & 13 & 14.1797 & -1.17968 \tabularnewline
239 & 16 & 14.1367 & 1.86326 \tabularnewline
240 & 10 & 11.5931 & -1.59306 \tabularnewline
241 & 12 & 12.1626 & -0.162645 \tabularnewline
242 & 12 & 13.396 & -1.39602 \tabularnewline
243 & 10 & 8.81037 & 1.18963 \tabularnewline
244 & 13 & 10.9797 & 2.02025 \tabularnewline
245 & 15 & 13.5802 & 1.41979 \tabularnewline
246 & 12 & 11.8071 & 0.192867 \tabularnewline
247 & 14 & 12.7458 & 1.25417 \tabularnewline
248 & 10 & 12.383 & -2.38303 \tabularnewline
249 & 12 & 10.7046 & 1.29544 \tabularnewline
250 & 12 & 11.5222 & 0.477753 \tabularnewline
251 & 11 & 11.7208 & -0.72083 \tabularnewline
252 & 10 & 11.5207 & -1.5207 \tabularnewline
253 & 12 & 11.2737 & 0.726256 \tabularnewline
254 & 16 & 12.7075 & 3.2925 \tabularnewline
255 & 12 & 13.2079 & -1.20786 \tabularnewline
256 & 14 & 13.7197 & 0.280292 \tabularnewline
257 & 16 & 14.1389 & 1.86112 \tabularnewline
258 & 14 & 11.5537 & 2.44632 \tabularnewline
259 & 13 & 14.0549 & -1.05494 \tabularnewline
260 & 4 & 9.33309 & -5.33309 \tabularnewline
261 & 15 & 13.5531 & 1.4469 \tabularnewline
262 & 11 & 14.7741 & -3.77412 \tabularnewline
263 & 11 & 11.1662 & -0.166228 \tabularnewline
264 & 14 & 12.6311 & 1.36892 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221927&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]16.0985[/C][C]-3.09854[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.7506[/C][C]0.249372[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]17.1063[/C][C]1.89368[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.1616[/C][C]2.83839[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.4018[/C][C]-2.40179[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.847[/C][C]-1.84701[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.3941[/C][C]3.60588[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]17.1035[/C][C]-2.10349[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]16.0597[/C][C]-2.05966[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4613[/C][C]0.53868[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]15.004[/C][C]0.99601[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1958[/C][C]-0.195778[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.5452[/C][C]0.454799[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.4976[/C][C]0.50243[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]18.0026[/C][C]-1.00262[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.4967[/C][C]-0.496691[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.5878[/C][C]0.412162[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.4221[/C][C]3.57787[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.5318[/C][C]2.46816[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.5984[/C][C]0.401602[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.3945[/C][C]0.605521[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.2136[/C][C]0.786386[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.4921[/C][C]2.50786[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]15.1609[/C][C]0.839081[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.1484[/C][C]0.851624[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.2218[/C][C]0.778197[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.9084[/C][C]1.09165[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.8091[/C][C]-1.80911[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.6848[/C][C]0.315176[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.263[/C][C]-0.26303[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.766[/C][C]-0.765961[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.8493[/C][C]-0.849289[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.804[/C][C]-0.803962[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]16.0017[/C][C]-0.00174961[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.4902[/C][C]-1.49021[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]13.0305[/C][C]-3.03048[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]13.0355[/C][C]-3.03553[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.747[/C][C]-1.74703[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.5546[/C][C]1.44544[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.4949[/C][C]1.50511[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.7205[/C][C]1.27946[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.701[/C][C]-1.70095[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.4871[/C][C]2.51288[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.1534[/C][C]-0.153378[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.4624[/C][C]-0.462355[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.4909[/C][C]-4.49095[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.6308[/C][C]-2.63076[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.1467[/C][C]-0.146742[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.4179[/C][C]0.582123[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.6302[/C][C]-1.63025[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]17.0253[/C][C]-1.0253[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.1419[/C][C]-0.141941[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]15.0172[/C][C]-3.01719[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]16.0362[/C][C]-0.0361861[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.3433[/C][C]-2.34329[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.385[/C][C]1.61502[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.8545[/C][C]0.14546[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.5299[/C][C]0.470117[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.1124[/C][C]-0.112393[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.2211[/C][C]1.77894[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.5596[/C][C]0.440447[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.6407[/C][C]0.359318[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.5488[/C][C]-0.548817[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.711[/C][C]-0.710986[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.3063[/C][C]0.693679[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.0542[/C][C]0.945814[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.3332[/C][C]1.66682[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.3959[/C][C]3.60411[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.8997[/C][C]-3.89971[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.6516[/C][C]0.348421[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.4124[/C][C]-3.41238[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.9243[/C][C]-0.924295[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.9281[/C][C]1.07194[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.141[/C][C]0.859016[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.2323[/C][C]0.767705[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.4919[/C][C]3.50811[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.4191[/C][C]-0.4191[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.5312[/C][C]1.4688[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.2166[/C][C]-2.21658[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.1421[/C][C]0.85786[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.6586[/C][C]0.341373[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.7632[/C][C]0.236759[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.6434[/C][C]-0.643414[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.8842[/C][C]0.115768[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.1607[/C][C]1.83926[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.1556[/C][C]-0.155569[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.3675[/C][C]0.632512[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.8726[/C][C]1.12741[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.5195[/C][C]0.480519[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.908[/C][C]-1.90797[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.7585[/C][C]0.241506[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.8056[/C][C]0.194438[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.0531[/C][C]-0.0531068[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]15.0299[/C][C]-2.02985[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.7436[/C][C]1.25639[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.7882[/C][C]0.211757[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.6774[/C][C]2.32262[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.7737[/C][C]0.226292[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.4298[/C][C]-0.429782[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]16.9923[/C][C]-0.992298[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.6766[/C][C]1.32338[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.4542[/C][C]2.54578[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.2397[/C][C]0.76034[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.9599[/C][C]1.04014[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.8422[/C][C]-1.8422[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.7017[/C][C]1.29827[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7011[/C][C]0.298877[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.3587[/C][C]1.64135[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.3043[/C][C]-0.304342[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.2857[/C][C]0.714319[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]15.9928[/C][C]0.00717285[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.0564[/C][C]1.94359[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.2812[/C][C]-1.28118[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.5799[/C][C]-2.57987[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.1615[/C][C]1.83853[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.8657[/C][C]-1.86573[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.2289[/C][C]0.771112[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7929[/C][C]-1.79292[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5204[/C][C]0.479616[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.4292[/C][C]-1.42922[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.3854[/C][C]0.614577[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.8212[/C][C]-2.82121[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.8545[/C][C]-0.854504[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.8438[/C][C]-0.843765[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.7849[/C][C]-0.784934[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.6587[/C][C]0.341278[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.4906[/C][C]1.50942[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]14.0483[/C][C]0.951748[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.6859[/C][C]-2.68587[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9403[/C][C]2.05973[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.724[/C][C]-3.72395[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4583[/C][C]2.54167[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.166[/C][C]-2.16599[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.544[/C][C]-1.54405[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.0837[/C][C]-0.0836567[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.1121[/C][C]0.887887[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.5313[/C][C]0.468722[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.499[/C][C]-2.49895[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]13.0065[/C][C]-1.00648[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.34[/C][C]-2.33996[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8565[/C][C]3.1435[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.6441[/C][C]1.35588[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.8414[/C][C]0.158636[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.1244[/C][C]1.8756[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.2668[/C][C]-3.26675[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.4975[/C][C]2.50245[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]14.9458[/C][C]-1.94575[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.843[/C][C]1.15699[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.8272[/C][C]0.172772[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.9005[/C][C]-2.90046[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]15.8784[/C][C]-0.878418[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.8249[/C][C]2.17514[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.8526[/C][C]4.14742[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.3963[/C][C]1.6037[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.4816[/C][C]-2.48163[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.4393[/C][C]0.560693[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.7067[/C][C]1.29331[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.9009[/C][C]1.09907[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.5374[/C][C]1.4626[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.6989[/C][C]-0.698904[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6931[/C][C]0.306895[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.6702[/C][C]0.329796[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.3814[/C][C]-0.381358[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.2131[/C][C]0.786902[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.6682[/C][C]1.33178[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.6198[/C][C]-1.61976[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.3442[/C][C]-0.344192[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.1943[/C][C]-3.19435[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.7896[/C][C]-1.7896[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.3872[/C][C]1.61281[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.4815[/C][C]1.51847[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.3378[/C][C]0.662212[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.8444[/C][C]-1.84444[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.3336[/C][C]-2.33361[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.907[/C][C]-2.90704[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.473[/C][C]0.526992[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.2943[/C][C]-0.294328[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6504[/C][C]-0.650368[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.7939[/C][C]0.206132[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.2889[/C][C]-1.2889[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.0069[/C][C]0.993126[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.4515[/C][C]-0.451506[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]16.7016[/C][C]2.29842[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.111[/C][C]-0.110982[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.597[/C][C]-6.59699[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.6989[/C][C]1.30106[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.3896[/C][C]2.61042[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.3486[/C][C]-0.348623[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.4121[/C][C]-0.41207[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.455[/C][C]0.545032[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.4365[/C][C]-0.436491[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.3764[/C][C]0.623572[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.72248[/C][C]2.27752[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.0886[/C][C]1.91136[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.6329[/C][C]-0.632885[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]14.999[/C][C]0.00102459[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.9126[/C][C]3.08737[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]14.9919[/C][C]1.00806[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4076[/C][C]1.59237[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.4604[/C][C]1.53964[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]14.0333[/C][C]1.96668[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.2955[/C][C]0.704538[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.313[/C][C]-2.31296[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.4949[/C][C]-2.49492[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.6779[/C][C]2.32212[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.4188[/C][C]0.581163[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.532[/C][C]1.46799[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]14.8431[/C][C]1.15687[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.5801[/C][C]-2.58015[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.8886[/C][C]1.11145[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.2038[/C][C]-2.20379[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.7224[/C][C]-3.72243[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.1091[/C][C]0.890921[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.0906[/C][C]2.90942[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.4647[/C][C]1.53526[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.0805[/C][C]0.919486[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.5749[/C][C]2.42513[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.9049[/C][C]0.0950769[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.8321[/C][C]1.16789[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.1299[/C][C]-0.12991[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.5727[/C][C]-1.57269[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]13.8921[/C][C]0.107851[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.2[/C][C]0.800012[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.0555[/C][C]-1.05545[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.2689[/C][C]0.731083[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.6574[/C][C]-3.65737[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.6833[/C][C]0.316721[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.8143[/C][C]1.18571[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.1979[/C][C]-1.19789[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.8304[/C][C]-0.83039[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.1855[/C][C]1.81451[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.2189[/C][C]-3.21891[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.3488[/C][C]4.65121[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.7738[/C][C]2.22625[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.7267[/C][C]-0.726661[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.2216[/C][C]-2.22156[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.9938[/C][C]-6.99382[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.1797[/C][C]-1.17968[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.1367[/C][C]1.86326[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.5931[/C][C]-1.59306[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.1626[/C][C]-0.162645[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.396[/C][C]-1.39602[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.81037[/C][C]1.18963[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]10.9797[/C][C]2.02025[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.5802[/C][C]1.41979[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]11.8071[/C][C]0.192867[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]12.7458[/C][C]1.25417[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.383[/C][C]-2.38303[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.7046[/C][C]1.29544[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5222[/C][C]0.477753[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.7208[/C][C]-0.72083[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.5207[/C][C]-1.5207[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.2737[/C][C]0.726256[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.7075[/C][C]3.2925[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.2079[/C][C]-1.20786[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.7197[/C][C]0.280292[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.1389[/C][C]1.86112[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.5537[/C][C]2.44632[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.0549[/C][C]-1.05494[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.33309[/C][C]-5.33309[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.5531[/C][C]1.4469[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]14.7741[/C][C]-3.77412[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.1662[/C][C]-0.166228[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.6311[/C][C]1.36892[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221927&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221927&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
11316.0985-3.09854
21615.75060.249372
31917.10631.89368
41512.16162.83839
51416.4018-2.40179
61314.847-1.84701
71915.39413.60588
81517.1035-2.10349
91416.0597-2.05966
101514.46130.53868
111615.0040.99601
121616.1958-0.195778
131615.54520.454799
141615.49760.50243
151718.0026-1.00262
161515.4967-0.496691
171514.58780.412162
182016.42213.57787
191815.53182.46816
201615.59840.401602
211615.39450.605521
221615.21360.786386
231916.49212.50786
241615.16090.839081
251716.14840.851624
261716.22180.778197
271614.90841.09165
281516.8091-1.80911
291615.68480.315176
301414.263-0.26303
311515.766-0.765961
321212.8493-0.849289
331414.804-0.803962
341616.0017-0.00174961
351415.4902-1.49021
361013.0305-3.03048
371013.0355-3.03553
381415.747-1.74703
391614.55461.44544
401614.49491.50511
411614.72051.27946
421415.701-1.70095
432017.48712.51288
441414.1534-0.153378
451414.4624-0.462355
461115.4909-4.49095
471416.6308-2.63076
481515.1467-0.146742
491615.41790.582123
501415.6302-1.63025
511617.0253-1.0253
521414.1419-0.141941
531215.0172-3.01719
541616.0362-0.0361861
55911.3433-2.34329
561412.3851.61502
571615.85450.14546
581615.52990.470117
591515.1124-0.112393
601614.22111.77894
611211.55960.440447
621615.64070.359318
631616.5488-0.548817
641414.711-0.710986
651615.30630.693679
661716.05420.945814
671816.33321.66682
681814.39593.60411
691215.8997-3.89971
701615.65160.348421
711013.4124-3.41238
721414.9243-0.924295
731816.92811.07194
741817.1410.859016
751615.23230.767705
761713.49193.50811
771616.4191-0.4191
781614.53121.4688
791315.2166-2.21658
801615.14210.85786
811615.65860.341373
821615.76320.236759
831515.6434-0.643414
841514.88420.115768
851614.16071.83926
861414.1556-0.155569
871615.36750.632512
881614.87261.12741
891514.51950.480519
901213.908-1.90797
911716.75850.241506
921615.80560.194438
931515.0531-0.0531068
941315.0299-2.02985
951614.74361.25639
961615.78820.211757
971613.67742.32262
981615.77370.226292
991414.4298-0.429782
1001616.9923-0.992298
1011614.67661.32338
1022017.45422.54578
1031514.23970.76034
1041614.95991.04014
1051314.8422-1.8422
1061715.70171.29827
1071615.70110.298877
1081614.35871.64135
1091212.3043-0.304342
1101615.28570.714319
1111615.99280.00717285
1121715.05641.94359
1131314.2812-1.28118
1141214.5799-2.57987
1151816.16151.83853
1161415.8657-1.86573
1171413.22890.771112
1181314.7929-1.79292
1191615.52040.479616
1201314.4292-1.42922
1211615.38540.614577
1221315.8212-2.82121
1231616.8545-0.854504
1241515.8438-0.843765
1251616.7849-0.784934
1261514.65870.341278
1271715.49061.50942
1281514.04830.951748
1291214.6859-2.68587
1301613.94032.05973
1311013.724-3.72395
1321613.45832.54167
1331214.166-2.16599
1341415.544-1.54405
1351515.0837-0.0836567
1361312.11210.887887
1371514.53130.468722
1381113.499-2.49895
1391213.0065-1.00648
1401113.34-2.33996
1411612.85653.1435
1421513.64411.35588
1431716.84140.158636
1441614.12441.8756
1451013.2668-3.26675
1461815.49752.50245
1471314.9458-1.94575
1481614.8431.15699
1491312.82720.172772
1501012.9005-2.90046
1511515.8784-0.878418
1521613.82492.17514
1531611.85264.14742
1541412.39631.6037
1551012.4816-2.48163
1561716.43930.560693
1571311.70671.29331
1581513.90091.09907
1591614.53741.4626
1601212.6989-0.698904
1611312.69310.306895
1621312.67020.329796
1631212.3814-0.381358
1641716.21310.786902
1651513.66821.33178
1661011.6198-1.61976
1671414.3442-0.344192
1681114.1943-3.19435
1691314.7896-1.7896
1701614.38721.61281
1711210.48151.51847
1721615.33780.662212
1731213.8444-1.84444
174911.3336-2.33361
1751214.907-2.90704
1761514.4730.526992
1771212.2943-0.294328
1781212.6504-0.650368
1791413.79390.206132
1801213.2889-1.2889
1811615.00690.993126
1821111.4515-0.451506
1831916.70162.29842
1841515.111-0.110982
185814.597-6.59699
1861614.69891.30106
1871714.38962.61042
1881212.3486-0.348623
1891111.4121-0.41207
1901110.4550.545032
1911414.4365-0.436491
1921615.37640.623572
193129.722482.27752
1941614.08861.91136
1951313.6329-0.632885
1961514.9990.00102459
1971612.91263.08737
1981614.99191.00806
1991412.40761.59237
2001614.46041.53964
2011614.03331.96668
2021413.29550.704538
2031113.313-2.31296
2041214.4949-2.49492
2051512.67792.32212
2061514.41880.581163
2071614.5321.46799
2081614.84311.15687
2091113.5801-2.58015
2101513.88861.11145
2111214.2038-2.20379
2121215.7224-3.72243
2131514.10910.890921
2141512.09062.90942
2151614.46471.53526
2161413.08050.919486
2171714.57492.42513
2181413.90490.0950769
2191311.83211.16789
2201515.1299-0.12991
2211314.5727-1.57269
2221413.89210.107851
2231514.20.800012
2241213.0555-1.05545
2251312.26890.731083
226811.6574-3.65737
2271413.68330.316721
2281412.81431.18571
2291112.1979-1.19789
2301212.8304-0.83039
2311311.18551.81451
2321013.2189-3.21891
2331611.34884.65121
2341815.77382.22625
2351313.7267-0.726661
2361113.2216-2.22156
237410.9938-6.99382
2381314.1797-1.17968
2391614.13671.86326
2401011.5931-1.59306
2411212.1626-0.162645
2421213.396-1.39602
243108.810371.18963
2441310.97972.02025
2451513.58021.41979
2461211.80710.192867
2471412.74581.25417
2481012.383-2.38303
2491210.70461.29544
2501211.52220.477753
2511111.7208-0.72083
2521011.5207-1.5207
2531211.27370.726256
2541612.70753.2925
2551213.2079-1.20786
2561413.71970.280292
2571614.13891.86112
2581411.55372.44632
2591314.0549-1.05494
26049.33309-5.33309
2611513.55311.4469
2621114.7741-3.77412
2631111.1662-0.166228
2641412.63111.36892






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.4024750.804950.597525
120.7998130.4003740.200187
130.7608270.4783470.239173
140.6735530.6528950.326447
150.6181150.7637710.381885
160.6808330.6383340.319167
170.6081430.7837150.391857
180.8576940.2846110.142306
190.830980.3380390.16902
200.7804670.4390650.219533
210.7164350.567130.283565
220.6779250.644150.322075
230.6400810.7198390.359919
240.6080030.7839940.391997
250.5446030.9107950.455397
260.4951190.9902380.504881
270.4356950.871390.564305
280.4894290.9788570.510571
290.4295310.8590620.570469
300.4391110.8782210.560889
310.3907780.7815550.609222
320.3865360.7730730.613464
330.3675740.7351470.632426
340.3119460.6238920.688054
350.300790.601580.69921
360.3994470.7988940.600553
370.4802340.9604670.519766
380.4564140.9128290.543586
390.5040370.9919260.495963
400.4846630.9693250.515337
410.4489820.8979630.551018
420.4193310.8386620.580669
430.4354890.8709780.564511
440.3883570.7767140.611643
450.3497840.6995690.650216
460.574490.8510190.42551
470.5925140.8149720.407486
480.5540650.891870.445935
490.5413440.9173120.458656
500.5141860.9716280.485814
510.4699710.9399420.530029
520.4284280.8568550.571572
530.4356610.8713230.564339
540.4060090.8120180.593991
550.4042780.8085550.595722
560.4207350.8414690.579265
570.3801420.7602830.619858
580.3656290.7312580.634371
590.3265080.6530160.673492
600.3533720.7067440.646628
610.327220.6544410.67278
620.2931320.5862640.706868
630.2591180.5182350.740882
640.2265140.4530290.773486
650.2029090.4058190.797091
660.1931320.3862640.806868
670.1958310.3916620.804169
680.3093030.6186060.690697
690.4222180.8444370.577782
700.3901980.7803950.609802
710.4626710.9253420.537329
720.4277990.8555990.572201
730.4210240.8420490.578976
740.3996320.7992640.600368
750.3635920.7271840.636408
760.4415620.8831230.558438
770.4034170.8068330.596583
780.3826230.7652460.617377
790.3920520.7841040.607948
800.3577740.7155480.642226
810.3260490.6520980.673951
820.2940410.5880820.705959
830.267060.5341190.73294
840.2370940.4741880.762906
850.234220.4684390.76578
860.2054570.4109150.794543
870.182360.364720.81764
880.1686670.3373340.831333
890.1460350.2920710.853965
900.1414010.2828030.858599
910.1214530.2429070.878547
920.1055380.2110770.894462
930.09047320.1809460.909527
940.09445170.1889030.905548
950.08514530.1702910.914855
960.07134380.1426880.928656
970.0765390.1530780.923461
980.06391730.1278350.936083
990.05325610.1065120.946744
1000.04719650.09439290.952804
1010.04182380.08364750.958176
1020.04956470.09912930.950435
1030.04181590.08363190.958184
1040.03715460.07430920.962845
1050.044380.08875990.95562
1060.03924670.07849340.960753
1070.03210150.06420310.967898
1080.0306390.06127790.969361
1090.02497670.04995330.975023
1100.02068030.04136060.97932
1110.01653670.03307340.983463
1120.01746110.03492220.982539
1130.01518680.03037360.984813
1140.02034280.04068560.979657
1150.01955460.03910920.980445
1160.01915660.03831320.980843
1170.01618950.03237910.98381
1180.01614290.03228580.983857
1190.01311160.02622320.986888
1200.01185130.02370260.988149
1210.009611390.01922280.990389
1220.01429760.02859520.985702
1230.01191820.02383650.988082
1240.01004170.02008340.989958
1250.008203860.01640770.991796
1260.006524020.0130480.993476
1270.005924990.011850.994075
1280.004989580.009979160.99501
1290.006796770.01359350.993203
1300.007378960.01475790.992621
1310.0150380.0300760.984962
1320.0179020.0358040.982098
1330.01900140.03800290.980999
1340.017940.03587990.98206
1350.01432810.02865620.985672
1360.01223090.02446190.987769
1370.009906490.0198130.990094
1380.01253840.02507680.987462
1390.01076180.02152360.989238
1400.01290530.02581060.987095
1410.0201560.0403120.979844
1420.01852430.03704860.981476
1430.01502050.03004110.984979
1440.01572360.03144720.984276
1450.02669750.05339490.973303
1460.03289930.06579860.967101
1470.03471070.06942130.965289
1480.03082680.06165360.969173
1490.02516940.05033890.974831
1500.03474320.06948630.965257
1510.0295650.05912990.970435
1520.03121190.06242380.968788
1530.06149220.1229840.938508
1540.05926930.1185390.940731
1550.06685150.1337030.933149
1560.05688280.1137660.943117
1570.05072640.1014530.949274
1580.04430690.08861390.955693
1590.04289640.08579270.957104
1600.03682890.07365790.963171
1610.03014940.06029880.969851
1620.02468830.04937650.975312
1630.02045570.04091140.979544
1640.01746630.03493270.982534
1650.015290.03057990.98471
1660.01621590.03243170.983784
1670.01295190.02590380.987048
1680.01900980.03801960.98099
1690.01931450.0386290.980685
1700.01780190.03560390.982198
1710.01632720.03265440.983673
1720.01317770.02635530.986822
1730.01281280.02562560.987187
1740.0146860.02937190.985314
1750.0188930.0377860.981107
1760.01514540.03029080.984855
1770.01198090.02396170.988019
1780.01007820.02015630.989922
1790.007837990.0156760.992162
1800.006892280.01378460.993108
1810.005579290.01115860.994421
1820.00430170.00860340.995698
1830.004542720.009085450.995457
1840.003463410.006926820.996537
1850.09454860.1890970.905451
1860.08376730.1675350.916233
1870.0937320.1874640.906268
1880.07914220.1582840.920858
1890.07054190.1410840.929458
1900.05967060.1193410.940329
1910.05168880.1033780.948311
1920.0430110.0860220.956989
1930.04331210.08662420.956688
1940.04106970.08213930.95893
1950.03570280.07140550.964297
1960.0284550.056910.971545
1970.03732220.07464450.962678
1980.03051950.0610390.969481
1990.02740580.05481160.972594
2000.02327650.04655310.976723
2010.02131140.04262270.978689
2020.01781660.03563310.982183
2030.01984690.03969380.980153
2040.02636750.0527350.973632
2050.02782370.05564740.972176
2060.02175030.04350070.97825
2070.01938690.03877390.980613
2080.01549040.03098070.98451
2090.01807790.03615580.981922
2100.01496370.02992740.985036
2110.01839580.03679170.981604
2120.03247180.06494350.967528
2130.02537110.05074220.974629
2140.03147910.06295820.968521
2150.02676130.05352250.973239
2160.02072940.04145870.979271
2170.02313710.04627410.976863
2180.01960680.03921350.980393
2190.01829440.03658880.981706
2200.01374190.02748380.986258
2210.01140250.0228050.988597
2220.008311550.01662310.991688
2230.006416310.01283260.993584
2240.004916910.009833820.995083
2250.00343960.00687920.99656
2260.007101990.0142040.992898
2270.005651570.01130310.994348
2280.004122620.008245240.995877
2290.002931620.005863240.997068
2300.002075990.004151980.997924
2310.002268510.004537020.997731
2320.007798520.0155970.992201
2330.02936980.05873970.97063
2340.04495070.08990150.955049
2350.03309140.06618280.966909
2360.02710120.05420230.972899
2370.2389590.4779180.761041
2380.1929490.3858990.807051
2390.163290.326580.83671
2400.1304480.2608950.869552
2410.1168170.2336350.883183
2420.1779080.3558160.822092
2430.1504540.3009080.849546
2440.1514530.3029060.848547
2450.1328520.2657040.867148
2460.1164760.2329520.883524
2470.07925630.1585130.920744
2480.07042910.1408580.929571
2490.05349780.1069960.946502
2500.130780.261560.86922
2510.1074730.2149460.892527
2520.5439780.9120430.456022
2530.3822890.7645770.617711

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.402475 & 0.80495 & 0.597525 \tabularnewline
12 & 0.799813 & 0.400374 & 0.200187 \tabularnewline
13 & 0.760827 & 0.478347 & 0.239173 \tabularnewline
14 & 0.673553 & 0.652895 & 0.326447 \tabularnewline
15 & 0.618115 & 0.763771 & 0.381885 \tabularnewline
16 & 0.680833 & 0.638334 & 0.319167 \tabularnewline
17 & 0.608143 & 0.783715 & 0.391857 \tabularnewline
18 & 0.857694 & 0.284611 & 0.142306 \tabularnewline
19 & 0.83098 & 0.338039 & 0.16902 \tabularnewline
20 & 0.780467 & 0.439065 & 0.219533 \tabularnewline
21 & 0.716435 & 0.56713 & 0.283565 \tabularnewline
22 & 0.677925 & 0.64415 & 0.322075 \tabularnewline
23 & 0.640081 & 0.719839 & 0.359919 \tabularnewline
24 & 0.608003 & 0.783994 & 0.391997 \tabularnewline
25 & 0.544603 & 0.910795 & 0.455397 \tabularnewline
26 & 0.495119 & 0.990238 & 0.504881 \tabularnewline
27 & 0.435695 & 0.87139 & 0.564305 \tabularnewline
28 & 0.489429 & 0.978857 & 0.510571 \tabularnewline
29 & 0.429531 & 0.859062 & 0.570469 \tabularnewline
30 & 0.439111 & 0.878221 & 0.560889 \tabularnewline
31 & 0.390778 & 0.781555 & 0.609222 \tabularnewline
32 & 0.386536 & 0.773073 & 0.613464 \tabularnewline
33 & 0.367574 & 0.735147 & 0.632426 \tabularnewline
34 & 0.311946 & 0.623892 & 0.688054 \tabularnewline
35 & 0.30079 & 0.60158 & 0.69921 \tabularnewline
36 & 0.399447 & 0.798894 & 0.600553 \tabularnewline
37 & 0.480234 & 0.960467 & 0.519766 \tabularnewline
38 & 0.456414 & 0.912829 & 0.543586 \tabularnewline
39 & 0.504037 & 0.991926 & 0.495963 \tabularnewline
40 & 0.484663 & 0.969325 & 0.515337 \tabularnewline
41 & 0.448982 & 0.897963 & 0.551018 \tabularnewline
42 & 0.419331 & 0.838662 & 0.580669 \tabularnewline
43 & 0.435489 & 0.870978 & 0.564511 \tabularnewline
44 & 0.388357 & 0.776714 & 0.611643 \tabularnewline
45 & 0.349784 & 0.699569 & 0.650216 \tabularnewline
46 & 0.57449 & 0.851019 & 0.42551 \tabularnewline
47 & 0.592514 & 0.814972 & 0.407486 \tabularnewline
48 & 0.554065 & 0.89187 & 0.445935 \tabularnewline
49 & 0.541344 & 0.917312 & 0.458656 \tabularnewline
50 & 0.514186 & 0.971628 & 0.485814 \tabularnewline
51 & 0.469971 & 0.939942 & 0.530029 \tabularnewline
52 & 0.428428 & 0.856855 & 0.571572 \tabularnewline
53 & 0.435661 & 0.871323 & 0.564339 \tabularnewline
54 & 0.406009 & 0.812018 & 0.593991 \tabularnewline
55 & 0.404278 & 0.808555 & 0.595722 \tabularnewline
56 & 0.420735 & 0.841469 & 0.579265 \tabularnewline
57 & 0.380142 & 0.760283 & 0.619858 \tabularnewline
58 & 0.365629 & 0.731258 & 0.634371 \tabularnewline
59 & 0.326508 & 0.653016 & 0.673492 \tabularnewline
60 & 0.353372 & 0.706744 & 0.646628 \tabularnewline
61 & 0.32722 & 0.654441 & 0.67278 \tabularnewline
62 & 0.293132 & 0.586264 & 0.706868 \tabularnewline
63 & 0.259118 & 0.518235 & 0.740882 \tabularnewline
64 & 0.226514 & 0.453029 & 0.773486 \tabularnewline
65 & 0.202909 & 0.405819 & 0.797091 \tabularnewline
66 & 0.193132 & 0.386264 & 0.806868 \tabularnewline
67 & 0.195831 & 0.391662 & 0.804169 \tabularnewline
68 & 0.309303 & 0.618606 & 0.690697 \tabularnewline
69 & 0.422218 & 0.844437 & 0.577782 \tabularnewline
70 & 0.390198 & 0.780395 & 0.609802 \tabularnewline
71 & 0.462671 & 0.925342 & 0.537329 \tabularnewline
72 & 0.427799 & 0.855599 & 0.572201 \tabularnewline
73 & 0.421024 & 0.842049 & 0.578976 \tabularnewline
74 & 0.399632 & 0.799264 & 0.600368 \tabularnewline
75 & 0.363592 & 0.727184 & 0.636408 \tabularnewline
76 & 0.441562 & 0.883123 & 0.558438 \tabularnewline
77 & 0.403417 & 0.806833 & 0.596583 \tabularnewline
78 & 0.382623 & 0.765246 & 0.617377 \tabularnewline
79 & 0.392052 & 0.784104 & 0.607948 \tabularnewline
80 & 0.357774 & 0.715548 & 0.642226 \tabularnewline
81 & 0.326049 & 0.652098 & 0.673951 \tabularnewline
82 & 0.294041 & 0.588082 & 0.705959 \tabularnewline
83 & 0.26706 & 0.534119 & 0.73294 \tabularnewline
84 & 0.237094 & 0.474188 & 0.762906 \tabularnewline
85 & 0.23422 & 0.468439 & 0.76578 \tabularnewline
86 & 0.205457 & 0.410915 & 0.794543 \tabularnewline
87 & 0.18236 & 0.36472 & 0.81764 \tabularnewline
88 & 0.168667 & 0.337334 & 0.831333 \tabularnewline
89 & 0.146035 & 0.292071 & 0.853965 \tabularnewline
90 & 0.141401 & 0.282803 & 0.858599 \tabularnewline
91 & 0.121453 & 0.242907 & 0.878547 \tabularnewline
92 & 0.105538 & 0.211077 & 0.894462 \tabularnewline
93 & 0.0904732 & 0.180946 & 0.909527 \tabularnewline
94 & 0.0944517 & 0.188903 & 0.905548 \tabularnewline
95 & 0.0851453 & 0.170291 & 0.914855 \tabularnewline
96 & 0.0713438 & 0.142688 & 0.928656 \tabularnewline
97 & 0.076539 & 0.153078 & 0.923461 \tabularnewline
98 & 0.0639173 & 0.127835 & 0.936083 \tabularnewline
99 & 0.0532561 & 0.106512 & 0.946744 \tabularnewline
100 & 0.0471965 & 0.0943929 & 0.952804 \tabularnewline
101 & 0.0418238 & 0.0836475 & 0.958176 \tabularnewline
102 & 0.0495647 & 0.0991293 & 0.950435 \tabularnewline
103 & 0.0418159 & 0.0836319 & 0.958184 \tabularnewline
104 & 0.0371546 & 0.0743092 & 0.962845 \tabularnewline
105 & 0.04438 & 0.0887599 & 0.95562 \tabularnewline
106 & 0.0392467 & 0.0784934 & 0.960753 \tabularnewline
107 & 0.0321015 & 0.0642031 & 0.967898 \tabularnewline
108 & 0.030639 & 0.0612779 & 0.969361 \tabularnewline
109 & 0.0249767 & 0.0499533 & 0.975023 \tabularnewline
110 & 0.0206803 & 0.0413606 & 0.97932 \tabularnewline
111 & 0.0165367 & 0.0330734 & 0.983463 \tabularnewline
112 & 0.0174611 & 0.0349222 & 0.982539 \tabularnewline
113 & 0.0151868 & 0.0303736 & 0.984813 \tabularnewline
114 & 0.0203428 & 0.0406856 & 0.979657 \tabularnewline
115 & 0.0195546 & 0.0391092 & 0.980445 \tabularnewline
116 & 0.0191566 & 0.0383132 & 0.980843 \tabularnewline
117 & 0.0161895 & 0.0323791 & 0.98381 \tabularnewline
118 & 0.0161429 & 0.0322858 & 0.983857 \tabularnewline
119 & 0.0131116 & 0.0262232 & 0.986888 \tabularnewline
120 & 0.0118513 & 0.0237026 & 0.988149 \tabularnewline
121 & 0.00961139 & 0.0192228 & 0.990389 \tabularnewline
122 & 0.0142976 & 0.0285952 & 0.985702 \tabularnewline
123 & 0.0119182 & 0.0238365 & 0.988082 \tabularnewline
124 & 0.0100417 & 0.0200834 & 0.989958 \tabularnewline
125 & 0.00820386 & 0.0164077 & 0.991796 \tabularnewline
126 & 0.00652402 & 0.013048 & 0.993476 \tabularnewline
127 & 0.00592499 & 0.01185 & 0.994075 \tabularnewline
128 & 0.00498958 & 0.00997916 & 0.99501 \tabularnewline
129 & 0.00679677 & 0.0135935 & 0.993203 \tabularnewline
130 & 0.00737896 & 0.0147579 & 0.992621 \tabularnewline
131 & 0.015038 & 0.030076 & 0.984962 \tabularnewline
132 & 0.017902 & 0.035804 & 0.982098 \tabularnewline
133 & 0.0190014 & 0.0380029 & 0.980999 \tabularnewline
134 & 0.01794 & 0.0358799 & 0.98206 \tabularnewline
135 & 0.0143281 & 0.0286562 & 0.985672 \tabularnewline
136 & 0.0122309 & 0.0244619 & 0.987769 \tabularnewline
137 & 0.00990649 & 0.019813 & 0.990094 \tabularnewline
138 & 0.0125384 & 0.0250768 & 0.987462 \tabularnewline
139 & 0.0107618 & 0.0215236 & 0.989238 \tabularnewline
140 & 0.0129053 & 0.0258106 & 0.987095 \tabularnewline
141 & 0.020156 & 0.040312 & 0.979844 \tabularnewline
142 & 0.0185243 & 0.0370486 & 0.981476 \tabularnewline
143 & 0.0150205 & 0.0300411 & 0.984979 \tabularnewline
144 & 0.0157236 & 0.0314472 & 0.984276 \tabularnewline
145 & 0.0266975 & 0.0533949 & 0.973303 \tabularnewline
146 & 0.0328993 & 0.0657986 & 0.967101 \tabularnewline
147 & 0.0347107 & 0.0694213 & 0.965289 \tabularnewline
148 & 0.0308268 & 0.0616536 & 0.969173 \tabularnewline
149 & 0.0251694 & 0.0503389 & 0.974831 \tabularnewline
150 & 0.0347432 & 0.0694863 & 0.965257 \tabularnewline
151 & 0.029565 & 0.0591299 & 0.970435 \tabularnewline
152 & 0.0312119 & 0.0624238 & 0.968788 \tabularnewline
153 & 0.0614922 & 0.122984 & 0.938508 \tabularnewline
154 & 0.0592693 & 0.118539 & 0.940731 \tabularnewline
155 & 0.0668515 & 0.133703 & 0.933149 \tabularnewline
156 & 0.0568828 & 0.113766 & 0.943117 \tabularnewline
157 & 0.0507264 & 0.101453 & 0.949274 \tabularnewline
158 & 0.0443069 & 0.0886139 & 0.955693 \tabularnewline
159 & 0.0428964 & 0.0857927 & 0.957104 \tabularnewline
160 & 0.0368289 & 0.0736579 & 0.963171 \tabularnewline
161 & 0.0301494 & 0.0602988 & 0.969851 \tabularnewline
162 & 0.0246883 & 0.0493765 & 0.975312 \tabularnewline
163 & 0.0204557 & 0.0409114 & 0.979544 \tabularnewline
164 & 0.0174663 & 0.0349327 & 0.982534 \tabularnewline
165 & 0.01529 & 0.0305799 & 0.98471 \tabularnewline
166 & 0.0162159 & 0.0324317 & 0.983784 \tabularnewline
167 & 0.0129519 & 0.0259038 & 0.987048 \tabularnewline
168 & 0.0190098 & 0.0380196 & 0.98099 \tabularnewline
169 & 0.0193145 & 0.038629 & 0.980685 \tabularnewline
170 & 0.0178019 & 0.0356039 & 0.982198 \tabularnewline
171 & 0.0163272 & 0.0326544 & 0.983673 \tabularnewline
172 & 0.0131777 & 0.0263553 & 0.986822 \tabularnewline
173 & 0.0128128 & 0.0256256 & 0.987187 \tabularnewline
174 & 0.014686 & 0.0293719 & 0.985314 \tabularnewline
175 & 0.018893 & 0.037786 & 0.981107 \tabularnewline
176 & 0.0151454 & 0.0302908 & 0.984855 \tabularnewline
177 & 0.0119809 & 0.0239617 & 0.988019 \tabularnewline
178 & 0.0100782 & 0.0201563 & 0.989922 \tabularnewline
179 & 0.00783799 & 0.015676 & 0.992162 \tabularnewline
180 & 0.00689228 & 0.0137846 & 0.993108 \tabularnewline
181 & 0.00557929 & 0.0111586 & 0.994421 \tabularnewline
182 & 0.0043017 & 0.0086034 & 0.995698 \tabularnewline
183 & 0.00454272 & 0.00908545 & 0.995457 \tabularnewline
184 & 0.00346341 & 0.00692682 & 0.996537 \tabularnewline
185 & 0.0945486 & 0.189097 & 0.905451 \tabularnewline
186 & 0.0837673 & 0.167535 & 0.916233 \tabularnewline
187 & 0.093732 & 0.187464 & 0.906268 \tabularnewline
188 & 0.0791422 & 0.158284 & 0.920858 \tabularnewline
189 & 0.0705419 & 0.141084 & 0.929458 \tabularnewline
190 & 0.0596706 & 0.119341 & 0.940329 \tabularnewline
191 & 0.0516888 & 0.103378 & 0.948311 \tabularnewline
192 & 0.043011 & 0.086022 & 0.956989 \tabularnewline
193 & 0.0433121 & 0.0866242 & 0.956688 \tabularnewline
194 & 0.0410697 & 0.0821393 & 0.95893 \tabularnewline
195 & 0.0357028 & 0.0714055 & 0.964297 \tabularnewline
196 & 0.028455 & 0.05691 & 0.971545 \tabularnewline
197 & 0.0373222 & 0.0746445 & 0.962678 \tabularnewline
198 & 0.0305195 & 0.061039 & 0.969481 \tabularnewline
199 & 0.0274058 & 0.0548116 & 0.972594 \tabularnewline
200 & 0.0232765 & 0.0465531 & 0.976723 \tabularnewline
201 & 0.0213114 & 0.0426227 & 0.978689 \tabularnewline
202 & 0.0178166 & 0.0356331 & 0.982183 \tabularnewline
203 & 0.0198469 & 0.0396938 & 0.980153 \tabularnewline
204 & 0.0263675 & 0.052735 & 0.973632 \tabularnewline
205 & 0.0278237 & 0.0556474 & 0.972176 \tabularnewline
206 & 0.0217503 & 0.0435007 & 0.97825 \tabularnewline
207 & 0.0193869 & 0.0387739 & 0.980613 \tabularnewline
208 & 0.0154904 & 0.0309807 & 0.98451 \tabularnewline
209 & 0.0180779 & 0.0361558 & 0.981922 \tabularnewline
210 & 0.0149637 & 0.0299274 & 0.985036 \tabularnewline
211 & 0.0183958 & 0.0367917 & 0.981604 \tabularnewline
212 & 0.0324718 & 0.0649435 & 0.967528 \tabularnewline
213 & 0.0253711 & 0.0507422 & 0.974629 \tabularnewline
214 & 0.0314791 & 0.0629582 & 0.968521 \tabularnewline
215 & 0.0267613 & 0.0535225 & 0.973239 \tabularnewline
216 & 0.0207294 & 0.0414587 & 0.979271 \tabularnewline
217 & 0.0231371 & 0.0462741 & 0.976863 \tabularnewline
218 & 0.0196068 & 0.0392135 & 0.980393 \tabularnewline
219 & 0.0182944 & 0.0365888 & 0.981706 \tabularnewline
220 & 0.0137419 & 0.0274838 & 0.986258 \tabularnewline
221 & 0.0114025 & 0.022805 & 0.988597 \tabularnewline
222 & 0.00831155 & 0.0166231 & 0.991688 \tabularnewline
223 & 0.00641631 & 0.0128326 & 0.993584 \tabularnewline
224 & 0.00491691 & 0.00983382 & 0.995083 \tabularnewline
225 & 0.0034396 & 0.0068792 & 0.99656 \tabularnewline
226 & 0.00710199 & 0.014204 & 0.992898 \tabularnewline
227 & 0.00565157 & 0.0113031 & 0.994348 \tabularnewline
228 & 0.00412262 & 0.00824524 & 0.995877 \tabularnewline
229 & 0.00293162 & 0.00586324 & 0.997068 \tabularnewline
230 & 0.00207599 & 0.00415198 & 0.997924 \tabularnewline
231 & 0.00226851 & 0.00453702 & 0.997731 \tabularnewline
232 & 0.00779852 & 0.015597 & 0.992201 \tabularnewline
233 & 0.0293698 & 0.0587397 & 0.97063 \tabularnewline
234 & 0.0449507 & 0.0899015 & 0.955049 \tabularnewline
235 & 0.0330914 & 0.0661828 & 0.966909 \tabularnewline
236 & 0.0271012 & 0.0542023 & 0.972899 \tabularnewline
237 & 0.238959 & 0.477918 & 0.761041 \tabularnewline
238 & 0.192949 & 0.385899 & 0.807051 \tabularnewline
239 & 0.16329 & 0.32658 & 0.83671 \tabularnewline
240 & 0.130448 & 0.260895 & 0.869552 \tabularnewline
241 & 0.116817 & 0.233635 & 0.883183 \tabularnewline
242 & 0.177908 & 0.355816 & 0.822092 \tabularnewline
243 & 0.150454 & 0.300908 & 0.849546 \tabularnewline
244 & 0.151453 & 0.302906 & 0.848547 \tabularnewline
245 & 0.132852 & 0.265704 & 0.867148 \tabularnewline
246 & 0.116476 & 0.232952 & 0.883524 \tabularnewline
247 & 0.0792563 & 0.158513 & 0.920744 \tabularnewline
248 & 0.0704291 & 0.140858 & 0.929571 \tabularnewline
249 & 0.0534978 & 0.106996 & 0.946502 \tabularnewline
250 & 0.13078 & 0.26156 & 0.86922 \tabularnewline
251 & 0.107473 & 0.214946 & 0.892527 \tabularnewline
252 & 0.543978 & 0.912043 & 0.456022 \tabularnewline
253 & 0.382289 & 0.764577 & 0.617711 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221927&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]0.402475[/C][C]0.80495[/C][C]0.597525[/C][/ROW]
[ROW][C]12[/C][C]0.799813[/C][C]0.400374[/C][C]0.200187[/C][/ROW]
[ROW][C]13[/C][C]0.760827[/C][C]0.478347[/C][C]0.239173[/C][/ROW]
[ROW][C]14[/C][C]0.673553[/C][C]0.652895[/C][C]0.326447[/C][/ROW]
[ROW][C]15[/C][C]0.618115[/C][C]0.763771[/C][C]0.381885[/C][/ROW]
[ROW][C]16[/C][C]0.680833[/C][C]0.638334[/C][C]0.319167[/C][/ROW]
[ROW][C]17[/C][C]0.608143[/C][C]0.783715[/C][C]0.391857[/C][/ROW]
[ROW][C]18[/C][C]0.857694[/C][C]0.284611[/C][C]0.142306[/C][/ROW]
[ROW][C]19[/C][C]0.83098[/C][C]0.338039[/C][C]0.16902[/C][/ROW]
[ROW][C]20[/C][C]0.780467[/C][C]0.439065[/C][C]0.219533[/C][/ROW]
[ROW][C]21[/C][C]0.716435[/C][C]0.56713[/C][C]0.283565[/C][/ROW]
[ROW][C]22[/C][C]0.677925[/C][C]0.64415[/C][C]0.322075[/C][/ROW]
[ROW][C]23[/C][C]0.640081[/C][C]0.719839[/C][C]0.359919[/C][/ROW]
[ROW][C]24[/C][C]0.608003[/C][C]0.783994[/C][C]0.391997[/C][/ROW]
[ROW][C]25[/C][C]0.544603[/C][C]0.910795[/C][C]0.455397[/C][/ROW]
[ROW][C]26[/C][C]0.495119[/C][C]0.990238[/C][C]0.504881[/C][/ROW]
[ROW][C]27[/C][C]0.435695[/C][C]0.87139[/C][C]0.564305[/C][/ROW]
[ROW][C]28[/C][C]0.489429[/C][C]0.978857[/C][C]0.510571[/C][/ROW]
[ROW][C]29[/C][C]0.429531[/C][C]0.859062[/C][C]0.570469[/C][/ROW]
[ROW][C]30[/C][C]0.439111[/C][C]0.878221[/C][C]0.560889[/C][/ROW]
[ROW][C]31[/C][C]0.390778[/C][C]0.781555[/C][C]0.609222[/C][/ROW]
[ROW][C]32[/C][C]0.386536[/C][C]0.773073[/C][C]0.613464[/C][/ROW]
[ROW][C]33[/C][C]0.367574[/C][C]0.735147[/C][C]0.632426[/C][/ROW]
[ROW][C]34[/C][C]0.311946[/C][C]0.623892[/C][C]0.688054[/C][/ROW]
[ROW][C]35[/C][C]0.30079[/C][C]0.60158[/C][C]0.69921[/C][/ROW]
[ROW][C]36[/C][C]0.399447[/C][C]0.798894[/C][C]0.600553[/C][/ROW]
[ROW][C]37[/C][C]0.480234[/C][C]0.960467[/C][C]0.519766[/C][/ROW]
[ROW][C]38[/C][C]0.456414[/C][C]0.912829[/C][C]0.543586[/C][/ROW]
[ROW][C]39[/C][C]0.504037[/C][C]0.991926[/C][C]0.495963[/C][/ROW]
[ROW][C]40[/C][C]0.484663[/C][C]0.969325[/C][C]0.515337[/C][/ROW]
[ROW][C]41[/C][C]0.448982[/C][C]0.897963[/C][C]0.551018[/C][/ROW]
[ROW][C]42[/C][C]0.419331[/C][C]0.838662[/C][C]0.580669[/C][/ROW]
[ROW][C]43[/C][C]0.435489[/C][C]0.870978[/C][C]0.564511[/C][/ROW]
[ROW][C]44[/C][C]0.388357[/C][C]0.776714[/C][C]0.611643[/C][/ROW]
[ROW][C]45[/C][C]0.349784[/C][C]0.699569[/C][C]0.650216[/C][/ROW]
[ROW][C]46[/C][C]0.57449[/C][C]0.851019[/C][C]0.42551[/C][/ROW]
[ROW][C]47[/C][C]0.592514[/C][C]0.814972[/C][C]0.407486[/C][/ROW]
[ROW][C]48[/C][C]0.554065[/C][C]0.89187[/C][C]0.445935[/C][/ROW]
[ROW][C]49[/C][C]0.541344[/C][C]0.917312[/C][C]0.458656[/C][/ROW]
[ROW][C]50[/C][C]0.514186[/C][C]0.971628[/C][C]0.485814[/C][/ROW]
[ROW][C]51[/C][C]0.469971[/C][C]0.939942[/C][C]0.530029[/C][/ROW]
[ROW][C]52[/C][C]0.428428[/C][C]0.856855[/C][C]0.571572[/C][/ROW]
[ROW][C]53[/C][C]0.435661[/C][C]0.871323[/C][C]0.564339[/C][/ROW]
[ROW][C]54[/C][C]0.406009[/C][C]0.812018[/C][C]0.593991[/C][/ROW]
[ROW][C]55[/C][C]0.404278[/C][C]0.808555[/C][C]0.595722[/C][/ROW]
[ROW][C]56[/C][C]0.420735[/C][C]0.841469[/C][C]0.579265[/C][/ROW]
[ROW][C]57[/C][C]0.380142[/C][C]0.760283[/C][C]0.619858[/C][/ROW]
[ROW][C]58[/C][C]0.365629[/C][C]0.731258[/C][C]0.634371[/C][/ROW]
[ROW][C]59[/C][C]0.326508[/C][C]0.653016[/C][C]0.673492[/C][/ROW]
[ROW][C]60[/C][C]0.353372[/C][C]0.706744[/C][C]0.646628[/C][/ROW]
[ROW][C]61[/C][C]0.32722[/C][C]0.654441[/C][C]0.67278[/C][/ROW]
[ROW][C]62[/C][C]0.293132[/C][C]0.586264[/C][C]0.706868[/C][/ROW]
[ROW][C]63[/C][C]0.259118[/C][C]0.518235[/C][C]0.740882[/C][/ROW]
[ROW][C]64[/C][C]0.226514[/C][C]0.453029[/C][C]0.773486[/C][/ROW]
[ROW][C]65[/C][C]0.202909[/C][C]0.405819[/C][C]0.797091[/C][/ROW]
[ROW][C]66[/C][C]0.193132[/C][C]0.386264[/C][C]0.806868[/C][/ROW]
[ROW][C]67[/C][C]0.195831[/C][C]0.391662[/C][C]0.804169[/C][/ROW]
[ROW][C]68[/C][C]0.309303[/C][C]0.618606[/C][C]0.690697[/C][/ROW]
[ROW][C]69[/C][C]0.422218[/C][C]0.844437[/C][C]0.577782[/C][/ROW]
[ROW][C]70[/C][C]0.390198[/C][C]0.780395[/C][C]0.609802[/C][/ROW]
[ROW][C]71[/C][C]0.462671[/C][C]0.925342[/C][C]0.537329[/C][/ROW]
[ROW][C]72[/C][C]0.427799[/C][C]0.855599[/C][C]0.572201[/C][/ROW]
[ROW][C]73[/C][C]0.421024[/C][C]0.842049[/C][C]0.578976[/C][/ROW]
[ROW][C]74[/C][C]0.399632[/C][C]0.799264[/C][C]0.600368[/C][/ROW]
[ROW][C]75[/C][C]0.363592[/C][C]0.727184[/C][C]0.636408[/C][/ROW]
[ROW][C]76[/C][C]0.441562[/C][C]0.883123[/C][C]0.558438[/C][/ROW]
[ROW][C]77[/C][C]0.403417[/C][C]0.806833[/C][C]0.596583[/C][/ROW]
[ROW][C]78[/C][C]0.382623[/C][C]0.765246[/C][C]0.617377[/C][/ROW]
[ROW][C]79[/C][C]0.392052[/C][C]0.784104[/C][C]0.607948[/C][/ROW]
[ROW][C]80[/C][C]0.357774[/C][C]0.715548[/C][C]0.642226[/C][/ROW]
[ROW][C]81[/C][C]0.326049[/C][C]0.652098[/C][C]0.673951[/C][/ROW]
[ROW][C]82[/C][C]0.294041[/C][C]0.588082[/C][C]0.705959[/C][/ROW]
[ROW][C]83[/C][C]0.26706[/C][C]0.534119[/C][C]0.73294[/C][/ROW]
[ROW][C]84[/C][C]0.237094[/C][C]0.474188[/C][C]0.762906[/C][/ROW]
[ROW][C]85[/C][C]0.23422[/C][C]0.468439[/C][C]0.76578[/C][/ROW]
[ROW][C]86[/C][C]0.205457[/C][C]0.410915[/C][C]0.794543[/C][/ROW]
[ROW][C]87[/C][C]0.18236[/C][C]0.36472[/C][C]0.81764[/C][/ROW]
[ROW][C]88[/C][C]0.168667[/C][C]0.337334[/C][C]0.831333[/C][/ROW]
[ROW][C]89[/C][C]0.146035[/C][C]0.292071[/C][C]0.853965[/C][/ROW]
[ROW][C]90[/C][C]0.141401[/C][C]0.282803[/C][C]0.858599[/C][/ROW]
[ROW][C]91[/C][C]0.121453[/C][C]0.242907[/C][C]0.878547[/C][/ROW]
[ROW][C]92[/C][C]0.105538[/C][C]0.211077[/C][C]0.894462[/C][/ROW]
[ROW][C]93[/C][C]0.0904732[/C][C]0.180946[/C][C]0.909527[/C][/ROW]
[ROW][C]94[/C][C]0.0944517[/C][C]0.188903[/C][C]0.905548[/C][/ROW]
[ROW][C]95[/C][C]0.0851453[/C][C]0.170291[/C][C]0.914855[/C][/ROW]
[ROW][C]96[/C][C]0.0713438[/C][C]0.142688[/C][C]0.928656[/C][/ROW]
[ROW][C]97[/C][C]0.076539[/C][C]0.153078[/C][C]0.923461[/C][/ROW]
[ROW][C]98[/C][C]0.0639173[/C][C]0.127835[/C][C]0.936083[/C][/ROW]
[ROW][C]99[/C][C]0.0532561[/C][C]0.106512[/C][C]0.946744[/C][/ROW]
[ROW][C]100[/C][C]0.0471965[/C][C]0.0943929[/C][C]0.952804[/C][/ROW]
[ROW][C]101[/C][C]0.0418238[/C][C]0.0836475[/C][C]0.958176[/C][/ROW]
[ROW][C]102[/C][C]0.0495647[/C][C]0.0991293[/C][C]0.950435[/C][/ROW]
[ROW][C]103[/C][C]0.0418159[/C][C]0.0836319[/C][C]0.958184[/C][/ROW]
[ROW][C]104[/C][C]0.0371546[/C][C]0.0743092[/C][C]0.962845[/C][/ROW]
[ROW][C]105[/C][C]0.04438[/C][C]0.0887599[/C][C]0.95562[/C][/ROW]
[ROW][C]106[/C][C]0.0392467[/C][C]0.0784934[/C][C]0.960753[/C][/ROW]
[ROW][C]107[/C][C]0.0321015[/C][C]0.0642031[/C][C]0.967898[/C][/ROW]
[ROW][C]108[/C][C]0.030639[/C][C]0.0612779[/C][C]0.969361[/C][/ROW]
[ROW][C]109[/C][C]0.0249767[/C][C]0.0499533[/C][C]0.975023[/C][/ROW]
[ROW][C]110[/C][C]0.0206803[/C][C]0.0413606[/C][C]0.97932[/C][/ROW]
[ROW][C]111[/C][C]0.0165367[/C][C]0.0330734[/C][C]0.983463[/C][/ROW]
[ROW][C]112[/C][C]0.0174611[/C][C]0.0349222[/C][C]0.982539[/C][/ROW]
[ROW][C]113[/C][C]0.0151868[/C][C]0.0303736[/C][C]0.984813[/C][/ROW]
[ROW][C]114[/C][C]0.0203428[/C][C]0.0406856[/C][C]0.979657[/C][/ROW]
[ROW][C]115[/C][C]0.0195546[/C][C]0.0391092[/C][C]0.980445[/C][/ROW]
[ROW][C]116[/C][C]0.0191566[/C][C]0.0383132[/C][C]0.980843[/C][/ROW]
[ROW][C]117[/C][C]0.0161895[/C][C]0.0323791[/C][C]0.98381[/C][/ROW]
[ROW][C]118[/C][C]0.0161429[/C][C]0.0322858[/C][C]0.983857[/C][/ROW]
[ROW][C]119[/C][C]0.0131116[/C][C]0.0262232[/C][C]0.986888[/C][/ROW]
[ROW][C]120[/C][C]0.0118513[/C][C]0.0237026[/C][C]0.988149[/C][/ROW]
[ROW][C]121[/C][C]0.00961139[/C][C]0.0192228[/C][C]0.990389[/C][/ROW]
[ROW][C]122[/C][C]0.0142976[/C][C]0.0285952[/C][C]0.985702[/C][/ROW]
[ROW][C]123[/C][C]0.0119182[/C][C]0.0238365[/C][C]0.988082[/C][/ROW]
[ROW][C]124[/C][C]0.0100417[/C][C]0.0200834[/C][C]0.989958[/C][/ROW]
[ROW][C]125[/C][C]0.00820386[/C][C]0.0164077[/C][C]0.991796[/C][/ROW]
[ROW][C]126[/C][C]0.00652402[/C][C]0.013048[/C][C]0.993476[/C][/ROW]
[ROW][C]127[/C][C]0.00592499[/C][C]0.01185[/C][C]0.994075[/C][/ROW]
[ROW][C]128[/C][C]0.00498958[/C][C]0.00997916[/C][C]0.99501[/C][/ROW]
[ROW][C]129[/C][C]0.00679677[/C][C]0.0135935[/C][C]0.993203[/C][/ROW]
[ROW][C]130[/C][C]0.00737896[/C][C]0.0147579[/C][C]0.992621[/C][/ROW]
[ROW][C]131[/C][C]0.015038[/C][C]0.030076[/C][C]0.984962[/C][/ROW]
[ROW][C]132[/C][C]0.017902[/C][C]0.035804[/C][C]0.982098[/C][/ROW]
[ROW][C]133[/C][C]0.0190014[/C][C]0.0380029[/C][C]0.980999[/C][/ROW]
[ROW][C]134[/C][C]0.01794[/C][C]0.0358799[/C][C]0.98206[/C][/ROW]
[ROW][C]135[/C][C]0.0143281[/C][C]0.0286562[/C][C]0.985672[/C][/ROW]
[ROW][C]136[/C][C]0.0122309[/C][C]0.0244619[/C][C]0.987769[/C][/ROW]
[ROW][C]137[/C][C]0.00990649[/C][C]0.019813[/C][C]0.990094[/C][/ROW]
[ROW][C]138[/C][C]0.0125384[/C][C]0.0250768[/C][C]0.987462[/C][/ROW]
[ROW][C]139[/C][C]0.0107618[/C][C]0.0215236[/C][C]0.989238[/C][/ROW]
[ROW][C]140[/C][C]0.0129053[/C][C]0.0258106[/C][C]0.987095[/C][/ROW]
[ROW][C]141[/C][C]0.020156[/C][C]0.040312[/C][C]0.979844[/C][/ROW]
[ROW][C]142[/C][C]0.0185243[/C][C]0.0370486[/C][C]0.981476[/C][/ROW]
[ROW][C]143[/C][C]0.0150205[/C][C]0.0300411[/C][C]0.984979[/C][/ROW]
[ROW][C]144[/C][C]0.0157236[/C][C]0.0314472[/C][C]0.984276[/C][/ROW]
[ROW][C]145[/C][C]0.0266975[/C][C]0.0533949[/C][C]0.973303[/C][/ROW]
[ROW][C]146[/C][C]0.0328993[/C][C]0.0657986[/C][C]0.967101[/C][/ROW]
[ROW][C]147[/C][C]0.0347107[/C][C]0.0694213[/C][C]0.965289[/C][/ROW]
[ROW][C]148[/C][C]0.0308268[/C][C]0.0616536[/C][C]0.969173[/C][/ROW]
[ROW][C]149[/C][C]0.0251694[/C][C]0.0503389[/C][C]0.974831[/C][/ROW]
[ROW][C]150[/C][C]0.0347432[/C][C]0.0694863[/C][C]0.965257[/C][/ROW]
[ROW][C]151[/C][C]0.029565[/C][C]0.0591299[/C][C]0.970435[/C][/ROW]
[ROW][C]152[/C][C]0.0312119[/C][C]0.0624238[/C][C]0.968788[/C][/ROW]
[ROW][C]153[/C][C]0.0614922[/C][C]0.122984[/C][C]0.938508[/C][/ROW]
[ROW][C]154[/C][C]0.0592693[/C][C]0.118539[/C][C]0.940731[/C][/ROW]
[ROW][C]155[/C][C]0.0668515[/C][C]0.133703[/C][C]0.933149[/C][/ROW]
[ROW][C]156[/C][C]0.0568828[/C][C]0.113766[/C][C]0.943117[/C][/ROW]
[ROW][C]157[/C][C]0.0507264[/C][C]0.101453[/C][C]0.949274[/C][/ROW]
[ROW][C]158[/C][C]0.0443069[/C][C]0.0886139[/C][C]0.955693[/C][/ROW]
[ROW][C]159[/C][C]0.0428964[/C][C]0.0857927[/C][C]0.957104[/C][/ROW]
[ROW][C]160[/C][C]0.0368289[/C][C]0.0736579[/C][C]0.963171[/C][/ROW]
[ROW][C]161[/C][C]0.0301494[/C][C]0.0602988[/C][C]0.969851[/C][/ROW]
[ROW][C]162[/C][C]0.0246883[/C][C]0.0493765[/C][C]0.975312[/C][/ROW]
[ROW][C]163[/C][C]0.0204557[/C][C]0.0409114[/C][C]0.979544[/C][/ROW]
[ROW][C]164[/C][C]0.0174663[/C][C]0.0349327[/C][C]0.982534[/C][/ROW]
[ROW][C]165[/C][C]0.01529[/C][C]0.0305799[/C][C]0.98471[/C][/ROW]
[ROW][C]166[/C][C]0.0162159[/C][C]0.0324317[/C][C]0.983784[/C][/ROW]
[ROW][C]167[/C][C]0.0129519[/C][C]0.0259038[/C][C]0.987048[/C][/ROW]
[ROW][C]168[/C][C]0.0190098[/C][C]0.0380196[/C][C]0.98099[/C][/ROW]
[ROW][C]169[/C][C]0.0193145[/C][C]0.038629[/C][C]0.980685[/C][/ROW]
[ROW][C]170[/C][C]0.0178019[/C][C]0.0356039[/C][C]0.982198[/C][/ROW]
[ROW][C]171[/C][C]0.0163272[/C][C]0.0326544[/C][C]0.983673[/C][/ROW]
[ROW][C]172[/C][C]0.0131777[/C][C]0.0263553[/C][C]0.986822[/C][/ROW]
[ROW][C]173[/C][C]0.0128128[/C][C]0.0256256[/C][C]0.987187[/C][/ROW]
[ROW][C]174[/C][C]0.014686[/C][C]0.0293719[/C][C]0.985314[/C][/ROW]
[ROW][C]175[/C][C]0.018893[/C][C]0.037786[/C][C]0.981107[/C][/ROW]
[ROW][C]176[/C][C]0.0151454[/C][C]0.0302908[/C][C]0.984855[/C][/ROW]
[ROW][C]177[/C][C]0.0119809[/C][C]0.0239617[/C][C]0.988019[/C][/ROW]
[ROW][C]178[/C][C]0.0100782[/C][C]0.0201563[/C][C]0.989922[/C][/ROW]
[ROW][C]179[/C][C]0.00783799[/C][C]0.015676[/C][C]0.992162[/C][/ROW]
[ROW][C]180[/C][C]0.00689228[/C][C]0.0137846[/C][C]0.993108[/C][/ROW]
[ROW][C]181[/C][C]0.00557929[/C][C]0.0111586[/C][C]0.994421[/C][/ROW]
[ROW][C]182[/C][C]0.0043017[/C][C]0.0086034[/C][C]0.995698[/C][/ROW]
[ROW][C]183[/C][C]0.00454272[/C][C]0.00908545[/C][C]0.995457[/C][/ROW]
[ROW][C]184[/C][C]0.00346341[/C][C]0.00692682[/C][C]0.996537[/C][/ROW]
[ROW][C]185[/C][C]0.0945486[/C][C]0.189097[/C][C]0.905451[/C][/ROW]
[ROW][C]186[/C][C]0.0837673[/C][C]0.167535[/C][C]0.916233[/C][/ROW]
[ROW][C]187[/C][C]0.093732[/C][C]0.187464[/C][C]0.906268[/C][/ROW]
[ROW][C]188[/C][C]0.0791422[/C][C]0.158284[/C][C]0.920858[/C][/ROW]
[ROW][C]189[/C][C]0.0705419[/C][C]0.141084[/C][C]0.929458[/C][/ROW]
[ROW][C]190[/C][C]0.0596706[/C][C]0.119341[/C][C]0.940329[/C][/ROW]
[ROW][C]191[/C][C]0.0516888[/C][C]0.103378[/C][C]0.948311[/C][/ROW]
[ROW][C]192[/C][C]0.043011[/C][C]0.086022[/C][C]0.956989[/C][/ROW]
[ROW][C]193[/C][C]0.0433121[/C][C]0.0866242[/C][C]0.956688[/C][/ROW]
[ROW][C]194[/C][C]0.0410697[/C][C]0.0821393[/C][C]0.95893[/C][/ROW]
[ROW][C]195[/C][C]0.0357028[/C][C]0.0714055[/C][C]0.964297[/C][/ROW]
[ROW][C]196[/C][C]0.028455[/C][C]0.05691[/C][C]0.971545[/C][/ROW]
[ROW][C]197[/C][C]0.0373222[/C][C]0.0746445[/C][C]0.962678[/C][/ROW]
[ROW][C]198[/C][C]0.0305195[/C][C]0.061039[/C][C]0.969481[/C][/ROW]
[ROW][C]199[/C][C]0.0274058[/C][C]0.0548116[/C][C]0.972594[/C][/ROW]
[ROW][C]200[/C][C]0.0232765[/C][C]0.0465531[/C][C]0.976723[/C][/ROW]
[ROW][C]201[/C][C]0.0213114[/C][C]0.0426227[/C][C]0.978689[/C][/ROW]
[ROW][C]202[/C][C]0.0178166[/C][C]0.0356331[/C][C]0.982183[/C][/ROW]
[ROW][C]203[/C][C]0.0198469[/C][C]0.0396938[/C][C]0.980153[/C][/ROW]
[ROW][C]204[/C][C]0.0263675[/C][C]0.052735[/C][C]0.973632[/C][/ROW]
[ROW][C]205[/C][C]0.0278237[/C][C]0.0556474[/C][C]0.972176[/C][/ROW]
[ROW][C]206[/C][C]0.0217503[/C][C]0.0435007[/C][C]0.97825[/C][/ROW]
[ROW][C]207[/C][C]0.0193869[/C][C]0.0387739[/C][C]0.980613[/C][/ROW]
[ROW][C]208[/C][C]0.0154904[/C][C]0.0309807[/C][C]0.98451[/C][/ROW]
[ROW][C]209[/C][C]0.0180779[/C][C]0.0361558[/C][C]0.981922[/C][/ROW]
[ROW][C]210[/C][C]0.0149637[/C][C]0.0299274[/C][C]0.985036[/C][/ROW]
[ROW][C]211[/C][C]0.0183958[/C][C]0.0367917[/C][C]0.981604[/C][/ROW]
[ROW][C]212[/C][C]0.0324718[/C][C]0.0649435[/C][C]0.967528[/C][/ROW]
[ROW][C]213[/C][C]0.0253711[/C][C]0.0507422[/C][C]0.974629[/C][/ROW]
[ROW][C]214[/C][C]0.0314791[/C][C]0.0629582[/C][C]0.968521[/C][/ROW]
[ROW][C]215[/C][C]0.0267613[/C][C]0.0535225[/C][C]0.973239[/C][/ROW]
[ROW][C]216[/C][C]0.0207294[/C][C]0.0414587[/C][C]0.979271[/C][/ROW]
[ROW][C]217[/C][C]0.0231371[/C][C]0.0462741[/C][C]0.976863[/C][/ROW]
[ROW][C]218[/C][C]0.0196068[/C][C]0.0392135[/C][C]0.980393[/C][/ROW]
[ROW][C]219[/C][C]0.0182944[/C][C]0.0365888[/C][C]0.981706[/C][/ROW]
[ROW][C]220[/C][C]0.0137419[/C][C]0.0274838[/C][C]0.986258[/C][/ROW]
[ROW][C]221[/C][C]0.0114025[/C][C]0.022805[/C][C]0.988597[/C][/ROW]
[ROW][C]222[/C][C]0.00831155[/C][C]0.0166231[/C][C]0.991688[/C][/ROW]
[ROW][C]223[/C][C]0.00641631[/C][C]0.0128326[/C][C]0.993584[/C][/ROW]
[ROW][C]224[/C][C]0.00491691[/C][C]0.00983382[/C][C]0.995083[/C][/ROW]
[ROW][C]225[/C][C]0.0034396[/C][C]0.0068792[/C][C]0.99656[/C][/ROW]
[ROW][C]226[/C][C]0.00710199[/C][C]0.014204[/C][C]0.992898[/C][/ROW]
[ROW][C]227[/C][C]0.00565157[/C][C]0.0113031[/C][C]0.994348[/C][/ROW]
[ROW][C]228[/C][C]0.00412262[/C][C]0.00824524[/C][C]0.995877[/C][/ROW]
[ROW][C]229[/C][C]0.00293162[/C][C]0.00586324[/C][C]0.997068[/C][/ROW]
[ROW][C]230[/C][C]0.00207599[/C][C]0.00415198[/C][C]0.997924[/C][/ROW]
[ROW][C]231[/C][C]0.00226851[/C][C]0.00453702[/C][C]0.997731[/C][/ROW]
[ROW][C]232[/C][C]0.00779852[/C][C]0.015597[/C][C]0.992201[/C][/ROW]
[ROW][C]233[/C][C]0.0293698[/C][C]0.0587397[/C][C]0.97063[/C][/ROW]
[ROW][C]234[/C][C]0.0449507[/C][C]0.0899015[/C][C]0.955049[/C][/ROW]
[ROW][C]235[/C][C]0.0330914[/C][C]0.0661828[/C][C]0.966909[/C][/ROW]
[ROW][C]236[/C][C]0.0271012[/C][C]0.0542023[/C][C]0.972899[/C][/ROW]
[ROW][C]237[/C][C]0.238959[/C][C]0.477918[/C][C]0.761041[/C][/ROW]
[ROW][C]238[/C][C]0.192949[/C][C]0.385899[/C][C]0.807051[/C][/ROW]
[ROW][C]239[/C][C]0.16329[/C][C]0.32658[/C][C]0.83671[/C][/ROW]
[ROW][C]240[/C][C]0.130448[/C][C]0.260895[/C][C]0.869552[/C][/ROW]
[ROW][C]241[/C][C]0.116817[/C][C]0.233635[/C][C]0.883183[/C][/ROW]
[ROW][C]242[/C][C]0.177908[/C][C]0.355816[/C][C]0.822092[/C][/ROW]
[ROW][C]243[/C][C]0.150454[/C][C]0.300908[/C][C]0.849546[/C][/ROW]
[ROW][C]244[/C][C]0.151453[/C][C]0.302906[/C][C]0.848547[/C][/ROW]
[ROW][C]245[/C][C]0.132852[/C][C]0.265704[/C][C]0.867148[/C][/ROW]
[ROW][C]246[/C][C]0.116476[/C][C]0.232952[/C][C]0.883524[/C][/ROW]
[ROW][C]247[/C][C]0.0792563[/C][C]0.158513[/C][C]0.920744[/C][/ROW]
[ROW][C]248[/C][C]0.0704291[/C][C]0.140858[/C][C]0.929571[/C][/ROW]
[ROW][C]249[/C][C]0.0534978[/C][C]0.106996[/C][C]0.946502[/C][/ROW]
[ROW][C]250[/C][C]0.13078[/C][C]0.26156[/C][C]0.86922[/C][/ROW]
[ROW][C]251[/C][C]0.107473[/C][C]0.214946[/C][C]0.892527[/C][/ROW]
[ROW][C]252[/C][C]0.543978[/C][C]0.912043[/C][C]0.456022[/C][/ROW]
[ROW][C]253[/C][C]0.382289[/C][C]0.764577[/C][C]0.617711[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221927&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221927&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
110.4024750.804950.597525
120.7998130.4003740.200187
130.7608270.4783470.239173
140.6735530.6528950.326447
150.6181150.7637710.381885
160.6808330.6383340.319167
170.6081430.7837150.391857
180.8576940.2846110.142306
190.830980.3380390.16902
200.7804670.4390650.219533
210.7164350.567130.283565
220.6779250.644150.322075
230.6400810.7198390.359919
240.6080030.7839940.391997
250.5446030.9107950.455397
260.4951190.9902380.504881
270.4356950.871390.564305
280.4894290.9788570.510571
290.4295310.8590620.570469
300.4391110.8782210.560889
310.3907780.7815550.609222
320.3865360.7730730.613464
330.3675740.7351470.632426
340.3119460.6238920.688054
350.300790.601580.69921
360.3994470.7988940.600553
370.4802340.9604670.519766
380.4564140.9128290.543586
390.5040370.9919260.495963
400.4846630.9693250.515337
410.4489820.8979630.551018
420.4193310.8386620.580669
430.4354890.8709780.564511
440.3883570.7767140.611643
450.3497840.6995690.650216
460.574490.8510190.42551
470.5925140.8149720.407486
480.5540650.891870.445935
490.5413440.9173120.458656
500.5141860.9716280.485814
510.4699710.9399420.530029
520.4284280.8568550.571572
530.4356610.8713230.564339
540.4060090.8120180.593991
550.4042780.8085550.595722
560.4207350.8414690.579265
570.3801420.7602830.619858
580.3656290.7312580.634371
590.3265080.6530160.673492
600.3533720.7067440.646628
610.327220.6544410.67278
620.2931320.5862640.706868
630.2591180.5182350.740882
640.2265140.4530290.773486
650.2029090.4058190.797091
660.1931320.3862640.806868
670.1958310.3916620.804169
680.3093030.6186060.690697
690.4222180.8444370.577782
700.3901980.7803950.609802
710.4626710.9253420.537329
720.4277990.8555990.572201
730.4210240.8420490.578976
740.3996320.7992640.600368
750.3635920.7271840.636408
760.4415620.8831230.558438
770.4034170.8068330.596583
780.3826230.7652460.617377
790.3920520.7841040.607948
800.3577740.7155480.642226
810.3260490.6520980.673951
820.2940410.5880820.705959
830.267060.5341190.73294
840.2370940.4741880.762906
850.234220.4684390.76578
860.2054570.4109150.794543
870.182360.364720.81764
880.1686670.3373340.831333
890.1460350.2920710.853965
900.1414010.2828030.858599
910.1214530.2429070.878547
920.1055380.2110770.894462
930.09047320.1809460.909527
940.09445170.1889030.905548
950.08514530.1702910.914855
960.07134380.1426880.928656
970.0765390.1530780.923461
980.06391730.1278350.936083
990.05325610.1065120.946744
1000.04719650.09439290.952804
1010.04182380.08364750.958176
1020.04956470.09912930.950435
1030.04181590.08363190.958184
1040.03715460.07430920.962845
1050.044380.08875990.95562
1060.03924670.07849340.960753
1070.03210150.06420310.967898
1080.0306390.06127790.969361
1090.02497670.04995330.975023
1100.02068030.04136060.97932
1110.01653670.03307340.983463
1120.01746110.03492220.982539
1130.01518680.03037360.984813
1140.02034280.04068560.979657
1150.01955460.03910920.980445
1160.01915660.03831320.980843
1170.01618950.03237910.98381
1180.01614290.03228580.983857
1190.01311160.02622320.986888
1200.01185130.02370260.988149
1210.009611390.01922280.990389
1220.01429760.02859520.985702
1230.01191820.02383650.988082
1240.01004170.02008340.989958
1250.008203860.01640770.991796
1260.006524020.0130480.993476
1270.005924990.011850.994075
1280.004989580.009979160.99501
1290.006796770.01359350.993203
1300.007378960.01475790.992621
1310.0150380.0300760.984962
1320.0179020.0358040.982098
1330.01900140.03800290.980999
1340.017940.03587990.98206
1350.01432810.02865620.985672
1360.01223090.02446190.987769
1370.009906490.0198130.990094
1380.01253840.02507680.987462
1390.01076180.02152360.989238
1400.01290530.02581060.987095
1410.0201560.0403120.979844
1420.01852430.03704860.981476
1430.01502050.03004110.984979
1440.01572360.03144720.984276
1450.02669750.05339490.973303
1460.03289930.06579860.967101
1470.03471070.06942130.965289
1480.03082680.06165360.969173
1490.02516940.05033890.974831
1500.03474320.06948630.965257
1510.0295650.05912990.970435
1520.03121190.06242380.968788
1530.06149220.1229840.938508
1540.05926930.1185390.940731
1550.06685150.1337030.933149
1560.05688280.1137660.943117
1570.05072640.1014530.949274
1580.04430690.08861390.955693
1590.04289640.08579270.957104
1600.03682890.07365790.963171
1610.03014940.06029880.969851
1620.02468830.04937650.975312
1630.02045570.04091140.979544
1640.01746630.03493270.982534
1650.015290.03057990.98471
1660.01621590.03243170.983784
1670.01295190.02590380.987048
1680.01900980.03801960.98099
1690.01931450.0386290.980685
1700.01780190.03560390.982198
1710.01632720.03265440.983673
1720.01317770.02635530.986822
1730.01281280.02562560.987187
1740.0146860.02937190.985314
1750.0188930.0377860.981107
1760.01514540.03029080.984855
1770.01198090.02396170.988019
1780.01007820.02015630.989922
1790.007837990.0156760.992162
1800.006892280.01378460.993108
1810.005579290.01115860.994421
1820.00430170.00860340.995698
1830.004542720.009085450.995457
1840.003463410.006926820.996537
1850.09454860.1890970.905451
1860.08376730.1675350.916233
1870.0937320.1874640.906268
1880.07914220.1582840.920858
1890.07054190.1410840.929458
1900.05967060.1193410.940329
1910.05168880.1033780.948311
1920.0430110.0860220.956989
1930.04331210.08662420.956688
1940.04106970.08213930.95893
1950.03570280.07140550.964297
1960.0284550.056910.971545
1970.03732220.07464450.962678
1980.03051950.0610390.969481
1990.02740580.05481160.972594
2000.02327650.04655310.976723
2010.02131140.04262270.978689
2020.01781660.03563310.982183
2030.01984690.03969380.980153
2040.02636750.0527350.973632
2050.02782370.05564740.972176
2060.02175030.04350070.97825
2070.01938690.03877390.980613
2080.01549040.03098070.98451
2090.01807790.03615580.981922
2100.01496370.02992740.985036
2110.01839580.03679170.981604
2120.03247180.06494350.967528
2130.02537110.05074220.974629
2140.03147910.06295820.968521
2150.02676130.05352250.973239
2160.02072940.04145870.979271
2170.02313710.04627410.976863
2180.01960680.03921350.980393
2190.01829440.03658880.981706
2200.01374190.02748380.986258
2210.01140250.0228050.988597
2220.008311550.01662310.991688
2230.006416310.01283260.993584
2240.004916910.009833820.995083
2250.00343960.00687920.99656
2260.007101990.0142040.992898
2270.005651570.01130310.994348
2280.004122620.008245240.995877
2290.002931620.005863240.997068
2300.002075990.004151980.997924
2310.002268510.004537020.997731
2320.007798520.0155970.992201
2330.02936980.05873970.97063
2340.04495070.08990150.955049
2350.03309140.06618280.966909
2360.02710120.05420230.972899
2370.2389590.4779180.761041
2380.1929490.3858990.807051
2390.163290.326580.83671
2400.1304480.2608950.869552
2410.1168170.2336350.883183
2420.1779080.3558160.822092
2430.1504540.3009080.849546
2440.1514530.3029060.848547
2450.1328520.2657040.867148
2460.1164760.2329520.883524
2470.07925630.1585130.920744
2480.07042910.1408580.929571
2490.05349780.1069960.946502
2500.130780.261560.86922
2510.1074730.2149460.892527
2520.5439780.9120430.456022
2530.3822890.7645770.617711






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.0411523NOK
5% type I error level860.353909NOK
10% type I error level1250.514403NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 10 & 0.0411523 & NOK \tabularnewline
5% type I error level & 86 & 0.353909 & NOK \tabularnewline
10% type I error level & 125 & 0.514403 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221927&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]10[/C][C]0.0411523[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]86[/C][C]0.353909[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]125[/C][C]0.514403[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221927&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221927&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.0411523NOK
5% type I error level860.353909NOK
10% type I error level1250.514403NOK


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 = 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')
}