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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 computationWed, 20 Nov 2013 07:55:02 -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/20/t13849530152ritjmbnhk2ijn2.htm/, Retrieved Wed, 01 May 2024 17:51:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226600, Retrieved Wed, 01 May 2024 17:51:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [WS 7 - Happiness_...] [2013-11-20 12:55:02] [e5eda3cc50f4d89e40bb52bce43bc7fc] [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 time20 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 20 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.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=226600&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]20 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.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=226600&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226600&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 time20 seconds
R Server'Gertrude Mary Cox' @ cox.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
Happiness[t] = + 15.8448 + 0.00296944Connected[t] + 0.0120368Separate[t] + 0.0816225Learning[t] -0.0341131Software[t] -0.360392Depression[t] + 0.0261257Sport1[t] -0.00437231t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  15.8448 +  0.00296944Connected[t] +  0.0120368Separate[t] +  0.0816225Learning[t] -0.0341131Software[t] -0.360392Depression[t] +  0.0261257Sport1[t] -0.00437231t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226600&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  15.8448 +  0.00296944Connected[t] +  0.0120368Separate[t] +  0.0816225Learning[t] -0.0341131Software[t] -0.360392Depression[t] +  0.0261257Sport1[t] -0.00437231t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226600&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226600&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
Happiness[t] = + 15.8448 + 0.00296944Connected[t] + 0.0120368Separate[t] + 0.0816225Learning[t] -0.0341131Software[t] -0.360392Depression[t] + 0.0261257Sport1[t] -0.00437231t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.84481.881688.4212.70374e-151.35187e-15
Connected0.002969440.03717340.079880.9363950.468197
Separate0.01203680.03791560.31750.7511510.375575
Learning0.08162250.06718381.2150.2255180.112759
Software-0.03411310.0690358-0.49410.6216340.310817
Depression-0.3603920.0390338-9.2331.03729e-175.18647e-18
Sport10.02612570.01270032.0570.04069090.0203455
t-0.004372310.00182082-2.4010.01705120.00852559

\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) & 15.8448 & 1.88168 & 8.421 & 2.70374e-15 & 1.35187e-15 \tabularnewline
Connected & 0.00296944 & 0.0371734 & 0.07988 & 0.936395 & 0.468197 \tabularnewline
Separate & 0.0120368 & 0.0379156 & 0.3175 & 0.751151 & 0.375575 \tabularnewline
Learning & 0.0816225 & 0.0671838 & 1.215 & 0.225518 & 0.112759 \tabularnewline
Software & -0.0341131 & 0.0690358 & -0.4941 & 0.621634 & 0.310817 \tabularnewline
Depression & -0.360392 & 0.0390338 & -9.233 & 1.03729e-17 & 5.18647e-18 \tabularnewline
Sport1 & 0.0261257 & 0.0127003 & 2.057 & 0.0406909 & 0.0203455 \tabularnewline
t & -0.00437231 & 0.00182082 & -2.401 & 0.0170512 & 0.00852559 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226600&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]15.8448[/C][C]1.88168[/C][C]8.421[/C][C]2.70374e-15[/C][C]1.35187e-15[/C][/ROW]
[ROW][C]Connected[/C][C]0.00296944[/C][C]0.0371734[/C][C]0.07988[/C][C]0.936395[/C][C]0.468197[/C][/ROW]
[ROW][C]Separate[/C][C]0.0120368[/C][C]0.0379156[/C][C]0.3175[/C][C]0.751151[/C][C]0.375575[/C][/ROW]
[ROW][C]Learning[/C][C]0.0816225[/C][C]0.0671838[/C][C]1.215[/C][C]0.225518[/C][C]0.112759[/C][/ROW]
[ROW][C]Software[/C][C]-0.0341131[/C][C]0.0690358[/C][C]-0.4941[/C][C]0.621634[/C][C]0.310817[/C][/ROW]
[ROW][C]Depression[/C][C]-0.360392[/C][C]0.0390338[/C][C]-9.233[/C][C]1.03729e-17[/C][C]5.18647e-18[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0261257[/C][C]0.0127003[/C][C]2.057[/C][C]0.0406909[/C][C]0.0203455[/C][/ROW]
[ROW][C]t[/C][C]-0.00437231[/C][C]0.00182082[/C][C]-2.401[/C][C]0.0170512[/C][C]0.00852559[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226600&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226600&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)15.84481.881688.4212.70374e-151.35187e-15
Connected0.002969440.03717340.079880.9363950.468197
Separate0.01203680.03791560.31750.7511510.375575
Learning0.08162250.06718381.2150.2255180.112759
Software-0.03411310.0690358-0.49410.6216340.310817
Depression-0.3603920.0390338-9.2331.03729e-175.18647e-18
Sport10.02612570.01270032.0570.04069090.0203455
t-0.004372310.00182082-2.4010.01705120.00852559






Multiple Linear Regression - Regression Statistics
Multiple R0.614034
R-squared0.377038
Adjusted R-squared0.360004
F-TEST (value)22.1343
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.99891
Sum Squared Residuals1022.88

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.614034 \tabularnewline
R-squared & 0.377038 \tabularnewline
Adjusted R-squared & 0.360004 \tabularnewline
F-TEST (value) & 22.1343 \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 & 1.99891 \tabularnewline
Sum Squared Residuals & 1022.88 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226600&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.614034[/C][/ROW]
[ROW][C]R-squared[/C][C]0.377038[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.360004[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]22.1343[/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]1.99891[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1022.88[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226600&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226600&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 R0.614034
R-squared0.377038
Adjusted R-squared0.360004
F-TEST (value)22.1343
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.99891
Sum Squared Residuals1022.88






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.1313-0.131296
21815.47192.52809
31114.06-3.06002
41214.762-2.76198
51611.48594.51414
61814.70473.29535
71410.90073.09932
81415.2166-1.21663
91515.3964-0.396405
101514.58610.41385
111715.70761.29245
121915.73283.26723
131013.5633-3.56326
141613.65282.34716
151815.86752.1325
161413.55190.448108
171414.0597-0.0597227
181715.89421.10579
191415.497-1.49705
201613.93832.06175
211815.47652.52346
221113.8415-2.84149
231414.5109-0.510914
241213.6675-1.66747
251715.49721.50277
26916.0287-7.02871
271615.2410.758966
281413.40930.590695
291514.10220.897843
301114.0787-3.07875
311615.8360.164011
321312.88170.118259
331715.23611.76386
341515.3693-0.369342
351414.1354-0.135426
361615.72890.271116
37911.0896-2.08959
381514.44640.553626
391715.481.51997
401315.3347-2.33466
411515.8152-0.815214
421613.80672.19334
431615.80320.196758
441213.2682-1.26823
451514.73790.262111
461113.7548-2.7548
471515.3755-0.375492
481514.98640.0135905
491713.6533.34698
501314.8527-1.8527
511615.27980.720231
521413.58010.419887
531111.8343-0.834309
541213.6039-1.60388
551214.3302-2.3302
561513.8291.17096
571614.26551.73452
581515.4901-0.490097
591215.2824-3.28241
601213.4834-1.48342
61810.9217-2.92173
621314.6794-1.67941
631114.6854-3.68535
641413.15890.841138
651513.6571.34297
661015.1754-5.1754
671112.6693-1.66933
681214.638-2.63802
691513.67141.32864
701513.74181.25815
711413.68920.310795
721612.85193.14815
731514.51880.481247
741515.318-0.318001
751315.0697-2.06971
761212.3126-0.312618
771714.06962.93042
781312.58460.415384
791513.9341.06598
801314.9938-1.99377
811515.0182-0.018209
821515.5436-0.543591
831614.38651.61354
841514.38730.612732
851414.2357-0.235727
861514.16110.838887
871414.3463-0.346253
881312.83290.167131
89710.6661-3.66605
901713.87123.12877
911312.81980.180179
921514.26320.736799
931413.42170.578336
941314.1179-1.11794
951615.06920.930835
961212.8551-0.855136
971414.9702-0.970221
981714.98392.01606
991515.1235-0.123534
1001715.16381.83623
1011213.006-1.006
1021614.96781.03215
1031114.4356-3.43561
1041513.18591.81409
105911.4705-2.47053
1061614.9151.08504
1071512.95342.04657
1081012.8364-2.83643
109109.294530.705467
1101513.9341.06599
1111113.2046-2.20457
1121315.2907-2.29075
1131412.11571.88426
1141814.16473.83531
1151615.50570.494315
1161412.98171.01835
1171413.85080.149162
1181415.0932-1.09317
1191413.71270.287277
1201212.5543-0.554262
1211413.53540.464619
1221514.90630.0937088
1231515.8051-0.805096
1241514.50640.493565
1251314.6814-1.68144
1261716.14630.853714
1271715.23141.76864
1281914.88574.11432
1291513.58211.41787
1301314.6241-1.62411
131910.6978-1.69782
1321515.2726-0.272637
1331512.60112.39889
1341514.16820.831837
1351613.68882.31117
136119.4741.526
1371413.21760.782403
1381111.9531-0.953055
1391514.16460.835442
1401313.8148-0.814846
1411514.57250.427469
1421613.82482.1752
1431414.528-0.527952
1441514.20180.798194
1451614.6071.39304
1461614.31311.68693
1471113.2765-2.27651
1481214.5576-2.55761
149911.4963-2.49627
1501614.24471.75533
1511312.47280.527178
1521615.34890.651064
1531214.4069-2.40686
154911.5186-2.51862
1551311.73231.26768
1561312.53560.464379
1571413.31240.68764
1581914.75454.24549
1591315.5175-2.51752
1601212.1117-0.111748
1611312.49980.500238
162109.32450.675503
1631413.31440.685589
1641611.48234.51771
1651011.971-1.971
166119.216491.78351
1671414.0815-0.0815225
1681212.8647-0.864711
169912.692-3.69204
170911.9438-2.9438
1711110.61820.381847
1721614.0981.902
173913.9829-4.98289
1741311.38161.61835
1751613.28972.71033
1761315.235-2.23498
177912.2949-3.29486
1781211.50480.495185
1791614.47551.52453
1801113.1763-2.17628
1811413.93670.0632546
1821314.7142-1.71417
1831514.47370.526308
1841414.8395-0.839457
1851614.04281.95719
1861311.59461.40537
1871413.44350.556489
1881514.20070.799306
1891312.4630.537006
1901110.29520.704844
1911112.5791-1.57911
1921414.8518-0.851767
1931512.76712.23287
1941112.3301-1.33013
1951513.0281.97205
1961213.8742-1.8742
1971411.6732.32699
1981413.28610.713877
199811.078-3.07799
2001313.6559-0.655936
201911.9888-2.98879
2021513.67351.32645
2031714.01732.9827
2041312.37440.62557
2051514.32390.67608
2061513.57571.42428
2071414.3157-0.315749
2081612.32193.6781
2091312.77520.224841
2101614.17791.82212
211911.5359-2.53594
2121614.36961.63037
2131112.113-1.11296
2141013.7137-3.71368
2151111.9504-0.950362
2161513.09911.90087
2171714.6842.31597
2181414.062-0.062038
21989.86871-1.86871
2201513.37111.62894
2211113.6923-2.69228
2221613.41252.58749
2231011.9223-1.92234
2241514.65260.347363
22599.57397-0.573967
2261614.26721.73278
2271913.57765.42239
2281213.5121-1.5121
22989.36786-1.36786
2301113.1776-2.1776
2311413.68350.316474
232911.8451-2.84509
2331514.70340.296601
2341312.08670.913321
2351614.6611.33904
2361112.633-1.63303
2371211.26030.739734
2381312.5090.490961
2391014.0724-4.07244
2401113.4002-2.40023
2411214.6582-2.65816
242810.4534-2.45339
2431211.66540.334562
2441212.0936-0.0935692
2451513.23661.76335
2461110.5780.421958
2471312.48750.512456
248148.62235.3777
2491010.0271-0.0270819
2501211.34570.65431
2511512.69112.30895
2521311.71481.28525
2531313.9202-0.92019
2541313.4123-0.412329
2551211.52520.474803
2561212.3357-0.335707
257910.5582-1.55824
258911.1966-2.19655
2591512.26192.73809
2601014.6825-4.68251
2611413.34140.65863
2621513.1981.80202
26379.59724-2.59724
2641413.55390.446125

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 14.1313 & -0.131296 \tabularnewline
2 & 18 & 15.4719 & 2.52809 \tabularnewline
3 & 11 & 14.06 & -3.06002 \tabularnewline
4 & 12 & 14.762 & -2.76198 \tabularnewline
5 & 16 & 11.4859 & 4.51414 \tabularnewline
6 & 18 & 14.7047 & 3.29535 \tabularnewline
7 & 14 & 10.9007 & 3.09932 \tabularnewline
8 & 14 & 15.2166 & -1.21663 \tabularnewline
9 & 15 & 15.3964 & -0.396405 \tabularnewline
10 & 15 & 14.5861 & 0.41385 \tabularnewline
11 & 17 & 15.7076 & 1.29245 \tabularnewline
12 & 19 & 15.7328 & 3.26723 \tabularnewline
13 & 10 & 13.5633 & -3.56326 \tabularnewline
14 & 16 & 13.6528 & 2.34716 \tabularnewline
15 & 18 & 15.8675 & 2.1325 \tabularnewline
16 & 14 & 13.5519 & 0.448108 \tabularnewline
17 & 14 & 14.0597 & -0.0597227 \tabularnewline
18 & 17 & 15.8942 & 1.10579 \tabularnewline
19 & 14 & 15.497 & -1.49705 \tabularnewline
20 & 16 & 13.9383 & 2.06175 \tabularnewline
21 & 18 & 15.4765 & 2.52346 \tabularnewline
22 & 11 & 13.8415 & -2.84149 \tabularnewline
23 & 14 & 14.5109 & -0.510914 \tabularnewline
24 & 12 & 13.6675 & -1.66747 \tabularnewline
25 & 17 & 15.4972 & 1.50277 \tabularnewline
26 & 9 & 16.0287 & -7.02871 \tabularnewline
27 & 16 & 15.241 & 0.758966 \tabularnewline
28 & 14 & 13.4093 & 0.590695 \tabularnewline
29 & 15 & 14.1022 & 0.897843 \tabularnewline
30 & 11 & 14.0787 & -3.07875 \tabularnewline
31 & 16 & 15.836 & 0.164011 \tabularnewline
32 & 13 & 12.8817 & 0.118259 \tabularnewline
33 & 17 & 15.2361 & 1.76386 \tabularnewline
34 & 15 & 15.3693 & -0.369342 \tabularnewline
35 & 14 & 14.1354 & -0.135426 \tabularnewline
36 & 16 & 15.7289 & 0.271116 \tabularnewline
37 & 9 & 11.0896 & -2.08959 \tabularnewline
38 & 15 & 14.4464 & 0.553626 \tabularnewline
39 & 17 & 15.48 & 1.51997 \tabularnewline
40 & 13 & 15.3347 & -2.33466 \tabularnewline
41 & 15 & 15.8152 & -0.815214 \tabularnewline
42 & 16 & 13.8067 & 2.19334 \tabularnewline
43 & 16 & 15.8032 & 0.196758 \tabularnewline
44 & 12 & 13.2682 & -1.26823 \tabularnewline
45 & 15 & 14.7379 & 0.262111 \tabularnewline
46 & 11 & 13.7548 & -2.7548 \tabularnewline
47 & 15 & 15.3755 & -0.375492 \tabularnewline
48 & 15 & 14.9864 & 0.0135905 \tabularnewline
49 & 17 & 13.653 & 3.34698 \tabularnewline
50 & 13 & 14.8527 & -1.8527 \tabularnewline
51 & 16 & 15.2798 & 0.720231 \tabularnewline
52 & 14 & 13.5801 & 0.419887 \tabularnewline
53 & 11 & 11.8343 & -0.834309 \tabularnewline
54 & 12 & 13.6039 & -1.60388 \tabularnewline
55 & 12 & 14.3302 & -2.3302 \tabularnewline
56 & 15 & 13.829 & 1.17096 \tabularnewline
57 & 16 & 14.2655 & 1.73452 \tabularnewline
58 & 15 & 15.4901 & -0.490097 \tabularnewline
59 & 12 & 15.2824 & -3.28241 \tabularnewline
60 & 12 & 13.4834 & -1.48342 \tabularnewline
61 & 8 & 10.9217 & -2.92173 \tabularnewline
62 & 13 & 14.6794 & -1.67941 \tabularnewline
63 & 11 & 14.6854 & -3.68535 \tabularnewline
64 & 14 & 13.1589 & 0.841138 \tabularnewline
65 & 15 & 13.657 & 1.34297 \tabularnewline
66 & 10 & 15.1754 & -5.1754 \tabularnewline
67 & 11 & 12.6693 & -1.66933 \tabularnewline
68 & 12 & 14.638 & -2.63802 \tabularnewline
69 & 15 & 13.6714 & 1.32864 \tabularnewline
70 & 15 & 13.7418 & 1.25815 \tabularnewline
71 & 14 & 13.6892 & 0.310795 \tabularnewline
72 & 16 & 12.8519 & 3.14815 \tabularnewline
73 & 15 & 14.5188 & 0.481247 \tabularnewline
74 & 15 & 15.318 & -0.318001 \tabularnewline
75 & 13 & 15.0697 & -2.06971 \tabularnewline
76 & 12 & 12.3126 & -0.312618 \tabularnewline
77 & 17 & 14.0696 & 2.93042 \tabularnewline
78 & 13 & 12.5846 & 0.415384 \tabularnewline
79 & 15 & 13.934 & 1.06598 \tabularnewline
80 & 13 & 14.9938 & -1.99377 \tabularnewline
81 & 15 & 15.0182 & -0.018209 \tabularnewline
82 & 15 & 15.5436 & -0.543591 \tabularnewline
83 & 16 & 14.3865 & 1.61354 \tabularnewline
84 & 15 & 14.3873 & 0.612732 \tabularnewline
85 & 14 & 14.2357 & -0.235727 \tabularnewline
86 & 15 & 14.1611 & 0.838887 \tabularnewline
87 & 14 & 14.3463 & -0.346253 \tabularnewline
88 & 13 & 12.8329 & 0.167131 \tabularnewline
89 & 7 & 10.6661 & -3.66605 \tabularnewline
90 & 17 & 13.8712 & 3.12877 \tabularnewline
91 & 13 & 12.8198 & 0.180179 \tabularnewline
92 & 15 & 14.2632 & 0.736799 \tabularnewline
93 & 14 & 13.4217 & 0.578336 \tabularnewline
94 & 13 & 14.1179 & -1.11794 \tabularnewline
95 & 16 & 15.0692 & 0.930835 \tabularnewline
96 & 12 & 12.8551 & -0.855136 \tabularnewline
97 & 14 & 14.9702 & -0.970221 \tabularnewline
98 & 17 & 14.9839 & 2.01606 \tabularnewline
99 & 15 & 15.1235 & -0.123534 \tabularnewline
100 & 17 & 15.1638 & 1.83623 \tabularnewline
101 & 12 & 13.006 & -1.006 \tabularnewline
102 & 16 & 14.9678 & 1.03215 \tabularnewline
103 & 11 & 14.4356 & -3.43561 \tabularnewline
104 & 15 & 13.1859 & 1.81409 \tabularnewline
105 & 9 & 11.4705 & -2.47053 \tabularnewline
106 & 16 & 14.915 & 1.08504 \tabularnewline
107 & 15 & 12.9534 & 2.04657 \tabularnewline
108 & 10 & 12.8364 & -2.83643 \tabularnewline
109 & 10 & 9.29453 & 0.705467 \tabularnewline
110 & 15 & 13.934 & 1.06599 \tabularnewline
111 & 11 & 13.2046 & -2.20457 \tabularnewline
112 & 13 & 15.2907 & -2.29075 \tabularnewline
113 & 14 & 12.1157 & 1.88426 \tabularnewline
114 & 18 & 14.1647 & 3.83531 \tabularnewline
115 & 16 & 15.5057 & 0.494315 \tabularnewline
116 & 14 & 12.9817 & 1.01835 \tabularnewline
117 & 14 & 13.8508 & 0.149162 \tabularnewline
118 & 14 & 15.0932 & -1.09317 \tabularnewline
119 & 14 & 13.7127 & 0.287277 \tabularnewline
120 & 12 & 12.5543 & -0.554262 \tabularnewline
121 & 14 & 13.5354 & 0.464619 \tabularnewline
122 & 15 & 14.9063 & 0.0937088 \tabularnewline
123 & 15 & 15.8051 & -0.805096 \tabularnewline
124 & 15 & 14.5064 & 0.493565 \tabularnewline
125 & 13 & 14.6814 & -1.68144 \tabularnewline
126 & 17 & 16.1463 & 0.853714 \tabularnewline
127 & 17 & 15.2314 & 1.76864 \tabularnewline
128 & 19 & 14.8857 & 4.11432 \tabularnewline
129 & 15 & 13.5821 & 1.41787 \tabularnewline
130 & 13 & 14.6241 & -1.62411 \tabularnewline
131 & 9 & 10.6978 & -1.69782 \tabularnewline
132 & 15 & 15.2726 & -0.272637 \tabularnewline
133 & 15 & 12.6011 & 2.39889 \tabularnewline
134 & 15 & 14.1682 & 0.831837 \tabularnewline
135 & 16 & 13.6888 & 2.31117 \tabularnewline
136 & 11 & 9.474 & 1.526 \tabularnewline
137 & 14 & 13.2176 & 0.782403 \tabularnewline
138 & 11 & 11.9531 & -0.953055 \tabularnewline
139 & 15 & 14.1646 & 0.835442 \tabularnewline
140 & 13 & 13.8148 & -0.814846 \tabularnewline
141 & 15 & 14.5725 & 0.427469 \tabularnewline
142 & 16 & 13.8248 & 2.1752 \tabularnewline
143 & 14 & 14.528 & -0.527952 \tabularnewline
144 & 15 & 14.2018 & 0.798194 \tabularnewline
145 & 16 & 14.607 & 1.39304 \tabularnewline
146 & 16 & 14.3131 & 1.68693 \tabularnewline
147 & 11 & 13.2765 & -2.27651 \tabularnewline
148 & 12 & 14.5576 & -2.55761 \tabularnewline
149 & 9 & 11.4963 & -2.49627 \tabularnewline
150 & 16 & 14.2447 & 1.75533 \tabularnewline
151 & 13 & 12.4728 & 0.527178 \tabularnewline
152 & 16 & 15.3489 & 0.651064 \tabularnewline
153 & 12 & 14.4069 & -2.40686 \tabularnewline
154 & 9 & 11.5186 & -2.51862 \tabularnewline
155 & 13 & 11.7323 & 1.26768 \tabularnewline
156 & 13 & 12.5356 & 0.464379 \tabularnewline
157 & 14 & 13.3124 & 0.68764 \tabularnewline
158 & 19 & 14.7545 & 4.24549 \tabularnewline
159 & 13 & 15.5175 & -2.51752 \tabularnewline
160 & 12 & 12.1117 & -0.111748 \tabularnewline
161 & 13 & 12.4998 & 0.500238 \tabularnewline
162 & 10 & 9.3245 & 0.675503 \tabularnewline
163 & 14 & 13.3144 & 0.685589 \tabularnewline
164 & 16 & 11.4823 & 4.51771 \tabularnewline
165 & 10 & 11.971 & -1.971 \tabularnewline
166 & 11 & 9.21649 & 1.78351 \tabularnewline
167 & 14 & 14.0815 & -0.0815225 \tabularnewline
168 & 12 & 12.8647 & -0.864711 \tabularnewline
169 & 9 & 12.692 & -3.69204 \tabularnewline
170 & 9 & 11.9438 & -2.9438 \tabularnewline
171 & 11 & 10.6182 & 0.381847 \tabularnewline
172 & 16 & 14.098 & 1.902 \tabularnewline
173 & 9 & 13.9829 & -4.98289 \tabularnewline
174 & 13 & 11.3816 & 1.61835 \tabularnewline
175 & 16 & 13.2897 & 2.71033 \tabularnewline
176 & 13 & 15.235 & -2.23498 \tabularnewline
177 & 9 & 12.2949 & -3.29486 \tabularnewline
178 & 12 & 11.5048 & 0.495185 \tabularnewline
179 & 16 & 14.4755 & 1.52453 \tabularnewline
180 & 11 & 13.1763 & -2.17628 \tabularnewline
181 & 14 & 13.9367 & 0.0632546 \tabularnewline
182 & 13 & 14.7142 & -1.71417 \tabularnewline
183 & 15 & 14.4737 & 0.526308 \tabularnewline
184 & 14 & 14.8395 & -0.839457 \tabularnewline
185 & 16 & 14.0428 & 1.95719 \tabularnewline
186 & 13 & 11.5946 & 1.40537 \tabularnewline
187 & 14 & 13.4435 & 0.556489 \tabularnewline
188 & 15 & 14.2007 & 0.799306 \tabularnewline
189 & 13 & 12.463 & 0.537006 \tabularnewline
190 & 11 & 10.2952 & 0.704844 \tabularnewline
191 & 11 & 12.5791 & -1.57911 \tabularnewline
192 & 14 & 14.8518 & -0.851767 \tabularnewline
193 & 15 & 12.7671 & 2.23287 \tabularnewline
194 & 11 & 12.3301 & -1.33013 \tabularnewline
195 & 15 & 13.028 & 1.97205 \tabularnewline
196 & 12 & 13.8742 & -1.8742 \tabularnewline
197 & 14 & 11.673 & 2.32699 \tabularnewline
198 & 14 & 13.2861 & 0.713877 \tabularnewline
199 & 8 & 11.078 & -3.07799 \tabularnewline
200 & 13 & 13.6559 & -0.655936 \tabularnewline
201 & 9 & 11.9888 & -2.98879 \tabularnewline
202 & 15 & 13.6735 & 1.32645 \tabularnewline
203 & 17 & 14.0173 & 2.9827 \tabularnewline
204 & 13 & 12.3744 & 0.62557 \tabularnewline
205 & 15 & 14.3239 & 0.67608 \tabularnewline
206 & 15 & 13.5757 & 1.42428 \tabularnewline
207 & 14 & 14.3157 & -0.315749 \tabularnewline
208 & 16 & 12.3219 & 3.6781 \tabularnewline
209 & 13 & 12.7752 & 0.224841 \tabularnewline
210 & 16 & 14.1779 & 1.82212 \tabularnewline
211 & 9 & 11.5359 & -2.53594 \tabularnewline
212 & 16 & 14.3696 & 1.63037 \tabularnewline
213 & 11 & 12.113 & -1.11296 \tabularnewline
214 & 10 & 13.7137 & -3.71368 \tabularnewline
215 & 11 & 11.9504 & -0.950362 \tabularnewline
216 & 15 & 13.0991 & 1.90087 \tabularnewline
217 & 17 & 14.684 & 2.31597 \tabularnewline
218 & 14 & 14.062 & -0.062038 \tabularnewline
219 & 8 & 9.86871 & -1.86871 \tabularnewline
220 & 15 & 13.3711 & 1.62894 \tabularnewline
221 & 11 & 13.6923 & -2.69228 \tabularnewline
222 & 16 & 13.4125 & 2.58749 \tabularnewline
223 & 10 & 11.9223 & -1.92234 \tabularnewline
224 & 15 & 14.6526 & 0.347363 \tabularnewline
225 & 9 & 9.57397 & -0.573967 \tabularnewline
226 & 16 & 14.2672 & 1.73278 \tabularnewline
227 & 19 & 13.5776 & 5.42239 \tabularnewline
228 & 12 & 13.5121 & -1.5121 \tabularnewline
229 & 8 & 9.36786 & -1.36786 \tabularnewline
230 & 11 & 13.1776 & -2.1776 \tabularnewline
231 & 14 & 13.6835 & 0.316474 \tabularnewline
232 & 9 & 11.8451 & -2.84509 \tabularnewline
233 & 15 & 14.7034 & 0.296601 \tabularnewline
234 & 13 & 12.0867 & 0.913321 \tabularnewline
235 & 16 & 14.661 & 1.33904 \tabularnewline
236 & 11 & 12.633 & -1.63303 \tabularnewline
237 & 12 & 11.2603 & 0.739734 \tabularnewline
238 & 13 & 12.509 & 0.490961 \tabularnewline
239 & 10 & 14.0724 & -4.07244 \tabularnewline
240 & 11 & 13.4002 & -2.40023 \tabularnewline
241 & 12 & 14.6582 & -2.65816 \tabularnewline
242 & 8 & 10.4534 & -2.45339 \tabularnewline
243 & 12 & 11.6654 & 0.334562 \tabularnewline
244 & 12 & 12.0936 & -0.0935692 \tabularnewline
245 & 15 & 13.2366 & 1.76335 \tabularnewline
246 & 11 & 10.578 & 0.421958 \tabularnewline
247 & 13 & 12.4875 & 0.512456 \tabularnewline
248 & 14 & 8.6223 & 5.3777 \tabularnewline
249 & 10 & 10.0271 & -0.0270819 \tabularnewline
250 & 12 & 11.3457 & 0.65431 \tabularnewline
251 & 15 & 12.6911 & 2.30895 \tabularnewline
252 & 13 & 11.7148 & 1.28525 \tabularnewline
253 & 13 & 13.9202 & -0.92019 \tabularnewline
254 & 13 & 13.4123 & -0.412329 \tabularnewline
255 & 12 & 11.5252 & 0.474803 \tabularnewline
256 & 12 & 12.3357 & -0.335707 \tabularnewline
257 & 9 & 10.5582 & -1.55824 \tabularnewline
258 & 9 & 11.1966 & -2.19655 \tabularnewline
259 & 15 & 12.2619 & 2.73809 \tabularnewline
260 & 10 & 14.6825 & -4.68251 \tabularnewline
261 & 14 & 13.3414 & 0.65863 \tabularnewline
262 & 15 & 13.198 & 1.80202 \tabularnewline
263 & 7 & 9.59724 & -2.59724 \tabularnewline
264 & 14 & 13.5539 & 0.446125 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226600&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]14[/C][C]14.1313[/C][C]-0.131296[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.4719[/C][C]2.52809[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]14.06[/C][C]-3.06002[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.762[/C][C]-2.76198[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]11.4859[/C][C]4.51414[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.7047[/C][C]3.29535[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.9007[/C][C]3.09932[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]15.2166[/C][C]-1.21663[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.3964[/C][C]-0.396405[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.5861[/C][C]0.41385[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.7076[/C][C]1.29245[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.7328[/C][C]3.26723[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.5633[/C][C]-3.56326[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.6528[/C][C]2.34716[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.8675[/C][C]2.1325[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.5519[/C][C]0.448108[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]14.0597[/C][C]-0.0597227[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.8942[/C][C]1.10579[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.497[/C][C]-1.49705[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.9383[/C][C]2.06175[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.4765[/C][C]2.52346[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.8415[/C][C]-2.84149[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.5109[/C][C]-0.510914[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.6675[/C][C]-1.66747[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.4972[/C][C]1.50277[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]16.0287[/C][C]-7.02871[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.241[/C][C]0.758966[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.4093[/C][C]0.590695[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]14.1022[/C][C]0.897843[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]14.0787[/C][C]-3.07875[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.836[/C][C]0.164011[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.8817[/C][C]0.118259[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]15.2361[/C][C]1.76386[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.3693[/C][C]-0.369342[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14.1354[/C][C]-0.135426[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.7289[/C][C]0.271116[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]11.0896[/C][C]-2.08959[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.4464[/C][C]0.553626[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.48[/C][C]1.51997[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.3347[/C][C]-2.33466[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.8152[/C][C]-0.815214[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.8067[/C][C]2.19334[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.8032[/C][C]0.196758[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.2682[/C][C]-1.26823[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.7379[/C][C]0.262111[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.7548[/C][C]-2.7548[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.3755[/C][C]-0.375492[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.9864[/C][C]0.0135905[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.653[/C][C]3.34698[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.8527[/C][C]-1.8527[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.2798[/C][C]0.720231[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.5801[/C][C]0.419887[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.8343[/C][C]-0.834309[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.6039[/C][C]-1.60388[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.3302[/C][C]-2.3302[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.829[/C][C]1.17096[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.2655[/C][C]1.73452[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.4901[/C][C]-0.490097[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.2824[/C][C]-3.28241[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.4834[/C][C]-1.48342[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.9217[/C][C]-2.92173[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.6794[/C][C]-1.67941[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.6854[/C][C]-3.68535[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.1589[/C][C]0.841138[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.657[/C][C]1.34297[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.1754[/C][C]-5.1754[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.6693[/C][C]-1.66933[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.638[/C][C]-2.63802[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.6714[/C][C]1.32864[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.7418[/C][C]1.25815[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.6892[/C][C]0.310795[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.8519[/C][C]3.14815[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.5188[/C][C]0.481247[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.318[/C][C]-0.318001[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]15.0697[/C][C]-2.06971[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.3126[/C][C]-0.312618[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]14.0696[/C][C]2.93042[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.5846[/C][C]0.415384[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.934[/C][C]1.06598[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]14.9938[/C][C]-1.99377[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]15.0182[/C][C]-0.018209[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.5436[/C][C]-0.543591[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.3865[/C][C]1.61354[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.3873[/C][C]0.612732[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.2357[/C][C]-0.235727[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]14.1611[/C][C]0.838887[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.3463[/C][C]-0.346253[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.8329[/C][C]0.167131[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.6661[/C][C]-3.66605[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.8712[/C][C]3.12877[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.8198[/C][C]0.180179[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.2632[/C][C]0.736799[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.4217[/C][C]0.578336[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.1179[/C][C]-1.11794[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]15.0692[/C][C]0.930835[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.8551[/C][C]-0.855136[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.9702[/C][C]-0.970221[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.9839[/C][C]2.01606[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]15.1235[/C][C]-0.123534[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.1638[/C][C]1.83623[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]13.006[/C][C]-1.006[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]14.9678[/C][C]1.03215[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.4356[/C][C]-3.43561[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.1859[/C][C]1.81409[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.4705[/C][C]-2.47053[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.915[/C][C]1.08504[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9534[/C][C]2.04657[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.8364[/C][C]-2.83643[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.29453[/C][C]0.705467[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.934[/C][C]1.06599[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.2046[/C][C]-2.20457[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.2907[/C][C]-2.29075[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]12.1157[/C][C]1.88426[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.1647[/C][C]3.83531[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.5057[/C][C]0.494315[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]12.9817[/C][C]1.01835[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.8508[/C][C]0.149162[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.0932[/C][C]-1.09317[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.7127[/C][C]0.287277[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.5543[/C][C]-0.554262[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.5354[/C][C]0.464619[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.9063[/C][C]0.0937088[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.8051[/C][C]-0.805096[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.5064[/C][C]0.493565[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.6814[/C][C]-1.68144[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.1463[/C][C]0.853714[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.2314[/C][C]1.76864[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.8857[/C][C]4.11432[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5821[/C][C]1.41787[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.6241[/C][C]-1.62411[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.6978[/C][C]-1.69782[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.2726[/C][C]-0.272637[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.6011[/C][C]2.39889[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.1682[/C][C]0.831837[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.6888[/C][C]2.31117[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.474[/C][C]1.526[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.2176[/C][C]0.782403[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]11.9531[/C][C]-0.953055[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.1646[/C][C]0.835442[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.8148[/C][C]-0.814846[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.5725[/C][C]0.427469[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.8248[/C][C]2.1752[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.528[/C][C]-0.527952[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.2018[/C][C]0.798194[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.607[/C][C]1.39304[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.3131[/C][C]1.68693[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.2765[/C][C]-2.27651[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.5576[/C][C]-2.55761[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.4963[/C][C]-2.49627[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.2447[/C][C]1.75533[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.4728[/C][C]0.527178[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.3489[/C][C]0.651064[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.4069[/C][C]-2.40686[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.5186[/C][C]-2.51862[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.7323[/C][C]1.26768[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.5356[/C][C]0.464379[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.3124[/C][C]0.68764[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.7545[/C][C]4.24549[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.5175[/C][C]-2.51752[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.1117[/C][C]-0.111748[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.4998[/C][C]0.500238[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.3245[/C][C]0.675503[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.3144[/C][C]0.685589[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.4823[/C][C]4.51771[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.971[/C][C]-1.971[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]9.21649[/C][C]1.78351[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.0815[/C][C]-0.0815225[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.8647[/C][C]-0.864711[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.692[/C][C]-3.69204[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.9438[/C][C]-2.9438[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.6182[/C][C]0.381847[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.098[/C][C]1.902[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]13.9829[/C][C]-4.98289[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.3816[/C][C]1.61835[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.2897[/C][C]2.71033[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.235[/C][C]-2.23498[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.2949[/C][C]-3.29486[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.5048[/C][C]0.495185[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.4755[/C][C]1.52453[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.1763[/C][C]-2.17628[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]13.9367[/C][C]0.0632546[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.7142[/C][C]-1.71417[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.4737[/C][C]0.526308[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.8395[/C][C]-0.839457[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]14.0428[/C][C]1.95719[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.5946[/C][C]1.40537[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.4435[/C][C]0.556489[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.2007[/C][C]0.799306[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.463[/C][C]0.537006[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.2952[/C][C]0.704844[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.5791[/C][C]-1.57911[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.8518[/C][C]-0.851767[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.7671[/C][C]2.23287[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.3301[/C][C]-1.33013[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.028[/C][C]1.97205[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]13.8742[/C][C]-1.8742[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.673[/C][C]2.32699[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.2861[/C][C]0.713877[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.078[/C][C]-3.07799[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.6559[/C][C]-0.655936[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]11.9888[/C][C]-2.98879[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.6735[/C][C]1.32645[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]14.0173[/C][C]2.9827[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.3744[/C][C]0.62557[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.3239[/C][C]0.67608[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.5757[/C][C]1.42428[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.3157[/C][C]-0.315749[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.3219[/C][C]3.6781[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.7752[/C][C]0.224841[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.1779[/C][C]1.82212[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.5359[/C][C]-2.53594[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.3696[/C][C]1.63037[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.113[/C][C]-1.11296[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.7137[/C][C]-3.71368[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]11.9504[/C][C]-0.950362[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.0991[/C][C]1.90087[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.684[/C][C]2.31597[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.062[/C][C]-0.062038[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.86871[/C][C]-1.86871[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.3711[/C][C]1.62894[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.6923[/C][C]-2.69228[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.4125[/C][C]2.58749[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]11.9223[/C][C]-1.92234[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.6526[/C][C]0.347363[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.57397[/C][C]-0.573967[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.2672[/C][C]1.73278[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]13.5776[/C][C]5.42239[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.5121[/C][C]-1.5121[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.36786[/C][C]-1.36786[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.1776[/C][C]-2.1776[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.6835[/C][C]0.316474[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]11.8451[/C][C]-2.84509[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]14.7034[/C][C]0.296601[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.0867[/C][C]0.913321[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]14.661[/C][C]1.33904[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.633[/C][C]-1.63303[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.2603[/C][C]0.739734[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]12.509[/C][C]0.490961[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.0724[/C][C]-4.07244[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.4002[/C][C]-2.40023[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.6582[/C][C]-2.65816[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.4534[/C][C]-2.45339[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.6654[/C][C]0.334562[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.0936[/C][C]-0.0935692[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.2366[/C][C]1.76335[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.578[/C][C]0.421958[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.4875[/C][C]0.512456[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.6223[/C][C]5.3777[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.0271[/C][C]-0.0270819[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.3457[/C][C]0.65431[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.6911[/C][C]2.30895[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.7148[/C][C]1.28525[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]13.9202[/C][C]-0.92019[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.4123[/C][C]-0.412329[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.5252[/C][C]0.474803[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.3357[/C][C]-0.335707[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.5582[/C][C]-1.55824[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.1966[/C][C]-2.19655[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.2619[/C][C]2.73809[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.6825[/C][C]-4.68251[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.3414[/C][C]0.65863[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.198[/C][C]1.80202[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.59724[/C][C]-2.59724[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.5539[/C][C]0.446125[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226600&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226600&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
11414.1313-0.131296
21815.47192.52809
31114.06-3.06002
41214.762-2.76198
51611.48594.51414
61814.70473.29535
71410.90073.09932
81415.2166-1.21663
91515.3964-0.396405
101514.58610.41385
111715.70761.29245
121915.73283.26723
131013.5633-3.56326
141613.65282.34716
151815.86752.1325
161413.55190.448108
171414.0597-0.0597227
181715.89421.10579
191415.497-1.49705
201613.93832.06175
211815.47652.52346
221113.8415-2.84149
231414.5109-0.510914
241213.6675-1.66747
251715.49721.50277
26916.0287-7.02871
271615.2410.758966
281413.40930.590695
291514.10220.897843
301114.0787-3.07875
311615.8360.164011
321312.88170.118259
331715.23611.76386
341515.3693-0.369342
351414.1354-0.135426
361615.72890.271116
37911.0896-2.08959
381514.44640.553626
391715.481.51997
401315.3347-2.33466
411515.8152-0.815214
421613.80672.19334
431615.80320.196758
441213.2682-1.26823
451514.73790.262111
461113.7548-2.7548
471515.3755-0.375492
481514.98640.0135905
491713.6533.34698
501314.8527-1.8527
511615.27980.720231
521413.58010.419887
531111.8343-0.834309
541213.6039-1.60388
551214.3302-2.3302
561513.8291.17096
571614.26551.73452
581515.4901-0.490097
591215.2824-3.28241
601213.4834-1.48342
61810.9217-2.92173
621314.6794-1.67941
631114.6854-3.68535
641413.15890.841138
651513.6571.34297
661015.1754-5.1754
671112.6693-1.66933
681214.638-2.63802
691513.67141.32864
701513.74181.25815
711413.68920.310795
721612.85193.14815
731514.51880.481247
741515.318-0.318001
751315.0697-2.06971
761212.3126-0.312618
771714.06962.93042
781312.58460.415384
791513.9341.06598
801314.9938-1.99377
811515.0182-0.018209
821515.5436-0.543591
831614.38651.61354
841514.38730.612732
851414.2357-0.235727
861514.16110.838887
871414.3463-0.346253
881312.83290.167131
89710.6661-3.66605
901713.87123.12877
911312.81980.180179
921514.26320.736799
931413.42170.578336
941314.1179-1.11794
951615.06920.930835
961212.8551-0.855136
971414.9702-0.970221
981714.98392.01606
991515.1235-0.123534
1001715.16381.83623
1011213.006-1.006
1021614.96781.03215
1031114.4356-3.43561
1041513.18591.81409
105911.4705-2.47053
1061614.9151.08504
1071512.95342.04657
1081012.8364-2.83643
109109.294530.705467
1101513.9341.06599
1111113.2046-2.20457
1121315.2907-2.29075
1131412.11571.88426
1141814.16473.83531
1151615.50570.494315
1161412.98171.01835
1171413.85080.149162
1181415.0932-1.09317
1191413.71270.287277
1201212.5543-0.554262
1211413.53540.464619
1221514.90630.0937088
1231515.8051-0.805096
1241514.50640.493565
1251314.6814-1.68144
1261716.14630.853714
1271715.23141.76864
1281914.88574.11432
1291513.58211.41787
1301314.6241-1.62411
131910.6978-1.69782
1321515.2726-0.272637
1331512.60112.39889
1341514.16820.831837
1351613.68882.31117
136119.4741.526
1371413.21760.782403
1381111.9531-0.953055
1391514.16460.835442
1401313.8148-0.814846
1411514.57250.427469
1421613.82482.1752
1431414.528-0.527952
1441514.20180.798194
1451614.6071.39304
1461614.31311.68693
1471113.2765-2.27651
1481214.5576-2.55761
149911.4963-2.49627
1501614.24471.75533
1511312.47280.527178
1521615.34890.651064
1531214.4069-2.40686
154911.5186-2.51862
1551311.73231.26768
1561312.53560.464379
1571413.31240.68764
1581914.75454.24549
1591315.5175-2.51752
1601212.1117-0.111748
1611312.49980.500238
162109.32450.675503
1631413.31440.685589
1641611.48234.51771
1651011.971-1.971
166119.216491.78351
1671414.0815-0.0815225
1681212.8647-0.864711
169912.692-3.69204
170911.9438-2.9438
1711110.61820.381847
1721614.0981.902
173913.9829-4.98289
1741311.38161.61835
1751613.28972.71033
1761315.235-2.23498
177912.2949-3.29486
1781211.50480.495185
1791614.47551.52453
1801113.1763-2.17628
1811413.93670.0632546
1821314.7142-1.71417
1831514.47370.526308
1841414.8395-0.839457
1851614.04281.95719
1861311.59461.40537
1871413.44350.556489
1881514.20070.799306
1891312.4630.537006
1901110.29520.704844
1911112.5791-1.57911
1921414.8518-0.851767
1931512.76712.23287
1941112.3301-1.33013
1951513.0281.97205
1961213.8742-1.8742
1971411.6732.32699
1981413.28610.713877
199811.078-3.07799
2001313.6559-0.655936
201911.9888-2.98879
2021513.67351.32645
2031714.01732.9827
2041312.37440.62557
2051514.32390.67608
2061513.57571.42428
2071414.3157-0.315749
2081612.32193.6781
2091312.77520.224841
2101614.17791.82212
211911.5359-2.53594
2121614.36961.63037
2131112.113-1.11296
2141013.7137-3.71368
2151111.9504-0.950362
2161513.09911.90087
2171714.6842.31597
2181414.062-0.062038
21989.86871-1.86871
2201513.37111.62894
2211113.6923-2.69228
2221613.41252.58749
2231011.9223-1.92234
2241514.65260.347363
22599.57397-0.573967
2261614.26721.73278
2271913.57765.42239
2281213.5121-1.5121
22989.36786-1.36786
2301113.1776-2.1776
2311413.68350.316474
232911.8451-2.84509
2331514.70340.296601
2341312.08670.913321
2351614.6611.33904
2361112.633-1.63303
2371211.26030.739734
2381312.5090.490961
2391014.0724-4.07244
2401113.4002-2.40023
2411214.6582-2.65816
242810.4534-2.45339
2431211.66540.334562
2441212.0936-0.0935692
2451513.23661.76335
2461110.5780.421958
2471312.48750.512456
248148.62235.3777
2491010.0271-0.0270819
2501211.34570.65431
2511512.69112.30895
2521311.71481.28525
2531313.9202-0.92019
2541313.4123-0.412329
2551211.52520.474803
2561212.3357-0.335707
257910.5582-1.55824
258911.1966-2.19655
2591512.26192.73809
2601014.6825-4.68251
2611413.34140.65863
2621513.1981.80202
26379.59724-2.59724
2641413.55390.446125






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.04250680.08501370.957493
120.7947010.4105980.205299
130.9824130.03517430.0175871
140.980720.03855940.0192797
150.9811950.037610.018805
160.9697250.06054960.0302748
170.9655490.06890120.0344506
180.9492470.1015050.0507526
190.9337560.1324880.0662441
200.9183580.1632830.0816417
210.9158990.1682020.084101
220.9648210.07035780.0351789
230.9505050.09898910.0494946
240.9388860.1222270.0611135
250.9188050.162390.081195
260.9985060.002987970.00149398
270.9979450.004109170.00205459
280.9968180.006363460.00318173
290.9953530.009293710.00464686
300.9963020.007395340.00369767
310.9947770.01044670.00522335
320.9922890.01542250.00771124
330.9921920.01561560.0078078
340.9887580.02248370.0112418
350.9841450.03171080.0158554
360.9783360.04332840.0216642
370.9806010.03879820.0193991
380.9751160.04976750.0248838
390.9747070.05058590.0252929
400.9713680.05726490.0286325
410.9622270.07554520.0377726
420.9649620.0700750.0350375
430.9570060.08598830.0429942
440.9462810.1074370.0537185
450.9321580.1356840.067842
460.934590.1308210.0654105
470.9211090.1577820.078891
480.9041120.1917770.0958884
490.9387060.1225870.0612937
500.9316370.1367260.068363
510.9198030.1603940.080197
520.9029150.194170.0970848
530.88450.2310.1155
540.8696570.2606860.130343
550.8587070.2825870.141293
560.8442490.3115020.155751
570.8388160.3223690.161184
580.8110130.3779740.188987
590.8354510.3290970.164549
600.8189420.3621160.181058
610.8302780.3394440.169722
620.8129560.3740880.187044
630.850560.2988810.14944
640.8477360.3045270.152264
650.8498130.3003740.150187
660.9228470.1543060.077153
670.911880.176240.0881202
680.9117770.1764450.0882226
690.9151410.1697180.084859
700.9150830.1698330.0849165
710.9022530.1954940.0977469
720.9332180.1335650.0667823
730.9227030.1545940.0772971
740.9077740.1844510.0922256
750.8990970.2018070.100903
760.8816020.2367960.118398
770.9097710.1804590.0902293
780.8959310.2081380.104069
790.8899840.2200330.110016
800.8820130.2359740.117987
810.8630670.2738660.136933
820.8421890.3156220.157811
830.8423180.3153650.157682
840.82410.35180.1759
850.7998810.4002380.200119
860.7764910.4470180.223509
870.7480020.5039970.251998
880.7189710.5620570.281029
890.7872330.4255330.212767
900.8255920.3488160.174408
910.8040580.3918840.195942
920.7794840.4410330.220516
930.7595220.4809550.240478
940.7359080.5281840.264092
950.7124860.5750280.287514
960.6852690.6294610.314731
970.6586540.6826930.341346
980.6638880.6722240.336112
990.6294830.7410340.370517
1000.6248460.7503080.375154
1010.5991190.8017620.400881
1020.5716930.8566140.428307
1030.624790.7504190.37521
1040.6115470.7769070.388453
1050.6283120.7433750.371688
1060.6043620.7912760.395638
1070.5970420.8059150.402958
1080.6323370.7353260.367663
1090.5990440.8019130.400956
1100.573060.853880.42694
1110.5776280.8447440.422372
1120.6016790.7966420.398321
1130.6083040.7833920.391696
1140.6941640.6116720.305836
1150.6662760.6674480.333724
1160.6400870.7198250.359913
1170.6064110.7871790.393589
1180.5820570.8358850.417943
1190.5465480.9069040.453452
1200.5136090.9727820.486391
1210.4879440.9758870.512056
1220.4532030.9064050.546797
1230.424670.849340.57533
1240.3944640.7889270.605536
1250.384930.769860.61507
1260.3569690.7139380.643031
1270.3419250.6838490.658075
1280.4454120.8908240.554588
1290.425660.8513190.57434
1300.4150010.8300030.584999
1310.4041290.8082570.595871
1320.3723760.7447510.627624
1330.392140.784280.60786
1340.3623820.7247640.637618
1350.3726190.7452390.627381
1360.3620710.7241420.637929
1370.3326230.6652460.667377
1380.3089650.617930.691035
1390.2816650.563330.718335
1400.2581930.5163870.741807
1410.2310530.4621050.768947
1420.2337220.4674450.766278
1430.2088610.4177230.791139
1440.1890.3780.811
1450.1738110.3476220.826189
1460.1657920.3315840.834208
1470.1747470.3494950.825253
1480.1931970.3863950.806803
1490.2130530.4261050.786947
1500.2083430.4166860.791657
1510.184880.3697610.81512
1520.1639360.3278710.836064
1530.1757120.3514230.824288
1540.1930350.3860690.806965
1550.1770430.3540860.822957
1560.1565170.3130340.843483
1570.1381630.2763260.861837
1580.2207130.4414270.779287
1590.2392220.4784440.760778
1600.2156840.4313680.784316
1610.1925290.3850580.807471
1620.1703780.3407560.829622
1630.1495730.2991470.850427
1640.2492280.4984570.750772
1650.2446280.4892570.755372
1660.2408740.4817480.759126
1670.2131090.4262190.786891
1680.1923440.3846880.807656
1690.246770.4935410.75323
1700.2763010.5526010.723699
1710.2471810.4943630.752819
1720.2432050.4864110.756795
1730.4106890.8213780.589311
1740.392220.784440.60778
1750.412770.825540.58723
1760.4246740.8493480.575326
1770.4882420.9764840.511758
1780.4513520.9027030.548648
1790.4291070.8582130.570893
1800.4366350.873270.563365
1810.4012520.8025050.598748
1820.4053020.8106030.594698
1830.3692490.7384980.630751
1840.3472230.6944450.652777
1850.3480090.6960180.651991
1860.3332560.6665120.666744
1870.2988640.5977290.701136
1880.2677170.5354350.732283
1890.2368460.4736910.763154
1900.2121690.4243380.787831
1910.2249650.449930.775035
1920.2080770.4161550.791923
1930.2144370.4288740.785563
1940.2054260.4108520.794574
1950.2019530.4039060.798047
1960.2146870.4293750.785313
1970.2534980.5069960.746502
1980.2346830.4693650.765317
1990.2707650.5415310.729235
2000.2390150.4780310.760985
2010.2800280.5600560.719972
2020.2546540.5093070.745346
2030.2921240.5842490.707876
2040.2599690.5199390.740031
2050.2274570.4549150.772543
2060.2073970.4147950.792603
2070.1774360.3548720.822564
2080.2030280.4060560.796972
2090.1732970.3465940.826703
2100.182880.365760.81712
2110.2023710.4047420.797629
2120.1931380.3862760.806862
2130.1677030.3354060.832297
2140.2074970.4149940.792503
2150.1844280.3688570.815572
2160.173170.3463410.82683
2170.2035130.4070270.796487
2180.1756350.351270.824365
2190.1622090.3244180.837791
2200.1795860.3591710.820414
2210.1840360.3680730.815964
2220.1817470.3634930.818253
2230.1651970.3303950.834803
2240.1371220.2742450.862878
2250.1345480.2690970.865452
2260.1653470.3306930.834653
2270.393670.787340.60633
2280.352070.7041390.64793
2290.3131510.6263010.686849
2300.2872840.5745680.712716
2310.2510730.5021460.748927
2320.280320.5606410.71968
2330.2374380.4748760.762562
2340.1992210.3984420.800779
2350.2063150.412630.793685
2360.1780840.3561670.821916
2370.1537060.3074120.846294
2380.1184560.2369120.881544
2390.2270570.4541140.772943
2400.2370290.4740580.762971
2410.2406920.4813840.759308
2420.8584860.2830280.141514
2430.8088030.3823950.191197
2440.7549860.4900280.245014
2450.7014370.5971260.298563
2460.6325390.7349210.367461
2470.6468170.7063670.353183
2480.650390.699220.34961
2490.5449410.9101180.455059
2500.4595640.9191280.540436
2510.3999390.7998780.600061
2520.9055950.1888110.0944054
2530.8175870.3648260.182413

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.0425068 & 0.0850137 & 0.957493 \tabularnewline
12 & 0.794701 & 0.410598 & 0.205299 \tabularnewline
13 & 0.982413 & 0.0351743 & 0.0175871 \tabularnewline
14 & 0.98072 & 0.0385594 & 0.0192797 \tabularnewline
15 & 0.981195 & 0.03761 & 0.018805 \tabularnewline
16 & 0.969725 & 0.0605496 & 0.0302748 \tabularnewline
17 & 0.965549 & 0.0689012 & 0.0344506 \tabularnewline
18 & 0.949247 & 0.101505 & 0.0507526 \tabularnewline
19 & 0.933756 & 0.132488 & 0.0662441 \tabularnewline
20 & 0.918358 & 0.163283 & 0.0816417 \tabularnewline
21 & 0.915899 & 0.168202 & 0.084101 \tabularnewline
22 & 0.964821 & 0.0703578 & 0.0351789 \tabularnewline
23 & 0.950505 & 0.0989891 & 0.0494946 \tabularnewline
24 & 0.938886 & 0.122227 & 0.0611135 \tabularnewline
25 & 0.918805 & 0.16239 & 0.081195 \tabularnewline
26 & 0.998506 & 0.00298797 & 0.00149398 \tabularnewline
27 & 0.997945 & 0.00410917 & 0.00205459 \tabularnewline
28 & 0.996818 & 0.00636346 & 0.00318173 \tabularnewline
29 & 0.995353 & 0.00929371 & 0.00464686 \tabularnewline
30 & 0.996302 & 0.00739534 & 0.00369767 \tabularnewline
31 & 0.994777 & 0.0104467 & 0.00522335 \tabularnewline
32 & 0.992289 & 0.0154225 & 0.00771124 \tabularnewline
33 & 0.992192 & 0.0156156 & 0.0078078 \tabularnewline
34 & 0.988758 & 0.0224837 & 0.0112418 \tabularnewline
35 & 0.984145 & 0.0317108 & 0.0158554 \tabularnewline
36 & 0.978336 & 0.0433284 & 0.0216642 \tabularnewline
37 & 0.980601 & 0.0387982 & 0.0193991 \tabularnewline
38 & 0.975116 & 0.0497675 & 0.0248838 \tabularnewline
39 & 0.974707 & 0.0505859 & 0.0252929 \tabularnewline
40 & 0.971368 & 0.0572649 & 0.0286325 \tabularnewline
41 & 0.962227 & 0.0755452 & 0.0377726 \tabularnewline
42 & 0.964962 & 0.070075 & 0.0350375 \tabularnewline
43 & 0.957006 & 0.0859883 & 0.0429942 \tabularnewline
44 & 0.946281 & 0.107437 & 0.0537185 \tabularnewline
45 & 0.932158 & 0.135684 & 0.067842 \tabularnewline
46 & 0.93459 & 0.130821 & 0.0654105 \tabularnewline
47 & 0.921109 & 0.157782 & 0.078891 \tabularnewline
48 & 0.904112 & 0.191777 & 0.0958884 \tabularnewline
49 & 0.938706 & 0.122587 & 0.0612937 \tabularnewline
50 & 0.931637 & 0.136726 & 0.068363 \tabularnewline
51 & 0.919803 & 0.160394 & 0.080197 \tabularnewline
52 & 0.902915 & 0.19417 & 0.0970848 \tabularnewline
53 & 0.8845 & 0.231 & 0.1155 \tabularnewline
54 & 0.869657 & 0.260686 & 0.130343 \tabularnewline
55 & 0.858707 & 0.282587 & 0.141293 \tabularnewline
56 & 0.844249 & 0.311502 & 0.155751 \tabularnewline
57 & 0.838816 & 0.322369 & 0.161184 \tabularnewline
58 & 0.811013 & 0.377974 & 0.188987 \tabularnewline
59 & 0.835451 & 0.329097 & 0.164549 \tabularnewline
60 & 0.818942 & 0.362116 & 0.181058 \tabularnewline
61 & 0.830278 & 0.339444 & 0.169722 \tabularnewline
62 & 0.812956 & 0.374088 & 0.187044 \tabularnewline
63 & 0.85056 & 0.298881 & 0.14944 \tabularnewline
64 & 0.847736 & 0.304527 & 0.152264 \tabularnewline
65 & 0.849813 & 0.300374 & 0.150187 \tabularnewline
66 & 0.922847 & 0.154306 & 0.077153 \tabularnewline
67 & 0.91188 & 0.17624 & 0.0881202 \tabularnewline
68 & 0.911777 & 0.176445 & 0.0882226 \tabularnewline
69 & 0.915141 & 0.169718 & 0.084859 \tabularnewline
70 & 0.915083 & 0.169833 & 0.0849165 \tabularnewline
71 & 0.902253 & 0.195494 & 0.0977469 \tabularnewline
72 & 0.933218 & 0.133565 & 0.0667823 \tabularnewline
73 & 0.922703 & 0.154594 & 0.0772971 \tabularnewline
74 & 0.907774 & 0.184451 & 0.0922256 \tabularnewline
75 & 0.899097 & 0.201807 & 0.100903 \tabularnewline
76 & 0.881602 & 0.236796 & 0.118398 \tabularnewline
77 & 0.909771 & 0.180459 & 0.0902293 \tabularnewline
78 & 0.895931 & 0.208138 & 0.104069 \tabularnewline
79 & 0.889984 & 0.220033 & 0.110016 \tabularnewline
80 & 0.882013 & 0.235974 & 0.117987 \tabularnewline
81 & 0.863067 & 0.273866 & 0.136933 \tabularnewline
82 & 0.842189 & 0.315622 & 0.157811 \tabularnewline
83 & 0.842318 & 0.315365 & 0.157682 \tabularnewline
84 & 0.8241 & 0.3518 & 0.1759 \tabularnewline
85 & 0.799881 & 0.400238 & 0.200119 \tabularnewline
86 & 0.776491 & 0.447018 & 0.223509 \tabularnewline
87 & 0.748002 & 0.503997 & 0.251998 \tabularnewline
88 & 0.718971 & 0.562057 & 0.281029 \tabularnewline
89 & 0.787233 & 0.425533 & 0.212767 \tabularnewline
90 & 0.825592 & 0.348816 & 0.174408 \tabularnewline
91 & 0.804058 & 0.391884 & 0.195942 \tabularnewline
92 & 0.779484 & 0.441033 & 0.220516 \tabularnewline
93 & 0.759522 & 0.480955 & 0.240478 \tabularnewline
94 & 0.735908 & 0.528184 & 0.264092 \tabularnewline
95 & 0.712486 & 0.575028 & 0.287514 \tabularnewline
96 & 0.685269 & 0.629461 & 0.314731 \tabularnewline
97 & 0.658654 & 0.682693 & 0.341346 \tabularnewline
98 & 0.663888 & 0.672224 & 0.336112 \tabularnewline
99 & 0.629483 & 0.741034 & 0.370517 \tabularnewline
100 & 0.624846 & 0.750308 & 0.375154 \tabularnewline
101 & 0.599119 & 0.801762 & 0.400881 \tabularnewline
102 & 0.571693 & 0.856614 & 0.428307 \tabularnewline
103 & 0.62479 & 0.750419 & 0.37521 \tabularnewline
104 & 0.611547 & 0.776907 & 0.388453 \tabularnewline
105 & 0.628312 & 0.743375 & 0.371688 \tabularnewline
106 & 0.604362 & 0.791276 & 0.395638 \tabularnewline
107 & 0.597042 & 0.805915 & 0.402958 \tabularnewline
108 & 0.632337 & 0.735326 & 0.367663 \tabularnewline
109 & 0.599044 & 0.801913 & 0.400956 \tabularnewline
110 & 0.57306 & 0.85388 & 0.42694 \tabularnewline
111 & 0.577628 & 0.844744 & 0.422372 \tabularnewline
112 & 0.601679 & 0.796642 & 0.398321 \tabularnewline
113 & 0.608304 & 0.783392 & 0.391696 \tabularnewline
114 & 0.694164 & 0.611672 & 0.305836 \tabularnewline
115 & 0.666276 & 0.667448 & 0.333724 \tabularnewline
116 & 0.640087 & 0.719825 & 0.359913 \tabularnewline
117 & 0.606411 & 0.787179 & 0.393589 \tabularnewline
118 & 0.582057 & 0.835885 & 0.417943 \tabularnewline
119 & 0.546548 & 0.906904 & 0.453452 \tabularnewline
120 & 0.513609 & 0.972782 & 0.486391 \tabularnewline
121 & 0.487944 & 0.975887 & 0.512056 \tabularnewline
122 & 0.453203 & 0.906405 & 0.546797 \tabularnewline
123 & 0.42467 & 0.84934 & 0.57533 \tabularnewline
124 & 0.394464 & 0.788927 & 0.605536 \tabularnewline
125 & 0.38493 & 0.76986 & 0.61507 \tabularnewline
126 & 0.356969 & 0.713938 & 0.643031 \tabularnewline
127 & 0.341925 & 0.683849 & 0.658075 \tabularnewline
128 & 0.445412 & 0.890824 & 0.554588 \tabularnewline
129 & 0.42566 & 0.851319 & 0.57434 \tabularnewline
130 & 0.415001 & 0.830003 & 0.584999 \tabularnewline
131 & 0.404129 & 0.808257 & 0.595871 \tabularnewline
132 & 0.372376 & 0.744751 & 0.627624 \tabularnewline
133 & 0.39214 & 0.78428 & 0.60786 \tabularnewline
134 & 0.362382 & 0.724764 & 0.637618 \tabularnewline
135 & 0.372619 & 0.745239 & 0.627381 \tabularnewline
136 & 0.362071 & 0.724142 & 0.637929 \tabularnewline
137 & 0.332623 & 0.665246 & 0.667377 \tabularnewline
138 & 0.308965 & 0.61793 & 0.691035 \tabularnewline
139 & 0.281665 & 0.56333 & 0.718335 \tabularnewline
140 & 0.258193 & 0.516387 & 0.741807 \tabularnewline
141 & 0.231053 & 0.462105 & 0.768947 \tabularnewline
142 & 0.233722 & 0.467445 & 0.766278 \tabularnewline
143 & 0.208861 & 0.417723 & 0.791139 \tabularnewline
144 & 0.189 & 0.378 & 0.811 \tabularnewline
145 & 0.173811 & 0.347622 & 0.826189 \tabularnewline
146 & 0.165792 & 0.331584 & 0.834208 \tabularnewline
147 & 0.174747 & 0.349495 & 0.825253 \tabularnewline
148 & 0.193197 & 0.386395 & 0.806803 \tabularnewline
149 & 0.213053 & 0.426105 & 0.786947 \tabularnewline
150 & 0.208343 & 0.416686 & 0.791657 \tabularnewline
151 & 0.18488 & 0.369761 & 0.81512 \tabularnewline
152 & 0.163936 & 0.327871 & 0.836064 \tabularnewline
153 & 0.175712 & 0.351423 & 0.824288 \tabularnewline
154 & 0.193035 & 0.386069 & 0.806965 \tabularnewline
155 & 0.177043 & 0.354086 & 0.822957 \tabularnewline
156 & 0.156517 & 0.313034 & 0.843483 \tabularnewline
157 & 0.138163 & 0.276326 & 0.861837 \tabularnewline
158 & 0.220713 & 0.441427 & 0.779287 \tabularnewline
159 & 0.239222 & 0.478444 & 0.760778 \tabularnewline
160 & 0.215684 & 0.431368 & 0.784316 \tabularnewline
161 & 0.192529 & 0.385058 & 0.807471 \tabularnewline
162 & 0.170378 & 0.340756 & 0.829622 \tabularnewline
163 & 0.149573 & 0.299147 & 0.850427 \tabularnewline
164 & 0.249228 & 0.498457 & 0.750772 \tabularnewline
165 & 0.244628 & 0.489257 & 0.755372 \tabularnewline
166 & 0.240874 & 0.481748 & 0.759126 \tabularnewline
167 & 0.213109 & 0.426219 & 0.786891 \tabularnewline
168 & 0.192344 & 0.384688 & 0.807656 \tabularnewline
169 & 0.24677 & 0.493541 & 0.75323 \tabularnewline
170 & 0.276301 & 0.552601 & 0.723699 \tabularnewline
171 & 0.247181 & 0.494363 & 0.752819 \tabularnewline
172 & 0.243205 & 0.486411 & 0.756795 \tabularnewline
173 & 0.410689 & 0.821378 & 0.589311 \tabularnewline
174 & 0.39222 & 0.78444 & 0.60778 \tabularnewline
175 & 0.41277 & 0.82554 & 0.58723 \tabularnewline
176 & 0.424674 & 0.849348 & 0.575326 \tabularnewline
177 & 0.488242 & 0.976484 & 0.511758 \tabularnewline
178 & 0.451352 & 0.902703 & 0.548648 \tabularnewline
179 & 0.429107 & 0.858213 & 0.570893 \tabularnewline
180 & 0.436635 & 0.87327 & 0.563365 \tabularnewline
181 & 0.401252 & 0.802505 & 0.598748 \tabularnewline
182 & 0.405302 & 0.810603 & 0.594698 \tabularnewline
183 & 0.369249 & 0.738498 & 0.630751 \tabularnewline
184 & 0.347223 & 0.694445 & 0.652777 \tabularnewline
185 & 0.348009 & 0.696018 & 0.651991 \tabularnewline
186 & 0.333256 & 0.666512 & 0.666744 \tabularnewline
187 & 0.298864 & 0.597729 & 0.701136 \tabularnewline
188 & 0.267717 & 0.535435 & 0.732283 \tabularnewline
189 & 0.236846 & 0.473691 & 0.763154 \tabularnewline
190 & 0.212169 & 0.424338 & 0.787831 \tabularnewline
191 & 0.224965 & 0.44993 & 0.775035 \tabularnewline
192 & 0.208077 & 0.416155 & 0.791923 \tabularnewline
193 & 0.214437 & 0.428874 & 0.785563 \tabularnewline
194 & 0.205426 & 0.410852 & 0.794574 \tabularnewline
195 & 0.201953 & 0.403906 & 0.798047 \tabularnewline
196 & 0.214687 & 0.429375 & 0.785313 \tabularnewline
197 & 0.253498 & 0.506996 & 0.746502 \tabularnewline
198 & 0.234683 & 0.469365 & 0.765317 \tabularnewline
199 & 0.270765 & 0.541531 & 0.729235 \tabularnewline
200 & 0.239015 & 0.478031 & 0.760985 \tabularnewline
201 & 0.280028 & 0.560056 & 0.719972 \tabularnewline
202 & 0.254654 & 0.509307 & 0.745346 \tabularnewline
203 & 0.292124 & 0.584249 & 0.707876 \tabularnewline
204 & 0.259969 & 0.519939 & 0.740031 \tabularnewline
205 & 0.227457 & 0.454915 & 0.772543 \tabularnewline
206 & 0.207397 & 0.414795 & 0.792603 \tabularnewline
207 & 0.177436 & 0.354872 & 0.822564 \tabularnewline
208 & 0.203028 & 0.406056 & 0.796972 \tabularnewline
209 & 0.173297 & 0.346594 & 0.826703 \tabularnewline
210 & 0.18288 & 0.36576 & 0.81712 \tabularnewline
211 & 0.202371 & 0.404742 & 0.797629 \tabularnewline
212 & 0.193138 & 0.386276 & 0.806862 \tabularnewline
213 & 0.167703 & 0.335406 & 0.832297 \tabularnewline
214 & 0.207497 & 0.414994 & 0.792503 \tabularnewline
215 & 0.184428 & 0.368857 & 0.815572 \tabularnewline
216 & 0.17317 & 0.346341 & 0.82683 \tabularnewline
217 & 0.203513 & 0.407027 & 0.796487 \tabularnewline
218 & 0.175635 & 0.35127 & 0.824365 \tabularnewline
219 & 0.162209 & 0.324418 & 0.837791 \tabularnewline
220 & 0.179586 & 0.359171 & 0.820414 \tabularnewline
221 & 0.184036 & 0.368073 & 0.815964 \tabularnewline
222 & 0.181747 & 0.363493 & 0.818253 \tabularnewline
223 & 0.165197 & 0.330395 & 0.834803 \tabularnewline
224 & 0.137122 & 0.274245 & 0.862878 \tabularnewline
225 & 0.134548 & 0.269097 & 0.865452 \tabularnewline
226 & 0.165347 & 0.330693 & 0.834653 \tabularnewline
227 & 0.39367 & 0.78734 & 0.60633 \tabularnewline
228 & 0.35207 & 0.704139 & 0.64793 \tabularnewline
229 & 0.313151 & 0.626301 & 0.686849 \tabularnewline
230 & 0.287284 & 0.574568 & 0.712716 \tabularnewline
231 & 0.251073 & 0.502146 & 0.748927 \tabularnewline
232 & 0.28032 & 0.560641 & 0.71968 \tabularnewline
233 & 0.237438 & 0.474876 & 0.762562 \tabularnewline
234 & 0.199221 & 0.398442 & 0.800779 \tabularnewline
235 & 0.206315 & 0.41263 & 0.793685 \tabularnewline
236 & 0.178084 & 0.356167 & 0.821916 \tabularnewline
237 & 0.153706 & 0.307412 & 0.846294 \tabularnewline
238 & 0.118456 & 0.236912 & 0.881544 \tabularnewline
239 & 0.227057 & 0.454114 & 0.772943 \tabularnewline
240 & 0.237029 & 0.474058 & 0.762971 \tabularnewline
241 & 0.240692 & 0.481384 & 0.759308 \tabularnewline
242 & 0.858486 & 0.283028 & 0.141514 \tabularnewline
243 & 0.808803 & 0.382395 & 0.191197 \tabularnewline
244 & 0.754986 & 0.490028 & 0.245014 \tabularnewline
245 & 0.701437 & 0.597126 & 0.298563 \tabularnewline
246 & 0.632539 & 0.734921 & 0.367461 \tabularnewline
247 & 0.646817 & 0.706367 & 0.353183 \tabularnewline
248 & 0.65039 & 0.69922 & 0.34961 \tabularnewline
249 & 0.544941 & 0.910118 & 0.455059 \tabularnewline
250 & 0.459564 & 0.919128 & 0.540436 \tabularnewline
251 & 0.399939 & 0.799878 & 0.600061 \tabularnewline
252 & 0.905595 & 0.188811 & 0.0944054 \tabularnewline
253 & 0.817587 & 0.364826 & 0.182413 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226600&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]0.0425068[/C][C]0.0850137[/C][C]0.957493[/C][/ROW]
[ROW][C]12[/C][C]0.794701[/C][C]0.410598[/C][C]0.205299[/C][/ROW]
[ROW][C]13[/C][C]0.982413[/C][C]0.0351743[/C][C]0.0175871[/C][/ROW]
[ROW][C]14[/C][C]0.98072[/C][C]0.0385594[/C][C]0.0192797[/C][/ROW]
[ROW][C]15[/C][C]0.981195[/C][C]0.03761[/C][C]0.018805[/C][/ROW]
[ROW][C]16[/C][C]0.969725[/C][C]0.0605496[/C][C]0.0302748[/C][/ROW]
[ROW][C]17[/C][C]0.965549[/C][C]0.0689012[/C][C]0.0344506[/C][/ROW]
[ROW][C]18[/C][C]0.949247[/C][C]0.101505[/C][C]0.0507526[/C][/ROW]
[ROW][C]19[/C][C]0.933756[/C][C]0.132488[/C][C]0.0662441[/C][/ROW]
[ROW][C]20[/C][C]0.918358[/C][C]0.163283[/C][C]0.0816417[/C][/ROW]
[ROW][C]21[/C][C]0.915899[/C][C]0.168202[/C][C]0.084101[/C][/ROW]
[ROW][C]22[/C][C]0.964821[/C][C]0.0703578[/C][C]0.0351789[/C][/ROW]
[ROW][C]23[/C][C]0.950505[/C][C]0.0989891[/C][C]0.0494946[/C][/ROW]
[ROW][C]24[/C][C]0.938886[/C][C]0.122227[/C][C]0.0611135[/C][/ROW]
[ROW][C]25[/C][C]0.918805[/C][C]0.16239[/C][C]0.081195[/C][/ROW]
[ROW][C]26[/C][C]0.998506[/C][C]0.00298797[/C][C]0.00149398[/C][/ROW]
[ROW][C]27[/C][C]0.997945[/C][C]0.00410917[/C][C]0.00205459[/C][/ROW]
[ROW][C]28[/C][C]0.996818[/C][C]0.00636346[/C][C]0.00318173[/C][/ROW]
[ROW][C]29[/C][C]0.995353[/C][C]0.00929371[/C][C]0.00464686[/C][/ROW]
[ROW][C]30[/C][C]0.996302[/C][C]0.00739534[/C][C]0.00369767[/C][/ROW]
[ROW][C]31[/C][C]0.994777[/C][C]0.0104467[/C][C]0.00522335[/C][/ROW]
[ROW][C]32[/C][C]0.992289[/C][C]0.0154225[/C][C]0.00771124[/C][/ROW]
[ROW][C]33[/C][C]0.992192[/C][C]0.0156156[/C][C]0.0078078[/C][/ROW]
[ROW][C]34[/C][C]0.988758[/C][C]0.0224837[/C][C]0.0112418[/C][/ROW]
[ROW][C]35[/C][C]0.984145[/C][C]0.0317108[/C][C]0.0158554[/C][/ROW]
[ROW][C]36[/C][C]0.978336[/C][C]0.0433284[/C][C]0.0216642[/C][/ROW]
[ROW][C]37[/C][C]0.980601[/C][C]0.0387982[/C][C]0.0193991[/C][/ROW]
[ROW][C]38[/C][C]0.975116[/C][C]0.0497675[/C][C]0.0248838[/C][/ROW]
[ROW][C]39[/C][C]0.974707[/C][C]0.0505859[/C][C]0.0252929[/C][/ROW]
[ROW][C]40[/C][C]0.971368[/C][C]0.0572649[/C][C]0.0286325[/C][/ROW]
[ROW][C]41[/C][C]0.962227[/C][C]0.0755452[/C][C]0.0377726[/C][/ROW]
[ROW][C]42[/C][C]0.964962[/C][C]0.070075[/C][C]0.0350375[/C][/ROW]
[ROW][C]43[/C][C]0.957006[/C][C]0.0859883[/C][C]0.0429942[/C][/ROW]
[ROW][C]44[/C][C]0.946281[/C][C]0.107437[/C][C]0.0537185[/C][/ROW]
[ROW][C]45[/C][C]0.932158[/C][C]0.135684[/C][C]0.067842[/C][/ROW]
[ROW][C]46[/C][C]0.93459[/C][C]0.130821[/C][C]0.0654105[/C][/ROW]
[ROW][C]47[/C][C]0.921109[/C][C]0.157782[/C][C]0.078891[/C][/ROW]
[ROW][C]48[/C][C]0.904112[/C][C]0.191777[/C][C]0.0958884[/C][/ROW]
[ROW][C]49[/C][C]0.938706[/C][C]0.122587[/C][C]0.0612937[/C][/ROW]
[ROW][C]50[/C][C]0.931637[/C][C]0.136726[/C][C]0.068363[/C][/ROW]
[ROW][C]51[/C][C]0.919803[/C][C]0.160394[/C][C]0.080197[/C][/ROW]
[ROW][C]52[/C][C]0.902915[/C][C]0.19417[/C][C]0.0970848[/C][/ROW]
[ROW][C]53[/C][C]0.8845[/C][C]0.231[/C][C]0.1155[/C][/ROW]
[ROW][C]54[/C][C]0.869657[/C][C]0.260686[/C][C]0.130343[/C][/ROW]
[ROW][C]55[/C][C]0.858707[/C][C]0.282587[/C][C]0.141293[/C][/ROW]
[ROW][C]56[/C][C]0.844249[/C][C]0.311502[/C][C]0.155751[/C][/ROW]
[ROW][C]57[/C][C]0.838816[/C][C]0.322369[/C][C]0.161184[/C][/ROW]
[ROW][C]58[/C][C]0.811013[/C][C]0.377974[/C][C]0.188987[/C][/ROW]
[ROW][C]59[/C][C]0.835451[/C][C]0.329097[/C][C]0.164549[/C][/ROW]
[ROW][C]60[/C][C]0.818942[/C][C]0.362116[/C][C]0.181058[/C][/ROW]
[ROW][C]61[/C][C]0.830278[/C][C]0.339444[/C][C]0.169722[/C][/ROW]
[ROW][C]62[/C][C]0.812956[/C][C]0.374088[/C][C]0.187044[/C][/ROW]
[ROW][C]63[/C][C]0.85056[/C][C]0.298881[/C][C]0.14944[/C][/ROW]
[ROW][C]64[/C][C]0.847736[/C][C]0.304527[/C][C]0.152264[/C][/ROW]
[ROW][C]65[/C][C]0.849813[/C][C]0.300374[/C][C]0.150187[/C][/ROW]
[ROW][C]66[/C][C]0.922847[/C][C]0.154306[/C][C]0.077153[/C][/ROW]
[ROW][C]67[/C][C]0.91188[/C][C]0.17624[/C][C]0.0881202[/C][/ROW]
[ROW][C]68[/C][C]0.911777[/C][C]0.176445[/C][C]0.0882226[/C][/ROW]
[ROW][C]69[/C][C]0.915141[/C][C]0.169718[/C][C]0.084859[/C][/ROW]
[ROW][C]70[/C][C]0.915083[/C][C]0.169833[/C][C]0.0849165[/C][/ROW]
[ROW][C]71[/C][C]0.902253[/C][C]0.195494[/C][C]0.0977469[/C][/ROW]
[ROW][C]72[/C][C]0.933218[/C][C]0.133565[/C][C]0.0667823[/C][/ROW]
[ROW][C]73[/C][C]0.922703[/C][C]0.154594[/C][C]0.0772971[/C][/ROW]
[ROW][C]74[/C][C]0.907774[/C][C]0.184451[/C][C]0.0922256[/C][/ROW]
[ROW][C]75[/C][C]0.899097[/C][C]0.201807[/C][C]0.100903[/C][/ROW]
[ROW][C]76[/C][C]0.881602[/C][C]0.236796[/C][C]0.118398[/C][/ROW]
[ROW][C]77[/C][C]0.909771[/C][C]0.180459[/C][C]0.0902293[/C][/ROW]
[ROW][C]78[/C][C]0.895931[/C][C]0.208138[/C][C]0.104069[/C][/ROW]
[ROW][C]79[/C][C]0.889984[/C][C]0.220033[/C][C]0.110016[/C][/ROW]
[ROW][C]80[/C][C]0.882013[/C][C]0.235974[/C][C]0.117987[/C][/ROW]
[ROW][C]81[/C][C]0.863067[/C][C]0.273866[/C][C]0.136933[/C][/ROW]
[ROW][C]82[/C][C]0.842189[/C][C]0.315622[/C][C]0.157811[/C][/ROW]
[ROW][C]83[/C][C]0.842318[/C][C]0.315365[/C][C]0.157682[/C][/ROW]
[ROW][C]84[/C][C]0.8241[/C][C]0.3518[/C][C]0.1759[/C][/ROW]
[ROW][C]85[/C][C]0.799881[/C][C]0.400238[/C][C]0.200119[/C][/ROW]
[ROW][C]86[/C][C]0.776491[/C][C]0.447018[/C][C]0.223509[/C][/ROW]
[ROW][C]87[/C][C]0.748002[/C][C]0.503997[/C][C]0.251998[/C][/ROW]
[ROW][C]88[/C][C]0.718971[/C][C]0.562057[/C][C]0.281029[/C][/ROW]
[ROW][C]89[/C][C]0.787233[/C][C]0.425533[/C][C]0.212767[/C][/ROW]
[ROW][C]90[/C][C]0.825592[/C][C]0.348816[/C][C]0.174408[/C][/ROW]
[ROW][C]91[/C][C]0.804058[/C][C]0.391884[/C][C]0.195942[/C][/ROW]
[ROW][C]92[/C][C]0.779484[/C][C]0.441033[/C][C]0.220516[/C][/ROW]
[ROW][C]93[/C][C]0.759522[/C][C]0.480955[/C][C]0.240478[/C][/ROW]
[ROW][C]94[/C][C]0.735908[/C][C]0.528184[/C][C]0.264092[/C][/ROW]
[ROW][C]95[/C][C]0.712486[/C][C]0.575028[/C][C]0.287514[/C][/ROW]
[ROW][C]96[/C][C]0.685269[/C][C]0.629461[/C][C]0.314731[/C][/ROW]
[ROW][C]97[/C][C]0.658654[/C][C]0.682693[/C][C]0.341346[/C][/ROW]
[ROW][C]98[/C][C]0.663888[/C][C]0.672224[/C][C]0.336112[/C][/ROW]
[ROW][C]99[/C][C]0.629483[/C][C]0.741034[/C][C]0.370517[/C][/ROW]
[ROW][C]100[/C][C]0.624846[/C][C]0.750308[/C][C]0.375154[/C][/ROW]
[ROW][C]101[/C][C]0.599119[/C][C]0.801762[/C][C]0.400881[/C][/ROW]
[ROW][C]102[/C][C]0.571693[/C][C]0.856614[/C][C]0.428307[/C][/ROW]
[ROW][C]103[/C][C]0.62479[/C][C]0.750419[/C][C]0.37521[/C][/ROW]
[ROW][C]104[/C][C]0.611547[/C][C]0.776907[/C][C]0.388453[/C][/ROW]
[ROW][C]105[/C][C]0.628312[/C][C]0.743375[/C][C]0.371688[/C][/ROW]
[ROW][C]106[/C][C]0.604362[/C][C]0.791276[/C][C]0.395638[/C][/ROW]
[ROW][C]107[/C][C]0.597042[/C][C]0.805915[/C][C]0.402958[/C][/ROW]
[ROW][C]108[/C][C]0.632337[/C][C]0.735326[/C][C]0.367663[/C][/ROW]
[ROW][C]109[/C][C]0.599044[/C][C]0.801913[/C][C]0.400956[/C][/ROW]
[ROW][C]110[/C][C]0.57306[/C][C]0.85388[/C][C]0.42694[/C][/ROW]
[ROW][C]111[/C][C]0.577628[/C][C]0.844744[/C][C]0.422372[/C][/ROW]
[ROW][C]112[/C][C]0.601679[/C][C]0.796642[/C][C]0.398321[/C][/ROW]
[ROW][C]113[/C][C]0.608304[/C][C]0.783392[/C][C]0.391696[/C][/ROW]
[ROW][C]114[/C][C]0.694164[/C][C]0.611672[/C][C]0.305836[/C][/ROW]
[ROW][C]115[/C][C]0.666276[/C][C]0.667448[/C][C]0.333724[/C][/ROW]
[ROW][C]116[/C][C]0.640087[/C][C]0.719825[/C][C]0.359913[/C][/ROW]
[ROW][C]117[/C][C]0.606411[/C][C]0.787179[/C][C]0.393589[/C][/ROW]
[ROW][C]118[/C][C]0.582057[/C][C]0.835885[/C][C]0.417943[/C][/ROW]
[ROW][C]119[/C][C]0.546548[/C][C]0.906904[/C][C]0.453452[/C][/ROW]
[ROW][C]120[/C][C]0.513609[/C][C]0.972782[/C][C]0.486391[/C][/ROW]
[ROW][C]121[/C][C]0.487944[/C][C]0.975887[/C][C]0.512056[/C][/ROW]
[ROW][C]122[/C][C]0.453203[/C][C]0.906405[/C][C]0.546797[/C][/ROW]
[ROW][C]123[/C][C]0.42467[/C][C]0.84934[/C][C]0.57533[/C][/ROW]
[ROW][C]124[/C][C]0.394464[/C][C]0.788927[/C][C]0.605536[/C][/ROW]
[ROW][C]125[/C][C]0.38493[/C][C]0.76986[/C][C]0.61507[/C][/ROW]
[ROW][C]126[/C][C]0.356969[/C][C]0.713938[/C][C]0.643031[/C][/ROW]
[ROW][C]127[/C][C]0.341925[/C][C]0.683849[/C][C]0.658075[/C][/ROW]
[ROW][C]128[/C][C]0.445412[/C][C]0.890824[/C][C]0.554588[/C][/ROW]
[ROW][C]129[/C][C]0.42566[/C][C]0.851319[/C][C]0.57434[/C][/ROW]
[ROW][C]130[/C][C]0.415001[/C][C]0.830003[/C][C]0.584999[/C][/ROW]
[ROW][C]131[/C][C]0.404129[/C][C]0.808257[/C][C]0.595871[/C][/ROW]
[ROW][C]132[/C][C]0.372376[/C][C]0.744751[/C][C]0.627624[/C][/ROW]
[ROW][C]133[/C][C]0.39214[/C][C]0.78428[/C][C]0.60786[/C][/ROW]
[ROW][C]134[/C][C]0.362382[/C][C]0.724764[/C][C]0.637618[/C][/ROW]
[ROW][C]135[/C][C]0.372619[/C][C]0.745239[/C][C]0.627381[/C][/ROW]
[ROW][C]136[/C][C]0.362071[/C][C]0.724142[/C][C]0.637929[/C][/ROW]
[ROW][C]137[/C][C]0.332623[/C][C]0.665246[/C][C]0.667377[/C][/ROW]
[ROW][C]138[/C][C]0.308965[/C][C]0.61793[/C][C]0.691035[/C][/ROW]
[ROW][C]139[/C][C]0.281665[/C][C]0.56333[/C][C]0.718335[/C][/ROW]
[ROW][C]140[/C][C]0.258193[/C][C]0.516387[/C][C]0.741807[/C][/ROW]
[ROW][C]141[/C][C]0.231053[/C][C]0.462105[/C][C]0.768947[/C][/ROW]
[ROW][C]142[/C][C]0.233722[/C][C]0.467445[/C][C]0.766278[/C][/ROW]
[ROW][C]143[/C][C]0.208861[/C][C]0.417723[/C][C]0.791139[/C][/ROW]
[ROW][C]144[/C][C]0.189[/C][C]0.378[/C][C]0.811[/C][/ROW]
[ROW][C]145[/C][C]0.173811[/C][C]0.347622[/C][C]0.826189[/C][/ROW]
[ROW][C]146[/C][C]0.165792[/C][C]0.331584[/C][C]0.834208[/C][/ROW]
[ROW][C]147[/C][C]0.174747[/C][C]0.349495[/C][C]0.825253[/C][/ROW]
[ROW][C]148[/C][C]0.193197[/C][C]0.386395[/C][C]0.806803[/C][/ROW]
[ROW][C]149[/C][C]0.213053[/C][C]0.426105[/C][C]0.786947[/C][/ROW]
[ROW][C]150[/C][C]0.208343[/C][C]0.416686[/C][C]0.791657[/C][/ROW]
[ROW][C]151[/C][C]0.18488[/C][C]0.369761[/C][C]0.81512[/C][/ROW]
[ROW][C]152[/C][C]0.163936[/C][C]0.327871[/C][C]0.836064[/C][/ROW]
[ROW][C]153[/C][C]0.175712[/C][C]0.351423[/C][C]0.824288[/C][/ROW]
[ROW][C]154[/C][C]0.193035[/C][C]0.386069[/C][C]0.806965[/C][/ROW]
[ROW][C]155[/C][C]0.177043[/C][C]0.354086[/C][C]0.822957[/C][/ROW]
[ROW][C]156[/C][C]0.156517[/C][C]0.313034[/C][C]0.843483[/C][/ROW]
[ROW][C]157[/C][C]0.138163[/C][C]0.276326[/C][C]0.861837[/C][/ROW]
[ROW][C]158[/C][C]0.220713[/C][C]0.441427[/C][C]0.779287[/C][/ROW]
[ROW][C]159[/C][C]0.239222[/C][C]0.478444[/C][C]0.760778[/C][/ROW]
[ROW][C]160[/C][C]0.215684[/C][C]0.431368[/C][C]0.784316[/C][/ROW]
[ROW][C]161[/C][C]0.192529[/C][C]0.385058[/C][C]0.807471[/C][/ROW]
[ROW][C]162[/C][C]0.170378[/C][C]0.340756[/C][C]0.829622[/C][/ROW]
[ROW][C]163[/C][C]0.149573[/C][C]0.299147[/C][C]0.850427[/C][/ROW]
[ROW][C]164[/C][C]0.249228[/C][C]0.498457[/C][C]0.750772[/C][/ROW]
[ROW][C]165[/C][C]0.244628[/C][C]0.489257[/C][C]0.755372[/C][/ROW]
[ROW][C]166[/C][C]0.240874[/C][C]0.481748[/C][C]0.759126[/C][/ROW]
[ROW][C]167[/C][C]0.213109[/C][C]0.426219[/C][C]0.786891[/C][/ROW]
[ROW][C]168[/C][C]0.192344[/C][C]0.384688[/C][C]0.807656[/C][/ROW]
[ROW][C]169[/C][C]0.24677[/C][C]0.493541[/C][C]0.75323[/C][/ROW]
[ROW][C]170[/C][C]0.276301[/C][C]0.552601[/C][C]0.723699[/C][/ROW]
[ROW][C]171[/C][C]0.247181[/C][C]0.494363[/C][C]0.752819[/C][/ROW]
[ROW][C]172[/C][C]0.243205[/C][C]0.486411[/C][C]0.756795[/C][/ROW]
[ROW][C]173[/C][C]0.410689[/C][C]0.821378[/C][C]0.589311[/C][/ROW]
[ROW][C]174[/C][C]0.39222[/C][C]0.78444[/C][C]0.60778[/C][/ROW]
[ROW][C]175[/C][C]0.41277[/C][C]0.82554[/C][C]0.58723[/C][/ROW]
[ROW][C]176[/C][C]0.424674[/C][C]0.849348[/C][C]0.575326[/C][/ROW]
[ROW][C]177[/C][C]0.488242[/C][C]0.976484[/C][C]0.511758[/C][/ROW]
[ROW][C]178[/C][C]0.451352[/C][C]0.902703[/C][C]0.548648[/C][/ROW]
[ROW][C]179[/C][C]0.429107[/C][C]0.858213[/C][C]0.570893[/C][/ROW]
[ROW][C]180[/C][C]0.436635[/C][C]0.87327[/C][C]0.563365[/C][/ROW]
[ROW][C]181[/C][C]0.401252[/C][C]0.802505[/C][C]0.598748[/C][/ROW]
[ROW][C]182[/C][C]0.405302[/C][C]0.810603[/C][C]0.594698[/C][/ROW]
[ROW][C]183[/C][C]0.369249[/C][C]0.738498[/C][C]0.630751[/C][/ROW]
[ROW][C]184[/C][C]0.347223[/C][C]0.694445[/C][C]0.652777[/C][/ROW]
[ROW][C]185[/C][C]0.348009[/C][C]0.696018[/C][C]0.651991[/C][/ROW]
[ROW][C]186[/C][C]0.333256[/C][C]0.666512[/C][C]0.666744[/C][/ROW]
[ROW][C]187[/C][C]0.298864[/C][C]0.597729[/C][C]0.701136[/C][/ROW]
[ROW][C]188[/C][C]0.267717[/C][C]0.535435[/C][C]0.732283[/C][/ROW]
[ROW][C]189[/C][C]0.236846[/C][C]0.473691[/C][C]0.763154[/C][/ROW]
[ROW][C]190[/C][C]0.212169[/C][C]0.424338[/C][C]0.787831[/C][/ROW]
[ROW][C]191[/C][C]0.224965[/C][C]0.44993[/C][C]0.775035[/C][/ROW]
[ROW][C]192[/C][C]0.208077[/C][C]0.416155[/C][C]0.791923[/C][/ROW]
[ROW][C]193[/C][C]0.214437[/C][C]0.428874[/C][C]0.785563[/C][/ROW]
[ROW][C]194[/C][C]0.205426[/C][C]0.410852[/C][C]0.794574[/C][/ROW]
[ROW][C]195[/C][C]0.201953[/C][C]0.403906[/C][C]0.798047[/C][/ROW]
[ROW][C]196[/C][C]0.214687[/C][C]0.429375[/C][C]0.785313[/C][/ROW]
[ROW][C]197[/C][C]0.253498[/C][C]0.506996[/C][C]0.746502[/C][/ROW]
[ROW][C]198[/C][C]0.234683[/C][C]0.469365[/C][C]0.765317[/C][/ROW]
[ROW][C]199[/C][C]0.270765[/C][C]0.541531[/C][C]0.729235[/C][/ROW]
[ROW][C]200[/C][C]0.239015[/C][C]0.478031[/C][C]0.760985[/C][/ROW]
[ROW][C]201[/C][C]0.280028[/C][C]0.560056[/C][C]0.719972[/C][/ROW]
[ROW][C]202[/C][C]0.254654[/C][C]0.509307[/C][C]0.745346[/C][/ROW]
[ROW][C]203[/C][C]0.292124[/C][C]0.584249[/C][C]0.707876[/C][/ROW]
[ROW][C]204[/C][C]0.259969[/C][C]0.519939[/C][C]0.740031[/C][/ROW]
[ROW][C]205[/C][C]0.227457[/C][C]0.454915[/C][C]0.772543[/C][/ROW]
[ROW][C]206[/C][C]0.207397[/C][C]0.414795[/C][C]0.792603[/C][/ROW]
[ROW][C]207[/C][C]0.177436[/C][C]0.354872[/C][C]0.822564[/C][/ROW]
[ROW][C]208[/C][C]0.203028[/C][C]0.406056[/C][C]0.796972[/C][/ROW]
[ROW][C]209[/C][C]0.173297[/C][C]0.346594[/C][C]0.826703[/C][/ROW]
[ROW][C]210[/C][C]0.18288[/C][C]0.36576[/C][C]0.81712[/C][/ROW]
[ROW][C]211[/C][C]0.202371[/C][C]0.404742[/C][C]0.797629[/C][/ROW]
[ROW][C]212[/C][C]0.193138[/C][C]0.386276[/C][C]0.806862[/C][/ROW]
[ROW][C]213[/C][C]0.167703[/C][C]0.335406[/C][C]0.832297[/C][/ROW]
[ROW][C]214[/C][C]0.207497[/C][C]0.414994[/C][C]0.792503[/C][/ROW]
[ROW][C]215[/C][C]0.184428[/C][C]0.368857[/C][C]0.815572[/C][/ROW]
[ROW][C]216[/C][C]0.17317[/C][C]0.346341[/C][C]0.82683[/C][/ROW]
[ROW][C]217[/C][C]0.203513[/C][C]0.407027[/C][C]0.796487[/C][/ROW]
[ROW][C]218[/C][C]0.175635[/C][C]0.35127[/C][C]0.824365[/C][/ROW]
[ROW][C]219[/C][C]0.162209[/C][C]0.324418[/C][C]0.837791[/C][/ROW]
[ROW][C]220[/C][C]0.179586[/C][C]0.359171[/C][C]0.820414[/C][/ROW]
[ROW][C]221[/C][C]0.184036[/C][C]0.368073[/C][C]0.815964[/C][/ROW]
[ROW][C]222[/C][C]0.181747[/C][C]0.363493[/C][C]0.818253[/C][/ROW]
[ROW][C]223[/C][C]0.165197[/C][C]0.330395[/C][C]0.834803[/C][/ROW]
[ROW][C]224[/C][C]0.137122[/C][C]0.274245[/C][C]0.862878[/C][/ROW]
[ROW][C]225[/C][C]0.134548[/C][C]0.269097[/C][C]0.865452[/C][/ROW]
[ROW][C]226[/C][C]0.165347[/C][C]0.330693[/C][C]0.834653[/C][/ROW]
[ROW][C]227[/C][C]0.39367[/C][C]0.78734[/C][C]0.60633[/C][/ROW]
[ROW][C]228[/C][C]0.35207[/C][C]0.704139[/C][C]0.64793[/C][/ROW]
[ROW][C]229[/C][C]0.313151[/C][C]0.626301[/C][C]0.686849[/C][/ROW]
[ROW][C]230[/C][C]0.287284[/C][C]0.574568[/C][C]0.712716[/C][/ROW]
[ROW][C]231[/C][C]0.251073[/C][C]0.502146[/C][C]0.748927[/C][/ROW]
[ROW][C]232[/C][C]0.28032[/C][C]0.560641[/C][C]0.71968[/C][/ROW]
[ROW][C]233[/C][C]0.237438[/C][C]0.474876[/C][C]0.762562[/C][/ROW]
[ROW][C]234[/C][C]0.199221[/C][C]0.398442[/C][C]0.800779[/C][/ROW]
[ROW][C]235[/C][C]0.206315[/C][C]0.41263[/C][C]0.793685[/C][/ROW]
[ROW][C]236[/C][C]0.178084[/C][C]0.356167[/C][C]0.821916[/C][/ROW]
[ROW][C]237[/C][C]0.153706[/C][C]0.307412[/C][C]0.846294[/C][/ROW]
[ROW][C]238[/C][C]0.118456[/C][C]0.236912[/C][C]0.881544[/C][/ROW]
[ROW][C]239[/C][C]0.227057[/C][C]0.454114[/C][C]0.772943[/C][/ROW]
[ROW][C]240[/C][C]0.237029[/C][C]0.474058[/C][C]0.762971[/C][/ROW]
[ROW][C]241[/C][C]0.240692[/C][C]0.481384[/C][C]0.759308[/C][/ROW]
[ROW][C]242[/C][C]0.858486[/C][C]0.283028[/C][C]0.141514[/C][/ROW]
[ROW][C]243[/C][C]0.808803[/C][C]0.382395[/C][C]0.191197[/C][/ROW]
[ROW][C]244[/C][C]0.754986[/C][C]0.490028[/C][C]0.245014[/C][/ROW]
[ROW][C]245[/C][C]0.701437[/C][C]0.597126[/C][C]0.298563[/C][/ROW]
[ROW][C]246[/C][C]0.632539[/C][C]0.734921[/C][C]0.367461[/C][/ROW]
[ROW][C]247[/C][C]0.646817[/C][C]0.706367[/C][C]0.353183[/C][/ROW]
[ROW][C]248[/C][C]0.65039[/C][C]0.69922[/C][C]0.34961[/C][/ROW]
[ROW][C]249[/C][C]0.544941[/C][C]0.910118[/C][C]0.455059[/C][/ROW]
[ROW][C]250[/C][C]0.459564[/C][C]0.919128[/C][C]0.540436[/C][/ROW]
[ROW][C]251[/C][C]0.399939[/C][C]0.799878[/C][C]0.600061[/C][/ROW]
[ROW][C]252[/C][C]0.905595[/C][C]0.188811[/C][C]0.0944054[/C][/ROW]
[ROW][C]253[/C][C]0.817587[/C][C]0.364826[/C][C]0.182413[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226600&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226600&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
110.04250680.08501370.957493
120.7947010.4105980.205299
130.9824130.03517430.0175871
140.980720.03855940.0192797
150.9811950.037610.018805
160.9697250.06054960.0302748
170.9655490.06890120.0344506
180.9492470.1015050.0507526
190.9337560.1324880.0662441
200.9183580.1632830.0816417
210.9158990.1682020.084101
220.9648210.07035780.0351789
230.9505050.09898910.0494946
240.9388860.1222270.0611135
250.9188050.162390.081195
260.9985060.002987970.00149398
270.9979450.004109170.00205459
280.9968180.006363460.00318173
290.9953530.009293710.00464686
300.9963020.007395340.00369767
310.9947770.01044670.00522335
320.9922890.01542250.00771124
330.9921920.01561560.0078078
340.9887580.02248370.0112418
350.9841450.03171080.0158554
360.9783360.04332840.0216642
370.9806010.03879820.0193991
380.9751160.04976750.0248838
390.9747070.05058590.0252929
400.9713680.05726490.0286325
410.9622270.07554520.0377726
420.9649620.0700750.0350375
430.9570060.08598830.0429942
440.9462810.1074370.0537185
450.9321580.1356840.067842
460.934590.1308210.0654105
470.9211090.1577820.078891
480.9041120.1917770.0958884
490.9387060.1225870.0612937
500.9316370.1367260.068363
510.9198030.1603940.080197
520.9029150.194170.0970848
530.88450.2310.1155
540.8696570.2606860.130343
550.8587070.2825870.141293
560.8442490.3115020.155751
570.8388160.3223690.161184
580.8110130.3779740.188987
590.8354510.3290970.164549
600.8189420.3621160.181058
610.8302780.3394440.169722
620.8129560.3740880.187044
630.850560.2988810.14944
640.8477360.3045270.152264
650.8498130.3003740.150187
660.9228470.1543060.077153
670.911880.176240.0881202
680.9117770.1764450.0882226
690.9151410.1697180.084859
700.9150830.1698330.0849165
710.9022530.1954940.0977469
720.9332180.1335650.0667823
730.9227030.1545940.0772971
740.9077740.1844510.0922256
750.8990970.2018070.100903
760.8816020.2367960.118398
770.9097710.1804590.0902293
780.8959310.2081380.104069
790.8899840.2200330.110016
800.8820130.2359740.117987
810.8630670.2738660.136933
820.8421890.3156220.157811
830.8423180.3153650.157682
840.82410.35180.1759
850.7998810.4002380.200119
860.7764910.4470180.223509
870.7480020.5039970.251998
880.7189710.5620570.281029
890.7872330.4255330.212767
900.8255920.3488160.174408
910.8040580.3918840.195942
920.7794840.4410330.220516
930.7595220.4809550.240478
940.7359080.5281840.264092
950.7124860.5750280.287514
960.6852690.6294610.314731
970.6586540.6826930.341346
980.6638880.6722240.336112
990.6294830.7410340.370517
1000.6248460.7503080.375154
1010.5991190.8017620.400881
1020.5716930.8566140.428307
1030.624790.7504190.37521
1040.6115470.7769070.388453
1050.6283120.7433750.371688
1060.6043620.7912760.395638
1070.5970420.8059150.402958
1080.6323370.7353260.367663
1090.5990440.8019130.400956
1100.573060.853880.42694
1110.5776280.8447440.422372
1120.6016790.7966420.398321
1130.6083040.7833920.391696
1140.6941640.6116720.305836
1150.6662760.6674480.333724
1160.6400870.7198250.359913
1170.6064110.7871790.393589
1180.5820570.8358850.417943
1190.5465480.9069040.453452
1200.5136090.9727820.486391
1210.4879440.9758870.512056
1220.4532030.9064050.546797
1230.424670.849340.57533
1240.3944640.7889270.605536
1250.384930.769860.61507
1260.3569690.7139380.643031
1270.3419250.6838490.658075
1280.4454120.8908240.554588
1290.425660.8513190.57434
1300.4150010.8300030.584999
1310.4041290.8082570.595871
1320.3723760.7447510.627624
1330.392140.784280.60786
1340.3623820.7247640.637618
1350.3726190.7452390.627381
1360.3620710.7241420.637929
1370.3326230.6652460.667377
1380.3089650.617930.691035
1390.2816650.563330.718335
1400.2581930.5163870.741807
1410.2310530.4621050.768947
1420.2337220.4674450.766278
1430.2088610.4177230.791139
1440.1890.3780.811
1450.1738110.3476220.826189
1460.1657920.3315840.834208
1470.1747470.3494950.825253
1480.1931970.3863950.806803
1490.2130530.4261050.786947
1500.2083430.4166860.791657
1510.184880.3697610.81512
1520.1639360.3278710.836064
1530.1757120.3514230.824288
1540.1930350.3860690.806965
1550.1770430.3540860.822957
1560.1565170.3130340.843483
1570.1381630.2763260.861837
1580.2207130.4414270.779287
1590.2392220.4784440.760778
1600.2156840.4313680.784316
1610.1925290.3850580.807471
1620.1703780.3407560.829622
1630.1495730.2991470.850427
1640.2492280.4984570.750772
1650.2446280.4892570.755372
1660.2408740.4817480.759126
1670.2131090.4262190.786891
1680.1923440.3846880.807656
1690.246770.4935410.75323
1700.2763010.5526010.723699
1710.2471810.4943630.752819
1720.2432050.4864110.756795
1730.4106890.8213780.589311
1740.392220.784440.60778
1750.412770.825540.58723
1760.4246740.8493480.575326
1770.4882420.9764840.511758
1780.4513520.9027030.548648
1790.4291070.8582130.570893
1800.4366350.873270.563365
1810.4012520.8025050.598748
1820.4053020.8106030.594698
1830.3692490.7384980.630751
1840.3472230.6944450.652777
1850.3480090.6960180.651991
1860.3332560.6665120.666744
1870.2988640.5977290.701136
1880.2677170.5354350.732283
1890.2368460.4736910.763154
1900.2121690.4243380.787831
1910.2249650.449930.775035
1920.2080770.4161550.791923
1930.2144370.4288740.785563
1940.2054260.4108520.794574
1950.2019530.4039060.798047
1960.2146870.4293750.785313
1970.2534980.5069960.746502
1980.2346830.4693650.765317
1990.2707650.5415310.729235
2000.2390150.4780310.760985
2010.2800280.5600560.719972
2020.2546540.5093070.745346
2030.2921240.5842490.707876
2040.2599690.5199390.740031
2050.2274570.4549150.772543
2060.2073970.4147950.792603
2070.1774360.3548720.822564
2080.2030280.4060560.796972
2090.1732970.3465940.826703
2100.182880.365760.81712
2110.2023710.4047420.797629
2120.1931380.3862760.806862
2130.1677030.3354060.832297
2140.2074970.4149940.792503
2150.1844280.3688570.815572
2160.173170.3463410.82683
2170.2035130.4070270.796487
2180.1756350.351270.824365
2190.1622090.3244180.837791
2200.1795860.3591710.820414
2210.1840360.3680730.815964
2220.1817470.3634930.818253
2230.1651970.3303950.834803
2240.1371220.2742450.862878
2250.1345480.2690970.865452
2260.1653470.3306930.834653
2270.393670.787340.60633
2280.352070.7041390.64793
2290.3131510.6263010.686849
2300.2872840.5745680.712716
2310.2510730.5021460.748927
2320.280320.5606410.71968
2330.2374380.4748760.762562
2340.1992210.3984420.800779
2350.2063150.412630.793685
2360.1780840.3561670.821916
2370.1537060.3074120.846294
2380.1184560.2369120.881544
2390.2270570.4541140.772943
2400.2370290.4740580.762971
2410.2406920.4813840.759308
2420.8584860.2830280.141514
2430.8088030.3823950.191197
2440.7549860.4900280.245014
2450.7014370.5971260.298563
2460.6325390.7349210.367461
2470.6468170.7063670.353183
2480.650390.699220.34961
2490.5449410.9101180.455059
2500.4595640.9191280.540436
2510.3999390.7998780.600061
2520.9055950.1888110.0944054
2530.8175870.3648260.182413






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level50.0205761NOK
5% type I error level160.0658436NOK
10% type I error level260.106996NOK

\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 & 5 & 0.0205761 & NOK \tabularnewline
5% type I error level & 16 & 0.0658436 & NOK \tabularnewline
10% type I error level & 26 & 0.106996 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226600&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]5[/C][C]0.0205761[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]16[/C][C]0.0658436[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]26[/C][C]0.106996[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226600&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226600&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 level50.0205761NOK
5% type I error level160.0658436NOK
10% type I error level260.106996NOK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 5 ; 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')
}