FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 06:35:52 -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/t138494745825j04xo4kcz4b6n.htm/, Retrieved Wed, 01 May 2024 22:21:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226588, Retrieved Wed, 01 May 2024 22:21:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Workshop 71] [2013-11-18 11:34:41] [4e6b221caf797a012ce5465db674848b]
-    D    [Multiple Regression] [workshop 7 ] [2013-11-20 11:35:52] [249761a82d67c41cbe9b5c486860cdc6] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12 41 38 13 14 12 53
11 39 32 16 18 11 83
15 30 35 19 11 14 66
6 31 33 15 12 12 67
13 34 37 14 16 21 76
10 35 29 13 18 12 78
12 39 31 19 14 22 53
14 34 36 15 14 11 80
12 36 35 14 15 10 74
9 37 38 15 15 13 76
10 38 31 16 17 10 79
12 36 34 16 19 8 54
12 38 35 16 10 15 67
11 39 38 16 16 14 54
15 33 37 17 18 10 87
12 32 33 15 14 14 58
10 36 32 15 14 14 75
12 38 38 20 17 11 88
11 39 38 18 14 10 64
12 32 32 16 16 13 57
11 32 33 16 18 9.5 66
12 31 31 16 11 14 68
13 39 38 19 14 12 54
11 37 39 16 12 14 56
12 39 32 17 17 11 86
13 41 32 17 9 9 80
10 36 35 16 16 11 76
14 33 37 15 14 15 69
12 33 33 16 15 14 78
10 34 33 14 11 13 67
12 31 31 15 16 9 80
8 27 32 12 13 15 54
10 37 31 14 17 10 71
12 34 37 16 15 11 84
12 34 30 14 14 13 74
7 32 33 10 16 8 71
9 29 31 10 9 20 63
12 36 33 14 15 12 71
10 29 31 16 17 10 76
10 35 33 16 13 10 69
10 37 32 16 15 9 74
12 34 33 14 16 14 75
15 38 32 20 16 8 54
10 35 33 14 12 14 52
10 38 28 14 15 11 69
12 37 35 11 11 13 68
13 38 39 14 15 9 65
11 33 34 15 15 11 75
11 36 38 16 17 15 74
12 38 32 14 13 11 75
14 32 38 16 16 10 72
10 32 30 14 14 14 67
12 32 33 12 11 18 63
13 34 38 16 12 14 62
5 32 32 9 12 11 63
6 37 35 14 15 14.5 76
12 39 34 16 16 13 74
12 29 34 16 15 9 67
11 37 36 15 12 10 73
10 35 34 16 12 15 70
7 30 28 12 8 20 53
12 38 34 16 13 12 77
14 34 35 16 11 12 80
11 31 35 14 14 14 52
12 34 31 16 15 13 54
13 35 37 17 10 11 80
14 36 35 18 11 17 66
11 30 27 18 12 12 73
12 39 40 12 15 13 63
12 35 37 16 15 14 69
8 38 36 10 14 13 67
11 31 38 14 16 15 54
14 34 39 18 15 13 81
14 38 41 18 15 10 69
12 34 27 16 13 11 84
9 39 30 17 12 19 80
13 37 37 16 17 13 70
11 34 31 16 13 17 69
12 28 31 13 15 13 77
12 37 27 16 13 9 54
12 33 36 16 15 11 79
12 35 37 16 15 9 71
12 37 33 15 16 12 73
11 32 34 15 15 12 72
10 33 31 16 14 13 77
9 38 39 14 15 13 75
12 33 34 16 14 12 69
12 29 32 16 13 15 54
12 33 33 15 7 22 70
9 31 36 12 17 13 73
15 36 32 17 13 15 54
12 35 41 16 15 13 77
12 32 28 15 14 15 82
12 29 30 13 13 12.5 80
10 39 36 16 16 11 80
13 37 35 16 12 16 69
9 35 31 16 14 11 78
12 37 34 16 17 11 81
10 32 36 14 15 10 76
14 38 36 16 17 10 76
11 37 35 16 12 16 73
15 36 37 20 16 12 85
11 32 28 15 11 11 66
11 33 39 16 15 16 79
12 40 32 13 9 19 68
12 38 35 17 16 11 76
12 41 39 16 15 16 71
11 36 35 16 10 15 54
7 43 42 12 10 24 46
12 30 34 16 15 14 85
14 31 33 16 11 15 74
11 32 41 17 13 11 88
11 32 33 13 14 15 38
10 37 34 12 18 12 76
13 37 32 18 16 10 86
13 33 40 14 14 14 54
8 34 40 14 14 13 67
11 33 35 13 14 9 69
12 38 36 16 14 15 90
11 33 37 13 12 15 54
13 31 27 16 14 14 76
12 38 39 13 15 11 89
14 37 38 16 15 8 76
13 36 31 15 15 11 73
15 31 33 16 13 11 79
10 39 32 15 17 8 90
11 44 39 17 17 10 74
9 33 36 15 19 11 81
11 35 33 12 15 13 72
10 32 33 16 13 11 71
11 28 32 10 9 20 66
8 40 37 16 15 10 77
11 27 30 12 15 15 65
12 37 38 14 15 12 74
12 32 29 15 16 14 85
9 28 22 13 11 23 54
11 34 35 15 14 14 63
10 30 35 11 11 16 54
8 35 34 12 15 11 64
9 31 35 11 13 12 69
8 32 34 16 15 10 54
9 30 37 15 16 14 84
15 30 35 17 14 12 86
11 31 23 16 15 12 77
8 40 31 10 16 11 89
13 32 27 18 16 12 76
12 36 36 13 11 13 60
12 32 31 16 12 11 75
9 35 32 13 9 19 73
7 38 39 10 16 12 85
13 42 37 15 13 17 79
9 34 38 16 16 9 71
6 35 39 16 12 12 72
8 38 34 14 9 19 69
8 33 31 10 13 18 78
15 36 32 17 13 15 54
6 32 37 13 14 14 69
9 33 36 15 19 11 81
11 34 32 16 13 9 84
8 32 38 12 12 18 84
8 34 36 13 13 16 69
10 27 26 13 10 24 66
8 31 26 12 14 14 81
14 38 33 17 16 20 82
10 34 39 15 10 18 72
8 24 30 10 11 23 54
11 30 33 14 14 12 78
12 26 25 11 12 14 74
12 34 38 13 9 16 82
12 27 37 16 9 18 73
5 37 31 12 11 20 55
12 36 37 16 16 12 72
10 41 35 12 9 12 78
7 29 25 9 13 17 59
12 36 28 12 16 13 72
11 32 35 15 13 9 78
8 37 33 12 9 16 68
9 30 30 12 12 18 69
10 31 31 14 16 10 67
9 38 37 12 11 14 74
12 36 36 16 14 11 54
6 35 30 11 13 9 67
15 31 36 19 15 11 70
12 38 32 15 14 10 80
12 22 28 8 16 11 89
12 32 36 16 13 19 76
11 36 34 17 14 14 74
7 39 31 12 15 12 87
7 28 28 11 13 14 54
5 32 36 11 11 21 61
12 32 36 14 11 13 38
12 38 40 16 14 10 75
3 32 33 12 15 15 69
11 35 37 16 11 16 62
10 32 32 13 15 14 72
12 37 38 15 12 12 70
9 34 31 16 14 19 79
12 33 37 16 14 15 87
9 33 33 14 8 19 62
12 26 32 16 13 13 77
12 30 30 16 9 17 69
10 24 30 14 15 12 69
9 34 31 11 17 11 75
12 34 32 12 13 14 54
8 33 34 15 15 11 72
11 34 36 15 15 13 74
11 35 37 16 14 12 85
12 35 36 16 16 15 52
10 36 33 11 13 14 70
10 34 33 15 16 12 84
12 34 33 12 9 17 64
12 41 44 12 16 11 84
11 32 39 15 11 18 87
8 30 32 15 10 13 79
12 35 35 16 11 17 67
10 28 25 14 15 13 65
11 33 35 17 17 11 85
10 39 34 14 14 12 83
8 36 35 13 8 22 61
12 36 39 15 15 14 82
12 35 33 13 11 12 76
10 38 36 14 16 12 58
12 33 32 15 10 17 72
9 31 32 12 15 9 72
9 34 36 13 9 21 38
6 32 36 8 16 10 78
10 31 32 14 19 11 54
9 33 34 14 12 12 63
9 34 33 11 8 23 66
9 34 35 12 11 13 70
6 34 30 13 14 12 71
10 33 38 10 9 16 67
6 32 34 16 15 9 58
14 41 33 18 13 17 72
10 34 32 13 16 9 72
10 36 31 11 11 14 70
6 37 30 4 12 17 76
12 36 27 13 13 13 50
12 29 31 16 10 11 72
7 37 30 10 11 12 72
8 27 32 12 12 10 88
11 35 35 12 8 19 53
3 28 28 10 12 16 58
6 35 33 13 12 16 66
10 37 31 15 15 14 82
8 29 35 12 11 20 69
9 32 35 14 13 15 68
9 36 32 10 14 23 44
8 19 21 12 10 20 56
9 21 20 12 12 16 53
7 31 34 11 15 14 70
7 33 32 10 13 17 78
6 36 34 12 13 11 71
9 33 32 16 13 13 72
10 37 33 12 12 17 68
11 34 33 14 12 15 67
12 35 37 16 9 21 75
8 31 32 14 9 18 62
11 37 34 13 15 15 67
3 35 30 4 10 8 83
11 27 30 15 14 12 64
12 34 38 11 15 12 68
7 40 36 11 7 22 62
9 29 32 14 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 time19 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 19 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226588&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]19 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226588&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226588&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 time19 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 1.39513 -0.0114212Connected[t] + 0.037437Separate[t] + 0.575114Learning[t] -0.00628486Happiness[t] -0.0115006Depression[t] + 0.00431674Sport1[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Software[t] =  +  1.39513 -0.0114212Connected[t] +  0.037437Separate[t] +  0.575114Learning[t] -0.00628486Happiness[t] -0.0115006Depression[t] +  0.00431674Sport1[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226588&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Software[t] =  +  1.39513 -0.0114212Connected[t] +  0.037437Separate[t] +  0.575114Learning[t] -0.00628486Happiness[t] -0.0115006Depression[t] +  0.00431674Sport1[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226588&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226588&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 1.39513 -0.0114212Connected[t] + 0.037437Separate[t] + 0.575114Learning[t] -0.00628486Happiness[t] -0.0115006Depression[t] + 0.00431674Sport1[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.395131.854640.75220.4525950.226298
Connected-0.01142120.033756-0.33830.7353780.367689
Separate0.0374370.03462341.0810.2805940.140297
Learning0.5751140.048921711.768.07639e-264.03819e-26
Happiness-0.006284860.0565706-0.11110.9116260.455813
Depression-0.01150060.0411385-0.27960.7800410.39002
Sport10.004316740.01163330.37110.7108940.355447

\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) & 1.39513 & 1.85464 & 0.7522 & 0.452595 & 0.226298 \tabularnewline
Connected & -0.0114212 & 0.033756 & -0.3383 & 0.735378 & 0.367689 \tabularnewline
Separate & 0.037437 & 0.0346234 & 1.081 & 0.280594 & 0.140297 \tabularnewline
Learning & 0.575114 & 0.0489217 & 11.76 & 8.07639e-26 & 4.03819e-26 \tabularnewline
Happiness & -0.00628486 & 0.0565706 & -0.1111 & 0.911626 & 0.455813 \tabularnewline
Depression & -0.0115006 & 0.0411385 & -0.2796 & 0.780041 & 0.39002 \tabularnewline
Sport1 & 0.00431674 & 0.0116333 & 0.3711 & 0.710894 & 0.355447 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226588&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]1.39513[/C][C]1.85464[/C][C]0.7522[/C][C]0.452595[/C][C]0.226298[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0114212[/C][C]0.033756[/C][C]-0.3383[/C][C]0.735378[/C][C]0.367689[/C][/ROW]
[ROW][C]Separate[/C][C]0.037437[/C][C]0.0346234[/C][C]1.081[/C][C]0.280594[/C][C]0.140297[/C][/ROW]
[ROW][C]Learning[/C][C]0.575114[/C][C]0.0489217[/C][C]11.76[/C][C]8.07639e-26[/C][C]4.03819e-26[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.00628486[/C][C]0.0565706[/C][C]-0.1111[/C][C]0.911626[/C][C]0.455813[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0115006[/C][C]0.0411385[/C][C]-0.2796[/C][C]0.780041[/C][C]0.39002[/C][/ROW]
[ROW][C]Sport1[/C][C]0.00431674[/C][C]0.0116333[/C][C]0.3711[/C][C]0.710894[/C][C]0.355447[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226588&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226588&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)1.395131.854640.75220.4525950.226298
Connected-0.01142120.033756-0.33830.7353780.367689
Separate0.0374370.03462341.0810.2805940.140297
Learning0.5751140.048921711.768.07639e-264.03819e-26
Happiness-0.006284860.0565706-0.11110.9116260.455813
Depression-0.01150060.0411385-0.27960.7800410.39002
Sport10.004316740.01163330.37110.7108940.355447






Multiple Linear Regression - Regression Statistics
Multiple R0.626341
R-squared0.392303
Adjusted R-squared0.378115
F-TEST (value)27.6513
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.82958
Sum Squared Residuals860.269

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.626341 \tabularnewline
R-squared & 0.392303 \tabularnewline
Adjusted R-squared & 0.378115 \tabularnewline
F-TEST (value) & 27.6513 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 257 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.82958 \tabularnewline
Sum Squared Residuals & 860.269 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226588&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.626341[/C][/ROW]
[ROW][C]R-squared[/C][C]0.392303[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.378115[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]27.6513[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]257[/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]1.82958[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]860.269[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226588&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226588&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 R0.626341
R-squared0.392303
Adjusted R-squared0.378115
F-TEST (value)27.6513
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.82958
Sum Squared Residuals860.269






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
1129.828742.17126
21111.4682-0.468165
31513.34471.65528
4610.979-4.979
51310.42962.57043
6109.643110.356887
71212.9252-0.9252
81411.11212.88791
91210.4561.54398
10911.1062-2.10615
111011.4427-1.44267
121211.48030.519665
131211.52710.472894
141111.5457-0.54567
151512.32782.67224
161210.89321.10684
171010.8834-0.883419
181214.0325-2.03253
191112.7976-1.79764
201211.42540.574553
211111.5294-0.529418
221211.46680.533161
231313.3066-0.306583
241111.6397-0.639722
251212.0625-0.0625146
261312.08710.912948
271011.5971-1.59709
281411.06752.93253
291211.53690.463101
301010.3644-0.364406
311210.96961.03039
3289.165-1.165
331010.2693-0.269328
341211.73560.264372
351210.26351.73654
3678.13014-1.13014
3797.960981.03902
381210.34521.65481
391011.5325-1.53251
401011.5338-1.53378
411011.494-1.49401
421210.3561.64399
431513.70191.29807
441010.2704-0.270448
451010.138-0.138031
46128.683993.31601
471310.55562.44443
481111.0208-0.0207736
491111.6485-0.648483
501210.32621.67375
511411.74932.25068
521010.2446-0.244582
53129.162252.83775
541311.66241.33755
5557.47369-2.47369
56610.4015-4.40148
571211.49380.506243
581211.630.36996
591111.0717-0.0716844
601011.5243-1.52431
6178.95059-1.95059
621211.54850.451516
631411.65712.34287
641110.37840.621563
651211.35850.641498
661312.31350.686522
671412.66661.33343
681112.517-1.51704
69129.376722.62328
701211.6250.375046
7188.11172-0.111721
721110.47530.524689
731412.92481.07522
741412.93671.06333
751211.37380.626172
76911.9012-2.90116
771311.60541.39464
781111.3898-0.389821
79129.800972.19903
801211.23310.766937
811211.6880.311971
821211.69110.30891
831210.91121.08877
841111.0077-0.00774398
851011.4755-1.47549
86910.5527-1.55274
871211.56480.435229
881211.44260.557386
891210.88551.11448
9099.34894-0.348944
911511.93783.06222
921211.82070.179264
931210.79811.20193
94129.783392.21661
951011.6175-1.61753
961311.52311.47691
97911.48-2.47997
981211.56350.436467
991010.5478-0.547772
1001411.61692.3831
1011111.5404-0.540357
1021513.99981.00023
1031110.79390.206138
1041111.7428-0.742836
105129.631212.36879
1061212.1494-0.149364
1071211.61690.383068
1081111.4938-0.493831
10979.23745-2.23745
1101211.63880.361183
1111411.55612.44389
1121112.5132-1.51317
113119.645091.35491
114109.223710.776292
1151312.67830.321743
1161310.55142.44859
117810.6076-2.60761
118119.911371.08863
1191211.63870.361311
120119.865061.13494
1211311.33281.66723
1221210.06111.93894
1231411.73882.26123
1241310.86562.13443
1251511.61113.38887
1261010.9641-0.964055
1271112.2272-1.22717
128911.0964-2.09641
129119.19921.8008
1301011.5652-1.56517
131118.022792.97721
132811.6484-3.64838
133119.125041.87496
1341210.53391.46609
1351210.84741.15261
13699.27489-0.274888
1371110.96680.0332286
138108.6691.331
13989.2251-1.2251
14098.755770.244234
141811.5282-3.52816
142911.1654-2.16541
1431512.2852.71503
1441111.2041-0.204056
14588.00709-0.00709344
1461312.4820.517991
147129.848542.15146
1481211.51390.486148
14999.7099-0.7099
15078.30066-1.30066
1511310.99112.00887
152911.7337-2.73366
153611.7546-5.75463
154810.3084-2.30836
15587.977910.022092
1561511.93783.06222
15769.94016-3.94016
158911.0964-2.09641
1591111.584-0.584014
16089.4338-1.4338
16189.86316-1.86316
162109.482640.517358
16389.01646-1.01646
1641411.99692.00312
1651011.1345-1.13451
16687.894730.105273
1671110.45020.549779
168128.443373.55663
1691210.01931.9807
1701211.72530.274703
17158.97273-3.97273
1721211.64320.356801
173109.280660.719343
17477.15334-0.15334
175128.994313.00569
1761111.1182-0.118153
17789.1623-1.1623
17899.0924-0.0923969
1791010.3269-0.326873
18099.33696-0.336957
1811211.55210.447869
18268.54876-2.54876
1831513.39741.60264
1841210.92821.07184
185126.950145.04986
1861211.60710.392936
1871112.1042-1.1042
18879.15489-2.15489
18978.44022-1.44022
19058.65631-3.65631
1911210.37441.62563
1921211.78120.218811
19339.19751-6.19751
1941111.5969-0.596875
195109.759640.240359
1961211.11060.889393
197911.4037-2.4037
1981211.72030.279718
199910.3041-1.30409
2001211.59920.400836
2011211.42320.576792
2021010.3613-0.361302
20398.584020.415984
204129.096552.90345
205811.0078-3.00782
2061111.0569-0.0569083
2071111.7233-0.723308
2081211.49630.503653
209108.60511.3949
2101010.993-0.992981
211129.167792.83221
212129.6112.389
2131111.2158-0.215816
214811.0059-3.00585
2151211.53210.467916
2161010.0997-0.0996641
2171112.239-1.23904
2181010.4065-0.40645
21989.73077-1.73077
2201211.16940.83059
221129.828222.17178
2221010.3723-0.372257
2231210.89541.10463
22499.25345-0.253451
22599.69698-0.696982
22667.09944-1.09944
2271010.2778-0.277837
228910.4012-1.40121
22998.538590.461405
23099.302-0.302002
23169.68689-3.68689
232108.240621.75938
233611.5569-5.55693
2341412.54791.45208
235109.788020.211983
236108.54281.4572
23764.453251.54675
238129.455872.54413
2391211.54770.452264
24077.95046-0.950459
24189.37556-1.37556
242119.167051.83295
24337.86565-4.86565
24469.73277-3.73277
2451010.8585-0.858493
24689.27429-1.27429
247910.4309-1.43087
24897.770521.22948
24988.81455-0.814548
25098.774750.225249
25178.68707-1.68707
25278.02685-1.02685
25369.25647-3.25647
254911.4976-2.49763
255109.131940.868057
2561110.33510.664881
2571211.60810.391941
258810.2947-2.29472
259119.744321.25568
26034.62239-1.62239
2611110.88690.113147
262128.816933.18307
26378.5829-1.5829
264910.3983-1.3983

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 9.82874 & 2.17126 \tabularnewline
2 & 11 & 11.4682 & -0.468165 \tabularnewline
3 & 15 & 13.3447 & 1.65528 \tabularnewline
4 & 6 & 10.979 & -4.979 \tabularnewline
5 & 13 & 10.4296 & 2.57043 \tabularnewline
6 & 10 & 9.64311 & 0.356887 \tabularnewline
7 & 12 & 12.9252 & -0.9252 \tabularnewline
8 & 14 & 11.1121 & 2.88791 \tabularnewline
9 & 12 & 10.456 & 1.54398 \tabularnewline
10 & 9 & 11.1062 & -2.10615 \tabularnewline
11 & 10 & 11.4427 & -1.44267 \tabularnewline
12 & 12 & 11.4803 & 0.519665 \tabularnewline
13 & 12 & 11.5271 & 0.472894 \tabularnewline
14 & 11 & 11.5457 & -0.54567 \tabularnewline
15 & 15 & 12.3278 & 2.67224 \tabularnewline
16 & 12 & 10.8932 & 1.10684 \tabularnewline
17 & 10 & 10.8834 & -0.883419 \tabularnewline
18 & 12 & 14.0325 & -2.03253 \tabularnewline
19 & 11 & 12.7976 & -1.79764 \tabularnewline
20 & 12 & 11.4254 & 0.574553 \tabularnewline
21 & 11 & 11.5294 & -0.529418 \tabularnewline
22 & 12 & 11.4668 & 0.533161 \tabularnewline
23 & 13 & 13.3066 & -0.306583 \tabularnewline
24 & 11 & 11.6397 & -0.639722 \tabularnewline
25 & 12 & 12.0625 & -0.0625146 \tabularnewline
26 & 13 & 12.0871 & 0.912948 \tabularnewline
27 & 10 & 11.5971 & -1.59709 \tabularnewline
28 & 14 & 11.0675 & 2.93253 \tabularnewline
29 & 12 & 11.5369 & 0.463101 \tabularnewline
30 & 10 & 10.3644 & -0.364406 \tabularnewline
31 & 12 & 10.9696 & 1.03039 \tabularnewline
32 & 8 & 9.165 & -1.165 \tabularnewline
33 & 10 & 10.2693 & -0.269328 \tabularnewline
34 & 12 & 11.7356 & 0.264372 \tabularnewline
35 & 12 & 10.2635 & 1.73654 \tabularnewline
36 & 7 & 8.13014 & -1.13014 \tabularnewline
37 & 9 & 7.96098 & 1.03902 \tabularnewline
38 & 12 & 10.3452 & 1.65481 \tabularnewline
39 & 10 & 11.5325 & -1.53251 \tabularnewline
40 & 10 & 11.5338 & -1.53378 \tabularnewline
41 & 10 & 11.494 & -1.49401 \tabularnewline
42 & 12 & 10.356 & 1.64399 \tabularnewline
43 & 15 & 13.7019 & 1.29807 \tabularnewline
44 & 10 & 10.2704 & -0.270448 \tabularnewline
45 & 10 & 10.138 & -0.138031 \tabularnewline
46 & 12 & 8.68399 & 3.31601 \tabularnewline
47 & 13 & 10.5556 & 2.44443 \tabularnewline
48 & 11 & 11.0208 & -0.0207736 \tabularnewline
49 & 11 & 11.6485 & -0.648483 \tabularnewline
50 & 12 & 10.3262 & 1.67375 \tabularnewline
51 & 14 & 11.7493 & 2.25068 \tabularnewline
52 & 10 & 10.2446 & -0.244582 \tabularnewline
53 & 12 & 9.16225 & 2.83775 \tabularnewline
54 & 13 & 11.6624 & 1.33755 \tabularnewline
55 & 5 & 7.47369 & -2.47369 \tabularnewline
56 & 6 & 10.4015 & -4.40148 \tabularnewline
57 & 12 & 11.4938 & 0.506243 \tabularnewline
58 & 12 & 11.63 & 0.36996 \tabularnewline
59 & 11 & 11.0717 & -0.0716844 \tabularnewline
60 & 10 & 11.5243 & -1.52431 \tabularnewline
61 & 7 & 8.95059 & -1.95059 \tabularnewline
62 & 12 & 11.5485 & 0.451516 \tabularnewline
63 & 14 & 11.6571 & 2.34287 \tabularnewline
64 & 11 & 10.3784 & 0.621563 \tabularnewline
65 & 12 & 11.3585 & 0.641498 \tabularnewline
66 & 13 & 12.3135 & 0.686522 \tabularnewline
67 & 14 & 12.6666 & 1.33343 \tabularnewline
68 & 11 & 12.517 & -1.51704 \tabularnewline
69 & 12 & 9.37672 & 2.62328 \tabularnewline
70 & 12 & 11.625 & 0.375046 \tabularnewline
71 & 8 & 8.11172 & -0.111721 \tabularnewline
72 & 11 & 10.4753 & 0.524689 \tabularnewline
73 & 14 & 12.9248 & 1.07522 \tabularnewline
74 & 14 & 12.9367 & 1.06333 \tabularnewline
75 & 12 & 11.3738 & 0.626172 \tabularnewline
76 & 9 & 11.9012 & -2.90116 \tabularnewline
77 & 13 & 11.6054 & 1.39464 \tabularnewline
78 & 11 & 11.3898 & -0.389821 \tabularnewline
79 & 12 & 9.80097 & 2.19903 \tabularnewline
80 & 12 & 11.2331 & 0.766937 \tabularnewline
81 & 12 & 11.688 & 0.311971 \tabularnewline
82 & 12 & 11.6911 & 0.30891 \tabularnewline
83 & 12 & 10.9112 & 1.08877 \tabularnewline
84 & 11 & 11.0077 & -0.00774398 \tabularnewline
85 & 10 & 11.4755 & -1.47549 \tabularnewline
86 & 9 & 10.5527 & -1.55274 \tabularnewline
87 & 12 & 11.5648 & 0.435229 \tabularnewline
88 & 12 & 11.4426 & 0.557386 \tabularnewline
89 & 12 & 10.8855 & 1.11448 \tabularnewline
90 & 9 & 9.34894 & -0.348944 \tabularnewline
91 & 15 & 11.9378 & 3.06222 \tabularnewline
92 & 12 & 11.8207 & 0.179264 \tabularnewline
93 & 12 & 10.7981 & 1.20193 \tabularnewline
94 & 12 & 9.78339 & 2.21661 \tabularnewline
95 & 10 & 11.6175 & -1.61753 \tabularnewline
96 & 13 & 11.5231 & 1.47691 \tabularnewline
97 & 9 & 11.48 & -2.47997 \tabularnewline
98 & 12 & 11.5635 & 0.436467 \tabularnewline
99 & 10 & 10.5478 & -0.547772 \tabularnewline
100 & 14 & 11.6169 & 2.3831 \tabularnewline
101 & 11 & 11.5404 & -0.540357 \tabularnewline
102 & 15 & 13.9998 & 1.00023 \tabularnewline
103 & 11 & 10.7939 & 0.206138 \tabularnewline
104 & 11 & 11.7428 & -0.742836 \tabularnewline
105 & 12 & 9.63121 & 2.36879 \tabularnewline
106 & 12 & 12.1494 & -0.149364 \tabularnewline
107 & 12 & 11.6169 & 0.383068 \tabularnewline
108 & 11 & 11.4938 & -0.493831 \tabularnewline
109 & 7 & 9.23745 & -2.23745 \tabularnewline
110 & 12 & 11.6388 & 0.361183 \tabularnewline
111 & 14 & 11.5561 & 2.44389 \tabularnewline
112 & 11 & 12.5132 & -1.51317 \tabularnewline
113 & 11 & 9.64509 & 1.35491 \tabularnewline
114 & 10 & 9.22371 & 0.776292 \tabularnewline
115 & 13 & 12.6783 & 0.321743 \tabularnewline
116 & 13 & 10.5514 & 2.44859 \tabularnewline
117 & 8 & 10.6076 & -2.60761 \tabularnewline
118 & 11 & 9.91137 & 1.08863 \tabularnewline
119 & 12 & 11.6387 & 0.361311 \tabularnewline
120 & 11 & 9.86506 & 1.13494 \tabularnewline
121 & 13 & 11.3328 & 1.66723 \tabularnewline
122 & 12 & 10.0611 & 1.93894 \tabularnewline
123 & 14 & 11.7388 & 2.26123 \tabularnewline
124 & 13 & 10.8656 & 2.13443 \tabularnewline
125 & 15 & 11.6111 & 3.38887 \tabularnewline
126 & 10 & 10.9641 & -0.964055 \tabularnewline
127 & 11 & 12.2272 & -1.22717 \tabularnewline
128 & 9 & 11.0964 & -2.09641 \tabularnewline
129 & 11 & 9.1992 & 1.8008 \tabularnewline
130 & 10 & 11.5652 & -1.56517 \tabularnewline
131 & 11 & 8.02279 & 2.97721 \tabularnewline
132 & 8 & 11.6484 & -3.64838 \tabularnewline
133 & 11 & 9.12504 & 1.87496 \tabularnewline
134 & 12 & 10.5339 & 1.46609 \tabularnewline
135 & 12 & 10.8474 & 1.15261 \tabularnewline
136 & 9 & 9.27489 & -0.274888 \tabularnewline
137 & 11 & 10.9668 & 0.0332286 \tabularnewline
138 & 10 & 8.669 & 1.331 \tabularnewline
139 & 8 & 9.2251 & -1.2251 \tabularnewline
140 & 9 & 8.75577 & 0.244234 \tabularnewline
141 & 8 & 11.5282 & -3.52816 \tabularnewline
142 & 9 & 11.1654 & -2.16541 \tabularnewline
143 & 15 & 12.285 & 2.71503 \tabularnewline
144 & 11 & 11.2041 & -0.204056 \tabularnewline
145 & 8 & 8.00709 & -0.00709344 \tabularnewline
146 & 13 & 12.482 & 0.517991 \tabularnewline
147 & 12 & 9.84854 & 2.15146 \tabularnewline
148 & 12 & 11.5139 & 0.486148 \tabularnewline
149 & 9 & 9.7099 & -0.7099 \tabularnewline
150 & 7 & 8.30066 & -1.30066 \tabularnewline
151 & 13 & 10.9911 & 2.00887 \tabularnewline
152 & 9 & 11.7337 & -2.73366 \tabularnewline
153 & 6 & 11.7546 & -5.75463 \tabularnewline
154 & 8 & 10.3084 & -2.30836 \tabularnewline
155 & 8 & 7.97791 & 0.022092 \tabularnewline
156 & 15 & 11.9378 & 3.06222 \tabularnewline
157 & 6 & 9.94016 & -3.94016 \tabularnewline
158 & 9 & 11.0964 & -2.09641 \tabularnewline
159 & 11 & 11.584 & -0.584014 \tabularnewline
160 & 8 & 9.4338 & -1.4338 \tabularnewline
161 & 8 & 9.86316 & -1.86316 \tabularnewline
162 & 10 & 9.48264 & 0.517358 \tabularnewline
163 & 8 & 9.01646 & -1.01646 \tabularnewline
164 & 14 & 11.9969 & 2.00312 \tabularnewline
165 & 10 & 11.1345 & -1.13451 \tabularnewline
166 & 8 & 7.89473 & 0.105273 \tabularnewline
167 & 11 & 10.4502 & 0.549779 \tabularnewline
168 & 12 & 8.44337 & 3.55663 \tabularnewline
169 & 12 & 10.0193 & 1.9807 \tabularnewline
170 & 12 & 11.7253 & 0.274703 \tabularnewline
171 & 5 & 8.97273 & -3.97273 \tabularnewline
172 & 12 & 11.6432 & 0.356801 \tabularnewline
173 & 10 & 9.28066 & 0.719343 \tabularnewline
174 & 7 & 7.15334 & -0.15334 \tabularnewline
175 & 12 & 8.99431 & 3.00569 \tabularnewline
176 & 11 & 11.1182 & -0.118153 \tabularnewline
177 & 8 & 9.1623 & -1.1623 \tabularnewline
178 & 9 & 9.0924 & -0.0923969 \tabularnewline
179 & 10 & 10.3269 & -0.326873 \tabularnewline
180 & 9 & 9.33696 & -0.336957 \tabularnewline
181 & 12 & 11.5521 & 0.447869 \tabularnewline
182 & 6 & 8.54876 & -2.54876 \tabularnewline
183 & 15 & 13.3974 & 1.60264 \tabularnewline
184 & 12 & 10.9282 & 1.07184 \tabularnewline
185 & 12 & 6.95014 & 5.04986 \tabularnewline
186 & 12 & 11.6071 & 0.392936 \tabularnewline
187 & 11 & 12.1042 & -1.1042 \tabularnewline
188 & 7 & 9.15489 & -2.15489 \tabularnewline
189 & 7 & 8.44022 & -1.44022 \tabularnewline
190 & 5 & 8.65631 & -3.65631 \tabularnewline
191 & 12 & 10.3744 & 1.62563 \tabularnewline
192 & 12 & 11.7812 & 0.218811 \tabularnewline
193 & 3 & 9.19751 & -6.19751 \tabularnewline
194 & 11 & 11.5969 & -0.596875 \tabularnewline
195 & 10 & 9.75964 & 0.240359 \tabularnewline
196 & 12 & 11.1106 & 0.889393 \tabularnewline
197 & 9 & 11.4037 & -2.4037 \tabularnewline
198 & 12 & 11.7203 & 0.279718 \tabularnewline
199 & 9 & 10.3041 & -1.30409 \tabularnewline
200 & 12 & 11.5992 & 0.400836 \tabularnewline
201 & 12 & 11.4232 & 0.576792 \tabularnewline
202 & 10 & 10.3613 & -0.361302 \tabularnewline
203 & 9 & 8.58402 & 0.415984 \tabularnewline
204 & 12 & 9.09655 & 2.90345 \tabularnewline
205 & 8 & 11.0078 & -3.00782 \tabularnewline
206 & 11 & 11.0569 & -0.0569083 \tabularnewline
207 & 11 & 11.7233 & -0.723308 \tabularnewline
208 & 12 & 11.4963 & 0.503653 \tabularnewline
209 & 10 & 8.6051 & 1.3949 \tabularnewline
210 & 10 & 10.993 & -0.992981 \tabularnewline
211 & 12 & 9.16779 & 2.83221 \tabularnewline
212 & 12 & 9.611 & 2.389 \tabularnewline
213 & 11 & 11.2158 & -0.215816 \tabularnewline
214 & 8 & 11.0059 & -3.00585 \tabularnewline
215 & 12 & 11.5321 & 0.467916 \tabularnewline
216 & 10 & 10.0997 & -0.0996641 \tabularnewline
217 & 11 & 12.239 & -1.23904 \tabularnewline
218 & 10 & 10.4065 & -0.40645 \tabularnewline
219 & 8 & 9.73077 & -1.73077 \tabularnewline
220 & 12 & 11.1694 & 0.83059 \tabularnewline
221 & 12 & 9.82822 & 2.17178 \tabularnewline
222 & 10 & 10.3723 & -0.372257 \tabularnewline
223 & 12 & 10.8954 & 1.10463 \tabularnewline
224 & 9 & 9.25345 & -0.253451 \tabularnewline
225 & 9 & 9.69698 & -0.696982 \tabularnewline
226 & 6 & 7.09944 & -1.09944 \tabularnewline
227 & 10 & 10.2778 & -0.277837 \tabularnewline
228 & 9 & 10.4012 & -1.40121 \tabularnewline
229 & 9 & 8.53859 & 0.461405 \tabularnewline
230 & 9 & 9.302 & -0.302002 \tabularnewline
231 & 6 & 9.68689 & -3.68689 \tabularnewline
232 & 10 & 8.24062 & 1.75938 \tabularnewline
233 & 6 & 11.5569 & -5.55693 \tabularnewline
234 & 14 & 12.5479 & 1.45208 \tabularnewline
235 & 10 & 9.78802 & 0.211983 \tabularnewline
236 & 10 & 8.5428 & 1.4572 \tabularnewline
237 & 6 & 4.45325 & 1.54675 \tabularnewline
238 & 12 & 9.45587 & 2.54413 \tabularnewline
239 & 12 & 11.5477 & 0.452264 \tabularnewline
240 & 7 & 7.95046 & -0.950459 \tabularnewline
241 & 8 & 9.37556 & -1.37556 \tabularnewline
242 & 11 & 9.16705 & 1.83295 \tabularnewline
243 & 3 & 7.86565 & -4.86565 \tabularnewline
244 & 6 & 9.73277 & -3.73277 \tabularnewline
245 & 10 & 10.8585 & -0.858493 \tabularnewline
246 & 8 & 9.27429 & -1.27429 \tabularnewline
247 & 9 & 10.4309 & -1.43087 \tabularnewline
248 & 9 & 7.77052 & 1.22948 \tabularnewline
249 & 8 & 8.81455 & -0.814548 \tabularnewline
250 & 9 & 8.77475 & 0.225249 \tabularnewline
251 & 7 & 8.68707 & -1.68707 \tabularnewline
252 & 7 & 8.02685 & -1.02685 \tabularnewline
253 & 6 & 9.25647 & -3.25647 \tabularnewline
254 & 9 & 11.4976 & -2.49763 \tabularnewline
255 & 10 & 9.13194 & 0.868057 \tabularnewline
256 & 11 & 10.3351 & 0.664881 \tabularnewline
257 & 12 & 11.6081 & 0.391941 \tabularnewline
258 & 8 & 10.2947 & -2.29472 \tabularnewline
259 & 11 & 9.74432 & 1.25568 \tabularnewline
260 & 3 & 4.62239 & -1.62239 \tabularnewline
261 & 11 & 10.8869 & 0.113147 \tabularnewline
262 & 12 & 8.81693 & 3.18307 \tabularnewline
263 & 7 & 8.5829 & -1.5829 \tabularnewline
264 & 9 & 10.3983 & -1.3983 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226588&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]9.82874[/C][C]2.17126[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]11.4682[/C][C]-0.468165[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]13.3447[/C][C]1.65528[/C][/ROW]
[ROW][C]4[/C][C]6[/C][C]10.979[/C][C]-4.979[/C][/ROW]
[ROW][C]5[/C][C]13[/C][C]10.4296[/C][C]2.57043[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]9.64311[/C][C]0.356887[/C][/ROW]
[ROW][C]7[/C][C]12[/C][C]12.9252[/C][C]-0.9252[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]11.1121[/C][C]2.88791[/C][/ROW]
[ROW][C]9[/C][C]12[/C][C]10.456[/C][C]1.54398[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]11.1062[/C][C]-2.10615[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]11.4427[/C][C]-1.44267[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]11.4803[/C][C]0.519665[/C][/ROW]
[ROW][C]13[/C][C]12[/C][C]11.5271[/C][C]0.472894[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]11.5457[/C][C]-0.54567[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]12.3278[/C][C]2.67224[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]10.8932[/C][C]1.10684[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]10.8834[/C][C]-0.883419[/C][/ROW]
[ROW][C]18[/C][C]12[/C][C]14.0325[/C][C]-2.03253[/C][/ROW]
[ROW][C]19[/C][C]11[/C][C]12.7976[/C][C]-1.79764[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]11.4254[/C][C]0.574553[/C][/ROW]
[ROW][C]21[/C][C]11[/C][C]11.5294[/C][C]-0.529418[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]11.4668[/C][C]0.533161[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]13.3066[/C][C]-0.306583[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]11.6397[/C][C]-0.639722[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]12.0625[/C][C]-0.0625146[/C][/ROW]
[ROW][C]26[/C][C]13[/C][C]12.0871[/C][C]0.912948[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]11.5971[/C][C]-1.59709[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]11.0675[/C][C]2.93253[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]11.5369[/C][C]0.463101[/C][/ROW]
[ROW][C]30[/C][C]10[/C][C]10.3644[/C][C]-0.364406[/C][/ROW]
[ROW][C]31[/C][C]12[/C][C]10.9696[/C][C]1.03039[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]9.165[/C][C]-1.165[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.2693[/C][C]-0.269328[/C][/ROW]
[ROW][C]34[/C][C]12[/C][C]11.7356[/C][C]0.264372[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.2635[/C][C]1.73654[/C][/ROW]
[ROW][C]36[/C][C]7[/C][C]8.13014[/C][C]-1.13014[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]7.96098[/C][C]1.03902[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]10.3452[/C][C]1.65481[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]11.5325[/C][C]-1.53251[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]11.5338[/C][C]-1.53378[/C][/ROW]
[ROW][C]41[/C][C]10[/C][C]11.494[/C][C]-1.49401[/C][/ROW]
[ROW][C]42[/C][C]12[/C][C]10.356[/C][C]1.64399[/C][/ROW]
[ROW][C]43[/C][C]15[/C][C]13.7019[/C][C]1.29807[/C][/ROW]
[ROW][C]44[/C][C]10[/C][C]10.2704[/C][C]-0.270448[/C][/ROW]
[ROW][C]45[/C][C]10[/C][C]10.138[/C][C]-0.138031[/C][/ROW]
[ROW][C]46[/C][C]12[/C][C]8.68399[/C][C]3.31601[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]10.5556[/C][C]2.44443[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.0208[/C][C]-0.0207736[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]11.6485[/C][C]-0.648483[/C][/ROW]
[ROW][C]50[/C][C]12[/C][C]10.3262[/C][C]1.67375[/C][/ROW]
[ROW][C]51[/C][C]14[/C][C]11.7493[/C][C]2.25068[/C][/ROW]
[ROW][C]52[/C][C]10[/C][C]10.2446[/C][C]-0.244582[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]9.16225[/C][C]2.83775[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.6624[/C][C]1.33755[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]7.47369[/C][C]-2.47369[/C][/ROW]
[ROW][C]56[/C][C]6[/C][C]10.4015[/C][C]-4.40148[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]11.4938[/C][C]0.506243[/C][/ROW]
[ROW][C]58[/C][C]12[/C][C]11.63[/C][C]0.36996[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]11.0717[/C][C]-0.0716844[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]11.5243[/C][C]-1.52431[/C][/ROW]
[ROW][C]61[/C][C]7[/C][C]8.95059[/C][C]-1.95059[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]11.5485[/C][C]0.451516[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]11.6571[/C][C]2.34287[/C][/ROW]
[ROW][C]64[/C][C]11[/C][C]10.3784[/C][C]0.621563[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]11.3585[/C][C]0.641498[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]12.3135[/C][C]0.686522[/C][/ROW]
[ROW][C]67[/C][C]14[/C][C]12.6666[/C][C]1.33343[/C][/ROW]
[ROW][C]68[/C][C]11[/C][C]12.517[/C][C]-1.51704[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]9.37672[/C][C]2.62328[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]11.625[/C][C]0.375046[/C][/ROW]
[ROW][C]71[/C][C]8[/C][C]8.11172[/C][C]-0.111721[/C][/ROW]
[ROW][C]72[/C][C]11[/C][C]10.4753[/C][C]0.524689[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]12.9248[/C][C]1.07522[/C][/ROW]
[ROW][C]74[/C][C]14[/C][C]12.9367[/C][C]1.06333[/C][/ROW]
[ROW][C]75[/C][C]12[/C][C]11.3738[/C][C]0.626172[/C][/ROW]
[ROW][C]76[/C][C]9[/C][C]11.9012[/C][C]-2.90116[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.6054[/C][C]1.39464[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]11.3898[/C][C]-0.389821[/C][/ROW]
[ROW][C]79[/C][C]12[/C][C]9.80097[/C][C]2.19903[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]11.2331[/C][C]0.766937[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]11.688[/C][C]0.311971[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]11.6911[/C][C]0.30891[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]10.9112[/C][C]1.08877[/C][/ROW]
[ROW][C]84[/C][C]11[/C][C]11.0077[/C][C]-0.00774398[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]11.4755[/C][C]-1.47549[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]10.5527[/C][C]-1.55274[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]11.5648[/C][C]0.435229[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.4426[/C][C]0.557386[/C][/ROW]
[ROW][C]89[/C][C]12[/C][C]10.8855[/C][C]1.11448[/C][/ROW]
[ROW][C]90[/C][C]9[/C][C]9.34894[/C][C]-0.348944[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]11.9378[/C][C]3.06222[/C][/ROW]
[ROW][C]92[/C][C]12[/C][C]11.8207[/C][C]0.179264[/C][/ROW]
[ROW][C]93[/C][C]12[/C][C]10.7981[/C][C]1.20193[/C][/ROW]
[ROW][C]94[/C][C]12[/C][C]9.78339[/C][C]2.21661[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]11.6175[/C][C]-1.61753[/C][/ROW]
[ROW][C]96[/C][C]13[/C][C]11.5231[/C][C]1.47691[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]11.48[/C][C]-2.47997[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]11.5635[/C][C]0.436467[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]10.5478[/C][C]-0.547772[/C][/ROW]
[ROW][C]100[/C][C]14[/C][C]11.6169[/C][C]2.3831[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]11.5404[/C][C]-0.540357[/C][/ROW]
[ROW][C]102[/C][C]15[/C][C]13.9998[/C][C]1.00023[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]10.7939[/C][C]0.206138[/C][/ROW]
[ROW][C]104[/C][C]11[/C][C]11.7428[/C][C]-0.742836[/C][/ROW]
[ROW][C]105[/C][C]12[/C][C]9.63121[/C][C]2.36879[/C][/ROW]
[ROW][C]106[/C][C]12[/C][C]12.1494[/C][C]-0.149364[/C][/ROW]
[ROW][C]107[/C][C]12[/C][C]11.6169[/C][C]0.383068[/C][/ROW]
[ROW][C]108[/C][C]11[/C][C]11.4938[/C][C]-0.493831[/C][/ROW]
[ROW][C]109[/C][C]7[/C][C]9.23745[/C][C]-2.23745[/C][/ROW]
[ROW][C]110[/C][C]12[/C][C]11.6388[/C][C]0.361183[/C][/ROW]
[ROW][C]111[/C][C]14[/C][C]11.5561[/C][C]2.44389[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.5132[/C][C]-1.51317[/C][/ROW]
[ROW][C]113[/C][C]11[/C][C]9.64509[/C][C]1.35491[/C][/ROW]
[ROW][C]114[/C][C]10[/C][C]9.22371[/C][C]0.776292[/C][/ROW]
[ROW][C]115[/C][C]13[/C][C]12.6783[/C][C]0.321743[/C][/ROW]
[ROW][C]116[/C][C]13[/C][C]10.5514[/C][C]2.44859[/C][/ROW]
[ROW][C]117[/C][C]8[/C][C]10.6076[/C][C]-2.60761[/C][/ROW]
[ROW][C]118[/C][C]11[/C][C]9.91137[/C][C]1.08863[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]11.6387[/C][C]0.361311[/C][/ROW]
[ROW][C]120[/C][C]11[/C][C]9.86506[/C][C]1.13494[/C][/ROW]
[ROW][C]121[/C][C]13[/C][C]11.3328[/C][C]1.66723[/C][/ROW]
[ROW][C]122[/C][C]12[/C][C]10.0611[/C][C]1.93894[/C][/ROW]
[ROW][C]123[/C][C]14[/C][C]11.7388[/C][C]2.26123[/C][/ROW]
[ROW][C]124[/C][C]13[/C][C]10.8656[/C][C]2.13443[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]11.6111[/C][C]3.38887[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]10.9641[/C][C]-0.964055[/C][/ROW]
[ROW][C]127[/C][C]11[/C][C]12.2272[/C][C]-1.22717[/C][/ROW]
[ROW][C]128[/C][C]9[/C][C]11.0964[/C][C]-2.09641[/C][/ROW]
[ROW][C]129[/C][C]11[/C][C]9.1992[/C][C]1.8008[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]11.5652[/C][C]-1.56517[/C][/ROW]
[ROW][C]131[/C][C]11[/C][C]8.02279[/C][C]2.97721[/C][/ROW]
[ROW][C]132[/C][C]8[/C][C]11.6484[/C][C]-3.64838[/C][/ROW]
[ROW][C]133[/C][C]11[/C][C]9.12504[/C][C]1.87496[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]10.5339[/C][C]1.46609[/C][/ROW]
[ROW][C]135[/C][C]12[/C][C]10.8474[/C][C]1.15261[/C][/ROW]
[ROW][C]136[/C][C]9[/C][C]9.27489[/C][C]-0.274888[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]10.9668[/C][C]0.0332286[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]8.669[/C][C]1.331[/C][/ROW]
[ROW][C]139[/C][C]8[/C][C]9.2251[/C][C]-1.2251[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]8.75577[/C][C]0.244234[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]11.5282[/C][C]-3.52816[/C][/ROW]
[ROW][C]142[/C][C]9[/C][C]11.1654[/C][C]-2.16541[/C][/ROW]
[ROW][C]143[/C][C]15[/C][C]12.285[/C][C]2.71503[/C][/ROW]
[ROW][C]144[/C][C]11[/C][C]11.2041[/C][C]-0.204056[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]8.00709[/C][C]-0.00709344[/C][/ROW]
[ROW][C]146[/C][C]13[/C][C]12.482[/C][C]0.517991[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]9.84854[/C][C]2.15146[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]11.5139[/C][C]0.486148[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]9.7099[/C][C]-0.7099[/C][/ROW]
[ROW][C]150[/C][C]7[/C][C]8.30066[/C][C]-1.30066[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]10.9911[/C][C]2.00887[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.7337[/C][C]-2.73366[/C][/ROW]
[ROW][C]153[/C][C]6[/C][C]11.7546[/C][C]-5.75463[/C][/ROW]
[ROW][C]154[/C][C]8[/C][C]10.3084[/C][C]-2.30836[/C][/ROW]
[ROW][C]155[/C][C]8[/C][C]7.97791[/C][C]0.022092[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]11.9378[/C][C]3.06222[/C][/ROW]
[ROW][C]157[/C][C]6[/C][C]9.94016[/C][C]-3.94016[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]11.0964[/C][C]-2.09641[/C][/ROW]
[ROW][C]159[/C][C]11[/C][C]11.584[/C][C]-0.584014[/C][/ROW]
[ROW][C]160[/C][C]8[/C][C]9.4338[/C][C]-1.4338[/C][/ROW]
[ROW][C]161[/C][C]8[/C][C]9.86316[/C][C]-1.86316[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.48264[/C][C]0.517358[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]9.01646[/C][C]-1.01646[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]11.9969[/C][C]2.00312[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.1345[/C][C]-1.13451[/C][/ROW]
[ROW][C]166[/C][C]8[/C][C]7.89473[/C][C]0.105273[/C][/ROW]
[ROW][C]167[/C][C]11[/C][C]10.4502[/C][C]0.549779[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]8.44337[/C][C]3.55663[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]10.0193[/C][C]1.9807[/C][/ROW]
[ROW][C]170[/C][C]12[/C][C]11.7253[/C][C]0.274703[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]8.97273[/C][C]-3.97273[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.6432[/C][C]0.356801[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]9.28066[/C][C]0.719343[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]7.15334[/C][C]-0.15334[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]8.99431[/C][C]3.00569[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]11.1182[/C][C]-0.118153[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]9.1623[/C][C]-1.1623[/C][/ROW]
[ROW][C]178[/C][C]9[/C][C]9.0924[/C][C]-0.0923969[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]10.3269[/C][C]-0.326873[/C][/ROW]
[ROW][C]180[/C][C]9[/C][C]9.33696[/C][C]-0.336957[/C][/ROW]
[ROW][C]181[/C][C]12[/C][C]11.5521[/C][C]0.447869[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]8.54876[/C][C]-2.54876[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]13.3974[/C][C]1.60264[/C][/ROW]
[ROW][C]184[/C][C]12[/C][C]10.9282[/C][C]1.07184[/C][/ROW]
[ROW][C]185[/C][C]12[/C][C]6.95014[/C][C]5.04986[/C][/ROW]
[ROW][C]186[/C][C]12[/C][C]11.6071[/C][C]0.392936[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]12.1042[/C][C]-1.1042[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]9.15489[/C][C]-2.15489[/C][/ROW]
[ROW][C]189[/C][C]7[/C][C]8.44022[/C][C]-1.44022[/C][/ROW]
[ROW][C]190[/C][C]5[/C][C]8.65631[/C][C]-3.65631[/C][/ROW]
[ROW][C]191[/C][C]12[/C][C]10.3744[/C][C]1.62563[/C][/ROW]
[ROW][C]192[/C][C]12[/C][C]11.7812[/C][C]0.218811[/C][/ROW]
[ROW][C]193[/C][C]3[/C][C]9.19751[/C][C]-6.19751[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]11.5969[/C][C]-0.596875[/C][/ROW]
[ROW][C]195[/C][C]10[/C][C]9.75964[/C][C]0.240359[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]11.1106[/C][C]0.889393[/C][/ROW]
[ROW][C]197[/C][C]9[/C][C]11.4037[/C][C]-2.4037[/C][/ROW]
[ROW][C]198[/C][C]12[/C][C]11.7203[/C][C]0.279718[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]10.3041[/C][C]-1.30409[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]11.5992[/C][C]0.400836[/C][/ROW]
[ROW][C]201[/C][C]12[/C][C]11.4232[/C][C]0.576792[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]10.3613[/C][C]-0.361302[/C][/ROW]
[ROW][C]203[/C][C]9[/C][C]8.58402[/C][C]0.415984[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]9.09655[/C][C]2.90345[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]11.0078[/C][C]-3.00782[/C][/ROW]
[ROW][C]206[/C][C]11[/C][C]11.0569[/C][C]-0.0569083[/C][/ROW]
[ROW][C]207[/C][C]11[/C][C]11.7233[/C][C]-0.723308[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]11.4963[/C][C]0.503653[/C][/ROW]
[ROW][C]209[/C][C]10[/C][C]8.6051[/C][C]1.3949[/C][/ROW]
[ROW][C]210[/C][C]10[/C][C]10.993[/C][C]-0.992981[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]9.16779[/C][C]2.83221[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]9.611[/C][C]2.389[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.2158[/C][C]-0.215816[/C][/ROW]
[ROW][C]214[/C][C]8[/C][C]11.0059[/C][C]-3.00585[/C][/ROW]
[ROW][C]215[/C][C]12[/C][C]11.5321[/C][C]0.467916[/C][/ROW]
[ROW][C]216[/C][C]10[/C][C]10.0997[/C][C]-0.0996641[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]12.239[/C][C]-1.23904[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]10.4065[/C][C]-0.40645[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.73077[/C][C]-1.73077[/C][/ROW]
[ROW][C]220[/C][C]12[/C][C]11.1694[/C][C]0.83059[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]9.82822[/C][C]2.17178[/C][/ROW]
[ROW][C]222[/C][C]10[/C][C]10.3723[/C][C]-0.372257[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]10.8954[/C][C]1.10463[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]9.25345[/C][C]-0.253451[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.69698[/C][C]-0.696982[/C][/ROW]
[ROW][C]226[/C][C]6[/C][C]7.09944[/C][C]-1.09944[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]10.2778[/C][C]-0.277837[/C][/ROW]
[ROW][C]228[/C][C]9[/C][C]10.4012[/C][C]-1.40121[/C][/ROW]
[ROW][C]229[/C][C]9[/C][C]8.53859[/C][C]0.461405[/C][/ROW]
[ROW][C]230[/C][C]9[/C][C]9.302[/C][C]-0.302002[/C][/ROW]
[ROW][C]231[/C][C]6[/C][C]9.68689[/C][C]-3.68689[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]8.24062[/C][C]1.75938[/C][/ROW]
[ROW][C]233[/C][C]6[/C][C]11.5569[/C][C]-5.55693[/C][/ROW]
[ROW][C]234[/C][C]14[/C][C]12.5479[/C][C]1.45208[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]9.78802[/C][C]0.211983[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]8.5428[/C][C]1.4572[/C][/ROW]
[ROW][C]237[/C][C]6[/C][C]4.45325[/C][C]1.54675[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]9.45587[/C][C]2.54413[/C][/ROW]
[ROW][C]239[/C][C]12[/C][C]11.5477[/C][C]0.452264[/C][/ROW]
[ROW][C]240[/C][C]7[/C][C]7.95046[/C][C]-0.950459[/C][/ROW]
[ROW][C]241[/C][C]8[/C][C]9.37556[/C][C]-1.37556[/C][/ROW]
[ROW][C]242[/C][C]11[/C][C]9.16705[/C][C]1.83295[/C][/ROW]
[ROW][C]243[/C][C]3[/C][C]7.86565[/C][C]-4.86565[/C][/ROW]
[ROW][C]244[/C][C]6[/C][C]9.73277[/C][C]-3.73277[/C][/ROW]
[ROW][C]245[/C][C]10[/C][C]10.8585[/C][C]-0.858493[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]9.27429[/C][C]-1.27429[/C][/ROW]
[ROW][C]247[/C][C]9[/C][C]10.4309[/C][C]-1.43087[/C][/ROW]
[ROW][C]248[/C][C]9[/C][C]7.77052[/C][C]1.22948[/C][/ROW]
[ROW][C]249[/C][C]8[/C][C]8.81455[/C][C]-0.814548[/C][/ROW]
[ROW][C]250[/C][C]9[/C][C]8.77475[/C][C]0.225249[/C][/ROW]
[ROW][C]251[/C][C]7[/C][C]8.68707[/C][C]-1.68707[/C][/ROW]
[ROW][C]252[/C][C]7[/C][C]8.02685[/C][C]-1.02685[/C][/ROW]
[ROW][C]253[/C][C]6[/C][C]9.25647[/C][C]-3.25647[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]11.4976[/C][C]-2.49763[/C][/ROW]
[ROW][C]255[/C][C]10[/C][C]9.13194[/C][C]0.868057[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]10.3351[/C][C]0.664881[/C][/ROW]
[ROW][C]257[/C][C]12[/C][C]11.6081[/C][C]0.391941[/C][/ROW]
[ROW][C]258[/C][C]8[/C][C]10.2947[/C][C]-2.29472[/C][/ROW]
[ROW][C]259[/C][C]11[/C][C]9.74432[/C][C]1.25568[/C][/ROW]
[ROW][C]260[/C][C]3[/C][C]4.62239[/C][C]-1.62239[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]10.8869[/C][C]0.113147[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]8.81693[/C][C]3.18307[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]8.5829[/C][C]-1.5829[/C][/ROW]
[ROW][C]264[/C][C]9[/C][C]10.3983[/C][C]-1.3983[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226588&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226588&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
1129.828742.17126
21111.4682-0.468165
31513.34471.65528
4610.979-4.979
51310.42962.57043
6109.643110.356887
71212.9252-0.9252
81411.11212.88791
91210.4561.54398
10911.1062-2.10615
111011.4427-1.44267
121211.48030.519665
131211.52710.472894
141111.5457-0.54567
151512.32782.67224
161210.89321.10684
171010.8834-0.883419
181214.0325-2.03253
191112.7976-1.79764
201211.42540.574553
211111.5294-0.529418
221211.46680.533161
231313.3066-0.306583
241111.6397-0.639722
251212.0625-0.0625146
261312.08710.912948
271011.5971-1.59709
281411.06752.93253
291211.53690.463101
301010.3644-0.364406
311210.96961.03039
3289.165-1.165
331010.2693-0.269328
341211.73560.264372
351210.26351.73654
3678.13014-1.13014
3797.960981.03902
381210.34521.65481
391011.5325-1.53251
401011.5338-1.53378
411011.494-1.49401
421210.3561.64399
431513.70191.29807
441010.2704-0.270448
451010.138-0.138031
46128.683993.31601
471310.55562.44443
481111.0208-0.0207736
491111.6485-0.648483
501210.32621.67375
511411.74932.25068
521010.2446-0.244582
53129.162252.83775
541311.66241.33755
5557.47369-2.47369
56610.4015-4.40148
571211.49380.506243
581211.630.36996
591111.0717-0.0716844
601011.5243-1.52431
6178.95059-1.95059
621211.54850.451516
631411.65712.34287
641110.37840.621563
651211.35850.641498
661312.31350.686522
671412.66661.33343
681112.517-1.51704
69129.376722.62328
701211.6250.375046
7188.11172-0.111721
721110.47530.524689
731412.92481.07522
741412.93671.06333
751211.37380.626172
76911.9012-2.90116
771311.60541.39464
781111.3898-0.389821
79129.800972.19903
801211.23310.766937
811211.6880.311971
821211.69110.30891
831210.91121.08877
841111.0077-0.00774398
851011.4755-1.47549
86910.5527-1.55274
871211.56480.435229
881211.44260.557386
891210.88551.11448
9099.34894-0.348944
911511.93783.06222
921211.82070.179264
931210.79811.20193
94129.783392.21661
951011.6175-1.61753
961311.52311.47691
97911.48-2.47997
981211.56350.436467
991010.5478-0.547772
1001411.61692.3831
1011111.5404-0.540357
1021513.99981.00023
1031110.79390.206138
1041111.7428-0.742836
105129.631212.36879
1061212.1494-0.149364
1071211.61690.383068
1081111.4938-0.493831
10979.23745-2.23745
1101211.63880.361183
1111411.55612.44389
1121112.5132-1.51317
113119.645091.35491
114109.223710.776292
1151312.67830.321743
1161310.55142.44859
117810.6076-2.60761
118119.911371.08863
1191211.63870.361311
120119.865061.13494
1211311.33281.66723
1221210.06111.93894
1231411.73882.26123
1241310.86562.13443
1251511.61113.38887
1261010.9641-0.964055
1271112.2272-1.22717
128911.0964-2.09641
129119.19921.8008
1301011.5652-1.56517
131118.022792.97721
132811.6484-3.64838
133119.125041.87496
1341210.53391.46609
1351210.84741.15261
13699.27489-0.274888
1371110.96680.0332286
138108.6691.331
13989.2251-1.2251
14098.755770.244234
141811.5282-3.52816
142911.1654-2.16541
1431512.2852.71503
1441111.2041-0.204056
14588.00709-0.00709344
1461312.4820.517991
147129.848542.15146
1481211.51390.486148
14999.7099-0.7099
15078.30066-1.30066
1511310.99112.00887
152911.7337-2.73366
153611.7546-5.75463
154810.3084-2.30836
15587.977910.022092
1561511.93783.06222
15769.94016-3.94016
158911.0964-2.09641
1591111.584-0.584014
16089.4338-1.4338
16189.86316-1.86316
162109.482640.517358
16389.01646-1.01646
1641411.99692.00312
1651011.1345-1.13451
16687.894730.105273
1671110.45020.549779
168128.443373.55663
1691210.01931.9807
1701211.72530.274703
17158.97273-3.97273
1721211.64320.356801
173109.280660.719343
17477.15334-0.15334
175128.994313.00569
1761111.1182-0.118153
17789.1623-1.1623
17899.0924-0.0923969
1791010.3269-0.326873
18099.33696-0.336957
1811211.55210.447869
18268.54876-2.54876
1831513.39741.60264
1841210.92821.07184
185126.950145.04986
1861211.60710.392936
1871112.1042-1.1042
18879.15489-2.15489
18978.44022-1.44022
19058.65631-3.65631
1911210.37441.62563
1921211.78120.218811
19339.19751-6.19751
1941111.5969-0.596875
195109.759640.240359
1961211.11060.889393
197911.4037-2.4037
1981211.72030.279718
199910.3041-1.30409
2001211.59920.400836
2011211.42320.576792
2021010.3613-0.361302
20398.584020.415984
204129.096552.90345
205811.0078-3.00782
2061111.0569-0.0569083
2071111.7233-0.723308
2081211.49630.503653
209108.60511.3949
2101010.993-0.992981
211129.167792.83221
212129.6112.389
2131111.2158-0.215816
214811.0059-3.00585
2151211.53210.467916
2161010.0997-0.0996641
2171112.239-1.23904
2181010.4065-0.40645
21989.73077-1.73077
2201211.16940.83059
221129.828222.17178
2221010.3723-0.372257
2231210.89541.10463
22499.25345-0.253451
22599.69698-0.696982
22667.09944-1.09944
2271010.2778-0.277837
228910.4012-1.40121
22998.538590.461405
23099.302-0.302002
23169.68689-3.68689
232108.240621.75938
233611.5569-5.55693
2341412.54791.45208
235109.788020.211983
236108.54281.4572
23764.453251.54675
238129.455872.54413
2391211.54770.452264
24077.95046-0.950459
24189.37556-1.37556
242119.167051.83295
24337.86565-4.86565
24469.73277-3.73277
2451010.8585-0.858493
24689.27429-1.27429
247910.4309-1.43087
24897.770521.22948
24988.81455-0.814548
25098.774750.225249
25178.68707-1.68707
25278.02685-1.02685
25369.25647-3.25647
254911.4976-2.49763
255109.131940.868057
2561110.33510.664881
2571211.60810.391941
258810.2947-2.29472
259119.744321.25568
26034.62239-1.62239
2611110.88690.113147
262128.816933.18307
26378.5829-1.5829
264910.3983-1.3983






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.9912690.01746240.00873122
110.9815260.03694890.0184744
120.9792970.04140620.0207031
130.9661320.06773580.0338679
140.9583470.08330530.0416526
150.9407890.1184220.059211
160.923470.1530590.0765297
170.8883660.2232680.111634
180.8993120.2013760.100688
190.8729540.2540920.127046
200.8276810.3446370.172319
210.7859560.4280880.214044
220.742130.5157390.25787
230.6840930.6318140.315907
240.6385230.7229540.361477
250.5867380.8265250.413262
260.6199050.7601910.380095
270.6072880.7854240.392712
280.6208540.7582930.379146
290.5589360.8821280.441064
300.5105370.9789260.489463
310.4607720.9215450.539228
320.4798580.9597150.520142
330.4205660.8411310.579434
340.3664980.7329950.633502
350.3543850.7087690.645615
360.3509050.701810.649095
370.3018780.6037560.698122
380.2876350.575270.712365
390.2678970.5357930.732103
400.2435670.4871330.756433
410.2164040.4328080.783596
420.1945720.3891440.805428
430.2412030.4824060.758797
440.2032640.4065290.796736
450.1689060.3378120.831094
460.2115010.4230020.788499
470.2157650.4315290.784235
480.1814140.3628270.818586
490.1666050.3332090.833395
500.1539330.3078650.846067
510.1615740.3231490.838426
520.1343490.2686970.865651
530.1421910.2843810.857809
540.1221750.244350.877825
550.188880.377760.81112
560.4464060.8928120.553594
570.4045730.8091460.595427
580.3632860.7265710.636714
590.3240770.6481550.675923
600.3207860.6415730.679214
610.3249990.6499990.675001
620.2881340.5762680.711866
630.2986880.5973750.701312
640.2642780.5285560.735722
650.2405710.4811430.759429
660.2097030.4194070.790297
670.1919070.3838140.808093
680.1721380.3442770.827862
690.1720050.344010.827995
700.1472490.2944990.852751
710.1303180.2606360.869682
720.1106870.2213750.889313
730.09440820.1888160.905592
740.08021550.1604310.919785
750.07193490.143870.928065
760.09196040.1839210.90804
770.08214650.1642930.917854
780.06798740.1359750.932013
790.07260060.1452010.927399
800.06963440.1392690.930366
810.05758440.1151690.942416
820.04743140.09486270.952569
830.04143420.08286850.958566
840.03360110.06720220.966399
850.03086070.06172140.969139
860.03497240.06994480.965028
870.02823820.05647630.971762
880.02294710.04589420.977053
890.01945540.03891080.980545
900.01638130.03276270.983619
910.02746770.05493550.972532
920.02263130.04526250.977369
930.02089190.04178380.979108
940.02284480.04568950.977155
950.02247030.04494060.97753
960.02029110.04058220.979709
970.02472570.04945140.975274
980.02005020.04010040.97995
990.01694690.03389390.983053
1000.02022260.04044520.979777
1010.01669640.03339280.983304
1020.01415720.02831450.985843
1030.01117040.02234070.98883
1040.009788990.0195780.990211
1050.01110810.02221610.988892
1060.008681060.01736210.991319
1070.006815910.01363180.993184
1080.005561520.0111230.994438
1090.007929450.01585890.992071
1100.006174420.01234880.993826
1110.007240330.01448070.99276
1120.007725480.0154510.992275
1130.00678330.01356660.993217
1140.005454110.01090820.994546
1150.00424290.00848580.995757
1160.005018980.0100380.994981
1170.00770540.01541080.992295
1180.00645650.0129130.993543
1190.005026310.01005260.994974
1200.004237030.008474060.995763
1210.004052270.008104550.995948
1220.004095840.008191680.995904
1230.004831860.009663710.995168
1240.005441790.01088360.994558
1250.009958990.0199180.990041
1260.008365210.01673040.991635
1270.007082220.01416440.992918
1280.007894560.01578910.992105
1290.0077190.0154380.992281
1300.007556430.01511290.992444
1310.009543820.01908760.990456
1320.01865650.03731310.981343
1330.01811640.03623270.981884
1340.01691870.03383730.983081
1350.01460050.02920110.985399
1360.01196290.02392570.988037
1370.009568030.01913610.990432
1380.008540860.01708170.991459
1390.007736820.01547360.992263
1400.00628150.0125630.993719
1410.01189020.02378050.98811
1420.01381160.02762320.986188
1430.01830280.03660570.981697
1440.01469490.02938990.985305
1450.0116960.0233920.988304
1460.009472920.01894580.990527
1470.01042050.02084110.989579
1480.008413160.01682630.991587
1490.00715370.01430740.992846
1500.006545280.01309060.993455
1510.006954430.01390890.993046
1520.008935380.01787080.991065
1530.05626130.1125230.943739
1540.06415780.1283160.935842
1550.05413640.1082730.945864
1560.07762640.1552530.922374
1570.1364170.2728330.863583
1580.1401450.280290.859855
1590.1223610.2447220.877639
1600.1175320.2350640.882468
1610.1183150.236630.881685
1620.1034490.2068980.896551
1630.09290890.1858180.907091
1640.09825870.1965170.901741
1650.08861110.1772220.911389
1660.07571730.1514350.924283
1670.06469530.1293910.935305
1680.1056920.2113840.894308
1690.107560.2151210.89244
1700.09310230.1862050.906898
1710.1599090.3198190.840091
1720.1394720.2789440.860528
1730.1228820.2457650.877118
1740.1058470.2116940.894153
1750.1428280.2856550.857172
1760.1231860.2463720.876814
1770.1111550.2223090.888845
1780.09516330.1903270.904837
1790.08074650.1614930.919254
1800.06781640.1356330.932184
1810.05721870.1144370.942781
1820.06553580.1310720.934464
1830.06716310.1343260.932837
1840.06176930.1235390.938231
1850.2356180.4712370.764382
1860.2148110.4296210.785189
1870.1931820.3863650.806818
1880.1972560.3945120.802744
1890.1829980.3659960.817002
1900.2634530.5269060.736547
1910.252470.5049390.74753
1920.2221570.4443140.777843
1930.5901040.8197910.409896
1940.5526370.8947260.447363
1950.5156990.9686020.484301
1960.4870350.974070.512965
1970.5110290.9779410.488971
1980.4739880.9479760.526012
1990.4493140.8986270.550686
2000.438380.8767610.56162
2010.4184430.8368870.581557
2020.3940830.7881670.605917
2030.3575460.7150930.642454
2040.429860.859720.57014
2050.4674820.9349650.532518
2060.425050.8501010.57495
2070.3838740.7677480.616126
2080.3464180.6928360.653582
2090.3291670.6583330.670833
2100.2940540.5881090.705946
2110.3678320.7356640.632168
2120.3920790.7841590.607921
2130.3504450.7008890.649555
2140.3700950.7401910.629905
2150.3335110.6670220.666489
2160.2977870.5955730.702213
2170.2625380.5250760.737462
2180.2257650.4515290.774235
2190.2271210.4542430.772879
2200.2047510.4095030.795249
2210.2450750.4901510.754925
2220.2073230.4146460.792677
2230.1978630.3957260.802137
2240.1726120.3452240.827388
2250.1482570.2965150.851743
2260.1223880.2447760.877612
2270.09961780.1992360.900382
2280.08120180.1624040.918798
2290.06287790.1257560.937122
2300.04847710.09695420.951523
2310.07359870.1471970.926401
2320.09123230.1824650.908768
2330.3170880.6341760.682912
2340.2847960.5695920.715204
2350.2359550.4719110.764045
2360.2332730.4665460.766727
2370.2796240.5592490.720376
2380.2992450.5984910.700755
2390.2924570.5849130.707543
2400.2442820.4885650.755718
2410.2030030.4060060.796997
2420.250880.501760.74912
2430.5467010.9065980.453299
2440.7022760.5954480.297724
2450.6239540.7520920.376046
2460.5668520.8662970.433148
2470.5191390.9617210.480861
2480.4606390.9212780.539361
2490.3644030.7288060.635597
2500.3362970.6725950.663703
2510.4739770.9479550.526023
2520.688350.62330.31165
2530.6818080.6363840.318192
2540.7097640.5804730.290236

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.991269 & 0.0174624 & 0.00873122 \tabularnewline
11 & 0.981526 & 0.0369489 & 0.0184744 \tabularnewline
12 & 0.979297 & 0.0414062 & 0.0207031 \tabularnewline
13 & 0.966132 & 0.0677358 & 0.0338679 \tabularnewline
14 & 0.958347 & 0.0833053 & 0.0416526 \tabularnewline
15 & 0.940789 & 0.118422 & 0.059211 \tabularnewline
16 & 0.92347 & 0.153059 & 0.0765297 \tabularnewline
17 & 0.888366 & 0.223268 & 0.111634 \tabularnewline
18 & 0.899312 & 0.201376 & 0.100688 \tabularnewline
19 & 0.872954 & 0.254092 & 0.127046 \tabularnewline
20 & 0.827681 & 0.344637 & 0.172319 \tabularnewline
21 & 0.785956 & 0.428088 & 0.214044 \tabularnewline
22 & 0.74213 & 0.515739 & 0.25787 \tabularnewline
23 & 0.684093 & 0.631814 & 0.315907 \tabularnewline
24 & 0.638523 & 0.722954 & 0.361477 \tabularnewline
25 & 0.586738 & 0.826525 & 0.413262 \tabularnewline
26 & 0.619905 & 0.760191 & 0.380095 \tabularnewline
27 & 0.607288 & 0.785424 & 0.392712 \tabularnewline
28 & 0.620854 & 0.758293 & 0.379146 \tabularnewline
29 & 0.558936 & 0.882128 & 0.441064 \tabularnewline
30 & 0.510537 & 0.978926 & 0.489463 \tabularnewline
31 & 0.460772 & 0.921545 & 0.539228 \tabularnewline
32 & 0.479858 & 0.959715 & 0.520142 \tabularnewline
33 & 0.420566 & 0.841131 & 0.579434 \tabularnewline
34 & 0.366498 & 0.732995 & 0.633502 \tabularnewline
35 & 0.354385 & 0.708769 & 0.645615 \tabularnewline
36 & 0.350905 & 0.70181 & 0.649095 \tabularnewline
37 & 0.301878 & 0.603756 & 0.698122 \tabularnewline
38 & 0.287635 & 0.57527 & 0.712365 \tabularnewline
39 & 0.267897 & 0.535793 & 0.732103 \tabularnewline
40 & 0.243567 & 0.487133 & 0.756433 \tabularnewline
41 & 0.216404 & 0.432808 & 0.783596 \tabularnewline
42 & 0.194572 & 0.389144 & 0.805428 \tabularnewline
43 & 0.241203 & 0.482406 & 0.758797 \tabularnewline
44 & 0.203264 & 0.406529 & 0.796736 \tabularnewline
45 & 0.168906 & 0.337812 & 0.831094 \tabularnewline
46 & 0.211501 & 0.423002 & 0.788499 \tabularnewline
47 & 0.215765 & 0.431529 & 0.784235 \tabularnewline
48 & 0.181414 & 0.362827 & 0.818586 \tabularnewline
49 & 0.166605 & 0.333209 & 0.833395 \tabularnewline
50 & 0.153933 & 0.307865 & 0.846067 \tabularnewline
51 & 0.161574 & 0.323149 & 0.838426 \tabularnewline
52 & 0.134349 & 0.268697 & 0.865651 \tabularnewline
53 & 0.142191 & 0.284381 & 0.857809 \tabularnewline
54 & 0.122175 & 0.24435 & 0.877825 \tabularnewline
55 & 0.18888 & 0.37776 & 0.81112 \tabularnewline
56 & 0.446406 & 0.892812 & 0.553594 \tabularnewline
57 & 0.404573 & 0.809146 & 0.595427 \tabularnewline
58 & 0.363286 & 0.726571 & 0.636714 \tabularnewline
59 & 0.324077 & 0.648155 & 0.675923 \tabularnewline
60 & 0.320786 & 0.641573 & 0.679214 \tabularnewline
61 & 0.324999 & 0.649999 & 0.675001 \tabularnewline
62 & 0.288134 & 0.576268 & 0.711866 \tabularnewline
63 & 0.298688 & 0.597375 & 0.701312 \tabularnewline
64 & 0.264278 & 0.528556 & 0.735722 \tabularnewline
65 & 0.240571 & 0.481143 & 0.759429 \tabularnewline
66 & 0.209703 & 0.419407 & 0.790297 \tabularnewline
67 & 0.191907 & 0.383814 & 0.808093 \tabularnewline
68 & 0.172138 & 0.344277 & 0.827862 \tabularnewline
69 & 0.172005 & 0.34401 & 0.827995 \tabularnewline
70 & 0.147249 & 0.294499 & 0.852751 \tabularnewline
71 & 0.130318 & 0.260636 & 0.869682 \tabularnewline
72 & 0.110687 & 0.221375 & 0.889313 \tabularnewline
73 & 0.0944082 & 0.188816 & 0.905592 \tabularnewline
74 & 0.0802155 & 0.160431 & 0.919785 \tabularnewline
75 & 0.0719349 & 0.14387 & 0.928065 \tabularnewline
76 & 0.0919604 & 0.183921 & 0.90804 \tabularnewline
77 & 0.0821465 & 0.164293 & 0.917854 \tabularnewline
78 & 0.0679874 & 0.135975 & 0.932013 \tabularnewline
79 & 0.0726006 & 0.145201 & 0.927399 \tabularnewline
80 & 0.0696344 & 0.139269 & 0.930366 \tabularnewline
81 & 0.0575844 & 0.115169 & 0.942416 \tabularnewline
82 & 0.0474314 & 0.0948627 & 0.952569 \tabularnewline
83 & 0.0414342 & 0.0828685 & 0.958566 \tabularnewline
84 & 0.0336011 & 0.0672022 & 0.966399 \tabularnewline
85 & 0.0308607 & 0.0617214 & 0.969139 \tabularnewline
86 & 0.0349724 & 0.0699448 & 0.965028 \tabularnewline
87 & 0.0282382 & 0.0564763 & 0.971762 \tabularnewline
88 & 0.0229471 & 0.0458942 & 0.977053 \tabularnewline
89 & 0.0194554 & 0.0389108 & 0.980545 \tabularnewline
90 & 0.0163813 & 0.0327627 & 0.983619 \tabularnewline
91 & 0.0274677 & 0.0549355 & 0.972532 \tabularnewline
92 & 0.0226313 & 0.0452625 & 0.977369 \tabularnewline
93 & 0.0208919 & 0.0417838 & 0.979108 \tabularnewline
94 & 0.0228448 & 0.0456895 & 0.977155 \tabularnewline
95 & 0.0224703 & 0.0449406 & 0.97753 \tabularnewline
96 & 0.0202911 & 0.0405822 & 0.979709 \tabularnewline
97 & 0.0247257 & 0.0494514 & 0.975274 \tabularnewline
98 & 0.0200502 & 0.0401004 & 0.97995 \tabularnewline
99 & 0.0169469 & 0.0338939 & 0.983053 \tabularnewline
100 & 0.0202226 & 0.0404452 & 0.979777 \tabularnewline
101 & 0.0166964 & 0.0333928 & 0.983304 \tabularnewline
102 & 0.0141572 & 0.0283145 & 0.985843 \tabularnewline
103 & 0.0111704 & 0.0223407 & 0.98883 \tabularnewline
104 & 0.00978899 & 0.019578 & 0.990211 \tabularnewline
105 & 0.0111081 & 0.0222161 & 0.988892 \tabularnewline
106 & 0.00868106 & 0.0173621 & 0.991319 \tabularnewline
107 & 0.00681591 & 0.0136318 & 0.993184 \tabularnewline
108 & 0.00556152 & 0.011123 & 0.994438 \tabularnewline
109 & 0.00792945 & 0.0158589 & 0.992071 \tabularnewline
110 & 0.00617442 & 0.0123488 & 0.993826 \tabularnewline
111 & 0.00724033 & 0.0144807 & 0.99276 \tabularnewline
112 & 0.00772548 & 0.015451 & 0.992275 \tabularnewline
113 & 0.0067833 & 0.0135666 & 0.993217 \tabularnewline
114 & 0.00545411 & 0.0109082 & 0.994546 \tabularnewline
115 & 0.0042429 & 0.0084858 & 0.995757 \tabularnewline
116 & 0.00501898 & 0.010038 & 0.994981 \tabularnewline
117 & 0.0077054 & 0.0154108 & 0.992295 \tabularnewline
118 & 0.0064565 & 0.012913 & 0.993543 \tabularnewline
119 & 0.00502631 & 0.0100526 & 0.994974 \tabularnewline
120 & 0.00423703 & 0.00847406 & 0.995763 \tabularnewline
121 & 0.00405227 & 0.00810455 & 0.995948 \tabularnewline
122 & 0.00409584 & 0.00819168 & 0.995904 \tabularnewline
123 & 0.00483186 & 0.00966371 & 0.995168 \tabularnewline
124 & 0.00544179 & 0.0108836 & 0.994558 \tabularnewline
125 & 0.00995899 & 0.019918 & 0.990041 \tabularnewline
126 & 0.00836521 & 0.0167304 & 0.991635 \tabularnewline
127 & 0.00708222 & 0.0141644 & 0.992918 \tabularnewline
128 & 0.00789456 & 0.0157891 & 0.992105 \tabularnewline
129 & 0.007719 & 0.015438 & 0.992281 \tabularnewline
130 & 0.00755643 & 0.0151129 & 0.992444 \tabularnewline
131 & 0.00954382 & 0.0190876 & 0.990456 \tabularnewline
132 & 0.0186565 & 0.0373131 & 0.981343 \tabularnewline
133 & 0.0181164 & 0.0362327 & 0.981884 \tabularnewline
134 & 0.0169187 & 0.0338373 & 0.983081 \tabularnewline
135 & 0.0146005 & 0.0292011 & 0.985399 \tabularnewline
136 & 0.0119629 & 0.0239257 & 0.988037 \tabularnewline
137 & 0.00956803 & 0.0191361 & 0.990432 \tabularnewline
138 & 0.00854086 & 0.0170817 & 0.991459 \tabularnewline
139 & 0.00773682 & 0.0154736 & 0.992263 \tabularnewline
140 & 0.0062815 & 0.012563 & 0.993719 \tabularnewline
141 & 0.0118902 & 0.0237805 & 0.98811 \tabularnewline
142 & 0.0138116 & 0.0276232 & 0.986188 \tabularnewline
143 & 0.0183028 & 0.0366057 & 0.981697 \tabularnewline
144 & 0.0146949 & 0.0293899 & 0.985305 \tabularnewline
145 & 0.011696 & 0.023392 & 0.988304 \tabularnewline
146 & 0.00947292 & 0.0189458 & 0.990527 \tabularnewline
147 & 0.0104205 & 0.0208411 & 0.989579 \tabularnewline
148 & 0.00841316 & 0.0168263 & 0.991587 \tabularnewline
149 & 0.0071537 & 0.0143074 & 0.992846 \tabularnewline
150 & 0.00654528 & 0.0130906 & 0.993455 \tabularnewline
151 & 0.00695443 & 0.0139089 & 0.993046 \tabularnewline
152 & 0.00893538 & 0.0178708 & 0.991065 \tabularnewline
153 & 0.0562613 & 0.112523 & 0.943739 \tabularnewline
154 & 0.0641578 & 0.128316 & 0.935842 \tabularnewline
155 & 0.0541364 & 0.108273 & 0.945864 \tabularnewline
156 & 0.0776264 & 0.155253 & 0.922374 \tabularnewline
157 & 0.136417 & 0.272833 & 0.863583 \tabularnewline
158 & 0.140145 & 0.28029 & 0.859855 \tabularnewline
159 & 0.122361 & 0.244722 & 0.877639 \tabularnewline
160 & 0.117532 & 0.235064 & 0.882468 \tabularnewline
161 & 0.118315 & 0.23663 & 0.881685 \tabularnewline
162 & 0.103449 & 0.206898 & 0.896551 \tabularnewline
163 & 0.0929089 & 0.185818 & 0.907091 \tabularnewline
164 & 0.0982587 & 0.196517 & 0.901741 \tabularnewline
165 & 0.0886111 & 0.177222 & 0.911389 \tabularnewline
166 & 0.0757173 & 0.151435 & 0.924283 \tabularnewline
167 & 0.0646953 & 0.129391 & 0.935305 \tabularnewline
168 & 0.105692 & 0.211384 & 0.894308 \tabularnewline
169 & 0.10756 & 0.215121 & 0.89244 \tabularnewline
170 & 0.0931023 & 0.186205 & 0.906898 \tabularnewline
171 & 0.159909 & 0.319819 & 0.840091 \tabularnewline
172 & 0.139472 & 0.278944 & 0.860528 \tabularnewline
173 & 0.122882 & 0.245765 & 0.877118 \tabularnewline
174 & 0.105847 & 0.211694 & 0.894153 \tabularnewline
175 & 0.142828 & 0.285655 & 0.857172 \tabularnewline
176 & 0.123186 & 0.246372 & 0.876814 \tabularnewline
177 & 0.111155 & 0.222309 & 0.888845 \tabularnewline
178 & 0.0951633 & 0.190327 & 0.904837 \tabularnewline
179 & 0.0807465 & 0.161493 & 0.919254 \tabularnewline
180 & 0.0678164 & 0.135633 & 0.932184 \tabularnewline
181 & 0.0572187 & 0.114437 & 0.942781 \tabularnewline
182 & 0.0655358 & 0.131072 & 0.934464 \tabularnewline
183 & 0.0671631 & 0.134326 & 0.932837 \tabularnewline
184 & 0.0617693 & 0.123539 & 0.938231 \tabularnewline
185 & 0.235618 & 0.471237 & 0.764382 \tabularnewline
186 & 0.214811 & 0.429621 & 0.785189 \tabularnewline
187 & 0.193182 & 0.386365 & 0.806818 \tabularnewline
188 & 0.197256 & 0.394512 & 0.802744 \tabularnewline
189 & 0.182998 & 0.365996 & 0.817002 \tabularnewline
190 & 0.263453 & 0.526906 & 0.736547 \tabularnewline
191 & 0.25247 & 0.504939 & 0.74753 \tabularnewline
192 & 0.222157 & 0.444314 & 0.777843 \tabularnewline
193 & 0.590104 & 0.819791 & 0.409896 \tabularnewline
194 & 0.552637 & 0.894726 & 0.447363 \tabularnewline
195 & 0.515699 & 0.968602 & 0.484301 \tabularnewline
196 & 0.487035 & 0.97407 & 0.512965 \tabularnewline
197 & 0.511029 & 0.977941 & 0.488971 \tabularnewline
198 & 0.473988 & 0.947976 & 0.526012 \tabularnewline
199 & 0.449314 & 0.898627 & 0.550686 \tabularnewline
200 & 0.43838 & 0.876761 & 0.56162 \tabularnewline
201 & 0.418443 & 0.836887 & 0.581557 \tabularnewline
202 & 0.394083 & 0.788167 & 0.605917 \tabularnewline
203 & 0.357546 & 0.715093 & 0.642454 \tabularnewline
204 & 0.42986 & 0.85972 & 0.57014 \tabularnewline
205 & 0.467482 & 0.934965 & 0.532518 \tabularnewline
206 & 0.42505 & 0.850101 & 0.57495 \tabularnewline
207 & 0.383874 & 0.767748 & 0.616126 \tabularnewline
208 & 0.346418 & 0.692836 & 0.653582 \tabularnewline
209 & 0.329167 & 0.658333 & 0.670833 \tabularnewline
210 & 0.294054 & 0.588109 & 0.705946 \tabularnewline
211 & 0.367832 & 0.735664 & 0.632168 \tabularnewline
212 & 0.392079 & 0.784159 & 0.607921 \tabularnewline
213 & 0.350445 & 0.700889 & 0.649555 \tabularnewline
214 & 0.370095 & 0.740191 & 0.629905 \tabularnewline
215 & 0.333511 & 0.667022 & 0.666489 \tabularnewline
216 & 0.297787 & 0.595573 & 0.702213 \tabularnewline
217 & 0.262538 & 0.525076 & 0.737462 \tabularnewline
218 & 0.225765 & 0.451529 & 0.774235 \tabularnewline
219 & 0.227121 & 0.454243 & 0.772879 \tabularnewline
220 & 0.204751 & 0.409503 & 0.795249 \tabularnewline
221 & 0.245075 & 0.490151 & 0.754925 \tabularnewline
222 & 0.207323 & 0.414646 & 0.792677 \tabularnewline
223 & 0.197863 & 0.395726 & 0.802137 \tabularnewline
224 & 0.172612 & 0.345224 & 0.827388 \tabularnewline
225 & 0.148257 & 0.296515 & 0.851743 \tabularnewline
226 & 0.122388 & 0.244776 & 0.877612 \tabularnewline
227 & 0.0996178 & 0.199236 & 0.900382 \tabularnewline
228 & 0.0812018 & 0.162404 & 0.918798 \tabularnewline
229 & 0.0628779 & 0.125756 & 0.937122 \tabularnewline
230 & 0.0484771 & 0.0969542 & 0.951523 \tabularnewline
231 & 0.0735987 & 0.147197 & 0.926401 \tabularnewline
232 & 0.0912323 & 0.182465 & 0.908768 \tabularnewline
233 & 0.317088 & 0.634176 & 0.682912 \tabularnewline
234 & 0.284796 & 0.569592 & 0.715204 \tabularnewline
235 & 0.235955 & 0.471911 & 0.764045 \tabularnewline
236 & 0.233273 & 0.466546 & 0.766727 \tabularnewline
237 & 0.279624 & 0.559249 & 0.720376 \tabularnewline
238 & 0.299245 & 0.598491 & 0.700755 \tabularnewline
239 & 0.292457 & 0.584913 & 0.707543 \tabularnewline
240 & 0.244282 & 0.488565 & 0.755718 \tabularnewline
241 & 0.203003 & 0.406006 & 0.796997 \tabularnewline
242 & 0.25088 & 0.50176 & 0.74912 \tabularnewline
243 & 0.546701 & 0.906598 & 0.453299 \tabularnewline
244 & 0.702276 & 0.595448 & 0.297724 \tabularnewline
245 & 0.623954 & 0.752092 & 0.376046 \tabularnewline
246 & 0.566852 & 0.866297 & 0.433148 \tabularnewline
247 & 0.519139 & 0.961721 & 0.480861 \tabularnewline
248 & 0.460639 & 0.921278 & 0.539361 \tabularnewline
249 & 0.364403 & 0.728806 & 0.635597 \tabularnewline
250 & 0.336297 & 0.672595 & 0.663703 \tabularnewline
251 & 0.473977 & 0.947955 & 0.526023 \tabularnewline
252 & 0.68835 & 0.6233 & 0.31165 \tabularnewline
253 & 0.681808 & 0.636384 & 0.318192 \tabularnewline
254 & 0.709764 & 0.580473 & 0.290236 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226588&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]10[/C][C]0.991269[/C][C]0.0174624[/C][C]0.00873122[/C][/ROW]
[ROW][C]11[/C][C]0.981526[/C][C]0.0369489[/C][C]0.0184744[/C][/ROW]
[ROW][C]12[/C][C]0.979297[/C][C]0.0414062[/C][C]0.0207031[/C][/ROW]
[ROW][C]13[/C][C]0.966132[/C][C]0.0677358[/C][C]0.0338679[/C][/ROW]
[ROW][C]14[/C][C]0.958347[/C][C]0.0833053[/C][C]0.0416526[/C][/ROW]
[ROW][C]15[/C][C]0.940789[/C][C]0.118422[/C][C]0.059211[/C][/ROW]
[ROW][C]16[/C][C]0.92347[/C][C]0.153059[/C][C]0.0765297[/C][/ROW]
[ROW][C]17[/C][C]0.888366[/C][C]0.223268[/C][C]0.111634[/C][/ROW]
[ROW][C]18[/C][C]0.899312[/C][C]0.201376[/C][C]0.100688[/C][/ROW]
[ROW][C]19[/C][C]0.872954[/C][C]0.254092[/C][C]0.127046[/C][/ROW]
[ROW][C]20[/C][C]0.827681[/C][C]0.344637[/C][C]0.172319[/C][/ROW]
[ROW][C]21[/C][C]0.785956[/C][C]0.428088[/C][C]0.214044[/C][/ROW]
[ROW][C]22[/C][C]0.74213[/C][C]0.515739[/C][C]0.25787[/C][/ROW]
[ROW][C]23[/C][C]0.684093[/C][C]0.631814[/C][C]0.315907[/C][/ROW]
[ROW][C]24[/C][C]0.638523[/C][C]0.722954[/C][C]0.361477[/C][/ROW]
[ROW][C]25[/C][C]0.586738[/C][C]0.826525[/C][C]0.413262[/C][/ROW]
[ROW][C]26[/C][C]0.619905[/C][C]0.760191[/C][C]0.380095[/C][/ROW]
[ROW][C]27[/C][C]0.607288[/C][C]0.785424[/C][C]0.392712[/C][/ROW]
[ROW][C]28[/C][C]0.620854[/C][C]0.758293[/C][C]0.379146[/C][/ROW]
[ROW][C]29[/C][C]0.558936[/C][C]0.882128[/C][C]0.441064[/C][/ROW]
[ROW][C]30[/C][C]0.510537[/C][C]0.978926[/C][C]0.489463[/C][/ROW]
[ROW][C]31[/C][C]0.460772[/C][C]0.921545[/C][C]0.539228[/C][/ROW]
[ROW][C]32[/C][C]0.479858[/C][C]0.959715[/C][C]0.520142[/C][/ROW]
[ROW][C]33[/C][C]0.420566[/C][C]0.841131[/C][C]0.579434[/C][/ROW]
[ROW][C]34[/C][C]0.366498[/C][C]0.732995[/C][C]0.633502[/C][/ROW]
[ROW][C]35[/C][C]0.354385[/C][C]0.708769[/C][C]0.645615[/C][/ROW]
[ROW][C]36[/C][C]0.350905[/C][C]0.70181[/C][C]0.649095[/C][/ROW]
[ROW][C]37[/C][C]0.301878[/C][C]0.603756[/C][C]0.698122[/C][/ROW]
[ROW][C]38[/C][C]0.287635[/C][C]0.57527[/C][C]0.712365[/C][/ROW]
[ROW][C]39[/C][C]0.267897[/C][C]0.535793[/C][C]0.732103[/C][/ROW]
[ROW][C]40[/C][C]0.243567[/C][C]0.487133[/C][C]0.756433[/C][/ROW]
[ROW][C]41[/C][C]0.216404[/C][C]0.432808[/C][C]0.783596[/C][/ROW]
[ROW][C]42[/C][C]0.194572[/C][C]0.389144[/C][C]0.805428[/C][/ROW]
[ROW][C]43[/C][C]0.241203[/C][C]0.482406[/C][C]0.758797[/C][/ROW]
[ROW][C]44[/C][C]0.203264[/C][C]0.406529[/C][C]0.796736[/C][/ROW]
[ROW][C]45[/C][C]0.168906[/C][C]0.337812[/C][C]0.831094[/C][/ROW]
[ROW][C]46[/C][C]0.211501[/C][C]0.423002[/C][C]0.788499[/C][/ROW]
[ROW][C]47[/C][C]0.215765[/C][C]0.431529[/C][C]0.784235[/C][/ROW]
[ROW][C]48[/C][C]0.181414[/C][C]0.362827[/C][C]0.818586[/C][/ROW]
[ROW][C]49[/C][C]0.166605[/C][C]0.333209[/C][C]0.833395[/C][/ROW]
[ROW][C]50[/C][C]0.153933[/C][C]0.307865[/C][C]0.846067[/C][/ROW]
[ROW][C]51[/C][C]0.161574[/C][C]0.323149[/C][C]0.838426[/C][/ROW]
[ROW][C]52[/C][C]0.134349[/C][C]0.268697[/C][C]0.865651[/C][/ROW]
[ROW][C]53[/C][C]0.142191[/C][C]0.284381[/C][C]0.857809[/C][/ROW]
[ROW][C]54[/C][C]0.122175[/C][C]0.24435[/C][C]0.877825[/C][/ROW]
[ROW][C]55[/C][C]0.18888[/C][C]0.37776[/C][C]0.81112[/C][/ROW]
[ROW][C]56[/C][C]0.446406[/C][C]0.892812[/C][C]0.553594[/C][/ROW]
[ROW][C]57[/C][C]0.404573[/C][C]0.809146[/C][C]0.595427[/C][/ROW]
[ROW][C]58[/C][C]0.363286[/C][C]0.726571[/C][C]0.636714[/C][/ROW]
[ROW][C]59[/C][C]0.324077[/C][C]0.648155[/C][C]0.675923[/C][/ROW]
[ROW][C]60[/C][C]0.320786[/C][C]0.641573[/C][C]0.679214[/C][/ROW]
[ROW][C]61[/C][C]0.324999[/C][C]0.649999[/C][C]0.675001[/C][/ROW]
[ROW][C]62[/C][C]0.288134[/C][C]0.576268[/C][C]0.711866[/C][/ROW]
[ROW][C]63[/C][C]0.298688[/C][C]0.597375[/C][C]0.701312[/C][/ROW]
[ROW][C]64[/C][C]0.264278[/C][C]0.528556[/C][C]0.735722[/C][/ROW]
[ROW][C]65[/C][C]0.240571[/C][C]0.481143[/C][C]0.759429[/C][/ROW]
[ROW][C]66[/C][C]0.209703[/C][C]0.419407[/C][C]0.790297[/C][/ROW]
[ROW][C]67[/C][C]0.191907[/C][C]0.383814[/C][C]0.808093[/C][/ROW]
[ROW][C]68[/C][C]0.172138[/C][C]0.344277[/C][C]0.827862[/C][/ROW]
[ROW][C]69[/C][C]0.172005[/C][C]0.34401[/C][C]0.827995[/C][/ROW]
[ROW][C]70[/C][C]0.147249[/C][C]0.294499[/C][C]0.852751[/C][/ROW]
[ROW][C]71[/C][C]0.130318[/C][C]0.260636[/C][C]0.869682[/C][/ROW]
[ROW][C]72[/C][C]0.110687[/C][C]0.221375[/C][C]0.889313[/C][/ROW]
[ROW][C]73[/C][C]0.0944082[/C][C]0.188816[/C][C]0.905592[/C][/ROW]
[ROW][C]74[/C][C]0.0802155[/C][C]0.160431[/C][C]0.919785[/C][/ROW]
[ROW][C]75[/C][C]0.0719349[/C][C]0.14387[/C][C]0.928065[/C][/ROW]
[ROW][C]76[/C][C]0.0919604[/C][C]0.183921[/C][C]0.90804[/C][/ROW]
[ROW][C]77[/C][C]0.0821465[/C][C]0.164293[/C][C]0.917854[/C][/ROW]
[ROW][C]78[/C][C]0.0679874[/C][C]0.135975[/C][C]0.932013[/C][/ROW]
[ROW][C]79[/C][C]0.0726006[/C][C]0.145201[/C][C]0.927399[/C][/ROW]
[ROW][C]80[/C][C]0.0696344[/C][C]0.139269[/C][C]0.930366[/C][/ROW]
[ROW][C]81[/C][C]0.0575844[/C][C]0.115169[/C][C]0.942416[/C][/ROW]
[ROW][C]82[/C][C]0.0474314[/C][C]0.0948627[/C][C]0.952569[/C][/ROW]
[ROW][C]83[/C][C]0.0414342[/C][C]0.0828685[/C][C]0.958566[/C][/ROW]
[ROW][C]84[/C][C]0.0336011[/C][C]0.0672022[/C][C]0.966399[/C][/ROW]
[ROW][C]85[/C][C]0.0308607[/C][C]0.0617214[/C][C]0.969139[/C][/ROW]
[ROW][C]86[/C][C]0.0349724[/C][C]0.0699448[/C][C]0.965028[/C][/ROW]
[ROW][C]87[/C][C]0.0282382[/C][C]0.0564763[/C][C]0.971762[/C][/ROW]
[ROW][C]88[/C][C]0.0229471[/C][C]0.0458942[/C][C]0.977053[/C][/ROW]
[ROW][C]89[/C][C]0.0194554[/C][C]0.0389108[/C][C]0.980545[/C][/ROW]
[ROW][C]90[/C][C]0.0163813[/C][C]0.0327627[/C][C]0.983619[/C][/ROW]
[ROW][C]91[/C][C]0.0274677[/C][C]0.0549355[/C][C]0.972532[/C][/ROW]
[ROW][C]92[/C][C]0.0226313[/C][C]0.0452625[/C][C]0.977369[/C][/ROW]
[ROW][C]93[/C][C]0.0208919[/C][C]0.0417838[/C][C]0.979108[/C][/ROW]
[ROW][C]94[/C][C]0.0228448[/C][C]0.0456895[/C][C]0.977155[/C][/ROW]
[ROW][C]95[/C][C]0.0224703[/C][C]0.0449406[/C][C]0.97753[/C][/ROW]
[ROW][C]96[/C][C]0.0202911[/C][C]0.0405822[/C][C]0.979709[/C][/ROW]
[ROW][C]97[/C][C]0.0247257[/C][C]0.0494514[/C][C]0.975274[/C][/ROW]
[ROW][C]98[/C][C]0.0200502[/C][C]0.0401004[/C][C]0.97995[/C][/ROW]
[ROW][C]99[/C][C]0.0169469[/C][C]0.0338939[/C][C]0.983053[/C][/ROW]
[ROW][C]100[/C][C]0.0202226[/C][C]0.0404452[/C][C]0.979777[/C][/ROW]
[ROW][C]101[/C][C]0.0166964[/C][C]0.0333928[/C][C]0.983304[/C][/ROW]
[ROW][C]102[/C][C]0.0141572[/C][C]0.0283145[/C][C]0.985843[/C][/ROW]
[ROW][C]103[/C][C]0.0111704[/C][C]0.0223407[/C][C]0.98883[/C][/ROW]
[ROW][C]104[/C][C]0.00978899[/C][C]0.019578[/C][C]0.990211[/C][/ROW]
[ROW][C]105[/C][C]0.0111081[/C][C]0.0222161[/C][C]0.988892[/C][/ROW]
[ROW][C]106[/C][C]0.00868106[/C][C]0.0173621[/C][C]0.991319[/C][/ROW]
[ROW][C]107[/C][C]0.00681591[/C][C]0.0136318[/C][C]0.993184[/C][/ROW]
[ROW][C]108[/C][C]0.00556152[/C][C]0.011123[/C][C]0.994438[/C][/ROW]
[ROW][C]109[/C][C]0.00792945[/C][C]0.0158589[/C][C]0.992071[/C][/ROW]
[ROW][C]110[/C][C]0.00617442[/C][C]0.0123488[/C][C]0.993826[/C][/ROW]
[ROW][C]111[/C][C]0.00724033[/C][C]0.0144807[/C][C]0.99276[/C][/ROW]
[ROW][C]112[/C][C]0.00772548[/C][C]0.015451[/C][C]0.992275[/C][/ROW]
[ROW][C]113[/C][C]0.0067833[/C][C]0.0135666[/C][C]0.993217[/C][/ROW]
[ROW][C]114[/C][C]0.00545411[/C][C]0.0109082[/C][C]0.994546[/C][/ROW]
[ROW][C]115[/C][C]0.0042429[/C][C]0.0084858[/C][C]0.995757[/C][/ROW]
[ROW][C]116[/C][C]0.00501898[/C][C]0.010038[/C][C]0.994981[/C][/ROW]
[ROW][C]117[/C][C]0.0077054[/C][C]0.0154108[/C][C]0.992295[/C][/ROW]
[ROW][C]118[/C][C]0.0064565[/C][C]0.012913[/C][C]0.993543[/C][/ROW]
[ROW][C]119[/C][C]0.00502631[/C][C]0.0100526[/C][C]0.994974[/C][/ROW]
[ROW][C]120[/C][C]0.00423703[/C][C]0.00847406[/C][C]0.995763[/C][/ROW]
[ROW][C]121[/C][C]0.00405227[/C][C]0.00810455[/C][C]0.995948[/C][/ROW]
[ROW][C]122[/C][C]0.00409584[/C][C]0.00819168[/C][C]0.995904[/C][/ROW]
[ROW][C]123[/C][C]0.00483186[/C][C]0.00966371[/C][C]0.995168[/C][/ROW]
[ROW][C]124[/C][C]0.00544179[/C][C]0.0108836[/C][C]0.994558[/C][/ROW]
[ROW][C]125[/C][C]0.00995899[/C][C]0.019918[/C][C]0.990041[/C][/ROW]
[ROW][C]126[/C][C]0.00836521[/C][C]0.0167304[/C][C]0.991635[/C][/ROW]
[ROW][C]127[/C][C]0.00708222[/C][C]0.0141644[/C][C]0.992918[/C][/ROW]
[ROW][C]128[/C][C]0.00789456[/C][C]0.0157891[/C][C]0.992105[/C][/ROW]
[ROW][C]129[/C][C]0.007719[/C][C]0.015438[/C][C]0.992281[/C][/ROW]
[ROW][C]130[/C][C]0.00755643[/C][C]0.0151129[/C][C]0.992444[/C][/ROW]
[ROW][C]131[/C][C]0.00954382[/C][C]0.0190876[/C][C]0.990456[/C][/ROW]
[ROW][C]132[/C][C]0.0186565[/C][C]0.0373131[/C][C]0.981343[/C][/ROW]
[ROW][C]133[/C][C]0.0181164[/C][C]0.0362327[/C][C]0.981884[/C][/ROW]
[ROW][C]134[/C][C]0.0169187[/C][C]0.0338373[/C][C]0.983081[/C][/ROW]
[ROW][C]135[/C][C]0.0146005[/C][C]0.0292011[/C][C]0.985399[/C][/ROW]
[ROW][C]136[/C][C]0.0119629[/C][C]0.0239257[/C][C]0.988037[/C][/ROW]
[ROW][C]137[/C][C]0.00956803[/C][C]0.0191361[/C][C]0.990432[/C][/ROW]
[ROW][C]138[/C][C]0.00854086[/C][C]0.0170817[/C][C]0.991459[/C][/ROW]
[ROW][C]139[/C][C]0.00773682[/C][C]0.0154736[/C][C]0.992263[/C][/ROW]
[ROW][C]140[/C][C]0.0062815[/C][C]0.012563[/C][C]0.993719[/C][/ROW]
[ROW][C]141[/C][C]0.0118902[/C][C]0.0237805[/C][C]0.98811[/C][/ROW]
[ROW][C]142[/C][C]0.0138116[/C][C]0.0276232[/C][C]0.986188[/C][/ROW]
[ROW][C]143[/C][C]0.0183028[/C][C]0.0366057[/C][C]0.981697[/C][/ROW]
[ROW][C]144[/C][C]0.0146949[/C][C]0.0293899[/C][C]0.985305[/C][/ROW]
[ROW][C]145[/C][C]0.011696[/C][C]0.023392[/C][C]0.988304[/C][/ROW]
[ROW][C]146[/C][C]0.00947292[/C][C]0.0189458[/C][C]0.990527[/C][/ROW]
[ROW][C]147[/C][C]0.0104205[/C][C]0.0208411[/C][C]0.989579[/C][/ROW]
[ROW][C]148[/C][C]0.00841316[/C][C]0.0168263[/C][C]0.991587[/C][/ROW]
[ROW][C]149[/C][C]0.0071537[/C][C]0.0143074[/C][C]0.992846[/C][/ROW]
[ROW][C]150[/C][C]0.00654528[/C][C]0.0130906[/C][C]0.993455[/C][/ROW]
[ROW][C]151[/C][C]0.00695443[/C][C]0.0139089[/C][C]0.993046[/C][/ROW]
[ROW][C]152[/C][C]0.00893538[/C][C]0.0178708[/C][C]0.991065[/C][/ROW]
[ROW][C]153[/C][C]0.0562613[/C][C]0.112523[/C][C]0.943739[/C][/ROW]
[ROW][C]154[/C][C]0.0641578[/C][C]0.128316[/C][C]0.935842[/C][/ROW]
[ROW][C]155[/C][C]0.0541364[/C][C]0.108273[/C][C]0.945864[/C][/ROW]
[ROW][C]156[/C][C]0.0776264[/C][C]0.155253[/C][C]0.922374[/C][/ROW]
[ROW][C]157[/C][C]0.136417[/C][C]0.272833[/C][C]0.863583[/C][/ROW]
[ROW][C]158[/C][C]0.140145[/C][C]0.28029[/C][C]0.859855[/C][/ROW]
[ROW][C]159[/C][C]0.122361[/C][C]0.244722[/C][C]0.877639[/C][/ROW]
[ROW][C]160[/C][C]0.117532[/C][C]0.235064[/C][C]0.882468[/C][/ROW]
[ROW][C]161[/C][C]0.118315[/C][C]0.23663[/C][C]0.881685[/C][/ROW]
[ROW][C]162[/C][C]0.103449[/C][C]0.206898[/C][C]0.896551[/C][/ROW]
[ROW][C]163[/C][C]0.0929089[/C][C]0.185818[/C][C]0.907091[/C][/ROW]
[ROW][C]164[/C][C]0.0982587[/C][C]0.196517[/C][C]0.901741[/C][/ROW]
[ROW][C]165[/C][C]0.0886111[/C][C]0.177222[/C][C]0.911389[/C][/ROW]
[ROW][C]166[/C][C]0.0757173[/C][C]0.151435[/C][C]0.924283[/C][/ROW]
[ROW][C]167[/C][C]0.0646953[/C][C]0.129391[/C][C]0.935305[/C][/ROW]
[ROW][C]168[/C][C]0.105692[/C][C]0.211384[/C][C]0.894308[/C][/ROW]
[ROW][C]169[/C][C]0.10756[/C][C]0.215121[/C][C]0.89244[/C][/ROW]
[ROW][C]170[/C][C]0.0931023[/C][C]0.186205[/C][C]0.906898[/C][/ROW]
[ROW][C]171[/C][C]0.159909[/C][C]0.319819[/C][C]0.840091[/C][/ROW]
[ROW][C]172[/C][C]0.139472[/C][C]0.278944[/C][C]0.860528[/C][/ROW]
[ROW][C]173[/C][C]0.122882[/C][C]0.245765[/C][C]0.877118[/C][/ROW]
[ROW][C]174[/C][C]0.105847[/C][C]0.211694[/C][C]0.894153[/C][/ROW]
[ROW][C]175[/C][C]0.142828[/C][C]0.285655[/C][C]0.857172[/C][/ROW]
[ROW][C]176[/C][C]0.123186[/C][C]0.246372[/C][C]0.876814[/C][/ROW]
[ROW][C]177[/C][C]0.111155[/C][C]0.222309[/C][C]0.888845[/C][/ROW]
[ROW][C]178[/C][C]0.0951633[/C][C]0.190327[/C][C]0.904837[/C][/ROW]
[ROW][C]179[/C][C]0.0807465[/C][C]0.161493[/C][C]0.919254[/C][/ROW]
[ROW][C]180[/C][C]0.0678164[/C][C]0.135633[/C][C]0.932184[/C][/ROW]
[ROW][C]181[/C][C]0.0572187[/C][C]0.114437[/C][C]0.942781[/C][/ROW]
[ROW][C]182[/C][C]0.0655358[/C][C]0.131072[/C][C]0.934464[/C][/ROW]
[ROW][C]183[/C][C]0.0671631[/C][C]0.134326[/C][C]0.932837[/C][/ROW]
[ROW][C]184[/C][C]0.0617693[/C][C]0.123539[/C][C]0.938231[/C][/ROW]
[ROW][C]185[/C][C]0.235618[/C][C]0.471237[/C][C]0.764382[/C][/ROW]
[ROW][C]186[/C][C]0.214811[/C][C]0.429621[/C][C]0.785189[/C][/ROW]
[ROW][C]187[/C][C]0.193182[/C][C]0.386365[/C][C]0.806818[/C][/ROW]
[ROW][C]188[/C][C]0.197256[/C][C]0.394512[/C][C]0.802744[/C][/ROW]
[ROW][C]189[/C][C]0.182998[/C][C]0.365996[/C][C]0.817002[/C][/ROW]
[ROW][C]190[/C][C]0.263453[/C][C]0.526906[/C][C]0.736547[/C][/ROW]
[ROW][C]191[/C][C]0.25247[/C][C]0.504939[/C][C]0.74753[/C][/ROW]
[ROW][C]192[/C][C]0.222157[/C][C]0.444314[/C][C]0.777843[/C][/ROW]
[ROW][C]193[/C][C]0.590104[/C][C]0.819791[/C][C]0.409896[/C][/ROW]
[ROW][C]194[/C][C]0.552637[/C][C]0.894726[/C][C]0.447363[/C][/ROW]
[ROW][C]195[/C][C]0.515699[/C][C]0.968602[/C][C]0.484301[/C][/ROW]
[ROW][C]196[/C][C]0.487035[/C][C]0.97407[/C][C]0.512965[/C][/ROW]
[ROW][C]197[/C][C]0.511029[/C][C]0.977941[/C][C]0.488971[/C][/ROW]
[ROW][C]198[/C][C]0.473988[/C][C]0.947976[/C][C]0.526012[/C][/ROW]
[ROW][C]199[/C][C]0.449314[/C][C]0.898627[/C][C]0.550686[/C][/ROW]
[ROW][C]200[/C][C]0.43838[/C][C]0.876761[/C][C]0.56162[/C][/ROW]
[ROW][C]201[/C][C]0.418443[/C][C]0.836887[/C][C]0.581557[/C][/ROW]
[ROW][C]202[/C][C]0.394083[/C][C]0.788167[/C][C]0.605917[/C][/ROW]
[ROW][C]203[/C][C]0.357546[/C][C]0.715093[/C][C]0.642454[/C][/ROW]
[ROW][C]204[/C][C]0.42986[/C][C]0.85972[/C][C]0.57014[/C][/ROW]
[ROW][C]205[/C][C]0.467482[/C][C]0.934965[/C][C]0.532518[/C][/ROW]
[ROW][C]206[/C][C]0.42505[/C][C]0.850101[/C][C]0.57495[/C][/ROW]
[ROW][C]207[/C][C]0.383874[/C][C]0.767748[/C][C]0.616126[/C][/ROW]
[ROW][C]208[/C][C]0.346418[/C][C]0.692836[/C][C]0.653582[/C][/ROW]
[ROW][C]209[/C][C]0.329167[/C][C]0.658333[/C][C]0.670833[/C][/ROW]
[ROW][C]210[/C][C]0.294054[/C][C]0.588109[/C][C]0.705946[/C][/ROW]
[ROW][C]211[/C][C]0.367832[/C][C]0.735664[/C][C]0.632168[/C][/ROW]
[ROW][C]212[/C][C]0.392079[/C][C]0.784159[/C][C]0.607921[/C][/ROW]
[ROW][C]213[/C][C]0.350445[/C][C]0.700889[/C][C]0.649555[/C][/ROW]
[ROW][C]214[/C][C]0.370095[/C][C]0.740191[/C][C]0.629905[/C][/ROW]
[ROW][C]215[/C][C]0.333511[/C][C]0.667022[/C][C]0.666489[/C][/ROW]
[ROW][C]216[/C][C]0.297787[/C][C]0.595573[/C][C]0.702213[/C][/ROW]
[ROW][C]217[/C][C]0.262538[/C][C]0.525076[/C][C]0.737462[/C][/ROW]
[ROW][C]218[/C][C]0.225765[/C][C]0.451529[/C][C]0.774235[/C][/ROW]
[ROW][C]219[/C][C]0.227121[/C][C]0.454243[/C][C]0.772879[/C][/ROW]
[ROW][C]220[/C][C]0.204751[/C][C]0.409503[/C][C]0.795249[/C][/ROW]
[ROW][C]221[/C][C]0.245075[/C][C]0.490151[/C][C]0.754925[/C][/ROW]
[ROW][C]222[/C][C]0.207323[/C][C]0.414646[/C][C]0.792677[/C][/ROW]
[ROW][C]223[/C][C]0.197863[/C][C]0.395726[/C][C]0.802137[/C][/ROW]
[ROW][C]224[/C][C]0.172612[/C][C]0.345224[/C][C]0.827388[/C][/ROW]
[ROW][C]225[/C][C]0.148257[/C][C]0.296515[/C][C]0.851743[/C][/ROW]
[ROW][C]226[/C][C]0.122388[/C][C]0.244776[/C][C]0.877612[/C][/ROW]
[ROW][C]227[/C][C]0.0996178[/C][C]0.199236[/C][C]0.900382[/C][/ROW]
[ROW][C]228[/C][C]0.0812018[/C][C]0.162404[/C][C]0.918798[/C][/ROW]
[ROW][C]229[/C][C]0.0628779[/C][C]0.125756[/C][C]0.937122[/C][/ROW]
[ROW][C]230[/C][C]0.0484771[/C][C]0.0969542[/C][C]0.951523[/C][/ROW]
[ROW][C]231[/C][C]0.0735987[/C][C]0.147197[/C][C]0.926401[/C][/ROW]
[ROW][C]232[/C][C]0.0912323[/C][C]0.182465[/C][C]0.908768[/C][/ROW]
[ROW][C]233[/C][C]0.317088[/C][C]0.634176[/C][C]0.682912[/C][/ROW]
[ROW][C]234[/C][C]0.284796[/C][C]0.569592[/C][C]0.715204[/C][/ROW]
[ROW][C]235[/C][C]0.235955[/C][C]0.471911[/C][C]0.764045[/C][/ROW]
[ROW][C]236[/C][C]0.233273[/C][C]0.466546[/C][C]0.766727[/C][/ROW]
[ROW][C]237[/C][C]0.279624[/C][C]0.559249[/C][C]0.720376[/C][/ROW]
[ROW][C]238[/C][C]0.299245[/C][C]0.598491[/C][C]0.700755[/C][/ROW]
[ROW][C]239[/C][C]0.292457[/C][C]0.584913[/C][C]0.707543[/C][/ROW]
[ROW][C]240[/C][C]0.244282[/C][C]0.488565[/C][C]0.755718[/C][/ROW]
[ROW][C]241[/C][C]0.203003[/C][C]0.406006[/C][C]0.796997[/C][/ROW]
[ROW][C]242[/C][C]0.25088[/C][C]0.50176[/C][C]0.74912[/C][/ROW]
[ROW][C]243[/C][C]0.546701[/C][C]0.906598[/C][C]0.453299[/C][/ROW]
[ROW][C]244[/C][C]0.702276[/C][C]0.595448[/C][C]0.297724[/C][/ROW]
[ROW][C]245[/C][C]0.623954[/C][C]0.752092[/C][C]0.376046[/C][/ROW]
[ROW][C]246[/C][C]0.566852[/C][C]0.866297[/C][C]0.433148[/C][/ROW]
[ROW][C]247[/C][C]0.519139[/C][C]0.961721[/C][C]0.480861[/C][/ROW]
[ROW][C]248[/C][C]0.460639[/C][C]0.921278[/C][C]0.539361[/C][/ROW]
[ROW][C]249[/C][C]0.364403[/C][C]0.728806[/C][C]0.635597[/C][/ROW]
[ROW][C]250[/C][C]0.336297[/C][C]0.672595[/C][C]0.663703[/C][/ROW]
[ROW][C]251[/C][C]0.473977[/C][C]0.947955[/C][C]0.526023[/C][/ROW]
[ROW][C]252[/C][C]0.68835[/C][C]0.6233[/C][C]0.31165[/C][/ROW]
[ROW][C]253[/C][C]0.681808[/C][C]0.636384[/C][C]0.318192[/C][/ROW]
[ROW][C]254[/C][C]0.709764[/C][C]0.580473[/C][C]0.290236[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226588&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226588&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
100.9912690.01746240.00873122
110.9815260.03694890.0184744
120.9792970.04140620.0207031
130.9661320.06773580.0338679
140.9583470.08330530.0416526
150.9407890.1184220.059211
160.923470.1530590.0765297
170.8883660.2232680.111634
180.8993120.2013760.100688
190.8729540.2540920.127046
200.8276810.3446370.172319
210.7859560.4280880.214044
220.742130.5157390.25787
230.6840930.6318140.315907
240.6385230.7229540.361477
250.5867380.8265250.413262
260.6199050.7601910.380095
270.6072880.7854240.392712
280.6208540.7582930.379146
290.5589360.8821280.441064
300.5105370.9789260.489463
310.4607720.9215450.539228
320.4798580.9597150.520142
330.4205660.8411310.579434
340.3664980.7329950.633502
350.3543850.7087690.645615
360.3509050.701810.649095
370.3018780.6037560.698122
380.2876350.575270.712365
390.2678970.5357930.732103
400.2435670.4871330.756433
410.2164040.4328080.783596
420.1945720.3891440.805428
430.2412030.4824060.758797
440.2032640.4065290.796736
450.1689060.3378120.831094
460.2115010.4230020.788499
470.2157650.4315290.784235
480.1814140.3628270.818586
490.1666050.3332090.833395
500.1539330.3078650.846067
510.1615740.3231490.838426
520.1343490.2686970.865651
530.1421910.2843810.857809
540.1221750.244350.877825
550.188880.377760.81112
560.4464060.8928120.553594
570.4045730.8091460.595427
580.3632860.7265710.636714
590.3240770.6481550.675923
600.3207860.6415730.679214
610.3249990.6499990.675001
620.2881340.5762680.711866
630.2986880.5973750.701312
640.2642780.5285560.735722
650.2405710.4811430.759429
660.2097030.4194070.790297
670.1919070.3838140.808093
680.1721380.3442770.827862
690.1720050.344010.827995
700.1472490.2944990.852751
710.1303180.2606360.869682
720.1106870.2213750.889313
730.09440820.1888160.905592
740.08021550.1604310.919785
750.07193490.143870.928065
760.09196040.1839210.90804
770.08214650.1642930.917854
780.06798740.1359750.932013
790.07260060.1452010.927399
800.06963440.1392690.930366
810.05758440.1151690.942416
820.04743140.09486270.952569
830.04143420.08286850.958566
840.03360110.06720220.966399
850.03086070.06172140.969139
860.03497240.06994480.965028
870.02823820.05647630.971762
880.02294710.04589420.977053
890.01945540.03891080.980545
900.01638130.03276270.983619
910.02746770.05493550.972532
920.02263130.04526250.977369
930.02089190.04178380.979108
940.02284480.04568950.977155
950.02247030.04494060.97753
960.02029110.04058220.979709
970.02472570.04945140.975274
980.02005020.04010040.97995
990.01694690.03389390.983053
1000.02022260.04044520.979777
1010.01669640.03339280.983304
1020.01415720.02831450.985843
1030.01117040.02234070.98883
1040.009788990.0195780.990211
1050.01110810.02221610.988892
1060.008681060.01736210.991319
1070.006815910.01363180.993184
1080.005561520.0111230.994438
1090.007929450.01585890.992071
1100.006174420.01234880.993826
1110.007240330.01448070.99276
1120.007725480.0154510.992275
1130.00678330.01356660.993217
1140.005454110.01090820.994546
1150.00424290.00848580.995757
1160.005018980.0100380.994981
1170.00770540.01541080.992295
1180.00645650.0129130.993543
1190.005026310.01005260.994974
1200.004237030.008474060.995763
1210.004052270.008104550.995948
1220.004095840.008191680.995904
1230.004831860.009663710.995168
1240.005441790.01088360.994558
1250.009958990.0199180.990041
1260.008365210.01673040.991635
1270.007082220.01416440.992918
1280.007894560.01578910.992105
1290.0077190.0154380.992281
1300.007556430.01511290.992444
1310.009543820.01908760.990456
1320.01865650.03731310.981343
1330.01811640.03623270.981884
1340.01691870.03383730.983081
1350.01460050.02920110.985399
1360.01196290.02392570.988037
1370.009568030.01913610.990432
1380.008540860.01708170.991459
1390.007736820.01547360.992263
1400.00628150.0125630.993719
1410.01189020.02378050.98811
1420.01381160.02762320.986188
1430.01830280.03660570.981697
1440.01469490.02938990.985305
1450.0116960.0233920.988304
1460.009472920.01894580.990527
1470.01042050.02084110.989579
1480.008413160.01682630.991587
1490.00715370.01430740.992846
1500.006545280.01309060.993455
1510.006954430.01390890.993046
1520.008935380.01787080.991065
1530.05626130.1125230.943739
1540.06415780.1283160.935842
1550.05413640.1082730.945864
1560.07762640.1552530.922374
1570.1364170.2728330.863583
1580.1401450.280290.859855
1590.1223610.2447220.877639
1600.1175320.2350640.882468
1610.1183150.236630.881685
1620.1034490.2068980.896551
1630.09290890.1858180.907091
1640.09825870.1965170.901741
1650.08861110.1772220.911389
1660.07571730.1514350.924283
1670.06469530.1293910.935305
1680.1056920.2113840.894308
1690.107560.2151210.89244
1700.09310230.1862050.906898
1710.1599090.3198190.840091
1720.1394720.2789440.860528
1730.1228820.2457650.877118
1740.1058470.2116940.894153
1750.1428280.2856550.857172
1760.1231860.2463720.876814
1770.1111550.2223090.888845
1780.09516330.1903270.904837
1790.08074650.1614930.919254
1800.06781640.1356330.932184
1810.05721870.1144370.942781
1820.06553580.1310720.934464
1830.06716310.1343260.932837
1840.06176930.1235390.938231
1850.2356180.4712370.764382
1860.2148110.4296210.785189
1870.1931820.3863650.806818
1880.1972560.3945120.802744
1890.1829980.3659960.817002
1900.2634530.5269060.736547
1910.252470.5049390.74753
1920.2221570.4443140.777843
1930.5901040.8197910.409896
1940.5526370.8947260.447363
1950.5156990.9686020.484301
1960.4870350.974070.512965
1970.5110290.9779410.488971
1980.4739880.9479760.526012
1990.4493140.8986270.550686
2000.438380.8767610.56162
2010.4184430.8368870.581557
2020.3940830.7881670.605917
2030.3575460.7150930.642454
2040.429860.859720.57014
2050.4674820.9349650.532518
2060.425050.8501010.57495
2070.3838740.7677480.616126
2080.3464180.6928360.653582
2090.3291670.6583330.670833
2100.2940540.5881090.705946
2110.3678320.7356640.632168
2120.3920790.7841590.607921
2130.3504450.7008890.649555
2140.3700950.7401910.629905
2150.3335110.6670220.666489
2160.2977870.5955730.702213
2170.2625380.5250760.737462
2180.2257650.4515290.774235
2190.2271210.4542430.772879
2200.2047510.4095030.795249
2210.2450750.4901510.754925
2220.2073230.4146460.792677
2230.1978630.3957260.802137
2240.1726120.3452240.827388
2250.1482570.2965150.851743
2260.1223880.2447760.877612
2270.09961780.1992360.900382
2280.08120180.1624040.918798
2290.06287790.1257560.937122
2300.04847710.09695420.951523
2310.07359870.1471970.926401
2320.09123230.1824650.908768
2330.3170880.6341760.682912
2340.2847960.5695920.715204
2350.2359550.4719110.764045
2360.2332730.4665460.766727
2370.2796240.5592490.720376
2380.2992450.5984910.700755
2390.2924570.5849130.707543
2400.2442820.4885650.755718
2410.2030030.4060060.796997
2420.250880.501760.74912
2430.5467010.9065980.453299
2440.7022760.5954480.297724
2450.6239540.7520920.376046
2460.5668520.8662970.433148
2470.5191390.9617210.480861
2480.4606390.9212780.539361
2490.3644030.7288060.635597
2500.3362970.6725950.663703
2510.4739770.9479550.526023
2520.688350.62330.31165
2530.6818080.6363840.318192
2540.7097640.5804730.290236






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level50.0204082NOK
5% type I error level670.273469NOK
10% type I error level770.314286NOK

\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 & 0.0204082 & NOK \tabularnewline
5% type I error level & 67 & 0.273469 & NOK \tabularnewline
10% type I error level & 77 & 0.314286 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226588&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]0.0204082[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]67[/C][C]0.273469[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]77[/C][C]0.314286[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226588&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226588&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 level50.0204082NOK
5% type I error level670.273469NOK
10% type I error level770.314286NOK


Figures (Output of Computation)

Figure 1
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 2
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 3
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 4
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 5
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 6
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 7
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 8
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 9
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 10
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}