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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 10 Nov 2014 14:32:18 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/10/t1415630078wb19uo0mknjfiv4.htm/, Retrieved Sun, 12 May 2024 06:00:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=253350, Retrieved Sun, 12 May 2024 06:00:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact106

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2013-11-04 07:18:26] [0307e7a6407eb638caabc417e3a6b260]
- RMPD    [Multiple Regression] [WS7 (learning)] [2014-11-10 14:32:18] [21b927ddce509724d48ffb8407994bd0] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'George Udny Yule' @ yule.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 & 9 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253350&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253350&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253350&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 time9 seconds
R Server'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 3.87617 + 0.0459126Connected[t] + 0.0418904Separate[t] + 0.608044Software[t] + 0.0981425Happiness[t] -0.0409809Depression[t] + 0.00351895Sport1[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  3.87617 +  0.0459126Connected[t] +  0.0418904Separate[t] +  0.608044Software[t] +  0.0981425Happiness[t] -0.0409809Depression[t] +  0.00351895Sport1[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253350&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  3.87617 +  0.0459126Connected[t] +  0.0418904Separate[t] +  0.608044Software[t] +  0.0981425Happiness[t] -0.0409809Depression[t] +  0.00351895Sport1[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253350&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253350&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 3.87617 + 0.0459126Connected[t] + 0.0418904Separate[t] + 0.608044Software[t] + 0.0981425Happiness[t] -0.0409809Depression[t] + 0.00351895Sport1[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)3.876171.893722.0470.04168930.0208446
Connected0.04591260.03459841.3270.1856810.0928405
Separate0.04189040.03558591.1770.240220.12011
Software0.6080440.051722911.768.07639e-264.03819e-26
Happiness0.09814250.0578461.6970.09097960.0454898
Depression-0.04098090.042229-0.97040.3327380.166369
Sport10.003518950.0119630.29420.7688780.384439

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 3.87617 & 1.89372 & 2.047 & 0.0416893 & 0.0208446 \tabularnewline
Connected & 0.0459126 & 0.0345984 & 1.327 & 0.185681 & 0.0928405 \tabularnewline
Separate & 0.0418904 & 0.0355859 & 1.177 & 0.24022 & 0.12011 \tabularnewline
Software & 0.608044 & 0.0517229 & 11.76 & 8.07639e-26 & 4.03819e-26 \tabularnewline
Happiness & 0.0981425 & 0.057846 & 1.697 & 0.0909796 & 0.0454898 \tabularnewline
Depression & -0.0409809 & 0.042229 & -0.9704 & 0.332738 & 0.166369 \tabularnewline
Sport1 & 0.00351895 & 0.011963 & 0.2942 & 0.768878 & 0.384439 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253350&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]3.87617[/C][C]1.89372[/C][C]2.047[/C][C]0.0416893[/C][C]0.0208446[/C][/ROW]
[ROW][C]Connected[/C][C]0.0459126[/C][C]0.0345984[/C][C]1.327[/C][C]0.185681[/C][C]0.0928405[/C][/ROW]
[ROW][C]Separate[/C][C]0.0418904[/C][C]0.0355859[/C][C]1.177[/C][C]0.24022[/C][C]0.12011[/C][/ROW]
[ROW][C]Software[/C][C]0.608044[/C][C]0.0517229[/C][C]11.76[/C][C]8.07639e-26[/C][C]4.03819e-26[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0981425[/C][C]0.057846[/C][C]1.697[/C][C]0.0909796[/C][C]0.0454898[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0409809[/C][C]0.042229[/C][C]-0.9704[/C][C]0.332738[/C][C]0.166369[/C][/ROW]
[ROW][C]Sport1[/C][C]0.00351895[/C][C]0.011963[/C][C]0.2942[/C][C]0.768878[/C][C]0.384439[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253350&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253350&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)3.876171.893722.0470.04168930.0208446
Connected0.04591260.03459841.3270.1856810.0928405
Separate0.04189040.03558591.1770.240220.12011
Software0.6080440.051722911.768.07639e-264.03819e-26
Happiness0.09814250.0578461.6970.09097960.0454898
Depression-0.04098090.042229-0.97040.3327380.166369
Sport10.003518950.0119630.29420.7688780.384439






Multiple Linear Regression - Regression Statistics
Multiple R0.653192
R-squared0.426659
Adjusted R-squared0.413274
F-TEST (value)31.875
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.88123
Sum Squared Residuals909.527

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.653192 \tabularnewline
R-squared & 0.426659 \tabularnewline
Adjusted R-squared & 0.413274 \tabularnewline
F-TEST (value) & 31.875 \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 & 1.88123 \tabularnewline
Sum Squared Residuals & 909.527 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253350&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.653192[/C][/ROW]
[ROW][C]R-squared[/C][C]0.426659[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.413274[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]31.875[/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]1.88123[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]909.527[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253350&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253350&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 R0.653192
R-squared0.426659
Adjusted R-squared0.413274
F-TEST (value)31.875
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.88123
Sum Squared Residuals909.527






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.7157-2.71568
21615.30360.69641
31916.57852.42154
41511.25183.74818
51415.8688-1.86884
61314.3276-1.32765
71914.92084.07918
81516.6626-1.66259
91415.6145-1.61445
101513.8461.154
111614.53651.46349
121615.97670.0232872
131614.9861.01397
141615.13370.866345
151717.7248-0.7248
161515.0286-0.0286499
171514.01410.985856
182016.03653.96348
191815.13652.86352
201615.22050.779494
211615.02570.974259
221614.63971.36028
231916.23542.76458
241614.69821.30181
251715.8241.17595
261715.79961.20037
271614.46261.53744
281516.4559-1.45594
291615.24310.756916
301413.68260.317389
311515.3776-0.377563
321212.1718-0.171821
331414.4624-0.462441
341615.60060.399385
351415.0921-1.09209
361012.4763-2.47635
371012.264-2.264
381415.4382-1.43815
391614.11271.88726
401614.05481.94521
411614.35961.64042
421415.3766-1.37658
432017.51452.48554
441413.73290.267099
451414.1384-0.138379
461115.1237-4.12374
471416.4912-2.49119
481514.78930.210684
491615.12350.876542
501415.3469-1.34686
511616.8637-0.863664
521413.71860.281439
531214.5879-2.58789
541615.75580.244238
55910.6747-1.6747
561411.83472.16528
571615.68550.314502
581615.26750.73248
591514.79630.203737
601613.79722.20285
611210.83481.16518
621615.39670.603305
631616.2853-0.285295
641414.4374-0.43736
651615.16170.838258
661715.74981.25022
671816.1231.87705
681814.01593.9841
691215.8-3.79999
701615.47080.5292
711013.0703-3.07027
721414.7254-0.725374
731816.8081.19203
741817.15610.843888
751614.98541.01457
761713.07653.92354
771616.4115-0.411455
781614.24631.75373
791314.9672-1.9672
801615.09960.900443
811615.49520.504783
821615.68270.317257
831515.5892-0.589244
841514.69190.308134
851613.88252.11747
861413.93030.0697186
871615.23710.762877
881614.69581.30418
891514.10190.898055
901213.6725-1.67247
911716.84130.158657
921615.70750.292505
931514.86270.137328
941314.806-1.80599
951614.65631.34373
961615.71050.2895
971613.45182.5482
981615.79840.201591
991414.2636-0.26364
1001617.1676-1.16758
1011614.50851.49151
1022017.57732.42275
1031514.06780.93218
1041614.80791.19206
1051314.6936-1.69363
1061715.77051.22952
1071615.75510.244867
1081614.24041.75959
1091212.0259-0.0258758
1101615.17190.828131
1111615.91970.0802797
1121714.88612.1139
1131314.3092-1.30925
1141214.6219-2.62189
1151816.28311.71689
1161415.9618-1.96176
1171413.05420.945817
1181314.7939-1.79391
1191615.50140.498578
1201314.3827-1.38274
1211615.40280.59722
1221315.8856-2.88564
1231617.0911-1.09112
1241516.0104-1.01043
1251616.9056-0.905568
1261514.7450.255021
1271715.73761.26245
1281514.07070.929307
1291214.7467-2.74673
1301613.88312.11689
1311013.4866-3.48662
1321613.46032.53974
1331214.1472-2.14717
1341415.7041-1.70407
1351515.1524-0.152385
1361311.88271.11726
1371514.61380.386193
1381113.4141-2.41405
1391213.0183-1.0183
1401113.2649-2.26491
1411612.88643.11365
1421513.5681.43197
1431717.0252-0.0252302
1441614.20281.79725
1451013.3083-3.30831
1461815.72692.27306
1471315.0916-2.09156
1481614.93131.06865
1491312.65750.342468
1501012.8885-2.88851
1511516.1162-1.11619
1521613.95272.04727
1531611.70444.29559
1541412.25691.74307
1551012.3669-2.36692
1561716.84130.158657
1571311.58671.41334
1581514.07070.929307
1591614.66881.3312
1601212.5372-0.53721
1611312.67260.327426
1621312.51550.484461
1631212.3383-0.338264
1641716.55510.444932
1651513.64851.3515
1661011.4262-1.42617
1671414.4811-0.481121
1681114.2781-3.27807
1691314.8417-1.84171
1701614.36481.6352
1711210.36731.63275
1721615.70740.292626
1731213.9712-1.97118
174911.298-2.298
1751215.2894-3.28938
1761514.68150.318472
1771212.2886-0.288552
1781212.6655-0.665521
1791414.0747-0.0747474
1801213.4094-1.40943
1811615.44680.553162
1821111.5309-0.530884
1831917.19591.80415
1841515.5036-0.503576
185814.7884-6.78839
1861614.91461.08538
1871714.70242.29755
1881212.5082-0.508191
1891111.4831-0.483109
1901110.32730.672724
1911414.8305-0.830496
1921615.82110.178896
193129.652122.34788
1941614.36361.63641
1951313.9181-0.918079
1961515.3956-0.395569
1971613.08162.91844
1981615.30320.696807
1991412.47071.52925
2001614.7211.27902
2011614.23621.76379
2021413.53840.461598
2031113.6898-2.68975
2041214.9664-2.96637
2051512.95462.04537
2061514.83350.166471
2071614.90291.09712
2081615.42620.573751
2091113.9403-2.9403
2101514.27410.725874
2111214.5279-2.52793
2121216.3134-4.31338
2131514.31560.684353
2141512.18512.81493
2151614.86451.13553
2161413.45750.542456
2171715.06271.93732
2181414.3458-0.345776
2191311.95781.04224
2201515.6462-0.64624
2211315.0173-2.01726
2221414.492-0.491955
2231514.56640.433575
2241213.469-1.46903
2251312.57410.425944
226811.9366-3.93664
2271414.3243-0.324338
2281413.19560.804408
2291112.3668-1.36681
2301213.1689-1.1689
2311311.47421.52575
2321013.5269-3.52692
2331611.72534.27468
2341816.48611.51387
2351314.313-1.31295
2361113.6602-2.66023
237411.2284-7.22839
2381314.8756-1.87564
2391614.58681.41323
2401011.9291-1.92912
2411212.3982-0.398227
2421213.8308-1.83077
243108.88491.1151
2441311.2681.73197
2451514.14090.859059
2461212.0409-0.0409122
2471413.18440.815635
2481012.9282-2.92818
2491210.85141.14857
2501211.85910.140938
2511112.1248-1.12478
2521011.8417-1.84175
2531211.67650.323527
2541613.20062.79936
2551213.7581-1.75809
2561414.3068-0.306836
2571614.61621.38381
2581411.86812.13189
2591314.7809-1.78089
26049.50961-5.50961
2611514.16840.831553
2621115.5452-4.54522
2631111.4806-0.480633
2641413.15610.843884

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 15.7157 & -2.71568 \tabularnewline
2 & 16 & 15.3036 & 0.69641 \tabularnewline
3 & 19 & 16.5785 & 2.42154 \tabularnewline
4 & 15 & 11.2518 & 3.74818 \tabularnewline
5 & 14 & 15.8688 & -1.86884 \tabularnewline
6 & 13 & 14.3276 & -1.32765 \tabularnewline
7 & 19 & 14.9208 & 4.07918 \tabularnewline
8 & 15 & 16.6626 & -1.66259 \tabularnewline
9 & 14 & 15.6145 & -1.61445 \tabularnewline
10 & 15 & 13.846 & 1.154 \tabularnewline
11 & 16 & 14.5365 & 1.46349 \tabularnewline
12 & 16 & 15.9767 & 0.0232872 \tabularnewline
13 & 16 & 14.986 & 1.01397 \tabularnewline
14 & 16 & 15.1337 & 0.866345 \tabularnewline
15 & 17 & 17.7248 & -0.7248 \tabularnewline
16 & 15 & 15.0286 & -0.0286499 \tabularnewline
17 & 15 & 14.0141 & 0.985856 \tabularnewline
18 & 20 & 16.0365 & 3.96348 \tabularnewline
19 & 18 & 15.1365 & 2.86352 \tabularnewline
20 & 16 & 15.2205 & 0.779494 \tabularnewline
21 & 16 & 15.0257 & 0.974259 \tabularnewline
22 & 16 & 14.6397 & 1.36028 \tabularnewline
23 & 19 & 16.2354 & 2.76458 \tabularnewline
24 & 16 & 14.6982 & 1.30181 \tabularnewline
25 & 17 & 15.824 & 1.17595 \tabularnewline
26 & 17 & 15.7996 & 1.20037 \tabularnewline
27 & 16 & 14.4626 & 1.53744 \tabularnewline
28 & 15 & 16.4559 & -1.45594 \tabularnewline
29 & 16 & 15.2431 & 0.756916 \tabularnewline
30 & 14 & 13.6826 & 0.317389 \tabularnewline
31 & 15 & 15.3776 & -0.377563 \tabularnewline
32 & 12 & 12.1718 & -0.171821 \tabularnewline
33 & 14 & 14.4624 & -0.462441 \tabularnewline
34 & 16 & 15.6006 & 0.399385 \tabularnewline
35 & 14 & 15.0921 & -1.09209 \tabularnewline
36 & 10 & 12.4763 & -2.47635 \tabularnewline
37 & 10 & 12.264 & -2.264 \tabularnewline
38 & 14 & 15.4382 & -1.43815 \tabularnewline
39 & 16 & 14.1127 & 1.88726 \tabularnewline
40 & 16 & 14.0548 & 1.94521 \tabularnewline
41 & 16 & 14.3596 & 1.64042 \tabularnewline
42 & 14 & 15.3766 & -1.37658 \tabularnewline
43 & 20 & 17.5145 & 2.48554 \tabularnewline
44 & 14 & 13.7329 & 0.267099 \tabularnewline
45 & 14 & 14.1384 & -0.138379 \tabularnewline
46 & 11 & 15.1237 & -4.12374 \tabularnewline
47 & 14 & 16.4912 & -2.49119 \tabularnewline
48 & 15 & 14.7893 & 0.210684 \tabularnewline
49 & 16 & 15.1235 & 0.876542 \tabularnewline
50 & 14 & 15.3469 & -1.34686 \tabularnewline
51 & 16 & 16.8637 & -0.863664 \tabularnewline
52 & 14 & 13.7186 & 0.281439 \tabularnewline
53 & 12 & 14.5879 & -2.58789 \tabularnewline
54 & 16 & 15.7558 & 0.244238 \tabularnewline
55 & 9 & 10.6747 & -1.6747 \tabularnewline
56 & 14 & 11.8347 & 2.16528 \tabularnewline
57 & 16 & 15.6855 & 0.314502 \tabularnewline
58 & 16 & 15.2675 & 0.73248 \tabularnewline
59 & 15 & 14.7963 & 0.203737 \tabularnewline
60 & 16 & 13.7972 & 2.20285 \tabularnewline
61 & 12 & 10.8348 & 1.16518 \tabularnewline
62 & 16 & 15.3967 & 0.603305 \tabularnewline
63 & 16 & 16.2853 & -0.285295 \tabularnewline
64 & 14 & 14.4374 & -0.43736 \tabularnewline
65 & 16 & 15.1617 & 0.838258 \tabularnewline
66 & 17 & 15.7498 & 1.25022 \tabularnewline
67 & 18 & 16.123 & 1.87705 \tabularnewline
68 & 18 & 14.0159 & 3.9841 \tabularnewline
69 & 12 & 15.8 & -3.79999 \tabularnewline
70 & 16 & 15.4708 & 0.5292 \tabularnewline
71 & 10 & 13.0703 & -3.07027 \tabularnewline
72 & 14 & 14.7254 & -0.725374 \tabularnewline
73 & 18 & 16.808 & 1.19203 \tabularnewline
74 & 18 & 17.1561 & 0.843888 \tabularnewline
75 & 16 & 14.9854 & 1.01457 \tabularnewline
76 & 17 & 13.0765 & 3.92354 \tabularnewline
77 & 16 & 16.4115 & -0.411455 \tabularnewline
78 & 16 & 14.2463 & 1.75373 \tabularnewline
79 & 13 & 14.9672 & -1.9672 \tabularnewline
80 & 16 & 15.0996 & 0.900443 \tabularnewline
81 & 16 & 15.4952 & 0.504783 \tabularnewline
82 & 16 & 15.6827 & 0.317257 \tabularnewline
83 & 15 & 15.5892 & -0.589244 \tabularnewline
84 & 15 & 14.6919 & 0.308134 \tabularnewline
85 & 16 & 13.8825 & 2.11747 \tabularnewline
86 & 14 & 13.9303 & 0.0697186 \tabularnewline
87 & 16 & 15.2371 & 0.762877 \tabularnewline
88 & 16 & 14.6958 & 1.30418 \tabularnewline
89 & 15 & 14.1019 & 0.898055 \tabularnewline
90 & 12 & 13.6725 & -1.67247 \tabularnewline
91 & 17 & 16.8413 & 0.158657 \tabularnewline
92 & 16 & 15.7075 & 0.292505 \tabularnewline
93 & 15 & 14.8627 & 0.137328 \tabularnewline
94 & 13 & 14.806 & -1.80599 \tabularnewline
95 & 16 & 14.6563 & 1.34373 \tabularnewline
96 & 16 & 15.7105 & 0.2895 \tabularnewline
97 & 16 & 13.4518 & 2.5482 \tabularnewline
98 & 16 & 15.7984 & 0.201591 \tabularnewline
99 & 14 & 14.2636 & -0.26364 \tabularnewline
100 & 16 & 17.1676 & -1.16758 \tabularnewline
101 & 16 & 14.5085 & 1.49151 \tabularnewline
102 & 20 & 17.5773 & 2.42275 \tabularnewline
103 & 15 & 14.0678 & 0.93218 \tabularnewline
104 & 16 & 14.8079 & 1.19206 \tabularnewline
105 & 13 & 14.6936 & -1.69363 \tabularnewline
106 & 17 & 15.7705 & 1.22952 \tabularnewline
107 & 16 & 15.7551 & 0.244867 \tabularnewline
108 & 16 & 14.2404 & 1.75959 \tabularnewline
109 & 12 & 12.0259 & -0.0258758 \tabularnewline
110 & 16 & 15.1719 & 0.828131 \tabularnewline
111 & 16 & 15.9197 & 0.0802797 \tabularnewline
112 & 17 & 14.8861 & 2.1139 \tabularnewline
113 & 13 & 14.3092 & -1.30925 \tabularnewline
114 & 12 & 14.6219 & -2.62189 \tabularnewline
115 & 18 & 16.2831 & 1.71689 \tabularnewline
116 & 14 & 15.9618 & -1.96176 \tabularnewline
117 & 14 & 13.0542 & 0.945817 \tabularnewline
118 & 13 & 14.7939 & -1.79391 \tabularnewline
119 & 16 & 15.5014 & 0.498578 \tabularnewline
120 & 13 & 14.3827 & -1.38274 \tabularnewline
121 & 16 & 15.4028 & 0.59722 \tabularnewline
122 & 13 & 15.8856 & -2.88564 \tabularnewline
123 & 16 & 17.0911 & -1.09112 \tabularnewline
124 & 15 & 16.0104 & -1.01043 \tabularnewline
125 & 16 & 16.9056 & -0.905568 \tabularnewline
126 & 15 & 14.745 & 0.255021 \tabularnewline
127 & 17 & 15.7376 & 1.26245 \tabularnewline
128 & 15 & 14.0707 & 0.929307 \tabularnewline
129 & 12 & 14.7467 & -2.74673 \tabularnewline
130 & 16 & 13.8831 & 2.11689 \tabularnewline
131 & 10 & 13.4866 & -3.48662 \tabularnewline
132 & 16 & 13.4603 & 2.53974 \tabularnewline
133 & 12 & 14.1472 & -2.14717 \tabularnewline
134 & 14 & 15.7041 & -1.70407 \tabularnewline
135 & 15 & 15.1524 & -0.152385 \tabularnewline
136 & 13 & 11.8827 & 1.11726 \tabularnewline
137 & 15 & 14.6138 & 0.386193 \tabularnewline
138 & 11 & 13.4141 & -2.41405 \tabularnewline
139 & 12 & 13.0183 & -1.0183 \tabularnewline
140 & 11 & 13.2649 & -2.26491 \tabularnewline
141 & 16 & 12.8864 & 3.11365 \tabularnewline
142 & 15 & 13.568 & 1.43197 \tabularnewline
143 & 17 & 17.0252 & -0.0252302 \tabularnewline
144 & 16 & 14.2028 & 1.79725 \tabularnewline
145 & 10 & 13.3083 & -3.30831 \tabularnewline
146 & 18 & 15.7269 & 2.27306 \tabularnewline
147 & 13 & 15.0916 & -2.09156 \tabularnewline
148 & 16 & 14.9313 & 1.06865 \tabularnewline
149 & 13 & 12.6575 & 0.342468 \tabularnewline
150 & 10 & 12.8885 & -2.88851 \tabularnewline
151 & 15 & 16.1162 & -1.11619 \tabularnewline
152 & 16 & 13.9527 & 2.04727 \tabularnewline
153 & 16 & 11.7044 & 4.29559 \tabularnewline
154 & 14 & 12.2569 & 1.74307 \tabularnewline
155 & 10 & 12.3669 & -2.36692 \tabularnewline
156 & 17 & 16.8413 & 0.158657 \tabularnewline
157 & 13 & 11.5867 & 1.41334 \tabularnewline
158 & 15 & 14.0707 & 0.929307 \tabularnewline
159 & 16 & 14.6688 & 1.3312 \tabularnewline
160 & 12 & 12.5372 & -0.53721 \tabularnewline
161 & 13 & 12.6726 & 0.327426 \tabularnewline
162 & 13 & 12.5155 & 0.484461 \tabularnewline
163 & 12 & 12.3383 & -0.338264 \tabularnewline
164 & 17 & 16.5551 & 0.444932 \tabularnewline
165 & 15 & 13.6485 & 1.3515 \tabularnewline
166 & 10 & 11.4262 & -1.42617 \tabularnewline
167 & 14 & 14.4811 & -0.481121 \tabularnewline
168 & 11 & 14.2781 & -3.27807 \tabularnewline
169 & 13 & 14.8417 & -1.84171 \tabularnewline
170 & 16 & 14.3648 & 1.6352 \tabularnewline
171 & 12 & 10.3673 & 1.63275 \tabularnewline
172 & 16 & 15.7074 & 0.292626 \tabularnewline
173 & 12 & 13.9712 & -1.97118 \tabularnewline
174 & 9 & 11.298 & -2.298 \tabularnewline
175 & 12 & 15.2894 & -3.28938 \tabularnewline
176 & 15 & 14.6815 & 0.318472 \tabularnewline
177 & 12 & 12.2886 & -0.288552 \tabularnewline
178 & 12 & 12.6655 & -0.665521 \tabularnewline
179 & 14 & 14.0747 & -0.0747474 \tabularnewline
180 & 12 & 13.4094 & -1.40943 \tabularnewline
181 & 16 & 15.4468 & 0.553162 \tabularnewline
182 & 11 & 11.5309 & -0.530884 \tabularnewline
183 & 19 & 17.1959 & 1.80415 \tabularnewline
184 & 15 & 15.5036 & -0.503576 \tabularnewline
185 & 8 & 14.7884 & -6.78839 \tabularnewline
186 & 16 & 14.9146 & 1.08538 \tabularnewline
187 & 17 & 14.7024 & 2.29755 \tabularnewline
188 & 12 & 12.5082 & -0.508191 \tabularnewline
189 & 11 & 11.4831 & -0.483109 \tabularnewline
190 & 11 & 10.3273 & 0.672724 \tabularnewline
191 & 14 & 14.8305 & -0.830496 \tabularnewline
192 & 16 & 15.8211 & 0.178896 \tabularnewline
193 & 12 & 9.65212 & 2.34788 \tabularnewline
194 & 16 & 14.3636 & 1.63641 \tabularnewline
195 & 13 & 13.9181 & -0.918079 \tabularnewline
196 & 15 & 15.3956 & -0.395569 \tabularnewline
197 & 16 & 13.0816 & 2.91844 \tabularnewline
198 & 16 & 15.3032 & 0.696807 \tabularnewline
199 & 14 & 12.4707 & 1.52925 \tabularnewline
200 & 16 & 14.721 & 1.27902 \tabularnewline
201 & 16 & 14.2362 & 1.76379 \tabularnewline
202 & 14 & 13.5384 & 0.461598 \tabularnewline
203 & 11 & 13.6898 & -2.68975 \tabularnewline
204 & 12 & 14.9664 & -2.96637 \tabularnewline
205 & 15 & 12.9546 & 2.04537 \tabularnewline
206 & 15 & 14.8335 & 0.166471 \tabularnewline
207 & 16 & 14.9029 & 1.09712 \tabularnewline
208 & 16 & 15.4262 & 0.573751 \tabularnewline
209 & 11 & 13.9403 & -2.9403 \tabularnewline
210 & 15 & 14.2741 & 0.725874 \tabularnewline
211 & 12 & 14.5279 & -2.52793 \tabularnewline
212 & 12 & 16.3134 & -4.31338 \tabularnewline
213 & 15 & 14.3156 & 0.684353 \tabularnewline
214 & 15 & 12.1851 & 2.81493 \tabularnewline
215 & 16 & 14.8645 & 1.13553 \tabularnewline
216 & 14 & 13.4575 & 0.542456 \tabularnewline
217 & 17 & 15.0627 & 1.93732 \tabularnewline
218 & 14 & 14.3458 & -0.345776 \tabularnewline
219 & 13 & 11.9578 & 1.04224 \tabularnewline
220 & 15 & 15.6462 & -0.64624 \tabularnewline
221 & 13 & 15.0173 & -2.01726 \tabularnewline
222 & 14 & 14.492 & -0.491955 \tabularnewline
223 & 15 & 14.5664 & 0.433575 \tabularnewline
224 & 12 & 13.469 & -1.46903 \tabularnewline
225 & 13 & 12.5741 & 0.425944 \tabularnewline
226 & 8 & 11.9366 & -3.93664 \tabularnewline
227 & 14 & 14.3243 & -0.324338 \tabularnewline
228 & 14 & 13.1956 & 0.804408 \tabularnewline
229 & 11 & 12.3668 & -1.36681 \tabularnewline
230 & 12 & 13.1689 & -1.1689 \tabularnewline
231 & 13 & 11.4742 & 1.52575 \tabularnewline
232 & 10 & 13.5269 & -3.52692 \tabularnewline
233 & 16 & 11.7253 & 4.27468 \tabularnewline
234 & 18 & 16.4861 & 1.51387 \tabularnewline
235 & 13 & 14.313 & -1.31295 \tabularnewline
236 & 11 & 13.6602 & -2.66023 \tabularnewline
237 & 4 & 11.2284 & -7.22839 \tabularnewline
238 & 13 & 14.8756 & -1.87564 \tabularnewline
239 & 16 & 14.5868 & 1.41323 \tabularnewline
240 & 10 & 11.9291 & -1.92912 \tabularnewline
241 & 12 & 12.3982 & -0.398227 \tabularnewline
242 & 12 & 13.8308 & -1.83077 \tabularnewline
243 & 10 & 8.8849 & 1.1151 \tabularnewline
244 & 13 & 11.268 & 1.73197 \tabularnewline
245 & 15 & 14.1409 & 0.859059 \tabularnewline
246 & 12 & 12.0409 & -0.0409122 \tabularnewline
247 & 14 & 13.1844 & 0.815635 \tabularnewline
248 & 10 & 12.9282 & -2.92818 \tabularnewline
249 & 12 & 10.8514 & 1.14857 \tabularnewline
250 & 12 & 11.8591 & 0.140938 \tabularnewline
251 & 11 & 12.1248 & -1.12478 \tabularnewline
252 & 10 & 11.8417 & -1.84175 \tabularnewline
253 & 12 & 11.6765 & 0.323527 \tabularnewline
254 & 16 & 13.2006 & 2.79936 \tabularnewline
255 & 12 & 13.7581 & -1.75809 \tabularnewline
256 & 14 & 14.3068 & -0.306836 \tabularnewline
257 & 16 & 14.6162 & 1.38381 \tabularnewline
258 & 14 & 11.8681 & 2.13189 \tabularnewline
259 & 13 & 14.7809 & -1.78089 \tabularnewline
260 & 4 & 9.50961 & -5.50961 \tabularnewline
261 & 15 & 14.1684 & 0.831553 \tabularnewline
262 & 11 & 15.5452 & -4.54522 \tabularnewline
263 & 11 & 11.4806 & -0.480633 \tabularnewline
264 & 14 & 13.1561 & 0.843884 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253350&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]13[/C][C]15.7157[/C][C]-2.71568[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.3036[/C][C]0.69641[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]16.5785[/C][C]2.42154[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]11.2518[/C][C]3.74818[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]15.8688[/C][C]-1.86884[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.3276[/C][C]-1.32765[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]14.9208[/C][C]4.07918[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]16.6626[/C][C]-1.66259[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.6145[/C][C]-1.61445[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]13.846[/C][C]1.154[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.5365[/C][C]1.46349[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]15.9767[/C][C]0.0232872[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]14.986[/C][C]1.01397[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.1337[/C][C]0.866345[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.7248[/C][C]-0.7248[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.0286[/C][C]-0.0286499[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.0141[/C][C]0.985856[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.0365[/C][C]3.96348[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.1365[/C][C]2.86352[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.2205[/C][C]0.779494[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.0257[/C][C]0.974259[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]14.6397[/C][C]1.36028[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.2354[/C][C]2.76458[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.6982[/C][C]1.30181[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.824[/C][C]1.17595[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]15.7996[/C][C]1.20037[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.4626[/C][C]1.53744[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.4559[/C][C]-1.45594[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.2431[/C][C]0.756916[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]13.6826[/C][C]0.317389[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.3776[/C][C]-0.377563[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.1718[/C][C]-0.171821[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.4624[/C][C]-0.462441[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.6006[/C][C]0.399385[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.0921[/C][C]-1.09209[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.4763[/C][C]-2.47635[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]12.264[/C][C]-2.264[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.4382[/C][C]-1.43815[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.1127[/C][C]1.88726[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.0548[/C][C]1.94521[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.3596[/C][C]1.64042[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.3766[/C][C]-1.37658[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.5145[/C][C]2.48554[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]13.7329[/C][C]0.267099[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.1384[/C][C]-0.138379[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.1237[/C][C]-4.12374[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.4912[/C][C]-2.49119[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.7893[/C][C]0.210684[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.1235[/C][C]0.876542[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.3469[/C][C]-1.34686[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.8637[/C][C]-0.863664[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.7186[/C][C]0.281439[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.5879[/C][C]-2.58789[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.7558[/C][C]0.244238[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]10.6747[/C][C]-1.6747[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]11.8347[/C][C]2.16528[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.6855[/C][C]0.314502[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.2675[/C][C]0.73248[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]14.7963[/C][C]0.203737[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]13.7972[/C][C]2.20285[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]10.8348[/C][C]1.16518[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.3967[/C][C]0.603305[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.2853[/C][C]-0.285295[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.4374[/C][C]-0.43736[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.1617[/C][C]0.838258[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]15.7498[/C][C]1.25022[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.123[/C][C]1.87705[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.0159[/C][C]3.9841[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.8[/C][C]-3.79999[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.4708[/C][C]0.5292[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.0703[/C][C]-3.07027[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.7254[/C][C]-0.725374[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]16.808[/C][C]1.19203[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.1561[/C][C]0.843888[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]14.9854[/C][C]1.01457[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.0765[/C][C]3.92354[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.4115[/C][C]-0.411455[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.2463[/C][C]1.75373[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]14.9672[/C][C]-1.9672[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.0996[/C][C]0.900443[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.4952[/C][C]0.504783[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.6827[/C][C]0.317257[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.5892[/C][C]-0.589244[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.6919[/C][C]0.308134[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]13.8825[/C][C]2.11747[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]13.9303[/C][C]0.0697186[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.2371[/C][C]0.762877[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.6958[/C][C]1.30418[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.1019[/C][C]0.898055[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.6725[/C][C]-1.67247[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.8413[/C][C]0.158657[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.7075[/C][C]0.292505[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]14.8627[/C][C]0.137328[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.806[/C][C]-1.80599[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.6563[/C][C]1.34373[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.7105[/C][C]0.2895[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.4518[/C][C]2.5482[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.7984[/C][C]0.201591[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.2636[/C][C]-0.26364[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.1676[/C][C]-1.16758[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.5085[/C][C]1.49151[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.5773[/C][C]2.42275[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.0678[/C][C]0.93218[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.8079[/C][C]1.19206[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.6936[/C][C]-1.69363[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.7705[/C][C]1.22952[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7551[/C][C]0.244867[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.2404[/C][C]1.75959[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.0259[/C][C]-0.0258758[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.1719[/C][C]0.828131[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]15.9197[/C][C]0.0802797[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]14.8861[/C][C]2.1139[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.3092[/C][C]-1.30925[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.6219[/C][C]-2.62189[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.2831[/C][C]1.71689[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.9618[/C][C]-1.96176[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.0542[/C][C]0.945817[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7939[/C][C]-1.79391[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5014[/C][C]0.498578[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.3827[/C][C]-1.38274[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.4028[/C][C]0.59722[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.8856[/C][C]-2.88564[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]17.0911[/C][C]-1.09112[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]16.0104[/C][C]-1.01043[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.9056[/C][C]-0.905568[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.745[/C][C]0.255021[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.7376[/C][C]1.26245[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]14.0707[/C][C]0.929307[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.7467[/C][C]-2.74673[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.8831[/C][C]2.11689[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.4866[/C][C]-3.48662[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4603[/C][C]2.53974[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.1472[/C][C]-2.14717[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.7041[/C][C]-1.70407[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.1524[/C][C]-0.152385[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]11.8827[/C][C]1.11726[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.6138[/C][C]0.386193[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.4141[/C][C]-2.41405[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]13.0183[/C][C]-1.0183[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.2649[/C][C]-2.26491[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8864[/C][C]3.11365[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.568[/C][C]1.43197[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]17.0252[/C][C]-0.0252302[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.2028[/C][C]1.79725[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.3083[/C][C]-3.30831[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.7269[/C][C]2.27306[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.0916[/C][C]-2.09156[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.9313[/C][C]1.06865[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.6575[/C][C]0.342468[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.8885[/C][C]-2.88851[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]16.1162[/C][C]-1.11619[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.9527[/C][C]2.04727[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.7044[/C][C]4.29559[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.2569[/C][C]1.74307[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.3669[/C][C]-2.36692[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.8413[/C][C]0.158657[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.5867[/C][C]1.41334[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]14.0707[/C][C]0.929307[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.6688[/C][C]1.3312[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.5372[/C][C]-0.53721[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6726[/C][C]0.327426[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.5155[/C][C]0.484461[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.3383[/C][C]-0.338264[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.5551[/C][C]0.444932[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.6485[/C][C]1.3515[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.4262[/C][C]-1.42617[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.4811[/C][C]-0.481121[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.2781[/C][C]-3.27807[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.8417[/C][C]-1.84171[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.3648[/C][C]1.6352[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.3673[/C][C]1.63275[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.7074[/C][C]0.292626[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.9712[/C][C]-1.97118[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.298[/C][C]-2.298[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]15.2894[/C][C]-3.28938[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.6815[/C][C]0.318472[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.2886[/C][C]-0.288552[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.6655[/C][C]-0.665521[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]14.0747[/C][C]-0.0747474[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.4094[/C][C]-1.40943[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.4468[/C][C]0.553162[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.5309[/C][C]-0.530884[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]17.1959[/C][C]1.80415[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.5036[/C][C]-0.503576[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.7884[/C][C]-6.78839[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.9146[/C][C]1.08538[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.7024[/C][C]2.29755[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.5082[/C][C]-0.508191[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.4831[/C][C]-0.483109[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.3273[/C][C]0.672724[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.8305[/C][C]-0.830496[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.8211[/C][C]0.178896[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.65212[/C][C]2.34788[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.3636[/C][C]1.63641[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.9181[/C][C]-0.918079[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15.3956[/C][C]-0.395569[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]13.0816[/C][C]2.91844[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.3032[/C][C]0.696807[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4707[/C][C]1.52925[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.721[/C][C]1.27902[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]14.2362[/C][C]1.76379[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.5384[/C][C]0.461598[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.6898[/C][C]-2.68975[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.9664[/C][C]-2.96637[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.9546[/C][C]2.04537[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.8335[/C][C]0.166471[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.9029[/C][C]1.09712[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]15.4262[/C][C]0.573751[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.9403[/C][C]-2.9403[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]14.2741[/C][C]0.725874[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.5279[/C][C]-2.52793[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]16.3134[/C][C]-4.31338[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.3156[/C][C]0.684353[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.1851[/C][C]2.81493[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.8645[/C][C]1.13553[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.4575[/C][C]0.542456[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]15.0627[/C][C]1.93732[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.3458[/C][C]-0.345776[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.9578[/C][C]1.04224[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.6462[/C][C]-0.64624[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]15.0173[/C][C]-2.01726[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.492[/C][C]-0.491955[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.5664[/C][C]0.433575[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.469[/C][C]-1.46903[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.5741[/C][C]0.425944[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.9366[/C][C]-3.93664[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]14.3243[/C][C]-0.324338[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]13.1956[/C][C]0.804408[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.3668[/C][C]-1.36681[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]13.1689[/C][C]-1.1689[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.4742[/C][C]1.52575[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.5269[/C][C]-3.52692[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.7253[/C][C]4.27468[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]16.4861[/C][C]1.51387[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]14.313[/C][C]-1.31295[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.6602[/C][C]-2.66023[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]11.2284[/C][C]-7.22839[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.8756[/C][C]-1.87564[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.5868[/C][C]1.41323[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.9291[/C][C]-1.92912[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.3982[/C][C]-0.398227[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.8308[/C][C]-1.83077[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.8849[/C][C]1.1151[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]11.268[/C][C]1.73197[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]14.1409[/C][C]0.859059[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]12.0409[/C][C]-0.0409122[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]13.1844[/C][C]0.815635[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.9282[/C][C]-2.92818[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.8514[/C][C]1.14857[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.8591[/C][C]0.140938[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]12.1248[/C][C]-1.12478[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.8417[/C][C]-1.84175[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.6765[/C][C]0.323527[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]13.2006[/C][C]2.79936[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.7581[/C][C]-1.75809[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]14.3068[/C][C]-0.306836[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.6162[/C][C]1.38381[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.8681[/C][C]2.13189[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.7809[/C][C]-1.78089[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.50961[/C][C]-5.50961[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]14.1684[/C][C]0.831553[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]15.5452[/C][C]-4.54522[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.4806[/C][C]-0.480633[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.1561[/C][C]0.843884[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253350&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253350&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11315.7157-2.71568
21615.30360.69641
31916.57852.42154
41511.25183.74818
51415.8688-1.86884
61314.3276-1.32765
71914.92084.07918
81516.6626-1.66259
91415.6145-1.61445
101513.8461.154
111614.53651.46349
121615.97670.0232872
131614.9861.01397
141615.13370.866345
151717.7248-0.7248
161515.0286-0.0286499
171514.01410.985856
182016.03653.96348
191815.13652.86352
201615.22050.779494
211615.02570.974259
221614.63971.36028
231916.23542.76458
241614.69821.30181
251715.8241.17595
261715.79961.20037
271614.46261.53744
281516.4559-1.45594
291615.24310.756916
301413.68260.317389
311515.3776-0.377563
321212.1718-0.171821
331414.4624-0.462441
341615.60060.399385
351415.0921-1.09209
361012.4763-2.47635
371012.264-2.264
381415.4382-1.43815
391614.11271.88726
401614.05481.94521
411614.35961.64042
421415.3766-1.37658
432017.51452.48554
441413.73290.267099
451414.1384-0.138379
461115.1237-4.12374
471416.4912-2.49119
481514.78930.210684
491615.12350.876542
501415.3469-1.34686
511616.8637-0.863664
521413.71860.281439
531214.5879-2.58789
541615.75580.244238
55910.6747-1.6747
561411.83472.16528
571615.68550.314502
581615.26750.73248
591514.79630.203737
601613.79722.20285
611210.83481.16518
621615.39670.603305
631616.2853-0.285295
641414.4374-0.43736
651615.16170.838258
661715.74981.25022
671816.1231.87705
681814.01593.9841
691215.8-3.79999
701615.47080.5292
711013.0703-3.07027
721414.7254-0.725374
731816.8081.19203
741817.15610.843888
751614.98541.01457
761713.07653.92354
771616.4115-0.411455
781614.24631.75373
791314.9672-1.9672
801615.09960.900443
811615.49520.504783
821615.68270.317257
831515.5892-0.589244
841514.69190.308134
851613.88252.11747
861413.93030.0697186
871615.23710.762877
881614.69581.30418
891514.10190.898055
901213.6725-1.67247
911716.84130.158657
921615.70750.292505
931514.86270.137328
941314.806-1.80599
951614.65631.34373
961615.71050.2895
971613.45182.5482
981615.79840.201591
991414.2636-0.26364
1001617.1676-1.16758
1011614.50851.49151
1022017.57732.42275
1031514.06780.93218
1041614.80791.19206
1051314.6936-1.69363
1061715.77051.22952
1071615.75510.244867
1081614.24041.75959
1091212.0259-0.0258758
1101615.17190.828131
1111615.91970.0802797
1121714.88612.1139
1131314.3092-1.30925
1141214.6219-2.62189
1151816.28311.71689
1161415.9618-1.96176
1171413.05420.945817
1181314.7939-1.79391
1191615.50140.498578
1201314.3827-1.38274
1211615.40280.59722
1221315.8856-2.88564
1231617.0911-1.09112
1241516.0104-1.01043
1251616.9056-0.905568
1261514.7450.255021
1271715.73761.26245
1281514.07070.929307
1291214.7467-2.74673
1301613.88312.11689
1311013.4866-3.48662
1321613.46032.53974
1331214.1472-2.14717
1341415.7041-1.70407
1351515.1524-0.152385
1361311.88271.11726
1371514.61380.386193
1381113.4141-2.41405
1391213.0183-1.0183
1401113.2649-2.26491
1411612.88643.11365
1421513.5681.43197
1431717.0252-0.0252302
1441614.20281.79725
1451013.3083-3.30831
1461815.72692.27306
1471315.0916-2.09156
1481614.93131.06865
1491312.65750.342468
1501012.8885-2.88851
1511516.1162-1.11619
1521613.95272.04727
1531611.70444.29559
1541412.25691.74307
1551012.3669-2.36692
1561716.84130.158657
1571311.58671.41334
1581514.07070.929307
1591614.66881.3312
1601212.5372-0.53721
1611312.67260.327426
1621312.51550.484461
1631212.3383-0.338264
1641716.55510.444932
1651513.64851.3515
1661011.4262-1.42617
1671414.4811-0.481121
1681114.2781-3.27807
1691314.8417-1.84171
1701614.36481.6352
1711210.36731.63275
1721615.70740.292626
1731213.9712-1.97118
174911.298-2.298
1751215.2894-3.28938
1761514.68150.318472
1771212.2886-0.288552
1781212.6655-0.665521
1791414.0747-0.0747474
1801213.4094-1.40943
1811615.44680.553162
1821111.5309-0.530884
1831917.19591.80415
1841515.5036-0.503576
185814.7884-6.78839
1861614.91461.08538
1871714.70242.29755
1881212.5082-0.508191
1891111.4831-0.483109
1901110.32730.672724
1911414.8305-0.830496
1921615.82110.178896
193129.652122.34788
1941614.36361.63641
1951313.9181-0.918079
1961515.3956-0.395569
1971613.08162.91844
1981615.30320.696807
1991412.47071.52925
2001614.7211.27902
2011614.23621.76379
2021413.53840.461598
2031113.6898-2.68975
2041214.9664-2.96637
2051512.95462.04537
2061514.83350.166471
2071614.90291.09712
2081615.42620.573751
2091113.9403-2.9403
2101514.27410.725874
2111214.5279-2.52793
2121216.3134-4.31338
2131514.31560.684353
2141512.18512.81493
2151614.86451.13553
2161413.45750.542456
2171715.06271.93732
2181414.3458-0.345776
2191311.95781.04224
2201515.6462-0.64624
2211315.0173-2.01726
2221414.492-0.491955
2231514.56640.433575
2241213.469-1.46903
2251312.57410.425944
226811.9366-3.93664
2271414.3243-0.324338
2281413.19560.804408
2291112.3668-1.36681
2301213.1689-1.1689
2311311.47421.52575
2321013.5269-3.52692
2331611.72534.27468
2341816.48611.51387
2351314.313-1.31295
2361113.6602-2.66023
237411.2284-7.22839
2381314.8756-1.87564
2391614.58681.41323
2401011.9291-1.92912
2411212.3982-0.398227
2421213.8308-1.83077
243108.88491.1151
2441311.2681.73197
2451514.14090.859059
2461212.0409-0.0409122
2471413.18440.815635
2481012.9282-2.92818
2491210.85141.14857
2501211.85910.140938
2511112.1248-1.12478
2521011.8417-1.84175
2531211.67650.323527
2541613.20062.79936
2551213.7581-1.75809
2561414.3068-0.306836
2571614.61621.38381
2581411.86812.13189
2591314.7809-1.78089
26049.50961-5.50961
2611514.16840.831553
2621115.5452-4.54522
2631111.4806-0.480633
2641413.15610.843884






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.3940620.7881230.605938
110.2504770.5009550.749523
120.7581020.4837970.241898
130.6677240.6645510.332276
140.6076770.7846460.392323
150.6187690.7624620.381231
160.5989140.8021720.401086
170.510380.9792390.48962
180.8590560.2818890.140944
190.8691870.2616250.130813
200.8264890.3470230.173511
210.7818830.4362340.218117
220.7245890.5508220.275411
230.7443670.5112670.255633
240.6889350.622130.311065
250.6358310.7283380.364169
260.575990.848020.42401
270.5169280.9661430.483072
280.4980220.9960440.501978
290.4349020.8698040.565098
300.4112320.8224650.588768
310.3556640.7113280.644336
320.3350830.6701660.664917
330.3080610.6161230.691939
340.2574670.5149340.742533
350.2445380.4890770.755462
360.3380860.6761720.661914
370.4287050.857410.571295
380.4263650.852730.573635
390.4547280.9094560.545272
400.4288820.8577640.571118
410.3913540.7827080.608646
420.3724180.7448360.627582
430.3767340.7534680.623266
440.3361010.6722030.663899
450.3047930.6095860.695207
460.5697510.8604990.430249
470.6338780.7322450.366122
480.5875970.8248060.412403
490.5462840.9074320.453716
500.5372990.9254020.462701
510.4947570.9895140.505243
520.4481620.8963240.551838
530.4815960.9631920.518404
540.4372670.8745350.562733
550.447490.8949810.55251
560.4344310.8688630.565569
570.3921640.7843280.607836
580.3625730.7251450.637427
590.3216240.6432480.678376
600.3285150.657030.671485
610.2998950.599790.700105
620.2644140.5288280.735586
630.2299830.4599650.770017
640.2002320.4004650.799768
650.1749440.3498880.825056
660.1620840.3241690.837916
670.1595140.3190280.840486
680.2628020.5256040.737198
690.3844450.768890.615555
700.3487950.697590.651205
710.4297110.8594210.570289
720.3919730.7839460.608027
730.3742470.7484930.625753
740.3478830.6957650.652117
750.3161840.6323690.683816
760.3898080.7796160.610192
770.3538530.7077050.646147
780.3356690.6713380.664331
790.3454460.6908930.654554
800.3167310.6334620.683269
810.2851890.5703780.714811
820.2542290.5084590.745771
830.2317970.4635940.768203
840.2035440.4070880.796456
850.2020030.4040070.797997
860.1756290.3512580.824371
870.1549360.3098720.845064
880.1431690.2863370.856831
890.1243770.2487530.875623
900.1189650.2379290.881035
910.102390.2047810.89761
920.0877070.1754140.912293
930.07558190.1511640.924418
940.07880060.1576010.921199
950.07070670.1414130.929293
960.05933140.1186630.940669
970.06503650.1300730.934964
980.05430720.1086140.945693
990.04475570.08951140.955244
1000.03994560.07989130.960054
1010.0356830.07136610.964317
1020.04244120.08488230.957559
1030.03633190.07266380.963668
1040.03230870.06461730.967691
1050.0389530.07790590.961047
1060.03460350.06920710.965396
1070.02834670.05669330.971653
1080.02749860.05499720.972501
1090.02237960.04475920.97762
1100.01855090.03710180.981449
1110.0148510.02970190.985149
1120.01590320.03180640.984097
1130.01368510.02737020.986315
1140.01861990.03723990.98138
1150.01800380.03600760.981996
1160.01755280.03510550.982447
1170.01475320.02950640.985247
1180.01480080.02960160.985199
1190.01217060.02434130.987829
1200.01089580.02179170.989104
1210.008952360.01790470.991048
1220.01376710.02753420.986233
1230.01163450.0232690.988365
1240.01017120.02034240.989829
1250.008447440.01689490.991553
1260.006929310.01385860.993071
1270.006202820.01240560.993797
1280.005109350.01021870.994891
1290.007318970.01463790.992681
1300.007766610.01553320.992233
1310.01578270.03156540.984217
1320.01879050.0375810.981209
1330.02005090.04010180.979949
1340.01928240.03856480.980718
1350.0156740.03134810.984326
1360.01337770.02675550.986622
1370.01071550.02143090.989285
1380.01306330.02612670.986937
1390.01132070.02264150.988679
1400.0130880.0261760.986912
1410.01971580.03943160.980284
1420.01788030.03576050.98212
1430.01431810.02863620.985682
1440.01552720.03105440.984473
1450.02789010.05578030.97211
1460.03460820.06921630.965392
1470.03632880.07265760.963671
1480.03284770.06569550.967152
1490.02737510.05475030.972625
1500.03742660.07485310.962573
1510.03268590.06537190.967314
1520.03360580.06721170.966394
1530.06679540.1335910.933205
1540.06574310.1314860.934257
1550.07400090.1480020.925999
1560.0632710.1265420.936729
1570.05639660.1127930.943603
1580.04917110.09834220.950829
1590.04837940.09675880.951621
1600.04141940.08283880.958581
1610.03401890.06803790.965981
1620.02796330.05592660.972037
1630.02375930.04751850.976241
1640.02033220.04066430.979668
1650.01772870.03545750.982271
1660.01827550.03655110.981724
1670.01471670.02943350.985283
1680.02141230.04282460.978588
1690.0212960.0425920.978704
1700.01943620.03887240.980564
1710.01865720.03731440.981343
1720.01511550.03023090.984885
1730.01518720.03037450.984813
1740.01684570.03369140.983154
1750.02203680.04407360.977963
1760.01790010.03580020.9821
1770.01451380.02902760.985486
1780.01180250.02360490.988198
1790.009230510.0184610.990769
1800.008047060.01609410.991953
1810.006516160.01303230.993484
1820.005256030.01051210.994744
1830.005294290.01058860.994706
1840.004264030.008528050.995736
1850.08973070.1794610.910269
1860.07743840.1548770.922562
1870.09184050.1836810.908159
1880.0811360.1622720.918864
1890.06858030.1371610.93142
1900.05677890.1135580.943221
1910.04760270.09520550.952397
1920.04085150.08170310.959148
1930.04648940.09297890.953511
1940.04591030.09182070.95409
1950.03878880.07757770.961211
1960.03174960.06349920.96825
1970.04455740.08911480.955443
1980.03663080.07326170.963369
1990.03434640.06869290.965654
2000.0287650.057530.971235
2010.02668810.05337620.973312
2020.02187370.04374740.978126
2030.02396670.04793340.976033
2040.03015590.06031180.969844
2050.03372420.06744840.966276
2060.02671930.05343850.973281
2070.02446520.04893040.975535
2080.0196950.039390.980305
2090.02241540.04483080.977585
2100.01922540.03845090.980775
2110.02218310.04436620.977817
2120.03829430.07658860.961706
2130.03021920.06043840.969781
2140.04156420.08312840.958436
2150.03632140.07264270.963679
2160.02841580.05683160.971584
2170.03199710.06399430.968003
2180.02786270.05572540.972137
2190.02565130.05130260.974349
2200.01958090.03916180.980419
2210.01715580.03431160.982844
2220.01279670.02559330.987203
2230.009753220.01950640.990247
2240.0079120.0158240.992088
2250.005597840.01119570.994402
2260.01162040.02324090.98838
2270.009058260.01811650.990942
2280.006810810.01362160.993189
2290.004971570.009943140.995028
2300.003566170.007132340.996434
2310.004056790.008113580.995943
2320.01045920.02091850.989541
2330.04433170.08866340.955668
2340.06358790.1271760.936412
2350.04820060.09640120.951799
2360.04203860.08407710.957961
2370.29140.5827990.7086
2380.2422670.4845340.757733
2390.2193440.4386890.780656
2400.1776210.3552410.822379
2410.1449620.2899240.855038
2420.1223360.2446710.877664
2430.1128680.2257370.887132
2440.1693690.3387390.830631
2450.1759560.3519120.824044
2460.1436450.2872890.856355
2470.1086970.2173940.891303
2480.09636120.1927220.903639
2490.07384480.147690.926155
2500.1176840.2353690.882316
2510.07673580.1534720.923264
2520.1770770.3541530.822923
2530.3371130.6742260.662887
2540.8847210.2305570.115279

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.394062 & 0.788123 & 0.605938 \tabularnewline
11 & 0.250477 & 0.500955 & 0.749523 \tabularnewline
12 & 0.758102 & 0.483797 & 0.241898 \tabularnewline
13 & 0.667724 & 0.664551 & 0.332276 \tabularnewline
14 & 0.607677 & 0.784646 & 0.392323 \tabularnewline
15 & 0.618769 & 0.762462 & 0.381231 \tabularnewline
16 & 0.598914 & 0.802172 & 0.401086 \tabularnewline
17 & 0.51038 & 0.979239 & 0.48962 \tabularnewline
18 & 0.859056 & 0.281889 & 0.140944 \tabularnewline
19 & 0.869187 & 0.261625 & 0.130813 \tabularnewline
20 & 0.826489 & 0.347023 & 0.173511 \tabularnewline
21 & 0.781883 & 0.436234 & 0.218117 \tabularnewline
22 & 0.724589 & 0.550822 & 0.275411 \tabularnewline
23 & 0.744367 & 0.511267 & 0.255633 \tabularnewline
24 & 0.688935 & 0.62213 & 0.311065 \tabularnewline
25 & 0.635831 & 0.728338 & 0.364169 \tabularnewline
26 & 0.57599 & 0.84802 & 0.42401 \tabularnewline
27 & 0.516928 & 0.966143 & 0.483072 \tabularnewline
28 & 0.498022 & 0.996044 & 0.501978 \tabularnewline
29 & 0.434902 & 0.869804 & 0.565098 \tabularnewline
30 & 0.411232 & 0.822465 & 0.588768 \tabularnewline
31 & 0.355664 & 0.711328 & 0.644336 \tabularnewline
32 & 0.335083 & 0.670166 & 0.664917 \tabularnewline
33 & 0.308061 & 0.616123 & 0.691939 \tabularnewline
34 & 0.257467 & 0.514934 & 0.742533 \tabularnewline
35 & 0.244538 & 0.489077 & 0.755462 \tabularnewline
36 & 0.338086 & 0.676172 & 0.661914 \tabularnewline
37 & 0.428705 & 0.85741 & 0.571295 \tabularnewline
38 & 0.426365 & 0.85273 & 0.573635 \tabularnewline
39 & 0.454728 & 0.909456 & 0.545272 \tabularnewline
40 & 0.428882 & 0.857764 & 0.571118 \tabularnewline
41 & 0.391354 & 0.782708 & 0.608646 \tabularnewline
42 & 0.372418 & 0.744836 & 0.627582 \tabularnewline
43 & 0.376734 & 0.753468 & 0.623266 \tabularnewline
44 & 0.336101 & 0.672203 & 0.663899 \tabularnewline
45 & 0.304793 & 0.609586 & 0.695207 \tabularnewline
46 & 0.569751 & 0.860499 & 0.430249 \tabularnewline
47 & 0.633878 & 0.732245 & 0.366122 \tabularnewline
48 & 0.587597 & 0.824806 & 0.412403 \tabularnewline
49 & 0.546284 & 0.907432 & 0.453716 \tabularnewline
50 & 0.537299 & 0.925402 & 0.462701 \tabularnewline
51 & 0.494757 & 0.989514 & 0.505243 \tabularnewline
52 & 0.448162 & 0.896324 & 0.551838 \tabularnewline
53 & 0.481596 & 0.963192 & 0.518404 \tabularnewline
54 & 0.437267 & 0.874535 & 0.562733 \tabularnewline
55 & 0.44749 & 0.894981 & 0.55251 \tabularnewline
56 & 0.434431 & 0.868863 & 0.565569 \tabularnewline
57 & 0.392164 & 0.784328 & 0.607836 \tabularnewline
58 & 0.362573 & 0.725145 & 0.637427 \tabularnewline
59 & 0.321624 & 0.643248 & 0.678376 \tabularnewline
60 & 0.328515 & 0.65703 & 0.671485 \tabularnewline
61 & 0.299895 & 0.59979 & 0.700105 \tabularnewline
62 & 0.264414 & 0.528828 & 0.735586 \tabularnewline
63 & 0.229983 & 0.459965 & 0.770017 \tabularnewline
64 & 0.200232 & 0.400465 & 0.799768 \tabularnewline
65 & 0.174944 & 0.349888 & 0.825056 \tabularnewline
66 & 0.162084 & 0.324169 & 0.837916 \tabularnewline
67 & 0.159514 & 0.319028 & 0.840486 \tabularnewline
68 & 0.262802 & 0.525604 & 0.737198 \tabularnewline
69 & 0.384445 & 0.76889 & 0.615555 \tabularnewline
70 & 0.348795 & 0.69759 & 0.651205 \tabularnewline
71 & 0.429711 & 0.859421 & 0.570289 \tabularnewline
72 & 0.391973 & 0.783946 & 0.608027 \tabularnewline
73 & 0.374247 & 0.748493 & 0.625753 \tabularnewline
74 & 0.347883 & 0.695765 & 0.652117 \tabularnewline
75 & 0.316184 & 0.632369 & 0.683816 \tabularnewline
76 & 0.389808 & 0.779616 & 0.610192 \tabularnewline
77 & 0.353853 & 0.707705 & 0.646147 \tabularnewline
78 & 0.335669 & 0.671338 & 0.664331 \tabularnewline
79 & 0.345446 & 0.690893 & 0.654554 \tabularnewline
80 & 0.316731 & 0.633462 & 0.683269 \tabularnewline
81 & 0.285189 & 0.570378 & 0.714811 \tabularnewline
82 & 0.254229 & 0.508459 & 0.745771 \tabularnewline
83 & 0.231797 & 0.463594 & 0.768203 \tabularnewline
84 & 0.203544 & 0.407088 & 0.796456 \tabularnewline
85 & 0.202003 & 0.404007 & 0.797997 \tabularnewline
86 & 0.175629 & 0.351258 & 0.824371 \tabularnewline
87 & 0.154936 & 0.309872 & 0.845064 \tabularnewline
88 & 0.143169 & 0.286337 & 0.856831 \tabularnewline
89 & 0.124377 & 0.248753 & 0.875623 \tabularnewline
90 & 0.118965 & 0.237929 & 0.881035 \tabularnewline
91 & 0.10239 & 0.204781 & 0.89761 \tabularnewline
92 & 0.087707 & 0.175414 & 0.912293 \tabularnewline
93 & 0.0755819 & 0.151164 & 0.924418 \tabularnewline
94 & 0.0788006 & 0.157601 & 0.921199 \tabularnewline
95 & 0.0707067 & 0.141413 & 0.929293 \tabularnewline
96 & 0.0593314 & 0.118663 & 0.940669 \tabularnewline
97 & 0.0650365 & 0.130073 & 0.934964 \tabularnewline
98 & 0.0543072 & 0.108614 & 0.945693 \tabularnewline
99 & 0.0447557 & 0.0895114 & 0.955244 \tabularnewline
100 & 0.0399456 & 0.0798913 & 0.960054 \tabularnewline
101 & 0.035683 & 0.0713661 & 0.964317 \tabularnewline
102 & 0.0424412 & 0.0848823 & 0.957559 \tabularnewline
103 & 0.0363319 & 0.0726638 & 0.963668 \tabularnewline
104 & 0.0323087 & 0.0646173 & 0.967691 \tabularnewline
105 & 0.038953 & 0.0779059 & 0.961047 \tabularnewline
106 & 0.0346035 & 0.0692071 & 0.965396 \tabularnewline
107 & 0.0283467 & 0.0566933 & 0.971653 \tabularnewline
108 & 0.0274986 & 0.0549972 & 0.972501 \tabularnewline
109 & 0.0223796 & 0.0447592 & 0.97762 \tabularnewline
110 & 0.0185509 & 0.0371018 & 0.981449 \tabularnewline
111 & 0.014851 & 0.0297019 & 0.985149 \tabularnewline
112 & 0.0159032 & 0.0318064 & 0.984097 \tabularnewline
113 & 0.0136851 & 0.0273702 & 0.986315 \tabularnewline
114 & 0.0186199 & 0.0372399 & 0.98138 \tabularnewline
115 & 0.0180038 & 0.0360076 & 0.981996 \tabularnewline
116 & 0.0175528 & 0.0351055 & 0.982447 \tabularnewline
117 & 0.0147532 & 0.0295064 & 0.985247 \tabularnewline
118 & 0.0148008 & 0.0296016 & 0.985199 \tabularnewline
119 & 0.0121706 & 0.0243413 & 0.987829 \tabularnewline
120 & 0.0108958 & 0.0217917 & 0.989104 \tabularnewline
121 & 0.00895236 & 0.0179047 & 0.991048 \tabularnewline
122 & 0.0137671 & 0.0275342 & 0.986233 \tabularnewline
123 & 0.0116345 & 0.023269 & 0.988365 \tabularnewline
124 & 0.0101712 & 0.0203424 & 0.989829 \tabularnewline
125 & 0.00844744 & 0.0168949 & 0.991553 \tabularnewline
126 & 0.00692931 & 0.0138586 & 0.993071 \tabularnewline
127 & 0.00620282 & 0.0124056 & 0.993797 \tabularnewline
128 & 0.00510935 & 0.0102187 & 0.994891 \tabularnewline
129 & 0.00731897 & 0.0146379 & 0.992681 \tabularnewline
130 & 0.00776661 & 0.0155332 & 0.992233 \tabularnewline
131 & 0.0157827 & 0.0315654 & 0.984217 \tabularnewline
132 & 0.0187905 & 0.037581 & 0.981209 \tabularnewline
133 & 0.0200509 & 0.0401018 & 0.979949 \tabularnewline
134 & 0.0192824 & 0.0385648 & 0.980718 \tabularnewline
135 & 0.015674 & 0.0313481 & 0.984326 \tabularnewline
136 & 0.0133777 & 0.0267555 & 0.986622 \tabularnewline
137 & 0.0107155 & 0.0214309 & 0.989285 \tabularnewline
138 & 0.0130633 & 0.0261267 & 0.986937 \tabularnewline
139 & 0.0113207 & 0.0226415 & 0.988679 \tabularnewline
140 & 0.013088 & 0.026176 & 0.986912 \tabularnewline
141 & 0.0197158 & 0.0394316 & 0.980284 \tabularnewline
142 & 0.0178803 & 0.0357605 & 0.98212 \tabularnewline
143 & 0.0143181 & 0.0286362 & 0.985682 \tabularnewline
144 & 0.0155272 & 0.0310544 & 0.984473 \tabularnewline
145 & 0.0278901 & 0.0557803 & 0.97211 \tabularnewline
146 & 0.0346082 & 0.0692163 & 0.965392 \tabularnewline
147 & 0.0363288 & 0.0726576 & 0.963671 \tabularnewline
148 & 0.0328477 & 0.0656955 & 0.967152 \tabularnewline
149 & 0.0273751 & 0.0547503 & 0.972625 \tabularnewline
150 & 0.0374266 & 0.0748531 & 0.962573 \tabularnewline
151 & 0.0326859 & 0.0653719 & 0.967314 \tabularnewline
152 & 0.0336058 & 0.0672117 & 0.966394 \tabularnewline
153 & 0.0667954 & 0.133591 & 0.933205 \tabularnewline
154 & 0.0657431 & 0.131486 & 0.934257 \tabularnewline
155 & 0.0740009 & 0.148002 & 0.925999 \tabularnewline
156 & 0.063271 & 0.126542 & 0.936729 \tabularnewline
157 & 0.0563966 & 0.112793 & 0.943603 \tabularnewline
158 & 0.0491711 & 0.0983422 & 0.950829 \tabularnewline
159 & 0.0483794 & 0.0967588 & 0.951621 \tabularnewline
160 & 0.0414194 & 0.0828388 & 0.958581 \tabularnewline
161 & 0.0340189 & 0.0680379 & 0.965981 \tabularnewline
162 & 0.0279633 & 0.0559266 & 0.972037 \tabularnewline
163 & 0.0237593 & 0.0475185 & 0.976241 \tabularnewline
164 & 0.0203322 & 0.0406643 & 0.979668 \tabularnewline
165 & 0.0177287 & 0.0354575 & 0.982271 \tabularnewline
166 & 0.0182755 & 0.0365511 & 0.981724 \tabularnewline
167 & 0.0147167 & 0.0294335 & 0.985283 \tabularnewline
168 & 0.0214123 & 0.0428246 & 0.978588 \tabularnewline
169 & 0.021296 & 0.042592 & 0.978704 \tabularnewline
170 & 0.0194362 & 0.0388724 & 0.980564 \tabularnewline
171 & 0.0186572 & 0.0373144 & 0.981343 \tabularnewline
172 & 0.0151155 & 0.0302309 & 0.984885 \tabularnewline
173 & 0.0151872 & 0.0303745 & 0.984813 \tabularnewline
174 & 0.0168457 & 0.0336914 & 0.983154 \tabularnewline
175 & 0.0220368 & 0.0440736 & 0.977963 \tabularnewline
176 & 0.0179001 & 0.0358002 & 0.9821 \tabularnewline
177 & 0.0145138 & 0.0290276 & 0.985486 \tabularnewline
178 & 0.0118025 & 0.0236049 & 0.988198 \tabularnewline
179 & 0.00923051 & 0.018461 & 0.990769 \tabularnewline
180 & 0.00804706 & 0.0160941 & 0.991953 \tabularnewline
181 & 0.00651616 & 0.0130323 & 0.993484 \tabularnewline
182 & 0.00525603 & 0.0105121 & 0.994744 \tabularnewline
183 & 0.00529429 & 0.0105886 & 0.994706 \tabularnewline
184 & 0.00426403 & 0.00852805 & 0.995736 \tabularnewline
185 & 0.0897307 & 0.179461 & 0.910269 \tabularnewline
186 & 0.0774384 & 0.154877 & 0.922562 \tabularnewline
187 & 0.0918405 & 0.183681 & 0.908159 \tabularnewline
188 & 0.081136 & 0.162272 & 0.918864 \tabularnewline
189 & 0.0685803 & 0.137161 & 0.93142 \tabularnewline
190 & 0.0567789 & 0.113558 & 0.943221 \tabularnewline
191 & 0.0476027 & 0.0952055 & 0.952397 \tabularnewline
192 & 0.0408515 & 0.0817031 & 0.959148 \tabularnewline
193 & 0.0464894 & 0.0929789 & 0.953511 \tabularnewline
194 & 0.0459103 & 0.0918207 & 0.95409 \tabularnewline
195 & 0.0387888 & 0.0775777 & 0.961211 \tabularnewline
196 & 0.0317496 & 0.0634992 & 0.96825 \tabularnewline
197 & 0.0445574 & 0.0891148 & 0.955443 \tabularnewline
198 & 0.0366308 & 0.0732617 & 0.963369 \tabularnewline
199 & 0.0343464 & 0.0686929 & 0.965654 \tabularnewline
200 & 0.028765 & 0.05753 & 0.971235 \tabularnewline
201 & 0.0266881 & 0.0533762 & 0.973312 \tabularnewline
202 & 0.0218737 & 0.0437474 & 0.978126 \tabularnewline
203 & 0.0239667 & 0.0479334 & 0.976033 \tabularnewline
204 & 0.0301559 & 0.0603118 & 0.969844 \tabularnewline
205 & 0.0337242 & 0.0674484 & 0.966276 \tabularnewline
206 & 0.0267193 & 0.0534385 & 0.973281 \tabularnewline
207 & 0.0244652 & 0.0489304 & 0.975535 \tabularnewline
208 & 0.019695 & 0.03939 & 0.980305 \tabularnewline
209 & 0.0224154 & 0.0448308 & 0.977585 \tabularnewline
210 & 0.0192254 & 0.0384509 & 0.980775 \tabularnewline
211 & 0.0221831 & 0.0443662 & 0.977817 \tabularnewline
212 & 0.0382943 & 0.0765886 & 0.961706 \tabularnewline
213 & 0.0302192 & 0.0604384 & 0.969781 \tabularnewline
214 & 0.0415642 & 0.0831284 & 0.958436 \tabularnewline
215 & 0.0363214 & 0.0726427 & 0.963679 \tabularnewline
216 & 0.0284158 & 0.0568316 & 0.971584 \tabularnewline
217 & 0.0319971 & 0.0639943 & 0.968003 \tabularnewline
218 & 0.0278627 & 0.0557254 & 0.972137 \tabularnewline
219 & 0.0256513 & 0.0513026 & 0.974349 \tabularnewline
220 & 0.0195809 & 0.0391618 & 0.980419 \tabularnewline
221 & 0.0171558 & 0.0343116 & 0.982844 \tabularnewline
222 & 0.0127967 & 0.0255933 & 0.987203 \tabularnewline
223 & 0.00975322 & 0.0195064 & 0.990247 \tabularnewline
224 & 0.007912 & 0.015824 & 0.992088 \tabularnewline
225 & 0.00559784 & 0.0111957 & 0.994402 \tabularnewline
226 & 0.0116204 & 0.0232409 & 0.98838 \tabularnewline
227 & 0.00905826 & 0.0181165 & 0.990942 \tabularnewline
228 & 0.00681081 & 0.0136216 & 0.993189 \tabularnewline
229 & 0.00497157 & 0.00994314 & 0.995028 \tabularnewline
230 & 0.00356617 & 0.00713234 & 0.996434 \tabularnewline
231 & 0.00405679 & 0.00811358 & 0.995943 \tabularnewline
232 & 0.0104592 & 0.0209185 & 0.989541 \tabularnewline
233 & 0.0443317 & 0.0886634 & 0.955668 \tabularnewline
234 & 0.0635879 & 0.127176 & 0.936412 \tabularnewline
235 & 0.0482006 & 0.0964012 & 0.951799 \tabularnewline
236 & 0.0420386 & 0.0840771 & 0.957961 \tabularnewline
237 & 0.2914 & 0.582799 & 0.7086 \tabularnewline
238 & 0.242267 & 0.484534 & 0.757733 \tabularnewline
239 & 0.219344 & 0.438689 & 0.780656 \tabularnewline
240 & 0.177621 & 0.355241 & 0.822379 \tabularnewline
241 & 0.144962 & 0.289924 & 0.855038 \tabularnewline
242 & 0.122336 & 0.244671 & 0.877664 \tabularnewline
243 & 0.112868 & 0.225737 & 0.887132 \tabularnewline
244 & 0.169369 & 0.338739 & 0.830631 \tabularnewline
245 & 0.175956 & 0.351912 & 0.824044 \tabularnewline
246 & 0.143645 & 0.287289 & 0.856355 \tabularnewline
247 & 0.108697 & 0.217394 & 0.891303 \tabularnewline
248 & 0.0963612 & 0.192722 & 0.903639 \tabularnewline
249 & 0.0738448 & 0.14769 & 0.926155 \tabularnewline
250 & 0.117684 & 0.235369 & 0.882316 \tabularnewline
251 & 0.0767358 & 0.153472 & 0.923264 \tabularnewline
252 & 0.177077 & 0.354153 & 0.822923 \tabularnewline
253 & 0.337113 & 0.674226 & 0.662887 \tabularnewline
254 & 0.884721 & 0.230557 & 0.115279 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253350&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]0.394062[/C][C]0.788123[/C][C]0.605938[/C][/ROW]
[ROW][C]11[/C][C]0.250477[/C][C]0.500955[/C][C]0.749523[/C][/ROW]
[ROW][C]12[/C][C]0.758102[/C][C]0.483797[/C][C]0.241898[/C][/ROW]
[ROW][C]13[/C][C]0.667724[/C][C]0.664551[/C][C]0.332276[/C][/ROW]
[ROW][C]14[/C][C]0.607677[/C][C]0.784646[/C][C]0.392323[/C][/ROW]
[ROW][C]15[/C][C]0.618769[/C][C]0.762462[/C][C]0.381231[/C][/ROW]
[ROW][C]16[/C][C]0.598914[/C][C]0.802172[/C][C]0.401086[/C][/ROW]
[ROW][C]17[/C][C]0.51038[/C][C]0.979239[/C][C]0.48962[/C][/ROW]
[ROW][C]18[/C][C]0.859056[/C][C]0.281889[/C][C]0.140944[/C][/ROW]
[ROW][C]19[/C][C]0.869187[/C][C]0.261625[/C][C]0.130813[/C][/ROW]
[ROW][C]20[/C][C]0.826489[/C][C]0.347023[/C][C]0.173511[/C][/ROW]
[ROW][C]21[/C][C]0.781883[/C][C]0.436234[/C][C]0.218117[/C][/ROW]
[ROW][C]22[/C][C]0.724589[/C][C]0.550822[/C][C]0.275411[/C][/ROW]
[ROW][C]23[/C][C]0.744367[/C][C]0.511267[/C][C]0.255633[/C][/ROW]
[ROW][C]24[/C][C]0.688935[/C][C]0.62213[/C][C]0.311065[/C][/ROW]
[ROW][C]25[/C][C]0.635831[/C][C]0.728338[/C][C]0.364169[/C][/ROW]
[ROW][C]26[/C][C]0.57599[/C][C]0.84802[/C][C]0.42401[/C][/ROW]
[ROW][C]27[/C][C]0.516928[/C][C]0.966143[/C][C]0.483072[/C][/ROW]
[ROW][C]28[/C][C]0.498022[/C][C]0.996044[/C][C]0.501978[/C][/ROW]
[ROW][C]29[/C][C]0.434902[/C][C]0.869804[/C][C]0.565098[/C][/ROW]
[ROW][C]30[/C][C]0.411232[/C][C]0.822465[/C][C]0.588768[/C][/ROW]
[ROW][C]31[/C][C]0.355664[/C][C]0.711328[/C][C]0.644336[/C][/ROW]
[ROW][C]32[/C][C]0.335083[/C][C]0.670166[/C][C]0.664917[/C][/ROW]
[ROW][C]33[/C][C]0.308061[/C][C]0.616123[/C][C]0.691939[/C][/ROW]
[ROW][C]34[/C][C]0.257467[/C][C]0.514934[/C][C]0.742533[/C][/ROW]
[ROW][C]35[/C][C]0.244538[/C][C]0.489077[/C][C]0.755462[/C][/ROW]
[ROW][C]36[/C][C]0.338086[/C][C]0.676172[/C][C]0.661914[/C][/ROW]
[ROW][C]37[/C][C]0.428705[/C][C]0.85741[/C][C]0.571295[/C][/ROW]
[ROW][C]38[/C][C]0.426365[/C][C]0.85273[/C][C]0.573635[/C][/ROW]
[ROW][C]39[/C][C]0.454728[/C][C]0.909456[/C][C]0.545272[/C][/ROW]
[ROW][C]40[/C][C]0.428882[/C][C]0.857764[/C][C]0.571118[/C][/ROW]
[ROW][C]41[/C][C]0.391354[/C][C]0.782708[/C][C]0.608646[/C][/ROW]
[ROW][C]42[/C][C]0.372418[/C][C]0.744836[/C][C]0.627582[/C][/ROW]
[ROW][C]43[/C][C]0.376734[/C][C]0.753468[/C][C]0.623266[/C][/ROW]
[ROW][C]44[/C][C]0.336101[/C][C]0.672203[/C][C]0.663899[/C][/ROW]
[ROW][C]45[/C][C]0.304793[/C][C]0.609586[/C][C]0.695207[/C][/ROW]
[ROW][C]46[/C][C]0.569751[/C][C]0.860499[/C][C]0.430249[/C][/ROW]
[ROW][C]47[/C][C]0.633878[/C][C]0.732245[/C][C]0.366122[/C][/ROW]
[ROW][C]48[/C][C]0.587597[/C][C]0.824806[/C][C]0.412403[/C][/ROW]
[ROW][C]49[/C][C]0.546284[/C][C]0.907432[/C][C]0.453716[/C][/ROW]
[ROW][C]50[/C][C]0.537299[/C][C]0.925402[/C][C]0.462701[/C][/ROW]
[ROW][C]51[/C][C]0.494757[/C][C]0.989514[/C][C]0.505243[/C][/ROW]
[ROW][C]52[/C][C]0.448162[/C][C]0.896324[/C][C]0.551838[/C][/ROW]
[ROW][C]53[/C][C]0.481596[/C][C]0.963192[/C][C]0.518404[/C][/ROW]
[ROW][C]54[/C][C]0.437267[/C][C]0.874535[/C][C]0.562733[/C][/ROW]
[ROW][C]55[/C][C]0.44749[/C][C]0.894981[/C][C]0.55251[/C][/ROW]
[ROW][C]56[/C][C]0.434431[/C][C]0.868863[/C][C]0.565569[/C][/ROW]
[ROW][C]57[/C][C]0.392164[/C][C]0.784328[/C][C]0.607836[/C][/ROW]
[ROW][C]58[/C][C]0.362573[/C][C]0.725145[/C][C]0.637427[/C][/ROW]
[ROW][C]59[/C][C]0.321624[/C][C]0.643248[/C][C]0.678376[/C][/ROW]
[ROW][C]60[/C][C]0.328515[/C][C]0.65703[/C][C]0.671485[/C][/ROW]
[ROW][C]61[/C][C]0.299895[/C][C]0.59979[/C][C]0.700105[/C][/ROW]
[ROW][C]62[/C][C]0.264414[/C][C]0.528828[/C][C]0.735586[/C][/ROW]
[ROW][C]63[/C][C]0.229983[/C][C]0.459965[/C][C]0.770017[/C][/ROW]
[ROW][C]64[/C][C]0.200232[/C][C]0.400465[/C][C]0.799768[/C][/ROW]
[ROW][C]65[/C][C]0.174944[/C][C]0.349888[/C][C]0.825056[/C][/ROW]
[ROW][C]66[/C][C]0.162084[/C][C]0.324169[/C][C]0.837916[/C][/ROW]
[ROW][C]67[/C][C]0.159514[/C][C]0.319028[/C][C]0.840486[/C][/ROW]
[ROW][C]68[/C][C]0.262802[/C][C]0.525604[/C][C]0.737198[/C][/ROW]
[ROW][C]69[/C][C]0.384445[/C][C]0.76889[/C][C]0.615555[/C][/ROW]
[ROW][C]70[/C][C]0.348795[/C][C]0.69759[/C][C]0.651205[/C][/ROW]
[ROW][C]71[/C][C]0.429711[/C][C]0.859421[/C][C]0.570289[/C][/ROW]
[ROW][C]72[/C][C]0.391973[/C][C]0.783946[/C][C]0.608027[/C][/ROW]
[ROW][C]73[/C][C]0.374247[/C][C]0.748493[/C][C]0.625753[/C][/ROW]
[ROW][C]74[/C][C]0.347883[/C][C]0.695765[/C][C]0.652117[/C][/ROW]
[ROW][C]75[/C][C]0.316184[/C][C]0.632369[/C][C]0.683816[/C][/ROW]
[ROW][C]76[/C][C]0.389808[/C][C]0.779616[/C][C]0.610192[/C][/ROW]
[ROW][C]77[/C][C]0.353853[/C][C]0.707705[/C][C]0.646147[/C][/ROW]
[ROW][C]78[/C][C]0.335669[/C][C]0.671338[/C][C]0.664331[/C][/ROW]
[ROW][C]79[/C][C]0.345446[/C][C]0.690893[/C][C]0.654554[/C][/ROW]
[ROW][C]80[/C][C]0.316731[/C][C]0.633462[/C][C]0.683269[/C][/ROW]
[ROW][C]81[/C][C]0.285189[/C][C]0.570378[/C][C]0.714811[/C][/ROW]
[ROW][C]82[/C][C]0.254229[/C][C]0.508459[/C][C]0.745771[/C][/ROW]
[ROW][C]83[/C][C]0.231797[/C][C]0.463594[/C][C]0.768203[/C][/ROW]
[ROW][C]84[/C][C]0.203544[/C][C]0.407088[/C][C]0.796456[/C][/ROW]
[ROW][C]85[/C][C]0.202003[/C][C]0.404007[/C][C]0.797997[/C][/ROW]
[ROW][C]86[/C][C]0.175629[/C][C]0.351258[/C][C]0.824371[/C][/ROW]
[ROW][C]87[/C][C]0.154936[/C][C]0.309872[/C][C]0.845064[/C][/ROW]
[ROW][C]88[/C][C]0.143169[/C][C]0.286337[/C][C]0.856831[/C][/ROW]
[ROW][C]89[/C][C]0.124377[/C][C]0.248753[/C][C]0.875623[/C][/ROW]
[ROW][C]90[/C][C]0.118965[/C][C]0.237929[/C][C]0.881035[/C][/ROW]
[ROW][C]91[/C][C]0.10239[/C][C]0.204781[/C][C]0.89761[/C][/ROW]
[ROW][C]92[/C][C]0.087707[/C][C]0.175414[/C][C]0.912293[/C][/ROW]
[ROW][C]93[/C][C]0.0755819[/C][C]0.151164[/C][C]0.924418[/C][/ROW]
[ROW][C]94[/C][C]0.0788006[/C][C]0.157601[/C][C]0.921199[/C][/ROW]
[ROW][C]95[/C][C]0.0707067[/C][C]0.141413[/C][C]0.929293[/C][/ROW]
[ROW][C]96[/C][C]0.0593314[/C][C]0.118663[/C][C]0.940669[/C][/ROW]
[ROW][C]97[/C][C]0.0650365[/C][C]0.130073[/C][C]0.934964[/C][/ROW]
[ROW][C]98[/C][C]0.0543072[/C][C]0.108614[/C][C]0.945693[/C][/ROW]
[ROW][C]99[/C][C]0.0447557[/C][C]0.0895114[/C][C]0.955244[/C][/ROW]
[ROW][C]100[/C][C]0.0399456[/C][C]0.0798913[/C][C]0.960054[/C][/ROW]
[ROW][C]101[/C][C]0.035683[/C][C]0.0713661[/C][C]0.964317[/C][/ROW]
[ROW][C]102[/C][C]0.0424412[/C][C]0.0848823[/C][C]0.957559[/C][/ROW]
[ROW][C]103[/C][C]0.0363319[/C][C]0.0726638[/C][C]0.963668[/C][/ROW]
[ROW][C]104[/C][C]0.0323087[/C][C]0.0646173[/C][C]0.967691[/C][/ROW]
[ROW][C]105[/C][C]0.038953[/C][C]0.0779059[/C][C]0.961047[/C][/ROW]
[ROW][C]106[/C][C]0.0346035[/C][C]0.0692071[/C][C]0.965396[/C][/ROW]
[ROW][C]107[/C][C]0.0283467[/C][C]0.0566933[/C][C]0.971653[/C][/ROW]
[ROW][C]108[/C][C]0.0274986[/C][C]0.0549972[/C][C]0.972501[/C][/ROW]
[ROW][C]109[/C][C]0.0223796[/C][C]0.0447592[/C][C]0.97762[/C][/ROW]
[ROW][C]110[/C][C]0.0185509[/C][C]0.0371018[/C][C]0.981449[/C][/ROW]
[ROW][C]111[/C][C]0.014851[/C][C]0.0297019[/C][C]0.985149[/C][/ROW]
[ROW][C]112[/C][C]0.0159032[/C][C]0.0318064[/C][C]0.984097[/C][/ROW]
[ROW][C]113[/C][C]0.0136851[/C][C]0.0273702[/C][C]0.986315[/C][/ROW]
[ROW][C]114[/C][C]0.0186199[/C][C]0.0372399[/C][C]0.98138[/C][/ROW]
[ROW][C]115[/C][C]0.0180038[/C][C]0.0360076[/C][C]0.981996[/C][/ROW]
[ROW][C]116[/C][C]0.0175528[/C][C]0.0351055[/C][C]0.982447[/C][/ROW]
[ROW][C]117[/C][C]0.0147532[/C][C]0.0295064[/C][C]0.985247[/C][/ROW]
[ROW][C]118[/C][C]0.0148008[/C][C]0.0296016[/C][C]0.985199[/C][/ROW]
[ROW][C]119[/C][C]0.0121706[/C][C]0.0243413[/C][C]0.987829[/C][/ROW]
[ROW][C]120[/C][C]0.0108958[/C][C]0.0217917[/C][C]0.989104[/C][/ROW]
[ROW][C]121[/C][C]0.00895236[/C][C]0.0179047[/C][C]0.991048[/C][/ROW]
[ROW][C]122[/C][C]0.0137671[/C][C]0.0275342[/C][C]0.986233[/C][/ROW]
[ROW][C]123[/C][C]0.0116345[/C][C]0.023269[/C][C]0.988365[/C][/ROW]
[ROW][C]124[/C][C]0.0101712[/C][C]0.0203424[/C][C]0.989829[/C][/ROW]
[ROW][C]125[/C][C]0.00844744[/C][C]0.0168949[/C][C]0.991553[/C][/ROW]
[ROW][C]126[/C][C]0.00692931[/C][C]0.0138586[/C][C]0.993071[/C][/ROW]
[ROW][C]127[/C][C]0.00620282[/C][C]0.0124056[/C][C]0.993797[/C][/ROW]
[ROW][C]128[/C][C]0.00510935[/C][C]0.0102187[/C][C]0.994891[/C][/ROW]
[ROW][C]129[/C][C]0.00731897[/C][C]0.0146379[/C][C]0.992681[/C][/ROW]
[ROW][C]130[/C][C]0.00776661[/C][C]0.0155332[/C][C]0.992233[/C][/ROW]
[ROW][C]131[/C][C]0.0157827[/C][C]0.0315654[/C][C]0.984217[/C][/ROW]
[ROW][C]132[/C][C]0.0187905[/C][C]0.037581[/C][C]0.981209[/C][/ROW]
[ROW][C]133[/C][C]0.0200509[/C][C]0.0401018[/C][C]0.979949[/C][/ROW]
[ROW][C]134[/C][C]0.0192824[/C][C]0.0385648[/C][C]0.980718[/C][/ROW]
[ROW][C]135[/C][C]0.015674[/C][C]0.0313481[/C][C]0.984326[/C][/ROW]
[ROW][C]136[/C][C]0.0133777[/C][C]0.0267555[/C][C]0.986622[/C][/ROW]
[ROW][C]137[/C][C]0.0107155[/C][C]0.0214309[/C][C]0.989285[/C][/ROW]
[ROW][C]138[/C][C]0.0130633[/C][C]0.0261267[/C][C]0.986937[/C][/ROW]
[ROW][C]139[/C][C]0.0113207[/C][C]0.0226415[/C][C]0.988679[/C][/ROW]
[ROW][C]140[/C][C]0.013088[/C][C]0.026176[/C][C]0.986912[/C][/ROW]
[ROW][C]141[/C][C]0.0197158[/C][C]0.0394316[/C][C]0.980284[/C][/ROW]
[ROW][C]142[/C][C]0.0178803[/C][C]0.0357605[/C][C]0.98212[/C][/ROW]
[ROW][C]143[/C][C]0.0143181[/C][C]0.0286362[/C][C]0.985682[/C][/ROW]
[ROW][C]144[/C][C]0.0155272[/C][C]0.0310544[/C][C]0.984473[/C][/ROW]
[ROW][C]145[/C][C]0.0278901[/C][C]0.0557803[/C][C]0.97211[/C][/ROW]
[ROW][C]146[/C][C]0.0346082[/C][C]0.0692163[/C][C]0.965392[/C][/ROW]
[ROW][C]147[/C][C]0.0363288[/C][C]0.0726576[/C][C]0.963671[/C][/ROW]
[ROW][C]148[/C][C]0.0328477[/C][C]0.0656955[/C][C]0.967152[/C][/ROW]
[ROW][C]149[/C][C]0.0273751[/C][C]0.0547503[/C][C]0.972625[/C][/ROW]
[ROW][C]150[/C][C]0.0374266[/C][C]0.0748531[/C][C]0.962573[/C][/ROW]
[ROW][C]151[/C][C]0.0326859[/C][C]0.0653719[/C][C]0.967314[/C][/ROW]
[ROW][C]152[/C][C]0.0336058[/C][C]0.0672117[/C][C]0.966394[/C][/ROW]
[ROW][C]153[/C][C]0.0667954[/C][C]0.133591[/C][C]0.933205[/C][/ROW]
[ROW][C]154[/C][C]0.0657431[/C][C]0.131486[/C][C]0.934257[/C][/ROW]
[ROW][C]155[/C][C]0.0740009[/C][C]0.148002[/C][C]0.925999[/C][/ROW]
[ROW][C]156[/C][C]0.063271[/C][C]0.126542[/C][C]0.936729[/C][/ROW]
[ROW][C]157[/C][C]0.0563966[/C][C]0.112793[/C][C]0.943603[/C][/ROW]
[ROW][C]158[/C][C]0.0491711[/C][C]0.0983422[/C][C]0.950829[/C][/ROW]
[ROW][C]159[/C][C]0.0483794[/C][C]0.0967588[/C][C]0.951621[/C][/ROW]
[ROW][C]160[/C][C]0.0414194[/C][C]0.0828388[/C][C]0.958581[/C][/ROW]
[ROW][C]161[/C][C]0.0340189[/C][C]0.0680379[/C][C]0.965981[/C][/ROW]
[ROW][C]162[/C][C]0.0279633[/C][C]0.0559266[/C][C]0.972037[/C][/ROW]
[ROW][C]163[/C][C]0.0237593[/C][C]0.0475185[/C][C]0.976241[/C][/ROW]
[ROW][C]164[/C][C]0.0203322[/C][C]0.0406643[/C][C]0.979668[/C][/ROW]
[ROW][C]165[/C][C]0.0177287[/C][C]0.0354575[/C][C]0.982271[/C][/ROW]
[ROW][C]166[/C][C]0.0182755[/C][C]0.0365511[/C][C]0.981724[/C][/ROW]
[ROW][C]167[/C][C]0.0147167[/C][C]0.0294335[/C][C]0.985283[/C][/ROW]
[ROW][C]168[/C][C]0.0214123[/C][C]0.0428246[/C][C]0.978588[/C][/ROW]
[ROW][C]169[/C][C]0.021296[/C][C]0.042592[/C][C]0.978704[/C][/ROW]
[ROW][C]170[/C][C]0.0194362[/C][C]0.0388724[/C][C]0.980564[/C][/ROW]
[ROW][C]171[/C][C]0.0186572[/C][C]0.0373144[/C][C]0.981343[/C][/ROW]
[ROW][C]172[/C][C]0.0151155[/C][C]0.0302309[/C][C]0.984885[/C][/ROW]
[ROW][C]173[/C][C]0.0151872[/C][C]0.0303745[/C][C]0.984813[/C][/ROW]
[ROW][C]174[/C][C]0.0168457[/C][C]0.0336914[/C][C]0.983154[/C][/ROW]
[ROW][C]175[/C][C]0.0220368[/C][C]0.0440736[/C][C]0.977963[/C][/ROW]
[ROW][C]176[/C][C]0.0179001[/C][C]0.0358002[/C][C]0.9821[/C][/ROW]
[ROW][C]177[/C][C]0.0145138[/C][C]0.0290276[/C][C]0.985486[/C][/ROW]
[ROW][C]178[/C][C]0.0118025[/C][C]0.0236049[/C][C]0.988198[/C][/ROW]
[ROW][C]179[/C][C]0.00923051[/C][C]0.018461[/C][C]0.990769[/C][/ROW]
[ROW][C]180[/C][C]0.00804706[/C][C]0.0160941[/C][C]0.991953[/C][/ROW]
[ROW][C]181[/C][C]0.00651616[/C][C]0.0130323[/C][C]0.993484[/C][/ROW]
[ROW][C]182[/C][C]0.00525603[/C][C]0.0105121[/C][C]0.994744[/C][/ROW]
[ROW][C]183[/C][C]0.00529429[/C][C]0.0105886[/C][C]0.994706[/C][/ROW]
[ROW][C]184[/C][C]0.00426403[/C][C]0.00852805[/C][C]0.995736[/C][/ROW]
[ROW][C]185[/C][C]0.0897307[/C][C]0.179461[/C][C]0.910269[/C][/ROW]
[ROW][C]186[/C][C]0.0774384[/C][C]0.154877[/C][C]0.922562[/C][/ROW]
[ROW][C]187[/C][C]0.0918405[/C][C]0.183681[/C][C]0.908159[/C][/ROW]
[ROW][C]188[/C][C]0.081136[/C][C]0.162272[/C][C]0.918864[/C][/ROW]
[ROW][C]189[/C][C]0.0685803[/C][C]0.137161[/C][C]0.93142[/C][/ROW]
[ROW][C]190[/C][C]0.0567789[/C][C]0.113558[/C][C]0.943221[/C][/ROW]
[ROW][C]191[/C][C]0.0476027[/C][C]0.0952055[/C][C]0.952397[/C][/ROW]
[ROW][C]192[/C][C]0.0408515[/C][C]0.0817031[/C][C]0.959148[/C][/ROW]
[ROW][C]193[/C][C]0.0464894[/C][C]0.0929789[/C][C]0.953511[/C][/ROW]
[ROW][C]194[/C][C]0.0459103[/C][C]0.0918207[/C][C]0.95409[/C][/ROW]
[ROW][C]195[/C][C]0.0387888[/C][C]0.0775777[/C][C]0.961211[/C][/ROW]
[ROW][C]196[/C][C]0.0317496[/C][C]0.0634992[/C][C]0.96825[/C][/ROW]
[ROW][C]197[/C][C]0.0445574[/C][C]0.0891148[/C][C]0.955443[/C][/ROW]
[ROW][C]198[/C][C]0.0366308[/C][C]0.0732617[/C][C]0.963369[/C][/ROW]
[ROW][C]199[/C][C]0.0343464[/C][C]0.0686929[/C][C]0.965654[/C][/ROW]
[ROW][C]200[/C][C]0.028765[/C][C]0.05753[/C][C]0.971235[/C][/ROW]
[ROW][C]201[/C][C]0.0266881[/C][C]0.0533762[/C][C]0.973312[/C][/ROW]
[ROW][C]202[/C][C]0.0218737[/C][C]0.0437474[/C][C]0.978126[/C][/ROW]
[ROW][C]203[/C][C]0.0239667[/C][C]0.0479334[/C][C]0.976033[/C][/ROW]
[ROW][C]204[/C][C]0.0301559[/C][C]0.0603118[/C][C]0.969844[/C][/ROW]
[ROW][C]205[/C][C]0.0337242[/C][C]0.0674484[/C][C]0.966276[/C][/ROW]
[ROW][C]206[/C][C]0.0267193[/C][C]0.0534385[/C][C]0.973281[/C][/ROW]
[ROW][C]207[/C][C]0.0244652[/C][C]0.0489304[/C][C]0.975535[/C][/ROW]
[ROW][C]208[/C][C]0.019695[/C][C]0.03939[/C][C]0.980305[/C][/ROW]
[ROW][C]209[/C][C]0.0224154[/C][C]0.0448308[/C][C]0.977585[/C][/ROW]
[ROW][C]210[/C][C]0.0192254[/C][C]0.0384509[/C][C]0.980775[/C][/ROW]
[ROW][C]211[/C][C]0.0221831[/C][C]0.0443662[/C][C]0.977817[/C][/ROW]
[ROW][C]212[/C][C]0.0382943[/C][C]0.0765886[/C][C]0.961706[/C][/ROW]
[ROW][C]213[/C][C]0.0302192[/C][C]0.0604384[/C][C]0.969781[/C][/ROW]
[ROW][C]214[/C][C]0.0415642[/C][C]0.0831284[/C][C]0.958436[/C][/ROW]
[ROW][C]215[/C][C]0.0363214[/C][C]0.0726427[/C][C]0.963679[/C][/ROW]
[ROW][C]216[/C][C]0.0284158[/C][C]0.0568316[/C][C]0.971584[/C][/ROW]
[ROW][C]217[/C][C]0.0319971[/C][C]0.0639943[/C][C]0.968003[/C][/ROW]
[ROW][C]218[/C][C]0.0278627[/C][C]0.0557254[/C][C]0.972137[/C][/ROW]
[ROW][C]219[/C][C]0.0256513[/C][C]0.0513026[/C][C]0.974349[/C][/ROW]
[ROW][C]220[/C][C]0.0195809[/C][C]0.0391618[/C][C]0.980419[/C][/ROW]
[ROW][C]221[/C][C]0.0171558[/C][C]0.0343116[/C][C]0.982844[/C][/ROW]
[ROW][C]222[/C][C]0.0127967[/C][C]0.0255933[/C][C]0.987203[/C][/ROW]
[ROW][C]223[/C][C]0.00975322[/C][C]0.0195064[/C][C]0.990247[/C][/ROW]
[ROW][C]224[/C][C]0.007912[/C][C]0.015824[/C][C]0.992088[/C][/ROW]
[ROW][C]225[/C][C]0.00559784[/C][C]0.0111957[/C][C]0.994402[/C][/ROW]
[ROW][C]226[/C][C]0.0116204[/C][C]0.0232409[/C][C]0.98838[/C][/ROW]
[ROW][C]227[/C][C]0.00905826[/C][C]0.0181165[/C][C]0.990942[/C][/ROW]
[ROW][C]228[/C][C]0.00681081[/C][C]0.0136216[/C][C]0.993189[/C][/ROW]
[ROW][C]229[/C][C]0.00497157[/C][C]0.00994314[/C][C]0.995028[/C][/ROW]
[ROW][C]230[/C][C]0.00356617[/C][C]0.00713234[/C][C]0.996434[/C][/ROW]
[ROW][C]231[/C][C]0.00405679[/C][C]0.00811358[/C][C]0.995943[/C][/ROW]
[ROW][C]232[/C][C]0.0104592[/C][C]0.0209185[/C][C]0.989541[/C][/ROW]
[ROW][C]233[/C][C]0.0443317[/C][C]0.0886634[/C][C]0.955668[/C][/ROW]
[ROW][C]234[/C][C]0.0635879[/C][C]0.127176[/C][C]0.936412[/C][/ROW]
[ROW][C]235[/C][C]0.0482006[/C][C]0.0964012[/C][C]0.951799[/C][/ROW]
[ROW][C]236[/C][C]0.0420386[/C][C]0.0840771[/C][C]0.957961[/C][/ROW]
[ROW][C]237[/C][C]0.2914[/C][C]0.582799[/C][C]0.7086[/C][/ROW]
[ROW][C]238[/C][C]0.242267[/C][C]0.484534[/C][C]0.757733[/C][/ROW]
[ROW][C]239[/C][C]0.219344[/C][C]0.438689[/C][C]0.780656[/C][/ROW]
[ROW][C]240[/C][C]0.177621[/C][C]0.355241[/C][C]0.822379[/C][/ROW]
[ROW][C]241[/C][C]0.144962[/C][C]0.289924[/C][C]0.855038[/C][/ROW]
[ROW][C]242[/C][C]0.122336[/C][C]0.244671[/C][C]0.877664[/C][/ROW]
[ROW][C]243[/C][C]0.112868[/C][C]0.225737[/C][C]0.887132[/C][/ROW]
[ROW][C]244[/C][C]0.169369[/C][C]0.338739[/C][C]0.830631[/C][/ROW]
[ROW][C]245[/C][C]0.175956[/C][C]0.351912[/C][C]0.824044[/C][/ROW]
[ROW][C]246[/C][C]0.143645[/C][C]0.287289[/C][C]0.856355[/C][/ROW]
[ROW][C]247[/C][C]0.108697[/C][C]0.217394[/C][C]0.891303[/C][/ROW]
[ROW][C]248[/C][C]0.0963612[/C][C]0.192722[/C][C]0.903639[/C][/ROW]
[ROW][C]249[/C][C]0.0738448[/C][C]0.14769[/C][C]0.926155[/C][/ROW]
[ROW][C]250[/C][C]0.117684[/C][C]0.235369[/C][C]0.882316[/C][/ROW]
[ROW][C]251[/C][C]0.0767358[/C][C]0.153472[/C][C]0.923264[/C][/ROW]
[ROW][C]252[/C][C]0.177077[/C][C]0.354153[/C][C]0.822923[/C][/ROW]
[ROW][C]253[/C][C]0.337113[/C][C]0.674226[/C][C]0.662887[/C][/ROW]
[ROW][C]254[/C][C]0.884721[/C][C]0.230557[/C][C]0.115279[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253350&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253350&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
100.3940620.7881230.605938
110.2504770.5009550.749523
120.7581020.4837970.241898
130.6677240.6645510.332276
140.6076770.7846460.392323
150.6187690.7624620.381231
160.5989140.8021720.401086
170.510380.9792390.48962
180.8590560.2818890.140944
190.8691870.2616250.130813
200.8264890.3470230.173511
210.7818830.4362340.218117
220.7245890.5508220.275411
230.7443670.5112670.255633
240.6889350.622130.311065
250.6358310.7283380.364169
260.575990.848020.42401
270.5169280.9661430.483072
280.4980220.9960440.501978
290.4349020.8698040.565098
300.4112320.8224650.588768
310.3556640.7113280.644336
320.3350830.6701660.664917
330.3080610.6161230.691939
340.2574670.5149340.742533
350.2445380.4890770.755462
360.3380860.6761720.661914
370.4287050.857410.571295
380.4263650.852730.573635
390.4547280.9094560.545272
400.4288820.8577640.571118
410.3913540.7827080.608646
420.3724180.7448360.627582
430.3767340.7534680.623266
440.3361010.6722030.663899
450.3047930.6095860.695207
460.5697510.8604990.430249
470.6338780.7322450.366122
480.5875970.8248060.412403
490.5462840.9074320.453716
500.5372990.9254020.462701
510.4947570.9895140.505243
520.4481620.8963240.551838
530.4815960.9631920.518404
540.4372670.8745350.562733
550.447490.8949810.55251
560.4344310.8688630.565569
570.3921640.7843280.607836
580.3625730.7251450.637427
590.3216240.6432480.678376
600.3285150.657030.671485
610.2998950.599790.700105
620.2644140.5288280.735586
630.2299830.4599650.770017
640.2002320.4004650.799768
650.1749440.3498880.825056
660.1620840.3241690.837916
670.1595140.3190280.840486
680.2628020.5256040.737198
690.3844450.768890.615555
700.3487950.697590.651205
710.4297110.8594210.570289
720.3919730.7839460.608027
730.3742470.7484930.625753
740.3478830.6957650.652117
750.3161840.6323690.683816
760.3898080.7796160.610192
770.3538530.7077050.646147
780.3356690.6713380.664331
790.3454460.6908930.654554
800.3167310.6334620.683269
810.2851890.5703780.714811
820.2542290.5084590.745771
830.2317970.4635940.768203
840.2035440.4070880.796456
850.2020030.4040070.797997
860.1756290.3512580.824371
870.1549360.3098720.845064
880.1431690.2863370.856831
890.1243770.2487530.875623
900.1189650.2379290.881035
910.102390.2047810.89761
920.0877070.1754140.912293
930.07558190.1511640.924418
940.07880060.1576010.921199
950.07070670.1414130.929293
960.05933140.1186630.940669
970.06503650.1300730.934964
980.05430720.1086140.945693
990.04475570.08951140.955244
1000.03994560.07989130.960054
1010.0356830.07136610.964317
1020.04244120.08488230.957559
1030.03633190.07266380.963668
1040.03230870.06461730.967691
1050.0389530.07790590.961047
1060.03460350.06920710.965396
1070.02834670.05669330.971653
1080.02749860.05499720.972501
1090.02237960.04475920.97762
1100.01855090.03710180.981449
1110.0148510.02970190.985149
1120.01590320.03180640.984097
1130.01368510.02737020.986315
1140.01861990.03723990.98138
1150.01800380.03600760.981996
1160.01755280.03510550.982447
1170.01475320.02950640.985247
1180.01480080.02960160.985199
1190.01217060.02434130.987829
1200.01089580.02179170.989104
1210.008952360.01790470.991048
1220.01376710.02753420.986233
1230.01163450.0232690.988365
1240.01017120.02034240.989829
1250.008447440.01689490.991553
1260.006929310.01385860.993071
1270.006202820.01240560.993797
1280.005109350.01021870.994891
1290.007318970.01463790.992681
1300.007766610.01553320.992233
1310.01578270.03156540.984217
1320.01879050.0375810.981209
1330.02005090.04010180.979949
1340.01928240.03856480.980718
1350.0156740.03134810.984326
1360.01337770.02675550.986622
1370.01071550.02143090.989285
1380.01306330.02612670.986937
1390.01132070.02264150.988679
1400.0130880.0261760.986912
1410.01971580.03943160.980284
1420.01788030.03576050.98212
1430.01431810.02863620.985682
1440.01552720.03105440.984473
1450.02789010.05578030.97211
1460.03460820.06921630.965392
1470.03632880.07265760.963671
1480.03284770.06569550.967152
1490.02737510.05475030.972625
1500.03742660.07485310.962573
1510.03268590.06537190.967314
1520.03360580.06721170.966394
1530.06679540.1335910.933205
1540.06574310.1314860.934257
1550.07400090.1480020.925999
1560.0632710.1265420.936729
1570.05639660.1127930.943603
1580.04917110.09834220.950829
1590.04837940.09675880.951621
1600.04141940.08283880.958581
1610.03401890.06803790.965981
1620.02796330.05592660.972037
1630.02375930.04751850.976241
1640.02033220.04066430.979668
1650.01772870.03545750.982271
1660.01827550.03655110.981724
1670.01471670.02943350.985283
1680.02141230.04282460.978588
1690.0212960.0425920.978704
1700.01943620.03887240.980564
1710.01865720.03731440.981343
1720.01511550.03023090.984885
1730.01518720.03037450.984813
1740.01684570.03369140.983154
1750.02203680.04407360.977963
1760.01790010.03580020.9821
1770.01451380.02902760.985486
1780.01180250.02360490.988198
1790.009230510.0184610.990769
1800.008047060.01609410.991953
1810.006516160.01303230.993484
1820.005256030.01051210.994744
1830.005294290.01058860.994706
1840.004264030.008528050.995736
1850.08973070.1794610.910269
1860.07743840.1548770.922562
1870.09184050.1836810.908159
1880.0811360.1622720.918864
1890.06858030.1371610.93142
1900.05677890.1135580.943221
1910.04760270.09520550.952397
1920.04085150.08170310.959148
1930.04648940.09297890.953511
1940.04591030.09182070.95409
1950.03878880.07757770.961211
1960.03174960.06349920.96825
1970.04455740.08911480.955443
1980.03663080.07326170.963369
1990.03434640.06869290.965654
2000.0287650.057530.971235
2010.02668810.05337620.973312
2020.02187370.04374740.978126
2030.02396670.04793340.976033
2040.03015590.06031180.969844
2050.03372420.06744840.966276
2060.02671930.05343850.973281
2070.02446520.04893040.975535
2080.0196950.039390.980305
2090.02241540.04483080.977585
2100.01922540.03845090.980775
2110.02218310.04436620.977817
2120.03829430.07658860.961706
2130.03021920.06043840.969781
2140.04156420.08312840.958436
2150.03632140.07264270.963679
2160.02841580.05683160.971584
2170.03199710.06399430.968003
2180.02786270.05572540.972137
2190.02565130.05130260.974349
2200.01958090.03916180.980419
2210.01715580.03431160.982844
2220.01279670.02559330.987203
2230.009753220.01950640.990247
2240.0079120.0158240.992088
2250.005597840.01119570.994402
2260.01162040.02324090.98838
2270.009058260.01811650.990942
2280.006810810.01362160.993189
2290.004971570.009943140.995028
2300.003566170.007132340.996434
2310.004056790.008113580.995943
2320.01045920.02091850.989541
2330.04433170.08866340.955668
2340.06358790.1271760.936412
2350.04820060.09640120.951799
2360.04203860.08407710.957961
2370.29140.5827990.7086
2380.2422670.4845340.757733
2390.2193440.4386890.780656
2400.1776210.3552410.822379
2410.1449620.2899240.855038
2420.1223360.2446710.877664
2430.1128680.2257370.887132
2440.1693690.3387390.830631
2450.1759560.3519120.824044
2460.1436450.2872890.856355
2470.1086970.2173940.891303
2480.09636120.1927220.903639
2490.07384480.147690.926155
2500.1176840.2353690.882316
2510.07673580.1534720.923264
2520.1770770.3541530.822923
2530.3371130.6742260.662887
2540.8847210.2305570.115279






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0163265NOK
5% type I error level780.318367NOK
10% type I error level1260.514286NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 4 & 0.0163265 & NOK \tabularnewline
5% type I error level & 78 & 0.318367 & NOK \tabularnewline
10% type I error level & 126 & 0.514286 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253350&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]4[/C][C]0.0163265[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]78[/C][C]0.318367[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]126[/C][C]0.514286[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253350&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253350&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0163265NOK
5% type I error level780.318367NOK
10% type I error level1260.514286NOK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 3 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 3 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '7'
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')
}