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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 computationTue, 11 Nov 2014 19:26:37 +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/11/t141573445807v5o9jdf17gz4b.htm/, Retrieved Sun, 19 May 2024 08:45:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=253717, Retrieved Sun, 19 May 2024 08:45:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact69

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [ws7 comp1] [2014-11-11 19:26:37] [5a1a6480a94cc63423bd5720e139a09a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
38 41 13 12 14 12 53
32 39 16 11 18 11 83
35 30 19 15 11 14 66
33 31 15 6 12 12 67
37 34 14 13 16 21 76
29 35 13 10 18 12 78
31 39 19 12 14 22 53
36 34 15 14 14 11 80
35 36 14 12 15 10 74
38 37 15 9 15 13 76
31 38 16 10 17 10 79
34 36 16 12 19 8 54
35 38 16 12 10 15 67
38 39 16 11 16 14 54
37 33 17 15 18 10 87
33 32 15 12 14 14 58
32 36 15 10 14 14 75
38 38 20 12 17 11 88
38 39 18 11 14 10 64
32 32 16 12 16 13 57
33 32 16 11 18 9.5 66
31 31 16 12 11 14 68
38 39 19 13 14 12 54
39 37 16 11 12 14 56
32 39 17 12 17 11 86
32 41 17 13 9 9 80
35 36 16 10 16 11 76
37 33 15 14 14 15 69
33 33 16 12 15 14 78
33 34 14 10 11 13 67
31 31 15 12 16 9 80
32 27 12 8 13 15 54
31 37 14 10 17 10 71
37 34 16 12 15 11 84
30 34 14 12 14 13 74
33 32 10 7 16 8 71
31 29 10 9 9 20 63
33 36 14 12 15 12 71
31 29 16 10 17 10 76
33 35 16 10 13 10 69
32 37 16 10 15 9 74
33 34 14 12 16 14 75
32 38 20 15 16 8 54
33 35 14 10 12 14 52
28 38 14 10 15 11 69
35 37 11 12 11 13 68
39 38 14 13 15 9 65
34 33 15 11 15 11 75
38 36 16 11 17 15 74
32 38 14 12 13 11 75
38 32 16 14 16 10 72
30 32 14 10 14 14 67
33 32 12 12 11 18 63
38 34 16 13 12 14 62
32 32 9 5 12 11 63
35 37 14 6 15 14.5 76
34 39 16 12 16 13 74
34 29 16 12 15 9 67
36 37 15 11 12 10 73
34 35 16 10 12 15 70
28 30 12 7 8 20 53
34 38 16 12 13 12 77
35 34 16 14 11 12 80
35 31 14 11 14 14 52
31 34 16 12 15 13 54
37 35 17 13 10 11 80
35 36 18 14 11 17 66
27 30 18 11 12 12 73
40 39 12 12 15 13 63
37 35 16 12 15 14 69
36 38 10 8 14 13 67
38 31 14 11 16 15 54
39 34 18 14 15 13 81
41 38 18 14 15 10 69
27 34 16 12 13 11 84
30 39 17 9 12 19 80
37 37 16 13 17 13 70
31 34 16 11 13 17 69
31 28 13 12 15 13 77
27 37 16 12 13 9 54
36 33 16 12 15 11 79
37 35 16 12 15 9 71
33 37 15 12 16 12 73
34 32 15 11 15 12 72
31 33 16 10 14 13 77
39 38 14 9 15 13 75
34 33 16 12 14 12 69
32 29 16 12 13 15 54
33 33 15 12 7 22 70
36 31 12 9 17 13 73
32 36 17 15 13 15 54
41 35 16 12 15 13 77
28 32 15 12 14 15 82
30 29 13 12 13 12.5 80
36 39 16 10 16 11 80
35 37 16 13 12 16 69
31 35 16 9 14 11 78
34 37 16 12 17 11 81
36 32 14 10 15 10 76
36 38 16 14 17 10 76
35 37 16 11 12 16 73
37 36 20 15 16 12 85
28 32 15 11 11 11 66
39 33 16 11 15 16 79
32 40 13 12 9 19 68
35 38 17 12 16 11 76
39 41 16 12 15 16 71
35 36 16 11 10 15 54
42 43 12 7 10 24 46
34 30 16 12 15 14 85
33 31 16 14 11 15 74
41 32 17 11 13 11 88
33 32 13 11 14 15 38
34 37 12 10 18 12 76
32 37 18 13 16 10 86
40 33 14 13 14 14 54
40 34 14 8 14 13 67
35 33 13 11 14 9 69
36 38 16 12 14 15 90
37 33 13 11 12 15 54
27 31 16 13 14 14 76
39 38 13 12 15 11 89
38 37 16 14 15 8 76
31 36 15 13 15 11 73
33 31 16 15 13 11 79
32 39 15 10 17 8 90
39 44 17 11 17 10 74
36 33 15 9 19 11 81
33 35 12 11 15 13 72
33 32 16 10 13 11 71
32 28 10 11 9 20 66
37 40 16 8 15 10 77
30 27 12 11 15 15 65
38 37 14 12 15 12 74
29 32 15 12 16 14 85
22 28 13 9 11 23 54
35 34 15 11 14 14 63
35 30 11 10 11 16 54
34 35 12 8 15 11 64
35 31 11 9 13 12 69
34 32 16 8 15 10 54
37 30 15 9 16 14 84
35 30 17 15 14 12 86
23 31 16 11 15 12 77
31 40 10 8 16 11 89
27 32 18 13 16 12 76
36 36 13 12 11 13 60
31 32 16 12 12 11 75
32 35 13 9 9 19 73
39 38 10 7 16 12 85
37 42 15 13 13 17 79
38 34 16 9 16 9 71
39 35 16 6 12 12 72
34 38 14 8 9 19 69
31 33 10 8 13 18 78
32 36 17 15 13 15 54
37 32 13 6 14 14 69
36 33 15 9 19 11 81
32 34 16 11 13 9 84
38 32 12 8 12 18 84
36 34 13 8 13 16 69
26 27 13 10 10 24 66
26 31 12 8 14 14 81
33 38 17 14 16 20 82
39 34 15 10 10 18 72
30 24 10 8 11 23 54
33 30 14 11 14 12 78
25 26 11 12 12 14 74
38 34 13 12 9 16 82
37 27 16 12 9 18 73
31 37 12 5 11 20 55
37 36 16 12 16 12 72
35 41 12 10 9 12 78
25 29 9 7 13 17 59
28 36 12 12 16 13 72
35 32 15 11 13 9 78
33 37 12 8 9 16 68
30 30 12 9 12 18 69
31 31 14 10 16 10 67
37 38 12 9 11 14 74
36 36 16 12 14 11 54
30 35 11 6 13 9 67
36 31 19 15 15 11 70
32 38 15 12 14 10 80
28 22 8 12 16 11 89
36 32 16 12 13 19 76
34 36 17 11 14 14 74
31 39 12 7 15 12 87
28 28 11 7 13 14 54
36 32 11 5 11 21 61
36 32 14 12 11 13 38
40 38 16 12 14 10 75
33 32 12 3 15 15 69
37 35 16 11 11 16 62
32 32 13 10 15 14 72
38 37 15 12 12 12 70
31 34 16 9 14 19 79
37 33 16 12 14 15 87
33 33 14 9 8 19 62
32 26 16 12 13 13 77
30 30 16 12 9 17 69
30 24 14 10 15 12 69
31 34 11 9 17 11 75
32 34 12 12 13 14 54
34 33 15 8 15 11 72
36 34 15 11 15 13 74
37 35 16 11 14 12 85
36 35 16 12 16 15 52
33 36 11 10 13 14 70
33 34 15 10 16 12 84
33 34 12 12 9 17 64
44 41 12 12 16 11 84
39 32 15 11 11 18 87
32 30 15 8 10 13 79
35 35 16 12 11 17 67
25 28 14 10 15 13 65
35 33 17 11 17 11 85
34 39 14 10 14 12 83
35 36 13 8 8 22 61
39 36 15 12 15 14 82
33 35 13 12 11 12 76
36 38 14 10 16 12 58
32 33 15 12 10 17 72
32 31 12 9 15 9 72
36 34 13 9 9 21 38
36 32 8 6 16 10 78
32 31 14 10 19 11 54
34 33 14 9 12 12 63
33 34 11 9 8 23 66
35 34 12 9 11 13 70
30 34 13 6 14 12 71
38 33 10 10 9 16 67
34 32 16 6 15 9 58
33 41 18 14 13 17 72
32 34 13 10 16 9 72
31 36 11 10 11 14 70
30 37 4 6 12 17 76
27 36 13 12 13 13 50
31 29 16 12 10 11 72
30 37 10 7 11 12 72
32 27 12 8 12 10 88
35 35 12 11 8 19 53
28 28 10 3 12 16 58
33 35 13 6 12 16 66
31 37 15 10 15 14 82
35 29 12 8 11 20 69
35 32 14 9 13 15 68
32 36 10 9 14 23 44
21 19 12 8 10 20 56
20 21 12 9 12 16 53
34 31 11 7 15 14 70
32 33 10 7 13 17 78
34 36 12 6 13 11 71
32 33 16 9 13 13 72
33 37 12 10 12 17 68
33 34 14 11 12 15 67
37 35 16 12 9 21 75
32 31 14 8 9 18 62
34 37 13 11 15 15 67
30 35 4 3 10 8 83
30 27 15 11 14 12 64
38 34 11 12 15 12 68
36 40 11 7 7 22 62
32 29 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 time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 8 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253717&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253717&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253717&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 time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Separate[t] = + 15.0021 + 0.415895Connected[t] + 0.134993Learning[t] + 0.127421Software[t] + 0.0326938Happiness[t] + 0.0080234Depression[t] + 0.00783445Sport1[t] + 0.00106934t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Separate[t] =  +  15.0021 +  0.415895Connected[t] +  0.134993Learning[t] +  0.127421Software[t] +  0.0326938Happiness[t] +  0.0080234Depression[t] +  0.00783445Sport1[t] +  0.00106934t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253717&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Separate[t] =  +  15.0021 +  0.415895Connected[t] +  0.134993Learning[t] +  0.127421Software[t] +  0.0326938Happiness[t] +  0.0080234Depression[t] +  0.00783445Sport1[t] +  0.00106934t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253717&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253717&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
Separate[t] = + 15.0021 + 0.415895Connected[t] + 0.134993Learning[t] + 0.127421Software[t] + 0.0326938Happiness[t] + 0.0080234Depression[t] + 0.00783445Sport1[t] + 0.00106934t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.00213.376644.4431.32202e-056.61012e-06
Connected0.4158950.05547787.4971.07115e-125.35573e-13
Learning0.1349930.1107221.2190.2238860.111943
Software0.1274210.1135511.1220.2628530.131426
Happiness0.03269380.1029840.31750.7511510.375575
Depression0.00802340.07427130.1080.9140580.457029
Sport10.007834450.02109770.37130.710690.355345
t0.001069340.003033710.35250.7247640.362382

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 15.0021 & 3.37664 & 4.443 & 1.32202e-05 & 6.61012e-06 \tabularnewline
Connected & 0.415895 & 0.0554778 & 7.497 & 1.07115e-12 & 5.35573e-13 \tabularnewline
Learning & 0.134993 & 0.110722 & 1.219 & 0.223886 & 0.111943 \tabularnewline
Software & 0.127421 & 0.113551 & 1.122 & 0.262853 & 0.131426 \tabularnewline
Happiness & 0.0326938 & 0.102984 & 0.3175 & 0.751151 & 0.375575 \tabularnewline
Depression & 0.0080234 & 0.0742713 & 0.108 & 0.914058 & 0.457029 \tabularnewline
Sport1 & 0.00783445 & 0.0210977 & 0.3713 & 0.71069 & 0.355345 \tabularnewline
t & 0.00106934 & 0.00303371 & 0.3525 & 0.724764 & 0.362382 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253717&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]15.0021[/C][C]3.37664[/C][C]4.443[/C][C]1.32202e-05[/C][C]6.61012e-06[/C][/ROW]
[ROW][C]Connected[/C][C]0.415895[/C][C]0.0554778[/C][C]7.497[/C][C]1.07115e-12[/C][C]5.35573e-13[/C][/ROW]
[ROW][C]Learning[/C][C]0.134993[/C][C]0.110722[/C][C]1.219[/C][C]0.223886[/C][C]0.111943[/C][/ROW]
[ROW][C]Software[/C][C]0.127421[/C][C]0.113551[/C][C]1.122[/C][C]0.262853[/C][C]0.131426[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0326938[/C][C]0.102984[/C][C]0.3175[/C][C]0.751151[/C][C]0.375575[/C][/ROW]
[ROW][C]Depression[/C][C]0.0080234[/C][C]0.0742713[/C][C]0.108[/C][C]0.914058[/C][C]0.457029[/C][/ROW]
[ROW][C]Sport1[/C][C]0.00783445[/C][C]0.0210977[/C][C]0.3713[/C][C]0.71069[/C][C]0.355345[/C][/ROW]
[ROW][C]t[/C][C]0.00106934[/C][C]0.00303371[/C][C]0.3525[/C][C]0.724764[/C][C]0.362382[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253717&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253717&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.00213.376644.4431.32202e-056.61012e-06
Connected0.4158950.05547787.4971.07115e-125.35573e-13
Learning0.1349930.1107221.2190.2238860.111943
Software0.1274210.1135511.1220.2628530.131426
Happiness0.03269380.1029840.31750.7511510.375575
Depression0.00802340.07427130.1080.9140580.457029
Sport10.007834450.02109770.37130.710690.355345
t0.001069340.003033710.35250.7247640.362382






Multiple Linear Regression - Regression Statistics
Multiple R0.479615
R-squared0.230031
Adjusted R-squared0.208977
F-TEST (value)10.9258
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value4.5981e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.29435
Sum Squared Residuals2778.3

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.479615 \tabularnewline
R-squared & 0.230031 \tabularnewline
Adjusted R-squared & 0.208977 \tabularnewline
F-TEST (value) & 10.9258 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 4.5981e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.29435 \tabularnewline
Sum Squared Residuals & 2778.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253717&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.479615[/C][/ROW]
[ROW][C]R-squared[/C][C]0.230031[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.208977[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]10.9258[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]4.5981e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.29435[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2778.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253717&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253717&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 R0.479615
R-squared0.230031
Adjusted R-squared0.208977
F-TEST (value)10.9258
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value4.5981e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.29435
Sum Squared Residuals2778.3






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
13836.3081.69196
23236.1127-4.11267
33532.94742.05263
43331.70211.29795
53733.98133.01874
62933.8898-4.88981
73136.3729-5.37286
83634.13261.8674
93534.55330.446715
103834.76273.23728
113135.5069-4.50692
123434.7845-0.784519
133535.4811-0.481146
143835.8572.14302
153734.29922.70081
163332.90620.093768
173234.4492-2.44923
183836.38781.61225
193836.11321.88682
203233.095-1.09503
213333.0765-0.0764964
223132.612-1.61201
233836.4451.55501
243934.92084.07922
253236.3905-4.39048
263237.0262-5.02616
273534.64410.355936
283733.6843.316
293333.6604-0.660405
303333.3276-0.327563
313132.704-1.70401
323229.87322.12681
333134.7819-3.78189
343734.10462.89542
353033.7407-3.74067
363331.73461.26536
373130.54760.452383
383334.5768-1.57684
393131.7703-0.770301
403334.0811-1.08112
413235.0105-3.01052
423333.8294-0.829405
433236.4736-4.47361
443333.6816-0.681629
452835.1376-7.13758
463534.45010.549945
473935.47463.5254
483433.37070.629266
493834.84413.15587
503235.3794-3.37939
513833.47654.52353
523032.6254-2.6254
533332.5140.485997
543834.0073.99298
553231.19570.804255
563534.30670.693312
573436.179-2.17905
583431.90152.09846
593634.92431.0757
603434.1178-0.117769
612830.8933-2.89328
623435.6859-1.6859
633534.23630.763654
643532.23222.76776
653133.9187-2.91875
663734.62232.3777
673535.2728-0.272835
682732.4437-5.44369
694035.5334.46696
703734.46552.53447
713634.33831.66175
723832.32995.67012
733934.66374.33634
744136.21024.78977
752734.083-7.08304
763035.9165-5.91647
773735.49741.50258
783133.8894-2.88945
793131.2136-0.213559
802735.085-8.08499
813633.69982.30023
823734.45392.54609
833335.2242-2.22421
843432.97791.02214
853133.4169-2.41689
863935.11713.88294
873433.60320.396824
883231.81450.185476
893333.3295-0.329533
903631.98984.0102
913235.2463-3.24625
924134.54376.45629
932833.1846-5.18462
943031.5996-1.5996
953635.99580.00419749
963535.3705-0.370507
973134.1259-3.12588
983435.4626-1.46259
993632.74683.25323
1003636.0883-0.0882707
1013535.1523-0.15235
1023735.97991.02012
1032832.8124-4.81237
1043933.63715.36293
1053236.0136-4.01357
1063535.9502-0.950168
1073937.03221.96782
1083534.52170.478325
1094236.39395.60611
1103432.55421.44582
1113333.0171-0.0170527
1124133.32977.67028
1133332.46390.536115
1143434.6864-0.68643
1153235.8766-3.87663
1164033.39026.60985
1174033.26386.73616
1183533.07991.92015
1193635.90550.0945359
1203732.94724.05277
1212733.0061-6.00605
1223935.49653.50354
1233835.61552.38446
1243134.9389-3.93886
1253333.2319-0.231911
1263235.9809-3.98093
1273938.34960.650425
1283633.37922.62078
1293333.8767-0.876705
1303332.95340.046628
1313230.51061.48941
1323736.13220.867799
1333030.515-0.515027
1343835.11892.8811
1352933.3104-4.3104
1362230.6615-8.66151
1373533.77921.22084
1383531.29673.70329
1393433.42640.573587
1403531.73813.26186
1413432.63451.36553
1423732.0964.904
1433533.06581.93418
1442332.8003-9.80029
1453135.4709-4.47087
1462733.768-6.76801
1473634.34951.65053
1483133.2261-2.22611
1493233.6381-1.63806
1503934.49374.50631
1513737.4929-0.492865
1523833.76334.2367
1533933.69915.30087
1543434.8673-0.867322
1553132.4422-1.4422
1563235.3158-3.31576
1573732.10874.89132
1583633.41132.5887
1593234.0294-2.0294
1603832.3165.68404
1613633.18292.81706
1622630.4702-4.47019
1632631.9131-5.91306
1643336.3862-3.38625
1653933.65355.34649
1663028.49761.50239
1673332.11410.88586
1682530.0934-5.09339
1693833.67224.32775
1703731.11265.88743
1713133.7811-2.78108
1723735.03061.96935
1733536.1345-1.13453
1742530.3796-5.37965
1752834.5019-6.5019
1763533.03381.96622
1773334.1741-1.17413
1783031.5133-1.51332
1793132.3786-1.37861
1803734.8172.183
1813634.82581.17416
1823033.0246-3.02463
1833633.69382.30621
1843235.7215-3.72152
1852828.2672-0.267232
1863633.37152.62854
1873435.0206-1.02059
1883135.2032-4.20319
1892830.1865-2.18654
1903631.6424.35804
1913632.69563.30442
1924035.82594.17411
1933331.67061.32937
1943734.30112.69886
1953232.7152-0.715192
1963835.19082.80923
1973133.8889-2.88894
1983733.8873.11304
1993332.87590.124148
2003230.85081.14925
2013032.354-2.35404
2023029.4910.509041
2033133.223-2.22295
2043233.47-1.47005
2053433.13290.867145
2063633.96382.0362
2073734.56122.43878
2083634.52061.47937
2093334.0427-1.0427
2103333.9437-0.943669
2113333.4492-0.449172
2124436.69897.30109
2133933.15075.84932
2143231.80220.197788
2153534.49820.501792
2162531.1462-6.1462
2173533.96521.03483
2183435.8235-1.82348
2193533.89871.10125
2203935.00873.99132
2213334.13-1.13004
2223635.28140.718607
2233233.5465-1.54646
2243232.0278-0.0277764
2253633.04532.95473
2263631.61134.3887
2273232.4342-0.434194
2283432.98931.01069
2293332.98230.0177204
2303533.16751.83247
2313033.0192-3.01922
2323832.54645.45362
2333432.50131.49868
2343337.6433-4.64328
2353233.5823-1.58233
2363134.0062-3.00618
2373033.0723-3.07228
2382734.4338-7.43383
2393131.9868-0.98684
2403033.9087-3.90872
2413230.29021.70975
2423533.6681.33203
2432829.6143-1.6143
2443333.3765-0.37655
2453135.1965-4.19647
2463531.02613.97393
2473532.68972.31033
2483233.7232-1.7232
2492126.7358-5.73578
2502027.7059-7.70586
2513431.69132.30874
2523232.4105-0.410486
2533433.69880.301175
2543233.3983-1.39833
2553334.6185-1.61849
2563333.7454-0.745396
2573734.57252.4275
2583232.0044-0.00440256
2593434.9594-0.959378
2603031.8001-1.80007
2613030.9923-0.992284
2623833.55614.4439
2633635.18710.812889
2643231.50010.499878

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 38 & 36.308 & 1.69196 \tabularnewline
2 & 32 & 36.1127 & -4.11267 \tabularnewline
3 & 35 & 32.9474 & 2.05263 \tabularnewline
4 & 33 & 31.7021 & 1.29795 \tabularnewline
5 & 37 & 33.9813 & 3.01874 \tabularnewline
6 & 29 & 33.8898 & -4.88981 \tabularnewline
7 & 31 & 36.3729 & -5.37286 \tabularnewline
8 & 36 & 34.1326 & 1.8674 \tabularnewline
9 & 35 & 34.5533 & 0.446715 \tabularnewline
10 & 38 & 34.7627 & 3.23728 \tabularnewline
11 & 31 & 35.5069 & -4.50692 \tabularnewline
12 & 34 & 34.7845 & -0.784519 \tabularnewline
13 & 35 & 35.4811 & -0.481146 \tabularnewline
14 & 38 & 35.857 & 2.14302 \tabularnewline
15 & 37 & 34.2992 & 2.70081 \tabularnewline
16 & 33 & 32.9062 & 0.093768 \tabularnewline
17 & 32 & 34.4492 & -2.44923 \tabularnewline
18 & 38 & 36.3878 & 1.61225 \tabularnewline
19 & 38 & 36.1132 & 1.88682 \tabularnewline
20 & 32 & 33.095 & -1.09503 \tabularnewline
21 & 33 & 33.0765 & -0.0764964 \tabularnewline
22 & 31 & 32.612 & -1.61201 \tabularnewline
23 & 38 & 36.445 & 1.55501 \tabularnewline
24 & 39 & 34.9208 & 4.07922 \tabularnewline
25 & 32 & 36.3905 & -4.39048 \tabularnewline
26 & 32 & 37.0262 & -5.02616 \tabularnewline
27 & 35 & 34.6441 & 0.355936 \tabularnewline
28 & 37 & 33.684 & 3.316 \tabularnewline
29 & 33 & 33.6604 & -0.660405 \tabularnewline
30 & 33 & 33.3276 & -0.327563 \tabularnewline
31 & 31 & 32.704 & -1.70401 \tabularnewline
32 & 32 & 29.8732 & 2.12681 \tabularnewline
33 & 31 & 34.7819 & -3.78189 \tabularnewline
34 & 37 & 34.1046 & 2.89542 \tabularnewline
35 & 30 & 33.7407 & -3.74067 \tabularnewline
36 & 33 & 31.7346 & 1.26536 \tabularnewline
37 & 31 & 30.5476 & 0.452383 \tabularnewline
38 & 33 & 34.5768 & -1.57684 \tabularnewline
39 & 31 & 31.7703 & -0.770301 \tabularnewline
40 & 33 & 34.0811 & -1.08112 \tabularnewline
41 & 32 & 35.0105 & -3.01052 \tabularnewline
42 & 33 & 33.8294 & -0.829405 \tabularnewline
43 & 32 & 36.4736 & -4.47361 \tabularnewline
44 & 33 & 33.6816 & -0.681629 \tabularnewline
45 & 28 & 35.1376 & -7.13758 \tabularnewline
46 & 35 & 34.4501 & 0.549945 \tabularnewline
47 & 39 & 35.4746 & 3.5254 \tabularnewline
48 & 34 & 33.3707 & 0.629266 \tabularnewline
49 & 38 & 34.8441 & 3.15587 \tabularnewline
50 & 32 & 35.3794 & -3.37939 \tabularnewline
51 & 38 & 33.4765 & 4.52353 \tabularnewline
52 & 30 & 32.6254 & -2.6254 \tabularnewline
53 & 33 & 32.514 & 0.485997 \tabularnewline
54 & 38 & 34.007 & 3.99298 \tabularnewline
55 & 32 & 31.1957 & 0.804255 \tabularnewline
56 & 35 & 34.3067 & 0.693312 \tabularnewline
57 & 34 & 36.179 & -2.17905 \tabularnewline
58 & 34 & 31.9015 & 2.09846 \tabularnewline
59 & 36 & 34.9243 & 1.0757 \tabularnewline
60 & 34 & 34.1178 & -0.117769 \tabularnewline
61 & 28 & 30.8933 & -2.89328 \tabularnewline
62 & 34 & 35.6859 & -1.6859 \tabularnewline
63 & 35 & 34.2363 & 0.763654 \tabularnewline
64 & 35 & 32.2322 & 2.76776 \tabularnewline
65 & 31 & 33.9187 & -2.91875 \tabularnewline
66 & 37 & 34.6223 & 2.3777 \tabularnewline
67 & 35 & 35.2728 & -0.272835 \tabularnewline
68 & 27 & 32.4437 & -5.44369 \tabularnewline
69 & 40 & 35.533 & 4.46696 \tabularnewline
70 & 37 & 34.4655 & 2.53447 \tabularnewline
71 & 36 & 34.3383 & 1.66175 \tabularnewline
72 & 38 & 32.3299 & 5.67012 \tabularnewline
73 & 39 & 34.6637 & 4.33634 \tabularnewline
74 & 41 & 36.2102 & 4.78977 \tabularnewline
75 & 27 & 34.083 & -7.08304 \tabularnewline
76 & 30 & 35.9165 & -5.91647 \tabularnewline
77 & 37 & 35.4974 & 1.50258 \tabularnewline
78 & 31 & 33.8894 & -2.88945 \tabularnewline
79 & 31 & 31.2136 & -0.213559 \tabularnewline
80 & 27 & 35.085 & -8.08499 \tabularnewline
81 & 36 & 33.6998 & 2.30023 \tabularnewline
82 & 37 & 34.4539 & 2.54609 \tabularnewline
83 & 33 & 35.2242 & -2.22421 \tabularnewline
84 & 34 & 32.9779 & 1.02214 \tabularnewline
85 & 31 & 33.4169 & -2.41689 \tabularnewline
86 & 39 & 35.1171 & 3.88294 \tabularnewline
87 & 34 & 33.6032 & 0.396824 \tabularnewline
88 & 32 & 31.8145 & 0.185476 \tabularnewline
89 & 33 & 33.3295 & -0.329533 \tabularnewline
90 & 36 & 31.9898 & 4.0102 \tabularnewline
91 & 32 & 35.2463 & -3.24625 \tabularnewline
92 & 41 & 34.5437 & 6.45629 \tabularnewline
93 & 28 & 33.1846 & -5.18462 \tabularnewline
94 & 30 & 31.5996 & -1.5996 \tabularnewline
95 & 36 & 35.9958 & 0.00419749 \tabularnewline
96 & 35 & 35.3705 & -0.370507 \tabularnewline
97 & 31 & 34.1259 & -3.12588 \tabularnewline
98 & 34 & 35.4626 & -1.46259 \tabularnewline
99 & 36 & 32.7468 & 3.25323 \tabularnewline
100 & 36 & 36.0883 & -0.0882707 \tabularnewline
101 & 35 & 35.1523 & -0.15235 \tabularnewline
102 & 37 & 35.9799 & 1.02012 \tabularnewline
103 & 28 & 32.8124 & -4.81237 \tabularnewline
104 & 39 & 33.6371 & 5.36293 \tabularnewline
105 & 32 & 36.0136 & -4.01357 \tabularnewline
106 & 35 & 35.9502 & -0.950168 \tabularnewline
107 & 39 & 37.0322 & 1.96782 \tabularnewline
108 & 35 & 34.5217 & 0.478325 \tabularnewline
109 & 42 & 36.3939 & 5.60611 \tabularnewline
110 & 34 & 32.5542 & 1.44582 \tabularnewline
111 & 33 & 33.0171 & -0.0170527 \tabularnewline
112 & 41 & 33.3297 & 7.67028 \tabularnewline
113 & 33 & 32.4639 & 0.536115 \tabularnewline
114 & 34 & 34.6864 & -0.68643 \tabularnewline
115 & 32 & 35.8766 & -3.87663 \tabularnewline
116 & 40 & 33.3902 & 6.60985 \tabularnewline
117 & 40 & 33.2638 & 6.73616 \tabularnewline
118 & 35 & 33.0799 & 1.92015 \tabularnewline
119 & 36 & 35.9055 & 0.0945359 \tabularnewline
120 & 37 & 32.9472 & 4.05277 \tabularnewline
121 & 27 & 33.0061 & -6.00605 \tabularnewline
122 & 39 & 35.4965 & 3.50354 \tabularnewline
123 & 38 & 35.6155 & 2.38446 \tabularnewline
124 & 31 & 34.9389 & -3.93886 \tabularnewline
125 & 33 & 33.2319 & -0.231911 \tabularnewline
126 & 32 & 35.9809 & -3.98093 \tabularnewline
127 & 39 & 38.3496 & 0.650425 \tabularnewline
128 & 36 & 33.3792 & 2.62078 \tabularnewline
129 & 33 & 33.8767 & -0.876705 \tabularnewline
130 & 33 & 32.9534 & 0.046628 \tabularnewline
131 & 32 & 30.5106 & 1.48941 \tabularnewline
132 & 37 & 36.1322 & 0.867799 \tabularnewline
133 & 30 & 30.515 & -0.515027 \tabularnewline
134 & 38 & 35.1189 & 2.8811 \tabularnewline
135 & 29 & 33.3104 & -4.3104 \tabularnewline
136 & 22 & 30.6615 & -8.66151 \tabularnewline
137 & 35 & 33.7792 & 1.22084 \tabularnewline
138 & 35 & 31.2967 & 3.70329 \tabularnewline
139 & 34 & 33.4264 & 0.573587 \tabularnewline
140 & 35 & 31.7381 & 3.26186 \tabularnewline
141 & 34 & 32.6345 & 1.36553 \tabularnewline
142 & 37 & 32.096 & 4.904 \tabularnewline
143 & 35 & 33.0658 & 1.93418 \tabularnewline
144 & 23 & 32.8003 & -9.80029 \tabularnewline
145 & 31 & 35.4709 & -4.47087 \tabularnewline
146 & 27 & 33.768 & -6.76801 \tabularnewline
147 & 36 & 34.3495 & 1.65053 \tabularnewline
148 & 31 & 33.2261 & -2.22611 \tabularnewline
149 & 32 & 33.6381 & -1.63806 \tabularnewline
150 & 39 & 34.4937 & 4.50631 \tabularnewline
151 & 37 & 37.4929 & -0.492865 \tabularnewline
152 & 38 & 33.7633 & 4.2367 \tabularnewline
153 & 39 & 33.6991 & 5.30087 \tabularnewline
154 & 34 & 34.8673 & -0.867322 \tabularnewline
155 & 31 & 32.4422 & -1.4422 \tabularnewline
156 & 32 & 35.3158 & -3.31576 \tabularnewline
157 & 37 & 32.1087 & 4.89132 \tabularnewline
158 & 36 & 33.4113 & 2.5887 \tabularnewline
159 & 32 & 34.0294 & -2.0294 \tabularnewline
160 & 38 & 32.316 & 5.68404 \tabularnewline
161 & 36 & 33.1829 & 2.81706 \tabularnewline
162 & 26 & 30.4702 & -4.47019 \tabularnewline
163 & 26 & 31.9131 & -5.91306 \tabularnewline
164 & 33 & 36.3862 & -3.38625 \tabularnewline
165 & 39 & 33.6535 & 5.34649 \tabularnewline
166 & 30 & 28.4976 & 1.50239 \tabularnewline
167 & 33 & 32.1141 & 0.88586 \tabularnewline
168 & 25 & 30.0934 & -5.09339 \tabularnewline
169 & 38 & 33.6722 & 4.32775 \tabularnewline
170 & 37 & 31.1126 & 5.88743 \tabularnewline
171 & 31 & 33.7811 & -2.78108 \tabularnewline
172 & 37 & 35.0306 & 1.96935 \tabularnewline
173 & 35 & 36.1345 & -1.13453 \tabularnewline
174 & 25 & 30.3796 & -5.37965 \tabularnewline
175 & 28 & 34.5019 & -6.5019 \tabularnewline
176 & 35 & 33.0338 & 1.96622 \tabularnewline
177 & 33 & 34.1741 & -1.17413 \tabularnewline
178 & 30 & 31.5133 & -1.51332 \tabularnewline
179 & 31 & 32.3786 & -1.37861 \tabularnewline
180 & 37 & 34.817 & 2.183 \tabularnewline
181 & 36 & 34.8258 & 1.17416 \tabularnewline
182 & 30 & 33.0246 & -3.02463 \tabularnewline
183 & 36 & 33.6938 & 2.30621 \tabularnewline
184 & 32 & 35.7215 & -3.72152 \tabularnewline
185 & 28 & 28.2672 & -0.267232 \tabularnewline
186 & 36 & 33.3715 & 2.62854 \tabularnewline
187 & 34 & 35.0206 & -1.02059 \tabularnewline
188 & 31 & 35.2032 & -4.20319 \tabularnewline
189 & 28 & 30.1865 & -2.18654 \tabularnewline
190 & 36 & 31.642 & 4.35804 \tabularnewline
191 & 36 & 32.6956 & 3.30442 \tabularnewline
192 & 40 & 35.8259 & 4.17411 \tabularnewline
193 & 33 & 31.6706 & 1.32937 \tabularnewline
194 & 37 & 34.3011 & 2.69886 \tabularnewline
195 & 32 & 32.7152 & -0.715192 \tabularnewline
196 & 38 & 35.1908 & 2.80923 \tabularnewline
197 & 31 & 33.8889 & -2.88894 \tabularnewline
198 & 37 & 33.887 & 3.11304 \tabularnewline
199 & 33 & 32.8759 & 0.124148 \tabularnewline
200 & 32 & 30.8508 & 1.14925 \tabularnewline
201 & 30 & 32.354 & -2.35404 \tabularnewline
202 & 30 & 29.491 & 0.509041 \tabularnewline
203 & 31 & 33.223 & -2.22295 \tabularnewline
204 & 32 & 33.47 & -1.47005 \tabularnewline
205 & 34 & 33.1329 & 0.867145 \tabularnewline
206 & 36 & 33.9638 & 2.0362 \tabularnewline
207 & 37 & 34.5612 & 2.43878 \tabularnewline
208 & 36 & 34.5206 & 1.47937 \tabularnewline
209 & 33 & 34.0427 & -1.0427 \tabularnewline
210 & 33 & 33.9437 & -0.943669 \tabularnewline
211 & 33 & 33.4492 & -0.449172 \tabularnewline
212 & 44 & 36.6989 & 7.30109 \tabularnewline
213 & 39 & 33.1507 & 5.84932 \tabularnewline
214 & 32 & 31.8022 & 0.197788 \tabularnewline
215 & 35 & 34.4982 & 0.501792 \tabularnewline
216 & 25 & 31.1462 & -6.1462 \tabularnewline
217 & 35 & 33.9652 & 1.03483 \tabularnewline
218 & 34 & 35.8235 & -1.82348 \tabularnewline
219 & 35 & 33.8987 & 1.10125 \tabularnewline
220 & 39 & 35.0087 & 3.99132 \tabularnewline
221 & 33 & 34.13 & -1.13004 \tabularnewline
222 & 36 & 35.2814 & 0.718607 \tabularnewline
223 & 32 & 33.5465 & -1.54646 \tabularnewline
224 & 32 & 32.0278 & -0.0277764 \tabularnewline
225 & 36 & 33.0453 & 2.95473 \tabularnewline
226 & 36 & 31.6113 & 4.3887 \tabularnewline
227 & 32 & 32.4342 & -0.434194 \tabularnewline
228 & 34 & 32.9893 & 1.01069 \tabularnewline
229 & 33 & 32.9823 & 0.0177204 \tabularnewline
230 & 35 & 33.1675 & 1.83247 \tabularnewline
231 & 30 & 33.0192 & -3.01922 \tabularnewline
232 & 38 & 32.5464 & 5.45362 \tabularnewline
233 & 34 & 32.5013 & 1.49868 \tabularnewline
234 & 33 & 37.6433 & -4.64328 \tabularnewline
235 & 32 & 33.5823 & -1.58233 \tabularnewline
236 & 31 & 34.0062 & -3.00618 \tabularnewline
237 & 30 & 33.0723 & -3.07228 \tabularnewline
238 & 27 & 34.4338 & -7.43383 \tabularnewline
239 & 31 & 31.9868 & -0.98684 \tabularnewline
240 & 30 & 33.9087 & -3.90872 \tabularnewline
241 & 32 & 30.2902 & 1.70975 \tabularnewline
242 & 35 & 33.668 & 1.33203 \tabularnewline
243 & 28 & 29.6143 & -1.6143 \tabularnewline
244 & 33 & 33.3765 & -0.37655 \tabularnewline
245 & 31 & 35.1965 & -4.19647 \tabularnewline
246 & 35 & 31.0261 & 3.97393 \tabularnewline
247 & 35 & 32.6897 & 2.31033 \tabularnewline
248 & 32 & 33.7232 & -1.7232 \tabularnewline
249 & 21 & 26.7358 & -5.73578 \tabularnewline
250 & 20 & 27.7059 & -7.70586 \tabularnewline
251 & 34 & 31.6913 & 2.30874 \tabularnewline
252 & 32 & 32.4105 & -0.410486 \tabularnewline
253 & 34 & 33.6988 & 0.301175 \tabularnewline
254 & 32 & 33.3983 & -1.39833 \tabularnewline
255 & 33 & 34.6185 & -1.61849 \tabularnewline
256 & 33 & 33.7454 & -0.745396 \tabularnewline
257 & 37 & 34.5725 & 2.4275 \tabularnewline
258 & 32 & 32.0044 & -0.00440256 \tabularnewline
259 & 34 & 34.9594 & -0.959378 \tabularnewline
260 & 30 & 31.8001 & -1.80007 \tabularnewline
261 & 30 & 30.9923 & -0.992284 \tabularnewline
262 & 38 & 33.5561 & 4.4439 \tabularnewline
263 & 36 & 35.1871 & 0.812889 \tabularnewline
264 & 32 & 31.5001 & 0.499878 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253717&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]38[/C][C]36.308[/C][C]1.69196[/C][/ROW]
[ROW][C]2[/C][C]32[/C][C]36.1127[/C][C]-4.11267[/C][/ROW]
[ROW][C]3[/C][C]35[/C][C]32.9474[/C][C]2.05263[/C][/ROW]
[ROW][C]4[/C][C]33[/C][C]31.7021[/C][C]1.29795[/C][/ROW]
[ROW][C]5[/C][C]37[/C][C]33.9813[/C][C]3.01874[/C][/ROW]
[ROW][C]6[/C][C]29[/C][C]33.8898[/C][C]-4.88981[/C][/ROW]
[ROW][C]7[/C][C]31[/C][C]36.3729[/C][C]-5.37286[/C][/ROW]
[ROW][C]8[/C][C]36[/C][C]34.1326[/C][C]1.8674[/C][/ROW]
[ROW][C]9[/C][C]35[/C][C]34.5533[/C][C]0.446715[/C][/ROW]
[ROW][C]10[/C][C]38[/C][C]34.7627[/C][C]3.23728[/C][/ROW]
[ROW][C]11[/C][C]31[/C][C]35.5069[/C][C]-4.50692[/C][/ROW]
[ROW][C]12[/C][C]34[/C][C]34.7845[/C][C]-0.784519[/C][/ROW]
[ROW][C]13[/C][C]35[/C][C]35.4811[/C][C]-0.481146[/C][/ROW]
[ROW][C]14[/C][C]38[/C][C]35.857[/C][C]2.14302[/C][/ROW]
[ROW][C]15[/C][C]37[/C][C]34.2992[/C][C]2.70081[/C][/ROW]
[ROW][C]16[/C][C]33[/C][C]32.9062[/C][C]0.093768[/C][/ROW]
[ROW][C]17[/C][C]32[/C][C]34.4492[/C][C]-2.44923[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]36.3878[/C][C]1.61225[/C][/ROW]
[ROW][C]19[/C][C]38[/C][C]36.1132[/C][C]1.88682[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.095[/C][C]-1.09503[/C][/ROW]
[ROW][C]21[/C][C]33[/C][C]33.0765[/C][C]-0.0764964[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]32.612[/C][C]-1.61201[/C][/ROW]
[ROW][C]23[/C][C]38[/C][C]36.445[/C][C]1.55501[/C][/ROW]
[ROW][C]24[/C][C]39[/C][C]34.9208[/C][C]4.07922[/C][/ROW]
[ROW][C]25[/C][C]32[/C][C]36.3905[/C][C]-4.39048[/C][/ROW]
[ROW][C]26[/C][C]32[/C][C]37.0262[/C][C]-5.02616[/C][/ROW]
[ROW][C]27[/C][C]35[/C][C]34.6441[/C][C]0.355936[/C][/ROW]
[ROW][C]28[/C][C]37[/C][C]33.684[/C][C]3.316[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]33.6604[/C][C]-0.660405[/C][/ROW]
[ROW][C]30[/C][C]33[/C][C]33.3276[/C][C]-0.327563[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]32.704[/C][C]-1.70401[/C][/ROW]
[ROW][C]32[/C][C]32[/C][C]29.8732[/C][C]2.12681[/C][/ROW]
[ROW][C]33[/C][C]31[/C][C]34.7819[/C][C]-3.78189[/C][/ROW]
[ROW][C]34[/C][C]37[/C][C]34.1046[/C][C]2.89542[/C][/ROW]
[ROW][C]35[/C][C]30[/C][C]33.7407[/C][C]-3.74067[/C][/ROW]
[ROW][C]36[/C][C]33[/C][C]31.7346[/C][C]1.26536[/C][/ROW]
[ROW][C]37[/C][C]31[/C][C]30.5476[/C][C]0.452383[/C][/ROW]
[ROW][C]38[/C][C]33[/C][C]34.5768[/C][C]-1.57684[/C][/ROW]
[ROW][C]39[/C][C]31[/C][C]31.7703[/C][C]-0.770301[/C][/ROW]
[ROW][C]40[/C][C]33[/C][C]34.0811[/C][C]-1.08112[/C][/ROW]
[ROW][C]41[/C][C]32[/C][C]35.0105[/C][C]-3.01052[/C][/ROW]
[ROW][C]42[/C][C]33[/C][C]33.8294[/C][C]-0.829405[/C][/ROW]
[ROW][C]43[/C][C]32[/C][C]36.4736[/C][C]-4.47361[/C][/ROW]
[ROW][C]44[/C][C]33[/C][C]33.6816[/C][C]-0.681629[/C][/ROW]
[ROW][C]45[/C][C]28[/C][C]35.1376[/C][C]-7.13758[/C][/ROW]
[ROW][C]46[/C][C]35[/C][C]34.4501[/C][C]0.549945[/C][/ROW]
[ROW][C]47[/C][C]39[/C][C]35.4746[/C][C]3.5254[/C][/ROW]
[ROW][C]48[/C][C]34[/C][C]33.3707[/C][C]0.629266[/C][/ROW]
[ROW][C]49[/C][C]38[/C][C]34.8441[/C][C]3.15587[/C][/ROW]
[ROW][C]50[/C][C]32[/C][C]35.3794[/C][C]-3.37939[/C][/ROW]
[ROW][C]51[/C][C]38[/C][C]33.4765[/C][C]4.52353[/C][/ROW]
[ROW][C]52[/C][C]30[/C][C]32.6254[/C][C]-2.6254[/C][/ROW]
[ROW][C]53[/C][C]33[/C][C]32.514[/C][C]0.485997[/C][/ROW]
[ROW][C]54[/C][C]38[/C][C]34.007[/C][C]3.99298[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]31.1957[/C][C]0.804255[/C][/ROW]
[ROW][C]56[/C][C]35[/C][C]34.3067[/C][C]0.693312[/C][/ROW]
[ROW][C]57[/C][C]34[/C][C]36.179[/C][C]-2.17905[/C][/ROW]
[ROW][C]58[/C][C]34[/C][C]31.9015[/C][C]2.09846[/C][/ROW]
[ROW][C]59[/C][C]36[/C][C]34.9243[/C][C]1.0757[/C][/ROW]
[ROW][C]60[/C][C]34[/C][C]34.1178[/C][C]-0.117769[/C][/ROW]
[ROW][C]61[/C][C]28[/C][C]30.8933[/C][C]-2.89328[/C][/ROW]
[ROW][C]62[/C][C]34[/C][C]35.6859[/C][C]-1.6859[/C][/ROW]
[ROW][C]63[/C][C]35[/C][C]34.2363[/C][C]0.763654[/C][/ROW]
[ROW][C]64[/C][C]35[/C][C]32.2322[/C][C]2.76776[/C][/ROW]
[ROW][C]65[/C][C]31[/C][C]33.9187[/C][C]-2.91875[/C][/ROW]
[ROW][C]66[/C][C]37[/C][C]34.6223[/C][C]2.3777[/C][/ROW]
[ROW][C]67[/C][C]35[/C][C]35.2728[/C][C]-0.272835[/C][/ROW]
[ROW][C]68[/C][C]27[/C][C]32.4437[/C][C]-5.44369[/C][/ROW]
[ROW][C]69[/C][C]40[/C][C]35.533[/C][C]4.46696[/C][/ROW]
[ROW][C]70[/C][C]37[/C][C]34.4655[/C][C]2.53447[/C][/ROW]
[ROW][C]71[/C][C]36[/C][C]34.3383[/C][C]1.66175[/C][/ROW]
[ROW][C]72[/C][C]38[/C][C]32.3299[/C][C]5.67012[/C][/ROW]
[ROW][C]73[/C][C]39[/C][C]34.6637[/C][C]4.33634[/C][/ROW]
[ROW][C]74[/C][C]41[/C][C]36.2102[/C][C]4.78977[/C][/ROW]
[ROW][C]75[/C][C]27[/C][C]34.083[/C][C]-7.08304[/C][/ROW]
[ROW][C]76[/C][C]30[/C][C]35.9165[/C][C]-5.91647[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.4974[/C][C]1.50258[/C][/ROW]
[ROW][C]78[/C][C]31[/C][C]33.8894[/C][C]-2.88945[/C][/ROW]
[ROW][C]79[/C][C]31[/C][C]31.2136[/C][C]-0.213559[/C][/ROW]
[ROW][C]80[/C][C]27[/C][C]35.085[/C][C]-8.08499[/C][/ROW]
[ROW][C]81[/C][C]36[/C][C]33.6998[/C][C]2.30023[/C][/ROW]
[ROW][C]82[/C][C]37[/C][C]34.4539[/C][C]2.54609[/C][/ROW]
[ROW][C]83[/C][C]33[/C][C]35.2242[/C][C]-2.22421[/C][/ROW]
[ROW][C]84[/C][C]34[/C][C]32.9779[/C][C]1.02214[/C][/ROW]
[ROW][C]85[/C][C]31[/C][C]33.4169[/C][C]-2.41689[/C][/ROW]
[ROW][C]86[/C][C]39[/C][C]35.1171[/C][C]3.88294[/C][/ROW]
[ROW][C]87[/C][C]34[/C][C]33.6032[/C][C]0.396824[/C][/ROW]
[ROW][C]88[/C][C]32[/C][C]31.8145[/C][C]0.185476[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.3295[/C][C]-0.329533[/C][/ROW]
[ROW][C]90[/C][C]36[/C][C]31.9898[/C][C]4.0102[/C][/ROW]
[ROW][C]91[/C][C]32[/C][C]35.2463[/C][C]-3.24625[/C][/ROW]
[ROW][C]92[/C][C]41[/C][C]34.5437[/C][C]6.45629[/C][/ROW]
[ROW][C]93[/C][C]28[/C][C]33.1846[/C][C]-5.18462[/C][/ROW]
[ROW][C]94[/C][C]30[/C][C]31.5996[/C][C]-1.5996[/C][/ROW]
[ROW][C]95[/C][C]36[/C][C]35.9958[/C][C]0.00419749[/C][/ROW]
[ROW][C]96[/C][C]35[/C][C]35.3705[/C][C]-0.370507[/C][/ROW]
[ROW][C]97[/C][C]31[/C][C]34.1259[/C][C]-3.12588[/C][/ROW]
[ROW][C]98[/C][C]34[/C][C]35.4626[/C][C]-1.46259[/C][/ROW]
[ROW][C]99[/C][C]36[/C][C]32.7468[/C][C]3.25323[/C][/ROW]
[ROW][C]100[/C][C]36[/C][C]36.0883[/C][C]-0.0882707[/C][/ROW]
[ROW][C]101[/C][C]35[/C][C]35.1523[/C][C]-0.15235[/C][/ROW]
[ROW][C]102[/C][C]37[/C][C]35.9799[/C][C]1.02012[/C][/ROW]
[ROW][C]103[/C][C]28[/C][C]32.8124[/C][C]-4.81237[/C][/ROW]
[ROW][C]104[/C][C]39[/C][C]33.6371[/C][C]5.36293[/C][/ROW]
[ROW][C]105[/C][C]32[/C][C]36.0136[/C][C]-4.01357[/C][/ROW]
[ROW][C]106[/C][C]35[/C][C]35.9502[/C][C]-0.950168[/C][/ROW]
[ROW][C]107[/C][C]39[/C][C]37.0322[/C][C]1.96782[/C][/ROW]
[ROW][C]108[/C][C]35[/C][C]34.5217[/C][C]0.478325[/C][/ROW]
[ROW][C]109[/C][C]42[/C][C]36.3939[/C][C]5.60611[/C][/ROW]
[ROW][C]110[/C][C]34[/C][C]32.5542[/C][C]1.44582[/C][/ROW]
[ROW][C]111[/C][C]33[/C][C]33.0171[/C][C]-0.0170527[/C][/ROW]
[ROW][C]112[/C][C]41[/C][C]33.3297[/C][C]7.67028[/C][/ROW]
[ROW][C]113[/C][C]33[/C][C]32.4639[/C][C]0.536115[/C][/ROW]
[ROW][C]114[/C][C]34[/C][C]34.6864[/C][C]-0.68643[/C][/ROW]
[ROW][C]115[/C][C]32[/C][C]35.8766[/C][C]-3.87663[/C][/ROW]
[ROW][C]116[/C][C]40[/C][C]33.3902[/C][C]6.60985[/C][/ROW]
[ROW][C]117[/C][C]40[/C][C]33.2638[/C][C]6.73616[/C][/ROW]
[ROW][C]118[/C][C]35[/C][C]33.0799[/C][C]1.92015[/C][/ROW]
[ROW][C]119[/C][C]36[/C][C]35.9055[/C][C]0.0945359[/C][/ROW]
[ROW][C]120[/C][C]37[/C][C]32.9472[/C][C]4.05277[/C][/ROW]
[ROW][C]121[/C][C]27[/C][C]33.0061[/C][C]-6.00605[/C][/ROW]
[ROW][C]122[/C][C]39[/C][C]35.4965[/C][C]3.50354[/C][/ROW]
[ROW][C]123[/C][C]38[/C][C]35.6155[/C][C]2.38446[/C][/ROW]
[ROW][C]124[/C][C]31[/C][C]34.9389[/C][C]-3.93886[/C][/ROW]
[ROW][C]125[/C][C]33[/C][C]33.2319[/C][C]-0.231911[/C][/ROW]
[ROW][C]126[/C][C]32[/C][C]35.9809[/C][C]-3.98093[/C][/ROW]
[ROW][C]127[/C][C]39[/C][C]38.3496[/C][C]0.650425[/C][/ROW]
[ROW][C]128[/C][C]36[/C][C]33.3792[/C][C]2.62078[/C][/ROW]
[ROW][C]129[/C][C]33[/C][C]33.8767[/C][C]-0.876705[/C][/ROW]
[ROW][C]130[/C][C]33[/C][C]32.9534[/C][C]0.046628[/C][/ROW]
[ROW][C]131[/C][C]32[/C][C]30.5106[/C][C]1.48941[/C][/ROW]
[ROW][C]132[/C][C]37[/C][C]36.1322[/C][C]0.867799[/C][/ROW]
[ROW][C]133[/C][C]30[/C][C]30.515[/C][C]-0.515027[/C][/ROW]
[ROW][C]134[/C][C]38[/C][C]35.1189[/C][C]2.8811[/C][/ROW]
[ROW][C]135[/C][C]29[/C][C]33.3104[/C][C]-4.3104[/C][/ROW]
[ROW][C]136[/C][C]22[/C][C]30.6615[/C][C]-8.66151[/C][/ROW]
[ROW][C]137[/C][C]35[/C][C]33.7792[/C][C]1.22084[/C][/ROW]
[ROW][C]138[/C][C]35[/C][C]31.2967[/C][C]3.70329[/C][/ROW]
[ROW][C]139[/C][C]34[/C][C]33.4264[/C][C]0.573587[/C][/ROW]
[ROW][C]140[/C][C]35[/C][C]31.7381[/C][C]3.26186[/C][/ROW]
[ROW][C]141[/C][C]34[/C][C]32.6345[/C][C]1.36553[/C][/ROW]
[ROW][C]142[/C][C]37[/C][C]32.096[/C][C]4.904[/C][/ROW]
[ROW][C]143[/C][C]35[/C][C]33.0658[/C][C]1.93418[/C][/ROW]
[ROW][C]144[/C][C]23[/C][C]32.8003[/C][C]-9.80029[/C][/ROW]
[ROW][C]145[/C][C]31[/C][C]35.4709[/C][C]-4.47087[/C][/ROW]
[ROW][C]146[/C][C]27[/C][C]33.768[/C][C]-6.76801[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]34.3495[/C][C]1.65053[/C][/ROW]
[ROW][C]148[/C][C]31[/C][C]33.2261[/C][C]-2.22611[/C][/ROW]
[ROW][C]149[/C][C]32[/C][C]33.6381[/C][C]-1.63806[/C][/ROW]
[ROW][C]150[/C][C]39[/C][C]34.4937[/C][C]4.50631[/C][/ROW]
[ROW][C]151[/C][C]37[/C][C]37.4929[/C][C]-0.492865[/C][/ROW]
[ROW][C]152[/C][C]38[/C][C]33.7633[/C][C]4.2367[/C][/ROW]
[ROW][C]153[/C][C]39[/C][C]33.6991[/C][C]5.30087[/C][/ROW]
[ROW][C]154[/C][C]34[/C][C]34.8673[/C][C]-0.867322[/C][/ROW]
[ROW][C]155[/C][C]31[/C][C]32.4422[/C][C]-1.4422[/C][/ROW]
[ROW][C]156[/C][C]32[/C][C]35.3158[/C][C]-3.31576[/C][/ROW]
[ROW][C]157[/C][C]37[/C][C]32.1087[/C][C]4.89132[/C][/ROW]
[ROW][C]158[/C][C]36[/C][C]33.4113[/C][C]2.5887[/C][/ROW]
[ROW][C]159[/C][C]32[/C][C]34.0294[/C][C]-2.0294[/C][/ROW]
[ROW][C]160[/C][C]38[/C][C]32.316[/C][C]5.68404[/C][/ROW]
[ROW][C]161[/C][C]36[/C][C]33.1829[/C][C]2.81706[/C][/ROW]
[ROW][C]162[/C][C]26[/C][C]30.4702[/C][C]-4.47019[/C][/ROW]
[ROW][C]163[/C][C]26[/C][C]31.9131[/C][C]-5.91306[/C][/ROW]
[ROW][C]164[/C][C]33[/C][C]36.3862[/C][C]-3.38625[/C][/ROW]
[ROW][C]165[/C][C]39[/C][C]33.6535[/C][C]5.34649[/C][/ROW]
[ROW][C]166[/C][C]30[/C][C]28.4976[/C][C]1.50239[/C][/ROW]
[ROW][C]167[/C][C]33[/C][C]32.1141[/C][C]0.88586[/C][/ROW]
[ROW][C]168[/C][C]25[/C][C]30.0934[/C][C]-5.09339[/C][/ROW]
[ROW][C]169[/C][C]38[/C][C]33.6722[/C][C]4.32775[/C][/ROW]
[ROW][C]170[/C][C]37[/C][C]31.1126[/C][C]5.88743[/C][/ROW]
[ROW][C]171[/C][C]31[/C][C]33.7811[/C][C]-2.78108[/C][/ROW]
[ROW][C]172[/C][C]37[/C][C]35.0306[/C][C]1.96935[/C][/ROW]
[ROW][C]173[/C][C]35[/C][C]36.1345[/C][C]-1.13453[/C][/ROW]
[ROW][C]174[/C][C]25[/C][C]30.3796[/C][C]-5.37965[/C][/ROW]
[ROW][C]175[/C][C]28[/C][C]34.5019[/C][C]-6.5019[/C][/ROW]
[ROW][C]176[/C][C]35[/C][C]33.0338[/C][C]1.96622[/C][/ROW]
[ROW][C]177[/C][C]33[/C][C]34.1741[/C][C]-1.17413[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.5133[/C][C]-1.51332[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]32.3786[/C][C]-1.37861[/C][/ROW]
[ROW][C]180[/C][C]37[/C][C]34.817[/C][C]2.183[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]34.8258[/C][C]1.17416[/C][/ROW]
[ROW][C]182[/C][C]30[/C][C]33.0246[/C][C]-3.02463[/C][/ROW]
[ROW][C]183[/C][C]36[/C][C]33.6938[/C][C]2.30621[/C][/ROW]
[ROW][C]184[/C][C]32[/C][C]35.7215[/C][C]-3.72152[/C][/ROW]
[ROW][C]185[/C][C]28[/C][C]28.2672[/C][C]-0.267232[/C][/ROW]
[ROW][C]186[/C][C]36[/C][C]33.3715[/C][C]2.62854[/C][/ROW]
[ROW][C]187[/C][C]34[/C][C]35.0206[/C][C]-1.02059[/C][/ROW]
[ROW][C]188[/C][C]31[/C][C]35.2032[/C][C]-4.20319[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.1865[/C][C]-2.18654[/C][/ROW]
[ROW][C]190[/C][C]36[/C][C]31.642[/C][C]4.35804[/C][/ROW]
[ROW][C]191[/C][C]36[/C][C]32.6956[/C][C]3.30442[/C][/ROW]
[ROW][C]192[/C][C]40[/C][C]35.8259[/C][C]4.17411[/C][/ROW]
[ROW][C]193[/C][C]33[/C][C]31.6706[/C][C]1.32937[/C][/ROW]
[ROW][C]194[/C][C]37[/C][C]34.3011[/C][C]2.69886[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]32.7152[/C][C]-0.715192[/C][/ROW]
[ROW][C]196[/C][C]38[/C][C]35.1908[/C][C]2.80923[/C][/ROW]
[ROW][C]197[/C][C]31[/C][C]33.8889[/C][C]-2.88894[/C][/ROW]
[ROW][C]198[/C][C]37[/C][C]33.887[/C][C]3.11304[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]32.8759[/C][C]0.124148[/C][/ROW]
[ROW][C]200[/C][C]32[/C][C]30.8508[/C][C]1.14925[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]32.354[/C][C]-2.35404[/C][/ROW]
[ROW][C]202[/C][C]30[/C][C]29.491[/C][C]0.509041[/C][/ROW]
[ROW][C]203[/C][C]31[/C][C]33.223[/C][C]-2.22295[/C][/ROW]
[ROW][C]204[/C][C]32[/C][C]33.47[/C][C]-1.47005[/C][/ROW]
[ROW][C]205[/C][C]34[/C][C]33.1329[/C][C]0.867145[/C][/ROW]
[ROW][C]206[/C][C]36[/C][C]33.9638[/C][C]2.0362[/C][/ROW]
[ROW][C]207[/C][C]37[/C][C]34.5612[/C][C]2.43878[/C][/ROW]
[ROW][C]208[/C][C]36[/C][C]34.5206[/C][C]1.47937[/C][/ROW]
[ROW][C]209[/C][C]33[/C][C]34.0427[/C][C]-1.0427[/C][/ROW]
[ROW][C]210[/C][C]33[/C][C]33.9437[/C][C]-0.943669[/C][/ROW]
[ROW][C]211[/C][C]33[/C][C]33.4492[/C][C]-0.449172[/C][/ROW]
[ROW][C]212[/C][C]44[/C][C]36.6989[/C][C]7.30109[/C][/ROW]
[ROW][C]213[/C][C]39[/C][C]33.1507[/C][C]5.84932[/C][/ROW]
[ROW][C]214[/C][C]32[/C][C]31.8022[/C][C]0.197788[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]34.4982[/C][C]0.501792[/C][/ROW]
[ROW][C]216[/C][C]25[/C][C]31.1462[/C][C]-6.1462[/C][/ROW]
[ROW][C]217[/C][C]35[/C][C]33.9652[/C][C]1.03483[/C][/ROW]
[ROW][C]218[/C][C]34[/C][C]35.8235[/C][C]-1.82348[/C][/ROW]
[ROW][C]219[/C][C]35[/C][C]33.8987[/C][C]1.10125[/C][/ROW]
[ROW][C]220[/C][C]39[/C][C]35.0087[/C][C]3.99132[/C][/ROW]
[ROW][C]221[/C][C]33[/C][C]34.13[/C][C]-1.13004[/C][/ROW]
[ROW][C]222[/C][C]36[/C][C]35.2814[/C][C]0.718607[/C][/ROW]
[ROW][C]223[/C][C]32[/C][C]33.5465[/C][C]-1.54646[/C][/ROW]
[ROW][C]224[/C][C]32[/C][C]32.0278[/C][C]-0.0277764[/C][/ROW]
[ROW][C]225[/C][C]36[/C][C]33.0453[/C][C]2.95473[/C][/ROW]
[ROW][C]226[/C][C]36[/C][C]31.6113[/C][C]4.3887[/C][/ROW]
[ROW][C]227[/C][C]32[/C][C]32.4342[/C][C]-0.434194[/C][/ROW]
[ROW][C]228[/C][C]34[/C][C]32.9893[/C][C]1.01069[/C][/ROW]
[ROW][C]229[/C][C]33[/C][C]32.9823[/C][C]0.0177204[/C][/ROW]
[ROW][C]230[/C][C]35[/C][C]33.1675[/C][C]1.83247[/C][/ROW]
[ROW][C]231[/C][C]30[/C][C]33.0192[/C][C]-3.01922[/C][/ROW]
[ROW][C]232[/C][C]38[/C][C]32.5464[/C][C]5.45362[/C][/ROW]
[ROW][C]233[/C][C]34[/C][C]32.5013[/C][C]1.49868[/C][/ROW]
[ROW][C]234[/C][C]33[/C][C]37.6433[/C][C]-4.64328[/C][/ROW]
[ROW][C]235[/C][C]32[/C][C]33.5823[/C][C]-1.58233[/C][/ROW]
[ROW][C]236[/C][C]31[/C][C]34.0062[/C][C]-3.00618[/C][/ROW]
[ROW][C]237[/C][C]30[/C][C]33.0723[/C][C]-3.07228[/C][/ROW]
[ROW][C]238[/C][C]27[/C][C]34.4338[/C][C]-7.43383[/C][/ROW]
[ROW][C]239[/C][C]31[/C][C]31.9868[/C][C]-0.98684[/C][/ROW]
[ROW][C]240[/C][C]30[/C][C]33.9087[/C][C]-3.90872[/C][/ROW]
[ROW][C]241[/C][C]32[/C][C]30.2902[/C][C]1.70975[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.668[/C][C]1.33203[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]29.6143[/C][C]-1.6143[/C][/ROW]
[ROW][C]244[/C][C]33[/C][C]33.3765[/C][C]-0.37655[/C][/ROW]
[ROW][C]245[/C][C]31[/C][C]35.1965[/C][C]-4.19647[/C][/ROW]
[ROW][C]246[/C][C]35[/C][C]31.0261[/C][C]3.97393[/C][/ROW]
[ROW][C]247[/C][C]35[/C][C]32.6897[/C][C]2.31033[/C][/ROW]
[ROW][C]248[/C][C]32[/C][C]33.7232[/C][C]-1.7232[/C][/ROW]
[ROW][C]249[/C][C]21[/C][C]26.7358[/C][C]-5.73578[/C][/ROW]
[ROW][C]250[/C][C]20[/C][C]27.7059[/C][C]-7.70586[/C][/ROW]
[ROW][C]251[/C][C]34[/C][C]31.6913[/C][C]2.30874[/C][/ROW]
[ROW][C]252[/C][C]32[/C][C]32.4105[/C][C]-0.410486[/C][/ROW]
[ROW][C]253[/C][C]34[/C][C]33.6988[/C][C]0.301175[/C][/ROW]
[ROW][C]254[/C][C]32[/C][C]33.3983[/C][C]-1.39833[/C][/ROW]
[ROW][C]255[/C][C]33[/C][C]34.6185[/C][C]-1.61849[/C][/ROW]
[ROW][C]256[/C][C]33[/C][C]33.7454[/C][C]-0.745396[/C][/ROW]
[ROW][C]257[/C][C]37[/C][C]34.5725[/C][C]2.4275[/C][/ROW]
[ROW][C]258[/C][C]32[/C][C]32.0044[/C][C]-0.00440256[/C][/ROW]
[ROW][C]259[/C][C]34[/C][C]34.9594[/C][C]-0.959378[/C][/ROW]
[ROW][C]260[/C][C]30[/C][C]31.8001[/C][C]-1.80007[/C][/ROW]
[ROW][C]261[/C][C]30[/C][C]30.9923[/C][C]-0.992284[/C][/ROW]
[ROW][C]262[/C][C]38[/C][C]33.5561[/C][C]4.4439[/C][/ROW]
[ROW][C]263[/C][C]36[/C][C]35.1871[/C][C]0.812889[/C][/ROW]
[ROW][C]264[/C][C]32[/C][C]31.5001[/C][C]0.499878[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253717&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253717&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
13836.3081.69196
23236.1127-4.11267
33532.94742.05263
43331.70211.29795
53733.98133.01874
62933.8898-4.88981
73136.3729-5.37286
83634.13261.8674
93534.55330.446715
103834.76273.23728
113135.5069-4.50692
123434.7845-0.784519
133535.4811-0.481146
143835.8572.14302
153734.29922.70081
163332.90620.093768
173234.4492-2.44923
183836.38781.61225
193836.11321.88682
203233.095-1.09503
213333.0765-0.0764964
223132.612-1.61201
233836.4451.55501
243934.92084.07922
253236.3905-4.39048
263237.0262-5.02616
273534.64410.355936
283733.6843.316
293333.6604-0.660405
303333.3276-0.327563
313132.704-1.70401
323229.87322.12681
333134.7819-3.78189
343734.10462.89542
353033.7407-3.74067
363331.73461.26536
373130.54760.452383
383334.5768-1.57684
393131.7703-0.770301
403334.0811-1.08112
413235.0105-3.01052
423333.8294-0.829405
433236.4736-4.47361
443333.6816-0.681629
452835.1376-7.13758
463534.45010.549945
473935.47463.5254
483433.37070.629266
493834.84413.15587
503235.3794-3.37939
513833.47654.52353
523032.6254-2.6254
533332.5140.485997
543834.0073.99298
553231.19570.804255
563534.30670.693312
573436.179-2.17905
583431.90152.09846
593634.92431.0757
603434.1178-0.117769
612830.8933-2.89328
623435.6859-1.6859
633534.23630.763654
643532.23222.76776
653133.9187-2.91875
663734.62232.3777
673535.2728-0.272835
682732.4437-5.44369
694035.5334.46696
703734.46552.53447
713634.33831.66175
723832.32995.67012
733934.66374.33634
744136.21024.78977
752734.083-7.08304
763035.9165-5.91647
773735.49741.50258
783133.8894-2.88945
793131.2136-0.213559
802735.085-8.08499
813633.69982.30023
823734.45392.54609
833335.2242-2.22421
843432.97791.02214
853133.4169-2.41689
863935.11713.88294
873433.60320.396824
883231.81450.185476
893333.3295-0.329533
903631.98984.0102
913235.2463-3.24625
924134.54376.45629
932833.1846-5.18462
943031.5996-1.5996
953635.99580.00419749
963535.3705-0.370507
973134.1259-3.12588
983435.4626-1.46259
993632.74683.25323
1003636.0883-0.0882707
1013535.1523-0.15235
1023735.97991.02012
1032832.8124-4.81237
1043933.63715.36293
1053236.0136-4.01357
1063535.9502-0.950168
1073937.03221.96782
1083534.52170.478325
1094236.39395.60611
1103432.55421.44582
1113333.0171-0.0170527
1124133.32977.67028
1133332.46390.536115
1143434.6864-0.68643
1153235.8766-3.87663
1164033.39026.60985
1174033.26386.73616
1183533.07991.92015
1193635.90550.0945359
1203732.94724.05277
1212733.0061-6.00605
1223935.49653.50354
1233835.61552.38446
1243134.9389-3.93886
1253333.2319-0.231911
1263235.9809-3.98093
1273938.34960.650425
1283633.37922.62078
1293333.8767-0.876705
1303332.95340.046628
1313230.51061.48941
1323736.13220.867799
1333030.515-0.515027
1343835.11892.8811
1352933.3104-4.3104
1362230.6615-8.66151
1373533.77921.22084
1383531.29673.70329
1393433.42640.573587
1403531.73813.26186
1413432.63451.36553
1423732.0964.904
1433533.06581.93418
1442332.8003-9.80029
1453135.4709-4.47087
1462733.768-6.76801
1473634.34951.65053
1483133.2261-2.22611
1493233.6381-1.63806
1503934.49374.50631
1513737.4929-0.492865
1523833.76334.2367
1533933.69915.30087
1543434.8673-0.867322
1553132.4422-1.4422
1563235.3158-3.31576
1573732.10874.89132
1583633.41132.5887
1593234.0294-2.0294
1603832.3165.68404
1613633.18292.81706
1622630.4702-4.47019
1632631.9131-5.91306
1643336.3862-3.38625
1653933.65355.34649
1663028.49761.50239
1673332.11410.88586
1682530.0934-5.09339
1693833.67224.32775
1703731.11265.88743
1713133.7811-2.78108
1723735.03061.96935
1733536.1345-1.13453
1742530.3796-5.37965
1752834.5019-6.5019
1763533.03381.96622
1773334.1741-1.17413
1783031.5133-1.51332
1793132.3786-1.37861
1803734.8172.183
1813634.82581.17416
1823033.0246-3.02463
1833633.69382.30621
1843235.7215-3.72152
1852828.2672-0.267232
1863633.37152.62854
1873435.0206-1.02059
1883135.2032-4.20319
1892830.1865-2.18654
1903631.6424.35804
1913632.69563.30442
1924035.82594.17411
1933331.67061.32937
1943734.30112.69886
1953232.7152-0.715192
1963835.19082.80923
1973133.8889-2.88894
1983733.8873.11304
1993332.87590.124148
2003230.85081.14925
2013032.354-2.35404
2023029.4910.509041
2033133.223-2.22295
2043233.47-1.47005
2053433.13290.867145
2063633.96382.0362
2073734.56122.43878
2083634.52061.47937
2093334.0427-1.0427
2103333.9437-0.943669
2113333.4492-0.449172
2124436.69897.30109
2133933.15075.84932
2143231.80220.197788
2153534.49820.501792
2162531.1462-6.1462
2173533.96521.03483
2183435.8235-1.82348
2193533.89871.10125
2203935.00873.99132
2213334.13-1.13004
2223635.28140.718607
2233233.5465-1.54646
2243232.0278-0.0277764
2253633.04532.95473
2263631.61134.3887
2273232.4342-0.434194
2283432.98931.01069
2293332.98230.0177204
2303533.16751.83247
2313033.0192-3.01922
2323832.54645.45362
2333432.50131.49868
2343337.6433-4.64328
2353233.5823-1.58233
2363134.0062-3.00618
2373033.0723-3.07228
2382734.4338-7.43383
2393131.9868-0.98684
2403033.9087-3.90872
2413230.29021.70975
2423533.6681.33203
2432829.6143-1.6143
2443333.3765-0.37655
2453135.1965-4.19647
2463531.02613.97393
2473532.68972.31033
2483233.7232-1.7232
2492126.7358-5.73578
2502027.7059-7.70586
2513431.69132.30874
2523232.4105-0.410486
2533433.69880.301175
2543233.3983-1.39833
2553334.6185-1.61849
2563333.7454-0.745396
2573734.57252.4275
2583232.0044-0.00440256
2593434.9594-0.959378
2603031.8001-1.80007
2613030.9923-0.992284
2623833.55614.4439
2633635.18710.812889
2643231.50010.499878






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.2129830.4259660.787017
120.6539320.6921350.346068
130.6010350.7979290.398965
140.590670.8186590.40933
150.5400110.9199790.459989
160.5520660.8958670.447934
170.5032750.9934510.496725
180.5429740.9140520.457026
190.4756710.9513420.524329
200.4205440.8410880.579456
210.3387250.677450.661275
220.3492450.698490.650755
230.2874160.5748310.712584
240.2908020.5816040.709198
250.3242110.6484220.675789
260.4330450.866090.566955
270.3808770.7617540.619123
280.3500790.7001580.649921
290.293290.5865790.70671
300.2406990.4813990.759301
310.2118490.4236980.788151
320.1704960.3409910.829504
330.1576230.3152460.842377
340.1711940.3423890.828806
350.1816070.3632140.818393
360.1594670.3189350.840533
370.1265230.2530460.873477
380.1006560.2013120.899344
390.07914420.1582880.920856
400.06043730.1208750.939563
410.04880920.09761840.951191
420.0363440.07268810.963656
430.04163940.08327880.958361
440.03089950.06179910.9691
450.04911640.09823280.950884
460.04183880.08367770.958161
470.06515230.1303050.934848
480.05485190.1097040.945148
490.08148070.1629610.918519
500.07277750.1455550.927222
510.08653810.1730760.913462
520.07981190.1596240.920188
530.06326090.1265220.936739
540.07033920.1406780.929661
550.0597420.1194840.940258
560.05878210.1175640.941218
570.04795670.09591340.952043
580.03847080.07694160.961529
590.03271480.06542960.967285
600.0251390.0502780.974861
610.02786560.05573110.972134
620.02189260.04378520.978107
630.01668880.03337770.983311
640.01386680.02773360.986133
650.01445070.02890130.985549
660.01294840.02589680.987052
670.009696550.01939310.990303
680.01929350.0385870.980707
690.02623320.05246640.973767
700.02459750.0491950.975403
710.020960.04191990.97904
720.02765710.05531410.972343
730.03184330.06368650.968157
740.03945080.07890170.960549
750.09335240.1867050.906648
760.1106120.2212230.889388
770.09389620.1877920.906104
780.09055930.1811190.909441
790.07970580.1594120.920294
800.2067710.4135410.793229
810.1939560.3879130.806044
820.1843250.3686510.815675
830.1716530.3433050.828347
840.148830.2976590.85117
850.1359260.2718530.864074
860.16410.3281990.8359
870.1409890.2819770.859011
880.121950.24390.87805
890.1038350.207670.896165
900.1047090.2094180.895291
910.1147890.2295780.885211
920.1771080.3542150.822892
930.2344570.4689140.765543
940.2226360.4452720.777364
950.1987830.3975670.801217
960.1741080.3482170.825892
970.1687750.3375490.831225
980.1509850.3019690.849015
990.1478380.2956760.852162
1000.1276730.2553460.872327
1010.1111930.2223870.888807
1020.09664180.1932840.903358
1030.1215440.2430880.878456
1040.1531970.3063930.846803
1050.1649050.3298090.835095
1060.1456950.2913910.854305
1070.1339270.2678540.866073
1080.1186280.2372570.881372
1090.1572620.3145240.842738
1100.1377980.2755970.862202
1110.1190970.2381930.880903
1120.226990.4539790.77301
1130.2045870.4091750.795413
1140.1858730.3717470.814127
1150.2000730.4001460.799927
1160.2585240.5170480.741476
1170.34370.68740.6563
1180.3165720.6331440.683428
1190.2853310.5706620.714669
1200.2886280.5772570.711372
1210.3969150.793830.603085
1220.3942370.7884750.605763
1230.3729880.7459770.627012
1240.4031310.8062610.596869
1250.3706240.7412490.629376
1260.393810.787620.60619
1270.3618960.7237920.638104
1280.3427120.6854230.657288
1290.3196280.6392570.680372
1300.2888330.5776660.711167
1310.2655880.5311770.734412
1320.2404330.4808660.759567
1330.2268680.4537370.773132
1340.2164970.4329930.783503
1350.2470790.4941580.752921
1360.4656980.9313970.534302
1370.4327990.8655980.567201
1380.4388270.8776530.561173
1390.405240.810480.59476
1400.4021180.8042370.597882
1410.3720450.7440890.627955
1420.4065760.8131520.593424
1430.3816780.7633570.618322
1440.6773430.6453130.322657
1450.7124390.5751210.287561
1460.8182110.3635790.181789
1470.7991010.4017980.200899
1480.7917920.4164160.208208
1490.7773340.4453320.222666
1500.7948870.4102260.205113
1510.7710610.4578770.228939
1520.780990.4380210.21901
1530.8101570.3796860.189843
1540.790970.4180590.20903
1550.7712670.4574670.228733
1560.7767190.4465610.223281
1570.803160.3936790.19684
1580.7924590.4150820.207541
1590.7857610.4284790.214239
1600.8303550.3392910.169645
1610.8242470.3515060.175753
1620.8476750.304650.152325
1630.8980680.2038650.101932
1640.910160.1796810.0898403
1650.9258750.1482490.0741245
1660.9186590.1626820.0813409
1670.9039260.1921470.0960737
1680.9282920.1434160.0717081
1690.9313660.1372690.0686343
1700.9507970.09840540.0492027
1710.9481260.1037490.0518744
1720.939950.12010.0600498
1730.9316860.1366280.0683139
1740.9486140.1027730.0513865
1750.9763760.04724880.0236244
1760.9716430.05671430.0283572
1770.9670820.06583680.0329184
1780.962460.07507990.03754
1790.9560040.08799150.0439958
1800.9480810.1038370.0519187
1810.9374790.1250430.0625214
1820.9379860.1240280.0620139
1830.9288610.1422780.0711389
1840.9445450.1109090.0554546
1850.9325940.1348130.0674064
1860.9229560.1540880.0770441
1870.9142960.1714080.0857039
1880.9461370.1077270.0538634
1890.9411190.1177620.0588811
1900.9450050.1099910.0549953
1910.9489830.1020340.0510168
1920.9486720.1026570.0513284
1930.9377160.1245690.0622843
1940.9315210.1369590.0684793
1950.91820.1636010.0818003
1960.9097830.1804340.090217
1970.9248730.1502530.0751266
1980.9133090.1733820.0866908
1990.8947190.2105620.105281
2000.8749530.2500950.125047
2010.8691660.2616680.130834
2020.8463440.3073130.153656
2030.8406530.3186950.159347
2040.8157870.3684250.184213
2050.7843130.4313740.215687
2060.7551350.4897290.244865
2070.7239870.5520250.276013
2080.6992010.6015990.300799
2090.6672830.6654330.332717
2100.6446470.7107050.355353
2110.6021670.7956670.397833
2120.7145790.5708410.285421
2130.7599460.4801090.240054
2140.7204130.5591740.279587
2150.6791540.6416910.320846
2160.7649260.4701490.235074
2170.7252540.5494910.274746
2180.7113210.5773590.288679
2190.666970.6660610.33303
2200.6738870.6522260.326113
2210.6308730.7382550.369127
2220.5884230.8231540.411577
2230.5497250.900550.450275
2240.4968790.9937580.503121
2250.5378520.9242970.462148
2260.5980090.8039820.401991
2270.5801120.8397750.419888
2280.5570280.8859430.442972
2290.5010480.9979040.498952
2300.4937680.9875360.506232
2310.4525630.9051260.547437
2320.7317910.5364180.268209
2330.7819590.4360830.218041
2340.8052370.3895260.194763
2350.7662490.4675010.233751
2360.7184330.5631340.281567
2370.6870510.6258980.312949
2380.7369610.5260780.263039
2390.6747560.6504870.325244
2400.6986690.6026620.301331
2410.6593170.6813670.340683
2420.6559920.6880160.344008
2430.5923910.8152180.407609
2440.5228680.9542640.477132
2450.7629990.4740030.237001
2460.8613070.2773850.138693
2470.9003360.1993270.0996637
2480.8437070.3125860.156293
2490.7710830.4578330.228917
2500.8147240.3705520.185276
2510.8205890.3588220.179411
2520.7458880.5082240.254112
2530.7996030.4007940.200397

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.212983 & 0.425966 & 0.787017 \tabularnewline
12 & 0.653932 & 0.692135 & 0.346068 \tabularnewline
13 & 0.601035 & 0.797929 & 0.398965 \tabularnewline
14 & 0.59067 & 0.818659 & 0.40933 \tabularnewline
15 & 0.540011 & 0.919979 & 0.459989 \tabularnewline
16 & 0.552066 & 0.895867 & 0.447934 \tabularnewline
17 & 0.503275 & 0.993451 & 0.496725 \tabularnewline
18 & 0.542974 & 0.914052 & 0.457026 \tabularnewline
19 & 0.475671 & 0.951342 & 0.524329 \tabularnewline
20 & 0.420544 & 0.841088 & 0.579456 \tabularnewline
21 & 0.338725 & 0.67745 & 0.661275 \tabularnewline
22 & 0.349245 & 0.69849 & 0.650755 \tabularnewline
23 & 0.287416 & 0.574831 & 0.712584 \tabularnewline
24 & 0.290802 & 0.581604 & 0.709198 \tabularnewline
25 & 0.324211 & 0.648422 & 0.675789 \tabularnewline
26 & 0.433045 & 0.86609 & 0.566955 \tabularnewline
27 & 0.380877 & 0.761754 & 0.619123 \tabularnewline
28 & 0.350079 & 0.700158 & 0.649921 \tabularnewline
29 & 0.29329 & 0.586579 & 0.70671 \tabularnewline
30 & 0.240699 & 0.481399 & 0.759301 \tabularnewline
31 & 0.211849 & 0.423698 & 0.788151 \tabularnewline
32 & 0.170496 & 0.340991 & 0.829504 \tabularnewline
33 & 0.157623 & 0.315246 & 0.842377 \tabularnewline
34 & 0.171194 & 0.342389 & 0.828806 \tabularnewline
35 & 0.181607 & 0.363214 & 0.818393 \tabularnewline
36 & 0.159467 & 0.318935 & 0.840533 \tabularnewline
37 & 0.126523 & 0.253046 & 0.873477 \tabularnewline
38 & 0.100656 & 0.201312 & 0.899344 \tabularnewline
39 & 0.0791442 & 0.158288 & 0.920856 \tabularnewline
40 & 0.0604373 & 0.120875 & 0.939563 \tabularnewline
41 & 0.0488092 & 0.0976184 & 0.951191 \tabularnewline
42 & 0.036344 & 0.0726881 & 0.963656 \tabularnewline
43 & 0.0416394 & 0.0832788 & 0.958361 \tabularnewline
44 & 0.0308995 & 0.0617991 & 0.9691 \tabularnewline
45 & 0.0491164 & 0.0982328 & 0.950884 \tabularnewline
46 & 0.0418388 & 0.0836777 & 0.958161 \tabularnewline
47 & 0.0651523 & 0.130305 & 0.934848 \tabularnewline
48 & 0.0548519 & 0.109704 & 0.945148 \tabularnewline
49 & 0.0814807 & 0.162961 & 0.918519 \tabularnewline
50 & 0.0727775 & 0.145555 & 0.927222 \tabularnewline
51 & 0.0865381 & 0.173076 & 0.913462 \tabularnewline
52 & 0.0798119 & 0.159624 & 0.920188 \tabularnewline
53 & 0.0632609 & 0.126522 & 0.936739 \tabularnewline
54 & 0.0703392 & 0.140678 & 0.929661 \tabularnewline
55 & 0.059742 & 0.119484 & 0.940258 \tabularnewline
56 & 0.0587821 & 0.117564 & 0.941218 \tabularnewline
57 & 0.0479567 & 0.0959134 & 0.952043 \tabularnewline
58 & 0.0384708 & 0.0769416 & 0.961529 \tabularnewline
59 & 0.0327148 & 0.0654296 & 0.967285 \tabularnewline
60 & 0.025139 & 0.050278 & 0.974861 \tabularnewline
61 & 0.0278656 & 0.0557311 & 0.972134 \tabularnewline
62 & 0.0218926 & 0.0437852 & 0.978107 \tabularnewline
63 & 0.0166888 & 0.0333777 & 0.983311 \tabularnewline
64 & 0.0138668 & 0.0277336 & 0.986133 \tabularnewline
65 & 0.0144507 & 0.0289013 & 0.985549 \tabularnewline
66 & 0.0129484 & 0.0258968 & 0.987052 \tabularnewline
67 & 0.00969655 & 0.0193931 & 0.990303 \tabularnewline
68 & 0.0192935 & 0.038587 & 0.980707 \tabularnewline
69 & 0.0262332 & 0.0524664 & 0.973767 \tabularnewline
70 & 0.0245975 & 0.049195 & 0.975403 \tabularnewline
71 & 0.02096 & 0.0419199 & 0.97904 \tabularnewline
72 & 0.0276571 & 0.0553141 & 0.972343 \tabularnewline
73 & 0.0318433 & 0.0636865 & 0.968157 \tabularnewline
74 & 0.0394508 & 0.0789017 & 0.960549 \tabularnewline
75 & 0.0933524 & 0.186705 & 0.906648 \tabularnewline
76 & 0.110612 & 0.221223 & 0.889388 \tabularnewline
77 & 0.0938962 & 0.187792 & 0.906104 \tabularnewline
78 & 0.0905593 & 0.181119 & 0.909441 \tabularnewline
79 & 0.0797058 & 0.159412 & 0.920294 \tabularnewline
80 & 0.206771 & 0.413541 & 0.793229 \tabularnewline
81 & 0.193956 & 0.387913 & 0.806044 \tabularnewline
82 & 0.184325 & 0.368651 & 0.815675 \tabularnewline
83 & 0.171653 & 0.343305 & 0.828347 \tabularnewline
84 & 0.14883 & 0.297659 & 0.85117 \tabularnewline
85 & 0.135926 & 0.271853 & 0.864074 \tabularnewline
86 & 0.1641 & 0.328199 & 0.8359 \tabularnewline
87 & 0.140989 & 0.281977 & 0.859011 \tabularnewline
88 & 0.12195 & 0.2439 & 0.87805 \tabularnewline
89 & 0.103835 & 0.20767 & 0.896165 \tabularnewline
90 & 0.104709 & 0.209418 & 0.895291 \tabularnewline
91 & 0.114789 & 0.229578 & 0.885211 \tabularnewline
92 & 0.177108 & 0.354215 & 0.822892 \tabularnewline
93 & 0.234457 & 0.468914 & 0.765543 \tabularnewline
94 & 0.222636 & 0.445272 & 0.777364 \tabularnewline
95 & 0.198783 & 0.397567 & 0.801217 \tabularnewline
96 & 0.174108 & 0.348217 & 0.825892 \tabularnewline
97 & 0.168775 & 0.337549 & 0.831225 \tabularnewline
98 & 0.150985 & 0.301969 & 0.849015 \tabularnewline
99 & 0.147838 & 0.295676 & 0.852162 \tabularnewline
100 & 0.127673 & 0.255346 & 0.872327 \tabularnewline
101 & 0.111193 & 0.222387 & 0.888807 \tabularnewline
102 & 0.0966418 & 0.193284 & 0.903358 \tabularnewline
103 & 0.121544 & 0.243088 & 0.878456 \tabularnewline
104 & 0.153197 & 0.306393 & 0.846803 \tabularnewline
105 & 0.164905 & 0.329809 & 0.835095 \tabularnewline
106 & 0.145695 & 0.291391 & 0.854305 \tabularnewline
107 & 0.133927 & 0.267854 & 0.866073 \tabularnewline
108 & 0.118628 & 0.237257 & 0.881372 \tabularnewline
109 & 0.157262 & 0.314524 & 0.842738 \tabularnewline
110 & 0.137798 & 0.275597 & 0.862202 \tabularnewline
111 & 0.119097 & 0.238193 & 0.880903 \tabularnewline
112 & 0.22699 & 0.453979 & 0.77301 \tabularnewline
113 & 0.204587 & 0.409175 & 0.795413 \tabularnewline
114 & 0.185873 & 0.371747 & 0.814127 \tabularnewline
115 & 0.200073 & 0.400146 & 0.799927 \tabularnewline
116 & 0.258524 & 0.517048 & 0.741476 \tabularnewline
117 & 0.3437 & 0.6874 & 0.6563 \tabularnewline
118 & 0.316572 & 0.633144 & 0.683428 \tabularnewline
119 & 0.285331 & 0.570662 & 0.714669 \tabularnewline
120 & 0.288628 & 0.577257 & 0.711372 \tabularnewline
121 & 0.396915 & 0.79383 & 0.603085 \tabularnewline
122 & 0.394237 & 0.788475 & 0.605763 \tabularnewline
123 & 0.372988 & 0.745977 & 0.627012 \tabularnewline
124 & 0.403131 & 0.806261 & 0.596869 \tabularnewline
125 & 0.370624 & 0.741249 & 0.629376 \tabularnewline
126 & 0.39381 & 0.78762 & 0.60619 \tabularnewline
127 & 0.361896 & 0.723792 & 0.638104 \tabularnewline
128 & 0.342712 & 0.685423 & 0.657288 \tabularnewline
129 & 0.319628 & 0.639257 & 0.680372 \tabularnewline
130 & 0.288833 & 0.577666 & 0.711167 \tabularnewline
131 & 0.265588 & 0.531177 & 0.734412 \tabularnewline
132 & 0.240433 & 0.480866 & 0.759567 \tabularnewline
133 & 0.226868 & 0.453737 & 0.773132 \tabularnewline
134 & 0.216497 & 0.432993 & 0.783503 \tabularnewline
135 & 0.247079 & 0.494158 & 0.752921 \tabularnewline
136 & 0.465698 & 0.931397 & 0.534302 \tabularnewline
137 & 0.432799 & 0.865598 & 0.567201 \tabularnewline
138 & 0.438827 & 0.877653 & 0.561173 \tabularnewline
139 & 0.40524 & 0.81048 & 0.59476 \tabularnewline
140 & 0.402118 & 0.804237 & 0.597882 \tabularnewline
141 & 0.372045 & 0.744089 & 0.627955 \tabularnewline
142 & 0.406576 & 0.813152 & 0.593424 \tabularnewline
143 & 0.381678 & 0.763357 & 0.618322 \tabularnewline
144 & 0.677343 & 0.645313 & 0.322657 \tabularnewline
145 & 0.712439 & 0.575121 & 0.287561 \tabularnewline
146 & 0.818211 & 0.363579 & 0.181789 \tabularnewline
147 & 0.799101 & 0.401798 & 0.200899 \tabularnewline
148 & 0.791792 & 0.416416 & 0.208208 \tabularnewline
149 & 0.777334 & 0.445332 & 0.222666 \tabularnewline
150 & 0.794887 & 0.410226 & 0.205113 \tabularnewline
151 & 0.771061 & 0.457877 & 0.228939 \tabularnewline
152 & 0.78099 & 0.438021 & 0.21901 \tabularnewline
153 & 0.810157 & 0.379686 & 0.189843 \tabularnewline
154 & 0.79097 & 0.418059 & 0.20903 \tabularnewline
155 & 0.771267 & 0.457467 & 0.228733 \tabularnewline
156 & 0.776719 & 0.446561 & 0.223281 \tabularnewline
157 & 0.80316 & 0.393679 & 0.19684 \tabularnewline
158 & 0.792459 & 0.415082 & 0.207541 \tabularnewline
159 & 0.785761 & 0.428479 & 0.214239 \tabularnewline
160 & 0.830355 & 0.339291 & 0.169645 \tabularnewline
161 & 0.824247 & 0.351506 & 0.175753 \tabularnewline
162 & 0.847675 & 0.30465 & 0.152325 \tabularnewline
163 & 0.898068 & 0.203865 & 0.101932 \tabularnewline
164 & 0.91016 & 0.179681 & 0.0898403 \tabularnewline
165 & 0.925875 & 0.148249 & 0.0741245 \tabularnewline
166 & 0.918659 & 0.162682 & 0.0813409 \tabularnewline
167 & 0.903926 & 0.192147 & 0.0960737 \tabularnewline
168 & 0.928292 & 0.143416 & 0.0717081 \tabularnewline
169 & 0.931366 & 0.137269 & 0.0686343 \tabularnewline
170 & 0.950797 & 0.0984054 & 0.0492027 \tabularnewline
171 & 0.948126 & 0.103749 & 0.0518744 \tabularnewline
172 & 0.93995 & 0.1201 & 0.0600498 \tabularnewline
173 & 0.931686 & 0.136628 & 0.0683139 \tabularnewline
174 & 0.948614 & 0.102773 & 0.0513865 \tabularnewline
175 & 0.976376 & 0.0472488 & 0.0236244 \tabularnewline
176 & 0.971643 & 0.0567143 & 0.0283572 \tabularnewline
177 & 0.967082 & 0.0658368 & 0.0329184 \tabularnewline
178 & 0.96246 & 0.0750799 & 0.03754 \tabularnewline
179 & 0.956004 & 0.0879915 & 0.0439958 \tabularnewline
180 & 0.948081 & 0.103837 & 0.0519187 \tabularnewline
181 & 0.937479 & 0.125043 & 0.0625214 \tabularnewline
182 & 0.937986 & 0.124028 & 0.0620139 \tabularnewline
183 & 0.928861 & 0.142278 & 0.0711389 \tabularnewline
184 & 0.944545 & 0.110909 & 0.0554546 \tabularnewline
185 & 0.932594 & 0.134813 & 0.0674064 \tabularnewline
186 & 0.922956 & 0.154088 & 0.0770441 \tabularnewline
187 & 0.914296 & 0.171408 & 0.0857039 \tabularnewline
188 & 0.946137 & 0.107727 & 0.0538634 \tabularnewline
189 & 0.941119 & 0.117762 & 0.0588811 \tabularnewline
190 & 0.945005 & 0.109991 & 0.0549953 \tabularnewline
191 & 0.948983 & 0.102034 & 0.0510168 \tabularnewline
192 & 0.948672 & 0.102657 & 0.0513284 \tabularnewline
193 & 0.937716 & 0.124569 & 0.0622843 \tabularnewline
194 & 0.931521 & 0.136959 & 0.0684793 \tabularnewline
195 & 0.9182 & 0.163601 & 0.0818003 \tabularnewline
196 & 0.909783 & 0.180434 & 0.090217 \tabularnewline
197 & 0.924873 & 0.150253 & 0.0751266 \tabularnewline
198 & 0.913309 & 0.173382 & 0.0866908 \tabularnewline
199 & 0.894719 & 0.210562 & 0.105281 \tabularnewline
200 & 0.874953 & 0.250095 & 0.125047 \tabularnewline
201 & 0.869166 & 0.261668 & 0.130834 \tabularnewline
202 & 0.846344 & 0.307313 & 0.153656 \tabularnewline
203 & 0.840653 & 0.318695 & 0.159347 \tabularnewline
204 & 0.815787 & 0.368425 & 0.184213 \tabularnewline
205 & 0.784313 & 0.431374 & 0.215687 \tabularnewline
206 & 0.755135 & 0.489729 & 0.244865 \tabularnewline
207 & 0.723987 & 0.552025 & 0.276013 \tabularnewline
208 & 0.699201 & 0.601599 & 0.300799 \tabularnewline
209 & 0.667283 & 0.665433 & 0.332717 \tabularnewline
210 & 0.644647 & 0.710705 & 0.355353 \tabularnewline
211 & 0.602167 & 0.795667 & 0.397833 \tabularnewline
212 & 0.714579 & 0.570841 & 0.285421 \tabularnewline
213 & 0.759946 & 0.480109 & 0.240054 \tabularnewline
214 & 0.720413 & 0.559174 & 0.279587 \tabularnewline
215 & 0.679154 & 0.641691 & 0.320846 \tabularnewline
216 & 0.764926 & 0.470149 & 0.235074 \tabularnewline
217 & 0.725254 & 0.549491 & 0.274746 \tabularnewline
218 & 0.711321 & 0.577359 & 0.288679 \tabularnewline
219 & 0.66697 & 0.666061 & 0.33303 \tabularnewline
220 & 0.673887 & 0.652226 & 0.326113 \tabularnewline
221 & 0.630873 & 0.738255 & 0.369127 \tabularnewline
222 & 0.588423 & 0.823154 & 0.411577 \tabularnewline
223 & 0.549725 & 0.90055 & 0.450275 \tabularnewline
224 & 0.496879 & 0.993758 & 0.503121 \tabularnewline
225 & 0.537852 & 0.924297 & 0.462148 \tabularnewline
226 & 0.598009 & 0.803982 & 0.401991 \tabularnewline
227 & 0.580112 & 0.839775 & 0.419888 \tabularnewline
228 & 0.557028 & 0.885943 & 0.442972 \tabularnewline
229 & 0.501048 & 0.997904 & 0.498952 \tabularnewline
230 & 0.493768 & 0.987536 & 0.506232 \tabularnewline
231 & 0.452563 & 0.905126 & 0.547437 \tabularnewline
232 & 0.731791 & 0.536418 & 0.268209 \tabularnewline
233 & 0.781959 & 0.436083 & 0.218041 \tabularnewline
234 & 0.805237 & 0.389526 & 0.194763 \tabularnewline
235 & 0.766249 & 0.467501 & 0.233751 \tabularnewline
236 & 0.718433 & 0.563134 & 0.281567 \tabularnewline
237 & 0.687051 & 0.625898 & 0.312949 \tabularnewline
238 & 0.736961 & 0.526078 & 0.263039 \tabularnewline
239 & 0.674756 & 0.650487 & 0.325244 \tabularnewline
240 & 0.698669 & 0.602662 & 0.301331 \tabularnewline
241 & 0.659317 & 0.681367 & 0.340683 \tabularnewline
242 & 0.655992 & 0.688016 & 0.344008 \tabularnewline
243 & 0.592391 & 0.815218 & 0.407609 \tabularnewline
244 & 0.522868 & 0.954264 & 0.477132 \tabularnewline
245 & 0.762999 & 0.474003 & 0.237001 \tabularnewline
246 & 0.861307 & 0.277385 & 0.138693 \tabularnewline
247 & 0.900336 & 0.199327 & 0.0996637 \tabularnewline
248 & 0.843707 & 0.312586 & 0.156293 \tabularnewline
249 & 0.771083 & 0.457833 & 0.228917 \tabularnewline
250 & 0.814724 & 0.370552 & 0.185276 \tabularnewline
251 & 0.820589 & 0.358822 & 0.179411 \tabularnewline
252 & 0.745888 & 0.508224 & 0.254112 \tabularnewline
253 & 0.799603 & 0.400794 & 0.200397 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253717&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.212983[/C][C]0.425966[/C][C]0.787017[/C][/ROW]
[ROW][C]12[/C][C]0.653932[/C][C]0.692135[/C][C]0.346068[/C][/ROW]
[ROW][C]13[/C][C]0.601035[/C][C]0.797929[/C][C]0.398965[/C][/ROW]
[ROW][C]14[/C][C]0.59067[/C][C]0.818659[/C][C]0.40933[/C][/ROW]
[ROW][C]15[/C][C]0.540011[/C][C]0.919979[/C][C]0.459989[/C][/ROW]
[ROW][C]16[/C][C]0.552066[/C][C]0.895867[/C][C]0.447934[/C][/ROW]
[ROW][C]17[/C][C]0.503275[/C][C]0.993451[/C][C]0.496725[/C][/ROW]
[ROW][C]18[/C][C]0.542974[/C][C]0.914052[/C][C]0.457026[/C][/ROW]
[ROW][C]19[/C][C]0.475671[/C][C]0.951342[/C][C]0.524329[/C][/ROW]
[ROW][C]20[/C][C]0.420544[/C][C]0.841088[/C][C]0.579456[/C][/ROW]
[ROW][C]21[/C][C]0.338725[/C][C]0.67745[/C][C]0.661275[/C][/ROW]
[ROW][C]22[/C][C]0.349245[/C][C]0.69849[/C][C]0.650755[/C][/ROW]
[ROW][C]23[/C][C]0.287416[/C][C]0.574831[/C][C]0.712584[/C][/ROW]
[ROW][C]24[/C][C]0.290802[/C][C]0.581604[/C][C]0.709198[/C][/ROW]
[ROW][C]25[/C][C]0.324211[/C][C]0.648422[/C][C]0.675789[/C][/ROW]
[ROW][C]26[/C][C]0.433045[/C][C]0.86609[/C][C]0.566955[/C][/ROW]
[ROW][C]27[/C][C]0.380877[/C][C]0.761754[/C][C]0.619123[/C][/ROW]
[ROW][C]28[/C][C]0.350079[/C][C]0.700158[/C][C]0.649921[/C][/ROW]
[ROW][C]29[/C][C]0.29329[/C][C]0.586579[/C][C]0.70671[/C][/ROW]
[ROW][C]30[/C][C]0.240699[/C][C]0.481399[/C][C]0.759301[/C][/ROW]
[ROW][C]31[/C][C]0.211849[/C][C]0.423698[/C][C]0.788151[/C][/ROW]
[ROW][C]32[/C][C]0.170496[/C][C]0.340991[/C][C]0.829504[/C][/ROW]
[ROW][C]33[/C][C]0.157623[/C][C]0.315246[/C][C]0.842377[/C][/ROW]
[ROW][C]34[/C][C]0.171194[/C][C]0.342389[/C][C]0.828806[/C][/ROW]
[ROW][C]35[/C][C]0.181607[/C][C]0.363214[/C][C]0.818393[/C][/ROW]
[ROW][C]36[/C][C]0.159467[/C][C]0.318935[/C][C]0.840533[/C][/ROW]
[ROW][C]37[/C][C]0.126523[/C][C]0.253046[/C][C]0.873477[/C][/ROW]
[ROW][C]38[/C][C]0.100656[/C][C]0.201312[/C][C]0.899344[/C][/ROW]
[ROW][C]39[/C][C]0.0791442[/C][C]0.158288[/C][C]0.920856[/C][/ROW]
[ROW][C]40[/C][C]0.0604373[/C][C]0.120875[/C][C]0.939563[/C][/ROW]
[ROW][C]41[/C][C]0.0488092[/C][C]0.0976184[/C][C]0.951191[/C][/ROW]
[ROW][C]42[/C][C]0.036344[/C][C]0.0726881[/C][C]0.963656[/C][/ROW]
[ROW][C]43[/C][C]0.0416394[/C][C]0.0832788[/C][C]0.958361[/C][/ROW]
[ROW][C]44[/C][C]0.0308995[/C][C]0.0617991[/C][C]0.9691[/C][/ROW]
[ROW][C]45[/C][C]0.0491164[/C][C]0.0982328[/C][C]0.950884[/C][/ROW]
[ROW][C]46[/C][C]0.0418388[/C][C]0.0836777[/C][C]0.958161[/C][/ROW]
[ROW][C]47[/C][C]0.0651523[/C][C]0.130305[/C][C]0.934848[/C][/ROW]
[ROW][C]48[/C][C]0.0548519[/C][C]0.109704[/C][C]0.945148[/C][/ROW]
[ROW][C]49[/C][C]0.0814807[/C][C]0.162961[/C][C]0.918519[/C][/ROW]
[ROW][C]50[/C][C]0.0727775[/C][C]0.145555[/C][C]0.927222[/C][/ROW]
[ROW][C]51[/C][C]0.0865381[/C][C]0.173076[/C][C]0.913462[/C][/ROW]
[ROW][C]52[/C][C]0.0798119[/C][C]0.159624[/C][C]0.920188[/C][/ROW]
[ROW][C]53[/C][C]0.0632609[/C][C]0.126522[/C][C]0.936739[/C][/ROW]
[ROW][C]54[/C][C]0.0703392[/C][C]0.140678[/C][C]0.929661[/C][/ROW]
[ROW][C]55[/C][C]0.059742[/C][C]0.119484[/C][C]0.940258[/C][/ROW]
[ROW][C]56[/C][C]0.0587821[/C][C]0.117564[/C][C]0.941218[/C][/ROW]
[ROW][C]57[/C][C]0.0479567[/C][C]0.0959134[/C][C]0.952043[/C][/ROW]
[ROW][C]58[/C][C]0.0384708[/C][C]0.0769416[/C][C]0.961529[/C][/ROW]
[ROW][C]59[/C][C]0.0327148[/C][C]0.0654296[/C][C]0.967285[/C][/ROW]
[ROW][C]60[/C][C]0.025139[/C][C]0.050278[/C][C]0.974861[/C][/ROW]
[ROW][C]61[/C][C]0.0278656[/C][C]0.0557311[/C][C]0.972134[/C][/ROW]
[ROW][C]62[/C][C]0.0218926[/C][C]0.0437852[/C][C]0.978107[/C][/ROW]
[ROW][C]63[/C][C]0.0166888[/C][C]0.0333777[/C][C]0.983311[/C][/ROW]
[ROW][C]64[/C][C]0.0138668[/C][C]0.0277336[/C][C]0.986133[/C][/ROW]
[ROW][C]65[/C][C]0.0144507[/C][C]0.0289013[/C][C]0.985549[/C][/ROW]
[ROW][C]66[/C][C]0.0129484[/C][C]0.0258968[/C][C]0.987052[/C][/ROW]
[ROW][C]67[/C][C]0.00969655[/C][C]0.0193931[/C][C]0.990303[/C][/ROW]
[ROW][C]68[/C][C]0.0192935[/C][C]0.038587[/C][C]0.980707[/C][/ROW]
[ROW][C]69[/C][C]0.0262332[/C][C]0.0524664[/C][C]0.973767[/C][/ROW]
[ROW][C]70[/C][C]0.0245975[/C][C]0.049195[/C][C]0.975403[/C][/ROW]
[ROW][C]71[/C][C]0.02096[/C][C]0.0419199[/C][C]0.97904[/C][/ROW]
[ROW][C]72[/C][C]0.0276571[/C][C]0.0553141[/C][C]0.972343[/C][/ROW]
[ROW][C]73[/C][C]0.0318433[/C][C]0.0636865[/C][C]0.968157[/C][/ROW]
[ROW][C]74[/C][C]0.0394508[/C][C]0.0789017[/C][C]0.960549[/C][/ROW]
[ROW][C]75[/C][C]0.0933524[/C][C]0.186705[/C][C]0.906648[/C][/ROW]
[ROW][C]76[/C][C]0.110612[/C][C]0.221223[/C][C]0.889388[/C][/ROW]
[ROW][C]77[/C][C]0.0938962[/C][C]0.187792[/C][C]0.906104[/C][/ROW]
[ROW][C]78[/C][C]0.0905593[/C][C]0.181119[/C][C]0.909441[/C][/ROW]
[ROW][C]79[/C][C]0.0797058[/C][C]0.159412[/C][C]0.920294[/C][/ROW]
[ROW][C]80[/C][C]0.206771[/C][C]0.413541[/C][C]0.793229[/C][/ROW]
[ROW][C]81[/C][C]0.193956[/C][C]0.387913[/C][C]0.806044[/C][/ROW]
[ROW][C]82[/C][C]0.184325[/C][C]0.368651[/C][C]0.815675[/C][/ROW]
[ROW][C]83[/C][C]0.171653[/C][C]0.343305[/C][C]0.828347[/C][/ROW]
[ROW][C]84[/C][C]0.14883[/C][C]0.297659[/C][C]0.85117[/C][/ROW]
[ROW][C]85[/C][C]0.135926[/C][C]0.271853[/C][C]0.864074[/C][/ROW]
[ROW][C]86[/C][C]0.1641[/C][C]0.328199[/C][C]0.8359[/C][/ROW]
[ROW][C]87[/C][C]0.140989[/C][C]0.281977[/C][C]0.859011[/C][/ROW]
[ROW][C]88[/C][C]0.12195[/C][C]0.2439[/C][C]0.87805[/C][/ROW]
[ROW][C]89[/C][C]0.103835[/C][C]0.20767[/C][C]0.896165[/C][/ROW]
[ROW][C]90[/C][C]0.104709[/C][C]0.209418[/C][C]0.895291[/C][/ROW]
[ROW][C]91[/C][C]0.114789[/C][C]0.229578[/C][C]0.885211[/C][/ROW]
[ROW][C]92[/C][C]0.177108[/C][C]0.354215[/C][C]0.822892[/C][/ROW]
[ROW][C]93[/C][C]0.234457[/C][C]0.468914[/C][C]0.765543[/C][/ROW]
[ROW][C]94[/C][C]0.222636[/C][C]0.445272[/C][C]0.777364[/C][/ROW]
[ROW][C]95[/C][C]0.198783[/C][C]0.397567[/C][C]0.801217[/C][/ROW]
[ROW][C]96[/C][C]0.174108[/C][C]0.348217[/C][C]0.825892[/C][/ROW]
[ROW][C]97[/C][C]0.168775[/C][C]0.337549[/C][C]0.831225[/C][/ROW]
[ROW][C]98[/C][C]0.150985[/C][C]0.301969[/C][C]0.849015[/C][/ROW]
[ROW][C]99[/C][C]0.147838[/C][C]0.295676[/C][C]0.852162[/C][/ROW]
[ROW][C]100[/C][C]0.127673[/C][C]0.255346[/C][C]0.872327[/C][/ROW]
[ROW][C]101[/C][C]0.111193[/C][C]0.222387[/C][C]0.888807[/C][/ROW]
[ROW][C]102[/C][C]0.0966418[/C][C]0.193284[/C][C]0.903358[/C][/ROW]
[ROW][C]103[/C][C]0.121544[/C][C]0.243088[/C][C]0.878456[/C][/ROW]
[ROW][C]104[/C][C]0.153197[/C][C]0.306393[/C][C]0.846803[/C][/ROW]
[ROW][C]105[/C][C]0.164905[/C][C]0.329809[/C][C]0.835095[/C][/ROW]
[ROW][C]106[/C][C]0.145695[/C][C]0.291391[/C][C]0.854305[/C][/ROW]
[ROW][C]107[/C][C]0.133927[/C][C]0.267854[/C][C]0.866073[/C][/ROW]
[ROW][C]108[/C][C]0.118628[/C][C]0.237257[/C][C]0.881372[/C][/ROW]
[ROW][C]109[/C][C]0.157262[/C][C]0.314524[/C][C]0.842738[/C][/ROW]
[ROW][C]110[/C][C]0.137798[/C][C]0.275597[/C][C]0.862202[/C][/ROW]
[ROW][C]111[/C][C]0.119097[/C][C]0.238193[/C][C]0.880903[/C][/ROW]
[ROW][C]112[/C][C]0.22699[/C][C]0.453979[/C][C]0.77301[/C][/ROW]
[ROW][C]113[/C][C]0.204587[/C][C]0.409175[/C][C]0.795413[/C][/ROW]
[ROW][C]114[/C][C]0.185873[/C][C]0.371747[/C][C]0.814127[/C][/ROW]
[ROW][C]115[/C][C]0.200073[/C][C]0.400146[/C][C]0.799927[/C][/ROW]
[ROW][C]116[/C][C]0.258524[/C][C]0.517048[/C][C]0.741476[/C][/ROW]
[ROW][C]117[/C][C]0.3437[/C][C]0.6874[/C][C]0.6563[/C][/ROW]
[ROW][C]118[/C][C]0.316572[/C][C]0.633144[/C][C]0.683428[/C][/ROW]
[ROW][C]119[/C][C]0.285331[/C][C]0.570662[/C][C]0.714669[/C][/ROW]
[ROW][C]120[/C][C]0.288628[/C][C]0.577257[/C][C]0.711372[/C][/ROW]
[ROW][C]121[/C][C]0.396915[/C][C]0.79383[/C][C]0.603085[/C][/ROW]
[ROW][C]122[/C][C]0.394237[/C][C]0.788475[/C][C]0.605763[/C][/ROW]
[ROW][C]123[/C][C]0.372988[/C][C]0.745977[/C][C]0.627012[/C][/ROW]
[ROW][C]124[/C][C]0.403131[/C][C]0.806261[/C][C]0.596869[/C][/ROW]
[ROW][C]125[/C][C]0.370624[/C][C]0.741249[/C][C]0.629376[/C][/ROW]
[ROW][C]126[/C][C]0.39381[/C][C]0.78762[/C][C]0.60619[/C][/ROW]
[ROW][C]127[/C][C]0.361896[/C][C]0.723792[/C][C]0.638104[/C][/ROW]
[ROW][C]128[/C][C]0.342712[/C][C]0.685423[/C][C]0.657288[/C][/ROW]
[ROW][C]129[/C][C]0.319628[/C][C]0.639257[/C][C]0.680372[/C][/ROW]
[ROW][C]130[/C][C]0.288833[/C][C]0.577666[/C][C]0.711167[/C][/ROW]
[ROW][C]131[/C][C]0.265588[/C][C]0.531177[/C][C]0.734412[/C][/ROW]
[ROW][C]132[/C][C]0.240433[/C][C]0.480866[/C][C]0.759567[/C][/ROW]
[ROW][C]133[/C][C]0.226868[/C][C]0.453737[/C][C]0.773132[/C][/ROW]
[ROW][C]134[/C][C]0.216497[/C][C]0.432993[/C][C]0.783503[/C][/ROW]
[ROW][C]135[/C][C]0.247079[/C][C]0.494158[/C][C]0.752921[/C][/ROW]
[ROW][C]136[/C][C]0.465698[/C][C]0.931397[/C][C]0.534302[/C][/ROW]
[ROW][C]137[/C][C]0.432799[/C][C]0.865598[/C][C]0.567201[/C][/ROW]
[ROW][C]138[/C][C]0.438827[/C][C]0.877653[/C][C]0.561173[/C][/ROW]
[ROW][C]139[/C][C]0.40524[/C][C]0.81048[/C][C]0.59476[/C][/ROW]
[ROW][C]140[/C][C]0.402118[/C][C]0.804237[/C][C]0.597882[/C][/ROW]
[ROW][C]141[/C][C]0.372045[/C][C]0.744089[/C][C]0.627955[/C][/ROW]
[ROW][C]142[/C][C]0.406576[/C][C]0.813152[/C][C]0.593424[/C][/ROW]
[ROW][C]143[/C][C]0.381678[/C][C]0.763357[/C][C]0.618322[/C][/ROW]
[ROW][C]144[/C][C]0.677343[/C][C]0.645313[/C][C]0.322657[/C][/ROW]
[ROW][C]145[/C][C]0.712439[/C][C]0.575121[/C][C]0.287561[/C][/ROW]
[ROW][C]146[/C][C]0.818211[/C][C]0.363579[/C][C]0.181789[/C][/ROW]
[ROW][C]147[/C][C]0.799101[/C][C]0.401798[/C][C]0.200899[/C][/ROW]
[ROW][C]148[/C][C]0.791792[/C][C]0.416416[/C][C]0.208208[/C][/ROW]
[ROW][C]149[/C][C]0.777334[/C][C]0.445332[/C][C]0.222666[/C][/ROW]
[ROW][C]150[/C][C]0.794887[/C][C]0.410226[/C][C]0.205113[/C][/ROW]
[ROW][C]151[/C][C]0.771061[/C][C]0.457877[/C][C]0.228939[/C][/ROW]
[ROW][C]152[/C][C]0.78099[/C][C]0.438021[/C][C]0.21901[/C][/ROW]
[ROW][C]153[/C][C]0.810157[/C][C]0.379686[/C][C]0.189843[/C][/ROW]
[ROW][C]154[/C][C]0.79097[/C][C]0.418059[/C][C]0.20903[/C][/ROW]
[ROW][C]155[/C][C]0.771267[/C][C]0.457467[/C][C]0.228733[/C][/ROW]
[ROW][C]156[/C][C]0.776719[/C][C]0.446561[/C][C]0.223281[/C][/ROW]
[ROW][C]157[/C][C]0.80316[/C][C]0.393679[/C][C]0.19684[/C][/ROW]
[ROW][C]158[/C][C]0.792459[/C][C]0.415082[/C][C]0.207541[/C][/ROW]
[ROW][C]159[/C][C]0.785761[/C][C]0.428479[/C][C]0.214239[/C][/ROW]
[ROW][C]160[/C][C]0.830355[/C][C]0.339291[/C][C]0.169645[/C][/ROW]
[ROW][C]161[/C][C]0.824247[/C][C]0.351506[/C][C]0.175753[/C][/ROW]
[ROW][C]162[/C][C]0.847675[/C][C]0.30465[/C][C]0.152325[/C][/ROW]
[ROW][C]163[/C][C]0.898068[/C][C]0.203865[/C][C]0.101932[/C][/ROW]
[ROW][C]164[/C][C]0.91016[/C][C]0.179681[/C][C]0.0898403[/C][/ROW]
[ROW][C]165[/C][C]0.925875[/C][C]0.148249[/C][C]0.0741245[/C][/ROW]
[ROW][C]166[/C][C]0.918659[/C][C]0.162682[/C][C]0.0813409[/C][/ROW]
[ROW][C]167[/C][C]0.903926[/C][C]0.192147[/C][C]0.0960737[/C][/ROW]
[ROW][C]168[/C][C]0.928292[/C][C]0.143416[/C][C]0.0717081[/C][/ROW]
[ROW][C]169[/C][C]0.931366[/C][C]0.137269[/C][C]0.0686343[/C][/ROW]
[ROW][C]170[/C][C]0.950797[/C][C]0.0984054[/C][C]0.0492027[/C][/ROW]
[ROW][C]171[/C][C]0.948126[/C][C]0.103749[/C][C]0.0518744[/C][/ROW]
[ROW][C]172[/C][C]0.93995[/C][C]0.1201[/C][C]0.0600498[/C][/ROW]
[ROW][C]173[/C][C]0.931686[/C][C]0.136628[/C][C]0.0683139[/C][/ROW]
[ROW][C]174[/C][C]0.948614[/C][C]0.102773[/C][C]0.0513865[/C][/ROW]
[ROW][C]175[/C][C]0.976376[/C][C]0.0472488[/C][C]0.0236244[/C][/ROW]
[ROW][C]176[/C][C]0.971643[/C][C]0.0567143[/C][C]0.0283572[/C][/ROW]
[ROW][C]177[/C][C]0.967082[/C][C]0.0658368[/C][C]0.0329184[/C][/ROW]
[ROW][C]178[/C][C]0.96246[/C][C]0.0750799[/C][C]0.03754[/C][/ROW]
[ROW][C]179[/C][C]0.956004[/C][C]0.0879915[/C][C]0.0439958[/C][/ROW]
[ROW][C]180[/C][C]0.948081[/C][C]0.103837[/C][C]0.0519187[/C][/ROW]
[ROW][C]181[/C][C]0.937479[/C][C]0.125043[/C][C]0.0625214[/C][/ROW]
[ROW][C]182[/C][C]0.937986[/C][C]0.124028[/C][C]0.0620139[/C][/ROW]
[ROW][C]183[/C][C]0.928861[/C][C]0.142278[/C][C]0.0711389[/C][/ROW]
[ROW][C]184[/C][C]0.944545[/C][C]0.110909[/C][C]0.0554546[/C][/ROW]
[ROW][C]185[/C][C]0.932594[/C][C]0.134813[/C][C]0.0674064[/C][/ROW]
[ROW][C]186[/C][C]0.922956[/C][C]0.154088[/C][C]0.0770441[/C][/ROW]
[ROW][C]187[/C][C]0.914296[/C][C]0.171408[/C][C]0.0857039[/C][/ROW]
[ROW][C]188[/C][C]0.946137[/C][C]0.107727[/C][C]0.0538634[/C][/ROW]
[ROW][C]189[/C][C]0.941119[/C][C]0.117762[/C][C]0.0588811[/C][/ROW]
[ROW][C]190[/C][C]0.945005[/C][C]0.109991[/C][C]0.0549953[/C][/ROW]
[ROW][C]191[/C][C]0.948983[/C][C]0.102034[/C][C]0.0510168[/C][/ROW]
[ROW][C]192[/C][C]0.948672[/C][C]0.102657[/C][C]0.0513284[/C][/ROW]
[ROW][C]193[/C][C]0.937716[/C][C]0.124569[/C][C]0.0622843[/C][/ROW]
[ROW][C]194[/C][C]0.931521[/C][C]0.136959[/C][C]0.0684793[/C][/ROW]
[ROW][C]195[/C][C]0.9182[/C][C]0.163601[/C][C]0.0818003[/C][/ROW]
[ROW][C]196[/C][C]0.909783[/C][C]0.180434[/C][C]0.090217[/C][/ROW]
[ROW][C]197[/C][C]0.924873[/C][C]0.150253[/C][C]0.0751266[/C][/ROW]
[ROW][C]198[/C][C]0.913309[/C][C]0.173382[/C][C]0.0866908[/C][/ROW]
[ROW][C]199[/C][C]0.894719[/C][C]0.210562[/C][C]0.105281[/C][/ROW]
[ROW][C]200[/C][C]0.874953[/C][C]0.250095[/C][C]0.125047[/C][/ROW]
[ROW][C]201[/C][C]0.869166[/C][C]0.261668[/C][C]0.130834[/C][/ROW]
[ROW][C]202[/C][C]0.846344[/C][C]0.307313[/C][C]0.153656[/C][/ROW]
[ROW][C]203[/C][C]0.840653[/C][C]0.318695[/C][C]0.159347[/C][/ROW]
[ROW][C]204[/C][C]0.815787[/C][C]0.368425[/C][C]0.184213[/C][/ROW]
[ROW][C]205[/C][C]0.784313[/C][C]0.431374[/C][C]0.215687[/C][/ROW]
[ROW][C]206[/C][C]0.755135[/C][C]0.489729[/C][C]0.244865[/C][/ROW]
[ROW][C]207[/C][C]0.723987[/C][C]0.552025[/C][C]0.276013[/C][/ROW]
[ROW][C]208[/C][C]0.699201[/C][C]0.601599[/C][C]0.300799[/C][/ROW]
[ROW][C]209[/C][C]0.667283[/C][C]0.665433[/C][C]0.332717[/C][/ROW]
[ROW][C]210[/C][C]0.644647[/C][C]0.710705[/C][C]0.355353[/C][/ROW]
[ROW][C]211[/C][C]0.602167[/C][C]0.795667[/C][C]0.397833[/C][/ROW]
[ROW][C]212[/C][C]0.714579[/C][C]0.570841[/C][C]0.285421[/C][/ROW]
[ROW][C]213[/C][C]0.759946[/C][C]0.480109[/C][C]0.240054[/C][/ROW]
[ROW][C]214[/C][C]0.720413[/C][C]0.559174[/C][C]0.279587[/C][/ROW]
[ROW][C]215[/C][C]0.679154[/C][C]0.641691[/C][C]0.320846[/C][/ROW]
[ROW][C]216[/C][C]0.764926[/C][C]0.470149[/C][C]0.235074[/C][/ROW]
[ROW][C]217[/C][C]0.725254[/C][C]0.549491[/C][C]0.274746[/C][/ROW]
[ROW][C]218[/C][C]0.711321[/C][C]0.577359[/C][C]0.288679[/C][/ROW]
[ROW][C]219[/C][C]0.66697[/C][C]0.666061[/C][C]0.33303[/C][/ROW]
[ROW][C]220[/C][C]0.673887[/C][C]0.652226[/C][C]0.326113[/C][/ROW]
[ROW][C]221[/C][C]0.630873[/C][C]0.738255[/C][C]0.369127[/C][/ROW]
[ROW][C]222[/C][C]0.588423[/C][C]0.823154[/C][C]0.411577[/C][/ROW]
[ROW][C]223[/C][C]0.549725[/C][C]0.90055[/C][C]0.450275[/C][/ROW]
[ROW][C]224[/C][C]0.496879[/C][C]0.993758[/C][C]0.503121[/C][/ROW]
[ROW][C]225[/C][C]0.537852[/C][C]0.924297[/C][C]0.462148[/C][/ROW]
[ROW][C]226[/C][C]0.598009[/C][C]0.803982[/C][C]0.401991[/C][/ROW]
[ROW][C]227[/C][C]0.580112[/C][C]0.839775[/C][C]0.419888[/C][/ROW]
[ROW][C]228[/C][C]0.557028[/C][C]0.885943[/C][C]0.442972[/C][/ROW]
[ROW][C]229[/C][C]0.501048[/C][C]0.997904[/C][C]0.498952[/C][/ROW]
[ROW][C]230[/C][C]0.493768[/C][C]0.987536[/C][C]0.506232[/C][/ROW]
[ROW][C]231[/C][C]0.452563[/C][C]0.905126[/C][C]0.547437[/C][/ROW]
[ROW][C]232[/C][C]0.731791[/C][C]0.536418[/C][C]0.268209[/C][/ROW]
[ROW][C]233[/C][C]0.781959[/C][C]0.436083[/C][C]0.218041[/C][/ROW]
[ROW][C]234[/C][C]0.805237[/C][C]0.389526[/C][C]0.194763[/C][/ROW]
[ROW][C]235[/C][C]0.766249[/C][C]0.467501[/C][C]0.233751[/C][/ROW]
[ROW][C]236[/C][C]0.718433[/C][C]0.563134[/C][C]0.281567[/C][/ROW]
[ROW][C]237[/C][C]0.687051[/C][C]0.625898[/C][C]0.312949[/C][/ROW]
[ROW][C]238[/C][C]0.736961[/C][C]0.526078[/C][C]0.263039[/C][/ROW]
[ROW][C]239[/C][C]0.674756[/C][C]0.650487[/C][C]0.325244[/C][/ROW]
[ROW][C]240[/C][C]0.698669[/C][C]0.602662[/C][C]0.301331[/C][/ROW]
[ROW][C]241[/C][C]0.659317[/C][C]0.681367[/C][C]0.340683[/C][/ROW]
[ROW][C]242[/C][C]0.655992[/C][C]0.688016[/C][C]0.344008[/C][/ROW]
[ROW][C]243[/C][C]0.592391[/C][C]0.815218[/C][C]0.407609[/C][/ROW]
[ROW][C]244[/C][C]0.522868[/C][C]0.954264[/C][C]0.477132[/C][/ROW]
[ROW][C]245[/C][C]0.762999[/C][C]0.474003[/C][C]0.237001[/C][/ROW]
[ROW][C]246[/C][C]0.861307[/C][C]0.277385[/C][C]0.138693[/C][/ROW]
[ROW][C]247[/C][C]0.900336[/C][C]0.199327[/C][C]0.0996637[/C][/ROW]
[ROW][C]248[/C][C]0.843707[/C][C]0.312586[/C][C]0.156293[/C][/ROW]
[ROW][C]249[/C][C]0.771083[/C][C]0.457833[/C][C]0.228917[/C][/ROW]
[ROW][C]250[/C][C]0.814724[/C][C]0.370552[/C][C]0.185276[/C][/ROW]
[ROW][C]251[/C][C]0.820589[/C][C]0.358822[/C][C]0.179411[/C][/ROW]
[ROW][C]252[/C][C]0.745888[/C][C]0.508224[/C][C]0.254112[/C][/ROW]
[ROW][C]253[/C][C]0.799603[/C][C]0.400794[/C][C]0.200397[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253717&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253717&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.2129830.4259660.787017
120.6539320.6921350.346068
130.6010350.7979290.398965
140.590670.8186590.40933
150.5400110.9199790.459989
160.5520660.8958670.447934
170.5032750.9934510.496725
180.5429740.9140520.457026
190.4756710.9513420.524329
200.4205440.8410880.579456
210.3387250.677450.661275
220.3492450.698490.650755
230.2874160.5748310.712584
240.2908020.5816040.709198
250.3242110.6484220.675789
260.4330450.866090.566955
270.3808770.7617540.619123
280.3500790.7001580.649921
290.293290.5865790.70671
300.2406990.4813990.759301
310.2118490.4236980.788151
320.1704960.3409910.829504
330.1576230.3152460.842377
340.1711940.3423890.828806
350.1816070.3632140.818393
360.1594670.3189350.840533
370.1265230.2530460.873477
380.1006560.2013120.899344
390.07914420.1582880.920856
400.06043730.1208750.939563
410.04880920.09761840.951191
420.0363440.07268810.963656
430.04163940.08327880.958361
440.03089950.06179910.9691
450.04911640.09823280.950884
460.04183880.08367770.958161
470.06515230.1303050.934848
480.05485190.1097040.945148
490.08148070.1629610.918519
500.07277750.1455550.927222
510.08653810.1730760.913462
520.07981190.1596240.920188
530.06326090.1265220.936739
540.07033920.1406780.929661
550.0597420.1194840.940258
560.05878210.1175640.941218
570.04795670.09591340.952043
580.03847080.07694160.961529
590.03271480.06542960.967285
600.0251390.0502780.974861
610.02786560.05573110.972134
620.02189260.04378520.978107
630.01668880.03337770.983311
640.01386680.02773360.986133
650.01445070.02890130.985549
660.01294840.02589680.987052
670.009696550.01939310.990303
680.01929350.0385870.980707
690.02623320.05246640.973767
700.02459750.0491950.975403
710.020960.04191990.97904
720.02765710.05531410.972343
730.03184330.06368650.968157
740.03945080.07890170.960549
750.09335240.1867050.906648
760.1106120.2212230.889388
770.09389620.1877920.906104
780.09055930.1811190.909441
790.07970580.1594120.920294
800.2067710.4135410.793229
810.1939560.3879130.806044
820.1843250.3686510.815675
830.1716530.3433050.828347
840.148830.2976590.85117
850.1359260.2718530.864074
860.16410.3281990.8359
870.1409890.2819770.859011
880.121950.24390.87805
890.1038350.207670.896165
900.1047090.2094180.895291
910.1147890.2295780.885211
920.1771080.3542150.822892
930.2344570.4689140.765543
940.2226360.4452720.777364
950.1987830.3975670.801217
960.1741080.3482170.825892
970.1687750.3375490.831225
980.1509850.3019690.849015
990.1478380.2956760.852162
1000.1276730.2553460.872327
1010.1111930.2223870.888807
1020.09664180.1932840.903358
1030.1215440.2430880.878456
1040.1531970.3063930.846803
1050.1649050.3298090.835095
1060.1456950.2913910.854305
1070.1339270.2678540.866073
1080.1186280.2372570.881372
1090.1572620.3145240.842738
1100.1377980.2755970.862202
1110.1190970.2381930.880903
1120.226990.4539790.77301
1130.2045870.4091750.795413
1140.1858730.3717470.814127
1150.2000730.4001460.799927
1160.2585240.5170480.741476
1170.34370.68740.6563
1180.3165720.6331440.683428
1190.2853310.5706620.714669
1200.2886280.5772570.711372
1210.3969150.793830.603085
1220.3942370.7884750.605763
1230.3729880.7459770.627012
1240.4031310.8062610.596869
1250.3706240.7412490.629376
1260.393810.787620.60619
1270.3618960.7237920.638104
1280.3427120.6854230.657288
1290.3196280.6392570.680372
1300.2888330.5776660.711167
1310.2655880.5311770.734412
1320.2404330.4808660.759567
1330.2268680.4537370.773132
1340.2164970.4329930.783503
1350.2470790.4941580.752921
1360.4656980.9313970.534302
1370.4327990.8655980.567201
1380.4388270.8776530.561173
1390.405240.810480.59476
1400.4021180.8042370.597882
1410.3720450.7440890.627955
1420.4065760.8131520.593424
1430.3816780.7633570.618322
1440.6773430.6453130.322657
1450.7124390.5751210.287561
1460.8182110.3635790.181789
1470.7991010.4017980.200899
1480.7917920.4164160.208208
1490.7773340.4453320.222666
1500.7948870.4102260.205113
1510.7710610.4578770.228939
1520.780990.4380210.21901
1530.8101570.3796860.189843
1540.790970.4180590.20903
1550.7712670.4574670.228733
1560.7767190.4465610.223281
1570.803160.3936790.19684
1580.7924590.4150820.207541
1590.7857610.4284790.214239
1600.8303550.3392910.169645
1610.8242470.3515060.175753
1620.8476750.304650.152325
1630.8980680.2038650.101932
1640.910160.1796810.0898403
1650.9258750.1482490.0741245
1660.9186590.1626820.0813409
1670.9039260.1921470.0960737
1680.9282920.1434160.0717081
1690.9313660.1372690.0686343
1700.9507970.09840540.0492027
1710.9481260.1037490.0518744
1720.939950.12010.0600498
1730.9316860.1366280.0683139
1740.9486140.1027730.0513865
1750.9763760.04724880.0236244
1760.9716430.05671430.0283572
1770.9670820.06583680.0329184
1780.962460.07507990.03754
1790.9560040.08799150.0439958
1800.9480810.1038370.0519187
1810.9374790.1250430.0625214
1820.9379860.1240280.0620139
1830.9288610.1422780.0711389
1840.9445450.1109090.0554546
1850.9325940.1348130.0674064
1860.9229560.1540880.0770441
1870.9142960.1714080.0857039
1880.9461370.1077270.0538634
1890.9411190.1177620.0588811
1900.9450050.1099910.0549953
1910.9489830.1020340.0510168
1920.9486720.1026570.0513284
1930.9377160.1245690.0622843
1940.9315210.1369590.0684793
1950.91820.1636010.0818003
1960.9097830.1804340.090217
1970.9248730.1502530.0751266
1980.9133090.1733820.0866908
1990.8947190.2105620.105281
2000.8749530.2500950.125047
2010.8691660.2616680.130834
2020.8463440.3073130.153656
2030.8406530.3186950.159347
2040.8157870.3684250.184213
2050.7843130.4313740.215687
2060.7551350.4897290.244865
2070.7239870.5520250.276013
2080.6992010.6015990.300799
2090.6672830.6654330.332717
2100.6446470.7107050.355353
2110.6021670.7956670.397833
2120.7145790.5708410.285421
2130.7599460.4801090.240054
2140.7204130.5591740.279587
2150.6791540.6416910.320846
2160.7649260.4701490.235074
2170.7252540.5494910.274746
2180.7113210.5773590.288679
2190.666970.6660610.33303
2200.6738870.6522260.326113
2210.6308730.7382550.369127
2220.5884230.8231540.411577
2230.5497250.900550.450275
2240.4968790.9937580.503121
2250.5378520.9242970.462148
2260.5980090.8039820.401991
2270.5801120.8397750.419888
2280.5570280.8859430.442972
2290.5010480.9979040.498952
2300.4937680.9875360.506232
2310.4525630.9051260.547437
2320.7317910.5364180.268209
2330.7819590.4360830.218041
2340.8052370.3895260.194763
2350.7662490.4675010.233751
2360.7184330.5631340.281567
2370.6870510.6258980.312949
2380.7369610.5260780.263039
2390.6747560.6504870.325244
2400.6986690.6026620.301331
2410.6593170.6813670.340683
2420.6559920.6880160.344008
2430.5923910.8152180.407609
2440.5228680.9542640.477132
2450.7629990.4740030.237001
2460.8613070.2773850.138693
2470.9003360.1993270.0996637
2480.8437070.3125860.156293
2490.7710830.4578330.228917
2500.8147240.3705520.185276
2510.8205890.3588220.179411
2520.7458880.5082240.254112
2530.7996030.4007940.200397






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level100.0411523OK
10% type I error level300.123457NOK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 10 & 0.0411523 & OK \tabularnewline
10% type I error level & 30 & 0.123457 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253717&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]10[/C][C]0.0411523[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]30[/C][C]0.123457[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253717&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253717&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 level00OK
5% type I error level100.0411523OK
10% type I error level300.123457NOK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
R code (references can be found in the software module):
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- ''
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')
}