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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 17 Nov 2013 11:04:59 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/17/t13847043538p7zkmcls59u4zu.htm/, Retrieved Sun, 28 Apr 2024 19:37:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=225809, Retrieved Sun, 28 Apr 2024 19:37:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact79

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [Workshop 7 - vraag 1] [2013-11-17 16:04:59] [47fc20d512b54de2decb1f477fea32db] [Current]
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Dataset

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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 19 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225809&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]19 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225809&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225809&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time19 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 16.5164 + 0.148225Learning[t] + 0.436729Separate[t] -0.0389838Software[t] + 0.0398685Happiness[t] -0.0489113Depression[t] + 0.0175415Sport1[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Connected[t] =  +  16.5164 +  0.148225Learning[t] +  0.436729Separate[t] -0.0389838Software[t] +  0.0398685Happiness[t] -0.0489113Depression[t] +  0.0175415Sport1[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225809&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Connected[t] =  +  16.5164 +  0.148225Learning[t] +  0.436729Separate[t] -0.0389838Software[t] +  0.0398685Happiness[t] -0.0489113Depression[t] +  0.0175415Sport1[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225809&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225809&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
Connected[t] = + 16.5164 + 0.148225Learning[t] + 0.436729Separate[t] -0.0389838Software[t] + 0.0398685Happiness[t] -0.0489113Depression[t] + 0.0175415Sport1[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)16.51643.271845.0488.45958e-074.22979e-07
Learning0.1482250.1116981.3270.1856810.0928405
Separate0.4367290.05803657.5258.87662e-134.43831e-13
Software-0.03898380.115219-0.33830.7353780.367689
Happiness0.03986850.1044870.38160.70310.35155
Depression-0.04891130.0759539-0.6440.5201760.260088
Sport10.01754150.02147060.8170.4146840.207342

\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) & 16.5164 & 3.27184 & 5.048 & 8.45958e-07 & 4.22979e-07 \tabularnewline
Learning & 0.148225 & 0.111698 & 1.327 & 0.185681 & 0.0928405 \tabularnewline
Separate & 0.436729 & 0.0580365 & 7.525 & 8.87662e-13 & 4.43831e-13 \tabularnewline
Software & -0.0389838 & 0.115219 & -0.3383 & 0.735378 & 0.367689 \tabularnewline
Happiness & 0.0398685 & 0.104487 & 0.3816 & 0.7031 & 0.35155 \tabularnewline
Depression & -0.0489113 & 0.0759539 & -0.644 & 0.520176 & 0.260088 \tabularnewline
Sport1 & 0.0175415 & 0.0214706 & 0.817 & 0.414684 & 0.207342 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225809&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]16.5164[/C][C]3.27184[/C][C]5.048[/C][C]8.45958e-07[/C][C]4.22979e-07[/C][/ROW]
[ROW][C]Learning[/C][C]0.148225[/C][C]0.111698[/C][C]1.327[/C][C]0.185681[/C][C]0.0928405[/C][/ROW]
[ROW][C]Separate[/C][C]0.436729[/C][C]0.0580365[/C][C]7.525[/C][C]8.87662e-13[/C][C]4.43831e-13[/C][/ROW]
[ROW][C]Software[/C][C]-0.0389838[/C][C]0.115219[/C][C]-0.3383[/C][C]0.735378[/C][C]0.367689[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0398685[/C][C]0.104487[/C][C]0.3816[/C][C]0.7031[/C][C]0.35155[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0489113[/C][C]0.0759539[/C][C]-0.644[/C][C]0.520176[/C][C]0.260088[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0175415[/C][C]0.0214706[/C][C]0.817[/C][C]0.414684[/C][C]0.207342[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225809&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225809&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)16.51643.271845.0488.45958e-074.22979e-07
Learning0.1482250.1116981.3270.1856810.0928405
Separate0.4367290.05803657.5258.87662e-134.43831e-13
Software-0.03898380.115219-0.33830.7353780.367689
Happiness0.03986850.1044870.38160.70310.35155
Depression-0.04891130.0759539-0.6440.5201760.260088
Sport10.01754150.02147060.8170.4146840.207342






Multiple Linear Regression - Regression Statistics
Multiple R0.474745
R-squared0.225383
Adjusted R-squared0.207299
F-TEST (value)12.4628
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value2.53164e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.38015
Sum Squared Residuals2936.33

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.474745 \tabularnewline
R-squared & 0.225383 \tabularnewline
Adjusted R-squared & 0.207299 \tabularnewline
F-TEST (value) & 12.4628 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 257 \tabularnewline
p-value & 2.53164e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.38015 \tabularnewline
Sum Squared Residuals & 2936.33 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225809&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.474745[/C][/ROW]
[ROW][C]R-squared[/C][C]0.225383[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.207299[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]12.4628[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]257[/C][/ROW]
[ROW][C]p-value[/C][C]2.53164e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.38015[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2936.33[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225809&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225809&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 R0.474745
R-squared0.225383
Adjusted R-squared0.207299
F-TEST (value)12.4628
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value2.53164e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.38015
Sum Squared Residuals2936.33






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14135.47215.52785
23934.07014.92994
33034.945-4.94497
43133.9847-2.9847
53435.1876-1.18765
63532.21762.78244
73932.81536.18472
83435.3397-1.3397
93634.81621.18375
103736.280.720041
113833.61124.38881
123634.58241.41757
133834.5463.45399
143935.95533.04474
153336.3651-3.36507
163233.5748-1.57484
173633.51432.48572
183837.29220.707809
193936.5432.45697
203233.3974-1.39744
213234.282-2.28195
223132.9054-1.90541
233936.34012.65995
243736.26760.7324
253934.19214.80794
264133.82677.1733
273635.21670.783296
283335.3878-2.38783
293334.1138-1.11376
303433.59180.408243
313133.4116-2.41158
322732.6904-5.69042
333733.17443.82559
343436.1127-2.11266
353432.4461.554
363233.6299-1.62987
372931.6721-2.6721
383633.79232.20766
392933.5586-4.55857
403534.14980.850239
413733.92943.07061
423433.80460.195447
433834.06533.93468
443533.31961.68041
453831.70056.29951
463733.96013.03989
473836.41521.58478
483334.5354-1.53536
493636.297-0.297048
503833.3954.60505
513236.3497-4.3497
523232.3523-0.352264
533232.9026-0.902617
543435.8582-1.85815
553232.6763-0.676347
563734.86512.13487
573934.56914.4309
582934.6021-5.60209
593735.3031.69696
603534.31960.680393
613030.521-0.521048
623834.5513.44897
633434.8827-0.882681
643134.2338-3.2338
653432.86821.13178
663535.9524-0.952391
673634.6891.31101
683031.7193-1.71933
693936.36382.63625
703535.7028-0.702802
713834.50663.49338
723135.6099-4.6099
733437.0542-3.05415
743837.86380.136154
753431.66562.33437
763932.73976.26033
773735.811.18999
783432.89491.10506
792832.827-4.82699
803731.23725.76279
813335.5882-2.58822
823535.9824-0.982441
833734.01552.98448
843234.4338-2.43382
853333.3098-0.30977
863836.55091.44908
873334.4506-1.45057
882933.1274-4.12739
893333.115-0.114964
903134.9889-3.98894
913633.15872.84134
923537.639-2.63896
933231.76330.236726
942932.3876-3.38761
953935.72363.2764
963734.57292.42707
973533.46411.53588
983734.82962.17042
993235.366-3.36603
1003835.58632.41372
1013734.72112.27893
1023636.5971-0.597106
1033231.59760.402366
1043336.6928-3.69284
1054032.57327.42683
1063835.2872.71304
1074136.51354.48648
1083634.3571.64305
1094336.39666.60344
1103034.6733-4.67328
1113133.7572-2.75724
1123238.0372-6.03721
1133232.9176-0.917629
1143734.21792.7821
1153734.31032.68966
1163336.3746-3.37456
1173436.8464-2.84643
1183334.6283-1.62834
1193835.54572.45434
1203334.8655-1.86547
1213131.3794-0.379449
1223836.62911.37085
1233736.47780.522179
1243633.11212.88788
1253134.0813-3.08135
1263934.19054.80953
1274437.12666.87344
1283335.7515-2.75151
1293533.50351.4965
1303234.1359-2.13593
1312832.0835-4.08349
1324036.19473.80529
1332731.9727-4.9727
1343736.02860.971389
1353232.3813-0.381276
1362827.96130.0386561
1373434.575-0.574985
1383033.6458-3.64577
1393534.01470.985324
1403134.2233-3.22326
1413234.4811-2.48107
1423035.9745-5.97452
1433035.2168-5.21678
1443129.86571.13427
1454032.88647.11356
1463231.85350.146541
1473634.5531.44704
1483233.2148-1.2148
1493532.77782.22217
1503836.30021.69982
1514235.46456.53546
1523436.576-2.57599
1533536.841-1.841
1543833.76834.23167
1553332.23150.768497
1563633.15872.84134
1573235.4522-3.45216
1583335.7515-2.75151
1593433.98610.0139183
1603235.6504-3.65044
1613434.7998-0.799773
1622729.791-2.79099
1633130.63240.367554
1643834.00063.99942
1653436.1636-2.16364
1662431.0495-7.04949
1673033.9142-3.91425
1682629.689-3.68903
1693435.5859-1.58586
1702735.3381-8.33811
1713732.06394.93611
1723635.89310.106882
1734134.33096.6691
1742929.2175-0.21751
1753631.32074.67926
1763235.0428-3.0428
1773733.16433.83565
1783031.8545-1.8545
1793133.0644-2.06438
1803835.15512.84491
1813635.10980.890184
1823532.26822.73179
1833135.7581-4.75807
1843833.71974.28034
1852231.1239-9.12387
1863235.0646-3.06457
1873634.62771.37234
1883933.0985.90199
1892830.8832-2.88317
1903234.1556-2.15565
1913234.3153-2.31527
1923837.2740.725985
1933233.6649-1.66493
1943535.3617-0.361699
1953233.2051-1.20507
1963735.98711.01294
1973433.09040.909631
1983335.9298-2.92977
1993333.13-0.12996
2002633.6287-7.62866
2013032.2598-2.25975
2022432.525-8.52504
2033432.791.21003
2043432.58341.4166
2053334.5997-1.59968
2063435.2935-1.29345
2073536.0804-1.0804
2083534.95880.0411746
2093633.23052.76947
2103434.2864-0.286441
2113432.88931.11067
2124138.61672.38327
2133236.4276-4.42765
2143033.5519-3.55185
2153534.48810.511947
2162830.2223-2.22232
2173335.5237-2.52369
2183934.47774.52233
2193633.72992.2701
2203636.6561-0.656074
2213533.57231.42765
2223834.99233.00767
2233333.0775-0.0774793
2243133.3404-2.34039
2253433.8130.187027
2263234.7076-2.70756
2273133.3438-2.34376
2283334.0861-1.08608
2293432.55981.44019
2303434.2604-0.260373
2313432.5281.47204
2323334.956-1.95603
2333234.6781-2.67812
2344134.00056.99948
2353433.48950.510502
2363632.27733.72266
2373730.95746.04265
2383630.52675.47328
2392933.0824-4.08244
2403731.94225.05776
2412733.4915-6.49152
2423533.47111.52887
2432830.8234-2.82336
2443533.47511.52494
2453733.24023.75979
2462933.9394-4.93944
2473234.5037-2.50366
2483631.82824.17185
2491927.5573-8.55732
2502127.3044-6.30437
2513133.8639-2.86395
2523332.75610.243873
2533634.13571.8643
2543333.6579-0.657907
2553733.15713.84293
2563433.49480.505181
2573535.2265-0.226461
2583132.821-1.821
2593733.90293.09707
2603531.55763.44244
2612732.5067-5.5067
2623435.4787-1.47869
2634033.88686.11316
2642933.4502-4.45024

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 41 & 35.4721 & 5.52785 \tabularnewline
2 & 39 & 34.0701 & 4.92994 \tabularnewline
3 & 30 & 34.945 & -4.94497 \tabularnewline
4 & 31 & 33.9847 & -2.9847 \tabularnewline
5 & 34 & 35.1876 & -1.18765 \tabularnewline
6 & 35 & 32.2176 & 2.78244 \tabularnewline
7 & 39 & 32.8153 & 6.18472 \tabularnewline
8 & 34 & 35.3397 & -1.3397 \tabularnewline
9 & 36 & 34.8162 & 1.18375 \tabularnewline
10 & 37 & 36.28 & 0.720041 \tabularnewline
11 & 38 & 33.6112 & 4.38881 \tabularnewline
12 & 36 & 34.5824 & 1.41757 \tabularnewline
13 & 38 & 34.546 & 3.45399 \tabularnewline
14 & 39 & 35.9553 & 3.04474 \tabularnewline
15 & 33 & 36.3651 & -3.36507 \tabularnewline
16 & 32 & 33.5748 & -1.57484 \tabularnewline
17 & 36 & 33.5143 & 2.48572 \tabularnewline
18 & 38 & 37.2922 & 0.707809 \tabularnewline
19 & 39 & 36.543 & 2.45697 \tabularnewline
20 & 32 & 33.3974 & -1.39744 \tabularnewline
21 & 32 & 34.282 & -2.28195 \tabularnewline
22 & 31 & 32.9054 & -1.90541 \tabularnewline
23 & 39 & 36.3401 & 2.65995 \tabularnewline
24 & 37 & 36.2676 & 0.7324 \tabularnewline
25 & 39 & 34.1921 & 4.80794 \tabularnewline
26 & 41 & 33.8267 & 7.1733 \tabularnewline
27 & 36 & 35.2167 & 0.783296 \tabularnewline
28 & 33 & 35.3878 & -2.38783 \tabularnewline
29 & 33 & 34.1138 & -1.11376 \tabularnewline
30 & 34 & 33.5918 & 0.408243 \tabularnewline
31 & 31 & 33.4116 & -2.41158 \tabularnewline
32 & 27 & 32.6904 & -5.69042 \tabularnewline
33 & 37 & 33.1744 & 3.82559 \tabularnewline
34 & 34 & 36.1127 & -2.11266 \tabularnewline
35 & 34 & 32.446 & 1.554 \tabularnewline
36 & 32 & 33.6299 & -1.62987 \tabularnewline
37 & 29 & 31.6721 & -2.6721 \tabularnewline
38 & 36 & 33.7923 & 2.20766 \tabularnewline
39 & 29 & 33.5586 & -4.55857 \tabularnewline
40 & 35 & 34.1498 & 0.850239 \tabularnewline
41 & 37 & 33.9294 & 3.07061 \tabularnewline
42 & 34 & 33.8046 & 0.195447 \tabularnewline
43 & 38 & 34.0653 & 3.93468 \tabularnewline
44 & 35 & 33.3196 & 1.68041 \tabularnewline
45 & 38 & 31.7005 & 6.29951 \tabularnewline
46 & 37 & 33.9601 & 3.03989 \tabularnewline
47 & 38 & 36.4152 & 1.58478 \tabularnewline
48 & 33 & 34.5354 & -1.53536 \tabularnewline
49 & 36 & 36.297 & -0.297048 \tabularnewline
50 & 38 & 33.395 & 4.60505 \tabularnewline
51 & 32 & 36.3497 & -4.3497 \tabularnewline
52 & 32 & 32.3523 & -0.352264 \tabularnewline
53 & 32 & 32.9026 & -0.902617 \tabularnewline
54 & 34 & 35.8582 & -1.85815 \tabularnewline
55 & 32 & 32.6763 & -0.676347 \tabularnewline
56 & 37 & 34.8651 & 2.13487 \tabularnewline
57 & 39 & 34.5691 & 4.4309 \tabularnewline
58 & 29 & 34.6021 & -5.60209 \tabularnewline
59 & 37 & 35.303 & 1.69696 \tabularnewline
60 & 35 & 34.3196 & 0.680393 \tabularnewline
61 & 30 & 30.521 & -0.521048 \tabularnewline
62 & 38 & 34.551 & 3.44897 \tabularnewline
63 & 34 & 34.8827 & -0.882681 \tabularnewline
64 & 31 & 34.2338 & -3.2338 \tabularnewline
65 & 34 & 32.8682 & 1.13178 \tabularnewline
66 & 35 & 35.9524 & -0.952391 \tabularnewline
67 & 36 & 34.689 & 1.31101 \tabularnewline
68 & 30 & 31.7193 & -1.71933 \tabularnewline
69 & 39 & 36.3638 & 2.63625 \tabularnewline
70 & 35 & 35.7028 & -0.702802 \tabularnewline
71 & 38 & 34.5066 & 3.49338 \tabularnewline
72 & 31 & 35.6099 & -4.6099 \tabularnewline
73 & 34 & 37.0542 & -3.05415 \tabularnewline
74 & 38 & 37.8638 & 0.136154 \tabularnewline
75 & 34 & 31.6656 & 2.33437 \tabularnewline
76 & 39 & 32.7397 & 6.26033 \tabularnewline
77 & 37 & 35.81 & 1.18999 \tabularnewline
78 & 34 & 32.8949 & 1.10506 \tabularnewline
79 & 28 & 32.827 & -4.82699 \tabularnewline
80 & 37 & 31.2372 & 5.76279 \tabularnewline
81 & 33 & 35.5882 & -2.58822 \tabularnewline
82 & 35 & 35.9824 & -0.982441 \tabularnewline
83 & 37 & 34.0155 & 2.98448 \tabularnewline
84 & 32 & 34.4338 & -2.43382 \tabularnewline
85 & 33 & 33.3098 & -0.30977 \tabularnewline
86 & 38 & 36.5509 & 1.44908 \tabularnewline
87 & 33 & 34.4506 & -1.45057 \tabularnewline
88 & 29 & 33.1274 & -4.12739 \tabularnewline
89 & 33 & 33.115 & -0.114964 \tabularnewline
90 & 31 & 34.9889 & -3.98894 \tabularnewline
91 & 36 & 33.1587 & 2.84134 \tabularnewline
92 & 35 & 37.639 & -2.63896 \tabularnewline
93 & 32 & 31.7633 & 0.236726 \tabularnewline
94 & 29 & 32.3876 & -3.38761 \tabularnewline
95 & 39 & 35.7236 & 3.2764 \tabularnewline
96 & 37 & 34.5729 & 2.42707 \tabularnewline
97 & 35 & 33.4641 & 1.53588 \tabularnewline
98 & 37 & 34.8296 & 2.17042 \tabularnewline
99 & 32 & 35.366 & -3.36603 \tabularnewline
100 & 38 & 35.5863 & 2.41372 \tabularnewline
101 & 37 & 34.7211 & 2.27893 \tabularnewline
102 & 36 & 36.5971 & -0.597106 \tabularnewline
103 & 32 & 31.5976 & 0.402366 \tabularnewline
104 & 33 & 36.6928 & -3.69284 \tabularnewline
105 & 40 & 32.5732 & 7.42683 \tabularnewline
106 & 38 & 35.287 & 2.71304 \tabularnewline
107 & 41 & 36.5135 & 4.48648 \tabularnewline
108 & 36 & 34.357 & 1.64305 \tabularnewline
109 & 43 & 36.3966 & 6.60344 \tabularnewline
110 & 30 & 34.6733 & -4.67328 \tabularnewline
111 & 31 & 33.7572 & -2.75724 \tabularnewline
112 & 32 & 38.0372 & -6.03721 \tabularnewline
113 & 32 & 32.9176 & -0.917629 \tabularnewline
114 & 37 & 34.2179 & 2.7821 \tabularnewline
115 & 37 & 34.3103 & 2.68966 \tabularnewline
116 & 33 & 36.3746 & -3.37456 \tabularnewline
117 & 34 & 36.8464 & -2.84643 \tabularnewline
118 & 33 & 34.6283 & -1.62834 \tabularnewline
119 & 38 & 35.5457 & 2.45434 \tabularnewline
120 & 33 & 34.8655 & -1.86547 \tabularnewline
121 & 31 & 31.3794 & -0.379449 \tabularnewline
122 & 38 & 36.6291 & 1.37085 \tabularnewline
123 & 37 & 36.4778 & 0.522179 \tabularnewline
124 & 36 & 33.1121 & 2.88788 \tabularnewline
125 & 31 & 34.0813 & -3.08135 \tabularnewline
126 & 39 & 34.1905 & 4.80953 \tabularnewline
127 & 44 & 37.1266 & 6.87344 \tabularnewline
128 & 33 & 35.7515 & -2.75151 \tabularnewline
129 & 35 & 33.5035 & 1.4965 \tabularnewline
130 & 32 & 34.1359 & -2.13593 \tabularnewline
131 & 28 & 32.0835 & -4.08349 \tabularnewline
132 & 40 & 36.1947 & 3.80529 \tabularnewline
133 & 27 & 31.9727 & -4.9727 \tabularnewline
134 & 37 & 36.0286 & 0.971389 \tabularnewline
135 & 32 & 32.3813 & -0.381276 \tabularnewline
136 & 28 & 27.9613 & 0.0386561 \tabularnewline
137 & 34 & 34.575 & -0.574985 \tabularnewline
138 & 30 & 33.6458 & -3.64577 \tabularnewline
139 & 35 & 34.0147 & 0.985324 \tabularnewline
140 & 31 & 34.2233 & -3.22326 \tabularnewline
141 & 32 & 34.4811 & -2.48107 \tabularnewline
142 & 30 & 35.9745 & -5.97452 \tabularnewline
143 & 30 & 35.2168 & -5.21678 \tabularnewline
144 & 31 & 29.8657 & 1.13427 \tabularnewline
145 & 40 & 32.8864 & 7.11356 \tabularnewline
146 & 32 & 31.8535 & 0.146541 \tabularnewline
147 & 36 & 34.553 & 1.44704 \tabularnewline
148 & 32 & 33.2148 & -1.2148 \tabularnewline
149 & 35 & 32.7778 & 2.22217 \tabularnewline
150 & 38 & 36.3002 & 1.69982 \tabularnewline
151 & 42 & 35.4645 & 6.53546 \tabularnewline
152 & 34 & 36.576 & -2.57599 \tabularnewline
153 & 35 & 36.841 & -1.841 \tabularnewline
154 & 38 & 33.7683 & 4.23167 \tabularnewline
155 & 33 & 32.2315 & 0.768497 \tabularnewline
156 & 36 & 33.1587 & 2.84134 \tabularnewline
157 & 32 & 35.4522 & -3.45216 \tabularnewline
158 & 33 & 35.7515 & -2.75151 \tabularnewline
159 & 34 & 33.9861 & 0.0139183 \tabularnewline
160 & 32 & 35.6504 & -3.65044 \tabularnewline
161 & 34 & 34.7998 & -0.799773 \tabularnewline
162 & 27 & 29.791 & -2.79099 \tabularnewline
163 & 31 & 30.6324 & 0.367554 \tabularnewline
164 & 38 & 34.0006 & 3.99942 \tabularnewline
165 & 34 & 36.1636 & -2.16364 \tabularnewline
166 & 24 & 31.0495 & -7.04949 \tabularnewline
167 & 30 & 33.9142 & -3.91425 \tabularnewline
168 & 26 & 29.689 & -3.68903 \tabularnewline
169 & 34 & 35.5859 & -1.58586 \tabularnewline
170 & 27 & 35.3381 & -8.33811 \tabularnewline
171 & 37 & 32.0639 & 4.93611 \tabularnewline
172 & 36 & 35.8931 & 0.106882 \tabularnewline
173 & 41 & 34.3309 & 6.6691 \tabularnewline
174 & 29 & 29.2175 & -0.21751 \tabularnewline
175 & 36 & 31.3207 & 4.67926 \tabularnewline
176 & 32 & 35.0428 & -3.0428 \tabularnewline
177 & 37 & 33.1643 & 3.83565 \tabularnewline
178 & 30 & 31.8545 & -1.8545 \tabularnewline
179 & 31 & 33.0644 & -2.06438 \tabularnewline
180 & 38 & 35.1551 & 2.84491 \tabularnewline
181 & 36 & 35.1098 & 0.890184 \tabularnewline
182 & 35 & 32.2682 & 2.73179 \tabularnewline
183 & 31 & 35.7581 & -4.75807 \tabularnewline
184 & 38 & 33.7197 & 4.28034 \tabularnewline
185 & 22 & 31.1239 & -9.12387 \tabularnewline
186 & 32 & 35.0646 & -3.06457 \tabularnewline
187 & 36 & 34.6277 & 1.37234 \tabularnewline
188 & 39 & 33.098 & 5.90199 \tabularnewline
189 & 28 & 30.8832 & -2.88317 \tabularnewline
190 & 32 & 34.1556 & -2.15565 \tabularnewline
191 & 32 & 34.3153 & -2.31527 \tabularnewline
192 & 38 & 37.274 & 0.725985 \tabularnewline
193 & 32 & 33.6649 & -1.66493 \tabularnewline
194 & 35 & 35.3617 & -0.361699 \tabularnewline
195 & 32 & 33.2051 & -1.20507 \tabularnewline
196 & 37 & 35.9871 & 1.01294 \tabularnewline
197 & 34 & 33.0904 & 0.909631 \tabularnewline
198 & 33 & 35.9298 & -2.92977 \tabularnewline
199 & 33 & 33.13 & -0.12996 \tabularnewline
200 & 26 & 33.6287 & -7.62866 \tabularnewline
201 & 30 & 32.2598 & -2.25975 \tabularnewline
202 & 24 & 32.525 & -8.52504 \tabularnewline
203 & 34 & 32.79 & 1.21003 \tabularnewline
204 & 34 & 32.5834 & 1.4166 \tabularnewline
205 & 33 & 34.5997 & -1.59968 \tabularnewline
206 & 34 & 35.2935 & -1.29345 \tabularnewline
207 & 35 & 36.0804 & -1.0804 \tabularnewline
208 & 35 & 34.9588 & 0.0411746 \tabularnewline
209 & 36 & 33.2305 & 2.76947 \tabularnewline
210 & 34 & 34.2864 & -0.286441 \tabularnewline
211 & 34 & 32.8893 & 1.11067 \tabularnewline
212 & 41 & 38.6167 & 2.38327 \tabularnewline
213 & 32 & 36.4276 & -4.42765 \tabularnewline
214 & 30 & 33.5519 & -3.55185 \tabularnewline
215 & 35 & 34.4881 & 0.511947 \tabularnewline
216 & 28 & 30.2223 & -2.22232 \tabularnewline
217 & 33 & 35.5237 & -2.52369 \tabularnewline
218 & 39 & 34.4777 & 4.52233 \tabularnewline
219 & 36 & 33.7299 & 2.2701 \tabularnewline
220 & 36 & 36.6561 & -0.656074 \tabularnewline
221 & 35 & 33.5723 & 1.42765 \tabularnewline
222 & 38 & 34.9923 & 3.00767 \tabularnewline
223 & 33 & 33.0775 & -0.0774793 \tabularnewline
224 & 31 & 33.3404 & -2.34039 \tabularnewline
225 & 34 & 33.813 & 0.187027 \tabularnewline
226 & 32 & 34.7076 & -2.70756 \tabularnewline
227 & 31 & 33.3438 & -2.34376 \tabularnewline
228 & 33 & 34.0861 & -1.08608 \tabularnewline
229 & 34 & 32.5598 & 1.44019 \tabularnewline
230 & 34 & 34.2604 & -0.260373 \tabularnewline
231 & 34 & 32.528 & 1.47204 \tabularnewline
232 & 33 & 34.956 & -1.95603 \tabularnewline
233 & 32 & 34.6781 & -2.67812 \tabularnewline
234 & 41 & 34.0005 & 6.99948 \tabularnewline
235 & 34 & 33.4895 & 0.510502 \tabularnewline
236 & 36 & 32.2773 & 3.72266 \tabularnewline
237 & 37 & 30.9574 & 6.04265 \tabularnewline
238 & 36 & 30.5267 & 5.47328 \tabularnewline
239 & 29 & 33.0824 & -4.08244 \tabularnewline
240 & 37 & 31.9422 & 5.05776 \tabularnewline
241 & 27 & 33.4915 & -6.49152 \tabularnewline
242 & 35 & 33.4711 & 1.52887 \tabularnewline
243 & 28 & 30.8234 & -2.82336 \tabularnewline
244 & 35 & 33.4751 & 1.52494 \tabularnewline
245 & 37 & 33.2402 & 3.75979 \tabularnewline
246 & 29 & 33.9394 & -4.93944 \tabularnewline
247 & 32 & 34.5037 & -2.50366 \tabularnewline
248 & 36 & 31.8282 & 4.17185 \tabularnewline
249 & 19 & 27.5573 & -8.55732 \tabularnewline
250 & 21 & 27.3044 & -6.30437 \tabularnewline
251 & 31 & 33.8639 & -2.86395 \tabularnewline
252 & 33 & 32.7561 & 0.243873 \tabularnewline
253 & 36 & 34.1357 & 1.8643 \tabularnewline
254 & 33 & 33.6579 & -0.657907 \tabularnewline
255 & 37 & 33.1571 & 3.84293 \tabularnewline
256 & 34 & 33.4948 & 0.505181 \tabularnewline
257 & 35 & 35.2265 & -0.226461 \tabularnewline
258 & 31 & 32.821 & -1.821 \tabularnewline
259 & 37 & 33.9029 & 3.09707 \tabularnewline
260 & 35 & 31.5576 & 3.44244 \tabularnewline
261 & 27 & 32.5067 & -5.5067 \tabularnewline
262 & 34 & 35.4787 & -1.47869 \tabularnewline
263 & 40 & 33.8868 & 6.11316 \tabularnewline
264 & 29 & 33.4502 & -4.45024 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225809&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]41[/C][C]35.4721[/C][C]5.52785[/C][/ROW]
[ROW][C]2[/C][C]39[/C][C]34.0701[/C][C]4.92994[/C][/ROW]
[ROW][C]3[/C][C]30[/C][C]34.945[/C][C]-4.94497[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]33.9847[/C][C]-2.9847[/C][/ROW]
[ROW][C]5[/C][C]34[/C][C]35.1876[/C][C]-1.18765[/C][/ROW]
[ROW][C]6[/C][C]35[/C][C]32.2176[/C][C]2.78244[/C][/ROW]
[ROW][C]7[/C][C]39[/C][C]32.8153[/C][C]6.18472[/C][/ROW]
[ROW][C]8[/C][C]34[/C][C]35.3397[/C][C]-1.3397[/C][/ROW]
[ROW][C]9[/C][C]36[/C][C]34.8162[/C][C]1.18375[/C][/ROW]
[ROW][C]10[/C][C]37[/C][C]36.28[/C][C]0.720041[/C][/ROW]
[ROW][C]11[/C][C]38[/C][C]33.6112[/C][C]4.38881[/C][/ROW]
[ROW][C]12[/C][C]36[/C][C]34.5824[/C][C]1.41757[/C][/ROW]
[ROW][C]13[/C][C]38[/C][C]34.546[/C][C]3.45399[/C][/ROW]
[ROW][C]14[/C][C]39[/C][C]35.9553[/C][C]3.04474[/C][/ROW]
[ROW][C]15[/C][C]33[/C][C]36.3651[/C][C]-3.36507[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]33.5748[/C][C]-1.57484[/C][/ROW]
[ROW][C]17[/C][C]36[/C][C]33.5143[/C][C]2.48572[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]37.2922[/C][C]0.707809[/C][/ROW]
[ROW][C]19[/C][C]39[/C][C]36.543[/C][C]2.45697[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.3974[/C][C]-1.39744[/C][/ROW]
[ROW][C]21[/C][C]32[/C][C]34.282[/C][C]-2.28195[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]32.9054[/C][C]-1.90541[/C][/ROW]
[ROW][C]23[/C][C]39[/C][C]36.3401[/C][C]2.65995[/C][/ROW]
[ROW][C]24[/C][C]37[/C][C]36.2676[/C][C]0.7324[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]34.1921[/C][C]4.80794[/C][/ROW]
[ROW][C]26[/C][C]41[/C][C]33.8267[/C][C]7.1733[/C][/ROW]
[ROW][C]27[/C][C]36[/C][C]35.2167[/C][C]0.783296[/C][/ROW]
[ROW][C]28[/C][C]33[/C][C]35.3878[/C][C]-2.38783[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]34.1138[/C][C]-1.11376[/C][/ROW]
[ROW][C]30[/C][C]34[/C][C]33.5918[/C][C]0.408243[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]33.4116[/C][C]-2.41158[/C][/ROW]
[ROW][C]32[/C][C]27[/C][C]32.6904[/C][C]-5.69042[/C][/ROW]
[ROW][C]33[/C][C]37[/C][C]33.1744[/C][C]3.82559[/C][/ROW]
[ROW][C]34[/C][C]34[/C][C]36.1127[/C][C]-2.11266[/C][/ROW]
[ROW][C]35[/C][C]34[/C][C]32.446[/C][C]1.554[/C][/ROW]
[ROW][C]36[/C][C]32[/C][C]33.6299[/C][C]-1.62987[/C][/ROW]
[ROW][C]37[/C][C]29[/C][C]31.6721[/C][C]-2.6721[/C][/ROW]
[ROW][C]38[/C][C]36[/C][C]33.7923[/C][C]2.20766[/C][/ROW]
[ROW][C]39[/C][C]29[/C][C]33.5586[/C][C]-4.55857[/C][/ROW]
[ROW][C]40[/C][C]35[/C][C]34.1498[/C][C]0.850239[/C][/ROW]
[ROW][C]41[/C][C]37[/C][C]33.9294[/C][C]3.07061[/C][/ROW]
[ROW][C]42[/C][C]34[/C][C]33.8046[/C][C]0.195447[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]34.0653[/C][C]3.93468[/C][/ROW]
[ROW][C]44[/C][C]35[/C][C]33.3196[/C][C]1.68041[/C][/ROW]
[ROW][C]45[/C][C]38[/C][C]31.7005[/C][C]6.29951[/C][/ROW]
[ROW][C]46[/C][C]37[/C][C]33.9601[/C][C]3.03989[/C][/ROW]
[ROW][C]47[/C][C]38[/C][C]36.4152[/C][C]1.58478[/C][/ROW]
[ROW][C]48[/C][C]33[/C][C]34.5354[/C][C]-1.53536[/C][/ROW]
[ROW][C]49[/C][C]36[/C][C]36.297[/C][C]-0.297048[/C][/ROW]
[ROW][C]50[/C][C]38[/C][C]33.395[/C][C]4.60505[/C][/ROW]
[ROW][C]51[/C][C]32[/C][C]36.3497[/C][C]-4.3497[/C][/ROW]
[ROW][C]52[/C][C]32[/C][C]32.3523[/C][C]-0.352264[/C][/ROW]
[ROW][C]53[/C][C]32[/C][C]32.9026[/C][C]-0.902617[/C][/ROW]
[ROW][C]54[/C][C]34[/C][C]35.8582[/C][C]-1.85815[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]32.6763[/C][C]-0.676347[/C][/ROW]
[ROW][C]56[/C][C]37[/C][C]34.8651[/C][C]2.13487[/C][/ROW]
[ROW][C]57[/C][C]39[/C][C]34.5691[/C][C]4.4309[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]34.6021[/C][C]-5.60209[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]35.303[/C][C]1.69696[/C][/ROW]
[ROW][C]60[/C][C]35[/C][C]34.3196[/C][C]0.680393[/C][/ROW]
[ROW][C]61[/C][C]30[/C][C]30.521[/C][C]-0.521048[/C][/ROW]
[ROW][C]62[/C][C]38[/C][C]34.551[/C][C]3.44897[/C][/ROW]
[ROW][C]63[/C][C]34[/C][C]34.8827[/C][C]-0.882681[/C][/ROW]
[ROW][C]64[/C][C]31[/C][C]34.2338[/C][C]-3.2338[/C][/ROW]
[ROW][C]65[/C][C]34[/C][C]32.8682[/C][C]1.13178[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]35.9524[/C][C]-0.952391[/C][/ROW]
[ROW][C]67[/C][C]36[/C][C]34.689[/C][C]1.31101[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]31.7193[/C][C]-1.71933[/C][/ROW]
[ROW][C]69[/C][C]39[/C][C]36.3638[/C][C]2.63625[/C][/ROW]
[ROW][C]70[/C][C]35[/C][C]35.7028[/C][C]-0.702802[/C][/ROW]
[ROW][C]71[/C][C]38[/C][C]34.5066[/C][C]3.49338[/C][/ROW]
[ROW][C]72[/C][C]31[/C][C]35.6099[/C][C]-4.6099[/C][/ROW]
[ROW][C]73[/C][C]34[/C][C]37.0542[/C][C]-3.05415[/C][/ROW]
[ROW][C]74[/C][C]38[/C][C]37.8638[/C][C]0.136154[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]31.6656[/C][C]2.33437[/C][/ROW]
[ROW][C]76[/C][C]39[/C][C]32.7397[/C][C]6.26033[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.81[/C][C]1.18999[/C][/ROW]
[ROW][C]78[/C][C]34[/C][C]32.8949[/C][C]1.10506[/C][/ROW]
[ROW][C]79[/C][C]28[/C][C]32.827[/C][C]-4.82699[/C][/ROW]
[ROW][C]80[/C][C]37[/C][C]31.2372[/C][C]5.76279[/C][/ROW]
[ROW][C]81[/C][C]33[/C][C]35.5882[/C][C]-2.58822[/C][/ROW]
[ROW][C]82[/C][C]35[/C][C]35.9824[/C][C]-0.982441[/C][/ROW]
[ROW][C]83[/C][C]37[/C][C]34.0155[/C][C]2.98448[/C][/ROW]
[ROW][C]84[/C][C]32[/C][C]34.4338[/C][C]-2.43382[/C][/ROW]
[ROW][C]85[/C][C]33[/C][C]33.3098[/C][C]-0.30977[/C][/ROW]
[ROW][C]86[/C][C]38[/C][C]36.5509[/C][C]1.44908[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]34.4506[/C][C]-1.45057[/C][/ROW]
[ROW][C]88[/C][C]29[/C][C]33.1274[/C][C]-4.12739[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.115[/C][C]-0.114964[/C][/ROW]
[ROW][C]90[/C][C]31[/C][C]34.9889[/C][C]-3.98894[/C][/ROW]
[ROW][C]91[/C][C]36[/C][C]33.1587[/C][C]2.84134[/C][/ROW]
[ROW][C]92[/C][C]35[/C][C]37.639[/C][C]-2.63896[/C][/ROW]
[ROW][C]93[/C][C]32[/C][C]31.7633[/C][C]0.236726[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]32.3876[/C][C]-3.38761[/C][/ROW]
[ROW][C]95[/C][C]39[/C][C]35.7236[/C][C]3.2764[/C][/ROW]
[ROW][C]96[/C][C]37[/C][C]34.5729[/C][C]2.42707[/C][/ROW]
[ROW][C]97[/C][C]35[/C][C]33.4641[/C][C]1.53588[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]34.8296[/C][C]2.17042[/C][/ROW]
[ROW][C]99[/C][C]32[/C][C]35.366[/C][C]-3.36603[/C][/ROW]
[ROW][C]100[/C][C]38[/C][C]35.5863[/C][C]2.41372[/C][/ROW]
[ROW][C]101[/C][C]37[/C][C]34.7211[/C][C]2.27893[/C][/ROW]
[ROW][C]102[/C][C]36[/C][C]36.5971[/C][C]-0.597106[/C][/ROW]
[ROW][C]103[/C][C]32[/C][C]31.5976[/C][C]0.402366[/C][/ROW]
[ROW][C]104[/C][C]33[/C][C]36.6928[/C][C]-3.69284[/C][/ROW]
[ROW][C]105[/C][C]40[/C][C]32.5732[/C][C]7.42683[/C][/ROW]
[ROW][C]106[/C][C]38[/C][C]35.287[/C][C]2.71304[/C][/ROW]
[ROW][C]107[/C][C]41[/C][C]36.5135[/C][C]4.48648[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]34.357[/C][C]1.64305[/C][/ROW]
[ROW][C]109[/C][C]43[/C][C]36.3966[/C][C]6.60344[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]34.6733[/C][C]-4.67328[/C][/ROW]
[ROW][C]111[/C][C]31[/C][C]33.7572[/C][C]-2.75724[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]38.0372[/C][C]-6.03721[/C][/ROW]
[ROW][C]113[/C][C]32[/C][C]32.9176[/C][C]-0.917629[/C][/ROW]
[ROW][C]114[/C][C]37[/C][C]34.2179[/C][C]2.7821[/C][/ROW]
[ROW][C]115[/C][C]37[/C][C]34.3103[/C][C]2.68966[/C][/ROW]
[ROW][C]116[/C][C]33[/C][C]36.3746[/C][C]-3.37456[/C][/ROW]
[ROW][C]117[/C][C]34[/C][C]36.8464[/C][C]-2.84643[/C][/ROW]
[ROW][C]118[/C][C]33[/C][C]34.6283[/C][C]-1.62834[/C][/ROW]
[ROW][C]119[/C][C]38[/C][C]35.5457[/C][C]2.45434[/C][/ROW]
[ROW][C]120[/C][C]33[/C][C]34.8655[/C][C]-1.86547[/C][/ROW]
[ROW][C]121[/C][C]31[/C][C]31.3794[/C][C]-0.379449[/C][/ROW]
[ROW][C]122[/C][C]38[/C][C]36.6291[/C][C]1.37085[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]36.4778[/C][C]0.522179[/C][/ROW]
[ROW][C]124[/C][C]36[/C][C]33.1121[/C][C]2.88788[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]34.0813[/C][C]-3.08135[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]34.1905[/C][C]4.80953[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]37.1266[/C][C]6.87344[/C][/ROW]
[ROW][C]128[/C][C]33[/C][C]35.7515[/C][C]-2.75151[/C][/ROW]
[ROW][C]129[/C][C]35[/C][C]33.5035[/C][C]1.4965[/C][/ROW]
[ROW][C]130[/C][C]32[/C][C]34.1359[/C][C]-2.13593[/C][/ROW]
[ROW][C]131[/C][C]28[/C][C]32.0835[/C][C]-4.08349[/C][/ROW]
[ROW][C]132[/C][C]40[/C][C]36.1947[/C][C]3.80529[/C][/ROW]
[ROW][C]133[/C][C]27[/C][C]31.9727[/C][C]-4.9727[/C][/ROW]
[ROW][C]134[/C][C]37[/C][C]36.0286[/C][C]0.971389[/C][/ROW]
[ROW][C]135[/C][C]32[/C][C]32.3813[/C][C]-0.381276[/C][/ROW]
[ROW][C]136[/C][C]28[/C][C]27.9613[/C][C]0.0386561[/C][/ROW]
[ROW][C]137[/C][C]34[/C][C]34.575[/C][C]-0.574985[/C][/ROW]
[ROW][C]138[/C][C]30[/C][C]33.6458[/C][C]-3.64577[/C][/ROW]
[ROW][C]139[/C][C]35[/C][C]34.0147[/C][C]0.985324[/C][/ROW]
[ROW][C]140[/C][C]31[/C][C]34.2233[/C][C]-3.22326[/C][/ROW]
[ROW][C]141[/C][C]32[/C][C]34.4811[/C][C]-2.48107[/C][/ROW]
[ROW][C]142[/C][C]30[/C][C]35.9745[/C][C]-5.97452[/C][/ROW]
[ROW][C]143[/C][C]30[/C][C]35.2168[/C][C]-5.21678[/C][/ROW]
[ROW][C]144[/C][C]31[/C][C]29.8657[/C][C]1.13427[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]32.8864[/C][C]7.11356[/C][/ROW]
[ROW][C]146[/C][C]32[/C][C]31.8535[/C][C]0.146541[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]34.553[/C][C]1.44704[/C][/ROW]
[ROW][C]148[/C][C]32[/C][C]33.2148[/C][C]-1.2148[/C][/ROW]
[ROW][C]149[/C][C]35[/C][C]32.7778[/C][C]2.22217[/C][/ROW]
[ROW][C]150[/C][C]38[/C][C]36.3002[/C][C]1.69982[/C][/ROW]
[ROW][C]151[/C][C]42[/C][C]35.4645[/C][C]6.53546[/C][/ROW]
[ROW][C]152[/C][C]34[/C][C]36.576[/C][C]-2.57599[/C][/ROW]
[ROW][C]153[/C][C]35[/C][C]36.841[/C][C]-1.841[/C][/ROW]
[ROW][C]154[/C][C]38[/C][C]33.7683[/C][C]4.23167[/C][/ROW]
[ROW][C]155[/C][C]33[/C][C]32.2315[/C][C]0.768497[/C][/ROW]
[ROW][C]156[/C][C]36[/C][C]33.1587[/C][C]2.84134[/C][/ROW]
[ROW][C]157[/C][C]32[/C][C]35.4522[/C][C]-3.45216[/C][/ROW]
[ROW][C]158[/C][C]33[/C][C]35.7515[/C][C]-2.75151[/C][/ROW]
[ROW][C]159[/C][C]34[/C][C]33.9861[/C][C]0.0139183[/C][/ROW]
[ROW][C]160[/C][C]32[/C][C]35.6504[/C][C]-3.65044[/C][/ROW]
[ROW][C]161[/C][C]34[/C][C]34.7998[/C][C]-0.799773[/C][/ROW]
[ROW][C]162[/C][C]27[/C][C]29.791[/C][C]-2.79099[/C][/ROW]
[ROW][C]163[/C][C]31[/C][C]30.6324[/C][C]0.367554[/C][/ROW]
[ROW][C]164[/C][C]38[/C][C]34.0006[/C][C]3.99942[/C][/ROW]
[ROW][C]165[/C][C]34[/C][C]36.1636[/C][C]-2.16364[/C][/ROW]
[ROW][C]166[/C][C]24[/C][C]31.0495[/C][C]-7.04949[/C][/ROW]
[ROW][C]167[/C][C]30[/C][C]33.9142[/C][C]-3.91425[/C][/ROW]
[ROW][C]168[/C][C]26[/C][C]29.689[/C][C]-3.68903[/C][/ROW]
[ROW][C]169[/C][C]34[/C][C]35.5859[/C][C]-1.58586[/C][/ROW]
[ROW][C]170[/C][C]27[/C][C]35.3381[/C][C]-8.33811[/C][/ROW]
[ROW][C]171[/C][C]37[/C][C]32.0639[/C][C]4.93611[/C][/ROW]
[ROW][C]172[/C][C]36[/C][C]35.8931[/C][C]0.106882[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]34.3309[/C][C]6.6691[/C][/ROW]
[ROW][C]174[/C][C]29[/C][C]29.2175[/C][C]-0.21751[/C][/ROW]
[ROW][C]175[/C][C]36[/C][C]31.3207[/C][C]4.67926[/C][/ROW]
[ROW][C]176[/C][C]32[/C][C]35.0428[/C][C]-3.0428[/C][/ROW]
[ROW][C]177[/C][C]37[/C][C]33.1643[/C][C]3.83565[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.8545[/C][C]-1.8545[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]33.0644[/C][C]-2.06438[/C][/ROW]
[ROW][C]180[/C][C]38[/C][C]35.1551[/C][C]2.84491[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]35.1098[/C][C]0.890184[/C][/ROW]
[ROW][C]182[/C][C]35[/C][C]32.2682[/C][C]2.73179[/C][/ROW]
[ROW][C]183[/C][C]31[/C][C]35.7581[/C][C]-4.75807[/C][/ROW]
[ROW][C]184[/C][C]38[/C][C]33.7197[/C][C]4.28034[/C][/ROW]
[ROW][C]185[/C][C]22[/C][C]31.1239[/C][C]-9.12387[/C][/ROW]
[ROW][C]186[/C][C]32[/C][C]35.0646[/C][C]-3.06457[/C][/ROW]
[ROW][C]187[/C][C]36[/C][C]34.6277[/C][C]1.37234[/C][/ROW]
[ROW][C]188[/C][C]39[/C][C]33.098[/C][C]5.90199[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.8832[/C][C]-2.88317[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]34.1556[/C][C]-2.15565[/C][/ROW]
[ROW][C]191[/C][C]32[/C][C]34.3153[/C][C]-2.31527[/C][/ROW]
[ROW][C]192[/C][C]38[/C][C]37.274[/C][C]0.725985[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]33.6649[/C][C]-1.66493[/C][/ROW]
[ROW][C]194[/C][C]35[/C][C]35.3617[/C][C]-0.361699[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]33.2051[/C][C]-1.20507[/C][/ROW]
[ROW][C]196[/C][C]37[/C][C]35.9871[/C][C]1.01294[/C][/ROW]
[ROW][C]197[/C][C]34[/C][C]33.0904[/C][C]0.909631[/C][/ROW]
[ROW][C]198[/C][C]33[/C][C]35.9298[/C][C]-2.92977[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]33.13[/C][C]-0.12996[/C][/ROW]
[ROW][C]200[/C][C]26[/C][C]33.6287[/C][C]-7.62866[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]32.2598[/C][C]-2.25975[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]32.525[/C][C]-8.52504[/C][/ROW]
[ROW][C]203[/C][C]34[/C][C]32.79[/C][C]1.21003[/C][/ROW]
[ROW][C]204[/C][C]34[/C][C]32.5834[/C][C]1.4166[/C][/ROW]
[ROW][C]205[/C][C]33[/C][C]34.5997[/C][C]-1.59968[/C][/ROW]
[ROW][C]206[/C][C]34[/C][C]35.2935[/C][C]-1.29345[/C][/ROW]
[ROW][C]207[/C][C]35[/C][C]36.0804[/C][C]-1.0804[/C][/ROW]
[ROW][C]208[/C][C]35[/C][C]34.9588[/C][C]0.0411746[/C][/ROW]
[ROW][C]209[/C][C]36[/C][C]33.2305[/C][C]2.76947[/C][/ROW]
[ROW][C]210[/C][C]34[/C][C]34.2864[/C][C]-0.286441[/C][/ROW]
[ROW][C]211[/C][C]34[/C][C]32.8893[/C][C]1.11067[/C][/ROW]
[ROW][C]212[/C][C]41[/C][C]38.6167[/C][C]2.38327[/C][/ROW]
[ROW][C]213[/C][C]32[/C][C]36.4276[/C][C]-4.42765[/C][/ROW]
[ROW][C]214[/C][C]30[/C][C]33.5519[/C][C]-3.55185[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]34.4881[/C][C]0.511947[/C][/ROW]
[ROW][C]216[/C][C]28[/C][C]30.2223[/C][C]-2.22232[/C][/ROW]
[ROW][C]217[/C][C]33[/C][C]35.5237[/C][C]-2.52369[/C][/ROW]
[ROW][C]218[/C][C]39[/C][C]34.4777[/C][C]4.52233[/C][/ROW]
[ROW][C]219[/C][C]36[/C][C]33.7299[/C][C]2.2701[/C][/ROW]
[ROW][C]220[/C][C]36[/C][C]36.6561[/C][C]-0.656074[/C][/ROW]
[ROW][C]221[/C][C]35[/C][C]33.5723[/C][C]1.42765[/C][/ROW]
[ROW][C]222[/C][C]38[/C][C]34.9923[/C][C]3.00767[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]33.0775[/C][C]-0.0774793[/C][/ROW]
[ROW][C]224[/C][C]31[/C][C]33.3404[/C][C]-2.34039[/C][/ROW]
[ROW][C]225[/C][C]34[/C][C]33.813[/C][C]0.187027[/C][/ROW]
[ROW][C]226[/C][C]32[/C][C]34.7076[/C][C]-2.70756[/C][/ROW]
[ROW][C]227[/C][C]31[/C][C]33.3438[/C][C]-2.34376[/C][/ROW]
[ROW][C]228[/C][C]33[/C][C]34.0861[/C][C]-1.08608[/C][/ROW]
[ROW][C]229[/C][C]34[/C][C]32.5598[/C][C]1.44019[/C][/ROW]
[ROW][C]230[/C][C]34[/C][C]34.2604[/C][C]-0.260373[/C][/ROW]
[ROW][C]231[/C][C]34[/C][C]32.528[/C][C]1.47204[/C][/ROW]
[ROW][C]232[/C][C]33[/C][C]34.956[/C][C]-1.95603[/C][/ROW]
[ROW][C]233[/C][C]32[/C][C]34.6781[/C][C]-2.67812[/C][/ROW]
[ROW][C]234[/C][C]41[/C][C]34.0005[/C][C]6.99948[/C][/ROW]
[ROW][C]235[/C][C]34[/C][C]33.4895[/C][C]0.510502[/C][/ROW]
[ROW][C]236[/C][C]36[/C][C]32.2773[/C][C]3.72266[/C][/ROW]
[ROW][C]237[/C][C]37[/C][C]30.9574[/C][C]6.04265[/C][/ROW]
[ROW][C]238[/C][C]36[/C][C]30.5267[/C][C]5.47328[/C][/ROW]
[ROW][C]239[/C][C]29[/C][C]33.0824[/C][C]-4.08244[/C][/ROW]
[ROW][C]240[/C][C]37[/C][C]31.9422[/C][C]5.05776[/C][/ROW]
[ROW][C]241[/C][C]27[/C][C]33.4915[/C][C]-6.49152[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.4711[/C][C]1.52887[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]30.8234[/C][C]-2.82336[/C][/ROW]
[ROW][C]244[/C][C]35[/C][C]33.4751[/C][C]1.52494[/C][/ROW]
[ROW][C]245[/C][C]37[/C][C]33.2402[/C][C]3.75979[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]33.9394[/C][C]-4.93944[/C][/ROW]
[ROW][C]247[/C][C]32[/C][C]34.5037[/C][C]-2.50366[/C][/ROW]
[ROW][C]248[/C][C]36[/C][C]31.8282[/C][C]4.17185[/C][/ROW]
[ROW][C]249[/C][C]19[/C][C]27.5573[/C][C]-8.55732[/C][/ROW]
[ROW][C]250[/C][C]21[/C][C]27.3044[/C][C]-6.30437[/C][/ROW]
[ROW][C]251[/C][C]31[/C][C]33.8639[/C][C]-2.86395[/C][/ROW]
[ROW][C]252[/C][C]33[/C][C]32.7561[/C][C]0.243873[/C][/ROW]
[ROW][C]253[/C][C]36[/C][C]34.1357[/C][C]1.8643[/C][/ROW]
[ROW][C]254[/C][C]33[/C][C]33.6579[/C][C]-0.657907[/C][/ROW]
[ROW][C]255[/C][C]37[/C][C]33.1571[/C][C]3.84293[/C][/ROW]
[ROW][C]256[/C][C]34[/C][C]33.4948[/C][C]0.505181[/C][/ROW]
[ROW][C]257[/C][C]35[/C][C]35.2265[/C][C]-0.226461[/C][/ROW]
[ROW][C]258[/C][C]31[/C][C]32.821[/C][C]-1.821[/C][/ROW]
[ROW][C]259[/C][C]37[/C][C]33.9029[/C][C]3.09707[/C][/ROW]
[ROW][C]260[/C][C]35[/C][C]31.5576[/C][C]3.44244[/C][/ROW]
[ROW][C]261[/C][C]27[/C][C]32.5067[/C][C]-5.5067[/C][/ROW]
[ROW][C]262[/C][C]34[/C][C]35.4787[/C][C]-1.47869[/C][/ROW]
[ROW][C]263[/C][C]40[/C][C]33.8868[/C][C]6.11316[/C][/ROW]
[ROW][C]264[/C][C]29[/C][C]33.4502[/C][C]-4.45024[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225809&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225809&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
14135.47215.52785
23934.07014.92994
33034.945-4.94497
43133.9847-2.9847
53435.1876-1.18765
63532.21762.78244
73932.81536.18472
83435.3397-1.3397
93634.81621.18375
103736.280.720041
113833.61124.38881
123634.58241.41757
133834.5463.45399
143935.95533.04474
153336.3651-3.36507
163233.5748-1.57484
173633.51432.48572
183837.29220.707809
193936.5432.45697
203233.3974-1.39744
213234.282-2.28195
223132.9054-1.90541
233936.34012.65995
243736.26760.7324
253934.19214.80794
264133.82677.1733
273635.21670.783296
283335.3878-2.38783
293334.1138-1.11376
303433.59180.408243
313133.4116-2.41158
322732.6904-5.69042
333733.17443.82559
343436.1127-2.11266
353432.4461.554
363233.6299-1.62987
372931.6721-2.6721
383633.79232.20766
392933.5586-4.55857
403534.14980.850239
413733.92943.07061
423433.80460.195447
433834.06533.93468
443533.31961.68041
453831.70056.29951
463733.96013.03989
473836.41521.58478
483334.5354-1.53536
493636.297-0.297048
503833.3954.60505
513236.3497-4.3497
523232.3523-0.352264
533232.9026-0.902617
543435.8582-1.85815
553232.6763-0.676347
563734.86512.13487
573934.56914.4309
582934.6021-5.60209
593735.3031.69696
603534.31960.680393
613030.521-0.521048
623834.5513.44897
633434.8827-0.882681
643134.2338-3.2338
653432.86821.13178
663535.9524-0.952391
673634.6891.31101
683031.7193-1.71933
693936.36382.63625
703535.7028-0.702802
713834.50663.49338
723135.6099-4.6099
733437.0542-3.05415
743837.86380.136154
753431.66562.33437
763932.73976.26033
773735.811.18999
783432.89491.10506
792832.827-4.82699
803731.23725.76279
813335.5882-2.58822
823535.9824-0.982441
833734.01552.98448
843234.4338-2.43382
853333.3098-0.30977
863836.55091.44908
873334.4506-1.45057
882933.1274-4.12739
893333.115-0.114964
903134.9889-3.98894
913633.15872.84134
923537.639-2.63896
933231.76330.236726
942932.3876-3.38761
953935.72363.2764
963734.57292.42707
973533.46411.53588
983734.82962.17042
993235.366-3.36603
1003835.58632.41372
1013734.72112.27893
1023636.5971-0.597106
1033231.59760.402366
1043336.6928-3.69284
1054032.57327.42683
1063835.2872.71304
1074136.51354.48648
1083634.3571.64305
1094336.39666.60344
1103034.6733-4.67328
1113133.7572-2.75724
1123238.0372-6.03721
1133232.9176-0.917629
1143734.21792.7821
1153734.31032.68966
1163336.3746-3.37456
1173436.8464-2.84643
1183334.6283-1.62834
1193835.54572.45434
1203334.8655-1.86547
1213131.3794-0.379449
1223836.62911.37085
1233736.47780.522179
1243633.11212.88788
1253134.0813-3.08135
1263934.19054.80953
1274437.12666.87344
1283335.7515-2.75151
1293533.50351.4965
1303234.1359-2.13593
1312832.0835-4.08349
1324036.19473.80529
1332731.9727-4.9727
1343736.02860.971389
1353232.3813-0.381276
1362827.96130.0386561
1373434.575-0.574985
1383033.6458-3.64577
1393534.01470.985324
1403134.2233-3.22326
1413234.4811-2.48107
1423035.9745-5.97452
1433035.2168-5.21678
1443129.86571.13427
1454032.88647.11356
1463231.85350.146541
1473634.5531.44704
1483233.2148-1.2148
1493532.77782.22217
1503836.30021.69982
1514235.46456.53546
1523436.576-2.57599
1533536.841-1.841
1543833.76834.23167
1553332.23150.768497
1563633.15872.84134
1573235.4522-3.45216
1583335.7515-2.75151
1593433.98610.0139183
1603235.6504-3.65044
1613434.7998-0.799773
1622729.791-2.79099
1633130.63240.367554
1643834.00063.99942
1653436.1636-2.16364
1662431.0495-7.04949
1673033.9142-3.91425
1682629.689-3.68903
1693435.5859-1.58586
1702735.3381-8.33811
1713732.06394.93611
1723635.89310.106882
1734134.33096.6691
1742929.2175-0.21751
1753631.32074.67926
1763235.0428-3.0428
1773733.16433.83565
1783031.8545-1.8545
1793133.0644-2.06438
1803835.15512.84491
1813635.10980.890184
1823532.26822.73179
1833135.7581-4.75807
1843833.71974.28034
1852231.1239-9.12387
1863235.0646-3.06457
1873634.62771.37234
1883933.0985.90199
1892830.8832-2.88317
1903234.1556-2.15565
1913234.3153-2.31527
1923837.2740.725985
1933233.6649-1.66493
1943535.3617-0.361699
1953233.2051-1.20507
1963735.98711.01294
1973433.09040.909631
1983335.9298-2.92977
1993333.13-0.12996
2002633.6287-7.62866
2013032.2598-2.25975
2022432.525-8.52504
2033432.791.21003
2043432.58341.4166
2053334.5997-1.59968
2063435.2935-1.29345
2073536.0804-1.0804
2083534.95880.0411746
2093633.23052.76947
2103434.2864-0.286441
2113432.88931.11067
2124138.61672.38327
2133236.4276-4.42765
2143033.5519-3.55185
2153534.48810.511947
2162830.2223-2.22232
2173335.5237-2.52369
2183934.47774.52233
2193633.72992.2701
2203636.6561-0.656074
2213533.57231.42765
2223834.99233.00767
2233333.0775-0.0774793
2243133.3404-2.34039
2253433.8130.187027
2263234.7076-2.70756
2273133.3438-2.34376
2283334.0861-1.08608
2293432.55981.44019
2303434.2604-0.260373
2313432.5281.47204
2323334.956-1.95603
2333234.6781-2.67812
2344134.00056.99948
2353433.48950.510502
2363632.27733.72266
2373730.95746.04265
2383630.52675.47328
2392933.0824-4.08244
2403731.94225.05776
2412733.4915-6.49152
2423533.47111.52887
2432830.8234-2.82336
2443533.47511.52494
2453733.24023.75979
2462933.9394-4.93944
2473234.5037-2.50366
2483631.82824.17185
2491927.5573-8.55732
2502127.3044-6.30437
2513133.8639-2.86395
2523332.75610.243873
2533634.13571.8643
2543333.6579-0.657907
2553733.15713.84293
2563433.49480.505181
2573535.2265-0.226461
2583132.821-1.821
2593733.90293.09707
2603531.55763.44244
2612732.5067-5.5067
2623435.4787-1.47869
2634033.88686.11316
2642933.4502-4.45024






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.1369360.2738710.863064
110.05464010.109280.94536
120.755130.489740.24487
130.8060790.3878420.193921
140.726770.546460.27323
150.6548890.6902220.345111
160.7058850.588230.294115
170.6288630.7422730.371137
180.5730840.8538320.426916
190.5182780.9634430.481722
200.5450710.9098590.454929
210.5781730.8436530.421827
220.517460.965080.48254
230.4687890.9375780.531211
240.3976060.7952120.602394
250.4463180.8926360.553682
260.6891850.621630.310815
270.6308550.7382910.369145
280.5970030.8059940.402997
290.5584660.8830690.441534
300.500460.999080.49954
310.4999540.9999080.500046
320.6354250.7291510.364575
330.6245980.7508050.375402
340.5957570.8084860.404243
350.5455860.9088270.454414
360.4951660.9903320.504834
370.4477960.8955930.552204
380.4149260.8298520.585074
390.5260480.9479030.473952
400.4732430.9464860.526757
410.4413730.8827460.558627
420.3902590.7805190.609741
430.3559520.7119030.644048
440.316520.6330410.68348
450.382530.7650610.61747
460.397470.7949390.60253
470.360020.720040.63998
480.3321550.6643110.667845
490.288880.5777610.71112
500.3024640.6049280.697536
510.3435890.6871770.656411
520.3086980.6173950.691302
530.2705030.5410060.729497
540.2449210.4898410.755079
550.2103190.4206380.789681
560.1962010.3924030.803799
570.2103690.4207380.789631
580.3145510.6291020.685449
590.2839140.5678290.716086
600.2478920.4957830.752108
610.2196650.439330.780335
620.2117470.4234940.788253
630.1861770.3723530.813823
640.1843310.3686630.815669
650.1582320.3164640.841768
660.1373920.2747850.862608
670.1166490.2332970.883351
680.125170.250340.87483
690.1259250.251850.874075
700.1067830.2135660.893217
710.1122970.2245950.887703
720.1306920.2613840.869308
730.1275320.2550630.872468
740.1072980.2145960.892702
750.09294440.1858890.907056
760.1262050.2524090.873795
770.108680.2173590.89132
780.09185930.1837190.908141
790.1195290.2390580.880471
800.1431240.2862490.856876
810.1363670.2727330.863633
820.1179070.2358140.882093
830.1116330.2232650.888367
840.1061030.2122060.893897
850.09212660.1842530.907873
860.08144120.1628820.918559
870.071830.143660.92817
880.08576280.1715260.914237
890.07149180.1429840.928508
900.0758210.1516420.924179
910.07074710.1414940.929253
920.0633590.1267180.936641
930.05303770.1060750.946962
940.05507870.1101570.944921
950.05416360.1083270.945836
960.04992210.09984430.950078
970.04236590.08473180.957634
980.03735780.07471560.962642
990.03745130.07490270.962549
1000.03441680.06883360.965583
1010.03072650.0614530.969273
1020.02542160.05084330.974578
1030.0210670.04213390.978933
1040.02142050.04284090.97858
1050.05108880.1021780.948911
1060.04785440.09570890.952146
1070.05890930.1178190.941091
1080.0512240.1024480.948776
1090.08594390.1718880.914056
1100.1021190.2042380.897881
1110.09800430.1960090.901996
1120.1308650.261730.869135
1130.1177090.2354180.882291
1140.113480.226960.88652
1150.1082830.2165650.891717
1160.1056230.2112470.894377
1170.1002170.2004340.899783
1180.08750680.1750140.912493
1190.0820340.1640680.917966
1200.0726840.1453680.927316
1210.06350360.1270070.936496
1220.05741620.1148320.942584
1230.04866960.09733930.95133
1240.04675910.09351830.953241
1250.04443460.08886920.955565
1260.05497570.1099510.945024
1270.1002130.2004250.899787
1280.09637180.1927440.903628
1290.08496060.1699210.915039
1300.07834990.15670.92165
1310.08606020.172120.91394
1320.09193390.1838680.908066
1330.1121360.2242730.887864
1340.09836080.1967220.901639
1350.08459550.1691910.915405
1360.07351920.1470380.926481
1370.06232910.1246580.937671
1380.06471190.1294240.935288
1390.05500350.1100070.944996
1400.05404520.108090.945955
1410.05202950.1040590.947971
1420.07506430.1501290.924936
1430.09040130.1808030.909599
1440.08353960.1670790.91646
1450.1466630.2933270.853337
1460.1346690.2693390.865331
1470.1198780.2397570.880122
1480.1052010.2104030.894799
1490.09635230.1927050.903648
1500.08487740.1697550.915123
1510.1347530.2695060.865247
1520.1258160.2516320.874184
1530.1135860.2271730.886414
1540.124090.248180.87591
1550.1071080.2142170.892892
1560.1069320.2138630.893068
1570.1095660.2191320.890434
1580.1024270.2048540.897573
1590.0892620.1785240.910738
1600.09502140.1900430.904979
1610.08161890.1632380.918381
1620.07721260.1544250.922787
1630.06684060.1336810.933159
1640.08168270.1633650.918317
1650.07402020.148040.92598
1660.1352330.2704660.864767
1670.1361540.2723090.863846
1680.1324950.2649910.867505
1690.1191590.2383180.880841
1700.2355460.4710920.764454
1710.269260.538520.73074
1720.2400320.4800640.759968
1730.3278220.6556440.672178
1740.2946480.5892950.705352
1750.3481610.6963220.651839
1760.3342050.668410.665795
1770.3413990.6827990.658601
1780.314540.629080.68546
1790.2888040.5776080.711196
1800.2741230.5482460.725877
1810.2472040.4944090.752796
1820.2448650.4897310.755135
1830.2547930.5095850.745207
1840.3039510.6079020.696049
1850.5718390.8563210.428161
1860.5678550.864290.432145
1870.5528530.8942950.447147
1880.6649420.6701160.335058
1890.648230.7035410.35177
1900.6395510.7208980.360449
1910.6269930.7460140.373007
1920.5914520.8170960.408548
1930.5575950.8848110.442405
1940.5166950.9666090.483305
1950.4788330.9576670.521167
1960.4422790.8845580.557721
1970.4268850.8537690.573115
1980.406820.813640.59318
1990.3669560.7339110.633044
2000.4868240.9736480.513176
2010.4525920.9051840.547408
2020.640240.719520.35976
2030.6028050.794390.397195
2040.5630750.873850.436925
2050.5233420.9533170.476658
2060.4843360.9686710.515664
2070.4412890.8825780.558711
2080.3975640.7951280.602436
2090.3711040.7422080.628896
2100.3315630.6631250.668437
2110.2937160.5874310.706284
2120.2643990.5287980.735601
2130.3164650.6329290.683535
2140.2945810.5891630.705419
2150.2555930.5111870.744407
2160.2234530.4469060.776547
2170.1999510.3999020.800049
2180.2272450.454490.772755
2190.2009060.4018130.799094
2200.1774310.3548620.822569
2210.1496270.2992540.850373
2220.1420310.2840630.857969
2230.1155490.2310970.884451
2240.09856540.1971310.901435
2250.07826410.1565280.921736
2260.0860760.1721520.913924
2270.07445870.1489170.925541
2280.05784120.1156820.942159
2290.04443890.08887790.955561
2300.03355060.06710120.966449
2310.03102060.06204120.968979
2320.04376730.08753460.956233
2330.03414410.06828830.965856
2340.1177620.2355240.882238
2350.09285480.185710.907145
2360.08585750.1717150.914142
2370.08104430.1620890.918956
2380.1879960.3759910.812004
2390.1526910.3053820.847309
2400.2418370.4836740.758163
2410.3275390.6550780.672461
2420.2683940.5367880.731606
2430.2221230.4442450.777877
2440.1812020.3624050.818798
2450.387180.7743610.61282
2460.6367850.726430.363215
2470.6041040.7917920.395896
2480.5606830.8786330.439317
2490.5978960.8042080.402104
2500.5254620.9490750.474538
2510.5711880.8576240.428812
2520.7571010.4857980.242899
2530.6731220.6537560.326878
2540.8717430.2565140.128257

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.136936 & 0.273871 & 0.863064 \tabularnewline
11 & 0.0546401 & 0.10928 & 0.94536 \tabularnewline
12 & 0.75513 & 0.48974 & 0.24487 \tabularnewline
13 & 0.806079 & 0.387842 & 0.193921 \tabularnewline
14 & 0.72677 & 0.54646 & 0.27323 \tabularnewline
15 & 0.654889 & 0.690222 & 0.345111 \tabularnewline
16 & 0.705885 & 0.58823 & 0.294115 \tabularnewline
17 & 0.628863 & 0.742273 & 0.371137 \tabularnewline
18 & 0.573084 & 0.853832 & 0.426916 \tabularnewline
19 & 0.518278 & 0.963443 & 0.481722 \tabularnewline
20 & 0.545071 & 0.909859 & 0.454929 \tabularnewline
21 & 0.578173 & 0.843653 & 0.421827 \tabularnewline
22 & 0.51746 & 0.96508 & 0.48254 \tabularnewline
23 & 0.468789 & 0.937578 & 0.531211 \tabularnewline
24 & 0.397606 & 0.795212 & 0.602394 \tabularnewline
25 & 0.446318 & 0.892636 & 0.553682 \tabularnewline
26 & 0.689185 & 0.62163 & 0.310815 \tabularnewline
27 & 0.630855 & 0.738291 & 0.369145 \tabularnewline
28 & 0.597003 & 0.805994 & 0.402997 \tabularnewline
29 & 0.558466 & 0.883069 & 0.441534 \tabularnewline
30 & 0.50046 & 0.99908 & 0.49954 \tabularnewline
31 & 0.499954 & 0.999908 & 0.500046 \tabularnewline
32 & 0.635425 & 0.729151 & 0.364575 \tabularnewline
33 & 0.624598 & 0.750805 & 0.375402 \tabularnewline
34 & 0.595757 & 0.808486 & 0.404243 \tabularnewline
35 & 0.545586 & 0.908827 & 0.454414 \tabularnewline
36 & 0.495166 & 0.990332 & 0.504834 \tabularnewline
37 & 0.447796 & 0.895593 & 0.552204 \tabularnewline
38 & 0.414926 & 0.829852 & 0.585074 \tabularnewline
39 & 0.526048 & 0.947903 & 0.473952 \tabularnewline
40 & 0.473243 & 0.946486 & 0.526757 \tabularnewline
41 & 0.441373 & 0.882746 & 0.558627 \tabularnewline
42 & 0.390259 & 0.780519 & 0.609741 \tabularnewline
43 & 0.355952 & 0.711903 & 0.644048 \tabularnewline
44 & 0.31652 & 0.633041 & 0.68348 \tabularnewline
45 & 0.38253 & 0.765061 & 0.61747 \tabularnewline
46 & 0.39747 & 0.794939 & 0.60253 \tabularnewline
47 & 0.36002 & 0.72004 & 0.63998 \tabularnewline
48 & 0.332155 & 0.664311 & 0.667845 \tabularnewline
49 & 0.28888 & 0.577761 & 0.71112 \tabularnewline
50 & 0.302464 & 0.604928 & 0.697536 \tabularnewline
51 & 0.343589 & 0.687177 & 0.656411 \tabularnewline
52 & 0.308698 & 0.617395 & 0.691302 \tabularnewline
53 & 0.270503 & 0.541006 & 0.729497 \tabularnewline
54 & 0.244921 & 0.489841 & 0.755079 \tabularnewline
55 & 0.210319 & 0.420638 & 0.789681 \tabularnewline
56 & 0.196201 & 0.392403 & 0.803799 \tabularnewline
57 & 0.210369 & 0.420738 & 0.789631 \tabularnewline
58 & 0.314551 & 0.629102 & 0.685449 \tabularnewline
59 & 0.283914 & 0.567829 & 0.716086 \tabularnewline
60 & 0.247892 & 0.495783 & 0.752108 \tabularnewline
61 & 0.219665 & 0.43933 & 0.780335 \tabularnewline
62 & 0.211747 & 0.423494 & 0.788253 \tabularnewline
63 & 0.186177 & 0.372353 & 0.813823 \tabularnewline
64 & 0.184331 & 0.368663 & 0.815669 \tabularnewline
65 & 0.158232 & 0.316464 & 0.841768 \tabularnewline
66 & 0.137392 & 0.274785 & 0.862608 \tabularnewline
67 & 0.116649 & 0.233297 & 0.883351 \tabularnewline
68 & 0.12517 & 0.25034 & 0.87483 \tabularnewline
69 & 0.125925 & 0.25185 & 0.874075 \tabularnewline
70 & 0.106783 & 0.213566 & 0.893217 \tabularnewline
71 & 0.112297 & 0.224595 & 0.887703 \tabularnewline
72 & 0.130692 & 0.261384 & 0.869308 \tabularnewline
73 & 0.127532 & 0.255063 & 0.872468 \tabularnewline
74 & 0.107298 & 0.214596 & 0.892702 \tabularnewline
75 & 0.0929444 & 0.185889 & 0.907056 \tabularnewline
76 & 0.126205 & 0.252409 & 0.873795 \tabularnewline
77 & 0.10868 & 0.217359 & 0.89132 \tabularnewline
78 & 0.0918593 & 0.183719 & 0.908141 \tabularnewline
79 & 0.119529 & 0.239058 & 0.880471 \tabularnewline
80 & 0.143124 & 0.286249 & 0.856876 \tabularnewline
81 & 0.136367 & 0.272733 & 0.863633 \tabularnewline
82 & 0.117907 & 0.235814 & 0.882093 \tabularnewline
83 & 0.111633 & 0.223265 & 0.888367 \tabularnewline
84 & 0.106103 & 0.212206 & 0.893897 \tabularnewline
85 & 0.0921266 & 0.184253 & 0.907873 \tabularnewline
86 & 0.0814412 & 0.162882 & 0.918559 \tabularnewline
87 & 0.07183 & 0.14366 & 0.92817 \tabularnewline
88 & 0.0857628 & 0.171526 & 0.914237 \tabularnewline
89 & 0.0714918 & 0.142984 & 0.928508 \tabularnewline
90 & 0.075821 & 0.151642 & 0.924179 \tabularnewline
91 & 0.0707471 & 0.141494 & 0.929253 \tabularnewline
92 & 0.063359 & 0.126718 & 0.936641 \tabularnewline
93 & 0.0530377 & 0.106075 & 0.946962 \tabularnewline
94 & 0.0550787 & 0.110157 & 0.944921 \tabularnewline
95 & 0.0541636 & 0.108327 & 0.945836 \tabularnewline
96 & 0.0499221 & 0.0998443 & 0.950078 \tabularnewline
97 & 0.0423659 & 0.0847318 & 0.957634 \tabularnewline
98 & 0.0373578 & 0.0747156 & 0.962642 \tabularnewline
99 & 0.0374513 & 0.0749027 & 0.962549 \tabularnewline
100 & 0.0344168 & 0.0688336 & 0.965583 \tabularnewline
101 & 0.0307265 & 0.061453 & 0.969273 \tabularnewline
102 & 0.0254216 & 0.0508433 & 0.974578 \tabularnewline
103 & 0.021067 & 0.0421339 & 0.978933 \tabularnewline
104 & 0.0214205 & 0.0428409 & 0.97858 \tabularnewline
105 & 0.0510888 & 0.102178 & 0.948911 \tabularnewline
106 & 0.0478544 & 0.0957089 & 0.952146 \tabularnewline
107 & 0.0589093 & 0.117819 & 0.941091 \tabularnewline
108 & 0.051224 & 0.102448 & 0.948776 \tabularnewline
109 & 0.0859439 & 0.171888 & 0.914056 \tabularnewline
110 & 0.102119 & 0.204238 & 0.897881 \tabularnewline
111 & 0.0980043 & 0.196009 & 0.901996 \tabularnewline
112 & 0.130865 & 0.26173 & 0.869135 \tabularnewline
113 & 0.117709 & 0.235418 & 0.882291 \tabularnewline
114 & 0.11348 & 0.22696 & 0.88652 \tabularnewline
115 & 0.108283 & 0.216565 & 0.891717 \tabularnewline
116 & 0.105623 & 0.211247 & 0.894377 \tabularnewline
117 & 0.100217 & 0.200434 & 0.899783 \tabularnewline
118 & 0.0875068 & 0.175014 & 0.912493 \tabularnewline
119 & 0.082034 & 0.164068 & 0.917966 \tabularnewline
120 & 0.072684 & 0.145368 & 0.927316 \tabularnewline
121 & 0.0635036 & 0.127007 & 0.936496 \tabularnewline
122 & 0.0574162 & 0.114832 & 0.942584 \tabularnewline
123 & 0.0486696 & 0.0973393 & 0.95133 \tabularnewline
124 & 0.0467591 & 0.0935183 & 0.953241 \tabularnewline
125 & 0.0444346 & 0.0888692 & 0.955565 \tabularnewline
126 & 0.0549757 & 0.109951 & 0.945024 \tabularnewline
127 & 0.100213 & 0.200425 & 0.899787 \tabularnewline
128 & 0.0963718 & 0.192744 & 0.903628 \tabularnewline
129 & 0.0849606 & 0.169921 & 0.915039 \tabularnewline
130 & 0.0783499 & 0.1567 & 0.92165 \tabularnewline
131 & 0.0860602 & 0.17212 & 0.91394 \tabularnewline
132 & 0.0919339 & 0.183868 & 0.908066 \tabularnewline
133 & 0.112136 & 0.224273 & 0.887864 \tabularnewline
134 & 0.0983608 & 0.196722 & 0.901639 \tabularnewline
135 & 0.0845955 & 0.169191 & 0.915405 \tabularnewline
136 & 0.0735192 & 0.147038 & 0.926481 \tabularnewline
137 & 0.0623291 & 0.124658 & 0.937671 \tabularnewline
138 & 0.0647119 & 0.129424 & 0.935288 \tabularnewline
139 & 0.0550035 & 0.110007 & 0.944996 \tabularnewline
140 & 0.0540452 & 0.10809 & 0.945955 \tabularnewline
141 & 0.0520295 & 0.104059 & 0.947971 \tabularnewline
142 & 0.0750643 & 0.150129 & 0.924936 \tabularnewline
143 & 0.0904013 & 0.180803 & 0.909599 \tabularnewline
144 & 0.0835396 & 0.167079 & 0.91646 \tabularnewline
145 & 0.146663 & 0.293327 & 0.853337 \tabularnewline
146 & 0.134669 & 0.269339 & 0.865331 \tabularnewline
147 & 0.119878 & 0.239757 & 0.880122 \tabularnewline
148 & 0.105201 & 0.210403 & 0.894799 \tabularnewline
149 & 0.0963523 & 0.192705 & 0.903648 \tabularnewline
150 & 0.0848774 & 0.169755 & 0.915123 \tabularnewline
151 & 0.134753 & 0.269506 & 0.865247 \tabularnewline
152 & 0.125816 & 0.251632 & 0.874184 \tabularnewline
153 & 0.113586 & 0.227173 & 0.886414 \tabularnewline
154 & 0.12409 & 0.24818 & 0.87591 \tabularnewline
155 & 0.107108 & 0.214217 & 0.892892 \tabularnewline
156 & 0.106932 & 0.213863 & 0.893068 \tabularnewline
157 & 0.109566 & 0.219132 & 0.890434 \tabularnewline
158 & 0.102427 & 0.204854 & 0.897573 \tabularnewline
159 & 0.089262 & 0.178524 & 0.910738 \tabularnewline
160 & 0.0950214 & 0.190043 & 0.904979 \tabularnewline
161 & 0.0816189 & 0.163238 & 0.918381 \tabularnewline
162 & 0.0772126 & 0.154425 & 0.922787 \tabularnewline
163 & 0.0668406 & 0.133681 & 0.933159 \tabularnewline
164 & 0.0816827 & 0.163365 & 0.918317 \tabularnewline
165 & 0.0740202 & 0.14804 & 0.92598 \tabularnewline
166 & 0.135233 & 0.270466 & 0.864767 \tabularnewline
167 & 0.136154 & 0.272309 & 0.863846 \tabularnewline
168 & 0.132495 & 0.264991 & 0.867505 \tabularnewline
169 & 0.119159 & 0.238318 & 0.880841 \tabularnewline
170 & 0.235546 & 0.471092 & 0.764454 \tabularnewline
171 & 0.26926 & 0.53852 & 0.73074 \tabularnewline
172 & 0.240032 & 0.480064 & 0.759968 \tabularnewline
173 & 0.327822 & 0.655644 & 0.672178 \tabularnewline
174 & 0.294648 & 0.589295 & 0.705352 \tabularnewline
175 & 0.348161 & 0.696322 & 0.651839 \tabularnewline
176 & 0.334205 & 0.66841 & 0.665795 \tabularnewline
177 & 0.341399 & 0.682799 & 0.658601 \tabularnewline
178 & 0.31454 & 0.62908 & 0.68546 \tabularnewline
179 & 0.288804 & 0.577608 & 0.711196 \tabularnewline
180 & 0.274123 & 0.548246 & 0.725877 \tabularnewline
181 & 0.247204 & 0.494409 & 0.752796 \tabularnewline
182 & 0.244865 & 0.489731 & 0.755135 \tabularnewline
183 & 0.254793 & 0.509585 & 0.745207 \tabularnewline
184 & 0.303951 & 0.607902 & 0.696049 \tabularnewline
185 & 0.571839 & 0.856321 & 0.428161 \tabularnewline
186 & 0.567855 & 0.86429 & 0.432145 \tabularnewline
187 & 0.552853 & 0.894295 & 0.447147 \tabularnewline
188 & 0.664942 & 0.670116 & 0.335058 \tabularnewline
189 & 0.64823 & 0.703541 & 0.35177 \tabularnewline
190 & 0.639551 & 0.720898 & 0.360449 \tabularnewline
191 & 0.626993 & 0.746014 & 0.373007 \tabularnewline
192 & 0.591452 & 0.817096 & 0.408548 \tabularnewline
193 & 0.557595 & 0.884811 & 0.442405 \tabularnewline
194 & 0.516695 & 0.966609 & 0.483305 \tabularnewline
195 & 0.478833 & 0.957667 & 0.521167 \tabularnewline
196 & 0.442279 & 0.884558 & 0.557721 \tabularnewline
197 & 0.426885 & 0.853769 & 0.573115 \tabularnewline
198 & 0.40682 & 0.81364 & 0.59318 \tabularnewline
199 & 0.366956 & 0.733911 & 0.633044 \tabularnewline
200 & 0.486824 & 0.973648 & 0.513176 \tabularnewline
201 & 0.452592 & 0.905184 & 0.547408 \tabularnewline
202 & 0.64024 & 0.71952 & 0.35976 \tabularnewline
203 & 0.602805 & 0.79439 & 0.397195 \tabularnewline
204 & 0.563075 & 0.87385 & 0.436925 \tabularnewline
205 & 0.523342 & 0.953317 & 0.476658 \tabularnewline
206 & 0.484336 & 0.968671 & 0.515664 \tabularnewline
207 & 0.441289 & 0.882578 & 0.558711 \tabularnewline
208 & 0.397564 & 0.795128 & 0.602436 \tabularnewline
209 & 0.371104 & 0.742208 & 0.628896 \tabularnewline
210 & 0.331563 & 0.663125 & 0.668437 \tabularnewline
211 & 0.293716 & 0.587431 & 0.706284 \tabularnewline
212 & 0.264399 & 0.528798 & 0.735601 \tabularnewline
213 & 0.316465 & 0.632929 & 0.683535 \tabularnewline
214 & 0.294581 & 0.589163 & 0.705419 \tabularnewline
215 & 0.255593 & 0.511187 & 0.744407 \tabularnewline
216 & 0.223453 & 0.446906 & 0.776547 \tabularnewline
217 & 0.199951 & 0.399902 & 0.800049 \tabularnewline
218 & 0.227245 & 0.45449 & 0.772755 \tabularnewline
219 & 0.200906 & 0.401813 & 0.799094 \tabularnewline
220 & 0.177431 & 0.354862 & 0.822569 \tabularnewline
221 & 0.149627 & 0.299254 & 0.850373 \tabularnewline
222 & 0.142031 & 0.284063 & 0.857969 \tabularnewline
223 & 0.115549 & 0.231097 & 0.884451 \tabularnewline
224 & 0.0985654 & 0.197131 & 0.901435 \tabularnewline
225 & 0.0782641 & 0.156528 & 0.921736 \tabularnewline
226 & 0.086076 & 0.172152 & 0.913924 \tabularnewline
227 & 0.0744587 & 0.148917 & 0.925541 \tabularnewline
228 & 0.0578412 & 0.115682 & 0.942159 \tabularnewline
229 & 0.0444389 & 0.0888779 & 0.955561 \tabularnewline
230 & 0.0335506 & 0.0671012 & 0.966449 \tabularnewline
231 & 0.0310206 & 0.0620412 & 0.968979 \tabularnewline
232 & 0.0437673 & 0.0875346 & 0.956233 \tabularnewline
233 & 0.0341441 & 0.0682883 & 0.965856 \tabularnewline
234 & 0.117762 & 0.235524 & 0.882238 \tabularnewline
235 & 0.0928548 & 0.18571 & 0.907145 \tabularnewline
236 & 0.0858575 & 0.171715 & 0.914142 \tabularnewline
237 & 0.0810443 & 0.162089 & 0.918956 \tabularnewline
238 & 0.187996 & 0.375991 & 0.812004 \tabularnewline
239 & 0.152691 & 0.305382 & 0.847309 \tabularnewline
240 & 0.241837 & 0.483674 & 0.758163 \tabularnewline
241 & 0.327539 & 0.655078 & 0.672461 \tabularnewline
242 & 0.268394 & 0.536788 & 0.731606 \tabularnewline
243 & 0.222123 & 0.444245 & 0.777877 \tabularnewline
244 & 0.181202 & 0.362405 & 0.818798 \tabularnewline
245 & 0.38718 & 0.774361 & 0.61282 \tabularnewline
246 & 0.636785 & 0.72643 & 0.363215 \tabularnewline
247 & 0.604104 & 0.791792 & 0.395896 \tabularnewline
248 & 0.560683 & 0.878633 & 0.439317 \tabularnewline
249 & 0.597896 & 0.804208 & 0.402104 \tabularnewline
250 & 0.525462 & 0.949075 & 0.474538 \tabularnewline
251 & 0.571188 & 0.857624 & 0.428812 \tabularnewline
252 & 0.757101 & 0.485798 & 0.242899 \tabularnewline
253 & 0.673122 & 0.653756 & 0.326878 \tabularnewline
254 & 0.871743 & 0.256514 & 0.128257 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225809&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]10[/C][C]0.136936[/C][C]0.273871[/C][C]0.863064[/C][/ROW]
[ROW][C]11[/C][C]0.0546401[/C][C]0.10928[/C][C]0.94536[/C][/ROW]
[ROW][C]12[/C][C]0.75513[/C][C]0.48974[/C][C]0.24487[/C][/ROW]
[ROW][C]13[/C][C]0.806079[/C][C]0.387842[/C][C]0.193921[/C][/ROW]
[ROW][C]14[/C][C]0.72677[/C][C]0.54646[/C][C]0.27323[/C][/ROW]
[ROW][C]15[/C][C]0.654889[/C][C]0.690222[/C][C]0.345111[/C][/ROW]
[ROW][C]16[/C][C]0.705885[/C][C]0.58823[/C][C]0.294115[/C][/ROW]
[ROW][C]17[/C][C]0.628863[/C][C]0.742273[/C][C]0.371137[/C][/ROW]
[ROW][C]18[/C][C]0.573084[/C][C]0.853832[/C][C]0.426916[/C][/ROW]
[ROW][C]19[/C][C]0.518278[/C][C]0.963443[/C][C]0.481722[/C][/ROW]
[ROW][C]20[/C][C]0.545071[/C][C]0.909859[/C][C]0.454929[/C][/ROW]
[ROW][C]21[/C][C]0.578173[/C][C]0.843653[/C][C]0.421827[/C][/ROW]
[ROW][C]22[/C][C]0.51746[/C][C]0.96508[/C][C]0.48254[/C][/ROW]
[ROW][C]23[/C][C]0.468789[/C][C]0.937578[/C][C]0.531211[/C][/ROW]
[ROW][C]24[/C][C]0.397606[/C][C]0.795212[/C][C]0.602394[/C][/ROW]
[ROW][C]25[/C][C]0.446318[/C][C]0.892636[/C][C]0.553682[/C][/ROW]
[ROW][C]26[/C][C]0.689185[/C][C]0.62163[/C][C]0.310815[/C][/ROW]
[ROW][C]27[/C][C]0.630855[/C][C]0.738291[/C][C]0.369145[/C][/ROW]
[ROW][C]28[/C][C]0.597003[/C][C]0.805994[/C][C]0.402997[/C][/ROW]
[ROW][C]29[/C][C]0.558466[/C][C]0.883069[/C][C]0.441534[/C][/ROW]
[ROW][C]30[/C][C]0.50046[/C][C]0.99908[/C][C]0.49954[/C][/ROW]
[ROW][C]31[/C][C]0.499954[/C][C]0.999908[/C][C]0.500046[/C][/ROW]
[ROW][C]32[/C][C]0.635425[/C][C]0.729151[/C][C]0.364575[/C][/ROW]
[ROW][C]33[/C][C]0.624598[/C][C]0.750805[/C][C]0.375402[/C][/ROW]
[ROW][C]34[/C][C]0.595757[/C][C]0.808486[/C][C]0.404243[/C][/ROW]
[ROW][C]35[/C][C]0.545586[/C][C]0.908827[/C][C]0.454414[/C][/ROW]
[ROW][C]36[/C][C]0.495166[/C][C]0.990332[/C][C]0.504834[/C][/ROW]
[ROW][C]37[/C][C]0.447796[/C][C]0.895593[/C][C]0.552204[/C][/ROW]
[ROW][C]38[/C][C]0.414926[/C][C]0.829852[/C][C]0.585074[/C][/ROW]
[ROW][C]39[/C][C]0.526048[/C][C]0.947903[/C][C]0.473952[/C][/ROW]
[ROW][C]40[/C][C]0.473243[/C][C]0.946486[/C][C]0.526757[/C][/ROW]
[ROW][C]41[/C][C]0.441373[/C][C]0.882746[/C][C]0.558627[/C][/ROW]
[ROW][C]42[/C][C]0.390259[/C][C]0.780519[/C][C]0.609741[/C][/ROW]
[ROW][C]43[/C][C]0.355952[/C][C]0.711903[/C][C]0.644048[/C][/ROW]
[ROW][C]44[/C][C]0.31652[/C][C]0.633041[/C][C]0.68348[/C][/ROW]
[ROW][C]45[/C][C]0.38253[/C][C]0.765061[/C][C]0.61747[/C][/ROW]
[ROW][C]46[/C][C]0.39747[/C][C]0.794939[/C][C]0.60253[/C][/ROW]
[ROW][C]47[/C][C]0.36002[/C][C]0.72004[/C][C]0.63998[/C][/ROW]
[ROW][C]48[/C][C]0.332155[/C][C]0.664311[/C][C]0.667845[/C][/ROW]
[ROW][C]49[/C][C]0.28888[/C][C]0.577761[/C][C]0.71112[/C][/ROW]
[ROW][C]50[/C][C]0.302464[/C][C]0.604928[/C][C]0.697536[/C][/ROW]
[ROW][C]51[/C][C]0.343589[/C][C]0.687177[/C][C]0.656411[/C][/ROW]
[ROW][C]52[/C][C]0.308698[/C][C]0.617395[/C][C]0.691302[/C][/ROW]
[ROW][C]53[/C][C]0.270503[/C][C]0.541006[/C][C]0.729497[/C][/ROW]
[ROW][C]54[/C][C]0.244921[/C][C]0.489841[/C][C]0.755079[/C][/ROW]
[ROW][C]55[/C][C]0.210319[/C][C]0.420638[/C][C]0.789681[/C][/ROW]
[ROW][C]56[/C][C]0.196201[/C][C]0.392403[/C][C]0.803799[/C][/ROW]
[ROW][C]57[/C][C]0.210369[/C][C]0.420738[/C][C]0.789631[/C][/ROW]
[ROW][C]58[/C][C]0.314551[/C][C]0.629102[/C][C]0.685449[/C][/ROW]
[ROW][C]59[/C][C]0.283914[/C][C]0.567829[/C][C]0.716086[/C][/ROW]
[ROW][C]60[/C][C]0.247892[/C][C]0.495783[/C][C]0.752108[/C][/ROW]
[ROW][C]61[/C][C]0.219665[/C][C]0.43933[/C][C]0.780335[/C][/ROW]
[ROW][C]62[/C][C]0.211747[/C][C]0.423494[/C][C]0.788253[/C][/ROW]
[ROW][C]63[/C][C]0.186177[/C][C]0.372353[/C][C]0.813823[/C][/ROW]
[ROW][C]64[/C][C]0.184331[/C][C]0.368663[/C][C]0.815669[/C][/ROW]
[ROW][C]65[/C][C]0.158232[/C][C]0.316464[/C][C]0.841768[/C][/ROW]
[ROW][C]66[/C][C]0.137392[/C][C]0.274785[/C][C]0.862608[/C][/ROW]
[ROW][C]67[/C][C]0.116649[/C][C]0.233297[/C][C]0.883351[/C][/ROW]
[ROW][C]68[/C][C]0.12517[/C][C]0.25034[/C][C]0.87483[/C][/ROW]
[ROW][C]69[/C][C]0.125925[/C][C]0.25185[/C][C]0.874075[/C][/ROW]
[ROW][C]70[/C][C]0.106783[/C][C]0.213566[/C][C]0.893217[/C][/ROW]
[ROW][C]71[/C][C]0.112297[/C][C]0.224595[/C][C]0.887703[/C][/ROW]
[ROW][C]72[/C][C]0.130692[/C][C]0.261384[/C][C]0.869308[/C][/ROW]
[ROW][C]73[/C][C]0.127532[/C][C]0.255063[/C][C]0.872468[/C][/ROW]
[ROW][C]74[/C][C]0.107298[/C][C]0.214596[/C][C]0.892702[/C][/ROW]
[ROW][C]75[/C][C]0.0929444[/C][C]0.185889[/C][C]0.907056[/C][/ROW]
[ROW][C]76[/C][C]0.126205[/C][C]0.252409[/C][C]0.873795[/C][/ROW]
[ROW][C]77[/C][C]0.10868[/C][C]0.217359[/C][C]0.89132[/C][/ROW]
[ROW][C]78[/C][C]0.0918593[/C][C]0.183719[/C][C]0.908141[/C][/ROW]
[ROW][C]79[/C][C]0.119529[/C][C]0.239058[/C][C]0.880471[/C][/ROW]
[ROW][C]80[/C][C]0.143124[/C][C]0.286249[/C][C]0.856876[/C][/ROW]
[ROW][C]81[/C][C]0.136367[/C][C]0.272733[/C][C]0.863633[/C][/ROW]
[ROW][C]82[/C][C]0.117907[/C][C]0.235814[/C][C]0.882093[/C][/ROW]
[ROW][C]83[/C][C]0.111633[/C][C]0.223265[/C][C]0.888367[/C][/ROW]
[ROW][C]84[/C][C]0.106103[/C][C]0.212206[/C][C]0.893897[/C][/ROW]
[ROW][C]85[/C][C]0.0921266[/C][C]0.184253[/C][C]0.907873[/C][/ROW]
[ROW][C]86[/C][C]0.0814412[/C][C]0.162882[/C][C]0.918559[/C][/ROW]
[ROW][C]87[/C][C]0.07183[/C][C]0.14366[/C][C]0.92817[/C][/ROW]
[ROW][C]88[/C][C]0.0857628[/C][C]0.171526[/C][C]0.914237[/C][/ROW]
[ROW][C]89[/C][C]0.0714918[/C][C]0.142984[/C][C]0.928508[/C][/ROW]
[ROW][C]90[/C][C]0.075821[/C][C]0.151642[/C][C]0.924179[/C][/ROW]
[ROW][C]91[/C][C]0.0707471[/C][C]0.141494[/C][C]0.929253[/C][/ROW]
[ROW][C]92[/C][C]0.063359[/C][C]0.126718[/C][C]0.936641[/C][/ROW]
[ROW][C]93[/C][C]0.0530377[/C][C]0.106075[/C][C]0.946962[/C][/ROW]
[ROW][C]94[/C][C]0.0550787[/C][C]0.110157[/C][C]0.944921[/C][/ROW]
[ROW][C]95[/C][C]0.0541636[/C][C]0.108327[/C][C]0.945836[/C][/ROW]
[ROW][C]96[/C][C]0.0499221[/C][C]0.0998443[/C][C]0.950078[/C][/ROW]
[ROW][C]97[/C][C]0.0423659[/C][C]0.0847318[/C][C]0.957634[/C][/ROW]
[ROW][C]98[/C][C]0.0373578[/C][C]0.0747156[/C][C]0.962642[/C][/ROW]
[ROW][C]99[/C][C]0.0374513[/C][C]0.0749027[/C][C]0.962549[/C][/ROW]
[ROW][C]100[/C][C]0.0344168[/C][C]0.0688336[/C][C]0.965583[/C][/ROW]
[ROW][C]101[/C][C]0.0307265[/C][C]0.061453[/C][C]0.969273[/C][/ROW]
[ROW][C]102[/C][C]0.0254216[/C][C]0.0508433[/C][C]0.974578[/C][/ROW]
[ROW][C]103[/C][C]0.021067[/C][C]0.0421339[/C][C]0.978933[/C][/ROW]
[ROW][C]104[/C][C]0.0214205[/C][C]0.0428409[/C][C]0.97858[/C][/ROW]
[ROW][C]105[/C][C]0.0510888[/C][C]0.102178[/C][C]0.948911[/C][/ROW]
[ROW][C]106[/C][C]0.0478544[/C][C]0.0957089[/C][C]0.952146[/C][/ROW]
[ROW][C]107[/C][C]0.0589093[/C][C]0.117819[/C][C]0.941091[/C][/ROW]
[ROW][C]108[/C][C]0.051224[/C][C]0.102448[/C][C]0.948776[/C][/ROW]
[ROW][C]109[/C][C]0.0859439[/C][C]0.171888[/C][C]0.914056[/C][/ROW]
[ROW][C]110[/C][C]0.102119[/C][C]0.204238[/C][C]0.897881[/C][/ROW]
[ROW][C]111[/C][C]0.0980043[/C][C]0.196009[/C][C]0.901996[/C][/ROW]
[ROW][C]112[/C][C]0.130865[/C][C]0.26173[/C][C]0.869135[/C][/ROW]
[ROW][C]113[/C][C]0.117709[/C][C]0.235418[/C][C]0.882291[/C][/ROW]
[ROW][C]114[/C][C]0.11348[/C][C]0.22696[/C][C]0.88652[/C][/ROW]
[ROW][C]115[/C][C]0.108283[/C][C]0.216565[/C][C]0.891717[/C][/ROW]
[ROW][C]116[/C][C]0.105623[/C][C]0.211247[/C][C]0.894377[/C][/ROW]
[ROW][C]117[/C][C]0.100217[/C][C]0.200434[/C][C]0.899783[/C][/ROW]
[ROW][C]118[/C][C]0.0875068[/C][C]0.175014[/C][C]0.912493[/C][/ROW]
[ROW][C]119[/C][C]0.082034[/C][C]0.164068[/C][C]0.917966[/C][/ROW]
[ROW][C]120[/C][C]0.072684[/C][C]0.145368[/C][C]0.927316[/C][/ROW]
[ROW][C]121[/C][C]0.0635036[/C][C]0.127007[/C][C]0.936496[/C][/ROW]
[ROW][C]122[/C][C]0.0574162[/C][C]0.114832[/C][C]0.942584[/C][/ROW]
[ROW][C]123[/C][C]0.0486696[/C][C]0.0973393[/C][C]0.95133[/C][/ROW]
[ROW][C]124[/C][C]0.0467591[/C][C]0.0935183[/C][C]0.953241[/C][/ROW]
[ROW][C]125[/C][C]0.0444346[/C][C]0.0888692[/C][C]0.955565[/C][/ROW]
[ROW][C]126[/C][C]0.0549757[/C][C]0.109951[/C][C]0.945024[/C][/ROW]
[ROW][C]127[/C][C]0.100213[/C][C]0.200425[/C][C]0.899787[/C][/ROW]
[ROW][C]128[/C][C]0.0963718[/C][C]0.192744[/C][C]0.903628[/C][/ROW]
[ROW][C]129[/C][C]0.0849606[/C][C]0.169921[/C][C]0.915039[/C][/ROW]
[ROW][C]130[/C][C]0.0783499[/C][C]0.1567[/C][C]0.92165[/C][/ROW]
[ROW][C]131[/C][C]0.0860602[/C][C]0.17212[/C][C]0.91394[/C][/ROW]
[ROW][C]132[/C][C]0.0919339[/C][C]0.183868[/C][C]0.908066[/C][/ROW]
[ROW][C]133[/C][C]0.112136[/C][C]0.224273[/C][C]0.887864[/C][/ROW]
[ROW][C]134[/C][C]0.0983608[/C][C]0.196722[/C][C]0.901639[/C][/ROW]
[ROW][C]135[/C][C]0.0845955[/C][C]0.169191[/C][C]0.915405[/C][/ROW]
[ROW][C]136[/C][C]0.0735192[/C][C]0.147038[/C][C]0.926481[/C][/ROW]
[ROW][C]137[/C][C]0.0623291[/C][C]0.124658[/C][C]0.937671[/C][/ROW]
[ROW][C]138[/C][C]0.0647119[/C][C]0.129424[/C][C]0.935288[/C][/ROW]
[ROW][C]139[/C][C]0.0550035[/C][C]0.110007[/C][C]0.944996[/C][/ROW]
[ROW][C]140[/C][C]0.0540452[/C][C]0.10809[/C][C]0.945955[/C][/ROW]
[ROW][C]141[/C][C]0.0520295[/C][C]0.104059[/C][C]0.947971[/C][/ROW]
[ROW][C]142[/C][C]0.0750643[/C][C]0.150129[/C][C]0.924936[/C][/ROW]
[ROW][C]143[/C][C]0.0904013[/C][C]0.180803[/C][C]0.909599[/C][/ROW]
[ROW][C]144[/C][C]0.0835396[/C][C]0.167079[/C][C]0.91646[/C][/ROW]
[ROW][C]145[/C][C]0.146663[/C][C]0.293327[/C][C]0.853337[/C][/ROW]
[ROW][C]146[/C][C]0.134669[/C][C]0.269339[/C][C]0.865331[/C][/ROW]
[ROW][C]147[/C][C]0.119878[/C][C]0.239757[/C][C]0.880122[/C][/ROW]
[ROW][C]148[/C][C]0.105201[/C][C]0.210403[/C][C]0.894799[/C][/ROW]
[ROW][C]149[/C][C]0.0963523[/C][C]0.192705[/C][C]0.903648[/C][/ROW]
[ROW][C]150[/C][C]0.0848774[/C][C]0.169755[/C][C]0.915123[/C][/ROW]
[ROW][C]151[/C][C]0.134753[/C][C]0.269506[/C][C]0.865247[/C][/ROW]
[ROW][C]152[/C][C]0.125816[/C][C]0.251632[/C][C]0.874184[/C][/ROW]
[ROW][C]153[/C][C]0.113586[/C][C]0.227173[/C][C]0.886414[/C][/ROW]
[ROW][C]154[/C][C]0.12409[/C][C]0.24818[/C][C]0.87591[/C][/ROW]
[ROW][C]155[/C][C]0.107108[/C][C]0.214217[/C][C]0.892892[/C][/ROW]
[ROW][C]156[/C][C]0.106932[/C][C]0.213863[/C][C]0.893068[/C][/ROW]
[ROW][C]157[/C][C]0.109566[/C][C]0.219132[/C][C]0.890434[/C][/ROW]
[ROW][C]158[/C][C]0.102427[/C][C]0.204854[/C][C]0.897573[/C][/ROW]
[ROW][C]159[/C][C]0.089262[/C][C]0.178524[/C][C]0.910738[/C][/ROW]
[ROW][C]160[/C][C]0.0950214[/C][C]0.190043[/C][C]0.904979[/C][/ROW]
[ROW][C]161[/C][C]0.0816189[/C][C]0.163238[/C][C]0.918381[/C][/ROW]
[ROW][C]162[/C][C]0.0772126[/C][C]0.154425[/C][C]0.922787[/C][/ROW]
[ROW][C]163[/C][C]0.0668406[/C][C]0.133681[/C][C]0.933159[/C][/ROW]
[ROW][C]164[/C][C]0.0816827[/C][C]0.163365[/C][C]0.918317[/C][/ROW]
[ROW][C]165[/C][C]0.0740202[/C][C]0.14804[/C][C]0.92598[/C][/ROW]
[ROW][C]166[/C][C]0.135233[/C][C]0.270466[/C][C]0.864767[/C][/ROW]
[ROW][C]167[/C][C]0.136154[/C][C]0.272309[/C][C]0.863846[/C][/ROW]
[ROW][C]168[/C][C]0.132495[/C][C]0.264991[/C][C]0.867505[/C][/ROW]
[ROW][C]169[/C][C]0.119159[/C][C]0.238318[/C][C]0.880841[/C][/ROW]
[ROW][C]170[/C][C]0.235546[/C][C]0.471092[/C][C]0.764454[/C][/ROW]
[ROW][C]171[/C][C]0.26926[/C][C]0.53852[/C][C]0.73074[/C][/ROW]
[ROW][C]172[/C][C]0.240032[/C][C]0.480064[/C][C]0.759968[/C][/ROW]
[ROW][C]173[/C][C]0.327822[/C][C]0.655644[/C][C]0.672178[/C][/ROW]
[ROW][C]174[/C][C]0.294648[/C][C]0.589295[/C][C]0.705352[/C][/ROW]
[ROW][C]175[/C][C]0.348161[/C][C]0.696322[/C][C]0.651839[/C][/ROW]
[ROW][C]176[/C][C]0.334205[/C][C]0.66841[/C][C]0.665795[/C][/ROW]
[ROW][C]177[/C][C]0.341399[/C][C]0.682799[/C][C]0.658601[/C][/ROW]
[ROW][C]178[/C][C]0.31454[/C][C]0.62908[/C][C]0.68546[/C][/ROW]
[ROW][C]179[/C][C]0.288804[/C][C]0.577608[/C][C]0.711196[/C][/ROW]
[ROW][C]180[/C][C]0.274123[/C][C]0.548246[/C][C]0.725877[/C][/ROW]
[ROW][C]181[/C][C]0.247204[/C][C]0.494409[/C][C]0.752796[/C][/ROW]
[ROW][C]182[/C][C]0.244865[/C][C]0.489731[/C][C]0.755135[/C][/ROW]
[ROW][C]183[/C][C]0.254793[/C][C]0.509585[/C][C]0.745207[/C][/ROW]
[ROW][C]184[/C][C]0.303951[/C][C]0.607902[/C][C]0.696049[/C][/ROW]
[ROW][C]185[/C][C]0.571839[/C][C]0.856321[/C][C]0.428161[/C][/ROW]
[ROW][C]186[/C][C]0.567855[/C][C]0.86429[/C][C]0.432145[/C][/ROW]
[ROW][C]187[/C][C]0.552853[/C][C]0.894295[/C][C]0.447147[/C][/ROW]
[ROW][C]188[/C][C]0.664942[/C][C]0.670116[/C][C]0.335058[/C][/ROW]
[ROW][C]189[/C][C]0.64823[/C][C]0.703541[/C][C]0.35177[/C][/ROW]
[ROW][C]190[/C][C]0.639551[/C][C]0.720898[/C][C]0.360449[/C][/ROW]
[ROW][C]191[/C][C]0.626993[/C][C]0.746014[/C][C]0.373007[/C][/ROW]
[ROW][C]192[/C][C]0.591452[/C][C]0.817096[/C][C]0.408548[/C][/ROW]
[ROW][C]193[/C][C]0.557595[/C][C]0.884811[/C][C]0.442405[/C][/ROW]
[ROW][C]194[/C][C]0.516695[/C][C]0.966609[/C][C]0.483305[/C][/ROW]
[ROW][C]195[/C][C]0.478833[/C][C]0.957667[/C][C]0.521167[/C][/ROW]
[ROW][C]196[/C][C]0.442279[/C][C]0.884558[/C][C]0.557721[/C][/ROW]
[ROW][C]197[/C][C]0.426885[/C][C]0.853769[/C][C]0.573115[/C][/ROW]
[ROW][C]198[/C][C]0.40682[/C][C]0.81364[/C][C]0.59318[/C][/ROW]
[ROW][C]199[/C][C]0.366956[/C][C]0.733911[/C][C]0.633044[/C][/ROW]
[ROW][C]200[/C][C]0.486824[/C][C]0.973648[/C][C]0.513176[/C][/ROW]
[ROW][C]201[/C][C]0.452592[/C][C]0.905184[/C][C]0.547408[/C][/ROW]
[ROW][C]202[/C][C]0.64024[/C][C]0.71952[/C][C]0.35976[/C][/ROW]
[ROW][C]203[/C][C]0.602805[/C][C]0.79439[/C][C]0.397195[/C][/ROW]
[ROW][C]204[/C][C]0.563075[/C][C]0.87385[/C][C]0.436925[/C][/ROW]
[ROW][C]205[/C][C]0.523342[/C][C]0.953317[/C][C]0.476658[/C][/ROW]
[ROW][C]206[/C][C]0.484336[/C][C]0.968671[/C][C]0.515664[/C][/ROW]
[ROW][C]207[/C][C]0.441289[/C][C]0.882578[/C][C]0.558711[/C][/ROW]
[ROW][C]208[/C][C]0.397564[/C][C]0.795128[/C][C]0.602436[/C][/ROW]
[ROW][C]209[/C][C]0.371104[/C][C]0.742208[/C][C]0.628896[/C][/ROW]
[ROW][C]210[/C][C]0.331563[/C][C]0.663125[/C][C]0.668437[/C][/ROW]
[ROW][C]211[/C][C]0.293716[/C][C]0.587431[/C][C]0.706284[/C][/ROW]
[ROW][C]212[/C][C]0.264399[/C][C]0.528798[/C][C]0.735601[/C][/ROW]
[ROW][C]213[/C][C]0.316465[/C][C]0.632929[/C][C]0.683535[/C][/ROW]
[ROW][C]214[/C][C]0.294581[/C][C]0.589163[/C][C]0.705419[/C][/ROW]
[ROW][C]215[/C][C]0.255593[/C][C]0.511187[/C][C]0.744407[/C][/ROW]
[ROW][C]216[/C][C]0.223453[/C][C]0.446906[/C][C]0.776547[/C][/ROW]
[ROW][C]217[/C][C]0.199951[/C][C]0.399902[/C][C]0.800049[/C][/ROW]
[ROW][C]218[/C][C]0.227245[/C][C]0.45449[/C][C]0.772755[/C][/ROW]
[ROW][C]219[/C][C]0.200906[/C][C]0.401813[/C][C]0.799094[/C][/ROW]
[ROW][C]220[/C][C]0.177431[/C][C]0.354862[/C][C]0.822569[/C][/ROW]
[ROW][C]221[/C][C]0.149627[/C][C]0.299254[/C][C]0.850373[/C][/ROW]
[ROW][C]222[/C][C]0.142031[/C][C]0.284063[/C][C]0.857969[/C][/ROW]
[ROW][C]223[/C][C]0.115549[/C][C]0.231097[/C][C]0.884451[/C][/ROW]
[ROW][C]224[/C][C]0.0985654[/C][C]0.197131[/C][C]0.901435[/C][/ROW]
[ROW][C]225[/C][C]0.0782641[/C][C]0.156528[/C][C]0.921736[/C][/ROW]
[ROW][C]226[/C][C]0.086076[/C][C]0.172152[/C][C]0.913924[/C][/ROW]
[ROW][C]227[/C][C]0.0744587[/C][C]0.148917[/C][C]0.925541[/C][/ROW]
[ROW][C]228[/C][C]0.0578412[/C][C]0.115682[/C][C]0.942159[/C][/ROW]
[ROW][C]229[/C][C]0.0444389[/C][C]0.0888779[/C][C]0.955561[/C][/ROW]
[ROW][C]230[/C][C]0.0335506[/C][C]0.0671012[/C][C]0.966449[/C][/ROW]
[ROW][C]231[/C][C]0.0310206[/C][C]0.0620412[/C][C]0.968979[/C][/ROW]
[ROW][C]232[/C][C]0.0437673[/C][C]0.0875346[/C][C]0.956233[/C][/ROW]
[ROW][C]233[/C][C]0.0341441[/C][C]0.0682883[/C][C]0.965856[/C][/ROW]
[ROW][C]234[/C][C]0.117762[/C][C]0.235524[/C][C]0.882238[/C][/ROW]
[ROW][C]235[/C][C]0.0928548[/C][C]0.18571[/C][C]0.907145[/C][/ROW]
[ROW][C]236[/C][C]0.0858575[/C][C]0.171715[/C][C]0.914142[/C][/ROW]
[ROW][C]237[/C][C]0.0810443[/C][C]0.162089[/C][C]0.918956[/C][/ROW]
[ROW][C]238[/C][C]0.187996[/C][C]0.375991[/C][C]0.812004[/C][/ROW]
[ROW][C]239[/C][C]0.152691[/C][C]0.305382[/C][C]0.847309[/C][/ROW]
[ROW][C]240[/C][C]0.241837[/C][C]0.483674[/C][C]0.758163[/C][/ROW]
[ROW][C]241[/C][C]0.327539[/C][C]0.655078[/C][C]0.672461[/C][/ROW]
[ROW][C]242[/C][C]0.268394[/C][C]0.536788[/C][C]0.731606[/C][/ROW]
[ROW][C]243[/C][C]0.222123[/C][C]0.444245[/C][C]0.777877[/C][/ROW]
[ROW][C]244[/C][C]0.181202[/C][C]0.362405[/C][C]0.818798[/C][/ROW]
[ROW][C]245[/C][C]0.38718[/C][C]0.774361[/C][C]0.61282[/C][/ROW]
[ROW][C]246[/C][C]0.636785[/C][C]0.72643[/C][C]0.363215[/C][/ROW]
[ROW][C]247[/C][C]0.604104[/C][C]0.791792[/C][C]0.395896[/C][/ROW]
[ROW][C]248[/C][C]0.560683[/C][C]0.878633[/C][C]0.439317[/C][/ROW]
[ROW][C]249[/C][C]0.597896[/C][C]0.804208[/C][C]0.402104[/C][/ROW]
[ROW][C]250[/C][C]0.525462[/C][C]0.949075[/C][C]0.474538[/C][/ROW]
[ROW][C]251[/C][C]0.571188[/C][C]0.857624[/C][C]0.428812[/C][/ROW]
[ROW][C]252[/C][C]0.757101[/C][C]0.485798[/C][C]0.242899[/C][/ROW]
[ROW][C]253[/C][C]0.673122[/C][C]0.653756[/C][C]0.326878[/C][/ROW]
[ROW][C]254[/C][C]0.871743[/C][C]0.256514[/C][C]0.128257[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225809&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225809&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.1369360.2738710.863064
110.05464010.109280.94536
120.755130.489740.24487
130.8060790.3878420.193921
140.726770.546460.27323
150.6548890.6902220.345111
160.7058850.588230.294115
170.6288630.7422730.371137
180.5730840.8538320.426916
190.5182780.9634430.481722
200.5450710.9098590.454929
210.5781730.8436530.421827
220.517460.965080.48254
230.4687890.9375780.531211
240.3976060.7952120.602394
250.4463180.8926360.553682
260.6891850.621630.310815
270.6308550.7382910.369145
280.5970030.8059940.402997
290.5584660.8830690.441534
300.500460.999080.49954
310.4999540.9999080.500046
320.6354250.7291510.364575
330.6245980.7508050.375402
340.5957570.8084860.404243
350.5455860.9088270.454414
360.4951660.9903320.504834
370.4477960.8955930.552204
380.4149260.8298520.585074
390.5260480.9479030.473952
400.4732430.9464860.526757
410.4413730.8827460.558627
420.3902590.7805190.609741
430.3559520.7119030.644048
440.316520.6330410.68348
450.382530.7650610.61747
460.397470.7949390.60253
470.360020.720040.63998
480.3321550.6643110.667845
490.288880.5777610.71112
500.3024640.6049280.697536
510.3435890.6871770.656411
520.3086980.6173950.691302
530.2705030.5410060.729497
540.2449210.4898410.755079
550.2103190.4206380.789681
560.1962010.3924030.803799
570.2103690.4207380.789631
580.3145510.6291020.685449
590.2839140.5678290.716086
600.2478920.4957830.752108
610.2196650.439330.780335
620.2117470.4234940.788253
630.1861770.3723530.813823
640.1843310.3686630.815669
650.1582320.3164640.841768
660.1373920.2747850.862608
670.1166490.2332970.883351
680.125170.250340.87483
690.1259250.251850.874075
700.1067830.2135660.893217
710.1122970.2245950.887703
720.1306920.2613840.869308
730.1275320.2550630.872468
740.1072980.2145960.892702
750.09294440.1858890.907056
760.1262050.2524090.873795
770.108680.2173590.89132
780.09185930.1837190.908141
790.1195290.2390580.880471
800.1431240.2862490.856876
810.1363670.2727330.863633
820.1179070.2358140.882093
830.1116330.2232650.888367
840.1061030.2122060.893897
850.09212660.1842530.907873
860.08144120.1628820.918559
870.071830.143660.92817
880.08576280.1715260.914237
890.07149180.1429840.928508
900.0758210.1516420.924179
910.07074710.1414940.929253
920.0633590.1267180.936641
930.05303770.1060750.946962
940.05507870.1101570.944921
950.05416360.1083270.945836
960.04992210.09984430.950078
970.04236590.08473180.957634
980.03735780.07471560.962642
990.03745130.07490270.962549
1000.03441680.06883360.965583
1010.03072650.0614530.969273
1020.02542160.05084330.974578
1030.0210670.04213390.978933
1040.02142050.04284090.97858
1050.05108880.1021780.948911
1060.04785440.09570890.952146
1070.05890930.1178190.941091
1080.0512240.1024480.948776
1090.08594390.1718880.914056
1100.1021190.2042380.897881
1110.09800430.1960090.901996
1120.1308650.261730.869135
1130.1177090.2354180.882291
1140.113480.226960.88652
1150.1082830.2165650.891717
1160.1056230.2112470.894377
1170.1002170.2004340.899783
1180.08750680.1750140.912493
1190.0820340.1640680.917966
1200.0726840.1453680.927316
1210.06350360.1270070.936496
1220.05741620.1148320.942584
1230.04866960.09733930.95133
1240.04675910.09351830.953241
1250.04443460.08886920.955565
1260.05497570.1099510.945024
1270.1002130.2004250.899787
1280.09637180.1927440.903628
1290.08496060.1699210.915039
1300.07834990.15670.92165
1310.08606020.172120.91394
1320.09193390.1838680.908066
1330.1121360.2242730.887864
1340.09836080.1967220.901639
1350.08459550.1691910.915405
1360.07351920.1470380.926481
1370.06232910.1246580.937671
1380.06471190.1294240.935288
1390.05500350.1100070.944996
1400.05404520.108090.945955
1410.05202950.1040590.947971
1420.07506430.1501290.924936
1430.09040130.1808030.909599
1440.08353960.1670790.91646
1450.1466630.2933270.853337
1460.1346690.2693390.865331
1470.1198780.2397570.880122
1480.1052010.2104030.894799
1490.09635230.1927050.903648
1500.08487740.1697550.915123
1510.1347530.2695060.865247
1520.1258160.2516320.874184
1530.1135860.2271730.886414
1540.124090.248180.87591
1550.1071080.2142170.892892
1560.1069320.2138630.893068
1570.1095660.2191320.890434
1580.1024270.2048540.897573
1590.0892620.1785240.910738
1600.09502140.1900430.904979
1610.08161890.1632380.918381
1620.07721260.1544250.922787
1630.06684060.1336810.933159
1640.08168270.1633650.918317
1650.07402020.148040.92598
1660.1352330.2704660.864767
1670.1361540.2723090.863846
1680.1324950.2649910.867505
1690.1191590.2383180.880841
1700.2355460.4710920.764454
1710.269260.538520.73074
1720.2400320.4800640.759968
1730.3278220.6556440.672178
1740.2946480.5892950.705352
1750.3481610.6963220.651839
1760.3342050.668410.665795
1770.3413990.6827990.658601
1780.314540.629080.68546
1790.2888040.5776080.711196
1800.2741230.5482460.725877
1810.2472040.4944090.752796
1820.2448650.4897310.755135
1830.2547930.5095850.745207
1840.3039510.6079020.696049
1850.5718390.8563210.428161
1860.5678550.864290.432145
1870.5528530.8942950.447147
1880.6649420.6701160.335058
1890.648230.7035410.35177
1900.6395510.7208980.360449
1910.6269930.7460140.373007
1920.5914520.8170960.408548
1930.5575950.8848110.442405
1940.5166950.9666090.483305
1950.4788330.9576670.521167
1960.4422790.8845580.557721
1970.4268850.8537690.573115
1980.406820.813640.59318
1990.3669560.7339110.633044
2000.4868240.9736480.513176
2010.4525920.9051840.547408
2020.640240.719520.35976
2030.6028050.794390.397195
2040.5630750.873850.436925
2050.5233420.9533170.476658
2060.4843360.9686710.515664
2070.4412890.8825780.558711
2080.3975640.7951280.602436
2090.3711040.7422080.628896
2100.3315630.6631250.668437
2110.2937160.5874310.706284
2120.2643990.5287980.735601
2130.3164650.6329290.683535
2140.2945810.5891630.705419
2150.2555930.5111870.744407
2160.2234530.4469060.776547
2170.1999510.3999020.800049
2180.2272450.454490.772755
2190.2009060.4018130.799094
2200.1774310.3548620.822569
2210.1496270.2992540.850373
2220.1420310.2840630.857969
2230.1155490.2310970.884451
2240.09856540.1971310.901435
2250.07826410.1565280.921736
2260.0860760.1721520.913924
2270.07445870.1489170.925541
2280.05784120.1156820.942159
2290.04443890.08887790.955561
2300.03355060.06710120.966449
2310.03102060.06204120.968979
2320.04376730.08753460.956233
2330.03414410.06828830.965856
2340.1177620.2355240.882238
2350.09285480.185710.907145
2360.08585750.1717150.914142
2370.08104430.1620890.918956
2380.1879960.3759910.812004
2390.1526910.3053820.847309
2400.2418370.4836740.758163
2410.3275390.6550780.672461
2420.2683940.5367880.731606
2430.2221230.4442450.777877
2440.1812020.3624050.818798
2450.387180.7743610.61282
2460.6367850.726430.363215
2470.6041040.7917920.395896
2480.5606830.8786330.439317
2490.5978960.8042080.402104
2500.5254620.9490750.474538
2510.5711880.8576240.428812
2520.7571010.4857980.242899
2530.6731220.6537560.326878
2540.8717430.2565140.128257






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00816327OK
10% type I error level180.0734694OK

\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 & 2 & 0.00816327 & OK \tabularnewline
10% type I error level & 18 & 0.0734694 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225809&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]2[/C][C]0.00816327[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]18[/C][C]0.0734694[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225809&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225809&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 level20.00816327OK
10% type I error level180.0734694OK


Figures (Output of Computation)

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

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