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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationTue, 11 Nov 2014 19:50:34 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/11/t1415735473bdxmzem6epfja3m.htm/, Retrieved Fri, 17 May 2024 03:04:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=253721, Retrieved Fri, 17 May 2024 03:04:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact73

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [ws7 comp1] [2014-11-11 19:50:34] [5a1a6480a94cc63423bd5720e139a09a] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253721&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253721&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253721&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Separate[t] = + 15.3799 + 0.413425Connected[t] + 0.128023Learning[t] + 0.120964Software[t] + 0.0273196Happiness[t] + 0.00988595Depression[t] + 0.00872567Sport1[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Separate[t] =  +  15.3799 +  0.413425Connected[t] +  0.128023Learning[t] +  0.120964Software[t] +  0.0273196Happiness[t] +  0.00988595Depression[t] +  0.00872567Sport1[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253721&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Separate[t] =  +  15.3799 +  0.413425Connected[t] +  0.128023Learning[t] +  0.120964Software[t] +  0.0273196Happiness[t] +  0.00988595Depression[t] +  0.00872567Sport1[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253721&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253721&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Separate[t] = + 15.3799 + 0.413425Connected[t] + 0.128023Learning[t] + 0.120964Software[t] + 0.0273196Happiness[t] + 0.00988595Depression[t] + 0.00872567Sport1[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.37993.196594.8112.55817e-061.27908e-06
Connected0.4134250.05493967.5258.87662e-134.43831e-13
Learning0.1280230.1087561.1770.240220.12011
Software0.1209640.1118731.0810.2805940.140297
Happiness0.02731960.1016760.26870.7883810.394191
Depression0.009885950.07395670.13370.8937660.446883
Sport10.008725670.02090990.41730.6768080.338404

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 15.3799 & 3.19659 & 4.811 & 2.55817e-06 & 1.27908e-06 \tabularnewline
Connected & 0.413425 & 0.0549396 & 7.525 & 8.87662e-13 & 4.43831e-13 \tabularnewline
Learning & 0.128023 & 0.108756 & 1.177 & 0.24022 & 0.12011 \tabularnewline
Software & 0.120964 & 0.111873 & 1.081 & 0.280594 & 0.140297 \tabularnewline
Happiness & 0.0273196 & 0.101676 & 0.2687 & 0.788381 & 0.394191 \tabularnewline
Depression & 0.00988595 & 0.0739567 & 0.1337 & 0.893766 & 0.446883 \tabularnewline
Sport1 & 0.00872567 & 0.0209099 & 0.4173 & 0.676808 & 0.338404 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253721&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]15.3799[/C][C]3.19659[/C][C]4.811[/C][C]2.55817e-06[/C][C]1.27908e-06[/C][/ROW]
[ROW][C]Connected[/C][C]0.413425[/C][C]0.0549396[/C][C]7.525[/C][C]8.87662e-13[/C][C]4.43831e-13[/C][/ROW]
[ROW][C]Learning[/C][C]0.128023[/C][C]0.108756[/C][C]1.177[/C][C]0.24022[/C][C]0.12011[/C][/ROW]
[ROW][C]Software[/C][C]0.120964[/C][C]0.111873[/C][C]1.081[/C][C]0.280594[/C][C]0.140297[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0273196[/C][C]0.101676[/C][C]0.2687[/C][C]0.788381[/C][C]0.394191[/C][/ROW]
[ROW][C]Depression[/C][C]0.00988595[/C][C]0.0739567[/C][C]0.1337[/C][C]0.893766[/C][C]0.446883[/C][/ROW]
[ROW][C]Sport1[/C][C]0.00872567[/C][C]0.0209099[/C][C]0.4173[/C][C]0.676808[/C][C]0.338404[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253721&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253721&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.37993.196594.8112.55817e-061.27908e-06
Connected0.4134250.05493967.5258.87662e-134.43831e-13
Learning0.1280230.1087561.1770.240220.12011
Software0.1209640.1118731.0810.2805940.140297
Happiness0.02731960.1016760.26870.7883810.394191
Depression0.009885950.07395670.13370.8937660.446883
Sport10.008725670.02090990.41730.6768080.338404






Multiple Linear Regression - Regression Statistics
Multiple R0.479225
R-squared0.229657
Adjusted R-squared0.211672
F-TEST (value)12.7696
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value1.28941e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.28873
Sum Squared Residuals2779.65

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.479225 \tabularnewline
R-squared & 0.229657 \tabularnewline
Adjusted R-squared & 0.211672 \tabularnewline
F-TEST (value) & 12.7696 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 257 \tabularnewline
p-value & 1.28941e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.28873 \tabularnewline
Sum Squared Residuals & 2779.65 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253721&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.479225[/C][/ROW]
[ROW][C]R-squared[/C][C]0.229657[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.211672[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]12.7696[/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]1.28941e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.28873[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2779.65[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253721&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253721&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 R0.479225
R-squared0.229657
Adjusted R-squared0.211672
F-TEST (value)12.7696
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value1.28941e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.28873
Sum Squared Residuals2779.65






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
13836.40971.59026
23236.2072-4.20716
33533.04431.95566
43331.87331.12673
53734.10912.89095
62934.0147-5.01468
73136.4499-5.44989
83634.23941.76055
93534.66140.338577
103834.88713.11291
113135.6007-4.60066
123434.8325-0.832464
133535.5961-0.596073
143835.92912.07087
153734.36352.6365
163333.0084-0.00835932
173234.5685-2.56847
183836.44311.5569
193836.17831.82175
203233.1724-1.17241
213333.15-0.150016
223132.7283-1.72826
233836.48071.51928
243935.01053.98955
253236.455-4.455
263237.1121-5.11213
273534.73020.269801
283733.76963.23042
293333.7516-0.751641
303333.4519-0.451944
313132.7921-1.79211
323230.0211.97903
333134.8614-3.86138
343734.18782.81224
353033.8369-3.83691
363331.87221.12782
373130.73140.268581
383334.655-1.65502
393131.8537-0.853656
403334.1638-1.16385
413235.0791-3.07908
423333.9102-0.910162
433236.4523-4.45234
443333.7717-0.77169
452835.2126-7.2126
463534.55880.441196
473935.52083.47918
483433.44680.553181
493834.90063.09942
503235.4522-3.45225
513833.51564.48443
523032.7169-2.71694
533332.62550.374498
543834.06453.93554
553231.35280.6472
563534.4110.588999
573436.2147-2.21472
583431.95252.04747
593634.99121.00878
603434.1947-0.194685
612831.0444-3.04439
623435.7356-1.73563
633534.29540.704604
643532.29362.70641
653133.9458-2.94576
663734.67872.32133
673535.3056-0.305564
682732.5011-5.50109
694035.57934.42067
703734.52.50004
713634.43361.56642
723832.37565.62443
733934.67934.32067
744136.19874.80133
752734.1331-7.13312
763035.9822-5.98225
773735.50131.49875
783133.9406-2.94059
793131.2818-0.281833
802735.0919-8.09186
813633.73072.26929
823734.4682.53202
833335.2412-2.24124
843433.01710.982898
853133.4638-2.46378
863935.16383.83624
873433.6260.373981
883231.84380.156229
893333.4143-0.414343
903632.05093.94907
913235.2287-3.22866
924134.55996.44012
932833.2277-5.22766
943031.6619-1.66185
953636.0054-0.00537722
963535.3856-0.385588
973134.1586-3.15862
983435.4565-1.4565
993632.78323.21675
1003636.0583-0.05834
1013535.1786-0.178562
1023735.93551.06447
1032832.8456-4.84558
1043933.65925.34083
1053236.0598-4.0598
1063535.927-0.927001
1073937.01771.98226
1083534.53480.465176
1094236.4525.54798
1103432.57241.42755
1113333.0324-0.0324239
1124133.34827.65177
1133332.46670.533279
1143434.6961-0.696055
1153235.8399-3.83993
1164033.37986.62018
1174033.2926.70803
1183533.09131.90867
1193635.9060.0939582
1203732.96514.03488
1212733.001-6.00098
1223935.5013.49898
1233835.57052.4295
1243134.9116-3.91157
1253333.2121-0.212112
1263235.9623-3.96227
1273938.28660.713429
1283633.36652.63348
1293333.8832-0.883194
1303332.95090.0490895
1313230.58611.4139
1323736.11350.886509
1333030.5345-0.534484
1343835.09462.90538
1352933.2986-4.29859
1362230.7078-8.70783
1373533.75791.24213
1383531.33043.6696
1393433.43070.569277
1403531.76883.23116
1413432.60541.3946
1423732.10014.89988
1433533.0251.975
1442332.7753-9.77533
1453135.4873-4.48726
1462733.7053-6.70532
1473634.33161.66838
1483133.2004-2.20042
1493233.6734-1.67341
1503934.51444.48557
1513737.4492-0.449153
1523833.7194.28102
1533933.69865.30138
1543434.8858-0.885844
1553132.4845-1.48455
1563235.2287-3.22866
1573732.12254.87749
1583633.36652.63348
1593233.9924-1.99239
1603832.35225.6478
1613633.18372.81626
1622630.5026-4.50264
1632631.9277-5.9277
1643336.3103-3.31026
1653933.64575.35429
1663028.54911.4509
1673332.08730.912737
1682530.1007-5.10069
1693833.67184.32825
1703731.10315.89691
1713133.7958-2.79585
1723734.94712.05289
1733536.1213-1.12133
1742530.4062-5.40619
1752834.4449-6.4449
1763532.98522.01484
1773334.178-1.17799
1783031.5154-1.51543
1793132.3186-1.31861
1803734.79962.2004
1813634.72551.27448
1823033.0125-3.01254
1833633.57232.42771
1843235.6413-3.64133
1852828.2734-0.27342
1863633.31562.68444
1873434.9368-0.936754
1883135.174-4.17404
1892830.1755-2.17552
1903631.66294.33706
1913632.6143.38602
1924035.72574.27427
1933331.66881.3312
1943734.22842.77159
1953232.6599-0.659863
1963835.10582.89422
1973133.833-2.83301
1983733.81273.18726
1993332.85130.148717
2003230.78441.21559
2013032.2986-2.29857
2023029.43450.565464
2033133.1609-2.16086
2043233.3889-1.38892
2053433.05770.942251
2063633.87132.12871
2073734.47152.52848
2083634.38881.61117
2093333.9854-0.985426
2103333.855-0.855016
2113333.3966-0.396553
2124436.5977.40303
2133933.0985.90198
2143231.76170.238274
2153534.40290.597111
2162531.0632-6.06322
2173533.84481.15524
2183435.7308-1.73075
2193533.86351.1365
2203934.89884.1012
2213334.0479-1.04792
2223635.15380.846174
2233233.4643-1.46432
2243231.9480.0519797
2253632.97443.02564
2263631.5764.42398
2273232.297-0.29702
2283432.90011.09991
2293332.95510.0449156
2303533.10111.89889
2313032.947-2.94704
2323832.50145.49856
2333432.38851.61151
2343337.4797-4.47968
2353233.4646-1.4646
2363133.9308-2.93079
2373033.0735-3.07352
2382734.299-7.299
2393131.8793-0.87933
2403033.851-3.85098
2413230.24091.75911
2423533.58551.41452
2432829.591-1.591
2443333.3017-0.301741
2453135.0703-4.07029
2463530.97354.0265
2473532.58732.41273
2483233.6259-1.62586
2492126.6985-5.69849
2502027.6352-7.63522
2513431.612.38995
2523232.3537-0.353698
2533433.60870.391339
2543233.2719-1.27187
2553334.5118-1.51176
2563333.62-0.62
2573734.45762.5424
2583231.92090.0790981
2593434.8142-0.814211
2603031.8012-1.80125
2613030.8529-0.852851
2623833.41794.58208
2633635.12160.878401
2643231.37960.620445

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 38 & 36.4097 & 1.59026 \tabularnewline
2 & 32 & 36.2072 & -4.20716 \tabularnewline
3 & 35 & 33.0443 & 1.95566 \tabularnewline
4 & 33 & 31.8733 & 1.12673 \tabularnewline
5 & 37 & 34.1091 & 2.89095 \tabularnewline
6 & 29 & 34.0147 & -5.01468 \tabularnewline
7 & 31 & 36.4499 & -5.44989 \tabularnewline
8 & 36 & 34.2394 & 1.76055 \tabularnewline
9 & 35 & 34.6614 & 0.338577 \tabularnewline
10 & 38 & 34.8871 & 3.11291 \tabularnewline
11 & 31 & 35.6007 & -4.60066 \tabularnewline
12 & 34 & 34.8325 & -0.832464 \tabularnewline
13 & 35 & 35.5961 & -0.596073 \tabularnewline
14 & 38 & 35.9291 & 2.07087 \tabularnewline
15 & 37 & 34.3635 & 2.6365 \tabularnewline
16 & 33 & 33.0084 & -0.00835932 \tabularnewline
17 & 32 & 34.5685 & -2.56847 \tabularnewline
18 & 38 & 36.4431 & 1.5569 \tabularnewline
19 & 38 & 36.1783 & 1.82175 \tabularnewline
20 & 32 & 33.1724 & -1.17241 \tabularnewline
21 & 33 & 33.15 & -0.150016 \tabularnewline
22 & 31 & 32.7283 & -1.72826 \tabularnewline
23 & 38 & 36.4807 & 1.51928 \tabularnewline
24 & 39 & 35.0105 & 3.98955 \tabularnewline
25 & 32 & 36.455 & -4.455 \tabularnewline
26 & 32 & 37.1121 & -5.11213 \tabularnewline
27 & 35 & 34.7302 & 0.269801 \tabularnewline
28 & 37 & 33.7696 & 3.23042 \tabularnewline
29 & 33 & 33.7516 & -0.751641 \tabularnewline
30 & 33 & 33.4519 & -0.451944 \tabularnewline
31 & 31 & 32.7921 & -1.79211 \tabularnewline
32 & 32 & 30.021 & 1.97903 \tabularnewline
33 & 31 & 34.8614 & -3.86138 \tabularnewline
34 & 37 & 34.1878 & 2.81224 \tabularnewline
35 & 30 & 33.8369 & -3.83691 \tabularnewline
36 & 33 & 31.8722 & 1.12782 \tabularnewline
37 & 31 & 30.7314 & 0.268581 \tabularnewline
38 & 33 & 34.655 & -1.65502 \tabularnewline
39 & 31 & 31.8537 & -0.853656 \tabularnewline
40 & 33 & 34.1638 & -1.16385 \tabularnewline
41 & 32 & 35.0791 & -3.07908 \tabularnewline
42 & 33 & 33.9102 & -0.910162 \tabularnewline
43 & 32 & 36.4523 & -4.45234 \tabularnewline
44 & 33 & 33.7717 & -0.77169 \tabularnewline
45 & 28 & 35.2126 & -7.2126 \tabularnewline
46 & 35 & 34.5588 & 0.441196 \tabularnewline
47 & 39 & 35.5208 & 3.47918 \tabularnewline
48 & 34 & 33.4468 & 0.553181 \tabularnewline
49 & 38 & 34.9006 & 3.09942 \tabularnewline
50 & 32 & 35.4522 & -3.45225 \tabularnewline
51 & 38 & 33.5156 & 4.48443 \tabularnewline
52 & 30 & 32.7169 & -2.71694 \tabularnewline
53 & 33 & 32.6255 & 0.374498 \tabularnewline
54 & 38 & 34.0645 & 3.93554 \tabularnewline
55 & 32 & 31.3528 & 0.6472 \tabularnewline
56 & 35 & 34.411 & 0.588999 \tabularnewline
57 & 34 & 36.2147 & -2.21472 \tabularnewline
58 & 34 & 31.9525 & 2.04747 \tabularnewline
59 & 36 & 34.9912 & 1.00878 \tabularnewline
60 & 34 & 34.1947 & -0.194685 \tabularnewline
61 & 28 & 31.0444 & -3.04439 \tabularnewline
62 & 34 & 35.7356 & -1.73563 \tabularnewline
63 & 35 & 34.2954 & 0.704604 \tabularnewline
64 & 35 & 32.2936 & 2.70641 \tabularnewline
65 & 31 & 33.9458 & -2.94576 \tabularnewline
66 & 37 & 34.6787 & 2.32133 \tabularnewline
67 & 35 & 35.3056 & -0.305564 \tabularnewline
68 & 27 & 32.5011 & -5.50109 \tabularnewline
69 & 40 & 35.5793 & 4.42067 \tabularnewline
70 & 37 & 34.5 & 2.50004 \tabularnewline
71 & 36 & 34.4336 & 1.56642 \tabularnewline
72 & 38 & 32.3756 & 5.62443 \tabularnewline
73 & 39 & 34.6793 & 4.32067 \tabularnewline
74 & 41 & 36.1987 & 4.80133 \tabularnewline
75 & 27 & 34.1331 & -7.13312 \tabularnewline
76 & 30 & 35.9822 & -5.98225 \tabularnewline
77 & 37 & 35.5013 & 1.49875 \tabularnewline
78 & 31 & 33.9406 & -2.94059 \tabularnewline
79 & 31 & 31.2818 & -0.281833 \tabularnewline
80 & 27 & 35.0919 & -8.09186 \tabularnewline
81 & 36 & 33.7307 & 2.26929 \tabularnewline
82 & 37 & 34.468 & 2.53202 \tabularnewline
83 & 33 & 35.2412 & -2.24124 \tabularnewline
84 & 34 & 33.0171 & 0.982898 \tabularnewline
85 & 31 & 33.4638 & -2.46378 \tabularnewline
86 & 39 & 35.1638 & 3.83624 \tabularnewline
87 & 34 & 33.626 & 0.373981 \tabularnewline
88 & 32 & 31.8438 & 0.156229 \tabularnewline
89 & 33 & 33.4143 & -0.414343 \tabularnewline
90 & 36 & 32.0509 & 3.94907 \tabularnewline
91 & 32 & 35.2287 & -3.22866 \tabularnewline
92 & 41 & 34.5599 & 6.44012 \tabularnewline
93 & 28 & 33.2277 & -5.22766 \tabularnewline
94 & 30 & 31.6619 & -1.66185 \tabularnewline
95 & 36 & 36.0054 & -0.00537722 \tabularnewline
96 & 35 & 35.3856 & -0.385588 \tabularnewline
97 & 31 & 34.1586 & -3.15862 \tabularnewline
98 & 34 & 35.4565 & -1.4565 \tabularnewline
99 & 36 & 32.7832 & 3.21675 \tabularnewline
100 & 36 & 36.0583 & -0.05834 \tabularnewline
101 & 35 & 35.1786 & -0.178562 \tabularnewline
102 & 37 & 35.9355 & 1.06447 \tabularnewline
103 & 28 & 32.8456 & -4.84558 \tabularnewline
104 & 39 & 33.6592 & 5.34083 \tabularnewline
105 & 32 & 36.0598 & -4.0598 \tabularnewline
106 & 35 & 35.927 & -0.927001 \tabularnewline
107 & 39 & 37.0177 & 1.98226 \tabularnewline
108 & 35 & 34.5348 & 0.465176 \tabularnewline
109 & 42 & 36.452 & 5.54798 \tabularnewline
110 & 34 & 32.5724 & 1.42755 \tabularnewline
111 & 33 & 33.0324 & -0.0324239 \tabularnewline
112 & 41 & 33.3482 & 7.65177 \tabularnewline
113 & 33 & 32.4667 & 0.533279 \tabularnewline
114 & 34 & 34.6961 & -0.696055 \tabularnewline
115 & 32 & 35.8399 & -3.83993 \tabularnewline
116 & 40 & 33.3798 & 6.62018 \tabularnewline
117 & 40 & 33.292 & 6.70803 \tabularnewline
118 & 35 & 33.0913 & 1.90867 \tabularnewline
119 & 36 & 35.906 & 0.0939582 \tabularnewline
120 & 37 & 32.9651 & 4.03488 \tabularnewline
121 & 27 & 33.001 & -6.00098 \tabularnewline
122 & 39 & 35.501 & 3.49898 \tabularnewline
123 & 38 & 35.5705 & 2.4295 \tabularnewline
124 & 31 & 34.9116 & -3.91157 \tabularnewline
125 & 33 & 33.2121 & -0.212112 \tabularnewline
126 & 32 & 35.9623 & -3.96227 \tabularnewline
127 & 39 & 38.2866 & 0.713429 \tabularnewline
128 & 36 & 33.3665 & 2.63348 \tabularnewline
129 & 33 & 33.8832 & -0.883194 \tabularnewline
130 & 33 & 32.9509 & 0.0490895 \tabularnewline
131 & 32 & 30.5861 & 1.4139 \tabularnewline
132 & 37 & 36.1135 & 0.886509 \tabularnewline
133 & 30 & 30.5345 & -0.534484 \tabularnewline
134 & 38 & 35.0946 & 2.90538 \tabularnewline
135 & 29 & 33.2986 & -4.29859 \tabularnewline
136 & 22 & 30.7078 & -8.70783 \tabularnewline
137 & 35 & 33.7579 & 1.24213 \tabularnewline
138 & 35 & 31.3304 & 3.6696 \tabularnewline
139 & 34 & 33.4307 & 0.569277 \tabularnewline
140 & 35 & 31.7688 & 3.23116 \tabularnewline
141 & 34 & 32.6054 & 1.3946 \tabularnewline
142 & 37 & 32.1001 & 4.89988 \tabularnewline
143 & 35 & 33.025 & 1.975 \tabularnewline
144 & 23 & 32.7753 & -9.77533 \tabularnewline
145 & 31 & 35.4873 & -4.48726 \tabularnewline
146 & 27 & 33.7053 & -6.70532 \tabularnewline
147 & 36 & 34.3316 & 1.66838 \tabularnewline
148 & 31 & 33.2004 & -2.20042 \tabularnewline
149 & 32 & 33.6734 & -1.67341 \tabularnewline
150 & 39 & 34.5144 & 4.48557 \tabularnewline
151 & 37 & 37.4492 & -0.449153 \tabularnewline
152 & 38 & 33.719 & 4.28102 \tabularnewline
153 & 39 & 33.6986 & 5.30138 \tabularnewline
154 & 34 & 34.8858 & -0.885844 \tabularnewline
155 & 31 & 32.4845 & -1.48455 \tabularnewline
156 & 32 & 35.2287 & -3.22866 \tabularnewline
157 & 37 & 32.1225 & 4.87749 \tabularnewline
158 & 36 & 33.3665 & 2.63348 \tabularnewline
159 & 32 & 33.9924 & -1.99239 \tabularnewline
160 & 38 & 32.3522 & 5.6478 \tabularnewline
161 & 36 & 33.1837 & 2.81626 \tabularnewline
162 & 26 & 30.5026 & -4.50264 \tabularnewline
163 & 26 & 31.9277 & -5.9277 \tabularnewline
164 & 33 & 36.3103 & -3.31026 \tabularnewline
165 & 39 & 33.6457 & 5.35429 \tabularnewline
166 & 30 & 28.5491 & 1.4509 \tabularnewline
167 & 33 & 32.0873 & 0.912737 \tabularnewline
168 & 25 & 30.1007 & -5.10069 \tabularnewline
169 & 38 & 33.6718 & 4.32825 \tabularnewline
170 & 37 & 31.1031 & 5.89691 \tabularnewline
171 & 31 & 33.7958 & -2.79585 \tabularnewline
172 & 37 & 34.9471 & 2.05289 \tabularnewline
173 & 35 & 36.1213 & -1.12133 \tabularnewline
174 & 25 & 30.4062 & -5.40619 \tabularnewline
175 & 28 & 34.4449 & -6.4449 \tabularnewline
176 & 35 & 32.9852 & 2.01484 \tabularnewline
177 & 33 & 34.178 & -1.17799 \tabularnewline
178 & 30 & 31.5154 & -1.51543 \tabularnewline
179 & 31 & 32.3186 & -1.31861 \tabularnewline
180 & 37 & 34.7996 & 2.2004 \tabularnewline
181 & 36 & 34.7255 & 1.27448 \tabularnewline
182 & 30 & 33.0125 & -3.01254 \tabularnewline
183 & 36 & 33.5723 & 2.42771 \tabularnewline
184 & 32 & 35.6413 & -3.64133 \tabularnewline
185 & 28 & 28.2734 & -0.27342 \tabularnewline
186 & 36 & 33.3156 & 2.68444 \tabularnewline
187 & 34 & 34.9368 & -0.936754 \tabularnewline
188 & 31 & 35.174 & -4.17404 \tabularnewline
189 & 28 & 30.1755 & -2.17552 \tabularnewline
190 & 36 & 31.6629 & 4.33706 \tabularnewline
191 & 36 & 32.614 & 3.38602 \tabularnewline
192 & 40 & 35.7257 & 4.27427 \tabularnewline
193 & 33 & 31.6688 & 1.3312 \tabularnewline
194 & 37 & 34.2284 & 2.77159 \tabularnewline
195 & 32 & 32.6599 & -0.659863 \tabularnewline
196 & 38 & 35.1058 & 2.89422 \tabularnewline
197 & 31 & 33.833 & -2.83301 \tabularnewline
198 & 37 & 33.8127 & 3.18726 \tabularnewline
199 & 33 & 32.8513 & 0.148717 \tabularnewline
200 & 32 & 30.7844 & 1.21559 \tabularnewline
201 & 30 & 32.2986 & -2.29857 \tabularnewline
202 & 30 & 29.4345 & 0.565464 \tabularnewline
203 & 31 & 33.1609 & -2.16086 \tabularnewline
204 & 32 & 33.3889 & -1.38892 \tabularnewline
205 & 34 & 33.0577 & 0.942251 \tabularnewline
206 & 36 & 33.8713 & 2.12871 \tabularnewline
207 & 37 & 34.4715 & 2.52848 \tabularnewline
208 & 36 & 34.3888 & 1.61117 \tabularnewline
209 & 33 & 33.9854 & -0.985426 \tabularnewline
210 & 33 & 33.855 & -0.855016 \tabularnewline
211 & 33 & 33.3966 & -0.396553 \tabularnewline
212 & 44 & 36.597 & 7.40303 \tabularnewline
213 & 39 & 33.098 & 5.90198 \tabularnewline
214 & 32 & 31.7617 & 0.238274 \tabularnewline
215 & 35 & 34.4029 & 0.597111 \tabularnewline
216 & 25 & 31.0632 & -6.06322 \tabularnewline
217 & 35 & 33.8448 & 1.15524 \tabularnewline
218 & 34 & 35.7308 & -1.73075 \tabularnewline
219 & 35 & 33.8635 & 1.1365 \tabularnewline
220 & 39 & 34.8988 & 4.1012 \tabularnewline
221 & 33 & 34.0479 & -1.04792 \tabularnewline
222 & 36 & 35.1538 & 0.846174 \tabularnewline
223 & 32 & 33.4643 & -1.46432 \tabularnewline
224 & 32 & 31.948 & 0.0519797 \tabularnewline
225 & 36 & 32.9744 & 3.02564 \tabularnewline
226 & 36 & 31.576 & 4.42398 \tabularnewline
227 & 32 & 32.297 & -0.29702 \tabularnewline
228 & 34 & 32.9001 & 1.09991 \tabularnewline
229 & 33 & 32.9551 & 0.0449156 \tabularnewline
230 & 35 & 33.1011 & 1.89889 \tabularnewline
231 & 30 & 32.947 & -2.94704 \tabularnewline
232 & 38 & 32.5014 & 5.49856 \tabularnewline
233 & 34 & 32.3885 & 1.61151 \tabularnewline
234 & 33 & 37.4797 & -4.47968 \tabularnewline
235 & 32 & 33.4646 & -1.4646 \tabularnewline
236 & 31 & 33.9308 & -2.93079 \tabularnewline
237 & 30 & 33.0735 & -3.07352 \tabularnewline
238 & 27 & 34.299 & -7.299 \tabularnewline
239 & 31 & 31.8793 & -0.87933 \tabularnewline
240 & 30 & 33.851 & -3.85098 \tabularnewline
241 & 32 & 30.2409 & 1.75911 \tabularnewline
242 & 35 & 33.5855 & 1.41452 \tabularnewline
243 & 28 & 29.591 & -1.591 \tabularnewline
244 & 33 & 33.3017 & -0.301741 \tabularnewline
245 & 31 & 35.0703 & -4.07029 \tabularnewline
246 & 35 & 30.9735 & 4.0265 \tabularnewline
247 & 35 & 32.5873 & 2.41273 \tabularnewline
248 & 32 & 33.6259 & -1.62586 \tabularnewline
249 & 21 & 26.6985 & -5.69849 \tabularnewline
250 & 20 & 27.6352 & -7.63522 \tabularnewline
251 & 34 & 31.61 & 2.38995 \tabularnewline
252 & 32 & 32.3537 & -0.353698 \tabularnewline
253 & 34 & 33.6087 & 0.391339 \tabularnewline
254 & 32 & 33.2719 & -1.27187 \tabularnewline
255 & 33 & 34.5118 & -1.51176 \tabularnewline
256 & 33 & 33.62 & -0.62 \tabularnewline
257 & 37 & 34.4576 & 2.5424 \tabularnewline
258 & 32 & 31.9209 & 0.0790981 \tabularnewline
259 & 34 & 34.8142 & -0.814211 \tabularnewline
260 & 30 & 31.8012 & -1.80125 \tabularnewline
261 & 30 & 30.8529 & -0.852851 \tabularnewline
262 & 38 & 33.4179 & 4.58208 \tabularnewline
263 & 36 & 35.1216 & 0.878401 \tabularnewline
264 & 32 & 31.3796 & 0.620445 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253721&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]38[/C][C]36.4097[/C][C]1.59026[/C][/ROW]
[ROW][C]2[/C][C]32[/C][C]36.2072[/C][C]-4.20716[/C][/ROW]
[ROW][C]3[/C][C]35[/C][C]33.0443[/C][C]1.95566[/C][/ROW]
[ROW][C]4[/C][C]33[/C][C]31.8733[/C][C]1.12673[/C][/ROW]
[ROW][C]5[/C][C]37[/C][C]34.1091[/C][C]2.89095[/C][/ROW]
[ROW][C]6[/C][C]29[/C][C]34.0147[/C][C]-5.01468[/C][/ROW]
[ROW][C]7[/C][C]31[/C][C]36.4499[/C][C]-5.44989[/C][/ROW]
[ROW][C]8[/C][C]36[/C][C]34.2394[/C][C]1.76055[/C][/ROW]
[ROW][C]9[/C][C]35[/C][C]34.6614[/C][C]0.338577[/C][/ROW]
[ROW][C]10[/C][C]38[/C][C]34.8871[/C][C]3.11291[/C][/ROW]
[ROW][C]11[/C][C]31[/C][C]35.6007[/C][C]-4.60066[/C][/ROW]
[ROW][C]12[/C][C]34[/C][C]34.8325[/C][C]-0.832464[/C][/ROW]
[ROW][C]13[/C][C]35[/C][C]35.5961[/C][C]-0.596073[/C][/ROW]
[ROW][C]14[/C][C]38[/C][C]35.9291[/C][C]2.07087[/C][/ROW]
[ROW][C]15[/C][C]37[/C][C]34.3635[/C][C]2.6365[/C][/ROW]
[ROW][C]16[/C][C]33[/C][C]33.0084[/C][C]-0.00835932[/C][/ROW]
[ROW][C]17[/C][C]32[/C][C]34.5685[/C][C]-2.56847[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]36.4431[/C][C]1.5569[/C][/ROW]
[ROW][C]19[/C][C]38[/C][C]36.1783[/C][C]1.82175[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.1724[/C][C]-1.17241[/C][/ROW]
[ROW][C]21[/C][C]33[/C][C]33.15[/C][C]-0.150016[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]32.7283[/C][C]-1.72826[/C][/ROW]
[ROW][C]23[/C][C]38[/C][C]36.4807[/C][C]1.51928[/C][/ROW]
[ROW][C]24[/C][C]39[/C][C]35.0105[/C][C]3.98955[/C][/ROW]
[ROW][C]25[/C][C]32[/C][C]36.455[/C][C]-4.455[/C][/ROW]
[ROW][C]26[/C][C]32[/C][C]37.1121[/C][C]-5.11213[/C][/ROW]
[ROW][C]27[/C][C]35[/C][C]34.7302[/C][C]0.269801[/C][/ROW]
[ROW][C]28[/C][C]37[/C][C]33.7696[/C][C]3.23042[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]33.7516[/C][C]-0.751641[/C][/ROW]
[ROW][C]30[/C][C]33[/C][C]33.4519[/C][C]-0.451944[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]32.7921[/C][C]-1.79211[/C][/ROW]
[ROW][C]32[/C][C]32[/C][C]30.021[/C][C]1.97903[/C][/ROW]
[ROW][C]33[/C][C]31[/C][C]34.8614[/C][C]-3.86138[/C][/ROW]
[ROW][C]34[/C][C]37[/C][C]34.1878[/C][C]2.81224[/C][/ROW]
[ROW][C]35[/C][C]30[/C][C]33.8369[/C][C]-3.83691[/C][/ROW]
[ROW][C]36[/C][C]33[/C][C]31.8722[/C][C]1.12782[/C][/ROW]
[ROW][C]37[/C][C]31[/C][C]30.7314[/C][C]0.268581[/C][/ROW]
[ROW][C]38[/C][C]33[/C][C]34.655[/C][C]-1.65502[/C][/ROW]
[ROW][C]39[/C][C]31[/C][C]31.8537[/C][C]-0.853656[/C][/ROW]
[ROW][C]40[/C][C]33[/C][C]34.1638[/C][C]-1.16385[/C][/ROW]
[ROW][C]41[/C][C]32[/C][C]35.0791[/C][C]-3.07908[/C][/ROW]
[ROW][C]42[/C][C]33[/C][C]33.9102[/C][C]-0.910162[/C][/ROW]
[ROW][C]43[/C][C]32[/C][C]36.4523[/C][C]-4.45234[/C][/ROW]
[ROW][C]44[/C][C]33[/C][C]33.7717[/C][C]-0.77169[/C][/ROW]
[ROW][C]45[/C][C]28[/C][C]35.2126[/C][C]-7.2126[/C][/ROW]
[ROW][C]46[/C][C]35[/C][C]34.5588[/C][C]0.441196[/C][/ROW]
[ROW][C]47[/C][C]39[/C][C]35.5208[/C][C]3.47918[/C][/ROW]
[ROW][C]48[/C][C]34[/C][C]33.4468[/C][C]0.553181[/C][/ROW]
[ROW][C]49[/C][C]38[/C][C]34.9006[/C][C]3.09942[/C][/ROW]
[ROW][C]50[/C][C]32[/C][C]35.4522[/C][C]-3.45225[/C][/ROW]
[ROW][C]51[/C][C]38[/C][C]33.5156[/C][C]4.48443[/C][/ROW]
[ROW][C]52[/C][C]30[/C][C]32.7169[/C][C]-2.71694[/C][/ROW]
[ROW][C]53[/C][C]33[/C][C]32.6255[/C][C]0.374498[/C][/ROW]
[ROW][C]54[/C][C]38[/C][C]34.0645[/C][C]3.93554[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]31.3528[/C][C]0.6472[/C][/ROW]
[ROW][C]56[/C][C]35[/C][C]34.411[/C][C]0.588999[/C][/ROW]
[ROW][C]57[/C][C]34[/C][C]36.2147[/C][C]-2.21472[/C][/ROW]
[ROW][C]58[/C][C]34[/C][C]31.9525[/C][C]2.04747[/C][/ROW]
[ROW][C]59[/C][C]36[/C][C]34.9912[/C][C]1.00878[/C][/ROW]
[ROW][C]60[/C][C]34[/C][C]34.1947[/C][C]-0.194685[/C][/ROW]
[ROW][C]61[/C][C]28[/C][C]31.0444[/C][C]-3.04439[/C][/ROW]
[ROW][C]62[/C][C]34[/C][C]35.7356[/C][C]-1.73563[/C][/ROW]
[ROW][C]63[/C][C]35[/C][C]34.2954[/C][C]0.704604[/C][/ROW]
[ROW][C]64[/C][C]35[/C][C]32.2936[/C][C]2.70641[/C][/ROW]
[ROW][C]65[/C][C]31[/C][C]33.9458[/C][C]-2.94576[/C][/ROW]
[ROW][C]66[/C][C]37[/C][C]34.6787[/C][C]2.32133[/C][/ROW]
[ROW][C]67[/C][C]35[/C][C]35.3056[/C][C]-0.305564[/C][/ROW]
[ROW][C]68[/C][C]27[/C][C]32.5011[/C][C]-5.50109[/C][/ROW]
[ROW][C]69[/C][C]40[/C][C]35.5793[/C][C]4.42067[/C][/ROW]
[ROW][C]70[/C][C]37[/C][C]34.5[/C][C]2.50004[/C][/ROW]
[ROW][C]71[/C][C]36[/C][C]34.4336[/C][C]1.56642[/C][/ROW]
[ROW][C]72[/C][C]38[/C][C]32.3756[/C][C]5.62443[/C][/ROW]
[ROW][C]73[/C][C]39[/C][C]34.6793[/C][C]4.32067[/C][/ROW]
[ROW][C]74[/C][C]41[/C][C]36.1987[/C][C]4.80133[/C][/ROW]
[ROW][C]75[/C][C]27[/C][C]34.1331[/C][C]-7.13312[/C][/ROW]
[ROW][C]76[/C][C]30[/C][C]35.9822[/C][C]-5.98225[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.5013[/C][C]1.49875[/C][/ROW]
[ROW][C]78[/C][C]31[/C][C]33.9406[/C][C]-2.94059[/C][/ROW]
[ROW][C]79[/C][C]31[/C][C]31.2818[/C][C]-0.281833[/C][/ROW]
[ROW][C]80[/C][C]27[/C][C]35.0919[/C][C]-8.09186[/C][/ROW]
[ROW][C]81[/C][C]36[/C][C]33.7307[/C][C]2.26929[/C][/ROW]
[ROW][C]82[/C][C]37[/C][C]34.468[/C][C]2.53202[/C][/ROW]
[ROW][C]83[/C][C]33[/C][C]35.2412[/C][C]-2.24124[/C][/ROW]
[ROW][C]84[/C][C]34[/C][C]33.0171[/C][C]0.982898[/C][/ROW]
[ROW][C]85[/C][C]31[/C][C]33.4638[/C][C]-2.46378[/C][/ROW]
[ROW][C]86[/C][C]39[/C][C]35.1638[/C][C]3.83624[/C][/ROW]
[ROW][C]87[/C][C]34[/C][C]33.626[/C][C]0.373981[/C][/ROW]
[ROW][C]88[/C][C]32[/C][C]31.8438[/C][C]0.156229[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.4143[/C][C]-0.414343[/C][/ROW]
[ROW][C]90[/C][C]36[/C][C]32.0509[/C][C]3.94907[/C][/ROW]
[ROW][C]91[/C][C]32[/C][C]35.2287[/C][C]-3.22866[/C][/ROW]
[ROW][C]92[/C][C]41[/C][C]34.5599[/C][C]6.44012[/C][/ROW]
[ROW][C]93[/C][C]28[/C][C]33.2277[/C][C]-5.22766[/C][/ROW]
[ROW][C]94[/C][C]30[/C][C]31.6619[/C][C]-1.66185[/C][/ROW]
[ROW][C]95[/C][C]36[/C][C]36.0054[/C][C]-0.00537722[/C][/ROW]
[ROW][C]96[/C][C]35[/C][C]35.3856[/C][C]-0.385588[/C][/ROW]
[ROW][C]97[/C][C]31[/C][C]34.1586[/C][C]-3.15862[/C][/ROW]
[ROW][C]98[/C][C]34[/C][C]35.4565[/C][C]-1.4565[/C][/ROW]
[ROW][C]99[/C][C]36[/C][C]32.7832[/C][C]3.21675[/C][/ROW]
[ROW][C]100[/C][C]36[/C][C]36.0583[/C][C]-0.05834[/C][/ROW]
[ROW][C]101[/C][C]35[/C][C]35.1786[/C][C]-0.178562[/C][/ROW]
[ROW][C]102[/C][C]37[/C][C]35.9355[/C][C]1.06447[/C][/ROW]
[ROW][C]103[/C][C]28[/C][C]32.8456[/C][C]-4.84558[/C][/ROW]
[ROW][C]104[/C][C]39[/C][C]33.6592[/C][C]5.34083[/C][/ROW]
[ROW][C]105[/C][C]32[/C][C]36.0598[/C][C]-4.0598[/C][/ROW]
[ROW][C]106[/C][C]35[/C][C]35.927[/C][C]-0.927001[/C][/ROW]
[ROW][C]107[/C][C]39[/C][C]37.0177[/C][C]1.98226[/C][/ROW]
[ROW][C]108[/C][C]35[/C][C]34.5348[/C][C]0.465176[/C][/ROW]
[ROW][C]109[/C][C]42[/C][C]36.452[/C][C]5.54798[/C][/ROW]
[ROW][C]110[/C][C]34[/C][C]32.5724[/C][C]1.42755[/C][/ROW]
[ROW][C]111[/C][C]33[/C][C]33.0324[/C][C]-0.0324239[/C][/ROW]
[ROW][C]112[/C][C]41[/C][C]33.3482[/C][C]7.65177[/C][/ROW]
[ROW][C]113[/C][C]33[/C][C]32.4667[/C][C]0.533279[/C][/ROW]
[ROW][C]114[/C][C]34[/C][C]34.6961[/C][C]-0.696055[/C][/ROW]
[ROW][C]115[/C][C]32[/C][C]35.8399[/C][C]-3.83993[/C][/ROW]
[ROW][C]116[/C][C]40[/C][C]33.3798[/C][C]6.62018[/C][/ROW]
[ROW][C]117[/C][C]40[/C][C]33.292[/C][C]6.70803[/C][/ROW]
[ROW][C]118[/C][C]35[/C][C]33.0913[/C][C]1.90867[/C][/ROW]
[ROW][C]119[/C][C]36[/C][C]35.906[/C][C]0.0939582[/C][/ROW]
[ROW][C]120[/C][C]37[/C][C]32.9651[/C][C]4.03488[/C][/ROW]
[ROW][C]121[/C][C]27[/C][C]33.001[/C][C]-6.00098[/C][/ROW]
[ROW][C]122[/C][C]39[/C][C]35.501[/C][C]3.49898[/C][/ROW]
[ROW][C]123[/C][C]38[/C][C]35.5705[/C][C]2.4295[/C][/ROW]
[ROW][C]124[/C][C]31[/C][C]34.9116[/C][C]-3.91157[/C][/ROW]
[ROW][C]125[/C][C]33[/C][C]33.2121[/C][C]-0.212112[/C][/ROW]
[ROW][C]126[/C][C]32[/C][C]35.9623[/C][C]-3.96227[/C][/ROW]
[ROW][C]127[/C][C]39[/C][C]38.2866[/C][C]0.713429[/C][/ROW]
[ROW][C]128[/C][C]36[/C][C]33.3665[/C][C]2.63348[/C][/ROW]
[ROW][C]129[/C][C]33[/C][C]33.8832[/C][C]-0.883194[/C][/ROW]
[ROW][C]130[/C][C]33[/C][C]32.9509[/C][C]0.0490895[/C][/ROW]
[ROW][C]131[/C][C]32[/C][C]30.5861[/C][C]1.4139[/C][/ROW]
[ROW][C]132[/C][C]37[/C][C]36.1135[/C][C]0.886509[/C][/ROW]
[ROW][C]133[/C][C]30[/C][C]30.5345[/C][C]-0.534484[/C][/ROW]
[ROW][C]134[/C][C]38[/C][C]35.0946[/C][C]2.90538[/C][/ROW]
[ROW][C]135[/C][C]29[/C][C]33.2986[/C][C]-4.29859[/C][/ROW]
[ROW][C]136[/C][C]22[/C][C]30.7078[/C][C]-8.70783[/C][/ROW]
[ROW][C]137[/C][C]35[/C][C]33.7579[/C][C]1.24213[/C][/ROW]
[ROW][C]138[/C][C]35[/C][C]31.3304[/C][C]3.6696[/C][/ROW]
[ROW][C]139[/C][C]34[/C][C]33.4307[/C][C]0.569277[/C][/ROW]
[ROW][C]140[/C][C]35[/C][C]31.7688[/C][C]3.23116[/C][/ROW]
[ROW][C]141[/C][C]34[/C][C]32.6054[/C][C]1.3946[/C][/ROW]
[ROW][C]142[/C][C]37[/C][C]32.1001[/C][C]4.89988[/C][/ROW]
[ROW][C]143[/C][C]35[/C][C]33.025[/C][C]1.975[/C][/ROW]
[ROW][C]144[/C][C]23[/C][C]32.7753[/C][C]-9.77533[/C][/ROW]
[ROW][C]145[/C][C]31[/C][C]35.4873[/C][C]-4.48726[/C][/ROW]
[ROW][C]146[/C][C]27[/C][C]33.7053[/C][C]-6.70532[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]34.3316[/C][C]1.66838[/C][/ROW]
[ROW][C]148[/C][C]31[/C][C]33.2004[/C][C]-2.20042[/C][/ROW]
[ROW][C]149[/C][C]32[/C][C]33.6734[/C][C]-1.67341[/C][/ROW]
[ROW][C]150[/C][C]39[/C][C]34.5144[/C][C]4.48557[/C][/ROW]
[ROW][C]151[/C][C]37[/C][C]37.4492[/C][C]-0.449153[/C][/ROW]
[ROW][C]152[/C][C]38[/C][C]33.719[/C][C]4.28102[/C][/ROW]
[ROW][C]153[/C][C]39[/C][C]33.6986[/C][C]5.30138[/C][/ROW]
[ROW][C]154[/C][C]34[/C][C]34.8858[/C][C]-0.885844[/C][/ROW]
[ROW][C]155[/C][C]31[/C][C]32.4845[/C][C]-1.48455[/C][/ROW]
[ROW][C]156[/C][C]32[/C][C]35.2287[/C][C]-3.22866[/C][/ROW]
[ROW][C]157[/C][C]37[/C][C]32.1225[/C][C]4.87749[/C][/ROW]
[ROW][C]158[/C][C]36[/C][C]33.3665[/C][C]2.63348[/C][/ROW]
[ROW][C]159[/C][C]32[/C][C]33.9924[/C][C]-1.99239[/C][/ROW]
[ROW][C]160[/C][C]38[/C][C]32.3522[/C][C]5.6478[/C][/ROW]
[ROW][C]161[/C][C]36[/C][C]33.1837[/C][C]2.81626[/C][/ROW]
[ROW][C]162[/C][C]26[/C][C]30.5026[/C][C]-4.50264[/C][/ROW]
[ROW][C]163[/C][C]26[/C][C]31.9277[/C][C]-5.9277[/C][/ROW]
[ROW][C]164[/C][C]33[/C][C]36.3103[/C][C]-3.31026[/C][/ROW]
[ROW][C]165[/C][C]39[/C][C]33.6457[/C][C]5.35429[/C][/ROW]
[ROW][C]166[/C][C]30[/C][C]28.5491[/C][C]1.4509[/C][/ROW]
[ROW][C]167[/C][C]33[/C][C]32.0873[/C][C]0.912737[/C][/ROW]
[ROW][C]168[/C][C]25[/C][C]30.1007[/C][C]-5.10069[/C][/ROW]
[ROW][C]169[/C][C]38[/C][C]33.6718[/C][C]4.32825[/C][/ROW]
[ROW][C]170[/C][C]37[/C][C]31.1031[/C][C]5.89691[/C][/ROW]
[ROW][C]171[/C][C]31[/C][C]33.7958[/C][C]-2.79585[/C][/ROW]
[ROW][C]172[/C][C]37[/C][C]34.9471[/C][C]2.05289[/C][/ROW]
[ROW][C]173[/C][C]35[/C][C]36.1213[/C][C]-1.12133[/C][/ROW]
[ROW][C]174[/C][C]25[/C][C]30.4062[/C][C]-5.40619[/C][/ROW]
[ROW][C]175[/C][C]28[/C][C]34.4449[/C][C]-6.4449[/C][/ROW]
[ROW][C]176[/C][C]35[/C][C]32.9852[/C][C]2.01484[/C][/ROW]
[ROW][C]177[/C][C]33[/C][C]34.178[/C][C]-1.17799[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.5154[/C][C]-1.51543[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]32.3186[/C][C]-1.31861[/C][/ROW]
[ROW][C]180[/C][C]37[/C][C]34.7996[/C][C]2.2004[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]34.7255[/C][C]1.27448[/C][/ROW]
[ROW][C]182[/C][C]30[/C][C]33.0125[/C][C]-3.01254[/C][/ROW]
[ROW][C]183[/C][C]36[/C][C]33.5723[/C][C]2.42771[/C][/ROW]
[ROW][C]184[/C][C]32[/C][C]35.6413[/C][C]-3.64133[/C][/ROW]
[ROW][C]185[/C][C]28[/C][C]28.2734[/C][C]-0.27342[/C][/ROW]
[ROW][C]186[/C][C]36[/C][C]33.3156[/C][C]2.68444[/C][/ROW]
[ROW][C]187[/C][C]34[/C][C]34.9368[/C][C]-0.936754[/C][/ROW]
[ROW][C]188[/C][C]31[/C][C]35.174[/C][C]-4.17404[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.1755[/C][C]-2.17552[/C][/ROW]
[ROW][C]190[/C][C]36[/C][C]31.6629[/C][C]4.33706[/C][/ROW]
[ROW][C]191[/C][C]36[/C][C]32.614[/C][C]3.38602[/C][/ROW]
[ROW][C]192[/C][C]40[/C][C]35.7257[/C][C]4.27427[/C][/ROW]
[ROW][C]193[/C][C]33[/C][C]31.6688[/C][C]1.3312[/C][/ROW]
[ROW][C]194[/C][C]37[/C][C]34.2284[/C][C]2.77159[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]32.6599[/C][C]-0.659863[/C][/ROW]
[ROW][C]196[/C][C]38[/C][C]35.1058[/C][C]2.89422[/C][/ROW]
[ROW][C]197[/C][C]31[/C][C]33.833[/C][C]-2.83301[/C][/ROW]
[ROW][C]198[/C][C]37[/C][C]33.8127[/C][C]3.18726[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]32.8513[/C][C]0.148717[/C][/ROW]
[ROW][C]200[/C][C]32[/C][C]30.7844[/C][C]1.21559[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]32.2986[/C][C]-2.29857[/C][/ROW]
[ROW][C]202[/C][C]30[/C][C]29.4345[/C][C]0.565464[/C][/ROW]
[ROW][C]203[/C][C]31[/C][C]33.1609[/C][C]-2.16086[/C][/ROW]
[ROW][C]204[/C][C]32[/C][C]33.3889[/C][C]-1.38892[/C][/ROW]
[ROW][C]205[/C][C]34[/C][C]33.0577[/C][C]0.942251[/C][/ROW]
[ROW][C]206[/C][C]36[/C][C]33.8713[/C][C]2.12871[/C][/ROW]
[ROW][C]207[/C][C]37[/C][C]34.4715[/C][C]2.52848[/C][/ROW]
[ROW][C]208[/C][C]36[/C][C]34.3888[/C][C]1.61117[/C][/ROW]
[ROW][C]209[/C][C]33[/C][C]33.9854[/C][C]-0.985426[/C][/ROW]
[ROW][C]210[/C][C]33[/C][C]33.855[/C][C]-0.855016[/C][/ROW]
[ROW][C]211[/C][C]33[/C][C]33.3966[/C][C]-0.396553[/C][/ROW]
[ROW][C]212[/C][C]44[/C][C]36.597[/C][C]7.40303[/C][/ROW]
[ROW][C]213[/C][C]39[/C][C]33.098[/C][C]5.90198[/C][/ROW]
[ROW][C]214[/C][C]32[/C][C]31.7617[/C][C]0.238274[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]34.4029[/C][C]0.597111[/C][/ROW]
[ROW][C]216[/C][C]25[/C][C]31.0632[/C][C]-6.06322[/C][/ROW]
[ROW][C]217[/C][C]35[/C][C]33.8448[/C][C]1.15524[/C][/ROW]
[ROW][C]218[/C][C]34[/C][C]35.7308[/C][C]-1.73075[/C][/ROW]
[ROW][C]219[/C][C]35[/C][C]33.8635[/C][C]1.1365[/C][/ROW]
[ROW][C]220[/C][C]39[/C][C]34.8988[/C][C]4.1012[/C][/ROW]
[ROW][C]221[/C][C]33[/C][C]34.0479[/C][C]-1.04792[/C][/ROW]
[ROW][C]222[/C][C]36[/C][C]35.1538[/C][C]0.846174[/C][/ROW]
[ROW][C]223[/C][C]32[/C][C]33.4643[/C][C]-1.46432[/C][/ROW]
[ROW][C]224[/C][C]32[/C][C]31.948[/C][C]0.0519797[/C][/ROW]
[ROW][C]225[/C][C]36[/C][C]32.9744[/C][C]3.02564[/C][/ROW]
[ROW][C]226[/C][C]36[/C][C]31.576[/C][C]4.42398[/C][/ROW]
[ROW][C]227[/C][C]32[/C][C]32.297[/C][C]-0.29702[/C][/ROW]
[ROW][C]228[/C][C]34[/C][C]32.9001[/C][C]1.09991[/C][/ROW]
[ROW][C]229[/C][C]33[/C][C]32.9551[/C][C]0.0449156[/C][/ROW]
[ROW][C]230[/C][C]35[/C][C]33.1011[/C][C]1.89889[/C][/ROW]
[ROW][C]231[/C][C]30[/C][C]32.947[/C][C]-2.94704[/C][/ROW]
[ROW][C]232[/C][C]38[/C][C]32.5014[/C][C]5.49856[/C][/ROW]
[ROW][C]233[/C][C]34[/C][C]32.3885[/C][C]1.61151[/C][/ROW]
[ROW][C]234[/C][C]33[/C][C]37.4797[/C][C]-4.47968[/C][/ROW]
[ROW][C]235[/C][C]32[/C][C]33.4646[/C][C]-1.4646[/C][/ROW]
[ROW][C]236[/C][C]31[/C][C]33.9308[/C][C]-2.93079[/C][/ROW]
[ROW][C]237[/C][C]30[/C][C]33.0735[/C][C]-3.07352[/C][/ROW]
[ROW][C]238[/C][C]27[/C][C]34.299[/C][C]-7.299[/C][/ROW]
[ROW][C]239[/C][C]31[/C][C]31.8793[/C][C]-0.87933[/C][/ROW]
[ROW][C]240[/C][C]30[/C][C]33.851[/C][C]-3.85098[/C][/ROW]
[ROW][C]241[/C][C]32[/C][C]30.2409[/C][C]1.75911[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.5855[/C][C]1.41452[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]29.591[/C][C]-1.591[/C][/ROW]
[ROW][C]244[/C][C]33[/C][C]33.3017[/C][C]-0.301741[/C][/ROW]
[ROW][C]245[/C][C]31[/C][C]35.0703[/C][C]-4.07029[/C][/ROW]
[ROW][C]246[/C][C]35[/C][C]30.9735[/C][C]4.0265[/C][/ROW]
[ROW][C]247[/C][C]35[/C][C]32.5873[/C][C]2.41273[/C][/ROW]
[ROW][C]248[/C][C]32[/C][C]33.6259[/C][C]-1.62586[/C][/ROW]
[ROW][C]249[/C][C]21[/C][C]26.6985[/C][C]-5.69849[/C][/ROW]
[ROW][C]250[/C][C]20[/C][C]27.6352[/C][C]-7.63522[/C][/ROW]
[ROW][C]251[/C][C]34[/C][C]31.61[/C][C]2.38995[/C][/ROW]
[ROW][C]252[/C][C]32[/C][C]32.3537[/C][C]-0.353698[/C][/ROW]
[ROW][C]253[/C][C]34[/C][C]33.6087[/C][C]0.391339[/C][/ROW]
[ROW][C]254[/C][C]32[/C][C]33.2719[/C][C]-1.27187[/C][/ROW]
[ROW][C]255[/C][C]33[/C][C]34.5118[/C][C]-1.51176[/C][/ROW]
[ROW][C]256[/C][C]33[/C][C]33.62[/C][C]-0.62[/C][/ROW]
[ROW][C]257[/C][C]37[/C][C]34.4576[/C][C]2.5424[/C][/ROW]
[ROW][C]258[/C][C]32[/C][C]31.9209[/C][C]0.0790981[/C][/ROW]
[ROW][C]259[/C][C]34[/C][C]34.8142[/C][C]-0.814211[/C][/ROW]
[ROW][C]260[/C][C]30[/C][C]31.8012[/C][C]-1.80125[/C][/ROW]
[ROW][C]261[/C][C]30[/C][C]30.8529[/C][C]-0.852851[/C][/ROW]
[ROW][C]262[/C][C]38[/C][C]33.4179[/C][C]4.58208[/C][/ROW]
[ROW][C]263[/C][C]36[/C][C]35.1216[/C][C]0.878401[/C][/ROW]
[ROW][C]264[/C][C]32[/C][C]31.3796[/C][C]0.620445[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253721&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253721&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
13836.40971.59026
23236.2072-4.20716
33533.04431.95566
43331.87331.12673
53734.10912.89095
62934.0147-5.01468
73136.4499-5.44989
83634.23941.76055
93534.66140.338577
103834.88713.11291
113135.6007-4.60066
123434.8325-0.832464
133535.5961-0.596073
143835.92912.07087
153734.36352.6365
163333.0084-0.00835932
173234.5685-2.56847
183836.44311.5569
193836.17831.82175
203233.1724-1.17241
213333.15-0.150016
223132.7283-1.72826
233836.48071.51928
243935.01053.98955
253236.455-4.455
263237.1121-5.11213
273534.73020.269801
283733.76963.23042
293333.7516-0.751641
303333.4519-0.451944
313132.7921-1.79211
323230.0211.97903
333134.8614-3.86138
343734.18782.81224
353033.8369-3.83691
363331.87221.12782
373130.73140.268581
383334.655-1.65502
393131.8537-0.853656
403334.1638-1.16385
413235.0791-3.07908
423333.9102-0.910162
433236.4523-4.45234
443333.7717-0.77169
452835.2126-7.2126
463534.55880.441196
473935.52083.47918
483433.44680.553181
493834.90063.09942
503235.4522-3.45225
513833.51564.48443
523032.7169-2.71694
533332.62550.374498
543834.06453.93554
553231.35280.6472
563534.4110.588999
573436.2147-2.21472
583431.95252.04747
593634.99121.00878
603434.1947-0.194685
612831.0444-3.04439
623435.7356-1.73563
633534.29540.704604
643532.29362.70641
653133.9458-2.94576
663734.67872.32133
673535.3056-0.305564
682732.5011-5.50109
694035.57934.42067
703734.52.50004
713634.43361.56642
723832.37565.62443
733934.67934.32067
744136.19874.80133
752734.1331-7.13312
763035.9822-5.98225
773735.50131.49875
783133.9406-2.94059
793131.2818-0.281833
802735.0919-8.09186
813633.73072.26929
823734.4682.53202
833335.2412-2.24124
843433.01710.982898
853133.4638-2.46378
863935.16383.83624
873433.6260.373981
883231.84380.156229
893333.4143-0.414343
903632.05093.94907
913235.2287-3.22866
924134.55996.44012
932833.2277-5.22766
943031.6619-1.66185
953636.0054-0.00537722
963535.3856-0.385588
973134.1586-3.15862
983435.4565-1.4565
993632.78323.21675
1003636.0583-0.05834
1013535.1786-0.178562
1023735.93551.06447
1032832.8456-4.84558
1043933.65925.34083
1053236.0598-4.0598
1063535.927-0.927001
1073937.01771.98226
1083534.53480.465176
1094236.4525.54798
1103432.57241.42755
1113333.0324-0.0324239
1124133.34827.65177
1133332.46670.533279
1143434.6961-0.696055
1153235.8399-3.83993
1164033.37986.62018
1174033.2926.70803
1183533.09131.90867
1193635.9060.0939582
1203732.96514.03488
1212733.001-6.00098
1223935.5013.49898
1233835.57052.4295
1243134.9116-3.91157
1253333.2121-0.212112
1263235.9623-3.96227
1273938.28660.713429
1283633.36652.63348
1293333.8832-0.883194
1303332.95090.0490895
1313230.58611.4139
1323736.11350.886509
1333030.5345-0.534484
1343835.09462.90538
1352933.2986-4.29859
1362230.7078-8.70783
1373533.75791.24213
1383531.33043.6696
1393433.43070.569277
1403531.76883.23116
1413432.60541.3946
1423732.10014.89988
1433533.0251.975
1442332.7753-9.77533
1453135.4873-4.48726
1462733.7053-6.70532
1473634.33161.66838
1483133.2004-2.20042
1493233.6734-1.67341
1503934.51444.48557
1513737.4492-0.449153
1523833.7194.28102
1533933.69865.30138
1543434.8858-0.885844
1553132.4845-1.48455
1563235.2287-3.22866
1573732.12254.87749
1583633.36652.63348
1593233.9924-1.99239
1603832.35225.6478
1613633.18372.81626
1622630.5026-4.50264
1632631.9277-5.9277
1643336.3103-3.31026
1653933.64575.35429
1663028.54911.4509
1673332.08730.912737
1682530.1007-5.10069
1693833.67184.32825
1703731.10315.89691
1713133.7958-2.79585
1723734.94712.05289
1733536.1213-1.12133
1742530.4062-5.40619
1752834.4449-6.4449
1763532.98522.01484
1773334.178-1.17799
1783031.5154-1.51543
1793132.3186-1.31861
1803734.79962.2004
1813634.72551.27448
1823033.0125-3.01254
1833633.57232.42771
1843235.6413-3.64133
1852828.2734-0.27342
1863633.31562.68444
1873434.9368-0.936754
1883135.174-4.17404
1892830.1755-2.17552
1903631.66294.33706
1913632.6143.38602
1924035.72574.27427
1933331.66881.3312
1943734.22842.77159
1953232.6599-0.659863
1963835.10582.89422
1973133.833-2.83301
1983733.81273.18726
1993332.85130.148717
2003230.78441.21559
2013032.2986-2.29857
2023029.43450.565464
2033133.1609-2.16086
2043233.3889-1.38892
2053433.05770.942251
2063633.87132.12871
2073734.47152.52848
2083634.38881.61117
2093333.9854-0.985426
2103333.855-0.855016
2113333.3966-0.396553
2124436.5977.40303
2133933.0985.90198
2143231.76170.238274
2153534.40290.597111
2162531.0632-6.06322
2173533.84481.15524
2183435.7308-1.73075
2193533.86351.1365
2203934.89884.1012
2213334.0479-1.04792
2223635.15380.846174
2233233.4643-1.46432
2243231.9480.0519797
2253632.97443.02564
2263631.5764.42398
2273232.297-0.29702
2283432.90011.09991
2293332.95510.0449156
2303533.10111.89889
2313032.947-2.94704
2323832.50145.49856
2333432.38851.61151
2343337.4797-4.47968
2353233.4646-1.4646
2363133.9308-2.93079
2373033.0735-3.07352
2382734.299-7.299
2393131.8793-0.87933
2403033.851-3.85098
2413230.24091.75911
2423533.58551.41452
2432829.591-1.591
2443333.3017-0.301741
2453135.0703-4.07029
2463530.97354.0265
2473532.58732.41273
2483233.6259-1.62586
2492126.6985-5.69849
2502027.6352-7.63522
2513431.612.38995
2523232.3537-0.353698
2533433.60870.391339
2543233.2719-1.27187
2553334.5118-1.51176
2563333.62-0.62
2573734.45762.5424
2583231.92090.0790981
2593434.8142-0.814211
2603031.8012-1.80125
2613030.8529-0.852851
2623833.41794.58208
2633635.12160.878401
2643231.37960.620445






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.2372710.4745410.762729
110.1165260.2330530.883474
120.5658920.8682150.434108
130.4796570.9593150.520343
140.5168420.9663160.483158
150.5286940.9426120.471306
160.4781640.9563280.521836
170.414850.82970.58515
180.4768140.9536280.523186
190.429990.8599810.57001
200.3607740.7215480.639226
210.2863560.5727120.713644
220.2846930.5693860.715307
230.2310520.4621040.768948
240.2515090.5030180.748491
250.2685220.5370440.731478
260.3813590.7627170.618641
270.3274310.6548610.672569
280.2992980.5985960.700702
290.2467260.4934510.753274
300.1996720.3993440.800328
310.1762850.352570.823715
320.1396920.2793830.860308
330.1346710.2693430.865329
340.141670.2833390.85833
350.1586870.3173740.841313
360.1361440.2722890.863856
370.1076570.2153140.892343
380.08684210.1736840.913158
390.06946170.1389230.930538
400.05359120.1071820.946409
410.04555350.0911070.954446
420.03409830.06819670.965902
430.04964360.09928710.950356
440.03820530.07641070.961795
450.0795170.1590340.920483
460.06382570.1276510.936174
470.07815280.1563060.921847
480.06234110.1246820.937659
490.07408570.1481710.925914
500.06885580.1377120.931144
510.07689940.1537990.923101
520.0744510.1489020.925549
530.0595690.1191380.940431
540.06238150.1247630.937619
550.05224010.104480.94776
560.04995060.09990110.950049
570.04063820.08127640.959362
580.03239440.06478880.967606
590.02742440.05484870.972576
600.02094630.04189250.979054
610.02331590.04663180.976684
620.01822410.03644820.981776
630.0138010.02760210.986199
640.01143260.02286520.988567
650.01220970.02441930.98779
660.01080090.02160180.989199
670.008065660.01613130.991934
680.01707560.03415130.982924
690.0224040.04480790.977596
700.02099670.04199340.979003
710.01804630.03609260.981954
720.02533760.05067510.974662
730.03192170.06384340.968078
740.04476430.08952860.955236
750.09189190.1837840.908108
760.104090.208180.89591
770.08940020.17880.9106
780.08379110.1675820.916209
790.07275490.145510.927245
800.1887090.3774180.811291
810.1769250.353850.823075
820.1691870.3383750.830813
830.1561570.3123130.843843
840.1352020.2704050.864798
850.1220030.2440070.877997
860.1516540.3033080.848346
870.1299980.2599960.870002
880.1117390.2234780.888261
890.09451820.1890360.905482
900.09839350.1967870.901606
910.1054110.2108220.894589
920.1719820.3439630.828018
930.2214760.4429530.778524
940.2082660.4165320.791734
950.1859860.3719710.814014
960.1620850.3241690.837915
970.1538970.3077930.846103
980.1361440.2722870.863856
990.1361210.2722420.863879
1000.116890.233780.88311
1010.1014410.2028810.898559
1020.08858060.1771610.911419
1030.1067550.2135090.893245
1040.1411880.2823750.858812
1050.146710.293420.85329
1060.1279540.2559070.872046
1070.1192980.2385950.880702
1080.1055480.2110960.894452
1090.1522560.3045120.847744
1100.1349570.2699140.865043
1110.116120.2322410.88388
1120.2402590.4805170.759741
1130.2148980.4297960.785102
1140.1921730.3843460.807827
1150.1993840.3987680.800616
1160.2727960.5455930.727204
1170.3822230.7644460.617777
1180.3587860.7175710.641214
1190.3269930.6539850.673007
1200.3393450.678690.660655
1210.4322880.8645760.567712
1220.4379310.8758620.562069
1230.4233230.8466470.576677
1240.4405730.8811460.559427
1250.4059140.8118270.594086
1260.4201320.8402640.579868
1270.3919050.783810.608095
1280.3780110.7560220.621989
1290.3496620.6993240.650338
1300.3181650.6363310.681835
1310.2942150.5884310.705785
1320.2722210.5444420.727779
1330.2525910.5051810.747409
1340.246050.4920990.75395
1350.2703220.5406440.729678
1360.4734530.9469060.526547
1370.4429750.885950.557025
1380.456150.91230.54385
1390.4225030.8450060.577497
1400.4229220.8458440.577078
1410.3944660.7889330.605534
1420.4353730.8707450.564627
1430.4123330.8246670.587667
1440.6936470.6127060.306353
1450.7236430.5527140.276357
1460.8204310.3591370.179569
1470.8036930.3926150.196307
1480.7937290.4125420.206271
1490.776620.4467590.22338
1500.7995240.4009520.200476
1510.7752390.4495210.224761
1520.7906860.4186280.209314
1530.8249040.3501930.175096
1540.805960.3880790.19404
1550.785620.4287610.21438
1560.7853120.4293770.214688
1570.816570.366860.18343
1580.8083020.3833960.191698
1590.8002520.3994950.199748
1600.8454860.3090290.154514
1610.8403720.3192570.159628
1620.8613110.2773780.138689
1630.905840.1883210.0941604
1640.9152930.1694150.0847074
1650.9330740.1338530.0669263
1660.9270120.1459750.0729875
1670.9136820.1726360.0863181
1680.9344090.1311810.0655905
1690.9387250.122550.0612749
1700.9574130.0851730.0425865
1710.9545510.0908970.0454485
1720.9477980.1044040.0522018
1730.940180.119640.0598202
1740.9535890.09282280.0464114
1750.9769150.04616930.0230847
1760.9729390.05412150.0270607
1770.9675210.06495750.0324787
1780.9615510.07689820.0384491
1790.9539520.09209590.046048
1800.9475170.1049650.0524827
1810.9380.1239990.0619997
1820.934470.131060.0655299
1830.9267360.1465280.0732642
1840.9372060.1255880.0627941
1850.9240190.1519610.0759805
1860.9164330.1671340.0835668
1870.9041670.1916650.0958327
1880.9270220.1459570.0729783
1890.9154580.1690840.084542
1900.9339650.132070.0660349
1910.9460340.1079320.0539662
1920.9488930.1022130.0511066
1930.9403320.1193350.0596676
1940.9373090.1253810.0626907
1950.9238310.1523380.0761688
1960.9187710.1624580.0812291
1970.9279460.1441070.0720535
1980.9188050.162390.0811949
1990.9014360.1971280.0985638
2000.8843170.2313660.115683
2010.8734210.2531580.126579
2020.8543340.2913310.145666
2030.8418570.3162860.158143
2040.8148940.3702130.185106
2050.7858940.4282120.214106
2060.7620720.4758560.237928
2070.7357060.5285880.264294
2080.7190270.5619460.280973
2090.6833920.6332160.316608
2100.6539540.6920930.346046
2110.6100660.7798670.389934
2120.7410380.5179240.258962
2130.793590.4128190.20641
2140.7573180.4853640.242682
2150.7198520.5602950.280148
2160.7871090.4257830.212891
2170.7519330.4961340.248067
2180.7302250.5395490.269775
2190.6916760.6166480.308324
2200.7126230.5747530.287377
2210.6695590.6608810.330441
2220.6319650.736070.368035
2230.5892310.8215370.410769
2240.5389560.9220890.461044
2250.5887330.8225340.411267
2260.6440930.7118130.355907
2270.6174060.7651880.382594
2280.5840510.8318980.415949
2290.5278330.9443350.472167
2300.4999810.9999620.500019
2310.4740520.9481040.525948
2320.6601210.6797580.339879
2330.6554290.6891410.344571
2340.7567260.4865490.243274
2350.7042030.5915930.295797
2360.6738920.6522170.326108
2370.6851970.6296070.314803
2380.772240.4555210.22776
2390.7157060.5685870.284294
2400.7554610.4890790.244539
2410.716280.567440.28372
2420.6646930.6706140.335307
2430.6011220.7977560.398878
2440.521440.957120.47856
2450.824120.351760.17588
2460.895320.2093610.10468
2470.8835530.2328950.116447
2480.824010.351980.17599
2490.7524150.495170.247585
2500.8835620.2328760.116438
2510.8724670.2550660.127533
2520.781370.437260.21863
2530.7710010.4579980.228999
2540.7221990.5556020.277801

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.237271 & 0.474541 & 0.762729 \tabularnewline
11 & 0.116526 & 0.233053 & 0.883474 \tabularnewline
12 & 0.565892 & 0.868215 & 0.434108 \tabularnewline
13 & 0.479657 & 0.959315 & 0.520343 \tabularnewline
14 & 0.516842 & 0.966316 & 0.483158 \tabularnewline
15 & 0.528694 & 0.942612 & 0.471306 \tabularnewline
16 & 0.478164 & 0.956328 & 0.521836 \tabularnewline
17 & 0.41485 & 0.8297 & 0.58515 \tabularnewline
18 & 0.476814 & 0.953628 & 0.523186 \tabularnewline
19 & 0.42999 & 0.859981 & 0.57001 \tabularnewline
20 & 0.360774 & 0.721548 & 0.639226 \tabularnewline
21 & 0.286356 & 0.572712 & 0.713644 \tabularnewline
22 & 0.284693 & 0.569386 & 0.715307 \tabularnewline
23 & 0.231052 & 0.462104 & 0.768948 \tabularnewline
24 & 0.251509 & 0.503018 & 0.748491 \tabularnewline
25 & 0.268522 & 0.537044 & 0.731478 \tabularnewline
26 & 0.381359 & 0.762717 & 0.618641 \tabularnewline
27 & 0.327431 & 0.654861 & 0.672569 \tabularnewline
28 & 0.299298 & 0.598596 & 0.700702 \tabularnewline
29 & 0.246726 & 0.493451 & 0.753274 \tabularnewline
30 & 0.199672 & 0.399344 & 0.800328 \tabularnewline
31 & 0.176285 & 0.35257 & 0.823715 \tabularnewline
32 & 0.139692 & 0.279383 & 0.860308 \tabularnewline
33 & 0.134671 & 0.269343 & 0.865329 \tabularnewline
34 & 0.14167 & 0.283339 & 0.85833 \tabularnewline
35 & 0.158687 & 0.317374 & 0.841313 \tabularnewline
36 & 0.136144 & 0.272289 & 0.863856 \tabularnewline
37 & 0.107657 & 0.215314 & 0.892343 \tabularnewline
38 & 0.0868421 & 0.173684 & 0.913158 \tabularnewline
39 & 0.0694617 & 0.138923 & 0.930538 \tabularnewline
40 & 0.0535912 & 0.107182 & 0.946409 \tabularnewline
41 & 0.0455535 & 0.091107 & 0.954446 \tabularnewline
42 & 0.0340983 & 0.0681967 & 0.965902 \tabularnewline
43 & 0.0496436 & 0.0992871 & 0.950356 \tabularnewline
44 & 0.0382053 & 0.0764107 & 0.961795 \tabularnewline
45 & 0.079517 & 0.159034 & 0.920483 \tabularnewline
46 & 0.0638257 & 0.127651 & 0.936174 \tabularnewline
47 & 0.0781528 & 0.156306 & 0.921847 \tabularnewline
48 & 0.0623411 & 0.124682 & 0.937659 \tabularnewline
49 & 0.0740857 & 0.148171 & 0.925914 \tabularnewline
50 & 0.0688558 & 0.137712 & 0.931144 \tabularnewline
51 & 0.0768994 & 0.153799 & 0.923101 \tabularnewline
52 & 0.074451 & 0.148902 & 0.925549 \tabularnewline
53 & 0.059569 & 0.119138 & 0.940431 \tabularnewline
54 & 0.0623815 & 0.124763 & 0.937619 \tabularnewline
55 & 0.0522401 & 0.10448 & 0.94776 \tabularnewline
56 & 0.0499506 & 0.0999011 & 0.950049 \tabularnewline
57 & 0.0406382 & 0.0812764 & 0.959362 \tabularnewline
58 & 0.0323944 & 0.0647888 & 0.967606 \tabularnewline
59 & 0.0274244 & 0.0548487 & 0.972576 \tabularnewline
60 & 0.0209463 & 0.0418925 & 0.979054 \tabularnewline
61 & 0.0233159 & 0.0466318 & 0.976684 \tabularnewline
62 & 0.0182241 & 0.0364482 & 0.981776 \tabularnewline
63 & 0.013801 & 0.0276021 & 0.986199 \tabularnewline
64 & 0.0114326 & 0.0228652 & 0.988567 \tabularnewline
65 & 0.0122097 & 0.0244193 & 0.98779 \tabularnewline
66 & 0.0108009 & 0.0216018 & 0.989199 \tabularnewline
67 & 0.00806566 & 0.0161313 & 0.991934 \tabularnewline
68 & 0.0170756 & 0.0341513 & 0.982924 \tabularnewline
69 & 0.022404 & 0.0448079 & 0.977596 \tabularnewline
70 & 0.0209967 & 0.0419934 & 0.979003 \tabularnewline
71 & 0.0180463 & 0.0360926 & 0.981954 \tabularnewline
72 & 0.0253376 & 0.0506751 & 0.974662 \tabularnewline
73 & 0.0319217 & 0.0638434 & 0.968078 \tabularnewline
74 & 0.0447643 & 0.0895286 & 0.955236 \tabularnewline
75 & 0.0918919 & 0.183784 & 0.908108 \tabularnewline
76 & 0.10409 & 0.20818 & 0.89591 \tabularnewline
77 & 0.0894002 & 0.1788 & 0.9106 \tabularnewline
78 & 0.0837911 & 0.167582 & 0.916209 \tabularnewline
79 & 0.0727549 & 0.14551 & 0.927245 \tabularnewline
80 & 0.188709 & 0.377418 & 0.811291 \tabularnewline
81 & 0.176925 & 0.35385 & 0.823075 \tabularnewline
82 & 0.169187 & 0.338375 & 0.830813 \tabularnewline
83 & 0.156157 & 0.312313 & 0.843843 \tabularnewline
84 & 0.135202 & 0.270405 & 0.864798 \tabularnewline
85 & 0.122003 & 0.244007 & 0.877997 \tabularnewline
86 & 0.151654 & 0.303308 & 0.848346 \tabularnewline
87 & 0.129998 & 0.259996 & 0.870002 \tabularnewline
88 & 0.111739 & 0.223478 & 0.888261 \tabularnewline
89 & 0.0945182 & 0.189036 & 0.905482 \tabularnewline
90 & 0.0983935 & 0.196787 & 0.901606 \tabularnewline
91 & 0.105411 & 0.210822 & 0.894589 \tabularnewline
92 & 0.171982 & 0.343963 & 0.828018 \tabularnewline
93 & 0.221476 & 0.442953 & 0.778524 \tabularnewline
94 & 0.208266 & 0.416532 & 0.791734 \tabularnewline
95 & 0.185986 & 0.371971 & 0.814014 \tabularnewline
96 & 0.162085 & 0.324169 & 0.837915 \tabularnewline
97 & 0.153897 & 0.307793 & 0.846103 \tabularnewline
98 & 0.136144 & 0.272287 & 0.863856 \tabularnewline
99 & 0.136121 & 0.272242 & 0.863879 \tabularnewline
100 & 0.11689 & 0.23378 & 0.88311 \tabularnewline
101 & 0.101441 & 0.202881 & 0.898559 \tabularnewline
102 & 0.0885806 & 0.177161 & 0.911419 \tabularnewline
103 & 0.106755 & 0.213509 & 0.893245 \tabularnewline
104 & 0.141188 & 0.282375 & 0.858812 \tabularnewline
105 & 0.14671 & 0.29342 & 0.85329 \tabularnewline
106 & 0.127954 & 0.255907 & 0.872046 \tabularnewline
107 & 0.119298 & 0.238595 & 0.880702 \tabularnewline
108 & 0.105548 & 0.211096 & 0.894452 \tabularnewline
109 & 0.152256 & 0.304512 & 0.847744 \tabularnewline
110 & 0.134957 & 0.269914 & 0.865043 \tabularnewline
111 & 0.11612 & 0.232241 & 0.88388 \tabularnewline
112 & 0.240259 & 0.480517 & 0.759741 \tabularnewline
113 & 0.214898 & 0.429796 & 0.785102 \tabularnewline
114 & 0.192173 & 0.384346 & 0.807827 \tabularnewline
115 & 0.199384 & 0.398768 & 0.800616 \tabularnewline
116 & 0.272796 & 0.545593 & 0.727204 \tabularnewline
117 & 0.382223 & 0.764446 & 0.617777 \tabularnewline
118 & 0.358786 & 0.717571 & 0.641214 \tabularnewline
119 & 0.326993 & 0.653985 & 0.673007 \tabularnewline
120 & 0.339345 & 0.67869 & 0.660655 \tabularnewline
121 & 0.432288 & 0.864576 & 0.567712 \tabularnewline
122 & 0.437931 & 0.875862 & 0.562069 \tabularnewline
123 & 0.423323 & 0.846647 & 0.576677 \tabularnewline
124 & 0.440573 & 0.881146 & 0.559427 \tabularnewline
125 & 0.405914 & 0.811827 & 0.594086 \tabularnewline
126 & 0.420132 & 0.840264 & 0.579868 \tabularnewline
127 & 0.391905 & 0.78381 & 0.608095 \tabularnewline
128 & 0.378011 & 0.756022 & 0.621989 \tabularnewline
129 & 0.349662 & 0.699324 & 0.650338 \tabularnewline
130 & 0.318165 & 0.636331 & 0.681835 \tabularnewline
131 & 0.294215 & 0.588431 & 0.705785 \tabularnewline
132 & 0.272221 & 0.544442 & 0.727779 \tabularnewline
133 & 0.252591 & 0.505181 & 0.747409 \tabularnewline
134 & 0.24605 & 0.492099 & 0.75395 \tabularnewline
135 & 0.270322 & 0.540644 & 0.729678 \tabularnewline
136 & 0.473453 & 0.946906 & 0.526547 \tabularnewline
137 & 0.442975 & 0.88595 & 0.557025 \tabularnewline
138 & 0.45615 & 0.9123 & 0.54385 \tabularnewline
139 & 0.422503 & 0.845006 & 0.577497 \tabularnewline
140 & 0.422922 & 0.845844 & 0.577078 \tabularnewline
141 & 0.394466 & 0.788933 & 0.605534 \tabularnewline
142 & 0.435373 & 0.870745 & 0.564627 \tabularnewline
143 & 0.412333 & 0.824667 & 0.587667 \tabularnewline
144 & 0.693647 & 0.612706 & 0.306353 \tabularnewline
145 & 0.723643 & 0.552714 & 0.276357 \tabularnewline
146 & 0.820431 & 0.359137 & 0.179569 \tabularnewline
147 & 0.803693 & 0.392615 & 0.196307 \tabularnewline
148 & 0.793729 & 0.412542 & 0.206271 \tabularnewline
149 & 0.77662 & 0.446759 & 0.22338 \tabularnewline
150 & 0.799524 & 0.400952 & 0.200476 \tabularnewline
151 & 0.775239 & 0.449521 & 0.224761 \tabularnewline
152 & 0.790686 & 0.418628 & 0.209314 \tabularnewline
153 & 0.824904 & 0.350193 & 0.175096 \tabularnewline
154 & 0.80596 & 0.388079 & 0.19404 \tabularnewline
155 & 0.78562 & 0.428761 & 0.21438 \tabularnewline
156 & 0.785312 & 0.429377 & 0.214688 \tabularnewline
157 & 0.81657 & 0.36686 & 0.18343 \tabularnewline
158 & 0.808302 & 0.383396 & 0.191698 \tabularnewline
159 & 0.800252 & 0.399495 & 0.199748 \tabularnewline
160 & 0.845486 & 0.309029 & 0.154514 \tabularnewline
161 & 0.840372 & 0.319257 & 0.159628 \tabularnewline
162 & 0.861311 & 0.277378 & 0.138689 \tabularnewline
163 & 0.90584 & 0.188321 & 0.0941604 \tabularnewline
164 & 0.915293 & 0.169415 & 0.0847074 \tabularnewline
165 & 0.933074 & 0.133853 & 0.0669263 \tabularnewline
166 & 0.927012 & 0.145975 & 0.0729875 \tabularnewline
167 & 0.913682 & 0.172636 & 0.0863181 \tabularnewline
168 & 0.934409 & 0.131181 & 0.0655905 \tabularnewline
169 & 0.938725 & 0.12255 & 0.0612749 \tabularnewline
170 & 0.957413 & 0.085173 & 0.0425865 \tabularnewline
171 & 0.954551 & 0.090897 & 0.0454485 \tabularnewline
172 & 0.947798 & 0.104404 & 0.0522018 \tabularnewline
173 & 0.94018 & 0.11964 & 0.0598202 \tabularnewline
174 & 0.953589 & 0.0928228 & 0.0464114 \tabularnewline
175 & 0.976915 & 0.0461693 & 0.0230847 \tabularnewline
176 & 0.972939 & 0.0541215 & 0.0270607 \tabularnewline
177 & 0.967521 & 0.0649575 & 0.0324787 \tabularnewline
178 & 0.961551 & 0.0768982 & 0.0384491 \tabularnewline
179 & 0.953952 & 0.0920959 & 0.046048 \tabularnewline
180 & 0.947517 & 0.104965 & 0.0524827 \tabularnewline
181 & 0.938 & 0.123999 & 0.0619997 \tabularnewline
182 & 0.93447 & 0.13106 & 0.0655299 \tabularnewline
183 & 0.926736 & 0.146528 & 0.0732642 \tabularnewline
184 & 0.937206 & 0.125588 & 0.0627941 \tabularnewline
185 & 0.924019 & 0.151961 & 0.0759805 \tabularnewline
186 & 0.916433 & 0.167134 & 0.0835668 \tabularnewline
187 & 0.904167 & 0.191665 & 0.0958327 \tabularnewline
188 & 0.927022 & 0.145957 & 0.0729783 \tabularnewline
189 & 0.915458 & 0.169084 & 0.084542 \tabularnewline
190 & 0.933965 & 0.13207 & 0.0660349 \tabularnewline
191 & 0.946034 & 0.107932 & 0.0539662 \tabularnewline
192 & 0.948893 & 0.102213 & 0.0511066 \tabularnewline
193 & 0.940332 & 0.119335 & 0.0596676 \tabularnewline
194 & 0.937309 & 0.125381 & 0.0626907 \tabularnewline
195 & 0.923831 & 0.152338 & 0.0761688 \tabularnewline
196 & 0.918771 & 0.162458 & 0.0812291 \tabularnewline
197 & 0.927946 & 0.144107 & 0.0720535 \tabularnewline
198 & 0.918805 & 0.16239 & 0.0811949 \tabularnewline
199 & 0.901436 & 0.197128 & 0.0985638 \tabularnewline
200 & 0.884317 & 0.231366 & 0.115683 \tabularnewline
201 & 0.873421 & 0.253158 & 0.126579 \tabularnewline
202 & 0.854334 & 0.291331 & 0.145666 \tabularnewline
203 & 0.841857 & 0.316286 & 0.158143 \tabularnewline
204 & 0.814894 & 0.370213 & 0.185106 \tabularnewline
205 & 0.785894 & 0.428212 & 0.214106 \tabularnewline
206 & 0.762072 & 0.475856 & 0.237928 \tabularnewline
207 & 0.735706 & 0.528588 & 0.264294 \tabularnewline
208 & 0.719027 & 0.561946 & 0.280973 \tabularnewline
209 & 0.683392 & 0.633216 & 0.316608 \tabularnewline
210 & 0.653954 & 0.692093 & 0.346046 \tabularnewline
211 & 0.610066 & 0.779867 & 0.389934 \tabularnewline
212 & 0.741038 & 0.517924 & 0.258962 \tabularnewline
213 & 0.79359 & 0.412819 & 0.20641 \tabularnewline
214 & 0.757318 & 0.485364 & 0.242682 \tabularnewline
215 & 0.719852 & 0.560295 & 0.280148 \tabularnewline
216 & 0.787109 & 0.425783 & 0.212891 \tabularnewline
217 & 0.751933 & 0.496134 & 0.248067 \tabularnewline
218 & 0.730225 & 0.539549 & 0.269775 \tabularnewline
219 & 0.691676 & 0.616648 & 0.308324 \tabularnewline
220 & 0.712623 & 0.574753 & 0.287377 \tabularnewline
221 & 0.669559 & 0.660881 & 0.330441 \tabularnewline
222 & 0.631965 & 0.73607 & 0.368035 \tabularnewline
223 & 0.589231 & 0.821537 & 0.410769 \tabularnewline
224 & 0.538956 & 0.922089 & 0.461044 \tabularnewline
225 & 0.588733 & 0.822534 & 0.411267 \tabularnewline
226 & 0.644093 & 0.711813 & 0.355907 \tabularnewline
227 & 0.617406 & 0.765188 & 0.382594 \tabularnewline
228 & 0.584051 & 0.831898 & 0.415949 \tabularnewline
229 & 0.527833 & 0.944335 & 0.472167 \tabularnewline
230 & 0.499981 & 0.999962 & 0.500019 \tabularnewline
231 & 0.474052 & 0.948104 & 0.525948 \tabularnewline
232 & 0.660121 & 0.679758 & 0.339879 \tabularnewline
233 & 0.655429 & 0.689141 & 0.344571 \tabularnewline
234 & 0.756726 & 0.486549 & 0.243274 \tabularnewline
235 & 0.704203 & 0.591593 & 0.295797 \tabularnewline
236 & 0.673892 & 0.652217 & 0.326108 \tabularnewline
237 & 0.685197 & 0.629607 & 0.314803 \tabularnewline
238 & 0.77224 & 0.455521 & 0.22776 \tabularnewline
239 & 0.715706 & 0.568587 & 0.284294 \tabularnewline
240 & 0.755461 & 0.489079 & 0.244539 \tabularnewline
241 & 0.71628 & 0.56744 & 0.28372 \tabularnewline
242 & 0.664693 & 0.670614 & 0.335307 \tabularnewline
243 & 0.601122 & 0.797756 & 0.398878 \tabularnewline
244 & 0.52144 & 0.95712 & 0.47856 \tabularnewline
245 & 0.82412 & 0.35176 & 0.17588 \tabularnewline
246 & 0.89532 & 0.209361 & 0.10468 \tabularnewline
247 & 0.883553 & 0.232895 & 0.116447 \tabularnewline
248 & 0.82401 & 0.35198 & 0.17599 \tabularnewline
249 & 0.752415 & 0.49517 & 0.247585 \tabularnewline
250 & 0.883562 & 0.232876 & 0.116438 \tabularnewline
251 & 0.872467 & 0.255066 & 0.127533 \tabularnewline
252 & 0.78137 & 0.43726 & 0.21863 \tabularnewline
253 & 0.771001 & 0.457998 & 0.228999 \tabularnewline
254 & 0.722199 & 0.555602 & 0.277801 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253721&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]0.237271[/C][C]0.474541[/C][C]0.762729[/C][/ROW]
[ROW][C]11[/C][C]0.116526[/C][C]0.233053[/C][C]0.883474[/C][/ROW]
[ROW][C]12[/C][C]0.565892[/C][C]0.868215[/C][C]0.434108[/C][/ROW]
[ROW][C]13[/C][C]0.479657[/C][C]0.959315[/C][C]0.520343[/C][/ROW]
[ROW][C]14[/C][C]0.516842[/C][C]0.966316[/C][C]0.483158[/C][/ROW]
[ROW][C]15[/C][C]0.528694[/C][C]0.942612[/C][C]0.471306[/C][/ROW]
[ROW][C]16[/C][C]0.478164[/C][C]0.956328[/C][C]0.521836[/C][/ROW]
[ROW][C]17[/C][C]0.41485[/C][C]0.8297[/C][C]0.58515[/C][/ROW]
[ROW][C]18[/C][C]0.476814[/C][C]0.953628[/C][C]0.523186[/C][/ROW]
[ROW][C]19[/C][C]0.42999[/C][C]0.859981[/C][C]0.57001[/C][/ROW]
[ROW][C]20[/C][C]0.360774[/C][C]0.721548[/C][C]0.639226[/C][/ROW]
[ROW][C]21[/C][C]0.286356[/C][C]0.572712[/C][C]0.713644[/C][/ROW]
[ROW][C]22[/C][C]0.284693[/C][C]0.569386[/C][C]0.715307[/C][/ROW]
[ROW][C]23[/C][C]0.231052[/C][C]0.462104[/C][C]0.768948[/C][/ROW]
[ROW][C]24[/C][C]0.251509[/C][C]0.503018[/C][C]0.748491[/C][/ROW]
[ROW][C]25[/C][C]0.268522[/C][C]0.537044[/C][C]0.731478[/C][/ROW]
[ROW][C]26[/C][C]0.381359[/C][C]0.762717[/C][C]0.618641[/C][/ROW]
[ROW][C]27[/C][C]0.327431[/C][C]0.654861[/C][C]0.672569[/C][/ROW]
[ROW][C]28[/C][C]0.299298[/C][C]0.598596[/C][C]0.700702[/C][/ROW]
[ROW][C]29[/C][C]0.246726[/C][C]0.493451[/C][C]0.753274[/C][/ROW]
[ROW][C]30[/C][C]0.199672[/C][C]0.399344[/C][C]0.800328[/C][/ROW]
[ROW][C]31[/C][C]0.176285[/C][C]0.35257[/C][C]0.823715[/C][/ROW]
[ROW][C]32[/C][C]0.139692[/C][C]0.279383[/C][C]0.860308[/C][/ROW]
[ROW][C]33[/C][C]0.134671[/C][C]0.269343[/C][C]0.865329[/C][/ROW]
[ROW][C]34[/C][C]0.14167[/C][C]0.283339[/C][C]0.85833[/C][/ROW]
[ROW][C]35[/C][C]0.158687[/C][C]0.317374[/C][C]0.841313[/C][/ROW]
[ROW][C]36[/C][C]0.136144[/C][C]0.272289[/C][C]0.863856[/C][/ROW]
[ROW][C]37[/C][C]0.107657[/C][C]0.215314[/C][C]0.892343[/C][/ROW]
[ROW][C]38[/C][C]0.0868421[/C][C]0.173684[/C][C]0.913158[/C][/ROW]
[ROW][C]39[/C][C]0.0694617[/C][C]0.138923[/C][C]0.930538[/C][/ROW]
[ROW][C]40[/C][C]0.0535912[/C][C]0.107182[/C][C]0.946409[/C][/ROW]
[ROW][C]41[/C][C]0.0455535[/C][C]0.091107[/C][C]0.954446[/C][/ROW]
[ROW][C]42[/C][C]0.0340983[/C][C]0.0681967[/C][C]0.965902[/C][/ROW]
[ROW][C]43[/C][C]0.0496436[/C][C]0.0992871[/C][C]0.950356[/C][/ROW]
[ROW][C]44[/C][C]0.0382053[/C][C]0.0764107[/C][C]0.961795[/C][/ROW]
[ROW][C]45[/C][C]0.079517[/C][C]0.159034[/C][C]0.920483[/C][/ROW]
[ROW][C]46[/C][C]0.0638257[/C][C]0.127651[/C][C]0.936174[/C][/ROW]
[ROW][C]47[/C][C]0.0781528[/C][C]0.156306[/C][C]0.921847[/C][/ROW]
[ROW][C]48[/C][C]0.0623411[/C][C]0.124682[/C][C]0.937659[/C][/ROW]
[ROW][C]49[/C][C]0.0740857[/C][C]0.148171[/C][C]0.925914[/C][/ROW]
[ROW][C]50[/C][C]0.0688558[/C][C]0.137712[/C][C]0.931144[/C][/ROW]
[ROW][C]51[/C][C]0.0768994[/C][C]0.153799[/C][C]0.923101[/C][/ROW]
[ROW][C]52[/C][C]0.074451[/C][C]0.148902[/C][C]0.925549[/C][/ROW]
[ROW][C]53[/C][C]0.059569[/C][C]0.119138[/C][C]0.940431[/C][/ROW]
[ROW][C]54[/C][C]0.0623815[/C][C]0.124763[/C][C]0.937619[/C][/ROW]
[ROW][C]55[/C][C]0.0522401[/C][C]0.10448[/C][C]0.94776[/C][/ROW]
[ROW][C]56[/C][C]0.0499506[/C][C]0.0999011[/C][C]0.950049[/C][/ROW]
[ROW][C]57[/C][C]0.0406382[/C][C]0.0812764[/C][C]0.959362[/C][/ROW]
[ROW][C]58[/C][C]0.0323944[/C][C]0.0647888[/C][C]0.967606[/C][/ROW]
[ROW][C]59[/C][C]0.0274244[/C][C]0.0548487[/C][C]0.972576[/C][/ROW]
[ROW][C]60[/C][C]0.0209463[/C][C]0.0418925[/C][C]0.979054[/C][/ROW]
[ROW][C]61[/C][C]0.0233159[/C][C]0.0466318[/C][C]0.976684[/C][/ROW]
[ROW][C]62[/C][C]0.0182241[/C][C]0.0364482[/C][C]0.981776[/C][/ROW]
[ROW][C]63[/C][C]0.013801[/C][C]0.0276021[/C][C]0.986199[/C][/ROW]
[ROW][C]64[/C][C]0.0114326[/C][C]0.0228652[/C][C]0.988567[/C][/ROW]
[ROW][C]65[/C][C]0.0122097[/C][C]0.0244193[/C][C]0.98779[/C][/ROW]
[ROW][C]66[/C][C]0.0108009[/C][C]0.0216018[/C][C]0.989199[/C][/ROW]
[ROW][C]67[/C][C]0.00806566[/C][C]0.0161313[/C][C]0.991934[/C][/ROW]
[ROW][C]68[/C][C]0.0170756[/C][C]0.0341513[/C][C]0.982924[/C][/ROW]
[ROW][C]69[/C][C]0.022404[/C][C]0.0448079[/C][C]0.977596[/C][/ROW]
[ROW][C]70[/C][C]0.0209967[/C][C]0.0419934[/C][C]0.979003[/C][/ROW]
[ROW][C]71[/C][C]0.0180463[/C][C]0.0360926[/C][C]0.981954[/C][/ROW]
[ROW][C]72[/C][C]0.0253376[/C][C]0.0506751[/C][C]0.974662[/C][/ROW]
[ROW][C]73[/C][C]0.0319217[/C][C]0.0638434[/C][C]0.968078[/C][/ROW]
[ROW][C]74[/C][C]0.0447643[/C][C]0.0895286[/C][C]0.955236[/C][/ROW]
[ROW][C]75[/C][C]0.0918919[/C][C]0.183784[/C][C]0.908108[/C][/ROW]
[ROW][C]76[/C][C]0.10409[/C][C]0.20818[/C][C]0.89591[/C][/ROW]
[ROW][C]77[/C][C]0.0894002[/C][C]0.1788[/C][C]0.9106[/C][/ROW]
[ROW][C]78[/C][C]0.0837911[/C][C]0.167582[/C][C]0.916209[/C][/ROW]
[ROW][C]79[/C][C]0.0727549[/C][C]0.14551[/C][C]0.927245[/C][/ROW]
[ROW][C]80[/C][C]0.188709[/C][C]0.377418[/C][C]0.811291[/C][/ROW]
[ROW][C]81[/C][C]0.176925[/C][C]0.35385[/C][C]0.823075[/C][/ROW]
[ROW][C]82[/C][C]0.169187[/C][C]0.338375[/C][C]0.830813[/C][/ROW]
[ROW][C]83[/C][C]0.156157[/C][C]0.312313[/C][C]0.843843[/C][/ROW]
[ROW][C]84[/C][C]0.135202[/C][C]0.270405[/C][C]0.864798[/C][/ROW]
[ROW][C]85[/C][C]0.122003[/C][C]0.244007[/C][C]0.877997[/C][/ROW]
[ROW][C]86[/C][C]0.151654[/C][C]0.303308[/C][C]0.848346[/C][/ROW]
[ROW][C]87[/C][C]0.129998[/C][C]0.259996[/C][C]0.870002[/C][/ROW]
[ROW][C]88[/C][C]0.111739[/C][C]0.223478[/C][C]0.888261[/C][/ROW]
[ROW][C]89[/C][C]0.0945182[/C][C]0.189036[/C][C]0.905482[/C][/ROW]
[ROW][C]90[/C][C]0.0983935[/C][C]0.196787[/C][C]0.901606[/C][/ROW]
[ROW][C]91[/C][C]0.105411[/C][C]0.210822[/C][C]0.894589[/C][/ROW]
[ROW][C]92[/C][C]0.171982[/C][C]0.343963[/C][C]0.828018[/C][/ROW]
[ROW][C]93[/C][C]0.221476[/C][C]0.442953[/C][C]0.778524[/C][/ROW]
[ROW][C]94[/C][C]0.208266[/C][C]0.416532[/C][C]0.791734[/C][/ROW]
[ROW][C]95[/C][C]0.185986[/C][C]0.371971[/C][C]0.814014[/C][/ROW]
[ROW][C]96[/C][C]0.162085[/C][C]0.324169[/C][C]0.837915[/C][/ROW]
[ROW][C]97[/C][C]0.153897[/C][C]0.307793[/C][C]0.846103[/C][/ROW]
[ROW][C]98[/C][C]0.136144[/C][C]0.272287[/C][C]0.863856[/C][/ROW]
[ROW][C]99[/C][C]0.136121[/C][C]0.272242[/C][C]0.863879[/C][/ROW]
[ROW][C]100[/C][C]0.11689[/C][C]0.23378[/C][C]0.88311[/C][/ROW]
[ROW][C]101[/C][C]0.101441[/C][C]0.202881[/C][C]0.898559[/C][/ROW]
[ROW][C]102[/C][C]0.0885806[/C][C]0.177161[/C][C]0.911419[/C][/ROW]
[ROW][C]103[/C][C]0.106755[/C][C]0.213509[/C][C]0.893245[/C][/ROW]
[ROW][C]104[/C][C]0.141188[/C][C]0.282375[/C][C]0.858812[/C][/ROW]
[ROW][C]105[/C][C]0.14671[/C][C]0.29342[/C][C]0.85329[/C][/ROW]
[ROW][C]106[/C][C]0.127954[/C][C]0.255907[/C][C]0.872046[/C][/ROW]
[ROW][C]107[/C][C]0.119298[/C][C]0.238595[/C][C]0.880702[/C][/ROW]
[ROW][C]108[/C][C]0.105548[/C][C]0.211096[/C][C]0.894452[/C][/ROW]
[ROW][C]109[/C][C]0.152256[/C][C]0.304512[/C][C]0.847744[/C][/ROW]
[ROW][C]110[/C][C]0.134957[/C][C]0.269914[/C][C]0.865043[/C][/ROW]
[ROW][C]111[/C][C]0.11612[/C][C]0.232241[/C][C]0.88388[/C][/ROW]
[ROW][C]112[/C][C]0.240259[/C][C]0.480517[/C][C]0.759741[/C][/ROW]
[ROW][C]113[/C][C]0.214898[/C][C]0.429796[/C][C]0.785102[/C][/ROW]
[ROW][C]114[/C][C]0.192173[/C][C]0.384346[/C][C]0.807827[/C][/ROW]
[ROW][C]115[/C][C]0.199384[/C][C]0.398768[/C][C]0.800616[/C][/ROW]
[ROW][C]116[/C][C]0.272796[/C][C]0.545593[/C][C]0.727204[/C][/ROW]
[ROW][C]117[/C][C]0.382223[/C][C]0.764446[/C][C]0.617777[/C][/ROW]
[ROW][C]118[/C][C]0.358786[/C][C]0.717571[/C][C]0.641214[/C][/ROW]
[ROW][C]119[/C][C]0.326993[/C][C]0.653985[/C][C]0.673007[/C][/ROW]
[ROW][C]120[/C][C]0.339345[/C][C]0.67869[/C][C]0.660655[/C][/ROW]
[ROW][C]121[/C][C]0.432288[/C][C]0.864576[/C][C]0.567712[/C][/ROW]
[ROW][C]122[/C][C]0.437931[/C][C]0.875862[/C][C]0.562069[/C][/ROW]
[ROW][C]123[/C][C]0.423323[/C][C]0.846647[/C][C]0.576677[/C][/ROW]
[ROW][C]124[/C][C]0.440573[/C][C]0.881146[/C][C]0.559427[/C][/ROW]
[ROW][C]125[/C][C]0.405914[/C][C]0.811827[/C][C]0.594086[/C][/ROW]
[ROW][C]126[/C][C]0.420132[/C][C]0.840264[/C][C]0.579868[/C][/ROW]
[ROW][C]127[/C][C]0.391905[/C][C]0.78381[/C][C]0.608095[/C][/ROW]
[ROW][C]128[/C][C]0.378011[/C][C]0.756022[/C][C]0.621989[/C][/ROW]
[ROW][C]129[/C][C]0.349662[/C][C]0.699324[/C][C]0.650338[/C][/ROW]
[ROW][C]130[/C][C]0.318165[/C][C]0.636331[/C][C]0.681835[/C][/ROW]
[ROW][C]131[/C][C]0.294215[/C][C]0.588431[/C][C]0.705785[/C][/ROW]
[ROW][C]132[/C][C]0.272221[/C][C]0.544442[/C][C]0.727779[/C][/ROW]
[ROW][C]133[/C][C]0.252591[/C][C]0.505181[/C][C]0.747409[/C][/ROW]
[ROW][C]134[/C][C]0.24605[/C][C]0.492099[/C][C]0.75395[/C][/ROW]
[ROW][C]135[/C][C]0.270322[/C][C]0.540644[/C][C]0.729678[/C][/ROW]
[ROW][C]136[/C][C]0.473453[/C][C]0.946906[/C][C]0.526547[/C][/ROW]
[ROW][C]137[/C][C]0.442975[/C][C]0.88595[/C][C]0.557025[/C][/ROW]
[ROW][C]138[/C][C]0.45615[/C][C]0.9123[/C][C]0.54385[/C][/ROW]
[ROW][C]139[/C][C]0.422503[/C][C]0.845006[/C][C]0.577497[/C][/ROW]
[ROW][C]140[/C][C]0.422922[/C][C]0.845844[/C][C]0.577078[/C][/ROW]
[ROW][C]141[/C][C]0.394466[/C][C]0.788933[/C][C]0.605534[/C][/ROW]
[ROW][C]142[/C][C]0.435373[/C][C]0.870745[/C][C]0.564627[/C][/ROW]
[ROW][C]143[/C][C]0.412333[/C][C]0.824667[/C][C]0.587667[/C][/ROW]
[ROW][C]144[/C][C]0.693647[/C][C]0.612706[/C][C]0.306353[/C][/ROW]
[ROW][C]145[/C][C]0.723643[/C][C]0.552714[/C][C]0.276357[/C][/ROW]
[ROW][C]146[/C][C]0.820431[/C][C]0.359137[/C][C]0.179569[/C][/ROW]
[ROW][C]147[/C][C]0.803693[/C][C]0.392615[/C][C]0.196307[/C][/ROW]
[ROW][C]148[/C][C]0.793729[/C][C]0.412542[/C][C]0.206271[/C][/ROW]
[ROW][C]149[/C][C]0.77662[/C][C]0.446759[/C][C]0.22338[/C][/ROW]
[ROW][C]150[/C][C]0.799524[/C][C]0.400952[/C][C]0.200476[/C][/ROW]
[ROW][C]151[/C][C]0.775239[/C][C]0.449521[/C][C]0.224761[/C][/ROW]
[ROW][C]152[/C][C]0.790686[/C][C]0.418628[/C][C]0.209314[/C][/ROW]
[ROW][C]153[/C][C]0.824904[/C][C]0.350193[/C][C]0.175096[/C][/ROW]
[ROW][C]154[/C][C]0.80596[/C][C]0.388079[/C][C]0.19404[/C][/ROW]
[ROW][C]155[/C][C]0.78562[/C][C]0.428761[/C][C]0.21438[/C][/ROW]
[ROW][C]156[/C][C]0.785312[/C][C]0.429377[/C][C]0.214688[/C][/ROW]
[ROW][C]157[/C][C]0.81657[/C][C]0.36686[/C][C]0.18343[/C][/ROW]
[ROW][C]158[/C][C]0.808302[/C][C]0.383396[/C][C]0.191698[/C][/ROW]
[ROW][C]159[/C][C]0.800252[/C][C]0.399495[/C][C]0.199748[/C][/ROW]
[ROW][C]160[/C][C]0.845486[/C][C]0.309029[/C][C]0.154514[/C][/ROW]
[ROW][C]161[/C][C]0.840372[/C][C]0.319257[/C][C]0.159628[/C][/ROW]
[ROW][C]162[/C][C]0.861311[/C][C]0.277378[/C][C]0.138689[/C][/ROW]
[ROW][C]163[/C][C]0.90584[/C][C]0.188321[/C][C]0.0941604[/C][/ROW]
[ROW][C]164[/C][C]0.915293[/C][C]0.169415[/C][C]0.0847074[/C][/ROW]
[ROW][C]165[/C][C]0.933074[/C][C]0.133853[/C][C]0.0669263[/C][/ROW]
[ROW][C]166[/C][C]0.927012[/C][C]0.145975[/C][C]0.0729875[/C][/ROW]
[ROW][C]167[/C][C]0.913682[/C][C]0.172636[/C][C]0.0863181[/C][/ROW]
[ROW][C]168[/C][C]0.934409[/C][C]0.131181[/C][C]0.0655905[/C][/ROW]
[ROW][C]169[/C][C]0.938725[/C][C]0.12255[/C][C]0.0612749[/C][/ROW]
[ROW][C]170[/C][C]0.957413[/C][C]0.085173[/C][C]0.0425865[/C][/ROW]
[ROW][C]171[/C][C]0.954551[/C][C]0.090897[/C][C]0.0454485[/C][/ROW]
[ROW][C]172[/C][C]0.947798[/C][C]0.104404[/C][C]0.0522018[/C][/ROW]
[ROW][C]173[/C][C]0.94018[/C][C]0.11964[/C][C]0.0598202[/C][/ROW]
[ROW][C]174[/C][C]0.953589[/C][C]0.0928228[/C][C]0.0464114[/C][/ROW]
[ROW][C]175[/C][C]0.976915[/C][C]0.0461693[/C][C]0.0230847[/C][/ROW]
[ROW][C]176[/C][C]0.972939[/C][C]0.0541215[/C][C]0.0270607[/C][/ROW]
[ROW][C]177[/C][C]0.967521[/C][C]0.0649575[/C][C]0.0324787[/C][/ROW]
[ROW][C]178[/C][C]0.961551[/C][C]0.0768982[/C][C]0.0384491[/C][/ROW]
[ROW][C]179[/C][C]0.953952[/C][C]0.0920959[/C][C]0.046048[/C][/ROW]
[ROW][C]180[/C][C]0.947517[/C][C]0.104965[/C][C]0.0524827[/C][/ROW]
[ROW][C]181[/C][C]0.938[/C][C]0.123999[/C][C]0.0619997[/C][/ROW]
[ROW][C]182[/C][C]0.93447[/C][C]0.13106[/C][C]0.0655299[/C][/ROW]
[ROW][C]183[/C][C]0.926736[/C][C]0.146528[/C][C]0.0732642[/C][/ROW]
[ROW][C]184[/C][C]0.937206[/C][C]0.125588[/C][C]0.0627941[/C][/ROW]
[ROW][C]185[/C][C]0.924019[/C][C]0.151961[/C][C]0.0759805[/C][/ROW]
[ROW][C]186[/C][C]0.916433[/C][C]0.167134[/C][C]0.0835668[/C][/ROW]
[ROW][C]187[/C][C]0.904167[/C][C]0.191665[/C][C]0.0958327[/C][/ROW]
[ROW][C]188[/C][C]0.927022[/C][C]0.145957[/C][C]0.0729783[/C][/ROW]
[ROW][C]189[/C][C]0.915458[/C][C]0.169084[/C][C]0.084542[/C][/ROW]
[ROW][C]190[/C][C]0.933965[/C][C]0.13207[/C][C]0.0660349[/C][/ROW]
[ROW][C]191[/C][C]0.946034[/C][C]0.107932[/C][C]0.0539662[/C][/ROW]
[ROW][C]192[/C][C]0.948893[/C][C]0.102213[/C][C]0.0511066[/C][/ROW]
[ROW][C]193[/C][C]0.940332[/C][C]0.119335[/C][C]0.0596676[/C][/ROW]
[ROW][C]194[/C][C]0.937309[/C][C]0.125381[/C][C]0.0626907[/C][/ROW]
[ROW][C]195[/C][C]0.923831[/C][C]0.152338[/C][C]0.0761688[/C][/ROW]
[ROW][C]196[/C][C]0.918771[/C][C]0.162458[/C][C]0.0812291[/C][/ROW]
[ROW][C]197[/C][C]0.927946[/C][C]0.144107[/C][C]0.0720535[/C][/ROW]
[ROW][C]198[/C][C]0.918805[/C][C]0.16239[/C][C]0.0811949[/C][/ROW]
[ROW][C]199[/C][C]0.901436[/C][C]0.197128[/C][C]0.0985638[/C][/ROW]
[ROW][C]200[/C][C]0.884317[/C][C]0.231366[/C][C]0.115683[/C][/ROW]
[ROW][C]201[/C][C]0.873421[/C][C]0.253158[/C][C]0.126579[/C][/ROW]
[ROW][C]202[/C][C]0.854334[/C][C]0.291331[/C][C]0.145666[/C][/ROW]
[ROW][C]203[/C][C]0.841857[/C][C]0.316286[/C][C]0.158143[/C][/ROW]
[ROW][C]204[/C][C]0.814894[/C][C]0.370213[/C][C]0.185106[/C][/ROW]
[ROW][C]205[/C][C]0.785894[/C][C]0.428212[/C][C]0.214106[/C][/ROW]
[ROW][C]206[/C][C]0.762072[/C][C]0.475856[/C][C]0.237928[/C][/ROW]
[ROW][C]207[/C][C]0.735706[/C][C]0.528588[/C][C]0.264294[/C][/ROW]
[ROW][C]208[/C][C]0.719027[/C][C]0.561946[/C][C]0.280973[/C][/ROW]
[ROW][C]209[/C][C]0.683392[/C][C]0.633216[/C][C]0.316608[/C][/ROW]
[ROW][C]210[/C][C]0.653954[/C][C]0.692093[/C][C]0.346046[/C][/ROW]
[ROW][C]211[/C][C]0.610066[/C][C]0.779867[/C][C]0.389934[/C][/ROW]
[ROW][C]212[/C][C]0.741038[/C][C]0.517924[/C][C]0.258962[/C][/ROW]
[ROW][C]213[/C][C]0.79359[/C][C]0.412819[/C][C]0.20641[/C][/ROW]
[ROW][C]214[/C][C]0.757318[/C][C]0.485364[/C][C]0.242682[/C][/ROW]
[ROW][C]215[/C][C]0.719852[/C][C]0.560295[/C][C]0.280148[/C][/ROW]
[ROW][C]216[/C][C]0.787109[/C][C]0.425783[/C][C]0.212891[/C][/ROW]
[ROW][C]217[/C][C]0.751933[/C][C]0.496134[/C][C]0.248067[/C][/ROW]
[ROW][C]218[/C][C]0.730225[/C][C]0.539549[/C][C]0.269775[/C][/ROW]
[ROW][C]219[/C][C]0.691676[/C][C]0.616648[/C][C]0.308324[/C][/ROW]
[ROW][C]220[/C][C]0.712623[/C][C]0.574753[/C][C]0.287377[/C][/ROW]
[ROW][C]221[/C][C]0.669559[/C][C]0.660881[/C][C]0.330441[/C][/ROW]
[ROW][C]222[/C][C]0.631965[/C][C]0.73607[/C][C]0.368035[/C][/ROW]
[ROW][C]223[/C][C]0.589231[/C][C]0.821537[/C][C]0.410769[/C][/ROW]
[ROW][C]224[/C][C]0.538956[/C][C]0.922089[/C][C]0.461044[/C][/ROW]
[ROW][C]225[/C][C]0.588733[/C][C]0.822534[/C][C]0.411267[/C][/ROW]
[ROW][C]226[/C][C]0.644093[/C][C]0.711813[/C][C]0.355907[/C][/ROW]
[ROW][C]227[/C][C]0.617406[/C][C]0.765188[/C][C]0.382594[/C][/ROW]
[ROW][C]228[/C][C]0.584051[/C][C]0.831898[/C][C]0.415949[/C][/ROW]
[ROW][C]229[/C][C]0.527833[/C][C]0.944335[/C][C]0.472167[/C][/ROW]
[ROW][C]230[/C][C]0.499981[/C][C]0.999962[/C][C]0.500019[/C][/ROW]
[ROW][C]231[/C][C]0.474052[/C][C]0.948104[/C][C]0.525948[/C][/ROW]
[ROW][C]232[/C][C]0.660121[/C][C]0.679758[/C][C]0.339879[/C][/ROW]
[ROW][C]233[/C][C]0.655429[/C][C]0.689141[/C][C]0.344571[/C][/ROW]
[ROW][C]234[/C][C]0.756726[/C][C]0.486549[/C][C]0.243274[/C][/ROW]
[ROW][C]235[/C][C]0.704203[/C][C]0.591593[/C][C]0.295797[/C][/ROW]
[ROW][C]236[/C][C]0.673892[/C][C]0.652217[/C][C]0.326108[/C][/ROW]
[ROW][C]237[/C][C]0.685197[/C][C]0.629607[/C][C]0.314803[/C][/ROW]
[ROW][C]238[/C][C]0.77224[/C][C]0.455521[/C][C]0.22776[/C][/ROW]
[ROW][C]239[/C][C]0.715706[/C][C]0.568587[/C][C]0.284294[/C][/ROW]
[ROW][C]240[/C][C]0.755461[/C][C]0.489079[/C][C]0.244539[/C][/ROW]
[ROW][C]241[/C][C]0.71628[/C][C]0.56744[/C][C]0.28372[/C][/ROW]
[ROW][C]242[/C][C]0.664693[/C][C]0.670614[/C][C]0.335307[/C][/ROW]
[ROW][C]243[/C][C]0.601122[/C][C]0.797756[/C][C]0.398878[/C][/ROW]
[ROW][C]244[/C][C]0.52144[/C][C]0.95712[/C][C]0.47856[/C][/ROW]
[ROW][C]245[/C][C]0.82412[/C][C]0.35176[/C][C]0.17588[/C][/ROW]
[ROW][C]246[/C][C]0.89532[/C][C]0.209361[/C][C]0.10468[/C][/ROW]
[ROW][C]247[/C][C]0.883553[/C][C]0.232895[/C][C]0.116447[/C][/ROW]
[ROW][C]248[/C][C]0.82401[/C][C]0.35198[/C][C]0.17599[/C][/ROW]
[ROW][C]249[/C][C]0.752415[/C][C]0.49517[/C][C]0.247585[/C][/ROW]
[ROW][C]250[/C][C]0.883562[/C][C]0.232876[/C][C]0.116438[/C][/ROW]
[ROW][C]251[/C][C]0.872467[/C][C]0.255066[/C][C]0.127533[/C][/ROW]
[ROW][C]252[/C][C]0.78137[/C][C]0.43726[/C][C]0.21863[/C][/ROW]
[ROW][C]253[/C][C]0.771001[/C][C]0.457998[/C][C]0.228999[/C][/ROW]
[ROW][C]254[/C][C]0.722199[/C][C]0.555602[/C][C]0.277801[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253721&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253721&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
100.2372710.4745410.762729
110.1165260.2330530.883474
120.5658920.8682150.434108
130.4796570.9593150.520343
140.5168420.9663160.483158
150.5286940.9426120.471306
160.4781640.9563280.521836
170.414850.82970.58515
180.4768140.9536280.523186
190.429990.8599810.57001
200.3607740.7215480.639226
210.2863560.5727120.713644
220.2846930.5693860.715307
230.2310520.4621040.768948
240.2515090.5030180.748491
250.2685220.5370440.731478
260.3813590.7627170.618641
270.3274310.6548610.672569
280.2992980.5985960.700702
290.2467260.4934510.753274
300.1996720.3993440.800328
310.1762850.352570.823715
320.1396920.2793830.860308
330.1346710.2693430.865329
340.141670.2833390.85833
350.1586870.3173740.841313
360.1361440.2722890.863856
370.1076570.2153140.892343
380.08684210.1736840.913158
390.06946170.1389230.930538
400.05359120.1071820.946409
410.04555350.0911070.954446
420.03409830.06819670.965902
430.04964360.09928710.950356
440.03820530.07641070.961795
450.0795170.1590340.920483
460.06382570.1276510.936174
470.07815280.1563060.921847
480.06234110.1246820.937659
490.07408570.1481710.925914
500.06885580.1377120.931144
510.07689940.1537990.923101
520.0744510.1489020.925549
530.0595690.1191380.940431
540.06238150.1247630.937619
550.05224010.104480.94776
560.04995060.09990110.950049
570.04063820.08127640.959362
580.03239440.06478880.967606
590.02742440.05484870.972576
600.02094630.04189250.979054
610.02331590.04663180.976684
620.01822410.03644820.981776
630.0138010.02760210.986199
640.01143260.02286520.988567
650.01220970.02441930.98779
660.01080090.02160180.989199
670.008065660.01613130.991934
680.01707560.03415130.982924
690.0224040.04480790.977596
700.02099670.04199340.979003
710.01804630.03609260.981954
720.02533760.05067510.974662
730.03192170.06384340.968078
740.04476430.08952860.955236
750.09189190.1837840.908108
760.104090.208180.89591
770.08940020.17880.9106
780.08379110.1675820.916209
790.07275490.145510.927245
800.1887090.3774180.811291
810.1769250.353850.823075
820.1691870.3383750.830813
830.1561570.3123130.843843
840.1352020.2704050.864798
850.1220030.2440070.877997
860.1516540.3033080.848346
870.1299980.2599960.870002
880.1117390.2234780.888261
890.09451820.1890360.905482
900.09839350.1967870.901606
910.1054110.2108220.894589
920.1719820.3439630.828018
930.2214760.4429530.778524
940.2082660.4165320.791734
950.1859860.3719710.814014
960.1620850.3241690.837915
970.1538970.3077930.846103
980.1361440.2722870.863856
990.1361210.2722420.863879
1000.116890.233780.88311
1010.1014410.2028810.898559
1020.08858060.1771610.911419
1030.1067550.2135090.893245
1040.1411880.2823750.858812
1050.146710.293420.85329
1060.1279540.2559070.872046
1070.1192980.2385950.880702
1080.1055480.2110960.894452
1090.1522560.3045120.847744
1100.1349570.2699140.865043
1110.116120.2322410.88388
1120.2402590.4805170.759741
1130.2148980.4297960.785102
1140.1921730.3843460.807827
1150.1993840.3987680.800616
1160.2727960.5455930.727204
1170.3822230.7644460.617777
1180.3587860.7175710.641214
1190.3269930.6539850.673007
1200.3393450.678690.660655
1210.4322880.8645760.567712
1220.4379310.8758620.562069
1230.4233230.8466470.576677
1240.4405730.8811460.559427
1250.4059140.8118270.594086
1260.4201320.8402640.579868
1270.3919050.783810.608095
1280.3780110.7560220.621989
1290.3496620.6993240.650338
1300.3181650.6363310.681835
1310.2942150.5884310.705785
1320.2722210.5444420.727779
1330.2525910.5051810.747409
1340.246050.4920990.75395
1350.2703220.5406440.729678
1360.4734530.9469060.526547
1370.4429750.885950.557025
1380.456150.91230.54385
1390.4225030.8450060.577497
1400.4229220.8458440.577078
1410.3944660.7889330.605534
1420.4353730.8707450.564627
1430.4123330.8246670.587667
1440.6936470.6127060.306353
1450.7236430.5527140.276357
1460.8204310.3591370.179569
1470.8036930.3926150.196307
1480.7937290.4125420.206271
1490.776620.4467590.22338
1500.7995240.4009520.200476
1510.7752390.4495210.224761
1520.7906860.4186280.209314
1530.8249040.3501930.175096
1540.805960.3880790.19404
1550.785620.4287610.21438
1560.7853120.4293770.214688
1570.816570.366860.18343
1580.8083020.3833960.191698
1590.8002520.3994950.199748
1600.8454860.3090290.154514
1610.8403720.3192570.159628
1620.8613110.2773780.138689
1630.905840.1883210.0941604
1640.9152930.1694150.0847074
1650.9330740.1338530.0669263
1660.9270120.1459750.0729875
1670.9136820.1726360.0863181
1680.9344090.1311810.0655905
1690.9387250.122550.0612749
1700.9574130.0851730.0425865
1710.9545510.0908970.0454485
1720.9477980.1044040.0522018
1730.940180.119640.0598202
1740.9535890.09282280.0464114
1750.9769150.04616930.0230847
1760.9729390.05412150.0270607
1770.9675210.06495750.0324787
1780.9615510.07689820.0384491
1790.9539520.09209590.046048
1800.9475170.1049650.0524827
1810.9380.1239990.0619997
1820.934470.131060.0655299
1830.9267360.1465280.0732642
1840.9372060.1255880.0627941
1850.9240190.1519610.0759805
1860.9164330.1671340.0835668
1870.9041670.1916650.0958327
1880.9270220.1459570.0729783
1890.9154580.1690840.084542
1900.9339650.132070.0660349
1910.9460340.1079320.0539662
1920.9488930.1022130.0511066
1930.9403320.1193350.0596676
1940.9373090.1253810.0626907
1950.9238310.1523380.0761688
1960.9187710.1624580.0812291
1970.9279460.1441070.0720535
1980.9188050.162390.0811949
1990.9014360.1971280.0985638
2000.8843170.2313660.115683
2010.8734210.2531580.126579
2020.8543340.2913310.145666
2030.8418570.3162860.158143
2040.8148940.3702130.185106
2050.7858940.4282120.214106
2060.7620720.4758560.237928
2070.7357060.5285880.264294
2080.7190270.5619460.280973
2090.6833920.6332160.316608
2100.6539540.6920930.346046
2110.6100660.7798670.389934
2120.7410380.5179240.258962
2130.793590.4128190.20641
2140.7573180.4853640.242682
2150.7198520.5602950.280148
2160.7871090.4257830.212891
2170.7519330.4961340.248067
2180.7302250.5395490.269775
2190.6916760.6166480.308324
2200.7126230.5747530.287377
2210.6695590.6608810.330441
2220.6319650.736070.368035
2230.5892310.8215370.410769
2240.5389560.9220890.461044
2250.5887330.8225340.411267
2260.6440930.7118130.355907
2270.6174060.7651880.382594
2280.5840510.8318980.415949
2290.5278330.9443350.472167
2300.4999810.9999620.500019
2310.4740520.9481040.525948
2320.6601210.6797580.339879
2330.6554290.6891410.344571
2340.7567260.4865490.243274
2350.7042030.5915930.295797
2360.6738920.6522170.326108
2370.6851970.6296070.314803
2380.772240.4555210.22776
2390.7157060.5685870.284294
2400.7554610.4890790.244539
2410.716280.567440.28372
2420.6646930.6706140.335307
2430.6011220.7977560.398878
2440.521440.957120.47856
2450.824120.351760.17588
2460.895320.2093610.10468
2470.8835530.2328950.116447
2480.824010.351980.17599
2490.7524150.495170.247585
2500.8835620.2328760.116438
2510.8724670.2550660.127533
2520.781370.437260.21863
2530.7710010.4579980.228999
2540.7221990.5556020.277801






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level130.0530612NOK
10% type I error level310.126531NOK

\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 & 13 & 0.0530612 & NOK \tabularnewline
10% type I error level & 31 & 0.126531 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253721&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]13[/C][C]0.0530612[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]31[/C][C]0.126531[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253721&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253721&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 level130.0530612NOK
10% type I error level310.126531NOK


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')
}