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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 computationThu, 14 Nov 2013 16:09:28 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/14/t1384463632n9yty8rw7vs5ein.htm/, Retrieved Mon, 29 Apr 2024 11:30:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=225428, Retrieved Mon, 29 Apr 2024 11:30:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Multiple Lineair ...] [2013-11-14 21:09:28] [00fa7281f92d923399435cbd3b96dfd1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 12 14 12 53 32
39 32 11 18 11 83 51
30 35 15 11 14 66 42
31 33 6 12 12 67 41
34 37 13 16 21 76 46
35 29 10 18 12 78 47
39 31 12 14 22 53 37
34 36 14 14 11 80 49
36 35 12 15 10 74 45
37 38 9 15 13 76 47
38 31 10 17 10 79 49
36 34 12 19 8 54 33
38 35 12 10 15 67 42
39 38 11 16 14 54 33
33 37 15 18 10 87 53
32 33 12 14 14 58 36
36 32 10 14 14 75 45
38 38 12 17 11 88 54
39 38 11 14 10 64 41
32 32 12 16 13 57 36
32 33 11 18 9.5 66 41
31 31 12 11 14 68 44
39 38 13 14 12 54 33
37 39 11 12 14 56 37
39 32 12 17 11 86 52
41 32 13 9 9 80 47
36 35 10 16 11 76 43
33 37 14 14 15 69 44
33 33 12 15 14 78 45
34 33 10 11 13 67 44
31 31 12 16 9 80 49
27 32 8 13 15 54 33
37 31 10 17 10 71 43
34 37 12 15 11 84 54
34 30 12 14 13 74 42
32 33 7 16 8 71 44
29 31 9 9 20 63 37
36 33 12 15 12 71 43
29 31 10 17 10 76 46
35 33 10 13 10 69 42
37 32 10 15 9 74 45
34 33 12 16 14 75 44
38 32 15 16 8 54 33
35 33 10 12 14 52 31
38 28 10 15 11 69 42
37 35 12 11 13 68 40
38 39 13 15 9 65 43
33 34 11 15 11 75 46
36 38 11 17 15 74 42
38 32 12 13 11 75 45
32 38 14 16 10 72 44
32 30 10 14 14 67 40
32 33 12 11 18 63 37
34 38 13 12 14 62 46
32 32 5 12 11 63 36
37 35 6 15 14.5 76 47
39 34 12 16 13 74 45
29 34 12 15 9 67 42
37 36 11 12 10 73 43
35 34 10 12 15 70 43
30 28 7 8 20 53 32
38 34 12 13 12 77 45
34 35 14 11 12 80 48
31 35 11 14 14 52 31
34 31 12 15 13 54 33
35 37 13 10 11 80 49
36 35 14 11 17 66 42
30 27 11 12 12 73 41
39 40 12 15 13 63 38
35 37 12 15 14 69 42
38 36 8 14 13 67 44
31 38 11 16 15 54 33
34 39 14 15 13 81 48
38 41 14 15 10 69 40
34 27 12 13 11 84 50
39 30 9 12 19 80 49
37 37 13 17 13 70 43
34 31 11 13 17 69 44
28 31 12 15 13 77 47
37 27 12 13 9 54 33
33 36 12 15 11 79 46
35 37 12 15 9 71 45
37 33 12 16 12 73 43
32 34 11 15 12 72 44
33 31 10 14 13 77 47
38 39 9 15 13 75 45
33 34 12 14 12 69 42
29 32 12 13 15 54 33
33 33 12 7 22 70 43
31 36 9 17 13 73 46
36 32 15 13 15 54 33
35 41 12 15 13 77 46
32 28 12 14 15 82 48
29 30 12 13 12.5 80 47
39 36 10 16 11 80 47
37 35 13 12 16 69 43
35 31 9 14 11 78 46
37 34 12 17 11 81 48
32 36 10 15 10 76 46
38 36 14 17 10 76 45
37 35 11 12 16 73 45
36 37 15 16 12 85 52
32 28 11 11 11 66 42
33 39 11 15 16 79 47
40 32 12 9 19 68 41
38 35 12 16 11 76 47
41 39 12 15 16 71 43
36 35 11 10 15 54 33
43 42 7 10 24 46 30
30 34 12 15 14 85 52
31 33 14 11 15 74 44
32 41 11 13 11 88 55
32 33 11 14 15 38 11
37 34 10 18 12 76 47
37 32 13 16 10 86 53
33 40 13 14 14 54 33
34 40 8 14 13 67 44
33 35 11 14 9 69 42
38 36 12 14 15 90 55
33 37 11 12 15 54 33
31 27 13 14 14 76 46
38 39 12 15 11 89 54
37 38 14 15 8 76 47
36 31 13 15 11 73 45
31 33 15 13 11 79 47
39 32 10 17 8 90 55
44 39 11 17 10 74 44
33 36 9 19 11 81 53
35 33 11 15 13 72 44
32 33 10 13 11 71 42
28 32 11 9 20 66 40
40 37 8 15 10 77 46
27 30 11 15 15 65 40
37 38 12 15 12 74 46
32 29 12 16 14 85 53
28 22 9 11 23 54 33
34 35 11 14 14 63 42
30 35 10 11 16 54 35
35 34 8 15 11 64 40
31 35 9 13 12 69 41
32 34 8 15 10 54 33
30 37 9 16 14 84 51
30 35 15 14 12 86 53
31 23 11 15 12 77 46
40 31 8 16 11 89 55
32 27 13 16 12 76 47
36 36 12 11 13 60 38
32 31 12 12 11 75 46
35 32 9 9 19 73 46
38 39 7 16 12 85 53
42 37 13 13 17 79 47
34 38 9 16 9 71 41
35 39 6 12 12 72 44
38 34 8 9 19 69 43
33 31 8 13 18 78 51
36 32 15 13 15 54 33
32 37 6 14 14 69 43
33 36 9 19 11 81 53
34 32 11 13 9 84 51
32 38 8 12 18 84 50
34 36 8 13 16 69 46
27 26 10 10 24 66 43
31 26 8 14 14 81 47
38 33 14 16 20 82 50
34 39 10 10 18 72 43
24 30 8 11 23 54 33
30 33 11 14 12 78 48
26 25 12 12 14 74 44
34 38 12 9 16 82 50
27 37 12 9 18 73 41
37 31 5 11 20 55 34
36 37 12 16 12 72 44
41 35 10 9 12 78 47
29 25 7 13 17 59 35
36 28 12 16 13 72 44
32 35 11 13 9 78 44
37 33 8 9 16 68 43
30 30 9 12 18 69 41
31 31 10 16 10 67 41
38 37 9 11 14 74 42
36 36 12 14 11 54 33
35 30 6 13 9 67 41
31 36 15 15 11 70 44
38 32 12 14 10 80 48
22 28 12 16 11 89 55
32 36 12 13 19 76 44
36 34 11 14 14 74 43
39 31 7 15 12 87 52
28 28 7 13 14 54 30
32 36 5 11 21 61 39
32 36 12 11 13 38 11
38 40 12 14 10 75 44
32 33 3 15 15 69 42
35 37 11 11 16 62 41
32 32 10 15 14 72 44
37 38 12 12 12 70 44
34 31 9 14 19 79 48
33 37 12 14 15 87 53
33 33 9 8 19 62 37
26 32 12 13 13 77 44
30 30 12 9 17 69 44
24 30 10 15 12 69 40
34 31 9 17 11 75 42
34 32 12 13 14 54 35
33 34 8 15 11 72 43
34 36 11 15 13 74 45
35 37 11 14 12 85 55
35 36 12 16 15 52 31
36 33 10 13 14 70 44
34 33 10 16 12 84 50
34 33 12 9 17 64 40
41 44 12 16 11 84 53
32 39 11 11 18 87 54
30 32 8 10 13 79 49
35 35 12 11 17 67 40
28 25 10 15 13 65 41
33 35 11 17 11 85 52
39 34 10 14 12 83 52
36 35 8 8 22 61 36
36 39 12 15 14 82 52
35 33 12 11 12 76 46
38 36 10 16 12 58 31
33 32 12 10 17 72 44
31 32 9 15 9 72 44
34 36 9 9 21 38 11
32 36 6 16 10 78 46
31 32 10 19 11 54 33
33 34 9 12 12 63 34
34 33 9 8 23 66 42
34 35 9 11 13 70 43
34 30 6 14 12 71 43
33 38 10 9 16 67 44
32 34 6 15 9 58 36
41 33 14 13 17 72 46
34 32 10 16 9 72 44
36 31 10 11 14 70 43
37 30 6 12 17 76 50
36 27 12 13 13 50 33
29 31 12 10 11 72 43
37 30 7 11 12 72 44
27 32 8 12 10 88 53
35 35 11 8 19 53 34
28 28 3 12 16 58 35
35 33 6 12 16 66 40
37 31 10 15 14 82 53
29 35 8 11 20 69 42
32 35 9 13 15 68 43
36 32 9 14 23 44 29
19 21 8 10 20 56 36
21 20 9 12 16 53 30
31 34 7 15 14 70 42
33 32 7 13 17 78 47
36 34 6 13 11 71 44
33 32 9 13 13 72 45
37 33 10 12 17 68 44
34 33 11 12 15 67 43
35 37 12 9 21 75 43
31 32 8 9 18 62 40
37 34 11 15 15 67 41
35 30 3 10 8 83 52
27 30 11 14 12 64 38
34 38 12 15 12 68 41
40 36 7 7 22 62 39
29 32 9 14 12 72 43

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 14 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225428&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]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225428&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225428&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 time14 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 17.776 + 0.441888Separate[t] + 0.0557129Software[t] + 0.0508634Happiness[t] -0.0664862Depression[t] -0.0708645Sport1[t] + 0.139818Sport2[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Connected[t] =  +  17.776 +  0.441888Separate[t] +  0.0557129Software[t] +  0.0508634Happiness[t] -0.0664862Depression[t] -0.0708645Sport1[t] +  0.139818Sport2[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225428&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Connected[t] =  +  17.776 +  0.441888Separate[t] +  0.0557129Software[t] +  0.0508634Happiness[t] -0.0664862Depression[t] -0.0708645Sport1[t] +  0.139818Sport2[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225428&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225428&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 17.776 + 0.441888Separate[t] + 0.0557129Software[t] + 0.0508634Happiness[t] -0.0664862Depression[t] -0.0708645Sport1[t] + 0.139818Sport2[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)17.7763.254925.4611.11486e-075.57432e-08
Separate0.4418880.05767427.6623.74844e-131.87422e-13
Software0.05571290.09290030.59970.5492310.274615
Happiness0.05086340.1038870.48960.6248320.312416
Depression-0.06648620.076198-0.87250.3837260.191863
Sport1-0.07086450.0677131-1.0470.2962950.148148
Sport20.1398180.1008361.3870.1667670.0833837

\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) & 17.776 & 3.25492 & 5.461 & 1.11486e-07 & 5.57432e-08 \tabularnewline
Separate & 0.441888 & 0.0576742 & 7.662 & 3.74844e-13 & 1.87422e-13 \tabularnewline
Software & 0.0557129 & 0.0929003 & 0.5997 & 0.549231 & 0.274615 \tabularnewline
Happiness & 0.0508634 & 0.103887 & 0.4896 & 0.624832 & 0.312416 \tabularnewline
Depression & -0.0664862 & 0.076198 & -0.8725 & 0.383726 & 0.191863 \tabularnewline
Sport1 & -0.0708645 & 0.0677131 & -1.047 & 0.296295 & 0.148148 \tabularnewline
Sport2 & 0.139818 & 0.100836 & 1.387 & 0.166767 & 0.0833837 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225428&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]17.776[/C][C]3.25492[/C][C]5.461[/C][C]1.11486e-07[/C][C]5.57432e-08[/C][/ROW]
[ROW][C]Separate[/C][C]0.441888[/C][C]0.0576742[/C][C]7.662[/C][C]3.74844e-13[/C][C]1.87422e-13[/C][/ROW]
[ROW][C]Software[/C][C]0.0557129[/C][C]0.0929003[/C][C]0.5997[/C][C]0.549231[/C][C]0.274615[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0508634[/C][C]0.103887[/C][C]0.4896[/C][C]0.624832[/C][C]0.312416[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0664862[/C][C]0.076198[/C][C]-0.8725[/C][C]0.383726[/C][C]0.191863[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.0708645[/C][C]0.0677131[/C][C]-1.047[/C][C]0.296295[/C][C]0.148148[/C][/ROW]
[ROW][C]Sport2[/C][C]0.139818[/C][C]0.100836[/C][C]1.387[/C][C]0.166767[/C][C]0.0833837[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225428&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225428&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)17.7763.254925.4611.11486e-075.57432e-08
Separate0.4418880.05767427.6623.74844e-131.87422e-13
Software0.05571290.09290030.59970.5492310.274615
Happiness0.05086340.1038870.48960.6248320.312416
Depression-0.06648620.076198-0.87250.3837260.191863
Sport1-0.07086450.0677131-1.0470.2962950.148148
Sport20.1398180.1008361.3870.1667670.0833837






Multiple Linear Regression - Regression Statistics
Multiple R0.475255
R-squared0.225867
Adjusted R-squared0.207794
F-TEST (value)12.4974
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value2.34612e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.3791
Sum Squared Residuals2934.5

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.475255 \tabularnewline
R-squared & 0.225867 \tabularnewline
Adjusted R-squared & 0.207794 \tabularnewline
F-TEST (value) & 12.4974 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 257 \tabularnewline
p-value & 2.34612e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.3791 \tabularnewline
Sum Squared Residuals & 2934.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225428&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.475255[/C][/ROW]
[ROW][C]R-squared[/C][C]0.225867[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.207794[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]12.4974[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]257[/C][/ROW]
[ROW][C]p-value[/C][C]2.34612e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.3791[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2934.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225428&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225428&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 R0.475255
R-squared0.225867
Adjusted R-squared0.207794
F-TEST (value)12.4974
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value2.34612e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.3791
Sum Squared Residuals2934.5






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14135.86895.13112
23933.96245.03762
33034.9017-4.90173
43133.4897-2.48969
53435.3136-1.31362
63532.30962.69043
73932.80996.19011
83435.6266-1.62657
93635.05650.943474
103736.15350.8465
113833.48424.51578
123634.69051.30946
133834.54643.45362
143935.85093.14913
153336.4573-3.45734
163233.7314-1.73141
173633.23182.76824
183836.68371.31631
193936.4252.57501
203233.5286-1.5286
213234.3105-2.31051
223133.1049-2.10494
233935.99353.00646
243736.50680.493151
253933.89455.10555
264133.40237.59767
273634.50811.49189
283335.8829-2.88294
293333.6233-0.623347
303434.0146-0.0146449
313133.5404-2.54041
322732.8133-5.81333
333733.21223.78777
343436.4235-2.42353
353432.17731.82269
363234.1508-2.1508
372931.8128-2.81276
383633.97272.02727
392933.2774-4.27736
403533.89451.10553
413733.68593.31408
423433.7470.253014
433833.82134.17869
443533.24441.75564
453831.72036.27974
463734.37972.62029
473837.30440.695578
483334.5614-1.56139
493635.67630.32368
503833.49184.50822
513236.5464-4.54639
523232.2158-0.215813
533233.0984-1.09837
543437.0096-3.00956
553232.6429-0.642943
563734.5612.43903
573934.4664.53396
582934.7577-5.75772
593735.08131.91866
603534.0220.977987
613030.3344-0.33436
623834.16733.83266
633434.8258-0.825792
643134.2856-3.28557
653432.8291.17101
663535.8093-0.809297
673634.64661.35344
683030.6917-0.691737
693936.86732.13271
703535.6092-0.609226
713835.38152.61853
723135.7844-4.78439
733436.6594-2.65945
743837.47450.525486
753431.34372.65635
763932.06316.93694
773735.90211.09789
783432.88061.11937
792833.1566-5.15656
803731.22575.77435
813335.2174-2.21742
823536.2194-1.21938
833733.88193.11813
843234.4279-2.42786
853332.99430.00573258
863836.38661.61338
873334.3657-1.36567
882933.0362-4.03618
893332.97180.0281697
903135.4442-4.44423
913633.20332.79668
923537.4356-2.43562
933231.43260.567449
942932.4336-3.43359
953935.22583.77419
963734.63542.36458
973532.86082.13916
983734.57332.42672
993235.3851-3.38508
1003835.56982.43016
1013734.52022.47983
1023636.2245-0.224548
1033231.78510.214883
1043336.2948-3.29476
1054032.69327.30678
1063835.17882.82119
1074136.35814.64188
1083634.15351.84646
1094336.5736.42701
1103034.5479-4.54791
1113133.6085-2.60847
1123237.89-5.89001
1133231.53110.468945
1143734.66072.33926
1153734.10562.89439
1163336.7443-3.74435
1173437.149-3.14903
1183334.9513-1.9513
1193835.37952.62053
1203335.139-2.13904
1213131.2584-0.258413
1223836.9531.04701
1233736.76450.235505
1243633.34912.65094
1253134.097-3.09699
1263934.11854.88152
1274436.73037.26973
1283336.0907-3.09073
1293533.91951.08051
1303233.6863-1.68625
1312832.5729-4.57293
1324035.64474.35532
1332732.3976-5.39763
1343736.3890.610964
1353232.5291-0.529149
1362827.81650.183459
1373435.0441-1.04406
1383034.3618-4.36184
1393534.33490.665145
1403134.4497-3.44974
1413234.1313-2.13126
1423035.6883-5.68835
1433035.308-5.308
1443129.49241.50759
1454033.38576.61429
1463231.63290.36707
1473635.10890.891121
1483233.1388-1.13885
1493532.87082.12915
1503836.80241.19756
1514235.35426.6458
1523435.9857-1.98572
1533536.2062-1.20615
1543833.56294.43708
1553332.9880.0120455
1563633.20332.79668
1573235.3639-3.3639
1583336.0907-3.09073
1593433.77020.22983
1603235.4653-3.4653
1613435.2691-1.26906
1622730.0703-3.07026
1633130.32350.676544
1643833.80244.19765
1653435.7885-1.78854
1662431.2959-7.29593
1673034.0692-4.0692
1682630.0793-4.07929
1693435.8103-1.81027
1702734.6148-7.61483
1713731.83915.1609
1723635.86010.139895
1734134.50316.49687
1742929.4567-0.456737
1753631.81664.18338
1763234.5423-2.5423
1773733.39143.60865
1783031.7905-1.79052
1793133.1652-2.16519
1803834.88433.11569
1813635.12050.879461
1823532.41432.58565
1833135.7427-4.74271
1843833.67434.32574
1852232.2829-10.2829
1863234.5168-2.51677
1873633.96252.03752
1883932.93496.06508
1892830.6371-2.63709
1903234.256-2.25595
1913232.8928-0.892815
1923837.00440.995579
1933233.2738-1.27377
1943535.5733-0.573321
1953233.3554-1.3554
1963736.24030.759732
1973432.53771.46227
1983335.7543-2.75431
1993332.7830.216978
2002633.0773-7.07726
2013032.291-2.29101
2022432.2579-8.25792
2033432.66681.33324
2043433.38230.6177
2053334.1874-1.18739
2063435.2432-1.24324
2073536.3194-1.31942
2083534.81840.181585
2093633.83732.16271
2103433.96970.0303407
2113433.41170.588279
2124139.42781.5722
2133236.3701-4.37015
2143033.2592-3.25918
2153534.18460.815369
2162830.4053-2.40527
2173335.2353-2.23527
2183934.66034.33968
2193633.34272.65733
2203636.9699-0.969944
2213533.83441.16559
2223834.48133.51874
2233333.0131-0.0130519
2243133.6321-2.63212
2253432.09211.90794
2263235.0714-3.07136
2273133.4959-2.49588
2283333.4034-0.403449
2293432.93271.06729
2303434.4903-0.490297
2313432.26191.73807
2323335.9229-2.9229
2333234.2223-2.22232
2344133.99867.00141
2353433.73870.261304
2363632.7123.28803
2373732.45224.54783
2383631.24324.75683
2392932.8303-3.83026
2403732.2344.76599
2412733.4819-6.48186
2423533.99661.00345
2432830.646-2.64604
2443533.15481.84521
2453733.46323.53677
2462933.9002-4.90023
2473234.6008-2.60078
2483632.53743.46261
2491927.7453-8.74526
2502127.1004-6.10044
2513133.9341-2.93413
2523332.88130.118655
2533634.18491.81508
2543333.4043-0.404266
2553733.72873.2713
2563433.84840.151569
2573534.55330.446726
2583132.8222-1.82222
2593734.16332.83673
2603532.56532.43473
2612732.3375-5.33746
2623436.1151-2.11513
2634034.02665.97342
2642933.242-4.24198

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 41 & 35.8689 & 5.13112 \tabularnewline
2 & 39 & 33.9624 & 5.03762 \tabularnewline
3 & 30 & 34.9017 & -4.90173 \tabularnewline
4 & 31 & 33.4897 & -2.48969 \tabularnewline
5 & 34 & 35.3136 & -1.31362 \tabularnewline
6 & 35 & 32.3096 & 2.69043 \tabularnewline
7 & 39 & 32.8099 & 6.19011 \tabularnewline
8 & 34 & 35.6266 & -1.62657 \tabularnewline
9 & 36 & 35.0565 & 0.943474 \tabularnewline
10 & 37 & 36.1535 & 0.8465 \tabularnewline
11 & 38 & 33.4842 & 4.51578 \tabularnewline
12 & 36 & 34.6905 & 1.30946 \tabularnewline
13 & 38 & 34.5464 & 3.45362 \tabularnewline
14 & 39 & 35.8509 & 3.14913 \tabularnewline
15 & 33 & 36.4573 & -3.45734 \tabularnewline
16 & 32 & 33.7314 & -1.73141 \tabularnewline
17 & 36 & 33.2318 & 2.76824 \tabularnewline
18 & 38 & 36.6837 & 1.31631 \tabularnewline
19 & 39 & 36.425 & 2.57501 \tabularnewline
20 & 32 & 33.5286 & -1.5286 \tabularnewline
21 & 32 & 34.3105 & -2.31051 \tabularnewline
22 & 31 & 33.1049 & -2.10494 \tabularnewline
23 & 39 & 35.9935 & 3.00646 \tabularnewline
24 & 37 & 36.5068 & 0.493151 \tabularnewline
25 & 39 & 33.8945 & 5.10555 \tabularnewline
26 & 41 & 33.4023 & 7.59767 \tabularnewline
27 & 36 & 34.5081 & 1.49189 \tabularnewline
28 & 33 & 35.8829 & -2.88294 \tabularnewline
29 & 33 & 33.6233 & -0.623347 \tabularnewline
30 & 34 & 34.0146 & -0.0146449 \tabularnewline
31 & 31 & 33.5404 & -2.54041 \tabularnewline
32 & 27 & 32.8133 & -5.81333 \tabularnewline
33 & 37 & 33.2122 & 3.78777 \tabularnewline
34 & 34 & 36.4235 & -2.42353 \tabularnewline
35 & 34 & 32.1773 & 1.82269 \tabularnewline
36 & 32 & 34.1508 & -2.1508 \tabularnewline
37 & 29 & 31.8128 & -2.81276 \tabularnewline
38 & 36 & 33.9727 & 2.02727 \tabularnewline
39 & 29 & 33.2774 & -4.27736 \tabularnewline
40 & 35 & 33.8945 & 1.10553 \tabularnewline
41 & 37 & 33.6859 & 3.31408 \tabularnewline
42 & 34 & 33.747 & 0.253014 \tabularnewline
43 & 38 & 33.8213 & 4.17869 \tabularnewline
44 & 35 & 33.2444 & 1.75564 \tabularnewline
45 & 38 & 31.7203 & 6.27974 \tabularnewline
46 & 37 & 34.3797 & 2.62029 \tabularnewline
47 & 38 & 37.3044 & 0.695578 \tabularnewline
48 & 33 & 34.5614 & -1.56139 \tabularnewline
49 & 36 & 35.6763 & 0.32368 \tabularnewline
50 & 38 & 33.4918 & 4.50822 \tabularnewline
51 & 32 & 36.5464 & -4.54639 \tabularnewline
52 & 32 & 32.2158 & -0.215813 \tabularnewline
53 & 32 & 33.0984 & -1.09837 \tabularnewline
54 & 34 & 37.0096 & -3.00956 \tabularnewline
55 & 32 & 32.6429 & -0.642943 \tabularnewline
56 & 37 & 34.561 & 2.43903 \tabularnewline
57 & 39 & 34.466 & 4.53396 \tabularnewline
58 & 29 & 34.7577 & -5.75772 \tabularnewline
59 & 37 & 35.0813 & 1.91866 \tabularnewline
60 & 35 & 34.022 & 0.977987 \tabularnewline
61 & 30 & 30.3344 & -0.33436 \tabularnewline
62 & 38 & 34.1673 & 3.83266 \tabularnewline
63 & 34 & 34.8258 & -0.825792 \tabularnewline
64 & 31 & 34.2856 & -3.28557 \tabularnewline
65 & 34 & 32.829 & 1.17101 \tabularnewline
66 & 35 & 35.8093 & -0.809297 \tabularnewline
67 & 36 & 34.6466 & 1.35344 \tabularnewline
68 & 30 & 30.6917 & -0.691737 \tabularnewline
69 & 39 & 36.8673 & 2.13271 \tabularnewline
70 & 35 & 35.6092 & -0.609226 \tabularnewline
71 & 38 & 35.3815 & 2.61853 \tabularnewline
72 & 31 & 35.7844 & -4.78439 \tabularnewline
73 & 34 & 36.6594 & -2.65945 \tabularnewline
74 & 38 & 37.4745 & 0.525486 \tabularnewline
75 & 34 & 31.3437 & 2.65635 \tabularnewline
76 & 39 & 32.0631 & 6.93694 \tabularnewline
77 & 37 & 35.9021 & 1.09789 \tabularnewline
78 & 34 & 32.8806 & 1.11937 \tabularnewline
79 & 28 & 33.1566 & -5.15656 \tabularnewline
80 & 37 & 31.2257 & 5.77435 \tabularnewline
81 & 33 & 35.2174 & -2.21742 \tabularnewline
82 & 35 & 36.2194 & -1.21938 \tabularnewline
83 & 37 & 33.8819 & 3.11813 \tabularnewline
84 & 32 & 34.4279 & -2.42786 \tabularnewline
85 & 33 & 32.9943 & 0.00573258 \tabularnewline
86 & 38 & 36.3866 & 1.61338 \tabularnewline
87 & 33 & 34.3657 & -1.36567 \tabularnewline
88 & 29 & 33.0362 & -4.03618 \tabularnewline
89 & 33 & 32.9718 & 0.0281697 \tabularnewline
90 & 31 & 35.4442 & -4.44423 \tabularnewline
91 & 36 & 33.2033 & 2.79668 \tabularnewline
92 & 35 & 37.4356 & -2.43562 \tabularnewline
93 & 32 & 31.4326 & 0.567449 \tabularnewline
94 & 29 & 32.4336 & -3.43359 \tabularnewline
95 & 39 & 35.2258 & 3.77419 \tabularnewline
96 & 37 & 34.6354 & 2.36458 \tabularnewline
97 & 35 & 32.8608 & 2.13916 \tabularnewline
98 & 37 & 34.5733 & 2.42672 \tabularnewline
99 & 32 & 35.3851 & -3.38508 \tabularnewline
100 & 38 & 35.5698 & 2.43016 \tabularnewline
101 & 37 & 34.5202 & 2.47983 \tabularnewline
102 & 36 & 36.2245 & -0.224548 \tabularnewline
103 & 32 & 31.7851 & 0.214883 \tabularnewline
104 & 33 & 36.2948 & -3.29476 \tabularnewline
105 & 40 & 32.6932 & 7.30678 \tabularnewline
106 & 38 & 35.1788 & 2.82119 \tabularnewline
107 & 41 & 36.3581 & 4.64188 \tabularnewline
108 & 36 & 34.1535 & 1.84646 \tabularnewline
109 & 43 & 36.573 & 6.42701 \tabularnewline
110 & 30 & 34.5479 & -4.54791 \tabularnewline
111 & 31 & 33.6085 & -2.60847 \tabularnewline
112 & 32 & 37.89 & -5.89001 \tabularnewline
113 & 32 & 31.5311 & 0.468945 \tabularnewline
114 & 37 & 34.6607 & 2.33926 \tabularnewline
115 & 37 & 34.1056 & 2.89439 \tabularnewline
116 & 33 & 36.7443 & -3.74435 \tabularnewline
117 & 34 & 37.149 & -3.14903 \tabularnewline
118 & 33 & 34.9513 & -1.9513 \tabularnewline
119 & 38 & 35.3795 & 2.62053 \tabularnewline
120 & 33 & 35.139 & -2.13904 \tabularnewline
121 & 31 & 31.2584 & -0.258413 \tabularnewline
122 & 38 & 36.953 & 1.04701 \tabularnewline
123 & 37 & 36.7645 & 0.235505 \tabularnewline
124 & 36 & 33.3491 & 2.65094 \tabularnewline
125 & 31 & 34.097 & -3.09699 \tabularnewline
126 & 39 & 34.1185 & 4.88152 \tabularnewline
127 & 44 & 36.7303 & 7.26973 \tabularnewline
128 & 33 & 36.0907 & -3.09073 \tabularnewline
129 & 35 & 33.9195 & 1.08051 \tabularnewline
130 & 32 & 33.6863 & -1.68625 \tabularnewline
131 & 28 & 32.5729 & -4.57293 \tabularnewline
132 & 40 & 35.6447 & 4.35532 \tabularnewline
133 & 27 & 32.3976 & -5.39763 \tabularnewline
134 & 37 & 36.389 & 0.610964 \tabularnewline
135 & 32 & 32.5291 & -0.529149 \tabularnewline
136 & 28 & 27.8165 & 0.183459 \tabularnewline
137 & 34 & 35.0441 & -1.04406 \tabularnewline
138 & 30 & 34.3618 & -4.36184 \tabularnewline
139 & 35 & 34.3349 & 0.665145 \tabularnewline
140 & 31 & 34.4497 & -3.44974 \tabularnewline
141 & 32 & 34.1313 & -2.13126 \tabularnewline
142 & 30 & 35.6883 & -5.68835 \tabularnewline
143 & 30 & 35.308 & -5.308 \tabularnewline
144 & 31 & 29.4924 & 1.50759 \tabularnewline
145 & 40 & 33.3857 & 6.61429 \tabularnewline
146 & 32 & 31.6329 & 0.36707 \tabularnewline
147 & 36 & 35.1089 & 0.891121 \tabularnewline
148 & 32 & 33.1388 & -1.13885 \tabularnewline
149 & 35 & 32.8708 & 2.12915 \tabularnewline
150 & 38 & 36.8024 & 1.19756 \tabularnewline
151 & 42 & 35.3542 & 6.6458 \tabularnewline
152 & 34 & 35.9857 & -1.98572 \tabularnewline
153 & 35 & 36.2062 & -1.20615 \tabularnewline
154 & 38 & 33.5629 & 4.43708 \tabularnewline
155 & 33 & 32.988 & 0.0120455 \tabularnewline
156 & 36 & 33.2033 & 2.79668 \tabularnewline
157 & 32 & 35.3639 & -3.3639 \tabularnewline
158 & 33 & 36.0907 & -3.09073 \tabularnewline
159 & 34 & 33.7702 & 0.22983 \tabularnewline
160 & 32 & 35.4653 & -3.4653 \tabularnewline
161 & 34 & 35.2691 & -1.26906 \tabularnewline
162 & 27 & 30.0703 & -3.07026 \tabularnewline
163 & 31 & 30.3235 & 0.676544 \tabularnewline
164 & 38 & 33.8024 & 4.19765 \tabularnewline
165 & 34 & 35.7885 & -1.78854 \tabularnewline
166 & 24 & 31.2959 & -7.29593 \tabularnewline
167 & 30 & 34.0692 & -4.0692 \tabularnewline
168 & 26 & 30.0793 & -4.07929 \tabularnewline
169 & 34 & 35.8103 & -1.81027 \tabularnewline
170 & 27 & 34.6148 & -7.61483 \tabularnewline
171 & 37 & 31.8391 & 5.1609 \tabularnewline
172 & 36 & 35.8601 & 0.139895 \tabularnewline
173 & 41 & 34.5031 & 6.49687 \tabularnewline
174 & 29 & 29.4567 & -0.456737 \tabularnewline
175 & 36 & 31.8166 & 4.18338 \tabularnewline
176 & 32 & 34.5423 & -2.5423 \tabularnewline
177 & 37 & 33.3914 & 3.60865 \tabularnewline
178 & 30 & 31.7905 & -1.79052 \tabularnewline
179 & 31 & 33.1652 & -2.16519 \tabularnewline
180 & 38 & 34.8843 & 3.11569 \tabularnewline
181 & 36 & 35.1205 & 0.879461 \tabularnewline
182 & 35 & 32.4143 & 2.58565 \tabularnewline
183 & 31 & 35.7427 & -4.74271 \tabularnewline
184 & 38 & 33.6743 & 4.32574 \tabularnewline
185 & 22 & 32.2829 & -10.2829 \tabularnewline
186 & 32 & 34.5168 & -2.51677 \tabularnewline
187 & 36 & 33.9625 & 2.03752 \tabularnewline
188 & 39 & 32.9349 & 6.06508 \tabularnewline
189 & 28 & 30.6371 & -2.63709 \tabularnewline
190 & 32 & 34.256 & -2.25595 \tabularnewline
191 & 32 & 32.8928 & -0.892815 \tabularnewline
192 & 38 & 37.0044 & 0.995579 \tabularnewline
193 & 32 & 33.2738 & -1.27377 \tabularnewline
194 & 35 & 35.5733 & -0.573321 \tabularnewline
195 & 32 & 33.3554 & -1.3554 \tabularnewline
196 & 37 & 36.2403 & 0.759732 \tabularnewline
197 & 34 & 32.5377 & 1.46227 \tabularnewline
198 & 33 & 35.7543 & -2.75431 \tabularnewline
199 & 33 & 32.783 & 0.216978 \tabularnewline
200 & 26 & 33.0773 & -7.07726 \tabularnewline
201 & 30 & 32.291 & -2.29101 \tabularnewline
202 & 24 & 32.2579 & -8.25792 \tabularnewline
203 & 34 & 32.6668 & 1.33324 \tabularnewline
204 & 34 & 33.3823 & 0.6177 \tabularnewline
205 & 33 & 34.1874 & -1.18739 \tabularnewline
206 & 34 & 35.2432 & -1.24324 \tabularnewline
207 & 35 & 36.3194 & -1.31942 \tabularnewline
208 & 35 & 34.8184 & 0.181585 \tabularnewline
209 & 36 & 33.8373 & 2.16271 \tabularnewline
210 & 34 & 33.9697 & 0.0303407 \tabularnewline
211 & 34 & 33.4117 & 0.588279 \tabularnewline
212 & 41 & 39.4278 & 1.5722 \tabularnewline
213 & 32 & 36.3701 & -4.37015 \tabularnewline
214 & 30 & 33.2592 & -3.25918 \tabularnewline
215 & 35 & 34.1846 & 0.815369 \tabularnewline
216 & 28 & 30.4053 & -2.40527 \tabularnewline
217 & 33 & 35.2353 & -2.23527 \tabularnewline
218 & 39 & 34.6603 & 4.33968 \tabularnewline
219 & 36 & 33.3427 & 2.65733 \tabularnewline
220 & 36 & 36.9699 & -0.969944 \tabularnewline
221 & 35 & 33.8344 & 1.16559 \tabularnewline
222 & 38 & 34.4813 & 3.51874 \tabularnewline
223 & 33 & 33.0131 & -0.0130519 \tabularnewline
224 & 31 & 33.6321 & -2.63212 \tabularnewline
225 & 34 & 32.0921 & 1.90794 \tabularnewline
226 & 32 & 35.0714 & -3.07136 \tabularnewline
227 & 31 & 33.4959 & -2.49588 \tabularnewline
228 & 33 & 33.4034 & -0.403449 \tabularnewline
229 & 34 & 32.9327 & 1.06729 \tabularnewline
230 & 34 & 34.4903 & -0.490297 \tabularnewline
231 & 34 & 32.2619 & 1.73807 \tabularnewline
232 & 33 & 35.9229 & -2.9229 \tabularnewline
233 & 32 & 34.2223 & -2.22232 \tabularnewline
234 & 41 & 33.9986 & 7.00141 \tabularnewline
235 & 34 & 33.7387 & 0.261304 \tabularnewline
236 & 36 & 32.712 & 3.28803 \tabularnewline
237 & 37 & 32.4522 & 4.54783 \tabularnewline
238 & 36 & 31.2432 & 4.75683 \tabularnewline
239 & 29 & 32.8303 & -3.83026 \tabularnewline
240 & 37 & 32.234 & 4.76599 \tabularnewline
241 & 27 & 33.4819 & -6.48186 \tabularnewline
242 & 35 & 33.9966 & 1.00345 \tabularnewline
243 & 28 & 30.646 & -2.64604 \tabularnewline
244 & 35 & 33.1548 & 1.84521 \tabularnewline
245 & 37 & 33.4632 & 3.53677 \tabularnewline
246 & 29 & 33.9002 & -4.90023 \tabularnewline
247 & 32 & 34.6008 & -2.60078 \tabularnewline
248 & 36 & 32.5374 & 3.46261 \tabularnewline
249 & 19 & 27.7453 & -8.74526 \tabularnewline
250 & 21 & 27.1004 & -6.10044 \tabularnewline
251 & 31 & 33.9341 & -2.93413 \tabularnewline
252 & 33 & 32.8813 & 0.118655 \tabularnewline
253 & 36 & 34.1849 & 1.81508 \tabularnewline
254 & 33 & 33.4043 & -0.404266 \tabularnewline
255 & 37 & 33.7287 & 3.2713 \tabularnewline
256 & 34 & 33.8484 & 0.151569 \tabularnewline
257 & 35 & 34.5533 & 0.446726 \tabularnewline
258 & 31 & 32.8222 & -1.82222 \tabularnewline
259 & 37 & 34.1633 & 2.83673 \tabularnewline
260 & 35 & 32.5653 & 2.43473 \tabularnewline
261 & 27 & 32.3375 & -5.33746 \tabularnewline
262 & 34 & 36.1151 & -2.11513 \tabularnewline
263 & 40 & 34.0266 & 5.97342 \tabularnewline
264 & 29 & 33.242 & -4.24198 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225428&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]41[/C][C]35.8689[/C][C]5.13112[/C][/ROW]
[ROW][C]2[/C][C]39[/C][C]33.9624[/C][C]5.03762[/C][/ROW]
[ROW][C]3[/C][C]30[/C][C]34.9017[/C][C]-4.90173[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]33.4897[/C][C]-2.48969[/C][/ROW]
[ROW][C]5[/C][C]34[/C][C]35.3136[/C][C]-1.31362[/C][/ROW]
[ROW][C]6[/C][C]35[/C][C]32.3096[/C][C]2.69043[/C][/ROW]
[ROW][C]7[/C][C]39[/C][C]32.8099[/C][C]6.19011[/C][/ROW]
[ROW][C]8[/C][C]34[/C][C]35.6266[/C][C]-1.62657[/C][/ROW]
[ROW][C]9[/C][C]36[/C][C]35.0565[/C][C]0.943474[/C][/ROW]
[ROW][C]10[/C][C]37[/C][C]36.1535[/C][C]0.8465[/C][/ROW]
[ROW][C]11[/C][C]38[/C][C]33.4842[/C][C]4.51578[/C][/ROW]
[ROW][C]12[/C][C]36[/C][C]34.6905[/C][C]1.30946[/C][/ROW]
[ROW][C]13[/C][C]38[/C][C]34.5464[/C][C]3.45362[/C][/ROW]
[ROW][C]14[/C][C]39[/C][C]35.8509[/C][C]3.14913[/C][/ROW]
[ROW][C]15[/C][C]33[/C][C]36.4573[/C][C]-3.45734[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]33.7314[/C][C]-1.73141[/C][/ROW]
[ROW][C]17[/C][C]36[/C][C]33.2318[/C][C]2.76824[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]36.6837[/C][C]1.31631[/C][/ROW]
[ROW][C]19[/C][C]39[/C][C]36.425[/C][C]2.57501[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.5286[/C][C]-1.5286[/C][/ROW]
[ROW][C]21[/C][C]32[/C][C]34.3105[/C][C]-2.31051[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]33.1049[/C][C]-2.10494[/C][/ROW]
[ROW][C]23[/C][C]39[/C][C]35.9935[/C][C]3.00646[/C][/ROW]
[ROW][C]24[/C][C]37[/C][C]36.5068[/C][C]0.493151[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]33.8945[/C][C]5.10555[/C][/ROW]
[ROW][C]26[/C][C]41[/C][C]33.4023[/C][C]7.59767[/C][/ROW]
[ROW][C]27[/C][C]36[/C][C]34.5081[/C][C]1.49189[/C][/ROW]
[ROW][C]28[/C][C]33[/C][C]35.8829[/C][C]-2.88294[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]33.6233[/C][C]-0.623347[/C][/ROW]
[ROW][C]30[/C][C]34[/C][C]34.0146[/C][C]-0.0146449[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]33.5404[/C][C]-2.54041[/C][/ROW]
[ROW][C]32[/C][C]27[/C][C]32.8133[/C][C]-5.81333[/C][/ROW]
[ROW][C]33[/C][C]37[/C][C]33.2122[/C][C]3.78777[/C][/ROW]
[ROW][C]34[/C][C]34[/C][C]36.4235[/C][C]-2.42353[/C][/ROW]
[ROW][C]35[/C][C]34[/C][C]32.1773[/C][C]1.82269[/C][/ROW]
[ROW][C]36[/C][C]32[/C][C]34.1508[/C][C]-2.1508[/C][/ROW]
[ROW][C]37[/C][C]29[/C][C]31.8128[/C][C]-2.81276[/C][/ROW]
[ROW][C]38[/C][C]36[/C][C]33.9727[/C][C]2.02727[/C][/ROW]
[ROW][C]39[/C][C]29[/C][C]33.2774[/C][C]-4.27736[/C][/ROW]
[ROW][C]40[/C][C]35[/C][C]33.8945[/C][C]1.10553[/C][/ROW]
[ROW][C]41[/C][C]37[/C][C]33.6859[/C][C]3.31408[/C][/ROW]
[ROW][C]42[/C][C]34[/C][C]33.747[/C][C]0.253014[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]33.8213[/C][C]4.17869[/C][/ROW]
[ROW][C]44[/C][C]35[/C][C]33.2444[/C][C]1.75564[/C][/ROW]
[ROW][C]45[/C][C]38[/C][C]31.7203[/C][C]6.27974[/C][/ROW]
[ROW][C]46[/C][C]37[/C][C]34.3797[/C][C]2.62029[/C][/ROW]
[ROW][C]47[/C][C]38[/C][C]37.3044[/C][C]0.695578[/C][/ROW]
[ROW][C]48[/C][C]33[/C][C]34.5614[/C][C]-1.56139[/C][/ROW]
[ROW][C]49[/C][C]36[/C][C]35.6763[/C][C]0.32368[/C][/ROW]
[ROW][C]50[/C][C]38[/C][C]33.4918[/C][C]4.50822[/C][/ROW]
[ROW][C]51[/C][C]32[/C][C]36.5464[/C][C]-4.54639[/C][/ROW]
[ROW][C]52[/C][C]32[/C][C]32.2158[/C][C]-0.215813[/C][/ROW]
[ROW][C]53[/C][C]32[/C][C]33.0984[/C][C]-1.09837[/C][/ROW]
[ROW][C]54[/C][C]34[/C][C]37.0096[/C][C]-3.00956[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]32.6429[/C][C]-0.642943[/C][/ROW]
[ROW][C]56[/C][C]37[/C][C]34.561[/C][C]2.43903[/C][/ROW]
[ROW][C]57[/C][C]39[/C][C]34.466[/C][C]4.53396[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]34.7577[/C][C]-5.75772[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]35.0813[/C][C]1.91866[/C][/ROW]
[ROW][C]60[/C][C]35[/C][C]34.022[/C][C]0.977987[/C][/ROW]
[ROW][C]61[/C][C]30[/C][C]30.3344[/C][C]-0.33436[/C][/ROW]
[ROW][C]62[/C][C]38[/C][C]34.1673[/C][C]3.83266[/C][/ROW]
[ROW][C]63[/C][C]34[/C][C]34.8258[/C][C]-0.825792[/C][/ROW]
[ROW][C]64[/C][C]31[/C][C]34.2856[/C][C]-3.28557[/C][/ROW]
[ROW][C]65[/C][C]34[/C][C]32.829[/C][C]1.17101[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]35.8093[/C][C]-0.809297[/C][/ROW]
[ROW][C]67[/C][C]36[/C][C]34.6466[/C][C]1.35344[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]30.6917[/C][C]-0.691737[/C][/ROW]
[ROW][C]69[/C][C]39[/C][C]36.8673[/C][C]2.13271[/C][/ROW]
[ROW][C]70[/C][C]35[/C][C]35.6092[/C][C]-0.609226[/C][/ROW]
[ROW][C]71[/C][C]38[/C][C]35.3815[/C][C]2.61853[/C][/ROW]
[ROW][C]72[/C][C]31[/C][C]35.7844[/C][C]-4.78439[/C][/ROW]
[ROW][C]73[/C][C]34[/C][C]36.6594[/C][C]-2.65945[/C][/ROW]
[ROW][C]74[/C][C]38[/C][C]37.4745[/C][C]0.525486[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]31.3437[/C][C]2.65635[/C][/ROW]
[ROW][C]76[/C][C]39[/C][C]32.0631[/C][C]6.93694[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.9021[/C][C]1.09789[/C][/ROW]
[ROW][C]78[/C][C]34[/C][C]32.8806[/C][C]1.11937[/C][/ROW]
[ROW][C]79[/C][C]28[/C][C]33.1566[/C][C]-5.15656[/C][/ROW]
[ROW][C]80[/C][C]37[/C][C]31.2257[/C][C]5.77435[/C][/ROW]
[ROW][C]81[/C][C]33[/C][C]35.2174[/C][C]-2.21742[/C][/ROW]
[ROW][C]82[/C][C]35[/C][C]36.2194[/C][C]-1.21938[/C][/ROW]
[ROW][C]83[/C][C]37[/C][C]33.8819[/C][C]3.11813[/C][/ROW]
[ROW][C]84[/C][C]32[/C][C]34.4279[/C][C]-2.42786[/C][/ROW]
[ROW][C]85[/C][C]33[/C][C]32.9943[/C][C]0.00573258[/C][/ROW]
[ROW][C]86[/C][C]38[/C][C]36.3866[/C][C]1.61338[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]34.3657[/C][C]-1.36567[/C][/ROW]
[ROW][C]88[/C][C]29[/C][C]33.0362[/C][C]-4.03618[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]32.9718[/C][C]0.0281697[/C][/ROW]
[ROW][C]90[/C][C]31[/C][C]35.4442[/C][C]-4.44423[/C][/ROW]
[ROW][C]91[/C][C]36[/C][C]33.2033[/C][C]2.79668[/C][/ROW]
[ROW][C]92[/C][C]35[/C][C]37.4356[/C][C]-2.43562[/C][/ROW]
[ROW][C]93[/C][C]32[/C][C]31.4326[/C][C]0.567449[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]32.4336[/C][C]-3.43359[/C][/ROW]
[ROW][C]95[/C][C]39[/C][C]35.2258[/C][C]3.77419[/C][/ROW]
[ROW][C]96[/C][C]37[/C][C]34.6354[/C][C]2.36458[/C][/ROW]
[ROW][C]97[/C][C]35[/C][C]32.8608[/C][C]2.13916[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]34.5733[/C][C]2.42672[/C][/ROW]
[ROW][C]99[/C][C]32[/C][C]35.3851[/C][C]-3.38508[/C][/ROW]
[ROW][C]100[/C][C]38[/C][C]35.5698[/C][C]2.43016[/C][/ROW]
[ROW][C]101[/C][C]37[/C][C]34.5202[/C][C]2.47983[/C][/ROW]
[ROW][C]102[/C][C]36[/C][C]36.2245[/C][C]-0.224548[/C][/ROW]
[ROW][C]103[/C][C]32[/C][C]31.7851[/C][C]0.214883[/C][/ROW]
[ROW][C]104[/C][C]33[/C][C]36.2948[/C][C]-3.29476[/C][/ROW]
[ROW][C]105[/C][C]40[/C][C]32.6932[/C][C]7.30678[/C][/ROW]
[ROW][C]106[/C][C]38[/C][C]35.1788[/C][C]2.82119[/C][/ROW]
[ROW][C]107[/C][C]41[/C][C]36.3581[/C][C]4.64188[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]34.1535[/C][C]1.84646[/C][/ROW]
[ROW][C]109[/C][C]43[/C][C]36.573[/C][C]6.42701[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]34.5479[/C][C]-4.54791[/C][/ROW]
[ROW][C]111[/C][C]31[/C][C]33.6085[/C][C]-2.60847[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]37.89[/C][C]-5.89001[/C][/ROW]
[ROW][C]113[/C][C]32[/C][C]31.5311[/C][C]0.468945[/C][/ROW]
[ROW][C]114[/C][C]37[/C][C]34.6607[/C][C]2.33926[/C][/ROW]
[ROW][C]115[/C][C]37[/C][C]34.1056[/C][C]2.89439[/C][/ROW]
[ROW][C]116[/C][C]33[/C][C]36.7443[/C][C]-3.74435[/C][/ROW]
[ROW][C]117[/C][C]34[/C][C]37.149[/C][C]-3.14903[/C][/ROW]
[ROW][C]118[/C][C]33[/C][C]34.9513[/C][C]-1.9513[/C][/ROW]
[ROW][C]119[/C][C]38[/C][C]35.3795[/C][C]2.62053[/C][/ROW]
[ROW][C]120[/C][C]33[/C][C]35.139[/C][C]-2.13904[/C][/ROW]
[ROW][C]121[/C][C]31[/C][C]31.2584[/C][C]-0.258413[/C][/ROW]
[ROW][C]122[/C][C]38[/C][C]36.953[/C][C]1.04701[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]36.7645[/C][C]0.235505[/C][/ROW]
[ROW][C]124[/C][C]36[/C][C]33.3491[/C][C]2.65094[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]34.097[/C][C]-3.09699[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]34.1185[/C][C]4.88152[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]36.7303[/C][C]7.26973[/C][/ROW]
[ROW][C]128[/C][C]33[/C][C]36.0907[/C][C]-3.09073[/C][/ROW]
[ROW][C]129[/C][C]35[/C][C]33.9195[/C][C]1.08051[/C][/ROW]
[ROW][C]130[/C][C]32[/C][C]33.6863[/C][C]-1.68625[/C][/ROW]
[ROW][C]131[/C][C]28[/C][C]32.5729[/C][C]-4.57293[/C][/ROW]
[ROW][C]132[/C][C]40[/C][C]35.6447[/C][C]4.35532[/C][/ROW]
[ROW][C]133[/C][C]27[/C][C]32.3976[/C][C]-5.39763[/C][/ROW]
[ROW][C]134[/C][C]37[/C][C]36.389[/C][C]0.610964[/C][/ROW]
[ROW][C]135[/C][C]32[/C][C]32.5291[/C][C]-0.529149[/C][/ROW]
[ROW][C]136[/C][C]28[/C][C]27.8165[/C][C]0.183459[/C][/ROW]
[ROW][C]137[/C][C]34[/C][C]35.0441[/C][C]-1.04406[/C][/ROW]
[ROW][C]138[/C][C]30[/C][C]34.3618[/C][C]-4.36184[/C][/ROW]
[ROW][C]139[/C][C]35[/C][C]34.3349[/C][C]0.665145[/C][/ROW]
[ROW][C]140[/C][C]31[/C][C]34.4497[/C][C]-3.44974[/C][/ROW]
[ROW][C]141[/C][C]32[/C][C]34.1313[/C][C]-2.13126[/C][/ROW]
[ROW][C]142[/C][C]30[/C][C]35.6883[/C][C]-5.68835[/C][/ROW]
[ROW][C]143[/C][C]30[/C][C]35.308[/C][C]-5.308[/C][/ROW]
[ROW][C]144[/C][C]31[/C][C]29.4924[/C][C]1.50759[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]33.3857[/C][C]6.61429[/C][/ROW]
[ROW][C]146[/C][C]32[/C][C]31.6329[/C][C]0.36707[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]35.1089[/C][C]0.891121[/C][/ROW]
[ROW][C]148[/C][C]32[/C][C]33.1388[/C][C]-1.13885[/C][/ROW]
[ROW][C]149[/C][C]35[/C][C]32.8708[/C][C]2.12915[/C][/ROW]
[ROW][C]150[/C][C]38[/C][C]36.8024[/C][C]1.19756[/C][/ROW]
[ROW][C]151[/C][C]42[/C][C]35.3542[/C][C]6.6458[/C][/ROW]
[ROW][C]152[/C][C]34[/C][C]35.9857[/C][C]-1.98572[/C][/ROW]
[ROW][C]153[/C][C]35[/C][C]36.2062[/C][C]-1.20615[/C][/ROW]
[ROW][C]154[/C][C]38[/C][C]33.5629[/C][C]4.43708[/C][/ROW]
[ROW][C]155[/C][C]33[/C][C]32.988[/C][C]0.0120455[/C][/ROW]
[ROW][C]156[/C][C]36[/C][C]33.2033[/C][C]2.79668[/C][/ROW]
[ROW][C]157[/C][C]32[/C][C]35.3639[/C][C]-3.3639[/C][/ROW]
[ROW][C]158[/C][C]33[/C][C]36.0907[/C][C]-3.09073[/C][/ROW]
[ROW][C]159[/C][C]34[/C][C]33.7702[/C][C]0.22983[/C][/ROW]
[ROW][C]160[/C][C]32[/C][C]35.4653[/C][C]-3.4653[/C][/ROW]
[ROW][C]161[/C][C]34[/C][C]35.2691[/C][C]-1.26906[/C][/ROW]
[ROW][C]162[/C][C]27[/C][C]30.0703[/C][C]-3.07026[/C][/ROW]
[ROW][C]163[/C][C]31[/C][C]30.3235[/C][C]0.676544[/C][/ROW]
[ROW][C]164[/C][C]38[/C][C]33.8024[/C][C]4.19765[/C][/ROW]
[ROW][C]165[/C][C]34[/C][C]35.7885[/C][C]-1.78854[/C][/ROW]
[ROW][C]166[/C][C]24[/C][C]31.2959[/C][C]-7.29593[/C][/ROW]
[ROW][C]167[/C][C]30[/C][C]34.0692[/C][C]-4.0692[/C][/ROW]
[ROW][C]168[/C][C]26[/C][C]30.0793[/C][C]-4.07929[/C][/ROW]
[ROW][C]169[/C][C]34[/C][C]35.8103[/C][C]-1.81027[/C][/ROW]
[ROW][C]170[/C][C]27[/C][C]34.6148[/C][C]-7.61483[/C][/ROW]
[ROW][C]171[/C][C]37[/C][C]31.8391[/C][C]5.1609[/C][/ROW]
[ROW][C]172[/C][C]36[/C][C]35.8601[/C][C]0.139895[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]34.5031[/C][C]6.49687[/C][/ROW]
[ROW][C]174[/C][C]29[/C][C]29.4567[/C][C]-0.456737[/C][/ROW]
[ROW][C]175[/C][C]36[/C][C]31.8166[/C][C]4.18338[/C][/ROW]
[ROW][C]176[/C][C]32[/C][C]34.5423[/C][C]-2.5423[/C][/ROW]
[ROW][C]177[/C][C]37[/C][C]33.3914[/C][C]3.60865[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.7905[/C][C]-1.79052[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]33.1652[/C][C]-2.16519[/C][/ROW]
[ROW][C]180[/C][C]38[/C][C]34.8843[/C][C]3.11569[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]35.1205[/C][C]0.879461[/C][/ROW]
[ROW][C]182[/C][C]35[/C][C]32.4143[/C][C]2.58565[/C][/ROW]
[ROW][C]183[/C][C]31[/C][C]35.7427[/C][C]-4.74271[/C][/ROW]
[ROW][C]184[/C][C]38[/C][C]33.6743[/C][C]4.32574[/C][/ROW]
[ROW][C]185[/C][C]22[/C][C]32.2829[/C][C]-10.2829[/C][/ROW]
[ROW][C]186[/C][C]32[/C][C]34.5168[/C][C]-2.51677[/C][/ROW]
[ROW][C]187[/C][C]36[/C][C]33.9625[/C][C]2.03752[/C][/ROW]
[ROW][C]188[/C][C]39[/C][C]32.9349[/C][C]6.06508[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.6371[/C][C]-2.63709[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]34.256[/C][C]-2.25595[/C][/ROW]
[ROW][C]191[/C][C]32[/C][C]32.8928[/C][C]-0.892815[/C][/ROW]
[ROW][C]192[/C][C]38[/C][C]37.0044[/C][C]0.995579[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]33.2738[/C][C]-1.27377[/C][/ROW]
[ROW][C]194[/C][C]35[/C][C]35.5733[/C][C]-0.573321[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]33.3554[/C][C]-1.3554[/C][/ROW]
[ROW][C]196[/C][C]37[/C][C]36.2403[/C][C]0.759732[/C][/ROW]
[ROW][C]197[/C][C]34[/C][C]32.5377[/C][C]1.46227[/C][/ROW]
[ROW][C]198[/C][C]33[/C][C]35.7543[/C][C]-2.75431[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]32.783[/C][C]0.216978[/C][/ROW]
[ROW][C]200[/C][C]26[/C][C]33.0773[/C][C]-7.07726[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]32.291[/C][C]-2.29101[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]32.2579[/C][C]-8.25792[/C][/ROW]
[ROW][C]203[/C][C]34[/C][C]32.6668[/C][C]1.33324[/C][/ROW]
[ROW][C]204[/C][C]34[/C][C]33.3823[/C][C]0.6177[/C][/ROW]
[ROW][C]205[/C][C]33[/C][C]34.1874[/C][C]-1.18739[/C][/ROW]
[ROW][C]206[/C][C]34[/C][C]35.2432[/C][C]-1.24324[/C][/ROW]
[ROW][C]207[/C][C]35[/C][C]36.3194[/C][C]-1.31942[/C][/ROW]
[ROW][C]208[/C][C]35[/C][C]34.8184[/C][C]0.181585[/C][/ROW]
[ROW][C]209[/C][C]36[/C][C]33.8373[/C][C]2.16271[/C][/ROW]
[ROW][C]210[/C][C]34[/C][C]33.9697[/C][C]0.0303407[/C][/ROW]
[ROW][C]211[/C][C]34[/C][C]33.4117[/C][C]0.588279[/C][/ROW]
[ROW][C]212[/C][C]41[/C][C]39.4278[/C][C]1.5722[/C][/ROW]
[ROW][C]213[/C][C]32[/C][C]36.3701[/C][C]-4.37015[/C][/ROW]
[ROW][C]214[/C][C]30[/C][C]33.2592[/C][C]-3.25918[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]34.1846[/C][C]0.815369[/C][/ROW]
[ROW][C]216[/C][C]28[/C][C]30.4053[/C][C]-2.40527[/C][/ROW]
[ROW][C]217[/C][C]33[/C][C]35.2353[/C][C]-2.23527[/C][/ROW]
[ROW][C]218[/C][C]39[/C][C]34.6603[/C][C]4.33968[/C][/ROW]
[ROW][C]219[/C][C]36[/C][C]33.3427[/C][C]2.65733[/C][/ROW]
[ROW][C]220[/C][C]36[/C][C]36.9699[/C][C]-0.969944[/C][/ROW]
[ROW][C]221[/C][C]35[/C][C]33.8344[/C][C]1.16559[/C][/ROW]
[ROW][C]222[/C][C]38[/C][C]34.4813[/C][C]3.51874[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]33.0131[/C][C]-0.0130519[/C][/ROW]
[ROW][C]224[/C][C]31[/C][C]33.6321[/C][C]-2.63212[/C][/ROW]
[ROW][C]225[/C][C]34[/C][C]32.0921[/C][C]1.90794[/C][/ROW]
[ROW][C]226[/C][C]32[/C][C]35.0714[/C][C]-3.07136[/C][/ROW]
[ROW][C]227[/C][C]31[/C][C]33.4959[/C][C]-2.49588[/C][/ROW]
[ROW][C]228[/C][C]33[/C][C]33.4034[/C][C]-0.403449[/C][/ROW]
[ROW][C]229[/C][C]34[/C][C]32.9327[/C][C]1.06729[/C][/ROW]
[ROW][C]230[/C][C]34[/C][C]34.4903[/C][C]-0.490297[/C][/ROW]
[ROW][C]231[/C][C]34[/C][C]32.2619[/C][C]1.73807[/C][/ROW]
[ROW][C]232[/C][C]33[/C][C]35.9229[/C][C]-2.9229[/C][/ROW]
[ROW][C]233[/C][C]32[/C][C]34.2223[/C][C]-2.22232[/C][/ROW]
[ROW][C]234[/C][C]41[/C][C]33.9986[/C][C]7.00141[/C][/ROW]
[ROW][C]235[/C][C]34[/C][C]33.7387[/C][C]0.261304[/C][/ROW]
[ROW][C]236[/C][C]36[/C][C]32.712[/C][C]3.28803[/C][/ROW]
[ROW][C]237[/C][C]37[/C][C]32.4522[/C][C]4.54783[/C][/ROW]
[ROW][C]238[/C][C]36[/C][C]31.2432[/C][C]4.75683[/C][/ROW]
[ROW][C]239[/C][C]29[/C][C]32.8303[/C][C]-3.83026[/C][/ROW]
[ROW][C]240[/C][C]37[/C][C]32.234[/C][C]4.76599[/C][/ROW]
[ROW][C]241[/C][C]27[/C][C]33.4819[/C][C]-6.48186[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.9966[/C][C]1.00345[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]30.646[/C][C]-2.64604[/C][/ROW]
[ROW][C]244[/C][C]35[/C][C]33.1548[/C][C]1.84521[/C][/ROW]
[ROW][C]245[/C][C]37[/C][C]33.4632[/C][C]3.53677[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]33.9002[/C][C]-4.90023[/C][/ROW]
[ROW][C]247[/C][C]32[/C][C]34.6008[/C][C]-2.60078[/C][/ROW]
[ROW][C]248[/C][C]36[/C][C]32.5374[/C][C]3.46261[/C][/ROW]
[ROW][C]249[/C][C]19[/C][C]27.7453[/C][C]-8.74526[/C][/ROW]
[ROW][C]250[/C][C]21[/C][C]27.1004[/C][C]-6.10044[/C][/ROW]
[ROW][C]251[/C][C]31[/C][C]33.9341[/C][C]-2.93413[/C][/ROW]
[ROW][C]252[/C][C]33[/C][C]32.8813[/C][C]0.118655[/C][/ROW]
[ROW][C]253[/C][C]36[/C][C]34.1849[/C][C]1.81508[/C][/ROW]
[ROW][C]254[/C][C]33[/C][C]33.4043[/C][C]-0.404266[/C][/ROW]
[ROW][C]255[/C][C]37[/C][C]33.7287[/C][C]3.2713[/C][/ROW]
[ROW][C]256[/C][C]34[/C][C]33.8484[/C][C]0.151569[/C][/ROW]
[ROW][C]257[/C][C]35[/C][C]34.5533[/C][C]0.446726[/C][/ROW]
[ROW][C]258[/C][C]31[/C][C]32.8222[/C][C]-1.82222[/C][/ROW]
[ROW][C]259[/C][C]37[/C][C]34.1633[/C][C]2.83673[/C][/ROW]
[ROW][C]260[/C][C]35[/C][C]32.5653[/C][C]2.43473[/C][/ROW]
[ROW][C]261[/C][C]27[/C][C]32.3375[/C][C]-5.33746[/C][/ROW]
[ROW][C]262[/C][C]34[/C][C]36.1151[/C][C]-2.11513[/C][/ROW]
[ROW][C]263[/C][C]40[/C][C]34.0266[/C][C]5.97342[/C][/ROW]
[ROW][C]264[/C][C]29[/C][C]33.242[/C][C]-4.24198[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225428&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225428&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14135.86895.13112
23933.96245.03762
33034.9017-4.90173
43133.4897-2.48969
53435.3136-1.31362
63532.30962.69043
73932.80996.19011
83435.6266-1.62657
93635.05650.943474
103736.15350.8465
113833.48424.51578
123634.69051.30946
133834.54643.45362
143935.85093.14913
153336.4573-3.45734
163233.7314-1.73141
173633.23182.76824
183836.68371.31631
193936.4252.57501
203233.5286-1.5286
213234.3105-2.31051
223133.1049-2.10494
233935.99353.00646
243736.50680.493151
253933.89455.10555
264133.40237.59767
273634.50811.49189
283335.8829-2.88294
293333.6233-0.623347
303434.0146-0.0146449
313133.5404-2.54041
322732.8133-5.81333
333733.21223.78777
343436.4235-2.42353
353432.17731.82269
363234.1508-2.1508
372931.8128-2.81276
383633.97272.02727
392933.2774-4.27736
403533.89451.10553
413733.68593.31408
423433.7470.253014
433833.82134.17869
443533.24441.75564
453831.72036.27974
463734.37972.62029
473837.30440.695578
483334.5614-1.56139
493635.67630.32368
503833.49184.50822
513236.5464-4.54639
523232.2158-0.215813
533233.0984-1.09837
543437.0096-3.00956
553232.6429-0.642943
563734.5612.43903
573934.4664.53396
582934.7577-5.75772
593735.08131.91866
603534.0220.977987
613030.3344-0.33436
623834.16733.83266
633434.8258-0.825792
643134.2856-3.28557
653432.8291.17101
663535.8093-0.809297
673634.64661.35344
683030.6917-0.691737
693936.86732.13271
703535.6092-0.609226
713835.38152.61853
723135.7844-4.78439
733436.6594-2.65945
743837.47450.525486
753431.34372.65635
763932.06316.93694
773735.90211.09789
783432.88061.11937
792833.1566-5.15656
803731.22575.77435
813335.2174-2.21742
823536.2194-1.21938
833733.88193.11813
843234.4279-2.42786
853332.99430.00573258
863836.38661.61338
873334.3657-1.36567
882933.0362-4.03618
893332.97180.0281697
903135.4442-4.44423
913633.20332.79668
923537.4356-2.43562
933231.43260.567449
942932.4336-3.43359
953935.22583.77419
963734.63542.36458
973532.86082.13916
983734.57332.42672
993235.3851-3.38508
1003835.56982.43016
1013734.52022.47983
1023636.2245-0.224548
1033231.78510.214883
1043336.2948-3.29476
1054032.69327.30678
1063835.17882.82119
1074136.35814.64188
1083634.15351.84646
1094336.5736.42701
1103034.5479-4.54791
1113133.6085-2.60847
1123237.89-5.89001
1133231.53110.468945
1143734.66072.33926
1153734.10562.89439
1163336.7443-3.74435
1173437.149-3.14903
1183334.9513-1.9513
1193835.37952.62053
1203335.139-2.13904
1213131.2584-0.258413
1223836.9531.04701
1233736.76450.235505
1243633.34912.65094
1253134.097-3.09699
1263934.11854.88152
1274436.73037.26973
1283336.0907-3.09073
1293533.91951.08051
1303233.6863-1.68625
1312832.5729-4.57293
1324035.64474.35532
1332732.3976-5.39763
1343736.3890.610964
1353232.5291-0.529149
1362827.81650.183459
1373435.0441-1.04406
1383034.3618-4.36184
1393534.33490.665145
1403134.4497-3.44974
1413234.1313-2.13126
1423035.6883-5.68835
1433035.308-5.308
1443129.49241.50759
1454033.38576.61429
1463231.63290.36707
1473635.10890.891121
1483233.1388-1.13885
1493532.87082.12915
1503836.80241.19756
1514235.35426.6458
1523435.9857-1.98572
1533536.2062-1.20615
1543833.56294.43708
1553332.9880.0120455
1563633.20332.79668
1573235.3639-3.3639
1583336.0907-3.09073
1593433.77020.22983
1603235.4653-3.4653
1613435.2691-1.26906
1622730.0703-3.07026
1633130.32350.676544
1643833.80244.19765
1653435.7885-1.78854
1662431.2959-7.29593
1673034.0692-4.0692
1682630.0793-4.07929
1693435.8103-1.81027
1702734.6148-7.61483
1713731.83915.1609
1723635.86010.139895
1734134.50316.49687
1742929.4567-0.456737
1753631.81664.18338
1763234.5423-2.5423
1773733.39143.60865
1783031.7905-1.79052
1793133.1652-2.16519
1803834.88433.11569
1813635.12050.879461
1823532.41432.58565
1833135.7427-4.74271
1843833.67434.32574
1852232.2829-10.2829
1863234.5168-2.51677
1873633.96252.03752
1883932.93496.06508
1892830.6371-2.63709
1903234.256-2.25595
1913232.8928-0.892815
1923837.00440.995579
1933233.2738-1.27377
1943535.5733-0.573321
1953233.3554-1.3554
1963736.24030.759732
1973432.53771.46227
1983335.7543-2.75431
1993332.7830.216978
2002633.0773-7.07726
2013032.291-2.29101
2022432.2579-8.25792
2033432.66681.33324
2043433.38230.6177
2053334.1874-1.18739
2063435.2432-1.24324
2073536.3194-1.31942
2083534.81840.181585
2093633.83732.16271
2103433.96970.0303407
2113433.41170.588279
2124139.42781.5722
2133236.3701-4.37015
2143033.2592-3.25918
2153534.18460.815369
2162830.4053-2.40527
2173335.2353-2.23527
2183934.66034.33968
2193633.34272.65733
2203636.9699-0.969944
2213533.83441.16559
2223834.48133.51874
2233333.0131-0.0130519
2243133.6321-2.63212
2253432.09211.90794
2263235.0714-3.07136
2273133.4959-2.49588
2283333.4034-0.403449
2293432.93271.06729
2303434.4903-0.490297
2313432.26191.73807
2323335.9229-2.9229
2333234.2223-2.22232
2344133.99867.00141
2353433.73870.261304
2363632.7123.28803
2373732.45224.54783
2383631.24324.75683
2392932.8303-3.83026
2403732.2344.76599
2412733.4819-6.48186
2423533.99661.00345
2432830.646-2.64604
2443533.15481.84521
2453733.46323.53677
2462933.9002-4.90023
2473234.6008-2.60078
2483632.53743.46261
2491927.7453-8.74526
2502127.1004-6.10044
2513133.9341-2.93413
2523332.88130.118655
2533634.18491.81508
2543333.4043-0.404266
2553733.72873.2713
2563433.84840.151569
2573534.55330.446726
2583132.8222-1.82222
2593734.16332.83673
2603532.56532.43473
2612732.3375-5.33746
2623436.1151-2.11513
2634034.02665.97342
2642933.242-4.24198






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.04565970.09131940.95434
110.01248780.02497560.987512
120.6335890.7328220.366411
130.764310.4713810.23569
140.6749940.6500130.325006
150.646120.7077590.35388
160.6407430.7185130.359257
170.592570.8148590.40743
180.5139880.9720230.486012
190.4323550.864710.567645
200.4679410.9358820.532059
210.5258230.9483530.474177
220.4797390.9594780.520261
230.4558860.9117720.544114
240.3951430.7902870.604857
250.4669930.9339870.533007
260.7035650.5928690.296435
270.6546880.6906240.345312
280.6312680.7374640.368732
290.605460.789080.39454
300.5520030.8959940.447997
310.559160.881680.44084
320.7572350.4855310.242765
330.7363850.527230.263615
340.7112140.5775720.288786
350.6631770.6736470.336823
360.6478450.7043090.352155
370.6463730.7072530.353627
380.601220.797560.39878
390.6615410.6769180.338459
400.6136970.7726050.386303
410.5934240.8131510.406576
420.5442840.9114310.455716
430.5192950.961410.480705
440.4732180.9464360.526782
450.5334980.9330040.466502
460.4989590.9979180.501041
470.4513620.9027240.548638
480.4224090.8448180.577591
490.3754890.7509780.624511
500.376150.7522990.62385
510.4359490.8718970.564051
520.3996650.7993310.600335
530.3673550.734710.632645
540.3360890.6721780.663911
550.3023360.6046720.697664
560.3003380.6006750.699662
570.3190690.6381370.680931
580.4325280.8650550.567472
590.3976920.7953840.602308
600.3578640.7157280.642136
610.3216340.6432680.678366
620.314490.6289810.68551
630.2842680.5685360.715732
640.293620.587240.70638
650.259090.5181790.74091
660.2277390.4554770.772261
670.2024110.4048210.797589
680.192310.384620.80769
690.1765160.3530320.823484
700.1519880.3039760.848012
710.1467310.2934610.853269
720.1724230.3448460.827577
730.1633990.3267980.836601
740.1401340.2802670.859866
750.1238150.247630.876185
760.1852510.3705010.814749
770.161860.323720.83814
780.139170.2783390.86083
790.1980630.3961260.801937
800.2290150.4580310.770985
810.2162090.4324180.783791
820.1915250.3830510.808475
830.1816250.363250.818375
840.1742470.3484930.825753
850.1522250.304450.847775
860.1376640.2753290.862336
870.1226830.2453660.877317
880.139050.27810.86095
890.1186640.2373280.881336
900.1340050.2680090.865995
910.12480.24960.8752
920.1121390.2242770.887861
930.09736150.1947230.902638
940.1095420.2190840.890458
950.1137630.2275260.886237
960.105450.21090.89455
970.09332820.1866560.906672
980.08472280.1694460.915277
990.08618470.1723690.913815
1000.0789770.1579540.921023
1010.07320460.1464090.926795
1020.06113540.1222710.938865
1030.05170320.1034060.948297
1040.05005940.1001190.949941
1050.09248330.1849670.907517
1060.08830160.1766030.911698
1070.107090.2141810.89291
1080.09522570.1904510.904774
1090.1450680.2901360.854932
1100.16620.33240.8338
1110.161810.3236190.83819
1120.1990550.3981090.800945
1130.1858210.3716420.814179
1140.1727910.3455830.827209
1150.1674170.3348330.832583
1160.1693060.3386120.830694
1170.165110.3302190.83489
1180.1500960.3001920.849904
1190.1423190.2846380.857681
1200.1308970.2617930.869103
1210.1171740.2343490.882826
1220.1032070.2064140.896793
1230.08856310.1771260.911437
1240.08333890.1666780.916661
1250.08109030.1621810.91891
1260.09727840.1945570.902722
1270.1764250.3528510.823575
1280.1735910.3471830.826409
1290.154340.308680.84566
1300.1404060.2808110.859594
1310.164440.328880.83556
1320.1799220.3598430.820078
1330.2251660.4503310.774834
1340.2006930.4013870.799307
1350.1787570.3575130.821243
1360.1587740.3175490.841226
1370.1397360.2794730.860264
1380.1559170.3118340.844083
1390.1360540.2721080.863946
1400.1385650.277130.861435
1410.1283930.2567870.871607
1420.1647870.3295750.835213
1430.1929080.3858160.807092
1440.1807410.3614820.819259
1450.2620830.5241650.737917
1460.2395090.4790180.760491
1470.2142530.4285070.785747
1480.1917530.3835070.808247
1490.1762740.3525480.823726
1500.1561170.3122350.843883
1510.2360710.4721420.763929
1520.21850.4370.7815
1530.198980.397960.80102
1540.2117240.4234480.788276
1550.1872170.3744330.812783
1560.1830370.3660740.816963
1570.189750.3795010.81025
1580.1856430.3712860.814357
1590.1646230.3292460.835377
1600.1677420.3354850.832258
1610.1526340.3052690.847366
1620.1474690.2949380.852531
1630.1368560.2737110.863144
1640.1704490.3408990.829551
1650.1561670.3123350.843833
1660.2554120.5108250.744588
1670.260650.5213010.73935
1680.2606180.5212360.739382
1690.2382870.4765740.761713
1700.360440.720880.63956
1710.3934560.7869120.606544
1720.3579770.7159540.642023
1730.4574020.9148050.542598
1740.4241070.8482150.575893
1750.4929910.9859830.507009
1760.4694840.9389680.530516
1770.4672580.9345170.532742
1780.435660.8713210.56434
1790.4085230.8170460.591477
1800.4019230.8038460.598077
1810.3662590.7325180.633741
1820.3567710.7135410.643229
1830.3828720.7657430.617128
1840.4495050.8990090.550495
1850.670340.659320.32966
1860.6523360.6953290.347664
1870.636990.7260210.36301
1880.7698440.4603120.230156
1890.7512950.497410.248705
1900.7609630.4780740.239037
1910.7315740.5368510.268426
1920.7012440.5975120.298756
1930.6742120.6515760.325788
1940.6515770.6968450.348423
1950.615050.7699010.38495
1960.5752910.8494170.424709
1970.5543180.8913650.445682
1980.5297680.9404640.470232
1990.4874270.9748540.512573
2000.5615690.8768610.438431
2010.5339910.9320180.466009
2020.680550.6389010.31945
2030.675130.6497390.32487
2040.634750.7305010.36525
2050.5946680.8106640.405332
2060.5564150.8871690.443585
2070.5238370.9523260.476163
2080.4815170.9630330.518483
2090.453490.906980.54651
2100.4171120.8342240.582888
2110.3732780.7465560.626722
2120.3333960.6667910.666604
2130.396180.792360.60382
2140.3849910.7699810.615009
2150.341280.682560.65872
2160.3043350.6086690.695665
2170.2768570.5537130.723143
2180.3018710.6037420.698129
2190.2702710.5405420.729729
2200.2498570.4997140.750143
2210.219570.439140.78043
2220.2354640.4709280.764536
2230.1979890.3959790.802011
2240.1720080.3440160.827992
2250.2624150.5248290.737585
2260.2381530.4763070.761847
2270.2115620.4231230.788438
2280.2268450.4536890.773155
2290.188470.376940.81153
2300.1533080.3066170.846692
2310.1461480.2922960.853852
2320.26550.5310.7345
2330.2398180.4796360.760182
2340.3170560.6341130.682944
2350.2705190.5410380.729481
2360.3002990.6005970.699701
2370.2733730.5467470.726627
2380.3756830.7513660.624317
2390.3201980.6403960.679802
2400.5174320.9651360.482568
2410.5840480.8319040.415952
2420.5099180.9801650.490082
2430.4393470.8786940.560653
2440.3899310.7798630.610069
2450.3918020.7836040.608198
2460.610410.779180.38959
2470.6545930.6908130.345407
2480.6290680.7418650.370932
2490.7994650.401070.200535
2500.8068890.3862220.193111
2510.7969530.4060950.203047
2520.8240420.3519170.175958
2530.7033070.5933860.296693
2540.5521990.8956020.447801

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.0456597 & 0.0913194 & 0.95434 \tabularnewline
11 & 0.0124878 & 0.0249756 & 0.987512 \tabularnewline
12 & 0.633589 & 0.732822 & 0.366411 \tabularnewline
13 & 0.76431 & 0.471381 & 0.23569 \tabularnewline
14 & 0.674994 & 0.650013 & 0.325006 \tabularnewline
15 & 0.64612 & 0.707759 & 0.35388 \tabularnewline
16 & 0.640743 & 0.718513 & 0.359257 \tabularnewline
17 & 0.59257 & 0.814859 & 0.40743 \tabularnewline
18 & 0.513988 & 0.972023 & 0.486012 \tabularnewline
19 & 0.432355 & 0.86471 & 0.567645 \tabularnewline
20 & 0.467941 & 0.935882 & 0.532059 \tabularnewline
21 & 0.525823 & 0.948353 & 0.474177 \tabularnewline
22 & 0.479739 & 0.959478 & 0.520261 \tabularnewline
23 & 0.455886 & 0.911772 & 0.544114 \tabularnewline
24 & 0.395143 & 0.790287 & 0.604857 \tabularnewline
25 & 0.466993 & 0.933987 & 0.533007 \tabularnewline
26 & 0.703565 & 0.592869 & 0.296435 \tabularnewline
27 & 0.654688 & 0.690624 & 0.345312 \tabularnewline
28 & 0.631268 & 0.737464 & 0.368732 \tabularnewline
29 & 0.60546 & 0.78908 & 0.39454 \tabularnewline
30 & 0.552003 & 0.895994 & 0.447997 \tabularnewline
31 & 0.55916 & 0.88168 & 0.44084 \tabularnewline
32 & 0.757235 & 0.485531 & 0.242765 \tabularnewline
33 & 0.736385 & 0.52723 & 0.263615 \tabularnewline
34 & 0.711214 & 0.577572 & 0.288786 \tabularnewline
35 & 0.663177 & 0.673647 & 0.336823 \tabularnewline
36 & 0.647845 & 0.704309 & 0.352155 \tabularnewline
37 & 0.646373 & 0.707253 & 0.353627 \tabularnewline
38 & 0.60122 & 0.79756 & 0.39878 \tabularnewline
39 & 0.661541 & 0.676918 & 0.338459 \tabularnewline
40 & 0.613697 & 0.772605 & 0.386303 \tabularnewline
41 & 0.593424 & 0.813151 & 0.406576 \tabularnewline
42 & 0.544284 & 0.911431 & 0.455716 \tabularnewline
43 & 0.519295 & 0.96141 & 0.480705 \tabularnewline
44 & 0.473218 & 0.946436 & 0.526782 \tabularnewline
45 & 0.533498 & 0.933004 & 0.466502 \tabularnewline
46 & 0.498959 & 0.997918 & 0.501041 \tabularnewline
47 & 0.451362 & 0.902724 & 0.548638 \tabularnewline
48 & 0.422409 & 0.844818 & 0.577591 \tabularnewline
49 & 0.375489 & 0.750978 & 0.624511 \tabularnewline
50 & 0.37615 & 0.752299 & 0.62385 \tabularnewline
51 & 0.435949 & 0.871897 & 0.564051 \tabularnewline
52 & 0.399665 & 0.799331 & 0.600335 \tabularnewline
53 & 0.367355 & 0.73471 & 0.632645 \tabularnewline
54 & 0.336089 & 0.672178 & 0.663911 \tabularnewline
55 & 0.302336 & 0.604672 & 0.697664 \tabularnewline
56 & 0.300338 & 0.600675 & 0.699662 \tabularnewline
57 & 0.319069 & 0.638137 & 0.680931 \tabularnewline
58 & 0.432528 & 0.865055 & 0.567472 \tabularnewline
59 & 0.397692 & 0.795384 & 0.602308 \tabularnewline
60 & 0.357864 & 0.715728 & 0.642136 \tabularnewline
61 & 0.321634 & 0.643268 & 0.678366 \tabularnewline
62 & 0.31449 & 0.628981 & 0.68551 \tabularnewline
63 & 0.284268 & 0.568536 & 0.715732 \tabularnewline
64 & 0.29362 & 0.58724 & 0.70638 \tabularnewline
65 & 0.25909 & 0.518179 & 0.74091 \tabularnewline
66 & 0.227739 & 0.455477 & 0.772261 \tabularnewline
67 & 0.202411 & 0.404821 & 0.797589 \tabularnewline
68 & 0.19231 & 0.38462 & 0.80769 \tabularnewline
69 & 0.176516 & 0.353032 & 0.823484 \tabularnewline
70 & 0.151988 & 0.303976 & 0.848012 \tabularnewline
71 & 0.146731 & 0.293461 & 0.853269 \tabularnewline
72 & 0.172423 & 0.344846 & 0.827577 \tabularnewline
73 & 0.163399 & 0.326798 & 0.836601 \tabularnewline
74 & 0.140134 & 0.280267 & 0.859866 \tabularnewline
75 & 0.123815 & 0.24763 & 0.876185 \tabularnewline
76 & 0.185251 & 0.370501 & 0.814749 \tabularnewline
77 & 0.16186 & 0.32372 & 0.83814 \tabularnewline
78 & 0.13917 & 0.278339 & 0.86083 \tabularnewline
79 & 0.198063 & 0.396126 & 0.801937 \tabularnewline
80 & 0.229015 & 0.458031 & 0.770985 \tabularnewline
81 & 0.216209 & 0.432418 & 0.783791 \tabularnewline
82 & 0.191525 & 0.383051 & 0.808475 \tabularnewline
83 & 0.181625 & 0.36325 & 0.818375 \tabularnewline
84 & 0.174247 & 0.348493 & 0.825753 \tabularnewline
85 & 0.152225 & 0.30445 & 0.847775 \tabularnewline
86 & 0.137664 & 0.275329 & 0.862336 \tabularnewline
87 & 0.122683 & 0.245366 & 0.877317 \tabularnewline
88 & 0.13905 & 0.2781 & 0.86095 \tabularnewline
89 & 0.118664 & 0.237328 & 0.881336 \tabularnewline
90 & 0.134005 & 0.268009 & 0.865995 \tabularnewline
91 & 0.1248 & 0.2496 & 0.8752 \tabularnewline
92 & 0.112139 & 0.224277 & 0.887861 \tabularnewline
93 & 0.0973615 & 0.194723 & 0.902638 \tabularnewline
94 & 0.109542 & 0.219084 & 0.890458 \tabularnewline
95 & 0.113763 & 0.227526 & 0.886237 \tabularnewline
96 & 0.10545 & 0.2109 & 0.89455 \tabularnewline
97 & 0.0933282 & 0.186656 & 0.906672 \tabularnewline
98 & 0.0847228 & 0.169446 & 0.915277 \tabularnewline
99 & 0.0861847 & 0.172369 & 0.913815 \tabularnewline
100 & 0.078977 & 0.157954 & 0.921023 \tabularnewline
101 & 0.0732046 & 0.146409 & 0.926795 \tabularnewline
102 & 0.0611354 & 0.122271 & 0.938865 \tabularnewline
103 & 0.0517032 & 0.103406 & 0.948297 \tabularnewline
104 & 0.0500594 & 0.100119 & 0.949941 \tabularnewline
105 & 0.0924833 & 0.184967 & 0.907517 \tabularnewline
106 & 0.0883016 & 0.176603 & 0.911698 \tabularnewline
107 & 0.10709 & 0.214181 & 0.89291 \tabularnewline
108 & 0.0952257 & 0.190451 & 0.904774 \tabularnewline
109 & 0.145068 & 0.290136 & 0.854932 \tabularnewline
110 & 0.1662 & 0.3324 & 0.8338 \tabularnewline
111 & 0.16181 & 0.323619 & 0.83819 \tabularnewline
112 & 0.199055 & 0.398109 & 0.800945 \tabularnewline
113 & 0.185821 & 0.371642 & 0.814179 \tabularnewline
114 & 0.172791 & 0.345583 & 0.827209 \tabularnewline
115 & 0.167417 & 0.334833 & 0.832583 \tabularnewline
116 & 0.169306 & 0.338612 & 0.830694 \tabularnewline
117 & 0.16511 & 0.330219 & 0.83489 \tabularnewline
118 & 0.150096 & 0.300192 & 0.849904 \tabularnewline
119 & 0.142319 & 0.284638 & 0.857681 \tabularnewline
120 & 0.130897 & 0.261793 & 0.869103 \tabularnewline
121 & 0.117174 & 0.234349 & 0.882826 \tabularnewline
122 & 0.103207 & 0.206414 & 0.896793 \tabularnewline
123 & 0.0885631 & 0.177126 & 0.911437 \tabularnewline
124 & 0.0833389 & 0.166678 & 0.916661 \tabularnewline
125 & 0.0810903 & 0.162181 & 0.91891 \tabularnewline
126 & 0.0972784 & 0.194557 & 0.902722 \tabularnewline
127 & 0.176425 & 0.352851 & 0.823575 \tabularnewline
128 & 0.173591 & 0.347183 & 0.826409 \tabularnewline
129 & 0.15434 & 0.30868 & 0.84566 \tabularnewline
130 & 0.140406 & 0.280811 & 0.859594 \tabularnewline
131 & 0.16444 & 0.32888 & 0.83556 \tabularnewline
132 & 0.179922 & 0.359843 & 0.820078 \tabularnewline
133 & 0.225166 & 0.450331 & 0.774834 \tabularnewline
134 & 0.200693 & 0.401387 & 0.799307 \tabularnewline
135 & 0.178757 & 0.357513 & 0.821243 \tabularnewline
136 & 0.158774 & 0.317549 & 0.841226 \tabularnewline
137 & 0.139736 & 0.279473 & 0.860264 \tabularnewline
138 & 0.155917 & 0.311834 & 0.844083 \tabularnewline
139 & 0.136054 & 0.272108 & 0.863946 \tabularnewline
140 & 0.138565 & 0.27713 & 0.861435 \tabularnewline
141 & 0.128393 & 0.256787 & 0.871607 \tabularnewline
142 & 0.164787 & 0.329575 & 0.835213 \tabularnewline
143 & 0.192908 & 0.385816 & 0.807092 \tabularnewline
144 & 0.180741 & 0.361482 & 0.819259 \tabularnewline
145 & 0.262083 & 0.524165 & 0.737917 \tabularnewline
146 & 0.239509 & 0.479018 & 0.760491 \tabularnewline
147 & 0.214253 & 0.428507 & 0.785747 \tabularnewline
148 & 0.191753 & 0.383507 & 0.808247 \tabularnewline
149 & 0.176274 & 0.352548 & 0.823726 \tabularnewline
150 & 0.156117 & 0.312235 & 0.843883 \tabularnewline
151 & 0.236071 & 0.472142 & 0.763929 \tabularnewline
152 & 0.2185 & 0.437 & 0.7815 \tabularnewline
153 & 0.19898 & 0.39796 & 0.80102 \tabularnewline
154 & 0.211724 & 0.423448 & 0.788276 \tabularnewline
155 & 0.187217 & 0.374433 & 0.812783 \tabularnewline
156 & 0.183037 & 0.366074 & 0.816963 \tabularnewline
157 & 0.18975 & 0.379501 & 0.81025 \tabularnewline
158 & 0.185643 & 0.371286 & 0.814357 \tabularnewline
159 & 0.164623 & 0.329246 & 0.835377 \tabularnewline
160 & 0.167742 & 0.335485 & 0.832258 \tabularnewline
161 & 0.152634 & 0.305269 & 0.847366 \tabularnewline
162 & 0.147469 & 0.294938 & 0.852531 \tabularnewline
163 & 0.136856 & 0.273711 & 0.863144 \tabularnewline
164 & 0.170449 & 0.340899 & 0.829551 \tabularnewline
165 & 0.156167 & 0.312335 & 0.843833 \tabularnewline
166 & 0.255412 & 0.510825 & 0.744588 \tabularnewline
167 & 0.26065 & 0.521301 & 0.73935 \tabularnewline
168 & 0.260618 & 0.521236 & 0.739382 \tabularnewline
169 & 0.238287 & 0.476574 & 0.761713 \tabularnewline
170 & 0.36044 & 0.72088 & 0.63956 \tabularnewline
171 & 0.393456 & 0.786912 & 0.606544 \tabularnewline
172 & 0.357977 & 0.715954 & 0.642023 \tabularnewline
173 & 0.457402 & 0.914805 & 0.542598 \tabularnewline
174 & 0.424107 & 0.848215 & 0.575893 \tabularnewline
175 & 0.492991 & 0.985983 & 0.507009 \tabularnewline
176 & 0.469484 & 0.938968 & 0.530516 \tabularnewline
177 & 0.467258 & 0.934517 & 0.532742 \tabularnewline
178 & 0.43566 & 0.871321 & 0.56434 \tabularnewline
179 & 0.408523 & 0.817046 & 0.591477 \tabularnewline
180 & 0.401923 & 0.803846 & 0.598077 \tabularnewline
181 & 0.366259 & 0.732518 & 0.633741 \tabularnewline
182 & 0.356771 & 0.713541 & 0.643229 \tabularnewline
183 & 0.382872 & 0.765743 & 0.617128 \tabularnewline
184 & 0.449505 & 0.899009 & 0.550495 \tabularnewline
185 & 0.67034 & 0.65932 & 0.32966 \tabularnewline
186 & 0.652336 & 0.695329 & 0.347664 \tabularnewline
187 & 0.63699 & 0.726021 & 0.36301 \tabularnewline
188 & 0.769844 & 0.460312 & 0.230156 \tabularnewline
189 & 0.751295 & 0.49741 & 0.248705 \tabularnewline
190 & 0.760963 & 0.478074 & 0.239037 \tabularnewline
191 & 0.731574 & 0.536851 & 0.268426 \tabularnewline
192 & 0.701244 & 0.597512 & 0.298756 \tabularnewline
193 & 0.674212 & 0.651576 & 0.325788 \tabularnewline
194 & 0.651577 & 0.696845 & 0.348423 \tabularnewline
195 & 0.61505 & 0.769901 & 0.38495 \tabularnewline
196 & 0.575291 & 0.849417 & 0.424709 \tabularnewline
197 & 0.554318 & 0.891365 & 0.445682 \tabularnewline
198 & 0.529768 & 0.940464 & 0.470232 \tabularnewline
199 & 0.487427 & 0.974854 & 0.512573 \tabularnewline
200 & 0.561569 & 0.876861 & 0.438431 \tabularnewline
201 & 0.533991 & 0.932018 & 0.466009 \tabularnewline
202 & 0.68055 & 0.638901 & 0.31945 \tabularnewline
203 & 0.67513 & 0.649739 & 0.32487 \tabularnewline
204 & 0.63475 & 0.730501 & 0.36525 \tabularnewline
205 & 0.594668 & 0.810664 & 0.405332 \tabularnewline
206 & 0.556415 & 0.887169 & 0.443585 \tabularnewline
207 & 0.523837 & 0.952326 & 0.476163 \tabularnewline
208 & 0.481517 & 0.963033 & 0.518483 \tabularnewline
209 & 0.45349 & 0.90698 & 0.54651 \tabularnewline
210 & 0.417112 & 0.834224 & 0.582888 \tabularnewline
211 & 0.373278 & 0.746556 & 0.626722 \tabularnewline
212 & 0.333396 & 0.666791 & 0.666604 \tabularnewline
213 & 0.39618 & 0.79236 & 0.60382 \tabularnewline
214 & 0.384991 & 0.769981 & 0.615009 \tabularnewline
215 & 0.34128 & 0.68256 & 0.65872 \tabularnewline
216 & 0.304335 & 0.608669 & 0.695665 \tabularnewline
217 & 0.276857 & 0.553713 & 0.723143 \tabularnewline
218 & 0.301871 & 0.603742 & 0.698129 \tabularnewline
219 & 0.270271 & 0.540542 & 0.729729 \tabularnewline
220 & 0.249857 & 0.499714 & 0.750143 \tabularnewline
221 & 0.21957 & 0.43914 & 0.78043 \tabularnewline
222 & 0.235464 & 0.470928 & 0.764536 \tabularnewline
223 & 0.197989 & 0.395979 & 0.802011 \tabularnewline
224 & 0.172008 & 0.344016 & 0.827992 \tabularnewline
225 & 0.262415 & 0.524829 & 0.737585 \tabularnewline
226 & 0.238153 & 0.476307 & 0.761847 \tabularnewline
227 & 0.211562 & 0.423123 & 0.788438 \tabularnewline
228 & 0.226845 & 0.453689 & 0.773155 \tabularnewline
229 & 0.18847 & 0.37694 & 0.81153 \tabularnewline
230 & 0.153308 & 0.306617 & 0.846692 \tabularnewline
231 & 0.146148 & 0.292296 & 0.853852 \tabularnewline
232 & 0.2655 & 0.531 & 0.7345 \tabularnewline
233 & 0.239818 & 0.479636 & 0.760182 \tabularnewline
234 & 0.317056 & 0.634113 & 0.682944 \tabularnewline
235 & 0.270519 & 0.541038 & 0.729481 \tabularnewline
236 & 0.300299 & 0.600597 & 0.699701 \tabularnewline
237 & 0.273373 & 0.546747 & 0.726627 \tabularnewline
238 & 0.375683 & 0.751366 & 0.624317 \tabularnewline
239 & 0.320198 & 0.640396 & 0.679802 \tabularnewline
240 & 0.517432 & 0.965136 & 0.482568 \tabularnewline
241 & 0.584048 & 0.831904 & 0.415952 \tabularnewline
242 & 0.509918 & 0.980165 & 0.490082 \tabularnewline
243 & 0.439347 & 0.878694 & 0.560653 \tabularnewline
244 & 0.389931 & 0.779863 & 0.610069 \tabularnewline
245 & 0.391802 & 0.783604 & 0.608198 \tabularnewline
246 & 0.61041 & 0.77918 & 0.38959 \tabularnewline
247 & 0.654593 & 0.690813 & 0.345407 \tabularnewline
248 & 0.629068 & 0.741865 & 0.370932 \tabularnewline
249 & 0.799465 & 0.40107 & 0.200535 \tabularnewline
250 & 0.806889 & 0.386222 & 0.193111 \tabularnewline
251 & 0.796953 & 0.406095 & 0.203047 \tabularnewline
252 & 0.824042 & 0.351917 & 0.175958 \tabularnewline
253 & 0.703307 & 0.593386 & 0.296693 \tabularnewline
254 & 0.552199 & 0.895602 & 0.447801 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225428&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]0.0456597[/C][C]0.0913194[/C][C]0.95434[/C][/ROW]
[ROW][C]11[/C][C]0.0124878[/C][C]0.0249756[/C][C]0.987512[/C][/ROW]
[ROW][C]12[/C][C]0.633589[/C][C]0.732822[/C][C]0.366411[/C][/ROW]
[ROW][C]13[/C][C]0.76431[/C][C]0.471381[/C][C]0.23569[/C][/ROW]
[ROW][C]14[/C][C]0.674994[/C][C]0.650013[/C][C]0.325006[/C][/ROW]
[ROW][C]15[/C][C]0.64612[/C][C]0.707759[/C][C]0.35388[/C][/ROW]
[ROW][C]16[/C][C]0.640743[/C][C]0.718513[/C][C]0.359257[/C][/ROW]
[ROW][C]17[/C][C]0.59257[/C][C]0.814859[/C][C]0.40743[/C][/ROW]
[ROW][C]18[/C][C]0.513988[/C][C]0.972023[/C][C]0.486012[/C][/ROW]
[ROW][C]19[/C][C]0.432355[/C][C]0.86471[/C][C]0.567645[/C][/ROW]
[ROW][C]20[/C][C]0.467941[/C][C]0.935882[/C][C]0.532059[/C][/ROW]
[ROW][C]21[/C][C]0.525823[/C][C]0.948353[/C][C]0.474177[/C][/ROW]
[ROW][C]22[/C][C]0.479739[/C][C]0.959478[/C][C]0.520261[/C][/ROW]
[ROW][C]23[/C][C]0.455886[/C][C]0.911772[/C][C]0.544114[/C][/ROW]
[ROW][C]24[/C][C]0.395143[/C][C]0.790287[/C][C]0.604857[/C][/ROW]
[ROW][C]25[/C][C]0.466993[/C][C]0.933987[/C][C]0.533007[/C][/ROW]
[ROW][C]26[/C][C]0.703565[/C][C]0.592869[/C][C]0.296435[/C][/ROW]
[ROW][C]27[/C][C]0.654688[/C][C]0.690624[/C][C]0.345312[/C][/ROW]
[ROW][C]28[/C][C]0.631268[/C][C]0.737464[/C][C]0.368732[/C][/ROW]
[ROW][C]29[/C][C]0.60546[/C][C]0.78908[/C][C]0.39454[/C][/ROW]
[ROW][C]30[/C][C]0.552003[/C][C]0.895994[/C][C]0.447997[/C][/ROW]
[ROW][C]31[/C][C]0.55916[/C][C]0.88168[/C][C]0.44084[/C][/ROW]
[ROW][C]32[/C][C]0.757235[/C][C]0.485531[/C][C]0.242765[/C][/ROW]
[ROW][C]33[/C][C]0.736385[/C][C]0.52723[/C][C]0.263615[/C][/ROW]
[ROW][C]34[/C][C]0.711214[/C][C]0.577572[/C][C]0.288786[/C][/ROW]
[ROW][C]35[/C][C]0.663177[/C][C]0.673647[/C][C]0.336823[/C][/ROW]
[ROW][C]36[/C][C]0.647845[/C][C]0.704309[/C][C]0.352155[/C][/ROW]
[ROW][C]37[/C][C]0.646373[/C][C]0.707253[/C][C]0.353627[/C][/ROW]
[ROW][C]38[/C][C]0.60122[/C][C]0.79756[/C][C]0.39878[/C][/ROW]
[ROW][C]39[/C][C]0.661541[/C][C]0.676918[/C][C]0.338459[/C][/ROW]
[ROW][C]40[/C][C]0.613697[/C][C]0.772605[/C][C]0.386303[/C][/ROW]
[ROW][C]41[/C][C]0.593424[/C][C]0.813151[/C][C]0.406576[/C][/ROW]
[ROW][C]42[/C][C]0.544284[/C][C]0.911431[/C][C]0.455716[/C][/ROW]
[ROW][C]43[/C][C]0.519295[/C][C]0.96141[/C][C]0.480705[/C][/ROW]
[ROW][C]44[/C][C]0.473218[/C][C]0.946436[/C][C]0.526782[/C][/ROW]
[ROW][C]45[/C][C]0.533498[/C][C]0.933004[/C][C]0.466502[/C][/ROW]
[ROW][C]46[/C][C]0.498959[/C][C]0.997918[/C][C]0.501041[/C][/ROW]
[ROW][C]47[/C][C]0.451362[/C][C]0.902724[/C][C]0.548638[/C][/ROW]
[ROW][C]48[/C][C]0.422409[/C][C]0.844818[/C][C]0.577591[/C][/ROW]
[ROW][C]49[/C][C]0.375489[/C][C]0.750978[/C][C]0.624511[/C][/ROW]
[ROW][C]50[/C][C]0.37615[/C][C]0.752299[/C][C]0.62385[/C][/ROW]
[ROW][C]51[/C][C]0.435949[/C][C]0.871897[/C][C]0.564051[/C][/ROW]
[ROW][C]52[/C][C]0.399665[/C][C]0.799331[/C][C]0.600335[/C][/ROW]
[ROW][C]53[/C][C]0.367355[/C][C]0.73471[/C][C]0.632645[/C][/ROW]
[ROW][C]54[/C][C]0.336089[/C][C]0.672178[/C][C]0.663911[/C][/ROW]
[ROW][C]55[/C][C]0.302336[/C][C]0.604672[/C][C]0.697664[/C][/ROW]
[ROW][C]56[/C][C]0.300338[/C][C]0.600675[/C][C]0.699662[/C][/ROW]
[ROW][C]57[/C][C]0.319069[/C][C]0.638137[/C][C]0.680931[/C][/ROW]
[ROW][C]58[/C][C]0.432528[/C][C]0.865055[/C][C]0.567472[/C][/ROW]
[ROW][C]59[/C][C]0.397692[/C][C]0.795384[/C][C]0.602308[/C][/ROW]
[ROW][C]60[/C][C]0.357864[/C][C]0.715728[/C][C]0.642136[/C][/ROW]
[ROW][C]61[/C][C]0.321634[/C][C]0.643268[/C][C]0.678366[/C][/ROW]
[ROW][C]62[/C][C]0.31449[/C][C]0.628981[/C][C]0.68551[/C][/ROW]
[ROW][C]63[/C][C]0.284268[/C][C]0.568536[/C][C]0.715732[/C][/ROW]
[ROW][C]64[/C][C]0.29362[/C][C]0.58724[/C][C]0.70638[/C][/ROW]
[ROW][C]65[/C][C]0.25909[/C][C]0.518179[/C][C]0.74091[/C][/ROW]
[ROW][C]66[/C][C]0.227739[/C][C]0.455477[/C][C]0.772261[/C][/ROW]
[ROW][C]67[/C][C]0.202411[/C][C]0.404821[/C][C]0.797589[/C][/ROW]
[ROW][C]68[/C][C]0.19231[/C][C]0.38462[/C][C]0.80769[/C][/ROW]
[ROW][C]69[/C][C]0.176516[/C][C]0.353032[/C][C]0.823484[/C][/ROW]
[ROW][C]70[/C][C]0.151988[/C][C]0.303976[/C][C]0.848012[/C][/ROW]
[ROW][C]71[/C][C]0.146731[/C][C]0.293461[/C][C]0.853269[/C][/ROW]
[ROW][C]72[/C][C]0.172423[/C][C]0.344846[/C][C]0.827577[/C][/ROW]
[ROW][C]73[/C][C]0.163399[/C][C]0.326798[/C][C]0.836601[/C][/ROW]
[ROW][C]74[/C][C]0.140134[/C][C]0.280267[/C][C]0.859866[/C][/ROW]
[ROW][C]75[/C][C]0.123815[/C][C]0.24763[/C][C]0.876185[/C][/ROW]
[ROW][C]76[/C][C]0.185251[/C][C]0.370501[/C][C]0.814749[/C][/ROW]
[ROW][C]77[/C][C]0.16186[/C][C]0.32372[/C][C]0.83814[/C][/ROW]
[ROW][C]78[/C][C]0.13917[/C][C]0.278339[/C][C]0.86083[/C][/ROW]
[ROW][C]79[/C][C]0.198063[/C][C]0.396126[/C][C]0.801937[/C][/ROW]
[ROW][C]80[/C][C]0.229015[/C][C]0.458031[/C][C]0.770985[/C][/ROW]
[ROW][C]81[/C][C]0.216209[/C][C]0.432418[/C][C]0.783791[/C][/ROW]
[ROW][C]82[/C][C]0.191525[/C][C]0.383051[/C][C]0.808475[/C][/ROW]
[ROW][C]83[/C][C]0.181625[/C][C]0.36325[/C][C]0.818375[/C][/ROW]
[ROW][C]84[/C][C]0.174247[/C][C]0.348493[/C][C]0.825753[/C][/ROW]
[ROW][C]85[/C][C]0.152225[/C][C]0.30445[/C][C]0.847775[/C][/ROW]
[ROW][C]86[/C][C]0.137664[/C][C]0.275329[/C][C]0.862336[/C][/ROW]
[ROW][C]87[/C][C]0.122683[/C][C]0.245366[/C][C]0.877317[/C][/ROW]
[ROW][C]88[/C][C]0.13905[/C][C]0.2781[/C][C]0.86095[/C][/ROW]
[ROW][C]89[/C][C]0.118664[/C][C]0.237328[/C][C]0.881336[/C][/ROW]
[ROW][C]90[/C][C]0.134005[/C][C]0.268009[/C][C]0.865995[/C][/ROW]
[ROW][C]91[/C][C]0.1248[/C][C]0.2496[/C][C]0.8752[/C][/ROW]
[ROW][C]92[/C][C]0.112139[/C][C]0.224277[/C][C]0.887861[/C][/ROW]
[ROW][C]93[/C][C]0.0973615[/C][C]0.194723[/C][C]0.902638[/C][/ROW]
[ROW][C]94[/C][C]0.109542[/C][C]0.219084[/C][C]0.890458[/C][/ROW]
[ROW][C]95[/C][C]0.113763[/C][C]0.227526[/C][C]0.886237[/C][/ROW]
[ROW][C]96[/C][C]0.10545[/C][C]0.2109[/C][C]0.89455[/C][/ROW]
[ROW][C]97[/C][C]0.0933282[/C][C]0.186656[/C][C]0.906672[/C][/ROW]
[ROW][C]98[/C][C]0.0847228[/C][C]0.169446[/C][C]0.915277[/C][/ROW]
[ROW][C]99[/C][C]0.0861847[/C][C]0.172369[/C][C]0.913815[/C][/ROW]
[ROW][C]100[/C][C]0.078977[/C][C]0.157954[/C][C]0.921023[/C][/ROW]
[ROW][C]101[/C][C]0.0732046[/C][C]0.146409[/C][C]0.926795[/C][/ROW]
[ROW][C]102[/C][C]0.0611354[/C][C]0.122271[/C][C]0.938865[/C][/ROW]
[ROW][C]103[/C][C]0.0517032[/C][C]0.103406[/C][C]0.948297[/C][/ROW]
[ROW][C]104[/C][C]0.0500594[/C][C]0.100119[/C][C]0.949941[/C][/ROW]
[ROW][C]105[/C][C]0.0924833[/C][C]0.184967[/C][C]0.907517[/C][/ROW]
[ROW][C]106[/C][C]0.0883016[/C][C]0.176603[/C][C]0.911698[/C][/ROW]
[ROW][C]107[/C][C]0.10709[/C][C]0.214181[/C][C]0.89291[/C][/ROW]
[ROW][C]108[/C][C]0.0952257[/C][C]0.190451[/C][C]0.904774[/C][/ROW]
[ROW][C]109[/C][C]0.145068[/C][C]0.290136[/C][C]0.854932[/C][/ROW]
[ROW][C]110[/C][C]0.1662[/C][C]0.3324[/C][C]0.8338[/C][/ROW]
[ROW][C]111[/C][C]0.16181[/C][C]0.323619[/C][C]0.83819[/C][/ROW]
[ROW][C]112[/C][C]0.199055[/C][C]0.398109[/C][C]0.800945[/C][/ROW]
[ROW][C]113[/C][C]0.185821[/C][C]0.371642[/C][C]0.814179[/C][/ROW]
[ROW][C]114[/C][C]0.172791[/C][C]0.345583[/C][C]0.827209[/C][/ROW]
[ROW][C]115[/C][C]0.167417[/C][C]0.334833[/C][C]0.832583[/C][/ROW]
[ROW][C]116[/C][C]0.169306[/C][C]0.338612[/C][C]0.830694[/C][/ROW]
[ROW][C]117[/C][C]0.16511[/C][C]0.330219[/C][C]0.83489[/C][/ROW]
[ROW][C]118[/C][C]0.150096[/C][C]0.300192[/C][C]0.849904[/C][/ROW]
[ROW][C]119[/C][C]0.142319[/C][C]0.284638[/C][C]0.857681[/C][/ROW]
[ROW][C]120[/C][C]0.130897[/C][C]0.261793[/C][C]0.869103[/C][/ROW]
[ROW][C]121[/C][C]0.117174[/C][C]0.234349[/C][C]0.882826[/C][/ROW]
[ROW][C]122[/C][C]0.103207[/C][C]0.206414[/C][C]0.896793[/C][/ROW]
[ROW][C]123[/C][C]0.0885631[/C][C]0.177126[/C][C]0.911437[/C][/ROW]
[ROW][C]124[/C][C]0.0833389[/C][C]0.166678[/C][C]0.916661[/C][/ROW]
[ROW][C]125[/C][C]0.0810903[/C][C]0.162181[/C][C]0.91891[/C][/ROW]
[ROW][C]126[/C][C]0.0972784[/C][C]0.194557[/C][C]0.902722[/C][/ROW]
[ROW][C]127[/C][C]0.176425[/C][C]0.352851[/C][C]0.823575[/C][/ROW]
[ROW][C]128[/C][C]0.173591[/C][C]0.347183[/C][C]0.826409[/C][/ROW]
[ROW][C]129[/C][C]0.15434[/C][C]0.30868[/C][C]0.84566[/C][/ROW]
[ROW][C]130[/C][C]0.140406[/C][C]0.280811[/C][C]0.859594[/C][/ROW]
[ROW][C]131[/C][C]0.16444[/C][C]0.32888[/C][C]0.83556[/C][/ROW]
[ROW][C]132[/C][C]0.179922[/C][C]0.359843[/C][C]0.820078[/C][/ROW]
[ROW][C]133[/C][C]0.225166[/C][C]0.450331[/C][C]0.774834[/C][/ROW]
[ROW][C]134[/C][C]0.200693[/C][C]0.401387[/C][C]0.799307[/C][/ROW]
[ROW][C]135[/C][C]0.178757[/C][C]0.357513[/C][C]0.821243[/C][/ROW]
[ROW][C]136[/C][C]0.158774[/C][C]0.317549[/C][C]0.841226[/C][/ROW]
[ROW][C]137[/C][C]0.139736[/C][C]0.279473[/C][C]0.860264[/C][/ROW]
[ROW][C]138[/C][C]0.155917[/C][C]0.311834[/C][C]0.844083[/C][/ROW]
[ROW][C]139[/C][C]0.136054[/C][C]0.272108[/C][C]0.863946[/C][/ROW]
[ROW][C]140[/C][C]0.138565[/C][C]0.27713[/C][C]0.861435[/C][/ROW]
[ROW][C]141[/C][C]0.128393[/C][C]0.256787[/C][C]0.871607[/C][/ROW]
[ROW][C]142[/C][C]0.164787[/C][C]0.329575[/C][C]0.835213[/C][/ROW]
[ROW][C]143[/C][C]0.192908[/C][C]0.385816[/C][C]0.807092[/C][/ROW]
[ROW][C]144[/C][C]0.180741[/C][C]0.361482[/C][C]0.819259[/C][/ROW]
[ROW][C]145[/C][C]0.262083[/C][C]0.524165[/C][C]0.737917[/C][/ROW]
[ROW][C]146[/C][C]0.239509[/C][C]0.479018[/C][C]0.760491[/C][/ROW]
[ROW][C]147[/C][C]0.214253[/C][C]0.428507[/C][C]0.785747[/C][/ROW]
[ROW][C]148[/C][C]0.191753[/C][C]0.383507[/C][C]0.808247[/C][/ROW]
[ROW][C]149[/C][C]0.176274[/C][C]0.352548[/C][C]0.823726[/C][/ROW]
[ROW][C]150[/C][C]0.156117[/C][C]0.312235[/C][C]0.843883[/C][/ROW]
[ROW][C]151[/C][C]0.236071[/C][C]0.472142[/C][C]0.763929[/C][/ROW]
[ROW][C]152[/C][C]0.2185[/C][C]0.437[/C][C]0.7815[/C][/ROW]
[ROW][C]153[/C][C]0.19898[/C][C]0.39796[/C][C]0.80102[/C][/ROW]
[ROW][C]154[/C][C]0.211724[/C][C]0.423448[/C][C]0.788276[/C][/ROW]
[ROW][C]155[/C][C]0.187217[/C][C]0.374433[/C][C]0.812783[/C][/ROW]
[ROW][C]156[/C][C]0.183037[/C][C]0.366074[/C][C]0.816963[/C][/ROW]
[ROW][C]157[/C][C]0.18975[/C][C]0.379501[/C][C]0.81025[/C][/ROW]
[ROW][C]158[/C][C]0.185643[/C][C]0.371286[/C][C]0.814357[/C][/ROW]
[ROW][C]159[/C][C]0.164623[/C][C]0.329246[/C][C]0.835377[/C][/ROW]
[ROW][C]160[/C][C]0.167742[/C][C]0.335485[/C][C]0.832258[/C][/ROW]
[ROW][C]161[/C][C]0.152634[/C][C]0.305269[/C][C]0.847366[/C][/ROW]
[ROW][C]162[/C][C]0.147469[/C][C]0.294938[/C][C]0.852531[/C][/ROW]
[ROW][C]163[/C][C]0.136856[/C][C]0.273711[/C][C]0.863144[/C][/ROW]
[ROW][C]164[/C][C]0.170449[/C][C]0.340899[/C][C]0.829551[/C][/ROW]
[ROW][C]165[/C][C]0.156167[/C][C]0.312335[/C][C]0.843833[/C][/ROW]
[ROW][C]166[/C][C]0.255412[/C][C]0.510825[/C][C]0.744588[/C][/ROW]
[ROW][C]167[/C][C]0.26065[/C][C]0.521301[/C][C]0.73935[/C][/ROW]
[ROW][C]168[/C][C]0.260618[/C][C]0.521236[/C][C]0.739382[/C][/ROW]
[ROW][C]169[/C][C]0.238287[/C][C]0.476574[/C][C]0.761713[/C][/ROW]
[ROW][C]170[/C][C]0.36044[/C][C]0.72088[/C][C]0.63956[/C][/ROW]
[ROW][C]171[/C][C]0.393456[/C][C]0.786912[/C][C]0.606544[/C][/ROW]
[ROW][C]172[/C][C]0.357977[/C][C]0.715954[/C][C]0.642023[/C][/ROW]
[ROW][C]173[/C][C]0.457402[/C][C]0.914805[/C][C]0.542598[/C][/ROW]
[ROW][C]174[/C][C]0.424107[/C][C]0.848215[/C][C]0.575893[/C][/ROW]
[ROW][C]175[/C][C]0.492991[/C][C]0.985983[/C][C]0.507009[/C][/ROW]
[ROW][C]176[/C][C]0.469484[/C][C]0.938968[/C][C]0.530516[/C][/ROW]
[ROW][C]177[/C][C]0.467258[/C][C]0.934517[/C][C]0.532742[/C][/ROW]
[ROW][C]178[/C][C]0.43566[/C][C]0.871321[/C][C]0.56434[/C][/ROW]
[ROW][C]179[/C][C]0.408523[/C][C]0.817046[/C][C]0.591477[/C][/ROW]
[ROW][C]180[/C][C]0.401923[/C][C]0.803846[/C][C]0.598077[/C][/ROW]
[ROW][C]181[/C][C]0.366259[/C][C]0.732518[/C][C]0.633741[/C][/ROW]
[ROW][C]182[/C][C]0.356771[/C][C]0.713541[/C][C]0.643229[/C][/ROW]
[ROW][C]183[/C][C]0.382872[/C][C]0.765743[/C][C]0.617128[/C][/ROW]
[ROW][C]184[/C][C]0.449505[/C][C]0.899009[/C][C]0.550495[/C][/ROW]
[ROW][C]185[/C][C]0.67034[/C][C]0.65932[/C][C]0.32966[/C][/ROW]
[ROW][C]186[/C][C]0.652336[/C][C]0.695329[/C][C]0.347664[/C][/ROW]
[ROW][C]187[/C][C]0.63699[/C][C]0.726021[/C][C]0.36301[/C][/ROW]
[ROW][C]188[/C][C]0.769844[/C][C]0.460312[/C][C]0.230156[/C][/ROW]
[ROW][C]189[/C][C]0.751295[/C][C]0.49741[/C][C]0.248705[/C][/ROW]
[ROW][C]190[/C][C]0.760963[/C][C]0.478074[/C][C]0.239037[/C][/ROW]
[ROW][C]191[/C][C]0.731574[/C][C]0.536851[/C][C]0.268426[/C][/ROW]
[ROW][C]192[/C][C]0.701244[/C][C]0.597512[/C][C]0.298756[/C][/ROW]
[ROW][C]193[/C][C]0.674212[/C][C]0.651576[/C][C]0.325788[/C][/ROW]
[ROW][C]194[/C][C]0.651577[/C][C]0.696845[/C][C]0.348423[/C][/ROW]
[ROW][C]195[/C][C]0.61505[/C][C]0.769901[/C][C]0.38495[/C][/ROW]
[ROW][C]196[/C][C]0.575291[/C][C]0.849417[/C][C]0.424709[/C][/ROW]
[ROW][C]197[/C][C]0.554318[/C][C]0.891365[/C][C]0.445682[/C][/ROW]
[ROW][C]198[/C][C]0.529768[/C][C]0.940464[/C][C]0.470232[/C][/ROW]
[ROW][C]199[/C][C]0.487427[/C][C]0.974854[/C][C]0.512573[/C][/ROW]
[ROW][C]200[/C][C]0.561569[/C][C]0.876861[/C][C]0.438431[/C][/ROW]
[ROW][C]201[/C][C]0.533991[/C][C]0.932018[/C][C]0.466009[/C][/ROW]
[ROW][C]202[/C][C]0.68055[/C][C]0.638901[/C][C]0.31945[/C][/ROW]
[ROW][C]203[/C][C]0.67513[/C][C]0.649739[/C][C]0.32487[/C][/ROW]
[ROW][C]204[/C][C]0.63475[/C][C]0.730501[/C][C]0.36525[/C][/ROW]
[ROW][C]205[/C][C]0.594668[/C][C]0.810664[/C][C]0.405332[/C][/ROW]
[ROW][C]206[/C][C]0.556415[/C][C]0.887169[/C][C]0.443585[/C][/ROW]
[ROW][C]207[/C][C]0.523837[/C][C]0.952326[/C][C]0.476163[/C][/ROW]
[ROW][C]208[/C][C]0.481517[/C][C]0.963033[/C][C]0.518483[/C][/ROW]
[ROW][C]209[/C][C]0.45349[/C][C]0.90698[/C][C]0.54651[/C][/ROW]
[ROW][C]210[/C][C]0.417112[/C][C]0.834224[/C][C]0.582888[/C][/ROW]
[ROW][C]211[/C][C]0.373278[/C][C]0.746556[/C][C]0.626722[/C][/ROW]
[ROW][C]212[/C][C]0.333396[/C][C]0.666791[/C][C]0.666604[/C][/ROW]
[ROW][C]213[/C][C]0.39618[/C][C]0.79236[/C][C]0.60382[/C][/ROW]
[ROW][C]214[/C][C]0.384991[/C][C]0.769981[/C][C]0.615009[/C][/ROW]
[ROW][C]215[/C][C]0.34128[/C][C]0.68256[/C][C]0.65872[/C][/ROW]
[ROW][C]216[/C][C]0.304335[/C][C]0.608669[/C][C]0.695665[/C][/ROW]
[ROW][C]217[/C][C]0.276857[/C][C]0.553713[/C][C]0.723143[/C][/ROW]
[ROW][C]218[/C][C]0.301871[/C][C]0.603742[/C][C]0.698129[/C][/ROW]
[ROW][C]219[/C][C]0.270271[/C][C]0.540542[/C][C]0.729729[/C][/ROW]
[ROW][C]220[/C][C]0.249857[/C][C]0.499714[/C][C]0.750143[/C][/ROW]
[ROW][C]221[/C][C]0.21957[/C][C]0.43914[/C][C]0.78043[/C][/ROW]
[ROW][C]222[/C][C]0.235464[/C][C]0.470928[/C][C]0.764536[/C][/ROW]
[ROW][C]223[/C][C]0.197989[/C][C]0.395979[/C][C]0.802011[/C][/ROW]
[ROW][C]224[/C][C]0.172008[/C][C]0.344016[/C][C]0.827992[/C][/ROW]
[ROW][C]225[/C][C]0.262415[/C][C]0.524829[/C][C]0.737585[/C][/ROW]
[ROW][C]226[/C][C]0.238153[/C][C]0.476307[/C][C]0.761847[/C][/ROW]
[ROW][C]227[/C][C]0.211562[/C][C]0.423123[/C][C]0.788438[/C][/ROW]
[ROW][C]228[/C][C]0.226845[/C][C]0.453689[/C][C]0.773155[/C][/ROW]
[ROW][C]229[/C][C]0.18847[/C][C]0.37694[/C][C]0.81153[/C][/ROW]
[ROW][C]230[/C][C]0.153308[/C][C]0.306617[/C][C]0.846692[/C][/ROW]
[ROW][C]231[/C][C]0.146148[/C][C]0.292296[/C][C]0.853852[/C][/ROW]
[ROW][C]232[/C][C]0.2655[/C][C]0.531[/C][C]0.7345[/C][/ROW]
[ROW][C]233[/C][C]0.239818[/C][C]0.479636[/C][C]0.760182[/C][/ROW]
[ROW][C]234[/C][C]0.317056[/C][C]0.634113[/C][C]0.682944[/C][/ROW]
[ROW][C]235[/C][C]0.270519[/C][C]0.541038[/C][C]0.729481[/C][/ROW]
[ROW][C]236[/C][C]0.300299[/C][C]0.600597[/C][C]0.699701[/C][/ROW]
[ROW][C]237[/C][C]0.273373[/C][C]0.546747[/C][C]0.726627[/C][/ROW]
[ROW][C]238[/C][C]0.375683[/C][C]0.751366[/C][C]0.624317[/C][/ROW]
[ROW][C]239[/C][C]0.320198[/C][C]0.640396[/C][C]0.679802[/C][/ROW]
[ROW][C]240[/C][C]0.517432[/C][C]0.965136[/C][C]0.482568[/C][/ROW]
[ROW][C]241[/C][C]0.584048[/C][C]0.831904[/C][C]0.415952[/C][/ROW]
[ROW][C]242[/C][C]0.509918[/C][C]0.980165[/C][C]0.490082[/C][/ROW]
[ROW][C]243[/C][C]0.439347[/C][C]0.878694[/C][C]0.560653[/C][/ROW]
[ROW][C]244[/C][C]0.389931[/C][C]0.779863[/C][C]0.610069[/C][/ROW]
[ROW][C]245[/C][C]0.391802[/C][C]0.783604[/C][C]0.608198[/C][/ROW]
[ROW][C]246[/C][C]0.61041[/C][C]0.77918[/C][C]0.38959[/C][/ROW]
[ROW][C]247[/C][C]0.654593[/C][C]0.690813[/C][C]0.345407[/C][/ROW]
[ROW][C]248[/C][C]0.629068[/C][C]0.741865[/C][C]0.370932[/C][/ROW]
[ROW][C]249[/C][C]0.799465[/C][C]0.40107[/C][C]0.200535[/C][/ROW]
[ROW][C]250[/C][C]0.806889[/C][C]0.386222[/C][C]0.193111[/C][/ROW]
[ROW][C]251[/C][C]0.796953[/C][C]0.406095[/C][C]0.203047[/C][/ROW]
[ROW][C]252[/C][C]0.824042[/C][C]0.351917[/C][C]0.175958[/C][/ROW]
[ROW][C]253[/C][C]0.703307[/C][C]0.593386[/C][C]0.296693[/C][/ROW]
[ROW][C]254[/C][C]0.552199[/C][C]0.895602[/C][C]0.447801[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225428&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225428&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
100.04565970.09131940.95434
110.01248780.02497560.987512
120.6335890.7328220.366411
130.764310.4713810.23569
140.6749940.6500130.325006
150.646120.7077590.35388
160.6407430.7185130.359257
170.592570.8148590.40743
180.5139880.9720230.486012
190.4323550.864710.567645
200.4679410.9358820.532059
210.5258230.9483530.474177
220.4797390.9594780.520261
230.4558860.9117720.544114
240.3951430.7902870.604857
250.4669930.9339870.533007
260.7035650.5928690.296435
270.6546880.6906240.345312
280.6312680.7374640.368732
290.605460.789080.39454
300.5520030.8959940.447997
310.559160.881680.44084
320.7572350.4855310.242765
330.7363850.527230.263615
340.7112140.5775720.288786
350.6631770.6736470.336823
360.6478450.7043090.352155
370.6463730.7072530.353627
380.601220.797560.39878
390.6615410.6769180.338459
400.6136970.7726050.386303
410.5934240.8131510.406576
420.5442840.9114310.455716
430.5192950.961410.480705
440.4732180.9464360.526782
450.5334980.9330040.466502
460.4989590.9979180.501041
470.4513620.9027240.548638
480.4224090.8448180.577591
490.3754890.7509780.624511
500.376150.7522990.62385
510.4359490.8718970.564051
520.3996650.7993310.600335
530.3673550.734710.632645
540.3360890.6721780.663911
550.3023360.6046720.697664
560.3003380.6006750.699662
570.3190690.6381370.680931
580.4325280.8650550.567472
590.3976920.7953840.602308
600.3578640.7157280.642136
610.3216340.6432680.678366
620.314490.6289810.68551
630.2842680.5685360.715732
640.293620.587240.70638
650.259090.5181790.74091
660.2277390.4554770.772261
670.2024110.4048210.797589
680.192310.384620.80769
690.1765160.3530320.823484
700.1519880.3039760.848012
710.1467310.2934610.853269
720.1724230.3448460.827577
730.1633990.3267980.836601
740.1401340.2802670.859866
750.1238150.247630.876185
760.1852510.3705010.814749
770.161860.323720.83814
780.139170.2783390.86083
790.1980630.3961260.801937
800.2290150.4580310.770985
810.2162090.4324180.783791
820.1915250.3830510.808475
830.1816250.363250.818375
840.1742470.3484930.825753
850.1522250.304450.847775
860.1376640.2753290.862336
870.1226830.2453660.877317
880.139050.27810.86095
890.1186640.2373280.881336
900.1340050.2680090.865995
910.12480.24960.8752
920.1121390.2242770.887861
930.09736150.1947230.902638
940.1095420.2190840.890458
950.1137630.2275260.886237
960.105450.21090.89455
970.09332820.1866560.906672
980.08472280.1694460.915277
990.08618470.1723690.913815
1000.0789770.1579540.921023
1010.07320460.1464090.926795
1020.06113540.1222710.938865
1030.05170320.1034060.948297
1040.05005940.1001190.949941
1050.09248330.1849670.907517
1060.08830160.1766030.911698
1070.107090.2141810.89291
1080.09522570.1904510.904774
1090.1450680.2901360.854932
1100.16620.33240.8338
1110.161810.3236190.83819
1120.1990550.3981090.800945
1130.1858210.3716420.814179
1140.1727910.3455830.827209
1150.1674170.3348330.832583
1160.1693060.3386120.830694
1170.165110.3302190.83489
1180.1500960.3001920.849904
1190.1423190.2846380.857681
1200.1308970.2617930.869103
1210.1171740.2343490.882826
1220.1032070.2064140.896793
1230.08856310.1771260.911437
1240.08333890.1666780.916661
1250.08109030.1621810.91891
1260.09727840.1945570.902722
1270.1764250.3528510.823575
1280.1735910.3471830.826409
1290.154340.308680.84566
1300.1404060.2808110.859594
1310.164440.328880.83556
1320.1799220.3598430.820078
1330.2251660.4503310.774834
1340.2006930.4013870.799307
1350.1787570.3575130.821243
1360.1587740.3175490.841226
1370.1397360.2794730.860264
1380.1559170.3118340.844083
1390.1360540.2721080.863946
1400.1385650.277130.861435
1410.1283930.2567870.871607
1420.1647870.3295750.835213
1430.1929080.3858160.807092
1440.1807410.3614820.819259
1450.2620830.5241650.737917
1460.2395090.4790180.760491
1470.2142530.4285070.785747
1480.1917530.3835070.808247
1490.1762740.3525480.823726
1500.1561170.3122350.843883
1510.2360710.4721420.763929
1520.21850.4370.7815
1530.198980.397960.80102
1540.2117240.4234480.788276
1550.1872170.3744330.812783
1560.1830370.3660740.816963
1570.189750.3795010.81025
1580.1856430.3712860.814357
1590.1646230.3292460.835377
1600.1677420.3354850.832258
1610.1526340.3052690.847366
1620.1474690.2949380.852531
1630.1368560.2737110.863144
1640.1704490.3408990.829551
1650.1561670.3123350.843833
1660.2554120.5108250.744588
1670.260650.5213010.73935
1680.2606180.5212360.739382
1690.2382870.4765740.761713
1700.360440.720880.63956
1710.3934560.7869120.606544
1720.3579770.7159540.642023
1730.4574020.9148050.542598
1740.4241070.8482150.575893
1750.4929910.9859830.507009
1760.4694840.9389680.530516
1770.4672580.9345170.532742
1780.435660.8713210.56434
1790.4085230.8170460.591477
1800.4019230.8038460.598077
1810.3662590.7325180.633741
1820.3567710.7135410.643229
1830.3828720.7657430.617128
1840.4495050.8990090.550495
1850.670340.659320.32966
1860.6523360.6953290.347664
1870.636990.7260210.36301
1880.7698440.4603120.230156
1890.7512950.497410.248705
1900.7609630.4780740.239037
1910.7315740.5368510.268426
1920.7012440.5975120.298756
1930.6742120.6515760.325788
1940.6515770.6968450.348423
1950.615050.7699010.38495
1960.5752910.8494170.424709
1970.5543180.8913650.445682
1980.5297680.9404640.470232
1990.4874270.9748540.512573
2000.5615690.8768610.438431
2010.5339910.9320180.466009
2020.680550.6389010.31945
2030.675130.6497390.32487
2040.634750.7305010.36525
2050.5946680.8106640.405332
2060.5564150.8871690.443585
2070.5238370.9523260.476163
2080.4815170.9630330.518483
2090.453490.906980.54651
2100.4171120.8342240.582888
2110.3732780.7465560.626722
2120.3333960.6667910.666604
2130.396180.792360.60382
2140.3849910.7699810.615009
2150.341280.682560.65872
2160.3043350.6086690.695665
2170.2768570.5537130.723143
2180.3018710.6037420.698129
2190.2702710.5405420.729729
2200.2498570.4997140.750143
2210.219570.439140.78043
2220.2354640.4709280.764536
2230.1979890.3959790.802011
2240.1720080.3440160.827992
2250.2624150.5248290.737585
2260.2381530.4763070.761847
2270.2115620.4231230.788438
2280.2268450.4536890.773155
2290.188470.376940.81153
2300.1533080.3066170.846692
2310.1461480.2922960.853852
2320.26550.5310.7345
2330.2398180.4796360.760182
2340.3170560.6341130.682944
2350.2705190.5410380.729481
2360.3002990.6005970.699701
2370.2733730.5467470.726627
2380.3756830.7513660.624317
2390.3201980.6403960.679802
2400.5174320.9651360.482568
2410.5840480.8319040.415952
2420.5099180.9801650.490082
2430.4393470.8786940.560653
2440.3899310.7798630.610069
2450.3918020.7836040.608198
2460.610410.779180.38959
2470.6545930.6908130.345407
2480.6290680.7418650.370932
2490.7994650.401070.200535
2500.8068890.3862220.193111
2510.7969530.4060950.203047
2520.8240420.3519170.175958
2530.7033070.5933860.296693
2540.5521990.8956020.447801






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.00408163OK
10% type I error level20.00816327OK

\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 & 1 & 0.00408163 & OK \tabularnewline
10% type I error level & 2 & 0.00816327 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225428&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]1[/C][C]0.00408163[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]2[/C][C]0.00816327[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225428&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225428&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 level10.00408163OK
10% type I error level20.00816327OK


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')
}