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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 18 Nov 2013 12:08:26 -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/18/t1384794540wtubsmirzc2k65t.htm/, Retrieved Sat, 27 Apr 2024 07:18:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226174, Retrieved Sat, 27 Apr 2024 07:18:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact49

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [time effect in su...] [2010-11-17 08:55:33] [b98453cac15ba1066b407e146608df68]
- RMPD    [Multiple Regression] [WS 7] [2013-11-18 17:08:26] [93c26c69267707c240373d21fead6bfa] [Current]
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Dataset

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

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=226174&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=226174&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226174&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
Happiness[t] = + 12.8069 + 0.0046016Connected[t] + 0.0115701Separate[t] + 0.0797831Learning[t] -0.0411911Software[t] -0.363249Depression[t] + 0.0253404Sport1[t] + 0.361015Month[t] -0.00790136t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  12.8069 +  0.0046016Connected[t] +  0.0115701Separate[t] +  0.0797831Learning[t] -0.0411911Software[t] -0.363249Depression[t] +  0.0253404Sport1[t] +  0.361015Month[t] -0.00790136t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226174&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  12.8069 +  0.0046016Connected[t] +  0.0115701Separate[t] +  0.0797831Learning[t] -0.0411911Software[t] -0.363249Depression[t] +  0.0253404Sport1[t] +  0.361015Month[t] -0.00790136t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226174&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226174&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
Happiness[t] = + 12.8069 + 0.0046016Connected[t] + 0.0115701Separate[t] + 0.0797831Learning[t] -0.0411911Software[t] -0.363249Depression[t] + 0.0253404Sport1[t] + 0.361015Month[t] -0.00790136t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)12.80694.108033.1180.002032810.00101641
Connected0.00460160.03724750.12350.9017760.450888
Separate0.01157010.03794250.30490.7606630.380331
Learning0.07978310.06726051.1860.2366550.118327
Software-0.04119110.0695991-0.59180.5544860.277243
Depression-0.3632490.0392079-9.2658.46015e-184.23008e-18
Sport10.02534040.01274291.9890.04781650.0239083
Month0.3610150.4338850.83210.4061580.203079
t-0.007901360.00461614-1.7120.0881710.0440855

\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) & 12.8069 & 4.10803 & 3.118 & 0.00203281 & 0.00101641 \tabularnewline
Connected & 0.0046016 & 0.0372475 & 0.1235 & 0.901776 & 0.450888 \tabularnewline
Separate & 0.0115701 & 0.0379425 & 0.3049 & 0.760663 & 0.380331 \tabularnewline
Learning & 0.0797831 & 0.0672605 & 1.186 & 0.236655 & 0.118327 \tabularnewline
Software & -0.0411911 & 0.0695991 & -0.5918 & 0.554486 & 0.277243 \tabularnewline
Depression & -0.363249 & 0.0392079 & -9.265 & 8.46015e-18 & 4.23008e-18 \tabularnewline
Sport1 & 0.0253404 & 0.0127429 & 1.989 & 0.0478165 & 0.0239083 \tabularnewline
Month & 0.361015 & 0.433885 & 0.8321 & 0.406158 & 0.203079 \tabularnewline
t & -0.00790136 & 0.00461614 & -1.712 & 0.088171 & 0.0440855 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226174&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]12.8069[/C][C]4.10803[/C][C]3.118[/C][C]0.00203281[/C][C]0.00101641[/C][/ROW]
[ROW][C]Connected[/C][C]0.0046016[/C][C]0.0372475[/C][C]0.1235[/C][C]0.901776[/C][C]0.450888[/C][/ROW]
[ROW][C]Separate[/C][C]0.0115701[/C][C]0.0379425[/C][C]0.3049[/C][C]0.760663[/C][C]0.380331[/C][/ROW]
[ROW][C]Learning[/C][C]0.0797831[/C][C]0.0672605[/C][C]1.186[/C][C]0.236655[/C][C]0.118327[/C][/ROW]
[ROW][C]Software[/C][C]-0.0411911[/C][C]0.0695991[/C][C]-0.5918[/C][C]0.554486[/C][C]0.277243[/C][/ROW]
[ROW][C]Depression[/C][C]-0.363249[/C][C]0.0392079[/C][C]-9.265[/C][C]8.46015e-18[/C][C]4.23008e-18[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0253404[/C][C]0.0127429[/C][C]1.989[/C][C]0.0478165[/C][C]0.0239083[/C][/ROW]
[ROW][C]Month[/C][C]0.361015[/C][C]0.433885[/C][C]0.8321[/C][C]0.406158[/C][C]0.203079[/C][/ROW]
[ROW][C]t[/C][C]-0.00790136[/C][C]0.00461614[/C][C]-1.712[/C][C]0.088171[/C][C]0.0440855[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226174&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226174&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)12.80694.108033.1180.002032810.00101641
Connected0.00460160.03724750.12350.9017760.450888
Separate0.01157010.03794250.30490.7606630.380331
Learning0.07978310.06726051.1860.2366550.118327
Software-0.04119110.0695991-0.59180.5544860.277243
Depression-0.3632490.0392079-9.2658.46015e-184.23008e-18
Sport10.02534040.01274291.9890.04781650.0239083
Month0.3610150.4338850.83210.4061580.203079
t-0.007901360.00461614-1.7120.0881710.0440855






Multiple Linear Regression - Regression Statistics
Multiple R0.615406
R-squared0.378725
Adjusted R-squared0.359234
F-TEST (value)19.4308
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.00011
Sum Squared Residuals1020.11

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.615406 \tabularnewline
R-squared & 0.378725 \tabularnewline
Adjusted R-squared & 0.359234 \tabularnewline
F-TEST (value) & 19.4308 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 255 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.00011 \tabularnewline
Sum Squared Residuals & 1020.11 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226174&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.615406[/C][/ROW]
[ROW][C]R-squared[/C][C]0.378725[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.359234[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]19.4308[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]255[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.00011[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1020.11[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226174&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226174&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 R0.615406
R-squared0.378725
Adjusted R-squared0.359234
F-TEST (value)19.4308
F-TEST (DF numerator)8
F-TEST (DF denominator)255
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.00011
Sum Squared Residuals1020.11






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.2034-0.203375
21815.52092.47915
31114.0603-3.0603
41214.8373-2.83728
51611.48024.51983
61814.7483.25198
71410.9123.08802
81415.2173-1.21734
91515.4209-0.420876
101514.61660.383425
111715.73661.26335
121915.76493.23514
131013.5644-3.56441
141613.67082.32916
151815.8282.172
161413.54540.45464
171414.0575-0.057463
181715.86391.13611
191415.4973-1.4973
201613.91992.08012
211815.46422.53583
221113.8034-2.8034
231414.4832-0.48319
241213.6449-1.64487
251715.45371.54627
26915.9883-6.9883
271615.2080.791969
281413.33450.665462
291514.03380.966166
301114.0379-3.03786
311615.77280.227168
321312.84520.154836
331715.19591.80407
341515.287-0.286999
351414.0586-0.0586386
361615.70330.296707
37911.0143-2.01435
381514.36610.633924
391715.3981.60203
401315.2634-2.26344
411515.7431-0.743121
421613.70012.29987
431615.70150.298461
441213.1885-1.18848
451514.65710.34293
461113.652-2.65199
471515.2701-0.270102
481514.87040.129587
491713.5243.47596
501314.7335-1.7335
511615.13180.868175
521413.45690.543137
531111.6874-0.687364
541213.4521-1.45211
551214.2517-2.25173
561513.71731.28268
571614.11371.88634
581515.3354-0.335361
591215.1376-3.13761
601213.3261-1.32607
61810.7832-2.78315
621314.5088-1.50883
631114.4877-3.48773
641412.9941.006
651513.48591.51407
661015.337-5.337
671112.8149-1.81489
681214.804-2.80402
691513.85141.14859
701513.89831.10169
711413.89130.108719
721613.01392.98606
731514.63770.362334
741515.457-0.456974
751315.2084-2.20836
761212.4542-0.454175
771714.19962.80039
781312.71250.287476
791514.05220.947808
801315.1489-2.14894
811515.1338-0.133777
821515.6704-0.670424
831614.50661.4934
841514.50310.496893
851414.3495-0.349524
861514.28810.711865
871414.4466-0.446575
881312.92730.0727257
89710.7323-3.73227
901713.97943.02064
911312.8920.108009
921514.33670.663264
931413.4850.514961
941314.1843-1.18435
951615.15850.84151
961212.9113-0.911251
971415.0569-1.05694
981715.04541.9546
991515.197-0.196995
1001715.21151.7885
1011213.0555-1.05549
1021614.97761.02242
1031114.4948-3.49477
1041513.21171.7883
105911.506-2.50599
1061614.95141.04856
1071512.98092.0191
1081012.8774-2.87736
109109.356330.643674
1101513.931.07001
1111113.1907-2.19074
1121315.2911-2.29112
1131412.15151.84849
1141814.19233.80772
1151615.49630.503737
1161412.97951.0205
1171413.87480.125175
1181415.1048-1.10479
1191413.68230.31772
1201212.5525-0.552529
1211413.49740.502572
1221514.88160.118407
1231515.7748-0.774811
1241514.4770.523044
1251314.6186-1.61863
1261716.13060.869364
1271715.21321.78684
1281914.85694.14312
1291513.54721.45282
1301314.587-1.58696
131910.6332-1.63324
1321515.2519-0.251922
1331512.54022.45983
1341514.1070.892966
1351613.6042.39598
136119.405941.59406
1371413.15050.849454
1381111.8917-0.891735
1391514.12710.872913
1401313.7548-0.754828
1411514.52650.473542
1421613.73032.2697
1431414.3889-0.38886
1441514.10360.896362
1451614.54191.45808
1461614.19061.80944
1471113.1788-2.17878
1481214.4406-2.44057
149911.3856-2.38559
1501614.16241.83765
1511312.33320.666804
1521615.24790.752129
1531214.3153-2.31531
154911.0416-2.04163
1551311.60921.39079
1561312.37840.621597
1571413.20490.795112
1581914.61984.38016
1591315.3702-2.37018
1601211.95770.0423036
1611312.3620.637966
162109.502840.497162
1631413.52850.471459
1641611.63154.36855
1651012.1529-2.15286
166119.405911.59409
1671414.2598-0.259795
1681213.0325-1.03253
169912.8476-3.84764
170912.0807-3.08074
1711110.8360.163982
1721614.26051.73949
173914.1678-5.16777
1741311.57551.42454
1751613.45032.54971
1761315.3906-2.39056
177912.4706-3.4706
1781211.65340.346573
1791614.63541.36461
1801113.3351-2.33513
1811414.085-0.0849515
1821314.9072-1.90718
1831514.56740.432637
1841414.9665-0.966486
1851614.1451.85499
1861311.67851.32147
1871413.55240.447563
1881514.34540.654598
1891312.60970.390341
1901110.42970.570255
1911112.696-1.69602
1921414.9489-0.948917
1931512.91572.08429
1941112.4169-1.41687
1951513.11911.88094
1961213.9566-1.95659
1971411.74262.25744
1981413.33160.668372
199811.1549-3.15495
2001313.6989-0.698859
201912.0305-3.0305
2021513.73411.26594
2031714.10092.89913
2041312.43890.561144
2051514.39950.600518
2061513.61991.38007
2071414.35-0.349978
2081612.36333.63666
2091312.82820.171833
2101614.21151.78854
211911.5588-2.55877
2121614.39671.60334
2131112.1033-1.10331
2141013.7423-3.74231
2151111.9501-0.950062
2161513.11941.88062
2171714.68172.31835
2181414.0777-0.0777028
21989.88018-1.88018
2201513.35151.64849
2211113.6845-2.68447
2221613.43112.56887
2231011.8899-1.88986
2241514.6630.33703
22599.57437-0.574374
2261614.29131.70872
2271913.5755.42498
2281213.5055-1.50546
22989.33152-1.33152
2301113.1604-2.1604
2311413.68660.313406
232911.8082-2.80818
2331514.70750.292459
2341312.00830.991708
2351614.62851.37155
2361112.5917-1.59169
2371211.24540.754603
2381312.46320.536767
2391013.9927-3.99274
2401113.3741-2.37409
2411214.5936-2.59363
242810.3775-2.37752
2431211.64280.35717
2441212.0435-0.0434889
2451513.14841.8516
2461110.48410.515925
2471312.39930.60074
248148.541765.45824
249109.922950.0770507
2501211.24850.751534
2511512.60842.39155
2521311.61981.3802
2531313.8517-0.851713
2541313.3013-0.301268
2551211.40870.591339
2561212.2065-0.206488
257910.3911-1.39107
258911.0724-2.07243
2591512.12842.87162
2601014.6247-4.62466
2611413.19360.80643
2621513.05151.94852
26379.46947-2.46947
2641413.40750.592469

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 14.2034 & -0.203375 \tabularnewline
2 & 18 & 15.5209 & 2.47915 \tabularnewline
3 & 11 & 14.0603 & -3.0603 \tabularnewline
4 & 12 & 14.8373 & -2.83728 \tabularnewline
5 & 16 & 11.4802 & 4.51983 \tabularnewline
6 & 18 & 14.748 & 3.25198 \tabularnewline
7 & 14 & 10.912 & 3.08802 \tabularnewline
8 & 14 & 15.2173 & -1.21734 \tabularnewline
9 & 15 & 15.4209 & -0.420876 \tabularnewline
10 & 15 & 14.6166 & 0.383425 \tabularnewline
11 & 17 & 15.7366 & 1.26335 \tabularnewline
12 & 19 & 15.7649 & 3.23514 \tabularnewline
13 & 10 & 13.5644 & -3.56441 \tabularnewline
14 & 16 & 13.6708 & 2.32916 \tabularnewline
15 & 18 & 15.828 & 2.172 \tabularnewline
16 & 14 & 13.5454 & 0.45464 \tabularnewline
17 & 14 & 14.0575 & -0.057463 \tabularnewline
18 & 17 & 15.8639 & 1.13611 \tabularnewline
19 & 14 & 15.4973 & -1.4973 \tabularnewline
20 & 16 & 13.9199 & 2.08012 \tabularnewline
21 & 18 & 15.4642 & 2.53583 \tabularnewline
22 & 11 & 13.8034 & -2.8034 \tabularnewline
23 & 14 & 14.4832 & -0.48319 \tabularnewline
24 & 12 & 13.6449 & -1.64487 \tabularnewline
25 & 17 & 15.4537 & 1.54627 \tabularnewline
26 & 9 & 15.9883 & -6.9883 \tabularnewline
27 & 16 & 15.208 & 0.791969 \tabularnewline
28 & 14 & 13.3345 & 0.665462 \tabularnewline
29 & 15 & 14.0338 & 0.966166 \tabularnewline
30 & 11 & 14.0379 & -3.03786 \tabularnewline
31 & 16 & 15.7728 & 0.227168 \tabularnewline
32 & 13 & 12.8452 & 0.154836 \tabularnewline
33 & 17 & 15.1959 & 1.80407 \tabularnewline
34 & 15 & 15.287 & -0.286999 \tabularnewline
35 & 14 & 14.0586 & -0.0586386 \tabularnewline
36 & 16 & 15.7033 & 0.296707 \tabularnewline
37 & 9 & 11.0143 & -2.01435 \tabularnewline
38 & 15 & 14.3661 & 0.633924 \tabularnewline
39 & 17 & 15.398 & 1.60203 \tabularnewline
40 & 13 & 15.2634 & -2.26344 \tabularnewline
41 & 15 & 15.7431 & -0.743121 \tabularnewline
42 & 16 & 13.7001 & 2.29987 \tabularnewline
43 & 16 & 15.7015 & 0.298461 \tabularnewline
44 & 12 & 13.1885 & -1.18848 \tabularnewline
45 & 15 & 14.6571 & 0.34293 \tabularnewline
46 & 11 & 13.652 & -2.65199 \tabularnewline
47 & 15 & 15.2701 & -0.270102 \tabularnewline
48 & 15 & 14.8704 & 0.129587 \tabularnewline
49 & 17 & 13.524 & 3.47596 \tabularnewline
50 & 13 & 14.7335 & -1.7335 \tabularnewline
51 & 16 & 15.1318 & 0.868175 \tabularnewline
52 & 14 & 13.4569 & 0.543137 \tabularnewline
53 & 11 & 11.6874 & -0.687364 \tabularnewline
54 & 12 & 13.4521 & -1.45211 \tabularnewline
55 & 12 & 14.2517 & -2.25173 \tabularnewline
56 & 15 & 13.7173 & 1.28268 \tabularnewline
57 & 16 & 14.1137 & 1.88634 \tabularnewline
58 & 15 & 15.3354 & -0.335361 \tabularnewline
59 & 12 & 15.1376 & -3.13761 \tabularnewline
60 & 12 & 13.3261 & -1.32607 \tabularnewline
61 & 8 & 10.7832 & -2.78315 \tabularnewline
62 & 13 & 14.5088 & -1.50883 \tabularnewline
63 & 11 & 14.4877 & -3.48773 \tabularnewline
64 & 14 & 12.994 & 1.006 \tabularnewline
65 & 15 & 13.4859 & 1.51407 \tabularnewline
66 & 10 & 15.337 & -5.337 \tabularnewline
67 & 11 & 12.8149 & -1.81489 \tabularnewline
68 & 12 & 14.804 & -2.80402 \tabularnewline
69 & 15 & 13.8514 & 1.14859 \tabularnewline
70 & 15 & 13.8983 & 1.10169 \tabularnewline
71 & 14 & 13.8913 & 0.108719 \tabularnewline
72 & 16 & 13.0139 & 2.98606 \tabularnewline
73 & 15 & 14.6377 & 0.362334 \tabularnewline
74 & 15 & 15.457 & -0.456974 \tabularnewline
75 & 13 & 15.2084 & -2.20836 \tabularnewline
76 & 12 & 12.4542 & -0.454175 \tabularnewline
77 & 17 & 14.1996 & 2.80039 \tabularnewline
78 & 13 & 12.7125 & 0.287476 \tabularnewline
79 & 15 & 14.0522 & 0.947808 \tabularnewline
80 & 13 & 15.1489 & -2.14894 \tabularnewline
81 & 15 & 15.1338 & -0.133777 \tabularnewline
82 & 15 & 15.6704 & -0.670424 \tabularnewline
83 & 16 & 14.5066 & 1.4934 \tabularnewline
84 & 15 & 14.5031 & 0.496893 \tabularnewline
85 & 14 & 14.3495 & -0.349524 \tabularnewline
86 & 15 & 14.2881 & 0.711865 \tabularnewline
87 & 14 & 14.4466 & -0.446575 \tabularnewline
88 & 13 & 12.9273 & 0.0727257 \tabularnewline
89 & 7 & 10.7323 & -3.73227 \tabularnewline
90 & 17 & 13.9794 & 3.02064 \tabularnewline
91 & 13 & 12.892 & 0.108009 \tabularnewline
92 & 15 & 14.3367 & 0.663264 \tabularnewline
93 & 14 & 13.485 & 0.514961 \tabularnewline
94 & 13 & 14.1843 & -1.18435 \tabularnewline
95 & 16 & 15.1585 & 0.84151 \tabularnewline
96 & 12 & 12.9113 & -0.911251 \tabularnewline
97 & 14 & 15.0569 & -1.05694 \tabularnewline
98 & 17 & 15.0454 & 1.9546 \tabularnewline
99 & 15 & 15.197 & -0.196995 \tabularnewline
100 & 17 & 15.2115 & 1.7885 \tabularnewline
101 & 12 & 13.0555 & -1.05549 \tabularnewline
102 & 16 & 14.9776 & 1.02242 \tabularnewline
103 & 11 & 14.4948 & -3.49477 \tabularnewline
104 & 15 & 13.2117 & 1.7883 \tabularnewline
105 & 9 & 11.506 & -2.50599 \tabularnewline
106 & 16 & 14.9514 & 1.04856 \tabularnewline
107 & 15 & 12.9809 & 2.0191 \tabularnewline
108 & 10 & 12.8774 & -2.87736 \tabularnewline
109 & 10 & 9.35633 & 0.643674 \tabularnewline
110 & 15 & 13.93 & 1.07001 \tabularnewline
111 & 11 & 13.1907 & -2.19074 \tabularnewline
112 & 13 & 15.2911 & -2.29112 \tabularnewline
113 & 14 & 12.1515 & 1.84849 \tabularnewline
114 & 18 & 14.1923 & 3.80772 \tabularnewline
115 & 16 & 15.4963 & 0.503737 \tabularnewline
116 & 14 & 12.9795 & 1.0205 \tabularnewline
117 & 14 & 13.8748 & 0.125175 \tabularnewline
118 & 14 & 15.1048 & -1.10479 \tabularnewline
119 & 14 & 13.6823 & 0.31772 \tabularnewline
120 & 12 & 12.5525 & -0.552529 \tabularnewline
121 & 14 & 13.4974 & 0.502572 \tabularnewline
122 & 15 & 14.8816 & 0.118407 \tabularnewline
123 & 15 & 15.7748 & -0.774811 \tabularnewline
124 & 15 & 14.477 & 0.523044 \tabularnewline
125 & 13 & 14.6186 & -1.61863 \tabularnewline
126 & 17 & 16.1306 & 0.869364 \tabularnewline
127 & 17 & 15.2132 & 1.78684 \tabularnewline
128 & 19 & 14.8569 & 4.14312 \tabularnewline
129 & 15 & 13.5472 & 1.45282 \tabularnewline
130 & 13 & 14.587 & -1.58696 \tabularnewline
131 & 9 & 10.6332 & -1.63324 \tabularnewline
132 & 15 & 15.2519 & -0.251922 \tabularnewline
133 & 15 & 12.5402 & 2.45983 \tabularnewline
134 & 15 & 14.107 & 0.892966 \tabularnewline
135 & 16 & 13.604 & 2.39598 \tabularnewline
136 & 11 & 9.40594 & 1.59406 \tabularnewline
137 & 14 & 13.1505 & 0.849454 \tabularnewline
138 & 11 & 11.8917 & -0.891735 \tabularnewline
139 & 15 & 14.1271 & 0.872913 \tabularnewline
140 & 13 & 13.7548 & -0.754828 \tabularnewline
141 & 15 & 14.5265 & 0.473542 \tabularnewline
142 & 16 & 13.7303 & 2.2697 \tabularnewline
143 & 14 & 14.3889 & -0.38886 \tabularnewline
144 & 15 & 14.1036 & 0.896362 \tabularnewline
145 & 16 & 14.5419 & 1.45808 \tabularnewline
146 & 16 & 14.1906 & 1.80944 \tabularnewline
147 & 11 & 13.1788 & -2.17878 \tabularnewline
148 & 12 & 14.4406 & -2.44057 \tabularnewline
149 & 9 & 11.3856 & -2.38559 \tabularnewline
150 & 16 & 14.1624 & 1.83765 \tabularnewline
151 & 13 & 12.3332 & 0.666804 \tabularnewline
152 & 16 & 15.2479 & 0.752129 \tabularnewline
153 & 12 & 14.3153 & -2.31531 \tabularnewline
154 & 9 & 11.0416 & -2.04163 \tabularnewline
155 & 13 & 11.6092 & 1.39079 \tabularnewline
156 & 13 & 12.3784 & 0.621597 \tabularnewline
157 & 14 & 13.2049 & 0.795112 \tabularnewline
158 & 19 & 14.6198 & 4.38016 \tabularnewline
159 & 13 & 15.3702 & -2.37018 \tabularnewline
160 & 12 & 11.9577 & 0.0423036 \tabularnewline
161 & 13 & 12.362 & 0.637966 \tabularnewline
162 & 10 & 9.50284 & 0.497162 \tabularnewline
163 & 14 & 13.5285 & 0.471459 \tabularnewline
164 & 16 & 11.6315 & 4.36855 \tabularnewline
165 & 10 & 12.1529 & -2.15286 \tabularnewline
166 & 11 & 9.40591 & 1.59409 \tabularnewline
167 & 14 & 14.2598 & -0.259795 \tabularnewline
168 & 12 & 13.0325 & -1.03253 \tabularnewline
169 & 9 & 12.8476 & -3.84764 \tabularnewline
170 & 9 & 12.0807 & -3.08074 \tabularnewline
171 & 11 & 10.836 & 0.163982 \tabularnewline
172 & 16 & 14.2605 & 1.73949 \tabularnewline
173 & 9 & 14.1678 & -5.16777 \tabularnewline
174 & 13 & 11.5755 & 1.42454 \tabularnewline
175 & 16 & 13.4503 & 2.54971 \tabularnewline
176 & 13 & 15.3906 & -2.39056 \tabularnewline
177 & 9 & 12.4706 & -3.4706 \tabularnewline
178 & 12 & 11.6534 & 0.346573 \tabularnewline
179 & 16 & 14.6354 & 1.36461 \tabularnewline
180 & 11 & 13.3351 & -2.33513 \tabularnewline
181 & 14 & 14.085 & -0.0849515 \tabularnewline
182 & 13 & 14.9072 & -1.90718 \tabularnewline
183 & 15 & 14.5674 & 0.432637 \tabularnewline
184 & 14 & 14.9665 & -0.966486 \tabularnewline
185 & 16 & 14.145 & 1.85499 \tabularnewline
186 & 13 & 11.6785 & 1.32147 \tabularnewline
187 & 14 & 13.5524 & 0.447563 \tabularnewline
188 & 15 & 14.3454 & 0.654598 \tabularnewline
189 & 13 & 12.6097 & 0.390341 \tabularnewline
190 & 11 & 10.4297 & 0.570255 \tabularnewline
191 & 11 & 12.696 & -1.69602 \tabularnewline
192 & 14 & 14.9489 & -0.948917 \tabularnewline
193 & 15 & 12.9157 & 2.08429 \tabularnewline
194 & 11 & 12.4169 & -1.41687 \tabularnewline
195 & 15 & 13.1191 & 1.88094 \tabularnewline
196 & 12 & 13.9566 & -1.95659 \tabularnewline
197 & 14 & 11.7426 & 2.25744 \tabularnewline
198 & 14 & 13.3316 & 0.668372 \tabularnewline
199 & 8 & 11.1549 & -3.15495 \tabularnewline
200 & 13 & 13.6989 & -0.698859 \tabularnewline
201 & 9 & 12.0305 & -3.0305 \tabularnewline
202 & 15 & 13.7341 & 1.26594 \tabularnewline
203 & 17 & 14.1009 & 2.89913 \tabularnewline
204 & 13 & 12.4389 & 0.561144 \tabularnewline
205 & 15 & 14.3995 & 0.600518 \tabularnewline
206 & 15 & 13.6199 & 1.38007 \tabularnewline
207 & 14 & 14.35 & -0.349978 \tabularnewline
208 & 16 & 12.3633 & 3.63666 \tabularnewline
209 & 13 & 12.8282 & 0.171833 \tabularnewline
210 & 16 & 14.2115 & 1.78854 \tabularnewline
211 & 9 & 11.5588 & -2.55877 \tabularnewline
212 & 16 & 14.3967 & 1.60334 \tabularnewline
213 & 11 & 12.1033 & -1.10331 \tabularnewline
214 & 10 & 13.7423 & -3.74231 \tabularnewline
215 & 11 & 11.9501 & -0.950062 \tabularnewline
216 & 15 & 13.1194 & 1.88062 \tabularnewline
217 & 17 & 14.6817 & 2.31835 \tabularnewline
218 & 14 & 14.0777 & -0.0777028 \tabularnewline
219 & 8 & 9.88018 & -1.88018 \tabularnewline
220 & 15 & 13.3515 & 1.64849 \tabularnewline
221 & 11 & 13.6845 & -2.68447 \tabularnewline
222 & 16 & 13.4311 & 2.56887 \tabularnewline
223 & 10 & 11.8899 & -1.88986 \tabularnewline
224 & 15 & 14.663 & 0.33703 \tabularnewline
225 & 9 & 9.57437 & -0.574374 \tabularnewline
226 & 16 & 14.2913 & 1.70872 \tabularnewline
227 & 19 & 13.575 & 5.42498 \tabularnewline
228 & 12 & 13.5055 & -1.50546 \tabularnewline
229 & 8 & 9.33152 & -1.33152 \tabularnewline
230 & 11 & 13.1604 & -2.1604 \tabularnewline
231 & 14 & 13.6866 & 0.313406 \tabularnewline
232 & 9 & 11.8082 & -2.80818 \tabularnewline
233 & 15 & 14.7075 & 0.292459 \tabularnewline
234 & 13 & 12.0083 & 0.991708 \tabularnewline
235 & 16 & 14.6285 & 1.37155 \tabularnewline
236 & 11 & 12.5917 & -1.59169 \tabularnewline
237 & 12 & 11.2454 & 0.754603 \tabularnewline
238 & 13 & 12.4632 & 0.536767 \tabularnewline
239 & 10 & 13.9927 & -3.99274 \tabularnewline
240 & 11 & 13.3741 & -2.37409 \tabularnewline
241 & 12 & 14.5936 & -2.59363 \tabularnewline
242 & 8 & 10.3775 & -2.37752 \tabularnewline
243 & 12 & 11.6428 & 0.35717 \tabularnewline
244 & 12 & 12.0435 & -0.0434889 \tabularnewline
245 & 15 & 13.1484 & 1.8516 \tabularnewline
246 & 11 & 10.4841 & 0.515925 \tabularnewline
247 & 13 & 12.3993 & 0.60074 \tabularnewline
248 & 14 & 8.54176 & 5.45824 \tabularnewline
249 & 10 & 9.92295 & 0.0770507 \tabularnewline
250 & 12 & 11.2485 & 0.751534 \tabularnewline
251 & 15 & 12.6084 & 2.39155 \tabularnewline
252 & 13 & 11.6198 & 1.3802 \tabularnewline
253 & 13 & 13.8517 & -0.851713 \tabularnewline
254 & 13 & 13.3013 & -0.301268 \tabularnewline
255 & 12 & 11.4087 & 0.591339 \tabularnewline
256 & 12 & 12.2065 & -0.206488 \tabularnewline
257 & 9 & 10.3911 & -1.39107 \tabularnewline
258 & 9 & 11.0724 & -2.07243 \tabularnewline
259 & 15 & 12.1284 & 2.87162 \tabularnewline
260 & 10 & 14.6247 & -4.62466 \tabularnewline
261 & 14 & 13.1936 & 0.80643 \tabularnewline
262 & 15 & 13.0515 & 1.94852 \tabularnewline
263 & 7 & 9.46947 & -2.46947 \tabularnewline
264 & 14 & 13.4075 & 0.592469 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226174&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]14[/C][C]14.2034[/C][C]-0.203375[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.5209[/C][C]2.47915[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]14.0603[/C][C]-3.0603[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.8373[/C][C]-2.83728[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]11.4802[/C][C]4.51983[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.748[/C][C]3.25198[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.912[/C][C]3.08802[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]15.2173[/C][C]-1.21734[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.4209[/C][C]-0.420876[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.6166[/C][C]0.383425[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.7366[/C][C]1.26335[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.7649[/C][C]3.23514[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.5644[/C][C]-3.56441[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.6708[/C][C]2.32916[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.828[/C][C]2.172[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.5454[/C][C]0.45464[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]14.0575[/C][C]-0.057463[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.8639[/C][C]1.13611[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.4973[/C][C]-1.4973[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.9199[/C][C]2.08012[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.4642[/C][C]2.53583[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.8034[/C][C]-2.8034[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.4832[/C][C]-0.48319[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.6449[/C][C]-1.64487[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.4537[/C][C]1.54627[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.9883[/C][C]-6.9883[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.208[/C][C]0.791969[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.3345[/C][C]0.665462[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]14.0338[/C][C]0.966166[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]14.0379[/C][C]-3.03786[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.7728[/C][C]0.227168[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.8452[/C][C]0.154836[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]15.1959[/C][C]1.80407[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.287[/C][C]-0.286999[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14.0586[/C][C]-0.0586386[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.7033[/C][C]0.296707[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]11.0143[/C][C]-2.01435[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.3661[/C][C]0.633924[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.398[/C][C]1.60203[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.2634[/C][C]-2.26344[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.7431[/C][C]-0.743121[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.7001[/C][C]2.29987[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.7015[/C][C]0.298461[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.1885[/C][C]-1.18848[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.6571[/C][C]0.34293[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.652[/C][C]-2.65199[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.2701[/C][C]-0.270102[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.8704[/C][C]0.129587[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.524[/C][C]3.47596[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.7335[/C][C]-1.7335[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.1318[/C][C]0.868175[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.4569[/C][C]0.543137[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.6874[/C][C]-0.687364[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.4521[/C][C]-1.45211[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.2517[/C][C]-2.25173[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.7173[/C][C]1.28268[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.1137[/C][C]1.88634[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.3354[/C][C]-0.335361[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.1376[/C][C]-3.13761[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.3261[/C][C]-1.32607[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.7832[/C][C]-2.78315[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.5088[/C][C]-1.50883[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.4877[/C][C]-3.48773[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]12.994[/C][C]1.006[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.4859[/C][C]1.51407[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.337[/C][C]-5.337[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.8149[/C][C]-1.81489[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.804[/C][C]-2.80402[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.8514[/C][C]1.14859[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.8983[/C][C]1.10169[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.8913[/C][C]0.108719[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]13.0139[/C][C]2.98606[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.6377[/C][C]0.362334[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.457[/C][C]-0.456974[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]15.2084[/C][C]-2.20836[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.4542[/C][C]-0.454175[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]14.1996[/C][C]2.80039[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.7125[/C][C]0.287476[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]14.0522[/C][C]0.947808[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]15.1489[/C][C]-2.14894[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]15.1338[/C][C]-0.133777[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.6704[/C][C]-0.670424[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.5066[/C][C]1.4934[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.5031[/C][C]0.496893[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.3495[/C][C]-0.349524[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]14.2881[/C][C]0.711865[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.4466[/C][C]-0.446575[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.9273[/C][C]0.0727257[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.7323[/C][C]-3.73227[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.9794[/C][C]3.02064[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.892[/C][C]0.108009[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.3367[/C][C]0.663264[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.485[/C][C]0.514961[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.1843[/C][C]-1.18435[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]15.1585[/C][C]0.84151[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.9113[/C][C]-0.911251[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]15.0569[/C][C]-1.05694[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]15.0454[/C][C]1.9546[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]15.197[/C][C]-0.196995[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.2115[/C][C]1.7885[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]13.0555[/C][C]-1.05549[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]14.9776[/C][C]1.02242[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.4948[/C][C]-3.49477[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.2117[/C][C]1.7883[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.506[/C][C]-2.50599[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.9514[/C][C]1.04856[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9809[/C][C]2.0191[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.8774[/C][C]-2.87736[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.35633[/C][C]0.643674[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.93[/C][C]1.07001[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.1907[/C][C]-2.19074[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.2911[/C][C]-2.29112[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]12.1515[/C][C]1.84849[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.1923[/C][C]3.80772[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.4963[/C][C]0.503737[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]12.9795[/C][C]1.0205[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.8748[/C][C]0.125175[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.1048[/C][C]-1.10479[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.6823[/C][C]0.31772[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.5525[/C][C]-0.552529[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.4974[/C][C]0.502572[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.8816[/C][C]0.118407[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.7748[/C][C]-0.774811[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.477[/C][C]0.523044[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.6186[/C][C]-1.61863[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.1306[/C][C]0.869364[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.2132[/C][C]1.78684[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.8569[/C][C]4.14312[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5472[/C][C]1.45282[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.587[/C][C]-1.58696[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.6332[/C][C]-1.63324[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.2519[/C][C]-0.251922[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.5402[/C][C]2.45983[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.107[/C][C]0.892966[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.604[/C][C]2.39598[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.40594[/C][C]1.59406[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.1505[/C][C]0.849454[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]11.8917[/C][C]-0.891735[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.1271[/C][C]0.872913[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.7548[/C][C]-0.754828[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.5265[/C][C]0.473542[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.7303[/C][C]2.2697[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.3889[/C][C]-0.38886[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.1036[/C][C]0.896362[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.5419[/C][C]1.45808[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.1906[/C][C]1.80944[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.1788[/C][C]-2.17878[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.4406[/C][C]-2.44057[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.3856[/C][C]-2.38559[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.1624[/C][C]1.83765[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.3332[/C][C]0.666804[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.2479[/C][C]0.752129[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.3153[/C][C]-2.31531[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.0416[/C][C]-2.04163[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.6092[/C][C]1.39079[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.3784[/C][C]0.621597[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.2049[/C][C]0.795112[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.6198[/C][C]4.38016[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.3702[/C][C]-2.37018[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.9577[/C][C]0.0423036[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.362[/C][C]0.637966[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.50284[/C][C]0.497162[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.5285[/C][C]0.471459[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.6315[/C][C]4.36855[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]12.1529[/C][C]-2.15286[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]9.40591[/C][C]1.59409[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.2598[/C][C]-0.259795[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]13.0325[/C][C]-1.03253[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.8476[/C][C]-3.84764[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]12.0807[/C][C]-3.08074[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.836[/C][C]0.163982[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.2605[/C][C]1.73949[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]14.1678[/C][C]-5.16777[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.5755[/C][C]1.42454[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.4503[/C][C]2.54971[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.3906[/C][C]-2.39056[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.4706[/C][C]-3.4706[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.6534[/C][C]0.346573[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.6354[/C][C]1.36461[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.3351[/C][C]-2.33513[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]14.085[/C][C]-0.0849515[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.9072[/C][C]-1.90718[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.5674[/C][C]0.432637[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.9665[/C][C]-0.966486[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]14.145[/C][C]1.85499[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.6785[/C][C]1.32147[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.5524[/C][C]0.447563[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.3454[/C][C]0.654598[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.6097[/C][C]0.390341[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.4297[/C][C]0.570255[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.696[/C][C]-1.69602[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.9489[/C][C]-0.948917[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.9157[/C][C]2.08429[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.4169[/C][C]-1.41687[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.1191[/C][C]1.88094[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]13.9566[/C][C]-1.95659[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.7426[/C][C]2.25744[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.3316[/C][C]0.668372[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.1549[/C][C]-3.15495[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.6989[/C][C]-0.698859[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.0305[/C][C]-3.0305[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.7341[/C][C]1.26594[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]14.1009[/C][C]2.89913[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.4389[/C][C]0.561144[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.3995[/C][C]0.600518[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.6199[/C][C]1.38007[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.35[/C][C]-0.349978[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.3633[/C][C]3.63666[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.8282[/C][C]0.171833[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.2115[/C][C]1.78854[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.5588[/C][C]-2.55877[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.3967[/C][C]1.60334[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.1033[/C][C]-1.10331[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.7423[/C][C]-3.74231[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]11.9501[/C][C]-0.950062[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.1194[/C][C]1.88062[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.6817[/C][C]2.31835[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.0777[/C][C]-0.0777028[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.88018[/C][C]-1.88018[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.3515[/C][C]1.64849[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.6845[/C][C]-2.68447[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.4311[/C][C]2.56887[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]11.8899[/C][C]-1.88986[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.663[/C][C]0.33703[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.57437[/C][C]-0.574374[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.2913[/C][C]1.70872[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]13.575[/C][C]5.42498[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.5055[/C][C]-1.50546[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.33152[/C][C]-1.33152[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.1604[/C][C]-2.1604[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.6866[/C][C]0.313406[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]11.8082[/C][C]-2.80818[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]14.7075[/C][C]0.292459[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.0083[/C][C]0.991708[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]14.6285[/C][C]1.37155[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.5917[/C][C]-1.59169[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.2454[/C][C]0.754603[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]12.4632[/C][C]0.536767[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]13.9927[/C][C]-3.99274[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.3741[/C][C]-2.37409[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.5936[/C][C]-2.59363[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.3775[/C][C]-2.37752[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.6428[/C][C]0.35717[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.0435[/C][C]-0.0434889[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.1484[/C][C]1.8516[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.4841[/C][C]0.515925[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.3993[/C][C]0.60074[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.54176[/C][C]5.45824[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]9.92295[/C][C]0.0770507[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.2485[/C][C]0.751534[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.6084[/C][C]2.39155[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.6198[/C][C]1.3802[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]13.8517[/C][C]-0.851713[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.3013[/C][C]-0.301268[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.4087[/C][C]0.591339[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.2065[/C][C]-0.206488[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.3911[/C][C]-1.39107[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.0724[/C][C]-2.07243[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.1284[/C][C]2.87162[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.6247[/C][C]-4.62466[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.1936[/C][C]0.80643[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.0515[/C][C]1.94852[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.46947[/C][C]-2.46947[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.4075[/C][C]0.592469[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226174&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226174&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
11414.2034-0.203375
21815.52092.47915
31114.0603-3.0603
41214.8373-2.83728
51611.48024.51983
61814.7483.25198
71410.9123.08802
81415.2173-1.21734
91515.4209-0.420876
101514.61660.383425
111715.73661.26335
121915.76493.23514
131013.5644-3.56441
141613.67082.32916
151815.8282.172
161413.54540.45464
171414.0575-0.057463
181715.86391.13611
191415.4973-1.4973
201613.91992.08012
211815.46422.53583
221113.8034-2.8034
231414.4832-0.48319
241213.6449-1.64487
251715.45371.54627
26915.9883-6.9883
271615.2080.791969
281413.33450.665462
291514.03380.966166
301114.0379-3.03786
311615.77280.227168
321312.84520.154836
331715.19591.80407
341515.287-0.286999
351414.0586-0.0586386
361615.70330.296707
37911.0143-2.01435
381514.36610.633924
391715.3981.60203
401315.2634-2.26344
411515.7431-0.743121
421613.70012.29987
431615.70150.298461
441213.1885-1.18848
451514.65710.34293
461113.652-2.65199
471515.2701-0.270102
481514.87040.129587
491713.5243.47596
501314.7335-1.7335
511615.13180.868175
521413.45690.543137
531111.6874-0.687364
541213.4521-1.45211
551214.2517-2.25173
561513.71731.28268
571614.11371.88634
581515.3354-0.335361
591215.1376-3.13761
601213.3261-1.32607
61810.7832-2.78315
621314.5088-1.50883
631114.4877-3.48773
641412.9941.006
651513.48591.51407
661015.337-5.337
671112.8149-1.81489
681214.804-2.80402
691513.85141.14859
701513.89831.10169
711413.89130.108719
721613.01392.98606
731514.63770.362334
741515.457-0.456974
751315.2084-2.20836
761212.4542-0.454175
771714.19962.80039
781312.71250.287476
791514.05220.947808
801315.1489-2.14894
811515.1338-0.133777
821515.6704-0.670424
831614.50661.4934
841514.50310.496893
851414.3495-0.349524
861514.28810.711865
871414.4466-0.446575
881312.92730.0727257
89710.7323-3.73227
901713.97943.02064
911312.8920.108009
921514.33670.663264
931413.4850.514961
941314.1843-1.18435
951615.15850.84151
961212.9113-0.911251
971415.0569-1.05694
981715.04541.9546
991515.197-0.196995
1001715.21151.7885
1011213.0555-1.05549
1021614.97761.02242
1031114.4948-3.49477
1041513.21171.7883
105911.506-2.50599
1061614.95141.04856
1071512.98092.0191
1081012.8774-2.87736
109109.356330.643674
1101513.931.07001
1111113.1907-2.19074
1121315.2911-2.29112
1131412.15151.84849
1141814.19233.80772
1151615.49630.503737
1161412.97951.0205
1171413.87480.125175
1181415.1048-1.10479
1191413.68230.31772
1201212.5525-0.552529
1211413.49740.502572
1221514.88160.118407
1231515.7748-0.774811
1241514.4770.523044
1251314.6186-1.61863
1261716.13060.869364
1271715.21321.78684
1281914.85694.14312
1291513.54721.45282
1301314.587-1.58696
131910.6332-1.63324
1321515.2519-0.251922
1331512.54022.45983
1341514.1070.892966
1351613.6042.39598
136119.405941.59406
1371413.15050.849454
1381111.8917-0.891735
1391514.12710.872913
1401313.7548-0.754828
1411514.52650.473542
1421613.73032.2697
1431414.3889-0.38886
1441514.10360.896362
1451614.54191.45808
1461614.19061.80944
1471113.1788-2.17878
1481214.4406-2.44057
149911.3856-2.38559
1501614.16241.83765
1511312.33320.666804
1521615.24790.752129
1531214.3153-2.31531
154911.0416-2.04163
1551311.60921.39079
1561312.37840.621597
1571413.20490.795112
1581914.61984.38016
1591315.3702-2.37018
1601211.95770.0423036
1611312.3620.637966
162109.502840.497162
1631413.52850.471459
1641611.63154.36855
1651012.1529-2.15286
166119.405911.59409
1671414.2598-0.259795
1681213.0325-1.03253
169912.8476-3.84764
170912.0807-3.08074
1711110.8360.163982
1721614.26051.73949
173914.1678-5.16777
1741311.57551.42454
1751613.45032.54971
1761315.3906-2.39056
177912.4706-3.4706
1781211.65340.346573
1791614.63541.36461
1801113.3351-2.33513
1811414.085-0.0849515
1821314.9072-1.90718
1831514.56740.432637
1841414.9665-0.966486
1851614.1451.85499
1861311.67851.32147
1871413.55240.447563
1881514.34540.654598
1891312.60970.390341
1901110.42970.570255
1911112.696-1.69602
1921414.9489-0.948917
1931512.91572.08429
1941112.4169-1.41687
1951513.11911.88094
1961213.9566-1.95659
1971411.74262.25744
1981413.33160.668372
199811.1549-3.15495
2001313.6989-0.698859
201912.0305-3.0305
2021513.73411.26594
2031714.10092.89913
2041312.43890.561144
2051514.39950.600518
2061513.61991.38007
2071414.35-0.349978
2081612.36333.63666
2091312.82820.171833
2101614.21151.78854
211911.5588-2.55877
2121614.39671.60334
2131112.1033-1.10331
2141013.7423-3.74231
2151111.9501-0.950062
2161513.11941.88062
2171714.68172.31835
2181414.0777-0.0777028
21989.88018-1.88018
2201513.35151.64849
2211113.6845-2.68447
2221613.43112.56887
2231011.8899-1.88986
2241514.6630.33703
22599.57437-0.574374
2261614.29131.70872
2271913.5755.42498
2281213.5055-1.50546
22989.33152-1.33152
2301113.1604-2.1604
2311413.68660.313406
232911.8082-2.80818
2331514.70750.292459
2341312.00830.991708
2351614.62851.37155
2361112.5917-1.59169
2371211.24540.754603
2381312.46320.536767
2391013.9927-3.99274
2401113.3741-2.37409
2411214.5936-2.59363
242810.3775-2.37752
2431211.64280.35717
2441212.0435-0.0434889
2451513.14841.8516
2461110.48410.515925
2471312.39930.60074
248148.541765.45824
249109.922950.0770507
2501211.24850.751534
2511512.60842.39155
2521311.61981.3802
2531313.8517-0.851713
2541313.3013-0.301268
2551211.40870.591339
2561212.2065-0.206488
257910.3911-1.39107
258911.0724-2.07243
2591512.12842.87162
2601014.6247-4.62466
2611413.19360.80643
2621513.05151.94852
26379.46947-2.46947
2641413.40750.592469






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.8832470.2335070.116753
130.9915190.01696120.00848058
140.9899340.0201310.0100655
150.9896620.02067690.0103384
160.9820890.0358220.017911
170.9787410.04251710.0212585
180.9669890.06602240.0330112
190.955130.08973960.0448698
200.9428480.1143040.0571522
210.940060.1198790.0599397
220.9758110.04837720.0241886
230.9648280.07034420.0351721
240.955490.0890190.0445095
250.9392950.1214110.0607054
260.9990320.001935610.000967807
270.998640.002720810.0013604
280.9978430.004313520.00215676
290.9967850.006430580.00321529
300.9974260.005148320.00257416
310.9962930.007414080.00370704
320.9944150.01116950.00558474
330.9943080.01138460.00569232
340.9916450.01670920.00835459
350.9880070.0239860.011993
360.9833440.03331290.0166564
370.9849990.03000210.0150011
380.980520.03895930.0194796
390.9801530.03969310.0198465
400.9772410.04551740.0227587
410.9695250.06094990.0304749
420.9718590.05628210.028141
430.9651090.06978290.0348914
440.9557950.08841070.0442053
450.9435640.1128710.0564356
460.9451210.1097580.0548789
470.9331110.1337790.0668893
480.9179210.1641580.082079
490.9487540.1024910.0512456
500.9421120.1157770.0578883
510.9317770.1364470.0682234
520.9168320.1663360.0831682
530.8999430.2001150.100057
540.88570.22860.1143
550.8747820.2504360.125218
560.8616710.2766590.138329
570.8574090.2851830.142591
580.8311780.3376430.168822
590.8518230.2963540.148177
600.8355540.3288910.164446
610.8449610.3100780.155039
620.828110.343780.17189
630.8636450.272710.136355
640.8606030.2787940.139397
650.8620420.2759150.137958
660.880150.2396990.11985
670.8810680.2378640.118932
680.8733550.253290.126645
690.9124220.1751560.0875779
700.9198960.1602080.0801042
710.9093960.1812090.0906044
720.9375510.1248990.0624493
730.9265540.1468910.0734457
740.9118320.1763360.0881681
750.9041750.191650.0958251
760.8868580.2262840.113142
770.9104330.1791340.0895672
780.8952060.2095880.104794
790.8851640.2296720.114836
800.8783710.2432570.121629
810.8580580.2838850.141942
820.8363680.3272650.163632
830.8325910.3348180.167409
840.811290.3774210.18871
850.7851790.4296430.214821
860.7594650.481070.240535
870.729450.5410990.27055
880.6979740.6040520.302026
890.7705480.4589040.229452
900.8056860.3886280.194314
910.7819640.4360720.218036
920.7558080.4883840.244192
930.7338050.5323890.266195
940.7095430.5809150.290457
950.6851160.6297690.314884
960.6563070.6873860.343693
970.6287410.7425180.371259
980.6355250.7289490.364475
990.6000370.7999260.399963
1000.5969150.8061690.403085
1010.5694030.8611950.430597
1020.5446880.9106230.455312
1030.5995310.8009380.400469
1040.5883980.8232040.411602
1050.6035250.792950.396475
1060.5810070.8379870.418993
1070.5765480.8469030.423452
1080.6103140.7793730.389686
1090.5763570.8472860.423643
1100.5521360.8957270.447864
1110.5536760.8926490.446324
1120.5721620.8556770.427838
1130.5793930.8412150.420607
1140.6709610.6580780.329039
1150.6444290.7111420.355571
1160.6183860.7632280.381614
1170.5837380.8325230.416262
1180.5582350.8835290.441765
1190.5228970.9542070.477103
1200.4890950.978190.510905
1210.4662840.9325680.533716
1220.4309880.8619760.569012
1230.4012570.8025130.598743
1240.3730570.7461130.626943
1250.3613750.7227490.638625
1260.3357020.6714040.664298
1270.3236450.6472890.676355
1280.4315860.8631720.568414
1290.4132950.826590.586705
1300.4006620.8013240.599338
1310.3879760.7759510.612024
1320.3555360.7110720.644464
1330.3781790.7563570.621821
1340.3493770.6987550.650623
1350.363560.7271190.63644
1360.3553850.710770.644615
1370.3269570.6539150.673043
1380.3022960.6045920.697704
1390.2756840.5513680.724316
1400.2515640.5031280.748436
1410.2251150.4502290.774885
1420.2302060.4604120.769794
1430.2046420.4092850.795358
1440.1857120.3714230.814288
1450.1716580.3433160.828342
1460.1659560.3319130.834044
1470.1715650.343130.828435
1480.186630.373260.81337
1490.2036760.4073520.796324
1500.1991680.3983350.800832
1510.1765480.3530960.823452
1520.1566530.3133070.843347
1530.1653670.3307330.834633
1540.1822450.364490.817755
1550.1638660.3277320.836134
1560.1485590.2971170.851441
1570.1291920.2583840.870808
1580.2049120.4098240.795088
1590.2239540.4479070.776046
1600.1982690.3965390.801731
1610.1738610.3477220.826139
1620.1516440.3032880.848356
1630.1314570.2629130.868543
1640.2166640.4333280.783336
1650.2189260.4378510.781074
1660.2117340.4234680.788266
1670.1869490.3738980.813051
1680.1694380.3388760.830562
1690.2266780.4533570.773322
1700.2576830.5153650.742317
1710.229550.4591010.77045
1720.2235450.447090.776455
1730.3933650.7867290.606635
1740.3729540.7459080.627046
1750.3901850.780370.609815
1760.4040880.8081760.595912
1770.4698920.9397850.530108
1780.432730.8654590.56727
1790.4091720.8183440.590828
1800.4178960.8357920.582104
1810.3825410.7650820.617459
1820.3872980.7745950.612702
1830.3514190.7028380.648581
1840.3297780.6595560.670222
1850.3297530.6595050.670247
1860.3148620.6297240.685138
1870.281030.5620590.71897
1880.2504120.5008240.749588
1890.2202920.4405840.779708
1900.1963520.3927040.803648
1910.2084320.4168640.791568
1920.1922080.3844160.807792
1930.1973350.394670.802665
1940.1886160.3772330.811384
1950.1848870.3697740.815113
1960.1967530.3935050.803247
1970.2332280.4664560.766772
1980.2150410.4300820.784959
1990.2490660.4981310.750934
2000.2185210.4370420.781479
2010.2568430.5136860.743157
2020.2323690.4647390.767631
2030.2674450.5348890.732555
2040.2365690.4731380.763431
2050.2055270.4110540.794473
2060.1864960.3729920.813504
2070.1583030.3166050.841697
2080.1821790.3643590.817821
2090.1542760.3085510.845724
2100.1628890.3257770.837111
2110.1802150.3604310.819785
2120.1713850.3427710.828615
2130.1474350.294870.852565
2140.1833120.3666230.816688
2150.1615550.3231110.838445
2160.1511910.3023820.848809
2170.178820.357640.82118
2180.1528780.3057570.847122
2190.140050.28010.85995
2200.1555580.3111160.844442
2210.1586940.3173870.841306
2220.1564750.312950.843525
2230.1407430.2814860.859257
2240.1153970.2307940.884603
2250.1126560.2253120.887344
2260.1394080.2788160.860592
2270.3503910.7007820.649609
2280.3096110.6192220.690389
2290.2718490.5436980.728151
2300.2465680.4931360.753432
2310.2126330.4252660.787367
2320.2375880.4751750.762412
2330.1979180.3958360.802082
2340.163510.327020.83649
2350.1689440.3378880.831056
2360.1431840.2863690.856816
2370.1215490.2430980.878451
2380.09143350.1828670.908567
2390.1811360.3622720.818864
2400.1878890.3757780.812111
2410.1887720.3775440.811228
2420.805860.3882810.19414
2430.7442860.5114270.255714
2440.6793990.6412030.320601
2450.6167770.7664450.383223
2460.5389950.9220090.461005
2470.5478290.9043410.452171
2480.5453370.9093270.454663
2490.4304050.8608110.569595
2500.3403410.6806820.659659
2510.2759970.5519950.724003
2520.7956330.4087330.204367

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.883247 & 0.233507 & 0.116753 \tabularnewline
13 & 0.991519 & 0.0169612 & 0.00848058 \tabularnewline
14 & 0.989934 & 0.020131 & 0.0100655 \tabularnewline
15 & 0.989662 & 0.0206769 & 0.0103384 \tabularnewline
16 & 0.982089 & 0.035822 & 0.017911 \tabularnewline
17 & 0.978741 & 0.0425171 & 0.0212585 \tabularnewline
18 & 0.966989 & 0.0660224 & 0.0330112 \tabularnewline
19 & 0.95513 & 0.0897396 & 0.0448698 \tabularnewline
20 & 0.942848 & 0.114304 & 0.0571522 \tabularnewline
21 & 0.94006 & 0.119879 & 0.0599397 \tabularnewline
22 & 0.975811 & 0.0483772 & 0.0241886 \tabularnewline
23 & 0.964828 & 0.0703442 & 0.0351721 \tabularnewline
24 & 0.95549 & 0.089019 & 0.0445095 \tabularnewline
25 & 0.939295 & 0.121411 & 0.0607054 \tabularnewline
26 & 0.999032 & 0.00193561 & 0.000967807 \tabularnewline
27 & 0.99864 & 0.00272081 & 0.0013604 \tabularnewline
28 & 0.997843 & 0.00431352 & 0.00215676 \tabularnewline
29 & 0.996785 & 0.00643058 & 0.00321529 \tabularnewline
30 & 0.997426 & 0.00514832 & 0.00257416 \tabularnewline
31 & 0.996293 & 0.00741408 & 0.00370704 \tabularnewline
32 & 0.994415 & 0.0111695 & 0.00558474 \tabularnewline
33 & 0.994308 & 0.0113846 & 0.00569232 \tabularnewline
34 & 0.991645 & 0.0167092 & 0.00835459 \tabularnewline
35 & 0.988007 & 0.023986 & 0.011993 \tabularnewline
36 & 0.983344 & 0.0333129 & 0.0166564 \tabularnewline
37 & 0.984999 & 0.0300021 & 0.0150011 \tabularnewline
38 & 0.98052 & 0.0389593 & 0.0194796 \tabularnewline
39 & 0.980153 & 0.0396931 & 0.0198465 \tabularnewline
40 & 0.977241 & 0.0455174 & 0.0227587 \tabularnewline
41 & 0.969525 & 0.0609499 & 0.0304749 \tabularnewline
42 & 0.971859 & 0.0562821 & 0.028141 \tabularnewline
43 & 0.965109 & 0.0697829 & 0.0348914 \tabularnewline
44 & 0.955795 & 0.0884107 & 0.0442053 \tabularnewline
45 & 0.943564 & 0.112871 & 0.0564356 \tabularnewline
46 & 0.945121 & 0.109758 & 0.0548789 \tabularnewline
47 & 0.933111 & 0.133779 & 0.0668893 \tabularnewline
48 & 0.917921 & 0.164158 & 0.082079 \tabularnewline
49 & 0.948754 & 0.102491 & 0.0512456 \tabularnewline
50 & 0.942112 & 0.115777 & 0.0578883 \tabularnewline
51 & 0.931777 & 0.136447 & 0.0682234 \tabularnewline
52 & 0.916832 & 0.166336 & 0.0831682 \tabularnewline
53 & 0.899943 & 0.200115 & 0.100057 \tabularnewline
54 & 0.8857 & 0.2286 & 0.1143 \tabularnewline
55 & 0.874782 & 0.250436 & 0.125218 \tabularnewline
56 & 0.861671 & 0.276659 & 0.138329 \tabularnewline
57 & 0.857409 & 0.285183 & 0.142591 \tabularnewline
58 & 0.831178 & 0.337643 & 0.168822 \tabularnewline
59 & 0.851823 & 0.296354 & 0.148177 \tabularnewline
60 & 0.835554 & 0.328891 & 0.164446 \tabularnewline
61 & 0.844961 & 0.310078 & 0.155039 \tabularnewline
62 & 0.82811 & 0.34378 & 0.17189 \tabularnewline
63 & 0.863645 & 0.27271 & 0.136355 \tabularnewline
64 & 0.860603 & 0.278794 & 0.139397 \tabularnewline
65 & 0.862042 & 0.275915 & 0.137958 \tabularnewline
66 & 0.88015 & 0.239699 & 0.11985 \tabularnewline
67 & 0.881068 & 0.237864 & 0.118932 \tabularnewline
68 & 0.873355 & 0.25329 & 0.126645 \tabularnewline
69 & 0.912422 & 0.175156 & 0.0875779 \tabularnewline
70 & 0.919896 & 0.160208 & 0.0801042 \tabularnewline
71 & 0.909396 & 0.181209 & 0.0906044 \tabularnewline
72 & 0.937551 & 0.124899 & 0.0624493 \tabularnewline
73 & 0.926554 & 0.146891 & 0.0734457 \tabularnewline
74 & 0.911832 & 0.176336 & 0.0881681 \tabularnewline
75 & 0.904175 & 0.19165 & 0.0958251 \tabularnewline
76 & 0.886858 & 0.226284 & 0.113142 \tabularnewline
77 & 0.910433 & 0.179134 & 0.0895672 \tabularnewline
78 & 0.895206 & 0.209588 & 0.104794 \tabularnewline
79 & 0.885164 & 0.229672 & 0.114836 \tabularnewline
80 & 0.878371 & 0.243257 & 0.121629 \tabularnewline
81 & 0.858058 & 0.283885 & 0.141942 \tabularnewline
82 & 0.836368 & 0.327265 & 0.163632 \tabularnewline
83 & 0.832591 & 0.334818 & 0.167409 \tabularnewline
84 & 0.81129 & 0.377421 & 0.18871 \tabularnewline
85 & 0.785179 & 0.429643 & 0.214821 \tabularnewline
86 & 0.759465 & 0.48107 & 0.240535 \tabularnewline
87 & 0.72945 & 0.541099 & 0.27055 \tabularnewline
88 & 0.697974 & 0.604052 & 0.302026 \tabularnewline
89 & 0.770548 & 0.458904 & 0.229452 \tabularnewline
90 & 0.805686 & 0.388628 & 0.194314 \tabularnewline
91 & 0.781964 & 0.436072 & 0.218036 \tabularnewline
92 & 0.755808 & 0.488384 & 0.244192 \tabularnewline
93 & 0.733805 & 0.532389 & 0.266195 \tabularnewline
94 & 0.709543 & 0.580915 & 0.290457 \tabularnewline
95 & 0.685116 & 0.629769 & 0.314884 \tabularnewline
96 & 0.656307 & 0.687386 & 0.343693 \tabularnewline
97 & 0.628741 & 0.742518 & 0.371259 \tabularnewline
98 & 0.635525 & 0.728949 & 0.364475 \tabularnewline
99 & 0.600037 & 0.799926 & 0.399963 \tabularnewline
100 & 0.596915 & 0.806169 & 0.403085 \tabularnewline
101 & 0.569403 & 0.861195 & 0.430597 \tabularnewline
102 & 0.544688 & 0.910623 & 0.455312 \tabularnewline
103 & 0.599531 & 0.800938 & 0.400469 \tabularnewline
104 & 0.588398 & 0.823204 & 0.411602 \tabularnewline
105 & 0.603525 & 0.79295 & 0.396475 \tabularnewline
106 & 0.581007 & 0.837987 & 0.418993 \tabularnewline
107 & 0.576548 & 0.846903 & 0.423452 \tabularnewline
108 & 0.610314 & 0.779373 & 0.389686 \tabularnewline
109 & 0.576357 & 0.847286 & 0.423643 \tabularnewline
110 & 0.552136 & 0.895727 & 0.447864 \tabularnewline
111 & 0.553676 & 0.892649 & 0.446324 \tabularnewline
112 & 0.572162 & 0.855677 & 0.427838 \tabularnewline
113 & 0.579393 & 0.841215 & 0.420607 \tabularnewline
114 & 0.670961 & 0.658078 & 0.329039 \tabularnewline
115 & 0.644429 & 0.711142 & 0.355571 \tabularnewline
116 & 0.618386 & 0.763228 & 0.381614 \tabularnewline
117 & 0.583738 & 0.832523 & 0.416262 \tabularnewline
118 & 0.558235 & 0.883529 & 0.441765 \tabularnewline
119 & 0.522897 & 0.954207 & 0.477103 \tabularnewline
120 & 0.489095 & 0.97819 & 0.510905 \tabularnewline
121 & 0.466284 & 0.932568 & 0.533716 \tabularnewline
122 & 0.430988 & 0.861976 & 0.569012 \tabularnewline
123 & 0.401257 & 0.802513 & 0.598743 \tabularnewline
124 & 0.373057 & 0.746113 & 0.626943 \tabularnewline
125 & 0.361375 & 0.722749 & 0.638625 \tabularnewline
126 & 0.335702 & 0.671404 & 0.664298 \tabularnewline
127 & 0.323645 & 0.647289 & 0.676355 \tabularnewline
128 & 0.431586 & 0.863172 & 0.568414 \tabularnewline
129 & 0.413295 & 0.82659 & 0.586705 \tabularnewline
130 & 0.400662 & 0.801324 & 0.599338 \tabularnewline
131 & 0.387976 & 0.775951 & 0.612024 \tabularnewline
132 & 0.355536 & 0.711072 & 0.644464 \tabularnewline
133 & 0.378179 & 0.756357 & 0.621821 \tabularnewline
134 & 0.349377 & 0.698755 & 0.650623 \tabularnewline
135 & 0.36356 & 0.727119 & 0.63644 \tabularnewline
136 & 0.355385 & 0.71077 & 0.644615 \tabularnewline
137 & 0.326957 & 0.653915 & 0.673043 \tabularnewline
138 & 0.302296 & 0.604592 & 0.697704 \tabularnewline
139 & 0.275684 & 0.551368 & 0.724316 \tabularnewline
140 & 0.251564 & 0.503128 & 0.748436 \tabularnewline
141 & 0.225115 & 0.450229 & 0.774885 \tabularnewline
142 & 0.230206 & 0.460412 & 0.769794 \tabularnewline
143 & 0.204642 & 0.409285 & 0.795358 \tabularnewline
144 & 0.185712 & 0.371423 & 0.814288 \tabularnewline
145 & 0.171658 & 0.343316 & 0.828342 \tabularnewline
146 & 0.165956 & 0.331913 & 0.834044 \tabularnewline
147 & 0.171565 & 0.34313 & 0.828435 \tabularnewline
148 & 0.18663 & 0.37326 & 0.81337 \tabularnewline
149 & 0.203676 & 0.407352 & 0.796324 \tabularnewline
150 & 0.199168 & 0.398335 & 0.800832 \tabularnewline
151 & 0.176548 & 0.353096 & 0.823452 \tabularnewline
152 & 0.156653 & 0.313307 & 0.843347 \tabularnewline
153 & 0.165367 & 0.330733 & 0.834633 \tabularnewline
154 & 0.182245 & 0.36449 & 0.817755 \tabularnewline
155 & 0.163866 & 0.327732 & 0.836134 \tabularnewline
156 & 0.148559 & 0.297117 & 0.851441 \tabularnewline
157 & 0.129192 & 0.258384 & 0.870808 \tabularnewline
158 & 0.204912 & 0.409824 & 0.795088 \tabularnewline
159 & 0.223954 & 0.447907 & 0.776046 \tabularnewline
160 & 0.198269 & 0.396539 & 0.801731 \tabularnewline
161 & 0.173861 & 0.347722 & 0.826139 \tabularnewline
162 & 0.151644 & 0.303288 & 0.848356 \tabularnewline
163 & 0.131457 & 0.262913 & 0.868543 \tabularnewline
164 & 0.216664 & 0.433328 & 0.783336 \tabularnewline
165 & 0.218926 & 0.437851 & 0.781074 \tabularnewline
166 & 0.211734 & 0.423468 & 0.788266 \tabularnewline
167 & 0.186949 & 0.373898 & 0.813051 \tabularnewline
168 & 0.169438 & 0.338876 & 0.830562 \tabularnewline
169 & 0.226678 & 0.453357 & 0.773322 \tabularnewline
170 & 0.257683 & 0.515365 & 0.742317 \tabularnewline
171 & 0.22955 & 0.459101 & 0.77045 \tabularnewline
172 & 0.223545 & 0.44709 & 0.776455 \tabularnewline
173 & 0.393365 & 0.786729 & 0.606635 \tabularnewline
174 & 0.372954 & 0.745908 & 0.627046 \tabularnewline
175 & 0.390185 & 0.78037 & 0.609815 \tabularnewline
176 & 0.404088 & 0.808176 & 0.595912 \tabularnewline
177 & 0.469892 & 0.939785 & 0.530108 \tabularnewline
178 & 0.43273 & 0.865459 & 0.56727 \tabularnewline
179 & 0.409172 & 0.818344 & 0.590828 \tabularnewline
180 & 0.417896 & 0.835792 & 0.582104 \tabularnewline
181 & 0.382541 & 0.765082 & 0.617459 \tabularnewline
182 & 0.387298 & 0.774595 & 0.612702 \tabularnewline
183 & 0.351419 & 0.702838 & 0.648581 \tabularnewline
184 & 0.329778 & 0.659556 & 0.670222 \tabularnewline
185 & 0.329753 & 0.659505 & 0.670247 \tabularnewline
186 & 0.314862 & 0.629724 & 0.685138 \tabularnewline
187 & 0.28103 & 0.562059 & 0.71897 \tabularnewline
188 & 0.250412 & 0.500824 & 0.749588 \tabularnewline
189 & 0.220292 & 0.440584 & 0.779708 \tabularnewline
190 & 0.196352 & 0.392704 & 0.803648 \tabularnewline
191 & 0.208432 & 0.416864 & 0.791568 \tabularnewline
192 & 0.192208 & 0.384416 & 0.807792 \tabularnewline
193 & 0.197335 & 0.39467 & 0.802665 \tabularnewline
194 & 0.188616 & 0.377233 & 0.811384 \tabularnewline
195 & 0.184887 & 0.369774 & 0.815113 \tabularnewline
196 & 0.196753 & 0.393505 & 0.803247 \tabularnewline
197 & 0.233228 & 0.466456 & 0.766772 \tabularnewline
198 & 0.215041 & 0.430082 & 0.784959 \tabularnewline
199 & 0.249066 & 0.498131 & 0.750934 \tabularnewline
200 & 0.218521 & 0.437042 & 0.781479 \tabularnewline
201 & 0.256843 & 0.513686 & 0.743157 \tabularnewline
202 & 0.232369 & 0.464739 & 0.767631 \tabularnewline
203 & 0.267445 & 0.534889 & 0.732555 \tabularnewline
204 & 0.236569 & 0.473138 & 0.763431 \tabularnewline
205 & 0.205527 & 0.411054 & 0.794473 \tabularnewline
206 & 0.186496 & 0.372992 & 0.813504 \tabularnewline
207 & 0.158303 & 0.316605 & 0.841697 \tabularnewline
208 & 0.182179 & 0.364359 & 0.817821 \tabularnewline
209 & 0.154276 & 0.308551 & 0.845724 \tabularnewline
210 & 0.162889 & 0.325777 & 0.837111 \tabularnewline
211 & 0.180215 & 0.360431 & 0.819785 \tabularnewline
212 & 0.171385 & 0.342771 & 0.828615 \tabularnewline
213 & 0.147435 & 0.29487 & 0.852565 \tabularnewline
214 & 0.183312 & 0.366623 & 0.816688 \tabularnewline
215 & 0.161555 & 0.323111 & 0.838445 \tabularnewline
216 & 0.151191 & 0.302382 & 0.848809 \tabularnewline
217 & 0.17882 & 0.35764 & 0.82118 \tabularnewline
218 & 0.152878 & 0.305757 & 0.847122 \tabularnewline
219 & 0.14005 & 0.2801 & 0.85995 \tabularnewline
220 & 0.155558 & 0.311116 & 0.844442 \tabularnewline
221 & 0.158694 & 0.317387 & 0.841306 \tabularnewline
222 & 0.156475 & 0.31295 & 0.843525 \tabularnewline
223 & 0.140743 & 0.281486 & 0.859257 \tabularnewline
224 & 0.115397 & 0.230794 & 0.884603 \tabularnewline
225 & 0.112656 & 0.225312 & 0.887344 \tabularnewline
226 & 0.139408 & 0.278816 & 0.860592 \tabularnewline
227 & 0.350391 & 0.700782 & 0.649609 \tabularnewline
228 & 0.309611 & 0.619222 & 0.690389 \tabularnewline
229 & 0.271849 & 0.543698 & 0.728151 \tabularnewline
230 & 0.246568 & 0.493136 & 0.753432 \tabularnewline
231 & 0.212633 & 0.425266 & 0.787367 \tabularnewline
232 & 0.237588 & 0.475175 & 0.762412 \tabularnewline
233 & 0.197918 & 0.395836 & 0.802082 \tabularnewline
234 & 0.16351 & 0.32702 & 0.83649 \tabularnewline
235 & 0.168944 & 0.337888 & 0.831056 \tabularnewline
236 & 0.143184 & 0.286369 & 0.856816 \tabularnewline
237 & 0.121549 & 0.243098 & 0.878451 \tabularnewline
238 & 0.0914335 & 0.182867 & 0.908567 \tabularnewline
239 & 0.181136 & 0.362272 & 0.818864 \tabularnewline
240 & 0.187889 & 0.375778 & 0.812111 \tabularnewline
241 & 0.188772 & 0.377544 & 0.811228 \tabularnewline
242 & 0.80586 & 0.388281 & 0.19414 \tabularnewline
243 & 0.744286 & 0.511427 & 0.255714 \tabularnewline
244 & 0.679399 & 0.641203 & 0.320601 \tabularnewline
245 & 0.616777 & 0.766445 & 0.383223 \tabularnewline
246 & 0.538995 & 0.922009 & 0.461005 \tabularnewline
247 & 0.547829 & 0.904341 & 0.452171 \tabularnewline
248 & 0.545337 & 0.909327 & 0.454663 \tabularnewline
249 & 0.430405 & 0.860811 & 0.569595 \tabularnewline
250 & 0.340341 & 0.680682 & 0.659659 \tabularnewline
251 & 0.275997 & 0.551995 & 0.724003 \tabularnewline
252 & 0.795633 & 0.408733 & 0.204367 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226174&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]12[/C][C]0.883247[/C][C]0.233507[/C][C]0.116753[/C][/ROW]
[ROW][C]13[/C][C]0.991519[/C][C]0.0169612[/C][C]0.00848058[/C][/ROW]
[ROW][C]14[/C][C]0.989934[/C][C]0.020131[/C][C]0.0100655[/C][/ROW]
[ROW][C]15[/C][C]0.989662[/C][C]0.0206769[/C][C]0.0103384[/C][/ROW]
[ROW][C]16[/C][C]0.982089[/C][C]0.035822[/C][C]0.017911[/C][/ROW]
[ROW][C]17[/C][C]0.978741[/C][C]0.0425171[/C][C]0.0212585[/C][/ROW]
[ROW][C]18[/C][C]0.966989[/C][C]0.0660224[/C][C]0.0330112[/C][/ROW]
[ROW][C]19[/C][C]0.95513[/C][C]0.0897396[/C][C]0.0448698[/C][/ROW]
[ROW][C]20[/C][C]0.942848[/C][C]0.114304[/C][C]0.0571522[/C][/ROW]
[ROW][C]21[/C][C]0.94006[/C][C]0.119879[/C][C]0.0599397[/C][/ROW]
[ROW][C]22[/C][C]0.975811[/C][C]0.0483772[/C][C]0.0241886[/C][/ROW]
[ROW][C]23[/C][C]0.964828[/C][C]0.0703442[/C][C]0.0351721[/C][/ROW]
[ROW][C]24[/C][C]0.95549[/C][C]0.089019[/C][C]0.0445095[/C][/ROW]
[ROW][C]25[/C][C]0.939295[/C][C]0.121411[/C][C]0.0607054[/C][/ROW]
[ROW][C]26[/C][C]0.999032[/C][C]0.00193561[/C][C]0.000967807[/C][/ROW]
[ROW][C]27[/C][C]0.99864[/C][C]0.00272081[/C][C]0.0013604[/C][/ROW]
[ROW][C]28[/C][C]0.997843[/C][C]0.00431352[/C][C]0.00215676[/C][/ROW]
[ROW][C]29[/C][C]0.996785[/C][C]0.00643058[/C][C]0.00321529[/C][/ROW]
[ROW][C]30[/C][C]0.997426[/C][C]0.00514832[/C][C]0.00257416[/C][/ROW]
[ROW][C]31[/C][C]0.996293[/C][C]0.00741408[/C][C]0.00370704[/C][/ROW]
[ROW][C]32[/C][C]0.994415[/C][C]0.0111695[/C][C]0.00558474[/C][/ROW]
[ROW][C]33[/C][C]0.994308[/C][C]0.0113846[/C][C]0.00569232[/C][/ROW]
[ROW][C]34[/C][C]0.991645[/C][C]0.0167092[/C][C]0.00835459[/C][/ROW]
[ROW][C]35[/C][C]0.988007[/C][C]0.023986[/C][C]0.011993[/C][/ROW]
[ROW][C]36[/C][C]0.983344[/C][C]0.0333129[/C][C]0.0166564[/C][/ROW]
[ROW][C]37[/C][C]0.984999[/C][C]0.0300021[/C][C]0.0150011[/C][/ROW]
[ROW][C]38[/C][C]0.98052[/C][C]0.0389593[/C][C]0.0194796[/C][/ROW]
[ROW][C]39[/C][C]0.980153[/C][C]0.0396931[/C][C]0.0198465[/C][/ROW]
[ROW][C]40[/C][C]0.977241[/C][C]0.0455174[/C][C]0.0227587[/C][/ROW]
[ROW][C]41[/C][C]0.969525[/C][C]0.0609499[/C][C]0.0304749[/C][/ROW]
[ROW][C]42[/C][C]0.971859[/C][C]0.0562821[/C][C]0.028141[/C][/ROW]
[ROW][C]43[/C][C]0.965109[/C][C]0.0697829[/C][C]0.0348914[/C][/ROW]
[ROW][C]44[/C][C]0.955795[/C][C]0.0884107[/C][C]0.0442053[/C][/ROW]
[ROW][C]45[/C][C]0.943564[/C][C]0.112871[/C][C]0.0564356[/C][/ROW]
[ROW][C]46[/C][C]0.945121[/C][C]0.109758[/C][C]0.0548789[/C][/ROW]
[ROW][C]47[/C][C]0.933111[/C][C]0.133779[/C][C]0.0668893[/C][/ROW]
[ROW][C]48[/C][C]0.917921[/C][C]0.164158[/C][C]0.082079[/C][/ROW]
[ROW][C]49[/C][C]0.948754[/C][C]0.102491[/C][C]0.0512456[/C][/ROW]
[ROW][C]50[/C][C]0.942112[/C][C]0.115777[/C][C]0.0578883[/C][/ROW]
[ROW][C]51[/C][C]0.931777[/C][C]0.136447[/C][C]0.0682234[/C][/ROW]
[ROW][C]52[/C][C]0.916832[/C][C]0.166336[/C][C]0.0831682[/C][/ROW]
[ROW][C]53[/C][C]0.899943[/C][C]0.200115[/C][C]0.100057[/C][/ROW]
[ROW][C]54[/C][C]0.8857[/C][C]0.2286[/C][C]0.1143[/C][/ROW]
[ROW][C]55[/C][C]0.874782[/C][C]0.250436[/C][C]0.125218[/C][/ROW]
[ROW][C]56[/C][C]0.861671[/C][C]0.276659[/C][C]0.138329[/C][/ROW]
[ROW][C]57[/C][C]0.857409[/C][C]0.285183[/C][C]0.142591[/C][/ROW]
[ROW][C]58[/C][C]0.831178[/C][C]0.337643[/C][C]0.168822[/C][/ROW]
[ROW][C]59[/C][C]0.851823[/C][C]0.296354[/C][C]0.148177[/C][/ROW]
[ROW][C]60[/C][C]0.835554[/C][C]0.328891[/C][C]0.164446[/C][/ROW]
[ROW][C]61[/C][C]0.844961[/C][C]0.310078[/C][C]0.155039[/C][/ROW]
[ROW][C]62[/C][C]0.82811[/C][C]0.34378[/C][C]0.17189[/C][/ROW]
[ROW][C]63[/C][C]0.863645[/C][C]0.27271[/C][C]0.136355[/C][/ROW]
[ROW][C]64[/C][C]0.860603[/C][C]0.278794[/C][C]0.139397[/C][/ROW]
[ROW][C]65[/C][C]0.862042[/C][C]0.275915[/C][C]0.137958[/C][/ROW]
[ROW][C]66[/C][C]0.88015[/C][C]0.239699[/C][C]0.11985[/C][/ROW]
[ROW][C]67[/C][C]0.881068[/C][C]0.237864[/C][C]0.118932[/C][/ROW]
[ROW][C]68[/C][C]0.873355[/C][C]0.25329[/C][C]0.126645[/C][/ROW]
[ROW][C]69[/C][C]0.912422[/C][C]0.175156[/C][C]0.0875779[/C][/ROW]
[ROW][C]70[/C][C]0.919896[/C][C]0.160208[/C][C]0.0801042[/C][/ROW]
[ROW][C]71[/C][C]0.909396[/C][C]0.181209[/C][C]0.0906044[/C][/ROW]
[ROW][C]72[/C][C]0.937551[/C][C]0.124899[/C][C]0.0624493[/C][/ROW]
[ROW][C]73[/C][C]0.926554[/C][C]0.146891[/C][C]0.0734457[/C][/ROW]
[ROW][C]74[/C][C]0.911832[/C][C]0.176336[/C][C]0.0881681[/C][/ROW]
[ROW][C]75[/C][C]0.904175[/C][C]0.19165[/C][C]0.0958251[/C][/ROW]
[ROW][C]76[/C][C]0.886858[/C][C]0.226284[/C][C]0.113142[/C][/ROW]
[ROW][C]77[/C][C]0.910433[/C][C]0.179134[/C][C]0.0895672[/C][/ROW]
[ROW][C]78[/C][C]0.895206[/C][C]0.209588[/C][C]0.104794[/C][/ROW]
[ROW][C]79[/C][C]0.885164[/C][C]0.229672[/C][C]0.114836[/C][/ROW]
[ROW][C]80[/C][C]0.878371[/C][C]0.243257[/C][C]0.121629[/C][/ROW]
[ROW][C]81[/C][C]0.858058[/C][C]0.283885[/C][C]0.141942[/C][/ROW]
[ROW][C]82[/C][C]0.836368[/C][C]0.327265[/C][C]0.163632[/C][/ROW]
[ROW][C]83[/C][C]0.832591[/C][C]0.334818[/C][C]0.167409[/C][/ROW]
[ROW][C]84[/C][C]0.81129[/C][C]0.377421[/C][C]0.18871[/C][/ROW]
[ROW][C]85[/C][C]0.785179[/C][C]0.429643[/C][C]0.214821[/C][/ROW]
[ROW][C]86[/C][C]0.759465[/C][C]0.48107[/C][C]0.240535[/C][/ROW]
[ROW][C]87[/C][C]0.72945[/C][C]0.541099[/C][C]0.27055[/C][/ROW]
[ROW][C]88[/C][C]0.697974[/C][C]0.604052[/C][C]0.302026[/C][/ROW]
[ROW][C]89[/C][C]0.770548[/C][C]0.458904[/C][C]0.229452[/C][/ROW]
[ROW][C]90[/C][C]0.805686[/C][C]0.388628[/C][C]0.194314[/C][/ROW]
[ROW][C]91[/C][C]0.781964[/C][C]0.436072[/C][C]0.218036[/C][/ROW]
[ROW][C]92[/C][C]0.755808[/C][C]0.488384[/C][C]0.244192[/C][/ROW]
[ROW][C]93[/C][C]0.733805[/C][C]0.532389[/C][C]0.266195[/C][/ROW]
[ROW][C]94[/C][C]0.709543[/C][C]0.580915[/C][C]0.290457[/C][/ROW]
[ROW][C]95[/C][C]0.685116[/C][C]0.629769[/C][C]0.314884[/C][/ROW]
[ROW][C]96[/C][C]0.656307[/C][C]0.687386[/C][C]0.343693[/C][/ROW]
[ROW][C]97[/C][C]0.628741[/C][C]0.742518[/C][C]0.371259[/C][/ROW]
[ROW][C]98[/C][C]0.635525[/C][C]0.728949[/C][C]0.364475[/C][/ROW]
[ROW][C]99[/C][C]0.600037[/C][C]0.799926[/C][C]0.399963[/C][/ROW]
[ROW][C]100[/C][C]0.596915[/C][C]0.806169[/C][C]0.403085[/C][/ROW]
[ROW][C]101[/C][C]0.569403[/C][C]0.861195[/C][C]0.430597[/C][/ROW]
[ROW][C]102[/C][C]0.544688[/C][C]0.910623[/C][C]0.455312[/C][/ROW]
[ROW][C]103[/C][C]0.599531[/C][C]0.800938[/C][C]0.400469[/C][/ROW]
[ROW][C]104[/C][C]0.588398[/C][C]0.823204[/C][C]0.411602[/C][/ROW]
[ROW][C]105[/C][C]0.603525[/C][C]0.79295[/C][C]0.396475[/C][/ROW]
[ROW][C]106[/C][C]0.581007[/C][C]0.837987[/C][C]0.418993[/C][/ROW]
[ROW][C]107[/C][C]0.576548[/C][C]0.846903[/C][C]0.423452[/C][/ROW]
[ROW][C]108[/C][C]0.610314[/C][C]0.779373[/C][C]0.389686[/C][/ROW]
[ROW][C]109[/C][C]0.576357[/C][C]0.847286[/C][C]0.423643[/C][/ROW]
[ROW][C]110[/C][C]0.552136[/C][C]0.895727[/C][C]0.447864[/C][/ROW]
[ROW][C]111[/C][C]0.553676[/C][C]0.892649[/C][C]0.446324[/C][/ROW]
[ROW][C]112[/C][C]0.572162[/C][C]0.855677[/C][C]0.427838[/C][/ROW]
[ROW][C]113[/C][C]0.579393[/C][C]0.841215[/C][C]0.420607[/C][/ROW]
[ROW][C]114[/C][C]0.670961[/C][C]0.658078[/C][C]0.329039[/C][/ROW]
[ROW][C]115[/C][C]0.644429[/C][C]0.711142[/C][C]0.355571[/C][/ROW]
[ROW][C]116[/C][C]0.618386[/C][C]0.763228[/C][C]0.381614[/C][/ROW]
[ROW][C]117[/C][C]0.583738[/C][C]0.832523[/C][C]0.416262[/C][/ROW]
[ROW][C]118[/C][C]0.558235[/C][C]0.883529[/C][C]0.441765[/C][/ROW]
[ROW][C]119[/C][C]0.522897[/C][C]0.954207[/C][C]0.477103[/C][/ROW]
[ROW][C]120[/C][C]0.489095[/C][C]0.97819[/C][C]0.510905[/C][/ROW]
[ROW][C]121[/C][C]0.466284[/C][C]0.932568[/C][C]0.533716[/C][/ROW]
[ROW][C]122[/C][C]0.430988[/C][C]0.861976[/C][C]0.569012[/C][/ROW]
[ROW][C]123[/C][C]0.401257[/C][C]0.802513[/C][C]0.598743[/C][/ROW]
[ROW][C]124[/C][C]0.373057[/C][C]0.746113[/C][C]0.626943[/C][/ROW]
[ROW][C]125[/C][C]0.361375[/C][C]0.722749[/C][C]0.638625[/C][/ROW]
[ROW][C]126[/C][C]0.335702[/C][C]0.671404[/C][C]0.664298[/C][/ROW]
[ROW][C]127[/C][C]0.323645[/C][C]0.647289[/C][C]0.676355[/C][/ROW]
[ROW][C]128[/C][C]0.431586[/C][C]0.863172[/C][C]0.568414[/C][/ROW]
[ROW][C]129[/C][C]0.413295[/C][C]0.82659[/C][C]0.586705[/C][/ROW]
[ROW][C]130[/C][C]0.400662[/C][C]0.801324[/C][C]0.599338[/C][/ROW]
[ROW][C]131[/C][C]0.387976[/C][C]0.775951[/C][C]0.612024[/C][/ROW]
[ROW][C]132[/C][C]0.355536[/C][C]0.711072[/C][C]0.644464[/C][/ROW]
[ROW][C]133[/C][C]0.378179[/C][C]0.756357[/C][C]0.621821[/C][/ROW]
[ROW][C]134[/C][C]0.349377[/C][C]0.698755[/C][C]0.650623[/C][/ROW]
[ROW][C]135[/C][C]0.36356[/C][C]0.727119[/C][C]0.63644[/C][/ROW]
[ROW][C]136[/C][C]0.355385[/C][C]0.71077[/C][C]0.644615[/C][/ROW]
[ROW][C]137[/C][C]0.326957[/C][C]0.653915[/C][C]0.673043[/C][/ROW]
[ROW][C]138[/C][C]0.302296[/C][C]0.604592[/C][C]0.697704[/C][/ROW]
[ROW][C]139[/C][C]0.275684[/C][C]0.551368[/C][C]0.724316[/C][/ROW]
[ROW][C]140[/C][C]0.251564[/C][C]0.503128[/C][C]0.748436[/C][/ROW]
[ROW][C]141[/C][C]0.225115[/C][C]0.450229[/C][C]0.774885[/C][/ROW]
[ROW][C]142[/C][C]0.230206[/C][C]0.460412[/C][C]0.769794[/C][/ROW]
[ROW][C]143[/C][C]0.204642[/C][C]0.409285[/C][C]0.795358[/C][/ROW]
[ROW][C]144[/C][C]0.185712[/C][C]0.371423[/C][C]0.814288[/C][/ROW]
[ROW][C]145[/C][C]0.171658[/C][C]0.343316[/C][C]0.828342[/C][/ROW]
[ROW][C]146[/C][C]0.165956[/C][C]0.331913[/C][C]0.834044[/C][/ROW]
[ROW][C]147[/C][C]0.171565[/C][C]0.34313[/C][C]0.828435[/C][/ROW]
[ROW][C]148[/C][C]0.18663[/C][C]0.37326[/C][C]0.81337[/C][/ROW]
[ROW][C]149[/C][C]0.203676[/C][C]0.407352[/C][C]0.796324[/C][/ROW]
[ROW][C]150[/C][C]0.199168[/C][C]0.398335[/C][C]0.800832[/C][/ROW]
[ROW][C]151[/C][C]0.176548[/C][C]0.353096[/C][C]0.823452[/C][/ROW]
[ROW][C]152[/C][C]0.156653[/C][C]0.313307[/C][C]0.843347[/C][/ROW]
[ROW][C]153[/C][C]0.165367[/C][C]0.330733[/C][C]0.834633[/C][/ROW]
[ROW][C]154[/C][C]0.182245[/C][C]0.36449[/C][C]0.817755[/C][/ROW]
[ROW][C]155[/C][C]0.163866[/C][C]0.327732[/C][C]0.836134[/C][/ROW]
[ROW][C]156[/C][C]0.148559[/C][C]0.297117[/C][C]0.851441[/C][/ROW]
[ROW][C]157[/C][C]0.129192[/C][C]0.258384[/C][C]0.870808[/C][/ROW]
[ROW][C]158[/C][C]0.204912[/C][C]0.409824[/C][C]0.795088[/C][/ROW]
[ROW][C]159[/C][C]0.223954[/C][C]0.447907[/C][C]0.776046[/C][/ROW]
[ROW][C]160[/C][C]0.198269[/C][C]0.396539[/C][C]0.801731[/C][/ROW]
[ROW][C]161[/C][C]0.173861[/C][C]0.347722[/C][C]0.826139[/C][/ROW]
[ROW][C]162[/C][C]0.151644[/C][C]0.303288[/C][C]0.848356[/C][/ROW]
[ROW][C]163[/C][C]0.131457[/C][C]0.262913[/C][C]0.868543[/C][/ROW]
[ROW][C]164[/C][C]0.216664[/C][C]0.433328[/C][C]0.783336[/C][/ROW]
[ROW][C]165[/C][C]0.218926[/C][C]0.437851[/C][C]0.781074[/C][/ROW]
[ROW][C]166[/C][C]0.211734[/C][C]0.423468[/C][C]0.788266[/C][/ROW]
[ROW][C]167[/C][C]0.186949[/C][C]0.373898[/C][C]0.813051[/C][/ROW]
[ROW][C]168[/C][C]0.169438[/C][C]0.338876[/C][C]0.830562[/C][/ROW]
[ROW][C]169[/C][C]0.226678[/C][C]0.453357[/C][C]0.773322[/C][/ROW]
[ROW][C]170[/C][C]0.257683[/C][C]0.515365[/C][C]0.742317[/C][/ROW]
[ROW][C]171[/C][C]0.22955[/C][C]0.459101[/C][C]0.77045[/C][/ROW]
[ROW][C]172[/C][C]0.223545[/C][C]0.44709[/C][C]0.776455[/C][/ROW]
[ROW][C]173[/C][C]0.393365[/C][C]0.786729[/C][C]0.606635[/C][/ROW]
[ROW][C]174[/C][C]0.372954[/C][C]0.745908[/C][C]0.627046[/C][/ROW]
[ROW][C]175[/C][C]0.390185[/C][C]0.78037[/C][C]0.609815[/C][/ROW]
[ROW][C]176[/C][C]0.404088[/C][C]0.808176[/C][C]0.595912[/C][/ROW]
[ROW][C]177[/C][C]0.469892[/C][C]0.939785[/C][C]0.530108[/C][/ROW]
[ROW][C]178[/C][C]0.43273[/C][C]0.865459[/C][C]0.56727[/C][/ROW]
[ROW][C]179[/C][C]0.409172[/C][C]0.818344[/C][C]0.590828[/C][/ROW]
[ROW][C]180[/C][C]0.417896[/C][C]0.835792[/C][C]0.582104[/C][/ROW]
[ROW][C]181[/C][C]0.382541[/C][C]0.765082[/C][C]0.617459[/C][/ROW]
[ROW][C]182[/C][C]0.387298[/C][C]0.774595[/C][C]0.612702[/C][/ROW]
[ROW][C]183[/C][C]0.351419[/C][C]0.702838[/C][C]0.648581[/C][/ROW]
[ROW][C]184[/C][C]0.329778[/C][C]0.659556[/C][C]0.670222[/C][/ROW]
[ROW][C]185[/C][C]0.329753[/C][C]0.659505[/C][C]0.670247[/C][/ROW]
[ROW][C]186[/C][C]0.314862[/C][C]0.629724[/C][C]0.685138[/C][/ROW]
[ROW][C]187[/C][C]0.28103[/C][C]0.562059[/C][C]0.71897[/C][/ROW]
[ROW][C]188[/C][C]0.250412[/C][C]0.500824[/C][C]0.749588[/C][/ROW]
[ROW][C]189[/C][C]0.220292[/C][C]0.440584[/C][C]0.779708[/C][/ROW]
[ROW][C]190[/C][C]0.196352[/C][C]0.392704[/C][C]0.803648[/C][/ROW]
[ROW][C]191[/C][C]0.208432[/C][C]0.416864[/C][C]0.791568[/C][/ROW]
[ROW][C]192[/C][C]0.192208[/C][C]0.384416[/C][C]0.807792[/C][/ROW]
[ROW][C]193[/C][C]0.197335[/C][C]0.39467[/C][C]0.802665[/C][/ROW]
[ROW][C]194[/C][C]0.188616[/C][C]0.377233[/C][C]0.811384[/C][/ROW]
[ROW][C]195[/C][C]0.184887[/C][C]0.369774[/C][C]0.815113[/C][/ROW]
[ROW][C]196[/C][C]0.196753[/C][C]0.393505[/C][C]0.803247[/C][/ROW]
[ROW][C]197[/C][C]0.233228[/C][C]0.466456[/C][C]0.766772[/C][/ROW]
[ROW][C]198[/C][C]0.215041[/C][C]0.430082[/C][C]0.784959[/C][/ROW]
[ROW][C]199[/C][C]0.249066[/C][C]0.498131[/C][C]0.750934[/C][/ROW]
[ROW][C]200[/C][C]0.218521[/C][C]0.437042[/C][C]0.781479[/C][/ROW]
[ROW][C]201[/C][C]0.256843[/C][C]0.513686[/C][C]0.743157[/C][/ROW]
[ROW][C]202[/C][C]0.232369[/C][C]0.464739[/C][C]0.767631[/C][/ROW]
[ROW][C]203[/C][C]0.267445[/C][C]0.534889[/C][C]0.732555[/C][/ROW]
[ROW][C]204[/C][C]0.236569[/C][C]0.473138[/C][C]0.763431[/C][/ROW]
[ROW][C]205[/C][C]0.205527[/C][C]0.411054[/C][C]0.794473[/C][/ROW]
[ROW][C]206[/C][C]0.186496[/C][C]0.372992[/C][C]0.813504[/C][/ROW]
[ROW][C]207[/C][C]0.158303[/C][C]0.316605[/C][C]0.841697[/C][/ROW]
[ROW][C]208[/C][C]0.182179[/C][C]0.364359[/C][C]0.817821[/C][/ROW]
[ROW][C]209[/C][C]0.154276[/C][C]0.308551[/C][C]0.845724[/C][/ROW]
[ROW][C]210[/C][C]0.162889[/C][C]0.325777[/C][C]0.837111[/C][/ROW]
[ROW][C]211[/C][C]0.180215[/C][C]0.360431[/C][C]0.819785[/C][/ROW]
[ROW][C]212[/C][C]0.171385[/C][C]0.342771[/C][C]0.828615[/C][/ROW]
[ROW][C]213[/C][C]0.147435[/C][C]0.29487[/C][C]0.852565[/C][/ROW]
[ROW][C]214[/C][C]0.183312[/C][C]0.366623[/C][C]0.816688[/C][/ROW]
[ROW][C]215[/C][C]0.161555[/C][C]0.323111[/C][C]0.838445[/C][/ROW]
[ROW][C]216[/C][C]0.151191[/C][C]0.302382[/C][C]0.848809[/C][/ROW]
[ROW][C]217[/C][C]0.17882[/C][C]0.35764[/C][C]0.82118[/C][/ROW]
[ROW][C]218[/C][C]0.152878[/C][C]0.305757[/C][C]0.847122[/C][/ROW]
[ROW][C]219[/C][C]0.14005[/C][C]0.2801[/C][C]0.85995[/C][/ROW]
[ROW][C]220[/C][C]0.155558[/C][C]0.311116[/C][C]0.844442[/C][/ROW]
[ROW][C]221[/C][C]0.158694[/C][C]0.317387[/C][C]0.841306[/C][/ROW]
[ROW][C]222[/C][C]0.156475[/C][C]0.31295[/C][C]0.843525[/C][/ROW]
[ROW][C]223[/C][C]0.140743[/C][C]0.281486[/C][C]0.859257[/C][/ROW]
[ROW][C]224[/C][C]0.115397[/C][C]0.230794[/C][C]0.884603[/C][/ROW]
[ROW][C]225[/C][C]0.112656[/C][C]0.225312[/C][C]0.887344[/C][/ROW]
[ROW][C]226[/C][C]0.139408[/C][C]0.278816[/C][C]0.860592[/C][/ROW]
[ROW][C]227[/C][C]0.350391[/C][C]0.700782[/C][C]0.649609[/C][/ROW]
[ROW][C]228[/C][C]0.309611[/C][C]0.619222[/C][C]0.690389[/C][/ROW]
[ROW][C]229[/C][C]0.271849[/C][C]0.543698[/C][C]0.728151[/C][/ROW]
[ROW][C]230[/C][C]0.246568[/C][C]0.493136[/C][C]0.753432[/C][/ROW]
[ROW][C]231[/C][C]0.212633[/C][C]0.425266[/C][C]0.787367[/C][/ROW]
[ROW][C]232[/C][C]0.237588[/C][C]0.475175[/C][C]0.762412[/C][/ROW]
[ROW][C]233[/C][C]0.197918[/C][C]0.395836[/C][C]0.802082[/C][/ROW]
[ROW][C]234[/C][C]0.16351[/C][C]0.32702[/C][C]0.83649[/C][/ROW]
[ROW][C]235[/C][C]0.168944[/C][C]0.337888[/C][C]0.831056[/C][/ROW]
[ROW][C]236[/C][C]0.143184[/C][C]0.286369[/C][C]0.856816[/C][/ROW]
[ROW][C]237[/C][C]0.121549[/C][C]0.243098[/C][C]0.878451[/C][/ROW]
[ROW][C]238[/C][C]0.0914335[/C][C]0.182867[/C][C]0.908567[/C][/ROW]
[ROW][C]239[/C][C]0.181136[/C][C]0.362272[/C][C]0.818864[/C][/ROW]
[ROW][C]240[/C][C]0.187889[/C][C]0.375778[/C][C]0.812111[/C][/ROW]
[ROW][C]241[/C][C]0.188772[/C][C]0.377544[/C][C]0.811228[/C][/ROW]
[ROW][C]242[/C][C]0.80586[/C][C]0.388281[/C][C]0.19414[/C][/ROW]
[ROW][C]243[/C][C]0.744286[/C][C]0.511427[/C][C]0.255714[/C][/ROW]
[ROW][C]244[/C][C]0.679399[/C][C]0.641203[/C][C]0.320601[/C][/ROW]
[ROW][C]245[/C][C]0.616777[/C][C]0.766445[/C][C]0.383223[/C][/ROW]
[ROW][C]246[/C][C]0.538995[/C][C]0.922009[/C][C]0.461005[/C][/ROW]
[ROW][C]247[/C][C]0.547829[/C][C]0.904341[/C][C]0.452171[/C][/ROW]
[ROW][C]248[/C][C]0.545337[/C][C]0.909327[/C][C]0.454663[/C][/ROW]
[ROW][C]249[/C][C]0.430405[/C][C]0.860811[/C][C]0.569595[/C][/ROW]
[ROW][C]250[/C][C]0.340341[/C][C]0.680682[/C][C]0.659659[/C][/ROW]
[ROW][C]251[/C][C]0.275997[/C][C]0.551995[/C][C]0.724003[/C][/ROW]
[ROW][C]252[/C][C]0.795633[/C][C]0.408733[/C][C]0.204367[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226174&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226174&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
120.8832470.2335070.116753
130.9915190.01696120.00848058
140.9899340.0201310.0100655
150.9896620.02067690.0103384
160.9820890.0358220.017911
170.9787410.04251710.0212585
180.9669890.06602240.0330112
190.955130.08973960.0448698
200.9428480.1143040.0571522
210.940060.1198790.0599397
220.9758110.04837720.0241886
230.9648280.07034420.0351721
240.955490.0890190.0445095
250.9392950.1214110.0607054
260.9990320.001935610.000967807
270.998640.002720810.0013604
280.9978430.004313520.00215676
290.9967850.006430580.00321529
300.9974260.005148320.00257416
310.9962930.007414080.00370704
320.9944150.01116950.00558474
330.9943080.01138460.00569232
340.9916450.01670920.00835459
350.9880070.0239860.011993
360.9833440.03331290.0166564
370.9849990.03000210.0150011
380.980520.03895930.0194796
390.9801530.03969310.0198465
400.9772410.04551740.0227587
410.9695250.06094990.0304749
420.9718590.05628210.028141
430.9651090.06978290.0348914
440.9557950.08841070.0442053
450.9435640.1128710.0564356
460.9451210.1097580.0548789
470.9331110.1337790.0668893
480.9179210.1641580.082079
490.9487540.1024910.0512456
500.9421120.1157770.0578883
510.9317770.1364470.0682234
520.9168320.1663360.0831682
530.8999430.2001150.100057
540.88570.22860.1143
550.8747820.2504360.125218
560.8616710.2766590.138329
570.8574090.2851830.142591
580.8311780.3376430.168822
590.8518230.2963540.148177
600.8355540.3288910.164446
610.8449610.3100780.155039
620.828110.343780.17189
630.8636450.272710.136355
640.8606030.2787940.139397
650.8620420.2759150.137958
660.880150.2396990.11985
670.8810680.2378640.118932
680.8733550.253290.126645
690.9124220.1751560.0875779
700.9198960.1602080.0801042
710.9093960.1812090.0906044
720.9375510.1248990.0624493
730.9265540.1468910.0734457
740.9118320.1763360.0881681
750.9041750.191650.0958251
760.8868580.2262840.113142
770.9104330.1791340.0895672
780.8952060.2095880.104794
790.8851640.2296720.114836
800.8783710.2432570.121629
810.8580580.2838850.141942
820.8363680.3272650.163632
830.8325910.3348180.167409
840.811290.3774210.18871
850.7851790.4296430.214821
860.7594650.481070.240535
870.729450.5410990.27055
880.6979740.6040520.302026
890.7705480.4589040.229452
900.8056860.3886280.194314
910.7819640.4360720.218036
920.7558080.4883840.244192
930.7338050.5323890.266195
940.7095430.5809150.290457
950.6851160.6297690.314884
960.6563070.6873860.343693
970.6287410.7425180.371259
980.6355250.7289490.364475
990.6000370.7999260.399963
1000.5969150.8061690.403085
1010.5694030.8611950.430597
1020.5446880.9106230.455312
1030.5995310.8009380.400469
1040.5883980.8232040.411602
1050.6035250.792950.396475
1060.5810070.8379870.418993
1070.5765480.8469030.423452
1080.6103140.7793730.389686
1090.5763570.8472860.423643
1100.5521360.8957270.447864
1110.5536760.8926490.446324
1120.5721620.8556770.427838
1130.5793930.8412150.420607
1140.6709610.6580780.329039
1150.6444290.7111420.355571
1160.6183860.7632280.381614
1170.5837380.8325230.416262
1180.5582350.8835290.441765
1190.5228970.9542070.477103
1200.4890950.978190.510905
1210.4662840.9325680.533716
1220.4309880.8619760.569012
1230.4012570.8025130.598743
1240.3730570.7461130.626943
1250.3613750.7227490.638625
1260.3357020.6714040.664298
1270.3236450.6472890.676355
1280.4315860.8631720.568414
1290.4132950.826590.586705
1300.4006620.8013240.599338
1310.3879760.7759510.612024
1320.3555360.7110720.644464
1330.3781790.7563570.621821
1340.3493770.6987550.650623
1350.363560.7271190.63644
1360.3553850.710770.644615
1370.3269570.6539150.673043
1380.3022960.6045920.697704
1390.2756840.5513680.724316
1400.2515640.5031280.748436
1410.2251150.4502290.774885
1420.2302060.4604120.769794
1430.2046420.4092850.795358
1440.1857120.3714230.814288
1450.1716580.3433160.828342
1460.1659560.3319130.834044
1470.1715650.343130.828435
1480.186630.373260.81337
1490.2036760.4073520.796324
1500.1991680.3983350.800832
1510.1765480.3530960.823452
1520.1566530.3133070.843347
1530.1653670.3307330.834633
1540.1822450.364490.817755
1550.1638660.3277320.836134
1560.1485590.2971170.851441
1570.1291920.2583840.870808
1580.2049120.4098240.795088
1590.2239540.4479070.776046
1600.1982690.3965390.801731
1610.1738610.3477220.826139
1620.1516440.3032880.848356
1630.1314570.2629130.868543
1640.2166640.4333280.783336
1650.2189260.4378510.781074
1660.2117340.4234680.788266
1670.1869490.3738980.813051
1680.1694380.3388760.830562
1690.2266780.4533570.773322
1700.2576830.5153650.742317
1710.229550.4591010.77045
1720.2235450.447090.776455
1730.3933650.7867290.606635
1740.3729540.7459080.627046
1750.3901850.780370.609815
1760.4040880.8081760.595912
1770.4698920.9397850.530108
1780.432730.8654590.56727
1790.4091720.8183440.590828
1800.4178960.8357920.582104
1810.3825410.7650820.617459
1820.3872980.7745950.612702
1830.3514190.7028380.648581
1840.3297780.6595560.670222
1850.3297530.6595050.670247
1860.3148620.6297240.685138
1870.281030.5620590.71897
1880.2504120.5008240.749588
1890.2202920.4405840.779708
1900.1963520.3927040.803648
1910.2084320.4168640.791568
1920.1922080.3844160.807792
1930.1973350.394670.802665
1940.1886160.3772330.811384
1950.1848870.3697740.815113
1960.1967530.3935050.803247
1970.2332280.4664560.766772
1980.2150410.4300820.784959
1990.2490660.4981310.750934
2000.2185210.4370420.781479
2010.2568430.5136860.743157
2020.2323690.4647390.767631
2030.2674450.5348890.732555
2040.2365690.4731380.763431
2050.2055270.4110540.794473
2060.1864960.3729920.813504
2070.1583030.3166050.841697
2080.1821790.3643590.817821
2090.1542760.3085510.845724
2100.1628890.3257770.837111
2110.1802150.3604310.819785
2120.1713850.3427710.828615
2130.1474350.294870.852565
2140.1833120.3666230.816688
2150.1615550.3231110.838445
2160.1511910.3023820.848809
2170.178820.357640.82118
2180.1528780.3057570.847122
2190.140050.28010.85995
2200.1555580.3111160.844442
2210.1586940.3173870.841306
2220.1564750.312950.843525
2230.1407430.2814860.859257
2240.1153970.2307940.884603
2250.1126560.2253120.887344
2260.1394080.2788160.860592
2270.3503910.7007820.649609
2280.3096110.6192220.690389
2290.2718490.5436980.728151
2300.2465680.4931360.753432
2310.2126330.4252660.787367
2320.2375880.4751750.762412
2330.1979180.3958360.802082
2340.163510.327020.83649
2350.1689440.3378880.831056
2360.1431840.2863690.856816
2370.1215490.2430980.878451
2380.09143350.1828670.908567
2390.1811360.3622720.818864
2400.1878890.3757780.812111
2410.1887720.3775440.811228
2420.805860.3882810.19414
2430.7442860.5114270.255714
2440.6793990.6412030.320601
2450.6167770.7664450.383223
2460.5389950.9220090.461005
2470.5478290.9043410.452171
2480.5453370.9093270.454663
2490.4304050.8608110.569595
2500.3403410.6806820.659659
2510.2759970.5519950.724003
2520.7956330.4087330.204367






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level60.0248963NOK
5% type I error level210.0871369NOK
10% type I error level290.120332NOK

\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 & 6 & 0.0248963 & NOK \tabularnewline
5% type I error level & 21 & 0.0871369 & NOK \tabularnewline
10% type I error level & 29 & 0.120332 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226174&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]6[/C][C]0.0248963[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]21[/C][C]0.0871369[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]29[/C][C]0.120332[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226174&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226174&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 level60.0248963NOK
5% type I error level210.0871369NOK
10% type I error level290.120332NOK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = 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')
}