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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 17 Nov 2013 09:34:04 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/17/t1384698860h1bdyilfl3pd047.htm/, Retrieved Mon, 29 Apr 2024 03:25:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=225761, Retrieved Mon, 29 Apr 2024 03:25:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [ws 7 ] [2013-11-17 14:34:04] [3ab494e3ec4169588a52211572c2f14a] [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 time19 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 19 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.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=225761&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]19 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[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=225761&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225761&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time19 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net
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] = + 18.2138 + 0.00467834Connected[t] + 0.0119577Separate[t] + 0.0920534Learning[t] -0.0203603Software[t] -0.36232Depression[t] + 0.0259464Sport1[t] -0.321366Month[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  18.2138 +  0.00467834Connected[t] +  0.0119577Separate[t] +  0.0920534Learning[t] -0.0203603Software[t] -0.36232Depression[t] +  0.0259464Sport1[t] -0.321366Month[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225761&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  18.2138 +  0.00467834Connected[t] +  0.0119577Separate[t] +  0.0920534Learning[t] -0.0203603Software[t] -0.36232Depression[t] +  0.0259464Sport1[t] -0.321366Month[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225761&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225761&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] = + 18.2138 + 0.00467834Connected[t] + 0.0119577Separate[t] + 0.0920534Learning[t] -0.0203603Software[t] -0.36232Depression[t] + 0.0259464Sport1[t] -0.321366Month[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)18.21382.636256.9093.85665e-111.92833e-11
Connected0.004678340.03738760.12510.9005180.450259
Separate0.01195770.03808460.3140.7537950.376897
Learning0.09205340.0671291.3710.1714850.0857425
Software-0.02036030.0687847-0.2960.7674690.383735
Depression-0.362320.0393517-9.2071.24078e-176.20389e-18
Sport10.02594640.01278592.0290.04346320.0217316
Month-0.3213660.171891-1.870.06268270.0313413

\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) & 18.2138 & 2.63625 & 6.909 & 3.85665e-11 & 1.92833e-11 \tabularnewline
Connected & 0.00467834 & 0.0373876 & 0.1251 & 0.900518 & 0.450259 \tabularnewline
Separate & 0.0119577 & 0.0380846 & 0.314 & 0.753795 & 0.376897 \tabularnewline
Learning & 0.0920534 & 0.067129 & 1.371 & 0.171485 & 0.0857425 \tabularnewline
Software & -0.0203603 & 0.0687847 & -0.296 & 0.767469 & 0.383735 \tabularnewline
Depression & -0.36232 & 0.0393517 & -9.207 & 1.24078e-17 & 6.20389e-18 \tabularnewline
Sport1 & 0.0259464 & 0.0127859 & 2.029 & 0.0434632 & 0.0217316 \tabularnewline
Month & -0.321366 & 0.171891 & -1.87 & 0.0626827 & 0.0313413 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225761&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]18.2138[/C][C]2.63625[/C][C]6.909[/C][C]3.85665e-11[/C][C]1.92833e-11[/C][/ROW]
[ROW][C]Connected[/C][C]0.00467834[/C][C]0.0373876[/C][C]0.1251[/C][C]0.900518[/C][C]0.450259[/C][/ROW]
[ROW][C]Separate[/C][C]0.0119577[/C][C]0.0380846[/C][C]0.314[/C][C]0.753795[/C][C]0.376897[/C][/ROW]
[ROW][C]Learning[/C][C]0.0920534[/C][C]0.067129[/C][C]1.371[/C][C]0.171485[/C][C]0.0857425[/C][/ROW]
[ROW][C]Software[/C][C]-0.0203603[/C][C]0.0687847[/C][C]-0.296[/C][C]0.767469[/C][C]0.383735[/C][/ROW]
[ROW][C]Depression[/C][C]-0.36232[/C][C]0.0393517[/C][C]-9.207[/C][C]1.24078e-17[/C][C]6.20389e-18[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0259464[/C][C]0.0127859[/C][C]2.029[/C][C]0.0434632[/C][C]0.0217316[/C][/ROW]
[ROW][C]Month[/C][C]-0.321366[/C][C]0.171891[/C][C]-1.87[/C][C]0.0626827[/C][C]0.0313413[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225761&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225761&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)18.21382.636256.9093.85665e-111.92833e-11
Connected0.004678340.03738760.12510.9005180.450259
Separate0.01195770.03808460.3140.7537950.376897
Learning0.09205340.0671291.3710.1714850.0857425
Software-0.02036030.0687847-0.2960.7674690.383735
Depression-0.362320.0393517-9.2071.24078e-176.20389e-18
Sport10.02594640.01278592.0290.04346320.0217316
Month-0.3213660.171891-1.870.06268270.0313413






Multiple Linear Regression - Regression Statistics
Multiple R0.609579
R-squared0.371587
Adjusted R-squared0.354403
F-TEST (value)21.625
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.00764
Sum Squared Residuals1031.83

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.609579 \tabularnewline
R-squared & 0.371587 \tabularnewline
Adjusted R-squared & 0.354403 \tabularnewline
F-TEST (value) & 21.625 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 256 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.00764 \tabularnewline
Sum Squared Residuals & 1031.83 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225761&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.609579[/C][/ROW]
[ROW][C]R-squared[/C][C]0.371587[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.354403[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]21.625[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]256[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.00764[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1031.83[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225761&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225761&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 R0.609579
R-squared0.371587
Adjusted R-squared0.354403
F-TEST (value)21.625
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.00764
Sum Squared Residuals1031.83






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.94740.0526336
21815.30352.6965
31113.9639-2.96393
41214.5103-2.51031
51611.31024.68976
61814.50113.49894
71410.78343.21657
81415.097-1.09696
91515.2497-0.24967
101514.40830.591712
111715.56581.43424
121915.62753.37247
131013.4499-3.44991
141613.53582.46416
151815.81192.18807
161413.43470.565328
171413.92320.0767628
181715.84811.15185
191415.4287-1.42869
201613.85112.14886
211815.38512.6149
221113.7576-2.7576
231414.4959-0.495916
241213.5903-1.59033
251715.4531.54697
26916.011-7.01099
271615.16410.83593
281413.36960.63045
291514.05030.949668
301113.9885-2.98853
311615.78850.2115
321312.73850.261502
331715.16941.8306
341515.3455-0.34548
351414.0936-0.0935648
361615.58740.412569
37910.9533-1.95335
381514.42330.576725
391715.44581.55419
401315.3162-2.31617
411515.8056-0.805623
421613.79312.20694
431615.92010.0798948
441213.2417-1.2417
451514.7240.276008
461113.7355-2.73555
471515.4153-0.415299
481514.99970.000282479
491713.67843.32159
501314.8868-1.88678
511615.35830.641677
521413.5810.419016
531111.839-0.838963
541213.6793-1.6793
551214.2296-2.22961
561513.7981.20204
571614.34891.65111
581515.5698-0.569766
591215.3528-3.35277
601213.5425-1.54248
61810.8875-2.88752
621314.7844-1.78437
631114.8147-3.81474
641413.22650.773463
651513.77071.2293
661014.9967-4.9967
671112.512-1.51198
681214.4426-2.44256
691513.44561.55435
701513.55261.44736
711413.39430.605739
721612.63063.36938
731514.38890.611064
741515.2072-0.207168
751314.9045-1.90454
761212.1146-0.11459
771713.92993.0701
781312.40960.590389
791513.74191.25813
801314.8648-1.86482
811514.87770.122254
821515.4161-0.416129
831614.25051.74947
841514.23350.766486
851414.0821-0.0821449
861513.98561.01444
871414.232-0.232046
881312.71330.286739
89710.5308-3.53078
901713.68093.31906
911312.7770.223019
921514.17040.829643
931413.31390.686089
941313.9936-0.993592
951614.97251.02752
961212.7931-0.793076
971414.8624-0.862449
981714.92442.07556
991515.0142-0.0141619
1001715.14491.8551
1011212.9376-0.937582
1021615.00420.995771
1031114.3684-3.36841
1041513.12241.87762
105911.4025-2.40253
1061614.90341.09661
1071512.93192.06813
1081012.8022-2.80224
109109.163470.83653
1101513.90851.09149
1111113.2128-2.21278
1121315.2788-2.27879
1131412.06831.93169
1141814.10493.89511
1151615.55630.44368
1161412.98551.01451
1171413.79160.208408
1181415.0752-1.07516
1191413.73730.262733
1201212.536-0.535962
1211413.57560.42439
1221514.92030.0796859
1231515.8888-0.888775
1241514.56390.4361
1251314.7714-1.77143
1261716.1790.820977
1271715.31011.68992
1281914.89874.10133
1291513.59711.40289
1301314.6703-1.67034
131910.6764-1.67638
1321515.3143-0.31432
1331512.61752.38245
1341514.24420.755785
1351613.7662.23397
136119.475371.52463
1371413.29670.70333
1381111.9719-0.971945
1391514.18720.812782
1401313.8355-0.835461
1411514.64430.355747
1421613.88752.11253
1431414.702-0.70203
1441514.31910.680913
1451614.63931.36071
1461614.4891.51096
1471113.398-2.398
1481214.7095-2.70949
149911.57-2.56995
1501614.27981.72015
1511312.64550.354526
1521615.48450.515511
1531214.5012-2.50119
154911.9379-2.9379
1551311.78491.21511
1561312.7770.223019
1571413.38460.615398
1581914.89874.10133
1591315.7093-2.70933
1601212.2037-0.203701
1611312.61660.38336
162109.125830.874172
1631413.10560.894393
1641611.41224.58781
1651011.8277-1.82773
166118.975152.02485
1671413.95450.0455415
1681212.7151-0.715137
169912.5751-3.57505
170911.8483-2.84835
1711110.4060.593982
1721614.03841.96157
173913.8661-4.86609
1741311.17071.82929
1751613.20032.79973
1761315.1667-2.16674
177912.1554-3.15544
1781211.36780.632239
1791614.39481.60519
1801113.0679-2.0679
1811413.92180.0782458
1821314.5692-1.56917
1831514.52860.471416
1841414.8282-0.828154
1851613.93232.06771
1861311.57531.4247
1871413.44220.557779
1881514.10350.896499
1891312.34320.656759
1901110.14370.85628
1911112.5792-1.57915
1921414.8861-0.886136
1931512.62212.37789
1941112.3454-1.34536
1951512.99982.00015
1961213.9111-1.91112
1971411.66382.33621
1981413.32660.673372
199811.0578-3.05783
2001313.6993-0.699267
201912.0372-3.03721
2021513.67741.32264
2031713.99833.0017
2041312.40940.590607
2051514.34020.659773
2061513.6351.36501
2071414.3914-0.391413
2081612.41593.5841
2091312.79450.205483
2101614.24131.75874
211911.5939-2.59385
2121614.4511.54901
2131112.1872-1.18721
2141013.7593-3.75926
2151112.0685-1.0685
2161513.17021.82982
2171714.81252.18749
2181414.1586-0.158614
21989.91118-1.91118
2201513.50511.49489
2211113.8135-2.81354
2221613.52922.47081
2231012.0609-2.06095
2241514.73510.264925
22599.65897-0.658974
2261614.27381.72619
2271913.70715.29285
2281213.632-1.63198
22989.44085-1.44085
2301113.2838-2.28381
2311413.76540.234578
232911.9457-2.94574
2331514.82970.170287
2341312.34580.654226
2351614.82081.1792
2361112.7706-1.7706
2371211.26910.730892
2381312.70950.290451
2391014.2963-4.29625
2401113.5089-2.50888
2411214.7895-2.78954
242810.6328-2.63276
2431211.71180.288226
2441212.227-0.226961
2451513.45491.54515
2461110.71860.281409
2471312.6820.317973
248148.775385.22462
2491010.1671-0.167097
2501211.51560.484423
2511512.84422.15584
2521311.85821.14184
2531314.0929-1.09288
2541313.6634-0.663365
2551211.75240.247604
2561212.6008-0.600801
257910.8507-1.85071
258911.4192-2.4192
2591512.53472.46526
2601014.7633-4.76334
2611413.63340.366646
2621513.4771.52302
26379.80405-2.80405
2641413.82290.177135

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 13.9474 & 0.0526336 \tabularnewline
2 & 18 & 15.3035 & 2.6965 \tabularnewline
3 & 11 & 13.9639 & -2.96393 \tabularnewline
4 & 12 & 14.5103 & -2.51031 \tabularnewline
5 & 16 & 11.3102 & 4.68976 \tabularnewline
6 & 18 & 14.5011 & 3.49894 \tabularnewline
7 & 14 & 10.7834 & 3.21657 \tabularnewline
8 & 14 & 15.097 & -1.09696 \tabularnewline
9 & 15 & 15.2497 & -0.24967 \tabularnewline
10 & 15 & 14.4083 & 0.591712 \tabularnewline
11 & 17 & 15.5658 & 1.43424 \tabularnewline
12 & 19 & 15.6275 & 3.37247 \tabularnewline
13 & 10 & 13.4499 & -3.44991 \tabularnewline
14 & 16 & 13.5358 & 2.46416 \tabularnewline
15 & 18 & 15.8119 & 2.18807 \tabularnewline
16 & 14 & 13.4347 & 0.565328 \tabularnewline
17 & 14 & 13.9232 & 0.0767628 \tabularnewline
18 & 17 & 15.8481 & 1.15185 \tabularnewline
19 & 14 & 15.4287 & -1.42869 \tabularnewline
20 & 16 & 13.8511 & 2.14886 \tabularnewline
21 & 18 & 15.3851 & 2.6149 \tabularnewline
22 & 11 & 13.7576 & -2.7576 \tabularnewline
23 & 14 & 14.4959 & -0.495916 \tabularnewline
24 & 12 & 13.5903 & -1.59033 \tabularnewline
25 & 17 & 15.453 & 1.54697 \tabularnewline
26 & 9 & 16.011 & -7.01099 \tabularnewline
27 & 16 & 15.1641 & 0.83593 \tabularnewline
28 & 14 & 13.3696 & 0.63045 \tabularnewline
29 & 15 & 14.0503 & 0.949668 \tabularnewline
30 & 11 & 13.9885 & -2.98853 \tabularnewline
31 & 16 & 15.7885 & 0.2115 \tabularnewline
32 & 13 & 12.7385 & 0.261502 \tabularnewline
33 & 17 & 15.1694 & 1.8306 \tabularnewline
34 & 15 & 15.3455 & -0.34548 \tabularnewline
35 & 14 & 14.0936 & -0.0935648 \tabularnewline
36 & 16 & 15.5874 & 0.412569 \tabularnewline
37 & 9 & 10.9533 & -1.95335 \tabularnewline
38 & 15 & 14.4233 & 0.576725 \tabularnewline
39 & 17 & 15.4458 & 1.55419 \tabularnewline
40 & 13 & 15.3162 & -2.31617 \tabularnewline
41 & 15 & 15.8056 & -0.805623 \tabularnewline
42 & 16 & 13.7931 & 2.20694 \tabularnewline
43 & 16 & 15.9201 & 0.0798948 \tabularnewline
44 & 12 & 13.2417 & -1.2417 \tabularnewline
45 & 15 & 14.724 & 0.276008 \tabularnewline
46 & 11 & 13.7355 & -2.73555 \tabularnewline
47 & 15 & 15.4153 & -0.415299 \tabularnewline
48 & 15 & 14.9997 & 0.000282479 \tabularnewline
49 & 17 & 13.6784 & 3.32159 \tabularnewline
50 & 13 & 14.8868 & -1.88678 \tabularnewline
51 & 16 & 15.3583 & 0.641677 \tabularnewline
52 & 14 & 13.581 & 0.419016 \tabularnewline
53 & 11 & 11.839 & -0.838963 \tabularnewline
54 & 12 & 13.6793 & -1.6793 \tabularnewline
55 & 12 & 14.2296 & -2.22961 \tabularnewline
56 & 15 & 13.798 & 1.20204 \tabularnewline
57 & 16 & 14.3489 & 1.65111 \tabularnewline
58 & 15 & 15.5698 & -0.569766 \tabularnewline
59 & 12 & 15.3528 & -3.35277 \tabularnewline
60 & 12 & 13.5425 & -1.54248 \tabularnewline
61 & 8 & 10.8875 & -2.88752 \tabularnewline
62 & 13 & 14.7844 & -1.78437 \tabularnewline
63 & 11 & 14.8147 & -3.81474 \tabularnewline
64 & 14 & 13.2265 & 0.773463 \tabularnewline
65 & 15 & 13.7707 & 1.2293 \tabularnewline
66 & 10 & 14.9967 & -4.9967 \tabularnewline
67 & 11 & 12.512 & -1.51198 \tabularnewline
68 & 12 & 14.4426 & -2.44256 \tabularnewline
69 & 15 & 13.4456 & 1.55435 \tabularnewline
70 & 15 & 13.5526 & 1.44736 \tabularnewline
71 & 14 & 13.3943 & 0.605739 \tabularnewline
72 & 16 & 12.6306 & 3.36938 \tabularnewline
73 & 15 & 14.3889 & 0.611064 \tabularnewline
74 & 15 & 15.2072 & -0.207168 \tabularnewline
75 & 13 & 14.9045 & -1.90454 \tabularnewline
76 & 12 & 12.1146 & -0.11459 \tabularnewline
77 & 17 & 13.9299 & 3.0701 \tabularnewline
78 & 13 & 12.4096 & 0.590389 \tabularnewline
79 & 15 & 13.7419 & 1.25813 \tabularnewline
80 & 13 & 14.8648 & -1.86482 \tabularnewline
81 & 15 & 14.8777 & 0.122254 \tabularnewline
82 & 15 & 15.4161 & -0.416129 \tabularnewline
83 & 16 & 14.2505 & 1.74947 \tabularnewline
84 & 15 & 14.2335 & 0.766486 \tabularnewline
85 & 14 & 14.0821 & -0.0821449 \tabularnewline
86 & 15 & 13.9856 & 1.01444 \tabularnewline
87 & 14 & 14.232 & -0.232046 \tabularnewline
88 & 13 & 12.7133 & 0.286739 \tabularnewline
89 & 7 & 10.5308 & -3.53078 \tabularnewline
90 & 17 & 13.6809 & 3.31906 \tabularnewline
91 & 13 & 12.777 & 0.223019 \tabularnewline
92 & 15 & 14.1704 & 0.829643 \tabularnewline
93 & 14 & 13.3139 & 0.686089 \tabularnewline
94 & 13 & 13.9936 & -0.993592 \tabularnewline
95 & 16 & 14.9725 & 1.02752 \tabularnewline
96 & 12 & 12.7931 & -0.793076 \tabularnewline
97 & 14 & 14.8624 & -0.862449 \tabularnewline
98 & 17 & 14.9244 & 2.07556 \tabularnewline
99 & 15 & 15.0142 & -0.0141619 \tabularnewline
100 & 17 & 15.1449 & 1.8551 \tabularnewline
101 & 12 & 12.9376 & -0.937582 \tabularnewline
102 & 16 & 15.0042 & 0.995771 \tabularnewline
103 & 11 & 14.3684 & -3.36841 \tabularnewline
104 & 15 & 13.1224 & 1.87762 \tabularnewline
105 & 9 & 11.4025 & -2.40253 \tabularnewline
106 & 16 & 14.9034 & 1.09661 \tabularnewline
107 & 15 & 12.9319 & 2.06813 \tabularnewline
108 & 10 & 12.8022 & -2.80224 \tabularnewline
109 & 10 & 9.16347 & 0.83653 \tabularnewline
110 & 15 & 13.9085 & 1.09149 \tabularnewline
111 & 11 & 13.2128 & -2.21278 \tabularnewline
112 & 13 & 15.2788 & -2.27879 \tabularnewline
113 & 14 & 12.0683 & 1.93169 \tabularnewline
114 & 18 & 14.1049 & 3.89511 \tabularnewline
115 & 16 & 15.5563 & 0.44368 \tabularnewline
116 & 14 & 12.9855 & 1.01451 \tabularnewline
117 & 14 & 13.7916 & 0.208408 \tabularnewline
118 & 14 & 15.0752 & -1.07516 \tabularnewline
119 & 14 & 13.7373 & 0.262733 \tabularnewline
120 & 12 & 12.536 & -0.535962 \tabularnewline
121 & 14 & 13.5756 & 0.42439 \tabularnewline
122 & 15 & 14.9203 & 0.0796859 \tabularnewline
123 & 15 & 15.8888 & -0.888775 \tabularnewline
124 & 15 & 14.5639 & 0.4361 \tabularnewline
125 & 13 & 14.7714 & -1.77143 \tabularnewline
126 & 17 & 16.179 & 0.820977 \tabularnewline
127 & 17 & 15.3101 & 1.68992 \tabularnewline
128 & 19 & 14.8987 & 4.10133 \tabularnewline
129 & 15 & 13.5971 & 1.40289 \tabularnewline
130 & 13 & 14.6703 & -1.67034 \tabularnewline
131 & 9 & 10.6764 & -1.67638 \tabularnewline
132 & 15 & 15.3143 & -0.31432 \tabularnewline
133 & 15 & 12.6175 & 2.38245 \tabularnewline
134 & 15 & 14.2442 & 0.755785 \tabularnewline
135 & 16 & 13.766 & 2.23397 \tabularnewline
136 & 11 & 9.47537 & 1.52463 \tabularnewline
137 & 14 & 13.2967 & 0.70333 \tabularnewline
138 & 11 & 11.9719 & -0.971945 \tabularnewline
139 & 15 & 14.1872 & 0.812782 \tabularnewline
140 & 13 & 13.8355 & -0.835461 \tabularnewline
141 & 15 & 14.6443 & 0.355747 \tabularnewline
142 & 16 & 13.8875 & 2.11253 \tabularnewline
143 & 14 & 14.702 & -0.70203 \tabularnewline
144 & 15 & 14.3191 & 0.680913 \tabularnewline
145 & 16 & 14.6393 & 1.36071 \tabularnewline
146 & 16 & 14.489 & 1.51096 \tabularnewline
147 & 11 & 13.398 & -2.398 \tabularnewline
148 & 12 & 14.7095 & -2.70949 \tabularnewline
149 & 9 & 11.57 & -2.56995 \tabularnewline
150 & 16 & 14.2798 & 1.72015 \tabularnewline
151 & 13 & 12.6455 & 0.354526 \tabularnewline
152 & 16 & 15.4845 & 0.515511 \tabularnewline
153 & 12 & 14.5012 & -2.50119 \tabularnewline
154 & 9 & 11.9379 & -2.9379 \tabularnewline
155 & 13 & 11.7849 & 1.21511 \tabularnewline
156 & 13 & 12.777 & 0.223019 \tabularnewline
157 & 14 & 13.3846 & 0.615398 \tabularnewline
158 & 19 & 14.8987 & 4.10133 \tabularnewline
159 & 13 & 15.7093 & -2.70933 \tabularnewline
160 & 12 & 12.2037 & -0.203701 \tabularnewline
161 & 13 & 12.6166 & 0.38336 \tabularnewline
162 & 10 & 9.12583 & 0.874172 \tabularnewline
163 & 14 & 13.1056 & 0.894393 \tabularnewline
164 & 16 & 11.4122 & 4.58781 \tabularnewline
165 & 10 & 11.8277 & -1.82773 \tabularnewline
166 & 11 & 8.97515 & 2.02485 \tabularnewline
167 & 14 & 13.9545 & 0.0455415 \tabularnewline
168 & 12 & 12.7151 & -0.715137 \tabularnewline
169 & 9 & 12.5751 & -3.57505 \tabularnewline
170 & 9 & 11.8483 & -2.84835 \tabularnewline
171 & 11 & 10.406 & 0.593982 \tabularnewline
172 & 16 & 14.0384 & 1.96157 \tabularnewline
173 & 9 & 13.8661 & -4.86609 \tabularnewline
174 & 13 & 11.1707 & 1.82929 \tabularnewline
175 & 16 & 13.2003 & 2.79973 \tabularnewline
176 & 13 & 15.1667 & -2.16674 \tabularnewline
177 & 9 & 12.1554 & -3.15544 \tabularnewline
178 & 12 & 11.3678 & 0.632239 \tabularnewline
179 & 16 & 14.3948 & 1.60519 \tabularnewline
180 & 11 & 13.0679 & -2.0679 \tabularnewline
181 & 14 & 13.9218 & 0.0782458 \tabularnewline
182 & 13 & 14.5692 & -1.56917 \tabularnewline
183 & 15 & 14.5286 & 0.471416 \tabularnewline
184 & 14 & 14.8282 & -0.828154 \tabularnewline
185 & 16 & 13.9323 & 2.06771 \tabularnewline
186 & 13 & 11.5753 & 1.4247 \tabularnewline
187 & 14 & 13.4422 & 0.557779 \tabularnewline
188 & 15 & 14.1035 & 0.896499 \tabularnewline
189 & 13 & 12.3432 & 0.656759 \tabularnewline
190 & 11 & 10.1437 & 0.85628 \tabularnewline
191 & 11 & 12.5792 & -1.57915 \tabularnewline
192 & 14 & 14.8861 & -0.886136 \tabularnewline
193 & 15 & 12.6221 & 2.37789 \tabularnewline
194 & 11 & 12.3454 & -1.34536 \tabularnewline
195 & 15 & 12.9998 & 2.00015 \tabularnewline
196 & 12 & 13.9111 & -1.91112 \tabularnewline
197 & 14 & 11.6638 & 2.33621 \tabularnewline
198 & 14 & 13.3266 & 0.673372 \tabularnewline
199 & 8 & 11.0578 & -3.05783 \tabularnewline
200 & 13 & 13.6993 & -0.699267 \tabularnewline
201 & 9 & 12.0372 & -3.03721 \tabularnewline
202 & 15 & 13.6774 & 1.32264 \tabularnewline
203 & 17 & 13.9983 & 3.0017 \tabularnewline
204 & 13 & 12.4094 & 0.590607 \tabularnewline
205 & 15 & 14.3402 & 0.659773 \tabularnewline
206 & 15 & 13.635 & 1.36501 \tabularnewline
207 & 14 & 14.3914 & -0.391413 \tabularnewline
208 & 16 & 12.4159 & 3.5841 \tabularnewline
209 & 13 & 12.7945 & 0.205483 \tabularnewline
210 & 16 & 14.2413 & 1.75874 \tabularnewline
211 & 9 & 11.5939 & -2.59385 \tabularnewline
212 & 16 & 14.451 & 1.54901 \tabularnewline
213 & 11 & 12.1872 & -1.18721 \tabularnewline
214 & 10 & 13.7593 & -3.75926 \tabularnewline
215 & 11 & 12.0685 & -1.0685 \tabularnewline
216 & 15 & 13.1702 & 1.82982 \tabularnewline
217 & 17 & 14.8125 & 2.18749 \tabularnewline
218 & 14 & 14.1586 & -0.158614 \tabularnewline
219 & 8 & 9.91118 & -1.91118 \tabularnewline
220 & 15 & 13.5051 & 1.49489 \tabularnewline
221 & 11 & 13.8135 & -2.81354 \tabularnewline
222 & 16 & 13.5292 & 2.47081 \tabularnewline
223 & 10 & 12.0609 & -2.06095 \tabularnewline
224 & 15 & 14.7351 & 0.264925 \tabularnewline
225 & 9 & 9.65897 & -0.658974 \tabularnewline
226 & 16 & 14.2738 & 1.72619 \tabularnewline
227 & 19 & 13.7071 & 5.29285 \tabularnewline
228 & 12 & 13.632 & -1.63198 \tabularnewline
229 & 8 & 9.44085 & -1.44085 \tabularnewline
230 & 11 & 13.2838 & -2.28381 \tabularnewline
231 & 14 & 13.7654 & 0.234578 \tabularnewline
232 & 9 & 11.9457 & -2.94574 \tabularnewline
233 & 15 & 14.8297 & 0.170287 \tabularnewline
234 & 13 & 12.3458 & 0.654226 \tabularnewline
235 & 16 & 14.8208 & 1.1792 \tabularnewline
236 & 11 & 12.7706 & -1.7706 \tabularnewline
237 & 12 & 11.2691 & 0.730892 \tabularnewline
238 & 13 & 12.7095 & 0.290451 \tabularnewline
239 & 10 & 14.2963 & -4.29625 \tabularnewline
240 & 11 & 13.5089 & -2.50888 \tabularnewline
241 & 12 & 14.7895 & -2.78954 \tabularnewline
242 & 8 & 10.6328 & -2.63276 \tabularnewline
243 & 12 & 11.7118 & 0.288226 \tabularnewline
244 & 12 & 12.227 & -0.226961 \tabularnewline
245 & 15 & 13.4549 & 1.54515 \tabularnewline
246 & 11 & 10.7186 & 0.281409 \tabularnewline
247 & 13 & 12.682 & 0.317973 \tabularnewline
248 & 14 & 8.77538 & 5.22462 \tabularnewline
249 & 10 & 10.1671 & -0.167097 \tabularnewline
250 & 12 & 11.5156 & 0.484423 \tabularnewline
251 & 15 & 12.8442 & 2.15584 \tabularnewline
252 & 13 & 11.8582 & 1.14184 \tabularnewline
253 & 13 & 14.0929 & -1.09288 \tabularnewline
254 & 13 & 13.6634 & -0.663365 \tabularnewline
255 & 12 & 11.7524 & 0.247604 \tabularnewline
256 & 12 & 12.6008 & -0.600801 \tabularnewline
257 & 9 & 10.8507 & -1.85071 \tabularnewline
258 & 9 & 11.4192 & -2.4192 \tabularnewline
259 & 15 & 12.5347 & 2.46526 \tabularnewline
260 & 10 & 14.7633 & -4.76334 \tabularnewline
261 & 14 & 13.6334 & 0.366646 \tabularnewline
262 & 15 & 13.477 & 1.52302 \tabularnewline
263 & 7 & 9.80405 & -2.80405 \tabularnewline
264 & 14 & 13.8229 & 0.177135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225761&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]13.9474[/C][C]0.0526336[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.3035[/C][C]2.6965[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.9639[/C][C]-2.96393[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.5103[/C][C]-2.51031[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]11.3102[/C][C]4.68976[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.5011[/C][C]3.49894[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.7834[/C][C]3.21657[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]15.097[/C][C]-1.09696[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.2497[/C][C]-0.24967[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4083[/C][C]0.591712[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.5658[/C][C]1.43424[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.6275[/C][C]3.37247[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.4499[/C][C]-3.44991[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.5358[/C][C]2.46416[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.8119[/C][C]2.18807[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.4347[/C][C]0.565328[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.9232[/C][C]0.0767628[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.8481[/C][C]1.15185[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.4287[/C][C]-1.42869[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.8511[/C][C]2.14886[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.3851[/C][C]2.6149[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.7576[/C][C]-2.7576[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.4959[/C][C]-0.495916[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.5903[/C][C]-1.59033[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.453[/C][C]1.54697[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]16.011[/C][C]-7.01099[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.1641[/C][C]0.83593[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.3696[/C][C]0.63045[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]14.0503[/C][C]0.949668[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]13.9885[/C][C]-2.98853[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.7885[/C][C]0.2115[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.7385[/C][C]0.261502[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]15.1694[/C][C]1.8306[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.3455[/C][C]-0.34548[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14.0936[/C][C]-0.0935648[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.5874[/C][C]0.412569[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.9533[/C][C]-1.95335[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.4233[/C][C]0.576725[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.4458[/C][C]1.55419[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.3162[/C][C]-2.31617[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.8056[/C][C]-0.805623[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.7931[/C][C]2.20694[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.9201[/C][C]0.0798948[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.2417[/C][C]-1.2417[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.724[/C][C]0.276008[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.7355[/C][C]-2.73555[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.4153[/C][C]-0.415299[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.9997[/C][C]0.000282479[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.6784[/C][C]3.32159[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.8868[/C][C]-1.88678[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.3583[/C][C]0.641677[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.581[/C][C]0.419016[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.839[/C][C]-0.838963[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.6793[/C][C]-1.6793[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.2296[/C][C]-2.22961[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.798[/C][C]1.20204[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.3489[/C][C]1.65111[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.5698[/C][C]-0.569766[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.3528[/C][C]-3.35277[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.5425[/C][C]-1.54248[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.8875[/C][C]-2.88752[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.7844[/C][C]-1.78437[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.8147[/C][C]-3.81474[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.2265[/C][C]0.773463[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.7707[/C][C]1.2293[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]14.9967[/C][C]-4.9967[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.512[/C][C]-1.51198[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.4426[/C][C]-2.44256[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.4456[/C][C]1.55435[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.5526[/C][C]1.44736[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.3943[/C][C]0.605739[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.6306[/C][C]3.36938[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.3889[/C][C]0.611064[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.2072[/C][C]-0.207168[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.9045[/C][C]-1.90454[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.1146[/C][C]-0.11459[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]13.9299[/C][C]3.0701[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.4096[/C][C]0.590389[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.7419[/C][C]1.25813[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]14.8648[/C][C]-1.86482[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.8777[/C][C]0.122254[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.4161[/C][C]-0.416129[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.2505[/C][C]1.74947[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2335[/C][C]0.766486[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.0821[/C][C]-0.0821449[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.9856[/C][C]1.01444[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.232[/C][C]-0.232046[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.7133[/C][C]0.286739[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.5308[/C][C]-3.53078[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.6809[/C][C]3.31906[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.777[/C][C]0.223019[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.1704[/C][C]0.829643[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.3139[/C][C]0.686089[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.9936[/C][C]-0.993592[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.9725[/C][C]1.02752[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.7931[/C][C]-0.793076[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.8624[/C][C]-0.862449[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.9244[/C][C]2.07556[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]15.0142[/C][C]-0.0141619[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.1449[/C][C]1.8551[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.9376[/C][C]-0.937582[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]15.0042[/C][C]0.995771[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.3684[/C][C]-3.36841[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.1224[/C][C]1.87762[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.4025[/C][C]-2.40253[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.9034[/C][C]1.09661[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9319[/C][C]2.06813[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.8022[/C][C]-2.80224[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.16347[/C][C]0.83653[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.9085[/C][C]1.09149[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.2128[/C][C]-2.21278[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.2788[/C][C]-2.27879[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]12.0683[/C][C]1.93169[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.1049[/C][C]3.89511[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.5563[/C][C]0.44368[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]12.9855[/C][C]1.01451[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.7916[/C][C]0.208408[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.0752[/C][C]-1.07516[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.7373[/C][C]0.262733[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.536[/C][C]-0.535962[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.5756[/C][C]0.42439[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.9203[/C][C]0.0796859[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.8888[/C][C]-0.888775[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.5639[/C][C]0.4361[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.7714[/C][C]-1.77143[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.179[/C][C]0.820977[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.3101[/C][C]1.68992[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.8987[/C][C]4.10133[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5971[/C][C]1.40289[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.6703[/C][C]-1.67034[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.6764[/C][C]-1.67638[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.3143[/C][C]-0.31432[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.6175[/C][C]2.38245[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.2442[/C][C]0.755785[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.766[/C][C]2.23397[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.47537[/C][C]1.52463[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.2967[/C][C]0.70333[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]11.9719[/C][C]-0.971945[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.1872[/C][C]0.812782[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.8355[/C][C]-0.835461[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.6443[/C][C]0.355747[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.8875[/C][C]2.11253[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.702[/C][C]-0.70203[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.3191[/C][C]0.680913[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.6393[/C][C]1.36071[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.489[/C][C]1.51096[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.398[/C][C]-2.398[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.7095[/C][C]-2.70949[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.57[/C][C]-2.56995[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.2798[/C][C]1.72015[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.6455[/C][C]0.354526[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.4845[/C][C]0.515511[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.5012[/C][C]-2.50119[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.9379[/C][C]-2.9379[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.7849[/C][C]1.21511[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.777[/C][C]0.223019[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.3846[/C][C]0.615398[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.8987[/C][C]4.10133[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.7093[/C][C]-2.70933[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.2037[/C][C]-0.203701[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6166[/C][C]0.38336[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.12583[/C][C]0.874172[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.1056[/C][C]0.894393[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.4122[/C][C]4.58781[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.8277[/C][C]-1.82773[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]8.97515[/C][C]2.02485[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]13.9545[/C][C]0.0455415[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.7151[/C][C]-0.715137[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.5751[/C][C]-3.57505[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.8483[/C][C]-2.84835[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.406[/C][C]0.593982[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.0384[/C][C]1.96157[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]13.8661[/C][C]-4.86609[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.1707[/C][C]1.82929[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.2003[/C][C]2.79973[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.1667[/C][C]-2.16674[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.1554[/C][C]-3.15544[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.3678[/C][C]0.632239[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.3948[/C][C]1.60519[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.0679[/C][C]-2.0679[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]13.9218[/C][C]0.0782458[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.5692[/C][C]-1.56917[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.5286[/C][C]0.471416[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.8282[/C][C]-0.828154[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]13.9323[/C][C]2.06771[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.5753[/C][C]1.4247[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.4422[/C][C]0.557779[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.1035[/C][C]0.896499[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.3432[/C][C]0.656759[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.1437[/C][C]0.85628[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.5792[/C][C]-1.57915[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.8861[/C][C]-0.886136[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.6221[/C][C]2.37789[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.3454[/C][C]-1.34536[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]12.9998[/C][C]2.00015[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]13.9111[/C][C]-1.91112[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.6638[/C][C]2.33621[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.3266[/C][C]0.673372[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.0578[/C][C]-3.05783[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.6993[/C][C]-0.699267[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.0372[/C][C]-3.03721[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.6774[/C][C]1.32264[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]13.9983[/C][C]3.0017[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.4094[/C][C]0.590607[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.3402[/C][C]0.659773[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.635[/C][C]1.36501[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.3914[/C][C]-0.391413[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.4159[/C][C]3.5841[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.7945[/C][C]0.205483[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.2413[/C][C]1.75874[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.5939[/C][C]-2.59385[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.451[/C][C]1.54901[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.1872[/C][C]-1.18721[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.7593[/C][C]-3.75926[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.0685[/C][C]-1.0685[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.1702[/C][C]1.82982[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.8125[/C][C]2.18749[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.1586[/C][C]-0.158614[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.91118[/C][C]-1.91118[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.5051[/C][C]1.49489[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.8135[/C][C]-2.81354[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.5292[/C][C]2.47081[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.0609[/C][C]-2.06095[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.7351[/C][C]0.264925[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.65897[/C][C]-0.658974[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.2738[/C][C]1.72619[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]13.7071[/C][C]5.29285[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.632[/C][C]-1.63198[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.44085[/C][C]-1.44085[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.2838[/C][C]-2.28381[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.7654[/C][C]0.234578[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]11.9457[/C][C]-2.94574[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]14.8297[/C][C]0.170287[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.3458[/C][C]0.654226[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]14.8208[/C][C]1.1792[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.7706[/C][C]-1.7706[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.2691[/C][C]0.730892[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]12.7095[/C][C]0.290451[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.2963[/C][C]-4.29625[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.5089[/C][C]-2.50888[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.7895[/C][C]-2.78954[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.6328[/C][C]-2.63276[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.7118[/C][C]0.288226[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.227[/C][C]-0.226961[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.4549[/C][C]1.54515[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.7186[/C][C]0.281409[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.682[/C][C]0.317973[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.77538[/C][C]5.22462[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.1671[/C][C]-0.167097[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5156[/C][C]0.484423[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.8442[/C][C]2.15584[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.8582[/C][C]1.14184[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.0929[/C][C]-1.09288[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.6634[/C][C]-0.663365[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.7524[/C][C]0.247604[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.6008[/C][C]-0.600801[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.8507[/C][C]-1.85071[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.4192[/C][C]-2.4192[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.5347[/C][C]2.46526[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.7633[/C][C]-4.76334[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.6334[/C][C]0.366646[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.477[/C][C]1.52302[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.80405[/C][C]-2.80405[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.8229[/C][C]0.177135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225761&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225761&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
11413.94740.0526336
21815.30352.6965
31113.9639-2.96393
41214.5103-2.51031
51611.31024.68976
61814.50113.49894
71410.78343.21657
81415.097-1.09696
91515.2497-0.24967
101514.40830.591712
111715.56581.43424
121915.62753.37247
131013.4499-3.44991
141613.53582.46416
151815.81192.18807
161413.43470.565328
171413.92320.0767628
181715.84811.15185
191415.4287-1.42869
201613.85112.14886
211815.38512.6149
221113.7576-2.7576
231414.4959-0.495916
241213.5903-1.59033
251715.4531.54697
26916.011-7.01099
271615.16410.83593
281413.36960.63045
291514.05030.949668
301113.9885-2.98853
311615.78850.2115
321312.73850.261502
331715.16941.8306
341515.3455-0.34548
351414.0936-0.0935648
361615.58740.412569
37910.9533-1.95335
381514.42330.576725
391715.44581.55419
401315.3162-2.31617
411515.8056-0.805623
421613.79312.20694
431615.92010.0798948
441213.2417-1.2417
451514.7240.276008
461113.7355-2.73555
471515.4153-0.415299
481514.99970.000282479
491713.67843.32159
501314.8868-1.88678
511615.35830.641677
521413.5810.419016
531111.839-0.838963
541213.6793-1.6793
551214.2296-2.22961
561513.7981.20204
571614.34891.65111
581515.5698-0.569766
591215.3528-3.35277
601213.5425-1.54248
61810.8875-2.88752
621314.7844-1.78437
631114.8147-3.81474
641413.22650.773463
651513.77071.2293
661014.9967-4.9967
671112.512-1.51198
681214.4426-2.44256
691513.44561.55435
701513.55261.44736
711413.39430.605739
721612.63063.36938
731514.38890.611064
741515.2072-0.207168
751314.9045-1.90454
761212.1146-0.11459
771713.92993.0701
781312.40960.590389
791513.74191.25813
801314.8648-1.86482
811514.87770.122254
821515.4161-0.416129
831614.25051.74947
841514.23350.766486
851414.0821-0.0821449
861513.98561.01444
871414.232-0.232046
881312.71330.286739
89710.5308-3.53078
901713.68093.31906
911312.7770.223019
921514.17040.829643
931413.31390.686089
941313.9936-0.993592
951614.97251.02752
961212.7931-0.793076
971414.8624-0.862449
981714.92442.07556
991515.0142-0.0141619
1001715.14491.8551
1011212.9376-0.937582
1021615.00420.995771
1031114.3684-3.36841
1041513.12241.87762
105911.4025-2.40253
1061614.90341.09661
1071512.93192.06813
1081012.8022-2.80224
109109.163470.83653
1101513.90851.09149
1111113.2128-2.21278
1121315.2788-2.27879
1131412.06831.93169
1141814.10493.89511
1151615.55630.44368
1161412.98551.01451
1171413.79160.208408
1181415.0752-1.07516
1191413.73730.262733
1201212.536-0.535962
1211413.57560.42439
1221514.92030.0796859
1231515.8888-0.888775
1241514.56390.4361
1251314.7714-1.77143
1261716.1790.820977
1271715.31011.68992
1281914.89874.10133
1291513.59711.40289
1301314.6703-1.67034
131910.6764-1.67638
1321515.3143-0.31432
1331512.61752.38245
1341514.24420.755785
1351613.7662.23397
136119.475371.52463
1371413.29670.70333
1381111.9719-0.971945
1391514.18720.812782
1401313.8355-0.835461
1411514.64430.355747
1421613.88752.11253
1431414.702-0.70203
1441514.31910.680913
1451614.63931.36071
1461614.4891.51096
1471113.398-2.398
1481214.7095-2.70949
149911.57-2.56995
1501614.27981.72015
1511312.64550.354526
1521615.48450.515511
1531214.5012-2.50119
154911.9379-2.9379
1551311.78491.21511
1561312.7770.223019
1571413.38460.615398
1581914.89874.10133
1591315.7093-2.70933
1601212.2037-0.203701
1611312.61660.38336
162109.125830.874172
1631413.10560.894393
1641611.41224.58781
1651011.8277-1.82773
166118.975152.02485
1671413.95450.0455415
1681212.7151-0.715137
169912.5751-3.57505
170911.8483-2.84835
1711110.4060.593982
1721614.03841.96157
173913.8661-4.86609
1741311.17071.82929
1751613.20032.79973
1761315.1667-2.16674
177912.1554-3.15544
1781211.36780.632239
1791614.39481.60519
1801113.0679-2.0679
1811413.92180.0782458
1821314.5692-1.56917
1831514.52860.471416
1841414.8282-0.828154
1851613.93232.06771
1861311.57531.4247
1871413.44220.557779
1881514.10350.896499
1891312.34320.656759
1901110.14370.85628
1911112.5792-1.57915
1921414.8861-0.886136
1931512.62212.37789
1941112.3454-1.34536
1951512.99982.00015
1961213.9111-1.91112
1971411.66382.33621
1981413.32660.673372
199811.0578-3.05783
2001313.6993-0.699267
201912.0372-3.03721
2021513.67741.32264
2031713.99833.0017
2041312.40940.590607
2051514.34020.659773
2061513.6351.36501
2071414.3914-0.391413
2081612.41593.5841
2091312.79450.205483
2101614.24131.75874
211911.5939-2.59385
2121614.4511.54901
2131112.1872-1.18721
2141013.7593-3.75926
2151112.0685-1.0685
2161513.17021.82982
2171714.81252.18749
2181414.1586-0.158614
21989.91118-1.91118
2201513.50511.49489
2211113.8135-2.81354
2221613.52922.47081
2231012.0609-2.06095
2241514.73510.264925
22599.65897-0.658974
2261614.27381.72619
2271913.70715.29285
2281213.632-1.63198
22989.44085-1.44085
2301113.2838-2.28381
2311413.76540.234578
232911.9457-2.94574
2331514.82970.170287
2341312.34580.654226
2351614.82081.1792
2361112.7706-1.7706
2371211.26910.730892
2381312.70950.290451
2391014.2963-4.29625
2401113.5089-2.50888
2411214.7895-2.78954
242810.6328-2.63276
2431211.71180.288226
2441212.227-0.226961
2451513.45491.54515
2461110.71860.281409
2471312.6820.317973
248148.775385.22462
2491010.1671-0.167097
2501211.51560.484423
2511512.84422.15584
2521311.85821.14184
2531314.0929-1.09288
2541313.6634-0.663365
2551211.75240.247604
2561212.6008-0.600801
257910.8507-1.85071
258911.4192-2.4192
2591512.53472.46526
2601014.7633-4.76334
2611413.63340.366646
2621513.4771.52302
26379.80405-2.80405
2641413.82290.177135






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.05116410.1023280.948836
120.8975010.2049970.102499
130.9818150.03636990.0181849
140.981860.03627930.0181396
150.9864650.0270690.0135345
160.9760080.04798430.0239922
170.9665680.06686340.0334317
180.9522860.09542780.0477139
190.9347430.1305140.0652572
200.9290560.1418880.070944
210.940110.119780.05989
220.9653570.06928520.0346426
230.9503760.09924790.0496239
240.9370510.1258970.0629487
250.9165760.1668480.0834238
260.9989470.002106460.00105323
270.9983420.003316860.00165843
280.9973780.005244860.00262243
290.9959780.008044990.0040225
300.9978650.00427090.00213545
310.9967080.006583290.00329165
320.9950990.009801010.0049005
330.9939880.01202370.00601185
340.991290.01741950.00870976
350.9882240.02355210.0117761
360.9834870.03302680.0165134
370.9881040.02379280.0118964
380.9835550.03289020.0164451
390.9811970.03760640.0188032
400.9815450.03691040.0184552
410.97590.04820020.0241001
420.973570.05286030.0264302
430.9653710.06925830.0346291
440.9588220.08235560.0411778
450.9470170.1059650.0529826
460.9564930.08701380.0435069
470.9444180.1111650.0555825
480.9298030.1403940.0701968
490.9436360.1127280.0563642
500.9403540.1192920.0596459
510.9271480.1457030.0728516
520.910350.17930.0896499
530.8958520.2082960.104148
540.8890040.2219920.110996
550.8820320.2359360.117968
560.8627810.2744380.137219
570.8490230.3019550.150977
580.8221830.3556330.177817
590.8585460.2829090.141454
600.8551620.2896750.144838
610.8763610.2472780.123639
620.8751460.2497080.124854
630.9250840.1498320.0749159
640.9138030.1723950.0861973
650.9034280.1931430.0965716
660.9151670.1696660.0848331
670.913630.172740.0863701
680.9057880.1884240.0942119
690.9380620.1238770.0619384
700.9428810.1142390.0571195
710.9357140.1285720.064286
720.9581360.08372710.0418636
730.9494420.1011150.0505577
740.9382570.1234860.0617431
750.9315650.1368690.0684347
760.9175510.1648980.0824492
770.9341690.1316630.0658313
780.9218050.1563890.0781947
790.9147650.1704710.0852353
800.9078630.1842740.092137
810.8907820.2184360.109218
820.8722390.2555220.127761
830.8670720.2658560.132928
840.848190.3036210.15181
850.8246160.3507680.175384
860.8015940.3968120.198406
870.77430.45140.2257
880.7450220.5099560.254978
890.8156750.368650.184325
900.8461560.3076890.153844
910.8236130.3527730.176387
920.8003680.3992650.199632
930.7779630.4440730.222037
940.7553560.4892890.244644
950.72950.5409990.2705
960.7050030.5899950.294997
970.678870.642260.32113
980.6769020.6461950.323098
990.6432960.7134080.356704
1000.6330590.7338820.366941
1010.6098850.780230.390115
1020.5800970.8398060.419903
1030.6343110.7313770.365689
1040.6200130.7599750.379987
1050.6387450.7225090.361255
1060.6113860.7772280.388614
1070.6016230.7967550.398377
1080.639970.7200590.36003
1090.6098040.7803910.390196
1100.5821220.8357570.417878
1110.5896520.8206970.410348
1120.6202730.7594540.379727
1130.6191690.7616620.380831
1140.697470.605060.30253
1150.667050.66590.33295
1160.6410840.7178320.358916
1170.6093760.7812480.390624
1180.5865320.8269370.413468
1190.5514280.8971440.448572
1200.5197140.9605720.480286
1210.4896570.9793150.510343
1220.4566240.9132470.543376
1230.430260.8605210.56974
1240.3972380.7944750.602762
1250.3901370.7802730.609863
1260.359430.7188610.64057
1270.3428130.6856260.657187
1280.4410230.8820460.558977
1290.4204660.8409330.579534
1300.4109820.8219640.589018
1310.4005730.8011470.599427
1320.3708180.7416350.629182
1330.3863770.7727540.613623
1340.3572050.714410.642795
1350.3643260.7286520.635674
1360.3518470.7036930.648153
1370.3229740.6459480.677026
1380.2995350.5990710.700465
1390.2733990.5467990.726601
1400.2503550.500710.749645
1410.22350.4469990.7765
1420.2271350.454270.772865
1430.2029760.4059510.797024
1440.1825110.3650220.817489
1450.1691030.3382050.830897
1460.1614490.3228980.838551
1470.1683560.3367120.831644
1480.1861830.3723670.813817
1490.2069120.4138240.793088
1500.2032450.406490.796755
1510.180470.3609390.81953
1520.1604090.3208180.839591
1530.1731060.3462120.826894
1540.2125360.4250720.787464
1550.190810.381620.80919
1560.1712070.3424150.828793
1570.1493450.298690.850655
1580.222070.4441410.77793
1590.2496620.4993230.750338
1600.2238220.4476430.776178
1610.1972520.3945040.802748
1620.1747280.3494560.825272
1630.1540010.3080020.845999
1640.2541540.5083080.745846
1650.2512710.5025420.748729
1660.2485560.4971120.751444
1670.2208380.4416760.779162
1680.1998470.3996940.800153
1690.2549850.5099710.745015
1700.2809010.5618020.719099
1710.253680.507360.74632
1720.2507390.5014790.749261
1730.4092190.8184390.590781
1740.3973610.7947220.602639
1750.42250.8450010.5775
1760.431650.86330.56835
1770.4816730.9633460.518327
1780.4482020.8964050.551798
1790.4292620.8585240.570738
1800.4279350.855870.572065
1810.3906330.7812660.609367
1820.3796540.7593070.620346
1830.3440090.6880180.655991
1840.3159140.6318280.684086
1850.3329880.6659760.667012
1860.325190.650380.67481
1870.2917870.5835750.708213
1880.2644550.528910.735545
1890.234590.469180.76541
1900.2143570.4287150.785643
1910.2199530.4399050.780047
1920.2004630.4009260.799537
1930.2184830.4369660.781517
1940.2056380.4112760.794362
1950.2072110.4144220.792789
1960.2153920.4307840.784608
1970.2631650.526330.736835
1980.2453040.4906090.754696
1990.275580.5511610.72442
2000.2430970.4861950.756903
2010.2733070.5466150.726693
2020.2531270.5062540.746873
2030.3012210.6024430.698779
2040.2663580.5327160.733642
2050.2343730.4687450.765627
2060.2152890.4305790.784711
2070.1849720.3699430.815028
2080.2105220.4210450.789478
2090.1802210.3604430.819779
2100.1883830.3767650.811617
2110.2101260.4202520.789874
2120.2003740.4007480.799626
2130.1747090.3494180.825291
2140.2149930.4299860.785007
2150.1899620.3799230.810038
2160.1804710.3609420.819529
2170.2102670.4205340.789733
2180.1808710.3617420.819129
2190.1695030.3390070.830497
2200.1828370.3656730.817163
2210.192170.384340.80783
2220.1865630.3731260.813437
2230.1725050.3450110.827495
2240.1432440.2864890.856756
2250.1406820.2813640.859318
2260.1694680.3389360.830532
2270.3638090.7276180.636191
2280.3342220.6684430.665778
2290.3080590.6161180.691941
2300.2909520.5819030.709048
2310.2505370.5010730.749463
2320.2883410.5766820.711659
2330.2454140.4908280.754586
2340.2054490.4108990.794551
2350.2046040.4092080.795396
2360.1816330.3632660.818367
2370.1522190.3044380.847781
2380.1183150.2366290.881685
2390.2285840.4571690.771416
2400.2168470.4336950.783153
2410.187570.375140.81243
2420.3883690.7767390.611631
2430.3455890.6911780.654411
2440.2851920.5703850.714808
2450.4003450.800690.599655
2460.3173990.6347980.682601
2470.2404020.4808050.759598
2480.3869860.7739710.613014
2490.2899610.5799210.710039
2500.2030810.4061630.796919
2510.32110.6421990.6789
2520.8384290.3231410.161571
2530.6984720.6030560.301528

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.0511641 & 0.102328 & 0.948836 \tabularnewline
12 & 0.897501 & 0.204997 & 0.102499 \tabularnewline
13 & 0.981815 & 0.0363699 & 0.0181849 \tabularnewline
14 & 0.98186 & 0.0362793 & 0.0181396 \tabularnewline
15 & 0.986465 & 0.027069 & 0.0135345 \tabularnewline
16 & 0.976008 & 0.0479843 & 0.0239922 \tabularnewline
17 & 0.966568 & 0.0668634 & 0.0334317 \tabularnewline
18 & 0.952286 & 0.0954278 & 0.0477139 \tabularnewline
19 & 0.934743 & 0.130514 & 0.0652572 \tabularnewline
20 & 0.929056 & 0.141888 & 0.070944 \tabularnewline
21 & 0.94011 & 0.11978 & 0.05989 \tabularnewline
22 & 0.965357 & 0.0692852 & 0.0346426 \tabularnewline
23 & 0.950376 & 0.0992479 & 0.0496239 \tabularnewline
24 & 0.937051 & 0.125897 & 0.0629487 \tabularnewline
25 & 0.916576 & 0.166848 & 0.0834238 \tabularnewline
26 & 0.998947 & 0.00210646 & 0.00105323 \tabularnewline
27 & 0.998342 & 0.00331686 & 0.00165843 \tabularnewline
28 & 0.997378 & 0.00524486 & 0.00262243 \tabularnewline
29 & 0.995978 & 0.00804499 & 0.0040225 \tabularnewline
30 & 0.997865 & 0.0042709 & 0.00213545 \tabularnewline
31 & 0.996708 & 0.00658329 & 0.00329165 \tabularnewline
32 & 0.995099 & 0.00980101 & 0.0049005 \tabularnewline
33 & 0.993988 & 0.0120237 & 0.00601185 \tabularnewline
34 & 0.99129 & 0.0174195 & 0.00870976 \tabularnewline
35 & 0.988224 & 0.0235521 & 0.0117761 \tabularnewline
36 & 0.983487 & 0.0330268 & 0.0165134 \tabularnewline
37 & 0.988104 & 0.0237928 & 0.0118964 \tabularnewline
38 & 0.983555 & 0.0328902 & 0.0164451 \tabularnewline
39 & 0.981197 & 0.0376064 & 0.0188032 \tabularnewline
40 & 0.981545 & 0.0369104 & 0.0184552 \tabularnewline
41 & 0.9759 & 0.0482002 & 0.0241001 \tabularnewline
42 & 0.97357 & 0.0528603 & 0.0264302 \tabularnewline
43 & 0.965371 & 0.0692583 & 0.0346291 \tabularnewline
44 & 0.958822 & 0.0823556 & 0.0411778 \tabularnewline
45 & 0.947017 & 0.105965 & 0.0529826 \tabularnewline
46 & 0.956493 & 0.0870138 & 0.0435069 \tabularnewline
47 & 0.944418 & 0.111165 & 0.0555825 \tabularnewline
48 & 0.929803 & 0.140394 & 0.0701968 \tabularnewline
49 & 0.943636 & 0.112728 & 0.0563642 \tabularnewline
50 & 0.940354 & 0.119292 & 0.0596459 \tabularnewline
51 & 0.927148 & 0.145703 & 0.0728516 \tabularnewline
52 & 0.91035 & 0.1793 & 0.0896499 \tabularnewline
53 & 0.895852 & 0.208296 & 0.104148 \tabularnewline
54 & 0.889004 & 0.221992 & 0.110996 \tabularnewline
55 & 0.882032 & 0.235936 & 0.117968 \tabularnewline
56 & 0.862781 & 0.274438 & 0.137219 \tabularnewline
57 & 0.849023 & 0.301955 & 0.150977 \tabularnewline
58 & 0.822183 & 0.355633 & 0.177817 \tabularnewline
59 & 0.858546 & 0.282909 & 0.141454 \tabularnewline
60 & 0.855162 & 0.289675 & 0.144838 \tabularnewline
61 & 0.876361 & 0.247278 & 0.123639 \tabularnewline
62 & 0.875146 & 0.249708 & 0.124854 \tabularnewline
63 & 0.925084 & 0.149832 & 0.0749159 \tabularnewline
64 & 0.913803 & 0.172395 & 0.0861973 \tabularnewline
65 & 0.903428 & 0.193143 & 0.0965716 \tabularnewline
66 & 0.915167 & 0.169666 & 0.0848331 \tabularnewline
67 & 0.91363 & 0.17274 & 0.0863701 \tabularnewline
68 & 0.905788 & 0.188424 & 0.0942119 \tabularnewline
69 & 0.938062 & 0.123877 & 0.0619384 \tabularnewline
70 & 0.942881 & 0.114239 & 0.0571195 \tabularnewline
71 & 0.935714 & 0.128572 & 0.064286 \tabularnewline
72 & 0.958136 & 0.0837271 & 0.0418636 \tabularnewline
73 & 0.949442 & 0.101115 & 0.0505577 \tabularnewline
74 & 0.938257 & 0.123486 & 0.0617431 \tabularnewline
75 & 0.931565 & 0.136869 & 0.0684347 \tabularnewline
76 & 0.917551 & 0.164898 & 0.0824492 \tabularnewline
77 & 0.934169 & 0.131663 & 0.0658313 \tabularnewline
78 & 0.921805 & 0.156389 & 0.0781947 \tabularnewline
79 & 0.914765 & 0.170471 & 0.0852353 \tabularnewline
80 & 0.907863 & 0.184274 & 0.092137 \tabularnewline
81 & 0.890782 & 0.218436 & 0.109218 \tabularnewline
82 & 0.872239 & 0.255522 & 0.127761 \tabularnewline
83 & 0.867072 & 0.265856 & 0.132928 \tabularnewline
84 & 0.84819 & 0.303621 & 0.15181 \tabularnewline
85 & 0.824616 & 0.350768 & 0.175384 \tabularnewline
86 & 0.801594 & 0.396812 & 0.198406 \tabularnewline
87 & 0.7743 & 0.4514 & 0.2257 \tabularnewline
88 & 0.745022 & 0.509956 & 0.254978 \tabularnewline
89 & 0.815675 & 0.36865 & 0.184325 \tabularnewline
90 & 0.846156 & 0.307689 & 0.153844 \tabularnewline
91 & 0.823613 & 0.352773 & 0.176387 \tabularnewline
92 & 0.800368 & 0.399265 & 0.199632 \tabularnewline
93 & 0.777963 & 0.444073 & 0.222037 \tabularnewline
94 & 0.755356 & 0.489289 & 0.244644 \tabularnewline
95 & 0.7295 & 0.540999 & 0.2705 \tabularnewline
96 & 0.705003 & 0.589995 & 0.294997 \tabularnewline
97 & 0.67887 & 0.64226 & 0.32113 \tabularnewline
98 & 0.676902 & 0.646195 & 0.323098 \tabularnewline
99 & 0.643296 & 0.713408 & 0.356704 \tabularnewline
100 & 0.633059 & 0.733882 & 0.366941 \tabularnewline
101 & 0.609885 & 0.78023 & 0.390115 \tabularnewline
102 & 0.580097 & 0.839806 & 0.419903 \tabularnewline
103 & 0.634311 & 0.731377 & 0.365689 \tabularnewline
104 & 0.620013 & 0.759975 & 0.379987 \tabularnewline
105 & 0.638745 & 0.722509 & 0.361255 \tabularnewline
106 & 0.611386 & 0.777228 & 0.388614 \tabularnewline
107 & 0.601623 & 0.796755 & 0.398377 \tabularnewline
108 & 0.63997 & 0.720059 & 0.36003 \tabularnewline
109 & 0.609804 & 0.780391 & 0.390196 \tabularnewline
110 & 0.582122 & 0.835757 & 0.417878 \tabularnewline
111 & 0.589652 & 0.820697 & 0.410348 \tabularnewline
112 & 0.620273 & 0.759454 & 0.379727 \tabularnewline
113 & 0.619169 & 0.761662 & 0.380831 \tabularnewline
114 & 0.69747 & 0.60506 & 0.30253 \tabularnewline
115 & 0.66705 & 0.6659 & 0.33295 \tabularnewline
116 & 0.641084 & 0.717832 & 0.358916 \tabularnewline
117 & 0.609376 & 0.781248 & 0.390624 \tabularnewline
118 & 0.586532 & 0.826937 & 0.413468 \tabularnewline
119 & 0.551428 & 0.897144 & 0.448572 \tabularnewline
120 & 0.519714 & 0.960572 & 0.480286 \tabularnewline
121 & 0.489657 & 0.979315 & 0.510343 \tabularnewline
122 & 0.456624 & 0.913247 & 0.543376 \tabularnewline
123 & 0.43026 & 0.860521 & 0.56974 \tabularnewline
124 & 0.397238 & 0.794475 & 0.602762 \tabularnewline
125 & 0.390137 & 0.780273 & 0.609863 \tabularnewline
126 & 0.35943 & 0.718861 & 0.64057 \tabularnewline
127 & 0.342813 & 0.685626 & 0.657187 \tabularnewline
128 & 0.441023 & 0.882046 & 0.558977 \tabularnewline
129 & 0.420466 & 0.840933 & 0.579534 \tabularnewline
130 & 0.410982 & 0.821964 & 0.589018 \tabularnewline
131 & 0.400573 & 0.801147 & 0.599427 \tabularnewline
132 & 0.370818 & 0.741635 & 0.629182 \tabularnewline
133 & 0.386377 & 0.772754 & 0.613623 \tabularnewline
134 & 0.357205 & 0.71441 & 0.642795 \tabularnewline
135 & 0.364326 & 0.728652 & 0.635674 \tabularnewline
136 & 0.351847 & 0.703693 & 0.648153 \tabularnewline
137 & 0.322974 & 0.645948 & 0.677026 \tabularnewline
138 & 0.299535 & 0.599071 & 0.700465 \tabularnewline
139 & 0.273399 & 0.546799 & 0.726601 \tabularnewline
140 & 0.250355 & 0.50071 & 0.749645 \tabularnewline
141 & 0.2235 & 0.446999 & 0.7765 \tabularnewline
142 & 0.227135 & 0.45427 & 0.772865 \tabularnewline
143 & 0.202976 & 0.405951 & 0.797024 \tabularnewline
144 & 0.182511 & 0.365022 & 0.817489 \tabularnewline
145 & 0.169103 & 0.338205 & 0.830897 \tabularnewline
146 & 0.161449 & 0.322898 & 0.838551 \tabularnewline
147 & 0.168356 & 0.336712 & 0.831644 \tabularnewline
148 & 0.186183 & 0.372367 & 0.813817 \tabularnewline
149 & 0.206912 & 0.413824 & 0.793088 \tabularnewline
150 & 0.203245 & 0.40649 & 0.796755 \tabularnewline
151 & 0.18047 & 0.360939 & 0.81953 \tabularnewline
152 & 0.160409 & 0.320818 & 0.839591 \tabularnewline
153 & 0.173106 & 0.346212 & 0.826894 \tabularnewline
154 & 0.212536 & 0.425072 & 0.787464 \tabularnewline
155 & 0.19081 & 0.38162 & 0.80919 \tabularnewline
156 & 0.171207 & 0.342415 & 0.828793 \tabularnewline
157 & 0.149345 & 0.29869 & 0.850655 \tabularnewline
158 & 0.22207 & 0.444141 & 0.77793 \tabularnewline
159 & 0.249662 & 0.499323 & 0.750338 \tabularnewline
160 & 0.223822 & 0.447643 & 0.776178 \tabularnewline
161 & 0.197252 & 0.394504 & 0.802748 \tabularnewline
162 & 0.174728 & 0.349456 & 0.825272 \tabularnewline
163 & 0.154001 & 0.308002 & 0.845999 \tabularnewline
164 & 0.254154 & 0.508308 & 0.745846 \tabularnewline
165 & 0.251271 & 0.502542 & 0.748729 \tabularnewline
166 & 0.248556 & 0.497112 & 0.751444 \tabularnewline
167 & 0.220838 & 0.441676 & 0.779162 \tabularnewline
168 & 0.199847 & 0.399694 & 0.800153 \tabularnewline
169 & 0.254985 & 0.509971 & 0.745015 \tabularnewline
170 & 0.280901 & 0.561802 & 0.719099 \tabularnewline
171 & 0.25368 & 0.50736 & 0.74632 \tabularnewline
172 & 0.250739 & 0.501479 & 0.749261 \tabularnewline
173 & 0.409219 & 0.818439 & 0.590781 \tabularnewline
174 & 0.397361 & 0.794722 & 0.602639 \tabularnewline
175 & 0.4225 & 0.845001 & 0.5775 \tabularnewline
176 & 0.43165 & 0.8633 & 0.56835 \tabularnewline
177 & 0.481673 & 0.963346 & 0.518327 \tabularnewline
178 & 0.448202 & 0.896405 & 0.551798 \tabularnewline
179 & 0.429262 & 0.858524 & 0.570738 \tabularnewline
180 & 0.427935 & 0.85587 & 0.572065 \tabularnewline
181 & 0.390633 & 0.781266 & 0.609367 \tabularnewline
182 & 0.379654 & 0.759307 & 0.620346 \tabularnewline
183 & 0.344009 & 0.688018 & 0.655991 \tabularnewline
184 & 0.315914 & 0.631828 & 0.684086 \tabularnewline
185 & 0.332988 & 0.665976 & 0.667012 \tabularnewline
186 & 0.32519 & 0.65038 & 0.67481 \tabularnewline
187 & 0.291787 & 0.583575 & 0.708213 \tabularnewline
188 & 0.264455 & 0.52891 & 0.735545 \tabularnewline
189 & 0.23459 & 0.46918 & 0.76541 \tabularnewline
190 & 0.214357 & 0.428715 & 0.785643 \tabularnewline
191 & 0.219953 & 0.439905 & 0.780047 \tabularnewline
192 & 0.200463 & 0.400926 & 0.799537 \tabularnewline
193 & 0.218483 & 0.436966 & 0.781517 \tabularnewline
194 & 0.205638 & 0.411276 & 0.794362 \tabularnewline
195 & 0.207211 & 0.414422 & 0.792789 \tabularnewline
196 & 0.215392 & 0.430784 & 0.784608 \tabularnewline
197 & 0.263165 & 0.52633 & 0.736835 \tabularnewline
198 & 0.245304 & 0.490609 & 0.754696 \tabularnewline
199 & 0.27558 & 0.551161 & 0.72442 \tabularnewline
200 & 0.243097 & 0.486195 & 0.756903 \tabularnewline
201 & 0.273307 & 0.546615 & 0.726693 \tabularnewline
202 & 0.253127 & 0.506254 & 0.746873 \tabularnewline
203 & 0.301221 & 0.602443 & 0.698779 \tabularnewline
204 & 0.266358 & 0.532716 & 0.733642 \tabularnewline
205 & 0.234373 & 0.468745 & 0.765627 \tabularnewline
206 & 0.215289 & 0.430579 & 0.784711 \tabularnewline
207 & 0.184972 & 0.369943 & 0.815028 \tabularnewline
208 & 0.210522 & 0.421045 & 0.789478 \tabularnewline
209 & 0.180221 & 0.360443 & 0.819779 \tabularnewline
210 & 0.188383 & 0.376765 & 0.811617 \tabularnewline
211 & 0.210126 & 0.420252 & 0.789874 \tabularnewline
212 & 0.200374 & 0.400748 & 0.799626 \tabularnewline
213 & 0.174709 & 0.349418 & 0.825291 \tabularnewline
214 & 0.214993 & 0.429986 & 0.785007 \tabularnewline
215 & 0.189962 & 0.379923 & 0.810038 \tabularnewline
216 & 0.180471 & 0.360942 & 0.819529 \tabularnewline
217 & 0.210267 & 0.420534 & 0.789733 \tabularnewline
218 & 0.180871 & 0.361742 & 0.819129 \tabularnewline
219 & 0.169503 & 0.339007 & 0.830497 \tabularnewline
220 & 0.182837 & 0.365673 & 0.817163 \tabularnewline
221 & 0.19217 & 0.38434 & 0.80783 \tabularnewline
222 & 0.186563 & 0.373126 & 0.813437 \tabularnewline
223 & 0.172505 & 0.345011 & 0.827495 \tabularnewline
224 & 0.143244 & 0.286489 & 0.856756 \tabularnewline
225 & 0.140682 & 0.281364 & 0.859318 \tabularnewline
226 & 0.169468 & 0.338936 & 0.830532 \tabularnewline
227 & 0.363809 & 0.727618 & 0.636191 \tabularnewline
228 & 0.334222 & 0.668443 & 0.665778 \tabularnewline
229 & 0.308059 & 0.616118 & 0.691941 \tabularnewline
230 & 0.290952 & 0.581903 & 0.709048 \tabularnewline
231 & 0.250537 & 0.501073 & 0.749463 \tabularnewline
232 & 0.288341 & 0.576682 & 0.711659 \tabularnewline
233 & 0.245414 & 0.490828 & 0.754586 \tabularnewline
234 & 0.205449 & 0.410899 & 0.794551 \tabularnewline
235 & 0.204604 & 0.409208 & 0.795396 \tabularnewline
236 & 0.181633 & 0.363266 & 0.818367 \tabularnewline
237 & 0.152219 & 0.304438 & 0.847781 \tabularnewline
238 & 0.118315 & 0.236629 & 0.881685 \tabularnewline
239 & 0.228584 & 0.457169 & 0.771416 \tabularnewline
240 & 0.216847 & 0.433695 & 0.783153 \tabularnewline
241 & 0.18757 & 0.37514 & 0.81243 \tabularnewline
242 & 0.388369 & 0.776739 & 0.611631 \tabularnewline
243 & 0.345589 & 0.691178 & 0.654411 \tabularnewline
244 & 0.285192 & 0.570385 & 0.714808 \tabularnewline
245 & 0.400345 & 0.80069 & 0.599655 \tabularnewline
246 & 0.317399 & 0.634798 & 0.682601 \tabularnewline
247 & 0.240402 & 0.480805 & 0.759598 \tabularnewline
248 & 0.386986 & 0.773971 & 0.613014 \tabularnewline
249 & 0.289961 & 0.579921 & 0.710039 \tabularnewline
250 & 0.203081 & 0.406163 & 0.796919 \tabularnewline
251 & 0.3211 & 0.642199 & 0.6789 \tabularnewline
252 & 0.838429 & 0.323141 & 0.161571 \tabularnewline
253 & 0.698472 & 0.603056 & 0.301528 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225761&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.0511641[/C][C]0.102328[/C][C]0.948836[/C][/ROW]
[ROW][C]12[/C][C]0.897501[/C][C]0.204997[/C][C]0.102499[/C][/ROW]
[ROW][C]13[/C][C]0.981815[/C][C]0.0363699[/C][C]0.0181849[/C][/ROW]
[ROW][C]14[/C][C]0.98186[/C][C]0.0362793[/C][C]0.0181396[/C][/ROW]
[ROW][C]15[/C][C]0.986465[/C][C]0.027069[/C][C]0.0135345[/C][/ROW]
[ROW][C]16[/C][C]0.976008[/C][C]0.0479843[/C][C]0.0239922[/C][/ROW]
[ROW][C]17[/C][C]0.966568[/C][C]0.0668634[/C][C]0.0334317[/C][/ROW]
[ROW][C]18[/C][C]0.952286[/C][C]0.0954278[/C][C]0.0477139[/C][/ROW]
[ROW][C]19[/C][C]0.934743[/C][C]0.130514[/C][C]0.0652572[/C][/ROW]
[ROW][C]20[/C][C]0.929056[/C][C]0.141888[/C][C]0.070944[/C][/ROW]
[ROW][C]21[/C][C]0.94011[/C][C]0.11978[/C][C]0.05989[/C][/ROW]
[ROW][C]22[/C][C]0.965357[/C][C]0.0692852[/C][C]0.0346426[/C][/ROW]
[ROW][C]23[/C][C]0.950376[/C][C]0.0992479[/C][C]0.0496239[/C][/ROW]
[ROW][C]24[/C][C]0.937051[/C][C]0.125897[/C][C]0.0629487[/C][/ROW]
[ROW][C]25[/C][C]0.916576[/C][C]0.166848[/C][C]0.0834238[/C][/ROW]
[ROW][C]26[/C][C]0.998947[/C][C]0.00210646[/C][C]0.00105323[/C][/ROW]
[ROW][C]27[/C][C]0.998342[/C][C]0.00331686[/C][C]0.00165843[/C][/ROW]
[ROW][C]28[/C][C]0.997378[/C][C]0.00524486[/C][C]0.00262243[/C][/ROW]
[ROW][C]29[/C][C]0.995978[/C][C]0.00804499[/C][C]0.0040225[/C][/ROW]
[ROW][C]30[/C][C]0.997865[/C][C]0.0042709[/C][C]0.00213545[/C][/ROW]
[ROW][C]31[/C][C]0.996708[/C][C]0.00658329[/C][C]0.00329165[/C][/ROW]
[ROW][C]32[/C][C]0.995099[/C][C]0.00980101[/C][C]0.0049005[/C][/ROW]
[ROW][C]33[/C][C]0.993988[/C][C]0.0120237[/C][C]0.00601185[/C][/ROW]
[ROW][C]34[/C][C]0.99129[/C][C]0.0174195[/C][C]0.00870976[/C][/ROW]
[ROW][C]35[/C][C]0.988224[/C][C]0.0235521[/C][C]0.0117761[/C][/ROW]
[ROW][C]36[/C][C]0.983487[/C][C]0.0330268[/C][C]0.0165134[/C][/ROW]
[ROW][C]37[/C][C]0.988104[/C][C]0.0237928[/C][C]0.0118964[/C][/ROW]
[ROW][C]38[/C][C]0.983555[/C][C]0.0328902[/C][C]0.0164451[/C][/ROW]
[ROW][C]39[/C][C]0.981197[/C][C]0.0376064[/C][C]0.0188032[/C][/ROW]
[ROW][C]40[/C][C]0.981545[/C][C]0.0369104[/C][C]0.0184552[/C][/ROW]
[ROW][C]41[/C][C]0.9759[/C][C]0.0482002[/C][C]0.0241001[/C][/ROW]
[ROW][C]42[/C][C]0.97357[/C][C]0.0528603[/C][C]0.0264302[/C][/ROW]
[ROW][C]43[/C][C]0.965371[/C][C]0.0692583[/C][C]0.0346291[/C][/ROW]
[ROW][C]44[/C][C]0.958822[/C][C]0.0823556[/C][C]0.0411778[/C][/ROW]
[ROW][C]45[/C][C]0.947017[/C][C]0.105965[/C][C]0.0529826[/C][/ROW]
[ROW][C]46[/C][C]0.956493[/C][C]0.0870138[/C][C]0.0435069[/C][/ROW]
[ROW][C]47[/C][C]0.944418[/C][C]0.111165[/C][C]0.0555825[/C][/ROW]
[ROW][C]48[/C][C]0.929803[/C][C]0.140394[/C][C]0.0701968[/C][/ROW]
[ROW][C]49[/C][C]0.943636[/C][C]0.112728[/C][C]0.0563642[/C][/ROW]
[ROW][C]50[/C][C]0.940354[/C][C]0.119292[/C][C]0.0596459[/C][/ROW]
[ROW][C]51[/C][C]0.927148[/C][C]0.145703[/C][C]0.0728516[/C][/ROW]
[ROW][C]52[/C][C]0.91035[/C][C]0.1793[/C][C]0.0896499[/C][/ROW]
[ROW][C]53[/C][C]0.895852[/C][C]0.208296[/C][C]0.104148[/C][/ROW]
[ROW][C]54[/C][C]0.889004[/C][C]0.221992[/C][C]0.110996[/C][/ROW]
[ROW][C]55[/C][C]0.882032[/C][C]0.235936[/C][C]0.117968[/C][/ROW]
[ROW][C]56[/C][C]0.862781[/C][C]0.274438[/C][C]0.137219[/C][/ROW]
[ROW][C]57[/C][C]0.849023[/C][C]0.301955[/C][C]0.150977[/C][/ROW]
[ROW][C]58[/C][C]0.822183[/C][C]0.355633[/C][C]0.177817[/C][/ROW]
[ROW][C]59[/C][C]0.858546[/C][C]0.282909[/C][C]0.141454[/C][/ROW]
[ROW][C]60[/C][C]0.855162[/C][C]0.289675[/C][C]0.144838[/C][/ROW]
[ROW][C]61[/C][C]0.876361[/C][C]0.247278[/C][C]0.123639[/C][/ROW]
[ROW][C]62[/C][C]0.875146[/C][C]0.249708[/C][C]0.124854[/C][/ROW]
[ROW][C]63[/C][C]0.925084[/C][C]0.149832[/C][C]0.0749159[/C][/ROW]
[ROW][C]64[/C][C]0.913803[/C][C]0.172395[/C][C]0.0861973[/C][/ROW]
[ROW][C]65[/C][C]0.903428[/C][C]0.193143[/C][C]0.0965716[/C][/ROW]
[ROW][C]66[/C][C]0.915167[/C][C]0.169666[/C][C]0.0848331[/C][/ROW]
[ROW][C]67[/C][C]0.91363[/C][C]0.17274[/C][C]0.0863701[/C][/ROW]
[ROW][C]68[/C][C]0.905788[/C][C]0.188424[/C][C]0.0942119[/C][/ROW]
[ROW][C]69[/C][C]0.938062[/C][C]0.123877[/C][C]0.0619384[/C][/ROW]
[ROW][C]70[/C][C]0.942881[/C][C]0.114239[/C][C]0.0571195[/C][/ROW]
[ROW][C]71[/C][C]0.935714[/C][C]0.128572[/C][C]0.064286[/C][/ROW]
[ROW][C]72[/C][C]0.958136[/C][C]0.0837271[/C][C]0.0418636[/C][/ROW]
[ROW][C]73[/C][C]0.949442[/C][C]0.101115[/C][C]0.0505577[/C][/ROW]
[ROW][C]74[/C][C]0.938257[/C][C]0.123486[/C][C]0.0617431[/C][/ROW]
[ROW][C]75[/C][C]0.931565[/C][C]0.136869[/C][C]0.0684347[/C][/ROW]
[ROW][C]76[/C][C]0.917551[/C][C]0.164898[/C][C]0.0824492[/C][/ROW]
[ROW][C]77[/C][C]0.934169[/C][C]0.131663[/C][C]0.0658313[/C][/ROW]
[ROW][C]78[/C][C]0.921805[/C][C]0.156389[/C][C]0.0781947[/C][/ROW]
[ROW][C]79[/C][C]0.914765[/C][C]0.170471[/C][C]0.0852353[/C][/ROW]
[ROW][C]80[/C][C]0.907863[/C][C]0.184274[/C][C]0.092137[/C][/ROW]
[ROW][C]81[/C][C]0.890782[/C][C]0.218436[/C][C]0.109218[/C][/ROW]
[ROW][C]82[/C][C]0.872239[/C][C]0.255522[/C][C]0.127761[/C][/ROW]
[ROW][C]83[/C][C]0.867072[/C][C]0.265856[/C][C]0.132928[/C][/ROW]
[ROW][C]84[/C][C]0.84819[/C][C]0.303621[/C][C]0.15181[/C][/ROW]
[ROW][C]85[/C][C]0.824616[/C][C]0.350768[/C][C]0.175384[/C][/ROW]
[ROW][C]86[/C][C]0.801594[/C][C]0.396812[/C][C]0.198406[/C][/ROW]
[ROW][C]87[/C][C]0.7743[/C][C]0.4514[/C][C]0.2257[/C][/ROW]
[ROW][C]88[/C][C]0.745022[/C][C]0.509956[/C][C]0.254978[/C][/ROW]
[ROW][C]89[/C][C]0.815675[/C][C]0.36865[/C][C]0.184325[/C][/ROW]
[ROW][C]90[/C][C]0.846156[/C][C]0.307689[/C][C]0.153844[/C][/ROW]
[ROW][C]91[/C][C]0.823613[/C][C]0.352773[/C][C]0.176387[/C][/ROW]
[ROW][C]92[/C][C]0.800368[/C][C]0.399265[/C][C]0.199632[/C][/ROW]
[ROW][C]93[/C][C]0.777963[/C][C]0.444073[/C][C]0.222037[/C][/ROW]
[ROW][C]94[/C][C]0.755356[/C][C]0.489289[/C][C]0.244644[/C][/ROW]
[ROW][C]95[/C][C]0.7295[/C][C]0.540999[/C][C]0.2705[/C][/ROW]
[ROW][C]96[/C][C]0.705003[/C][C]0.589995[/C][C]0.294997[/C][/ROW]
[ROW][C]97[/C][C]0.67887[/C][C]0.64226[/C][C]0.32113[/C][/ROW]
[ROW][C]98[/C][C]0.676902[/C][C]0.646195[/C][C]0.323098[/C][/ROW]
[ROW][C]99[/C][C]0.643296[/C][C]0.713408[/C][C]0.356704[/C][/ROW]
[ROW][C]100[/C][C]0.633059[/C][C]0.733882[/C][C]0.366941[/C][/ROW]
[ROW][C]101[/C][C]0.609885[/C][C]0.78023[/C][C]0.390115[/C][/ROW]
[ROW][C]102[/C][C]0.580097[/C][C]0.839806[/C][C]0.419903[/C][/ROW]
[ROW][C]103[/C][C]0.634311[/C][C]0.731377[/C][C]0.365689[/C][/ROW]
[ROW][C]104[/C][C]0.620013[/C][C]0.759975[/C][C]0.379987[/C][/ROW]
[ROW][C]105[/C][C]0.638745[/C][C]0.722509[/C][C]0.361255[/C][/ROW]
[ROW][C]106[/C][C]0.611386[/C][C]0.777228[/C][C]0.388614[/C][/ROW]
[ROW][C]107[/C][C]0.601623[/C][C]0.796755[/C][C]0.398377[/C][/ROW]
[ROW][C]108[/C][C]0.63997[/C][C]0.720059[/C][C]0.36003[/C][/ROW]
[ROW][C]109[/C][C]0.609804[/C][C]0.780391[/C][C]0.390196[/C][/ROW]
[ROW][C]110[/C][C]0.582122[/C][C]0.835757[/C][C]0.417878[/C][/ROW]
[ROW][C]111[/C][C]0.589652[/C][C]0.820697[/C][C]0.410348[/C][/ROW]
[ROW][C]112[/C][C]0.620273[/C][C]0.759454[/C][C]0.379727[/C][/ROW]
[ROW][C]113[/C][C]0.619169[/C][C]0.761662[/C][C]0.380831[/C][/ROW]
[ROW][C]114[/C][C]0.69747[/C][C]0.60506[/C][C]0.30253[/C][/ROW]
[ROW][C]115[/C][C]0.66705[/C][C]0.6659[/C][C]0.33295[/C][/ROW]
[ROW][C]116[/C][C]0.641084[/C][C]0.717832[/C][C]0.358916[/C][/ROW]
[ROW][C]117[/C][C]0.609376[/C][C]0.781248[/C][C]0.390624[/C][/ROW]
[ROW][C]118[/C][C]0.586532[/C][C]0.826937[/C][C]0.413468[/C][/ROW]
[ROW][C]119[/C][C]0.551428[/C][C]0.897144[/C][C]0.448572[/C][/ROW]
[ROW][C]120[/C][C]0.519714[/C][C]0.960572[/C][C]0.480286[/C][/ROW]
[ROW][C]121[/C][C]0.489657[/C][C]0.979315[/C][C]0.510343[/C][/ROW]
[ROW][C]122[/C][C]0.456624[/C][C]0.913247[/C][C]0.543376[/C][/ROW]
[ROW][C]123[/C][C]0.43026[/C][C]0.860521[/C][C]0.56974[/C][/ROW]
[ROW][C]124[/C][C]0.397238[/C][C]0.794475[/C][C]0.602762[/C][/ROW]
[ROW][C]125[/C][C]0.390137[/C][C]0.780273[/C][C]0.609863[/C][/ROW]
[ROW][C]126[/C][C]0.35943[/C][C]0.718861[/C][C]0.64057[/C][/ROW]
[ROW][C]127[/C][C]0.342813[/C][C]0.685626[/C][C]0.657187[/C][/ROW]
[ROW][C]128[/C][C]0.441023[/C][C]0.882046[/C][C]0.558977[/C][/ROW]
[ROW][C]129[/C][C]0.420466[/C][C]0.840933[/C][C]0.579534[/C][/ROW]
[ROW][C]130[/C][C]0.410982[/C][C]0.821964[/C][C]0.589018[/C][/ROW]
[ROW][C]131[/C][C]0.400573[/C][C]0.801147[/C][C]0.599427[/C][/ROW]
[ROW][C]132[/C][C]0.370818[/C][C]0.741635[/C][C]0.629182[/C][/ROW]
[ROW][C]133[/C][C]0.386377[/C][C]0.772754[/C][C]0.613623[/C][/ROW]
[ROW][C]134[/C][C]0.357205[/C][C]0.71441[/C][C]0.642795[/C][/ROW]
[ROW][C]135[/C][C]0.364326[/C][C]0.728652[/C][C]0.635674[/C][/ROW]
[ROW][C]136[/C][C]0.351847[/C][C]0.703693[/C][C]0.648153[/C][/ROW]
[ROW][C]137[/C][C]0.322974[/C][C]0.645948[/C][C]0.677026[/C][/ROW]
[ROW][C]138[/C][C]0.299535[/C][C]0.599071[/C][C]0.700465[/C][/ROW]
[ROW][C]139[/C][C]0.273399[/C][C]0.546799[/C][C]0.726601[/C][/ROW]
[ROW][C]140[/C][C]0.250355[/C][C]0.50071[/C][C]0.749645[/C][/ROW]
[ROW][C]141[/C][C]0.2235[/C][C]0.446999[/C][C]0.7765[/C][/ROW]
[ROW][C]142[/C][C]0.227135[/C][C]0.45427[/C][C]0.772865[/C][/ROW]
[ROW][C]143[/C][C]0.202976[/C][C]0.405951[/C][C]0.797024[/C][/ROW]
[ROW][C]144[/C][C]0.182511[/C][C]0.365022[/C][C]0.817489[/C][/ROW]
[ROW][C]145[/C][C]0.169103[/C][C]0.338205[/C][C]0.830897[/C][/ROW]
[ROW][C]146[/C][C]0.161449[/C][C]0.322898[/C][C]0.838551[/C][/ROW]
[ROW][C]147[/C][C]0.168356[/C][C]0.336712[/C][C]0.831644[/C][/ROW]
[ROW][C]148[/C][C]0.186183[/C][C]0.372367[/C][C]0.813817[/C][/ROW]
[ROW][C]149[/C][C]0.206912[/C][C]0.413824[/C][C]0.793088[/C][/ROW]
[ROW][C]150[/C][C]0.203245[/C][C]0.40649[/C][C]0.796755[/C][/ROW]
[ROW][C]151[/C][C]0.18047[/C][C]0.360939[/C][C]0.81953[/C][/ROW]
[ROW][C]152[/C][C]0.160409[/C][C]0.320818[/C][C]0.839591[/C][/ROW]
[ROW][C]153[/C][C]0.173106[/C][C]0.346212[/C][C]0.826894[/C][/ROW]
[ROW][C]154[/C][C]0.212536[/C][C]0.425072[/C][C]0.787464[/C][/ROW]
[ROW][C]155[/C][C]0.19081[/C][C]0.38162[/C][C]0.80919[/C][/ROW]
[ROW][C]156[/C][C]0.171207[/C][C]0.342415[/C][C]0.828793[/C][/ROW]
[ROW][C]157[/C][C]0.149345[/C][C]0.29869[/C][C]0.850655[/C][/ROW]
[ROW][C]158[/C][C]0.22207[/C][C]0.444141[/C][C]0.77793[/C][/ROW]
[ROW][C]159[/C][C]0.249662[/C][C]0.499323[/C][C]0.750338[/C][/ROW]
[ROW][C]160[/C][C]0.223822[/C][C]0.447643[/C][C]0.776178[/C][/ROW]
[ROW][C]161[/C][C]0.197252[/C][C]0.394504[/C][C]0.802748[/C][/ROW]
[ROW][C]162[/C][C]0.174728[/C][C]0.349456[/C][C]0.825272[/C][/ROW]
[ROW][C]163[/C][C]0.154001[/C][C]0.308002[/C][C]0.845999[/C][/ROW]
[ROW][C]164[/C][C]0.254154[/C][C]0.508308[/C][C]0.745846[/C][/ROW]
[ROW][C]165[/C][C]0.251271[/C][C]0.502542[/C][C]0.748729[/C][/ROW]
[ROW][C]166[/C][C]0.248556[/C][C]0.497112[/C][C]0.751444[/C][/ROW]
[ROW][C]167[/C][C]0.220838[/C][C]0.441676[/C][C]0.779162[/C][/ROW]
[ROW][C]168[/C][C]0.199847[/C][C]0.399694[/C][C]0.800153[/C][/ROW]
[ROW][C]169[/C][C]0.254985[/C][C]0.509971[/C][C]0.745015[/C][/ROW]
[ROW][C]170[/C][C]0.280901[/C][C]0.561802[/C][C]0.719099[/C][/ROW]
[ROW][C]171[/C][C]0.25368[/C][C]0.50736[/C][C]0.74632[/C][/ROW]
[ROW][C]172[/C][C]0.250739[/C][C]0.501479[/C][C]0.749261[/C][/ROW]
[ROW][C]173[/C][C]0.409219[/C][C]0.818439[/C][C]0.590781[/C][/ROW]
[ROW][C]174[/C][C]0.397361[/C][C]0.794722[/C][C]0.602639[/C][/ROW]
[ROW][C]175[/C][C]0.4225[/C][C]0.845001[/C][C]0.5775[/C][/ROW]
[ROW][C]176[/C][C]0.43165[/C][C]0.8633[/C][C]0.56835[/C][/ROW]
[ROW][C]177[/C][C]0.481673[/C][C]0.963346[/C][C]0.518327[/C][/ROW]
[ROW][C]178[/C][C]0.448202[/C][C]0.896405[/C][C]0.551798[/C][/ROW]
[ROW][C]179[/C][C]0.429262[/C][C]0.858524[/C][C]0.570738[/C][/ROW]
[ROW][C]180[/C][C]0.427935[/C][C]0.85587[/C][C]0.572065[/C][/ROW]
[ROW][C]181[/C][C]0.390633[/C][C]0.781266[/C][C]0.609367[/C][/ROW]
[ROW][C]182[/C][C]0.379654[/C][C]0.759307[/C][C]0.620346[/C][/ROW]
[ROW][C]183[/C][C]0.344009[/C][C]0.688018[/C][C]0.655991[/C][/ROW]
[ROW][C]184[/C][C]0.315914[/C][C]0.631828[/C][C]0.684086[/C][/ROW]
[ROW][C]185[/C][C]0.332988[/C][C]0.665976[/C][C]0.667012[/C][/ROW]
[ROW][C]186[/C][C]0.32519[/C][C]0.65038[/C][C]0.67481[/C][/ROW]
[ROW][C]187[/C][C]0.291787[/C][C]0.583575[/C][C]0.708213[/C][/ROW]
[ROW][C]188[/C][C]0.264455[/C][C]0.52891[/C][C]0.735545[/C][/ROW]
[ROW][C]189[/C][C]0.23459[/C][C]0.46918[/C][C]0.76541[/C][/ROW]
[ROW][C]190[/C][C]0.214357[/C][C]0.428715[/C][C]0.785643[/C][/ROW]
[ROW][C]191[/C][C]0.219953[/C][C]0.439905[/C][C]0.780047[/C][/ROW]
[ROW][C]192[/C][C]0.200463[/C][C]0.400926[/C][C]0.799537[/C][/ROW]
[ROW][C]193[/C][C]0.218483[/C][C]0.436966[/C][C]0.781517[/C][/ROW]
[ROW][C]194[/C][C]0.205638[/C][C]0.411276[/C][C]0.794362[/C][/ROW]
[ROW][C]195[/C][C]0.207211[/C][C]0.414422[/C][C]0.792789[/C][/ROW]
[ROW][C]196[/C][C]0.215392[/C][C]0.430784[/C][C]0.784608[/C][/ROW]
[ROW][C]197[/C][C]0.263165[/C][C]0.52633[/C][C]0.736835[/C][/ROW]
[ROW][C]198[/C][C]0.245304[/C][C]0.490609[/C][C]0.754696[/C][/ROW]
[ROW][C]199[/C][C]0.27558[/C][C]0.551161[/C][C]0.72442[/C][/ROW]
[ROW][C]200[/C][C]0.243097[/C][C]0.486195[/C][C]0.756903[/C][/ROW]
[ROW][C]201[/C][C]0.273307[/C][C]0.546615[/C][C]0.726693[/C][/ROW]
[ROW][C]202[/C][C]0.253127[/C][C]0.506254[/C][C]0.746873[/C][/ROW]
[ROW][C]203[/C][C]0.301221[/C][C]0.602443[/C][C]0.698779[/C][/ROW]
[ROW][C]204[/C][C]0.266358[/C][C]0.532716[/C][C]0.733642[/C][/ROW]
[ROW][C]205[/C][C]0.234373[/C][C]0.468745[/C][C]0.765627[/C][/ROW]
[ROW][C]206[/C][C]0.215289[/C][C]0.430579[/C][C]0.784711[/C][/ROW]
[ROW][C]207[/C][C]0.184972[/C][C]0.369943[/C][C]0.815028[/C][/ROW]
[ROW][C]208[/C][C]0.210522[/C][C]0.421045[/C][C]0.789478[/C][/ROW]
[ROW][C]209[/C][C]0.180221[/C][C]0.360443[/C][C]0.819779[/C][/ROW]
[ROW][C]210[/C][C]0.188383[/C][C]0.376765[/C][C]0.811617[/C][/ROW]
[ROW][C]211[/C][C]0.210126[/C][C]0.420252[/C][C]0.789874[/C][/ROW]
[ROW][C]212[/C][C]0.200374[/C][C]0.400748[/C][C]0.799626[/C][/ROW]
[ROW][C]213[/C][C]0.174709[/C][C]0.349418[/C][C]0.825291[/C][/ROW]
[ROW][C]214[/C][C]0.214993[/C][C]0.429986[/C][C]0.785007[/C][/ROW]
[ROW][C]215[/C][C]0.189962[/C][C]0.379923[/C][C]0.810038[/C][/ROW]
[ROW][C]216[/C][C]0.180471[/C][C]0.360942[/C][C]0.819529[/C][/ROW]
[ROW][C]217[/C][C]0.210267[/C][C]0.420534[/C][C]0.789733[/C][/ROW]
[ROW][C]218[/C][C]0.180871[/C][C]0.361742[/C][C]0.819129[/C][/ROW]
[ROW][C]219[/C][C]0.169503[/C][C]0.339007[/C][C]0.830497[/C][/ROW]
[ROW][C]220[/C][C]0.182837[/C][C]0.365673[/C][C]0.817163[/C][/ROW]
[ROW][C]221[/C][C]0.19217[/C][C]0.38434[/C][C]0.80783[/C][/ROW]
[ROW][C]222[/C][C]0.186563[/C][C]0.373126[/C][C]0.813437[/C][/ROW]
[ROW][C]223[/C][C]0.172505[/C][C]0.345011[/C][C]0.827495[/C][/ROW]
[ROW][C]224[/C][C]0.143244[/C][C]0.286489[/C][C]0.856756[/C][/ROW]
[ROW][C]225[/C][C]0.140682[/C][C]0.281364[/C][C]0.859318[/C][/ROW]
[ROW][C]226[/C][C]0.169468[/C][C]0.338936[/C][C]0.830532[/C][/ROW]
[ROW][C]227[/C][C]0.363809[/C][C]0.727618[/C][C]0.636191[/C][/ROW]
[ROW][C]228[/C][C]0.334222[/C][C]0.668443[/C][C]0.665778[/C][/ROW]
[ROW][C]229[/C][C]0.308059[/C][C]0.616118[/C][C]0.691941[/C][/ROW]
[ROW][C]230[/C][C]0.290952[/C][C]0.581903[/C][C]0.709048[/C][/ROW]
[ROW][C]231[/C][C]0.250537[/C][C]0.501073[/C][C]0.749463[/C][/ROW]
[ROW][C]232[/C][C]0.288341[/C][C]0.576682[/C][C]0.711659[/C][/ROW]
[ROW][C]233[/C][C]0.245414[/C][C]0.490828[/C][C]0.754586[/C][/ROW]
[ROW][C]234[/C][C]0.205449[/C][C]0.410899[/C][C]0.794551[/C][/ROW]
[ROW][C]235[/C][C]0.204604[/C][C]0.409208[/C][C]0.795396[/C][/ROW]
[ROW][C]236[/C][C]0.181633[/C][C]0.363266[/C][C]0.818367[/C][/ROW]
[ROW][C]237[/C][C]0.152219[/C][C]0.304438[/C][C]0.847781[/C][/ROW]
[ROW][C]238[/C][C]0.118315[/C][C]0.236629[/C][C]0.881685[/C][/ROW]
[ROW][C]239[/C][C]0.228584[/C][C]0.457169[/C][C]0.771416[/C][/ROW]
[ROW][C]240[/C][C]0.216847[/C][C]0.433695[/C][C]0.783153[/C][/ROW]
[ROW][C]241[/C][C]0.18757[/C][C]0.37514[/C][C]0.81243[/C][/ROW]
[ROW][C]242[/C][C]0.388369[/C][C]0.776739[/C][C]0.611631[/C][/ROW]
[ROW][C]243[/C][C]0.345589[/C][C]0.691178[/C][C]0.654411[/C][/ROW]
[ROW][C]244[/C][C]0.285192[/C][C]0.570385[/C][C]0.714808[/C][/ROW]
[ROW][C]245[/C][C]0.400345[/C][C]0.80069[/C][C]0.599655[/C][/ROW]
[ROW][C]246[/C][C]0.317399[/C][C]0.634798[/C][C]0.682601[/C][/ROW]
[ROW][C]247[/C][C]0.240402[/C][C]0.480805[/C][C]0.759598[/C][/ROW]
[ROW][C]248[/C][C]0.386986[/C][C]0.773971[/C][C]0.613014[/C][/ROW]
[ROW][C]249[/C][C]0.289961[/C][C]0.579921[/C][C]0.710039[/C][/ROW]
[ROW][C]250[/C][C]0.203081[/C][C]0.406163[/C][C]0.796919[/C][/ROW]
[ROW][C]251[/C][C]0.3211[/C][C]0.642199[/C][C]0.6789[/C][/ROW]
[ROW][C]252[/C][C]0.838429[/C][C]0.323141[/C][C]0.161571[/C][/ROW]
[ROW][C]253[/C][C]0.698472[/C][C]0.603056[/C][C]0.301528[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225761&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225761&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.05116410.1023280.948836
120.8975010.2049970.102499
130.9818150.03636990.0181849
140.981860.03627930.0181396
150.9864650.0270690.0135345
160.9760080.04798430.0239922
170.9665680.06686340.0334317
180.9522860.09542780.0477139
190.9347430.1305140.0652572
200.9290560.1418880.070944
210.940110.119780.05989
220.9653570.06928520.0346426
230.9503760.09924790.0496239
240.9370510.1258970.0629487
250.9165760.1668480.0834238
260.9989470.002106460.00105323
270.9983420.003316860.00165843
280.9973780.005244860.00262243
290.9959780.008044990.0040225
300.9978650.00427090.00213545
310.9967080.006583290.00329165
320.9950990.009801010.0049005
330.9939880.01202370.00601185
340.991290.01741950.00870976
350.9882240.02355210.0117761
360.9834870.03302680.0165134
370.9881040.02379280.0118964
380.9835550.03289020.0164451
390.9811970.03760640.0188032
400.9815450.03691040.0184552
410.97590.04820020.0241001
420.973570.05286030.0264302
430.9653710.06925830.0346291
440.9588220.08235560.0411778
450.9470170.1059650.0529826
460.9564930.08701380.0435069
470.9444180.1111650.0555825
480.9298030.1403940.0701968
490.9436360.1127280.0563642
500.9403540.1192920.0596459
510.9271480.1457030.0728516
520.910350.17930.0896499
530.8958520.2082960.104148
540.8890040.2219920.110996
550.8820320.2359360.117968
560.8627810.2744380.137219
570.8490230.3019550.150977
580.8221830.3556330.177817
590.8585460.2829090.141454
600.8551620.2896750.144838
610.8763610.2472780.123639
620.8751460.2497080.124854
630.9250840.1498320.0749159
640.9138030.1723950.0861973
650.9034280.1931430.0965716
660.9151670.1696660.0848331
670.913630.172740.0863701
680.9057880.1884240.0942119
690.9380620.1238770.0619384
700.9428810.1142390.0571195
710.9357140.1285720.064286
720.9581360.08372710.0418636
730.9494420.1011150.0505577
740.9382570.1234860.0617431
750.9315650.1368690.0684347
760.9175510.1648980.0824492
770.9341690.1316630.0658313
780.9218050.1563890.0781947
790.9147650.1704710.0852353
800.9078630.1842740.092137
810.8907820.2184360.109218
820.8722390.2555220.127761
830.8670720.2658560.132928
840.848190.3036210.15181
850.8246160.3507680.175384
860.8015940.3968120.198406
870.77430.45140.2257
880.7450220.5099560.254978
890.8156750.368650.184325
900.8461560.3076890.153844
910.8236130.3527730.176387
920.8003680.3992650.199632
930.7779630.4440730.222037
940.7553560.4892890.244644
950.72950.5409990.2705
960.7050030.5899950.294997
970.678870.642260.32113
980.6769020.6461950.323098
990.6432960.7134080.356704
1000.6330590.7338820.366941
1010.6098850.780230.390115
1020.5800970.8398060.419903
1030.6343110.7313770.365689
1040.6200130.7599750.379987
1050.6387450.7225090.361255
1060.6113860.7772280.388614
1070.6016230.7967550.398377
1080.639970.7200590.36003
1090.6098040.7803910.390196
1100.5821220.8357570.417878
1110.5896520.8206970.410348
1120.6202730.7594540.379727
1130.6191690.7616620.380831
1140.697470.605060.30253
1150.667050.66590.33295
1160.6410840.7178320.358916
1170.6093760.7812480.390624
1180.5865320.8269370.413468
1190.5514280.8971440.448572
1200.5197140.9605720.480286
1210.4896570.9793150.510343
1220.4566240.9132470.543376
1230.430260.8605210.56974
1240.3972380.7944750.602762
1250.3901370.7802730.609863
1260.359430.7188610.64057
1270.3428130.6856260.657187
1280.4410230.8820460.558977
1290.4204660.8409330.579534
1300.4109820.8219640.589018
1310.4005730.8011470.599427
1320.3708180.7416350.629182
1330.3863770.7727540.613623
1340.3572050.714410.642795
1350.3643260.7286520.635674
1360.3518470.7036930.648153
1370.3229740.6459480.677026
1380.2995350.5990710.700465
1390.2733990.5467990.726601
1400.2503550.500710.749645
1410.22350.4469990.7765
1420.2271350.454270.772865
1430.2029760.4059510.797024
1440.1825110.3650220.817489
1450.1691030.3382050.830897
1460.1614490.3228980.838551
1470.1683560.3367120.831644
1480.1861830.3723670.813817
1490.2069120.4138240.793088
1500.2032450.406490.796755
1510.180470.3609390.81953
1520.1604090.3208180.839591
1530.1731060.3462120.826894
1540.2125360.4250720.787464
1550.190810.381620.80919
1560.1712070.3424150.828793
1570.1493450.298690.850655
1580.222070.4441410.77793
1590.2496620.4993230.750338
1600.2238220.4476430.776178
1610.1972520.3945040.802748
1620.1747280.3494560.825272
1630.1540010.3080020.845999
1640.2541540.5083080.745846
1650.2512710.5025420.748729
1660.2485560.4971120.751444
1670.2208380.4416760.779162
1680.1998470.3996940.800153
1690.2549850.5099710.745015
1700.2809010.5618020.719099
1710.253680.507360.74632
1720.2507390.5014790.749261
1730.4092190.8184390.590781
1740.3973610.7947220.602639
1750.42250.8450010.5775
1760.431650.86330.56835
1770.4816730.9633460.518327
1780.4482020.8964050.551798
1790.4292620.8585240.570738
1800.4279350.855870.572065
1810.3906330.7812660.609367
1820.3796540.7593070.620346
1830.3440090.6880180.655991
1840.3159140.6318280.684086
1850.3329880.6659760.667012
1860.325190.650380.67481
1870.2917870.5835750.708213
1880.2644550.528910.735545
1890.234590.469180.76541
1900.2143570.4287150.785643
1910.2199530.4399050.780047
1920.2004630.4009260.799537
1930.2184830.4369660.781517
1940.2056380.4112760.794362
1950.2072110.4144220.792789
1960.2153920.4307840.784608
1970.2631650.526330.736835
1980.2453040.4906090.754696
1990.275580.5511610.72442
2000.2430970.4861950.756903
2010.2733070.5466150.726693
2020.2531270.5062540.746873
2030.3012210.6024430.698779
2040.2663580.5327160.733642
2050.2343730.4687450.765627
2060.2152890.4305790.784711
2070.1849720.3699430.815028
2080.2105220.4210450.789478
2090.1802210.3604430.819779
2100.1883830.3767650.811617
2110.2101260.4202520.789874
2120.2003740.4007480.799626
2130.1747090.3494180.825291
2140.2149930.4299860.785007
2150.1899620.3799230.810038
2160.1804710.3609420.819529
2170.2102670.4205340.789733
2180.1808710.3617420.819129
2190.1695030.3390070.830497
2200.1828370.3656730.817163
2210.192170.384340.80783
2220.1865630.3731260.813437
2230.1725050.3450110.827495
2240.1432440.2864890.856756
2250.1406820.2813640.859318
2260.1694680.3389360.830532
2270.3638090.7276180.636191
2280.3342220.6684430.665778
2290.3080590.6161180.691941
2300.2909520.5819030.709048
2310.2505370.5010730.749463
2320.2883410.5766820.711659
2330.2454140.4908280.754586
2340.2054490.4108990.794551
2350.2046040.4092080.795396
2360.1816330.3632660.818367
2370.1522190.3044380.847781
2380.1183150.2366290.881685
2390.2285840.4571690.771416
2400.2168470.4336950.783153
2410.187570.375140.81243
2420.3883690.7767390.611631
2430.3455890.6911780.654411
2440.2851920.5703850.714808
2450.4003450.800690.599655
2460.3173990.6347980.682601
2470.2404020.4808050.759598
2480.3869860.7739710.613014
2490.2899610.5799210.710039
2500.2030810.4061630.796919
2510.32110.6421990.6789
2520.8384290.3231410.161571
2530.6984720.6030560.301528






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level70.0288066NOK
5% type I error level200.0823045NOK
10% type I error level290.119342NOK

\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 & 7 & 0.0288066 & NOK \tabularnewline
5% type I error level & 20 & 0.0823045 & NOK \tabularnewline
10% type I error level & 29 & 0.119342 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225761&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]7[/C][C]0.0288066[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]20[/C][C]0.0823045[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]29[/C][C]0.119342[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225761&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225761&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 level70.0288066NOK
5% type I error level200.0823045NOK
10% type I error level290.119342NOK


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 = No Linear Trend ;
Parameters (R input):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
par3 <- 'No Linear Trend'
par2 <- 'Include Monthly Dummies'
par1 <- '5'
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')
}