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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 computationWed, 20 Nov 2013 11:17:49 -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/20/t1384964297u4aftd5ykc5sp6m.htm/, Retrieved Wed, 01 May 2024 17:50:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226663, Retrieved Wed, 01 May 2024 17:50:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-11-17 09:20:01] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [] [2013-11-20 16:17:49] [a5501fab9c787febb2a952032c60b28f] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 14 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226663&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226663&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226663&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 24.5677 -0.0209019Connected[t] + 0.004683Separate[t] -0.0639853Learning[t] -0.010107Software[t] -0.686595Happiness[t] -0.0593705Sport1[t] + 0.401842Month[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Depression[t] =  +  24.5677 -0.0209019Connected[t] +  0.004683Separate[t] -0.0639853Learning[t] -0.010107Software[t] -0.686595Happiness[t] -0.0593705Sport1[t] +  0.401842Month[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226663&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Depression[t] =  +  24.5677 -0.0209019Connected[t] +  0.004683Separate[t] -0.0639853Learning[t] -0.010107Software[t] -0.686595Happiness[t] -0.0593705Sport1[t] +  0.401842Month[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226663&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226663&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
Depression[t] = + 24.5677 -0.0209019Connected[t] + 0.004683Separate[t] -0.0639853Learning[t] -0.010107Software[t] -0.686595Happiness[t] -0.0593705Sport1[t] + 0.401842Month[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)24.56773.64256.7451.0152e-105.07598e-11
Connected-0.02090190.0514523-0.40620.6849060.342453
Separate0.0046830.05243610.089310.9289060.464453
Learning-0.06398530.0926615-0.69050.4904890.245244
Software-0.0101070.0947023-0.10670.9150910.457546
Happiness-0.6865950.0745712-9.2071.24078e-176.20389e-18
Sport1-0.05937050.0173496-3.4220.0007234830.000361741
Month0.4018420.2369061.6960.09106260.0455313

\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) & 24.5677 & 3.6425 & 6.745 & 1.0152e-10 & 5.07598e-11 \tabularnewline
Connected & -0.0209019 & 0.0514523 & -0.4062 & 0.684906 & 0.342453 \tabularnewline
Separate & 0.004683 & 0.0524361 & 0.08931 & 0.928906 & 0.464453 \tabularnewline
Learning & -0.0639853 & 0.0926615 & -0.6905 & 0.490489 & 0.245244 \tabularnewline
Software & -0.010107 & 0.0947023 & -0.1067 & 0.915091 & 0.457546 \tabularnewline
Happiness & -0.686595 & 0.0745712 & -9.207 & 1.24078e-17 & 6.20389e-18 \tabularnewline
Sport1 & -0.0593705 & 0.0173496 & -3.422 & 0.000723483 & 0.000361741 \tabularnewline
Month & 0.401842 & 0.236906 & 1.696 & 0.0910626 & 0.0455313 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226663&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]24.5677[/C][C]3.6425[/C][C]6.745[/C][C]1.0152e-10[/C][C]5.07598e-11[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0209019[/C][C]0.0514523[/C][C]-0.4062[/C][C]0.684906[/C][C]0.342453[/C][/ROW]
[ROW][C]Separate[/C][C]0.004683[/C][C]0.0524361[/C][C]0.08931[/C][C]0.928906[/C][C]0.464453[/C][/ROW]
[ROW][C]Learning[/C][C]-0.0639853[/C][C]0.0926615[/C][C]-0.6905[/C][C]0.490489[/C][C]0.245244[/C][/ROW]
[ROW][C]Software[/C][C]-0.010107[/C][C]0.0947023[/C][C]-0.1067[/C][C]0.915091[/C][C]0.457546[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.686595[/C][C]0.0745712[/C][C]-9.207[/C][C]1.24078e-17[/C][C]6.20389e-18[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.0593705[/C][C]0.0173496[/C][C]-3.422[/C][C]0.000723483[/C][C]0.000361741[/C][/ROW]
[ROW][C]Month[/C][C]0.401842[/C][C]0.236906[/C][C]1.696[/C][C]0.0910626[/C][C]0.0455313[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226663&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226663&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)24.56773.64256.7451.0152e-105.07598e-11
Connected-0.02090190.0514523-0.40620.6849060.342453
Separate0.0046830.05243610.089310.9289060.464453
Learning-0.06398530.0926615-0.69050.4904890.245244
Software-0.0101070.0947023-0.10670.9150910.457546
Happiness-0.6865950.0745712-9.2071.24078e-176.20389e-18
Sport1-0.05937050.0173496-3.4220.0007234830.000361741
Month0.4018420.2369061.6960.09106260.0455313






Multiple Linear Regression - Regression Statistics
Multiple R0.618378
R-squared0.382391
Adjusted R-squared0.365504
F-TEST (value)22.6431
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.76369
Sum Squared Residuals1955.32

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.618378 \tabularnewline
R-squared & 0.382391 \tabularnewline
Adjusted R-squared & 0.365504 \tabularnewline
F-TEST (value) & 22.6431 \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 & 2.76369 \tabularnewline
Sum Squared Residuals & 1955.32 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226663&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.618378[/C][/ROW]
[ROW][C]R-squared[/C][C]0.382391[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.365504[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]22.6431[/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]2.76369[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1955.32[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226663&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226663&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 R0.618378
R-squared0.382391
Adjusted R-squared0.365504
F-TEST (value)22.6431
F-TEST (DF numerator)7
F-TEST (DF denominator)256
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.76369
Sum Squared Residuals1955.32






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.7932-1.79323
2119.097591.90241
31414.8828-0.882839
41214.4535-2.45351
52111.12219.87794
6129.666072.33393
72213.41838.58166
81112.179-1.17899
91011.8863-1.88633
101311.72711.27293
111010.048-0.0479953
12810.1947-2.19471
131515.5651-0.565125
141412.22061.77938
15108.904521.09548
161413.53310.46689
171412.45571.54427
18119.270291.72971
191012.8721-2.87214
201312.15060.849379
219.510.2579-0.757887
221414.9467-0.946741
231213.3816-1.38164
241414.8948-0.894751
25119.531981.46802
26915.3291-6.32906
271110.97320.0267623
281512.85772.14235
291411.57422.42578
301315.101-2.10096
31910.8653-1.8653
321514.78940.210603
331010.6718-0.671832
341111.2158-0.215825
351312.59130.408686
36811.7586-3.75856
372017.07282.92718
381212.0551-0.0550758
391010.4142-0.414224
401013.4602-3.46015
41911.7436-2.74362
421411.17282.8272
43811.9171-3.91706
441415.284-1.28402
451112.1288-1.12881
461315.16-2.15999
47912.3875-3.38749
481111.8311-0.831104
491510.40934.59067
501113.1443-2.1443
511011.2679-1.26795
521413.06890.931074
531815.4882.512
541414.5763-0.576337
551115.0594-4.05943
5614.511.80732.69267
571311.00441.99562
58912.3156-3.31558
591013.9354-3.93539
601514.09210.90794
612018.21041.78959
621212.907-0.906952
631214.1701-2.17011
641413.99370.00630734
651312.96880.0311589
661115.1931-4.19313
671715.23341.76664
681214.2494-2.24944
691313.0299-0.0299269
701412.48731.51268
711313.6496-0.649609
721512.91772.08235
731311.6571.34304
741012.2952-2.29516
751112.944-1.94403
761913.7445.25602
771311.00281.99715
781713.86343.13658
791312.32250.677471
80914.6624-5.66244
811111.9307-0.930738
82912.3686-3.36858
831211.56670.433306
841212.432-0.431959
851312.73290.267127
861312.23610.763949
871213.2017-1.20167
881514.85310.146934
892218.00783.99223
901311.24181.75816
911514.61240.387554
921312.03110.96891
931512.48662.51336
9412.513.492-0.992023
951111.0796-0.0795746
961614.48581.51417
971112.6418-1.64181
981110.34580.654167
991012.2779-2.27794
1001010.6109-0.610935
1011614.26861.73144
1021210.54361.45637
1031115.5065-4.50646
1041611.95494.04511
1051916.73032.26971
1061111.2491-0.249076
1071612.25253.74746
1081516.7907-1.79069
1092417.44856.55151
1101411.62792.37215
1111514.98150.0184884
1121112.76-1.76003
1131515.2604-0.260438
1141210.23221.76775
1151010.5881-0.588132
1161414.2382-0.23819
1171313.496-0.496007
118913.4084-4.40842
1191511.85973.14025
1201515.6815-0.681531
1211412.7851.21501
1221111.4385-0.438528
123812.0144-4.01439
1241112.2547-1.25472
1251113.3014-2.30136
12689.84453-1.84453
1271010.5846-0.584649
128119.159921.84008
1291312.55650.443474
1301113.806-2.80596
1312017.30192.69808
1321011.9483-1.94828
1331513.12531.87471
1341212.2813-0.281319
1351410.943.05997
1362316.42266.5774
1371413.61580.384232
1381616.5595-0.559544
1391113.0665-2.06649
1401214.285-2.285
1411013.467-3.46696
1421411.1092.89101
1431212.1655-0.165456
1441212.0405-0.0405106
1451110.9050.0949508
1461211.26290.737069
1471315.9344-2.93441
1481114.2255-3.22549
1491916.56832.43173
1501211.23190.768094
1511713.17443.82563
152911.7379-2.73789
1531214.439-2.439
1541916.29672.70331
1551813.76424.23578
1561514.61240.387554
1571413.48920.510779
158119.159921.84008
159912.9775-3.97755
1601814.02033.97969
1611614.10911.89089
1622416.82817.17188
1631413.19180.808223
1642011.26518.73489
1651816.25851.74151
1662317.14765.85242
1671213.2653-1.26528
1681415.1039-1.10394
1691616.4545-0.454459
1701816.93851.06153
1712016.72353.27648
1721212.0036-0.00355462
1731216.6158-4.61578
1741715.42371.57629
1751312.21730.782651
176913.8555-4.85545
1771617.3039-1.30394
1781815.30692.69306
1791012.525-2.525
1801415.5622-1.56225
1811114.4407-3.44073
182914.7289-5.72888
1831112.6864-1.68644
1841012.9005-2.90055
1851111.7566-0.756619
1861913.90485.09522
1871413.19010.809923
1881212.0153-0.0152652
1891415.6275-1.62754
1902116.55924.44079
1911317.662-4.66202
1921013.1709-3.17088
1931513.281.71996
1941616.0612-0.0612442
1951412.96251.03749
1961214.9164-2.91644
1971913.00525.99482
1981512.54892.45111
1991918.29230.707714
2001313.9521-0.952092
2011717.0805-0.0804628
2021213.2345-1.23449
2031111.5028-0.502801
2041415.4063-1.40634
2051112.8432-1.84322
2061312.68260.317378
2071212.6359-0.635938
2081513.20721.79282
2091414.5035-0.50349
2101211.39840.60162
2111717.5637-0.563698
2121111.4753-0.475321
2131814.7133.28696
2141315.9139-2.91394
2151715.74491.25508
2161313.3649-0.364947
2171110.54460.455395
2181212.7951-0.7951
2192218.37243.62759
2201412.16981.8302
2211215.3932-3.39317
2221212.9364-0.936439
2231716.22640.773598
224913.0575-4.05751
2252119.08771.91229
2261012.2988-2.29878
2271111.2417-0.241717
2281215.4912-3.49122
2292318.22594.77414
2301315.874-2.87397
2311213.6977-1.69774
2321617.5781-1.57809
233913.6515-4.65154
2341713.79193.20809
235912.2341-3.23411
2361415.8673-1.86731
2371715.28721.71276
2381315.5146-2.51462
2391116.2413-5.24134
2401215.8173-3.81729
2411014.2611-4.26108
2421918.90190.0980609
2431616.1811-0.181066
2441615.36090.639074
2451412.13161.86836
2462016.0483.95204
2471514.53340.466645
2482315.42997.57006
2492017.64982.35017
2501616.3982-0.398155
2511413.26980.730187
2521714.18092.81914
2531114.4252-3.42524
2541314.133-1.13295
2551715.22391.77606
2561515.2079-0.207937
2572116.65254.34749
2581817.65290.347081
2591513.15411.84589
260816.317-8.31696
2611214.0811-2.08114
2621213.294-1.29405
2632219.05882.94121
2641213.6579-1.65794

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 13.7932 & -1.79323 \tabularnewline
2 & 11 & 9.09759 & 1.90241 \tabularnewline
3 & 14 & 14.8828 & -0.882839 \tabularnewline
4 & 12 & 14.4535 & -2.45351 \tabularnewline
5 & 21 & 11.1221 & 9.87794 \tabularnewline
6 & 12 & 9.66607 & 2.33393 \tabularnewline
7 & 22 & 13.4183 & 8.58166 \tabularnewline
8 & 11 & 12.179 & -1.17899 \tabularnewline
9 & 10 & 11.8863 & -1.88633 \tabularnewline
10 & 13 & 11.7271 & 1.27293 \tabularnewline
11 & 10 & 10.048 & -0.0479953 \tabularnewline
12 & 8 & 10.1947 & -2.19471 \tabularnewline
13 & 15 & 15.5651 & -0.565125 \tabularnewline
14 & 14 & 12.2206 & 1.77938 \tabularnewline
15 & 10 & 8.90452 & 1.09548 \tabularnewline
16 & 14 & 13.5331 & 0.46689 \tabularnewline
17 & 14 & 12.4557 & 1.54427 \tabularnewline
18 & 11 & 9.27029 & 1.72971 \tabularnewline
19 & 10 & 12.8721 & -2.87214 \tabularnewline
20 & 13 & 12.1506 & 0.849379 \tabularnewline
21 & 9.5 & 10.2579 & -0.757887 \tabularnewline
22 & 14 & 14.9467 & -0.946741 \tabularnewline
23 & 12 & 13.3816 & -1.38164 \tabularnewline
24 & 14 & 14.8948 & -0.894751 \tabularnewline
25 & 11 & 9.53198 & 1.46802 \tabularnewline
26 & 9 & 15.3291 & -6.32906 \tabularnewline
27 & 11 & 10.9732 & 0.0267623 \tabularnewline
28 & 15 & 12.8577 & 2.14235 \tabularnewline
29 & 14 & 11.5742 & 2.42578 \tabularnewline
30 & 13 & 15.101 & -2.10096 \tabularnewline
31 & 9 & 10.8653 & -1.8653 \tabularnewline
32 & 15 & 14.7894 & 0.210603 \tabularnewline
33 & 10 & 10.6718 & -0.671832 \tabularnewline
34 & 11 & 11.2158 & -0.215825 \tabularnewline
35 & 13 & 12.5913 & 0.408686 \tabularnewline
36 & 8 & 11.7586 & -3.75856 \tabularnewline
37 & 20 & 17.0728 & 2.92718 \tabularnewline
38 & 12 & 12.0551 & -0.0550758 \tabularnewline
39 & 10 & 10.4142 & -0.414224 \tabularnewline
40 & 10 & 13.4602 & -3.46015 \tabularnewline
41 & 9 & 11.7436 & -2.74362 \tabularnewline
42 & 14 & 11.1728 & 2.8272 \tabularnewline
43 & 8 & 11.9171 & -3.91706 \tabularnewline
44 & 14 & 15.284 & -1.28402 \tabularnewline
45 & 11 & 12.1288 & -1.12881 \tabularnewline
46 & 13 & 15.16 & -2.15999 \tabularnewline
47 & 9 & 12.3875 & -3.38749 \tabularnewline
48 & 11 & 11.8311 & -0.831104 \tabularnewline
49 & 15 & 10.4093 & 4.59067 \tabularnewline
50 & 11 & 13.1443 & -2.1443 \tabularnewline
51 & 10 & 11.2679 & -1.26795 \tabularnewline
52 & 14 & 13.0689 & 0.931074 \tabularnewline
53 & 18 & 15.488 & 2.512 \tabularnewline
54 & 14 & 14.5763 & -0.576337 \tabularnewline
55 & 11 & 15.0594 & -4.05943 \tabularnewline
56 & 14.5 & 11.8073 & 2.69267 \tabularnewline
57 & 13 & 11.0044 & 1.99562 \tabularnewline
58 & 9 & 12.3156 & -3.31558 \tabularnewline
59 & 10 & 13.9354 & -3.93539 \tabularnewline
60 & 15 & 14.0921 & 0.90794 \tabularnewline
61 & 20 & 18.2104 & 1.78959 \tabularnewline
62 & 12 & 12.907 & -0.906952 \tabularnewline
63 & 12 & 14.1701 & -2.17011 \tabularnewline
64 & 14 & 13.9937 & 0.00630734 \tabularnewline
65 & 13 & 12.9688 & 0.0311589 \tabularnewline
66 & 11 & 15.1931 & -4.19313 \tabularnewline
67 & 17 & 15.2334 & 1.76664 \tabularnewline
68 & 12 & 14.2494 & -2.24944 \tabularnewline
69 & 13 & 13.0299 & -0.0299269 \tabularnewline
70 & 14 & 12.4873 & 1.51268 \tabularnewline
71 & 13 & 13.6496 & -0.649609 \tabularnewline
72 & 15 & 12.9177 & 2.08235 \tabularnewline
73 & 13 & 11.657 & 1.34304 \tabularnewline
74 & 10 & 12.2952 & -2.29516 \tabularnewline
75 & 11 & 12.944 & -1.94403 \tabularnewline
76 & 19 & 13.744 & 5.25602 \tabularnewline
77 & 13 & 11.0028 & 1.99715 \tabularnewline
78 & 17 & 13.8634 & 3.13658 \tabularnewline
79 & 13 & 12.3225 & 0.677471 \tabularnewline
80 & 9 & 14.6624 & -5.66244 \tabularnewline
81 & 11 & 11.9307 & -0.930738 \tabularnewline
82 & 9 & 12.3686 & -3.36858 \tabularnewline
83 & 12 & 11.5667 & 0.433306 \tabularnewline
84 & 12 & 12.432 & -0.431959 \tabularnewline
85 & 13 & 12.7329 & 0.267127 \tabularnewline
86 & 13 & 12.2361 & 0.763949 \tabularnewline
87 & 12 & 13.2017 & -1.20167 \tabularnewline
88 & 15 & 14.8531 & 0.146934 \tabularnewline
89 & 22 & 18.0078 & 3.99223 \tabularnewline
90 & 13 & 11.2418 & 1.75816 \tabularnewline
91 & 15 & 14.6124 & 0.387554 \tabularnewline
92 & 13 & 12.0311 & 0.96891 \tabularnewline
93 & 15 & 12.4866 & 2.51336 \tabularnewline
94 & 12.5 & 13.492 & -0.992023 \tabularnewline
95 & 11 & 11.0796 & -0.0795746 \tabularnewline
96 & 16 & 14.4858 & 1.51417 \tabularnewline
97 & 11 & 12.6418 & -1.64181 \tabularnewline
98 & 11 & 10.3458 & 0.654167 \tabularnewline
99 & 10 & 12.2779 & -2.27794 \tabularnewline
100 & 10 & 10.6109 & -0.610935 \tabularnewline
101 & 16 & 14.2686 & 1.73144 \tabularnewline
102 & 12 & 10.5436 & 1.45637 \tabularnewline
103 & 11 & 15.5065 & -4.50646 \tabularnewline
104 & 16 & 11.9549 & 4.04511 \tabularnewline
105 & 19 & 16.7303 & 2.26971 \tabularnewline
106 & 11 & 11.2491 & -0.249076 \tabularnewline
107 & 16 & 12.2525 & 3.74746 \tabularnewline
108 & 15 & 16.7907 & -1.79069 \tabularnewline
109 & 24 & 17.4485 & 6.55151 \tabularnewline
110 & 14 & 11.6279 & 2.37215 \tabularnewline
111 & 15 & 14.9815 & 0.0184884 \tabularnewline
112 & 11 & 12.76 & -1.76003 \tabularnewline
113 & 15 & 15.2604 & -0.260438 \tabularnewline
114 & 12 & 10.2322 & 1.76775 \tabularnewline
115 & 10 & 10.5881 & -0.588132 \tabularnewline
116 & 14 & 14.2382 & -0.23819 \tabularnewline
117 & 13 & 13.496 & -0.496007 \tabularnewline
118 & 9 & 13.4084 & -4.40842 \tabularnewline
119 & 15 & 11.8597 & 3.14025 \tabularnewline
120 & 15 & 15.6815 & -0.681531 \tabularnewline
121 & 14 & 12.785 & 1.21501 \tabularnewline
122 & 11 & 11.4385 & -0.438528 \tabularnewline
123 & 8 & 12.0144 & -4.01439 \tabularnewline
124 & 11 & 12.2547 & -1.25472 \tabularnewline
125 & 11 & 13.3014 & -2.30136 \tabularnewline
126 & 8 & 9.84453 & -1.84453 \tabularnewline
127 & 10 & 10.5846 & -0.584649 \tabularnewline
128 & 11 & 9.15992 & 1.84008 \tabularnewline
129 & 13 & 12.5565 & 0.443474 \tabularnewline
130 & 11 & 13.806 & -2.80596 \tabularnewline
131 & 20 & 17.3019 & 2.69808 \tabularnewline
132 & 10 & 11.9483 & -1.94828 \tabularnewline
133 & 15 & 13.1253 & 1.87471 \tabularnewline
134 & 12 & 12.2813 & -0.281319 \tabularnewline
135 & 14 & 10.94 & 3.05997 \tabularnewline
136 & 23 & 16.4226 & 6.5774 \tabularnewline
137 & 14 & 13.6158 & 0.384232 \tabularnewline
138 & 16 & 16.5595 & -0.559544 \tabularnewline
139 & 11 & 13.0665 & -2.06649 \tabularnewline
140 & 12 & 14.285 & -2.285 \tabularnewline
141 & 10 & 13.467 & -3.46696 \tabularnewline
142 & 14 & 11.109 & 2.89101 \tabularnewline
143 & 12 & 12.1655 & -0.165456 \tabularnewline
144 & 12 & 12.0405 & -0.0405106 \tabularnewline
145 & 11 & 10.905 & 0.0949508 \tabularnewline
146 & 12 & 11.2629 & 0.737069 \tabularnewline
147 & 13 & 15.9344 & -2.93441 \tabularnewline
148 & 11 & 14.2255 & -3.22549 \tabularnewline
149 & 19 & 16.5683 & 2.43173 \tabularnewline
150 & 12 & 11.2319 & 0.768094 \tabularnewline
151 & 17 & 13.1744 & 3.82563 \tabularnewline
152 & 9 & 11.7379 & -2.73789 \tabularnewline
153 & 12 & 14.439 & -2.439 \tabularnewline
154 & 19 & 16.2967 & 2.70331 \tabularnewline
155 & 18 & 13.7642 & 4.23578 \tabularnewline
156 & 15 & 14.6124 & 0.387554 \tabularnewline
157 & 14 & 13.4892 & 0.510779 \tabularnewline
158 & 11 & 9.15992 & 1.84008 \tabularnewline
159 & 9 & 12.9775 & -3.97755 \tabularnewline
160 & 18 & 14.0203 & 3.97969 \tabularnewline
161 & 16 & 14.1091 & 1.89089 \tabularnewline
162 & 24 & 16.8281 & 7.17188 \tabularnewline
163 & 14 & 13.1918 & 0.808223 \tabularnewline
164 & 20 & 11.2651 & 8.73489 \tabularnewline
165 & 18 & 16.2585 & 1.74151 \tabularnewline
166 & 23 & 17.1476 & 5.85242 \tabularnewline
167 & 12 & 13.2653 & -1.26528 \tabularnewline
168 & 14 & 15.1039 & -1.10394 \tabularnewline
169 & 16 & 16.4545 & -0.454459 \tabularnewline
170 & 18 & 16.9385 & 1.06153 \tabularnewline
171 & 20 & 16.7235 & 3.27648 \tabularnewline
172 & 12 & 12.0036 & -0.00355462 \tabularnewline
173 & 12 & 16.6158 & -4.61578 \tabularnewline
174 & 17 & 15.4237 & 1.57629 \tabularnewline
175 & 13 & 12.2173 & 0.782651 \tabularnewline
176 & 9 & 13.8555 & -4.85545 \tabularnewline
177 & 16 & 17.3039 & -1.30394 \tabularnewline
178 & 18 & 15.3069 & 2.69306 \tabularnewline
179 & 10 & 12.525 & -2.525 \tabularnewline
180 & 14 & 15.5622 & -1.56225 \tabularnewline
181 & 11 & 14.4407 & -3.44073 \tabularnewline
182 & 9 & 14.7289 & -5.72888 \tabularnewline
183 & 11 & 12.6864 & -1.68644 \tabularnewline
184 & 10 & 12.9005 & -2.90055 \tabularnewline
185 & 11 & 11.7566 & -0.756619 \tabularnewline
186 & 19 & 13.9048 & 5.09522 \tabularnewline
187 & 14 & 13.1901 & 0.809923 \tabularnewline
188 & 12 & 12.0153 & -0.0152652 \tabularnewline
189 & 14 & 15.6275 & -1.62754 \tabularnewline
190 & 21 & 16.5592 & 4.44079 \tabularnewline
191 & 13 & 17.662 & -4.66202 \tabularnewline
192 & 10 & 13.1709 & -3.17088 \tabularnewline
193 & 15 & 13.28 & 1.71996 \tabularnewline
194 & 16 & 16.0612 & -0.0612442 \tabularnewline
195 & 14 & 12.9625 & 1.03749 \tabularnewline
196 & 12 & 14.9164 & -2.91644 \tabularnewline
197 & 19 & 13.0052 & 5.99482 \tabularnewline
198 & 15 & 12.5489 & 2.45111 \tabularnewline
199 & 19 & 18.2923 & 0.707714 \tabularnewline
200 & 13 & 13.9521 & -0.952092 \tabularnewline
201 & 17 & 17.0805 & -0.0804628 \tabularnewline
202 & 12 & 13.2345 & -1.23449 \tabularnewline
203 & 11 & 11.5028 & -0.502801 \tabularnewline
204 & 14 & 15.4063 & -1.40634 \tabularnewline
205 & 11 & 12.8432 & -1.84322 \tabularnewline
206 & 13 & 12.6826 & 0.317378 \tabularnewline
207 & 12 & 12.6359 & -0.635938 \tabularnewline
208 & 15 & 13.2072 & 1.79282 \tabularnewline
209 & 14 & 14.5035 & -0.50349 \tabularnewline
210 & 12 & 11.3984 & 0.60162 \tabularnewline
211 & 17 & 17.5637 & -0.563698 \tabularnewline
212 & 11 & 11.4753 & -0.475321 \tabularnewline
213 & 18 & 14.713 & 3.28696 \tabularnewline
214 & 13 & 15.9139 & -2.91394 \tabularnewline
215 & 17 & 15.7449 & 1.25508 \tabularnewline
216 & 13 & 13.3649 & -0.364947 \tabularnewline
217 & 11 & 10.5446 & 0.455395 \tabularnewline
218 & 12 & 12.7951 & -0.7951 \tabularnewline
219 & 22 & 18.3724 & 3.62759 \tabularnewline
220 & 14 & 12.1698 & 1.8302 \tabularnewline
221 & 12 & 15.3932 & -3.39317 \tabularnewline
222 & 12 & 12.9364 & -0.936439 \tabularnewline
223 & 17 & 16.2264 & 0.773598 \tabularnewline
224 & 9 & 13.0575 & -4.05751 \tabularnewline
225 & 21 & 19.0877 & 1.91229 \tabularnewline
226 & 10 & 12.2988 & -2.29878 \tabularnewline
227 & 11 & 11.2417 & -0.241717 \tabularnewline
228 & 12 & 15.4912 & -3.49122 \tabularnewline
229 & 23 & 18.2259 & 4.77414 \tabularnewline
230 & 13 & 15.874 & -2.87397 \tabularnewline
231 & 12 & 13.6977 & -1.69774 \tabularnewline
232 & 16 & 17.5781 & -1.57809 \tabularnewline
233 & 9 & 13.6515 & -4.65154 \tabularnewline
234 & 17 & 13.7919 & 3.20809 \tabularnewline
235 & 9 & 12.2341 & -3.23411 \tabularnewline
236 & 14 & 15.8673 & -1.86731 \tabularnewline
237 & 17 & 15.2872 & 1.71276 \tabularnewline
238 & 13 & 15.5146 & -2.51462 \tabularnewline
239 & 11 & 16.2413 & -5.24134 \tabularnewline
240 & 12 & 15.8173 & -3.81729 \tabularnewline
241 & 10 & 14.2611 & -4.26108 \tabularnewline
242 & 19 & 18.9019 & 0.0980609 \tabularnewline
243 & 16 & 16.1811 & -0.181066 \tabularnewline
244 & 16 & 15.3609 & 0.639074 \tabularnewline
245 & 14 & 12.1316 & 1.86836 \tabularnewline
246 & 20 & 16.048 & 3.95204 \tabularnewline
247 & 15 & 14.5334 & 0.466645 \tabularnewline
248 & 23 & 15.4299 & 7.57006 \tabularnewline
249 & 20 & 17.6498 & 2.35017 \tabularnewline
250 & 16 & 16.3982 & -0.398155 \tabularnewline
251 & 14 & 13.2698 & 0.730187 \tabularnewline
252 & 17 & 14.1809 & 2.81914 \tabularnewline
253 & 11 & 14.4252 & -3.42524 \tabularnewline
254 & 13 & 14.133 & -1.13295 \tabularnewline
255 & 17 & 15.2239 & 1.77606 \tabularnewline
256 & 15 & 15.2079 & -0.207937 \tabularnewline
257 & 21 & 16.6525 & 4.34749 \tabularnewline
258 & 18 & 17.6529 & 0.347081 \tabularnewline
259 & 15 & 13.1541 & 1.84589 \tabularnewline
260 & 8 & 16.317 & -8.31696 \tabularnewline
261 & 12 & 14.0811 & -2.08114 \tabularnewline
262 & 12 & 13.294 & -1.29405 \tabularnewline
263 & 22 & 19.0588 & 2.94121 \tabularnewline
264 & 12 & 13.6579 & -1.65794 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226663&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]12[/C][C]13.7932[/C][C]-1.79323[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]9.09759[/C][C]1.90241[/C][/ROW]
[ROW][C]3[/C][C]14[/C][C]14.8828[/C][C]-0.882839[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.4535[/C][C]-2.45351[/C][/ROW]
[ROW][C]5[/C][C]21[/C][C]11.1221[/C][C]9.87794[/C][/ROW]
[ROW][C]6[/C][C]12[/C][C]9.66607[/C][C]2.33393[/C][/ROW]
[ROW][C]7[/C][C]22[/C][C]13.4183[/C][C]8.58166[/C][/ROW]
[ROW][C]8[/C][C]11[/C][C]12.179[/C][C]-1.17899[/C][/ROW]
[ROW][C]9[/C][C]10[/C][C]11.8863[/C][C]-1.88633[/C][/ROW]
[ROW][C]10[/C][C]13[/C][C]11.7271[/C][C]1.27293[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]10.048[/C][C]-0.0479953[/C][/ROW]
[ROW][C]12[/C][C]8[/C][C]10.1947[/C][C]-2.19471[/C][/ROW]
[ROW][C]13[/C][C]15[/C][C]15.5651[/C][C]-0.565125[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]12.2206[/C][C]1.77938[/C][/ROW]
[ROW][C]15[/C][C]10[/C][C]8.90452[/C][C]1.09548[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.5331[/C][C]0.46689[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]12.4557[/C][C]1.54427[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]9.27029[/C][C]1.72971[/C][/ROW]
[ROW][C]19[/C][C]10[/C][C]12.8721[/C][C]-2.87214[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]12.1506[/C][C]0.849379[/C][/ROW]
[ROW][C]21[/C][C]9.5[/C][C]10.2579[/C][C]-0.757887[/C][/ROW]
[ROW][C]22[/C][C]14[/C][C]14.9467[/C][C]-0.946741[/C][/ROW]
[ROW][C]23[/C][C]12[/C][C]13.3816[/C][C]-1.38164[/C][/ROW]
[ROW][C]24[/C][C]14[/C][C]14.8948[/C][C]-0.894751[/C][/ROW]
[ROW][C]25[/C][C]11[/C][C]9.53198[/C][C]1.46802[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.3291[/C][C]-6.32906[/C][/ROW]
[ROW][C]27[/C][C]11[/C][C]10.9732[/C][C]0.0267623[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]12.8577[/C][C]2.14235[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]11.5742[/C][C]2.42578[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]15.101[/C][C]-2.10096[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]10.8653[/C][C]-1.8653[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]14.7894[/C][C]0.210603[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.6718[/C][C]-0.671832[/C][/ROW]
[ROW][C]34[/C][C]11[/C][C]11.2158[/C][C]-0.215825[/C][/ROW]
[ROW][C]35[/C][C]13[/C][C]12.5913[/C][C]0.408686[/C][/ROW]
[ROW][C]36[/C][C]8[/C][C]11.7586[/C][C]-3.75856[/C][/ROW]
[ROW][C]37[/C][C]20[/C][C]17.0728[/C][C]2.92718[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]12.0551[/C][C]-0.0550758[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.4142[/C][C]-0.414224[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]13.4602[/C][C]-3.46015[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]11.7436[/C][C]-2.74362[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]11.1728[/C][C]2.8272[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]11.9171[/C][C]-3.91706[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]15.284[/C][C]-1.28402[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]12.1288[/C][C]-1.12881[/C][/ROW]
[ROW][C]46[/C][C]13[/C][C]15.16[/C][C]-2.15999[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]12.3875[/C][C]-3.38749[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.8311[/C][C]-0.831104[/C][/ROW]
[ROW][C]49[/C][C]15[/C][C]10.4093[/C][C]4.59067[/C][/ROW]
[ROW][C]50[/C][C]11[/C][C]13.1443[/C][C]-2.1443[/C][/ROW]
[ROW][C]51[/C][C]10[/C][C]11.2679[/C][C]-1.26795[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.0689[/C][C]0.931074[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]15.488[/C][C]2.512[/C][/ROW]
[ROW][C]54[/C][C]14[/C][C]14.5763[/C][C]-0.576337[/C][/ROW]
[ROW][C]55[/C][C]11[/C][C]15.0594[/C][C]-4.05943[/C][/ROW]
[ROW][C]56[/C][C]14.5[/C][C]11.8073[/C][C]2.69267[/C][/ROW]
[ROW][C]57[/C][C]13[/C][C]11.0044[/C][C]1.99562[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]12.3156[/C][C]-3.31558[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]13.9354[/C][C]-3.93539[/C][/ROW]
[ROW][C]60[/C][C]15[/C][C]14.0921[/C][C]0.90794[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]18.2104[/C][C]1.78959[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]12.907[/C][C]-0.906952[/C][/ROW]
[ROW][C]63[/C][C]12[/C][C]14.1701[/C][C]-2.17011[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.9937[/C][C]0.00630734[/C][/ROW]
[ROW][C]65[/C][C]13[/C][C]12.9688[/C][C]0.0311589[/C][/ROW]
[ROW][C]66[/C][C]11[/C][C]15.1931[/C][C]-4.19313[/C][/ROW]
[ROW][C]67[/C][C]17[/C][C]15.2334[/C][C]1.76664[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.2494[/C][C]-2.24944[/C][/ROW]
[ROW][C]69[/C][C]13[/C][C]13.0299[/C][C]-0.0299269[/C][/ROW]
[ROW][C]70[/C][C]14[/C][C]12.4873[/C][C]1.51268[/C][/ROW]
[ROW][C]71[/C][C]13[/C][C]13.6496[/C][C]-0.649609[/C][/ROW]
[ROW][C]72[/C][C]15[/C][C]12.9177[/C][C]2.08235[/C][/ROW]
[ROW][C]73[/C][C]13[/C][C]11.657[/C][C]1.34304[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]12.2952[/C][C]-2.29516[/C][/ROW]
[ROW][C]75[/C][C]11[/C][C]12.944[/C][C]-1.94403[/C][/ROW]
[ROW][C]76[/C][C]19[/C][C]13.744[/C][C]5.25602[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.0028[/C][C]1.99715[/C][/ROW]
[ROW][C]78[/C][C]17[/C][C]13.8634[/C][C]3.13658[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]12.3225[/C][C]0.677471[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]14.6624[/C][C]-5.66244[/C][/ROW]
[ROW][C]81[/C][C]11[/C][C]11.9307[/C][C]-0.930738[/C][/ROW]
[ROW][C]82[/C][C]9[/C][C]12.3686[/C][C]-3.36858[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]11.5667[/C][C]0.433306[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]12.432[/C][C]-0.431959[/C][/ROW]
[ROW][C]85[/C][C]13[/C][C]12.7329[/C][C]0.267127[/C][/ROW]
[ROW][C]86[/C][C]13[/C][C]12.2361[/C][C]0.763949[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]13.2017[/C][C]-1.20167[/C][/ROW]
[ROW][C]88[/C][C]15[/C][C]14.8531[/C][C]0.146934[/C][/ROW]
[ROW][C]89[/C][C]22[/C][C]18.0078[/C][C]3.99223[/C][/ROW]
[ROW][C]90[/C][C]13[/C][C]11.2418[/C][C]1.75816[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]14.6124[/C][C]0.387554[/C][/ROW]
[ROW][C]92[/C][C]13[/C][C]12.0311[/C][C]0.96891[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]12.4866[/C][C]2.51336[/C][/ROW]
[ROW][C]94[/C][C]12.5[/C][C]13.492[/C][C]-0.992023[/C][/ROW]
[ROW][C]95[/C][C]11[/C][C]11.0796[/C][C]-0.0795746[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]14.4858[/C][C]1.51417[/C][/ROW]
[ROW][C]97[/C][C]11[/C][C]12.6418[/C][C]-1.64181[/C][/ROW]
[ROW][C]98[/C][C]11[/C][C]10.3458[/C][C]0.654167[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]12.2779[/C][C]-2.27794[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]10.6109[/C][C]-0.610935[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.2686[/C][C]1.73144[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]10.5436[/C][C]1.45637[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]15.5065[/C][C]-4.50646[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]11.9549[/C][C]4.04511[/C][/ROW]
[ROW][C]105[/C][C]19[/C][C]16.7303[/C][C]2.26971[/C][/ROW]
[ROW][C]106[/C][C]11[/C][C]11.2491[/C][C]-0.249076[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]12.2525[/C][C]3.74746[/C][/ROW]
[ROW][C]108[/C][C]15[/C][C]16.7907[/C][C]-1.79069[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]17.4485[/C][C]6.55151[/C][/ROW]
[ROW][C]110[/C][C]14[/C][C]11.6279[/C][C]2.37215[/C][/ROW]
[ROW][C]111[/C][C]15[/C][C]14.9815[/C][C]0.0184884[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.76[/C][C]-1.76003[/C][/ROW]
[ROW][C]113[/C][C]15[/C][C]15.2604[/C][C]-0.260438[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]10.2322[/C][C]1.76775[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]10.5881[/C][C]-0.588132[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14.2382[/C][C]-0.23819[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]13.496[/C][C]-0.496007[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]13.4084[/C][C]-4.40842[/C][/ROW]
[ROW][C]119[/C][C]15[/C][C]11.8597[/C][C]3.14025[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]15.6815[/C][C]-0.681531[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]12.785[/C][C]1.21501[/C][/ROW]
[ROW][C]122[/C][C]11[/C][C]11.4385[/C][C]-0.438528[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]12.0144[/C][C]-4.01439[/C][/ROW]
[ROW][C]124[/C][C]11[/C][C]12.2547[/C][C]-1.25472[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]13.3014[/C][C]-2.30136[/C][/ROW]
[ROW][C]126[/C][C]8[/C][C]9.84453[/C][C]-1.84453[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]10.5846[/C][C]-0.584649[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]9.15992[/C][C]1.84008[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]12.5565[/C][C]0.443474[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]13.806[/C][C]-2.80596[/C][/ROW]
[ROW][C]131[/C][C]20[/C][C]17.3019[/C][C]2.69808[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]11.9483[/C][C]-1.94828[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]13.1253[/C][C]1.87471[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]12.2813[/C][C]-0.281319[/C][/ROW]
[ROW][C]135[/C][C]14[/C][C]10.94[/C][C]3.05997[/C][/ROW]
[ROW][C]136[/C][C]23[/C][C]16.4226[/C][C]6.5774[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.6158[/C][C]0.384232[/C][/ROW]
[ROW][C]138[/C][C]16[/C][C]16.5595[/C][C]-0.559544[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]13.0665[/C][C]-2.06649[/C][/ROW]
[ROW][C]140[/C][C]12[/C][C]14.285[/C][C]-2.285[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]13.467[/C][C]-3.46696[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]11.109[/C][C]2.89101[/C][/ROW]
[ROW][C]143[/C][C]12[/C][C]12.1655[/C][C]-0.165456[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]12.0405[/C][C]-0.0405106[/C][/ROW]
[ROW][C]145[/C][C]11[/C][C]10.905[/C][C]0.0949508[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]11.2629[/C][C]0.737069[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.9344[/C][C]-2.93441[/C][/ROW]
[ROW][C]148[/C][C]11[/C][C]14.2255[/C][C]-3.22549[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]16.5683[/C][C]2.43173[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]11.2319[/C][C]0.768094[/C][/ROW]
[ROW][C]151[/C][C]17[/C][C]13.1744[/C][C]3.82563[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.7379[/C][C]-2.73789[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.439[/C][C]-2.439[/C][/ROW]
[ROW][C]154[/C][C]19[/C][C]16.2967[/C][C]2.70331[/C][/ROW]
[ROW][C]155[/C][C]18[/C][C]13.7642[/C][C]4.23578[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]14.6124[/C][C]0.387554[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.4892[/C][C]0.510779[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]9.15992[/C][C]1.84008[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]12.9775[/C][C]-3.97755[/C][/ROW]
[ROW][C]160[/C][C]18[/C][C]14.0203[/C][C]3.97969[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]14.1091[/C][C]1.89089[/C][/ROW]
[ROW][C]162[/C][C]24[/C][C]16.8281[/C][C]7.17188[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.1918[/C][C]0.808223[/C][/ROW]
[ROW][C]164[/C][C]20[/C][C]11.2651[/C][C]8.73489[/C][/ROW]
[ROW][C]165[/C][C]18[/C][C]16.2585[/C][C]1.74151[/C][/ROW]
[ROW][C]166[/C][C]23[/C][C]17.1476[/C][C]5.85242[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]13.2653[/C][C]-1.26528[/C][/ROW]
[ROW][C]168[/C][C]14[/C][C]15.1039[/C][C]-1.10394[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]16.4545[/C][C]-0.454459[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]16.9385[/C][C]1.06153[/C][/ROW]
[ROW][C]171[/C][C]20[/C][C]16.7235[/C][C]3.27648[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]12.0036[/C][C]-0.00355462[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]16.6158[/C][C]-4.61578[/C][/ROW]
[ROW][C]174[/C][C]17[/C][C]15.4237[/C][C]1.57629[/C][/ROW]
[ROW][C]175[/C][C]13[/C][C]12.2173[/C][C]0.782651[/C][/ROW]
[ROW][C]176[/C][C]9[/C][C]13.8555[/C][C]-4.85545[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]17.3039[/C][C]-1.30394[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]15.3069[/C][C]2.69306[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]12.525[/C][C]-2.525[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]15.5622[/C][C]-1.56225[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]14.4407[/C][C]-3.44073[/C][/ROW]
[ROW][C]182[/C][C]9[/C][C]14.7289[/C][C]-5.72888[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]12.6864[/C][C]-1.68644[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]12.9005[/C][C]-2.90055[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]11.7566[/C][C]-0.756619[/C][/ROW]
[ROW][C]186[/C][C]19[/C][C]13.9048[/C][C]5.09522[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.1901[/C][C]0.809923[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.0153[/C][C]-0.0152652[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]15.6275[/C][C]-1.62754[/C][/ROW]
[ROW][C]190[/C][C]21[/C][C]16.5592[/C][C]4.44079[/C][/ROW]
[ROW][C]191[/C][C]13[/C][C]17.662[/C][C]-4.66202[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]13.1709[/C][C]-3.17088[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]13.28[/C][C]1.71996[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]16.0612[/C][C]-0.0612442[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]12.9625[/C][C]1.03749[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.9164[/C][C]-2.91644[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]13.0052[/C][C]5.99482[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]12.5489[/C][C]2.45111[/C][/ROW]
[ROW][C]199[/C][C]19[/C][C]18.2923[/C][C]0.707714[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.9521[/C][C]-0.952092[/C][/ROW]
[ROW][C]201[/C][C]17[/C][C]17.0805[/C][C]-0.0804628[/C][/ROW]
[ROW][C]202[/C][C]12[/C][C]13.2345[/C][C]-1.23449[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]11.5028[/C][C]-0.502801[/C][/ROW]
[ROW][C]204[/C][C]14[/C][C]15.4063[/C][C]-1.40634[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]12.8432[/C][C]-1.84322[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]12.6826[/C][C]0.317378[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]12.6359[/C][C]-0.635938[/C][/ROW]
[ROW][C]208[/C][C]15[/C][C]13.2072[/C][C]1.79282[/C][/ROW]
[ROW][C]209[/C][C]14[/C][C]14.5035[/C][C]-0.50349[/C][/ROW]
[ROW][C]210[/C][C]12[/C][C]11.3984[/C][C]0.60162[/C][/ROW]
[ROW][C]211[/C][C]17[/C][C]17.5637[/C][C]-0.563698[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]11.4753[/C][C]-0.475321[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]14.713[/C][C]3.28696[/C][/ROW]
[ROW][C]214[/C][C]13[/C][C]15.9139[/C][C]-2.91394[/C][/ROW]
[ROW][C]215[/C][C]17[/C][C]15.7449[/C][C]1.25508[/C][/ROW]
[ROW][C]216[/C][C]13[/C][C]13.3649[/C][C]-0.364947[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]10.5446[/C][C]0.455395[/C][/ROW]
[ROW][C]218[/C][C]12[/C][C]12.7951[/C][C]-0.7951[/C][/ROW]
[ROW][C]219[/C][C]22[/C][C]18.3724[/C][C]3.62759[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]12.1698[/C][C]1.8302[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]15.3932[/C][C]-3.39317[/C][/ROW]
[ROW][C]222[/C][C]12[/C][C]12.9364[/C][C]-0.936439[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]16.2264[/C][C]0.773598[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]13.0575[/C][C]-4.05751[/C][/ROW]
[ROW][C]225[/C][C]21[/C][C]19.0877[/C][C]1.91229[/C][/ROW]
[ROW][C]226[/C][C]10[/C][C]12.2988[/C][C]-2.29878[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]11.2417[/C][C]-0.241717[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]15.4912[/C][C]-3.49122[/C][/ROW]
[ROW][C]229[/C][C]23[/C][C]18.2259[/C][C]4.77414[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]15.874[/C][C]-2.87397[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]13.6977[/C][C]-1.69774[/C][/ROW]
[ROW][C]232[/C][C]16[/C][C]17.5781[/C][C]-1.57809[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]13.6515[/C][C]-4.65154[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]13.7919[/C][C]3.20809[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]12.2341[/C][C]-3.23411[/C][/ROW]
[ROW][C]236[/C][C]14[/C][C]15.8673[/C][C]-1.86731[/C][/ROW]
[ROW][C]237[/C][C]17[/C][C]15.2872[/C][C]1.71276[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]15.5146[/C][C]-2.51462[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]16.2413[/C][C]-5.24134[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]15.8173[/C][C]-3.81729[/C][/ROW]
[ROW][C]241[/C][C]10[/C][C]14.2611[/C][C]-4.26108[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]18.9019[/C][C]0.0980609[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]16.1811[/C][C]-0.181066[/C][/ROW]
[ROW][C]244[/C][C]16[/C][C]15.3609[/C][C]0.639074[/C][/ROW]
[ROW][C]245[/C][C]14[/C][C]12.1316[/C][C]1.86836[/C][/ROW]
[ROW][C]246[/C][C]20[/C][C]16.048[/C][C]3.95204[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]14.5334[/C][C]0.466645[/C][/ROW]
[ROW][C]248[/C][C]23[/C][C]15.4299[/C][C]7.57006[/C][/ROW]
[ROW][C]249[/C][C]20[/C][C]17.6498[/C][C]2.35017[/C][/ROW]
[ROW][C]250[/C][C]16[/C][C]16.3982[/C][C]-0.398155[/C][/ROW]
[ROW][C]251[/C][C]14[/C][C]13.2698[/C][C]0.730187[/C][/ROW]
[ROW][C]252[/C][C]17[/C][C]14.1809[/C][C]2.81914[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]14.4252[/C][C]-3.42524[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]14.133[/C][C]-1.13295[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]15.2239[/C][C]1.77606[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]15.2079[/C][C]-0.207937[/C][/ROW]
[ROW][C]257[/C][C]21[/C][C]16.6525[/C][C]4.34749[/C][/ROW]
[ROW][C]258[/C][C]18[/C][C]17.6529[/C][C]0.347081[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]13.1541[/C][C]1.84589[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]16.317[/C][C]-8.31696[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]14.0811[/C][C]-2.08114[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]13.294[/C][C]-1.29405[/C][/ROW]
[ROW][C]263[/C][C]22[/C][C]19.0588[/C][C]2.94121[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]13.6579[/C][C]-1.65794[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226663&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226663&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
11213.7932-1.79323
2119.097591.90241
31414.8828-0.882839
41214.4535-2.45351
52111.12219.87794
6129.666072.33393
72213.41838.58166
81112.179-1.17899
91011.8863-1.88633
101311.72711.27293
111010.048-0.0479953
12810.1947-2.19471
131515.5651-0.565125
141412.22061.77938
15108.904521.09548
161413.53310.46689
171412.45571.54427
18119.270291.72971
191012.8721-2.87214
201312.15060.849379
219.510.2579-0.757887
221414.9467-0.946741
231213.3816-1.38164
241414.8948-0.894751
25119.531981.46802
26915.3291-6.32906
271110.97320.0267623
281512.85772.14235
291411.57422.42578
301315.101-2.10096
31910.8653-1.8653
321514.78940.210603
331010.6718-0.671832
341111.2158-0.215825
351312.59130.408686
36811.7586-3.75856
372017.07282.92718
381212.0551-0.0550758
391010.4142-0.414224
401013.4602-3.46015
41911.7436-2.74362
421411.17282.8272
43811.9171-3.91706
441415.284-1.28402
451112.1288-1.12881
461315.16-2.15999
47912.3875-3.38749
481111.8311-0.831104
491510.40934.59067
501113.1443-2.1443
511011.2679-1.26795
521413.06890.931074
531815.4882.512
541414.5763-0.576337
551115.0594-4.05943
5614.511.80732.69267
571311.00441.99562
58912.3156-3.31558
591013.9354-3.93539
601514.09210.90794
612018.21041.78959
621212.907-0.906952
631214.1701-2.17011
641413.99370.00630734
651312.96880.0311589
661115.1931-4.19313
671715.23341.76664
681214.2494-2.24944
691313.0299-0.0299269
701412.48731.51268
711313.6496-0.649609
721512.91772.08235
731311.6571.34304
741012.2952-2.29516
751112.944-1.94403
761913.7445.25602
771311.00281.99715
781713.86343.13658
791312.32250.677471
80914.6624-5.66244
811111.9307-0.930738
82912.3686-3.36858
831211.56670.433306
841212.432-0.431959
851312.73290.267127
861312.23610.763949
871213.2017-1.20167
881514.85310.146934
892218.00783.99223
901311.24181.75816
911514.61240.387554
921312.03110.96891
931512.48662.51336
9412.513.492-0.992023
951111.0796-0.0795746
961614.48581.51417
971112.6418-1.64181
981110.34580.654167
991012.2779-2.27794
1001010.6109-0.610935
1011614.26861.73144
1021210.54361.45637
1031115.5065-4.50646
1041611.95494.04511
1051916.73032.26971
1061111.2491-0.249076
1071612.25253.74746
1081516.7907-1.79069
1092417.44856.55151
1101411.62792.37215
1111514.98150.0184884
1121112.76-1.76003
1131515.2604-0.260438
1141210.23221.76775
1151010.5881-0.588132
1161414.2382-0.23819
1171313.496-0.496007
118913.4084-4.40842
1191511.85973.14025
1201515.6815-0.681531
1211412.7851.21501
1221111.4385-0.438528
123812.0144-4.01439
1241112.2547-1.25472
1251113.3014-2.30136
12689.84453-1.84453
1271010.5846-0.584649
128119.159921.84008
1291312.55650.443474
1301113.806-2.80596
1312017.30192.69808
1321011.9483-1.94828
1331513.12531.87471
1341212.2813-0.281319
1351410.943.05997
1362316.42266.5774
1371413.61580.384232
1381616.5595-0.559544
1391113.0665-2.06649
1401214.285-2.285
1411013.467-3.46696
1421411.1092.89101
1431212.1655-0.165456
1441212.0405-0.0405106
1451110.9050.0949508
1461211.26290.737069
1471315.9344-2.93441
1481114.2255-3.22549
1491916.56832.43173
1501211.23190.768094
1511713.17443.82563
152911.7379-2.73789
1531214.439-2.439
1541916.29672.70331
1551813.76424.23578
1561514.61240.387554
1571413.48920.510779
158119.159921.84008
159912.9775-3.97755
1601814.02033.97969
1611614.10911.89089
1622416.82817.17188
1631413.19180.808223
1642011.26518.73489
1651816.25851.74151
1662317.14765.85242
1671213.2653-1.26528
1681415.1039-1.10394
1691616.4545-0.454459
1701816.93851.06153
1712016.72353.27648
1721212.0036-0.00355462
1731216.6158-4.61578
1741715.42371.57629
1751312.21730.782651
176913.8555-4.85545
1771617.3039-1.30394
1781815.30692.69306
1791012.525-2.525
1801415.5622-1.56225
1811114.4407-3.44073
182914.7289-5.72888
1831112.6864-1.68644
1841012.9005-2.90055
1851111.7566-0.756619
1861913.90485.09522
1871413.19010.809923
1881212.0153-0.0152652
1891415.6275-1.62754
1902116.55924.44079
1911317.662-4.66202
1921013.1709-3.17088
1931513.281.71996
1941616.0612-0.0612442
1951412.96251.03749
1961214.9164-2.91644
1971913.00525.99482
1981512.54892.45111
1991918.29230.707714
2001313.9521-0.952092
2011717.0805-0.0804628
2021213.2345-1.23449
2031111.5028-0.502801
2041415.4063-1.40634
2051112.8432-1.84322
2061312.68260.317378
2071212.6359-0.635938
2081513.20721.79282
2091414.5035-0.50349
2101211.39840.60162
2111717.5637-0.563698
2121111.4753-0.475321
2131814.7133.28696
2141315.9139-2.91394
2151715.74491.25508
2161313.3649-0.364947
2171110.54460.455395
2181212.7951-0.7951
2192218.37243.62759
2201412.16981.8302
2211215.3932-3.39317
2221212.9364-0.936439
2231716.22640.773598
224913.0575-4.05751
2252119.08771.91229
2261012.2988-2.29878
2271111.2417-0.241717
2281215.4912-3.49122
2292318.22594.77414
2301315.874-2.87397
2311213.6977-1.69774
2321617.5781-1.57809
233913.6515-4.65154
2341713.79193.20809
235912.2341-3.23411
2361415.8673-1.86731
2371715.28721.71276
2381315.5146-2.51462
2391116.2413-5.24134
2401215.8173-3.81729
2411014.2611-4.26108
2421918.90190.0980609
2431616.1811-0.181066
2441615.36090.639074
2451412.13161.86836
2462016.0483.95204
2471514.53340.466645
2482315.42997.57006
2492017.64982.35017
2501616.3982-0.398155
2511413.26980.730187
2521714.18092.81914
2531114.4252-3.42524
2541314.133-1.13295
2551715.22391.77606
2561515.2079-0.207937
2572116.65254.34749
2581817.65290.347081
2591513.15411.84589
260816.317-8.31696
2611214.0811-2.08114
2621213.294-1.29405
2632219.05882.94121
2641213.6579-1.65794






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.8546430.2907150.145357
120.9997960.0004070250.000203512
130.9995030.000993920.00049696
140.9988710.002258530.00112926
150.9979170.004166570.00208328
160.9959160.00816770.00408385
170.9927280.01454410.00727207
180.9879830.02403360.0120168
190.9882730.02345350.0117268
200.9810920.03781640.0189082
210.9731060.0537880.026894
220.9618740.07625230.0381261
230.951020.09796040.0489802
240.9310760.1378480.0689239
250.9103060.1793880.089694
260.9619890.07602250.0380113
270.9470670.1058650.0529327
280.9350810.1298380.0649189
290.9212950.1574110.0787054
300.8992930.2014130.100707
310.8990410.2019190.100959
320.8720780.2558450.127922
330.847940.3041190.15206
340.8124830.3750330.187517
350.7724210.4551580.227579
360.7817950.4364110.218205
370.8433960.3132070.156604
380.8097330.3805340.190267
390.7784740.4430520.221526
400.7784870.4430260.221513
410.7659480.4681050.234052
420.7481750.503650.251825
430.8073650.3852710.192635
440.7730930.4538130.226907
450.7360130.5279730.263987
460.7128390.5743210.287161
470.7384240.5231520.261576
480.7028130.5943740.297187
490.7472290.5055420.252771
500.7192790.5614420.280721
510.7055070.5889870.294493
520.6699930.6600140.330007
530.6736730.6526540.326327
540.6317110.7365790.368289
550.6435020.7129960.356498
560.6612750.677450.338725
570.6387930.7224130.361207
580.6703170.6593650.329683
590.6878680.6242630.312132
600.6631360.6737280.336864
610.6754830.6490340.324517
620.6381080.7237850.361892
630.6143030.7713940.385697
640.5728980.8542030.427102
650.5308440.9383120.469156
660.5175260.9649490.482474
670.5437110.9125780.456289
680.5207070.9585850.479293
690.4798220.9596440.520178
700.4519930.9039860.548007
710.4123480.8246970.587652
720.3844340.7688680.615566
730.3517240.7034480.648276
740.3419230.6838460.658077
750.3177070.6354130.682293
760.4507310.9014620.549269
770.4213560.8427120.578644
780.4222220.8444440.577778
790.3843950.768790.615605
800.5128580.9742850.487142
810.4833860.9667730.516614
820.5098750.980250.490125
830.4709780.9419560.529022
840.4344440.8688890.565556
850.3964550.7929090.603545
860.3609060.7218120.639094
870.3321230.6642460.667877
880.2985590.5971170.701441
890.3728720.7457450.627128
900.3441540.6883080.655846
910.3124470.6248950.687553
920.2812310.5624610.718769
930.2692440.5384870.730756
940.245510.491020.75449
950.2174120.4348240.782588
960.1998580.3997160.800142
970.1867290.3734580.813271
980.1627870.3255740.837213
990.1610340.3220680.838966
1000.1414670.2829340.858533
1010.1298310.2596620.870169
1020.1140180.2280350.885982
1030.1468720.2937440.853128
1040.1640880.3281760.835912
1050.1642250.328450.835775
1060.1432650.2865310.856735
1070.1556840.3113670.844316
1080.143620.287240.85638
1090.2412110.4824220.758789
1100.2298420.4596850.770158
1110.203510.407020.79649
1120.1951710.3903410.804829
1130.171550.34310.82845
1140.1549620.3099240.845038
1150.1359820.2719630.864018
1160.1181360.2362710.881864
1170.1040590.2081170.895941
1180.1380940.2761880.861906
1190.1386040.2772070.861396
1200.1211640.2423270.878836
1210.1076450.215290.892355
1220.09406420.1881280.905936
1230.1169620.2339240.883038
1240.1045980.2091960.895402
1250.1005890.2011770.899411
1260.09595180.1919040.904048
1270.08415860.1683170.915841
1280.07505350.1501070.924947
1290.06314110.1262820.936859
1300.06577040.1315410.93423
1310.06501740.1300350.934983
1320.0618860.1237720.938114
1330.0549790.1099580.945021
1340.04607520.09215040.953925
1350.04613730.09227450.953863
1360.09244910.1848980.907551
1370.07842920.1568580.921571
1380.06719360.1343870.932806
1390.06468590.1293720.935314
1400.06337430.1267490.936626
1410.07394760.1478950.926052
1420.07235770.1447150.927642
1430.06103540.1220710.938965
1440.05116630.1023330.948834
1450.04259030.08518070.95741
1460.03515240.07030480.964848
1470.03873830.07747660.961262
1480.04576450.09152890.954236
1490.0417970.0835940.958203
1500.03448830.06897650.965512
1510.03780870.07561730.962191
1520.03984870.07969740.960151
1530.04096670.08193350.959033
1540.03799750.07599510.962002
1550.04286240.08572490.957138
1560.03602480.07204960.963975
1570.02953660.05907330.970463
1580.02522990.05045970.97477
1590.04049990.08099990.9595
1600.04028640.08057290.959714
1610.03394130.06788260.966059
1620.08252010.165040.91748
1630.07182340.1436470.928177
1640.2528840.5057680.747116
1650.2300980.4601960.769902
1660.3112410.6224830.688759
1670.2922490.5844970.707751
1680.2740790.5481580.725921
1690.2468340.4936670.753166
1700.2206980.4413960.779302
1710.2199910.4399820.780009
1720.1947350.3894690.805265
1730.2565270.5130540.743473
1740.2419420.4838840.758058
1750.2213110.4426210.778689
1760.2899380.5798770.710062
1770.2687880.5375770.731212
1780.2693180.5386350.730682
1790.2643510.5287020.735649
1800.2461660.4923320.753834
1810.2716540.5433070.728346
1820.3813310.7626610.618669
1830.3603610.7207230.639639
1840.3638880.7277770.636112
1850.3461090.6922170.653891
1860.4346630.8693260.565337
1870.3969040.7938080.603096
1880.3597940.7195880.640206
1890.3330760.6661510.666924
1900.3905070.7810130.609493
1910.4990130.9980250.500987
1920.5277820.9444370.472218
1930.5192850.9614290.480715
1940.4840740.9681480.515926
1950.4550270.9100550.544973
1960.4867290.9734580.513271
1970.6757950.6484110.324205
1980.6788280.6423450.321172
1990.6397450.720510.360255
2000.6012310.7975390.398769
2010.5593780.8812440.440622
2020.5208490.9583020.479151
2030.4847440.9694890.515256
2040.4697280.9394550.530272
2050.4368320.8736650.563168
2060.3943510.7887020.605649
2070.3527540.7055090.647246
2080.3169390.6338790.683061
2090.2785180.5570350.721482
2100.2589390.5178780.741061
2110.2340920.4681840.765908
2120.201980.4039590.79802
2130.2308580.4617170.769142
2140.2138610.4277220.786139
2150.1829240.3658490.817076
2160.155520.3110410.84448
2170.1449270.2898550.855073
2180.1202440.2404890.879756
2190.1188090.2376170.881191
2200.1176040.2352070.882396
2210.1239740.2479490.876026
2220.1055960.2111930.894404
2230.08528020.170560.91472
2240.08773980.175480.91226
2250.07335790.1467160.926642
2260.05936370.1187270.940636
2270.04549280.09098570.954507
2280.05383140.1076630.946169
2290.07440150.1488030.925599
2300.07158040.1431610.92842
2310.05541530.1108310.944585
2320.0516080.1032160.948392
2330.1039110.2078230.896089
2340.1122560.2245120.887744
2350.1096170.2192340.890383
2360.0862930.1725860.913707
2370.1232270.2464550.876773
2380.1663690.3327370.833631
2390.2737080.5474170.726292
2400.2712780.5425560.728722
2410.2260250.4520510.773975
2420.2755170.5510350.724483
2430.2152040.4304080.784796
2440.1615290.3230590.838471
2450.2214950.442990.778505
2460.2384030.4768050.761597
2470.1734150.3468310.826585
2480.2187150.437430.781285
2490.2145380.4290770.785462
2500.1959870.3919740.804013
2510.2239760.4479520.776024
2520.8808720.2382550.119128
2530.7949060.4101890.205094

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.854643 & 0.290715 & 0.145357 \tabularnewline
12 & 0.999796 & 0.000407025 & 0.000203512 \tabularnewline
13 & 0.999503 & 0.00099392 & 0.00049696 \tabularnewline
14 & 0.998871 & 0.00225853 & 0.00112926 \tabularnewline
15 & 0.997917 & 0.00416657 & 0.00208328 \tabularnewline
16 & 0.995916 & 0.0081677 & 0.00408385 \tabularnewline
17 & 0.992728 & 0.0145441 & 0.00727207 \tabularnewline
18 & 0.987983 & 0.0240336 & 0.0120168 \tabularnewline
19 & 0.988273 & 0.0234535 & 0.0117268 \tabularnewline
20 & 0.981092 & 0.0378164 & 0.0189082 \tabularnewline
21 & 0.973106 & 0.053788 & 0.026894 \tabularnewline
22 & 0.961874 & 0.0762523 & 0.0381261 \tabularnewline
23 & 0.95102 & 0.0979604 & 0.0489802 \tabularnewline
24 & 0.931076 & 0.137848 & 0.0689239 \tabularnewline
25 & 0.910306 & 0.179388 & 0.089694 \tabularnewline
26 & 0.961989 & 0.0760225 & 0.0380113 \tabularnewline
27 & 0.947067 & 0.105865 & 0.0529327 \tabularnewline
28 & 0.935081 & 0.129838 & 0.0649189 \tabularnewline
29 & 0.921295 & 0.157411 & 0.0787054 \tabularnewline
30 & 0.899293 & 0.201413 & 0.100707 \tabularnewline
31 & 0.899041 & 0.201919 & 0.100959 \tabularnewline
32 & 0.872078 & 0.255845 & 0.127922 \tabularnewline
33 & 0.84794 & 0.304119 & 0.15206 \tabularnewline
34 & 0.812483 & 0.375033 & 0.187517 \tabularnewline
35 & 0.772421 & 0.455158 & 0.227579 \tabularnewline
36 & 0.781795 & 0.436411 & 0.218205 \tabularnewline
37 & 0.843396 & 0.313207 & 0.156604 \tabularnewline
38 & 0.809733 & 0.380534 & 0.190267 \tabularnewline
39 & 0.778474 & 0.443052 & 0.221526 \tabularnewline
40 & 0.778487 & 0.443026 & 0.221513 \tabularnewline
41 & 0.765948 & 0.468105 & 0.234052 \tabularnewline
42 & 0.748175 & 0.50365 & 0.251825 \tabularnewline
43 & 0.807365 & 0.385271 & 0.192635 \tabularnewline
44 & 0.773093 & 0.453813 & 0.226907 \tabularnewline
45 & 0.736013 & 0.527973 & 0.263987 \tabularnewline
46 & 0.712839 & 0.574321 & 0.287161 \tabularnewline
47 & 0.738424 & 0.523152 & 0.261576 \tabularnewline
48 & 0.702813 & 0.594374 & 0.297187 \tabularnewline
49 & 0.747229 & 0.505542 & 0.252771 \tabularnewline
50 & 0.719279 & 0.561442 & 0.280721 \tabularnewline
51 & 0.705507 & 0.588987 & 0.294493 \tabularnewline
52 & 0.669993 & 0.660014 & 0.330007 \tabularnewline
53 & 0.673673 & 0.652654 & 0.326327 \tabularnewline
54 & 0.631711 & 0.736579 & 0.368289 \tabularnewline
55 & 0.643502 & 0.712996 & 0.356498 \tabularnewline
56 & 0.661275 & 0.67745 & 0.338725 \tabularnewline
57 & 0.638793 & 0.722413 & 0.361207 \tabularnewline
58 & 0.670317 & 0.659365 & 0.329683 \tabularnewline
59 & 0.687868 & 0.624263 & 0.312132 \tabularnewline
60 & 0.663136 & 0.673728 & 0.336864 \tabularnewline
61 & 0.675483 & 0.649034 & 0.324517 \tabularnewline
62 & 0.638108 & 0.723785 & 0.361892 \tabularnewline
63 & 0.614303 & 0.771394 & 0.385697 \tabularnewline
64 & 0.572898 & 0.854203 & 0.427102 \tabularnewline
65 & 0.530844 & 0.938312 & 0.469156 \tabularnewline
66 & 0.517526 & 0.964949 & 0.482474 \tabularnewline
67 & 0.543711 & 0.912578 & 0.456289 \tabularnewline
68 & 0.520707 & 0.958585 & 0.479293 \tabularnewline
69 & 0.479822 & 0.959644 & 0.520178 \tabularnewline
70 & 0.451993 & 0.903986 & 0.548007 \tabularnewline
71 & 0.412348 & 0.824697 & 0.587652 \tabularnewline
72 & 0.384434 & 0.768868 & 0.615566 \tabularnewline
73 & 0.351724 & 0.703448 & 0.648276 \tabularnewline
74 & 0.341923 & 0.683846 & 0.658077 \tabularnewline
75 & 0.317707 & 0.635413 & 0.682293 \tabularnewline
76 & 0.450731 & 0.901462 & 0.549269 \tabularnewline
77 & 0.421356 & 0.842712 & 0.578644 \tabularnewline
78 & 0.422222 & 0.844444 & 0.577778 \tabularnewline
79 & 0.384395 & 0.76879 & 0.615605 \tabularnewline
80 & 0.512858 & 0.974285 & 0.487142 \tabularnewline
81 & 0.483386 & 0.966773 & 0.516614 \tabularnewline
82 & 0.509875 & 0.98025 & 0.490125 \tabularnewline
83 & 0.470978 & 0.941956 & 0.529022 \tabularnewline
84 & 0.434444 & 0.868889 & 0.565556 \tabularnewline
85 & 0.396455 & 0.792909 & 0.603545 \tabularnewline
86 & 0.360906 & 0.721812 & 0.639094 \tabularnewline
87 & 0.332123 & 0.664246 & 0.667877 \tabularnewline
88 & 0.298559 & 0.597117 & 0.701441 \tabularnewline
89 & 0.372872 & 0.745745 & 0.627128 \tabularnewline
90 & 0.344154 & 0.688308 & 0.655846 \tabularnewline
91 & 0.312447 & 0.624895 & 0.687553 \tabularnewline
92 & 0.281231 & 0.562461 & 0.718769 \tabularnewline
93 & 0.269244 & 0.538487 & 0.730756 \tabularnewline
94 & 0.24551 & 0.49102 & 0.75449 \tabularnewline
95 & 0.217412 & 0.434824 & 0.782588 \tabularnewline
96 & 0.199858 & 0.399716 & 0.800142 \tabularnewline
97 & 0.186729 & 0.373458 & 0.813271 \tabularnewline
98 & 0.162787 & 0.325574 & 0.837213 \tabularnewline
99 & 0.161034 & 0.322068 & 0.838966 \tabularnewline
100 & 0.141467 & 0.282934 & 0.858533 \tabularnewline
101 & 0.129831 & 0.259662 & 0.870169 \tabularnewline
102 & 0.114018 & 0.228035 & 0.885982 \tabularnewline
103 & 0.146872 & 0.293744 & 0.853128 \tabularnewline
104 & 0.164088 & 0.328176 & 0.835912 \tabularnewline
105 & 0.164225 & 0.32845 & 0.835775 \tabularnewline
106 & 0.143265 & 0.286531 & 0.856735 \tabularnewline
107 & 0.155684 & 0.311367 & 0.844316 \tabularnewline
108 & 0.14362 & 0.28724 & 0.85638 \tabularnewline
109 & 0.241211 & 0.482422 & 0.758789 \tabularnewline
110 & 0.229842 & 0.459685 & 0.770158 \tabularnewline
111 & 0.20351 & 0.40702 & 0.79649 \tabularnewline
112 & 0.195171 & 0.390341 & 0.804829 \tabularnewline
113 & 0.17155 & 0.3431 & 0.82845 \tabularnewline
114 & 0.154962 & 0.309924 & 0.845038 \tabularnewline
115 & 0.135982 & 0.271963 & 0.864018 \tabularnewline
116 & 0.118136 & 0.236271 & 0.881864 \tabularnewline
117 & 0.104059 & 0.208117 & 0.895941 \tabularnewline
118 & 0.138094 & 0.276188 & 0.861906 \tabularnewline
119 & 0.138604 & 0.277207 & 0.861396 \tabularnewline
120 & 0.121164 & 0.242327 & 0.878836 \tabularnewline
121 & 0.107645 & 0.21529 & 0.892355 \tabularnewline
122 & 0.0940642 & 0.188128 & 0.905936 \tabularnewline
123 & 0.116962 & 0.233924 & 0.883038 \tabularnewline
124 & 0.104598 & 0.209196 & 0.895402 \tabularnewline
125 & 0.100589 & 0.201177 & 0.899411 \tabularnewline
126 & 0.0959518 & 0.191904 & 0.904048 \tabularnewline
127 & 0.0841586 & 0.168317 & 0.915841 \tabularnewline
128 & 0.0750535 & 0.150107 & 0.924947 \tabularnewline
129 & 0.0631411 & 0.126282 & 0.936859 \tabularnewline
130 & 0.0657704 & 0.131541 & 0.93423 \tabularnewline
131 & 0.0650174 & 0.130035 & 0.934983 \tabularnewline
132 & 0.061886 & 0.123772 & 0.938114 \tabularnewline
133 & 0.054979 & 0.109958 & 0.945021 \tabularnewline
134 & 0.0460752 & 0.0921504 & 0.953925 \tabularnewline
135 & 0.0461373 & 0.0922745 & 0.953863 \tabularnewline
136 & 0.0924491 & 0.184898 & 0.907551 \tabularnewline
137 & 0.0784292 & 0.156858 & 0.921571 \tabularnewline
138 & 0.0671936 & 0.134387 & 0.932806 \tabularnewline
139 & 0.0646859 & 0.129372 & 0.935314 \tabularnewline
140 & 0.0633743 & 0.126749 & 0.936626 \tabularnewline
141 & 0.0739476 & 0.147895 & 0.926052 \tabularnewline
142 & 0.0723577 & 0.144715 & 0.927642 \tabularnewline
143 & 0.0610354 & 0.122071 & 0.938965 \tabularnewline
144 & 0.0511663 & 0.102333 & 0.948834 \tabularnewline
145 & 0.0425903 & 0.0851807 & 0.95741 \tabularnewline
146 & 0.0351524 & 0.0703048 & 0.964848 \tabularnewline
147 & 0.0387383 & 0.0774766 & 0.961262 \tabularnewline
148 & 0.0457645 & 0.0915289 & 0.954236 \tabularnewline
149 & 0.041797 & 0.083594 & 0.958203 \tabularnewline
150 & 0.0344883 & 0.0689765 & 0.965512 \tabularnewline
151 & 0.0378087 & 0.0756173 & 0.962191 \tabularnewline
152 & 0.0398487 & 0.0796974 & 0.960151 \tabularnewline
153 & 0.0409667 & 0.0819335 & 0.959033 \tabularnewline
154 & 0.0379975 & 0.0759951 & 0.962002 \tabularnewline
155 & 0.0428624 & 0.0857249 & 0.957138 \tabularnewline
156 & 0.0360248 & 0.0720496 & 0.963975 \tabularnewline
157 & 0.0295366 & 0.0590733 & 0.970463 \tabularnewline
158 & 0.0252299 & 0.0504597 & 0.97477 \tabularnewline
159 & 0.0404999 & 0.0809999 & 0.9595 \tabularnewline
160 & 0.0402864 & 0.0805729 & 0.959714 \tabularnewline
161 & 0.0339413 & 0.0678826 & 0.966059 \tabularnewline
162 & 0.0825201 & 0.16504 & 0.91748 \tabularnewline
163 & 0.0718234 & 0.143647 & 0.928177 \tabularnewline
164 & 0.252884 & 0.505768 & 0.747116 \tabularnewline
165 & 0.230098 & 0.460196 & 0.769902 \tabularnewline
166 & 0.311241 & 0.622483 & 0.688759 \tabularnewline
167 & 0.292249 & 0.584497 & 0.707751 \tabularnewline
168 & 0.274079 & 0.548158 & 0.725921 \tabularnewline
169 & 0.246834 & 0.493667 & 0.753166 \tabularnewline
170 & 0.220698 & 0.441396 & 0.779302 \tabularnewline
171 & 0.219991 & 0.439982 & 0.780009 \tabularnewline
172 & 0.194735 & 0.389469 & 0.805265 \tabularnewline
173 & 0.256527 & 0.513054 & 0.743473 \tabularnewline
174 & 0.241942 & 0.483884 & 0.758058 \tabularnewline
175 & 0.221311 & 0.442621 & 0.778689 \tabularnewline
176 & 0.289938 & 0.579877 & 0.710062 \tabularnewline
177 & 0.268788 & 0.537577 & 0.731212 \tabularnewline
178 & 0.269318 & 0.538635 & 0.730682 \tabularnewline
179 & 0.264351 & 0.528702 & 0.735649 \tabularnewline
180 & 0.246166 & 0.492332 & 0.753834 \tabularnewline
181 & 0.271654 & 0.543307 & 0.728346 \tabularnewline
182 & 0.381331 & 0.762661 & 0.618669 \tabularnewline
183 & 0.360361 & 0.720723 & 0.639639 \tabularnewline
184 & 0.363888 & 0.727777 & 0.636112 \tabularnewline
185 & 0.346109 & 0.692217 & 0.653891 \tabularnewline
186 & 0.434663 & 0.869326 & 0.565337 \tabularnewline
187 & 0.396904 & 0.793808 & 0.603096 \tabularnewline
188 & 0.359794 & 0.719588 & 0.640206 \tabularnewline
189 & 0.333076 & 0.666151 & 0.666924 \tabularnewline
190 & 0.390507 & 0.781013 & 0.609493 \tabularnewline
191 & 0.499013 & 0.998025 & 0.500987 \tabularnewline
192 & 0.527782 & 0.944437 & 0.472218 \tabularnewline
193 & 0.519285 & 0.961429 & 0.480715 \tabularnewline
194 & 0.484074 & 0.968148 & 0.515926 \tabularnewline
195 & 0.455027 & 0.910055 & 0.544973 \tabularnewline
196 & 0.486729 & 0.973458 & 0.513271 \tabularnewline
197 & 0.675795 & 0.648411 & 0.324205 \tabularnewline
198 & 0.678828 & 0.642345 & 0.321172 \tabularnewline
199 & 0.639745 & 0.72051 & 0.360255 \tabularnewline
200 & 0.601231 & 0.797539 & 0.398769 \tabularnewline
201 & 0.559378 & 0.881244 & 0.440622 \tabularnewline
202 & 0.520849 & 0.958302 & 0.479151 \tabularnewline
203 & 0.484744 & 0.969489 & 0.515256 \tabularnewline
204 & 0.469728 & 0.939455 & 0.530272 \tabularnewline
205 & 0.436832 & 0.873665 & 0.563168 \tabularnewline
206 & 0.394351 & 0.788702 & 0.605649 \tabularnewline
207 & 0.352754 & 0.705509 & 0.647246 \tabularnewline
208 & 0.316939 & 0.633879 & 0.683061 \tabularnewline
209 & 0.278518 & 0.557035 & 0.721482 \tabularnewline
210 & 0.258939 & 0.517878 & 0.741061 \tabularnewline
211 & 0.234092 & 0.468184 & 0.765908 \tabularnewline
212 & 0.20198 & 0.403959 & 0.79802 \tabularnewline
213 & 0.230858 & 0.461717 & 0.769142 \tabularnewline
214 & 0.213861 & 0.427722 & 0.786139 \tabularnewline
215 & 0.182924 & 0.365849 & 0.817076 \tabularnewline
216 & 0.15552 & 0.311041 & 0.84448 \tabularnewline
217 & 0.144927 & 0.289855 & 0.855073 \tabularnewline
218 & 0.120244 & 0.240489 & 0.879756 \tabularnewline
219 & 0.118809 & 0.237617 & 0.881191 \tabularnewline
220 & 0.117604 & 0.235207 & 0.882396 \tabularnewline
221 & 0.123974 & 0.247949 & 0.876026 \tabularnewline
222 & 0.105596 & 0.211193 & 0.894404 \tabularnewline
223 & 0.0852802 & 0.17056 & 0.91472 \tabularnewline
224 & 0.0877398 & 0.17548 & 0.91226 \tabularnewline
225 & 0.0733579 & 0.146716 & 0.926642 \tabularnewline
226 & 0.0593637 & 0.118727 & 0.940636 \tabularnewline
227 & 0.0454928 & 0.0909857 & 0.954507 \tabularnewline
228 & 0.0538314 & 0.107663 & 0.946169 \tabularnewline
229 & 0.0744015 & 0.148803 & 0.925599 \tabularnewline
230 & 0.0715804 & 0.143161 & 0.92842 \tabularnewline
231 & 0.0554153 & 0.110831 & 0.944585 \tabularnewline
232 & 0.051608 & 0.103216 & 0.948392 \tabularnewline
233 & 0.103911 & 0.207823 & 0.896089 \tabularnewline
234 & 0.112256 & 0.224512 & 0.887744 \tabularnewline
235 & 0.109617 & 0.219234 & 0.890383 \tabularnewline
236 & 0.086293 & 0.172586 & 0.913707 \tabularnewline
237 & 0.123227 & 0.246455 & 0.876773 \tabularnewline
238 & 0.166369 & 0.332737 & 0.833631 \tabularnewline
239 & 0.273708 & 0.547417 & 0.726292 \tabularnewline
240 & 0.271278 & 0.542556 & 0.728722 \tabularnewline
241 & 0.226025 & 0.452051 & 0.773975 \tabularnewline
242 & 0.275517 & 0.551035 & 0.724483 \tabularnewline
243 & 0.215204 & 0.430408 & 0.784796 \tabularnewline
244 & 0.161529 & 0.323059 & 0.838471 \tabularnewline
245 & 0.221495 & 0.44299 & 0.778505 \tabularnewline
246 & 0.238403 & 0.476805 & 0.761597 \tabularnewline
247 & 0.173415 & 0.346831 & 0.826585 \tabularnewline
248 & 0.218715 & 0.43743 & 0.781285 \tabularnewline
249 & 0.214538 & 0.429077 & 0.785462 \tabularnewline
250 & 0.195987 & 0.391974 & 0.804013 \tabularnewline
251 & 0.223976 & 0.447952 & 0.776024 \tabularnewline
252 & 0.880872 & 0.238255 & 0.119128 \tabularnewline
253 & 0.794906 & 0.410189 & 0.205094 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226663&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]0.854643[/C][C]0.290715[/C][C]0.145357[/C][/ROW]
[ROW][C]12[/C][C]0.999796[/C][C]0.000407025[/C][C]0.000203512[/C][/ROW]
[ROW][C]13[/C][C]0.999503[/C][C]0.00099392[/C][C]0.00049696[/C][/ROW]
[ROW][C]14[/C][C]0.998871[/C][C]0.00225853[/C][C]0.00112926[/C][/ROW]
[ROW][C]15[/C][C]0.997917[/C][C]0.00416657[/C][C]0.00208328[/C][/ROW]
[ROW][C]16[/C][C]0.995916[/C][C]0.0081677[/C][C]0.00408385[/C][/ROW]
[ROW][C]17[/C][C]0.992728[/C][C]0.0145441[/C][C]0.00727207[/C][/ROW]
[ROW][C]18[/C][C]0.987983[/C][C]0.0240336[/C][C]0.0120168[/C][/ROW]
[ROW][C]19[/C][C]0.988273[/C][C]0.0234535[/C][C]0.0117268[/C][/ROW]
[ROW][C]20[/C][C]0.981092[/C][C]0.0378164[/C][C]0.0189082[/C][/ROW]
[ROW][C]21[/C][C]0.973106[/C][C]0.053788[/C][C]0.026894[/C][/ROW]
[ROW][C]22[/C][C]0.961874[/C][C]0.0762523[/C][C]0.0381261[/C][/ROW]
[ROW][C]23[/C][C]0.95102[/C][C]0.0979604[/C][C]0.0489802[/C][/ROW]
[ROW][C]24[/C][C]0.931076[/C][C]0.137848[/C][C]0.0689239[/C][/ROW]
[ROW][C]25[/C][C]0.910306[/C][C]0.179388[/C][C]0.089694[/C][/ROW]
[ROW][C]26[/C][C]0.961989[/C][C]0.0760225[/C][C]0.0380113[/C][/ROW]
[ROW][C]27[/C][C]0.947067[/C][C]0.105865[/C][C]0.0529327[/C][/ROW]
[ROW][C]28[/C][C]0.935081[/C][C]0.129838[/C][C]0.0649189[/C][/ROW]
[ROW][C]29[/C][C]0.921295[/C][C]0.157411[/C][C]0.0787054[/C][/ROW]
[ROW][C]30[/C][C]0.899293[/C][C]0.201413[/C][C]0.100707[/C][/ROW]
[ROW][C]31[/C][C]0.899041[/C][C]0.201919[/C][C]0.100959[/C][/ROW]
[ROW][C]32[/C][C]0.872078[/C][C]0.255845[/C][C]0.127922[/C][/ROW]
[ROW][C]33[/C][C]0.84794[/C][C]0.304119[/C][C]0.15206[/C][/ROW]
[ROW][C]34[/C][C]0.812483[/C][C]0.375033[/C][C]0.187517[/C][/ROW]
[ROW][C]35[/C][C]0.772421[/C][C]0.455158[/C][C]0.227579[/C][/ROW]
[ROW][C]36[/C][C]0.781795[/C][C]0.436411[/C][C]0.218205[/C][/ROW]
[ROW][C]37[/C][C]0.843396[/C][C]0.313207[/C][C]0.156604[/C][/ROW]
[ROW][C]38[/C][C]0.809733[/C][C]0.380534[/C][C]0.190267[/C][/ROW]
[ROW][C]39[/C][C]0.778474[/C][C]0.443052[/C][C]0.221526[/C][/ROW]
[ROW][C]40[/C][C]0.778487[/C][C]0.443026[/C][C]0.221513[/C][/ROW]
[ROW][C]41[/C][C]0.765948[/C][C]0.468105[/C][C]0.234052[/C][/ROW]
[ROW][C]42[/C][C]0.748175[/C][C]0.50365[/C][C]0.251825[/C][/ROW]
[ROW][C]43[/C][C]0.807365[/C][C]0.385271[/C][C]0.192635[/C][/ROW]
[ROW][C]44[/C][C]0.773093[/C][C]0.453813[/C][C]0.226907[/C][/ROW]
[ROW][C]45[/C][C]0.736013[/C][C]0.527973[/C][C]0.263987[/C][/ROW]
[ROW][C]46[/C][C]0.712839[/C][C]0.574321[/C][C]0.287161[/C][/ROW]
[ROW][C]47[/C][C]0.738424[/C][C]0.523152[/C][C]0.261576[/C][/ROW]
[ROW][C]48[/C][C]0.702813[/C][C]0.594374[/C][C]0.297187[/C][/ROW]
[ROW][C]49[/C][C]0.747229[/C][C]0.505542[/C][C]0.252771[/C][/ROW]
[ROW][C]50[/C][C]0.719279[/C][C]0.561442[/C][C]0.280721[/C][/ROW]
[ROW][C]51[/C][C]0.705507[/C][C]0.588987[/C][C]0.294493[/C][/ROW]
[ROW][C]52[/C][C]0.669993[/C][C]0.660014[/C][C]0.330007[/C][/ROW]
[ROW][C]53[/C][C]0.673673[/C][C]0.652654[/C][C]0.326327[/C][/ROW]
[ROW][C]54[/C][C]0.631711[/C][C]0.736579[/C][C]0.368289[/C][/ROW]
[ROW][C]55[/C][C]0.643502[/C][C]0.712996[/C][C]0.356498[/C][/ROW]
[ROW][C]56[/C][C]0.661275[/C][C]0.67745[/C][C]0.338725[/C][/ROW]
[ROW][C]57[/C][C]0.638793[/C][C]0.722413[/C][C]0.361207[/C][/ROW]
[ROW][C]58[/C][C]0.670317[/C][C]0.659365[/C][C]0.329683[/C][/ROW]
[ROW][C]59[/C][C]0.687868[/C][C]0.624263[/C][C]0.312132[/C][/ROW]
[ROW][C]60[/C][C]0.663136[/C][C]0.673728[/C][C]0.336864[/C][/ROW]
[ROW][C]61[/C][C]0.675483[/C][C]0.649034[/C][C]0.324517[/C][/ROW]
[ROW][C]62[/C][C]0.638108[/C][C]0.723785[/C][C]0.361892[/C][/ROW]
[ROW][C]63[/C][C]0.614303[/C][C]0.771394[/C][C]0.385697[/C][/ROW]
[ROW][C]64[/C][C]0.572898[/C][C]0.854203[/C][C]0.427102[/C][/ROW]
[ROW][C]65[/C][C]0.530844[/C][C]0.938312[/C][C]0.469156[/C][/ROW]
[ROW][C]66[/C][C]0.517526[/C][C]0.964949[/C][C]0.482474[/C][/ROW]
[ROW][C]67[/C][C]0.543711[/C][C]0.912578[/C][C]0.456289[/C][/ROW]
[ROW][C]68[/C][C]0.520707[/C][C]0.958585[/C][C]0.479293[/C][/ROW]
[ROW][C]69[/C][C]0.479822[/C][C]0.959644[/C][C]0.520178[/C][/ROW]
[ROW][C]70[/C][C]0.451993[/C][C]0.903986[/C][C]0.548007[/C][/ROW]
[ROW][C]71[/C][C]0.412348[/C][C]0.824697[/C][C]0.587652[/C][/ROW]
[ROW][C]72[/C][C]0.384434[/C][C]0.768868[/C][C]0.615566[/C][/ROW]
[ROW][C]73[/C][C]0.351724[/C][C]0.703448[/C][C]0.648276[/C][/ROW]
[ROW][C]74[/C][C]0.341923[/C][C]0.683846[/C][C]0.658077[/C][/ROW]
[ROW][C]75[/C][C]0.317707[/C][C]0.635413[/C][C]0.682293[/C][/ROW]
[ROW][C]76[/C][C]0.450731[/C][C]0.901462[/C][C]0.549269[/C][/ROW]
[ROW][C]77[/C][C]0.421356[/C][C]0.842712[/C][C]0.578644[/C][/ROW]
[ROW][C]78[/C][C]0.422222[/C][C]0.844444[/C][C]0.577778[/C][/ROW]
[ROW][C]79[/C][C]0.384395[/C][C]0.76879[/C][C]0.615605[/C][/ROW]
[ROW][C]80[/C][C]0.512858[/C][C]0.974285[/C][C]0.487142[/C][/ROW]
[ROW][C]81[/C][C]0.483386[/C][C]0.966773[/C][C]0.516614[/C][/ROW]
[ROW][C]82[/C][C]0.509875[/C][C]0.98025[/C][C]0.490125[/C][/ROW]
[ROW][C]83[/C][C]0.470978[/C][C]0.941956[/C][C]0.529022[/C][/ROW]
[ROW][C]84[/C][C]0.434444[/C][C]0.868889[/C][C]0.565556[/C][/ROW]
[ROW][C]85[/C][C]0.396455[/C][C]0.792909[/C][C]0.603545[/C][/ROW]
[ROW][C]86[/C][C]0.360906[/C][C]0.721812[/C][C]0.639094[/C][/ROW]
[ROW][C]87[/C][C]0.332123[/C][C]0.664246[/C][C]0.667877[/C][/ROW]
[ROW][C]88[/C][C]0.298559[/C][C]0.597117[/C][C]0.701441[/C][/ROW]
[ROW][C]89[/C][C]0.372872[/C][C]0.745745[/C][C]0.627128[/C][/ROW]
[ROW][C]90[/C][C]0.344154[/C][C]0.688308[/C][C]0.655846[/C][/ROW]
[ROW][C]91[/C][C]0.312447[/C][C]0.624895[/C][C]0.687553[/C][/ROW]
[ROW][C]92[/C][C]0.281231[/C][C]0.562461[/C][C]0.718769[/C][/ROW]
[ROW][C]93[/C][C]0.269244[/C][C]0.538487[/C][C]0.730756[/C][/ROW]
[ROW][C]94[/C][C]0.24551[/C][C]0.49102[/C][C]0.75449[/C][/ROW]
[ROW][C]95[/C][C]0.217412[/C][C]0.434824[/C][C]0.782588[/C][/ROW]
[ROW][C]96[/C][C]0.199858[/C][C]0.399716[/C][C]0.800142[/C][/ROW]
[ROW][C]97[/C][C]0.186729[/C][C]0.373458[/C][C]0.813271[/C][/ROW]
[ROW][C]98[/C][C]0.162787[/C][C]0.325574[/C][C]0.837213[/C][/ROW]
[ROW][C]99[/C][C]0.161034[/C][C]0.322068[/C][C]0.838966[/C][/ROW]
[ROW][C]100[/C][C]0.141467[/C][C]0.282934[/C][C]0.858533[/C][/ROW]
[ROW][C]101[/C][C]0.129831[/C][C]0.259662[/C][C]0.870169[/C][/ROW]
[ROW][C]102[/C][C]0.114018[/C][C]0.228035[/C][C]0.885982[/C][/ROW]
[ROW][C]103[/C][C]0.146872[/C][C]0.293744[/C][C]0.853128[/C][/ROW]
[ROW][C]104[/C][C]0.164088[/C][C]0.328176[/C][C]0.835912[/C][/ROW]
[ROW][C]105[/C][C]0.164225[/C][C]0.32845[/C][C]0.835775[/C][/ROW]
[ROW][C]106[/C][C]0.143265[/C][C]0.286531[/C][C]0.856735[/C][/ROW]
[ROW][C]107[/C][C]0.155684[/C][C]0.311367[/C][C]0.844316[/C][/ROW]
[ROW][C]108[/C][C]0.14362[/C][C]0.28724[/C][C]0.85638[/C][/ROW]
[ROW][C]109[/C][C]0.241211[/C][C]0.482422[/C][C]0.758789[/C][/ROW]
[ROW][C]110[/C][C]0.229842[/C][C]0.459685[/C][C]0.770158[/C][/ROW]
[ROW][C]111[/C][C]0.20351[/C][C]0.40702[/C][C]0.79649[/C][/ROW]
[ROW][C]112[/C][C]0.195171[/C][C]0.390341[/C][C]0.804829[/C][/ROW]
[ROW][C]113[/C][C]0.17155[/C][C]0.3431[/C][C]0.82845[/C][/ROW]
[ROW][C]114[/C][C]0.154962[/C][C]0.309924[/C][C]0.845038[/C][/ROW]
[ROW][C]115[/C][C]0.135982[/C][C]0.271963[/C][C]0.864018[/C][/ROW]
[ROW][C]116[/C][C]0.118136[/C][C]0.236271[/C][C]0.881864[/C][/ROW]
[ROW][C]117[/C][C]0.104059[/C][C]0.208117[/C][C]0.895941[/C][/ROW]
[ROW][C]118[/C][C]0.138094[/C][C]0.276188[/C][C]0.861906[/C][/ROW]
[ROW][C]119[/C][C]0.138604[/C][C]0.277207[/C][C]0.861396[/C][/ROW]
[ROW][C]120[/C][C]0.121164[/C][C]0.242327[/C][C]0.878836[/C][/ROW]
[ROW][C]121[/C][C]0.107645[/C][C]0.21529[/C][C]0.892355[/C][/ROW]
[ROW][C]122[/C][C]0.0940642[/C][C]0.188128[/C][C]0.905936[/C][/ROW]
[ROW][C]123[/C][C]0.116962[/C][C]0.233924[/C][C]0.883038[/C][/ROW]
[ROW][C]124[/C][C]0.104598[/C][C]0.209196[/C][C]0.895402[/C][/ROW]
[ROW][C]125[/C][C]0.100589[/C][C]0.201177[/C][C]0.899411[/C][/ROW]
[ROW][C]126[/C][C]0.0959518[/C][C]0.191904[/C][C]0.904048[/C][/ROW]
[ROW][C]127[/C][C]0.0841586[/C][C]0.168317[/C][C]0.915841[/C][/ROW]
[ROW][C]128[/C][C]0.0750535[/C][C]0.150107[/C][C]0.924947[/C][/ROW]
[ROW][C]129[/C][C]0.0631411[/C][C]0.126282[/C][C]0.936859[/C][/ROW]
[ROW][C]130[/C][C]0.0657704[/C][C]0.131541[/C][C]0.93423[/C][/ROW]
[ROW][C]131[/C][C]0.0650174[/C][C]0.130035[/C][C]0.934983[/C][/ROW]
[ROW][C]132[/C][C]0.061886[/C][C]0.123772[/C][C]0.938114[/C][/ROW]
[ROW][C]133[/C][C]0.054979[/C][C]0.109958[/C][C]0.945021[/C][/ROW]
[ROW][C]134[/C][C]0.0460752[/C][C]0.0921504[/C][C]0.953925[/C][/ROW]
[ROW][C]135[/C][C]0.0461373[/C][C]0.0922745[/C][C]0.953863[/C][/ROW]
[ROW][C]136[/C][C]0.0924491[/C][C]0.184898[/C][C]0.907551[/C][/ROW]
[ROW][C]137[/C][C]0.0784292[/C][C]0.156858[/C][C]0.921571[/C][/ROW]
[ROW][C]138[/C][C]0.0671936[/C][C]0.134387[/C][C]0.932806[/C][/ROW]
[ROW][C]139[/C][C]0.0646859[/C][C]0.129372[/C][C]0.935314[/C][/ROW]
[ROW][C]140[/C][C]0.0633743[/C][C]0.126749[/C][C]0.936626[/C][/ROW]
[ROW][C]141[/C][C]0.0739476[/C][C]0.147895[/C][C]0.926052[/C][/ROW]
[ROW][C]142[/C][C]0.0723577[/C][C]0.144715[/C][C]0.927642[/C][/ROW]
[ROW][C]143[/C][C]0.0610354[/C][C]0.122071[/C][C]0.938965[/C][/ROW]
[ROW][C]144[/C][C]0.0511663[/C][C]0.102333[/C][C]0.948834[/C][/ROW]
[ROW][C]145[/C][C]0.0425903[/C][C]0.0851807[/C][C]0.95741[/C][/ROW]
[ROW][C]146[/C][C]0.0351524[/C][C]0.0703048[/C][C]0.964848[/C][/ROW]
[ROW][C]147[/C][C]0.0387383[/C][C]0.0774766[/C][C]0.961262[/C][/ROW]
[ROW][C]148[/C][C]0.0457645[/C][C]0.0915289[/C][C]0.954236[/C][/ROW]
[ROW][C]149[/C][C]0.041797[/C][C]0.083594[/C][C]0.958203[/C][/ROW]
[ROW][C]150[/C][C]0.0344883[/C][C]0.0689765[/C][C]0.965512[/C][/ROW]
[ROW][C]151[/C][C]0.0378087[/C][C]0.0756173[/C][C]0.962191[/C][/ROW]
[ROW][C]152[/C][C]0.0398487[/C][C]0.0796974[/C][C]0.960151[/C][/ROW]
[ROW][C]153[/C][C]0.0409667[/C][C]0.0819335[/C][C]0.959033[/C][/ROW]
[ROW][C]154[/C][C]0.0379975[/C][C]0.0759951[/C][C]0.962002[/C][/ROW]
[ROW][C]155[/C][C]0.0428624[/C][C]0.0857249[/C][C]0.957138[/C][/ROW]
[ROW][C]156[/C][C]0.0360248[/C][C]0.0720496[/C][C]0.963975[/C][/ROW]
[ROW][C]157[/C][C]0.0295366[/C][C]0.0590733[/C][C]0.970463[/C][/ROW]
[ROW][C]158[/C][C]0.0252299[/C][C]0.0504597[/C][C]0.97477[/C][/ROW]
[ROW][C]159[/C][C]0.0404999[/C][C]0.0809999[/C][C]0.9595[/C][/ROW]
[ROW][C]160[/C][C]0.0402864[/C][C]0.0805729[/C][C]0.959714[/C][/ROW]
[ROW][C]161[/C][C]0.0339413[/C][C]0.0678826[/C][C]0.966059[/C][/ROW]
[ROW][C]162[/C][C]0.0825201[/C][C]0.16504[/C][C]0.91748[/C][/ROW]
[ROW][C]163[/C][C]0.0718234[/C][C]0.143647[/C][C]0.928177[/C][/ROW]
[ROW][C]164[/C][C]0.252884[/C][C]0.505768[/C][C]0.747116[/C][/ROW]
[ROW][C]165[/C][C]0.230098[/C][C]0.460196[/C][C]0.769902[/C][/ROW]
[ROW][C]166[/C][C]0.311241[/C][C]0.622483[/C][C]0.688759[/C][/ROW]
[ROW][C]167[/C][C]0.292249[/C][C]0.584497[/C][C]0.707751[/C][/ROW]
[ROW][C]168[/C][C]0.274079[/C][C]0.548158[/C][C]0.725921[/C][/ROW]
[ROW][C]169[/C][C]0.246834[/C][C]0.493667[/C][C]0.753166[/C][/ROW]
[ROW][C]170[/C][C]0.220698[/C][C]0.441396[/C][C]0.779302[/C][/ROW]
[ROW][C]171[/C][C]0.219991[/C][C]0.439982[/C][C]0.780009[/C][/ROW]
[ROW][C]172[/C][C]0.194735[/C][C]0.389469[/C][C]0.805265[/C][/ROW]
[ROW][C]173[/C][C]0.256527[/C][C]0.513054[/C][C]0.743473[/C][/ROW]
[ROW][C]174[/C][C]0.241942[/C][C]0.483884[/C][C]0.758058[/C][/ROW]
[ROW][C]175[/C][C]0.221311[/C][C]0.442621[/C][C]0.778689[/C][/ROW]
[ROW][C]176[/C][C]0.289938[/C][C]0.579877[/C][C]0.710062[/C][/ROW]
[ROW][C]177[/C][C]0.268788[/C][C]0.537577[/C][C]0.731212[/C][/ROW]
[ROW][C]178[/C][C]0.269318[/C][C]0.538635[/C][C]0.730682[/C][/ROW]
[ROW][C]179[/C][C]0.264351[/C][C]0.528702[/C][C]0.735649[/C][/ROW]
[ROW][C]180[/C][C]0.246166[/C][C]0.492332[/C][C]0.753834[/C][/ROW]
[ROW][C]181[/C][C]0.271654[/C][C]0.543307[/C][C]0.728346[/C][/ROW]
[ROW][C]182[/C][C]0.381331[/C][C]0.762661[/C][C]0.618669[/C][/ROW]
[ROW][C]183[/C][C]0.360361[/C][C]0.720723[/C][C]0.639639[/C][/ROW]
[ROW][C]184[/C][C]0.363888[/C][C]0.727777[/C][C]0.636112[/C][/ROW]
[ROW][C]185[/C][C]0.346109[/C][C]0.692217[/C][C]0.653891[/C][/ROW]
[ROW][C]186[/C][C]0.434663[/C][C]0.869326[/C][C]0.565337[/C][/ROW]
[ROW][C]187[/C][C]0.396904[/C][C]0.793808[/C][C]0.603096[/C][/ROW]
[ROW][C]188[/C][C]0.359794[/C][C]0.719588[/C][C]0.640206[/C][/ROW]
[ROW][C]189[/C][C]0.333076[/C][C]0.666151[/C][C]0.666924[/C][/ROW]
[ROW][C]190[/C][C]0.390507[/C][C]0.781013[/C][C]0.609493[/C][/ROW]
[ROW][C]191[/C][C]0.499013[/C][C]0.998025[/C][C]0.500987[/C][/ROW]
[ROW][C]192[/C][C]0.527782[/C][C]0.944437[/C][C]0.472218[/C][/ROW]
[ROW][C]193[/C][C]0.519285[/C][C]0.961429[/C][C]0.480715[/C][/ROW]
[ROW][C]194[/C][C]0.484074[/C][C]0.968148[/C][C]0.515926[/C][/ROW]
[ROW][C]195[/C][C]0.455027[/C][C]0.910055[/C][C]0.544973[/C][/ROW]
[ROW][C]196[/C][C]0.486729[/C][C]0.973458[/C][C]0.513271[/C][/ROW]
[ROW][C]197[/C][C]0.675795[/C][C]0.648411[/C][C]0.324205[/C][/ROW]
[ROW][C]198[/C][C]0.678828[/C][C]0.642345[/C][C]0.321172[/C][/ROW]
[ROW][C]199[/C][C]0.639745[/C][C]0.72051[/C][C]0.360255[/C][/ROW]
[ROW][C]200[/C][C]0.601231[/C][C]0.797539[/C][C]0.398769[/C][/ROW]
[ROW][C]201[/C][C]0.559378[/C][C]0.881244[/C][C]0.440622[/C][/ROW]
[ROW][C]202[/C][C]0.520849[/C][C]0.958302[/C][C]0.479151[/C][/ROW]
[ROW][C]203[/C][C]0.484744[/C][C]0.969489[/C][C]0.515256[/C][/ROW]
[ROW][C]204[/C][C]0.469728[/C][C]0.939455[/C][C]0.530272[/C][/ROW]
[ROW][C]205[/C][C]0.436832[/C][C]0.873665[/C][C]0.563168[/C][/ROW]
[ROW][C]206[/C][C]0.394351[/C][C]0.788702[/C][C]0.605649[/C][/ROW]
[ROW][C]207[/C][C]0.352754[/C][C]0.705509[/C][C]0.647246[/C][/ROW]
[ROW][C]208[/C][C]0.316939[/C][C]0.633879[/C][C]0.683061[/C][/ROW]
[ROW][C]209[/C][C]0.278518[/C][C]0.557035[/C][C]0.721482[/C][/ROW]
[ROW][C]210[/C][C]0.258939[/C][C]0.517878[/C][C]0.741061[/C][/ROW]
[ROW][C]211[/C][C]0.234092[/C][C]0.468184[/C][C]0.765908[/C][/ROW]
[ROW][C]212[/C][C]0.20198[/C][C]0.403959[/C][C]0.79802[/C][/ROW]
[ROW][C]213[/C][C]0.230858[/C][C]0.461717[/C][C]0.769142[/C][/ROW]
[ROW][C]214[/C][C]0.213861[/C][C]0.427722[/C][C]0.786139[/C][/ROW]
[ROW][C]215[/C][C]0.182924[/C][C]0.365849[/C][C]0.817076[/C][/ROW]
[ROW][C]216[/C][C]0.15552[/C][C]0.311041[/C][C]0.84448[/C][/ROW]
[ROW][C]217[/C][C]0.144927[/C][C]0.289855[/C][C]0.855073[/C][/ROW]
[ROW][C]218[/C][C]0.120244[/C][C]0.240489[/C][C]0.879756[/C][/ROW]
[ROW][C]219[/C][C]0.118809[/C][C]0.237617[/C][C]0.881191[/C][/ROW]
[ROW][C]220[/C][C]0.117604[/C][C]0.235207[/C][C]0.882396[/C][/ROW]
[ROW][C]221[/C][C]0.123974[/C][C]0.247949[/C][C]0.876026[/C][/ROW]
[ROW][C]222[/C][C]0.105596[/C][C]0.211193[/C][C]0.894404[/C][/ROW]
[ROW][C]223[/C][C]0.0852802[/C][C]0.17056[/C][C]0.91472[/C][/ROW]
[ROW][C]224[/C][C]0.0877398[/C][C]0.17548[/C][C]0.91226[/C][/ROW]
[ROW][C]225[/C][C]0.0733579[/C][C]0.146716[/C][C]0.926642[/C][/ROW]
[ROW][C]226[/C][C]0.0593637[/C][C]0.118727[/C][C]0.940636[/C][/ROW]
[ROW][C]227[/C][C]0.0454928[/C][C]0.0909857[/C][C]0.954507[/C][/ROW]
[ROW][C]228[/C][C]0.0538314[/C][C]0.107663[/C][C]0.946169[/C][/ROW]
[ROW][C]229[/C][C]0.0744015[/C][C]0.148803[/C][C]0.925599[/C][/ROW]
[ROW][C]230[/C][C]0.0715804[/C][C]0.143161[/C][C]0.92842[/C][/ROW]
[ROW][C]231[/C][C]0.0554153[/C][C]0.110831[/C][C]0.944585[/C][/ROW]
[ROW][C]232[/C][C]0.051608[/C][C]0.103216[/C][C]0.948392[/C][/ROW]
[ROW][C]233[/C][C]0.103911[/C][C]0.207823[/C][C]0.896089[/C][/ROW]
[ROW][C]234[/C][C]0.112256[/C][C]0.224512[/C][C]0.887744[/C][/ROW]
[ROW][C]235[/C][C]0.109617[/C][C]0.219234[/C][C]0.890383[/C][/ROW]
[ROW][C]236[/C][C]0.086293[/C][C]0.172586[/C][C]0.913707[/C][/ROW]
[ROW][C]237[/C][C]0.123227[/C][C]0.246455[/C][C]0.876773[/C][/ROW]
[ROW][C]238[/C][C]0.166369[/C][C]0.332737[/C][C]0.833631[/C][/ROW]
[ROW][C]239[/C][C]0.273708[/C][C]0.547417[/C][C]0.726292[/C][/ROW]
[ROW][C]240[/C][C]0.271278[/C][C]0.542556[/C][C]0.728722[/C][/ROW]
[ROW][C]241[/C][C]0.226025[/C][C]0.452051[/C][C]0.773975[/C][/ROW]
[ROW][C]242[/C][C]0.275517[/C][C]0.551035[/C][C]0.724483[/C][/ROW]
[ROW][C]243[/C][C]0.215204[/C][C]0.430408[/C][C]0.784796[/C][/ROW]
[ROW][C]244[/C][C]0.161529[/C][C]0.323059[/C][C]0.838471[/C][/ROW]
[ROW][C]245[/C][C]0.221495[/C][C]0.44299[/C][C]0.778505[/C][/ROW]
[ROW][C]246[/C][C]0.238403[/C][C]0.476805[/C][C]0.761597[/C][/ROW]
[ROW][C]247[/C][C]0.173415[/C][C]0.346831[/C][C]0.826585[/C][/ROW]
[ROW][C]248[/C][C]0.218715[/C][C]0.43743[/C][C]0.781285[/C][/ROW]
[ROW][C]249[/C][C]0.214538[/C][C]0.429077[/C][C]0.785462[/C][/ROW]
[ROW][C]250[/C][C]0.195987[/C][C]0.391974[/C][C]0.804013[/C][/ROW]
[ROW][C]251[/C][C]0.223976[/C][C]0.447952[/C][C]0.776024[/C][/ROW]
[ROW][C]252[/C][C]0.880872[/C][C]0.238255[/C][C]0.119128[/C][/ROW]
[ROW][C]253[/C][C]0.794906[/C][C]0.410189[/C][C]0.205094[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226663&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226663&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
110.8546430.2907150.145357
120.9997960.0004070250.000203512
130.9995030.000993920.00049696
140.9988710.002258530.00112926
150.9979170.004166570.00208328
160.9959160.00816770.00408385
170.9927280.01454410.00727207
180.9879830.02403360.0120168
190.9882730.02345350.0117268
200.9810920.03781640.0189082
210.9731060.0537880.026894
220.9618740.07625230.0381261
230.951020.09796040.0489802
240.9310760.1378480.0689239
250.9103060.1793880.089694
260.9619890.07602250.0380113
270.9470670.1058650.0529327
280.9350810.1298380.0649189
290.9212950.1574110.0787054
300.8992930.2014130.100707
310.8990410.2019190.100959
320.8720780.2558450.127922
330.847940.3041190.15206
340.8124830.3750330.187517
350.7724210.4551580.227579
360.7817950.4364110.218205
370.8433960.3132070.156604
380.8097330.3805340.190267
390.7784740.4430520.221526
400.7784870.4430260.221513
410.7659480.4681050.234052
420.7481750.503650.251825
430.8073650.3852710.192635
440.7730930.4538130.226907
450.7360130.5279730.263987
460.7128390.5743210.287161
470.7384240.5231520.261576
480.7028130.5943740.297187
490.7472290.5055420.252771
500.7192790.5614420.280721
510.7055070.5889870.294493
520.6699930.6600140.330007
530.6736730.6526540.326327
540.6317110.7365790.368289
550.6435020.7129960.356498
560.6612750.677450.338725
570.6387930.7224130.361207
580.6703170.6593650.329683
590.6878680.6242630.312132
600.6631360.6737280.336864
610.6754830.6490340.324517
620.6381080.7237850.361892
630.6143030.7713940.385697
640.5728980.8542030.427102
650.5308440.9383120.469156
660.5175260.9649490.482474
670.5437110.9125780.456289
680.5207070.9585850.479293
690.4798220.9596440.520178
700.4519930.9039860.548007
710.4123480.8246970.587652
720.3844340.7688680.615566
730.3517240.7034480.648276
740.3419230.6838460.658077
750.3177070.6354130.682293
760.4507310.9014620.549269
770.4213560.8427120.578644
780.4222220.8444440.577778
790.3843950.768790.615605
800.5128580.9742850.487142
810.4833860.9667730.516614
820.5098750.980250.490125
830.4709780.9419560.529022
840.4344440.8688890.565556
850.3964550.7929090.603545
860.3609060.7218120.639094
870.3321230.6642460.667877
880.2985590.5971170.701441
890.3728720.7457450.627128
900.3441540.6883080.655846
910.3124470.6248950.687553
920.2812310.5624610.718769
930.2692440.5384870.730756
940.245510.491020.75449
950.2174120.4348240.782588
960.1998580.3997160.800142
970.1867290.3734580.813271
980.1627870.3255740.837213
990.1610340.3220680.838966
1000.1414670.2829340.858533
1010.1298310.2596620.870169
1020.1140180.2280350.885982
1030.1468720.2937440.853128
1040.1640880.3281760.835912
1050.1642250.328450.835775
1060.1432650.2865310.856735
1070.1556840.3113670.844316
1080.143620.287240.85638
1090.2412110.4824220.758789
1100.2298420.4596850.770158
1110.203510.407020.79649
1120.1951710.3903410.804829
1130.171550.34310.82845
1140.1549620.3099240.845038
1150.1359820.2719630.864018
1160.1181360.2362710.881864
1170.1040590.2081170.895941
1180.1380940.2761880.861906
1190.1386040.2772070.861396
1200.1211640.2423270.878836
1210.1076450.215290.892355
1220.09406420.1881280.905936
1230.1169620.2339240.883038
1240.1045980.2091960.895402
1250.1005890.2011770.899411
1260.09595180.1919040.904048
1270.08415860.1683170.915841
1280.07505350.1501070.924947
1290.06314110.1262820.936859
1300.06577040.1315410.93423
1310.06501740.1300350.934983
1320.0618860.1237720.938114
1330.0549790.1099580.945021
1340.04607520.09215040.953925
1350.04613730.09227450.953863
1360.09244910.1848980.907551
1370.07842920.1568580.921571
1380.06719360.1343870.932806
1390.06468590.1293720.935314
1400.06337430.1267490.936626
1410.07394760.1478950.926052
1420.07235770.1447150.927642
1430.06103540.1220710.938965
1440.05116630.1023330.948834
1450.04259030.08518070.95741
1460.03515240.07030480.964848
1470.03873830.07747660.961262
1480.04576450.09152890.954236
1490.0417970.0835940.958203
1500.03448830.06897650.965512
1510.03780870.07561730.962191
1520.03984870.07969740.960151
1530.04096670.08193350.959033
1540.03799750.07599510.962002
1550.04286240.08572490.957138
1560.03602480.07204960.963975
1570.02953660.05907330.970463
1580.02522990.05045970.97477
1590.04049990.08099990.9595
1600.04028640.08057290.959714
1610.03394130.06788260.966059
1620.08252010.165040.91748
1630.07182340.1436470.928177
1640.2528840.5057680.747116
1650.2300980.4601960.769902
1660.3112410.6224830.688759
1670.2922490.5844970.707751
1680.2740790.5481580.725921
1690.2468340.4936670.753166
1700.2206980.4413960.779302
1710.2199910.4399820.780009
1720.1947350.3894690.805265
1730.2565270.5130540.743473
1740.2419420.4838840.758058
1750.2213110.4426210.778689
1760.2899380.5798770.710062
1770.2687880.5375770.731212
1780.2693180.5386350.730682
1790.2643510.5287020.735649
1800.2461660.4923320.753834
1810.2716540.5433070.728346
1820.3813310.7626610.618669
1830.3603610.7207230.639639
1840.3638880.7277770.636112
1850.3461090.6922170.653891
1860.4346630.8693260.565337
1870.3969040.7938080.603096
1880.3597940.7195880.640206
1890.3330760.6661510.666924
1900.3905070.7810130.609493
1910.4990130.9980250.500987
1920.5277820.9444370.472218
1930.5192850.9614290.480715
1940.4840740.9681480.515926
1950.4550270.9100550.544973
1960.4867290.9734580.513271
1970.6757950.6484110.324205
1980.6788280.6423450.321172
1990.6397450.720510.360255
2000.6012310.7975390.398769
2010.5593780.8812440.440622
2020.5208490.9583020.479151
2030.4847440.9694890.515256
2040.4697280.9394550.530272
2050.4368320.8736650.563168
2060.3943510.7887020.605649
2070.3527540.7055090.647246
2080.3169390.6338790.683061
2090.2785180.5570350.721482
2100.2589390.5178780.741061
2110.2340920.4681840.765908
2120.201980.4039590.79802
2130.2308580.4617170.769142
2140.2138610.4277220.786139
2150.1829240.3658490.817076
2160.155520.3110410.84448
2170.1449270.2898550.855073
2180.1202440.2404890.879756
2190.1188090.2376170.881191
2200.1176040.2352070.882396
2210.1239740.2479490.876026
2220.1055960.2111930.894404
2230.08528020.170560.91472
2240.08773980.175480.91226
2250.07335790.1467160.926642
2260.05936370.1187270.940636
2270.04549280.09098570.954507
2280.05383140.1076630.946169
2290.07440150.1488030.925599
2300.07158040.1431610.92842
2310.05541530.1108310.944585
2320.0516080.1032160.948392
2330.1039110.2078230.896089
2340.1122560.2245120.887744
2350.1096170.2192340.890383
2360.0862930.1725860.913707
2370.1232270.2464550.876773
2380.1663690.3327370.833631
2390.2737080.5474170.726292
2400.2712780.5425560.728722
2410.2260250.4520510.773975
2420.2755170.5510350.724483
2430.2152040.4304080.784796
2440.1615290.3230590.838471
2450.2214950.442990.778505
2460.2384030.4768050.761597
2470.1734150.3468310.826585
2480.2187150.437430.781285
2490.2145380.4290770.785462
2500.1959870.3919740.804013
2510.2239760.4479520.776024
2520.8808720.2382550.119128
2530.7949060.4101890.205094






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level50.0205761NOK
5% type I error level90.037037OK
10% type I error level330.135802NOK

\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 & 5 & 0.0205761 & NOK \tabularnewline
5% type I error level & 9 & 0.037037 & OK \tabularnewline
10% type I error level & 33 & 0.135802 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226663&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]5[/C][C]0.0205761[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]9[/C][C]0.037037[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]33[/C][C]0.135802[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226663&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226663&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 level50.0205761NOK
5% type I error level90.037037OK
10% type I error level330.135802NOK


Figures (Output of Computation)

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