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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 08 Dec 2013 18:06:23 -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/Dec/08/t1386544117h1dokixkthpxuzz.htm/, Retrieved Thu, 28 Mar 2024 11:52:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231545, Retrieved Thu, 28 Mar 2024 11:52:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact33
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [WS10: Perceived L...] [2013-12-08 23:06:23] [cb725e3dac64282bf746e0e2ee8aee47] [Current]
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Dataseries X:
14 12 13 38 41 1 1
18 11 16 32 39 1 1
11 15 19 35 30 1 1
12 6 15 33 31 0 1
16 13 14 37 34 1 1
18 10 13 29 35 1 1
14 12 19 31 39 1 1
14 14 15 36 34 1 1
15 12 14 35 36 1 1
15 9 15 38 37 1 1
17 10 16 31 38 0 1
19 12 16 34 36 1 1
10 12 16 35 38 0 1
16 11 16 38 39 1 1
18 15 17 37 33 1 1
14 12 15 33 32 0 1
14 10 15 32 36 0 1
17 12 20 38 38 1 1
14 11 18 38 39 0 1
16 12 16 32 32 1 1
18 11 16 33 32 0 1
11 12 16 31 31 1 1
14 13 19 38 39 1 1
12 11 16 39 37 1 1
17 12 17 32 39 0 1
9 13 17 32 41 1 1
16 10 16 35 36 0 1
14 14 15 37 33 1 1
15 12 16 33 33 1 1
11 10 14 33 34 0 1
16 12 15 31 31 1 1
13 8 12 32 27 0 1
17 10 14 31 37 1 1
15 12 16 37 34 1 1
14 12 14 30 34 0 1
16 7 10 33 32 0 1
9 9 10 31 29 0 1
15 12 14 33 36 0 1
17 10 16 31 29 1 1
13 10 16 33 35 0 1
15 10 16 32 37 0 1
16 12 14 33 34 1 1
16 15 20 32 38 0 1
12 10 14 33 35 0 1
15 10 14 28 38 1 1
11 12 11 35 37 1 1
15 13 14 39 38 1 1
15 11 15 34 33 1 1
17 11 16 38 36 1 1
13 12 14 32 38 0 1
16 14 16 38 32 1 1
14 10 14 30 32 0 1
11 12 12 33 32 0 1
12 13 16 38 34 1 1
12 5 9 32 32 0 1
15 6 14 35 37 1 1
16 12 16 34 39 1 1
15 12 16 34 29 1 1
12 11 15 36 37 0 1
12 10 16 34 35 1 1
8 7 12 28 30 0 1
13 12 16 34 38 0 1
11 14 16 35 34 1 1
14 11 14 35 31 1 1
15 12 16 31 34 1 1
10 13 17 37 35 0 1
11 14 18 35 36 1 1
12 11 18 27 30 0 1
15 12 12 40 39 1 1
15 12 16 37 35 0 1
14 8 10 36 38 0 1
16 11 14 38 31 1 1
15 14 18 39 34 1 1
15 14 18 41 38 0 1
13 12 16 27 34 0 1
12 9 17 30 39 1 1
17 13 16 37 37 1 1
13 11 16 31 34 1 1
15 12 13 31 28 0 1
13 12 16 27 37 0 1
15 12 16 36 33 0 1
15 12 16 37 35 1 1
16 12 15 33 37 0 1
15 11 15 34 32 1 1
14 10 16 31 33 1 1
15 9 14 39 38 0 1
14 12 16 34 33 1 1
13 12 16 32 29 1 1
7 12 15 33 33 1 1
17 9 12 36 31 1 1
13 15 17 32 36 1 1
15 12 16 41 35 1 1
14 12 15 28 32 1 1
13 12 13 30 29 1 1
16 10 16 36 39 1 1
12 13 16 35 37 1 1
14 9 16 31 35 1 1
17 12 16 34 37 0 1
15 10 14 36 32 0 1
17 14 16 36 38 1 1
12 11 16 35 37 0 1
16 15 20 37 36 1 1
11 11 15 28 32 0 1
15 11 16 39 33 1 1
9 12 13 32 40 0 1
16 12 17 35 38 1 1
15 12 16 39 41 0 1
10 11 16 35 36 0 1
10 7 12 42 43 1 1
15 12 16 34 30 1 1
11 14 16 33 31 1 1
13 11 17 41 32 1 1
18 10 12 34 37 1 1
16 13 18 32 37 0 1
14 13 14 40 33 1 1
14 8 14 40 34 1 1
14 11 13 35 33 1 1
14 12 16 36 38 1 1
12 11 13 37 33 0 1
14 13 16 27 31 1 1
15 12 13 39 38 1 1
15 14 16 38 37 1 1
15 13 15 31 36 1 1
13 15 16 33 31 1 1
17 10 15 32 39 0 1
17 11 17 39 44 1 1
19 9 15 36 33 1 1
15 11 12 33 35 1 1
13 10 16 33 32 0 1
9 11 10 32 28 0 1
15 8 16 37 40 1 1
15 11 12 30 27 0 1
15 12 14 38 37 0 1
16 12 15 29 32 1 1
11 9 13 22 28 0 1
14 11 15 35 34 0 1
11 10 11 35 30 1 1
15 8 12 34 35 1 1
13 9 11 35 31 0 1
15 8 16 34 32 1 1
16 9 15 37 30 0 1
14 15 17 35 30 1 1
15 11 16 23 31 0 1
16 8 10 31 40 1 1
16 13 18 27 32 1 1
11 12 13 36 36 0 1
12 12 16 31 32 0 1
9 9 13 32 35 0 1
16 7 10 39 38 1 1
13 13 15 37 42 1 1
16 9 16 38 34 0 1
12 6 16 39 35 1 1
9 8 14 34 38 1 1
13 8 10 31 33 1 1
14 6 13 37 32 1 1
19 9 15 36 33 1 1
13 11 16 32 34 1 1
12 8 12 38 32 1 1
10 10 13 26 27 0 0
14 8 12 26 31 0 0
16 14 17 33 38 0 0
10 10 15 39 34 1 0
11 8 10 30 24 0 0
14 11 14 33 30 0 0
12 12 11 25 26 1 0
9 12 13 38 34 1 0
9 12 16 37 27 0 0
11 5 12 31 37 0 0
16 12 16 37 36 1 0
9 10 12 35 41 0 0
13 7 9 25 29 1 0
16 12 12 28 36 1 0
13 11 15 35 32 0 0
9 8 12 33 37 1 0
12 9 12 30 30 0 0
16 10 14 31 31 1 0
11 9 12 37 38 1 0
14 12 16 36 36 1 0
13 6 11 30 35 0 0
15 15 19 36 31 0 0
14 12 15 32 38 0 0
16 12 8 28 22 1 0
13 12 16 36 32 1 0
14 11 17 34 36 0 0
15 7 12 31 39 1 0
13 7 11 28 28 0 0
11 5 11 36 32 0 0
11 12 14 36 32 1 0
14 12 16 40 38 1 0
15 3 12 33 32 1 0
11 11 16 37 35 1 0
15 10 13 32 32 1 0
12 12 15 38 37 0 0
14 9 16 31 34 1 0
14 12 16 37 33 1 0
8 9 14 33 33 0 0
9 12 16 30 30 0 0
15 10 14 30 24 0 0
17 9 11 31 34 0 0
13 12 12 32 34 0 0
15 8 15 34 33 1 0
15 11 15 36 34 1 0
14 11 16 37 35 1 0
16 12 16 36 35 0 0
13 10 11 33 36 0 0
16 10 15 33 34 0 0
9 12 12 33 34 1 0
16 12 12 44 41 0 0
11 11 15 39 32 0 0
10 8 15 32 30 0 0
11 12 16 35 35 1 0
15 10 14 25 28 0 0
17 11 17 35 33 1 0
14 10 14 34 39 1 0
8 8 13 35 36 0 0
15 12 15 39 36 1 0
11 12 13 33 35 0 0
16 10 14 36 38 0 0
10 12 15 32 33 1 0
15 9 12 32 31 0 0
16 6 8 36 32 1 0
19 10 14 32 31 0 0
12 9 14 34 33 0 0
8 9 11 33 34 0 0
11 9 12 35 34 0 0
14 6 13 30 34 1 0
9 10 10 38 33 0 0
15 6 16 34 32 0 0
13 14 18 33 41 1 0
16 10 13 32 34 1 0
11 10 11 31 36 0 0
12 6 4 30 37 0 0
13 12 13 27 36 0 0
10 12 16 31 29 1 0
11 7 10 30 37 0 0
12 8 12 32 27 0 0
8 11 12 35 35 0 0
12 3 10 28 28 0 0
12 6 13 33 35 0 0
11 8 12 35 29 0 0
13 9 14 35 32 0 0
14 9 10 32 36 1 0
10 8 12 21 19 1 0
12 9 12 20 21 1 0
15 7 11 34 31 0 0
13 7 10 32 33 0 0
13 6 12 34 36 1 0
13 9 16 32 33 1 0
12 10 12 33 37 0 0
12 11 14 33 34 0 0
9 12 16 37 35 0 0
9 8 14 32 31 1 0
15 11 13 34 37 1 0
10 3 4 30 35 1 0
14 11 15 30 27 1 0
15 12 11 38 34 0 0
7 7 11 36 40 0 0
14 9 14 32 29 0 0
8 12 15 34 38 0 0
10 8 14 33 34 1 0
13 11 13 27 21 0 0
13 8 11 32 36 0 0
13 10 15 34 38 1 0
8 8 11 29 30 0 0
12 7 13 35 35 0 0
13 8 13 27 30 1 0
12 10 16 33 36 1 0
10 8 13 38 34 0 0
13 12 16 36 35 1 0
12 14 16 33 34 0 0
9 7 12 39 32 0 0
15 6 7 29 33 1 0
13 11 16 32 33 0 0
13 4 5 34 26 1 0
13 9 16 38 35 0 0
15 5 4 17 21 0 0
15 9 12 35 38 0 0
14 11 15 32 35 0 0
15 12 14 34 33 1 0
11 9 11 36 37 0 0
15 12 16 31 38 0 0
14 10 15 35 34 1 0
13 9 12 29 27 0 0
12 6 6 22 16 1 0
16 10 16 41 40 0 0
16 9 10 36 36 0 0
9 13 15 42 42 1 0
14 12 14 33 30 1 0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time26 seconds
R Server'George Udny Yule' @ yule.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 & 26 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231545&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]26 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231545&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231545&T=0

As an alternative you can also use a 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 time26 seconds
R Server'George Udny Yule' @ yule.wessa.net







Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 10.5668 -0.0160952Software[t] + 0.118947Learning[t] -0.0159941Separate[t] + 0.027303Connected[t] + 0.790352Gender[t] + 0.998144Pop[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  10.5668 -0.0160952Software[t] +  0.118947Learning[t] -0.0159941Separate[t] +  0.027303Connected[t] +  0.790352Gender[t] +  0.998144Pop[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231545&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  10.5668 -0.0160952Software[t] +  0.118947Learning[t] -0.0159941Separate[t] +  0.027303Connected[t] +  0.790352Gender[t] +  0.998144Pop[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231545&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231545&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 10.5668 -0.0160952Software[t] + 0.118947Learning[t] -0.0159941Separate[t] + 0.027303Connected[t] + 0.790352Gender[t] + 0.998144Pop[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)10.56681.42817.3991.59129e-127.95643e-13
Software-0.01609520.0793879-0.20270.8394840.419742
Learning0.1189470.07405941.6060.1093730.0546867
Separate-0.01599410.0429532-0.37240.7099050.354953
Connected0.0273030.04130290.6610.5091270.254563
Gender0.7903520.2886972.7380.006582840.00329142
Pop0.9981440.3079843.2410.001334930.000667467

\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) & 10.5668 & 1.4281 & 7.399 & 1.59129e-12 & 7.95643e-13 \tabularnewline
Software & -0.0160952 & 0.0793879 & -0.2027 & 0.839484 & 0.419742 \tabularnewline
Learning & 0.118947 & 0.0740594 & 1.606 & 0.109373 & 0.0546867 \tabularnewline
Separate & -0.0159941 & 0.0429532 & -0.3724 & 0.709905 & 0.354953 \tabularnewline
Connected & 0.027303 & 0.0413029 & 0.661 & 0.509127 & 0.254563 \tabularnewline
Gender & 0.790352 & 0.288697 & 2.738 & 0.00658284 & 0.00329142 \tabularnewline
Pop & 0.998144 & 0.307984 & 3.241 & 0.00133493 & 0.000667467 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231545&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]10.5668[/C][C]1.4281[/C][C]7.399[/C][C]1.59129e-12[/C][C]7.95643e-13[/C][/ROW]
[ROW][C]Software[/C][C]-0.0160952[/C][C]0.0793879[/C][C]-0.2027[/C][C]0.839484[/C][C]0.419742[/C][/ROW]
[ROW][C]Learning[/C][C]0.118947[/C][C]0.0740594[/C][C]1.606[/C][C]0.109373[/C][C]0.0546867[/C][/ROW]
[ROW][C]Separate[/C][C]-0.0159941[/C][C]0.0429532[/C][C]-0.3724[/C][C]0.709905[/C][C]0.354953[/C][/ROW]
[ROW][C]Connected[/C][C]0.027303[/C][C]0.0413029[/C][C]0.661[/C][C]0.509127[/C][C]0.254563[/C][/ROW]
[ROW][C]Gender[/C][C]0.790352[/C][C]0.288697[/C][C]2.738[/C][C]0.00658284[/C][C]0.00329142[/C][/ROW]
[ROW][C]Pop[/C][C]0.998144[/C][C]0.307984[/C][C]3.241[/C][C]0.00133493[/C][C]0.000667467[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231545&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231545&T=2

As an alternative you can also use a 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)10.56681.42817.3991.59129e-127.95643e-13
Software-0.01609520.0793879-0.20270.8394840.419742
Learning0.1189470.07405941.6060.1093730.0546867
Separate-0.01599410.0429532-0.37240.7099050.354953
Connected0.0273030.04130290.6610.5091270.254563
Gender0.7903520.2886972.7380.006582840.00329142
Pop0.9981440.3079843.2410.001334930.000667467







Multiple Linear Regression - Regression Statistics
Multiple R0.341681
R-squared0.116746
Adjusted R-squared0.0978865
F-TEST (value)6.1903
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value4.06812e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.36852
Sum Squared Residuals1576.38

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.341681 \tabularnewline
R-squared & 0.116746 \tabularnewline
Adjusted R-squared & 0.0978865 \tabularnewline
F-TEST (value) & 6.1903 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 281 \tabularnewline
p-value & 4.06812e-06 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.36852 \tabularnewline
Sum Squared Residuals & 1576.38 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231545&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.341681[/C][/ROW]
[ROW][C]R-squared[/C][C]0.116746[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0978865[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]6.1903[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]281[/C][/ROW]
[ROW][C]p-value[/C][C]4.06812e-06[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.36852[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1576.38[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231545&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231545&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.341681
R-squared0.116746
Adjusted R-squared0.0978865
F-TEST (value)6.1903
F-TEST (DF numerator)6
F-TEST (DF denominator)281
p-value4.06812e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.36852
Sum Squared Residuals1576.38







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.2201-0.220102
21814.63443.3656
31114.6332-3.63315
41213.5712-1.57116
51614.14781.85217
61814.23243.76758
71414.9911-0.991139
81414.2667-0.266674
91514.25050.749483
101514.39710.602929
111713.84883.15117
121914.50444.49559
131013.7527-3.75267
141614.53841.46157
151814.44523.55482
161413.50190.498111
171413.65930.340715
181714.97082.02918
191413.9860.0140234
201614.42721.57282
211813.63694.36307
221114.4159-3.41587
231414.8631-0.863085
241214.4678-2.46783
251713.94693.0531
26914.7758-5.77576
271613.73032.26975
281414.2234-0.223377
291514.43850.561509
301113.4697-2.46974
311614.29691.70307
321313.0889-0.0889064
331714.3742.62601
341514.40180.598182
351413.48550.514471
361612.98763.01237
37912.9055-3.90552
381513.49221.50785
391714.39352.60654
401313.7349-0.734935
411513.80551.19446
421614.22791.7721
431614.22821.77185
441213.497-1.49704
451514.44930.550728
461113.921-2.92098
471514.22510.774949
481514.31960.680355
491714.45652.54348
501313.5628-0.562753
511614.2991.70097
521413.46310.536886
531113.145-2.14505
541214.3697-2.36973
551212.9169-0.916865
561514.37440.625609
571614.58631.41369
581514.31330.686715
591213.6065-1.60652
601214.5093-2.50929
61813.2509-5.25089
621313.7687-0.76866
631114.4016-3.40162
641414.1301-0.130097
651514.49780.502218
661013.7416-3.74162
671114.6941-3.69412
681213.9162-1.91618
691514.01460.985439
701513.63881.36123
711413.08740.912632
721614.08211.91789
731514.57550.424466
741513.86241.13759
751313.7714-0.771406
761214.8175-2.81752
771714.46762.53237
781314.5139-1.51388
791513.18681.81323
801313.8533-0.853315
811513.60021.39984
821514.42910.570879
831613.63842.3616
841514.29230.707658
851414.5027-0.502669
861513.49911.50092
871414.4225-0.422497
881314.3453-1.34527
89714.3195-7.31954
901713.90843.0916
911314.6071-1.60706
921514.36510.634856
931414.3722-0.372211
941314.0204-1.02042
951614.58651.41348
961214.4996-2.49962
971414.5734-0.57337
981713.74143.25864
991513.36711.63285
1001714.49482.50517
1011213.7415-1.74146
1021614.88391.11607
1031113.598-2.59795
1041514.35860.641378
105913.4984-4.49841
1061614.6621.33803
1071513.77061.2294
1081013.7142-3.71416
1091014.1723-4.17226
1101514.34060.659412
1111114.3517-3.35169
1121314.4183-1.41828
1131814.08813.91189
1141613.99512.00486
1151414.0725-0.0725424
1161414.1803-0.180321
1171414.0658-0.0657558
1181414.527-0.527024
1191213.2434-1.24342
1201414.4638-0.463754
1211514.12220.877801
1221514.43550.564458
1231514.41730.582655
1241314.3356-1.3356
1251713.74123.25881
1261714.77792.2221
1271914.31984.68015
1281514.03340.966597
1291313.653-0.653026
130912.83-3.83003
1311514.630.369984
1321513.07261.92739
1331513.43951.56051
1341614.35621.64378
1351113.379-2.379
1361413.54060.459398
1371113.762-2.76205
1381514.06570.934306
1391313.0151-0.0150936
1401514.45960.540426
1411613.43162.56841
1421414.3953-0.395256
1431513.76961.23043
1441614.01231.9877
1451614.7291.27105
1461113.3252-2.32522
1471213.6528-1.65282
148913.4102-4.41018
1491613.84582.15417
1501314.4852-1.4852
1511613.64382.35624
1521214.4937-2.4937
153914.3855-5.3855
1541313.8212-0.821175
1551414.0869-0.0869406
1561914.31984.68015
1571314.4979-1.49788
1581213.9198-1.91981
1591012.2735-2.27348
1601412.29591.70406
1611612.87333.12673
1621013.2849-3.28493
1631111.8029-0.802947
1641412.34631.65371
1651212.7824-0.782441
166913.0308-4.03084
167912.4222-3.4222
1681112.4281-1.42807
1691613.45832.54172
170912.3928-3.39283
1711312.70690.293069
1721613.12642.87356
1731312.48790.512149
174913.1381-4.13815
1751212.1886-0.188564
1761613.2122.78798
1771113.0854-2.08538
1781413.47430.525727
1791312.25440.745583
1801512.8562.14404
1811412.68361.31644
1821612.26843.7316
1831313.3651-0.365061
1841412.8511.14905
1851513.24081.75916
1861312.07920.920811
1871112.0926-1.09264
1881113.1272-2.12717
1891413.46490.535097
1901513.08211.91789
1911113.4471-2.44707
1921513.10441.89561
1931212.5603-0.560289
1941413.54790.452077
1951413.37640.62363
196812.4604-4.46039
197912.6161-3.61607
1981512.24652.75345
1991712.16284.83717
2001312.21750.782498
2011513.36981.63021
2021513.31681.68318
2031413.44710.552929
2041612.65663.34338
2051312.16940.830643
2061612.59053.40946
207912.9919-3.99186
2081612.21673.78331
2091112.4239-1.42388
2101012.5295-2.52951
2111113.463-2.46296
2121512.43572.56427
2131713.54343.4566
2141413.38250.617534
215812.4075-4.40745
2161513.30731.69266
2171112.3478-1.34776
2181612.53283.46718
2191013.3374-3.33739
2201512.18392.81612
2211612.51013.48995
2221912.40576.59432
2231212.4444-0.444391
224812.1308-4.13085
2251112.2178-1.21781
2261413.25540.744639
227911.8885-2.88853
2281512.70332.29673
2291313.8645-0.864475
2301613.1592.84101
2311112.2013-1.20135
2321211.47640.523608
2331312.4710.528974
2341013.3631-3.36312
2351112.174-1.17398
2361212.0908-0.0907621
237812.2129-4.21292
2381212.0246-0.0246226
2391212.4443-0.44433
2401112.0974-1.09739
2411312.40110.598906
2421412.87291.12715
2431012.8386-2.83862
2441212.8931-0.89313
2451512.06512.93487
2461312.03280.967219
2471313.127-0.127043
2481313.5046-0.504626
2491212.3156-0.315608
2501212.4555-0.455498
251912.6406-3.64062
252913.2282-4.22822
2531513.19281.80718
2541012.2604-2.26042
2551413.22170.778341
2561512.00262.99741
257712.2789-5.27887
2581412.36721.63283
259812.6516-4.65157
2601013.2941-3.29414
2611312.07760.922424
2621312.21750.782458
2631313.4741-0.47411
264812.1017-4.10171
2651212.3962-0.396246
2661313.1619-0.161941
2671213.5544-1.55445
2681012.3049-2.30487
2691313.447-0.44697
2701212.6451-0.645107
271912.1314-3.13141
2721512.53042.46963
2731312.68210.317916
2741312.05360.946428
2751312.67290.327084
2761511.26363.73644
2771512.3272.67298
2781412.61771.38226
2791513.18651.81354
2801112.1648-1.16477
2811512.81852.1815
2821413.34890.651096
2831312.12260.877351
2841212.0592-0.0592278
2851612.74543.25465
2861612.01853.98148
287913.4071-4.40708
2881413.12050.879457

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 14.2201 & -0.220102 \tabularnewline
2 & 18 & 14.6344 & 3.3656 \tabularnewline
3 & 11 & 14.6332 & -3.63315 \tabularnewline
4 & 12 & 13.5712 & -1.57116 \tabularnewline
5 & 16 & 14.1478 & 1.85217 \tabularnewline
6 & 18 & 14.2324 & 3.76758 \tabularnewline
7 & 14 & 14.9911 & -0.991139 \tabularnewline
8 & 14 & 14.2667 & -0.266674 \tabularnewline
9 & 15 & 14.2505 & 0.749483 \tabularnewline
10 & 15 & 14.3971 & 0.602929 \tabularnewline
11 & 17 & 13.8488 & 3.15117 \tabularnewline
12 & 19 & 14.5044 & 4.49559 \tabularnewline
13 & 10 & 13.7527 & -3.75267 \tabularnewline
14 & 16 & 14.5384 & 1.46157 \tabularnewline
15 & 18 & 14.4452 & 3.55482 \tabularnewline
16 & 14 & 13.5019 & 0.498111 \tabularnewline
17 & 14 & 13.6593 & 0.340715 \tabularnewline
18 & 17 & 14.9708 & 2.02918 \tabularnewline
19 & 14 & 13.986 & 0.0140234 \tabularnewline
20 & 16 & 14.4272 & 1.57282 \tabularnewline
21 & 18 & 13.6369 & 4.36307 \tabularnewline
22 & 11 & 14.4159 & -3.41587 \tabularnewline
23 & 14 & 14.8631 & -0.863085 \tabularnewline
24 & 12 & 14.4678 & -2.46783 \tabularnewline
25 & 17 & 13.9469 & 3.0531 \tabularnewline
26 & 9 & 14.7758 & -5.77576 \tabularnewline
27 & 16 & 13.7303 & 2.26975 \tabularnewline
28 & 14 & 14.2234 & -0.223377 \tabularnewline
29 & 15 & 14.4385 & 0.561509 \tabularnewline
30 & 11 & 13.4697 & -2.46974 \tabularnewline
31 & 16 & 14.2969 & 1.70307 \tabularnewline
32 & 13 & 13.0889 & -0.0889064 \tabularnewline
33 & 17 & 14.374 & 2.62601 \tabularnewline
34 & 15 & 14.4018 & 0.598182 \tabularnewline
35 & 14 & 13.4855 & 0.514471 \tabularnewline
36 & 16 & 12.9876 & 3.01237 \tabularnewline
37 & 9 & 12.9055 & -3.90552 \tabularnewline
38 & 15 & 13.4922 & 1.50785 \tabularnewline
39 & 17 & 14.3935 & 2.60654 \tabularnewline
40 & 13 & 13.7349 & -0.734935 \tabularnewline
41 & 15 & 13.8055 & 1.19446 \tabularnewline
42 & 16 & 14.2279 & 1.7721 \tabularnewline
43 & 16 & 14.2282 & 1.77185 \tabularnewline
44 & 12 & 13.497 & -1.49704 \tabularnewline
45 & 15 & 14.4493 & 0.550728 \tabularnewline
46 & 11 & 13.921 & -2.92098 \tabularnewline
47 & 15 & 14.2251 & 0.774949 \tabularnewline
48 & 15 & 14.3196 & 0.680355 \tabularnewline
49 & 17 & 14.4565 & 2.54348 \tabularnewline
50 & 13 & 13.5628 & -0.562753 \tabularnewline
51 & 16 & 14.299 & 1.70097 \tabularnewline
52 & 14 & 13.4631 & 0.536886 \tabularnewline
53 & 11 & 13.145 & -2.14505 \tabularnewline
54 & 12 & 14.3697 & -2.36973 \tabularnewline
55 & 12 & 12.9169 & -0.916865 \tabularnewline
56 & 15 & 14.3744 & 0.625609 \tabularnewline
57 & 16 & 14.5863 & 1.41369 \tabularnewline
58 & 15 & 14.3133 & 0.686715 \tabularnewline
59 & 12 & 13.6065 & -1.60652 \tabularnewline
60 & 12 & 14.5093 & -2.50929 \tabularnewline
61 & 8 & 13.2509 & -5.25089 \tabularnewline
62 & 13 & 13.7687 & -0.76866 \tabularnewline
63 & 11 & 14.4016 & -3.40162 \tabularnewline
64 & 14 & 14.1301 & -0.130097 \tabularnewline
65 & 15 & 14.4978 & 0.502218 \tabularnewline
66 & 10 & 13.7416 & -3.74162 \tabularnewline
67 & 11 & 14.6941 & -3.69412 \tabularnewline
68 & 12 & 13.9162 & -1.91618 \tabularnewline
69 & 15 & 14.0146 & 0.985439 \tabularnewline
70 & 15 & 13.6388 & 1.36123 \tabularnewline
71 & 14 & 13.0874 & 0.912632 \tabularnewline
72 & 16 & 14.0821 & 1.91789 \tabularnewline
73 & 15 & 14.5755 & 0.424466 \tabularnewline
74 & 15 & 13.8624 & 1.13759 \tabularnewline
75 & 13 & 13.7714 & -0.771406 \tabularnewline
76 & 12 & 14.8175 & -2.81752 \tabularnewline
77 & 17 & 14.4676 & 2.53237 \tabularnewline
78 & 13 & 14.5139 & -1.51388 \tabularnewline
79 & 15 & 13.1868 & 1.81323 \tabularnewline
80 & 13 & 13.8533 & -0.853315 \tabularnewline
81 & 15 & 13.6002 & 1.39984 \tabularnewline
82 & 15 & 14.4291 & 0.570879 \tabularnewline
83 & 16 & 13.6384 & 2.3616 \tabularnewline
84 & 15 & 14.2923 & 0.707658 \tabularnewline
85 & 14 & 14.5027 & -0.502669 \tabularnewline
86 & 15 & 13.4991 & 1.50092 \tabularnewline
87 & 14 & 14.4225 & -0.422497 \tabularnewline
88 & 13 & 14.3453 & -1.34527 \tabularnewline
89 & 7 & 14.3195 & -7.31954 \tabularnewline
90 & 17 & 13.9084 & 3.0916 \tabularnewline
91 & 13 & 14.6071 & -1.60706 \tabularnewline
92 & 15 & 14.3651 & 0.634856 \tabularnewline
93 & 14 & 14.3722 & -0.372211 \tabularnewline
94 & 13 & 14.0204 & -1.02042 \tabularnewline
95 & 16 & 14.5865 & 1.41348 \tabularnewline
96 & 12 & 14.4996 & -2.49962 \tabularnewline
97 & 14 & 14.5734 & -0.57337 \tabularnewline
98 & 17 & 13.7414 & 3.25864 \tabularnewline
99 & 15 & 13.3671 & 1.63285 \tabularnewline
100 & 17 & 14.4948 & 2.50517 \tabularnewline
101 & 12 & 13.7415 & -1.74146 \tabularnewline
102 & 16 & 14.8839 & 1.11607 \tabularnewline
103 & 11 & 13.598 & -2.59795 \tabularnewline
104 & 15 & 14.3586 & 0.641378 \tabularnewline
105 & 9 & 13.4984 & -4.49841 \tabularnewline
106 & 16 & 14.662 & 1.33803 \tabularnewline
107 & 15 & 13.7706 & 1.2294 \tabularnewline
108 & 10 & 13.7142 & -3.71416 \tabularnewline
109 & 10 & 14.1723 & -4.17226 \tabularnewline
110 & 15 & 14.3406 & 0.659412 \tabularnewline
111 & 11 & 14.3517 & -3.35169 \tabularnewline
112 & 13 & 14.4183 & -1.41828 \tabularnewline
113 & 18 & 14.0881 & 3.91189 \tabularnewline
114 & 16 & 13.9951 & 2.00486 \tabularnewline
115 & 14 & 14.0725 & -0.0725424 \tabularnewline
116 & 14 & 14.1803 & -0.180321 \tabularnewline
117 & 14 & 14.0658 & -0.0657558 \tabularnewline
118 & 14 & 14.527 & -0.527024 \tabularnewline
119 & 12 & 13.2434 & -1.24342 \tabularnewline
120 & 14 & 14.4638 & -0.463754 \tabularnewline
121 & 15 & 14.1222 & 0.877801 \tabularnewline
122 & 15 & 14.4355 & 0.564458 \tabularnewline
123 & 15 & 14.4173 & 0.582655 \tabularnewline
124 & 13 & 14.3356 & -1.3356 \tabularnewline
125 & 17 & 13.7412 & 3.25881 \tabularnewline
126 & 17 & 14.7779 & 2.2221 \tabularnewline
127 & 19 & 14.3198 & 4.68015 \tabularnewline
128 & 15 & 14.0334 & 0.966597 \tabularnewline
129 & 13 & 13.653 & -0.653026 \tabularnewline
130 & 9 & 12.83 & -3.83003 \tabularnewline
131 & 15 & 14.63 & 0.369984 \tabularnewline
132 & 15 & 13.0726 & 1.92739 \tabularnewline
133 & 15 & 13.4395 & 1.56051 \tabularnewline
134 & 16 & 14.3562 & 1.64378 \tabularnewline
135 & 11 & 13.379 & -2.379 \tabularnewline
136 & 14 & 13.5406 & 0.459398 \tabularnewline
137 & 11 & 13.762 & -2.76205 \tabularnewline
138 & 15 & 14.0657 & 0.934306 \tabularnewline
139 & 13 & 13.0151 & -0.0150936 \tabularnewline
140 & 15 & 14.4596 & 0.540426 \tabularnewline
141 & 16 & 13.4316 & 2.56841 \tabularnewline
142 & 14 & 14.3953 & -0.395256 \tabularnewline
143 & 15 & 13.7696 & 1.23043 \tabularnewline
144 & 16 & 14.0123 & 1.9877 \tabularnewline
145 & 16 & 14.729 & 1.27105 \tabularnewline
146 & 11 & 13.3252 & -2.32522 \tabularnewline
147 & 12 & 13.6528 & -1.65282 \tabularnewline
148 & 9 & 13.4102 & -4.41018 \tabularnewline
149 & 16 & 13.8458 & 2.15417 \tabularnewline
150 & 13 & 14.4852 & -1.4852 \tabularnewline
151 & 16 & 13.6438 & 2.35624 \tabularnewline
152 & 12 & 14.4937 & -2.4937 \tabularnewline
153 & 9 & 14.3855 & -5.3855 \tabularnewline
154 & 13 & 13.8212 & -0.821175 \tabularnewline
155 & 14 & 14.0869 & -0.0869406 \tabularnewline
156 & 19 & 14.3198 & 4.68015 \tabularnewline
157 & 13 & 14.4979 & -1.49788 \tabularnewline
158 & 12 & 13.9198 & -1.91981 \tabularnewline
159 & 10 & 12.2735 & -2.27348 \tabularnewline
160 & 14 & 12.2959 & 1.70406 \tabularnewline
161 & 16 & 12.8733 & 3.12673 \tabularnewline
162 & 10 & 13.2849 & -3.28493 \tabularnewline
163 & 11 & 11.8029 & -0.802947 \tabularnewline
164 & 14 & 12.3463 & 1.65371 \tabularnewline
165 & 12 & 12.7824 & -0.782441 \tabularnewline
166 & 9 & 13.0308 & -4.03084 \tabularnewline
167 & 9 & 12.4222 & -3.4222 \tabularnewline
168 & 11 & 12.4281 & -1.42807 \tabularnewline
169 & 16 & 13.4583 & 2.54172 \tabularnewline
170 & 9 & 12.3928 & -3.39283 \tabularnewline
171 & 13 & 12.7069 & 0.293069 \tabularnewline
172 & 16 & 13.1264 & 2.87356 \tabularnewline
173 & 13 & 12.4879 & 0.512149 \tabularnewline
174 & 9 & 13.1381 & -4.13815 \tabularnewline
175 & 12 & 12.1886 & -0.188564 \tabularnewline
176 & 16 & 13.212 & 2.78798 \tabularnewline
177 & 11 & 13.0854 & -2.08538 \tabularnewline
178 & 14 & 13.4743 & 0.525727 \tabularnewline
179 & 13 & 12.2544 & 0.745583 \tabularnewline
180 & 15 & 12.856 & 2.14404 \tabularnewline
181 & 14 & 12.6836 & 1.31644 \tabularnewline
182 & 16 & 12.2684 & 3.7316 \tabularnewline
183 & 13 & 13.3651 & -0.365061 \tabularnewline
184 & 14 & 12.851 & 1.14905 \tabularnewline
185 & 15 & 13.2408 & 1.75916 \tabularnewline
186 & 13 & 12.0792 & 0.920811 \tabularnewline
187 & 11 & 12.0926 & -1.09264 \tabularnewline
188 & 11 & 13.1272 & -2.12717 \tabularnewline
189 & 14 & 13.4649 & 0.535097 \tabularnewline
190 & 15 & 13.0821 & 1.91789 \tabularnewline
191 & 11 & 13.4471 & -2.44707 \tabularnewline
192 & 15 & 13.1044 & 1.89561 \tabularnewline
193 & 12 & 12.5603 & -0.560289 \tabularnewline
194 & 14 & 13.5479 & 0.452077 \tabularnewline
195 & 14 & 13.3764 & 0.62363 \tabularnewline
196 & 8 & 12.4604 & -4.46039 \tabularnewline
197 & 9 & 12.6161 & -3.61607 \tabularnewline
198 & 15 & 12.2465 & 2.75345 \tabularnewline
199 & 17 & 12.1628 & 4.83717 \tabularnewline
200 & 13 & 12.2175 & 0.782498 \tabularnewline
201 & 15 & 13.3698 & 1.63021 \tabularnewline
202 & 15 & 13.3168 & 1.68318 \tabularnewline
203 & 14 & 13.4471 & 0.552929 \tabularnewline
204 & 16 & 12.6566 & 3.34338 \tabularnewline
205 & 13 & 12.1694 & 0.830643 \tabularnewline
206 & 16 & 12.5905 & 3.40946 \tabularnewline
207 & 9 & 12.9919 & -3.99186 \tabularnewline
208 & 16 & 12.2167 & 3.78331 \tabularnewline
209 & 11 & 12.4239 & -1.42388 \tabularnewline
210 & 10 & 12.5295 & -2.52951 \tabularnewline
211 & 11 & 13.463 & -2.46296 \tabularnewline
212 & 15 & 12.4357 & 2.56427 \tabularnewline
213 & 17 & 13.5434 & 3.4566 \tabularnewline
214 & 14 & 13.3825 & 0.617534 \tabularnewline
215 & 8 & 12.4075 & -4.40745 \tabularnewline
216 & 15 & 13.3073 & 1.69266 \tabularnewline
217 & 11 & 12.3478 & -1.34776 \tabularnewline
218 & 16 & 12.5328 & 3.46718 \tabularnewline
219 & 10 & 13.3374 & -3.33739 \tabularnewline
220 & 15 & 12.1839 & 2.81612 \tabularnewline
221 & 16 & 12.5101 & 3.48995 \tabularnewline
222 & 19 & 12.4057 & 6.59432 \tabularnewline
223 & 12 & 12.4444 & -0.444391 \tabularnewline
224 & 8 & 12.1308 & -4.13085 \tabularnewline
225 & 11 & 12.2178 & -1.21781 \tabularnewline
226 & 14 & 13.2554 & 0.744639 \tabularnewline
227 & 9 & 11.8885 & -2.88853 \tabularnewline
228 & 15 & 12.7033 & 2.29673 \tabularnewline
229 & 13 & 13.8645 & -0.864475 \tabularnewline
230 & 16 & 13.159 & 2.84101 \tabularnewline
231 & 11 & 12.2013 & -1.20135 \tabularnewline
232 & 12 & 11.4764 & 0.523608 \tabularnewline
233 & 13 & 12.471 & 0.528974 \tabularnewline
234 & 10 & 13.3631 & -3.36312 \tabularnewline
235 & 11 & 12.174 & -1.17398 \tabularnewline
236 & 12 & 12.0908 & -0.0907621 \tabularnewline
237 & 8 & 12.2129 & -4.21292 \tabularnewline
238 & 12 & 12.0246 & -0.0246226 \tabularnewline
239 & 12 & 12.4443 & -0.44433 \tabularnewline
240 & 11 & 12.0974 & -1.09739 \tabularnewline
241 & 13 & 12.4011 & 0.598906 \tabularnewline
242 & 14 & 12.8729 & 1.12715 \tabularnewline
243 & 10 & 12.8386 & -2.83862 \tabularnewline
244 & 12 & 12.8931 & -0.89313 \tabularnewline
245 & 15 & 12.0651 & 2.93487 \tabularnewline
246 & 13 & 12.0328 & 0.967219 \tabularnewline
247 & 13 & 13.127 & -0.127043 \tabularnewline
248 & 13 & 13.5046 & -0.504626 \tabularnewline
249 & 12 & 12.3156 & -0.315608 \tabularnewline
250 & 12 & 12.4555 & -0.455498 \tabularnewline
251 & 9 & 12.6406 & -3.64062 \tabularnewline
252 & 9 & 13.2282 & -4.22822 \tabularnewline
253 & 15 & 13.1928 & 1.80718 \tabularnewline
254 & 10 & 12.2604 & -2.26042 \tabularnewline
255 & 14 & 13.2217 & 0.778341 \tabularnewline
256 & 15 & 12.0026 & 2.99741 \tabularnewline
257 & 7 & 12.2789 & -5.27887 \tabularnewline
258 & 14 & 12.3672 & 1.63283 \tabularnewline
259 & 8 & 12.6516 & -4.65157 \tabularnewline
260 & 10 & 13.2941 & -3.29414 \tabularnewline
261 & 13 & 12.0776 & 0.922424 \tabularnewline
262 & 13 & 12.2175 & 0.782458 \tabularnewline
263 & 13 & 13.4741 & -0.47411 \tabularnewline
264 & 8 & 12.1017 & -4.10171 \tabularnewline
265 & 12 & 12.3962 & -0.396246 \tabularnewline
266 & 13 & 13.1619 & -0.161941 \tabularnewline
267 & 12 & 13.5544 & -1.55445 \tabularnewline
268 & 10 & 12.3049 & -2.30487 \tabularnewline
269 & 13 & 13.447 & -0.44697 \tabularnewline
270 & 12 & 12.6451 & -0.645107 \tabularnewline
271 & 9 & 12.1314 & -3.13141 \tabularnewline
272 & 15 & 12.5304 & 2.46963 \tabularnewline
273 & 13 & 12.6821 & 0.317916 \tabularnewline
274 & 13 & 12.0536 & 0.946428 \tabularnewline
275 & 13 & 12.6729 & 0.327084 \tabularnewline
276 & 15 & 11.2636 & 3.73644 \tabularnewline
277 & 15 & 12.327 & 2.67298 \tabularnewline
278 & 14 & 12.6177 & 1.38226 \tabularnewline
279 & 15 & 13.1865 & 1.81354 \tabularnewline
280 & 11 & 12.1648 & -1.16477 \tabularnewline
281 & 15 & 12.8185 & 2.1815 \tabularnewline
282 & 14 & 13.3489 & 0.651096 \tabularnewline
283 & 13 & 12.1226 & 0.877351 \tabularnewline
284 & 12 & 12.0592 & -0.0592278 \tabularnewline
285 & 16 & 12.7454 & 3.25465 \tabularnewline
286 & 16 & 12.0185 & 3.98148 \tabularnewline
287 & 9 & 13.4071 & -4.40708 \tabularnewline
288 & 14 & 13.1205 & 0.879457 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231545&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]14[/C][C]14.2201[/C][C]-0.220102[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]14.6344[/C][C]3.3656[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]14.6332[/C][C]-3.63315[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]13.5712[/C][C]-1.57116[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]14.1478[/C][C]1.85217[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.2324[/C][C]3.76758[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]14.9911[/C][C]-0.991139[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.2667[/C][C]-0.266674[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]14.2505[/C][C]0.749483[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.3971[/C][C]0.602929[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]13.8488[/C][C]3.15117[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]14.5044[/C][C]4.49559[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.7527[/C][C]-3.75267[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]14.5384[/C][C]1.46157[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]14.4452[/C][C]3.55482[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.5019[/C][C]0.498111[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.6593[/C][C]0.340715[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]14.9708[/C][C]2.02918[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]13.986[/C][C]0.0140234[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]14.4272[/C][C]1.57282[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]13.6369[/C][C]4.36307[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]14.4159[/C][C]-3.41587[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.8631[/C][C]-0.863085[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]14.4678[/C][C]-2.46783[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]13.9469[/C][C]3.0531[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]14.7758[/C][C]-5.77576[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]13.7303[/C][C]2.26975[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]14.2234[/C][C]-0.223377[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]14.4385[/C][C]0.561509[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]13.4697[/C][C]-2.46974[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]14.2969[/C][C]1.70307[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]13.0889[/C][C]-0.0889064[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]14.374[/C][C]2.62601[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]14.4018[/C][C]0.598182[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.4855[/C][C]0.514471[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]12.9876[/C][C]3.01237[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]12.9055[/C][C]-3.90552[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]13.4922[/C][C]1.50785[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]14.3935[/C][C]2.60654[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]13.7349[/C][C]-0.734935[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]13.8055[/C][C]1.19446[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]14.2279[/C][C]1.7721[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]14.2282[/C][C]1.77185[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.497[/C][C]-1.49704[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.4493[/C][C]0.550728[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.921[/C][C]-2.92098[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]14.2251[/C][C]0.774949[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.3196[/C][C]0.680355[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]14.4565[/C][C]2.54348[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]13.5628[/C][C]-0.562753[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]14.299[/C][C]1.70097[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.4631[/C][C]0.536886[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]13.145[/C][C]-2.14505[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]14.3697[/C][C]-2.36973[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]12.9169[/C][C]-0.916865[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]14.3744[/C][C]0.625609[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.5863[/C][C]1.41369[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]14.3133[/C][C]0.686715[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]13.6065[/C][C]-1.60652[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]14.5093[/C][C]-2.50929[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]13.2509[/C][C]-5.25089[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]13.7687[/C][C]-0.76866[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.4016[/C][C]-3.40162[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.1301[/C][C]-0.130097[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]14.4978[/C][C]0.502218[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]13.7416[/C][C]-3.74162[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]14.6941[/C][C]-3.69412[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]13.9162[/C][C]-1.91618[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]14.0146[/C][C]0.985439[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.6388[/C][C]1.36123[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.0874[/C][C]0.912632[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]14.0821[/C][C]1.91789[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.5755[/C][C]0.424466[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]13.8624[/C][C]1.13759[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]13.7714[/C][C]-0.771406[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]14.8175[/C][C]-2.81752[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]14.4676[/C][C]2.53237[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]14.5139[/C][C]-1.51388[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.1868[/C][C]1.81323[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]13.8533[/C][C]-0.853315[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]13.6002[/C][C]1.39984[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]14.4291[/C][C]0.570879[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]13.6384[/C][C]2.3616[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2923[/C][C]0.707658[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.5027[/C][C]-0.502669[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.4991[/C][C]1.50092[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.4225[/C][C]-0.422497[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]14.3453[/C][C]-1.34527[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]14.3195[/C][C]-7.31954[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.9084[/C][C]3.0916[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]14.6071[/C][C]-1.60706[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.3651[/C][C]0.634856[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]14.3722[/C][C]-0.372211[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.0204[/C][C]-1.02042[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.5865[/C][C]1.41348[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]14.4996[/C][C]-2.49962[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.5734[/C][C]-0.57337[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]13.7414[/C][C]3.25864[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]13.3671[/C][C]1.63285[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]14.4948[/C][C]2.50517[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]13.7415[/C][C]-1.74146[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]14.8839[/C][C]1.11607[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]13.598[/C][C]-2.59795[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]14.3586[/C][C]0.641378[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]13.4984[/C][C]-4.49841[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.662[/C][C]1.33803[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]13.7706[/C][C]1.2294[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]13.7142[/C][C]-3.71416[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]14.1723[/C][C]-4.17226[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]14.3406[/C][C]0.659412[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]14.3517[/C][C]-3.35169[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]14.4183[/C][C]-1.41828[/C][/ROW]
[ROW][C]113[/C][C]18[/C][C]14.0881[/C][C]3.91189[/C][/ROW]
[ROW][C]114[/C][C]16[/C][C]13.9951[/C][C]2.00486[/C][/ROW]
[ROW][C]115[/C][C]14[/C][C]14.0725[/C][C]-0.0725424[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]14.1803[/C][C]-0.180321[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]14.0658[/C][C]-0.0657558[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]14.527[/C][C]-0.527024[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]13.2434[/C][C]-1.24342[/C][/ROW]
[ROW][C]120[/C][C]14[/C][C]14.4638[/C][C]-0.463754[/C][/ROW]
[ROW][C]121[/C][C]15[/C][C]14.1222[/C][C]0.877801[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.4355[/C][C]0.564458[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]14.4173[/C][C]0.582655[/C][/ROW]
[ROW][C]124[/C][C]13[/C][C]14.3356[/C][C]-1.3356[/C][/ROW]
[ROW][C]125[/C][C]17[/C][C]13.7412[/C][C]3.25881[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]14.7779[/C][C]2.2221[/C][/ROW]
[ROW][C]127[/C][C]19[/C][C]14.3198[/C][C]4.68015[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]14.0334[/C][C]0.966597[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]13.653[/C][C]-0.653026[/C][/ROW]
[ROW][C]130[/C][C]9[/C][C]12.83[/C][C]-3.83003[/C][/ROW]
[ROW][C]131[/C][C]15[/C][C]14.63[/C][C]0.369984[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]13.0726[/C][C]1.92739[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]13.4395[/C][C]1.56051[/C][/ROW]
[ROW][C]134[/C][C]16[/C][C]14.3562[/C][C]1.64378[/C][/ROW]
[ROW][C]135[/C][C]11[/C][C]13.379[/C][C]-2.379[/C][/ROW]
[ROW][C]136[/C][C]14[/C][C]13.5406[/C][C]0.459398[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]13.762[/C][C]-2.76205[/C][/ROW]
[ROW][C]138[/C][C]15[/C][C]14.0657[/C][C]0.934306[/C][/ROW]
[ROW][C]139[/C][C]13[/C][C]13.0151[/C][C]-0.0150936[/C][/ROW]
[ROW][C]140[/C][C]15[/C][C]14.4596[/C][C]0.540426[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]13.4316[/C][C]2.56841[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]14.3953[/C][C]-0.395256[/C][/ROW]
[ROW][C]143[/C][C]15[/C][C]13.7696[/C][C]1.23043[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.0123[/C][C]1.9877[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.729[/C][C]1.27105[/C][/ROW]
[ROW][C]146[/C][C]11[/C][C]13.3252[/C][C]-2.32522[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]13.6528[/C][C]-1.65282[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]13.4102[/C][C]-4.41018[/C][/ROW]
[ROW][C]149[/C][C]16[/C][C]13.8458[/C][C]2.15417[/C][/ROW]
[ROW][C]150[/C][C]13[/C][C]14.4852[/C][C]-1.4852[/C][/ROW]
[ROW][C]151[/C][C]16[/C][C]13.6438[/C][C]2.35624[/C][/ROW]
[ROW][C]152[/C][C]12[/C][C]14.4937[/C][C]-2.4937[/C][/ROW]
[ROW][C]153[/C][C]9[/C][C]14.3855[/C][C]-5.3855[/C][/ROW]
[ROW][C]154[/C][C]13[/C][C]13.8212[/C][C]-0.821175[/C][/ROW]
[ROW][C]155[/C][C]14[/C][C]14.0869[/C][C]-0.0869406[/C][/ROW]
[ROW][C]156[/C][C]19[/C][C]14.3198[/C][C]4.68015[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]14.4979[/C][C]-1.49788[/C][/ROW]
[ROW][C]158[/C][C]12[/C][C]13.9198[/C][C]-1.91981[/C][/ROW]
[ROW][C]159[/C][C]10[/C][C]12.2735[/C][C]-2.27348[/C][/ROW]
[ROW][C]160[/C][C]14[/C][C]12.2959[/C][C]1.70406[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]12.8733[/C][C]3.12673[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]13.2849[/C][C]-3.28493[/C][/ROW]
[ROW][C]163[/C][C]11[/C][C]11.8029[/C][C]-0.802947[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]12.3463[/C][C]1.65371[/C][/ROW]
[ROW][C]165[/C][C]12[/C][C]12.7824[/C][C]-0.782441[/C][/ROW]
[ROW][C]166[/C][C]9[/C][C]13.0308[/C][C]-4.03084[/C][/ROW]
[ROW][C]167[/C][C]9[/C][C]12.4222[/C][C]-3.4222[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]12.4281[/C][C]-1.42807[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]13.4583[/C][C]2.54172[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]12.3928[/C][C]-3.39283[/C][/ROW]
[ROW][C]171[/C][C]13[/C][C]12.7069[/C][C]0.293069[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]13.1264[/C][C]2.87356[/C][/ROW]
[ROW][C]173[/C][C]13[/C][C]12.4879[/C][C]0.512149[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]13.1381[/C][C]-4.13815[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]12.1886[/C][C]-0.188564[/C][/ROW]
[ROW][C]176[/C][C]16[/C][C]13.212[/C][C]2.78798[/C][/ROW]
[ROW][C]177[/C][C]11[/C][C]13.0854[/C][C]-2.08538[/C][/ROW]
[ROW][C]178[/C][C]14[/C][C]13.4743[/C][C]0.525727[/C][/ROW]
[ROW][C]179[/C][C]13[/C][C]12.2544[/C][C]0.745583[/C][/ROW]
[ROW][C]180[/C][C]15[/C][C]12.856[/C][C]2.14404[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]12.6836[/C][C]1.31644[/C][/ROW]
[ROW][C]182[/C][C]16[/C][C]12.2684[/C][C]3.7316[/C][/ROW]
[ROW][C]183[/C][C]13[/C][C]13.3651[/C][C]-0.365061[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]12.851[/C][C]1.14905[/C][/ROW]
[ROW][C]185[/C][C]15[/C][C]13.2408[/C][C]1.75916[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]12.0792[/C][C]0.920811[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]12.0926[/C][C]-1.09264[/C][/ROW]
[ROW][C]188[/C][C]11[/C][C]13.1272[/C][C]-2.12717[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]13.4649[/C][C]0.535097[/C][/ROW]
[ROW][C]190[/C][C]15[/C][C]13.0821[/C][C]1.91789[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]13.4471[/C][C]-2.44707[/C][/ROW]
[ROW][C]192[/C][C]15[/C][C]13.1044[/C][C]1.89561[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]12.5603[/C][C]-0.560289[/C][/ROW]
[ROW][C]194[/C][C]14[/C][C]13.5479[/C][C]0.452077[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]13.3764[/C][C]0.62363[/C][/ROW]
[ROW][C]196[/C][C]8[/C][C]12.4604[/C][C]-4.46039[/C][/ROW]
[ROW][C]197[/C][C]9[/C][C]12.6161[/C][C]-3.61607[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]12.2465[/C][C]2.75345[/C][/ROW]
[ROW][C]199[/C][C]17[/C][C]12.1628[/C][C]4.83717[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]12.2175[/C][C]0.782498[/C][/ROW]
[ROW][C]201[/C][C]15[/C][C]13.3698[/C][C]1.63021[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.3168[/C][C]1.68318[/C][/ROW]
[ROW][C]203[/C][C]14[/C][C]13.4471[/C][C]0.552929[/C][/ROW]
[ROW][C]204[/C][C]16[/C][C]12.6566[/C][C]3.34338[/C][/ROW]
[ROW][C]205[/C][C]13[/C][C]12.1694[/C][C]0.830643[/C][/ROW]
[ROW][C]206[/C][C]16[/C][C]12.5905[/C][C]3.40946[/C][/ROW]
[ROW][C]207[/C][C]9[/C][C]12.9919[/C][C]-3.99186[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.2167[/C][C]3.78331[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]12.4239[/C][C]-1.42388[/C][/ROW]
[ROW][C]210[/C][C]10[/C][C]12.5295[/C][C]-2.52951[/C][/ROW]
[ROW][C]211[/C][C]11[/C][C]13.463[/C][C]-2.46296[/C][/ROW]
[ROW][C]212[/C][C]15[/C][C]12.4357[/C][C]2.56427[/C][/ROW]
[ROW][C]213[/C][C]17[/C][C]13.5434[/C][C]3.4566[/C][/ROW]
[ROW][C]214[/C][C]14[/C][C]13.3825[/C][C]0.617534[/C][/ROW]
[ROW][C]215[/C][C]8[/C][C]12.4075[/C][C]-4.40745[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.3073[/C][C]1.69266[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]12.3478[/C][C]-1.34776[/C][/ROW]
[ROW][C]218[/C][C]16[/C][C]12.5328[/C][C]3.46718[/C][/ROW]
[ROW][C]219[/C][C]10[/C][C]13.3374[/C][C]-3.33739[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]12.1839[/C][C]2.81612[/C][/ROW]
[ROW][C]221[/C][C]16[/C][C]12.5101[/C][C]3.48995[/C][/ROW]
[ROW][C]222[/C][C]19[/C][C]12.4057[/C][C]6.59432[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]12.4444[/C][C]-0.444391[/C][/ROW]
[ROW][C]224[/C][C]8[/C][C]12.1308[/C][C]-4.13085[/C][/ROW]
[ROW][C]225[/C][C]11[/C][C]12.2178[/C][C]-1.21781[/C][/ROW]
[ROW][C]226[/C][C]14[/C][C]13.2554[/C][C]0.744639[/C][/ROW]
[ROW][C]227[/C][C]9[/C][C]11.8885[/C][C]-2.88853[/C][/ROW]
[ROW][C]228[/C][C]15[/C][C]12.7033[/C][C]2.29673[/C][/ROW]
[ROW][C]229[/C][C]13[/C][C]13.8645[/C][C]-0.864475[/C][/ROW]
[ROW][C]230[/C][C]16[/C][C]13.159[/C][C]2.84101[/C][/ROW]
[ROW][C]231[/C][C]11[/C][C]12.2013[/C][C]-1.20135[/C][/ROW]
[ROW][C]232[/C][C]12[/C][C]11.4764[/C][C]0.523608[/C][/ROW]
[ROW][C]233[/C][C]13[/C][C]12.471[/C][C]0.528974[/C][/ROW]
[ROW][C]234[/C][C]10[/C][C]13.3631[/C][C]-3.36312[/C][/ROW]
[ROW][C]235[/C][C]11[/C][C]12.174[/C][C]-1.17398[/C][/ROW]
[ROW][C]236[/C][C]12[/C][C]12.0908[/C][C]-0.0907621[/C][/ROW]
[ROW][C]237[/C][C]8[/C][C]12.2129[/C][C]-4.21292[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]12.0246[/C][C]-0.0246226[/C][/ROW]
[ROW][C]239[/C][C]12[/C][C]12.4443[/C][C]-0.44433[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]12.0974[/C][C]-1.09739[/C][/ROW]
[ROW][C]241[/C][C]13[/C][C]12.4011[/C][C]0.598906[/C][/ROW]
[ROW][C]242[/C][C]14[/C][C]12.8729[/C][C]1.12715[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]12.8386[/C][C]-2.83862[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.8931[/C][C]-0.89313[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]12.0651[/C][C]2.93487[/C][/ROW]
[ROW][C]246[/C][C]13[/C][C]12.0328[/C][C]0.967219[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]13.127[/C][C]-0.127043[/C][/ROW]
[ROW][C]248[/C][C]13[/C][C]13.5046[/C][C]-0.504626[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]12.3156[/C][C]-0.315608[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]12.4555[/C][C]-0.455498[/C][/ROW]
[ROW][C]251[/C][C]9[/C][C]12.6406[/C][C]-3.64062[/C][/ROW]
[ROW][C]252[/C][C]9[/C][C]13.2282[/C][C]-4.22822[/C][/ROW]
[ROW][C]253[/C][C]15[/C][C]13.1928[/C][C]1.80718[/C][/ROW]
[ROW][C]254[/C][C]10[/C][C]12.2604[/C][C]-2.26042[/C][/ROW]
[ROW][C]255[/C][C]14[/C][C]13.2217[/C][C]0.778341[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]12.0026[/C][C]2.99741[/C][/ROW]
[ROW][C]257[/C][C]7[/C][C]12.2789[/C][C]-5.27887[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]12.3672[/C][C]1.63283[/C][/ROW]
[ROW][C]259[/C][C]8[/C][C]12.6516[/C][C]-4.65157[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]13.2941[/C][C]-3.29414[/C][/ROW]
[ROW][C]261[/C][C]13[/C][C]12.0776[/C][C]0.922424[/C][/ROW]
[ROW][C]262[/C][C]13[/C][C]12.2175[/C][C]0.782458[/C][/ROW]
[ROW][C]263[/C][C]13[/C][C]13.4741[/C][C]-0.47411[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]12.1017[/C][C]-4.10171[/C][/ROW]
[ROW][C]265[/C][C]12[/C][C]12.3962[/C][C]-0.396246[/C][/ROW]
[ROW][C]266[/C][C]13[/C][C]13.1619[/C][C]-0.161941[/C][/ROW]
[ROW][C]267[/C][C]12[/C][C]13.5544[/C][C]-1.55445[/C][/ROW]
[ROW][C]268[/C][C]10[/C][C]12.3049[/C][C]-2.30487[/C][/ROW]
[ROW][C]269[/C][C]13[/C][C]13.447[/C][C]-0.44697[/C][/ROW]
[ROW][C]270[/C][C]12[/C][C]12.6451[/C][C]-0.645107[/C][/ROW]
[ROW][C]271[/C][C]9[/C][C]12.1314[/C][C]-3.13141[/C][/ROW]
[ROW][C]272[/C][C]15[/C][C]12.5304[/C][C]2.46963[/C][/ROW]
[ROW][C]273[/C][C]13[/C][C]12.6821[/C][C]0.317916[/C][/ROW]
[ROW][C]274[/C][C]13[/C][C]12.0536[/C][C]0.946428[/C][/ROW]
[ROW][C]275[/C][C]13[/C][C]12.6729[/C][C]0.327084[/C][/ROW]
[ROW][C]276[/C][C]15[/C][C]11.2636[/C][C]3.73644[/C][/ROW]
[ROW][C]277[/C][C]15[/C][C]12.327[/C][C]2.67298[/C][/ROW]
[ROW][C]278[/C][C]14[/C][C]12.6177[/C][C]1.38226[/C][/ROW]
[ROW][C]279[/C][C]15[/C][C]13.1865[/C][C]1.81354[/C][/ROW]
[ROW][C]280[/C][C]11[/C][C]12.1648[/C][C]-1.16477[/C][/ROW]
[ROW][C]281[/C][C]15[/C][C]12.8185[/C][C]2.1815[/C][/ROW]
[ROW][C]282[/C][C]14[/C][C]13.3489[/C][C]0.651096[/C][/ROW]
[ROW][C]283[/C][C]13[/C][C]12.1226[/C][C]0.877351[/C][/ROW]
[ROW][C]284[/C][C]12[/C][C]12.0592[/C][C]-0.0592278[/C][/ROW]
[ROW][C]285[/C][C]16[/C][C]12.7454[/C][C]3.25465[/C][/ROW]
[ROW][C]286[/C][C]16[/C][C]12.0185[/C][C]3.98148[/C][/ROW]
[ROW][C]287[/C][C]9[/C][C]13.4071[/C][C]-4.40708[/C][/ROW]
[ROW][C]288[/C][C]14[/C][C]13.1205[/C][C]0.879457[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231545&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231545&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.2201-0.220102
21814.63443.3656
31114.6332-3.63315
41213.5712-1.57116
51614.14781.85217
61814.23243.76758
71414.9911-0.991139
81414.2667-0.266674
91514.25050.749483
101514.39710.602929
111713.84883.15117
121914.50444.49559
131013.7527-3.75267
141614.53841.46157
151814.44523.55482
161413.50190.498111
171413.65930.340715
181714.97082.02918
191413.9860.0140234
201614.42721.57282
211813.63694.36307
221114.4159-3.41587
231414.8631-0.863085
241214.4678-2.46783
251713.94693.0531
26914.7758-5.77576
271613.73032.26975
281414.2234-0.223377
291514.43850.561509
301113.4697-2.46974
311614.29691.70307
321313.0889-0.0889064
331714.3742.62601
341514.40180.598182
351413.48550.514471
361612.98763.01237
37912.9055-3.90552
381513.49221.50785
391714.39352.60654
401313.7349-0.734935
411513.80551.19446
421614.22791.7721
431614.22821.77185
441213.497-1.49704
451514.44930.550728
461113.921-2.92098
471514.22510.774949
481514.31960.680355
491714.45652.54348
501313.5628-0.562753
511614.2991.70097
521413.46310.536886
531113.145-2.14505
541214.3697-2.36973
551212.9169-0.916865
561514.37440.625609
571614.58631.41369
581514.31330.686715
591213.6065-1.60652
601214.5093-2.50929
61813.2509-5.25089
621313.7687-0.76866
631114.4016-3.40162
641414.1301-0.130097
651514.49780.502218
661013.7416-3.74162
671114.6941-3.69412
681213.9162-1.91618
691514.01460.985439
701513.63881.36123
711413.08740.912632
721614.08211.91789
731514.57550.424466
741513.86241.13759
751313.7714-0.771406
761214.8175-2.81752
771714.46762.53237
781314.5139-1.51388
791513.18681.81323
801313.8533-0.853315
811513.60021.39984
821514.42910.570879
831613.63842.3616
841514.29230.707658
851414.5027-0.502669
861513.49911.50092
871414.4225-0.422497
881314.3453-1.34527
89714.3195-7.31954
901713.90843.0916
911314.6071-1.60706
921514.36510.634856
931414.3722-0.372211
941314.0204-1.02042
951614.58651.41348
961214.4996-2.49962
971414.5734-0.57337
981713.74143.25864
991513.36711.63285
1001714.49482.50517
1011213.7415-1.74146
1021614.88391.11607
1031113.598-2.59795
1041514.35860.641378
105913.4984-4.49841
1061614.6621.33803
1071513.77061.2294
1081013.7142-3.71416
1091014.1723-4.17226
1101514.34060.659412
1111114.3517-3.35169
1121314.4183-1.41828
1131814.08813.91189
1141613.99512.00486
1151414.0725-0.0725424
1161414.1803-0.180321
1171414.0658-0.0657558
1181414.527-0.527024
1191213.2434-1.24342
1201414.4638-0.463754
1211514.12220.877801
1221514.43550.564458
1231514.41730.582655
1241314.3356-1.3356
1251713.74123.25881
1261714.77792.2221
1271914.31984.68015
1281514.03340.966597
1291313.653-0.653026
130912.83-3.83003
1311514.630.369984
1321513.07261.92739
1331513.43951.56051
1341614.35621.64378
1351113.379-2.379
1361413.54060.459398
1371113.762-2.76205
1381514.06570.934306
1391313.0151-0.0150936
1401514.45960.540426
1411613.43162.56841
1421414.3953-0.395256
1431513.76961.23043
1441614.01231.9877
1451614.7291.27105
1461113.3252-2.32522
1471213.6528-1.65282
148913.4102-4.41018
1491613.84582.15417
1501314.4852-1.4852
1511613.64382.35624
1521214.4937-2.4937
153914.3855-5.3855
1541313.8212-0.821175
1551414.0869-0.0869406
1561914.31984.68015
1571314.4979-1.49788
1581213.9198-1.91981
1591012.2735-2.27348
1601412.29591.70406
1611612.87333.12673
1621013.2849-3.28493
1631111.8029-0.802947
1641412.34631.65371
1651212.7824-0.782441
166913.0308-4.03084
167912.4222-3.4222
1681112.4281-1.42807
1691613.45832.54172
170912.3928-3.39283
1711312.70690.293069
1721613.12642.87356
1731312.48790.512149
174913.1381-4.13815
1751212.1886-0.188564
1761613.2122.78798
1771113.0854-2.08538
1781413.47430.525727
1791312.25440.745583
1801512.8562.14404
1811412.68361.31644
1821612.26843.7316
1831313.3651-0.365061
1841412.8511.14905
1851513.24081.75916
1861312.07920.920811
1871112.0926-1.09264
1881113.1272-2.12717
1891413.46490.535097
1901513.08211.91789
1911113.4471-2.44707
1921513.10441.89561
1931212.5603-0.560289
1941413.54790.452077
1951413.37640.62363
196812.4604-4.46039
197912.6161-3.61607
1981512.24652.75345
1991712.16284.83717
2001312.21750.782498
2011513.36981.63021
2021513.31681.68318
2031413.44710.552929
2041612.65663.34338
2051312.16940.830643
2061612.59053.40946
207912.9919-3.99186
2081612.21673.78331
2091112.4239-1.42388
2101012.5295-2.52951
2111113.463-2.46296
2121512.43572.56427
2131713.54343.4566
2141413.38250.617534
215812.4075-4.40745
2161513.30731.69266
2171112.3478-1.34776
2181612.53283.46718
2191013.3374-3.33739
2201512.18392.81612
2211612.51013.48995
2221912.40576.59432
2231212.4444-0.444391
224812.1308-4.13085
2251112.2178-1.21781
2261413.25540.744639
227911.8885-2.88853
2281512.70332.29673
2291313.8645-0.864475
2301613.1592.84101
2311112.2013-1.20135
2321211.47640.523608
2331312.4710.528974
2341013.3631-3.36312
2351112.174-1.17398
2361212.0908-0.0907621
237812.2129-4.21292
2381212.0246-0.0246226
2391212.4443-0.44433
2401112.0974-1.09739
2411312.40110.598906
2421412.87291.12715
2431012.8386-2.83862
2441212.8931-0.89313
2451512.06512.93487
2461312.03280.967219
2471313.127-0.127043
2481313.5046-0.504626
2491212.3156-0.315608
2501212.4555-0.455498
251912.6406-3.64062
252913.2282-4.22822
2531513.19281.80718
2541012.2604-2.26042
2551413.22170.778341
2561512.00262.99741
257712.2789-5.27887
2581412.36721.63283
259812.6516-4.65157
2601013.2941-3.29414
2611312.07760.922424
2621312.21750.782458
2631313.4741-0.47411
264812.1017-4.10171
2651212.3962-0.396246
2661313.1619-0.161941
2671213.5544-1.55445
2681012.3049-2.30487
2691313.447-0.44697
2701212.6451-0.645107
271912.1314-3.13141
2721512.53042.46963
2731312.68210.317916
2741312.05360.946428
2751312.67290.327084
2761511.26363.73644
2771512.3272.67298
2781412.61771.38226
2791513.18651.81354
2801112.1648-1.16477
2811512.81852.1815
2821413.34890.651096
2831312.12260.877351
2841212.0592-0.0592278
2851612.74543.25465
2861612.01853.98148
287913.4071-4.40708
2881413.12050.879457







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.358930.717860.64107
110.448740.8974790.55126
120.6763630.6472740.323637
130.6959730.6080530.304027
140.6341850.731630.365815
150.8302230.3395540.169777
160.7738070.4523870.226193
170.6983290.6033410.301671
180.7191540.5616930.280846
190.6660030.6679950.333997
200.5904270.8191460.409573
210.7546010.4907970.245399
220.8652310.2695380.134769
230.8315990.3368010.168401
240.8378550.3242890.162145
250.816860.3662810.18314
260.9685520.0628970.0314485
270.9608340.07833270.0391663
280.9467240.1065520.0532758
290.9284090.1431820.0715911
300.9438270.1123460.0561728
310.9291330.1417330.0708667
320.9124990.1750010.0875007
330.8982220.2035560.101778
340.8720180.2559650.127982
350.8416220.3167560.158378
360.8215890.3568230.178411
370.9004630.1990750.0995373
380.8818460.2363080.118154
390.87340.25320.1266
400.8504720.2990570.149528
410.8219980.3560040.178002
420.7957490.4085010.204251
430.778570.4428590.22143
440.7635470.4729070.236453
450.7312690.5374610.268731
460.7537140.4925730.246286
470.7208580.5582850.279142
480.6802790.6394420.319721
490.6725250.6549490.327475
500.6318150.7363690.368185
510.607940.7841190.39206
520.5635950.8728090.436405
530.5444570.9110870.455543
540.5495370.9009260.450463
550.515450.96910.48455
560.4740460.9480920.525954
570.4372030.8744050.562797
580.3949180.7898350.605082
590.3692220.7384440.630778
600.4044740.8089490.595526
610.5756280.8487440.424372
620.5381880.9236240.461812
630.5885730.8228530.411427
640.5470750.905850.452925
650.5059580.9880840.494042
660.5515110.8969780.448489
670.6187970.7624060.381203
680.603740.792520.39626
690.5698910.8602180.430109
700.5506510.8986970.449349
710.5157730.9684530.484227
720.5010410.9979170.498959
730.4620030.9240070.537997
740.4339340.8678680.566066
750.3964260.7928520.603574
760.4314170.8628350.568583
770.4289940.8579890.571006
780.4066680.8133360.593332
790.4021970.8043950.597803
800.3670850.734170.632915
810.3437650.687530.656235
820.3098320.6196650.690168
830.3109570.6219130.689043
840.2801980.5603950.719802
850.2500260.5000520.749974
860.2277910.4555820.772209
870.2010980.4021960.798902
880.1816290.3632580.818371
890.4511520.9023050.548848
900.470790.941580.52921
910.4454850.890970.554515
920.410570.821140.58943
930.3758670.7517340.624133
940.3441660.6883310.655834
950.3179370.6358730.682063
960.3227240.6454480.677276
970.2922940.5845870.707706
980.3186220.6372430.681378
990.2984190.5968380.701581
1000.3005780.6011560.699422
1010.2905820.5811640.709418
1020.2665910.5331810.733409
1030.2629070.5258140.737093
1040.2357560.4715110.764244
1050.3097610.6195220.690239
1060.2867120.5734240.713288
1070.2612790.5225580.738721
1080.3110630.6221270.688937
1090.4144420.8288830.585558
1100.3824580.7649160.617542
1110.4129730.8259470.587027
1120.3997620.7995230.600238
1130.4582830.9165670.541717
1140.4492120.8984250.550788
1150.4153310.8306620.584669
1160.383280.766560.61672
1170.3502920.7005830.649708
1180.3205530.6411070.679447
1190.2986420.5972850.701358
1200.2703320.5406640.729668
1210.2451850.490370.754815
1220.2196820.4393630.780318
1230.1968590.3937180.803141
1240.179640.3592790.82036
1250.1988480.3976950.801152
1260.1913690.3827380.808631
1270.265210.530420.73479
1280.2436790.4873570.756321
1290.2187630.4375260.781237
1300.2491280.4982560.750872
1310.2254430.4508860.774557
1320.2250180.4500360.774982
1330.2110280.4220570.788972
1340.2028390.4056790.797161
1350.1969460.3938930.803054
1360.1751380.3502760.824862
1370.1790660.3581310.820934
1380.1613720.3227450.838628
1390.1413170.2826350.858683
1400.1244630.2489270.875537
1410.1290270.2580530.870973
1420.111870.223740.88813
1430.1039930.2079850.896007
1440.1025280.2050560.897472
1450.09577650.1915530.904223
1460.09157720.1831540.908423
1470.08210680.1642140.917893
1480.1152640.2305280.884736
1490.1141470.2282950.885853
1500.1041890.2083780.895811
1510.1059220.2118440.894078
1520.1105130.2210250.889487
1530.1894050.3788090.810595
1540.1708520.3417050.829148
1550.1502180.3004360.849782
1560.2242550.4485110.775745
1570.2040470.4080940.795953
1580.1893270.3786540.810673
1590.1840340.3680680.815966
1600.1782230.3564460.821777
1610.1821190.3642390.817881
1620.2107980.4215960.789202
1630.1902160.3804320.809784
1640.1773460.3546930.822654
1650.16010.32020.8399
1660.2003490.4006970.799651
1670.2246870.4493740.775313
1680.2036560.4073120.796344
1690.2131020.4262030.786898
1700.2323270.4646540.767673
1710.2112120.4224240.788788
1720.2278870.4557730.772113
1730.2041880.4083760.795812
1740.2459030.4918070.754097
1750.2208420.4416840.779158
1760.2352850.4705690.764715
1770.2245270.4490530.775473
1780.2013420.4026850.798658
1790.1811450.3622910.818855
1800.1768970.3537940.823103
1810.1618710.3237420.838129
1820.1942330.3884660.805767
1830.1712320.3424650.828768
1840.154710.309420.84529
1850.1459960.2919920.854004
1860.1289650.2579290.871035
1870.1153170.2306340.884683
1880.110850.2216990.88915
1890.09619140.1923830.903809
1900.09171580.1834320.908284
1910.09060780.1812160.909392
1920.08548080.1709620.914519
1930.07289970.1457990.9271
1940.06226340.1245270.937737
1950.05281760.1056350.947182
1960.08002640.1600530.919974
1970.09942240.1988450.900578
1980.1014480.2028960.898552
1990.1552250.310450.844775
2000.1357510.2715020.864249
2010.1273830.2547660.872617
2020.1197250.239450.880275
2030.1044020.2088050.895598
2040.119760.2395210.88024
2050.1034360.2068720.896564
2060.1209190.2418380.879081
2070.1552190.3104380.844781
2080.190790.3815810.80921
2090.1730810.3461620.826919
2100.1747910.3495810.825209
2110.1709110.3418220.829089
2120.1706320.3412650.829368
2130.2073420.4146840.792658
2140.1855580.3711150.814442
2150.2482180.4964370.751782
2160.2434730.4869450.756527
2170.2222560.4445110.777744
2180.2607930.5215860.739207
2190.2782720.5565450.721728
2200.2880150.5760310.711985
2210.3408460.6816930.659154
2220.6145080.7709850.385492
2230.574680.850640.42532
2240.656090.687820.34391
2250.624690.750620.37531
2260.5939980.8120040.406002
2270.6179740.7640530.382026
2280.6534660.6930670.346534
2290.6143580.7712840.385642
2300.6538560.6922870.346144
2310.6294620.7410760.370538
2320.5908710.8182580.409129
2330.5467360.9065280.453264
2340.5666840.8666310.433316
2350.5341050.931790.465895
2360.488020.9760390.51198
2370.6268890.7462220.373111
2380.586290.827420.41371
2390.5434590.9130820.456541
2400.5048090.9903830.495191
2410.464250.92850.53575
2420.4241250.848250.575875
2430.4414760.8829520.558524
2440.412670.8253410.58733
2450.4488690.8977380.551131
2460.4077430.8154850.592257
2470.3783280.7566550.621672
2480.3390860.6781720.660914
2490.2956720.5913440.704328
2500.2556260.5112520.744374
2510.3116620.6233230.688338
2520.3458450.6916890.654155
2530.3260540.6521070.673946
2540.3029280.6058570.697072
2550.2593670.5187340.740633
2560.2498020.4996040.750198
2570.4419940.8839880.558006
2580.4167140.8334280.583286
2590.6640370.6719260.335963
2600.6806230.6387540.319377
2610.6287770.7424450.371223
2620.5678350.8643290.432165
2630.5047340.9905320.495266
2640.7847750.4304510.215225
2650.7368350.526330.263165
2660.6893180.6213630.310682
2670.709240.581520.29076
2680.7110420.5779160.288958
2690.6336120.7327770.366388
2700.5554920.8890160.444508
2710.6611960.6776080.338804
2720.573450.8531010.42655
2730.5028870.9942270.497113
2740.4071280.8142570.592872
2750.3514740.7029480.648526
2760.2640970.5281940.735903
2770.1897390.3794790.810261
2780.112030.224060.88797

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.35893 & 0.71786 & 0.64107 \tabularnewline
11 & 0.44874 & 0.897479 & 0.55126 \tabularnewline
12 & 0.676363 & 0.647274 & 0.323637 \tabularnewline
13 & 0.695973 & 0.608053 & 0.304027 \tabularnewline
14 & 0.634185 & 0.73163 & 0.365815 \tabularnewline
15 & 0.830223 & 0.339554 & 0.169777 \tabularnewline
16 & 0.773807 & 0.452387 & 0.226193 \tabularnewline
17 & 0.698329 & 0.603341 & 0.301671 \tabularnewline
18 & 0.719154 & 0.561693 & 0.280846 \tabularnewline
19 & 0.666003 & 0.667995 & 0.333997 \tabularnewline
20 & 0.590427 & 0.819146 & 0.409573 \tabularnewline
21 & 0.754601 & 0.490797 & 0.245399 \tabularnewline
22 & 0.865231 & 0.269538 & 0.134769 \tabularnewline
23 & 0.831599 & 0.336801 & 0.168401 \tabularnewline
24 & 0.837855 & 0.324289 & 0.162145 \tabularnewline
25 & 0.81686 & 0.366281 & 0.18314 \tabularnewline
26 & 0.968552 & 0.062897 & 0.0314485 \tabularnewline
27 & 0.960834 & 0.0783327 & 0.0391663 \tabularnewline
28 & 0.946724 & 0.106552 & 0.0532758 \tabularnewline
29 & 0.928409 & 0.143182 & 0.0715911 \tabularnewline
30 & 0.943827 & 0.112346 & 0.0561728 \tabularnewline
31 & 0.929133 & 0.141733 & 0.0708667 \tabularnewline
32 & 0.912499 & 0.175001 & 0.0875007 \tabularnewline
33 & 0.898222 & 0.203556 & 0.101778 \tabularnewline
34 & 0.872018 & 0.255965 & 0.127982 \tabularnewline
35 & 0.841622 & 0.316756 & 0.158378 \tabularnewline
36 & 0.821589 & 0.356823 & 0.178411 \tabularnewline
37 & 0.900463 & 0.199075 & 0.0995373 \tabularnewline
38 & 0.881846 & 0.236308 & 0.118154 \tabularnewline
39 & 0.8734 & 0.2532 & 0.1266 \tabularnewline
40 & 0.850472 & 0.299057 & 0.149528 \tabularnewline
41 & 0.821998 & 0.356004 & 0.178002 \tabularnewline
42 & 0.795749 & 0.408501 & 0.204251 \tabularnewline
43 & 0.77857 & 0.442859 & 0.22143 \tabularnewline
44 & 0.763547 & 0.472907 & 0.236453 \tabularnewline
45 & 0.731269 & 0.537461 & 0.268731 \tabularnewline
46 & 0.753714 & 0.492573 & 0.246286 \tabularnewline
47 & 0.720858 & 0.558285 & 0.279142 \tabularnewline
48 & 0.680279 & 0.639442 & 0.319721 \tabularnewline
49 & 0.672525 & 0.654949 & 0.327475 \tabularnewline
50 & 0.631815 & 0.736369 & 0.368185 \tabularnewline
51 & 0.60794 & 0.784119 & 0.39206 \tabularnewline
52 & 0.563595 & 0.872809 & 0.436405 \tabularnewline
53 & 0.544457 & 0.911087 & 0.455543 \tabularnewline
54 & 0.549537 & 0.900926 & 0.450463 \tabularnewline
55 & 0.51545 & 0.9691 & 0.48455 \tabularnewline
56 & 0.474046 & 0.948092 & 0.525954 \tabularnewline
57 & 0.437203 & 0.874405 & 0.562797 \tabularnewline
58 & 0.394918 & 0.789835 & 0.605082 \tabularnewline
59 & 0.369222 & 0.738444 & 0.630778 \tabularnewline
60 & 0.404474 & 0.808949 & 0.595526 \tabularnewline
61 & 0.575628 & 0.848744 & 0.424372 \tabularnewline
62 & 0.538188 & 0.923624 & 0.461812 \tabularnewline
63 & 0.588573 & 0.822853 & 0.411427 \tabularnewline
64 & 0.547075 & 0.90585 & 0.452925 \tabularnewline
65 & 0.505958 & 0.988084 & 0.494042 \tabularnewline
66 & 0.551511 & 0.896978 & 0.448489 \tabularnewline
67 & 0.618797 & 0.762406 & 0.381203 \tabularnewline
68 & 0.60374 & 0.79252 & 0.39626 \tabularnewline
69 & 0.569891 & 0.860218 & 0.430109 \tabularnewline
70 & 0.550651 & 0.898697 & 0.449349 \tabularnewline
71 & 0.515773 & 0.968453 & 0.484227 \tabularnewline
72 & 0.501041 & 0.997917 & 0.498959 \tabularnewline
73 & 0.462003 & 0.924007 & 0.537997 \tabularnewline
74 & 0.433934 & 0.867868 & 0.566066 \tabularnewline
75 & 0.396426 & 0.792852 & 0.603574 \tabularnewline
76 & 0.431417 & 0.862835 & 0.568583 \tabularnewline
77 & 0.428994 & 0.857989 & 0.571006 \tabularnewline
78 & 0.406668 & 0.813336 & 0.593332 \tabularnewline
79 & 0.402197 & 0.804395 & 0.597803 \tabularnewline
80 & 0.367085 & 0.73417 & 0.632915 \tabularnewline
81 & 0.343765 & 0.68753 & 0.656235 \tabularnewline
82 & 0.309832 & 0.619665 & 0.690168 \tabularnewline
83 & 0.310957 & 0.621913 & 0.689043 \tabularnewline
84 & 0.280198 & 0.560395 & 0.719802 \tabularnewline
85 & 0.250026 & 0.500052 & 0.749974 \tabularnewline
86 & 0.227791 & 0.455582 & 0.772209 \tabularnewline
87 & 0.201098 & 0.402196 & 0.798902 \tabularnewline
88 & 0.181629 & 0.363258 & 0.818371 \tabularnewline
89 & 0.451152 & 0.902305 & 0.548848 \tabularnewline
90 & 0.47079 & 0.94158 & 0.52921 \tabularnewline
91 & 0.445485 & 0.89097 & 0.554515 \tabularnewline
92 & 0.41057 & 0.82114 & 0.58943 \tabularnewline
93 & 0.375867 & 0.751734 & 0.624133 \tabularnewline
94 & 0.344166 & 0.688331 & 0.655834 \tabularnewline
95 & 0.317937 & 0.635873 & 0.682063 \tabularnewline
96 & 0.322724 & 0.645448 & 0.677276 \tabularnewline
97 & 0.292294 & 0.584587 & 0.707706 \tabularnewline
98 & 0.318622 & 0.637243 & 0.681378 \tabularnewline
99 & 0.298419 & 0.596838 & 0.701581 \tabularnewline
100 & 0.300578 & 0.601156 & 0.699422 \tabularnewline
101 & 0.290582 & 0.581164 & 0.709418 \tabularnewline
102 & 0.266591 & 0.533181 & 0.733409 \tabularnewline
103 & 0.262907 & 0.525814 & 0.737093 \tabularnewline
104 & 0.235756 & 0.471511 & 0.764244 \tabularnewline
105 & 0.309761 & 0.619522 & 0.690239 \tabularnewline
106 & 0.286712 & 0.573424 & 0.713288 \tabularnewline
107 & 0.261279 & 0.522558 & 0.738721 \tabularnewline
108 & 0.311063 & 0.622127 & 0.688937 \tabularnewline
109 & 0.414442 & 0.828883 & 0.585558 \tabularnewline
110 & 0.382458 & 0.764916 & 0.617542 \tabularnewline
111 & 0.412973 & 0.825947 & 0.587027 \tabularnewline
112 & 0.399762 & 0.799523 & 0.600238 \tabularnewline
113 & 0.458283 & 0.916567 & 0.541717 \tabularnewline
114 & 0.449212 & 0.898425 & 0.550788 \tabularnewline
115 & 0.415331 & 0.830662 & 0.584669 \tabularnewline
116 & 0.38328 & 0.76656 & 0.61672 \tabularnewline
117 & 0.350292 & 0.700583 & 0.649708 \tabularnewline
118 & 0.320553 & 0.641107 & 0.679447 \tabularnewline
119 & 0.298642 & 0.597285 & 0.701358 \tabularnewline
120 & 0.270332 & 0.540664 & 0.729668 \tabularnewline
121 & 0.245185 & 0.49037 & 0.754815 \tabularnewline
122 & 0.219682 & 0.439363 & 0.780318 \tabularnewline
123 & 0.196859 & 0.393718 & 0.803141 \tabularnewline
124 & 0.17964 & 0.359279 & 0.82036 \tabularnewline
125 & 0.198848 & 0.397695 & 0.801152 \tabularnewline
126 & 0.191369 & 0.382738 & 0.808631 \tabularnewline
127 & 0.26521 & 0.53042 & 0.73479 \tabularnewline
128 & 0.243679 & 0.487357 & 0.756321 \tabularnewline
129 & 0.218763 & 0.437526 & 0.781237 \tabularnewline
130 & 0.249128 & 0.498256 & 0.750872 \tabularnewline
131 & 0.225443 & 0.450886 & 0.774557 \tabularnewline
132 & 0.225018 & 0.450036 & 0.774982 \tabularnewline
133 & 0.211028 & 0.422057 & 0.788972 \tabularnewline
134 & 0.202839 & 0.405679 & 0.797161 \tabularnewline
135 & 0.196946 & 0.393893 & 0.803054 \tabularnewline
136 & 0.175138 & 0.350276 & 0.824862 \tabularnewline
137 & 0.179066 & 0.358131 & 0.820934 \tabularnewline
138 & 0.161372 & 0.322745 & 0.838628 \tabularnewline
139 & 0.141317 & 0.282635 & 0.858683 \tabularnewline
140 & 0.124463 & 0.248927 & 0.875537 \tabularnewline
141 & 0.129027 & 0.258053 & 0.870973 \tabularnewline
142 & 0.11187 & 0.22374 & 0.88813 \tabularnewline
143 & 0.103993 & 0.207985 & 0.896007 \tabularnewline
144 & 0.102528 & 0.205056 & 0.897472 \tabularnewline
145 & 0.0957765 & 0.191553 & 0.904223 \tabularnewline
146 & 0.0915772 & 0.183154 & 0.908423 \tabularnewline
147 & 0.0821068 & 0.164214 & 0.917893 \tabularnewline
148 & 0.115264 & 0.230528 & 0.884736 \tabularnewline
149 & 0.114147 & 0.228295 & 0.885853 \tabularnewline
150 & 0.104189 & 0.208378 & 0.895811 \tabularnewline
151 & 0.105922 & 0.211844 & 0.894078 \tabularnewline
152 & 0.110513 & 0.221025 & 0.889487 \tabularnewline
153 & 0.189405 & 0.378809 & 0.810595 \tabularnewline
154 & 0.170852 & 0.341705 & 0.829148 \tabularnewline
155 & 0.150218 & 0.300436 & 0.849782 \tabularnewline
156 & 0.224255 & 0.448511 & 0.775745 \tabularnewline
157 & 0.204047 & 0.408094 & 0.795953 \tabularnewline
158 & 0.189327 & 0.378654 & 0.810673 \tabularnewline
159 & 0.184034 & 0.368068 & 0.815966 \tabularnewline
160 & 0.178223 & 0.356446 & 0.821777 \tabularnewline
161 & 0.182119 & 0.364239 & 0.817881 \tabularnewline
162 & 0.210798 & 0.421596 & 0.789202 \tabularnewline
163 & 0.190216 & 0.380432 & 0.809784 \tabularnewline
164 & 0.177346 & 0.354693 & 0.822654 \tabularnewline
165 & 0.1601 & 0.3202 & 0.8399 \tabularnewline
166 & 0.200349 & 0.400697 & 0.799651 \tabularnewline
167 & 0.224687 & 0.449374 & 0.775313 \tabularnewline
168 & 0.203656 & 0.407312 & 0.796344 \tabularnewline
169 & 0.213102 & 0.426203 & 0.786898 \tabularnewline
170 & 0.232327 & 0.464654 & 0.767673 \tabularnewline
171 & 0.211212 & 0.422424 & 0.788788 \tabularnewline
172 & 0.227887 & 0.455773 & 0.772113 \tabularnewline
173 & 0.204188 & 0.408376 & 0.795812 \tabularnewline
174 & 0.245903 & 0.491807 & 0.754097 \tabularnewline
175 & 0.220842 & 0.441684 & 0.779158 \tabularnewline
176 & 0.235285 & 0.470569 & 0.764715 \tabularnewline
177 & 0.224527 & 0.449053 & 0.775473 \tabularnewline
178 & 0.201342 & 0.402685 & 0.798658 \tabularnewline
179 & 0.181145 & 0.362291 & 0.818855 \tabularnewline
180 & 0.176897 & 0.353794 & 0.823103 \tabularnewline
181 & 0.161871 & 0.323742 & 0.838129 \tabularnewline
182 & 0.194233 & 0.388466 & 0.805767 \tabularnewline
183 & 0.171232 & 0.342465 & 0.828768 \tabularnewline
184 & 0.15471 & 0.30942 & 0.84529 \tabularnewline
185 & 0.145996 & 0.291992 & 0.854004 \tabularnewline
186 & 0.128965 & 0.257929 & 0.871035 \tabularnewline
187 & 0.115317 & 0.230634 & 0.884683 \tabularnewline
188 & 0.11085 & 0.221699 & 0.88915 \tabularnewline
189 & 0.0961914 & 0.192383 & 0.903809 \tabularnewline
190 & 0.0917158 & 0.183432 & 0.908284 \tabularnewline
191 & 0.0906078 & 0.181216 & 0.909392 \tabularnewline
192 & 0.0854808 & 0.170962 & 0.914519 \tabularnewline
193 & 0.0728997 & 0.145799 & 0.9271 \tabularnewline
194 & 0.0622634 & 0.124527 & 0.937737 \tabularnewline
195 & 0.0528176 & 0.105635 & 0.947182 \tabularnewline
196 & 0.0800264 & 0.160053 & 0.919974 \tabularnewline
197 & 0.0994224 & 0.198845 & 0.900578 \tabularnewline
198 & 0.101448 & 0.202896 & 0.898552 \tabularnewline
199 & 0.155225 & 0.31045 & 0.844775 \tabularnewline
200 & 0.135751 & 0.271502 & 0.864249 \tabularnewline
201 & 0.127383 & 0.254766 & 0.872617 \tabularnewline
202 & 0.119725 & 0.23945 & 0.880275 \tabularnewline
203 & 0.104402 & 0.208805 & 0.895598 \tabularnewline
204 & 0.11976 & 0.239521 & 0.88024 \tabularnewline
205 & 0.103436 & 0.206872 & 0.896564 \tabularnewline
206 & 0.120919 & 0.241838 & 0.879081 \tabularnewline
207 & 0.155219 & 0.310438 & 0.844781 \tabularnewline
208 & 0.19079 & 0.381581 & 0.80921 \tabularnewline
209 & 0.173081 & 0.346162 & 0.826919 \tabularnewline
210 & 0.174791 & 0.349581 & 0.825209 \tabularnewline
211 & 0.170911 & 0.341822 & 0.829089 \tabularnewline
212 & 0.170632 & 0.341265 & 0.829368 \tabularnewline
213 & 0.207342 & 0.414684 & 0.792658 \tabularnewline
214 & 0.185558 & 0.371115 & 0.814442 \tabularnewline
215 & 0.248218 & 0.496437 & 0.751782 \tabularnewline
216 & 0.243473 & 0.486945 & 0.756527 \tabularnewline
217 & 0.222256 & 0.444511 & 0.777744 \tabularnewline
218 & 0.260793 & 0.521586 & 0.739207 \tabularnewline
219 & 0.278272 & 0.556545 & 0.721728 \tabularnewline
220 & 0.288015 & 0.576031 & 0.711985 \tabularnewline
221 & 0.340846 & 0.681693 & 0.659154 \tabularnewline
222 & 0.614508 & 0.770985 & 0.385492 \tabularnewline
223 & 0.57468 & 0.85064 & 0.42532 \tabularnewline
224 & 0.65609 & 0.68782 & 0.34391 \tabularnewline
225 & 0.62469 & 0.75062 & 0.37531 \tabularnewline
226 & 0.593998 & 0.812004 & 0.406002 \tabularnewline
227 & 0.617974 & 0.764053 & 0.382026 \tabularnewline
228 & 0.653466 & 0.693067 & 0.346534 \tabularnewline
229 & 0.614358 & 0.771284 & 0.385642 \tabularnewline
230 & 0.653856 & 0.692287 & 0.346144 \tabularnewline
231 & 0.629462 & 0.741076 & 0.370538 \tabularnewline
232 & 0.590871 & 0.818258 & 0.409129 \tabularnewline
233 & 0.546736 & 0.906528 & 0.453264 \tabularnewline
234 & 0.566684 & 0.866631 & 0.433316 \tabularnewline
235 & 0.534105 & 0.93179 & 0.465895 \tabularnewline
236 & 0.48802 & 0.976039 & 0.51198 \tabularnewline
237 & 0.626889 & 0.746222 & 0.373111 \tabularnewline
238 & 0.58629 & 0.82742 & 0.41371 \tabularnewline
239 & 0.543459 & 0.913082 & 0.456541 \tabularnewline
240 & 0.504809 & 0.990383 & 0.495191 \tabularnewline
241 & 0.46425 & 0.9285 & 0.53575 \tabularnewline
242 & 0.424125 & 0.84825 & 0.575875 \tabularnewline
243 & 0.441476 & 0.882952 & 0.558524 \tabularnewline
244 & 0.41267 & 0.825341 & 0.58733 \tabularnewline
245 & 0.448869 & 0.897738 & 0.551131 \tabularnewline
246 & 0.407743 & 0.815485 & 0.592257 \tabularnewline
247 & 0.378328 & 0.756655 & 0.621672 \tabularnewline
248 & 0.339086 & 0.678172 & 0.660914 \tabularnewline
249 & 0.295672 & 0.591344 & 0.704328 \tabularnewline
250 & 0.255626 & 0.511252 & 0.744374 \tabularnewline
251 & 0.311662 & 0.623323 & 0.688338 \tabularnewline
252 & 0.345845 & 0.691689 & 0.654155 \tabularnewline
253 & 0.326054 & 0.652107 & 0.673946 \tabularnewline
254 & 0.302928 & 0.605857 & 0.697072 \tabularnewline
255 & 0.259367 & 0.518734 & 0.740633 \tabularnewline
256 & 0.249802 & 0.499604 & 0.750198 \tabularnewline
257 & 0.441994 & 0.883988 & 0.558006 \tabularnewline
258 & 0.416714 & 0.833428 & 0.583286 \tabularnewline
259 & 0.664037 & 0.671926 & 0.335963 \tabularnewline
260 & 0.680623 & 0.638754 & 0.319377 \tabularnewline
261 & 0.628777 & 0.742445 & 0.371223 \tabularnewline
262 & 0.567835 & 0.864329 & 0.432165 \tabularnewline
263 & 0.504734 & 0.990532 & 0.495266 \tabularnewline
264 & 0.784775 & 0.430451 & 0.215225 \tabularnewline
265 & 0.736835 & 0.52633 & 0.263165 \tabularnewline
266 & 0.689318 & 0.621363 & 0.310682 \tabularnewline
267 & 0.70924 & 0.58152 & 0.29076 \tabularnewline
268 & 0.711042 & 0.577916 & 0.288958 \tabularnewline
269 & 0.633612 & 0.732777 & 0.366388 \tabularnewline
270 & 0.555492 & 0.889016 & 0.444508 \tabularnewline
271 & 0.661196 & 0.677608 & 0.338804 \tabularnewline
272 & 0.57345 & 0.853101 & 0.42655 \tabularnewline
273 & 0.502887 & 0.994227 & 0.497113 \tabularnewline
274 & 0.407128 & 0.814257 & 0.592872 \tabularnewline
275 & 0.351474 & 0.702948 & 0.648526 \tabularnewline
276 & 0.264097 & 0.528194 & 0.735903 \tabularnewline
277 & 0.189739 & 0.379479 & 0.810261 \tabularnewline
278 & 0.11203 & 0.22406 & 0.88797 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231545&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]10[/C][C]0.35893[/C][C]0.71786[/C][C]0.64107[/C][/ROW]
[ROW][C]11[/C][C]0.44874[/C][C]0.897479[/C][C]0.55126[/C][/ROW]
[ROW][C]12[/C][C]0.676363[/C][C]0.647274[/C][C]0.323637[/C][/ROW]
[ROW][C]13[/C][C]0.695973[/C][C]0.608053[/C][C]0.304027[/C][/ROW]
[ROW][C]14[/C][C]0.634185[/C][C]0.73163[/C][C]0.365815[/C][/ROW]
[ROW][C]15[/C][C]0.830223[/C][C]0.339554[/C][C]0.169777[/C][/ROW]
[ROW][C]16[/C][C]0.773807[/C][C]0.452387[/C][C]0.226193[/C][/ROW]
[ROW][C]17[/C][C]0.698329[/C][C]0.603341[/C][C]0.301671[/C][/ROW]
[ROW][C]18[/C][C]0.719154[/C][C]0.561693[/C][C]0.280846[/C][/ROW]
[ROW][C]19[/C][C]0.666003[/C][C]0.667995[/C][C]0.333997[/C][/ROW]
[ROW][C]20[/C][C]0.590427[/C][C]0.819146[/C][C]0.409573[/C][/ROW]
[ROW][C]21[/C][C]0.754601[/C][C]0.490797[/C][C]0.245399[/C][/ROW]
[ROW][C]22[/C][C]0.865231[/C][C]0.269538[/C][C]0.134769[/C][/ROW]
[ROW][C]23[/C][C]0.831599[/C][C]0.336801[/C][C]0.168401[/C][/ROW]
[ROW][C]24[/C][C]0.837855[/C][C]0.324289[/C][C]0.162145[/C][/ROW]
[ROW][C]25[/C][C]0.81686[/C][C]0.366281[/C][C]0.18314[/C][/ROW]
[ROW][C]26[/C][C]0.968552[/C][C]0.062897[/C][C]0.0314485[/C][/ROW]
[ROW][C]27[/C][C]0.960834[/C][C]0.0783327[/C][C]0.0391663[/C][/ROW]
[ROW][C]28[/C][C]0.946724[/C][C]0.106552[/C][C]0.0532758[/C][/ROW]
[ROW][C]29[/C][C]0.928409[/C][C]0.143182[/C][C]0.0715911[/C][/ROW]
[ROW][C]30[/C][C]0.943827[/C][C]0.112346[/C][C]0.0561728[/C][/ROW]
[ROW][C]31[/C][C]0.929133[/C][C]0.141733[/C][C]0.0708667[/C][/ROW]
[ROW][C]32[/C][C]0.912499[/C][C]0.175001[/C][C]0.0875007[/C][/ROW]
[ROW][C]33[/C][C]0.898222[/C][C]0.203556[/C][C]0.101778[/C][/ROW]
[ROW][C]34[/C][C]0.872018[/C][C]0.255965[/C][C]0.127982[/C][/ROW]
[ROW][C]35[/C][C]0.841622[/C][C]0.316756[/C][C]0.158378[/C][/ROW]
[ROW][C]36[/C][C]0.821589[/C][C]0.356823[/C][C]0.178411[/C][/ROW]
[ROW][C]37[/C][C]0.900463[/C][C]0.199075[/C][C]0.0995373[/C][/ROW]
[ROW][C]38[/C][C]0.881846[/C][C]0.236308[/C][C]0.118154[/C][/ROW]
[ROW][C]39[/C][C]0.8734[/C][C]0.2532[/C][C]0.1266[/C][/ROW]
[ROW][C]40[/C][C]0.850472[/C][C]0.299057[/C][C]0.149528[/C][/ROW]
[ROW][C]41[/C][C]0.821998[/C][C]0.356004[/C][C]0.178002[/C][/ROW]
[ROW][C]42[/C][C]0.795749[/C][C]0.408501[/C][C]0.204251[/C][/ROW]
[ROW][C]43[/C][C]0.77857[/C][C]0.442859[/C][C]0.22143[/C][/ROW]
[ROW][C]44[/C][C]0.763547[/C][C]0.472907[/C][C]0.236453[/C][/ROW]
[ROW][C]45[/C][C]0.731269[/C][C]0.537461[/C][C]0.268731[/C][/ROW]
[ROW][C]46[/C][C]0.753714[/C][C]0.492573[/C][C]0.246286[/C][/ROW]
[ROW][C]47[/C][C]0.720858[/C][C]0.558285[/C][C]0.279142[/C][/ROW]
[ROW][C]48[/C][C]0.680279[/C][C]0.639442[/C][C]0.319721[/C][/ROW]
[ROW][C]49[/C][C]0.672525[/C][C]0.654949[/C][C]0.327475[/C][/ROW]
[ROW][C]50[/C][C]0.631815[/C][C]0.736369[/C][C]0.368185[/C][/ROW]
[ROW][C]51[/C][C]0.60794[/C][C]0.784119[/C][C]0.39206[/C][/ROW]
[ROW][C]52[/C][C]0.563595[/C][C]0.872809[/C][C]0.436405[/C][/ROW]
[ROW][C]53[/C][C]0.544457[/C][C]0.911087[/C][C]0.455543[/C][/ROW]
[ROW][C]54[/C][C]0.549537[/C][C]0.900926[/C][C]0.450463[/C][/ROW]
[ROW][C]55[/C][C]0.51545[/C][C]0.9691[/C][C]0.48455[/C][/ROW]
[ROW][C]56[/C][C]0.474046[/C][C]0.948092[/C][C]0.525954[/C][/ROW]
[ROW][C]57[/C][C]0.437203[/C][C]0.874405[/C][C]0.562797[/C][/ROW]
[ROW][C]58[/C][C]0.394918[/C][C]0.789835[/C][C]0.605082[/C][/ROW]
[ROW][C]59[/C][C]0.369222[/C][C]0.738444[/C][C]0.630778[/C][/ROW]
[ROW][C]60[/C][C]0.404474[/C][C]0.808949[/C][C]0.595526[/C][/ROW]
[ROW][C]61[/C][C]0.575628[/C][C]0.848744[/C][C]0.424372[/C][/ROW]
[ROW][C]62[/C][C]0.538188[/C][C]0.923624[/C][C]0.461812[/C][/ROW]
[ROW][C]63[/C][C]0.588573[/C][C]0.822853[/C][C]0.411427[/C][/ROW]
[ROW][C]64[/C][C]0.547075[/C][C]0.90585[/C][C]0.452925[/C][/ROW]
[ROW][C]65[/C][C]0.505958[/C][C]0.988084[/C][C]0.494042[/C][/ROW]
[ROW][C]66[/C][C]0.551511[/C][C]0.896978[/C][C]0.448489[/C][/ROW]
[ROW][C]67[/C][C]0.618797[/C][C]0.762406[/C][C]0.381203[/C][/ROW]
[ROW][C]68[/C][C]0.60374[/C][C]0.79252[/C][C]0.39626[/C][/ROW]
[ROW][C]69[/C][C]0.569891[/C][C]0.860218[/C][C]0.430109[/C][/ROW]
[ROW][C]70[/C][C]0.550651[/C][C]0.898697[/C][C]0.449349[/C][/ROW]
[ROW][C]71[/C][C]0.515773[/C][C]0.968453[/C][C]0.484227[/C][/ROW]
[ROW][C]72[/C][C]0.501041[/C][C]0.997917[/C][C]0.498959[/C][/ROW]
[ROW][C]73[/C][C]0.462003[/C][C]0.924007[/C][C]0.537997[/C][/ROW]
[ROW][C]74[/C][C]0.433934[/C][C]0.867868[/C][C]0.566066[/C][/ROW]
[ROW][C]75[/C][C]0.396426[/C][C]0.792852[/C][C]0.603574[/C][/ROW]
[ROW][C]76[/C][C]0.431417[/C][C]0.862835[/C][C]0.568583[/C][/ROW]
[ROW][C]77[/C][C]0.428994[/C][C]0.857989[/C][C]0.571006[/C][/ROW]
[ROW][C]78[/C][C]0.406668[/C][C]0.813336[/C][C]0.593332[/C][/ROW]
[ROW][C]79[/C][C]0.402197[/C][C]0.804395[/C][C]0.597803[/C][/ROW]
[ROW][C]80[/C][C]0.367085[/C][C]0.73417[/C][C]0.632915[/C][/ROW]
[ROW][C]81[/C][C]0.343765[/C][C]0.68753[/C][C]0.656235[/C][/ROW]
[ROW][C]82[/C][C]0.309832[/C][C]0.619665[/C][C]0.690168[/C][/ROW]
[ROW][C]83[/C][C]0.310957[/C][C]0.621913[/C][C]0.689043[/C][/ROW]
[ROW][C]84[/C][C]0.280198[/C][C]0.560395[/C][C]0.719802[/C][/ROW]
[ROW][C]85[/C][C]0.250026[/C][C]0.500052[/C][C]0.749974[/C][/ROW]
[ROW][C]86[/C][C]0.227791[/C][C]0.455582[/C][C]0.772209[/C][/ROW]
[ROW][C]87[/C][C]0.201098[/C][C]0.402196[/C][C]0.798902[/C][/ROW]
[ROW][C]88[/C][C]0.181629[/C][C]0.363258[/C][C]0.818371[/C][/ROW]
[ROW][C]89[/C][C]0.451152[/C][C]0.902305[/C][C]0.548848[/C][/ROW]
[ROW][C]90[/C][C]0.47079[/C][C]0.94158[/C][C]0.52921[/C][/ROW]
[ROW][C]91[/C][C]0.445485[/C][C]0.89097[/C][C]0.554515[/C][/ROW]
[ROW][C]92[/C][C]0.41057[/C][C]0.82114[/C][C]0.58943[/C][/ROW]
[ROW][C]93[/C][C]0.375867[/C][C]0.751734[/C][C]0.624133[/C][/ROW]
[ROW][C]94[/C][C]0.344166[/C][C]0.688331[/C][C]0.655834[/C][/ROW]
[ROW][C]95[/C][C]0.317937[/C][C]0.635873[/C][C]0.682063[/C][/ROW]
[ROW][C]96[/C][C]0.322724[/C][C]0.645448[/C][C]0.677276[/C][/ROW]
[ROW][C]97[/C][C]0.292294[/C][C]0.584587[/C][C]0.707706[/C][/ROW]
[ROW][C]98[/C][C]0.318622[/C][C]0.637243[/C][C]0.681378[/C][/ROW]
[ROW][C]99[/C][C]0.298419[/C][C]0.596838[/C][C]0.701581[/C][/ROW]
[ROW][C]100[/C][C]0.300578[/C][C]0.601156[/C][C]0.699422[/C][/ROW]
[ROW][C]101[/C][C]0.290582[/C][C]0.581164[/C][C]0.709418[/C][/ROW]
[ROW][C]102[/C][C]0.266591[/C][C]0.533181[/C][C]0.733409[/C][/ROW]
[ROW][C]103[/C][C]0.262907[/C][C]0.525814[/C][C]0.737093[/C][/ROW]
[ROW][C]104[/C][C]0.235756[/C][C]0.471511[/C][C]0.764244[/C][/ROW]
[ROW][C]105[/C][C]0.309761[/C][C]0.619522[/C][C]0.690239[/C][/ROW]
[ROW][C]106[/C][C]0.286712[/C][C]0.573424[/C][C]0.713288[/C][/ROW]
[ROW][C]107[/C][C]0.261279[/C][C]0.522558[/C][C]0.738721[/C][/ROW]
[ROW][C]108[/C][C]0.311063[/C][C]0.622127[/C][C]0.688937[/C][/ROW]
[ROW][C]109[/C][C]0.414442[/C][C]0.828883[/C][C]0.585558[/C][/ROW]
[ROW][C]110[/C][C]0.382458[/C][C]0.764916[/C][C]0.617542[/C][/ROW]
[ROW][C]111[/C][C]0.412973[/C][C]0.825947[/C][C]0.587027[/C][/ROW]
[ROW][C]112[/C][C]0.399762[/C][C]0.799523[/C][C]0.600238[/C][/ROW]
[ROW][C]113[/C][C]0.458283[/C][C]0.916567[/C][C]0.541717[/C][/ROW]
[ROW][C]114[/C][C]0.449212[/C][C]0.898425[/C][C]0.550788[/C][/ROW]
[ROW][C]115[/C][C]0.415331[/C][C]0.830662[/C][C]0.584669[/C][/ROW]
[ROW][C]116[/C][C]0.38328[/C][C]0.76656[/C][C]0.61672[/C][/ROW]
[ROW][C]117[/C][C]0.350292[/C][C]0.700583[/C][C]0.649708[/C][/ROW]
[ROW][C]118[/C][C]0.320553[/C][C]0.641107[/C][C]0.679447[/C][/ROW]
[ROW][C]119[/C][C]0.298642[/C][C]0.597285[/C][C]0.701358[/C][/ROW]
[ROW][C]120[/C][C]0.270332[/C][C]0.540664[/C][C]0.729668[/C][/ROW]
[ROW][C]121[/C][C]0.245185[/C][C]0.49037[/C][C]0.754815[/C][/ROW]
[ROW][C]122[/C][C]0.219682[/C][C]0.439363[/C][C]0.780318[/C][/ROW]
[ROW][C]123[/C][C]0.196859[/C][C]0.393718[/C][C]0.803141[/C][/ROW]
[ROW][C]124[/C][C]0.17964[/C][C]0.359279[/C][C]0.82036[/C][/ROW]
[ROW][C]125[/C][C]0.198848[/C][C]0.397695[/C][C]0.801152[/C][/ROW]
[ROW][C]126[/C][C]0.191369[/C][C]0.382738[/C][C]0.808631[/C][/ROW]
[ROW][C]127[/C][C]0.26521[/C][C]0.53042[/C][C]0.73479[/C][/ROW]
[ROW][C]128[/C][C]0.243679[/C][C]0.487357[/C][C]0.756321[/C][/ROW]
[ROW][C]129[/C][C]0.218763[/C][C]0.437526[/C][C]0.781237[/C][/ROW]
[ROW][C]130[/C][C]0.249128[/C][C]0.498256[/C][C]0.750872[/C][/ROW]
[ROW][C]131[/C][C]0.225443[/C][C]0.450886[/C][C]0.774557[/C][/ROW]
[ROW][C]132[/C][C]0.225018[/C][C]0.450036[/C][C]0.774982[/C][/ROW]
[ROW][C]133[/C][C]0.211028[/C][C]0.422057[/C][C]0.788972[/C][/ROW]
[ROW][C]134[/C][C]0.202839[/C][C]0.405679[/C][C]0.797161[/C][/ROW]
[ROW][C]135[/C][C]0.196946[/C][C]0.393893[/C][C]0.803054[/C][/ROW]
[ROW][C]136[/C][C]0.175138[/C][C]0.350276[/C][C]0.824862[/C][/ROW]
[ROW][C]137[/C][C]0.179066[/C][C]0.358131[/C][C]0.820934[/C][/ROW]
[ROW][C]138[/C][C]0.161372[/C][C]0.322745[/C][C]0.838628[/C][/ROW]
[ROW][C]139[/C][C]0.141317[/C][C]0.282635[/C][C]0.858683[/C][/ROW]
[ROW][C]140[/C][C]0.124463[/C][C]0.248927[/C][C]0.875537[/C][/ROW]
[ROW][C]141[/C][C]0.129027[/C][C]0.258053[/C][C]0.870973[/C][/ROW]
[ROW][C]142[/C][C]0.11187[/C][C]0.22374[/C][C]0.88813[/C][/ROW]
[ROW][C]143[/C][C]0.103993[/C][C]0.207985[/C][C]0.896007[/C][/ROW]
[ROW][C]144[/C][C]0.102528[/C][C]0.205056[/C][C]0.897472[/C][/ROW]
[ROW][C]145[/C][C]0.0957765[/C][C]0.191553[/C][C]0.904223[/C][/ROW]
[ROW][C]146[/C][C]0.0915772[/C][C]0.183154[/C][C]0.908423[/C][/ROW]
[ROW][C]147[/C][C]0.0821068[/C][C]0.164214[/C][C]0.917893[/C][/ROW]
[ROW][C]148[/C][C]0.115264[/C][C]0.230528[/C][C]0.884736[/C][/ROW]
[ROW][C]149[/C][C]0.114147[/C][C]0.228295[/C][C]0.885853[/C][/ROW]
[ROW][C]150[/C][C]0.104189[/C][C]0.208378[/C][C]0.895811[/C][/ROW]
[ROW][C]151[/C][C]0.105922[/C][C]0.211844[/C][C]0.894078[/C][/ROW]
[ROW][C]152[/C][C]0.110513[/C][C]0.221025[/C][C]0.889487[/C][/ROW]
[ROW][C]153[/C][C]0.189405[/C][C]0.378809[/C][C]0.810595[/C][/ROW]
[ROW][C]154[/C][C]0.170852[/C][C]0.341705[/C][C]0.829148[/C][/ROW]
[ROW][C]155[/C][C]0.150218[/C][C]0.300436[/C][C]0.849782[/C][/ROW]
[ROW][C]156[/C][C]0.224255[/C][C]0.448511[/C][C]0.775745[/C][/ROW]
[ROW][C]157[/C][C]0.204047[/C][C]0.408094[/C][C]0.795953[/C][/ROW]
[ROW][C]158[/C][C]0.189327[/C][C]0.378654[/C][C]0.810673[/C][/ROW]
[ROW][C]159[/C][C]0.184034[/C][C]0.368068[/C][C]0.815966[/C][/ROW]
[ROW][C]160[/C][C]0.178223[/C][C]0.356446[/C][C]0.821777[/C][/ROW]
[ROW][C]161[/C][C]0.182119[/C][C]0.364239[/C][C]0.817881[/C][/ROW]
[ROW][C]162[/C][C]0.210798[/C][C]0.421596[/C][C]0.789202[/C][/ROW]
[ROW][C]163[/C][C]0.190216[/C][C]0.380432[/C][C]0.809784[/C][/ROW]
[ROW][C]164[/C][C]0.177346[/C][C]0.354693[/C][C]0.822654[/C][/ROW]
[ROW][C]165[/C][C]0.1601[/C][C]0.3202[/C][C]0.8399[/C][/ROW]
[ROW][C]166[/C][C]0.200349[/C][C]0.400697[/C][C]0.799651[/C][/ROW]
[ROW][C]167[/C][C]0.224687[/C][C]0.449374[/C][C]0.775313[/C][/ROW]
[ROW][C]168[/C][C]0.203656[/C][C]0.407312[/C][C]0.796344[/C][/ROW]
[ROW][C]169[/C][C]0.213102[/C][C]0.426203[/C][C]0.786898[/C][/ROW]
[ROW][C]170[/C][C]0.232327[/C][C]0.464654[/C][C]0.767673[/C][/ROW]
[ROW][C]171[/C][C]0.211212[/C][C]0.422424[/C][C]0.788788[/C][/ROW]
[ROW][C]172[/C][C]0.227887[/C][C]0.455773[/C][C]0.772113[/C][/ROW]
[ROW][C]173[/C][C]0.204188[/C][C]0.408376[/C][C]0.795812[/C][/ROW]
[ROW][C]174[/C][C]0.245903[/C][C]0.491807[/C][C]0.754097[/C][/ROW]
[ROW][C]175[/C][C]0.220842[/C][C]0.441684[/C][C]0.779158[/C][/ROW]
[ROW][C]176[/C][C]0.235285[/C][C]0.470569[/C][C]0.764715[/C][/ROW]
[ROW][C]177[/C][C]0.224527[/C][C]0.449053[/C][C]0.775473[/C][/ROW]
[ROW][C]178[/C][C]0.201342[/C][C]0.402685[/C][C]0.798658[/C][/ROW]
[ROW][C]179[/C][C]0.181145[/C][C]0.362291[/C][C]0.818855[/C][/ROW]
[ROW][C]180[/C][C]0.176897[/C][C]0.353794[/C][C]0.823103[/C][/ROW]
[ROW][C]181[/C][C]0.161871[/C][C]0.323742[/C][C]0.838129[/C][/ROW]
[ROW][C]182[/C][C]0.194233[/C][C]0.388466[/C][C]0.805767[/C][/ROW]
[ROW][C]183[/C][C]0.171232[/C][C]0.342465[/C][C]0.828768[/C][/ROW]
[ROW][C]184[/C][C]0.15471[/C][C]0.30942[/C][C]0.84529[/C][/ROW]
[ROW][C]185[/C][C]0.145996[/C][C]0.291992[/C][C]0.854004[/C][/ROW]
[ROW][C]186[/C][C]0.128965[/C][C]0.257929[/C][C]0.871035[/C][/ROW]
[ROW][C]187[/C][C]0.115317[/C][C]0.230634[/C][C]0.884683[/C][/ROW]
[ROW][C]188[/C][C]0.11085[/C][C]0.221699[/C][C]0.88915[/C][/ROW]
[ROW][C]189[/C][C]0.0961914[/C][C]0.192383[/C][C]0.903809[/C][/ROW]
[ROW][C]190[/C][C]0.0917158[/C][C]0.183432[/C][C]0.908284[/C][/ROW]
[ROW][C]191[/C][C]0.0906078[/C][C]0.181216[/C][C]0.909392[/C][/ROW]
[ROW][C]192[/C][C]0.0854808[/C][C]0.170962[/C][C]0.914519[/C][/ROW]
[ROW][C]193[/C][C]0.0728997[/C][C]0.145799[/C][C]0.9271[/C][/ROW]
[ROW][C]194[/C][C]0.0622634[/C][C]0.124527[/C][C]0.937737[/C][/ROW]
[ROW][C]195[/C][C]0.0528176[/C][C]0.105635[/C][C]0.947182[/C][/ROW]
[ROW][C]196[/C][C]0.0800264[/C][C]0.160053[/C][C]0.919974[/C][/ROW]
[ROW][C]197[/C][C]0.0994224[/C][C]0.198845[/C][C]0.900578[/C][/ROW]
[ROW][C]198[/C][C]0.101448[/C][C]0.202896[/C][C]0.898552[/C][/ROW]
[ROW][C]199[/C][C]0.155225[/C][C]0.31045[/C][C]0.844775[/C][/ROW]
[ROW][C]200[/C][C]0.135751[/C][C]0.271502[/C][C]0.864249[/C][/ROW]
[ROW][C]201[/C][C]0.127383[/C][C]0.254766[/C][C]0.872617[/C][/ROW]
[ROW][C]202[/C][C]0.119725[/C][C]0.23945[/C][C]0.880275[/C][/ROW]
[ROW][C]203[/C][C]0.104402[/C][C]0.208805[/C][C]0.895598[/C][/ROW]
[ROW][C]204[/C][C]0.11976[/C][C]0.239521[/C][C]0.88024[/C][/ROW]
[ROW][C]205[/C][C]0.103436[/C][C]0.206872[/C][C]0.896564[/C][/ROW]
[ROW][C]206[/C][C]0.120919[/C][C]0.241838[/C][C]0.879081[/C][/ROW]
[ROW][C]207[/C][C]0.155219[/C][C]0.310438[/C][C]0.844781[/C][/ROW]
[ROW][C]208[/C][C]0.19079[/C][C]0.381581[/C][C]0.80921[/C][/ROW]
[ROW][C]209[/C][C]0.173081[/C][C]0.346162[/C][C]0.826919[/C][/ROW]
[ROW][C]210[/C][C]0.174791[/C][C]0.349581[/C][C]0.825209[/C][/ROW]
[ROW][C]211[/C][C]0.170911[/C][C]0.341822[/C][C]0.829089[/C][/ROW]
[ROW][C]212[/C][C]0.170632[/C][C]0.341265[/C][C]0.829368[/C][/ROW]
[ROW][C]213[/C][C]0.207342[/C][C]0.414684[/C][C]0.792658[/C][/ROW]
[ROW][C]214[/C][C]0.185558[/C][C]0.371115[/C][C]0.814442[/C][/ROW]
[ROW][C]215[/C][C]0.248218[/C][C]0.496437[/C][C]0.751782[/C][/ROW]
[ROW][C]216[/C][C]0.243473[/C][C]0.486945[/C][C]0.756527[/C][/ROW]
[ROW][C]217[/C][C]0.222256[/C][C]0.444511[/C][C]0.777744[/C][/ROW]
[ROW][C]218[/C][C]0.260793[/C][C]0.521586[/C][C]0.739207[/C][/ROW]
[ROW][C]219[/C][C]0.278272[/C][C]0.556545[/C][C]0.721728[/C][/ROW]
[ROW][C]220[/C][C]0.288015[/C][C]0.576031[/C][C]0.711985[/C][/ROW]
[ROW][C]221[/C][C]0.340846[/C][C]0.681693[/C][C]0.659154[/C][/ROW]
[ROW][C]222[/C][C]0.614508[/C][C]0.770985[/C][C]0.385492[/C][/ROW]
[ROW][C]223[/C][C]0.57468[/C][C]0.85064[/C][C]0.42532[/C][/ROW]
[ROW][C]224[/C][C]0.65609[/C][C]0.68782[/C][C]0.34391[/C][/ROW]
[ROW][C]225[/C][C]0.62469[/C][C]0.75062[/C][C]0.37531[/C][/ROW]
[ROW][C]226[/C][C]0.593998[/C][C]0.812004[/C][C]0.406002[/C][/ROW]
[ROW][C]227[/C][C]0.617974[/C][C]0.764053[/C][C]0.382026[/C][/ROW]
[ROW][C]228[/C][C]0.653466[/C][C]0.693067[/C][C]0.346534[/C][/ROW]
[ROW][C]229[/C][C]0.614358[/C][C]0.771284[/C][C]0.385642[/C][/ROW]
[ROW][C]230[/C][C]0.653856[/C][C]0.692287[/C][C]0.346144[/C][/ROW]
[ROW][C]231[/C][C]0.629462[/C][C]0.741076[/C][C]0.370538[/C][/ROW]
[ROW][C]232[/C][C]0.590871[/C][C]0.818258[/C][C]0.409129[/C][/ROW]
[ROW][C]233[/C][C]0.546736[/C][C]0.906528[/C][C]0.453264[/C][/ROW]
[ROW][C]234[/C][C]0.566684[/C][C]0.866631[/C][C]0.433316[/C][/ROW]
[ROW][C]235[/C][C]0.534105[/C][C]0.93179[/C][C]0.465895[/C][/ROW]
[ROW][C]236[/C][C]0.48802[/C][C]0.976039[/C][C]0.51198[/C][/ROW]
[ROW][C]237[/C][C]0.626889[/C][C]0.746222[/C][C]0.373111[/C][/ROW]
[ROW][C]238[/C][C]0.58629[/C][C]0.82742[/C][C]0.41371[/C][/ROW]
[ROW][C]239[/C][C]0.543459[/C][C]0.913082[/C][C]0.456541[/C][/ROW]
[ROW][C]240[/C][C]0.504809[/C][C]0.990383[/C][C]0.495191[/C][/ROW]
[ROW][C]241[/C][C]0.46425[/C][C]0.9285[/C][C]0.53575[/C][/ROW]
[ROW][C]242[/C][C]0.424125[/C][C]0.84825[/C][C]0.575875[/C][/ROW]
[ROW][C]243[/C][C]0.441476[/C][C]0.882952[/C][C]0.558524[/C][/ROW]
[ROW][C]244[/C][C]0.41267[/C][C]0.825341[/C][C]0.58733[/C][/ROW]
[ROW][C]245[/C][C]0.448869[/C][C]0.897738[/C][C]0.551131[/C][/ROW]
[ROW][C]246[/C][C]0.407743[/C][C]0.815485[/C][C]0.592257[/C][/ROW]
[ROW][C]247[/C][C]0.378328[/C][C]0.756655[/C][C]0.621672[/C][/ROW]
[ROW][C]248[/C][C]0.339086[/C][C]0.678172[/C][C]0.660914[/C][/ROW]
[ROW][C]249[/C][C]0.295672[/C][C]0.591344[/C][C]0.704328[/C][/ROW]
[ROW][C]250[/C][C]0.255626[/C][C]0.511252[/C][C]0.744374[/C][/ROW]
[ROW][C]251[/C][C]0.311662[/C][C]0.623323[/C][C]0.688338[/C][/ROW]
[ROW][C]252[/C][C]0.345845[/C][C]0.691689[/C][C]0.654155[/C][/ROW]
[ROW][C]253[/C][C]0.326054[/C][C]0.652107[/C][C]0.673946[/C][/ROW]
[ROW][C]254[/C][C]0.302928[/C][C]0.605857[/C][C]0.697072[/C][/ROW]
[ROW][C]255[/C][C]0.259367[/C][C]0.518734[/C][C]0.740633[/C][/ROW]
[ROW][C]256[/C][C]0.249802[/C][C]0.499604[/C][C]0.750198[/C][/ROW]
[ROW][C]257[/C][C]0.441994[/C][C]0.883988[/C][C]0.558006[/C][/ROW]
[ROW][C]258[/C][C]0.416714[/C][C]0.833428[/C][C]0.583286[/C][/ROW]
[ROW][C]259[/C][C]0.664037[/C][C]0.671926[/C][C]0.335963[/C][/ROW]
[ROW][C]260[/C][C]0.680623[/C][C]0.638754[/C][C]0.319377[/C][/ROW]
[ROW][C]261[/C][C]0.628777[/C][C]0.742445[/C][C]0.371223[/C][/ROW]
[ROW][C]262[/C][C]0.567835[/C][C]0.864329[/C][C]0.432165[/C][/ROW]
[ROW][C]263[/C][C]0.504734[/C][C]0.990532[/C][C]0.495266[/C][/ROW]
[ROW][C]264[/C][C]0.784775[/C][C]0.430451[/C][C]0.215225[/C][/ROW]
[ROW][C]265[/C][C]0.736835[/C][C]0.52633[/C][C]0.263165[/C][/ROW]
[ROW][C]266[/C][C]0.689318[/C][C]0.621363[/C][C]0.310682[/C][/ROW]
[ROW][C]267[/C][C]0.70924[/C][C]0.58152[/C][C]0.29076[/C][/ROW]
[ROW][C]268[/C][C]0.711042[/C][C]0.577916[/C][C]0.288958[/C][/ROW]
[ROW][C]269[/C][C]0.633612[/C][C]0.732777[/C][C]0.366388[/C][/ROW]
[ROW][C]270[/C][C]0.555492[/C][C]0.889016[/C][C]0.444508[/C][/ROW]
[ROW][C]271[/C][C]0.661196[/C][C]0.677608[/C][C]0.338804[/C][/ROW]
[ROW][C]272[/C][C]0.57345[/C][C]0.853101[/C][C]0.42655[/C][/ROW]
[ROW][C]273[/C][C]0.502887[/C][C]0.994227[/C][C]0.497113[/C][/ROW]
[ROW][C]274[/C][C]0.407128[/C][C]0.814257[/C][C]0.592872[/C][/ROW]
[ROW][C]275[/C][C]0.351474[/C][C]0.702948[/C][C]0.648526[/C][/ROW]
[ROW][C]276[/C][C]0.264097[/C][C]0.528194[/C][C]0.735903[/C][/ROW]
[ROW][C]277[/C][C]0.189739[/C][C]0.379479[/C][C]0.810261[/C][/ROW]
[ROW][C]278[/C][C]0.11203[/C][C]0.22406[/C][C]0.88797[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231545&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231545&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.358930.717860.64107
110.448740.8974790.55126
120.6763630.6472740.323637
130.6959730.6080530.304027
140.6341850.731630.365815
150.8302230.3395540.169777
160.7738070.4523870.226193
170.6983290.6033410.301671
180.7191540.5616930.280846
190.6660030.6679950.333997
200.5904270.8191460.409573
210.7546010.4907970.245399
220.8652310.2695380.134769
230.8315990.3368010.168401
240.8378550.3242890.162145
250.816860.3662810.18314
260.9685520.0628970.0314485
270.9608340.07833270.0391663
280.9467240.1065520.0532758
290.9284090.1431820.0715911
300.9438270.1123460.0561728
310.9291330.1417330.0708667
320.9124990.1750010.0875007
330.8982220.2035560.101778
340.8720180.2559650.127982
350.8416220.3167560.158378
360.8215890.3568230.178411
370.9004630.1990750.0995373
380.8818460.2363080.118154
390.87340.25320.1266
400.8504720.2990570.149528
410.8219980.3560040.178002
420.7957490.4085010.204251
430.778570.4428590.22143
440.7635470.4729070.236453
450.7312690.5374610.268731
460.7537140.4925730.246286
470.7208580.5582850.279142
480.6802790.6394420.319721
490.6725250.6549490.327475
500.6318150.7363690.368185
510.607940.7841190.39206
520.5635950.8728090.436405
530.5444570.9110870.455543
540.5495370.9009260.450463
550.515450.96910.48455
560.4740460.9480920.525954
570.4372030.8744050.562797
580.3949180.7898350.605082
590.3692220.7384440.630778
600.4044740.8089490.595526
610.5756280.8487440.424372
620.5381880.9236240.461812
630.5885730.8228530.411427
640.5470750.905850.452925
650.5059580.9880840.494042
660.5515110.8969780.448489
670.6187970.7624060.381203
680.603740.792520.39626
690.5698910.8602180.430109
700.5506510.8986970.449349
710.5157730.9684530.484227
720.5010410.9979170.498959
730.4620030.9240070.537997
740.4339340.8678680.566066
750.3964260.7928520.603574
760.4314170.8628350.568583
770.4289940.8579890.571006
780.4066680.8133360.593332
790.4021970.8043950.597803
800.3670850.734170.632915
810.3437650.687530.656235
820.3098320.6196650.690168
830.3109570.6219130.689043
840.2801980.5603950.719802
850.2500260.5000520.749974
860.2277910.4555820.772209
870.2010980.4021960.798902
880.1816290.3632580.818371
890.4511520.9023050.548848
900.470790.941580.52921
910.4454850.890970.554515
920.410570.821140.58943
930.3758670.7517340.624133
940.3441660.6883310.655834
950.3179370.6358730.682063
960.3227240.6454480.677276
970.2922940.5845870.707706
980.3186220.6372430.681378
990.2984190.5968380.701581
1000.3005780.6011560.699422
1010.2905820.5811640.709418
1020.2665910.5331810.733409
1030.2629070.5258140.737093
1040.2357560.4715110.764244
1050.3097610.6195220.690239
1060.2867120.5734240.713288
1070.2612790.5225580.738721
1080.3110630.6221270.688937
1090.4144420.8288830.585558
1100.3824580.7649160.617542
1110.4129730.8259470.587027
1120.3997620.7995230.600238
1130.4582830.9165670.541717
1140.4492120.8984250.550788
1150.4153310.8306620.584669
1160.383280.766560.61672
1170.3502920.7005830.649708
1180.3205530.6411070.679447
1190.2986420.5972850.701358
1200.2703320.5406640.729668
1210.2451850.490370.754815
1220.2196820.4393630.780318
1230.1968590.3937180.803141
1240.179640.3592790.82036
1250.1988480.3976950.801152
1260.1913690.3827380.808631
1270.265210.530420.73479
1280.2436790.4873570.756321
1290.2187630.4375260.781237
1300.2491280.4982560.750872
1310.2254430.4508860.774557
1320.2250180.4500360.774982
1330.2110280.4220570.788972
1340.2028390.4056790.797161
1350.1969460.3938930.803054
1360.1751380.3502760.824862
1370.1790660.3581310.820934
1380.1613720.3227450.838628
1390.1413170.2826350.858683
1400.1244630.2489270.875537
1410.1290270.2580530.870973
1420.111870.223740.88813
1430.1039930.2079850.896007
1440.1025280.2050560.897472
1450.09577650.1915530.904223
1460.09157720.1831540.908423
1470.08210680.1642140.917893
1480.1152640.2305280.884736
1490.1141470.2282950.885853
1500.1041890.2083780.895811
1510.1059220.2118440.894078
1520.1105130.2210250.889487
1530.1894050.3788090.810595
1540.1708520.3417050.829148
1550.1502180.3004360.849782
1560.2242550.4485110.775745
1570.2040470.4080940.795953
1580.1893270.3786540.810673
1590.1840340.3680680.815966
1600.1782230.3564460.821777
1610.1821190.3642390.817881
1620.2107980.4215960.789202
1630.1902160.3804320.809784
1640.1773460.3546930.822654
1650.16010.32020.8399
1660.2003490.4006970.799651
1670.2246870.4493740.775313
1680.2036560.4073120.796344
1690.2131020.4262030.786898
1700.2323270.4646540.767673
1710.2112120.4224240.788788
1720.2278870.4557730.772113
1730.2041880.4083760.795812
1740.2459030.4918070.754097
1750.2208420.4416840.779158
1760.2352850.4705690.764715
1770.2245270.4490530.775473
1780.2013420.4026850.798658
1790.1811450.3622910.818855
1800.1768970.3537940.823103
1810.1618710.3237420.838129
1820.1942330.3884660.805767
1830.1712320.3424650.828768
1840.154710.309420.84529
1850.1459960.2919920.854004
1860.1289650.2579290.871035
1870.1153170.2306340.884683
1880.110850.2216990.88915
1890.09619140.1923830.903809
1900.09171580.1834320.908284
1910.09060780.1812160.909392
1920.08548080.1709620.914519
1930.07289970.1457990.9271
1940.06226340.1245270.937737
1950.05281760.1056350.947182
1960.08002640.1600530.919974
1970.09942240.1988450.900578
1980.1014480.2028960.898552
1990.1552250.310450.844775
2000.1357510.2715020.864249
2010.1273830.2547660.872617
2020.1197250.239450.880275
2030.1044020.2088050.895598
2040.119760.2395210.88024
2050.1034360.2068720.896564
2060.1209190.2418380.879081
2070.1552190.3104380.844781
2080.190790.3815810.80921
2090.1730810.3461620.826919
2100.1747910.3495810.825209
2110.1709110.3418220.829089
2120.1706320.3412650.829368
2130.2073420.4146840.792658
2140.1855580.3711150.814442
2150.2482180.4964370.751782
2160.2434730.4869450.756527
2170.2222560.4445110.777744
2180.2607930.5215860.739207
2190.2782720.5565450.721728
2200.2880150.5760310.711985
2210.3408460.6816930.659154
2220.6145080.7709850.385492
2230.574680.850640.42532
2240.656090.687820.34391
2250.624690.750620.37531
2260.5939980.8120040.406002
2270.6179740.7640530.382026
2280.6534660.6930670.346534
2290.6143580.7712840.385642
2300.6538560.6922870.346144
2310.6294620.7410760.370538
2320.5908710.8182580.409129
2330.5467360.9065280.453264
2340.5666840.8666310.433316
2350.5341050.931790.465895
2360.488020.9760390.51198
2370.6268890.7462220.373111
2380.586290.827420.41371
2390.5434590.9130820.456541
2400.5048090.9903830.495191
2410.464250.92850.53575
2420.4241250.848250.575875
2430.4414760.8829520.558524
2440.412670.8253410.58733
2450.4488690.8977380.551131
2460.4077430.8154850.592257
2470.3783280.7566550.621672
2480.3390860.6781720.660914
2490.2956720.5913440.704328
2500.2556260.5112520.744374
2510.3116620.6233230.688338
2520.3458450.6916890.654155
2530.3260540.6521070.673946
2540.3029280.6058570.697072
2550.2593670.5187340.740633
2560.2498020.4996040.750198
2570.4419940.8839880.558006
2580.4167140.8334280.583286
2590.6640370.6719260.335963
2600.6806230.6387540.319377
2610.6287770.7424450.371223
2620.5678350.8643290.432165
2630.5047340.9905320.495266
2640.7847750.4304510.215225
2650.7368350.526330.263165
2660.6893180.6213630.310682
2670.709240.581520.29076
2680.7110420.5779160.288958
2690.6336120.7327770.366388
2700.5554920.8890160.444508
2710.6611960.6776080.338804
2720.573450.8531010.42655
2730.5028870.9942270.497113
2740.4071280.8142570.592872
2750.3514740.7029480.648526
2760.2640970.5281940.735903
2770.1897390.3794790.810261
2780.112030.224060.88797







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level20.00743494OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 2 & 0.00743494 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231545&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]2[/C][C]0.00743494[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231545&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231545&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level20.00743494OK



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