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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 20 Nov 2013 10:25:22 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/20/t1384961306zjg71717oszb53g.htm/, Retrieved Wed, 01 May 2024 23:48:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226642, Retrieved Wed, 01 May 2024 23:48:07 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- R PD  [Multiple Regression] [Workshop 7 1] [2013-11-18 18:21:50] [cac6c5fb035463be46c296b46e439cb5]
- R PD    [Multiple Regression] [Workshop 7 monthl...] [2013-11-20 14:56:48] [cac6c5fb035463be46c296b46e439cb5]
-   P         [Multiple Regression] [Workshop 7 linear...] [2013-11-20 15:25:22] [37aff36f52ac1d7cbcd609d857f1662d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14 41 38 12 13
18 39 32 11 16
11 30 35 14 19
12 31 33 12 15
16 34 37 21 14
18 35 29 12 13
14 39 31 22 19
14 34 36 11 15
15 36 35 10 14
15 37 38 13 15
17 38 31 10 16
19 36 34 8 16
10 38 35 15 16
16 39 38 14 16
18 33 37 10 17
14 32 33 14 15
14 36 32 14 15
17 38 38 11 20
14 39 38 10 18
16 32 32 13 16
18 32 33 9.5 16
11 31 31 14 16
14 39 38 12 19
12 37 39 14 16
17 39 32 11 17
9 41 32 9 17
16 36 35 11 16
14 33 37 15 15
15 33 33 14 16
11 34 33 13 14
16 31 31 9 15
13 27 32 15 12
17 37 31 10 14
15 34 37 11 16
14 34 30 13 14
16 32 33 8 10
9 29 31 20 10
15 36 33 12 14
17 29 31 10 16
13 35 33 10 16
15 37 32 9 16
16 34 33 14 14
16 38 32 8 20
12 35 33 14 14
15 38 28 11 14
11 37 35 13 11
15 38 39 9 14
15 33 34 11 15
17 36 38 15 16
13 38 32 11 14
16 32 38 10 16
14 32 30 14 14
11 32 33 18 12
12 34 38 14 16
12 32 32 11 9
15 37 35 14.5 14
16 39 34 13 16
15 29 34 9 16
12 37 36 10 15
12 35 34 15 16
8 30 28 20 12
13 38 34 12 16
11 34 35 12 16
14 31 35 14 14
15 34 31 13 16
10 35 37 11 17
11 36 35 17 18
12 30 27 12 18
15 39 40 13 12
15 35 37 14 16
14 38 36 13 10
16 31 38 15 14
15 34 39 13 18
15 38 41 10 18
13 34 27 11 16
12 39 30 19 17
17 37 37 13 16
13 34 31 17 16
15 28 31 13 13
13 37 27 9 16
15 33 36 11 16
15 35 37 9 16
16 37 33 12 15
15 32 34 12 15
14 33 31 13 16
15 38 39 13 14
14 33 34 12 16
13 29 32 15 16
7 33 33 22 15
17 31 36 13 12
13 36 32 15 17
15 35 41 13 16
14 32 28 15 15
13 29 30 12.5 13
16 39 36 11 16
12 37 35 16 16
14 35 31 11 16
17 37 34 11 16
15 32 36 10 14
17 38 36 10 16
12 37 35 16 16
16 36 37 12 20
11 32 28 11 15
15 33 39 16 16
9 40 32 19 13
16 38 35 11 17
15 41 39 16 16
10 36 35 15 16
10 43 42 24 12
15 30 34 14 16
11 31 33 15 16
13 32 41 11 17
14 32 33 15 13
18 37 34 12 12
16 37 32 10 18
14 33 40 14 14
14 34 40 13 14
14 33 35 9 13
14 38 36 15 16
12 33 37 15 13
14 31 27 14 16
15 38 39 11 13
15 37 38 8 16
15 36 31 11 15
13 31 33 11 16
17 39 32 8 15
17 44 39 10 17
19 33 36 11 15
15 35 33 13 12
13 32 33 11 16
9 28 32 20 10
15 40 37 10 16
15 27 30 15 12
15 37 38 12 14
16 32 29 14 15
11 28 22 23 13
14 34 35 14 15
11 30 35 16 11
15 35 34 11 12
13 31 35 12 11
15 32 34 10 16
16 30 37 14 15
14 30 35 12 17
15 31 23 12 16
16 40 31 11 10
16 32 27 12 18
11 36 36 13 13
12 32 31 11 16
9 35 32 19 13
16 38 39 12 10
13 42 37 17 15
16 34 38 9 16
12 35 39 12 16
9 38 34 19 14
13 33 31 18 10
13 36 32 15 17
14 32 37 14 13
19 33 36 11 15
13 34 32 9 16
12 32 38 18 12
13 34 36 16 13
10 27 26 24 13
14 31 26 14 12
16 38 33 20 17
10 34 39 18 15
11 24 30 23 10
14 30 33 12 14
12 26 25 14 11
9 34 38 16 13
9 27 37 18 16
11 37 31 20 12
16 36 37 12 16
9 41 35 12 12
13 29 25 17 9
16 36 28 13 12
13 32 35 9 15
9 37 33 16 12
12 30 30 18 12
16 31 31 10 14
11 38 37 14 12
14 36 36 11 16
13 35 30 9 11
15 31 36 11 19
14 38 32 10 15
16 22 28 11 8
13 32 36 19 16
14 36 34 14 17
15 39 31 12 12
13 28 28 14 11
11 32 36 21 11
11 32 36 13 14
14 38 40 10 16
15 32 33 15 12
11 35 37 16 16
15 32 32 14 13
12 37 38 12 15
14 34 31 19 16
14 33 37 15 16
8 33 33 19 14
13 26 32 13 16
9 30 30 17 16
15 24 30 12 14
17 34 31 11 11
13 34 32 14 12
15 33 34 11 15
15 34 36 13 15
14 35 37 12 16
16 35 36 15 16
13 36 33 14 11
16 34 33 12 15
9 34 33 17 12
16 41 44 11 12
11 32 39 18 15
10 30 32 13 15
11 35 35 17 16
15 28 25 13 14
17 33 35 11 17
14 39 34 12 14
8 36 35 22 13
15 36 39 14 15
11 35 33 12 13
16 38 36 12 14
10 33 32 17 15
15 31 32 9 12
9 34 36 21 13
16 32 36 10 8
19 31 32 11 14
12 33 34 12 14
8 34 33 23 11
11 34 35 13 12
14 34 30 12 13
9 33 38 16 10
15 32 34 9 16
13 41 33 17 18
16 34 32 9 13
11 36 31 14 11
12 37 30 17 4
13 36 27 13 13
10 29 31 11 16
11 37 30 12 10
12 27 32 10 12
8 35 35 19 12
12 28 28 16 10
12 35 33 16 13
15 37 31 14 15
11 29 35 20 12
13 32 35 15 14
14 36 32 23 10
10 19 21 20 12
12 21 20 16 12
15 31 34 14 11
13 33 32 17 10
13 36 34 11 12
13 33 32 13 16
12 37 33 17 12
12 34 33 15 14
9 35 37 21 16
9 31 32 18 14
15 37 34 15 13
10 35 30 8 4
14 27 30 12 15
15 34 38 12 11
7 40 36 22 11
14 29 32 12 14

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time20 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 20 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226642&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]20 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226642&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226642&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time20 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 17.4334 + 0.00645862Connected[t] + 0.00998702Separate[t] -0.39153Depression[t] + 0.0779111Learning[t] + 0.215428M1[t] + 0.0854128M2[t] -0.080116M3[t] + 0.0880191M4[t] + 0.267281M5[t] + 1.01923M6[t] + 0.187619M7[t] + 0.565177M8[t] + 0.0724241M9[t] + 0.0956282M10[t] + 0.397392M11[t] -0.00380036t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  17.4334 +  0.00645862Connected[t] +  0.00998702Separate[t] -0.39153Depression[t] +  0.0779111Learning[t] +  0.215428M1[t] +  0.0854128M2[t] -0.080116M3[t] +  0.0880191M4[t] +  0.267281M5[t] +  1.01923M6[t] +  0.187619M7[t] +  0.565177M8[t] +  0.0724241M9[t] +  0.0956282M10[t] +  0.397392M11[t] -0.00380036t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226642&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  17.4334 +  0.00645862Connected[t] +  0.00998702Separate[t] -0.39153Depression[t] +  0.0779111Learning[t] +  0.215428M1[t] +  0.0854128M2[t] -0.080116M3[t] +  0.0880191M4[t] +  0.267281M5[t] +  1.01923M6[t] +  0.187619M7[t] +  0.565177M8[t] +  0.0724241M9[t] +  0.0956282M10[t] +  0.397392M11[t] -0.00380036t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226642&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226642&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 17.4334 + 0.00645862Connected[t] + 0.00998702Separate[t] -0.39153Depression[t] + 0.0779111Learning[t] + 0.215428M1[t] + 0.0854128M2[t] -0.080116M3[t] + 0.0880191M4[t] + 0.267281M5[t] + 1.01923M6[t] + 0.187619M7[t] + 0.565177M8[t] + 0.0724241M9[t] + 0.0956282M10[t] + 0.397392M11[t] -0.00380036t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)17.43341.761419.8971.14275e-195.71376e-20
Connected0.006458620.03895970.16580.8684680.434234
Separate0.009987020.03904340.25580.7983240.399162
Depression-0.391530.0385753-10.151.86036e-209.3018e-21
Learning0.07791110.05833861.3350.1829430.0914715
M10.2154280.6160550.34970.7268690.363435
M20.08541280.6170540.13840.8900210.44501
M3-0.0801160.61514-0.13020.8964820.448241
M40.08801910.6159010.14290.8864770.443238
M50.2672810.6176470.43270.6655810.332791
M61.019230.6164721.6530.09953620.0497681
M70.1876190.6187440.30320.7619730.380987
M80.5651770.6138310.92070.3580860.179043
M90.07242410.6146190.11780.9062940.453147
M100.09562820.6179170.15480.8771380.438569
M110.3973920.613530.64770.5177720.258886
t-0.003800360.00182691-2.080.03853690.0192684

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 17.4334 & 1.76141 & 9.897 & 1.14275e-19 & 5.71376e-20 \tabularnewline
Connected & 0.00645862 & 0.0389597 & 0.1658 & 0.868468 & 0.434234 \tabularnewline
Separate & 0.00998702 & 0.0390434 & 0.2558 & 0.798324 & 0.399162 \tabularnewline
Depression & -0.39153 & 0.0385753 & -10.15 & 1.86036e-20 & 9.3018e-21 \tabularnewline
Learning & 0.0779111 & 0.0583386 & 1.335 & 0.182943 & 0.0914715 \tabularnewline
M1 & 0.215428 & 0.616055 & 0.3497 & 0.726869 & 0.363435 \tabularnewline
M2 & 0.0854128 & 0.617054 & 0.1384 & 0.890021 & 0.44501 \tabularnewline
M3 & -0.080116 & 0.61514 & -0.1302 & 0.896482 & 0.448241 \tabularnewline
M4 & 0.0880191 & 0.615901 & 0.1429 & 0.886477 & 0.443238 \tabularnewline
M5 & 0.267281 & 0.617647 & 0.4327 & 0.665581 & 0.332791 \tabularnewline
M6 & 1.01923 & 0.616472 & 1.653 & 0.0995362 & 0.0497681 \tabularnewline
M7 & 0.187619 & 0.618744 & 0.3032 & 0.761973 & 0.380987 \tabularnewline
M8 & 0.565177 & 0.613831 & 0.9207 & 0.358086 & 0.179043 \tabularnewline
M9 & 0.0724241 & 0.614619 & 0.1178 & 0.906294 & 0.453147 \tabularnewline
M10 & 0.0956282 & 0.617917 & 0.1548 & 0.877138 & 0.438569 \tabularnewline
M11 & 0.397392 & 0.61353 & 0.6477 & 0.517772 & 0.258886 \tabularnewline
t & -0.00380036 & 0.00182691 & -2.08 & 0.0385369 & 0.0192684 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226642&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]17.4334[/C][C]1.76141[/C][C]9.897[/C][C]1.14275e-19[/C][C]5.71376e-20[/C][/ROW]
[ROW][C]Connected[/C][C]0.00645862[/C][C]0.0389597[/C][C]0.1658[/C][C]0.868468[/C][C]0.434234[/C][/ROW]
[ROW][C]Separate[/C][C]0.00998702[/C][C]0.0390434[/C][C]0.2558[/C][C]0.798324[/C][C]0.399162[/C][/ROW]
[ROW][C]Depression[/C][C]-0.39153[/C][C]0.0385753[/C][C]-10.15[/C][C]1.86036e-20[/C][C]9.3018e-21[/C][/ROW]
[ROW][C]Learning[/C][C]0.0779111[/C][C]0.0583386[/C][C]1.335[/C][C]0.182943[/C][C]0.0914715[/C][/ROW]
[ROW][C]M1[/C][C]0.215428[/C][C]0.616055[/C][C]0.3497[/C][C]0.726869[/C][C]0.363435[/C][/ROW]
[ROW][C]M2[/C][C]0.0854128[/C][C]0.617054[/C][C]0.1384[/C][C]0.890021[/C][C]0.44501[/C][/ROW]
[ROW][C]M3[/C][C]-0.080116[/C][C]0.61514[/C][C]-0.1302[/C][C]0.896482[/C][C]0.448241[/C][/ROW]
[ROW][C]M4[/C][C]0.0880191[/C][C]0.615901[/C][C]0.1429[/C][C]0.886477[/C][C]0.443238[/C][/ROW]
[ROW][C]M5[/C][C]0.267281[/C][C]0.617647[/C][C]0.4327[/C][C]0.665581[/C][C]0.332791[/C][/ROW]
[ROW][C]M6[/C][C]1.01923[/C][C]0.616472[/C][C]1.653[/C][C]0.0995362[/C][C]0.0497681[/C][/ROW]
[ROW][C]M7[/C][C]0.187619[/C][C]0.618744[/C][C]0.3032[/C][C]0.761973[/C][C]0.380987[/C][/ROW]
[ROW][C]M8[/C][C]0.565177[/C][C]0.613831[/C][C]0.9207[/C][C]0.358086[/C][C]0.179043[/C][/ROW]
[ROW][C]M9[/C][C]0.0724241[/C][C]0.614619[/C][C]0.1178[/C][C]0.906294[/C][C]0.453147[/C][/ROW]
[ROW][C]M10[/C][C]0.0956282[/C][C]0.617917[/C][C]0.1548[/C][C]0.877138[/C][C]0.438569[/C][/ROW]
[ROW][C]M11[/C][C]0.397392[/C][C]0.61353[/C][C]0.6477[/C][C]0.517772[/C][C]0.258886[/C][/ROW]
[ROW][C]t[/C][C]-0.00380036[/C][C]0.00182691[/C][C]-2.08[/C][C]0.0385369[/C][C]0.0192684[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226642&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226642&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)17.43341.761419.8971.14275e-195.71376e-20
Connected0.006458620.03895970.16580.8684680.434234
Separate0.009987020.03904340.25580.7983240.399162
Depression-0.391530.0385753-10.151.86036e-209.3018e-21
Learning0.07791110.05833861.3350.1829430.0914715
M10.2154280.6160550.34970.7268690.363435
M20.08541280.6170540.13840.8900210.44501
M3-0.0801160.61514-0.13020.8964820.448241
M40.08801910.6159010.14290.8864770.443238
M50.2672810.6176470.43270.6655810.332791
M61.019230.6164721.6530.09953620.0497681
M70.1876190.6187440.30320.7619730.380987
M80.5651770.6138310.92070.3580860.179043
M90.07242410.6146190.11780.9062940.453147
M100.09562820.6179170.15480.8771380.438569
M110.3973920.613530.64770.5177720.258886
t-0.003800360.00182691-2.080.03853690.0192684






Multiple Linear Regression - Regression Statistics
Multiple R0.616093
R-squared0.379571
Adjusted R-squared0.339381
F-TEST (value)9.44446
F-TEST (DF numerator)16
F-TEST (DF denominator)247
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.03086
Sum Squared Residuals1018.72

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.616093 \tabularnewline
R-squared & 0.379571 \tabularnewline
Adjusted R-squared & 0.339381 \tabularnewline
F-TEST (value) & 9.44446 \tabularnewline
F-TEST (DF numerator) & 16 \tabularnewline
F-TEST (DF denominator) & 247 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.03086 \tabularnewline
Sum Squared Residuals & 1018.72 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226642&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.616093[/C][/ROW]
[ROW][C]R-squared[/C][C]0.379571[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.339381[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]9.44446[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]16[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]247[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.03086[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1018.72[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226642&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226642&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.616093
R-squared0.379571
Adjusted R-squared0.339381
F-TEST (value)9.44446
F-TEST (DF numerator)16
F-TEST (DF denominator)247
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.03086
Sum Squared Residuals1018.72






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.6039-0.603864
21815.02252.97753
31113.8841-2.88412
41214.5064-2.50635
51611.13954.86054
61815.262.73998
71411.02262.97741
81415.4092-1.40918
91515.2292-0.229175
101514.18830.811682
111715.67531.32467
121916.07422.92576
131013.5681-3.56807
141613.86222.1378
151815.28822.71184
161413.68410.315851
171413.87550.124543
181716.26060.739413
191415.6673-1.66735
201614.60561.39444
211815.48932.51065
221113.7204-2.72043
231415.1568-1.15677
241213.7359-1.73585
251715.1431.85701
26915.8052-6.80515
271614.77251.22748
281413.29340.706579
291513.89841.10162
301114.8887-3.88869
311615.6580.342039
321313.433-0.432957
331715.10451.89552
341514.92870.0712816
351414.2179-0.21789
361615.47970.520252
37910.9537-1.95366
381514.32890.671082
391715.03331.96671
401315.2563-2.25635
411515.8263-0.826269
421614.45161.54845
431616.4486-0.44864
441213.9964-1.99636
451514.64380.356161
461113.7099-2.7099
471515.8541-0.854124
481514.66560.334446
491713.44833.5517
501314.6778-1.67777
511615.0770.923032
521413.43950.560536
531111.9229-0.922943
541214.6117-2.6117
551214.3327-2.33267
561513.78791.21212
571614.03741.96262
581515.5583-0.558316
591215.4585-3.45848
601213.1447-1.14466
61810.9948-2.99477
621314.4164-1.41644
631114.2313-3.23126
641413.43730.562664
651514.13960.860423
661015.8151-5.81507
671112.6949-1.69488
681214.9076-2.90764
691513.74011.25995
701513.62381.37623
711413.85520.144811
721612.95733.04266
731514.2930.70696
741515.3796-0.379623
751314.4973-1.49729
761211.66950.330453
771714.17332.82673
781313.276-0.275996
791513.73421.26577
801315.926-2.92602
811514.71050.289548
821515.5358-0.53582
831614.55431.44575
841514.13080.869248
851414.0053-0.00525887
861513.82781.17219
871414.1236-0.123605
881313.0675-0.0675406
89710.4602-3.4602
901714.51542.48457
911313.2789-0.278861
921514.44120.558807
931412.93451.06554
941313.7775-0.777466
951615.0210.979034
961212.6392-0.639218
971414.7556-0.755632
981714.66472.33531
991514.71880.281246
1001715.07771.92234
1011212.8875-0.887497
1021615.52690.473078
1031114.5778-3.57777
1041513.18811.81189
105911.2585-2.25853
1061614.73891.26114
1071513.06061.93941
1081012.9787-2.97869
109109.470020.529983
1101513.39931.60071
1111112.8349-1.8349
1121314.7296-1.72962
1131412.94741.05258
1141814.83453.16547
1151615.22970.770327
1161413.77970.220273
1171413.68120.318837
1181415.1324-1.13238
1191413.35720.642822
1201212.6999-0.699946
1211413.42410.57595
1221514.39610.603853
1231515.6187-0.618696
1241514.45420.545839
1251314.6952-1.69521
1261716.58170.41828
1271715.22131.77872
1281914.94674.05332
1291513.41631.58371
1301314.511-1.51102
131910.7819-1.78192
1321514.89090.109063
1331512.67942.3206
1341514.02050.979523
1351613.02382.97618
136119.412821.58718
1371413.43650.563542
1381113.0641-2.06406
1391514.28650.713476
1401314.175-1.17499
1411514.84750.152472
1421613.23992.76006
1431414.4568-0.456815
1441513.86431.13567
1451614.1381.86196
1461614.14441.85563
1471113.3097-2.30967
1481214.415-2.41503
149911.2539-2.25388
1501614.59831.40171
1511312.20060.799357
1521615.74290.257128
1531214.0882-2.08817
154911.1805-2.18048
1551311.49611.50392
1561312.84420.155782
1571413.15980.840167
1581914.35294.6471
1591315.0111-2.01105
1601211.3870.613022
1611312.41640.583646
162109.887180.112825
1631412.9151.08501
1641611.44424.55575
1651011.609-1.60902
166119.126751.87325
1671414.1119-0.111899
1681212.5882-0.588182
169912.3541-3.35407
170911.6157-2.61573
1711110.35640.643638
1721614.0181.98195
173913.8942-4.89418
1741312.27360.726431
1751613.31322.68681
1761315.5309-2.53087
177912.0722-3.0722
1781211.23340.766633
1791614.83581.16416
1801112.8178-1.81784
1811414.4928-0.492796
1821314.6861-1.6861
1831514.39110.608909
1841414.6406-0.640574
1851613.73582.26416
1861312.11950.880486
1871413.32550.67447
1881514.08220.917792
1891312.62370.376323
1901110.00810.9919
1911113.672-2.67204
1921414.68-0.679959
1931512.51362.48637
1941112.3593-1.35925
1951512.66992.33006
1961213.8654-1.86537
1971411.28872.71125
1981413.65650.343523
199811.0592-3.05918
2001313.8827-0.882743
201911.8259-2.82593
2021513.60841.39159
2031714.13872.86126
2041312.65090.349141
2051514.28430.715674
2061513.39391.60612
2071413.71040.28956
2081612.69023.3098
2091312.84410.155869
2101614.67411.32594
211911.6473-2.64727
2121614.52531.47472
2131111.4137-0.413684
2141013.3079-3.30791
2151112.1799-1.17992
2161513.04391.95605
2171714.40452.59547
2181413.67420.325784
21989.50228-1.50228
2201512.99462.00537
2211113.731-2.73095
2221614.60631.39366
2231011.819-1.81895
2241515.0783-0.078304
225910.0206-1.02062
2261613.94442.05561
2271914.27194.72812
2281213.512-1.51205
22989.17958-1.17958
2301113.059-2.05895
2311413.30910.69087
232911.747-2.74705
2331515.0843-0.0842812
2341312.90410.0958537
2351614.75621.24377
2361113.0194-2.01944
2371210.79941.20061
2381313.0497-0.0496982
2391014.3592-4.35919
2401113.1407-2.14069
2411214.2466-2.24658
242810.6706-2.67063
2431211.40490.595054
2441211.89820.10184
2451513.00541.99455
2461111.159-0.158955
2471312.45640.543602
248149.382144.61786
249109.996350.00365142
2501211.58480.415196
2511512.79232.20768
2521311.13161.86843
2531313.8876-0.887551
2541313.243-0.242969
2551211.23170.768304
2561212.3155-0.315538
257910.344-1.34405
258912.0352-3.03519
2591512.35522.64481
2601014.7156-4.71559
2611413.45830.541728
2621513.29111.70886
26379.69258-2.69258
2641413.32940.670573

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 14.6039 & -0.603864 \tabularnewline
2 & 18 & 15.0225 & 2.97753 \tabularnewline
3 & 11 & 13.8841 & -2.88412 \tabularnewline
4 & 12 & 14.5064 & -2.50635 \tabularnewline
5 & 16 & 11.1395 & 4.86054 \tabularnewline
6 & 18 & 15.26 & 2.73998 \tabularnewline
7 & 14 & 11.0226 & 2.97741 \tabularnewline
8 & 14 & 15.4092 & -1.40918 \tabularnewline
9 & 15 & 15.2292 & -0.229175 \tabularnewline
10 & 15 & 14.1883 & 0.811682 \tabularnewline
11 & 17 & 15.6753 & 1.32467 \tabularnewline
12 & 19 & 16.0742 & 2.92576 \tabularnewline
13 & 10 & 13.5681 & -3.56807 \tabularnewline
14 & 16 & 13.8622 & 2.1378 \tabularnewline
15 & 18 & 15.2882 & 2.71184 \tabularnewline
16 & 14 & 13.6841 & 0.315851 \tabularnewline
17 & 14 & 13.8755 & 0.124543 \tabularnewline
18 & 17 & 16.2606 & 0.739413 \tabularnewline
19 & 14 & 15.6673 & -1.66735 \tabularnewline
20 & 16 & 14.6056 & 1.39444 \tabularnewline
21 & 18 & 15.4893 & 2.51065 \tabularnewline
22 & 11 & 13.7204 & -2.72043 \tabularnewline
23 & 14 & 15.1568 & -1.15677 \tabularnewline
24 & 12 & 13.7359 & -1.73585 \tabularnewline
25 & 17 & 15.143 & 1.85701 \tabularnewline
26 & 9 & 15.8052 & -6.80515 \tabularnewline
27 & 16 & 14.7725 & 1.22748 \tabularnewline
28 & 14 & 13.2934 & 0.706579 \tabularnewline
29 & 15 & 13.8984 & 1.10162 \tabularnewline
30 & 11 & 14.8887 & -3.88869 \tabularnewline
31 & 16 & 15.658 & 0.342039 \tabularnewline
32 & 13 & 13.433 & -0.432957 \tabularnewline
33 & 17 & 15.1045 & 1.89552 \tabularnewline
34 & 15 & 14.9287 & 0.0712816 \tabularnewline
35 & 14 & 14.2179 & -0.21789 \tabularnewline
36 & 16 & 15.4797 & 0.520252 \tabularnewline
37 & 9 & 10.9537 & -1.95366 \tabularnewline
38 & 15 & 14.3289 & 0.671082 \tabularnewline
39 & 17 & 15.0333 & 1.96671 \tabularnewline
40 & 13 & 15.2563 & -2.25635 \tabularnewline
41 & 15 & 15.8263 & -0.826269 \tabularnewline
42 & 16 & 14.4516 & 1.54845 \tabularnewline
43 & 16 & 16.4486 & -0.44864 \tabularnewline
44 & 12 & 13.9964 & -1.99636 \tabularnewline
45 & 15 & 14.6438 & 0.356161 \tabularnewline
46 & 11 & 13.7099 & -2.7099 \tabularnewline
47 & 15 & 15.8541 & -0.854124 \tabularnewline
48 & 15 & 14.6656 & 0.334446 \tabularnewline
49 & 17 & 13.4483 & 3.5517 \tabularnewline
50 & 13 & 14.6778 & -1.67777 \tabularnewline
51 & 16 & 15.077 & 0.923032 \tabularnewline
52 & 14 & 13.4395 & 0.560536 \tabularnewline
53 & 11 & 11.9229 & -0.922943 \tabularnewline
54 & 12 & 14.6117 & -2.6117 \tabularnewline
55 & 12 & 14.3327 & -2.33267 \tabularnewline
56 & 15 & 13.7879 & 1.21212 \tabularnewline
57 & 16 & 14.0374 & 1.96262 \tabularnewline
58 & 15 & 15.5583 & -0.558316 \tabularnewline
59 & 12 & 15.4585 & -3.45848 \tabularnewline
60 & 12 & 13.1447 & -1.14466 \tabularnewline
61 & 8 & 10.9948 & -2.99477 \tabularnewline
62 & 13 & 14.4164 & -1.41644 \tabularnewline
63 & 11 & 14.2313 & -3.23126 \tabularnewline
64 & 14 & 13.4373 & 0.562664 \tabularnewline
65 & 15 & 14.1396 & 0.860423 \tabularnewline
66 & 10 & 15.8151 & -5.81507 \tabularnewline
67 & 11 & 12.6949 & -1.69488 \tabularnewline
68 & 12 & 14.9076 & -2.90764 \tabularnewline
69 & 15 & 13.7401 & 1.25995 \tabularnewline
70 & 15 & 13.6238 & 1.37623 \tabularnewline
71 & 14 & 13.8552 & 0.144811 \tabularnewline
72 & 16 & 12.9573 & 3.04266 \tabularnewline
73 & 15 & 14.293 & 0.70696 \tabularnewline
74 & 15 & 15.3796 & -0.379623 \tabularnewline
75 & 13 & 14.4973 & -1.49729 \tabularnewline
76 & 12 & 11.6695 & 0.330453 \tabularnewline
77 & 17 & 14.1733 & 2.82673 \tabularnewline
78 & 13 & 13.276 & -0.275996 \tabularnewline
79 & 15 & 13.7342 & 1.26577 \tabularnewline
80 & 13 & 15.926 & -2.92602 \tabularnewline
81 & 15 & 14.7105 & 0.289548 \tabularnewline
82 & 15 & 15.5358 & -0.53582 \tabularnewline
83 & 16 & 14.5543 & 1.44575 \tabularnewline
84 & 15 & 14.1308 & 0.869248 \tabularnewline
85 & 14 & 14.0053 & -0.00525887 \tabularnewline
86 & 15 & 13.8278 & 1.17219 \tabularnewline
87 & 14 & 14.1236 & -0.123605 \tabularnewline
88 & 13 & 13.0675 & -0.0675406 \tabularnewline
89 & 7 & 10.4602 & -3.4602 \tabularnewline
90 & 17 & 14.5154 & 2.48457 \tabularnewline
91 & 13 & 13.2789 & -0.278861 \tabularnewline
92 & 15 & 14.4412 & 0.558807 \tabularnewline
93 & 14 & 12.9345 & 1.06554 \tabularnewline
94 & 13 & 13.7775 & -0.777466 \tabularnewline
95 & 16 & 15.021 & 0.979034 \tabularnewline
96 & 12 & 12.6392 & -0.639218 \tabularnewline
97 & 14 & 14.7556 & -0.755632 \tabularnewline
98 & 17 & 14.6647 & 2.33531 \tabularnewline
99 & 15 & 14.7188 & 0.281246 \tabularnewline
100 & 17 & 15.0777 & 1.92234 \tabularnewline
101 & 12 & 12.8875 & -0.887497 \tabularnewline
102 & 16 & 15.5269 & 0.473078 \tabularnewline
103 & 11 & 14.5778 & -3.57777 \tabularnewline
104 & 15 & 13.1881 & 1.81189 \tabularnewline
105 & 9 & 11.2585 & -2.25853 \tabularnewline
106 & 16 & 14.7389 & 1.26114 \tabularnewline
107 & 15 & 13.0606 & 1.93941 \tabularnewline
108 & 10 & 12.9787 & -2.97869 \tabularnewline
109 & 10 & 9.47002 & 0.529983 \tabularnewline
110 & 15 & 13.3993 & 1.60071 \tabularnewline
111 & 11 & 12.8349 & -1.8349 \tabularnewline
112 & 13 & 14.7296 & -1.72962 \tabularnewline
113 & 14 & 12.9474 & 1.05258 \tabularnewline
114 & 18 & 14.8345 & 3.16547 \tabularnewline
115 & 16 & 15.2297 & 0.770327 \tabularnewline
116 & 14 & 13.7797 & 0.220273 \tabularnewline
117 & 14 & 13.6812 & 0.318837 \tabularnewline
118 & 14 & 15.1324 & -1.13238 \tabularnewline
119 & 14 & 13.3572 & 0.642822 \tabularnewline
120 & 12 & 12.6999 & -0.699946 \tabularnewline
121 & 14 & 13.4241 & 0.57595 \tabularnewline
122 & 15 & 14.3961 & 0.603853 \tabularnewline
123 & 15 & 15.6187 & -0.618696 \tabularnewline
124 & 15 & 14.4542 & 0.545839 \tabularnewline
125 & 13 & 14.6952 & -1.69521 \tabularnewline
126 & 17 & 16.5817 & 0.41828 \tabularnewline
127 & 17 & 15.2213 & 1.77872 \tabularnewline
128 & 19 & 14.9467 & 4.05332 \tabularnewline
129 & 15 & 13.4163 & 1.58371 \tabularnewline
130 & 13 & 14.511 & -1.51102 \tabularnewline
131 & 9 & 10.7819 & -1.78192 \tabularnewline
132 & 15 & 14.8909 & 0.109063 \tabularnewline
133 & 15 & 12.6794 & 2.3206 \tabularnewline
134 & 15 & 14.0205 & 0.979523 \tabularnewline
135 & 16 & 13.0238 & 2.97618 \tabularnewline
136 & 11 & 9.41282 & 1.58718 \tabularnewline
137 & 14 & 13.4365 & 0.563542 \tabularnewline
138 & 11 & 13.0641 & -2.06406 \tabularnewline
139 & 15 & 14.2865 & 0.713476 \tabularnewline
140 & 13 & 14.175 & -1.17499 \tabularnewline
141 & 15 & 14.8475 & 0.152472 \tabularnewline
142 & 16 & 13.2399 & 2.76006 \tabularnewline
143 & 14 & 14.4568 & -0.456815 \tabularnewline
144 & 15 & 13.8643 & 1.13567 \tabularnewline
145 & 16 & 14.138 & 1.86196 \tabularnewline
146 & 16 & 14.1444 & 1.85563 \tabularnewline
147 & 11 & 13.3097 & -2.30967 \tabularnewline
148 & 12 & 14.415 & -2.41503 \tabularnewline
149 & 9 & 11.2539 & -2.25388 \tabularnewline
150 & 16 & 14.5983 & 1.40171 \tabularnewline
151 & 13 & 12.2006 & 0.799357 \tabularnewline
152 & 16 & 15.7429 & 0.257128 \tabularnewline
153 & 12 & 14.0882 & -2.08817 \tabularnewline
154 & 9 & 11.1805 & -2.18048 \tabularnewline
155 & 13 & 11.4961 & 1.50392 \tabularnewline
156 & 13 & 12.8442 & 0.155782 \tabularnewline
157 & 14 & 13.1598 & 0.840167 \tabularnewline
158 & 19 & 14.3529 & 4.6471 \tabularnewline
159 & 13 & 15.0111 & -2.01105 \tabularnewline
160 & 12 & 11.387 & 0.613022 \tabularnewline
161 & 13 & 12.4164 & 0.583646 \tabularnewline
162 & 10 & 9.88718 & 0.112825 \tabularnewline
163 & 14 & 12.915 & 1.08501 \tabularnewline
164 & 16 & 11.4442 & 4.55575 \tabularnewline
165 & 10 & 11.609 & -1.60902 \tabularnewline
166 & 11 & 9.12675 & 1.87325 \tabularnewline
167 & 14 & 14.1119 & -0.111899 \tabularnewline
168 & 12 & 12.5882 & -0.588182 \tabularnewline
169 & 9 & 12.3541 & -3.35407 \tabularnewline
170 & 9 & 11.6157 & -2.61573 \tabularnewline
171 & 11 & 10.3564 & 0.643638 \tabularnewline
172 & 16 & 14.018 & 1.98195 \tabularnewline
173 & 9 & 13.8942 & -4.89418 \tabularnewline
174 & 13 & 12.2736 & 0.726431 \tabularnewline
175 & 16 & 13.3132 & 2.68681 \tabularnewline
176 & 13 & 15.5309 & -2.53087 \tabularnewline
177 & 9 & 12.0722 & -3.0722 \tabularnewline
178 & 12 & 11.2334 & 0.766633 \tabularnewline
179 & 16 & 14.8358 & 1.16416 \tabularnewline
180 & 11 & 12.8178 & -1.81784 \tabularnewline
181 & 14 & 14.4928 & -0.492796 \tabularnewline
182 & 13 & 14.6861 & -1.6861 \tabularnewline
183 & 15 & 14.3911 & 0.608909 \tabularnewline
184 & 14 & 14.6406 & -0.640574 \tabularnewline
185 & 16 & 13.7358 & 2.26416 \tabularnewline
186 & 13 & 12.1195 & 0.880486 \tabularnewline
187 & 14 & 13.3255 & 0.67447 \tabularnewline
188 & 15 & 14.0822 & 0.917792 \tabularnewline
189 & 13 & 12.6237 & 0.376323 \tabularnewline
190 & 11 & 10.0081 & 0.9919 \tabularnewline
191 & 11 & 13.672 & -2.67204 \tabularnewline
192 & 14 & 14.68 & -0.679959 \tabularnewline
193 & 15 & 12.5136 & 2.48637 \tabularnewline
194 & 11 & 12.3593 & -1.35925 \tabularnewline
195 & 15 & 12.6699 & 2.33006 \tabularnewline
196 & 12 & 13.8654 & -1.86537 \tabularnewline
197 & 14 & 11.2887 & 2.71125 \tabularnewline
198 & 14 & 13.6565 & 0.343523 \tabularnewline
199 & 8 & 11.0592 & -3.05918 \tabularnewline
200 & 13 & 13.8827 & -0.882743 \tabularnewline
201 & 9 & 11.8259 & -2.82593 \tabularnewline
202 & 15 & 13.6084 & 1.39159 \tabularnewline
203 & 17 & 14.1387 & 2.86126 \tabularnewline
204 & 13 & 12.6509 & 0.349141 \tabularnewline
205 & 15 & 14.2843 & 0.715674 \tabularnewline
206 & 15 & 13.3939 & 1.60612 \tabularnewline
207 & 14 & 13.7104 & 0.28956 \tabularnewline
208 & 16 & 12.6902 & 3.3098 \tabularnewline
209 & 13 & 12.8441 & 0.155869 \tabularnewline
210 & 16 & 14.6741 & 1.32594 \tabularnewline
211 & 9 & 11.6473 & -2.64727 \tabularnewline
212 & 16 & 14.5253 & 1.47472 \tabularnewline
213 & 11 & 11.4137 & -0.413684 \tabularnewline
214 & 10 & 13.3079 & -3.30791 \tabularnewline
215 & 11 & 12.1799 & -1.17992 \tabularnewline
216 & 15 & 13.0439 & 1.95605 \tabularnewline
217 & 17 & 14.4045 & 2.59547 \tabularnewline
218 & 14 & 13.6742 & 0.325784 \tabularnewline
219 & 8 & 9.50228 & -1.50228 \tabularnewline
220 & 15 & 12.9946 & 2.00537 \tabularnewline
221 & 11 & 13.731 & -2.73095 \tabularnewline
222 & 16 & 14.6063 & 1.39366 \tabularnewline
223 & 10 & 11.819 & -1.81895 \tabularnewline
224 & 15 & 15.0783 & -0.078304 \tabularnewline
225 & 9 & 10.0206 & -1.02062 \tabularnewline
226 & 16 & 13.9444 & 2.05561 \tabularnewline
227 & 19 & 14.2719 & 4.72812 \tabularnewline
228 & 12 & 13.512 & -1.51205 \tabularnewline
229 & 8 & 9.17958 & -1.17958 \tabularnewline
230 & 11 & 13.059 & -2.05895 \tabularnewline
231 & 14 & 13.3091 & 0.69087 \tabularnewline
232 & 9 & 11.747 & -2.74705 \tabularnewline
233 & 15 & 15.0843 & -0.0842812 \tabularnewline
234 & 13 & 12.9041 & 0.0958537 \tabularnewline
235 & 16 & 14.7562 & 1.24377 \tabularnewline
236 & 11 & 13.0194 & -2.01944 \tabularnewline
237 & 12 & 10.7994 & 1.20061 \tabularnewline
238 & 13 & 13.0497 & -0.0496982 \tabularnewline
239 & 10 & 14.3592 & -4.35919 \tabularnewline
240 & 11 & 13.1407 & -2.14069 \tabularnewline
241 & 12 & 14.2466 & -2.24658 \tabularnewline
242 & 8 & 10.6706 & -2.67063 \tabularnewline
243 & 12 & 11.4049 & 0.595054 \tabularnewline
244 & 12 & 11.8982 & 0.10184 \tabularnewline
245 & 15 & 13.0054 & 1.99455 \tabularnewline
246 & 11 & 11.159 & -0.158955 \tabularnewline
247 & 13 & 12.4564 & 0.543602 \tabularnewline
248 & 14 & 9.38214 & 4.61786 \tabularnewline
249 & 10 & 9.99635 & 0.00365142 \tabularnewline
250 & 12 & 11.5848 & 0.415196 \tabularnewline
251 & 15 & 12.7923 & 2.20768 \tabularnewline
252 & 13 & 11.1316 & 1.86843 \tabularnewline
253 & 13 & 13.8876 & -0.887551 \tabularnewline
254 & 13 & 13.243 & -0.242969 \tabularnewline
255 & 12 & 11.2317 & 0.768304 \tabularnewline
256 & 12 & 12.3155 & -0.315538 \tabularnewline
257 & 9 & 10.344 & -1.34405 \tabularnewline
258 & 9 & 12.0352 & -3.03519 \tabularnewline
259 & 15 & 12.3552 & 2.64481 \tabularnewline
260 & 10 & 14.7156 & -4.71559 \tabularnewline
261 & 14 & 13.4583 & 0.541728 \tabularnewline
262 & 15 & 13.2911 & 1.70886 \tabularnewline
263 & 7 & 9.69258 & -2.69258 \tabularnewline
264 & 14 & 13.3294 & 0.670573 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226642&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]14.6039[/C][C]-0.603864[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.0225[/C][C]2.97753[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.8841[/C][C]-2.88412[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.5064[/C][C]-2.50635[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]11.1395[/C][C]4.86054[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]15.26[/C][C]2.73998[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]11.0226[/C][C]2.97741[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]15.4092[/C][C]-1.40918[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.2292[/C][C]-0.229175[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.1883[/C][C]0.811682[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.6753[/C][C]1.32467[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]16.0742[/C][C]2.92576[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.5681[/C][C]-3.56807[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.8622[/C][C]2.1378[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.2882[/C][C]2.71184[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.6841[/C][C]0.315851[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.8755[/C][C]0.124543[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]16.2606[/C][C]0.739413[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.6673[/C][C]-1.66735[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]14.6056[/C][C]1.39444[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.4893[/C][C]2.51065[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.7204[/C][C]-2.72043[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]15.1568[/C][C]-1.15677[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.7359[/C][C]-1.73585[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.143[/C][C]1.85701[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.8052[/C][C]-6.80515[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.7725[/C][C]1.22748[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.2934[/C][C]0.706579[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.8984[/C][C]1.10162[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]14.8887[/C][C]-3.88869[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.658[/C][C]0.342039[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]13.433[/C][C]-0.432957[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]15.1045[/C][C]1.89552[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]14.9287[/C][C]0.0712816[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14.2179[/C][C]-0.21789[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.4797[/C][C]0.520252[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.9537[/C][C]-1.95366[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.3289[/C][C]0.671082[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.0333[/C][C]1.96671[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.2563[/C][C]-2.25635[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.8263[/C][C]-0.826269[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]14.4516[/C][C]1.54845[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]16.4486[/C][C]-0.44864[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.9964[/C][C]-1.99636[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.6438[/C][C]0.356161[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.7099[/C][C]-2.7099[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.8541[/C][C]-0.854124[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.6656[/C][C]0.334446[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.4483[/C][C]3.5517[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.6778[/C][C]-1.67777[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.077[/C][C]0.923032[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.4395[/C][C]0.560536[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.9229[/C][C]-0.922943[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]14.6117[/C][C]-2.6117[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.3327[/C][C]-2.33267[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.7879[/C][C]1.21212[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.0374[/C][C]1.96262[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.5583[/C][C]-0.558316[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.4585[/C][C]-3.45848[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.1447[/C][C]-1.14466[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.9948[/C][C]-2.99477[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.4164[/C][C]-1.41644[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.2313[/C][C]-3.23126[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.4373[/C][C]0.562664[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]14.1396[/C][C]0.860423[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.8151[/C][C]-5.81507[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.6949[/C][C]-1.69488[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.9076[/C][C]-2.90764[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.7401[/C][C]1.25995[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.6238[/C][C]1.37623[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.8552[/C][C]0.144811[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.9573[/C][C]3.04266[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.293[/C][C]0.70696[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.3796[/C][C]-0.379623[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.4973[/C][C]-1.49729[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]11.6695[/C][C]0.330453[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]14.1733[/C][C]2.82673[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]13.276[/C][C]-0.275996[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.7342[/C][C]1.26577[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]15.926[/C][C]-2.92602[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.7105[/C][C]0.289548[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.5358[/C][C]-0.53582[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.5543[/C][C]1.44575[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.1308[/C][C]0.869248[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.0053[/C][C]-0.00525887[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.8278[/C][C]1.17219[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.1236[/C][C]-0.123605[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]13.0675[/C][C]-0.0675406[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.4602[/C][C]-3.4602[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]14.5154[/C][C]2.48457[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]13.2789[/C][C]-0.278861[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.4412[/C][C]0.558807[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]12.9345[/C][C]1.06554[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.7775[/C][C]-0.777466[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]15.021[/C][C]0.979034[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.6392[/C][C]-0.639218[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.7556[/C][C]-0.755632[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.6647[/C][C]2.33531[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]14.7188[/C][C]0.281246[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.0777[/C][C]1.92234[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.8875[/C][C]-0.887497[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]15.5269[/C][C]0.473078[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.5778[/C][C]-3.57777[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.1881[/C][C]1.81189[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.2585[/C][C]-2.25853[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.7389[/C][C]1.26114[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]13.0606[/C][C]1.93941[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.9787[/C][C]-2.97869[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.47002[/C][C]0.529983[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.3993[/C][C]1.60071[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]12.8349[/C][C]-1.8349[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]14.7296[/C][C]-1.72962[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]12.9474[/C][C]1.05258[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.8345[/C][C]3.16547[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.2297[/C][C]0.770327[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.7797[/C][C]0.220273[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.6812[/C][C]0.318837[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.1324[/C][C]-1.13238[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.3572[/C][C]0.642822[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.6999[/C][C]-0.699946[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.4241[/C][C]0.57595[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.3961[/C][C]0.603853[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.6187[/C][C]-0.618696[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.4542[/C][C]0.545839[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.6952[/C][C]-1.69521[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.5817[/C][C]0.41828[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.2213[/C][C]1.77872[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.9467[/C][C]4.05332[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.4163[/C][C]1.58371[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.511[/C][C]-1.51102[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.7819[/C][C]-1.78192[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]14.8909[/C][C]0.109063[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.6794[/C][C]2.3206[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.0205[/C][C]0.979523[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.0238[/C][C]2.97618[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.41282[/C][C]1.58718[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.4365[/C][C]0.563542[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.0641[/C][C]-2.06406[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.2865[/C][C]0.713476[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]14.175[/C][C]-1.17499[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.8475[/C][C]0.152472[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.2399[/C][C]2.76006[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.4568[/C][C]-0.456815[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]13.8643[/C][C]1.13567[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.138[/C][C]1.86196[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.1444[/C][C]1.85563[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.3097[/C][C]-2.30967[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.415[/C][C]-2.41503[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.2539[/C][C]-2.25388[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.5983[/C][C]1.40171[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.2006[/C][C]0.799357[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.7429[/C][C]0.257128[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.0882[/C][C]-2.08817[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.1805[/C][C]-2.18048[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.4961[/C][C]1.50392[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.8442[/C][C]0.155782[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.1598[/C][C]0.840167[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.3529[/C][C]4.6471[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.0111[/C][C]-2.01105[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.387[/C][C]0.613022[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.4164[/C][C]0.583646[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.88718[/C][C]0.112825[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]12.915[/C][C]1.08501[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.4442[/C][C]4.55575[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.609[/C][C]-1.60902[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]9.12675[/C][C]1.87325[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.1119[/C][C]-0.111899[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.5882[/C][C]-0.588182[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.3541[/C][C]-3.35407[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.6157[/C][C]-2.61573[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.3564[/C][C]0.643638[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.018[/C][C]1.98195[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]13.8942[/C][C]-4.89418[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]12.2736[/C][C]0.726431[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.3132[/C][C]2.68681[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.5309[/C][C]-2.53087[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.0722[/C][C]-3.0722[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.2334[/C][C]0.766633[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.8358[/C][C]1.16416[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]12.8178[/C][C]-1.81784[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]14.4928[/C][C]-0.492796[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.6861[/C][C]-1.6861[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.3911[/C][C]0.608909[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.6406[/C][C]-0.640574[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]13.7358[/C][C]2.26416[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]12.1195[/C][C]0.880486[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.3255[/C][C]0.67447[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.0822[/C][C]0.917792[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.6237[/C][C]0.376323[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.0081[/C][C]0.9919[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]13.672[/C][C]-2.67204[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.68[/C][C]-0.679959[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.5136[/C][C]2.48637[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.3593[/C][C]-1.35925[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]12.6699[/C][C]2.33006[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]13.8654[/C][C]-1.86537[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.2887[/C][C]2.71125[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.6565[/C][C]0.343523[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.0592[/C][C]-3.05918[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.8827[/C][C]-0.882743[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]11.8259[/C][C]-2.82593[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.6084[/C][C]1.39159[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]14.1387[/C][C]2.86126[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.6509[/C][C]0.349141[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.2843[/C][C]0.715674[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.3939[/C][C]1.60612[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]13.7104[/C][C]0.28956[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.6902[/C][C]3.3098[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.8441[/C][C]0.155869[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.6741[/C][C]1.32594[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.6473[/C][C]-2.64727[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.5253[/C][C]1.47472[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.4137[/C][C]-0.413684[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.3079[/C][C]-3.30791[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.1799[/C][C]-1.17992[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.0439[/C][C]1.95605[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.4045[/C][C]2.59547[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.6742[/C][C]0.325784[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.50228[/C][C]-1.50228[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]12.9946[/C][C]2.00537[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.731[/C][C]-2.73095[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]14.6063[/C][C]1.39366[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]11.819[/C][C]-1.81895[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]15.0783[/C][C]-0.078304[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]10.0206[/C][C]-1.02062[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]13.9444[/C][C]2.05561[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]14.2719[/C][C]4.72812[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.512[/C][C]-1.51205[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.17958[/C][C]-1.17958[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.059[/C][C]-2.05895[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.3091[/C][C]0.69087[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]11.747[/C][C]-2.74705[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]15.0843[/C][C]-0.0842812[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.9041[/C][C]0.0958537[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]14.7562[/C][C]1.24377[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.0194[/C][C]-2.01944[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]10.7994[/C][C]1.20061[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.0497[/C][C]-0.0496982[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.3592[/C][C]-4.35919[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.1407[/C][C]-2.14069[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.2466[/C][C]-2.24658[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.6706[/C][C]-2.67063[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.4049[/C][C]0.595054[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]11.8982[/C][C]0.10184[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.0054[/C][C]1.99455[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]11.159[/C][C]-0.158955[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.4564[/C][C]0.543602[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]9.38214[/C][C]4.61786[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]9.99635[/C][C]0.00365142[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5848[/C][C]0.415196[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.7923[/C][C]2.20768[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.1316[/C][C]1.86843[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]13.8876[/C][C]-0.887551[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.243[/C][C]-0.242969[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.2317[/C][C]0.768304[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.3155[/C][C]-0.315538[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.344[/C][C]-1.34405[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]12.0352[/C][C]-3.03519[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.3552[/C][C]2.64481[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.7156[/C][C]-4.71559[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.4583[/C][C]0.541728[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.2911[/C][C]1.70886[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.69258[/C][C]-2.69258[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.3294[/C][C]0.670573[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226642&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226642&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.6039-0.603864
21815.02252.97753
31113.8841-2.88412
41214.5064-2.50635
51611.13954.86054
61815.262.73998
71411.02262.97741
81415.4092-1.40918
91515.2292-0.229175
101514.18830.811682
111715.67531.32467
121916.07422.92576
131013.5681-3.56807
141613.86222.1378
151815.28822.71184
161413.68410.315851
171413.87550.124543
181716.26060.739413
191415.6673-1.66735
201614.60561.39444
211815.48932.51065
221113.7204-2.72043
231415.1568-1.15677
241213.7359-1.73585
251715.1431.85701
26915.8052-6.80515
271614.77251.22748
281413.29340.706579
291513.89841.10162
301114.8887-3.88869
311615.6580.342039
321313.433-0.432957
331715.10451.89552
341514.92870.0712816
351414.2179-0.21789
361615.47970.520252
37910.9537-1.95366
381514.32890.671082
391715.03331.96671
401315.2563-2.25635
411515.8263-0.826269
421614.45161.54845
431616.4486-0.44864
441213.9964-1.99636
451514.64380.356161
461113.7099-2.7099
471515.8541-0.854124
481514.66560.334446
491713.44833.5517
501314.6778-1.67777
511615.0770.923032
521413.43950.560536
531111.9229-0.922943
541214.6117-2.6117
551214.3327-2.33267
561513.78791.21212
571614.03741.96262
581515.5583-0.558316
591215.4585-3.45848
601213.1447-1.14466
61810.9948-2.99477
621314.4164-1.41644
631114.2313-3.23126
641413.43730.562664
651514.13960.860423
661015.8151-5.81507
671112.6949-1.69488
681214.9076-2.90764
691513.74011.25995
701513.62381.37623
711413.85520.144811
721612.95733.04266
731514.2930.70696
741515.3796-0.379623
751314.4973-1.49729
761211.66950.330453
771714.17332.82673
781313.276-0.275996
791513.73421.26577
801315.926-2.92602
811514.71050.289548
821515.5358-0.53582
831614.55431.44575
841514.13080.869248
851414.0053-0.00525887
861513.82781.17219
871414.1236-0.123605
881313.0675-0.0675406
89710.4602-3.4602
901714.51542.48457
911313.2789-0.278861
921514.44120.558807
931412.93451.06554
941313.7775-0.777466
951615.0210.979034
961212.6392-0.639218
971414.7556-0.755632
981714.66472.33531
991514.71880.281246
1001715.07771.92234
1011212.8875-0.887497
1021615.52690.473078
1031114.5778-3.57777
1041513.18811.81189
105911.2585-2.25853
1061614.73891.26114
1071513.06061.93941
1081012.9787-2.97869
109109.470020.529983
1101513.39931.60071
1111112.8349-1.8349
1121314.7296-1.72962
1131412.94741.05258
1141814.83453.16547
1151615.22970.770327
1161413.77970.220273
1171413.68120.318837
1181415.1324-1.13238
1191413.35720.642822
1201212.6999-0.699946
1211413.42410.57595
1221514.39610.603853
1231515.6187-0.618696
1241514.45420.545839
1251314.6952-1.69521
1261716.58170.41828
1271715.22131.77872
1281914.94674.05332
1291513.41631.58371
1301314.511-1.51102
131910.7819-1.78192
1321514.89090.109063
1331512.67942.3206
1341514.02050.979523
1351613.02382.97618
136119.412821.58718
1371413.43650.563542
1381113.0641-2.06406
1391514.28650.713476
1401314.175-1.17499
1411514.84750.152472
1421613.23992.76006
1431414.4568-0.456815
1441513.86431.13567
1451614.1381.86196
1461614.14441.85563
1471113.3097-2.30967
1481214.415-2.41503
149911.2539-2.25388
1501614.59831.40171
1511312.20060.799357
1521615.74290.257128
1531214.0882-2.08817
154911.1805-2.18048
1551311.49611.50392
1561312.84420.155782
1571413.15980.840167
1581914.35294.6471
1591315.0111-2.01105
1601211.3870.613022
1611312.41640.583646
162109.887180.112825
1631412.9151.08501
1641611.44424.55575
1651011.609-1.60902
166119.126751.87325
1671414.1119-0.111899
1681212.5882-0.588182
169912.3541-3.35407
170911.6157-2.61573
1711110.35640.643638
1721614.0181.98195
173913.8942-4.89418
1741312.27360.726431
1751613.31322.68681
1761315.5309-2.53087
177912.0722-3.0722
1781211.23340.766633
1791614.83581.16416
1801112.8178-1.81784
1811414.4928-0.492796
1821314.6861-1.6861
1831514.39110.608909
1841414.6406-0.640574
1851613.73582.26416
1861312.11950.880486
1871413.32550.67447
1881514.08220.917792
1891312.62370.376323
1901110.00810.9919
1911113.672-2.67204
1921414.68-0.679959
1931512.51362.48637
1941112.3593-1.35925
1951512.66992.33006
1961213.8654-1.86537
1971411.28872.71125
1981413.65650.343523
199811.0592-3.05918
2001313.8827-0.882743
201911.8259-2.82593
2021513.60841.39159
2031714.13872.86126
2041312.65090.349141
2051514.28430.715674
2061513.39391.60612
2071413.71040.28956
2081612.69023.3098
2091312.84410.155869
2101614.67411.32594
211911.6473-2.64727
2121614.52531.47472
2131111.4137-0.413684
2141013.3079-3.30791
2151112.1799-1.17992
2161513.04391.95605
2171714.40452.59547
2181413.67420.325784
21989.50228-1.50228
2201512.99462.00537
2211113.731-2.73095
2221614.60631.39366
2231011.819-1.81895
2241515.0783-0.078304
225910.0206-1.02062
2261613.94442.05561
2271914.27194.72812
2281213.512-1.51205
22989.17958-1.17958
2301113.059-2.05895
2311413.30910.69087
232911.747-2.74705
2331515.0843-0.0842812
2341312.90410.0958537
2351614.75621.24377
2361113.0194-2.01944
2371210.79941.20061
2381313.0497-0.0496982
2391014.3592-4.35919
2401113.1407-2.14069
2411214.2466-2.24658
242810.6706-2.67063
2431211.40490.595054
2441211.89820.10184
2451513.00541.99455
2461111.159-0.158955
2471312.45640.543602
248149.382144.61786
249109.996350.00365142
2501211.58480.415196
2511512.79232.20768
2521311.13161.86843
2531313.8876-0.887551
2541313.243-0.242969
2551211.23170.768304
2561212.3155-0.315538
257910.344-1.34405
258912.0352-3.03519
2591512.35522.64481
2601014.7156-4.71559
2611413.45830.541728
2621513.29111.70886
26379.69258-2.69258
2641413.32940.670573






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
200.805960.3880790.19404
210.9135240.1729520.0864761
220.8881560.2236880.111844
230.8650060.2699870.134994
240.9627770.07444570.0372228
250.973510.05298070.0264903
260.9997360.0005287550.000264377
270.9995780.0008446530.000422326
280.9993740.001251790.000625897
290.9988660.002267290.00113364
300.9995840.0008327720.000416386
310.9994410.001117450.000558725
320.9990070.001986870.000993436
330.9984840.003031060.00151553
340.9981270.00374650.00187325
350.9969340.006131280.00306564
360.9951830.009633910.00481695
370.9930510.01389850.00694925
380.9916990.01660150.00830075
390.9912550.01749010.00874505
400.9883780.02324390.0116219
410.984680.03064070.0153203
420.9826250.0347510.0173755
430.9761530.04769420.0238471
440.9711920.05761680.0288084
450.9618470.07630610.0381531
460.9582140.08357150.0417857
470.9455950.108810.0544051
480.930630.138740.0693698
490.9731570.0536870.0268435
500.9661430.06771470.0338573
510.9570770.08584560.0429228
520.9512840.0974320.048716
530.9465120.1069760.053488
540.9476250.104750.0523752
550.9419510.1160990.0580493
560.9391990.1216020.0608011
570.929470.141060.07053
580.9179040.1641910.0820957
590.9264110.1471780.0735888
600.9168420.1663160.0831579
610.921430.1571410.0785703
620.9062360.1875280.0937642
630.921070.157860.0789302
640.9151610.1696770.0848387
650.9004740.1990530.0995263
660.9583310.08333840.0416692
670.9509380.0981250.0490625
680.9505940.09881160.0494058
690.9416680.1166640.0583322
700.9482520.1034970.0517483
710.9414180.1171640.0585818
720.954240.091520.04576
730.9508130.09837450.0491872
740.9404810.1190390.0595193
750.9307030.1385940.069297
760.9194970.1610050.0805026
770.9289010.1421970.0710986
780.9192990.1614020.0807008
790.9186510.1626980.0813488
800.9228170.1543660.0771828
810.9083990.1832020.091601
820.8943190.2113610.105681
830.8958790.2082430.104121
840.8795180.2409630.120482
850.8641840.2716320.135816
860.8535730.2928540.146427
870.8300540.3398920.169946
880.804970.3900610.19503
890.8743290.2513420.125671
900.8980540.2038920.101946
910.8807080.2385840.119292
920.8633490.2733020.136651
930.8439330.3121340.156067
940.8249540.3500920.175046
950.808940.382120.19106
960.7860280.4279440.213972
970.7640480.4719050.235952
980.7809080.4381830.219092
990.7521290.4957410.247871
1000.7512250.497550.248775
1010.7293040.5413920.270696
1020.7016650.5966690.298335
1030.7567840.4864310.243216
1040.7465590.5068820.253441
1050.7649260.4701470.235074
1060.7553080.4893840.244692
1070.7467310.5065370.253269
1080.7821870.4356270.217813
1090.7541490.4917030.245851
1100.7384720.5230560.261528
1110.7325050.5349890.267495
1120.7346310.5307370.265369
1130.7102910.5794180.289709
1140.7633940.4732120.236606
1150.7432360.5135280.256764
1160.7119590.5760820.288041
1170.6881790.6236420.311821
1180.6655110.6689770.334489
1190.6332120.7335770.366788
1200.6021580.7956830.397842
1210.5799440.8401130.420056
1220.5454130.9091740.454587
1230.5127510.9744980.487249
1240.4822330.9644650.517767
1250.4755290.9510590.524471
1260.4432410.8864830.556759
1270.4260580.8521160.573942
1280.5224610.9550780.477539
1290.5069390.9861220.493061
1300.4961620.9923240.503838
1310.4837330.9674650.516267
1320.4468650.893730.553135
1330.4567930.9135850.543207
1340.4274510.8549020.572549
1350.4673260.9346530.532674
1360.4543150.9086310.545685
1370.4203580.8407160.579642
1380.4248040.8496080.575196
1390.3909090.7818170.609091
1400.3702750.7405490.629725
1410.3399320.6798650.660068
1420.3623790.7247580.637621
1430.3305170.6610350.669483
1440.3073550.614710.692645
1450.2962520.5925030.703748
1460.2864180.5728360.713582
1470.2998940.5997870.700106
1480.3255820.6511640.674418
1490.336640.6732810.66336
1500.3175660.6351310.682434
1510.2883270.5766540.711673
1520.2569260.5138520.743074
1530.2604110.5208210.739589
1540.2711420.5422830.728858
1550.2534150.506830.746585
1560.223950.4479010.77605
1570.200770.401540.79923
1580.3380.6759990.662
1590.3477570.6955150.652243
1600.3147910.6295820.685209
1610.2858080.5716160.714192
1620.2562840.5125680.743716
1630.2309540.4619080.769046
1640.3465180.6930360.653482
1650.3322570.6645150.667743
1660.3211280.6422550.678872
1670.2872670.5745350.712733
1680.2587370.5174740.741263
1690.3072640.6145280.692736
1700.316830.633660.68317
1710.2832280.5664560.716772
1720.2748160.5496310.725184
1730.4493240.8986480.550676
1740.4118480.8236960.588152
1750.4281470.8562940.571853
1760.4477440.8954880.552256
1770.4897820.9795640.510218
1780.45160.9031990.5484
1790.4199780.8399550.580022
1800.4141390.8282790.585861
1810.3810890.7621780.618911
1820.3649040.7298070.635096
1830.3286290.6572590.671371
1840.3035040.6070080.696496
1850.2997320.5994640.700268
1860.2688670.5377330.731133
1870.2376110.4752220.762389
1880.2089090.4178170.791091
1890.18050.3610.8195
1900.1579380.3158770.842062
1910.1783390.3566780.821661
1920.1593650.318730.840635
1930.1660650.3321310.833935
1940.1474060.2948130.852594
1950.1429990.2859970.857001
1960.1494650.2989290.850535
1970.170340.3406790.82966
1980.1439140.2878280.856086
1990.1629720.3259440.837028
2000.1406850.2813710.859315
2010.1736130.3472260.826387
2020.151840.3036790.84816
2030.1655720.3311440.834428
2040.1381890.2763780.861811
2050.1155680.2311360.884432
2060.1143730.2287470.885627
2070.09378650.1875730.906213
2080.1123840.2247680.887616
2090.09512290.1902460.904877
2100.08476270.1695250.915237
2110.09120450.1824090.908796
2120.07967140.1593430.920329
2130.06395480.127910.936045
2140.1140030.2280060.885997
2150.1031110.2062210.896889
2160.09659760.1931950.903402
2170.1088130.2176260.891187
2180.09522430.1904490.904776
2190.09511940.1902390.904881
2200.09389250.1877850.906108
2210.09768270.1953650.902317
2220.09460550.1892110.905394
2230.117790.235580.88221
2240.09220460.1844090.907795
2250.09732930.1946590.902671
2260.08210060.1642010.917899
2270.3434130.6868260.656587
2280.3103990.6207980.689601
2290.2709970.5419930.729003
2300.2229220.4458440.777078
2310.1753970.3507930.824603
2320.182250.36450.81775
2330.1410750.2821490.858925
2340.1143050.228610.885695
2350.08629620.1725920.913704
2360.07447090.1489420.925529
2370.05901910.1180380.940981
2380.03878310.07756620.961217
2390.1573070.3146130.842693
2400.3645930.7291870.635407
2410.3234140.6468290.676586
2420.2956630.5913250.704337
2430.1905960.3811910.809404
2440.1459590.2919180.854041

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
20 & 0.80596 & 0.388079 & 0.19404 \tabularnewline
21 & 0.913524 & 0.172952 & 0.0864761 \tabularnewline
22 & 0.888156 & 0.223688 & 0.111844 \tabularnewline
23 & 0.865006 & 0.269987 & 0.134994 \tabularnewline
24 & 0.962777 & 0.0744457 & 0.0372228 \tabularnewline
25 & 0.97351 & 0.0529807 & 0.0264903 \tabularnewline
26 & 0.999736 & 0.000528755 & 0.000264377 \tabularnewline
27 & 0.999578 & 0.000844653 & 0.000422326 \tabularnewline
28 & 0.999374 & 0.00125179 & 0.000625897 \tabularnewline
29 & 0.998866 & 0.00226729 & 0.00113364 \tabularnewline
30 & 0.999584 & 0.000832772 & 0.000416386 \tabularnewline
31 & 0.999441 & 0.00111745 & 0.000558725 \tabularnewline
32 & 0.999007 & 0.00198687 & 0.000993436 \tabularnewline
33 & 0.998484 & 0.00303106 & 0.00151553 \tabularnewline
34 & 0.998127 & 0.0037465 & 0.00187325 \tabularnewline
35 & 0.996934 & 0.00613128 & 0.00306564 \tabularnewline
36 & 0.995183 & 0.00963391 & 0.00481695 \tabularnewline
37 & 0.993051 & 0.0138985 & 0.00694925 \tabularnewline
38 & 0.991699 & 0.0166015 & 0.00830075 \tabularnewline
39 & 0.991255 & 0.0174901 & 0.00874505 \tabularnewline
40 & 0.988378 & 0.0232439 & 0.0116219 \tabularnewline
41 & 0.98468 & 0.0306407 & 0.0153203 \tabularnewline
42 & 0.982625 & 0.034751 & 0.0173755 \tabularnewline
43 & 0.976153 & 0.0476942 & 0.0238471 \tabularnewline
44 & 0.971192 & 0.0576168 & 0.0288084 \tabularnewline
45 & 0.961847 & 0.0763061 & 0.0381531 \tabularnewline
46 & 0.958214 & 0.0835715 & 0.0417857 \tabularnewline
47 & 0.945595 & 0.10881 & 0.0544051 \tabularnewline
48 & 0.93063 & 0.13874 & 0.0693698 \tabularnewline
49 & 0.973157 & 0.053687 & 0.0268435 \tabularnewline
50 & 0.966143 & 0.0677147 & 0.0338573 \tabularnewline
51 & 0.957077 & 0.0858456 & 0.0429228 \tabularnewline
52 & 0.951284 & 0.097432 & 0.048716 \tabularnewline
53 & 0.946512 & 0.106976 & 0.053488 \tabularnewline
54 & 0.947625 & 0.10475 & 0.0523752 \tabularnewline
55 & 0.941951 & 0.116099 & 0.0580493 \tabularnewline
56 & 0.939199 & 0.121602 & 0.0608011 \tabularnewline
57 & 0.92947 & 0.14106 & 0.07053 \tabularnewline
58 & 0.917904 & 0.164191 & 0.0820957 \tabularnewline
59 & 0.926411 & 0.147178 & 0.0735888 \tabularnewline
60 & 0.916842 & 0.166316 & 0.0831579 \tabularnewline
61 & 0.92143 & 0.157141 & 0.0785703 \tabularnewline
62 & 0.906236 & 0.187528 & 0.0937642 \tabularnewline
63 & 0.92107 & 0.15786 & 0.0789302 \tabularnewline
64 & 0.915161 & 0.169677 & 0.0848387 \tabularnewline
65 & 0.900474 & 0.199053 & 0.0995263 \tabularnewline
66 & 0.958331 & 0.0833384 & 0.0416692 \tabularnewline
67 & 0.950938 & 0.098125 & 0.0490625 \tabularnewline
68 & 0.950594 & 0.0988116 & 0.0494058 \tabularnewline
69 & 0.941668 & 0.116664 & 0.0583322 \tabularnewline
70 & 0.948252 & 0.103497 & 0.0517483 \tabularnewline
71 & 0.941418 & 0.117164 & 0.0585818 \tabularnewline
72 & 0.95424 & 0.09152 & 0.04576 \tabularnewline
73 & 0.950813 & 0.0983745 & 0.0491872 \tabularnewline
74 & 0.940481 & 0.119039 & 0.0595193 \tabularnewline
75 & 0.930703 & 0.138594 & 0.069297 \tabularnewline
76 & 0.919497 & 0.161005 & 0.0805026 \tabularnewline
77 & 0.928901 & 0.142197 & 0.0710986 \tabularnewline
78 & 0.919299 & 0.161402 & 0.0807008 \tabularnewline
79 & 0.918651 & 0.162698 & 0.0813488 \tabularnewline
80 & 0.922817 & 0.154366 & 0.0771828 \tabularnewline
81 & 0.908399 & 0.183202 & 0.091601 \tabularnewline
82 & 0.894319 & 0.211361 & 0.105681 \tabularnewline
83 & 0.895879 & 0.208243 & 0.104121 \tabularnewline
84 & 0.879518 & 0.240963 & 0.120482 \tabularnewline
85 & 0.864184 & 0.271632 & 0.135816 \tabularnewline
86 & 0.853573 & 0.292854 & 0.146427 \tabularnewline
87 & 0.830054 & 0.339892 & 0.169946 \tabularnewline
88 & 0.80497 & 0.390061 & 0.19503 \tabularnewline
89 & 0.874329 & 0.251342 & 0.125671 \tabularnewline
90 & 0.898054 & 0.203892 & 0.101946 \tabularnewline
91 & 0.880708 & 0.238584 & 0.119292 \tabularnewline
92 & 0.863349 & 0.273302 & 0.136651 \tabularnewline
93 & 0.843933 & 0.312134 & 0.156067 \tabularnewline
94 & 0.824954 & 0.350092 & 0.175046 \tabularnewline
95 & 0.80894 & 0.38212 & 0.19106 \tabularnewline
96 & 0.786028 & 0.427944 & 0.213972 \tabularnewline
97 & 0.764048 & 0.471905 & 0.235952 \tabularnewline
98 & 0.780908 & 0.438183 & 0.219092 \tabularnewline
99 & 0.752129 & 0.495741 & 0.247871 \tabularnewline
100 & 0.751225 & 0.49755 & 0.248775 \tabularnewline
101 & 0.729304 & 0.541392 & 0.270696 \tabularnewline
102 & 0.701665 & 0.596669 & 0.298335 \tabularnewline
103 & 0.756784 & 0.486431 & 0.243216 \tabularnewline
104 & 0.746559 & 0.506882 & 0.253441 \tabularnewline
105 & 0.764926 & 0.470147 & 0.235074 \tabularnewline
106 & 0.755308 & 0.489384 & 0.244692 \tabularnewline
107 & 0.746731 & 0.506537 & 0.253269 \tabularnewline
108 & 0.782187 & 0.435627 & 0.217813 \tabularnewline
109 & 0.754149 & 0.491703 & 0.245851 \tabularnewline
110 & 0.738472 & 0.523056 & 0.261528 \tabularnewline
111 & 0.732505 & 0.534989 & 0.267495 \tabularnewline
112 & 0.734631 & 0.530737 & 0.265369 \tabularnewline
113 & 0.710291 & 0.579418 & 0.289709 \tabularnewline
114 & 0.763394 & 0.473212 & 0.236606 \tabularnewline
115 & 0.743236 & 0.513528 & 0.256764 \tabularnewline
116 & 0.711959 & 0.576082 & 0.288041 \tabularnewline
117 & 0.688179 & 0.623642 & 0.311821 \tabularnewline
118 & 0.665511 & 0.668977 & 0.334489 \tabularnewline
119 & 0.633212 & 0.733577 & 0.366788 \tabularnewline
120 & 0.602158 & 0.795683 & 0.397842 \tabularnewline
121 & 0.579944 & 0.840113 & 0.420056 \tabularnewline
122 & 0.545413 & 0.909174 & 0.454587 \tabularnewline
123 & 0.512751 & 0.974498 & 0.487249 \tabularnewline
124 & 0.482233 & 0.964465 & 0.517767 \tabularnewline
125 & 0.475529 & 0.951059 & 0.524471 \tabularnewline
126 & 0.443241 & 0.886483 & 0.556759 \tabularnewline
127 & 0.426058 & 0.852116 & 0.573942 \tabularnewline
128 & 0.522461 & 0.955078 & 0.477539 \tabularnewline
129 & 0.506939 & 0.986122 & 0.493061 \tabularnewline
130 & 0.496162 & 0.992324 & 0.503838 \tabularnewline
131 & 0.483733 & 0.967465 & 0.516267 \tabularnewline
132 & 0.446865 & 0.89373 & 0.553135 \tabularnewline
133 & 0.456793 & 0.913585 & 0.543207 \tabularnewline
134 & 0.427451 & 0.854902 & 0.572549 \tabularnewline
135 & 0.467326 & 0.934653 & 0.532674 \tabularnewline
136 & 0.454315 & 0.908631 & 0.545685 \tabularnewline
137 & 0.420358 & 0.840716 & 0.579642 \tabularnewline
138 & 0.424804 & 0.849608 & 0.575196 \tabularnewline
139 & 0.390909 & 0.781817 & 0.609091 \tabularnewline
140 & 0.370275 & 0.740549 & 0.629725 \tabularnewline
141 & 0.339932 & 0.679865 & 0.660068 \tabularnewline
142 & 0.362379 & 0.724758 & 0.637621 \tabularnewline
143 & 0.330517 & 0.661035 & 0.669483 \tabularnewline
144 & 0.307355 & 0.61471 & 0.692645 \tabularnewline
145 & 0.296252 & 0.592503 & 0.703748 \tabularnewline
146 & 0.286418 & 0.572836 & 0.713582 \tabularnewline
147 & 0.299894 & 0.599787 & 0.700106 \tabularnewline
148 & 0.325582 & 0.651164 & 0.674418 \tabularnewline
149 & 0.33664 & 0.673281 & 0.66336 \tabularnewline
150 & 0.317566 & 0.635131 & 0.682434 \tabularnewline
151 & 0.288327 & 0.576654 & 0.711673 \tabularnewline
152 & 0.256926 & 0.513852 & 0.743074 \tabularnewline
153 & 0.260411 & 0.520821 & 0.739589 \tabularnewline
154 & 0.271142 & 0.542283 & 0.728858 \tabularnewline
155 & 0.253415 & 0.50683 & 0.746585 \tabularnewline
156 & 0.22395 & 0.447901 & 0.77605 \tabularnewline
157 & 0.20077 & 0.40154 & 0.79923 \tabularnewline
158 & 0.338 & 0.675999 & 0.662 \tabularnewline
159 & 0.347757 & 0.695515 & 0.652243 \tabularnewline
160 & 0.314791 & 0.629582 & 0.685209 \tabularnewline
161 & 0.285808 & 0.571616 & 0.714192 \tabularnewline
162 & 0.256284 & 0.512568 & 0.743716 \tabularnewline
163 & 0.230954 & 0.461908 & 0.769046 \tabularnewline
164 & 0.346518 & 0.693036 & 0.653482 \tabularnewline
165 & 0.332257 & 0.664515 & 0.667743 \tabularnewline
166 & 0.321128 & 0.642255 & 0.678872 \tabularnewline
167 & 0.287267 & 0.574535 & 0.712733 \tabularnewline
168 & 0.258737 & 0.517474 & 0.741263 \tabularnewline
169 & 0.307264 & 0.614528 & 0.692736 \tabularnewline
170 & 0.31683 & 0.63366 & 0.68317 \tabularnewline
171 & 0.283228 & 0.566456 & 0.716772 \tabularnewline
172 & 0.274816 & 0.549631 & 0.725184 \tabularnewline
173 & 0.449324 & 0.898648 & 0.550676 \tabularnewline
174 & 0.411848 & 0.823696 & 0.588152 \tabularnewline
175 & 0.428147 & 0.856294 & 0.571853 \tabularnewline
176 & 0.447744 & 0.895488 & 0.552256 \tabularnewline
177 & 0.489782 & 0.979564 & 0.510218 \tabularnewline
178 & 0.4516 & 0.903199 & 0.5484 \tabularnewline
179 & 0.419978 & 0.839955 & 0.580022 \tabularnewline
180 & 0.414139 & 0.828279 & 0.585861 \tabularnewline
181 & 0.381089 & 0.762178 & 0.618911 \tabularnewline
182 & 0.364904 & 0.729807 & 0.635096 \tabularnewline
183 & 0.328629 & 0.657259 & 0.671371 \tabularnewline
184 & 0.303504 & 0.607008 & 0.696496 \tabularnewline
185 & 0.299732 & 0.599464 & 0.700268 \tabularnewline
186 & 0.268867 & 0.537733 & 0.731133 \tabularnewline
187 & 0.237611 & 0.475222 & 0.762389 \tabularnewline
188 & 0.208909 & 0.417817 & 0.791091 \tabularnewline
189 & 0.1805 & 0.361 & 0.8195 \tabularnewline
190 & 0.157938 & 0.315877 & 0.842062 \tabularnewline
191 & 0.178339 & 0.356678 & 0.821661 \tabularnewline
192 & 0.159365 & 0.31873 & 0.840635 \tabularnewline
193 & 0.166065 & 0.332131 & 0.833935 \tabularnewline
194 & 0.147406 & 0.294813 & 0.852594 \tabularnewline
195 & 0.142999 & 0.285997 & 0.857001 \tabularnewline
196 & 0.149465 & 0.298929 & 0.850535 \tabularnewline
197 & 0.17034 & 0.340679 & 0.82966 \tabularnewline
198 & 0.143914 & 0.287828 & 0.856086 \tabularnewline
199 & 0.162972 & 0.325944 & 0.837028 \tabularnewline
200 & 0.140685 & 0.281371 & 0.859315 \tabularnewline
201 & 0.173613 & 0.347226 & 0.826387 \tabularnewline
202 & 0.15184 & 0.303679 & 0.84816 \tabularnewline
203 & 0.165572 & 0.331144 & 0.834428 \tabularnewline
204 & 0.138189 & 0.276378 & 0.861811 \tabularnewline
205 & 0.115568 & 0.231136 & 0.884432 \tabularnewline
206 & 0.114373 & 0.228747 & 0.885627 \tabularnewline
207 & 0.0937865 & 0.187573 & 0.906213 \tabularnewline
208 & 0.112384 & 0.224768 & 0.887616 \tabularnewline
209 & 0.0951229 & 0.190246 & 0.904877 \tabularnewline
210 & 0.0847627 & 0.169525 & 0.915237 \tabularnewline
211 & 0.0912045 & 0.182409 & 0.908796 \tabularnewline
212 & 0.0796714 & 0.159343 & 0.920329 \tabularnewline
213 & 0.0639548 & 0.12791 & 0.936045 \tabularnewline
214 & 0.114003 & 0.228006 & 0.885997 \tabularnewline
215 & 0.103111 & 0.206221 & 0.896889 \tabularnewline
216 & 0.0965976 & 0.193195 & 0.903402 \tabularnewline
217 & 0.108813 & 0.217626 & 0.891187 \tabularnewline
218 & 0.0952243 & 0.190449 & 0.904776 \tabularnewline
219 & 0.0951194 & 0.190239 & 0.904881 \tabularnewline
220 & 0.0938925 & 0.187785 & 0.906108 \tabularnewline
221 & 0.0976827 & 0.195365 & 0.902317 \tabularnewline
222 & 0.0946055 & 0.189211 & 0.905394 \tabularnewline
223 & 0.11779 & 0.23558 & 0.88221 \tabularnewline
224 & 0.0922046 & 0.184409 & 0.907795 \tabularnewline
225 & 0.0973293 & 0.194659 & 0.902671 \tabularnewline
226 & 0.0821006 & 0.164201 & 0.917899 \tabularnewline
227 & 0.343413 & 0.686826 & 0.656587 \tabularnewline
228 & 0.310399 & 0.620798 & 0.689601 \tabularnewline
229 & 0.270997 & 0.541993 & 0.729003 \tabularnewline
230 & 0.222922 & 0.445844 & 0.777078 \tabularnewline
231 & 0.175397 & 0.350793 & 0.824603 \tabularnewline
232 & 0.18225 & 0.3645 & 0.81775 \tabularnewline
233 & 0.141075 & 0.282149 & 0.858925 \tabularnewline
234 & 0.114305 & 0.22861 & 0.885695 \tabularnewline
235 & 0.0862962 & 0.172592 & 0.913704 \tabularnewline
236 & 0.0744709 & 0.148942 & 0.925529 \tabularnewline
237 & 0.0590191 & 0.118038 & 0.940981 \tabularnewline
238 & 0.0387831 & 0.0775662 & 0.961217 \tabularnewline
239 & 0.157307 & 0.314613 & 0.842693 \tabularnewline
240 & 0.364593 & 0.729187 & 0.635407 \tabularnewline
241 & 0.323414 & 0.646829 & 0.676586 \tabularnewline
242 & 0.295663 & 0.591325 & 0.704337 \tabularnewline
243 & 0.190596 & 0.381191 & 0.809404 \tabularnewline
244 & 0.145959 & 0.291918 & 0.854041 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226642&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]20[/C][C]0.80596[/C][C]0.388079[/C][C]0.19404[/C][/ROW]
[ROW][C]21[/C][C]0.913524[/C][C]0.172952[/C][C]0.0864761[/C][/ROW]
[ROW][C]22[/C][C]0.888156[/C][C]0.223688[/C][C]0.111844[/C][/ROW]
[ROW][C]23[/C][C]0.865006[/C][C]0.269987[/C][C]0.134994[/C][/ROW]
[ROW][C]24[/C][C]0.962777[/C][C]0.0744457[/C][C]0.0372228[/C][/ROW]
[ROW][C]25[/C][C]0.97351[/C][C]0.0529807[/C][C]0.0264903[/C][/ROW]
[ROW][C]26[/C][C]0.999736[/C][C]0.000528755[/C][C]0.000264377[/C][/ROW]
[ROW][C]27[/C][C]0.999578[/C][C]0.000844653[/C][C]0.000422326[/C][/ROW]
[ROW][C]28[/C][C]0.999374[/C][C]0.00125179[/C][C]0.000625897[/C][/ROW]
[ROW][C]29[/C][C]0.998866[/C][C]0.00226729[/C][C]0.00113364[/C][/ROW]
[ROW][C]30[/C][C]0.999584[/C][C]0.000832772[/C][C]0.000416386[/C][/ROW]
[ROW][C]31[/C][C]0.999441[/C][C]0.00111745[/C][C]0.000558725[/C][/ROW]
[ROW][C]32[/C][C]0.999007[/C][C]0.00198687[/C][C]0.000993436[/C][/ROW]
[ROW][C]33[/C][C]0.998484[/C][C]0.00303106[/C][C]0.00151553[/C][/ROW]
[ROW][C]34[/C][C]0.998127[/C][C]0.0037465[/C][C]0.00187325[/C][/ROW]
[ROW][C]35[/C][C]0.996934[/C][C]0.00613128[/C][C]0.00306564[/C][/ROW]
[ROW][C]36[/C][C]0.995183[/C][C]0.00963391[/C][C]0.00481695[/C][/ROW]
[ROW][C]37[/C][C]0.993051[/C][C]0.0138985[/C][C]0.00694925[/C][/ROW]
[ROW][C]38[/C][C]0.991699[/C][C]0.0166015[/C][C]0.00830075[/C][/ROW]
[ROW][C]39[/C][C]0.991255[/C][C]0.0174901[/C][C]0.00874505[/C][/ROW]
[ROW][C]40[/C][C]0.988378[/C][C]0.0232439[/C][C]0.0116219[/C][/ROW]
[ROW][C]41[/C][C]0.98468[/C][C]0.0306407[/C][C]0.0153203[/C][/ROW]
[ROW][C]42[/C][C]0.982625[/C][C]0.034751[/C][C]0.0173755[/C][/ROW]
[ROW][C]43[/C][C]0.976153[/C][C]0.0476942[/C][C]0.0238471[/C][/ROW]
[ROW][C]44[/C][C]0.971192[/C][C]0.0576168[/C][C]0.0288084[/C][/ROW]
[ROW][C]45[/C][C]0.961847[/C][C]0.0763061[/C][C]0.0381531[/C][/ROW]
[ROW][C]46[/C][C]0.958214[/C][C]0.0835715[/C][C]0.0417857[/C][/ROW]
[ROW][C]47[/C][C]0.945595[/C][C]0.10881[/C][C]0.0544051[/C][/ROW]
[ROW][C]48[/C][C]0.93063[/C][C]0.13874[/C][C]0.0693698[/C][/ROW]
[ROW][C]49[/C][C]0.973157[/C][C]0.053687[/C][C]0.0268435[/C][/ROW]
[ROW][C]50[/C][C]0.966143[/C][C]0.0677147[/C][C]0.0338573[/C][/ROW]
[ROW][C]51[/C][C]0.957077[/C][C]0.0858456[/C][C]0.0429228[/C][/ROW]
[ROW][C]52[/C][C]0.951284[/C][C]0.097432[/C][C]0.048716[/C][/ROW]
[ROW][C]53[/C][C]0.946512[/C][C]0.106976[/C][C]0.053488[/C][/ROW]
[ROW][C]54[/C][C]0.947625[/C][C]0.10475[/C][C]0.0523752[/C][/ROW]
[ROW][C]55[/C][C]0.941951[/C][C]0.116099[/C][C]0.0580493[/C][/ROW]
[ROW][C]56[/C][C]0.939199[/C][C]0.121602[/C][C]0.0608011[/C][/ROW]
[ROW][C]57[/C][C]0.92947[/C][C]0.14106[/C][C]0.07053[/C][/ROW]
[ROW][C]58[/C][C]0.917904[/C][C]0.164191[/C][C]0.0820957[/C][/ROW]
[ROW][C]59[/C][C]0.926411[/C][C]0.147178[/C][C]0.0735888[/C][/ROW]
[ROW][C]60[/C][C]0.916842[/C][C]0.166316[/C][C]0.0831579[/C][/ROW]
[ROW][C]61[/C][C]0.92143[/C][C]0.157141[/C][C]0.0785703[/C][/ROW]
[ROW][C]62[/C][C]0.906236[/C][C]0.187528[/C][C]0.0937642[/C][/ROW]
[ROW][C]63[/C][C]0.92107[/C][C]0.15786[/C][C]0.0789302[/C][/ROW]
[ROW][C]64[/C][C]0.915161[/C][C]0.169677[/C][C]0.0848387[/C][/ROW]
[ROW][C]65[/C][C]0.900474[/C][C]0.199053[/C][C]0.0995263[/C][/ROW]
[ROW][C]66[/C][C]0.958331[/C][C]0.0833384[/C][C]0.0416692[/C][/ROW]
[ROW][C]67[/C][C]0.950938[/C][C]0.098125[/C][C]0.0490625[/C][/ROW]
[ROW][C]68[/C][C]0.950594[/C][C]0.0988116[/C][C]0.0494058[/C][/ROW]
[ROW][C]69[/C][C]0.941668[/C][C]0.116664[/C][C]0.0583322[/C][/ROW]
[ROW][C]70[/C][C]0.948252[/C][C]0.103497[/C][C]0.0517483[/C][/ROW]
[ROW][C]71[/C][C]0.941418[/C][C]0.117164[/C][C]0.0585818[/C][/ROW]
[ROW][C]72[/C][C]0.95424[/C][C]0.09152[/C][C]0.04576[/C][/ROW]
[ROW][C]73[/C][C]0.950813[/C][C]0.0983745[/C][C]0.0491872[/C][/ROW]
[ROW][C]74[/C][C]0.940481[/C][C]0.119039[/C][C]0.0595193[/C][/ROW]
[ROW][C]75[/C][C]0.930703[/C][C]0.138594[/C][C]0.069297[/C][/ROW]
[ROW][C]76[/C][C]0.919497[/C][C]0.161005[/C][C]0.0805026[/C][/ROW]
[ROW][C]77[/C][C]0.928901[/C][C]0.142197[/C][C]0.0710986[/C][/ROW]
[ROW][C]78[/C][C]0.919299[/C][C]0.161402[/C][C]0.0807008[/C][/ROW]
[ROW][C]79[/C][C]0.918651[/C][C]0.162698[/C][C]0.0813488[/C][/ROW]
[ROW][C]80[/C][C]0.922817[/C][C]0.154366[/C][C]0.0771828[/C][/ROW]
[ROW][C]81[/C][C]0.908399[/C][C]0.183202[/C][C]0.091601[/C][/ROW]
[ROW][C]82[/C][C]0.894319[/C][C]0.211361[/C][C]0.105681[/C][/ROW]
[ROW][C]83[/C][C]0.895879[/C][C]0.208243[/C][C]0.104121[/C][/ROW]
[ROW][C]84[/C][C]0.879518[/C][C]0.240963[/C][C]0.120482[/C][/ROW]
[ROW][C]85[/C][C]0.864184[/C][C]0.271632[/C][C]0.135816[/C][/ROW]
[ROW][C]86[/C][C]0.853573[/C][C]0.292854[/C][C]0.146427[/C][/ROW]
[ROW][C]87[/C][C]0.830054[/C][C]0.339892[/C][C]0.169946[/C][/ROW]
[ROW][C]88[/C][C]0.80497[/C][C]0.390061[/C][C]0.19503[/C][/ROW]
[ROW][C]89[/C][C]0.874329[/C][C]0.251342[/C][C]0.125671[/C][/ROW]
[ROW][C]90[/C][C]0.898054[/C][C]0.203892[/C][C]0.101946[/C][/ROW]
[ROW][C]91[/C][C]0.880708[/C][C]0.238584[/C][C]0.119292[/C][/ROW]
[ROW][C]92[/C][C]0.863349[/C][C]0.273302[/C][C]0.136651[/C][/ROW]
[ROW][C]93[/C][C]0.843933[/C][C]0.312134[/C][C]0.156067[/C][/ROW]
[ROW][C]94[/C][C]0.824954[/C][C]0.350092[/C][C]0.175046[/C][/ROW]
[ROW][C]95[/C][C]0.80894[/C][C]0.38212[/C][C]0.19106[/C][/ROW]
[ROW][C]96[/C][C]0.786028[/C][C]0.427944[/C][C]0.213972[/C][/ROW]
[ROW][C]97[/C][C]0.764048[/C][C]0.471905[/C][C]0.235952[/C][/ROW]
[ROW][C]98[/C][C]0.780908[/C][C]0.438183[/C][C]0.219092[/C][/ROW]
[ROW][C]99[/C][C]0.752129[/C][C]0.495741[/C][C]0.247871[/C][/ROW]
[ROW][C]100[/C][C]0.751225[/C][C]0.49755[/C][C]0.248775[/C][/ROW]
[ROW][C]101[/C][C]0.729304[/C][C]0.541392[/C][C]0.270696[/C][/ROW]
[ROW][C]102[/C][C]0.701665[/C][C]0.596669[/C][C]0.298335[/C][/ROW]
[ROW][C]103[/C][C]0.756784[/C][C]0.486431[/C][C]0.243216[/C][/ROW]
[ROW][C]104[/C][C]0.746559[/C][C]0.506882[/C][C]0.253441[/C][/ROW]
[ROW][C]105[/C][C]0.764926[/C][C]0.470147[/C][C]0.235074[/C][/ROW]
[ROW][C]106[/C][C]0.755308[/C][C]0.489384[/C][C]0.244692[/C][/ROW]
[ROW][C]107[/C][C]0.746731[/C][C]0.506537[/C][C]0.253269[/C][/ROW]
[ROW][C]108[/C][C]0.782187[/C][C]0.435627[/C][C]0.217813[/C][/ROW]
[ROW][C]109[/C][C]0.754149[/C][C]0.491703[/C][C]0.245851[/C][/ROW]
[ROW][C]110[/C][C]0.738472[/C][C]0.523056[/C][C]0.261528[/C][/ROW]
[ROW][C]111[/C][C]0.732505[/C][C]0.534989[/C][C]0.267495[/C][/ROW]
[ROW][C]112[/C][C]0.734631[/C][C]0.530737[/C][C]0.265369[/C][/ROW]
[ROW][C]113[/C][C]0.710291[/C][C]0.579418[/C][C]0.289709[/C][/ROW]
[ROW][C]114[/C][C]0.763394[/C][C]0.473212[/C][C]0.236606[/C][/ROW]
[ROW][C]115[/C][C]0.743236[/C][C]0.513528[/C][C]0.256764[/C][/ROW]
[ROW][C]116[/C][C]0.711959[/C][C]0.576082[/C][C]0.288041[/C][/ROW]
[ROW][C]117[/C][C]0.688179[/C][C]0.623642[/C][C]0.311821[/C][/ROW]
[ROW][C]118[/C][C]0.665511[/C][C]0.668977[/C][C]0.334489[/C][/ROW]
[ROW][C]119[/C][C]0.633212[/C][C]0.733577[/C][C]0.366788[/C][/ROW]
[ROW][C]120[/C][C]0.602158[/C][C]0.795683[/C][C]0.397842[/C][/ROW]
[ROW][C]121[/C][C]0.579944[/C][C]0.840113[/C][C]0.420056[/C][/ROW]
[ROW][C]122[/C][C]0.545413[/C][C]0.909174[/C][C]0.454587[/C][/ROW]
[ROW][C]123[/C][C]0.512751[/C][C]0.974498[/C][C]0.487249[/C][/ROW]
[ROW][C]124[/C][C]0.482233[/C][C]0.964465[/C][C]0.517767[/C][/ROW]
[ROW][C]125[/C][C]0.475529[/C][C]0.951059[/C][C]0.524471[/C][/ROW]
[ROW][C]126[/C][C]0.443241[/C][C]0.886483[/C][C]0.556759[/C][/ROW]
[ROW][C]127[/C][C]0.426058[/C][C]0.852116[/C][C]0.573942[/C][/ROW]
[ROW][C]128[/C][C]0.522461[/C][C]0.955078[/C][C]0.477539[/C][/ROW]
[ROW][C]129[/C][C]0.506939[/C][C]0.986122[/C][C]0.493061[/C][/ROW]
[ROW][C]130[/C][C]0.496162[/C][C]0.992324[/C][C]0.503838[/C][/ROW]
[ROW][C]131[/C][C]0.483733[/C][C]0.967465[/C][C]0.516267[/C][/ROW]
[ROW][C]132[/C][C]0.446865[/C][C]0.89373[/C][C]0.553135[/C][/ROW]
[ROW][C]133[/C][C]0.456793[/C][C]0.913585[/C][C]0.543207[/C][/ROW]
[ROW][C]134[/C][C]0.427451[/C][C]0.854902[/C][C]0.572549[/C][/ROW]
[ROW][C]135[/C][C]0.467326[/C][C]0.934653[/C][C]0.532674[/C][/ROW]
[ROW][C]136[/C][C]0.454315[/C][C]0.908631[/C][C]0.545685[/C][/ROW]
[ROW][C]137[/C][C]0.420358[/C][C]0.840716[/C][C]0.579642[/C][/ROW]
[ROW][C]138[/C][C]0.424804[/C][C]0.849608[/C][C]0.575196[/C][/ROW]
[ROW][C]139[/C][C]0.390909[/C][C]0.781817[/C][C]0.609091[/C][/ROW]
[ROW][C]140[/C][C]0.370275[/C][C]0.740549[/C][C]0.629725[/C][/ROW]
[ROW][C]141[/C][C]0.339932[/C][C]0.679865[/C][C]0.660068[/C][/ROW]
[ROW][C]142[/C][C]0.362379[/C][C]0.724758[/C][C]0.637621[/C][/ROW]
[ROW][C]143[/C][C]0.330517[/C][C]0.661035[/C][C]0.669483[/C][/ROW]
[ROW][C]144[/C][C]0.307355[/C][C]0.61471[/C][C]0.692645[/C][/ROW]
[ROW][C]145[/C][C]0.296252[/C][C]0.592503[/C][C]0.703748[/C][/ROW]
[ROW][C]146[/C][C]0.286418[/C][C]0.572836[/C][C]0.713582[/C][/ROW]
[ROW][C]147[/C][C]0.299894[/C][C]0.599787[/C][C]0.700106[/C][/ROW]
[ROW][C]148[/C][C]0.325582[/C][C]0.651164[/C][C]0.674418[/C][/ROW]
[ROW][C]149[/C][C]0.33664[/C][C]0.673281[/C][C]0.66336[/C][/ROW]
[ROW][C]150[/C][C]0.317566[/C][C]0.635131[/C][C]0.682434[/C][/ROW]
[ROW][C]151[/C][C]0.288327[/C][C]0.576654[/C][C]0.711673[/C][/ROW]
[ROW][C]152[/C][C]0.256926[/C][C]0.513852[/C][C]0.743074[/C][/ROW]
[ROW][C]153[/C][C]0.260411[/C][C]0.520821[/C][C]0.739589[/C][/ROW]
[ROW][C]154[/C][C]0.271142[/C][C]0.542283[/C][C]0.728858[/C][/ROW]
[ROW][C]155[/C][C]0.253415[/C][C]0.50683[/C][C]0.746585[/C][/ROW]
[ROW][C]156[/C][C]0.22395[/C][C]0.447901[/C][C]0.77605[/C][/ROW]
[ROW][C]157[/C][C]0.20077[/C][C]0.40154[/C][C]0.79923[/C][/ROW]
[ROW][C]158[/C][C]0.338[/C][C]0.675999[/C][C]0.662[/C][/ROW]
[ROW][C]159[/C][C]0.347757[/C][C]0.695515[/C][C]0.652243[/C][/ROW]
[ROW][C]160[/C][C]0.314791[/C][C]0.629582[/C][C]0.685209[/C][/ROW]
[ROW][C]161[/C][C]0.285808[/C][C]0.571616[/C][C]0.714192[/C][/ROW]
[ROW][C]162[/C][C]0.256284[/C][C]0.512568[/C][C]0.743716[/C][/ROW]
[ROW][C]163[/C][C]0.230954[/C][C]0.461908[/C][C]0.769046[/C][/ROW]
[ROW][C]164[/C][C]0.346518[/C][C]0.693036[/C][C]0.653482[/C][/ROW]
[ROW][C]165[/C][C]0.332257[/C][C]0.664515[/C][C]0.667743[/C][/ROW]
[ROW][C]166[/C][C]0.321128[/C][C]0.642255[/C][C]0.678872[/C][/ROW]
[ROW][C]167[/C][C]0.287267[/C][C]0.574535[/C][C]0.712733[/C][/ROW]
[ROW][C]168[/C][C]0.258737[/C][C]0.517474[/C][C]0.741263[/C][/ROW]
[ROW][C]169[/C][C]0.307264[/C][C]0.614528[/C][C]0.692736[/C][/ROW]
[ROW][C]170[/C][C]0.31683[/C][C]0.63366[/C][C]0.68317[/C][/ROW]
[ROW][C]171[/C][C]0.283228[/C][C]0.566456[/C][C]0.716772[/C][/ROW]
[ROW][C]172[/C][C]0.274816[/C][C]0.549631[/C][C]0.725184[/C][/ROW]
[ROW][C]173[/C][C]0.449324[/C][C]0.898648[/C][C]0.550676[/C][/ROW]
[ROW][C]174[/C][C]0.411848[/C][C]0.823696[/C][C]0.588152[/C][/ROW]
[ROW][C]175[/C][C]0.428147[/C][C]0.856294[/C][C]0.571853[/C][/ROW]
[ROW][C]176[/C][C]0.447744[/C][C]0.895488[/C][C]0.552256[/C][/ROW]
[ROW][C]177[/C][C]0.489782[/C][C]0.979564[/C][C]0.510218[/C][/ROW]
[ROW][C]178[/C][C]0.4516[/C][C]0.903199[/C][C]0.5484[/C][/ROW]
[ROW][C]179[/C][C]0.419978[/C][C]0.839955[/C][C]0.580022[/C][/ROW]
[ROW][C]180[/C][C]0.414139[/C][C]0.828279[/C][C]0.585861[/C][/ROW]
[ROW][C]181[/C][C]0.381089[/C][C]0.762178[/C][C]0.618911[/C][/ROW]
[ROW][C]182[/C][C]0.364904[/C][C]0.729807[/C][C]0.635096[/C][/ROW]
[ROW][C]183[/C][C]0.328629[/C][C]0.657259[/C][C]0.671371[/C][/ROW]
[ROW][C]184[/C][C]0.303504[/C][C]0.607008[/C][C]0.696496[/C][/ROW]
[ROW][C]185[/C][C]0.299732[/C][C]0.599464[/C][C]0.700268[/C][/ROW]
[ROW][C]186[/C][C]0.268867[/C][C]0.537733[/C][C]0.731133[/C][/ROW]
[ROW][C]187[/C][C]0.237611[/C][C]0.475222[/C][C]0.762389[/C][/ROW]
[ROW][C]188[/C][C]0.208909[/C][C]0.417817[/C][C]0.791091[/C][/ROW]
[ROW][C]189[/C][C]0.1805[/C][C]0.361[/C][C]0.8195[/C][/ROW]
[ROW][C]190[/C][C]0.157938[/C][C]0.315877[/C][C]0.842062[/C][/ROW]
[ROW][C]191[/C][C]0.178339[/C][C]0.356678[/C][C]0.821661[/C][/ROW]
[ROW][C]192[/C][C]0.159365[/C][C]0.31873[/C][C]0.840635[/C][/ROW]
[ROW][C]193[/C][C]0.166065[/C][C]0.332131[/C][C]0.833935[/C][/ROW]
[ROW][C]194[/C][C]0.147406[/C][C]0.294813[/C][C]0.852594[/C][/ROW]
[ROW][C]195[/C][C]0.142999[/C][C]0.285997[/C][C]0.857001[/C][/ROW]
[ROW][C]196[/C][C]0.149465[/C][C]0.298929[/C][C]0.850535[/C][/ROW]
[ROW][C]197[/C][C]0.17034[/C][C]0.340679[/C][C]0.82966[/C][/ROW]
[ROW][C]198[/C][C]0.143914[/C][C]0.287828[/C][C]0.856086[/C][/ROW]
[ROW][C]199[/C][C]0.162972[/C][C]0.325944[/C][C]0.837028[/C][/ROW]
[ROW][C]200[/C][C]0.140685[/C][C]0.281371[/C][C]0.859315[/C][/ROW]
[ROW][C]201[/C][C]0.173613[/C][C]0.347226[/C][C]0.826387[/C][/ROW]
[ROW][C]202[/C][C]0.15184[/C][C]0.303679[/C][C]0.84816[/C][/ROW]
[ROW][C]203[/C][C]0.165572[/C][C]0.331144[/C][C]0.834428[/C][/ROW]
[ROW][C]204[/C][C]0.138189[/C][C]0.276378[/C][C]0.861811[/C][/ROW]
[ROW][C]205[/C][C]0.115568[/C][C]0.231136[/C][C]0.884432[/C][/ROW]
[ROW][C]206[/C][C]0.114373[/C][C]0.228747[/C][C]0.885627[/C][/ROW]
[ROW][C]207[/C][C]0.0937865[/C][C]0.187573[/C][C]0.906213[/C][/ROW]
[ROW][C]208[/C][C]0.112384[/C][C]0.224768[/C][C]0.887616[/C][/ROW]
[ROW][C]209[/C][C]0.0951229[/C][C]0.190246[/C][C]0.904877[/C][/ROW]
[ROW][C]210[/C][C]0.0847627[/C][C]0.169525[/C][C]0.915237[/C][/ROW]
[ROW][C]211[/C][C]0.0912045[/C][C]0.182409[/C][C]0.908796[/C][/ROW]
[ROW][C]212[/C][C]0.0796714[/C][C]0.159343[/C][C]0.920329[/C][/ROW]
[ROW][C]213[/C][C]0.0639548[/C][C]0.12791[/C][C]0.936045[/C][/ROW]
[ROW][C]214[/C][C]0.114003[/C][C]0.228006[/C][C]0.885997[/C][/ROW]
[ROW][C]215[/C][C]0.103111[/C][C]0.206221[/C][C]0.896889[/C][/ROW]
[ROW][C]216[/C][C]0.0965976[/C][C]0.193195[/C][C]0.903402[/C][/ROW]
[ROW][C]217[/C][C]0.108813[/C][C]0.217626[/C][C]0.891187[/C][/ROW]
[ROW][C]218[/C][C]0.0952243[/C][C]0.190449[/C][C]0.904776[/C][/ROW]
[ROW][C]219[/C][C]0.0951194[/C][C]0.190239[/C][C]0.904881[/C][/ROW]
[ROW][C]220[/C][C]0.0938925[/C][C]0.187785[/C][C]0.906108[/C][/ROW]
[ROW][C]221[/C][C]0.0976827[/C][C]0.195365[/C][C]0.902317[/C][/ROW]
[ROW][C]222[/C][C]0.0946055[/C][C]0.189211[/C][C]0.905394[/C][/ROW]
[ROW][C]223[/C][C]0.11779[/C][C]0.23558[/C][C]0.88221[/C][/ROW]
[ROW][C]224[/C][C]0.0922046[/C][C]0.184409[/C][C]0.907795[/C][/ROW]
[ROW][C]225[/C][C]0.0973293[/C][C]0.194659[/C][C]0.902671[/C][/ROW]
[ROW][C]226[/C][C]0.0821006[/C][C]0.164201[/C][C]0.917899[/C][/ROW]
[ROW][C]227[/C][C]0.343413[/C][C]0.686826[/C][C]0.656587[/C][/ROW]
[ROW][C]228[/C][C]0.310399[/C][C]0.620798[/C][C]0.689601[/C][/ROW]
[ROW][C]229[/C][C]0.270997[/C][C]0.541993[/C][C]0.729003[/C][/ROW]
[ROW][C]230[/C][C]0.222922[/C][C]0.445844[/C][C]0.777078[/C][/ROW]
[ROW][C]231[/C][C]0.175397[/C][C]0.350793[/C][C]0.824603[/C][/ROW]
[ROW][C]232[/C][C]0.18225[/C][C]0.3645[/C][C]0.81775[/C][/ROW]
[ROW][C]233[/C][C]0.141075[/C][C]0.282149[/C][C]0.858925[/C][/ROW]
[ROW][C]234[/C][C]0.114305[/C][C]0.22861[/C][C]0.885695[/C][/ROW]
[ROW][C]235[/C][C]0.0862962[/C][C]0.172592[/C][C]0.913704[/C][/ROW]
[ROW][C]236[/C][C]0.0744709[/C][C]0.148942[/C][C]0.925529[/C][/ROW]
[ROW][C]237[/C][C]0.0590191[/C][C]0.118038[/C][C]0.940981[/C][/ROW]
[ROW][C]238[/C][C]0.0387831[/C][C]0.0775662[/C][C]0.961217[/C][/ROW]
[ROW][C]239[/C][C]0.157307[/C][C]0.314613[/C][C]0.842693[/C][/ROW]
[ROW][C]240[/C][C]0.364593[/C][C]0.729187[/C][C]0.635407[/C][/ROW]
[ROW][C]241[/C][C]0.323414[/C][C]0.646829[/C][C]0.676586[/C][/ROW]
[ROW][C]242[/C][C]0.295663[/C][C]0.591325[/C][C]0.704337[/C][/ROW]
[ROW][C]243[/C][C]0.190596[/C][C]0.381191[/C][C]0.809404[/C][/ROW]
[ROW][C]244[/C][C]0.145959[/C][C]0.291918[/C][C]0.854041[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226642&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226642&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
200.805960.3880790.19404
210.9135240.1729520.0864761
220.8881560.2236880.111844
230.8650060.2699870.134994
240.9627770.07444570.0372228
250.973510.05298070.0264903
260.9997360.0005287550.000264377
270.9995780.0008446530.000422326
280.9993740.001251790.000625897
290.9988660.002267290.00113364
300.9995840.0008327720.000416386
310.9994410.001117450.000558725
320.9990070.001986870.000993436
330.9984840.003031060.00151553
340.9981270.00374650.00187325
350.9969340.006131280.00306564
360.9951830.009633910.00481695
370.9930510.01389850.00694925
380.9916990.01660150.00830075
390.9912550.01749010.00874505
400.9883780.02324390.0116219
410.984680.03064070.0153203
420.9826250.0347510.0173755
430.9761530.04769420.0238471
440.9711920.05761680.0288084
450.9618470.07630610.0381531
460.9582140.08357150.0417857
470.9455950.108810.0544051
480.930630.138740.0693698
490.9731570.0536870.0268435
500.9661430.06771470.0338573
510.9570770.08584560.0429228
520.9512840.0974320.048716
530.9465120.1069760.053488
540.9476250.104750.0523752
550.9419510.1160990.0580493
560.9391990.1216020.0608011
570.929470.141060.07053
580.9179040.1641910.0820957
590.9264110.1471780.0735888
600.9168420.1663160.0831579
610.921430.1571410.0785703
620.9062360.1875280.0937642
630.921070.157860.0789302
640.9151610.1696770.0848387
650.9004740.1990530.0995263
660.9583310.08333840.0416692
670.9509380.0981250.0490625
680.9505940.09881160.0494058
690.9416680.1166640.0583322
700.9482520.1034970.0517483
710.9414180.1171640.0585818
720.954240.091520.04576
730.9508130.09837450.0491872
740.9404810.1190390.0595193
750.9307030.1385940.069297
760.9194970.1610050.0805026
770.9289010.1421970.0710986
780.9192990.1614020.0807008
790.9186510.1626980.0813488
800.9228170.1543660.0771828
810.9083990.1832020.091601
820.8943190.2113610.105681
830.8958790.2082430.104121
840.8795180.2409630.120482
850.8641840.2716320.135816
860.8535730.2928540.146427
870.8300540.3398920.169946
880.804970.3900610.19503
890.8743290.2513420.125671
900.8980540.2038920.101946
910.8807080.2385840.119292
920.8633490.2733020.136651
930.8439330.3121340.156067
940.8249540.3500920.175046
950.808940.382120.19106
960.7860280.4279440.213972
970.7640480.4719050.235952
980.7809080.4381830.219092
990.7521290.4957410.247871
1000.7512250.497550.248775
1010.7293040.5413920.270696
1020.7016650.5966690.298335
1030.7567840.4864310.243216
1040.7465590.5068820.253441
1050.7649260.4701470.235074
1060.7553080.4893840.244692
1070.7467310.5065370.253269
1080.7821870.4356270.217813
1090.7541490.4917030.245851
1100.7384720.5230560.261528
1110.7325050.5349890.267495
1120.7346310.5307370.265369
1130.7102910.5794180.289709
1140.7633940.4732120.236606
1150.7432360.5135280.256764
1160.7119590.5760820.288041
1170.6881790.6236420.311821
1180.6655110.6689770.334489
1190.6332120.7335770.366788
1200.6021580.7956830.397842
1210.5799440.8401130.420056
1220.5454130.9091740.454587
1230.5127510.9744980.487249
1240.4822330.9644650.517767
1250.4755290.9510590.524471
1260.4432410.8864830.556759
1270.4260580.8521160.573942
1280.5224610.9550780.477539
1290.5069390.9861220.493061
1300.4961620.9923240.503838
1310.4837330.9674650.516267
1320.4468650.893730.553135
1330.4567930.9135850.543207
1340.4274510.8549020.572549
1350.4673260.9346530.532674
1360.4543150.9086310.545685
1370.4203580.8407160.579642
1380.4248040.8496080.575196
1390.3909090.7818170.609091
1400.3702750.7405490.629725
1410.3399320.6798650.660068
1420.3623790.7247580.637621
1430.3305170.6610350.669483
1440.3073550.614710.692645
1450.2962520.5925030.703748
1460.2864180.5728360.713582
1470.2998940.5997870.700106
1480.3255820.6511640.674418
1490.336640.6732810.66336
1500.3175660.6351310.682434
1510.2883270.5766540.711673
1520.2569260.5138520.743074
1530.2604110.5208210.739589
1540.2711420.5422830.728858
1550.2534150.506830.746585
1560.223950.4479010.77605
1570.200770.401540.79923
1580.3380.6759990.662
1590.3477570.6955150.652243
1600.3147910.6295820.685209
1610.2858080.5716160.714192
1620.2562840.5125680.743716
1630.2309540.4619080.769046
1640.3465180.6930360.653482
1650.3322570.6645150.667743
1660.3211280.6422550.678872
1670.2872670.5745350.712733
1680.2587370.5174740.741263
1690.3072640.6145280.692736
1700.316830.633660.68317
1710.2832280.5664560.716772
1720.2748160.5496310.725184
1730.4493240.8986480.550676
1740.4118480.8236960.588152
1750.4281470.8562940.571853
1760.4477440.8954880.552256
1770.4897820.9795640.510218
1780.45160.9031990.5484
1790.4199780.8399550.580022
1800.4141390.8282790.585861
1810.3810890.7621780.618911
1820.3649040.7298070.635096
1830.3286290.6572590.671371
1840.3035040.6070080.696496
1850.2997320.5994640.700268
1860.2688670.5377330.731133
1870.2376110.4752220.762389
1880.2089090.4178170.791091
1890.18050.3610.8195
1900.1579380.3158770.842062
1910.1783390.3566780.821661
1920.1593650.318730.840635
1930.1660650.3321310.833935
1940.1474060.2948130.852594
1950.1429990.2859970.857001
1960.1494650.2989290.850535
1970.170340.3406790.82966
1980.1439140.2878280.856086
1990.1629720.3259440.837028
2000.1406850.2813710.859315
2010.1736130.3472260.826387
2020.151840.3036790.84816
2030.1655720.3311440.834428
2040.1381890.2763780.861811
2050.1155680.2311360.884432
2060.1143730.2287470.885627
2070.09378650.1875730.906213
2080.1123840.2247680.887616
2090.09512290.1902460.904877
2100.08476270.1695250.915237
2110.09120450.1824090.908796
2120.07967140.1593430.920329
2130.06395480.127910.936045
2140.1140030.2280060.885997
2150.1031110.2062210.896889
2160.09659760.1931950.903402
2170.1088130.2176260.891187
2180.09522430.1904490.904776
2190.09511940.1902390.904881
2200.09389250.1877850.906108
2210.09768270.1953650.902317
2220.09460550.1892110.905394
2230.117790.235580.88221
2240.09220460.1844090.907795
2250.09732930.1946590.902671
2260.08210060.1642010.917899
2270.3434130.6868260.656587
2280.3103990.6207980.689601
2290.2709970.5419930.729003
2300.2229220.4458440.777078
2310.1753970.3507930.824603
2320.182250.36450.81775
2330.1410750.2821490.858925
2340.1143050.228610.885695
2350.08629620.1725920.913704
2360.07447090.1489420.925529
2370.05901910.1180380.940981
2380.03878310.07756620.961217
2390.1573070.3146130.842693
2400.3645930.7291870.635407
2410.3234140.6468290.676586
2420.2956630.5913250.704337
2430.1905960.3811910.809404
2440.1459590.2919180.854041






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level110.0488889NOK
5% type I error level180.08NOK
10% type I error level330.146667NOK

\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 & 11 & 0.0488889 & NOK \tabularnewline
5% type I error level & 18 & 0.08 & NOK \tabularnewline
10% type I error level & 33 & 0.146667 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226642&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]11[/C][C]0.0488889[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]18[/C][C]0.08[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]33[/C][C]0.146667[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226642&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226642&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level110.0488889NOK
5% type I error level180.08NOK
10% type I error level330.146667NOK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}