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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 computationFri, 01 Nov 2013 14:33:47 -0400
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/01/t1383330862j1x496avfei46so.htm/, Retrieved Sun, 28 Apr 2024 22:52:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221698, Retrieved Sun, 28 Apr 2024 22:52:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact58

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2013-11-01 18:33:47] [0147fd68123b42babc023061627c5370] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 13 12 14 12 9
39 32 16 11 18 11 9
30 35 19 15 11 14 9
31 33 15 6 12 12 9
34 37 14 13 16 21 9
35 29 13 10 18 12 9
39 31 19 12 14 22 9
34 36 15 14 14 11 9
36 35 14 12 15 10 9
37 38 15 9 15 13 9
38 31 16 10 17 10 9
36 34 16 12 19 8 9
38 35 16 12 10 15 9
39 38 16 11 16 14 9
33 37 17 15 18 10 9
32 33 15 12 14 14 9
36 32 15 10 14 14 9
38 38 20 12 17 11 9
39 38 18 11 14 10 9
32 32 16 12 16 13 9
32 33 16 11 18 9.5 9
31 31 16 12 11 14 9
39 38 19 13 14 12 9
37 39 16 11 12 14 9
39 32 17 12 17 11 9
41 32 17 13 9 9 9
36 35 16 10 16 11 9
33 37 15 14 14 15 9
33 33 16 12 15 14 9
34 33 14 10 11 13 9
31 31 15 12 16 9 9
27 32 12 8 13 15 9
37 31 14 10 17 10 9
34 37 16 12 15 11 9
34 30 14 12 14 13 9
32 33 10 7 16 8 9
29 31 10 9 9 20 9
36 33 14 12 15 12 9
29 31 16 10 17 10 9
35 33 16 10 13 10 9
37 32 16 10 15 9 9
34 33 14 12 16 14 9
38 32 20 15 16 8 9
35 33 14 10 12 14 9
38 28 14 10 15 11 9
37 35 11 12 11 13 9
38 39 14 13 15 9 9
33 34 15 11 15 11 9
36 38 16 11 17 15 9
38 32 14 12 13 11 9
32 38 16 14 16 10 9
32 30 14 10 14 14 9
32 33 12 12 11 18 9
34 38 16 13 12 14 9
32 32 9 5 12 11 9
37 35 14 6 15 14.5 9
39 34 16 12 16 13 9
29 34 16 12 15 9 9
37 36 15 11 12 10 9
35 34 16 10 12 15 9
30 28 12 7 8 20 9
38 34 16 12 13 12 9
34 35 16 14 11 12 9
31 35 14 11 14 14 9
34 31 16 12 15 13 9
35 37 17 13 10 11 10
36 35 18 14 11 17 10
30 27 18 11 12 12 10
39 40 12 12 15 13 10
35 37 16 12 15 14 10
38 36 10 8 14 13 10
31 38 14 11 16 15 10
34 39 18 14 15 13 10
38 41 18 14 15 10 10
34 27 16 12 13 11 10
39 30 17 9 12 19 10
37 37 16 13 17 13 10
34 31 16 11 13 17 10
28 31 13 12 15 13 10
37 27 16 12 13 9 10
33 36 16 12 15 11 10
35 37 16 12 15 9 10
37 33 15 12 16 12 10
32 34 15 11 15 12 10
33 31 16 10 14 13 10
38 39 14 9 15 13 10
33 34 16 12 14 12 10
29 32 16 12 13 15 10
33 33 15 12 7 22 10
31 36 12 9 17 13 10
36 32 17 15 13 15 10
35 41 16 12 15 13 10
32 28 15 12 14 15 10
29 30 13 12 13 12.5 10
39 36 16 10 16 11 10
37 35 16 13 12 16 10
35 31 16 9 14 11 10
37 34 16 12 17 11 10
32 36 14 10 15 10 10
38 36 16 14 17 10 10
37 35 16 11 12 16 10
36 37 20 15 16 12 10
32 28 15 11 11 11 10
33 39 16 11 15 16 10
40 32 13 12 9 19 10
38 35 17 12 16 11 10
41 39 16 12 15 16 10
36 35 16 11 10 15 10
43 42 12 7 10 24 10
30 34 16 12 15 14 10
31 33 16 14 11 15 10
32 41 17 11 13 11 10
32 33 13 11 14 15 10
37 34 12 10 18 12 10
37 32 18 13 16 10 10
33 40 14 13 14 14 10
34 40 14 8 14 13 10
33 35 13 11 14 9 10
38 36 16 12 14 15 10
33 37 13 11 12 15 10
31 27 16 13 14 14 10
38 39 13 12 15 11 10
37 38 16 14 15 8 10
36 31 15 13 15 11 10
31 33 16 15 13 11 10
39 32 15 10 17 8 10
44 39 17 11 17 10 10
33 36 15 9 19 11 10
35 33 12 11 15 13 10
32 33 16 10 13 11 10
28 32 10 11 9 20 10
40 37 16 8 15 10 10
27 30 12 11 15 15 10
37 38 14 12 15 12 10
32 29 15 12 16 14 10
28 22 13 9 11 23 10
34 35 15 11 14 14 10
30 35 11 10 11 16 10
35 34 12 8 15 11 10
31 35 11 9 13 12 10
32 34 16 8 15 10 10
30 37 15 9 16 14 10
30 35 17 15 14 12 10
31 23 16 11 15 12 10
40 31 10 8 16 11 10
32 27 18 13 16 12 10
36 36 13 12 11 13 10
32 31 16 12 12 11 10
35 32 13 9 9 19 10
38 39 10 7 16 12 10
42 37 15 13 13 17 10
34 38 16 9 16 9 10
35 39 16 6 12 12 10
38 34 14 8 9 19 9
33 31 10 8 13 18 10
36 32 17 15 13 15 10
32 37 13 6 14 14 10
33 36 15 9 19 11 10
34 32 16 11 13 9 10
32 38 12 8 12 18 10
34 36 13 8 13 16 10
27 26 13 10 10 24 11
31 26 12 8 14 14 11
38 33 17 14 16 20 11
34 39 15 10 10 18 11
24 30 10 8 11 23 11
30 33 14 11 14 12 11
26 25 11 12 12 14 11
34 38 13 12 9 16 11
27 37 16 12 9 18 11
37 31 12 5 11 20 11
36 37 16 12 16 12 11
41 35 12 10 9 12 11
29 25 9 7 13 17 11
36 28 12 12 16 13 11
32 35 15 11 13 9 11
37 33 12 8 9 16 11
30 30 12 9 12 18 11
31 31 14 10 16 10 11
38 37 12 9 11 14 11
36 36 16 12 14 11 11
35 30 11 6 13 9 11
31 36 19 15 15 11 11
38 32 15 12 14 10 11
22 28 8 12 16 11 11
32 36 16 12 13 19 11
36 34 17 11 14 14 11
39 31 12 7 15 12 11
28 28 11 7 13 14 11
32 36 11 5 11 21 11
32 36 14 12 11 13 11
38 40 16 12 14 10 11
32 33 12 3 15 15 11
35 37 16 11 11 16 11
32 32 13 10 15 14 11
37 38 15 12 12 12 11
34 31 16 9 14 19 11
33 37 16 12 14 15 11
33 33 14 9 8 19 11
26 32 16 12 13 13 11
30 30 16 12 9 17 11
24 30 14 10 15 12 11
34 31 11 9 17 11 11
34 32 12 12 13 14 11
33 34 15 8 15 11 11
34 36 15 11 15 13 11
35 37 16 11 14 12 11
35 36 16 12 16 15 11
36 33 11 10 13 14 11
34 33 15 10 16 12 11
34 33 12 12 9 17 11
41 44 12 12 16 11 11
32 39 15 11 11 18 11
30 32 15 8 10 13 11
35 35 16 12 11 17 11
28 25 14 10 15 13 11
33 35 17 11 17 11 11
39 34 14 10 14 12 11
36 35 13 8 8 22 11
36 39 15 12 15 14 11
35 33 13 12 11 12 11
38 36 14 10 16 12 11
33 32 15 12 10 17 11
31 32 12 9 15 9 11
34 36 13 9 9 21 11
32 36 8 6 16 10 11
31 32 14 10 19 11 11
33 34 14 9 12 12 11
34 33 11 9 8 23 11
34 35 12 9 11 13 11
34 30 13 6 14 12 11
33 38 10 10 9 16 11
32 34 16 6 15 9 11
41 33 18 14 13 17 11
34 32 13 10 16 9 11
36 31 11 10 11 14 11
37 30 4 6 12 17 11
36 27 13 12 13 13 11
29 31 16 12 10 11 11
37 30 10 7 11 12 11
27 32 12 8 12 10 11
35 35 12 11 8 19 11
28 28 10 3 12 16 11
35 33 13 6 12 16 11
37 31 15 10 15 14 11
29 35 12 8 11 20 11
32 35 14 9 13 15 11
36 32 10 9 14 23 11
19 21 12 8 10 20 11
21 20 12 9 12 16 11
31 34 11 7 15 14 11
33 32 10 7 13 17 11
36 34 12 6 13 11 11
33 32 16 9 13 13 11
37 33 12 10 12 17 11
34 33 14 11 12 15 11
35 37 16 12 9 21 11
31 32 14 8 9 18 11
37 34 13 11 15 15 11
35 30 4 3 10 8 11
27 30 15 11 14 12 11
34 38 11 12 15 12 11
40 36 11 7 7 22 11
29 32 14 9 14 12 11

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time18 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 18 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221698&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]18 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221698&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221698&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 time18 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Software[t] = + 4.61109 -0.0173093Connected[t] + 0.0389883Separate[t] + 0.556295Learning[t] -0.0126553Happiness[t] -0.00944437Depression[t] -0.240347Month[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Software[t] =  +  4.61109 -0.0173093Connected[t] +  0.0389883Separate[t] +  0.556295Learning[t] -0.0126553Happiness[t] -0.00944437Depression[t] -0.240347Month[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221698&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Software[t] =  +  4.61109 -0.0173093Connected[t] +  0.0389883Separate[t] +  0.556295Learning[t] -0.0126553Happiness[t] -0.00944437Depression[t] -0.240347Month[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221698&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221698&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
Software[t] = + 4.61109 -0.0173093Connected[t] + 0.0389883Separate[t] + 0.556295Learning[t] -0.0126553Happiness[t] -0.00944437Depression[t] -0.240347Month[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.611092.547281.810.07143220.0357161
Connected-0.01730930.0338269-0.51170.6092990.30465
Separate0.03898830.03446691.1310.2590340.129517
Learning0.5562950.050270311.071.55781e-237.78907e-24
Happiness-0.01265530.0562507-0.2250.8221740.411087
Depression-0.009444370.0402785-0.23450.8148010.407401
Month-0.2403470.154841-1.5520.121840.0609199

\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) & 4.61109 & 2.54728 & 1.81 & 0.0714322 & 0.0357161 \tabularnewline
Connected & -0.0173093 & 0.0338269 & -0.5117 & 0.609299 & 0.30465 \tabularnewline
Separate & 0.0389883 & 0.0344669 & 1.131 & 0.259034 & 0.129517 \tabularnewline
Learning & 0.556295 & 0.0502703 & 11.07 & 1.55781e-23 & 7.78907e-24 \tabularnewline
Happiness & -0.0126553 & 0.0562507 & -0.225 & 0.822174 & 0.411087 \tabularnewline
Depression & -0.00944437 & 0.0402785 & -0.2345 & 0.814801 & 0.407401 \tabularnewline
Month & -0.240347 & 0.154841 & -1.552 & 0.12184 & 0.0609199 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221698&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]4.61109[/C][C]2.54728[/C][C]1.81[/C][C]0.0714322[/C][C]0.0357161[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0173093[/C][C]0.0338269[/C][C]-0.5117[/C][C]0.609299[/C][C]0.30465[/C][/ROW]
[ROW][C]Separate[/C][C]0.0389883[/C][C]0.0344669[/C][C]1.131[/C][C]0.259034[/C][C]0.129517[/C][/ROW]
[ROW][C]Learning[/C][C]0.556295[/C][C]0.0502703[/C][C]11.07[/C][C]1.55781e-23[/C][C]7.78907e-24[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.0126553[/C][C]0.0562507[/C][C]-0.225[/C][C]0.822174[/C][C]0.411087[/C][/ROW]
[ROW][C]Depression[/C][C]-0.00944437[/C][C]0.0402785[/C][C]-0.2345[/C][C]0.814801[/C][C]0.407401[/C][/ROW]
[ROW][C]Month[/C][C]-0.240347[/C][C]0.154841[/C][C]-1.552[/C][C]0.12184[/C][C]0.0609199[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221698&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221698&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)4.611092.547281.810.07143220.0357161
Connected-0.01730930.0338269-0.51170.6092990.30465
Separate0.03898830.03446691.1310.2590340.129517
Learning0.5562950.050270311.071.55781e-237.78907e-24
Happiness-0.01265530.0562507-0.2250.8221740.411087
Depression-0.009444370.0402785-0.23450.8148010.407401
Month-0.2403470.154841-1.5520.121840.0609199






Multiple Linear Regression - Regression Statistics
Multiple R0.630575
R-squared0.397624
Adjusted R-squared0.383561
F-TEST (value)28.274
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.82155
Sum Squared Residuals852.736

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.630575 \tabularnewline
R-squared & 0.397624 \tabularnewline
Adjusted R-squared & 0.383561 \tabularnewline
F-TEST (value) & 28.274 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 257 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.82155 \tabularnewline
Sum Squared Residuals & 852.736 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221698&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.630575[/C][/ROW]
[ROW][C]R-squared[/C][C]0.397624[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.383561[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]28.274[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]257[/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]1.82155[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]852.736[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221698&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221698&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 R0.630575
R-squared0.397624
Adjusted R-squared0.383561
F-TEST (value)28.274
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.82155
Sum Squared Residuals852.736






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.16121.83884
21111.5896-0.589561
31513.59141.40855
4611.2772-5.27722
51310.68932.31067
6109.86350.136496
71213.1662-1.16619
81411.32642.67361
91210.69331.30673
10911.3209-2.32089
111011.59-1.58998
121211.73510.264856
131211.78730.2127
141111.8205-0.820469
151512.45412.5459
161211.21570.784293
171011.1075-1.10748
181214.0786-2.07864
191112.9961-1.99615
201211.71710.282852
211111.7639-0.763881
221211.74930.250699
231313.5336-0.533553
241111.9447-0.944696
251212.1585-0.158512
261312.2440.755976
271011.7838-1.78376
281411.34492.65509
291211.7420.257962
301010.6722-0.672204
311211.1770.823048
3289.59759-1.59759
331010.4947-0.494701
341211.9090.0909849
351210.51731.48273
3678.46559-1.46559
3798.414790.585207
381210.59641.40359
391011.7458-1.74577
401011.7705-1.77051
411011.681-1.68103
421210.59951.40052
431513.88571.11431
441010.6328-0.632795
451010.3763-0.376293
46129.029372.97063
471310.82412.17595
481111.2531-0.253064
491111.8503-0.850297
501210.55761.44244
511411.97942.02059
521010.5424-0.542448
53129.547012.45299
541311.95761.04236
5557.89259-2.89259
56610.6335-4.63347
571211.6740.32604
581211.89750.102515
591111.3092-0.309214
601011.7749-1.77493
6179.40576-2.40576
621211.73870.261321
631411.87222.12778
641110.75470.245302
651211.65620.343803
661312.27090.72907
671412.66261.33738
681112.4891-1.48913
69129.455022.54498
701211.6230.376975
7188.21644-0.216438
721110.59660.403439
731412.84031.15965
741412.87741.12258
751211.30410.695905
76911.8279-2.82791
771311.57251.42746
781111.4034-0.403382
79129.850822.14918
801211.27110.728944
811211.6470.353011
821211.67020.329753
831210.88241.11761
841111.0206-0.020582
851011.4458-1.44581
86910.5459-1.54593
871211.57220.427777
881211.54780.452194
891210.97111.02892
9099.41223-0.412228
911511.98293.01706
921211.78840.211577
931210.7711.22903
94129.824552.17545
951011.5305-1.53048
961311.52951.47049
97911.4301-2.43008
981211.47450.525536
991010.5612-0.561152
1001411.54462.45542
1011111.5295-0.529507
1021513.83711.16287
1031110.84670.153282
1041111.7167-0.716732
105129.701362.29864
1061212.0651-0.0650938
1071211.57830.421743
1081111.5816-0.581571
10979.42314-2.42314
1101211.59260.407393
1111411.57752.42251
1121112.4408-1.44085
113119.853331.14667
114109.227180.772815
1151312.53120.468822
1161310.67472.32533
117810.6668-2.66681
118119.970661.02934
1191211.53530.46468
1201110.01730.98272
1211311.3151.68497
1221210.00851.99148
1231411.68412.31594
1241310.84382.15618
1251511.593.41005
1261010.8339-0.833907
1271112.114-1.11398
128911.0401-2.04007
129119.251341.74866
1301011.5726-1.57264
131118.230742.76926
132811.5743-3.57426
133119.253961.74604
1341210.53371.46631
1351210.79411.2059
13699.4561-0.456102
1371111.0187-0.0187182
138108.881851.11815
13989.30921-1.30921
14098.877010.12299
141811.5958-3.59577
142911.1406-2.14062
1431512.21942.78057
1441111.1653-0.165315
14587.980460.0195435
1461312.40390.596106
147129.957912.04209
1481211.50730.492678
14999.78791-0.787908
15078.31754-1.31754
1511310.94252.05746
152911.7139-2.71389
153611.7579-5.75786
154810.6106-2.6106
15588.07348-0.0734766
1561511.98293.01706
157610.0187-4.01872
158911.0401-2.04007
1591111.5179-0.517926
16089.48895-1.48895
16189.93888-1.93888
162109.392230.607772
16388.81052-0.810519
1641411.66182.33823
1651010.9472-0.947168
16687.928010.0719867
1671110.23220.767775
168128.327093.67291
169129.827132.17287
1701211.55930.440694
17158.8829-3.8829
1721211.37160.628398
173109.070490.929514
17477.12159-0.121586
175128.786083.21392
1761110.87290.127133
17789.02397-1.02397
17898.971310.0286857
1791010.1305-0.130517
18099.15619-0.156191
1811211.36740.632631
18268.40082-2.40082
1831513.11011.88985
1841210.62991.37005
185126.822125.17788
1861211.37370.626294
1871111.8174-0.817354
18878.87322-1.87322
18978.39678-1.39678
19058.59865-3.59865
1911210.34311.65691
1921211.49810.501852
19339.04403-6.04403
1941111.4144-0.41441
195109.570780.429221
1961210.88761.11239
197911.1315-2.13149
1981211.42050.579492
199910.1901-1.19012
2001211.37830.621725
2011211.24390.756095
2021010.2065-0.206461
20398.38760.612395
204129.005182.99482
205810.7724-2.77237
2061110.81410.185852
2071111.4142-0.414222
2081211.32160.67841
209108.453251.54675
2101010.694-0.693973
211129.066452.93355
212129.342242.65776
2131110.96910.0308691
214810.7907-2.79071
2151211.3270.673011
216109.932840.0671623
2171111.8986-0.898638
2181010.1154-0.11543
21989.63154-1.63154
2201210.88711.11295
221129.627352.37265
2221010.1854-0.185405
2231210.7011.299
22499.07902-0.0790152
22599.70193-0.701935
22666.97038-0.970379
2271010.1221-0.122096
228910.2446-1.2446
22998.466150.533854
23099.1569-0.156896
23169.48973-3.48973
232108.175561.82444
233611.3649-5.36486
2341412.23241.76756
235109.570730.429273
236108.400581.59942
23764.409231.59077
238129.341362.65864
2391211.34420.655787
24077.80688-0.806881
24189.17677-1.17677
242119.120891.87911
24337.83425-4.83425
24469.57692-3.57692
2451010.5578-0.557835
24689.17733-1.17733
247910.2599-1.25991
24897.760311.23969
24988.81724-0.817244
25098.75610.243896
25178.55347-1.55347
25277.88156-0.881562
25369.07687-3.07687
254911.2571-2.25711
255108.976561.02344
2561110.160.840035
2571211.39250.607501
258810.1825-2.18254
259119.552761.44724
26034.55416-1.55416
2611110.72350.276517
262128.676393.32361
26378.50135-1.50135
264910.2105-1.21055

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 10.1612 & 1.83884 \tabularnewline
2 & 11 & 11.5896 & -0.589561 \tabularnewline
3 & 15 & 13.5914 & 1.40855 \tabularnewline
4 & 6 & 11.2772 & -5.27722 \tabularnewline
5 & 13 & 10.6893 & 2.31067 \tabularnewline
6 & 10 & 9.8635 & 0.136496 \tabularnewline
7 & 12 & 13.1662 & -1.16619 \tabularnewline
8 & 14 & 11.3264 & 2.67361 \tabularnewline
9 & 12 & 10.6933 & 1.30673 \tabularnewline
10 & 9 & 11.3209 & -2.32089 \tabularnewline
11 & 10 & 11.59 & -1.58998 \tabularnewline
12 & 12 & 11.7351 & 0.264856 \tabularnewline
13 & 12 & 11.7873 & 0.2127 \tabularnewline
14 & 11 & 11.8205 & -0.820469 \tabularnewline
15 & 15 & 12.4541 & 2.5459 \tabularnewline
16 & 12 & 11.2157 & 0.784293 \tabularnewline
17 & 10 & 11.1075 & -1.10748 \tabularnewline
18 & 12 & 14.0786 & -2.07864 \tabularnewline
19 & 11 & 12.9961 & -1.99615 \tabularnewline
20 & 12 & 11.7171 & 0.282852 \tabularnewline
21 & 11 & 11.7639 & -0.763881 \tabularnewline
22 & 12 & 11.7493 & 0.250699 \tabularnewline
23 & 13 & 13.5336 & -0.533553 \tabularnewline
24 & 11 & 11.9447 & -0.944696 \tabularnewline
25 & 12 & 12.1585 & -0.158512 \tabularnewline
26 & 13 & 12.244 & 0.755976 \tabularnewline
27 & 10 & 11.7838 & -1.78376 \tabularnewline
28 & 14 & 11.3449 & 2.65509 \tabularnewline
29 & 12 & 11.742 & 0.257962 \tabularnewline
30 & 10 & 10.6722 & -0.672204 \tabularnewline
31 & 12 & 11.177 & 0.823048 \tabularnewline
32 & 8 & 9.59759 & -1.59759 \tabularnewline
33 & 10 & 10.4947 & -0.494701 \tabularnewline
34 & 12 & 11.909 & 0.0909849 \tabularnewline
35 & 12 & 10.5173 & 1.48273 \tabularnewline
36 & 7 & 8.46559 & -1.46559 \tabularnewline
37 & 9 & 8.41479 & 0.585207 \tabularnewline
38 & 12 & 10.5964 & 1.40359 \tabularnewline
39 & 10 & 11.7458 & -1.74577 \tabularnewline
40 & 10 & 11.7705 & -1.77051 \tabularnewline
41 & 10 & 11.681 & -1.68103 \tabularnewline
42 & 12 & 10.5995 & 1.40052 \tabularnewline
43 & 15 & 13.8857 & 1.11431 \tabularnewline
44 & 10 & 10.6328 & -0.632795 \tabularnewline
45 & 10 & 10.3763 & -0.376293 \tabularnewline
46 & 12 & 9.02937 & 2.97063 \tabularnewline
47 & 13 & 10.8241 & 2.17595 \tabularnewline
48 & 11 & 11.2531 & -0.253064 \tabularnewline
49 & 11 & 11.8503 & -0.850297 \tabularnewline
50 & 12 & 10.5576 & 1.44244 \tabularnewline
51 & 14 & 11.9794 & 2.02059 \tabularnewline
52 & 10 & 10.5424 & -0.542448 \tabularnewline
53 & 12 & 9.54701 & 2.45299 \tabularnewline
54 & 13 & 11.9576 & 1.04236 \tabularnewline
55 & 5 & 7.89259 & -2.89259 \tabularnewline
56 & 6 & 10.6335 & -4.63347 \tabularnewline
57 & 12 & 11.674 & 0.32604 \tabularnewline
58 & 12 & 11.8975 & 0.102515 \tabularnewline
59 & 11 & 11.3092 & -0.309214 \tabularnewline
60 & 10 & 11.7749 & -1.77493 \tabularnewline
61 & 7 & 9.40576 & -2.40576 \tabularnewline
62 & 12 & 11.7387 & 0.261321 \tabularnewline
63 & 14 & 11.8722 & 2.12778 \tabularnewline
64 & 11 & 10.7547 & 0.245302 \tabularnewline
65 & 12 & 11.6562 & 0.343803 \tabularnewline
66 & 13 & 12.2709 & 0.72907 \tabularnewline
67 & 14 & 12.6626 & 1.33738 \tabularnewline
68 & 11 & 12.4891 & -1.48913 \tabularnewline
69 & 12 & 9.45502 & 2.54498 \tabularnewline
70 & 12 & 11.623 & 0.376975 \tabularnewline
71 & 8 & 8.21644 & -0.216438 \tabularnewline
72 & 11 & 10.5966 & 0.403439 \tabularnewline
73 & 14 & 12.8403 & 1.15965 \tabularnewline
74 & 14 & 12.8774 & 1.12258 \tabularnewline
75 & 12 & 11.3041 & 0.695905 \tabularnewline
76 & 9 & 11.8279 & -2.82791 \tabularnewline
77 & 13 & 11.5725 & 1.42746 \tabularnewline
78 & 11 & 11.4034 & -0.403382 \tabularnewline
79 & 12 & 9.85082 & 2.14918 \tabularnewline
80 & 12 & 11.2711 & 0.728944 \tabularnewline
81 & 12 & 11.647 & 0.353011 \tabularnewline
82 & 12 & 11.6702 & 0.329753 \tabularnewline
83 & 12 & 10.8824 & 1.11761 \tabularnewline
84 & 11 & 11.0206 & -0.020582 \tabularnewline
85 & 10 & 11.4458 & -1.44581 \tabularnewline
86 & 9 & 10.5459 & -1.54593 \tabularnewline
87 & 12 & 11.5722 & 0.427777 \tabularnewline
88 & 12 & 11.5478 & 0.452194 \tabularnewline
89 & 12 & 10.9711 & 1.02892 \tabularnewline
90 & 9 & 9.41223 & -0.412228 \tabularnewline
91 & 15 & 11.9829 & 3.01706 \tabularnewline
92 & 12 & 11.7884 & 0.211577 \tabularnewline
93 & 12 & 10.771 & 1.22903 \tabularnewline
94 & 12 & 9.82455 & 2.17545 \tabularnewline
95 & 10 & 11.5305 & -1.53048 \tabularnewline
96 & 13 & 11.5295 & 1.47049 \tabularnewline
97 & 9 & 11.4301 & -2.43008 \tabularnewline
98 & 12 & 11.4745 & 0.525536 \tabularnewline
99 & 10 & 10.5612 & -0.561152 \tabularnewline
100 & 14 & 11.5446 & 2.45542 \tabularnewline
101 & 11 & 11.5295 & -0.529507 \tabularnewline
102 & 15 & 13.8371 & 1.16287 \tabularnewline
103 & 11 & 10.8467 & 0.153282 \tabularnewline
104 & 11 & 11.7167 & -0.716732 \tabularnewline
105 & 12 & 9.70136 & 2.29864 \tabularnewline
106 & 12 & 12.0651 & -0.0650938 \tabularnewline
107 & 12 & 11.5783 & 0.421743 \tabularnewline
108 & 11 & 11.5816 & -0.581571 \tabularnewline
109 & 7 & 9.42314 & -2.42314 \tabularnewline
110 & 12 & 11.5926 & 0.407393 \tabularnewline
111 & 14 & 11.5775 & 2.42251 \tabularnewline
112 & 11 & 12.4408 & -1.44085 \tabularnewline
113 & 11 & 9.85333 & 1.14667 \tabularnewline
114 & 10 & 9.22718 & 0.772815 \tabularnewline
115 & 13 & 12.5312 & 0.468822 \tabularnewline
116 & 13 & 10.6747 & 2.32533 \tabularnewline
117 & 8 & 10.6668 & -2.66681 \tabularnewline
118 & 11 & 9.97066 & 1.02934 \tabularnewline
119 & 12 & 11.5353 & 0.46468 \tabularnewline
120 & 11 & 10.0173 & 0.98272 \tabularnewline
121 & 13 & 11.315 & 1.68497 \tabularnewline
122 & 12 & 10.0085 & 1.99148 \tabularnewline
123 & 14 & 11.6841 & 2.31594 \tabularnewline
124 & 13 & 10.8438 & 2.15618 \tabularnewline
125 & 15 & 11.59 & 3.41005 \tabularnewline
126 & 10 & 10.8339 & -0.833907 \tabularnewline
127 & 11 & 12.114 & -1.11398 \tabularnewline
128 & 9 & 11.0401 & -2.04007 \tabularnewline
129 & 11 & 9.25134 & 1.74866 \tabularnewline
130 & 10 & 11.5726 & -1.57264 \tabularnewline
131 & 11 & 8.23074 & 2.76926 \tabularnewline
132 & 8 & 11.5743 & -3.57426 \tabularnewline
133 & 11 & 9.25396 & 1.74604 \tabularnewline
134 & 12 & 10.5337 & 1.46631 \tabularnewline
135 & 12 & 10.7941 & 1.2059 \tabularnewline
136 & 9 & 9.4561 & -0.456102 \tabularnewline
137 & 11 & 11.0187 & -0.0187182 \tabularnewline
138 & 10 & 8.88185 & 1.11815 \tabularnewline
139 & 8 & 9.30921 & -1.30921 \tabularnewline
140 & 9 & 8.87701 & 0.12299 \tabularnewline
141 & 8 & 11.5958 & -3.59577 \tabularnewline
142 & 9 & 11.1406 & -2.14062 \tabularnewline
143 & 15 & 12.2194 & 2.78057 \tabularnewline
144 & 11 & 11.1653 & -0.165315 \tabularnewline
145 & 8 & 7.98046 & 0.0195435 \tabularnewline
146 & 13 & 12.4039 & 0.596106 \tabularnewline
147 & 12 & 9.95791 & 2.04209 \tabularnewline
148 & 12 & 11.5073 & 0.492678 \tabularnewline
149 & 9 & 9.78791 & -0.787908 \tabularnewline
150 & 7 & 8.31754 & -1.31754 \tabularnewline
151 & 13 & 10.9425 & 2.05746 \tabularnewline
152 & 9 & 11.7139 & -2.71389 \tabularnewline
153 & 6 & 11.7579 & -5.75786 \tabularnewline
154 & 8 & 10.6106 & -2.6106 \tabularnewline
155 & 8 & 8.07348 & -0.0734766 \tabularnewline
156 & 15 & 11.9829 & 3.01706 \tabularnewline
157 & 6 & 10.0187 & -4.01872 \tabularnewline
158 & 9 & 11.0401 & -2.04007 \tabularnewline
159 & 11 & 11.5179 & -0.517926 \tabularnewline
160 & 8 & 9.48895 & -1.48895 \tabularnewline
161 & 8 & 9.93888 & -1.93888 \tabularnewline
162 & 10 & 9.39223 & 0.607772 \tabularnewline
163 & 8 & 8.81052 & -0.810519 \tabularnewline
164 & 14 & 11.6618 & 2.33823 \tabularnewline
165 & 10 & 10.9472 & -0.947168 \tabularnewline
166 & 8 & 7.92801 & 0.0719867 \tabularnewline
167 & 11 & 10.2322 & 0.767775 \tabularnewline
168 & 12 & 8.32709 & 3.67291 \tabularnewline
169 & 12 & 9.82713 & 2.17287 \tabularnewline
170 & 12 & 11.5593 & 0.440694 \tabularnewline
171 & 5 & 8.8829 & -3.8829 \tabularnewline
172 & 12 & 11.3716 & 0.628398 \tabularnewline
173 & 10 & 9.07049 & 0.929514 \tabularnewline
174 & 7 & 7.12159 & -0.121586 \tabularnewline
175 & 12 & 8.78608 & 3.21392 \tabularnewline
176 & 11 & 10.8729 & 0.127133 \tabularnewline
177 & 8 & 9.02397 & -1.02397 \tabularnewline
178 & 9 & 8.97131 & 0.0286857 \tabularnewline
179 & 10 & 10.1305 & -0.130517 \tabularnewline
180 & 9 & 9.15619 & -0.156191 \tabularnewline
181 & 12 & 11.3674 & 0.632631 \tabularnewline
182 & 6 & 8.40082 & -2.40082 \tabularnewline
183 & 15 & 13.1101 & 1.88985 \tabularnewline
184 & 12 & 10.6299 & 1.37005 \tabularnewline
185 & 12 & 6.82212 & 5.17788 \tabularnewline
186 & 12 & 11.3737 & 0.626294 \tabularnewline
187 & 11 & 11.8174 & -0.817354 \tabularnewline
188 & 7 & 8.87322 & -1.87322 \tabularnewline
189 & 7 & 8.39678 & -1.39678 \tabularnewline
190 & 5 & 8.59865 & -3.59865 \tabularnewline
191 & 12 & 10.3431 & 1.65691 \tabularnewline
192 & 12 & 11.4981 & 0.501852 \tabularnewline
193 & 3 & 9.04403 & -6.04403 \tabularnewline
194 & 11 & 11.4144 & -0.41441 \tabularnewline
195 & 10 & 9.57078 & 0.429221 \tabularnewline
196 & 12 & 10.8876 & 1.11239 \tabularnewline
197 & 9 & 11.1315 & -2.13149 \tabularnewline
198 & 12 & 11.4205 & 0.579492 \tabularnewline
199 & 9 & 10.1901 & -1.19012 \tabularnewline
200 & 12 & 11.3783 & 0.621725 \tabularnewline
201 & 12 & 11.2439 & 0.756095 \tabularnewline
202 & 10 & 10.2065 & -0.206461 \tabularnewline
203 & 9 & 8.3876 & 0.612395 \tabularnewline
204 & 12 & 9.00518 & 2.99482 \tabularnewline
205 & 8 & 10.7724 & -2.77237 \tabularnewline
206 & 11 & 10.8141 & 0.185852 \tabularnewline
207 & 11 & 11.4142 & -0.414222 \tabularnewline
208 & 12 & 11.3216 & 0.67841 \tabularnewline
209 & 10 & 8.45325 & 1.54675 \tabularnewline
210 & 10 & 10.694 & -0.693973 \tabularnewline
211 & 12 & 9.06645 & 2.93355 \tabularnewline
212 & 12 & 9.34224 & 2.65776 \tabularnewline
213 & 11 & 10.9691 & 0.0308691 \tabularnewline
214 & 8 & 10.7907 & -2.79071 \tabularnewline
215 & 12 & 11.327 & 0.673011 \tabularnewline
216 & 10 & 9.93284 & 0.0671623 \tabularnewline
217 & 11 & 11.8986 & -0.898638 \tabularnewline
218 & 10 & 10.1154 & -0.11543 \tabularnewline
219 & 8 & 9.63154 & -1.63154 \tabularnewline
220 & 12 & 10.8871 & 1.11295 \tabularnewline
221 & 12 & 9.62735 & 2.37265 \tabularnewline
222 & 10 & 10.1854 & -0.185405 \tabularnewline
223 & 12 & 10.701 & 1.299 \tabularnewline
224 & 9 & 9.07902 & -0.0790152 \tabularnewline
225 & 9 & 9.70193 & -0.701935 \tabularnewline
226 & 6 & 6.97038 & -0.970379 \tabularnewline
227 & 10 & 10.1221 & -0.122096 \tabularnewline
228 & 9 & 10.2446 & -1.2446 \tabularnewline
229 & 9 & 8.46615 & 0.533854 \tabularnewline
230 & 9 & 9.1569 & -0.156896 \tabularnewline
231 & 6 & 9.48973 & -3.48973 \tabularnewline
232 & 10 & 8.17556 & 1.82444 \tabularnewline
233 & 6 & 11.3649 & -5.36486 \tabularnewline
234 & 14 & 12.2324 & 1.76756 \tabularnewline
235 & 10 & 9.57073 & 0.429273 \tabularnewline
236 & 10 & 8.40058 & 1.59942 \tabularnewline
237 & 6 & 4.40923 & 1.59077 \tabularnewline
238 & 12 & 9.34136 & 2.65864 \tabularnewline
239 & 12 & 11.3442 & 0.655787 \tabularnewline
240 & 7 & 7.80688 & -0.806881 \tabularnewline
241 & 8 & 9.17677 & -1.17677 \tabularnewline
242 & 11 & 9.12089 & 1.87911 \tabularnewline
243 & 3 & 7.83425 & -4.83425 \tabularnewline
244 & 6 & 9.57692 & -3.57692 \tabularnewline
245 & 10 & 10.5578 & -0.557835 \tabularnewline
246 & 8 & 9.17733 & -1.17733 \tabularnewline
247 & 9 & 10.2599 & -1.25991 \tabularnewline
248 & 9 & 7.76031 & 1.23969 \tabularnewline
249 & 8 & 8.81724 & -0.817244 \tabularnewline
250 & 9 & 8.7561 & 0.243896 \tabularnewline
251 & 7 & 8.55347 & -1.55347 \tabularnewline
252 & 7 & 7.88156 & -0.881562 \tabularnewline
253 & 6 & 9.07687 & -3.07687 \tabularnewline
254 & 9 & 11.2571 & -2.25711 \tabularnewline
255 & 10 & 8.97656 & 1.02344 \tabularnewline
256 & 11 & 10.16 & 0.840035 \tabularnewline
257 & 12 & 11.3925 & 0.607501 \tabularnewline
258 & 8 & 10.1825 & -2.18254 \tabularnewline
259 & 11 & 9.55276 & 1.44724 \tabularnewline
260 & 3 & 4.55416 & -1.55416 \tabularnewline
261 & 11 & 10.7235 & 0.276517 \tabularnewline
262 & 12 & 8.67639 & 3.32361 \tabularnewline
263 & 7 & 8.50135 & -1.50135 \tabularnewline
264 & 9 & 10.2105 & -1.21055 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221698&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]10.1612[/C][C]1.83884[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]11.5896[/C][C]-0.589561[/C][/ROW]
[ROW][C]3[/C][C]15[/C][C]13.5914[/C][C]1.40855[/C][/ROW]
[ROW][C]4[/C][C]6[/C][C]11.2772[/C][C]-5.27722[/C][/ROW]
[ROW][C]5[/C][C]13[/C][C]10.6893[/C][C]2.31067[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]9.8635[/C][C]0.136496[/C][/ROW]
[ROW][C]7[/C][C]12[/C][C]13.1662[/C][C]-1.16619[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]11.3264[/C][C]2.67361[/C][/ROW]
[ROW][C]9[/C][C]12[/C][C]10.6933[/C][C]1.30673[/C][/ROW]
[ROW][C]10[/C][C]9[/C][C]11.3209[/C][C]-2.32089[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]11.59[/C][C]-1.58998[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]11.7351[/C][C]0.264856[/C][/ROW]
[ROW][C]13[/C][C]12[/C][C]11.7873[/C][C]0.2127[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]11.8205[/C][C]-0.820469[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]12.4541[/C][C]2.5459[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]11.2157[/C][C]0.784293[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]11.1075[/C][C]-1.10748[/C][/ROW]
[ROW][C]18[/C][C]12[/C][C]14.0786[/C][C]-2.07864[/C][/ROW]
[ROW][C]19[/C][C]11[/C][C]12.9961[/C][C]-1.99615[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]11.7171[/C][C]0.282852[/C][/ROW]
[ROW][C]21[/C][C]11[/C][C]11.7639[/C][C]-0.763881[/C][/ROW]
[ROW][C]22[/C][C]12[/C][C]11.7493[/C][C]0.250699[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]13.5336[/C][C]-0.533553[/C][/ROW]
[ROW][C]24[/C][C]11[/C][C]11.9447[/C][C]-0.944696[/C][/ROW]
[ROW][C]25[/C][C]12[/C][C]12.1585[/C][C]-0.158512[/C][/ROW]
[ROW][C]26[/C][C]13[/C][C]12.244[/C][C]0.755976[/C][/ROW]
[ROW][C]27[/C][C]10[/C][C]11.7838[/C][C]-1.78376[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]11.3449[/C][C]2.65509[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]11.742[/C][C]0.257962[/C][/ROW]
[ROW][C]30[/C][C]10[/C][C]10.6722[/C][C]-0.672204[/C][/ROW]
[ROW][C]31[/C][C]12[/C][C]11.177[/C][C]0.823048[/C][/ROW]
[ROW][C]32[/C][C]8[/C][C]9.59759[/C][C]-1.59759[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.4947[/C][C]-0.494701[/C][/ROW]
[ROW][C]34[/C][C]12[/C][C]11.909[/C][C]0.0909849[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.5173[/C][C]1.48273[/C][/ROW]
[ROW][C]36[/C][C]7[/C][C]8.46559[/C][C]-1.46559[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]8.41479[/C][C]0.585207[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]10.5964[/C][C]1.40359[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]11.7458[/C][C]-1.74577[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]11.7705[/C][C]-1.77051[/C][/ROW]
[ROW][C]41[/C][C]10[/C][C]11.681[/C][C]-1.68103[/C][/ROW]
[ROW][C]42[/C][C]12[/C][C]10.5995[/C][C]1.40052[/C][/ROW]
[ROW][C]43[/C][C]15[/C][C]13.8857[/C][C]1.11431[/C][/ROW]
[ROW][C]44[/C][C]10[/C][C]10.6328[/C][C]-0.632795[/C][/ROW]
[ROW][C]45[/C][C]10[/C][C]10.3763[/C][C]-0.376293[/C][/ROW]
[ROW][C]46[/C][C]12[/C][C]9.02937[/C][C]2.97063[/C][/ROW]
[ROW][C]47[/C][C]13[/C][C]10.8241[/C][C]2.17595[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]11.2531[/C][C]-0.253064[/C][/ROW]
[ROW][C]49[/C][C]11[/C][C]11.8503[/C][C]-0.850297[/C][/ROW]
[ROW][C]50[/C][C]12[/C][C]10.5576[/C][C]1.44244[/C][/ROW]
[ROW][C]51[/C][C]14[/C][C]11.9794[/C][C]2.02059[/C][/ROW]
[ROW][C]52[/C][C]10[/C][C]10.5424[/C][C]-0.542448[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]9.54701[/C][C]2.45299[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.9576[/C][C]1.04236[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]7.89259[/C][C]-2.89259[/C][/ROW]
[ROW][C]56[/C][C]6[/C][C]10.6335[/C][C]-4.63347[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]11.674[/C][C]0.32604[/C][/ROW]
[ROW][C]58[/C][C]12[/C][C]11.8975[/C][C]0.102515[/C][/ROW]
[ROW][C]59[/C][C]11[/C][C]11.3092[/C][C]-0.309214[/C][/ROW]
[ROW][C]60[/C][C]10[/C][C]11.7749[/C][C]-1.77493[/C][/ROW]
[ROW][C]61[/C][C]7[/C][C]9.40576[/C][C]-2.40576[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]11.7387[/C][C]0.261321[/C][/ROW]
[ROW][C]63[/C][C]14[/C][C]11.8722[/C][C]2.12778[/C][/ROW]
[ROW][C]64[/C][C]11[/C][C]10.7547[/C][C]0.245302[/C][/ROW]
[ROW][C]65[/C][C]12[/C][C]11.6562[/C][C]0.343803[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]12.2709[/C][C]0.72907[/C][/ROW]
[ROW][C]67[/C][C]14[/C][C]12.6626[/C][C]1.33738[/C][/ROW]
[ROW][C]68[/C][C]11[/C][C]12.4891[/C][C]-1.48913[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]9.45502[/C][C]2.54498[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]11.623[/C][C]0.376975[/C][/ROW]
[ROW][C]71[/C][C]8[/C][C]8.21644[/C][C]-0.216438[/C][/ROW]
[ROW][C]72[/C][C]11[/C][C]10.5966[/C][C]0.403439[/C][/ROW]
[ROW][C]73[/C][C]14[/C][C]12.8403[/C][C]1.15965[/C][/ROW]
[ROW][C]74[/C][C]14[/C][C]12.8774[/C][C]1.12258[/C][/ROW]
[ROW][C]75[/C][C]12[/C][C]11.3041[/C][C]0.695905[/C][/ROW]
[ROW][C]76[/C][C]9[/C][C]11.8279[/C][C]-2.82791[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.5725[/C][C]1.42746[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]11.4034[/C][C]-0.403382[/C][/ROW]
[ROW][C]79[/C][C]12[/C][C]9.85082[/C][C]2.14918[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]11.2711[/C][C]0.728944[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]11.647[/C][C]0.353011[/C][/ROW]
[ROW][C]82[/C][C]12[/C][C]11.6702[/C][C]0.329753[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]10.8824[/C][C]1.11761[/C][/ROW]
[ROW][C]84[/C][C]11[/C][C]11.0206[/C][C]-0.020582[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]11.4458[/C][C]-1.44581[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]10.5459[/C][C]-1.54593[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]11.5722[/C][C]0.427777[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]11.5478[/C][C]0.452194[/C][/ROW]
[ROW][C]89[/C][C]12[/C][C]10.9711[/C][C]1.02892[/C][/ROW]
[ROW][C]90[/C][C]9[/C][C]9.41223[/C][C]-0.412228[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]11.9829[/C][C]3.01706[/C][/ROW]
[ROW][C]92[/C][C]12[/C][C]11.7884[/C][C]0.211577[/C][/ROW]
[ROW][C]93[/C][C]12[/C][C]10.771[/C][C]1.22903[/C][/ROW]
[ROW][C]94[/C][C]12[/C][C]9.82455[/C][C]2.17545[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]11.5305[/C][C]-1.53048[/C][/ROW]
[ROW][C]96[/C][C]13[/C][C]11.5295[/C][C]1.47049[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]11.4301[/C][C]-2.43008[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]11.4745[/C][C]0.525536[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]10.5612[/C][C]-0.561152[/C][/ROW]
[ROW][C]100[/C][C]14[/C][C]11.5446[/C][C]2.45542[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]11.5295[/C][C]-0.529507[/C][/ROW]
[ROW][C]102[/C][C]15[/C][C]13.8371[/C][C]1.16287[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]10.8467[/C][C]0.153282[/C][/ROW]
[ROW][C]104[/C][C]11[/C][C]11.7167[/C][C]-0.716732[/C][/ROW]
[ROW][C]105[/C][C]12[/C][C]9.70136[/C][C]2.29864[/C][/ROW]
[ROW][C]106[/C][C]12[/C][C]12.0651[/C][C]-0.0650938[/C][/ROW]
[ROW][C]107[/C][C]12[/C][C]11.5783[/C][C]0.421743[/C][/ROW]
[ROW][C]108[/C][C]11[/C][C]11.5816[/C][C]-0.581571[/C][/ROW]
[ROW][C]109[/C][C]7[/C][C]9.42314[/C][C]-2.42314[/C][/ROW]
[ROW][C]110[/C][C]12[/C][C]11.5926[/C][C]0.407393[/C][/ROW]
[ROW][C]111[/C][C]14[/C][C]11.5775[/C][C]2.42251[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]12.4408[/C][C]-1.44085[/C][/ROW]
[ROW][C]113[/C][C]11[/C][C]9.85333[/C][C]1.14667[/C][/ROW]
[ROW][C]114[/C][C]10[/C][C]9.22718[/C][C]0.772815[/C][/ROW]
[ROW][C]115[/C][C]13[/C][C]12.5312[/C][C]0.468822[/C][/ROW]
[ROW][C]116[/C][C]13[/C][C]10.6747[/C][C]2.32533[/C][/ROW]
[ROW][C]117[/C][C]8[/C][C]10.6668[/C][C]-2.66681[/C][/ROW]
[ROW][C]118[/C][C]11[/C][C]9.97066[/C][C]1.02934[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]11.5353[/C][C]0.46468[/C][/ROW]
[ROW][C]120[/C][C]11[/C][C]10.0173[/C][C]0.98272[/C][/ROW]
[ROW][C]121[/C][C]13[/C][C]11.315[/C][C]1.68497[/C][/ROW]
[ROW][C]122[/C][C]12[/C][C]10.0085[/C][C]1.99148[/C][/ROW]
[ROW][C]123[/C][C]14[/C][C]11.6841[/C][C]2.31594[/C][/ROW]
[ROW][C]124[/C][C]13[/C][C]10.8438[/C][C]2.15618[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]11.59[/C][C]3.41005[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]10.8339[/C][C]-0.833907[/C][/ROW]
[ROW][C]127[/C][C]11[/C][C]12.114[/C][C]-1.11398[/C][/ROW]
[ROW][C]128[/C][C]9[/C][C]11.0401[/C][C]-2.04007[/C][/ROW]
[ROW][C]129[/C][C]11[/C][C]9.25134[/C][C]1.74866[/C][/ROW]
[ROW][C]130[/C][C]10[/C][C]11.5726[/C][C]-1.57264[/C][/ROW]
[ROW][C]131[/C][C]11[/C][C]8.23074[/C][C]2.76926[/C][/ROW]
[ROW][C]132[/C][C]8[/C][C]11.5743[/C][C]-3.57426[/C][/ROW]
[ROW][C]133[/C][C]11[/C][C]9.25396[/C][C]1.74604[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]10.5337[/C][C]1.46631[/C][/ROW]
[ROW][C]135[/C][C]12[/C][C]10.7941[/C][C]1.2059[/C][/ROW]
[ROW][C]136[/C][C]9[/C][C]9.4561[/C][C]-0.456102[/C][/ROW]
[ROW][C]137[/C][C]11[/C][C]11.0187[/C][C]-0.0187182[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]8.88185[/C][C]1.11815[/C][/ROW]
[ROW][C]139[/C][C]8[/C][C]9.30921[/C][C]-1.30921[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]8.87701[/C][C]0.12299[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]11.5958[/C][C]-3.59577[/C][/ROW]
[ROW][C]142[/C][C]9[/C][C]11.1406[/C][C]-2.14062[/C][/ROW]
[ROW][C]143[/C][C]15[/C][C]12.2194[/C][C]2.78057[/C][/ROW]
[ROW][C]144[/C][C]11[/C][C]11.1653[/C][C]-0.165315[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]7.98046[/C][C]0.0195435[/C][/ROW]
[ROW][C]146[/C][C]13[/C][C]12.4039[/C][C]0.596106[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]9.95791[/C][C]2.04209[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]11.5073[/C][C]0.492678[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]9.78791[/C][C]-0.787908[/C][/ROW]
[ROW][C]150[/C][C]7[/C][C]8.31754[/C][C]-1.31754[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]10.9425[/C][C]2.05746[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.7139[/C][C]-2.71389[/C][/ROW]
[ROW][C]153[/C][C]6[/C][C]11.7579[/C][C]-5.75786[/C][/ROW]
[ROW][C]154[/C][C]8[/C][C]10.6106[/C][C]-2.6106[/C][/ROW]
[ROW][C]155[/C][C]8[/C][C]8.07348[/C][C]-0.0734766[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]11.9829[/C][C]3.01706[/C][/ROW]
[ROW][C]157[/C][C]6[/C][C]10.0187[/C][C]-4.01872[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]11.0401[/C][C]-2.04007[/C][/ROW]
[ROW][C]159[/C][C]11[/C][C]11.5179[/C][C]-0.517926[/C][/ROW]
[ROW][C]160[/C][C]8[/C][C]9.48895[/C][C]-1.48895[/C][/ROW]
[ROW][C]161[/C][C]8[/C][C]9.93888[/C][C]-1.93888[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.39223[/C][C]0.607772[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]8.81052[/C][C]-0.810519[/C][/ROW]
[ROW][C]164[/C][C]14[/C][C]11.6618[/C][C]2.33823[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]10.9472[/C][C]-0.947168[/C][/ROW]
[ROW][C]166[/C][C]8[/C][C]7.92801[/C][C]0.0719867[/C][/ROW]
[ROW][C]167[/C][C]11[/C][C]10.2322[/C][C]0.767775[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]8.32709[/C][C]3.67291[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]9.82713[/C][C]2.17287[/C][/ROW]
[ROW][C]170[/C][C]12[/C][C]11.5593[/C][C]0.440694[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]8.8829[/C][C]-3.8829[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.3716[/C][C]0.628398[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]9.07049[/C][C]0.929514[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]7.12159[/C][C]-0.121586[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]8.78608[/C][C]3.21392[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]10.8729[/C][C]0.127133[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]9.02397[/C][C]-1.02397[/C][/ROW]
[ROW][C]178[/C][C]9[/C][C]8.97131[/C][C]0.0286857[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]10.1305[/C][C]-0.130517[/C][/ROW]
[ROW][C]180[/C][C]9[/C][C]9.15619[/C][C]-0.156191[/C][/ROW]
[ROW][C]181[/C][C]12[/C][C]11.3674[/C][C]0.632631[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]8.40082[/C][C]-2.40082[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]13.1101[/C][C]1.88985[/C][/ROW]
[ROW][C]184[/C][C]12[/C][C]10.6299[/C][C]1.37005[/C][/ROW]
[ROW][C]185[/C][C]12[/C][C]6.82212[/C][C]5.17788[/C][/ROW]
[ROW][C]186[/C][C]12[/C][C]11.3737[/C][C]0.626294[/C][/ROW]
[ROW][C]187[/C][C]11[/C][C]11.8174[/C][C]-0.817354[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]8.87322[/C][C]-1.87322[/C][/ROW]
[ROW][C]189[/C][C]7[/C][C]8.39678[/C][C]-1.39678[/C][/ROW]
[ROW][C]190[/C][C]5[/C][C]8.59865[/C][C]-3.59865[/C][/ROW]
[ROW][C]191[/C][C]12[/C][C]10.3431[/C][C]1.65691[/C][/ROW]
[ROW][C]192[/C][C]12[/C][C]11.4981[/C][C]0.501852[/C][/ROW]
[ROW][C]193[/C][C]3[/C][C]9.04403[/C][C]-6.04403[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]11.4144[/C][C]-0.41441[/C][/ROW]
[ROW][C]195[/C][C]10[/C][C]9.57078[/C][C]0.429221[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]10.8876[/C][C]1.11239[/C][/ROW]
[ROW][C]197[/C][C]9[/C][C]11.1315[/C][C]-2.13149[/C][/ROW]
[ROW][C]198[/C][C]12[/C][C]11.4205[/C][C]0.579492[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]10.1901[/C][C]-1.19012[/C][/ROW]
[ROW][C]200[/C][C]12[/C][C]11.3783[/C][C]0.621725[/C][/ROW]
[ROW][C]201[/C][C]12[/C][C]11.2439[/C][C]0.756095[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]10.2065[/C][C]-0.206461[/C][/ROW]
[ROW][C]203[/C][C]9[/C][C]8.3876[/C][C]0.612395[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]9.00518[/C][C]2.99482[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]10.7724[/C][C]-2.77237[/C][/ROW]
[ROW][C]206[/C][C]11[/C][C]10.8141[/C][C]0.185852[/C][/ROW]
[ROW][C]207[/C][C]11[/C][C]11.4142[/C][C]-0.414222[/C][/ROW]
[ROW][C]208[/C][C]12[/C][C]11.3216[/C][C]0.67841[/C][/ROW]
[ROW][C]209[/C][C]10[/C][C]8.45325[/C][C]1.54675[/C][/ROW]
[ROW][C]210[/C][C]10[/C][C]10.694[/C][C]-0.693973[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]9.06645[/C][C]2.93355[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]9.34224[/C][C]2.65776[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]10.9691[/C][C]0.0308691[/C][/ROW]
[ROW][C]214[/C][C]8[/C][C]10.7907[/C][C]-2.79071[/C][/ROW]
[ROW][C]215[/C][C]12[/C][C]11.327[/C][C]0.673011[/C][/ROW]
[ROW][C]216[/C][C]10[/C][C]9.93284[/C][C]0.0671623[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]11.8986[/C][C]-0.898638[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]10.1154[/C][C]-0.11543[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.63154[/C][C]-1.63154[/C][/ROW]
[ROW][C]220[/C][C]12[/C][C]10.8871[/C][C]1.11295[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]9.62735[/C][C]2.37265[/C][/ROW]
[ROW][C]222[/C][C]10[/C][C]10.1854[/C][C]-0.185405[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]10.701[/C][C]1.299[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]9.07902[/C][C]-0.0790152[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.70193[/C][C]-0.701935[/C][/ROW]
[ROW][C]226[/C][C]6[/C][C]6.97038[/C][C]-0.970379[/C][/ROW]
[ROW][C]227[/C][C]10[/C][C]10.1221[/C][C]-0.122096[/C][/ROW]
[ROW][C]228[/C][C]9[/C][C]10.2446[/C][C]-1.2446[/C][/ROW]
[ROW][C]229[/C][C]9[/C][C]8.46615[/C][C]0.533854[/C][/ROW]
[ROW][C]230[/C][C]9[/C][C]9.1569[/C][C]-0.156896[/C][/ROW]
[ROW][C]231[/C][C]6[/C][C]9.48973[/C][C]-3.48973[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]8.17556[/C][C]1.82444[/C][/ROW]
[ROW][C]233[/C][C]6[/C][C]11.3649[/C][C]-5.36486[/C][/ROW]
[ROW][C]234[/C][C]14[/C][C]12.2324[/C][C]1.76756[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]9.57073[/C][C]0.429273[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]8.40058[/C][C]1.59942[/C][/ROW]
[ROW][C]237[/C][C]6[/C][C]4.40923[/C][C]1.59077[/C][/ROW]
[ROW][C]238[/C][C]12[/C][C]9.34136[/C][C]2.65864[/C][/ROW]
[ROW][C]239[/C][C]12[/C][C]11.3442[/C][C]0.655787[/C][/ROW]
[ROW][C]240[/C][C]7[/C][C]7.80688[/C][C]-0.806881[/C][/ROW]
[ROW][C]241[/C][C]8[/C][C]9.17677[/C][C]-1.17677[/C][/ROW]
[ROW][C]242[/C][C]11[/C][C]9.12089[/C][C]1.87911[/C][/ROW]
[ROW][C]243[/C][C]3[/C][C]7.83425[/C][C]-4.83425[/C][/ROW]
[ROW][C]244[/C][C]6[/C][C]9.57692[/C][C]-3.57692[/C][/ROW]
[ROW][C]245[/C][C]10[/C][C]10.5578[/C][C]-0.557835[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]9.17733[/C][C]-1.17733[/C][/ROW]
[ROW][C]247[/C][C]9[/C][C]10.2599[/C][C]-1.25991[/C][/ROW]
[ROW][C]248[/C][C]9[/C][C]7.76031[/C][C]1.23969[/C][/ROW]
[ROW][C]249[/C][C]8[/C][C]8.81724[/C][C]-0.817244[/C][/ROW]
[ROW][C]250[/C][C]9[/C][C]8.7561[/C][C]0.243896[/C][/ROW]
[ROW][C]251[/C][C]7[/C][C]8.55347[/C][C]-1.55347[/C][/ROW]
[ROW][C]252[/C][C]7[/C][C]7.88156[/C][C]-0.881562[/C][/ROW]
[ROW][C]253[/C][C]6[/C][C]9.07687[/C][C]-3.07687[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]11.2571[/C][C]-2.25711[/C][/ROW]
[ROW][C]255[/C][C]10[/C][C]8.97656[/C][C]1.02344[/C][/ROW]
[ROW][C]256[/C][C]11[/C][C]10.16[/C][C]0.840035[/C][/ROW]
[ROW][C]257[/C][C]12[/C][C]11.3925[/C][C]0.607501[/C][/ROW]
[ROW][C]258[/C][C]8[/C][C]10.1825[/C][C]-2.18254[/C][/ROW]
[ROW][C]259[/C][C]11[/C][C]9.55276[/C][C]1.44724[/C][/ROW]
[ROW][C]260[/C][C]3[/C][C]4.55416[/C][C]-1.55416[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]10.7235[/C][C]0.276517[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]8.67639[/C][C]3.32361[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]8.50135[/C][C]-1.50135[/C][/ROW]
[ROW][C]264[/C][C]9[/C][C]10.2105[/C][C]-1.21055[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221698&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221698&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
11210.16121.83884
21111.5896-0.589561
31513.59141.40855
4611.2772-5.27722
51310.68932.31067
6109.86350.136496
71213.1662-1.16619
81411.32642.67361
91210.69331.30673
10911.3209-2.32089
111011.59-1.58998
121211.73510.264856
131211.78730.2127
141111.8205-0.820469
151512.45412.5459
161211.21570.784293
171011.1075-1.10748
181214.0786-2.07864
191112.9961-1.99615
201211.71710.282852
211111.7639-0.763881
221211.74930.250699
231313.5336-0.533553
241111.9447-0.944696
251212.1585-0.158512
261312.2440.755976
271011.7838-1.78376
281411.34492.65509
291211.7420.257962
301010.6722-0.672204
311211.1770.823048
3289.59759-1.59759
331010.4947-0.494701
341211.9090.0909849
351210.51731.48273
3678.46559-1.46559
3798.414790.585207
381210.59641.40359
391011.7458-1.74577
401011.7705-1.77051
411011.681-1.68103
421210.59951.40052
431513.88571.11431
441010.6328-0.632795
451010.3763-0.376293
46129.029372.97063
471310.82412.17595
481111.2531-0.253064
491111.8503-0.850297
501210.55761.44244
511411.97942.02059
521010.5424-0.542448
53129.547012.45299
541311.95761.04236
5557.89259-2.89259
56610.6335-4.63347
571211.6740.32604
581211.89750.102515
591111.3092-0.309214
601011.7749-1.77493
6179.40576-2.40576
621211.73870.261321
631411.87222.12778
641110.75470.245302
651211.65620.343803
661312.27090.72907
671412.66261.33738
681112.4891-1.48913
69129.455022.54498
701211.6230.376975
7188.21644-0.216438
721110.59660.403439
731412.84031.15965
741412.87741.12258
751211.30410.695905
76911.8279-2.82791
771311.57251.42746
781111.4034-0.403382
79129.850822.14918
801211.27110.728944
811211.6470.353011
821211.67020.329753
831210.88241.11761
841111.0206-0.020582
851011.4458-1.44581
86910.5459-1.54593
871211.57220.427777
881211.54780.452194
891210.97111.02892
9099.41223-0.412228
911511.98293.01706
921211.78840.211577
931210.7711.22903
94129.824552.17545
951011.5305-1.53048
961311.52951.47049
97911.4301-2.43008
981211.47450.525536
991010.5612-0.561152
1001411.54462.45542
1011111.5295-0.529507
1021513.83711.16287
1031110.84670.153282
1041111.7167-0.716732
105129.701362.29864
1061212.0651-0.0650938
1071211.57830.421743
1081111.5816-0.581571
10979.42314-2.42314
1101211.59260.407393
1111411.57752.42251
1121112.4408-1.44085
113119.853331.14667
114109.227180.772815
1151312.53120.468822
1161310.67472.32533
117810.6668-2.66681
118119.970661.02934
1191211.53530.46468
1201110.01730.98272
1211311.3151.68497
1221210.00851.99148
1231411.68412.31594
1241310.84382.15618
1251511.593.41005
1261010.8339-0.833907
1271112.114-1.11398
128911.0401-2.04007
129119.251341.74866
1301011.5726-1.57264
131118.230742.76926
132811.5743-3.57426
133119.253961.74604
1341210.53371.46631
1351210.79411.2059
13699.4561-0.456102
1371111.0187-0.0187182
138108.881851.11815
13989.30921-1.30921
14098.877010.12299
141811.5958-3.59577
142911.1406-2.14062
1431512.21942.78057
1441111.1653-0.165315
14587.980460.0195435
1461312.40390.596106
147129.957912.04209
1481211.50730.492678
14999.78791-0.787908
15078.31754-1.31754
1511310.94252.05746
152911.7139-2.71389
153611.7579-5.75786
154810.6106-2.6106
15588.07348-0.0734766
1561511.98293.01706
157610.0187-4.01872
158911.0401-2.04007
1591111.5179-0.517926
16089.48895-1.48895
16189.93888-1.93888
162109.392230.607772
16388.81052-0.810519
1641411.66182.33823
1651010.9472-0.947168
16687.928010.0719867
1671110.23220.767775
168128.327093.67291
169129.827132.17287
1701211.55930.440694
17158.8829-3.8829
1721211.37160.628398
173109.070490.929514
17477.12159-0.121586
175128.786083.21392
1761110.87290.127133
17789.02397-1.02397
17898.971310.0286857
1791010.1305-0.130517
18099.15619-0.156191
1811211.36740.632631
18268.40082-2.40082
1831513.11011.88985
1841210.62991.37005
185126.822125.17788
1861211.37370.626294
1871111.8174-0.817354
18878.87322-1.87322
18978.39678-1.39678
19058.59865-3.59865
1911210.34311.65691
1921211.49810.501852
19339.04403-6.04403
1941111.4144-0.41441
195109.570780.429221
1961210.88761.11239
197911.1315-2.13149
1981211.42050.579492
199910.1901-1.19012
2001211.37830.621725
2011211.24390.756095
2021010.2065-0.206461
20398.38760.612395
204129.005182.99482
205810.7724-2.77237
2061110.81410.185852
2071111.4142-0.414222
2081211.32160.67841
209108.453251.54675
2101010.694-0.693973
211129.066452.93355
212129.342242.65776
2131110.96910.0308691
214810.7907-2.79071
2151211.3270.673011
216109.932840.0671623
2171111.8986-0.898638
2181010.1154-0.11543
21989.63154-1.63154
2201210.88711.11295
221129.627352.37265
2221010.1854-0.185405
2231210.7011.299
22499.07902-0.0790152
22599.70193-0.701935
22666.97038-0.970379
2271010.1221-0.122096
228910.2446-1.2446
22998.466150.533854
23099.1569-0.156896
23169.48973-3.48973
232108.175561.82444
233611.3649-5.36486
2341412.23241.76756
235109.570730.429273
236108.400581.59942
23764.409231.59077
238129.341362.65864
2391211.34420.655787
24077.80688-0.806881
24189.17677-1.17677
242119.120891.87911
24337.83425-4.83425
24469.57692-3.57692
2451010.5578-0.557835
24689.17733-1.17733
247910.2599-1.25991
24897.760311.23969
24988.81724-0.817244
25098.75610.243896
25178.55347-1.55347
25277.88156-0.881562
25369.07687-3.07687
254911.2571-2.25711
255108.976561.02344
2561110.160.840035
2571211.39250.607501
258810.1825-2.18254
259119.552761.44724
26034.55416-1.55416
2611110.72350.276517
262128.676393.32361
26378.50135-1.50135
264910.2105-1.21055






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.9954510.009098930.00454947
110.9901460.01970830.00985417
120.9802640.03947110.0197356
130.967910.06418090.0320905
140.9628060.07438740.0371937
150.9517530.09649490.0482474
160.9303750.139250.0696251
170.8971180.2057650.102882
180.9033460.1933080.096654
190.878310.243380.12169
200.8341950.331610.165805
210.7939460.4121080.206054
220.7511630.4976740.248837
230.6940880.6118230.305912
240.650680.6986390.34932
250.6031530.7936950.396847
260.6512190.6975610.348781
270.6355590.7288810.364441
280.6506790.6986430.349321
290.5908190.8183620.409181
300.5439290.9121420.456071
310.4954880.9909750.504512
320.539240.9215190.46076
330.4808840.9617690.519116
340.4223610.8447220.577639
350.4134560.8269110.586544
360.4130890.8261780.586911
370.359510.7190210.64049
380.3427430.6854860.657257
390.3230620.6461240.676938
400.3011460.6022920.698854
410.273170.546340.72683
420.2510190.5020370.748981
430.2681520.5363040.731848
440.2310570.4621140.768943
450.1943160.3886320.805684
460.2386080.4772170.761392
470.2367450.4734890.763255
480.2003180.4006360.799682
490.1831160.3662330.816884
500.1706360.3412720.829364
510.1770230.3540460.822977
520.148610.2972190.85139
530.1543990.3087990.845601
540.1319980.2639950.868002
550.2101450.420290.789855
560.4674060.9348110.532594
570.4251230.8502460.574877
580.3824560.7649120.617544
590.3424560.6849110.657544
600.341260.682520.65874
610.3577440.7154880.642256
620.3199520.6399030.680048
630.3338510.6677020.666149
640.2953660.5907320.704634
650.2651260.5302520.734874
660.232080.4641610.76792
670.2066040.4132080.793396
680.1914240.3828490.808576
690.1807010.3614010.819299
700.1576160.3152310.842384
710.1436520.2873030.856348
720.1232850.246570.876715
730.1058090.2116190.894191
740.08990230.1798050.910098
750.08048460.1609690.919515
760.101450.20290.89855
770.089840.179680.91016
780.07494560.1498910.925054
790.07818570.1563710.921814
800.06930710.1386140.930693
810.05768940.1153790.942311
820.04798370.09596740.952016
830.04070550.08141110.959294
840.03342340.06684680.966577
850.03168740.06337490.968313
860.03706590.07413170.962934
870.02983990.05967980.97016
880.02395920.04791840.976041
890.02014830.04029660.979852
900.01718320.03436640.982817
910.02643710.05287420.973563
920.02198610.04397220.978014
930.01970950.03941910.98029
940.02063780.04127570.979362
950.02121220.04242450.978788
960.01862140.03724270.981379
970.02396230.04792460.976038
980.01927280.03854560.980727
990.01656280.03312560.983437
1000.01893520.03787050.981065
1010.01582660.03165330.984173
1020.01331370.02662740.986686
1030.01043080.02086150.989569
1040.009295490.0185910.990705
1050.01008620.02017240.989914
1060.00789930.01579860.992101
1070.006178260.01235650.993822
1080.005133880.01026780.994866
1090.007902110.01580420.992098
1100.006151430.01230290.993849
1110.00704680.01409360.992953
1120.007499760.01499950.9925
1130.006243080.01248620.993757
1140.004946390.009892780.995054
1150.003823720.007647430.996176
1160.004194050.008388090.995806
1170.006869120.01373820.993131
1180.005617490.0112350.994383
1190.004371960.008743930.995628
1200.003547020.007094040.996453
1210.003341220.006682450.996659
1220.003396870.006793730.996603
1230.00389050.0077810.996109
1240.004246520.008493050.995753
1250.007958880.01591780.992041
1260.006762440.01352490.993238
1270.005833480.0116670.994167
1280.006654350.01330870.993346
1290.006478160.01295630.993522
1300.006494660.01298930.993505
1310.008580190.01716040.99142
1320.01706290.03412580.982937
1330.01678390.03356790.983216
1340.01596040.03192070.98404
1350.01431180.02862350.985688
1360.01183340.02366690.988167
1370.009603820.01920760.990396
1380.008855120.01771020.991145
1390.008151240.01630250.991849
1400.006884720.01376940.993115
1410.01375930.02751860.986241
1420.01497440.02994880.985026
1430.02270870.04541750.977291
1440.01841580.03683150.981584
1450.0148530.0297060.985147
1460.01261550.0252310.987384
1470.01524020.03048040.98476
1480.01360430.02720860.986396
1490.01158360.02316720.988416
1500.01021980.02043960.98978
1510.0131920.02638410.986808
1520.01536080.03072160.984639
1530.06878060.1375610.931219
1540.06880710.1376140.931193
1550.05990220.1198040.940098
1560.1055110.2110230.894489
1570.150850.30170.84915
1580.1446690.2893380.855331
1590.1303460.2606920.869654
1600.1193370.2386740.880663
1610.1116980.2233960.888302
1620.09816220.1963240.901838
1630.08748130.1749630.912519
1640.0952190.1904380.904781
1650.0858220.1716440.914178
1660.0731110.1462220.926889
1670.06259010.125180.93741
1680.1038770.2077540.896123
1690.1058670.2117340.894133
1700.09176110.1835220.908239
1710.1606970.3213930.839303
1720.1401340.2802690.859866
1730.123520.247040.87648
1740.1066060.2132120.893394
1750.142790.2855790.85721
1760.12330.2465990.8767
1770.1115670.2231330.888433
1780.09556180.1911240.904438
1790.0812590.1625180.918741
1800.06826050.1365210.931739
1810.05753680.1150740.942463
1820.0659950.131990.934005
1830.06765770.1353150.932342
1840.06225720.1245140.937743
1850.2248820.4497640.775118
1860.2021980.4043970.797802
1870.1820610.3641220.817939
1880.1906210.3812410.809379
1890.1767930.3535850.823207
1900.253540.5070810.74646
1910.2518080.5036160.748192
1920.221820.4436390.77818
1930.587880.8242410.41212
1940.5494970.9010060.450503
1950.5122150.9755690.487785
1960.4854540.9709090.514546
1970.5096030.9807940.490397
1980.4727730.9455460.527227
1990.4471670.8943330.552833
2000.4351570.8703140.564843
2010.4147580.8295150.585242
2020.3897610.7795230.610239
2030.3531970.7063930.646803
2040.428180.856360.57182
2050.4635240.9270490.536476
2060.4211480.8422960.578852
2070.3792160.7584320.620784
2080.3417390.6834790.658261
2090.3255340.6510680.674466
2100.2892670.5785340.710733
2110.3623330.7246660.637667
2120.3896180.7792350.610382
2130.3489120.6978230.651088
2140.3645370.7290740.635463
2150.3285230.6570450.671477
2160.2931120.5862240.706888
2170.2564620.5129250.743538
2180.2194620.4389240.780538
2190.2206510.4413010.779349
2200.2013390.4026790.798661
2210.24290.48580.7571
2220.2052720.4105430.794728
2230.1960080.3920160.803992
2240.1707730.3415450.829227
2250.1444140.2888290.855586
2260.1188250.237650.881175
2270.09740060.1948010.902599
2280.07879660.1575930.921203
2290.0609380.1218760.939062
2300.04693380.09386770.953066
2310.07117760.1423550.928822
2320.08910590.1782120.910894
2330.2697370.5394740.730263
2340.2319760.4639520.768024
2350.1898660.3797330.810134
2360.1849480.3698960.815052
2370.1839540.3679070.816046
2380.2577290.5154590.742271
2390.2629920.5259850.737008
2400.2181570.4363150.781843
2410.1729430.3458860.827057
2420.2473120.4946240.752688
2430.5262180.9475630.473782
2440.6657360.6685280.334264
2450.5964980.8070040.403502
2460.5446950.9106110.455305
2470.4923070.9846140.507693
2480.4063680.8127360.593632
2490.3158020.6316030.684198
2500.324940.6498810.67506
2510.4515590.9031170.548441
2520.6173360.7653280.382664
2530.6686010.6627990.331399
2540.7016070.5967870.298393

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.995451 & 0.00909893 & 0.00454947 \tabularnewline
11 & 0.990146 & 0.0197083 & 0.00985417 \tabularnewline
12 & 0.980264 & 0.0394711 & 0.0197356 \tabularnewline
13 & 0.96791 & 0.0641809 & 0.0320905 \tabularnewline
14 & 0.962806 & 0.0743874 & 0.0371937 \tabularnewline
15 & 0.951753 & 0.0964949 & 0.0482474 \tabularnewline
16 & 0.930375 & 0.13925 & 0.0696251 \tabularnewline
17 & 0.897118 & 0.205765 & 0.102882 \tabularnewline
18 & 0.903346 & 0.193308 & 0.096654 \tabularnewline
19 & 0.87831 & 0.24338 & 0.12169 \tabularnewline
20 & 0.834195 & 0.33161 & 0.165805 \tabularnewline
21 & 0.793946 & 0.412108 & 0.206054 \tabularnewline
22 & 0.751163 & 0.497674 & 0.248837 \tabularnewline
23 & 0.694088 & 0.611823 & 0.305912 \tabularnewline
24 & 0.65068 & 0.698639 & 0.34932 \tabularnewline
25 & 0.603153 & 0.793695 & 0.396847 \tabularnewline
26 & 0.651219 & 0.697561 & 0.348781 \tabularnewline
27 & 0.635559 & 0.728881 & 0.364441 \tabularnewline
28 & 0.650679 & 0.698643 & 0.349321 \tabularnewline
29 & 0.590819 & 0.818362 & 0.409181 \tabularnewline
30 & 0.543929 & 0.912142 & 0.456071 \tabularnewline
31 & 0.495488 & 0.990975 & 0.504512 \tabularnewline
32 & 0.53924 & 0.921519 & 0.46076 \tabularnewline
33 & 0.480884 & 0.961769 & 0.519116 \tabularnewline
34 & 0.422361 & 0.844722 & 0.577639 \tabularnewline
35 & 0.413456 & 0.826911 & 0.586544 \tabularnewline
36 & 0.413089 & 0.826178 & 0.586911 \tabularnewline
37 & 0.35951 & 0.719021 & 0.64049 \tabularnewline
38 & 0.342743 & 0.685486 & 0.657257 \tabularnewline
39 & 0.323062 & 0.646124 & 0.676938 \tabularnewline
40 & 0.301146 & 0.602292 & 0.698854 \tabularnewline
41 & 0.27317 & 0.54634 & 0.72683 \tabularnewline
42 & 0.251019 & 0.502037 & 0.748981 \tabularnewline
43 & 0.268152 & 0.536304 & 0.731848 \tabularnewline
44 & 0.231057 & 0.462114 & 0.768943 \tabularnewline
45 & 0.194316 & 0.388632 & 0.805684 \tabularnewline
46 & 0.238608 & 0.477217 & 0.761392 \tabularnewline
47 & 0.236745 & 0.473489 & 0.763255 \tabularnewline
48 & 0.200318 & 0.400636 & 0.799682 \tabularnewline
49 & 0.183116 & 0.366233 & 0.816884 \tabularnewline
50 & 0.170636 & 0.341272 & 0.829364 \tabularnewline
51 & 0.177023 & 0.354046 & 0.822977 \tabularnewline
52 & 0.14861 & 0.297219 & 0.85139 \tabularnewline
53 & 0.154399 & 0.308799 & 0.845601 \tabularnewline
54 & 0.131998 & 0.263995 & 0.868002 \tabularnewline
55 & 0.210145 & 0.42029 & 0.789855 \tabularnewline
56 & 0.467406 & 0.934811 & 0.532594 \tabularnewline
57 & 0.425123 & 0.850246 & 0.574877 \tabularnewline
58 & 0.382456 & 0.764912 & 0.617544 \tabularnewline
59 & 0.342456 & 0.684911 & 0.657544 \tabularnewline
60 & 0.34126 & 0.68252 & 0.65874 \tabularnewline
61 & 0.357744 & 0.715488 & 0.642256 \tabularnewline
62 & 0.319952 & 0.639903 & 0.680048 \tabularnewline
63 & 0.333851 & 0.667702 & 0.666149 \tabularnewline
64 & 0.295366 & 0.590732 & 0.704634 \tabularnewline
65 & 0.265126 & 0.530252 & 0.734874 \tabularnewline
66 & 0.23208 & 0.464161 & 0.76792 \tabularnewline
67 & 0.206604 & 0.413208 & 0.793396 \tabularnewline
68 & 0.191424 & 0.382849 & 0.808576 \tabularnewline
69 & 0.180701 & 0.361401 & 0.819299 \tabularnewline
70 & 0.157616 & 0.315231 & 0.842384 \tabularnewline
71 & 0.143652 & 0.287303 & 0.856348 \tabularnewline
72 & 0.123285 & 0.24657 & 0.876715 \tabularnewline
73 & 0.105809 & 0.211619 & 0.894191 \tabularnewline
74 & 0.0899023 & 0.179805 & 0.910098 \tabularnewline
75 & 0.0804846 & 0.160969 & 0.919515 \tabularnewline
76 & 0.10145 & 0.2029 & 0.89855 \tabularnewline
77 & 0.08984 & 0.17968 & 0.91016 \tabularnewline
78 & 0.0749456 & 0.149891 & 0.925054 \tabularnewline
79 & 0.0781857 & 0.156371 & 0.921814 \tabularnewline
80 & 0.0693071 & 0.138614 & 0.930693 \tabularnewline
81 & 0.0576894 & 0.115379 & 0.942311 \tabularnewline
82 & 0.0479837 & 0.0959674 & 0.952016 \tabularnewline
83 & 0.0407055 & 0.0814111 & 0.959294 \tabularnewline
84 & 0.0334234 & 0.0668468 & 0.966577 \tabularnewline
85 & 0.0316874 & 0.0633749 & 0.968313 \tabularnewline
86 & 0.0370659 & 0.0741317 & 0.962934 \tabularnewline
87 & 0.0298399 & 0.0596798 & 0.97016 \tabularnewline
88 & 0.0239592 & 0.0479184 & 0.976041 \tabularnewline
89 & 0.0201483 & 0.0402966 & 0.979852 \tabularnewline
90 & 0.0171832 & 0.0343664 & 0.982817 \tabularnewline
91 & 0.0264371 & 0.0528742 & 0.973563 \tabularnewline
92 & 0.0219861 & 0.0439722 & 0.978014 \tabularnewline
93 & 0.0197095 & 0.0394191 & 0.98029 \tabularnewline
94 & 0.0206378 & 0.0412757 & 0.979362 \tabularnewline
95 & 0.0212122 & 0.0424245 & 0.978788 \tabularnewline
96 & 0.0186214 & 0.0372427 & 0.981379 \tabularnewline
97 & 0.0239623 & 0.0479246 & 0.976038 \tabularnewline
98 & 0.0192728 & 0.0385456 & 0.980727 \tabularnewline
99 & 0.0165628 & 0.0331256 & 0.983437 \tabularnewline
100 & 0.0189352 & 0.0378705 & 0.981065 \tabularnewline
101 & 0.0158266 & 0.0316533 & 0.984173 \tabularnewline
102 & 0.0133137 & 0.0266274 & 0.986686 \tabularnewline
103 & 0.0104308 & 0.0208615 & 0.989569 \tabularnewline
104 & 0.00929549 & 0.018591 & 0.990705 \tabularnewline
105 & 0.0100862 & 0.0201724 & 0.989914 \tabularnewline
106 & 0.0078993 & 0.0157986 & 0.992101 \tabularnewline
107 & 0.00617826 & 0.0123565 & 0.993822 \tabularnewline
108 & 0.00513388 & 0.0102678 & 0.994866 \tabularnewline
109 & 0.00790211 & 0.0158042 & 0.992098 \tabularnewline
110 & 0.00615143 & 0.0123029 & 0.993849 \tabularnewline
111 & 0.0070468 & 0.0140936 & 0.992953 \tabularnewline
112 & 0.00749976 & 0.0149995 & 0.9925 \tabularnewline
113 & 0.00624308 & 0.0124862 & 0.993757 \tabularnewline
114 & 0.00494639 & 0.00989278 & 0.995054 \tabularnewline
115 & 0.00382372 & 0.00764743 & 0.996176 \tabularnewline
116 & 0.00419405 & 0.00838809 & 0.995806 \tabularnewline
117 & 0.00686912 & 0.0137382 & 0.993131 \tabularnewline
118 & 0.00561749 & 0.011235 & 0.994383 \tabularnewline
119 & 0.00437196 & 0.00874393 & 0.995628 \tabularnewline
120 & 0.00354702 & 0.00709404 & 0.996453 \tabularnewline
121 & 0.00334122 & 0.00668245 & 0.996659 \tabularnewline
122 & 0.00339687 & 0.00679373 & 0.996603 \tabularnewline
123 & 0.0038905 & 0.007781 & 0.996109 \tabularnewline
124 & 0.00424652 & 0.00849305 & 0.995753 \tabularnewline
125 & 0.00795888 & 0.0159178 & 0.992041 \tabularnewline
126 & 0.00676244 & 0.0135249 & 0.993238 \tabularnewline
127 & 0.00583348 & 0.011667 & 0.994167 \tabularnewline
128 & 0.00665435 & 0.0133087 & 0.993346 \tabularnewline
129 & 0.00647816 & 0.0129563 & 0.993522 \tabularnewline
130 & 0.00649466 & 0.0129893 & 0.993505 \tabularnewline
131 & 0.00858019 & 0.0171604 & 0.99142 \tabularnewline
132 & 0.0170629 & 0.0341258 & 0.982937 \tabularnewline
133 & 0.0167839 & 0.0335679 & 0.983216 \tabularnewline
134 & 0.0159604 & 0.0319207 & 0.98404 \tabularnewline
135 & 0.0143118 & 0.0286235 & 0.985688 \tabularnewline
136 & 0.0118334 & 0.0236669 & 0.988167 \tabularnewline
137 & 0.00960382 & 0.0192076 & 0.990396 \tabularnewline
138 & 0.00885512 & 0.0177102 & 0.991145 \tabularnewline
139 & 0.00815124 & 0.0163025 & 0.991849 \tabularnewline
140 & 0.00688472 & 0.0137694 & 0.993115 \tabularnewline
141 & 0.0137593 & 0.0275186 & 0.986241 \tabularnewline
142 & 0.0149744 & 0.0299488 & 0.985026 \tabularnewline
143 & 0.0227087 & 0.0454175 & 0.977291 \tabularnewline
144 & 0.0184158 & 0.0368315 & 0.981584 \tabularnewline
145 & 0.014853 & 0.029706 & 0.985147 \tabularnewline
146 & 0.0126155 & 0.025231 & 0.987384 \tabularnewline
147 & 0.0152402 & 0.0304804 & 0.98476 \tabularnewline
148 & 0.0136043 & 0.0272086 & 0.986396 \tabularnewline
149 & 0.0115836 & 0.0231672 & 0.988416 \tabularnewline
150 & 0.0102198 & 0.0204396 & 0.98978 \tabularnewline
151 & 0.013192 & 0.0263841 & 0.986808 \tabularnewline
152 & 0.0153608 & 0.0307216 & 0.984639 \tabularnewline
153 & 0.0687806 & 0.137561 & 0.931219 \tabularnewline
154 & 0.0688071 & 0.137614 & 0.931193 \tabularnewline
155 & 0.0599022 & 0.119804 & 0.940098 \tabularnewline
156 & 0.105511 & 0.211023 & 0.894489 \tabularnewline
157 & 0.15085 & 0.3017 & 0.84915 \tabularnewline
158 & 0.144669 & 0.289338 & 0.855331 \tabularnewline
159 & 0.130346 & 0.260692 & 0.869654 \tabularnewline
160 & 0.119337 & 0.238674 & 0.880663 \tabularnewline
161 & 0.111698 & 0.223396 & 0.888302 \tabularnewline
162 & 0.0981622 & 0.196324 & 0.901838 \tabularnewline
163 & 0.0874813 & 0.174963 & 0.912519 \tabularnewline
164 & 0.095219 & 0.190438 & 0.904781 \tabularnewline
165 & 0.085822 & 0.171644 & 0.914178 \tabularnewline
166 & 0.073111 & 0.146222 & 0.926889 \tabularnewline
167 & 0.0625901 & 0.12518 & 0.93741 \tabularnewline
168 & 0.103877 & 0.207754 & 0.896123 \tabularnewline
169 & 0.105867 & 0.211734 & 0.894133 \tabularnewline
170 & 0.0917611 & 0.183522 & 0.908239 \tabularnewline
171 & 0.160697 & 0.321393 & 0.839303 \tabularnewline
172 & 0.140134 & 0.280269 & 0.859866 \tabularnewline
173 & 0.12352 & 0.24704 & 0.87648 \tabularnewline
174 & 0.106606 & 0.213212 & 0.893394 \tabularnewline
175 & 0.14279 & 0.285579 & 0.85721 \tabularnewline
176 & 0.1233 & 0.246599 & 0.8767 \tabularnewline
177 & 0.111567 & 0.223133 & 0.888433 \tabularnewline
178 & 0.0955618 & 0.191124 & 0.904438 \tabularnewline
179 & 0.081259 & 0.162518 & 0.918741 \tabularnewline
180 & 0.0682605 & 0.136521 & 0.931739 \tabularnewline
181 & 0.0575368 & 0.115074 & 0.942463 \tabularnewline
182 & 0.065995 & 0.13199 & 0.934005 \tabularnewline
183 & 0.0676577 & 0.135315 & 0.932342 \tabularnewline
184 & 0.0622572 & 0.124514 & 0.937743 \tabularnewline
185 & 0.224882 & 0.449764 & 0.775118 \tabularnewline
186 & 0.202198 & 0.404397 & 0.797802 \tabularnewline
187 & 0.182061 & 0.364122 & 0.817939 \tabularnewline
188 & 0.190621 & 0.381241 & 0.809379 \tabularnewline
189 & 0.176793 & 0.353585 & 0.823207 \tabularnewline
190 & 0.25354 & 0.507081 & 0.74646 \tabularnewline
191 & 0.251808 & 0.503616 & 0.748192 \tabularnewline
192 & 0.22182 & 0.443639 & 0.77818 \tabularnewline
193 & 0.58788 & 0.824241 & 0.41212 \tabularnewline
194 & 0.549497 & 0.901006 & 0.450503 \tabularnewline
195 & 0.512215 & 0.975569 & 0.487785 \tabularnewline
196 & 0.485454 & 0.970909 & 0.514546 \tabularnewline
197 & 0.509603 & 0.980794 & 0.490397 \tabularnewline
198 & 0.472773 & 0.945546 & 0.527227 \tabularnewline
199 & 0.447167 & 0.894333 & 0.552833 \tabularnewline
200 & 0.435157 & 0.870314 & 0.564843 \tabularnewline
201 & 0.414758 & 0.829515 & 0.585242 \tabularnewline
202 & 0.389761 & 0.779523 & 0.610239 \tabularnewline
203 & 0.353197 & 0.706393 & 0.646803 \tabularnewline
204 & 0.42818 & 0.85636 & 0.57182 \tabularnewline
205 & 0.463524 & 0.927049 & 0.536476 \tabularnewline
206 & 0.421148 & 0.842296 & 0.578852 \tabularnewline
207 & 0.379216 & 0.758432 & 0.620784 \tabularnewline
208 & 0.341739 & 0.683479 & 0.658261 \tabularnewline
209 & 0.325534 & 0.651068 & 0.674466 \tabularnewline
210 & 0.289267 & 0.578534 & 0.710733 \tabularnewline
211 & 0.362333 & 0.724666 & 0.637667 \tabularnewline
212 & 0.389618 & 0.779235 & 0.610382 \tabularnewline
213 & 0.348912 & 0.697823 & 0.651088 \tabularnewline
214 & 0.364537 & 0.729074 & 0.635463 \tabularnewline
215 & 0.328523 & 0.657045 & 0.671477 \tabularnewline
216 & 0.293112 & 0.586224 & 0.706888 \tabularnewline
217 & 0.256462 & 0.512925 & 0.743538 \tabularnewline
218 & 0.219462 & 0.438924 & 0.780538 \tabularnewline
219 & 0.220651 & 0.441301 & 0.779349 \tabularnewline
220 & 0.201339 & 0.402679 & 0.798661 \tabularnewline
221 & 0.2429 & 0.4858 & 0.7571 \tabularnewline
222 & 0.205272 & 0.410543 & 0.794728 \tabularnewline
223 & 0.196008 & 0.392016 & 0.803992 \tabularnewline
224 & 0.170773 & 0.341545 & 0.829227 \tabularnewline
225 & 0.144414 & 0.288829 & 0.855586 \tabularnewline
226 & 0.118825 & 0.23765 & 0.881175 \tabularnewline
227 & 0.0974006 & 0.194801 & 0.902599 \tabularnewline
228 & 0.0787966 & 0.157593 & 0.921203 \tabularnewline
229 & 0.060938 & 0.121876 & 0.939062 \tabularnewline
230 & 0.0469338 & 0.0938677 & 0.953066 \tabularnewline
231 & 0.0711776 & 0.142355 & 0.928822 \tabularnewline
232 & 0.0891059 & 0.178212 & 0.910894 \tabularnewline
233 & 0.269737 & 0.539474 & 0.730263 \tabularnewline
234 & 0.231976 & 0.463952 & 0.768024 \tabularnewline
235 & 0.189866 & 0.379733 & 0.810134 \tabularnewline
236 & 0.184948 & 0.369896 & 0.815052 \tabularnewline
237 & 0.183954 & 0.367907 & 0.816046 \tabularnewline
238 & 0.257729 & 0.515459 & 0.742271 \tabularnewline
239 & 0.262992 & 0.525985 & 0.737008 \tabularnewline
240 & 0.218157 & 0.436315 & 0.781843 \tabularnewline
241 & 0.172943 & 0.345886 & 0.827057 \tabularnewline
242 & 0.247312 & 0.494624 & 0.752688 \tabularnewline
243 & 0.526218 & 0.947563 & 0.473782 \tabularnewline
244 & 0.665736 & 0.668528 & 0.334264 \tabularnewline
245 & 0.596498 & 0.807004 & 0.403502 \tabularnewline
246 & 0.544695 & 0.910611 & 0.455305 \tabularnewline
247 & 0.492307 & 0.984614 & 0.507693 \tabularnewline
248 & 0.406368 & 0.812736 & 0.593632 \tabularnewline
249 & 0.315802 & 0.631603 & 0.684198 \tabularnewline
250 & 0.32494 & 0.649881 & 0.67506 \tabularnewline
251 & 0.451559 & 0.903117 & 0.548441 \tabularnewline
252 & 0.617336 & 0.765328 & 0.382664 \tabularnewline
253 & 0.668601 & 0.662799 & 0.331399 \tabularnewline
254 & 0.701607 & 0.596787 & 0.298393 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221698&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]10[/C][C]0.995451[/C][C]0.00909893[/C][C]0.00454947[/C][/ROW]
[ROW][C]11[/C][C]0.990146[/C][C]0.0197083[/C][C]0.00985417[/C][/ROW]
[ROW][C]12[/C][C]0.980264[/C][C]0.0394711[/C][C]0.0197356[/C][/ROW]
[ROW][C]13[/C][C]0.96791[/C][C]0.0641809[/C][C]0.0320905[/C][/ROW]
[ROW][C]14[/C][C]0.962806[/C][C]0.0743874[/C][C]0.0371937[/C][/ROW]
[ROW][C]15[/C][C]0.951753[/C][C]0.0964949[/C][C]0.0482474[/C][/ROW]
[ROW][C]16[/C][C]0.930375[/C][C]0.13925[/C][C]0.0696251[/C][/ROW]
[ROW][C]17[/C][C]0.897118[/C][C]0.205765[/C][C]0.102882[/C][/ROW]
[ROW][C]18[/C][C]0.903346[/C][C]0.193308[/C][C]0.096654[/C][/ROW]
[ROW][C]19[/C][C]0.87831[/C][C]0.24338[/C][C]0.12169[/C][/ROW]
[ROW][C]20[/C][C]0.834195[/C][C]0.33161[/C][C]0.165805[/C][/ROW]
[ROW][C]21[/C][C]0.793946[/C][C]0.412108[/C][C]0.206054[/C][/ROW]
[ROW][C]22[/C][C]0.751163[/C][C]0.497674[/C][C]0.248837[/C][/ROW]
[ROW][C]23[/C][C]0.694088[/C][C]0.611823[/C][C]0.305912[/C][/ROW]
[ROW][C]24[/C][C]0.65068[/C][C]0.698639[/C][C]0.34932[/C][/ROW]
[ROW][C]25[/C][C]0.603153[/C][C]0.793695[/C][C]0.396847[/C][/ROW]
[ROW][C]26[/C][C]0.651219[/C][C]0.697561[/C][C]0.348781[/C][/ROW]
[ROW][C]27[/C][C]0.635559[/C][C]0.728881[/C][C]0.364441[/C][/ROW]
[ROW][C]28[/C][C]0.650679[/C][C]0.698643[/C][C]0.349321[/C][/ROW]
[ROW][C]29[/C][C]0.590819[/C][C]0.818362[/C][C]0.409181[/C][/ROW]
[ROW][C]30[/C][C]0.543929[/C][C]0.912142[/C][C]0.456071[/C][/ROW]
[ROW][C]31[/C][C]0.495488[/C][C]0.990975[/C][C]0.504512[/C][/ROW]
[ROW][C]32[/C][C]0.53924[/C][C]0.921519[/C][C]0.46076[/C][/ROW]
[ROW][C]33[/C][C]0.480884[/C][C]0.961769[/C][C]0.519116[/C][/ROW]
[ROW][C]34[/C][C]0.422361[/C][C]0.844722[/C][C]0.577639[/C][/ROW]
[ROW][C]35[/C][C]0.413456[/C][C]0.826911[/C][C]0.586544[/C][/ROW]
[ROW][C]36[/C][C]0.413089[/C][C]0.826178[/C][C]0.586911[/C][/ROW]
[ROW][C]37[/C][C]0.35951[/C][C]0.719021[/C][C]0.64049[/C][/ROW]
[ROW][C]38[/C][C]0.342743[/C][C]0.685486[/C][C]0.657257[/C][/ROW]
[ROW][C]39[/C][C]0.323062[/C][C]0.646124[/C][C]0.676938[/C][/ROW]
[ROW][C]40[/C][C]0.301146[/C][C]0.602292[/C][C]0.698854[/C][/ROW]
[ROW][C]41[/C][C]0.27317[/C][C]0.54634[/C][C]0.72683[/C][/ROW]
[ROW][C]42[/C][C]0.251019[/C][C]0.502037[/C][C]0.748981[/C][/ROW]
[ROW][C]43[/C][C]0.268152[/C][C]0.536304[/C][C]0.731848[/C][/ROW]
[ROW][C]44[/C][C]0.231057[/C][C]0.462114[/C][C]0.768943[/C][/ROW]
[ROW][C]45[/C][C]0.194316[/C][C]0.388632[/C][C]0.805684[/C][/ROW]
[ROW][C]46[/C][C]0.238608[/C][C]0.477217[/C][C]0.761392[/C][/ROW]
[ROW][C]47[/C][C]0.236745[/C][C]0.473489[/C][C]0.763255[/C][/ROW]
[ROW][C]48[/C][C]0.200318[/C][C]0.400636[/C][C]0.799682[/C][/ROW]
[ROW][C]49[/C][C]0.183116[/C][C]0.366233[/C][C]0.816884[/C][/ROW]
[ROW][C]50[/C][C]0.170636[/C][C]0.341272[/C][C]0.829364[/C][/ROW]
[ROW][C]51[/C][C]0.177023[/C][C]0.354046[/C][C]0.822977[/C][/ROW]
[ROW][C]52[/C][C]0.14861[/C][C]0.297219[/C][C]0.85139[/C][/ROW]
[ROW][C]53[/C][C]0.154399[/C][C]0.308799[/C][C]0.845601[/C][/ROW]
[ROW][C]54[/C][C]0.131998[/C][C]0.263995[/C][C]0.868002[/C][/ROW]
[ROW][C]55[/C][C]0.210145[/C][C]0.42029[/C][C]0.789855[/C][/ROW]
[ROW][C]56[/C][C]0.467406[/C][C]0.934811[/C][C]0.532594[/C][/ROW]
[ROW][C]57[/C][C]0.425123[/C][C]0.850246[/C][C]0.574877[/C][/ROW]
[ROW][C]58[/C][C]0.382456[/C][C]0.764912[/C][C]0.617544[/C][/ROW]
[ROW][C]59[/C][C]0.342456[/C][C]0.684911[/C][C]0.657544[/C][/ROW]
[ROW][C]60[/C][C]0.34126[/C][C]0.68252[/C][C]0.65874[/C][/ROW]
[ROW][C]61[/C][C]0.357744[/C][C]0.715488[/C][C]0.642256[/C][/ROW]
[ROW][C]62[/C][C]0.319952[/C][C]0.639903[/C][C]0.680048[/C][/ROW]
[ROW][C]63[/C][C]0.333851[/C][C]0.667702[/C][C]0.666149[/C][/ROW]
[ROW][C]64[/C][C]0.295366[/C][C]0.590732[/C][C]0.704634[/C][/ROW]
[ROW][C]65[/C][C]0.265126[/C][C]0.530252[/C][C]0.734874[/C][/ROW]
[ROW][C]66[/C][C]0.23208[/C][C]0.464161[/C][C]0.76792[/C][/ROW]
[ROW][C]67[/C][C]0.206604[/C][C]0.413208[/C][C]0.793396[/C][/ROW]
[ROW][C]68[/C][C]0.191424[/C][C]0.382849[/C][C]0.808576[/C][/ROW]
[ROW][C]69[/C][C]0.180701[/C][C]0.361401[/C][C]0.819299[/C][/ROW]
[ROW][C]70[/C][C]0.157616[/C][C]0.315231[/C][C]0.842384[/C][/ROW]
[ROW][C]71[/C][C]0.143652[/C][C]0.287303[/C][C]0.856348[/C][/ROW]
[ROW][C]72[/C][C]0.123285[/C][C]0.24657[/C][C]0.876715[/C][/ROW]
[ROW][C]73[/C][C]0.105809[/C][C]0.211619[/C][C]0.894191[/C][/ROW]
[ROW][C]74[/C][C]0.0899023[/C][C]0.179805[/C][C]0.910098[/C][/ROW]
[ROW][C]75[/C][C]0.0804846[/C][C]0.160969[/C][C]0.919515[/C][/ROW]
[ROW][C]76[/C][C]0.10145[/C][C]0.2029[/C][C]0.89855[/C][/ROW]
[ROW][C]77[/C][C]0.08984[/C][C]0.17968[/C][C]0.91016[/C][/ROW]
[ROW][C]78[/C][C]0.0749456[/C][C]0.149891[/C][C]0.925054[/C][/ROW]
[ROW][C]79[/C][C]0.0781857[/C][C]0.156371[/C][C]0.921814[/C][/ROW]
[ROW][C]80[/C][C]0.0693071[/C][C]0.138614[/C][C]0.930693[/C][/ROW]
[ROW][C]81[/C][C]0.0576894[/C][C]0.115379[/C][C]0.942311[/C][/ROW]
[ROW][C]82[/C][C]0.0479837[/C][C]0.0959674[/C][C]0.952016[/C][/ROW]
[ROW][C]83[/C][C]0.0407055[/C][C]0.0814111[/C][C]0.959294[/C][/ROW]
[ROW][C]84[/C][C]0.0334234[/C][C]0.0668468[/C][C]0.966577[/C][/ROW]
[ROW][C]85[/C][C]0.0316874[/C][C]0.0633749[/C][C]0.968313[/C][/ROW]
[ROW][C]86[/C][C]0.0370659[/C][C]0.0741317[/C][C]0.962934[/C][/ROW]
[ROW][C]87[/C][C]0.0298399[/C][C]0.0596798[/C][C]0.97016[/C][/ROW]
[ROW][C]88[/C][C]0.0239592[/C][C]0.0479184[/C][C]0.976041[/C][/ROW]
[ROW][C]89[/C][C]0.0201483[/C][C]0.0402966[/C][C]0.979852[/C][/ROW]
[ROW][C]90[/C][C]0.0171832[/C][C]0.0343664[/C][C]0.982817[/C][/ROW]
[ROW][C]91[/C][C]0.0264371[/C][C]0.0528742[/C][C]0.973563[/C][/ROW]
[ROW][C]92[/C][C]0.0219861[/C][C]0.0439722[/C][C]0.978014[/C][/ROW]
[ROW][C]93[/C][C]0.0197095[/C][C]0.0394191[/C][C]0.98029[/C][/ROW]
[ROW][C]94[/C][C]0.0206378[/C][C]0.0412757[/C][C]0.979362[/C][/ROW]
[ROW][C]95[/C][C]0.0212122[/C][C]0.0424245[/C][C]0.978788[/C][/ROW]
[ROW][C]96[/C][C]0.0186214[/C][C]0.0372427[/C][C]0.981379[/C][/ROW]
[ROW][C]97[/C][C]0.0239623[/C][C]0.0479246[/C][C]0.976038[/C][/ROW]
[ROW][C]98[/C][C]0.0192728[/C][C]0.0385456[/C][C]0.980727[/C][/ROW]
[ROW][C]99[/C][C]0.0165628[/C][C]0.0331256[/C][C]0.983437[/C][/ROW]
[ROW][C]100[/C][C]0.0189352[/C][C]0.0378705[/C][C]0.981065[/C][/ROW]
[ROW][C]101[/C][C]0.0158266[/C][C]0.0316533[/C][C]0.984173[/C][/ROW]
[ROW][C]102[/C][C]0.0133137[/C][C]0.0266274[/C][C]0.986686[/C][/ROW]
[ROW][C]103[/C][C]0.0104308[/C][C]0.0208615[/C][C]0.989569[/C][/ROW]
[ROW][C]104[/C][C]0.00929549[/C][C]0.018591[/C][C]0.990705[/C][/ROW]
[ROW][C]105[/C][C]0.0100862[/C][C]0.0201724[/C][C]0.989914[/C][/ROW]
[ROW][C]106[/C][C]0.0078993[/C][C]0.0157986[/C][C]0.992101[/C][/ROW]
[ROW][C]107[/C][C]0.00617826[/C][C]0.0123565[/C][C]0.993822[/C][/ROW]
[ROW][C]108[/C][C]0.00513388[/C][C]0.0102678[/C][C]0.994866[/C][/ROW]
[ROW][C]109[/C][C]0.00790211[/C][C]0.0158042[/C][C]0.992098[/C][/ROW]
[ROW][C]110[/C][C]0.00615143[/C][C]0.0123029[/C][C]0.993849[/C][/ROW]
[ROW][C]111[/C][C]0.0070468[/C][C]0.0140936[/C][C]0.992953[/C][/ROW]
[ROW][C]112[/C][C]0.00749976[/C][C]0.0149995[/C][C]0.9925[/C][/ROW]
[ROW][C]113[/C][C]0.00624308[/C][C]0.0124862[/C][C]0.993757[/C][/ROW]
[ROW][C]114[/C][C]0.00494639[/C][C]0.00989278[/C][C]0.995054[/C][/ROW]
[ROW][C]115[/C][C]0.00382372[/C][C]0.00764743[/C][C]0.996176[/C][/ROW]
[ROW][C]116[/C][C]0.00419405[/C][C]0.00838809[/C][C]0.995806[/C][/ROW]
[ROW][C]117[/C][C]0.00686912[/C][C]0.0137382[/C][C]0.993131[/C][/ROW]
[ROW][C]118[/C][C]0.00561749[/C][C]0.011235[/C][C]0.994383[/C][/ROW]
[ROW][C]119[/C][C]0.00437196[/C][C]0.00874393[/C][C]0.995628[/C][/ROW]
[ROW][C]120[/C][C]0.00354702[/C][C]0.00709404[/C][C]0.996453[/C][/ROW]
[ROW][C]121[/C][C]0.00334122[/C][C]0.00668245[/C][C]0.996659[/C][/ROW]
[ROW][C]122[/C][C]0.00339687[/C][C]0.00679373[/C][C]0.996603[/C][/ROW]
[ROW][C]123[/C][C]0.0038905[/C][C]0.007781[/C][C]0.996109[/C][/ROW]
[ROW][C]124[/C][C]0.00424652[/C][C]0.00849305[/C][C]0.995753[/C][/ROW]
[ROW][C]125[/C][C]0.00795888[/C][C]0.0159178[/C][C]0.992041[/C][/ROW]
[ROW][C]126[/C][C]0.00676244[/C][C]0.0135249[/C][C]0.993238[/C][/ROW]
[ROW][C]127[/C][C]0.00583348[/C][C]0.011667[/C][C]0.994167[/C][/ROW]
[ROW][C]128[/C][C]0.00665435[/C][C]0.0133087[/C][C]0.993346[/C][/ROW]
[ROW][C]129[/C][C]0.00647816[/C][C]0.0129563[/C][C]0.993522[/C][/ROW]
[ROW][C]130[/C][C]0.00649466[/C][C]0.0129893[/C][C]0.993505[/C][/ROW]
[ROW][C]131[/C][C]0.00858019[/C][C]0.0171604[/C][C]0.99142[/C][/ROW]
[ROW][C]132[/C][C]0.0170629[/C][C]0.0341258[/C][C]0.982937[/C][/ROW]
[ROW][C]133[/C][C]0.0167839[/C][C]0.0335679[/C][C]0.983216[/C][/ROW]
[ROW][C]134[/C][C]0.0159604[/C][C]0.0319207[/C][C]0.98404[/C][/ROW]
[ROW][C]135[/C][C]0.0143118[/C][C]0.0286235[/C][C]0.985688[/C][/ROW]
[ROW][C]136[/C][C]0.0118334[/C][C]0.0236669[/C][C]0.988167[/C][/ROW]
[ROW][C]137[/C][C]0.00960382[/C][C]0.0192076[/C][C]0.990396[/C][/ROW]
[ROW][C]138[/C][C]0.00885512[/C][C]0.0177102[/C][C]0.991145[/C][/ROW]
[ROW][C]139[/C][C]0.00815124[/C][C]0.0163025[/C][C]0.991849[/C][/ROW]
[ROW][C]140[/C][C]0.00688472[/C][C]0.0137694[/C][C]0.993115[/C][/ROW]
[ROW][C]141[/C][C]0.0137593[/C][C]0.0275186[/C][C]0.986241[/C][/ROW]
[ROW][C]142[/C][C]0.0149744[/C][C]0.0299488[/C][C]0.985026[/C][/ROW]
[ROW][C]143[/C][C]0.0227087[/C][C]0.0454175[/C][C]0.977291[/C][/ROW]
[ROW][C]144[/C][C]0.0184158[/C][C]0.0368315[/C][C]0.981584[/C][/ROW]
[ROW][C]145[/C][C]0.014853[/C][C]0.029706[/C][C]0.985147[/C][/ROW]
[ROW][C]146[/C][C]0.0126155[/C][C]0.025231[/C][C]0.987384[/C][/ROW]
[ROW][C]147[/C][C]0.0152402[/C][C]0.0304804[/C][C]0.98476[/C][/ROW]
[ROW][C]148[/C][C]0.0136043[/C][C]0.0272086[/C][C]0.986396[/C][/ROW]
[ROW][C]149[/C][C]0.0115836[/C][C]0.0231672[/C][C]0.988416[/C][/ROW]
[ROW][C]150[/C][C]0.0102198[/C][C]0.0204396[/C][C]0.98978[/C][/ROW]
[ROW][C]151[/C][C]0.013192[/C][C]0.0263841[/C][C]0.986808[/C][/ROW]
[ROW][C]152[/C][C]0.0153608[/C][C]0.0307216[/C][C]0.984639[/C][/ROW]
[ROW][C]153[/C][C]0.0687806[/C][C]0.137561[/C][C]0.931219[/C][/ROW]
[ROW][C]154[/C][C]0.0688071[/C][C]0.137614[/C][C]0.931193[/C][/ROW]
[ROW][C]155[/C][C]0.0599022[/C][C]0.119804[/C][C]0.940098[/C][/ROW]
[ROW][C]156[/C][C]0.105511[/C][C]0.211023[/C][C]0.894489[/C][/ROW]
[ROW][C]157[/C][C]0.15085[/C][C]0.3017[/C][C]0.84915[/C][/ROW]
[ROW][C]158[/C][C]0.144669[/C][C]0.289338[/C][C]0.855331[/C][/ROW]
[ROW][C]159[/C][C]0.130346[/C][C]0.260692[/C][C]0.869654[/C][/ROW]
[ROW][C]160[/C][C]0.119337[/C][C]0.238674[/C][C]0.880663[/C][/ROW]
[ROW][C]161[/C][C]0.111698[/C][C]0.223396[/C][C]0.888302[/C][/ROW]
[ROW][C]162[/C][C]0.0981622[/C][C]0.196324[/C][C]0.901838[/C][/ROW]
[ROW][C]163[/C][C]0.0874813[/C][C]0.174963[/C][C]0.912519[/C][/ROW]
[ROW][C]164[/C][C]0.095219[/C][C]0.190438[/C][C]0.904781[/C][/ROW]
[ROW][C]165[/C][C]0.085822[/C][C]0.171644[/C][C]0.914178[/C][/ROW]
[ROW][C]166[/C][C]0.073111[/C][C]0.146222[/C][C]0.926889[/C][/ROW]
[ROW][C]167[/C][C]0.0625901[/C][C]0.12518[/C][C]0.93741[/C][/ROW]
[ROW][C]168[/C][C]0.103877[/C][C]0.207754[/C][C]0.896123[/C][/ROW]
[ROW][C]169[/C][C]0.105867[/C][C]0.211734[/C][C]0.894133[/C][/ROW]
[ROW][C]170[/C][C]0.0917611[/C][C]0.183522[/C][C]0.908239[/C][/ROW]
[ROW][C]171[/C][C]0.160697[/C][C]0.321393[/C][C]0.839303[/C][/ROW]
[ROW][C]172[/C][C]0.140134[/C][C]0.280269[/C][C]0.859866[/C][/ROW]
[ROW][C]173[/C][C]0.12352[/C][C]0.24704[/C][C]0.87648[/C][/ROW]
[ROW][C]174[/C][C]0.106606[/C][C]0.213212[/C][C]0.893394[/C][/ROW]
[ROW][C]175[/C][C]0.14279[/C][C]0.285579[/C][C]0.85721[/C][/ROW]
[ROW][C]176[/C][C]0.1233[/C][C]0.246599[/C][C]0.8767[/C][/ROW]
[ROW][C]177[/C][C]0.111567[/C][C]0.223133[/C][C]0.888433[/C][/ROW]
[ROW][C]178[/C][C]0.0955618[/C][C]0.191124[/C][C]0.904438[/C][/ROW]
[ROW][C]179[/C][C]0.081259[/C][C]0.162518[/C][C]0.918741[/C][/ROW]
[ROW][C]180[/C][C]0.0682605[/C][C]0.136521[/C][C]0.931739[/C][/ROW]
[ROW][C]181[/C][C]0.0575368[/C][C]0.115074[/C][C]0.942463[/C][/ROW]
[ROW][C]182[/C][C]0.065995[/C][C]0.13199[/C][C]0.934005[/C][/ROW]
[ROW][C]183[/C][C]0.0676577[/C][C]0.135315[/C][C]0.932342[/C][/ROW]
[ROW][C]184[/C][C]0.0622572[/C][C]0.124514[/C][C]0.937743[/C][/ROW]
[ROW][C]185[/C][C]0.224882[/C][C]0.449764[/C][C]0.775118[/C][/ROW]
[ROW][C]186[/C][C]0.202198[/C][C]0.404397[/C][C]0.797802[/C][/ROW]
[ROW][C]187[/C][C]0.182061[/C][C]0.364122[/C][C]0.817939[/C][/ROW]
[ROW][C]188[/C][C]0.190621[/C][C]0.381241[/C][C]0.809379[/C][/ROW]
[ROW][C]189[/C][C]0.176793[/C][C]0.353585[/C][C]0.823207[/C][/ROW]
[ROW][C]190[/C][C]0.25354[/C][C]0.507081[/C][C]0.74646[/C][/ROW]
[ROW][C]191[/C][C]0.251808[/C][C]0.503616[/C][C]0.748192[/C][/ROW]
[ROW][C]192[/C][C]0.22182[/C][C]0.443639[/C][C]0.77818[/C][/ROW]
[ROW][C]193[/C][C]0.58788[/C][C]0.824241[/C][C]0.41212[/C][/ROW]
[ROW][C]194[/C][C]0.549497[/C][C]0.901006[/C][C]0.450503[/C][/ROW]
[ROW][C]195[/C][C]0.512215[/C][C]0.975569[/C][C]0.487785[/C][/ROW]
[ROW][C]196[/C][C]0.485454[/C][C]0.970909[/C][C]0.514546[/C][/ROW]
[ROW][C]197[/C][C]0.509603[/C][C]0.980794[/C][C]0.490397[/C][/ROW]
[ROW][C]198[/C][C]0.472773[/C][C]0.945546[/C][C]0.527227[/C][/ROW]
[ROW][C]199[/C][C]0.447167[/C][C]0.894333[/C][C]0.552833[/C][/ROW]
[ROW][C]200[/C][C]0.435157[/C][C]0.870314[/C][C]0.564843[/C][/ROW]
[ROW][C]201[/C][C]0.414758[/C][C]0.829515[/C][C]0.585242[/C][/ROW]
[ROW][C]202[/C][C]0.389761[/C][C]0.779523[/C][C]0.610239[/C][/ROW]
[ROW][C]203[/C][C]0.353197[/C][C]0.706393[/C][C]0.646803[/C][/ROW]
[ROW][C]204[/C][C]0.42818[/C][C]0.85636[/C][C]0.57182[/C][/ROW]
[ROW][C]205[/C][C]0.463524[/C][C]0.927049[/C][C]0.536476[/C][/ROW]
[ROW][C]206[/C][C]0.421148[/C][C]0.842296[/C][C]0.578852[/C][/ROW]
[ROW][C]207[/C][C]0.379216[/C][C]0.758432[/C][C]0.620784[/C][/ROW]
[ROW][C]208[/C][C]0.341739[/C][C]0.683479[/C][C]0.658261[/C][/ROW]
[ROW][C]209[/C][C]0.325534[/C][C]0.651068[/C][C]0.674466[/C][/ROW]
[ROW][C]210[/C][C]0.289267[/C][C]0.578534[/C][C]0.710733[/C][/ROW]
[ROW][C]211[/C][C]0.362333[/C][C]0.724666[/C][C]0.637667[/C][/ROW]
[ROW][C]212[/C][C]0.389618[/C][C]0.779235[/C][C]0.610382[/C][/ROW]
[ROW][C]213[/C][C]0.348912[/C][C]0.697823[/C][C]0.651088[/C][/ROW]
[ROW][C]214[/C][C]0.364537[/C][C]0.729074[/C][C]0.635463[/C][/ROW]
[ROW][C]215[/C][C]0.328523[/C][C]0.657045[/C][C]0.671477[/C][/ROW]
[ROW][C]216[/C][C]0.293112[/C][C]0.586224[/C][C]0.706888[/C][/ROW]
[ROW][C]217[/C][C]0.256462[/C][C]0.512925[/C][C]0.743538[/C][/ROW]
[ROW][C]218[/C][C]0.219462[/C][C]0.438924[/C][C]0.780538[/C][/ROW]
[ROW][C]219[/C][C]0.220651[/C][C]0.441301[/C][C]0.779349[/C][/ROW]
[ROW][C]220[/C][C]0.201339[/C][C]0.402679[/C][C]0.798661[/C][/ROW]
[ROW][C]221[/C][C]0.2429[/C][C]0.4858[/C][C]0.7571[/C][/ROW]
[ROW][C]222[/C][C]0.205272[/C][C]0.410543[/C][C]0.794728[/C][/ROW]
[ROW][C]223[/C][C]0.196008[/C][C]0.392016[/C][C]0.803992[/C][/ROW]
[ROW][C]224[/C][C]0.170773[/C][C]0.341545[/C][C]0.829227[/C][/ROW]
[ROW][C]225[/C][C]0.144414[/C][C]0.288829[/C][C]0.855586[/C][/ROW]
[ROW][C]226[/C][C]0.118825[/C][C]0.23765[/C][C]0.881175[/C][/ROW]
[ROW][C]227[/C][C]0.0974006[/C][C]0.194801[/C][C]0.902599[/C][/ROW]
[ROW][C]228[/C][C]0.0787966[/C][C]0.157593[/C][C]0.921203[/C][/ROW]
[ROW][C]229[/C][C]0.060938[/C][C]0.121876[/C][C]0.939062[/C][/ROW]
[ROW][C]230[/C][C]0.0469338[/C][C]0.0938677[/C][C]0.953066[/C][/ROW]
[ROW][C]231[/C][C]0.0711776[/C][C]0.142355[/C][C]0.928822[/C][/ROW]
[ROW][C]232[/C][C]0.0891059[/C][C]0.178212[/C][C]0.910894[/C][/ROW]
[ROW][C]233[/C][C]0.269737[/C][C]0.539474[/C][C]0.730263[/C][/ROW]
[ROW][C]234[/C][C]0.231976[/C][C]0.463952[/C][C]0.768024[/C][/ROW]
[ROW][C]235[/C][C]0.189866[/C][C]0.379733[/C][C]0.810134[/C][/ROW]
[ROW][C]236[/C][C]0.184948[/C][C]0.369896[/C][C]0.815052[/C][/ROW]
[ROW][C]237[/C][C]0.183954[/C][C]0.367907[/C][C]0.816046[/C][/ROW]
[ROW][C]238[/C][C]0.257729[/C][C]0.515459[/C][C]0.742271[/C][/ROW]
[ROW][C]239[/C][C]0.262992[/C][C]0.525985[/C][C]0.737008[/C][/ROW]
[ROW][C]240[/C][C]0.218157[/C][C]0.436315[/C][C]0.781843[/C][/ROW]
[ROW][C]241[/C][C]0.172943[/C][C]0.345886[/C][C]0.827057[/C][/ROW]
[ROW][C]242[/C][C]0.247312[/C][C]0.494624[/C][C]0.752688[/C][/ROW]
[ROW][C]243[/C][C]0.526218[/C][C]0.947563[/C][C]0.473782[/C][/ROW]
[ROW][C]244[/C][C]0.665736[/C][C]0.668528[/C][C]0.334264[/C][/ROW]
[ROW][C]245[/C][C]0.596498[/C][C]0.807004[/C][C]0.403502[/C][/ROW]
[ROW][C]246[/C][C]0.544695[/C][C]0.910611[/C][C]0.455305[/C][/ROW]
[ROW][C]247[/C][C]0.492307[/C][C]0.984614[/C][C]0.507693[/C][/ROW]
[ROW][C]248[/C][C]0.406368[/C][C]0.812736[/C][C]0.593632[/C][/ROW]
[ROW][C]249[/C][C]0.315802[/C][C]0.631603[/C][C]0.684198[/C][/ROW]
[ROW][C]250[/C][C]0.32494[/C][C]0.649881[/C][C]0.67506[/C][/ROW]
[ROW][C]251[/C][C]0.451559[/C][C]0.903117[/C][C]0.548441[/C][/ROW]
[ROW][C]252[/C][C]0.617336[/C][C]0.765328[/C][C]0.382664[/C][/ROW]
[ROW][C]253[/C][C]0.668601[/C][C]0.662799[/C][C]0.331399[/C][/ROW]
[ROW][C]254[/C][C]0.701607[/C][C]0.596787[/C][C]0.298393[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221698&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221698&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
100.9954510.009098930.00454947
110.9901460.01970830.00985417
120.9802640.03947110.0197356
130.967910.06418090.0320905
140.9628060.07438740.0371937
150.9517530.09649490.0482474
160.9303750.139250.0696251
170.8971180.2057650.102882
180.9033460.1933080.096654
190.878310.243380.12169
200.8341950.331610.165805
210.7939460.4121080.206054
220.7511630.4976740.248837
230.6940880.6118230.305912
240.650680.6986390.34932
250.6031530.7936950.396847
260.6512190.6975610.348781
270.6355590.7288810.364441
280.6506790.6986430.349321
290.5908190.8183620.409181
300.5439290.9121420.456071
310.4954880.9909750.504512
320.539240.9215190.46076
330.4808840.9617690.519116
340.4223610.8447220.577639
350.4134560.8269110.586544
360.4130890.8261780.586911
370.359510.7190210.64049
380.3427430.6854860.657257
390.3230620.6461240.676938
400.3011460.6022920.698854
410.273170.546340.72683
420.2510190.5020370.748981
430.2681520.5363040.731848
440.2310570.4621140.768943
450.1943160.3886320.805684
460.2386080.4772170.761392
470.2367450.4734890.763255
480.2003180.4006360.799682
490.1831160.3662330.816884
500.1706360.3412720.829364
510.1770230.3540460.822977
520.148610.2972190.85139
530.1543990.3087990.845601
540.1319980.2639950.868002
550.2101450.420290.789855
560.4674060.9348110.532594
570.4251230.8502460.574877
580.3824560.7649120.617544
590.3424560.6849110.657544
600.341260.682520.65874
610.3577440.7154880.642256
620.3199520.6399030.680048
630.3338510.6677020.666149
640.2953660.5907320.704634
650.2651260.5302520.734874
660.232080.4641610.76792
670.2066040.4132080.793396
680.1914240.3828490.808576
690.1807010.3614010.819299
700.1576160.3152310.842384
710.1436520.2873030.856348
720.1232850.246570.876715
730.1058090.2116190.894191
740.08990230.1798050.910098
750.08048460.1609690.919515
760.101450.20290.89855
770.089840.179680.91016
780.07494560.1498910.925054
790.07818570.1563710.921814
800.06930710.1386140.930693
810.05768940.1153790.942311
820.04798370.09596740.952016
830.04070550.08141110.959294
840.03342340.06684680.966577
850.03168740.06337490.968313
860.03706590.07413170.962934
870.02983990.05967980.97016
880.02395920.04791840.976041
890.02014830.04029660.979852
900.01718320.03436640.982817
910.02643710.05287420.973563
920.02198610.04397220.978014
930.01970950.03941910.98029
940.02063780.04127570.979362
950.02121220.04242450.978788
960.01862140.03724270.981379
970.02396230.04792460.976038
980.01927280.03854560.980727
990.01656280.03312560.983437
1000.01893520.03787050.981065
1010.01582660.03165330.984173
1020.01331370.02662740.986686
1030.01043080.02086150.989569
1040.009295490.0185910.990705
1050.01008620.02017240.989914
1060.00789930.01579860.992101
1070.006178260.01235650.993822
1080.005133880.01026780.994866
1090.007902110.01580420.992098
1100.006151430.01230290.993849
1110.00704680.01409360.992953
1120.007499760.01499950.9925
1130.006243080.01248620.993757
1140.004946390.009892780.995054
1150.003823720.007647430.996176
1160.004194050.008388090.995806
1170.006869120.01373820.993131
1180.005617490.0112350.994383
1190.004371960.008743930.995628
1200.003547020.007094040.996453
1210.003341220.006682450.996659
1220.003396870.006793730.996603
1230.00389050.0077810.996109
1240.004246520.008493050.995753
1250.007958880.01591780.992041
1260.006762440.01352490.993238
1270.005833480.0116670.994167
1280.006654350.01330870.993346
1290.006478160.01295630.993522
1300.006494660.01298930.993505
1310.008580190.01716040.99142
1320.01706290.03412580.982937
1330.01678390.03356790.983216
1340.01596040.03192070.98404
1350.01431180.02862350.985688
1360.01183340.02366690.988167
1370.009603820.01920760.990396
1380.008855120.01771020.991145
1390.008151240.01630250.991849
1400.006884720.01376940.993115
1410.01375930.02751860.986241
1420.01497440.02994880.985026
1430.02270870.04541750.977291
1440.01841580.03683150.981584
1450.0148530.0297060.985147
1460.01261550.0252310.987384
1470.01524020.03048040.98476
1480.01360430.02720860.986396
1490.01158360.02316720.988416
1500.01021980.02043960.98978
1510.0131920.02638410.986808
1520.01536080.03072160.984639
1530.06878060.1375610.931219
1540.06880710.1376140.931193
1550.05990220.1198040.940098
1560.1055110.2110230.894489
1570.150850.30170.84915
1580.1446690.2893380.855331
1590.1303460.2606920.869654
1600.1193370.2386740.880663
1610.1116980.2233960.888302
1620.09816220.1963240.901838
1630.08748130.1749630.912519
1640.0952190.1904380.904781
1650.0858220.1716440.914178
1660.0731110.1462220.926889
1670.06259010.125180.93741
1680.1038770.2077540.896123
1690.1058670.2117340.894133
1700.09176110.1835220.908239
1710.1606970.3213930.839303
1720.1401340.2802690.859866
1730.123520.247040.87648
1740.1066060.2132120.893394
1750.142790.2855790.85721
1760.12330.2465990.8767
1770.1115670.2231330.888433
1780.09556180.1911240.904438
1790.0812590.1625180.918741
1800.06826050.1365210.931739
1810.05753680.1150740.942463
1820.0659950.131990.934005
1830.06765770.1353150.932342
1840.06225720.1245140.937743
1850.2248820.4497640.775118
1860.2021980.4043970.797802
1870.1820610.3641220.817939
1880.1906210.3812410.809379
1890.1767930.3535850.823207
1900.253540.5070810.74646
1910.2518080.5036160.748192
1920.221820.4436390.77818
1930.587880.8242410.41212
1940.5494970.9010060.450503
1950.5122150.9755690.487785
1960.4854540.9709090.514546
1970.5096030.9807940.490397
1980.4727730.9455460.527227
1990.4471670.8943330.552833
2000.4351570.8703140.564843
2010.4147580.8295150.585242
2020.3897610.7795230.610239
2030.3531970.7063930.646803
2040.428180.856360.57182
2050.4635240.9270490.536476
2060.4211480.8422960.578852
2070.3792160.7584320.620784
2080.3417390.6834790.658261
2090.3255340.6510680.674466
2100.2892670.5785340.710733
2110.3623330.7246660.637667
2120.3896180.7792350.610382
2130.3489120.6978230.651088
2140.3645370.7290740.635463
2150.3285230.6570450.671477
2160.2931120.5862240.706888
2170.2564620.5129250.743538
2180.2194620.4389240.780538
2190.2206510.4413010.779349
2200.2013390.4026790.798661
2210.24290.48580.7571
2220.2052720.4105430.794728
2230.1960080.3920160.803992
2240.1707730.3415450.829227
2250.1444140.2888290.855586
2260.1188250.237650.881175
2270.09740060.1948010.902599
2280.07879660.1575930.921203
2290.0609380.1218760.939062
2300.04693380.09386770.953066
2310.07117760.1423550.928822
2320.08910590.1782120.910894
2330.2697370.5394740.730263
2340.2319760.4639520.768024
2350.1898660.3797330.810134
2360.1849480.3698960.815052
2370.1839540.3679070.816046
2380.2577290.5154590.742271
2390.2629920.5259850.737008
2400.2181570.4363150.781843
2410.1729430.3458860.827057
2420.2473120.4946240.752688
2430.5262180.9475630.473782
2440.6657360.6685280.334264
2450.5964980.8070040.403502
2460.5446950.9106110.455305
2470.4923070.9846140.507693
2480.4063680.8127360.593632
2490.3158020.6316030.684198
2500.324940.6498810.67506
2510.4515590.9031170.548441
2520.6173360.7653280.382664
2530.6686010.6627990.331399
2540.7016070.5967870.298393






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level100.0408163NOK
5% type I error level670.273469NOK
10% type I error level780.318367NOK

\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 & 10 & 0.0408163 & NOK \tabularnewline
5% type I error level & 67 & 0.273469 & NOK \tabularnewline
10% type I error level & 78 & 0.318367 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221698&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]10[/C][C]0.0408163[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]67[/C][C]0.273469[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]78[/C][C]0.318367[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221698&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221698&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 level100.0408163NOK
5% type I error level670.273469NOK
10% type I error level780.318367NOK


Figures (Output of Computation)

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

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