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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 09 Nov 2014 14:03:23 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/09/t1415542079foh6k7vh9ms8pxg.htm/, Retrieved Sat, 11 May 2024 19:21:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=253181, Retrieved Sat, 11 May 2024 19:21:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2013-11-04 07:18:26] [0307e7a6407eb638caabc417e3a6b260]
-  MPD    [Multiple Regression] [] [2014-11-09 14:03:23] [f235c2d73cdbd6a2c0ce149cb9653e7d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 13 12 14 12 32
39 32 16 11 18 11 51
30 35 19 15 11 14 42
31 33 15 6 12 12 41
34 37 14 13 16 21 46
35 29 13 10 18 12 47
39 31 19 12 14 22 37
34 36 15 14 14 11 49
36 35 14 12 15 10 45
37 38 15 9 15 13 47
38 31 16 10 17 10 49
36 34 16 12 19 8 33
38 35 16 12 10 15 42
39 38 16 11 16 14 33
33 37 17 15 18 10 53
32 33 15 12 14 14 36
36 32 15 10 14 14 45
38 38 20 12 17 11 54
39 38 18 11 14 10 41
32 32 16 12 16 13 36
32 33 16 11 18 9.5 41
31 31 16 12 11 14 44
39 38 19 13 14 12 33
37 39 16 11 12 14 37
39 32 17 12 17 11 52
41 32 17 13 9 9 47
36 35 16 10 16 11 43
33 37 15 14 14 15 44
33 33 16 12 15 14 45
34 33 14 10 11 13 44
31 31 15 12 16 9 49
27 32 12 8 13 15 33
37 31 14 10 17 10 43
34 37 16 12 15 11 54
34 30 14 12 14 13 42
32 33 10 7 16 8 44
29 31 10 9 9 20 37
36 33 14 12 15 12 43
29 31 16 10 17 10 46
35 33 16 10 13 10 42
37 32 16 10 15 9 45
34 33 14 12 16 14 44
38 32 20 15 16 8 33
35 33 14 10 12 14 31
38 28 14 10 15 11 42
37 35 11 12 11 13 40
38 39 14 13 15 9 43
33 34 15 11 15 11 46
36 38 16 11 17 15 42
38 32 14 12 13 11 45
32 38 16 14 16 10 44
32 30 14 10 14 14 40
32 33 12 12 11 18 37
34 38 16 13 12 14 46
32 32 9 5 12 11 36
37 35 14 6 15 14.5 47
39 34 16 12 16 13 45
29 34 16 12 15 9 42
37 36 15 11 12 10 43
35 34 16 10 12 15 43
30 28 12 7 8 20 32
38 34 16 12 13 12 45
34 35 16 14 11 12 48
31 35 14 11 14 14 31
34 31 16 12 15 13 33
35 37 17 13 10 11 49
36 35 18 14 11 17 42
30 27 18 11 12 12 41
39 40 12 12 15 13 38
35 37 16 12 15 14 42
38 36 10 8 14 13 44
31 38 14 11 16 15 33
34 39 18 14 15 13 48
38 41 18 14 15 10 40
34 27 16 12 13 11 50
39 30 17 9 12 19 49
37 37 16 13 17 13 43
34 31 16 11 13 17 44
28 31 13 12 15 13 47
37 27 16 12 13 9 33
33 36 16 12 15 11 46
35 37 16 12 15 9 45
37 33 15 12 16 12 43
32 34 15 11 15 12 44
33 31 16 10 14 13 47
38 39 14 9 15 13 45
33 34 16 12 14 12 42
29 32 16 12 13 15 33
33 33 15 12 7 22 43
31 36 12 9 17 13 46
36 32 17 15 13 15 33
35 41 16 12 15 13 46
32 28 15 12 14 15 48
29 30 13 12 13 12.5 47
39 36 16 10 16 11 47
37 35 16 13 12 16 43
35 31 16 9 14 11 46
37 34 16 12 17 11 48
32 36 14 10 15 10 46
38 36 16 14 17 10 45
37 35 16 11 12 16 45
36 37 20 15 16 12 52
32 28 15 11 11 11 42
33 39 16 11 15 16 47
40 32 13 12 9 19 41
38 35 17 12 16 11 47
41 39 16 12 15 16 43
36 35 16 11 10 15 33
43 42 12 7 10 24 30
30 34 16 12 15 14 52
31 33 16 14 11 15 44
32 41 17 11 13 11 55
32 33 13 11 14 15 11
37 34 12 10 18 12 47
37 32 18 13 16 10 53
33 40 14 13 14 14 33
34 40 14 8 14 13 44
33 35 13 11 14 9 42
38 36 16 12 14 15 55
33 37 13 11 12 15 33
31 27 16 13 14 14 46
38 39 13 12 15 11 54
37 38 16 14 15 8 47
36 31 15 13 15 11 45
31 33 16 15 13 11 47
39 32 15 10 17 8 55
44 39 17 11 17 10 44
33 36 15 9 19 11 53
35 33 12 11 15 13 44
32 33 16 10 13 11 42
28 32 10 11 9 20 40
40 37 16 8 15 10 46
27 30 12 11 15 15 40
37 38 14 12 15 12 46
32 29 15 12 16 14 53
28 22 13 9 11 23 33
34 35 15 11 14 14 42
30 35 11 10 11 16 35
35 34 12 8 15 11 40
31 35 11 9 13 12 41
32 34 16 8 15 10 33
30 37 15 9 16 14 51
30 35 17 15 14 12 53
31 23 16 11 15 12 46
40 31 10 8 16 11 55
32 27 18 13 16 12 47
36 36 13 12 11 13 38
32 31 16 12 12 11 46
35 32 13 9 9 19 46
38 39 10 7 16 12 53
42 37 15 13 13 17 47
34 38 16 9 16 9 41
35 39 16 6 12 12 44
38 34 14 8 9 19 43
33 31 10 8 13 18 51
36 32 17 15 13 15 33
32 37 13 6 14 14 43
33 36 15 9 19 11 53
34 32 16 11 13 9 51
32 38 12 8 12 18 50
34 36 13 8 13 16 46
27 26 13 10 10 24 43
31 26 12 8 14 14 47
38 33 17 14 16 20 50
34 39 15 10 10 18 43
24 30 10 8 11 23 33
30 33 14 11 14 12 48
26 25 11 12 12 14 44
34 38 13 12 9 16 50
27 37 16 12 9 18 41
37 31 12 5 11 20 34
36 37 16 12 16 12 44
41 35 12 10 9 12 47
29 25 9 7 13 17 35
36 28 12 12 16 13 44
32 35 15 11 13 9 44
37 33 12 8 9 16 43
30 30 12 9 12 18 41
31 31 14 10 16 10 41
38 37 12 9 11 14 42
36 36 16 12 14 11 33
35 30 11 6 13 9 41
31 36 19 15 15 11 44
38 32 15 12 14 10 48
22 28 8 12 16 11 55
32 36 16 12 13 19 44
36 34 17 11 14 14 43
39 31 12 7 15 12 52
28 28 11 7 13 14 30
32 36 11 5 11 21 39
32 36 14 12 11 13 11
38 40 16 12 14 10 44
32 33 12 3 15 15 42
35 37 16 11 11 16 41
32 32 13 10 15 14 44
37 38 15 12 12 12 44
34 31 16 9 14 19 48
33 37 16 12 14 15 53
33 33 14 9 8 19 37
26 32 16 12 13 13 44
30 30 16 12 9 17 44
24 30 14 10 15 12 40
34 31 11 9 17 11 42
34 32 12 12 13 14 35
33 34 15 8 15 11 43
34 36 15 11 15 13 45
35 37 16 11 14 12 55
35 36 16 12 16 15 31
36 33 11 10 13 14 44
34 33 15 10 16 12 50
34 33 12 12 9 17 40
41 44 12 12 16 11 53
32 39 15 11 11 18 54
30 32 15 8 10 13 49
35 35 16 12 11 17 40
28 25 14 10 15 13 41
33 35 17 11 17 11 52
39 34 14 10 14 12 52
36 35 13 8 8 22 36
36 39 15 12 15 14 52
35 33 13 12 11 12 46
38 36 14 10 16 12 31
33 32 15 12 10 17 44
31 32 12 9 15 9 44
34 36 13 9 9 21 11
32 36 8 6 16 10 46
31 32 14 10 19 11 33
33 34 14 9 12 12 34
34 33 11 9 8 23 42
34 35 12 9 11 13 43
34 30 13 6 14 12 43
33 38 10 10 9 16 44
32 34 16 6 15 9 36
41 33 18 14 13 17 46
34 32 13 10 16 9 44
36 31 11 10 11 14 43
37 30 4 6 12 17 50
36 27 13 12 13 13 33
29 31 16 12 10 11 43
37 30 10 7 11 12 44
27 32 12 8 12 10 53
35 35 12 11 8 19 34
28 28 10 3 12 16 35
35 33 13 6 12 16 40
37 31 15 10 15 14 53
29 35 12 8 11 20 42
32 35 14 9 13 15 43
36 32 10 9 14 23 29
19 21 12 8 10 20 36
21 20 12 9 12 16 30
31 34 11 7 15 14 42
33 32 10 7 13 17 47
36 34 12 6 13 11 44
33 32 16 9 13 13 45
37 33 12 10 12 17 44
34 33 14 11 12 15 43
35 37 16 12 9 21 43
31 32 14 8 9 18 40
37 34 13 11 15 15 41
35 30 4 3 10 8 52
27 30 15 11 14 12 38
34 38 11 12 15 12 41
40 36 11 7 7 22 39
29 32 14 9 14 12 43

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253181&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253181&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253181&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 time8 seconds
R Server'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 28.8067 -0.0321267Connected[t] + 0.00640344Separate[t] -0.0935099Learning[t] -0.0299331Software[t] -0.729032Happiness[t] -0.065641Sport2[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Depression[t] =  +  28.8067 -0.0321267Connected[t] +  0.00640344Separate[t] -0.0935099Learning[t] -0.0299331Software[t] -0.729032Happiness[t] -0.065641Sport2[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253181&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Depression[t] =  +  28.8067 -0.0321267Connected[t] +  0.00640344Separate[t] -0.0935099Learning[t] -0.0299331Software[t] -0.729032Happiness[t] -0.065641Sport2[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253181&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253181&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 28.8067 -0.0321267Connected[t] + 0.00640344Separate[t] -0.0935099Learning[t] -0.0299331Software[t] -0.729032Happiness[t] -0.065641Sport2[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)28.80672.1076513.672.47921e-321.23961e-32
Connected-0.03212670.0516366-0.62220.5343820.267191
Separate0.006403440.05302820.12080.9039790.45199
Learning-0.09350990.0925068-1.0110.3130420.156521
Software-0.02993310.0952876-0.31410.7536740.376837
Happiness-0.7290320.073548-9.9128.00739e-204.00369e-20
Sport2-0.0656410.0262005-2.5050.01285290.00642645

\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) & 28.8067 & 2.10765 & 13.67 & 2.47921e-32 & 1.23961e-32 \tabularnewline
Connected & -0.0321267 & 0.0516366 & -0.6222 & 0.534382 & 0.267191 \tabularnewline
Separate & 0.00640344 & 0.0530282 & 0.1208 & 0.903979 & 0.45199 \tabularnewline
Learning & -0.0935099 & 0.0925068 & -1.011 & 0.313042 & 0.156521 \tabularnewline
Software & -0.0299331 & 0.0952876 & -0.3141 & 0.753674 & 0.376837 \tabularnewline
Happiness & -0.729032 & 0.073548 & -9.912 & 8.00739e-20 & 4.00369e-20 \tabularnewline
Sport2 & -0.065641 & 0.0262005 & -2.505 & 0.0128529 & 0.00642645 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253181&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]28.8067[/C][C]2.10765[/C][C]13.67[/C][C]2.47921e-32[/C][C]1.23961e-32[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0321267[/C][C]0.0516366[/C][C]-0.6222[/C][C]0.534382[/C][C]0.267191[/C][/ROW]
[ROW][C]Separate[/C][C]0.00640344[/C][C]0.0530282[/C][C]0.1208[/C][C]0.903979[/C][C]0.45199[/C][/ROW]
[ROW][C]Learning[/C][C]-0.0935099[/C][C]0.0925068[/C][C]-1.011[/C][C]0.313042[/C][C]0.156521[/C][/ROW]
[ROW][C]Software[/C][C]-0.0299331[/C][C]0.0952876[/C][C]-0.3141[/C][C]0.753674[/C][C]0.376837[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.729032[/C][C]0.073548[/C][C]-9.912[/C][C]8.00739e-20[/C][C]4.00369e-20[/C][/ROW]
[ROW][C]Sport2[/C][C]-0.065641[/C][C]0.0262005[/C][C]-2.505[/C][C]0.0128529[/C][C]0.00642645[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253181&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253181&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)28.80672.1076513.672.47921e-321.23961e-32
Connected-0.03212670.0516366-0.62220.5343820.267191
Separate0.006403440.05302820.12080.9039790.45199
Learning-0.09350990.0925068-1.0110.3130420.156521
Software-0.02993310.0952876-0.31410.7536740.376837
Happiness-0.7290320.073548-9.9128.00739e-204.00369e-20
Sport2-0.0656410.0262005-2.5050.01285290.00642645






Multiple Linear Regression - Regression Statistics
Multiple R0.60459
R-squared0.365529
Adjusted R-squared0.350716
F-TEST (value)24.6769
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.79571
Sum Squared Residuals2008.71

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.60459 \tabularnewline
R-squared & 0.365529 \tabularnewline
Adjusted R-squared & 0.350716 \tabularnewline
F-TEST (value) & 24.6769 \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 & 2.79571 \tabularnewline
Sum Squared Residuals & 2008.71 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253181&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.60459[/C][/ROW]
[ROW][C]R-squared[/C][C]0.365529[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.350716[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]24.6769[/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]2.79571[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2008.71[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253181&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253181&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 R0.60459
R-squared0.365529
Adjusted R-squared0.350716
F-TEST (value)24.6769
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.79571
Sum Squared Residuals2008.71






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.851-1.85102
2119.462951.53705
31415.065-1.06503
41215.0001-3.00015
52111.5699.43097
61210.14531.85472
72212.98129.01881
81112.7003-1.70032
91012.3166-2.31657
101312.16870.831338
111010.3789-0.378923
1289.99471-1.99471
131515.9074-0.907379
141412.1411.85903
15109.343210.656793
161413.65860.341438
171412.99271.00725
18119.661641.33836
191012.8869-2.88689
201312.10060.899415
219.510.3507-0.850654
221415.2463-1.24634
231213.2586-1.25864
241414.8652-0.865194
251110.00290.997099
26916.0692-7.06917
271111.5917-0.591668
281513.06711.93295
291412.21311.78688
301315.4097-2.40965
31911.3665-2.36649
321515.139-0.139008
331010.9919-0.991916
341111.6158-0.615843
351313.2748-0.274762
36812.2926-4.29259
372017.8792.121
381212.435-0.435046
391010.865-0.864987
401013.8637-3.86372
41912.1381-3.13808
421411.70462.29537
43811.6409-3.64091
441415.5018-1.50183
451112.4643-1.46428
461315.8093-2.80931
47912.3793-3.37928
481112.2773-1.27733
491510.91764.08245
501113.6912-2.69117
511011.554-1.55401
521413.53020.469836
531816.06051.93946
541414.3045-0.304536
551115.8808-4.88081
5614.512.33282.16724
571311.29771.70226
58912.545-3.54496
591014.5456-4.54565
601514.53350.466483
612018.75771.24225
621213.517-1.51696
631214.8531-2.85314
641414.1551-0.155143
651312.95590.0441173
661115.4336-4.43364
671714.99572.00429
681214.5637-2.56366
691312.89870.101285
701412.37141.62859
711313.5472-0.547166
721512.5852.41499
731311.77561.22439
741012.185-2.18504
751113.2724-2.27244
761913.9225.07803
771310.75352.24648
781713.72183.27817
791312.51020.489801
80914.292-5.29195
811112.1667-1.16669
82912.1745-3.17448
831211.58040.419622
841212.4407-0.440739
851312.85790.142066
861312.36770.632269
871213.1455-1.14548
881514.5810.419017
892218.27023.72983
901311.23671.76328
911514.17280.827213
921312.13450.865542
931512.83892.16115
9412.513.9297-1.42973
951111.2391-0.239127
961614.38591.61413
971112.8893-1.88925
981110.4360.563965
991012.4457-2.44571
1001010.5538-0.553772
1011614.31451.68555
1021210.491.51
1031115.4497-4.44973
1041612.15023.8498
1051916.89912.10088
1061111.1115-0.111475
1071612.12583.87419
1081516.5923-1.59233
1092417.1036.89703
1101411.85642.14358
1111515.1993-0.199279
1121113.0346-2.03456
1131515.5165-0.516539
1141210.20661.79345
1151010.6071-0.607102
1161413.93180.0682414
1171313.3272-0.327247
118913.4623-4.46235
1191512.14432.85568
1201515.524-0.523988
1211412.87241.12759
1221111.7807-0.780673
123811.9255-3.92549
1241112.1675-1.16751
1251113.5144-2.51436
126810.0529-2.05286
1271010.4422-0.442152
128118.974392.02561
1291312.61850.381515
1301113.9601-2.9601
1312017.66072.33926
1321012.0679-2.06794
1331513.11891.88115
1341212.238-0.238014
1351411.0592.94101
1362316.37756.62253
1371413.24320.756798
1381616.4223-0.422263
1391112.9773-1.97725
1401214.5682-2.56816
1411013.1591-3.15908
1421411.39562.60445
1431212.3429-0.342906
1441212.1776-0.177636
1451111.2708-0.270781
1461211.12960.870436
1471315.7921-2.7921
1481114.3539-3.3539
1491916.82132.17865
1501211.54750.452523
1511713.343.66004
152911.8363-2.83635
1531214.6196-2.61963
1541916.87112.12888
1551813.94534.05467
1561514.17280.827213
1571413.59130.408693
158118.974392.02561
159913.2687-4.26874
1601814.62993.37007
1611613.99292.00711
1622416.47797.5221
1631413.32410.675924
1642010.84199.15812
1651816.14921.85077
1662316.86776.13234
1671213.0586-1.05857
1681415.1071-1.10707
1691616.5395-0.539529
1701817.06830.931748
1712016.29363.70644
1721211.4790.521032
1731216.6457-4.64573
1741715.20911.79089
1751311.79541.20462
176913.9052-4.90521
1771617.0839-1.08386
1781815.20382.79621
1791012.045-2.04499
1801415.655-1.65499
1811113.6527-2.65268
182914.4974-5.49744
1831111.9919-0.9919
1841012.6717-2.67171
1851111.8971-0.897139
1861913.78825.21183
1871412.91991.08012
1881212.0718-0.0717759
1891415.4016-1.40163
1902116.25154.74848
1911317.5994-4.5994
1921012.892-2.89199
1931513.08561.91439
1941615.38310.616892
1951412.64491.35512
1961214.4629-2.46288
1971912.79016.2099
1981512.44262.55736
1991918.11830.881708
2001313.9553-0.955312
2011716.73010.269875
2021213.0581-1.05815
2031111.4644-0.4644
2041414.6631-0.663107
2051112.5641-1.56405
2061312.32370.676349
2071212.277-0.27704
2081512.3582.64198
2091414.1679-0.167864
2101211.27710.722862
2111717.2574-0.257432
2121111.1464-0.146429
2131814.73253.26753
2141315.8989-2.89894
2151715.4061.59399
2161312.8320.168019
2171110.24480.755195
2181212.5432-0.543199
2192218.22383.7762
2201411.78922.21081
2211215.2799-3.27989
2221212.5085-0.508529
2231716.0110.98897
224912.8005-3.80045
2252119.17651.82348
2261012.3975-2.39747
2271110.38940.610574
2281215.4055-3.40549
2292318.03854.96151
2301315.7051-2.70505
2311213.4822-1.48223
2321617.3059-1.3059
233913.022-4.02202
2341713.10163.89835
235911.8516-2.8516
2361415.6788-1.67876
2371715.2261.77399
2381314.6046-1.60461
2391116.1053-5.10526
2401215.7579-3.7579
2411014.5552-4.55522
2421918.39090.609078
2431616.0157-0.015703
2441615.12430.875701
2451411.70012.29994
2462015.96134.03874
2471514.12420.875778
2482314.54058.45951
2492017.31582.68424
2501616.1509-0.150949
2511413.09790.90208
2521714.24422.75577
2531114.2005-3.20049
2541313.7546-0.754584
2551714.77132.22874
2561514.71630.283673
2572116.684.32004
2581817.28010.719879
2591512.6642.33595
260816.7068-8.70685
2611213.6986-1.69864
2621212.9431-0.943129
2632218.85083.14924
2641213.4724-1.47236

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 13.851 & -1.85102 \tabularnewline
2 & 11 & 9.46295 & 1.53705 \tabularnewline
3 & 14 & 15.065 & -1.06503 \tabularnewline
4 & 12 & 15.0001 & -3.00015 \tabularnewline
5 & 21 & 11.569 & 9.43097 \tabularnewline
6 & 12 & 10.1453 & 1.85472 \tabularnewline
7 & 22 & 12.9812 & 9.01881 \tabularnewline
8 & 11 & 12.7003 & -1.70032 \tabularnewline
9 & 10 & 12.3166 & -2.31657 \tabularnewline
10 & 13 & 12.1687 & 0.831338 \tabularnewline
11 & 10 & 10.3789 & -0.378923 \tabularnewline
12 & 8 & 9.99471 & -1.99471 \tabularnewline
13 & 15 & 15.9074 & -0.907379 \tabularnewline
14 & 14 & 12.141 & 1.85903 \tabularnewline
15 & 10 & 9.34321 & 0.656793 \tabularnewline
16 & 14 & 13.6586 & 0.341438 \tabularnewline
17 & 14 & 12.9927 & 1.00725 \tabularnewline
18 & 11 & 9.66164 & 1.33836 \tabularnewline
19 & 10 & 12.8869 & -2.88689 \tabularnewline
20 & 13 & 12.1006 & 0.899415 \tabularnewline
21 & 9.5 & 10.3507 & -0.850654 \tabularnewline
22 & 14 & 15.2463 & -1.24634 \tabularnewline
23 & 12 & 13.2586 & -1.25864 \tabularnewline
24 & 14 & 14.8652 & -0.865194 \tabularnewline
25 & 11 & 10.0029 & 0.997099 \tabularnewline
26 & 9 & 16.0692 & -7.06917 \tabularnewline
27 & 11 & 11.5917 & -0.591668 \tabularnewline
28 & 15 & 13.0671 & 1.93295 \tabularnewline
29 & 14 & 12.2131 & 1.78688 \tabularnewline
30 & 13 & 15.4097 & -2.40965 \tabularnewline
31 & 9 & 11.3665 & -2.36649 \tabularnewline
32 & 15 & 15.139 & -0.139008 \tabularnewline
33 & 10 & 10.9919 & -0.991916 \tabularnewline
34 & 11 & 11.6158 & -0.615843 \tabularnewline
35 & 13 & 13.2748 & -0.274762 \tabularnewline
36 & 8 & 12.2926 & -4.29259 \tabularnewline
37 & 20 & 17.879 & 2.121 \tabularnewline
38 & 12 & 12.435 & -0.435046 \tabularnewline
39 & 10 & 10.865 & -0.864987 \tabularnewline
40 & 10 & 13.8637 & -3.86372 \tabularnewline
41 & 9 & 12.1381 & -3.13808 \tabularnewline
42 & 14 & 11.7046 & 2.29537 \tabularnewline
43 & 8 & 11.6409 & -3.64091 \tabularnewline
44 & 14 & 15.5018 & -1.50183 \tabularnewline
45 & 11 & 12.4643 & -1.46428 \tabularnewline
46 & 13 & 15.8093 & -2.80931 \tabularnewline
47 & 9 & 12.3793 & -3.37928 \tabularnewline
48 & 11 & 12.2773 & -1.27733 \tabularnewline
49 & 15 & 10.9176 & 4.08245 \tabularnewline
50 & 11 & 13.6912 & -2.69117 \tabularnewline
51 & 10 & 11.554 & -1.55401 \tabularnewline
52 & 14 & 13.5302 & 0.469836 \tabularnewline
53 & 18 & 16.0605 & 1.93946 \tabularnewline
54 & 14 & 14.3045 & -0.304536 \tabularnewline
55 & 11 & 15.8808 & -4.88081 \tabularnewline
56 & 14.5 & 12.3328 & 2.16724 \tabularnewline
57 & 13 & 11.2977 & 1.70226 \tabularnewline
58 & 9 & 12.545 & -3.54496 \tabularnewline
59 & 10 & 14.5456 & -4.54565 \tabularnewline
60 & 15 & 14.5335 & 0.466483 \tabularnewline
61 & 20 & 18.7577 & 1.24225 \tabularnewline
62 & 12 & 13.517 & -1.51696 \tabularnewline
63 & 12 & 14.8531 & -2.85314 \tabularnewline
64 & 14 & 14.1551 & -0.155143 \tabularnewline
65 & 13 & 12.9559 & 0.0441173 \tabularnewline
66 & 11 & 15.4336 & -4.43364 \tabularnewline
67 & 17 & 14.9957 & 2.00429 \tabularnewline
68 & 12 & 14.5637 & -2.56366 \tabularnewline
69 & 13 & 12.8987 & 0.101285 \tabularnewline
70 & 14 & 12.3714 & 1.62859 \tabularnewline
71 & 13 & 13.5472 & -0.547166 \tabularnewline
72 & 15 & 12.585 & 2.41499 \tabularnewline
73 & 13 & 11.7756 & 1.22439 \tabularnewline
74 & 10 & 12.185 & -2.18504 \tabularnewline
75 & 11 & 13.2724 & -2.27244 \tabularnewline
76 & 19 & 13.922 & 5.07803 \tabularnewline
77 & 13 & 10.7535 & 2.24648 \tabularnewline
78 & 17 & 13.7218 & 3.27817 \tabularnewline
79 & 13 & 12.5102 & 0.489801 \tabularnewline
80 & 9 & 14.292 & -5.29195 \tabularnewline
81 & 11 & 12.1667 & -1.16669 \tabularnewline
82 & 9 & 12.1745 & -3.17448 \tabularnewline
83 & 12 & 11.5804 & 0.419622 \tabularnewline
84 & 12 & 12.4407 & -0.440739 \tabularnewline
85 & 13 & 12.8579 & 0.142066 \tabularnewline
86 & 13 & 12.3677 & 0.632269 \tabularnewline
87 & 12 & 13.1455 & -1.14548 \tabularnewline
88 & 15 & 14.581 & 0.419017 \tabularnewline
89 & 22 & 18.2702 & 3.72983 \tabularnewline
90 & 13 & 11.2367 & 1.76328 \tabularnewline
91 & 15 & 14.1728 & 0.827213 \tabularnewline
92 & 13 & 12.1345 & 0.865542 \tabularnewline
93 & 15 & 12.8389 & 2.16115 \tabularnewline
94 & 12.5 & 13.9297 & -1.42973 \tabularnewline
95 & 11 & 11.2391 & -0.239127 \tabularnewline
96 & 16 & 14.3859 & 1.61413 \tabularnewline
97 & 11 & 12.8893 & -1.88925 \tabularnewline
98 & 11 & 10.436 & 0.563965 \tabularnewline
99 & 10 & 12.4457 & -2.44571 \tabularnewline
100 & 10 & 10.5538 & -0.553772 \tabularnewline
101 & 16 & 14.3145 & 1.68555 \tabularnewline
102 & 12 & 10.49 & 1.51 \tabularnewline
103 & 11 & 15.4497 & -4.44973 \tabularnewline
104 & 16 & 12.1502 & 3.8498 \tabularnewline
105 & 19 & 16.8991 & 2.10088 \tabularnewline
106 & 11 & 11.1115 & -0.111475 \tabularnewline
107 & 16 & 12.1258 & 3.87419 \tabularnewline
108 & 15 & 16.5923 & -1.59233 \tabularnewline
109 & 24 & 17.103 & 6.89703 \tabularnewline
110 & 14 & 11.8564 & 2.14358 \tabularnewline
111 & 15 & 15.1993 & -0.199279 \tabularnewline
112 & 11 & 13.0346 & -2.03456 \tabularnewline
113 & 15 & 15.5165 & -0.516539 \tabularnewline
114 & 12 & 10.2066 & 1.79345 \tabularnewline
115 & 10 & 10.6071 & -0.607102 \tabularnewline
116 & 14 & 13.9318 & 0.0682414 \tabularnewline
117 & 13 & 13.3272 & -0.327247 \tabularnewline
118 & 9 & 13.4623 & -4.46235 \tabularnewline
119 & 15 & 12.1443 & 2.85568 \tabularnewline
120 & 15 & 15.524 & -0.523988 \tabularnewline
121 & 14 & 12.8724 & 1.12759 \tabularnewline
122 & 11 & 11.7807 & -0.780673 \tabularnewline
123 & 8 & 11.9255 & -3.92549 \tabularnewline
124 & 11 & 12.1675 & -1.16751 \tabularnewline
125 & 11 & 13.5144 & -2.51436 \tabularnewline
126 & 8 & 10.0529 & -2.05286 \tabularnewline
127 & 10 & 10.4422 & -0.442152 \tabularnewline
128 & 11 & 8.97439 & 2.02561 \tabularnewline
129 & 13 & 12.6185 & 0.381515 \tabularnewline
130 & 11 & 13.9601 & -2.9601 \tabularnewline
131 & 20 & 17.6607 & 2.33926 \tabularnewline
132 & 10 & 12.0679 & -2.06794 \tabularnewline
133 & 15 & 13.1189 & 1.88115 \tabularnewline
134 & 12 & 12.238 & -0.238014 \tabularnewline
135 & 14 & 11.059 & 2.94101 \tabularnewline
136 & 23 & 16.3775 & 6.62253 \tabularnewline
137 & 14 & 13.2432 & 0.756798 \tabularnewline
138 & 16 & 16.4223 & -0.422263 \tabularnewline
139 & 11 & 12.9773 & -1.97725 \tabularnewline
140 & 12 & 14.5682 & -2.56816 \tabularnewline
141 & 10 & 13.1591 & -3.15908 \tabularnewline
142 & 14 & 11.3956 & 2.60445 \tabularnewline
143 & 12 & 12.3429 & -0.342906 \tabularnewline
144 & 12 & 12.1776 & -0.177636 \tabularnewline
145 & 11 & 11.2708 & -0.270781 \tabularnewline
146 & 12 & 11.1296 & 0.870436 \tabularnewline
147 & 13 & 15.7921 & -2.7921 \tabularnewline
148 & 11 & 14.3539 & -3.3539 \tabularnewline
149 & 19 & 16.8213 & 2.17865 \tabularnewline
150 & 12 & 11.5475 & 0.452523 \tabularnewline
151 & 17 & 13.34 & 3.66004 \tabularnewline
152 & 9 & 11.8363 & -2.83635 \tabularnewline
153 & 12 & 14.6196 & -2.61963 \tabularnewline
154 & 19 & 16.8711 & 2.12888 \tabularnewline
155 & 18 & 13.9453 & 4.05467 \tabularnewline
156 & 15 & 14.1728 & 0.827213 \tabularnewline
157 & 14 & 13.5913 & 0.408693 \tabularnewline
158 & 11 & 8.97439 & 2.02561 \tabularnewline
159 & 9 & 13.2687 & -4.26874 \tabularnewline
160 & 18 & 14.6299 & 3.37007 \tabularnewline
161 & 16 & 13.9929 & 2.00711 \tabularnewline
162 & 24 & 16.4779 & 7.5221 \tabularnewline
163 & 14 & 13.3241 & 0.675924 \tabularnewline
164 & 20 & 10.8419 & 9.15812 \tabularnewline
165 & 18 & 16.1492 & 1.85077 \tabularnewline
166 & 23 & 16.8677 & 6.13234 \tabularnewline
167 & 12 & 13.0586 & -1.05857 \tabularnewline
168 & 14 & 15.1071 & -1.10707 \tabularnewline
169 & 16 & 16.5395 & -0.539529 \tabularnewline
170 & 18 & 17.0683 & 0.931748 \tabularnewline
171 & 20 & 16.2936 & 3.70644 \tabularnewline
172 & 12 & 11.479 & 0.521032 \tabularnewline
173 & 12 & 16.6457 & -4.64573 \tabularnewline
174 & 17 & 15.2091 & 1.79089 \tabularnewline
175 & 13 & 11.7954 & 1.20462 \tabularnewline
176 & 9 & 13.9052 & -4.90521 \tabularnewline
177 & 16 & 17.0839 & -1.08386 \tabularnewline
178 & 18 & 15.2038 & 2.79621 \tabularnewline
179 & 10 & 12.045 & -2.04499 \tabularnewline
180 & 14 & 15.655 & -1.65499 \tabularnewline
181 & 11 & 13.6527 & -2.65268 \tabularnewline
182 & 9 & 14.4974 & -5.49744 \tabularnewline
183 & 11 & 11.9919 & -0.9919 \tabularnewline
184 & 10 & 12.6717 & -2.67171 \tabularnewline
185 & 11 & 11.8971 & -0.897139 \tabularnewline
186 & 19 & 13.7882 & 5.21183 \tabularnewline
187 & 14 & 12.9199 & 1.08012 \tabularnewline
188 & 12 & 12.0718 & -0.0717759 \tabularnewline
189 & 14 & 15.4016 & -1.40163 \tabularnewline
190 & 21 & 16.2515 & 4.74848 \tabularnewline
191 & 13 & 17.5994 & -4.5994 \tabularnewline
192 & 10 & 12.892 & -2.89199 \tabularnewline
193 & 15 & 13.0856 & 1.91439 \tabularnewline
194 & 16 & 15.3831 & 0.616892 \tabularnewline
195 & 14 & 12.6449 & 1.35512 \tabularnewline
196 & 12 & 14.4629 & -2.46288 \tabularnewline
197 & 19 & 12.7901 & 6.2099 \tabularnewline
198 & 15 & 12.4426 & 2.55736 \tabularnewline
199 & 19 & 18.1183 & 0.881708 \tabularnewline
200 & 13 & 13.9553 & -0.955312 \tabularnewline
201 & 17 & 16.7301 & 0.269875 \tabularnewline
202 & 12 & 13.0581 & -1.05815 \tabularnewline
203 & 11 & 11.4644 & -0.4644 \tabularnewline
204 & 14 & 14.6631 & -0.663107 \tabularnewline
205 & 11 & 12.5641 & -1.56405 \tabularnewline
206 & 13 & 12.3237 & 0.676349 \tabularnewline
207 & 12 & 12.277 & -0.27704 \tabularnewline
208 & 15 & 12.358 & 2.64198 \tabularnewline
209 & 14 & 14.1679 & -0.167864 \tabularnewline
210 & 12 & 11.2771 & 0.722862 \tabularnewline
211 & 17 & 17.2574 & -0.257432 \tabularnewline
212 & 11 & 11.1464 & -0.146429 \tabularnewline
213 & 18 & 14.7325 & 3.26753 \tabularnewline
214 & 13 & 15.8989 & -2.89894 \tabularnewline
215 & 17 & 15.406 & 1.59399 \tabularnewline
216 & 13 & 12.832 & 0.168019 \tabularnewline
217 & 11 & 10.2448 & 0.755195 \tabularnewline
218 & 12 & 12.5432 & -0.543199 \tabularnewline
219 & 22 & 18.2238 & 3.7762 \tabularnewline
220 & 14 & 11.7892 & 2.21081 \tabularnewline
221 & 12 & 15.2799 & -3.27989 \tabularnewline
222 & 12 & 12.5085 & -0.508529 \tabularnewline
223 & 17 & 16.011 & 0.98897 \tabularnewline
224 & 9 & 12.8005 & -3.80045 \tabularnewline
225 & 21 & 19.1765 & 1.82348 \tabularnewline
226 & 10 & 12.3975 & -2.39747 \tabularnewline
227 & 11 & 10.3894 & 0.610574 \tabularnewline
228 & 12 & 15.4055 & -3.40549 \tabularnewline
229 & 23 & 18.0385 & 4.96151 \tabularnewline
230 & 13 & 15.7051 & -2.70505 \tabularnewline
231 & 12 & 13.4822 & -1.48223 \tabularnewline
232 & 16 & 17.3059 & -1.3059 \tabularnewline
233 & 9 & 13.022 & -4.02202 \tabularnewline
234 & 17 & 13.1016 & 3.89835 \tabularnewline
235 & 9 & 11.8516 & -2.8516 \tabularnewline
236 & 14 & 15.6788 & -1.67876 \tabularnewline
237 & 17 & 15.226 & 1.77399 \tabularnewline
238 & 13 & 14.6046 & -1.60461 \tabularnewline
239 & 11 & 16.1053 & -5.10526 \tabularnewline
240 & 12 & 15.7579 & -3.7579 \tabularnewline
241 & 10 & 14.5552 & -4.55522 \tabularnewline
242 & 19 & 18.3909 & 0.609078 \tabularnewline
243 & 16 & 16.0157 & -0.015703 \tabularnewline
244 & 16 & 15.1243 & 0.875701 \tabularnewline
245 & 14 & 11.7001 & 2.29994 \tabularnewline
246 & 20 & 15.9613 & 4.03874 \tabularnewline
247 & 15 & 14.1242 & 0.875778 \tabularnewline
248 & 23 & 14.5405 & 8.45951 \tabularnewline
249 & 20 & 17.3158 & 2.68424 \tabularnewline
250 & 16 & 16.1509 & -0.150949 \tabularnewline
251 & 14 & 13.0979 & 0.90208 \tabularnewline
252 & 17 & 14.2442 & 2.75577 \tabularnewline
253 & 11 & 14.2005 & -3.20049 \tabularnewline
254 & 13 & 13.7546 & -0.754584 \tabularnewline
255 & 17 & 14.7713 & 2.22874 \tabularnewline
256 & 15 & 14.7163 & 0.283673 \tabularnewline
257 & 21 & 16.68 & 4.32004 \tabularnewline
258 & 18 & 17.2801 & 0.719879 \tabularnewline
259 & 15 & 12.664 & 2.33595 \tabularnewline
260 & 8 & 16.7068 & -8.70685 \tabularnewline
261 & 12 & 13.6986 & -1.69864 \tabularnewline
262 & 12 & 12.9431 & -0.943129 \tabularnewline
263 & 22 & 18.8508 & 3.14924 \tabularnewline
264 & 12 & 13.4724 & -1.47236 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253181&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]13.851[/C][C]-1.85102[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]9.46295[/C][C]1.53705[/C][/ROW]
[ROW][C]3[/C][C]14[/C][C]15.065[/C][C]-1.06503[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]15.0001[/C][C]-3.00015[/C][/ROW]
[ROW][C]5[/C][C]21[/C][C]11.569[/C][C]9.43097[/C][/ROW]
[ROW][C]6[/C][C]12[/C][C]10.1453[/C][C]1.85472[/C][/ROW]
[ROW][C]7[/C][C]22[/C][C]12.9812[/C][C]9.01881[/C][/ROW]
[ROW][C]8[/C][C]11[/C][C]12.7003[/C][C]-1.70032[/C][/ROW]
[ROW][C]9[/C][C]10[/C][C]12.3166[/C][C]-2.31657[/C][/ROW]
[ROW][C]10[/C][C]13[/C][C]12.1687[/C][C]0.831338[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]10.3789[/C][C]-0.378923[/C][/ROW]
[ROW][C]12[/C][C]8[/C][C]9.99471[/C][C]-1.99471[/C][/ROW]
[ROW][C]13[/C][C]15[/C][C]15.9074[/C][C]-0.907379[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]12.141[/C][C]1.85903[/C][/ROW]
[ROW][C]15[/C][C]10[/C][C]9.34321[/C][C]0.656793[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.6586[/C][C]0.341438[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]12.9927[/C][C]1.00725[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]9.66164[/C][C]1.33836[/C][/ROW]
[ROW][C]19[/C][C]10[/C][C]12.8869[/C][C]-2.88689[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]12.1006[/C][C]0.899415[/C][/ROW]
[ROW][C]21[/C][C]9.5[/C][C]10.3507[/C][C]-0.850654[/C][/ROW]
[ROW][C]22[/C][C]14[/C][C]15.2463[/C][C]-1.24634[/C][/ROW]
[ROW][C]23[/C][C]12[/C][C]13.2586[/C][C]-1.25864[/C][/ROW]
[ROW][C]24[/C][C]14[/C][C]14.8652[/C][C]-0.865194[/C][/ROW]
[ROW][C]25[/C][C]11[/C][C]10.0029[/C][C]0.997099[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]16.0692[/C][C]-7.06917[/C][/ROW]
[ROW][C]27[/C][C]11[/C][C]11.5917[/C][C]-0.591668[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]13.0671[/C][C]1.93295[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]12.2131[/C][C]1.78688[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]15.4097[/C][C]-2.40965[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]11.3665[/C][C]-2.36649[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]15.139[/C][C]-0.139008[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.9919[/C][C]-0.991916[/C][/ROW]
[ROW][C]34[/C][C]11[/C][C]11.6158[/C][C]-0.615843[/C][/ROW]
[ROW][C]35[/C][C]13[/C][C]13.2748[/C][C]-0.274762[/C][/ROW]
[ROW][C]36[/C][C]8[/C][C]12.2926[/C][C]-4.29259[/C][/ROW]
[ROW][C]37[/C][C]20[/C][C]17.879[/C][C]2.121[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]12.435[/C][C]-0.435046[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.865[/C][C]-0.864987[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]13.8637[/C][C]-3.86372[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]12.1381[/C][C]-3.13808[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]11.7046[/C][C]2.29537[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]11.6409[/C][C]-3.64091[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]15.5018[/C][C]-1.50183[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]12.4643[/C][C]-1.46428[/C][/ROW]
[ROW][C]46[/C][C]13[/C][C]15.8093[/C][C]-2.80931[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]12.3793[/C][C]-3.37928[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]12.2773[/C][C]-1.27733[/C][/ROW]
[ROW][C]49[/C][C]15[/C][C]10.9176[/C][C]4.08245[/C][/ROW]
[ROW][C]50[/C][C]11[/C][C]13.6912[/C][C]-2.69117[/C][/ROW]
[ROW][C]51[/C][C]10[/C][C]11.554[/C][C]-1.55401[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.5302[/C][C]0.469836[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]16.0605[/C][C]1.93946[/C][/ROW]
[ROW][C]54[/C][C]14[/C][C]14.3045[/C][C]-0.304536[/C][/ROW]
[ROW][C]55[/C][C]11[/C][C]15.8808[/C][C]-4.88081[/C][/ROW]
[ROW][C]56[/C][C]14.5[/C][C]12.3328[/C][C]2.16724[/C][/ROW]
[ROW][C]57[/C][C]13[/C][C]11.2977[/C][C]1.70226[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]12.545[/C][C]-3.54496[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]14.5456[/C][C]-4.54565[/C][/ROW]
[ROW][C]60[/C][C]15[/C][C]14.5335[/C][C]0.466483[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]18.7577[/C][C]1.24225[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]13.517[/C][C]-1.51696[/C][/ROW]
[ROW][C]63[/C][C]12[/C][C]14.8531[/C][C]-2.85314[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.1551[/C][C]-0.155143[/C][/ROW]
[ROW][C]65[/C][C]13[/C][C]12.9559[/C][C]0.0441173[/C][/ROW]
[ROW][C]66[/C][C]11[/C][C]15.4336[/C][C]-4.43364[/C][/ROW]
[ROW][C]67[/C][C]17[/C][C]14.9957[/C][C]2.00429[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.5637[/C][C]-2.56366[/C][/ROW]
[ROW][C]69[/C][C]13[/C][C]12.8987[/C][C]0.101285[/C][/ROW]
[ROW][C]70[/C][C]14[/C][C]12.3714[/C][C]1.62859[/C][/ROW]
[ROW][C]71[/C][C]13[/C][C]13.5472[/C][C]-0.547166[/C][/ROW]
[ROW][C]72[/C][C]15[/C][C]12.585[/C][C]2.41499[/C][/ROW]
[ROW][C]73[/C][C]13[/C][C]11.7756[/C][C]1.22439[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]12.185[/C][C]-2.18504[/C][/ROW]
[ROW][C]75[/C][C]11[/C][C]13.2724[/C][C]-2.27244[/C][/ROW]
[ROW][C]76[/C][C]19[/C][C]13.922[/C][C]5.07803[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.7535[/C][C]2.24648[/C][/ROW]
[ROW][C]78[/C][C]17[/C][C]13.7218[/C][C]3.27817[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]12.5102[/C][C]0.489801[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]14.292[/C][C]-5.29195[/C][/ROW]
[ROW][C]81[/C][C]11[/C][C]12.1667[/C][C]-1.16669[/C][/ROW]
[ROW][C]82[/C][C]9[/C][C]12.1745[/C][C]-3.17448[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]11.5804[/C][C]0.419622[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]12.4407[/C][C]-0.440739[/C][/ROW]
[ROW][C]85[/C][C]13[/C][C]12.8579[/C][C]0.142066[/C][/ROW]
[ROW][C]86[/C][C]13[/C][C]12.3677[/C][C]0.632269[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]13.1455[/C][C]-1.14548[/C][/ROW]
[ROW][C]88[/C][C]15[/C][C]14.581[/C][C]0.419017[/C][/ROW]
[ROW][C]89[/C][C]22[/C][C]18.2702[/C][C]3.72983[/C][/ROW]
[ROW][C]90[/C][C]13[/C][C]11.2367[/C][C]1.76328[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]14.1728[/C][C]0.827213[/C][/ROW]
[ROW][C]92[/C][C]13[/C][C]12.1345[/C][C]0.865542[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]12.8389[/C][C]2.16115[/C][/ROW]
[ROW][C]94[/C][C]12.5[/C][C]13.9297[/C][C]-1.42973[/C][/ROW]
[ROW][C]95[/C][C]11[/C][C]11.2391[/C][C]-0.239127[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]14.3859[/C][C]1.61413[/C][/ROW]
[ROW][C]97[/C][C]11[/C][C]12.8893[/C][C]-1.88925[/C][/ROW]
[ROW][C]98[/C][C]11[/C][C]10.436[/C][C]0.563965[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]12.4457[/C][C]-2.44571[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]10.5538[/C][C]-0.553772[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.3145[/C][C]1.68555[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]10.49[/C][C]1.51[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]15.4497[/C][C]-4.44973[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]12.1502[/C][C]3.8498[/C][/ROW]
[ROW][C]105[/C][C]19[/C][C]16.8991[/C][C]2.10088[/C][/ROW]
[ROW][C]106[/C][C]11[/C][C]11.1115[/C][C]-0.111475[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]12.1258[/C][C]3.87419[/C][/ROW]
[ROW][C]108[/C][C]15[/C][C]16.5923[/C][C]-1.59233[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]17.103[/C][C]6.89703[/C][/ROW]
[ROW][C]110[/C][C]14[/C][C]11.8564[/C][C]2.14358[/C][/ROW]
[ROW][C]111[/C][C]15[/C][C]15.1993[/C][C]-0.199279[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]13.0346[/C][C]-2.03456[/C][/ROW]
[ROW][C]113[/C][C]15[/C][C]15.5165[/C][C]-0.516539[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]10.2066[/C][C]1.79345[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]10.6071[/C][C]-0.607102[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.9318[/C][C]0.0682414[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]13.3272[/C][C]-0.327247[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]13.4623[/C][C]-4.46235[/C][/ROW]
[ROW][C]119[/C][C]15[/C][C]12.1443[/C][C]2.85568[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]15.524[/C][C]-0.523988[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]12.8724[/C][C]1.12759[/C][/ROW]
[ROW][C]122[/C][C]11[/C][C]11.7807[/C][C]-0.780673[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]11.9255[/C][C]-3.92549[/C][/ROW]
[ROW][C]124[/C][C]11[/C][C]12.1675[/C][C]-1.16751[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]13.5144[/C][C]-2.51436[/C][/ROW]
[ROW][C]126[/C][C]8[/C][C]10.0529[/C][C]-2.05286[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]10.4422[/C][C]-0.442152[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]8.97439[/C][C]2.02561[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]12.6185[/C][C]0.381515[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]13.9601[/C][C]-2.9601[/C][/ROW]
[ROW][C]131[/C][C]20[/C][C]17.6607[/C][C]2.33926[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]12.0679[/C][C]-2.06794[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]13.1189[/C][C]1.88115[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]12.238[/C][C]-0.238014[/C][/ROW]
[ROW][C]135[/C][C]14[/C][C]11.059[/C][C]2.94101[/C][/ROW]
[ROW][C]136[/C][C]23[/C][C]16.3775[/C][C]6.62253[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.2432[/C][C]0.756798[/C][/ROW]
[ROW][C]138[/C][C]16[/C][C]16.4223[/C][C]-0.422263[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]12.9773[/C][C]-1.97725[/C][/ROW]
[ROW][C]140[/C][C]12[/C][C]14.5682[/C][C]-2.56816[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]13.1591[/C][C]-3.15908[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]11.3956[/C][C]2.60445[/C][/ROW]
[ROW][C]143[/C][C]12[/C][C]12.3429[/C][C]-0.342906[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]12.1776[/C][C]-0.177636[/C][/ROW]
[ROW][C]145[/C][C]11[/C][C]11.2708[/C][C]-0.270781[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]11.1296[/C][C]0.870436[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.7921[/C][C]-2.7921[/C][/ROW]
[ROW][C]148[/C][C]11[/C][C]14.3539[/C][C]-3.3539[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]16.8213[/C][C]2.17865[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]11.5475[/C][C]0.452523[/C][/ROW]
[ROW][C]151[/C][C]17[/C][C]13.34[/C][C]3.66004[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.8363[/C][C]-2.83635[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.6196[/C][C]-2.61963[/C][/ROW]
[ROW][C]154[/C][C]19[/C][C]16.8711[/C][C]2.12888[/C][/ROW]
[ROW][C]155[/C][C]18[/C][C]13.9453[/C][C]4.05467[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]14.1728[/C][C]0.827213[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.5913[/C][C]0.408693[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]8.97439[/C][C]2.02561[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]13.2687[/C][C]-4.26874[/C][/ROW]
[ROW][C]160[/C][C]18[/C][C]14.6299[/C][C]3.37007[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]13.9929[/C][C]2.00711[/C][/ROW]
[ROW][C]162[/C][C]24[/C][C]16.4779[/C][C]7.5221[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.3241[/C][C]0.675924[/C][/ROW]
[ROW][C]164[/C][C]20[/C][C]10.8419[/C][C]9.15812[/C][/ROW]
[ROW][C]165[/C][C]18[/C][C]16.1492[/C][C]1.85077[/C][/ROW]
[ROW][C]166[/C][C]23[/C][C]16.8677[/C][C]6.13234[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]13.0586[/C][C]-1.05857[/C][/ROW]
[ROW][C]168[/C][C]14[/C][C]15.1071[/C][C]-1.10707[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]16.5395[/C][C]-0.539529[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]17.0683[/C][C]0.931748[/C][/ROW]
[ROW][C]171[/C][C]20[/C][C]16.2936[/C][C]3.70644[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.479[/C][C]0.521032[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]16.6457[/C][C]-4.64573[/C][/ROW]
[ROW][C]174[/C][C]17[/C][C]15.2091[/C][C]1.79089[/C][/ROW]
[ROW][C]175[/C][C]13[/C][C]11.7954[/C][C]1.20462[/C][/ROW]
[ROW][C]176[/C][C]9[/C][C]13.9052[/C][C]-4.90521[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]17.0839[/C][C]-1.08386[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]15.2038[/C][C]2.79621[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]12.045[/C][C]-2.04499[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]15.655[/C][C]-1.65499[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]13.6527[/C][C]-2.65268[/C][/ROW]
[ROW][C]182[/C][C]9[/C][C]14.4974[/C][C]-5.49744[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]11.9919[/C][C]-0.9919[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]12.6717[/C][C]-2.67171[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]11.8971[/C][C]-0.897139[/C][/ROW]
[ROW][C]186[/C][C]19[/C][C]13.7882[/C][C]5.21183[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]12.9199[/C][C]1.08012[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.0718[/C][C]-0.0717759[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]15.4016[/C][C]-1.40163[/C][/ROW]
[ROW][C]190[/C][C]21[/C][C]16.2515[/C][C]4.74848[/C][/ROW]
[ROW][C]191[/C][C]13[/C][C]17.5994[/C][C]-4.5994[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]12.892[/C][C]-2.89199[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]13.0856[/C][C]1.91439[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]15.3831[/C][C]0.616892[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]12.6449[/C][C]1.35512[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.4629[/C][C]-2.46288[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]12.7901[/C][C]6.2099[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]12.4426[/C][C]2.55736[/C][/ROW]
[ROW][C]199[/C][C]19[/C][C]18.1183[/C][C]0.881708[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.9553[/C][C]-0.955312[/C][/ROW]
[ROW][C]201[/C][C]17[/C][C]16.7301[/C][C]0.269875[/C][/ROW]
[ROW][C]202[/C][C]12[/C][C]13.0581[/C][C]-1.05815[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]11.4644[/C][C]-0.4644[/C][/ROW]
[ROW][C]204[/C][C]14[/C][C]14.6631[/C][C]-0.663107[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]12.5641[/C][C]-1.56405[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]12.3237[/C][C]0.676349[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]12.277[/C][C]-0.27704[/C][/ROW]
[ROW][C]208[/C][C]15[/C][C]12.358[/C][C]2.64198[/C][/ROW]
[ROW][C]209[/C][C]14[/C][C]14.1679[/C][C]-0.167864[/C][/ROW]
[ROW][C]210[/C][C]12[/C][C]11.2771[/C][C]0.722862[/C][/ROW]
[ROW][C]211[/C][C]17[/C][C]17.2574[/C][C]-0.257432[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]11.1464[/C][C]-0.146429[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]14.7325[/C][C]3.26753[/C][/ROW]
[ROW][C]214[/C][C]13[/C][C]15.8989[/C][C]-2.89894[/C][/ROW]
[ROW][C]215[/C][C]17[/C][C]15.406[/C][C]1.59399[/C][/ROW]
[ROW][C]216[/C][C]13[/C][C]12.832[/C][C]0.168019[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]10.2448[/C][C]0.755195[/C][/ROW]
[ROW][C]218[/C][C]12[/C][C]12.5432[/C][C]-0.543199[/C][/ROW]
[ROW][C]219[/C][C]22[/C][C]18.2238[/C][C]3.7762[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]11.7892[/C][C]2.21081[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]15.2799[/C][C]-3.27989[/C][/ROW]
[ROW][C]222[/C][C]12[/C][C]12.5085[/C][C]-0.508529[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]16.011[/C][C]0.98897[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]12.8005[/C][C]-3.80045[/C][/ROW]
[ROW][C]225[/C][C]21[/C][C]19.1765[/C][C]1.82348[/C][/ROW]
[ROW][C]226[/C][C]10[/C][C]12.3975[/C][C]-2.39747[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]10.3894[/C][C]0.610574[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]15.4055[/C][C]-3.40549[/C][/ROW]
[ROW][C]229[/C][C]23[/C][C]18.0385[/C][C]4.96151[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]15.7051[/C][C]-2.70505[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]13.4822[/C][C]-1.48223[/C][/ROW]
[ROW][C]232[/C][C]16[/C][C]17.3059[/C][C]-1.3059[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]13.022[/C][C]-4.02202[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]13.1016[/C][C]3.89835[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]11.8516[/C][C]-2.8516[/C][/ROW]
[ROW][C]236[/C][C]14[/C][C]15.6788[/C][C]-1.67876[/C][/ROW]
[ROW][C]237[/C][C]17[/C][C]15.226[/C][C]1.77399[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.6046[/C][C]-1.60461[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]16.1053[/C][C]-5.10526[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]15.7579[/C][C]-3.7579[/C][/ROW]
[ROW][C]241[/C][C]10[/C][C]14.5552[/C][C]-4.55522[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]18.3909[/C][C]0.609078[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]16.0157[/C][C]-0.015703[/C][/ROW]
[ROW][C]244[/C][C]16[/C][C]15.1243[/C][C]0.875701[/C][/ROW]
[ROW][C]245[/C][C]14[/C][C]11.7001[/C][C]2.29994[/C][/ROW]
[ROW][C]246[/C][C]20[/C][C]15.9613[/C][C]4.03874[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]14.1242[/C][C]0.875778[/C][/ROW]
[ROW][C]248[/C][C]23[/C][C]14.5405[/C][C]8.45951[/C][/ROW]
[ROW][C]249[/C][C]20[/C][C]17.3158[/C][C]2.68424[/C][/ROW]
[ROW][C]250[/C][C]16[/C][C]16.1509[/C][C]-0.150949[/C][/ROW]
[ROW][C]251[/C][C]14[/C][C]13.0979[/C][C]0.90208[/C][/ROW]
[ROW][C]252[/C][C]17[/C][C]14.2442[/C][C]2.75577[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]14.2005[/C][C]-3.20049[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.7546[/C][C]-0.754584[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]14.7713[/C][C]2.22874[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]14.7163[/C][C]0.283673[/C][/ROW]
[ROW][C]257[/C][C]21[/C][C]16.68[/C][C]4.32004[/C][/ROW]
[ROW][C]258[/C][C]18[/C][C]17.2801[/C][C]0.719879[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.664[/C][C]2.33595[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]16.7068[/C][C]-8.70685[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]13.6986[/C][C]-1.69864[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]12.9431[/C][C]-0.943129[/C][/ROW]
[ROW][C]263[/C][C]22[/C][C]18.8508[/C][C]3.14924[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]13.4724[/C][C]-1.47236[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253181&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253181&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.851-1.85102
2119.462951.53705
31415.065-1.06503
41215.0001-3.00015
52111.5699.43097
61210.14531.85472
72212.98129.01881
81112.7003-1.70032
91012.3166-2.31657
101312.16870.831338
111010.3789-0.378923
1289.99471-1.99471
131515.9074-0.907379
141412.1411.85903
15109.343210.656793
161413.65860.341438
171412.99271.00725
18119.661641.33836
191012.8869-2.88689
201312.10060.899415
219.510.3507-0.850654
221415.2463-1.24634
231213.2586-1.25864
241414.8652-0.865194
251110.00290.997099
26916.0692-7.06917
271111.5917-0.591668
281513.06711.93295
291412.21311.78688
301315.4097-2.40965
31911.3665-2.36649
321515.139-0.139008
331010.9919-0.991916
341111.6158-0.615843
351313.2748-0.274762
36812.2926-4.29259
372017.8792.121
381212.435-0.435046
391010.865-0.864987
401013.8637-3.86372
41912.1381-3.13808
421411.70462.29537
43811.6409-3.64091
441415.5018-1.50183
451112.4643-1.46428
461315.8093-2.80931
47912.3793-3.37928
481112.2773-1.27733
491510.91764.08245
501113.6912-2.69117
511011.554-1.55401
521413.53020.469836
531816.06051.93946
541414.3045-0.304536
551115.8808-4.88081
5614.512.33282.16724
571311.29771.70226
58912.545-3.54496
591014.5456-4.54565
601514.53350.466483
612018.75771.24225
621213.517-1.51696
631214.8531-2.85314
641414.1551-0.155143
651312.95590.0441173
661115.4336-4.43364
671714.99572.00429
681214.5637-2.56366
691312.89870.101285
701412.37141.62859
711313.5472-0.547166
721512.5852.41499
731311.77561.22439
741012.185-2.18504
751113.2724-2.27244
761913.9225.07803
771310.75352.24648
781713.72183.27817
791312.51020.489801
80914.292-5.29195
811112.1667-1.16669
82912.1745-3.17448
831211.58040.419622
841212.4407-0.440739
851312.85790.142066
861312.36770.632269
871213.1455-1.14548
881514.5810.419017
892218.27023.72983
901311.23671.76328
911514.17280.827213
921312.13450.865542
931512.83892.16115
9412.513.9297-1.42973
951111.2391-0.239127
961614.38591.61413
971112.8893-1.88925
981110.4360.563965
991012.4457-2.44571
1001010.5538-0.553772
1011614.31451.68555
1021210.491.51
1031115.4497-4.44973
1041612.15023.8498
1051916.89912.10088
1061111.1115-0.111475
1071612.12583.87419
1081516.5923-1.59233
1092417.1036.89703
1101411.85642.14358
1111515.1993-0.199279
1121113.0346-2.03456
1131515.5165-0.516539
1141210.20661.79345
1151010.6071-0.607102
1161413.93180.0682414
1171313.3272-0.327247
118913.4623-4.46235
1191512.14432.85568
1201515.524-0.523988
1211412.87241.12759
1221111.7807-0.780673
123811.9255-3.92549
1241112.1675-1.16751
1251113.5144-2.51436
126810.0529-2.05286
1271010.4422-0.442152
128118.974392.02561
1291312.61850.381515
1301113.9601-2.9601
1312017.66072.33926
1321012.0679-2.06794
1331513.11891.88115
1341212.238-0.238014
1351411.0592.94101
1362316.37756.62253
1371413.24320.756798
1381616.4223-0.422263
1391112.9773-1.97725
1401214.5682-2.56816
1411013.1591-3.15908
1421411.39562.60445
1431212.3429-0.342906
1441212.1776-0.177636
1451111.2708-0.270781
1461211.12960.870436
1471315.7921-2.7921
1481114.3539-3.3539
1491916.82132.17865
1501211.54750.452523
1511713.343.66004
152911.8363-2.83635
1531214.6196-2.61963
1541916.87112.12888
1551813.94534.05467
1561514.17280.827213
1571413.59130.408693
158118.974392.02561
159913.2687-4.26874
1601814.62993.37007
1611613.99292.00711
1622416.47797.5221
1631413.32410.675924
1642010.84199.15812
1651816.14921.85077
1662316.86776.13234
1671213.0586-1.05857
1681415.1071-1.10707
1691616.5395-0.539529
1701817.06830.931748
1712016.29363.70644
1721211.4790.521032
1731216.6457-4.64573
1741715.20911.79089
1751311.79541.20462
176913.9052-4.90521
1771617.0839-1.08386
1781815.20382.79621
1791012.045-2.04499
1801415.655-1.65499
1811113.6527-2.65268
182914.4974-5.49744
1831111.9919-0.9919
1841012.6717-2.67171
1851111.8971-0.897139
1861913.78825.21183
1871412.91991.08012
1881212.0718-0.0717759
1891415.4016-1.40163
1902116.25154.74848
1911317.5994-4.5994
1921012.892-2.89199
1931513.08561.91439
1941615.38310.616892
1951412.64491.35512
1961214.4629-2.46288
1971912.79016.2099
1981512.44262.55736
1991918.11830.881708
2001313.9553-0.955312
2011716.73010.269875
2021213.0581-1.05815
2031111.4644-0.4644
2041414.6631-0.663107
2051112.5641-1.56405
2061312.32370.676349
2071212.277-0.27704
2081512.3582.64198
2091414.1679-0.167864
2101211.27710.722862
2111717.2574-0.257432
2121111.1464-0.146429
2131814.73253.26753
2141315.8989-2.89894
2151715.4061.59399
2161312.8320.168019
2171110.24480.755195
2181212.5432-0.543199
2192218.22383.7762
2201411.78922.21081
2211215.2799-3.27989
2221212.5085-0.508529
2231716.0110.98897
224912.8005-3.80045
2252119.17651.82348
2261012.3975-2.39747
2271110.38940.610574
2281215.4055-3.40549
2292318.03854.96151
2301315.7051-2.70505
2311213.4822-1.48223
2321617.3059-1.3059
233913.022-4.02202
2341713.10163.89835
235911.8516-2.8516
2361415.6788-1.67876
2371715.2261.77399
2381314.6046-1.60461
2391116.1053-5.10526
2401215.7579-3.7579
2411014.5552-4.55522
2421918.39090.609078
2431616.0157-0.015703
2441615.12430.875701
2451411.70012.29994
2462015.96134.03874
2471514.12420.875778
2482314.54058.45951
2492017.31582.68424
2501616.1509-0.150949
2511413.09790.90208
2521714.24422.75577
2531114.2005-3.20049
2541313.7546-0.754584
2551714.77132.22874
2561514.71630.283673
2572116.684.32004
2581817.28010.719879
2591512.6642.33595
260816.7068-8.70685
2611213.6986-1.69864
2621212.9431-0.943129
2632218.85083.14924
2641213.4724-1.47236






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.9396040.1207930.0603964
110.9039180.1921650.0960824
120.9993380.00132340.0006617
130.9986070.002786820.00139341
140.9971870.005626960.00281348
150.9954340.009132240.00456612
160.9918580.01628430.00814215
170.9861320.02773520.0138676
180.9787990.04240190.0212009
190.9790890.04182210.0209111
200.9677360.06452850.0322642
210.955280.08944090.0447204
220.9391160.1217680.060884
230.923510.152980.0764902
240.8968980.2062050.103102
250.8711040.2577920.128896
260.9519180.09616410.048082
270.9356990.1286020.0643009
280.9224420.1551160.0775582
290.9029240.1941520.0970759
300.8779860.2440280.122014
310.8804190.2391610.119581
320.851260.2974810.14874
330.8247150.350570.175285
340.7868050.4263910.213195
350.7435870.5128260.256413
360.7536810.4926390.246319
370.8101360.3797280.189864
380.7728210.4543570.227179
390.740630.5187390.25937
400.7456640.5086720.254336
410.7356870.5286260.264313
420.7109050.578190.289095
430.7681050.4637910.231895
440.7308680.5382630.269132
450.6915430.6169140.308457
460.6709530.6580940.329047
470.6888340.6223330.311166
480.651780.6964410.34822
490.6850620.6298760.314938
500.6575460.6849080.342454
510.6442640.7114710.355736
520.6054860.7890290.394514
530.6044730.7910540.395527
540.5606510.8786990.439349
550.5818390.8363220.418161
560.6002720.7994560.399728
570.5754810.8490380.424519
580.6080190.7839610.391981
590.6346420.7307170.365358
600.6077540.7844920.392246
610.6215750.756850.378425
620.584650.8307010.41535
630.564610.870780.43539
640.5221350.9557310.477865
650.4795240.9590480.520476
660.4944010.9888020.505599
670.5012710.9974570.498729
680.484060.9681210.51594
690.4431110.8862220.556889
700.4178480.8356950.582152
710.3791770.7583550.620823
720.3593030.7186060.640697
730.3282320.6564650.671768
740.3175870.6351750.682413
750.2941980.5883950.705802
760.4434740.8869490.556526
770.4244780.8489570.575522
780.4545860.9091720.545414
790.4173530.8347060.582647
800.4970630.9941250.502937
810.4651610.9303220.534839
820.4760340.9520680.523966
830.4383360.8766730.561664
840.4009670.8019340.599033
850.3646920.7293840.635308
860.3311990.6623980.668801
870.3010680.6021360.698932
880.2708240.5416480.729176
890.3500770.7001550.649923
900.3269270.6538540.673073
910.300860.6017210.69914
920.2711180.5422350.728882
930.2618990.5237990.738101
940.237690.475380.76231
950.2095990.4191990.790401
960.1978290.3956570.802171
970.182570.3651410.81743
980.1592180.3184360.840782
990.1536310.3072620.846369
1000.1337740.2675490.866226
1010.1253830.2507660.874617
1020.1103530.2207050.889647
1030.1319330.2638650.868067
1040.1487420.2974830.851258
1050.1538220.3076430.846178
1060.133060.266120.86694
1070.1506250.3012490.849375
1080.1351790.2703580.864821
1090.2599630.5199250.740037
1100.2506440.5012880.749356
1110.224040.4480790.77596
1120.2141950.4283890.785805
1130.1890350.378070.810965
1140.1742860.3485720.825714
1150.1531170.3062350.846883
1160.132980.2659610.86702
1170.1154670.2309340.884533
1180.1426680.2853350.857332
1190.142350.28470.85765
1200.1232730.2465470.876727
1210.1121470.2242940.887853
1220.09779350.1955870.902206
1230.1158550.231710.884145
1240.1019330.2038670.898067
1250.09786130.1957230.902139
1260.09208510.184170.907915
1270.07987580.1597520.920124
1280.07333710.1466740.926663
1290.06205420.1241080.937946
1300.06295380.1259080.937046
1310.06398280.1279660.936017
1320.06000770.1200150.939992
1330.05545750.1109150.944543
1340.0462280.0924560.953772
1350.0474160.0948320.952584
1360.1076440.2152880.892356
1370.09297520.185950.907025
1380.07909790.1581960.920902
1390.07278350.1455670.927216
1400.07002760.1400550.929972
1410.07334540.1466910.926655
1420.07179680.1435940.928203
1430.06061740.1212350.939383
1440.05083630.1016730.949164
1450.0422210.0844420.957779
1460.03520590.07041180.964794
1470.0350320.07006390.964968
1480.03870070.07740140.961299
1490.03639480.07278950.963605
1500.03014170.06028350.969858
1510.03381570.06763150.966184
1520.03378780.06757560.966212
1530.03251230.06502460.967488
1540.03001030.06002050.96999
1550.03731550.07463090.962685
1560.03107460.06214930.968925
1570.02540970.05081940.97459
1580.0228970.0457940.977103
1590.03093860.06187720.969061
1600.03456410.06912810.965436
1610.03141210.06282420.968588
1620.09037850.1807570.909622
1630.07708110.1541620.922919
1640.2774830.5549670.722517
1650.2589890.5179780.741011
1660.38170.7633990.6183
1670.3513780.7027560.648622
1680.3233170.6466330.676683
1690.291690.5833810.70831
1700.2636820.5273630.736318
1710.2811070.5622140.718893
1720.2511060.5022120.748894
1730.3118140.6236290.688186
1740.2973850.594770.702615
1750.2729560.5459110.727044
1760.3438820.6877650.656118
1770.3164330.6328660.683567
1780.3184280.6368550.681572
1790.3003610.6007210.699639
1800.2814370.5628740.718563
1810.2857390.5714780.714261
1820.3801310.7602620.619869
1830.3526140.7052270.647386
1840.3590460.7180920.640954
1850.3352240.6704470.664776
1860.4148070.8296130.585193
1870.378880.757760.62112
1880.3420140.6840280.657986
1890.3120010.6240010.687999
1900.3901350.780270.609865
1910.5037270.9925460.496273
1920.5342890.9314210.465711
1930.5317120.9365750.468288
1940.4930160.9860320.506984
1950.4643280.9286570.535672
1960.4845890.9691770.515411
1970.6575630.6848740.342437
1980.6529250.6941510.347075
1990.6139860.7720280.386014
2000.5765650.8468690.423435
2010.5345030.9309950.465497
2020.4944430.9888870.505557
2030.452290.904580.54771
2040.4241070.8482140.575893
2050.3904890.7809780.609511
2060.3499540.6999090.650046
2070.3101030.6202060.689897
2080.2846230.5692450.715377
2090.2481090.4962190.751891
2100.2208770.4417540.779123
2110.1966260.3932520.803374
2120.167720.3354390.83228
2130.1849380.3698750.815062
2140.1719980.3439970.828002
2150.1464150.292830.853585
2160.1229290.2458590.877071
2170.1086030.2172050.891397
2180.08818980.176380.91181
2190.08875420.1775080.911246
2200.08681660.1736330.913183
2210.09913230.1982650.900868
2220.08511020.170220.91489
2230.06773960.1354790.93226
2240.06995140.1399030.930049
2250.06629660.1325930.933703
2260.05378520.107570.946215
2270.04099450.0819890.959005
2280.06046780.1209360.939532
2290.08560690.1712140.914393
2300.08314180.1662840.916858
2310.0651590.1303180.934841
2320.05462440.1092490.945376
2330.09218140.1843630.907819
2340.09989790.1997960.900102
2350.09990020.19980.9001
2360.08117580.1623520.918824
2370.1284150.256830.871585
2380.1604030.3208060.839597
2390.2918280.5836570.708172
2400.3181610.6363220.681839
2410.2718290.5436570.728171
2420.3023120.6046240.697688
2430.2398920.4797830.760108
2440.1859020.3718040.814098
2450.2988360.5976720.701164
2460.3312810.6625620.668719
2470.2604210.5208410.739579
2480.3327970.6655940.667203
2490.3989750.7979490.601025
2500.3235860.6471710.676414
2510.3576510.7153010.642349
2520.9637380.07252360.0362618
2530.9364550.1270890.0635446
2540.9505980.09880460.0494023

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.939604 & 0.120793 & 0.0603964 \tabularnewline
11 & 0.903918 & 0.192165 & 0.0960824 \tabularnewline
12 & 0.999338 & 0.0013234 & 0.0006617 \tabularnewline
13 & 0.998607 & 0.00278682 & 0.00139341 \tabularnewline
14 & 0.997187 & 0.00562696 & 0.00281348 \tabularnewline
15 & 0.995434 & 0.00913224 & 0.00456612 \tabularnewline
16 & 0.991858 & 0.0162843 & 0.00814215 \tabularnewline
17 & 0.986132 & 0.0277352 & 0.0138676 \tabularnewline
18 & 0.978799 & 0.0424019 & 0.0212009 \tabularnewline
19 & 0.979089 & 0.0418221 & 0.0209111 \tabularnewline
20 & 0.967736 & 0.0645285 & 0.0322642 \tabularnewline
21 & 0.95528 & 0.0894409 & 0.0447204 \tabularnewline
22 & 0.939116 & 0.121768 & 0.060884 \tabularnewline
23 & 0.92351 & 0.15298 & 0.0764902 \tabularnewline
24 & 0.896898 & 0.206205 & 0.103102 \tabularnewline
25 & 0.871104 & 0.257792 & 0.128896 \tabularnewline
26 & 0.951918 & 0.0961641 & 0.048082 \tabularnewline
27 & 0.935699 & 0.128602 & 0.0643009 \tabularnewline
28 & 0.922442 & 0.155116 & 0.0775582 \tabularnewline
29 & 0.902924 & 0.194152 & 0.0970759 \tabularnewline
30 & 0.877986 & 0.244028 & 0.122014 \tabularnewline
31 & 0.880419 & 0.239161 & 0.119581 \tabularnewline
32 & 0.85126 & 0.297481 & 0.14874 \tabularnewline
33 & 0.824715 & 0.35057 & 0.175285 \tabularnewline
34 & 0.786805 & 0.426391 & 0.213195 \tabularnewline
35 & 0.743587 & 0.512826 & 0.256413 \tabularnewline
36 & 0.753681 & 0.492639 & 0.246319 \tabularnewline
37 & 0.810136 & 0.379728 & 0.189864 \tabularnewline
38 & 0.772821 & 0.454357 & 0.227179 \tabularnewline
39 & 0.74063 & 0.518739 & 0.25937 \tabularnewline
40 & 0.745664 & 0.508672 & 0.254336 \tabularnewline
41 & 0.735687 & 0.528626 & 0.264313 \tabularnewline
42 & 0.710905 & 0.57819 & 0.289095 \tabularnewline
43 & 0.768105 & 0.463791 & 0.231895 \tabularnewline
44 & 0.730868 & 0.538263 & 0.269132 \tabularnewline
45 & 0.691543 & 0.616914 & 0.308457 \tabularnewline
46 & 0.670953 & 0.658094 & 0.329047 \tabularnewline
47 & 0.688834 & 0.622333 & 0.311166 \tabularnewline
48 & 0.65178 & 0.696441 & 0.34822 \tabularnewline
49 & 0.685062 & 0.629876 & 0.314938 \tabularnewline
50 & 0.657546 & 0.684908 & 0.342454 \tabularnewline
51 & 0.644264 & 0.711471 & 0.355736 \tabularnewline
52 & 0.605486 & 0.789029 & 0.394514 \tabularnewline
53 & 0.604473 & 0.791054 & 0.395527 \tabularnewline
54 & 0.560651 & 0.878699 & 0.439349 \tabularnewline
55 & 0.581839 & 0.836322 & 0.418161 \tabularnewline
56 & 0.600272 & 0.799456 & 0.399728 \tabularnewline
57 & 0.575481 & 0.849038 & 0.424519 \tabularnewline
58 & 0.608019 & 0.783961 & 0.391981 \tabularnewline
59 & 0.634642 & 0.730717 & 0.365358 \tabularnewline
60 & 0.607754 & 0.784492 & 0.392246 \tabularnewline
61 & 0.621575 & 0.75685 & 0.378425 \tabularnewline
62 & 0.58465 & 0.830701 & 0.41535 \tabularnewline
63 & 0.56461 & 0.87078 & 0.43539 \tabularnewline
64 & 0.522135 & 0.955731 & 0.477865 \tabularnewline
65 & 0.479524 & 0.959048 & 0.520476 \tabularnewline
66 & 0.494401 & 0.988802 & 0.505599 \tabularnewline
67 & 0.501271 & 0.997457 & 0.498729 \tabularnewline
68 & 0.48406 & 0.968121 & 0.51594 \tabularnewline
69 & 0.443111 & 0.886222 & 0.556889 \tabularnewline
70 & 0.417848 & 0.835695 & 0.582152 \tabularnewline
71 & 0.379177 & 0.758355 & 0.620823 \tabularnewline
72 & 0.359303 & 0.718606 & 0.640697 \tabularnewline
73 & 0.328232 & 0.656465 & 0.671768 \tabularnewline
74 & 0.317587 & 0.635175 & 0.682413 \tabularnewline
75 & 0.294198 & 0.588395 & 0.705802 \tabularnewline
76 & 0.443474 & 0.886949 & 0.556526 \tabularnewline
77 & 0.424478 & 0.848957 & 0.575522 \tabularnewline
78 & 0.454586 & 0.909172 & 0.545414 \tabularnewline
79 & 0.417353 & 0.834706 & 0.582647 \tabularnewline
80 & 0.497063 & 0.994125 & 0.502937 \tabularnewline
81 & 0.465161 & 0.930322 & 0.534839 \tabularnewline
82 & 0.476034 & 0.952068 & 0.523966 \tabularnewline
83 & 0.438336 & 0.876673 & 0.561664 \tabularnewline
84 & 0.400967 & 0.801934 & 0.599033 \tabularnewline
85 & 0.364692 & 0.729384 & 0.635308 \tabularnewline
86 & 0.331199 & 0.662398 & 0.668801 \tabularnewline
87 & 0.301068 & 0.602136 & 0.698932 \tabularnewline
88 & 0.270824 & 0.541648 & 0.729176 \tabularnewline
89 & 0.350077 & 0.700155 & 0.649923 \tabularnewline
90 & 0.326927 & 0.653854 & 0.673073 \tabularnewline
91 & 0.30086 & 0.601721 & 0.69914 \tabularnewline
92 & 0.271118 & 0.542235 & 0.728882 \tabularnewline
93 & 0.261899 & 0.523799 & 0.738101 \tabularnewline
94 & 0.23769 & 0.47538 & 0.76231 \tabularnewline
95 & 0.209599 & 0.419199 & 0.790401 \tabularnewline
96 & 0.197829 & 0.395657 & 0.802171 \tabularnewline
97 & 0.18257 & 0.365141 & 0.81743 \tabularnewline
98 & 0.159218 & 0.318436 & 0.840782 \tabularnewline
99 & 0.153631 & 0.307262 & 0.846369 \tabularnewline
100 & 0.133774 & 0.267549 & 0.866226 \tabularnewline
101 & 0.125383 & 0.250766 & 0.874617 \tabularnewline
102 & 0.110353 & 0.220705 & 0.889647 \tabularnewline
103 & 0.131933 & 0.263865 & 0.868067 \tabularnewline
104 & 0.148742 & 0.297483 & 0.851258 \tabularnewline
105 & 0.153822 & 0.307643 & 0.846178 \tabularnewline
106 & 0.13306 & 0.26612 & 0.86694 \tabularnewline
107 & 0.150625 & 0.301249 & 0.849375 \tabularnewline
108 & 0.135179 & 0.270358 & 0.864821 \tabularnewline
109 & 0.259963 & 0.519925 & 0.740037 \tabularnewline
110 & 0.250644 & 0.501288 & 0.749356 \tabularnewline
111 & 0.22404 & 0.448079 & 0.77596 \tabularnewline
112 & 0.214195 & 0.428389 & 0.785805 \tabularnewline
113 & 0.189035 & 0.37807 & 0.810965 \tabularnewline
114 & 0.174286 & 0.348572 & 0.825714 \tabularnewline
115 & 0.153117 & 0.306235 & 0.846883 \tabularnewline
116 & 0.13298 & 0.265961 & 0.86702 \tabularnewline
117 & 0.115467 & 0.230934 & 0.884533 \tabularnewline
118 & 0.142668 & 0.285335 & 0.857332 \tabularnewline
119 & 0.14235 & 0.2847 & 0.85765 \tabularnewline
120 & 0.123273 & 0.246547 & 0.876727 \tabularnewline
121 & 0.112147 & 0.224294 & 0.887853 \tabularnewline
122 & 0.0977935 & 0.195587 & 0.902206 \tabularnewline
123 & 0.115855 & 0.23171 & 0.884145 \tabularnewline
124 & 0.101933 & 0.203867 & 0.898067 \tabularnewline
125 & 0.0978613 & 0.195723 & 0.902139 \tabularnewline
126 & 0.0920851 & 0.18417 & 0.907915 \tabularnewline
127 & 0.0798758 & 0.159752 & 0.920124 \tabularnewline
128 & 0.0733371 & 0.146674 & 0.926663 \tabularnewline
129 & 0.0620542 & 0.124108 & 0.937946 \tabularnewline
130 & 0.0629538 & 0.125908 & 0.937046 \tabularnewline
131 & 0.0639828 & 0.127966 & 0.936017 \tabularnewline
132 & 0.0600077 & 0.120015 & 0.939992 \tabularnewline
133 & 0.0554575 & 0.110915 & 0.944543 \tabularnewline
134 & 0.046228 & 0.092456 & 0.953772 \tabularnewline
135 & 0.047416 & 0.094832 & 0.952584 \tabularnewline
136 & 0.107644 & 0.215288 & 0.892356 \tabularnewline
137 & 0.0929752 & 0.18595 & 0.907025 \tabularnewline
138 & 0.0790979 & 0.158196 & 0.920902 \tabularnewline
139 & 0.0727835 & 0.145567 & 0.927216 \tabularnewline
140 & 0.0700276 & 0.140055 & 0.929972 \tabularnewline
141 & 0.0733454 & 0.146691 & 0.926655 \tabularnewline
142 & 0.0717968 & 0.143594 & 0.928203 \tabularnewline
143 & 0.0606174 & 0.121235 & 0.939383 \tabularnewline
144 & 0.0508363 & 0.101673 & 0.949164 \tabularnewline
145 & 0.042221 & 0.084442 & 0.957779 \tabularnewline
146 & 0.0352059 & 0.0704118 & 0.964794 \tabularnewline
147 & 0.035032 & 0.0700639 & 0.964968 \tabularnewline
148 & 0.0387007 & 0.0774014 & 0.961299 \tabularnewline
149 & 0.0363948 & 0.0727895 & 0.963605 \tabularnewline
150 & 0.0301417 & 0.0602835 & 0.969858 \tabularnewline
151 & 0.0338157 & 0.0676315 & 0.966184 \tabularnewline
152 & 0.0337878 & 0.0675756 & 0.966212 \tabularnewline
153 & 0.0325123 & 0.0650246 & 0.967488 \tabularnewline
154 & 0.0300103 & 0.0600205 & 0.96999 \tabularnewline
155 & 0.0373155 & 0.0746309 & 0.962685 \tabularnewline
156 & 0.0310746 & 0.0621493 & 0.968925 \tabularnewline
157 & 0.0254097 & 0.0508194 & 0.97459 \tabularnewline
158 & 0.022897 & 0.045794 & 0.977103 \tabularnewline
159 & 0.0309386 & 0.0618772 & 0.969061 \tabularnewline
160 & 0.0345641 & 0.0691281 & 0.965436 \tabularnewline
161 & 0.0314121 & 0.0628242 & 0.968588 \tabularnewline
162 & 0.0903785 & 0.180757 & 0.909622 \tabularnewline
163 & 0.0770811 & 0.154162 & 0.922919 \tabularnewline
164 & 0.277483 & 0.554967 & 0.722517 \tabularnewline
165 & 0.258989 & 0.517978 & 0.741011 \tabularnewline
166 & 0.3817 & 0.763399 & 0.6183 \tabularnewline
167 & 0.351378 & 0.702756 & 0.648622 \tabularnewline
168 & 0.323317 & 0.646633 & 0.676683 \tabularnewline
169 & 0.29169 & 0.583381 & 0.70831 \tabularnewline
170 & 0.263682 & 0.527363 & 0.736318 \tabularnewline
171 & 0.281107 & 0.562214 & 0.718893 \tabularnewline
172 & 0.251106 & 0.502212 & 0.748894 \tabularnewline
173 & 0.311814 & 0.623629 & 0.688186 \tabularnewline
174 & 0.297385 & 0.59477 & 0.702615 \tabularnewline
175 & 0.272956 & 0.545911 & 0.727044 \tabularnewline
176 & 0.343882 & 0.687765 & 0.656118 \tabularnewline
177 & 0.316433 & 0.632866 & 0.683567 \tabularnewline
178 & 0.318428 & 0.636855 & 0.681572 \tabularnewline
179 & 0.300361 & 0.600721 & 0.699639 \tabularnewline
180 & 0.281437 & 0.562874 & 0.718563 \tabularnewline
181 & 0.285739 & 0.571478 & 0.714261 \tabularnewline
182 & 0.380131 & 0.760262 & 0.619869 \tabularnewline
183 & 0.352614 & 0.705227 & 0.647386 \tabularnewline
184 & 0.359046 & 0.718092 & 0.640954 \tabularnewline
185 & 0.335224 & 0.670447 & 0.664776 \tabularnewline
186 & 0.414807 & 0.829613 & 0.585193 \tabularnewline
187 & 0.37888 & 0.75776 & 0.62112 \tabularnewline
188 & 0.342014 & 0.684028 & 0.657986 \tabularnewline
189 & 0.312001 & 0.624001 & 0.687999 \tabularnewline
190 & 0.390135 & 0.78027 & 0.609865 \tabularnewline
191 & 0.503727 & 0.992546 & 0.496273 \tabularnewline
192 & 0.534289 & 0.931421 & 0.465711 \tabularnewline
193 & 0.531712 & 0.936575 & 0.468288 \tabularnewline
194 & 0.493016 & 0.986032 & 0.506984 \tabularnewline
195 & 0.464328 & 0.928657 & 0.535672 \tabularnewline
196 & 0.484589 & 0.969177 & 0.515411 \tabularnewline
197 & 0.657563 & 0.684874 & 0.342437 \tabularnewline
198 & 0.652925 & 0.694151 & 0.347075 \tabularnewline
199 & 0.613986 & 0.772028 & 0.386014 \tabularnewline
200 & 0.576565 & 0.846869 & 0.423435 \tabularnewline
201 & 0.534503 & 0.930995 & 0.465497 \tabularnewline
202 & 0.494443 & 0.988887 & 0.505557 \tabularnewline
203 & 0.45229 & 0.90458 & 0.54771 \tabularnewline
204 & 0.424107 & 0.848214 & 0.575893 \tabularnewline
205 & 0.390489 & 0.780978 & 0.609511 \tabularnewline
206 & 0.349954 & 0.699909 & 0.650046 \tabularnewline
207 & 0.310103 & 0.620206 & 0.689897 \tabularnewline
208 & 0.284623 & 0.569245 & 0.715377 \tabularnewline
209 & 0.248109 & 0.496219 & 0.751891 \tabularnewline
210 & 0.220877 & 0.441754 & 0.779123 \tabularnewline
211 & 0.196626 & 0.393252 & 0.803374 \tabularnewline
212 & 0.16772 & 0.335439 & 0.83228 \tabularnewline
213 & 0.184938 & 0.369875 & 0.815062 \tabularnewline
214 & 0.171998 & 0.343997 & 0.828002 \tabularnewline
215 & 0.146415 & 0.29283 & 0.853585 \tabularnewline
216 & 0.122929 & 0.245859 & 0.877071 \tabularnewline
217 & 0.108603 & 0.217205 & 0.891397 \tabularnewline
218 & 0.0881898 & 0.17638 & 0.91181 \tabularnewline
219 & 0.0887542 & 0.177508 & 0.911246 \tabularnewline
220 & 0.0868166 & 0.173633 & 0.913183 \tabularnewline
221 & 0.0991323 & 0.198265 & 0.900868 \tabularnewline
222 & 0.0851102 & 0.17022 & 0.91489 \tabularnewline
223 & 0.0677396 & 0.135479 & 0.93226 \tabularnewline
224 & 0.0699514 & 0.139903 & 0.930049 \tabularnewline
225 & 0.0662966 & 0.132593 & 0.933703 \tabularnewline
226 & 0.0537852 & 0.10757 & 0.946215 \tabularnewline
227 & 0.0409945 & 0.081989 & 0.959005 \tabularnewline
228 & 0.0604678 & 0.120936 & 0.939532 \tabularnewline
229 & 0.0856069 & 0.171214 & 0.914393 \tabularnewline
230 & 0.0831418 & 0.166284 & 0.916858 \tabularnewline
231 & 0.065159 & 0.130318 & 0.934841 \tabularnewline
232 & 0.0546244 & 0.109249 & 0.945376 \tabularnewline
233 & 0.0921814 & 0.184363 & 0.907819 \tabularnewline
234 & 0.0998979 & 0.199796 & 0.900102 \tabularnewline
235 & 0.0999002 & 0.1998 & 0.9001 \tabularnewline
236 & 0.0811758 & 0.162352 & 0.918824 \tabularnewline
237 & 0.128415 & 0.25683 & 0.871585 \tabularnewline
238 & 0.160403 & 0.320806 & 0.839597 \tabularnewline
239 & 0.291828 & 0.583657 & 0.708172 \tabularnewline
240 & 0.318161 & 0.636322 & 0.681839 \tabularnewline
241 & 0.271829 & 0.543657 & 0.728171 \tabularnewline
242 & 0.302312 & 0.604624 & 0.697688 \tabularnewline
243 & 0.239892 & 0.479783 & 0.760108 \tabularnewline
244 & 0.185902 & 0.371804 & 0.814098 \tabularnewline
245 & 0.298836 & 0.597672 & 0.701164 \tabularnewline
246 & 0.331281 & 0.662562 & 0.668719 \tabularnewline
247 & 0.260421 & 0.520841 & 0.739579 \tabularnewline
248 & 0.332797 & 0.665594 & 0.667203 \tabularnewline
249 & 0.398975 & 0.797949 & 0.601025 \tabularnewline
250 & 0.323586 & 0.647171 & 0.676414 \tabularnewline
251 & 0.357651 & 0.715301 & 0.642349 \tabularnewline
252 & 0.963738 & 0.0725236 & 0.0362618 \tabularnewline
253 & 0.936455 & 0.127089 & 0.0635446 \tabularnewline
254 & 0.950598 & 0.0988046 & 0.0494023 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253181&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]0.939604[/C][C]0.120793[/C][C]0.0603964[/C][/ROW]
[ROW][C]11[/C][C]0.903918[/C][C]0.192165[/C][C]0.0960824[/C][/ROW]
[ROW][C]12[/C][C]0.999338[/C][C]0.0013234[/C][C]0.0006617[/C][/ROW]
[ROW][C]13[/C][C]0.998607[/C][C]0.00278682[/C][C]0.00139341[/C][/ROW]
[ROW][C]14[/C][C]0.997187[/C][C]0.00562696[/C][C]0.00281348[/C][/ROW]
[ROW][C]15[/C][C]0.995434[/C][C]0.00913224[/C][C]0.00456612[/C][/ROW]
[ROW][C]16[/C][C]0.991858[/C][C]0.0162843[/C][C]0.00814215[/C][/ROW]
[ROW][C]17[/C][C]0.986132[/C][C]0.0277352[/C][C]0.0138676[/C][/ROW]
[ROW][C]18[/C][C]0.978799[/C][C]0.0424019[/C][C]0.0212009[/C][/ROW]
[ROW][C]19[/C][C]0.979089[/C][C]0.0418221[/C][C]0.0209111[/C][/ROW]
[ROW][C]20[/C][C]0.967736[/C][C]0.0645285[/C][C]0.0322642[/C][/ROW]
[ROW][C]21[/C][C]0.95528[/C][C]0.0894409[/C][C]0.0447204[/C][/ROW]
[ROW][C]22[/C][C]0.939116[/C][C]0.121768[/C][C]0.060884[/C][/ROW]
[ROW][C]23[/C][C]0.92351[/C][C]0.15298[/C][C]0.0764902[/C][/ROW]
[ROW][C]24[/C][C]0.896898[/C][C]0.206205[/C][C]0.103102[/C][/ROW]
[ROW][C]25[/C][C]0.871104[/C][C]0.257792[/C][C]0.128896[/C][/ROW]
[ROW][C]26[/C][C]0.951918[/C][C]0.0961641[/C][C]0.048082[/C][/ROW]
[ROW][C]27[/C][C]0.935699[/C][C]0.128602[/C][C]0.0643009[/C][/ROW]
[ROW][C]28[/C][C]0.922442[/C][C]0.155116[/C][C]0.0775582[/C][/ROW]
[ROW][C]29[/C][C]0.902924[/C][C]0.194152[/C][C]0.0970759[/C][/ROW]
[ROW][C]30[/C][C]0.877986[/C][C]0.244028[/C][C]0.122014[/C][/ROW]
[ROW][C]31[/C][C]0.880419[/C][C]0.239161[/C][C]0.119581[/C][/ROW]
[ROW][C]32[/C][C]0.85126[/C][C]0.297481[/C][C]0.14874[/C][/ROW]
[ROW][C]33[/C][C]0.824715[/C][C]0.35057[/C][C]0.175285[/C][/ROW]
[ROW][C]34[/C][C]0.786805[/C][C]0.426391[/C][C]0.213195[/C][/ROW]
[ROW][C]35[/C][C]0.743587[/C][C]0.512826[/C][C]0.256413[/C][/ROW]
[ROW][C]36[/C][C]0.753681[/C][C]0.492639[/C][C]0.246319[/C][/ROW]
[ROW][C]37[/C][C]0.810136[/C][C]0.379728[/C][C]0.189864[/C][/ROW]
[ROW][C]38[/C][C]0.772821[/C][C]0.454357[/C][C]0.227179[/C][/ROW]
[ROW][C]39[/C][C]0.74063[/C][C]0.518739[/C][C]0.25937[/C][/ROW]
[ROW][C]40[/C][C]0.745664[/C][C]0.508672[/C][C]0.254336[/C][/ROW]
[ROW][C]41[/C][C]0.735687[/C][C]0.528626[/C][C]0.264313[/C][/ROW]
[ROW][C]42[/C][C]0.710905[/C][C]0.57819[/C][C]0.289095[/C][/ROW]
[ROW][C]43[/C][C]0.768105[/C][C]0.463791[/C][C]0.231895[/C][/ROW]
[ROW][C]44[/C][C]0.730868[/C][C]0.538263[/C][C]0.269132[/C][/ROW]
[ROW][C]45[/C][C]0.691543[/C][C]0.616914[/C][C]0.308457[/C][/ROW]
[ROW][C]46[/C][C]0.670953[/C][C]0.658094[/C][C]0.329047[/C][/ROW]
[ROW][C]47[/C][C]0.688834[/C][C]0.622333[/C][C]0.311166[/C][/ROW]
[ROW][C]48[/C][C]0.65178[/C][C]0.696441[/C][C]0.34822[/C][/ROW]
[ROW][C]49[/C][C]0.685062[/C][C]0.629876[/C][C]0.314938[/C][/ROW]
[ROW][C]50[/C][C]0.657546[/C][C]0.684908[/C][C]0.342454[/C][/ROW]
[ROW][C]51[/C][C]0.644264[/C][C]0.711471[/C][C]0.355736[/C][/ROW]
[ROW][C]52[/C][C]0.605486[/C][C]0.789029[/C][C]0.394514[/C][/ROW]
[ROW][C]53[/C][C]0.604473[/C][C]0.791054[/C][C]0.395527[/C][/ROW]
[ROW][C]54[/C][C]0.560651[/C][C]0.878699[/C][C]0.439349[/C][/ROW]
[ROW][C]55[/C][C]0.581839[/C][C]0.836322[/C][C]0.418161[/C][/ROW]
[ROW][C]56[/C][C]0.600272[/C][C]0.799456[/C][C]0.399728[/C][/ROW]
[ROW][C]57[/C][C]0.575481[/C][C]0.849038[/C][C]0.424519[/C][/ROW]
[ROW][C]58[/C][C]0.608019[/C][C]0.783961[/C][C]0.391981[/C][/ROW]
[ROW][C]59[/C][C]0.634642[/C][C]0.730717[/C][C]0.365358[/C][/ROW]
[ROW][C]60[/C][C]0.607754[/C][C]0.784492[/C][C]0.392246[/C][/ROW]
[ROW][C]61[/C][C]0.621575[/C][C]0.75685[/C][C]0.378425[/C][/ROW]
[ROW][C]62[/C][C]0.58465[/C][C]0.830701[/C][C]0.41535[/C][/ROW]
[ROW][C]63[/C][C]0.56461[/C][C]0.87078[/C][C]0.43539[/C][/ROW]
[ROW][C]64[/C][C]0.522135[/C][C]0.955731[/C][C]0.477865[/C][/ROW]
[ROW][C]65[/C][C]0.479524[/C][C]0.959048[/C][C]0.520476[/C][/ROW]
[ROW][C]66[/C][C]0.494401[/C][C]0.988802[/C][C]0.505599[/C][/ROW]
[ROW][C]67[/C][C]0.501271[/C][C]0.997457[/C][C]0.498729[/C][/ROW]
[ROW][C]68[/C][C]0.48406[/C][C]0.968121[/C][C]0.51594[/C][/ROW]
[ROW][C]69[/C][C]0.443111[/C][C]0.886222[/C][C]0.556889[/C][/ROW]
[ROW][C]70[/C][C]0.417848[/C][C]0.835695[/C][C]0.582152[/C][/ROW]
[ROW][C]71[/C][C]0.379177[/C][C]0.758355[/C][C]0.620823[/C][/ROW]
[ROW][C]72[/C][C]0.359303[/C][C]0.718606[/C][C]0.640697[/C][/ROW]
[ROW][C]73[/C][C]0.328232[/C][C]0.656465[/C][C]0.671768[/C][/ROW]
[ROW][C]74[/C][C]0.317587[/C][C]0.635175[/C][C]0.682413[/C][/ROW]
[ROW][C]75[/C][C]0.294198[/C][C]0.588395[/C][C]0.705802[/C][/ROW]
[ROW][C]76[/C][C]0.443474[/C][C]0.886949[/C][C]0.556526[/C][/ROW]
[ROW][C]77[/C][C]0.424478[/C][C]0.848957[/C][C]0.575522[/C][/ROW]
[ROW][C]78[/C][C]0.454586[/C][C]0.909172[/C][C]0.545414[/C][/ROW]
[ROW][C]79[/C][C]0.417353[/C][C]0.834706[/C][C]0.582647[/C][/ROW]
[ROW][C]80[/C][C]0.497063[/C][C]0.994125[/C][C]0.502937[/C][/ROW]
[ROW][C]81[/C][C]0.465161[/C][C]0.930322[/C][C]0.534839[/C][/ROW]
[ROW][C]82[/C][C]0.476034[/C][C]0.952068[/C][C]0.523966[/C][/ROW]
[ROW][C]83[/C][C]0.438336[/C][C]0.876673[/C][C]0.561664[/C][/ROW]
[ROW][C]84[/C][C]0.400967[/C][C]0.801934[/C][C]0.599033[/C][/ROW]
[ROW][C]85[/C][C]0.364692[/C][C]0.729384[/C][C]0.635308[/C][/ROW]
[ROW][C]86[/C][C]0.331199[/C][C]0.662398[/C][C]0.668801[/C][/ROW]
[ROW][C]87[/C][C]0.301068[/C][C]0.602136[/C][C]0.698932[/C][/ROW]
[ROW][C]88[/C][C]0.270824[/C][C]0.541648[/C][C]0.729176[/C][/ROW]
[ROW][C]89[/C][C]0.350077[/C][C]0.700155[/C][C]0.649923[/C][/ROW]
[ROW][C]90[/C][C]0.326927[/C][C]0.653854[/C][C]0.673073[/C][/ROW]
[ROW][C]91[/C][C]0.30086[/C][C]0.601721[/C][C]0.69914[/C][/ROW]
[ROW][C]92[/C][C]0.271118[/C][C]0.542235[/C][C]0.728882[/C][/ROW]
[ROW][C]93[/C][C]0.261899[/C][C]0.523799[/C][C]0.738101[/C][/ROW]
[ROW][C]94[/C][C]0.23769[/C][C]0.47538[/C][C]0.76231[/C][/ROW]
[ROW][C]95[/C][C]0.209599[/C][C]0.419199[/C][C]0.790401[/C][/ROW]
[ROW][C]96[/C][C]0.197829[/C][C]0.395657[/C][C]0.802171[/C][/ROW]
[ROW][C]97[/C][C]0.18257[/C][C]0.365141[/C][C]0.81743[/C][/ROW]
[ROW][C]98[/C][C]0.159218[/C][C]0.318436[/C][C]0.840782[/C][/ROW]
[ROW][C]99[/C][C]0.153631[/C][C]0.307262[/C][C]0.846369[/C][/ROW]
[ROW][C]100[/C][C]0.133774[/C][C]0.267549[/C][C]0.866226[/C][/ROW]
[ROW][C]101[/C][C]0.125383[/C][C]0.250766[/C][C]0.874617[/C][/ROW]
[ROW][C]102[/C][C]0.110353[/C][C]0.220705[/C][C]0.889647[/C][/ROW]
[ROW][C]103[/C][C]0.131933[/C][C]0.263865[/C][C]0.868067[/C][/ROW]
[ROW][C]104[/C][C]0.148742[/C][C]0.297483[/C][C]0.851258[/C][/ROW]
[ROW][C]105[/C][C]0.153822[/C][C]0.307643[/C][C]0.846178[/C][/ROW]
[ROW][C]106[/C][C]0.13306[/C][C]0.26612[/C][C]0.86694[/C][/ROW]
[ROW][C]107[/C][C]0.150625[/C][C]0.301249[/C][C]0.849375[/C][/ROW]
[ROW][C]108[/C][C]0.135179[/C][C]0.270358[/C][C]0.864821[/C][/ROW]
[ROW][C]109[/C][C]0.259963[/C][C]0.519925[/C][C]0.740037[/C][/ROW]
[ROW][C]110[/C][C]0.250644[/C][C]0.501288[/C][C]0.749356[/C][/ROW]
[ROW][C]111[/C][C]0.22404[/C][C]0.448079[/C][C]0.77596[/C][/ROW]
[ROW][C]112[/C][C]0.214195[/C][C]0.428389[/C][C]0.785805[/C][/ROW]
[ROW][C]113[/C][C]0.189035[/C][C]0.37807[/C][C]0.810965[/C][/ROW]
[ROW][C]114[/C][C]0.174286[/C][C]0.348572[/C][C]0.825714[/C][/ROW]
[ROW][C]115[/C][C]0.153117[/C][C]0.306235[/C][C]0.846883[/C][/ROW]
[ROW][C]116[/C][C]0.13298[/C][C]0.265961[/C][C]0.86702[/C][/ROW]
[ROW][C]117[/C][C]0.115467[/C][C]0.230934[/C][C]0.884533[/C][/ROW]
[ROW][C]118[/C][C]0.142668[/C][C]0.285335[/C][C]0.857332[/C][/ROW]
[ROW][C]119[/C][C]0.14235[/C][C]0.2847[/C][C]0.85765[/C][/ROW]
[ROW][C]120[/C][C]0.123273[/C][C]0.246547[/C][C]0.876727[/C][/ROW]
[ROW][C]121[/C][C]0.112147[/C][C]0.224294[/C][C]0.887853[/C][/ROW]
[ROW][C]122[/C][C]0.0977935[/C][C]0.195587[/C][C]0.902206[/C][/ROW]
[ROW][C]123[/C][C]0.115855[/C][C]0.23171[/C][C]0.884145[/C][/ROW]
[ROW][C]124[/C][C]0.101933[/C][C]0.203867[/C][C]0.898067[/C][/ROW]
[ROW][C]125[/C][C]0.0978613[/C][C]0.195723[/C][C]0.902139[/C][/ROW]
[ROW][C]126[/C][C]0.0920851[/C][C]0.18417[/C][C]0.907915[/C][/ROW]
[ROW][C]127[/C][C]0.0798758[/C][C]0.159752[/C][C]0.920124[/C][/ROW]
[ROW][C]128[/C][C]0.0733371[/C][C]0.146674[/C][C]0.926663[/C][/ROW]
[ROW][C]129[/C][C]0.0620542[/C][C]0.124108[/C][C]0.937946[/C][/ROW]
[ROW][C]130[/C][C]0.0629538[/C][C]0.125908[/C][C]0.937046[/C][/ROW]
[ROW][C]131[/C][C]0.0639828[/C][C]0.127966[/C][C]0.936017[/C][/ROW]
[ROW][C]132[/C][C]0.0600077[/C][C]0.120015[/C][C]0.939992[/C][/ROW]
[ROW][C]133[/C][C]0.0554575[/C][C]0.110915[/C][C]0.944543[/C][/ROW]
[ROW][C]134[/C][C]0.046228[/C][C]0.092456[/C][C]0.953772[/C][/ROW]
[ROW][C]135[/C][C]0.047416[/C][C]0.094832[/C][C]0.952584[/C][/ROW]
[ROW][C]136[/C][C]0.107644[/C][C]0.215288[/C][C]0.892356[/C][/ROW]
[ROW][C]137[/C][C]0.0929752[/C][C]0.18595[/C][C]0.907025[/C][/ROW]
[ROW][C]138[/C][C]0.0790979[/C][C]0.158196[/C][C]0.920902[/C][/ROW]
[ROW][C]139[/C][C]0.0727835[/C][C]0.145567[/C][C]0.927216[/C][/ROW]
[ROW][C]140[/C][C]0.0700276[/C][C]0.140055[/C][C]0.929972[/C][/ROW]
[ROW][C]141[/C][C]0.0733454[/C][C]0.146691[/C][C]0.926655[/C][/ROW]
[ROW][C]142[/C][C]0.0717968[/C][C]0.143594[/C][C]0.928203[/C][/ROW]
[ROW][C]143[/C][C]0.0606174[/C][C]0.121235[/C][C]0.939383[/C][/ROW]
[ROW][C]144[/C][C]0.0508363[/C][C]0.101673[/C][C]0.949164[/C][/ROW]
[ROW][C]145[/C][C]0.042221[/C][C]0.084442[/C][C]0.957779[/C][/ROW]
[ROW][C]146[/C][C]0.0352059[/C][C]0.0704118[/C][C]0.964794[/C][/ROW]
[ROW][C]147[/C][C]0.035032[/C][C]0.0700639[/C][C]0.964968[/C][/ROW]
[ROW][C]148[/C][C]0.0387007[/C][C]0.0774014[/C][C]0.961299[/C][/ROW]
[ROW][C]149[/C][C]0.0363948[/C][C]0.0727895[/C][C]0.963605[/C][/ROW]
[ROW][C]150[/C][C]0.0301417[/C][C]0.0602835[/C][C]0.969858[/C][/ROW]
[ROW][C]151[/C][C]0.0338157[/C][C]0.0676315[/C][C]0.966184[/C][/ROW]
[ROW][C]152[/C][C]0.0337878[/C][C]0.0675756[/C][C]0.966212[/C][/ROW]
[ROW][C]153[/C][C]0.0325123[/C][C]0.0650246[/C][C]0.967488[/C][/ROW]
[ROW][C]154[/C][C]0.0300103[/C][C]0.0600205[/C][C]0.96999[/C][/ROW]
[ROW][C]155[/C][C]0.0373155[/C][C]0.0746309[/C][C]0.962685[/C][/ROW]
[ROW][C]156[/C][C]0.0310746[/C][C]0.0621493[/C][C]0.968925[/C][/ROW]
[ROW][C]157[/C][C]0.0254097[/C][C]0.0508194[/C][C]0.97459[/C][/ROW]
[ROW][C]158[/C][C]0.022897[/C][C]0.045794[/C][C]0.977103[/C][/ROW]
[ROW][C]159[/C][C]0.0309386[/C][C]0.0618772[/C][C]0.969061[/C][/ROW]
[ROW][C]160[/C][C]0.0345641[/C][C]0.0691281[/C][C]0.965436[/C][/ROW]
[ROW][C]161[/C][C]0.0314121[/C][C]0.0628242[/C][C]0.968588[/C][/ROW]
[ROW][C]162[/C][C]0.0903785[/C][C]0.180757[/C][C]0.909622[/C][/ROW]
[ROW][C]163[/C][C]0.0770811[/C][C]0.154162[/C][C]0.922919[/C][/ROW]
[ROW][C]164[/C][C]0.277483[/C][C]0.554967[/C][C]0.722517[/C][/ROW]
[ROW][C]165[/C][C]0.258989[/C][C]0.517978[/C][C]0.741011[/C][/ROW]
[ROW][C]166[/C][C]0.3817[/C][C]0.763399[/C][C]0.6183[/C][/ROW]
[ROW][C]167[/C][C]0.351378[/C][C]0.702756[/C][C]0.648622[/C][/ROW]
[ROW][C]168[/C][C]0.323317[/C][C]0.646633[/C][C]0.676683[/C][/ROW]
[ROW][C]169[/C][C]0.29169[/C][C]0.583381[/C][C]0.70831[/C][/ROW]
[ROW][C]170[/C][C]0.263682[/C][C]0.527363[/C][C]0.736318[/C][/ROW]
[ROW][C]171[/C][C]0.281107[/C][C]0.562214[/C][C]0.718893[/C][/ROW]
[ROW][C]172[/C][C]0.251106[/C][C]0.502212[/C][C]0.748894[/C][/ROW]
[ROW][C]173[/C][C]0.311814[/C][C]0.623629[/C][C]0.688186[/C][/ROW]
[ROW][C]174[/C][C]0.297385[/C][C]0.59477[/C][C]0.702615[/C][/ROW]
[ROW][C]175[/C][C]0.272956[/C][C]0.545911[/C][C]0.727044[/C][/ROW]
[ROW][C]176[/C][C]0.343882[/C][C]0.687765[/C][C]0.656118[/C][/ROW]
[ROW][C]177[/C][C]0.316433[/C][C]0.632866[/C][C]0.683567[/C][/ROW]
[ROW][C]178[/C][C]0.318428[/C][C]0.636855[/C][C]0.681572[/C][/ROW]
[ROW][C]179[/C][C]0.300361[/C][C]0.600721[/C][C]0.699639[/C][/ROW]
[ROW][C]180[/C][C]0.281437[/C][C]0.562874[/C][C]0.718563[/C][/ROW]
[ROW][C]181[/C][C]0.285739[/C][C]0.571478[/C][C]0.714261[/C][/ROW]
[ROW][C]182[/C][C]0.380131[/C][C]0.760262[/C][C]0.619869[/C][/ROW]
[ROW][C]183[/C][C]0.352614[/C][C]0.705227[/C][C]0.647386[/C][/ROW]
[ROW][C]184[/C][C]0.359046[/C][C]0.718092[/C][C]0.640954[/C][/ROW]
[ROW][C]185[/C][C]0.335224[/C][C]0.670447[/C][C]0.664776[/C][/ROW]
[ROW][C]186[/C][C]0.414807[/C][C]0.829613[/C][C]0.585193[/C][/ROW]
[ROW][C]187[/C][C]0.37888[/C][C]0.75776[/C][C]0.62112[/C][/ROW]
[ROW][C]188[/C][C]0.342014[/C][C]0.684028[/C][C]0.657986[/C][/ROW]
[ROW][C]189[/C][C]0.312001[/C][C]0.624001[/C][C]0.687999[/C][/ROW]
[ROW][C]190[/C][C]0.390135[/C][C]0.78027[/C][C]0.609865[/C][/ROW]
[ROW][C]191[/C][C]0.503727[/C][C]0.992546[/C][C]0.496273[/C][/ROW]
[ROW][C]192[/C][C]0.534289[/C][C]0.931421[/C][C]0.465711[/C][/ROW]
[ROW][C]193[/C][C]0.531712[/C][C]0.936575[/C][C]0.468288[/C][/ROW]
[ROW][C]194[/C][C]0.493016[/C][C]0.986032[/C][C]0.506984[/C][/ROW]
[ROW][C]195[/C][C]0.464328[/C][C]0.928657[/C][C]0.535672[/C][/ROW]
[ROW][C]196[/C][C]0.484589[/C][C]0.969177[/C][C]0.515411[/C][/ROW]
[ROW][C]197[/C][C]0.657563[/C][C]0.684874[/C][C]0.342437[/C][/ROW]
[ROW][C]198[/C][C]0.652925[/C][C]0.694151[/C][C]0.347075[/C][/ROW]
[ROW][C]199[/C][C]0.613986[/C][C]0.772028[/C][C]0.386014[/C][/ROW]
[ROW][C]200[/C][C]0.576565[/C][C]0.846869[/C][C]0.423435[/C][/ROW]
[ROW][C]201[/C][C]0.534503[/C][C]0.930995[/C][C]0.465497[/C][/ROW]
[ROW][C]202[/C][C]0.494443[/C][C]0.988887[/C][C]0.505557[/C][/ROW]
[ROW][C]203[/C][C]0.45229[/C][C]0.90458[/C][C]0.54771[/C][/ROW]
[ROW][C]204[/C][C]0.424107[/C][C]0.848214[/C][C]0.575893[/C][/ROW]
[ROW][C]205[/C][C]0.390489[/C][C]0.780978[/C][C]0.609511[/C][/ROW]
[ROW][C]206[/C][C]0.349954[/C][C]0.699909[/C][C]0.650046[/C][/ROW]
[ROW][C]207[/C][C]0.310103[/C][C]0.620206[/C][C]0.689897[/C][/ROW]
[ROW][C]208[/C][C]0.284623[/C][C]0.569245[/C][C]0.715377[/C][/ROW]
[ROW][C]209[/C][C]0.248109[/C][C]0.496219[/C][C]0.751891[/C][/ROW]
[ROW][C]210[/C][C]0.220877[/C][C]0.441754[/C][C]0.779123[/C][/ROW]
[ROW][C]211[/C][C]0.196626[/C][C]0.393252[/C][C]0.803374[/C][/ROW]
[ROW][C]212[/C][C]0.16772[/C][C]0.335439[/C][C]0.83228[/C][/ROW]
[ROW][C]213[/C][C]0.184938[/C][C]0.369875[/C][C]0.815062[/C][/ROW]
[ROW][C]214[/C][C]0.171998[/C][C]0.343997[/C][C]0.828002[/C][/ROW]
[ROW][C]215[/C][C]0.146415[/C][C]0.29283[/C][C]0.853585[/C][/ROW]
[ROW][C]216[/C][C]0.122929[/C][C]0.245859[/C][C]0.877071[/C][/ROW]
[ROW][C]217[/C][C]0.108603[/C][C]0.217205[/C][C]0.891397[/C][/ROW]
[ROW][C]218[/C][C]0.0881898[/C][C]0.17638[/C][C]0.91181[/C][/ROW]
[ROW][C]219[/C][C]0.0887542[/C][C]0.177508[/C][C]0.911246[/C][/ROW]
[ROW][C]220[/C][C]0.0868166[/C][C]0.173633[/C][C]0.913183[/C][/ROW]
[ROW][C]221[/C][C]0.0991323[/C][C]0.198265[/C][C]0.900868[/C][/ROW]
[ROW][C]222[/C][C]0.0851102[/C][C]0.17022[/C][C]0.91489[/C][/ROW]
[ROW][C]223[/C][C]0.0677396[/C][C]0.135479[/C][C]0.93226[/C][/ROW]
[ROW][C]224[/C][C]0.0699514[/C][C]0.139903[/C][C]0.930049[/C][/ROW]
[ROW][C]225[/C][C]0.0662966[/C][C]0.132593[/C][C]0.933703[/C][/ROW]
[ROW][C]226[/C][C]0.0537852[/C][C]0.10757[/C][C]0.946215[/C][/ROW]
[ROW][C]227[/C][C]0.0409945[/C][C]0.081989[/C][C]0.959005[/C][/ROW]
[ROW][C]228[/C][C]0.0604678[/C][C]0.120936[/C][C]0.939532[/C][/ROW]
[ROW][C]229[/C][C]0.0856069[/C][C]0.171214[/C][C]0.914393[/C][/ROW]
[ROW][C]230[/C][C]0.0831418[/C][C]0.166284[/C][C]0.916858[/C][/ROW]
[ROW][C]231[/C][C]0.065159[/C][C]0.130318[/C][C]0.934841[/C][/ROW]
[ROW][C]232[/C][C]0.0546244[/C][C]0.109249[/C][C]0.945376[/C][/ROW]
[ROW][C]233[/C][C]0.0921814[/C][C]0.184363[/C][C]0.907819[/C][/ROW]
[ROW][C]234[/C][C]0.0998979[/C][C]0.199796[/C][C]0.900102[/C][/ROW]
[ROW][C]235[/C][C]0.0999002[/C][C]0.1998[/C][C]0.9001[/C][/ROW]
[ROW][C]236[/C][C]0.0811758[/C][C]0.162352[/C][C]0.918824[/C][/ROW]
[ROW][C]237[/C][C]0.128415[/C][C]0.25683[/C][C]0.871585[/C][/ROW]
[ROW][C]238[/C][C]0.160403[/C][C]0.320806[/C][C]0.839597[/C][/ROW]
[ROW][C]239[/C][C]0.291828[/C][C]0.583657[/C][C]0.708172[/C][/ROW]
[ROW][C]240[/C][C]0.318161[/C][C]0.636322[/C][C]0.681839[/C][/ROW]
[ROW][C]241[/C][C]0.271829[/C][C]0.543657[/C][C]0.728171[/C][/ROW]
[ROW][C]242[/C][C]0.302312[/C][C]0.604624[/C][C]0.697688[/C][/ROW]
[ROW][C]243[/C][C]0.239892[/C][C]0.479783[/C][C]0.760108[/C][/ROW]
[ROW][C]244[/C][C]0.185902[/C][C]0.371804[/C][C]0.814098[/C][/ROW]
[ROW][C]245[/C][C]0.298836[/C][C]0.597672[/C][C]0.701164[/C][/ROW]
[ROW][C]246[/C][C]0.331281[/C][C]0.662562[/C][C]0.668719[/C][/ROW]
[ROW][C]247[/C][C]0.260421[/C][C]0.520841[/C][C]0.739579[/C][/ROW]
[ROW][C]248[/C][C]0.332797[/C][C]0.665594[/C][C]0.667203[/C][/ROW]
[ROW][C]249[/C][C]0.398975[/C][C]0.797949[/C][C]0.601025[/C][/ROW]
[ROW][C]250[/C][C]0.323586[/C][C]0.647171[/C][C]0.676414[/C][/ROW]
[ROW][C]251[/C][C]0.357651[/C][C]0.715301[/C][C]0.642349[/C][/ROW]
[ROW][C]252[/C][C]0.963738[/C][C]0.0725236[/C][C]0.0362618[/C][/ROW]
[ROW][C]253[/C][C]0.936455[/C][C]0.127089[/C][C]0.0635446[/C][/ROW]
[ROW][C]254[/C][C]0.950598[/C][C]0.0988046[/C][C]0.0494023[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253181&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253181&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
100.9396040.1207930.0603964
110.9039180.1921650.0960824
120.9993380.00132340.0006617
130.9986070.002786820.00139341
140.9971870.005626960.00281348
150.9954340.009132240.00456612
160.9918580.01628430.00814215
170.9861320.02773520.0138676
180.9787990.04240190.0212009
190.9790890.04182210.0209111
200.9677360.06452850.0322642
210.955280.08944090.0447204
220.9391160.1217680.060884
230.923510.152980.0764902
240.8968980.2062050.103102
250.8711040.2577920.128896
260.9519180.09616410.048082
270.9356990.1286020.0643009
280.9224420.1551160.0775582
290.9029240.1941520.0970759
300.8779860.2440280.122014
310.8804190.2391610.119581
320.851260.2974810.14874
330.8247150.350570.175285
340.7868050.4263910.213195
350.7435870.5128260.256413
360.7536810.4926390.246319
370.8101360.3797280.189864
380.7728210.4543570.227179
390.740630.5187390.25937
400.7456640.5086720.254336
410.7356870.5286260.264313
420.7109050.578190.289095
430.7681050.4637910.231895
440.7308680.5382630.269132
450.6915430.6169140.308457
460.6709530.6580940.329047
470.6888340.6223330.311166
480.651780.6964410.34822
490.6850620.6298760.314938
500.6575460.6849080.342454
510.6442640.7114710.355736
520.6054860.7890290.394514
530.6044730.7910540.395527
540.5606510.8786990.439349
550.5818390.8363220.418161
560.6002720.7994560.399728
570.5754810.8490380.424519
580.6080190.7839610.391981
590.6346420.7307170.365358
600.6077540.7844920.392246
610.6215750.756850.378425
620.584650.8307010.41535
630.564610.870780.43539
640.5221350.9557310.477865
650.4795240.9590480.520476
660.4944010.9888020.505599
670.5012710.9974570.498729
680.484060.9681210.51594
690.4431110.8862220.556889
700.4178480.8356950.582152
710.3791770.7583550.620823
720.3593030.7186060.640697
730.3282320.6564650.671768
740.3175870.6351750.682413
750.2941980.5883950.705802
760.4434740.8869490.556526
770.4244780.8489570.575522
780.4545860.9091720.545414
790.4173530.8347060.582647
800.4970630.9941250.502937
810.4651610.9303220.534839
820.4760340.9520680.523966
830.4383360.8766730.561664
840.4009670.8019340.599033
850.3646920.7293840.635308
860.3311990.6623980.668801
870.3010680.6021360.698932
880.2708240.5416480.729176
890.3500770.7001550.649923
900.3269270.6538540.673073
910.300860.6017210.69914
920.2711180.5422350.728882
930.2618990.5237990.738101
940.237690.475380.76231
950.2095990.4191990.790401
960.1978290.3956570.802171
970.182570.3651410.81743
980.1592180.3184360.840782
990.1536310.3072620.846369
1000.1337740.2675490.866226
1010.1253830.2507660.874617
1020.1103530.2207050.889647
1030.1319330.2638650.868067
1040.1487420.2974830.851258
1050.1538220.3076430.846178
1060.133060.266120.86694
1070.1506250.3012490.849375
1080.1351790.2703580.864821
1090.2599630.5199250.740037
1100.2506440.5012880.749356
1110.224040.4480790.77596
1120.2141950.4283890.785805
1130.1890350.378070.810965
1140.1742860.3485720.825714
1150.1531170.3062350.846883
1160.132980.2659610.86702
1170.1154670.2309340.884533
1180.1426680.2853350.857332
1190.142350.28470.85765
1200.1232730.2465470.876727
1210.1121470.2242940.887853
1220.09779350.1955870.902206
1230.1158550.231710.884145
1240.1019330.2038670.898067
1250.09786130.1957230.902139
1260.09208510.184170.907915
1270.07987580.1597520.920124
1280.07333710.1466740.926663
1290.06205420.1241080.937946
1300.06295380.1259080.937046
1310.06398280.1279660.936017
1320.06000770.1200150.939992
1330.05545750.1109150.944543
1340.0462280.0924560.953772
1350.0474160.0948320.952584
1360.1076440.2152880.892356
1370.09297520.185950.907025
1380.07909790.1581960.920902
1390.07278350.1455670.927216
1400.07002760.1400550.929972
1410.07334540.1466910.926655
1420.07179680.1435940.928203
1430.06061740.1212350.939383
1440.05083630.1016730.949164
1450.0422210.0844420.957779
1460.03520590.07041180.964794
1470.0350320.07006390.964968
1480.03870070.07740140.961299
1490.03639480.07278950.963605
1500.03014170.06028350.969858
1510.03381570.06763150.966184
1520.03378780.06757560.966212
1530.03251230.06502460.967488
1540.03001030.06002050.96999
1550.03731550.07463090.962685
1560.03107460.06214930.968925
1570.02540970.05081940.97459
1580.0228970.0457940.977103
1590.03093860.06187720.969061
1600.03456410.06912810.965436
1610.03141210.06282420.968588
1620.09037850.1807570.909622
1630.07708110.1541620.922919
1640.2774830.5549670.722517
1650.2589890.5179780.741011
1660.38170.7633990.6183
1670.3513780.7027560.648622
1680.3233170.6466330.676683
1690.291690.5833810.70831
1700.2636820.5273630.736318
1710.2811070.5622140.718893
1720.2511060.5022120.748894
1730.3118140.6236290.688186
1740.2973850.594770.702615
1750.2729560.5459110.727044
1760.3438820.6877650.656118
1770.3164330.6328660.683567
1780.3184280.6368550.681572
1790.3003610.6007210.699639
1800.2814370.5628740.718563
1810.2857390.5714780.714261
1820.3801310.7602620.619869
1830.3526140.7052270.647386
1840.3590460.7180920.640954
1850.3352240.6704470.664776
1860.4148070.8296130.585193
1870.378880.757760.62112
1880.3420140.6840280.657986
1890.3120010.6240010.687999
1900.3901350.780270.609865
1910.5037270.9925460.496273
1920.5342890.9314210.465711
1930.5317120.9365750.468288
1940.4930160.9860320.506984
1950.4643280.9286570.535672
1960.4845890.9691770.515411
1970.6575630.6848740.342437
1980.6529250.6941510.347075
1990.6139860.7720280.386014
2000.5765650.8468690.423435
2010.5345030.9309950.465497
2020.4944430.9888870.505557
2030.452290.904580.54771
2040.4241070.8482140.575893
2050.3904890.7809780.609511
2060.3499540.6999090.650046
2070.3101030.6202060.689897
2080.2846230.5692450.715377
2090.2481090.4962190.751891
2100.2208770.4417540.779123
2110.1966260.3932520.803374
2120.167720.3354390.83228
2130.1849380.3698750.815062
2140.1719980.3439970.828002
2150.1464150.292830.853585
2160.1229290.2458590.877071
2170.1086030.2172050.891397
2180.08818980.176380.91181
2190.08875420.1775080.911246
2200.08681660.1736330.913183
2210.09913230.1982650.900868
2220.08511020.170220.91489
2230.06773960.1354790.93226
2240.06995140.1399030.930049
2250.06629660.1325930.933703
2260.05378520.107570.946215
2270.04099450.0819890.959005
2280.06046780.1209360.939532
2290.08560690.1712140.914393
2300.08314180.1662840.916858
2310.0651590.1303180.934841
2320.05462440.1092490.945376
2330.09218140.1843630.907819
2340.09989790.1997960.900102
2350.09990020.19980.9001
2360.08117580.1623520.918824
2370.1284150.256830.871585
2380.1604030.3208060.839597
2390.2918280.5836570.708172
2400.3181610.6363220.681839
2410.2718290.5436570.728171
2420.3023120.6046240.697688
2430.2398920.4797830.760108
2440.1859020.3718040.814098
2450.2988360.5976720.701164
2460.3312810.6625620.668719
2470.2604210.5208410.739579
2480.3327970.6655940.667203
2490.3989750.7979490.601025
2500.3235860.6471710.676414
2510.3576510.7153010.642349
2520.9637380.07252360.0362618
2530.9364550.1270890.0635446
2540.9505980.09880460.0494023






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0163265NOK
5% type I error level90.0367347OK
10% type I error level330.134694NOK

\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 & 4 & 0.0163265 & NOK \tabularnewline
5% type I error level & 9 & 0.0367347 & OK \tabularnewline
10% type I error level & 33 & 0.134694 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253181&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]4[/C][C]0.0163265[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]9[/C][C]0.0367347[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]33[/C][C]0.134694[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253181&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253181&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 level40.0163265NOK
5% type I error level90.0367347OK
10% type I error level330.134694NOK


Figures (Output of Computation)

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

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