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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 15 Nov 2013 09:19:23 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/15/t1384525197eiryovx7wsll4l1.htm/, Retrieved Tue, 30 Apr 2024 09:59:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=225489, Retrieved Tue, 30 Apr 2024 09:59:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact54

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2013-11-15 14:19:23] [df6648d3354c48eb8905db6c004499bd] [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 time17 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 17 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225489&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]17 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225489&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225489&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 time17 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 14.8572 + 0.0123869Connected[t] + 0.0100955Separate[t] + 0.11369Learning[t] -0.00690721Software[t] -0.379372Depression[t] + 0.0351116Sport2[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  14.8572 +  0.0123869Connected[t] +  0.0100955Separate[t] +  0.11369Learning[t] -0.00690721Software[t] -0.379372Depression[t] +  0.0351116Sport2[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225489&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  14.8572 +  0.0123869Connected[t] +  0.0100955Separate[t] +  0.11369Learning[t] -0.00690721Software[t] -0.379372Depression[t] +  0.0351116Sport2[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225489&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225489&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 14.8572 + 0.0123869Connected[t] + 0.0100955Separate[t] + 0.11369Learning[t] -0.00690721Software[t] -0.379372Depression[t] + 0.0351116Sport2[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)14.85721.770028.3943.18829e-151.59414e-15
Connected0.01238690.03726920.33240.7398860.369943
Separate0.01009550.0382490.26390.7920360.396018
Learning0.113690.06648721.710.08848080.0442404
Software-0.006907210.0687497-0.10050.920050.460025
Depression-0.3793720.0382728-9.9128.00739e-204.00369e-20
Sport20.03511160.01900391.8480.06580980.0329049

\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) & 14.8572 & 1.77002 & 8.394 & 3.18829e-15 & 1.59414e-15 \tabularnewline
Connected & 0.0123869 & 0.0372692 & 0.3324 & 0.739886 & 0.369943 \tabularnewline
Separate & 0.0100955 & 0.038249 & 0.2639 & 0.792036 & 0.396018 \tabularnewline
Learning & 0.11369 & 0.0664872 & 1.71 & 0.0884808 & 0.0442404 \tabularnewline
Software & -0.00690721 & 0.0687497 & -0.1005 & 0.92005 & 0.460025 \tabularnewline
Depression & -0.379372 & 0.0382728 & -9.912 & 8.00739e-20 & 4.00369e-20 \tabularnewline
Sport2 & 0.0351116 & 0.0190039 & 1.848 & 0.0658098 & 0.0329049 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225489&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]14.8572[/C][C]1.77002[/C][C]8.394[/C][C]3.18829e-15[/C][C]1.59414e-15[/C][/ROW]
[ROW][C]Connected[/C][C]0.0123869[/C][C]0.0372692[/C][C]0.3324[/C][C]0.739886[/C][C]0.369943[/C][/ROW]
[ROW][C]Separate[/C][C]0.0100955[/C][C]0.038249[/C][C]0.2639[/C][C]0.792036[/C][C]0.396018[/C][/ROW]
[ROW][C]Learning[/C][C]0.11369[/C][C]0.0664872[/C][C]1.71[/C][C]0.0884808[/C][C]0.0442404[/C][/ROW]
[ROW][C]Software[/C][C]-0.00690721[/C][C]0.0687497[/C][C]-0.1005[/C][C]0.92005[/C][C]0.460025[/C][/ROW]
[ROW][C]Depression[/C][C]-0.379372[/C][C]0.0382728[/C][C]-9.912[/C][C]8.00739e-20[/C][C]4.00369e-20[/C][/ROW]
[ROW][C]Sport2[/C][C]0.0351116[/C][C]0.0190039[/C][C]1.848[/C][C]0.0658098[/C][C]0.0329049[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225489&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225489&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)14.85721.770028.3943.18829e-151.59414e-15
Connected0.01238690.03726920.33240.7398860.369943
Separate0.01009550.0382490.26390.7920360.396018
Learning0.113690.06648721.710.08848080.0442404
Software-0.006907210.0687497-0.10050.920050.460025
Depression-0.3793720.0382728-9.9128.00739e-204.00369e-20
Sport20.03511160.01900391.8480.06580980.0329049






Multiple Linear Regression - Regression Statistics
Multiple R0.602821
R-squared0.363393
Adjusted R-squared0.34853
F-TEST (value)24.4504
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01675
Sum Squared Residuals1045.29

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.602821 \tabularnewline
R-squared & 0.363393 \tabularnewline
Adjusted R-squared & 0.34853 \tabularnewline
F-TEST (value) & 24.4504 \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 & 2.01675 \tabularnewline
Sum Squared Residuals & 1045.29 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225489&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.602821[/C][/ROW]
[ROW][C]R-squared[/C][C]0.363393[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.34853[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]24.4504[/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]2.01675[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1045.29[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225489&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225489&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 R0.602821
R-squared0.363393
Adjusted R-squared0.34853
F-TEST (value)24.4504
F-TEST (DF numerator)6
F-TEST (DF denominator)257
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01675
Sum Squared Residuals1045.29






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.71480.285156
21815.0242.97603
31113.8021-2.80209
41214.1253-2.12533
51610.8025.19796
61814.09023.90985
71410.68343.31662
81414.7978-0.79778
91514.95150.0484916
101514.06070.939299
111715.31751.68246
121915.50623.4938
131013.2015-3.20147
141613.31442.68558
151815.53582.46422
161413.1620.838033
171413.53120.468762
181715.62531.37466
191415.3402-1.34018
201613.64492.35507
211815.16532.8347
221113.524-2.52397
231414.4004-0.400416
241213.4402-1.44018
251715.16591.83414
26915.7669-6.76692
271614.74311.25689
281413.10240.897557
291513.6041.39595
301113.7471-2.74713
311615.48270.517299
321312.29180.708212
331714.86712.1329
341515.1109-0.110938
351413.63280.367194
361615.18520.814823
37910.3158-1.31576
381514.10240.89765
391715.10071.89928
401315.0548-2.05479
411515.5542-0.554176
421613.35392.64606
431615.94480.0551793
441212.9237-0.923694
451514.43470.565279
461113.3092-2.30915
471515.3189-0.318906
481514.68060.319411
491713.21393.78611
501314.5666-1.56662
511615.11070.889298
521413.17230.827749
531111.3385-0.33852
541213.6951-1.69512
551213.6562-1.6562
561513.36841.63161
571614.06781.93216
581515.3561-0.356122
591215.0244-3.02437
601213.2031-1.20314
61810.3635-2.3635
621314.4348-1.43482
631114.4869-3.48689
641412.88741.11257
651513.55431.44572
661015.0546-5.05455
671112.6315-1.63152
681214.3589-2.3589
691513.42791.57213
701513.56391.43613
711413.3860.613982
721612.60863.39143
731514.37530.624718
741515.3022-0.302244
751314.8695-1.86954
761212.0261-0.0260817
771713.99623.00378
781312.42990.570076
791513.63041.36955
801315.0685-2.06854
811514.80760.192437
821515.5661-0.566065
831614.22841.77157
841514.21860.781393
851414.0473-0.0472676
861513.89931.10073
871414.2676-0.267554
881312.74370.256306
89710.3852-3.38516
901713.593.40999
911312.92340.0766285
921514.12410.87593
931413.15350.846543
941313.8224-0.822425
951614.93081.06919
961212.8379-0.837913
971414.8026-0.802581
981714.90712.09286
991514.9610.0390177
1001715.19991.80006
1011212.922-0.921951
1021615.12020.879844
1031114.4672-3.46718
1041512.9832.01699
105911.3023-2.30228
1061615.00820.991796
1071512.93472.06525
1081012.8676-2.8676
109109.078160.921842
1101513.82281.17724
1111113.151-2.15098
1121315.2823-2.28226
1131411.68432.31567
1141814.05173.94829
1151615.66240.337645
1161413.01910.98091
1171413.83160.168387
1181415.0816-1.0816
1191413.6680.331986
1201212.5096-0.509556
1211413.54690.453094
1221514.83960.160394
1231516.0367-1.03672
1241514.63850.361463
1251314.7669-1.76689
1261716.19570.804253
1271715.40391.59615
1281914.96044.03962
1291513.52521.47477
1301314.6383-1.63826
131910.405-1.40499
1321515.3114-0.311368
1331512.49672.50334
1341514.27050.729451
1351613.71852.28152
136119.275031.72497
1371413.42450.575491
1381111.9226-0.922582
1391514.17430.825656
1401313.67-0.670034
1411514.72550.274465
1421613.7252.27503
1431414.7197-0.719685
1441514.27910.720917
1451614.50531.49471
1461614.58051.41947
1471113.464-2.46402
1481214.7447-2.7447
149911.4366-2.43663
1501614.11861.88141
1511312.56740.432577
1521615.4440.555951
1531214.4545-2.45447
154911.5092-2.50924
1551311.62251.37747
1561312.92340.0766285
1571413.26220.737807
1581914.96044.03962
1591315.7208-2.72078
1601211.87310.126923
1611312.60960.390352
162109.267860.732142
1631413.15170.848303
1641611.66524.33482
1651011.9894-1.98942
166118.972082.02792
1671414.2105-0.210494
1681212.833-0.833014
169912.7427-3.74266
170911.9122-2.91217
1711110.56450.435465
1721614.40521.59478
173914.1114-5.11136
1741311.22321.77679
1751613.48022.51977
1761315.3668-2.36682
177912.3975-3.3975
1781211.44460.555373
1791614.72261.27744
1801113.167-2.16699
1811414.3883-0.388273
1821314.8279-1.82794
1831515.0329-0.0329154
1841415.165-1.16502
1851613.9972.00297
1861311.691.31002
1871413.70170.298321
1881514.24250.75752
1891312.4310.568953
1901110.23560.764427
1911112.5801-1.58015
1921415.219-1.21903
1931512.71442.28564
1941112.7769-1.77692
1951513.21921.7808
1961214.314-2.31402
1971411.82542.17456
1981413.5460.454048
199811.2196-3.21964
2001313.8515-0.851506
201912.3634-3.36337
2021513.83191.1681
2031714.08132.9187
2041312.80050.199537
2051514.5960.404024
2061513.91931.08069
2071414.786-0.785972
2081612.78823.21183
2091313.0515-0.0514611
2101614.45091.54914
211911.848-2.848
2121614.77841.22156
2131112.344-1.34397
2141013.9905-3.99055
2151112.3353-1.33534
2161513.48671.51329
2171715.12871.87127
2181414.4794-0.479425
21989.99698-1.99698
2201513.83391.16613
2211114.0816-3.08161
2221613.74992.25011
2231012.307-2.30704
2241514.99690.0031111
22599.47697-0.476974
2261614.30651.69353
2271914.07244.92761
2281213.78-1.78
22989.54902-1.54902
2301113.5117-2.51174
2311413.9750.0249574
232912.1923-3.19234
2331515.2241-0.224057
2341312.81370.186294
2351615.14080.859167
2361112.9962-1.99616
2371211.33790.662088
2381313.1976-0.197599
2391014.6022-4.6022
2401113.6993-2.69934
2411214.8909-2.89088
242810.9181-2.91807
2431211.76180.2382
2441212.3949-0.394893
2451513.81441.18558
2461110.7660.234007
2471312.95560.0444012
248148.993565.00644
2491010.2901-0.290117
2501211.60470.395293
2511512.95012.04988
2521311.87851.12155
2531314.341-1.34099
2541313.994-0.994047
2551212.0394-0.039422
2561212.9464-0.946367
257910.9434-1.94338
258911.6764-2.67638
2591512.80972.19029
2601014.8184-4.81843
2611413.90560.0943792
2621513.71681.28324
26379.94148-2.94148
2641414.0263-0.0262678

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 13.7148 & 0.285156 \tabularnewline
2 & 18 & 15.024 & 2.97603 \tabularnewline
3 & 11 & 13.8021 & -2.80209 \tabularnewline
4 & 12 & 14.1253 & -2.12533 \tabularnewline
5 & 16 & 10.802 & 5.19796 \tabularnewline
6 & 18 & 14.0902 & 3.90985 \tabularnewline
7 & 14 & 10.6834 & 3.31662 \tabularnewline
8 & 14 & 14.7978 & -0.79778 \tabularnewline
9 & 15 & 14.9515 & 0.0484916 \tabularnewline
10 & 15 & 14.0607 & 0.939299 \tabularnewline
11 & 17 & 15.3175 & 1.68246 \tabularnewline
12 & 19 & 15.5062 & 3.4938 \tabularnewline
13 & 10 & 13.2015 & -3.20147 \tabularnewline
14 & 16 & 13.3144 & 2.68558 \tabularnewline
15 & 18 & 15.5358 & 2.46422 \tabularnewline
16 & 14 & 13.162 & 0.838033 \tabularnewline
17 & 14 & 13.5312 & 0.468762 \tabularnewline
18 & 17 & 15.6253 & 1.37466 \tabularnewline
19 & 14 & 15.3402 & -1.34018 \tabularnewline
20 & 16 & 13.6449 & 2.35507 \tabularnewline
21 & 18 & 15.1653 & 2.8347 \tabularnewline
22 & 11 & 13.524 & -2.52397 \tabularnewline
23 & 14 & 14.4004 & -0.400416 \tabularnewline
24 & 12 & 13.4402 & -1.44018 \tabularnewline
25 & 17 & 15.1659 & 1.83414 \tabularnewline
26 & 9 & 15.7669 & -6.76692 \tabularnewline
27 & 16 & 14.7431 & 1.25689 \tabularnewline
28 & 14 & 13.1024 & 0.897557 \tabularnewline
29 & 15 & 13.604 & 1.39595 \tabularnewline
30 & 11 & 13.7471 & -2.74713 \tabularnewline
31 & 16 & 15.4827 & 0.517299 \tabularnewline
32 & 13 & 12.2918 & 0.708212 \tabularnewline
33 & 17 & 14.8671 & 2.1329 \tabularnewline
34 & 15 & 15.1109 & -0.110938 \tabularnewline
35 & 14 & 13.6328 & 0.367194 \tabularnewline
36 & 16 & 15.1852 & 0.814823 \tabularnewline
37 & 9 & 10.3158 & -1.31576 \tabularnewline
38 & 15 & 14.1024 & 0.89765 \tabularnewline
39 & 17 & 15.1007 & 1.89928 \tabularnewline
40 & 13 & 15.0548 & -2.05479 \tabularnewline
41 & 15 & 15.5542 & -0.554176 \tabularnewline
42 & 16 & 13.3539 & 2.64606 \tabularnewline
43 & 16 & 15.9448 & 0.0551793 \tabularnewline
44 & 12 & 12.9237 & -0.923694 \tabularnewline
45 & 15 & 14.4347 & 0.565279 \tabularnewline
46 & 11 & 13.3092 & -2.30915 \tabularnewline
47 & 15 & 15.3189 & -0.318906 \tabularnewline
48 & 15 & 14.6806 & 0.319411 \tabularnewline
49 & 17 & 13.2139 & 3.78611 \tabularnewline
50 & 13 & 14.5666 & -1.56662 \tabularnewline
51 & 16 & 15.1107 & 0.889298 \tabularnewline
52 & 14 & 13.1723 & 0.827749 \tabularnewline
53 & 11 & 11.3385 & -0.33852 \tabularnewline
54 & 12 & 13.6951 & -1.69512 \tabularnewline
55 & 12 & 13.6562 & -1.6562 \tabularnewline
56 & 15 & 13.3684 & 1.63161 \tabularnewline
57 & 16 & 14.0678 & 1.93216 \tabularnewline
58 & 15 & 15.3561 & -0.356122 \tabularnewline
59 & 12 & 15.0244 & -3.02437 \tabularnewline
60 & 12 & 13.2031 & -1.20314 \tabularnewline
61 & 8 & 10.3635 & -2.3635 \tabularnewline
62 & 13 & 14.4348 & -1.43482 \tabularnewline
63 & 11 & 14.4869 & -3.48689 \tabularnewline
64 & 14 & 12.8874 & 1.11257 \tabularnewline
65 & 15 & 13.5543 & 1.44572 \tabularnewline
66 & 10 & 15.0546 & -5.05455 \tabularnewline
67 & 11 & 12.6315 & -1.63152 \tabularnewline
68 & 12 & 14.3589 & -2.3589 \tabularnewline
69 & 15 & 13.4279 & 1.57213 \tabularnewline
70 & 15 & 13.5639 & 1.43613 \tabularnewline
71 & 14 & 13.386 & 0.613982 \tabularnewline
72 & 16 & 12.6086 & 3.39143 \tabularnewline
73 & 15 & 14.3753 & 0.624718 \tabularnewline
74 & 15 & 15.3022 & -0.302244 \tabularnewline
75 & 13 & 14.8695 & -1.86954 \tabularnewline
76 & 12 & 12.0261 & -0.0260817 \tabularnewline
77 & 17 & 13.9962 & 3.00378 \tabularnewline
78 & 13 & 12.4299 & 0.570076 \tabularnewline
79 & 15 & 13.6304 & 1.36955 \tabularnewline
80 & 13 & 15.0685 & -2.06854 \tabularnewline
81 & 15 & 14.8076 & 0.192437 \tabularnewline
82 & 15 & 15.5661 & -0.566065 \tabularnewline
83 & 16 & 14.2284 & 1.77157 \tabularnewline
84 & 15 & 14.2186 & 0.781393 \tabularnewline
85 & 14 & 14.0473 & -0.0472676 \tabularnewline
86 & 15 & 13.8993 & 1.10073 \tabularnewline
87 & 14 & 14.2676 & -0.267554 \tabularnewline
88 & 13 & 12.7437 & 0.256306 \tabularnewline
89 & 7 & 10.3852 & -3.38516 \tabularnewline
90 & 17 & 13.59 & 3.40999 \tabularnewline
91 & 13 & 12.9234 & 0.0766285 \tabularnewline
92 & 15 & 14.1241 & 0.87593 \tabularnewline
93 & 14 & 13.1535 & 0.846543 \tabularnewline
94 & 13 & 13.8224 & -0.822425 \tabularnewline
95 & 16 & 14.9308 & 1.06919 \tabularnewline
96 & 12 & 12.8379 & -0.837913 \tabularnewline
97 & 14 & 14.8026 & -0.802581 \tabularnewline
98 & 17 & 14.9071 & 2.09286 \tabularnewline
99 & 15 & 14.961 & 0.0390177 \tabularnewline
100 & 17 & 15.1999 & 1.80006 \tabularnewline
101 & 12 & 12.922 & -0.921951 \tabularnewline
102 & 16 & 15.1202 & 0.879844 \tabularnewline
103 & 11 & 14.4672 & -3.46718 \tabularnewline
104 & 15 & 12.983 & 2.01699 \tabularnewline
105 & 9 & 11.3023 & -2.30228 \tabularnewline
106 & 16 & 15.0082 & 0.991796 \tabularnewline
107 & 15 & 12.9347 & 2.06525 \tabularnewline
108 & 10 & 12.8676 & -2.8676 \tabularnewline
109 & 10 & 9.07816 & 0.921842 \tabularnewline
110 & 15 & 13.8228 & 1.17724 \tabularnewline
111 & 11 & 13.151 & -2.15098 \tabularnewline
112 & 13 & 15.2823 & -2.28226 \tabularnewline
113 & 14 & 11.6843 & 2.31567 \tabularnewline
114 & 18 & 14.0517 & 3.94829 \tabularnewline
115 & 16 & 15.6624 & 0.337645 \tabularnewline
116 & 14 & 13.0191 & 0.98091 \tabularnewline
117 & 14 & 13.8316 & 0.168387 \tabularnewline
118 & 14 & 15.0816 & -1.0816 \tabularnewline
119 & 14 & 13.668 & 0.331986 \tabularnewline
120 & 12 & 12.5096 & -0.509556 \tabularnewline
121 & 14 & 13.5469 & 0.453094 \tabularnewline
122 & 15 & 14.8396 & 0.160394 \tabularnewline
123 & 15 & 16.0367 & -1.03672 \tabularnewline
124 & 15 & 14.6385 & 0.361463 \tabularnewline
125 & 13 & 14.7669 & -1.76689 \tabularnewline
126 & 17 & 16.1957 & 0.804253 \tabularnewline
127 & 17 & 15.4039 & 1.59615 \tabularnewline
128 & 19 & 14.9604 & 4.03962 \tabularnewline
129 & 15 & 13.5252 & 1.47477 \tabularnewline
130 & 13 & 14.6383 & -1.63826 \tabularnewline
131 & 9 & 10.405 & -1.40499 \tabularnewline
132 & 15 & 15.3114 & -0.311368 \tabularnewline
133 & 15 & 12.4967 & 2.50334 \tabularnewline
134 & 15 & 14.2705 & 0.729451 \tabularnewline
135 & 16 & 13.7185 & 2.28152 \tabularnewline
136 & 11 & 9.27503 & 1.72497 \tabularnewline
137 & 14 & 13.4245 & 0.575491 \tabularnewline
138 & 11 & 11.9226 & -0.922582 \tabularnewline
139 & 15 & 14.1743 & 0.825656 \tabularnewline
140 & 13 & 13.67 & -0.670034 \tabularnewline
141 & 15 & 14.7255 & 0.274465 \tabularnewline
142 & 16 & 13.725 & 2.27503 \tabularnewline
143 & 14 & 14.7197 & -0.719685 \tabularnewline
144 & 15 & 14.2791 & 0.720917 \tabularnewline
145 & 16 & 14.5053 & 1.49471 \tabularnewline
146 & 16 & 14.5805 & 1.41947 \tabularnewline
147 & 11 & 13.464 & -2.46402 \tabularnewline
148 & 12 & 14.7447 & -2.7447 \tabularnewline
149 & 9 & 11.4366 & -2.43663 \tabularnewline
150 & 16 & 14.1186 & 1.88141 \tabularnewline
151 & 13 & 12.5674 & 0.432577 \tabularnewline
152 & 16 & 15.444 & 0.555951 \tabularnewline
153 & 12 & 14.4545 & -2.45447 \tabularnewline
154 & 9 & 11.5092 & -2.50924 \tabularnewline
155 & 13 & 11.6225 & 1.37747 \tabularnewline
156 & 13 & 12.9234 & 0.0766285 \tabularnewline
157 & 14 & 13.2622 & 0.737807 \tabularnewline
158 & 19 & 14.9604 & 4.03962 \tabularnewline
159 & 13 & 15.7208 & -2.72078 \tabularnewline
160 & 12 & 11.8731 & 0.126923 \tabularnewline
161 & 13 & 12.6096 & 0.390352 \tabularnewline
162 & 10 & 9.26786 & 0.732142 \tabularnewline
163 & 14 & 13.1517 & 0.848303 \tabularnewline
164 & 16 & 11.6652 & 4.33482 \tabularnewline
165 & 10 & 11.9894 & -1.98942 \tabularnewline
166 & 11 & 8.97208 & 2.02792 \tabularnewline
167 & 14 & 14.2105 & -0.210494 \tabularnewline
168 & 12 & 12.833 & -0.833014 \tabularnewline
169 & 9 & 12.7427 & -3.74266 \tabularnewline
170 & 9 & 11.9122 & -2.91217 \tabularnewline
171 & 11 & 10.5645 & 0.435465 \tabularnewline
172 & 16 & 14.4052 & 1.59478 \tabularnewline
173 & 9 & 14.1114 & -5.11136 \tabularnewline
174 & 13 & 11.2232 & 1.77679 \tabularnewline
175 & 16 & 13.4802 & 2.51977 \tabularnewline
176 & 13 & 15.3668 & -2.36682 \tabularnewline
177 & 9 & 12.3975 & -3.3975 \tabularnewline
178 & 12 & 11.4446 & 0.555373 \tabularnewline
179 & 16 & 14.7226 & 1.27744 \tabularnewline
180 & 11 & 13.167 & -2.16699 \tabularnewline
181 & 14 & 14.3883 & -0.388273 \tabularnewline
182 & 13 & 14.8279 & -1.82794 \tabularnewline
183 & 15 & 15.0329 & -0.0329154 \tabularnewline
184 & 14 & 15.165 & -1.16502 \tabularnewline
185 & 16 & 13.997 & 2.00297 \tabularnewline
186 & 13 & 11.69 & 1.31002 \tabularnewline
187 & 14 & 13.7017 & 0.298321 \tabularnewline
188 & 15 & 14.2425 & 0.75752 \tabularnewline
189 & 13 & 12.431 & 0.568953 \tabularnewline
190 & 11 & 10.2356 & 0.764427 \tabularnewline
191 & 11 & 12.5801 & -1.58015 \tabularnewline
192 & 14 & 15.219 & -1.21903 \tabularnewline
193 & 15 & 12.7144 & 2.28564 \tabularnewline
194 & 11 & 12.7769 & -1.77692 \tabularnewline
195 & 15 & 13.2192 & 1.7808 \tabularnewline
196 & 12 & 14.314 & -2.31402 \tabularnewline
197 & 14 & 11.8254 & 2.17456 \tabularnewline
198 & 14 & 13.546 & 0.454048 \tabularnewline
199 & 8 & 11.2196 & -3.21964 \tabularnewline
200 & 13 & 13.8515 & -0.851506 \tabularnewline
201 & 9 & 12.3634 & -3.36337 \tabularnewline
202 & 15 & 13.8319 & 1.1681 \tabularnewline
203 & 17 & 14.0813 & 2.9187 \tabularnewline
204 & 13 & 12.8005 & 0.199537 \tabularnewline
205 & 15 & 14.596 & 0.404024 \tabularnewline
206 & 15 & 13.9193 & 1.08069 \tabularnewline
207 & 14 & 14.786 & -0.785972 \tabularnewline
208 & 16 & 12.7882 & 3.21183 \tabularnewline
209 & 13 & 13.0515 & -0.0514611 \tabularnewline
210 & 16 & 14.4509 & 1.54914 \tabularnewline
211 & 9 & 11.848 & -2.848 \tabularnewline
212 & 16 & 14.7784 & 1.22156 \tabularnewline
213 & 11 & 12.344 & -1.34397 \tabularnewline
214 & 10 & 13.9905 & -3.99055 \tabularnewline
215 & 11 & 12.3353 & -1.33534 \tabularnewline
216 & 15 & 13.4867 & 1.51329 \tabularnewline
217 & 17 & 15.1287 & 1.87127 \tabularnewline
218 & 14 & 14.4794 & -0.479425 \tabularnewline
219 & 8 & 9.99698 & -1.99698 \tabularnewline
220 & 15 & 13.8339 & 1.16613 \tabularnewline
221 & 11 & 14.0816 & -3.08161 \tabularnewline
222 & 16 & 13.7499 & 2.25011 \tabularnewline
223 & 10 & 12.307 & -2.30704 \tabularnewline
224 & 15 & 14.9969 & 0.0031111 \tabularnewline
225 & 9 & 9.47697 & -0.476974 \tabularnewline
226 & 16 & 14.3065 & 1.69353 \tabularnewline
227 & 19 & 14.0724 & 4.92761 \tabularnewline
228 & 12 & 13.78 & -1.78 \tabularnewline
229 & 8 & 9.54902 & -1.54902 \tabularnewline
230 & 11 & 13.5117 & -2.51174 \tabularnewline
231 & 14 & 13.975 & 0.0249574 \tabularnewline
232 & 9 & 12.1923 & -3.19234 \tabularnewline
233 & 15 & 15.2241 & -0.224057 \tabularnewline
234 & 13 & 12.8137 & 0.186294 \tabularnewline
235 & 16 & 15.1408 & 0.859167 \tabularnewline
236 & 11 & 12.9962 & -1.99616 \tabularnewline
237 & 12 & 11.3379 & 0.662088 \tabularnewline
238 & 13 & 13.1976 & -0.197599 \tabularnewline
239 & 10 & 14.6022 & -4.6022 \tabularnewline
240 & 11 & 13.6993 & -2.69934 \tabularnewline
241 & 12 & 14.8909 & -2.89088 \tabularnewline
242 & 8 & 10.9181 & -2.91807 \tabularnewline
243 & 12 & 11.7618 & 0.2382 \tabularnewline
244 & 12 & 12.3949 & -0.394893 \tabularnewline
245 & 15 & 13.8144 & 1.18558 \tabularnewline
246 & 11 & 10.766 & 0.234007 \tabularnewline
247 & 13 & 12.9556 & 0.0444012 \tabularnewline
248 & 14 & 8.99356 & 5.00644 \tabularnewline
249 & 10 & 10.2901 & -0.290117 \tabularnewline
250 & 12 & 11.6047 & 0.395293 \tabularnewline
251 & 15 & 12.9501 & 2.04988 \tabularnewline
252 & 13 & 11.8785 & 1.12155 \tabularnewline
253 & 13 & 14.341 & -1.34099 \tabularnewline
254 & 13 & 13.994 & -0.994047 \tabularnewline
255 & 12 & 12.0394 & -0.039422 \tabularnewline
256 & 12 & 12.9464 & -0.946367 \tabularnewline
257 & 9 & 10.9434 & -1.94338 \tabularnewline
258 & 9 & 11.6764 & -2.67638 \tabularnewline
259 & 15 & 12.8097 & 2.19029 \tabularnewline
260 & 10 & 14.8184 & -4.81843 \tabularnewline
261 & 14 & 13.9056 & 0.0943792 \tabularnewline
262 & 15 & 13.7168 & 1.28324 \tabularnewline
263 & 7 & 9.94148 & -2.94148 \tabularnewline
264 & 14 & 14.0263 & -0.0262678 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225489&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]14[/C][C]13.7148[/C][C]0.285156[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.024[/C][C]2.97603[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.8021[/C][C]-2.80209[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.1253[/C][C]-2.12533[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]10.802[/C][C]5.19796[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.0902[/C][C]3.90985[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.6834[/C][C]3.31662[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.7978[/C][C]-0.79778[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]14.9515[/C][C]0.0484916[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.0607[/C][C]0.939299[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.3175[/C][C]1.68246[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.5062[/C][C]3.4938[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.2015[/C][C]-3.20147[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.3144[/C][C]2.68558[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.5358[/C][C]2.46422[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.162[/C][C]0.838033[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.5312[/C][C]0.468762[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.6253[/C][C]1.37466[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.3402[/C][C]-1.34018[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.6449[/C][C]2.35507[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.1653[/C][C]2.8347[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.524[/C][C]-2.52397[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.4004[/C][C]-0.400416[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.4402[/C][C]-1.44018[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.1659[/C][C]1.83414[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.7669[/C][C]-6.76692[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.7431[/C][C]1.25689[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.1024[/C][C]0.897557[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.604[/C][C]1.39595[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]13.7471[/C][C]-2.74713[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.4827[/C][C]0.517299[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.2918[/C][C]0.708212[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]14.8671[/C][C]2.1329[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.1109[/C][C]-0.110938[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.6328[/C][C]0.367194[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.1852[/C][C]0.814823[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.3158[/C][C]-1.31576[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.1024[/C][C]0.89765[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.1007[/C][C]1.89928[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.0548[/C][C]-2.05479[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.5542[/C][C]-0.554176[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.3539[/C][C]2.64606[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.9448[/C][C]0.0551793[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]12.9237[/C][C]-0.923694[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.4347[/C][C]0.565279[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.3092[/C][C]-2.30915[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.3189[/C][C]-0.318906[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.6806[/C][C]0.319411[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.2139[/C][C]3.78611[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.5666[/C][C]-1.56662[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.1107[/C][C]0.889298[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.1723[/C][C]0.827749[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.3385[/C][C]-0.33852[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.6951[/C][C]-1.69512[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]13.6562[/C][C]-1.6562[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.3684[/C][C]1.63161[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.0678[/C][C]1.93216[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.3561[/C][C]-0.356122[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.0244[/C][C]-3.02437[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.2031[/C][C]-1.20314[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.3635[/C][C]-2.3635[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.4348[/C][C]-1.43482[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.4869[/C][C]-3.48689[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]12.8874[/C][C]1.11257[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.5543[/C][C]1.44572[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.0546[/C][C]-5.05455[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.6315[/C][C]-1.63152[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.3589[/C][C]-2.3589[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.4279[/C][C]1.57213[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.5639[/C][C]1.43613[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.386[/C][C]0.613982[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.6086[/C][C]3.39143[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.3753[/C][C]0.624718[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.3022[/C][C]-0.302244[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.8695[/C][C]-1.86954[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.0261[/C][C]-0.0260817[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]13.9962[/C][C]3.00378[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.4299[/C][C]0.570076[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.6304[/C][C]1.36955[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]15.0685[/C][C]-2.06854[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.8076[/C][C]0.192437[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.5661[/C][C]-0.566065[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.2284[/C][C]1.77157[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2186[/C][C]0.781393[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.0473[/C][C]-0.0472676[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.8993[/C][C]1.10073[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.2676[/C][C]-0.267554[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.7437[/C][C]0.256306[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.3852[/C][C]-3.38516[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.59[/C][C]3.40999[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.9234[/C][C]0.0766285[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.1241[/C][C]0.87593[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.1535[/C][C]0.846543[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.8224[/C][C]-0.822425[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.9308[/C][C]1.06919[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.8379[/C][C]-0.837913[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.8026[/C][C]-0.802581[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.9071[/C][C]2.09286[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]14.961[/C][C]0.0390177[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.1999[/C][C]1.80006[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.922[/C][C]-0.921951[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]15.1202[/C][C]0.879844[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.4672[/C][C]-3.46718[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]12.983[/C][C]2.01699[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.3023[/C][C]-2.30228[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]15.0082[/C][C]0.991796[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9347[/C][C]2.06525[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.8676[/C][C]-2.8676[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.07816[/C][C]0.921842[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.8228[/C][C]1.17724[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.151[/C][C]-2.15098[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.2823[/C][C]-2.28226[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]11.6843[/C][C]2.31567[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.0517[/C][C]3.94829[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.6624[/C][C]0.337645[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.0191[/C][C]0.98091[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.8316[/C][C]0.168387[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.0816[/C][C]-1.0816[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.668[/C][C]0.331986[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.5096[/C][C]-0.509556[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.5469[/C][C]0.453094[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.8396[/C][C]0.160394[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]16.0367[/C][C]-1.03672[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.6385[/C][C]0.361463[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.7669[/C][C]-1.76689[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.1957[/C][C]0.804253[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.4039[/C][C]1.59615[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.9604[/C][C]4.03962[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5252[/C][C]1.47477[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.6383[/C][C]-1.63826[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.405[/C][C]-1.40499[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.3114[/C][C]-0.311368[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.4967[/C][C]2.50334[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.2705[/C][C]0.729451[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.7185[/C][C]2.28152[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.27503[/C][C]1.72497[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.4245[/C][C]0.575491[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]11.9226[/C][C]-0.922582[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.1743[/C][C]0.825656[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.67[/C][C]-0.670034[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.7255[/C][C]0.274465[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.725[/C][C]2.27503[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.7197[/C][C]-0.719685[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.2791[/C][C]0.720917[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.5053[/C][C]1.49471[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.5805[/C][C]1.41947[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.464[/C][C]-2.46402[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.7447[/C][C]-2.7447[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.4366[/C][C]-2.43663[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.1186[/C][C]1.88141[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.5674[/C][C]0.432577[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.444[/C][C]0.555951[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.4545[/C][C]-2.45447[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.5092[/C][C]-2.50924[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.6225[/C][C]1.37747[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.9234[/C][C]0.0766285[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.2622[/C][C]0.737807[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.9604[/C][C]4.03962[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.7208[/C][C]-2.72078[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.8731[/C][C]0.126923[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6096[/C][C]0.390352[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.26786[/C][C]0.732142[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.1517[/C][C]0.848303[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.6652[/C][C]4.33482[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.9894[/C][C]-1.98942[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]8.97208[/C][C]2.02792[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.2105[/C][C]-0.210494[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.833[/C][C]-0.833014[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.7427[/C][C]-3.74266[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.9122[/C][C]-2.91217[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.5645[/C][C]0.435465[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.4052[/C][C]1.59478[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]14.1114[/C][C]-5.11136[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.2232[/C][C]1.77679[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.4802[/C][C]2.51977[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.3668[/C][C]-2.36682[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.3975[/C][C]-3.3975[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.4446[/C][C]0.555373[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.7226[/C][C]1.27744[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.167[/C][C]-2.16699[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]14.3883[/C][C]-0.388273[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.8279[/C][C]-1.82794[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]15.0329[/C][C]-0.0329154[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]15.165[/C][C]-1.16502[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]13.997[/C][C]2.00297[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.69[/C][C]1.31002[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.7017[/C][C]0.298321[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.2425[/C][C]0.75752[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.431[/C][C]0.568953[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.2356[/C][C]0.764427[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.5801[/C][C]-1.58015[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]15.219[/C][C]-1.21903[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.7144[/C][C]2.28564[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.7769[/C][C]-1.77692[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.2192[/C][C]1.7808[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.314[/C][C]-2.31402[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.8254[/C][C]2.17456[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.546[/C][C]0.454048[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.2196[/C][C]-3.21964[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.8515[/C][C]-0.851506[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.3634[/C][C]-3.36337[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.8319[/C][C]1.1681[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]14.0813[/C][C]2.9187[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.8005[/C][C]0.199537[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.596[/C][C]0.404024[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.9193[/C][C]1.08069[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.786[/C][C]-0.785972[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.7882[/C][C]3.21183[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]13.0515[/C][C]-0.0514611[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.4509[/C][C]1.54914[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.848[/C][C]-2.848[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.7784[/C][C]1.22156[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.344[/C][C]-1.34397[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.9905[/C][C]-3.99055[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.3353[/C][C]-1.33534[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.4867[/C][C]1.51329[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]15.1287[/C][C]1.87127[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.4794[/C][C]-0.479425[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.99698[/C][C]-1.99698[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.8339[/C][C]1.16613[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]14.0816[/C][C]-3.08161[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.7499[/C][C]2.25011[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.307[/C][C]-2.30704[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.9969[/C][C]0.0031111[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.47697[/C][C]-0.476974[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.3065[/C][C]1.69353[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]14.0724[/C][C]4.92761[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.78[/C][C]-1.78[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.54902[/C][C]-1.54902[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.5117[/C][C]-2.51174[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.975[/C][C]0.0249574[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]12.1923[/C][C]-3.19234[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]15.2241[/C][C]-0.224057[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.8137[/C][C]0.186294[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]15.1408[/C][C]0.859167[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.9962[/C][C]-1.99616[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.3379[/C][C]0.662088[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.1976[/C][C]-0.197599[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.6022[/C][C]-4.6022[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.6993[/C][C]-2.69934[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.8909[/C][C]-2.89088[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.9181[/C][C]-2.91807[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.7618[/C][C]0.2382[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.3949[/C][C]-0.394893[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.8144[/C][C]1.18558[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.766[/C][C]0.234007[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.9556[/C][C]0.0444012[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.99356[/C][C]5.00644[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.2901[/C][C]-0.290117[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.6047[/C][C]0.395293[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.9501[/C][C]2.04988[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.8785[/C][C]1.12155[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.341[/C][C]-1.34099[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.994[/C][C]-0.994047[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]12.0394[/C][C]-0.039422[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.9464[/C][C]-0.946367[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.9434[/C][C]-1.94338[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.6764[/C][C]-2.67638[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.8097[/C][C]2.19029[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.8184[/C][C]-4.81843[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.9056[/C][C]0.0943792[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.7168[/C][C]1.28324[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.94148[/C][C]-2.94148[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]14.0263[/C][C]-0.0262678[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225489&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225489&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
11413.71480.285156
21815.0242.97603
31113.8021-2.80209
41214.1253-2.12533
51610.8025.19796
61814.09023.90985
71410.68343.31662
81414.7978-0.79778
91514.95150.0484916
101514.06070.939299
111715.31751.68246
121915.50623.4938
131013.2015-3.20147
141613.31442.68558
151815.53582.46422
161413.1620.838033
171413.53120.468762
181715.62531.37466
191415.3402-1.34018
201613.64492.35507
211815.16532.8347
221113.524-2.52397
231414.4004-0.400416
241213.4402-1.44018
251715.16591.83414
26915.7669-6.76692
271614.74311.25689
281413.10240.897557
291513.6041.39595
301113.7471-2.74713
311615.48270.517299
321312.29180.708212
331714.86712.1329
341515.1109-0.110938
351413.63280.367194
361615.18520.814823
37910.3158-1.31576
381514.10240.89765
391715.10071.89928
401315.0548-2.05479
411515.5542-0.554176
421613.35392.64606
431615.94480.0551793
441212.9237-0.923694
451514.43470.565279
461113.3092-2.30915
471515.3189-0.318906
481514.68060.319411
491713.21393.78611
501314.5666-1.56662
511615.11070.889298
521413.17230.827749
531111.3385-0.33852
541213.6951-1.69512
551213.6562-1.6562
561513.36841.63161
571614.06781.93216
581515.3561-0.356122
591215.0244-3.02437
601213.2031-1.20314
61810.3635-2.3635
621314.4348-1.43482
631114.4869-3.48689
641412.88741.11257
651513.55431.44572
661015.0546-5.05455
671112.6315-1.63152
681214.3589-2.3589
691513.42791.57213
701513.56391.43613
711413.3860.613982
721612.60863.39143
731514.37530.624718
741515.3022-0.302244
751314.8695-1.86954
761212.0261-0.0260817
771713.99623.00378
781312.42990.570076
791513.63041.36955
801315.0685-2.06854
811514.80760.192437
821515.5661-0.566065
831614.22841.77157
841514.21860.781393
851414.0473-0.0472676
861513.89931.10073
871414.2676-0.267554
881312.74370.256306
89710.3852-3.38516
901713.593.40999
911312.92340.0766285
921514.12410.87593
931413.15350.846543
941313.8224-0.822425
951614.93081.06919
961212.8379-0.837913
971414.8026-0.802581
981714.90712.09286
991514.9610.0390177
1001715.19991.80006
1011212.922-0.921951
1021615.12020.879844
1031114.4672-3.46718
1041512.9832.01699
105911.3023-2.30228
1061615.00820.991796
1071512.93472.06525
1081012.8676-2.8676
109109.078160.921842
1101513.82281.17724
1111113.151-2.15098
1121315.2823-2.28226
1131411.68432.31567
1141814.05173.94829
1151615.66240.337645
1161413.01910.98091
1171413.83160.168387
1181415.0816-1.0816
1191413.6680.331986
1201212.5096-0.509556
1211413.54690.453094
1221514.83960.160394
1231516.0367-1.03672
1241514.63850.361463
1251314.7669-1.76689
1261716.19570.804253
1271715.40391.59615
1281914.96044.03962
1291513.52521.47477
1301314.6383-1.63826
131910.405-1.40499
1321515.3114-0.311368
1331512.49672.50334
1341514.27050.729451
1351613.71852.28152
136119.275031.72497
1371413.42450.575491
1381111.9226-0.922582
1391514.17430.825656
1401313.67-0.670034
1411514.72550.274465
1421613.7252.27503
1431414.7197-0.719685
1441514.27910.720917
1451614.50531.49471
1461614.58051.41947
1471113.464-2.46402
1481214.7447-2.7447
149911.4366-2.43663
1501614.11861.88141
1511312.56740.432577
1521615.4440.555951
1531214.4545-2.45447
154911.5092-2.50924
1551311.62251.37747
1561312.92340.0766285
1571413.26220.737807
1581914.96044.03962
1591315.7208-2.72078
1601211.87310.126923
1611312.60960.390352
162109.267860.732142
1631413.15170.848303
1641611.66524.33482
1651011.9894-1.98942
166118.972082.02792
1671414.2105-0.210494
1681212.833-0.833014
169912.7427-3.74266
170911.9122-2.91217
1711110.56450.435465
1721614.40521.59478
173914.1114-5.11136
1741311.22321.77679
1751613.48022.51977
1761315.3668-2.36682
177912.3975-3.3975
1781211.44460.555373
1791614.72261.27744
1801113.167-2.16699
1811414.3883-0.388273
1821314.8279-1.82794
1831515.0329-0.0329154
1841415.165-1.16502
1851613.9972.00297
1861311.691.31002
1871413.70170.298321
1881514.24250.75752
1891312.4310.568953
1901110.23560.764427
1911112.5801-1.58015
1921415.219-1.21903
1931512.71442.28564
1941112.7769-1.77692
1951513.21921.7808
1961214.314-2.31402
1971411.82542.17456
1981413.5460.454048
199811.2196-3.21964
2001313.8515-0.851506
201912.3634-3.36337
2021513.83191.1681
2031714.08132.9187
2041312.80050.199537
2051514.5960.404024
2061513.91931.08069
2071414.786-0.785972
2081612.78823.21183
2091313.0515-0.0514611
2101614.45091.54914
211911.848-2.848
2121614.77841.22156
2131112.344-1.34397
2141013.9905-3.99055
2151112.3353-1.33534
2161513.48671.51329
2171715.12871.87127
2181414.4794-0.479425
21989.99698-1.99698
2201513.83391.16613
2211114.0816-3.08161
2221613.74992.25011
2231012.307-2.30704
2241514.99690.0031111
22599.47697-0.476974
2261614.30651.69353
2271914.07244.92761
2281213.78-1.78
22989.54902-1.54902
2301113.5117-2.51174
2311413.9750.0249574
232912.1923-3.19234
2331515.2241-0.224057
2341312.81370.186294
2351615.14080.859167
2361112.9962-1.99616
2371211.33790.662088
2381313.1976-0.197599
2391014.6022-4.6022
2401113.6993-2.69934
2411214.8909-2.89088
242810.9181-2.91807
2431211.76180.2382
2441212.3949-0.394893
2451513.81441.18558
2461110.7660.234007
2471312.95560.0444012
248148.993565.00644
2491010.2901-0.290117
2501211.60470.395293
2511512.95012.04988
2521311.87851.12155
2531314.341-1.34099
2541313.994-0.994047
2551212.0394-0.039422
2561212.9464-0.946367
257910.9434-1.94338
258911.6764-2.67638
2591512.80972.19029
2601014.8184-4.81843
2611413.90560.0943792
2621513.71681.28324
26379.94148-2.94148
2641414.0263-0.0262678






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.07873180.1574640.921268
110.02607970.05215950.97392
120.8351340.3297310.164866
130.9668490.06630160.0331508
140.9682310.06353880.0317694
150.9787080.04258420.0212921
160.9644690.07106270.0355313
170.9512060.09758760.0487938
180.9355110.1289770.0644887
190.9164950.1670110.0835053
200.9086060.1827870.0913936
210.9215740.1568510.0784257
220.9557980.0884040.044202
230.9382540.1234910.0617457
240.9258750.148250.0741252
250.9030030.1939940.0969971
260.9983320.003335530.00166777
270.9975330.004933320.00246666
280.996220.007560790.00378039
290.9944370.01112570.00556283
300.9972740.005452020.00272601
310.9958760.008247050.00412353
320.9939890.01202280.00601142
330.992750.01450020.00725009
340.9896560.02068770.0103438
350.9859440.0281130.0140565
360.9805910.0388190.0194095
370.9851410.02971810.014859
380.9798370.04032690.0201634
390.9775730.04485460.0224273
400.9778040.04439150.0221958
410.9712360.05752750.0287637
420.9698420.06031550.0301578
430.960720.07856040.0392802
440.953360.0932810.0466405
450.9407060.1185880.0592941
460.9501030.09979380.0498969
470.9367360.1265270.0632635
480.9208940.1582120.0791059
490.9429110.1141780.0570891
500.9387960.1224070.0612037
510.9258850.148230.074115
520.9094970.1810060.090503
530.894240.211520.10576
540.8960730.2078530.103927
550.8870570.2258870.112943
560.8705230.2589550.129477
570.8597630.2804740.140237
580.8343790.3312410.165621
590.861810.276380.13819
600.8562670.2874670.143733
610.8745670.2508650.125433
620.8673250.265350.132675
630.9109630.1780730.0890367
640.8995860.2008280.100414
650.8893860.2212270.110614
660.9586570.08268690.0413435
670.9574940.0850130.0425065
680.9604610.07907790.039539
690.9555160.0889680.044484
700.9493440.1013120.0506562
710.9383690.1232620.0616308
720.9528680.0942640.047132
730.9428790.1142420.0571212
740.9309950.1380110.0690054
750.9257530.1484940.0742472
760.9116980.1766050.0883023
770.924280.151440.0757202
780.9099750.180050.0900248
790.9008970.1982050.0991027
800.8948860.2102280.105114
810.8762420.2475160.123758
820.856960.2860810.14304
830.8507160.2985680.149284
840.8301460.3397080.169854
850.8047660.3904680.195234
860.7815710.4368580.218429
870.7529550.4940890.247045
880.7222890.5554220.277711
890.7945740.4108520.205426
900.8267240.3465520.173276
910.8020150.395970.197985
920.7784280.4431450.221572
930.7559520.4880960.244048
940.7302540.5394930.269746
950.7048210.5903590.295179
960.6796590.6406830.320341
970.6510640.6978720.348936
980.6520450.6959090.347955
990.6181250.763750.381875
1000.6103820.7792360.389618
1010.5861110.8277790.413889
1020.5570990.8858010.442901
1030.6129250.774150.387075
1040.603980.792040.39602
1050.6182810.7634390.381719
1060.5906790.8186410.409321
1070.5844710.8310570.415529
1080.622590.754820.37741
1090.5966920.8066170.403308
1100.5711670.8576670.428833
1110.573430.8531410.42657
1120.6041570.7916850.395843
1130.6176260.7647490.382374
1140.7006880.5986240.299312
1150.6705820.6588360.329418
1160.6481270.7037470.351873
1170.6187060.7625880.381294
1180.5960560.8078890.403944
1190.5618730.8762550.438127
1200.5319520.9360960.468048
1210.5010660.9978690.498934
1220.4687630.9375270.531237
1230.4426320.8852650.557368
1240.4090430.8180860.590957
1250.3965270.7930540.603473
1260.3666810.7333620.633319
1270.3548110.7096230.645189
1280.452430.904860.54757
1290.4350770.8701540.564923
1300.4219960.8439930.578004
1310.4066520.8133050.593348
1320.3772390.7544780.622761
1330.3964540.7929080.603546
1340.36960.73920.6304
1350.379520.7590390.62048
1360.3674160.7348310.632584
1370.33790.67580.6621
1380.3154640.6309280.684536
1390.2896730.5793460.710327
1400.2651910.5303820.734809
1410.2377460.4754930.762254
1420.2449770.4899540.755023
1430.2196170.4392340.780383
1440.1983040.3966080.801696
1450.1851180.3702360.814882
1460.1761780.3523570.823822
1470.1858570.3717140.814143
1480.2032470.4064940.796753
1490.2217330.4434660.778267
1500.2225180.4450360.777482
1510.2000350.400070.799965
1520.1801780.3603570.819822
1530.1923050.3846090.807695
1540.2085210.4170420.791479
1550.1935870.3871740.806413
1560.169930.3398610.83007
1570.1525350.305070.847465
1580.2370790.4741570.762921
1590.2557090.5114190.744291
1600.2331480.4662950.766852
1610.2105670.4211350.789433
1620.1864240.3728480.813576
1630.16530.3305990.8347
1640.2707430.5414850.729257
1650.2655090.5310180.734491
1660.2633040.5266070.736696
1670.2347080.4694170.765292
1680.2130270.4260530.786973
1690.270960.541920.72904
1700.2955060.5910110.704494
1710.2678620.5357230.732138
1720.2633830.5267670.736617
1730.4317440.8634870.568256
1740.4179690.8359380.582031
1750.4403610.8807210.559639
1760.4499240.8998480.550076
1770.508860.9822810.49114
1780.4752930.9505860.524707
1790.4528760.9057520.547124
1800.4523540.9047080.547646
1810.4150990.8301990.584901
1820.4083970.8167930.591603
1830.37110.7422010.6289
1840.34410.6882010.6559
1850.3600360.7200720.639964
1860.3513860.7027730.648614
1870.3165840.6331690.683416
1880.287380.5747590.71262
1890.2561320.5122630.743868
1900.2347770.4695530.765223
1910.2410620.4821230.758938
1920.2224970.4449930.777503
1930.2408480.4816960.759152
1940.229440.458880.77056
1950.2291580.4583170.770842
1960.2406850.4813690.759315
1970.2856630.5713260.714337
1980.2651580.5303160.734842
1990.3005070.6010150.699493
2000.2680220.5360450.731978
2010.3053430.6106860.694657
2020.2821690.5643380.717831
2030.3210420.6420840.678958
2040.283470.5669390.71653
2050.250260.500520.74974
2060.2292010.4584010.770799
2070.1992080.3984170.800792
2080.2282840.4565680.771716
2090.1969360.3938720.803064
2100.1993610.3987230.800639
2110.2231970.4463930.776803
2120.2131090.4262170.786891
2130.1862420.3724840.813758
2140.235790.471580.76421
2150.2109230.4218460.789077
2160.1992210.3984410.800779
2170.2218020.4436040.778198
2180.1906250.381250.809375
2190.1805990.3611970.819401
2200.1906940.3813870.809306
2210.2077160.4154320.792284
2220.2014910.4029820.798509
2230.1918070.3836130.808193
2240.1609350.321870.839065
2250.1714060.3428110.828594
2260.1987110.3974220.801289
2270.4094640.8189270.590536
2280.3866390.7732780.613361
2290.3595460.7190920.640454
2300.3444290.6888570.655571
2310.3005690.6011390.699431
2320.3353030.6706070.664697
2330.2927430.5854860.707257
2340.2481440.4962880.751856
2350.2477880.4955770.752212
2360.2255370.4510750.774463
2370.1930830.3861670.806917
2380.153260.306520.84674
2390.2894340.5788680.710566
2400.2846530.5693070.715347
2410.2500420.5000840.749958
2420.4655860.9311730.534414
2430.4201490.8402980.579851
2440.3542160.7084330.645784
2450.5074390.9851210.492561
2460.422540.8450790.57746
2470.3433750.6867490.656625
2480.4959360.9918730.504064
2490.3955890.7911770.604411
2500.2975580.5951150.702442
2510.4399110.8798220.560089
2520.9402510.1194990.0597494
2530.8736250.252750.126375
2540.8109990.3780020.189001

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.0787318 & 0.157464 & 0.921268 \tabularnewline
11 & 0.0260797 & 0.0521595 & 0.97392 \tabularnewline
12 & 0.835134 & 0.329731 & 0.164866 \tabularnewline
13 & 0.966849 & 0.0663016 & 0.0331508 \tabularnewline
14 & 0.968231 & 0.0635388 & 0.0317694 \tabularnewline
15 & 0.978708 & 0.0425842 & 0.0212921 \tabularnewline
16 & 0.964469 & 0.0710627 & 0.0355313 \tabularnewline
17 & 0.951206 & 0.0975876 & 0.0487938 \tabularnewline
18 & 0.935511 & 0.128977 & 0.0644887 \tabularnewline
19 & 0.916495 & 0.167011 & 0.0835053 \tabularnewline
20 & 0.908606 & 0.182787 & 0.0913936 \tabularnewline
21 & 0.921574 & 0.156851 & 0.0784257 \tabularnewline
22 & 0.955798 & 0.088404 & 0.044202 \tabularnewline
23 & 0.938254 & 0.123491 & 0.0617457 \tabularnewline
24 & 0.925875 & 0.14825 & 0.0741252 \tabularnewline
25 & 0.903003 & 0.193994 & 0.0969971 \tabularnewline
26 & 0.998332 & 0.00333553 & 0.00166777 \tabularnewline
27 & 0.997533 & 0.00493332 & 0.00246666 \tabularnewline
28 & 0.99622 & 0.00756079 & 0.00378039 \tabularnewline
29 & 0.994437 & 0.0111257 & 0.00556283 \tabularnewline
30 & 0.997274 & 0.00545202 & 0.00272601 \tabularnewline
31 & 0.995876 & 0.00824705 & 0.00412353 \tabularnewline
32 & 0.993989 & 0.0120228 & 0.00601142 \tabularnewline
33 & 0.99275 & 0.0145002 & 0.00725009 \tabularnewline
34 & 0.989656 & 0.0206877 & 0.0103438 \tabularnewline
35 & 0.985944 & 0.028113 & 0.0140565 \tabularnewline
36 & 0.980591 & 0.038819 & 0.0194095 \tabularnewline
37 & 0.985141 & 0.0297181 & 0.014859 \tabularnewline
38 & 0.979837 & 0.0403269 & 0.0201634 \tabularnewline
39 & 0.977573 & 0.0448546 & 0.0224273 \tabularnewline
40 & 0.977804 & 0.0443915 & 0.0221958 \tabularnewline
41 & 0.971236 & 0.0575275 & 0.0287637 \tabularnewline
42 & 0.969842 & 0.0603155 & 0.0301578 \tabularnewline
43 & 0.96072 & 0.0785604 & 0.0392802 \tabularnewline
44 & 0.95336 & 0.093281 & 0.0466405 \tabularnewline
45 & 0.940706 & 0.118588 & 0.0592941 \tabularnewline
46 & 0.950103 & 0.0997938 & 0.0498969 \tabularnewline
47 & 0.936736 & 0.126527 & 0.0632635 \tabularnewline
48 & 0.920894 & 0.158212 & 0.0791059 \tabularnewline
49 & 0.942911 & 0.114178 & 0.0570891 \tabularnewline
50 & 0.938796 & 0.122407 & 0.0612037 \tabularnewline
51 & 0.925885 & 0.14823 & 0.074115 \tabularnewline
52 & 0.909497 & 0.181006 & 0.090503 \tabularnewline
53 & 0.89424 & 0.21152 & 0.10576 \tabularnewline
54 & 0.896073 & 0.207853 & 0.103927 \tabularnewline
55 & 0.887057 & 0.225887 & 0.112943 \tabularnewline
56 & 0.870523 & 0.258955 & 0.129477 \tabularnewline
57 & 0.859763 & 0.280474 & 0.140237 \tabularnewline
58 & 0.834379 & 0.331241 & 0.165621 \tabularnewline
59 & 0.86181 & 0.27638 & 0.13819 \tabularnewline
60 & 0.856267 & 0.287467 & 0.143733 \tabularnewline
61 & 0.874567 & 0.250865 & 0.125433 \tabularnewline
62 & 0.867325 & 0.26535 & 0.132675 \tabularnewline
63 & 0.910963 & 0.178073 & 0.0890367 \tabularnewline
64 & 0.899586 & 0.200828 & 0.100414 \tabularnewline
65 & 0.889386 & 0.221227 & 0.110614 \tabularnewline
66 & 0.958657 & 0.0826869 & 0.0413435 \tabularnewline
67 & 0.957494 & 0.085013 & 0.0425065 \tabularnewline
68 & 0.960461 & 0.0790779 & 0.039539 \tabularnewline
69 & 0.955516 & 0.088968 & 0.044484 \tabularnewline
70 & 0.949344 & 0.101312 & 0.0506562 \tabularnewline
71 & 0.938369 & 0.123262 & 0.0616308 \tabularnewline
72 & 0.952868 & 0.094264 & 0.047132 \tabularnewline
73 & 0.942879 & 0.114242 & 0.0571212 \tabularnewline
74 & 0.930995 & 0.138011 & 0.0690054 \tabularnewline
75 & 0.925753 & 0.148494 & 0.0742472 \tabularnewline
76 & 0.911698 & 0.176605 & 0.0883023 \tabularnewline
77 & 0.92428 & 0.15144 & 0.0757202 \tabularnewline
78 & 0.909975 & 0.18005 & 0.0900248 \tabularnewline
79 & 0.900897 & 0.198205 & 0.0991027 \tabularnewline
80 & 0.894886 & 0.210228 & 0.105114 \tabularnewline
81 & 0.876242 & 0.247516 & 0.123758 \tabularnewline
82 & 0.85696 & 0.286081 & 0.14304 \tabularnewline
83 & 0.850716 & 0.298568 & 0.149284 \tabularnewline
84 & 0.830146 & 0.339708 & 0.169854 \tabularnewline
85 & 0.804766 & 0.390468 & 0.195234 \tabularnewline
86 & 0.781571 & 0.436858 & 0.218429 \tabularnewline
87 & 0.752955 & 0.494089 & 0.247045 \tabularnewline
88 & 0.722289 & 0.555422 & 0.277711 \tabularnewline
89 & 0.794574 & 0.410852 & 0.205426 \tabularnewline
90 & 0.826724 & 0.346552 & 0.173276 \tabularnewline
91 & 0.802015 & 0.39597 & 0.197985 \tabularnewline
92 & 0.778428 & 0.443145 & 0.221572 \tabularnewline
93 & 0.755952 & 0.488096 & 0.244048 \tabularnewline
94 & 0.730254 & 0.539493 & 0.269746 \tabularnewline
95 & 0.704821 & 0.590359 & 0.295179 \tabularnewline
96 & 0.679659 & 0.640683 & 0.320341 \tabularnewline
97 & 0.651064 & 0.697872 & 0.348936 \tabularnewline
98 & 0.652045 & 0.695909 & 0.347955 \tabularnewline
99 & 0.618125 & 0.76375 & 0.381875 \tabularnewline
100 & 0.610382 & 0.779236 & 0.389618 \tabularnewline
101 & 0.586111 & 0.827779 & 0.413889 \tabularnewline
102 & 0.557099 & 0.885801 & 0.442901 \tabularnewline
103 & 0.612925 & 0.77415 & 0.387075 \tabularnewline
104 & 0.60398 & 0.79204 & 0.39602 \tabularnewline
105 & 0.618281 & 0.763439 & 0.381719 \tabularnewline
106 & 0.590679 & 0.818641 & 0.409321 \tabularnewline
107 & 0.584471 & 0.831057 & 0.415529 \tabularnewline
108 & 0.62259 & 0.75482 & 0.37741 \tabularnewline
109 & 0.596692 & 0.806617 & 0.403308 \tabularnewline
110 & 0.571167 & 0.857667 & 0.428833 \tabularnewline
111 & 0.57343 & 0.853141 & 0.42657 \tabularnewline
112 & 0.604157 & 0.791685 & 0.395843 \tabularnewline
113 & 0.617626 & 0.764749 & 0.382374 \tabularnewline
114 & 0.700688 & 0.598624 & 0.299312 \tabularnewline
115 & 0.670582 & 0.658836 & 0.329418 \tabularnewline
116 & 0.648127 & 0.703747 & 0.351873 \tabularnewline
117 & 0.618706 & 0.762588 & 0.381294 \tabularnewline
118 & 0.596056 & 0.807889 & 0.403944 \tabularnewline
119 & 0.561873 & 0.876255 & 0.438127 \tabularnewline
120 & 0.531952 & 0.936096 & 0.468048 \tabularnewline
121 & 0.501066 & 0.997869 & 0.498934 \tabularnewline
122 & 0.468763 & 0.937527 & 0.531237 \tabularnewline
123 & 0.442632 & 0.885265 & 0.557368 \tabularnewline
124 & 0.409043 & 0.818086 & 0.590957 \tabularnewline
125 & 0.396527 & 0.793054 & 0.603473 \tabularnewline
126 & 0.366681 & 0.733362 & 0.633319 \tabularnewline
127 & 0.354811 & 0.709623 & 0.645189 \tabularnewline
128 & 0.45243 & 0.90486 & 0.54757 \tabularnewline
129 & 0.435077 & 0.870154 & 0.564923 \tabularnewline
130 & 0.421996 & 0.843993 & 0.578004 \tabularnewline
131 & 0.406652 & 0.813305 & 0.593348 \tabularnewline
132 & 0.377239 & 0.754478 & 0.622761 \tabularnewline
133 & 0.396454 & 0.792908 & 0.603546 \tabularnewline
134 & 0.3696 & 0.7392 & 0.6304 \tabularnewline
135 & 0.37952 & 0.759039 & 0.62048 \tabularnewline
136 & 0.367416 & 0.734831 & 0.632584 \tabularnewline
137 & 0.3379 & 0.6758 & 0.6621 \tabularnewline
138 & 0.315464 & 0.630928 & 0.684536 \tabularnewline
139 & 0.289673 & 0.579346 & 0.710327 \tabularnewline
140 & 0.265191 & 0.530382 & 0.734809 \tabularnewline
141 & 0.237746 & 0.475493 & 0.762254 \tabularnewline
142 & 0.244977 & 0.489954 & 0.755023 \tabularnewline
143 & 0.219617 & 0.439234 & 0.780383 \tabularnewline
144 & 0.198304 & 0.396608 & 0.801696 \tabularnewline
145 & 0.185118 & 0.370236 & 0.814882 \tabularnewline
146 & 0.176178 & 0.352357 & 0.823822 \tabularnewline
147 & 0.185857 & 0.371714 & 0.814143 \tabularnewline
148 & 0.203247 & 0.406494 & 0.796753 \tabularnewline
149 & 0.221733 & 0.443466 & 0.778267 \tabularnewline
150 & 0.222518 & 0.445036 & 0.777482 \tabularnewline
151 & 0.200035 & 0.40007 & 0.799965 \tabularnewline
152 & 0.180178 & 0.360357 & 0.819822 \tabularnewline
153 & 0.192305 & 0.384609 & 0.807695 \tabularnewline
154 & 0.208521 & 0.417042 & 0.791479 \tabularnewline
155 & 0.193587 & 0.387174 & 0.806413 \tabularnewline
156 & 0.16993 & 0.339861 & 0.83007 \tabularnewline
157 & 0.152535 & 0.30507 & 0.847465 \tabularnewline
158 & 0.237079 & 0.474157 & 0.762921 \tabularnewline
159 & 0.255709 & 0.511419 & 0.744291 \tabularnewline
160 & 0.233148 & 0.466295 & 0.766852 \tabularnewline
161 & 0.210567 & 0.421135 & 0.789433 \tabularnewline
162 & 0.186424 & 0.372848 & 0.813576 \tabularnewline
163 & 0.1653 & 0.330599 & 0.8347 \tabularnewline
164 & 0.270743 & 0.541485 & 0.729257 \tabularnewline
165 & 0.265509 & 0.531018 & 0.734491 \tabularnewline
166 & 0.263304 & 0.526607 & 0.736696 \tabularnewline
167 & 0.234708 & 0.469417 & 0.765292 \tabularnewline
168 & 0.213027 & 0.426053 & 0.786973 \tabularnewline
169 & 0.27096 & 0.54192 & 0.72904 \tabularnewline
170 & 0.295506 & 0.591011 & 0.704494 \tabularnewline
171 & 0.267862 & 0.535723 & 0.732138 \tabularnewline
172 & 0.263383 & 0.526767 & 0.736617 \tabularnewline
173 & 0.431744 & 0.863487 & 0.568256 \tabularnewline
174 & 0.417969 & 0.835938 & 0.582031 \tabularnewline
175 & 0.440361 & 0.880721 & 0.559639 \tabularnewline
176 & 0.449924 & 0.899848 & 0.550076 \tabularnewline
177 & 0.50886 & 0.982281 & 0.49114 \tabularnewline
178 & 0.475293 & 0.950586 & 0.524707 \tabularnewline
179 & 0.452876 & 0.905752 & 0.547124 \tabularnewline
180 & 0.452354 & 0.904708 & 0.547646 \tabularnewline
181 & 0.415099 & 0.830199 & 0.584901 \tabularnewline
182 & 0.408397 & 0.816793 & 0.591603 \tabularnewline
183 & 0.3711 & 0.742201 & 0.6289 \tabularnewline
184 & 0.3441 & 0.688201 & 0.6559 \tabularnewline
185 & 0.360036 & 0.720072 & 0.639964 \tabularnewline
186 & 0.351386 & 0.702773 & 0.648614 \tabularnewline
187 & 0.316584 & 0.633169 & 0.683416 \tabularnewline
188 & 0.28738 & 0.574759 & 0.71262 \tabularnewline
189 & 0.256132 & 0.512263 & 0.743868 \tabularnewline
190 & 0.234777 & 0.469553 & 0.765223 \tabularnewline
191 & 0.241062 & 0.482123 & 0.758938 \tabularnewline
192 & 0.222497 & 0.444993 & 0.777503 \tabularnewline
193 & 0.240848 & 0.481696 & 0.759152 \tabularnewline
194 & 0.22944 & 0.45888 & 0.77056 \tabularnewline
195 & 0.229158 & 0.458317 & 0.770842 \tabularnewline
196 & 0.240685 & 0.481369 & 0.759315 \tabularnewline
197 & 0.285663 & 0.571326 & 0.714337 \tabularnewline
198 & 0.265158 & 0.530316 & 0.734842 \tabularnewline
199 & 0.300507 & 0.601015 & 0.699493 \tabularnewline
200 & 0.268022 & 0.536045 & 0.731978 \tabularnewline
201 & 0.305343 & 0.610686 & 0.694657 \tabularnewline
202 & 0.282169 & 0.564338 & 0.717831 \tabularnewline
203 & 0.321042 & 0.642084 & 0.678958 \tabularnewline
204 & 0.28347 & 0.566939 & 0.71653 \tabularnewline
205 & 0.25026 & 0.50052 & 0.74974 \tabularnewline
206 & 0.229201 & 0.458401 & 0.770799 \tabularnewline
207 & 0.199208 & 0.398417 & 0.800792 \tabularnewline
208 & 0.228284 & 0.456568 & 0.771716 \tabularnewline
209 & 0.196936 & 0.393872 & 0.803064 \tabularnewline
210 & 0.199361 & 0.398723 & 0.800639 \tabularnewline
211 & 0.223197 & 0.446393 & 0.776803 \tabularnewline
212 & 0.213109 & 0.426217 & 0.786891 \tabularnewline
213 & 0.186242 & 0.372484 & 0.813758 \tabularnewline
214 & 0.23579 & 0.47158 & 0.76421 \tabularnewline
215 & 0.210923 & 0.421846 & 0.789077 \tabularnewline
216 & 0.199221 & 0.398441 & 0.800779 \tabularnewline
217 & 0.221802 & 0.443604 & 0.778198 \tabularnewline
218 & 0.190625 & 0.38125 & 0.809375 \tabularnewline
219 & 0.180599 & 0.361197 & 0.819401 \tabularnewline
220 & 0.190694 & 0.381387 & 0.809306 \tabularnewline
221 & 0.207716 & 0.415432 & 0.792284 \tabularnewline
222 & 0.201491 & 0.402982 & 0.798509 \tabularnewline
223 & 0.191807 & 0.383613 & 0.808193 \tabularnewline
224 & 0.160935 & 0.32187 & 0.839065 \tabularnewline
225 & 0.171406 & 0.342811 & 0.828594 \tabularnewline
226 & 0.198711 & 0.397422 & 0.801289 \tabularnewline
227 & 0.409464 & 0.818927 & 0.590536 \tabularnewline
228 & 0.386639 & 0.773278 & 0.613361 \tabularnewline
229 & 0.359546 & 0.719092 & 0.640454 \tabularnewline
230 & 0.344429 & 0.688857 & 0.655571 \tabularnewline
231 & 0.300569 & 0.601139 & 0.699431 \tabularnewline
232 & 0.335303 & 0.670607 & 0.664697 \tabularnewline
233 & 0.292743 & 0.585486 & 0.707257 \tabularnewline
234 & 0.248144 & 0.496288 & 0.751856 \tabularnewline
235 & 0.247788 & 0.495577 & 0.752212 \tabularnewline
236 & 0.225537 & 0.451075 & 0.774463 \tabularnewline
237 & 0.193083 & 0.386167 & 0.806917 \tabularnewline
238 & 0.15326 & 0.30652 & 0.84674 \tabularnewline
239 & 0.289434 & 0.578868 & 0.710566 \tabularnewline
240 & 0.284653 & 0.569307 & 0.715347 \tabularnewline
241 & 0.250042 & 0.500084 & 0.749958 \tabularnewline
242 & 0.465586 & 0.931173 & 0.534414 \tabularnewline
243 & 0.420149 & 0.840298 & 0.579851 \tabularnewline
244 & 0.354216 & 0.708433 & 0.645784 \tabularnewline
245 & 0.507439 & 0.985121 & 0.492561 \tabularnewline
246 & 0.42254 & 0.845079 & 0.57746 \tabularnewline
247 & 0.343375 & 0.686749 & 0.656625 \tabularnewline
248 & 0.495936 & 0.991873 & 0.504064 \tabularnewline
249 & 0.395589 & 0.791177 & 0.604411 \tabularnewline
250 & 0.297558 & 0.595115 & 0.702442 \tabularnewline
251 & 0.439911 & 0.879822 & 0.560089 \tabularnewline
252 & 0.940251 & 0.119499 & 0.0597494 \tabularnewline
253 & 0.873625 & 0.25275 & 0.126375 \tabularnewline
254 & 0.810999 & 0.378002 & 0.189001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225489&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]0.0787318[/C][C]0.157464[/C][C]0.921268[/C][/ROW]
[ROW][C]11[/C][C]0.0260797[/C][C]0.0521595[/C][C]0.97392[/C][/ROW]
[ROW][C]12[/C][C]0.835134[/C][C]0.329731[/C][C]0.164866[/C][/ROW]
[ROW][C]13[/C][C]0.966849[/C][C]0.0663016[/C][C]0.0331508[/C][/ROW]
[ROW][C]14[/C][C]0.968231[/C][C]0.0635388[/C][C]0.0317694[/C][/ROW]
[ROW][C]15[/C][C]0.978708[/C][C]0.0425842[/C][C]0.0212921[/C][/ROW]
[ROW][C]16[/C][C]0.964469[/C][C]0.0710627[/C][C]0.0355313[/C][/ROW]
[ROW][C]17[/C][C]0.951206[/C][C]0.0975876[/C][C]0.0487938[/C][/ROW]
[ROW][C]18[/C][C]0.935511[/C][C]0.128977[/C][C]0.0644887[/C][/ROW]
[ROW][C]19[/C][C]0.916495[/C][C]0.167011[/C][C]0.0835053[/C][/ROW]
[ROW][C]20[/C][C]0.908606[/C][C]0.182787[/C][C]0.0913936[/C][/ROW]
[ROW][C]21[/C][C]0.921574[/C][C]0.156851[/C][C]0.0784257[/C][/ROW]
[ROW][C]22[/C][C]0.955798[/C][C]0.088404[/C][C]0.044202[/C][/ROW]
[ROW][C]23[/C][C]0.938254[/C][C]0.123491[/C][C]0.0617457[/C][/ROW]
[ROW][C]24[/C][C]0.925875[/C][C]0.14825[/C][C]0.0741252[/C][/ROW]
[ROW][C]25[/C][C]0.903003[/C][C]0.193994[/C][C]0.0969971[/C][/ROW]
[ROW][C]26[/C][C]0.998332[/C][C]0.00333553[/C][C]0.00166777[/C][/ROW]
[ROW][C]27[/C][C]0.997533[/C][C]0.00493332[/C][C]0.00246666[/C][/ROW]
[ROW][C]28[/C][C]0.99622[/C][C]0.00756079[/C][C]0.00378039[/C][/ROW]
[ROW][C]29[/C][C]0.994437[/C][C]0.0111257[/C][C]0.00556283[/C][/ROW]
[ROW][C]30[/C][C]0.997274[/C][C]0.00545202[/C][C]0.00272601[/C][/ROW]
[ROW][C]31[/C][C]0.995876[/C][C]0.00824705[/C][C]0.00412353[/C][/ROW]
[ROW][C]32[/C][C]0.993989[/C][C]0.0120228[/C][C]0.00601142[/C][/ROW]
[ROW][C]33[/C][C]0.99275[/C][C]0.0145002[/C][C]0.00725009[/C][/ROW]
[ROW][C]34[/C][C]0.989656[/C][C]0.0206877[/C][C]0.0103438[/C][/ROW]
[ROW][C]35[/C][C]0.985944[/C][C]0.028113[/C][C]0.0140565[/C][/ROW]
[ROW][C]36[/C][C]0.980591[/C][C]0.038819[/C][C]0.0194095[/C][/ROW]
[ROW][C]37[/C][C]0.985141[/C][C]0.0297181[/C][C]0.014859[/C][/ROW]
[ROW][C]38[/C][C]0.979837[/C][C]0.0403269[/C][C]0.0201634[/C][/ROW]
[ROW][C]39[/C][C]0.977573[/C][C]0.0448546[/C][C]0.0224273[/C][/ROW]
[ROW][C]40[/C][C]0.977804[/C][C]0.0443915[/C][C]0.0221958[/C][/ROW]
[ROW][C]41[/C][C]0.971236[/C][C]0.0575275[/C][C]0.0287637[/C][/ROW]
[ROW][C]42[/C][C]0.969842[/C][C]0.0603155[/C][C]0.0301578[/C][/ROW]
[ROW][C]43[/C][C]0.96072[/C][C]0.0785604[/C][C]0.0392802[/C][/ROW]
[ROW][C]44[/C][C]0.95336[/C][C]0.093281[/C][C]0.0466405[/C][/ROW]
[ROW][C]45[/C][C]0.940706[/C][C]0.118588[/C][C]0.0592941[/C][/ROW]
[ROW][C]46[/C][C]0.950103[/C][C]0.0997938[/C][C]0.0498969[/C][/ROW]
[ROW][C]47[/C][C]0.936736[/C][C]0.126527[/C][C]0.0632635[/C][/ROW]
[ROW][C]48[/C][C]0.920894[/C][C]0.158212[/C][C]0.0791059[/C][/ROW]
[ROW][C]49[/C][C]0.942911[/C][C]0.114178[/C][C]0.0570891[/C][/ROW]
[ROW][C]50[/C][C]0.938796[/C][C]0.122407[/C][C]0.0612037[/C][/ROW]
[ROW][C]51[/C][C]0.925885[/C][C]0.14823[/C][C]0.074115[/C][/ROW]
[ROW][C]52[/C][C]0.909497[/C][C]0.181006[/C][C]0.090503[/C][/ROW]
[ROW][C]53[/C][C]0.89424[/C][C]0.21152[/C][C]0.10576[/C][/ROW]
[ROW][C]54[/C][C]0.896073[/C][C]0.207853[/C][C]0.103927[/C][/ROW]
[ROW][C]55[/C][C]0.887057[/C][C]0.225887[/C][C]0.112943[/C][/ROW]
[ROW][C]56[/C][C]0.870523[/C][C]0.258955[/C][C]0.129477[/C][/ROW]
[ROW][C]57[/C][C]0.859763[/C][C]0.280474[/C][C]0.140237[/C][/ROW]
[ROW][C]58[/C][C]0.834379[/C][C]0.331241[/C][C]0.165621[/C][/ROW]
[ROW][C]59[/C][C]0.86181[/C][C]0.27638[/C][C]0.13819[/C][/ROW]
[ROW][C]60[/C][C]0.856267[/C][C]0.287467[/C][C]0.143733[/C][/ROW]
[ROW][C]61[/C][C]0.874567[/C][C]0.250865[/C][C]0.125433[/C][/ROW]
[ROW][C]62[/C][C]0.867325[/C][C]0.26535[/C][C]0.132675[/C][/ROW]
[ROW][C]63[/C][C]0.910963[/C][C]0.178073[/C][C]0.0890367[/C][/ROW]
[ROW][C]64[/C][C]0.899586[/C][C]0.200828[/C][C]0.100414[/C][/ROW]
[ROW][C]65[/C][C]0.889386[/C][C]0.221227[/C][C]0.110614[/C][/ROW]
[ROW][C]66[/C][C]0.958657[/C][C]0.0826869[/C][C]0.0413435[/C][/ROW]
[ROW][C]67[/C][C]0.957494[/C][C]0.085013[/C][C]0.0425065[/C][/ROW]
[ROW][C]68[/C][C]0.960461[/C][C]0.0790779[/C][C]0.039539[/C][/ROW]
[ROW][C]69[/C][C]0.955516[/C][C]0.088968[/C][C]0.044484[/C][/ROW]
[ROW][C]70[/C][C]0.949344[/C][C]0.101312[/C][C]0.0506562[/C][/ROW]
[ROW][C]71[/C][C]0.938369[/C][C]0.123262[/C][C]0.0616308[/C][/ROW]
[ROW][C]72[/C][C]0.952868[/C][C]0.094264[/C][C]0.047132[/C][/ROW]
[ROW][C]73[/C][C]0.942879[/C][C]0.114242[/C][C]0.0571212[/C][/ROW]
[ROW][C]74[/C][C]0.930995[/C][C]0.138011[/C][C]0.0690054[/C][/ROW]
[ROW][C]75[/C][C]0.925753[/C][C]0.148494[/C][C]0.0742472[/C][/ROW]
[ROW][C]76[/C][C]0.911698[/C][C]0.176605[/C][C]0.0883023[/C][/ROW]
[ROW][C]77[/C][C]0.92428[/C][C]0.15144[/C][C]0.0757202[/C][/ROW]
[ROW][C]78[/C][C]0.909975[/C][C]0.18005[/C][C]0.0900248[/C][/ROW]
[ROW][C]79[/C][C]0.900897[/C][C]0.198205[/C][C]0.0991027[/C][/ROW]
[ROW][C]80[/C][C]0.894886[/C][C]0.210228[/C][C]0.105114[/C][/ROW]
[ROW][C]81[/C][C]0.876242[/C][C]0.247516[/C][C]0.123758[/C][/ROW]
[ROW][C]82[/C][C]0.85696[/C][C]0.286081[/C][C]0.14304[/C][/ROW]
[ROW][C]83[/C][C]0.850716[/C][C]0.298568[/C][C]0.149284[/C][/ROW]
[ROW][C]84[/C][C]0.830146[/C][C]0.339708[/C][C]0.169854[/C][/ROW]
[ROW][C]85[/C][C]0.804766[/C][C]0.390468[/C][C]0.195234[/C][/ROW]
[ROW][C]86[/C][C]0.781571[/C][C]0.436858[/C][C]0.218429[/C][/ROW]
[ROW][C]87[/C][C]0.752955[/C][C]0.494089[/C][C]0.247045[/C][/ROW]
[ROW][C]88[/C][C]0.722289[/C][C]0.555422[/C][C]0.277711[/C][/ROW]
[ROW][C]89[/C][C]0.794574[/C][C]0.410852[/C][C]0.205426[/C][/ROW]
[ROW][C]90[/C][C]0.826724[/C][C]0.346552[/C][C]0.173276[/C][/ROW]
[ROW][C]91[/C][C]0.802015[/C][C]0.39597[/C][C]0.197985[/C][/ROW]
[ROW][C]92[/C][C]0.778428[/C][C]0.443145[/C][C]0.221572[/C][/ROW]
[ROW][C]93[/C][C]0.755952[/C][C]0.488096[/C][C]0.244048[/C][/ROW]
[ROW][C]94[/C][C]0.730254[/C][C]0.539493[/C][C]0.269746[/C][/ROW]
[ROW][C]95[/C][C]0.704821[/C][C]0.590359[/C][C]0.295179[/C][/ROW]
[ROW][C]96[/C][C]0.679659[/C][C]0.640683[/C][C]0.320341[/C][/ROW]
[ROW][C]97[/C][C]0.651064[/C][C]0.697872[/C][C]0.348936[/C][/ROW]
[ROW][C]98[/C][C]0.652045[/C][C]0.695909[/C][C]0.347955[/C][/ROW]
[ROW][C]99[/C][C]0.618125[/C][C]0.76375[/C][C]0.381875[/C][/ROW]
[ROW][C]100[/C][C]0.610382[/C][C]0.779236[/C][C]0.389618[/C][/ROW]
[ROW][C]101[/C][C]0.586111[/C][C]0.827779[/C][C]0.413889[/C][/ROW]
[ROW][C]102[/C][C]0.557099[/C][C]0.885801[/C][C]0.442901[/C][/ROW]
[ROW][C]103[/C][C]0.612925[/C][C]0.77415[/C][C]0.387075[/C][/ROW]
[ROW][C]104[/C][C]0.60398[/C][C]0.79204[/C][C]0.39602[/C][/ROW]
[ROW][C]105[/C][C]0.618281[/C][C]0.763439[/C][C]0.381719[/C][/ROW]
[ROW][C]106[/C][C]0.590679[/C][C]0.818641[/C][C]0.409321[/C][/ROW]
[ROW][C]107[/C][C]0.584471[/C][C]0.831057[/C][C]0.415529[/C][/ROW]
[ROW][C]108[/C][C]0.62259[/C][C]0.75482[/C][C]0.37741[/C][/ROW]
[ROW][C]109[/C][C]0.596692[/C][C]0.806617[/C][C]0.403308[/C][/ROW]
[ROW][C]110[/C][C]0.571167[/C][C]0.857667[/C][C]0.428833[/C][/ROW]
[ROW][C]111[/C][C]0.57343[/C][C]0.853141[/C][C]0.42657[/C][/ROW]
[ROW][C]112[/C][C]0.604157[/C][C]0.791685[/C][C]0.395843[/C][/ROW]
[ROW][C]113[/C][C]0.617626[/C][C]0.764749[/C][C]0.382374[/C][/ROW]
[ROW][C]114[/C][C]0.700688[/C][C]0.598624[/C][C]0.299312[/C][/ROW]
[ROW][C]115[/C][C]0.670582[/C][C]0.658836[/C][C]0.329418[/C][/ROW]
[ROW][C]116[/C][C]0.648127[/C][C]0.703747[/C][C]0.351873[/C][/ROW]
[ROW][C]117[/C][C]0.618706[/C][C]0.762588[/C][C]0.381294[/C][/ROW]
[ROW][C]118[/C][C]0.596056[/C][C]0.807889[/C][C]0.403944[/C][/ROW]
[ROW][C]119[/C][C]0.561873[/C][C]0.876255[/C][C]0.438127[/C][/ROW]
[ROW][C]120[/C][C]0.531952[/C][C]0.936096[/C][C]0.468048[/C][/ROW]
[ROW][C]121[/C][C]0.501066[/C][C]0.997869[/C][C]0.498934[/C][/ROW]
[ROW][C]122[/C][C]0.468763[/C][C]0.937527[/C][C]0.531237[/C][/ROW]
[ROW][C]123[/C][C]0.442632[/C][C]0.885265[/C][C]0.557368[/C][/ROW]
[ROW][C]124[/C][C]0.409043[/C][C]0.818086[/C][C]0.590957[/C][/ROW]
[ROW][C]125[/C][C]0.396527[/C][C]0.793054[/C][C]0.603473[/C][/ROW]
[ROW][C]126[/C][C]0.366681[/C][C]0.733362[/C][C]0.633319[/C][/ROW]
[ROW][C]127[/C][C]0.354811[/C][C]0.709623[/C][C]0.645189[/C][/ROW]
[ROW][C]128[/C][C]0.45243[/C][C]0.90486[/C][C]0.54757[/C][/ROW]
[ROW][C]129[/C][C]0.435077[/C][C]0.870154[/C][C]0.564923[/C][/ROW]
[ROW][C]130[/C][C]0.421996[/C][C]0.843993[/C][C]0.578004[/C][/ROW]
[ROW][C]131[/C][C]0.406652[/C][C]0.813305[/C][C]0.593348[/C][/ROW]
[ROW][C]132[/C][C]0.377239[/C][C]0.754478[/C][C]0.622761[/C][/ROW]
[ROW][C]133[/C][C]0.396454[/C][C]0.792908[/C][C]0.603546[/C][/ROW]
[ROW][C]134[/C][C]0.3696[/C][C]0.7392[/C][C]0.6304[/C][/ROW]
[ROW][C]135[/C][C]0.37952[/C][C]0.759039[/C][C]0.62048[/C][/ROW]
[ROW][C]136[/C][C]0.367416[/C][C]0.734831[/C][C]0.632584[/C][/ROW]
[ROW][C]137[/C][C]0.3379[/C][C]0.6758[/C][C]0.6621[/C][/ROW]
[ROW][C]138[/C][C]0.315464[/C][C]0.630928[/C][C]0.684536[/C][/ROW]
[ROW][C]139[/C][C]0.289673[/C][C]0.579346[/C][C]0.710327[/C][/ROW]
[ROW][C]140[/C][C]0.265191[/C][C]0.530382[/C][C]0.734809[/C][/ROW]
[ROW][C]141[/C][C]0.237746[/C][C]0.475493[/C][C]0.762254[/C][/ROW]
[ROW][C]142[/C][C]0.244977[/C][C]0.489954[/C][C]0.755023[/C][/ROW]
[ROW][C]143[/C][C]0.219617[/C][C]0.439234[/C][C]0.780383[/C][/ROW]
[ROW][C]144[/C][C]0.198304[/C][C]0.396608[/C][C]0.801696[/C][/ROW]
[ROW][C]145[/C][C]0.185118[/C][C]0.370236[/C][C]0.814882[/C][/ROW]
[ROW][C]146[/C][C]0.176178[/C][C]0.352357[/C][C]0.823822[/C][/ROW]
[ROW][C]147[/C][C]0.185857[/C][C]0.371714[/C][C]0.814143[/C][/ROW]
[ROW][C]148[/C][C]0.203247[/C][C]0.406494[/C][C]0.796753[/C][/ROW]
[ROW][C]149[/C][C]0.221733[/C][C]0.443466[/C][C]0.778267[/C][/ROW]
[ROW][C]150[/C][C]0.222518[/C][C]0.445036[/C][C]0.777482[/C][/ROW]
[ROW][C]151[/C][C]0.200035[/C][C]0.40007[/C][C]0.799965[/C][/ROW]
[ROW][C]152[/C][C]0.180178[/C][C]0.360357[/C][C]0.819822[/C][/ROW]
[ROW][C]153[/C][C]0.192305[/C][C]0.384609[/C][C]0.807695[/C][/ROW]
[ROW][C]154[/C][C]0.208521[/C][C]0.417042[/C][C]0.791479[/C][/ROW]
[ROW][C]155[/C][C]0.193587[/C][C]0.387174[/C][C]0.806413[/C][/ROW]
[ROW][C]156[/C][C]0.16993[/C][C]0.339861[/C][C]0.83007[/C][/ROW]
[ROW][C]157[/C][C]0.152535[/C][C]0.30507[/C][C]0.847465[/C][/ROW]
[ROW][C]158[/C][C]0.237079[/C][C]0.474157[/C][C]0.762921[/C][/ROW]
[ROW][C]159[/C][C]0.255709[/C][C]0.511419[/C][C]0.744291[/C][/ROW]
[ROW][C]160[/C][C]0.233148[/C][C]0.466295[/C][C]0.766852[/C][/ROW]
[ROW][C]161[/C][C]0.210567[/C][C]0.421135[/C][C]0.789433[/C][/ROW]
[ROW][C]162[/C][C]0.186424[/C][C]0.372848[/C][C]0.813576[/C][/ROW]
[ROW][C]163[/C][C]0.1653[/C][C]0.330599[/C][C]0.8347[/C][/ROW]
[ROW][C]164[/C][C]0.270743[/C][C]0.541485[/C][C]0.729257[/C][/ROW]
[ROW][C]165[/C][C]0.265509[/C][C]0.531018[/C][C]0.734491[/C][/ROW]
[ROW][C]166[/C][C]0.263304[/C][C]0.526607[/C][C]0.736696[/C][/ROW]
[ROW][C]167[/C][C]0.234708[/C][C]0.469417[/C][C]0.765292[/C][/ROW]
[ROW][C]168[/C][C]0.213027[/C][C]0.426053[/C][C]0.786973[/C][/ROW]
[ROW][C]169[/C][C]0.27096[/C][C]0.54192[/C][C]0.72904[/C][/ROW]
[ROW][C]170[/C][C]0.295506[/C][C]0.591011[/C][C]0.704494[/C][/ROW]
[ROW][C]171[/C][C]0.267862[/C][C]0.535723[/C][C]0.732138[/C][/ROW]
[ROW][C]172[/C][C]0.263383[/C][C]0.526767[/C][C]0.736617[/C][/ROW]
[ROW][C]173[/C][C]0.431744[/C][C]0.863487[/C][C]0.568256[/C][/ROW]
[ROW][C]174[/C][C]0.417969[/C][C]0.835938[/C][C]0.582031[/C][/ROW]
[ROW][C]175[/C][C]0.440361[/C][C]0.880721[/C][C]0.559639[/C][/ROW]
[ROW][C]176[/C][C]0.449924[/C][C]0.899848[/C][C]0.550076[/C][/ROW]
[ROW][C]177[/C][C]0.50886[/C][C]0.982281[/C][C]0.49114[/C][/ROW]
[ROW][C]178[/C][C]0.475293[/C][C]0.950586[/C][C]0.524707[/C][/ROW]
[ROW][C]179[/C][C]0.452876[/C][C]0.905752[/C][C]0.547124[/C][/ROW]
[ROW][C]180[/C][C]0.452354[/C][C]0.904708[/C][C]0.547646[/C][/ROW]
[ROW][C]181[/C][C]0.415099[/C][C]0.830199[/C][C]0.584901[/C][/ROW]
[ROW][C]182[/C][C]0.408397[/C][C]0.816793[/C][C]0.591603[/C][/ROW]
[ROW][C]183[/C][C]0.3711[/C][C]0.742201[/C][C]0.6289[/C][/ROW]
[ROW][C]184[/C][C]0.3441[/C][C]0.688201[/C][C]0.6559[/C][/ROW]
[ROW][C]185[/C][C]0.360036[/C][C]0.720072[/C][C]0.639964[/C][/ROW]
[ROW][C]186[/C][C]0.351386[/C][C]0.702773[/C][C]0.648614[/C][/ROW]
[ROW][C]187[/C][C]0.316584[/C][C]0.633169[/C][C]0.683416[/C][/ROW]
[ROW][C]188[/C][C]0.28738[/C][C]0.574759[/C][C]0.71262[/C][/ROW]
[ROW][C]189[/C][C]0.256132[/C][C]0.512263[/C][C]0.743868[/C][/ROW]
[ROW][C]190[/C][C]0.234777[/C][C]0.469553[/C][C]0.765223[/C][/ROW]
[ROW][C]191[/C][C]0.241062[/C][C]0.482123[/C][C]0.758938[/C][/ROW]
[ROW][C]192[/C][C]0.222497[/C][C]0.444993[/C][C]0.777503[/C][/ROW]
[ROW][C]193[/C][C]0.240848[/C][C]0.481696[/C][C]0.759152[/C][/ROW]
[ROW][C]194[/C][C]0.22944[/C][C]0.45888[/C][C]0.77056[/C][/ROW]
[ROW][C]195[/C][C]0.229158[/C][C]0.458317[/C][C]0.770842[/C][/ROW]
[ROW][C]196[/C][C]0.240685[/C][C]0.481369[/C][C]0.759315[/C][/ROW]
[ROW][C]197[/C][C]0.285663[/C][C]0.571326[/C][C]0.714337[/C][/ROW]
[ROW][C]198[/C][C]0.265158[/C][C]0.530316[/C][C]0.734842[/C][/ROW]
[ROW][C]199[/C][C]0.300507[/C][C]0.601015[/C][C]0.699493[/C][/ROW]
[ROW][C]200[/C][C]0.268022[/C][C]0.536045[/C][C]0.731978[/C][/ROW]
[ROW][C]201[/C][C]0.305343[/C][C]0.610686[/C][C]0.694657[/C][/ROW]
[ROW][C]202[/C][C]0.282169[/C][C]0.564338[/C][C]0.717831[/C][/ROW]
[ROW][C]203[/C][C]0.321042[/C][C]0.642084[/C][C]0.678958[/C][/ROW]
[ROW][C]204[/C][C]0.28347[/C][C]0.566939[/C][C]0.71653[/C][/ROW]
[ROW][C]205[/C][C]0.25026[/C][C]0.50052[/C][C]0.74974[/C][/ROW]
[ROW][C]206[/C][C]0.229201[/C][C]0.458401[/C][C]0.770799[/C][/ROW]
[ROW][C]207[/C][C]0.199208[/C][C]0.398417[/C][C]0.800792[/C][/ROW]
[ROW][C]208[/C][C]0.228284[/C][C]0.456568[/C][C]0.771716[/C][/ROW]
[ROW][C]209[/C][C]0.196936[/C][C]0.393872[/C][C]0.803064[/C][/ROW]
[ROW][C]210[/C][C]0.199361[/C][C]0.398723[/C][C]0.800639[/C][/ROW]
[ROW][C]211[/C][C]0.223197[/C][C]0.446393[/C][C]0.776803[/C][/ROW]
[ROW][C]212[/C][C]0.213109[/C][C]0.426217[/C][C]0.786891[/C][/ROW]
[ROW][C]213[/C][C]0.186242[/C][C]0.372484[/C][C]0.813758[/C][/ROW]
[ROW][C]214[/C][C]0.23579[/C][C]0.47158[/C][C]0.76421[/C][/ROW]
[ROW][C]215[/C][C]0.210923[/C][C]0.421846[/C][C]0.789077[/C][/ROW]
[ROW][C]216[/C][C]0.199221[/C][C]0.398441[/C][C]0.800779[/C][/ROW]
[ROW][C]217[/C][C]0.221802[/C][C]0.443604[/C][C]0.778198[/C][/ROW]
[ROW][C]218[/C][C]0.190625[/C][C]0.38125[/C][C]0.809375[/C][/ROW]
[ROW][C]219[/C][C]0.180599[/C][C]0.361197[/C][C]0.819401[/C][/ROW]
[ROW][C]220[/C][C]0.190694[/C][C]0.381387[/C][C]0.809306[/C][/ROW]
[ROW][C]221[/C][C]0.207716[/C][C]0.415432[/C][C]0.792284[/C][/ROW]
[ROW][C]222[/C][C]0.201491[/C][C]0.402982[/C][C]0.798509[/C][/ROW]
[ROW][C]223[/C][C]0.191807[/C][C]0.383613[/C][C]0.808193[/C][/ROW]
[ROW][C]224[/C][C]0.160935[/C][C]0.32187[/C][C]0.839065[/C][/ROW]
[ROW][C]225[/C][C]0.171406[/C][C]0.342811[/C][C]0.828594[/C][/ROW]
[ROW][C]226[/C][C]0.198711[/C][C]0.397422[/C][C]0.801289[/C][/ROW]
[ROW][C]227[/C][C]0.409464[/C][C]0.818927[/C][C]0.590536[/C][/ROW]
[ROW][C]228[/C][C]0.386639[/C][C]0.773278[/C][C]0.613361[/C][/ROW]
[ROW][C]229[/C][C]0.359546[/C][C]0.719092[/C][C]0.640454[/C][/ROW]
[ROW][C]230[/C][C]0.344429[/C][C]0.688857[/C][C]0.655571[/C][/ROW]
[ROW][C]231[/C][C]0.300569[/C][C]0.601139[/C][C]0.699431[/C][/ROW]
[ROW][C]232[/C][C]0.335303[/C][C]0.670607[/C][C]0.664697[/C][/ROW]
[ROW][C]233[/C][C]0.292743[/C][C]0.585486[/C][C]0.707257[/C][/ROW]
[ROW][C]234[/C][C]0.248144[/C][C]0.496288[/C][C]0.751856[/C][/ROW]
[ROW][C]235[/C][C]0.247788[/C][C]0.495577[/C][C]0.752212[/C][/ROW]
[ROW][C]236[/C][C]0.225537[/C][C]0.451075[/C][C]0.774463[/C][/ROW]
[ROW][C]237[/C][C]0.193083[/C][C]0.386167[/C][C]0.806917[/C][/ROW]
[ROW][C]238[/C][C]0.15326[/C][C]0.30652[/C][C]0.84674[/C][/ROW]
[ROW][C]239[/C][C]0.289434[/C][C]0.578868[/C][C]0.710566[/C][/ROW]
[ROW][C]240[/C][C]0.284653[/C][C]0.569307[/C][C]0.715347[/C][/ROW]
[ROW][C]241[/C][C]0.250042[/C][C]0.500084[/C][C]0.749958[/C][/ROW]
[ROW][C]242[/C][C]0.465586[/C][C]0.931173[/C][C]0.534414[/C][/ROW]
[ROW][C]243[/C][C]0.420149[/C][C]0.840298[/C][C]0.579851[/C][/ROW]
[ROW][C]244[/C][C]0.354216[/C][C]0.708433[/C][C]0.645784[/C][/ROW]
[ROW][C]245[/C][C]0.507439[/C][C]0.985121[/C][C]0.492561[/C][/ROW]
[ROW][C]246[/C][C]0.42254[/C][C]0.845079[/C][C]0.57746[/C][/ROW]
[ROW][C]247[/C][C]0.343375[/C][C]0.686749[/C][C]0.656625[/C][/ROW]
[ROW][C]248[/C][C]0.495936[/C][C]0.991873[/C][C]0.504064[/C][/ROW]
[ROW][C]249[/C][C]0.395589[/C][C]0.791177[/C][C]0.604411[/C][/ROW]
[ROW][C]250[/C][C]0.297558[/C][C]0.595115[/C][C]0.702442[/C][/ROW]
[ROW][C]251[/C][C]0.439911[/C][C]0.879822[/C][C]0.560089[/C][/ROW]
[ROW][C]252[/C][C]0.940251[/C][C]0.119499[/C][C]0.0597494[/C][/ROW]
[ROW][C]253[/C][C]0.873625[/C][C]0.25275[/C][C]0.126375[/C][/ROW]
[ROW][C]254[/C][C]0.810999[/C][C]0.378002[/C][C]0.189001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225489&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225489&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
100.07873180.1574640.921268
110.02607970.05215950.97392
120.8351340.3297310.164866
130.9668490.06630160.0331508
140.9682310.06353880.0317694
150.9787080.04258420.0212921
160.9644690.07106270.0355313
170.9512060.09758760.0487938
180.9355110.1289770.0644887
190.9164950.1670110.0835053
200.9086060.1827870.0913936
210.9215740.1568510.0784257
220.9557980.0884040.044202
230.9382540.1234910.0617457
240.9258750.148250.0741252
250.9030030.1939940.0969971
260.9983320.003335530.00166777
270.9975330.004933320.00246666
280.996220.007560790.00378039
290.9944370.01112570.00556283
300.9972740.005452020.00272601
310.9958760.008247050.00412353
320.9939890.01202280.00601142
330.992750.01450020.00725009
340.9896560.02068770.0103438
350.9859440.0281130.0140565
360.9805910.0388190.0194095
370.9851410.02971810.014859
380.9798370.04032690.0201634
390.9775730.04485460.0224273
400.9778040.04439150.0221958
410.9712360.05752750.0287637
420.9698420.06031550.0301578
430.960720.07856040.0392802
440.953360.0932810.0466405
450.9407060.1185880.0592941
460.9501030.09979380.0498969
470.9367360.1265270.0632635
480.9208940.1582120.0791059
490.9429110.1141780.0570891
500.9387960.1224070.0612037
510.9258850.148230.074115
520.9094970.1810060.090503
530.894240.211520.10576
540.8960730.2078530.103927
550.8870570.2258870.112943
560.8705230.2589550.129477
570.8597630.2804740.140237
580.8343790.3312410.165621
590.861810.276380.13819
600.8562670.2874670.143733
610.8745670.2508650.125433
620.8673250.265350.132675
630.9109630.1780730.0890367
640.8995860.2008280.100414
650.8893860.2212270.110614
660.9586570.08268690.0413435
670.9574940.0850130.0425065
680.9604610.07907790.039539
690.9555160.0889680.044484
700.9493440.1013120.0506562
710.9383690.1232620.0616308
720.9528680.0942640.047132
730.9428790.1142420.0571212
740.9309950.1380110.0690054
750.9257530.1484940.0742472
760.9116980.1766050.0883023
770.924280.151440.0757202
780.9099750.180050.0900248
790.9008970.1982050.0991027
800.8948860.2102280.105114
810.8762420.2475160.123758
820.856960.2860810.14304
830.8507160.2985680.149284
840.8301460.3397080.169854
850.8047660.3904680.195234
860.7815710.4368580.218429
870.7529550.4940890.247045
880.7222890.5554220.277711
890.7945740.4108520.205426
900.8267240.3465520.173276
910.8020150.395970.197985
920.7784280.4431450.221572
930.7559520.4880960.244048
940.7302540.5394930.269746
950.7048210.5903590.295179
960.6796590.6406830.320341
970.6510640.6978720.348936
980.6520450.6959090.347955
990.6181250.763750.381875
1000.6103820.7792360.389618
1010.5861110.8277790.413889
1020.5570990.8858010.442901
1030.6129250.774150.387075
1040.603980.792040.39602
1050.6182810.7634390.381719
1060.5906790.8186410.409321
1070.5844710.8310570.415529
1080.622590.754820.37741
1090.5966920.8066170.403308
1100.5711670.8576670.428833
1110.573430.8531410.42657
1120.6041570.7916850.395843
1130.6176260.7647490.382374
1140.7006880.5986240.299312
1150.6705820.6588360.329418
1160.6481270.7037470.351873
1170.6187060.7625880.381294
1180.5960560.8078890.403944
1190.5618730.8762550.438127
1200.5319520.9360960.468048
1210.5010660.9978690.498934
1220.4687630.9375270.531237
1230.4426320.8852650.557368
1240.4090430.8180860.590957
1250.3965270.7930540.603473
1260.3666810.7333620.633319
1270.3548110.7096230.645189
1280.452430.904860.54757
1290.4350770.8701540.564923
1300.4219960.8439930.578004
1310.4066520.8133050.593348
1320.3772390.7544780.622761
1330.3964540.7929080.603546
1340.36960.73920.6304
1350.379520.7590390.62048
1360.3674160.7348310.632584
1370.33790.67580.6621
1380.3154640.6309280.684536
1390.2896730.5793460.710327
1400.2651910.5303820.734809
1410.2377460.4754930.762254
1420.2449770.4899540.755023
1430.2196170.4392340.780383
1440.1983040.3966080.801696
1450.1851180.3702360.814882
1460.1761780.3523570.823822
1470.1858570.3717140.814143
1480.2032470.4064940.796753
1490.2217330.4434660.778267
1500.2225180.4450360.777482
1510.2000350.400070.799965
1520.1801780.3603570.819822
1530.1923050.3846090.807695
1540.2085210.4170420.791479
1550.1935870.3871740.806413
1560.169930.3398610.83007
1570.1525350.305070.847465
1580.2370790.4741570.762921
1590.2557090.5114190.744291
1600.2331480.4662950.766852
1610.2105670.4211350.789433
1620.1864240.3728480.813576
1630.16530.3305990.8347
1640.2707430.5414850.729257
1650.2655090.5310180.734491
1660.2633040.5266070.736696
1670.2347080.4694170.765292
1680.2130270.4260530.786973
1690.270960.541920.72904
1700.2955060.5910110.704494
1710.2678620.5357230.732138
1720.2633830.5267670.736617
1730.4317440.8634870.568256
1740.4179690.8359380.582031
1750.4403610.8807210.559639
1760.4499240.8998480.550076
1770.508860.9822810.49114
1780.4752930.9505860.524707
1790.4528760.9057520.547124
1800.4523540.9047080.547646
1810.4150990.8301990.584901
1820.4083970.8167930.591603
1830.37110.7422010.6289
1840.34410.6882010.6559
1850.3600360.7200720.639964
1860.3513860.7027730.648614
1870.3165840.6331690.683416
1880.287380.5747590.71262
1890.2561320.5122630.743868
1900.2347770.4695530.765223
1910.2410620.4821230.758938
1920.2224970.4449930.777503
1930.2408480.4816960.759152
1940.229440.458880.77056
1950.2291580.4583170.770842
1960.2406850.4813690.759315
1970.2856630.5713260.714337
1980.2651580.5303160.734842
1990.3005070.6010150.699493
2000.2680220.5360450.731978
2010.3053430.6106860.694657
2020.2821690.5643380.717831
2030.3210420.6420840.678958
2040.283470.5669390.71653
2050.250260.500520.74974
2060.2292010.4584010.770799
2070.1992080.3984170.800792
2080.2282840.4565680.771716
2090.1969360.3938720.803064
2100.1993610.3987230.800639
2110.2231970.4463930.776803
2120.2131090.4262170.786891
2130.1862420.3724840.813758
2140.235790.471580.76421
2150.2109230.4218460.789077
2160.1992210.3984410.800779
2170.2218020.4436040.778198
2180.1906250.381250.809375
2190.1805990.3611970.819401
2200.1906940.3813870.809306
2210.2077160.4154320.792284
2220.2014910.4029820.798509
2230.1918070.3836130.808193
2240.1609350.321870.839065
2250.1714060.3428110.828594
2260.1987110.3974220.801289
2270.4094640.8189270.590536
2280.3866390.7732780.613361
2290.3595460.7190920.640454
2300.3444290.6888570.655571
2310.3005690.6011390.699431
2320.3353030.6706070.664697
2330.2927430.5854860.707257
2340.2481440.4962880.751856
2350.2477880.4955770.752212
2360.2255370.4510750.774463
2370.1930830.3861670.806917
2380.153260.306520.84674
2390.2894340.5788680.710566
2400.2846530.5693070.715347
2410.2500420.5000840.749958
2420.4655860.9311730.534414
2430.4201490.8402980.579851
2440.3542160.7084330.645784
2450.5074390.9851210.492561
2460.422540.8450790.57746
2470.3433750.6867490.656625
2480.4959360.9918730.504064
2490.3955890.7911770.604411
2500.2975580.5951150.702442
2510.4399110.8798220.560089
2520.9402510.1194990.0597494
2530.8736250.252750.126375
2540.8109990.3780020.189001






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level50.0204082NOK
5% type I error level160.0653061NOK
10% type I error level320.130612NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 5 & 0.0204082 & NOK \tabularnewline
5% type I error level & 16 & 0.0653061 & NOK \tabularnewline
10% type I error level & 32 & 0.130612 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225489&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]5[/C][C]0.0204082[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]16[/C][C]0.0653061[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]32[/C][C]0.130612[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225489&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225489&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level50.0204082NOK
5% type I error level160.0653061NOK
10% type I error level320.130612NOK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 5 ; 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')
}