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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 03 Nov 2013 04:11:49 -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/03/t1383469923it2d8vs6fkavcg9.htm/, Retrieved Mon, 29 Apr 2024 15:14:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221845, Retrieved Mon, 29 Apr 2024 15:14:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Happiness 7] [2013-11-03 09:11:49] [c762d1649a4d3d7755470a4359a854f5] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 13 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221845&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221845&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221845&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 time13 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 16.2899 + 0.0178216Connected[t] + 0.0122179Separate[t] + 0.116518Learning[t] -0.00484806Software[t] -0.397333Depression[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  16.2899 +  0.0178216Connected[t] +  0.0122179Separate[t] +  0.116518Learning[t] -0.00484806Software[t] -0.397333Depression[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221845&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  16.2899 +  0.0178216Connected[t] +  0.0122179Separate[t] +  0.116518Learning[t] -0.00484806Software[t] -0.397333Depression[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221845&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221845&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] = + 16.2899 + 0.0178216Connected[t] + 0.0122179Separate[t] + 0.116518Learning[t] -0.00484806Software[t] -0.397333Depression[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)16.28991.5985310.191.02802e-205.1401e-21
Connected0.01782160.03732630.47750.6334440.316722
Separate0.01221790.03841010.31810.7506740.375337
Learning0.1165180.06677981.7450.08220850.0411042
Software-0.004848060.0690614-0.07020.9440890.472045
Depression-0.3973330.0371904-10.682.66713e-221.33357e-22

\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) & 16.2899 & 1.59853 & 10.19 & 1.02802e-20 & 5.1401e-21 \tabularnewline
Connected & 0.0178216 & 0.0373263 & 0.4775 & 0.633444 & 0.316722 \tabularnewline
Separate & 0.0122179 & 0.0384101 & 0.3181 & 0.750674 & 0.375337 \tabularnewline
Learning & 0.116518 & 0.0667798 & 1.745 & 0.0822085 & 0.0411042 \tabularnewline
Software & -0.00484806 & 0.0690614 & -0.0702 & 0.944089 & 0.472045 \tabularnewline
Depression & -0.397333 & 0.0371904 & -10.68 & 2.66713e-22 & 1.33357e-22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221845&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]16.2899[/C][C]1.59853[/C][C]10.19[/C][C]1.02802e-20[/C][C]5.1401e-21[/C][/ROW]
[ROW][C]Connected[/C][C]0.0178216[/C][C]0.0373263[/C][C]0.4775[/C][C]0.633444[/C][C]0.316722[/C][/ROW]
[ROW][C]Separate[/C][C]0.0122179[/C][C]0.0384101[/C][C]0.3181[/C][C]0.750674[/C][C]0.375337[/C][/ROW]
[ROW][C]Learning[/C][C]0.116518[/C][C]0.0667798[/C][C]1.745[/C][C]0.0822085[/C][C]0.0411042[/C][/ROW]
[ROW][C]Software[/C][C]-0.00484806[/C][C]0.0690614[/C][C]-0.0702[/C][C]0.944089[/C][C]0.472045[/C][/ROW]
[ROW][C]Depression[/C][C]-0.397333[/C][C]0.0371904[/C][C]-10.68[/C][C]2.66713e-22[/C][C]1.33357e-22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221845&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221845&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)16.28991.5985310.191.02802e-205.1401e-21
Connected0.01782160.03732630.47750.6334440.316722
Separate0.01221790.03841010.31810.7506740.375337
Learning0.1165180.06677981.7450.08220850.0411042
Software-0.004848060.0690614-0.07020.9440890.472045
Depression-0.3973330.0371904-10.682.66713e-221.33357e-22






Multiple Linear Regression - Regression Statistics
Multiple R0.595766
R-squared0.354937
Adjusted R-squared0.342436
F-TEST (value)28.3922
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.02616
Sum Squared Residuals1059.17

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.595766 \tabularnewline
R-squared & 0.354937 \tabularnewline
Adjusted R-squared & 0.342436 \tabularnewline
F-TEST (value) & 28.3922 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 258 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.02616 \tabularnewline
Sum Squared Residuals & 1059.17 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221845&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.595766[/C][/ROW]
[ROW][C]R-squared[/C][C]0.354937[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.342436[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]28.3922[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]258[/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]2.02616[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1059.17[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221845&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221845&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 R0.595766
R-squared0.354937
Adjusted R-squared0.342436
F-TEST (value)28.3922
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.02616
Sum Squared Residuals1059.17






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.1734-0.173419
21814.81623.1838
31113.8306-2.83063
41214.1962-2.19624
51610.57215.42788
61813.96624.03378
71410.7783.22197
81414.6449-0.644905
91514.95880.0411583
101513.95241.04762
111715.18831.81165
121915.97433.02567
131013.2409-3.24086
141613.69752.30249
151815.26482.73518
161413.39030.609694
171413.45910.54093
181715.33291.66709
191415.5199-1.51988
201613.89192.10806
211815.29972.70033
221113.4646-2.46457
231414.832-0.832037
241213.6741-1.67409
251714.92792.07213
26915.7533-6.75334
271614.80421.19576
281413.050.95003
291513.52461.47535
301113.7165-2.71646
311615.33470.665287
321312.56150.438515
331714.93752.06251
341514.78330.216662
351413.67010.32989
361615.2160.784047
37910.3604-1.36036
381514.13970.86026
391715.0281.97205
401315.1593-2.15932
411515.5801-0.580075
421613.30942.69057
431616.4371-0.437062
441213.3369-1.33695
451514.52130.478677
461113.4351-2.43511
471515.4358-0.435841
481514.61720.382808
491713.24673.75329
501314.5605-1.5605
511615.14750.852451
521413.24680.75317
531111.4514-0.45142
541213.5987-1.59871
551213.9049-1.90491
561513.21781.78225
571614.04111.95887
581515.4522-0.452242
591215.1102-3.11025
601213.1849-1.18487
61810.5843-2.58426
621314.4206-1.42064
631114.3519-3.35187
641413.28530.71475
651513.91541.08464
661014.9128-4.91283
671112.6339-1.63389
681214.4304-2.43042
691513.64841.35164
701513.60921.39084
711413.3680.631976
721612.92463.07543
731514.23640.763553
741515.5242-0.524168
751314.6612-1.66116
761211.73930.260681
771714.03732.96271
781312.33090.669119
791513.45891.54112
801315.5093-2.50929
811514.75330.246702
821515.5958-0.595825
831614.27411.72592
841514.2020.797962
851413.90720.0927611
861513.86591.1341
871414.3315-0.331529
881313.0438-0.0438084
89710.2295-3.22946
901713.47153.52854
911313.2705-0.270533
921514.05540.944635
931412.93191.06812
941313.6632-0.663151
951614.86991.13008
961212.8209-0.820854
971414.7424-0.742396
981714.80012.19985
991514.90950.0905306
1001715.231.76996
1011212.8305-0.83055
1021614.87321.12682
1031114.5261-3.52606
1041512.80812.19187
105911.301-2.30096
1061614.94671.05329
1071512.94592.05414
1081013.2101-3.21006
109109.397660.60234
1101513.48341.5166
1111113.082-2.08197
1121314.9179-1.91793
1131412.76481.23522
1141813.94644.05356
1151615.40120.598766
1161413.37230.627714
1171413.81170.188319
1181415.191-1.19104
1191413.25310.746926
1201212.8315-0.831478
1211413.41080.589153
1221514.52950.470495
1231516.0313-1.03132
1241514.62430.375693
1251314.6665-1.66646
1261715.89651.10347
1271715.50471.49531
1281914.65134.34868
1291513.49641.5036
1301314.7085-1.70852
131910.3451-1.34506
1321515.307-0.306992
1331512.52252.47749
1341514.21870.781349
1351613.34142.65857
136119.390131.60987
1371413.45520.544767
1381112.1281-1.12806
1391514.31780.682175
1401313.7401-0.740058
1411515.1278-0.127766
1421613.41812.58192
1431414.3923-0.392256
1441514.16630.833662
1451614.13721.86276
1461614.45641.54363
1471113.6625-2.66254
1481214.6744-2.67439
149911.2264-2.2264
1501613.80692.19314
1511312.42050.579454
1521615.60480.395234
1531214.4574-2.45735
154911.4257-2.42566
1551311.23121.76884
1561313.2705-0.270533
1571413.23520.76477
1581914.65134.34868
1591315.5218-2.52176
1601211.53190.468099
1611312.45430.545707
162109.0190.980997
1631412.95681.0432
1641611.33664.66342
1651011.9196-1.91962
166119.071881.92812
1671414.0377-0.0376586
1681212.7196-0.719561
169912.4593-3.45934
170911.8773-2.87726
1711110.75540.244638
1721614.42161.57835
173914.0299-5.02994
1741311.37221.62777
1751613.44832.55172
1761315.4063-2.40625
177912.3546-3.35459
1781211.39370.606333
1791614.83061.16944
1801113.2111-2.2111
1811414.8068-0.806763
1821314.9568-1.9568
1831515.0527-0.0526651
1841415.0743-1.07435
1851613.52742.47263
1861311.55681.44319
1871413.71170.288306
1881513.961.04003
1891312.81610.183902
1901110.21350.786507
1911113.7078-2.70777
1921415.2886-1.28861
1931512.68712.31295
1941112.8193-1.81934
1951513.15471.84525
1961214.3352-2.33517
1971411.54592.45409
1981413.17620.823816
199811.3195-3.31949
2001313.785-0.78501
201912.2425-3.24253
2021513.89891.10108
2031714.1422.85802
2041313.0642-0.0641768
2051514.63170.368264
2061513.86481.13522
2071414.4087-0.408674
2081613.19962.80039
2091313.0052-0.00521584
2101614.23031.76969
211911.8844-2.8844
2121614.52751.47246
2131111.8791-0.879129
2141013.7592-3.75917
2151112.3927-1.39273
2161513.51181.48821
2171714.86242.13755
2181414.2151-0.215119
219810.0937-2.09372
2201513.53491.4651
2211114.0054-3.0054
2221614.22171.77827
2231012.2039-2.20391
2241515.0119-0.0119211
225910.4628-1.46278
2261614.22981.77025
2271914.44544.55456
2281214.113-2.11304
22989.39842-1.39842
2301113.5127-2.51271
2311413.980.0199866
232912.1017-3.10166
2331515.5348-0.534795
2341312.69860.301441
2351615.17710.822944
2361112.9808-1.98078
2371210.99821.00185
2381313.5526-0.552582
2391014.6209-4.62092
2401113.6791-2.67908
2411214.5481-2.54815
242811.1368-3.13684
2431211.92430.0756938
2441212.4452-0.445157
2451513.46471.53533
2461110.64710.352883
2471312.91540.0845653
248149.305334.69467
2491010.2979-0.297851
2501211.90580.09424
2511512.94292.05713
2521311.64561.35444
2531314.3453-1.34534
2541313.9243-0.924305
2551211.94760.0524434
2561212.9169-0.916946
257910.8278-1.82783
258911.6738-2.67381
2591512.86612.13389
2601014.553-4.55305
2611414.0641-0.0640583
2621513.81561.18437
26379.94904-2.94904
2641414.0173-0.0173152

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 14.1734 & -0.173419 \tabularnewline
2 & 18 & 14.8162 & 3.1838 \tabularnewline
3 & 11 & 13.8306 & -2.83063 \tabularnewline
4 & 12 & 14.1962 & -2.19624 \tabularnewline
5 & 16 & 10.5721 & 5.42788 \tabularnewline
6 & 18 & 13.9662 & 4.03378 \tabularnewline
7 & 14 & 10.778 & 3.22197 \tabularnewline
8 & 14 & 14.6449 & -0.644905 \tabularnewline
9 & 15 & 14.9588 & 0.0411583 \tabularnewline
10 & 15 & 13.9524 & 1.04762 \tabularnewline
11 & 17 & 15.1883 & 1.81165 \tabularnewline
12 & 19 & 15.9743 & 3.02567 \tabularnewline
13 & 10 & 13.2409 & -3.24086 \tabularnewline
14 & 16 & 13.6975 & 2.30249 \tabularnewline
15 & 18 & 15.2648 & 2.73518 \tabularnewline
16 & 14 & 13.3903 & 0.609694 \tabularnewline
17 & 14 & 13.4591 & 0.54093 \tabularnewline
18 & 17 & 15.3329 & 1.66709 \tabularnewline
19 & 14 & 15.5199 & -1.51988 \tabularnewline
20 & 16 & 13.8919 & 2.10806 \tabularnewline
21 & 18 & 15.2997 & 2.70033 \tabularnewline
22 & 11 & 13.4646 & -2.46457 \tabularnewline
23 & 14 & 14.832 & -0.832037 \tabularnewline
24 & 12 & 13.6741 & -1.67409 \tabularnewline
25 & 17 & 14.9279 & 2.07213 \tabularnewline
26 & 9 & 15.7533 & -6.75334 \tabularnewline
27 & 16 & 14.8042 & 1.19576 \tabularnewline
28 & 14 & 13.05 & 0.95003 \tabularnewline
29 & 15 & 13.5246 & 1.47535 \tabularnewline
30 & 11 & 13.7165 & -2.71646 \tabularnewline
31 & 16 & 15.3347 & 0.665287 \tabularnewline
32 & 13 & 12.5615 & 0.438515 \tabularnewline
33 & 17 & 14.9375 & 2.06251 \tabularnewline
34 & 15 & 14.7833 & 0.216662 \tabularnewline
35 & 14 & 13.6701 & 0.32989 \tabularnewline
36 & 16 & 15.216 & 0.784047 \tabularnewline
37 & 9 & 10.3604 & -1.36036 \tabularnewline
38 & 15 & 14.1397 & 0.86026 \tabularnewline
39 & 17 & 15.028 & 1.97205 \tabularnewline
40 & 13 & 15.1593 & -2.15932 \tabularnewline
41 & 15 & 15.5801 & -0.580075 \tabularnewline
42 & 16 & 13.3094 & 2.69057 \tabularnewline
43 & 16 & 16.4371 & -0.437062 \tabularnewline
44 & 12 & 13.3369 & -1.33695 \tabularnewline
45 & 15 & 14.5213 & 0.478677 \tabularnewline
46 & 11 & 13.4351 & -2.43511 \tabularnewline
47 & 15 & 15.4358 & -0.435841 \tabularnewline
48 & 15 & 14.6172 & 0.382808 \tabularnewline
49 & 17 & 13.2467 & 3.75329 \tabularnewline
50 & 13 & 14.5605 & -1.5605 \tabularnewline
51 & 16 & 15.1475 & 0.852451 \tabularnewline
52 & 14 & 13.2468 & 0.75317 \tabularnewline
53 & 11 & 11.4514 & -0.45142 \tabularnewline
54 & 12 & 13.5987 & -1.59871 \tabularnewline
55 & 12 & 13.9049 & -1.90491 \tabularnewline
56 & 15 & 13.2178 & 1.78225 \tabularnewline
57 & 16 & 14.0411 & 1.95887 \tabularnewline
58 & 15 & 15.4522 & -0.452242 \tabularnewline
59 & 12 & 15.1102 & -3.11025 \tabularnewline
60 & 12 & 13.1849 & -1.18487 \tabularnewline
61 & 8 & 10.5843 & -2.58426 \tabularnewline
62 & 13 & 14.4206 & -1.42064 \tabularnewline
63 & 11 & 14.3519 & -3.35187 \tabularnewline
64 & 14 & 13.2853 & 0.71475 \tabularnewline
65 & 15 & 13.9154 & 1.08464 \tabularnewline
66 & 10 & 14.9128 & -4.91283 \tabularnewline
67 & 11 & 12.6339 & -1.63389 \tabularnewline
68 & 12 & 14.4304 & -2.43042 \tabularnewline
69 & 15 & 13.6484 & 1.35164 \tabularnewline
70 & 15 & 13.6092 & 1.39084 \tabularnewline
71 & 14 & 13.368 & 0.631976 \tabularnewline
72 & 16 & 12.9246 & 3.07543 \tabularnewline
73 & 15 & 14.2364 & 0.763553 \tabularnewline
74 & 15 & 15.5242 & -0.524168 \tabularnewline
75 & 13 & 14.6612 & -1.66116 \tabularnewline
76 & 12 & 11.7393 & 0.260681 \tabularnewline
77 & 17 & 14.0373 & 2.96271 \tabularnewline
78 & 13 & 12.3309 & 0.669119 \tabularnewline
79 & 15 & 13.4589 & 1.54112 \tabularnewline
80 & 13 & 15.5093 & -2.50929 \tabularnewline
81 & 15 & 14.7533 & 0.246702 \tabularnewline
82 & 15 & 15.5958 & -0.595825 \tabularnewline
83 & 16 & 14.2741 & 1.72592 \tabularnewline
84 & 15 & 14.202 & 0.797962 \tabularnewline
85 & 14 & 13.9072 & 0.0927611 \tabularnewline
86 & 15 & 13.8659 & 1.1341 \tabularnewline
87 & 14 & 14.3315 & -0.331529 \tabularnewline
88 & 13 & 13.0438 & -0.0438084 \tabularnewline
89 & 7 & 10.2295 & -3.22946 \tabularnewline
90 & 17 & 13.4715 & 3.52854 \tabularnewline
91 & 13 & 13.2705 & -0.270533 \tabularnewline
92 & 15 & 14.0554 & 0.944635 \tabularnewline
93 & 14 & 12.9319 & 1.06812 \tabularnewline
94 & 13 & 13.6632 & -0.663151 \tabularnewline
95 & 16 & 14.8699 & 1.13008 \tabularnewline
96 & 12 & 12.8209 & -0.820854 \tabularnewline
97 & 14 & 14.7424 & -0.742396 \tabularnewline
98 & 17 & 14.8001 & 2.19985 \tabularnewline
99 & 15 & 14.9095 & 0.0905306 \tabularnewline
100 & 17 & 15.23 & 1.76996 \tabularnewline
101 & 12 & 12.8305 & -0.83055 \tabularnewline
102 & 16 & 14.8732 & 1.12682 \tabularnewline
103 & 11 & 14.5261 & -3.52606 \tabularnewline
104 & 15 & 12.8081 & 2.19187 \tabularnewline
105 & 9 & 11.301 & -2.30096 \tabularnewline
106 & 16 & 14.9467 & 1.05329 \tabularnewline
107 & 15 & 12.9459 & 2.05414 \tabularnewline
108 & 10 & 13.2101 & -3.21006 \tabularnewline
109 & 10 & 9.39766 & 0.60234 \tabularnewline
110 & 15 & 13.4834 & 1.5166 \tabularnewline
111 & 11 & 13.082 & -2.08197 \tabularnewline
112 & 13 & 14.9179 & -1.91793 \tabularnewline
113 & 14 & 12.7648 & 1.23522 \tabularnewline
114 & 18 & 13.9464 & 4.05356 \tabularnewline
115 & 16 & 15.4012 & 0.598766 \tabularnewline
116 & 14 & 13.3723 & 0.627714 \tabularnewline
117 & 14 & 13.8117 & 0.188319 \tabularnewline
118 & 14 & 15.191 & -1.19104 \tabularnewline
119 & 14 & 13.2531 & 0.746926 \tabularnewline
120 & 12 & 12.8315 & -0.831478 \tabularnewline
121 & 14 & 13.4108 & 0.589153 \tabularnewline
122 & 15 & 14.5295 & 0.470495 \tabularnewline
123 & 15 & 16.0313 & -1.03132 \tabularnewline
124 & 15 & 14.6243 & 0.375693 \tabularnewline
125 & 13 & 14.6665 & -1.66646 \tabularnewline
126 & 17 & 15.8965 & 1.10347 \tabularnewline
127 & 17 & 15.5047 & 1.49531 \tabularnewline
128 & 19 & 14.6513 & 4.34868 \tabularnewline
129 & 15 & 13.4964 & 1.5036 \tabularnewline
130 & 13 & 14.7085 & -1.70852 \tabularnewline
131 & 9 & 10.3451 & -1.34506 \tabularnewline
132 & 15 & 15.307 & -0.306992 \tabularnewline
133 & 15 & 12.5225 & 2.47749 \tabularnewline
134 & 15 & 14.2187 & 0.781349 \tabularnewline
135 & 16 & 13.3414 & 2.65857 \tabularnewline
136 & 11 & 9.39013 & 1.60987 \tabularnewline
137 & 14 & 13.4552 & 0.544767 \tabularnewline
138 & 11 & 12.1281 & -1.12806 \tabularnewline
139 & 15 & 14.3178 & 0.682175 \tabularnewline
140 & 13 & 13.7401 & -0.740058 \tabularnewline
141 & 15 & 15.1278 & -0.127766 \tabularnewline
142 & 16 & 13.4181 & 2.58192 \tabularnewline
143 & 14 & 14.3923 & -0.392256 \tabularnewline
144 & 15 & 14.1663 & 0.833662 \tabularnewline
145 & 16 & 14.1372 & 1.86276 \tabularnewline
146 & 16 & 14.4564 & 1.54363 \tabularnewline
147 & 11 & 13.6625 & -2.66254 \tabularnewline
148 & 12 & 14.6744 & -2.67439 \tabularnewline
149 & 9 & 11.2264 & -2.2264 \tabularnewline
150 & 16 & 13.8069 & 2.19314 \tabularnewline
151 & 13 & 12.4205 & 0.579454 \tabularnewline
152 & 16 & 15.6048 & 0.395234 \tabularnewline
153 & 12 & 14.4574 & -2.45735 \tabularnewline
154 & 9 & 11.4257 & -2.42566 \tabularnewline
155 & 13 & 11.2312 & 1.76884 \tabularnewline
156 & 13 & 13.2705 & -0.270533 \tabularnewline
157 & 14 & 13.2352 & 0.76477 \tabularnewline
158 & 19 & 14.6513 & 4.34868 \tabularnewline
159 & 13 & 15.5218 & -2.52176 \tabularnewline
160 & 12 & 11.5319 & 0.468099 \tabularnewline
161 & 13 & 12.4543 & 0.545707 \tabularnewline
162 & 10 & 9.019 & 0.980997 \tabularnewline
163 & 14 & 12.9568 & 1.0432 \tabularnewline
164 & 16 & 11.3366 & 4.66342 \tabularnewline
165 & 10 & 11.9196 & -1.91962 \tabularnewline
166 & 11 & 9.07188 & 1.92812 \tabularnewline
167 & 14 & 14.0377 & -0.0376586 \tabularnewline
168 & 12 & 12.7196 & -0.719561 \tabularnewline
169 & 9 & 12.4593 & -3.45934 \tabularnewline
170 & 9 & 11.8773 & -2.87726 \tabularnewline
171 & 11 & 10.7554 & 0.244638 \tabularnewline
172 & 16 & 14.4216 & 1.57835 \tabularnewline
173 & 9 & 14.0299 & -5.02994 \tabularnewline
174 & 13 & 11.3722 & 1.62777 \tabularnewline
175 & 16 & 13.4483 & 2.55172 \tabularnewline
176 & 13 & 15.4063 & -2.40625 \tabularnewline
177 & 9 & 12.3546 & -3.35459 \tabularnewline
178 & 12 & 11.3937 & 0.606333 \tabularnewline
179 & 16 & 14.8306 & 1.16944 \tabularnewline
180 & 11 & 13.2111 & -2.2111 \tabularnewline
181 & 14 & 14.8068 & -0.806763 \tabularnewline
182 & 13 & 14.9568 & -1.9568 \tabularnewline
183 & 15 & 15.0527 & -0.0526651 \tabularnewline
184 & 14 & 15.0743 & -1.07435 \tabularnewline
185 & 16 & 13.5274 & 2.47263 \tabularnewline
186 & 13 & 11.5568 & 1.44319 \tabularnewline
187 & 14 & 13.7117 & 0.288306 \tabularnewline
188 & 15 & 13.96 & 1.04003 \tabularnewline
189 & 13 & 12.8161 & 0.183902 \tabularnewline
190 & 11 & 10.2135 & 0.786507 \tabularnewline
191 & 11 & 13.7078 & -2.70777 \tabularnewline
192 & 14 & 15.2886 & -1.28861 \tabularnewline
193 & 15 & 12.6871 & 2.31295 \tabularnewline
194 & 11 & 12.8193 & -1.81934 \tabularnewline
195 & 15 & 13.1547 & 1.84525 \tabularnewline
196 & 12 & 14.3352 & -2.33517 \tabularnewline
197 & 14 & 11.5459 & 2.45409 \tabularnewline
198 & 14 & 13.1762 & 0.823816 \tabularnewline
199 & 8 & 11.3195 & -3.31949 \tabularnewline
200 & 13 & 13.785 & -0.78501 \tabularnewline
201 & 9 & 12.2425 & -3.24253 \tabularnewline
202 & 15 & 13.8989 & 1.10108 \tabularnewline
203 & 17 & 14.142 & 2.85802 \tabularnewline
204 & 13 & 13.0642 & -0.0641768 \tabularnewline
205 & 15 & 14.6317 & 0.368264 \tabularnewline
206 & 15 & 13.8648 & 1.13522 \tabularnewline
207 & 14 & 14.4087 & -0.408674 \tabularnewline
208 & 16 & 13.1996 & 2.80039 \tabularnewline
209 & 13 & 13.0052 & -0.00521584 \tabularnewline
210 & 16 & 14.2303 & 1.76969 \tabularnewline
211 & 9 & 11.8844 & -2.8844 \tabularnewline
212 & 16 & 14.5275 & 1.47246 \tabularnewline
213 & 11 & 11.8791 & -0.879129 \tabularnewline
214 & 10 & 13.7592 & -3.75917 \tabularnewline
215 & 11 & 12.3927 & -1.39273 \tabularnewline
216 & 15 & 13.5118 & 1.48821 \tabularnewline
217 & 17 & 14.8624 & 2.13755 \tabularnewline
218 & 14 & 14.2151 & -0.215119 \tabularnewline
219 & 8 & 10.0937 & -2.09372 \tabularnewline
220 & 15 & 13.5349 & 1.4651 \tabularnewline
221 & 11 & 14.0054 & -3.0054 \tabularnewline
222 & 16 & 14.2217 & 1.77827 \tabularnewline
223 & 10 & 12.2039 & -2.20391 \tabularnewline
224 & 15 & 15.0119 & -0.0119211 \tabularnewline
225 & 9 & 10.4628 & -1.46278 \tabularnewline
226 & 16 & 14.2298 & 1.77025 \tabularnewline
227 & 19 & 14.4454 & 4.55456 \tabularnewline
228 & 12 & 14.113 & -2.11304 \tabularnewline
229 & 8 & 9.39842 & -1.39842 \tabularnewline
230 & 11 & 13.5127 & -2.51271 \tabularnewline
231 & 14 & 13.98 & 0.0199866 \tabularnewline
232 & 9 & 12.1017 & -3.10166 \tabularnewline
233 & 15 & 15.5348 & -0.534795 \tabularnewline
234 & 13 & 12.6986 & 0.301441 \tabularnewline
235 & 16 & 15.1771 & 0.822944 \tabularnewline
236 & 11 & 12.9808 & -1.98078 \tabularnewline
237 & 12 & 10.9982 & 1.00185 \tabularnewline
238 & 13 & 13.5526 & -0.552582 \tabularnewline
239 & 10 & 14.6209 & -4.62092 \tabularnewline
240 & 11 & 13.6791 & -2.67908 \tabularnewline
241 & 12 & 14.5481 & -2.54815 \tabularnewline
242 & 8 & 11.1368 & -3.13684 \tabularnewline
243 & 12 & 11.9243 & 0.0756938 \tabularnewline
244 & 12 & 12.4452 & -0.445157 \tabularnewline
245 & 15 & 13.4647 & 1.53533 \tabularnewline
246 & 11 & 10.6471 & 0.352883 \tabularnewline
247 & 13 & 12.9154 & 0.0845653 \tabularnewline
248 & 14 & 9.30533 & 4.69467 \tabularnewline
249 & 10 & 10.2979 & -0.297851 \tabularnewline
250 & 12 & 11.9058 & 0.09424 \tabularnewline
251 & 15 & 12.9429 & 2.05713 \tabularnewline
252 & 13 & 11.6456 & 1.35444 \tabularnewline
253 & 13 & 14.3453 & -1.34534 \tabularnewline
254 & 13 & 13.9243 & -0.924305 \tabularnewline
255 & 12 & 11.9476 & 0.0524434 \tabularnewline
256 & 12 & 12.9169 & -0.916946 \tabularnewline
257 & 9 & 10.8278 & -1.82783 \tabularnewline
258 & 9 & 11.6738 & -2.67381 \tabularnewline
259 & 15 & 12.8661 & 2.13389 \tabularnewline
260 & 10 & 14.553 & -4.55305 \tabularnewline
261 & 14 & 14.0641 & -0.0640583 \tabularnewline
262 & 15 & 13.8156 & 1.18437 \tabularnewline
263 & 7 & 9.94904 & -2.94904 \tabularnewline
264 & 14 & 14.0173 & -0.0173152 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221845&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]14[/C][C]14.1734[/C][C]-0.173419[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]14.8162[/C][C]3.1838[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.8306[/C][C]-2.83063[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.1962[/C][C]-2.19624[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]10.5721[/C][C]5.42788[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]13.9662[/C][C]4.03378[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.778[/C][C]3.22197[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.6449[/C][C]-0.644905[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]14.9588[/C][C]0.0411583[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]13.9524[/C][C]1.04762[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.1883[/C][C]1.81165[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.9743[/C][C]3.02567[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.2409[/C][C]-3.24086[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.6975[/C][C]2.30249[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.2648[/C][C]2.73518[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.3903[/C][C]0.609694[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.4591[/C][C]0.54093[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.3329[/C][C]1.66709[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.5199[/C][C]-1.51988[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.8919[/C][C]2.10806[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.2997[/C][C]2.70033[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.4646[/C][C]-2.46457[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.832[/C][C]-0.832037[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.6741[/C][C]-1.67409[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]14.9279[/C][C]2.07213[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.7533[/C][C]-6.75334[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.8042[/C][C]1.19576[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.05[/C][C]0.95003[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.5246[/C][C]1.47535[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]13.7165[/C][C]-2.71646[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.3347[/C][C]0.665287[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.5615[/C][C]0.438515[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]14.9375[/C][C]2.06251[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]14.7833[/C][C]0.216662[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.6701[/C][C]0.32989[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.216[/C][C]0.784047[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.3604[/C][C]-1.36036[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.1397[/C][C]0.86026[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.028[/C][C]1.97205[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.1593[/C][C]-2.15932[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.5801[/C][C]-0.580075[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.3094[/C][C]2.69057[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]16.4371[/C][C]-0.437062[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.3369[/C][C]-1.33695[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.5213[/C][C]0.478677[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.4351[/C][C]-2.43511[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.4358[/C][C]-0.435841[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.6172[/C][C]0.382808[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.2467[/C][C]3.75329[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.5605[/C][C]-1.5605[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.1475[/C][C]0.852451[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.2468[/C][C]0.75317[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.4514[/C][C]-0.45142[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.5987[/C][C]-1.59871[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]13.9049[/C][C]-1.90491[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.2178[/C][C]1.78225[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.0411[/C][C]1.95887[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.4522[/C][C]-0.452242[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.1102[/C][C]-3.11025[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.1849[/C][C]-1.18487[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.5843[/C][C]-2.58426[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.4206[/C][C]-1.42064[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.3519[/C][C]-3.35187[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.2853[/C][C]0.71475[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.9154[/C][C]1.08464[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]14.9128[/C][C]-4.91283[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.6339[/C][C]-1.63389[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.4304[/C][C]-2.43042[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.6484[/C][C]1.35164[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.6092[/C][C]1.39084[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.368[/C][C]0.631976[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.9246[/C][C]3.07543[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.2364[/C][C]0.763553[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.5242[/C][C]-0.524168[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.6612[/C][C]-1.66116[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]11.7393[/C][C]0.260681[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]14.0373[/C][C]2.96271[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.3309[/C][C]0.669119[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.4589[/C][C]1.54112[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]15.5093[/C][C]-2.50929[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.7533[/C][C]0.246702[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.5958[/C][C]-0.595825[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.2741[/C][C]1.72592[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.202[/C][C]0.797962[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]13.9072[/C][C]0.0927611[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.8659[/C][C]1.1341[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.3315[/C][C]-0.331529[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]13.0438[/C][C]-0.0438084[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.2295[/C][C]-3.22946[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.4715[/C][C]3.52854[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]13.2705[/C][C]-0.270533[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.0554[/C][C]0.944635[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]12.9319[/C][C]1.06812[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.6632[/C][C]-0.663151[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.8699[/C][C]1.13008[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.8209[/C][C]-0.820854[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.7424[/C][C]-0.742396[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.8001[/C][C]2.19985[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]14.9095[/C][C]0.0905306[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.23[/C][C]1.76996[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.8305[/C][C]-0.83055[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]14.8732[/C][C]1.12682[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.5261[/C][C]-3.52606[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]12.8081[/C][C]2.19187[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.301[/C][C]-2.30096[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.9467[/C][C]1.05329[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9459[/C][C]2.05414[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]13.2101[/C][C]-3.21006[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.39766[/C][C]0.60234[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.4834[/C][C]1.5166[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.082[/C][C]-2.08197[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]14.9179[/C][C]-1.91793[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]12.7648[/C][C]1.23522[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]13.9464[/C][C]4.05356[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.4012[/C][C]0.598766[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.3723[/C][C]0.627714[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.8117[/C][C]0.188319[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.191[/C][C]-1.19104[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.2531[/C][C]0.746926[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.8315[/C][C]-0.831478[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.4108[/C][C]0.589153[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.5295[/C][C]0.470495[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]16.0313[/C][C]-1.03132[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.6243[/C][C]0.375693[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.6665[/C][C]-1.66646[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]15.8965[/C][C]1.10347[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.5047[/C][C]1.49531[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.6513[/C][C]4.34868[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.4964[/C][C]1.5036[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.7085[/C][C]-1.70852[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.3451[/C][C]-1.34506[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.307[/C][C]-0.306992[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.5225[/C][C]2.47749[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.2187[/C][C]0.781349[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.3414[/C][C]2.65857[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.39013[/C][C]1.60987[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.4552[/C][C]0.544767[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]12.1281[/C][C]-1.12806[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.3178[/C][C]0.682175[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.7401[/C][C]-0.740058[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]15.1278[/C][C]-0.127766[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.4181[/C][C]2.58192[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.3923[/C][C]-0.392256[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.1663[/C][C]0.833662[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.1372[/C][C]1.86276[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.4564[/C][C]1.54363[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.6625[/C][C]-2.66254[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.6744[/C][C]-2.67439[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.2264[/C][C]-2.2264[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]13.8069[/C][C]2.19314[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.4205[/C][C]0.579454[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.6048[/C][C]0.395234[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.4574[/C][C]-2.45735[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.4257[/C][C]-2.42566[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.2312[/C][C]1.76884[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]13.2705[/C][C]-0.270533[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.2352[/C][C]0.76477[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.6513[/C][C]4.34868[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.5218[/C][C]-2.52176[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.5319[/C][C]0.468099[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.4543[/C][C]0.545707[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.019[/C][C]0.980997[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]12.9568[/C][C]1.0432[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.3366[/C][C]4.66342[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.9196[/C][C]-1.91962[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]9.07188[/C][C]1.92812[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.0377[/C][C]-0.0376586[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.7196[/C][C]-0.719561[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.4593[/C][C]-3.45934[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.8773[/C][C]-2.87726[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.7554[/C][C]0.244638[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.4216[/C][C]1.57835[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]14.0299[/C][C]-5.02994[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.3722[/C][C]1.62777[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.4483[/C][C]2.55172[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.4063[/C][C]-2.40625[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.3546[/C][C]-3.35459[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.3937[/C][C]0.606333[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.8306[/C][C]1.16944[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.2111[/C][C]-2.2111[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]14.8068[/C][C]-0.806763[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.9568[/C][C]-1.9568[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]15.0527[/C][C]-0.0526651[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]15.0743[/C][C]-1.07435[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]13.5274[/C][C]2.47263[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.5568[/C][C]1.44319[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.7117[/C][C]0.288306[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]13.96[/C][C]1.04003[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.8161[/C][C]0.183902[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.2135[/C][C]0.786507[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]13.7078[/C][C]-2.70777[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]15.2886[/C][C]-1.28861[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.6871[/C][C]2.31295[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.8193[/C][C]-1.81934[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.1547[/C][C]1.84525[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.3352[/C][C]-2.33517[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.5459[/C][C]2.45409[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.1762[/C][C]0.823816[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.3195[/C][C]-3.31949[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.785[/C][C]-0.78501[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.2425[/C][C]-3.24253[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.8989[/C][C]1.10108[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]14.142[/C][C]2.85802[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]13.0642[/C][C]-0.0641768[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.6317[/C][C]0.368264[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.8648[/C][C]1.13522[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.4087[/C][C]-0.408674[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]13.1996[/C][C]2.80039[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]13.0052[/C][C]-0.00521584[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.2303[/C][C]1.76969[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.8844[/C][C]-2.8844[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.5275[/C][C]1.47246[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.8791[/C][C]-0.879129[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.7592[/C][C]-3.75917[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.3927[/C][C]-1.39273[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.5118[/C][C]1.48821[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.8624[/C][C]2.13755[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.2151[/C][C]-0.215119[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]10.0937[/C][C]-2.09372[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.5349[/C][C]1.4651[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]14.0054[/C][C]-3.0054[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]14.2217[/C][C]1.77827[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.2039[/C][C]-2.20391[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]15.0119[/C][C]-0.0119211[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]10.4628[/C][C]-1.46278[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.2298[/C][C]1.77025[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]14.4454[/C][C]4.55456[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]14.113[/C][C]-2.11304[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.39842[/C][C]-1.39842[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.5127[/C][C]-2.51271[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.98[/C][C]0.0199866[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]12.1017[/C][C]-3.10166[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]15.5348[/C][C]-0.534795[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.6986[/C][C]0.301441[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]15.1771[/C][C]0.822944[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.9808[/C][C]-1.98078[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]10.9982[/C][C]1.00185[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.5526[/C][C]-0.552582[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.6209[/C][C]-4.62092[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.6791[/C][C]-2.67908[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.5481[/C][C]-2.54815[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]11.1368[/C][C]-3.13684[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.9243[/C][C]0.0756938[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.4452[/C][C]-0.445157[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.4647[/C][C]1.53533[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.6471[/C][C]0.352883[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.9154[/C][C]0.0845653[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]9.30533[/C][C]4.69467[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.2979[/C][C]-0.297851[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.9058[/C][C]0.09424[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.9429[/C][C]2.05713[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.6456[/C][C]1.35444[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.3453[/C][C]-1.34534[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.9243[/C][C]-0.924305[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.9476[/C][C]0.0524434[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.9169[/C][C]-0.916946[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.8278[/C][C]-1.82783[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.6738[/C][C]-2.67381[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.8661[/C][C]2.13389[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.553[/C][C]-4.55305[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]14.0641[/C][C]-0.0640583[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.8156[/C][C]1.18437[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.94904[/C][C]-2.94904[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]14.0173[/C][C]-0.0173152[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221845&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221845&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.1734-0.173419
21814.81623.1838
31113.8306-2.83063
41214.1962-2.19624
51610.57215.42788
61813.96624.03378
71410.7783.22197
81414.6449-0.644905
91514.95880.0411583
101513.95241.04762
111715.18831.81165
121915.97433.02567
131013.2409-3.24086
141613.69752.30249
151815.26482.73518
161413.39030.609694
171413.45910.54093
181715.33291.66709
191415.5199-1.51988
201613.89192.10806
211815.29972.70033
221113.4646-2.46457
231414.832-0.832037
241213.6741-1.67409
251714.92792.07213
26915.7533-6.75334
271614.80421.19576
281413.050.95003
291513.52461.47535
301113.7165-2.71646
311615.33470.665287
321312.56150.438515
331714.93752.06251
341514.78330.216662
351413.67010.32989
361615.2160.784047
37910.3604-1.36036
381514.13970.86026
391715.0281.97205
401315.1593-2.15932
411515.5801-0.580075
421613.30942.69057
431616.4371-0.437062
441213.3369-1.33695
451514.52130.478677
461113.4351-2.43511
471515.4358-0.435841
481514.61720.382808
491713.24673.75329
501314.5605-1.5605
511615.14750.852451
521413.24680.75317
531111.4514-0.45142
541213.5987-1.59871
551213.9049-1.90491
561513.21781.78225
571614.04111.95887
581515.4522-0.452242
591215.1102-3.11025
601213.1849-1.18487
61810.5843-2.58426
621314.4206-1.42064
631114.3519-3.35187
641413.28530.71475
651513.91541.08464
661014.9128-4.91283
671112.6339-1.63389
681214.4304-2.43042
691513.64841.35164
701513.60921.39084
711413.3680.631976
721612.92463.07543
731514.23640.763553
741515.5242-0.524168
751314.6612-1.66116
761211.73930.260681
771714.03732.96271
781312.33090.669119
791513.45891.54112
801315.5093-2.50929
811514.75330.246702
821515.5958-0.595825
831614.27411.72592
841514.2020.797962
851413.90720.0927611
861513.86591.1341
871414.3315-0.331529
881313.0438-0.0438084
89710.2295-3.22946
901713.47153.52854
911313.2705-0.270533
921514.05540.944635
931412.93191.06812
941313.6632-0.663151
951614.86991.13008
961212.8209-0.820854
971414.7424-0.742396
981714.80012.19985
991514.90950.0905306
1001715.231.76996
1011212.8305-0.83055
1021614.87321.12682
1031114.5261-3.52606
1041512.80812.19187
105911.301-2.30096
1061614.94671.05329
1071512.94592.05414
1081013.2101-3.21006
109109.397660.60234
1101513.48341.5166
1111113.082-2.08197
1121314.9179-1.91793
1131412.76481.23522
1141813.94644.05356
1151615.40120.598766
1161413.37230.627714
1171413.81170.188319
1181415.191-1.19104
1191413.25310.746926
1201212.8315-0.831478
1211413.41080.589153
1221514.52950.470495
1231516.0313-1.03132
1241514.62430.375693
1251314.6665-1.66646
1261715.89651.10347
1271715.50471.49531
1281914.65134.34868
1291513.49641.5036
1301314.7085-1.70852
131910.3451-1.34506
1321515.307-0.306992
1331512.52252.47749
1341514.21870.781349
1351613.34142.65857
136119.390131.60987
1371413.45520.544767
1381112.1281-1.12806
1391514.31780.682175
1401313.7401-0.740058
1411515.1278-0.127766
1421613.41812.58192
1431414.3923-0.392256
1441514.16630.833662
1451614.13721.86276
1461614.45641.54363
1471113.6625-2.66254
1481214.6744-2.67439
149911.2264-2.2264
1501613.80692.19314
1511312.42050.579454
1521615.60480.395234
1531214.4574-2.45735
154911.4257-2.42566
1551311.23121.76884
1561313.2705-0.270533
1571413.23520.76477
1581914.65134.34868
1591315.5218-2.52176
1601211.53190.468099
1611312.45430.545707
162109.0190.980997
1631412.95681.0432
1641611.33664.66342
1651011.9196-1.91962
166119.071881.92812
1671414.0377-0.0376586
1681212.7196-0.719561
169912.4593-3.45934
170911.8773-2.87726
1711110.75540.244638
1721614.42161.57835
173914.0299-5.02994
1741311.37221.62777
1751613.44832.55172
1761315.4063-2.40625
177912.3546-3.35459
1781211.39370.606333
1791614.83061.16944
1801113.2111-2.2111
1811414.8068-0.806763
1821314.9568-1.9568
1831515.0527-0.0526651
1841415.0743-1.07435
1851613.52742.47263
1861311.55681.44319
1871413.71170.288306
1881513.961.04003
1891312.81610.183902
1901110.21350.786507
1911113.7078-2.70777
1921415.2886-1.28861
1931512.68712.31295
1941112.8193-1.81934
1951513.15471.84525
1961214.3352-2.33517
1971411.54592.45409
1981413.17620.823816
199811.3195-3.31949
2001313.785-0.78501
201912.2425-3.24253
2021513.89891.10108
2031714.1422.85802
2041313.0642-0.0641768
2051514.63170.368264
2061513.86481.13522
2071414.4087-0.408674
2081613.19962.80039
2091313.0052-0.00521584
2101614.23031.76969
211911.8844-2.8844
2121614.52751.47246
2131111.8791-0.879129
2141013.7592-3.75917
2151112.3927-1.39273
2161513.51181.48821
2171714.86242.13755
2181414.2151-0.215119
219810.0937-2.09372
2201513.53491.4651
2211114.0054-3.0054
2221614.22171.77827
2231012.2039-2.20391
2241515.0119-0.0119211
225910.4628-1.46278
2261614.22981.77025
2271914.44544.55456
2281214.113-2.11304
22989.39842-1.39842
2301113.5127-2.51271
2311413.980.0199866
232912.1017-3.10166
2331515.5348-0.534795
2341312.69860.301441
2351615.17710.822944
2361112.9808-1.98078
2371210.99821.00185
2381313.5526-0.552582
2391014.6209-4.62092
2401113.6791-2.67908
2411214.5481-2.54815
242811.1368-3.13684
2431211.92430.0756938
2441212.4452-0.445157
2451513.46471.53533
2461110.64710.352883
2471312.91540.0845653
248149.305334.69467
2491010.2979-0.297851
2501211.90580.09424
2511512.94292.05713
2521311.64561.35444
2531314.3453-1.34534
2541313.9243-0.924305
2551211.94760.0524434
2561212.9169-0.916946
257910.8278-1.82783
258911.6738-2.67381
2591512.86612.13389
2601014.553-4.55305
2611414.0641-0.0640583
2621513.81561.18437
26379.94904-2.94904
2641414.0173-0.0173152






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.5644540.8710920.435546
100.6121530.7756950.387847
110.5089210.9821570.491079
120.7639090.4721810.236091
130.9449480.1101050.0550525
140.9452680.1094640.0547321
150.9706820.05863620.0293181
160.9552520.08949690.0447485
170.9386280.1227430.0613716
180.935610.1287790.0643897
190.9225940.1548110.0774057
200.9022770.1954460.0977232
210.9084150.183170.091585
220.9455950.108810.054405
230.9308820.1382350.0691177
240.9217110.1565770.0782886
250.8986010.2027990.101399
260.9979090.004182730.00209136
270.9969580.006084780.00304239
280.9953860.009228540.00461427
290.9933690.0132620.00663101
300.9965120.006975210.0034876
310.9948510.01029770.00514887
320.9928510.01429880.0071494
330.9912760.01744820.0087241
340.9876080.02478410.0123921
350.9835340.03293250.0164663
360.9775190.04496290.0224815
370.9825760.03484760.0174238
380.9765670.04686590.0234329
390.9743180.05136380.0256819
400.9754820.04903530.0245176
410.9684550.06308950.0315448
420.9675540.06489180.0324459
430.9582620.08347680.0417384
440.9556470.0887050.0443525
450.9435970.1128060.056403
460.9539380.09212470.0460623
470.9416060.1167870.0583935
480.9269350.146130.0730648
490.9481570.1036850.0518427
500.9431590.1136820.0568411
510.930820.1383590.0691796
520.9151810.1696390.0848193
530.9024090.1951830.0975913
540.8996250.200750.100375
550.8950890.2098220.104911
560.8842740.2314510.115726
570.8765160.2469670.123484
580.8542010.2915970.145799
590.8797970.2404060.120203
600.8728410.2543180.127159
610.8992720.2014550.100728
620.8910070.2179860.108993
630.920730.158540.0792699
640.9057470.1885050.0942527
650.8908060.2183880.109194
660.9540160.09196810.0459841
670.9526450.09471030.0473551
680.9566430.0867130.0433565
690.9501110.09977790.049889
700.9432090.1135830.0567914
710.9314190.1371620.0685811
720.9422070.1155860.057793
730.931060.1378790.0689397
740.9181260.1637490.0818745
750.9098050.1803910.0901954
760.8931520.2136960.106848
770.9069840.1860320.0930158
780.8908120.2183760.109188
790.88290.2342010.1171
800.884170.2316590.11583
810.8644350.271130.135565
820.8440290.3119430.155971
830.8369390.3261220.163061
840.8156120.3687750.184388
850.789110.421780.21089
860.7655020.4689960.234498
870.7361970.5276060.263803
880.7045010.5909990.295499
890.7704330.4591330.229567
900.8105830.3788350.189417
910.7843340.4313320.215666
920.7600450.4799090.239955
930.7408490.5183010.259151
940.7123810.5752380.287619
950.6874750.6250510.312525
960.6612340.6775320.338766
970.6311970.7376070.368803
980.636980.7260410.36302
990.6023640.7952720.397636
1000.5939570.8120870.406043
1010.5672710.8654590.432729
1020.5429440.9141120.457056
1030.6017680.7964650.398232
1040.5982340.8035320.401766
1050.6109060.7781870.389094
1060.5845130.8309750.415487
1070.5776650.8446690.422335
1080.6379570.7240870.362043
1090.6123590.7752820.387641
1100.5959490.8081010.404051
1110.595290.809420.40471
1120.6054760.7890490.394524
1130.582730.834540.41727
1140.6758010.6483990.324199
1150.6474970.7050060.352503
1160.6190450.7619090.380955
1170.5886550.8226910.411345
1180.567460.8650810.43254
1190.5367280.9265430.463272
1200.510580.9788390.48942
1210.4815830.9631670.518417
1220.4497880.8995750.550212
1230.4236990.8473990.576301
1240.3907850.7815710.609215
1250.3756840.7513680.624316
1260.351510.703020.64849
1270.3363460.6726920.663654
1280.4564710.9129420.543529
1290.4403640.8807270.559636
1300.4297690.8595390.570231
1310.4110890.8221790.588911
1320.3814860.7629730.618514
1330.3996440.7992880.600356
1340.3730320.7460640.626968
1350.4018250.803650.598175
1360.3862290.7724570.613771
1370.3558930.7117860.644107
1380.3365740.6731470.663426
1390.308440.616880.69156
1400.2834740.5669480.716526
1410.2544840.5089690.745516
1420.2738250.5476510.726175
1430.2451040.4902080.754896
1440.2237480.4474960.776252
1450.2178660.4357320.782134
1460.2104190.4208380.789581
1470.2274750.4549510.772525
1480.2436110.4872230.756389
1490.2531750.506350.746825
1500.262040.5240810.73796
1510.238310.476620.76169
1520.2152750.430550.784725
1530.2278190.4556380.772181
1540.2410690.4821380.758931
1550.2323070.4646130.767693
1560.2057270.4114530.794273
1570.1862640.3725280.813736
1580.2981770.5963550.701823
1590.3105490.6210980.689451
1600.2857240.5714480.714276
1610.2611690.5223380.738831
1620.2357580.4715160.764242
1630.2130560.4261120.786944
1640.3501980.7003970.649802
1650.3420920.6841850.657908
1660.3370360.6740710.662964
1670.3043220.6086440.695678
1680.278310.5566190.72169
1690.3283540.6567080.671646
1700.3538440.7076880.646156
1710.3240730.6481460.675927
1720.3188250.6376490.681175
1730.4867410.9734830.513259
1740.4696820.9393650.530318
1750.4937320.9874650.506268
1760.5044050.991190.495595
1770.5601620.8796760.439838
1780.5273820.9452370.472618
1790.5031480.9937040.496852
1800.5035910.9928180.496409
1810.4688750.937750.531125
1820.4650920.9301830.534908
1830.4267890.8535780.573211
1840.3974190.7948370.602581
1850.4257160.8514310.574284
1860.4180360.8360730.581964
1870.381190.7623810.61881
1880.3514460.7028910.648554
1890.3166510.6333020.683349
1900.2930490.5860970.706951
1910.3076190.6152370.692381
1920.2852990.5705980.714701
1930.3057060.6114130.694294
1940.2921930.5843870.707807
1950.2910520.5821040.708948
1960.3012510.6025020.698749
1970.3381590.6763190.661841
1980.3097630.6195260.690237
1990.3465770.6931550.653423
2000.3124310.6248610.687569
2010.3582820.7165640.641718
2020.3335440.6670870.666456
2030.3770390.7540780.622961
2040.3370080.6740160.662992
2050.3015230.6030460.698477
2060.2781890.5563780.721811
2070.2434070.4868140.756593
2080.2818610.5637220.718139
2090.2465350.4930710.753465
2100.2453360.4906730.754664
2110.2699930.5399870.730007
2120.2582760.5165510.741724
2130.2245930.4491870.775407
2140.2859880.5719760.714012
2150.2590140.5180280.740986
2160.2449580.4899160.755042
2170.2594670.5189340.740533
2180.2228780.4457560.777122
2190.2124610.4249210.787539
2200.2082580.4165170.791742
2210.2291530.4583060.770847
2220.2368220.4736440.763178
2230.2309810.4619630.769019
2240.1967360.3934720.803264
2250.172250.3445010.82775
2260.1995560.3991120.800444
2270.4644940.9289880.535506
2280.4307810.8615620.569219
2290.4093450.818690.590655
2300.3910840.7821690.608916
2310.3456730.6913460.654327
2320.3805540.7611080.619446
2330.3510350.702070.648965
2340.2997510.5995020.700249
2350.3042750.6085490.695725
2360.2809710.5619420.719029
2370.2362310.4724610.763769
2380.1901910.3803820.809809
2390.3286760.6573530.671324
2400.3185780.6371550.681422
2410.3015670.6031340.698433
2420.4624770.9249530.537523
2430.4536730.9073450.546327
2440.4057030.8114060.594297
2450.4096340.8192680.590366
2460.3317090.6634180.668291
2470.2644130.5288260.735587
2480.5933980.8132040.406602
2490.4965590.9931180.503441
2500.3976280.7952560.602372
2510.5647390.8705220.435261
2520.9175290.1649410.0824707
2530.8512690.2974620.148731
2540.794990.4100190.20501
2550.6962290.6075430.303771

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.564454 & 0.871092 & 0.435546 \tabularnewline
10 & 0.612153 & 0.775695 & 0.387847 \tabularnewline
11 & 0.508921 & 0.982157 & 0.491079 \tabularnewline
12 & 0.763909 & 0.472181 & 0.236091 \tabularnewline
13 & 0.944948 & 0.110105 & 0.0550525 \tabularnewline
14 & 0.945268 & 0.109464 & 0.0547321 \tabularnewline
15 & 0.970682 & 0.0586362 & 0.0293181 \tabularnewline
16 & 0.955252 & 0.0894969 & 0.0447485 \tabularnewline
17 & 0.938628 & 0.122743 & 0.0613716 \tabularnewline
18 & 0.93561 & 0.128779 & 0.0643897 \tabularnewline
19 & 0.922594 & 0.154811 & 0.0774057 \tabularnewline
20 & 0.902277 & 0.195446 & 0.0977232 \tabularnewline
21 & 0.908415 & 0.18317 & 0.091585 \tabularnewline
22 & 0.945595 & 0.10881 & 0.054405 \tabularnewline
23 & 0.930882 & 0.138235 & 0.0691177 \tabularnewline
24 & 0.921711 & 0.156577 & 0.0782886 \tabularnewline
25 & 0.898601 & 0.202799 & 0.101399 \tabularnewline
26 & 0.997909 & 0.00418273 & 0.00209136 \tabularnewline
27 & 0.996958 & 0.00608478 & 0.00304239 \tabularnewline
28 & 0.995386 & 0.00922854 & 0.00461427 \tabularnewline
29 & 0.993369 & 0.013262 & 0.00663101 \tabularnewline
30 & 0.996512 & 0.00697521 & 0.0034876 \tabularnewline
31 & 0.994851 & 0.0102977 & 0.00514887 \tabularnewline
32 & 0.992851 & 0.0142988 & 0.0071494 \tabularnewline
33 & 0.991276 & 0.0174482 & 0.0087241 \tabularnewline
34 & 0.987608 & 0.0247841 & 0.0123921 \tabularnewline
35 & 0.983534 & 0.0329325 & 0.0164663 \tabularnewline
36 & 0.977519 & 0.0449629 & 0.0224815 \tabularnewline
37 & 0.982576 & 0.0348476 & 0.0174238 \tabularnewline
38 & 0.976567 & 0.0468659 & 0.0234329 \tabularnewline
39 & 0.974318 & 0.0513638 & 0.0256819 \tabularnewline
40 & 0.975482 & 0.0490353 & 0.0245176 \tabularnewline
41 & 0.968455 & 0.0630895 & 0.0315448 \tabularnewline
42 & 0.967554 & 0.0648918 & 0.0324459 \tabularnewline
43 & 0.958262 & 0.0834768 & 0.0417384 \tabularnewline
44 & 0.955647 & 0.088705 & 0.0443525 \tabularnewline
45 & 0.943597 & 0.112806 & 0.056403 \tabularnewline
46 & 0.953938 & 0.0921247 & 0.0460623 \tabularnewline
47 & 0.941606 & 0.116787 & 0.0583935 \tabularnewline
48 & 0.926935 & 0.14613 & 0.0730648 \tabularnewline
49 & 0.948157 & 0.103685 & 0.0518427 \tabularnewline
50 & 0.943159 & 0.113682 & 0.0568411 \tabularnewline
51 & 0.93082 & 0.138359 & 0.0691796 \tabularnewline
52 & 0.915181 & 0.169639 & 0.0848193 \tabularnewline
53 & 0.902409 & 0.195183 & 0.0975913 \tabularnewline
54 & 0.899625 & 0.20075 & 0.100375 \tabularnewline
55 & 0.895089 & 0.209822 & 0.104911 \tabularnewline
56 & 0.884274 & 0.231451 & 0.115726 \tabularnewline
57 & 0.876516 & 0.246967 & 0.123484 \tabularnewline
58 & 0.854201 & 0.291597 & 0.145799 \tabularnewline
59 & 0.879797 & 0.240406 & 0.120203 \tabularnewline
60 & 0.872841 & 0.254318 & 0.127159 \tabularnewline
61 & 0.899272 & 0.201455 & 0.100728 \tabularnewline
62 & 0.891007 & 0.217986 & 0.108993 \tabularnewline
63 & 0.92073 & 0.15854 & 0.0792699 \tabularnewline
64 & 0.905747 & 0.188505 & 0.0942527 \tabularnewline
65 & 0.890806 & 0.218388 & 0.109194 \tabularnewline
66 & 0.954016 & 0.0919681 & 0.0459841 \tabularnewline
67 & 0.952645 & 0.0947103 & 0.0473551 \tabularnewline
68 & 0.956643 & 0.086713 & 0.0433565 \tabularnewline
69 & 0.950111 & 0.0997779 & 0.049889 \tabularnewline
70 & 0.943209 & 0.113583 & 0.0567914 \tabularnewline
71 & 0.931419 & 0.137162 & 0.0685811 \tabularnewline
72 & 0.942207 & 0.115586 & 0.057793 \tabularnewline
73 & 0.93106 & 0.137879 & 0.0689397 \tabularnewline
74 & 0.918126 & 0.163749 & 0.0818745 \tabularnewline
75 & 0.909805 & 0.180391 & 0.0901954 \tabularnewline
76 & 0.893152 & 0.213696 & 0.106848 \tabularnewline
77 & 0.906984 & 0.186032 & 0.0930158 \tabularnewline
78 & 0.890812 & 0.218376 & 0.109188 \tabularnewline
79 & 0.8829 & 0.234201 & 0.1171 \tabularnewline
80 & 0.88417 & 0.231659 & 0.11583 \tabularnewline
81 & 0.864435 & 0.27113 & 0.135565 \tabularnewline
82 & 0.844029 & 0.311943 & 0.155971 \tabularnewline
83 & 0.836939 & 0.326122 & 0.163061 \tabularnewline
84 & 0.815612 & 0.368775 & 0.184388 \tabularnewline
85 & 0.78911 & 0.42178 & 0.21089 \tabularnewline
86 & 0.765502 & 0.468996 & 0.234498 \tabularnewline
87 & 0.736197 & 0.527606 & 0.263803 \tabularnewline
88 & 0.704501 & 0.590999 & 0.295499 \tabularnewline
89 & 0.770433 & 0.459133 & 0.229567 \tabularnewline
90 & 0.810583 & 0.378835 & 0.189417 \tabularnewline
91 & 0.784334 & 0.431332 & 0.215666 \tabularnewline
92 & 0.760045 & 0.479909 & 0.239955 \tabularnewline
93 & 0.740849 & 0.518301 & 0.259151 \tabularnewline
94 & 0.712381 & 0.575238 & 0.287619 \tabularnewline
95 & 0.687475 & 0.625051 & 0.312525 \tabularnewline
96 & 0.661234 & 0.677532 & 0.338766 \tabularnewline
97 & 0.631197 & 0.737607 & 0.368803 \tabularnewline
98 & 0.63698 & 0.726041 & 0.36302 \tabularnewline
99 & 0.602364 & 0.795272 & 0.397636 \tabularnewline
100 & 0.593957 & 0.812087 & 0.406043 \tabularnewline
101 & 0.567271 & 0.865459 & 0.432729 \tabularnewline
102 & 0.542944 & 0.914112 & 0.457056 \tabularnewline
103 & 0.601768 & 0.796465 & 0.398232 \tabularnewline
104 & 0.598234 & 0.803532 & 0.401766 \tabularnewline
105 & 0.610906 & 0.778187 & 0.389094 \tabularnewline
106 & 0.584513 & 0.830975 & 0.415487 \tabularnewline
107 & 0.577665 & 0.844669 & 0.422335 \tabularnewline
108 & 0.637957 & 0.724087 & 0.362043 \tabularnewline
109 & 0.612359 & 0.775282 & 0.387641 \tabularnewline
110 & 0.595949 & 0.808101 & 0.404051 \tabularnewline
111 & 0.59529 & 0.80942 & 0.40471 \tabularnewline
112 & 0.605476 & 0.789049 & 0.394524 \tabularnewline
113 & 0.58273 & 0.83454 & 0.41727 \tabularnewline
114 & 0.675801 & 0.648399 & 0.324199 \tabularnewline
115 & 0.647497 & 0.705006 & 0.352503 \tabularnewline
116 & 0.619045 & 0.761909 & 0.380955 \tabularnewline
117 & 0.588655 & 0.822691 & 0.411345 \tabularnewline
118 & 0.56746 & 0.865081 & 0.43254 \tabularnewline
119 & 0.536728 & 0.926543 & 0.463272 \tabularnewline
120 & 0.51058 & 0.978839 & 0.48942 \tabularnewline
121 & 0.481583 & 0.963167 & 0.518417 \tabularnewline
122 & 0.449788 & 0.899575 & 0.550212 \tabularnewline
123 & 0.423699 & 0.847399 & 0.576301 \tabularnewline
124 & 0.390785 & 0.781571 & 0.609215 \tabularnewline
125 & 0.375684 & 0.751368 & 0.624316 \tabularnewline
126 & 0.35151 & 0.70302 & 0.64849 \tabularnewline
127 & 0.336346 & 0.672692 & 0.663654 \tabularnewline
128 & 0.456471 & 0.912942 & 0.543529 \tabularnewline
129 & 0.440364 & 0.880727 & 0.559636 \tabularnewline
130 & 0.429769 & 0.859539 & 0.570231 \tabularnewline
131 & 0.411089 & 0.822179 & 0.588911 \tabularnewline
132 & 0.381486 & 0.762973 & 0.618514 \tabularnewline
133 & 0.399644 & 0.799288 & 0.600356 \tabularnewline
134 & 0.373032 & 0.746064 & 0.626968 \tabularnewline
135 & 0.401825 & 0.80365 & 0.598175 \tabularnewline
136 & 0.386229 & 0.772457 & 0.613771 \tabularnewline
137 & 0.355893 & 0.711786 & 0.644107 \tabularnewline
138 & 0.336574 & 0.673147 & 0.663426 \tabularnewline
139 & 0.30844 & 0.61688 & 0.69156 \tabularnewline
140 & 0.283474 & 0.566948 & 0.716526 \tabularnewline
141 & 0.254484 & 0.508969 & 0.745516 \tabularnewline
142 & 0.273825 & 0.547651 & 0.726175 \tabularnewline
143 & 0.245104 & 0.490208 & 0.754896 \tabularnewline
144 & 0.223748 & 0.447496 & 0.776252 \tabularnewline
145 & 0.217866 & 0.435732 & 0.782134 \tabularnewline
146 & 0.210419 & 0.420838 & 0.789581 \tabularnewline
147 & 0.227475 & 0.454951 & 0.772525 \tabularnewline
148 & 0.243611 & 0.487223 & 0.756389 \tabularnewline
149 & 0.253175 & 0.50635 & 0.746825 \tabularnewline
150 & 0.26204 & 0.524081 & 0.73796 \tabularnewline
151 & 0.23831 & 0.47662 & 0.76169 \tabularnewline
152 & 0.215275 & 0.43055 & 0.784725 \tabularnewline
153 & 0.227819 & 0.455638 & 0.772181 \tabularnewline
154 & 0.241069 & 0.482138 & 0.758931 \tabularnewline
155 & 0.232307 & 0.464613 & 0.767693 \tabularnewline
156 & 0.205727 & 0.411453 & 0.794273 \tabularnewline
157 & 0.186264 & 0.372528 & 0.813736 \tabularnewline
158 & 0.298177 & 0.596355 & 0.701823 \tabularnewline
159 & 0.310549 & 0.621098 & 0.689451 \tabularnewline
160 & 0.285724 & 0.571448 & 0.714276 \tabularnewline
161 & 0.261169 & 0.522338 & 0.738831 \tabularnewline
162 & 0.235758 & 0.471516 & 0.764242 \tabularnewline
163 & 0.213056 & 0.426112 & 0.786944 \tabularnewline
164 & 0.350198 & 0.700397 & 0.649802 \tabularnewline
165 & 0.342092 & 0.684185 & 0.657908 \tabularnewline
166 & 0.337036 & 0.674071 & 0.662964 \tabularnewline
167 & 0.304322 & 0.608644 & 0.695678 \tabularnewline
168 & 0.27831 & 0.556619 & 0.72169 \tabularnewline
169 & 0.328354 & 0.656708 & 0.671646 \tabularnewline
170 & 0.353844 & 0.707688 & 0.646156 \tabularnewline
171 & 0.324073 & 0.648146 & 0.675927 \tabularnewline
172 & 0.318825 & 0.637649 & 0.681175 \tabularnewline
173 & 0.486741 & 0.973483 & 0.513259 \tabularnewline
174 & 0.469682 & 0.939365 & 0.530318 \tabularnewline
175 & 0.493732 & 0.987465 & 0.506268 \tabularnewline
176 & 0.504405 & 0.99119 & 0.495595 \tabularnewline
177 & 0.560162 & 0.879676 & 0.439838 \tabularnewline
178 & 0.527382 & 0.945237 & 0.472618 \tabularnewline
179 & 0.503148 & 0.993704 & 0.496852 \tabularnewline
180 & 0.503591 & 0.992818 & 0.496409 \tabularnewline
181 & 0.468875 & 0.93775 & 0.531125 \tabularnewline
182 & 0.465092 & 0.930183 & 0.534908 \tabularnewline
183 & 0.426789 & 0.853578 & 0.573211 \tabularnewline
184 & 0.397419 & 0.794837 & 0.602581 \tabularnewline
185 & 0.425716 & 0.851431 & 0.574284 \tabularnewline
186 & 0.418036 & 0.836073 & 0.581964 \tabularnewline
187 & 0.38119 & 0.762381 & 0.61881 \tabularnewline
188 & 0.351446 & 0.702891 & 0.648554 \tabularnewline
189 & 0.316651 & 0.633302 & 0.683349 \tabularnewline
190 & 0.293049 & 0.586097 & 0.706951 \tabularnewline
191 & 0.307619 & 0.615237 & 0.692381 \tabularnewline
192 & 0.285299 & 0.570598 & 0.714701 \tabularnewline
193 & 0.305706 & 0.611413 & 0.694294 \tabularnewline
194 & 0.292193 & 0.584387 & 0.707807 \tabularnewline
195 & 0.291052 & 0.582104 & 0.708948 \tabularnewline
196 & 0.301251 & 0.602502 & 0.698749 \tabularnewline
197 & 0.338159 & 0.676319 & 0.661841 \tabularnewline
198 & 0.309763 & 0.619526 & 0.690237 \tabularnewline
199 & 0.346577 & 0.693155 & 0.653423 \tabularnewline
200 & 0.312431 & 0.624861 & 0.687569 \tabularnewline
201 & 0.358282 & 0.716564 & 0.641718 \tabularnewline
202 & 0.333544 & 0.667087 & 0.666456 \tabularnewline
203 & 0.377039 & 0.754078 & 0.622961 \tabularnewline
204 & 0.337008 & 0.674016 & 0.662992 \tabularnewline
205 & 0.301523 & 0.603046 & 0.698477 \tabularnewline
206 & 0.278189 & 0.556378 & 0.721811 \tabularnewline
207 & 0.243407 & 0.486814 & 0.756593 \tabularnewline
208 & 0.281861 & 0.563722 & 0.718139 \tabularnewline
209 & 0.246535 & 0.493071 & 0.753465 \tabularnewline
210 & 0.245336 & 0.490673 & 0.754664 \tabularnewline
211 & 0.269993 & 0.539987 & 0.730007 \tabularnewline
212 & 0.258276 & 0.516551 & 0.741724 \tabularnewline
213 & 0.224593 & 0.449187 & 0.775407 \tabularnewline
214 & 0.285988 & 0.571976 & 0.714012 \tabularnewline
215 & 0.259014 & 0.518028 & 0.740986 \tabularnewline
216 & 0.244958 & 0.489916 & 0.755042 \tabularnewline
217 & 0.259467 & 0.518934 & 0.740533 \tabularnewline
218 & 0.222878 & 0.445756 & 0.777122 \tabularnewline
219 & 0.212461 & 0.424921 & 0.787539 \tabularnewline
220 & 0.208258 & 0.416517 & 0.791742 \tabularnewline
221 & 0.229153 & 0.458306 & 0.770847 \tabularnewline
222 & 0.236822 & 0.473644 & 0.763178 \tabularnewline
223 & 0.230981 & 0.461963 & 0.769019 \tabularnewline
224 & 0.196736 & 0.393472 & 0.803264 \tabularnewline
225 & 0.17225 & 0.344501 & 0.82775 \tabularnewline
226 & 0.199556 & 0.399112 & 0.800444 \tabularnewline
227 & 0.464494 & 0.928988 & 0.535506 \tabularnewline
228 & 0.430781 & 0.861562 & 0.569219 \tabularnewline
229 & 0.409345 & 0.81869 & 0.590655 \tabularnewline
230 & 0.391084 & 0.782169 & 0.608916 \tabularnewline
231 & 0.345673 & 0.691346 & 0.654327 \tabularnewline
232 & 0.380554 & 0.761108 & 0.619446 \tabularnewline
233 & 0.351035 & 0.70207 & 0.648965 \tabularnewline
234 & 0.299751 & 0.599502 & 0.700249 \tabularnewline
235 & 0.304275 & 0.608549 & 0.695725 \tabularnewline
236 & 0.280971 & 0.561942 & 0.719029 \tabularnewline
237 & 0.236231 & 0.472461 & 0.763769 \tabularnewline
238 & 0.190191 & 0.380382 & 0.809809 \tabularnewline
239 & 0.328676 & 0.657353 & 0.671324 \tabularnewline
240 & 0.318578 & 0.637155 & 0.681422 \tabularnewline
241 & 0.301567 & 0.603134 & 0.698433 \tabularnewline
242 & 0.462477 & 0.924953 & 0.537523 \tabularnewline
243 & 0.453673 & 0.907345 & 0.546327 \tabularnewline
244 & 0.405703 & 0.811406 & 0.594297 \tabularnewline
245 & 0.409634 & 0.819268 & 0.590366 \tabularnewline
246 & 0.331709 & 0.663418 & 0.668291 \tabularnewline
247 & 0.264413 & 0.528826 & 0.735587 \tabularnewline
248 & 0.593398 & 0.813204 & 0.406602 \tabularnewline
249 & 0.496559 & 0.993118 & 0.503441 \tabularnewline
250 & 0.397628 & 0.795256 & 0.602372 \tabularnewline
251 & 0.564739 & 0.870522 & 0.435261 \tabularnewline
252 & 0.917529 & 0.164941 & 0.0824707 \tabularnewline
253 & 0.851269 & 0.297462 & 0.148731 \tabularnewline
254 & 0.79499 & 0.410019 & 0.20501 \tabularnewline
255 & 0.696229 & 0.607543 & 0.303771 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221845&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]9[/C][C]0.564454[/C][C]0.871092[/C][C]0.435546[/C][/ROW]
[ROW][C]10[/C][C]0.612153[/C][C]0.775695[/C][C]0.387847[/C][/ROW]
[ROW][C]11[/C][C]0.508921[/C][C]0.982157[/C][C]0.491079[/C][/ROW]
[ROW][C]12[/C][C]0.763909[/C][C]0.472181[/C][C]0.236091[/C][/ROW]
[ROW][C]13[/C][C]0.944948[/C][C]0.110105[/C][C]0.0550525[/C][/ROW]
[ROW][C]14[/C][C]0.945268[/C][C]0.109464[/C][C]0.0547321[/C][/ROW]
[ROW][C]15[/C][C]0.970682[/C][C]0.0586362[/C][C]0.0293181[/C][/ROW]
[ROW][C]16[/C][C]0.955252[/C][C]0.0894969[/C][C]0.0447485[/C][/ROW]
[ROW][C]17[/C][C]0.938628[/C][C]0.122743[/C][C]0.0613716[/C][/ROW]
[ROW][C]18[/C][C]0.93561[/C][C]0.128779[/C][C]0.0643897[/C][/ROW]
[ROW][C]19[/C][C]0.922594[/C][C]0.154811[/C][C]0.0774057[/C][/ROW]
[ROW][C]20[/C][C]0.902277[/C][C]0.195446[/C][C]0.0977232[/C][/ROW]
[ROW][C]21[/C][C]0.908415[/C][C]0.18317[/C][C]0.091585[/C][/ROW]
[ROW][C]22[/C][C]0.945595[/C][C]0.10881[/C][C]0.054405[/C][/ROW]
[ROW][C]23[/C][C]0.930882[/C][C]0.138235[/C][C]0.0691177[/C][/ROW]
[ROW][C]24[/C][C]0.921711[/C][C]0.156577[/C][C]0.0782886[/C][/ROW]
[ROW][C]25[/C][C]0.898601[/C][C]0.202799[/C][C]0.101399[/C][/ROW]
[ROW][C]26[/C][C]0.997909[/C][C]0.00418273[/C][C]0.00209136[/C][/ROW]
[ROW][C]27[/C][C]0.996958[/C][C]0.00608478[/C][C]0.00304239[/C][/ROW]
[ROW][C]28[/C][C]0.995386[/C][C]0.00922854[/C][C]0.00461427[/C][/ROW]
[ROW][C]29[/C][C]0.993369[/C][C]0.013262[/C][C]0.00663101[/C][/ROW]
[ROW][C]30[/C][C]0.996512[/C][C]0.00697521[/C][C]0.0034876[/C][/ROW]
[ROW][C]31[/C][C]0.994851[/C][C]0.0102977[/C][C]0.00514887[/C][/ROW]
[ROW][C]32[/C][C]0.992851[/C][C]0.0142988[/C][C]0.0071494[/C][/ROW]
[ROW][C]33[/C][C]0.991276[/C][C]0.0174482[/C][C]0.0087241[/C][/ROW]
[ROW][C]34[/C][C]0.987608[/C][C]0.0247841[/C][C]0.0123921[/C][/ROW]
[ROW][C]35[/C][C]0.983534[/C][C]0.0329325[/C][C]0.0164663[/C][/ROW]
[ROW][C]36[/C][C]0.977519[/C][C]0.0449629[/C][C]0.0224815[/C][/ROW]
[ROW][C]37[/C][C]0.982576[/C][C]0.0348476[/C][C]0.0174238[/C][/ROW]
[ROW][C]38[/C][C]0.976567[/C][C]0.0468659[/C][C]0.0234329[/C][/ROW]
[ROW][C]39[/C][C]0.974318[/C][C]0.0513638[/C][C]0.0256819[/C][/ROW]
[ROW][C]40[/C][C]0.975482[/C][C]0.0490353[/C][C]0.0245176[/C][/ROW]
[ROW][C]41[/C][C]0.968455[/C][C]0.0630895[/C][C]0.0315448[/C][/ROW]
[ROW][C]42[/C][C]0.967554[/C][C]0.0648918[/C][C]0.0324459[/C][/ROW]
[ROW][C]43[/C][C]0.958262[/C][C]0.0834768[/C][C]0.0417384[/C][/ROW]
[ROW][C]44[/C][C]0.955647[/C][C]0.088705[/C][C]0.0443525[/C][/ROW]
[ROW][C]45[/C][C]0.943597[/C][C]0.112806[/C][C]0.056403[/C][/ROW]
[ROW][C]46[/C][C]0.953938[/C][C]0.0921247[/C][C]0.0460623[/C][/ROW]
[ROW][C]47[/C][C]0.941606[/C][C]0.116787[/C][C]0.0583935[/C][/ROW]
[ROW][C]48[/C][C]0.926935[/C][C]0.14613[/C][C]0.0730648[/C][/ROW]
[ROW][C]49[/C][C]0.948157[/C][C]0.103685[/C][C]0.0518427[/C][/ROW]
[ROW][C]50[/C][C]0.943159[/C][C]0.113682[/C][C]0.0568411[/C][/ROW]
[ROW][C]51[/C][C]0.93082[/C][C]0.138359[/C][C]0.0691796[/C][/ROW]
[ROW][C]52[/C][C]0.915181[/C][C]0.169639[/C][C]0.0848193[/C][/ROW]
[ROW][C]53[/C][C]0.902409[/C][C]0.195183[/C][C]0.0975913[/C][/ROW]
[ROW][C]54[/C][C]0.899625[/C][C]0.20075[/C][C]0.100375[/C][/ROW]
[ROW][C]55[/C][C]0.895089[/C][C]0.209822[/C][C]0.104911[/C][/ROW]
[ROW][C]56[/C][C]0.884274[/C][C]0.231451[/C][C]0.115726[/C][/ROW]
[ROW][C]57[/C][C]0.876516[/C][C]0.246967[/C][C]0.123484[/C][/ROW]
[ROW][C]58[/C][C]0.854201[/C][C]0.291597[/C][C]0.145799[/C][/ROW]
[ROW][C]59[/C][C]0.879797[/C][C]0.240406[/C][C]0.120203[/C][/ROW]
[ROW][C]60[/C][C]0.872841[/C][C]0.254318[/C][C]0.127159[/C][/ROW]
[ROW][C]61[/C][C]0.899272[/C][C]0.201455[/C][C]0.100728[/C][/ROW]
[ROW][C]62[/C][C]0.891007[/C][C]0.217986[/C][C]0.108993[/C][/ROW]
[ROW][C]63[/C][C]0.92073[/C][C]0.15854[/C][C]0.0792699[/C][/ROW]
[ROW][C]64[/C][C]0.905747[/C][C]0.188505[/C][C]0.0942527[/C][/ROW]
[ROW][C]65[/C][C]0.890806[/C][C]0.218388[/C][C]0.109194[/C][/ROW]
[ROW][C]66[/C][C]0.954016[/C][C]0.0919681[/C][C]0.0459841[/C][/ROW]
[ROW][C]67[/C][C]0.952645[/C][C]0.0947103[/C][C]0.0473551[/C][/ROW]
[ROW][C]68[/C][C]0.956643[/C][C]0.086713[/C][C]0.0433565[/C][/ROW]
[ROW][C]69[/C][C]0.950111[/C][C]0.0997779[/C][C]0.049889[/C][/ROW]
[ROW][C]70[/C][C]0.943209[/C][C]0.113583[/C][C]0.0567914[/C][/ROW]
[ROW][C]71[/C][C]0.931419[/C][C]0.137162[/C][C]0.0685811[/C][/ROW]
[ROW][C]72[/C][C]0.942207[/C][C]0.115586[/C][C]0.057793[/C][/ROW]
[ROW][C]73[/C][C]0.93106[/C][C]0.137879[/C][C]0.0689397[/C][/ROW]
[ROW][C]74[/C][C]0.918126[/C][C]0.163749[/C][C]0.0818745[/C][/ROW]
[ROW][C]75[/C][C]0.909805[/C][C]0.180391[/C][C]0.0901954[/C][/ROW]
[ROW][C]76[/C][C]0.893152[/C][C]0.213696[/C][C]0.106848[/C][/ROW]
[ROW][C]77[/C][C]0.906984[/C][C]0.186032[/C][C]0.0930158[/C][/ROW]
[ROW][C]78[/C][C]0.890812[/C][C]0.218376[/C][C]0.109188[/C][/ROW]
[ROW][C]79[/C][C]0.8829[/C][C]0.234201[/C][C]0.1171[/C][/ROW]
[ROW][C]80[/C][C]0.88417[/C][C]0.231659[/C][C]0.11583[/C][/ROW]
[ROW][C]81[/C][C]0.864435[/C][C]0.27113[/C][C]0.135565[/C][/ROW]
[ROW][C]82[/C][C]0.844029[/C][C]0.311943[/C][C]0.155971[/C][/ROW]
[ROW][C]83[/C][C]0.836939[/C][C]0.326122[/C][C]0.163061[/C][/ROW]
[ROW][C]84[/C][C]0.815612[/C][C]0.368775[/C][C]0.184388[/C][/ROW]
[ROW][C]85[/C][C]0.78911[/C][C]0.42178[/C][C]0.21089[/C][/ROW]
[ROW][C]86[/C][C]0.765502[/C][C]0.468996[/C][C]0.234498[/C][/ROW]
[ROW][C]87[/C][C]0.736197[/C][C]0.527606[/C][C]0.263803[/C][/ROW]
[ROW][C]88[/C][C]0.704501[/C][C]0.590999[/C][C]0.295499[/C][/ROW]
[ROW][C]89[/C][C]0.770433[/C][C]0.459133[/C][C]0.229567[/C][/ROW]
[ROW][C]90[/C][C]0.810583[/C][C]0.378835[/C][C]0.189417[/C][/ROW]
[ROW][C]91[/C][C]0.784334[/C][C]0.431332[/C][C]0.215666[/C][/ROW]
[ROW][C]92[/C][C]0.760045[/C][C]0.479909[/C][C]0.239955[/C][/ROW]
[ROW][C]93[/C][C]0.740849[/C][C]0.518301[/C][C]0.259151[/C][/ROW]
[ROW][C]94[/C][C]0.712381[/C][C]0.575238[/C][C]0.287619[/C][/ROW]
[ROW][C]95[/C][C]0.687475[/C][C]0.625051[/C][C]0.312525[/C][/ROW]
[ROW][C]96[/C][C]0.661234[/C][C]0.677532[/C][C]0.338766[/C][/ROW]
[ROW][C]97[/C][C]0.631197[/C][C]0.737607[/C][C]0.368803[/C][/ROW]
[ROW][C]98[/C][C]0.63698[/C][C]0.726041[/C][C]0.36302[/C][/ROW]
[ROW][C]99[/C][C]0.602364[/C][C]0.795272[/C][C]0.397636[/C][/ROW]
[ROW][C]100[/C][C]0.593957[/C][C]0.812087[/C][C]0.406043[/C][/ROW]
[ROW][C]101[/C][C]0.567271[/C][C]0.865459[/C][C]0.432729[/C][/ROW]
[ROW][C]102[/C][C]0.542944[/C][C]0.914112[/C][C]0.457056[/C][/ROW]
[ROW][C]103[/C][C]0.601768[/C][C]0.796465[/C][C]0.398232[/C][/ROW]
[ROW][C]104[/C][C]0.598234[/C][C]0.803532[/C][C]0.401766[/C][/ROW]
[ROW][C]105[/C][C]0.610906[/C][C]0.778187[/C][C]0.389094[/C][/ROW]
[ROW][C]106[/C][C]0.584513[/C][C]0.830975[/C][C]0.415487[/C][/ROW]
[ROW][C]107[/C][C]0.577665[/C][C]0.844669[/C][C]0.422335[/C][/ROW]
[ROW][C]108[/C][C]0.637957[/C][C]0.724087[/C][C]0.362043[/C][/ROW]
[ROW][C]109[/C][C]0.612359[/C][C]0.775282[/C][C]0.387641[/C][/ROW]
[ROW][C]110[/C][C]0.595949[/C][C]0.808101[/C][C]0.404051[/C][/ROW]
[ROW][C]111[/C][C]0.59529[/C][C]0.80942[/C][C]0.40471[/C][/ROW]
[ROW][C]112[/C][C]0.605476[/C][C]0.789049[/C][C]0.394524[/C][/ROW]
[ROW][C]113[/C][C]0.58273[/C][C]0.83454[/C][C]0.41727[/C][/ROW]
[ROW][C]114[/C][C]0.675801[/C][C]0.648399[/C][C]0.324199[/C][/ROW]
[ROW][C]115[/C][C]0.647497[/C][C]0.705006[/C][C]0.352503[/C][/ROW]
[ROW][C]116[/C][C]0.619045[/C][C]0.761909[/C][C]0.380955[/C][/ROW]
[ROW][C]117[/C][C]0.588655[/C][C]0.822691[/C][C]0.411345[/C][/ROW]
[ROW][C]118[/C][C]0.56746[/C][C]0.865081[/C][C]0.43254[/C][/ROW]
[ROW][C]119[/C][C]0.536728[/C][C]0.926543[/C][C]0.463272[/C][/ROW]
[ROW][C]120[/C][C]0.51058[/C][C]0.978839[/C][C]0.48942[/C][/ROW]
[ROW][C]121[/C][C]0.481583[/C][C]0.963167[/C][C]0.518417[/C][/ROW]
[ROW][C]122[/C][C]0.449788[/C][C]0.899575[/C][C]0.550212[/C][/ROW]
[ROW][C]123[/C][C]0.423699[/C][C]0.847399[/C][C]0.576301[/C][/ROW]
[ROW][C]124[/C][C]0.390785[/C][C]0.781571[/C][C]0.609215[/C][/ROW]
[ROW][C]125[/C][C]0.375684[/C][C]0.751368[/C][C]0.624316[/C][/ROW]
[ROW][C]126[/C][C]0.35151[/C][C]0.70302[/C][C]0.64849[/C][/ROW]
[ROW][C]127[/C][C]0.336346[/C][C]0.672692[/C][C]0.663654[/C][/ROW]
[ROW][C]128[/C][C]0.456471[/C][C]0.912942[/C][C]0.543529[/C][/ROW]
[ROW][C]129[/C][C]0.440364[/C][C]0.880727[/C][C]0.559636[/C][/ROW]
[ROW][C]130[/C][C]0.429769[/C][C]0.859539[/C][C]0.570231[/C][/ROW]
[ROW][C]131[/C][C]0.411089[/C][C]0.822179[/C][C]0.588911[/C][/ROW]
[ROW][C]132[/C][C]0.381486[/C][C]0.762973[/C][C]0.618514[/C][/ROW]
[ROW][C]133[/C][C]0.399644[/C][C]0.799288[/C][C]0.600356[/C][/ROW]
[ROW][C]134[/C][C]0.373032[/C][C]0.746064[/C][C]0.626968[/C][/ROW]
[ROW][C]135[/C][C]0.401825[/C][C]0.80365[/C][C]0.598175[/C][/ROW]
[ROW][C]136[/C][C]0.386229[/C][C]0.772457[/C][C]0.613771[/C][/ROW]
[ROW][C]137[/C][C]0.355893[/C][C]0.711786[/C][C]0.644107[/C][/ROW]
[ROW][C]138[/C][C]0.336574[/C][C]0.673147[/C][C]0.663426[/C][/ROW]
[ROW][C]139[/C][C]0.30844[/C][C]0.61688[/C][C]0.69156[/C][/ROW]
[ROW][C]140[/C][C]0.283474[/C][C]0.566948[/C][C]0.716526[/C][/ROW]
[ROW][C]141[/C][C]0.254484[/C][C]0.508969[/C][C]0.745516[/C][/ROW]
[ROW][C]142[/C][C]0.273825[/C][C]0.547651[/C][C]0.726175[/C][/ROW]
[ROW][C]143[/C][C]0.245104[/C][C]0.490208[/C][C]0.754896[/C][/ROW]
[ROW][C]144[/C][C]0.223748[/C][C]0.447496[/C][C]0.776252[/C][/ROW]
[ROW][C]145[/C][C]0.217866[/C][C]0.435732[/C][C]0.782134[/C][/ROW]
[ROW][C]146[/C][C]0.210419[/C][C]0.420838[/C][C]0.789581[/C][/ROW]
[ROW][C]147[/C][C]0.227475[/C][C]0.454951[/C][C]0.772525[/C][/ROW]
[ROW][C]148[/C][C]0.243611[/C][C]0.487223[/C][C]0.756389[/C][/ROW]
[ROW][C]149[/C][C]0.253175[/C][C]0.50635[/C][C]0.746825[/C][/ROW]
[ROW][C]150[/C][C]0.26204[/C][C]0.524081[/C][C]0.73796[/C][/ROW]
[ROW][C]151[/C][C]0.23831[/C][C]0.47662[/C][C]0.76169[/C][/ROW]
[ROW][C]152[/C][C]0.215275[/C][C]0.43055[/C][C]0.784725[/C][/ROW]
[ROW][C]153[/C][C]0.227819[/C][C]0.455638[/C][C]0.772181[/C][/ROW]
[ROW][C]154[/C][C]0.241069[/C][C]0.482138[/C][C]0.758931[/C][/ROW]
[ROW][C]155[/C][C]0.232307[/C][C]0.464613[/C][C]0.767693[/C][/ROW]
[ROW][C]156[/C][C]0.205727[/C][C]0.411453[/C][C]0.794273[/C][/ROW]
[ROW][C]157[/C][C]0.186264[/C][C]0.372528[/C][C]0.813736[/C][/ROW]
[ROW][C]158[/C][C]0.298177[/C][C]0.596355[/C][C]0.701823[/C][/ROW]
[ROW][C]159[/C][C]0.310549[/C][C]0.621098[/C][C]0.689451[/C][/ROW]
[ROW][C]160[/C][C]0.285724[/C][C]0.571448[/C][C]0.714276[/C][/ROW]
[ROW][C]161[/C][C]0.261169[/C][C]0.522338[/C][C]0.738831[/C][/ROW]
[ROW][C]162[/C][C]0.235758[/C][C]0.471516[/C][C]0.764242[/C][/ROW]
[ROW][C]163[/C][C]0.213056[/C][C]0.426112[/C][C]0.786944[/C][/ROW]
[ROW][C]164[/C][C]0.350198[/C][C]0.700397[/C][C]0.649802[/C][/ROW]
[ROW][C]165[/C][C]0.342092[/C][C]0.684185[/C][C]0.657908[/C][/ROW]
[ROW][C]166[/C][C]0.337036[/C][C]0.674071[/C][C]0.662964[/C][/ROW]
[ROW][C]167[/C][C]0.304322[/C][C]0.608644[/C][C]0.695678[/C][/ROW]
[ROW][C]168[/C][C]0.27831[/C][C]0.556619[/C][C]0.72169[/C][/ROW]
[ROW][C]169[/C][C]0.328354[/C][C]0.656708[/C][C]0.671646[/C][/ROW]
[ROW][C]170[/C][C]0.353844[/C][C]0.707688[/C][C]0.646156[/C][/ROW]
[ROW][C]171[/C][C]0.324073[/C][C]0.648146[/C][C]0.675927[/C][/ROW]
[ROW][C]172[/C][C]0.318825[/C][C]0.637649[/C][C]0.681175[/C][/ROW]
[ROW][C]173[/C][C]0.486741[/C][C]0.973483[/C][C]0.513259[/C][/ROW]
[ROW][C]174[/C][C]0.469682[/C][C]0.939365[/C][C]0.530318[/C][/ROW]
[ROW][C]175[/C][C]0.493732[/C][C]0.987465[/C][C]0.506268[/C][/ROW]
[ROW][C]176[/C][C]0.504405[/C][C]0.99119[/C][C]0.495595[/C][/ROW]
[ROW][C]177[/C][C]0.560162[/C][C]0.879676[/C][C]0.439838[/C][/ROW]
[ROW][C]178[/C][C]0.527382[/C][C]0.945237[/C][C]0.472618[/C][/ROW]
[ROW][C]179[/C][C]0.503148[/C][C]0.993704[/C][C]0.496852[/C][/ROW]
[ROW][C]180[/C][C]0.503591[/C][C]0.992818[/C][C]0.496409[/C][/ROW]
[ROW][C]181[/C][C]0.468875[/C][C]0.93775[/C][C]0.531125[/C][/ROW]
[ROW][C]182[/C][C]0.465092[/C][C]0.930183[/C][C]0.534908[/C][/ROW]
[ROW][C]183[/C][C]0.426789[/C][C]0.853578[/C][C]0.573211[/C][/ROW]
[ROW][C]184[/C][C]0.397419[/C][C]0.794837[/C][C]0.602581[/C][/ROW]
[ROW][C]185[/C][C]0.425716[/C][C]0.851431[/C][C]0.574284[/C][/ROW]
[ROW][C]186[/C][C]0.418036[/C][C]0.836073[/C][C]0.581964[/C][/ROW]
[ROW][C]187[/C][C]0.38119[/C][C]0.762381[/C][C]0.61881[/C][/ROW]
[ROW][C]188[/C][C]0.351446[/C][C]0.702891[/C][C]0.648554[/C][/ROW]
[ROW][C]189[/C][C]0.316651[/C][C]0.633302[/C][C]0.683349[/C][/ROW]
[ROW][C]190[/C][C]0.293049[/C][C]0.586097[/C][C]0.706951[/C][/ROW]
[ROW][C]191[/C][C]0.307619[/C][C]0.615237[/C][C]0.692381[/C][/ROW]
[ROW][C]192[/C][C]0.285299[/C][C]0.570598[/C][C]0.714701[/C][/ROW]
[ROW][C]193[/C][C]0.305706[/C][C]0.611413[/C][C]0.694294[/C][/ROW]
[ROW][C]194[/C][C]0.292193[/C][C]0.584387[/C][C]0.707807[/C][/ROW]
[ROW][C]195[/C][C]0.291052[/C][C]0.582104[/C][C]0.708948[/C][/ROW]
[ROW][C]196[/C][C]0.301251[/C][C]0.602502[/C][C]0.698749[/C][/ROW]
[ROW][C]197[/C][C]0.338159[/C][C]0.676319[/C][C]0.661841[/C][/ROW]
[ROW][C]198[/C][C]0.309763[/C][C]0.619526[/C][C]0.690237[/C][/ROW]
[ROW][C]199[/C][C]0.346577[/C][C]0.693155[/C][C]0.653423[/C][/ROW]
[ROW][C]200[/C][C]0.312431[/C][C]0.624861[/C][C]0.687569[/C][/ROW]
[ROW][C]201[/C][C]0.358282[/C][C]0.716564[/C][C]0.641718[/C][/ROW]
[ROW][C]202[/C][C]0.333544[/C][C]0.667087[/C][C]0.666456[/C][/ROW]
[ROW][C]203[/C][C]0.377039[/C][C]0.754078[/C][C]0.622961[/C][/ROW]
[ROW][C]204[/C][C]0.337008[/C][C]0.674016[/C][C]0.662992[/C][/ROW]
[ROW][C]205[/C][C]0.301523[/C][C]0.603046[/C][C]0.698477[/C][/ROW]
[ROW][C]206[/C][C]0.278189[/C][C]0.556378[/C][C]0.721811[/C][/ROW]
[ROW][C]207[/C][C]0.243407[/C][C]0.486814[/C][C]0.756593[/C][/ROW]
[ROW][C]208[/C][C]0.281861[/C][C]0.563722[/C][C]0.718139[/C][/ROW]
[ROW][C]209[/C][C]0.246535[/C][C]0.493071[/C][C]0.753465[/C][/ROW]
[ROW][C]210[/C][C]0.245336[/C][C]0.490673[/C][C]0.754664[/C][/ROW]
[ROW][C]211[/C][C]0.269993[/C][C]0.539987[/C][C]0.730007[/C][/ROW]
[ROW][C]212[/C][C]0.258276[/C][C]0.516551[/C][C]0.741724[/C][/ROW]
[ROW][C]213[/C][C]0.224593[/C][C]0.449187[/C][C]0.775407[/C][/ROW]
[ROW][C]214[/C][C]0.285988[/C][C]0.571976[/C][C]0.714012[/C][/ROW]
[ROW][C]215[/C][C]0.259014[/C][C]0.518028[/C][C]0.740986[/C][/ROW]
[ROW][C]216[/C][C]0.244958[/C][C]0.489916[/C][C]0.755042[/C][/ROW]
[ROW][C]217[/C][C]0.259467[/C][C]0.518934[/C][C]0.740533[/C][/ROW]
[ROW][C]218[/C][C]0.222878[/C][C]0.445756[/C][C]0.777122[/C][/ROW]
[ROW][C]219[/C][C]0.212461[/C][C]0.424921[/C][C]0.787539[/C][/ROW]
[ROW][C]220[/C][C]0.208258[/C][C]0.416517[/C][C]0.791742[/C][/ROW]
[ROW][C]221[/C][C]0.229153[/C][C]0.458306[/C][C]0.770847[/C][/ROW]
[ROW][C]222[/C][C]0.236822[/C][C]0.473644[/C][C]0.763178[/C][/ROW]
[ROW][C]223[/C][C]0.230981[/C][C]0.461963[/C][C]0.769019[/C][/ROW]
[ROW][C]224[/C][C]0.196736[/C][C]0.393472[/C][C]0.803264[/C][/ROW]
[ROW][C]225[/C][C]0.17225[/C][C]0.344501[/C][C]0.82775[/C][/ROW]
[ROW][C]226[/C][C]0.199556[/C][C]0.399112[/C][C]0.800444[/C][/ROW]
[ROW][C]227[/C][C]0.464494[/C][C]0.928988[/C][C]0.535506[/C][/ROW]
[ROW][C]228[/C][C]0.430781[/C][C]0.861562[/C][C]0.569219[/C][/ROW]
[ROW][C]229[/C][C]0.409345[/C][C]0.81869[/C][C]0.590655[/C][/ROW]
[ROW][C]230[/C][C]0.391084[/C][C]0.782169[/C][C]0.608916[/C][/ROW]
[ROW][C]231[/C][C]0.345673[/C][C]0.691346[/C][C]0.654327[/C][/ROW]
[ROW][C]232[/C][C]0.380554[/C][C]0.761108[/C][C]0.619446[/C][/ROW]
[ROW][C]233[/C][C]0.351035[/C][C]0.70207[/C][C]0.648965[/C][/ROW]
[ROW][C]234[/C][C]0.299751[/C][C]0.599502[/C][C]0.700249[/C][/ROW]
[ROW][C]235[/C][C]0.304275[/C][C]0.608549[/C][C]0.695725[/C][/ROW]
[ROW][C]236[/C][C]0.280971[/C][C]0.561942[/C][C]0.719029[/C][/ROW]
[ROW][C]237[/C][C]0.236231[/C][C]0.472461[/C][C]0.763769[/C][/ROW]
[ROW][C]238[/C][C]0.190191[/C][C]0.380382[/C][C]0.809809[/C][/ROW]
[ROW][C]239[/C][C]0.328676[/C][C]0.657353[/C][C]0.671324[/C][/ROW]
[ROW][C]240[/C][C]0.318578[/C][C]0.637155[/C][C]0.681422[/C][/ROW]
[ROW][C]241[/C][C]0.301567[/C][C]0.603134[/C][C]0.698433[/C][/ROW]
[ROW][C]242[/C][C]0.462477[/C][C]0.924953[/C][C]0.537523[/C][/ROW]
[ROW][C]243[/C][C]0.453673[/C][C]0.907345[/C][C]0.546327[/C][/ROW]
[ROW][C]244[/C][C]0.405703[/C][C]0.811406[/C][C]0.594297[/C][/ROW]
[ROW][C]245[/C][C]0.409634[/C][C]0.819268[/C][C]0.590366[/C][/ROW]
[ROW][C]246[/C][C]0.331709[/C][C]0.663418[/C][C]0.668291[/C][/ROW]
[ROW][C]247[/C][C]0.264413[/C][C]0.528826[/C][C]0.735587[/C][/ROW]
[ROW][C]248[/C][C]0.593398[/C][C]0.813204[/C][C]0.406602[/C][/ROW]
[ROW][C]249[/C][C]0.496559[/C][C]0.993118[/C][C]0.503441[/C][/ROW]
[ROW][C]250[/C][C]0.397628[/C][C]0.795256[/C][C]0.602372[/C][/ROW]
[ROW][C]251[/C][C]0.564739[/C][C]0.870522[/C][C]0.435261[/C][/ROW]
[ROW][C]252[/C][C]0.917529[/C][C]0.164941[/C][C]0.0824707[/C][/ROW]
[ROW][C]253[/C][C]0.851269[/C][C]0.297462[/C][C]0.148731[/C][/ROW]
[ROW][C]254[/C][C]0.79499[/C][C]0.410019[/C][C]0.20501[/C][/ROW]
[ROW][C]255[/C][C]0.696229[/C][C]0.607543[/C][C]0.303771[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221845&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221845&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
90.5644540.8710920.435546
100.6121530.7756950.387847
110.5089210.9821570.491079
120.7639090.4721810.236091
130.9449480.1101050.0550525
140.9452680.1094640.0547321
150.9706820.05863620.0293181
160.9552520.08949690.0447485
170.9386280.1227430.0613716
180.935610.1287790.0643897
190.9225940.1548110.0774057
200.9022770.1954460.0977232
210.9084150.183170.091585
220.9455950.108810.054405
230.9308820.1382350.0691177
240.9217110.1565770.0782886
250.8986010.2027990.101399
260.9979090.004182730.00209136
270.9969580.006084780.00304239
280.9953860.009228540.00461427
290.9933690.0132620.00663101
300.9965120.006975210.0034876
310.9948510.01029770.00514887
320.9928510.01429880.0071494
330.9912760.01744820.0087241
340.9876080.02478410.0123921
350.9835340.03293250.0164663
360.9775190.04496290.0224815
370.9825760.03484760.0174238
380.9765670.04686590.0234329
390.9743180.05136380.0256819
400.9754820.04903530.0245176
410.9684550.06308950.0315448
420.9675540.06489180.0324459
430.9582620.08347680.0417384
440.9556470.0887050.0443525
450.9435970.1128060.056403
460.9539380.09212470.0460623
470.9416060.1167870.0583935
480.9269350.146130.0730648
490.9481570.1036850.0518427
500.9431590.1136820.0568411
510.930820.1383590.0691796
520.9151810.1696390.0848193
530.9024090.1951830.0975913
540.8996250.200750.100375
550.8950890.2098220.104911
560.8842740.2314510.115726
570.8765160.2469670.123484
580.8542010.2915970.145799
590.8797970.2404060.120203
600.8728410.2543180.127159
610.8992720.2014550.100728
620.8910070.2179860.108993
630.920730.158540.0792699
640.9057470.1885050.0942527
650.8908060.2183880.109194
660.9540160.09196810.0459841
670.9526450.09471030.0473551
680.9566430.0867130.0433565
690.9501110.09977790.049889
700.9432090.1135830.0567914
710.9314190.1371620.0685811
720.9422070.1155860.057793
730.931060.1378790.0689397
740.9181260.1637490.0818745
750.9098050.1803910.0901954
760.8931520.2136960.106848
770.9069840.1860320.0930158
780.8908120.2183760.109188
790.88290.2342010.1171
800.884170.2316590.11583
810.8644350.271130.135565
820.8440290.3119430.155971
830.8369390.3261220.163061
840.8156120.3687750.184388
850.789110.421780.21089
860.7655020.4689960.234498
870.7361970.5276060.263803
880.7045010.5909990.295499
890.7704330.4591330.229567
900.8105830.3788350.189417
910.7843340.4313320.215666
920.7600450.4799090.239955
930.7408490.5183010.259151
940.7123810.5752380.287619
950.6874750.6250510.312525
960.6612340.6775320.338766
970.6311970.7376070.368803
980.636980.7260410.36302
990.6023640.7952720.397636
1000.5939570.8120870.406043
1010.5672710.8654590.432729
1020.5429440.9141120.457056
1030.6017680.7964650.398232
1040.5982340.8035320.401766
1050.6109060.7781870.389094
1060.5845130.8309750.415487
1070.5776650.8446690.422335
1080.6379570.7240870.362043
1090.6123590.7752820.387641
1100.5959490.8081010.404051
1110.595290.809420.40471
1120.6054760.7890490.394524
1130.582730.834540.41727
1140.6758010.6483990.324199
1150.6474970.7050060.352503
1160.6190450.7619090.380955
1170.5886550.8226910.411345
1180.567460.8650810.43254
1190.5367280.9265430.463272
1200.510580.9788390.48942
1210.4815830.9631670.518417
1220.4497880.8995750.550212
1230.4236990.8473990.576301
1240.3907850.7815710.609215
1250.3756840.7513680.624316
1260.351510.703020.64849
1270.3363460.6726920.663654
1280.4564710.9129420.543529
1290.4403640.8807270.559636
1300.4297690.8595390.570231
1310.4110890.8221790.588911
1320.3814860.7629730.618514
1330.3996440.7992880.600356
1340.3730320.7460640.626968
1350.4018250.803650.598175
1360.3862290.7724570.613771
1370.3558930.7117860.644107
1380.3365740.6731470.663426
1390.308440.616880.69156
1400.2834740.5669480.716526
1410.2544840.5089690.745516
1420.2738250.5476510.726175
1430.2451040.4902080.754896
1440.2237480.4474960.776252
1450.2178660.4357320.782134
1460.2104190.4208380.789581
1470.2274750.4549510.772525
1480.2436110.4872230.756389
1490.2531750.506350.746825
1500.262040.5240810.73796
1510.238310.476620.76169
1520.2152750.430550.784725
1530.2278190.4556380.772181
1540.2410690.4821380.758931
1550.2323070.4646130.767693
1560.2057270.4114530.794273
1570.1862640.3725280.813736
1580.2981770.5963550.701823
1590.3105490.6210980.689451
1600.2857240.5714480.714276
1610.2611690.5223380.738831
1620.2357580.4715160.764242
1630.2130560.4261120.786944
1640.3501980.7003970.649802
1650.3420920.6841850.657908
1660.3370360.6740710.662964
1670.3043220.6086440.695678
1680.278310.5566190.72169
1690.3283540.6567080.671646
1700.3538440.7076880.646156
1710.3240730.6481460.675927
1720.3188250.6376490.681175
1730.4867410.9734830.513259
1740.4696820.9393650.530318
1750.4937320.9874650.506268
1760.5044050.991190.495595
1770.5601620.8796760.439838
1780.5273820.9452370.472618
1790.5031480.9937040.496852
1800.5035910.9928180.496409
1810.4688750.937750.531125
1820.4650920.9301830.534908
1830.4267890.8535780.573211
1840.3974190.7948370.602581
1850.4257160.8514310.574284
1860.4180360.8360730.581964
1870.381190.7623810.61881
1880.3514460.7028910.648554
1890.3166510.6333020.683349
1900.2930490.5860970.706951
1910.3076190.6152370.692381
1920.2852990.5705980.714701
1930.3057060.6114130.694294
1940.2921930.5843870.707807
1950.2910520.5821040.708948
1960.3012510.6025020.698749
1970.3381590.6763190.661841
1980.3097630.6195260.690237
1990.3465770.6931550.653423
2000.3124310.6248610.687569
2010.3582820.7165640.641718
2020.3335440.6670870.666456
2030.3770390.7540780.622961
2040.3370080.6740160.662992
2050.3015230.6030460.698477
2060.2781890.5563780.721811
2070.2434070.4868140.756593
2080.2818610.5637220.718139
2090.2465350.4930710.753465
2100.2453360.4906730.754664
2110.2699930.5399870.730007
2120.2582760.5165510.741724
2130.2245930.4491870.775407
2140.2859880.5719760.714012
2150.2590140.5180280.740986
2160.2449580.4899160.755042
2170.2594670.5189340.740533
2180.2228780.4457560.777122
2190.2124610.4249210.787539
2200.2082580.4165170.791742
2210.2291530.4583060.770847
2220.2368220.4736440.763178
2230.2309810.4619630.769019
2240.1967360.3934720.803264
2250.172250.3445010.82775
2260.1995560.3991120.800444
2270.4644940.9289880.535506
2280.4307810.8615620.569219
2290.4093450.818690.590655
2300.3910840.7821690.608916
2310.3456730.6913460.654327
2320.3805540.7611080.619446
2330.3510350.702070.648965
2340.2997510.5995020.700249
2350.3042750.6085490.695725
2360.2809710.5619420.719029
2370.2362310.4724610.763769
2380.1901910.3803820.809809
2390.3286760.6573530.671324
2400.3185780.6371550.681422
2410.3015670.6031340.698433
2420.4624770.9249530.537523
2430.4536730.9073450.546327
2440.4057030.8114060.594297
2450.4096340.8192680.590366
2460.3317090.6634180.668291
2470.2644130.5288260.735587
2480.5933980.8132040.406602
2490.4965590.9931180.503441
2500.3976280.7952560.602372
2510.5647390.8705220.435261
2520.9175290.1649410.0824707
2530.8512690.2974620.148731
2540.794990.4100190.20501
2550.6962290.6075430.303771






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0161943NOK
5% type I error level140.0566802NOK
10% type I error level260.105263NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 4 & 0.0161943 & NOK \tabularnewline
5% type I error level & 14 & 0.0566802 & NOK \tabularnewline
10% type I error level & 26 & 0.105263 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221845&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]4[/C][C]0.0161943[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]14[/C][C]0.0566802[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]26[/C][C]0.105263[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221845&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221845&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0161943NOK
5% type I error level140.0566802NOK
10% type I error level260.105263NOK


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')
}