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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 04:13:10 -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/t1383470024b8ct8vyx9t1md0c.htm/, Retrieved Mon, 29 Apr 2024 12:54:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221846, Retrieved Mon, 29 Apr 2024 12:54:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Depession 7] [2013-11-03 09:13:10] [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 time12 seconds
R Server'George Udny Yule' @ yule.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 & 12 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.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=221846&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]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.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=221846&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221846&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 time12 seconds
R Server'George Udny Yule' @ yule.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
Depression[t] = + 27.1753 -0.0428722Connected[t] + 0.00280187Separate[t] -0.0982843Learning[t] -0.0347295Software[t] -0.771941Happiness[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Depression[t] =  +  27.1753 -0.0428722Connected[t] +  0.00280187Separate[t] -0.0982843Learning[t] -0.0347295Software[t] -0.771941Happiness[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221846&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Depression[t] =  +  27.1753 -0.0428722Connected[t] +  0.00280187Separate[t] -0.0982843Learning[t] -0.0347295Software[t] -0.771941Happiness[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221846&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221846&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 27.1753 -0.0428722Connected[t] + 0.00280187Separate[t] -0.0982843Learning[t] -0.0347295Software[t] -0.771941Happiness[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)27.17532.0249313.421.6657e-318.32849e-32
Connected-0.04287220.0519817-0.82480.4102720.205136
Separate0.002801870.0535480.052320.9583110.479155
Learning-0.09828430.0934282-1.0520.2937940.146897
Software-0.03472950.0962376-0.36090.7184910.359245
Happiness-0.7719410.0722537-10.682.66713e-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) & 27.1753 & 2.02493 & 13.42 & 1.6657e-31 & 8.32849e-32 \tabularnewline
Connected & -0.0428722 & 0.0519817 & -0.8248 & 0.410272 & 0.205136 \tabularnewline
Separate & 0.00280187 & 0.053548 & 0.05232 & 0.958311 & 0.479155 \tabularnewline
Learning & -0.0982843 & 0.0934282 & -1.052 & 0.293794 & 0.146897 \tabularnewline
Software & -0.0347295 & 0.0962376 & -0.3609 & 0.718491 & 0.359245 \tabularnewline
Happiness & -0.771941 & 0.0722537 & -10.68 & 2.66713e-22 & 1.33357e-22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221846&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]27.1753[/C][C]2.02493[/C][C]13.42[/C][C]1.6657e-31[/C][C]8.32849e-32[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0428722[/C][C]0.0519817[/C][C]-0.8248[/C][C]0.410272[/C][C]0.205136[/C][/ROW]
[ROW][C]Separate[/C][C]0.00280187[/C][C]0.053548[/C][C]0.05232[/C][C]0.958311[/C][C]0.479155[/C][/ROW]
[ROW][C]Learning[/C][C]-0.0982843[/C][C]0.0934282[/C][C]-1.052[/C][C]0.293794[/C][C]0.146897[/C][/ROW]
[ROW][C]Software[/C][C]-0.0347295[/C][C]0.0962376[/C][C]-0.3609[/C][C]0.718491[/C][C]0.359245[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.771941[/C][C]0.0722537[/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=221846&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221846&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)27.17532.0249313.421.6657e-318.32849e-32
Connected-0.04287220.0519817-0.82480.4102720.205136
Separate0.002801870.0535480.052320.9583110.479155
Learning-0.09828430.0934282-1.0520.2937940.146897
Software-0.03472950.0962376-0.36090.7184910.359245
Happiness-0.7719410.0722537-10.682.66713e-221.33357e-22






Multiple Linear Regression - Regression Statistics
Multiple R0.591636
R-squared0.350033
Adjusted R-squared0.337437
F-TEST (value)27.7886
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.82415
Sum Squared Residuals2057.77

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.591636 \tabularnewline
R-squared & 0.350033 \tabularnewline
Adjusted R-squared & 0.337437 \tabularnewline
F-TEST (value) & 27.7886 \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 & 2.82415 \tabularnewline
Sum Squared Residuals & 2057.77 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221846&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.591636[/C][/ROW]
[ROW][C]R-squared[/C][C]0.350033[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.337437[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]27.7886[/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]2.82415[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2057.77[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221846&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221846&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 R0.591636
R-squared0.350033
Adjusted R-squared0.337437
F-TEST (value)27.7886
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.82415
Sum Squared Residuals2057.77






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.0223-1.02234
2119.743391.25661
31415.1075-1.10746
41214.9927-2.99274
52111.64279.35725
61210.23611.76395
72212.49889.50123
81113.0508-2.05082
91012.3581-2.35807
101312.32950.670491
111010.5901-0.590127
1289.07094-1.07094
131515.9355-0.935465
141411.30412.69592
15109.777430.222574
161413.19760.802387
171413.09280.907219
181110.14710.852856
191012.6514-2.65139
201311.55261.44736
219.510.0463-0.546293
221415.4524-1.45242
231212.4837-0.483651
241414.4804-0.480391
251110.38230.617687
26916.4374-7.43737
271111.459-0.45902
281513.09651.90351
291412.28451.71548
301315.5954-2.59544
31911.691-2.691
321514.61490.385116
331010.8296-0.829568
341112.2529-1.25285
351313.2017-0.201747
36812.3188-4.3188
372017.77592.22406
381212.3525-0.352467
391010.976-0.975977
401013.8121-3.81211
41912.1797-3.17968
421411.66632.33373
43810.7981-2.79809
441414.7806-0.780622
451112.3222-1.32217
461315.6978-2.69782
47912.2488-3.2488
481112.4203-1.42033
491510.66084.33925
501113.8078-2.8078
511011.5-1.5
521413.3570.643049
531815.80832.19171
541414.5367-0.536747
551115.5715-4.57151
5614.512.52361.97642
571311.25811.74186
58912.4588-3.45881
591014.5703-4.57027
601514.58690.413144
612018.36951.6305
621213.6168-1.61684
631215.2656-3.26555
641413.37910.620897
651312.2360.763961
661115.9367-4.93667
671714.98322.01676
681214.5503-2.55031
691312.440.559968
701412.211.79002
711313.5791-0.579125
721511.84363.15637
731311.99241.00757
741011.8265-1.82654
751113.7687-2.76871
761914.34064.6594
771310.54562.45438
781713.81473.18535
791312.78810.211875
80913.6401-4.6401
811112.2929-1.29292
82912.21-3.20998
831211.43940.56063
841212.4632-0.463203
851313.1203-0.120312
861312.38770.612277
871213.0593-1.05926
881513.99711.00292
892218.55833.44167
901311.33211.66789
911513.49451.50549
921312.22120.778814
931513.18361.8164
9412.514.2863-1.78633
951111.3332-0.333205
961614.39971.60028
971113.0693-2.0693
981110.57190.428054
991012.6018-2.60182
1001010.4652-0.465218
1011614.46921.53082
1021210.89781.10216
1031115.5342-4.53416
1041612.33613.66394
1051916.90812.09189
1061111.2055-0.205533
1071611.95834.04165
1081516.0559-1.05594
1092416.30757.6925
1101412.41591.58407
1111515.3886-0.388566
1121113.8301-2.83013
1131513.42891.57109
1141210.26261.7374
1151011.107-1.10699
1161413.23790.762091
1171313.3687-0.368684
118913.3916-4.39164
1191512.85052.1495
1201514.94110.058871
1211413.09070.90934
1221112.3818-1.38182
123812.0576-4.05758
1241112.2138-1.21385
1251113.81-2.80995
126810.6483-2.64834
1271010.2223-0.222295
128119.407631.59237
1291312.62660.373362
1301113.9407-2.94073
1312017.75222.24784
1321012.1345-2.13454
1331512.96122.03879
1341212.3236-0.323605
1351411.64252.35748
1362315.95497.04514
1371413.15220.847798
1381616.0674-0.0673811
1391112.7336-1.73363
1401214.5154-2.51536
1411012.4691-2.46911
1421411.85492.14513
1431212.9882-0.988204
1441212.377-0.37697
1451111.9355-0.935489
1461211.30730.692663
1471315.5469-2.54692
1481114.6376-3.63761
1491917.22671.77334
1501212.0784-0.0783773
1511713.51733.48269
152911.5879-2.5879
1531214.7398-2.73978
1541917.04011.95991
1551814.55143.44858
1561513.49451.50549
1571413.61380.386234
158119.407631.59237
159913.8175-4.81745
1601815.18932.81072
1611614.22771.7723
1622416.74627.25385
1631413.65460.345357
1642011.13058.86953
1651816.28591.7141
1662316.47836.52165
1671213.4164-1.41637
1681415.3695-1.36945
1691617.1822-1.18215
1701817.18460.815396
1712015.83144.16857
1721211.39520.604835
1731217.0414-5.04139
1741714.83912.16089
1751311.76311.23691
176914.0099-5.00989
1771617.2767-1.27673
1781815.21792.78212
1791011.8587-1.85874
1801415.6665-1.66645
1811112.9362-1.93625
182914.434-5.43405
1831111.9796-0.979624
1841012.9376-2.93758
1851112.7564-1.75643
1861913.87975.12032
1871412.86711.13291
1881212.5885-0.588463
1891414.6938-0.693818
1902116.15814.84191
1911315.6201-2.62013
1921012.8617-2.86171
1931513.03311.96691
1941615.33250.667527
1951412.68891.3111
1961214.5411-2.54114
1971913.11225.88783
1981513.06771.93234
1991917.98891.01114
2001314.1257-1.1257
2011717.0364-0.036374
2021212.928-0.927987
2031111.2878-0.287767
2041414.1759-0.175861
2051112.5245-1.52452
2061312.38310.616938
2071213.0166-1.01665
2081511.43523.56476
2091414.2607-0.260662
2101211.63740.362555
2111717.2664-0.266428
2121111.5936-0.593554
2131815.5652.43502
2141316.5072-3.50724
2151715.29211.70786
2161312.74250.257511
2171110.68270.317318
2181213.0681-1.06805
2192217.99894.00114
2201412.2711.72901
2211215.5814-3.58139
2221211.57260.427354
2231716.23970.760296
224912.8648-3.86478
2252117.28073.71926
2261012.5585-2.5585
227119.545721.45428
2281214.9039-2.9039
2292318.24084.75916
2301315.8323-2.83234
2311213.5084-1.50841
2321617.5893-1.58934
233912.5386-3.53857
2341713.21943.78061
235911.8312-2.83121
2361415.7989-1.79894
2371715.80821.19177
2381313.9778-0.977823
2391116.3101-5.31011
2401215.9557-3.95574
2411015.3868-5.38683
2421918.03580.96417
2431615.7030.297038
2441615.01780.982176
2451412.27521.72483
2462016.08143.91857
2471514.17760.822369
2482313.61899.38107
2492017.24292.75714
2501615.57570.424294
2511413.03810.96187
2521714.58892.41105
2531114.3041-3.3041
2541313.9298-0.929784
2551714.89142.10855
2561514.78880.211235
2572116.84164.15837
2581817.33460.665408
2591512.44542.55459
260817.542-9.54205
2611213.4383-1.4383
2621212.7471-0.747074
2632218.83343.16659
2641213.5259-1.5259

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 13.0223 & -1.02234 \tabularnewline
2 & 11 & 9.74339 & 1.25661 \tabularnewline
3 & 14 & 15.1075 & -1.10746 \tabularnewline
4 & 12 & 14.9927 & -2.99274 \tabularnewline
5 & 21 & 11.6427 & 9.35725 \tabularnewline
6 & 12 & 10.2361 & 1.76395 \tabularnewline
7 & 22 & 12.4988 & 9.50123 \tabularnewline
8 & 11 & 13.0508 & -2.05082 \tabularnewline
9 & 10 & 12.3581 & -2.35807 \tabularnewline
10 & 13 & 12.3295 & 0.670491 \tabularnewline
11 & 10 & 10.5901 & -0.590127 \tabularnewline
12 & 8 & 9.07094 & -1.07094 \tabularnewline
13 & 15 & 15.9355 & -0.935465 \tabularnewline
14 & 14 & 11.3041 & 2.69592 \tabularnewline
15 & 10 & 9.77743 & 0.222574 \tabularnewline
16 & 14 & 13.1976 & 0.802387 \tabularnewline
17 & 14 & 13.0928 & 0.907219 \tabularnewline
18 & 11 & 10.1471 & 0.852856 \tabularnewline
19 & 10 & 12.6514 & -2.65139 \tabularnewline
20 & 13 & 11.5526 & 1.44736 \tabularnewline
21 & 9.5 & 10.0463 & -0.546293 \tabularnewline
22 & 14 & 15.4524 & -1.45242 \tabularnewline
23 & 12 & 12.4837 & -0.483651 \tabularnewline
24 & 14 & 14.4804 & -0.480391 \tabularnewline
25 & 11 & 10.3823 & 0.617687 \tabularnewline
26 & 9 & 16.4374 & -7.43737 \tabularnewline
27 & 11 & 11.459 & -0.45902 \tabularnewline
28 & 15 & 13.0965 & 1.90351 \tabularnewline
29 & 14 & 12.2845 & 1.71548 \tabularnewline
30 & 13 & 15.5954 & -2.59544 \tabularnewline
31 & 9 & 11.691 & -2.691 \tabularnewline
32 & 15 & 14.6149 & 0.385116 \tabularnewline
33 & 10 & 10.8296 & -0.829568 \tabularnewline
34 & 11 & 12.2529 & -1.25285 \tabularnewline
35 & 13 & 13.2017 & -0.201747 \tabularnewline
36 & 8 & 12.3188 & -4.3188 \tabularnewline
37 & 20 & 17.7759 & 2.22406 \tabularnewline
38 & 12 & 12.3525 & -0.352467 \tabularnewline
39 & 10 & 10.976 & -0.975977 \tabularnewline
40 & 10 & 13.8121 & -3.81211 \tabularnewline
41 & 9 & 12.1797 & -3.17968 \tabularnewline
42 & 14 & 11.6663 & 2.33373 \tabularnewline
43 & 8 & 10.7981 & -2.79809 \tabularnewline
44 & 14 & 14.7806 & -0.780622 \tabularnewline
45 & 11 & 12.3222 & -1.32217 \tabularnewline
46 & 13 & 15.6978 & -2.69782 \tabularnewline
47 & 9 & 12.2488 & -3.2488 \tabularnewline
48 & 11 & 12.4203 & -1.42033 \tabularnewline
49 & 15 & 10.6608 & 4.33925 \tabularnewline
50 & 11 & 13.8078 & -2.8078 \tabularnewline
51 & 10 & 11.5 & -1.5 \tabularnewline
52 & 14 & 13.357 & 0.643049 \tabularnewline
53 & 18 & 15.8083 & 2.19171 \tabularnewline
54 & 14 & 14.5367 & -0.536747 \tabularnewline
55 & 11 & 15.5715 & -4.57151 \tabularnewline
56 & 14.5 & 12.5236 & 1.97642 \tabularnewline
57 & 13 & 11.2581 & 1.74186 \tabularnewline
58 & 9 & 12.4588 & -3.45881 \tabularnewline
59 & 10 & 14.5703 & -4.57027 \tabularnewline
60 & 15 & 14.5869 & 0.413144 \tabularnewline
61 & 20 & 18.3695 & 1.6305 \tabularnewline
62 & 12 & 13.6168 & -1.61684 \tabularnewline
63 & 12 & 15.2656 & -3.26555 \tabularnewline
64 & 14 & 13.3791 & 0.620897 \tabularnewline
65 & 13 & 12.236 & 0.763961 \tabularnewline
66 & 11 & 15.9367 & -4.93667 \tabularnewline
67 & 17 & 14.9832 & 2.01676 \tabularnewline
68 & 12 & 14.5503 & -2.55031 \tabularnewline
69 & 13 & 12.44 & 0.559968 \tabularnewline
70 & 14 & 12.21 & 1.79002 \tabularnewline
71 & 13 & 13.5791 & -0.579125 \tabularnewline
72 & 15 & 11.8436 & 3.15637 \tabularnewline
73 & 13 & 11.9924 & 1.00757 \tabularnewline
74 & 10 & 11.8265 & -1.82654 \tabularnewline
75 & 11 & 13.7687 & -2.76871 \tabularnewline
76 & 19 & 14.3406 & 4.6594 \tabularnewline
77 & 13 & 10.5456 & 2.45438 \tabularnewline
78 & 17 & 13.8147 & 3.18535 \tabularnewline
79 & 13 & 12.7881 & 0.211875 \tabularnewline
80 & 9 & 13.6401 & -4.6401 \tabularnewline
81 & 11 & 12.2929 & -1.29292 \tabularnewline
82 & 9 & 12.21 & -3.20998 \tabularnewline
83 & 12 & 11.4394 & 0.56063 \tabularnewline
84 & 12 & 12.4632 & -0.463203 \tabularnewline
85 & 13 & 13.1203 & -0.120312 \tabularnewline
86 & 13 & 12.3877 & 0.612277 \tabularnewline
87 & 12 & 13.0593 & -1.05926 \tabularnewline
88 & 15 & 13.9971 & 1.00292 \tabularnewline
89 & 22 & 18.5583 & 3.44167 \tabularnewline
90 & 13 & 11.3321 & 1.66789 \tabularnewline
91 & 15 & 13.4945 & 1.50549 \tabularnewline
92 & 13 & 12.2212 & 0.778814 \tabularnewline
93 & 15 & 13.1836 & 1.8164 \tabularnewline
94 & 12.5 & 14.2863 & -1.78633 \tabularnewline
95 & 11 & 11.3332 & -0.333205 \tabularnewline
96 & 16 & 14.3997 & 1.60028 \tabularnewline
97 & 11 & 13.0693 & -2.0693 \tabularnewline
98 & 11 & 10.5719 & 0.428054 \tabularnewline
99 & 10 & 12.6018 & -2.60182 \tabularnewline
100 & 10 & 10.4652 & -0.465218 \tabularnewline
101 & 16 & 14.4692 & 1.53082 \tabularnewline
102 & 12 & 10.8978 & 1.10216 \tabularnewline
103 & 11 & 15.5342 & -4.53416 \tabularnewline
104 & 16 & 12.3361 & 3.66394 \tabularnewline
105 & 19 & 16.9081 & 2.09189 \tabularnewline
106 & 11 & 11.2055 & -0.205533 \tabularnewline
107 & 16 & 11.9583 & 4.04165 \tabularnewline
108 & 15 & 16.0559 & -1.05594 \tabularnewline
109 & 24 & 16.3075 & 7.6925 \tabularnewline
110 & 14 & 12.4159 & 1.58407 \tabularnewline
111 & 15 & 15.3886 & -0.388566 \tabularnewline
112 & 11 & 13.8301 & -2.83013 \tabularnewline
113 & 15 & 13.4289 & 1.57109 \tabularnewline
114 & 12 & 10.2626 & 1.7374 \tabularnewline
115 & 10 & 11.107 & -1.10699 \tabularnewline
116 & 14 & 13.2379 & 0.762091 \tabularnewline
117 & 13 & 13.3687 & -0.368684 \tabularnewline
118 & 9 & 13.3916 & -4.39164 \tabularnewline
119 & 15 & 12.8505 & 2.1495 \tabularnewline
120 & 15 & 14.9411 & 0.058871 \tabularnewline
121 & 14 & 13.0907 & 0.90934 \tabularnewline
122 & 11 & 12.3818 & -1.38182 \tabularnewline
123 & 8 & 12.0576 & -4.05758 \tabularnewline
124 & 11 & 12.2138 & -1.21385 \tabularnewline
125 & 11 & 13.81 & -2.80995 \tabularnewline
126 & 8 & 10.6483 & -2.64834 \tabularnewline
127 & 10 & 10.2223 & -0.222295 \tabularnewline
128 & 11 & 9.40763 & 1.59237 \tabularnewline
129 & 13 & 12.6266 & 0.373362 \tabularnewline
130 & 11 & 13.9407 & -2.94073 \tabularnewline
131 & 20 & 17.7522 & 2.24784 \tabularnewline
132 & 10 & 12.1345 & -2.13454 \tabularnewline
133 & 15 & 12.9612 & 2.03879 \tabularnewline
134 & 12 & 12.3236 & -0.323605 \tabularnewline
135 & 14 & 11.6425 & 2.35748 \tabularnewline
136 & 23 & 15.9549 & 7.04514 \tabularnewline
137 & 14 & 13.1522 & 0.847798 \tabularnewline
138 & 16 & 16.0674 & -0.0673811 \tabularnewline
139 & 11 & 12.7336 & -1.73363 \tabularnewline
140 & 12 & 14.5154 & -2.51536 \tabularnewline
141 & 10 & 12.4691 & -2.46911 \tabularnewline
142 & 14 & 11.8549 & 2.14513 \tabularnewline
143 & 12 & 12.9882 & -0.988204 \tabularnewline
144 & 12 & 12.377 & -0.37697 \tabularnewline
145 & 11 & 11.9355 & -0.935489 \tabularnewline
146 & 12 & 11.3073 & 0.692663 \tabularnewline
147 & 13 & 15.5469 & -2.54692 \tabularnewline
148 & 11 & 14.6376 & -3.63761 \tabularnewline
149 & 19 & 17.2267 & 1.77334 \tabularnewline
150 & 12 & 12.0784 & -0.0783773 \tabularnewline
151 & 17 & 13.5173 & 3.48269 \tabularnewline
152 & 9 & 11.5879 & -2.5879 \tabularnewline
153 & 12 & 14.7398 & -2.73978 \tabularnewline
154 & 19 & 17.0401 & 1.95991 \tabularnewline
155 & 18 & 14.5514 & 3.44858 \tabularnewline
156 & 15 & 13.4945 & 1.50549 \tabularnewline
157 & 14 & 13.6138 & 0.386234 \tabularnewline
158 & 11 & 9.40763 & 1.59237 \tabularnewline
159 & 9 & 13.8175 & -4.81745 \tabularnewline
160 & 18 & 15.1893 & 2.81072 \tabularnewline
161 & 16 & 14.2277 & 1.7723 \tabularnewline
162 & 24 & 16.7462 & 7.25385 \tabularnewline
163 & 14 & 13.6546 & 0.345357 \tabularnewline
164 & 20 & 11.1305 & 8.86953 \tabularnewline
165 & 18 & 16.2859 & 1.7141 \tabularnewline
166 & 23 & 16.4783 & 6.52165 \tabularnewline
167 & 12 & 13.4164 & -1.41637 \tabularnewline
168 & 14 & 15.3695 & -1.36945 \tabularnewline
169 & 16 & 17.1822 & -1.18215 \tabularnewline
170 & 18 & 17.1846 & 0.815396 \tabularnewline
171 & 20 & 15.8314 & 4.16857 \tabularnewline
172 & 12 & 11.3952 & 0.604835 \tabularnewline
173 & 12 & 17.0414 & -5.04139 \tabularnewline
174 & 17 & 14.8391 & 2.16089 \tabularnewline
175 & 13 & 11.7631 & 1.23691 \tabularnewline
176 & 9 & 14.0099 & -5.00989 \tabularnewline
177 & 16 & 17.2767 & -1.27673 \tabularnewline
178 & 18 & 15.2179 & 2.78212 \tabularnewline
179 & 10 & 11.8587 & -1.85874 \tabularnewline
180 & 14 & 15.6665 & -1.66645 \tabularnewline
181 & 11 & 12.9362 & -1.93625 \tabularnewline
182 & 9 & 14.434 & -5.43405 \tabularnewline
183 & 11 & 11.9796 & -0.979624 \tabularnewline
184 & 10 & 12.9376 & -2.93758 \tabularnewline
185 & 11 & 12.7564 & -1.75643 \tabularnewline
186 & 19 & 13.8797 & 5.12032 \tabularnewline
187 & 14 & 12.8671 & 1.13291 \tabularnewline
188 & 12 & 12.5885 & -0.588463 \tabularnewline
189 & 14 & 14.6938 & -0.693818 \tabularnewline
190 & 21 & 16.1581 & 4.84191 \tabularnewline
191 & 13 & 15.6201 & -2.62013 \tabularnewline
192 & 10 & 12.8617 & -2.86171 \tabularnewline
193 & 15 & 13.0331 & 1.96691 \tabularnewline
194 & 16 & 15.3325 & 0.667527 \tabularnewline
195 & 14 & 12.6889 & 1.3111 \tabularnewline
196 & 12 & 14.5411 & -2.54114 \tabularnewline
197 & 19 & 13.1122 & 5.88783 \tabularnewline
198 & 15 & 13.0677 & 1.93234 \tabularnewline
199 & 19 & 17.9889 & 1.01114 \tabularnewline
200 & 13 & 14.1257 & -1.1257 \tabularnewline
201 & 17 & 17.0364 & -0.036374 \tabularnewline
202 & 12 & 12.928 & -0.927987 \tabularnewline
203 & 11 & 11.2878 & -0.287767 \tabularnewline
204 & 14 & 14.1759 & -0.175861 \tabularnewline
205 & 11 & 12.5245 & -1.52452 \tabularnewline
206 & 13 & 12.3831 & 0.616938 \tabularnewline
207 & 12 & 13.0166 & -1.01665 \tabularnewline
208 & 15 & 11.4352 & 3.56476 \tabularnewline
209 & 14 & 14.2607 & -0.260662 \tabularnewline
210 & 12 & 11.6374 & 0.362555 \tabularnewline
211 & 17 & 17.2664 & -0.266428 \tabularnewline
212 & 11 & 11.5936 & -0.593554 \tabularnewline
213 & 18 & 15.565 & 2.43502 \tabularnewline
214 & 13 & 16.5072 & -3.50724 \tabularnewline
215 & 17 & 15.2921 & 1.70786 \tabularnewline
216 & 13 & 12.7425 & 0.257511 \tabularnewline
217 & 11 & 10.6827 & 0.317318 \tabularnewline
218 & 12 & 13.0681 & -1.06805 \tabularnewline
219 & 22 & 17.9989 & 4.00114 \tabularnewline
220 & 14 & 12.271 & 1.72901 \tabularnewline
221 & 12 & 15.5814 & -3.58139 \tabularnewline
222 & 12 & 11.5726 & 0.427354 \tabularnewline
223 & 17 & 16.2397 & 0.760296 \tabularnewline
224 & 9 & 12.8648 & -3.86478 \tabularnewline
225 & 21 & 17.2807 & 3.71926 \tabularnewline
226 & 10 & 12.5585 & -2.5585 \tabularnewline
227 & 11 & 9.54572 & 1.45428 \tabularnewline
228 & 12 & 14.9039 & -2.9039 \tabularnewline
229 & 23 & 18.2408 & 4.75916 \tabularnewline
230 & 13 & 15.8323 & -2.83234 \tabularnewline
231 & 12 & 13.5084 & -1.50841 \tabularnewline
232 & 16 & 17.5893 & -1.58934 \tabularnewline
233 & 9 & 12.5386 & -3.53857 \tabularnewline
234 & 17 & 13.2194 & 3.78061 \tabularnewline
235 & 9 & 11.8312 & -2.83121 \tabularnewline
236 & 14 & 15.7989 & -1.79894 \tabularnewline
237 & 17 & 15.8082 & 1.19177 \tabularnewline
238 & 13 & 13.9778 & -0.977823 \tabularnewline
239 & 11 & 16.3101 & -5.31011 \tabularnewline
240 & 12 & 15.9557 & -3.95574 \tabularnewline
241 & 10 & 15.3868 & -5.38683 \tabularnewline
242 & 19 & 18.0358 & 0.96417 \tabularnewline
243 & 16 & 15.703 & 0.297038 \tabularnewline
244 & 16 & 15.0178 & 0.982176 \tabularnewline
245 & 14 & 12.2752 & 1.72483 \tabularnewline
246 & 20 & 16.0814 & 3.91857 \tabularnewline
247 & 15 & 14.1776 & 0.822369 \tabularnewline
248 & 23 & 13.6189 & 9.38107 \tabularnewline
249 & 20 & 17.2429 & 2.75714 \tabularnewline
250 & 16 & 15.5757 & 0.424294 \tabularnewline
251 & 14 & 13.0381 & 0.96187 \tabularnewline
252 & 17 & 14.5889 & 2.41105 \tabularnewline
253 & 11 & 14.3041 & -3.3041 \tabularnewline
254 & 13 & 13.9298 & -0.929784 \tabularnewline
255 & 17 & 14.8914 & 2.10855 \tabularnewline
256 & 15 & 14.7888 & 0.211235 \tabularnewline
257 & 21 & 16.8416 & 4.15837 \tabularnewline
258 & 18 & 17.3346 & 0.665408 \tabularnewline
259 & 15 & 12.4454 & 2.55459 \tabularnewline
260 & 8 & 17.542 & -9.54205 \tabularnewline
261 & 12 & 13.4383 & -1.4383 \tabularnewline
262 & 12 & 12.7471 & -0.747074 \tabularnewline
263 & 22 & 18.8334 & 3.16659 \tabularnewline
264 & 12 & 13.5259 & -1.5259 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221846&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]13.0223[/C][C]-1.02234[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]9.74339[/C][C]1.25661[/C][/ROW]
[ROW][C]3[/C][C]14[/C][C]15.1075[/C][C]-1.10746[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.9927[/C][C]-2.99274[/C][/ROW]
[ROW][C]5[/C][C]21[/C][C]11.6427[/C][C]9.35725[/C][/ROW]
[ROW][C]6[/C][C]12[/C][C]10.2361[/C][C]1.76395[/C][/ROW]
[ROW][C]7[/C][C]22[/C][C]12.4988[/C][C]9.50123[/C][/ROW]
[ROW][C]8[/C][C]11[/C][C]13.0508[/C][C]-2.05082[/C][/ROW]
[ROW][C]9[/C][C]10[/C][C]12.3581[/C][C]-2.35807[/C][/ROW]
[ROW][C]10[/C][C]13[/C][C]12.3295[/C][C]0.670491[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]10.5901[/C][C]-0.590127[/C][/ROW]
[ROW][C]12[/C][C]8[/C][C]9.07094[/C][C]-1.07094[/C][/ROW]
[ROW][C]13[/C][C]15[/C][C]15.9355[/C][C]-0.935465[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]11.3041[/C][C]2.69592[/C][/ROW]
[ROW][C]15[/C][C]10[/C][C]9.77743[/C][C]0.222574[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.1976[/C][C]0.802387[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.0928[/C][C]0.907219[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]10.1471[/C][C]0.852856[/C][/ROW]
[ROW][C]19[/C][C]10[/C][C]12.6514[/C][C]-2.65139[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]11.5526[/C][C]1.44736[/C][/ROW]
[ROW][C]21[/C][C]9.5[/C][C]10.0463[/C][C]-0.546293[/C][/ROW]
[ROW][C]22[/C][C]14[/C][C]15.4524[/C][C]-1.45242[/C][/ROW]
[ROW][C]23[/C][C]12[/C][C]12.4837[/C][C]-0.483651[/C][/ROW]
[ROW][C]24[/C][C]14[/C][C]14.4804[/C][C]-0.480391[/C][/ROW]
[ROW][C]25[/C][C]11[/C][C]10.3823[/C][C]0.617687[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]16.4374[/C][C]-7.43737[/C][/ROW]
[ROW][C]27[/C][C]11[/C][C]11.459[/C][C]-0.45902[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]13.0965[/C][C]1.90351[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]12.2845[/C][C]1.71548[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]15.5954[/C][C]-2.59544[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]11.691[/C][C]-2.691[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]14.6149[/C][C]0.385116[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.8296[/C][C]-0.829568[/C][/ROW]
[ROW][C]34[/C][C]11[/C][C]12.2529[/C][C]-1.25285[/C][/ROW]
[ROW][C]35[/C][C]13[/C][C]13.2017[/C][C]-0.201747[/C][/ROW]
[ROW][C]36[/C][C]8[/C][C]12.3188[/C][C]-4.3188[/C][/ROW]
[ROW][C]37[/C][C]20[/C][C]17.7759[/C][C]2.22406[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]12.3525[/C][C]-0.352467[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.976[/C][C]-0.975977[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]13.8121[/C][C]-3.81211[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]12.1797[/C][C]-3.17968[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]11.6663[/C][C]2.33373[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]10.7981[/C][C]-2.79809[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.7806[/C][C]-0.780622[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]12.3222[/C][C]-1.32217[/C][/ROW]
[ROW][C]46[/C][C]13[/C][C]15.6978[/C][C]-2.69782[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]12.2488[/C][C]-3.2488[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]12.4203[/C][C]-1.42033[/C][/ROW]
[ROW][C]49[/C][C]15[/C][C]10.6608[/C][C]4.33925[/C][/ROW]
[ROW][C]50[/C][C]11[/C][C]13.8078[/C][C]-2.8078[/C][/ROW]
[ROW][C]51[/C][C]10[/C][C]11.5[/C][C]-1.5[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.357[/C][C]0.643049[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]15.8083[/C][C]2.19171[/C][/ROW]
[ROW][C]54[/C][C]14[/C][C]14.5367[/C][C]-0.536747[/C][/ROW]
[ROW][C]55[/C][C]11[/C][C]15.5715[/C][C]-4.57151[/C][/ROW]
[ROW][C]56[/C][C]14.5[/C][C]12.5236[/C][C]1.97642[/C][/ROW]
[ROW][C]57[/C][C]13[/C][C]11.2581[/C][C]1.74186[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]12.4588[/C][C]-3.45881[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]14.5703[/C][C]-4.57027[/C][/ROW]
[ROW][C]60[/C][C]15[/C][C]14.5869[/C][C]0.413144[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]18.3695[/C][C]1.6305[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]13.6168[/C][C]-1.61684[/C][/ROW]
[ROW][C]63[/C][C]12[/C][C]15.2656[/C][C]-3.26555[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.3791[/C][C]0.620897[/C][/ROW]
[ROW][C]65[/C][C]13[/C][C]12.236[/C][C]0.763961[/C][/ROW]
[ROW][C]66[/C][C]11[/C][C]15.9367[/C][C]-4.93667[/C][/ROW]
[ROW][C]67[/C][C]17[/C][C]14.9832[/C][C]2.01676[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.5503[/C][C]-2.55031[/C][/ROW]
[ROW][C]69[/C][C]13[/C][C]12.44[/C][C]0.559968[/C][/ROW]
[ROW][C]70[/C][C]14[/C][C]12.21[/C][C]1.79002[/C][/ROW]
[ROW][C]71[/C][C]13[/C][C]13.5791[/C][C]-0.579125[/C][/ROW]
[ROW][C]72[/C][C]15[/C][C]11.8436[/C][C]3.15637[/C][/ROW]
[ROW][C]73[/C][C]13[/C][C]11.9924[/C][C]1.00757[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]11.8265[/C][C]-1.82654[/C][/ROW]
[ROW][C]75[/C][C]11[/C][C]13.7687[/C][C]-2.76871[/C][/ROW]
[ROW][C]76[/C][C]19[/C][C]14.3406[/C][C]4.6594[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.5456[/C][C]2.45438[/C][/ROW]
[ROW][C]78[/C][C]17[/C][C]13.8147[/C][C]3.18535[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]12.7881[/C][C]0.211875[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]13.6401[/C][C]-4.6401[/C][/ROW]
[ROW][C]81[/C][C]11[/C][C]12.2929[/C][C]-1.29292[/C][/ROW]
[ROW][C]82[/C][C]9[/C][C]12.21[/C][C]-3.20998[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]11.4394[/C][C]0.56063[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]12.4632[/C][C]-0.463203[/C][/ROW]
[ROW][C]85[/C][C]13[/C][C]13.1203[/C][C]-0.120312[/C][/ROW]
[ROW][C]86[/C][C]13[/C][C]12.3877[/C][C]0.612277[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]13.0593[/C][C]-1.05926[/C][/ROW]
[ROW][C]88[/C][C]15[/C][C]13.9971[/C][C]1.00292[/C][/ROW]
[ROW][C]89[/C][C]22[/C][C]18.5583[/C][C]3.44167[/C][/ROW]
[ROW][C]90[/C][C]13[/C][C]11.3321[/C][C]1.66789[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]13.4945[/C][C]1.50549[/C][/ROW]
[ROW][C]92[/C][C]13[/C][C]12.2212[/C][C]0.778814[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]13.1836[/C][C]1.8164[/C][/ROW]
[ROW][C]94[/C][C]12.5[/C][C]14.2863[/C][C]-1.78633[/C][/ROW]
[ROW][C]95[/C][C]11[/C][C]11.3332[/C][C]-0.333205[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]14.3997[/C][C]1.60028[/C][/ROW]
[ROW][C]97[/C][C]11[/C][C]13.0693[/C][C]-2.0693[/C][/ROW]
[ROW][C]98[/C][C]11[/C][C]10.5719[/C][C]0.428054[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]12.6018[/C][C]-2.60182[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]10.4652[/C][C]-0.465218[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.4692[/C][C]1.53082[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]10.8978[/C][C]1.10216[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]15.5342[/C][C]-4.53416[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]12.3361[/C][C]3.66394[/C][/ROW]
[ROW][C]105[/C][C]19[/C][C]16.9081[/C][C]2.09189[/C][/ROW]
[ROW][C]106[/C][C]11[/C][C]11.2055[/C][C]-0.205533[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]11.9583[/C][C]4.04165[/C][/ROW]
[ROW][C]108[/C][C]15[/C][C]16.0559[/C][C]-1.05594[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]16.3075[/C][C]7.6925[/C][/ROW]
[ROW][C]110[/C][C]14[/C][C]12.4159[/C][C]1.58407[/C][/ROW]
[ROW][C]111[/C][C]15[/C][C]15.3886[/C][C]-0.388566[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]13.8301[/C][C]-2.83013[/C][/ROW]
[ROW][C]113[/C][C]15[/C][C]13.4289[/C][C]1.57109[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]10.2626[/C][C]1.7374[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]11.107[/C][C]-1.10699[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.2379[/C][C]0.762091[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]13.3687[/C][C]-0.368684[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]13.3916[/C][C]-4.39164[/C][/ROW]
[ROW][C]119[/C][C]15[/C][C]12.8505[/C][C]2.1495[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]14.9411[/C][C]0.058871[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.0907[/C][C]0.90934[/C][/ROW]
[ROW][C]122[/C][C]11[/C][C]12.3818[/C][C]-1.38182[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]12.0576[/C][C]-4.05758[/C][/ROW]
[ROW][C]124[/C][C]11[/C][C]12.2138[/C][C]-1.21385[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]13.81[/C][C]-2.80995[/C][/ROW]
[ROW][C]126[/C][C]8[/C][C]10.6483[/C][C]-2.64834[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]10.2223[/C][C]-0.222295[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]9.40763[/C][C]1.59237[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]12.6266[/C][C]0.373362[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]13.9407[/C][C]-2.94073[/C][/ROW]
[ROW][C]131[/C][C]20[/C][C]17.7522[/C][C]2.24784[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]12.1345[/C][C]-2.13454[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.9612[/C][C]2.03879[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]12.3236[/C][C]-0.323605[/C][/ROW]
[ROW][C]135[/C][C]14[/C][C]11.6425[/C][C]2.35748[/C][/ROW]
[ROW][C]136[/C][C]23[/C][C]15.9549[/C][C]7.04514[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.1522[/C][C]0.847798[/C][/ROW]
[ROW][C]138[/C][C]16[/C][C]16.0674[/C][C]-0.0673811[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]12.7336[/C][C]-1.73363[/C][/ROW]
[ROW][C]140[/C][C]12[/C][C]14.5154[/C][C]-2.51536[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]12.4691[/C][C]-2.46911[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]11.8549[/C][C]2.14513[/C][/ROW]
[ROW][C]143[/C][C]12[/C][C]12.9882[/C][C]-0.988204[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]12.377[/C][C]-0.37697[/C][/ROW]
[ROW][C]145[/C][C]11[/C][C]11.9355[/C][C]-0.935489[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]11.3073[/C][C]0.692663[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.5469[/C][C]-2.54692[/C][/ROW]
[ROW][C]148[/C][C]11[/C][C]14.6376[/C][C]-3.63761[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]17.2267[/C][C]1.77334[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]12.0784[/C][C]-0.0783773[/C][/ROW]
[ROW][C]151[/C][C]17[/C][C]13.5173[/C][C]3.48269[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.5879[/C][C]-2.5879[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.7398[/C][C]-2.73978[/C][/ROW]
[ROW][C]154[/C][C]19[/C][C]17.0401[/C][C]1.95991[/C][/ROW]
[ROW][C]155[/C][C]18[/C][C]14.5514[/C][C]3.44858[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]13.4945[/C][C]1.50549[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.6138[/C][C]0.386234[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]9.40763[/C][C]1.59237[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]13.8175[/C][C]-4.81745[/C][/ROW]
[ROW][C]160[/C][C]18[/C][C]15.1893[/C][C]2.81072[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]14.2277[/C][C]1.7723[/C][/ROW]
[ROW][C]162[/C][C]24[/C][C]16.7462[/C][C]7.25385[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.6546[/C][C]0.345357[/C][/ROW]
[ROW][C]164[/C][C]20[/C][C]11.1305[/C][C]8.86953[/C][/ROW]
[ROW][C]165[/C][C]18[/C][C]16.2859[/C][C]1.7141[/C][/ROW]
[ROW][C]166[/C][C]23[/C][C]16.4783[/C][C]6.52165[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]13.4164[/C][C]-1.41637[/C][/ROW]
[ROW][C]168[/C][C]14[/C][C]15.3695[/C][C]-1.36945[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]17.1822[/C][C]-1.18215[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]17.1846[/C][C]0.815396[/C][/ROW]
[ROW][C]171[/C][C]20[/C][C]15.8314[/C][C]4.16857[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.3952[/C][C]0.604835[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]17.0414[/C][C]-5.04139[/C][/ROW]
[ROW][C]174[/C][C]17[/C][C]14.8391[/C][C]2.16089[/C][/ROW]
[ROW][C]175[/C][C]13[/C][C]11.7631[/C][C]1.23691[/C][/ROW]
[ROW][C]176[/C][C]9[/C][C]14.0099[/C][C]-5.00989[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]17.2767[/C][C]-1.27673[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]15.2179[/C][C]2.78212[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]11.8587[/C][C]-1.85874[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]15.6665[/C][C]-1.66645[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]12.9362[/C][C]-1.93625[/C][/ROW]
[ROW][C]182[/C][C]9[/C][C]14.434[/C][C]-5.43405[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]11.9796[/C][C]-0.979624[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]12.9376[/C][C]-2.93758[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]12.7564[/C][C]-1.75643[/C][/ROW]
[ROW][C]186[/C][C]19[/C][C]13.8797[/C][C]5.12032[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]12.8671[/C][C]1.13291[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.5885[/C][C]-0.588463[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]14.6938[/C][C]-0.693818[/C][/ROW]
[ROW][C]190[/C][C]21[/C][C]16.1581[/C][C]4.84191[/C][/ROW]
[ROW][C]191[/C][C]13[/C][C]15.6201[/C][C]-2.62013[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]12.8617[/C][C]-2.86171[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]13.0331[/C][C]1.96691[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]15.3325[/C][C]0.667527[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]12.6889[/C][C]1.3111[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.5411[/C][C]-2.54114[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]13.1122[/C][C]5.88783[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]13.0677[/C][C]1.93234[/C][/ROW]
[ROW][C]199[/C][C]19[/C][C]17.9889[/C][C]1.01114[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]14.1257[/C][C]-1.1257[/C][/ROW]
[ROW][C]201[/C][C]17[/C][C]17.0364[/C][C]-0.036374[/C][/ROW]
[ROW][C]202[/C][C]12[/C][C]12.928[/C][C]-0.927987[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]11.2878[/C][C]-0.287767[/C][/ROW]
[ROW][C]204[/C][C]14[/C][C]14.1759[/C][C]-0.175861[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]12.5245[/C][C]-1.52452[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]12.3831[/C][C]0.616938[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]13.0166[/C][C]-1.01665[/C][/ROW]
[ROW][C]208[/C][C]15[/C][C]11.4352[/C][C]3.56476[/C][/ROW]
[ROW][C]209[/C][C]14[/C][C]14.2607[/C][C]-0.260662[/C][/ROW]
[ROW][C]210[/C][C]12[/C][C]11.6374[/C][C]0.362555[/C][/ROW]
[ROW][C]211[/C][C]17[/C][C]17.2664[/C][C]-0.266428[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]11.5936[/C][C]-0.593554[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]15.565[/C][C]2.43502[/C][/ROW]
[ROW][C]214[/C][C]13[/C][C]16.5072[/C][C]-3.50724[/C][/ROW]
[ROW][C]215[/C][C]17[/C][C]15.2921[/C][C]1.70786[/C][/ROW]
[ROW][C]216[/C][C]13[/C][C]12.7425[/C][C]0.257511[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]10.6827[/C][C]0.317318[/C][/ROW]
[ROW][C]218[/C][C]12[/C][C]13.0681[/C][C]-1.06805[/C][/ROW]
[ROW][C]219[/C][C]22[/C][C]17.9989[/C][C]4.00114[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]12.271[/C][C]1.72901[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]15.5814[/C][C]-3.58139[/C][/ROW]
[ROW][C]222[/C][C]12[/C][C]11.5726[/C][C]0.427354[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]16.2397[/C][C]0.760296[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]12.8648[/C][C]-3.86478[/C][/ROW]
[ROW][C]225[/C][C]21[/C][C]17.2807[/C][C]3.71926[/C][/ROW]
[ROW][C]226[/C][C]10[/C][C]12.5585[/C][C]-2.5585[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]9.54572[/C][C]1.45428[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]14.9039[/C][C]-2.9039[/C][/ROW]
[ROW][C]229[/C][C]23[/C][C]18.2408[/C][C]4.75916[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]15.8323[/C][C]-2.83234[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]13.5084[/C][C]-1.50841[/C][/ROW]
[ROW][C]232[/C][C]16[/C][C]17.5893[/C][C]-1.58934[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]12.5386[/C][C]-3.53857[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]13.2194[/C][C]3.78061[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]11.8312[/C][C]-2.83121[/C][/ROW]
[ROW][C]236[/C][C]14[/C][C]15.7989[/C][C]-1.79894[/C][/ROW]
[ROW][C]237[/C][C]17[/C][C]15.8082[/C][C]1.19177[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.9778[/C][C]-0.977823[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]16.3101[/C][C]-5.31011[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]15.9557[/C][C]-3.95574[/C][/ROW]
[ROW][C]241[/C][C]10[/C][C]15.3868[/C][C]-5.38683[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]18.0358[/C][C]0.96417[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]15.703[/C][C]0.297038[/C][/ROW]
[ROW][C]244[/C][C]16[/C][C]15.0178[/C][C]0.982176[/C][/ROW]
[ROW][C]245[/C][C]14[/C][C]12.2752[/C][C]1.72483[/C][/ROW]
[ROW][C]246[/C][C]20[/C][C]16.0814[/C][C]3.91857[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]14.1776[/C][C]0.822369[/C][/ROW]
[ROW][C]248[/C][C]23[/C][C]13.6189[/C][C]9.38107[/C][/ROW]
[ROW][C]249[/C][C]20[/C][C]17.2429[/C][C]2.75714[/C][/ROW]
[ROW][C]250[/C][C]16[/C][C]15.5757[/C][C]0.424294[/C][/ROW]
[ROW][C]251[/C][C]14[/C][C]13.0381[/C][C]0.96187[/C][/ROW]
[ROW][C]252[/C][C]17[/C][C]14.5889[/C][C]2.41105[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]14.3041[/C][C]-3.3041[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.9298[/C][C]-0.929784[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]14.8914[/C][C]2.10855[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]14.7888[/C][C]0.211235[/C][/ROW]
[ROW][C]257[/C][C]21[/C][C]16.8416[/C][C]4.15837[/C][/ROW]
[ROW][C]258[/C][C]18[/C][C]17.3346[/C][C]0.665408[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.4454[/C][C]2.55459[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]17.542[/C][C]-9.54205[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]13.4383[/C][C]-1.4383[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]12.7471[/C][C]-0.747074[/C][/ROW]
[ROW][C]263[/C][C]22[/C][C]18.8334[/C][C]3.16659[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]13.5259[/C][C]-1.5259[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221846&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221846&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.0223-1.02234
2119.743391.25661
31415.1075-1.10746
41214.9927-2.99274
52111.64279.35725
61210.23611.76395
72212.49889.50123
81113.0508-2.05082
91012.3581-2.35807
101312.32950.670491
111010.5901-0.590127
1289.07094-1.07094
131515.9355-0.935465
141411.30412.69592
15109.777430.222574
161413.19760.802387
171413.09280.907219
181110.14710.852856
191012.6514-2.65139
201311.55261.44736
219.510.0463-0.546293
221415.4524-1.45242
231212.4837-0.483651
241414.4804-0.480391
251110.38230.617687
26916.4374-7.43737
271111.459-0.45902
281513.09651.90351
291412.28451.71548
301315.5954-2.59544
31911.691-2.691
321514.61490.385116
331010.8296-0.829568
341112.2529-1.25285
351313.2017-0.201747
36812.3188-4.3188
372017.77592.22406
381212.3525-0.352467
391010.976-0.975977
401013.8121-3.81211
41912.1797-3.17968
421411.66632.33373
43810.7981-2.79809
441414.7806-0.780622
451112.3222-1.32217
461315.6978-2.69782
47912.2488-3.2488
481112.4203-1.42033
491510.66084.33925
501113.8078-2.8078
511011.5-1.5
521413.3570.643049
531815.80832.19171
541414.5367-0.536747
551115.5715-4.57151
5614.512.52361.97642
571311.25811.74186
58912.4588-3.45881
591014.5703-4.57027
601514.58690.413144
612018.36951.6305
621213.6168-1.61684
631215.2656-3.26555
641413.37910.620897
651312.2360.763961
661115.9367-4.93667
671714.98322.01676
681214.5503-2.55031
691312.440.559968
701412.211.79002
711313.5791-0.579125
721511.84363.15637
731311.99241.00757
741011.8265-1.82654
751113.7687-2.76871
761914.34064.6594
771310.54562.45438
781713.81473.18535
791312.78810.211875
80913.6401-4.6401
811112.2929-1.29292
82912.21-3.20998
831211.43940.56063
841212.4632-0.463203
851313.1203-0.120312
861312.38770.612277
871213.0593-1.05926
881513.99711.00292
892218.55833.44167
901311.33211.66789
911513.49451.50549
921312.22120.778814
931513.18361.8164
9412.514.2863-1.78633
951111.3332-0.333205
961614.39971.60028
971113.0693-2.0693
981110.57190.428054
991012.6018-2.60182
1001010.4652-0.465218
1011614.46921.53082
1021210.89781.10216
1031115.5342-4.53416
1041612.33613.66394
1051916.90812.09189
1061111.2055-0.205533
1071611.95834.04165
1081516.0559-1.05594
1092416.30757.6925
1101412.41591.58407
1111515.3886-0.388566
1121113.8301-2.83013
1131513.42891.57109
1141210.26261.7374
1151011.107-1.10699
1161413.23790.762091
1171313.3687-0.368684
118913.3916-4.39164
1191512.85052.1495
1201514.94110.058871
1211413.09070.90934
1221112.3818-1.38182
123812.0576-4.05758
1241112.2138-1.21385
1251113.81-2.80995
126810.6483-2.64834
1271010.2223-0.222295
128119.407631.59237
1291312.62660.373362
1301113.9407-2.94073
1312017.75222.24784
1321012.1345-2.13454
1331512.96122.03879
1341212.3236-0.323605
1351411.64252.35748
1362315.95497.04514
1371413.15220.847798
1381616.0674-0.0673811
1391112.7336-1.73363
1401214.5154-2.51536
1411012.4691-2.46911
1421411.85492.14513
1431212.9882-0.988204
1441212.377-0.37697
1451111.9355-0.935489
1461211.30730.692663
1471315.5469-2.54692
1481114.6376-3.63761
1491917.22671.77334
1501212.0784-0.0783773
1511713.51733.48269
152911.5879-2.5879
1531214.7398-2.73978
1541917.04011.95991
1551814.55143.44858
1561513.49451.50549
1571413.61380.386234
158119.407631.59237
159913.8175-4.81745
1601815.18932.81072
1611614.22771.7723
1622416.74627.25385
1631413.65460.345357
1642011.13058.86953
1651816.28591.7141
1662316.47836.52165
1671213.4164-1.41637
1681415.3695-1.36945
1691617.1822-1.18215
1701817.18460.815396
1712015.83144.16857
1721211.39520.604835
1731217.0414-5.04139
1741714.83912.16089
1751311.76311.23691
176914.0099-5.00989
1771617.2767-1.27673
1781815.21792.78212
1791011.8587-1.85874
1801415.6665-1.66645
1811112.9362-1.93625
182914.434-5.43405
1831111.9796-0.979624
1841012.9376-2.93758
1851112.7564-1.75643
1861913.87975.12032
1871412.86711.13291
1881212.5885-0.588463
1891414.6938-0.693818
1902116.15814.84191
1911315.6201-2.62013
1921012.8617-2.86171
1931513.03311.96691
1941615.33250.667527
1951412.68891.3111
1961214.5411-2.54114
1971913.11225.88783
1981513.06771.93234
1991917.98891.01114
2001314.1257-1.1257
2011717.0364-0.036374
2021212.928-0.927987
2031111.2878-0.287767
2041414.1759-0.175861
2051112.5245-1.52452
2061312.38310.616938
2071213.0166-1.01665
2081511.43523.56476
2091414.2607-0.260662
2101211.63740.362555
2111717.2664-0.266428
2121111.5936-0.593554
2131815.5652.43502
2141316.5072-3.50724
2151715.29211.70786
2161312.74250.257511
2171110.68270.317318
2181213.0681-1.06805
2192217.99894.00114
2201412.2711.72901
2211215.5814-3.58139
2221211.57260.427354
2231716.23970.760296
224912.8648-3.86478
2252117.28073.71926
2261012.5585-2.5585
227119.545721.45428
2281214.9039-2.9039
2292318.24084.75916
2301315.8323-2.83234
2311213.5084-1.50841
2321617.5893-1.58934
233912.5386-3.53857
2341713.21943.78061
235911.8312-2.83121
2361415.7989-1.79894
2371715.80821.19177
2381313.9778-0.977823
2391116.3101-5.31011
2401215.9557-3.95574
2411015.3868-5.38683
2421918.03580.96417
2431615.7030.297038
2441615.01780.982176
2451412.27521.72483
2462016.08143.91857
2471514.17760.822369
2482313.61899.38107
2492017.24292.75714
2501615.57570.424294
2511413.03810.96187
2521714.58892.41105
2531114.3041-3.3041
2541313.9298-0.929784
2551714.89142.10855
2561514.78880.211235
2572116.84164.15837
2581817.33460.665408
2591512.44542.55459
260817.542-9.54205
2611213.4383-1.4383
2621212.7471-0.747074
2632218.83343.16659
2641213.5259-1.5259






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9986350.002729680.00136484
100.9971440.005712870.00285644
110.9974350.005130020.00256501
120.9982440.003512530.00175626
130.9966310.006738430.00336921
140.9938420.01231570.00615785
150.9908150.01836990.00918494
160.9852160.02956830.0147842
170.9760530.04789390.0239469
180.9669090.06618220.0330911
190.9668050.06638940.0331947
200.9513650.09726960.0486348
210.9332690.1334620.0667308
220.9132030.1735940.0867969
230.8893150.221370.110685
240.8557560.2884880.144244
250.8281170.3437660.171883
260.94160.11680.0584
270.9233040.1533920.0766961
280.9069140.1861720.0930858
290.8843610.2312790.115639
300.8582750.283450.141725
310.8678660.2642670.132134
320.843290.3134210.15671
330.8146210.3707580.185379
340.7876550.424690.212345
350.7454260.5091470.254574
360.7670870.4658260.232913
370.8231150.3537710.176885
380.7876220.4247570.212378
390.7582870.4834270.241713
400.7618940.4762120.238106
410.7554530.4890950.244547
420.7318780.5362430.268122
430.7408960.5182090.259104
440.7006450.598710.299355
450.6591050.6817910.340895
460.6377710.7244580.362229
470.6558730.6882540.344127
480.6206280.7587440.379372
490.6608740.6782510.339126
500.6366280.7267450.363372
510.6222120.7555770.377788
520.5854490.8291030.414551
530.5930950.813810.406905
540.5486960.9026070.451304
550.5604240.8791520.439576
560.5631560.8736880.436844
570.5366830.9266350.463317
580.5645770.8708460.435423
590.5949510.8100980.405049
600.5652010.8695980.434799
610.5917210.8165590.408279
620.5558840.8882320.444116
630.5475760.9048470.452424
640.5089990.9820010.491001
650.4704650.940930.529535
660.5080660.9838670.491934
670.5149170.9701650.485083
680.4970460.9940920.502954
690.4588680.9177360.541132
700.4358720.8717430.564128
710.3961730.7923470.603827
720.3968990.7937990.603101
730.3612750.722550.638725
740.3407630.6815270.659237
750.3269030.6538050.673097
760.4419590.8839190.558041
770.4257680.8515360.574232
780.4503840.9007680.549616
790.4117350.8234690.588265
800.456560.9131210.54344
810.427150.8543010.57285
820.4398270.8796550.560173
830.4031310.8062630.596869
840.366990.7339790.63301
850.3313850.662770.668615
860.298570.597140.70143
870.2692750.5385510.730725
880.2455410.4910830.754459
890.3089840.6179680.691016
900.2851020.5702030.714898
910.268190.5363810.73181
920.2396170.4792340.760383
930.2251160.4502310.774884
940.2063150.412630.793685
950.1808730.3617460.819127
960.169520.339040.83048
970.1574730.3149450.842527
980.1361380.2722760.863862
990.1333090.2666190.866691
1000.1152940.2305890.884706
1010.1061820.2123630.893818
1020.09140010.18280.9086
1030.1109520.2219040.889048
1040.1221740.2443470.877826
1050.1255360.2510710.874464
1060.1077310.2154620.892269
1070.1249050.2498110.875095
1080.1089890.2179770.891011
1090.2511410.5022810.748859
1100.2338810.4677630.766119
1110.2083820.4167630.791618
1120.2123040.4246090.787696
1130.1964310.3928620.803569
1140.1802060.3604120.819794
1150.1608170.3216340.839183
1160.1413140.2826280.858686
1170.1234940.2469870.876506
1180.1508320.3016630.849168
1190.1411070.2822150.858893
1200.1219560.2439110.878044
1210.1098120.2196240.890188
1220.09926710.1985340.900733
1230.1193550.238710.880645
1240.1053330.2106660.894667
1250.1036450.207290.896355
1260.1039940.2079880.896006
1270.09007080.1801420.909929
1280.08043020.160860.91957
1290.06817890.1363580.931821
1300.0686910.1373820.931309
1310.0678380.1356760.932162
1320.06413640.1282730.935864
1330.06005120.1201020.939949
1340.05039680.1007940.949603
1350.04797310.09594630.952027
1360.1187370.2374740.881263
1370.1032570.2065150.896743
1380.08809360.1761870.911906
1390.07999130.1599830.920009
1400.07692620.1538520.923074
1410.07376260.1475250.926237
1420.06874450.1374890.931255
1430.0591360.1182720.940864
1440.04985760.09971510.950142
1450.04245170.08490340.957548
1460.03535770.07071540.964642
1470.03396630.06793270.966034
1480.03938970.07877930.96061
1490.03527720.07055440.964723
1500.02908090.05816180.970919
1510.03144490.06288980.968555
1520.03026150.0605230.969738
1530.02948880.05897750.970511
1540.02657140.05314280.973429
1550.02936050.05872110.970639
1560.02497930.04995850.975021
1570.02028280.04056570.979717
1580.01741090.03482170.982589
1590.02714690.05429390.972853
1600.02764950.0552990.972351
1610.02441010.04882010.97559
1620.06590240.1318050.934098
1630.05507630.1101530.944924
1640.1967310.3934630.803269
1650.1804260.3608530.819574
1660.3037820.6075640.696218
1670.2795890.5591790.720411
1680.2565340.5130680.743466
1690.2323340.4646680.767666
1700.2071910.4143820.792809
1710.2342570.4685130.765743
1720.2075450.415090.792455
1730.2759860.5519710.724014
1740.2684950.536990.731505
1750.2453860.4907720.754614
1760.3159350.6318710.684065
1770.2916370.5832740.708363
1780.2923190.5846380.707681
1790.2724770.5449540.727523
1800.2541160.5082310.745884
1810.2426870.4853740.757313
1820.3246960.6493930.675304
1830.2992990.5985980.700701
1840.3130130.6260260.686987
1850.2893820.5787640.710618
1860.3556650.7113290.644335
1870.3220870.6441730.677913
1880.2906250.5812490.709375
1890.2589290.5178570.741071
1900.3376810.6753620.662319
1910.3336930.6673860.666307
1920.3514990.7029970.648501
1930.3509980.7019960.649002
1940.3153550.630710.684645
1950.2882760.5765520.711724
1960.301660.6033210.69834
1970.4137450.8274890.586255
1980.3848830.7697670.615117
1990.3478520.6957050.652148
2000.3171160.6342330.682884
2010.2846960.5693910.715304
2020.2520050.504010.747995
2030.2204320.4408640.779568
2040.1916220.3832440.808378
2050.168950.33790.83105
2060.1435180.2870370.856482
2070.1266970.2533940.873303
2080.1297640.2595280.870236
2090.1082730.2165450.891727
2100.08945890.1789180.910541
2110.07576770.1515350.924232
2120.06333360.1266670.936666
2130.05584440.1116890.944156
2140.06123840.1224770.938762
2150.04989090.09978170.950109
2160.03963810.07927610.960362
2170.03077240.06154480.969228
2180.02528130.05056270.974719
2190.02791230.05582460.972088
2200.02224690.04449390.977753
2210.03120010.06240030.9688
2220.0236450.04729010.976355
2230.01798340.03596690.982017
2240.0198680.0397360.980132
2250.02161650.0432330.978384
2260.01724530.03449050.982755
2270.01385690.02771390.986143
2280.01332780.02665560.986672
2290.01894080.03788150.981059
2300.01799830.03599660.982002
2310.01329370.02658740.986706
2320.01076870.02153740.989231
2330.01045590.02091180.989544
2340.008615480.0172310.991385
2350.008977720.01795540.991022
2360.007324880.01464980.992675
2370.005781090.01156220.994219
2380.004645560.009291120.995354
2390.0224390.0448780.977561
2400.03025440.06050880.969746
2410.05549870.1109970.944501
2420.04279570.08559150.957204
2430.04026770.08053550.959732
2440.03126030.06252060.96874
2450.02068990.04137970.97931
2460.03273190.06546390.967268
2470.02194950.0438990.97805
2480.3126740.6253480.687326
2490.3245210.6490430.675479
2500.3778010.7556030.622199
2510.4516370.9032740.548363
2520.9284410.1431190.0715594
2530.8768830.2462330.123117
2540.9592930.08141460.0407073
2550.9323980.1352040.0676018

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.998635 & 0.00272968 & 0.00136484 \tabularnewline
10 & 0.997144 & 0.00571287 & 0.00285644 \tabularnewline
11 & 0.997435 & 0.00513002 & 0.00256501 \tabularnewline
12 & 0.998244 & 0.00351253 & 0.00175626 \tabularnewline
13 & 0.996631 & 0.00673843 & 0.00336921 \tabularnewline
14 & 0.993842 & 0.0123157 & 0.00615785 \tabularnewline
15 & 0.990815 & 0.0183699 & 0.00918494 \tabularnewline
16 & 0.985216 & 0.0295683 & 0.0147842 \tabularnewline
17 & 0.976053 & 0.0478939 & 0.0239469 \tabularnewline
18 & 0.966909 & 0.0661822 & 0.0330911 \tabularnewline
19 & 0.966805 & 0.0663894 & 0.0331947 \tabularnewline
20 & 0.951365 & 0.0972696 & 0.0486348 \tabularnewline
21 & 0.933269 & 0.133462 & 0.0667308 \tabularnewline
22 & 0.913203 & 0.173594 & 0.0867969 \tabularnewline
23 & 0.889315 & 0.22137 & 0.110685 \tabularnewline
24 & 0.855756 & 0.288488 & 0.144244 \tabularnewline
25 & 0.828117 & 0.343766 & 0.171883 \tabularnewline
26 & 0.9416 & 0.1168 & 0.0584 \tabularnewline
27 & 0.923304 & 0.153392 & 0.0766961 \tabularnewline
28 & 0.906914 & 0.186172 & 0.0930858 \tabularnewline
29 & 0.884361 & 0.231279 & 0.115639 \tabularnewline
30 & 0.858275 & 0.28345 & 0.141725 \tabularnewline
31 & 0.867866 & 0.264267 & 0.132134 \tabularnewline
32 & 0.84329 & 0.313421 & 0.15671 \tabularnewline
33 & 0.814621 & 0.370758 & 0.185379 \tabularnewline
34 & 0.787655 & 0.42469 & 0.212345 \tabularnewline
35 & 0.745426 & 0.509147 & 0.254574 \tabularnewline
36 & 0.767087 & 0.465826 & 0.232913 \tabularnewline
37 & 0.823115 & 0.353771 & 0.176885 \tabularnewline
38 & 0.787622 & 0.424757 & 0.212378 \tabularnewline
39 & 0.758287 & 0.483427 & 0.241713 \tabularnewline
40 & 0.761894 & 0.476212 & 0.238106 \tabularnewline
41 & 0.755453 & 0.489095 & 0.244547 \tabularnewline
42 & 0.731878 & 0.536243 & 0.268122 \tabularnewline
43 & 0.740896 & 0.518209 & 0.259104 \tabularnewline
44 & 0.700645 & 0.59871 & 0.299355 \tabularnewline
45 & 0.659105 & 0.681791 & 0.340895 \tabularnewline
46 & 0.637771 & 0.724458 & 0.362229 \tabularnewline
47 & 0.655873 & 0.688254 & 0.344127 \tabularnewline
48 & 0.620628 & 0.758744 & 0.379372 \tabularnewline
49 & 0.660874 & 0.678251 & 0.339126 \tabularnewline
50 & 0.636628 & 0.726745 & 0.363372 \tabularnewline
51 & 0.622212 & 0.755577 & 0.377788 \tabularnewline
52 & 0.585449 & 0.829103 & 0.414551 \tabularnewline
53 & 0.593095 & 0.81381 & 0.406905 \tabularnewline
54 & 0.548696 & 0.902607 & 0.451304 \tabularnewline
55 & 0.560424 & 0.879152 & 0.439576 \tabularnewline
56 & 0.563156 & 0.873688 & 0.436844 \tabularnewline
57 & 0.536683 & 0.926635 & 0.463317 \tabularnewline
58 & 0.564577 & 0.870846 & 0.435423 \tabularnewline
59 & 0.594951 & 0.810098 & 0.405049 \tabularnewline
60 & 0.565201 & 0.869598 & 0.434799 \tabularnewline
61 & 0.591721 & 0.816559 & 0.408279 \tabularnewline
62 & 0.555884 & 0.888232 & 0.444116 \tabularnewline
63 & 0.547576 & 0.904847 & 0.452424 \tabularnewline
64 & 0.508999 & 0.982001 & 0.491001 \tabularnewline
65 & 0.470465 & 0.94093 & 0.529535 \tabularnewline
66 & 0.508066 & 0.983867 & 0.491934 \tabularnewline
67 & 0.514917 & 0.970165 & 0.485083 \tabularnewline
68 & 0.497046 & 0.994092 & 0.502954 \tabularnewline
69 & 0.458868 & 0.917736 & 0.541132 \tabularnewline
70 & 0.435872 & 0.871743 & 0.564128 \tabularnewline
71 & 0.396173 & 0.792347 & 0.603827 \tabularnewline
72 & 0.396899 & 0.793799 & 0.603101 \tabularnewline
73 & 0.361275 & 0.72255 & 0.638725 \tabularnewline
74 & 0.340763 & 0.681527 & 0.659237 \tabularnewline
75 & 0.326903 & 0.653805 & 0.673097 \tabularnewline
76 & 0.441959 & 0.883919 & 0.558041 \tabularnewline
77 & 0.425768 & 0.851536 & 0.574232 \tabularnewline
78 & 0.450384 & 0.900768 & 0.549616 \tabularnewline
79 & 0.411735 & 0.823469 & 0.588265 \tabularnewline
80 & 0.45656 & 0.913121 & 0.54344 \tabularnewline
81 & 0.42715 & 0.854301 & 0.57285 \tabularnewline
82 & 0.439827 & 0.879655 & 0.560173 \tabularnewline
83 & 0.403131 & 0.806263 & 0.596869 \tabularnewline
84 & 0.36699 & 0.733979 & 0.63301 \tabularnewline
85 & 0.331385 & 0.66277 & 0.668615 \tabularnewline
86 & 0.29857 & 0.59714 & 0.70143 \tabularnewline
87 & 0.269275 & 0.538551 & 0.730725 \tabularnewline
88 & 0.245541 & 0.491083 & 0.754459 \tabularnewline
89 & 0.308984 & 0.617968 & 0.691016 \tabularnewline
90 & 0.285102 & 0.570203 & 0.714898 \tabularnewline
91 & 0.26819 & 0.536381 & 0.73181 \tabularnewline
92 & 0.239617 & 0.479234 & 0.760383 \tabularnewline
93 & 0.225116 & 0.450231 & 0.774884 \tabularnewline
94 & 0.206315 & 0.41263 & 0.793685 \tabularnewline
95 & 0.180873 & 0.361746 & 0.819127 \tabularnewline
96 & 0.16952 & 0.33904 & 0.83048 \tabularnewline
97 & 0.157473 & 0.314945 & 0.842527 \tabularnewline
98 & 0.136138 & 0.272276 & 0.863862 \tabularnewline
99 & 0.133309 & 0.266619 & 0.866691 \tabularnewline
100 & 0.115294 & 0.230589 & 0.884706 \tabularnewline
101 & 0.106182 & 0.212363 & 0.893818 \tabularnewline
102 & 0.0914001 & 0.1828 & 0.9086 \tabularnewline
103 & 0.110952 & 0.221904 & 0.889048 \tabularnewline
104 & 0.122174 & 0.244347 & 0.877826 \tabularnewline
105 & 0.125536 & 0.251071 & 0.874464 \tabularnewline
106 & 0.107731 & 0.215462 & 0.892269 \tabularnewline
107 & 0.124905 & 0.249811 & 0.875095 \tabularnewline
108 & 0.108989 & 0.217977 & 0.891011 \tabularnewline
109 & 0.251141 & 0.502281 & 0.748859 \tabularnewline
110 & 0.233881 & 0.467763 & 0.766119 \tabularnewline
111 & 0.208382 & 0.416763 & 0.791618 \tabularnewline
112 & 0.212304 & 0.424609 & 0.787696 \tabularnewline
113 & 0.196431 & 0.392862 & 0.803569 \tabularnewline
114 & 0.180206 & 0.360412 & 0.819794 \tabularnewline
115 & 0.160817 & 0.321634 & 0.839183 \tabularnewline
116 & 0.141314 & 0.282628 & 0.858686 \tabularnewline
117 & 0.123494 & 0.246987 & 0.876506 \tabularnewline
118 & 0.150832 & 0.301663 & 0.849168 \tabularnewline
119 & 0.141107 & 0.282215 & 0.858893 \tabularnewline
120 & 0.121956 & 0.243911 & 0.878044 \tabularnewline
121 & 0.109812 & 0.219624 & 0.890188 \tabularnewline
122 & 0.0992671 & 0.198534 & 0.900733 \tabularnewline
123 & 0.119355 & 0.23871 & 0.880645 \tabularnewline
124 & 0.105333 & 0.210666 & 0.894667 \tabularnewline
125 & 0.103645 & 0.20729 & 0.896355 \tabularnewline
126 & 0.103994 & 0.207988 & 0.896006 \tabularnewline
127 & 0.0900708 & 0.180142 & 0.909929 \tabularnewline
128 & 0.0804302 & 0.16086 & 0.91957 \tabularnewline
129 & 0.0681789 & 0.136358 & 0.931821 \tabularnewline
130 & 0.068691 & 0.137382 & 0.931309 \tabularnewline
131 & 0.067838 & 0.135676 & 0.932162 \tabularnewline
132 & 0.0641364 & 0.128273 & 0.935864 \tabularnewline
133 & 0.0600512 & 0.120102 & 0.939949 \tabularnewline
134 & 0.0503968 & 0.100794 & 0.949603 \tabularnewline
135 & 0.0479731 & 0.0959463 & 0.952027 \tabularnewline
136 & 0.118737 & 0.237474 & 0.881263 \tabularnewline
137 & 0.103257 & 0.206515 & 0.896743 \tabularnewline
138 & 0.0880936 & 0.176187 & 0.911906 \tabularnewline
139 & 0.0799913 & 0.159983 & 0.920009 \tabularnewline
140 & 0.0769262 & 0.153852 & 0.923074 \tabularnewline
141 & 0.0737626 & 0.147525 & 0.926237 \tabularnewline
142 & 0.0687445 & 0.137489 & 0.931255 \tabularnewline
143 & 0.059136 & 0.118272 & 0.940864 \tabularnewline
144 & 0.0498576 & 0.0997151 & 0.950142 \tabularnewline
145 & 0.0424517 & 0.0849034 & 0.957548 \tabularnewline
146 & 0.0353577 & 0.0707154 & 0.964642 \tabularnewline
147 & 0.0339663 & 0.0679327 & 0.966034 \tabularnewline
148 & 0.0393897 & 0.0787793 & 0.96061 \tabularnewline
149 & 0.0352772 & 0.0705544 & 0.964723 \tabularnewline
150 & 0.0290809 & 0.0581618 & 0.970919 \tabularnewline
151 & 0.0314449 & 0.0628898 & 0.968555 \tabularnewline
152 & 0.0302615 & 0.060523 & 0.969738 \tabularnewline
153 & 0.0294888 & 0.0589775 & 0.970511 \tabularnewline
154 & 0.0265714 & 0.0531428 & 0.973429 \tabularnewline
155 & 0.0293605 & 0.0587211 & 0.970639 \tabularnewline
156 & 0.0249793 & 0.0499585 & 0.975021 \tabularnewline
157 & 0.0202828 & 0.0405657 & 0.979717 \tabularnewline
158 & 0.0174109 & 0.0348217 & 0.982589 \tabularnewline
159 & 0.0271469 & 0.0542939 & 0.972853 \tabularnewline
160 & 0.0276495 & 0.055299 & 0.972351 \tabularnewline
161 & 0.0244101 & 0.0488201 & 0.97559 \tabularnewline
162 & 0.0659024 & 0.131805 & 0.934098 \tabularnewline
163 & 0.0550763 & 0.110153 & 0.944924 \tabularnewline
164 & 0.196731 & 0.393463 & 0.803269 \tabularnewline
165 & 0.180426 & 0.360853 & 0.819574 \tabularnewline
166 & 0.303782 & 0.607564 & 0.696218 \tabularnewline
167 & 0.279589 & 0.559179 & 0.720411 \tabularnewline
168 & 0.256534 & 0.513068 & 0.743466 \tabularnewline
169 & 0.232334 & 0.464668 & 0.767666 \tabularnewline
170 & 0.207191 & 0.414382 & 0.792809 \tabularnewline
171 & 0.234257 & 0.468513 & 0.765743 \tabularnewline
172 & 0.207545 & 0.41509 & 0.792455 \tabularnewline
173 & 0.275986 & 0.551971 & 0.724014 \tabularnewline
174 & 0.268495 & 0.53699 & 0.731505 \tabularnewline
175 & 0.245386 & 0.490772 & 0.754614 \tabularnewline
176 & 0.315935 & 0.631871 & 0.684065 \tabularnewline
177 & 0.291637 & 0.583274 & 0.708363 \tabularnewline
178 & 0.292319 & 0.584638 & 0.707681 \tabularnewline
179 & 0.272477 & 0.544954 & 0.727523 \tabularnewline
180 & 0.254116 & 0.508231 & 0.745884 \tabularnewline
181 & 0.242687 & 0.485374 & 0.757313 \tabularnewline
182 & 0.324696 & 0.649393 & 0.675304 \tabularnewline
183 & 0.299299 & 0.598598 & 0.700701 \tabularnewline
184 & 0.313013 & 0.626026 & 0.686987 \tabularnewline
185 & 0.289382 & 0.578764 & 0.710618 \tabularnewline
186 & 0.355665 & 0.711329 & 0.644335 \tabularnewline
187 & 0.322087 & 0.644173 & 0.677913 \tabularnewline
188 & 0.290625 & 0.581249 & 0.709375 \tabularnewline
189 & 0.258929 & 0.517857 & 0.741071 \tabularnewline
190 & 0.337681 & 0.675362 & 0.662319 \tabularnewline
191 & 0.333693 & 0.667386 & 0.666307 \tabularnewline
192 & 0.351499 & 0.702997 & 0.648501 \tabularnewline
193 & 0.350998 & 0.701996 & 0.649002 \tabularnewline
194 & 0.315355 & 0.63071 & 0.684645 \tabularnewline
195 & 0.288276 & 0.576552 & 0.711724 \tabularnewline
196 & 0.30166 & 0.603321 & 0.69834 \tabularnewline
197 & 0.413745 & 0.827489 & 0.586255 \tabularnewline
198 & 0.384883 & 0.769767 & 0.615117 \tabularnewline
199 & 0.347852 & 0.695705 & 0.652148 \tabularnewline
200 & 0.317116 & 0.634233 & 0.682884 \tabularnewline
201 & 0.284696 & 0.569391 & 0.715304 \tabularnewline
202 & 0.252005 & 0.50401 & 0.747995 \tabularnewline
203 & 0.220432 & 0.440864 & 0.779568 \tabularnewline
204 & 0.191622 & 0.383244 & 0.808378 \tabularnewline
205 & 0.16895 & 0.3379 & 0.83105 \tabularnewline
206 & 0.143518 & 0.287037 & 0.856482 \tabularnewline
207 & 0.126697 & 0.253394 & 0.873303 \tabularnewline
208 & 0.129764 & 0.259528 & 0.870236 \tabularnewline
209 & 0.108273 & 0.216545 & 0.891727 \tabularnewline
210 & 0.0894589 & 0.178918 & 0.910541 \tabularnewline
211 & 0.0757677 & 0.151535 & 0.924232 \tabularnewline
212 & 0.0633336 & 0.126667 & 0.936666 \tabularnewline
213 & 0.0558444 & 0.111689 & 0.944156 \tabularnewline
214 & 0.0612384 & 0.122477 & 0.938762 \tabularnewline
215 & 0.0498909 & 0.0997817 & 0.950109 \tabularnewline
216 & 0.0396381 & 0.0792761 & 0.960362 \tabularnewline
217 & 0.0307724 & 0.0615448 & 0.969228 \tabularnewline
218 & 0.0252813 & 0.0505627 & 0.974719 \tabularnewline
219 & 0.0279123 & 0.0558246 & 0.972088 \tabularnewline
220 & 0.0222469 & 0.0444939 & 0.977753 \tabularnewline
221 & 0.0312001 & 0.0624003 & 0.9688 \tabularnewline
222 & 0.023645 & 0.0472901 & 0.976355 \tabularnewline
223 & 0.0179834 & 0.0359669 & 0.982017 \tabularnewline
224 & 0.019868 & 0.039736 & 0.980132 \tabularnewline
225 & 0.0216165 & 0.043233 & 0.978384 \tabularnewline
226 & 0.0172453 & 0.0344905 & 0.982755 \tabularnewline
227 & 0.0138569 & 0.0277139 & 0.986143 \tabularnewline
228 & 0.0133278 & 0.0266556 & 0.986672 \tabularnewline
229 & 0.0189408 & 0.0378815 & 0.981059 \tabularnewline
230 & 0.0179983 & 0.0359966 & 0.982002 \tabularnewline
231 & 0.0132937 & 0.0265874 & 0.986706 \tabularnewline
232 & 0.0107687 & 0.0215374 & 0.989231 \tabularnewline
233 & 0.0104559 & 0.0209118 & 0.989544 \tabularnewline
234 & 0.00861548 & 0.017231 & 0.991385 \tabularnewline
235 & 0.00897772 & 0.0179554 & 0.991022 \tabularnewline
236 & 0.00732488 & 0.0146498 & 0.992675 \tabularnewline
237 & 0.00578109 & 0.0115622 & 0.994219 \tabularnewline
238 & 0.00464556 & 0.00929112 & 0.995354 \tabularnewline
239 & 0.022439 & 0.044878 & 0.977561 \tabularnewline
240 & 0.0302544 & 0.0605088 & 0.969746 \tabularnewline
241 & 0.0554987 & 0.110997 & 0.944501 \tabularnewline
242 & 0.0427957 & 0.0855915 & 0.957204 \tabularnewline
243 & 0.0402677 & 0.0805355 & 0.959732 \tabularnewline
244 & 0.0312603 & 0.0625206 & 0.96874 \tabularnewline
245 & 0.0206899 & 0.0413797 & 0.97931 \tabularnewline
246 & 0.0327319 & 0.0654639 & 0.967268 \tabularnewline
247 & 0.0219495 & 0.043899 & 0.97805 \tabularnewline
248 & 0.312674 & 0.625348 & 0.687326 \tabularnewline
249 & 0.324521 & 0.649043 & 0.675479 \tabularnewline
250 & 0.377801 & 0.755603 & 0.622199 \tabularnewline
251 & 0.451637 & 0.903274 & 0.548363 \tabularnewline
252 & 0.928441 & 0.143119 & 0.0715594 \tabularnewline
253 & 0.876883 & 0.246233 & 0.123117 \tabularnewline
254 & 0.959293 & 0.0814146 & 0.0407073 \tabularnewline
255 & 0.932398 & 0.135204 & 0.0676018 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221846&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]0.998635[/C][C]0.00272968[/C][C]0.00136484[/C][/ROW]
[ROW][C]10[/C][C]0.997144[/C][C]0.00571287[/C][C]0.00285644[/C][/ROW]
[ROW][C]11[/C][C]0.997435[/C][C]0.00513002[/C][C]0.00256501[/C][/ROW]
[ROW][C]12[/C][C]0.998244[/C][C]0.00351253[/C][C]0.00175626[/C][/ROW]
[ROW][C]13[/C][C]0.996631[/C][C]0.00673843[/C][C]0.00336921[/C][/ROW]
[ROW][C]14[/C][C]0.993842[/C][C]0.0123157[/C][C]0.00615785[/C][/ROW]
[ROW][C]15[/C][C]0.990815[/C][C]0.0183699[/C][C]0.00918494[/C][/ROW]
[ROW][C]16[/C][C]0.985216[/C][C]0.0295683[/C][C]0.0147842[/C][/ROW]
[ROW][C]17[/C][C]0.976053[/C][C]0.0478939[/C][C]0.0239469[/C][/ROW]
[ROW][C]18[/C][C]0.966909[/C][C]0.0661822[/C][C]0.0330911[/C][/ROW]
[ROW][C]19[/C][C]0.966805[/C][C]0.0663894[/C][C]0.0331947[/C][/ROW]
[ROW][C]20[/C][C]0.951365[/C][C]0.0972696[/C][C]0.0486348[/C][/ROW]
[ROW][C]21[/C][C]0.933269[/C][C]0.133462[/C][C]0.0667308[/C][/ROW]
[ROW][C]22[/C][C]0.913203[/C][C]0.173594[/C][C]0.0867969[/C][/ROW]
[ROW][C]23[/C][C]0.889315[/C][C]0.22137[/C][C]0.110685[/C][/ROW]
[ROW][C]24[/C][C]0.855756[/C][C]0.288488[/C][C]0.144244[/C][/ROW]
[ROW][C]25[/C][C]0.828117[/C][C]0.343766[/C][C]0.171883[/C][/ROW]
[ROW][C]26[/C][C]0.9416[/C][C]0.1168[/C][C]0.0584[/C][/ROW]
[ROW][C]27[/C][C]0.923304[/C][C]0.153392[/C][C]0.0766961[/C][/ROW]
[ROW][C]28[/C][C]0.906914[/C][C]0.186172[/C][C]0.0930858[/C][/ROW]
[ROW][C]29[/C][C]0.884361[/C][C]0.231279[/C][C]0.115639[/C][/ROW]
[ROW][C]30[/C][C]0.858275[/C][C]0.28345[/C][C]0.141725[/C][/ROW]
[ROW][C]31[/C][C]0.867866[/C][C]0.264267[/C][C]0.132134[/C][/ROW]
[ROW][C]32[/C][C]0.84329[/C][C]0.313421[/C][C]0.15671[/C][/ROW]
[ROW][C]33[/C][C]0.814621[/C][C]0.370758[/C][C]0.185379[/C][/ROW]
[ROW][C]34[/C][C]0.787655[/C][C]0.42469[/C][C]0.212345[/C][/ROW]
[ROW][C]35[/C][C]0.745426[/C][C]0.509147[/C][C]0.254574[/C][/ROW]
[ROW][C]36[/C][C]0.767087[/C][C]0.465826[/C][C]0.232913[/C][/ROW]
[ROW][C]37[/C][C]0.823115[/C][C]0.353771[/C][C]0.176885[/C][/ROW]
[ROW][C]38[/C][C]0.787622[/C][C]0.424757[/C][C]0.212378[/C][/ROW]
[ROW][C]39[/C][C]0.758287[/C][C]0.483427[/C][C]0.241713[/C][/ROW]
[ROW][C]40[/C][C]0.761894[/C][C]0.476212[/C][C]0.238106[/C][/ROW]
[ROW][C]41[/C][C]0.755453[/C][C]0.489095[/C][C]0.244547[/C][/ROW]
[ROW][C]42[/C][C]0.731878[/C][C]0.536243[/C][C]0.268122[/C][/ROW]
[ROW][C]43[/C][C]0.740896[/C][C]0.518209[/C][C]0.259104[/C][/ROW]
[ROW][C]44[/C][C]0.700645[/C][C]0.59871[/C][C]0.299355[/C][/ROW]
[ROW][C]45[/C][C]0.659105[/C][C]0.681791[/C][C]0.340895[/C][/ROW]
[ROW][C]46[/C][C]0.637771[/C][C]0.724458[/C][C]0.362229[/C][/ROW]
[ROW][C]47[/C][C]0.655873[/C][C]0.688254[/C][C]0.344127[/C][/ROW]
[ROW][C]48[/C][C]0.620628[/C][C]0.758744[/C][C]0.379372[/C][/ROW]
[ROW][C]49[/C][C]0.660874[/C][C]0.678251[/C][C]0.339126[/C][/ROW]
[ROW][C]50[/C][C]0.636628[/C][C]0.726745[/C][C]0.363372[/C][/ROW]
[ROW][C]51[/C][C]0.622212[/C][C]0.755577[/C][C]0.377788[/C][/ROW]
[ROW][C]52[/C][C]0.585449[/C][C]0.829103[/C][C]0.414551[/C][/ROW]
[ROW][C]53[/C][C]0.593095[/C][C]0.81381[/C][C]0.406905[/C][/ROW]
[ROW][C]54[/C][C]0.548696[/C][C]0.902607[/C][C]0.451304[/C][/ROW]
[ROW][C]55[/C][C]0.560424[/C][C]0.879152[/C][C]0.439576[/C][/ROW]
[ROW][C]56[/C][C]0.563156[/C][C]0.873688[/C][C]0.436844[/C][/ROW]
[ROW][C]57[/C][C]0.536683[/C][C]0.926635[/C][C]0.463317[/C][/ROW]
[ROW][C]58[/C][C]0.564577[/C][C]0.870846[/C][C]0.435423[/C][/ROW]
[ROW][C]59[/C][C]0.594951[/C][C]0.810098[/C][C]0.405049[/C][/ROW]
[ROW][C]60[/C][C]0.565201[/C][C]0.869598[/C][C]0.434799[/C][/ROW]
[ROW][C]61[/C][C]0.591721[/C][C]0.816559[/C][C]0.408279[/C][/ROW]
[ROW][C]62[/C][C]0.555884[/C][C]0.888232[/C][C]0.444116[/C][/ROW]
[ROW][C]63[/C][C]0.547576[/C][C]0.904847[/C][C]0.452424[/C][/ROW]
[ROW][C]64[/C][C]0.508999[/C][C]0.982001[/C][C]0.491001[/C][/ROW]
[ROW][C]65[/C][C]0.470465[/C][C]0.94093[/C][C]0.529535[/C][/ROW]
[ROW][C]66[/C][C]0.508066[/C][C]0.983867[/C][C]0.491934[/C][/ROW]
[ROW][C]67[/C][C]0.514917[/C][C]0.970165[/C][C]0.485083[/C][/ROW]
[ROW][C]68[/C][C]0.497046[/C][C]0.994092[/C][C]0.502954[/C][/ROW]
[ROW][C]69[/C][C]0.458868[/C][C]0.917736[/C][C]0.541132[/C][/ROW]
[ROW][C]70[/C][C]0.435872[/C][C]0.871743[/C][C]0.564128[/C][/ROW]
[ROW][C]71[/C][C]0.396173[/C][C]0.792347[/C][C]0.603827[/C][/ROW]
[ROW][C]72[/C][C]0.396899[/C][C]0.793799[/C][C]0.603101[/C][/ROW]
[ROW][C]73[/C][C]0.361275[/C][C]0.72255[/C][C]0.638725[/C][/ROW]
[ROW][C]74[/C][C]0.340763[/C][C]0.681527[/C][C]0.659237[/C][/ROW]
[ROW][C]75[/C][C]0.326903[/C][C]0.653805[/C][C]0.673097[/C][/ROW]
[ROW][C]76[/C][C]0.441959[/C][C]0.883919[/C][C]0.558041[/C][/ROW]
[ROW][C]77[/C][C]0.425768[/C][C]0.851536[/C][C]0.574232[/C][/ROW]
[ROW][C]78[/C][C]0.450384[/C][C]0.900768[/C][C]0.549616[/C][/ROW]
[ROW][C]79[/C][C]0.411735[/C][C]0.823469[/C][C]0.588265[/C][/ROW]
[ROW][C]80[/C][C]0.45656[/C][C]0.913121[/C][C]0.54344[/C][/ROW]
[ROW][C]81[/C][C]0.42715[/C][C]0.854301[/C][C]0.57285[/C][/ROW]
[ROW][C]82[/C][C]0.439827[/C][C]0.879655[/C][C]0.560173[/C][/ROW]
[ROW][C]83[/C][C]0.403131[/C][C]0.806263[/C][C]0.596869[/C][/ROW]
[ROW][C]84[/C][C]0.36699[/C][C]0.733979[/C][C]0.63301[/C][/ROW]
[ROW][C]85[/C][C]0.331385[/C][C]0.66277[/C][C]0.668615[/C][/ROW]
[ROW][C]86[/C][C]0.29857[/C][C]0.59714[/C][C]0.70143[/C][/ROW]
[ROW][C]87[/C][C]0.269275[/C][C]0.538551[/C][C]0.730725[/C][/ROW]
[ROW][C]88[/C][C]0.245541[/C][C]0.491083[/C][C]0.754459[/C][/ROW]
[ROW][C]89[/C][C]0.308984[/C][C]0.617968[/C][C]0.691016[/C][/ROW]
[ROW][C]90[/C][C]0.285102[/C][C]0.570203[/C][C]0.714898[/C][/ROW]
[ROW][C]91[/C][C]0.26819[/C][C]0.536381[/C][C]0.73181[/C][/ROW]
[ROW][C]92[/C][C]0.239617[/C][C]0.479234[/C][C]0.760383[/C][/ROW]
[ROW][C]93[/C][C]0.225116[/C][C]0.450231[/C][C]0.774884[/C][/ROW]
[ROW][C]94[/C][C]0.206315[/C][C]0.41263[/C][C]0.793685[/C][/ROW]
[ROW][C]95[/C][C]0.180873[/C][C]0.361746[/C][C]0.819127[/C][/ROW]
[ROW][C]96[/C][C]0.16952[/C][C]0.33904[/C][C]0.83048[/C][/ROW]
[ROW][C]97[/C][C]0.157473[/C][C]0.314945[/C][C]0.842527[/C][/ROW]
[ROW][C]98[/C][C]0.136138[/C][C]0.272276[/C][C]0.863862[/C][/ROW]
[ROW][C]99[/C][C]0.133309[/C][C]0.266619[/C][C]0.866691[/C][/ROW]
[ROW][C]100[/C][C]0.115294[/C][C]0.230589[/C][C]0.884706[/C][/ROW]
[ROW][C]101[/C][C]0.106182[/C][C]0.212363[/C][C]0.893818[/C][/ROW]
[ROW][C]102[/C][C]0.0914001[/C][C]0.1828[/C][C]0.9086[/C][/ROW]
[ROW][C]103[/C][C]0.110952[/C][C]0.221904[/C][C]0.889048[/C][/ROW]
[ROW][C]104[/C][C]0.122174[/C][C]0.244347[/C][C]0.877826[/C][/ROW]
[ROW][C]105[/C][C]0.125536[/C][C]0.251071[/C][C]0.874464[/C][/ROW]
[ROW][C]106[/C][C]0.107731[/C][C]0.215462[/C][C]0.892269[/C][/ROW]
[ROW][C]107[/C][C]0.124905[/C][C]0.249811[/C][C]0.875095[/C][/ROW]
[ROW][C]108[/C][C]0.108989[/C][C]0.217977[/C][C]0.891011[/C][/ROW]
[ROW][C]109[/C][C]0.251141[/C][C]0.502281[/C][C]0.748859[/C][/ROW]
[ROW][C]110[/C][C]0.233881[/C][C]0.467763[/C][C]0.766119[/C][/ROW]
[ROW][C]111[/C][C]0.208382[/C][C]0.416763[/C][C]0.791618[/C][/ROW]
[ROW][C]112[/C][C]0.212304[/C][C]0.424609[/C][C]0.787696[/C][/ROW]
[ROW][C]113[/C][C]0.196431[/C][C]0.392862[/C][C]0.803569[/C][/ROW]
[ROW][C]114[/C][C]0.180206[/C][C]0.360412[/C][C]0.819794[/C][/ROW]
[ROW][C]115[/C][C]0.160817[/C][C]0.321634[/C][C]0.839183[/C][/ROW]
[ROW][C]116[/C][C]0.141314[/C][C]0.282628[/C][C]0.858686[/C][/ROW]
[ROW][C]117[/C][C]0.123494[/C][C]0.246987[/C][C]0.876506[/C][/ROW]
[ROW][C]118[/C][C]0.150832[/C][C]0.301663[/C][C]0.849168[/C][/ROW]
[ROW][C]119[/C][C]0.141107[/C][C]0.282215[/C][C]0.858893[/C][/ROW]
[ROW][C]120[/C][C]0.121956[/C][C]0.243911[/C][C]0.878044[/C][/ROW]
[ROW][C]121[/C][C]0.109812[/C][C]0.219624[/C][C]0.890188[/C][/ROW]
[ROW][C]122[/C][C]0.0992671[/C][C]0.198534[/C][C]0.900733[/C][/ROW]
[ROW][C]123[/C][C]0.119355[/C][C]0.23871[/C][C]0.880645[/C][/ROW]
[ROW][C]124[/C][C]0.105333[/C][C]0.210666[/C][C]0.894667[/C][/ROW]
[ROW][C]125[/C][C]0.103645[/C][C]0.20729[/C][C]0.896355[/C][/ROW]
[ROW][C]126[/C][C]0.103994[/C][C]0.207988[/C][C]0.896006[/C][/ROW]
[ROW][C]127[/C][C]0.0900708[/C][C]0.180142[/C][C]0.909929[/C][/ROW]
[ROW][C]128[/C][C]0.0804302[/C][C]0.16086[/C][C]0.91957[/C][/ROW]
[ROW][C]129[/C][C]0.0681789[/C][C]0.136358[/C][C]0.931821[/C][/ROW]
[ROW][C]130[/C][C]0.068691[/C][C]0.137382[/C][C]0.931309[/C][/ROW]
[ROW][C]131[/C][C]0.067838[/C][C]0.135676[/C][C]0.932162[/C][/ROW]
[ROW][C]132[/C][C]0.0641364[/C][C]0.128273[/C][C]0.935864[/C][/ROW]
[ROW][C]133[/C][C]0.0600512[/C][C]0.120102[/C][C]0.939949[/C][/ROW]
[ROW][C]134[/C][C]0.0503968[/C][C]0.100794[/C][C]0.949603[/C][/ROW]
[ROW][C]135[/C][C]0.0479731[/C][C]0.0959463[/C][C]0.952027[/C][/ROW]
[ROW][C]136[/C][C]0.118737[/C][C]0.237474[/C][C]0.881263[/C][/ROW]
[ROW][C]137[/C][C]0.103257[/C][C]0.206515[/C][C]0.896743[/C][/ROW]
[ROW][C]138[/C][C]0.0880936[/C][C]0.176187[/C][C]0.911906[/C][/ROW]
[ROW][C]139[/C][C]0.0799913[/C][C]0.159983[/C][C]0.920009[/C][/ROW]
[ROW][C]140[/C][C]0.0769262[/C][C]0.153852[/C][C]0.923074[/C][/ROW]
[ROW][C]141[/C][C]0.0737626[/C][C]0.147525[/C][C]0.926237[/C][/ROW]
[ROW][C]142[/C][C]0.0687445[/C][C]0.137489[/C][C]0.931255[/C][/ROW]
[ROW][C]143[/C][C]0.059136[/C][C]0.118272[/C][C]0.940864[/C][/ROW]
[ROW][C]144[/C][C]0.0498576[/C][C]0.0997151[/C][C]0.950142[/C][/ROW]
[ROW][C]145[/C][C]0.0424517[/C][C]0.0849034[/C][C]0.957548[/C][/ROW]
[ROW][C]146[/C][C]0.0353577[/C][C]0.0707154[/C][C]0.964642[/C][/ROW]
[ROW][C]147[/C][C]0.0339663[/C][C]0.0679327[/C][C]0.966034[/C][/ROW]
[ROW][C]148[/C][C]0.0393897[/C][C]0.0787793[/C][C]0.96061[/C][/ROW]
[ROW][C]149[/C][C]0.0352772[/C][C]0.0705544[/C][C]0.964723[/C][/ROW]
[ROW][C]150[/C][C]0.0290809[/C][C]0.0581618[/C][C]0.970919[/C][/ROW]
[ROW][C]151[/C][C]0.0314449[/C][C]0.0628898[/C][C]0.968555[/C][/ROW]
[ROW][C]152[/C][C]0.0302615[/C][C]0.060523[/C][C]0.969738[/C][/ROW]
[ROW][C]153[/C][C]0.0294888[/C][C]0.0589775[/C][C]0.970511[/C][/ROW]
[ROW][C]154[/C][C]0.0265714[/C][C]0.0531428[/C][C]0.973429[/C][/ROW]
[ROW][C]155[/C][C]0.0293605[/C][C]0.0587211[/C][C]0.970639[/C][/ROW]
[ROW][C]156[/C][C]0.0249793[/C][C]0.0499585[/C][C]0.975021[/C][/ROW]
[ROW][C]157[/C][C]0.0202828[/C][C]0.0405657[/C][C]0.979717[/C][/ROW]
[ROW][C]158[/C][C]0.0174109[/C][C]0.0348217[/C][C]0.982589[/C][/ROW]
[ROW][C]159[/C][C]0.0271469[/C][C]0.0542939[/C][C]0.972853[/C][/ROW]
[ROW][C]160[/C][C]0.0276495[/C][C]0.055299[/C][C]0.972351[/C][/ROW]
[ROW][C]161[/C][C]0.0244101[/C][C]0.0488201[/C][C]0.97559[/C][/ROW]
[ROW][C]162[/C][C]0.0659024[/C][C]0.131805[/C][C]0.934098[/C][/ROW]
[ROW][C]163[/C][C]0.0550763[/C][C]0.110153[/C][C]0.944924[/C][/ROW]
[ROW][C]164[/C][C]0.196731[/C][C]0.393463[/C][C]0.803269[/C][/ROW]
[ROW][C]165[/C][C]0.180426[/C][C]0.360853[/C][C]0.819574[/C][/ROW]
[ROW][C]166[/C][C]0.303782[/C][C]0.607564[/C][C]0.696218[/C][/ROW]
[ROW][C]167[/C][C]0.279589[/C][C]0.559179[/C][C]0.720411[/C][/ROW]
[ROW][C]168[/C][C]0.256534[/C][C]0.513068[/C][C]0.743466[/C][/ROW]
[ROW][C]169[/C][C]0.232334[/C][C]0.464668[/C][C]0.767666[/C][/ROW]
[ROW][C]170[/C][C]0.207191[/C][C]0.414382[/C][C]0.792809[/C][/ROW]
[ROW][C]171[/C][C]0.234257[/C][C]0.468513[/C][C]0.765743[/C][/ROW]
[ROW][C]172[/C][C]0.207545[/C][C]0.41509[/C][C]0.792455[/C][/ROW]
[ROW][C]173[/C][C]0.275986[/C][C]0.551971[/C][C]0.724014[/C][/ROW]
[ROW][C]174[/C][C]0.268495[/C][C]0.53699[/C][C]0.731505[/C][/ROW]
[ROW][C]175[/C][C]0.245386[/C][C]0.490772[/C][C]0.754614[/C][/ROW]
[ROW][C]176[/C][C]0.315935[/C][C]0.631871[/C][C]0.684065[/C][/ROW]
[ROW][C]177[/C][C]0.291637[/C][C]0.583274[/C][C]0.708363[/C][/ROW]
[ROW][C]178[/C][C]0.292319[/C][C]0.584638[/C][C]0.707681[/C][/ROW]
[ROW][C]179[/C][C]0.272477[/C][C]0.544954[/C][C]0.727523[/C][/ROW]
[ROW][C]180[/C][C]0.254116[/C][C]0.508231[/C][C]0.745884[/C][/ROW]
[ROW][C]181[/C][C]0.242687[/C][C]0.485374[/C][C]0.757313[/C][/ROW]
[ROW][C]182[/C][C]0.324696[/C][C]0.649393[/C][C]0.675304[/C][/ROW]
[ROW][C]183[/C][C]0.299299[/C][C]0.598598[/C][C]0.700701[/C][/ROW]
[ROW][C]184[/C][C]0.313013[/C][C]0.626026[/C][C]0.686987[/C][/ROW]
[ROW][C]185[/C][C]0.289382[/C][C]0.578764[/C][C]0.710618[/C][/ROW]
[ROW][C]186[/C][C]0.355665[/C][C]0.711329[/C][C]0.644335[/C][/ROW]
[ROW][C]187[/C][C]0.322087[/C][C]0.644173[/C][C]0.677913[/C][/ROW]
[ROW][C]188[/C][C]0.290625[/C][C]0.581249[/C][C]0.709375[/C][/ROW]
[ROW][C]189[/C][C]0.258929[/C][C]0.517857[/C][C]0.741071[/C][/ROW]
[ROW][C]190[/C][C]0.337681[/C][C]0.675362[/C][C]0.662319[/C][/ROW]
[ROW][C]191[/C][C]0.333693[/C][C]0.667386[/C][C]0.666307[/C][/ROW]
[ROW][C]192[/C][C]0.351499[/C][C]0.702997[/C][C]0.648501[/C][/ROW]
[ROW][C]193[/C][C]0.350998[/C][C]0.701996[/C][C]0.649002[/C][/ROW]
[ROW][C]194[/C][C]0.315355[/C][C]0.63071[/C][C]0.684645[/C][/ROW]
[ROW][C]195[/C][C]0.288276[/C][C]0.576552[/C][C]0.711724[/C][/ROW]
[ROW][C]196[/C][C]0.30166[/C][C]0.603321[/C][C]0.69834[/C][/ROW]
[ROW][C]197[/C][C]0.413745[/C][C]0.827489[/C][C]0.586255[/C][/ROW]
[ROW][C]198[/C][C]0.384883[/C][C]0.769767[/C][C]0.615117[/C][/ROW]
[ROW][C]199[/C][C]0.347852[/C][C]0.695705[/C][C]0.652148[/C][/ROW]
[ROW][C]200[/C][C]0.317116[/C][C]0.634233[/C][C]0.682884[/C][/ROW]
[ROW][C]201[/C][C]0.284696[/C][C]0.569391[/C][C]0.715304[/C][/ROW]
[ROW][C]202[/C][C]0.252005[/C][C]0.50401[/C][C]0.747995[/C][/ROW]
[ROW][C]203[/C][C]0.220432[/C][C]0.440864[/C][C]0.779568[/C][/ROW]
[ROW][C]204[/C][C]0.191622[/C][C]0.383244[/C][C]0.808378[/C][/ROW]
[ROW][C]205[/C][C]0.16895[/C][C]0.3379[/C][C]0.83105[/C][/ROW]
[ROW][C]206[/C][C]0.143518[/C][C]0.287037[/C][C]0.856482[/C][/ROW]
[ROW][C]207[/C][C]0.126697[/C][C]0.253394[/C][C]0.873303[/C][/ROW]
[ROW][C]208[/C][C]0.129764[/C][C]0.259528[/C][C]0.870236[/C][/ROW]
[ROW][C]209[/C][C]0.108273[/C][C]0.216545[/C][C]0.891727[/C][/ROW]
[ROW][C]210[/C][C]0.0894589[/C][C]0.178918[/C][C]0.910541[/C][/ROW]
[ROW][C]211[/C][C]0.0757677[/C][C]0.151535[/C][C]0.924232[/C][/ROW]
[ROW][C]212[/C][C]0.0633336[/C][C]0.126667[/C][C]0.936666[/C][/ROW]
[ROW][C]213[/C][C]0.0558444[/C][C]0.111689[/C][C]0.944156[/C][/ROW]
[ROW][C]214[/C][C]0.0612384[/C][C]0.122477[/C][C]0.938762[/C][/ROW]
[ROW][C]215[/C][C]0.0498909[/C][C]0.0997817[/C][C]0.950109[/C][/ROW]
[ROW][C]216[/C][C]0.0396381[/C][C]0.0792761[/C][C]0.960362[/C][/ROW]
[ROW][C]217[/C][C]0.0307724[/C][C]0.0615448[/C][C]0.969228[/C][/ROW]
[ROW][C]218[/C][C]0.0252813[/C][C]0.0505627[/C][C]0.974719[/C][/ROW]
[ROW][C]219[/C][C]0.0279123[/C][C]0.0558246[/C][C]0.972088[/C][/ROW]
[ROW][C]220[/C][C]0.0222469[/C][C]0.0444939[/C][C]0.977753[/C][/ROW]
[ROW][C]221[/C][C]0.0312001[/C][C]0.0624003[/C][C]0.9688[/C][/ROW]
[ROW][C]222[/C][C]0.023645[/C][C]0.0472901[/C][C]0.976355[/C][/ROW]
[ROW][C]223[/C][C]0.0179834[/C][C]0.0359669[/C][C]0.982017[/C][/ROW]
[ROW][C]224[/C][C]0.019868[/C][C]0.039736[/C][C]0.980132[/C][/ROW]
[ROW][C]225[/C][C]0.0216165[/C][C]0.043233[/C][C]0.978384[/C][/ROW]
[ROW][C]226[/C][C]0.0172453[/C][C]0.0344905[/C][C]0.982755[/C][/ROW]
[ROW][C]227[/C][C]0.0138569[/C][C]0.0277139[/C][C]0.986143[/C][/ROW]
[ROW][C]228[/C][C]0.0133278[/C][C]0.0266556[/C][C]0.986672[/C][/ROW]
[ROW][C]229[/C][C]0.0189408[/C][C]0.0378815[/C][C]0.981059[/C][/ROW]
[ROW][C]230[/C][C]0.0179983[/C][C]0.0359966[/C][C]0.982002[/C][/ROW]
[ROW][C]231[/C][C]0.0132937[/C][C]0.0265874[/C][C]0.986706[/C][/ROW]
[ROW][C]232[/C][C]0.0107687[/C][C]0.0215374[/C][C]0.989231[/C][/ROW]
[ROW][C]233[/C][C]0.0104559[/C][C]0.0209118[/C][C]0.989544[/C][/ROW]
[ROW][C]234[/C][C]0.00861548[/C][C]0.017231[/C][C]0.991385[/C][/ROW]
[ROW][C]235[/C][C]0.00897772[/C][C]0.0179554[/C][C]0.991022[/C][/ROW]
[ROW][C]236[/C][C]0.00732488[/C][C]0.0146498[/C][C]0.992675[/C][/ROW]
[ROW][C]237[/C][C]0.00578109[/C][C]0.0115622[/C][C]0.994219[/C][/ROW]
[ROW][C]238[/C][C]0.00464556[/C][C]0.00929112[/C][C]0.995354[/C][/ROW]
[ROW][C]239[/C][C]0.022439[/C][C]0.044878[/C][C]0.977561[/C][/ROW]
[ROW][C]240[/C][C]0.0302544[/C][C]0.0605088[/C][C]0.969746[/C][/ROW]
[ROW][C]241[/C][C]0.0554987[/C][C]0.110997[/C][C]0.944501[/C][/ROW]
[ROW][C]242[/C][C]0.0427957[/C][C]0.0855915[/C][C]0.957204[/C][/ROW]
[ROW][C]243[/C][C]0.0402677[/C][C]0.0805355[/C][C]0.959732[/C][/ROW]
[ROW][C]244[/C][C]0.0312603[/C][C]0.0625206[/C][C]0.96874[/C][/ROW]
[ROW][C]245[/C][C]0.0206899[/C][C]0.0413797[/C][C]0.97931[/C][/ROW]
[ROW][C]246[/C][C]0.0327319[/C][C]0.0654639[/C][C]0.967268[/C][/ROW]
[ROW][C]247[/C][C]0.0219495[/C][C]0.043899[/C][C]0.97805[/C][/ROW]
[ROW][C]248[/C][C]0.312674[/C][C]0.625348[/C][C]0.687326[/C][/ROW]
[ROW][C]249[/C][C]0.324521[/C][C]0.649043[/C][C]0.675479[/C][/ROW]
[ROW][C]250[/C][C]0.377801[/C][C]0.755603[/C][C]0.622199[/C][/ROW]
[ROW][C]251[/C][C]0.451637[/C][C]0.903274[/C][C]0.548363[/C][/ROW]
[ROW][C]252[/C][C]0.928441[/C][C]0.143119[/C][C]0.0715594[/C][/ROW]
[ROW][C]253[/C][C]0.876883[/C][C]0.246233[/C][C]0.123117[/C][/ROW]
[ROW][C]254[/C][C]0.959293[/C][C]0.0814146[/C][C]0.0407073[/C][/ROW]
[ROW][C]255[/C][C]0.932398[/C][C]0.135204[/C][C]0.0676018[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221846&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221846&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
90.9986350.002729680.00136484
100.9971440.005712870.00285644
110.9974350.005130020.00256501
120.9982440.003512530.00175626
130.9966310.006738430.00336921
140.9938420.01231570.00615785
150.9908150.01836990.00918494
160.9852160.02956830.0147842
170.9760530.04789390.0239469
180.9669090.06618220.0330911
190.9668050.06638940.0331947
200.9513650.09726960.0486348
210.9332690.1334620.0667308
220.9132030.1735940.0867969
230.8893150.221370.110685
240.8557560.2884880.144244
250.8281170.3437660.171883
260.94160.11680.0584
270.9233040.1533920.0766961
280.9069140.1861720.0930858
290.8843610.2312790.115639
300.8582750.283450.141725
310.8678660.2642670.132134
320.843290.3134210.15671
330.8146210.3707580.185379
340.7876550.424690.212345
350.7454260.5091470.254574
360.7670870.4658260.232913
370.8231150.3537710.176885
380.7876220.4247570.212378
390.7582870.4834270.241713
400.7618940.4762120.238106
410.7554530.4890950.244547
420.7318780.5362430.268122
430.7408960.5182090.259104
440.7006450.598710.299355
450.6591050.6817910.340895
460.6377710.7244580.362229
470.6558730.6882540.344127
480.6206280.7587440.379372
490.6608740.6782510.339126
500.6366280.7267450.363372
510.6222120.7555770.377788
520.5854490.8291030.414551
530.5930950.813810.406905
540.5486960.9026070.451304
550.5604240.8791520.439576
560.5631560.8736880.436844
570.5366830.9266350.463317
580.5645770.8708460.435423
590.5949510.8100980.405049
600.5652010.8695980.434799
610.5917210.8165590.408279
620.5558840.8882320.444116
630.5475760.9048470.452424
640.5089990.9820010.491001
650.4704650.940930.529535
660.5080660.9838670.491934
670.5149170.9701650.485083
680.4970460.9940920.502954
690.4588680.9177360.541132
700.4358720.8717430.564128
710.3961730.7923470.603827
720.3968990.7937990.603101
730.3612750.722550.638725
740.3407630.6815270.659237
750.3269030.6538050.673097
760.4419590.8839190.558041
770.4257680.8515360.574232
780.4503840.9007680.549616
790.4117350.8234690.588265
800.456560.9131210.54344
810.427150.8543010.57285
820.4398270.8796550.560173
830.4031310.8062630.596869
840.366990.7339790.63301
850.3313850.662770.668615
860.298570.597140.70143
870.2692750.5385510.730725
880.2455410.4910830.754459
890.3089840.6179680.691016
900.2851020.5702030.714898
910.268190.5363810.73181
920.2396170.4792340.760383
930.2251160.4502310.774884
940.2063150.412630.793685
950.1808730.3617460.819127
960.169520.339040.83048
970.1574730.3149450.842527
980.1361380.2722760.863862
990.1333090.2666190.866691
1000.1152940.2305890.884706
1010.1061820.2123630.893818
1020.09140010.18280.9086
1030.1109520.2219040.889048
1040.1221740.2443470.877826
1050.1255360.2510710.874464
1060.1077310.2154620.892269
1070.1249050.2498110.875095
1080.1089890.2179770.891011
1090.2511410.5022810.748859
1100.2338810.4677630.766119
1110.2083820.4167630.791618
1120.2123040.4246090.787696
1130.1964310.3928620.803569
1140.1802060.3604120.819794
1150.1608170.3216340.839183
1160.1413140.2826280.858686
1170.1234940.2469870.876506
1180.1508320.3016630.849168
1190.1411070.2822150.858893
1200.1219560.2439110.878044
1210.1098120.2196240.890188
1220.09926710.1985340.900733
1230.1193550.238710.880645
1240.1053330.2106660.894667
1250.1036450.207290.896355
1260.1039940.2079880.896006
1270.09007080.1801420.909929
1280.08043020.160860.91957
1290.06817890.1363580.931821
1300.0686910.1373820.931309
1310.0678380.1356760.932162
1320.06413640.1282730.935864
1330.06005120.1201020.939949
1340.05039680.1007940.949603
1350.04797310.09594630.952027
1360.1187370.2374740.881263
1370.1032570.2065150.896743
1380.08809360.1761870.911906
1390.07999130.1599830.920009
1400.07692620.1538520.923074
1410.07376260.1475250.926237
1420.06874450.1374890.931255
1430.0591360.1182720.940864
1440.04985760.09971510.950142
1450.04245170.08490340.957548
1460.03535770.07071540.964642
1470.03396630.06793270.966034
1480.03938970.07877930.96061
1490.03527720.07055440.964723
1500.02908090.05816180.970919
1510.03144490.06288980.968555
1520.03026150.0605230.969738
1530.02948880.05897750.970511
1540.02657140.05314280.973429
1550.02936050.05872110.970639
1560.02497930.04995850.975021
1570.02028280.04056570.979717
1580.01741090.03482170.982589
1590.02714690.05429390.972853
1600.02764950.0552990.972351
1610.02441010.04882010.97559
1620.06590240.1318050.934098
1630.05507630.1101530.944924
1640.1967310.3934630.803269
1650.1804260.3608530.819574
1660.3037820.6075640.696218
1670.2795890.5591790.720411
1680.2565340.5130680.743466
1690.2323340.4646680.767666
1700.2071910.4143820.792809
1710.2342570.4685130.765743
1720.2075450.415090.792455
1730.2759860.5519710.724014
1740.2684950.536990.731505
1750.2453860.4907720.754614
1760.3159350.6318710.684065
1770.2916370.5832740.708363
1780.2923190.5846380.707681
1790.2724770.5449540.727523
1800.2541160.5082310.745884
1810.2426870.4853740.757313
1820.3246960.6493930.675304
1830.2992990.5985980.700701
1840.3130130.6260260.686987
1850.2893820.5787640.710618
1860.3556650.7113290.644335
1870.3220870.6441730.677913
1880.2906250.5812490.709375
1890.2589290.5178570.741071
1900.3376810.6753620.662319
1910.3336930.6673860.666307
1920.3514990.7029970.648501
1930.3509980.7019960.649002
1940.3153550.630710.684645
1950.2882760.5765520.711724
1960.301660.6033210.69834
1970.4137450.8274890.586255
1980.3848830.7697670.615117
1990.3478520.6957050.652148
2000.3171160.6342330.682884
2010.2846960.5693910.715304
2020.2520050.504010.747995
2030.2204320.4408640.779568
2040.1916220.3832440.808378
2050.168950.33790.83105
2060.1435180.2870370.856482
2070.1266970.2533940.873303
2080.1297640.2595280.870236
2090.1082730.2165450.891727
2100.08945890.1789180.910541
2110.07576770.1515350.924232
2120.06333360.1266670.936666
2130.05584440.1116890.944156
2140.06123840.1224770.938762
2150.04989090.09978170.950109
2160.03963810.07927610.960362
2170.03077240.06154480.969228
2180.02528130.05056270.974719
2190.02791230.05582460.972088
2200.02224690.04449390.977753
2210.03120010.06240030.9688
2220.0236450.04729010.976355
2230.01798340.03596690.982017
2240.0198680.0397360.980132
2250.02161650.0432330.978384
2260.01724530.03449050.982755
2270.01385690.02771390.986143
2280.01332780.02665560.986672
2290.01894080.03788150.981059
2300.01799830.03599660.982002
2310.01329370.02658740.986706
2320.01076870.02153740.989231
2330.01045590.02091180.989544
2340.008615480.0172310.991385
2350.008977720.01795540.991022
2360.007324880.01464980.992675
2370.005781090.01156220.994219
2380.004645560.009291120.995354
2390.0224390.0448780.977561
2400.03025440.06050880.969746
2410.05549870.1109970.944501
2420.04279570.08559150.957204
2430.04026770.08053550.959732
2440.03126030.06252060.96874
2450.02068990.04137970.97931
2460.03273190.06546390.967268
2470.02194950.0438990.97805
2480.3126740.6253480.687326
2490.3245210.6490430.675479
2500.3778010.7556030.622199
2510.4516370.9032740.548363
2520.9284410.1431190.0715594
2530.8768830.2462330.123117
2540.9592930.08141460.0407073
2550.9323980.1352040.0676018






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level60.0242915NOK
5% type I error level340.137652NOK
10% type I error level640.259109NOK

\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 & 6 & 0.0242915 & NOK \tabularnewline
5% type I error level & 34 & 0.137652 & NOK \tabularnewline
10% type I error level & 64 & 0.259109 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221846&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]6[/C][C]0.0242915[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]34[/C][C]0.137652[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]64[/C][C]0.259109[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221846&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221846&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 level60.0242915NOK
5% type I error level340.137652NOK
10% type I error level640.259109NOK


Figures (Output of Computation)

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

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