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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 04:00:59 -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/t13834694550mrua38tb0awrf8.htm/, Retrieved Mon, 29 Apr 2024 13:11:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221839, Retrieved Mon, 29 Apr 2024 13:11:09 +0000
QR Codes:

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

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [connected 7] [2013-11-03 09:00:59] [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 time14 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 14 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221839&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]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221839&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221839&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 time14 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 17.6545 + 0.439228Separate[t] + 0.150292Learning[t] -0.0369035Software[t] + 0.049535Happiness[t] -0.0613355Depression[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Connected[t] =  +  17.6545 +  0.439228Separate[t] +  0.150292Learning[t] -0.0369035Software[t] +  0.049535Happiness[t] -0.0613355Depression[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221839&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Connected[t] =  +  17.6545 +  0.439228Separate[t] +  0.150292Learning[t] -0.0369035Software[t] +  0.049535Happiness[t] -0.0613355Depression[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221839&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221839&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
Connected[t] = + 17.6545 + 0.439228Separate[t] + 0.150292Learning[t] -0.0369035Software[t] + 0.049535Happiness[t] -0.0613355Depression[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)17.65452.958585.9677.93269e-093.96634e-09
Separate0.4392280.05791847.5846.0858e-133.0429e-13
Learning0.1502920.1115971.3470.1792470.0896236
Software-0.03690350.115116-0.32060.7487910.374395
Happiness0.0495350.1037480.47750.6334440.316722
Depression-0.06133550.0743681-0.82480.4102720.205136

\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) & 17.6545 & 2.95858 & 5.967 & 7.93269e-09 & 3.96634e-09 \tabularnewline
Separate & 0.439228 & 0.0579184 & 7.584 & 6.0858e-13 & 3.0429e-13 \tabularnewline
Learning & 0.150292 & 0.111597 & 1.347 & 0.179247 & 0.0896236 \tabularnewline
Software & -0.0369035 & 0.115116 & -0.3206 & 0.748791 & 0.374395 \tabularnewline
Happiness & 0.049535 & 0.103748 & 0.4775 & 0.633444 & 0.316722 \tabularnewline
Depression & -0.0613355 & 0.0743681 & -0.8248 & 0.410272 & 0.205136 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221839&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]17.6545[/C][C]2.95858[/C][C]5.967[/C][C]7.93269e-09[/C][C]3.96634e-09[/C][/ROW]
[ROW][C]Separate[/C][C]0.439228[/C][C]0.0579184[/C][C]7.584[/C][C]6.0858e-13[/C][C]3.0429e-13[/C][/ROW]
[ROW][C]Learning[/C][C]0.150292[/C][C]0.111597[/C][C]1.347[/C][C]0.179247[/C][C]0.0896236[/C][/ROW]
[ROW][C]Software[/C][C]-0.0369035[/C][C]0.115116[/C][C]-0.3206[/C][C]0.748791[/C][C]0.374395[/C][/ROW]
[ROW][C]Happiness[/C][C]0.049535[/C][C]0.103748[/C][C]0.4775[/C][C]0.633444[/C][C]0.316722[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0613355[/C][C]0.0743681[/C][C]-0.8248[/C][C]0.410272[/C][C]0.205136[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221839&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221839&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)17.65452.958585.9677.93269e-093.96634e-09
Separate0.4392280.05791847.5846.0858e-133.0429e-13
Learning0.1502920.1115971.3470.1792470.0896236
Software-0.03690350.115116-0.32060.7487910.374395
Happiness0.0495350.1037480.47750.6334440.316722
Depression-0.06133550.0743681-0.82480.4102720.205136






Multiple Linear Regression - Regression Statistics
Multiple R0.472622
R-squared0.223371
Adjusted R-squared0.20832
F-TEST (value)14.841
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value8.45102e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.37797
Sum Squared Residuals2943.96

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.472622 \tabularnewline
R-squared & 0.223371 \tabularnewline
Adjusted R-squared & 0.20832 \tabularnewline
F-TEST (value) & 14.841 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 258 \tabularnewline
p-value & 8.45102e-13 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.37797 \tabularnewline
Sum Squared Residuals & 2943.96 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221839&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.472622[/C][/ROW]
[ROW][C]R-squared[/C][C]0.223371[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.20832[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]14.841[/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]8.45102e-13[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.37797[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2943.96[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221839&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221839&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 R0.472622
R-squared0.223371
Adjusted R-squared0.20832
F-TEST (value)14.841
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value8.45102e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.37797
Sum Squared Residuals2943.96






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14135.81365.18643
23933.92555.07454
33035.0157-5.01565
43134.0404-3.04037
53435.0348-1.03478
63532.13252.86753
73933.02745.97263
83435.2232-1.22323
93634.81841.18161
103736.21310.786933
113833.53494.46507
123635.00060.999447
133834.56463.43538
143936.27782.72225
153336.1856-3.18561
163233.7953-1.79535
173633.42992.57008
183837.07560.924442
193936.72462.27539
203233.6668-1.66681
213234.4567-2.45669
223132.9186-1.91858
233936.67842.32158
243736.51880.48116
253933.98935.01069
264133.67887.3212
273635.1810.819023
283335.4171-2.41712
293333.9952-0.995172
303433.63160.36841
313133.3226-2.32264
322732.942-5.94198
333733.23443.76565
343435.9361-1.93609
353432.38871.6113
363233.6955-1.69548
372931.6605-2.66045
383633.81732.18274
392933.5349-4.53493
403534.21530.784749
413733.93643.06357
423433.74410.255877
433834.4643.53605
443533.61981.38021
453831.75636.24374
463733.98543.01464
473836.59971.40027
483334.505-1.50502
493636.266-0.265951
503833.34034.6597
513236.4124-4.41238
523232.4012-0.401175
533232.9505-0.950522
543436.0058-2.0058
553232.7976-0.797624
563734.76382.2362
573934.54534.45473
582934.7411-5.74108
593735.29621.70379
603534.29830.701733
613030.6676-0.667622
623834.4583.542
633434.7244-0.724353
643134.5604-3.56041
653433.17810.821949
663535.8018-0.801805
673634.71831.28174
683031.6714-1.67136
693936.52992.47006
703535.7521-0.752085
713834.57053.42948
723135.9158-4.91583
733436.9187-2.91865
743837.98110.0188829
753431.44472.55526
763932.48326.51679
773735.87561.12441
783432.87051.12946
792832.7272-4.72717
803731.56745.43259
813335.4969-2.49686
823536.0588-1.05876
833734.01712.98291
843234.4437-2.44368
853333.2023-0.202323
863836.5021.498
873334.5075-1.50754
882933.3955-4.39554
893332.95790.0420835
903134.9828-3.9828
913633.43512.56488
923537.5703-2.57033
933231.53790.462131
942932.2195-3.21954
953935.62023.37979
963734.56542.43455
973533.36191.6381
983734.71752.28252
993235.3314-3.33142
1003835.58352.41654
1013734.63932.36074
1023636.4147-0.414749
1033231.67150.328491
1043336.5448-3.54477
1054032.50127.49882
1063835.25752.74254
1074136.50794.49213
1083634.60151.39848
1094336.67056.32946
1103034.4344-4.4344
1113133.6619-2.66189
1123237.7811-5.78113
1133233.4703-1.47033
1143734.17832.82169
1153734.11452.8855
1163336.6827-3.68275
1173436.9286-2.9286
1183334.7168-1.7168
1193835.2022.79801
1203335.1282-2.12817
1213131.2734-0.273365
1223836.36371.63633
1233736.48550.514481
1243633.11352.88647
1253133.9694-2.9694
1263933.94655.05346
1274437.16216.83785
1283335.6554-2.65542
1293533.49221.50776
1303234.1539-2.15392
1312832.0259-4.02587
1324036.1453.85496
1332732.0519-5.05189
1343736.01340.9866
1353232.1375-0.137502
1362828.0733-0.073337
1373434.7107-0.710705
1383033.8752-3.87516
1393534.16490.835148
1403134.2565-3.25648
1413234.8274-2.82736
1423035.762-5.76204
1433034.9863-4.98635
1443129.76251.23754
1454032.59617.40388
1463231.79570.20431
1473634.72521.27482
1483233.1521-1.15212
1493532.61192.38811
1503836.08551.91449
1514235.28186.71819
1523436.6582-2.65824
1533536.826-1.82603
1543833.67754.32246
1553332.01820.981835
1563633.43512.56488
1573235.4731-3.47309
1583335.6554-2.65542
1593433.80050.199545
1603235.3438-3.34381
1613434.7879-0.787853
1622729.6825-2.68248
1633130.41750.582515
1643833.75324.24682
1653436.061-2.06104
1662431.1732-7.17319
1673033.8046-3.80463
1682629.5813-3.58128
1693435.3206-1.32056
1702735.2095-8.20953
1713732.20774.79228
1723635.92430.0757091
1734134.17176.82827
1742929.3307-0.330742
1753631.30874.69127
1763234.9678-2.96785
1773733.12173.87826
1783031.7931-1.79308
1793133.1848-2.18482
1803835.06352.93651
1813635.44730.552672
1823532.35512.64495
1833135.837-4.83703
1843833.60154.39854
1852230.8302-8.83023
1863234.9071-2.90711
1873634.57211.42794
1883932.82276.17726
1892831.133-3.13302
1903234.1922-2.19223
1913234.8755-2.87547
1923837.26560.734424
1933233.6648-1.6648
1943535.4682-0.468178
1953233.1789-1.17887
1963736.01510.984913
1973432.87121.12879
1983335.6412-2.64121
1993333.1519-0.151876
2002633.5182-7.51821
2013032.1963-2.19627
2022432.5734-8.57338
2033432.7591.24096
2043432.85571.14429
2053334.6157-1.61573
2063435.2608-1.2608
2073535.8621-0.862124
2083535.3011-0.301056
2093633.21842.78155
2103434.0909-0.0908929
2113432.91281.08721
2124138.45912.54095
2133236.0737-4.07367
2143033.3669-3.36693
2153534.49150.508518
2162830.3159-2.3159
2173335.3439-2.3439
2183934.28084.71924
2193633.73292.26706
2203636.4802-0.480249
2213533.46881.53117
2223835.25832.74171
2233332.9740.0260294
2243133.3722-2.37216
2253434.2461-0.246132
2263234.6268-2.62682
2273133.7113-2.71131
2283334.2186-1.21859
2293432.45571.54434
2303434.2464-0.246366
2313432.52121.47883
2323334.9435-1.94349
2333234.9625-2.9625
2344133.93897.06113
2353433.53510.464913
2363632.24093.75908
2373730.76286.23721
2383630.87125.12881
2392933.053-4.05305
2403731.88485.11522
2412733.1991-6.19913
2423533.65591.34406
2432830.9581-2.95813
2443533.49441.50556
2453733.04023.95977
2462933.8539-4.85392
2473234.5233-2.52335
2483632.16333.83665
2491927.6552-8.65519
2502127.5235-6.52347
2513133.8675-2.86746
2523332.55560.444368
2533634.13961.86041
2543333.6289-0.62892
2553733.13523.8648
2563433.52160.478449
2573535.0255-0.0255269
2583132.8604-1.86042
2593733.95913.04091
2603531.32653.67355
2612732.6372-5.63723
2623435.5625-1.56252
2634033.85896.14105
2642933.4392-4.43921

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 41 & 35.8136 & 5.18643 \tabularnewline
2 & 39 & 33.9255 & 5.07454 \tabularnewline
3 & 30 & 35.0157 & -5.01565 \tabularnewline
4 & 31 & 34.0404 & -3.04037 \tabularnewline
5 & 34 & 35.0348 & -1.03478 \tabularnewline
6 & 35 & 32.1325 & 2.86753 \tabularnewline
7 & 39 & 33.0274 & 5.97263 \tabularnewline
8 & 34 & 35.2232 & -1.22323 \tabularnewline
9 & 36 & 34.8184 & 1.18161 \tabularnewline
10 & 37 & 36.2131 & 0.786933 \tabularnewline
11 & 38 & 33.5349 & 4.46507 \tabularnewline
12 & 36 & 35.0006 & 0.999447 \tabularnewline
13 & 38 & 34.5646 & 3.43538 \tabularnewline
14 & 39 & 36.2778 & 2.72225 \tabularnewline
15 & 33 & 36.1856 & -3.18561 \tabularnewline
16 & 32 & 33.7953 & -1.79535 \tabularnewline
17 & 36 & 33.4299 & 2.57008 \tabularnewline
18 & 38 & 37.0756 & 0.924442 \tabularnewline
19 & 39 & 36.7246 & 2.27539 \tabularnewline
20 & 32 & 33.6668 & -1.66681 \tabularnewline
21 & 32 & 34.4567 & -2.45669 \tabularnewline
22 & 31 & 32.9186 & -1.91858 \tabularnewline
23 & 39 & 36.6784 & 2.32158 \tabularnewline
24 & 37 & 36.5188 & 0.48116 \tabularnewline
25 & 39 & 33.9893 & 5.01069 \tabularnewline
26 & 41 & 33.6788 & 7.3212 \tabularnewline
27 & 36 & 35.181 & 0.819023 \tabularnewline
28 & 33 & 35.4171 & -2.41712 \tabularnewline
29 & 33 & 33.9952 & -0.995172 \tabularnewline
30 & 34 & 33.6316 & 0.36841 \tabularnewline
31 & 31 & 33.3226 & -2.32264 \tabularnewline
32 & 27 & 32.942 & -5.94198 \tabularnewline
33 & 37 & 33.2344 & 3.76565 \tabularnewline
34 & 34 & 35.9361 & -1.93609 \tabularnewline
35 & 34 & 32.3887 & 1.6113 \tabularnewline
36 & 32 & 33.6955 & -1.69548 \tabularnewline
37 & 29 & 31.6605 & -2.66045 \tabularnewline
38 & 36 & 33.8173 & 2.18274 \tabularnewline
39 & 29 & 33.5349 & -4.53493 \tabularnewline
40 & 35 & 34.2153 & 0.784749 \tabularnewline
41 & 37 & 33.9364 & 3.06357 \tabularnewline
42 & 34 & 33.7441 & 0.255877 \tabularnewline
43 & 38 & 34.464 & 3.53605 \tabularnewline
44 & 35 & 33.6198 & 1.38021 \tabularnewline
45 & 38 & 31.7563 & 6.24374 \tabularnewline
46 & 37 & 33.9854 & 3.01464 \tabularnewline
47 & 38 & 36.5997 & 1.40027 \tabularnewline
48 & 33 & 34.505 & -1.50502 \tabularnewline
49 & 36 & 36.266 & -0.265951 \tabularnewline
50 & 38 & 33.3403 & 4.6597 \tabularnewline
51 & 32 & 36.4124 & -4.41238 \tabularnewline
52 & 32 & 32.4012 & -0.401175 \tabularnewline
53 & 32 & 32.9505 & -0.950522 \tabularnewline
54 & 34 & 36.0058 & -2.0058 \tabularnewline
55 & 32 & 32.7976 & -0.797624 \tabularnewline
56 & 37 & 34.7638 & 2.2362 \tabularnewline
57 & 39 & 34.5453 & 4.45473 \tabularnewline
58 & 29 & 34.7411 & -5.74108 \tabularnewline
59 & 37 & 35.2962 & 1.70379 \tabularnewline
60 & 35 & 34.2983 & 0.701733 \tabularnewline
61 & 30 & 30.6676 & -0.667622 \tabularnewline
62 & 38 & 34.458 & 3.542 \tabularnewline
63 & 34 & 34.7244 & -0.724353 \tabularnewline
64 & 31 & 34.5604 & -3.56041 \tabularnewline
65 & 34 & 33.1781 & 0.821949 \tabularnewline
66 & 35 & 35.8018 & -0.801805 \tabularnewline
67 & 36 & 34.7183 & 1.28174 \tabularnewline
68 & 30 & 31.6714 & -1.67136 \tabularnewline
69 & 39 & 36.5299 & 2.47006 \tabularnewline
70 & 35 & 35.7521 & -0.752085 \tabularnewline
71 & 38 & 34.5705 & 3.42948 \tabularnewline
72 & 31 & 35.9158 & -4.91583 \tabularnewline
73 & 34 & 36.9187 & -2.91865 \tabularnewline
74 & 38 & 37.9811 & 0.0188829 \tabularnewline
75 & 34 & 31.4447 & 2.55526 \tabularnewline
76 & 39 & 32.4832 & 6.51679 \tabularnewline
77 & 37 & 35.8756 & 1.12441 \tabularnewline
78 & 34 & 32.8705 & 1.12946 \tabularnewline
79 & 28 & 32.7272 & -4.72717 \tabularnewline
80 & 37 & 31.5674 & 5.43259 \tabularnewline
81 & 33 & 35.4969 & -2.49686 \tabularnewline
82 & 35 & 36.0588 & -1.05876 \tabularnewline
83 & 37 & 34.0171 & 2.98291 \tabularnewline
84 & 32 & 34.4437 & -2.44368 \tabularnewline
85 & 33 & 33.2023 & -0.202323 \tabularnewline
86 & 38 & 36.502 & 1.498 \tabularnewline
87 & 33 & 34.5075 & -1.50754 \tabularnewline
88 & 29 & 33.3955 & -4.39554 \tabularnewline
89 & 33 & 32.9579 & 0.0420835 \tabularnewline
90 & 31 & 34.9828 & -3.9828 \tabularnewline
91 & 36 & 33.4351 & 2.56488 \tabularnewline
92 & 35 & 37.5703 & -2.57033 \tabularnewline
93 & 32 & 31.5379 & 0.462131 \tabularnewline
94 & 29 & 32.2195 & -3.21954 \tabularnewline
95 & 39 & 35.6202 & 3.37979 \tabularnewline
96 & 37 & 34.5654 & 2.43455 \tabularnewline
97 & 35 & 33.3619 & 1.6381 \tabularnewline
98 & 37 & 34.7175 & 2.28252 \tabularnewline
99 & 32 & 35.3314 & -3.33142 \tabularnewline
100 & 38 & 35.5835 & 2.41654 \tabularnewline
101 & 37 & 34.6393 & 2.36074 \tabularnewline
102 & 36 & 36.4147 & -0.414749 \tabularnewline
103 & 32 & 31.6715 & 0.328491 \tabularnewline
104 & 33 & 36.5448 & -3.54477 \tabularnewline
105 & 40 & 32.5012 & 7.49882 \tabularnewline
106 & 38 & 35.2575 & 2.74254 \tabularnewline
107 & 41 & 36.5079 & 4.49213 \tabularnewline
108 & 36 & 34.6015 & 1.39848 \tabularnewline
109 & 43 & 36.6705 & 6.32946 \tabularnewline
110 & 30 & 34.4344 & -4.4344 \tabularnewline
111 & 31 & 33.6619 & -2.66189 \tabularnewline
112 & 32 & 37.7811 & -5.78113 \tabularnewline
113 & 32 & 33.4703 & -1.47033 \tabularnewline
114 & 37 & 34.1783 & 2.82169 \tabularnewline
115 & 37 & 34.1145 & 2.8855 \tabularnewline
116 & 33 & 36.6827 & -3.68275 \tabularnewline
117 & 34 & 36.9286 & -2.9286 \tabularnewline
118 & 33 & 34.7168 & -1.7168 \tabularnewline
119 & 38 & 35.202 & 2.79801 \tabularnewline
120 & 33 & 35.1282 & -2.12817 \tabularnewline
121 & 31 & 31.2734 & -0.273365 \tabularnewline
122 & 38 & 36.3637 & 1.63633 \tabularnewline
123 & 37 & 36.4855 & 0.514481 \tabularnewline
124 & 36 & 33.1135 & 2.88647 \tabularnewline
125 & 31 & 33.9694 & -2.9694 \tabularnewline
126 & 39 & 33.9465 & 5.05346 \tabularnewline
127 & 44 & 37.1621 & 6.83785 \tabularnewline
128 & 33 & 35.6554 & -2.65542 \tabularnewline
129 & 35 & 33.4922 & 1.50776 \tabularnewline
130 & 32 & 34.1539 & -2.15392 \tabularnewline
131 & 28 & 32.0259 & -4.02587 \tabularnewline
132 & 40 & 36.145 & 3.85496 \tabularnewline
133 & 27 & 32.0519 & -5.05189 \tabularnewline
134 & 37 & 36.0134 & 0.9866 \tabularnewline
135 & 32 & 32.1375 & -0.137502 \tabularnewline
136 & 28 & 28.0733 & -0.073337 \tabularnewline
137 & 34 & 34.7107 & -0.710705 \tabularnewline
138 & 30 & 33.8752 & -3.87516 \tabularnewline
139 & 35 & 34.1649 & 0.835148 \tabularnewline
140 & 31 & 34.2565 & -3.25648 \tabularnewline
141 & 32 & 34.8274 & -2.82736 \tabularnewline
142 & 30 & 35.762 & -5.76204 \tabularnewline
143 & 30 & 34.9863 & -4.98635 \tabularnewline
144 & 31 & 29.7625 & 1.23754 \tabularnewline
145 & 40 & 32.5961 & 7.40388 \tabularnewline
146 & 32 & 31.7957 & 0.20431 \tabularnewline
147 & 36 & 34.7252 & 1.27482 \tabularnewline
148 & 32 & 33.1521 & -1.15212 \tabularnewline
149 & 35 & 32.6119 & 2.38811 \tabularnewline
150 & 38 & 36.0855 & 1.91449 \tabularnewline
151 & 42 & 35.2818 & 6.71819 \tabularnewline
152 & 34 & 36.6582 & -2.65824 \tabularnewline
153 & 35 & 36.826 & -1.82603 \tabularnewline
154 & 38 & 33.6775 & 4.32246 \tabularnewline
155 & 33 & 32.0182 & 0.981835 \tabularnewline
156 & 36 & 33.4351 & 2.56488 \tabularnewline
157 & 32 & 35.4731 & -3.47309 \tabularnewline
158 & 33 & 35.6554 & -2.65542 \tabularnewline
159 & 34 & 33.8005 & 0.199545 \tabularnewline
160 & 32 & 35.3438 & -3.34381 \tabularnewline
161 & 34 & 34.7879 & -0.787853 \tabularnewline
162 & 27 & 29.6825 & -2.68248 \tabularnewline
163 & 31 & 30.4175 & 0.582515 \tabularnewline
164 & 38 & 33.7532 & 4.24682 \tabularnewline
165 & 34 & 36.061 & -2.06104 \tabularnewline
166 & 24 & 31.1732 & -7.17319 \tabularnewline
167 & 30 & 33.8046 & -3.80463 \tabularnewline
168 & 26 & 29.5813 & -3.58128 \tabularnewline
169 & 34 & 35.3206 & -1.32056 \tabularnewline
170 & 27 & 35.2095 & -8.20953 \tabularnewline
171 & 37 & 32.2077 & 4.79228 \tabularnewline
172 & 36 & 35.9243 & 0.0757091 \tabularnewline
173 & 41 & 34.1717 & 6.82827 \tabularnewline
174 & 29 & 29.3307 & -0.330742 \tabularnewline
175 & 36 & 31.3087 & 4.69127 \tabularnewline
176 & 32 & 34.9678 & -2.96785 \tabularnewline
177 & 37 & 33.1217 & 3.87826 \tabularnewline
178 & 30 & 31.7931 & -1.79308 \tabularnewline
179 & 31 & 33.1848 & -2.18482 \tabularnewline
180 & 38 & 35.0635 & 2.93651 \tabularnewline
181 & 36 & 35.4473 & 0.552672 \tabularnewline
182 & 35 & 32.3551 & 2.64495 \tabularnewline
183 & 31 & 35.837 & -4.83703 \tabularnewline
184 & 38 & 33.6015 & 4.39854 \tabularnewline
185 & 22 & 30.8302 & -8.83023 \tabularnewline
186 & 32 & 34.9071 & -2.90711 \tabularnewline
187 & 36 & 34.5721 & 1.42794 \tabularnewline
188 & 39 & 32.8227 & 6.17726 \tabularnewline
189 & 28 & 31.133 & -3.13302 \tabularnewline
190 & 32 & 34.1922 & -2.19223 \tabularnewline
191 & 32 & 34.8755 & -2.87547 \tabularnewline
192 & 38 & 37.2656 & 0.734424 \tabularnewline
193 & 32 & 33.6648 & -1.6648 \tabularnewline
194 & 35 & 35.4682 & -0.468178 \tabularnewline
195 & 32 & 33.1789 & -1.17887 \tabularnewline
196 & 37 & 36.0151 & 0.984913 \tabularnewline
197 & 34 & 32.8712 & 1.12879 \tabularnewline
198 & 33 & 35.6412 & -2.64121 \tabularnewline
199 & 33 & 33.1519 & -0.151876 \tabularnewline
200 & 26 & 33.5182 & -7.51821 \tabularnewline
201 & 30 & 32.1963 & -2.19627 \tabularnewline
202 & 24 & 32.5734 & -8.57338 \tabularnewline
203 & 34 & 32.759 & 1.24096 \tabularnewline
204 & 34 & 32.8557 & 1.14429 \tabularnewline
205 & 33 & 34.6157 & -1.61573 \tabularnewline
206 & 34 & 35.2608 & -1.2608 \tabularnewline
207 & 35 & 35.8621 & -0.862124 \tabularnewline
208 & 35 & 35.3011 & -0.301056 \tabularnewline
209 & 36 & 33.2184 & 2.78155 \tabularnewline
210 & 34 & 34.0909 & -0.0908929 \tabularnewline
211 & 34 & 32.9128 & 1.08721 \tabularnewline
212 & 41 & 38.4591 & 2.54095 \tabularnewline
213 & 32 & 36.0737 & -4.07367 \tabularnewline
214 & 30 & 33.3669 & -3.36693 \tabularnewline
215 & 35 & 34.4915 & 0.508518 \tabularnewline
216 & 28 & 30.3159 & -2.3159 \tabularnewline
217 & 33 & 35.3439 & -2.3439 \tabularnewline
218 & 39 & 34.2808 & 4.71924 \tabularnewline
219 & 36 & 33.7329 & 2.26706 \tabularnewline
220 & 36 & 36.4802 & -0.480249 \tabularnewline
221 & 35 & 33.4688 & 1.53117 \tabularnewline
222 & 38 & 35.2583 & 2.74171 \tabularnewline
223 & 33 & 32.974 & 0.0260294 \tabularnewline
224 & 31 & 33.3722 & -2.37216 \tabularnewline
225 & 34 & 34.2461 & -0.246132 \tabularnewline
226 & 32 & 34.6268 & -2.62682 \tabularnewline
227 & 31 & 33.7113 & -2.71131 \tabularnewline
228 & 33 & 34.2186 & -1.21859 \tabularnewline
229 & 34 & 32.4557 & 1.54434 \tabularnewline
230 & 34 & 34.2464 & -0.246366 \tabularnewline
231 & 34 & 32.5212 & 1.47883 \tabularnewline
232 & 33 & 34.9435 & -1.94349 \tabularnewline
233 & 32 & 34.9625 & -2.9625 \tabularnewline
234 & 41 & 33.9389 & 7.06113 \tabularnewline
235 & 34 & 33.5351 & 0.464913 \tabularnewline
236 & 36 & 32.2409 & 3.75908 \tabularnewline
237 & 37 & 30.7628 & 6.23721 \tabularnewline
238 & 36 & 30.8712 & 5.12881 \tabularnewline
239 & 29 & 33.053 & -4.05305 \tabularnewline
240 & 37 & 31.8848 & 5.11522 \tabularnewline
241 & 27 & 33.1991 & -6.19913 \tabularnewline
242 & 35 & 33.6559 & 1.34406 \tabularnewline
243 & 28 & 30.9581 & -2.95813 \tabularnewline
244 & 35 & 33.4944 & 1.50556 \tabularnewline
245 & 37 & 33.0402 & 3.95977 \tabularnewline
246 & 29 & 33.8539 & -4.85392 \tabularnewline
247 & 32 & 34.5233 & -2.52335 \tabularnewline
248 & 36 & 32.1633 & 3.83665 \tabularnewline
249 & 19 & 27.6552 & -8.65519 \tabularnewline
250 & 21 & 27.5235 & -6.52347 \tabularnewline
251 & 31 & 33.8675 & -2.86746 \tabularnewline
252 & 33 & 32.5556 & 0.444368 \tabularnewline
253 & 36 & 34.1396 & 1.86041 \tabularnewline
254 & 33 & 33.6289 & -0.62892 \tabularnewline
255 & 37 & 33.1352 & 3.8648 \tabularnewline
256 & 34 & 33.5216 & 0.478449 \tabularnewline
257 & 35 & 35.0255 & -0.0255269 \tabularnewline
258 & 31 & 32.8604 & -1.86042 \tabularnewline
259 & 37 & 33.9591 & 3.04091 \tabularnewline
260 & 35 & 31.3265 & 3.67355 \tabularnewline
261 & 27 & 32.6372 & -5.63723 \tabularnewline
262 & 34 & 35.5625 & -1.56252 \tabularnewline
263 & 40 & 33.8589 & 6.14105 \tabularnewline
264 & 29 & 33.4392 & -4.43921 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221839&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]41[/C][C]35.8136[/C][C]5.18643[/C][/ROW]
[ROW][C]2[/C][C]39[/C][C]33.9255[/C][C]5.07454[/C][/ROW]
[ROW][C]3[/C][C]30[/C][C]35.0157[/C][C]-5.01565[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]34.0404[/C][C]-3.04037[/C][/ROW]
[ROW][C]5[/C][C]34[/C][C]35.0348[/C][C]-1.03478[/C][/ROW]
[ROW][C]6[/C][C]35[/C][C]32.1325[/C][C]2.86753[/C][/ROW]
[ROW][C]7[/C][C]39[/C][C]33.0274[/C][C]5.97263[/C][/ROW]
[ROW][C]8[/C][C]34[/C][C]35.2232[/C][C]-1.22323[/C][/ROW]
[ROW][C]9[/C][C]36[/C][C]34.8184[/C][C]1.18161[/C][/ROW]
[ROW][C]10[/C][C]37[/C][C]36.2131[/C][C]0.786933[/C][/ROW]
[ROW][C]11[/C][C]38[/C][C]33.5349[/C][C]4.46507[/C][/ROW]
[ROW][C]12[/C][C]36[/C][C]35.0006[/C][C]0.999447[/C][/ROW]
[ROW][C]13[/C][C]38[/C][C]34.5646[/C][C]3.43538[/C][/ROW]
[ROW][C]14[/C][C]39[/C][C]36.2778[/C][C]2.72225[/C][/ROW]
[ROW][C]15[/C][C]33[/C][C]36.1856[/C][C]-3.18561[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]33.7953[/C][C]-1.79535[/C][/ROW]
[ROW][C]17[/C][C]36[/C][C]33.4299[/C][C]2.57008[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]37.0756[/C][C]0.924442[/C][/ROW]
[ROW][C]19[/C][C]39[/C][C]36.7246[/C][C]2.27539[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.6668[/C][C]-1.66681[/C][/ROW]
[ROW][C]21[/C][C]32[/C][C]34.4567[/C][C]-2.45669[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]32.9186[/C][C]-1.91858[/C][/ROW]
[ROW][C]23[/C][C]39[/C][C]36.6784[/C][C]2.32158[/C][/ROW]
[ROW][C]24[/C][C]37[/C][C]36.5188[/C][C]0.48116[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]33.9893[/C][C]5.01069[/C][/ROW]
[ROW][C]26[/C][C]41[/C][C]33.6788[/C][C]7.3212[/C][/ROW]
[ROW][C]27[/C][C]36[/C][C]35.181[/C][C]0.819023[/C][/ROW]
[ROW][C]28[/C][C]33[/C][C]35.4171[/C][C]-2.41712[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]33.9952[/C][C]-0.995172[/C][/ROW]
[ROW][C]30[/C][C]34[/C][C]33.6316[/C][C]0.36841[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]33.3226[/C][C]-2.32264[/C][/ROW]
[ROW][C]32[/C][C]27[/C][C]32.942[/C][C]-5.94198[/C][/ROW]
[ROW][C]33[/C][C]37[/C][C]33.2344[/C][C]3.76565[/C][/ROW]
[ROW][C]34[/C][C]34[/C][C]35.9361[/C][C]-1.93609[/C][/ROW]
[ROW][C]35[/C][C]34[/C][C]32.3887[/C][C]1.6113[/C][/ROW]
[ROW][C]36[/C][C]32[/C][C]33.6955[/C][C]-1.69548[/C][/ROW]
[ROW][C]37[/C][C]29[/C][C]31.6605[/C][C]-2.66045[/C][/ROW]
[ROW][C]38[/C][C]36[/C][C]33.8173[/C][C]2.18274[/C][/ROW]
[ROW][C]39[/C][C]29[/C][C]33.5349[/C][C]-4.53493[/C][/ROW]
[ROW][C]40[/C][C]35[/C][C]34.2153[/C][C]0.784749[/C][/ROW]
[ROW][C]41[/C][C]37[/C][C]33.9364[/C][C]3.06357[/C][/ROW]
[ROW][C]42[/C][C]34[/C][C]33.7441[/C][C]0.255877[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]34.464[/C][C]3.53605[/C][/ROW]
[ROW][C]44[/C][C]35[/C][C]33.6198[/C][C]1.38021[/C][/ROW]
[ROW][C]45[/C][C]38[/C][C]31.7563[/C][C]6.24374[/C][/ROW]
[ROW][C]46[/C][C]37[/C][C]33.9854[/C][C]3.01464[/C][/ROW]
[ROW][C]47[/C][C]38[/C][C]36.5997[/C][C]1.40027[/C][/ROW]
[ROW][C]48[/C][C]33[/C][C]34.505[/C][C]-1.50502[/C][/ROW]
[ROW][C]49[/C][C]36[/C][C]36.266[/C][C]-0.265951[/C][/ROW]
[ROW][C]50[/C][C]38[/C][C]33.3403[/C][C]4.6597[/C][/ROW]
[ROW][C]51[/C][C]32[/C][C]36.4124[/C][C]-4.41238[/C][/ROW]
[ROW][C]52[/C][C]32[/C][C]32.4012[/C][C]-0.401175[/C][/ROW]
[ROW][C]53[/C][C]32[/C][C]32.9505[/C][C]-0.950522[/C][/ROW]
[ROW][C]54[/C][C]34[/C][C]36.0058[/C][C]-2.0058[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]32.7976[/C][C]-0.797624[/C][/ROW]
[ROW][C]56[/C][C]37[/C][C]34.7638[/C][C]2.2362[/C][/ROW]
[ROW][C]57[/C][C]39[/C][C]34.5453[/C][C]4.45473[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]34.7411[/C][C]-5.74108[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]35.2962[/C][C]1.70379[/C][/ROW]
[ROW][C]60[/C][C]35[/C][C]34.2983[/C][C]0.701733[/C][/ROW]
[ROW][C]61[/C][C]30[/C][C]30.6676[/C][C]-0.667622[/C][/ROW]
[ROW][C]62[/C][C]38[/C][C]34.458[/C][C]3.542[/C][/ROW]
[ROW][C]63[/C][C]34[/C][C]34.7244[/C][C]-0.724353[/C][/ROW]
[ROW][C]64[/C][C]31[/C][C]34.5604[/C][C]-3.56041[/C][/ROW]
[ROW][C]65[/C][C]34[/C][C]33.1781[/C][C]0.821949[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]35.8018[/C][C]-0.801805[/C][/ROW]
[ROW][C]67[/C][C]36[/C][C]34.7183[/C][C]1.28174[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]31.6714[/C][C]-1.67136[/C][/ROW]
[ROW][C]69[/C][C]39[/C][C]36.5299[/C][C]2.47006[/C][/ROW]
[ROW][C]70[/C][C]35[/C][C]35.7521[/C][C]-0.752085[/C][/ROW]
[ROW][C]71[/C][C]38[/C][C]34.5705[/C][C]3.42948[/C][/ROW]
[ROW][C]72[/C][C]31[/C][C]35.9158[/C][C]-4.91583[/C][/ROW]
[ROW][C]73[/C][C]34[/C][C]36.9187[/C][C]-2.91865[/C][/ROW]
[ROW][C]74[/C][C]38[/C][C]37.9811[/C][C]0.0188829[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]31.4447[/C][C]2.55526[/C][/ROW]
[ROW][C]76[/C][C]39[/C][C]32.4832[/C][C]6.51679[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.8756[/C][C]1.12441[/C][/ROW]
[ROW][C]78[/C][C]34[/C][C]32.8705[/C][C]1.12946[/C][/ROW]
[ROW][C]79[/C][C]28[/C][C]32.7272[/C][C]-4.72717[/C][/ROW]
[ROW][C]80[/C][C]37[/C][C]31.5674[/C][C]5.43259[/C][/ROW]
[ROW][C]81[/C][C]33[/C][C]35.4969[/C][C]-2.49686[/C][/ROW]
[ROW][C]82[/C][C]35[/C][C]36.0588[/C][C]-1.05876[/C][/ROW]
[ROW][C]83[/C][C]37[/C][C]34.0171[/C][C]2.98291[/C][/ROW]
[ROW][C]84[/C][C]32[/C][C]34.4437[/C][C]-2.44368[/C][/ROW]
[ROW][C]85[/C][C]33[/C][C]33.2023[/C][C]-0.202323[/C][/ROW]
[ROW][C]86[/C][C]38[/C][C]36.502[/C][C]1.498[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]34.5075[/C][C]-1.50754[/C][/ROW]
[ROW][C]88[/C][C]29[/C][C]33.3955[/C][C]-4.39554[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]32.9579[/C][C]0.0420835[/C][/ROW]
[ROW][C]90[/C][C]31[/C][C]34.9828[/C][C]-3.9828[/C][/ROW]
[ROW][C]91[/C][C]36[/C][C]33.4351[/C][C]2.56488[/C][/ROW]
[ROW][C]92[/C][C]35[/C][C]37.5703[/C][C]-2.57033[/C][/ROW]
[ROW][C]93[/C][C]32[/C][C]31.5379[/C][C]0.462131[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]32.2195[/C][C]-3.21954[/C][/ROW]
[ROW][C]95[/C][C]39[/C][C]35.6202[/C][C]3.37979[/C][/ROW]
[ROW][C]96[/C][C]37[/C][C]34.5654[/C][C]2.43455[/C][/ROW]
[ROW][C]97[/C][C]35[/C][C]33.3619[/C][C]1.6381[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]34.7175[/C][C]2.28252[/C][/ROW]
[ROW][C]99[/C][C]32[/C][C]35.3314[/C][C]-3.33142[/C][/ROW]
[ROW][C]100[/C][C]38[/C][C]35.5835[/C][C]2.41654[/C][/ROW]
[ROW][C]101[/C][C]37[/C][C]34.6393[/C][C]2.36074[/C][/ROW]
[ROW][C]102[/C][C]36[/C][C]36.4147[/C][C]-0.414749[/C][/ROW]
[ROW][C]103[/C][C]32[/C][C]31.6715[/C][C]0.328491[/C][/ROW]
[ROW][C]104[/C][C]33[/C][C]36.5448[/C][C]-3.54477[/C][/ROW]
[ROW][C]105[/C][C]40[/C][C]32.5012[/C][C]7.49882[/C][/ROW]
[ROW][C]106[/C][C]38[/C][C]35.2575[/C][C]2.74254[/C][/ROW]
[ROW][C]107[/C][C]41[/C][C]36.5079[/C][C]4.49213[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]34.6015[/C][C]1.39848[/C][/ROW]
[ROW][C]109[/C][C]43[/C][C]36.6705[/C][C]6.32946[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]34.4344[/C][C]-4.4344[/C][/ROW]
[ROW][C]111[/C][C]31[/C][C]33.6619[/C][C]-2.66189[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]37.7811[/C][C]-5.78113[/C][/ROW]
[ROW][C]113[/C][C]32[/C][C]33.4703[/C][C]-1.47033[/C][/ROW]
[ROW][C]114[/C][C]37[/C][C]34.1783[/C][C]2.82169[/C][/ROW]
[ROW][C]115[/C][C]37[/C][C]34.1145[/C][C]2.8855[/C][/ROW]
[ROW][C]116[/C][C]33[/C][C]36.6827[/C][C]-3.68275[/C][/ROW]
[ROW][C]117[/C][C]34[/C][C]36.9286[/C][C]-2.9286[/C][/ROW]
[ROW][C]118[/C][C]33[/C][C]34.7168[/C][C]-1.7168[/C][/ROW]
[ROW][C]119[/C][C]38[/C][C]35.202[/C][C]2.79801[/C][/ROW]
[ROW][C]120[/C][C]33[/C][C]35.1282[/C][C]-2.12817[/C][/ROW]
[ROW][C]121[/C][C]31[/C][C]31.2734[/C][C]-0.273365[/C][/ROW]
[ROW][C]122[/C][C]38[/C][C]36.3637[/C][C]1.63633[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]36.4855[/C][C]0.514481[/C][/ROW]
[ROW][C]124[/C][C]36[/C][C]33.1135[/C][C]2.88647[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]33.9694[/C][C]-2.9694[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]33.9465[/C][C]5.05346[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]37.1621[/C][C]6.83785[/C][/ROW]
[ROW][C]128[/C][C]33[/C][C]35.6554[/C][C]-2.65542[/C][/ROW]
[ROW][C]129[/C][C]35[/C][C]33.4922[/C][C]1.50776[/C][/ROW]
[ROW][C]130[/C][C]32[/C][C]34.1539[/C][C]-2.15392[/C][/ROW]
[ROW][C]131[/C][C]28[/C][C]32.0259[/C][C]-4.02587[/C][/ROW]
[ROW][C]132[/C][C]40[/C][C]36.145[/C][C]3.85496[/C][/ROW]
[ROW][C]133[/C][C]27[/C][C]32.0519[/C][C]-5.05189[/C][/ROW]
[ROW][C]134[/C][C]37[/C][C]36.0134[/C][C]0.9866[/C][/ROW]
[ROW][C]135[/C][C]32[/C][C]32.1375[/C][C]-0.137502[/C][/ROW]
[ROW][C]136[/C][C]28[/C][C]28.0733[/C][C]-0.073337[/C][/ROW]
[ROW][C]137[/C][C]34[/C][C]34.7107[/C][C]-0.710705[/C][/ROW]
[ROW][C]138[/C][C]30[/C][C]33.8752[/C][C]-3.87516[/C][/ROW]
[ROW][C]139[/C][C]35[/C][C]34.1649[/C][C]0.835148[/C][/ROW]
[ROW][C]140[/C][C]31[/C][C]34.2565[/C][C]-3.25648[/C][/ROW]
[ROW][C]141[/C][C]32[/C][C]34.8274[/C][C]-2.82736[/C][/ROW]
[ROW][C]142[/C][C]30[/C][C]35.762[/C][C]-5.76204[/C][/ROW]
[ROW][C]143[/C][C]30[/C][C]34.9863[/C][C]-4.98635[/C][/ROW]
[ROW][C]144[/C][C]31[/C][C]29.7625[/C][C]1.23754[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]32.5961[/C][C]7.40388[/C][/ROW]
[ROW][C]146[/C][C]32[/C][C]31.7957[/C][C]0.20431[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]34.7252[/C][C]1.27482[/C][/ROW]
[ROW][C]148[/C][C]32[/C][C]33.1521[/C][C]-1.15212[/C][/ROW]
[ROW][C]149[/C][C]35[/C][C]32.6119[/C][C]2.38811[/C][/ROW]
[ROW][C]150[/C][C]38[/C][C]36.0855[/C][C]1.91449[/C][/ROW]
[ROW][C]151[/C][C]42[/C][C]35.2818[/C][C]6.71819[/C][/ROW]
[ROW][C]152[/C][C]34[/C][C]36.6582[/C][C]-2.65824[/C][/ROW]
[ROW][C]153[/C][C]35[/C][C]36.826[/C][C]-1.82603[/C][/ROW]
[ROW][C]154[/C][C]38[/C][C]33.6775[/C][C]4.32246[/C][/ROW]
[ROW][C]155[/C][C]33[/C][C]32.0182[/C][C]0.981835[/C][/ROW]
[ROW][C]156[/C][C]36[/C][C]33.4351[/C][C]2.56488[/C][/ROW]
[ROW][C]157[/C][C]32[/C][C]35.4731[/C][C]-3.47309[/C][/ROW]
[ROW][C]158[/C][C]33[/C][C]35.6554[/C][C]-2.65542[/C][/ROW]
[ROW][C]159[/C][C]34[/C][C]33.8005[/C][C]0.199545[/C][/ROW]
[ROW][C]160[/C][C]32[/C][C]35.3438[/C][C]-3.34381[/C][/ROW]
[ROW][C]161[/C][C]34[/C][C]34.7879[/C][C]-0.787853[/C][/ROW]
[ROW][C]162[/C][C]27[/C][C]29.6825[/C][C]-2.68248[/C][/ROW]
[ROW][C]163[/C][C]31[/C][C]30.4175[/C][C]0.582515[/C][/ROW]
[ROW][C]164[/C][C]38[/C][C]33.7532[/C][C]4.24682[/C][/ROW]
[ROW][C]165[/C][C]34[/C][C]36.061[/C][C]-2.06104[/C][/ROW]
[ROW][C]166[/C][C]24[/C][C]31.1732[/C][C]-7.17319[/C][/ROW]
[ROW][C]167[/C][C]30[/C][C]33.8046[/C][C]-3.80463[/C][/ROW]
[ROW][C]168[/C][C]26[/C][C]29.5813[/C][C]-3.58128[/C][/ROW]
[ROW][C]169[/C][C]34[/C][C]35.3206[/C][C]-1.32056[/C][/ROW]
[ROW][C]170[/C][C]27[/C][C]35.2095[/C][C]-8.20953[/C][/ROW]
[ROW][C]171[/C][C]37[/C][C]32.2077[/C][C]4.79228[/C][/ROW]
[ROW][C]172[/C][C]36[/C][C]35.9243[/C][C]0.0757091[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]34.1717[/C][C]6.82827[/C][/ROW]
[ROW][C]174[/C][C]29[/C][C]29.3307[/C][C]-0.330742[/C][/ROW]
[ROW][C]175[/C][C]36[/C][C]31.3087[/C][C]4.69127[/C][/ROW]
[ROW][C]176[/C][C]32[/C][C]34.9678[/C][C]-2.96785[/C][/ROW]
[ROW][C]177[/C][C]37[/C][C]33.1217[/C][C]3.87826[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.7931[/C][C]-1.79308[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]33.1848[/C][C]-2.18482[/C][/ROW]
[ROW][C]180[/C][C]38[/C][C]35.0635[/C][C]2.93651[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]35.4473[/C][C]0.552672[/C][/ROW]
[ROW][C]182[/C][C]35[/C][C]32.3551[/C][C]2.64495[/C][/ROW]
[ROW][C]183[/C][C]31[/C][C]35.837[/C][C]-4.83703[/C][/ROW]
[ROW][C]184[/C][C]38[/C][C]33.6015[/C][C]4.39854[/C][/ROW]
[ROW][C]185[/C][C]22[/C][C]30.8302[/C][C]-8.83023[/C][/ROW]
[ROW][C]186[/C][C]32[/C][C]34.9071[/C][C]-2.90711[/C][/ROW]
[ROW][C]187[/C][C]36[/C][C]34.5721[/C][C]1.42794[/C][/ROW]
[ROW][C]188[/C][C]39[/C][C]32.8227[/C][C]6.17726[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]31.133[/C][C]-3.13302[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]34.1922[/C][C]-2.19223[/C][/ROW]
[ROW][C]191[/C][C]32[/C][C]34.8755[/C][C]-2.87547[/C][/ROW]
[ROW][C]192[/C][C]38[/C][C]37.2656[/C][C]0.734424[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]33.6648[/C][C]-1.6648[/C][/ROW]
[ROW][C]194[/C][C]35[/C][C]35.4682[/C][C]-0.468178[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]33.1789[/C][C]-1.17887[/C][/ROW]
[ROW][C]196[/C][C]37[/C][C]36.0151[/C][C]0.984913[/C][/ROW]
[ROW][C]197[/C][C]34[/C][C]32.8712[/C][C]1.12879[/C][/ROW]
[ROW][C]198[/C][C]33[/C][C]35.6412[/C][C]-2.64121[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]33.1519[/C][C]-0.151876[/C][/ROW]
[ROW][C]200[/C][C]26[/C][C]33.5182[/C][C]-7.51821[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]32.1963[/C][C]-2.19627[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]32.5734[/C][C]-8.57338[/C][/ROW]
[ROW][C]203[/C][C]34[/C][C]32.759[/C][C]1.24096[/C][/ROW]
[ROW][C]204[/C][C]34[/C][C]32.8557[/C][C]1.14429[/C][/ROW]
[ROW][C]205[/C][C]33[/C][C]34.6157[/C][C]-1.61573[/C][/ROW]
[ROW][C]206[/C][C]34[/C][C]35.2608[/C][C]-1.2608[/C][/ROW]
[ROW][C]207[/C][C]35[/C][C]35.8621[/C][C]-0.862124[/C][/ROW]
[ROW][C]208[/C][C]35[/C][C]35.3011[/C][C]-0.301056[/C][/ROW]
[ROW][C]209[/C][C]36[/C][C]33.2184[/C][C]2.78155[/C][/ROW]
[ROW][C]210[/C][C]34[/C][C]34.0909[/C][C]-0.0908929[/C][/ROW]
[ROW][C]211[/C][C]34[/C][C]32.9128[/C][C]1.08721[/C][/ROW]
[ROW][C]212[/C][C]41[/C][C]38.4591[/C][C]2.54095[/C][/ROW]
[ROW][C]213[/C][C]32[/C][C]36.0737[/C][C]-4.07367[/C][/ROW]
[ROW][C]214[/C][C]30[/C][C]33.3669[/C][C]-3.36693[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]34.4915[/C][C]0.508518[/C][/ROW]
[ROW][C]216[/C][C]28[/C][C]30.3159[/C][C]-2.3159[/C][/ROW]
[ROW][C]217[/C][C]33[/C][C]35.3439[/C][C]-2.3439[/C][/ROW]
[ROW][C]218[/C][C]39[/C][C]34.2808[/C][C]4.71924[/C][/ROW]
[ROW][C]219[/C][C]36[/C][C]33.7329[/C][C]2.26706[/C][/ROW]
[ROW][C]220[/C][C]36[/C][C]36.4802[/C][C]-0.480249[/C][/ROW]
[ROW][C]221[/C][C]35[/C][C]33.4688[/C][C]1.53117[/C][/ROW]
[ROW][C]222[/C][C]38[/C][C]35.2583[/C][C]2.74171[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]32.974[/C][C]0.0260294[/C][/ROW]
[ROW][C]224[/C][C]31[/C][C]33.3722[/C][C]-2.37216[/C][/ROW]
[ROW][C]225[/C][C]34[/C][C]34.2461[/C][C]-0.246132[/C][/ROW]
[ROW][C]226[/C][C]32[/C][C]34.6268[/C][C]-2.62682[/C][/ROW]
[ROW][C]227[/C][C]31[/C][C]33.7113[/C][C]-2.71131[/C][/ROW]
[ROW][C]228[/C][C]33[/C][C]34.2186[/C][C]-1.21859[/C][/ROW]
[ROW][C]229[/C][C]34[/C][C]32.4557[/C][C]1.54434[/C][/ROW]
[ROW][C]230[/C][C]34[/C][C]34.2464[/C][C]-0.246366[/C][/ROW]
[ROW][C]231[/C][C]34[/C][C]32.5212[/C][C]1.47883[/C][/ROW]
[ROW][C]232[/C][C]33[/C][C]34.9435[/C][C]-1.94349[/C][/ROW]
[ROW][C]233[/C][C]32[/C][C]34.9625[/C][C]-2.9625[/C][/ROW]
[ROW][C]234[/C][C]41[/C][C]33.9389[/C][C]7.06113[/C][/ROW]
[ROW][C]235[/C][C]34[/C][C]33.5351[/C][C]0.464913[/C][/ROW]
[ROW][C]236[/C][C]36[/C][C]32.2409[/C][C]3.75908[/C][/ROW]
[ROW][C]237[/C][C]37[/C][C]30.7628[/C][C]6.23721[/C][/ROW]
[ROW][C]238[/C][C]36[/C][C]30.8712[/C][C]5.12881[/C][/ROW]
[ROW][C]239[/C][C]29[/C][C]33.053[/C][C]-4.05305[/C][/ROW]
[ROW][C]240[/C][C]37[/C][C]31.8848[/C][C]5.11522[/C][/ROW]
[ROW][C]241[/C][C]27[/C][C]33.1991[/C][C]-6.19913[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.6559[/C][C]1.34406[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]30.9581[/C][C]-2.95813[/C][/ROW]
[ROW][C]244[/C][C]35[/C][C]33.4944[/C][C]1.50556[/C][/ROW]
[ROW][C]245[/C][C]37[/C][C]33.0402[/C][C]3.95977[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]33.8539[/C][C]-4.85392[/C][/ROW]
[ROW][C]247[/C][C]32[/C][C]34.5233[/C][C]-2.52335[/C][/ROW]
[ROW][C]248[/C][C]36[/C][C]32.1633[/C][C]3.83665[/C][/ROW]
[ROW][C]249[/C][C]19[/C][C]27.6552[/C][C]-8.65519[/C][/ROW]
[ROW][C]250[/C][C]21[/C][C]27.5235[/C][C]-6.52347[/C][/ROW]
[ROW][C]251[/C][C]31[/C][C]33.8675[/C][C]-2.86746[/C][/ROW]
[ROW][C]252[/C][C]33[/C][C]32.5556[/C][C]0.444368[/C][/ROW]
[ROW][C]253[/C][C]36[/C][C]34.1396[/C][C]1.86041[/C][/ROW]
[ROW][C]254[/C][C]33[/C][C]33.6289[/C][C]-0.62892[/C][/ROW]
[ROW][C]255[/C][C]37[/C][C]33.1352[/C][C]3.8648[/C][/ROW]
[ROW][C]256[/C][C]34[/C][C]33.5216[/C][C]0.478449[/C][/ROW]
[ROW][C]257[/C][C]35[/C][C]35.0255[/C][C]-0.0255269[/C][/ROW]
[ROW][C]258[/C][C]31[/C][C]32.8604[/C][C]-1.86042[/C][/ROW]
[ROW][C]259[/C][C]37[/C][C]33.9591[/C][C]3.04091[/C][/ROW]
[ROW][C]260[/C][C]35[/C][C]31.3265[/C][C]3.67355[/C][/ROW]
[ROW][C]261[/C][C]27[/C][C]32.6372[/C][C]-5.63723[/C][/ROW]
[ROW][C]262[/C][C]34[/C][C]35.5625[/C][C]-1.56252[/C][/ROW]
[ROW][C]263[/C][C]40[/C][C]33.8589[/C][C]6.14105[/C][/ROW]
[ROW][C]264[/C][C]29[/C][C]33.4392[/C][C]-4.43921[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221839&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221839&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
14135.81365.18643
23933.92555.07454
33035.0157-5.01565
43134.0404-3.04037
53435.0348-1.03478
63532.13252.86753
73933.02745.97263
83435.2232-1.22323
93634.81841.18161
103736.21310.786933
113833.53494.46507
123635.00060.999447
133834.56463.43538
143936.27782.72225
153336.1856-3.18561
163233.7953-1.79535
173633.42992.57008
183837.07560.924442
193936.72462.27539
203233.6668-1.66681
213234.4567-2.45669
223132.9186-1.91858
233936.67842.32158
243736.51880.48116
253933.98935.01069
264133.67887.3212
273635.1810.819023
283335.4171-2.41712
293333.9952-0.995172
303433.63160.36841
313133.3226-2.32264
322732.942-5.94198
333733.23443.76565
343435.9361-1.93609
353432.38871.6113
363233.6955-1.69548
372931.6605-2.66045
383633.81732.18274
392933.5349-4.53493
403534.21530.784749
413733.93643.06357
423433.74410.255877
433834.4643.53605
443533.61981.38021
453831.75636.24374
463733.98543.01464
473836.59971.40027
483334.505-1.50502
493636.266-0.265951
503833.34034.6597
513236.4124-4.41238
523232.4012-0.401175
533232.9505-0.950522
543436.0058-2.0058
553232.7976-0.797624
563734.76382.2362
573934.54534.45473
582934.7411-5.74108
593735.29621.70379
603534.29830.701733
613030.6676-0.667622
623834.4583.542
633434.7244-0.724353
643134.5604-3.56041
653433.17810.821949
663535.8018-0.801805
673634.71831.28174
683031.6714-1.67136
693936.52992.47006
703535.7521-0.752085
713834.57053.42948
723135.9158-4.91583
733436.9187-2.91865
743837.98110.0188829
753431.44472.55526
763932.48326.51679
773735.87561.12441
783432.87051.12946
792832.7272-4.72717
803731.56745.43259
813335.4969-2.49686
823536.0588-1.05876
833734.01712.98291
843234.4437-2.44368
853333.2023-0.202323
863836.5021.498
873334.5075-1.50754
882933.3955-4.39554
893332.95790.0420835
903134.9828-3.9828
913633.43512.56488
923537.5703-2.57033
933231.53790.462131
942932.2195-3.21954
953935.62023.37979
963734.56542.43455
973533.36191.6381
983734.71752.28252
993235.3314-3.33142
1003835.58352.41654
1013734.63932.36074
1023636.4147-0.414749
1033231.67150.328491
1043336.5448-3.54477
1054032.50127.49882
1063835.25752.74254
1074136.50794.49213
1083634.60151.39848
1094336.67056.32946
1103034.4344-4.4344
1113133.6619-2.66189
1123237.7811-5.78113
1133233.4703-1.47033
1143734.17832.82169
1153734.11452.8855
1163336.6827-3.68275
1173436.9286-2.9286
1183334.7168-1.7168
1193835.2022.79801
1203335.1282-2.12817
1213131.2734-0.273365
1223836.36371.63633
1233736.48550.514481
1243633.11352.88647
1253133.9694-2.9694
1263933.94655.05346
1274437.16216.83785
1283335.6554-2.65542
1293533.49221.50776
1303234.1539-2.15392
1312832.0259-4.02587
1324036.1453.85496
1332732.0519-5.05189
1343736.01340.9866
1353232.1375-0.137502
1362828.0733-0.073337
1373434.7107-0.710705
1383033.8752-3.87516
1393534.16490.835148
1403134.2565-3.25648
1413234.8274-2.82736
1423035.762-5.76204
1433034.9863-4.98635
1443129.76251.23754
1454032.59617.40388
1463231.79570.20431
1473634.72521.27482
1483233.1521-1.15212
1493532.61192.38811
1503836.08551.91449
1514235.28186.71819
1523436.6582-2.65824
1533536.826-1.82603
1543833.67754.32246
1553332.01820.981835
1563633.43512.56488
1573235.4731-3.47309
1583335.6554-2.65542
1593433.80050.199545
1603235.3438-3.34381
1613434.7879-0.787853
1622729.6825-2.68248
1633130.41750.582515
1643833.75324.24682
1653436.061-2.06104
1662431.1732-7.17319
1673033.8046-3.80463
1682629.5813-3.58128
1693435.3206-1.32056
1702735.2095-8.20953
1713732.20774.79228
1723635.92430.0757091
1734134.17176.82827
1742929.3307-0.330742
1753631.30874.69127
1763234.9678-2.96785
1773733.12173.87826
1783031.7931-1.79308
1793133.1848-2.18482
1803835.06352.93651
1813635.44730.552672
1823532.35512.64495
1833135.837-4.83703
1843833.60154.39854
1852230.8302-8.83023
1863234.9071-2.90711
1873634.57211.42794
1883932.82276.17726
1892831.133-3.13302
1903234.1922-2.19223
1913234.8755-2.87547
1923837.26560.734424
1933233.6648-1.6648
1943535.4682-0.468178
1953233.1789-1.17887
1963736.01510.984913
1973432.87121.12879
1983335.6412-2.64121
1993333.1519-0.151876
2002633.5182-7.51821
2013032.1963-2.19627
2022432.5734-8.57338
2033432.7591.24096
2043432.85571.14429
2053334.6157-1.61573
2063435.2608-1.2608
2073535.8621-0.862124
2083535.3011-0.301056
2093633.21842.78155
2103434.0909-0.0908929
2113432.91281.08721
2124138.45912.54095
2133236.0737-4.07367
2143033.3669-3.36693
2153534.49150.508518
2162830.3159-2.3159
2173335.3439-2.3439
2183934.28084.71924
2193633.73292.26706
2203636.4802-0.480249
2213533.46881.53117
2223835.25832.74171
2233332.9740.0260294
2243133.3722-2.37216
2253434.2461-0.246132
2263234.6268-2.62682
2273133.7113-2.71131
2283334.2186-1.21859
2293432.45571.54434
2303434.2464-0.246366
2313432.52121.47883
2323334.9435-1.94349
2333234.9625-2.9625
2344133.93897.06113
2353433.53510.464913
2363632.24093.75908
2373730.76286.23721
2383630.87125.12881
2392933.053-4.05305
2403731.88485.11522
2412733.1991-6.19913
2423533.65591.34406
2432830.9581-2.95813
2443533.49441.50556
2453733.04023.95977
2462933.8539-4.85392
2473234.5233-2.52335
2483632.16333.83665
2491927.6552-8.65519
2502127.5235-6.52347
2513133.8675-2.86746
2523332.55560.444368
2533634.13961.86041
2543333.6289-0.62892
2553733.13523.8648
2563433.52160.478449
2573535.0255-0.0255269
2583132.8604-1.86042
2593733.95913.04091
2603531.32653.67355
2612732.6372-5.63723
2623435.5625-1.56252
2634033.85896.14105
2642933.4392-4.43921






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.907060.1858790.0929397
100.8381410.3237190.161859
110.7500730.4998550.249927
120.7260010.5479980.273999
130.7803120.4393760.219688
140.7151020.5697960.284898
150.7104140.5791730.289586
160.6973920.6052170.302608
170.6188050.762390.381195
180.5416180.9167640.458382
190.5038950.992210.496105
200.4940530.9881050.505947
210.5155150.968970.484485
220.458480.916960.54152
230.4252060.8504130.574794
240.3559410.7118820.644059
250.3874350.774870.612565
260.6340120.7319750.365988
270.5734680.8530640.426532
280.5395510.9208980.460449
290.5009870.9980260.499013
300.4438850.8877690.556115
310.4447060.8894120.555294
320.5896840.8206320.410316
330.5779590.8440830.422041
340.5464870.9070270.453513
350.4965050.993010.503495
360.4469550.893910.553045
370.4008130.8016270.599187
380.3694270.7388530.630573
390.4803270.9606530.519673
400.4282870.8565730.571713
410.3975170.7950340.602483
420.3484070.6968140.651593
430.3135060.6270120.686494
440.2766770.5533530.723323
450.3405330.6810670.659467
460.3552240.7104480.644776
470.3199230.6398460.680077
480.2948750.5897510.705125
490.2542790.5085580.745721
500.2661680.5323350.733832
510.306130.6122610.69387
520.2731060.5462110.726894
530.2375330.4750660.762467
540.214120.4282390.78588
550.1824990.3649970.817501
560.1692610.3385220.830739
570.1823940.3647890.817606
580.2822660.5645320.717734
590.2536610.5073230.746339
600.2199790.4399570.780021
610.194330.388660.80567
620.188760.3775210.81124
630.1642310.3284620.835769
640.1674870.3349740.832513
650.143020.2860390.85698
660.1226030.2452060.877397
670.1035640.2071270.896436
680.1107370.2214730.889263
690.1104010.2208020.889599
700.09313640.1862730.906864
710.09811120.1962220.901889
720.1197870.2395730.880213
730.1147680.2295350.885232
740.09605320.1921060.903947
750.08379030.1675810.91621
760.1220010.2440030.877999
770.1049030.2098060.895097
780.08863790.1772760.911362
790.1127290.2254570.887271
800.1289330.2578660.871067
810.1219450.243890.878055
820.1051130.2102260.894887
830.09941130.1988230.900589
840.09441420.1888280.905586
850.08157390.1631480.918426
860.07214290.1442860.927857
870.06357360.1271470.936426
880.07936360.1587270.920636
890.06600770.1320150.933992
900.06976150.1395230.930238
910.06351270.1270250.936487
920.05650570.1130110.943494
930.04713420.09426840.952866
940.04840130.09680250.951599
950.04798440.09596880.952016
960.04419020.08838040.95581
970.03752660.07505320.962473
980.03324910.06649810.966751
990.03325140.06650280.966749
1000.03051750.0610350.969482
1010.02737070.05474140.972629
1020.02252370.04504740.977476
1030.01859250.0371850.981407
1040.01866840.03733670.981332
1050.0461670.0923340.953833
1060.04328580.08657170.956714
1070.05360120.1072020.946399
1080.04589470.09178930.954105
1090.0750110.1500220.924989
1100.08863410.1772680.911366
1110.08503410.1700680.914966
1120.1148460.2296910.885154
1130.1019090.2038190.898091
1140.09776990.195540.90223
1150.09427550.1885510.905725
1160.09422770.1884550.905772
1170.08998090.1799620.910019
1180.07866380.1573280.921336
1190.07480170.1496030.925198
1200.06697340.1339470.933027
1210.058540.117080.94146
1220.05318070.1063610.946819
1230.04497360.08994720.955026
1240.04316340.08632680.956837
1250.04079270.08158540.959207
1260.05231790.1046360.947682
1270.09536760.1907350.904632
1280.09133490.182670.908665
1290.08043590.1608720.919564
1300.07420810.1484160.925792
1310.08136330.1627270.918637
1320.08742350.1748470.912577
1330.1079950.2159890.892005
1340.09466660.1893330.905333
1350.0814970.1629940.918503
1360.0707870.1415740.929213
1370.06001740.1200350.939983
1380.06377860.1275570.936221
1390.05404540.1080910.945955
1400.05332150.1066430.946678
1410.05241470.1048290.947585
1420.07372390.1474480.926276
1430.08727980.174560.91272
1440.08144310.1628860.918557
1450.1488330.2976670.851167
1460.1371270.2742540.862873
1470.1218430.2436860.878157
1480.1069590.2139180.893041
1490.0987610.1975220.901239
1500.08785350.1757070.912146
1510.1422150.284430.857785
1520.1334140.2668270.866586
1530.1203950.2407890.879605
1540.1324610.2649220.867539
1550.1148870.2297750.885113
1560.1135870.2271730.886413
1570.1164570.2329140.883543
1580.1086410.2172820.891359
1590.09490520.189810.905095
1600.09913080.1982620.900869
1610.08533730.1706750.914663
1620.08043020.160860.91957
1630.07002590.1400520.929974
1640.08641080.1728220.913589
1650.07829770.1565950.921702
1660.1432470.2864940.856753
1670.1438750.287750.856125
1680.1398850.279770.860115
1690.1260310.2520630.873969
1700.2447020.4894030.755298
1710.2777380.5554750.722262
1720.2481170.4962330.751883
1730.3408080.6816170.659192
1740.3073190.6146370.692681
1750.3625630.7251260.637437
1760.348090.696180.65191
1770.3561420.7122830.643858
1780.328740.657480.67126
1790.3032390.6064780.696761
1800.2891180.5782360.710882
1810.2607850.521570.739215
1820.2577020.5154030.742298
1830.2693350.5386690.730665
1840.321980.6439610.67802
1850.5733270.8533460.426673
1860.5641170.8717650.435883
1870.5511140.8977720.448886
1880.6791380.6417230.320862
1890.6661980.6676050.333802
1900.6589110.6821780.341089
1910.6513160.6973690.348684
1920.6168810.7662380.383119
1930.5837430.8325130.416257
1940.5435010.9129980.456499
1950.505970.9880610.49403
1960.4695840.9391690.530416
1970.4526840.9053690.547316
1980.4328140.8656280.567186
1990.3925460.7850910.607454
2000.5130830.9738350.486917
2010.4787150.957430.521285
2020.6662210.6675590.333779
2030.6302040.7395920.369796
2040.5907540.8184920.409246
2050.5517590.8964820.448241
2060.5130640.9738710.486936
2070.4697220.9394440.530278
2080.425980.851960.57402
2090.3995080.7990170.600492
2100.3594980.7189950.640502
2110.3206680.6413360.679332
2120.2911840.5823680.708816
2130.3360540.6721080.663946
2140.3111220.6222450.688878
2150.2714220.5428430.728578
2160.2387270.4774530.761273
2170.2107230.4214460.789277
2180.2495920.4991840.750408
2190.222080.444160.77792
2200.1942940.3885880.805706
2210.1656450.3312910.834355
2220.1532830.3065670.846717
2230.1255930.2511860.874407
2240.1080320.2160640.891968
2250.0888240.1776480.911176
2260.09589630.1917930.904104
2270.0867680.1735360.913232
2280.06851120.1370220.931489
2290.05339760.1067950.946602
2300.04097340.08194680.959027
2310.03845830.07691660.961542
2320.05506110.1101220.944939
2330.04357240.08714490.956428
2340.1386020.2772050.861398
2350.1113630.2227270.888637
2360.1029840.2059680.897016
2370.09311140.1862230.906889
2380.2276540.4553080.772346
2390.188630.377260.81137
2400.2910180.5820370.708982
2410.3595240.7190480.640476
2420.2956480.5912960.704352
2430.2565020.5130040.743498
2440.2086870.4173740.791313
2450.4291310.8582610.570869
2460.7060640.5878730.293936
2470.6762330.6475340.323767
2480.6491750.701650.350825
2490.6898720.6202560.310128
2500.6298670.7402660.370133
2510.6782550.643490.321745
2520.7920120.4159750.207988
2530.7054740.5890520.294526
2540.9099770.1800450.0900226
2550.8246750.350650.175325

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.90706 & 0.185879 & 0.0929397 \tabularnewline
10 & 0.838141 & 0.323719 & 0.161859 \tabularnewline
11 & 0.750073 & 0.499855 & 0.249927 \tabularnewline
12 & 0.726001 & 0.547998 & 0.273999 \tabularnewline
13 & 0.780312 & 0.439376 & 0.219688 \tabularnewline
14 & 0.715102 & 0.569796 & 0.284898 \tabularnewline
15 & 0.710414 & 0.579173 & 0.289586 \tabularnewline
16 & 0.697392 & 0.605217 & 0.302608 \tabularnewline
17 & 0.618805 & 0.76239 & 0.381195 \tabularnewline
18 & 0.541618 & 0.916764 & 0.458382 \tabularnewline
19 & 0.503895 & 0.99221 & 0.496105 \tabularnewline
20 & 0.494053 & 0.988105 & 0.505947 \tabularnewline
21 & 0.515515 & 0.96897 & 0.484485 \tabularnewline
22 & 0.45848 & 0.91696 & 0.54152 \tabularnewline
23 & 0.425206 & 0.850413 & 0.574794 \tabularnewline
24 & 0.355941 & 0.711882 & 0.644059 \tabularnewline
25 & 0.387435 & 0.77487 & 0.612565 \tabularnewline
26 & 0.634012 & 0.731975 & 0.365988 \tabularnewline
27 & 0.573468 & 0.853064 & 0.426532 \tabularnewline
28 & 0.539551 & 0.920898 & 0.460449 \tabularnewline
29 & 0.500987 & 0.998026 & 0.499013 \tabularnewline
30 & 0.443885 & 0.887769 & 0.556115 \tabularnewline
31 & 0.444706 & 0.889412 & 0.555294 \tabularnewline
32 & 0.589684 & 0.820632 & 0.410316 \tabularnewline
33 & 0.577959 & 0.844083 & 0.422041 \tabularnewline
34 & 0.546487 & 0.907027 & 0.453513 \tabularnewline
35 & 0.496505 & 0.99301 & 0.503495 \tabularnewline
36 & 0.446955 & 0.89391 & 0.553045 \tabularnewline
37 & 0.400813 & 0.801627 & 0.599187 \tabularnewline
38 & 0.369427 & 0.738853 & 0.630573 \tabularnewline
39 & 0.480327 & 0.960653 & 0.519673 \tabularnewline
40 & 0.428287 & 0.856573 & 0.571713 \tabularnewline
41 & 0.397517 & 0.795034 & 0.602483 \tabularnewline
42 & 0.348407 & 0.696814 & 0.651593 \tabularnewline
43 & 0.313506 & 0.627012 & 0.686494 \tabularnewline
44 & 0.276677 & 0.553353 & 0.723323 \tabularnewline
45 & 0.340533 & 0.681067 & 0.659467 \tabularnewline
46 & 0.355224 & 0.710448 & 0.644776 \tabularnewline
47 & 0.319923 & 0.639846 & 0.680077 \tabularnewline
48 & 0.294875 & 0.589751 & 0.705125 \tabularnewline
49 & 0.254279 & 0.508558 & 0.745721 \tabularnewline
50 & 0.266168 & 0.532335 & 0.733832 \tabularnewline
51 & 0.30613 & 0.612261 & 0.69387 \tabularnewline
52 & 0.273106 & 0.546211 & 0.726894 \tabularnewline
53 & 0.237533 & 0.475066 & 0.762467 \tabularnewline
54 & 0.21412 & 0.428239 & 0.78588 \tabularnewline
55 & 0.182499 & 0.364997 & 0.817501 \tabularnewline
56 & 0.169261 & 0.338522 & 0.830739 \tabularnewline
57 & 0.182394 & 0.364789 & 0.817606 \tabularnewline
58 & 0.282266 & 0.564532 & 0.717734 \tabularnewline
59 & 0.253661 & 0.507323 & 0.746339 \tabularnewline
60 & 0.219979 & 0.439957 & 0.780021 \tabularnewline
61 & 0.19433 & 0.38866 & 0.80567 \tabularnewline
62 & 0.18876 & 0.377521 & 0.81124 \tabularnewline
63 & 0.164231 & 0.328462 & 0.835769 \tabularnewline
64 & 0.167487 & 0.334974 & 0.832513 \tabularnewline
65 & 0.14302 & 0.286039 & 0.85698 \tabularnewline
66 & 0.122603 & 0.245206 & 0.877397 \tabularnewline
67 & 0.103564 & 0.207127 & 0.896436 \tabularnewline
68 & 0.110737 & 0.221473 & 0.889263 \tabularnewline
69 & 0.110401 & 0.220802 & 0.889599 \tabularnewline
70 & 0.0931364 & 0.186273 & 0.906864 \tabularnewline
71 & 0.0981112 & 0.196222 & 0.901889 \tabularnewline
72 & 0.119787 & 0.239573 & 0.880213 \tabularnewline
73 & 0.114768 & 0.229535 & 0.885232 \tabularnewline
74 & 0.0960532 & 0.192106 & 0.903947 \tabularnewline
75 & 0.0837903 & 0.167581 & 0.91621 \tabularnewline
76 & 0.122001 & 0.244003 & 0.877999 \tabularnewline
77 & 0.104903 & 0.209806 & 0.895097 \tabularnewline
78 & 0.0886379 & 0.177276 & 0.911362 \tabularnewline
79 & 0.112729 & 0.225457 & 0.887271 \tabularnewline
80 & 0.128933 & 0.257866 & 0.871067 \tabularnewline
81 & 0.121945 & 0.24389 & 0.878055 \tabularnewline
82 & 0.105113 & 0.210226 & 0.894887 \tabularnewline
83 & 0.0994113 & 0.198823 & 0.900589 \tabularnewline
84 & 0.0944142 & 0.188828 & 0.905586 \tabularnewline
85 & 0.0815739 & 0.163148 & 0.918426 \tabularnewline
86 & 0.0721429 & 0.144286 & 0.927857 \tabularnewline
87 & 0.0635736 & 0.127147 & 0.936426 \tabularnewline
88 & 0.0793636 & 0.158727 & 0.920636 \tabularnewline
89 & 0.0660077 & 0.132015 & 0.933992 \tabularnewline
90 & 0.0697615 & 0.139523 & 0.930238 \tabularnewline
91 & 0.0635127 & 0.127025 & 0.936487 \tabularnewline
92 & 0.0565057 & 0.113011 & 0.943494 \tabularnewline
93 & 0.0471342 & 0.0942684 & 0.952866 \tabularnewline
94 & 0.0484013 & 0.0968025 & 0.951599 \tabularnewline
95 & 0.0479844 & 0.0959688 & 0.952016 \tabularnewline
96 & 0.0441902 & 0.0883804 & 0.95581 \tabularnewline
97 & 0.0375266 & 0.0750532 & 0.962473 \tabularnewline
98 & 0.0332491 & 0.0664981 & 0.966751 \tabularnewline
99 & 0.0332514 & 0.0665028 & 0.966749 \tabularnewline
100 & 0.0305175 & 0.061035 & 0.969482 \tabularnewline
101 & 0.0273707 & 0.0547414 & 0.972629 \tabularnewline
102 & 0.0225237 & 0.0450474 & 0.977476 \tabularnewline
103 & 0.0185925 & 0.037185 & 0.981407 \tabularnewline
104 & 0.0186684 & 0.0373367 & 0.981332 \tabularnewline
105 & 0.046167 & 0.092334 & 0.953833 \tabularnewline
106 & 0.0432858 & 0.0865717 & 0.956714 \tabularnewline
107 & 0.0536012 & 0.107202 & 0.946399 \tabularnewline
108 & 0.0458947 & 0.0917893 & 0.954105 \tabularnewline
109 & 0.075011 & 0.150022 & 0.924989 \tabularnewline
110 & 0.0886341 & 0.177268 & 0.911366 \tabularnewline
111 & 0.0850341 & 0.170068 & 0.914966 \tabularnewline
112 & 0.114846 & 0.229691 & 0.885154 \tabularnewline
113 & 0.101909 & 0.203819 & 0.898091 \tabularnewline
114 & 0.0977699 & 0.19554 & 0.90223 \tabularnewline
115 & 0.0942755 & 0.188551 & 0.905725 \tabularnewline
116 & 0.0942277 & 0.188455 & 0.905772 \tabularnewline
117 & 0.0899809 & 0.179962 & 0.910019 \tabularnewline
118 & 0.0786638 & 0.157328 & 0.921336 \tabularnewline
119 & 0.0748017 & 0.149603 & 0.925198 \tabularnewline
120 & 0.0669734 & 0.133947 & 0.933027 \tabularnewline
121 & 0.05854 & 0.11708 & 0.94146 \tabularnewline
122 & 0.0531807 & 0.106361 & 0.946819 \tabularnewline
123 & 0.0449736 & 0.0899472 & 0.955026 \tabularnewline
124 & 0.0431634 & 0.0863268 & 0.956837 \tabularnewline
125 & 0.0407927 & 0.0815854 & 0.959207 \tabularnewline
126 & 0.0523179 & 0.104636 & 0.947682 \tabularnewline
127 & 0.0953676 & 0.190735 & 0.904632 \tabularnewline
128 & 0.0913349 & 0.18267 & 0.908665 \tabularnewline
129 & 0.0804359 & 0.160872 & 0.919564 \tabularnewline
130 & 0.0742081 & 0.148416 & 0.925792 \tabularnewline
131 & 0.0813633 & 0.162727 & 0.918637 \tabularnewline
132 & 0.0874235 & 0.174847 & 0.912577 \tabularnewline
133 & 0.107995 & 0.215989 & 0.892005 \tabularnewline
134 & 0.0946666 & 0.189333 & 0.905333 \tabularnewline
135 & 0.081497 & 0.162994 & 0.918503 \tabularnewline
136 & 0.070787 & 0.141574 & 0.929213 \tabularnewline
137 & 0.0600174 & 0.120035 & 0.939983 \tabularnewline
138 & 0.0637786 & 0.127557 & 0.936221 \tabularnewline
139 & 0.0540454 & 0.108091 & 0.945955 \tabularnewline
140 & 0.0533215 & 0.106643 & 0.946678 \tabularnewline
141 & 0.0524147 & 0.104829 & 0.947585 \tabularnewline
142 & 0.0737239 & 0.147448 & 0.926276 \tabularnewline
143 & 0.0872798 & 0.17456 & 0.91272 \tabularnewline
144 & 0.0814431 & 0.162886 & 0.918557 \tabularnewline
145 & 0.148833 & 0.297667 & 0.851167 \tabularnewline
146 & 0.137127 & 0.274254 & 0.862873 \tabularnewline
147 & 0.121843 & 0.243686 & 0.878157 \tabularnewline
148 & 0.106959 & 0.213918 & 0.893041 \tabularnewline
149 & 0.098761 & 0.197522 & 0.901239 \tabularnewline
150 & 0.0878535 & 0.175707 & 0.912146 \tabularnewline
151 & 0.142215 & 0.28443 & 0.857785 \tabularnewline
152 & 0.133414 & 0.266827 & 0.866586 \tabularnewline
153 & 0.120395 & 0.240789 & 0.879605 \tabularnewline
154 & 0.132461 & 0.264922 & 0.867539 \tabularnewline
155 & 0.114887 & 0.229775 & 0.885113 \tabularnewline
156 & 0.113587 & 0.227173 & 0.886413 \tabularnewline
157 & 0.116457 & 0.232914 & 0.883543 \tabularnewline
158 & 0.108641 & 0.217282 & 0.891359 \tabularnewline
159 & 0.0949052 & 0.18981 & 0.905095 \tabularnewline
160 & 0.0991308 & 0.198262 & 0.900869 \tabularnewline
161 & 0.0853373 & 0.170675 & 0.914663 \tabularnewline
162 & 0.0804302 & 0.16086 & 0.91957 \tabularnewline
163 & 0.0700259 & 0.140052 & 0.929974 \tabularnewline
164 & 0.0864108 & 0.172822 & 0.913589 \tabularnewline
165 & 0.0782977 & 0.156595 & 0.921702 \tabularnewline
166 & 0.143247 & 0.286494 & 0.856753 \tabularnewline
167 & 0.143875 & 0.28775 & 0.856125 \tabularnewline
168 & 0.139885 & 0.27977 & 0.860115 \tabularnewline
169 & 0.126031 & 0.252063 & 0.873969 \tabularnewline
170 & 0.244702 & 0.489403 & 0.755298 \tabularnewline
171 & 0.277738 & 0.555475 & 0.722262 \tabularnewline
172 & 0.248117 & 0.496233 & 0.751883 \tabularnewline
173 & 0.340808 & 0.681617 & 0.659192 \tabularnewline
174 & 0.307319 & 0.614637 & 0.692681 \tabularnewline
175 & 0.362563 & 0.725126 & 0.637437 \tabularnewline
176 & 0.34809 & 0.69618 & 0.65191 \tabularnewline
177 & 0.356142 & 0.712283 & 0.643858 \tabularnewline
178 & 0.32874 & 0.65748 & 0.67126 \tabularnewline
179 & 0.303239 & 0.606478 & 0.696761 \tabularnewline
180 & 0.289118 & 0.578236 & 0.710882 \tabularnewline
181 & 0.260785 & 0.52157 & 0.739215 \tabularnewline
182 & 0.257702 & 0.515403 & 0.742298 \tabularnewline
183 & 0.269335 & 0.538669 & 0.730665 \tabularnewline
184 & 0.32198 & 0.643961 & 0.67802 \tabularnewline
185 & 0.573327 & 0.853346 & 0.426673 \tabularnewline
186 & 0.564117 & 0.871765 & 0.435883 \tabularnewline
187 & 0.551114 & 0.897772 & 0.448886 \tabularnewline
188 & 0.679138 & 0.641723 & 0.320862 \tabularnewline
189 & 0.666198 & 0.667605 & 0.333802 \tabularnewline
190 & 0.658911 & 0.682178 & 0.341089 \tabularnewline
191 & 0.651316 & 0.697369 & 0.348684 \tabularnewline
192 & 0.616881 & 0.766238 & 0.383119 \tabularnewline
193 & 0.583743 & 0.832513 & 0.416257 \tabularnewline
194 & 0.543501 & 0.912998 & 0.456499 \tabularnewline
195 & 0.50597 & 0.988061 & 0.49403 \tabularnewline
196 & 0.469584 & 0.939169 & 0.530416 \tabularnewline
197 & 0.452684 & 0.905369 & 0.547316 \tabularnewline
198 & 0.432814 & 0.865628 & 0.567186 \tabularnewline
199 & 0.392546 & 0.785091 & 0.607454 \tabularnewline
200 & 0.513083 & 0.973835 & 0.486917 \tabularnewline
201 & 0.478715 & 0.95743 & 0.521285 \tabularnewline
202 & 0.666221 & 0.667559 & 0.333779 \tabularnewline
203 & 0.630204 & 0.739592 & 0.369796 \tabularnewline
204 & 0.590754 & 0.818492 & 0.409246 \tabularnewline
205 & 0.551759 & 0.896482 & 0.448241 \tabularnewline
206 & 0.513064 & 0.973871 & 0.486936 \tabularnewline
207 & 0.469722 & 0.939444 & 0.530278 \tabularnewline
208 & 0.42598 & 0.85196 & 0.57402 \tabularnewline
209 & 0.399508 & 0.799017 & 0.600492 \tabularnewline
210 & 0.359498 & 0.718995 & 0.640502 \tabularnewline
211 & 0.320668 & 0.641336 & 0.679332 \tabularnewline
212 & 0.291184 & 0.582368 & 0.708816 \tabularnewline
213 & 0.336054 & 0.672108 & 0.663946 \tabularnewline
214 & 0.311122 & 0.622245 & 0.688878 \tabularnewline
215 & 0.271422 & 0.542843 & 0.728578 \tabularnewline
216 & 0.238727 & 0.477453 & 0.761273 \tabularnewline
217 & 0.210723 & 0.421446 & 0.789277 \tabularnewline
218 & 0.249592 & 0.499184 & 0.750408 \tabularnewline
219 & 0.22208 & 0.44416 & 0.77792 \tabularnewline
220 & 0.194294 & 0.388588 & 0.805706 \tabularnewline
221 & 0.165645 & 0.331291 & 0.834355 \tabularnewline
222 & 0.153283 & 0.306567 & 0.846717 \tabularnewline
223 & 0.125593 & 0.251186 & 0.874407 \tabularnewline
224 & 0.108032 & 0.216064 & 0.891968 \tabularnewline
225 & 0.088824 & 0.177648 & 0.911176 \tabularnewline
226 & 0.0958963 & 0.191793 & 0.904104 \tabularnewline
227 & 0.086768 & 0.173536 & 0.913232 \tabularnewline
228 & 0.0685112 & 0.137022 & 0.931489 \tabularnewline
229 & 0.0533976 & 0.106795 & 0.946602 \tabularnewline
230 & 0.0409734 & 0.0819468 & 0.959027 \tabularnewline
231 & 0.0384583 & 0.0769166 & 0.961542 \tabularnewline
232 & 0.0550611 & 0.110122 & 0.944939 \tabularnewline
233 & 0.0435724 & 0.0871449 & 0.956428 \tabularnewline
234 & 0.138602 & 0.277205 & 0.861398 \tabularnewline
235 & 0.111363 & 0.222727 & 0.888637 \tabularnewline
236 & 0.102984 & 0.205968 & 0.897016 \tabularnewline
237 & 0.0931114 & 0.186223 & 0.906889 \tabularnewline
238 & 0.227654 & 0.455308 & 0.772346 \tabularnewline
239 & 0.18863 & 0.37726 & 0.81137 \tabularnewline
240 & 0.291018 & 0.582037 & 0.708982 \tabularnewline
241 & 0.359524 & 0.719048 & 0.640476 \tabularnewline
242 & 0.295648 & 0.591296 & 0.704352 \tabularnewline
243 & 0.256502 & 0.513004 & 0.743498 \tabularnewline
244 & 0.208687 & 0.417374 & 0.791313 \tabularnewline
245 & 0.429131 & 0.858261 & 0.570869 \tabularnewline
246 & 0.706064 & 0.587873 & 0.293936 \tabularnewline
247 & 0.676233 & 0.647534 & 0.323767 \tabularnewline
248 & 0.649175 & 0.70165 & 0.350825 \tabularnewline
249 & 0.689872 & 0.620256 & 0.310128 \tabularnewline
250 & 0.629867 & 0.740266 & 0.370133 \tabularnewline
251 & 0.678255 & 0.64349 & 0.321745 \tabularnewline
252 & 0.792012 & 0.415975 & 0.207988 \tabularnewline
253 & 0.705474 & 0.589052 & 0.294526 \tabularnewline
254 & 0.909977 & 0.180045 & 0.0900226 \tabularnewline
255 & 0.824675 & 0.35065 & 0.175325 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221839&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]0.90706[/C][C]0.185879[/C][C]0.0929397[/C][/ROW]
[ROW][C]10[/C][C]0.838141[/C][C]0.323719[/C][C]0.161859[/C][/ROW]
[ROW][C]11[/C][C]0.750073[/C][C]0.499855[/C][C]0.249927[/C][/ROW]
[ROW][C]12[/C][C]0.726001[/C][C]0.547998[/C][C]0.273999[/C][/ROW]
[ROW][C]13[/C][C]0.780312[/C][C]0.439376[/C][C]0.219688[/C][/ROW]
[ROW][C]14[/C][C]0.715102[/C][C]0.569796[/C][C]0.284898[/C][/ROW]
[ROW][C]15[/C][C]0.710414[/C][C]0.579173[/C][C]0.289586[/C][/ROW]
[ROW][C]16[/C][C]0.697392[/C][C]0.605217[/C][C]0.302608[/C][/ROW]
[ROW][C]17[/C][C]0.618805[/C][C]0.76239[/C][C]0.381195[/C][/ROW]
[ROW][C]18[/C][C]0.541618[/C][C]0.916764[/C][C]0.458382[/C][/ROW]
[ROW][C]19[/C][C]0.503895[/C][C]0.99221[/C][C]0.496105[/C][/ROW]
[ROW][C]20[/C][C]0.494053[/C][C]0.988105[/C][C]0.505947[/C][/ROW]
[ROW][C]21[/C][C]0.515515[/C][C]0.96897[/C][C]0.484485[/C][/ROW]
[ROW][C]22[/C][C]0.45848[/C][C]0.91696[/C][C]0.54152[/C][/ROW]
[ROW][C]23[/C][C]0.425206[/C][C]0.850413[/C][C]0.574794[/C][/ROW]
[ROW][C]24[/C][C]0.355941[/C][C]0.711882[/C][C]0.644059[/C][/ROW]
[ROW][C]25[/C][C]0.387435[/C][C]0.77487[/C][C]0.612565[/C][/ROW]
[ROW][C]26[/C][C]0.634012[/C][C]0.731975[/C][C]0.365988[/C][/ROW]
[ROW][C]27[/C][C]0.573468[/C][C]0.853064[/C][C]0.426532[/C][/ROW]
[ROW][C]28[/C][C]0.539551[/C][C]0.920898[/C][C]0.460449[/C][/ROW]
[ROW][C]29[/C][C]0.500987[/C][C]0.998026[/C][C]0.499013[/C][/ROW]
[ROW][C]30[/C][C]0.443885[/C][C]0.887769[/C][C]0.556115[/C][/ROW]
[ROW][C]31[/C][C]0.444706[/C][C]0.889412[/C][C]0.555294[/C][/ROW]
[ROW][C]32[/C][C]0.589684[/C][C]0.820632[/C][C]0.410316[/C][/ROW]
[ROW][C]33[/C][C]0.577959[/C][C]0.844083[/C][C]0.422041[/C][/ROW]
[ROW][C]34[/C][C]0.546487[/C][C]0.907027[/C][C]0.453513[/C][/ROW]
[ROW][C]35[/C][C]0.496505[/C][C]0.99301[/C][C]0.503495[/C][/ROW]
[ROW][C]36[/C][C]0.446955[/C][C]0.89391[/C][C]0.553045[/C][/ROW]
[ROW][C]37[/C][C]0.400813[/C][C]0.801627[/C][C]0.599187[/C][/ROW]
[ROW][C]38[/C][C]0.369427[/C][C]0.738853[/C][C]0.630573[/C][/ROW]
[ROW][C]39[/C][C]0.480327[/C][C]0.960653[/C][C]0.519673[/C][/ROW]
[ROW][C]40[/C][C]0.428287[/C][C]0.856573[/C][C]0.571713[/C][/ROW]
[ROW][C]41[/C][C]0.397517[/C][C]0.795034[/C][C]0.602483[/C][/ROW]
[ROW][C]42[/C][C]0.348407[/C][C]0.696814[/C][C]0.651593[/C][/ROW]
[ROW][C]43[/C][C]0.313506[/C][C]0.627012[/C][C]0.686494[/C][/ROW]
[ROW][C]44[/C][C]0.276677[/C][C]0.553353[/C][C]0.723323[/C][/ROW]
[ROW][C]45[/C][C]0.340533[/C][C]0.681067[/C][C]0.659467[/C][/ROW]
[ROW][C]46[/C][C]0.355224[/C][C]0.710448[/C][C]0.644776[/C][/ROW]
[ROW][C]47[/C][C]0.319923[/C][C]0.639846[/C][C]0.680077[/C][/ROW]
[ROW][C]48[/C][C]0.294875[/C][C]0.589751[/C][C]0.705125[/C][/ROW]
[ROW][C]49[/C][C]0.254279[/C][C]0.508558[/C][C]0.745721[/C][/ROW]
[ROW][C]50[/C][C]0.266168[/C][C]0.532335[/C][C]0.733832[/C][/ROW]
[ROW][C]51[/C][C]0.30613[/C][C]0.612261[/C][C]0.69387[/C][/ROW]
[ROW][C]52[/C][C]0.273106[/C][C]0.546211[/C][C]0.726894[/C][/ROW]
[ROW][C]53[/C][C]0.237533[/C][C]0.475066[/C][C]0.762467[/C][/ROW]
[ROW][C]54[/C][C]0.21412[/C][C]0.428239[/C][C]0.78588[/C][/ROW]
[ROW][C]55[/C][C]0.182499[/C][C]0.364997[/C][C]0.817501[/C][/ROW]
[ROW][C]56[/C][C]0.169261[/C][C]0.338522[/C][C]0.830739[/C][/ROW]
[ROW][C]57[/C][C]0.182394[/C][C]0.364789[/C][C]0.817606[/C][/ROW]
[ROW][C]58[/C][C]0.282266[/C][C]0.564532[/C][C]0.717734[/C][/ROW]
[ROW][C]59[/C][C]0.253661[/C][C]0.507323[/C][C]0.746339[/C][/ROW]
[ROW][C]60[/C][C]0.219979[/C][C]0.439957[/C][C]0.780021[/C][/ROW]
[ROW][C]61[/C][C]0.19433[/C][C]0.38866[/C][C]0.80567[/C][/ROW]
[ROW][C]62[/C][C]0.18876[/C][C]0.377521[/C][C]0.81124[/C][/ROW]
[ROW][C]63[/C][C]0.164231[/C][C]0.328462[/C][C]0.835769[/C][/ROW]
[ROW][C]64[/C][C]0.167487[/C][C]0.334974[/C][C]0.832513[/C][/ROW]
[ROW][C]65[/C][C]0.14302[/C][C]0.286039[/C][C]0.85698[/C][/ROW]
[ROW][C]66[/C][C]0.122603[/C][C]0.245206[/C][C]0.877397[/C][/ROW]
[ROW][C]67[/C][C]0.103564[/C][C]0.207127[/C][C]0.896436[/C][/ROW]
[ROW][C]68[/C][C]0.110737[/C][C]0.221473[/C][C]0.889263[/C][/ROW]
[ROW][C]69[/C][C]0.110401[/C][C]0.220802[/C][C]0.889599[/C][/ROW]
[ROW][C]70[/C][C]0.0931364[/C][C]0.186273[/C][C]0.906864[/C][/ROW]
[ROW][C]71[/C][C]0.0981112[/C][C]0.196222[/C][C]0.901889[/C][/ROW]
[ROW][C]72[/C][C]0.119787[/C][C]0.239573[/C][C]0.880213[/C][/ROW]
[ROW][C]73[/C][C]0.114768[/C][C]0.229535[/C][C]0.885232[/C][/ROW]
[ROW][C]74[/C][C]0.0960532[/C][C]0.192106[/C][C]0.903947[/C][/ROW]
[ROW][C]75[/C][C]0.0837903[/C][C]0.167581[/C][C]0.91621[/C][/ROW]
[ROW][C]76[/C][C]0.122001[/C][C]0.244003[/C][C]0.877999[/C][/ROW]
[ROW][C]77[/C][C]0.104903[/C][C]0.209806[/C][C]0.895097[/C][/ROW]
[ROW][C]78[/C][C]0.0886379[/C][C]0.177276[/C][C]0.911362[/C][/ROW]
[ROW][C]79[/C][C]0.112729[/C][C]0.225457[/C][C]0.887271[/C][/ROW]
[ROW][C]80[/C][C]0.128933[/C][C]0.257866[/C][C]0.871067[/C][/ROW]
[ROW][C]81[/C][C]0.121945[/C][C]0.24389[/C][C]0.878055[/C][/ROW]
[ROW][C]82[/C][C]0.105113[/C][C]0.210226[/C][C]0.894887[/C][/ROW]
[ROW][C]83[/C][C]0.0994113[/C][C]0.198823[/C][C]0.900589[/C][/ROW]
[ROW][C]84[/C][C]0.0944142[/C][C]0.188828[/C][C]0.905586[/C][/ROW]
[ROW][C]85[/C][C]0.0815739[/C][C]0.163148[/C][C]0.918426[/C][/ROW]
[ROW][C]86[/C][C]0.0721429[/C][C]0.144286[/C][C]0.927857[/C][/ROW]
[ROW][C]87[/C][C]0.0635736[/C][C]0.127147[/C][C]0.936426[/C][/ROW]
[ROW][C]88[/C][C]0.0793636[/C][C]0.158727[/C][C]0.920636[/C][/ROW]
[ROW][C]89[/C][C]0.0660077[/C][C]0.132015[/C][C]0.933992[/C][/ROW]
[ROW][C]90[/C][C]0.0697615[/C][C]0.139523[/C][C]0.930238[/C][/ROW]
[ROW][C]91[/C][C]0.0635127[/C][C]0.127025[/C][C]0.936487[/C][/ROW]
[ROW][C]92[/C][C]0.0565057[/C][C]0.113011[/C][C]0.943494[/C][/ROW]
[ROW][C]93[/C][C]0.0471342[/C][C]0.0942684[/C][C]0.952866[/C][/ROW]
[ROW][C]94[/C][C]0.0484013[/C][C]0.0968025[/C][C]0.951599[/C][/ROW]
[ROW][C]95[/C][C]0.0479844[/C][C]0.0959688[/C][C]0.952016[/C][/ROW]
[ROW][C]96[/C][C]0.0441902[/C][C]0.0883804[/C][C]0.95581[/C][/ROW]
[ROW][C]97[/C][C]0.0375266[/C][C]0.0750532[/C][C]0.962473[/C][/ROW]
[ROW][C]98[/C][C]0.0332491[/C][C]0.0664981[/C][C]0.966751[/C][/ROW]
[ROW][C]99[/C][C]0.0332514[/C][C]0.0665028[/C][C]0.966749[/C][/ROW]
[ROW][C]100[/C][C]0.0305175[/C][C]0.061035[/C][C]0.969482[/C][/ROW]
[ROW][C]101[/C][C]0.0273707[/C][C]0.0547414[/C][C]0.972629[/C][/ROW]
[ROW][C]102[/C][C]0.0225237[/C][C]0.0450474[/C][C]0.977476[/C][/ROW]
[ROW][C]103[/C][C]0.0185925[/C][C]0.037185[/C][C]0.981407[/C][/ROW]
[ROW][C]104[/C][C]0.0186684[/C][C]0.0373367[/C][C]0.981332[/C][/ROW]
[ROW][C]105[/C][C]0.046167[/C][C]0.092334[/C][C]0.953833[/C][/ROW]
[ROW][C]106[/C][C]0.0432858[/C][C]0.0865717[/C][C]0.956714[/C][/ROW]
[ROW][C]107[/C][C]0.0536012[/C][C]0.107202[/C][C]0.946399[/C][/ROW]
[ROW][C]108[/C][C]0.0458947[/C][C]0.0917893[/C][C]0.954105[/C][/ROW]
[ROW][C]109[/C][C]0.075011[/C][C]0.150022[/C][C]0.924989[/C][/ROW]
[ROW][C]110[/C][C]0.0886341[/C][C]0.177268[/C][C]0.911366[/C][/ROW]
[ROW][C]111[/C][C]0.0850341[/C][C]0.170068[/C][C]0.914966[/C][/ROW]
[ROW][C]112[/C][C]0.114846[/C][C]0.229691[/C][C]0.885154[/C][/ROW]
[ROW][C]113[/C][C]0.101909[/C][C]0.203819[/C][C]0.898091[/C][/ROW]
[ROW][C]114[/C][C]0.0977699[/C][C]0.19554[/C][C]0.90223[/C][/ROW]
[ROW][C]115[/C][C]0.0942755[/C][C]0.188551[/C][C]0.905725[/C][/ROW]
[ROW][C]116[/C][C]0.0942277[/C][C]0.188455[/C][C]0.905772[/C][/ROW]
[ROW][C]117[/C][C]0.0899809[/C][C]0.179962[/C][C]0.910019[/C][/ROW]
[ROW][C]118[/C][C]0.0786638[/C][C]0.157328[/C][C]0.921336[/C][/ROW]
[ROW][C]119[/C][C]0.0748017[/C][C]0.149603[/C][C]0.925198[/C][/ROW]
[ROW][C]120[/C][C]0.0669734[/C][C]0.133947[/C][C]0.933027[/C][/ROW]
[ROW][C]121[/C][C]0.05854[/C][C]0.11708[/C][C]0.94146[/C][/ROW]
[ROW][C]122[/C][C]0.0531807[/C][C]0.106361[/C][C]0.946819[/C][/ROW]
[ROW][C]123[/C][C]0.0449736[/C][C]0.0899472[/C][C]0.955026[/C][/ROW]
[ROW][C]124[/C][C]0.0431634[/C][C]0.0863268[/C][C]0.956837[/C][/ROW]
[ROW][C]125[/C][C]0.0407927[/C][C]0.0815854[/C][C]0.959207[/C][/ROW]
[ROW][C]126[/C][C]0.0523179[/C][C]0.104636[/C][C]0.947682[/C][/ROW]
[ROW][C]127[/C][C]0.0953676[/C][C]0.190735[/C][C]0.904632[/C][/ROW]
[ROW][C]128[/C][C]0.0913349[/C][C]0.18267[/C][C]0.908665[/C][/ROW]
[ROW][C]129[/C][C]0.0804359[/C][C]0.160872[/C][C]0.919564[/C][/ROW]
[ROW][C]130[/C][C]0.0742081[/C][C]0.148416[/C][C]0.925792[/C][/ROW]
[ROW][C]131[/C][C]0.0813633[/C][C]0.162727[/C][C]0.918637[/C][/ROW]
[ROW][C]132[/C][C]0.0874235[/C][C]0.174847[/C][C]0.912577[/C][/ROW]
[ROW][C]133[/C][C]0.107995[/C][C]0.215989[/C][C]0.892005[/C][/ROW]
[ROW][C]134[/C][C]0.0946666[/C][C]0.189333[/C][C]0.905333[/C][/ROW]
[ROW][C]135[/C][C]0.081497[/C][C]0.162994[/C][C]0.918503[/C][/ROW]
[ROW][C]136[/C][C]0.070787[/C][C]0.141574[/C][C]0.929213[/C][/ROW]
[ROW][C]137[/C][C]0.0600174[/C][C]0.120035[/C][C]0.939983[/C][/ROW]
[ROW][C]138[/C][C]0.0637786[/C][C]0.127557[/C][C]0.936221[/C][/ROW]
[ROW][C]139[/C][C]0.0540454[/C][C]0.108091[/C][C]0.945955[/C][/ROW]
[ROW][C]140[/C][C]0.0533215[/C][C]0.106643[/C][C]0.946678[/C][/ROW]
[ROW][C]141[/C][C]0.0524147[/C][C]0.104829[/C][C]0.947585[/C][/ROW]
[ROW][C]142[/C][C]0.0737239[/C][C]0.147448[/C][C]0.926276[/C][/ROW]
[ROW][C]143[/C][C]0.0872798[/C][C]0.17456[/C][C]0.91272[/C][/ROW]
[ROW][C]144[/C][C]0.0814431[/C][C]0.162886[/C][C]0.918557[/C][/ROW]
[ROW][C]145[/C][C]0.148833[/C][C]0.297667[/C][C]0.851167[/C][/ROW]
[ROW][C]146[/C][C]0.137127[/C][C]0.274254[/C][C]0.862873[/C][/ROW]
[ROW][C]147[/C][C]0.121843[/C][C]0.243686[/C][C]0.878157[/C][/ROW]
[ROW][C]148[/C][C]0.106959[/C][C]0.213918[/C][C]0.893041[/C][/ROW]
[ROW][C]149[/C][C]0.098761[/C][C]0.197522[/C][C]0.901239[/C][/ROW]
[ROW][C]150[/C][C]0.0878535[/C][C]0.175707[/C][C]0.912146[/C][/ROW]
[ROW][C]151[/C][C]0.142215[/C][C]0.28443[/C][C]0.857785[/C][/ROW]
[ROW][C]152[/C][C]0.133414[/C][C]0.266827[/C][C]0.866586[/C][/ROW]
[ROW][C]153[/C][C]0.120395[/C][C]0.240789[/C][C]0.879605[/C][/ROW]
[ROW][C]154[/C][C]0.132461[/C][C]0.264922[/C][C]0.867539[/C][/ROW]
[ROW][C]155[/C][C]0.114887[/C][C]0.229775[/C][C]0.885113[/C][/ROW]
[ROW][C]156[/C][C]0.113587[/C][C]0.227173[/C][C]0.886413[/C][/ROW]
[ROW][C]157[/C][C]0.116457[/C][C]0.232914[/C][C]0.883543[/C][/ROW]
[ROW][C]158[/C][C]0.108641[/C][C]0.217282[/C][C]0.891359[/C][/ROW]
[ROW][C]159[/C][C]0.0949052[/C][C]0.18981[/C][C]0.905095[/C][/ROW]
[ROW][C]160[/C][C]0.0991308[/C][C]0.198262[/C][C]0.900869[/C][/ROW]
[ROW][C]161[/C][C]0.0853373[/C][C]0.170675[/C][C]0.914663[/C][/ROW]
[ROW][C]162[/C][C]0.0804302[/C][C]0.16086[/C][C]0.91957[/C][/ROW]
[ROW][C]163[/C][C]0.0700259[/C][C]0.140052[/C][C]0.929974[/C][/ROW]
[ROW][C]164[/C][C]0.0864108[/C][C]0.172822[/C][C]0.913589[/C][/ROW]
[ROW][C]165[/C][C]0.0782977[/C][C]0.156595[/C][C]0.921702[/C][/ROW]
[ROW][C]166[/C][C]0.143247[/C][C]0.286494[/C][C]0.856753[/C][/ROW]
[ROW][C]167[/C][C]0.143875[/C][C]0.28775[/C][C]0.856125[/C][/ROW]
[ROW][C]168[/C][C]0.139885[/C][C]0.27977[/C][C]0.860115[/C][/ROW]
[ROW][C]169[/C][C]0.126031[/C][C]0.252063[/C][C]0.873969[/C][/ROW]
[ROW][C]170[/C][C]0.244702[/C][C]0.489403[/C][C]0.755298[/C][/ROW]
[ROW][C]171[/C][C]0.277738[/C][C]0.555475[/C][C]0.722262[/C][/ROW]
[ROW][C]172[/C][C]0.248117[/C][C]0.496233[/C][C]0.751883[/C][/ROW]
[ROW][C]173[/C][C]0.340808[/C][C]0.681617[/C][C]0.659192[/C][/ROW]
[ROW][C]174[/C][C]0.307319[/C][C]0.614637[/C][C]0.692681[/C][/ROW]
[ROW][C]175[/C][C]0.362563[/C][C]0.725126[/C][C]0.637437[/C][/ROW]
[ROW][C]176[/C][C]0.34809[/C][C]0.69618[/C][C]0.65191[/C][/ROW]
[ROW][C]177[/C][C]0.356142[/C][C]0.712283[/C][C]0.643858[/C][/ROW]
[ROW][C]178[/C][C]0.32874[/C][C]0.65748[/C][C]0.67126[/C][/ROW]
[ROW][C]179[/C][C]0.303239[/C][C]0.606478[/C][C]0.696761[/C][/ROW]
[ROW][C]180[/C][C]0.289118[/C][C]0.578236[/C][C]0.710882[/C][/ROW]
[ROW][C]181[/C][C]0.260785[/C][C]0.52157[/C][C]0.739215[/C][/ROW]
[ROW][C]182[/C][C]0.257702[/C][C]0.515403[/C][C]0.742298[/C][/ROW]
[ROW][C]183[/C][C]0.269335[/C][C]0.538669[/C][C]0.730665[/C][/ROW]
[ROW][C]184[/C][C]0.32198[/C][C]0.643961[/C][C]0.67802[/C][/ROW]
[ROW][C]185[/C][C]0.573327[/C][C]0.853346[/C][C]0.426673[/C][/ROW]
[ROW][C]186[/C][C]0.564117[/C][C]0.871765[/C][C]0.435883[/C][/ROW]
[ROW][C]187[/C][C]0.551114[/C][C]0.897772[/C][C]0.448886[/C][/ROW]
[ROW][C]188[/C][C]0.679138[/C][C]0.641723[/C][C]0.320862[/C][/ROW]
[ROW][C]189[/C][C]0.666198[/C][C]0.667605[/C][C]0.333802[/C][/ROW]
[ROW][C]190[/C][C]0.658911[/C][C]0.682178[/C][C]0.341089[/C][/ROW]
[ROW][C]191[/C][C]0.651316[/C][C]0.697369[/C][C]0.348684[/C][/ROW]
[ROW][C]192[/C][C]0.616881[/C][C]0.766238[/C][C]0.383119[/C][/ROW]
[ROW][C]193[/C][C]0.583743[/C][C]0.832513[/C][C]0.416257[/C][/ROW]
[ROW][C]194[/C][C]0.543501[/C][C]0.912998[/C][C]0.456499[/C][/ROW]
[ROW][C]195[/C][C]0.50597[/C][C]0.988061[/C][C]0.49403[/C][/ROW]
[ROW][C]196[/C][C]0.469584[/C][C]0.939169[/C][C]0.530416[/C][/ROW]
[ROW][C]197[/C][C]0.452684[/C][C]0.905369[/C][C]0.547316[/C][/ROW]
[ROW][C]198[/C][C]0.432814[/C][C]0.865628[/C][C]0.567186[/C][/ROW]
[ROW][C]199[/C][C]0.392546[/C][C]0.785091[/C][C]0.607454[/C][/ROW]
[ROW][C]200[/C][C]0.513083[/C][C]0.973835[/C][C]0.486917[/C][/ROW]
[ROW][C]201[/C][C]0.478715[/C][C]0.95743[/C][C]0.521285[/C][/ROW]
[ROW][C]202[/C][C]0.666221[/C][C]0.667559[/C][C]0.333779[/C][/ROW]
[ROW][C]203[/C][C]0.630204[/C][C]0.739592[/C][C]0.369796[/C][/ROW]
[ROW][C]204[/C][C]0.590754[/C][C]0.818492[/C][C]0.409246[/C][/ROW]
[ROW][C]205[/C][C]0.551759[/C][C]0.896482[/C][C]0.448241[/C][/ROW]
[ROW][C]206[/C][C]0.513064[/C][C]0.973871[/C][C]0.486936[/C][/ROW]
[ROW][C]207[/C][C]0.469722[/C][C]0.939444[/C][C]0.530278[/C][/ROW]
[ROW][C]208[/C][C]0.42598[/C][C]0.85196[/C][C]0.57402[/C][/ROW]
[ROW][C]209[/C][C]0.399508[/C][C]0.799017[/C][C]0.600492[/C][/ROW]
[ROW][C]210[/C][C]0.359498[/C][C]0.718995[/C][C]0.640502[/C][/ROW]
[ROW][C]211[/C][C]0.320668[/C][C]0.641336[/C][C]0.679332[/C][/ROW]
[ROW][C]212[/C][C]0.291184[/C][C]0.582368[/C][C]0.708816[/C][/ROW]
[ROW][C]213[/C][C]0.336054[/C][C]0.672108[/C][C]0.663946[/C][/ROW]
[ROW][C]214[/C][C]0.311122[/C][C]0.622245[/C][C]0.688878[/C][/ROW]
[ROW][C]215[/C][C]0.271422[/C][C]0.542843[/C][C]0.728578[/C][/ROW]
[ROW][C]216[/C][C]0.238727[/C][C]0.477453[/C][C]0.761273[/C][/ROW]
[ROW][C]217[/C][C]0.210723[/C][C]0.421446[/C][C]0.789277[/C][/ROW]
[ROW][C]218[/C][C]0.249592[/C][C]0.499184[/C][C]0.750408[/C][/ROW]
[ROW][C]219[/C][C]0.22208[/C][C]0.44416[/C][C]0.77792[/C][/ROW]
[ROW][C]220[/C][C]0.194294[/C][C]0.388588[/C][C]0.805706[/C][/ROW]
[ROW][C]221[/C][C]0.165645[/C][C]0.331291[/C][C]0.834355[/C][/ROW]
[ROW][C]222[/C][C]0.153283[/C][C]0.306567[/C][C]0.846717[/C][/ROW]
[ROW][C]223[/C][C]0.125593[/C][C]0.251186[/C][C]0.874407[/C][/ROW]
[ROW][C]224[/C][C]0.108032[/C][C]0.216064[/C][C]0.891968[/C][/ROW]
[ROW][C]225[/C][C]0.088824[/C][C]0.177648[/C][C]0.911176[/C][/ROW]
[ROW][C]226[/C][C]0.0958963[/C][C]0.191793[/C][C]0.904104[/C][/ROW]
[ROW][C]227[/C][C]0.086768[/C][C]0.173536[/C][C]0.913232[/C][/ROW]
[ROW][C]228[/C][C]0.0685112[/C][C]0.137022[/C][C]0.931489[/C][/ROW]
[ROW][C]229[/C][C]0.0533976[/C][C]0.106795[/C][C]0.946602[/C][/ROW]
[ROW][C]230[/C][C]0.0409734[/C][C]0.0819468[/C][C]0.959027[/C][/ROW]
[ROW][C]231[/C][C]0.0384583[/C][C]0.0769166[/C][C]0.961542[/C][/ROW]
[ROW][C]232[/C][C]0.0550611[/C][C]0.110122[/C][C]0.944939[/C][/ROW]
[ROW][C]233[/C][C]0.0435724[/C][C]0.0871449[/C][C]0.956428[/C][/ROW]
[ROW][C]234[/C][C]0.138602[/C][C]0.277205[/C][C]0.861398[/C][/ROW]
[ROW][C]235[/C][C]0.111363[/C][C]0.222727[/C][C]0.888637[/C][/ROW]
[ROW][C]236[/C][C]0.102984[/C][C]0.205968[/C][C]0.897016[/C][/ROW]
[ROW][C]237[/C][C]0.0931114[/C][C]0.186223[/C][C]0.906889[/C][/ROW]
[ROW][C]238[/C][C]0.227654[/C][C]0.455308[/C][C]0.772346[/C][/ROW]
[ROW][C]239[/C][C]0.18863[/C][C]0.37726[/C][C]0.81137[/C][/ROW]
[ROW][C]240[/C][C]0.291018[/C][C]0.582037[/C][C]0.708982[/C][/ROW]
[ROW][C]241[/C][C]0.359524[/C][C]0.719048[/C][C]0.640476[/C][/ROW]
[ROW][C]242[/C][C]0.295648[/C][C]0.591296[/C][C]0.704352[/C][/ROW]
[ROW][C]243[/C][C]0.256502[/C][C]0.513004[/C][C]0.743498[/C][/ROW]
[ROW][C]244[/C][C]0.208687[/C][C]0.417374[/C][C]0.791313[/C][/ROW]
[ROW][C]245[/C][C]0.429131[/C][C]0.858261[/C][C]0.570869[/C][/ROW]
[ROW][C]246[/C][C]0.706064[/C][C]0.587873[/C][C]0.293936[/C][/ROW]
[ROW][C]247[/C][C]0.676233[/C][C]0.647534[/C][C]0.323767[/C][/ROW]
[ROW][C]248[/C][C]0.649175[/C][C]0.70165[/C][C]0.350825[/C][/ROW]
[ROW][C]249[/C][C]0.689872[/C][C]0.620256[/C][C]0.310128[/C][/ROW]
[ROW][C]250[/C][C]0.629867[/C][C]0.740266[/C][C]0.370133[/C][/ROW]
[ROW][C]251[/C][C]0.678255[/C][C]0.64349[/C][C]0.321745[/C][/ROW]
[ROW][C]252[/C][C]0.792012[/C][C]0.415975[/C][C]0.207988[/C][/ROW]
[ROW][C]253[/C][C]0.705474[/C][C]0.589052[/C][C]0.294526[/C][/ROW]
[ROW][C]254[/C][C]0.909977[/C][C]0.180045[/C][C]0.0900226[/C][/ROW]
[ROW][C]255[/C][C]0.824675[/C][C]0.35065[/C][C]0.175325[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221839&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221839&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
90.907060.1858790.0929397
100.8381410.3237190.161859
110.7500730.4998550.249927
120.7260010.5479980.273999
130.7803120.4393760.219688
140.7151020.5697960.284898
150.7104140.5791730.289586
160.6973920.6052170.302608
170.6188050.762390.381195
180.5416180.9167640.458382
190.5038950.992210.496105
200.4940530.9881050.505947
210.5155150.968970.484485
220.458480.916960.54152
230.4252060.8504130.574794
240.3559410.7118820.644059
250.3874350.774870.612565
260.6340120.7319750.365988
270.5734680.8530640.426532
280.5395510.9208980.460449
290.5009870.9980260.499013
300.4438850.8877690.556115
310.4447060.8894120.555294
320.5896840.8206320.410316
330.5779590.8440830.422041
340.5464870.9070270.453513
350.4965050.993010.503495
360.4469550.893910.553045
370.4008130.8016270.599187
380.3694270.7388530.630573
390.4803270.9606530.519673
400.4282870.8565730.571713
410.3975170.7950340.602483
420.3484070.6968140.651593
430.3135060.6270120.686494
440.2766770.5533530.723323
450.3405330.6810670.659467
460.3552240.7104480.644776
470.3199230.6398460.680077
480.2948750.5897510.705125
490.2542790.5085580.745721
500.2661680.5323350.733832
510.306130.6122610.69387
520.2731060.5462110.726894
530.2375330.4750660.762467
540.214120.4282390.78588
550.1824990.3649970.817501
560.1692610.3385220.830739
570.1823940.3647890.817606
580.2822660.5645320.717734
590.2536610.5073230.746339
600.2199790.4399570.780021
610.194330.388660.80567
620.188760.3775210.81124
630.1642310.3284620.835769
640.1674870.3349740.832513
650.143020.2860390.85698
660.1226030.2452060.877397
670.1035640.2071270.896436
680.1107370.2214730.889263
690.1104010.2208020.889599
700.09313640.1862730.906864
710.09811120.1962220.901889
720.1197870.2395730.880213
730.1147680.2295350.885232
740.09605320.1921060.903947
750.08379030.1675810.91621
760.1220010.2440030.877999
770.1049030.2098060.895097
780.08863790.1772760.911362
790.1127290.2254570.887271
800.1289330.2578660.871067
810.1219450.243890.878055
820.1051130.2102260.894887
830.09941130.1988230.900589
840.09441420.1888280.905586
850.08157390.1631480.918426
860.07214290.1442860.927857
870.06357360.1271470.936426
880.07936360.1587270.920636
890.06600770.1320150.933992
900.06976150.1395230.930238
910.06351270.1270250.936487
920.05650570.1130110.943494
930.04713420.09426840.952866
940.04840130.09680250.951599
950.04798440.09596880.952016
960.04419020.08838040.95581
970.03752660.07505320.962473
980.03324910.06649810.966751
990.03325140.06650280.966749
1000.03051750.0610350.969482
1010.02737070.05474140.972629
1020.02252370.04504740.977476
1030.01859250.0371850.981407
1040.01866840.03733670.981332
1050.0461670.0923340.953833
1060.04328580.08657170.956714
1070.05360120.1072020.946399
1080.04589470.09178930.954105
1090.0750110.1500220.924989
1100.08863410.1772680.911366
1110.08503410.1700680.914966
1120.1148460.2296910.885154
1130.1019090.2038190.898091
1140.09776990.195540.90223
1150.09427550.1885510.905725
1160.09422770.1884550.905772
1170.08998090.1799620.910019
1180.07866380.1573280.921336
1190.07480170.1496030.925198
1200.06697340.1339470.933027
1210.058540.117080.94146
1220.05318070.1063610.946819
1230.04497360.08994720.955026
1240.04316340.08632680.956837
1250.04079270.08158540.959207
1260.05231790.1046360.947682
1270.09536760.1907350.904632
1280.09133490.182670.908665
1290.08043590.1608720.919564
1300.07420810.1484160.925792
1310.08136330.1627270.918637
1320.08742350.1748470.912577
1330.1079950.2159890.892005
1340.09466660.1893330.905333
1350.0814970.1629940.918503
1360.0707870.1415740.929213
1370.06001740.1200350.939983
1380.06377860.1275570.936221
1390.05404540.1080910.945955
1400.05332150.1066430.946678
1410.05241470.1048290.947585
1420.07372390.1474480.926276
1430.08727980.174560.91272
1440.08144310.1628860.918557
1450.1488330.2976670.851167
1460.1371270.2742540.862873
1470.1218430.2436860.878157
1480.1069590.2139180.893041
1490.0987610.1975220.901239
1500.08785350.1757070.912146
1510.1422150.284430.857785
1520.1334140.2668270.866586
1530.1203950.2407890.879605
1540.1324610.2649220.867539
1550.1148870.2297750.885113
1560.1135870.2271730.886413
1570.1164570.2329140.883543
1580.1086410.2172820.891359
1590.09490520.189810.905095
1600.09913080.1982620.900869
1610.08533730.1706750.914663
1620.08043020.160860.91957
1630.07002590.1400520.929974
1640.08641080.1728220.913589
1650.07829770.1565950.921702
1660.1432470.2864940.856753
1670.1438750.287750.856125
1680.1398850.279770.860115
1690.1260310.2520630.873969
1700.2447020.4894030.755298
1710.2777380.5554750.722262
1720.2481170.4962330.751883
1730.3408080.6816170.659192
1740.3073190.6146370.692681
1750.3625630.7251260.637437
1760.348090.696180.65191
1770.3561420.7122830.643858
1780.328740.657480.67126
1790.3032390.6064780.696761
1800.2891180.5782360.710882
1810.2607850.521570.739215
1820.2577020.5154030.742298
1830.2693350.5386690.730665
1840.321980.6439610.67802
1850.5733270.8533460.426673
1860.5641170.8717650.435883
1870.5511140.8977720.448886
1880.6791380.6417230.320862
1890.6661980.6676050.333802
1900.6589110.6821780.341089
1910.6513160.6973690.348684
1920.6168810.7662380.383119
1930.5837430.8325130.416257
1940.5435010.9129980.456499
1950.505970.9880610.49403
1960.4695840.9391690.530416
1970.4526840.9053690.547316
1980.4328140.8656280.567186
1990.3925460.7850910.607454
2000.5130830.9738350.486917
2010.4787150.957430.521285
2020.6662210.6675590.333779
2030.6302040.7395920.369796
2040.5907540.8184920.409246
2050.5517590.8964820.448241
2060.5130640.9738710.486936
2070.4697220.9394440.530278
2080.425980.851960.57402
2090.3995080.7990170.600492
2100.3594980.7189950.640502
2110.3206680.6413360.679332
2120.2911840.5823680.708816
2130.3360540.6721080.663946
2140.3111220.6222450.688878
2150.2714220.5428430.728578
2160.2387270.4774530.761273
2170.2107230.4214460.789277
2180.2495920.4991840.750408
2190.222080.444160.77792
2200.1942940.3885880.805706
2210.1656450.3312910.834355
2220.1532830.3065670.846717
2230.1255930.2511860.874407
2240.1080320.2160640.891968
2250.0888240.1776480.911176
2260.09589630.1917930.904104
2270.0867680.1735360.913232
2280.06851120.1370220.931489
2290.05339760.1067950.946602
2300.04097340.08194680.959027
2310.03845830.07691660.961542
2320.05506110.1101220.944939
2330.04357240.08714490.956428
2340.1386020.2772050.861398
2350.1113630.2227270.888637
2360.1029840.2059680.897016
2370.09311140.1862230.906889
2380.2276540.4553080.772346
2390.188630.377260.81137
2400.2910180.5820370.708982
2410.3595240.7190480.640476
2420.2956480.5912960.704352
2430.2565020.5130040.743498
2440.2086870.4173740.791313
2450.4291310.8582610.570869
2460.7060640.5878730.293936
2470.6762330.6475340.323767
2480.6491750.701650.350825
2490.6898720.6202560.310128
2500.6298670.7402660.370133
2510.6782550.643490.321745
2520.7920120.4159750.207988
2530.7054740.5890520.294526
2540.9099770.1800450.0900226
2550.8246750.350650.175325






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level30.0121457OK
10% type I error level210.0850202OK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 3 & 0.0121457 & OK \tabularnewline
10% type I error level & 21 & 0.0850202 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221839&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]3[/C][C]0.0121457[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]21[/C][C]0.0850202[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221839&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221839&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 level00OK
5% type I error level30.0121457OK
10% type I error level210.0850202OK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; 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')
}