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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 04:06:08 -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/t1383469608wgmh6jpx22quek3.htm/, Retrieved Mon, 29 Apr 2024 14:23:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221840, Retrieved Mon, 29 Apr 2024 14:23:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Seperated 7] [2013-11-03 09:06:08] [c762d1649a4d3d7755470a4359a854f5] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 12 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.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=221840&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.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=221840&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221840&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 seconds
R Server'Sir Maurice George Kendall' @ kendall.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
Separate[t] = + 15.934 + 0.414995Connected[t] + 0.128945Learning[t] + 0.122129Software[t] + 0.0320859Happiness[t] + 0.00378736Depression[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Separate[t] =  +  15.934 +  0.414995Connected[t] +  0.128945Learning[t] +  0.122129Software[t] +  0.0320859Happiness[t] +  0.00378736Depression[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221840&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Separate[t] =  +  15.934 +  0.414995Connected[t] +  0.128945Learning[t] +  0.122129Software[t] +  0.0320859Happiness[t] +  0.00378736Depression[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221840&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221840&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
Separate[t] = + 15.934 + 0.414995Connected[t] + 0.128945Learning[t] + 0.122129Software[t] + 0.0320859Happiness[t] + 0.00378736Depression[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.9342.903035.4899.67102e-084.83551e-08
Connected0.4149950.05472297.5846.0858e-133.0429e-13
Learning0.1289450.1085591.1880.236010.118005
Software0.1221290.1116591.0940.2750760.137538
Happiness0.03208590.1008710.31810.7506740.375337
Depression0.003787360.07238230.052320.9583110.479155

\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) & 15.934 & 2.90303 & 5.489 & 9.67102e-08 & 4.83551e-08 \tabularnewline
Connected & 0.414995 & 0.0547229 & 7.584 & 6.0858e-13 & 3.0429e-13 \tabularnewline
Learning & 0.128945 & 0.108559 & 1.188 & 0.23601 & 0.118005 \tabularnewline
Software & 0.122129 & 0.111659 & 1.094 & 0.275076 & 0.137538 \tabularnewline
Happiness & 0.0320859 & 0.100871 & 0.3181 & 0.750674 & 0.375337 \tabularnewline
Depression & 0.00378736 & 0.0723823 & 0.05232 & 0.958311 & 0.479155 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221840&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]15.934[/C][C]2.90303[/C][C]5.489[/C][C]9.67102e-08[/C][C]4.83551e-08[/C][/ROW]
[ROW][C]Connected[/C][C]0.414995[/C][C]0.0547229[/C][C]7.584[/C][C]6.0858e-13[/C][C]3.0429e-13[/C][/ROW]
[ROW][C]Learning[/C][C]0.128945[/C][C]0.108559[/C][C]1.188[/C][C]0.23601[/C][C]0.118005[/C][/ROW]
[ROW][C]Software[/C][C]0.122129[/C][C]0.111659[/C][C]1.094[/C][C]0.275076[/C][C]0.137538[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0320859[/C][C]0.100871[/C][C]0.3181[/C][C]0.750674[/C][C]0.375337[/C][/ROW]
[ROW][C]Depression[/C][C]0.00378736[/C][C]0.0723823[/C][C]0.05232[/C][C]0.958311[/C][C]0.479155[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221840&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221840&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)15.9342.903035.4899.67102e-084.83551e-08
Connected0.4149950.05472297.5846.0858e-133.0429e-13
Learning0.1289450.1085591.1880.236010.118005
Software0.1221290.1116591.0940.2750760.137538
Happiness0.03208590.1008710.31810.7506740.375337
Depression0.003787360.07238230.052320.9583110.479155






Multiple Linear Regression - Regression Statistics
Multiple R0.47868
R-squared0.229135
Adjusted R-squared0.214196
F-TEST (value)15.3378
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value3.35398e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.28347
Sum Squared Residuals2781.54

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.47868 \tabularnewline
R-squared & 0.229135 \tabularnewline
Adjusted R-squared & 0.214196 \tabularnewline
F-TEST (value) & 15.3378 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 258 \tabularnewline
p-value & 3.35398e-13 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.28347 \tabularnewline
Sum Squared Residuals & 2781.54 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221840&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.47868[/C][/ROW]
[ROW][C]R-squared[/C][C]0.229135[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.214196[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]15.3378[/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]3.35398e-13[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.28347[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2781.54[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221840&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221840&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 R0.47868
R-squared0.229135
Adjusted R-squared0.214196
F-TEST (value)15.3378
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value3.35398e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.28347
Sum Squared Residuals2781.54






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
13836.58531.4147
23236.1446-4.14457
33533.07171.92827
43331.89631.1037
53734.02972.97033
62933.9794-4.97942
73136.5669-5.56686
83634.17871.8213
93534.66380.336217
103834.85273.1473
113135.5716-4.57158
123435.0424-1.04244
133535.6102-0.610171
143836.09181.90824
153734.26832.73172
163333.1158-0.115812
173234.5315-2.53153
183836.33541.6646
193836.27031.72967
203233.3051-1.30514
213333.2339-0.233929
223132.7335-1.73351
233836.65111.34889
243935.13343.86657
253236.3636-4.36356
263237.0514-5.05142
273534.71330.286712
283733.77893.22115
293333.6918-0.691839
303333.4726-0.472553
313132.7461-1.74605
323230.13721.86281
333134.8987-3.89869
343734.09552.90453
353033.8131-3.81307
363331.90191.09811
373130.7220.277992
383334.6714-1.67136
393131.8366-0.836623
403334.1982-1.19825
413235.0886-3.08862
423333.881-0.881029
433236.6583-4.65834
443333.9234-0.923421
452835.2533-7.2533
463534.5750.42504
473935.61213.38789
483433.42940.570598
493834.88273.11735
503235.4334-3.43339
513833.5384.46196
523032.7426-2.74261
533332.64790.352132
543834.13273.8673
553231.41170.588299
563534.3630.636955
573436.2101-2.21011
583432.01291.98708
593634.98931.01066
603434.1851-0.185099
612831.1185-3.11855
623435.6951-1.69507
633534.21520.784826
643532.44972.55026
653134.103-3.10305
663734.60112.39889
673535.322-0.321991
682732.4788-5.47878
694035.66224.33776
703734.52182.47817
713634.46881.53125
723832.51775.4823
733934.60524.3948
744136.25384.74619
752734.0313-7.0313
763035.867-5.86704
773735.53431.46567
783133.9319-2.93189
793131.2262-0.226241
802735.2687-8.26871
813633.68052.31952
823734.50292.49711
833335.2474-2.24738
843433.01820.981806
853133.4117-2.41171
863935.13873.86125
873433.65220.347822
883231.97150.0285253
893333.3365-0.336505
903632.04013.95994
913235.3718-3.37177
924134.5186.48196
932833.1196-5.1196
943031.5752-1.57517
953635.95830.0417272
963535.3853-0.385264
973134.112-3.11199
983435.4046-1.40463
993632.75953.24046
1003636.0601-0.0600938
1013535.141-0.141006
1023735.84351.1565
1032832.8861-4.88606
1043933.57735.42272
1053236.0364-4.03639
1063535.9165-0.916482
1073937.01941.98063
1083534.65810.341948
1094236.59285.4072
1103432.44691.55315
1113332.98160.0184488
1124133.20817.79187
1133332.73960.26042
1143434.6805-0.680461
1153235.7488-3.74877
1164033.5246.47601
1174033.32466.67545
1183533.13191.86815
1193635.73850.261486
1203733.09043.9096
1212732.9519-5.95189
1223935.36863.63139
1233835.57342.42665
1243134.9186-3.91864
1253333.1527-0.152703
1263235.8501-3.85005
1273938.31260.68738
1283633.31352.68651
1293333.8801-0.88013
1303332.95710.0429489
1313230.55131.44873
1323736.09310.906864
1333030.5677-0.567746
1343835.08642.91365
1352933.18-4.17998
1362230.7694-8.76938
1373533.82371.17633
1383531.43713.5629
1393433.50620.493833
1403531.7793.22101
1413432.77321.22682
1423731.98365.01639
1433532.90252.09747
1442332.7321-9.73214
1453135.3553-4.35534
1462733.6814-6.68137
1473634.41791.58214
1483133.1692-2.16922
1493233.595-1.59503
1503934.4074.59299
1513737.3672-0.367166
1523833.75364.24641
1533933.68525.31478
1543434.8468-0.846826
1553132.3806-1.38063
1563235.3718-3.37177
1573732.12514.87485
1583633.31352.68651
1593233.9016-1.9016
1603832.19145.80856
1613633.17492.82512
1622630.4482-4.44822
1632631.8255-5.82546
1643336.1948-3.19483
1653933.58835.41165
1663028.60041.39956
1673332.02720.972827
1682530.0459-5.04589
1693833.53514.46494
1703731.02455.9755
1713133.8755-2.87551
1723734.96132.03867
1733536.0517-1.05167
1742530.4658-5.46579
1752834.4493-6.44934
1763532.94272.05734
1773334.1626-1.16258
1783031.4836-1.48358
1793132.3766-1.37664
1803734.75632.2437
1813634.89341.10662
1823033.0612-3.06122
1833633.60372.39629
1843235.5906-3.59063
1852828.1161-0.116056
1863633.23162.76839
1873434.9116-0.911553
1883135.0478-4.0478
1892830.2973-2.29732
1903631.67544.32462
1913632.88683.11318
1924035.71964.28042
1933331.66571.33431
1943734.27892.72107
1953232.6457-0.645749
1963835.1192.88096
1973133.7273-2.7273
1983733.66353.33646
1993332.86190.138105
2003230.71891.28108
2013032.2657-2.2657
2023029.44720.552839
2033133.1485-2.14853
2043233.5269-1.52688
2053433.0630.936986
2063633.8522.14803
2073734.362.63996
2083634.55771.4423
2093333.9837-0.983666
2103333.7581-0.758141
2113333.4099-0.409899
2124436.51677.48326
2133932.91266.08743
2143231.66520.334826
2153534.40480.595153
2162531.1109-6.11093
2173533.75151.24854
2183435.64-1.64
2193533.86721.13283
2203934.80794.19212
2213333.9991-0.999074
2223635.28920.710825
2233233.4138-1.41383
2243231.96070.0392573
2253633.18762.81239
2263631.52944.47056
2273232.4767-0.476681
2283432.96371.03627
2293332.90520.0947964
2303533.09251.90747
2313032.9476-2.94756
2323832.4895.51103
2333432.52511.47487
2343337.4611-4.46114
2353233.4889-1.48889
2363133.9195-2.91949
2373032.9868-2.9868
2382734.482-7.48203
2393131.8601-0.860067
2403033.8316-3.83158
2413230.08621.91384
2423533.67831.32175
2432829.6553-1.65535
2443333.3135-0.313533
2453134.9786-3.97861
2463530.92194.07806
2473532.59222.40782
2483233.7988-1.79876
2492126.7399-5.73991
2502027.741-7.74105
2513431.60652.39352
2523232.2547-0.25471
2533433.61270.387268
2543233.2575-1.25749
2553334.5069-1.50688
2563333.6343-0.634343
2573734.35582.64418
2583231.93810.0619252
2593434.8466-0.84664
2603031.6922-1.69217
2613030.9111-0.911134
2623833.45454.54547
2633635.1150.884959
2643231.36790.63208

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 38 & 36.5853 & 1.4147 \tabularnewline
2 & 32 & 36.1446 & -4.14457 \tabularnewline
3 & 35 & 33.0717 & 1.92827 \tabularnewline
4 & 33 & 31.8963 & 1.1037 \tabularnewline
5 & 37 & 34.0297 & 2.97033 \tabularnewline
6 & 29 & 33.9794 & -4.97942 \tabularnewline
7 & 31 & 36.5669 & -5.56686 \tabularnewline
8 & 36 & 34.1787 & 1.8213 \tabularnewline
9 & 35 & 34.6638 & 0.336217 \tabularnewline
10 & 38 & 34.8527 & 3.1473 \tabularnewline
11 & 31 & 35.5716 & -4.57158 \tabularnewline
12 & 34 & 35.0424 & -1.04244 \tabularnewline
13 & 35 & 35.6102 & -0.610171 \tabularnewline
14 & 38 & 36.0918 & 1.90824 \tabularnewline
15 & 37 & 34.2683 & 2.73172 \tabularnewline
16 & 33 & 33.1158 & -0.115812 \tabularnewline
17 & 32 & 34.5315 & -2.53153 \tabularnewline
18 & 38 & 36.3354 & 1.6646 \tabularnewline
19 & 38 & 36.2703 & 1.72967 \tabularnewline
20 & 32 & 33.3051 & -1.30514 \tabularnewline
21 & 33 & 33.2339 & -0.233929 \tabularnewline
22 & 31 & 32.7335 & -1.73351 \tabularnewline
23 & 38 & 36.6511 & 1.34889 \tabularnewline
24 & 39 & 35.1334 & 3.86657 \tabularnewline
25 & 32 & 36.3636 & -4.36356 \tabularnewline
26 & 32 & 37.0514 & -5.05142 \tabularnewline
27 & 35 & 34.7133 & 0.286712 \tabularnewline
28 & 37 & 33.7789 & 3.22115 \tabularnewline
29 & 33 & 33.6918 & -0.691839 \tabularnewline
30 & 33 & 33.4726 & -0.472553 \tabularnewline
31 & 31 & 32.7461 & -1.74605 \tabularnewline
32 & 32 & 30.1372 & 1.86281 \tabularnewline
33 & 31 & 34.8987 & -3.89869 \tabularnewline
34 & 37 & 34.0955 & 2.90453 \tabularnewline
35 & 30 & 33.8131 & -3.81307 \tabularnewline
36 & 33 & 31.9019 & 1.09811 \tabularnewline
37 & 31 & 30.722 & 0.277992 \tabularnewline
38 & 33 & 34.6714 & -1.67136 \tabularnewline
39 & 31 & 31.8366 & -0.836623 \tabularnewline
40 & 33 & 34.1982 & -1.19825 \tabularnewline
41 & 32 & 35.0886 & -3.08862 \tabularnewline
42 & 33 & 33.881 & -0.881029 \tabularnewline
43 & 32 & 36.6583 & -4.65834 \tabularnewline
44 & 33 & 33.9234 & -0.923421 \tabularnewline
45 & 28 & 35.2533 & -7.2533 \tabularnewline
46 & 35 & 34.575 & 0.42504 \tabularnewline
47 & 39 & 35.6121 & 3.38789 \tabularnewline
48 & 34 & 33.4294 & 0.570598 \tabularnewline
49 & 38 & 34.8827 & 3.11735 \tabularnewline
50 & 32 & 35.4334 & -3.43339 \tabularnewline
51 & 38 & 33.538 & 4.46196 \tabularnewline
52 & 30 & 32.7426 & -2.74261 \tabularnewline
53 & 33 & 32.6479 & 0.352132 \tabularnewline
54 & 38 & 34.1327 & 3.8673 \tabularnewline
55 & 32 & 31.4117 & 0.588299 \tabularnewline
56 & 35 & 34.363 & 0.636955 \tabularnewline
57 & 34 & 36.2101 & -2.21011 \tabularnewline
58 & 34 & 32.0129 & 1.98708 \tabularnewline
59 & 36 & 34.9893 & 1.01066 \tabularnewline
60 & 34 & 34.1851 & -0.185099 \tabularnewline
61 & 28 & 31.1185 & -3.11855 \tabularnewline
62 & 34 & 35.6951 & -1.69507 \tabularnewline
63 & 35 & 34.2152 & 0.784826 \tabularnewline
64 & 35 & 32.4497 & 2.55026 \tabularnewline
65 & 31 & 34.103 & -3.10305 \tabularnewline
66 & 37 & 34.6011 & 2.39889 \tabularnewline
67 & 35 & 35.322 & -0.321991 \tabularnewline
68 & 27 & 32.4788 & -5.47878 \tabularnewline
69 & 40 & 35.6622 & 4.33776 \tabularnewline
70 & 37 & 34.5218 & 2.47817 \tabularnewline
71 & 36 & 34.4688 & 1.53125 \tabularnewline
72 & 38 & 32.5177 & 5.4823 \tabularnewline
73 & 39 & 34.6052 & 4.3948 \tabularnewline
74 & 41 & 36.2538 & 4.74619 \tabularnewline
75 & 27 & 34.0313 & -7.0313 \tabularnewline
76 & 30 & 35.867 & -5.86704 \tabularnewline
77 & 37 & 35.5343 & 1.46567 \tabularnewline
78 & 31 & 33.9319 & -2.93189 \tabularnewline
79 & 31 & 31.2262 & -0.226241 \tabularnewline
80 & 27 & 35.2687 & -8.26871 \tabularnewline
81 & 36 & 33.6805 & 2.31952 \tabularnewline
82 & 37 & 34.5029 & 2.49711 \tabularnewline
83 & 33 & 35.2474 & -2.24738 \tabularnewline
84 & 34 & 33.0182 & 0.981806 \tabularnewline
85 & 31 & 33.4117 & -2.41171 \tabularnewline
86 & 39 & 35.1387 & 3.86125 \tabularnewline
87 & 34 & 33.6522 & 0.347822 \tabularnewline
88 & 32 & 31.9715 & 0.0285253 \tabularnewline
89 & 33 & 33.3365 & -0.336505 \tabularnewline
90 & 36 & 32.0401 & 3.95994 \tabularnewline
91 & 32 & 35.3718 & -3.37177 \tabularnewline
92 & 41 & 34.518 & 6.48196 \tabularnewline
93 & 28 & 33.1196 & -5.1196 \tabularnewline
94 & 30 & 31.5752 & -1.57517 \tabularnewline
95 & 36 & 35.9583 & 0.0417272 \tabularnewline
96 & 35 & 35.3853 & -0.385264 \tabularnewline
97 & 31 & 34.112 & -3.11199 \tabularnewline
98 & 34 & 35.4046 & -1.40463 \tabularnewline
99 & 36 & 32.7595 & 3.24046 \tabularnewline
100 & 36 & 36.0601 & -0.0600938 \tabularnewline
101 & 35 & 35.141 & -0.141006 \tabularnewline
102 & 37 & 35.8435 & 1.1565 \tabularnewline
103 & 28 & 32.8861 & -4.88606 \tabularnewline
104 & 39 & 33.5773 & 5.42272 \tabularnewline
105 & 32 & 36.0364 & -4.03639 \tabularnewline
106 & 35 & 35.9165 & -0.916482 \tabularnewline
107 & 39 & 37.0194 & 1.98063 \tabularnewline
108 & 35 & 34.6581 & 0.341948 \tabularnewline
109 & 42 & 36.5928 & 5.4072 \tabularnewline
110 & 34 & 32.4469 & 1.55315 \tabularnewline
111 & 33 & 32.9816 & 0.0184488 \tabularnewline
112 & 41 & 33.2081 & 7.79187 \tabularnewline
113 & 33 & 32.7396 & 0.26042 \tabularnewline
114 & 34 & 34.6805 & -0.680461 \tabularnewline
115 & 32 & 35.7488 & -3.74877 \tabularnewline
116 & 40 & 33.524 & 6.47601 \tabularnewline
117 & 40 & 33.3246 & 6.67545 \tabularnewline
118 & 35 & 33.1319 & 1.86815 \tabularnewline
119 & 36 & 35.7385 & 0.261486 \tabularnewline
120 & 37 & 33.0904 & 3.9096 \tabularnewline
121 & 27 & 32.9519 & -5.95189 \tabularnewline
122 & 39 & 35.3686 & 3.63139 \tabularnewline
123 & 38 & 35.5734 & 2.42665 \tabularnewline
124 & 31 & 34.9186 & -3.91864 \tabularnewline
125 & 33 & 33.1527 & -0.152703 \tabularnewline
126 & 32 & 35.8501 & -3.85005 \tabularnewline
127 & 39 & 38.3126 & 0.68738 \tabularnewline
128 & 36 & 33.3135 & 2.68651 \tabularnewline
129 & 33 & 33.8801 & -0.88013 \tabularnewline
130 & 33 & 32.9571 & 0.0429489 \tabularnewline
131 & 32 & 30.5513 & 1.44873 \tabularnewline
132 & 37 & 36.0931 & 0.906864 \tabularnewline
133 & 30 & 30.5677 & -0.567746 \tabularnewline
134 & 38 & 35.0864 & 2.91365 \tabularnewline
135 & 29 & 33.18 & -4.17998 \tabularnewline
136 & 22 & 30.7694 & -8.76938 \tabularnewline
137 & 35 & 33.8237 & 1.17633 \tabularnewline
138 & 35 & 31.4371 & 3.5629 \tabularnewline
139 & 34 & 33.5062 & 0.493833 \tabularnewline
140 & 35 & 31.779 & 3.22101 \tabularnewline
141 & 34 & 32.7732 & 1.22682 \tabularnewline
142 & 37 & 31.9836 & 5.01639 \tabularnewline
143 & 35 & 32.9025 & 2.09747 \tabularnewline
144 & 23 & 32.7321 & -9.73214 \tabularnewline
145 & 31 & 35.3553 & -4.35534 \tabularnewline
146 & 27 & 33.6814 & -6.68137 \tabularnewline
147 & 36 & 34.4179 & 1.58214 \tabularnewline
148 & 31 & 33.1692 & -2.16922 \tabularnewline
149 & 32 & 33.595 & -1.59503 \tabularnewline
150 & 39 & 34.407 & 4.59299 \tabularnewline
151 & 37 & 37.3672 & -0.367166 \tabularnewline
152 & 38 & 33.7536 & 4.24641 \tabularnewline
153 & 39 & 33.6852 & 5.31478 \tabularnewline
154 & 34 & 34.8468 & -0.846826 \tabularnewline
155 & 31 & 32.3806 & -1.38063 \tabularnewline
156 & 32 & 35.3718 & -3.37177 \tabularnewline
157 & 37 & 32.1251 & 4.87485 \tabularnewline
158 & 36 & 33.3135 & 2.68651 \tabularnewline
159 & 32 & 33.9016 & -1.9016 \tabularnewline
160 & 38 & 32.1914 & 5.80856 \tabularnewline
161 & 36 & 33.1749 & 2.82512 \tabularnewline
162 & 26 & 30.4482 & -4.44822 \tabularnewline
163 & 26 & 31.8255 & -5.82546 \tabularnewline
164 & 33 & 36.1948 & -3.19483 \tabularnewline
165 & 39 & 33.5883 & 5.41165 \tabularnewline
166 & 30 & 28.6004 & 1.39956 \tabularnewline
167 & 33 & 32.0272 & 0.972827 \tabularnewline
168 & 25 & 30.0459 & -5.04589 \tabularnewline
169 & 38 & 33.5351 & 4.46494 \tabularnewline
170 & 37 & 31.0245 & 5.9755 \tabularnewline
171 & 31 & 33.8755 & -2.87551 \tabularnewline
172 & 37 & 34.9613 & 2.03867 \tabularnewline
173 & 35 & 36.0517 & -1.05167 \tabularnewline
174 & 25 & 30.4658 & -5.46579 \tabularnewline
175 & 28 & 34.4493 & -6.44934 \tabularnewline
176 & 35 & 32.9427 & 2.05734 \tabularnewline
177 & 33 & 34.1626 & -1.16258 \tabularnewline
178 & 30 & 31.4836 & -1.48358 \tabularnewline
179 & 31 & 32.3766 & -1.37664 \tabularnewline
180 & 37 & 34.7563 & 2.2437 \tabularnewline
181 & 36 & 34.8934 & 1.10662 \tabularnewline
182 & 30 & 33.0612 & -3.06122 \tabularnewline
183 & 36 & 33.6037 & 2.39629 \tabularnewline
184 & 32 & 35.5906 & -3.59063 \tabularnewline
185 & 28 & 28.1161 & -0.116056 \tabularnewline
186 & 36 & 33.2316 & 2.76839 \tabularnewline
187 & 34 & 34.9116 & -0.911553 \tabularnewline
188 & 31 & 35.0478 & -4.0478 \tabularnewline
189 & 28 & 30.2973 & -2.29732 \tabularnewline
190 & 36 & 31.6754 & 4.32462 \tabularnewline
191 & 36 & 32.8868 & 3.11318 \tabularnewline
192 & 40 & 35.7196 & 4.28042 \tabularnewline
193 & 33 & 31.6657 & 1.33431 \tabularnewline
194 & 37 & 34.2789 & 2.72107 \tabularnewline
195 & 32 & 32.6457 & -0.645749 \tabularnewline
196 & 38 & 35.119 & 2.88096 \tabularnewline
197 & 31 & 33.7273 & -2.7273 \tabularnewline
198 & 37 & 33.6635 & 3.33646 \tabularnewline
199 & 33 & 32.8619 & 0.138105 \tabularnewline
200 & 32 & 30.7189 & 1.28108 \tabularnewline
201 & 30 & 32.2657 & -2.2657 \tabularnewline
202 & 30 & 29.4472 & 0.552839 \tabularnewline
203 & 31 & 33.1485 & -2.14853 \tabularnewline
204 & 32 & 33.5269 & -1.52688 \tabularnewline
205 & 34 & 33.063 & 0.936986 \tabularnewline
206 & 36 & 33.852 & 2.14803 \tabularnewline
207 & 37 & 34.36 & 2.63996 \tabularnewline
208 & 36 & 34.5577 & 1.4423 \tabularnewline
209 & 33 & 33.9837 & -0.983666 \tabularnewline
210 & 33 & 33.7581 & -0.758141 \tabularnewline
211 & 33 & 33.4099 & -0.409899 \tabularnewline
212 & 44 & 36.5167 & 7.48326 \tabularnewline
213 & 39 & 32.9126 & 6.08743 \tabularnewline
214 & 32 & 31.6652 & 0.334826 \tabularnewline
215 & 35 & 34.4048 & 0.595153 \tabularnewline
216 & 25 & 31.1109 & -6.11093 \tabularnewline
217 & 35 & 33.7515 & 1.24854 \tabularnewline
218 & 34 & 35.64 & -1.64 \tabularnewline
219 & 35 & 33.8672 & 1.13283 \tabularnewline
220 & 39 & 34.8079 & 4.19212 \tabularnewline
221 & 33 & 33.9991 & -0.999074 \tabularnewline
222 & 36 & 35.2892 & 0.710825 \tabularnewline
223 & 32 & 33.4138 & -1.41383 \tabularnewline
224 & 32 & 31.9607 & 0.0392573 \tabularnewline
225 & 36 & 33.1876 & 2.81239 \tabularnewline
226 & 36 & 31.5294 & 4.47056 \tabularnewline
227 & 32 & 32.4767 & -0.476681 \tabularnewline
228 & 34 & 32.9637 & 1.03627 \tabularnewline
229 & 33 & 32.9052 & 0.0947964 \tabularnewline
230 & 35 & 33.0925 & 1.90747 \tabularnewline
231 & 30 & 32.9476 & -2.94756 \tabularnewline
232 & 38 & 32.489 & 5.51103 \tabularnewline
233 & 34 & 32.5251 & 1.47487 \tabularnewline
234 & 33 & 37.4611 & -4.46114 \tabularnewline
235 & 32 & 33.4889 & -1.48889 \tabularnewline
236 & 31 & 33.9195 & -2.91949 \tabularnewline
237 & 30 & 32.9868 & -2.9868 \tabularnewline
238 & 27 & 34.482 & -7.48203 \tabularnewline
239 & 31 & 31.8601 & -0.860067 \tabularnewline
240 & 30 & 33.8316 & -3.83158 \tabularnewline
241 & 32 & 30.0862 & 1.91384 \tabularnewline
242 & 35 & 33.6783 & 1.32175 \tabularnewline
243 & 28 & 29.6553 & -1.65535 \tabularnewline
244 & 33 & 33.3135 & -0.313533 \tabularnewline
245 & 31 & 34.9786 & -3.97861 \tabularnewline
246 & 35 & 30.9219 & 4.07806 \tabularnewline
247 & 35 & 32.5922 & 2.40782 \tabularnewline
248 & 32 & 33.7988 & -1.79876 \tabularnewline
249 & 21 & 26.7399 & -5.73991 \tabularnewline
250 & 20 & 27.741 & -7.74105 \tabularnewline
251 & 34 & 31.6065 & 2.39352 \tabularnewline
252 & 32 & 32.2547 & -0.25471 \tabularnewline
253 & 34 & 33.6127 & 0.387268 \tabularnewline
254 & 32 & 33.2575 & -1.25749 \tabularnewline
255 & 33 & 34.5069 & -1.50688 \tabularnewline
256 & 33 & 33.6343 & -0.634343 \tabularnewline
257 & 37 & 34.3558 & 2.64418 \tabularnewline
258 & 32 & 31.9381 & 0.0619252 \tabularnewline
259 & 34 & 34.8466 & -0.84664 \tabularnewline
260 & 30 & 31.6922 & -1.69217 \tabularnewline
261 & 30 & 30.9111 & -0.911134 \tabularnewline
262 & 38 & 33.4545 & 4.54547 \tabularnewline
263 & 36 & 35.115 & 0.884959 \tabularnewline
264 & 32 & 31.3679 & 0.63208 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221840&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]38[/C][C]36.5853[/C][C]1.4147[/C][/ROW]
[ROW][C]2[/C][C]32[/C][C]36.1446[/C][C]-4.14457[/C][/ROW]
[ROW][C]3[/C][C]35[/C][C]33.0717[/C][C]1.92827[/C][/ROW]
[ROW][C]4[/C][C]33[/C][C]31.8963[/C][C]1.1037[/C][/ROW]
[ROW][C]5[/C][C]37[/C][C]34.0297[/C][C]2.97033[/C][/ROW]
[ROW][C]6[/C][C]29[/C][C]33.9794[/C][C]-4.97942[/C][/ROW]
[ROW][C]7[/C][C]31[/C][C]36.5669[/C][C]-5.56686[/C][/ROW]
[ROW][C]8[/C][C]36[/C][C]34.1787[/C][C]1.8213[/C][/ROW]
[ROW][C]9[/C][C]35[/C][C]34.6638[/C][C]0.336217[/C][/ROW]
[ROW][C]10[/C][C]38[/C][C]34.8527[/C][C]3.1473[/C][/ROW]
[ROW][C]11[/C][C]31[/C][C]35.5716[/C][C]-4.57158[/C][/ROW]
[ROW][C]12[/C][C]34[/C][C]35.0424[/C][C]-1.04244[/C][/ROW]
[ROW][C]13[/C][C]35[/C][C]35.6102[/C][C]-0.610171[/C][/ROW]
[ROW][C]14[/C][C]38[/C][C]36.0918[/C][C]1.90824[/C][/ROW]
[ROW][C]15[/C][C]37[/C][C]34.2683[/C][C]2.73172[/C][/ROW]
[ROW][C]16[/C][C]33[/C][C]33.1158[/C][C]-0.115812[/C][/ROW]
[ROW][C]17[/C][C]32[/C][C]34.5315[/C][C]-2.53153[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]36.3354[/C][C]1.6646[/C][/ROW]
[ROW][C]19[/C][C]38[/C][C]36.2703[/C][C]1.72967[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.3051[/C][C]-1.30514[/C][/ROW]
[ROW][C]21[/C][C]33[/C][C]33.2339[/C][C]-0.233929[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]32.7335[/C][C]-1.73351[/C][/ROW]
[ROW][C]23[/C][C]38[/C][C]36.6511[/C][C]1.34889[/C][/ROW]
[ROW][C]24[/C][C]39[/C][C]35.1334[/C][C]3.86657[/C][/ROW]
[ROW][C]25[/C][C]32[/C][C]36.3636[/C][C]-4.36356[/C][/ROW]
[ROW][C]26[/C][C]32[/C][C]37.0514[/C][C]-5.05142[/C][/ROW]
[ROW][C]27[/C][C]35[/C][C]34.7133[/C][C]0.286712[/C][/ROW]
[ROW][C]28[/C][C]37[/C][C]33.7789[/C][C]3.22115[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]33.6918[/C][C]-0.691839[/C][/ROW]
[ROW][C]30[/C][C]33[/C][C]33.4726[/C][C]-0.472553[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]32.7461[/C][C]-1.74605[/C][/ROW]
[ROW][C]32[/C][C]32[/C][C]30.1372[/C][C]1.86281[/C][/ROW]
[ROW][C]33[/C][C]31[/C][C]34.8987[/C][C]-3.89869[/C][/ROW]
[ROW][C]34[/C][C]37[/C][C]34.0955[/C][C]2.90453[/C][/ROW]
[ROW][C]35[/C][C]30[/C][C]33.8131[/C][C]-3.81307[/C][/ROW]
[ROW][C]36[/C][C]33[/C][C]31.9019[/C][C]1.09811[/C][/ROW]
[ROW][C]37[/C][C]31[/C][C]30.722[/C][C]0.277992[/C][/ROW]
[ROW][C]38[/C][C]33[/C][C]34.6714[/C][C]-1.67136[/C][/ROW]
[ROW][C]39[/C][C]31[/C][C]31.8366[/C][C]-0.836623[/C][/ROW]
[ROW][C]40[/C][C]33[/C][C]34.1982[/C][C]-1.19825[/C][/ROW]
[ROW][C]41[/C][C]32[/C][C]35.0886[/C][C]-3.08862[/C][/ROW]
[ROW][C]42[/C][C]33[/C][C]33.881[/C][C]-0.881029[/C][/ROW]
[ROW][C]43[/C][C]32[/C][C]36.6583[/C][C]-4.65834[/C][/ROW]
[ROW][C]44[/C][C]33[/C][C]33.9234[/C][C]-0.923421[/C][/ROW]
[ROW][C]45[/C][C]28[/C][C]35.2533[/C][C]-7.2533[/C][/ROW]
[ROW][C]46[/C][C]35[/C][C]34.575[/C][C]0.42504[/C][/ROW]
[ROW][C]47[/C][C]39[/C][C]35.6121[/C][C]3.38789[/C][/ROW]
[ROW][C]48[/C][C]34[/C][C]33.4294[/C][C]0.570598[/C][/ROW]
[ROW][C]49[/C][C]38[/C][C]34.8827[/C][C]3.11735[/C][/ROW]
[ROW][C]50[/C][C]32[/C][C]35.4334[/C][C]-3.43339[/C][/ROW]
[ROW][C]51[/C][C]38[/C][C]33.538[/C][C]4.46196[/C][/ROW]
[ROW][C]52[/C][C]30[/C][C]32.7426[/C][C]-2.74261[/C][/ROW]
[ROW][C]53[/C][C]33[/C][C]32.6479[/C][C]0.352132[/C][/ROW]
[ROW][C]54[/C][C]38[/C][C]34.1327[/C][C]3.8673[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]31.4117[/C][C]0.588299[/C][/ROW]
[ROW][C]56[/C][C]35[/C][C]34.363[/C][C]0.636955[/C][/ROW]
[ROW][C]57[/C][C]34[/C][C]36.2101[/C][C]-2.21011[/C][/ROW]
[ROW][C]58[/C][C]34[/C][C]32.0129[/C][C]1.98708[/C][/ROW]
[ROW][C]59[/C][C]36[/C][C]34.9893[/C][C]1.01066[/C][/ROW]
[ROW][C]60[/C][C]34[/C][C]34.1851[/C][C]-0.185099[/C][/ROW]
[ROW][C]61[/C][C]28[/C][C]31.1185[/C][C]-3.11855[/C][/ROW]
[ROW][C]62[/C][C]34[/C][C]35.6951[/C][C]-1.69507[/C][/ROW]
[ROW][C]63[/C][C]35[/C][C]34.2152[/C][C]0.784826[/C][/ROW]
[ROW][C]64[/C][C]35[/C][C]32.4497[/C][C]2.55026[/C][/ROW]
[ROW][C]65[/C][C]31[/C][C]34.103[/C][C]-3.10305[/C][/ROW]
[ROW][C]66[/C][C]37[/C][C]34.6011[/C][C]2.39889[/C][/ROW]
[ROW][C]67[/C][C]35[/C][C]35.322[/C][C]-0.321991[/C][/ROW]
[ROW][C]68[/C][C]27[/C][C]32.4788[/C][C]-5.47878[/C][/ROW]
[ROW][C]69[/C][C]40[/C][C]35.6622[/C][C]4.33776[/C][/ROW]
[ROW][C]70[/C][C]37[/C][C]34.5218[/C][C]2.47817[/C][/ROW]
[ROW][C]71[/C][C]36[/C][C]34.4688[/C][C]1.53125[/C][/ROW]
[ROW][C]72[/C][C]38[/C][C]32.5177[/C][C]5.4823[/C][/ROW]
[ROW][C]73[/C][C]39[/C][C]34.6052[/C][C]4.3948[/C][/ROW]
[ROW][C]74[/C][C]41[/C][C]36.2538[/C][C]4.74619[/C][/ROW]
[ROW][C]75[/C][C]27[/C][C]34.0313[/C][C]-7.0313[/C][/ROW]
[ROW][C]76[/C][C]30[/C][C]35.867[/C][C]-5.86704[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.5343[/C][C]1.46567[/C][/ROW]
[ROW][C]78[/C][C]31[/C][C]33.9319[/C][C]-2.93189[/C][/ROW]
[ROW][C]79[/C][C]31[/C][C]31.2262[/C][C]-0.226241[/C][/ROW]
[ROW][C]80[/C][C]27[/C][C]35.2687[/C][C]-8.26871[/C][/ROW]
[ROW][C]81[/C][C]36[/C][C]33.6805[/C][C]2.31952[/C][/ROW]
[ROW][C]82[/C][C]37[/C][C]34.5029[/C][C]2.49711[/C][/ROW]
[ROW][C]83[/C][C]33[/C][C]35.2474[/C][C]-2.24738[/C][/ROW]
[ROW][C]84[/C][C]34[/C][C]33.0182[/C][C]0.981806[/C][/ROW]
[ROW][C]85[/C][C]31[/C][C]33.4117[/C][C]-2.41171[/C][/ROW]
[ROW][C]86[/C][C]39[/C][C]35.1387[/C][C]3.86125[/C][/ROW]
[ROW][C]87[/C][C]34[/C][C]33.6522[/C][C]0.347822[/C][/ROW]
[ROW][C]88[/C][C]32[/C][C]31.9715[/C][C]0.0285253[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.3365[/C][C]-0.336505[/C][/ROW]
[ROW][C]90[/C][C]36[/C][C]32.0401[/C][C]3.95994[/C][/ROW]
[ROW][C]91[/C][C]32[/C][C]35.3718[/C][C]-3.37177[/C][/ROW]
[ROW][C]92[/C][C]41[/C][C]34.518[/C][C]6.48196[/C][/ROW]
[ROW][C]93[/C][C]28[/C][C]33.1196[/C][C]-5.1196[/C][/ROW]
[ROW][C]94[/C][C]30[/C][C]31.5752[/C][C]-1.57517[/C][/ROW]
[ROW][C]95[/C][C]36[/C][C]35.9583[/C][C]0.0417272[/C][/ROW]
[ROW][C]96[/C][C]35[/C][C]35.3853[/C][C]-0.385264[/C][/ROW]
[ROW][C]97[/C][C]31[/C][C]34.112[/C][C]-3.11199[/C][/ROW]
[ROW][C]98[/C][C]34[/C][C]35.4046[/C][C]-1.40463[/C][/ROW]
[ROW][C]99[/C][C]36[/C][C]32.7595[/C][C]3.24046[/C][/ROW]
[ROW][C]100[/C][C]36[/C][C]36.0601[/C][C]-0.0600938[/C][/ROW]
[ROW][C]101[/C][C]35[/C][C]35.141[/C][C]-0.141006[/C][/ROW]
[ROW][C]102[/C][C]37[/C][C]35.8435[/C][C]1.1565[/C][/ROW]
[ROW][C]103[/C][C]28[/C][C]32.8861[/C][C]-4.88606[/C][/ROW]
[ROW][C]104[/C][C]39[/C][C]33.5773[/C][C]5.42272[/C][/ROW]
[ROW][C]105[/C][C]32[/C][C]36.0364[/C][C]-4.03639[/C][/ROW]
[ROW][C]106[/C][C]35[/C][C]35.9165[/C][C]-0.916482[/C][/ROW]
[ROW][C]107[/C][C]39[/C][C]37.0194[/C][C]1.98063[/C][/ROW]
[ROW][C]108[/C][C]35[/C][C]34.6581[/C][C]0.341948[/C][/ROW]
[ROW][C]109[/C][C]42[/C][C]36.5928[/C][C]5.4072[/C][/ROW]
[ROW][C]110[/C][C]34[/C][C]32.4469[/C][C]1.55315[/C][/ROW]
[ROW][C]111[/C][C]33[/C][C]32.9816[/C][C]0.0184488[/C][/ROW]
[ROW][C]112[/C][C]41[/C][C]33.2081[/C][C]7.79187[/C][/ROW]
[ROW][C]113[/C][C]33[/C][C]32.7396[/C][C]0.26042[/C][/ROW]
[ROW][C]114[/C][C]34[/C][C]34.6805[/C][C]-0.680461[/C][/ROW]
[ROW][C]115[/C][C]32[/C][C]35.7488[/C][C]-3.74877[/C][/ROW]
[ROW][C]116[/C][C]40[/C][C]33.524[/C][C]6.47601[/C][/ROW]
[ROW][C]117[/C][C]40[/C][C]33.3246[/C][C]6.67545[/C][/ROW]
[ROW][C]118[/C][C]35[/C][C]33.1319[/C][C]1.86815[/C][/ROW]
[ROW][C]119[/C][C]36[/C][C]35.7385[/C][C]0.261486[/C][/ROW]
[ROW][C]120[/C][C]37[/C][C]33.0904[/C][C]3.9096[/C][/ROW]
[ROW][C]121[/C][C]27[/C][C]32.9519[/C][C]-5.95189[/C][/ROW]
[ROW][C]122[/C][C]39[/C][C]35.3686[/C][C]3.63139[/C][/ROW]
[ROW][C]123[/C][C]38[/C][C]35.5734[/C][C]2.42665[/C][/ROW]
[ROW][C]124[/C][C]31[/C][C]34.9186[/C][C]-3.91864[/C][/ROW]
[ROW][C]125[/C][C]33[/C][C]33.1527[/C][C]-0.152703[/C][/ROW]
[ROW][C]126[/C][C]32[/C][C]35.8501[/C][C]-3.85005[/C][/ROW]
[ROW][C]127[/C][C]39[/C][C]38.3126[/C][C]0.68738[/C][/ROW]
[ROW][C]128[/C][C]36[/C][C]33.3135[/C][C]2.68651[/C][/ROW]
[ROW][C]129[/C][C]33[/C][C]33.8801[/C][C]-0.88013[/C][/ROW]
[ROW][C]130[/C][C]33[/C][C]32.9571[/C][C]0.0429489[/C][/ROW]
[ROW][C]131[/C][C]32[/C][C]30.5513[/C][C]1.44873[/C][/ROW]
[ROW][C]132[/C][C]37[/C][C]36.0931[/C][C]0.906864[/C][/ROW]
[ROW][C]133[/C][C]30[/C][C]30.5677[/C][C]-0.567746[/C][/ROW]
[ROW][C]134[/C][C]38[/C][C]35.0864[/C][C]2.91365[/C][/ROW]
[ROW][C]135[/C][C]29[/C][C]33.18[/C][C]-4.17998[/C][/ROW]
[ROW][C]136[/C][C]22[/C][C]30.7694[/C][C]-8.76938[/C][/ROW]
[ROW][C]137[/C][C]35[/C][C]33.8237[/C][C]1.17633[/C][/ROW]
[ROW][C]138[/C][C]35[/C][C]31.4371[/C][C]3.5629[/C][/ROW]
[ROW][C]139[/C][C]34[/C][C]33.5062[/C][C]0.493833[/C][/ROW]
[ROW][C]140[/C][C]35[/C][C]31.779[/C][C]3.22101[/C][/ROW]
[ROW][C]141[/C][C]34[/C][C]32.7732[/C][C]1.22682[/C][/ROW]
[ROW][C]142[/C][C]37[/C][C]31.9836[/C][C]5.01639[/C][/ROW]
[ROW][C]143[/C][C]35[/C][C]32.9025[/C][C]2.09747[/C][/ROW]
[ROW][C]144[/C][C]23[/C][C]32.7321[/C][C]-9.73214[/C][/ROW]
[ROW][C]145[/C][C]31[/C][C]35.3553[/C][C]-4.35534[/C][/ROW]
[ROW][C]146[/C][C]27[/C][C]33.6814[/C][C]-6.68137[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]34.4179[/C][C]1.58214[/C][/ROW]
[ROW][C]148[/C][C]31[/C][C]33.1692[/C][C]-2.16922[/C][/ROW]
[ROW][C]149[/C][C]32[/C][C]33.595[/C][C]-1.59503[/C][/ROW]
[ROW][C]150[/C][C]39[/C][C]34.407[/C][C]4.59299[/C][/ROW]
[ROW][C]151[/C][C]37[/C][C]37.3672[/C][C]-0.367166[/C][/ROW]
[ROW][C]152[/C][C]38[/C][C]33.7536[/C][C]4.24641[/C][/ROW]
[ROW][C]153[/C][C]39[/C][C]33.6852[/C][C]5.31478[/C][/ROW]
[ROW][C]154[/C][C]34[/C][C]34.8468[/C][C]-0.846826[/C][/ROW]
[ROW][C]155[/C][C]31[/C][C]32.3806[/C][C]-1.38063[/C][/ROW]
[ROW][C]156[/C][C]32[/C][C]35.3718[/C][C]-3.37177[/C][/ROW]
[ROW][C]157[/C][C]37[/C][C]32.1251[/C][C]4.87485[/C][/ROW]
[ROW][C]158[/C][C]36[/C][C]33.3135[/C][C]2.68651[/C][/ROW]
[ROW][C]159[/C][C]32[/C][C]33.9016[/C][C]-1.9016[/C][/ROW]
[ROW][C]160[/C][C]38[/C][C]32.1914[/C][C]5.80856[/C][/ROW]
[ROW][C]161[/C][C]36[/C][C]33.1749[/C][C]2.82512[/C][/ROW]
[ROW][C]162[/C][C]26[/C][C]30.4482[/C][C]-4.44822[/C][/ROW]
[ROW][C]163[/C][C]26[/C][C]31.8255[/C][C]-5.82546[/C][/ROW]
[ROW][C]164[/C][C]33[/C][C]36.1948[/C][C]-3.19483[/C][/ROW]
[ROW][C]165[/C][C]39[/C][C]33.5883[/C][C]5.41165[/C][/ROW]
[ROW][C]166[/C][C]30[/C][C]28.6004[/C][C]1.39956[/C][/ROW]
[ROW][C]167[/C][C]33[/C][C]32.0272[/C][C]0.972827[/C][/ROW]
[ROW][C]168[/C][C]25[/C][C]30.0459[/C][C]-5.04589[/C][/ROW]
[ROW][C]169[/C][C]38[/C][C]33.5351[/C][C]4.46494[/C][/ROW]
[ROW][C]170[/C][C]37[/C][C]31.0245[/C][C]5.9755[/C][/ROW]
[ROW][C]171[/C][C]31[/C][C]33.8755[/C][C]-2.87551[/C][/ROW]
[ROW][C]172[/C][C]37[/C][C]34.9613[/C][C]2.03867[/C][/ROW]
[ROW][C]173[/C][C]35[/C][C]36.0517[/C][C]-1.05167[/C][/ROW]
[ROW][C]174[/C][C]25[/C][C]30.4658[/C][C]-5.46579[/C][/ROW]
[ROW][C]175[/C][C]28[/C][C]34.4493[/C][C]-6.44934[/C][/ROW]
[ROW][C]176[/C][C]35[/C][C]32.9427[/C][C]2.05734[/C][/ROW]
[ROW][C]177[/C][C]33[/C][C]34.1626[/C][C]-1.16258[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.4836[/C][C]-1.48358[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]32.3766[/C][C]-1.37664[/C][/ROW]
[ROW][C]180[/C][C]37[/C][C]34.7563[/C][C]2.2437[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]34.8934[/C][C]1.10662[/C][/ROW]
[ROW][C]182[/C][C]30[/C][C]33.0612[/C][C]-3.06122[/C][/ROW]
[ROW][C]183[/C][C]36[/C][C]33.6037[/C][C]2.39629[/C][/ROW]
[ROW][C]184[/C][C]32[/C][C]35.5906[/C][C]-3.59063[/C][/ROW]
[ROW][C]185[/C][C]28[/C][C]28.1161[/C][C]-0.116056[/C][/ROW]
[ROW][C]186[/C][C]36[/C][C]33.2316[/C][C]2.76839[/C][/ROW]
[ROW][C]187[/C][C]34[/C][C]34.9116[/C][C]-0.911553[/C][/ROW]
[ROW][C]188[/C][C]31[/C][C]35.0478[/C][C]-4.0478[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.2973[/C][C]-2.29732[/C][/ROW]
[ROW][C]190[/C][C]36[/C][C]31.6754[/C][C]4.32462[/C][/ROW]
[ROW][C]191[/C][C]36[/C][C]32.8868[/C][C]3.11318[/C][/ROW]
[ROW][C]192[/C][C]40[/C][C]35.7196[/C][C]4.28042[/C][/ROW]
[ROW][C]193[/C][C]33[/C][C]31.6657[/C][C]1.33431[/C][/ROW]
[ROW][C]194[/C][C]37[/C][C]34.2789[/C][C]2.72107[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]32.6457[/C][C]-0.645749[/C][/ROW]
[ROW][C]196[/C][C]38[/C][C]35.119[/C][C]2.88096[/C][/ROW]
[ROW][C]197[/C][C]31[/C][C]33.7273[/C][C]-2.7273[/C][/ROW]
[ROW][C]198[/C][C]37[/C][C]33.6635[/C][C]3.33646[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]32.8619[/C][C]0.138105[/C][/ROW]
[ROW][C]200[/C][C]32[/C][C]30.7189[/C][C]1.28108[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]32.2657[/C][C]-2.2657[/C][/ROW]
[ROW][C]202[/C][C]30[/C][C]29.4472[/C][C]0.552839[/C][/ROW]
[ROW][C]203[/C][C]31[/C][C]33.1485[/C][C]-2.14853[/C][/ROW]
[ROW][C]204[/C][C]32[/C][C]33.5269[/C][C]-1.52688[/C][/ROW]
[ROW][C]205[/C][C]34[/C][C]33.063[/C][C]0.936986[/C][/ROW]
[ROW][C]206[/C][C]36[/C][C]33.852[/C][C]2.14803[/C][/ROW]
[ROW][C]207[/C][C]37[/C][C]34.36[/C][C]2.63996[/C][/ROW]
[ROW][C]208[/C][C]36[/C][C]34.5577[/C][C]1.4423[/C][/ROW]
[ROW][C]209[/C][C]33[/C][C]33.9837[/C][C]-0.983666[/C][/ROW]
[ROW][C]210[/C][C]33[/C][C]33.7581[/C][C]-0.758141[/C][/ROW]
[ROW][C]211[/C][C]33[/C][C]33.4099[/C][C]-0.409899[/C][/ROW]
[ROW][C]212[/C][C]44[/C][C]36.5167[/C][C]7.48326[/C][/ROW]
[ROW][C]213[/C][C]39[/C][C]32.9126[/C][C]6.08743[/C][/ROW]
[ROW][C]214[/C][C]32[/C][C]31.6652[/C][C]0.334826[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]34.4048[/C][C]0.595153[/C][/ROW]
[ROW][C]216[/C][C]25[/C][C]31.1109[/C][C]-6.11093[/C][/ROW]
[ROW][C]217[/C][C]35[/C][C]33.7515[/C][C]1.24854[/C][/ROW]
[ROW][C]218[/C][C]34[/C][C]35.64[/C][C]-1.64[/C][/ROW]
[ROW][C]219[/C][C]35[/C][C]33.8672[/C][C]1.13283[/C][/ROW]
[ROW][C]220[/C][C]39[/C][C]34.8079[/C][C]4.19212[/C][/ROW]
[ROW][C]221[/C][C]33[/C][C]33.9991[/C][C]-0.999074[/C][/ROW]
[ROW][C]222[/C][C]36[/C][C]35.2892[/C][C]0.710825[/C][/ROW]
[ROW][C]223[/C][C]32[/C][C]33.4138[/C][C]-1.41383[/C][/ROW]
[ROW][C]224[/C][C]32[/C][C]31.9607[/C][C]0.0392573[/C][/ROW]
[ROW][C]225[/C][C]36[/C][C]33.1876[/C][C]2.81239[/C][/ROW]
[ROW][C]226[/C][C]36[/C][C]31.5294[/C][C]4.47056[/C][/ROW]
[ROW][C]227[/C][C]32[/C][C]32.4767[/C][C]-0.476681[/C][/ROW]
[ROW][C]228[/C][C]34[/C][C]32.9637[/C][C]1.03627[/C][/ROW]
[ROW][C]229[/C][C]33[/C][C]32.9052[/C][C]0.0947964[/C][/ROW]
[ROW][C]230[/C][C]35[/C][C]33.0925[/C][C]1.90747[/C][/ROW]
[ROW][C]231[/C][C]30[/C][C]32.9476[/C][C]-2.94756[/C][/ROW]
[ROW][C]232[/C][C]38[/C][C]32.489[/C][C]5.51103[/C][/ROW]
[ROW][C]233[/C][C]34[/C][C]32.5251[/C][C]1.47487[/C][/ROW]
[ROW][C]234[/C][C]33[/C][C]37.4611[/C][C]-4.46114[/C][/ROW]
[ROW][C]235[/C][C]32[/C][C]33.4889[/C][C]-1.48889[/C][/ROW]
[ROW][C]236[/C][C]31[/C][C]33.9195[/C][C]-2.91949[/C][/ROW]
[ROW][C]237[/C][C]30[/C][C]32.9868[/C][C]-2.9868[/C][/ROW]
[ROW][C]238[/C][C]27[/C][C]34.482[/C][C]-7.48203[/C][/ROW]
[ROW][C]239[/C][C]31[/C][C]31.8601[/C][C]-0.860067[/C][/ROW]
[ROW][C]240[/C][C]30[/C][C]33.8316[/C][C]-3.83158[/C][/ROW]
[ROW][C]241[/C][C]32[/C][C]30.0862[/C][C]1.91384[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.6783[/C][C]1.32175[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]29.6553[/C][C]-1.65535[/C][/ROW]
[ROW][C]244[/C][C]33[/C][C]33.3135[/C][C]-0.313533[/C][/ROW]
[ROW][C]245[/C][C]31[/C][C]34.9786[/C][C]-3.97861[/C][/ROW]
[ROW][C]246[/C][C]35[/C][C]30.9219[/C][C]4.07806[/C][/ROW]
[ROW][C]247[/C][C]35[/C][C]32.5922[/C][C]2.40782[/C][/ROW]
[ROW][C]248[/C][C]32[/C][C]33.7988[/C][C]-1.79876[/C][/ROW]
[ROW][C]249[/C][C]21[/C][C]26.7399[/C][C]-5.73991[/C][/ROW]
[ROW][C]250[/C][C]20[/C][C]27.741[/C][C]-7.74105[/C][/ROW]
[ROW][C]251[/C][C]34[/C][C]31.6065[/C][C]2.39352[/C][/ROW]
[ROW][C]252[/C][C]32[/C][C]32.2547[/C][C]-0.25471[/C][/ROW]
[ROW][C]253[/C][C]34[/C][C]33.6127[/C][C]0.387268[/C][/ROW]
[ROW][C]254[/C][C]32[/C][C]33.2575[/C][C]-1.25749[/C][/ROW]
[ROW][C]255[/C][C]33[/C][C]34.5069[/C][C]-1.50688[/C][/ROW]
[ROW][C]256[/C][C]33[/C][C]33.6343[/C][C]-0.634343[/C][/ROW]
[ROW][C]257[/C][C]37[/C][C]34.3558[/C][C]2.64418[/C][/ROW]
[ROW][C]258[/C][C]32[/C][C]31.9381[/C][C]0.0619252[/C][/ROW]
[ROW][C]259[/C][C]34[/C][C]34.8466[/C][C]-0.84664[/C][/ROW]
[ROW][C]260[/C][C]30[/C][C]31.6922[/C][C]-1.69217[/C][/ROW]
[ROW][C]261[/C][C]30[/C][C]30.9111[/C][C]-0.911134[/C][/ROW]
[ROW][C]262[/C][C]38[/C][C]33.4545[/C][C]4.54547[/C][/ROW]
[ROW][C]263[/C][C]36[/C][C]35.115[/C][C]0.884959[/C][/ROW]
[ROW][C]264[/C][C]32[/C][C]31.3679[/C][C]0.63208[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221840&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221840&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
13836.58531.4147
23236.1446-4.14457
33533.07171.92827
43331.89631.1037
53734.02972.97033
62933.9794-4.97942
73136.5669-5.56686
83634.17871.8213
93534.66380.336217
103834.85273.1473
113135.5716-4.57158
123435.0424-1.04244
133535.6102-0.610171
143836.09181.90824
153734.26832.73172
163333.1158-0.115812
173234.5315-2.53153
183836.33541.6646
193836.27031.72967
203233.3051-1.30514
213333.2339-0.233929
223132.7335-1.73351
233836.65111.34889
243935.13343.86657
253236.3636-4.36356
263237.0514-5.05142
273534.71330.286712
283733.77893.22115
293333.6918-0.691839
303333.4726-0.472553
313132.7461-1.74605
323230.13721.86281
333134.8987-3.89869
343734.09552.90453
353033.8131-3.81307
363331.90191.09811
373130.7220.277992
383334.6714-1.67136
393131.8366-0.836623
403334.1982-1.19825
413235.0886-3.08862
423333.881-0.881029
433236.6583-4.65834
443333.9234-0.923421
452835.2533-7.2533
463534.5750.42504
473935.61213.38789
483433.42940.570598
493834.88273.11735
503235.4334-3.43339
513833.5384.46196
523032.7426-2.74261
533332.64790.352132
543834.13273.8673
553231.41170.588299
563534.3630.636955
573436.2101-2.21011
583432.01291.98708
593634.98931.01066
603434.1851-0.185099
612831.1185-3.11855
623435.6951-1.69507
633534.21520.784826
643532.44972.55026
653134.103-3.10305
663734.60112.39889
673535.322-0.321991
682732.4788-5.47878
694035.66224.33776
703734.52182.47817
713634.46881.53125
723832.51775.4823
733934.60524.3948
744136.25384.74619
752734.0313-7.0313
763035.867-5.86704
773735.53431.46567
783133.9319-2.93189
793131.2262-0.226241
802735.2687-8.26871
813633.68052.31952
823734.50292.49711
833335.2474-2.24738
843433.01820.981806
853133.4117-2.41171
863935.13873.86125
873433.65220.347822
883231.97150.0285253
893333.3365-0.336505
903632.04013.95994
913235.3718-3.37177
924134.5186.48196
932833.1196-5.1196
943031.5752-1.57517
953635.95830.0417272
963535.3853-0.385264
973134.112-3.11199
983435.4046-1.40463
993632.75953.24046
1003636.0601-0.0600938
1013535.141-0.141006
1023735.84351.1565
1032832.8861-4.88606
1043933.57735.42272
1053236.0364-4.03639
1063535.9165-0.916482
1073937.01941.98063
1083534.65810.341948
1094236.59285.4072
1103432.44691.55315
1113332.98160.0184488
1124133.20817.79187
1133332.73960.26042
1143434.6805-0.680461
1153235.7488-3.74877
1164033.5246.47601
1174033.32466.67545
1183533.13191.86815
1193635.73850.261486
1203733.09043.9096
1212732.9519-5.95189
1223935.36863.63139
1233835.57342.42665
1243134.9186-3.91864
1253333.1527-0.152703
1263235.8501-3.85005
1273938.31260.68738
1283633.31352.68651
1293333.8801-0.88013
1303332.95710.0429489
1313230.55131.44873
1323736.09310.906864
1333030.5677-0.567746
1343835.08642.91365
1352933.18-4.17998
1362230.7694-8.76938
1373533.82371.17633
1383531.43713.5629
1393433.50620.493833
1403531.7793.22101
1413432.77321.22682
1423731.98365.01639
1433532.90252.09747
1442332.7321-9.73214
1453135.3553-4.35534
1462733.6814-6.68137
1473634.41791.58214
1483133.1692-2.16922
1493233.595-1.59503
1503934.4074.59299
1513737.3672-0.367166
1523833.75364.24641
1533933.68525.31478
1543434.8468-0.846826
1553132.3806-1.38063
1563235.3718-3.37177
1573732.12514.87485
1583633.31352.68651
1593233.9016-1.9016
1603832.19145.80856
1613633.17492.82512
1622630.4482-4.44822
1632631.8255-5.82546
1643336.1948-3.19483
1653933.58835.41165
1663028.60041.39956
1673332.02720.972827
1682530.0459-5.04589
1693833.53514.46494
1703731.02455.9755
1713133.8755-2.87551
1723734.96132.03867
1733536.0517-1.05167
1742530.4658-5.46579
1752834.4493-6.44934
1763532.94272.05734
1773334.1626-1.16258
1783031.4836-1.48358
1793132.3766-1.37664
1803734.75632.2437
1813634.89341.10662
1823033.0612-3.06122
1833633.60372.39629
1843235.5906-3.59063
1852828.1161-0.116056
1863633.23162.76839
1873434.9116-0.911553
1883135.0478-4.0478
1892830.2973-2.29732
1903631.67544.32462
1913632.88683.11318
1924035.71964.28042
1933331.66571.33431
1943734.27892.72107
1953232.6457-0.645749
1963835.1192.88096
1973133.7273-2.7273
1983733.66353.33646
1993332.86190.138105
2003230.71891.28108
2013032.2657-2.2657
2023029.44720.552839
2033133.1485-2.14853
2043233.5269-1.52688
2053433.0630.936986
2063633.8522.14803
2073734.362.63996
2083634.55771.4423
2093333.9837-0.983666
2103333.7581-0.758141
2113333.4099-0.409899
2124436.51677.48326
2133932.91266.08743
2143231.66520.334826
2153534.40480.595153
2162531.1109-6.11093
2173533.75151.24854
2183435.64-1.64
2193533.86721.13283
2203934.80794.19212
2213333.9991-0.999074
2223635.28920.710825
2233233.4138-1.41383
2243231.96070.0392573
2253633.18762.81239
2263631.52944.47056
2273232.4767-0.476681
2283432.96371.03627
2293332.90520.0947964
2303533.09251.90747
2313032.9476-2.94756
2323832.4895.51103
2333432.52511.47487
2343337.4611-4.46114
2353233.4889-1.48889
2363133.9195-2.91949
2373032.9868-2.9868
2382734.482-7.48203
2393131.8601-0.860067
2403033.8316-3.83158
2413230.08621.91384
2423533.67831.32175
2432829.6553-1.65535
2443333.3135-0.313533
2453134.9786-3.97861
2463530.92194.07806
2473532.59222.40782
2483233.7988-1.79876
2492126.7399-5.73991
2502027.741-7.74105
2513431.60652.39352
2523232.2547-0.25471
2533433.61270.387268
2543233.2575-1.25749
2553334.5069-1.50688
2563333.6343-0.634343
2573734.35582.64418
2583231.93810.0619252
2593434.8466-0.84664
2603031.6922-1.69217
2613030.9111-0.911134
2623833.45454.54547
2633635.1150.884959
2643231.36790.63208






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.3399810.6799620.660019
100.5746170.8507660.425383
110.433930.867860.56607
120.4462710.8925410.553729
130.3792930.7585850.620707
140.475120.9502410.52488
150.4546610.9093230.545339
160.3918610.7837220.608139
170.3412130.6824270.658787
180.398760.7975210.60124
190.3552440.7104870.644756
200.2974560.5949120.702544
210.2311190.4622380.768881
220.2306190.4612370.769381
230.1826650.3653310.817335
240.201560.4031210.79844
250.2257020.4514030.774298
260.3684810.7369620.631519
270.3131120.6262230.686888
280.285310.5706210.71469
290.238780.4775590.76122
300.1937780.3875560.806222
310.1754150.350830.824585
320.1416960.2833920.858304
330.1355460.2710910.864454
340.1314730.2629460.868527
350.1528470.3056940.847153
360.1314240.2628480.868576
370.1051330.2102660.894867
380.08490670.1698130.915093
390.06860220.1372040.931398
400.05301710.1060340.946983
410.04564290.09128580.954357
420.03457450.06914910.965425
430.0422270.0844540.957773
440.0319430.06388590.968057
450.06836180.1367240.931638
460.05455780.1091160.945442
470.06989710.1397940.930103
480.05533230.1106650.944668
490.06495580.1299120.935044
500.06132390.1226480.938676
510.06943560.1388710.930564
520.06710280.1342060.932897
530.05346310.1069260.946537
540.05710940.1142190.942891
550.04815260.09630530.951847
560.04459650.0891930.955403
570.0363280.0726560.963672
580.02899310.05798610.971007
590.02423240.04846490.975768
600.01842350.03684690.981577
610.02024640.04049290.979754
620.01586060.03172120.984139
630.01193490.02386990.988065
640.01015250.0203050.989847
650.01039670.02079340.989603
660.009056240.01811250.990944
670.00673460.01346920.993265
680.01484350.0296870.985156
690.0200070.0400140.979993
700.01873760.03747520.981262
710.01607810.03215620.983922
720.02391210.04782420.976088
730.02898570.05797140.971014
740.04150630.08301260.958494
750.09299620.1859920.907004
760.1101050.220210.889895
770.09481850.1896370.905181
780.08980540.1796110.910195
790.08043140.1608630.919569
800.1847030.3694060.815297
810.1714460.3428920.828554
820.1640820.3281640.835918
830.1520180.3040360.847982
840.1314030.2628070.868597
850.1192290.2384590.880771
860.145830.2916590.85417
870.124870.249740.87513
880.1065240.2130480.893476
890.08992910.1798580.910071
900.09310810.1862160.906892
910.09869140.1973830.901309
920.1618040.3236080.838196
930.2120370.4240750.787963
940.2012190.4024380.798781
950.1787350.357470.821265
960.1555730.3111470.844427
970.1479860.2959730.852014
980.131240.2624790.86876
990.1306150.261230.869385
1000.112090.2241790.88791
1010.09686740.1937350.903133
1020.08396150.1679230.916039
1030.1017170.2034340.898283
1040.1345290.2690580.865471
1050.1402890.2805790.859711
1060.1222380.2444760.877762
1070.1138570.2277140.886143
1080.1014310.2028620.898569
1090.1492630.2985270.850737
1100.1320690.2641380.867931
1110.1135950.227190.886405
1120.2333840.4667680.766616
1130.2075820.4151630.792418
1140.1855370.3710730.814463
1150.1923340.3846680.807666
1160.2615030.5230060.738497
1170.3681250.736250.631875
1180.3444110.6888210.655589
1190.3122620.6245250.687738
1200.3207680.6415350.679232
1210.4120980.8241960.587902
1220.4178050.835610.582195
1230.4027210.8054420.597279
1240.4211710.8423410.578829
1250.3870770.7741550.612923
1260.3983410.7966820.601659
1270.3710760.7421520.628924
1280.3584610.7169230.641539
1290.3312240.6624470.668776
1300.3006490.6012990.699351
1310.2781150.5562290.721885
1320.2563590.5127180.743641
1330.2368130.4736270.763187
1340.2298670.4597340.770133
1350.252160.504320.74784
1360.45410.90820.5459
1370.4231460.8462920.576854
1380.429760.859520.57024
1390.395580.791160.60442
1400.3939720.7879440.606028
1410.3653480.7306970.634652
1420.4105220.8210440.589478
1430.3905850.781170.609415
1440.6677850.6644310.332215
1450.6955340.6089320.304466
1460.7942570.4114870.205743
1470.7731910.4536170.226809
1480.7614570.4770870.238543
1490.7408290.5183420.259171
1500.7705840.4588320.229416
1510.7432710.5134580.256729
1520.7579350.484130.242065
1530.7943870.4112250.205613
1540.7726520.4546960.227348
1550.7501510.4996970.249849
1560.7587510.4824980.241249
1570.7916720.4166570.208328
1580.7856920.4286160.214308
1590.7734840.4530310.226516
1600.8328310.3343380.167169
1610.8277840.3444320.172216
1620.8470290.3059420.152971
1630.8893410.2213180.110659
1640.892690.214620.10731
1650.9157620.1684750.0842376
1660.9074210.1851580.092579
1670.8922820.2154370.107718
1680.9145050.1709910.0854953
1690.9231510.1536980.0768491
1700.9483280.1033440.0516718
1710.9462640.1074720.0537359
1720.9385030.1229940.0614969
1730.9292170.1415670.0707834
1740.9459940.1080120.0540062
1750.9724480.05510360.0275518
1760.9681820.06363510.0318175
1770.9620260.07594880.0379744
1780.9549720.09005510.0450276
1790.9468320.1063360.053168
1800.9401180.1197650.0598824
1810.9281660.1436670.0718336
1820.9260070.1479870.0739934
1830.9169990.1660010.0830007
1840.926930.1461410.0730703
1850.9145040.1709930.0854964
1860.9090710.1818570.0909287
1870.8957920.2084170.104208
1880.9136710.1726580.086329
1890.9023720.1952560.0976279
1900.9222530.1554940.0777471
1910.919550.1608990.0804496
1920.9217520.1564960.0782481
1930.9104630.1790730.0895365
1940.9021710.1956570.0978287
1950.8832450.233510.116755
1960.8728640.2542720.127136
1970.8686220.2627570.131378
1980.8679230.2641550.132077
1990.8435590.3128820.156441
2000.8257410.3485180.174259
2010.8092460.3815090.190754
2020.7865810.4268380.213419
2030.7666010.4667990.233399
2040.7392920.5214170.260708
2050.7046650.590670.295335
2060.6803760.6392490.319624
2070.661730.6765390.33827
2080.6267280.7465440.373272
2090.5882540.8234930.411746
2100.5456580.9086840.454342
2110.5009390.9981210.499061
2120.6705350.6589310.329465
2130.7816510.4366980.218349
2140.7457660.5084680.254234
2150.7081910.5836170.291809
2160.7780440.4439130.221956
2170.7494760.5010480.250524
2180.719760.560480.28024
2190.6810640.6378730.318936
2200.726250.5475010.27375
2210.6839230.6321540.316077
2220.6423190.7153630.357681
2230.5972750.805450.402725
2240.5477710.9044590.452229
2250.5417630.9164750.458237
2260.6236590.7526820.376341
2270.5811930.8376130.418807
2280.5360480.9279040.463952
2290.4804010.9608020.519599
2300.4503910.9007810.549609
2310.4247180.8494360.575282
2320.5955580.8088840.404442
2330.5441290.9117420.455871
2340.6060620.7878760.393938
2350.5477070.9045860.452293
2360.5119060.9761890.488094
2370.4646970.9293940.535303
2380.7466520.5066950.253348
2390.6923160.6153690.307684
2400.7502010.4995990.249799
2410.7450360.5099280.254964
2420.6836910.6326180.316309
2430.6168160.7663680.383184
2440.5394180.9211640.460582
2450.6922430.6155140.307757
2460.8788790.2422430.121121
2470.86770.2645990.1323
2480.8310110.3379790.168989
2490.7669980.4660040.233002
2500.9323050.135390.067695
2510.9277120.1445770.0722884
2520.8701360.2597290.129864
2530.8652350.2695310.134765
2540.8254760.3490470.174524
2550.8407010.3185980.159299

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.339981 & 0.679962 & 0.660019 \tabularnewline
10 & 0.574617 & 0.850766 & 0.425383 \tabularnewline
11 & 0.43393 & 0.86786 & 0.56607 \tabularnewline
12 & 0.446271 & 0.892541 & 0.553729 \tabularnewline
13 & 0.379293 & 0.758585 & 0.620707 \tabularnewline
14 & 0.47512 & 0.950241 & 0.52488 \tabularnewline
15 & 0.454661 & 0.909323 & 0.545339 \tabularnewline
16 & 0.391861 & 0.783722 & 0.608139 \tabularnewline
17 & 0.341213 & 0.682427 & 0.658787 \tabularnewline
18 & 0.39876 & 0.797521 & 0.60124 \tabularnewline
19 & 0.355244 & 0.710487 & 0.644756 \tabularnewline
20 & 0.297456 & 0.594912 & 0.702544 \tabularnewline
21 & 0.231119 & 0.462238 & 0.768881 \tabularnewline
22 & 0.230619 & 0.461237 & 0.769381 \tabularnewline
23 & 0.182665 & 0.365331 & 0.817335 \tabularnewline
24 & 0.20156 & 0.403121 & 0.79844 \tabularnewline
25 & 0.225702 & 0.451403 & 0.774298 \tabularnewline
26 & 0.368481 & 0.736962 & 0.631519 \tabularnewline
27 & 0.313112 & 0.626223 & 0.686888 \tabularnewline
28 & 0.28531 & 0.570621 & 0.71469 \tabularnewline
29 & 0.23878 & 0.477559 & 0.76122 \tabularnewline
30 & 0.193778 & 0.387556 & 0.806222 \tabularnewline
31 & 0.175415 & 0.35083 & 0.824585 \tabularnewline
32 & 0.141696 & 0.283392 & 0.858304 \tabularnewline
33 & 0.135546 & 0.271091 & 0.864454 \tabularnewline
34 & 0.131473 & 0.262946 & 0.868527 \tabularnewline
35 & 0.152847 & 0.305694 & 0.847153 \tabularnewline
36 & 0.131424 & 0.262848 & 0.868576 \tabularnewline
37 & 0.105133 & 0.210266 & 0.894867 \tabularnewline
38 & 0.0849067 & 0.169813 & 0.915093 \tabularnewline
39 & 0.0686022 & 0.137204 & 0.931398 \tabularnewline
40 & 0.0530171 & 0.106034 & 0.946983 \tabularnewline
41 & 0.0456429 & 0.0912858 & 0.954357 \tabularnewline
42 & 0.0345745 & 0.0691491 & 0.965425 \tabularnewline
43 & 0.042227 & 0.084454 & 0.957773 \tabularnewline
44 & 0.031943 & 0.0638859 & 0.968057 \tabularnewline
45 & 0.0683618 & 0.136724 & 0.931638 \tabularnewline
46 & 0.0545578 & 0.109116 & 0.945442 \tabularnewline
47 & 0.0698971 & 0.139794 & 0.930103 \tabularnewline
48 & 0.0553323 & 0.110665 & 0.944668 \tabularnewline
49 & 0.0649558 & 0.129912 & 0.935044 \tabularnewline
50 & 0.0613239 & 0.122648 & 0.938676 \tabularnewline
51 & 0.0694356 & 0.138871 & 0.930564 \tabularnewline
52 & 0.0671028 & 0.134206 & 0.932897 \tabularnewline
53 & 0.0534631 & 0.106926 & 0.946537 \tabularnewline
54 & 0.0571094 & 0.114219 & 0.942891 \tabularnewline
55 & 0.0481526 & 0.0963053 & 0.951847 \tabularnewline
56 & 0.0445965 & 0.089193 & 0.955403 \tabularnewline
57 & 0.036328 & 0.072656 & 0.963672 \tabularnewline
58 & 0.0289931 & 0.0579861 & 0.971007 \tabularnewline
59 & 0.0242324 & 0.0484649 & 0.975768 \tabularnewline
60 & 0.0184235 & 0.0368469 & 0.981577 \tabularnewline
61 & 0.0202464 & 0.0404929 & 0.979754 \tabularnewline
62 & 0.0158606 & 0.0317212 & 0.984139 \tabularnewline
63 & 0.0119349 & 0.0238699 & 0.988065 \tabularnewline
64 & 0.0101525 & 0.020305 & 0.989847 \tabularnewline
65 & 0.0103967 & 0.0207934 & 0.989603 \tabularnewline
66 & 0.00905624 & 0.0181125 & 0.990944 \tabularnewline
67 & 0.0067346 & 0.0134692 & 0.993265 \tabularnewline
68 & 0.0148435 & 0.029687 & 0.985156 \tabularnewline
69 & 0.020007 & 0.040014 & 0.979993 \tabularnewline
70 & 0.0187376 & 0.0374752 & 0.981262 \tabularnewline
71 & 0.0160781 & 0.0321562 & 0.983922 \tabularnewline
72 & 0.0239121 & 0.0478242 & 0.976088 \tabularnewline
73 & 0.0289857 & 0.0579714 & 0.971014 \tabularnewline
74 & 0.0415063 & 0.0830126 & 0.958494 \tabularnewline
75 & 0.0929962 & 0.185992 & 0.907004 \tabularnewline
76 & 0.110105 & 0.22021 & 0.889895 \tabularnewline
77 & 0.0948185 & 0.189637 & 0.905181 \tabularnewline
78 & 0.0898054 & 0.179611 & 0.910195 \tabularnewline
79 & 0.0804314 & 0.160863 & 0.919569 \tabularnewline
80 & 0.184703 & 0.369406 & 0.815297 \tabularnewline
81 & 0.171446 & 0.342892 & 0.828554 \tabularnewline
82 & 0.164082 & 0.328164 & 0.835918 \tabularnewline
83 & 0.152018 & 0.304036 & 0.847982 \tabularnewline
84 & 0.131403 & 0.262807 & 0.868597 \tabularnewline
85 & 0.119229 & 0.238459 & 0.880771 \tabularnewline
86 & 0.14583 & 0.291659 & 0.85417 \tabularnewline
87 & 0.12487 & 0.24974 & 0.87513 \tabularnewline
88 & 0.106524 & 0.213048 & 0.893476 \tabularnewline
89 & 0.0899291 & 0.179858 & 0.910071 \tabularnewline
90 & 0.0931081 & 0.186216 & 0.906892 \tabularnewline
91 & 0.0986914 & 0.197383 & 0.901309 \tabularnewline
92 & 0.161804 & 0.323608 & 0.838196 \tabularnewline
93 & 0.212037 & 0.424075 & 0.787963 \tabularnewline
94 & 0.201219 & 0.402438 & 0.798781 \tabularnewline
95 & 0.178735 & 0.35747 & 0.821265 \tabularnewline
96 & 0.155573 & 0.311147 & 0.844427 \tabularnewline
97 & 0.147986 & 0.295973 & 0.852014 \tabularnewline
98 & 0.13124 & 0.262479 & 0.86876 \tabularnewline
99 & 0.130615 & 0.26123 & 0.869385 \tabularnewline
100 & 0.11209 & 0.224179 & 0.88791 \tabularnewline
101 & 0.0968674 & 0.193735 & 0.903133 \tabularnewline
102 & 0.0839615 & 0.167923 & 0.916039 \tabularnewline
103 & 0.101717 & 0.203434 & 0.898283 \tabularnewline
104 & 0.134529 & 0.269058 & 0.865471 \tabularnewline
105 & 0.140289 & 0.280579 & 0.859711 \tabularnewline
106 & 0.122238 & 0.244476 & 0.877762 \tabularnewline
107 & 0.113857 & 0.227714 & 0.886143 \tabularnewline
108 & 0.101431 & 0.202862 & 0.898569 \tabularnewline
109 & 0.149263 & 0.298527 & 0.850737 \tabularnewline
110 & 0.132069 & 0.264138 & 0.867931 \tabularnewline
111 & 0.113595 & 0.22719 & 0.886405 \tabularnewline
112 & 0.233384 & 0.466768 & 0.766616 \tabularnewline
113 & 0.207582 & 0.415163 & 0.792418 \tabularnewline
114 & 0.185537 & 0.371073 & 0.814463 \tabularnewline
115 & 0.192334 & 0.384668 & 0.807666 \tabularnewline
116 & 0.261503 & 0.523006 & 0.738497 \tabularnewline
117 & 0.368125 & 0.73625 & 0.631875 \tabularnewline
118 & 0.344411 & 0.688821 & 0.655589 \tabularnewline
119 & 0.312262 & 0.624525 & 0.687738 \tabularnewline
120 & 0.320768 & 0.641535 & 0.679232 \tabularnewline
121 & 0.412098 & 0.824196 & 0.587902 \tabularnewline
122 & 0.417805 & 0.83561 & 0.582195 \tabularnewline
123 & 0.402721 & 0.805442 & 0.597279 \tabularnewline
124 & 0.421171 & 0.842341 & 0.578829 \tabularnewline
125 & 0.387077 & 0.774155 & 0.612923 \tabularnewline
126 & 0.398341 & 0.796682 & 0.601659 \tabularnewline
127 & 0.371076 & 0.742152 & 0.628924 \tabularnewline
128 & 0.358461 & 0.716923 & 0.641539 \tabularnewline
129 & 0.331224 & 0.662447 & 0.668776 \tabularnewline
130 & 0.300649 & 0.601299 & 0.699351 \tabularnewline
131 & 0.278115 & 0.556229 & 0.721885 \tabularnewline
132 & 0.256359 & 0.512718 & 0.743641 \tabularnewline
133 & 0.236813 & 0.473627 & 0.763187 \tabularnewline
134 & 0.229867 & 0.459734 & 0.770133 \tabularnewline
135 & 0.25216 & 0.50432 & 0.74784 \tabularnewline
136 & 0.4541 & 0.9082 & 0.5459 \tabularnewline
137 & 0.423146 & 0.846292 & 0.576854 \tabularnewline
138 & 0.42976 & 0.85952 & 0.57024 \tabularnewline
139 & 0.39558 & 0.79116 & 0.60442 \tabularnewline
140 & 0.393972 & 0.787944 & 0.606028 \tabularnewline
141 & 0.365348 & 0.730697 & 0.634652 \tabularnewline
142 & 0.410522 & 0.821044 & 0.589478 \tabularnewline
143 & 0.390585 & 0.78117 & 0.609415 \tabularnewline
144 & 0.667785 & 0.664431 & 0.332215 \tabularnewline
145 & 0.695534 & 0.608932 & 0.304466 \tabularnewline
146 & 0.794257 & 0.411487 & 0.205743 \tabularnewline
147 & 0.773191 & 0.453617 & 0.226809 \tabularnewline
148 & 0.761457 & 0.477087 & 0.238543 \tabularnewline
149 & 0.740829 & 0.518342 & 0.259171 \tabularnewline
150 & 0.770584 & 0.458832 & 0.229416 \tabularnewline
151 & 0.743271 & 0.513458 & 0.256729 \tabularnewline
152 & 0.757935 & 0.48413 & 0.242065 \tabularnewline
153 & 0.794387 & 0.411225 & 0.205613 \tabularnewline
154 & 0.772652 & 0.454696 & 0.227348 \tabularnewline
155 & 0.750151 & 0.499697 & 0.249849 \tabularnewline
156 & 0.758751 & 0.482498 & 0.241249 \tabularnewline
157 & 0.791672 & 0.416657 & 0.208328 \tabularnewline
158 & 0.785692 & 0.428616 & 0.214308 \tabularnewline
159 & 0.773484 & 0.453031 & 0.226516 \tabularnewline
160 & 0.832831 & 0.334338 & 0.167169 \tabularnewline
161 & 0.827784 & 0.344432 & 0.172216 \tabularnewline
162 & 0.847029 & 0.305942 & 0.152971 \tabularnewline
163 & 0.889341 & 0.221318 & 0.110659 \tabularnewline
164 & 0.89269 & 0.21462 & 0.10731 \tabularnewline
165 & 0.915762 & 0.168475 & 0.0842376 \tabularnewline
166 & 0.907421 & 0.185158 & 0.092579 \tabularnewline
167 & 0.892282 & 0.215437 & 0.107718 \tabularnewline
168 & 0.914505 & 0.170991 & 0.0854953 \tabularnewline
169 & 0.923151 & 0.153698 & 0.0768491 \tabularnewline
170 & 0.948328 & 0.103344 & 0.0516718 \tabularnewline
171 & 0.946264 & 0.107472 & 0.0537359 \tabularnewline
172 & 0.938503 & 0.122994 & 0.0614969 \tabularnewline
173 & 0.929217 & 0.141567 & 0.0707834 \tabularnewline
174 & 0.945994 & 0.108012 & 0.0540062 \tabularnewline
175 & 0.972448 & 0.0551036 & 0.0275518 \tabularnewline
176 & 0.968182 & 0.0636351 & 0.0318175 \tabularnewline
177 & 0.962026 & 0.0759488 & 0.0379744 \tabularnewline
178 & 0.954972 & 0.0900551 & 0.0450276 \tabularnewline
179 & 0.946832 & 0.106336 & 0.053168 \tabularnewline
180 & 0.940118 & 0.119765 & 0.0598824 \tabularnewline
181 & 0.928166 & 0.143667 & 0.0718336 \tabularnewline
182 & 0.926007 & 0.147987 & 0.0739934 \tabularnewline
183 & 0.916999 & 0.166001 & 0.0830007 \tabularnewline
184 & 0.92693 & 0.146141 & 0.0730703 \tabularnewline
185 & 0.914504 & 0.170993 & 0.0854964 \tabularnewline
186 & 0.909071 & 0.181857 & 0.0909287 \tabularnewline
187 & 0.895792 & 0.208417 & 0.104208 \tabularnewline
188 & 0.913671 & 0.172658 & 0.086329 \tabularnewline
189 & 0.902372 & 0.195256 & 0.0976279 \tabularnewline
190 & 0.922253 & 0.155494 & 0.0777471 \tabularnewline
191 & 0.91955 & 0.160899 & 0.0804496 \tabularnewline
192 & 0.921752 & 0.156496 & 0.0782481 \tabularnewline
193 & 0.910463 & 0.179073 & 0.0895365 \tabularnewline
194 & 0.902171 & 0.195657 & 0.0978287 \tabularnewline
195 & 0.883245 & 0.23351 & 0.116755 \tabularnewline
196 & 0.872864 & 0.254272 & 0.127136 \tabularnewline
197 & 0.868622 & 0.262757 & 0.131378 \tabularnewline
198 & 0.867923 & 0.264155 & 0.132077 \tabularnewline
199 & 0.843559 & 0.312882 & 0.156441 \tabularnewline
200 & 0.825741 & 0.348518 & 0.174259 \tabularnewline
201 & 0.809246 & 0.381509 & 0.190754 \tabularnewline
202 & 0.786581 & 0.426838 & 0.213419 \tabularnewline
203 & 0.766601 & 0.466799 & 0.233399 \tabularnewline
204 & 0.739292 & 0.521417 & 0.260708 \tabularnewline
205 & 0.704665 & 0.59067 & 0.295335 \tabularnewline
206 & 0.680376 & 0.639249 & 0.319624 \tabularnewline
207 & 0.66173 & 0.676539 & 0.33827 \tabularnewline
208 & 0.626728 & 0.746544 & 0.373272 \tabularnewline
209 & 0.588254 & 0.823493 & 0.411746 \tabularnewline
210 & 0.545658 & 0.908684 & 0.454342 \tabularnewline
211 & 0.500939 & 0.998121 & 0.499061 \tabularnewline
212 & 0.670535 & 0.658931 & 0.329465 \tabularnewline
213 & 0.781651 & 0.436698 & 0.218349 \tabularnewline
214 & 0.745766 & 0.508468 & 0.254234 \tabularnewline
215 & 0.708191 & 0.583617 & 0.291809 \tabularnewline
216 & 0.778044 & 0.443913 & 0.221956 \tabularnewline
217 & 0.749476 & 0.501048 & 0.250524 \tabularnewline
218 & 0.71976 & 0.56048 & 0.28024 \tabularnewline
219 & 0.681064 & 0.637873 & 0.318936 \tabularnewline
220 & 0.72625 & 0.547501 & 0.27375 \tabularnewline
221 & 0.683923 & 0.632154 & 0.316077 \tabularnewline
222 & 0.642319 & 0.715363 & 0.357681 \tabularnewline
223 & 0.597275 & 0.80545 & 0.402725 \tabularnewline
224 & 0.547771 & 0.904459 & 0.452229 \tabularnewline
225 & 0.541763 & 0.916475 & 0.458237 \tabularnewline
226 & 0.623659 & 0.752682 & 0.376341 \tabularnewline
227 & 0.581193 & 0.837613 & 0.418807 \tabularnewline
228 & 0.536048 & 0.927904 & 0.463952 \tabularnewline
229 & 0.480401 & 0.960802 & 0.519599 \tabularnewline
230 & 0.450391 & 0.900781 & 0.549609 \tabularnewline
231 & 0.424718 & 0.849436 & 0.575282 \tabularnewline
232 & 0.595558 & 0.808884 & 0.404442 \tabularnewline
233 & 0.544129 & 0.911742 & 0.455871 \tabularnewline
234 & 0.606062 & 0.787876 & 0.393938 \tabularnewline
235 & 0.547707 & 0.904586 & 0.452293 \tabularnewline
236 & 0.511906 & 0.976189 & 0.488094 \tabularnewline
237 & 0.464697 & 0.929394 & 0.535303 \tabularnewline
238 & 0.746652 & 0.506695 & 0.253348 \tabularnewline
239 & 0.692316 & 0.615369 & 0.307684 \tabularnewline
240 & 0.750201 & 0.499599 & 0.249799 \tabularnewline
241 & 0.745036 & 0.509928 & 0.254964 \tabularnewline
242 & 0.683691 & 0.632618 & 0.316309 \tabularnewline
243 & 0.616816 & 0.766368 & 0.383184 \tabularnewline
244 & 0.539418 & 0.921164 & 0.460582 \tabularnewline
245 & 0.692243 & 0.615514 & 0.307757 \tabularnewline
246 & 0.878879 & 0.242243 & 0.121121 \tabularnewline
247 & 0.8677 & 0.264599 & 0.1323 \tabularnewline
248 & 0.831011 & 0.337979 & 0.168989 \tabularnewline
249 & 0.766998 & 0.466004 & 0.233002 \tabularnewline
250 & 0.932305 & 0.13539 & 0.067695 \tabularnewline
251 & 0.927712 & 0.144577 & 0.0722884 \tabularnewline
252 & 0.870136 & 0.259729 & 0.129864 \tabularnewline
253 & 0.865235 & 0.269531 & 0.134765 \tabularnewline
254 & 0.825476 & 0.349047 & 0.174524 \tabularnewline
255 & 0.840701 & 0.318598 & 0.159299 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221840&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]0.339981[/C][C]0.679962[/C][C]0.660019[/C][/ROW]
[ROW][C]10[/C][C]0.574617[/C][C]0.850766[/C][C]0.425383[/C][/ROW]
[ROW][C]11[/C][C]0.43393[/C][C]0.86786[/C][C]0.56607[/C][/ROW]
[ROW][C]12[/C][C]0.446271[/C][C]0.892541[/C][C]0.553729[/C][/ROW]
[ROW][C]13[/C][C]0.379293[/C][C]0.758585[/C][C]0.620707[/C][/ROW]
[ROW][C]14[/C][C]0.47512[/C][C]0.950241[/C][C]0.52488[/C][/ROW]
[ROW][C]15[/C][C]0.454661[/C][C]0.909323[/C][C]0.545339[/C][/ROW]
[ROW][C]16[/C][C]0.391861[/C][C]0.783722[/C][C]0.608139[/C][/ROW]
[ROW][C]17[/C][C]0.341213[/C][C]0.682427[/C][C]0.658787[/C][/ROW]
[ROW][C]18[/C][C]0.39876[/C][C]0.797521[/C][C]0.60124[/C][/ROW]
[ROW][C]19[/C][C]0.355244[/C][C]0.710487[/C][C]0.644756[/C][/ROW]
[ROW][C]20[/C][C]0.297456[/C][C]0.594912[/C][C]0.702544[/C][/ROW]
[ROW][C]21[/C][C]0.231119[/C][C]0.462238[/C][C]0.768881[/C][/ROW]
[ROW][C]22[/C][C]0.230619[/C][C]0.461237[/C][C]0.769381[/C][/ROW]
[ROW][C]23[/C][C]0.182665[/C][C]0.365331[/C][C]0.817335[/C][/ROW]
[ROW][C]24[/C][C]0.20156[/C][C]0.403121[/C][C]0.79844[/C][/ROW]
[ROW][C]25[/C][C]0.225702[/C][C]0.451403[/C][C]0.774298[/C][/ROW]
[ROW][C]26[/C][C]0.368481[/C][C]0.736962[/C][C]0.631519[/C][/ROW]
[ROW][C]27[/C][C]0.313112[/C][C]0.626223[/C][C]0.686888[/C][/ROW]
[ROW][C]28[/C][C]0.28531[/C][C]0.570621[/C][C]0.71469[/C][/ROW]
[ROW][C]29[/C][C]0.23878[/C][C]0.477559[/C][C]0.76122[/C][/ROW]
[ROW][C]30[/C][C]0.193778[/C][C]0.387556[/C][C]0.806222[/C][/ROW]
[ROW][C]31[/C][C]0.175415[/C][C]0.35083[/C][C]0.824585[/C][/ROW]
[ROW][C]32[/C][C]0.141696[/C][C]0.283392[/C][C]0.858304[/C][/ROW]
[ROW][C]33[/C][C]0.135546[/C][C]0.271091[/C][C]0.864454[/C][/ROW]
[ROW][C]34[/C][C]0.131473[/C][C]0.262946[/C][C]0.868527[/C][/ROW]
[ROW][C]35[/C][C]0.152847[/C][C]0.305694[/C][C]0.847153[/C][/ROW]
[ROW][C]36[/C][C]0.131424[/C][C]0.262848[/C][C]0.868576[/C][/ROW]
[ROW][C]37[/C][C]0.105133[/C][C]0.210266[/C][C]0.894867[/C][/ROW]
[ROW][C]38[/C][C]0.0849067[/C][C]0.169813[/C][C]0.915093[/C][/ROW]
[ROW][C]39[/C][C]0.0686022[/C][C]0.137204[/C][C]0.931398[/C][/ROW]
[ROW][C]40[/C][C]0.0530171[/C][C]0.106034[/C][C]0.946983[/C][/ROW]
[ROW][C]41[/C][C]0.0456429[/C][C]0.0912858[/C][C]0.954357[/C][/ROW]
[ROW][C]42[/C][C]0.0345745[/C][C]0.0691491[/C][C]0.965425[/C][/ROW]
[ROW][C]43[/C][C]0.042227[/C][C]0.084454[/C][C]0.957773[/C][/ROW]
[ROW][C]44[/C][C]0.031943[/C][C]0.0638859[/C][C]0.968057[/C][/ROW]
[ROW][C]45[/C][C]0.0683618[/C][C]0.136724[/C][C]0.931638[/C][/ROW]
[ROW][C]46[/C][C]0.0545578[/C][C]0.109116[/C][C]0.945442[/C][/ROW]
[ROW][C]47[/C][C]0.0698971[/C][C]0.139794[/C][C]0.930103[/C][/ROW]
[ROW][C]48[/C][C]0.0553323[/C][C]0.110665[/C][C]0.944668[/C][/ROW]
[ROW][C]49[/C][C]0.0649558[/C][C]0.129912[/C][C]0.935044[/C][/ROW]
[ROW][C]50[/C][C]0.0613239[/C][C]0.122648[/C][C]0.938676[/C][/ROW]
[ROW][C]51[/C][C]0.0694356[/C][C]0.138871[/C][C]0.930564[/C][/ROW]
[ROW][C]52[/C][C]0.0671028[/C][C]0.134206[/C][C]0.932897[/C][/ROW]
[ROW][C]53[/C][C]0.0534631[/C][C]0.106926[/C][C]0.946537[/C][/ROW]
[ROW][C]54[/C][C]0.0571094[/C][C]0.114219[/C][C]0.942891[/C][/ROW]
[ROW][C]55[/C][C]0.0481526[/C][C]0.0963053[/C][C]0.951847[/C][/ROW]
[ROW][C]56[/C][C]0.0445965[/C][C]0.089193[/C][C]0.955403[/C][/ROW]
[ROW][C]57[/C][C]0.036328[/C][C]0.072656[/C][C]0.963672[/C][/ROW]
[ROW][C]58[/C][C]0.0289931[/C][C]0.0579861[/C][C]0.971007[/C][/ROW]
[ROW][C]59[/C][C]0.0242324[/C][C]0.0484649[/C][C]0.975768[/C][/ROW]
[ROW][C]60[/C][C]0.0184235[/C][C]0.0368469[/C][C]0.981577[/C][/ROW]
[ROW][C]61[/C][C]0.0202464[/C][C]0.0404929[/C][C]0.979754[/C][/ROW]
[ROW][C]62[/C][C]0.0158606[/C][C]0.0317212[/C][C]0.984139[/C][/ROW]
[ROW][C]63[/C][C]0.0119349[/C][C]0.0238699[/C][C]0.988065[/C][/ROW]
[ROW][C]64[/C][C]0.0101525[/C][C]0.020305[/C][C]0.989847[/C][/ROW]
[ROW][C]65[/C][C]0.0103967[/C][C]0.0207934[/C][C]0.989603[/C][/ROW]
[ROW][C]66[/C][C]0.00905624[/C][C]0.0181125[/C][C]0.990944[/C][/ROW]
[ROW][C]67[/C][C]0.0067346[/C][C]0.0134692[/C][C]0.993265[/C][/ROW]
[ROW][C]68[/C][C]0.0148435[/C][C]0.029687[/C][C]0.985156[/C][/ROW]
[ROW][C]69[/C][C]0.020007[/C][C]0.040014[/C][C]0.979993[/C][/ROW]
[ROW][C]70[/C][C]0.0187376[/C][C]0.0374752[/C][C]0.981262[/C][/ROW]
[ROW][C]71[/C][C]0.0160781[/C][C]0.0321562[/C][C]0.983922[/C][/ROW]
[ROW][C]72[/C][C]0.0239121[/C][C]0.0478242[/C][C]0.976088[/C][/ROW]
[ROW][C]73[/C][C]0.0289857[/C][C]0.0579714[/C][C]0.971014[/C][/ROW]
[ROW][C]74[/C][C]0.0415063[/C][C]0.0830126[/C][C]0.958494[/C][/ROW]
[ROW][C]75[/C][C]0.0929962[/C][C]0.185992[/C][C]0.907004[/C][/ROW]
[ROW][C]76[/C][C]0.110105[/C][C]0.22021[/C][C]0.889895[/C][/ROW]
[ROW][C]77[/C][C]0.0948185[/C][C]0.189637[/C][C]0.905181[/C][/ROW]
[ROW][C]78[/C][C]0.0898054[/C][C]0.179611[/C][C]0.910195[/C][/ROW]
[ROW][C]79[/C][C]0.0804314[/C][C]0.160863[/C][C]0.919569[/C][/ROW]
[ROW][C]80[/C][C]0.184703[/C][C]0.369406[/C][C]0.815297[/C][/ROW]
[ROW][C]81[/C][C]0.171446[/C][C]0.342892[/C][C]0.828554[/C][/ROW]
[ROW][C]82[/C][C]0.164082[/C][C]0.328164[/C][C]0.835918[/C][/ROW]
[ROW][C]83[/C][C]0.152018[/C][C]0.304036[/C][C]0.847982[/C][/ROW]
[ROW][C]84[/C][C]0.131403[/C][C]0.262807[/C][C]0.868597[/C][/ROW]
[ROW][C]85[/C][C]0.119229[/C][C]0.238459[/C][C]0.880771[/C][/ROW]
[ROW][C]86[/C][C]0.14583[/C][C]0.291659[/C][C]0.85417[/C][/ROW]
[ROW][C]87[/C][C]0.12487[/C][C]0.24974[/C][C]0.87513[/C][/ROW]
[ROW][C]88[/C][C]0.106524[/C][C]0.213048[/C][C]0.893476[/C][/ROW]
[ROW][C]89[/C][C]0.0899291[/C][C]0.179858[/C][C]0.910071[/C][/ROW]
[ROW][C]90[/C][C]0.0931081[/C][C]0.186216[/C][C]0.906892[/C][/ROW]
[ROW][C]91[/C][C]0.0986914[/C][C]0.197383[/C][C]0.901309[/C][/ROW]
[ROW][C]92[/C][C]0.161804[/C][C]0.323608[/C][C]0.838196[/C][/ROW]
[ROW][C]93[/C][C]0.212037[/C][C]0.424075[/C][C]0.787963[/C][/ROW]
[ROW][C]94[/C][C]0.201219[/C][C]0.402438[/C][C]0.798781[/C][/ROW]
[ROW][C]95[/C][C]0.178735[/C][C]0.35747[/C][C]0.821265[/C][/ROW]
[ROW][C]96[/C][C]0.155573[/C][C]0.311147[/C][C]0.844427[/C][/ROW]
[ROW][C]97[/C][C]0.147986[/C][C]0.295973[/C][C]0.852014[/C][/ROW]
[ROW][C]98[/C][C]0.13124[/C][C]0.262479[/C][C]0.86876[/C][/ROW]
[ROW][C]99[/C][C]0.130615[/C][C]0.26123[/C][C]0.869385[/C][/ROW]
[ROW][C]100[/C][C]0.11209[/C][C]0.224179[/C][C]0.88791[/C][/ROW]
[ROW][C]101[/C][C]0.0968674[/C][C]0.193735[/C][C]0.903133[/C][/ROW]
[ROW][C]102[/C][C]0.0839615[/C][C]0.167923[/C][C]0.916039[/C][/ROW]
[ROW][C]103[/C][C]0.101717[/C][C]0.203434[/C][C]0.898283[/C][/ROW]
[ROW][C]104[/C][C]0.134529[/C][C]0.269058[/C][C]0.865471[/C][/ROW]
[ROW][C]105[/C][C]0.140289[/C][C]0.280579[/C][C]0.859711[/C][/ROW]
[ROW][C]106[/C][C]0.122238[/C][C]0.244476[/C][C]0.877762[/C][/ROW]
[ROW][C]107[/C][C]0.113857[/C][C]0.227714[/C][C]0.886143[/C][/ROW]
[ROW][C]108[/C][C]0.101431[/C][C]0.202862[/C][C]0.898569[/C][/ROW]
[ROW][C]109[/C][C]0.149263[/C][C]0.298527[/C][C]0.850737[/C][/ROW]
[ROW][C]110[/C][C]0.132069[/C][C]0.264138[/C][C]0.867931[/C][/ROW]
[ROW][C]111[/C][C]0.113595[/C][C]0.22719[/C][C]0.886405[/C][/ROW]
[ROW][C]112[/C][C]0.233384[/C][C]0.466768[/C][C]0.766616[/C][/ROW]
[ROW][C]113[/C][C]0.207582[/C][C]0.415163[/C][C]0.792418[/C][/ROW]
[ROW][C]114[/C][C]0.185537[/C][C]0.371073[/C][C]0.814463[/C][/ROW]
[ROW][C]115[/C][C]0.192334[/C][C]0.384668[/C][C]0.807666[/C][/ROW]
[ROW][C]116[/C][C]0.261503[/C][C]0.523006[/C][C]0.738497[/C][/ROW]
[ROW][C]117[/C][C]0.368125[/C][C]0.73625[/C][C]0.631875[/C][/ROW]
[ROW][C]118[/C][C]0.344411[/C][C]0.688821[/C][C]0.655589[/C][/ROW]
[ROW][C]119[/C][C]0.312262[/C][C]0.624525[/C][C]0.687738[/C][/ROW]
[ROW][C]120[/C][C]0.320768[/C][C]0.641535[/C][C]0.679232[/C][/ROW]
[ROW][C]121[/C][C]0.412098[/C][C]0.824196[/C][C]0.587902[/C][/ROW]
[ROW][C]122[/C][C]0.417805[/C][C]0.83561[/C][C]0.582195[/C][/ROW]
[ROW][C]123[/C][C]0.402721[/C][C]0.805442[/C][C]0.597279[/C][/ROW]
[ROW][C]124[/C][C]0.421171[/C][C]0.842341[/C][C]0.578829[/C][/ROW]
[ROW][C]125[/C][C]0.387077[/C][C]0.774155[/C][C]0.612923[/C][/ROW]
[ROW][C]126[/C][C]0.398341[/C][C]0.796682[/C][C]0.601659[/C][/ROW]
[ROW][C]127[/C][C]0.371076[/C][C]0.742152[/C][C]0.628924[/C][/ROW]
[ROW][C]128[/C][C]0.358461[/C][C]0.716923[/C][C]0.641539[/C][/ROW]
[ROW][C]129[/C][C]0.331224[/C][C]0.662447[/C][C]0.668776[/C][/ROW]
[ROW][C]130[/C][C]0.300649[/C][C]0.601299[/C][C]0.699351[/C][/ROW]
[ROW][C]131[/C][C]0.278115[/C][C]0.556229[/C][C]0.721885[/C][/ROW]
[ROW][C]132[/C][C]0.256359[/C][C]0.512718[/C][C]0.743641[/C][/ROW]
[ROW][C]133[/C][C]0.236813[/C][C]0.473627[/C][C]0.763187[/C][/ROW]
[ROW][C]134[/C][C]0.229867[/C][C]0.459734[/C][C]0.770133[/C][/ROW]
[ROW][C]135[/C][C]0.25216[/C][C]0.50432[/C][C]0.74784[/C][/ROW]
[ROW][C]136[/C][C]0.4541[/C][C]0.9082[/C][C]0.5459[/C][/ROW]
[ROW][C]137[/C][C]0.423146[/C][C]0.846292[/C][C]0.576854[/C][/ROW]
[ROW][C]138[/C][C]0.42976[/C][C]0.85952[/C][C]0.57024[/C][/ROW]
[ROW][C]139[/C][C]0.39558[/C][C]0.79116[/C][C]0.60442[/C][/ROW]
[ROW][C]140[/C][C]0.393972[/C][C]0.787944[/C][C]0.606028[/C][/ROW]
[ROW][C]141[/C][C]0.365348[/C][C]0.730697[/C][C]0.634652[/C][/ROW]
[ROW][C]142[/C][C]0.410522[/C][C]0.821044[/C][C]0.589478[/C][/ROW]
[ROW][C]143[/C][C]0.390585[/C][C]0.78117[/C][C]0.609415[/C][/ROW]
[ROW][C]144[/C][C]0.667785[/C][C]0.664431[/C][C]0.332215[/C][/ROW]
[ROW][C]145[/C][C]0.695534[/C][C]0.608932[/C][C]0.304466[/C][/ROW]
[ROW][C]146[/C][C]0.794257[/C][C]0.411487[/C][C]0.205743[/C][/ROW]
[ROW][C]147[/C][C]0.773191[/C][C]0.453617[/C][C]0.226809[/C][/ROW]
[ROW][C]148[/C][C]0.761457[/C][C]0.477087[/C][C]0.238543[/C][/ROW]
[ROW][C]149[/C][C]0.740829[/C][C]0.518342[/C][C]0.259171[/C][/ROW]
[ROW][C]150[/C][C]0.770584[/C][C]0.458832[/C][C]0.229416[/C][/ROW]
[ROW][C]151[/C][C]0.743271[/C][C]0.513458[/C][C]0.256729[/C][/ROW]
[ROW][C]152[/C][C]0.757935[/C][C]0.48413[/C][C]0.242065[/C][/ROW]
[ROW][C]153[/C][C]0.794387[/C][C]0.411225[/C][C]0.205613[/C][/ROW]
[ROW][C]154[/C][C]0.772652[/C][C]0.454696[/C][C]0.227348[/C][/ROW]
[ROW][C]155[/C][C]0.750151[/C][C]0.499697[/C][C]0.249849[/C][/ROW]
[ROW][C]156[/C][C]0.758751[/C][C]0.482498[/C][C]0.241249[/C][/ROW]
[ROW][C]157[/C][C]0.791672[/C][C]0.416657[/C][C]0.208328[/C][/ROW]
[ROW][C]158[/C][C]0.785692[/C][C]0.428616[/C][C]0.214308[/C][/ROW]
[ROW][C]159[/C][C]0.773484[/C][C]0.453031[/C][C]0.226516[/C][/ROW]
[ROW][C]160[/C][C]0.832831[/C][C]0.334338[/C][C]0.167169[/C][/ROW]
[ROW][C]161[/C][C]0.827784[/C][C]0.344432[/C][C]0.172216[/C][/ROW]
[ROW][C]162[/C][C]0.847029[/C][C]0.305942[/C][C]0.152971[/C][/ROW]
[ROW][C]163[/C][C]0.889341[/C][C]0.221318[/C][C]0.110659[/C][/ROW]
[ROW][C]164[/C][C]0.89269[/C][C]0.21462[/C][C]0.10731[/C][/ROW]
[ROW][C]165[/C][C]0.915762[/C][C]0.168475[/C][C]0.0842376[/C][/ROW]
[ROW][C]166[/C][C]0.907421[/C][C]0.185158[/C][C]0.092579[/C][/ROW]
[ROW][C]167[/C][C]0.892282[/C][C]0.215437[/C][C]0.107718[/C][/ROW]
[ROW][C]168[/C][C]0.914505[/C][C]0.170991[/C][C]0.0854953[/C][/ROW]
[ROW][C]169[/C][C]0.923151[/C][C]0.153698[/C][C]0.0768491[/C][/ROW]
[ROW][C]170[/C][C]0.948328[/C][C]0.103344[/C][C]0.0516718[/C][/ROW]
[ROW][C]171[/C][C]0.946264[/C][C]0.107472[/C][C]0.0537359[/C][/ROW]
[ROW][C]172[/C][C]0.938503[/C][C]0.122994[/C][C]0.0614969[/C][/ROW]
[ROW][C]173[/C][C]0.929217[/C][C]0.141567[/C][C]0.0707834[/C][/ROW]
[ROW][C]174[/C][C]0.945994[/C][C]0.108012[/C][C]0.0540062[/C][/ROW]
[ROW][C]175[/C][C]0.972448[/C][C]0.0551036[/C][C]0.0275518[/C][/ROW]
[ROW][C]176[/C][C]0.968182[/C][C]0.0636351[/C][C]0.0318175[/C][/ROW]
[ROW][C]177[/C][C]0.962026[/C][C]0.0759488[/C][C]0.0379744[/C][/ROW]
[ROW][C]178[/C][C]0.954972[/C][C]0.0900551[/C][C]0.0450276[/C][/ROW]
[ROW][C]179[/C][C]0.946832[/C][C]0.106336[/C][C]0.053168[/C][/ROW]
[ROW][C]180[/C][C]0.940118[/C][C]0.119765[/C][C]0.0598824[/C][/ROW]
[ROW][C]181[/C][C]0.928166[/C][C]0.143667[/C][C]0.0718336[/C][/ROW]
[ROW][C]182[/C][C]0.926007[/C][C]0.147987[/C][C]0.0739934[/C][/ROW]
[ROW][C]183[/C][C]0.916999[/C][C]0.166001[/C][C]0.0830007[/C][/ROW]
[ROW][C]184[/C][C]0.92693[/C][C]0.146141[/C][C]0.0730703[/C][/ROW]
[ROW][C]185[/C][C]0.914504[/C][C]0.170993[/C][C]0.0854964[/C][/ROW]
[ROW][C]186[/C][C]0.909071[/C][C]0.181857[/C][C]0.0909287[/C][/ROW]
[ROW][C]187[/C][C]0.895792[/C][C]0.208417[/C][C]0.104208[/C][/ROW]
[ROW][C]188[/C][C]0.913671[/C][C]0.172658[/C][C]0.086329[/C][/ROW]
[ROW][C]189[/C][C]0.902372[/C][C]0.195256[/C][C]0.0976279[/C][/ROW]
[ROW][C]190[/C][C]0.922253[/C][C]0.155494[/C][C]0.0777471[/C][/ROW]
[ROW][C]191[/C][C]0.91955[/C][C]0.160899[/C][C]0.0804496[/C][/ROW]
[ROW][C]192[/C][C]0.921752[/C][C]0.156496[/C][C]0.0782481[/C][/ROW]
[ROW][C]193[/C][C]0.910463[/C][C]0.179073[/C][C]0.0895365[/C][/ROW]
[ROW][C]194[/C][C]0.902171[/C][C]0.195657[/C][C]0.0978287[/C][/ROW]
[ROW][C]195[/C][C]0.883245[/C][C]0.23351[/C][C]0.116755[/C][/ROW]
[ROW][C]196[/C][C]0.872864[/C][C]0.254272[/C][C]0.127136[/C][/ROW]
[ROW][C]197[/C][C]0.868622[/C][C]0.262757[/C][C]0.131378[/C][/ROW]
[ROW][C]198[/C][C]0.867923[/C][C]0.264155[/C][C]0.132077[/C][/ROW]
[ROW][C]199[/C][C]0.843559[/C][C]0.312882[/C][C]0.156441[/C][/ROW]
[ROW][C]200[/C][C]0.825741[/C][C]0.348518[/C][C]0.174259[/C][/ROW]
[ROW][C]201[/C][C]0.809246[/C][C]0.381509[/C][C]0.190754[/C][/ROW]
[ROW][C]202[/C][C]0.786581[/C][C]0.426838[/C][C]0.213419[/C][/ROW]
[ROW][C]203[/C][C]0.766601[/C][C]0.466799[/C][C]0.233399[/C][/ROW]
[ROW][C]204[/C][C]0.739292[/C][C]0.521417[/C][C]0.260708[/C][/ROW]
[ROW][C]205[/C][C]0.704665[/C][C]0.59067[/C][C]0.295335[/C][/ROW]
[ROW][C]206[/C][C]0.680376[/C][C]0.639249[/C][C]0.319624[/C][/ROW]
[ROW][C]207[/C][C]0.66173[/C][C]0.676539[/C][C]0.33827[/C][/ROW]
[ROW][C]208[/C][C]0.626728[/C][C]0.746544[/C][C]0.373272[/C][/ROW]
[ROW][C]209[/C][C]0.588254[/C][C]0.823493[/C][C]0.411746[/C][/ROW]
[ROW][C]210[/C][C]0.545658[/C][C]0.908684[/C][C]0.454342[/C][/ROW]
[ROW][C]211[/C][C]0.500939[/C][C]0.998121[/C][C]0.499061[/C][/ROW]
[ROW][C]212[/C][C]0.670535[/C][C]0.658931[/C][C]0.329465[/C][/ROW]
[ROW][C]213[/C][C]0.781651[/C][C]0.436698[/C][C]0.218349[/C][/ROW]
[ROW][C]214[/C][C]0.745766[/C][C]0.508468[/C][C]0.254234[/C][/ROW]
[ROW][C]215[/C][C]0.708191[/C][C]0.583617[/C][C]0.291809[/C][/ROW]
[ROW][C]216[/C][C]0.778044[/C][C]0.443913[/C][C]0.221956[/C][/ROW]
[ROW][C]217[/C][C]0.749476[/C][C]0.501048[/C][C]0.250524[/C][/ROW]
[ROW][C]218[/C][C]0.71976[/C][C]0.56048[/C][C]0.28024[/C][/ROW]
[ROW][C]219[/C][C]0.681064[/C][C]0.637873[/C][C]0.318936[/C][/ROW]
[ROW][C]220[/C][C]0.72625[/C][C]0.547501[/C][C]0.27375[/C][/ROW]
[ROW][C]221[/C][C]0.683923[/C][C]0.632154[/C][C]0.316077[/C][/ROW]
[ROW][C]222[/C][C]0.642319[/C][C]0.715363[/C][C]0.357681[/C][/ROW]
[ROW][C]223[/C][C]0.597275[/C][C]0.80545[/C][C]0.402725[/C][/ROW]
[ROW][C]224[/C][C]0.547771[/C][C]0.904459[/C][C]0.452229[/C][/ROW]
[ROW][C]225[/C][C]0.541763[/C][C]0.916475[/C][C]0.458237[/C][/ROW]
[ROW][C]226[/C][C]0.623659[/C][C]0.752682[/C][C]0.376341[/C][/ROW]
[ROW][C]227[/C][C]0.581193[/C][C]0.837613[/C][C]0.418807[/C][/ROW]
[ROW][C]228[/C][C]0.536048[/C][C]0.927904[/C][C]0.463952[/C][/ROW]
[ROW][C]229[/C][C]0.480401[/C][C]0.960802[/C][C]0.519599[/C][/ROW]
[ROW][C]230[/C][C]0.450391[/C][C]0.900781[/C][C]0.549609[/C][/ROW]
[ROW][C]231[/C][C]0.424718[/C][C]0.849436[/C][C]0.575282[/C][/ROW]
[ROW][C]232[/C][C]0.595558[/C][C]0.808884[/C][C]0.404442[/C][/ROW]
[ROW][C]233[/C][C]0.544129[/C][C]0.911742[/C][C]0.455871[/C][/ROW]
[ROW][C]234[/C][C]0.606062[/C][C]0.787876[/C][C]0.393938[/C][/ROW]
[ROW][C]235[/C][C]0.547707[/C][C]0.904586[/C][C]0.452293[/C][/ROW]
[ROW][C]236[/C][C]0.511906[/C][C]0.976189[/C][C]0.488094[/C][/ROW]
[ROW][C]237[/C][C]0.464697[/C][C]0.929394[/C][C]0.535303[/C][/ROW]
[ROW][C]238[/C][C]0.746652[/C][C]0.506695[/C][C]0.253348[/C][/ROW]
[ROW][C]239[/C][C]0.692316[/C][C]0.615369[/C][C]0.307684[/C][/ROW]
[ROW][C]240[/C][C]0.750201[/C][C]0.499599[/C][C]0.249799[/C][/ROW]
[ROW][C]241[/C][C]0.745036[/C][C]0.509928[/C][C]0.254964[/C][/ROW]
[ROW][C]242[/C][C]0.683691[/C][C]0.632618[/C][C]0.316309[/C][/ROW]
[ROW][C]243[/C][C]0.616816[/C][C]0.766368[/C][C]0.383184[/C][/ROW]
[ROW][C]244[/C][C]0.539418[/C][C]0.921164[/C][C]0.460582[/C][/ROW]
[ROW][C]245[/C][C]0.692243[/C][C]0.615514[/C][C]0.307757[/C][/ROW]
[ROW][C]246[/C][C]0.878879[/C][C]0.242243[/C][C]0.121121[/C][/ROW]
[ROW][C]247[/C][C]0.8677[/C][C]0.264599[/C][C]0.1323[/C][/ROW]
[ROW][C]248[/C][C]0.831011[/C][C]0.337979[/C][C]0.168989[/C][/ROW]
[ROW][C]249[/C][C]0.766998[/C][C]0.466004[/C][C]0.233002[/C][/ROW]
[ROW][C]250[/C][C]0.932305[/C][C]0.13539[/C][C]0.067695[/C][/ROW]
[ROW][C]251[/C][C]0.927712[/C][C]0.144577[/C][C]0.0722884[/C][/ROW]
[ROW][C]252[/C][C]0.870136[/C][C]0.259729[/C][C]0.129864[/C][/ROW]
[ROW][C]253[/C][C]0.865235[/C][C]0.269531[/C][C]0.134765[/C][/ROW]
[ROW][C]254[/C][C]0.825476[/C][C]0.349047[/C][C]0.174524[/C][/ROW]
[ROW][C]255[/C][C]0.840701[/C][C]0.318598[/C][C]0.159299[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221840&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221840&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
90.3399810.6799620.660019
100.5746170.8507660.425383
110.433930.867860.56607
120.4462710.8925410.553729
130.3792930.7585850.620707
140.475120.9502410.52488
150.4546610.9093230.545339
160.3918610.7837220.608139
170.3412130.6824270.658787
180.398760.7975210.60124
190.3552440.7104870.644756
200.2974560.5949120.702544
210.2311190.4622380.768881
220.2306190.4612370.769381
230.1826650.3653310.817335
240.201560.4031210.79844
250.2257020.4514030.774298
260.3684810.7369620.631519
270.3131120.6262230.686888
280.285310.5706210.71469
290.238780.4775590.76122
300.1937780.3875560.806222
310.1754150.350830.824585
320.1416960.2833920.858304
330.1355460.2710910.864454
340.1314730.2629460.868527
350.1528470.3056940.847153
360.1314240.2628480.868576
370.1051330.2102660.894867
380.08490670.1698130.915093
390.06860220.1372040.931398
400.05301710.1060340.946983
410.04564290.09128580.954357
420.03457450.06914910.965425
430.0422270.0844540.957773
440.0319430.06388590.968057
450.06836180.1367240.931638
460.05455780.1091160.945442
470.06989710.1397940.930103
480.05533230.1106650.944668
490.06495580.1299120.935044
500.06132390.1226480.938676
510.06943560.1388710.930564
520.06710280.1342060.932897
530.05346310.1069260.946537
540.05710940.1142190.942891
550.04815260.09630530.951847
560.04459650.0891930.955403
570.0363280.0726560.963672
580.02899310.05798610.971007
590.02423240.04846490.975768
600.01842350.03684690.981577
610.02024640.04049290.979754
620.01586060.03172120.984139
630.01193490.02386990.988065
640.01015250.0203050.989847
650.01039670.02079340.989603
660.009056240.01811250.990944
670.00673460.01346920.993265
680.01484350.0296870.985156
690.0200070.0400140.979993
700.01873760.03747520.981262
710.01607810.03215620.983922
720.02391210.04782420.976088
730.02898570.05797140.971014
740.04150630.08301260.958494
750.09299620.1859920.907004
760.1101050.220210.889895
770.09481850.1896370.905181
780.08980540.1796110.910195
790.08043140.1608630.919569
800.1847030.3694060.815297
810.1714460.3428920.828554
820.1640820.3281640.835918
830.1520180.3040360.847982
840.1314030.2628070.868597
850.1192290.2384590.880771
860.145830.2916590.85417
870.124870.249740.87513
880.1065240.2130480.893476
890.08992910.1798580.910071
900.09310810.1862160.906892
910.09869140.1973830.901309
920.1618040.3236080.838196
930.2120370.4240750.787963
940.2012190.4024380.798781
950.1787350.357470.821265
960.1555730.3111470.844427
970.1479860.2959730.852014
980.131240.2624790.86876
990.1306150.261230.869385
1000.112090.2241790.88791
1010.09686740.1937350.903133
1020.08396150.1679230.916039
1030.1017170.2034340.898283
1040.1345290.2690580.865471
1050.1402890.2805790.859711
1060.1222380.2444760.877762
1070.1138570.2277140.886143
1080.1014310.2028620.898569
1090.1492630.2985270.850737
1100.1320690.2641380.867931
1110.1135950.227190.886405
1120.2333840.4667680.766616
1130.2075820.4151630.792418
1140.1855370.3710730.814463
1150.1923340.3846680.807666
1160.2615030.5230060.738497
1170.3681250.736250.631875
1180.3444110.6888210.655589
1190.3122620.6245250.687738
1200.3207680.6415350.679232
1210.4120980.8241960.587902
1220.4178050.835610.582195
1230.4027210.8054420.597279
1240.4211710.8423410.578829
1250.3870770.7741550.612923
1260.3983410.7966820.601659
1270.3710760.7421520.628924
1280.3584610.7169230.641539
1290.3312240.6624470.668776
1300.3006490.6012990.699351
1310.2781150.5562290.721885
1320.2563590.5127180.743641
1330.2368130.4736270.763187
1340.2298670.4597340.770133
1350.252160.504320.74784
1360.45410.90820.5459
1370.4231460.8462920.576854
1380.429760.859520.57024
1390.395580.791160.60442
1400.3939720.7879440.606028
1410.3653480.7306970.634652
1420.4105220.8210440.589478
1430.3905850.781170.609415
1440.6677850.6644310.332215
1450.6955340.6089320.304466
1460.7942570.4114870.205743
1470.7731910.4536170.226809
1480.7614570.4770870.238543
1490.7408290.5183420.259171
1500.7705840.4588320.229416
1510.7432710.5134580.256729
1520.7579350.484130.242065
1530.7943870.4112250.205613
1540.7726520.4546960.227348
1550.7501510.4996970.249849
1560.7587510.4824980.241249
1570.7916720.4166570.208328
1580.7856920.4286160.214308
1590.7734840.4530310.226516
1600.8328310.3343380.167169
1610.8277840.3444320.172216
1620.8470290.3059420.152971
1630.8893410.2213180.110659
1640.892690.214620.10731
1650.9157620.1684750.0842376
1660.9074210.1851580.092579
1670.8922820.2154370.107718
1680.9145050.1709910.0854953
1690.9231510.1536980.0768491
1700.9483280.1033440.0516718
1710.9462640.1074720.0537359
1720.9385030.1229940.0614969
1730.9292170.1415670.0707834
1740.9459940.1080120.0540062
1750.9724480.05510360.0275518
1760.9681820.06363510.0318175
1770.9620260.07594880.0379744
1780.9549720.09005510.0450276
1790.9468320.1063360.053168
1800.9401180.1197650.0598824
1810.9281660.1436670.0718336
1820.9260070.1479870.0739934
1830.9169990.1660010.0830007
1840.926930.1461410.0730703
1850.9145040.1709930.0854964
1860.9090710.1818570.0909287
1870.8957920.2084170.104208
1880.9136710.1726580.086329
1890.9023720.1952560.0976279
1900.9222530.1554940.0777471
1910.919550.1608990.0804496
1920.9217520.1564960.0782481
1930.9104630.1790730.0895365
1940.9021710.1956570.0978287
1950.8832450.233510.116755
1960.8728640.2542720.127136
1970.8686220.2627570.131378
1980.8679230.2641550.132077
1990.8435590.3128820.156441
2000.8257410.3485180.174259
2010.8092460.3815090.190754
2020.7865810.4268380.213419
2030.7666010.4667990.233399
2040.7392920.5214170.260708
2050.7046650.590670.295335
2060.6803760.6392490.319624
2070.661730.6765390.33827
2080.6267280.7465440.373272
2090.5882540.8234930.411746
2100.5456580.9086840.454342
2110.5009390.9981210.499061
2120.6705350.6589310.329465
2130.7816510.4366980.218349
2140.7457660.5084680.254234
2150.7081910.5836170.291809
2160.7780440.4439130.221956
2170.7494760.5010480.250524
2180.719760.560480.28024
2190.6810640.6378730.318936
2200.726250.5475010.27375
2210.6839230.6321540.316077
2220.6423190.7153630.357681
2230.5972750.805450.402725
2240.5477710.9044590.452229
2250.5417630.9164750.458237
2260.6236590.7526820.376341
2270.5811930.8376130.418807
2280.5360480.9279040.463952
2290.4804010.9608020.519599
2300.4503910.9007810.549609
2310.4247180.8494360.575282
2320.5955580.8088840.404442
2330.5441290.9117420.455871
2340.6060620.7878760.393938
2350.5477070.9045860.452293
2360.5119060.9761890.488094
2370.4646970.9293940.535303
2380.7466520.5066950.253348
2390.6923160.6153690.307684
2400.7502010.4995990.249799
2410.7450360.5099280.254964
2420.6836910.6326180.316309
2430.6168160.7663680.383184
2440.5394180.9211640.460582
2450.6922430.6155140.307757
2460.8788790.2422430.121121
2470.86770.2645990.1323
2480.8310110.3379790.168989
2490.7669980.4660040.233002
2500.9323050.135390.067695
2510.9277120.1445770.0722884
2520.8701360.2597290.129864
2530.8652350.2695310.134765
2540.8254760.3490470.174524
2550.8407010.3185980.159299






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level140.0566802NOK
10% type I error level280.11336NOK

\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 & 14 & 0.0566802 & NOK \tabularnewline
10% type I error level & 28 & 0.11336 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221840&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]14[/C][C]0.0566802[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]28[/C][C]0.11336[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221840&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221840&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 level140.0566802NOK
10% type I error level280.11336NOK


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 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 2 ; 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')
}