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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 computationWed, 20 Nov 2013 18:47:53 -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/20/t13849914013m3gln0s0xaw798.htm/, Retrieved Wed, 01 May 2024 23:07:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226747, Retrieved Wed, 01 May 2024 23:07:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact58

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2013-11-20 23:47:53] [0d95bc223fb54d4a417cab286c0d6b3b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 13 14 12
39 32 16 18 11
30 35 19 11 14
31 33 15 12 12
34 37 14 16 21
35 29 13 18 12
39 31 19 14 22
34 36 15 14 11
36 35 14 15 10
37 38 15 15 13
38 31 16 17 10
36 34 16 19 8
38 35 16 10 15
39 38 16 16 14
33 37 17 18 10
32 33 15 14 14
36 32 15 14 14
38 38 20 17 11
39 38 18 14 10
32 32 16 16 13
32 33 16 18 9.5
31 31 16 11 14
39 38 19 14 12
37 39 16 12 14
39 32 17 17 11
41 32 17 9 9
36 35 16 16 11
33 37 15 14 15
33 33 16 15 14
34 33 14 11 13
31 31 15 16 9
27 32 12 13 15
37 31 14 17 10
34 37 16 15 11
34 30 14 14 13
32 33 10 16 8
29 31 10 9 20
36 33 14 15 12
29 31 16 17 10
35 33 16 13 10
37 32 16 15 9
34 33 14 16 14
38 32 20 16 8
35 33 14 12 14
38 28 14 15 11
37 35 11 11 13
38 39 14 15 9
33 34 15 15 11
36 38 16 17 15
38 32 14 13 11
32 38 16 16 10
32 30 14 14 14
32 33 12 11 18
34 38 16 12 14
32 32 9 12 11
37 35 14 15 14.5
39 34 16 16 13
29 34 16 15 9
37 36 15 12 10
35 34 16 12 15
30 28 12 8 20
38 34 16 13 12
34 35 16 11 12
31 35 14 14 14
34 31 16 15 13
35 37 17 10 11
36 35 18 11 17
30 27 18 12 12
39 40 12 15 13
35 37 16 15 14
38 36 10 14 13
31 38 14 16 15
34 39 18 15 13
38 41 18 15 10
34 27 16 13 11
39 30 17 12 19
37 37 16 17 13
34 31 16 13 17
28 31 13 15 13
37 27 16 13 9
33 36 16 15 11
35 37 16 15 9
37 33 15 16 12
32 34 15 15 12
33 31 16 14 13
38 39 14 15 13
33 34 16 14 12
29 32 16 13 15
33 33 15 7 22
31 36 12 17 13
36 32 17 13 15
35 41 16 15 13
32 28 15 14 15
29 30 13 13 12.5
39 36 16 16 11
37 35 16 12 16
35 31 16 14 11
37 34 16 17 11
32 36 14 15 10
38 36 16 17 10
37 35 16 12 16
36 37 20 16 12
32 28 15 11 11
33 39 16 15 16
40 32 13 9 19
38 35 17 16 11
41 39 16 15 16
36 35 16 10 15
43 42 12 10 24
30 34 16 15 14
31 33 16 11 15
32 41 17 13 11
32 33 13 14 15
37 34 12 18 12
37 32 18 16 10
33 40 14 14 14
34 40 14 14 13
33 35 13 14 9
38 36 16 14 15
33 37 13 12 15
31 27 16 14 14
38 39 13 15 11
37 38 16 15 8
36 31 15 15 11
31 33 16 13 11
39 32 15 17 8
44 39 17 17 10
33 36 15 19 11
35 33 12 15 13
32 33 16 13 11
28 32 10 9 20
40 37 16 15 10
27 30 12 15 15
37 38 14 15 12
32 29 15 16 14
28 22 13 11 23
34 35 15 14 14
30 35 11 11 16
35 34 12 15 11
31 35 11 13 12
32 34 16 15 10
30 37 15 16 14
30 35 17 14 12
31 23 16 15 12
40 31 10 16 11
32 27 18 16 12
36 36 13 11 13
32 31 16 12 11
35 32 13 9 19
38 39 10 16 12
42 37 15 13 17
34 38 16 16 9
35 39 16 12 12
38 34 14 9 19
33 31 10 13 18
36 32 17 13 15
32 37 13 14 14
33 36 15 19 11
34 32 16 13 9
32 38 12 12 18
34 36 13 13 16
27 26 13 10 24
31 26 12 14 14
38 33 17 16 20
34 39 15 10 18
24 30 10 11 23
30 33 14 14 12
26 25 11 12 14
34 38 13 9 16
27 37 16 9 18
37 31 12 11 20
36 37 16 16 12
41 35 12 9 12
29 25 9 13 17
36 28 12 16 13
32 35 15 13 9
37 33 12 9 16
30 30 12 12 18
31 31 14 16 10
38 37 12 11 14
36 36 16 14 11
35 30 11 13 9
31 36 19 15 11
38 32 15 14 10
22 28 8 16 11
32 36 16 13 19
36 34 17 14 14
39 31 12 15 12
28 28 11 13 14
32 36 11 11 21
32 36 14 11 13
38 40 16 14 10
32 33 12 15 15
35 37 16 11 16
32 32 13 15 14
37 38 15 12 12
34 31 16 14 19
33 37 16 14 15
33 33 14 8 19
26 32 16 13 13
30 30 16 9 17
24 30 14 15 12
34 31 11 17 11
34 32 12 13 14
33 34 15 15 11
34 36 15 15 13
35 37 16 14 12
35 36 16 16 15
36 33 11 13 14
34 33 15 16 12
34 33 12 9 17
41 44 12 16 11
32 39 15 11 18
30 32 15 10 13
35 35 16 11 17
28 25 14 15 13
33 35 17 17 11
39 34 14 14 12
36 35 13 8 22
36 39 15 15 14
35 33 13 11 12
38 36 14 16 12
33 32 15 10 17
31 32 12 15 9
34 36 13 9 21
32 36 8 16 10
31 32 14 19 11
33 34 14 12 12
34 33 11 8 23
34 35 12 11 13
34 30 13 14 12
33 38 10 9 16
32 34 16 15 9
41 33 18 13 17
34 32 13 16 9
36 31 11 11 14
37 30 4 12 17
36 27 13 13 13
29 31 16 10 11
37 30 10 11 12
27 32 12 12 10
35 35 12 8 19
28 28 10 12 16
35 33 13 12 16
37 31 15 15 14
29 35 12 11 20
32 35 14 13 15
36 32 10 14 23
19 21 12 10 20
21 20 12 12 16
31 34 11 15 14
33 32 10 13 17
36 34 12 13 11
33 32 16 13 13
37 33 12 12 17
34 33 14 12 15
35 37 16 9 21
31 32 14 9 18
37 34 13 15 15
35 30 4 10 8
27 30 15 14 12
34 38 11 15 12
40 36 11 7 22
29 32 14 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'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 12 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226747&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226747&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226747&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'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 27.1311 -0.0425189Connected[t] + 0.00149012Separate[t] -0.118342Learning[t] -0.772194Happiness[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Depression[t] =  +  27.1311 -0.0425189Connected[t] +  0.00149012Separate[t] -0.118342Learning[t] -0.772194Happiness[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226747&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Depression[t] =  +  27.1311 -0.0425189Connected[t] +  0.00149012Separate[t] -0.118342Learning[t] -0.772194Happiness[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226747&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226747&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Depression[t] = + 27.1311 -0.0425189Connected[t] + 0.00149012Separate[t] -0.118342Learning[t] -0.772194Happiness[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)27.13112.0178413.451.28275e-316.41374e-32
Connected-0.04251890.0518851-0.81950.4132650.206633
Separate0.001490120.05333470.027940.9777320.488866
Learning-0.1183420.0749698-1.5790.1156630.0578317
Happiness-0.7721940.0721289-10.712.19497e-221.09749e-22

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 27.1311 & 2.01784 & 13.45 & 1.28275e-31 & 6.41374e-32 \tabularnewline
Connected & -0.0425189 & 0.0518851 & -0.8195 & 0.413265 & 0.206633 \tabularnewline
Separate & 0.00149012 & 0.0533347 & 0.02794 & 0.977732 & 0.488866 \tabularnewline
Learning & -0.118342 & 0.0749698 & -1.579 & 0.115663 & 0.0578317 \tabularnewline
Happiness & -0.772194 & 0.0721289 & -10.71 & 2.19497e-22 & 1.09749e-22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226747&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]27.1311[/C][C]2.01784[/C][C]13.45[/C][C]1.28275e-31[/C][C]6.41374e-32[/C][/ROW]
[ROW][C]Connected[/C][C]-0.0425189[/C][C]0.0518851[/C][C]-0.8195[/C][C]0.413265[/C][C]0.206633[/C][/ROW]
[ROW][C]Separate[/C][C]0.00149012[/C][C]0.0533347[/C][C]0.02794[/C][C]0.977732[/C][C]0.488866[/C][/ROW]
[ROW][C]Learning[/C][C]-0.118342[/C][C]0.0749698[/C][C]-1.579[/C][C]0.115663[/C][C]0.0578317[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.772194[/C][C]0.0721289[/C][C]-10.71[/C][C]2.19497e-22[/C][C]1.09749e-22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226747&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226747&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)27.13112.0178413.451.28275e-316.41374e-32
Connected-0.04251890.0518851-0.81950.4132650.206633
Separate0.001490120.05333470.027940.9777320.488866
Learning-0.1183420.0749698-1.5790.1156630.0578317
Happiness-0.7721940.0721289-10.712.19497e-221.09749e-22






Multiple Linear Regression - Regression Statistics
Multiple R0.591358
R-squared0.349705
Adjusted R-squared0.339662
F-TEST (value)34.8202
F-TEST (DF numerator)4
F-TEST (DF denominator)259
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.81941
Sum Squared Residuals2058.8

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.591358 \tabularnewline
R-squared & 0.349705 \tabularnewline
Adjusted R-squared & 0.339662 \tabularnewline
F-TEST (value) & 34.8202 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 259 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.81941 \tabularnewline
Sum Squared Residuals & 2058.8 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226747&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.591358[/C][/ROW]
[ROW][C]R-squared[/C][C]0.349705[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.339662[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]34.8202[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]259[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.81941[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2058.8[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226747&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226747&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 R0.591358
R-squared0.349705
Adjusted R-squared0.339662
F-TEST (value)34.8202
F-TEST (DF numerator)4
F-TEST (DF denominator)259
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.81941
Sum Squared Residuals2058.8






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.0953-1.09531
2119.72761.2724
31415.1651-1.16507
41214.8207-2.82075
52111.72879.27128
61210.24821.75177
72212.45999.54014
81113.1533-2.15327
91012.4129-2.41289
101312.25650.743497
111010.5408-0.540823
1289.08594-1.08594
131515.9521-0.952142
141411.28092.71907
15109.871820.128178
161413.23380.766159
171413.06230.937724
181110.07790.922116
191012.5886-2.58863
201311.56961.43038
219.510.0267-0.526723
221415.4716-1.47162
231212.4703-0.47029
241414.4562-0.456233
251110.38150.618548
26916.474-7.47397
271111.404-0.404015
281513.19731.80272
291412.30081.69921
301315.5837-2.58373
31911.729-2.72899
321514.57220.427833
331010.82-0.820027
341112.2642-1.26423
351313.2627-0.262676
36812.2812-4.28117
372017.81112.1889
381212.4099-0.409914
391010.9235-0.923493
401013.7601-3.76014
41912.1292-3.12922
421411.72282.27724
43810.8411-2.84114
441414.769-0.769015
451112.3174-1.31743
461315.8142-2.81418
47912.3338-3.33382
481112.4206-1.42062
491510.63634.36371
501113.8678-2.86777
511011.5786-1.57856
521413.34770.652287
531815.90552.09455
541414.5823-0.5823
551115.4868-4.48679
5614.512.37042.12962
571311.2751.72503
58912.4724-3.47235
591014.5701-4.57011
601514.53380.46618
612018.29961.70038
621213.6341-1.63407
631215.35-3.35002
641413.39770.602317
651312.25530.744713
661115.9643-4.96434
671715.02831.9717
681214.4993-2.4993
691312.52950.470527
701412.22171.77829
711313.5749-0.57491
721511.85783.14223
731312.03050.969477
741011.8634-1.86343
751113.7937-2.79371
761914.23944.76056
771310.59232.40772
781713.79973.20033
791312.86540.134572
80913.6662-4.66616
811112.3053-1.30526
82912.2217-3.22171
831211.47690.523141
841212.4631-0.463137
851313.07-0.0699998
861312.33380.666183
871213.0745-1.07447
881514.01380.98624
892218.59673.40332
901311.31931.68072
911513.59781.40222
921312.22770.772331
931513.22641.77361
9412.514.3658-1.86581
951111.2779-0.277949
961614.45031.54973
971112.985-1.98496
981110.58780.412188
991012.5845-2.58446
1001010.5483-0.548274
1011614.45031.54973
1021210.93361.06637
1031115.543-4.54297
1041612.30973.69027
1051916.98992.01014
1061111.2006-0.200635
1071611.96964.03042
1081516.0372-1.03718
1092416.22337.77665
1101412.42981.57017
1111515.4746-0.4746
1121113.7813-2.78127
1131513.47051.52947
1141210.2891.71101
1151011.1203-1.12034
1161413.32010.679904
1171313.2776-0.277577
118913.431-4.43099
1191512.86492.13514
1201514.97840.0216441
1211413.14910.850923
1221112.4522-1.45216
123812.1382-4.13816
1241112.2886-1.28859
1251113.9302-2.93021
126810.6181-2.61814
1271010.1793-0.179288
128119.334821.66518
1291312.68910.310882
1301113.8877-2.88769
1312017.85512.14489
1321012.0091-2.00911
1331513.02481.9752
1341212.3748-0.374846
1351411.68352.31651
1362315.94087.05921
1371413.15180.848216
1381616.1118-0.111811
1391112.6906-1.69061
1401214.5249-2.5249
1411012.3448-2.3448
1421411.78052.21955
1431213.0852-1.08517
1441212.3709-0.370923
1451111.938-0.938034
1461211.32550.674515
1471315.6215-2.6215
1481114.6569-3.65691
1491917.20241.79755
1501212.035-0.0349927
1511713.58683.41319
152911.4935-2.49352
1531214.5413-2.54127
1541916.95952.04047
1551814.55223.44775
1561513.59781.40222
1571413.47650.523513
158119.334821.66518
159913.8012-4.80117
1601815.14072.85929
1611614.16221.83785
1622416.76157.23853
1631413.6210.379043
1642011.19778.80235
1651816.24651.75348
1662316.47786.52218
1671213.4372-1.43722
1681415.4948-1.49479
1691617.2539-1.25391
1701817.1950.804976
1712015.68994.31012
1721211.4070.593004
1731217.0701-5.07015
1741714.83172.16827
1751311.8671.13305
176914.009-5.00902
1771617.2372-1.23724
1781815.21382.78618
1791011.8473-1.84733
1801415.6563-1.6563
1811112.9499-1.94989
182914.3474-5.34738
1831112.0353-1.03527
1841012.9772-2.97724
1851112.9356-1.93559
1861913.89225.10784
1871412.82861.17143
1881212.5161-0.516062
1891414.642-0.64203
1902116.02834.97174
1911315.6732-2.67324
1921012.8708-2.87082
1931512.81672.18333
1941615.31050.689515
1951412.69681.30316
1961214.5731-2.57309
1971913.02755.97252
1981513.07891.92106
1991917.94281.05717
2001314.1413-1.14132
2011717.057-0.0570367
2021212.9157-0.915671
2031111.3026-0.302611
2041414.2745-0.274535
2051112.4206-1.42062
2061312.38110.61892
2071212.9939-0.993903
2081511.4483.55198
2091414.3093-0.30933
2101211.60440.395585
2111717.3648-0.364801
2121111.6782-0.678202
2131815.55942.44064
2141316.4062-3.40617
2151715.30751.6925
2161312.73810.261856
2171110.6410.358964
2181213.056-1.05604
2192217.93664.0634
2201412.30051.69949
2211215.6596-3.65955
2221211.55720.442847
2231716.27860.721391
224912.8577-3.8577
2252117.25093.74907
2261012.5223-2.52232
227119.532241.46776
2281214.8555-2.85554
2292318.25534.74466
2301315.8234-2.82339
2311213.381-1.38102
2321617.6515-1.65146
233912.3448-3.3448
2341713.26833.73166
235911.8396-2.83961
2361415.8507-1.85074
2371715.86291.13707
2381314.0637-1.0637
2391116.3289-5.32885
2401215.9251-3.92507
2411015.3444-5.34436
2421918.09750.902543
2431615.53260.467433
2441614.88741.11264
2451412.24611.75393
2462016.0363.96401
2471514.12740.872642
2482313.6549.34601
2492017.21252.78749
2501615.58160.418407
2511412.9791.02097
2521714.55372.44626
2531114.1925-3.19248
2541313.8437-0.843684
2551714.92072.07934
2561514.81150.188466
2572116.85494.14513
2581817.25420.745817
2591512.48722.51277
260817.4924-9.49236
2611213.442-1.44197
2621212.8574-0.85743
2632218.77693.22311
2641213.4783-1.47825

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 13.0953 & -1.09531 \tabularnewline
2 & 11 & 9.7276 & 1.2724 \tabularnewline
3 & 14 & 15.1651 & -1.16507 \tabularnewline
4 & 12 & 14.8207 & -2.82075 \tabularnewline
5 & 21 & 11.7287 & 9.27128 \tabularnewline
6 & 12 & 10.2482 & 1.75177 \tabularnewline
7 & 22 & 12.4599 & 9.54014 \tabularnewline
8 & 11 & 13.1533 & -2.15327 \tabularnewline
9 & 10 & 12.4129 & -2.41289 \tabularnewline
10 & 13 & 12.2565 & 0.743497 \tabularnewline
11 & 10 & 10.5408 & -0.540823 \tabularnewline
12 & 8 & 9.08594 & -1.08594 \tabularnewline
13 & 15 & 15.9521 & -0.952142 \tabularnewline
14 & 14 & 11.2809 & 2.71907 \tabularnewline
15 & 10 & 9.87182 & 0.128178 \tabularnewline
16 & 14 & 13.2338 & 0.766159 \tabularnewline
17 & 14 & 13.0623 & 0.937724 \tabularnewline
18 & 11 & 10.0779 & 0.922116 \tabularnewline
19 & 10 & 12.5886 & -2.58863 \tabularnewline
20 & 13 & 11.5696 & 1.43038 \tabularnewline
21 & 9.5 & 10.0267 & -0.526723 \tabularnewline
22 & 14 & 15.4716 & -1.47162 \tabularnewline
23 & 12 & 12.4703 & -0.47029 \tabularnewline
24 & 14 & 14.4562 & -0.456233 \tabularnewline
25 & 11 & 10.3815 & 0.618548 \tabularnewline
26 & 9 & 16.474 & -7.47397 \tabularnewline
27 & 11 & 11.404 & -0.404015 \tabularnewline
28 & 15 & 13.1973 & 1.80272 \tabularnewline
29 & 14 & 12.3008 & 1.69921 \tabularnewline
30 & 13 & 15.5837 & -2.58373 \tabularnewline
31 & 9 & 11.729 & -2.72899 \tabularnewline
32 & 15 & 14.5722 & 0.427833 \tabularnewline
33 & 10 & 10.82 & -0.820027 \tabularnewline
34 & 11 & 12.2642 & -1.26423 \tabularnewline
35 & 13 & 13.2627 & -0.262676 \tabularnewline
36 & 8 & 12.2812 & -4.28117 \tabularnewline
37 & 20 & 17.8111 & 2.1889 \tabularnewline
38 & 12 & 12.4099 & -0.409914 \tabularnewline
39 & 10 & 10.9235 & -0.923493 \tabularnewline
40 & 10 & 13.7601 & -3.76014 \tabularnewline
41 & 9 & 12.1292 & -3.12922 \tabularnewline
42 & 14 & 11.7228 & 2.27724 \tabularnewline
43 & 8 & 10.8411 & -2.84114 \tabularnewline
44 & 14 & 14.769 & -0.769015 \tabularnewline
45 & 11 & 12.3174 & -1.31743 \tabularnewline
46 & 13 & 15.8142 & -2.81418 \tabularnewline
47 & 9 & 12.3338 & -3.33382 \tabularnewline
48 & 11 & 12.4206 & -1.42062 \tabularnewline
49 & 15 & 10.6363 & 4.36371 \tabularnewline
50 & 11 & 13.8678 & -2.86777 \tabularnewline
51 & 10 & 11.5786 & -1.57856 \tabularnewline
52 & 14 & 13.3477 & 0.652287 \tabularnewline
53 & 18 & 15.9055 & 2.09455 \tabularnewline
54 & 14 & 14.5823 & -0.5823 \tabularnewline
55 & 11 & 15.4868 & -4.48679 \tabularnewline
56 & 14.5 & 12.3704 & 2.12962 \tabularnewline
57 & 13 & 11.275 & 1.72503 \tabularnewline
58 & 9 & 12.4724 & -3.47235 \tabularnewline
59 & 10 & 14.5701 & -4.57011 \tabularnewline
60 & 15 & 14.5338 & 0.46618 \tabularnewline
61 & 20 & 18.2996 & 1.70038 \tabularnewline
62 & 12 & 13.6341 & -1.63407 \tabularnewline
63 & 12 & 15.35 & -3.35002 \tabularnewline
64 & 14 & 13.3977 & 0.602317 \tabularnewline
65 & 13 & 12.2553 & 0.744713 \tabularnewline
66 & 11 & 15.9643 & -4.96434 \tabularnewline
67 & 17 & 15.0283 & 1.9717 \tabularnewline
68 & 12 & 14.4993 & -2.4993 \tabularnewline
69 & 13 & 12.5295 & 0.470527 \tabularnewline
70 & 14 & 12.2217 & 1.77829 \tabularnewline
71 & 13 & 13.5749 & -0.57491 \tabularnewline
72 & 15 & 11.8578 & 3.14223 \tabularnewline
73 & 13 & 12.0305 & 0.969477 \tabularnewline
74 & 10 & 11.8634 & -1.86343 \tabularnewline
75 & 11 & 13.7937 & -2.79371 \tabularnewline
76 & 19 & 14.2394 & 4.76056 \tabularnewline
77 & 13 & 10.5923 & 2.40772 \tabularnewline
78 & 17 & 13.7997 & 3.20033 \tabularnewline
79 & 13 & 12.8654 & 0.134572 \tabularnewline
80 & 9 & 13.6662 & -4.66616 \tabularnewline
81 & 11 & 12.3053 & -1.30526 \tabularnewline
82 & 9 & 12.2217 & -3.22171 \tabularnewline
83 & 12 & 11.4769 & 0.523141 \tabularnewline
84 & 12 & 12.4631 & -0.463137 \tabularnewline
85 & 13 & 13.07 & -0.0699998 \tabularnewline
86 & 13 & 12.3338 & 0.666183 \tabularnewline
87 & 12 & 13.0745 & -1.07447 \tabularnewline
88 & 15 & 14.0138 & 0.98624 \tabularnewline
89 & 22 & 18.5967 & 3.40332 \tabularnewline
90 & 13 & 11.3193 & 1.68072 \tabularnewline
91 & 15 & 13.5978 & 1.40222 \tabularnewline
92 & 13 & 12.2277 & 0.772331 \tabularnewline
93 & 15 & 13.2264 & 1.77361 \tabularnewline
94 & 12.5 & 14.3658 & -1.86581 \tabularnewline
95 & 11 & 11.2779 & -0.277949 \tabularnewline
96 & 16 & 14.4503 & 1.54973 \tabularnewline
97 & 11 & 12.985 & -1.98496 \tabularnewline
98 & 11 & 10.5878 & 0.412188 \tabularnewline
99 & 10 & 12.5845 & -2.58446 \tabularnewline
100 & 10 & 10.5483 & -0.548274 \tabularnewline
101 & 16 & 14.4503 & 1.54973 \tabularnewline
102 & 12 & 10.9336 & 1.06637 \tabularnewline
103 & 11 & 15.543 & -4.54297 \tabularnewline
104 & 16 & 12.3097 & 3.69027 \tabularnewline
105 & 19 & 16.9899 & 2.01014 \tabularnewline
106 & 11 & 11.2006 & -0.200635 \tabularnewline
107 & 16 & 11.9696 & 4.03042 \tabularnewline
108 & 15 & 16.0372 & -1.03718 \tabularnewline
109 & 24 & 16.2233 & 7.77665 \tabularnewline
110 & 14 & 12.4298 & 1.57017 \tabularnewline
111 & 15 & 15.4746 & -0.4746 \tabularnewline
112 & 11 & 13.7813 & -2.78127 \tabularnewline
113 & 15 & 13.4705 & 1.52947 \tabularnewline
114 & 12 & 10.289 & 1.71101 \tabularnewline
115 & 10 & 11.1203 & -1.12034 \tabularnewline
116 & 14 & 13.3201 & 0.679904 \tabularnewline
117 & 13 & 13.2776 & -0.277577 \tabularnewline
118 & 9 & 13.431 & -4.43099 \tabularnewline
119 & 15 & 12.8649 & 2.13514 \tabularnewline
120 & 15 & 14.9784 & 0.0216441 \tabularnewline
121 & 14 & 13.1491 & 0.850923 \tabularnewline
122 & 11 & 12.4522 & -1.45216 \tabularnewline
123 & 8 & 12.1382 & -4.13816 \tabularnewline
124 & 11 & 12.2886 & -1.28859 \tabularnewline
125 & 11 & 13.9302 & -2.93021 \tabularnewline
126 & 8 & 10.6181 & -2.61814 \tabularnewline
127 & 10 & 10.1793 & -0.179288 \tabularnewline
128 & 11 & 9.33482 & 1.66518 \tabularnewline
129 & 13 & 12.6891 & 0.310882 \tabularnewline
130 & 11 & 13.8877 & -2.88769 \tabularnewline
131 & 20 & 17.8551 & 2.14489 \tabularnewline
132 & 10 & 12.0091 & -2.00911 \tabularnewline
133 & 15 & 13.0248 & 1.9752 \tabularnewline
134 & 12 & 12.3748 & -0.374846 \tabularnewline
135 & 14 & 11.6835 & 2.31651 \tabularnewline
136 & 23 & 15.9408 & 7.05921 \tabularnewline
137 & 14 & 13.1518 & 0.848216 \tabularnewline
138 & 16 & 16.1118 & -0.111811 \tabularnewline
139 & 11 & 12.6906 & -1.69061 \tabularnewline
140 & 12 & 14.5249 & -2.5249 \tabularnewline
141 & 10 & 12.3448 & -2.3448 \tabularnewline
142 & 14 & 11.7805 & 2.21955 \tabularnewline
143 & 12 & 13.0852 & -1.08517 \tabularnewline
144 & 12 & 12.3709 & -0.370923 \tabularnewline
145 & 11 & 11.938 & -0.938034 \tabularnewline
146 & 12 & 11.3255 & 0.674515 \tabularnewline
147 & 13 & 15.6215 & -2.6215 \tabularnewline
148 & 11 & 14.6569 & -3.65691 \tabularnewline
149 & 19 & 17.2024 & 1.79755 \tabularnewline
150 & 12 & 12.035 & -0.0349927 \tabularnewline
151 & 17 & 13.5868 & 3.41319 \tabularnewline
152 & 9 & 11.4935 & -2.49352 \tabularnewline
153 & 12 & 14.5413 & -2.54127 \tabularnewline
154 & 19 & 16.9595 & 2.04047 \tabularnewline
155 & 18 & 14.5522 & 3.44775 \tabularnewline
156 & 15 & 13.5978 & 1.40222 \tabularnewline
157 & 14 & 13.4765 & 0.523513 \tabularnewline
158 & 11 & 9.33482 & 1.66518 \tabularnewline
159 & 9 & 13.8012 & -4.80117 \tabularnewline
160 & 18 & 15.1407 & 2.85929 \tabularnewline
161 & 16 & 14.1622 & 1.83785 \tabularnewline
162 & 24 & 16.7615 & 7.23853 \tabularnewline
163 & 14 & 13.621 & 0.379043 \tabularnewline
164 & 20 & 11.1977 & 8.80235 \tabularnewline
165 & 18 & 16.2465 & 1.75348 \tabularnewline
166 & 23 & 16.4778 & 6.52218 \tabularnewline
167 & 12 & 13.4372 & -1.43722 \tabularnewline
168 & 14 & 15.4948 & -1.49479 \tabularnewline
169 & 16 & 17.2539 & -1.25391 \tabularnewline
170 & 18 & 17.195 & 0.804976 \tabularnewline
171 & 20 & 15.6899 & 4.31012 \tabularnewline
172 & 12 & 11.407 & 0.593004 \tabularnewline
173 & 12 & 17.0701 & -5.07015 \tabularnewline
174 & 17 & 14.8317 & 2.16827 \tabularnewline
175 & 13 & 11.867 & 1.13305 \tabularnewline
176 & 9 & 14.009 & -5.00902 \tabularnewline
177 & 16 & 17.2372 & -1.23724 \tabularnewline
178 & 18 & 15.2138 & 2.78618 \tabularnewline
179 & 10 & 11.8473 & -1.84733 \tabularnewline
180 & 14 & 15.6563 & -1.6563 \tabularnewline
181 & 11 & 12.9499 & -1.94989 \tabularnewline
182 & 9 & 14.3474 & -5.34738 \tabularnewline
183 & 11 & 12.0353 & -1.03527 \tabularnewline
184 & 10 & 12.9772 & -2.97724 \tabularnewline
185 & 11 & 12.9356 & -1.93559 \tabularnewline
186 & 19 & 13.8922 & 5.10784 \tabularnewline
187 & 14 & 12.8286 & 1.17143 \tabularnewline
188 & 12 & 12.5161 & -0.516062 \tabularnewline
189 & 14 & 14.642 & -0.64203 \tabularnewline
190 & 21 & 16.0283 & 4.97174 \tabularnewline
191 & 13 & 15.6732 & -2.67324 \tabularnewline
192 & 10 & 12.8708 & -2.87082 \tabularnewline
193 & 15 & 12.8167 & 2.18333 \tabularnewline
194 & 16 & 15.3105 & 0.689515 \tabularnewline
195 & 14 & 12.6968 & 1.30316 \tabularnewline
196 & 12 & 14.5731 & -2.57309 \tabularnewline
197 & 19 & 13.0275 & 5.97252 \tabularnewline
198 & 15 & 13.0789 & 1.92106 \tabularnewline
199 & 19 & 17.9428 & 1.05717 \tabularnewline
200 & 13 & 14.1413 & -1.14132 \tabularnewline
201 & 17 & 17.057 & -0.0570367 \tabularnewline
202 & 12 & 12.9157 & -0.915671 \tabularnewline
203 & 11 & 11.3026 & -0.302611 \tabularnewline
204 & 14 & 14.2745 & -0.274535 \tabularnewline
205 & 11 & 12.4206 & -1.42062 \tabularnewline
206 & 13 & 12.3811 & 0.61892 \tabularnewline
207 & 12 & 12.9939 & -0.993903 \tabularnewline
208 & 15 & 11.448 & 3.55198 \tabularnewline
209 & 14 & 14.3093 & -0.30933 \tabularnewline
210 & 12 & 11.6044 & 0.395585 \tabularnewline
211 & 17 & 17.3648 & -0.364801 \tabularnewline
212 & 11 & 11.6782 & -0.678202 \tabularnewline
213 & 18 & 15.5594 & 2.44064 \tabularnewline
214 & 13 & 16.4062 & -3.40617 \tabularnewline
215 & 17 & 15.3075 & 1.6925 \tabularnewline
216 & 13 & 12.7381 & 0.261856 \tabularnewline
217 & 11 & 10.641 & 0.358964 \tabularnewline
218 & 12 & 13.056 & -1.05604 \tabularnewline
219 & 22 & 17.9366 & 4.0634 \tabularnewline
220 & 14 & 12.3005 & 1.69949 \tabularnewline
221 & 12 & 15.6596 & -3.65955 \tabularnewline
222 & 12 & 11.5572 & 0.442847 \tabularnewline
223 & 17 & 16.2786 & 0.721391 \tabularnewline
224 & 9 & 12.8577 & -3.8577 \tabularnewline
225 & 21 & 17.2509 & 3.74907 \tabularnewline
226 & 10 & 12.5223 & -2.52232 \tabularnewline
227 & 11 & 9.53224 & 1.46776 \tabularnewline
228 & 12 & 14.8555 & -2.85554 \tabularnewline
229 & 23 & 18.2553 & 4.74466 \tabularnewline
230 & 13 & 15.8234 & -2.82339 \tabularnewline
231 & 12 & 13.381 & -1.38102 \tabularnewline
232 & 16 & 17.6515 & -1.65146 \tabularnewline
233 & 9 & 12.3448 & -3.3448 \tabularnewline
234 & 17 & 13.2683 & 3.73166 \tabularnewline
235 & 9 & 11.8396 & -2.83961 \tabularnewline
236 & 14 & 15.8507 & -1.85074 \tabularnewline
237 & 17 & 15.8629 & 1.13707 \tabularnewline
238 & 13 & 14.0637 & -1.0637 \tabularnewline
239 & 11 & 16.3289 & -5.32885 \tabularnewline
240 & 12 & 15.9251 & -3.92507 \tabularnewline
241 & 10 & 15.3444 & -5.34436 \tabularnewline
242 & 19 & 18.0975 & 0.902543 \tabularnewline
243 & 16 & 15.5326 & 0.467433 \tabularnewline
244 & 16 & 14.8874 & 1.11264 \tabularnewline
245 & 14 & 12.2461 & 1.75393 \tabularnewline
246 & 20 & 16.036 & 3.96401 \tabularnewline
247 & 15 & 14.1274 & 0.872642 \tabularnewline
248 & 23 & 13.654 & 9.34601 \tabularnewline
249 & 20 & 17.2125 & 2.78749 \tabularnewline
250 & 16 & 15.5816 & 0.418407 \tabularnewline
251 & 14 & 12.979 & 1.02097 \tabularnewline
252 & 17 & 14.5537 & 2.44626 \tabularnewline
253 & 11 & 14.1925 & -3.19248 \tabularnewline
254 & 13 & 13.8437 & -0.843684 \tabularnewline
255 & 17 & 14.9207 & 2.07934 \tabularnewline
256 & 15 & 14.8115 & 0.188466 \tabularnewline
257 & 21 & 16.8549 & 4.14513 \tabularnewline
258 & 18 & 17.2542 & 0.745817 \tabularnewline
259 & 15 & 12.4872 & 2.51277 \tabularnewline
260 & 8 & 17.4924 & -9.49236 \tabularnewline
261 & 12 & 13.442 & -1.44197 \tabularnewline
262 & 12 & 12.8574 & -0.85743 \tabularnewline
263 & 22 & 18.7769 & 3.22311 \tabularnewline
264 & 12 & 13.4783 & -1.47825 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226747&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]13.0953[/C][C]-1.09531[/C][/ROW]
[ROW][C]2[/C][C]11[/C][C]9.7276[/C][C]1.2724[/C][/ROW]
[ROW][C]3[/C][C]14[/C][C]15.1651[/C][C]-1.16507[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.8207[/C][C]-2.82075[/C][/ROW]
[ROW][C]5[/C][C]21[/C][C]11.7287[/C][C]9.27128[/C][/ROW]
[ROW][C]6[/C][C]12[/C][C]10.2482[/C][C]1.75177[/C][/ROW]
[ROW][C]7[/C][C]22[/C][C]12.4599[/C][C]9.54014[/C][/ROW]
[ROW][C]8[/C][C]11[/C][C]13.1533[/C][C]-2.15327[/C][/ROW]
[ROW][C]9[/C][C]10[/C][C]12.4129[/C][C]-2.41289[/C][/ROW]
[ROW][C]10[/C][C]13[/C][C]12.2565[/C][C]0.743497[/C][/ROW]
[ROW][C]11[/C][C]10[/C][C]10.5408[/C][C]-0.540823[/C][/ROW]
[ROW][C]12[/C][C]8[/C][C]9.08594[/C][C]-1.08594[/C][/ROW]
[ROW][C]13[/C][C]15[/C][C]15.9521[/C][C]-0.952142[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]11.2809[/C][C]2.71907[/C][/ROW]
[ROW][C]15[/C][C]10[/C][C]9.87182[/C][C]0.128178[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.2338[/C][C]0.766159[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.0623[/C][C]0.937724[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]10.0779[/C][C]0.922116[/C][/ROW]
[ROW][C]19[/C][C]10[/C][C]12.5886[/C][C]-2.58863[/C][/ROW]
[ROW][C]20[/C][C]13[/C][C]11.5696[/C][C]1.43038[/C][/ROW]
[ROW][C]21[/C][C]9.5[/C][C]10.0267[/C][C]-0.526723[/C][/ROW]
[ROW][C]22[/C][C]14[/C][C]15.4716[/C][C]-1.47162[/C][/ROW]
[ROW][C]23[/C][C]12[/C][C]12.4703[/C][C]-0.47029[/C][/ROW]
[ROW][C]24[/C][C]14[/C][C]14.4562[/C][C]-0.456233[/C][/ROW]
[ROW][C]25[/C][C]11[/C][C]10.3815[/C][C]0.618548[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]16.474[/C][C]-7.47397[/C][/ROW]
[ROW][C]27[/C][C]11[/C][C]11.404[/C][C]-0.404015[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]13.1973[/C][C]1.80272[/C][/ROW]
[ROW][C]29[/C][C]14[/C][C]12.3008[/C][C]1.69921[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]15.5837[/C][C]-2.58373[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]11.729[/C][C]-2.72899[/C][/ROW]
[ROW][C]32[/C][C]15[/C][C]14.5722[/C][C]0.427833[/C][/ROW]
[ROW][C]33[/C][C]10[/C][C]10.82[/C][C]-0.820027[/C][/ROW]
[ROW][C]34[/C][C]11[/C][C]12.2642[/C][C]-1.26423[/C][/ROW]
[ROW][C]35[/C][C]13[/C][C]13.2627[/C][C]-0.262676[/C][/ROW]
[ROW][C]36[/C][C]8[/C][C]12.2812[/C][C]-4.28117[/C][/ROW]
[ROW][C]37[/C][C]20[/C][C]17.8111[/C][C]2.1889[/C][/ROW]
[ROW][C]38[/C][C]12[/C][C]12.4099[/C][C]-0.409914[/C][/ROW]
[ROW][C]39[/C][C]10[/C][C]10.9235[/C][C]-0.923493[/C][/ROW]
[ROW][C]40[/C][C]10[/C][C]13.7601[/C][C]-3.76014[/C][/ROW]
[ROW][C]41[/C][C]9[/C][C]12.1292[/C][C]-3.12922[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]11.7228[/C][C]2.27724[/C][/ROW]
[ROW][C]43[/C][C]8[/C][C]10.8411[/C][C]-2.84114[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.769[/C][C]-0.769015[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]12.3174[/C][C]-1.31743[/C][/ROW]
[ROW][C]46[/C][C]13[/C][C]15.8142[/C][C]-2.81418[/C][/ROW]
[ROW][C]47[/C][C]9[/C][C]12.3338[/C][C]-3.33382[/C][/ROW]
[ROW][C]48[/C][C]11[/C][C]12.4206[/C][C]-1.42062[/C][/ROW]
[ROW][C]49[/C][C]15[/C][C]10.6363[/C][C]4.36371[/C][/ROW]
[ROW][C]50[/C][C]11[/C][C]13.8678[/C][C]-2.86777[/C][/ROW]
[ROW][C]51[/C][C]10[/C][C]11.5786[/C][C]-1.57856[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.3477[/C][C]0.652287[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]15.9055[/C][C]2.09455[/C][/ROW]
[ROW][C]54[/C][C]14[/C][C]14.5823[/C][C]-0.5823[/C][/ROW]
[ROW][C]55[/C][C]11[/C][C]15.4868[/C][C]-4.48679[/C][/ROW]
[ROW][C]56[/C][C]14.5[/C][C]12.3704[/C][C]2.12962[/C][/ROW]
[ROW][C]57[/C][C]13[/C][C]11.275[/C][C]1.72503[/C][/ROW]
[ROW][C]58[/C][C]9[/C][C]12.4724[/C][C]-3.47235[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]14.5701[/C][C]-4.57011[/C][/ROW]
[ROW][C]60[/C][C]15[/C][C]14.5338[/C][C]0.46618[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]18.2996[/C][C]1.70038[/C][/ROW]
[ROW][C]62[/C][C]12[/C][C]13.6341[/C][C]-1.63407[/C][/ROW]
[ROW][C]63[/C][C]12[/C][C]15.35[/C][C]-3.35002[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.3977[/C][C]0.602317[/C][/ROW]
[ROW][C]65[/C][C]13[/C][C]12.2553[/C][C]0.744713[/C][/ROW]
[ROW][C]66[/C][C]11[/C][C]15.9643[/C][C]-4.96434[/C][/ROW]
[ROW][C]67[/C][C]17[/C][C]15.0283[/C][C]1.9717[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.4993[/C][C]-2.4993[/C][/ROW]
[ROW][C]69[/C][C]13[/C][C]12.5295[/C][C]0.470527[/C][/ROW]
[ROW][C]70[/C][C]14[/C][C]12.2217[/C][C]1.77829[/C][/ROW]
[ROW][C]71[/C][C]13[/C][C]13.5749[/C][C]-0.57491[/C][/ROW]
[ROW][C]72[/C][C]15[/C][C]11.8578[/C][C]3.14223[/C][/ROW]
[ROW][C]73[/C][C]13[/C][C]12.0305[/C][C]0.969477[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]11.8634[/C][C]-1.86343[/C][/ROW]
[ROW][C]75[/C][C]11[/C][C]13.7937[/C][C]-2.79371[/C][/ROW]
[ROW][C]76[/C][C]19[/C][C]14.2394[/C][C]4.76056[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.5923[/C][C]2.40772[/C][/ROW]
[ROW][C]78[/C][C]17[/C][C]13.7997[/C][C]3.20033[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]12.8654[/C][C]0.134572[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]13.6662[/C][C]-4.66616[/C][/ROW]
[ROW][C]81[/C][C]11[/C][C]12.3053[/C][C]-1.30526[/C][/ROW]
[ROW][C]82[/C][C]9[/C][C]12.2217[/C][C]-3.22171[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]11.4769[/C][C]0.523141[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]12.4631[/C][C]-0.463137[/C][/ROW]
[ROW][C]85[/C][C]13[/C][C]13.07[/C][C]-0.0699998[/C][/ROW]
[ROW][C]86[/C][C]13[/C][C]12.3338[/C][C]0.666183[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]13.0745[/C][C]-1.07447[/C][/ROW]
[ROW][C]88[/C][C]15[/C][C]14.0138[/C][C]0.98624[/C][/ROW]
[ROW][C]89[/C][C]22[/C][C]18.5967[/C][C]3.40332[/C][/ROW]
[ROW][C]90[/C][C]13[/C][C]11.3193[/C][C]1.68072[/C][/ROW]
[ROW][C]91[/C][C]15[/C][C]13.5978[/C][C]1.40222[/C][/ROW]
[ROW][C]92[/C][C]13[/C][C]12.2277[/C][C]0.772331[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]13.2264[/C][C]1.77361[/C][/ROW]
[ROW][C]94[/C][C]12.5[/C][C]14.3658[/C][C]-1.86581[/C][/ROW]
[ROW][C]95[/C][C]11[/C][C]11.2779[/C][C]-0.277949[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]14.4503[/C][C]1.54973[/C][/ROW]
[ROW][C]97[/C][C]11[/C][C]12.985[/C][C]-1.98496[/C][/ROW]
[ROW][C]98[/C][C]11[/C][C]10.5878[/C][C]0.412188[/C][/ROW]
[ROW][C]99[/C][C]10[/C][C]12.5845[/C][C]-2.58446[/C][/ROW]
[ROW][C]100[/C][C]10[/C][C]10.5483[/C][C]-0.548274[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.4503[/C][C]1.54973[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]10.9336[/C][C]1.06637[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]15.543[/C][C]-4.54297[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]12.3097[/C][C]3.69027[/C][/ROW]
[ROW][C]105[/C][C]19[/C][C]16.9899[/C][C]2.01014[/C][/ROW]
[ROW][C]106[/C][C]11[/C][C]11.2006[/C][C]-0.200635[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]11.9696[/C][C]4.03042[/C][/ROW]
[ROW][C]108[/C][C]15[/C][C]16.0372[/C][C]-1.03718[/C][/ROW]
[ROW][C]109[/C][C]24[/C][C]16.2233[/C][C]7.77665[/C][/ROW]
[ROW][C]110[/C][C]14[/C][C]12.4298[/C][C]1.57017[/C][/ROW]
[ROW][C]111[/C][C]15[/C][C]15.4746[/C][C]-0.4746[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]13.7813[/C][C]-2.78127[/C][/ROW]
[ROW][C]113[/C][C]15[/C][C]13.4705[/C][C]1.52947[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]10.289[/C][C]1.71101[/C][/ROW]
[ROW][C]115[/C][C]10[/C][C]11.1203[/C][C]-1.12034[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.3201[/C][C]0.679904[/C][/ROW]
[ROW][C]117[/C][C]13[/C][C]13.2776[/C][C]-0.277577[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]13.431[/C][C]-4.43099[/C][/ROW]
[ROW][C]119[/C][C]15[/C][C]12.8649[/C][C]2.13514[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]14.9784[/C][C]0.0216441[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.1491[/C][C]0.850923[/C][/ROW]
[ROW][C]122[/C][C]11[/C][C]12.4522[/C][C]-1.45216[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]12.1382[/C][C]-4.13816[/C][/ROW]
[ROW][C]124[/C][C]11[/C][C]12.2886[/C][C]-1.28859[/C][/ROW]
[ROW][C]125[/C][C]11[/C][C]13.9302[/C][C]-2.93021[/C][/ROW]
[ROW][C]126[/C][C]8[/C][C]10.6181[/C][C]-2.61814[/C][/ROW]
[ROW][C]127[/C][C]10[/C][C]10.1793[/C][C]-0.179288[/C][/ROW]
[ROW][C]128[/C][C]11[/C][C]9.33482[/C][C]1.66518[/C][/ROW]
[ROW][C]129[/C][C]13[/C][C]12.6891[/C][C]0.310882[/C][/ROW]
[ROW][C]130[/C][C]11[/C][C]13.8877[/C][C]-2.88769[/C][/ROW]
[ROW][C]131[/C][C]20[/C][C]17.8551[/C][C]2.14489[/C][/ROW]
[ROW][C]132[/C][C]10[/C][C]12.0091[/C][C]-2.00911[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]13.0248[/C][C]1.9752[/C][/ROW]
[ROW][C]134[/C][C]12[/C][C]12.3748[/C][C]-0.374846[/C][/ROW]
[ROW][C]135[/C][C]14[/C][C]11.6835[/C][C]2.31651[/C][/ROW]
[ROW][C]136[/C][C]23[/C][C]15.9408[/C][C]7.05921[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.1518[/C][C]0.848216[/C][/ROW]
[ROW][C]138[/C][C]16[/C][C]16.1118[/C][C]-0.111811[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]12.6906[/C][C]-1.69061[/C][/ROW]
[ROW][C]140[/C][C]12[/C][C]14.5249[/C][C]-2.5249[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]12.3448[/C][C]-2.3448[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]11.7805[/C][C]2.21955[/C][/ROW]
[ROW][C]143[/C][C]12[/C][C]13.0852[/C][C]-1.08517[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]12.3709[/C][C]-0.370923[/C][/ROW]
[ROW][C]145[/C][C]11[/C][C]11.938[/C][C]-0.938034[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]11.3255[/C][C]0.674515[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.6215[/C][C]-2.6215[/C][/ROW]
[ROW][C]148[/C][C]11[/C][C]14.6569[/C][C]-3.65691[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]17.2024[/C][C]1.79755[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]12.035[/C][C]-0.0349927[/C][/ROW]
[ROW][C]151[/C][C]17[/C][C]13.5868[/C][C]3.41319[/C][/ROW]
[ROW][C]152[/C][C]9[/C][C]11.4935[/C][C]-2.49352[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.5413[/C][C]-2.54127[/C][/ROW]
[ROW][C]154[/C][C]19[/C][C]16.9595[/C][C]2.04047[/C][/ROW]
[ROW][C]155[/C][C]18[/C][C]14.5522[/C][C]3.44775[/C][/ROW]
[ROW][C]156[/C][C]15[/C][C]13.5978[/C][C]1.40222[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.4765[/C][C]0.523513[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]9.33482[/C][C]1.66518[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]13.8012[/C][C]-4.80117[/C][/ROW]
[ROW][C]160[/C][C]18[/C][C]15.1407[/C][C]2.85929[/C][/ROW]
[ROW][C]161[/C][C]16[/C][C]14.1622[/C][C]1.83785[/C][/ROW]
[ROW][C]162[/C][C]24[/C][C]16.7615[/C][C]7.23853[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.621[/C][C]0.379043[/C][/ROW]
[ROW][C]164[/C][C]20[/C][C]11.1977[/C][C]8.80235[/C][/ROW]
[ROW][C]165[/C][C]18[/C][C]16.2465[/C][C]1.75348[/C][/ROW]
[ROW][C]166[/C][C]23[/C][C]16.4778[/C][C]6.52218[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]13.4372[/C][C]-1.43722[/C][/ROW]
[ROW][C]168[/C][C]14[/C][C]15.4948[/C][C]-1.49479[/C][/ROW]
[ROW][C]169[/C][C]16[/C][C]17.2539[/C][C]-1.25391[/C][/ROW]
[ROW][C]170[/C][C]18[/C][C]17.195[/C][C]0.804976[/C][/ROW]
[ROW][C]171[/C][C]20[/C][C]15.6899[/C][C]4.31012[/C][/ROW]
[ROW][C]172[/C][C]12[/C][C]11.407[/C][C]0.593004[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]17.0701[/C][C]-5.07015[/C][/ROW]
[ROW][C]174[/C][C]17[/C][C]14.8317[/C][C]2.16827[/C][/ROW]
[ROW][C]175[/C][C]13[/C][C]11.867[/C][C]1.13305[/C][/ROW]
[ROW][C]176[/C][C]9[/C][C]14.009[/C][C]-5.00902[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]17.2372[/C][C]-1.23724[/C][/ROW]
[ROW][C]178[/C][C]18[/C][C]15.2138[/C][C]2.78618[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]11.8473[/C][C]-1.84733[/C][/ROW]
[ROW][C]180[/C][C]14[/C][C]15.6563[/C][C]-1.6563[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]12.9499[/C][C]-1.94989[/C][/ROW]
[ROW][C]182[/C][C]9[/C][C]14.3474[/C][C]-5.34738[/C][/ROW]
[ROW][C]183[/C][C]11[/C][C]12.0353[/C][C]-1.03527[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]12.9772[/C][C]-2.97724[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]12.9356[/C][C]-1.93559[/C][/ROW]
[ROW][C]186[/C][C]19[/C][C]13.8922[/C][C]5.10784[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]12.8286[/C][C]1.17143[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.5161[/C][C]-0.516062[/C][/ROW]
[ROW][C]189[/C][C]14[/C][C]14.642[/C][C]-0.64203[/C][/ROW]
[ROW][C]190[/C][C]21[/C][C]16.0283[/C][C]4.97174[/C][/ROW]
[ROW][C]191[/C][C]13[/C][C]15.6732[/C][C]-2.67324[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]12.8708[/C][C]-2.87082[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.8167[/C][C]2.18333[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]15.3105[/C][C]0.689515[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]12.6968[/C][C]1.30316[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.5731[/C][C]-2.57309[/C][/ROW]
[ROW][C]197[/C][C]19[/C][C]13.0275[/C][C]5.97252[/C][/ROW]
[ROW][C]198[/C][C]15[/C][C]13.0789[/C][C]1.92106[/C][/ROW]
[ROW][C]199[/C][C]19[/C][C]17.9428[/C][C]1.05717[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]14.1413[/C][C]-1.14132[/C][/ROW]
[ROW][C]201[/C][C]17[/C][C]17.057[/C][C]-0.0570367[/C][/ROW]
[ROW][C]202[/C][C]12[/C][C]12.9157[/C][C]-0.915671[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]11.3026[/C][C]-0.302611[/C][/ROW]
[ROW][C]204[/C][C]14[/C][C]14.2745[/C][C]-0.274535[/C][/ROW]
[ROW][C]205[/C][C]11[/C][C]12.4206[/C][C]-1.42062[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]12.3811[/C][C]0.61892[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]12.9939[/C][C]-0.993903[/C][/ROW]
[ROW][C]208[/C][C]15[/C][C]11.448[/C][C]3.55198[/C][/ROW]
[ROW][C]209[/C][C]14[/C][C]14.3093[/C][C]-0.30933[/C][/ROW]
[ROW][C]210[/C][C]12[/C][C]11.6044[/C][C]0.395585[/C][/ROW]
[ROW][C]211[/C][C]17[/C][C]17.3648[/C][C]-0.364801[/C][/ROW]
[ROW][C]212[/C][C]11[/C][C]11.6782[/C][C]-0.678202[/C][/ROW]
[ROW][C]213[/C][C]18[/C][C]15.5594[/C][C]2.44064[/C][/ROW]
[ROW][C]214[/C][C]13[/C][C]16.4062[/C][C]-3.40617[/C][/ROW]
[ROW][C]215[/C][C]17[/C][C]15.3075[/C][C]1.6925[/C][/ROW]
[ROW][C]216[/C][C]13[/C][C]12.7381[/C][C]0.261856[/C][/ROW]
[ROW][C]217[/C][C]11[/C][C]10.641[/C][C]0.358964[/C][/ROW]
[ROW][C]218[/C][C]12[/C][C]13.056[/C][C]-1.05604[/C][/ROW]
[ROW][C]219[/C][C]22[/C][C]17.9366[/C][C]4.0634[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]12.3005[/C][C]1.69949[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]15.6596[/C][C]-3.65955[/C][/ROW]
[ROW][C]222[/C][C]12[/C][C]11.5572[/C][C]0.442847[/C][/ROW]
[ROW][C]223[/C][C]17[/C][C]16.2786[/C][C]0.721391[/C][/ROW]
[ROW][C]224[/C][C]9[/C][C]12.8577[/C][C]-3.8577[/C][/ROW]
[ROW][C]225[/C][C]21[/C][C]17.2509[/C][C]3.74907[/C][/ROW]
[ROW][C]226[/C][C]10[/C][C]12.5223[/C][C]-2.52232[/C][/ROW]
[ROW][C]227[/C][C]11[/C][C]9.53224[/C][C]1.46776[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]14.8555[/C][C]-2.85554[/C][/ROW]
[ROW][C]229[/C][C]23[/C][C]18.2553[/C][C]4.74466[/C][/ROW]
[ROW][C]230[/C][C]13[/C][C]15.8234[/C][C]-2.82339[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]13.381[/C][C]-1.38102[/C][/ROW]
[ROW][C]232[/C][C]16[/C][C]17.6515[/C][C]-1.65146[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]12.3448[/C][C]-3.3448[/C][/ROW]
[ROW][C]234[/C][C]17[/C][C]13.2683[/C][C]3.73166[/C][/ROW]
[ROW][C]235[/C][C]9[/C][C]11.8396[/C][C]-2.83961[/C][/ROW]
[ROW][C]236[/C][C]14[/C][C]15.8507[/C][C]-1.85074[/C][/ROW]
[ROW][C]237[/C][C]17[/C][C]15.8629[/C][C]1.13707[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.0637[/C][C]-1.0637[/C][/ROW]
[ROW][C]239[/C][C]11[/C][C]16.3289[/C][C]-5.32885[/C][/ROW]
[ROW][C]240[/C][C]12[/C][C]15.9251[/C][C]-3.92507[/C][/ROW]
[ROW][C]241[/C][C]10[/C][C]15.3444[/C][C]-5.34436[/C][/ROW]
[ROW][C]242[/C][C]19[/C][C]18.0975[/C][C]0.902543[/C][/ROW]
[ROW][C]243[/C][C]16[/C][C]15.5326[/C][C]0.467433[/C][/ROW]
[ROW][C]244[/C][C]16[/C][C]14.8874[/C][C]1.11264[/C][/ROW]
[ROW][C]245[/C][C]14[/C][C]12.2461[/C][C]1.75393[/C][/ROW]
[ROW][C]246[/C][C]20[/C][C]16.036[/C][C]3.96401[/C][/ROW]
[ROW][C]247[/C][C]15[/C][C]14.1274[/C][C]0.872642[/C][/ROW]
[ROW][C]248[/C][C]23[/C][C]13.654[/C][C]9.34601[/C][/ROW]
[ROW][C]249[/C][C]20[/C][C]17.2125[/C][C]2.78749[/C][/ROW]
[ROW][C]250[/C][C]16[/C][C]15.5816[/C][C]0.418407[/C][/ROW]
[ROW][C]251[/C][C]14[/C][C]12.979[/C][C]1.02097[/C][/ROW]
[ROW][C]252[/C][C]17[/C][C]14.5537[/C][C]2.44626[/C][/ROW]
[ROW][C]253[/C][C]11[/C][C]14.1925[/C][C]-3.19248[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.8437[/C][C]-0.843684[/C][/ROW]
[ROW][C]255[/C][C]17[/C][C]14.9207[/C][C]2.07934[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]14.8115[/C][C]0.188466[/C][/ROW]
[ROW][C]257[/C][C]21[/C][C]16.8549[/C][C]4.14513[/C][/ROW]
[ROW][C]258[/C][C]18[/C][C]17.2542[/C][C]0.745817[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.4872[/C][C]2.51277[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]17.4924[/C][C]-9.49236[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]13.442[/C][C]-1.44197[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]12.8574[/C][C]-0.85743[/C][/ROW]
[ROW][C]263[/C][C]22[/C][C]18.7769[/C][C]3.22311[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]13.4783[/C][C]-1.47825[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226747&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226747&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11213.0953-1.09531
2119.72761.2724
31415.1651-1.16507
41214.8207-2.82075
52111.72879.27128
61210.24821.75177
72212.45999.54014
81113.1533-2.15327
91012.4129-2.41289
101312.25650.743497
111010.5408-0.540823
1289.08594-1.08594
131515.9521-0.952142
141411.28092.71907
15109.871820.128178
161413.23380.766159
171413.06230.937724
181110.07790.922116
191012.5886-2.58863
201311.56961.43038
219.510.0267-0.526723
221415.4716-1.47162
231212.4703-0.47029
241414.4562-0.456233
251110.38150.618548
26916.474-7.47397
271111.404-0.404015
281513.19731.80272
291412.30081.69921
301315.5837-2.58373
31911.729-2.72899
321514.57220.427833
331010.82-0.820027
341112.2642-1.26423
351313.2627-0.262676
36812.2812-4.28117
372017.81112.1889
381212.4099-0.409914
391010.9235-0.923493
401013.7601-3.76014
41912.1292-3.12922
421411.72282.27724
43810.8411-2.84114
441414.769-0.769015
451112.3174-1.31743
461315.8142-2.81418
47912.3338-3.33382
481112.4206-1.42062
491510.63634.36371
501113.8678-2.86777
511011.5786-1.57856
521413.34770.652287
531815.90552.09455
541414.5823-0.5823
551115.4868-4.48679
5614.512.37042.12962
571311.2751.72503
58912.4724-3.47235
591014.5701-4.57011
601514.53380.46618
612018.29961.70038
621213.6341-1.63407
631215.35-3.35002
641413.39770.602317
651312.25530.744713
661115.9643-4.96434
671715.02831.9717
681214.4993-2.4993
691312.52950.470527
701412.22171.77829
711313.5749-0.57491
721511.85783.14223
731312.03050.969477
741011.8634-1.86343
751113.7937-2.79371
761914.23944.76056
771310.59232.40772
781713.79973.20033
791312.86540.134572
80913.6662-4.66616
811112.3053-1.30526
82912.2217-3.22171
831211.47690.523141
841212.4631-0.463137
851313.07-0.0699998
861312.33380.666183
871213.0745-1.07447
881514.01380.98624
892218.59673.40332
901311.31931.68072
911513.59781.40222
921312.22770.772331
931513.22641.77361
9412.514.3658-1.86581
951111.2779-0.277949
961614.45031.54973
971112.985-1.98496
981110.58780.412188
991012.5845-2.58446
1001010.5483-0.548274
1011614.45031.54973
1021210.93361.06637
1031115.543-4.54297
1041612.30973.69027
1051916.98992.01014
1061111.2006-0.200635
1071611.96964.03042
1081516.0372-1.03718
1092416.22337.77665
1101412.42981.57017
1111515.4746-0.4746
1121113.7813-2.78127
1131513.47051.52947
1141210.2891.71101
1151011.1203-1.12034
1161413.32010.679904
1171313.2776-0.277577
118913.431-4.43099
1191512.86492.13514
1201514.97840.0216441
1211413.14910.850923
1221112.4522-1.45216
123812.1382-4.13816
1241112.2886-1.28859
1251113.9302-2.93021
126810.6181-2.61814
1271010.1793-0.179288
128119.334821.66518
1291312.68910.310882
1301113.8877-2.88769
1312017.85512.14489
1321012.0091-2.00911
1331513.02481.9752
1341212.3748-0.374846
1351411.68352.31651
1362315.94087.05921
1371413.15180.848216
1381616.1118-0.111811
1391112.6906-1.69061
1401214.5249-2.5249
1411012.3448-2.3448
1421411.78052.21955
1431213.0852-1.08517
1441212.3709-0.370923
1451111.938-0.938034
1461211.32550.674515
1471315.6215-2.6215
1481114.6569-3.65691
1491917.20241.79755
1501212.035-0.0349927
1511713.58683.41319
152911.4935-2.49352
1531214.5413-2.54127
1541916.95952.04047
1551814.55223.44775
1561513.59781.40222
1571413.47650.523513
158119.334821.66518
159913.8012-4.80117
1601815.14072.85929
1611614.16221.83785
1622416.76157.23853
1631413.6210.379043
1642011.19778.80235
1651816.24651.75348
1662316.47786.52218
1671213.4372-1.43722
1681415.4948-1.49479
1691617.2539-1.25391
1701817.1950.804976
1712015.68994.31012
1721211.4070.593004
1731217.0701-5.07015
1741714.83172.16827
1751311.8671.13305
176914.009-5.00902
1771617.2372-1.23724
1781815.21382.78618
1791011.8473-1.84733
1801415.6563-1.6563
1811112.9499-1.94989
182914.3474-5.34738
1831112.0353-1.03527
1841012.9772-2.97724
1851112.9356-1.93559
1861913.89225.10784
1871412.82861.17143
1881212.5161-0.516062
1891414.642-0.64203
1902116.02834.97174
1911315.6732-2.67324
1921012.8708-2.87082
1931512.81672.18333
1941615.31050.689515
1951412.69681.30316
1961214.5731-2.57309
1971913.02755.97252
1981513.07891.92106
1991917.94281.05717
2001314.1413-1.14132
2011717.057-0.0570367
2021212.9157-0.915671
2031111.3026-0.302611
2041414.2745-0.274535
2051112.4206-1.42062
2061312.38110.61892
2071212.9939-0.993903
2081511.4483.55198
2091414.3093-0.30933
2101211.60440.395585
2111717.3648-0.364801
2121111.6782-0.678202
2131815.55942.44064
2141316.4062-3.40617
2151715.30751.6925
2161312.73810.261856
2171110.6410.358964
2181213.056-1.05604
2192217.93664.0634
2201412.30051.69949
2211215.6596-3.65955
2221211.55720.442847
2231716.27860.721391
224912.8577-3.8577
2252117.25093.74907
2261012.5223-2.52232
227119.532241.46776
2281214.8555-2.85554
2292318.25534.74466
2301315.8234-2.82339
2311213.381-1.38102
2321617.6515-1.65146
233912.3448-3.3448
2341713.26833.73166
235911.8396-2.83961
2361415.8507-1.85074
2371715.86291.13707
2381314.0637-1.0637
2391116.3289-5.32885
2401215.9251-3.92507
2411015.3444-5.34436
2421918.09750.902543
2431615.53260.467433
2441614.88741.11264
2451412.24611.75393
2462016.0363.96401
2471514.12740.872642
2482313.6549.34601
2492017.21252.78749
2501615.58160.418407
2511412.9791.02097
2521714.55372.44626
2531114.1925-3.19248
2541313.8437-0.843684
2551714.92072.07934
2561514.81150.188466
2572116.85494.14513
2581817.25420.745817
2591512.48722.51277
260817.4924-9.49236
2611213.442-1.44197
2621212.8574-0.85743
2632218.77693.22311
2641213.4783-1.47825






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.9978470.004305770.00215289
90.9967940.006411330.00320566
100.9937690.01246130.00623064
110.9950440.009911420.00495571
120.9970530.005893240.00294662
130.9945490.0109020.00545098
140.9904180.0191650.00958249
150.9857440.0285110.0142555
160.9784650.0430710.0215355
170.966480.06704070.0335204
180.9583810.08323850.0416192
190.9627540.07449240.0372462
200.9465940.1068120.053406
210.9300930.1398150.0699075
220.9080080.1839830.0919917
230.8827960.2344080.117204
240.8475280.3049450.152472
250.8159470.3681060.184053
260.9259490.1481030.0740515
270.9053310.1893370.0946687
280.8891180.2217640.110882
290.8644790.2710430.135521
300.8369860.3260290.163014
310.8459130.3081740.154087
320.8166190.3667620.183381
330.7858980.4282040.214102
340.7573850.4852310.242615
350.7131720.5736570.286828
360.745120.509760.25488
370.8065550.3868910.193445
380.7689340.4621330.231066
390.7425220.5149560.257478
400.7539560.4920870.246044
410.7537910.4924170.246209
420.736570.526860.26343
430.7331030.5337940.266897
440.6923450.615310.307655
450.6507160.6985680.349284
460.6227610.7544780.377239
470.6349740.7300510.365026
480.5999270.8001460.400073
490.6369170.7261670.363083
500.6112820.7774360.388718
510.5944030.8111930.405597
520.5572540.8854930.442746
530.5691510.8616980.430849
540.5248030.9503950.475197
550.5488470.9023050.451153
560.5384870.9230260.461513
570.5127910.9744180.487209
580.5411110.9177780.458889
590.5734680.8530640.426532
600.5420230.9159540.457977
610.5671060.8657890.432894
620.5312580.9374840.468742
630.5240280.9519430.475972
640.4856070.9712140.514393
650.4473850.894770.552615
660.4858850.9717690.514115
670.4930230.9860450.506977
680.4753210.9506430.524679
690.4375970.8751940.562403
700.4149710.8299410.585029
710.3759890.7519780.624011
720.3767760.7535510.623224
730.3418980.6837950.658102
740.3223130.6446260.677687
750.3091070.6182140.690893
760.4285470.8570940.571453
770.411650.8232990.58835
780.4369170.8738340.563083
790.3985580.7971160.601442
800.447520.895040.55248
810.4183220.8366430.581678
820.4308370.8616730.569163
830.3941410.7882810.605859
840.3583450.716690.641655
850.3234410.6468830.676559
860.292160.5843210.70784
870.2634640.5269280.736536
880.2398560.4797110.760144
890.3004590.6009170.699541
900.2776550.555310.722345
910.2586080.5172150.741392
920.2308290.4616590.769171
930.215990.431980.78401
940.198660.3973210.80134
950.1737820.3475630.826218
960.1623160.3246320.837684
970.1500360.3000720.849964
980.1294750.258950.870525
990.1267280.2534560.873272
1000.1095590.2191190.890441
1010.1010080.2020160.898992
1020.08675630.1735130.913244
1030.105940.2118810.89406
1040.1176110.2352220.882389
1050.1201740.2403490.879826
1060.1029950.205990.897005
1070.1197270.2394550.880273
1080.1043280.2086560.895672
1090.2520370.5040740.747963
1100.2348420.4696840.765158
1110.209080.4181590.79092
1120.2105740.4211470.789426
1130.1943920.3887850.805608
1140.1781680.3563360.821832
1150.1591620.3183240.840838
1160.1396460.2792920.860354
1170.121530.243060.87847
1180.1497020.2994050.850298
1190.1400010.2800020.859999
1200.1210090.2420180.878991
1210.1085170.2170340.891483
1220.09870820.1974160.901292
1230.120940.241880.87906
1240.1072810.2145630.892719
1250.1068580.2137160.893142
1260.1066090.2132180.893391
1270.09217240.1843450.907828
1280.0828780.1657560.917122
1290.07030140.1406030.929699
1300.07019150.1403830.929808
1310.06865240.1373050.931348
1320.06416970.1283390.93583
1330.05998850.1199770.940011
1340.05043070.1008610.949569
1350.04791540.09583090.952085
1360.1201470.2402940.879853
1370.1046580.2093160.895342
1380.08940040.1788010.9106
1390.0808960.1617920.919104
1400.07775220.1555040.922248
1410.07396840.1479370.926032
1420.06937550.1387510.930625
1430.05987590.1197520.940124
1440.05054270.1010850.949457
1450.04309010.08618020.95691
1460.03591550.0718310.964085
1470.03466170.06932340.965338
1480.04020270.08040530.959797
1490.03620950.07241910.96379
1500.02985270.05970550.970147
1510.03213230.06426460.967868
1520.03081120.06162250.969189
1530.0297860.0595720.970214
1540.02694270.05388530.973057
1550.02980950.0596190.97019
1560.02532870.05065740.974671
1570.0206330.0412660.979367
1580.01780080.03560150.982199
1590.02778140.05556290.972219
1600.02844350.0568870.971557
1610.02523070.05046140.974769
1620.0679250.135850.932075
1630.05688710.1137740.943113
1640.1979360.3958720.802064
1650.1820010.3640020.817999
1660.3060330.6120670.693967
1670.2823380.5646760.717662
1680.2608690.5217390.739131
1690.2374650.4749310.762535
1700.2120440.4240880.787956
1710.2442220.4884450.755778
1720.2169380.4338750.783062
1730.2882610.5765220.711739
1740.2810090.5620180.718991
1750.2569330.5138660.743067
1760.329440.6588790.67056
1770.3044830.6089650.695517
1780.3055340.6110680.694466
1790.2852880.5705760.714712
1800.2665450.533090.733455
1810.2553110.5106220.744689
1820.3357850.671570.664215
1830.311390.6227790.68861
1840.3270230.6540450.672977
1850.3043490.6086970.695651
1860.3714460.7428920.628554
1870.3377750.675550.662225
1880.3051330.6102660.694867
1890.2725790.5451590.727421
1900.3584080.7168170.641592
1910.3541190.7082370.645881
1920.3725480.7450960.627452
1930.3639960.7279930.636004
1940.3283340.6566670.671666
1950.3019090.6038180.698091
1960.3132090.6264190.686791
1970.4172420.8344850.582758
1980.3900730.7801460.609927
1990.3530760.7061520.646924
2000.319740.6394810.68026
2010.2854570.5709140.714543
2020.2526550.505310.747345
2030.2218080.4436160.778192
2040.1916880.3833760.808312
2050.171450.3428990.82855
2060.1460780.2921560.853922
2070.1295230.2590450.870477
2080.1345630.2691270.865437
2090.1124860.2249730.887514
2100.09318710.1863740.906813
2110.07705610.1541120.922944
2120.06330340.1266070.936697
2130.0566660.1133320.943334
2140.06529940.1305990.934701
2150.05354840.1070970.946452
2160.04302220.08604440.956978
2170.03359430.06718860.966406
2180.02785550.0557110.972144
2190.02950620.05901250.970494
2200.02401510.04803010.975985
2210.0296810.0593620.970319
2220.02252030.04504050.97748
2230.01691120.03382250.983089
2240.01795260.03590530.982047
2250.01918890.03837780.980811
2260.01529130.03058260.984709
2270.01271480.02542950.987285
2280.01256760.02513520.987432
2290.01848730.03697450.981513
2300.01739930.03479860.982601
2310.01356330.02712650.986437
2320.01023390.02046770.989766
2330.01266360.02532730.987336
2340.01063830.02127660.989362
2350.01103360.02206720.988966
2360.008687020.0173740.991313
2370.007425240.01485050.992575
2380.005510320.01102060.99449
2390.02054730.04109460.979453
2400.02687030.05374050.97313
2410.0518970.1037940.948103
2420.03689380.07378760.963106
2430.02584120.05168250.974159
2440.01727620.03455250.982724
2450.01132290.02264580.988677
2460.01561220.03122430.984388
2470.009679530.01935910.99032
2480.2776120.5552240.722388
2490.300440.6008810.69956
2500.4557150.9114310.544285
2510.4549280.9098550.545072
2520.8346590.3306810.165341
2530.9042950.191410.0957051
2540.9824260.03514810.017574
2550.9625790.07484150.0374208
2560.9580620.08387560.0419378

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.997847 & 0.00430577 & 0.00215289 \tabularnewline
9 & 0.996794 & 0.00641133 & 0.00320566 \tabularnewline
10 & 0.993769 & 0.0124613 & 0.00623064 \tabularnewline
11 & 0.995044 & 0.00991142 & 0.00495571 \tabularnewline
12 & 0.997053 & 0.00589324 & 0.00294662 \tabularnewline
13 & 0.994549 & 0.010902 & 0.00545098 \tabularnewline
14 & 0.990418 & 0.019165 & 0.00958249 \tabularnewline
15 & 0.985744 & 0.028511 & 0.0142555 \tabularnewline
16 & 0.978465 & 0.043071 & 0.0215355 \tabularnewline
17 & 0.96648 & 0.0670407 & 0.0335204 \tabularnewline
18 & 0.958381 & 0.0832385 & 0.0416192 \tabularnewline
19 & 0.962754 & 0.0744924 & 0.0372462 \tabularnewline
20 & 0.946594 & 0.106812 & 0.053406 \tabularnewline
21 & 0.930093 & 0.139815 & 0.0699075 \tabularnewline
22 & 0.908008 & 0.183983 & 0.0919917 \tabularnewline
23 & 0.882796 & 0.234408 & 0.117204 \tabularnewline
24 & 0.847528 & 0.304945 & 0.152472 \tabularnewline
25 & 0.815947 & 0.368106 & 0.184053 \tabularnewline
26 & 0.925949 & 0.148103 & 0.0740515 \tabularnewline
27 & 0.905331 & 0.189337 & 0.0946687 \tabularnewline
28 & 0.889118 & 0.221764 & 0.110882 \tabularnewline
29 & 0.864479 & 0.271043 & 0.135521 \tabularnewline
30 & 0.836986 & 0.326029 & 0.163014 \tabularnewline
31 & 0.845913 & 0.308174 & 0.154087 \tabularnewline
32 & 0.816619 & 0.366762 & 0.183381 \tabularnewline
33 & 0.785898 & 0.428204 & 0.214102 \tabularnewline
34 & 0.757385 & 0.485231 & 0.242615 \tabularnewline
35 & 0.713172 & 0.573657 & 0.286828 \tabularnewline
36 & 0.74512 & 0.50976 & 0.25488 \tabularnewline
37 & 0.806555 & 0.386891 & 0.193445 \tabularnewline
38 & 0.768934 & 0.462133 & 0.231066 \tabularnewline
39 & 0.742522 & 0.514956 & 0.257478 \tabularnewline
40 & 0.753956 & 0.492087 & 0.246044 \tabularnewline
41 & 0.753791 & 0.492417 & 0.246209 \tabularnewline
42 & 0.73657 & 0.52686 & 0.26343 \tabularnewline
43 & 0.733103 & 0.533794 & 0.266897 \tabularnewline
44 & 0.692345 & 0.61531 & 0.307655 \tabularnewline
45 & 0.650716 & 0.698568 & 0.349284 \tabularnewline
46 & 0.622761 & 0.754478 & 0.377239 \tabularnewline
47 & 0.634974 & 0.730051 & 0.365026 \tabularnewline
48 & 0.599927 & 0.800146 & 0.400073 \tabularnewline
49 & 0.636917 & 0.726167 & 0.363083 \tabularnewline
50 & 0.611282 & 0.777436 & 0.388718 \tabularnewline
51 & 0.594403 & 0.811193 & 0.405597 \tabularnewline
52 & 0.557254 & 0.885493 & 0.442746 \tabularnewline
53 & 0.569151 & 0.861698 & 0.430849 \tabularnewline
54 & 0.524803 & 0.950395 & 0.475197 \tabularnewline
55 & 0.548847 & 0.902305 & 0.451153 \tabularnewline
56 & 0.538487 & 0.923026 & 0.461513 \tabularnewline
57 & 0.512791 & 0.974418 & 0.487209 \tabularnewline
58 & 0.541111 & 0.917778 & 0.458889 \tabularnewline
59 & 0.573468 & 0.853064 & 0.426532 \tabularnewline
60 & 0.542023 & 0.915954 & 0.457977 \tabularnewline
61 & 0.567106 & 0.865789 & 0.432894 \tabularnewline
62 & 0.531258 & 0.937484 & 0.468742 \tabularnewline
63 & 0.524028 & 0.951943 & 0.475972 \tabularnewline
64 & 0.485607 & 0.971214 & 0.514393 \tabularnewline
65 & 0.447385 & 0.89477 & 0.552615 \tabularnewline
66 & 0.485885 & 0.971769 & 0.514115 \tabularnewline
67 & 0.493023 & 0.986045 & 0.506977 \tabularnewline
68 & 0.475321 & 0.950643 & 0.524679 \tabularnewline
69 & 0.437597 & 0.875194 & 0.562403 \tabularnewline
70 & 0.414971 & 0.829941 & 0.585029 \tabularnewline
71 & 0.375989 & 0.751978 & 0.624011 \tabularnewline
72 & 0.376776 & 0.753551 & 0.623224 \tabularnewline
73 & 0.341898 & 0.683795 & 0.658102 \tabularnewline
74 & 0.322313 & 0.644626 & 0.677687 \tabularnewline
75 & 0.309107 & 0.618214 & 0.690893 \tabularnewline
76 & 0.428547 & 0.857094 & 0.571453 \tabularnewline
77 & 0.41165 & 0.823299 & 0.58835 \tabularnewline
78 & 0.436917 & 0.873834 & 0.563083 \tabularnewline
79 & 0.398558 & 0.797116 & 0.601442 \tabularnewline
80 & 0.44752 & 0.89504 & 0.55248 \tabularnewline
81 & 0.418322 & 0.836643 & 0.581678 \tabularnewline
82 & 0.430837 & 0.861673 & 0.569163 \tabularnewline
83 & 0.394141 & 0.788281 & 0.605859 \tabularnewline
84 & 0.358345 & 0.71669 & 0.641655 \tabularnewline
85 & 0.323441 & 0.646883 & 0.676559 \tabularnewline
86 & 0.29216 & 0.584321 & 0.70784 \tabularnewline
87 & 0.263464 & 0.526928 & 0.736536 \tabularnewline
88 & 0.239856 & 0.479711 & 0.760144 \tabularnewline
89 & 0.300459 & 0.600917 & 0.699541 \tabularnewline
90 & 0.277655 & 0.55531 & 0.722345 \tabularnewline
91 & 0.258608 & 0.517215 & 0.741392 \tabularnewline
92 & 0.230829 & 0.461659 & 0.769171 \tabularnewline
93 & 0.21599 & 0.43198 & 0.78401 \tabularnewline
94 & 0.19866 & 0.397321 & 0.80134 \tabularnewline
95 & 0.173782 & 0.347563 & 0.826218 \tabularnewline
96 & 0.162316 & 0.324632 & 0.837684 \tabularnewline
97 & 0.150036 & 0.300072 & 0.849964 \tabularnewline
98 & 0.129475 & 0.25895 & 0.870525 \tabularnewline
99 & 0.126728 & 0.253456 & 0.873272 \tabularnewline
100 & 0.109559 & 0.219119 & 0.890441 \tabularnewline
101 & 0.101008 & 0.202016 & 0.898992 \tabularnewline
102 & 0.0867563 & 0.173513 & 0.913244 \tabularnewline
103 & 0.10594 & 0.211881 & 0.89406 \tabularnewline
104 & 0.117611 & 0.235222 & 0.882389 \tabularnewline
105 & 0.120174 & 0.240349 & 0.879826 \tabularnewline
106 & 0.102995 & 0.20599 & 0.897005 \tabularnewline
107 & 0.119727 & 0.239455 & 0.880273 \tabularnewline
108 & 0.104328 & 0.208656 & 0.895672 \tabularnewline
109 & 0.252037 & 0.504074 & 0.747963 \tabularnewline
110 & 0.234842 & 0.469684 & 0.765158 \tabularnewline
111 & 0.20908 & 0.418159 & 0.79092 \tabularnewline
112 & 0.210574 & 0.421147 & 0.789426 \tabularnewline
113 & 0.194392 & 0.388785 & 0.805608 \tabularnewline
114 & 0.178168 & 0.356336 & 0.821832 \tabularnewline
115 & 0.159162 & 0.318324 & 0.840838 \tabularnewline
116 & 0.139646 & 0.279292 & 0.860354 \tabularnewline
117 & 0.12153 & 0.24306 & 0.87847 \tabularnewline
118 & 0.149702 & 0.299405 & 0.850298 \tabularnewline
119 & 0.140001 & 0.280002 & 0.859999 \tabularnewline
120 & 0.121009 & 0.242018 & 0.878991 \tabularnewline
121 & 0.108517 & 0.217034 & 0.891483 \tabularnewline
122 & 0.0987082 & 0.197416 & 0.901292 \tabularnewline
123 & 0.12094 & 0.24188 & 0.87906 \tabularnewline
124 & 0.107281 & 0.214563 & 0.892719 \tabularnewline
125 & 0.106858 & 0.213716 & 0.893142 \tabularnewline
126 & 0.106609 & 0.213218 & 0.893391 \tabularnewline
127 & 0.0921724 & 0.184345 & 0.907828 \tabularnewline
128 & 0.082878 & 0.165756 & 0.917122 \tabularnewline
129 & 0.0703014 & 0.140603 & 0.929699 \tabularnewline
130 & 0.0701915 & 0.140383 & 0.929808 \tabularnewline
131 & 0.0686524 & 0.137305 & 0.931348 \tabularnewline
132 & 0.0641697 & 0.128339 & 0.93583 \tabularnewline
133 & 0.0599885 & 0.119977 & 0.940011 \tabularnewline
134 & 0.0504307 & 0.100861 & 0.949569 \tabularnewline
135 & 0.0479154 & 0.0958309 & 0.952085 \tabularnewline
136 & 0.120147 & 0.240294 & 0.879853 \tabularnewline
137 & 0.104658 & 0.209316 & 0.895342 \tabularnewline
138 & 0.0894004 & 0.178801 & 0.9106 \tabularnewline
139 & 0.080896 & 0.161792 & 0.919104 \tabularnewline
140 & 0.0777522 & 0.155504 & 0.922248 \tabularnewline
141 & 0.0739684 & 0.147937 & 0.926032 \tabularnewline
142 & 0.0693755 & 0.138751 & 0.930625 \tabularnewline
143 & 0.0598759 & 0.119752 & 0.940124 \tabularnewline
144 & 0.0505427 & 0.101085 & 0.949457 \tabularnewline
145 & 0.0430901 & 0.0861802 & 0.95691 \tabularnewline
146 & 0.0359155 & 0.071831 & 0.964085 \tabularnewline
147 & 0.0346617 & 0.0693234 & 0.965338 \tabularnewline
148 & 0.0402027 & 0.0804053 & 0.959797 \tabularnewline
149 & 0.0362095 & 0.0724191 & 0.96379 \tabularnewline
150 & 0.0298527 & 0.0597055 & 0.970147 \tabularnewline
151 & 0.0321323 & 0.0642646 & 0.967868 \tabularnewline
152 & 0.0308112 & 0.0616225 & 0.969189 \tabularnewline
153 & 0.029786 & 0.059572 & 0.970214 \tabularnewline
154 & 0.0269427 & 0.0538853 & 0.973057 \tabularnewline
155 & 0.0298095 & 0.059619 & 0.97019 \tabularnewline
156 & 0.0253287 & 0.0506574 & 0.974671 \tabularnewline
157 & 0.020633 & 0.041266 & 0.979367 \tabularnewline
158 & 0.0178008 & 0.0356015 & 0.982199 \tabularnewline
159 & 0.0277814 & 0.0555629 & 0.972219 \tabularnewline
160 & 0.0284435 & 0.056887 & 0.971557 \tabularnewline
161 & 0.0252307 & 0.0504614 & 0.974769 \tabularnewline
162 & 0.067925 & 0.13585 & 0.932075 \tabularnewline
163 & 0.0568871 & 0.113774 & 0.943113 \tabularnewline
164 & 0.197936 & 0.395872 & 0.802064 \tabularnewline
165 & 0.182001 & 0.364002 & 0.817999 \tabularnewline
166 & 0.306033 & 0.612067 & 0.693967 \tabularnewline
167 & 0.282338 & 0.564676 & 0.717662 \tabularnewline
168 & 0.260869 & 0.521739 & 0.739131 \tabularnewline
169 & 0.237465 & 0.474931 & 0.762535 \tabularnewline
170 & 0.212044 & 0.424088 & 0.787956 \tabularnewline
171 & 0.244222 & 0.488445 & 0.755778 \tabularnewline
172 & 0.216938 & 0.433875 & 0.783062 \tabularnewline
173 & 0.288261 & 0.576522 & 0.711739 \tabularnewline
174 & 0.281009 & 0.562018 & 0.718991 \tabularnewline
175 & 0.256933 & 0.513866 & 0.743067 \tabularnewline
176 & 0.32944 & 0.658879 & 0.67056 \tabularnewline
177 & 0.304483 & 0.608965 & 0.695517 \tabularnewline
178 & 0.305534 & 0.611068 & 0.694466 \tabularnewline
179 & 0.285288 & 0.570576 & 0.714712 \tabularnewline
180 & 0.266545 & 0.53309 & 0.733455 \tabularnewline
181 & 0.255311 & 0.510622 & 0.744689 \tabularnewline
182 & 0.335785 & 0.67157 & 0.664215 \tabularnewline
183 & 0.31139 & 0.622779 & 0.68861 \tabularnewline
184 & 0.327023 & 0.654045 & 0.672977 \tabularnewline
185 & 0.304349 & 0.608697 & 0.695651 \tabularnewline
186 & 0.371446 & 0.742892 & 0.628554 \tabularnewline
187 & 0.337775 & 0.67555 & 0.662225 \tabularnewline
188 & 0.305133 & 0.610266 & 0.694867 \tabularnewline
189 & 0.272579 & 0.545159 & 0.727421 \tabularnewline
190 & 0.358408 & 0.716817 & 0.641592 \tabularnewline
191 & 0.354119 & 0.708237 & 0.645881 \tabularnewline
192 & 0.372548 & 0.745096 & 0.627452 \tabularnewline
193 & 0.363996 & 0.727993 & 0.636004 \tabularnewline
194 & 0.328334 & 0.656667 & 0.671666 \tabularnewline
195 & 0.301909 & 0.603818 & 0.698091 \tabularnewline
196 & 0.313209 & 0.626419 & 0.686791 \tabularnewline
197 & 0.417242 & 0.834485 & 0.582758 \tabularnewline
198 & 0.390073 & 0.780146 & 0.609927 \tabularnewline
199 & 0.353076 & 0.706152 & 0.646924 \tabularnewline
200 & 0.31974 & 0.639481 & 0.68026 \tabularnewline
201 & 0.285457 & 0.570914 & 0.714543 \tabularnewline
202 & 0.252655 & 0.50531 & 0.747345 \tabularnewline
203 & 0.221808 & 0.443616 & 0.778192 \tabularnewline
204 & 0.191688 & 0.383376 & 0.808312 \tabularnewline
205 & 0.17145 & 0.342899 & 0.82855 \tabularnewline
206 & 0.146078 & 0.292156 & 0.853922 \tabularnewline
207 & 0.129523 & 0.259045 & 0.870477 \tabularnewline
208 & 0.134563 & 0.269127 & 0.865437 \tabularnewline
209 & 0.112486 & 0.224973 & 0.887514 \tabularnewline
210 & 0.0931871 & 0.186374 & 0.906813 \tabularnewline
211 & 0.0770561 & 0.154112 & 0.922944 \tabularnewline
212 & 0.0633034 & 0.126607 & 0.936697 \tabularnewline
213 & 0.056666 & 0.113332 & 0.943334 \tabularnewline
214 & 0.0652994 & 0.130599 & 0.934701 \tabularnewline
215 & 0.0535484 & 0.107097 & 0.946452 \tabularnewline
216 & 0.0430222 & 0.0860444 & 0.956978 \tabularnewline
217 & 0.0335943 & 0.0671886 & 0.966406 \tabularnewline
218 & 0.0278555 & 0.055711 & 0.972144 \tabularnewline
219 & 0.0295062 & 0.0590125 & 0.970494 \tabularnewline
220 & 0.0240151 & 0.0480301 & 0.975985 \tabularnewline
221 & 0.029681 & 0.059362 & 0.970319 \tabularnewline
222 & 0.0225203 & 0.0450405 & 0.97748 \tabularnewline
223 & 0.0169112 & 0.0338225 & 0.983089 \tabularnewline
224 & 0.0179526 & 0.0359053 & 0.982047 \tabularnewline
225 & 0.0191889 & 0.0383778 & 0.980811 \tabularnewline
226 & 0.0152913 & 0.0305826 & 0.984709 \tabularnewline
227 & 0.0127148 & 0.0254295 & 0.987285 \tabularnewline
228 & 0.0125676 & 0.0251352 & 0.987432 \tabularnewline
229 & 0.0184873 & 0.0369745 & 0.981513 \tabularnewline
230 & 0.0173993 & 0.0347986 & 0.982601 \tabularnewline
231 & 0.0135633 & 0.0271265 & 0.986437 \tabularnewline
232 & 0.0102339 & 0.0204677 & 0.989766 \tabularnewline
233 & 0.0126636 & 0.0253273 & 0.987336 \tabularnewline
234 & 0.0106383 & 0.0212766 & 0.989362 \tabularnewline
235 & 0.0110336 & 0.0220672 & 0.988966 \tabularnewline
236 & 0.00868702 & 0.017374 & 0.991313 \tabularnewline
237 & 0.00742524 & 0.0148505 & 0.992575 \tabularnewline
238 & 0.00551032 & 0.0110206 & 0.99449 \tabularnewline
239 & 0.0205473 & 0.0410946 & 0.979453 \tabularnewline
240 & 0.0268703 & 0.0537405 & 0.97313 \tabularnewline
241 & 0.051897 & 0.103794 & 0.948103 \tabularnewline
242 & 0.0368938 & 0.0737876 & 0.963106 \tabularnewline
243 & 0.0258412 & 0.0516825 & 0.974159 \tabularnewline
244 & 0.0172762 & 0.0345525 & 0.982724 \tabularnewline
245 & 0.0113229 & 0.0226458 & 0.988677 \tabularnewline
246 & 0.0156122 & 0.0312243 & 0.984388 \tabularnewline
247 & 0.00967953 & 0.0193591 & 0.99032 \tabularnewline
248 & 0.277612 & 0.555224 & 0.722388 \tabularnewline
249 & 0.30044 & 0.600881 & 0.69956 \tabularnewline
250 & 0.455715 & 0.911431 & 0.544285 \tabularnewline
251 & 0.454928 & 0.909855 & 0.545072 \tabularnewline
252 & 0.834659 & 0.330681 & 0.165341 \tabularnewline
253 & 0.904295 & 0.19141 & 0.0957051 \tabularnewline
254 & 0.982426 & 0.0351481 & 0.017574 \tabularnewline
255 & 0.962579 & 0.0748415 & 0.0374208 \tabularnewline
256 & 0.958062 & 0.0838756 & 0.0419378 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226747&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]8[/C][C]0.997847[/C][C]0.00430577[/C][C]0.00215289[/C][/ROW]
[ROW][C]9[/C][C]0.996794[/C][C]0.00641133[/C][C]0.00320566[/C][/ROW]
[ROW][C]10[/C][C]0.993769[/C][C]0.0124613[/C][C]0.00623064[/C][/ROW]
[ROW][C]11[/C][C]0.995044[/C][C]0.00991142[/C][C]0.00495571[/C][/ROW]
[ROW][C]12[/C][C]0.997053[/C][C]0.00589324[/C][C]0.00294662[/C][/ROW]
[ROW][C]13[/C][C]0.994549[/C][C]0.010902[/C][C]0.00545098[/C][/ROW]
[ROW][C]14[/C][C]0.990418[/C][C]0.019165[/C][C]0.00958249[/C][/ROW]
[ROW][C]15[/C][C]0.985744[/C][C]0.028511[/C][C]0.0142555[/C][/ROW]
[ROW][C]16[/C][C]0.978465[/C][C]0.043071[/C][C]0.0215355[/C][/ROW]
[ROW][C]17[/C][C]0.96648[/C][C]0.0670407[/C][C]0.0335204[/C][/ROW]
[ROW][C]18[/C][C]0.958381[/C][C]0.0832385[/C][C]0.0416192[/C][/ROW]
[ROW][C]19[/C][C]0.962754[/C][C]0.0744924[/C][C]0.0372462[/C][/ROW]
[ROW][C]20[/C][C]0.946594[/C][C]0.106812[/C][C]0.053406[/C][/ROW]
[ROW][C]21[/C][C]0.930093[/C][C]0.139815[/C][C]0.0699075[/C][/ROW]
[ROW][C]22[/C][C]0.908008[/C][C]0.183983[/C][C]0.0919917[/C][/ROW]
[ROW][C]23[/C][C]0.882796[/C][C]0.234408[/C][C]0.117204[/C][/ROW]
[ROW][C]24[/C][C]0.847528[/C][C]0.304945[/C][C]0.152472[/C][/ROW]
[ROW][C]25[/C][C]0.815947[/C][C]0.368106[/C][C]0.184053[/C][/ROW]
[ROW][C]26[/C][C]0.925949[/C][C]0.148103[/C][C]0.0740515[/C][/ROW]
[ROW][C]27[/C][C]0.905331[/C][C]0.189337[/C][C]0.0946687[/C][/ROW]
[ROW][C]28[/C][C]0.889118[/C][C]0.221764[/C][C]0.110882[/C][/ROW]
[ROW][C]29[/C][C]0.864479[/C][C]0.271043[/C][C]0.135521[/C][/ROW]
[ROW][C]30[/C][C]0.836986[/C][C]0.326029[/C][C]0.163014[/C][/ROW]
[ROW][C]31[/C][C]0.845913[/C][C]0.308174[/C][C]0.154087[/C][/ROW]
[ROW][C]32[/C][C]0.816619[/C][C]0.366762[/C][C]0.183381[/C][/ROW]
[ROW][C]33[/C][C]0.785898[/C][C]0.428204[/C][C]0.214102[/C][/ROW]
[ROW][C]34[/C][C]0.757385[/C][C]0.485231[/C][C]0.242615[/C][/ROW]
[ROW][C]35[/C][C]0.713172[/C][C]0.573657[/C][C]0.286828[/C][/ROW]
[ROW][C]36[/C][C]0.74512[/C][C]0.50976[/C][C]0.25488[/C][/ROW]
[ROW][C]37[/C][C]0.806555[/C][C]0.386891[/C][C]0.193445[/C][/ROW]
[ROW][C]38[/C][C]0.768934[/C][C]0.462133[/C][C]0.231066[/C][/ROW]
[ROW][C]39[/C][C]0.742522[/C][C]0.514956[/C][C]0.257478[/C][/ROW]
[ROW][C]40[/C][C]0.753956[/C][C]0.492087[/C][C]0.246044[/C][/ROW]
[ROW][C]41[/C][C]0.753791[/C][C]0.492417[/C][C]0.246209[/C][/ROW]
[ROW][C]42[/C][C]0.73657[/C][C]0.52686[/C][C]0.26343[/C][/ROW]
[ROW][C]43[/C][C]0.733103[/C][C]0.533794[/C][C]0.266897[/C][/ROW]
[ROW][C]44[/C][C]0.692345[/C][C]0.61531[/C][C]0.307655[/C][/ROW]
[ROW][C]45[/C][C]0.650716[/C][C]0.698568[/C][C]0.349284[/C][/ROW]
[ROW][C]46[/C][C]0.622761[/C][C]0.754478[/C][C]0.377239[/C][/ROW]
[ROW][C]47[/C][C]0.634974[/C][C]0.730051[/C][C]0.365026[/C][/ROW]
[ROW][C]48[/C][C]0.599927[/C][C]0.800146[/C][C]0.400073[/C][/ROW]
[ROW][C]49[/C][C]0.636917[/C][C]0.726167[/C][C]0.363083[/C][/ROW]
[ROW][C]50[/C][C]0.611282[/C][C]0.777436[/C][C]0.388718[/C][/ROW]
[ROW][C]51[/C][C]0.594403[/C][C]0.811193[/C][C]0.405597[/C][/ROW]
[ROW][C]52[/C][C]0.557254[/C][C]0.885493[/C][C]0.442746[/C][/ROW]
[ROW][C]53[/C][C]0.569151[/C][C]0.861698[/C][C]0.430849[/C][/ROW]
[ROW][C]54[/C][C]0.524803[/C][C]0.950395[/C][C]0.475197[/C][/ROW]
[ROW][C]55[/C][C]0.548847[/C][C]0.902305[/C][C]0.451153[/C][/ROW]
[ROW][C]56[/C][C]0.538487[/C][C]0.923026[/C][C]0.461513[/C][/ROW]
[ROW][C]57[/C][C]0.512791[/C][C]0.974418[/C][C]0.487209[/C][/ROW]
[ROW][C]58[/C][C]0.541111[/C][C]0.917778[/C][C]0.458889[/C][/ROW]
[ROW][C]59[/C][C]0.573468[/C][C]0.853064[/C][C]0.426532[/C][/ROW]
[ROW][C]60[/C][C]0.542023[/C][C]0.915954[/C][C]0.457977[/C][/ROW]
[ROW][C]61[/C][C]0.567106[/C][C]0.865789[/C][C]0.432894[/C][/ROW]
[ROW][C]62[/C][C]0.531258[/C][C]0.937484[/C][C]0.468742[/C][/ROW]
[ROW][C]63[/C][C]0.524028[/C][C]0.951943[/C][C]0.475972[/C][/ROW]
[ROW][C]64[/C][C]0.485607[/C][C]0.971214[/C][C]0.514393[/C][/ROW]
[ROW][C]65[/C][C]0.447385[/C][C]0.89477[/C][C]0.552615[/C][/ROW]
[ROW][C]66[/C][C]0.485885[/C][C]0.971769[/C][C]0.514115[/C][/ROW]
[ROW][C]67[/C][C]0.493023[/C][C]0.986045[/C][C]0.506977[/C][/ROW]
[ROW][C]68[/C][C]0.475321[/C][C]0.950643[/C][C]0.524679[/C][/ROW]
[ROW][C]69[/C][C]0.437597[/C][C]0.875194[/C][C]0.562403[/C][/ROW]
[ROW][C]70[/C][C]0.414971[/C][C]0.829941[/C][C]0.585029[/C][/ROW]
[ROW][C]71[/C][C]0.375989[/C][C]0.751978[/C][C]0.624011[/C][/ROW]
[ROW][C]72[/C][C]0.376776[/C][C]0.753551[/C][C]0.623224[/C][/ROW]
[ROW][C]73[/C][C]0.341898[/C][C]0.683795[/C][C]0.658102[/C][/ROW]
[ROW][C]74[/C][C]0.322313[/C][C]0.644626[/C][C]0.677687[/C][/ROW]
[ROW][C]75[/C][C]0.309107[/C][C]0.618214[/C][C]0.690893[/C][/ROW]
[ROW][C]76[/C][C]0.428547[/C][C]0.857094[/C][C]0.571453[/C][/ROW]
[ROW][C]77[/C][C]0.41165[/C][C]0.823299[/C][C]0.58835[/C][/ROW]
[ROW][C]78[/C][C]0.436917[/C][C]0.873834[/C][C]0.563083[/C][/ROW]
[ROW][C]79[/C][C]0.398558[/C][C]0.797116[/C][C]0.601442[/C][/ROW]
[ROW][C]80[/C][C]0.44752[/C][C]0.89504[/C][C]0.55248[/C][/ROW]
[ROW][C]81[/C][C]0.418322[/C][C]0.836643[/C][C]0.581678[/C][/ROW]
[ROW][C]82[/C][C]0.430837[/C][C]0.861673[/C][C]0.569163[/C][/ROW]
[ROW][C]83[/C][C]0.394141[/C][C]0.788281[/C][C]0.605859[/C][/ROW]
[ROW][C]84[/C][C]0.358345[/C][C]0.71669[/C][C]0.641655[/C][/ROW]
[ROW][C]85[/C][C]0.323441[/C][C]0.646883[/C][C]0.676559[/C][/ROW]
[ROW][C]86[/C][C]0.29216[/C][C]0.584321[/C][C]0.70784[/C][/ROW]
[ROW][C]87[/C][C]0.263464[/C][C]0.526928[/C][C]0.736536[/C][/ROW]
[ROW][C]88[/C][C]0.239856[/C][C]0.479711[/C][C]0.760144[/C][/ROW]
[ROW][C]89[/C][C]0.300459[/C][C]0.600917[/C][C]0.699541[/C][/ROW]
[ROW][C]90[/C][C]0.277655[/C][C]0.55531[/C][C]0.722345[/C][/ROW]
[ROW][C]91[/C][C]0.258608[/C][C]0.517215[/C][C]0.741392[/C][/ROW]
[ROW][C]92[/C][C]0.230829[/C][C]0.461659[/C][C]0.769171[/C][/ROW]
[ROW][C]93[/C][C]0.21599[/C][C]0.43198[/C][C]0.78401[/C][/ROW]
[ROW][C]94[/C][C]0.19866[/C][C]0.397321[/C][C]0.80134[/C][/ROW]
[ROW][C]95[/C][C]0.173782[/C][C]0.347563[/C][C]0.826218[/C][/ROW]
[ROW][C]96[/C][C]0.162316[/C][C]0.324632[/C][C]0.837684[/C][/ROW]
[ROW][C]97[/C][C]0.150036[/C][C]0.300072[/C][C]0.849964[/C][/ROW]
[ROW][C]98[/C][C]0.129475[/C][C]0.25895[/C][C]0.870525[/C][/ROW]
[ROW][C]99[/C][C]0.126728[/C][C]0.253456[/C][C]0.873272[/C][/ROW]
[ROW][C]100[/C][C]0.109559[/C][C]0.219119[/C][C]0.890441[/C][/ROW]
[ROW][C]101[/C][C]0.101008[/C][C]0.202016[/C][C]0.898992[/C][/ROW]
[ROW][C]102[/C][C]0.0867563[/C][C]0.173513[/C][C]0.913244[/C][/ROW]
[ROW][C]103[/C][C]0.10594[/C][C]0.211881[/C][C]0.89406[/C][/ROW]
[ROW][C]104[/C][C]0.117611[/C][C]0.235222[/C][C]0.882389[/C][/ROW]
[ROW][C]105[/C][C]0.120174[/C][C]0.240349[/C][C]0.879826[/C][/ROW]
[ROW][C]106[/C][C]0.102995[/C][C]0.20599[/C][C]0.897005[/C][/ROW]
[ROW][C]107[/C][C]0.119727[/C][C]0.239455[/C][C]0.880273[/C][/ROW]
[ROW][C]108[/C][C]0.104328[/C][C]0.208656[/C][C]0.895672[/C][/ROW]
[ROW][C]109[/C][C]0.252037[/C][C]0.504074[/C][C]0.747963[/C][/ROW]
[ROW][C]110[/C][C]0.234842[/C][C]0.469684[/C][C]0.765158[/C][/ROW]
[ROW][C]111[/C][C]0.20908[/C][C]0.418159[/C][C]0.79092[/C][/ROW]
[ROW][C]112[/C][C]0.210574[/C][C]0.421147[/C][C]0.789426[/C][/ROW]
[ROW][C]113[/C][C]0.194392[/C][C]0.388785[/C][C]0.805608[/C][/ROW]
[ROW][C]114[/C][C]0.178168[/C][C]0.356336[/C][C]0.821832[/C][/ROW]
[ROW][C]115[/C][C]0.159162[/C][C]0.318324[/C][C]0.840838[/C][/ROW]
[ROW][C]116[/C][C]0.139646[/C][C]0.279292[/C][C]0.860354[/C][/ROW]
[ROW][C]117[/C][C]0.12153[/C][C]0.24306[/C][C]0.87847[/C][/ROW]
[ROW][C]118[/C][C]0.149702[/C][C]0.299405[/C][C]0.850298[/C][/ROW]
[ROW][C]119[/C][C]0.140001[/C][C]0.280002[/C][C]0.859999[/C][/ROW]
[ROW][C]120[/C][C]0.121009[/C][C]0.242018[/C][C]0.878991[/C][/ROW]
[ROW][C]121[/C][C]0.108517[/C][C]0.217034[/C][C]0.891483[/C][/ROW]
[ROW][C]122[/C][C]0.0987082[/C][C]0.197416[/C][C]0.901292[/C][/ROW]
[ROW][C]123[/C][C]0.12094[/C][C]0.24188[/C][C]0.87906[/C][/ROW]
[ROW][C]124[/C][C]0.107281[/C][C]0.214563[/C][C]0.892719[/C][/ROW]
[ROW][C]125[/C][C]0.106858[/C][C]0.213716[/C][C]0.893142[/C][/ROW]
[ROW][C]126[/C][C]0.106609[/C][C]0.213218[/C][C]0.893391[/C][/ROW]
[ROW][C]127[/C][C]0.0921724[/C][C]0.184345[/C][C]0.907828[/C][/ROW]
[ROW][C]128[/C][C]0.082878[/C][C]0.165756[/C][C]0.917122[/C][/ROW]
[ROW][C]129[/C][C]0.0703014[/C][C]0.140603[/C][C]0.929699[/C][/ROW]
[ROW][C]130[/C][C]0.0701915[/C][C]0.140383[/C][C]0.929808[/C][/ROW]
[ROW][C]131[/C][C]0.0686524[/C][C]0.137305[/C][C]0.931348[/C][/ROW]
[ROW][C]132[/C][C]0.0641697[/C][C]0.128339[/C][C]0.93583[/C][/ROW]
[ROW][C]133[/C][C]0.0599885[/C][C]0.119977[/C][C]0.940011[/C][/ROW]
[ROW][C]134[/C][C]0.0504307[/C][C]0.100861[/C][C]0.949569[/C][/ROW]
[ROW][C]135[/C][C]0.0479154[/C][C]0.0958309[/C][C]0.952085[/C][/ROW]
[ROW][C]136[/C][C]0.120147[/C][C]0.240294[/C][C]0.879853[/C][/ROW]
[ROW][C]137[/C][C]0.104658[/C][C]0.209316[/C][C]0.895342[/C][/ROW]
[ROW][C]138[/C][C]0.0894004[/C][C]0.178801[/C][C]0.9106[/C][/ROW]
[ROW][C]139[/C][C]0.080896[/C][C]0.161792[/C][C]0.919104[/C][/ROW]
[ROW][C]140[/C][C]0.0777522[/C][C]0.155504[/C][C]0.922248[/C][/ROW]
[ROW][C]141[/C][C]0.0739684[/C][C]0.147937[/C][C]0.926032[/C][/ROW]
[ROW][C]142[/C][C]0.0693755[/C][C]0.138751[/C][C]0.930625[/C][/ROW]
[ROW][C]143[/C][C]0.0598759[/C][C]0.119752[/C][C]0.940124[/C][/ROW]
[ROW][C]144[/C][C]0.0505427[/C][C]0.101085[/C][C]0.949457[/C][/ROW]
[ROW][C]145[/C][C]0.0430901[/C][C]0.0861802[/C][C]0.95691[/C][/ROW]
[ROW][C]146[/C][C]0.0359155[/C][C]0.071831[/C][C]0.964085[/C][/ROW]
[ROW][C]147[/C][C]0.0346617[/C][C]0.0693234[/C][C]0.965338[/C][/ROW]
[ROW][C]148[/C][C]0.0402027[/C][C]0.0804053[/C][C]0.959797[/C][/ROW]
[ROW][C]149[/C][C]0.0362095[/C][C]0.0724191[/C][C]0.96379[/C][/ROW]
[ROW][C]150[/C][C]0.0298527[/C][C]0.0597055[/C][C]0.970147[/C][/ROW]
[ROW][C]151[/C][C]0.0321323[/C][C]0.0642646[/C][C]0.967868[/C][/ROW]
[ROW][C]152[/C][C]0.0308112[/C][C]0.0616225[/C][C]0.969189[/C][/ROW]
[ROW][C]153[/C][C]0.029786[/C][C]0.059572[/C][C]0.970214[/C][/ROW]
[ROW][C]154[/C][C]0.0269427[/C][C]0.0538853[/C][C]0.973057[/C][/ROW]
[ROW][C]155[/C][C]0.0298095[/C][C]0.059619[/C][C]0.97019[/C][/ROW]
[ROW][C]156[/C][C]0.0253287[/C][C]0.0506574[/C][C]0.974671[/C][/ROW]
[ROW][C]157[/C][C]0.020633[/C][C]0.041266[/C][C]0.979367[/C][/ROW]
[ROW][C]158[/C][C]0.0178008[/C][C]0.0356015[/C][C]0.982199[/C][/ROW]
[ROW][C]159[/C][C]0.0277814[/C][C]0.0555629[/C][C]0.972219[/C][/ROW]
[ROW][C]160[/C][C]0.0284435[/C][C]0.056887[/C][C]0.971557[/C][/ROW]
[ROW][C]161[/C][C]0.0252307[/C][C]0.0504614[/C][C]0.974769[/C][/ROW]
[ROW][C]162[/C][C]0.067925[/C][C]0.13585[/C][C]0.932075[/C][/ROW]
[ROW][C]163[/C][C]0.0568871[/C][C]0.113774[/C][C]0.943113[/C][/ROW]
[ROW][C]164[/C][C]0.197936[/C][C]0.395872[/C][C]0.802064[/C][/ROW]
[ROW][C]165[/C][C]0.182001[/C][C]0.364002[/C][C]0.817999[/C][/ROW]
[ROW][C]166[/C][C]0.306033[/C][C]0.612067[/C][C]0.693967[/C][/ROW]
[ROW][C]167[/C][C]0.282338[/C][C]0.564676[/C][C]0.717662[/C][/ROW]
[ROW][C]168[/C][C]0.260869[/C][C]0.521739[/C][C]0.739131[/C][/ROW]
[ROW][C]169[/C][C]0.237465[/C][C]0.474931[/C][C]0.762535[/C][/ROW]
[ROW][C]170[/C][C]0.212044[/C][C]0.424088[/C][C]0.787956[/C][/ROW]
[ROW][C]171[/C][C]0.244222[/C][C]0.488445[/C][C]0.755778[/C][/ROW]
[ROW][C]172[/C][C]0.216938[/C][C]0.433875[/C][C]0.783062[/C][/ROW]
[ROW][C]173[/C][C]0.288261[/C][C]0.576522[/C][C]0.711739[/C][/ROW]
[ROW][C]174[/C][C]0.281009[/C][C]0.562018[/C][C]0.718991[/C][/ROW]
[ROW][C]175[/C][C]0.256933[/C][C]0.513866[/C][C]0.743067[/C][/ROW]
[ROW][C]176[/C][C]0.32944[/C][C]0.658879[/C][C]0.67056[/C][/ROW]
[ROW][C]177[/C][C]0.304483[/C][C]0.608965[/C][C]0.695517[/C][/ROW]
[ROW][C]178[/C][C]0.305534[/C][C]0.611068[/C][C]0.694466[/C][/ROW]
[ROW][C]179[/C][C]0.285288[/C][C]0.570576[/C][C]0.714712[/C][/ROW]
[ROW][C]180[/C][C]0.266545[/C][C]0.53309[/C][C]0.733455[/C][/ROW]
[ROW][C]181[/C][C]0.255311[/C][C]0.510622[/C][C]0.744689[/C][/ROW]
[ROW][C]182[/C][C]0.335785[/C][C]0.67157[/C][C]0.664215[/C][/ROW]
[ROW][C]183[/C][C]0.31139[/C][C]0.622779[/C][C]0.68861[/C][/ROW]
[ROW][C]184[/C][C]0.327023[/C][C]0.654045[/C][C]0.672977[/C][/ROW]
[ROW][C]185[/C][C]0.304349[/C][C]0.608697[/C][C]0.695651[/C][/ROW]
[ROW][C]186[/C][C]0.371446[/C][C]0.742892[/C][C]0.628554[/C][/ROW]
[ROW][C]187[/C][C]0.337775[/C][C]0.67555[/C][C]0.662225[/C][/ROW]
[ROW][C]188[/C][C]0.305133[/C][C]0.610266[/C][C]0.694867[/C][/ROW]
[ROW][C]189[/C][C]0.272579[/C][C]0.545159[/C][C]0.727421[/C][/ROW]
[ROW][C]190[/C][C]0.358408[/C][C]0.716817[/C][C]0.641592[/C][/ROW]
[ROW][C]191[/C][C]0.354119[/C][C]0.708237[/C][C]0.645881[/C][/ROW]
[ROW][C]192[/C][C]0.372548[/C][C]0.745096[/C][C]0.627452[/C][/ROW]
[ROW][C]193[/C][C]0.363996[/C][C]0.727993[/C][C]0.636004[/C][/ROW]
[ROW][C]194[/C][C]0.328334[/C][C]0.656667[/C][C]0.671666[/C][/ROW]
[ROW][C]195[/C][C]0.301909[/C][C]0.603818[/C][C]0.698091[/C][/ROW]
[ROW][C]196[/C][C]0.313209[/C][C]0.626419[/C][C]0.686791[/C][/ROW]
[ROW][C]197[/C][C]0.417242[/C][C]0.834485[/C][C]0.582758[/C][/ROW]
[ROW][C]198[/C][C]0.390073[/C][C]0.780146[/C][C]0.609927[/C][/ROW]
[ROW][C]199[/C][C]0.353076[/C][C]0.706152[/C][C]0.646924[/C][/ROW]
[ROW][C]200[/C][C]0.31974[/C][C]0.639481[/C][C]0.68026[/C][/ROW]
[ROW][C]201[/C][C]0.285457[/C][C]0.570914[/C][C]0.714543[/C][/ROW]
[ROW][C]202[/C][C]0.252655[/C][C]0.50531[/C][C]0.747345[/C][/ROW]
[ROW][C]203[/C][C]0.221808[/C][C]0.443616[/C][C]0.778192[/C][/ROW]
[ROW][C]204[/C][C]0.191688[/C][C]0.383376[/C][C]0.808312[/C][/ROW]
[ROW][C]205[/C][C]0.17145[/C][C]0.342899[/C][C]0.82855[/C][/ROW]
[ROW][C]206[/C][C]0.146078[/C][C]0.292156[/C][C]0.853922[/C][/ROW]
[ROW][C]207[/C][C]0.129523[/C][C]0.259045[/C][C]0.870477[/C][/ROW]
[ROW][C]208[/C][C]0.134563[/C][C]0.269127[/C][C]0.865437[/C][/ROW]
[ROW][C]209[/C][C]0.112486[/C][C]0.224973[/C][C]0.887514[/C][/ROW]
[ROW][C]210[/C][C]0.0931871[/C][C]0.186374[/C][C]0.906813[/C][/ROW]
[ROW][C]211[/C][C]0.0770561[/C][C]0.154112[/C][C]0.922944[/C][/ROW]
[ROW][C]212[/C][C]0.0633034[/C][C]0.126607[/C][C]0.936697[/C][/ROW]
[ROW][C]213[/C][C]0.056666[/C][C]0.113332[/C][C]0.943334[/C][/ROW]
[ROW][C]214[/C][C]0.0652994[/C][C]0.130599[/C][C]0.934701[/C][/ROW]
[ROW][C]215[/C][C]0.0535484[/C][C]0.107097[/C][C]0.946452[/C][/ROW]
[ROW][C]216[/C][C]0.0430222[/C][C]0.0860444[/C][C]0.956978[/C][/ROW]
[ROW][C]217[/C][C]0.0335943[/C][C]0.0671886[/C][C]0.966406[/C][/ROW]
[ROW][C]218[/C][C]0.0278555[/C][C]0.055711[/C][C]0.972144[/C][/ROW]
[ROW][C]219[/C][C]0.0295062[/C][C]0.0590125[/C][C]0.970494[/C][/ROW]
[ROW][C]220[/C][C]0.0240151[/C][C]0.0480301[/C][C]0.975985[/C][/ROW]
[ROW][C]221[/C][C]0.029681[/C][C]0.059362[/C][C]0.970319[/C][/ROW]
[ROW][C]222[/C][C]0.0225203[/C][C]0.0450405[/C][C]0.97748[/C][/ROW]
[ROW][C]223[/C][C]0.0169112[/C][C]0.0338225[/C][C]0.983089[/C][/ROW]
[ROW][C]224[/C][C]0.0179526[/C][C]0.0359053[/C][C]0.982047[/C][/ROW]
[ROW][C]225[/C][C]0.0191889[/C][C]0.0383778[/C][C]0.980811[/C][/ROW]
[ROW][C]226[/C][C]0.0152913[/C][C]0.0305826[/C][C]0.984709[/C][/ROW]
[ROW][C]227[/C][C]0.0127148[/C][C]0.0254295[/C][C]0.987285[/C][/ROW]
[ROW][C]228[/C][C]0.0125676[/C][C]0.0251352[/C][C]0.987432[/C][/ROW]
[ROW][C]229[/C][C]0.0184873[/C][C]0.0369745[/C][C]0.981513[/C][/ROW]
[ROW][C]230[/C][C]0.0173993[/C][C]0.0347986[/C][C]0.982601[/C][/ROW]
[ROW][C]231[/C][C]0.0135633[/C][C]0.0271265[/C][C]0.986437[/C][/ROW]
[ROW][C]232[/C][C]0.0102339[/C][C]0.0204677[/C][C]0.989766[/C][/ROW]
[ROW][C]233[/C][C]0.0126636[/C][C]0.0253273[/C][C]0.987336[/C][/ROW]
[ROW][C]234[/C][C]0.0106383[/C][C]0.0212766[/C][C]0.989362[/C][/ROW]
[ROW][C]235[/C][C]0.0110336[/C][C]0.0220672[/C][C]0.988966[/C][/ROW]
[ROW][C]236[/C][C]0.00868702[/C][C]0.017374[/C][C]0.991313[/C][/ROW]
[ROW][C]237[/C][C]0.00742524[/C][C]0.0148505[/C][C]0.992575[/C][/ROW]
[ROW][C]238[/C][C]0.00551032[/C][C]0.0110206[/C][C]0.99449[/C][/ROW]
[ROW][C]239[/C][C]0.0205473[/C][C]0.0410946[/C][C]0.979453[/C][/ROW]
[ROW][C]240[/C][C]0.0268703[/C][C]0.0537405[/C][C]0.97313[/C][/ROW]
[ROW][C]241[/C][C]0.051897[/C][C]0.103794[/C][C]0.948103[/C][/ROW]
[ROW][C]242[/C][C]0.0368938[/C][C]0.0737876[/C][C]0.963106[/C][/ROW]
[ROW][C]243[/C][C]0.0258412[/C][C]0.0516825[/C][C]0.974159[/C][/ROW]
[ROW][C]244[/C][C]0.0172762[/C][C]0.0345525[/C][C]0.982724[/C][/ROW]
[ROW][C]245[/C][C]0.0113229[/C][C]0.0226458[/C][C]0.988677[/C][/ROW]
[ROW][C]246[/C][C]0.0156122[/C][C]0.0312243[/C][C]0.984388[/C][/ROW]
[ROW][C]247[/C][C]0.00967953[/C][C]0.0193591[/C][C]0.99032[/C][/ROW]
[ROW][C]248[/C][C]0.277612[/C][C]0.555224[/C][C]0.722388[/C][/ROW]
[ROW][C]249[/C][C]0.30044[/C][C]0.600881[/C][C]0.69956[/C][/ROW]
[ROW][C]250[/C][C]0.455715[/C][C]0.911431[/C][C]0.544285[/C][/ROW]
[ROW][C]251[/C][C]0.454928[/C][C]0.909855[/C][C]0.545072[/C][/ROW]
[ROW][C]252[/C][C]0.834659[/C][C]0.330681[/C][C]0.165341[/C][/ROW]
[ROW][C]253[/C][C]0.904295[/C][C]0.19141[/C][C]0.0957051[/C][/ROW]
[ROW][C]254[/C][C]0.982426[/C][C]0.0351481[/C][C]0.017574[/C][/ROW]
[ROW][C]255[/C][C]0.962579[/C][C]0.0748415[/C][C]0.0374208[/C][/ROW]
[ROW][C]256[/C][C]0.958062[/C][C]0.0838756[/C][C]0.0419378[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226747&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226747&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
80.9978470.004305770.00215289
90.9967940.006411330.00320566
100.9937690.01246130.00623064
110.9950440.009911420.00495571
120.9970530.005893240.00294662
130.9945490.0109020.00545098
140.9904180.0191650.00958249
150.9857440.0285110.0142555
160.9784650.0430710.0215355
170.966480.06704070.0335204
180.9583810.08323850.0416192
190.9627540.07449240.0372462
200.9465940.1068120.053406
210.9300930.1398150.0699075
220.9080080.1839830.0919917
230.8827960.2344080.117204
240.8475280.3049450.152472
250.8159470.3681060.184053
260.9259490.1481030.0740515
270.9053310.1893370.0946687
280.8891180.2217640.110882
290.8644790.2710430.135521
300.8369860.3260290.163014
310.8459130.3081740.154087
320.8166190.3667620.183381
330.7858980.4282040.214102
340.7573850.4852310.242615
350.7131720.5736570.286828
360.745120.509760.25488
370.8065550.3868910.193445
380.7689340.4621330.231066
390.7425220.5149560.257478
400.7539560.4920870.246044
410.7537910.4924170.246209
420.736570.526860.26343
430.7331030.5337940.266897
440.6923450.615310.307655
450.6507160.6985680.349284
460.6227610.7544780.377239
470.6349740.7300510.365026
480.5999270.8001460.400073
490.6369170.7261670.363083
500.6112820.7774360.388718
510.5944030.8111930.405597
520.5572540.8854930.442746
530.5691510.8616980.430849
540.5248030.9503950.475197
550.5488470.9023050.451153
560.5384870.9230260.461513
570.5127910.9744180.487209
580.5411110.9177780.458889
590.5734680.8530640.426532
600.5420230.9159540.457977
610.5671060.8657890.432894
620.5312580.9374840.468742
630.5240280.9519430.475972
640.4856070.9712140.514393
650.4473850.894770.552615
660.4858850.9717690.514115
670.4930230.9860450.506977
680.4753210.9506430.524679
690.4375970.8751940.562403
700.4149710.8299410.585029
710.3759890.7519780.624011
720.3767760.7535510.623224
730.3418980.6837950.658102
740.3223130.6446260.677687
750.3091070.6182140.690893
760.4285470.8570940.571453
770.411650.8232990.58835
780.4369170.8738340.563083
790.3985580.7971160.601442
800.447520.895040.55248
810.4183220.8366430.581678
820.4308370.8616730.569163
830.3941410.7882810.605859
840.3583450.716690.641655
850.3234410.6468830.676559
860.292160.5843210.70784
870.2634640.5269280.736536
880.2398560.4797110.760144
890.3004590.6009170.699541
900.2776550.555310.722345
910.2586080.5172150.741392
920.2308290.4616590.769171
930.215990.431980.78401
940.198660.3973210.80134
950.1737820.3475630.826218
960.1623160.3246320.837684
970.1500360.3000720.849964
980.1294750.258950.870525
990.1267280.2534560.873272
1000.1095590.2191190.890441
1010.1010080.2020160.898992
1020.08675630.1735130.913244
1030.105940.2118810.89406
1040.1176110.2352220.882389
1050.1201740.2403490.879826
1060.1029950.205990.897005
1070.1197270.2394550.880273
1080.1043280.2086560.895672
1090.2520370.5040740.747963
1100.2348420.4696840.765158
1110.209080.4181590.79092
1120.2105740.4211470.789426
1130.1943920.3887850.805608
1140.1781680.3563360.821832
1150.1591620.3183240.840838
1160.1396460.2792920.860354
1170.121530.243060.87847
1180.1497020.2994050.850298
1190.1400010.2800020.859999
1200.1210090.2420180.878991
1210.1085170.2170340.891483
1220.09870820.1974160.901292
1230.120940.241880.87906
1240.1072810.2145630.892719
1250.1068580.2137160.893142
1260.1066090.2132180.893391
1270.09217240.1843450.907828
1280.0828780.1657560.917122
1290.07030140.1406030.929699
1300.07019150.1403830.929808
1310.06865240.1373050.931348
1320.06416970.1283390.93583
1330.05998850.1199770.940011
1340.05043070.1008610.949569
1350.04791540.09583090.952085
1360.1201470.2402940.879853
1370.1046580.2093160.895342
1380.08940040.1788010.9106
1390.0808960.1617920.919104
1400.07775220.1555040.922248
1410.07396840.1479370.926032
1420.06937550.1387510.930625
1430.05987590.1197520.940124
1440.05054270.1010850.949457
1450.04309010.08618020.95691
1460.03591550.0718310.964085
1470.03466170.06932340.965338
1480.04020270.08040530.959797
1490.03620950.07241910.96379
1500.02985270.05970550.970147
1510.03213230.06426460.967868
1520.03081120.06162250.969189
1530.0297860.0595720.970214
1540.02694270.05388530.973057
1550.02980950.0596190.97019
1560.02532870.05065740.974671
1570.0206330.0412660.979367
1580.01780080.03560150.982199
1590.02778140.05556290.972219
1600.02844350.0568870.971557
1610.02523070.05046140.974769
1620.0679250.135850.932075
1630.05688710.1137740.943113
1640.1979360.3958720.802064
1650.1820010.3640020.817999
1660.3060330.6120670.693967
1670.2823380.5646760.717662
1680.2608690.5217390.739131
1690.2374650.4749310.762535
1700.2120440.4240880.787956
1710.2442220.4884450.755778
1720.2169380.4338750.783062
1730.2882610.5765220.711739
1740.2810090.5620180.718991
1750.2569330.5138660.743067
1760.329440.6588790.67056
1770.3044830.6089650.695517
1780.3055340.6110680.694466
1790.2852880.5705760.714712
1800.2665450.533090.733455
1810.2553110.5106220.744689
1820.3357850.671570.664215
1830.311390.6227790.68861
1840.3270230.6540450.672977
1850.3043490.6086970.695651
1860.3714460.7428920.628554
1870.3377750.675550.662225
1880.3051330.6102660.694867
1890.2725790.5451590.727421
1900.3584080.7168170.641592
1910.3541190.7082370.645881
1920.3725480.7450960.627452
1930.3639960.7279930.636004
1940.3283340.6566670.671666
1950.3019090.6038180.698091
1960.3132090.6264190.686791
1970.4172420.8344850.582758
1980.3900730.7801460.609927
1990.3530760.7061520.646924
2000.319740.6394810.68026
2010.2854570.5709140.714543
2020.2526550.505310.747345
2030.2218080.4436160.778192
2040.1916880.3833760.808312
2050.171450.3428990.82855
2060.1460780.2921560.853922
2070.1295230.2590450.870477
2080.1345630.2691270.865437
2090.1124860.2249730.887514
2100.09318710.1863740.906813
2110.07705610.1541120.922944
2120.06330340.1266070.936697
2130.0566660.1133320.943334
2140.06529940.1305990.934701
2150.05354840.1070970.946452
2160.04302220.08604440.956978
2170.03359430.06718860.966406
2180.02785550.0557110.972144
2190.02950620.05901250.970494
2200.02401510.04803010.975985
2210.0296810.0593620.970319
2220.02252030.04504050.97748
2230.01691120.03382250.983089
2240.01795260.03590530.982047
2250.01918890.03837780.980811
2260.01529130.03058260.984709
2270.01271480.02542950.987285
2280.01256760.02513520.987432
2290.01848730.03697450.981513
2300.01739930.03479860.982601
2310.01356330.02712650.986437
2320.01023390.02046770.989766
2330.01266360.02532730.987336
2340.01063830.02127660.989362
2350.01103360.02206720.988966
2360.008687020.0173740.991313
2370.007425240.01485050.992575
2380.005510320.01102060.99449
2390.02054730.04109460.979453
2400.02687030.05374050.97313
2410.0518970.1037940.948103
2420.03689380.07378760.963106
2430.02584120.05168250.974159
2440.01727620.03455250.982724
2450.01132290.02264580.988677
2460.01561220.03122430.984388
2470.009679530.01935910.99032
2480.2776120.5552240.722388
2490.300440.6008810.69956
2500.4557150.9114310.544285
2510.4549280.9098550.545072
2520.8346590.3306810.165341
2530.9042950.191410.0957051
2540.9824260.03514810.017574
2550.9625790.07484150.0374208
2560.9580620.08387560.0419378






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0160643NOK
5% type I error level350.140562NOK
10% type I error level640.257028NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 4 & 0.0160643 & NOK \tabularnewline
5% type I error level & 35 & 0.140562 & NOK \tabularnewline
10% type I error level & 64 & 0.257028 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226747&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]4[/C][C]0.0160643[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]35[/C][C]0.140562[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]64[/C][C]0.257028[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226747&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226747&T=6

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level40.0160643NOK
5% type I error level350.140562NOK
10% type I error level640.257028NOK


Figures (Output of Computation)

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Figure 10
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Input Parameters & R Code

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