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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 computationMon, 18 Nov 2013 18:26:19 -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/18/t1384817275p2aoqgy5mysq4xe.htm/, Retrieved Sat, 27 Apr 2024 10:52:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226310, Retrieved Sat, 27 Apr 2024 10:52:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Decreasing Compet...] [2010-11-17 09:04:39] [b98453cac15ba1066b407e146608df68]
- R PD    [Multiple Regression] [Workshop 7 t waarde] [2013-11-18 23:26:19] [37aff36f52ac1d7cbcd609d857f1662d] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 14 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226310&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226310&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226310&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time14 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 19.4881 + 0.0102426Connected[t] + 0.0132824Separate[t] -0.387502Depression[t] + 0.0902568Learning[t] -0.274769Month[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  19.4881 +  0.0102426Connected[t] +  0.0132824Separate[t] -0.387502Depression[t] +  0.0902568Learning[t] -0.274769Month[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226310&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  19.4881 +  0.0102426Connected[t] +  0.0132824Separate[t] -0.387502Depression[t] +  0.0902568Learning[t] -0.274769Month[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226310&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226310&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 19.4881 + 0.0102426Connected[t] + 0.0132824Separate[t] -0.387502Depression[t] + 0.0902568Learning[t] -0.274769Month[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)19.48812.544867.6583.80486e-131.90243e-13
Connected0.01024260.03743360.27360.7845950.392297
Separate0.01328240.03813840.34830.7279240.363962
Depression-0.3875020.0374877-10.343.50593e-211.75297e-21
Learning0.09025680.05535381.6310.1042060.0521032
Month-0.2747690.170519-1.6110.1083220.0541611

\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) & 19.4881 & 2.54486 & 7.658 & 3.80486e-13 & 1.90243e-13 \tabularnewline
Connected & 0.0102426 & 0.0374336 & 0.2736 & 0.784595 & 0.392297 \tabularnewline
Separate & 0.0132824 & 0.0381384 & 0.3483 & 0.727924 & 0.363962 \tabularnewline
Depression & -0.387502 & 0.0374877 & -10.34 & 3.50593e-21 & 1.75297e-21 \tabularnewline
Learning & 0.0902568 & 0.0553538 & 1.631 & 0.104206 & 0.0521032 \tabularnewline
Month & -0.274769 & 0.170519 & -1.611 & 0.108322 & 0.0541611 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226310&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]19.4881[/C][C]2.54486[/C][C]7.658[/C][C]3.80486e-13[/C][C]1.90243e-13[/C][/ROW]
[ROW][C]Connected[/C][C]0.0102426[/C][C]0.0374336[/C][C]0.2736[/C][C]0.784595[/C][C]0.392297[/C][/ROW]
[ROW][C]Separate[/C][C]0.0132824[/C][C]0.0381384[/C][C]0.3483[/C][C]0.727924[/C][C]0.363962[/C][/ROW]
[ROW][C]Depression[/C][C]-0.387502[/C][C]0.0374877[/C][C]-10.34[/C][C]3.50593e-21[/C][C]1.75297e-21[/C][/ROW]
[ROW][C]Learning[/C][C]0.0902568[/C][C]0.0553538[/C][C]1.631[/C][C]0.104206[/C][C]0.0521032[/C][/ROW]
[ROW][C]Month[/C][C]-0.274769[/C][C]0.170519[/C][C]-1.611[/C][C]0.108322[/C][C]0.0541611[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226310&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226310&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)19.48812.544867.6583.80486e-131.90243e-13
Connected0.01024260.03743360.27360.7845950.392297
Separate0.01328240.03813840.34830.7279240.363962
Depression-0.3875020.0374877-10.343.50593e-211.75297e-21
Learning0.09025680.05535381.6310.1042060.0521032
Month-0.2747690.170519-1.6110.1083220.0541611






Multiple Linear Regression - Regression Statistics
Multiple R0.601126
R-squared0.361352
Adjusted R-squared0.348975
F-TEST (value)29.1957
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01606
Sum Squared Residuals1048.64

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.601126 \tabularnewline
R-squared & 0.361352 \tabularnewline
Adjusted R-squared & 0.348975 \tabularnewline
F-TEST (value) & 29.1957 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 258 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.01606 \tabularnewline
Sum Squared Residuals & 1048.64 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226310&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.601126[/C][/ROW]
[ROW][C]R-squared[/C][C]0.361352[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.348975[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]29.1957[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]258[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.01606[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1048.64[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226310&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226310&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 R0.601126
R-squared0.361352
Adjusted R-squared0.348975
F-TEST (value)29.1957
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01606
Sum Squared Residuals1048.64






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.4632-0.463178
21815.02132.97873
31114.0772-3.0772
41214.4749-2.47485
51610.98095.01906
61814.28223.71782
71411.01622.98376
81414.9329-0.93293
91515.2374-0.237378
101514.21520.78478
111715.38521.61475
121916.17962.82039
131013.5009-3.50087
141613.93852.06154
151815.5042.49601
161413.71010.289906
171413.73780.262218
181715.45171.54825
191415.669-1.66898
201614.17461.82543
211815.54412.45589
221113.7635-2.76354
231414.9842-0.984234
241213.9313-1.93126
251715.11151.88847
26915.907-6.90702
271615.03040.96961
281413.3860.614036
291513.81061.18941
301114.0278-3.02782
311615.61080.389206
321312.98730.012674
331715.19451.80551
341515.0365-0.0364696
351413.9880.0120236
361615.58380.416181
37910.8765-1.87651
381514.43580.56419
391715.29311.70694
401315.3811-2.38108
411515.7758-0.775789
421613.64032.35968
431616.5346-0.53456
441213.6506-1.65056
451514.77740.222615
461113.8143-2.81435
471515.6985-0.698494
481514.89610.103877
491713.52023.47977
501314.8305-1.83051
511615.41680.583232
521413.580.42001
531111.8893-0.889317
541213.8872-1.88725
551214.3178-2.31777
561513.50391.49614
571614.27281.72717
581515.7204-0.720413
591215.3512-3.35116
601213.4569-1.45686
61811.0274-3.02742
621314.6501-1.65009
631114.6224-3.6224
641413.63620.363841
651514.18180.818228
661014.8622-4.8622
671112.6111-1.61113
681214.3809-2.38092
691513.71671.28327
701513.60941.39056
711413.47280.527156
721613.01372.98627
731514.19380.806224
741515.4238-0.423815
751314.6289-1.62888
761211.71020.289819
771714.01742.98257
781312.3570.643003
791513.57481.42522
801315.4346-2.43461
811514.73820.261825
821515.5469-0.546946
831614.26151.73846
841514.22360.77639
851413.89680.103239
861513.87371.12628
871414.3241-0.324109
881313.0941-0.0940693
89710.3456-3.34555
901713.58173.41834
911313.256-0.256024
921514.05010.949931
931412.98141.01859
941313.7655-0.765488
951614.79961.20037
961212.8284-0.828356
971414.6922-0.692249
981714.75262.24742
991514.93490.0650793
1001715.17691.82311
1011212.8284-0.828356
1021614.75571.24429
1031114.5314-3.53142
1041512.84052.15949
105911.386-2.38596
1061614.86641.13364
1071512.92252.07754
1081013.2056-3.20561
109109.521750.478252
1101513.51841.48162
1111113.1278-2.12784
1121314.8846-1.8846
1131412.86731.13269
1141814.00413.99595
1151615.2940.705968
1161413.44830.551714
1171413.8460.153969
1181415.2291-1.22913
1191413.23940.760618
1201212.9307-0.930681
1211413.43560.564356
1221514.55850.441535
1231515.9682-0.968215
1241514.61220.387765
1251314.6778-1.67784
1261715.81871.18125
1271715.36841.63155
1281914.64794.35208
1291513.58281.41722
1301314.6881-1.68809
131910.6048-1.60478
1321515.2107-0.210658
1331512.6862.31401
1341514.23770.762305
1351613.38222.61781
136119.580221.41978
1371413.48240.517626
1381112.3054-1.30537
1391514.37110.628931
1401313.8656-0.865622
1411515.0889-0.0888696
1421613.4682.53203
1431414.3969-0.39692
1441514.15750.842482
1451614.20191.79808
1461614.40141.5986
1471113.7231-2.72313
1481214.6615-2.66152
149911.3347-2.33475
1501613.90022.09981
1511312.42840.571625
1521615.550.450014
1531214.411-2.41101
154911.7571-2.75707
1551311.41771.58229
1561313.256-0.256024
1571413.30790.69206
1581914.64794.35208
1591315.4703-2.47029
1601211.6810.319041
1611312.54010.45986
162108.960841.03916
1631412.78661.21343
1641611.07754.92248
1651011.7107-1.71073
166119.099971.90003
1671413.82480.175184
1681212.6318-0.631813
169912.2919-3.29194
170911.7027-2.70272
1711110.58940.410576
1721614.11991.88009
173913.7835-4.78354
1741311.31951.68048
1751613.25182.74816
1761315.1246-2.12463
177912.166-3.16599
1781211.27940.720554
1791614.58351.4165
1801113.0044-2.00437
1811414.4941-0.494134
1821314.7279-1.72792
1831514.71370.286309
1841414.7587-0.758735
1851613.52242.47758
1861311.35321.64685
1871413.39530.604679
1881513.70991.29008
1891312.69210.307855
1901110.12690.873136
1911113.4976-2.49765
1921414.9553-0.95525
1931512.50232.49772
1941112.5597-1.55967
1951512.96682.03324
1961214.0532-2.05318
1971411.30722.69278
1981412.92671.07332
199811.143-3.14303
2001313.5636-0.563575
201912.028-3.02797
2021513.72351.27649
2031713.9563.04405
2041312.8970.103013
2051514.34660.653415
2061513.60841.39161
2071414.1097-0.109672
2081612.93393.06611
2091312.84050.159502
2101613.9562.04396
211911.7478-2.74777
2121614.29061.70942
2131111.6902-0.690243
2141013.5143-3.51429
2151112.1456-1.1456
2161513.31061.68943
2171714.54042.45962
2181413.93030.069718
21989.94756-1.94756
2201513.28121.71878
2211113.7858-2.78577
2221613.94662.0534
2231011.995-1.99501
2241514.80380.196233
225910.3279-1.32786
2261614.11861.88139
2271914.20934.79072
2281213.8688-1.86883
22989.3325-1.3325
2301113.3243-2.32434
2311413.73570.264317
232912.0109-3.01092
2331515.2016-0.201602
2341312.3610.638996
2351614.92481.07525
2361112.8139-1.81393
2371211.01660.983409
2381313.3288-0.328819
2391014.356-4.35602
2401113.4956-2.49564
2411214.3753-2.3753
242811.0096-3.00957
2431211.82690.173115
2441212.2358-0.235766
2451513.18521.8148
2461110.56060.439388
2471312.70940.290639
248149.249454.75055
2491010.2722-0.272233
2501211.82940.170558
2511512.80262.19743
2521311.54371.45627
2531314.1065-1.10654
2541313.6353-0.635274
2551211.77850.221507
2561212.7033-0.703282
257910.6222-1.62216
258911.4968-2.49677
2591512.6572.34296
2601014.4836-4.48362
2611413.84450.155502
2621513.66141.33857
26379.8213-2.8213
2641413.80130.198709

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 14.4632 & -0.463178 \tabularnewline
2 & 18 & 15.0213 & 2.97873 \tabularnewline
3 & 11 & 14.0772 & -3.0772 \tabularnewline
4 & 12 & 14.4749 & -2.47485 \tabularnewline
5 & 16 & 10.9809 & 5.01906 \tabularnewline
6 & 18 & 14.2822 & 3.71782 \tabularnewline
7 & 14 & 11.0162 & 2.98376 \tabularnewline
8 & 14 & 14.9329 & -0.93293 \tabularnewline
9 & 15 & 15.2374 & -0.237378 \tabularnewline
10 & 15 & 14.2152 & 0.78478 \tabularnewline
11 & 17 & 15.3852 & 1.61475 \tabularnewline
12 & 19 & 16.1796 & 2.82039 \tabularnewline
13 & 10 & 13.5009 & -3.50087 \tabularnewline
14 & 16 & 13.9385 & 2.06154 \tabularnewline
15 & 18 & 15.504 & 2.49601 \tabularnewline
16 & 14 & 13.7101 & 0.289906 \tabularnewline
17 & 14 & 13.7378 & 0.262218 \tabularnewline
18 & 17 & 15.4517 & 1.54825 \tabularnewline
19 & 14 & 15.669 & -1.66898 \tabularnewline
20 & 16 & 14.1746 & 1.82543 \tabularnewline
21 & 18 & 15.5441 & 2.45589 \tabularnewline
22 & 11 & 13.7635 & -2.76354 \tabularnewline
23 & 14 & 14.9842 & -0.984234 \tabularnewline
24 & 12 & 13.9313 & -1.93126 \tabularnewline
25 & 17 & 15.1115 & 1.88847 \tabularnewline
26 & 9 & 15.907 & -6.90702 \tabularnewline
27 & 16 & 15.0304 & 0.96961 \tabularnewline
28 & 14 & 13.386 & 0.614036 \tabularnewline
29 & 15 & 13.8106 & 1.18941 \tabularnewline
30 & 11 & 14.0278 & -3.02782 \tabularnewline
31 & 16 & 15.6108 & 0.389206 \tabularnewline
32 & 13 & 12.9873 & 0.012674 \tabularnewline
33 & 17 & 15.1945 & 1.80551 \tabularnewline
34 & 15 & 15.0365 & -0.0364696 \tabularnewline
35 & 14 & 13.988 & 0.0120236 \tabularnewline
36 & 16 & 15.5838 & 0.416181 \tabularnewline
37 & 9 & 10.8765 & -1.87651 \tabularnewline
38 & 15 & 14.4358 & 0.56419 \tabularnewline
39 & 17 & 15.2931 & 1.70694 \tabularnewline
40 & 13 & 15.3811 & -2.38108 \tabularnewline
41 & 15 & 15.7758 & -0.775789 \tabularnewline
42 & 16 & 13.6403 & 2.35968 \tabularnewline
43 & 16 & 16.5346 & -0.53456 \tabularnewline
44 & 12 & 13.6506 & -1.65056 \tabularnewline
45 & 15 & 14.7774 & 0.222615 \tabularnewline
46 & 11 & 13.8143 & -2.81435 \tabularnewline
47 & 15 & 15.6985 & -0.698494 \tabularnewline
48 & 15 & 14.8961 & 0.103877 \tabularnewline
49 & 17 & 13.5202 & 3.47977 \tabularnewline
50 & 13 & 14.8305 & -1.83051 \tabularnewline
51 & 16 & 15.4168 & 0.583232 \tabularnewline
52 & 14 & 13.58 & 0.42001 \tabularnewline
53 & 11 & 11.8893 & -0.889317 \tabularnewline
54 & 12 & 13.8872 & -1.88725 \tabularnewline
55 & 12 & 14.3178 & -2.31777 \tabularnewline
56 & 15 & 13.5039 & 1.49614 \tabularnewline
57 & 16 & 14.2728 & 1.72717 \tabularnewline
58 & 15 & 15.7204 & -0.720413 \tabularnewline
59 & 12 & 15.3512 & -3.35116 \tabularnewline
60 & 12 & 13.4569 & -1.45686 \tabularnewline
61 & 8 & 11.0274 & -3.02742 \tabularnewline
62 & 13 & 14.6501 & -1.65009 \tabularnewline
63 & 11 & 14.6224 & -3.6224 \tabularnewline
64 & 14 & 13.6362 & 0.363841 \tabularnewline
65 & 15 & 14.1818 & 0.818228 \tabularnewline
66 & 10 & 14.8622 & -4.8622 \tabularnewline
67 & 11 & 12.6111 & -1.61113 \tabularnewline
68 & 12 & 14.3809 & -2.38092 \tabularnewline
69 & 15 & 13.7167 & 1.28327 \tabularnewline
70 & 15 & 13.6094 & 1.39056 \tabularnewline
71 & 14 & 13.4728 & 0.527156 \tabularnewline
72 & 16 & 13.0137 & 2.98627 \tabularnewline
73 & 15 & 14.1938 & 0.806224 \tabularnewline
74 & 15 & 15.4238 & -0.423815 \tabularnewline
75 & 13 & 14.6289 & -1.62888 \tabularnewline
76 & 12 & 11.7102 & 0.289819 \tabularnewline
77 & 17 & 14.0174 & 2.98257 \tabularnewline
78 & 13 & 12.357 & 0.643003 \tabularnewline
79 & 15 & 13.5748 & 1.42522 \tabularnewline
80 & 13 & 15.4346 & -2.43461 \tabularnewline
81 & 15 & 14.7382 & 0.261825 \tabularnewline
82 & 15 & 15.5469 & -0.546946 \tabularnewline
83 & 16 & 14.2615 & 1.73846 \tabularnewline
84 & 15 & 14.2236 & 0.77639 \tabularnewline
85 & 14 & 13.8968 & 0.103239 \tabularnewline
86 & 15 & 13.8737 & 1.12628 \tabularnewline
87 & 14 & 14.3241 & -0.324109 \tabularnewline
88 & 13 & 13.0941 & -0.0940693 \tabularnewline
89 & 7 & 10.3456 & -3.34555 \tabularnewline
90 & 17 & 13.5817 & 3.41834 \tabularnewline
91 & 13 & 13.256 & -0.256024 \tabularnewline
92 & 15 & 14.0501 & 0.949931 \tabularnewline
93 & 14 & 12.9814 & 1.01859 \tabularnewline
94 & 13 & 13.7655 & -0.765488 \tabularnewline
95 & 16 & 14.7996 & 1.20037 \tabularnewline
96 & 12 & 12.8284 & -0.828356 \tabularnewline
97 & 14 & 14.6922 & -0.692249 \tabularnewline
98 & 17 & 14.7526 & 2.24742 \tabularnewline
99 & 15 & 14.9349 & 0.0650793 \tabularnewline
100 & 17 & 15.1769 & 1.82311 \tabularnewline
101 & 12 & 12.8284 & -0.828356 \tabularnewline
102 & 16 & 14.7557 & 1.24429 \tabularnewline
103 & 11 & 14.5314 & -3.53142 \tabularnewline
104 & 15 & 12.8405 & 2.15949 \tabularnewline
105 & 9 & 11.386 & -2.38596 \tabularnewline
106 & 16 & 14.8664 & 1.13364 \tabularnewline
107 & 15 & 12.9225 & 2.07754 \tabularnewline
108 & 10 & 13.2056 & -3.20561 \tabularnewline
109 & 10 & 9.52175 & 0.478252 \tabularnewline
110 & 15 & 13.5184 & 1.48162 \tabularnewline
111 & 11 & 13.1278 & -2.12784 \tabularnewline
112 & 13 & 14.8846 & -1.8846 \tabularnewline
113 & 14 & 12.8673 & 1.13269 \tabularnewline
114 & 18 & 14.0041 & 3.99595 \tabularnewline
115 & 16 & 15.294 & 0.705968 \tabularnewline
116 & 14 & 13.4483 & 0.551714 \tabularnewline
117 & 14 & 13.846 & 0.153969 \tabularnewline
118 & 14 & 15.2291 & -1.22913 \tabularnewline
119 & 14 & 13.2394 & 0.760618 \tabularnewline
120 & 12 & 12.9307 & -0.930681 \tabularnewline
121 & 14 & 13.4356 & 0.564356 \tabularnewline
122 & 15 & 14.5585 & 0.441535 \tabularnewline
123 & 15 & 15.9682 & -0.968215 \tabularnewline
124 & 15 & 14.6122 & 0.387765 \tabularnewline
125 & 13 & 14.6778 & -1.67784 \tabularnewline
126 & 17 & 15.8187 & 1.18125 \tabularnewline
127 & 17 & 15.3684 & 1.63155 \tabularnewline
128 & 19 & 14.6479 & 4.35208 \tabularnewline
129 & 15 & 13.5828 & 1.41722 \tabularnewline
130 & 13 & 14.6881 & -1.68809 \tabularnewline
131 & 9 & 10.6048 & -1.60478 \tabularnewline
132 & 15 & 15.2107 & -0.210658 \tabularnewline
133 & 15 & 12.686 & 2.31401 \tabularnewline
134 & 15 & 14.2377 & 0.762305 \tabularnewline
135 & 16 & 13.3822 & 2.61781 \tabularnewline
136 & 11 & 9.58022 & 1.41978 \tabularnewline
137 & 14 & 13.4824 & 0.517626 \tabularnewline
138 & 11 & 12.3054 & -1.30537 \tabularnewline
139 & 15 & 14.3711 & 0.628931 \tabularnewline
140 & 13 & 13.8656 & -0.865622 \tabularnewline
141 & 15 & 15.0889 & -0.0888696 \tabularnewline
142 & 16 & 13.468 & 2.53203 \tabularnewline
143 & 14 & 14.3969 & -0.39692 \tabularnewline
144 & 15 & 14.1575 & 0.842482 \tabularnewline
145 & 16 & 14.2019 & 1.79808 \tabularnewline
146 & 16 & 14.4014 & 1.5986 \tabularnewline
147 & 11 & 13.7231 & -2.72313 \tabularnewline
148 & 12 & 14.6615 & -2.66152 \tabularnewline
149 & 9 & 11.3347 & -2.33475 \tabularnewline
150 & 16 & 13.9002 & 2.09981 \tabularnewline
151 & 13 & 12.4284 & 0.571625 \tabularnewline
152 & 16 & 15.55 & 0.450014 \tabularnewline
153 & 12 & 14.411 & -2.41101 \tabularnewline
154 & 9 & 11.7571 & -2.75707 \tabularnewline
155 & 13 & 11.4177 & 1.58229 \tabularnewline
156 & 13 & 13.256 & -0.256024 \tabularnewline
157 & 14 & 13.3079 & 0.69206 \tabularnewline
158 & 19 & 14.6479 & 4.35208 \tabularnewline
159 & 13 & 15.4703 & -2.47029 \tabularnewline
160 & 12 & 11.681 & 0.319041 \tabularnewline
161 & 13 & 12.5401 & 0.45986 \tabularnewline
162 & 10 & 8.96084 & 1.03916 \tabularnewline
163 & 14 & 12.7866 & 1.21343 \tabularnewline
164 & 16 & 11.0775 & 4.92248 \tabularnewline
165 & 10 & 11.7107 & -1.71073 \tabularnewline
166 & 11 & 9.09997 & 1.90003 \tabularnewline
167 & 14 & 13.8248 & 0.175184 \tabularnewline
168 & 12 & 12.6318 & -0.631813 \tabularnewline
169 & 9 & 12.2919 & -3.29194 \tabularnewline
170 & 9 & 11.7027 & -2.70272 \tabularnewline
171 & 11 & 10.5894 & 0.410576 \tabularnewline
172 & 16 & 14.1199 & 1.88009 \tabularnewline
173 & 9 & 13.7835 & -4.78354 \tabularnewline
174 & 13 & 11.3195 & 1.68048 \tabularnewline
175 & 16 & 13.2518 & 2.74816 \tabularnewline
176 & 13 & 15.1246 & -2.12463 \tabularnewline
177 & 9 & 12.166 & -3.16599 \tabularnewline
178 & 12 & 11.2794 & 0.720554 \tabularnewline
179 & 16 & 14.5835 & 1.4165 \tabularnewline
180 & 11 & 13.0044 & -2.00437 \tabularnewline
181 & 14 & 14.4941 & -0.494134 \tabularnewline
182 & 13 & 14.7279 & -1.72792 \tabularnewline
183 & 15 & 14.7137 & 0.286309 \tabularnewline
184 & 14 & 14.7587 & -0.758735 \tabularnewline
185 & 16 & 13.5224 & 2.47758 \tabularnewline
186 & 13 & 11.3532 & 1.64685 \tabularnewline
187 & 14 & 13.3953 & 0.604679 \tabularnewline
188 & 15 & 13.7099 & 1.29008 \tabularnewline
189 & 13 & 12.6921 & 0.307855 \tabularnewline
190 & 11 & 10.1269 & 0.873136 \tabularnewline
191 & 11 & 13.4976 & -2.49765 \tabularnewline
192 & 14 & 14.9553 & -0.95525 \tabularnewline
193 & 15 & 12.5023 & 2.49772 \tabularnewline
194 & 11 & 12.5597 & -1.55967 \tabularnewline
195 & 15 & 12.9668 & 2.03324 \tabularnewline
196 & 12 & 14.0532 & -2.05318 \tabularnewline
197 & 14 & 11.3072 & 2.69278 \tabularnewline
198 & 14 & 12.9267 & 1.07332 \tabularnewline
199 & 8 & 11.143 & -3.14303 \tabularnewline
200 & 13 & 13.5636 & -0.563575 \tabularnewline
201 & 9 & 12.028 & -3.02797 \tabularnewline
202 & 15 & 13.7235 & 1.27649 \tabularnewline
203 & 17 & 13.956 & 3.04405 \tabularnewline
204 & 13 & 12.897 & 0.103013 \tabularnewline
205 & 15 & 14.3466 & 0.653415 \tabularnewline
206 & 15 & 13.6084 & 1.39161 \tabularnewline
207 & 14 & 14.1097 & -0.109672 \tabularnewline
208 & 16 & 12.9339 & 3.06611 \tabularnewline
209 & 13 & 12.8405 & 0.159502 \tabularnewline
210 & 16 & 13.956 & 2.04396 \tabularnewline
211 & 9 & 11.7478 & -2.74777 \tabularnewline
212 & 16 & 14.2906 & 1.70942 \tabularnewline
213 & 11 & 11.6902 & -0.690243 \tabularnewline
214 & 10 & 13.5143 & -3.51429 \tabularnewline
215 & 11 & 12.1456 & -1.1456 \tabularnewline
216 & 15 & 13.3106 & 1.68943 \tabularnewline
217 & 17 & 14.5404 & 2.45962 \tabularnewline
218 & 14 & 13.9303 & 0.069718 \tabularnewline
219 & 8 & 9.94756 & -1.94756 \tabularnewline
220 & 15 & 13.2812 & 1.71878 \tabularnewline
221 & 11 & 13.7858 & -2.78577 \tabularnewline
222 & 16 & 13.9466 & 2.0534 \tabularnewline
223 & 10 & 11.995 & -1.99501 \tabularnewline
224 & 15 & 14.8038 & 0.196233 \tabularnewline
225 & 9 & 10.3279 & -1.32786 \tabularnewline
226 & 16 & 14.1186 & 1.88139 \tabularnewline
227 & 19 & 14.2093 & 4.79072 \tabularnewline
228 & 12 & 13.8688 & -1.86883 \tabularnewline
229 & 8 & 9.3325 & -1.3325 \tabularnewline
230 & 11 & 13.3243 & -2.32434 \tabularnewline
231 & 14 & 13.7357 & 0.264317 \tabularnewline
232 & 9 & 12.0109 & -3.01092 \tabularnewline
233 & 15 & 15.2016 & -0.201602 \tabularnewline
234 & 13 & 12.361 & 0.638996 \tabularnewline
235 & 16 & 14.9248 & 1.07525 \tabularnewline
236 & 11 & 12.8139 & -1.81393 \tabularnewline
237 & 12 & 11.0166 & 0.983409 \tabularnewline
238 & 13 & 13.3288 & -0.328819 \tabularnewline
239 & 10 & 14.356 & -4.35602 \tabularnewline
240 & 11 & 13.4956 & -2.49564 \tabularnewline
241 & 12 & 14.3753 & -2.3753 \tabularnewline
242 & 8 & 11.0096 & -3.00957 \tabularnewline
243 & 12 & 11.8269 & 0.173115 \tabularnewline
244 & 12 & 12.2358 & -0.235766 \tabularnewline
245 & 15 & 13.1852 & 1.8148 \tabularnewline
246 & 11 & 10.5606 & 0.439388 \tabularnewline
247 & 13 & 12.7094 & 0.290639 \tabularnewline
248 & 14 & 9.24945 & 4.75055 \tabularnewline
249 & 10 & 10.2722 & -0.272233 \tabularnewline
250 & 12 & 11.8294 & 0.170558 \tabularnewline
251 & 15 & 12.8026 & 2.19743 \tabularnewline
252 & 13 & 11.5437 & 1.45627 \tabularnewline
253 & 13 & 14.1065 & -1.10654 \tabularnewline
254 & 13 & 13.6353 & -0.635274 \tabularnewline
255 & 12 & 11.7785 & 0.221507 \tabularnewline
256 & 12 & 12.7033 & -0.703282 \tabularnewline
257 & 9 & 10.6222 & -1.62216 \tabularnewline
258 & 9 & 11.4968 & -2.49677 \tabularnewline
259 & 15 & 12.657 & 2.34296 \tabularnewline
260 & 10 & 14.4836 & -4.48362 \tabularnewline
261 & 14 & 13.8445 & 0.155502 \tabularnewline
262 & 15 & 13.6614 & 1.33857 \tabularnewline
263 & 7 & 9.8213 & -2.8213 \tabularnewline
264 & 14 & 13.8013 & 0.198709 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226310&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]14[/C][C]14.4632[/C][C]-0.463178[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.0213[/C][C]2.97873[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]14.0772[/C][C]-3.0772[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.4749[/C][C]-2.47485[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]10.9809[/C][C]5.01906[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.2822[/C][C]3.71782[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]11.0162[/C][C]2.98376[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.9329[/C][C]-0.93293[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.2374[/C][C]-0.237378[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.2152[/C][C]0.78478[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.3852[/C][C]1.61475[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]16.1796[/C][C]2.82039[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.5009[/C][C]-3.50087[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.9385[/C][C]2.06154[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.504[/C][C]2.49601[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.7101[/C][C]0.289906[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.7378[/C][C]0.262218[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.4517[/C][C]1.54825[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.669[/C][C]-1.66898[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]14.1746[/C][C]1.82543[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.5441[/C][C]2.45589[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.7635[/C][C]-2.76354[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.9842[/C][C]-0.984234[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.9313[/C][C]-1.93126[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.1115[/C][C]1.88847[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.907[/C][C]-6.90702[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.0304[/C][C]0.96961[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.386[/C][C]0.614036[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.8106[/C][C]1.18941[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]14.0278[/C][C]-3.02782[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.6108[/C][C]0.389206[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.9873[/C][C]0.012674[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]15.1945[/C][C]1.80551[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.0365[/C][C]-0.0364696[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.988[/C][C]0.0120236[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.5838[/C][C]0.416181[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.8765[/C][C]-1.87651[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.4358[/C][C]0.56419[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.2931[/C][C]1.70694[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.3811[/C][C]-2.38108[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.7758[/C][C]-0.775789[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.6403[/C][C]2.35968[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]16.5346[/C][C]-0.53456[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.6506[/C][C]-1.65056[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.7774[/C][C]0.222615[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.8143[/C][C]-2.81435[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.6985[/C][C]-0.698494[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.8961[/C][C]0.103877[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.5202[/C][C]3.47977[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.8305[/C][C]-1.83051[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.4168[/C][C]0.583232[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.58[/C][C]0.42001[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.8893[/C][C]-0.889317[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.8872[/C][C]-1.88725[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.3178[/C][C]-2.31777[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.5039[/C][C]1.49614[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.2728[/C][C]1.72717[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.7204[/C][C]-0.720413[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.3512[/C][C]-3.35116[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.4569[/C][C]-1.45686[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]11.0274[/C][C]-3.02742[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.6501[/C][C]-1.65009[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.6224[/C][C]-3.6224[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.6362[/C][C]0.363841[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]14.1818[/C][C]0.818228[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]14.8622[/C][C]-4.8622[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.6111[/C][C]-1.61113[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.3809[/C][C]-2.38092[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.7167[/C][C]1.28327[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.6094[/C][C]1.39056[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.4728[/C][C]0.527156[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]13.0137[/C][C]2.98627[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.1938[/C][C]0.806224[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.4238[/C][C]-0.423815[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.6289[/C][C]-1.62888[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]11.7102[/C][C]0.289819[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]14.0174[/C][C]2.98257[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.357[/C][C]0.643003[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.5748[/C][C]1.42522[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]15.4346[/C][C]-2.43461[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.7382[/C][C]0.261825[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.5469[/C][C]-0.546946[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.2615[/C][C]1.73846[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2236[/C][C]0.77639[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]13.8968[/C][C]0.103239[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.8737[/C][C]1.12628[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.3241[/C][C]-0.324109[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]13.0941[/C][C]-0.0940693[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.3456[/C][C]-3.34555[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.5817[/C][C]3.41834[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]13.256[/C][C]-0.256024[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.0501[/C][C]0.949931[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]12.9814[/C][C]1.01859[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.7655[/C][C]-0.765488[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.7996[/C][C]1.20037[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.8284[/C][C]-0.828356[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.6922[/C][C]-0.692249[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.7526[/C][C]2.24742[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]14.9349[/C][C]0.0650793[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.1769[/C][C]1.82311[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.8284[/C][C]-0.828356[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]14.7557[/C][C]1.24429[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.5314[/C][C]-3.53142[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]12.8405[/C][C]2.15949[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.386[/C][C]-2.38596[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.8664[/C][C]1.13364[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9225[/C][C]2.07754[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]13.2056[/C][C]-3.20561[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.52175[/C][C]0.478252[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.5184[/C][C]1.48162[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.1278[/C][C]-2.12784[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]14.8846[/C][C]-1.8846[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]12.8673[/C][C]1.13269[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.0041[/C][C]3.99595[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.294[/C][C]0.705968[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.4483[/C][C]0.551714[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.846[/C][C]0.153969[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.2291[/C][C]-1.22913[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.2394[/C][C]0.760618[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.9307[/C][C]-0.930681[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.4356[/C][C]0.564356[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.5585[/C][C]0.441535[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.9682[/C][C]-0.968215[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.6122[/C][C]0.387765[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.6778[/C][C]-1.67784[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]15.8187[/C][C]1.18125[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.3684[/C][C]1.63155[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.6479[/C][C]4.35208[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5828[/C][C]1.41722[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.6881[/C][C]-1.68809[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.6048[/C][C]-1.60478[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.2107[/C][C]-0.210658[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.686[/C][C]2.31401[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.2377[/C][C]0.762305[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.3822[/C][C]2.61781[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.58022[/C][C]1.41978[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.4824[/C][C]0.517626[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]12.3054[/C][C]-1.30537[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.3711[/C][C]0.628931[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.8656[/C][C]-0.865622[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]15.0889[/C][C]-0.0888696[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.468[/C][C]2.53203[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.3969[/C][C]-0.39692[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.1575[/C][C]0.842482[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.2019[/C][C]1.79808[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.4014[/C][C]1.5986[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.7231[/C][C]-2.72313[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.6615[/C][C]-2.66152[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.3347[/C][C]-2.33475[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]13.9002[/C][C]2.09981[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.4284[/C][C]0.571625[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.55[/C][C]0.450014[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.411[/C][C]-2.41101[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.7571[/C][C]-2.75707[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.4177[/C][C]1.58229[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]13.256[/C][C]-0.256024[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.3079[/C][C]0.69206[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.6479[/C][C]4.35208[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.4703[/C][C]-2.47029[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.681[/C][C]0.319041[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.5401[/C][C]0.45986[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]8.96084[/C][C]1.03916[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]12.7866[/C][C]1.21343[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.0775[/C][C]4.92248[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.7107[/C][C]-1.71073[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]9.09997[/C][C]1.90003[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]13.8248[/C][C]0.175184[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.6318[/C][C]-0.631813[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.2919[/C][C]-3.29194[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.7027[/C][C]-2.70272[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.5894[/C][C]0.410576[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.1199[/C][C]1.88009[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]13.7835[/C][C]-4.78354[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.3195[/C][C]1.68048[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.2518[/C][C]2.74816[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.1246[/C][C]-2.12463[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.166[/C][C]-3.16599[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.2794[/C][C]0.720554[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.5835[/C][C]1.4165[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.0044[/C][C]-2.00437[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]14.4941[/C][C]-0.494134[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.7279[/C][C]-1.72792[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.7137[/C][C]0.286309[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.7587[/C][C]-0.758735[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]13.5224[/C][C]2.47758[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.3532[/C][C]1.64685[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.3953[/C][C]0.604679[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]13.7099[/C][C]1.29008[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.6921[/C][C]0.307855[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.1269[/C][C]0.873136[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]13.4976[/C][C]-2.49765[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.9553[/C][C]-0.95525[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.5023[/C][C]2.49772[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.5597[/C][C]-1.55967[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]12.9668[/C][C]2.03324[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.0532[/C][C]-2.05318[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.3072[/C][C]2.69278[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]12.9267[/C][C]1.07332[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.143[/C][C]-3.14303[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.5636[/C][C]-0.563575[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.028[/C][C]-3.02797[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.7235[/C][C]1.27649[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]13.956[/C][C]3.04405[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.897[/C][C]0.103013[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.3466[/C][C]0.653415[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.6084[/C][C]1.39161[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.1097[/C][C]-0.109672[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.9339[/C][C]3.06611[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.8405[/C][C]0.159502[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]13.956[/C][C]2.04396[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.7478[/C][C]-2.74777[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.2906[/C][C]1.70942[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]11.6902[/C][C]-0.690243[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.5143[/C][C]-3.51429[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.1456[/C][C]-1.1456[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.3106[/C][C]1.68943[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.5404[/C][C]2.45962[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.9303[/C][C]0.069718[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.94756[/C][C]-1.94756[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.2812[/C][C]1.71878[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.7858[/C][C]-2.78577[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.9466[/C][C]2.0534[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]11.995[/C][C]-1.99501[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.8038[/C][C]0.196233[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]10.3279[/C][C]-1.32786[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.1186[/C][C]1.88139[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]14.2093[/C][C]4.79072[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.8688[/C][C]-1.86883[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.3325[/C][C]-1.3325[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.3243[/C][C]-2.32434[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.7357[/C][C]0.264317[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]12.0109[/C][C]-3.01092[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]15.2016[/C][C]-0.201602[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.361[/C][C]0.638996[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]14.9248[/C][C]1.07525[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.8139[/C][C]-1.81393[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.0166[/C][C]0.983409[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.3288[/C][C]-0.328819[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.356[/C][C]-4.35602[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.4956[/C][C]-2.49564[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.3753[/C][C]-2.3753[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]11.0096[/C][C]-3.00957[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.8269[/C][C]0.173115[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.2358[/C][C]-0.235766[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.1852[/C][C]1.8148[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.5606[/C][C]0.439388[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.7094[/C][C]0.290639[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]9.24945[/C][C]4.75055[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.2722[/C][C]-0.272233[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.8294[/C][C]0.170558[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.8026[/C][C]2.19743[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.5437[/C][C]1.45627[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.1065[/C][C]-1.10654[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.6353[/C][C]-0.635274[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.7785[/C][C]0.221507[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.7033[/C][C]-0.703282[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.6222[/C][C]-1.62216[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.4968[/C][C]-2.49677[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.657[/C][C]2.34296[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.4836[/C][C]-4.48362[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.8445[/C][C]0.155502[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.6614[/C][C]1.33857[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.8213[/C][C]-2.8213[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.8013[/C][C]0.198709[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226310&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226310&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.4632-0.463178
21815.02132.97873
31114.0772-3.0772
41214.4749-2.47485
51610.98095.01906
61814.28223.71782
71411.01622.98376
81414.9329-0.93293
91515.2374-0.237378
101514.21520.78478
111715.38521.61475
121916.17962.82039
131013.5009-3.50087
141613.93852.06154
151815.5042.49601
161413.71010.289906
171413.73780.262218
181715.45171.54825
191415.669-1.66898
201614.17461.82543
211815.54412.45589
221113.7635-2.76354
231414.9842-0.984234
241213.9313-1.93126
251715.11151.88847
26915.907-6.90702
271615.03040.96961
281413.3860.614036
291513.81061.18941
301114.0278-3.02782
311615.61080.389206
321312.98730.012674
331715.19451.80551
341515.0365-0.0364696
351413.9880.0120236
361615.58380.416181
37910.8765-1.87651
381514.43580.56419
391715.29311.70694
401315.3811-2.38108
411515.7758-0.775789
421613.64032.35968
431616.5346-0.53456
441213.6506-1.65056
451514.77740.222615
461113.8143-2.81435
471515.6985-0.698494
481514.89610.103877
491713.52023.47977
501314.8305-1.83051
511615.41680.583232
521413.580.42001
531111.8893-0.889317
541213.8872-1.88725
551214.3178-2.31777
561513.50391.49614
571614.27281.72717
581515.7204-0.720413
591215.3512-3.35116
601213.4569-1.45686
61811.0274-3.02742
621314.6501-1.65009
631114.6224-3.6224
641413.63620.363841
651514.18180.818228
661014.8622-4.8622
671112.6111-1.61113
681214.3809-2.38092
691513.71671.28327
701513.60941.39056
711413.47280.527156
721613.01372.98627
731514.19380.806224
741515.4238-0.423815
751314.6289-1.62888
761211.71020.289819
771714.01742.98257
781312.3570.643003
791513.57481.42522
801315.4346-2.43461
811514.73820.261825
821515.5469-0.546946
831614.26151.73846
841514.22360.77639
851413.89680.103239
861513.87371.12628
871414.3241-0.324109
881313.0941-0.0940693
89710.3456-3.34555
901713.58173.41834
911313.256-0.256024
921514.05010.949931
931412.98141.01859
941313.7655-0.765488
951614.79961.20037
961212.8284-0.828356
971414.6922-0.692249
981714.75262.24742
991514.93490.0650793
1001715.17691.82311
1011212.8284-0.828356
1021614.75571.24429
1031114.5314-3.53142
1041512.84052.15949
105911.386-2.38596
1061614.86641.13364
1071512.92252.07754
1081013.2056-3.20561
109109.521750.478252
1101513.51841.48162
1111113.1278-2.12784
1121314.8846-1.8846
1131412.86731.13269
1141814.00413.99595
1151615.2940.705968
1161413.44830.551714
1171413.8460.153969
1181415.2291-1.22913
1191413.23940.760618
1201212.9307-0.930681
1211413.43560.564356
1221514.55850.441535
1231515.9682-0.968215
1241514.61220.387765
1251314.6778-1.67784
1261715.81871.18125
1271715.36841.63155
1281914.64794.35208
1291513.58281.41722
1301314.6881-1.68809
131910.6048-1.60478
1321515.2107-0.210658
1331512.6862.31401
1341514.23770.762305
1351613.38222.61781
136119.580221.41978
1371413.48240.517626
1381112.3054-1.30537
1391514.37110.628931
1401313.8656-0.865622
1411515.0889-0.0888696
1421613.4682.53203
1431414.3969-0.39692
1441514.15750.842482
1451614.20191.79808
1461614.40141.5986
1471113.7231-2.72313
1481214.6615-2.66152
149911.3347-2.33475
1501613.90022.09981
1511312.42840.571625
1521615.550.450014
1531214.411-2.41101
154911.7571-2.75707
1551311.41771.58229
1561313.256-0.256024
1571413.30790.69206
1581914.64794.35208
1591315.4703-2.47029
1601211.6810.319041
1611312.54010.45986
162108.960841.03916
1631412.78661.21343
1641611.07754.92248
1651011.7107-1.71073
166119.099971.90003
1671413.82480.175184
1681212.6318-0.631813
169912.2919-3.29194
170911.7027-2.70272
1711110.58940.410576
1721614.11991.88009
173913.7835-4.78354
1741311.31951.68048
1751613.25182.74816
1761315.1246-2.12463
177912.166-3.16599
1781211.27940.720554
1791614.58351.4165
1801113.0044-2.00437
1811414.4941-0.494134
1821314.7279-1.72792
1831514.71370.286309
1841414.7587-0.758735
1851613.52242.47758
1861311.35321.64685
1871413.39530.604679
1881513.70991.29008
1891312.69210.307855
1901110.12690.873136
1911113.4976-2.49765
1921414.9553-0.95525
1931512.50232.49772
1941112.5597-1.55967
1951512.96682.03324
1961214.0532-2.05318
1971411.30722.69278
1981412.92671.07332
199811.143-3.14303
2001313.5636-0.563575
201912.028-3.02797
2021513.72351.27649
2031713.9563.04405
2041312.8970.103013
2051514.34660.653415
2061513.60841.39161
2071414.1097-0.109672
2081612.93393.06611
2091312.84050.159502
2101613.9562.04396
211911.7478-2.74777
2121614.29061.70942
2131111.6902-0.690243
2141013.5143-3.51429
2151112.1456-1.1456
2161513.31061.68943
2171714.54042.45962
2181413.93030.069718
21989.94756-1.94756
2201513.28121.71878
2211113.7858-2.78577
2221613.94662.0534
2231011.995-1.99501
2241514.80380.196233
225910.3279-1.32786
2261614.11861.88139
2271914.20934.79072
2281213.8688-1.86883
22989.3325-1.3325
2301113.3243-2.32434
2311413.73570.264317
232912.0109-3.01092
2331515.2016-0.201602
2341312.3610.638996
2351614.92481.07525
2361112.8139-1.81393
2371211.01660.983409
2381313.3288-0.328819
2391014.356-4.35602
2401113.4956-2.49564
2411214.3753-2.3753
242811.0096-3.00957
2431211.82690.173115
2441212.2358-0.235766
2451513.18521.8148
2461110.56060.439388
2471312.70940.290639
248149.249454.75055
2491010.2722-0.272233
2501211.82940.170558
2511512.80262.19743
2521311.54371.45627
2531314.1065-1.10654
2541313.6353-0.635274
2551211.77850.221507
2561212.7033-0.703282
257910.6222-1.62216
258911.4968-2.49677
2591512.6572.34296
2601014.4836-4.48362
2611413.84450.155502
2621513.66141.33857
26379.8213-2.8213
2641413.80130.198709






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.7533770.4932460.246623
100.6612390.6775220.338761
110.5551640.8896730.444836
120.806390.387220.19361
130.956370.08725910.0436296
140.9508390.09832240.0491612
150.9804870.03902540.0195127
160.9686060.0627870.0313935
170.9573050.08538970.0426949
180.9480560.1038880.051944
190.9419910.1160190.0580093
200.9267070.1465860.0732931
210.9279480.1441030.0720517
220.955540.08891910.0444595
230.9423290.1153420.0576708
240.9388950.1222090.0611046
250.9202720.1594560.0797279
260.9980070.003986050.00199302
270.9970780.005844890.00292244
280.9955360.008928770.00446439
290.9935320.01293560.00646781
300.9966870.006625750.00331287
310.9950940.009811420.00490571
320.9932960.0134070.00670352
330.9917220.01655590.00827797
340.9882070.02358580.0117929
350.9841070.03178570.0158928
360.9781940.04361230.0218061
370.983310.03338040.0166902
380.9774420.04511510.0225576
390.9748510.05029840.0251492
400.9765080.04698360.0234918
410.9699340.06013240.0300662
420.9692210.06155830.0307791
430.9600380.07992470.0399624
440.9581560.08368770.0418438
450.946530.106940.0534701
460.9555040.08899230.0444962
470.9436540.1126920.0563461
480.9292560.1414880.0707442
490.9490040.1019920.0509958
500.9447420.1105150.0552576
510.9322320.1355360.0677678
520.9165580.1668840.0834422
530.9047120.1905760.095288
540.9031270.1937460.096873
550.899230.2015410.10077
560.8889150.2221690.111085
570.8800130.2399740.119987
580.8585390.2829220.141461
590.8856180.2287650.114382
600.8793570.2412860.120643
610.908480.183040.09152
620.9026160.1947670.0973837
630.9345090.1309820.0654909
640.9210210.1579570.0789786
650.9064810.1870380.093519
660.9173980.1652040.0826021
670.913320.173360.0866799
680.9055310.1889380.0944692
690.9315930.1368140.0684068
700.9366840.1266310.0633155
710.9289590.1420820.0710409
720.9478170.1043660.052183
730.9387160.1225690.0612843
740.9262180.1475650.0737823
750.9169030.1661930.0830967
760.9012260.1975490.0987745
770.918280.1634390.0817195
780.9039430.1921130.0960565
790.8971570.2056850.102843
800.8982520.2034960.101748
810.8805440.2389130.119456
820.8615740.2768520.138426
830.8560580.2878850.143942
840.8365410.3269180.163459
850.8122030.3755950.187797
860.7898610.4202780.210139
870.7624950.475010.237505
880.7324690.5350620.267531
890.7983020.4033960.201698
900.835290.3294210.16471
910.8117420.3765160.188258
920.788420.4231610.21158
930.768990.462020.23101
940.7442770.5114460.255723
950.7213410.5573180.278659
960.6981540.6036930.301846
970.6695170.6609660.330483
980.6728810.6542380.327119
990.6390210.7219580.360979
1000.6262680.7474630.373732
1010.6009980.7980040.399002
1020.5752950.8494090.424705
1030.6419950.7160090.358005
1040.6359230.7281540.364077
1050.6574250.6851490.342575
1060.6313570.7372850.368643
1070.6217030.7565940.378297
1080.6830690.6338610.316931
1090.6543530.6912940.345647
1100.6358290.7283420.364171
1110.642830.7143410.35717
1120.6504550.699090.349545
1130.6257880.7484230.374212
1140.7083020.5833950.291698
1150.6807560.6384890.319244
1160.6505920.6988160.349408
1170.6189080.7621850.381092
1180.600730.7985410.39927
1190.5685460.8629080.431454
1200.5442550.911490.455745
1210.5151530.9696940.484847
1220.4809040.9618090.519096
1230.4569830.9139660.543017
1240.4231630.8463260.576837
1250.4149630.8299260.585037
1260.3893190.7786380.610681
1270.370590.7411790.62941
1280.489730.979460.51027
1290.4683730.9367470.531627
1300.459490.9189790.54051
1310.447940.8958810.55206
1320.4150860.8301720.584914
1330.4255190.8510370.574481
1340.3952910.7905810.604709
1350.4171220.8342430.582878
1360.3996240.7992470.600376
1370.3675490.7350980.632451
1380.35070.7013990.6493
1390.3206970.6413940.679303
1400.2962520.5925050.703748
1410.2661690.5323380.733831
1420.2839150.567830.716085
1430.2553060.5106120.744694
1440.232940.465880.76706
1450.2249790.4499580.775021
1460.2158980.4317960.784102
1470.2373630.4747270.762637
1480.2582010.5164020.741799
1490.2723510.5447020.727649
1500.2758170.5516350.724183
1510.2499220.4998430.750078
1520.2248530.4497070.775147
1530.2343830.4687660.765617
1540.2747640.5495270.725236
1550.2539230.5078460.746077
1560.2319890.4639780.768011
1570.205730.411460.79427
1580.3000090.6000170.699991
1590.3249590.6499180.675041
1600.2929030.5858070.707097
1610.26230.5246010.7377
1620.2365040.4730070.763496
1630.2132770.4265540.786723
1640.3430880.6861760.656912
1650.3386070.6772140.661393
1660.3322790.6645580.667721
1670.3002760.6005510.699724
1680.2761510.5523020.723849
1690.3306420.6612840.669358
1700.3562770.7125540.643723
1710.3250730.6501460.674927
1720.3198480.6396950.680152
1730.4859360.9718710.514064
1740.4702030.9404060.529797
1750.4961820.9923630.503818
1760.5054470.9891060.494553
1770.5575560.8848880.442444
1780.5251120.9497760.474888
1790.5022240.9955520.497776
1800.5002440.9995120.499756
1810.464590.9291790.53541
1820.4571780.9143570.542822
1830.419120.838240.58088
1840.3887530.7775060.611247
1850.4098450.819690.590155
1860.4018040.8036070.598196
1870.3661470.7322940.633853
1880.3398250.6796510.660175
1890.305710.611420.69429
1900.2860910.5721820.713909
1910.3005360.6010710.699464
1920.2772990.5545980.722701
1930.2991360.5982720.700864
1940.2841340.5682690.715866
1950.2852060.5704120.714794
1960.2920460.5840910.707954
1970.3258730.6517460.674127
1980.2994380.5988760.700562
1990.3351650.670330.664835
2000.3000490.6000970.699951
2010.3380860.6761730.661914
2020.3171180.6342360.682882
2030.3650020.7300030.634998
2040.3260620.6521240.673938
2050.290440.5808810.70956
2060.2690140.5380280.730986
2070.2346310.4692630.765369
2080.2759560.5519130.724044
2090.2413610.4827210.758639
2100.2409310.4818630.759069
2110.2575420.5150850.742458
2120.2515260.5030520.748474
2130.2178840.4357690.782116
2140.2795310.5590630.720469
2150.2516670.5033350.748333
2160.2395020.4790040.760498
2170.2554180.5108370.744582
2180.2189740.4379480.781026
2190.2086950.417390.791305
2200.2053320.4106640.794668
2210.2232130.4464260.776787
2220.2319420.4638850.768058
2230.2230880.4461750.776912
2240.1900980.3801970.809902
2250.1662640.3325280.833736
2260.1934530.3869050.806547
2270.4626770.9253540.537323
2280.427560.8551190.57244
2290.4059490.8118980.594051
2300.3861850.7723690.613815
2310.3391880.6783760.660812
2320.3631840.7263670.636816
2330.3181830.6363660.681817
2340.2707840.5415680.729216
2350.2802940.5605880.719706
2360.250150.50030.74985
2370.2138760.4277530.786124
2380.1722370.3444750.827763
2390.2738280.5476560.726172
2400.2588360.5176720.741164
2410.2426930.4853860.757307
2420.3159520.6319050.684048
2430.2547230.5094450.745277
2440.1994990.3989980.800501
2450.1990120.3980240.800988
2460.1553240.3106470.844676
2470.11140.22280.8886
2480.4303740.8607470.569626
2490.3408420.6816840.659158
2500.2867560.5735120.713244
2510.3001680.6003360.699832
2520.5721240.8557520.427876
2530.5698940.8602130.430106
2540.773140.4537210.22686
2550.6935980.6128040.306402

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.753377 & 0.493246 & 0.246623 \tabularnewline
10 & 0.661239 & 0.677522 & 0.338761 \tabularnewline
11 & 0.555164 & 0.889673 & 0.444836 \tabularnewline
12 & 0.80639 & 0.38722 & 0.19361 \tabularnewline
13 & 0.95637 & 0.0872591 & 0.0436296 \tabularnewline
14 & 0.950839 & 0.0983224 & 0.0491612 \tabularnewline
15 & 0.980487 & 0.0390254 & 0.0195127 \tabularnewline
16 & 0.968606 & 0.062787 & 0.0313935 \tabularnewline
17 & 0.957305 & 0.0853897 & 0.0426949 \tabularnewline
18 & 0.948056 & 0.103888 & 0.051944 \tabularnewline
19 & 0.941991 & 0.116019 & 0.0580093 \tabularnewline
20 & 0.926707 & 0.146586 & 0.0732931 \tabularnewline
21 & 0.927948 & 0.144103 & 0.0720517 \tabularnewline
22 & 0.95554 & 0.0889191 & 0.0444595 \tabularnewline
23 & 0.942329 & 0.115342 & 0.0576708 \tabularnewline
24 & 0.938895 & 0.122209 & 0.0611046 \tabularnewline
25 & 0.920272 & 0.159456 & 0.0797279 \tabularnewline
26 & 0.998007 & 0.00398605 & 0.00199302 \tabularnewline
27 & 0.997078 & 0.00584489 & 0.00292244 \tabularnewline
28 & 0.995536 & 0.00892877 & 0.00446439 \tabularnewline
29 & 0.993532 & 0.0129356 & 0.00646781 \tabularnewline
30 & 0.996687 & 0.00662575 & 0.00331287 \tabularnewline
31 & 0.995094 & 0.00981142 & 0.00490571 \tabularnewline
32 & 0.993296 & 0.013407 & 0.00670352 \tabularnewline
33 & 0.991722 & 0.0165559 & 0.00827797 \tabularnewline
34 & 0.988207 & 0.0235858 & 0.0117929 \tabularnewline
35 & 0.984107 & 0.0317857 & 0.0158928 \tabularnewline
36 & 0.978194 & 0.0436123 & 0.0218061 \tabularnewline
37 & 0.98331 & 0.0333804 & 0.0166902 \tabularnewline
38 & 0.977442 & 0.0451151 & 0.0225576 \tabularnewline
39 & 0.974851 & 0.0502984 & 0.0251492 \tabularnewline
40 & 0.976508 & 0.0469836 & 0.0234918 \tabularnewline
41 & 0.969934 & 0.0601324 & 0.0300662 \tabularnewline
42 & 0.969221 & 0.0615583 & 0.0307791 \tabularnewline
43 & 0.960038 & 0.0799247 & 0.0399624 \tabularnewline
44 & 0.958156 & 0.0836877 & 0.0418438 \tabularnewline
45 & 0.94653 & 0.10694 & 0.0534701 \tabularnewline
46 & 0.955504 & 0.0889923 & 0.0444962 \tabularnewline
47 & 0.943654 & 0.112692 & 0.0563461 \tabularnewline
48 & 0.929256 & 0.141488 & 0.0707442 \tabularnewline
49 & 0.949004 & 0.101992 & 0.0509958 \tabularnewline
50 & 0.944742 & 0.110515 & 0.0552576 \tabularnewline
51 & 0.932232 & 0.135536 & 0.0677678 \tabularnewline
52 & 0.916558 & 0.166884 & 0.0834422 \tabularnewline
53 & 0.904712 & 0.190576 & 0.095288 \tabularnewline
54 & 0.903127 & 0.193746 & 0.096873 \tabularnewline
55 & 0.89923 & 0.201541 & 0.10077 \tabularnewline
56 & 0.888915 & 0.222169 & 0.111085 \tabularnewline
57 & 0.880013 & 0.239974 & 0.119987 \tabularnewline
58 & 0.858539 & 0.282922 & 0.141461 \tabularnewline
59 & 0.885618 & 0.228765 & 0.114382 \tabularnewline
60 & 0.879357 & 0.241286 & 0.120643 \tabularnewline
61 & 0.90848 & 0.18304 & 0.09152 \tabularnewline
62 & 0.902616 & 0.194767 & 0.0973837 \tabularnewline
63 & 0.934509 & 0.130982 & 0.0654909 \tabularnewline
64 & 0.921021 & 0.157957 & 0.0789786 \tabularnewline
65 & 0.906481 & 0.187038 & 0.093519 \tabularnewline
66 & 0.917398 & 0.165204 & 0.0826021 \tabularnewline
67 & 0.91332 & 0.17336 & 0.0866799 \tabularnewline
68 & 0.905531 & 0.188938 & 0.0944692 \tabularnewline
69 & 0.931593 & 0.136814 & 0.0684068 \tabularnewline
70 & 0.936684 & 0.126631 & 0.0633155 \tabularnewline
71 & 0.928959 & 0.142082 & 0.0710409 \tabularnewline
72 & 0.947817 & 0.104366 & 0.052183 \tabularnewline
73 & 0.938716 & 0.122569 & 0.0612843 \tabularnewline
74 & 0.926218 & 0.147565 & 0.0737823 \tabularnewline
75 & 0.916903 & 0.166193 & 0.0830967 \tabularnewline
76 & 0.901226 & 0.197549 & 0.0987745 \tabularnewline
77 & 0.91828 & 0.163439 & 0.0817195 \tabularnewline
78 & 0.903943 & 0.192113 & 0.0960565 \tabularnewline
79 & 0.897157 & 0.205685 & 0.102843 \tabularnewline
80 & 0.898252 & 0.203496 & 0.101748 \tabularnewline
81 & 0.880544 & 0.238913 & 0.119456 \tabularnewline
82 & 0.861574 & 0.276852 & 0.138426 \tabularnewline
83 & 0.856058 & 0.287885 & 0.143942 \tabularnewline
84 & 0.836541 & 0.326918 & 0.163459 \tabularnewline
85 & 0.812203 & 0.375595 & 0.187797 \tabularnewline
86 & 0.789861 & 0.420278 & 0.210139 \tabularnewline
87 & 0.762495 & 0.47501 & 0.237505 \tabularnewline
88 & 0.732469 & 0.535062 & 0.267531 \tabularnewline
89 & 0.798302 & 0.403396 & 0.201698 \tabularnewline
90 & 0.83529 & 0.329421 & 0.16471 \tabularnewline
91 & 0.811742 & 0.376516 & 0.188258 \tabularnewline
92 & 0.78842 & 0.423161 & 0.21158 \tabularnewline
93 & 0.76899 & 0.46202 & 0.23101 \tabularnewline
94 & 0.744277 & 0.511446 & 0.255723 \tabularnewline
95 & 0.721341 & 0.557318 & 0.278659 \tabularnewline
96 & 0.698154 & 0.603693 & 0.301846 \tabularnewline
97 & 0.669517 & 0.660966 & 0.330483 \tabularnewline
98 & 0.672881 & 0.654238 & 0.327119 \tabularnewline
99 & 0.639021 & 0.721958 & 0.360979 \tabularnewline
100 & 0.626268 & 0.747463 & 0.373732 \tabularnewline
101 & 0.600998 & 0.798004 & 0.399002 \tabularnewline
102 & 0.575295 & 0.849409 & 0.424705 \tabularnewline
103 & 0.641995 & 0.716009 & 0.358005 \tabularnewline
104 & 0.635923 & 0.728154 & 0.364077 \tabularnewline
105 & 0.657425 & 0.685149 & 0.342575 \tabularnewline
106 & 0.631357 & 0.737285 & 0.368643 \tabularnewline
107 & 0.621703 & 0.756594 & 0.378297 \tabularnewline
108 & 0.683069 & 0.633861 & 0.316931 \tabularnewline
109 & 0.654353 & 0.691294 & 0.345647 \tabularnewline
110 & 0.635829 & 0.728342 & 0.364171 \tabularnewline
111 & 0.64283 & 0.714341 & 0.35717 \tabularnewline
112 & 0.650455 & 0.69909 & 0.349545 \tabularnewline
113 & 0.625788 & 0.748423 & 0.374212 \tabularnewline
114 & 0.708302 & 0.583395 & 0.291698 \tabularnewline
115 & 0.680756 & 0.638489 & 0.319244 \tabularnewline
116 & 0.650592 & 0.698816 & 0.349408 \tabularnewline
117 & 0.618908 & 0.762185 & 0.381092 \tabularnewline
118 & 0.60073 & 0.798541 & 0.39927 \tabularnewline
119 & 0.568546 & 0.862908 & 0.431454 \tabularnewline
120 & 0.544255 & 0.91149 & 0.455745 \tabularnewline
121 & 0.515153 & 0.969694 & 0.484847 \tabularnewline
122 & 0.480904 & 0.961809 & 0.519096 \tabularnewline
123 & 0.456983 & 0.913966 & 0.543017 \tabularnewline
124 & 0.423163 & 0.846326 & 0.576837 \tabularnewline
125 & 0.414963 & 0.829926 & 0.585037 \tabularnewline
126 & 0.389319 & 0.778638 & 0.610681 \tabularnewline
127 & 0.37059 & 0.741179 & 0.62941 \tabularnewline
128 & 0.48973 & 0.97946 & 0.51027 \tabularnewline
129 & 0.468373 & 0.936747 & 0.531627 \tabularnewline
130 & 0.45949 & 0.918979 & 0.54051 \tabularnewline
131 & 0.44794 & 0.895881 & 0.55206 \tabularnewline
132 & 0.415086 & 0.830172 & 0.584914 \tabularnewline
133 & 0.425519 & 0.851037 & 0.574481 \tabularnewline
134 & 0.395291 & 0.790581 & 0.604709 \tabularnewline
135 & 0.417122 & 0.834243 & 0.582878 \tabularnewline
136 & 0.399624 & 0.799247 & 0.600376 \tabularnewline
137 & 0.367549 & 0.735098 & 0.632451 \tabularnewline
138 & 0.3507 & 0.701399 & 0.6493 \tabularnewline
139 & 0.320697 & 0.641394 & 0.679303 \tabularnewline
140 & 0.296252 & 0.592505 & 0.703748 \tabularnewline
141 & 0.266169 & 0.532338 & 0.733831 \tabularnewline
142 & 0.283915 & 0.56783 & 0.716085 \tabularnewline
143 & 0.255306 & 0.510612 & 0.744694 \tabularnewline
144 & 0.23294 & 0.46588 & 0.76706 \tabularnewline
145 & 0.224979 & 0.449958 & 0.775021 \tabularnewline
146 & 0.215898 & 0.431796 & 0.784102 \tabularnewline
147 & 0.237363 & 0.474727 & 0.762637 \tabularnewline
148 & 0.258201 & 0.516402 & 0.741799 \tabularnewline
149 & 0.272351 & 0.544702 & 0.727649 \tabularnewline
150 & 0.275817 & 0.551635 & 0.724183 \tabularnewline
151 & 0.249922 & 0.499843 & 0.750078 \tabularnewline
152 & 0.224853 & 0.449707 & 0.775147 \tabularnewline
153 & 0.234383 & 0.468766 & 0.765617 \tabularnewline
154 & 0.274764 & 0.549527 & 0.725236 \tabularnewline
155 & 0.253923 & 0.507846 & 0.746077 \tabularnewline
156 & 0.231989 & 0.463978 & 0.768011 \tabularnewline
157 & 0.20573 & 0.41146 & 0.79427 \tabularnewline
158 & 0.300009 & 0.600017 & 0.699991 \tabularnewline
159 & 0.324959 & 0.649918 & 0.675041 \tabularnewline
160 & 0.292903 & 0.585807 & 0.707097 \tabularnewline
161 & 0.2623 & 0.524601 & 0.7377 \tabularnewline
162 & 0.236504 & 0.473007 & 0.763496 \tabularnewline
163 & 0.213277 & 0.426554 & 0.786723 \tabularnewline
164 & 0.343088 & 0.686176 & 0.656912 \tabularnewline
165 & 0.338607 & 0.677214 & 0.661393 \tabularnewline
166 & 0.332279 & 0.664558 & 0.667721 \tabularnewline
167 & 0.300276 & 0.600551 & 0.699724 \tabularnewline
168 & 0.276151 & 0.552302 & 0.723849 \tabularnewline
169 & 0.330642 & 0.661284 & 0.669358 \tabularnewline
170 & 0.356277 & 0.712554 & 0.643723 \tabularnewline
171 & 0.325073 & 0.650146 & 0.674927 \tabularnewline
172 & 0.319848 & 0.639695 & 0.680152 \tabularnewline
173 & 0.485936 & 0.971871 & 0.514064 \tabularnewline
174 & 0.470203 & 0.940406 & 0.529797 \tabularnewline
175 & 0.496182 & 0.992363 & 0.503818 \tabularnewline
176 & 0.505447 & 0.989106 & 0.494553 \tabularnewline
177 & 0.557556 & 0.884888 & 0.442444 \tabularnewline
178 & 0.525112 & 0.949776 & 0.474888 \tabularnewline
179 & 0.502224 & 0.995552 & 0.497776 \tabularnewline
180 & 0.500244 & 0.999512 & 0.499756 \tabularnewline
181 & 0.46459 & 0.929179 & 0.53541 \tabularnewline
182 & 0.457178 & 0.914357 & 0.542822 \tabularnewline
183 & 0.41912 & 0.83824 & 0.58088 \tabularnewline
184 & 0.388753 & 0.777506 & 0.611247 \tabularnewline
185 & 0.409845 & 0.81969 & 0.590155 \tabularnewline
186 & 0.401804 & 0.803607 & 0.598196 \tabularnewline
187 & 0.366147 & 0.732294 & 0.633853 \tabularnewline
188 & 0.339825 & 0.679651 & 0.660175 \tabularnewline
189 & 0.30571 & 0.61142 & 0.69429 \tabularnewline
190 & 0.286091 & 0.572182 & 0.713909 \tabularnewline
191 & 0.300536 & 0.601071 & 0.699464 \tabularnewline
192 & 0.277299 & 0.554598 & 0.722701 \tabularnewline
193 & 0.299136 & 0.598272 & 0.700864 \tabularnewline
194 & 0.284134 & 0.568269 & 0.715866 \tabularnewline
195 & 0.285206 & 0.570412 & 0.714794 \tabularnewline
196 & 0.292046 & 0.584091 & 0.707954 \tabularnewline
197 & 0.325873 & 0.651746 & 0.674127 \tabularnewline
198 & 0.299438 & 0.598876 & 0.700562 \tabularnewline
199 & 0.335165 & 0.67033 & 0.664835 \tabularnewline
200 & 0.300049 & 0.600097 & 0.699951 \tabularnewline
201 & 0.338086 & 0.676173 & 0.661914 \tabularnewline
202 & 0.317118 & 0.634236 & 0.682882 \tabularnewline
203 & 0.365002 & 0.730003 & 0.634998 \tabularnewline
204 & 0.326062 & 0.652124 & 0.673938 \tabularnewline
205 & 0.29044 & 0.580881 & 0.70956 \tabularnewline
206 & 0.269014 & 0.538028 & 0.730986 \tabularnewline
207 & 0.234631 & 0.469263 & 0.765369 \tabularnewline
208 & 0.275956 & 0.551913 & 0.724044 \tabularnewline
209 & 0.241361 & 0.482721 & 0.758639 \tabularnewline
210 & 0.240931 & 0.481863 & 0.759069 \tabularnewline
211 & 0.257542 & 0.515085 & 0.742458 \tabularnewline
212 & 0.251526 & 0.503052 & 0.748474 \tabularnewline
213 & 0.217884 & 0.435769 & 0.782116 \tabularnewline
214 & 0.279531 & 0.559063 & 0.720469 \tabularnewline
215 & 0.251667 & 0.503335 & 0.748333 \tabularnewline
216 & 0.239502 & 0.479004 & 0.760498 \tabularnewline
217 & 0.255418 & 0.510837 & 0.744582 \tabularnewline
218 & 0.218974 & 0.437948 & 0.781026 \tabularnewline
219 & 0.208695 & 0.41739 & 0.791305 \tabularnewline
220 & 0.205332 & 0.410664 & 0.794668 \tabularnewline
221 & 0.223213 & 0.446426 & 0.776787 \tabularnewline
222 & 0.231942 & 0.463885 & 0.768058 \tabularnewline
223 & 0.223088 & 0.446175 & 0.776912 \tabularnewline
224 & 0.190098 & 0.380197 & 0.809902 \tabularnewline
225 & 0.166264 & 0.332528 & 0.833736 \tabularnewline
226 & 0.193453 & 0.386905 & 0.806547 \tabularnewline
227 & 0.462677 & 0.925354 & 0.537323 \tabularnewline
228 & 0.42756 & 0.855119 & 0.57244 \tabularnewline
229 & 0.405949 & 0.811898 & 0.594051 \tabularnewline
230 & 0.386185 & 0.772369 & 0.613815 \tabularnewline
231 & 0.339188 & 0.678376 & 0.660812 \tabularnewline
232 & 0.363184 & 0.726367 & 0.636816 \tabularnewline
233 & 0.318183 & 0.636366 & 0.681817 \tabularnewline
234 & 0.270784 & 0.541568 & 0.729216 \tabularnewline
235 & 0.280294 & 0.560588 & 0.719706 \tabularnewline
236 & 0.25015 & 0.5003 & 0.74985 \tabularnewline
237 & 0.213876 & 0.427753 & 0.786124 \tabularnewline
238 & 0.172237 & 0.344475 & 0.827763 \tabularnewline
239 & 0.273828 & 0.547656 & 0.726172 \tabularnewline
240 & 0.258836 & 0.517672 & 0.741164 \tabularnewline
241 & 0.242693 & 0.485386 & 0.757307 \tabularnewline
242 & 0.315952 & 0.631905 & 0.684048 \tabularnewline
243 & 0.254723 & 0.509445 & 0.745277 \tabularnewline
244 & 0.199499 & 0.398998 & 0.800501 \tabularnewline
245 & 0.199012 & 0.398024 & 0.800988 \tabularnewline
246 & 0.155324 & 0.310647 & 0.844676 \tabularnewline
247 & 0.1114 & 0.2228 & 0.8886 \tabularnewline
248 & 0.430374 & 0.860747 & 0.569626 \tabularnewline
249 & 0.340842 & 0.681684 & 0.659158 \tabularnewline
250 & 0.286756 & 0.573512 & 0.713244 \tabularnewline
251 & 0.300168 & 0.600336 & 0.699832 \tabularnewline
252 & 0.572124 & 0.855752 & 0.427876 \tabularnewline
253 & 0.569894 & 0.860213 & 0.430106 \tabularnewline
254 & 0.77314 & 0.453721 & 0.22686 \tabularnewline
255 & 0.693598 & 0.612804 & 0.306402 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226310&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]9[/C][C]0.753377[/C][C]0.493246[/C][C]0.246623[/C][/ROW]
[ROW][C]10[/C][C]0.661239[/C][C]0.677522[/C][C]0.338761[/C][/ROW]
[ROW][C]11[/C][C]0.555164[/C][C]0.889673[/C][C]0.444836[/C][/ROW]
[ROW][C]12[/C][C]0.80639[/C][C]0.38722[/C][C]0.19361[/C][/ROW]
[ROW][C]13[/C][C]0.95637[/C][C]0.0872591[/C][C]0.0436296[/C][/ROW]
[ROW][C]14[/C][C]0.950839[/C][C]0.0983224[/C][C]0.0491612[/C][/ROW]
[ROW][C]15[/C][C]0.980487[/C][C]0.0390254[/C][C]0.0195127[/C][/ROW]
[ROW][C]16[/C][C]0.968606[/C][C]0.062787[/C][C]0.0313935[/C][/ROW]
[ROW][C]17[/C][C]0.957305[/C][C]0.0853897[/C][C]0.0426949[/C][/ROW]
[ROW][C]18[/C][C]0.948056[/C][C]0.103888[/C][C]0.051944[/C][/ROW]
[ROW][C]19[/C][C]0.941991[/C][C]0.116019[/C][C]0.0580093[/C][/ROW]
[ROW][C]20[/C][C]0.926707[/C][C]0.146586[/C][C]0.0732931[/C][/ROW]
[ROW][C]21[/C][C]0.927948[/C][C]0.144103[/C][C]0.0720517[/C][/ROW]
[ROW][C]22[/C][C]0.95554[/C][C]0.0889191[/C][C]0.0444595[/C][/ROW]
[ROW][C]23[/C][C]0.942329[/C][C]0.115342[/C][C]0.0576708[/C][/ROW]
[ROW][C]24[/C][C]0.938895[/C][C]0.122209[/C][C]0.0611046[/C][/ROW]
[ROW][C]25[/C][C]0.920272[/C][C]0.159456[/C][C]0.0797279[/C][/ROW]
[ROW][C]26[/C][C]0.998007[/C][C]0.00398605[/C][C]0.00199302[/C][/ROW]
[ROW][C]27[/C][C]0.997078[/C][C]0.00584489[/C][C]0.00292244[/C][/ROW]
[ROW][C]28[/C][C]0.995536[/C][C]0.00892877[/C][C]0.00446439[/C][/ROW]
[ROW][C]29[/C][C]0.993532[/C][C]0.0129356[/C][C]0.00646781[/C][/ROW]
[ROW][C]30[/C][C]0.996687[/C][C]0.00662575[/C][C]0.00331287[/C][/ROW]
[ROW][C]31[/C][C]0.995094[/C][C]0.00981142[/C][C]0.00490571[/C][/ROW]
[ROW][C]32[/C][C]0.993296[/C][C]0.013407[/C][C]0.00670352[/C][/ROW]
[ROW][C]33[/C][C]0.991722[/C][C]0.0165559[/C][C]0.00827797[/C][/ROW]
[ROW][C]34[/C][C]0.988207[/C][C]0.0235858[/C][C]0.0117929[/C][/ROW]
[ROW][C]35[/C][C]0.984107[/C][C]0.0317857[/C][C]0.0158928[/C][/ROW]
[ROW][C]36[/C][C]0.978194[/C][C]0.0436123[/C][C]0.0218061[/C][/ROW]
[ROW][C]37[/C][C]0.98331[/C][C]0.0333804[/C][C]0.0166902[/C][/ROW]
[ROW][C]38[/C][C]0.977442[/C][C]0.0451151[/C][C]0.0225576[/C][/ROW]
[ROW][C]39[/C][C]0.974851[/C][C]0.0502984[/C][C]0.0251492[/C][/ROW]
[ROW][C]40[/C][C]0.976508[/C][C]0.0469836[/C][C]0.0234918[/C][/ROW]
[ROW][C]41[/C][C]0.969934[/C][C]0.0601324[/C][C]0.0300662[/C][/ROW]
[ROW][C]42[/C][C]0.969221[/C][C]0.0615583[/C][C]0.0307791[/C][/ROW]
[ROW][C]43[/C][C]0.960038[/C][C]0.0799247[/C][C]0.0399624[/C][/ROW]
[ROW][C]44[/C][C]0.958156[/C][C]0.0836877[/C][C]0.0418438[/C][/ROW]
[ROW][C]45[/C][C]0.94653[/C][C]0.10694[/C][C]0.0534701[/C][/ROW]
[ROW][C]46[/C][C]0.955504[/C][C]0.0889923[/C][C]0.0444962[/C][/ROW]
[ROW][C]47[/C][C]0.943654[/C][C]0.112692[/C][C]0.0563461[/C][/ROW]
[ROW][C]48[/C][C]0.929256[/C][C]0.141488[/C][C]0.0707442[/C][/ROW]
[ROW][C]49[/C][C]0.949004[/C][C]0.101992[/C][C]0.0509958[/C][/ROW]
[ROW][C]50[/C][C]0.944742[/C][C]0.110515[/C][C]0.0552576[/C][/ROW]
[ROW][C]51[/C][C]0.932232[/C][C]0.135536[/C][C]0.0677678[/C][/ROW]
[ROW][C]52[/C][C]0.916558[/C][C]0.166884[/C][C]0.0834422[/C][/ROW]
[ROW][C]53[/C][C]0.904712[/C][C]0.190576[/C][C]0.095288[/C][/ROW]
[ROW][C]54[/C][C]0.903127[/C][C]0.193746[/C][C]0.096873[/C][/ROW]
[ROW][C]55[/C][C]0.89923[/C][C]0.201541[/C][C]0.10077[/C][/ROW]
[ROW][C]56[/C][C]0.888915[/C][C]0.222169[/C][C]0.111085[/C][/ROW]
[ROW][C]57[/C][C]0.880013[/C][C]0.239974[/C][C]0.119987[/C][/ROW]
[ROW][C]58[/C][C]0.858539[/C][C]0.282922[/C][C]0.141461[/C][/ROW]
[ROW][C]59[/C][C]0.885618[/C][C]0.228765[/C][C]0.114382[/C][/ROW]
[ROW][C]60[/C][C]0.879357[/C][C]0.241286[/C][C]0.120643[/C][/ROW]
[ROW][C]61[/C][C]0.90848[/C][C]0.18304[/C][C]0.09152[/C][/ROW]
[ROW][C]62[/C][C]0.902616[/C][C]0.194767[/C][C]0.0973837[/C][/ROW]
[ROW][C]63[/C][C]0.934509[/C][C]0.130982[/C][C]0.0654909[/C][/ROW]
[ROW][C]64[/C][C]0.921021[/C][C]0.157957[/C][C]0.0789786[/C][/ROW]
[ROW][C]65[/C][C]0.906481[/C][C]0.187038[/C][C]0.093519[/C][/ROW]
[ROW][C]66[/C][C]0.917398[/C][C]0.165204[/C][C]0.0826021[/C][/ROW]
[ROW][C]67[/C][C]0.91332[/C][C]0.17336[/C][C]0.0866799[/C][/ROW]
[ROW][C]68[/C][C]0.905531[/C][C]0.188938[/C][C]0.0944692[/C][/ROW]
[ROW][C]69[/C][C]0.931593[/C][C]0.136814[/C][C]0.0684068[/C][/ROW]
[ROW][C]70[/C][C]0.936684[/C][C]0.126631[/C][C]0.0633155[/C][/ROW]
[ROW][C]71[/C][C]0.928959[/C][C]0.142082[/C][C]0.0710409[/C][/ROW]
[ROW][C]72[/C][C]0.947817[/C][C]0.104366[/C][C]0.052183[/C][/ROW]
[ROW][C]73[/C][C]0.938716[/C][C]0.122569[/C][C]0.0612843[/C][/ROW]
[ROW][C]74[/C][C]0.926218[/C][C]0.147565[/C][C]0.0737823[/C][/ROW]
[ROW][C]75[/C][C]0.916903[/C][C]0.166193[/C][C]0.0830967[/C][/ROW]
[ROW][C]76[/C][C]0.901226[/C][C]0.197549[/C][C]0.0987745[/C][/ROW]
[ROW][C]77[/C][C]0.91828[/C][C]0.163439[/C][C]0.0817195[/C][/ROW]
[ROW][C]78[/C][C]0.903943[/C][C]0.192113[/C][C]0.0960565[/C][/ROW]
[ROW][C]79[/C][C]0.897157[/C][C]0.205685[/C][C]0.102843[/C][/ROW]
[ROW][C]80[/C][C]0.898252[/C][C]0.203496[/C][C]0.101748[/C][/ROW]
[ROW][C]81[/C][C]0.880544[/C][C]0.238913[/C][C]0.119456[/C][/ROW]
[ROW][C]82[/C][C]0.861574[/C][C]0.276852[/C][C]0.138426[/C][/ROW]
[ROW][C]83[/C][C]0.856058[/C][C]0.287885[/C][C]0.143942[/C][/ROW]
[ROW][C]84[/C][C]0.836541[/C][C]0.326918[/C][C]0.163459[/C][/ROW]
[ROW][C]85[/C][C]0.812203[/C][C]0.375595[/C][C]0.187797[/C][/ROW]
[ROW][C]86[/C][C]0.789861[/C][C]0.420278[/C][C]0.210139[/C][/ROW]
[ROW][C]87[/C][C]0.762495[/C][C]0.47501[/C][C]0.237505[/C][/ROW]
[ROW][C]88[/C][C]0.732469[/C][C]0.535062[/C][C]0.267531[/C][/ROW]
[ROW][C]89[/C][C]0.798302[/C][C]0.403396[/C][C]0.201698[/C][/ROW]
[ROW][C]90[/C][C]0.83529[/C][C]0.329421[/C][C]0.16471[/C][/ROW]
[ROW][C]91[/C][C]0.811742[/C][C]0.376516[/C][C]0.188258[/C][/ROW]
[ROW][C]92[/C][C]0.78842[/C][C]0.423161[/C][C]0.21158[/C][/ROW]
[ROW][C]93[/C][C]0.76899[/C][C]0.46202[/C][C]0.23101[/C][/ROW]
[ROW][C]94[/C][C]0.744277[/C][C]0.511446[/C][C]0.255723[/C][/ROW]
[ROW][C]95[/C][C]0.721341[/C][C]0.557318[/C][C]0.278659[/C][/ROW]
[ROW][C]96[/C][C]0.698154[/C][C]0.603693[/C][C]0.301846[/C][/ROW]
[ROW][C]97[/C][C]0.669517[/C][C]0.660966[/C][C]0.330483[/C][/ROW]
[ROW][C]98[/C][C]0.672881[/C][C]0.654238[/C][C]0.327119[/C][/ROW]
[ROW][C]99[/C][C]0.639021[/C][C]0.721958[/C][C]0.360979[/C][/ROW]
[ROW][C]100[/C][C]0.626268[/C][C]0.747463[/C][C]0.373732[/C][/ROW]
[ROW][C]101[/C][C]0.600998[/C][C]0.798004[/C][C]0.399002[/C][/ROW]
[ROW][C]102[/C][C]0.575295[/C][C]0.849409[/C][C]0.424705[/C][/ROW]
[ROW][C]103[/C][C]0.641995[/C][C]0.716009[/C][C]0.358005[/C][/ROW]
[ROW][C]104[/C][C]0.635923[/C][C]0.728154[/C][C]0.364077[/C][/ROW]
[ROW][C]105[/C][C]0.657425[/C][C]0.685149[/C][C]0.342575[/C][/ROW]
[ROW][C]106[/C][C]0.631357[/C][C]0.737285[/C][C]0.368643[/C][/ROW]
[ROW][C]107[/C][C]0.621703[/C][C]0.756594[/C][C]0.378297[/C][/ROW]
[ROW][C]108[/C][C]0.683069[/C][C]0.633861[/C][C]0.316931[/C][/ROW]
[ROW][C]109[/C][C]0.654353[/C][C]0.691294[/C][C]0.345647[/C][/ROW]
[ROW][C]110[/C][C]0.635829[/C][C]0.728342[/C][C]0.364171[/C][/ROW]
[ROW][C]111[/C][C]0.64283[/C][C]0.714341[/C][C]0.35717[/C][/ROW]
[ROW][C]112[/C][C]0.650455[/C][C]0.69909[/C][C]0.349545[/C][/ROW]
[ROW][C]113[/C][C]0.625788[/C][C]0.748423[/C][C]0.374212[/C][/ROW]
[ROW][C]114[/C][C]0.708302[/C][C]0.583395[/C][C]0.291698[/C][/ROW]
[ROW][C]115[/C][C]0.680756[/C][C]0.638489[/C][C]0.319244[/C][/ROW]
[ROW][C]116[/C][C]0.650592[/C][C]0.698816[/C][C]0.349408[/C][/ROW]
[ROW][C]117[/C][C]0.618908[/C][C]0.762185[/C][C]0.381092[/C][/ROW]
[ROW][C]118[/C][C]0.60073[/C][C]0.798541[/C][C]0.39927[/C][/ROW]
[ROW][C]119[/C][C]0.568546[/C][C]0.862908[/C][C]0.431454[/C][/ROW]
[ROW][C]120[/C][C]0.544255[/C][C]0.91149[/C][C]0.455745[/C][/ROW]
[ROW][C]121[/C][C]0.515153[/C][C]0.969694[/C][C]0.484847[/C][/ROW]
[ROW][C]122[/C][C]0.480904[/C][C]0.961809[/C][C]0.519096[/C][/ROW]
[ROW][C]123[/C][C]0.456983[/C][C]0.913966[/C][C]0.543017[/C][/ROW]
[ROW][C]124[/C][C]0.423163[/C][C]0.846326[/C][C]0.576837[/C][/ROW]
[ROW][C]125[/C][C]0.414963[/C][C]0.829926[/C][C]0.585037[/C][/ROW]
[ROW][C]126[/C][C]0.389319[/C][C]0.778638[/C][C]0.610681[/C][/ROW]
[ROW][C]127[/C][C]0.37059[/C][C]0.741179[/C][C]0.62941[/C][/ROW]
[ROW][C]128[/C][C]0.48973[/C][C]0.97946[/C][C]0.51027[/C][/ROW]
[ROW][C]129[/C][C]0.468373[/C][C]0.936747[/C][C]0.531627[/C][/ROW]
[ROW][C]130[/C][C]0.45949[/C][C]0.918979[/C][C]0.54051[/C][/ROW]
[ROW][C]131[/C][C]0.44794[/C][C]0.895881[/C][C]0.55206[/C][/ROW]
[ROW][C]132[/C][C]0.415086[/C][C]0.830172[/C][C]0.584914[/C][/ROW]
[ROW][C]133[/C][C]0.425519[/C][C]0.851037[/C][C]0.574481[/C][/ROW]
[ROW][C]134[/C][C]0.395291[/C][C]0.790581[/C][C]0.604709[/C][/ROW]
[ROW][C]135[/C][C]0.417122[/C][C]0.834243[/C][C]0.582878[/C][/ROW]
[ROW][C]136[/C][C]0.399624[/C][C]0.799247[/C][C]0.600376[/C][/ROW]
[ROW][C]137[/C][C]0.367549[/C][C]0.735098[/C][C]0.632451[/C][/ROW]
[ROW][C]138[/C][C]0.3507[/C][C]0.701399[/C][C]0.6493[/C][/ROW]
[ROW][C]139[/C][C]0.320697[/C][C]0.641394[/C][C]0.679303[/C][/ROW]
[ROW][C]140[/C][C]0.296252[/C][C]0.592505[/C][C]0.703748[/C][/ROW]
[ROW][C]141[/C][C]0.266169[/C][C]0.532338[/C][C]0.733831[/C][/ROW]
[ROW][C]142[/C][C]0.283915[/C][C]0.56783[/C][C]0.716085[/C][/ROW]
[ROW][C]143[/C][C]0.255306[/C][C]0.510612[/C][C]0.744694[/C][/ROW]
[ROW][C]144[/C][C]0.23294[/C][C]0.46588[/C][C]0.76706[/C][/ROW]
[ROW][C]145[/C][C]0.224979[/C][C]0.449958[/C][C]0.775021[/C][/ROW]
[ROW][C]146[/C][C]0.215898[/C][C]0.431796[/C][C]0.784102[/C][/ROW]
[ROW][C]147[/C][C]0.237363[/C][C]0.474727[/C][C]0.762637[/C][/ROW]
[ROW][C]148[/C][C]0.258201[/C][C]0.516402[/C][C]0.741799[/C][/ROW]
[ROW][C]149[/C][C]0.272351[/C][C]0.544702[/C][C]0.727649[/C][/ROW]
[ROW][C]150[/C][C]0.275817[/C][C]0.551635[/C][C]0.724183[/C][/ROW]
[ROW][C]151[/C][C]0.249922[/C][C]0.499843[/C][C]0.750078[/C][/ROW]
[ROW][C]152[/C][C]0.224853[/C][C]0.449707[/C][C]0.775147[/C][/ROW]
[ROW][C]153[/C][C]0.234383[/C][C]0.468766[/C][C]0.765617[/C][/ROW]
[ROW][C]154[/C][C]0.274764[/C][C]0.549527[/C][C]0.725236[/C][/ROW]
[ROW][C]155[/C][C]0.253923[/C][C]0.507846[/C][C]0.746077[/C][/ROW]
[ROW][C]156[/C][C]0.231989[/C][C]0.463978[/C][C]0.768011[/C][/ROW]
[ROW][C]157[/C][C]0.20573[/C][C]0.41146[/C][C]0.79427[/C][/ROW]
[ROW][C]158[/C][C]0.300009[/C][C]0.600017[/C][C]0.699991[/C][/ROW]
[ROW][C]159[/C][C]0.324959[/C][C]0.649918[/C][C]0.675041[/C][/ROW]
[ROW][C]160[/C][C]0.292903[/C][C]0.585807[/C][C]0.707097[/C][/ROW]
[ROW][C]161[/C][C]0.2623[/C][C]0.524601[/C][C]0.7377[/C][/ROW]
[ROW][C]162[/C][C]0.236504[/C][C]0.473007[/C][C]0.763496[/C][/ROW]
[ROW][C]163[/C][C]0.213277[/C][C]0.426554[/C][C]0.786723[/C][/ROW]
[ROW][C]164[/C][C]0.343088[/C][C]0.686176[/C][C]0.656912[/C][/ROW]
[ROW][C]165[/C][C]0.338607[/C][C]0.677214[/C][C]0.661393[/C][/ROW]
[ROW][C]166[/C][C]0.332279[/C][C]0.664558[/C][C]0.667721[/C][/ROW]
[ROW][C]167[/C][C]0.300276[/C][C]0.600551[/C][C]0.699724[/C][/ROW]
[ROW][C]168[/C][C]0.276151[/C][C]0.552302[/C][C]0.723849[/C][/ROW]
[ROW][C]169[/C][C]0.330642[/C][C]0.661284[/C][C]0.669358[/C][/ROW]
[ROW][C]170[/C][C]0.356277[/C][C]0.712554[/C][C]0.643723[/C][/ROW]
[ROW][C]171[/C][C]0.325073[/C][C]0.650146[/C][C]0.674927[/C][/ROW]
[ROW][C]172[/C][C]0.319848[/C][C]0.639695[/C][C]0.680152[/C][/ROW]
[ROW][C]173[/C][C]0.485936[/C][C]0.971871[/C][C]0.514064[/C][/ROW]
[ROW][C]174[/C][C]0.470203[/C][C]0.940406[/C][C]0.529797[/C][/ROW]
[ROW][C]175[/C][C]0.496182[/C][C]0.992363[/C][C]0.503818[/C][/ROW]
[ROW][C]176[/C][C]0.505447[/C][C]0.989106[/C][C]0.494553[/C][/ROW]
[ROW][C]177[/C][C]0.557556[/C][C]0.884888[/C][C]0.442444[/C][/ROW]
[ROW][C]178[/C][C]0.525112[/C][C]0.949776[/C][C]0.474888[/C][/ROW]
[ROW][C]179[/C][C]0.502224[/C][C]0.995552[/C][C]0.497776[/C][/ROW]
[ROW][C]180[/C][C]0.500244[/C][C]0.999512[/C][C]0.499756[/C][/ROW]
[ROW][C]181[/C][C]0.46459[/C][C]0.929179[/C][C]0.53541[/C][/ROW]
[ROW][C]182[/C][C]0.457178[/C][C]0.914357[/C][C]0.542822[/C][/ROW]
[ROW][C]183[/C][C]0.41912[/C][C]0.83824[/C][C]0.58088[/C][/ROW]
[ROW][C]184[/C][C]0.388753[/C][C]0.777506[/C][C]0.611247[/C][/ROW]
[ROW][C]185[/C][C]0.409845[/C][C]0.81969[/C][C]0.590155[/C][/ROW]
[ROW][C]186[/C][C]0.401804[/C][C]0.803607[/C][C]0.598196[/C][/ROW]
[ROW][C]187[/C][C]0.366147[/C][C]0.732294[/C][C]0.633853[/C][/ROW]
[ROW][C]188[/C][C]0.339825[/C][C]0.679651[/C][C]0.660175[/C][/ROW]
[ROW][C]189[/C][C]0.30571[/C][C]0.61142[/C][C]0.69429[/C][/ROW]
[ROW][C]190[/C][C]0.286091[/C][C]0.572182[/C][C]0.713909[/C][/ROW]
[ROW][C]191[/C][C]0.300536[/C][C]0.601071[/C][C]0.699464[/C][/ROW]
[ROW][C]192[/C][C]0.277299[/C][C]0.554598[/C][C]0.722701[/C][/ROW]
[ROW][C]193[/C][C]0.299136[/C][C]0.598272[/C][C]0.700864[/C][/ROW]
[ROW][C]194[/C][C]0.284134[/C][C]0.568269[/C][C]0.715866[/C][/ROW]
[ROW][C]195[/C][C]0.285206[/C][C]0.570412[/C][C]0.714794[/C][/ROW]
[ROW][C]196[/C][C]0.292046[/C][C]0.584091[/C][C]0.707954[/C][/ROW]
[ROW][C]197[/C][C]0.325873[/C][C]0.651746[/C][C]0.674127[/C][/ROW]
[ROW][C]198[/C][C]0.299438[/C][C]0.598876[/C][C]0.700562[/C][/ROW]
[ROW][C]199[/C][C]0.335165[/C][C]0.67033[/C][C]0.664835[/C][/ROW]
[ROW][C]200[/C][C]0.300049[/C][C]0.600097[/C][C]0.699951[/C][/ROW]
[ROW][C]201[/C][C]0.338086[/C][C]0.676173[/C][C]0.661914[/C][/ROW]
[ROW][C]202[/C][C]0.317118[/C][C]0.634236[/C][C]0.682882[/C][/ROW]
[ROW][C]203[/C][C]0.365002[/C][C]0.730003[/C][C]0.634998[/C][/ROW]
[ROW][C]204[/C][C]0.326062[/C][C]0.652124[/C][C]0.673938[/C][/ROW]
[ROW][C]205[/C][C]0.29044[/C][C]0.580881[/C][C]0.70956[/C][/ROW]
[ROW][C]206[/C][C]0.269014[/C][C]0.538028[/C][C]0.730986[/C][/ROW]
[ROW][C]207[/C][C]0.234631[/C][C]0.469263[/C][C]0.765369[/C][/ROW]
[ROW][C]208[/C][C]0.275956[/C][C]0.551913[/C][C]0.724044[/C][/ROW]
[ROW][C]209[/C][C]0.241361[/C][C]0.482721[/C][C]0.758639[/C][/ROW]
[ROW][C]210[/C][C]0.240931[/C][C]0.481863[/C][C]0.759069[/C][/ROW]
[ROW][C]211[/C][C]0.257542[/C][C]0.515085[/C][C]0.742458[/C][/ROW]
[ROW][C]212[/C][C]0.251526[/C][C]0.503052[/C][C]0.748474[/C][/ROW]
[ROW][C]213[/C][C]0.217884[/C][C]0.435769[/C][C]0.782116[/C][/ROW]
[ROW][C]214[/C][C]0.279531[/C][C]0.559063[/C][C]0.720469[/C][/ROW]
[ROW][C]215[/C][C]0.251667[/C][C]0.503335[/C][C]0.748333[/C][/ROW]
[ROW][C]216[/C][C]0.239502[/C][C]0.479004[/C][C]0.760498[/C][/ROW]
[ROW][C]217[/C][C]0.255418[/C][C]0.510837[/C][C]0.744582[/C][/ROW]
[ROW][C]218[/C][C]0.218974[/C][C]0.437948[/C][C]0.781026[/C][/ROW]
[ROW][C]219[/C][C]0.208695[/C][C]0.41739[/C][C]0.791305[/C][/ROW]
[ROW][C]220[/C][C]0.205332[/C][C]0.410664[/C][C]0.794668[/C][/ROW]
[ROW][C]221[/C][C]0.223213[/C][C]0.446426[/C][C]0.776787[/C][/ROW]
[ROW][C]222[/C][C]0.231942[/C][C]0.463885[/C][C]0.768058[/C][/ROW]
[ROW][C]223[/C][C]0.223088[/C][C]0.446175[/C][C]0.776912[/C][/ROW]
[ROW][C]224[/C][C]0.190098[/C][C]0.380197[/C][C]0.809902[/C][/ROW]
[ROW][C]225[/C][C]0.166264[/C][C]0.332528[/C][C]0.833736[/C][/ROW]
[ROW][C]226[/C][C]0.193453[/C][C]0.386905[/C][C]0.806547[/C][/ROW]
[ROW][C]227[/C][C]0.462677[/C][C]0.925354[/C][C]0.537323[/C][/ROW]
[ROW][C]228[/C][C]0.42756[/C][C]0.855119[/C][C]0.57244[/C][/ROW]
[ROW][C]229[/C][C]0.405949[/C][C]0.811898[/C][C]0.594051[/C][/ROW]
[ROW][C]230[/C][C]0.386185[/C][C]0.772369[/C][C]0.613815[/C][/ROW]
[ROW][C]231[/C][C]0.339188[/C][C]0.678376[/C][C]0.660812[/C][/ROW]
[ROW][C]232[/C][C]0.363184[/C][C]0.726367[/C][C]0.636816[/C][/ROW]
[ROW][C]233[/C][C]0.318183[/C][C]0.636366[/C][C]0.681817[/C][/ROW]
[ROW][C]234[/C][C]0.270784[/C][C]0.541568[/C][C]0.729216[/C][/ROW]
[ROW][C]235[/C][C]0.280294[/C][C]0.560588[/C][C]0.719706[/C][/ROW]
[ROW][C]236[/C][C]0.25015[/C][C]0.5003[/C][C]0.74985[/C][/ROW]
[ROW][C]237[/C][C]0.213876[/C][C]0.427753[/C][C]0.786124[/C][/ROW]
[ROW][C]238[/C][C]0.172237[/C][C]0.344475[/C][C]0.827763[/C][/ROW]
[ROW][C]239[/C][C]0.273828[/C][C]0.547656[/C][C]0.726172[/C][/ROW]
[ROW][C]240[/C][C]0.258836[/C][C]0.517672[/C][C]0.741164[/C][/ROW]
[ROW][C]241[/C][C]0.242693[/C][C]0.485386[/C][C]0.757307[/C][/ROW]
[ROW][C]242[/C][C]0.315952[/C][C]0.631905[/C][C]0.684048[/C][/ROW]
[ROW][C]243[/C][C]0.254723[/C][C]0.509445[/C][C]0.745277[/C][/ROW]
[ROW][C]244[/C][C]0.199499[/C][C]0.398998[/C][C]0.800501[/C][/ROW]
[ROW][C]245[/C][C]0.199012[/C][C]0.398024[/C][C]0.800988[/C][/ROW]
[ROW][C]246[/C][C]0.155324[/C][C]0.310647[/C][C]0.844676[/C][/ROW]
[ROW][C]247[/C][C]0.1114[/C][C]0.2228[/C][C]0.8886[/C][/ROW]
[ROW][C]248[/C][C]0.430374[/C][C]0.860747[/C][C]0.569626[/C][/ROW]
[ROW][C]249[/C][C]0.340842[/C][C]0.681684[/C][C]0.659158[/C][/ROW]
[ROW][C]250[/C][C]0.286756[/C][C]0.573512[/C][C]0.713244[/C][/ROW]
[ROW][C]251[/C][C]0.300168[/C][C]0.600336[/C][C]0.699832[/C][/ROW]
[ROW][C]252[/C][C]0.572124[/C][C]0.855752[/C][C]0.427876[/C][/ROW]
[ROW][C]253[/C][C]0.569894[/C][C]0.860213[/C][C]0.430106[/C][/ROW]
[ROW][C]254[/C][C]0.77314[/C][C]0.453721[/C][C]0.22686[/C][/ROW]
[ROW][C]255[/C][C]0.693598[/C][C]0.612804[/C][C]0.306402[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226310&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226310&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.7533770.4932460.246623
100.6612390.6775220.338761
110.5551640.8896730.444836
120.806390.387220.19361
130.956370.08725910.0436296
140.9508390.09832240.0491612
150.9804870.03902540.0195127
160.9686060.0627870.0313935
170.9573050.08538970.0426949
180.9480560.1038880.051944
190.9419910.1160190.0580093
200.9267070.1465860.0732931
210.9279480.1441030.0720517
220.955540.08891910.0444595
230.9423290.1153420.0576708
240.9388950.1222090.0611046
250.9202720.1594560.0797279
260.9980070.003986050.00199302
270.9970780.005844890.00292244
280.9955360.008928770.00446439
290.9935320.01293560.00646781
300.9966870.006625750.00331287
310.9950940.009811420.00490571
320.9932960.0134070.00670352
330.9917220.01655590.00827797
340.9882070.02358580.0117929
350.9841070.03178570.0158928
360.9781940.04361230.0218061
370.983310.03338040.0166902
380.9774420.04511510.0225576
390.9748510.05029840.0251492
400.9765080.04698360.0234918
410.9699340.06013240.0300662
420.9692210.06155830.0307791
430.9600380.07992470.0399624
440.9581560.08368770.0418438
450.946530.106940.0534701
460.9555040.08899230.0444962
470.9436540.1126920.0563461
480.9292560.1414880.0707442
490.9490040.1019920.0509958
500.9447420.1105150.0552576
510.9322320.1355360.0677678
520.9165580.1668840.0834422
530.9047120.1905760.095288
540.9031270.1937460.096873
550.899230.2015410.10077
560.8889150.2221690.111085
570.8800130.2399740.119987
580.8585390.2829220.141461
590.8856180.2287650.114382
600.8793570.2412860.120643
610.908480.183040.09152
620.9026160.1947670.0973837
630.9345090.1309820.0654909
640.9210210.1579570.0789786
650.9064810.1870380.093519
660.9173980.1652040.0826021
670.913320.173360.0866799
680.9055310.1889380.0944692
690.9315930.1368140.0684068
700.9366840.1266310.0633155
710.9289590.1420820.0710409
720.9478170.1043660.052183
730.9387160.1225690.0612843
740.9262180.1475650.0737823
750.9169030.1661930.0830967
760.9012260.1975490.0987745
770.918280.1634390.0817195
780.9039430.1921130.0960565
790.8971570.2056850.102843
800.8982520.2034960.101748
810.8805440.2389130.119456
820.8615740.2768520.138426
830.8560580.2878850.143942
840.8365410.3269180.163459
850.8122030.3755950.187797
860.7898610.4202780.210139
870.7624950.475010.237505
880.7324690.5350620.267531
890.7983020.4033960.201698
900.835290.3294210.16471
910.8117420.3765160.188258
920.788420.4231610.21158
930.768990.462020.23101
940.7442770.5114460.255723
950.7213410.5573180.278659
960.6981540.6036930.301846
970.6695170.6609660.330483
980.6728810.6542380.327119
990.6390210.7219580.360979
1000.6262680.7474630.373732
1010.6009980.7980040.399002
1020.5752950.8494090.424705
1030.6419950.7160090.358005
1040.6359230.7281540.364077
1050.6574250.6851490.342575
1060.6313570.7372850.368643
1070.6217030.7565940.378297
1080.6830690.6338610.316931
1090.6543530.6912940.345647
1100.6358290.7283420.364171
1110.642830.7143410.35717
1120.6504550.699090.349545
1130.6257880.7484230.374212
1140.7083020.5833950.291698
1150.6807560.6384890.319244
1160.6505920.6988160.349408
1170.6189080.7621850.381092
1180.600730.7985410.39927
1190.5685460.8629080.431454
1200.5442550.911490.455745
1210.5151530.9696940.484847
1220.4809040.9618090.519096
1230.4569830.9139660.543017
1240.4231630.8463260.576837
1250.4149630.8299260.585037
1260.3893190.7786380.610681
1270.370590.7411790.62941
1280.489730.979460.51027
1290.4683730.9367470.531627
1300.459490.9189790.54051
1310.447940.8958810.55206
1320.4150860.8301720.584914
1330.4255190.8510370.574481
1340.3952910.7905810.604709
1350.4171220.8342430.582878
1360.3996240.7992470.600376
1370.3675490.7350980.632451
1380.35070.7013990.6493
1390.3206970.6413940.679303
1400.2962520.5925050.703748
1410.2661690.5323380.733831
1420.2839150.567830.716085
1430.2553060.5106120.744694
1440.232940.465880.76706
1450.2249790.4499580.775021
1460.2158980.4317960.784102
1470.2373630.4747270.762637
1480.2582010.5164020.741799
1490.2723510.5447020.727649
1500.2758170.5516350.724183
1510.2499220.4998430.750078
1520.2248530.4497070.775147
1530.2343830.4687660.765617
1540.2747640.5495270.725236
1550.2539230.5078460.746077
1560.2319890.4639780.768011
1570.205730.411460.79427
1580.3000090.6000170.699991
1590.3249590.6499180.675041
1600.2929030.5858070.707097
1610.26230.5246010.7377
1620.2365040.4730070.763496
1630.2132770.4265540.786723
1640.3430880.6861760.656912
1650.3386070.6772140.661393
1660.3322790.6645580.667721
1670.3002760.6005510.699724
1680.2761510.5523020.723849
1690.3306420.6612840.669358
1700.3562770.7125540.643723
1710.3250730.6501460.674927
1720.3198480.6396950.680152
1730.4859360.9718710.514064
1740.4702030.9404060.529797
1750.4961820.9923630.503818
1760.5054470.9891060.494553
1770.5575560.8848880.442444
1780.5251120.9497760.474888
1790.5022240.9955520.497776
1800.5002440.9995120.499756
1810.464590.9291790.53541
1820.4571780.9143570.542822
1830.419120.838240.58088
1840.3887530.7775060.611247
1850.4098450.819690.590155
1860.4018040.8036070.598196
1870.3661470.7322940.633853
1880.3398250.6796510.660175
1890.305710.611420.69429
1900.2860910.5721820.713909
1910.3005360.6010710.699464
1920.2772990.5545980.722701
1930.2991360.5982720.700864
1940.2841340.5682690.715866
1950.2852060.5704120.714794
1960.2920460.5840910.707954
1970.3258730.6517460.674127
1980.2994380.5988760.700562
1990.3351650.670330.664835
2000.3000490.6000970.699951
2010.3380860.6761730.661914
2020.3171180.6342360.682882
2030.3650020.7300030.634998
2040.3260620.6521240.673938
2050.290440.5808810.70956
2060.2690140.5380280.730986
2070.2346310.4692630.765369
2080.2759560.5519130.724044
2090.2413610.4827210.758639
2100.2409310.4818630.759069
2110.2575420.5150850.742458
2120.2515260.5030520.748474
2130.2178840.4357690.782116
2140.2795310.5590630.720469
2150.2516670.5033350.748333
2160.2395020.4790040.760498
2170.2554180.5108370.744582
2180.2189740.4379480.781026
2190.2086950.417390.791305
2200.2053320.4106640.794668
2210.2232130.4464260.776787
2220.2319420.4638850.768058
2230.2230880.4461750.776912
2240.1900980.3801970.809902
2250.1662640.3325280.833736
2260.1934530.3869050.806547
2270.4626770.9253540.537323
2280.427560.8551190.57244
2290.4059490.8118980.594051
2300.3861850.7723690.613815
2310.3391880.6783760.660812
2320.3631840.7263670.636816
2330.3181830.6363660.681817
2340.2707840.5415680.729216
2350.2802940.5605880.719706
2360.250150.50030.74985
2370.2138760.4277530.786124
2380.1722370.3444750.827763
2390.2738280.5476560.726172
2400.2588360.5176720.741164
2410.2426930.4853860.757307
2420.3159520.6319050.684048
2430.2547230.5094450.745277
2440.1994990.3989980.800501
2450.1990120.3980240.800988
2460.1553240.3106470.844676
2470.11140.22280.8886
2480.4303740.8607470.569626
2490.3408420.6816840.659158
2500.2867560.5735120.713244
2510.3001680.6003360.699832
2520.5721240.8557520.427876
2530.5698940.8602130.430106
2540.773140.4537210.22686
2550.6935980.6128040.306402






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level50.0202429NOK
5% type I error level150.0607287NOK
10% type I error level260.105263NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 5 & 0.0202429 & NOK \tabularnewline
5% type I error level & 15 & 0.0607287 & NOK \tabularnewline
10% type I error level & 26 & 0.105263 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226310&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]5[/C][C]0.0202429[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]15[/C][C]0.0607287[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]26[/C][C]0.105263[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226310&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226310&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level50.0202429NOK
5% type I error level150.0607287NOK
10% type I error level260.105263NOK


Figures (Output of Computation)

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

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