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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 17 Nov 2013 12:46:19 -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/17/t138471048429nr4iicqdbrvmd.htm/, Retrieved Mon, 29 Apr 2024 03:00:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=225844, Retrieved Mon, 29 Apr 2024 03:00:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [time effect in su...] [2010-11-17 08:55:33] [b98453cac15ba1066b407e146608df68]
- RMPD    [Multiple Regression] [WS 7] [2013-11-17 17:46:19] [964acef360ea028b18952da197fdc0b8] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 15 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225844&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]15 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225844&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225844&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 time15 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 20.4347 + 0.44265Separate[t] -0.00883065Software[t] + 0.0308248Happiness[t] -0.058087Depression[t] -0.00632131t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Connected[t] =  +  20.4347 +  0.44265Separate[t] -0.00883065Software[t] +  0.0308248Happiness[t] -0.058087Depression[t] -0.00632131t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225844&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Connected[t] =  +  20.4347 +  0.44265Separate[t] -0.00883065Software[t] +  0.0308248Happiness[t] -0.058087Depression[t] -0.00632131t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225844&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225844&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 20.4347 + 0.44265Separate[t] -0.00883065Software[t] + 0.0308248Happiness[t] -0.058087Depression[t] -0.00632131t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)20.43473.049096.7021.28694e-106.43472e-11
Separate0.442650.05727357.7292.42434e-131.21217e-13
Software-0.008830650.0971039-0.090940.9276110.463805
Happiness0.03082480.1038670.29680.766880.38344
Depression-0.0580870.0739739-0.78520.4330350.216518
t-0.006321310.00299986-2.1070.03606540.0180327

\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) & 20.4347 & 3.04909 & 6.702 & 1.28694e-10 & 6.43472e-11 \tabularnewline
Separate & 0.44265 & 0.0572735 & 7.729 & 2.42434e-13 & 1.21217e-13 \tabularnewline
Software & -0.00883065 & 0.0971039 & -0.09094 & 0.927611 & 0.463805 \tabularnewline
Happiness & 0.0308248 & 0.103867 & 0.2968 & 0.76688 & 0.38344 \tabularnewline
Depression & -0.058087 & 0.0739739 & -0.7852 & 0.433035 & 0.216518 \tabularnewline
t & -0.00632131 & 0.00299986 & -2.107 & 0.0360654 & 0.0180327 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225844&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]20.4347[/C][C]3.04909[/C][C]6.702[/C][C]1.28694e-10[/C][C]6.43472e-11[/C][/ROW]
[ROW][C]Separate[/C][C]0.44265[/C][C]0.0572735[/C][C]7.729[/C][C]2.42434e-13[/C][C]1.21217e-13[/C][/ROW]
[ROW][C]Software[/C][C]-0.00883065[/C][C]0.0971039[/C][C]-0.09094[/C][C]0.927611[/C][C]0.463805[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0308248[/C][C]0.103867[/C][C]0.2968[/C][C]0.76688[/C][C]0.38344[/C][/ROW]
[ROW][C]Depression[/C][C]-0.058087[/C][C]0.0739739[/C][C]-0.7852[/C][C]0.433035[/C][C]0.216518[/C][/ROW]
[ROW][C]t[/C][C]-0.00632131[/C][C]0.00299986[/C][C]-2.107[/C][C]0.0360654[/C][C]0.0180327[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225844&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225844&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)20.43473.049096.7021.28694e-106.43472e-11
Separate0.442650.05727357.7292.42434e-131.21217e-13
Software-0.008830650.0971039-0.090940.9276110.463805
Happiness0.03082480.1038670.29680.766880.38344
Depression-0.0580870.0739739-0.78520.4330350.216518
t-0.006321310.00299986-2.1070.03606540.0180327






Multiple Linear Regression - Regression Statistics
Multiple R0.480774
R-squared0.231144
Adjusted R-squared0.216244
F-TEST (value)15.5127
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value2.42584e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.36103
Sum Squared Residuals2914.5

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.480774 \tabularnewline
R-squared & 0.231144 \tabularnewline
Adjusted R-squared & 0.216244 \tabularnewline
F-TEST (value) & 15.5127 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 258 \tabularnewline
p-value & 2.42584e-13 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.36103 \tabularnewline
Sum Squared Residuals & 2914.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225844&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.480774[/C][/ROW]
[ROW][C]R-squared[/C][C]0.231144[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.216244[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]15.5127[/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]2.42584e-13[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.36103[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2914.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225844&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225844&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 R0.480774
R-squared0.231144
Adjusted R-squared0.216244
F-TEST (value)15.5127
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value2.42584e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.36103
Sum Squared Residuals2914.5






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14136.87764.12241
23934.40564.59442
33035.3019-5.30186
43134.6367-3.63671
53435.9397-1.93969
63533.00311.99691
73933.16025.83976
83435.9885-1.98847
93635.64610.353932
103736.81990.180072
113833.94214.05786
123635.42390.576073
133835.17622.82378
143936.74972.25028
153336.5594-3.55942
163234.4533-2.45335
173634.0221.97797
183836.92071.07931
193936.88882.11119
203234.1051-2.10515
213234.8153-2.81526
223133.4376-2.43764
233936.72972.27031
243737.0059-0.00585678
253934.22054.77946
264134.0756.92504
273635.52270.477317
283336.0723-3.07234
293334.402-1.40199
303434.3481-0.348121
313133.8253-2.82531
322733.856-6.85596
333733.80313.19693
343436.3152-2.31525
353433.06340.936623
363234.7812-2.78124
372932.9591-3.95914
383634.46131.53872
392933.7651-4.76514
403534.52080.479182
413734.19162.80842
423434.3506-0.350641
433834.22373.7763
443534.23240.76764
453832.27955.72048
463735.11461.88538
473837.22570.774285
483334.9076-1.90763
493636.5012-0.501211
503833.93924.06079
513236.7217-4.72169
523232.9155-0.915489
533233.8946-1.89463
543436.3559-2.35591
553233.9386-1.93859
563735.14061.85944
573934.75664.24344
582934.9518-5.95176
593735.6891.31099
603534.51580.484218
613031.4663-1.46632
623834.69063.30944
633435.0476-1.04758
643135.0441-4.04405
653433.34720.652788
663535.95-0.950011
673634.73191.26814
683031.5321-1.53209
693937.30581.69422
703535.9134-0.91342
713835.5272.47297
723136.325-5.325
733436.8202-2.82018
743837.87340.126578
753431.56792.43208
763932.42056.57948
773735.98011.01992
783432.97991.02013
792833.2587-5.25871
803731.65255.34751
813335.5755-2.5755
823536.128-1.128
833734.20762.79236
843234.622-2.62198
853333.2076-0.207622
863836.78221.21784
873334.5634-1.56336
882933.4666-4.46665
893333.3114-0.311419
903135.4906-4.49057
913633.42122.57881
923537.603-2.60304
933231.69530.304734
942932.6886-3.68864
953935.53553.46452
963734.64632.35371
973533.25681.74323
983734.64442.35562
993235.5375-3.53746
1003835.55752.44253
1013734.63232.36766
1023635.83160.168355
1033231.78080.219243
1043336.4765-3.47645
1054033.00356.99646
1063835.00562.99436
1074136.44874.55134
1083634.58451.41547
1094337.18935.8107
1103034.3326-4.33262
1113133.6846-2.6846
1123237.54-5.53997
1133233.7909-1.79092
1143734.53362.46636
1153733.67013.32995
1163336.9109-3.91093
1173437.0069-3.00685
1183334.9931-1.99314
1193835.07212.92789
1203335.4556-2.45562
1213131.1249-0.124875
1223836.64431.35573
1233736.35190.648099
1243633.08162.9184
1253133.8813-2.88127
1263933.7745.22599
1274436.74127.25877
1283335.4282-2.42819
1293533.83681.16322
1303233.8938-1.89381
1312832.7899-4.78993
1324035.78924.21083
1332732.3674-5.36737
1343736.06770.93232
1353231.99220.0078424
1362828.2369-0.23687
1373434.5826-0.582597
1383034.3765-4.37646
1393534.35890.641118
1403134.6666-3.66664
1413234.4043-2.40433
1423035.5156-5.5156
1433034.6255-4.62552
1443129.37351.62646
1454033.02386.97617
1463231.14470.855334
1473634.91881.08118
1483232.8462-0.846243
1493532.75192.24811
1503836.48421.51583
1514235.15676.84335
1523436.1855-2.18547
1533536.3507-1.35073
1543833.61444.38558
1553332.46150.538468
1563633.01032.98969
1573235.3856-3.38562
1583335.2385-2.23855
1593433.37520.624812
1603235.4977-3.49765
1613434.753-0.753029
1622729.7454-2.74537
1633130.46090.539117
1643833.21334.78674
1653435.8294-1.82938
1662431.5973-7.59726
1673033.6238-3.62383
1682629.8897-3.88965
1693435.4291-1.42914
1702734.864-7.86399
1713732.20914.79094
1723635.41560.584356
1734134.32596.67409
1742929.7524-0.752443
1753631.35474.64526
1763234.5957-2.59568
1773733.20063.79936
1783031.8338-1.83384
1793132.8493-1.84933
1803835.12132.87873
1813634.91251.08746
1823532.38872.61135
1833134.9042-3.90423
1843833.18114.81894
1852231.4077-9.4077
1863234.3854-2.38541
1873633.82392.17612
1883932.67196.32807
1892831.1598-3.15984
1903234.2441-2.24412
1913234.6407-2.64068
1923836.67171.32831
1933233.3867-1.38669
1943534.89890.101066
1953232.9277-0.927666
1963735.58331.41672
1973432.15991.84006
1983335.0154-2.01538
1993332.84770.152347
2002632.8748-6.87484
2013031.6276-1.62757
2022432.1143-8.11429
2033432.67921.32081
2043432.79151.20854
2053333.9417-0.941675
2063434.678-0.677988
2073535.1416-0.141579
2083534.57120.428834
2093633.22022.77983
2103433.42250.577505
2113432.89231.1077
2124138.31942.68057
2133235.548-3.54796
2143032.7292-2.72918
2153533.8141.18603
2162829.7545-1.75445
2173334.3436-1.34363
2183933.75295.24707
2193633.44112.5589
2203635.85050.149477
2213533.18121.81882
2223834.67463.32541
2233332.40460.595377
2243133.0436-2.04361
2253433.92590.0741003
2263234.8008-2.8008
2273133.0229-2.02294
2283333.6369-0.636893
2293432.42571.57433
2303433.9780.0220113
2313431.93552.06453
2323335.0486-2.04856
2333233.8985-1.89851
2344132.85268.14745
2353432.99611.00393
2363632.10253.89746
2373731.54555.45454
2383630.42145.57863
2392932.2094-3.20935
2403731.77735.22273
2412732.7944-5.79442
2423533.44351.55652
2432830.7068-2.70681
2443532.88722.11275
2453732.16894.83105
2462933.4791-4.47907
2473233.816-1.816
2483632.04793.95214
2491927.2322-8.23218
2502127.0684-6.06837
2513133.4855-2.48546
2523332.35790.642068
2533633.59432.40574
2543332.560.440024
2553732.72434.2757
2563432.82531.17468
2573534.13980.860224
2583132.1298-1.12979
2593733.34153.65852
2603531.88773.11231
2612731.7017-4.70168
2623435.2586-1.25855
2634033.58366.41639
2642932.5857-3.58567

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 41 & 36.8776 & 4.12241 \tabularnewline
2 & 39 & 34.4056 & 4.59442 \tabularnewline
3 & 30 & 35.3019 & -5.30186 \tabularnewline
4 & 31 & 34.6367 & -3.63671 \tabularnewline
5 & 34 & 35.9397 & -1.93969 \tabularnewline
6 & 35 & 33.0031 & 1.99691 \tabularnewline
7 & 39 & 33.1602 & 5.83976 \tabularnewline
8 & 34 & 35.9885 & -1.98847 \tabularnewline
9 & 36 & 35.6461 & 0.353932 \tabularnewline
10 & 37 & 36.8199 & 0.180072 \tabularnewline
11 & 38 & 33.9421 & 4.05786 \tabularnewline
12 & 36 & 35.4239 & 0.576073 \tabularnewline
13 & 38 & 35.1762 & 2.82378 \tabularnewline
14 & 39 & 36.7497 & 2.25028 \tabularnewline
15 & 33 & 36.5594 & -3.55942 \tabularnewline
16 & 32 & 34.4533 & -2.45335 \tabularnewline
17 & 36 & 34.022 & 1.97797 \tabularnewline
18 & 38 & 36.9207 & 1.07931 \tabularnewline
19 & 39 & 36.8888 & 2.11119 \tabularnewline
20 & 32 & 34.1051 & -2.10515 \tabularnewline
21 & 32 & 34.8153 & -2.81526 \tabularnewline
22 & 31 & 33.4376 & -2.43764 \tabularnewline
23 & 39 & 36.7297 & 2.27031 \tabularnewline
24 & 37 & 37.0059 & -0.00585678 \tabularnewline
25 & 39 & 34.2205 & 4.77946 \tabularnewline
26 & 41 & 34.075 & 6.92504 \tabularnewline
27 & 36 & 35.5227 & 0.477317 \tabularnewline
28 & 33 & 36.0723 & -3.07234 \tabularnewline
29 & 33 & 34.402 & -1.40199 \tabularnewline
30 & 34 & 34.3481 & -0.348121 \tabularnewline
31 & 31 & 33.8253 & -2.82531 \tabularnewline
32 & 27 & 33.856 & -6.85596 \tabularnewline
33 & 37 & 33.8031 & 3.19693 \tabularnewline
34 & 34 & 36.3152 & -2.31525 \tabularnewline
35 & 34 & 33.0634 & 0.936623 \tabularnewline
36 & 32 & 34.7812 & -2.78124 \tabularnewline
37 & 29 & 32.9591 & -3.95914 \tabularnewline
38 & 36 & 34.4613 & 1.53872 \tabularnewline
39 & 29 & 33.7651 & -4.76514 \tabularnewline
40 & 35 & 34.5208 & 0.479182 \tabularnewline
41 & 37 & 34.1916 & 2.80842 \tabularnewline
42 & 34 & 34.3506 & -0.350641 \tabularnewline
43 & 38 & 34.2237 & 3.7763 \tabularnewline
44 & 35 & 34.2324 & 0.76764 \tabularnewline
45 & 38 & 32.2795 & 5.72048 \tabularnewline
46 & 37 & 35.1146 & 1.88538 \tabularnewline
47 & 38 & 37.2257 & 0.774285 \tabularnewline
48 & 33 & 34.9076 & -1.90763 \tabularnewline
49 & 36 & 36.5012 & -0.501211 \tabularnewline
50 & 38 & 33.9392 & 4.06079 \tabularnewline
51 & 32 & 36.7217 & -4.72169 \tabularnewline
52 & 32 & 32.9155 & -0.915489 \tabularnewline
53 & 32 & 33.8946 & -1.89463 \tabularnewline
54 & 34 & 36.3559 & -2.35591 \tabularnewline
55 & 32 & 33.9386 & -1.93859 \tabularnewline
56 & 37 & 35.1406 & 1.85944 \tabularnewline
57 & 39 & 34.7566 & 4.24344 \tabularnewline
58 & 29 & 34.9518 & -5.95176 \tabularnewline
59 & 37 & 35.689 & 1.31099 \tabularnewline
60 & 35 & 34.5158 & 0.484218 \tabularnewline
61 & 30 & 31.4663 & -1.46632 \tabularnewline
62 & 38 & 34.6906 & 3.30944 \tabularnewline
63 & 34 & 35.0476 & -1.04758 \tabularnewline
64 & 31 & 35.0441 & -4.04405 \tabularnewline
65 & 34 & 33.3472 & 0.652788 \tabularnewline
66 & 35 & 35.95 & -0.950011 \tabularnewline
67 & 36 & 34.7319 & 1.26814 \tabularnewline
68 & 30 & 31.5321 & -1.53209 \tabularnewline
69 & 39 & 37.3058 & 1.69422 \tabularnewline
70 & 35 & 35.9134 & -0.91342 \tabularnewline
71 & 38 & 35.527 & 2.47297 \tabularnewline
72 & 31 & 36.325 & -5.325 \tabularnewline
73 & 34 & 36.8202 & -2.82018 \tabularnewline
74 & 38 & 37.8734 & 0.126578 \tabularnewline
75 & 34 & 31.5679 & 2.43208 \tabularnewline
76 & 39 & 32.4205 & 6.57948 \tabularnewline
77 & 37 & 35.9801 & 1.01992 \tabularnewline
78 & 34 & 32.9799 & 1.02013 \tabularnewline
79 & 28 & 33.2587 & -5.25871 \tabularnewline
80 & 37 & 31.6525 & 5.34751 \tabularnewline
81 & 33 & 35.5755 & -2.5755 \tabularnewline
82 & 35 & 36.128 & -1.128 \tabularnewline
83 & 37 & 34.2076 & 2.79236 \tabularnewline
84 & 32 & 34.622 & -2.62198 \tabularnewline
85 & 33 & 33.2076 & -0.207622 \tabularnewline
86 & 38 & 36.7822 & 1.21784 \tabularnewline
87 & 33 & 34.5634 & -1.56336 \tabularnewline
88 & 29 & 33.4666 & -4.46665 \tabularnewline
89 & 33 & 33.3114 & -0.311419 \tabularnewline
90 & 31 & 35.4906 & -4.49057 \tabularnewline
91 & 36 & 33.4212 & 2.57881 \tabularnewline
92 & 35 & 37.603 & -2.60304 \tabularnewline
93 & 32 & 31.6953 & 0.304734 \tabularnewline
94 & 29 & 32.6886 & -3.68864 \tabularnewline
95 & 39 & 35.5355 & 3.46452 \tabularnewline
96 & 37 & 34.6463 & 2.35371 \tabularnewline
97 & 35 & 33.2568 & 1.74323 \tabularnewline
98 & 37 & 34.6444 & 2.35562 \tabularnewline
99 & 32 & 35.5375 & -3.53746 \tabularnewline
100 & 38 & 35.5575 & 2.44253 \tabularnewline
101 & 37 & 34.6323 & 2.36766 \tabularnewline
102 & 36 & 35.8316 & 0.168355 \tabularnewline
103 & 32 & 31.7808 & 0.219243 \tabularnewline
104 & 33 & 36.4765 & -3.47645 \tabularnewline
105 & 40 & 33.0035 & 6.99646 \tabularnewline
106 & 38 & 35.0056 & 2.99436 \tabularnewline
107 & 41 & 36.4487 & 4.55134 \tabularnewline
108 & 36 & 34.5845 & 1.41547 \tabularnewline
109 & 43 & 37.1893 & 5.8107 \tabularnewline
110 & 30 & 34.3326 & -4.33262 \tabularnewline
111 & 31 & 33.6846 & -2.6846 \tabularnewline
112 & 32 & 37.54 & -5.53997 \tabularnewline
113 & 32 & 33.7909 & -1.79092 \tabularnewline
114 & 37 & 34.5336 & 2.46636 \tabularnewline
115 & 37 & 33.6701 & 3.32995 \tabularnewline
116 & 33 & 36.9109 & -3.91093 \tabularnewline
117 & 34 & 37.0069 & -3.00685 \tabularnewline
118 & 33 & 34.9931 & -1.99314 \tabularnewline
119 & 38 & 35.0721 & 2.92789 \tabularnewline
120 & 33 & 35.4556 & -2.45562 \tabularnewline
121 & 31 & 31.1249 & -0.124875 \tabularnewline
122 & 38 & 36.6443 & 1.35573 \tabularnewline
123 & 37 & 36.3519 & 0.648099 \tabularnewline
124 & 36 & 33.0816 & 2.9184 \tabularnewline
125 & 31 & 33.8813 & -2.88127 \tabularnewline
126 & 39 & 33.774 & 5.22599 \tabularnewline
127 & 44 & 36.7412 & 7.25877 \tabularnewline
128 & 33 & 35.4282 & -2.42819 \tabularnewline
129 & 35 & 33.8368 & 1.16322 \tabularnewline
130 & 32 & 33.8938 & -1.89381 \tabularnewline
131 & 28 & 32.7899 & -4.78993 \tabularnewline
132 & 40 & 35.7892 & 4.21083 \tabularnewline
133 & 27 & 32.3674 & -5.36737 \tabularnewline
134 & 37 & 36.0677 & 0.93232 \tabularnewline
135 & 32 & 31.9922 & 0.0078424 \tabularnewline
136 & 28 & 28.2369 & -0.23687 \tabularnewline
137 & 34 & 34.5826 & -0.582597 \tabularnewline
138 & 30 & 34.3765 & -4.37646 \tabularnewline
139 & 35 & 34.3589 & 0.641118 \tabularnewline
140 & 31 & 34.6666 & -3.66664 \tabularnewline
141 & 32 & 34.4043 & -2.40433 \tabularnewline
142 & 30 & 35.5156 & -5.5156 \tabularnewline
143 & 30 & 34.6255 & -4.62552 \tabularnewline
144 & 31 & 29.3735 & 1.62646 \tabularnewline
145 & 40 & 33.0238 & 6.97617 \tabularnewline
146 & 32 & 31.1447 & 0.855334 \tabularnewline
147 & 36 & 34.9188 & 1.08118 \tabularnewline
148 & 32 & 32.8462 & -0.846243 \tabularnewline
149 & 35 & 32.7519 & 2.24811 \tabularnewline
150 & 38 & 36.4842 & 1.51583 \tabularnewline
151 & 42 & 35.1567 & 6.84335 \tabularnewline
152 & 34 & 36.1855 & -2.18547 \tabularnewline
153 & 35 & 36.3507 & -1.35073 \tabularnewline
154 & 38 & 33.6144 & 4.38558 \tabularnewline
155 & 33 & 32.4615 & 0.538468 \tabularnewline
156 & 36 & 33.0103 & 2.98969 \tabularnewline
157 & 32 & 35.3856 & -3.38562 \tabularnewline
158 & 33 & 35.2385 & -2.23855 \tabularnewline
159 & 34 & 33.3752 & 0.624812 \tabularnewline
160 & 32 & 35.4977 & -3.49765 \tabularnewline
161 & 34 & 34.753 & -0.753029 \tabularnewline
162 & 27 & 29.7454 & -2.74537 \tabularnewline
163 & 31 & 30.4609 & 0.539117 \tabularnewline
164 & 38 & 33.2133 & 4.78674 \tabularnewline
165 & 34 & 35.8294 & -1.82938 \tabularnewline
166 & 24 & 31.5973 & -7.59726 \tabularnewline
167 & 30 & 33.6238 & -3.62383 \tabularnewline
168 & 26 & 29.8897 & -3.88965 \tabularnewline
169 & 34 & 35.4291 & -1.42914 \tabularnewline
170 & 27 & 34.864 & -7.86399 \tabularnewline
171 & 37 & 32.2091 & 4.79094 \tabularnewline
172 & 36 & 35.4156 & 0.584356 \tabularnewline
173 & 41 & 34.3259 & 6.67409 \tabularnewline
174 & 29 & 29.7524 & -0.752443 \tabularnewline
175 & 36 & 31.3547 & 4.64526 \tabularnewline
176 & 32 & 34.5957 & -2.59568 \tabularnewline
177 & 37 & 33.2006 & 3.79936 \tabularnewline
178 & 30 & 31.8338 & -1.83384 \tabularnewline
179 & 31 & 32.8493 & -1.84933 \tabularnewline
180 & 38 & 35.1213 & 2.87873 \tabularnewline
181 & 36 & 34.9125 & 1.08746 \tabularnewline
182 & 35 & 32.3887 & 2.61135 \tabularnewline
183 & 31 & 34.9042 & -3.90423 \tabularnewline
184 & 38 & 33.1811 & 4.81894 \tabularnewline
185 & 22 & 31.4077 & -9.4077 \tabularnewline
186 & 32 & 34.3854 & -2.38541 \tabularnewline
187 & 36 & 33.8239 & 2.17612 \tabularnewline
188 & 39 & 32.6719 & 6.32807 \tabularnewline
189 & 28 & 31.1598 & -3.15984 \tabularnewline
190 & 32 & 34.2441 & -2.24412 \tabularnewline
191 & 32 & 34.6407 & -2.64068 \tabularnewline
192 & 38 & 36.6717 & 1.32831 \tabularnewline
193 & 32 & 33.3867 & -1.38669 \tabularnewline
194 & 35 & 34.8989 & 0.101066 \tabularnewline
195 & 32 & 32.9277 & -0.927666 \tabularnewline
196 & 37 & 35.5833 & 1.41672 \tabularnewline
197 & 34 & 32.1599 & 1.84006 \tabularnewline
198 & 33 & 35.0154 & -2.01538 \tabularnewline
199 & 33 & 32.8477 & 0.152347 \tabularnewline
200 & 26 & 32.8748 & -6.87484 \tabularnewline
201 & 30 & 31.6276 & -1.62757 \tabularnewline
202 & 24 & 32.1143 & -8.11429 \tabularnewline
203 & 34 & 32.6792 & 1.32081 \tabularnewline
204 & 34 & 32.7915 & 1.20854 \tabularnewline
205 & 33 & 33.9417 & -0.941675 \tabularnewline
206 & 34 & 34.678 & -0.677988 \tabularnewline
207 & 35 & 35.1416 & -0.141579 \tabularnewline
208 & 35 & 34.5712 & 0.428834 \tabularnewline
209 & 36 & 33.2202 & 2.77983 \tabularnewline
210 & 34 & 33.4225 & 0.577505 \tabularnewline
211 & 34 & 32.8923 & 1.1077 \tabularnewline
212 & 41 & 38.3194 & 2.68057 \tabularnewline
213 & 32 & 35.548 & -3.54796 \tabularnewline
214 & 30 & 32.7292 & -2.72918 \tabularnewline
215 & 35 & 33.814 & 1.18603 \tabularnewline
216 & 28 & 29.7545 & -1.75445 \tabularnewline
217 & 33 & 34.3436 & -1.34363 \tabularnewline
218 & 39 & 33.7529 & 5.24707 \tabularnewline
219 & 36 & 33.4411 & 2.5589 \tabularnewline
220 & 36 & 35.8505 & 0.149477 \tabularnewline
221 & 35 & 33.1812 & 1.81882 \tabularnewline
222 & 38 & 34.6746 & 3.32541 \tabularnewline
223 & 33 & 32.4046 & 0.595377 \tabularnewline
224 & 31 & 33.0436 & -2.04361 \tabularnewline
225 & 34 & 33.9259 & 0.0741003 \tabularnewline
226 & 32 & 34.8008 & -2.8008 \tabularnewline
227 & 31 & 33.0229 & -2.02294 \tabularnewline
228 & 33 & 33.6369 & -0.636893 \tabularnewline
229 & 34 & 32.4257 & 1.57433 \tabularnewline
230 & 34 & 33.978 & 0.0220113 \tabularnewline
231 & 34 & 31.9355 & 2.06453 \tabularnewline
232 & 33 & 35.0486 & -2.04856 \tabularnewline
233 & 32 & 33.8985 & -1.89851 \tabularnewline
234 & 41 & 32.8526 & 8.14745 \tabularnewline
235 & 34 & 32.9961 & 1.00393 \tabularnewline
236 & 36 & 32.1025 & 3.89746 \tabularnewline
237 & 37 & 31.5455 & 5.45454 \tabularnewline
238 & 36 & 30.4214 & 5.57863 \tabularnewline
239 & 29 & 32.2094 & -3.20935 \tabularnewline
240 & 37 & 31.7773 & 5.22273 \tabularnewline
241 & 27 & 32.7944 & -5.79442 \tabularnewline
242 & 35 & 33.4435 & 1.55652 \tabularnewline
243 & 28 & 30.7068 & -2.70681 \tabularnewline
244 & 35 & 32.8872 & 2.11275 \tabularnewline
245 & 37 & 32.1689 & 4.83105 \tabularnewline
246 & 29 & 33.4791 & -4.47907 \tabularnewline
247 & 32 & 33.816 & -1.816 \tabularnewline
248 & 36 & 32.0479 & 3.95214 \tabularnewline
249 & 19 & 27.2322 & -8.23218 \tabularnewline
250 & 21 & 27.0684 & -6.06837 \tabularnewline
251 & 31 & 33.4855 & -2.48546 \tabularnewline
252 & 33 & 32.3579 & 0.642068 \tabularnewline
253 & 36 & 33.5943 & 2.40574 \tabularnewline
254 & 33 & 32.56 & 0.440024 \tabularnewline
255 & 37 & 32.7243 & 4.2757 \tabularnewline
256 & 34 & 32.8253 & 1.17468 \tabularnewline
257 & 35 & 34.1398 & 0.860224 \tabularnewline
258 & 31 & 32.1298 & -1.12979 \tabularnewline
259 & 37 & 33.3415 & 3.65852 \tabularnewline
260 & 35 & 31.8877 & 3.11231 \tabularnewline
261 & 27 & 31.7017 & -4.70168 \tabularnewline
262 & 34 & 35.2586 & -1.25855 \tabularnewline
263 & 40 & 33.5836 & 6.41639 \tabularnewline
264 & 29 & 32.5857 & -3.58567 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225844&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]41[/C][C]36.8776[/C][C]4.12241[/C][/ROW]
[ROW][C]2[/C][C]39[/C][C]34.4056[/C][C]4.59442[/C][/ROW]
[ROW][C]3[/C][C]30[/C][C]35.3019[/C][C]-5.30186[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]34.6367[/C][C]-3.63671[/C][/ROW]
[ROW][C]5[/C][C]34[/C][C]35.9397[/C][C]-1.93969[/C][/ROW]
[ROW][C]6[/C][C]35[/C][C]33.0031[/C][C]1.99691[/C][/ROW]
[ROW][C]7[/C][C]39[/C][C]33.1602[/C][C]5.83976[/C][/ROW]
[ROW][C]8[/C][C]34[/C][C]35.9885[/C][C]-1.98847[/C][/ROW]
[ROW][C]9[/C][C]36[/C][C]35.6461[/C][C]0.353932[/C][/ROW]
[ROW][C]10[/C][C]37[/C][C]36.8199[/C][C]0.180072[/C][/ROW]
[ROW][C]11[/C][C]38[/C][C]33.9421[/C][C]4.05786[/C][/ROW]
[ROW][C]12[/C][C]36[/C][C]35.4239[/C][C]0.576073[/C][/ROW]
[ROW][C]13[/C][C]38[/C][C]35.1762[/C][C]2.82378[/C][/ROW]
[ROW][C]14[/C][C]39[/C][C]36.7497[/C][C]2.25028[/C][/ROW]
[ROW][C]15[/C][C]33[/C][C]36.5594[/C][C]-3.55942[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]34.4533[/C][C]-2.45335[/C][/ROW]
[ROW][C]17[/C][C]36[/C][C]34.022[/C][C]1.97797[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]36.9207[/C][C]1.07931[/C][/ROW]
[ROW][C]19[/C][C]39[/C][C]36.8888[/C][C]2.11119[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]34.1051[/C][C]-2.10515[/C][/ROW]
[ROW][C]21[/C][C]32[/C][C]34.8153[/C][C]-2.81526[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]33.4376[/C][C]-2.43764[/C][/ROW]
[ROW][C]23[/C][C]39[/C][C]36.7297[/C][C]2.27031[/C][/ROW]
[ROW][C]24[/C][C]37[/C][C]37.0059[/C][C]-0.00585678[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]34.2205[/C][C]4.77946[/C][/ROW]
[ROW][C]26[/C][C]41[/C][C]34.075[/C][C]6.92504[/C][/ROW]
[ROW][C]27[/C][C]36[/C][C]35.5227[/C][C]0.477317[/C][/ROW]
[ROW][C]28[/C][C]33[/C][C]36.0723[/C][C]-3.07234[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]34.402[/C][C]-1.40199[/C][/ROW]
[ROW][C]30[/C][C]34[/C][C]34.3481[/C][C]-0.348121[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]33.8253[/C][C]-2.82531[/C][/ROW]
[ROW][C]32[/C][C]27[/C][C]33.856[/C][C]-6.85596[/C][/ROW]
[ROW][C]33[/C][C]37[/C][C]33.8031[/C][C]3.19693[/C][/ROW]
[ROW][C]34[/C][C]34[/C][C]36.3152[/C][C]-2.31525[/C][/ROW]
[ROW][C]35[/C][C]34[/C][C]33.0634[/C][C]0.936623[/C][/ROW]
[ROW][C]36[/C][C]32[/C][C]34.7812[/C][C]-2.78124[/C][/ROW]
[ROW][C]37[/C][C]29[/C][C]32.9591[/C][C]-3.95914[/C][/ROW]
[ROW][C]38[/C][C]36[/C][C]34.4613[/C][C]1.53872[/C][/ROW]
[ROW][C]39[/C][C]29[/C][C]33.7651[/C][C]-4.76514[/C][/ROW]
[ROW][C]40[/C][C]35[/C][C]34.5208[/C][C]0.479182[/C][/ROW]
[ROW][C]41[/C][C]37[/C][C]34.1916[/C][C]2.80842[/C][/ROW]
[ROW][C]42[/C][C]34[/C][C]34.3506[/C][C]-0.350641[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]34.2237[/C][C]3.7763[/C][/ROW]
[ROW][C]44[/C][C]35[/C][C]34.2324[/C][C]0.76764[/C][/ROW]
[ROW][C]45[/C][C]38[/C][C]32.2795[/C][C]5.72048[/C][/ROW]
[ROW][C]46[/C][C]37[/C][C]35.1146[/C][C]1.88538[/C][/ROW]
[ROW][C]47[/C][C]38[/C][C]37.2257[/C][C]0.774285[/C][/ROW]
[ROW][C]48[/C][C]33[/C][C]34.9076[/C][C]-1.90763[/C][/ROW]
[ROW][C]49[/C][C]36[/C][C]36.5012[/C][C]-0.501211[/C][/ROW]
[ROW][C]50[/C][C]38[/C][C]33.9392[/C][C]4.06079[/C][/ROW]
[ROW][C]51[/C][C]32[/C][C]36.7217[/C][C]-4.72169[/C][/ROW]
[ROW][C]52[/C][C]32[/C][C]32.9155[/C][C]-0.915489[/C][/ROW]
[ROW][C]53[/C][C]32[/C][C]33.8946[/C][C]-1.89463[/C][/ROW]
[ROW][C]54[/C][C]34[/C][C]36.3559[/C][C]-2.35591[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]33.9386[/C][C]-1.93859[/C][/ROW]
[ROW][C]56[/C][C]37[/C][C]35.1406[/C][C]1.85944[/C][/ROW]
[ROW][C]57[/C][C]39[/C][C]34.7566[/C][C]4.24344[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]34.9518[/C][C]-5.95176[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]35.689[/C][C]1.31099[/C][/ROW]
[ROW][C]60[/C][C]35[/C][C]34.5158[/C][C]0.484218[/C][/ROW]
[ROW][C]61[/C][C]30[/C][C]31.4663[/C][C]-1.46632[/C][/ROW]
[ROW][C]62[/C][C]38[/C][C]34.6906[/C][C]3.30944[/C][/ROW]
[ROW][C]63[/C][C]34[/C][C]35.0476[/C][C]-1.04758[/C][/ROW]
[ROW][C]64[/C][C]31[/C][C]35.0441[/C][C]-4.04405[/C][/ROW]
[ROW][C]65[/C][C]34[/C][C]33.3472[/C][C]0.652788[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]35.95[/C][C]-0.950011[/C][/ROW]
[ROW][C]67[/C][C]36[/C][C]34.7319[/C][C]1.26814[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]31.5321[/C][C]-1.53209[/C][/ROW]
[ROW][C]69[/C][C]39[/C][C]37.3058[/C][C]1.69422[/C][/ROW]
[ROW][C]70[/C][C]35[/C][C]35.9134[/C][C]-0.91342[/C][/ROW]
[ROW][C]71[/C][C]38[/C][C]35.527[/C][C]2.47297[/C][/ROW]
[ROW][C]72[/C][C]31[/C][C]36.325[/C][C]-5.325[/C][/ROW]
[ROW][C]73[/C][C]34[/C][C]36.8202[/C][C]-2.82018[/C][/ROW]
[ROW][C]74[/C][C]38[/C][C]37.8734[/C][C]0.126578[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]31.5679[/C][C]2.43208[/C][/ROW]
[ROW][C]76[/C][C]39[/C][C]32.4205[/C][C]6.57948[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.9801[/C][C]1.01992[/C][/ROW]
[ROW][C]78[/C][C]34[/C][C]32.9799[/C][C]1.02013[/C][/ROW]
[ROW][C]79[/C][C]28[/C][C]33.2587[/C][C]-5.25871[/C][/ROW]
[ROW][C]80[/C][C]37[/C][C]31.6525[/C][C]5.34751[/C][/ROW]
[ROW][C]81[/C][C]33[/C][C]35.5755[/C][C]-2.5755[/C][/ROW]
[ROW][C]82[/C][C]35[/C][C]36.128[/C][C]-1.128[/C][/ROW]
[ROW][C]83[/C][C]37[/C][C]34.2076[/C][C]2.79236[/C][/ROW]
[ROW][C]84[/C][C]32[/C][C]34.622[/C][C]-2.62198[/C][/ROW]
[ROW][C]85[/C][C]33[/C][C]33.2076[/C][C]-0.207622[/C][/ROW]
[ROW][C]86[/C][C]38[/C][C]36.7822[/C][C]1.21784[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]34.5634[/C][C]-1.56336[/C][/ROW]
[ROW][C]88[/C][C]29[/C][C]33.4666[/C][C]-4.46665[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.3114[/C][C]-0.311419[/C][/ROW]
[ROW][C]90[/C][C]31[/C][C]35.4906[/C][C]-4.49057[/C][/ROW]
[ROW][C]91[/C][C]36[/C][C]33.4212[/C][C]2.57881[/C][/ROW]
[ROW][C]92[/C][C]35[/C][C]37.603[/C][C]-2.60304[/C][/ROW]
[ROW][C]93[/C][C]32[/C][C]31.6953[/C][C]0.304734[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]32.6886[/C][C]-3.68864[/C][/ROW]
[ROW][C]95[/C][C]39[/C][C]35.5355[/C][C]3.46452[/C][/ROW]
[ROW][C]96[/C][C]37[/C][C]34.6463[/C][C]2.35371[/C][/ROW]
[ROW][C]97[/C][C]35[/C][C]33.2568[/C][C]1.74323[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]34.6444[/C][C]2.35562[/C][/ROW]
[ROW][C]99[/C][C]32[/C][C]35.5375[/C][C]-3.53746[/C][/ROW]
[ROW][C]100[/C][C]38[/C][C]35.5575[/C][C]2.44253[/C][/ROW]
[ROW][C]101[/C][C]37[/C][C]34.6323[/C][C]2.36766[/C][/ROW]
[ROW][C]102[/C][C]36[/C][C]35.8316[/C][C]0.168355[/C][/ROW]
[ROW][C]103[/C][C]32[/C][C]31.7808[/C][C]0.219243[/C][/ROW]
[ROW][C]104[/C][C]33[/C][C]36.4765[/C][C]-3.47645[/C][/ROW]
[ROW][C]105[/C][C]40[/C][C]33.0035[/C][C]6.99646[/C][/ROW]
[ROW][C]106[/C][C]38[/C][C]35.0056[/C][C]2.99436[/C][/ROW]
[ROW][C]107[/C][C]41[/C][C]36.4487[/C][C]4.55134[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]34.5845[/C][C]1.41547[/C][/ROW]
[ROW][C]109[/C][C]43[/C][C]37.1893[/C][C]5.8107[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]34.3326[/C][C]-4.33262[/C][/ROW]
[ROW][C]111[/C][C]31[/C][C]33.6846[/C][C]-2.6846[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]37.54[/C][C]-5.53997[/C][/ROW]
[ROW][C]113[/C][C]32[/C][C]33.7909[/C][C]-1.79092[/C][/ROW]
[ROW][C]114[/C][C]37[/C][C]34.5336[/C][C]2.46636[/C][/ROW]
[ROW][C]115[/C][C]37[/C][C]33.6701[/C][C]3.32995[/C][/ROW]
[ROW][C]116[/C][C]33[/C][C]36.9109[/C][C]-3.91093[/C][/ROW]
[ROW][C]117[/C][C]34[/C][C]37.0069[/C][C]-3.00685[/C][/ROW]
[ROW][C]118[/C][C]33[/C][C]34.9931[/C][C]-1.99314[/C][/ROW]
[ROW][C]119[/C][C]38[/C][C]35.0721[/C][C]2.92789[/C][/ROW]
[ROW][C]120[/C][C]33[/C][C]35.4556[/C][C]-2.45562[/C][/ROW]
[ROW][C]121[/C][C]31[/C][C]31.1249[/C][C]-0.124875[/C][/ROW]
[ROW][C]122[/C][C]38[/C][C]36.6443[/C][C]1.35573[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]36.3519[/C][C]0.648099[/C][/ROW]
[ROW][C]124[/C][C]36[/C][C]33.0816[/C][C]2.9184[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]33.8813[/C][C]-2.88127[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]33.774[/C][C]5.22599[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]36.7412[/C][C]7.25877[/C][/ROW]
[ROW][C]128[/C][C]33[/C][C]35.4282[/C][C]-2.42819[/C][/ROW]
[ROW][C]129[/C][C]35[/C][C]33.8368[/C][C]1.16322[/C][/ROW]
[ROW][C]130[/C][C]32[/C][C]33.8938[/C][C]-1.89381[/C][/ROW]
[ROW][C]131[/C][C]28[/C][C]32.7899[/C][C]-4.78993[/C][/ROW]
[ROW][C]132[/C][C]40[/C][C]35.7892[/C][C]4.21083[/C][/ROW]
[ROW][C]133[/C][C]27[/C][C]32.3674[/C][C]-5.36737[/C][/ROW]
[ROW][C]134[/C][C]37[/C][C]36.0677[/C][C]0.93232[/C][/ROW]
[ROW][C]135[/C][C]32[/C][C]31.9922[/C][C]0.0078424[/C][/ROW]
[ROW][C]136[/C][C]28[/C][C]28.2369[/C][C]-0.23687[/C][/ROW]
[ROW][C]137[/C][C]34[/C][C]34.5826[/C][C]-0.582597[/C][/ROW]
[ROW][C]138[/C][C]30[/C][C]34.3765[/C][C]-4.37646[/C][/ROW]
[ROW][C]139[/C][C]35[/C][C]34.3589[/C][C]0.641118[/C][/ROW]
[ROW][C]140[/C][C]31[/C][C]34.6666[/C][C]-3.66664[/C][/ROW]
[ROW][C]141[/C][C]32[/C][C]34.4043[/C][C]-2.40433[/C][/ROW]
[ROW][C]142[/C][C]30[/C][C]35.5156[/C][C]-5.5156[/C][/ROW]
[ROW][C]143[/C][C]30[/C][C]34.6255[/C][C]-4.62552[/C][/ROW]
[ROW][C]144[/C][C]31[/C][C]29.3735[/C][C]1.62646[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]33.0238[/C][C]6.97617[/C][/ROW]
[ROW][C]146[/C][C]32[/C][C]31.1447[/C][C]0.855334[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]34.9188[/C][C]1.08118[/C][/ROW]
[ROW][C]148[/C][C]32[/C][C]32.8462[/C][C]-0.846243[/C][/ROW]
[ROW][C]149[/C][C]35[/C][C]32.7519[/C][C]2.24811[/C][/ROW]
[ROW][C]150[/C][C]38[/C][C]36.4842[/C][C]1.51583[/C][/ROW]
[ROW][C]151[/C][C]42[/C][C]35.1567[/C][C]6.84335[/C][/ROW]
[ROW][C]152[/C][C]34[/C][C]36.1855[/C][C]-2.18547[/C][/ROW]
[ROW][C]153[/C][C]35[/C][C]36.3507[/C][C]-1.35073[/C][/ROW]
[ROW][C]154[/C][C]38[/C][C]33.6144[/C][C]4.38558[/C][/ROW]
[ROW][C]155[/C][C]33[/C][C]32.4615[/C][C]0.538468[/C][/ROW]
[ROW][C]156[/C][C]36[/C][C]33.0103[/C][C]2.98969[/C][/ROW]
[ROW][C]157[/C][C]32[/C][C]35.3856[/C][C]-3.38562[/C][/ROW]
[ROW][C]158[/C][C]33[/C][C]35.2385[/C][C]-2.23855[/C][/ROW]
[ROW][C]159[/C][C]34[/C][C]33.3752[/C][C]0.624812[/C][/ROW]
[ROW][C]160[/C][C]32[/C][C]35.4977[/C][C]-3.49765[/C][/ROW]
[ROW][C]161[/C][C]34[/C][C]34.753[/C][C]-0.753029[/C][/ROW]
[ROW][C]162[/C][C]27[/C][C]29.7454[/C][C]-2.74537[/C][/ROW]
[ROW][C]163[/C][C]31[/C][C]30.4609[/C][C]0.539117[/C][/ROW]
[ROW][C]164[/C][C]38[/C][C]33.2133[/C][C]4.78674[/C][/ROW]
[ROW][C]165[/C][C]34[/C][C]35.8294[/C][C]-1.82938[/C][/ROW]
[ROW][C]166[/C][C]24[/C][C]31.5973[/C][C]-7.59726[/C][/ROW]
[ROW][C]167[/C][C]30[/C][C]33.6238[/C][C]-3.62383[/C][/ROW]
[ROW][C]168[/C][C]26[/C][C]29.8897[/C][C]-3.88965[/C][/ROW]
[ROW][C]169[/C][C]34[/C][C]35.4291[/C][C]-1.42914[/C][/ROW]
[ROW][C]170[/C][C]27[/C][C]34.864[/C][C]-7.86399[/C][/ROW]
[ROW][C]171[/C][C]37[/C][C]32.2091[/C][C]4.79094[/C][/ROW]
[ROW][C]172[/C][C]36[/C][C]35.4156[/C][C]0.584356[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]34.3259[/C][C]6.67409[/C][/ROW]
[ROW][C]174[/C][C]29[/C][C]29.7524[/C][C]-0.752443[/C][/ROW]
[ROW][C]175[/C][C]36[/C][C]31.3547[/C][C]4.64526[/C][/ROW]
[ROW][C]176[/C][C]32[/C][C]34.5957[/C][C]-2.59568[/C][/ROW]
[ROW][C]177[/C][C]37[/C][C]33.2006[/C][C]3.79936[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]31.8338[/C][C]-1.83384[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]32.8493[/C][C]-1.84933[/C][/ROW]
[ROW][C]180[/C][C]38[/C][C]35.1213[/C][C]2.87873[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]34.9125[/C][C]1.08746[/C][/ROW]
[ROW][C]182[/C][C]35[/C][C]32.3887[/C][C]2.61135[/C][/ROW]
[ROW][C]183[/C][C]31[/C][C]34.9042[/C][C]-3.90423[/C][/ROW]
[ROW][C]184[/C][C]38[/C][C]33.1811[/C][C]4.81894[/C][/ROW]
[ROW][C]185[/C][C]22[/C][C]31.4077[/C][C]-9.4077[/C][/ROW]
[ROW][C]186[/C][C]32[/C][C]34.3854[/C][C]-2.38541[/C][/ROW]
[ROW][C]187[/C][C]36[/C][C]33.8239[/C][C]2.17612[/C][/ROW]
[ROW][C]188[/C][C]39[/C][C]32.6719[/C][C]6.32807[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]31.1598[/C][C]-3.15984[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]34.2441[/C][C]-2.24412[/C][/ROW]
[ROW][C]191[/C][C]32[/C][C]34.6407[/C][C]-2.64068[/C][/ROW]
[ROW][C]192[/C][C]38[/C][C]36.6717[/C][C]1.32831[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]33.3867[/C][C]-1.38669[/C][/ROW]
[ROW][C]194[/C][C]35[/C][C]34.8989[/C][C]0.101066[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]32.9277[/C][C]-0.927666[/C][/ROW]
[ROW][C]196[/C][C]37[/C][C]35.5833[/C][C]1.41672[/C][/ROW]
[ROW][C]197[/C][C]34[/C][C]32.1599[/C][C]1.84006[/C][/ROW]
[ROW][C]198[/C][C]33[/C][C]35.0154[/C][C]-2.01538[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]32.8477[/C][C]0.152347[/C][/ROW]
[ROW][C]200[/C][C]26[/C][C]32.8748[/C][C]-6.87484[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]31.6276[/C][C]-1.62757[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]32.1143[/C][C]-8.11429[/C][/ROW]
[ROW][C]203[/C][C]34[/C][C]32.6792[/C][C]1.32081[/C][/ROW]
[ROW][C]204[/C][C]34[/C][C]32.7915[/C][C]1.20854[/C][/ROW]
[ROW][C]205[/C][C]33[/C][C]33.9417[/C][C]-0.941675[/C][/ROW]
[ROW][C]206[/C][C]34[/C][C]34.678[/C][C]-0.677988[/C][/ROW]
[ROW][C]207[/C][C]35[/C][C]35.1416[/C][C]-0.141579[/C][/ROW]
[ROW][C]208[/C][C]35[/C][C]34.5712[/C][C]0.428834[/C][/ROW]
[ROW][C]209[/C][C]36[/C][C]33.2202[/C][C]2.77983[/C][/ROW]
[ROW][C]210[/C][C]34[/C][C]33.4225[/C][C]0.577505[/C][/ROW]
[ROW][C]211[/C][C]34[/C][C]32.8923[/C][C]1.1077[/C][/ROW]
[ROW][C]212[/C][C]41[/C][C]38.3194[/C][C]2.68057[/C][/ROW]
[ROW][C]213[/C][C]32[/C][C]35.548[/C][C]-3.54796[/C][/ROW]
[ROW][C]214[/C][C]30[/C][C]32.7292[/C][C]-2.72918[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]33.814[/C][C]1.18603[/C][/ROW]
[ROW][C]216[/C][C]28[/C][C]29.7545[/C][C]-1.75445[/C][/ROW]
[ROW][C]217[/C][C]33[/C][C]34.3436[/C][C]-1.34363[/C][/ROW]
[ROW][C]218[/C][C]39[/C][C]33.7529[/C][C]5.24707[/C][/ROW]
[ROW][C]219[/C][C]36[/C][C]33.4411[/C][C]2.5589[/C][/ROW]
[ROW][C]220[/C][C]36[/C][C]35.8505[/C][C]0.149477[/C][/ROW]
[ROW][C]221[/C][C]35[/C][C]33.1812[/C][C]1.81882[/C][/ROW]
[ROW][C]222[/C][C]38[/C][C]34.6746[/C][C]3.32541[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]32.4046[/C][C]0.595377[/C][/ROW]
[ROW][C]224[/C][C]31[/C][C]33.0436[/C][C]-2.04361[/C][/ROW]
[ROW][C]225[/C][C]34[/C][C]33.9259[/C][C]0.0741003[/C][/ROW]
[ROW][C]226[/C][C]32[/C][C]34.8008[/C][C]-2.8008[/C][/ROW]
[ROW][C]227[/C][C]31[/C][C]33.0229[/C][C]-2.02294[/C][/ROW]
[ROW][C]228[/C][C]33[/C][C]33.6369[/C][C]-0.636893[/C][/ROW]
[ROW][C]229[/C][C]34[/C][C]32.4257[/C][C]1.57433[/C][/ROW]
[ROW][C]230[/C][C]34[/C][C]33.978[/C][C]0.0220113[/C][/ROW]
[ROW][C]231[/C][C]34[/C][C]31.9355[/C][C]2.06453[/C][/ROW]
[ROW][C]232[/C][C]33[/C][C]35.0486[/C][C]-2.04856[/C][/ROW]
[ROW][C]233[/C][C]32[/C][C]33.8985[/C][C]-1.89851[/C][/ROW]
[ROW][C]234[/C][C]41[/C][C]32.8526[/C][C]8.14745[/C][/ROW]
[ROW][C]235[/C][C]34[/C][C]32.9961[/C][C]1.00393[/C][/ROW]
[ROW][C]236[/C][C]36[/C][C]32.1025[/C][C]3.89746[/C][/ROW]
[ROW][C]237[/C][C]37[/C][C]31.5455[/C][C]5.45454[/C][/ROW]
[ROW][C]238[/C][C]36[/C][C]30.4214[/C][C]5.57863[/C][/ROW]
[ROW][C]239[/C][C]29[/C][C]32.2094[/C][C]-3.20935[/C][/ROW]
[ROW][C]240[/C][C]37[/C][C]31.7773[/C][C]5.22273[/C][/ROW]
[ROW][C]241[/C][C]27[/C][C]32.7944[/C][C]-5.79442[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]33.4435[/C][C]1.55652[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]30.7068[/C][C]-2.70681[/C][/ROW]
[ROW][C]244[/C][C]35[/C][C]32.8872[/C][C]2.11275[/C][/ROW]
[ROW][C]245[/C][C]37[/C][C]32.1689[/C][C]4.83105[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]33.4791[/C][C]-4.47907[/C][/ROW]
[ROW][C]247[/C][C]32[/C][C]33.816[/C][C]-1.816[/C][/ROW]
[ROW][C]248[/C][C]36[/C][C]32.0479[/C][C]3.95214[/C][/ROW]
[ROW][C]249[/C][C]19[/C][C]27.2322[/C][C]-8.23218[/C][/ROW]
[ROW][C]250[/C][C]21[/C][C]27.0684[/C][C]-6.06837[/C][/ROW]
[ROW][C]251[/C][C]31[/C][C]33.4855[/C][C]-2.48546[/C][/ROW]
[ROW][C]252[/C][C]33[/C][C]32.3579[/C][C]0.642068[/C][/ROW]
[ROW][C]253[/C][C]36[/C][C]33.5943[/C][C]2.40574[/C][/ROW]
[ROW][C]254[/C][C]33[/C][C]32.56[/C][C]0.440024[/C][/ROW]
[ROW][C]255[/C][C]37[/C][C]32.7243[/C][C]4.2757[/C][/ROW]
[ROW][C]256[/C][C]34[/C][C]32.8253[/C][C]1.17468[/C][/ROW]
[ROW][C]257[/C][C]35[/C][C]34.1398[/C][C]0.860224[/C][/ROW]
[ROW][C]258[/C][C]31[/C][C]32.1298[/C][C]-1.12979[/C][/ROW]
[ROW][C]259[/C][C]37[/C][C]33.3415[/C][C]3.65852[/C][/ROW]
[ROW][C]260[/C][C]35[/C][C]31.8877[/C][C]3.11231[/C][/ROW]
[ROW][C]261[/C][C]27[/C][C]31.7017[/C][C]-4.70168[/C][/ROW]
[ROW][C]262[/C][C]34[/C][C]35.2586[/C][C]-1.25855[/C][/ROW]
[ROW][C]263[/C][C]40[/C][C]33.5836[/C][C]6.41639[/C][/ROW]
[ROW][C]264[/C][C]29[/C][C]32.5857[/C][C]-3.58567[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225844&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225844&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
14136.87764.12241
23934.40564.59442
33035.3019-5.30186
43134.6367-3.63671
53435.9397-1.93969
63533.00311.99691
73933.16025.83976
83435.9885-1.98847
93635.64610.353932
103736.81990.180072
113833.94214.05786
123635.42390.576073
133835.17622.82378
143936.74972.25028
153336.5594-3.55942
163234.4533-2.45335
173634.0221.97797
183836.92071.07931
193936.88882.11119
203234.1051-2.10515
213234.8153-2.81526
223133.4376-2.43764
233936.72972.27031
243737.0059-0.00585678
253934.22054.77946
264134.0756.92504
273635.52270.477317
283336.0723-3.07234
293334.402-1.40199
303434.3481-0.348121
313133.8253-2.82531
322733.856-6.85596
333733.80313.19693
343436.3152-2.31525
353433.06340.936623
363234.7812-2.78124
372932.9591-3.95914
383634.46131.53872
392933.7651-4.76514
403534.52080.479182
413734.19162.80842
423434.3506-0.350641
433834.22373.7763
443534.23240.76764
453832.27955.72048
463735.11461.88538
473837.22570.774285
483334.9076-1.90763
493636.5012-0.501211
503833.93924.06079
513236.7217-4.72169
523232.9155-0.915489
533233.8946-1.89463
543436.3559-2.35591
553233.9386-1.93859
563735.14061.85944
573934.75664.24344
582934.9518-5.95176
593735.6891.31099
603534.51580.484218
613031.4663-1.46632
623834.69063.30944
633435.0476-1.04758
643135.0441-4.04405
653433.34720.652788
663535.95-0.950011
673634.73191.26814
683031.5321-1.53209
693937.30581.69422
703535.9134-0.91342
713835.5272.47297
723136.325-5.325
733436.8202-2.82018
743837.87340.126578
753431.56792.43208
763932.42056.57948
773735.98011.01992
783432.97991.02013
792833.2587-5.25871
803731.65255.34751
813335.5755-2.5755
823536.128-1.128
833734.20762.79236
843234.622-2.62198
853333.2076-0.207622
863836.78221.21784
873334.5634-1.56336
882933.4666-4.46665
893333.3114-0.311419
903135.4906-4.49057
913633.42122.57881
923537.603-2.60304
933231.69530.304734
942932.6886-3.68864
953935.53553.46452
963734.64632.35371
973533.25681.74323
983734.64442.35562
993235.5375-3.53746
1003835.55752.44253
1013734.63232.36766
1023635.83160.168355
1033231.78080.219243
1043336.4765-3.47645
1054033.00356.99646
1063835.00562.99436
1074136.44874.55134
1083634.58451.41547
1094337.18935.8107
1103034.3326-4.33262
1113133.6846-2.6846
1123237.54-5.53997
1133233.7909-1.79092
1143734.53362.46636
1153733.67013.32995
1163336.9109-3.91093
1173437.0069-3.00685
1183334.9931-1.99314
1193835.07212.92789
1203335.4556-2.45562
1213131.1249-0.124875
1223836.64431.35573
1233736.35190.648099
1243633.08162.9184
1253133.8813-2.88127
1263933.7745.22599
1274436.74127.25877
1283335.4282-2.42819
1293533.83681.16322
1303233.8938-1.89381
1312832.7899-4.78993
1324035.78924.21083
1332732.3674-5.36737
1343736.06770.93232
1353231.99220.0078424
1362828.2369-0.23687
1373434.5826-0.582597
1383034.3765-4.37646
1393534.35890.641118
1403134.6666-3.66664
1413234.4043-2.40433
1423035.5156-5.5156
1433034.6255-4.62552
1443129.37351.62646
1454033.02386.97617
1463231.14470.855334
1473634.91881.08118
1483232.8462-0.846243
1493532.75192.24811
1503836.48421.51583
1514235.15676.84335
1523436.1855-2.18547
1533536.3507-1.35073
1543833.61444.38558
1553332.46150.538468
1563633.01032.98969
1573235.3856-3.38562
1583335.2385-2.23855
1593433.37520.624812
1603235.4977-3.49765
1613434.753-0.753029
1622729.7454-2.74537
1633130.46090.539117
1643833.21334.78674
1653435.8294-1.82938
1662431.5973-7.59726
1673033.6238-3.62383
1682629.8897-3.88965
1693435.4291-1.42914
1702734.864-7.86399
1713732.20914.79094
1723635.41560.584356
1734134.32596.67409
1742929.7524-0.752443
1753631.35474.64526
1763234.5957-2.59568
1773733.20063.79936
1783031.8338-1.83384
1793132.8493-1.84933
1803835.12132.87873
1813634.91251.08746
1823532.38872.61135
1833134.9042-3.90423
1843833.18114.81894
1852231.4077-9.4077
1863234.3854-2.38541
1873633.82392.17612
1883932.67196.32807
1892831.1598-3.15984
1903234.2441-2.24412
1913234.6407-2.64068
1923836.67171.32831
1933233.3867-1.38669
1943534.89890.101066
1953232.9277-0.927666
1963735.58331.41672
1973432.15991.84006
1983335.0154-2.01538
1993332.84770.152347
2002632.8748-6.87484
2013031.6276-1.62757
2022432.1143-8.11429
2033432.67921.32081
2043432.79151.20854
2053333.9417-0.941675
2063434.678-0.677988
2073535.1416-0.141579
2083534.57120.428834
2093633.22022.77983
2103433.42250.577505
2113432.89231.1077
2124138.31942.68057
2133235.548-3.54796
2143032.7292-2.72918
2153533.8141.18603
2162829.7545-1.75445
2173334.3436-1.34363
2183933.75295.24707
2193633.44112.5589
2203635.85050.149477
2213533.18121.81882
2223834.67463.32541
2233332.40460.595377
2243133.0436-2.04361
2253433.92590.0741003
2263234.8008-2.8008
2273133.0229-2.02294
2283333.6369-0.636893
2293432.42571.57433
2303433.9780.0220113
2313431.93552.06453
2323335.0486-2.04856
2333233.8985-1.89851
2344132.85268.14745
2353432.99611.00393
2363632.10253.89746
2373731.54555.45454
2383630.42145.57863
2392932.2094-3.20935
2403731.77735.22273
2412732.7944-5.79442
2423533.44351.55652
2432830.7068-2.70681
2443532.88722.11275
2453732.16894.83105
2462933.4791-4.47907
2473233.816-1.816
2483632.04793.95214
2491927.2322-8.23218
2502127.0684-6.06837
2513133.4855-2.48546
2523332.35790.642068
2533633.59432.40574
2543332.560.440024
2553732.72434.2757
2563432.82531.17468
2573534.13980.860224
2583132.1298-1.12979
2593733.34153.65852
2603531.88773.11231
2612731.7017-4.70168
2623435.2586-1.25855
2634033.58366.41639
2642932.5857-3.58567






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9124440.1751130.0875563
100.8438190.3123610.156181
110.7785420.4429170.221458
120.7143870.5712260.285613
130.7702930.4594140.229707
140.6890240.6219530.310976
150.7159640.5680710.284036
160.6969510.6060990.303049
170.6209450.7581090.379055
180.5464510.9070980.453549
190.5132880.9734230.486712
200.5043240.9913520.495676
210.5038140.9923720.496186
220.4342010.8684030.565799
230.4389680.8779360.561032
240.3690540.7381090.630946
250.4205310.8410630.579469
260.6507130.6985740.349287
270.594660.810680.40534
280.5864070.8271870.413593
290.5482790.9034430.451721
300.495730.991460.50427
310.4954860.9909720.504514
320.6522580.6954850.347742
330.6518780.6962450.348122
340.6068640.7862720.393136
350.5591610.8816790.440839
360.5279610.9440780.472039
370.4970050.9940090.502995
380.4708240.9416480.529176
390.4942810.9885620.505719
400.454740.9094790.54526
410.4602390.9204790.539761
420.4131260.8262510.586874
430.4099990.8199990.590001
440.3790940.7581870.620906
450.4568660.9137320.543134
460.4333780.8667560.566622
470.3910540.7821090.608946
480.3565580.7131160.643442
490.3178970.6357940.682103
500.3255020.6510040.674498
510.3615570.7231140.638443
520.3207280.6414570.679272
530.2839530.5679050.716047
540.2506770.5013540.749323
550.2177590.4355170.782241
560.2299830.4599650.770017
570.2631030.5262070.736897
580.3489850.6979710.651015
590.3238840.6477670.676116
600.2910910.5821820.708909
610.2571580.5143160.742842
620.263110.526220.73689
630.2311220.4622440.768878
640.2310740.4621470.768926
650.2008340.4016680.799166
660.1725320.3450640.827468
670.1560.3119990.844
680.1416010.2832010.858399
690.1357650.2715290.864235
700.1144150.2288310.885585
710.1147140.2294290.885286
720.132870.2657390.86713
730.1195780.2391560.880422
740.1022550.204510.897745
750.09106250.1821250.908938
760.1633820.3267640.836618
770.1437210.2874420.856279
780.1237160.2474310.876284
790.1638520.3277050.836148
800.1885430.3770860.811457
810.1738270.3476540.826173
820.1505040.3010080.849496
830.1443570.2887140.855643
840.1339080.2678170.866092
850.1140930.2281850.885907
860.1057110.2114230.894289
870.09174960.1834990.90825
880.1035270.2070540.896473
890.08765620.1753120.912344
900.09196630.1839330.908034
910.08623290.1724660.913767
920.07572630.1514530.924274
930.06320250.1264050.936797
940.06693750.1338750.933063
950.07552210.1510440.924478
960.07264650.1452930.927354
970.064190.128380.93581
980.0595020.1190040.940498
990.05791860.1158370.942081
1000.05414570.1082910.945854
1010.05194280.1038860.948057
1020.04284650.0856930.957153
1030.03543730.07087460.964563
1040.03325790.06651590.966742
1050.06817470.1363490.931825
1060.06719360.1343870.932806
1070.08475280.1695060.915247
1080.0746220.1492440.925378
1090.1166720.2333440.883328
1100.1308890.2617790.869111
1110.1255620.2511240.874438
1120.1502020.3004040.849798
1130.135570.2711390.86443
1140.1278160.2556320.872184
1150.1280290.2560590.871971
1160.1302110.2604230.869789
1170.1219770.2439540.878023
1180.1086390.2172790.891361
1190.1060980.2121970.893902
1200.09679080.1935820.903209
1210.08407050.1681410.91593
1220.07495180.1499040.925048
1230.06425970.1285190.93574
1240.06165840.1233170.938342
1250.05864260.1172850.941357
1260.07648480.152970.923515
1270.1429610.2859220.857039
1280.1340690.2681390.865931
1290.1185960.2371920.881404
1300.1064630.2129250.893537
1310.1226870.2453740.877313
1320.1373160.2746320.862684
1330.1704690.3409370.829531
1340.1514520.3029050.848548
1350.1325720.2651450.867428
1360.1157150.231430.884285
1370.09941370.1988270.900586
1380.1061940.2123870.893806
1390.09185170.1837030.908148
1400.09165470.1833090.908345
1410.08312790.1662560.916872
1420.1040690.2081370.895931
1430.1158590.2317180.884141
1440.1053260.2106520.894674
1450.1767470.3534950.823253
1460.1592340.3184690.840766
1470.14240.2847990.8576
1480.1237250.2474510.876275
1490.116930.233860.88307
1500.1045290.2090580.895471
1510.1731810.3463620.826819
1520.1576090.3152180.842391
1530.1391890.2783790.860811
1540.1590350.3180690.840965
1550.1407190.2814390.859281
1560.1433270.2866540.856673
1570.1405710.2811430.859429
1580.1279660.2559320.872034
1590.1126590.2253180.887341
1600.1126690.2253380.887331
1610.09675350.1935070.903247
1620.08890310.1778060.911097
1630.07823790.1564760.921762
1640.1014770.2029550.898523
1650.09016880.1803380.909831
1660.1522070.3044150.847793
1670.1498070.2996140.850193
1680.146650.29330.85335
1690.1305340.2610670.869466
1700.2444570.4889140.755543
1710.2739310.5478610.726069
1720.2450110.4900210.754989
1730.3391640.6783280.660836
1740.3073420.6146830.692658
1750.3761180.7522350.623882
1760.3564580.7129170.643542
1770.3723240.7446470.627676
1780.3410720.6821440.658928
1790.3115220.6230450.688478
1800.3026180.6052370.697382
1810.2758780.5517560.724122
1820.2827990.5655980.717201
1830.2834260.5668530.716574
1840.3564870.7129750.643513
1850.537760.9244790.46224
1860.520710.9585810.47929
1870.504320.9913590.49568
1880.6606840.6786330.339316
1890.6359650.728070.364035
1900.6153660.7692680.384634
1910.5942980.8114050.405702
1920.5607050.878590.439295
1930.5229170.9541650.477083
1940.482850.96570.51715
1950.4425090.8850190.557491
1960.4101980.8203950.589802
1970.3887930.7775870.611207
1980.3652780.7305560.634722
1990.3273950.654790.672605
2000.4251540.8503070.574846
2010.3896050.779210.610395
2020.5614480.8771040.438552
2030.5295740.9408530.470426
2040.4916540.9833070.508346
2050.4504720.9009430.549528
2060.4135480.8270950.586452
2070.3745780.7491560.625422
2080.3364050.672810.663595
2090.319580.639160.68042
2100.2816470.5632940.718353
2110.2471810.4943620.752819
2120.2208250.441650.779175
2130.2665580.5331160.733442
2140.2555360.5110720.744464
2150.2227490.4454980.777251
2160.1923990.3847980.807601
2170.1739020.3478040.826098
2180.1986670.3973340.801333
2190.1725230.3450470.827477
2200.1515430.3030850.848457
2210.1284850.2569710.871515
2220.1166750.233350.883325
2230.09442920.1888580.905571
2240.07943820.1588760.920562
2250.06777760.1355550.932222
2260.06807390.1361480.931926
2270.06419150.1283830.935808
2280.05336950.1067390.946631
2290.04184170.08368330.958158
2300.03374890.06749780.966251
2310.02605180.05210350.973948
2320.03957370.07914730.960426
2330.0432680.0865360.956732
2340.07073860.1414770.929261
2350.05325240.1065050.946748
2360.04847530.09695070.951525
2370.05920010.11840.9408
2380.1845680.3691360.815432
2390.1499560.2999130.850044
2400.2919250.583850.708075
2410.3208470.6416940.679153
2420.2656840.5313680.734316
2430.2354350.470870.764565
2440.186510.3730190.81349
2450.4318990.8637990.568101
2460.6079490.7841030.392051
2470.5945670.8108660.405433
2480.6075160.7849670.392484
2490.6329430.7341130.367057
2500.5468840.9062310.453116
2510.6397770.7204470.360223
2520.6935210.6129580.306479
2530.7585850.482830.241415
2540.7614980.4770040.238502
2550.6039730.7920530.396027

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.912444 & 0.175113 & 0.0875563 \tabularnewline
10 & 0.843819 & 0.312361 & 0.156181 \tabularnewline
11 & 0.778542 & 0.442917 & 0.221458 \tabularnewline
12 & 0.714387 & 0.571226 & 0.285613 \tabularnewline
13 & 0.770293 & 0.459414 & 0.229707 \tabularnewline
14 & 0.689024 & 0.621953 & 0.310976 \tabularnewline
15 & 0.715964 & 0.568071 & 0.284036 \tabularnewline
16 & 0.696951 & 0.606099 & 0.303049 \tabularnewline
17 & 0.620945 & 0.758109 & 0.379055 \tabularnewline
18 & 0.546451 & 0.907098 & 0.453549 \tabularnewline
19 & 0.513288 & 0.973423 & 0.486712 \tabularnewline
20 & 0.504324 & 0.991352 & 0.495676 \tabularnewline
21 & 0.503814 & 0.992372 & 0.496186 \tabularnewline
22 & 0.434201 & 0.868403 & 0.565799 \tabularnewline
23 & 0.438968 & 0.877936 & 0.561032 \tabularnewline
24 & 0.369054 & 0.738109 & 0.630946 \tabularnewline
25 & 0.420531 & 0.841063 & 0.579469 \tabularnewline
26 & 0.650713 & 0.698574 & 0.349287 \tabularnewline
27 & 0.59466 & 0.81068 & 0.40534 \tabularnewline
28 & 0.586407 & 0.827187 & 0.413593 \tabularnewline
29 & 0.548279 & 0.903443 & 0.451721 \tabularnewline
30 & 0.49573 & 0.99146 & 0.50427 \tabularnewline
31 & 0.495486 & 0.990972 & 0.504514 \tabularnewline
32 & 0.652258 & 0.695485 & 0.347742 \tabularnewline
33 & 0.651878 & 0.696245 & 0.348122 \tabularnewline
34 & 0.606864 & 0.786272 & 0.393136 \tabularnewline
35 & 0.559161 & 0.881679 & 0.440839 \tabularnewline
36 & 0.527961 & 0.944078 & 0.472039 \tabularnewline
37 & 0.497005 & 0.994009 & 0.502995 \tabularnewline
38 & 0.470824 & 0.941648 & 0.529176 \tabularnewline
39 & 0.494281 & 0.988562 & 0.505719 \tabularnewline
40 & 0.45474 & 0.909479 & 0.54526 \tabularnewline
41 & 0.460239 & 0.920479 & 0.539761 \tabularnewline
42 & 0.413126 & 0.826251 & 0.586874 \tabularnewline
43 & 0.409999 & 0.819999 & 0.590001 \tabularnewline
44 & 0.379094 & 0.758187 & 0.620906 \tabularnewline
45 & 0.456866 & 0.913732 & 0.543134 \tabularnewline
46 & 0.433378 & 0.866756 & 0.566622 \tabularnewline
47 & 0.391054 & 0.782109 & 0.608946 \tabularnewline
48 & 0.356558 & 0.713116 & 0.643442 \tabularnewline
49 & 0.317897 & 0.635794 & 0.682103 \tabularnewline
50 & 0.325502 & 0.651004 & 0.674498 \tabularnewline
51 & 0.361557 & 0.723114 & 0.638443 \tabularnewline
52 & 0.320728 & 0.641457 & 0.679272 \tabularnewline
53 & 0.283953 & 0.567905 & 0.716047 \tabularnewline
54 & 0.250677 & 0.501354 & 0.749323 \tabularnewline
55 & 0.217759 & 0.435517 & 0.782241 \tabularnewline
56 & 0.229983 & 0.459965 & 0.770017 \tabularnewline
57 & 0.263103 & 0.526207 & 0.736897 \tabularnewline
58 & 0.348985 & 0.697971 & 0.651015 \tabularnewline
59 & 0.323884 & 0.647767 & 0.676116 \tabularnewline
60 & 0.291091 & 0.582182 & 0.708909 \tabularnewline
61 & 0.257158 & 0.514316 & 0.742842 \tabularnewline
62 & 0.26311 & 0.52622 & 0.73689 \tabularnewline
63 & 0.231122 & 0.462244 & 0.768878 \tabularnewline
64 & 0.231074 & 0.462147 & 0.768926 \tabularnewline
65 & 0.200834 & 0.401668 & 0.799166 \tabularnewline
66 & 0.172532 & 0.345064 & 0.827468 \tabularnewline
67 & 0.156 & 0.311999 & 0.844 \tabularnewline
68 & 0.141601 & 0.283201 & 0.858399 \tabularnewline
69 & 0.135765 & 0.271529 & 0.864235 \tabularnewline
70 & 0.114415 & 0.228831 & 0.885585 \tabularnewline
71 & 0.114714 & 0.229429 & 0.885286 \tabularnewline
72 & 0.13287 & 0.265739 & 0.86713 \tabularnewline
73 & 0.119578 & 0.239156 & 0.880422 \tabularnewline
74 & 0.102255 & 0.20451 & 0.897745 \tabularnewline
75 & 0.0910625 & 0.182125 & 0.908938 \tabularnewline
76 & 0.163382 & 0.326764 & 0.836618 \tabularnewline
77 & 0.143721 & 0.287442 & 0.856279 \tabularnewline
78 & 0.123716 & 0.247431 & 0.876284 \tabularnewline
79 & 0.163852 & 0.327705 & 0.836148 \tabularnewline
80 & 0.188543 & 0.377086 & 0.811457 \tabularnewline
81 & 0.173827 & 0.347654 & 0.826173 \tabularnewline
82 & 0.150504 & 0.301008 & 0.849496 \tabularnewline
83 & 0.144357 & 0.288714 & 0.855643 \tabularnewline
84 & 0.133908 & 0.267817 & 0.866092 \tabularnewline
85 & 0.114093 & 0.228185 & 0.885907 \tabularnewline
86 & 0.105711 & 0.211423 & 0.894289 \tabularnewline
87 & 0.0917496 & 0.183499 & 0.90825 \tabularnewline
88 & 0.103527 & 0.207054 & 0.896473 \tabularnewline
89 & 0.0876562 & 0.175312 & 0.912344 \tabularnewline
90 & 0.0919663 & 0.183933 & 0.908034 \tabularnewline
91 & 0.0862329 & 0.172466 & 0.913767 \tabularnewline
92 & 0.0757263 & 0.151453 & 0.924274 \tabularnewline
93 & 0.0632025 & 0.126405 & 0.936797 \tabularnewline
94 & 0.0669375 & 0.133875 & 0.933063 \tabularnewline
95 & 0.0755221 & 0.151044 & 0.924478 \tabularnewline
96 & 0.0726465 & 0.145293 & 0.927354 \tabularnewline
97 & 0.06419 & 0.12838 & 0.93581 \tabularnewline
98 & 0.059502 & 0.119004 & 0.940498 \tabularnewline
99 & 0.0579186 & 0.115837 & 0.942081 \tabularnewline
100 & 0.0541457 & 0.108291 & 0.945854 \tabularnewline
101 & 0.0519428 & 0.103886 & 0.948057 \tabularnewline
102 & 0.0428465 & 0.085693 & 0.957153 \tabularnewline
103 & 0.0354373 & 0.0708746 & 0.964563 \tabularnewline
104 & 0.0332579 & 0.0665159 & 0.966742 \tabularnewline
105 & 0.0681747 & 0.136349 & 0.931825 \tabularnewline
106 & 0.0671936 & 0.134387 & 0.932806 \tabularnewline
107 & 0.0847528 & 0.169506 & 0.915247 \tabularnewline
108 & 0.074622 & 0.149244 & 0.925378 \tabularnewline
109 & 0.116672 & 0.233344 & 0.883328 \tabularnewline
110 & 0.130889 & 0.261779 & 0.869111 \tabularnewline
111 & 0.125562 & 0.251124 & 0.874438 \tabularnewline
112 & 0.150202 & 0.300404 & 0.849798 \tabularnewline
113 & 0.13557 & 0.271139 & 0.86443 \tabularnewline
114 & 0.127816 & 0.255632 & 0.872184 \tabularnewline
115 & 0.128029 & 0.256059 & 0.871971 \tabularnewline
116 & 0.130211 & 0.260423 & 0.869789 \tabularnewline
117 & 0.121977 & 0.243954 & 0.878023 \tabularnewline
118 & 0.108639 & 0.217279 & 0.891361 \tabularnewline
119 & 0.106098 & 0.212197 & 0.893902 \tabularnewline
120 & 0.0967908 & 0.193582 & 0.903209 \tabularnewline
121 & 0.0840705 & 0.168141 & 0.91593 \tabularnewline
122 & 0.0749518 & 0.149904 & 0.925048 \tabularnewline
123 & 0.0642597 & 0.128519 & 0.93574 \tabularnewline
124 & 0.0616584 & 0.123317 & 0.938342 \tabularnewline
125 & 0.0586426 & 0.117285 & 0.941357 \tabularnewline
126 & 0.0764848 & 0.15297 & 0.923515 \tabularnewline
127 & 0.142961 & 0.285922 & 0.857039 \tabularnewline
128 & 0.134069 & 0.268139 & 0.865931 \tabularnewline
129 & 0.118596 & 0.237192 & 0.881404 \tabularnewline
130 & 0.106463 & 0.212925 & 0.893537 \tabularnewline
131 & 0.122687 & 0.245374 & 0.877313 \tabularnewline
132 & 0.137316 & 0.274632 & 0.862684 \tabularnewline
133 & 0.170469 & 0.340937 & 0.829531 \tabularnewline
134 & 0.151452 & 0.302905 & 0.848548 \tabularnewline
135 & 0.132572 & 0.265145 & 0.867428 \tabularnewline
136 & 0.115715 & 0.23143 & 0.884285 \tabularnewline
137 & 0.0994137 & 0.198827 & 0.900586 \tabularnewline
138 & 0.106194 & 0.212387 & 0.893806 \tabularnewline
139 & 0.0918517 & 0.183703 & 0.908148 \tabularnewline
140 & 0.0916547 & 0.183309 & 0.908345 \tabularnewline
141 & 0.0831279 & 0.166256 & 0.916872 \tabularnewline
142 & 0.104069 & 0.208137 & 0.895931 \tabularnewline
143 & 0.115859 & 0.231718 & 0.884141 \tabularnewline
144 & 0.105326 & 0.210652 & 0.894674 \tabularnewline
145 & 0.176747 & 0.353495 & 0.823253 \tabularnewline
146 & 0.159234 & 0.318469 & 0.840766 \tabularnewline
147 & 0.1424 & 0.284799 & 0.8576 \tabularnewline
148 & 0.123725 & 0.247451 & 0.876275 \tabularnewline
149 & 0.11693 & 0.23386 & 0.88307 \tabularnewline
150 & 0.104529 & 0.209058 & 0.895471 \tabularnewline
151 & 0.173181 & 0.346362 & 0.826819 \tabularnewline
152 & 0.157609 & 0.315218 & 0.842391 \tabularnewline
153 & 0.139189 & 0.278379 & 0.860811 \tabularnewline
154 & 0.159035 & 0.318069 & 0.840965 \tabularnewline
155 & 0.140719 & 0.281439 & 0.859281 \tabularnewline
156 & 0.143327 & 0.286654 & 0.856673 \tabularnewline
157 & 0.140571 & 0.281143 & 0.859429 \tabularnewline
158 & 0.127966 & 0.255932 & 0.872034 \tabularnewline
159 & 0.112659 & 0.225318 & 0.887341 \tabularnewline
160 & 0.112669 & 0.225338 & 0.887331 \tabularnewline
161 & 0.0967535 & 0.193507 & 0.903247 \tabularnewline
162 & 0.0889031 & 0.177806 & 0.911097 \tabularnewline
163 & 0.0782379 & 0.156476 & 0.921762 \tabularnewline
164 & 0.101477 & 0.202955 & 0.898523 \tabularnewline
165 & 0.0901688 & 0.180338 & 0.909831 \tabularnewline
166 & 0.152207 & 0.304415 & 0.847793 \tabularnewline
167 & 0.149807 & 0.299614 & 0.850193 \tabularnewline
168 & 0.14665 & 0.2933 & 0.85335 \tabularnewline
169 & 0.130534 & 0.261067 & 0.869466 \tabularnewline
170 & 0.244457 & 0.488914 & 0.755543 \tabularnewline
171 & 0.273931 & 0.547861 & 0.726069 \tabularnewline
172 & 0.245011 & 0.490021 & 0.754989 \tabularnewline
173 & 0.339164 & 0.678328 & 0.660836 \tabularnewline
174 & 0.307342 & 0.614683 & 0.692658 \tabularnewline
175 & 0.376118 & 0.752235 & 0.623882 \tabularnewline
176 & 0.356458 & 0.712917 & 0.643542 \tabularnewline
177 & 0.372324 & 0.744647 & 0.627676 \tabularnewline
178 & 0.341072 & 0.682144 & 0.658928 \tabularnewline
179 & 0.311522 & 0.623045 & 0.688478 \tabularnewline
180 & 0.302618 & 0.605237 & 0.697382 \tabularnewline
181 & 0.275878 & 0.551756 & 0.724122 \tabularnewline
182 & 0.282799 & 0.565598 & 0.717201 \tabularnewline
183 & 0.283426 & 0.566853 & 0.716574 \tabularnewline
184 & 0.356487 & 0.712975 & 0.643513 \tabularnewline
185 & 0.53776 & 0.924479 & 0.46224 \tabularnewline
186 & 0.52071 & 0.958581 & 0.47929 \tabularnewline
187 & 0.50432 & 0.991359 & 0.49568 \tabularnewline
188 & 0.660684 & 0.678633 & 0.339316 \tabularnewline
189 & 0.635965 & 0.72807 & 0.364035 \tabularnewline
190 & 0.615366 & 0.769268 & 0.384634 \tabularnewline
191 & 0.594298 & 0.811405 & 0.405702 \tabularnewline
192 & 0.560705 & 0.87859 & 0.439295 \tabularnewline
193 & 0.522917 & 0.954165 & 0.477083 \tabularnewline
194 & 0.48285 & 0.9657 & 0.51715 \tabularnewline
195 & 0.442509 & 0.885019 & 0.557491 \tabularnewline
196 & 0.410198 & 0.820395 & 0.589802 \tabularnewline
197 & 0.388793 & 0.777587 & 0.611207 \tabularnewline
198 & 0.365278 & 0.730556 & 0.634722 \tabularnewline
199 & 0.327395 & 0.65479 & 0.672605 \tabularnewline
200 & 0.425154 & 0.850307 & 0.574846 \tabularnewline
201 & 0.389605 & 0.77921 & 0.610395 \tabularnewline
202 & 0.561448 & 0.877104 & 0.438552 \tabularnewline
203 & 0.529574 & 0.940853 & 0.470426 \tabularnewline
204 & 0.491654 & 0.983307 & 0.508346 \tabularnewline
205 & 0.450472 & 0.900943 & 0.549528 \tabularnewline
206 & 0.413548 & 0.827095 & 0.586452 \tabularnewline
207 & 0.374578 & 0.749156 & 0.625422 \tabularnewline
208 & 0.336405 & 0.67281 & 0.663595 \tabularnewline
209 & 0.31958 & 0.63916 & 0.68042 \tabularnewline
210 & 0.281647 & 0.563294 & 0.718353 \tabularnewline
211 & 0.247181 & 0.494362 & 0.752819 \tabularnewline
212 & 0.220825 & 0.44165 & 0.779175 \tabularnewline
213 & 0.266558 & 0.533116 & 0.733442 \tabularnewline
214 & 0.255536 & 0.511072 & 0.744464 \tabularnewline
215 & 0.222749 & 0.445498 & 0.777251 \tabularnewline
216 & 0.192399 & 0.384798 & 0.807601 \tabularnewline
217 & 0.173902 & 0.347804 & 0.826098 \tabularnewline
218 & 0.198667 & 0.397334 & 0.801333 \tabularnewline
219 & 0.172523 & 0.345047 & 0.827477 \tabularnewline
220 & 0.151543 & 0.303085 & 0.848457 \tabularnewline
221 & 0.128485 & 0.256971 & 0.871515 \tabularnewline
222 & 0.116675 & 0.23335 & 0.883325 \tabularnewline
223 & 0.0944292 & 0.188858 & 0.905571 \tabularnewline
224 & 0.0794382 & 0.158876 & 0.920562 \tabularnewline
225 & 0.0677776 & 0.135555 & 0.932222 \tabularnewline
226 & 0.0680739 & 0.136148 & 0.931926 \tabularnewline
227 & 0.0641915 & 0.128383 & 0.935808 \tabularnewline
228 & 0.0533695 & 0.106739 & 0.946631 \tabularnewline
229 & 0.0418417 & 0.0836833 & 0.958158 \tabularnewline
230 & 0.0337489 & 0.0674978 & 0.966251 \tabularnewline
231 & 0.0260518 & 0.0521035 & 0.973948 \tabularnewline
232 & 0.0395737 & 0.0791473 & 0.960426 \tabularnewline
233 & 0.043268 & 0.086536 & 0.956732 \tabularnewline
234 & 0.0707386 & 0.141477 & 0.929261 \tabularnewline
235 & 0.0532524 & 0.106505 & 0.946748 \tabularnewline
236 & 0.0484753 & 0.0969507 & 0.951525 \tabularnewline
237 & 0.0592001 & 0.1184 & 0.9408 \tabularnewline
238 & 0.184568 & 0.369136 & 0.815432 \tabularnewline
239 & 0.149956 & 0.299913 & 0.850044 \tabularnewline
240 & 0.291925 & 0.58385 & 0.708075 \tabularnewline
241 & 0.320847 & 0.641694 & 0.679153 \tabularnewline
242 & 0.265684 & 0.531368 & 0.734316 \tabularnewline
243 & 0.235435 & 0.47087 & 0.764565 \tabularnewline
244 & 0.18651 & 0.373019 & 0.81349 \tabularnewline
245 & 0.431899 & 0.863799 & 0.568101 \tabularnewline
246 & 0.607949 & 0.784103 & 0.392051 \tabularnewline
247 & 0.594567 & 0.810866 & 0.405433 \tabularnewline
248 & 0.607516 & 0.784967 & 0.392484 \tabularnewline
249 & 0.632943 & 0.734113 & 0.367057 \tabularnewline
250 & 0.546884 & 0.906231 & 0.453116 \tabularnewline
251 & 0.639777 & 0.720447 & 0.360223 \tabularnewline
252 & 0.693521 & 0.612958 & 0.306479 \tabularnewline
253 & 0.758585 & 0.48283 & 0.241415 \tabularnewline
254 & 0.761498 & 0.477004 & 0.238502 \tabularnewline
255 & 0.603973 & 0.792053 & 0.396027 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225844&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]0.912444[/C][C]0.175113[/C][C]0.0875563[/C][/ROW]
[ROW][C]10[/C][C]0.843819[/C][C]0.312361[/C][C]0.156181[/C][/ROW]
[ROW][C]11[/C][C]0.778542[/C][C]0.442917[/C][C]0.221458[/C][/ROW]
[ROW][C]12[/C][C]0.714387[/C][C]0.571226[/C][C]0.285613[/C][/ROW]
[ROW][C]13[/C][C]0.770293[/C][C]0.459414[/C][C]0.229707[/C][/ROW]
[ROW][C]14[/C][C]0.689024[/C][C]0.621953[/C][C]0.310976[/C][/ROW]
[ROW][C]15[/C][C]0.715964[/C][C]0.568071[/C][C]0.284036[/C][/ROW]
[ROW][C]16[/C][C]0.696951[/C][C]0.606099[/C][C]0.303049[/C][/ROW]
[ROW][C]17[/C][C]0.620945[/C][C]0.758109[/C][C]0.379055[/C][/ROW]
[ROW][C]18[/C][C]0.546451[/C][C]0.907098[/C][C]0.453549[/C][/ROW]
[ROW][C]19[/C][C]0.513288[/C][C]0.973423[/C][C]0.486712[/C][/ROW]
[ROW][C]20[/C][C]0.504324[/C][C]0.991352[/C][C]0.495676[/C][/ROW]
[ROW][C]21[/C][C]0.503814[/C][C]0.992372[/C][C]0.496186[/C][/ROW]
[ROW][C]22[/C][C]0.434201[/C][C]0.868403[/C][C]0.565799[/C][/ROW]
[ROW][C]23[/C][C]0.438968[/C][C]0.877936[/C][C]0.561032[/C][/ROW]
[ROW][C]24[/C][C]0.369054[/C][C]0.738109[/C][C]0.630946[/C][/ROW]
[ROW][C]25[/C][C]0.420531[/C][C]0.841063[/C][C]0.579469[/C][/ROW]
[ROW][C]26[/C][C]0.650713[/C][C]0.698574[/C][C]0.349287[/C][/ROW]
[ROW][C]27[/C][C]0.59466[/C][C]0.81068[/C][C]0.40534[/C][/ROW]
[ROW][C]28[/C][C]0.586407[/C][C]0.827187[/C][C]0.413593[/C][/ROW]
[ROW][C]29[/C][C]0.548279[/C][C]0.903443[/C][C]0.451721[/C][/ROW]
[ROW][C]30[/C][C]0.49573[/C][C]0.99146[/C][C]0.50427[/C][/ROW]
[ROW][C]31[/C][C]0.495486[/C][C]0.990972[/C][C]0.504514[/C][/ROW]
[ROW][C]32[/C][C]0.652258[/C][C]0.695485[/C][C]0.347742[/C][/ROW]
[ROW][C]33[/C][C]0.651878[/C][C]0.696245[/C][C]0.348122[/C][/ROW]
[ROW][C]34[/C][C]0.606864[/C][C]0.786272[/C][C]0.393136[/C][/ROW]
[ROW][C]35[/C][C]0.559161[/C][C]0.881679[/C][C]0.440839[/C][/ROW]
[ROW][C]36[/C][C]0.527961[/C][C]0.944078[/C][C]0.472039[/C][/ROW]
[ROW][C]37[/C][C]0.497005[/C][C]0.994009[/C][C]0.502995[/C][/ROW]
[ROW][C]38[/C][C]0.470824[/C][C]0.941648[/C][C]0.529176[/C][/ROW]
[ROW][C]39[/C][C]0.494281[/C][C]0.988562[/C][C]0.505719[/C][/ROW]
[ROW][C]40[/C][C]0.45474[/C][C]0.909479[/C][C]0.54526[/C][/ROW]
[ROW][C]41[/C][C]0.460239[/C][C]0.920479[/C][C]0.539761[/C][/ROW]
[ROW][C]42[/C][C]0.413126[/C][C]0.826251[/C][C]0.586874[/C][/ROW]
[ROW][C]43[/C][C]0.409999[/C][C]0.819999[/C][C]0.590001[/C][/ROW]
[ROW][C]44[/C][C]0.379094[/C][C]0.758187[/C][C]0.620906[/C][/ROW]
[ROW][C]45[/C][C]0.456866[/C][C]0.913732[/C][C]0.543134[/C][/ROW]
[ROW][C]46[/C][C]0.433378[/C][C]0.866756[/C][C]0.566622[/C][/ROW]
[ROW][C]47[/C][C]0.391054[/C][C]0.782109[/C][C]0.608946[/C][/ROW]
[ROW][C]48[/C][C]0.356558[/C][C]0.713116[/C][C]0.643442[/C][/ROW]
[ROW][C]49[/C][C]0.317897[/C][C]0.635794[/C][C]0.682103[/C][/ROW]
[ROW][C]50[/C][C]0.325502[/C][C]0.651004[/C][C]0.674498[/C][/ROW]
[ROW][C]51[/C][C]0.361557[/C][C]0.723114[/C][C]0.638443[/C][/ROW]
[ROW][C]52[/C][C]0.320728[/C][C]0.641457[/C][C]0.679272[/C][/ROW]
[ROW][C]53[/C][C]0.283953[/C][C]0.567905[/C][C]0.716047[/C][/ROW]
[ROW][C]54[/C][C]0.250677[/C][C]0.501354[/C][C]0.749323[/C][/ROW]
[ROW][C]55[/C][C]0.217759[/C][C]0.435517[/C][C]0.782241[/C][/ROW]
[ROW][C]56[/C][C]0.229983[/C][C]0.459965[/C][C]0.770017[/C][/ROW]
[ROW][C]57[/C][C]0.263103[/C][C]0.526207[/C][C]0.736897[/C][/ROW]
[ROW][C]58[/C][C]0.348985[/C][C]0.697971[/C][C]0.651015[/C][/ROW]
[ROW][C]59[/C][C]0.323884[/C][C]0.647767[/C][C]0.676116[/C][/ROW]
[ROW][C]60[/C][C]0.291091[/C][C]0.582182[/C][C]0.708909[/C][/ROW]
[ROW][C]61[/C][C]0.257158[/C][C]0.514316[/C][C]0.742842[/C][/ROW]
[ROW][C]62[/C][C]0.26311[/C][C]0.52622[/C][C]0.73689[/C][/ROW]
[ROW][C]63[/C][C]0.231122[/C][C]0.462244[/C][C]0.768878[/C][/ROW]
[ROW][C]64[/C][C]0.231074[/C][C]0.462147[/C][C]0.768926[/C][/ROW]
[ROW][C]65[/C][C]0.200834[/C][C]0.401668[/C][C]0.799166[/C][/ROW]
[ROW][C]66[/C][C]0.172532[/C][C]0.345064[/C][C]0.827468[/C][/ROW]
[ROW][C]67[/C][C]0.156[/C][C]0.311999[/C][C]0.844[/C][/ROW]
[ROW][C]68[/C][C]0.141601[/C][C]0.283201[/C][C]0.858399[/C][/ROW]
[ROW][C]69[/C][C]0.135765[/C][C]0.271529[/C][C]0.864235[/C][/ROW]
[ROW][C]70[/C][C]0.114415[/C][C]0.228831[/C][C]0.885585[/C][/ROW]
[ROW][C]71[/C][C]0.114714[/C][C]0.229429[/C][C]0.885286[/C][/ROW]
[ROW][C]72[/C][C]0.13287[/C][C]0.265739[/C][C]0.86713[/C][/ROW]
[ROW][C]73[/C][C]0.119578[/C][C]0.239156[/C][C]0.880422[/C][/ROW]
[ROW][C]74[/C][C]0.102255[/C][C]0.20451[/C][C]0.897745[/C][/ROW]
[ROW][C]75[/C][C]0.0910625[/C][C]0.182125[/C][C]0.908938[/C][/ROW]
[ROW][C]76[/C][C]0.163382[/C][C]0.326764[/C][C]0.836618[/C][/ROW]
[ROW][C]77[/C][C]0.143721[/C][C]0.287442[/C][C]0.856279[/C][/ROW]
[ROW][C]78[/C][C]0.123716[/C][C]0.247431[/C][C]0.876284[/C][/ROW]
[ROW][C]79[/C][C]0.163852[/C][C]0.327705[/C][C]0.836148[/C][/ROW]
[ROW][C]80[/C][C]0.188543[/C][C]0.377086[/C][C]0.811457[/C][/ROW]
[ROW][C]81[/C][C]0.173827[/C][C]0.347654[/C][C]0.826173[/C][/ROW]
[ROW][C]82[/C][C]0.150504[/C][C]0.301008[/C][C]0.849496[/C][/ROW]
[ROW][C]83[/C][C]0.144357[/C][C]0.288714[/C][C]0.855643[/C][/ROW]
[ROW][C]84[/C][C]0.133908[/C][C]0.267817[/C][C]0.866092[/C][/ROW]
[ROW][C]85[/C][C]0.114093[/C][C]0.228185[/C][C]0.885907[/C][/ROW]
[ROW][C]86[/C][C]0.105711[/C][C]0.211423[/C][C]0.894289[/C][/ROW]
[ROW][C]87[/C][C]0.0917496[/C][C]0.183499[/C][C]0.90825[/C][/ROW]
[ROW][C]88[/C][C]0.103527[/C][C]0.207054[/C][C]0.896473[/C][/ROW]
[ROW][C]89[/C][C]0.0876562[/C][C]0.175312[/C][C]0.912344[/C][/ROW]
[ROW][C]90[/C][C]0.0919663[/C][C]0.183933[/C][C]0.908034[/C][/ROW]
[ROW][C]91[/C][C]0.0862329[/C][C]0.172466[/C][C]0.913767[/C][/ROW]
[ROW][C]92[/C][C]0.0757263[/C][C]0.151453[/C][C]0.924274[/C][/ROW]
[ROW][C]93[/C][C]0.0632025[/C][C]0.126405[/C][C]0.936797[/C][/ROW]
[ROW][C]94[/C][C]0.0669375[/C][C]0.133875[/C][C]0.933063[/C][/ROW]
[ROW][C]95[/C][C]0.0755221[/C][C]0.151044[/C][C]0.924478[/C][/ROW]
[ROW][C]96[/C][C]0.0726465[/C][C]0.145293[/C][C]0.927354[/C][/ROW]
[ROW][C]97[/C][C]0.06419[/C][C]0.12838[/C][C]0.93581[/C][/ROW]
[ROW][C]98[/C][C]0.059502[/C][C]0.119004[/C][C]0.940498[/C][/ROW]
[ROW][C]99[/C][C]0.0579186[/C][C]0.115837[/C][C]0.942081[/C][/ROW]
[ROW][C]100[/C][C]0.0541457[/C][C]0.108291[/C][C]0.945854[/C][/ROW]
[ROW][C]101[/C][C]0.0519428[/C][C]0.103886[/C][C]0.948057[/C][/ROW]
[ROW][C]102[/C][C]0.0428465[/C][C]0.085693[/C][C]0.957153[/C][/ROW]
[ROW][C]103[/C][C]0.0354373[/C][C]0.0708746[/C][C]0.964563[/C][/ROW]
[ROW][C]104[/C][C]0.0332579[/C][C]0.0665159[/C][C]0.966742[/C][/ROW]
[ROW][C]105[/C][C]0.0681747[/C][C]0.136349[/C][C]0.931825[/C][/ROW]
[ROW][C]106[/C][C]0.0671936[/C][C]0.134387[/C][C]0.932806[/C][/ROW]
[ROW][C]107[/C][C]0.0847528[/C][C]0.169506[/C][C]0.915247[/C][/ROW]
[ROW][C]108[/C][C]0.074622[/C][C]0.149244[/C][C]0.925378[/C][/ROW]
[ROW][C]109[/C][C]0.116672[/C][C]0.233344[/C][C]0.883328[/C][/ROW]
[ROW][C]110[/C][C]0.130889[/C][C]0.261779[/C][C]0.869111[/C][/ROW]
[ROW][C]111[/C][C]0.125562[/C][C]0.251124[/C][C]0.874438[/C][/ROW]
[ROW][C]112[/C][C]0.150202[/C][C]0.300404[/C][C]0.849798[/C][/ROW]
[ROW][C]113[/C][C]0.13557[/C][C]0.271139[/C][C]0.86443[/C][/ROW]
[ROW][C]114[/C][C]0.127816[/C][C]0.255632[/C][C]0.872184[/C][/ROW]
[ROW][C]115[/C][C]0.128029[/C][C]0.256059[/C][C]0.871971[/C][/ROW]
[ROW][C]116[/C][C]0.130211[/C][C]0.260423[/C][C]0.869789[/C][/ROW]
[ROW][C]117[/C][C]0.121977[/C][C]0.243954[/C][C]0.878023[/C][/ROW]
[ROW][C]118[/C][C]0.108639[/C][C]0.217279[/C][C]0.891361[/C][/ROW]
[ROW][C]119[/C][C]0.106098[/C][C]0.212197[/C][C]0.893902[/C][/ROW]
[ROW][C]120[/C][C]0.0967908[/C][C]0.193582[/C][C]0.903209[/C][/ROW]
[ROW][C]121[/C][C]0.0840705[/C][C]0.168141[/C][C]0.91593[/C][/ROW]
[ROW][C]122[/C][C]0.0749518[/C][C]0.149904[/C][C]0.925048[/C][/ROW]
[ROW][C]123[/C][C]0.0642597[/C][C]0.128519[/C][C]0.93574[/C][/ROW]
[ROW][C]124[/C][C]0.0616584[/C][C]0.123317[/C][C]0.938342[/C][/ROW]
[ROW][C]125[/C][C]0.0586426[/C][C]0.117285[/C][C]0.941357[/C][/ROW]
[ROW][C]126[/C][C]0.0764848[/C][C]0.15297[/C][C]0.923515[/C][/ROW]
[ROW][C]127[/C][C]0.142961[/C][C]0.285922[/C][C]0.857039[/C][/ROW]
[ROW][C]128[/C][C]0.134069[/C][C]0.268139[/C][C]0.865931[/C][/ROW]
[ROW][C]129[/C][C]0.118596[/C][C]0.237192[/C][C]0.881404[/C][/ROW]
[ROW][C]130[/C][C]0.106463[/C][C]0.212925[/C][C]0.893537[/C][/ROW]
[ROW][C]131[/C][C]0.122687[/C][C]0.245374[/C][C]0.877313[/C][/ROW]
[ROW][C]132[/C][C]0.137316[/C][C]0.274632[/C][C]0.862684[/C][/ROW]
[ROW][C]133[/C][C]0.170469[/C][C]0.340937[/C][C]0.829531[/C][/ROW]
[ROW][C]134[/C][C]0.151452[/C][C]0.302905[/C][C]0.848548[/C][/ROW]
[ROW][C]135[/C][C]0.132572[/C][C]0.265145[/C][C]0.867428[/C][/ROW]
[ROW][C]136[/C][C]0.115715[/C][C]0.23143[/C][C]0.884285[/C][/ROW]
[ROW][C]137[/C][C]0.0994137[/C][C]0.198827[/C][C]0.900586[/C][/ROW]
[ROW][C]138[/C][C]0.106194[/C][C]0.212387[/C][C]0.893806[/C][/ROW]
[ROW][C]139[/C][C]0.0918517[/C][C]0.183703[/C][C]0.908148[/C][/ROW]
[ROW][C]140[/C][C]0.0916547[/C][C]0.183309[/C][C]0.908345[/C][/ROW]
[ROW][C]141[/C][C]0.0831279[/C][C]0.166256[/C][C]0.916872[/C][/ROW]
[ROW][C]142[/C][C]0.104069[/C][C]0.208137[/C][C]0.895931[/C][/ROW]
[ROW][C]143[/C][C]0.115859[/C][C]0.231718[/C][C]0.884141[/C][/ROW]
[ROW][C]144[/C][C]0.105326[/C][C]0.210652[/C][C]0.894674[/C][/ROW]
[ROW][C]145[/C][C]0.176747[/C][C]0.353495[/C][C]0.823253[/C][/ROW]
[ROW][C]146[/C][C]0.159234[/C][C]0.318469[/C][C]0.840766[/C][/ROW]
[ROW][C]147[/C][C]0.1424[/C][C]0.284799[/C][C]0.8576[/C][/ROW]
[ROW][C]148[/C][C]0.123725[/C][C]0.247451[/C][C]0.876275[/C][/ROW]
[ROW][C]149[/C][C]0.11693[/C][C]0.23386[/C][C]0.88307[/C][/ROW]
[ROW][C]150[/C][C]0.104529[/C][C]0.209058[/C][C]0.895471[/C][/ROW]
[ROW][C]151[/C][C]0.173181[/C][C]0.346362[/C][C]0.826819[/C][/ROW]
[ROW][C]152[/C][C]0.157609[/C][C]0.315218[/C][C]0.842391[/C][/ROW]
[ROW][C]153[/C][C]0.139189[/C][C]0.278379[/C][C]0.860811[/C][/ROW]
[ROW][C]154[/C][C]0.159035[/C][C]0.318069[/C][C]0.840965[/C][/ROW]
[ROW][C]155[/C][C]0.140719[/C][C]0.281439[/C][C]0.859281[/C][/ROW]
[ROW][C]156[/C][C]0.143327[/C][C]0.286654[/C][C]0.856673[/C][/ROW]
[ROW][C]157[/C][C]0.140571[/C][C]0.281143[/C][C]0.859429[/C][/ROW]
[ROW][C]158[/C][C]0.127966[/C][C]0.255932[/C][C]0.872034[/C][/ROW]
[ROW][C]159[/C][C]0.112659[/C][C]0.225318[/C][C]0.887341[/C][/ROW]
[ROW][C]160[/C][C]0.112669[/C][C]0.225338[/C][C]0.887331[/C][/ROW]
[ROW][C]161[/C][C]0.0967535[/C][C]0.193507[/C][C]0.903247[/C][/ROW]
[ROW][C]162[/C][C]0.0889031[/C][C]0.177806[/C][C]0.911097[/C][/ROW]
[ROW][C]163[/C][C]0.0782379[/C][C]0.156476[/C][C]0.921762[/C][/ROW]
[ROW][C]164[/C][C]0.101477[/C][C]0.202955[/C][C]0.898523[/C][/ROW]
[ROW][C]165[/C][C]0.0901688[/C][C]0.180338[/C][C]0.909831[/C][/ROW]
[ROW][C]166[/C][C]0.152207[/C][C]0.304415[/C][C]0.847793[/C][/ROW]
[ROW][C]167[/C][C]0.149807[/C][C]0.299614[/C][C]0.850193[/C][/ROW]
[ROW][C]168[/C][C]0.14665[/C][C]0.2933[/C][C]0.85335[/C][/ROW]
[ROW][C]169[/C][C]0.130534[/C][C]0.261067[/C][C]0.869466[/C][/ROW]
[ROW][C]170[/C][C]0.244457[/C][C]0.488914[/C][C]0.755543[/C][/ROW]
[ROW][C]171[/C][C]0.273931[/C][C]0.547861[/C][C]0.726069[/C][/ROW]
[ROW][C]172[/C][C]0.245011[/C][C]0.490021[/C][C]0.754989[/C][/ROW]
[ROW][C]173[/C][C]0.339164[/C][C]0.678328[/C][C]0.660836[/C][/ROW]
[ROW][C]174[/C][C]0.307342[/C][C]0.614683[/C][C]0.692658[/C][/ROW]
[ROW][C]175[/C][C]0.376118[/C][C]0.752235[/C][C]0.623882[/C][/ROW]
[ROW][C]176[/C][C]0.356458[/C][C]0.712917[/C][C]0.643542[/C][/ROW]
[ROW][C]177[/C][C]0.372324[/C][C]0.744647[/C][C]0.627676[/C][/ROW]
[ROW][C]178[/C][C]0.341072[/C][C]0.682144[/C][C]0.658928[/C][/ROW]
[ROW][C]179[/C][C]0.311522[/C][C]0.623045[/C][C]0.688478[/C][/ROW]
[ROW][C]180[/C][C]0.302618[/C][C]0.605237[/C][C]0.697382[/C][/ROW]
[ROW][C]181[/C][C]0.275878[/C][C]0.551756[/C][C]0.724122[/C][/ROW]
[ROW][C]182[/C][C]0.282799[/C][C]0.565598[/C][C]0.717201[/C][/ROW]
[ROW][C]183[/C][C]0.283426[/C][C]0.566853[/C][C]0.716574[/C][/ROW]
[ROW][C]184[/C][C]0.356487[/C][C]0.712975[/C][C]0.643513[/C][/ROW]
[ROW][C]185[/C][C]0.53776[/C][C]0.924479[/C][C]0.46224[/C][/ROW]
[ROW][C]186[/C][C]0.52071[/C][C]0.958581[/C][C]0.47929[/C][/ROW]
[ROW][C]187[/C][C]0.50432[/C][C]0.991359[/C][C]0.49568[/C][/ROW]
[ROW][C]188[/C][C]0.660684[/C][C]0.678633[/C][C]0.339316[/C][/ROW]
[ROW][C]189[/C][C]0.635965[/C][C]0.72807[/C][C]0.364035[/C][/ROW]
[ROW][C]190[/C][C]0.615366[/C][C]0.769268[/C][C]0.384634[/C][/ROW]
[ROW][C]191[/C][C]0.594298[/C][C]0.811405[/C][C]0.405702[/C][/ROW]
[ROW][C]192[/C][C]0.560705[/C][C]0.87859[/C][C]0.439295[/C][/ROW]
[ROW][C]193[/C][C]0.522917[/C][C]0.954165[/C][C]0.477083[/C][/ROW]
[ROW][C]194[/C][C]0.48285[/C][C]0.9657[/C][C]0.51715[/C][/ROW]
[ROW][C]195[/C][C]0.442509[/C][C]0.885019[/C][C]0.557491[/C][/ROW]
[ROW][C]196[/C][C]0.410198[/C][C]0.820395[/C][C]0.589802[/C][/ROW]
[ROW][C]197[/C][C]0.388793[/C][C]0.777587[/C][C]0.611207[/C][/ROW]
[ROW][C]198[/C][C]0.365278[/C][C]0.730556[/C][C]0.634722[/C][/ROW]
[ROW][C]199[/C][C]0.327395[/C][C]0.65479[/C][C]0.672605[/C][/ROW]
[ROW][C]200[/C][C]0.425154[/C][C]0.850307[/C][C]0.574846[/C][/ROW]
[ROW][C]201[/C][C]0.389605[/C][C]0.77921[/C][C]0.610395[/C][/ROW]
[ROW][C]202[/C][C]0.561448[/C][C]0.877104[/C][C]0.438552[/C][/ROW]
[ROW][C]203[/C][C]0.529574[/C][C]0.940853[/C][C]0.470426[/C][/ROW]
[ROW][C]204[/C][C]0.491654[/C][C]0.983307[/C][C]0.508346[/C][/ROW]
[ROW][C]205[/C][C]0.450472[/C][C]0.900943[/C][C]0.549528[/C][/ROW]
[ROW][C]206[/C][C]0.413548[/C][C]0.827095[/C][C]0.586452[/C][/ROW]
[ROW][C]207[/C][C]0.374578[/C][C]0.749156[/C][C]0.625422[/C][/ROW]
[ROW][C]208[/C][C]0.336405[/C][C]0.67281[/C][C]0.663595[/C][/ROW]
[ROW][C]209[/C][C]0.31958[/C][C]0.63916[/C][C]0.68042[/C][/ROW]
[ROW][C]210[/C][C]0.281647[/C][C]0.563294[/C][C]0.718353[/C][/ROW]
[ROW][C]211[/C][C]0.247181[/C][C]0.494362[/C][C]0.752819[/C][/ROW]
[ROW][C]212[/C][C]0.220825[/C][C]0.44165[/C][C]0.779175[/C][/ROW]
[ROW][C]213[/C][C]0.266558[/C][C]0.533116[/C][C]0.733442[/C][/ROW]
[ROW][C]214[/C][C]0.255536[/C][C]0.511072[/C][C]0.744464[/C][/ROW]
[ROW][C]215[/C][C]0.222749[/C][C]0.445498[/C][C]0.777251[/C][/ROW]
[ROW][C]216[/C][C]0.192399[/C][C]0.384798[/C][C]0.807601[/C][/ROW]
[ROW][C]217[/C][C]0.173902[/C][C]0.347804[/C][C]0.826098[/C][/ROW]
[ROW][C]218[/C][C]0.198667[/C][C]0.397334[/C][C]0.801333[/C][/ROW]
[ROW][C]219[/C][C]0.172523[/C][C]0.345047[/C][C]0.827477[/C][/ROW]
[ROW][C]220[/C][C]0.151543[/C][C]0.303085[/C][C]0.848457[/C][/ROW]
[ROW][C]221[/C][C]0.128485[/C][C]0.256971[/C][C]0.871515[/C][/ROW]
[ROW][C]222[/C][C]0.116675[/C][C]0.23335[/C][C]0.883325[/C][/ROW]
[ROW][C]223[/C][C]0.0944292[/C][C]0.188858[/C][C]0.905571[/C][/ROW]
[ROW][C]224[/C][C]0.0794382[/C][C]0.158876[/C][C]0.920562[/C][/ROW]
[ROW][C]225[/C][C]0.0677776[/C][C]0.135555[/C][C]0.932222[/C][/ROW]
[ROW][C]226[/C][C]0.0680739[/C][C]0.136148[/C][C]0.931926[/C][/ROW]
[ROW][C]227[/C][C]0.0641915[/C][C]0.128383[/C][C]0.935808[/C][/ROW]
[ROW][C]228[/C][C]0.0533695[/C][C]0.106739[/C][C]0.946631[/C][/ROW]
[ROW][C]229[/C][C]0.0418417[/C][C]0.0836833[/C][C]0.958158[/C][/ROW]
[ROW][C]230[/C][C]0.0337489[/C][C]0.0674978[/C][C]0.966251[/C][/ROW]
[ROW][C]231[/C][C]0.0260518[/C][C]0.0521035[/C][C]0.973948[/C][/ROW]
[ROW][C]232[/C][C]0.0395737[/C][C]0.0791473[/C][C]0.960426[/C][/ROW]
[ROW][C]233[/C][C]0.043268[/C][C]0.086536[/C][C]0.956732[/C][/ROW]
[ROW][C]234[/C][C]0.0707386[/C][C]0.141477[/C][C]0.929261[/C][/ROW]
[ROW][C]235[/C][C]0.0532524[/C][C]0.106505[/C][C]0.946748[/C][/ROW]
[ROW][C]236[/C][C]0.0484753[/C][C]0.0969507[/C][C]0.951525[/C][/ROW]
[ROW][C]237[/C][C]0.0592001[/C][C]0.1184[/C][C]0.9408[/C][/ROW]
[ROW][C]238[/C][C]0.184568[/C][C]0.369136[/C][C]0.815432[/C][/ROW]
[ROW][C]239[/C][C]0.149956[/C][C]0.299913[/C][C]0.850044[/C][/ROW]
[ROW][C]240[/C][C]0.291925[/C][C]0.58385[/C][C]0.708075[/C][/ROW]
[ROW][C]241[/C][C]0.320847[/C][C]0.641694[/C][C]0.679153[/C][/ROW]
[ROW][C]242[/C][C]0.265684[/C][C]0.531368[/C][C]0.734316[/C][/ROW]
[ROW][C]243[/C][C]0.235435[/C][C]0.47087[/C][C]0.764565[/C][/ROW]
[ROW][C]244[/C][C]0.18651[/C][C]0.373019[/C][C]0.81349[/C][/ROW]
[ROW][C]245[/C][C]0.431899[/C][C]0.863799[/C][C]0.568101[/C][/ROW]
[ROW][C]246[/C][C]0.607949[/C][C]0.784103[/C][C]0.392051[/C][/ROW]
[ROW][C]247[/C][C]0.594567[/C][C]0.810866[/C][C]0.405433[/C][/ROW]
[ROW][C]248[/C][C]0.607516[/C][C]0.784967[/C][C]0.392484[/C][/ROW]
[ROW][C]249[/C][C]0.632943[/C][C]0.734113[/C][C]0.367057[/C][/ROW]
[ROW][C]250[/C][C]0.546884[/C][C]0.906231[/C][C]0.453116[/C][/ROW]
[ROW][C]251[/C][C]0.639777[/C][C]0.720447[/C][C]0.360223[/C][/ROW]
[ROW][C]252[/C][C]0.693521[/C][C]0.612958[/C][C]0.306479[/C][/ROW]
[ROW][C]253[/C][C]0.758585[/C][C]0.48283[/C][C]0.241415[/C][/ROW]
[ROW][C]254[/C][C]0.761498[/C][C]0.477004[/C][C]0.238502[/C][/ROW]
[ROW][C]255[/C][C]0.603973[/C][C]0.792053[/C][C]0.396027[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225844&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225844&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
90.9124440.1751130.0875563
100.8438190.3123610.156181
110.7785420.4429170.221458
120.7143870.5712260.285613
130.7702930.4594140.229707
140.6890240.6219530.310976
150.7159640.5680710.284036
160.6969510.6060990.303049
170.6209450.7581090.379055
180.5464510.9070980.453549
190.5132880.9734230.486712
200.5043240.9913520.495676
210.5038140.9923720.496186
220.4342010.8684030.565799
230.4389680.8779360.561032
240.3690540.7381090.630946
250.4205310.8410630.579469
260.6507130.6985740.349287
270.594660.810680.40534
280.5864070.8271870.413593
290.5482790.9034430.451721
300.495730.991460.50427
310.4954860.9909720.504514
320.6522580.6954850.347742
330.6518780.6962450.348122
340.6068640.7862720.393136
350.5591610.8816790.440839
360.5279610.9440780.472039
370.4970050.9940090.502995
380.4708240.9416480.529176
390.4942810.9885620.505719
400.454740.9094790.54526
410.4602390.9204790.539761
420.4131260.8262510.586874
430.4099990.8199990.590001
440.3790940.7581870.620906
450.4568660.9137320.543134
460.4333780.8667560.566622
470.3910540.7821090.608946
480.3565580.7131160.643442
490.3178970.6357940.682103
500.3255020.6510040.674498
510.3615570.7231140.638443
520.3207280.6414570.679272
530.2839530.5679050.716047
540.2506770.5013540.749323
550.2177590.4355170.782241
560.2299830.4599650.770017
570.2631030.5262070.736897
580.3489850.6979710.651015
590.3238840.6477670.676116
600.2910910.5821820.708909
610.2571580.5143160.742842
620.263110.526220.73689
630.2311220.4622440.768878
640.2310740.4621470.768926
650.2008340.4016680.799166
660.1725320.3450640.827468
670.1560.3119990.844
680.1416010.2832010.858399
690.1357650.2715290.864235
700.1144150.2288310.885585
710.1147140.2294290.885286
720.132870.2657390.86713
730.1195780.2391560.880422
740.1022550.204510.897745
750.09106250.1821250.908938
760.1633820.3267640.836618
770.1437210.2874420.856279
780.1237160.2474310.876284
790.1638520.3277050.836148
800.1885430.3770860.811457
810.1738270.3476540.826173
820.1505040.3010080.849496
830.1443570.2887140.855643
840.1339080.2678170.866092
850.1140930.2281850.885907
860.1057110.2114230.894289
870.09174960.1834990.90825
880.1035270.2070540.896473
890.08765620.1753120.912344
900.09196630.1839330.908034
910.08623290.1724660.913767
920.07572630.1514530.924274
930.06320250.1264050.936797
940.06693750.1338750.933063
950.07552210.1510440.924478
960.07264650.1452930.927354
970.064190.128380.93581
980.0595020.1190040.940498
990.05791860.1158370.942081
1000.05414570.1082910.945854
1010.05194280.1038860.948057
1020.04284650.0856930.957153
1030.03543730.07087460.964563
1040.03325790.06651590.966742
1050.06817470.1363490.931825
1060.06719360.1343870.932806
1070.08475280.1695060.915247
1080.0746220.1492440.925378
1090.1166720.2333440.883328
1100.1308890.2617790.869111
1110.1255620.2511240.874438
1120.1502020.3004040.849798
1130.135570.2711390.86443
1140.1278160.2556320.872184
1150.1280290.2560590.871971
1160.1302110.2604230.869789
1170.1219770.2439540.878023
1180.1086390.2172790.891361
1190.1060980.2121970.893902
1200.09679080.1935820.903209
1210.08407050.1681410.91593
1220.07495180.1499040.925048
1230.06425970.1285190.93574
1240.06165840.1233170.938342
1250.05864260.1172850.941357
1260.07648480.152970.923515
1270.1429610.2859220.857039
1280.1340690.2681390.865931
1290.1185960.2371920.881404
1300.1064630.2129250.893537
1310.1226870.2453740.877313
1320.1373160.2746320.862684
1330.1704690.3409370.829531
1340.1514520.3029050.848548
1350.1325720.2651450.867428
1360.1157150.231430.884285
1370.09941370.1988270.900586
1380.1061940.2123870.893806
1390.09185170.1837030.908148
1400.09165470.1833090.908345
1410.08312790.1662560.916872
1420.1040690.2081370.895931
1430.1158590.2317180.884141
1440.1053260.2106520.894674
1450.1767470.3534950.823253
1460.1592340.3184690.840766
1470.14240.2847990.8576
1480.1237250.2474510.876275
1490.116930.233860.88307
1500.1045290.2090580.895471
1510.1731810.3463620.826819
1520.1576090.3152180.842391
1530.1391890.2783790.860811
1540.1590350.3180690.840965
1550.1407190.2814390.859281
1560.1433270.2866540.856673
1570.1405710.2811430.859429
1580.1279660.2559320.872034
1590.1126590.2253180.887341
1600.1126690.2253380.887331
1610.09675350.1935070.903247
1620.08890310.1778060.911097
1630.07823790.1564760.921762
1640.1014770.2029550.898523
1650.09016880.1803380.909831
1660.1522070.3044150.847793
1670.1498070.2996140.850193
1680.146650.29330.85335
1690.1305340.2610670.869466
1700.2444570.4889140.755543
1710.2739310.5478610.726069
1720.2450110.4900210.754989
1730.3391640.6783280.660836
1740.3073420.6146830.692658
1750.3761180.7522350.623882
1760.3564580.7129170.643542
1770.3723240.7446470.627676
1780.3410720.6821440.658928
1790.3115220.6230450.688478
1800.3026180.6052370.697382
1810.2758780.5517560.724122
1820.2827990.5655980.717201
1830.2834260.5668530.716574
1840.3564870.7129750.643513
1850.537760.9244790.46224
1860.520710.9585810.47929
1870.504320.9913590.49568
1880.6606840.6786330.339316
1890.6359650.728070.364035
1900.6153660.7692680.384634
1910.5942980.8114050.405702
1920.5607050.878590.439295
1930.5229170.9541650.477083
1940.482850.96570.51715
1950.4425090.8850190.557491
1960.4101980.8203950.589802
1970.3887930.7775870.611207
1980.3652780.7305560.634722
1990.3273950.654790.672605
2000.4251540.8503070.574846
2010.3896050.779210.610395
2020.5614480.8771040.438552
2030.5295740.9408530.470426
2040.4916540.9833070.508346
2050.4504720.9009430.549528
2060.4135480.8270950.586452
2070.3745780.7491560.625422
2080.3364050.672810.663595
2090.319580.639160.68042
2100.2816470.5632940.718353
2110.2471810.4943620.752819
2120.2208250.441650.779175
2130.2665580.5331160.733442
2140.2555360.5110720.744464
2150.2227490.4454980.777251
2160.1923990.3847980.807601
2170.1739020.3478040.826098
2180.1986670.3973340.801333
2190.1725230.3450470.827477
2200.1515430.3030850.848457
2210.1284850.2569710.871515
2220.1166750.233350.883325
2230.09442920.1888580.905571
2240.07943820.1588760.920562
2250.06777760.1355550.932222
2260.06807390.1361480.931926
2270.06419150.1283830.935808
2280.05336950.1067390.946631
2290.04184170.08368330.958158
2300.03374890.06749780.966251
2310.02605180.05210350.973948
2320.03957370.07914730.960426
2330.0432680.0865360.956732
2340.07073860.1414770.929261
2350.05325240.1065050.946748
2360.04847530.09695070.951525
2370.05920010.11840.9408
2380.1845680.3691360.815432
2390.1499560.2999130.850044
2400.2919250.583850.708075
2410.3208470.6416940.679153
2420.2656840.5313680.734316
2430.2354350.470870.764565
2440.186510.3730190.81349
2450.4318990.8637990.568101
2460.6079490.7841030.392051
2470.5945670.8108660.405433
2480.6075160.7849670.392484
2490.6329430.7341130.367057
2500.5468840.9062310.453116
2510.6397770.7204470.360223
2520.6935210.6129580.306479
2530.7585850.482830.241415
2540.7614980.4770040.238502
2550.6039730.7920530.396027






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level90.0364372OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 9 & 0.0364372 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225844&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]9[/C][C]0.0364372[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225844&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225844&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level90.0364372OK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = 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')
}