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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 20 Nov 2013 07:56:24 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/20/t13849522316sn7px958plbu0y.htm/, Retrieved Wed, 01 May 2024 22:57:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226595, Retrieved Wed, 01 May 2024 22:57:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2013-11-20 12:56:24] [86ae564e1d54e2fca6d87caa651728c1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13 12 14 12 53
16 11 18 11 83
19 15 11 14 66
15 6 12 12 67
14 13 16 21 76
13 10 18 12 78
19 12 14 22 53
15 14 14 11 80
14 12 15 10 74
15 9 15 13 76
16 10 17 10 79
16 12 19 8 54
16 12 10 15 67
16 11 16 14 54
17 15 18 10 87
15 12 14 14 58
15 10 14 14 75
20 12 17 11 88
18 11 14 10 64
16 12 16 13 57
16 11 18 9.5 66
16 12 11 14 68
19 13 14 12 54
16 11 12 14 56
17 12 17 11 86
17 13 9 9 80
16 10 16 11 76
15 14 14 15 69
16 12 15 14 78
14 10 11 13 67
15 12 16 9 80
12 8 13 15 54
14 10 17 10 71
16 12 15 11 84
14 12 14 13 74
10 7 16 8 71
10 9 9 20 63
14 12 15 12 71
16 10 17 10 76
16 10 13 10 69
16 10 15 9 74
14 12 16 14 75
20 15 16 8 54
14 10 12 14 52
14 10 15 11 69
11 12 11 13 68
14 13 15 9 65
15 11 15 11 75
16 11 17 15 74
14 12 13 11 75
16 14 16 10 72
14 10 14 14 67
12 12 11 18 63
16 13 12 14 62
9 5 12 11 63
14 6 15 14.5 76
16 12 16 13 74
16 12 15 9 67
15 11 12 10 73
16 10 12 15 70
12 7 8 20 53
16 12 13 12 77
16 14 11 12 80
14 11 14 14 52
16 12 15 13 54
17 13 10 11 80
18 14 11 17 66
18 11 12 12 73
12 12 15 13 63
16 12 15 14 69
10 8 14 13 67
14 11 16 15 54
18 14 15 13 81
18 14 15 10 69
16 12 13 11 84
17 9 12 19 80
16 13 17 13 70
16 11 13 17 69
13 12 15 13 77
16 12 13 9 54
16 12 15 11 79
16 12 15 9 71
15 12 16 12 73
15 11 15 12 72
16 10 14 13 77
14 9 15 13 75
16 12 14 12 69
16 12 13 15 54
15 12 7 22 70
12 9 17 13 73
17 15 13 15 54
16 12 15 13 77
15 12 14 15 82
13 12 13 12.5 80
16 10 16 11 80
16 13 12 16 69
16 9 14 11 78
16 12 17 11 81
14 10 15 10 76
16 14 17 10 76
16 11 12 16 73
20 15 16 12 85
15 11 11 11 66
16 11 15 16 79
13 12 9 19 68
17 12 16 11 76
16 12 15 16 71
16 11 10 15 54
12 7 10 24 46
16 12 15 14 85
16 14 11 15 74
17 11 13 11 88
13 11 14 15 38
12 10 18 12 76
18 13 16 10 86
14 13 14 14 54
14 8 14 13 67
13 11 14 9 69
16 12 14 15 90
13 11 12 15 54
16 13 14 14 76
13 12 15 11 89
16 14 15 8 76
15 13 15 11 73
16 15 13 11 79
15 10 17 8 90
17 11 17 10 74
15 9 19 11 81
12 11 15 13 72
16 10 13 11 71
10 11 9 20 66
16 8 15 10 77
12 11 15 15 65
14 12 15 12 74
15 12 16 14 85
13 9 11 23 54
15 11 14 14 63
11 10 11 16 54
12 8 15 11 64
11 9 13 12 69
16 8 15 10 54
15 9 16 14 84
17 15 14 12 86
16 11 15 12 77
10 8 16 11 89
18 13 16 12 76
13 12 11 13 60
16 12 12 11 75
13 9 9 19 73
10 7 16 12 85
15 13 13 17 79
16 9 16 9 71
16 6 12 12 72
14 8 9 19 69
10 8 13 18 78
17 15 13 15 54
13 6 14 14 69
15 9 19 11 81
16 11 13 9 84
12 8 12 18 84
13 8 13 16 69
13 10 10 24 66
12 8 14 14 81
17 14 16 20 82
15 10 10 18 72
10 8 11 23 54
14 11 14 12 78
11 12 12 14 74
13 12 9 16 82
16 12 9 18 73
12 5 11 20 55
16 12 16 12 72
12 10 9 12 78
9 7 13 17 59
12 12 16 13 72
15 11 13 9 78
12 8 9 16 68
12 9 12 18 69
14 10 16 10 67
12 9 11 14 74
16 12 14 11 54
11 6 13 9 67
19 15 15 11 70
15 12 14 10 80
8 12 16 11 89
16 12 13 19 76
17 11 14 14 74
12 7 15 12 87
11 7 13 14 54
11 5 11 21 61
14 12 11 13 38
16 12 14 10 75
12 3 15 15 69
16 11 11 16 62
13 10 15 14 72
15 12 12 12 70
16 9 14 19 79
16 12 14 15 87
14 9 8 19 62
16 12 13 13 77
16 12 9 17 69
14 10 15 12 69
11 9 17 11 75
12 12 13 14 54
15 8 15 11 72
15 11 15 13 74
16 11 14 12 85
16 12 16 15 52
11 10 13 14 70
15 10 16 12 84
12 12 9 17 64
12 12 16 11 84
15 11 11 18 87
15 8 10 13 79
16 12 11 17 67
14 10 15 13 65
17 11 17 11 85
14 10 14 12 83
13 8 8 22 61
15 12 15 14 82
13 12 11 12 76
14 10 16 12 58
15 12 10 17 72
12 9 15 9 72
13 9 9 21 38
8 6 16 10 78
14 10 19 11 54
14 9 12 12 63
11 9 8 23 66
12 9 11 13 70
13 6 14 12 71
10 10 9 16 67
16 6 15 9 58
18 14 13 17 72
13 10 16 9 72
11 10 11 14 70
4 6 12 17 76
13 12 13 13 50
16 12 10 11 72
10 7 11 12 72
12 8 12 10 88
12 11 8 19 53
10 3 12 16 58
13 6 12 16 66
15 10 15 14 82
12 8 11 20 69
14 9 13 15 68
10 9 14 23 44
12 8 10 20 56
12 9 12 16 53
11 7 15 14 70
10 7 13 17 78
12 6 13 11 71
16 9 13 13 72
12 10 12 17 68
14 11 12 15 67
16 12 9 21 75
14 8 9 18 62
13 11 15 15 67
4 3 10 8 83
15 11 14 12 64
11 12 15 12 68
11 7 7 22 62
14 9 14 12 72

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time13 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 13 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226595&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226595&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226595&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 time13 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 15.357 + 0.118945Learning[t] -0.00609477Software[t] -0.377726Depression[t] + 0.0236104Sport1[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  15.357 +  0.118945Learning[t] -0.00609477Software[t] -0.377726Depression[t] +  0.0236104Sport1[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226595&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  15.357 +  0.118945Learning[t] -0.00609477Software[t] -0.377726Depression[t] +  0.0236104Sport1[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226595&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226595&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 15.357 + 0.118945Learning[t] -0.00609477Software[t] -0.377726Depression[t] + 0.0236104Sport1[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.3571.4152410.857.37376e-233.68688e-23
Learning0.1189450.06555861.8140.07078420.0353921
Software-0.006094770.0684053-0.08910.9290730.464536
Depression-0.3777260.0386127-9.7821.95395e-199.76973e-20
Sport10.02361040.01267141.8630.06355540.0317777

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 15.357 & 1.41524 & 10.85 & 7.37376e-23 & 3.68688e-23 \tabularnewline
Learning & 0.118945 & 0.0655586 & 1.814 & 0.0707842 & 0.0353921 \tabularnewline
Software & -0.00609477 & 0.0684053 & -0.0891 & 0.929073 & 0.464536 \tabularnewline
Depression & -0.377726 & 0.0386127 & -9.782 & 1.95395e-19 & 9.76973e-20 \tabularnewline
Sport1 & 0.0236104 & 0.0126714 & 1.863 & 0.0635554 & 0.0317777 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226595&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]15.357[/C][C]1.41524[/C][C]10.85[/C][C]7.37376e-23[/C][C]3.68688e-23[/C][/ROW]
[ROW][C]Learning[/C][C]0.118945[/C][C]0.0655586[/C][C]1.814[/C][C]0.0707842[/C][C]0.0353921[/C][/ROW]
[ROW][C]Software[/C][C]-0.00609477[/C][C]0.0684053[/C][C]-0.0891[/C][C]0.929073[/C][C]0.464536[/C][/ROW]
[ROW][C]Depression[/C][C]-0.377726[/C][C]0.0386127[/C][C]-9.782[/C][C]1.95395e-19[/C][C]9.76973e-20[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0236104[/C][C]0.0126714[/C][C]1.863[/C][C]0.0635554[/C][C]0.0317777[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226595&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226595&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.3571.4152410.857.37376e-233.68688e-23
Learning0.1189450.06555861.8140.07078420.0353921
Software-0.006094770.0684053-0.08910.9290730.464536
Depression-0.3777260.0386127-9.7821.95395e-199.76973e-20
Sport10.02361040.01267141.8630.06355540.0317777






Multiple Linear Regression - Regression Statistics
Multiple R0.601733
R-squared0.362083
Adjusted R-squared0.352231
F-TEST (value)36.7523
F-TEST (DF numerator)4
F-TEST (DF denominator)259
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01101
Sum Squared Residuals1047.44

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.601733 \tabularnewline
R-squared & 0.362083 \tabularnewline
Adjusted R-squared & 0.352231 \tabularnewline
F-TEST (value) & 36.7523 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 259 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.01101 \tabularnewline
Sum Squared Residuals & 1047.44 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226595&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.601733[/C][/ROW]
[ROW][C]R-squared[/C][C]0.362083[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.352231[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]36.7523[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]259[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.01101[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1047.44[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226595&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226595&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 R0.601733
R-squared0.362083
Adjusted R-squared0.352231
F-TEST (value)36.7523
F-TEST (DF numerator)4
F-TEST (DF denominator)259
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.01101
Sum Squared Residuals1047.44






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.54870.45126
21814.99773.00229
31113.7956-2.79561
41214.1537-2.15374
51610.80515.1949
61814.15123.84881
71410.48523.51485
81414.7896-0.789646
91514.9190.081046
101513.97021.02977
111715.28711.71291
121915.44013.55991
131013.1029-3.10294
141613.17982.82017
151815.56442.43556
161413.14920.85077
171413.56280.437204
181715.58541.41456
191415.1647-1.16472
201613.62232.37771
211815.16292.83708
221113.5043-2.50428
231414.2799-0.279925
241213.227-1.22705
251715.18141.81861
26915.7891-6.78908
271614.83851.16147
281413.0190.980971
291513.74041.25962
301113.6327-2.63269
311615.55730.442713
321312.34460.655392
331714.86032.13969
341515.0152-0.0152217
351413.78580.214223
361615.15830.841731
37910.4245-1.42449
381514.09270.907328
391715.21631.78375
401315.051-2.05098
411515.5468-0.546759
421613.43172.56834
431615.89760.102417
441212.9008-0.900813
451514.43540.564634
461113.2873-2.28728
471515.0781-0.0780917
481514.68990.310122
491713.27433.72569
501314.5648-1.56484
511615.09740.902567
521413.2550.745032
531111.3995-0.399545
541213.3565-1.35652
551213.7295-1.72945
561513.3031.69702
571614.02371.97633
581515.3693-0.369297
591215.0204-3.02038
601213.186-1.18596
61810.4385-2.43846
621314.4722-1.47222
631114.5309-3.53086
641412.89471.10528
651513.55151.44854
661015.0336-5.03363
671112.5496-1.54958
681214.6218-2.62177
691513.28821.71183
701513.52791.47211
711413.16910.830896
721612.56423.43579
731514.41460.585361
741515.2645-0.264492
751315.0152-2.01522
761212.0362-0.0362037
771713.92313.07687
781312.40080.599193
791513.73771.26234
801315.0624-2.06236
811514.89720.10283
821515.4637-0.463738
831614.25881.74116
841514.24130.758678
851414.1067-0.106687
861513.82771.17233
871414.2833-0.28334
881312.7960.203992
89710.4107-3.41075
901713.54263.45744
911312.89670.103332
921514.09450.905502
931413.33820.661847
941313.9974-0.997357
951614.9331.06703
961212.7663-0.766343
971414.8918-0.891844
981714.94442.05561
991514.97840.0216357
1001715.19191.80813
1011212.873-0.872974
1021615.11860.881399
1031114.4774-3.47739
1041513.01461.98536
105911.2588-2.25882
1061614.94531.05472
1071512.81972.18034
1081012.8021-2.8021
109108.762291.23771
1101513.90571.09435
1111113.256-2.25603
1121315.2347-2.2347
1131412.06751.9325
1141813.9854.01498
1151615.6720.328037
1161412.92971.07025
1171413.64490.355117
1181415.0658-1.06578
1191413.6460.354019
1201212.4453-0.445268
1211413.68710.312933
1221514.77640.223561
1231515.9473-0.947326
1241514.63050.369532
1251314.8789-1.87889
1261716.18330.816694
1271715.28191.71812
1281914.84374.15627
1291513.50681.49324
1301314.7205-1.72048
131910.4831-1.48313
1321515.2521-0.252054
1331512.5862.41396
1341514.16350.836497
1351613.78672.21329
136119.435651.56435
1371413.27340.726623
1381111.8357-0.835748
1391514.09160.908386
1401313.7069-0.706901
1411514.7090.290984
1421613.78142.21862
1431414.7854-0.785377
1441514.47830.521682
1451614.4441.55602
1461614.68041.31959
1471113.3363-2.33629
1481214.8027-2.80273
149911.3952-2.39515
1501613.97792.02209
1511312.50580.494224
1521615.4820.517977
1531214.3907-2.39074
154911.4257-2.42575
1551311.54021.45981
1561312.89670.103332
1571413.20760.792377
1581914.84374.15627
1591315.7768-2.77677
1601211.91970.0802586
1611312.440.560018
162109.335160.664844
1631413.35980.640187
1641611.67524.32478
1651011.9811-1.98106
166119.084911.91509
1671414.264-0.264039
1681213.0512-1.05122
169912.7225-3.72254
170912.1114-3.11143
1711110.49790.502126
1721614.35421.64583
173914.0322-5.03224
1741311.35651.64353
1751613.50072.49933
1761315.5162-2.51616
177912.2974-3.29743
1781211.55950.440509
1791614.76591.23413
1801113.1884-2.18845
1811414.3069-0.306911
1821314.8111-1.81114
1831515.0232-0.0232268
1841415.1796-1.17956
1851614.18171.81829
1861311.80451.19547
1871413.7710.229019
1881514.2630.736978
1891312.60950.390517
1901110.14290.857135
1911112.9358-1.9358
1921415.1805-1.18045
1931512.72922.27076
1941112.6133-1.61326
1951513.25411.74592
1961214.188-2.18801
1971411.89362.10635
1981413.57510.42485
199811.2544-3.25438
2001314.0945-1.0945
201912.3947-3.39471
2021514.05760.94236
2031714.22632.77371
2041312.6980.302046
2051514.63730.362668
2061513.91081.08918
2071414.6672-0.667201
2081612.74883.25121
2091312.9690.0310352
2101614.53071.46926
211911.8009-2.80088
2121614.53941.46056
2131112.3291-1.32912
2141014.0472-4.04715
2151112.3475-1.34749
2161513.58551.41453
2171715.16391.83613
2181414.3882-0.388185
21989.98475-1.98475
2201513.71591.28412
2211114.0918-3.09178
2221613.79792.20207
2231012.3466-2.3466
2241515.0299-0.0298536
22599.81334-0.813338
2261614.33631.6637
2271914.08124.91879
2281213.9221-1.92207
22989.48109-1.48109
2301113.4717-2.47173
2311414.0103-0.0102953
232912.0237-3.02374
2331515.1934-0.193372
2341312.69120.308757
2351615.14270.857296
2361112.969-1.96896
2371211.16920.830785
2381313.1002-0.100183
2391014.7319-4.7319
2401113.671-2.67098
2411215.036-3.03599
242810.7918-2.79181
2431211.85390.146092
2441212.3813-0.381341
2451513.72811.27193
2461110.81010.189865
2471312.90690.0930524
248148.842715.15729
2491010.5032-0.5032
2501211.93720.0628232
2511512.98722.01275
2521311.9241.07599
2531314.2691-1.26908
2541313.9947-0.99473
2551211.90750.0924882
2561212.8711-0.871148
257911.0255-2.02547
258911.6382-2.6382
2591512.75222.2478
2601014.7523-4.7523
2611414.0524-0.0524386
2621513.6651.33499
26379.77656-2.77656
2641414.1346-0.134566

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 13.5487 & 0.45126 \tabularnewline
2 & 18 & 14.9977 & 3.00229 \tabularnewline
3 & 11 & 13.7956 & -2.79561 \tabularnewline
4 & 12 & 14.1537 & -2.15374 \tabularnewline
5 & 16 & 10.8051 & 5.1949 \tabularnewline
6 & 18 & 14.1512 & 3.84881 \tabularnewline
7 & 14 & 10.4852 & 3.51485 \tabularnewline
8 & 14 & 14.7896 & -0.789646 \tabularnewline
9 & 15 & 14.919 & 0.081046 \tabularnewline
10 & 15 & 13.9702 & 1.02977 \tabularnewline
11 & 17 & 15.2871 & 1.71291 \tabularnewline
12 & 19 & 15.4401 & 3.55991 \tabularnewline
13 & 10 & 13.1029 & -3.10294 \tabularnewline
14 & 16 & 13.1798 & 2.82017 \tabularnewline
15 & 18 & 15.5644 & 2.43556 \tabularnewline
16 & 14 & 13.1492 & 0.85077 \tabularnewline
17 & 14 & 13.5628 & 0.437204 \tabularnewline
18 & 17 & 15.5854 & 1.41456 \tabularnewline
19 & 14 & 15.1647 & -1.16472 \tabularnewline
20 & 16 & 13.6223 & 2.37771 \tabularnewline
21 & 18 & 15.1629 & 2.83708 \tabularnewline
22 & 11 & 13.5043 & -2.50428 \tabularnewline
23 & 14 & 14.2799 & -0.279925 \tabularnewline
24 & 12 & 13.227 & -1.22705 \tabularnewline
25 & 17 & 15.1814 & 1.81861 \tabularnewline
26 & 9 & 15.7891 & -6.78908 \tabularnewline
27 & 16 & 14.8385 & 1.16147 \tabularnewline
28 & 14 & 13.019 & 0.980971 \tabularnewline
29 & 15 & 13.7404 & 1.25962 \tabularnewline
30 & 11 & 13.6327 & -2.63269 \tabularnewline
31 & 16 & 15.5573 & 0.442713 \tabularnewline
32 & 13 & 12.3446 & 0.655392 \tabularnewline
33 & 17 & 14.8603 & 2.13969 \tabularnewline
34 & 15 & 15.0152 & -0.0152217 \tabularnewline
35 & 14 & 13.7858 & 0.214223 \tabularnewline
36 & 16 & 15.1583 & 0.841731 \tabularnewline
37 & 9 & 10.4245 & -1.42449 \tabularnewline
38 & 15 & 14.0927 & 0.907328 \tabularnewline
39 & 17 & 15.2163 & 1.78375 \tabularnewline
40 & 13 & 15.051 & -2.05098 \tabularnewline
41 & 15 & 15.5468 & -0.546759 \tabularnewline
42 & 16 & 13.4317 & 2.56834 \tabularnewline
43 & 16 & 15.8976 & 0.102417 \tabularnewline
44 & 12 & 12.9008 & -0.900813 \tabularnewline
45 & 15 & 14.4354 & 0.564634 \tabularnewline
46 & 11 & 13.2873 & -2.28728 \tabularnewline
47 & 15 & 15.0781 & -0.0780917 \tabularnewline
48 & 15 & 14.6899 & 0.310122 \tabularnewline
49 & 17 & 13.2743 & 3.72569 \tabularnewline
50 & 13 & 14.5648 & -1.56484 \tabularnewline
51 & 16 & 15.0974 & 0.902567 \tabularnewline
52 & 14 & 13.255 & 0.745032 \tabularnewline
53 & 11 & 11.3995 & -0.399545 \tabularnewline
54 & 12 & 13.3565 & -1.35652 \tabularnewline
55 & 12 & 13.7295 & -1.72945 \tabularnewline
56 & 15 & 13.303 & 1.69702 \tabularnewline
57 & 16 & 14.0237 & 1.97633 \tabularnewline
58 & 15 & 15.3693 & -0.369297 \tabularnewline
59 & 12 & 15.0204 & -3.02038 \tabularnewline
60 & 12 & 13.186 & -1.18596 \tabularnewline
61 & 8 & 10.4385 & -2.43846 \tabularnewline
62 & 13 & 14.4722 & -1.47222 \tabularnewline
63 & 11 & 14.5309 & -3.53086 \tabularnewline
64 & 14 & 12.8947 & 1.10528 \tabularnewline
65 & 15 & 13.5515 & 1.44854 \tabularnewline
66 & 10 & 15.0336 & -5.03363 \tabularnewline
67 & 11 & 12.5496 & -1.54958 \tabularnewline
68 & 12 & 14.6218 & -2.62177 \tabularnewline
69 & 15 & 13.2882 & 1.71183 \tabularnewline
70 & 15 & 13.5279 & 1.47211 \tabularnewline
71 & 14 & 13.1691 & 0.830896 \tabularnewline
72 & 16 & 12.5642 & 3.43579 \tabularnewline
73 & 15 & 14.4146 & 0.585361 \tabularnewline
74 & 15 & 15.2645 & -0.264492 \tabularnewline
75 & 13 & 15.0152 & -2.01522 \tabularnewline
76 & 12 & 12.0362 & -0.0362037 \tabularnewline
77 & 17 & 13.9231 & 3.07687 \tabularnewline
78 & 13 & 12.4008 & 0.599193 \tabularnewline
79 & 15 & 13.7377 & 1.26234 \tabularnewline
80 & 13 & 15.0624 & -2.06236 \tabularnewline
81 & 15 & 14.8972 & 0.10283 \tabularnewline
82 & 15 & 15.4637 & -0.463738 \tabularnewline
83 & 16 & 14.2588 & 1.74116 \tabularnewline
84 & 15 & 14.2413 & 0.758678 \tabularnewline
85 & 14 & 14.1067 & -0.106687 \tabularnewline
86 & 15 & 13.8277 & 1.17233 \tabularnewline
87 & 14 & 14.2833 & -0.28334 \tabularnewline
88 & 13 & 12.796 & 0.203992 \tabularnewline
89 & 7 & 10.4107 & -3.41075 \tabularnewline
90 & 17 & 13.5426 & 3.45744 \tabularnewline
91 & 13 & 12.8967 & 0.103332 \tabularnewline
92 & 15 & 14.0945 & 0.905502 \tabularnewline
93 & 14 & 13.3382 & 0.661847 \tabularnewline
94 & 13 & 13.9974 & -0.997357 \tabularnewline
95 & 16 & 14.933 & 1.06703 \tabularnewline
96 & 12 & 12.7663 & -0.766343 \tabularnewline
97 & 14 & 14.8918 & -0.891844 \tabularnewline
98 & 17 & 14.9444 & 2.05561 \tabularnewline
99 & 15 & 14.9784 & 0.0216357 \tabularnewline
100 & 17 & 15.1919 & 1.80813 \tabularnewline
101 & 12 & 12.873 & -0.872974 \tabularnewline
102 & 16 & 15.1186 & 0.881399 \tabularnewline
103 & 11 & 14.4774 & -3.47739 \tabularnewline
104 & 15 & 13.0146 & 1.98536 \tabularnewline
105 & 9 & 11.2588 & -2.25882 \tabularnewline
106 & 16 & 14.9453 & 1.05472 \tabularnewline
107 & 15 & 12.8197 & 2.18034 \tabularnewline
108 & 10 & 12.8021 & -2.8021 \tabularnewline
109 & 10 & 8.76229 & 1.23771 \tabularnewline
110 & 15 & 13.9057 & 1.09435 \tabularnewline
111 & 11 & 13.256 & -2.25603 \tabularnewline
112 & 13 & 15.2347 & -2.2347 \tabularnewline
113 & 14 & 12.0675 & 1.9325 \tabularnewline
114 & 18 & 13.985 & 4.01498 \tabularnewline
115 & 16 & 15.672 & 0.328037 \tabularnewline
116 & 14 & 12.9297 & 1.07025 \tabularnewline
117 & 14 & 13.6449 & 0.355117 \tabularnewline
118 & 14 & 15.0658 & -1.06578 \tabularnewline
119 & 14 & 13.646 & 0.354019 \tabularnewline
120 & 12 & 12.4453 & -0.445268 \tabularnewline
121 & 14 & 13.6871 & 0.312933 \tabularnewline
122 & 15 & 14.7764 & 0.223561 \tabularnewline
123 & 15 & 15.9473 & -0.947326 \tabularnewline
124 & 15 & 14.6305 & 0.369532 \tabularnewline
125 & 13 & 14.8789 & -1.87889 \tabularnewline
126 & 17 & 16.1833 & 0.816694 \tabularnewline
127 & 17 & 15.2819 & 1.71812 \tabularnewline
128 & 19 & 14.8437 & 4.15627 \tabularnewline
129 & 15 & 13.5068 & 1.49324 \tabularnewline
130 & 13 & 14.7205 & -1.72048 \tabularnewline
131 & 9 & 10.4831 & -1.48313 \tabularnewline
132 & 15 & 15.2521 & -0.252054 \tabularnewline
133 & 15 & 12.586 & 2.41396 \tabularnewline
134 & 15 & 14.1635 & 0.836497 \tabularnewline
135 & 16 & 13.7867 & 2.21329 \tabularnewline
136 & 11 & 9.43565 & 1.56435 \tabularnewline
137 & 14 & 13.2734 & 0.726623 \tabularnewline
138 & 11 & 11.8357 & -0.835748 \tabularnewline
139 & 15 & 14.0916 & 0.908386 \tabularnewline
140 & 13 & 13.7069 & -0.706901 \tabularnewline
141 & 15 & 14.709 & 0.290984 \tabularnewline
142 & 16 & 13.7814 & 2.21862 \tabularnewline
143 & 14 & 14.7854 & -0.785377 \tabularnewline
144 & 15 & 14.4783 & 0.521682 \tabularnewline
145 & 16 & 14.444 & 1.55602 \tabularnewline
146 & 16 & 14.6804 & 1.31959 \tabularnewline
147 & 11 & 13.3363 & -2.33629 \tabularnewline
148 & 12 & 14.8027 & -2.80273 \tabularnewline
149 & 9 & 11.3952 & -2.39515 \tabularnewline
150 & 16 & 13.9779 & 2.02209 \tabularnewline
151 & 13 & 12.5058 & 0.494224 \tabularnewline
152 & 16 & 15.482 & 0.517977 \tabularnewline
153 & 12 & 14.3907 & -2.39074 \tabularnewline
154 & 9 & 11.4257 & -2.42575 \tabularnewline
155 & 13 & 11.5402 & 1.45981 \tabularnewline
156 & 13 & 12.8967 & 0.103332 \tabularnewline
157 & 14 & 13.2076 & 0.792377 \tabularnewline
158 & 19 & 14.8437 & 4.15627 \tabularnewline
159 & 13 & 15.7768 & -2.77677 \tabularnewline
160 & 12 & 11.9197 & 0.0802586 \tabularnewline
161 & 13 & 12.44 & 0.560018 \tabularnewline
162 & 10 & 9.33516 & 0.664844 \tabularnewline
163 & 14 & 13.3598 & 0.640187 \tabularnewline
164 & 16 & 11.6752 & 4.32478 \tabularnewline
165 & 10 & 11.9811 & -1.98106 \tabularnewline
166 & 11 & 9.08491 & 1.91509 \tabularnewline
167 & 14 & 14.264 & -0.264039 \tabularnewline
168 & 12 & 13.0512 & -1.05122 \tabularnewline
169 & 9 & 12.7225 & -3.72254 \tabularnewline
170 & 9 & 12.1114 & -3.11143 \tabularnewline
171 & 11 & 10.4979 & 0.502126 \tabularnewline
172 & 16 & 14.3542 & 1.64583 \tabularnewline
173 & 9 & 14.0322 & -5.03224 \tabularnewline
174 & 13 & 11.3565 & 1.64353 \tabularnewline
175 & 16 & 13.5007 & 2.49933 \tabularnewline
176 & 13 & 15.5162 & -2.51616 \tabularnewline
177 & 9 & 12.2974 & -3.29743 \tabularnewline
178 & 12 & 11.5595 & 0.440509 \tabularnewline
179 & 16 & 14.7659 & 1.23413 \tabularnewline
180 & 11 & 13.1884 & -2.18845 \tabularnewline
181 & 14 & 14.3069 & -0.306911 \tabularnewline
182 & 13 & 14.8111 & -1.81114 \tabularnewline
183 & 15 & 15.0232 & -0.0232268 \tabularnewline
184 & 14 & 15.1796 & -1.17956 \tabularnewline
185 & 16 & 14.1817 & 1.81829 \tabularnewline
186 & 13 & 11.8045 & 1.19547 \tabularnewline
187 & 14 & 13.771 & 0.229019 \tabularnewline
188 & 15 & 14.263 & 0.736978 \tabularnewline
189 & 13 & 12.6095 & 0.390517 \tabularnewline
190 & 11 & 10.1429 & 0.857135 \tabularnewline
191 & 11 & 12.9358 & -1.9358 \tabularnewline
192 & 14 & 15.1805 & -1.18045 \tabularnewline
193 & 15 & 12.7292 & 2.27076 \tabularnewline
194 & 11 & 12.6133 & -1.61326 \tabularnewline
195 & 15 & 13.2541 & 1.74592 \tabularnewline
196 & 12 & 14.188 & -2.18801 \tabularnewline
197 & 14 & 11.8936 & 2.10635 \tabularnewline
198 & 14 & 13.5751 & 0.42485 \tabularnewline
199 & 8 & 11.2544 & -3.25438 \tabularnewline
200 & 13 & 14.0945 & -1.0945 \tabularnewline
201 & 9 & 12.3947 & -3.39471 \tabularnewline
202 & 15 & 14.0576 & 0.94236 \tabularnewline
203 & 17 & 14.2263 & 2.77371 \tabularnewline
204 & 13 & 12.698 & 0.302046 \tabularnewline
205 & 15 & 14.6373 & 0.362668 \tabularnewline
206 & 15 & 13.9108 & 1.08918 \tabularnewline
207 & 14 & 14.6672 & -0.667201 \tabularnewline
208 & 16 & 12.7488 & 3.25121 \tabularnewline
209 & 13 & 12.969 & 0.0310352 \tabularnewline
210 & 16 & 14.5307 & 1.46926 \tabularnewline
211 & 9 & 11.8009 & -2.80088 \tabularnewline
212 & 16 & 14.5394 & 1.46056 \tabularnewline
213 & 11 & 12.3291 & -1.32912 \tabularnewline
214 & 10 & 14.0472 & -4.04715 \tabularnewline
215 & 11 & 12.3475 & -1.34749 \tabularnewline
216 & 15 & 13.5855 & 1.41453 \tabularnewline
217 & 17 & 15.1639 & 1.83613 \tabularnewline
218 & 14 & 14.3882 & -0.388185 \tabularnewline
219 & 8 & 9.98475 & -1.98475 \tabularnewline
220 & 15 & 13.7159 & 1.28412 \tabularnewline
221 & 11 & 14.0918 & -3.09178 \tabularnewline
222 & 16 & 13.7979 & 2.20207 \tabularnewline
223 & 10 & 12.3466 & -2.3466 \tabularnewline
224 & 15 & 15.0299 & -0.0298536 \tabularnewline
225 & 9 & 9.81334 & -0.813338 \tabularnewline
226 & 16 & 14.3363 & 1.6637 \tabularnewline
227 & 19 & 14.0812 & 4.91879 \tabularnewline
228 & 12 & 13.9221 & -1.92207 \tabularnewline
229 & 8 & 9.48109 & -1.48109 \tabularnewline
230 & 11 & 13.4717 & -2.47173 \tabularnewline
231 & 14 & 14.0103 & -0.0102953 \tabularnewline
232 & 9 & 12.0237 & -3.02374 \tabularnewline
233 & 15 & 15.1934 & -0.193372 \tabularnewline
234 & 13 & 12.6912 & 0.308757 \tabularnewline
235 & 16 & 15.1427 & 0.857296 \tabularnewline
236 & 11 & 12.969 & -1.96896 \tabularnewline
237 & 12 & 11.1692 & 0.830785 \tabularnewline
238 & 13 & 13.1002 & -0.100183 \tabularnewline
239 & 10 & 14.7319 & -4.7319 \tabularnewline
240 & 11 & 13.671 & -2.67098 \tabularnewline
241 & 12 & 15.036 & -3.03599 \tabularnewline
242 & 8 & 10.7918 & -2.79181 \tabularnewline
243 & 12 & 11.8539 & 0.146092 \tabularnewline
244 & 12 & 12.3813 & -0.381341 \tabularnewline
245 & 15 & 13.7281 & 1.27193 \tabularnewline
246 & 11 & 10.8101 & 0.189865 \tabularnewline
247 & 13 & 12.9069 & 0.0930524 \tabularnewline
248 & 14 & 8.84271 & 5.15729 \tabularnewline
249 & 10 & 10.5032 & -0.5032 \tabularnewline
250 & 12 & 11.9372 & 0.0628232 \tabularnewline
251 & 15 & 12.9872 & 2.01275 \tabularnewline
252 & 13 & 11.924 & 1.07599 \tabularnewline
253 & 13 & 14.2691 & -1.26908 \tabularnewline
254 & 13 & 13.9947 & -0.99473 \tabularnewline
255 & 12 & 11.9075 & 0.0924882 \tabularnewline
256 & 12 & 12.8711 & -0.871148 \tabularnewline
257 & 9 & 11.0255 & -2.02547 \tabularnewline
258 & 9 & 11.6382 & -2.6382 \tabularnewline
259 & 15 & 12.7522 & 2.2478 \tabularnewline
260 & 10 & 14.7523 & -4.7523 \tabularnewline
261 & 14 & 14.0524 & -0.0524386 \tabularnewline
262 & 15 & 13.665 & 1.33499 \tabularnewline
263 & 7 & 9.77656 & -2.77656 \tabularnewline
264 & 14 & 14.1346 & -0.134566 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226595&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]14[/C][C]13.5487[/C][C]0.45126[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]14.9977[/C][C]3.00229[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.7956[/C][C]-2.79561[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.1537[/C][C]-2.15374[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]10.8051[/C][C]5.1949[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.1512[/C][C]3.84881[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.4852[/C][C]3.51485[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]14.7896[/C][C]-0.789646[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]14.919[/C][C]0.081046[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]13.9702[/C][C]1.02977[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.2871[/C][C]1.71291[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.4401[/C][C]3.55991[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.1029[/C][C]-3.10294[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.1798[/C][C]2.82017[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.5644[/C][C]2.43556[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.1492[/C][C]0.85077[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.5628[/C][C]0.437204[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.5854[/C][C]1.41456[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.1647[/C][C]-1.16472[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.6223[/C][C]2.37771[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.1629[/C][C]2.83708[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.5043[/C][C]-2.50428[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.2799[/C][C]-0.279925[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.227[/C][C]-1.22705[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.1814[/C][C]1.81861[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.7891[/C][C]-6.78908[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.8385[/C][C]1.16147[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.019[/C][C]0.980971[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.7404[/C][C]1.25962[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]13.6327[/C][C]-2.63269[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.5573[/C][C]0.442713[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.3446[/C][C]0.655392[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]14.8603[/C][C]2.13969[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.0152[/C][C]-0.0152217[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.7858[/C][C]0.214223[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.1583[/C][C]0.841731[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.4245[/C][C]-1.42449[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.0927[/C][C]0.907328[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.2163[/C][C]1.78375[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.051[/C][C]-2.05098[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.5468[/C][C]-0.546759[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.4317[/C][C]2.56834[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.8976[/C][C]0.102417[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]12.9008[/C][C]-0.900813[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.4354[/C][C]0.564634[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.2873[/C][C]-2.28728[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.0781[/C][C]-0.0780917[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.6899[/C][C]0.310122[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.2743[/C][C]3.72569[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.5648[/C][C]-1.56484[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.0974[/C][C]0.902567[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.255[/C][C]0.745032[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.3995[/C][C]-0.399545[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.3565[/C][C]-1.35652[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]13.7295[/C][C]-1.72945[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.303[/C][C]1.69702[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.0237[/C][C]1.97633[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.3693[/C][C]-0.369297[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.0204[/C][C]-3.02038[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.186[/C][C]-1.18596[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.4385[/C][C]-2.43846[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.4722[/C][C]-1.47222[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.5309[/C][C]-3.53086[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]12.8947[/C][C]1.10528[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.5515[/C][C]1.44854[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.0336[/C][C]-5.03363[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.5496[/C][C]-1.54958[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.6218[/C][C]-2.62177[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.2882[/C][C]1.71183[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.5279[/C][C]1.47211[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.1691[/C][C]0.830896[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.5642[/C][C]3.43579[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.4146[/C][C]0.585361[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.2645[/C][C]-0.264492[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]15.0152[/C][C]-2.01522[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.0362[/C][C]-0.0362037[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]13.9231[/C][C]3.07687[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.4008[/C][C]0.599193[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.7377[/C][C]1.26234[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]15.0624[/C][C]-2.06236[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.8972[/C][C]0.10283[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.4637[/C][C]-0.463738[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.2588[/C][C]1.74116[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.2413[/C][C]0.758678[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.1067[/C][C]-0.106687[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.8277[/C][C]1.17233[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.2833[/C][C]-0.28334[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.796[/C][C]0.203992[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.4107[/C][C]-3.41075[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]13.5426[/C][C]3.45744[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.8967[/C][C]0.103332[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.0945[/C][C]0.905502[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.3382[/C][C]0.661847[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.9974[/C][C]-0.997357[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.933[/C][C]1.06703[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.7663[/C][C]-0.766343[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.8918[/C][C]-0.891844[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.9444[/C][C]2.05561[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]14.9784[/C][C]0.0216357[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.1919[/C][C]1.80813[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.873[/C][C]-0.872974[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]15.1186[/C][C]0.881399[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.4774[/C][C]-3.47739[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.0146[/C][C]1.98536[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.2588[/C][C]-2.25882[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.9453[/C][C]1.05472[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.8197[/C][C]2.18034[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.8021[/C][C]-2.8021[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]8.76229[/C][C]1.23771[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.9057[/C][C]1.09435[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.256[/C][C]-2.25603[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.2347[/C][C]-2.2347[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]12.0675[/C][C]1.9325[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]13.985[/C][C]4.01498[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.672[/C][C]0.328037[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]12.9297[/C][C]1.07025[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.6449[/C][C]0.355117[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.0658[/C][C]-1.06578[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.646[/C][C]0.354019[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.4453[/C][C]-0.445268[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.6871[/C][C]0.312933[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.7764[/C][C]0.223561[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.9473[/C][C]-0.947326[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.6305[/C][C]0.369532[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.8789[/C][C]-1.87889[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.1833[/C][C]0.816694[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.2819[/C][C]1.71812[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.8437[/C][C]4.15627[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5068[/C][C]1.49324[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.7205[/C][C]-1.72048[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.4831[/C][C]-1.48313[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.2521[/C][C]-0.252054[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.586[/C][C]2.41396[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.1635[/C][C]0.836497[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.7867[/C][C]2.21329[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.43565[/C][C]1.56435[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.2734[/C][C]0.726623[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]11.8357[/C][C]-0.835748[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.0916[/C][C]0.908386[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.7069[/C][C]-0.706901[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.709[/C][C]0.290984[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.7814[/C][C]2.21862[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.7854[/C][C]-0.785377[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.4783[/C][C]0.521682[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.444[/C][C]1.55602[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.6804[/C][C]1.31959[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.3363[/C][C]-2.33629[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.8027[/C][C]-2.80273[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.3952[/C][C]-2.39515[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]13.9779[/C][C]2.02209[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.5058[/C][C]0.494224[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.482[/C][C]0.517977[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.3907[/C][C]-2.39074[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.4257[/C][C]-2.42575[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.5402[/C][C]1.45981[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.8967[/C][C]0.103332[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.2076[/C][C]0.792377[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.8437[/C][C]4.15627[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.7768[/C][C]-2.77677[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.9197[/C][C]0.0802586[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.44[/C][C]0.560018[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.33516[/C][C]0.664844[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.3598[/C][C]0.640187[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.6752[/C][C]4.32478[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.9811[/C][C]-1.98106[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]9.08491[/C][C]1.91509[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.264[/C][C]-0.264039[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]13.0512[/C][C]-1.05122[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.7225[/C][C]-3.72254[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]12.1114[/C][C]-3.11143[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.4979[/C][C]0.502126[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.3542[/C][C]1.64583[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]14.0322[/C][C]-5.03224[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.3565[/C][C]1.64353[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.5007[/C][C]2.49933[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.5162[/C][C]-2.51616[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.2974[/C][C]-3.29743[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.5595[/C][C]0.440509[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.7659[/C][C]1.23413[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.1884[/C][C]-2.18845[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]14.3069[/C][C]-0.306911[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.8111[/C][C]-1.81114[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]15.0232[/C][C]-0.0232268[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]15.1796[/C][C]-1.17956[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]14.1817[/C][C]1.81829[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.8045[/C][C]1.19547[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.771[/C][C]0.229019[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.263[/C][C]0.736978[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.6095[/C][C]0.390517[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.1429[/C][C]0.857135[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.9358[/C][C]-1.9358[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]15.1805[/C][C]-1.18045[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.7292[/C][C]2.27076[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.6133[/C][C]-1.61326[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.2541[/C][C]1.74592[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.188[/C][C]-2.18801[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.8936[/C][C]2.10635[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.5751[/C][C]0.42485[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.2544[/C][C]-3.25438[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]14.0945[/C][C]-1.0945[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.3947[/C][C]-3.39471[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]14.0576[/C][C]0.94236[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]14.2263[/C][C]2.77371[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.698[/C][C]0.302046[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.6373[/C][C]0.362668[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.9108[/C][C]1.08918[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.6672[/C][C]-0.667201[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.7488[/C][C]3.25121[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.969[/C][C]0.0310352[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.5307[/C][C]1.46926[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.8009[/C][C]-2.80088[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.5394[/C][C]1.46056[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.3291[/C][C]-1.32912[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]14.0472[/C][C]-4.04715[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.3475[/C][C]-1.34749[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.5855[/C][C]1.41453[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]15.1639[/C][C]1.83613[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.3882[/C][C]-0.388185[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.98475[/C][C]-1.98475[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.7159[/C][C]1.28412[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]14.0918[/C][C]-3.09178[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.7979[/C][C]2.20207[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.3466[/C][C]-2.3466[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]15.0299[/C][C]-0.0298536[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.81334[/C][C]-0.813338[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.3363[/C][C]1.6637[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]14.0812[/C][C]4.91879[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.9221[/C][C]-1.92207[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.48109[/C][C]-1.48109[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.4717[/C][C]-2.47173[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]14.0103[/C][C]-0.0102953[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]12.0237[/C][C]-3.02374[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]15.1934[/C][C]-0.193372[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.6912[/C][C]0.308757[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]15.1427[/C][C]0.857296[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.969[/C][C]-1.96896[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.1692[/C][C]0.830785[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.1002[/C][C]-0.100183[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.7319[/C][C]-4.7319[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.671[/C][C]-2.67098[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]15.036[/C][C]-3.03599[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.7918[/C][C]-2.79181[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.8539[/C][C]0.146092[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.3813[/C][C]-0.381341[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.7281[/C][C]1.27193[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.8101[/C][C]0.189865[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.9069[/C][C]0.0930524[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.84271[/C][C]5.15729[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.5032[/C][C]-0.5032[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.9372[/C][C]0.0628232[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.9872[/C][C]2.01275[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.924[/C][C]1.07599[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.2691[/C][C]-1.26908[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.9947[/C][C]-0.99473[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.9075[/C][C]0.0924882[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.8711[/C][C]-0.871148[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]11.0255[/C][C]-2.02547[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.6382[/C][C]-2.6382[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.7522[/C][C]2.2478[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.7523[/C][C]-4.7523[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]14.0524[/C][C]-0.0524386[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.665[/C][C]1.33499[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.77656[/C][C]-2.77656[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]14.1346[/C][C]-0.134566[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226595&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226595&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
11413.54870.45126
21814.99773.00229
31113.7956-2.79561
41214.1537-2.15374
51610.80515.1949
61814.15123.84881
71410.48523.51485
81414.7896-0.789646
91514.9190.081046
101513.97021.02977
111715.28711.71291
121915.44013.55991
131013.1029-3.10294
141613.17982.82017
151815.56442.43556
161413.14920.85077
171413.56280.437204
181715.58541.41456
191415.1647-1.16472
201613.62232.37771
211815.16292.83708
221113.5043-2.50428
231414.2799-0.279925
241213.227-1.22705
251715.18141.81861
26915.7891-6.78908
271614.83851.16147
281413.0190.980971
291513.74041.25962
301113.6327-2.63269
311615.55730.442713
321312.34460.655392
331714.86032.13969
341515.0152-0.0152217
351413.78580.214223
361615.15830.841731
37910.4245-1.42449
381514.09270.907328
391715.21631.78375
401315.051-2.05098
411515.5468-0.546759
421613.43172.56834
431615.89760.102417
441212.9008-0.900813
451514.43540.564634
461113.2873-2.28728
471515.0781-0.0780917
481514.68990.310122
491713.27433.72569
501314.5648-1.56484
511615.09740.902567
521413.2550.745032
531111.3995-0.399545
541213.3565-1.35652
551213.7295-1.72945
561513.3031.69702
571614.02371.97633
581515.3693-0.369297
591215.0204-3.02038
601213.186-1.18596
61810.4385-2.43846
621314.4722-1.47222
631114.5309-3.53086
641412.89471.10528
651513.55151.44854
661015.0336-5.03363
671112.5496-1.54958
681214.6218-2.62177
691513.28821.71183
701513.52791.47211
711413.16910.830896
721612.56423.43579
731514.41460.585361
741515.2645-0.264492
751315.0152-2.01522
761212.0362-0.0362037
771713.92313.07687
781312.40080.599193
791513.73771.26234
801315.0624-2.06236
811514.89720.10283
821515.4637-0.463738
831614.25881.74116
841514.24130.758678
851414.1067-0.106687
861513.82771.17233
871414.2833-0.28334
881312.7960.203992
89710.4107-3.41075
901713.54263.45744
911312.89670.103332
921514.09450.905502
931413.33820.661847
941313.9974-0.997357
951614.9331.06703
961212.7663-0.766343
971414.8918-0.891844
981714.94442.05561
991514.97840.0216357
1001715.19191.80813
1011212.873-0.872974
1021615.11860.881399
1031114.4774-3.47739
1041513.01461.98536
105911.2588-2.25882
1061614.94531.05472
1071512.81972.18034
1081012.8021-2.8021
109108.762291.23771
1101513.90571.09435
1111113.256-2.25603
1121315.2347-2.2347
1131412.06751.9325
1141813.9854.01498
1151615.6720.328037
1161412.92971.07025
1171413.64490.355117
1181415.0658-1.06578
1191413.6460.354019
1201212.4453-0.445268
1211413.68710.312933
1221514.77640.223561
1231515.9473-0.947326
1241514.63050.369532
1251314.8789-1.87889
1261716.18330.816694
1271715.28191.71812
1281914.84374.15627
1291513.50681.49324
1301314.7205-1.72048
131910.4831-1.48313
1321515.2521-0.252054
1331512.5862.41396
1341514.16350.836497
1351613.78672.21329
136119.435651.56435
1371413.27340.726623
1381111.8357-0.835748
1391514.09160.908386
1401313.7069-0.706901
1411514.7090.290984
1421613.78142.21862
1431414.7854-0.785377
1441514.47830.521682
1451614.4441.55602
1461614.68041.31959
1471113.3363-2.33629
1481214.8027-2.80273
149911.3952-2.39515
1501613.97792.02209
1511312.50580.494224
1521615.4820.517977
1531214.3907-2.39074
154911.4257-2.42575
1551311.54021.45981
1561312.89670.103332
1571413.20760.792377
1581914.84374.15627
1591315.7768-2.77677
1601211.91970.0802586
1611312.440.560018
162109.335160.664844
1631413.35980.640187
1641611.67524.32478
1651011.9811-1.98106
166119.084911.91509
1671414.264-0.264039
1681213.0512-1.05122
169912.7225-3.72254
170912.1114-3.11143
1711110.49790.502126
1721614.35421.64583
173914.0322-5.03224
1741311.35651.64353
1751613.50072.49933
1761315.5162-2.51616
177912.2974-3.29743
1781211.55950.440509
1791614.76591.23413
1801113.1884-2.18845
1811414.3069-0.306911
1821314.8111-1.81114
1831515.0232-0.0232268
1841415.1796-1.17956
1851614.18171.81829
1861311.80451.19547
1871413.7710.229019
1881514.2630.736978
1891312.60950.390517
1901110.14290.857135
1911112.9358-1.9358
1921415.1805-1.18045
1931512.72922.27076
1941112.6133-1.61326
1951513.25411.74592
1961214.188-2.18801
1971411.89362.10635
1981413.57510.42485
199811.2544-3.25438
2001314.0945-1.0945
201912.3947-3.39471
2021514.05760.94236
2031714.22632.77371
2041312.6980.302046
2051514.63730.362668
2061513.91081.08918
2071414.6672-0.667201
2081612.74883.25121
2091312.9690.0310352
2101614.53071.46926
211911.8009-2.80088
2121614.53941.46056
2131112.3291-1.32912
2141014.0472-4.04715
2151112.3475-1.34749
2161513.58551.41453
2171715.16391.83613
2181414.3882-0.388185
21989.98475-1.98475
2201513.71591.28412
2211114.0918-3.09178
2221613.79792.20207
2231012.3466-2.3466
2241515.0299-0.0298536
22599.81334-0.813338
2261614.33631.6637
2271914.08124.91879
2281213.9221-1.92207
22989.48109-1.48109
2301113.4717-2.47173
2311414.0103-0.0102953
232912.0237-3.02374
2331515.1934-0.193372
2341312.69120.308757
2351615.14270.857296
2361112.969-1.96896
2371211.16920.830785
2381313.1002-0.100183
2391014.7319-4.7319
2401113.671-2.67098
2411215.036-3.03599
242810.7918-2.79181
2431211.85390.146092
2441212.3813-0.381341
2451513.72811.27193
2461110.81010.189865
2471312.90690.0930524
248148.842715.15729
2491010.5032-0.5032
2501211.93720.0628232
2511512.98722.01275
2521311.9241.07599
2531314.2691-1.26908
2541313.9947-0.99473
2551211.90750.0924882
2561212.8711-0.871148
257911.0255-2.02547
258911.6382-2.6382
2591512.75222.2478
2601014.7523-4.7523
2611414.0524-0.0524386
2621513.6651.33499
26379.77656-2.77656
2641414.1346-0.134566






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.8838790.2322430.116121
90.7930530.4138950.206947
100.6875460.6249080.312454
110.6754440.6491120.324556
120.9503910.09921730.0496086
130.9865660.02686830.0134341
140.9831990.03360220.0168011
150.9815070.03698540.0184927
160.9710950.05781010.028905
170.9589190.08216280.0410814
180.9458810.1082380.0541192
190.9281930.1436150.0718074
200.9165230.1669540.0834771
210.9210380.1579240.0789622
220.956340.08731970.0436598
230.939160.121680.0608401
240.9343740.1312510.0656256
250.9166090.1667810.0833906
260.9965640.006871310.00343566
270.9949710.01005860.00502931
280.9926380.01472460.00736232
290.9894550.02108990.0105449
300.9942090.01158190.00579097
310.9915680.01686340.00843172
320.9883450.02330960.0116548
330.9867840.02643210.013216
340.9819590.03608290.0180414
350.9762920.04741570.0237079
360.9682820.06343520.0317176
370.9772460.04550720.0227536
380.9699950.06000980.0300049
390.9651550.06968910.0348445
400.9659050.06818930.0340947
410.9566050.08678950.0433947
420.9540420.09191540.0459577
430.9419760.1160470.0580237
440.931960.1360790.0680397
450.9153620.1692760.0846381
460.928070.143860.0719299
470.9106640.1786730.0893364
480.8906580.2186830.109342
490.9123680.1752640.087632
500.9078240.1843520.0921759
510.8911220.2177560.108878
520.8696010.2607970.130399
530.8513020.2973970.148698
540.8412910.3174180.158709
550.8306190.3387620.169381
560.8093370.3813270.190663
570.7955650.408870.204435
580.7640430.4719140.235957
590.8051190.3897630.194881
600.8002650.399470.199735
610.8232810.3534390.176719
620.818970.3620610.18103
630.8802620.2394760.119738
640.8663150.267370.133685
650.8546320.2907370.145368
660.9446560.1106890.0553444
670.9428870.1142270.0571134
680.9510230.09795370.0489769
690.9473850.105230.0526149
700.9407470.1185060.0592529
710.9295530.1408940.070447
720.9468540.1062920.053146
730.9360170.1279650.0639827
740.9228520.1542970.0771485
750.9220810.1558390.0779193
760.9079520.1840960.0920479
770.9238650.152270.0761349
780.9097240.1805510.0902756
790.8979980.2040030.102002
800.8959140.2081720.104086
810.8775370.2449270.122463
820.8576310.2847390.142369
830.8499970.3000060.150003
840.8294210.3411590.170579
850.8045840.3908320.195416
860.7844690.4310630.215531
870.7566070.4867870.243393
880.7265050.5469910.273495
890.8024460.3951080.197554
900.8395530.3208930.160447
910.8158880.3682230.184112
920.794530.4109410.20547
930.768970.4620610.23103
940.7498880.5002240.250112
950.7272110.5455770.272789
960.7017170.5965650.298283
970.676370.6472610.32363
980.6760510.6478970.323949
990.6425460.7149090.357454
1000.6358350.728330.364165
1010.6095540.7808910.390446
1020.582080.8358410.41792
1030.6503390.6993220.349661
1040.6447340.7105320.355266
1050.6614840.6770330.338516
1060.6370160.7259670.362984
1070.6399350.720130.360065
1080.6685710.6628580.331429
1090.6446330.7107350.355367
1100.6191860.7616270.380814
1110.6291940.7416120.370806
1120.6388040.7223920.361196
1130.6349750.7300490.365025
1140.7188370.5623260.281163
1150.6890780.6218450.310922
1160.6659750.668050.334025
1170.6336330.7327340.366367
1180.6104280.7791450.389572
1190.5768280.8463430.423172
1200.5444780.9110440.455522
1210.5100710.9798580.489929
1220.4753540.9507070.524646
1230.4461770.8923540.553823
1240.4126720.8253440.587328
1250.4057560.8115130.594244
1260.376730.7534590.62327
1270.3691440.7382880.630856
1280.4761620.9523240.523838
1290.4579750.9159510.542025
1300.4484440.8968890.551556
1310.4399580.8799150.560042
1320.4068970.8137950.593103
1330.4183690.8367370.581631
1340.390440.7808790.60956
1350.3978020.7956050.602198
1360.3800060.7600120.619994
1370.3516060.7032120.648394
1380.3271990.6543990.672801
1390.3012490.6024980.698751
1400.2770520.5541050.722948
1410.2490740.4981470.750926
1420.2537720.5075450.746228
1430.2288580.4577160.771142
1440.2056070.4112150.794393
1450.1938920.3877840.806108
1460.1843040.3686080.815696
1470.1916060.3832110.808394
1480.2109170.4218340.789083
1490.228280.4565590.77172
1500.2267360.4534720.773264
1510.203260.4065190.79674
1520.181650.36330.81835
1530.192830.3856610.80717
1540.2070980.4141960.792902
1550.1945030.3890050.805497
1560.1710330.3420660.828967
1570.1523430.3046860.847657
1580.2398390.4796780.760161
1590.2581720.5163440.741828
1600.2325970.4651930.767403
1610.2086760.4173510.791324
1620.1865480.3730970.813452
1630.1678120.3356250.832188
1640.2875050.575010.712495
1650.2828930.5657860.717107
1660.2788740.5577480.721126
1670.2501840.5003680.749816
1680.2292770.4585540.770723
1690.2894220.5788440.710578
1700.3232360.6464720.676764
1710.2936950.587390.706305
1720.2879260.5758510.712074
1730.4608440.9216880.539156
1740.4483940.8967890.551606
1750.4737580.9475160.526242
1760.4885930.9771870.511407
1770.5457250.908550.454275
1780.5126130.9747740.487387
1790.4901970.9803930.509803
1800.4917810.9835620.508219
1810.4541810.9083630.545819
1820.4477520.8955040.552248
1830.4099950.819990.590005
1840.3822530.7645060.617747
1850.3870680.7741370.612932
1860.3747110.7494220.625289
1870.3403520.6807030.659648
1880.3147680.6295360.685232
1890.2812140.5624290.718786
1900.2583730.5167460.741627
1910.269370.538740.73063
1920.2465940.4931880.753406
1930.2680430.5360870.731957
1940.2542870.5085740.745713
1950.2525190.5050380.747481
1960.2589450.5178890.741055
1970.3058650.611730.694135
1980.286890.573780.71311
1990.3233850.6467710.676615
2000.2929860.5859710.707014
2010.3450390.6900780.654961
2020.3145770.6291550.685423
2030.360280.7205610.63972
2040.322550.6450990.67745
2050.2885890.5771780.711411
2060.2681060.5362120.731894
2070.2352820.4705630.764718
2080.2682910.5365830.731709
2090.2344520.4689040.765548
2100.2423510.4847020.757649
2110.2731420.5462840.726858
2120.2718250.543650.728175
2130.2416490.4832990.758351
2140.3001890.6003780.699811
2150.2718480.5436960.728152
2160.2537730.5075460.746227
2170.2878880.5757750.712112
2180.2559230.5118460.744077
2190.2408810.4817610.759119
2200.2618540.5237090.738146
2210.2772890.5545770.722711
2220.2752490.5504980.724751
2230.2612690.5225370.738731
2240.2241660.4483310.775834
2250.2208870.4417740.779113
2260.25430.50860.7457
2270.467560.935120.53244
2280.4422720.8845440.557728
2290.4168860.8337730.583114
2300.405350.81070.59465
2310.3660890.7321790.633911
2320.4189140.8378290.581086
2330.3773660.7547310.622634
2340.3290960.6581920.670904
2350.3325750.6651510.667425
2360.3086730.6173460.691327
2370.2678670.5357330.732133
2380.2221070.4442140.777893
2390.3918380.7836760.608162
2400.3781580.7563160.621842
2410.3520170.7040340.647983
2420.5838130.8323740.416187
2430.5462140.9075710.453786
2440.4931770.9863530.506823
2450.5503170.8993670.449683
2460.491990.983980.50801
2470.4219820.8439630.578018
2480.6242850.7514290.375715
2490.5378520.9242950.462148
2500.4417490.8834980.558251
2510.6505650.698870.349435
2520.9202970.1594060.0797031
2530.8911070.2177860.108893
2540.8257910.3484170.174209
2550.7347170.5305650.265283
2560.6256410.7487180.374359

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.883879 & 0.232243 & 0.116121 \tabularnewline
9 & 0.793053 & 0.413895 & 0.206947 \tabularnewline
10 & 0.687546 & 0.624908 & 0.312454 \tabularnewline
11 & 0.675444 & 0.649112 & 0.324556 \tabularnewline
12 & 0.950391 & 0.0992173 & 0.0496086 \tabularnewline
13 & 0.986566 & 0.0268683 & 0.0134341 \tabularnewline
14 & 0.983199 & 0.0336022 & 0.0168011 \tabularnewline
15 & 0.981507 & 0.0369854 & 0.0184927 \tabularnewline
16 & 0.971095 & 0.0578101 & 0.028905 \tabularnewline
17 & 0.958919 & 0.0821628 & 0.0410814 \tabularnewline
18 & 0.945881 & 0.108238 & 0.0541192 \tabularnewline
19 & 0.928193 & 0.143615 & 0.0718074 \tabularnewline
20 & 0.916523 & 0.166954 & 0.0834771 \tabularnewline
21 & 0.921038 & 0.157924 & 0.0789622 \tabularnewline
22 & 0.95634 & 0.0873197 & 0.0436598 \tabularnewline
23 & 0.93916 & 0.12168 & 0.0608401 \tabularnewline
24 & 0.934374 & 0.131251 & 0.0656256 \tabularnewline
25 & 0.916609 & 0.166781 & 0.0833906 \tabularnewline
26 & 0.996564 & 0.00687131 & 0.00343566 \tabularnewline
27 & 0.994971 & 0.0100586 & 0.00502931 \tabularnewline
28 & 0.992638 & 0.0147246 & 0.00736232 \tabularnewline
29 & 0.989455 & 0.0210899 & 0.0105449 \tabularnewline
30 & 0.994209 & 0.0115819 & 0.00579097 \tabularnewline
31 & 0.991568 & 0.0168634 & 0.00843172 \tabularnewline
32 & 0.988345 & 0.0233096 & 0.0116548 \tabularnewline
33 & 0.986784 & 0.0264321 & 0.013216 \tabularnewline
34 & 0.981959 & 0.0360829 & 0.0180414 \tabularnewline
35 & 0.976292 & 0.0474157 & 0.0237079 \tabularnewline
36 & 0.968282 & 0.0634352 & 0.0317176 \tabularnewline
37 & 0.977246 & 0.0455072 & 0.0227536 \tabularnewline
38 & 0.969995 & 0.0600098 & 0.0300049 \tabularnewline
39 & 0.965155 & 0.0696891 & 0.0348445 \tabularnewline
40 & 0.965905 & 0.0681893 & 0.0340947 \tabularnewline
41 & 0.956605 & 0.0867895 & 0.0433947 \tabularnewline
42 & 0.954042 & 0.0919154 & 0.0459577 \tabularnewline
43 & 0.941976 & 0.116047 & 0.0580237 \tabularnewline
44 & 0.93196 & 0.136079 & 0.0680397 \tabularnewline
45 & 0.915362 & 0.169276 & 0.0846381 \tabularnewline
46 & 0.92807 & 0.14386 & 0.0719299 \tabularnewline
47 & 0.910664 & 0.178673 & 0.0893364 \tabularnewline
48 & 0.890658 & 0.218683 & 0.109342 \tabularnewline
49 & 0.912368 & 0.175264 & 0.087632 \tabularnewline
50 & 0.907824 & 0.184352 & 0.0921759 \tabularnewline
51 & 0.891122 & 0.217756 & 0.108878 \tabularnewline
52 & 0.869601 & 0.260797 & 0.130399 \tabularnewline
53 & 0.851302 & 0.297397 & 0.148698 \tabularnewline
54 & 0.841291 & 0.317418 & 0.158709 \tabularnewline
55 & 0.830619 & 0.338762 & 0.169381 \tabularnewline
56 & 0.809337 & 0.381327 & 0.190663 \tabularnewline
57 & 0.795565 & 0.40887 & 0.204435 \tabularnewline
58 & 0.764043 & 0.471914 & 0.235957 \tabularnewline
59 & 0.805119 & 0.389763 & 0.194881 \tabularnewline
60 & 0.800265 & 0.39947 & 0.199735 \tabularnewline
61 & 0.823281 & 0.353439 & 0.176719 \tabularnewline
62 & 0.81897 & 0.362061 & 0.18103 \tabularnewline
63 & 0.880262 & 0.239476 & 0.119738 \tabularnewline
64 & 0.866315 & 0.26737 & 0.133685 \tabularnewline
65 & 0.854632 & 0.290737 & 0.145368 \tabularnewline
66 & 0.944656 & 0.110689 & 0.0553444 \tabularnewline
67 & 0.942887 & 0.114227 & 0.0571134 \tabularnewline
68 & 0.951023 & 0.0979537 & 0.0489769 \tabularnewline
69 & 0.947385 & 0.10523 & 0.0526149 \tabularnewline
70 & 0.940747 & 0.118506 & 0.0592529 \tabularnewline
71 & 0.929553 & 0.140894 & 0.070447 \tabularnewline
72 & 0.946854 & 0.106292 & 0.053146 \tabularnewline
73 & 0.936017 & 0.127965 & 0.0639827 \tabularnewline
74 & 0.922852 & 0.154297 & 0.0771485 \tabularnewline
75 & 0.922081 & 0.155839 & 0.0779193 \tabularnewline
76 & 0.907952 & 0.184096 & 0.0920479 \tabularnewline
77 & 0.923865 & 0.15227 & 0.0761349 \tabularnewline
78 & 0.909724 & 0.180551 & 0.0902756 \tabularnewline
79 & 0.897998 & 0.204003 & 0.102002 \tabularnewline
80 & 0.895914 & 0.208172 & 0.104086 \tabularnewline
81 & 0.877537 & 0.244927 & 0.122463 \tabularnewline
82 & 0.857631 & 0.284739 & 0.142369 \tabularnewline
83 & 0.849997 & 0.300006 & 0.150003 \tabularnewline
84 & 0.829421 & 0.341159 & 0.170579 \tabularnewline
85 & 0.804584 & 0.390832 & 0.195416 \tabularnewline
86 & 0.784469 & 0.431063 & 0.215531 \tabularnewline
87 & 0.756607 & 0.486787 & 0.243393 \tabularnewline
88 & 0.726505 & 0.546991 & 0.273495 \tabularnewline
89 & 0.802446 & 0.395108 & 0.197554 \tabularnewline
90 & 0.839553 & 0.320893 & 0.160447 \tabularnewline
91 & 0.815888 & 0.368223 & 0.184112 \tabularnewline
92 & 0.79453 & 0.410941 & 0.20547 \tabularnewline
93 & 0.76897 & 0.462061 & 0.23103 \tabularnewline
94 & 0.749888 & 0.500224 & 0.250112 \tabularnewline
95 & 0.727211 & 0.545577 & 0.272789 \tabularnewline
96 & 0.701717 & 0.596565 & 0.298283 \tabularnewline
97 & 0.67637 & 0.647261 & 0.32363 \tabularnewline
98 & 0.676051 & 0.647897 & 0.323949 \tabularnewline
99 & 0.642546 & 0.714909 & 0.357454 \tabularnewline
100 & 0.635835 & 0.72833 & 0.364165 \tabularnewline
101 & 0.609554 & 0.780891 & 0.390446 \tabularnewline
102 & 0.58208 & 0.835841 & 0.41792 \tabularnewline
103 & 0.650339 & 0.699322 & 0.349661 \tabularnewline
104 & 0.644734 & 0.710532 & 0.355266 \tabularnewline
105 & 0.661484 & 0.677033 & 0.338516 \tabularnewline
106 & 0.637016 & 0.725967 & 0.362984 \tabularnewline
107 & 0.639935 & 0.72013 & 0.360065 \tabularnewline
108 & 0.668571 & 0.662858 & 0.331429 \tabularnewline
109 & 0.644633 & 0.710735 & 0.355367 \tabularnewline
110 & 0.619186 & 0.761627 & 0.380814 \tabularnewline
111 & 0.629194 & 0.741612 & 0.370806 \tabularnewline
112 & 0.638804 & 0.722392 & 0.361196 \tabularnewline
113 & 0.634975 & 0.730049 & 0.365025 \tabularnewline
114 & 0.718837 & 0.562326 & 0.281163 \tabularnewline
115 & 0.689078 & 0.621845 & 0.310922 \tabularnewline
116 & 0.665975 & 0.66805 & 0.334025 \tabularnewline
117 & 0.633633 & 0.732734 & 0.366367 \tabularnewline
118 & 0.610428 & 0.779145 & 0.389572 \tabularnewline
119 & 0.576828 & 0.846343 & 0.423172 \tabularnewline
120 & 0.544478 & 0.911044 & 0.455522 \tabularnewline
121 & 0.510071 & 0.979858 & 0.489929 \tabularnewline
122 & 0.475354 & 0.950707 & 0.524646 \tabularnewline
123 & 0.446177 & 0.892354 & 0.553823 \tabularnewline
124 & 0.412672 & 0.825344 & 0.587328 \tabularnewline
125 & 0.405756 & 0.811513 & 0.594244 \tabularnewline
126 & 0.37673 & 0.753459 & 0.62327 \tabularnewline
127 & 0.369144 & 0.738288 & 0.630856 \tabularnewline
128 & 0.476162 & 0.952324 & 0.523838 \tabularnewline
129 & 0.457975 & 0.915951 & 0.542025 \tabularnewline
130 & 0.448444 & 0.896889 & 0.551556 \tabularnewline
131 & 0.439958 & 0.879915 & 0.560042 \tabularnewline
132 & 0.406897 & 0.813795 & 0.593103 \tabularnewline
133 & 0.418369 & 0.836737 & 0.581631 \tabularnewline
134 & 0.39044 & 0.780879 & 0.60956 \tabularnewline
135 & 0.397802 & 0.795605 & 0.602198 \tabularnewline
136 & 0.380006 & 0.760012 & 0.619994 \tabularnewline
137 & 0.351606 & 0.703212 & 0.648394 \tabularnewline
138 & 0.327199 & 0.654399 & 0.672801 \tabularnewline
139 & 0.301249 & 0.602498 & 0.698751 \tabularnewline
140 & 0.277052 & 0.554105 & 0.722948 \tabularnewline
141 & 0.249074 & 0.498147 & 0.750926 \tabularnewline
142 & 0.253772 & 0.507545 & 0.746228 \tabularnewline
143 & 0.228858 & 0.457716 & 0.771142 \tabularnewline
144 & 0.205607 & 0.411215 & 0.794393 \tabularnewline
145 & 0.193892 & 0.387784 & 0.806108 \tabularnewline
146 & 0.184304 & 0.368608 & 0.815696 \tabularnewline
147 & 0.191606 & 0.383211 & 0.808394 \tabularnewline
148 & 0.210917 & 0.421834 & 0.789083 \tabularnewline
149 & 0.22828 & 0.456559 & 0.77172 \tabularnewline
150 & 0.226736 & 0.453472 & 0.773264 \tabularnewline
151 & 0.20326 & 0.406519 & 0.79674 \tabularnewline
152 & 0.18165 & 0.3633 & 0.81835 \tabularnewline
153 & 0.19283 & 0.385661 & 0.80717 \tabularnewline
154 & 0.207098 & 0.414196 & 0.792902 \tabularnewline
155 & 0.194503 & 0.389005 & 0.805497 \tabularnewline
156 & 0.171033 & 0.342066 & 0.828967 \tabularnewline
157 & 0.152343 & 0.304686 & 0.847657 \tabularnewline
158 & 0.239839 & 0.479678 & 0.760161 \tabularnewline
159 & 0.258172 & 0.516344 & 0.741828 \tabularnewline
160 & 0.232597 & 0.465193 & 0.767403 \tabularnewline
161 & 0.208676 & 0.417351 & 0.791324 \tabularnewline
162 & 0.186548 & 0.373097 & 0.813452 \tabularnewline
163 & 0.167812 & 0.335625 & 0.832188 \tabularnewline
164 & 0.287505 & 0.57501 & 0.712495 \tabularnewline
165 & 0.282893 & 0.565786 & 0.717107 \tabularnewline
166 & 0.278874 & 0.557748 & 0.721126 \tabularnewline
167 & 0.250184 & 0.500368 & 0.749816 \tabularnewline
168 & 0.229277 & 0.458554 & 0.770723 \tabularnewline
169 & 0.289422 & 0.578844 & 0.710578 \tabularnewline
170 & 0.323236 & 0.646472 & 0.676764 \tabularnewline
171 & 0.293695 & 0.58739 & 0.706305 \tabularnewline
172 & 0.287926 & 0.575851 & 0.712074 \tabularnewline
173 & 0.460844 & 0.921688 & 0.539156 \tabularnewline
174 & 0.448394 & 0.896789 & 0.551606 \tabularnewline
175 & 0.473758 & 0.947516 & 0.526242 \tabularnewline
176 & 0.488593 & 0.977187 & 0.511407 \tabularnewline
177 & 0.545725 & 0.90855 & 0.454275 \tabularnewline
178 & 0.512613 & 0.974774 & 0.487387 \tabularnewline
179 & 0.490197 & 0.980393 & 0.509803 \tabularnewline
180 & 0.491781 & 0.983562 & 0.508219 \tabularnewline
181 & 0.454181 & 0.908363 & 0.545819 \tabularnewline
182 & 0.447752 & 0.895504 & 0.552248 \tabularnewline
183 & 0.409995 & 0.81999 & 0.590005 \tabularnewline
184 & 0.382253 & 0.764506 & 0.617747 \tabularnewline
185 & 0.387068 & 0.774137 & 0.612932 \tabularnewline
186 & 0.374711 & 0.749422 & 0.625289 \tabularnewline
187 & 0.340352 & 0.680703 & 0.659648 \tabularnewline
188 & 0.314768 & 0.629536 & 0.685232 \tabularnewline
189 & 0.281214 & 0.562429 & 0.718786 \tabularnewline
190 & 0.258373 & 0.516746 & 0.741627 \tabularnewline
191 & 0.26937 & 0.53874 & 0.73063 \tabularnewline
192 & 0.246594 & 0.493188 & 0.753406 \tabularnewline
193 & 0.268043 & 0.536087 & 0.731957 \tabularnewline
194 & 0.254287 & 0.508574 & 0.745713 \tabularnewline
195 & 0.252519 & 0.505038 & 0.747481 \tabularnewline
196 & 0.258945 & 0.517889 & 0.741055 \tabularnewline
197 & 0.305865 & 0.61173 & 0.694135 \tabularnewline
198 & 0.28689 & 0.57378 & 0.71311 \tabularnewline
199 & 0.323385 & 0.646771 & 0.676615 \tabularnewline
200 & 0.292986 & 0.585971 & 0.707014 \tabularnewline
201 & 0.345039 & 0.690078 & 0.654961 \tabularnewline
202 & 0.314577 & 0.629155 & 0.685423 \tabularnewline
203 & 0.36028 & 0.720561 & 0.63972 \tabularnewline
204 & 0.32255 & 0.645099 & 0.67745 \tabularnewline
205 & 0.288589 & 0.577178 & 0.711411 \tabularnewline
206 & 0.268106 & 0.536212 & 0.731894 \tabularnewline
207 & 0.235282 & 0.470563 & 0.764718 \tabularnewline
208 & 0.268291 & 0.536583 & 0.731709 \tabularnewline
209 & 0.234452 & 0.468904 & 0.765548 \tabularnewline
210 & 0.242351 & 0.484702 & 0.757649 \tabularnewline
211 & 0.273142 & 0.546284 & 0.726858 \tabularnewline
212 & 0.271825 & 0.54365 & 0.728175 \tabularnewline
213 & 0.241649 & 0.483299 & 0.758351 \tabularnewline
214 & 0.300189 & 0.600378 & 0.699811 \tabularnewline
215 & 0.271848 & 0.543696 & 0.728152 \tabularnewline
216 & 0.253773 & 0.507546 & 0.746227 \tabularnewline
217 & 0.287888 & 0.575775 & 0.712112 \tabularnewline
218 & 0.255923 & 0.511846 & 0.744077 \tabularnewline
219 & 0.240881 & 0.481761 & 0.759119 \tabularnewline
220 & 0.261854 & 0.523709 & 0.738146 \tabularnewline
221 & 0.277289 & 0.554577 & 0.722711 \tabularnewline
222 & 0.275249 & 0.550498 & 0.724751 \tabularnewline
223 & 0.261269 & 0.522537 & 0.738731 \tabularnewline
224 & 0.224166 & 0.448331 & 0.775834 \tabularnewline
225 & 0.220887 & 0.441774 & 0.779113 \tabularnewline
226 & 0.2543 & 0.5086 & 0.7457 \tabularnewline
227 & 0.46756 & 0.93512 & 0.53244 \tabularnewline
228 & 0.442272 & 0.884544 & 0.557728 \tabularnewline
229 & 0.416886 & 0.833773 & 0.583114 \tabularnewline
230 & 0.40535 & 0.8107 & 0.59465 \tabularnewline
231 & 0.366089 & 0.732179 & 0.633911 \tabularnewline
232 & 0.418914 & 0.837829 & 0.581086 \tabularnewline
233 & 0.377366 & 0.754731 & 0.622634 \tabularnewline
234 & 0.329096 & 0.658192 & 0.670904 \tabularnewline
235 & 0.332575 & 0.665151 & 0.667425 \tabularnewline
236 & 0.308673 & 0.617346 & 0.691327 \tabularnewline
237 & 0.267867 & 0.535733 & 0.732133 \tabularnewline
238 & 0.222107 & 0.444214 & 0.777893 \tabularnewline
239 & 0.391838 & 0.783676 & 0.608162 \tabularnewline
240 & 0.378158 & 0.756316 & 0.621842 \tabularnewline
241 & 0.352017 & 0.704034 & 0.647983 \tabularnewline
242 & 0.583813 & 0.832374 & 0.416187 \tabularnewline
243 & 0.546214 & 0.907571 & 0.453786 \tabularnewline
244 & 0.493177 & 0.986353 & 0.506823 \tabularnewline
245 & 0.550317 & 0.899367 & 0.449683 \tabularnewline
246 & 0.49199 & 0.98398 & 0.50801 \tabularnewline
247 & 0.421982 & 0.843963 & 0.578018 \tabularnewline
248 & 0.624285 & 0.751429 & 0.375715 \tabularnewline
249 & 0.537852 & 0.924295 & 0.462148 \tabularnewline
250 & 0.441749 & 0.883498 & 0.558251 \tabularnewline
251 & 0.650565 & 0.69887 & 0.349435 \tabularnewline
252 & 0.920297 & 0.159406 & 0.0797031 \tabularnewline
253 & 0.891107 & 0.217786 & 0.108893 \tabularnewline
254 & 0.825791 & 0.348417 & 0.174209 \tabularnewline
255 & 0.734717 & 0.530565 & 0.265283 \tabularnewline
256 & 0.625641 & 0.748718 & 0.374359 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226595&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]8[/C][C]0.883879[/C][C]0.232243[/C][C]0.116121[/C][/ROW]
[ROW][C]9[/C][C]0.793053[/C][C]0.413895[/C][C]0.206947[/C][/ROW]
[ROW][C]10[/C][C]0.687546[/C][C]0.624908[/C][C]0.312454[/C][/ROW]
[ROW][C]11[/C][C]0.675444[/C][C]0.649112[/C][C]0.324556[/C][/ROW]
[ROW][C]12[/C][C]0.950391[/C][C]0.0992173[/C][C]0.0496086[/C][/ROW]
[ROW][C]13[/C][C]0.986566[/C][C]0.0268683[/C][C]0.0134341[/C][/ROW]
[ROW][C]14[/C][C]0.983199[/C][C]0.0336022[/C][C]0.0168011[/C][/ROW]
[ROW][C]15[/C][C]0.981507[/C][C]0.0369854[/C][C]0.0184927[/C][/ROW]
[ROW][C]16[/C][C]0.971095[/C][C]0.0578101[/C][C]0.028905[/C][/ROW]
[ROW][C]17[/C][C]0.958919[/C][C]0.0821628[/C][C]0.0410814[/C][/ROW]
[ROW][C]18[/C][C]0.945881[/C][C]0.108238[/C][C]0.0541192[/C][/ROW]
[ROW][C]19[/C][C]0.928193[/C][C]0.143615[/C][C]0.0718074[/C][/ROW]
[ROW][C]20[/C][C]0.916523[/C][C]0.166954[/C][C]0.0834771[/C][/ROW]
[ROW][C]21[/C][C]0.921038[/C][C]0.157924[/C][C]0.0789622[/C][/ROW]
[ROW][C]22[/C][C]0.95634[/C][C]0.0873197[/C][C]0.0436598[/C][/ROW]
[ROW][C]23[/C][C]0.93916[/C][C]0.12168[/C][C]0.0608401[/C][/ROW]
[ROW][C]24[/C][C]0.934374[/C][C]0.131251[/C][C]0.0656256[/C][/ROW]
[ROW][C]25[/C][C]0.916609[/C][C]0.166781[/C][C]0.0833906[/C][/ROW]
[ROW][C]26[/C][C]0.996564[/C][C]0.00687131[/C][C]0.00343566[/C][/ROW]
[ROW][C]27[/C][C]0.994971[/C][C]0.0100586[/C][C]0.00502931[/C][/ROW]
[ROW][C]28[/C][C]0.992638[/C][C]0.0147246[/C][C]0.00736232[/C][/ROW]
[ROW][C]29[/C][C]0.989455[/C][C]0.0210899[/C][C]0.0105449[/C][/ROW]
[ROW][C]30[/C][C]0.994209[/C][C]0.0115819[/C][C]0.00579097[/C][/ROW]
[ROW][C]31[/C][C]0.991568[/C][C]0.0168634[/C][C]0.00843172[/C][/ROW]
[ROW][C]32[/C][C]0.988345[/C][C]0.0233096[/C][C]0.0116548[/C][/ROW]
[ROW][C]33[/C][C]0.986784[/C][C]0.0264321[/C][C]0.013216[/C][/ROW]
[ROW][C]34[/C][C]0.981959[/C][C]0.0360829[/C][C]0.0180414[/C][/ROW]
[ROW][C]35[/C][C]0.976292[/C][C]0.0474157[/C][C]0.0237079[/C][/ROW]
[ROW][C]36[/C][C]0.968282[/C][C]0.0634352[/C][C]0.0317176[/C][/ROW]
[ROW][C]37[/C][C]0.977246[/C][C]0.0455072[/C][C]0.0227536[/C][/ROW]
[ROW][C]38[/C][C]0.969995[/C][C]0.0600098[/C][C]0.0300049[/C][/ROW]
[ROW][C]39[/C][C]0.965155[/C][C]0.0696891[/C][C]0.0348445[/C][/ROW]
[ROW][C]40[/C][C]0.965905[/C][C]0.0681893[/C][C]0.0340947[/C][/ROW]
[ROW][C]41[/C][C]0.956605[/C][C]0.0867895[/C][C]0.0433947[/C][/ROW]
[ROW][C]42[/C][C]0.954042[/C][C]0.0919154[/C][C]0.0459577[/C][/ROW]
[ROW][C]43[/C][C]0.941976[/C][C]0.116047[/C][C]0.0580237[/C][/ROW]
[ROW][C]44[/C][C]0.93196[/C][C]0.136079[/C][C]0.0680397[/C][/ROW]
[ROW][C]45[/C][C]0.915362[/C][C]0.169276[/C][C]0.0846381[/C][/ROW]
[ROW][C]46[/C][C]0.92807[/C][C]0.14386[/C][C]0.0719299[/C][/ROW]
[ROW][C]47[/C][C]0.910664[/C][C]0.178673[/C][C]0.0893364[/C][/ROW]
[ROW][C]48[/C][C]0.890658[/C][C]0.218683[/C][C]0.109342[/C][/ROW]
[ROW][C]49[/C][C]0.912368[/C][C]0.175264[/C][C]0.087632[/C][/ROW]
[ROW][C]50[/C][C]0.907824[/C][C]0.184352[/C][C]0.0921759[/C][/ROW]
[ROW][C]51[/C][C]0.891122[/C][C]0.217756[/C][C]0.108878[/C][/ROW]
[ROW][C]52[/C][C]0.869601[/C][C]0.260797[/C][C]0.130399[/C][/ROW]
[ROW][C]53[/C][C]0.851302[/C][C]0.297397[/C][C]0.148698[/C][/ROW]
[ROW][C]54[/C][C]0.841291[/C][C]0.317418[/C][C]0.158709[/C][/ROW]
[ROW][C]55[/C][C]0.830619[/C][C]0.338762[/C][C]0.169381[/C][/ROW]
[ROW][C]56[/C][C]0.809337[/C][C]0.381327[/C][C]0.190663[/C][/ROW]
[ROW][C]57[/C][C]0.795565[/C][C]0.40887[/C][C]0.204435[/C][/ROW]
[ROW][C]58[/C][C]0.764043[/C][C]0.471914[/C][C]0.235957[/C][/ROW]
[ROW][C]59[/C][C]0.805119[/C][C]0.389763[/C][C]0.194881[/C][/ROW]
[ROW][C]60[/C][C]0.800265[/C][C]0.39947[/C][C]0.199735[/C][/ROW]
[ROW][C]61[/C][C]0.823281[/C][C]0.353439[/C][C]0.176719[/C][/ROW]
[ROW][C]62[/C][C]0.81897[/C][C]0.362061[/C][C]0.18103[/C][/ROW]
[ROW][C]63[/C][C]0.880262[/C][C]0.239476[/C][C]0.119738[/C][/ROW]
[ROW][C]64[/C][C]0.866315[/C][C]0.26737[/C][C]0.133685[/C][/ROW]
[ROW][C]65[/C][C]0.854632[/C][C]0.290737[/C][C]0.145368[/C][/ROW]
[ROW][C]66[/C][C]0.944656[/C][C]0.110689[/C][C]0.0553444[/C][/ROW]
[ROW][C]67[/C][C]0.942887[/C][C]0.114227[/C][C]0.0571134[/C][/ROW]
[ROW][C]68[/C][C]0.951023[/C][C]0.0979537[/C][C]0.0489769[/C][/ROW]
[ROW][C]69[/C][C]0.947385[/C][C]0.10523[/C][C]0.0526149[/C][/ROW]
[ROW][C]70[/C][C]0.940747[/C][C]0.118506[/C][C]0.0592529[/C][/ROW]
[ROW][C]71[/C][C]0.929553[/C][C]0.140894[/C][C]0.070447[/C][/ROW]
[ROW][C]72[/C][C]0.946854[/C][C]0.106292[/C][C]0.053146[/C][/ROW]
[ROW][C]73[/C][C]0.936017[/C][C]0.127965[/C][C]0.0639827[/C][/ROW]
[ROW][C]74[/C][C]0.922852[/C][C]0.154297[/C][C]0.0771485[/C][/ROW]
[ROW][C]75[/C][C]0.922081[/C][C]0.155839[/C][C]0.0779193[/C][/ROW]
[ROW][C]76[/C][C]0.907952[/C][C]0.184096[/C][C]0.0920479[/C][/ROW]
[ROW][C]77[/C][C]0.923865[/C][C]0.15227[/C][C]0.0761349[/C][/ROW]
[ROW][C]78[/C][C]0.909724[/C][C]0.180551[/C][C]0.0902756[/C][/ROW]
[ROW][C]79[/C][C]0.897998[/C][C]0.204003[/C][C]0.102002[/C][/ROW]
[ROW][C]80[/C][C]0.895914[/C][C]0.208172[/C][C]0.104086[/C][/ROW]
[ROW][C]81[/C][C]0.877537[/C][C]0.244927[/C][C]0.122463[/C][/ROW]
[ROW][C]82[/C][C]0.857631[/C][C]0.284739[/C][C]0.142369[/C][/ROW]
[ROW][C]83[/C][C]0.849997[/C][C]0.300006[/C][C]0.150003[/C][/ROW]
[ROW][C]84[/C][C]0.829421[/C][C]0.341159[/C][C]0.170579[/C][/ROW]
[ROW][C]85[/C][C]0.804584[/C][C]0.390832[/C][C]0.195416[/C][/ROW]
[ROW][C]86[/C][C]0.784469[/C][C]0.431063[/C][C]0.215531[/C][/ROW]
[ROW][C]87[/C][C]0.756607[/C][C]0.486787[/C][C]0.243393[/C][/ROW]
[ROW][C]88[/C][C]0.726505[/C][C]0.546991[/C][C]0.273495[/C][/ROW]
[ROW][C]89[/C][C]0.802446[/C][C]0.395108[/C][C]0.197554[/C][/ROW]
[ROW][C]90[/C][C]0.839553[/C][C]0.320893[/C][C]0.160447[/C][/ROW]
[ROW][C]91[/C][C]0.815888[/C][C]0.368223[/C][C]0.184112[/C][/ROW]
[ROW][C]92[/C][C]0.79453[/C][C]0.410941[/C][C]0.20547[/C][/ROW]
[ROW][C]93[/C][C]0.76897[/C][C]0.462061[/C][C]0.23103[/C][/ROW]
[ROW][C]94[/C][C]0.749888[/C][C]0.500224[/C][C]0.250112[/C][/ROW]
[ROW][C]95[/C][C]0.727211[/C][C]0.545577[/C][C]0.272789[/C][/ROW]
[ROW][C]96[/C][C]0.701717[/C][C]0.596565[/C][C]0.298283[/C][/ROW]
[ROW][C]97[/C][C]0.67637[/C][C]0.647261[/C][C]0.32363[/C][/ROW]
[ROW][C]98[/C][C]0.676051[/C][C]0.647897[/C][C]0.323949[/C][/ROW]
[ROW][C]99[/C][C]0.642546[/C][C]0.714909[/C][C]0.357454[/C][/ROW]
[ROW][C]100[/C][C]0.635835[/C][C]0.72833[/C][C]0.364165[/C][/ROW]
[ROW][C]101[/C][C]0.609554[/C][C]0.780891[/C][C]0.390446[/C][/ROW]
[ROW][C]102[/C][C]0.58208[/C][C]0.835841[/C][C]0.41792[/C][/ROW]
[ROW][C]103[/C][C]0.650339[/C][C]0.699322[/C][C]0.349661[/C][/ROW]
[ROW][C]104[/C][C]0.644734[/C][C]0.710532[/C][C]0.355266[/C][/ROW]
[ROW][C]105[/C][C]0.661484[/C][C]0.677033[/C][C]0.338516[/C][/ROW]
[ROW][C]106[/C][C]0.637016[/C][C]0.725967[/C][C]0.362984[/C][/ROW]
[ROW][C]107[/C][C]0.639935[/C][C]0.72013[/C][C]0.360065[/C][/ROW]
[ROW][C]108[/C][C]0.668571[/C][C]0.662858[/C][C]0.331429[/C][/ROW]
[ROW][C]109[/C][C]0.644633[/C][C]0.710735[/C][C]0.355367[/C][/ROW]
[ROW][C]110[/C][C]0.619186[/C][C]0.761627[/C][C]0.380814[/C][/ROW]
[ROW][C]111[/C][C]0.629194[/C][C]0.741612[/C][C]0.370806[/C][/ROW]
[ROW][C]112[/C][C]0.638804[/C][C]0.722392[/C][C]0.361196[/C][/ROW]
[ROW][C]113[/C][C]0.634975[/C][C]0.730049[/C][C]0.365025[/C][/ROW]
[ROW][C]114[/C][C]0.718837[/C][C]0.562326[/C][C]0.281163[/C][/ROW]
[ROW][C]115[/C][C]0.689078[/C][C]0.621845[/C][C]0.310922[/C][/ROW]
[ROW][C]116[/C][C]0.665975[/C][C]0.66805[/C][C]0.334025[/C][/ROW]
[ROW][C]117[/C][C]0.633633[/C][C]0.732734[/C][C]0.366367[/C][/ROW]
[ROW][C]118[/C][C]0.610428[/C][C]0.779145[/C][C]0.389572[/C][/ROW]
[ROW][C]119[/C][C]0.576828[/C][C]0.846343[/C][C]0.423172[/C][/ROW]
[ROW][C]120[/C][C]0.544478[/C][C]0.911044[/C][C]0.455522[/C][/ROW]
[ROW][C]121[/C][C]0.510071[/C][C]0.979858[/C][C]0.489929[/C][/ROW]
[ROW][C]122[/C][C]0.475354[/C][C]0.950707[/C][C]0.524646[/C][/ROW]
[ROW][C]123[/C][C]0.446177[/C][C]0.892354[/C][C]0.553823[/C][/ROW]
[ROW][C]124[/C][C]0.412672[/C][C]0.825344[/C][C]0.587328[/C][/ROW]
[ROW][C]125[/C][C]0.405756[/C][C]0.811513[/C][C]0.594244[/C][/ROW]
[ROW][C]126[/C][C]0.37673[/C][C]0.753459[/C][C]0.62327[/C][/ROW]
[ROW][C]127[/C][C]0.369144[/C][C]0.738288[/C][C]0.630856[/C][/ROW]
[ROW][C]128[/C][C]0.476162[/C][C]0.952324[/C][C]0.523838[/C][/ROW]
[ROW][C]129[/C][C]0.457975[/C][C]0.915951[/C][C]0.542025[/C][/ROW]
[ROW][C]130[/C][C]0.448444[/C][C]0.896889[/C][C]0.551556[/C][/ROW]
[ROW][C]131[/C][C]0.439958[/C][C]0.879915[/C][C]0.560042[/C][/ROW]
[ROW][C]132[/C][C]0.406897[/C][C]0.813795[/C][C]0.593103[/C][/ROW]
[ROW][C]133[/C][C]0.418369[/C][C]0.836737[/C][C]0.581631[/C][/ROW]
[ROW][C]134[/C][C]0.39044[/C][C]0.780879[/C][C]0.60956[/C][/ROW]
[ROW][C]135[/C][C]0.397802[/C][C]0.795605[/C][C]0.602198[/C][/ROW]
[ROW][C]136[/C][C]0.380006[/C][C]0.760012[/C][C]0.619994[/C][/ROW]
[ROW][C]137[/C][C]0.351606[/C][C]0.703212[/C][C]0.648394[/C][/ROW]
[ROW][C]138[/C][C]0.327199[/C][C]0.654399[/C][C]0.672801[/C][/ROW]
[ROW][C]139[/C][C]0.301249[/C][C]0.602498[/C][C]0.698751[/C][/ROW]
[ROW][C]140[/C][C]0.277052[/C][C]0.554105[/C][C]0.722948[/C][/ROW]
[ROW][C]141[/C][C]0.249074[/C][C]0.498147[/C][C]0.750926[/C][/ROW]
[ROW][C]142[/C][C]0.253772[/C][C]0.507545[/C][C]0.746228[/C][/ROW]
[ROW][C]143[/C][C]0.228858[/C][C]0.457716[/C][C]0.771142[/C][/ROW]
[ROW][C]144[/C][C]0.205607[/C][C]0.411215[/C][C]0.794393[/C][/ROW]
[ROW][C]145[/C][C]0.193892[/C][C]0.387784[/C][C]0.806108[/C][/ROW]
[ROW][C]146[/C][C]0.184304[/C][C]0.368608[/C][C]0.815696[/C][/ROW]
[ROW][C]147[/C][C]0.191606[/C][C]0.383211[/C][C]0.808394[/C][/ROW]
[ROW][C]148[/C][C]0.210917[/C][C]0.421834[/C][C]0.789083[/C][/ROW]
[ROW][C]149[/C][C]0.22828[/C][C]0.456559[/C][C]0.77172[/C][/ROW]
[ROW][C]150[/C][C]0.226736[/C][C]0.453472[/C][C]0.773264[/C][/ROW]
[ROW][C]151[/C][C]0.20326[/C][C]0.406519[/C][C]0.79674[/C][/ROW]
[ROW][C]152[/C][C]0.18165[/C][C]0.3633[/C][C]0.81835[/C][/ROW]
[ROW][C]153[/C][C]0.19283[/C][C]0.385661[/C][C]0.80717[/C][/ROW]
[ROW][C]154[/C][C]0.207098[/C][C]0.414196[/C][C]0.792902[/C][/ROW]
[ROW][C]155[/C][C]0.194503[/C][C]0.389005[/C][C]0.805497[/C][/ROW]
[ROW][C]156[/C][C]0.171033[/C][C]0.342066[/C][C]0.828967[/C][/ROW]
[ROW][C]157[/C][C]0.152343[/C][C]0.304686[/C][C]0.847657[/C][/ROW]
[ROW][C]158[/C][C]0.239839[/C][C]0.479678[/C][C]0.760161[/C][/ROW]
[ROW][C]159[/C][C]0.258172[/C][C]0.516344[/C][C]0.741828[/C][/ROW]
[ROW][C]160[/C][C]0.232597[/C][C]0.465193[/C][C]0.767403[/C][/ROW]
[ROW][C]161[/C][C]0.208676[/C][C]0.417351[/C][C]0.791324[/C][/ROW]
[ROW][C]162[/C][C]0.186548[/C][C]0.373097[/C][C]0.813452[/C][/ROW]
[ROW][C]163[/C][C]0.167812[/C][C]0.335625[/C][C]0.832188[/C][/ROW]
[ROW][C]164[/C][C]0.287505[/C][C]0.57501[/C][C]0.712495[/C][/ROW]
[ROW][C]165[/C][C]0.282893[/C][C]0.565786[/C][C]0.717107[/C][/ROW]
[ROW][C]166[/C][C]0.278874[/C][C]0.557748[/C][C]0.721126[/C][/ROW]
[ROW][C]167[/C][C]0.250184[/C][C]0.500368[/C][C]0.749816[/C][/ROW]
[ROW][C]168[/C][C]0.229277[/C][C]0.458554[/C][C]0.770723[/C][/ROW]
[ROW][C]169[/C][C]0.289422[/C][C]0.578844[/C][C]0.710578[/C][/ROW]
[ROW][C]170[/C][C]0.323236[/C][C]0.646472[/C][C]0.676764[/C][/ROW]
[ROW][C]171[/C][C]0.293695[/C][C]0.58739[/C][C]0.706305[/C][/ROW]
[ROW][C]172[/C][C]0.287926[/C][C]0.575851[/C][C]0.712074[/C][/ROW]
[ROW][C]173[/C][C]0.460844[/C][C]0.921688[/C][C]0.539156[/C][/ROW]
[ROW][C]174[/C][C]0.448394[/C][C]0.896789[/C][C]0.551606[/C][/ROW]
[ROW][C]175[/C][C]0.473758[/C][C]0.947516[/C][C]0.526242[/C][/ROW]
[ROW][C]176[/C][C]0.488593[/C][C]0.977187[/C][C]0.511407[/C][/ROW]
[ROW][C]177[/C][C]0.545725[/C][C]0.90855[/C][C]0.454275[/C][/ROW]
[ROW][C]178[/C][C]0.512613[/C][C]0.974774[/C][C]0.487387[/C][/ROW]
[ROW][C]179[/C][C]0.490197[/C][C]0.980393[/C][C]0.509803[/C][/ROW]
[ROW][C]180[/C][C]0.491781[/C][C]0.983562[/C][C]0.508219[/C][/ROW]
[ROW][C]181[/C][C]0.454181[/C][C]0.908363[/C][C]0.545819[/C][/ROW]
[ROW][C]182[/C][C]0.447752[/C][C]0.895504[/C][C]0.552248[/C][/ROW]
[ROW][C]183[/C][C]0.409995[/C][C]0.81999[/C][C]0.590005[/C][/ROW]
[ROW][C]184[/C][C]0.382253[/C][C]0.764506[/C][C]0.617747[/C][/ROW]
[ROW][C]185[/C][C]0.387068[/C][C]0.774137[/C][C]0.612932[/C][/ROW]
[ROW][C]186[/C][C]0.374711[/C][C]0.749422[/C][C]0.625289[/C][/ROW]
[ROW][C]187[/C][C]0.340352[/C][C]0.680703[/C][C]0.659648[/C][/ROW]
[ROW][C]188[/C][C]0.314768[/C][C]0.629536[/C][C]0.685232[/C][/ROW]
[ROW][C]189[/C][C]0.281214[/C][C]0.562429[/C][C]0.718786[/C][/ROW]
[ROW][C]190[/C][C]0.258373[/C][C]0.516746[/C][C]0.741627[/C][/ROW]
[ROW][C]191[/C][C]0.26937[/C][C]0.53874[/C][C]0.73063[/C][/ROW]
[ROW][C]192[/C][C]0.246594[/C][C]0.493188[/C][C]0.753406[/C][/ROW]
[ROW][C]193[/C][C]0.268043[/C][C]0.536087[/C][C]0.731957[/C][/ROW]
[ROW][C]194[/C][C]0.254287[/C][C]0.508574[/C][C]0.745713[/C][/ROW]
[ROW][C]195[/C][C]0.252519[/C][C]0.505038[/C][C]0.747481[/C][/ROW]
[ROW][C]196[/C][C]0.258945[/C][C]0.517889[/C][C]0.741055[/C][/ROW]
[ROW][C]197[/C][C]0.305865[/C][C]0.61173[/C][C]0.694135[/C][/ROW]
[ROW][C]198[/C][C]0.28689[/C][C]0.57378[/C][C]0.71311[/C][/ROW]
[ROW][C]199[/C][C]0.323385[/C][C]0.646771[/C][C]0.676615[/C][/ROW]
[ROW][C]200[/C][C]0.292986[/C][C]0.585971[/C][C]0.707014[/C][/ROW]
[ROW][C]201[/C][C]0.345039[/C][C]0.690078[/C][C]0.654961[/C][/ROW]
[ROW][C]202[/C][C]0.314577[/C][C]0.629155[/C][C]0.685423[/C][/ROW]
[ROW][C]203[/C][C]0.36028[/C][C]0.720561[/C][C]0.63972[/C][/ROW]
[ROW][C]204[/C][C]0.32255[/C][C]0.645099[/C][C]0.67745[/C][/ROW]
[ROW][C]205[/C][C]0.288589[/C][C]0.577178[/C][C]0.711411[/C][/ROW]
[ROW][C]206[/C][C]0.268106[/C][C]0.536212[/C][C]0.731894[/C][/ROW]
[ROW][C]207[/C][C]0.235282[/C][C]0.470563[/C][C]0.764718[/C][/ROW]
[ROW][C]208[/C][C]0.268291[/C][C]0.536583[/C][C]0.731709[/C][/ROW]
[ROW][C]209[/C][C]0.234452[/C][C]0.468904[/C][C]0.765548[/C][/ROW]
[ROW][C]210[/C][C]0.242351[/C][C]0.484702[/C][C]0.757649[/C][/ROW]
[ROW][C]211[/C][C]0.273142[/C][C]0.546284[/C][C]0.726858[/C][/ROW]
[ROW][C]212[/C][C]0.271825[/C][C]0.54365[/C][C]0.728175[/C][/ROW]
[ROW][C]213[/C][C]0.241649[/C][C]0.483299[/C][C]0.758351[/C][/ROW]
[ROW][C]214[/C][C]0.300189[/C][C]0.600378[/C][C]0.699811[/C][/ROW]
[ROW][C]215[/C][C]0.271848[/C][C]0.543696[/C][C]0.728152[/C][/ROW]
[ROW][C]216[/C][C]0.253773[/C][C]0.507546[/C][C]0.746227[/C][/ROW]
[ROW][C]217[/C][C]0.287888[/C][C]0.575775[/C][C]0.712112[/C][/ROW]
[ROW][C]218[/C][C]0.255923[/C][C]0.511846[/C][C]0.744077[/C][/ROW]
[ROW][C]219[/C][C]0.240881[/C][C]0.481761[/C][C]0.759119[/C][/ROW]
[ROW][C]220[/C][C]0.261854[/C][C]0.523709[/C][C]0.738146[/C][/ROW]
[ROW][C]221[/C][C]0.277289[/C][C]0.554577[/C][C]0.722711[/C][/ROW]
[ROW][C]222[/C][C]0.275249[/C][C]0.550498[/C][C]0.724751[/C][/ROW]
[ROW][C]223[/C][C]0.261269[/C][C]0.522537[/C][C]0.738731[/C][/ROW]
[ROW][C]224[/C][C]0.224166[/C][C]0.448331[/C][C]0.775834[/C][/ROW]
[ROW][C]225[/C][C]0.220887[/C][C]0.441774[/C][C]0.779113[/C][/ROW]
[ROW][C]226[/C][C]0.2543[/C][C]0.5086[/C][C]0.7457[/C][/ROW]
[ROW][C]227[/C][C]0.46756[/C][C]0.93512[/C][C]0.53244[/C][/ROW]
[ROW][C]228[/C][C]0.442272[/C][C]0.884544[/C][C]0.557728[/C][/ROW]
[ROW][C]229[/C][C]0.416886[/C][C]0.833773[/C][C]0.583114[/C][/ROW]
[ROW][C]230[/C][C]0.40535[/C][C]0.8107[/C][C]0.59465[/C][/ROW]
[ROW][C]231[/C][C]0.366089[/C][C]0.732179[/C][C]0.633911[/C][/ROW]
[ROW][C]232[/C][C]0.418914[/C][C]0.837829[/C][C]0.581086[/C][/ROW]
[ROW][C]233[/C][C]0.377366[/C][C]0.754731[/C][C]0.622634[/C][/ROW]
[ROW][C]234[/C][C]0.329096[/C][C]0.658192[/C][C]0.670904[/C][/ROW]
[ROW][C]235[/C][C]0.332575[/C][C]0.665151[/C][C]0.667425[/C][/ROW]
[ROW][C]236[/C][C]0.308673[/C][C]0.617346[/C][C]0.691327[/C][/ROW]
[ROW][C]237[/C][C]0.267867[/C][C]0.535733[/C][C]0.732133[/C][/ROW]
[ROW][C]238[/C][C]0.222107[/C][C]0.444214[/C][C]0.777893[/C][/ROW]
[ROW][C]239[/C][C]0.391838[/C][C]0.783676[/C][C]0.608162[/C][/ROW]
[ROW][C]240[/C][C]0.378158[/C][C]0.756316[/C][C]0.621842[/C][/ROW]
[ROW][C]241[/C][C]0.352017[/C][C]0.704034[/C][C]0.647983[/C][/ROW]
[ROW][C]242[/C][C]0.583813[/C][C]0.832374[/C][C]0.416187[/C][/ROW]
[ROW][C]243[/C][C]0.546214[/C][C]0.907571[/C][C]0.453786[/C][/ROW]
[ROW][C]244[/C][C]0.493177[/C][C]0.986353[/C][C]0.506823[/C][/ROW]
[ROW][C]245[/C][C]0.550317[/C][C]0.899367[/C][C]0.449683[/C][/ROW]
[ROW][C]246[/C][C]0.49199[/C][C]0.98398[/C][C]0.50801[/C][/ROW]
[ROW][C]247[/C][C]0.421982[/C][C]0.843963[/C][C]0.578018[/C][/ROW]
[ROW][C]248[/C][C]0.624285[/C][C]0.751429[/C][C]0.375715[/C][/ROW]
[ROW][C]249[/C][C]0.537852[/C][C]0.924295[/C][C]0.462148[/C][/ROW]
[ROW][C]250[/C][C]0.441749[/C][C]0.883498[/C][C]0.558251[/C][/ROW]
[ROW][C]251[/C][C]0.650565[/C][C]0.69887[/C][C]0.349435[/C][/ROW]
[ROW][C]252[/C][C]0.920297[/C][C]0.159406[/C][C]0.0797031[/C][/ROW]
[ROW][C]253[/C][C]0.891107[/C][C]0.217786[/C][C]0.108893[/C][/ROW]
[ROW][C]254[/C][C]0.825791[/C][C]0.348417[/C][C]0.174209[/C][/ROW]
[ROW][C]255[/C][C]0.734717[/C][C]0.530565[/C][C]0.265283[/C][/ROW]
[ROW][C]256[/C][C]0.625641[/C][C]0.748718[/C][C]0.374359[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226595&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226595&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.8838790.2322430.116121
90.7930530.4138950.206947
100.6875460.6249080.312454
110.6754440.6491120.324556
120.9503910.09921730.0496086
130.9865660.02686830.0134341
140.9831990.03360220.0168011
150.9815070.03698540.0184927
160.9710950.05781010.028905
170.9589190.08216280.0410814
180.9458810.1082380.0541192
190.9281930.1436150.0718074
200.9165230.1669540.0834771
210.9210380.1579240.0789622
220.956340.08731970.0436598
230.939160.121680.0608401
240.9343740.1312510.0656256
250.9166090.1667810.0833906
260.9965640.006871310.00343566
270.9949710.01005860.00502931
280.9926380.01472460.00736232
290.9894550.02108990.0105449
300.9942090.01158190.00579097
310.9915680.01686340.00843172
320.9883450.02330960.0116548
330.9867840.02643210.013216
340.9819590.03608290.0180414
350.9762920.04741570.0237079
360.9682820.06343520.0317176
370.9772460.04550720.0227536
380.9699950.06000980.0300049
390.9651550.06968910.0348445
400.9659050.06818930.0340947
410.9566050.08678950.0433947
420.9540420.09191540.0459577
430.9419760.1160470.0580237
440.931960.1360790.0680397
450.9153620.1692760.0846381
460.928070.143860.0719299
470.9106640.1786730.0893364
480.8906580.2186830.109342
490.9123680.1752640.087632
500.9078240.1843520.0921759
510.8911220.2177560.108878
520.8696010.2607970.130399
530.8513020.2973970.148698
540.8412910.3174180.158709
550.8306190.3387620.169381
560.8093370.3813270.190663
570.7955650.408870.204435
580.7640430.4719140.235957
590.8051190.3897630.194881
600.8002650.399470.199735
610.8232810.3534390.176719
620.818970.3620610.18103
630.8802620.2394760.119738
640.8663150.267370.133685
650.8546320.2907370.145368
660.9446560.1106890.0553444
670.9428870.1142270.0571134
680.9510230.09795370.0489769
690.9473850.105230.0526149
700.9407470.1185060.0592529
710.9295530.1408940.070447
720.9468540.1062920.053146
730.9360170.1279650.0639827
740.9228520.1542970.0771485
750.9220810.1558390.0779193
760.9079520.1840960.0920479
770.9238650.152270.0761349
780.9097240.1805510.0902756
790.8979980.2040030.102002
800.8959140.2081720.104086
810.8775370.2449270.122463
820.8576310.2847390.142369
830.8499970.3000060.150003
840.8294210.3411590.170579
850.8045840.3908320.195416
860.7844690.4310630.215531
870.7566070.4867870.243393
880.7265050.5469910.273495
890.8024460.3951080.197554
900.8395530.3208930.160447
910.8158880.3682230.184112
920.794530.4109410.20547
930.768970.4620610.23103
940.7498880.5002240.250112
950.7272110.5455770.272789
960.7017170.5965650.298283
970.676370.6472610.32363
980.6760510.6478970.323949
990.6425460.7149090.357454
1000.6358350.728330.364165
1010.6095540.7808910.390446
1020.582080.8358410.41792
1030.6503390.6993220.349661
1040.6447340.7105320.355266
1050.6614840.6770330.338516
1060.6370160.7259670.362984
1070.6399350.720130.360065
1080.6685710.6628580.331429
1090.6446330.7107350.355367
1100.6191860.7616270.380814
1110.6291940.7416120.370806
1120.6388040.7223920.361196
1130.6349750.7300490.365025
1140.7188370.5623260.281163
1150.6890780.6218450.310922
1160.6659750.668050.334025
1170.6336330.7327340.366367
1180.6104280.7791450.389572
1190.5768280.8463430.423172
1200.5444780.9110440.455522
1210.5100710.9798580.489929
1220.4753540.9507070.524646
1230.4461770.8923540.553823
1240.4126720.8253440.587328
1250.4057560.8115130.594244
1260.376730.7534590.62327
1270.3691440.7382880.630856
1280.4761620.9523240.523838
1290.4579750.9159510.542025
1300.4484440.8968890.551556
1310.4399580.8799150.560042
1320.4068970.8137950.593103
1330.4183690.8367370.581631
1340.390440.7808790.60956
1350.3978020.7956050.602198
1360.3800060.7600120.619994
1370.3516060.7032120.648394
1380.3271990.6543990.672801
1390.3012490.6024980.698751
1400.2770520.5541050.722948
1410.2490740.4981470.750926
1420.2537720.5075450.746228
1430.2288580.4577160.771142
1440.2056070.4112150.794393
1450.1938920.3877840.806108
1460.1843040.3686080.815696
1470.1916060.3832110.808394
1480.2109170.4218340.789083
1490.228280.4565590.77172
1500.2267360.4534720.773264
1510.203260.4065190.79674
1520.181650.36330.81835
1530.192830.3856610.80717
1540.2070980.4141960.792902
1550.1945030.3890050.805497
1560.1710330.3420660.828967
1570.1523430.3046860.847657
1580.2398390.4796780.760161
1590.2581720.5163440.741828
1600.2325970.4651930.767403
1610.2086760.4173510.791324
1620.1865480.3730970.813452
1630.1678120.3356250.832188
1640.2875050.575010.712495
1650.2828930.5657860.717107
1660.2788740.5577480.721126
1670.2501840.5003680.749816
1680.2292770.4585540.770723
1690.2894220.5788440.710578
1700.3232360.6464720.676764
1710.2936950.587390.706305
1720.2879260.5758510.712074
1730.4608440.9216880.539156
1740.4483940.8967890.551606
1750.4737580.9475160.526242
1760.4885930.9771870.511407
1770.5457250.908550.454275
1780.5126130.9747740.487387
1790.4901970.9803930.509803
1800.4917810.9835620.508219
1810.4541810.9083630.545819
1820.4477520.8955040.552248
1830.4099950.819990.590005
1840.3822530.7645060.617747
1850.3870680.7741370.612932
1860.3747110.7494220.625289
1870.3403520.6807030.659648
1880.3147680.6295360.685232
1890.2812140.5624290.718786
1900.2583730.5167460.741627
1910.269370.538740.73063
1920.2465940.4931880.753406
1930.2680430.5360870.731957
1940.2542870.5085740.745713
1950.2525190.5050380.747481
1960.2589450.5178890.741055
1970.3058650.611730.694135
1980.286890.573780.71311
1990.3233850.6467710.676615
2000.2929860.5859710.707014
2010.3450390.6900780.654961
2020.3145770.6291550.685423
2030.360280.7205610.63972
2040.322550.6450990.67745
2050.2885890.5771780.711411
2060.2681060.5362120.731894
2070.2352820.4705630.764718
2080.2682910.5365830.731709
2090.2344520.4689040.765548
2100.2423510.4847020.757649
2110.2731420.5462840.726858
2120.2718250.543650.728175
2130.2416490.4832990.758351
2140.3001890.6003780.699811
2150.2718480.5436960.728152
2160.2537730.5075460.746227
2170.2878880.5757750.712112
2180.2559230.5118460.744077
2190.2408810.4817610.759119
2200.2618540.5237090.738146
2210.2772890.5545770.722711
2220.2752490.5504980.724751
2230.2612690.5225370.738731
2240.2241660.4483310.775834
2250.2208870.4417740.779113
2260.25430.50860.7457
2270.467560.935120.53244
2280.4422720.8845440.557728
2290.4168860.8337730.583114
2300.405350.81070.59465
2310.3660890.7321790.633911
2320.4189140.8378290.581086
2330.3773660.7547310.622634
2340.3290960.6581920.670904
2350.3325750.6651510.667425
2360.3086730.6173460.691327
2370.2678670.5357330.732133
2380.2221070.4442140.777893
2390.3918380.7836760.608162
2400.3781580.7563160.621842
2410.3520170.7040340.647983
2420.5838130.8323740.416187
2430.5462140.9075710.453786
2440.4931770.9863530.506823
2450.5503170.8993670.449683
2460.491990.983980.50801
2470.4219820.8439630.578018
2480.6242850.7514290.375715
2490.5378520.9242950.462148
2500.4417490.8834980.558251
2510.6505650.698870.349435
2520.9202970.1594060.0797031
2530.8911070.2177860.108893
2540.8257910.3484170.174209
2550.7347170.5305650.265283
2560.6256410.7487180.374359






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level10.00401606OK
5% type I error level140.0562249NOK
10% type I error level250.100402NOK

\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 & 1 & 0.00401606 & OK \tabularnewline
5% type I error level & 14 & 0.0562249 & NOK \tabularnewline
10% type I error level & 25 & 0.100402 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226595&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]1[/C][C]0.00401606[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]14[/C][C]0.0562249[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]25[/C][C]0.100402[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226595&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226595&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 level10.00401606OK
5% type I error level140.0562249NOK
10% type I error level250.100402NOK


Figures (Output of Computation)

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Input Parameters & R Code

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