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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 14 Dec 2014 22:37:22 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/14/t1418596837kyw8nkqu1c5qcjg.htm/, Retrieved Thu, 16 May 2024 07:14:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267922, Retrieved Thu, 16 May 2024 07:14:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2014-12-11 14:47:08] [6b382800c0d3804662889dbce999b8c7]
- R PD    [Multiple Regression] [] [2014-12-14 22:37:22] [6993448de96b8662e47595bfdf466bf3] [Current]
- R  D      [Multiple Regression] [] [2014-12-14 23:10:45] [6b382800c0d3804662889dbce999b8c7]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1 0 0 1.00 0.50 0.67 0.67 0.00 0.50 12.9
1 0 1 0.89 0.50 0.83 0.33 0.50 1.00 12.2
1 0 0 0.89 0.40 1.00 0.67 0.00 1.00 12.8
1 0 1 0.89 0.50 0.83 0.00 0.00 0.00 7.4
1 0 1 0.89 0.70 0.67 0.00 1.00 1.00 6.7
1 0 1 0.78 0.30 0.00 0.00 0.50 0.50 12.6
1 0 0 0.89 0.40 0.83 0.67 0.50 0.00 14.8
1 0 1 1.00 0.40 0.50 0.67 1.00 1.00 13.3
1 0 1 0.89 0.70 0.83 0.00 0.50 0.00 11.1
1 0 1 0.78 0.60 0.33 0.67 0.50 0.50 8.2
1 0 1 1.00 0.60 0.50 1.00 0.00 0.50 11.4
1 0 1 0.78 0.20 0.67 0.00 0.50 0.50 6.4
1 0 1 0.89 0.40 1.00 0.00 0.50 0.50 10.6
1 0 0 0.89 0.40 0.50 0.67 0.00 1.00 12.0
1 0 0 0.89 0.50 0.67 0.33 0.00 0.00 6.3
1 1 0 0.89 0.30 0.17 0.67 0.00 0.50 11.3
1 0 1 0.89 0.40 0.83 0.33 0.50 0.50 11.9
1 0 0 0.67 0.70 0.67 0.33 0.50 1.00 9.3
1 1 1 1.00 0.50 0.67 0.33 0.00 1.00 9.6
1 0 0 0.78 0.20 0.67 0.00 0.00 1.00 10.0
1 0 1 0.78 0.30 0.50 0.67 0.00 0.50 6.4
1 0 1 0.89 0.60 1.00 0.33 0.00 1.00 13.8
1 0 0 0.78 0.60 0.83 0.33 0.00 1.00 10.8
1 0 1 0.89 0.20 0.83 0.33 0.00 1.00 13.8
1 0 1 0.89 0.70 1.00 0.67 1.00 0.00 11.7
1 0 1 0.33 0.20 0.67 0.00 0.00 0.00 10.9
1 1 1 1.00 1.00 1.00 0.33 1.00 1.00 16.1
1 1 0 0.89 0.40 0.83 0.67 0.00 0.50 13.4
1 0 1 0.89 0.40 1.00 1.00 0.00 1.00 9.9
1 0 0 0.67 0.20 0.83 0.67 0.00 0.50 11.5
1 0 0 0.56 0.40 0.67 0.33 0.00 1.00 8.3
1 0 0 0.89 0.40 0.67 0.00 0.50 1.00 11.7
1 0 1 0.89 0.70 1.00 0.67 0.50 0.50 9.0
1 0 1 1.00 0.20 0.67 0.67 0.00 0.50 9.7
1 0 1 0.78 0.60 1.00 1.00 0.00 0.50 10.8
1 0 1 0.78 0.30 1.00 1.00 0.50 0.50 10.3
1 0 0 0.33 0.30 0.50 0.33 0.00 0.00 10.4
1 1 1 0.78 0.20 0.67 0.00 0.50 0.00 12.7
1 0 1 0.89 0.50 0.83 0.67 0.50 0.50 9.3
1 0 0 0.89 0.70 1.00 0.67 0.50 1.00 11.8
1 0 1 0.78 0.60 1.00 0.67 0.50 0.50 5.9
1 0 1 0.89 0.40 1.00 0.67 0.50 1.00 11.4
1 0 1 0.89 0.60 1.00 0.33 0.50 1.00 13.0
1 0 1 1.00 0.40 1.00 1.00 0.00 1.00 10.8
1 1 1 0.67 0.30 0.83 0.67 0.00 1.00 12.3
1 0 0 1.00 0.50 0.83 0.67 0.50 0.50 11.3
1 0 1 0.89 0.20 0.50 0.00 0.00 1.00 11.8
1 1 1 0.89 0.30 0.83 0.00 0.50 1.00 7.9
1 0 0 0.89 0.50 0.17 0.00 0.00 1.00 12.7
1 1 1 0.78 0.70 0.83 1.00 0.50 1.00 12.3
1 1 1 0.89 0.40 1.00 0.67 1.00 0.50 11.6
1 1 1 0.78 0.30 1.00 0.00 0.00 0.50 6.7
1 0 1 0.78 0.20 0.67 0.67 1.00 1.00 10.9
1 1 1 1.00 0.50 1.00 0.00 0.00 0.50 12.1
1 0 1 0.78 0.40 1.00 0.00 0.50 0.00 13.3
1 0 1 1.00 0.60 1.00 0.67 1.00 1.00 10.1
1 1 0 0.78 0.40 0.83 1.00 0.00 1.00 5.7
1 0 1 0.67 0.40 0.33 0.00 0.00 0.50 14.3
1 1 0 0.33 0.20 0.33 0.33 0.00 0.00 8.0
1 1 1 1.00 0.90 1.00 0.67 0.50 1.00 13.3
1 0 1 1.00 0.80 1.00 0.67 1.00 0.50 9.3
1 0 0 0.78 0.80 0.83 0.00 0.50 1.00 12.5
1 0 0 0.67 0.30 1.00 1.00 0.50 1.00 7.6
1 0 1 1.00 0.20 0.83 0.67 0.00 0.50 15.9
1 0 0 0.89 0.40 0.67 0.00 0.50 1.00 9.2
1 1 1 0.89 0.20 0.83 1.00 0.00 1.00 9.1
1 0 0 0.78 0.20 0.67 0.67 0.50 1.00 11.1
1 0 1 1.00 0.10 0.83 0.67 0.00 1.00 13.0
1 0 1 0.56 0.40 0.67 1.00 0.50 0.00 14.5
1 1 0 0.67 0.50 1.00 0.00 0.50 0.50 12.2
1 0 0 0.89 0.80 0.83 0.33 0.50 1.00 12.3
1 0 0 0.89 0.40 0.67 0.67 0.00 0.50 11.4
1 1 0 0.89 0.60 0.83 0.33 0.50 0.50 8.8
1 1 1 0.89 0.50 0.83 0.67 0.50 1.00 14.6
1 0 0 0.78 0.30 0.67 0.00 0.00 0.00 12.6
1 0 1 0.89 0.80 1.00 1.00 0.50 1.00 NA
1 0 0 1.00 0.40 0.33 0.00 0.50 0.00 13.0
1 1 1 1.00 0.60 0.83 0.67 0.50 0.50 12.6
1 0 0 0.89 0.40 1.00 0.33 0.00 0.50 13.2
1 1 0 0.44 0.30 0.83 0.00 0.00 0.00 9.9
1 0 1 0.78 0.80 0.83 0.00 1.00 1.00 7.7
1 1 0 0.89 0.60 0.50 0.33 1.00 1.00 10.5
1 1 0 0.67 0.30 0.50 0.00 0.00 0.00 13.4
1 1 0 0.78 0.50 0.83 0.67 0.50 1.00 10.9
1 1 1 0.78 0.40 1.00 0.33 0.00 1.00 4.3
1 1 0 0.33 0.30 0.33 0.67 0.00 0.00 10.3
1 1 1 0.89 0.70 1.00 0.33 0.00 0.50 11.8
1 1 1 0.89 0.20 0.67 0.33 0.50 0.50 11.2
1 1 0 0.89 0.40 0.83 1.00 0.00 1.00 11.4
1 1 0 0.89 0.60 1.00 0.67 0.50 0.50 8.6
1 1 0 0.56 0.60 0.83 0.00 0.00 1.00 13.2
1 1 1 0.67 0.60 0.83 0.67 0.50 0.50 12.6
1 1 1 0.67 0.40 1.00 0.33 0.50 1.00 5.6
1 1 1 0.78 0.60 0.83 0.00 0.00 1.00 9.9
1 1 0 0.78 0.50 1.00 0.33 0.50 1.00 8.8
1 1 1 0.78 0.50 0.83 0.00 0.00 1.00 7.7
1 1 0 0.89 0.60 0.67 0.00 0.00 1.00 9.0
1 1 1 1.00 0.80 0.83 0.33 0.50 1.00 7.3
1 1 1 0.89 0.50 0.83 0.67 1.00 0.50 11.4
1 1 1 0.89 0.60 0.83 0.67 0.50 1.00 13.6
1 1 1 0.78 0.40 0.83 0.67 0.50 1.00 7.9
1 1 1 1.00 0.30 0.67 0.67 0.50 1.00 10.7
1 1 0 0.78 0.30 0.83 1.00 0.00 0.50 10.3
1 1 1 0.67 0.20 0.00 0.00 0.00 0.00 8.3
1 1 1 0.78 0.40 0.83 0.00 0.00 0.50 9.6
1 1 1 0.89 0.50 1.00 0.00 0.00 0.50 14.2
1 1 0 0.67 0.30 0.17 0.00 0.50 0.00 8.5
1 1 0 0.22 0.40 0.17 0.00 0.50 0.00 13.5
1 1 0 0.44 0.50 0.50 1.00 0.00 0.00 4.9
1 1 0 0.89 0.30 0.50 0.67 0.00 1.00 6.4
1 1 0 0.67 0.50 1.00 0.00 0.00 0.50 9.6
1 1 0 0.89 0.40 0.67 0.67 0.00 0.50 11.6
1 1 1 0.67 0.40 0.83 0.67 0.00 1.00 11.1
0 0 1 0.78 0.60 1.00 0.00 1.00 1.00 4.35
0 0 1 0.78 0.30 1.00 0.67 1.00 1.00 12.7
0 0 1 0.78 0.40 1.00 0.33 1.00 0.50 18.1
0 0 1 1.00 0.30 1.00 1.00 1.00 1.00 17.85
0 1 0 0.78 1.00 1.00 1.00 1.00 1.00 16.6
0 1 1 0.67 0.40 1.00 0.00 0.00 0.50 12.6
0 0 1 0.89 0.80 0.83 1.00 0.50 1.00 17.1
0 0 0 0.89 0.30 1.00 0.67 1.00 1.00 19.1
0 0 1 1.00 0.50 0.83 0.67 0.00 1.00 16.1
0 0 0 0.78 0.40 1.00 0.00 0.00 0.50 13.35
0 0 0 0.67 0.30 0.83 0.67 0.00 1.00 18.4
0 0 1 0.89 0.50 0.83 1.00 0.00 1.00 14.7
0 0 1 0.67 0.30 1.00 0.67 0.00 1.00 10.6
0 0 1 0.67 0.30 0.67 0.00 0.00 1.00 12.6
0 0 1 1.00 0.40 0.83 0.00 0.00 1.00 16.2
0 0 1 0.67 0.30 1.00 0.00 0.00 0.50 13.6
0 1 1 1.00 0.60 1.00 0.33 0.50 0.50 18.9
0 0 1 0.89 0.60 0.83 0.67 1.00 1.00 14.1
0 0 1 0.89 0.40 1.00 1.00 1.00 1.00 14.5
0 0 0 1.00 0.40 1.00 0.00 0.00 0.00 16.15
0 0 1 0.67 0.40 1.00 0.67 0.00 0.50 14.75
0 0 1 0.44 0.30 0.67 0.67 0.50 1.00 14.8
0 0 1 0.89 0.20 1.00 0.33 1.00 0.00 12.45
0 0 1 0.56 0.50 0.83 0.67 0.00 1.00 12.65
0 0 1 0.78 0.40 1.00 0.67 1.00 1.00 17.35
0 0 1 1.00 0.40 1.00 0.67 0.00 0.00 8.6
0 0 0 1.00 0.40 0.83 0.67 0.00 1.00 18.4
0 0 1 0.89 0.30 0.67 0.67 0.50 0.50 16.1
0 1 1 0.67 0.40 0.83 0.67 1.00 0.50 11.6
0 0 1 0.89 0.20 1.00 0.33 0.50 1.00 17.75
0 0 1 0.33 0.00 0.00 0.00 0.00 0.00 15.25
0 0 1 0.89 0.40 1.00 0.67 0.50 1.00 17.65
0 0 0 0.78 0.60 1.00 0.00 1.00 1.00 16.35
0 0 0 1.00 0.40 0.67 0.67 0.00 0.50 17.65
0 0 1 0.44 0.40 1.00 0.00 0.00 0.50 13.6
0 0 0 0.67 0.40 0.83 0.00 0.50 0.00 14.35
0 0 0 0.33 0.20 0.17 0.00 0.50 0.00 14.75
0 0 1 0.89 0.40 0.83 1.00 1.00 1.00 18.25
0 0 0 0.89 0.30 0.83 0.00 0.00 0.50 9.9
0 0 1 1.00 0.60 0.83 0.67 1.00 0.00 16
0 0 1 0.89 0.60 0.83 1.00 0.00 1.00 18.25
0 0 0 0.89 0.40 0.83 0.00 0.00 1.00 16.85
0 1 1 1.00 0.50 1.00 0.67 1.00 0.50 14.6
0 1 1 0.89 0.40 0.83 0.00 0.50 1.00 13.85
0 0 1 1.00 0.60 1.00 1.00 1.00 1.00 18.95
0 0 0 0.78 0.60 0.83 0.67 0.50 1.00 15.6
0 1 0 0.78 0.90 1.00 0.67 0.50 1.00 14.85
0 1 0 0.67 0.40 0.83 0.67 0.50 0.00 11.75
0 1 0 0.89 0.80 1.00 1.00 0.50 1.00 18.45
0 1 1 0.67 0.50 0.83 1.00 0.00 1.00 15.9
0 0 0 0.78 0.40 0.83 1.00 0.00 0.00 17.1
0 0 1 0.89 0.40 1.00 0.67 1.00 0.50 16.1
0 1 0 0.89 0.70 1.00 1.00 1.00 0.50 19.9
0 1 1 0.78 0.40 1.00 0.33 1.00 1.00 10.95
0 1 0 1.00 0.80 1.00 0.67 0.50 1.00 18.45
0 1 1 1.00 0.40 1.00 1.00 1.00 0.50 15.1
0 1 0 1.00 0.30 1.00 0.67 0.00 0.50 15
0 1 0 0.67 0.50 1.00 0.67 0.50 1.00 11.35
0 1 1 0.89 0.80 1.00 0.67 1.00 1.00 15.95
0 1 0 1.00 0.40 0.83 0.33 0.00 0.50 18.1
0 1 1 1.00 1.00 1.00 1.00 0.50 0.00 14.6
0 0 1 0.89 0.50 1.00 0.67 1.00 1.00 15.4
0 0 1 0.89 0.50 1.00 0.67 1.00 1.00 15.4
0 1 1 0.89 0.30 1.00 0.33 0.00 1.00 17.6
0 0 1 0.89 0.30 0.83 0.33 0.50 1.00 13.35
0 0 0 0.89 0.30 0.50 0.00 0.00 1.00 19.1
0 1 1 1.00 0.40 0.67 0.33 0.50 0.50 15.35
0 0 0 0.67 0.50 1.00 0.33 0.00 1.00 7.6
0 1 0 1.00 0.50 0.67 0.67 0.50 1.00 13.4
0 1 0 0.89 0.40 1.00 0.00 0.00 0.00 13.9
0 0 1 0.89 0.70 1.00 1.00 0.50 0.00 19.1
0 1 0 0.89 0.50 0.50 0.33 0.00 0.50 15.25
0 1 1 0.89 0.40 0.67 0.33 1.00 0.00 12.9
0 1 0 1.00 0.70 0.67 1.00 0.00 1.00 16.1
0 1 0 1.00 0.70 0.67 1.00 0.00 1.00 17.35
0 1 0 1.00 0.70 0.67 1.00 0.00 1.00 13.15
0 1 0 0.89 0.70 0.67 1.00 0.00 1.00 12.15
0 1 1 0.89 0.70 0.67 0.00 0.00 0.00 12.6
0 1 1 0.89 0.70 1.00 0.67 0.50 1.00 10.35
0 1 1 0.33 0.10 0.67 0.33 0.50 0.00 15.4
0 1 1 0.67 0.20 0.67 0.67 0.50 1.00 9.6
0 1 0 0.56 0.30 0.33 0.33 0.00 1.00 18.2
0 1 0 0.44 0.60 0.83 0.33 0.00 0.50 13.6
0 1 1 1.00 0.80 1.00 1.00 1.00 1.00 14.85
0 0 0 0.89 0.80 1.00 0.33 0.50 0.50 14.75
0 1 0 0.33 0.00 0.17 0.00 0.00 0.00 14.1
0 1 0 0.67 0.30 0.67 0.33 0.00 1.00 14.9
0 1 0 0.67 0.60 0.83 0.33 0.50 1.00 16.25
0 0 1 1.00 0.50 0.83 0.67 0.00 1.00 19.25
0 1 1 0.78 0.70 1.00 0.33 0.00 0.50 13.6
0 0 0 0.67 0.30 0.83 0.00 0.50 1.00 13.6
0 1 0 1.00 0.30 1.00 0.67 0.00 0.00 15.65
0 0 1 0.78 0.40 1.00 0.67 0.00 0.50 12.75
0 1 0 0.89 0.40 0.83 1.00 0.00 1.00 14.6
0 0 1 0.89 0.10 0.83 0.00 0.00 1.00 9.85
0 1 1 0.89 0.50 1.00 0.67 0.00 1.00 12.65
0 1 0 0.00 0.00 0.00 0.00 0.00 0.00 19.2
0 1 1 0.67 0.40 1.00 0.33 0.50 0.00 16.6
0 1 1 1.00 0.60 0.83 0.67 1.00 0.50 11.2
0 0 1 1.00 0.40 1.00 0.33 0.50 1.00 15.25
0 0 0 0.67 0.10 0.33 0.00 0.50 1.00 11.9
0 1 0 0.89 0.30 0.83 0.00 0.00 1.00 13.2
0 0 0 0.89 0.70 0.83 0.67 0.00 1.00 16.35
0 0 1 0.56 0.30 0.17 0.00 0.00 1.00 12.4
0 1 1 0.67 0.50 0.83 0.33 0.50 0.00 15.85
0 0 1 1.00 0.30 0.83 0.67 1.00 1.00 18.15
0 1 1 1.00 0.60 0.67 0.67 0.50 1.00 11.15
0 1 0 1.00 0.90 1.00 1.00 0.00 1.00 15.65
0 0 0 0.67 0.40 0.83 0.00 0.50 1.00 17.75
0 1 0 0.44 0.30 1.00 0.00 0.50 0.50 7.65
0 0 1 0.89 0.90 1.00 0.67 1.00 1.00 12.35
0 0 1 0.44 0.50 1.00 0.00 0.50 0.00 15.6
0 0 0 0.56 0.30 1.00 1.00 0.50 0.50 19.3
0 1 0 0.89 0.60 0.83 0.67 0.00 0.50 15.2
0 0 0 0.67 0.20 1.00 0.33 0.00 0.50 17.1
0 1 1 0.89 0.40 0.83 1.00 0.50 1.00 15.6
0 0 1 1.00 0.50 0.83 0.67 0.50 0.50 18.4
0 0 0 0.78 0.40 0.83 0.67 0.00 0.50 19.05
0 0 0 0.44 0.00 0.00 0.00 0.00 0.00 18.55
0 0 0 0.89 0.20 1.00 0.33 0.50 1.00 19.1
0 1 1 0.89 0.50 1.00 0.67 0.50 1.00 13.1
0 0 1 0.89 0.30 1.00 0.67 0.00 0.50 12.85
0 0 1 0.44 0.00 0.00 0.00 0.00 0.00 9.5
0 0 1 1.00 0.50 0.83 1.00 0.00 1.00 4.5
0 1 0 0.89 0.60 0.83 0.33 0.00 1.00 11.85
0 0 1 0.67 0.30 0.83 0.00 0.50 0.50 13.6
0 0 1 0.33 0.00 0.00 0.00 0.00 0.00 11.7
0 1 1 0.78 0.30 0.67 0.00 0.50 0.00 12.4
0 0 0 0.89 0.50 1.00 0.67 0.50 1.00 13.35
0 1 0 0.78 0.40 0.67 0.00 0.00 1.00 11.4
0 1 1 0.78 0.50 0.83 0.67 0.00 0.50 14.9
0 1 0 0.89 0.70 1.00 1.00 1.00 0.50 19.9
0 1 1 0.78 0.80 1.00 0.67 0.50 1.00 11.2
0 1 1 0.78 0.60 1.00 0.33 0.50 1.00 14.6
0 0 0 0.67 0.40 0.83 0.33 0.00 0.50 17.6
0 0 1 0.89 0.50 0.83 0.33 0.50 0.00 14.05
0 0 0 0.89 0.50 1.00 0.00 0.50 1.00 16.1
0 0 1 0.78 0.30 1.00 0.33 0.00 1.00 13.35
0 0 1 1.00 0.60 1.00 0.00 0.50 1.00 11.85
0 0 0 1.00 0.30 0.67 0.67 0.00 0.50 11.95
0 1 1 0.78 0.60 0.83 1.00 0.50 0.50 14.75
0 1 0 0.78 0.30 0.33 0.33 0.00 1.00 15.15
0 0 1 0.89 0.70 1.00 0.67 1.00 1.00 13.2
0 1 0 0.89 0.70 1.00 1.00 0.00 1.00 16.85
0 1 1 0.67 0.60 0.67 1.00 0.50 1.00 7.85
0 0 0 1.00 0.50 1.00 0.33 0.50 0.00 7.7
0 1 0 0.67 0.50 0.83 0.33 0.00 0.50 12.6
0 1 1 0.56 0.40 0.67 0.00 0.00 1.00 7.85
0 1 1 0.78 0.40 1.00 0.33 1.00 1.00 10.95
0 1 0 1.00 0.70 1.00 1.00 0.00 1.00 12.35
0 1 1 0.67 0.20 0.17 0.00 0.50 0.00 9.95
0 1 1 0.78 0.50 0.83 0.67 0.00 0.50 14.9
0 1 0 0.56 0.40 0.83 0.67 0.50 0.00 16.65
0 1 1 1.00 0.20 1.00 0.67 1.00 1.00 13.4
0 1 0 0.89 0.50 0.67 0.67 0.00 0.00 13.95
0 1 0 0.44 0.40 0.50 0.00 0.00 1.00 15.7
0 1 1 1.00 0.70 0.67 1.00 1.00 1.00 16.85
0 1 1 0.89 0.60 0.83 0.67 1.00 0.00 10.95
0 1 0 0.78 0.40 0.83 0.00 0.00 0.00 15.35
0 1 1 0.89 0.50 1.00 0.67 1.00 1.00 12.2
0 1 0 0.11 0.00 0.17 0.00 0.00 0.00 15.1
0 1 0 0.89 0.70 1.00 0.67 0.50 1.00 17.75
0 1 1 0.89 0.40 0.67 0.67 0.00 1.00 15.2
0 0 0 1.00 0.50 0.67 1.00 0.00 1.00 14.6
0 1 0 0.89 0.60 0.83 0.67 0.00 0.50 16.65
0 1 1 1.00 0.80 0.50 0.67 0.50 0.50 8.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 10 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267922&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]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267922&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267922&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 time10 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 13.9473 -3.75276jaar_bin[t] -0.708211group_bin[t] -1.13268gender_bin[t] + 1.63234Calculation[t] -0.36411Algebraic_Reasoning[t] -0.0340821Graphical_Interpretation[t] + 1.09364Proportionality_and_Ratio[t] + 0.522235Probability_and_Sampling[t] -0.439636Estimation[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  13.9473 -3.75276jaar_bin[t] -0.708211group_bin[t] -1.13268gender_bin[t] +  1.63234Calculation[t] -0.36411Algebraic_Reasoning[t] -0.0340821Graphical_Interpretation[t] +  1.09364Proportionality_and_Ratio[t] +  0.522235Probability_and_Sampling[t] -0.439636Estimation[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267922&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  13.9473 -3.75276jaar_bin[t] -0.708211group_bin[t] -1.13268gender_bin[t] +  1.63234Calculation[t] -0.36411Algebraic_Reasoning[t] -0.0340821Graphical_Interpretation[t] +  1.09364Proportionality_and_Ratio[t] +  0.522235Probability_and_Sampling[t] -0.439636Estimation[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267922&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267922&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
TOT[t] = + 13.9473 -3.75276jaar_bin[t] -0.708211group_bin[t] -1.13268gender_bin[t] + 1.63234Calculation[t] -0.36411Algebraic_Reasoning[t] -0.0340821Graphical_Interpretation[t] + 1.09364Proportionality_and_Ratio[t] + 0.522235Probability_and_Sampling[t] -0.439636Estimation[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)13.94730.8521116.373.22249e-421.61124e-42
jaar_bin-3.752760.345634-10.865.31766e-232.65883e-23
group_bin-0.7082110.3447-2.0550.04089010.0204451
gender_bin-1.132680.358369-3.1610.001754780.000877392
Calculation1.632341.138431.4340.1527830.0763914
Algebraic_Reasoning-0.364111.06666-0.34140.7331040.366552
Graphical_Interpretation-0.03408210.835891-0.040770.9675070.483753
Proportionality_and_Ratio1.093640.5238172.0880.03775790.0188789
Probability_and_Sampling0.5222350.5002891.0440.2974880.148744
Estimation-0.4396360.463029-0.94950.3432330.171617

\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) & 13.9473 & 0.85211 & 16.37 & 3.22249e-42 & 1.61124e-42 \tabularnewline
jaar_bin & -3.75276 & 0.345634 & -10.86 & 5.31766e-23 & 2.65883e-23 \tabularnewline
group_bin & -0.708211 & 0.3447 & -2.055 & 0.0408901 & 0.0204451 \tabularnewline
gender_bin & -1.13268 & 0.358369 & -3.161 & 0.00175478 & 0.000877392 \tabularnewline
Calculation & 1.63234 & 1.13843 & 1.434 & 0.152783 & 0.0763914 \tabularnewline
Algebraic_Reasoning & -0.36411 & 1.06666 & -0.3414 & 0.733104 & 0.366552 \tabularnewline
Graphical_Interpretation & -0.0340821 & 0.835891 & -0.04077 & 0.967507 & 0.483753 \tabularnewline
Proportionality_and_Ratio & 1.09364 & 0.523817 & 2.088 & 0.0377579 & 0.0188789 \tabularnewline
Probability_and_Sampling & 0.522235 & 0.500289 & 1.044 & 0.297488 & 0.148744 \tabularnewline
Estimation & -0.439636 & 0.463029 & -0.9495 & 0.343233 & 0.171617 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267922&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]13.9473[/C][C]0.85211[/C][C]16.37[/C][C]3.22249e-42[/C][C]1.61124e-42[/C][/ROW]
[ROW][C]jaar_bin[/C][C]-3.75276[/C][C]0.345634[/C][C]-10.86[/C][C]5.31766e-23[/C][C]2.65883e-23[/C][/ROW]
[ROW][C]group_bin[/C][C]-0.708211[/C][C]0.3447[/C][C]-2.055[/C][C]0.0408901[/C][C]0.0204451[/C][/ROW]
[ROW][C]gender_bin[/C][C]-1.13268[/C][C]0.358369[/C][C]-3.161[/C][C]0.00175478[/C][C]0.000877392[/C][/ROW]
[ROW][C]Calculation[/C][C]1.63234[/C][C]1.13843[/C][C]1.434[/C][C]0.152783[/C][C]0.0763914[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-0.36411[/C][C]1.06666[/C][C]-0.3414[/C][C]0.733104[/C][C]0.366552[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]-0.0340821[/C][C]0.835891[/C][C]-0.04077[/C][C]0.967507[/C][C]0.483753[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]1.09364[/C][C]0.523817[/C][C]2.088[/C][C]0.0377579[/C][C]0.0188789[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.522235[/C][C]0.500289[/C][C]1.044[/C][C]0.297488[/C][C]0.148744[/C][/ROW]
[ROW][C]Estimation[/C][C]-0.439636[/C][C]0.463029[/C][C]-0.9495[/C][C]0.343233[/C][C]0.171617[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267922&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267922&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)13.94730.8521116.373.22249e-421.61124e-42
jaar_bin-3.752760.345634-10.865.31766e-232.65883e-23
group_bin-0.7082110.3447-2.0550.04089010.0204451
gender_bin-1.132680.358369-3.1610.001754780.000877392
Calculation1.632341.138431.4340.1527830.0763914
Algebraic_Reasoning-0.364111.06666-0.34140.7331040.366552
Graphical_Interpretation-0.03408210.835891-0.040770.9675070.483753
Proportionality_and_Ratio1.093640.5238172.0880.03775790.0188789
Probability_and_Sampling0.5222350.5002891.0440.2974880.148744
Estimation-0.4396360.463029-0.94950.3432330.171617






Multiple Linear Regression - Regression Statistics
Multiple R0.599379
R-squared0.359256
Adjusted R-squared0.337738
F-TEST (value)16.6959
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.76231
Sum Squared Residuals2044.94

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.599379 \tabularnewline
R-squared & 0.359256 \tabularnewline
Adjusted R-squared & 0.337738 \tabularnewline
F-TEST (value) & 16.6959 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 268 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.76231 \tabularnewline
Sum Squared Residuals & 2044.94 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267922&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.599379[/C][/ROW]
[ROW][C]R-squared[/C][C]0.359256[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.337738[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]16.6959[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]268[/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]2.76231[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2044.94[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267922&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267922&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 R0.599379
R-squared0.359256
Adjusted R-squared0.337738
F-TEST (value)16.6959
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.76231
Sum Squared Residuals2044.94






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.13490.765095
212.210.48671.71332
312.811.76071.03931
47.410.3043-2.90429
56.710.3195-3.61952
612.610.26712.33285
714.812.46722.33276
813.311.34681.95316
911.110.49260.607412
108.210.8794-2.6794
1111.411.33250.0674933
126.410.2807-3.88072
1310.610.37620.223791
141211.77770.222265
156.311.8033-5.50333
1611.311.337-0.0369996
1711.910.74291.1571
189.311.1929-1.89287
199.69.70236-0.102357
201010.9325-0.932468
216.410.7217-4.32172
2213.810.18343.61665
2310.811.1423-0.342272
2413.810.33483.46521
2511.711.48060.21935
2610.99.504871.39513
2716.110.03136.06871
2813.411.27812.12191
299.910.9889-1.08891
3011.511.7-0.200014
318.310.8614-2.56143
3211.711.30030.39968
33910.9997-1.99971
349.711.1115-1.41146
3510.810.9564-0.156352
3610.311.3267-1.0267
3710.410.9678-0.567836
3812.79.792332.90767
399.311.0783-1.77833
4011.811.9126-0.112578
415.910.8566-4.95657
4211.410.88910.510871
431310.44452.55553
4410.811.1685-0.36847
4512.39.602892.69711
4611.312.3906-1.09057
4711.89.985141.81486
487.99.49038-1.59038
4912.711.01981.68017
5012.310.25882.04118
5111.610.66190.938147
526.79.26373-2.56373
5310.911.0548-0.154759
5412.19.550032.54997
5513.310.41652.88353
5610.111.257-1.15698
575.711.2396-5.53962
5814.39.778814.52119
59810.3018-2.30183
6013.310.17843.12158
619.311.404-2.10398
6212.510.96971.53033
637.612.06-4.46001
6415.911.1064.794
659.211.3003-2.10032
669.110.3593-1.25932
6711.111.9263-0.826323
681310.92262.0774
6914.511.16223.33776
7012.210.40521.79485
7112.311.51010.789876
7211.411.9918-0.591759
738.811.0946-2.29455
7414.610.15034.4497
7512.611.33571.26431
76NANA1.0689
771310.91332.08674
7812.611.00871.59133
7913.213.367-0.167034
809.912.2981-2.3981
817.78.3471-0.647099
8210.57.553722.94628
8313.413.6034-0.203426
8410.915.9684-5.06841
854.34.63726-0.337256
8610.38.158552.14145
8711.810.7131.08703
8811.211.2192-0.0191773
8911.414.2606-2.8606
908.65.114053.48595
9113.210.57462.62541
9212.616.45-3.84997
935.64.640480.959522
949.911.8258-1.92579
958.810.0769-1.27689
967.78.95817-1.25817
97911.5488-2.54879
987.36.531240.768764
9911.47.913893.48611
10013.615.7072-2.10716
1017.97.608130.291867
10210.711.8958-1.19585
10310.311.3745-1.07449
1048.37.933120.366882
1059.64.770474.82953
10614.216.4261-2.22608
1078.54.955123.54488
10813.519.6991-6.1991
1094.99.60593-4.70593
1106.46.94404-0.544038
1119.69.283550.316452
11211.610.06651.53352
11311.120.6679-9.56789
1144.356.40986-2.05986
11512.79.171433.52857
11618.115.72992.37012
11717.8516.54041.30964
11816.616.8005-0.200527
11912.610.36292.23706
12017.114.07213.0279
12119.117.52971.57029
12216.117.571-1.47098
12313.3510.14653.20346
12418.418.4111-0.0110556
12514.718.1581-3.45807
12610.611.3366-0.736578
12712.610.23342.36662
12816.216.14510.0548512
12913.68.588395.01161
13018.919.636-0.735979
13114.114.8639-0.763907
13214.513.74990.750091
13316.1515.64150.508524
13414.7513.9050.845004
13514.817.3936-2.59363
13612.4513.6115-1.16148
13712.6510.02342.62655
13817.3523.75-6.39996
1398.65.89882.7012
14018.417.20941.19063
14116.118.5613-2.46129
14211.68.192873.40713
14317.7515.85331.89671
14415.2512.24193.00811
14517.6516.35061.29943
14616.3514.62411.72592
14717.6517.18330.466699
14813.614.3781-0.778149
14914.3514.26850.0815292
15014.7511.76972.9803
15118.2523.3927-5.14274
1529.99.355170.544829
1531612.42463.57536
15418.2516.18652.06349
15516.8516.80780.0422408
15614.613.95670.643266
15713.8510.27063.57936
15818.9518.8780.0720138
15915.615.45470.145252
16014.8518.2527-3.40268
16111.758.581623.16838
16218.4516.19372.25627
16315.914.94020.959773
16417.116.12280.977176
16516.111.9994.10104
16619.922.5934-2.6934
16710.957.600273.34973
16818.4518.30510.144929
16915.115.341-0.241028
1701518.3208-3.32083
17111.359.449151.90085
17215.9512.68863.26143
17318.118.1953-0.0953058
17414.614.06660.533404
17515.414.86660.533404
17615.411.13714.26287
17717.618.5623-0.962257
17813.359.084174.26583
17919.117.72251.37754
18015.3522.4961-7.14609
1817.69.42075-1.82075
18213.414.0121-0.61214
18313.910.13323.76681
18419.118.48390.616147
18515.2516.6238-1.37384
18612.912.04770.852285
18716.113.99772.10229
18817.3519.4477-2.09771
18913.1516.0682-2.91816
19012.1512.8315-0.681473
19112.616.0744-3.47445
19210.358.157852.19215
19315.419.4586-4.05863
1949.65.353984.24602
19518.218.4516-0.251644
19613.613.33960.260391
19714.8515.5769-0.726908
19814.7514.4220.328036
19914.113.32190.778051
20014.912.91841.98162
20116.2511.52974.72029
20219.2518.88180.368249
20313.614.7249-1.12492
20413.613.41080.189154
20515.6517.321-1.67103
20612.7513.3219-0.571937
20714.618.5131-3.91306
2089.8510.8361-0.98615
20912.656.689095.96091
21019.216.24242.95764
21116.619.9271-3.32714
21211.210.39960.800391
21315.2518.1648-2.91479
21411.912.8147-0.914709
21513.212.260.939985
21616.3517.1241-0.774062
21712.410.16172.23825
21815.8512.82483.02523
21918.1521.0517-2.90166
22011.1510.66360.486355
22115.6512.58853.06149
22217.7523.9553-6.2053
2237.6510.021-2.37095
22412.3510.32782.02218
22515.612.1533.44697
22619.319.0580.241968
22715.213.17512.02486
22817.115.80041.29963
22915.612.21063.38935
23018.414.90953.49049
23119.0515.16553.88447
23218.5514.92563.62444
23319.119.8973-0.797267
23413.114.887-1.787
23512.8516.8828-4.03284
2369.519.8906-10.3906
2374.57.01638-2.51638
23811.8512.0621-0.21206
23913.615.2533-1.65329
24011.712.8087-1.10868
24112.414.7882-2.38816
24213.3515.8542-2.50419
24311.410.18221.2178
24414.910.7994.10104
24519.922.3085-2.40848
24611.29.909461.29054
24714.612.00812.59189
24817.618.2291-0.629071
24914.0512.95541.09458
25016.116.6158-0.515789
25113.3515.5159-2.16589
25211.8515.8605-4.01049
25311.9511.46780.482188
25414.7513.91310.836906
25515.1516.7438-1.59377
25613.211.40691.79309
25716.8522.8739-6.02389
2587.8516.1355-8.28552
2597.79.36349-1.66349
26012.617.1624-4.5624
2617.8510.5434-2.6934
26210.9513.8365-2.88647
26312.3515.7826-3.43257
2649.958.73221.2178
26514.913.22311.67688
26616.6517.6972-1.04717
26713.414.6697-1.26971
26813.9511.6052.34501
26915.713.48732.21273
27016.8520.4674-3.6174
27110.959.938381.01162
27215.3517.3084-1.95838
27312.210.51291.68715
27415.112.30712.79287
27517.7516.23381.51619
27615.216.6287-1.42875
27714.612.9081.69197
27816.6522.7545-6.10445
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.1349 & 0.765095 \tabularnewline
2 & 12.2 & 10.4867 & 1.71332 \tabularnewline
3 & 12.8 & 11.7607 & 1.03931 \tabularnewline
4 & 7.4 & 10.3043 & -2.90429 \tabularnewline
5 & 6.7 & 10.3195 & -3.61952 \tabularnewline
6 & 12.6 & 10.2671 & 2.33285 \tabularnewline
7 & 14.8 & 12.4672 & 2.33276 \tabularnewline
8 & 13.3 & 11.3468 & 1.95316 \tabularnewline
9 & 11.1 & 10.4926 & 0.607412 \tabularnewline
10 & 8.2 & 10.8794 & -2.6794 \tabularnewline
11 & 11.4 & 11.3325 & 0.0674933 \tabularnewline
12 & 6.4 & 10.2807 & -3.88072 \tabularnewline
13 & 10.6 & 10.3762 & 0.223791 \tabularnewline
14 & 12 & 11.7777 & 0.222265 \tabularnewline
15 & 6.3 & 11.8033 & -5.50333 \tabularnewline
16 & 11.3 & 11.337 & -0.0369996 \tabularnewline
17 & 11.9 & 10.7429 & 1.1571 \tabularnewline
18 & 9.3 & 11.1929 & -1.89287 \tabularnewline
19 & 9.6 & 9.70236 & -0.102357 \tabularnewline
20 & 10 & 10.9325 & -0.932468 \tabularnewline
21 & 6.4 & 10.7217 & -4.32172 \tabularnewline
22 & 13.8 & 10.1834 & 3.61665 \tabularnewline
23 & 10.8 & 11.1423 & -0.342272 \tabularnewline
24 & 13.8 & 10.3348 & 3.46521 \tabularnewline
25 & 11.7 & 11.4806 & 0.21935 \tabularnewline
26 & 10.9 & 9.50487 & 1.39513 \tabularnewline
27 & 16.1 & 10.0313 & 6.06871 \tabularnewline
28 & 13.4 & 11.2781 & 2.12191 \tabularnewline
29 & 9.9 & 10.9889 & -1.08891 \tabularnewline
30 & 11.5 & 11.7 & -0.200014 \tabularnewline
31 & 8.3 & 10.8614 & -2.56143 \tabularnewline
32 & 11.7 & 11.3003 & 0.39968 \tabularnewline
33 & 9 & 10.9997 & -1.99971 \tabularnewline
34 & 9.7 & 11.1115 & -1.41146 \tabularnewline
35 & 10.8 & 10.9564 & -0.156352 \tabularnewline
36 & 10.3 & 11.3267 & -1.0267 \tabularnewline
37 & 10.4 & 10.9678 & -0.567836 \tabularnewline
38 & 12.7 & 9.79233 & 2.90767 \tabularnewline
39 & 9.3 & 11.0783 & -1.77833 \tabularnewline
40 & 11.8 & 11.9126 & -0.112578 \tabularnewline
41 & 5.9 & 10.8566 & -4.95657 \tabularnewline
42 & 11.4 & 10.8891 & 0.510871 \tabularnewline
43 & 13 & 10.4445 & 2.55553 \tabularnewline
44 & 10.8 & 11.1685 & -0.36847 \tabularnewline
45 & 12.3 & 9.60289 & 2.69711 \tabularnewline
46 & 11.3 & 12.3906 & -1.09057 \tabularnewline
47 & 11.8 & 9.98514 & 1.81486 \tabularnewline
48 & 7.9 & 9.49038 & -1.59038 \tabularnewline
49 & 12.7 & 11.0198 & 1.68017 \tabularnewline
50 & 12.3 & 10.2588 & 2.04118 \tabularnewline
51 & 11.6 & 10.6619 & 0.938147 \tabularnewline
52 & 6.7 & 9.26373 & -2.56373 \tabularnewline
53 & 10.9 & 11.0548 & -0.154759 \tabularnewline
54 & 12.1 & 9.55003 & 2.54997 \tabularnewline
55 & 13.3 & 10.4165 & 2.88353 \tabularnewline
56 & 10.1 & 11.257 & -1.15698 \tabularnewline
57 & 5.7 & 11.2396 & -5.53962 \tabularnewline
58 & 14.3 & 9.77881 & 4.52119 \tabularnewline
59 & 8 & 10.3018 & -2.30183 \tabularnewline
60 & 13.3 & 10.1784 & 3.12158 \tabularnewline
61 & 9.3 & 11.404 & -2.10398 \tabularnewline
62 & 12.5 & 10.9697 & 1.53033 \tabularnewline
63 & 7.6 & 12.06 & -4.46001 \tabularnewline
64 & 15.9 & 11.106 & 4.794 \tabularnewline
65 & 9.2 & 11.3003 & -2.10032 \tabularnewline
66 & 9.1 & 10.3593 & -1.25932 \tabularnewline
67 & 11.1 & 11.9263 & -0.826323 \tabularnewline
68 & 13 & 10.9226 & 2.0774 \tabularnewline
69 & 14.5 & 11.1622 & 3.33776 \tabularnewline
70 & 12.2 & 10.4052 & 1.79485 \tabularnewline
71 & 12.3 & 11.5101 & 0.789876 \tabularnewline
72 & 11.4 & 11.9918 & -0.591759 \tabularnewline
73 & 8.8 & 11.0946 & -2.29455 \tabularnewline
74 & 14.6 & 10.1503 & 4.4497 \tabularnewline
75 & 12.6 & 11.3357 & 1.26431 \tabularnewline
76 & NA & NA & 1.0689 \tabularnewline
77 & 13 & 10.9133 & 2.08674 \tabularnewline
78 & 12.6 & 11.0087 & 1.59133 \tabularnewline
79 & 13.2 & 13.367 & -0.167034 \tabularnewline
80 & 9.9 & 12.2981 & -2.3981 \tabularnewline
81 & 7.7 & 8.3471 & -0.647099 \tabularnewline
82 & 10.5 & 7.55372 & 2.94628 \tabularnewline
83 & 13.4 & 13.6034 & -0.203426 \tabularnewline
84 & 10.9 & 15.9684 & -5.06841 \tabularnewline
85 & 4.3 & 4.63726 & -0.337256 \tabularnewline
86 & 10.3 & 8.15855 & 2.14145 \tabularnewline
87 & 11.8 & 10.713 & 1.08703 \tabularnewline
88 & 11.2 & 11.2192 & -0.0191773 \tabularnewline
89 & 11.4 & 14.2606 & -2.8606 \tabularnewline
90 & 8.6 & 5.11405 & 3.48595 \tabularnewline
91 & 13.2 & 10.5746 & 2.62541 \tabularnewline
92 & 12.6 & 16.45 & -3.84997 \tabularnewline
93 & 5.6 & 4.64048 & 0.959522 \tabularnewline
94 & 9.9 & 11.8258 & -1.92579 \tabularnewline
95 & 8.8 & 10.0769 & -1.27689 \tabularnewline
96 & 7.7 & 8.95817 & -1.25817 \tabularnewline
97 & 9 & 11.5488 & -2.54879 \tabularnewline
98 & 7.3 & 6.53124 & 0.768764 \tabularnewline
99 & 11.4 & 7.91389 & 3.48611 \tabularnewline
100 & 13.6 & 15.7072 & -2.10716 \tabularnewline
101 & 7.9 & 7.60813 & 0.291867 \tabularnewline
102 & 10.7 & 11.8958 & -1.19585 \tabularnewline
103 & 10.3 & 11.3745 & -1.07449 \tabularnewline
104 & 8.3 & 7.93312 & 0.366882 \tabularnewline
105 & 9.6 & 4.77047 & 4.82953 \tabularnewline
106 & 14.2 & 16.4261 & -2.22608 \tabularnewline
107 & 8.5 & 4.95512 & 3.54488 \tabularnewline
108 & 13.5 & 19.6991 & -6.1991 \tabularnewline
109 & 4.9 & 9.60593 & -4.70593 \tabularnewline
110 & 6.4 & 6.94404 & -0.544038 \tabularnewline
111 & 9.6 & 9.28355 & 0.316452 \tabularnewline
112 & 11.6 & 10.0665 & 1.53352 \tabularnewline
113 & 11.1 & 20.6679 & -9.56789 \tabularnewline
114 & 4.35 & 6.40986 & -2.05986 \tabularnewline
115 & 12.7 & 9.17143 & 3.52857 \tabularnewline
116 & 18.1 & 15.7299 & 2.37012 \tabularnewline
117 & 17.85 & 16.5404 & 1.30964 \tabularnewline
118 & 16.6 & 16.8005 & -0.200527 \tabularnewline
119 & 12.6 & 10.3629 & 2.23706 \tabularnewline
120 & 17.1 & 14.0721 & 3.0279 \tabularnewline
121 & 19.1 & 17.5297 & 1.57029 \tabularnewline
122 & 16.1 & 17.571 & -1.47098 \tabularnewline
123 & 13.35 & 10.1465 & 3.20346 \tabularnewline
124 & 18.4 & 18.4111 & -0.0110556 \tabularnewline
125 & 14.7 & 18.1581 & -3.45807 \tabularnewline
126 & 10.6 & 11.3366 & -0.736578 \tabularnewline
127 & 12.6 & 10.2334 & 2.36662 \tabularnewline
128 & 16.2 & 16.1451 & 0.0548512 \tabularnewline
129 & 13.6 & 8.58839 & 5.01161 \tabularnewline
130 & 18.9 & 19.636 & -0.735979 \tabularnewline
131 & 14.1 & 14.8639 & -0.763907 \tabularnewline
132 & 14.5 & 13.7499 & 0.750091 \tabularnewline
133 & 16.15 & 15.6415 & 0.508524 \tabularnewline
134 & 14.75 & 13.905 & 0.845004 \tabularnewline
135 & 14.8 & 17.3936 & -2.59363 \tabularnewline
136 & 12.45 & 13.6115 & -1.16148 \tabularnewline
137 & 12.65 & 10.0234 & 2.62655 \tabularnewline
138 & 17.35 & 23.75 & -6.39996 \tabularnewline
139 & 8.6 & 5.8988 & 2.7012 \tabularnewline
140 & 18.4 & 17.2094 & 1.19063 \tabularnewline
141 & 16.1 & 18.5613 & -2.46129 \tabularnewline
142 & 11.6 & 8.19287 & 3.40713 \tabularnewline
143 & 17.75 & 15.8533 & 1.89671 \tabularnewline
144 & 15.25 & 12.2419 & 3.00811 \tabularnewline
145 & 17.65 & 16.3506 & 1.29943 \tabularnewline
146 & 16.35 & 14.6241 & 1.72592 \tabularnewline
147 & 17.65 & 17.1833 & 0.466699 \tabularnewline
148 & 13.6 & 14.3781 & -0.778149 \tabularnewline
149 & 14.35 & 14.2685 & 0.0815292 \tabularnewline
150 & 14.75 & 11.7697 & 2.9803 \tabularnewline
151 & 18.25 & 23.3927 & -5.14274 \tabularnewline
152 & 9.9 & 9.35517 & 0.544829 \tabularnewline
153 & 16 & 12.4246 & 3.57536 \tabularnewline
154 & 18.25 & 16.1865 & 2.06349 \tabularnewline
155 & 16.85 & 16.8078 & 0.0422408 \tabularnewline
156 & 14.6 & 13.9567 & 0.643266 \tabularnewline
157 & 13.85 & 10.2706 & 3.57936 \tabularnewline
158 & 18.95 & 18.878 & 0.0720138 \tabularnewline
159 & 15.6 & 15.4547 & 0.145252 \tabularnewline
160 & 14.85 & 18.2527 & -3.40268 \tabularnewline
161 & 11.75 & 8.58162 & 3.16838 \tabularnewline
162 & 18.45 & 16.1937 & 2.25627 \tabularnewline
163 & 15.9 & 14.9402 & 0.959773 \tabularnewline
164 & 17.1 & 16.1228 & 0.977176 \tabularnewline
165 & 16.1 & 11.999 & 4.10104 \tabularnewline
166 & 19.9 & 22.5934 & -2.6934 \tabularnewline
167 & 10.95 & 7.60027 & 3.34973 \tabularnewline
168 & 18.45 & 18.3051 & 0.144929 \tabularnewline
169 & 15.1 & 15.341 & -0.241028 \tabularnewline
170 & 15 & 18.3208 & -3.32083 \tabularnewline
171 & 11.35 & 9.44915 & 1.90085 \tabularnewline
172 & 15.95 & 12.6886 & 3.26143 \tabularnewline
173 & 18.1 & 18.1953 & -0.0953058 \tabularnewline
174 & 14.6 & 14.0666 & 0.533404 \tabularnewline
175 & 15.4 & 14.8666 & 0.533404 \tabularnewline
176 & 15.4 & 11.1371 & 4.26287 \tabularnewline
177 & 17.6 & 18.5623 & -0.962257 \tabularnewline
178 & 13.35 & 9.08417 & 4.26583 \tabularnewline
179 & 19.1 & 17.7225 & 1.37754 \tabularnewline
180 & 15.35 & 22.4961 & -7.14609 \tabularnewline
181 & 7.6 & 9.42075 & -1.82075 \tabularnewline
182 & 13.4 & 14.0121 & -0.61214 \tabularnewline
183 & 13.9 & 10.1332 & 3.76681 \tabularnewline
184 & 19.1 & 18.4839 & 0.616147 \tabularnewline
185 & 15.25 & 16.6238 & -1.37384 \tabularnewline
186 & 12.9 & 12.0477 & 0.852285 \tabularnewline
187 & 16.1 & 13.9977 & 2.10229 \tabularnewline
188 & 17.35 & 19.4477 & -2.09771 \tabularnewline
189 & 13.15 & 16.0682 & -2.91816 \tabularnewline
190 & 12.15 & 12.8315 & -0.681473 \tabularnewline
191 & 12.6 & 16.0744 & -3.47445 \tabularnewline
192 & 10.35 & 8.15785 & 2.19215 \tabularnewline
193 & 15.4 & 19.4586 & -4.05863 \tabularnewline
194 & 9.6 & 5.35398 & 4.24602 \tabularnewline
195 & 18.2 & 18.4516 & -0.251644 \tabularnewline
196 & 13.6 & 13.3396 & 0.260391 \tabularnewline
197 & 14.85 & 15.5769 & -0.726908 \tabularnewline
198 & 14.75 & 14.422 & 0.328036 \tabularnewline
199 & 14.1 & 13.3219 & 0.778051 \tabularnewline
200 & 14.9 & 12.9184 & 1.98162 \tabularnewline
201 & 16.25 & 11.5297 & 4.72029 \tabularnewline
202 & 19.25 & 18.8818 & 0.368249 \tabularnewline
203 & 13.6 & 14.7249 & -1.12492 \tabularnewline
204 & 13.6 & 13.4108 & 0.189154 \tabularnewline
205 & 15.65 & 17.321 & -1.67103 \tabularnewline
206 & 12.75 & 13.3219 & -0.571937 \tabularnewline
207 & 14.6 & 18.5131 & -3.91306 \tabularnewline
208 & 9.85 & 10.8361 & -0.98615 \tabularnewline
209 & 12.65 & 6.68909 & 5.96091 \tabularnewline
210 & 19.2 & 16.2424 & 2.95764 \tabularnewline
211 & 16.6 & 19.9271 & -3.32714 \tabularnewline
212 & 11.2 & 10.3996 & 0.800391 \tabularnewline
213 & 15.25 & 18.1648 & -2.91479 \tabularnewline
214 & 11.9 & 12.8147 & -0.914709 \tabularnewline
215 & 13.2 & 12.26 & 0.939985 \tabularnewline
216 & 16.35 & 17.1241 & -0.774062 \tabularnewline
217 & 12.4 & 10.1617 & 2.23825 \tabularnewline
218 & 15.85 & 12.8248 & 3.02523 \tabularnewline
219 & 18.15 & 21.0517 & -2.90166 \tabularnewline
220 & 11.15 & 10.6636 & 0.486355 \tabularnewline
221 & 15.65 & 12.5885 & 3.06149 \tabularnewline
222 & 17.75 & 23.9553 & -6.2053 \tabularnewline
223 & 7.65 & 10.021 & -2.37095 \tabularnewline
224 & 12.35 & 10.3278 & 2.02218 \tabularnewline
225 & 15.6 & 12.153 & 3.44697 \tabularnewline
226 & 19.3 & 19.058 & 0.241968 \tabularnewline
227 & 15.2 & 13.1751 & 2.02486 \tabularnewline
228 & 17.1 & 15.8004 & 1.29963 \tabularnewline
229 & 15.6 & 12.2106 & 3.38935 \tabularnewline
230 & 18.4 & 14.9095 & 3.49049 \tabularnewline
231 & 19.05 & 15.1655 & 3.88447 \tabularnewline
232 & 18.55 & 14.9256 & 3.62444 \tabularnewline
233 & 19.1 & 19.8973 & -0.797267 \tabularnewline
234 & 13.1 & 14.887 & -1.787 \tabularnewline
235 & 12.85 & 16.8828 & -4.03284 \tabularnewline
236 & 9.5 & 19.8906 & -10.3906 \tabularnewline
237 & 4.5 & 7.01638 & -2.51638 \tabularnewline
238 & 11.85 & 12.0621 & -0.21206 \tabularnewline
239 & 13.6 & 15.2533 & -1.65329 \tabularnewline
240 & 11.7 & 12.8087 & -1.10868 \tabularnewline
241 & 12.4 & 14.7882 & -2.38816 \tabularnewline
242 & 13.35 & 15.8542 & -2.50419 \tabularnewline
243 & 11.4 & 10.1822 & 1.2178 \tabularnewline
244 & 14.9 & 10.799 & 4.10104 \tabularnewline
245 & 19.9 & 22.3085 & -2.40848 \tabularnewline
246 & 11.2 & 9.90946 & 1.29054 \tabularnewline
247 & 14.6 & 12.0081 & 2.59189 \tabularnewline
248 & 17.6 & 18.2291 & -0.629071 \tabularnewline
249 & 14.05 & 12.9554 & 1.09458 \tabularnewline
250 & 16.1 & 16.6158 & -0.515789 \tabularnewline
251 & 13.35 & 15.5159 & -2.16589 \tabularnewline
252 & 11.85 & 15.8605 & -4.01049 \tabularnewline
253 & 11.95 & 11.4678 & 0.482188 \tabularnewline
254 & 14.75 & 13.9131 & 0.836906 \tabularnewline
255 & 15.15 & 16.7438 & -1.59377 \tabularnewline
256 & 13.2 & 11.4069 & 1.79309 \tabularnewline
257 & 16.85 & 22.8739 & -6.02389 \tabularnewline
258 & 7.85 & 16.1355 & -8.28552 \tabularnewline
259 & 7.7 & 9.36349 & -1.66349 \tabularnewline
260 & 12.6 & 17.1624 & -4.5624 \tabularnewline
261 & 7.85 & 10.5434 & -2.6934 \tabularnewline
262 & 10.95 & 13.8365 & -2.88647 \tabularnewline
263 & 12.35 & 15.7826 & -3.43257 \tabularnewline
264 & 9.95 & 8.7322 & 1.2178 \tabularnewline
265 & 14.9 & 13.2231 & 1.67688 \tabularnewline
266 & 16.65 & 17.6972 & -1.04717 \tabularnewline
267 & 13.4 & 14.6697 & -1.26971 \tabularnewline
268 & 13.95 & 11.605 & 2.34501 \tabularnewline
269 & 15.7 & 13.4873 & 2.21273 \tabularnewline
270 & 16.85 & 20.4674 & -3.6174 \tabularnewline
271 & 10.95 & 9.93838 & 1.01162 \tabularnewline
272 & 15.35 & 17.3084 & -1.95838 \tabularnewline
273 & 12.2 & 10.5129 & 1.68715 \tabularnewline
274 & 15.1 & 12.3071 & 2.79287 \tabularnewline
275 & 17.75 & 16.2338 & 1.51619 \tabularnewline
276 & 15.2 & 16.6287 & -1.42875 \tabularnewline
277 & 14.6 & 12.908 & 1.69197 \tabularnewline
278 & 16.65 & 22.7545 & -6.10445 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267922&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]12.1349[/C][C]0.765095[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.4867[/C][C]1.71332[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.7607[/C][C]1.03931[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]10.3043[/C][C]-2.90429[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.3195[/C][C]-3.61952[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]10.2671[/C][C]2.33285[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.4672[/C][C]2.33276[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]11.3468[/C][C]1.95316[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]10.4926[/C][C]0.607412[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]10.8794[/C][C]-2.6794[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]11.3325[/C][C]0.0674933[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]10.2807[/C][C]-3.88072[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]10.3762[/C][C]0.223791[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]11.7777[/C][C]0.222265[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]11.8033[/C][C]-5.50333[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]11.337[/C][C]-0.0369996[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]10.7429[/C][C]1.1571[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]11.1929[/C][C]-1.89287[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]9.70236[/C][C]-0.102357[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]10.9325[/C][C]-0.932468[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]10.7217[/C][C]-4.32172[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]10.1834[/C][C]3.61665[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]11.1423[/C][C]-0.342272[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]10.3348[/C][C]3.46521[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]11.4806[/C][C]0.21935[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]9.50487[/C][C]1.39513[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]10.0313[/C][C]6.06871[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]11.2781[/C][C]2.12191[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]10.9889[/C][C]-1.08891[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]11.7[/C][C]-0.200014[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]10.8614[/C][C]-2.56143[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]11.3003[/C][C]0.39968[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]10.9997[/C][C]-1.99971[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]11.1115[/C][C]-1.41146[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]10.9564[/C][C]-0.156352[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]11.3267[/C][C]-1.0267[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]10.9678[/C][C]-0.567836[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]9.79233[/C][C]2.90767[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]11.0783[/C][C]-1.77833[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]11.9126[/C][C]-0.112578[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.8566[/C][C]-4.95657[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]10.8891[/C][C]0.510871[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]10.4445[/C][C]2.55553[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.1685[/C][C]-0.36847[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]9.60289[/C][C]2.69711[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.3906[/C][C]-1.09057[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]9.98514[/C][C]1.81486[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]9.49038[/C][C]-1.59038[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]11.0198[/C][C]1.68017[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]10.2588[/C][C]2.04118[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.6619[/C][C]0.938147[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]9.26373[/C][C]-2.56373[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]11.0548[/C][C]-0.154759[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]9.55003[/C][C]2.54997[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]10.4165[/C][C]2.88353[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]11.257[/C][C]-1.15698[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.2396[/C][C]-5.53962[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]9.77881[/C][C]4.52119[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]10.3018[/C][C]-2.30183[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]10.1784[/C][C]3.12158[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]11.404[/C][C]-2.10398[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]10.9697[/C][C]1.53033[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]12.06[/C][C]-4.46001[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]11.106[/C][C]4.794[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11.3003[/C][C]-2.10032[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]10.3593[/C][C]-1.25932[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]11.9263[/C][C]-0.826323[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]10.9226[/C][C]2.0774[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]11.1622[/C][C]3.33776[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.4052[/C][C]1.79485[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]11.5101[/C][C]0.789876[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]11.9918[/C][C]-0.591759[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]11.0946[/C][C]-2.29455[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]10.1503[/C][C]4.4497[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.3357[/C][C]1.26431[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]1.0689[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.9133[/C][C]2.08674[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]11.0087[/C][C]1.59133[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]13.367[/C][C]-0.167034[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]12.2981[/C][C]-2.3981[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]8.3471[/C][C]-0.647099[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]7.55372[/C][C]2.94628[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]13.6034[/C][C]-0.203426[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]15.9684[/C][C]-5.06841[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]4.63726[/C][C]-0.337256[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]8.15855[/C][C]2.14145[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]10.713[/C][C]1.08703[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]11.2192[/C][C]-0.0191773[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]14.2606[/C][C]-2.8606[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]5.11405[/C][C]3.48595[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]10.5746[/C][C]2.62541[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]16.45[/C][C]-3.84997[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]4.64048[/C][C]0.959522[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]11.8258[/C][C]-1.92579[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]10.0769[/C][C]-1.27689[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]8.95817[/C][C]-1.25817[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]11.5488[/C][C]-2.54879[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]6.53124[/C][C]0.768764[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]7.91389[/C][C]3.48611[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]15.7072[/C][C]-2.10716[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]7.60813[/C][C]0.291867[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]11.8958[/C][C]-1.19585[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]11.3745[/C][C]-1.07449[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]7.93312[/C][C]0.366882[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]4.77047[/C][C]4.82953[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]16.4261[/C][C]-2.22608[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]4.95512[/C][C]3.54488[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]19.6991[/C][C]-6.1991[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]9.60593[/C][C]-4.70593[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]6.94404[/C][C]-0.544038[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]9.28355[/C][C]0.316452[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]10.0665[/C][C]1.53352[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]20.6679[/C][C]-9.56789[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]6.40986[/C][C]-2.05986[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]9.17143[/C][C]3.52857[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]15.7299[/C][C]2.37012[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]16.5404[/C][C]1.30964[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]16.8005[/C][C]-0.200527[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]10.3629[/C][C]2.23706[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]14.0721[/C][C]3.0279[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]17.5297[/C][C]1.57029[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]17.571[/C][C]-1.47098[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]10.1465[/C][C]3.20346[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]18.4111[/C][C]-0.0110556[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]18.1581[/C][C]-3.45807[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]11.3366[/C][C]-0.736578[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]10.2334[/C][C]2.36662[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]16.1451[/C][C]0.0548512[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]8.58839[/C][C]5.01161[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]19.636[/C][C]-0.735979[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]14.8639[/C][C]-0.763907[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]13.7499[/C][C]0.750091[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]15.6415[/C][C]0.508524[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.905[/C][C]0.845004[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]17.3936[/C][C]-2.59363[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]13.6115[/C][C]-1.16148[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]10.0234[/C][C]2.62655[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]23.75[/C][C]-6.39996[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]5.8988[/C][C]2.7012[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]17.2094[/C][C]1.19063[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]18.5613[/C][C]-2.46129[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]8.19287[/C][C]3.40713[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]15.8533[/C][C]1.89671[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]12.2419[/C][C]3.00811[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]16.3506[/C][C]1.29943[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]14.6241[/C][C]1.72592[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]17.1833[/C][C]0.466699[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]14.3781[/C][C]-0.778149[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]14.2685[/C][C]0.0815292[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]11.7697[/C][C]2.9803[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]23.3927[/C][C]-5.14274[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]9.35517[/C][C]0.544829[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]12.4246[/C][C]3.57536[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]16.1865[/C][C]2.06349[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]16.8078[/C][C]0.0422408[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]13.9567[/C][C]0.643266[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]10.2706[/C][C]3.57936[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]18.878[/C][C]0.0720138[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]15.4547[/C][C]0.145252[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]18.2527[/C][C]-3.40268[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]8.58162[/C][C]3.16838[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]16.1937[/C][C]2.25627[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]14.9402[/C][C]0.959773[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]16.1228[/C][C]0.977176[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]11.999[/C][C]4.10104[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]22.5934[/C][C]-2.6934[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]7.60027[/C][C]3.34973[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]18.3051[/C][C]0.144929[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]15.341[/C][C]-0.241028[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]18.3208[/C][C]-3.32083[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]9.44915[/C][C]1.90085[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]12.6886[/C][C]3.26143[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]18.1953[/C][C]-0.0953058[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]14.0666[/C][C]0.533404[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]14.8666[/C][C]0.533404[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]11.1371[/C][C]4.26287[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]18.5623[/C][C]-0.962257[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]9.08417[/C][C]4.26583[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]17.7225[/C][C]1.37754[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]22.4961[/C][C]-7.14609[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]9.42075[/C][C]-1.82075[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]14.0121[/C][C]-0.61214[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]10.1332[/C][C]3.76681[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]18.4839[/C][C]0.616147[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]16.6238[/C][C]-1.37384[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]12.0477[/C][C]0.852285[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]13.9977[/C][C]2.10229[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]19.4477[/C][C]-2.09771[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]16.0682[/C][C]-2.91816[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]12.8315[/C][C]-0.681473[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]16.0744[/C][C]-3.47445[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]8.15785[/C][C]2.19215[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]19.4586[/C][C]-4.05863[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]5.35398[/C][C]4.24602[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]18.4516[/C][C]-0.251644[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]13.3396[/C][C]0.260391[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]15.5769[/C][C]-0.726908[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]14.422[/C][C]0.328036[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]13.3219[/C][C]0.778051[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]12.9184[/C][C]1.98162[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]11.5297[/C][C]4.72029[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]18.8818[/C][C]0.368249[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]14.7249[/C][C]-1.12492[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]13.4108[/C][C]0.189154[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]17.321[/C][C]-1.67103[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]13.3219[/C][C]-0.571937[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]18.5131[/C][C]-3.91306[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]10.8361[/C][C]-0.98615[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]6.68909[/C][C]5.96091[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]16.2424[/C][C]2.95764[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]19.9271[/C][C]-3.32714[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]10.3996[/C][C]0.800391[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]18.1648[/C][C]-2.91479[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]12.8147[/C][C]-0.914709[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]12.26[/C][C]0.939985[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]17.1241[/C][C]-0.774062[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]10.1617[/C][C]2.23825[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]12.8248[/C][C]3.02523[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]21.0517[/C][C]-2.90166[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]10.6636[/C][C]0.486355[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]12.5885[/C][C]3.06149[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]23.9553[/C][C]-6.2053[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]10.021[/C][C]-2.37095[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]10.3278[/C][C]2.02218[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]12.153[/C][C]3.44697[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]19.058[/C][C]0.241968[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]13.1751[/C][C]2.02486[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]15.8004[/C][C]1.29963[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]12.2106[/C][C]3.38935[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]14.9095[/C][C]3.49049[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]15.1655[/C][C]3.88447[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]14.9256[/C][C]3.62444[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]19.8973[/C][C]-0.797267[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]14.887[/C][C]-1.787[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]16.8828[/C][C]-4.03284[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]19.8906[/C][C]-10.3906[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]7.01638[/C][C]-2.51638[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]12.0621[/C][C]-0.21206[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]15.2533[/C][C]-1.65329[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]12.8087[/C][C]-1.10868[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]14.7882[/C][C]-2.38816[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]15.8542[/C][C]-2.50419[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]10.1822[/C][C]1.2178[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]10.799[/C][C]4.10104[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]22.3085[/C][C]-2.40848[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]9.90946[/C][C]1.29054[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]12.0081[/C][C]2.59189[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]18.2291[/C][C]-0.629071[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]12.9554[/C][C]1.09458[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]16.6158[/C][C]-0.515789[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]15.5159[/C][C]-2.16589[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]15.8605[/C][C]-4.01049[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]11.4678[/C][C]0.482188[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]13.9131[/C][C]0.836906[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]16.7438[/C][C]-1.59377[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]11.4069[/C][C]1.79309[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]22.8739[/C][C]-6.02389[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]16.1355[/C][C]-8.28552[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]9.36349[/C][C]-1.66349[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]17.1624[/C][C]-4.5624[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]10.5434[/C][C]-2.6934[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]13.8365[/C][C]-2.88647[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]15.7826[/C][C]-3.43257[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]8.7322[/C][C]1.2178[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]13.2231[/C][C]1.67688[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]17.6972[/C][C]-1.04717[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]14.6697[/C][C]-1.26971[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]11.605[/C][C]2.34501[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]13.4873[/C][C]2.21273[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]20.4674[/C][C]-3.6174[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]9.93838[/C][C]1.01162[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]17.3084[/C][C]-1.95838[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]10.5129[/C][C]1.68715[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]12.3071[/C][C]2.79287[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]16.2338[/C][C]1.51619[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]16.6287[/C][C]-1.42875[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]12.908[/C][C]1.69197[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]22.7545[/C][C]-6.10445[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267922&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267922&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
112.912.13490.765095
212.210.48671.71332
312.811.76071.03931
47.410.3043-2.90429
56.710.3195-3.61952
612.610.26712.33285
714.812.46722.33276
813.311.34681.95316
911.110.49260.607412
108.210.8794-2.6794
1111.411.33250.0674933
126.410.2807-3.88072
1310.610.37620.223791
141211.77770.222265
156.311.8033-5.50333
1611.311.337-0.0369996
1711.910.74291.1571
189.311.1929-1.89287
199.69.70236-0.102357
201010.9325-0.932468
216.410.7217-4.32172
2213.810.18343.61665
2310.811.1423-0.342272
2413.810.33483.46521
2511.711.48060.21935
2610.99.504871.39513
2716.110.03136.06871
2813.411.27812.12191
299.910.9889-1.08891
3011.511.7-0.200014
318.310.8614-2.56143
3211.711.30030.39968
33910.9997-1.99971
349.711.1115-1.41146
3510.810.9564-0.156352
3610.311.3267-1.0267
3710.410.9678-0.567836
3812.79.792332.90767
399.311.0783-1.77833
4011.811.9126-0.112578
415.910.8566-4.95657
4211.410.88910.510871
431310.44452.55553
4410.811.1685-0.36847
4512.39.602892.69711
4611.312.3906-1.09057
4711.89.985141.81486
487.99.49038-1.59038
4912.711.01981.68017
5012.310.25882.04118
5111.610.66190.938147
526.79.26373-2.56373
5310.911.0548-0.154759
5412.19.550032.54997
5513.310.41652.88353
5610.111.257-1.15698
575.711.2396-5.53962
5814.39.778814.52119
59810.3018-2.30183
6013.310.17843.12158
619.311.404-2.10398
6212.510.96971.53033
637.612.06-4.46001
6415.911.1064.794
659.211.3003-2.10032
669.110.3593-1.25932
6711.111.9263-0.826323
681310.92262.0774
6914.511.16223.33776
7012.210.40521.79485
7112.311.51010.789876
7211.411.9918-0.591759
738.811.0946-2.29455
7414.610.15034.4497
7512.611.33571.26431
76NANA1.0689
771310.91332.08674
7812.611.00871.59133
7913.213.367-0.167034
809.912.2981-2.3981
817.78.3471-0.647099
8210.57.553722.94628
8313.413.6034-0.203426
8410.915.9684-5.06841
854.34.63726-0.337256
8610.38.158552.14145
8711.810.7131.08703
8811.211.2192-0.0191773
8911.414.2606-2.8606
908.65.114053.48595
9113.210.57462.62541
9212.616.45-3.84997
935.64.640480.959522
949.911.8258-1.92579
958.810.0769-1.27689
967.78.95817-1.25817
97911.5488-2.54879
987.36.531240.768764
9911.47.913893.48611
10013.615.7072-2.10716
1017.97.608130.291867
10210.711.8958-1.19585
10310.311.3745-1.07449
1048.37.933120.366882
1059.64.770474.82953
10614.216.4261-2.22608
1078.54.955123.54488
10813.519.6991-6.1991
1094.99.60593-4.70593
1106.46.94404-0.544038
1119.69.283550.316452
11211.610.06651.53352
11311.120.6679-9.56789
1144.356.40986-2.05986
11512.79.171433.52857
11618.115.72992.37012
11717.8516.54041.30964
11816.616.8005-0.200527
11912.610.36292.23706
12017.114.07213.0279
12119.117.52971.57029
12216.117.571-1.47098
12313.3510.14653.20346
12418.418.4111-0.0110556
12514.718.1581-3.45807
12610.611.3366-0.736578
12712.610.23342.36662
12816.216.14510.0548512
12913.68.588395.01161
13018.919.636-0.735979
13114.114.8639-0.763907
13214.513.74990.750091
13316.1515.64150.508524
13414.7513.9050.845004
13514.817.3936-2.59363
13612.4513.6115-1.16148
13712.6510.02342.62655
13817.3523.75-6.39996
1398.65.89882.7012
14018.417.20941.19063
14116.118.5613-2.46129
14211.68.192873.40713
14317.7515.85331.89671
14415.2512.24193.00811
14517.6516.35061.29943
14616.3514.62411.72592
14717.6517.18330.466699
14813.614.3781-0.778149
14914.3514.26850.0815292
15014.7511.76972.9803
15118.2523.3927-5.14274
1529.99.355170.544829
1531612.42463.57536
15418.2516.18652.06349
15516.8516.80780.0422408
15614.613.95670.643266
15713.8510.27063.57936
15818.9518.8780.0720138
15915.615.45470.145252
16014.8518.2527-3.40268
16111.758.581623.16838
16218.4516.19372.25627
16315.914.94020.959773
16417.116.12280.977176
16516.111.9994.10104
16619.922.5934-2.6934
16710.957.600273.34973
16818.4518.30510.144929
16915.115.341-0.241028
1701518.3208-3.32083
17111.359.449151.90085
17215.9512.68863.26143
17318.118.1953-0.0953058
17414.614.06660.533404
17515.414.86660.533404
17615.411.13714.26287
17717.618.5623-0.962257
17813.359.084174.26583
17919.117.72251.37754
18015.3522.4961-7.14609
1817.69.42075-1.82075
18213.414.0121-0.61214
18313.910.13323.76681
18419.118.48390.616147
18515.2516.6238-1.37384
18612.912.04770.852285
18716.113.99772.10229
18817.3519.4477-2.09771
18913.1516.0682-2.91816
19012.1512.8315-0.681473
19112.616.0744-3.47445
19210.358.157852.19215
19315.419.4586-4.05863
1949.65.353984.24602
19518.218.4516-0.251644
19613.613.33960.260391
19714.8515.5769-0.726908
19814.7514.4220.328036
19914.113.32190.778051
20014.912.91841.98162
20116.2511.52974.72029
20219.2518.88180.368249
20313.614.7249-1.12492
20413.613.41080.189154
20515.6517.321-1.67103
20612.7513.3219-0.571937
20714.618.5131-3.91306
2089.8510.8361-0.98615
20912.656.689095.96091
21019.216.24242.95764
21116.619.9271-3.32714
21211.210.39960.800391
21315.2518.1648-2.91479
21411.912.8147-0.914709
21513.212.260.939985
21616.3517.1241-0.774062
21712.410.16172.23825
21815.8512.82483.02523
21918.1521.0517-2.90166
22011.1510.66360.486355
22115.6512.58853.06149
22217.7523.9553-6.2053
2237.6510.021-2.37095
22412.3510.32782.02218
22515.612.1533.44697
22619.319.0580.241968
22715.213.17512.02486
22817.115.80041.29963
22915.612.21063.38935
23018.414.90953.49049
23119.0515.16553.88447
23218.5514.92563.62444
23319.119.8973-0.797267
23413.114.887-1.787
23512.8516.8828-4.03284
2369.519.8906-10.3906
2374.57.01638-2.51638
23811.8512.0621-0.21206
23913.615.2533-1.65329
24011.712.8087-1.10868
24112.414.7882-2.38816
24213.3515.8542-2.50419
24311.410.18221.2178
24414.910.7994.10104
24519.922.3085-2.40848
24611.29.909461.29054
24714.612.00812.59189
24817.618.2291-0.629071
24914.0512.95541.09458
25016.116.6158-0.515789
25113.3515.5159-2.16589
25211.8515.8605-4.01049
25311.9511.46780.482188
25414.7513.91310.836906
25515.1516.7438-1.59377
25613.211.40691.79309
25716.8522.8739-6.02389
2587.8516.1355-8.28552
2597.79.36349-1.66349
26012.617.1624-4.5624
2617.8510.5434-2.6934
26210.9513.8365-2.88647
26312.3515.7826-3.43257
2649.958.73221.2178
26514.913.22311.67688
26616.6517.6972-1.04717
26713.414.6697-1.26971
26813.9511.6052.34501
26915.713.48732.21273
27016.8520.4674-3.6174
27110.959.938381.01162
27215.3517.3084-1.95838
27312.210.51291.68715
27415.112.30712.79287
27517.7516.23381.51619
27615.216.6287-1.42875
27714.612.9081.69197
27816.6522.7545-6.10445
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.8462370.3075260.153763
140.7431020.5137970.256898
150.8658560.2682870.134144
160.7905490.4189010.209451
170.7102970.5794060.289703
180.6341870.7316260.365813
190.5363680.9272640.463632
200.4399290.8798570.560071
210.4591040.9182090.540896
220.5907460.8185080.409254
230.5138090.9723830.486191
240.4932130.9864260.506787
250.4219890.8439770.578011
260.4889960.9779930.511004
270.5699530.8600940.430047
280.5022490.9955020.497751
290.5103720.9792570.489628
300.4430040.8860070.556996
310.4072290.8144580.592771
320.3475430.6950860.652457
330.3339930.6679860.666007
340.291550.5830990.70845
350.2405970.4811940.759403
360.2148150.429630.785185
370.1866540.3733080.813346
380.1546810.3093620.845319
390.1358590.2717180.864141
400.1069540.2139080.893046
410.1833970.3667930.816603
420.1484410.2968830.851559
430.1386850.2773710.861315
440.111240.2224810.88876
450.08987860.1797570.910121
460.07159920.1431980.928401
470.06149350.1229870.938506
480.1025240.2050480.897476
490.09436370.1887270.905636
500.07613710.1522740.923863
510.06104240.1220850.938958
520.07833890.1566780.921661
530.06223540.1244710.937765
540.0529670.1059340.947033
550.06363210.1272640.936368
560.05449060.1089810.945509
570.1285570.2571140.871443
580.1761660.3523320.823834
590.1578340.3156680.842166
600.1467740.2935490.853226
610.1377750.275550.862225
620.1188310.2376620.881169
630.1278050.255610.872195
640.1900710.3801420.809929
650.1787830.3575660.821217
660.1613120.3226240.838688
670.1388610.2777230.861139
680.1255870.2511730.874413
690.1692970.3385950.830703
700.1561990.3123970.843801
710.1353430.2706870.864657
720.1142660.2285330.885734
730.1092940.2185880.890706
740.1299910.2599820.870009
750.1181190.2362390.881881
760.1025560.2051110.897444
770.09023550.1804710.909764
780.08302110.1660420.916979
790.06845690.1369140.931543
800.06916170.1383230.930838
810.05729020.114580.94271
820.0571870.1143740.942813
830.04653040.09306080.95347
840.09463480.189270.905365
850.07972160.1594430.920278
860.07036060.1407210.929639
870.05918910.1183780.940811
880.04849580.09699150.951504
890.04909860.09819720.950901
900.05627450.1125490.943725
910.05442980.108860.94557
920.06889180.1377840.931108
930.05883880.1176780.941161
940.05194560.1038910.948054
950.04826780.09653550.951732
960.04284770.08569540.957152
970.04651510.09303010.953485
980.03851320.07702640.961487
990.04337440.08674880.956626
1000.03987520.07975030.960125
1010.03271990.06543980.96728
1020.02713630.05427260.972864
1030.02498330.04996670.975017
1040.02047690.04095370.979523
1050.03251170.06502330.967488
1060.02933760.05867530.970662
1070.04170220.08340430.958298
1080.07412130.1482430.925879
1090.09735710.1947140.902643
1100.08335440.1667090.916646
1110.07161130.1432230.928389
1120.06249750.1249950.937503
1130.1012950.202590.898705
1140.1489610.2979220.851039
1150.2595950.5191890.740405
1160.2876070.5752140.712393
1170.2835060.5670130.716494
1180.2548410.5096830.745159
1190.2483730.4967460.751627
1200.2639530.5279070.736047
1210.2426910.4853820.757309
1220.2237950.447590.776205
1230.2354620.4709250.764538
1240.2099650.4199310.790035
1250.2271860.4543720.772814
1260.2029760.4059510.797024
1270.1976090.3952180.802391
1280.1743550.348710.825645
1290.2242330.4484670.775767
1300.2016330.4032670.798367
1310.1811890.3623770.818811
1320.1620850.324170.837915
1330.1416040.2832080.858396
1340.1266260.2532510.873374
1350.1284510.2569020.871549
1360.1146070.2292130.885393
1370.112070.2241390.88793
1380.2154910.4309810.784509
1390.212130.424260.78787
1400.1906140.3812280.809386
1410.1889250.3778510.811075
1420.2011080.4022170.798892
1430.1876860.3753720.812314
1440.1897650.379530.810235
1450.1717370.3434750.828263
1460.1563320.3126630.843668
1470.1367880.2735750.863212
1480.1199830.2399670.880017
1490.104060.208120.89594
1500.1031280.2062570.896872
1510.14850.2970.8515
1520.1298820.2597640.870118
1530.1410520.2821040.858948
1540.1332140.2664270.866786
1550.1160560.2321130.883944
1560.1043280.2086550.895672
1570.1143540.2287090.885646
1580.09817740.1963550.901823
1590.08372370.1674470.916276
1600.09952710.1990540.900473
1610.09939310.1987860.900607
1620.0929070.1858140.907093
1630.0803830.1607660.919617
1640.06926170.1385230.930738
1650.07684480.153690.923155
1660.0768430.1536860.923157
1670.08044550.1608910.919555
1680.06830110.1366020.931699
1690.05783350.1156670.942166
1700.06706020.134120.93294
1710.06301750.1260350.936983
1720.06579550.1315910.934204
1730.05738040.1147610.94262
1740.04865260.09730520.951347
1750.0411390.0822780.958861
1760.05774830.1154970.942252
1770.04968050.09936110.950319
1780.06958670.1391730.930413
1790.06756880.1351380.932431
1800.1854980.3709970.814502
1810.1739370.3478730.826063
1820.1523080.3046160.847692
1830.1695830.3391650.830417
1840.1516580.3033160.848342
1850.1364130.2728270.863587
1860.1207350.241470.879265
1870.1162670.2325330.883733
1880.1101420.2202830.889858
1890.1151680.2303360.884832
1900.1073940.2147880.892606
1910.1134390.2268780.886561
1920.1029550.2059110.897045
1930.1271960.2543920.872804
1940.1499070.2998150.850093
1950.1342880.2685760.865712
1960.1174850.2349710.882515
1970.1001780.2003550.899822
1980.08504790.1700960.914952
1990.07126470.1425290.928735
2000.06315260.1263050.936847
2010.1200230.2400470.879977
2020.1071140.2142270.892886
2030.09494780.1898960.905052
2040.07927620.1585520.920724
2050.06921550.1384310.930785
2060.05823360.1164670.941766
2070.06028540.1205710.939715
2080.0502450.100490.949755
2090.06977860.1395570.930221
2100.07220390.1444080.927796
2110.07040.14080.9296
2120.06380490.127610.936195
2130.0673280.1346560.932672
2140.05519890.1103980.944801
2150.04620830.09241660.953792
2160.03902720.07805450.960973
2170.04073750.0814750.959262
2180.04645540.09291080.953545
2190.04154540.08309080.958455
2200.03367050.06734090.96633
2210.03344350.06688710.966556
2220.1580160.3160310.841984
2230.138220.276440.86178
2240.1247120.2494240.875288
2250.111810.223620.88819
2260.09208750.1841750.907913
2270.07671440.1534290.923286
2280.06766680.1353340.932333
2290.1389670.2779340.861033
2300.1573930.3147860.842607
2310.2083250.4166490.791675
2320.2336610.4673220.766339
2330.198020.396040.80198
2340.1715470.3430950.828453
2350.1572160.3144310.842784
2360.4678150.9356310.532185
2370.4453110.8906220.554689
2380.4063890.8127790.593611
2390.3609280.7218560.639072
2400.319930.639860.68007
2410.3031640.6063270.696836
2420.2913070.5826150.708693
2430.2757310.5514610.724269
2440.3192620.6385230.680738
2450.2890340.5780680.710966
2460.2578660.5157320.742134
2470.260660.5213210.73934
2480.302960.605920.69704
2490.2927350.5854690.707265
2500.2627350.525470.737265
2510.2911440.5822870.708856
2520.2509470.5018940.749053
2530.2191440.4382880.780856
2540.1699370.3398740.830063
2550.3100960.6201920.689904
2560.2453240.4906490.754676
2570.442970.885940.55703
2580.4094870.8189730.590513
2590.3592550.718510.640745
2600.4116880.8233760.588312
2610.3872010.7744020.612799
2620.6790610.6418790.320939
2630.5971660.8056670.402834
2640.4676580.9353150.532342
2650.3120160.6240330.687984
2660.2556680.5113350.744332

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.846237 & 0.307526 & 0.153763 \tabularnewline
14 & 0.743102 & 0.513797 & 0.256898 \tabularnewline
15 & 0.865856 & 0.268287 & 0.134144 \tabularnewline
16 & 0.790549 & 0.418901 & 0.209451 \tabularnewline
17 & 0.710297 & 0.579406 & 0.289703 \tabularnewline
18 & 0.634187 & 0.731626 & 0.365813 \tabularnewline
19 & 0.536368 & 0.927264 & 0.463632 \tabularnewline
20 & 0.439929 & 0.879857 & 0.560071 \tabularnewline
21 & 0.459104 & 0.918209 & 0.540896 \tabularnewline
22 & 0.590746 & 0.818508 & 0.409254 \tabularnewline
23 & 0.513809 & 0.972383 & 0.486191 \tabularnewline
24 & 0.493213 & 0.986426 & 0.506787 \tabularnewline
25 & 0.421989 & 0.843977 & 0.578011 \tabularnewline
26 & 0.488996 & 0.977993 & 0.511004 \tabularnewline
27 & 0.569953 & 0.860094 & 0.430047 \tabularnewline
28 & 0.502249 & 0.995502 & 0.497751 \tabularnewline
29 & 0.510372 & 0.979257 & 0.489628 \tabularnewline
30 & 0.443004 & 0.886007 & 0.556996 \tabularnewline
31 & 0.407229 & 0.814458 & 0.592771 \tabularnewline
32 & 0.347543 & 0.695086 & 0.652457 \tabularnewline
33 & 0.333993 & 0.667986 & 0.666007 \tabularnewline
34 & 0.29155 & 0.583099 & 0.70845 \tabularnewline
35 & 0.240597 & 0.481194 & 0.759403 \tabularnewline
36 & 0.214815 & 0.42963 & 0.785185 \tabularnewline
37 & 0.186654 & 0.373308 & 0.813346 \tabularnewline
38 & 0.154681 & 0.309362 & 0.845319 \tabularnewline
39 & 0.135859 & 0.271718 & 0.864141 \tabularnewline
40 & 0.106954 & 0.213908 & 0.893046 \tabularnewline
41 & 0.183397 & 0.366793 & 0.816603 \tabularnewline
42 & 0.148441 & 0.296883 & 0.851559 \tabularnewline
43 & 0.138685 & 0.277371 & 0.861315 \tabularnewline
44 & 0.11124 & 0.222481 & 0.88876 \tabularnewline
45 & 0.0898786 & 0.179757 & 0.910121 \tabularnewline
46 & 0.0715992 & 0.143198 & 0.928401 \tabularnewline
47 & 0.0614935 & 0.122987 & 0.938506 \tabularnewline
48 & 0.102524 & 0.205048 & 0.897476 \tabularnewline
49 & 0.0943637 & 0.188727 & 0.905636 \tabularnewline
50 & 0.0761371 & 0.152274 & 0.923863 \tabularnewline
51 & 0.0610424 & 0.122085 & 0.938958 \tabularnewline
52 & 0.0783389 & 0.156678 & 0.921661 \tabularnewline
53 & 0.0622354 & 0.124471 & 0.937765 \tabularnewline
54 & 0.052967 & 0.105934 & 0.947033 \tabularnewline
55 & 0.0636321 & 0.127264 & 0.936368 \tabularnewline
56 & 0.0544906 & 0.108981 & 0.945509 \tabularnewline
57 & 0.128557 & 0.257114 & 0.871443 \tabularnewline
58 & 0.176166 & 0.352332 & 0.823834 \tabularnewline
59 & 0.157834 & 0.315668 & 0.842166 \tabularnewline
60 & 0.146774 & 0.293549 & 0.853226 \tabularnewline
61 & 0.137775 & 0.27555 & 0.862225 \tabularnewline
62 & 0.118831 & 0.237662 & 0.881169 \tabularnewline
63 & 0.127805 & 0.25561 & 0.872195 \tabularnewline
64 & 0.190071 & 0.380142 & 0.809929 \tabularnewline
65 & 0.178783 & 0.357566 & 0.821217 \tabularnewline
66 & 0.161312 & 0.322624 & 0.838688 \tabularnewline
67 & 0.138861 & 0.277723 & 0.861139 \tabularnewline
68 & 0.125587 & 0.251173 & 0.874413 \tabularnewline
69 & 0.169297 & 0.338595 & 0.830703 \tabularnewline
70 & 0.156199 & 0.312397 & 0.843801 \tabularnewline
71 & 0.135343 & 0.270687 & 0.864657 \tabularnewline
72 & 0.114266 & 0.228533 & 0.885734 \tabularnewline
73 & 0.109294 & 0.218588 & 0.890706 \tabularnewline
74 & 0.129991 & 0.259982 & 0.870009 \tabularnewline
75 & 0.118119 & 0.236239 & 0.881881 \tabularnewline
76 & 0.102556 & 0.205111 & 0.897444 \tabularnewline
77 & 0.0902355 & 0.180471 & 0.909764 \tabularnewline
78 & 0.0830211 & 0.166042 & 0.916979 \tabularnewline
79 & 0.0684569 & 0.136914 & 0.931543 \tabularnewline
80 & 0.0691617 & 0.138323 & 0.930838 \tabularnewline
81 & 0.0572902 & 0.11458 & 0.94271 \tabularnewline
82 & 0.057187 & 0.114374 & 0.942813 \tabularnewline
83 & 0.0465304 & 0.0930608 & 0.95347 \tabularnewline
84 & 0.0946348 & 0.18927 & 0.905365 \tabularnewline
85 & 0.0797216 & 0.159443 & 0.920278 \tabularnewline
86 & 0.0703606 & 0.140721 & 0.929639 \tabularnewline
87 & 0.0591891 & 0.118378 & 0.940811 \tabularnewline
88 & 0.0484958 & 0.0969915 & 0.951504 \tabularnewline
89 & 0.0490986 & 0.0981972 & 0.950901 \tabularnewline
90 & 0.0562745 & 0.112549 & 0.943725 \tabularnewline
91 & 0.0544298 & 0.10886 & 0.94557 \tabularnewline
92 & 0.0688918 & 0.137784 & 0.931108 \tabularnewline
93 & 0.0588388 & 0.117678 & 0.941161 \tabularnewline
94 & 0.0519456 & 0.103891 & 0.948054 \tabularnewline
95 & 0.0482678 & 0.0965355 & 0.951732 \tabularnewline
96 & 0.0428477 & 0.0856954 & 0.957152 \tabularnewline
97 & 0.0465151 & 0.0930301 & 0.953485 \tabularnewline
98 & 0.0385132 & 0.0770264 & 0.961487 \tabularnewline
99 & 0.0433744 & 0.0867488 & 0.956626 \tabularnewline
100 & 0.0398752 & 0.0797503 & 0.960125 \tabularnewline
101 & 0.0327199 & 0.0654398 & 0.96728 \tabularnewline
102 & 0.0271363 & 0.0542726 & 0.972864 \tabularnewline
103 & 0.0249833 & 0.0499667 & 0.975017 \tabularnewline
104 & 0.0204769 & 0.0409537 & 0.979523 \tabularnewline
105 & 0.0325117 & 0.0650233 & 0.967488 \tabularnewline
106 & 0.0293376 & 0.0586753 & 0.970662 \tabularnewline
107 & 0.0417022 & 0.0834043 & 0.958298 \tabularnewline
108 & 0.0741213 & 0.148243 & 0.925879 \tabularnewline
109 & 0.0973571 & 0.194714 & 0.902643 \tabularnewline
110 & 0.0833544 & 0.166709 & 0.916646 \tabularnewline
111 & 0.0716113 & 0.143223 & 0.928389 \tabularnewline
112 & 0.0624975 & 0.124995 & 0.937503 \tabularnewline
113 & 0.101295 & 0.20259 & 0.898705 \tabularnewline
114 & 0.148961 & 0.297922 & 0.851039 \tabularnewline
115 & 0.259595 & 0.519189 & 0.740405 \tabularnewline
116 & 0.287607 & 0.575214 & 0.712393 \tabularnewline
117 & 0.283506 & 0.567013 & 0.716494 \tabularnewline
118 & 0.254841 & 0.509683 & 0.745159 \tabularnewline
119 & 0.248373 & 0.496746 & 0.751627 \tabularnewline
120 & 0.263953 & 0.527907 & 0.736047 \tabularnewline
121 & 0.242691 & 0.485382 & 0.757309 \tabularnewline
122 & 0.223795 & 0.44759 & 0.776205 \tabularnewline
123 & 0.235462 & 0.470925 & 0.764538 \tabularnewline
124 & 0.209965 & 0.419931 & 0.790035 \tabularnewline
125 & 0.227186 & 0.454372 & 0.772814 \tabularnewline
126 & 0.202976 & 0.405951 & 0.797024 \tabularnewline
127 & 0.197609 & 0.395218 & 0.802391 \tabularnewline
128 & 0.174355 & 0.34871 & 0.825645 \tabularnewline
129 & 0.224233 & 0.448467 & 0.775767 \tabularnewline
130 & 0.201633 & 0.403267 & 0.798367 \tabularnewline
131 & 0.181189 & 0.362377 & 0.818811 \tabularnewline
132 & 0.162085 & 0.32417 & 0.837915 \tabularnewline
133 & 0.141604 & 0.283208 & 0.858396 \tabularnewline
134 & 0.126626 & 0.253251 & 0.873374 \tabularnewline
135 & 0.128451 & 0.256902 & 0.871549 \tabularnewline
136 & 0.114607 & 0.229213 & 0.885393 \tabularnewline
137 & 0.11207 & 0.224139 & 0.88793 \tabularnewline
138 & 0.215491 & 0.430981 & 0.784509 \tabularnewline
139 & 0.21213 & 0.42426 & 0.78787 \tabularnewline
140 & 0.190614 & 0.381228 & 0.809386 \tabularnewline
141 & 0.188925 & 0.377851 & 0.811075 \tabularnewline
142 & 0.201108 & 0.402217 & 0.798892 \tabularnewline
143 & 0.187686 & 0.375372 & 0.812314 \tabularnewline
144 & 0.189765 & 0.37953 & 0.810235 \tabularnewline
145 & 0.171737 & 0.343475 & 0.828263 \tabularnewline
146 & 0.156332 & 0.312663 & 0.843668 \tabularnewline
147 & 0.136788 & 0.273575 & 0.863212 \tabularnewline
148 & 0.119983 & 0.239967 & 0.880017 \tabularnewline
149 & 0.10406 & 0.20812 & 0.89594 \tabularnewline
150 & 0.103128 & 0.206257 & 0.896872 \tabularnewline
151 & 0.1485 & 0.297 & 0.8515 \tabularnewline
152 & 0.129882 & 0.259764 & 0.870118 \tabularnewline
153 & 0.141052 & 0.282104 & 0.858948 \tabularnewline
154 & 0.133214 & 0.266427 & 0.866786 \tabularnewline
155 & 0.116056 & 0.232113 & 0.883944 \tabularnewline
156 & 0.104328 & 0.208655 & 0.895672 \tabularnewline
157 & 0.114354 & 0.228709 & 0.885646 \tabularnewline
158 & 0.0981774 & 0.196355 & 0.901823 \tabularnewline
159 & 0.0837237 & 0.167447 & 0.916276 \tabularnewline
160 & 0.0995271 & 0.199054 & 0.900473 \tabularnewline
161 & 0.0993931 & 0.198786 & 0.900607 \tabularnewline
162 & 0.092907 & 0.185814 & 0.907093 \tabularnewline
163 & 0.080383 & 0.160766 & 0.919617 \tabularnewline
164 & 0.0692617 & 0.138523 & 0.930738 \tabularnewline
165 & 0.0768448 & 0.15369 & 0.923155 \tabularnewline
166 & 0.076843 & 0.153686 & 0.923157 \tabularnewline
167 & 0.0804455 & 0.160891 & 0.919555 \tabularnewline
168 & 0.0683011 & 0.136602 & 0.931699 \tabularnewline
169 & 0.0578335 & 0.115667 & 0.942166 \tabularnewline
170 & 0.0670602 & 0.13412 & 0.93294 \tabularnewline
171 & 0.0630175 & 0.126035 & 0.936983 \tabularnewline
172 & 0.0657955 & 0.131591 & 0.934204 \tabularnewline
173 & 0.0573804 & 0.114761 & 0.94262 \tabularnewline
174 & 0.0486526 & 0.0973052 & 0.951347 \tabularnewline
175 & 0.041139 & 0.082278 & 0.958861 \tabularnewline
176 & 0.0577483 & 0.115497 & 0.942252 \tabularnewline
177 & 0.0496805 & 0.0993611 & 0.950319 \tabularnewline
178 & 0.0695867 & 0.139173 & 0.930413 \tabularnewline
179 & 0.0675688 & 0.135138 & 0.932431 \tabularnewline
180 & 0.185498 & 0.370997 & 0.814502 \tabularnewline
181 & 0.173937 & 0.347873 & 0.826063 \tabularnewline
182 & 0.152308 & 0.304616 & 0.847692 \tabularnewline
183 & 0.169583 & 0.339165 & 0.830417 \tabularnewline
184 & 0.151658 & 0.303316 & 0.848342 \tabularnewline
185 & 0.136413 & 0.272827 & 0.863587 \tabularnewline
186 & 0.120735 & 0.24147 & 0.879265 \tabularnewline
187 & 0.116267 & 0.232533 & 0.883733 \tabularnewline
188 & 0.110142 & 0.220283 & 0.889858 \tabularnewline
189 & 0.115168 & 0.230336 & 0.884832 \tabularnewline
190 & 0.107394 & 0.214788 & 0.892606 \tabularnewline
191 & 0.113439 & 0.226878 & 0.886561 \tabularnewline
192 & 0.102955 & 0.205911 & 0.897045 \tabularnewline
193 & 0.127196 & 0.254392 & 0.872804 \tabularnewline
194 & 0.149907 & 0.299815 & 0.850093 \tabularnewline
195 & 0.134288 & 0.268576 & 0.865712 \tabularnewline
196 & 0.117485 & 0.234971 & 0.882515 \tabularnewline
197 & 0.100178 & 0.200355 & 0.899822 \tabularnewline
198 & 0.0850479 & 0.170096 & 0.914952 \tabularnewline
199 & 0.0712647 & 0.142529 & 0.928735 \tabularnewline
200 & 0.0631526 & 0.126305 & 0.936847 \tabularnewline
201 & 0.120023 & 0.240047 & 0.879977 \tabularnewline
202 & 0.107114 & 0.214227 & 0.892886 \tabularnewline
203 & 0.0949478 & 0.189896 & 0.905052 \tabularnewline
204 & 0.0792762 & 0.158552 & 0.920724 \tabularnewline
205 & 0.0692155 & 0.138431 & 0.930785 \tabularnewline
206 & 0.0582336 & 0.116467 & 0.941766 \tabularnewline
207 & 0.0602854 & 0.120571 & 0.939715 \tabularnewline
208 & 0.050245 & 0.10049 & 0.949755 \tabularnewline
209 & 0.0697786 & 0.139557 & 0.930221 \tabularnewline
210 & 0.0722039 & 0.144408 & 0.927796 \tabularnewline
211 & 0.0704 & 0.1408 & 0.9296 \tabularnewline
212 & 0.0638049 & 0.12761 & 0.936195 \tabularnewline
213 & 0.067328 & 0.134656 & 0.932672 \tabularnewline
214 & 0.0551989 & 0.110398 & 0.944801 \tabularnewline
215 & 0.0462083 & 0.0924166 & 0.953792 \tabularnewline
216 & 0.0390272 & 0.0780545 & 0.960973 \tabularnewline
217 & 0.0407375 & 0.081475 & 0.959262 \tabularnewline
218 & 0.0464554 & 0.0929108 & 0.953545 \tabularnewline
219 & 0.0415454 & 0.0830908 & 0.958455 \tabularnewline
220 & 0.0336705 & 0.0673409 & 0.96633 \tabularnewline
221 & 0.0334435 & 0.0668871 & 0.966556 \tabularnewline
222 & 0.158016 & 0.316031 & 0.841984 \tabularnewline
223 & 0.13822 & 0.27644 & 0.86178 \tabularnewline
224 & 0.124712 & 0.249424 & 0.875288 \tabularnewline
225 & 0.11181 & 0.22362 & 0.88819 \tabularnewline
226 & 0.0920875 & 0.184175 & 0.907913 \tabularnewline
227 & 0.0767144 & 0.153429 & 0.923286 \tabularnewline
228 & 0.0676668 & 0.135334 & 0.932333 \tabularnewline
229 & 0.138967 & 0.277934 & 0.861033 \tabularnewline
230 & 0.157393 & 0.314786 & 0.842607 \tabularnewline
231 & 0.208325 & 0.416649 & 0.791675 \tabularnewline
232 & 0.233661 & 0.467322 & 0.766339 \tabularnewline
233 & 0.19802 & 0.39604 & 0.80198 \tabularnewline
234 & 0.171547 & 0.343095 & 0.828453 \tabularnewline
235 & 0.157216 & 0.314431 & 0.842784 \tabularnewline
236 & 0.467815 & 0.935631 & 0.532185 \tabularnewline
237 & 0.445311 & 0.890622 & 0.554689 \tabularnewline
238 & 0.406389 & 0.812779 & 0.593611 \tabularnewline
239 & 0.360928 & 0.721856 & 0.639072 \tabularnewline
240 & 0.31993 & 0.63986 & 0.68007 \tabularnewline
241 & 0.303164 & 0.606327 & 0.696836 \tabularnewline
242 & 0.291307 & 0.582615 & 0.708693 \tabularnewline
243 & 0.275731 & 0.551461 & 0.724269 \tabularnewline
244 & 0.319262 & 0.638523 & 0.680738 \tabularnewline
245 & 0.289034 & 0.578068 & 0.710966 \tabularnewline
246 & 0.257866 & 0.515732 & 0.742134 \tabularnewline
247 & 0.26066 & 0.521321 & 0.73934 \tabularnewline
248 & 0.30296 & 0.60592 & 0.69704 \tabularnewline
249 & 0.292735 & 0.585469 & 0.707265 \tabularnewline
250 & 0.262735 & 0.52547 & 0.737265 \tabularnewline
251 & 0.291144 & 0.582287 & 0.708856 \tabularnewline
252 & 0.250947 & 0.501894 & 0.749053 \tabularnewline
253 & 0.219144 & 0.438288 & 0.780856 \tabularnewline
254 & 0.169937 & 0.339874 & 0.830063 \tabularnewline
255 & 0.310096 & 0.620192 & 0.689904 \tabularnewline
256 & 0.245324 & 0.490649 & 0.754676 \tabularnewline
257 & 0.44297 & 0.88594 & 0.55703 \tabularnewline
258 & 0.409487 & 0.818973 & 0.590513 \tabularnewline
259 & 0.359255 & 0.71851 & 0.640745 \tabularnewline
260 & 0.411688 & 0.823376 & 0.588312 \tabularnewline
261 & 0.387201 & 0.774402 & 0.612799 \tabularnewline
262 & 0.679061 & 0.641879 & 0.320939 \tabularnewline
263 & 0.597166 & 0.805667 & 0.402834 \tabularnewline
264 & 0.467658 & 0.935315 & 0.532342 \tabularnewline
265 & 0.312016 & 0.624033 & 0.687984 \tabularnewline
266 & 0.255668 & 0.511335 & 0.744332 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267922&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]13[/C][C]0.846237[/C][C]0.307526[/C][C]0.153763[/C][/ROW]
[ROW][C]14[/C][C]0.743102[/C][C]0.513797[/C][C]0.256898[/C][/ROW]
[ROW][C]15[/C][C]0.865856[/C][C]0.268287[/C][C]0.134144[/C][/ROW]
[ROW][C]16[/C][C]0.790549[/C][C]0.418901[/C][C]0.209451[/C][/ROW]
[ROW][C]17[/C][C]0.710297[/C][C]0.579406[/C][C]0.289703[/C][/ROW]
[ROW][C]18[/C][C]0.634187[/C][C]0.731626[/C][C]0.365813[/C][/ROW]
[ROW][C]19[/C][C]0.536368[/C][C]0.927264[/C][C]0.463632[/C][/ROW]
[ROW][C]20[/C][C]0.439929[/C][C]0.879857[/C][C]0.560071[/C][/ROW]
[ROW][C]21[/C][C]0.459104[/C][C]0.918209[/C][C]0.540896[/C][/ROW]
[ROW][C]22[/C][C]0.590746[/C][C]0.818508[/C][C]0.409254[/C][/ROW]
[ROW][C]23[/C][C]0.513809[/C][C]0.972383[/C][C]0.486191[/C][/ROW]
[ROW][C]24[/C][C]0.493213[/C][C]0.986426[/C][C]0.506787[/C][/ROW]
[ROW][C]25[/C][C]0.421989[/C][C]0.843977[/C][C]0.578011[/C][/ROW]
[ROW][C]26[/C][C]0.488996[/C][C]0.977993[/C][C]0.511004[/C][/ROW]
[ROW][C]27[/C][C]0.569953[/C][C]0.860094[/C][C]0.430047[/C][/ROW]
[ROW][C]28[/C][C]0.502249[/C][C]0.995502[/C][C]0.497751[/C][/ROW]
[ROW][C]29[/C][C]0.510372[/C][C]0.979257[/C][C]0.489628[/C][/ROW]
[ROW][C]30[/C][C]0.443004[/C][C]0.886007[/C][C]0.556996[/C][/ROW]
[ROW][C]31[/C][C]0.407229[/C][C]0.814458[/C][C]0.592771[/C][/ROW]
[ROW][C]32[/C][C]0.347543[/C][C]0.695086[/C][C]0.652457[/C][/ROW]
[ROW][C]33[/C][C]0.333993[/C][C]0.667986[/C][C]0.666007[/C][/ROW]
[ROW][C]34[/C][C]0.29155[/C][C]0.583099[/C][C]0.70845[/C][/ROW]
[ROW][C]35[/C][C]0.240597[/C][C]0.481194[/C][C]0.759403[/C][/ROW]
[ROW][C]36[/C][C]0.214815[/C][C]0.42963[/C][C]0.785185[/C][/ROW]
[ROW][C]37[/C][C]0.186654[/C][C]0.373308[/C][C]0.813346[/C][/ROW]
[ROW][C]38[/C][C]0.154681[/C][C]0.309362[/C][C]0.845319[/C][/ROW]
[ROW][C]39[/C][C]0.135859[/C][C]0.271718[/C][C]0.864141[/C][/ROW]
[ROW][C]40[/C][C]0.106954[/C][C]0.213908[/C][C]0.893046[/C][/ROW]
[ROW][C]41[/C][C]0.183397[/C][C]0.366793[/C][C]0.816603[/C][/ROW]
[ROW][C]42[/C][C]0.148441[/C][C]0.296883[/C][C]0.851559[/C][/ROW]
[ROW][C]43[/C][C]0.138685[/C][C]0.277371[/C][C]0.861315[/C][/ROW]
[ROW][C]44[/C][C]0.11124[/C][C]0.222481[/C][C]0.88876[/C][/ROW]
[ROW][C]45[/C][C]0.0898786[/C][C]0.179757[/C][C]0.910121[/C][/ROW]
[ROW][C]46[/C][C]0.0715992[/C][C]0.143198[/C][C]0.928401[/C][/ROW]
[ROW][C]47[/C][C]0.0614935[/C][C]0.122987[/C][C]0.938506[/C][/ROW]
[ROW][C]48[/C][C]0.102524[/C][C]0.205048[/C][C]0.897476[/C][/ROW]
[ROW][C]49[/C][C]0.0943637[/C][C]0.188727[/C][C]0.905636[/C][/ROW]
[ROW][C]50[/C][C]0.0761371[/C][C]0.152274[/C][C]0.923863[/C][/ROW]
[ROW][C]51[/C][C]0.0610424[/C][C]0.122085[/C][C]0.938958[/C][/ROW]
[ROW][C]52[/C][C]0.0783389[/C][C]0.156678[/C][C]0.921661[/C][/ROW]
[ROW][C]53[/C][C]0.0622354[/C][C]0.124471[/C][C]0.937765[/C][/ROW]
[ROW][C]54[/C][C]0.052967[/C][C]0.105934[/C][C]0.947033[/C][/ROW]
[ROW][C]55[/C][C]0.0636321[/C][C]0.127264[/C][C]0.936368[/C][/ROW]
[ROW][C]56[/C][C]0.0544906[/C][C]0.108981[/C][C]0.945509[/C][/ROW]
[ROW][C]57[/C][C]0.128557[/C][C]0.257114[/C][C]0.871443[/C][/ROW]
[ROW][C]58[/C][C]0.176166[/C][C]0.352332[/C][C]0.823834[/C][/ROW]
[ROW][C]59[/C][C]0.157834[/C][C]0.315668[/C][C]0.842166[/C][/ROW]
[ROW][C]60[/C][C]0.146774[/C][C]0.293549[/C][C]0.853226[/C][/ROW]
[ROW][C]61[/C][C]0.137775[/C][C]0.27555[/C][C]0.862225[/C][/ROW]
[ROW][C]62[/C][C]0.118831[/C][C]0.237662[/C][C]0.881169[/C][/ROW]
[ROW][C]63[/C][C]0.127805[/C][C]0.25561[/C][C]0.872195[/C][/ROW]
[ROW][C]64[/C][C]0.190071[/C][C]0.380142[/C][C]0.809929[/C][/ROW]
[ROW][C]65[/C][C]0.178783[/C][C]0.357566[/C][C]0.821217[/C][/ROW]
[ROW][C]66[/C][C]0.161312[/C][C]0.322624[/C][C]0.838688[/C][/ROW]
[ROW][C]67[/C][C]0.138861[/C][C]0.277723[/C][C]0.861139[/C][/ROW]
[ROW][C]68[/C][C]0.125587[/C][C]0.251173[/C][C]0.874413[/C][/ROW]
[ROW][C]69[/C][C]0.169297[/C][C]0.338595[/C][C]0.830703[/C][/ROW]
[ROW][C]70[/C][C]0.156199[/C][C]0.312397[/C][C]0.843801[/C][/ROW]
[ROW][C]71[/C][C]0.135343[/C][C]0.270687[/C][C]0.864657[/C][/ROW]
[ROW][C]72[/C][C]0.114266[/C][C]0.228533[/C][C]0.885734[/C][/ROW]
[ROW][C]73[/C][C]0.109294[/C][C]0.218588[/C][C]0.890706[/C][/ROW]
[ROW][C]74[/C][C]0.129991[/C][C]0.259982[/C][C]0.870009[/C][/ROW]
[ROW][C]75[/C][C]0.118119[/C][C]0.236239[/C][C]0.881881[/C][/ROW]
[ROW][C]76[/C][C]0.102556[/C][C]0.205111[/C][C]0.897444[/C][/ROW]
[ROW][C]77[/C][C]0.0902355[/C][C]0.180471[/C][C]0.909764[/C][/ROW]
[ROW][C]78[/C][C]0.0830211[/C][C]0.166042[/C][C]0.916979[/C][/ROW]
[ROW][C]79[/C][C]0.0684569[/C][C]0.136914[/C][C]0.931543[/C][/ROW]
[ROW][C]80[/C][C]0.0691617[/C][C]0.138323[/C][C]0.930838[/C][/ROW]
[ROW][C]81[/C][C]0.0572902[/C][C]0.11458[/C][C]0.94271[/C][/ROW]
[ROW][C]82[/C][C]0.057187[/C][C]0.114374[/C][C]0.942813[/C][/ROW]
[ROW][C]83[/C][C]0.0465304[/C][C]0.0930608[/C][C]0.95347[/C][/ROW]
[ROW][C]84[/C][C]0.0946348[/C][C]0.18927[/C][C]0.905365[/C][/ROW]
[ROW][C]85[/C][C]0.0797216[/C][C]0.159443[/C][C]0.920278[/C][/ROW]
[ROW][C]86[/C][C]0.0703606[/C][C]0.140721[/C][C]0.929639[/C][/ROW]
[ROW][C]87[/C][C]0.0591891[/C][C]0.118378[/C][C]0.940811[/C][/ROW]
[ROW][C]88[/C][C]0.0484958[/C][C]0.0969915[/C][C]0.951504[/C][/ROW]
[ROW][C]89[/C][C]0.0490986[/C][C]0.0981972[/C][C]0.950901[/C][/ROW]
[ROW][C]90[/C][C]0.0562745[/C][C]0.112549[/C][C]0.943725[/C][/ROW]
[ROW][C]91[/C][C]0.0544298[/C][C]0.10886[/C][C]0.94557[/C][/ROW]
[ROW][C]92[/C][C]0.0688918[/C][C]0.137784[/C][C]0.931108[/C][/ROW]
[ROW][C]93[/C][C]0.0588388[/C][C]0.117678[/C][C]0.941161[/C][/ROW]
[ROW][C]94[/C][C]0.0519456[/C][C]0.103891[/C][C]0.948054[/C][/ROW]
[ROW][C]95[/C][C]0.0482678[/C][C]0.0965355[/C][C]0.951732[/C][/ROW]
[ROW][C]96[/C][C]0.0428477[/C][C]0.0856954[/C][C]0.957152[/C][/ROW]
[ROW][C]97[/C][C]0.0465151[/C][C]0.0930301[/C][C]0.953485[/C][/ROW]
[ROW][C]98[/C][C]0.0385132[/C][C]0.0770264[/C][C]0.961487[/C][/ROW]
[ROW][C]99[/C][C]0.0433744[/C][C]0.0867488[/C][C]0.956626[/C][/ROW]
[ROW][C]100[/C][C]0.0398752[/C][C]0.0797503[/C][C]0.960125[/C][/ROW]
[ROW][C]101[/C][C]0.0327199[/C][C]0.0654398[/C][C]0.96728[/C][/ROW]
[ROW][C]102[/C][C]0.0271363[/C][C]0.0542726[/C][C]0.972864[/C][/ROW]
[ROW][C]103[/C][C]0.0249833[/C][C]0.0499667[/C][C]0.975017[/C][/ROW]
[ROW][C]104[/C][C]0.0204769[/C][C]0.0409537[/C][C]0.979523[/C][/ROW]
[ROW][C]105[/C][C]0.0325117[/C][C]0.0650233[/C][C]0.967488[/C][/ROW]
[ROW][C]106[/C][C]0.0293376[/C][C]0.0586753[/C][C]0.970662[/C][/ROW]
[ROW][C]107[/C][C]0.0417022[/C][C]0.0834043[/C][C]0.958298[/C][/ROW]
[ROW][C]108[/C][C]0.0741213[/C][C]0.148243[/C][C]0.925879[/C][/ROW]
[ROW][C]109[/C][C]0.0973571[/C][C]0.194714[/C][C]0.902643[/C][/ROW]
[ROW][C]110[/C][C]0.0833544[/C][C]0.166709[/C][C]0.916646[/C][/ROW]
[ROW][C]111[/C][C]0.0716113[/C][C]0.143223[/C][C]0.928389[/C][/ROW]
[ROW][C]112[/C][C]0.0624975[/C][C]0.124995[/C][C]0.937503[/C][/ROW]
[ROW][C]113[/C][C]0.101295[/C][C]0.20259[/C][C]0.898705[/C][/ROW]
[ROW][C]114[/C][C]0.148961[/C][C]0.297922[/C][C]0.851039[/C][/ROW]
[ROW][C]115[/C][C]0.259595[/C][C]0.519189[/C][C]0.740405[/C][/ROW]
[ROW][C]116[/C][C]0.287607[/C][C]0.575214[/C][C]0.712393[/C][/ROW]
[ROW][C]117[/C][C]0.283506[/C][C]0.567013[/C][C]0.716494[/C][/ROW]
[ROW][C]118[/C][C]0.254841[/C][C]0.509683[/C][C]0.745159[/C][/ROW]
[ROW][C]119[/C][C]0.248373[/C][C]0.496746[/C][C]0.751627[/C][/ROW]
[ROW][C]120[/C][C]0.263953[/C][C]0.527907[/C][C]0.736047[/C][/ROW]
[ROW][C]121[/C][C]0.242691[/C][C]0.485382[/C][C]0.757309[/C][/ROW]
[ROW][C]122[/C][C]0.223795[/C][C]0.44759[/C][C]0.776205[/C][/ROW]
[ROW][C]123[/C][C]0.235462[/C][C]0.470925[/C][C]0.764538[/C][/ROW]
[ROW][C]124[/C][C]0.209965[/C][C]0.419931[/C][C]0.790035[/C][/ROW]
[ROW][C]125[/C][C]0.227186[/C][C]0.454372[/C][C]0.772814[/C][/ROW]
[ROW][C]126[/C][C]0.202976[/C][C]0.405951[/C][C]0.797024[/C][/ROW]
[ROW][C]127[/C][C]0.197609[/C][C]0.395218[/C][C]0.802391[/C][/ROW]
[ROW][C]128[/C][C]0.174355[/C][C]0.34871[/C][C]0.825645[/C][/ROW]
[ROW][C]129[/C][C]0.224233[/C][C]0.448467[/C][C]0.775767[/C][/ROW]
[ROW][C]130[/C][C]0.201633[/C][C]0.403267[/C][C]0.798367[/C][/ROW]
[ROW][C]131[/C][C]0.181189[/C][C]0.362377[/C][C]0.818811[/C][/ROW]
[ROW][C]132[/C][C]0.162085[/C][C]0.32417[/C][C]0.837915[/C][/ROW]
[ROW][C]133[/C][C]0.141604[/C][C]0.283208[/C][C]0.858396[/C][/ROW]
[ROW][C]134[/C][C]0.126626[/C][C]0.253251[/C][C]0.873374[/C][/ROW]
[ROW][C]135[/C][C]0.128451[/C][C]0.256902[/C][C]0.871549[/C][/ROW]
[ROW][C]136[/C][C]0.114607[/C][C]0.229213[/C][C]0.885393[/C][/ROW]
[ROW][C]137[/C][C]0.11207[/C][C]0.224139[/C][C]0.88793[/C][/ROW]
[ROW][C]138[/C][C]0.215491[/C][C]0.430981[/C][C]0.784509[/C][/ROW]
[ROW][C]139[/C][C]0.21213[/C][C]0.42426[/C][C]0.78787[/C][/ROW]
[ROW][C]140[/C][C]0.190614[/C][C]0.381228[/C][C]0.809386[/C][/ROW]
[ROW][C]141[/C][C]0.188925[/C][C]0.377851[/C][C]0.811075[/C][/ROW]
[ROW][C]142[/C][C]0.201108[/C][C]0.402217[/C][C]0.798892[/C][/ROW]
[ROW][C]143[/C][C]0.187686[/C][C]0.375372[/C][C]0.812314[/C][/ROW]
[ROW][C]144[/C][C]0.189765[/C][C]0.37953[/C][C]0.810235[/C][/ROW]
[ROW][C]145[/C][C]0.171737[/C][C]0.343475[/C][C]0.828263[/C][/ROW]
[ROW][C]146[/C][C]0.156332[/C][C]0.312663[/C][C]0.843668[/C][/ROW]
[ROW][C]147[/C][C]0.136788[/C][C]0.273575[/C][C]0.863212[/C][/ROW]
[ROW][C]148[/C][C]0.119983[/C][C]0.239967[/C][C]0.880017[/C][/ROW]
[ROW][C]149[/C][C]0.10406[/C][C]0.20812[/C][C]0.89594[/C][/ROW]
[ROW][C]150[/C][C]0.103128[/C][C]0.206257[/C][C]0.896872[/C][/ROW]
[ROW][C]151[/C][C]0.1485[/C][C]0.297[/C][C]0.8515[/C][/ROW]
[ROW][C]152[/C][C]0.129882[/C][C]0.259764[/C][C]0.870118[/C][/ROW]
[ROW][C]153[/C][C]0.141052[/C][C]0.282104[/C][C]0.858948[/C][/ROW]
[ROW][C]154[/C][C]0.133214[/C][C]0.266427[/C][C]0.866786[/C][/ROW]
[ROW][C]155[/C][C]0.116056[/C][C]0.232113[/C][C]0.883944[/C][/ROW]
[ROW][C]156[/C][C]0.104328[/C][C]0.208655[/C][C]0.895672[/C][/ROW]
[ROW][C]157[/C][C]0.114354[/C][C]0.228709[/C][C]0.885646[/C][/ROW]
[ROW][C]158[/C][C]0.0981774[/C][C]0.196355[/C][C]0.901823[/C][/ROW]
[ROW][C]159[/C][C]0.0837237[/C][C]0.167447[/C][C]0.916276[/C][/ROW]
[ROW][C]160[/C][C]0.0995271[/C][C]0.199054[/C][C]0.900473[/C][/ROW]
[ROW][C]161[/C][C]0.0993931[/C][C]0.198786[/C][C]0.900607[/C][/ROW]
[ROW][C]162[/C][C]0.092907[/C][C]0.185814[/C][C]0.907093[/C][/ROW]
[ROW][C]163[/C][C]0.080383[/C][C]0.160766[/C][C]0.919617[/C][/ROW]
[ROW][C]164[/C][C]0.0692617[/C][C]0.138523[/C][C]0.930738[/C][/ROW]
[ROW][C]165[/C][C]0.0768448[/C][C]0.15369[/C][C]0.923155[/C][/ROW]
[ROW][C]166[/C][C]0.076843[/C][C]0.153686[/C][C]0.923157[/C][/ROW]
[ROW][C]167[/C][C]0.0804455[/C][C]0.160891[/C][C]0.919555[/C][/ROW]
[ROW][C]168[/C][C]0.0683011[/C][C]0.136602[/C][C]0.931699[/C][/ROW]
[ROW][C]169[/C][C]0.0578335[/C][C]0.115667[/C][C]0.942166[/C][/ROW]
[ROW][C]170[/C][C]0.0670602[/C][C]0.13412[/C][C]0.93294[/C][/ROW]
[ROW][C]171[/C][C]0.0630175[/C][C]0.126035[/C][C]0.936983[/C][/ROW]
[ROW][C]172[/C][C]0.0657955[/C][C]0.131591[/C][C]0.934204[/C][/ROW]
[ROW][C]173[/C][C]0.0573804[/C][C]0.114761[/C][C]0.94262[/C][/ROW]
[ROW][C]174[/C][C]0.0486526[/C][C]0.0973052[/C][C]0.951347[/C][/ROW]
[ROW][C]175[/C][C]0.041139[/C][C]0.082278[/C][C]0.958861[/C][/ROW]
[ROW][C]176[/C][C]0.0577483[/C][C]0.115497[/C][C]0.942252[/C][/ROW]
[ROW][C]177[/C][C]0.0496805[/C][C]0.0993611[/C][C]0.950319[/C][/ROW]
[ROW][C]178[/C][C]0.0695867[/C][C]0.139173[/C][C]0.930413[/C][/ROW]
[ROW][C]179[/C][C]0.0675688[/C][C]0.135138[/C][C]0.932431[/C][/ROW]
[ROW][C]180[/C][C]0.185498[/C][C]0.370997[/C][C]0.814502[/C][/ROW]
[ROW][C]181[/C][C]0.173937[/C][C]0.347873[/C][C]0.826063[/C][/ROW]
[ROW][C]182[/C][C]0.152308[/C][C]0.304616[/C][C]0.847692[/C][/ROW]
[ROW][C]183[/C][C]0.169583[/C][C]0.339165[/C][C]0.830417[/C][/ROW]
[ROW][C]184[/C][C]0.151658[/C][C]0.303316[/C][C]0.848342[/C][/ROW]
[ROW][C]185[/C][C]0.136413[/C][C]0.272827[/C][C]0.863587[/C][/ROW]
[ROW][C]186[/C][C]0.120735[/C][C]0.24147[/C][C]0.879265[/C][/ROW]
[ROW][C]187[/C][C]0.116267[/C][C]0.232533[/C][C]0.883733[/C][/ROW]
[ROW][C]188[/C][C]0.110142[/C][C]0.220283[/C][C]0.889858[/C][/ROW]
[ROW][C]189[/C][C]0.115168[/C][C]0.230336[/C][C]0.884832[/C][/ROW]
[ROW][C]190[/C][C]0.107394[/C][C]0.214788[/C][C]0.892606[/C][/ROW]
[ROW][C]191[/C][C]0.113439[/C][C]0.226878[/C][C]0.886561[/C][/ROW]
[ROW][C]192[/C][C]0.102955[/C][C]0.205911[/C][C]0.897045[/C][/ROW]
[ROW][C]193[/C][C]0.127196[/C][C]0.254392[/C][C]0.872804[/C][/ROW]
[ROW][C]194[/C][C]0.149907[/C][C]0.299815[/C][C]0.850093[/C][/ROW]
[ROW][C]195[/C][C]0.134288[/C][C]0.268576[/C][C]0.865712[/C][/ROW]
[ROW][C]196[/C][C]0.117485[/C][C]0.234971[/C][C]0.882515[/C][/ROW]
[ROW][C]197[/C][C]0.100178[/C][C]0.200355[/C][C]0.899822[/C][/ROW]
[ROW][C]198[/C][C]0.0850479[/C][C]0.170096[/C][C]0.914952[/C][/ROW]
[ROW][C]199[/C][C]0.0712647[/C][C]0.142529[/C][C]0.928735[/C][/ROW]
[ROW][C]200[/C][C]0.0631526[/C][C]0.126305[/C][C]0.936847[/C][/ROW]
[ROW][C]201[/C][C]0.120023[/C][C]0.240047[/C][C]0.879977[/C][/ROW]
[ROW][C]202[/C][C]0.107114[/C][C]0.214227[/C][C]0.892886[/C][/ROW]
[ROW][C]203[/C][C]0.0949478[/C][C]0.189896[/C][C]0.905052[/C][/ROW]
[ROW][C]204[/C][C]0.0792762[/C][C]0.158552[/C][C]0.920724[/C][/ROW]
[ROW][C]205[/C][C]0.0692155[/C][C]0.138431[/C][C]0.930785[/C][/ROW]
[ROW][C]206[/C][C]0.0582336[/C][C]0.116467[/C][C]0.941766[/C][/ROW]
[ROW][C]207[/C][C]0.0602854[/C][C]0.120571[/C][C]0.939715[/C][/ROW]
[ROW][C]208[/C][C]0.050245[/C][C]0.10049[/C][C]0.949755[/C][/ROW]
[ROW][C]209[/C][C]0.0697786[/C][C]0.139557[/C][C]0.930221[/C][/ROW]
[ROW][C]210[/C][C]0.0722039[/C][C]0.144408[/C][C]0.927796[/C][/ROW]
[ROW][C]211[/C][C]0.0704[/C][C]0.1408[/C][C]0.9296[/C][/ROW]
[ROW][C]212[/C][C]0.0638049[/C][C]0.12761[/C][C]0.936195[/C][/ROW]
[ROW][C]213[/C][C]0.067328[/C][C]0.134656[/C][C]0.932672[/C][/ROW]
[ROW][C]214[/C][C]0.0551989[/C][C]0.110398[/C][C]0.944801[/C][/ROW]
[ROW][C]215[/C][C]0.0462083[/C][C]0.0924166[/C][C]0.953792[/C][/ROW]
[ROW][C]216[/C][C]0.0390272[/C][C]0.0780545[/C][C]0.960973[/C][/ROW]
[ROW][C]217[/C][C]0.0407375[/C][C]0.081475[/C][C]0.959262[/C][/ROW]
[ROW][C]218[/C][C]0.0464554[/C][C]0.0929108[/C][C]0.953545[/C][/ROW]
[ROW][C]219[/C][C]0.0415454[/C][C]0.0830908[/C][C]0.958455[/C][/ROW]
[ROW][C]220[/C][C]0.0336705[/C][C]0.0673409[/C][C]0.96633[/C][/ROW]
[ROW][C]221[/C][C]0.0334435[/C][C]0.0668871[/C][C]0.966556[/C][/ROW]
[ROW][C]222[/C][C]0.158016[/C][C]0.316031[/C][C]0.841984[/C][/ROW]
[ROW][C]223[/C][C]0.13822[/C][C]0.27644[/C][C]0.86178[/C][/ROW]
[ROW][C]224[/C][C]0.124712[/C][C]0.249424[/C][C]0.875288[/C][/ROW]
[ROW][C]225[/C][C]0.11181[/C][C]0.22362[/C][C]0.88819[/C][/ROW]
[ROW][C]226[/C][C]0.0920875[/C][C]0.184175[/C][C]0.907913[/C][/ROW]
[ROW][C]227[/C][C]0.0767144[/C][C]0.153429[/C][C]0.923286[/C][/ROW]
[ROW][C]228[/C][C]0.0676668[/C][C]0.135334[/C][C]0.932333[/C][/ROW]
[ROW][C]229[/C][C]0.138967[/C][C]0.277934[/C][C]0.861033[/C][/ROW]
[ROW][C]230[/C][C]0.157393[/C][C]0.314786[/C][C]0.842607[/C][/ROW]
[ROW][C]231[/C][C]0.208325[/C][C]0.416649[/C][C]0.791675[/C][/ROW]
[ROW][C]232[/C][C]0.233661[/C][C]0.467322[/C][C]0.766339[/C][/ROW]
[ROW][C]233[/C][C]0.19802[/C][C]0.39604[/C][C]0.80198[/C][/ROW]
[ROW][C]234[/C][C]0.171547[/C][C]0.343095[/C][C]0.828453[/C][/ROW]
[ROW][C]235[/C][C]0.157216[/C][C]0.314431[/C][C]0.842784[/C][/ROW]
[ROW][C]236[/C][C]0.467815[/C][C]0.935631[/C][C]0.532185[/C][/ROW]
[ROW][C]237[/C][C]0.445311[/C][C]0.890622[/C][C]0.554689[/C][/ROW]
[ROW][C]238[/C][C]0.406389[/C][C]0.812779[/C][C]0.593611[/C][/ROW]
[ROW][C]239[/C][C]0.360928[/C][C]0.721856[/C][C]0.639072[/C][/ROW]
[ROW][C]240[/C][C]0.31993[/C][C]0.63986[/C][C]0.68007[/C][/ROW]
[ROW][C]241[/C][C]0.303164[/C][C]0.606327[/C][C]0.696836[/C][/ROW]
[ROW][C]242[/C][C]0.291307[/C][C]0.582615[/C][C]0.708693[/C][/ROW]
[ROW][C]243[/C][C]0.275731[/C][C]0.551461[/C][C]0.724269[/C][/ROW]
[ROW][C]244[/C][C]0.319262[/C][C]0.638523[/C][C]0.680738[/C][/ROW]
[ROW][C]245[/C][C]0.289034[/C][C]0.578068[/C][C]0.710966[/C][/ROW]
[ROW][C]246[/C][C]0.257866[/C][C]0.515732[/C][C]0.742134[/C][/ROW]
[ROW][C]247[/C][C]0.26066[/C][C]0.521321[/C][C]0.73934[/C][/ROW]
[ROW][C]248[/C][C]0.30296[/C][C]0.60592[/C][C]0.69704[/C][/ROW]
[ROW][C]249[/C][C]0.292735[/C][C]0.585469[/C][C]0.707265[/C][/ROW]
[ROW][C]250[/C][C]0.262735[/C][C]0.52547[/C][C]0.737265[/C][/ROW]
[ROW][C]251[/C][C]0.291144[/C][C]0.582287[/C][C]0.708856[/C][/ROW]
[ROW][C]252[/C][C]0.250947[/C][C]0.501894[/C][C]0.749053[/C][/ROW]
[ROW][C]253[/C][C]0.219144[/C][C]0.438288[/C][C]0.780856[/C][/ROW]
[ROW][C]254[/C][C]0.169937[/C][C]0.339874[/C][C]0.830063[/C][/ROW]
[ROW][C]255[/C][C]0.310096[/C][C]0.620192[/C][C]0.689904[/C][/ROW]
[ROW][C]256[/C][C]0.245324[/C][C]0.490649[/C][C]0.754676[/C][/ROW]
[ROW][C]257[/C][C]0.44297[/C][C]0.88594[/C][C]0.55703[/C][/ROW]
[ROW][C]258[/C][C]0.409487[/C][C]0.818973[/C][C]0.590513[/C][/ROW]
[ROW][C]259[/C][C]0.359255[/C][C]0.71851[/C][C]0.640745[/C][/ROW]
[ROW][C]260[/C][C]0.411688[/C][C]0.823376[/C][C]0.588312[/C][/ROW]
[ROW][C]261[/C][C]0.387201[/C][C]0.774402[/C][C]0.612799[/C][/ROW]
[ROW][C]262[/C][C]0.679061[/C][C]0.641879[/C][C]0.320939[/C][/ROW]
[ROW][C]263[/C][C]0.597166[/C][C]0.805667[/C][C]0.402834[/C][/ROW]
[ROW][C]264[/C][C]0.467658[/C][C]0.935315[/C][C]0.532342[/C][/ROW]
[ROW][C]265[/C][C]0.312016[/C][C]0.624033[/C][C]0.687984[/C][/ROW]
[ROW][C]266[/C][C]0.255668[/C][C]0.511335[/C][C]0.744332[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267922&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267922&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
130.8462370.3075260.153763
140.7431020.5137970.256898
150.8658560.2682870.134144
160.7905490.4189010.209451
170.7102970.5794060.289703
180.6341870.7316260.365813
190.5363680.9272640.463632
200.4399290.8798570.560071
210.4591040.9182090.540896
220.5907460.8185080.409254
230.5138090.9723830.486191
240.4932130.9864260.506787
250.4219890.8439770.578011
260.4889960.9779930.511004
270.5699530.8600940.430047
280.5022490.9955020.497751
290.5103720.9792570.489628
300.4430040.8860070.556996
310.4072290.8144580.592771
320.3475430.6950860.652457
330.3339930.6679860.666007
340.291550.5830990.70845
350.2405970.4811940.759403
360.2148150.429630.785185
370.1866540.3733080.813346
380.1546810.3093620.845319
390.1358590.2717180.864141
400.1069540.2139080.893046
410.1833970.3667930.816603
420.1484410.2968830.851559
430.1386850.2773710.861315
440.111240.2224810.88876
450.08987860.1797570.910121
460.07159920.1431980.928401
470.06149350.1229870.938506
480.1025240.2050480.897476
490.09436370.1887270.905636
500.07613710.1522740.923863
510.06104240.1220850.938958
520.07833890.1566780.921661
530.06223540.1244710.937765
540.0529670.1059340.947033
550.06363210.1272640.936368
560.05449060.1089810.945509
570.1285570.2571140.871443
580.1761660.3523320.823834
590.1578340.3156680.842166
600.1467740.2935490.853226
610.1377750.275550.862225
620.1188310.2376620.881169
630.1278050.255610.872195
640.1900710.3801420.809929
650.1787830.3575660.821217
660.1613120.3226240.838688
670.1388610.2777230.861139
680.1255870.2511730.874413
690.1692970.3385950.830703
700.1561990.3123970.843801
710.1353430.2706870.864657
720.1142660.2285330.885734
730.1092940.2185880.890706
740.1299910.2599820.870009
750.1181190.2362390.881881
760.1025560.2051110.897444
770.09023550.1804710.909764
780.08302110.1660420.916979
790.06845690.1369140.931543
800.06916170.1383230.930838
810.05729020.114580.94271
820.0571870.1143740.942813
830.04653040.09306080.95347
840.09463480.189270.905365
850.07972160.1594430.920278
860.07036060.1407210.929639
870.05918910.1183780.940811
880.04849580.09699150.951504
890.04909860.09819720.950901
900.05627450.1125490.943725
910.05442980.108860.94557
920.06889180.1377840.931108
930.05883880.1176780.941161
940.05194560.1038910.948054
950.04826780.09653550.951732
960.04284770.08569540.957152
970.04651510.09303010.953485
980.03851320.07702640.961487
990.04337440.08674880.956626
1000.03987520.07975030.960125
1010.03271990.06543980.96728
1020.02713630.05427260.972864
1030.02498330.04996670.975017
1040.02047690.04095370.979523
1050.03251170.06502330.967488
1060.02933760.05867530.970662
1070.04170220.08340430.958298
1080.07412130.1482430.925879
1090.09735710.1947140.902643
1100.08335440.1667090.916646
1110.07161130.1432230.928389
1120.06249750.1249950.937503
1130.1012950.202590.898705
1140.1489610.2979220.851039
1150.2595950.5191890.740405
1160.2876070.5752140.712393
1170.2835060.5670130.716494
1180.2548410.5096830.745159
1190.2483730.4967460.751627
1200.2639530.5279070.736047
1210.2426910.4853820.757309
1220.2237950.447590.776205
1230.2354620.4709250.764538
1240.2099650.4199310.790035
1250.2271860.4543720.772814
1260.2029760.4059510.797024
1270.1976090.3952180.802391
1280.1743550.348710.825645
1290.2242330.4484670.775767
1300.2016330.4032670.798367
1310.1811890.3623770.818811
1320.1620850.324170.837915
1330.1416040.2832080.858396
1340.1266260.2532510.873374
1350.1284510.2569020.871549
1360.1146070.2292130.885393
1370.112070.2241390.88793
1380.2154910.4309810.784509
1390.212130.424260.78787
1400.1906140.3812280.809386
1410.1889250.3778510.811075
1420.2011080.4022170.798892
1430.1876860.3753720.812314
1440.1897650.379530.810235
1450.1717370.3434750.828263
1460.1563320.3126630.843668
1470.1367880.2735750.863212
1480.1199830.2399670.880017
1490.104060.208120.89594
1500.1031280.2062570.896872
1510.14850.2970.8515
1520.1298820.2597640.870118
1530.1410520.2821040.858948
1540.1332140.2664270.866786
1550.1160560.2321130.883944
1560.1043280.2086550.895672
1570.1143540.2287090.885646
1580.09817740.1963550.901823
1590.08372370.1674470.916276
1600.09952710.1990540.900473
1610.09939310.1987860.900607
1620.0929070.1858140.907093
1630.0803830.1607660.919617
1640.06926170.1385230.930738
1650.07684480.153690.923155
1660.0768430.1536860.923157
1670.08044550.1608910.919555
1680.06830110.1366020.931699
1690.05783350.1156670.942166
1700.06706020.134120.93294
1710.06301750.1260350.936983
1720.06579550.1315910.934204
1730.05738040.1147610.94262
1740.04865260.09730520.951347
1750.0411390.0822780.958861
1760.05774830.1154970.942252
1770.04968050.09936110.950319
1780.06958670.1391730.930413
1790.06756880.1351380.932431
1800.1854980.3709970.814502
1810.1739370.3478730.826063
1820.1523080.3046160.847692
1830.1695830.3391650.830417
1840.1516580.3033160.848342
1850.1364130.2728270.863587
1860.1207350.241470.879265
1870.1162670.2325330.883733
1880.1101420.2202830.889858
1890.1151680.2303360.884832
1900.1073940.2147880.892606
1910.1134390.2268780.886561
1920.1029550.2059110.897045
1930.1271960.2543920.872804
1940.1499070.2998150.850093
1950.1342880.2685760.865712
1960.1174850.2349710.882515
1970.1001780.2003550.899822
1980.08504790.1700960.914952
1990.07126470.1425290.928735
2000.06315260.1263050.936847
2010.1200230.2400470.879977
2020.1071140.2142270.892886
2030.09494780.1898960.905052
2040.07927620.1585520.920724
2050.06921550.1384310.930785
2060.05823360.1164670.941766
2070.06028540.1205710.939715
2080.0502450.100490.949755
2090.06977860.1395570.930221
2100.07220390.1444080.927796
2110.07040.14080.9296
2120.06380490.127610.936195
2130.0673280.1346560.932672
2140.05519890.1103980.944801
2150.04620830.09241660.953792
2160.03902720.07805450.960973
2170.04073750.0814750.959262
2180.04645540.09291080.953545
2190.04154540.08309080.958455
2200.03367050.06734090.96633
2210.03344350.06688710.966556
2220.1580160.3160310.841984
2230.138220.276440.86178
2240.1247120.2494240.875288
2250.111810.223620.88819
2260.09208750.1841750.907913
2270.07671440.1534290.923286
2280.06766680.1353340.932333
2290.1389670.2779340.861033
2300.1573930.3147860.842607
2310.2083250.4166490.791675
2320.2336610.4673220.766339
2330.198020.396040.80198
2340.1715470.3430950.828453
2350.1572160.3144310.842784
2360.4678150.9356310.532185
2370.4453110.8906220.554689
2380.4063890.8127790.593611
2390.3609280.7218560.639072
2400.319930.639860.68007
2410.3031640.6063270.696836
2420.2913070.5826150.708693
2430.2757310.5514610.724269
2440.3192620.6385230.680738
2450.2890340.5780680.710966
2460.2578660.5157320.742134
2470.260660.5213210.73934
2480.302960.605920.69704
2490.2927350.5854690.707265
2500.2627350.525470.737265
2510.2911440.5822870.708856
2520.2509470.5018940.749053
2530.2191440.4382880.780856
2540.1699370.3398740.830063
2550.3100960.6201920.689904
2560.2453240.4906490.754676
2570.442970.885940.55703
2580.4094870.8189730.590513
2590.3592550.718510.640745
2600.4116880.8233760.588312
2610.3872010.7744020.612799
2620.6790610.6418790.320939
2630.5971660.8056670.402834
2640.4676580.9353150.532342
2650.3120160.6240330.687984
2660.2556680.5113350.744332






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00787402OK
10% type I error level260.102362NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 2 & 0.00787402 & OK \tabularnewline
10% type I error level & 26 & 0.102362 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267922&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]2[/C][C]0.00787402[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]26[/C][C]0.102362[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267922&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267922&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00787402OK
10% type I error level260.102362NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 5 ; par2 = grey ; par3 = FALSE ; par4 = Unknown ;
Parameters (R input):
par1 = 10 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '9'
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')
}