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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_chi_squared_tests.wasp
Title produced by softwareChi-Squared and McNemar Tests
Date of computationFri, 10 Dec 2010 13:13:41 +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/2010/Dec/10/t1291986777w6une3qu9o3g6d3.htm/, Retrieved Mon, 29 Apr 2024 16:06:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107651, Retrieved Mon, 29 Apr 2024 16:06:41 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Chi-Squared and McNemar Tests] [paper, chi square ] [2010-12-10 13:13:41] [3f3a9898d211ad33ec6591a184de431c] [Current]
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Dataseries X:
1	1	2	0	0	2
1	1	1	1	2	0
0	1	2	1	2	0
0	1	1	1	2	3
0	1	2	1	2	2
1	1	1	0	0	4
1	1	2	1	0	6
0	1	1	0	0	3
1	1	2	2	0	5
0	1	1	0	0	7
0	1	1	1	0	4
1	1	2	1	0	1
1	1	2	0	0	2
1	1	2	0	0	2
1	1	1	0	0	8
0	1	1	0	0	0
0	1	1	0	1	2
1	1	2	0	1	5
1	1	2	0	0	3
0	1	1	0	0	3
1	1	1	1	1	3
1	1	2	1	1	4
1	1	1	0	0	2
1	1	2	0	0	4
1	1	2	0	0	2
0	1	1	0	0	2
1	1	1	1	0	2
1	1	2	1	0	1
1	1	2	0	0	3
1	1	1	0	0	2
0	1	1	0	0	4
1	1	1	0	0	4
1	1	2	0	0	3
1	1	2	0	0	5
0	1	1	0	0	4
1	1	2	0	0	4
1	1	2	0	1	2
1	1	1	0	0	0
0	1	1	0	0	4
0	1	1	0	0	4
0	1	1	0	0	0
1	1	2	0	0	4
1	1	2	2	0	5
1	1	2	0	0	6
1	1	2	0	0	4
0	1	1	0	0	4
0	1	1	0	0	0
1	1	1	0	0	4
1	1	2	0	0	5
1	1	1	0	1	3
1	1	2	0	1	5
0	1	1	0	0	3
0	1	1	0	0	2
0	1	1	0	0	1
1	1	1	1	2	1
1	1	2	1	2	1
1	1	1	1	2	3
1	1	2	1	2	3
0	1	1	0	0	4
1	1	2	0	0	0
0	1	1	1	0	3
1	1	2	1	0	7
0	1	1	1	0	4
1	1	2	1	0	4
1	1	1	1	0	2
1	1	2	1	0	3
1	1	2	0	0	3
1	1	2	0	0	3
1	1	1	0	0	4
1	1	2	0	1	0
0	1	1	0	0	0
0	1	1	1	0	2
1	1	2	1	0	2
1	1	2	0	0	2
0	1	1	0	0	0
0	1	1	0	0	4
1	1	2	1	1	3
0	1	1	1	1	3
1	1	2	0	2	6
1	1	2	2	0	5
0	1	1	0	0	0
0	1	1	1	1	7
1	1	2	0	2	3
1	1	2	1	1	6
0	1	1	1	0	3
1	1	2	1	0	3
1	1	1	0	0	5
1	1	1	0	0	2
1	1	2	0	0	3
0	1	1	1	0	3
1	1	2	1	2	2
1	1	1	1	0	3
1	1	2	1	0	1
1	1	1	1	1	5
1	1	1	0	2	0
1	1	2	1	1	5
0	1	1	1	0	5
1	1	2	1	1	2
1	1	2	1	0	4
1	1	2	1	0	4
1	1	1	1	0	4
0	1	1	0	0	3
1	1	2	0	1	2
1	1	2	0	0	3
1	1	2	1	0	5
0	1	2	0	0	3
0	1	1	0	0	0
1	1	2	0	0	0
1	1	2	0	0	0
1	1	1	0	0	3
0	1	1	0	0	3
1	1	2	3	2	2
1	1	2	3	2	2
1	1	2	3	2	2
0	1	1	3	2	1
0	1	1	1	4	6
1	1	2	1	4	6
1	1	2	0	0	3
0	1	1	0	0	0
1	1	1	2	0	5
1	1	1	1	0	4
1	1	2	1	0	0
1	1	2	0	2	2
1	1	1	1	1	6
1	1	2	1	1	4
0	1	1	0	0	0
0	1	1	1	0	3
1	1	2	1	0	3
0	1	1	0	0	4
1	1	2	0	0	3
1	1	2	0	1	2
1	1	2	0	1	4
0	1	1	0	0	2
1	1	1	1	0	4
1	1	2	1	0	0
0	1	1	0	0	7
1	1	1	0	0	5
1	1	2	0	0	1
0	1	1	0	1	3
1	1	2	0	1	5
1	1	1	0	1	2
1	1	2	0	1	4
0	1	1	0	0	4
1	1	1	1	0	2
1	1	2	1	0	2
1	1	1	1	0	4
1	1	2	1	0	4
0	1	1	0	0	0
0	1	1	1	0	4
1	1	2	1	0	3
0	1	1	0	0	4
1	1	1	0	0	2
1	1	1	0	0	0
1	1	2	0	0	2
0	1	1	1	1	5
1	1	2	1	1	5
0	1	1	0	0	4
0	1	1	0	0	0
0	1	1	0	0	5
1	1	2	0	1	1
1	1	2	0	1	4
1	1	2	1	0	5
0	1	1	1	0	4
1	1	2	1	0	3
1	1	1	0	0	3
1	1	1	1	0	3
0	1	1	0	0	0
1	1	2	1	0	3
1	1	2	0	0	3
0	1	2	0	0	5
1	1	1	0	0	4
0	1	1	0	0	4
0	1	1	0	0	5
0	1	1	0	0	3
0	1	1	0	0	5
0	1	1	1	0	4
1	1	2	1	0	0
1	1	1	1	0	4
1	1	2	1	0	4
0	1	1	0	0	0
1	1	2	0	0	3
1	1	2	0	0	4
1	1	2	0	0	3
1	1	1	0	0	3
0	1	1	0	0	0
0	1	1	0	0	4
1	1	2	0	0	5
1	1	2	0	1	1
1	1	2	0	1	5
0	1	1	0	0	2
1	1	2	0	0	2
0	1	1	0	0	3
1	1	2	0	0	5
1	1	2	0	1	1
0	1	1	0	0	3
1	1	2	0	0	1
1	1	1	0	0	0
0	1	1	1	0	1
1	1	2	1	0	1
1	1	2	0	0	2
0	1	1	0	0	4
0	1	1	0	0	5
1	1	1	0	0	3
0	1	1	1	0	2
1	1	2	1	0	0
0	1	1	0	0	6
0	1	1	2	0	4
1	1	2	1	0	3
1	1	2	1	0	3
1	1	1	1	0	3
0	1	1	0	0	5
0	1	1	0	0	4
0	1	1	0	1	3
1	1	2	1	0	3
1	1	2	1	0	2
0	1	1	0	2	5
1	1	2	0	2	1
0	1	1	0	0	6
1	1	2	0	0	3
1	1	1	0	0	0
1	1	2	0	1	2
0	1	1	0	1	6
0	1	1	0	0	2
0	1	1	0	0	0
0	1	1	0	0	4
0	1	1	0	0	2
0	1	1	1	0	2
1	1	2	1	0	2
0	1	1	1	0	1
1	1	2	1	0	1
1	1	2	0	0	3
1	1	1	0	0	5
0	1	1	0	0	4
1	1	2	0	1	5
0	1	1	0	0	3
1	1	1	0	0	0
0	1	1	0	0	2
0	1	1	0	0	0
1	1	2	0	1	4
0	1	1	0	0	3
1	1	1	0	0	4
0	1	1	0	0	0
1	1	2	0	0	3
0	1	1	0	0	4
0	1	1	0	0	3
1	1	2	0	0	3
0	1	1	1	0	5
1	1	2	1	0	5
0	1	1	0	0	3
1	1	1	2	2	1
1	1	2	2	2	1
1	1	2	2	2	2
0	1	1	1	3	6
1	1	2	1	3	4
1	1	1	0	0	0
1	1	2	0	0	2
1	1	1	0	0	0
1	1	2	1	0	3
1	1	2	0	0	3
1	1	1	0	0	3
1	1	2	0	0	4
1	1	1	0	0	3
0	1	1	1	0	5
1	1	2	1	0	3
1	1	1	0	0	5
1	1	1	0	0	2
0	1	1	0	0	5
0	1	1	0	0	5
0	1	1	1	0	2
0	1	1	0	0	0
1	1	2	1	0	1
1	1	1	1	0	2
1	1	2	1	0	2
1	1	1	0	2	0
1	1	1	1	1	4
1	1	2	1	1	4
0	1	1	1	0	5
1	1	2	1	0	0
1	1	1	0	0	3
0	1	1	0	0	6
1	1	1	1	0	5
1	1	2	1	0	4
1	1	2	1	0	5
0	1	1	0	0	0
1	1	2	0	0	6
0	1	1	1	0	6
0	1	2	1	0	6
0	1	1	0	0	6
1	1	2	0	0	4
1	1	2	0	2	1
0	1	1	1	1	5
1	1	2	1	1	3
1	1	1	1	0	4
1	1	2	1	0	0
0	1	1	1	1	4
1	1	1	0	2	1
1	1	2	1	1	3
1	1	2	0	0	0
1	1	1	0	0	3
0	1	1	0	0	4
0	1	1	0	0	6
0	1	1	0	0	4
1	1	2	0	0	3
0	1	1	1	0	6
1	1	2	1	0	6
0	1	1	0	0	6
0	1	1	0	1	5
0	1	1	0	1	2
1	1	2	0	0	5
1	1	2	0	2	3
0	1	1	1	1	5
1	1	2	1	1	4
0	1	1	1	1	5
0	1	1	0	2	2
1	1	2	1	1	5
1	1	2	0	0	2
0	1	1	0	1	5
1	1	1	0	1	2
0	1	1	0	0	0
1	1	2	0	0	3
1	1	1	0	0	0
0	1	1	0	0	6
1	1	2	0	0	3
0	2	1	1	0	3
1	2	2	1	0	2
0	2	1	0	0	3
0	2	1	0	0	1
0	2	1	0	0	2
0	2	1	1	0	3
1	2	2	1	0	3
0	2	1	0	0	5
0	2	1	0	0	1
0	2	1	0	0	2
1	2	2	0	0	3
0	2	1	0	0	2
0	2	1	0	0	5
1	2	1	1	0	3
1	2	2	1	0	1
0	2	1	0	0	2
1	2	1	2	1	0
1	2	2	2	1	0
1	2	2	2	1	1
1	2	2	0	3	3
1	2	1	0	0	3
1	2	2	0	0	1
0	2	1	0	0	2
0	2	1	0	0	2
0	2	1	0	0	4
0	2	1	0	0	2
1	2	2	0	0	2
1	2	2	0	2	1
0	2	1	1	1	6
1	2	2	1	1	4
1	2	2	1	0	2
0	2	1	1	0	2
1	2	2	0	0	3
0	2	1	0	0	2
0	2	1	0	0	4
1	2	2	0	0	4
1	2	1	0	2	0
1	2	1	1	1	2
1	2	2	1	1	2
1	2	2	0	0	3
0	2	1	0	0	0
0	2	1	0	0	1
0	2	2	1	0	4
0	2	1	1	0	5
0	2	1	0	0	5
0	2	1	1	0	3
0	2	2	1	0	2
1	2	2	1	1	2
1	2	2	0	2	4
0	2	1	1	0	2
1	2	2	1	0	2
0	2	1	0	0	2
0	2	1	0	0	2
1	2	1	0	0	2
1	2	2	0	2	0
0	2	1	1	1	3
1	2	2	1	1	3
1	2	2	0	0	2
0	2	2	0	0	3
0	2	2	0	0	0
0	2	1	0	0	2
0	2	1	0	0	0
1	2	1	1	1	0
0	2	1	0	0	1
1	2	2	0	2	4
1	2	2	0	0	2
0	2	1	0	0	3
0	2	1	0	0	1
0	2	1	1	0	2
1	2	2	1	0	2
0	2	1	0	0	2
0	2	1	0	0	1
1	2	2	0	1	1
1	2	2	0	1	3
0	2	1	0	0	5
1	2	1	0	2	0
0	2	1	1	1	4
1	2	2	1	1	3
1	2	2	1	0	2
1	2	2	1	0	3
0	2	1	0	0	2
0	2	1	0	0	2
0	2	1	0	0	1
0	2	1	1	0	4
1	2	2	1	0	2
0	2	1	0	0	1
0	2	1	0	0	3
0	2	1	0	0	0
0	2	2	0	0	3
0	2	1	0	0	3
0	2	1	1	0	3
0	2	1	1	0	3
1	2	2	0	0	3
0	2	1	0	0	1
0	2	1	0	0	2
0	2	1	0	0	4
0	2	1	1	0	2
0	2	1	1	0	2
0	2	1	0	0	2
0	2	1	0	0	2
0	2	1	0	0	3
0	2	1	0	0	3
0	2	1	0	0	5
0	2	1	0	0	3
1	2	1	1	1	0
1	2	2	0	2	2
0	2	1	0	0	4
1	2	2	0	1	0
0	2	1	0	1	2
1	2	1	0	0	6
0	2	1	0	0	3
1	2	2	0	2	0
0	2	1	1	1	4
1	2	2	1	1	4
1	2	2	1	2	2
1	2	2	1	2	2
0	2	1	1	2	4
1	2	2	1	2	4
1	2	2	0	0	5
0	2	1	2	0	2
0	2	1	2	0	3
0	2	1	2	0	2
0	2	2	1	1	1
1	2	2	2	1	2
0	2	1	2	1	2
0	2	1	0	0	3
1	2	2	1	3	5
0	2	1	0	0	5
0	2	1	1	0	4
1	2	2	1	0	2
0	2	1	0	0	2
1	2	1	0	0	4
0	2	1	1	0	6
0	2	2	1	0	6
0	2	1	0	0	3
1	2	2	0	0	1
0	2	1	1	0	4
1	2	2	2	1	2
0	2	1	0	0	4
0	2	1	2	0	2
0	2	1	2	0	2
0	2	1	0	0	3
1	2	2	0	0	2
0	2	1	1	0	3
1	2	2	1	0	2
0	2	2	0	0	2
1	2	2	0	0	0
0	2	1	0	0	3
1	2	2	0	0	4
0	2	1	0	0	5
0	2	1	0	0	0
0	2	1	0	0	3
0	2	2	1	1	2
0	2	1	1	1	3
0	2	1	0	0	0
1	2	2	1	2	0
1	2	2	1	2	0
0	2	1	1	2	2
1	2	2	1	2	2
1	2	2	0	0	1
1	2	2	0	0	0
1	2	2	0	0	3
0	2	1	0	0	3
0	2	1	0	0	2
0	2	1	0	0	6
0	2	1	1	0	5
1	2	2	1	0	4
0	2	2	0	0	5
0	2	1	0	0	0
1	2	1	0	2	0
0	2	1	1	1	3
1	2	2	1	1	2
0	2	1	0	0	0
0	2	1	0	0	3
0	2	1	0	0	4
0	2	1	0	0	3
0	2	1	0	0	3
0	2	1	0	0	4
1	2	2	0	1	1
1	2	2	0	1	4
1	2	1	0	0	1
0	2	1	0	0	3
0	2	1	0	0	4
0	2	1	0	0	7
0	2	1	0	0	2
0	2	1	0	0	5
0	2	1	0	0	3
0	2	1	0	0	1
0	2	1	0	0	6
0	2	1	1	0	3
1	2	2	1	0	1
1	2	1	1	1	0
1	2	1	1	1	0
0	2	1	0	2	3
0	2	1	0	0	2
0	2	1	1	1	1
0	2	1	0	0	2
1	2	1	0	0	2
1	2	2	0	0	2
0	2	1	0	0	3
1	2	1	0	0	2
1	2	1	0	0	0
0	2	1	0	0	2
1	2	1	0	0	2
0	2	1	0	0	2
0	2	1	0	0	0
1	2	2	0	1	5
0	2	1	0	0	1
0	2	1	0	0	0
0	2	1	0	0	4
1	2	2	0	1	2
1	2	2	0	0	1
0	2	1	0	1	4
1	2	2	0	0	3
0	2	1	0	0	3
1	2	1	0	0	3
0	2	1	0	0	2
1	2	2	1	1	0
1	2	2	1	1	0
1	2	2	0	2	3
0	2	1	0	0	3
0	2	1	1	0	3
1	2	2	3	0	3
1	2	2	0	0	2
0	2	1	0	0	2
1	2	1	1	1	0
1	2	1	1	1	0
1	2	2	2	3	2
1	2	2	0	0	5
0	2	1	0	0	1
1	2	2	0	0	2
0	2	1	0	0	2
0	2	1	0	0	2
0	2	1	0	0	2
1	2	2	0	1	2
1	2	2	0	2	1
1	2	2	0	0	2
1	2	2	0	0	3
0	2	1	0	0	5
1	2	2	0	0	3
0	2	1	0	0	3
1	2	2	0	0	4
0	2	1	0	0	2
0	2	1	0	0	4
0	2	1	0	0	2
0	2	1	0	0	1
0	2	1	0	0	1
1	2	2	0	0	5
0	2	1	0	0	2
1	2	2	0	0	2
1	2	2	0	0	2
0	2	1	1	0	2
0	2	2	1	0	2
0	2	1	0	0	4
1	2	2	0	0	3
0	2	1	1	0	3
0	2	1	1	0	2
1	2	2	0	0	3
0	2	1	0	0	0
1	2	2	0	0	1
1	2	2	0	0	4
1	2	2	0	0	3
0	2	1	1	0	2
1	2	2	1	0	2
1	2	1	1	1	0
1	2	2	1	1	0
1	2	2	0	2	2
1	2	2	1	2	0
1	2	2	1	2	0
0	2	1	1	2	3
1	2	2	1	2	3
0	2	1	0	0	6
0	2	1	0	0	0
1	2	1	0	0	3
1	2	1	0	0	0
1	2	2	0	0	2
0	2	2	0	0	2
0	3	1	0	0	4
0	3	1	0	2	1
0	3	1	1	1	1
1	3	2	1	1	3
1	3	2	0	0	1
1	3	1	0	0	2
1	3	1	0	0	2
1	3	2	0	0	1
0	3	1	0	0	3
0	3	1	0	0	2
0	3	2	1	0	4
1	3	1	0	1	0
1	3	2	0	1	1
1	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	3
0	3	1	0	0	1
0	3	1	0	0	3
1	3	2	1	0	1
0	3	1	4	2	0
0	3	2	4	2	0
0	3	2	4	2	0
1	3	2	4	2	1
0	3	2	4	2	3
0	3	2	4	2	0
0	3	2	4	2	1
0	3	1	1	5	3
1	3	1	0	0	2
0	3	1	0	0	2
0	3	2	1	5	3
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	1	0	2
0	3	2	1	0	1
0	3	1	0	0	2
0	3	1	0	0	3
0	3	1	4	2	0
0	3	1	4	2	0
1	3	1	4	2	0
0	3	1	4	2	1
1	3	2	4	2	0
0	3	1	1	5	4
1	3	1	0	0	2
1	3	2	1	5	3
1	3	2	0	0	4
0	3	1	0	0	2
0	3	1	0	0	2
0	3	2	0	0	1
0	3	1	0	0	3
0	3	1	0	0	2
1	3	2	0	0	1
0	3	1	0	0	2
0	3	1	1	0	3
1	3	2	3	0	3
1	3	2	2	1	0
1	3	2	2	1	0
1	3	2	2	1	0
1	3	2	0	3	2
1	3	2	0	0	1
0	3	1	0	0	4
0	3	1	0	0	2
1	3	1	0	0	2
0	3	2	0	1	1
0	3	2	0	1	4
0	3	2	0	0	2
0	3	1	0	0	2
0	3	1	0	0	1
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	0
0	3	1	0	0	2
1	3	1	0	0	3
0	3	1	0	0	2
0	3	1	0	0	1
0	3	1	0	0	2
0	3	1	1	1	0
0	3	2	1	1	0
0	3	1	0	0	0
0	3	2	0	2	0
0	3	2	0	2	0
0	3	1	1	1	4
0	3	2	1	1	3
0	3	1	0	0	2
1	3	2	0	0	2
0	3	2	0	0	2
0	3	1	1	0	2
0	3	1	1	0	2
0	3	1	0	0	2
0	3	1	0	0	3
0	3	2	0	0	1
1	3	1	0	0	2
0	3	1	0	0	1
0	3	2	0	0	1
0	3	2	0	0	2
0	3	2	0	0	3
0	3	1	0	0	1
0	3	1	0	0	3
0	3	1	0	0	1
0	3	1	0	0	1
0	3	2	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	1	0	0
0	3	2	1	0	0
0	3	1	0	0	2
0	3	1	0	0	2
1	3	2	0	0	1
0	3	2	0	0	3
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2
1	3	1	0	0	3
0	3	1	0	0	2
0	3	1	1	0	2
0	3	1	1	0	1
0	3	1	0	0	2
1	3	1	0	0	1
0	3	1	0	0	2
0	3	1	0	0	3
0	3	1	0	0	2
0	3	1	0	0	3
0	3	1	0	0	3
1	3	2	0	0	2
0	3	2	0	0	3
0	3	1	0	0	7
0	3	1	0	0	4
0	3	1	0	0	3
0	3	1	0	0	2
0	3	1	0	0	1
0	3	1	0	0	3
1	3	1	1	1	0
1	3	1	1	1	0
1	3	2	0	2	3
0	3	1	0	0	5
0	3	1	0	0	1
1	3	2	0	1	1
0	3	1	0	1	4
0	3	1	0	0	1
0	3	1	0	0	2
1	3	1	0	0	4
0	3	2	0	0	2
0	3	1	0	0	1
1	3	2	0	0	3
1	3	1	0	0	2
0	3	1	0	2	0
0	3	1	1	1	3
0	3	2	1	1	2
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	2	0	2
0	3	1	0	0	2
0	3	1	2	0	2
0	3	1	2	0	1
0	3	1	1	0	0
1	3	2	1	0	0
1	3	1	1	0	3
1	3	2	1	0	3
1	3	1	0	0	3
0	3	1	0	0	1
1	3	1	1	2	0
1	3	2	1	2	0
0	3	1	1	2	2
1	3	2	1	2	3
0	3	1	0	0	2
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	2
0	3	1	0	0	3
1	3	2	0	0	1
0	3	1	0	0	1
0	3	1	0	0	4
0	3	1	0	0	4
0	3	1	0	0	0
0	3	1	0	0	3
1	3	1	0	0	1
1	3	2	0	0	3
0	3	2	0	0	2
1	3	2	0	0	2
0	3	1	0	0	3
0	3	1	0	0	6
1	3	1	0	0	2
0	3	1	1	0	2
1	3	2	1	0	2
0	3	1	0	0	1
0	3	1	0	0	1
0	3	1	0	0	4
0	3	1	0	0	0
0	3	1	0	2	3
0	3	1	1	1	1
0	3	1	1	1	1
0	3	1	0	0	4
1	3	2	0	0	0
0	3	1	0	0	0
0	3	1	0	0	4
0	3	1	0	0	4
1	3	1	0	0	0
0	3	1	0	0	1
0	3	2	0	0	0
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	2
0	3	1	0	0	0
1	3	1	0	0	0
0	3	2	2	2	2
0	3	2	2	2	0
0	3	1	0	0	0
0	3	1	2	2	1
0	3	1	1	3	1
0	3	2	1	3	4
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	2
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	2
1	3	2	0	0	1
1	3	2	0	0	0
1	3	1	0	2	0
0	3	1	1	1	3
0	3	1	0	0	4
1	3	2	1	1	3
0	3	1	0	0	3
0	3	1	5	2	0
0	3	1	5	2	0
0	3	1	5	2	1
0	3	2	5	2	1
0	3	2	5	2	1
0	3	1	5	2	1
0	3	1	1	6	4
0	3	2	1	6	4
0	3	1	0	0	5
0	3	1	0	0	3
0	3	1	0	0	0
0	3	1	0	0	2
0	3	1	2	0	3
0	3	1	2	0	2
0	3	1	0	0	1
0	3	2	0	0	2
0	3	2	0	0	1
0	3	1	1	0	0
0	3	1	1	0	0
0	3	1	1	0	2
1	3	2	1	0	2
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	2	0	4
0	3	1	1	0	2
0	3	1	0	0	2
1	3	2	1	0	4
0	3	2	0	0	0
0	3	1	0	0	2
0	3	1	0	0	0
0	3	1	0	0	1
1	3	2	0	0	0
1	3	1	0	0	2
1	3	1	0	0	0
0	3	2	0	0	1
1	3	2	0	0	2
0	3	2	0	0	2
1	3	2	0	0	2
0	3	1	0	0	2
0	3	2	0	0	2
0	3	2	0	0	0
1	3	2	0	1	0
1	3	2	1	1	2
0	3	1	0	0	4
0	3	1	0	0	2
1	3	2	0	0	2
0	3	1	0	0	0
1	3	2	0	0	0
0	3	1	0	0	4
1	3	1	0	0	0
0	3	1	0	0	3
0	3	1	0	0	0
0	3	2	1	0	2
0	3	2	1	0	2
0	3	1	0	0	0
1	3	1	0	0	2
1	3	1	0	0	2
0	3	1	0	0	0
0	3	1	0	0	2
0	3	1	0	0	4
0	3	1	1	0	1
1	3	2	0	0	0
1	3	1	0	0	0
0	3	1	0	0	3
1	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	3
0	3	1	0	0	3
0	3	1	0	0	2
1	3	1	1	1	0
1	3	2	1	1	0
0	3	1	0	0	4
0	3	1	0	0	3
0	3	1	0	0	1
1	3	2	0	2	2
0	3	1	1	2	0
0	3	2	1	2	0
0	3	1	1	2	0
0	3	2	1	2	0
0	3	1	0	0	2
1	3	1	0	0	3
0	3	1	0	0	2
0	3	2	1	0	2
0	3	2	1	0	2
1	3	1	0	0	3
0	3	1	0	0	1
0	3	1	0	0	2
0	3	1	0	0	3
1	3	1	0	0	2
0	3	1	0	0	3
0	3	1	0	0	2
1	3	2	0	1	0
1	3	1	0	1	3
0	3	1	0	0	0
0	3	1	0	0	1
0	3	1	0	0	0
0	3	1	0	0	0
1	3	2	0	0	0
1	3	2	0	0	0
0	3	1	0	0	3
0	3	1	0	0	4
1	3	1	0	0	0
0	3	1	1	0	0
0	3	2	1	0	0
0	3	1	1	0	0
0	3	1	1	0	0
0	3	1	0	0	0
0	3	2	2	0	2
0	3	1	2	0	2
1	3	2	0	2	0
1	3	1	3	1	2
1	3	2	1	1	2
0	3	2	1	1	0
0	3	1	1	1	1
0	3	2	0	2	3
0	3	1	0	0	0
1	3	1	0	0	2
0	3	1	0	0	0
0	3	2	0	0	3
0	3	1	0	0	0
1	3	1	0	0	0
0	3	1	0	0	0
1	3	2	0	0	2
0	3	1	0	0	0
1	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2
1	3	1	0	0	2
0	3	1	3	1	0
0	3	2	3	1	0
0	3	2	3	1	0
0	3	2	3	1	0
0	3	2	0	4	0
0	3	1	0	0	3
0	3	1	0	0	3
0	3	2	1	0	0
0	3	1	1	0	0
0	3	1	0	0	3
0	3	1	0	0	3
0	3	1	0	0	2
0	3	2	0	0	2
0	3	2	0	0	4
0	3	1	1	0	3
0	3	2	1	0	3
1	3	1	1	0	2
0	3	1	0	0	0
0	3	1	0	0	2
0	3	1	0	0	0
0	3	1	1	0	3
0	3	2	1	0	2
0	3	1	0	0	0
0	3	1	0	0	2
1	3	1	0	0	2
0	3	1	0	0	5
1	3	2	0	0	2
1	3	1	0	0	3
0	3	1	0	0	0
0	3	1	0	0	0
1	3	2	0	0	0
1	3	1	0	0	2
0	3	1	0	0	2
0	3	2	0	0	0
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	2
1	3	1	0	0	0
0	3	2	0	0	3
1	3	2	0	0	0
0	3	1	0	0	0
0	3	1	0	0	3
0	3	1	0	0	3
1	3	2	0	0	0
0	3	1	0	0	0
1	3	2	0	0	0
1	3	1	0	0	0
1	3	2	2	0	0
1	3	2	2	0	0
1	3	1	2	0	0
1	3	2	0	0	0
0	3	1	0	0	0
1	3	2	0	0	0
1	3	2	0	0	1
0	3	2	0	0	3
0	3	1	0	0	0
0	3	1	1	0	2
0	3	2	1	0	1
0	3	2	0	0	0
0	3	2	0	0	0
0	3	2	0	0	0
0	3	1	0	0	5
0	3	1	0	0	0
1	3	1	0	0	2
0	3	1	0	0	0
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	0
1	3	2	0	0	0
0	3	1	0	0	2
1	3	1	0	1	0
1	3	2	0	1	2
0	3	1	0	0	0
1	3	2	1	0	0
0	3	1	1	0	0
0	3	1	0	0	0
0	3	1	0	0	3
0	3	1	0	0	0
1	3	1	0	0	0
1	3	1	1	1	0
1	3	1	1	1	0
1	3	2	0	2	0
1	3	2	0	0	0
0	3	1	0	0	0
1	3	2	0	0	0
1	3	2	0	0	2
0	3	1	0	0	0
1	3	2	1	0	0
1	3	2	1	0	0
1	3	2	0	0	0
0	3	1	0	0	1
0	3	1	0	0	2
1	3	2	0	0	1
1	3	2	0	2	0
1	3	1	1	1	2
1	3	2	1	1	1
0	3	1	0	0	3
0	3	1	0	0	0
0	3	1	0	0	0
0	3	2	0	0	0
0	3	1	0	0	0
1	3	1	1	0	1
1	3	2	1	0	1
0	3	2	0	0	2
0	3	1	0	0	2
1	3	2	0	0	1
1	3	2	0	0	2
0	3	1	0	0	2
0	3	1	0	0	4
1	3	1	0	0	3
0	3	1	0	0	2
0	3	1	0	0	2
1	3	2	0	0	2
0	3	1	0	0	6
0	3	1	1	0	0
0	3	1	0	0	0
1	3	2	1	0	0
0	3	1	0	0	0
0	3	1	0	0	0
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1	3	2	0	0	0
1	3	2	0	0	0
1	3	2	0	0	2
1	3	1	0	0	0
1	3	2	0	0	0
1	3	1	0	1	0
0	3	1	0	0	2
0	3	1	0	1	4
0	3	1	0	0	0
0	3	2	0	0	3
0	3	1	0	0	2
1	3	1	0	0	3
0	3	1	0	0	2
0	3	2	0	0	2
0	3	2	0	0	2
0	3	1	0	0	2
0	3	1	0	0	1
1	3	2	0	0	3
0	3	2	0	0	0
0	3	1	3	1	0
0	3	1	3	1	0
0	3	2	3	1	0
0	3	2	3	1	0
0	3	2	0	4	2
0	3	1	4	1	0
0	3	1	4	1	0
0	3	1	4	1	0
0	3	1	4	1	1
0	3	1	4	1	1
0	3	2	0	5	4
0	3	1	0	0	2
0	3	1	0	0	1
0	3	1	0	0	0
0	3	1	0	0	3
0	3	1	1	1	0
0	3	2	1	1	0
0	3	2	0	2	2
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2
1	3	1	1	0	2
1	3	1	1	1	0
1	3	2	1	1	0
1	3	2	0	2	0
0	3	2	0	0	0
0	3	1	0	0	2
0	3	2	0	0	2
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0	3	1	0	0	0
0	3	1	1	0	2
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1	3	1	0	0	3
0	3	1	0	0	0
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0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	3
0	3	1	0	0	2
0	3	1	4	1	1
0	3	1	4	1	0
0	3	1	4	1	0
0	3	1	4	1	0
0	3	1	4	1	0
0	3	2	0	5	3
0	3	2	0	0	2
0	3	1	0	0	3
1	3	2	0	0	0
0	3	1	0	0	0
0	3	2	0	0	0
0	3	1	1	0	5
0	3	2	1	0	4
0	3	1	0	0	0
0	3	1	0	0	0
0	3	2	1	1	0
0	3	1	1	1	1
0	3	2	0	2	4
1	3	2	0	0	0
0	3	1	0	0	5
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1	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	0
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0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	3
0	3	1	8	2	0
0	3	1	8	2	1
0	3	2	8	2	0
0	3	2	8	2	0
0	3	2	8	2	0
0	3	2	8	2	0
0	3	1	8	2	0
0	3	1	8	2	0
0	3	1	8	2	0
0	3	1	1	9	0
0	3	2	1	9	0
0	3	1	0	0	2
1	3	2	0	0	2
0	3	1	0	0	3
0	3	1	2	0	0
0	3	1	2	0	0
0	3	1	2	0	0
1	3	2	1	1	0
1	3	2	0	2	2
1	3	2	1	1	0
1	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	0
1	3	1	0	0	2
0	3	1	0	0	0
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0	3	1	0	0	2
0	3	1	0	0	0
0	3	1	0	0	4
0	3	1	0	0	2
1	3	2	0	0	1
0	3	1	3	2	0
0	3	1	3	2	1
0	3	2	3	2	0
0	3	2	3	2	0
0	3	1	1	4	4
0	3	2	1	4	4
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	0
1	3	2	0	0	0
0	3	1	0	0	1
0	3	1	0	0	3
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0	3	1	0	0	3
0	3	1	0	0	0
0	3	1	0	0	3
1	3	2	0	0	2
0	3	1	0	0	2
0	3	1	0	0	6
0	3	1	0	0	1
0	3	2	0	0	2
1	3	1	0	0	3
0	3	1	0	0	2
0	3	2	0	1	0
0	3	2	1	1	2
1	3	1	0	0	1
1	3	1	0	0	4
0	3	1	0	0	2
0	3	1	0	0	7
1	3	1	0	0	1
0	3	1	0	0	2
1	3	1	0	0	2
0	3	1	0	0	3
1	3	1	0	1	0
0	3	1	1	0	0
0	3	1	0	0	0
0	3	1	0	0	0
1	3	2	1	1	1
0	3	1	0	0	0
0	3	1	1	0	0
1	3	2	1	0	0
0	3	1	0	0	3
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	3
0	3	1	0	0	4
0	3	1	0	0	0
1	3	1	0	0	2
0	3	1	0	0	0
1	3	1	1	1	0
1	3	2	1	1	0
1	3	2	0	2	2
0	3	1	0	0	3
1	3	2	0	0	1
1	3	2	0	0	6
0	3	1	1	1	0
0	3	1	1	1	1
0	3	1	0	2	4
0	3	2	0	2	1
0	3	1	1	1	3
0	3	2	1	1	3
0	3	1	0	0	0
0	3	1	0	0	3
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	4
0	3	2	2	0	1
0	3	1	3	0	3
0	3	1	2	0	1
0	3	2	1	0	3
1	3	1	0	0	2
0	3	1	0	0	2
0	3	2	0	0	1
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	3
1	3	2	0	0	3
0	3	1	0	0	5
0	3	1	1	0	1
0	3	1	1	0	2
1	3	2	1	0	4
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	0
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	0
0	3	1	0	0	3
0	3	1	1	0	2
1	3	2	1	0	1
0	3	1	0	0	4
0	3	1	0	0	0
0	3	1	0	0	0
0	3	2	1	0	1
0	3	2	1	0	0
0	3	1	0	0	2
0	3	1	0	0	2
0	3	1	0	0	2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time21 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 21 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=107651&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]21 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=107651&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107651&T=0

As an alternative you can also use a 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 time21 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.







Tabulation of Results
survived x pclass
123
0123158528
1200119181

\begin{tabular}{lllllllll}
\hline
Tabulation of Results \tabularnewline
survived  x  pclass \tabularnewline
  & 1 & 2 & 3 \tabularnewline
0 & 123 & 158 & 528 \tabularnewline
1 & 200 & 119 & 181 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107651&T=1

[TABLE]
[ROW][C]Tabulation of Results[/C][/ROW]
[ROW][C]survived  x  pclass[/C][/ROW]
[ROW][C] [/C][C]1[/C][C]2[/C][C]3[/C][/ROW]
[C]0[/C][C]123[/C][C]158[/C][C]528[/C][/ROW]
[C]1[/C][C]200[/C][C]119[/C][C]181[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107651&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107651&T=1

As an alternative you can also use a QR Code:  

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

Tabulation of Results
survived x pclass
123
0123158528
1200119181







Tabulation of Expected Results
survived x pclass
123
0199.62171.19438.18
1123.38105.81270.82

\begin{tabular}{lllllllll}
\hline
Tabulation of Expected Results \tabularnewline
survived  x  pclass \tabularnewline
  & 1 & 2 & 3 \tabularnewline
0 & 199.62 & 171.19 & 438.18 \tabularnewline
1 & 123.38 & 105.81 & 270.82 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107651&T=2

[TABLE]
[ROW][C]Tabulation of Expected Results[/C][/ROW]
[ROW][C]survived  x  pclass[/C][/ROW]
[ROW][C] [/C][C]1[/C][C]2[/C][C]3[/C][/ROW]
[C]0[/C][C]199.62[/C][C]171.19[/C][C]438.18[/C][/ROW]
[C]1[/C][C]123.38[/C][C]105.81[/C][C]270.82[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107651&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107651&T=2

As an alternative you can also use a QR Code:  

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

Tabulation of Expected Results
survived x pclass
123
0199.62171.19438.18
1123.38105.81270.82







Statistical Results
Pearson's Chi-squared test
Chi Square Statistic127.86
Degrees of Freedom2
P value0

\begin{tabular}{lllllllll}
\hline
Statistical Results \tabularnewline
Pearson's Chi-squared test \tabularnewline
Chi Square Statistic & 127.86 \tabularnewline
Degrees of Freedom & 2 \tabularnewline
P value & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107651&T=3

[TABLE]
[ROW][C]Statistical Results[/C][/ROW]
[ROW][C]Pearson's Chi-squared test[/C][/ROW]
[ROW][C]Chi Square Statistic[/C][C]127.86[/C][/ROW]
[ROW][C]Degrees of Freedom[/C][C]2[/C][/ROW]
[ROW][C]P value[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107651&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107651&T=3

As an alternative you can also use a QR Code:  

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

Statistical Results
Pearson's Chi-squared test
Chi Square Statistic127.86
Degrees of Freedom2
P value0



Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = Pearson Chi-Squared ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = Pearson Chi-Squared ;
R code (references can be found in the software module):
library(vcd)
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
simulate.p.value=FALSE
if (par3 == 'Exact Pearson Chi-Squared by Simulation') simulate.p.value=TRUE
x <- t(x)
(z <- array(unlist(x),dim=c(length(x[,1]),length(x[1,]))))
(table1 <- table(z[,cat1],z[,cat2]))
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
bitmap(file='pic1.png')
assoc(ftable(z[,cat1],z[,cat2],row.vars=1,dnn=c(V1,V2)),shade=T)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tabulation of Results',ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1,TRUE)
for(nc in 1:ncol(table1)){
a<-table.element(a, colnames(table1)[nc], 1, TRUE)
}
a<-table.row.end(a)
for(nr in 1:nrow(table1) ){
a<-table.element(a, rownames(table1)[nr], 1, TRUE)
for(nc in 1:ncol(table1) ){
a<-table.element(a, table1[nr, nc], 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
(cst<-chisq.test(table1, simulate.p.value=simulate.p.value) )
if (par3 == 'McNemar Chi-Squared') {
(cst <- mcnemar.test(table1))
}
if (par3 != 'McNemar Chi-Squared') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tabulation of Expected Results',ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,paste(V1,' x ', V2),ncol(table1)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1,TRUE)
for(nc in 1:ncol(table1)){
a<-table.element(a, colnames(table1)[nc], 1, TRUE)
}
a<-table.row.end(a)
for(nr in 1:nrow(table1) ){
a<-table.element(a, rownames(table1)[nr], 1, TRUE)
for(nc in 1:ncol(table1) ){
a<-table.element(a, round(cst$expected[nr, nc], digits=2), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Statistical Results',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, cst$method, 2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Chi Square Statistic', 1, TRUE)
a<-table.element(a, round(cst$statistic, digits=2), 1,FALSE)
a<-table.row.end(a)
if(!simulate.p.value){
a<-table.row.start(a)
a<-table.element(a, 'Degrees of Freedom', 1, TRUE)
a<-table.element(a, cst$parameter, 1,FALSE)
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'P value', 1, TRUE)
a<-table.element(a, round(cst$p.value, digits=2), 1,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')