Free Statistics

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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_surveyscores.wasp
Title produced by softwareSurvey Scores
Date of computationMon, 22 Dec 2014 13:57:42 +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/22/t1419256672h5qvv23ub6xqu55.htm/, Retrieved Thu, 31 Oct 2024 23:20:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=271389, Retrieved Thu, 31 Oct 2024 23:20:46 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [E-Learn 2008 table 1] [2008-09-07 11:33:54] [b98453cac15ba1066b407e146608df68]
F RM D  [Survey Scores] [ATTLES] [2010-04-05 12:47:13] [b98453cac15ba1066b407e146608df68]
- RM        [Survey Scores] [jj] [2014-12-22 13:57:42] [e3ddd9a57cdbfec6dbe72df2938debe0] [Current]
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Dataseries X:
4	2	3	4	3	4	3	5	2	4	3	3	4	2	3	4	2	4	2	3
4	3	4	2	4	4	4	4	1	3	3	3	4	3	2	3	4	3	NA	3
2	1	4	3	3	4	2	3	3	4	4	4	4	2	4	3	2	3	2	3
5	3	5	4	5	2	4	2	1	3	3	4	5	4	5	5	4	1	3	1
2	1	4	4	4	5	2	4	2	4	5	2	2	2	4	4	4	5	5	2
4	3	4	4	3	4	3	3	3	4	4	4	3	3	4	4	4	3	4	4
4	5	4	3	4	4	5	5	3	4	4	4	2	4	5	4	4	4	4	4
4	2	5	1	2	4	2	2	1	4	4	5	1	3	2	3	5	2	2	4
4	4	4	4	5	5	3	5	2	4	4	5	3	4	4	3	4	4	4	3
5	4	5	2	4	5	4	5	2	4	4	2	3	4	5	4	4	5	5	1
4	2	4	4	4	4	3	4	3	4	4	4	2	4	4	4	4	4	4	3
5	2	5	4	4	5	4	4	3	4	4	3	3	3	4	4	3	4	4	3
5	4	5	3	4	5	3	4	5	5	3	4	2	4	4	4	3	4	4	5
5	1	5	4	5	5	3	4	3	5	5	4	4	5	5	4	4	4	4	3
4	3	4	5	3	4	3	2	2	3	4	3	3	4	NA	3	3	2	4	2
5	2	5	3	4	4	4	4	2	4	4	3	4	3	4	4	5	3	4	3
4	4	5	2	3	4	1	4	1	4	4	4	1	3	4	5	4	4	4	3
4	2	1	1	3	3	5	4	1	2	5	4	4	4	3	2	4	4	4	3
4	4	4	2	4	4	4	4	2	4	4	4	4	4	2	2	2	3	4	4
5	4	5	1	4	5	4	5	1	5	3	4	2	4	5	4	4	5	5	4
4	4	3	3	4	4	5	4	3	4	2	3	3	3	3	3	3	3	4	3
4	3	4	3	4	3	4	4	1	4	4	3	4	4	4	3	4	3	4	3
4	2	3	2	3	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4	1	5	2	4	5	1	5	4	4	4	5	4	4	3	3	2	4	2	2
4	4	4	4	5	5	4	4	3	4	4	4	4	4	4	4	4	4	4	4
5	4	5	4	4	5	4	5	2	4	4	3	4	4	5	2	2	5	4	4
5	2	2	2	5	4	4	5	3	4	2	5	4	5	4	2	5	4	2	4
5	1	5	3	4	4	4	5	3	5	5	4	5	3	5	3	3	4	4	3
4	2	4	2	4	4	3	4	1	5	5	3	4	3	3	2	4	4	4	3
4	3	4	2	2	4	3	4	3	4	4	3	4	3	4	3	4	4	4	3
5	1	5	4	4	5	2	4	2	4	5	3	4	4	4	3	1	4	4	2
4	1	4	4	3	5	4	5	3	4	3	4	3	3	4	3	5	4	4	3
5	3	4	3	3	4	4	4	3	3	3	3	4	3	4	3	4	3	3	2
5	2	3	3	4	5	3	4	1	4	5	3	3	2	4	3	3	4	4	2
4	3	4	2	3	5	3	4	1	3	4	3	4	1	3	2	3	3	3	1
4	1	5	3	5	4	3	5	1	4	4	4	4	4	3	3	4	3	4	4
4	5	5	3	4	5	3	4	3	3	3	3	4	4	4	3	3	4	2	2
3	2	4	2	3	3	3	4	3	3	3	3	2	4	3	3	3	4	3	3
4	2	3	1	4	2	2	1	2	4	3	4	4	2	2	3	4	4	1	4
4	2	3	2	4	3	4	3	1	3	4	2	4	4	3	3	3	4	3	2
5	3	4	4	4	5	3	4	3	4	5	4	5	3	4	3	3	4	4	2
4	2	4	1	4	5	3	3	1	4	4	1	4	2	3	2	3	4	1	1
2	1	3	1	3	4	3	4	1	4	4	3	4	2	3	3	3	3	3	2
4	2	3	3	2	2	2	3	2	5	5	4	3	3	3	4	4	3	3	5
4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	3	4	4	2
4	2	2	2	1	4	4	4	4	5	4	4	4	3	5	3	4	4	5	4
4	1	5	4	2	4	4	5	2	4	4	4	2	4	5	4	2	4	4	2
5	1	2	3	4	5	4	2	2	4	3	5	4	4	4	3	4	2	4	2
4	2	5	4	4	5	4	5	4	4	4	4	4	4	5	4	5	5	4	4
5	1	3	3	4	4	2	4	3	5	4	4	3	1	4	3	4	3	3	3
2	5	2	2	5	5	5	4	1	5	5	5	4	5	2	4	4	5	4	4
5	3	5	5	4	3	2	5	2	4	4	4	4	3	4	3	4	3	2	4
4	1	5	2	4	4	4	3	3	4	3	NA	2	2	4	4	2	5	3	2
1	1	5	4	4	5	3	5	1	3	4	1	5	1	4	3	2	3	3	4
5	3	5	2	1	4	3	4	2	5	3	3	4	4	2	3	3	4	2	3
4	3	4	3	2	4	3	4	1	4	4	3	4	3	3	4	3	5	4	3
4	3	5	4	4	5	4	5	3	3	4	3	4	4	4	3	2	5	4	3
4	4	5	4	5	5	4	5	3	4	3	4	4	5	5	4	3	5	4	4
3	2	5	4	4	4	2	5	2	4	4	3	4	2	5	4	3	3	4	2
5	3	5	5	5	5	5	5	3	4	3	1	5	3	5	3	5	5	5	1
4	4	4	2	4	4	4	4	2	4	4	4	4	4	2	2	2	3	4	4
4	4	5	3	2	5	4	5	2	5	5	2	4	2	5	2	4	3	4	4
4	2	5	4	NA	4	2	5	1	4	4	2	4	1	2	2	4	4	3	2
5	3	4	1	5	4	4	3	2	5	4	3	2	5	5	5	4	4	1	NA
4	1	5	4	4	4	3	4	2	5	4	4	3	4	5	4	4	5	4	1
4	1	4	2	4	4	4	5	4	5	4	4	5	2	2	4	3	5	4	4
4	3	5	4	4	5	4	4	4	3	3	4	5	3	4	4	5	4	3	4
5	3	3	3	4	4	4	4	3	2	3	3	4	3	4	3	3	4	3	4
5	1	4	4	4	5	4	4	1	4	3	4	2	4	3	4	4	3	3	2
5	2	4	2	3	4	2	4	2	4	3	5	4	4	4	3	4	3	3	3
5	1	4	3	4	5	5	4	1	4	5	3	4	2	4	4	4	4	4	2
4	2	4	4	5	4	3	5	3	3	4	3	4	2	4	4	3	4	4	3
5	4	5	3	5	5	4	4	3	4	3	4	3	3	3	2	4	4	4	3
4	2	3	4	4	5	4	4	3	4	4	4	3	4	4	4	5	5	5	4
4	3	4	5	4	4	3	4	1	4	4	4	4	4	4	3	4	4	4	1
5	1	4	4	4	3	3	4	3	5	4	3	3	4	3	3	4	3	3	3
5	3	4	2	1	4	1	5	3	5	3	5	2	4	2	4	4	4	4	4
4	4	5	4	4	4	3	2	3	4	4	4	NA	3	3	2	4	4	4	4
5	4	3	2	4	4	3	4	3	3	4	2	4	4	4	4	4	3	3	3
5	2	4	3	4	4	4	5	2	4	5	4	3	3	5	4	3	5	4	2
4	1	5	2	3	4	2	4	1	2	4	3	4	4	4	2	3	3	4	2
2	2	2	3	4	5	4	4	3	4	3	4	3	3	4	3	3	3	4	2
5	5	5	4	2	5	4	5	5	5	5	4	4	3	5	5	2	2	3	5
4	3	4	1	5	5	5	5	4	2	4	4	2	5	5	3	4	5	3	4
5	5	4	3	4	4	4	4	5	5	3	4	4	4	5	4	3	4	4	4
4	4	5	2	4	4	3	4	2	5	5	4	4	4	4	4	4	4	3	3
4	2	3	2	4	5	3	5	3	5	3	2	5	2	2	3	5	2	4	2
4	3	5	4	5	4	5	5	1	4	3	5	4	2	4	4	4	5	5	2
4	2	5	5	5	5	2	4	2	5	5	3	4	4	5	2	3	5	5	2
5	2	5	5	5	5	3	4	4	5	4	3	4	4	5	5	4	5	5	3
2	2	4	2	5	4	2	4	2	5	5	3	5	3	4	3	4	5	4	5
5	1	5	4	4	5	3	4	2	4	4	3	3	3	4	3	3	3	3	2
5	5	4	1	1	3	5	5	1	4	1	5	5	5	1	5	5	3	4	5
5	4	5	5	5	5	3	5	2	5	2	4	3	4	4	4	5	5	5	4
4	5	4	2	4	4	4	5	2	1	3	4	4	4	1	2	3	4	2	4
4	4	5	2	4	1	4	4	2	4	3	4	2	4	5	4	3	3	4	2
4	5	4	1	5	5	4	5	2	2	2	1	5	4	1	2	4	1	2	1
4	4	5	3	4	4	4	5	4	3	4	2	3	1	4	2	3	2	3	4
4	2	4	3	5	4	4	4	3	3	4	4	2	4	4	3	4	4	4	3
4	4	5	4	4	5	5	4	4	5	5	4	3	4	4	4	5	5	3	4
4	2	4	2	4	5	4	4	1	5	1	2	4	4	1	5	5	1	2	4
4	4	2	2	2	4	4	4	4	4	3	2	4	2	4	3	3	4	4	2
5	2	5	4	5	5	4	5	2	3	4	5	5	4	1	4	2	2	5	1
3	3	5	2	4	5	4	3	3	2	3	4	3	3	3	2	4	4	4	5
5	3	4	4	4	5	4	4	2	4	2	4	4	4	4	3	4	4	3	3
2	3	4	3	4	5	4	4	3	4	3	4	4	2	4	3	3	4	3	4
4	3	4	2	5	5	5	5	3	4	4	4	4	4	4	5	5	2	4	4
5	2	5	4	3	4	3	5	2	4	4	2	4	3	5	3	3	4	4	2
4	3	4	3	4	4	3	4	2	4	3	4	4	3	4	3	4	4	3	4
5	3	5	5	4	5	5	5	4	4	3	2	3	2	4	4	5	5	4	3
4	2	5	3	5	5	5	4	2	4	4	3	5	3	5	3	4	5	4	3
4	3	5	5	3	4	4	4	2	5	3	3	2	4	2	3	5	2	4	5
4	2	5	3	4	5	3	4	2	5	4	4	4	5	4	4	3	4	2	3
4	1	5	4	5	4	4	5	1	5	5	3	4	3	5	3	4	5	5	3
5	4	5	4	5	5	5	5	4	4	4	3	4	2	5	2	2	4	4	2
4	2	5	4	5	5	4	4	2	2	4	4	4	2	4	2	4	4	4	5
1	2	4	1	4	4	4	2	1	4	4	3	5	2	2	1	4	4	1	1
4	2	4	3	2	4	3	4	3	4	3	4	2	4	4	3	4	4	3	4
3	4	5	4	3	4	2	5	3	2	4	4	2	3	2	NA	NA	NA	NA	NA
4	4	5	4	5	5	4	5	4	2	5	4	4	2	4	3	3	4	4	4
4	4	2	1	5	4	4	4	1	4	4	4	2	4	4	2	4	5	2	1
4	1	4	4	3	2	4	2	4	5	4	4	2	4	2	2	4	3	3	3
4	4	3	3	3	3	3	3	3	4	4	3	3	3	3	3	3	3	3	3
4	3	5	3	4	5	2	4	4	4	5	3	3	5	5	3	1	5	4	4
4	5	4	3	4	3	4	4	2	4	3	4	4	2	5	4	3	4	3	2
4	3	5	3	4	4	4	4	1	3	3	1	4	2	3	3	4	3	3	4
4	2	3	2	5	3	4	4	2	4	4	3	5	5	4	3	3	2	3	2
5	2	5	2	5	4	4	5	3	4	4	5	2	4	4	4	4	4	4	2
5	2	4	3	5	4	4	4	3	4	5	5	4	3	4	4	4	3	3	3
5	1	4	4	4	5	5	4	3	4	4	3	3	3	4	3	3	3	3	4
3	2	5	3	4	5	4	4	3	5	4	3	2	3	4	4	4	4	4	3
4	4	3	2	3	4	2	2	3	3	2	4	3	3	4	2	4	2	2	1
5	4	5	4	5	4	5	5	4	2	4	4	3	3	2	3	5	5	2	3
4	2	5	3	4	4	2	4	2	4	4	4	2	3	2	4	4	4	4	4
5	4	5	3	5	4	4	2	3	4	4	4	3	5	3	4	4	4	4	4
5	1	3	4	4	4	4	4	3	4	4	4	3	4	3	3	4	4	3	3
4	2	2	3	4	4	4	4	2	3	3	4	3	2	5	3	3	4	4	3
5	4	4	4	3	4	5	4	1	3	4	4	4	5	3	4	3	3	4	2
5	4	5	4	4	4	4	5	3	4	3	4	2	4	4	3	5	4	4	3
5	4	5	4	4	5	3	4	2	4	3	4	3	4	2	4	3	3	2	4
4	2	4	3	3	4	4	5	2	4	4	4	4	3	4	4	4	4	4	4
5	2	4	5	5	5	4	4	1	4	4	4	5	5	5	3	4	3	3	4
5	1	4	3	4	4	3	4	2	4	4	4	3	3	4	4	3	3	4	3
4	3	2	2	2	2	4	4	2	3	3	3	3	3	3	2	3	4	4	3
4	3	4	1	2	3	2	4	2	5	2	4	2	4	4	4	4	3	4	4
5	2	3	3	4	4	4	4	3	4	4	5	2	4	4	4	4	3	4	4
3	3	3	2	4	5	4	2	3	2	4	4	4	4	4	3	3	4	3	4
4	1	3	4	4	3	4	4	3	4	3	4	3	4	3	2	3	3	4	2
5	1	4	3	4	3	3	4	1	5	4	4	3	3	3	3	3	3	3	3
5	2	5	2	5	4	4	4	2	4	2	4	4	5	2	4	4	4	2	4
5	1	5	4	5	5	3	5	2	5	5	3	5	2	5	3	5	5	5	1
4	3	5	4	5	5	3	4	2	4	3	4	3	NA	4	3	3	3	4	4
5	2	4	4	4	5	5	5	3	5	3	4	2	4	5	4	4	4	5	4
5	2	5	5	5	5	5	5	5	5	5	4	5	4	5	5	5	5	5	5
5	2	4	4	5	4	4	4	2	4	5	4	3	3	4	2	3	3	4	2
4	1	5	3	4	4	4	5	4	4	4	3	3	4	4	4	3	4	4	3
4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4
4	4	5	1	2	5	2	5	5	4	2	5	5	5	4	5	4	1	1	5
5	1	4	3	2	4	3	2	1	4	4	4	4	4	2	3	4	4	2	3
5	4	4	1	4	5	4	4	1	5	5	4	5	4	4	4	4	4	4	4
4	2	4	3	5	4	5	4	2	4	4	4	4	4	4	3	5	4	4	3
2	3	4	3	4	3	3	4	2	5	5	1	5	1	3	1	5	3	3	1
5	3	3	2	4	2	5	4	1	2	3	4	4	2	1	4	3	1	2	2
2	4	3	4	2	4	4	5	4	4	4	3	2	4	3	4	NA	3	3	4
5	3	4	3	3	4	5	4	2	4	4	4	3	4	3	3	3	3	3	NA
5	4	4	2	4	5	3	5	2	5	3	4	5	5	2	3	5	5	2	5
5	2	4	3	4	4	3	4	2	4	4	3	5	3	4	3	4	4	4	3
4	2	4	4	4	4	2	3	2	4	4	4	4	4	4	4	4	4	4	4
2	5	5	4	5	5	5	2	2	2	4	3	4	4	4	4	4	4	4	3
5	2	4	4	5	5	4	5	3	5	3	3	4	4	4	3	4	3	4	3
4	1	3	3	3	4	4	3	2	4	4	3	4	3	3	3	3	4	3	3
4	2	4	3	4	4	3	2	3	3	4	3	4	3	4	3	3	3	4	3
5	2	4	3	5	4	4	4	2	3	2	4	5	4	4	3	4	2	4	1
4	2	4	4	4	2	2	4	2	4	4	4	4	4	4	4	5	4	4	4
5	3	4	4	4	4	4	4	4	4	4	2	3	5	4	3	4	4	3	4
4	2	4	2	4	4	4	3	1	4	3	2	3	2	3	2	3	4	3	2
3	1	3	2	3	3	4	4	2	5	4	5	4	4	2	3	2	4	3	2
4	3	4	4	5	4	4	3	2	4	4	4	3	3	4	3	4	4	4	5
4	4	3	4	5	5	5	5	4	3	3	2	4	4	2	2	4	3	3	4
3	4	4	3	4	3	5	4	3	4	2	4	2	3	3	3	3	4	3	4
5	4	5	5	5	5	4	5	4	5	5	5	5	5	5	5	5	2	4	5
2	4	5	2	4	5	5	5	1	4	2	5	5	4	4	4	2	3	3	1
4	4	3	1	4	4	2	4	3	2	4	2	4	4	3	2	3	4	5	3
5	3	5	4	4	5	4	5	1	5	5	4	5	4	5	4	5	5	5	5
5	4	5	3	5	5	5	4	3	5	4	5	5	4	3	4	2	3	3	3
5	2	5	3	4	4	4	4	4	5	5	4	4	3	4	4	4	4	3	3
4	3	4	3	4	5	4	4	2	4	3	2	4	3	3	3	4	3	4	3
5	1	1	4	5	4	3	4	2	4	4	3	4	3	4	4	3	4	2	2
5	3	4	3	4	3	3	4	2	4	4	3	4	3	4	4	4	3	3	2
4	2	4	4	5	5	4	4	4	4	4	3	3	4	3	3	3	4	3	4
4	3	5	4	4	4	3	4	3	4	4	3	4	3	4	3	4	4	4	4
2	2	5	4	4	5	3	5	2	4	3	3	4	3	5	4	4	4	4	3
4	3	5	3	3	4	3	5	2	4	5	3	5	3	5	5	3	5	5	2
2	4	4	4	3	5	5	4	1	3	3	2	4	3	2	4	2	2	2	3
5	2	3	1	3	4	3	4	1	4	4	3	3	3	3	2	4	4	4	1
5	2	4	3	4	4	4	4	3	4	4	3	4	2	5	3	4	4	5	4
4	3	5	5	5	5	4	4	4	4	2	4	2	3	4	3	3	3	4	2
4	2	5	3	4	4	3	2	2	4	4	3	4	4	4	3	3	5	4	2
4	1	5	5	5	5	4	5	1	4	4	2	4	1	4	3	4	3	4	1
4	2	5	4	5	4	4	4	2	4	4	2	4	3	4	2	3	4	4	4
4	5	5	2	4	5	5	4	1	5	2	2	4	5	4	5	1	4	4	1
4	4	4	2	1	4	3	2	1	4	4	4	3	2	4	4	3	3	1	1
4	3	4	2	4	4	3	4	3	4	4	4	4	3	2	3	3	2	2	2
4	1	5	4	5	5	1	4	3	5	4	3	4	2	5	3	4	4	5	5
4	1	4	1	3	4	1	3	1	4	3	4	4	4	3	2	2	3	3	4
4	3	3	3	3	3	3	NA	3	3	3	3	3	3	3	3	3	3	3	3
5	2	4	3	5	4	3	4	3	5	4	5	5	4	3	4	3	3	4	4
4	1	4	2	5	4	2	4	1	2	3	3	4	3	2	2	3	4	3	3
4	1	4	3	5	5	3	5	1	4	4	4	3	4	4	5	4	5	4	3
5	4	5	3	4	4	4	3	2	4	5	4	4	4	5	5	4	4	3	3
5	4	5	4	2	5	3	4	2	5	3	4	4	3	5	4	4	4	4	3
4	5	5	3	5	5	5	4	3	5	3	4	3	4	4	4	4	4	3	4
5	1	3	3	4	4	3	4	2	4	3	4	3	3	4	3	3	3	4	3
4	4	4	2	3	4	4	3	4	3	4	2	4	4	3	3	3	4	4	3
5	5	5	4	4	3	5	4	3	4	2	4	2	5	4	2	4	4	4	5
1	1	5	1	5	5	1	5	1	5	5	5	4	3	5	5	3	3	3	3
4	3	3	3	5	4	4	5	2	3	5	5	4	5	4	5	4	3	4	2
3	2	5	2	5	5	5	5	3	5	5	4	2	4	5	5	4	5	5	3
4	4	4	3	4	4	4	4	4	4	4	4	4	4	4	3	4	4	3	4
5	3	4	2	2	5	4	5	2	4	4	4	5	5	5	4	3	3	4	3
4	4	5	4	5	5	2	3	1	4	3	4	3	2	3	3	2	4	4	4
5	1	4	3	4	5	4	4	3	4	5	3	4	4	4	4	5	4	4	3
5	2	3	3	4	4	3	5	3	5	5	3	4	3	4	2	3	4	4	5
4	4	4	2	4	4	3	4	3	4	4	4	2	4	4	3	4	4	4	3
4	2	3	4	4	4	2	1	3	3	2	2	4	3	4	3	3	3	2	2
3	3	4	2	4	2	4	4	2	4	3	4	3	4	4	3	4	4	3	4
4	2	3	4	3	3	4	5	3	4	4	4	2	4	4	4	4	3	4	2
2	4	5	4	4	4	5	5	4	5	4	4	2	4	4	2	2	3	4	3
5	2	5	4	5	5	5	4	2	4	4	4	4	3	4	4	5	3	4	3
4	3	4	2	5	5	4	5	1	2	4	3	4	3	5	3	2	3	4	1
5	3	4	1	2	3	4	4	3	4	4	4	4	4	4	4	4	4	4	3
4	4	3	4	4	4	4	4	4	4	3	4	4	4	5	4	4	3	4	4
2	4	3	3	4	4	4	3	3	4	2	4	3	4	2	3	4	3	3	3
4	5	5	3	2	3	3	5	4	5	3	3	2	4	3	3	5	3	3	4
2	2	5	5	5	5	5	5	3	4	5	4	4	4	5	4	5	5	5	5
3	1	4	2	3	5	4	4	3	5	4	5	4	4	4	3	4	3	4	3
3	4	4	2	3	2	3	2	3	4	2	4	2	3	2	3	2	2	2	2
3	3	2	4	4	2	3	2	4	2	4	4	2	3	2	3	4	NA	2	4
5	1	4	4	4	3	1	4	2	5	3	4	4	3	4	3	4	3	4	3
5	2	4	4	4	4	4	4	4	5	4	4	4	5	4	3	4	4	3	4
3	2	4	3	5	4	NA	4	3	4	4	4	5	3	4	2	3	4	4	4
5	4	2	2	4	5	4	4	2	5	4	5	4	4	4	4	4	3	4	2
5	2	4	3	5	4	3	4	2	5	3	4	4	4	5	3	4	3	4	4
4	3	3	3	4	4	3	3	4	5	5	3	3	3	3	3	3	3	3	3
4	4	4	4	4	4	4	4	4	5	5	4	3	2	4	4	4	4	3	3
4	5	NA	3	4	4	4	5	1	4	4	2	2	4	2	2	4	2	2	4
4	4	5	3	5	5	4	3	2	3	4	4	4	3	4	3	3	5	3	5
5	3	4	3	4	5	5	5	2	4	3	2	4	2	4	2	2	3	4	2
4	4	5	4	4	5	4	4	4	4	4	4	4	4	4	3	3	4	3	4
5	2	4	3	1	3	4	1	4	5	3	4	1	4	4	5	2	3	NA	2
5	1	4	4	4	5	5	5	3	4	4	4	5	4	4	4	3	4	4	4
4	3	4	4	4	5	4	4	2	4	4	2	4	4	4	3	5	3	2	3
3	3	4	4	3	4	3	4	4	3	4	4	3	4	2	3	3	3	4	3
4	4	4	3	4	4	2	3	2	4	4	2	5	2	4	3	3	3	4	2
4	4	5	3	4	5	4	4	1	4	3	3	4	2	2	3	5	2	3	3
3	1	4	1	3	2	2	4	1	3	4	4	4	2	5	3	3	3	4	1
4	2	5	3	4	3	5	5	3	5	3	4	3	4	5	3	4	2	4	5
5	3	4	5	5	5	4	4	3	4	4	5	3	4	4	5	5	2	3	4
4	1	5	5	5	5	5	5	4	5	5	3	5	1	5	5	5	5	5	3
2	4	3	3	4	4	4	5	2	4	3	4	3	4	4	4	4	4	3	3
4	2	3	4	5	5	3	4	2	5	5	4	3	4	3	3	4	3	3	3
5	3	3	2	4	3	3	4	2	5	3	4	4	3	3	3	3	3	3	3
5	2	2	3	NA	NA	NA	3	3	3	3	3	NA	3	3	3	3	3	4	4
5	4	5	3	3	4	4	5	3	5	4	3	5	4	5	3	4	3	3	1
4	3	4	3	3	3	3	4	3	3	4	3	3	4	3	3	3	3	4	3
5	3	5	4	5	5	1	5	4	5	5	3	4	3	5	4	3	2	4	3
5	2	3	1	2	3	2	2	5	5	3	2	4	3	3	3	3	4	3	3
5	1	3	2	4	3	3	4	3	2	3	3	4	3	3	3	3	3	4	3
5	3	4	4	4	5	4	4	4	3	4	4	3	4	4	4	4	3	4	4
5	5	5	5	5	5	4	5	5	5	4	5	5	5	5	5	4	3	5	5
4	2	5	4	5	3	3	4	5	4	4	4	4	4	3	5	4	3	5	3
5	4	2	3	3	3	2	2	2	3	3	4	4	3	3	4	2	2	4	2
4	1	5	3	5	5	4	4	3	5	5	4	4	3	4	3	4	5	4	3
5	2	4	4	3	4	3	4	2	4	5	4	3	3	4	4	3	3	4	3
4	1	4	3	4	4	4	4	3	4	4	3	4	4	4	3	4	5	4	2
4	2	5	3	4	4	3	3	2	4	4	4	4	3	4	3	3	4	2	2
4	3	2	2	2	3	2	2	1	3	2	1	1	3	2	4	2	4	2	1
4	5	5	5	5	5	5	5	3	5	2	5	5	5	4	4	5	4	4	4
3	3	3	2	2	3	2	2	2	2	3	4	4	2	3	2	2	2	3	3
3	2	2	2	4	4	4	3	2	4	3	1	2	3	2	4	4	4	2	3
4	3	4	4	4	4	3	3	1	4	3	2	3	4	2	3	4	4	4	2
4	3	4	4	5	5	4	4	4	4	3	4	3	3	3	4	4	4	4	4
5	3	1	2	4	3	4	3	3	4	4	4	3	3	4	4	4	4	3	4
3	2	2	4	4	4	3	4	1	5	4	4	4	3	3	3	4	4	2	4
3	3	4	4	3	4	4	4	2	4	4	2	3	4	2	4	2	3	4	3
5	3	4	4	4	4	3	4	2	4	3	4	4	4	4	4	4	4	4	2
4	4	5	3	4	5	5	4	2	4	3	4	4	4	4	4	5	4	3	3
5	NA	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	1
2	4	4	3	5	4	4	4	1	4	3	5	4	4	4	3	5	4	5	3
4	3	4	4	5	4	3	5	2	5	5	4	5	4	5	4	4	4	4	4
4	4	5	5	5	5	5	4	4	5	5	4	5	5	5	5	5	5	5	5
3	2	5	4	4	5	1	5	1	3	5	4	5	3	4	3	5	3	5	2
5	3	4	4	4	4	4	5	3	4	3	4	3	4	4	4	4	4	4	3
2	4	4	3	5	4	5	4	1	3	3	3	5	5	4	3	4	4	3	2
5	3	4	4	5	4	4	4	2	3	3	3	3	3	4	3	3	3	3	3
5	3	4	3	4	4	3	4	1	5	4	3	4	1	3	3	4	4	4	2
4	1	3	4	4	4	3	5	2	4	4	4	4	4	4	3	3	4	4	4
4	2	2	3	4	3	2	4	2	4	3	3	4	3	4	4	4	4	3	5
5	4	5	4	4	5	5	5	3	4	3	3	3	4	4	3	4	5	4	3
3	5	4	4	2	2	5	4	3	5	1	1	1	3	4	4	2	1	1	3
3	2	5	4	5	4	5	4	1	3	4	1	4	2	4	3	4	5	4	1
5	5	4	4	5	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
5	2	5	4	5	5	2	5	1	3	4	4	4	2	5	3	2	4	4	4
5	1	5	3	4	4	4	4	1	3	5	4	5	4	4	2	3	5	2	1
5	1	5	4	4	5	5	5	4	5	NA	4	4	4	5	5	5	4	4	4
3	2	2	4	5	3	3	5	2	2	2	4	2	3	4	1	4	4	2	2
4	3	NA	5	4	4	NA	5	4	5	3	5	5	4	3	5	4	4	4	5
5	3	4	4	3	4	4	5	3	3	4	3	4	3	4	4	3	4	4	3
4	1	5	3	5	5	4	4	3	4	5	3	4	4	5	4	4	5	4	3
4	2	4	3	4	3	4	4	3	3	3	2	4	4	1	3	3	2	4	4
2	4	2	4	1	1	1	2	5	4	2	3	1	1	4	2	2	2	NA	1
4	3	4	4	4	4	3	4	3	3	5	4	4	3	3	4	3	4	3	4
5	3	3	4	2	2	5	4	4	3	2	2	3	4	5	2	3	3	1	3
4	2	4	4	4	4	4	3	4	4	4	5	2	5	5	4	2	4	4	4
5	3	4	2	5	5	4	5	2	5	5	3	5	5	5	3	4	4	4	2
5	1	5	4	4	5	5	5	4	5	5	4	4	4	5	4	5	5	4	4
3	3	2	4	3	3	2	4	3	2	5	3	5	2	3	NA	2	3	2	1
4	3	2	3	3	2	3	3	4	3	4	3	4	3	3	3	4	3	3	4
3	3	4	4	4	4	3	4	3	4	4	4	4	4	3	4	4	4	2	4
5	2	4	4	4	4	5	4	2	4	4	4	4	2	4	4	4	4	4	3
4	4	3	5	4	4	5	5	4	5	3	2	1	4	4	5	5	2	4	2
5	4	3	4	4	5	4	4	3	5	4	2	3	4	2	2	3	3	3	3
4	3	2	2	3	2	4	3	4	4	4	3	2	2	2	4	5	2	3	4
4	3	4	3	4	5	3	5	1	4	5	1	4	3	3	3	2	4	4	3
5	4	5	4	5	5	5	5	2	4	3	4	4	4	5	4	5	5	5	5
4	4	5	4	1	3	3	5	2	4	5	5	5	4	2	3	3	4	4	4
5	4	5	3	4	5	5	4	2	5	4	4	4	4	5	4	4	3	4	3
3	1	4	4	5	4	2	3	1	4	4	4	3	4	5	3	3	4	3	2
4	2	4	4	5	5	4	5	2	3	4	4	4	3	4	3	3	4	4	3
3	3	4	4	4	4	3	4	2	3	4	2	4	3	4	2	4	3	4	3
5	3	4	2	4	5	5	4	3	5	5	3	4	3	4	3	4	4	3	2
5	4	4	4	2	5	5	4	4	4	4	4	2	4	4	4	1	3	5	4
3	3	3	3	3	3	3	3	3	3	3	3	3	3	3	3	3	3	3	3
5	4	5	3	5	4	5	4	3	5	5	3	5	3	4	3	3	4	4	4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 11 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271389&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]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271389&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271389&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 time11 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
11.14407260.88282230.85
2-0.27116206-0.2897150-0.21
31.07382280.86260250.82
40.181691080.22146860.26
50.92346400.79254320.78
61.15399190.91274170.88
70.59251560.64194460.62
81.05375280.86275250.83
9-0.4972235-0.5362171-0.47
100.98347230.88259220.84
110.74274290.81215260.78
120.51227570.6195460.62
130.6256570.64207500.61
140.42203630.53173530.53
150.72290530.69222460.66
160.35168510.53140480.49
170.58234420.7189380.67
180.62244390.72195330.71
190.54228520.63197440.63
200.081481230.09123940.13

\begin{tabular}{lllllllll}
\hline
Summary of survey scores (median of Likert score was subtracted) \tabularnewline
Question & mean & Sum ofpositives (Ps) & Sum ofnegatives (Ns) & (Ps-Ns)/(Ps+Ns) & Count ofpositives (Pc) & Count ofnegatives (Nc) & (Pc-Nc)/(Pc+Nc) \tabularnewline
1 & 1.14 & 407 & 26 & 0.88 & 282 & 23 & 0.85 \tabularnewline
2 & -0.27 & 116 & 206 & -0.28 & 97 & 150 & -0.21 \tabularnewline
3 & 1.07 & 382 & 28 & 0.86 & 260 & 25 & 0.82 \tabularnewline
4 & 0.18 & 169 & 108 & 0.22 & 146 & 86 & 0.26 \tabularnewline
5 & 0.92 & 346 & 40 & 0.79 & 254 & 32 & 0.78 \tabularnewline
6 & 1.15 & 399 & 19 & 0.91 & 274 & 17 & 0.88 \tabularnewline
7 & 0.59 & 251 & 56 & 0.64 & 194 & 46 & 0.62 \tabularnewline
8 & 1.05 & 375 & 28 & 0.86 & 275 & 25 & 0.83 \tabularnewline
9 & -0.49 & 72 & 235 & -0.53 & 62 & 171 & -0.47 \tabularnewline
10 & 0.98 & 347 & 23 & 0.88 & 259 & 22 & 0.84 \tabularnewline
11 & 0.74 & 274 & 29 & 0.81 & 215 & 26 & 0.78 \tabularnewline
12 & 0.51 & 227 & 57 & 0.6 & 195 & 46 & 0.62 \tabularnewline
13 & 0.6 & 256 & 57 & 0.64 & 207 & 50 & 0.61 \tabularnewline
14 & 0.42 & 203 & 63 & 0.53 & 173 & 53 & 0.53 \tabularnewline
15 & 0.72 & 290 & 53 & 0.69 & 222 & 46 & 0.66 \tabularnewline
16 & 0.35 & 168 & 51 & 0.53 & 140 & 48 & 0.49 \tabularnewline
17 & 0.58 & 234 & 42 & 0.7 & 189 & 38 & 0.67 \tabularnewline
18 & 0.62 & 244 & 39 & 0.72 & 195 & 33 & 0.71 \tabularnewline
19 & 0.54 & 228 & 52 & 0.63 & 197 & 44 & 0.63 \tabularnewline
20 & 0.08 & 148 & 123 & 0.09 & 123 & 94 & 0.13 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271389&T=1

[TABLE]
[ROW][C]Summary of survey scores (median of Likert score was subtracted)[/C][/ROW]
[ROW][C]Question[/C][C]mean[/C][C]Sum ofpositives (Ps)[/C][C]Sum ofnegatives (Ns)[/C][C](Ps-Ns)/(Ps+Ns)[/C][C]Count ofpositives (Pc)[/C][C]Count ofnegatives (Nc)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]1[/C][C]1.14[/C][C]407[/C][C]26[/C][C]0.88[/C][C]282[/C][C]23[/C][C]0.85[/C][/ROW]
[ROW][C]2[/C][C]-0.27[/C][C]116[/C][C]206[/C][C]-0.28[/C][C]97[/C][C]150[/C][C]-0.21[/C][/ROW]
[ROW][C]3[/C][C]1.07[/C][C]382[/C][C]28[/C][C]0.86[/C][C]260[/C][C]25[/C][C]0.82[/C][/ROW]
[ROW][C]4[/C][C]0.18[/C][C]169[/C][C]108[/C][C]0.22[/C][C]146[/C][C]86[/C][C]0.26[/C][/ROW]
[ROW][C]5[/C][C]0.92[/C][C]346[/C][C]40[/C][C]0.79[/C][C]254[/C][C]32[/C][C]0.78[/C][/ROW]
[ROW][C]6[/C][C]1.15[/C][C]399[/C][C]19[/C][C]0.91[/C][C]274[/C][C]17[/C][C]0.88[/C][/ROW]
[ROW][C]7[/C][C]0.59[/C][C]251[/C][C]56[/C][C]0.64[/C][C]194[/C][C]46[/C][C]0.62[/C][/ROW]
[ROW][C]8[/C][C]1.05[/C][C]375[/C][C]28[/C][C]0.86[/C][C]275[/C][C]25[/C][C]0.83[/C][/ROW]
[ROW][C]9[/C][C]-0.49[/C][C]72[/C][C]235[/C][C]-0.53[/C][C]62[/C][C]171[/C][C]-0.47[/C][/ROW]
[ROW][C]10[/C][C]0.98[/C][C]347[/C][C]23[/C][C]0.88[/C][C]259[/C][C]22[/C][C]0.84[/C][/ROW]
[ROW][C]11[/C][C]0.74[/C][C]274[/C][C]29[/C][C]0.81[/C][C]215[/C][C]26[/C][C]0.78[/C][/ROW]
[ROW][C]12[/C][C]0.51[/C][C]227[/C][C]57[/C][C]0.6[/C][C]195[/C][C]46[/C][C]0.62[/C][/ROW]
[ROW][C]13[/C][C]0.6[/C][C]256[/C][C]57[/C][C]0.64[/C][C]207[/C][C]50[/C][C]0.61[/C][/ROW]
[ROW][C]14[/C][C]0.42[/C][C]203[/C][C]63[/C][C]0.53[/C][C]173[/C][C]53[/C][C]0.53[/C][/ROW]
[ROW][C]15[/C][C]0.72[/C][C]290[/C][C]53[/C][C]0.69[/C][C]222[/C][C]46[/C][C]0.66[/C][/ROW]
[ROW][C]16[/C][C]0.35[/C][C]168[/C][C]51[/C][C]0.53[/C][C]140[/C][C]48[/C][C]0.49[/C][/ROW]
[ROW][C]17[/C][C]0.58[/C][C]234[/C][C]42[/C][C]0.7[/C][C]189[/C][C]38[/C][C]0.67[/C][/ROW]
[ROW][C]18[/C][C]0.62[/C][C]244[/C][C]39[/C][C]0.72[/C][C]195[/C][C]33[/C][C]0.71[/C][/ROW]
[ROW][C]19[/C][C]0.54[/C][C]228[/C][C]52[/C][C]0.63[/C][C]197[/C][C]44[/C][C]0.63[/C][/ROW]
[ROW][C]20[/C][C]0.08[/C][C]148[/C][C]123[/C][C]0.09[/C][C]123[/C][C]94[/C][C]0.13[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271389&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271389&T=1

As an alternative you can also use a QR Code:  

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

Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
11.14407260.88282230.85
2-0.27116206-0.2897150-0.21
31.07382280.86260250.82
40.181691080.22146860.26
50.92346400.79254320.78
61.15399190.91274170.88
70.59251560.64194460.62
81.05375280.86275250.83
9-0.4972235-0.5362171-0.47
100.98347230.88259220.84
110.74274290.81215260.78
120.51227570.6195460.62
130.6256570.64207500.61
140.42203630.53173530.53
150.72290530.69222460.66
160.35168510.53140480.49
170.58234420.7189380.67
180.62244390.72195330.71
190.54228520.63197440.63
200.081481230.09123940.13







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.959 (0)0.959 (0)
(Ps-Ns)/(Ps+Ns)0.959 (0)1 (0)0.999 (0)
(Pc-Nc)/(Pc+Nc)0.959 (0)0.999 (0)1 (0)

\begin{tabular}{lllllllll}
\hline
Pearson correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.959 (0) & 0.959 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.959 (0) & 1 (0) & 0.999 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.959 (0) & 0.999 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271389&T=2

[TABLE]
[ROW][C]Pearson correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0)[/C][C]0.959 (0)[/C][C]0.959 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.959 (0)[/C][C]1 (0)[/C][C]0.999 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.959 (0)[/C][C]0.999 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271389&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271389&T=2

As an alternative you can also use a QR Code:  

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

Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.959 (0)0.959 (0)
(Ps-Ns)/(Ps+Ns)0.959 (0)1 (0)0.999 (0)
(Pc-Nc)/(Pc+Nc)0.959 (0)0.999 (0)1 (0)







Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.915 (0)0.878 (0)
(Ps-Ns)/(Ps+Ns)0.915 (0)1 (0)0.952 (0)
(Pc-Nc)/(Pc+Nc)0.878 (0)0.952 (0)1 (0)

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.915 (0) & 0.878 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.915 (0) & 1 (0) & 0.952 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.878 (0) & 0.952 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271389&T=3

[TABLE]
[ROW][C]Kendall tau rank correlations of survey scores (and p-values)[/C][/ROW]
[ROW][C][/C][C]mean[/C][C](Ps-Ns)/(Ps+Ns)[/C][C](Pc-Nc)/(Pc+Nc)[/C][/ROW]
[ROW][C]mean[/C][C]1 (0)[/C][C]0.915 (0)[/C][C]0.878 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.915 (0)[/C][C]1 (0)[/C][C]0.952 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.878 (0)[/C][C]0.952 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271389&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271389&T=3

As an alternative you can also use a QR Code:  

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

Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.915 (0)0.878 (0)
(Ps-Ns)/(Ps+Ns)0.915 (0)1 (0)0.952 (0)
(Pc-Nc)/(Pc+Nc)0.878 (0)0.952 (0)1 (0)



Parameters (Session):
par1 = 1 2 3 4 5 ;
Parameters (R input):
par1 = 1 2 3 4 5 ;
R code (references can be found in the software module):
docor <- function(x,y,method) {
r <- cor.test(x,y,method=method)
paste(round(r$estimate,3),' (',round(r$p.value,3),')',sep='')
}
x <- t(x)
nx <- length(x[,1])
cx <- length(x[1,])
mymedian <- median(as.numeric(strsplit(par1,' ')[[1]]))
myresult <- array(NA, dim = c(cx,7))
rownames(myresult) <- paste('Q',1:cx,sep='')
colnames(myresult) <- c('mean','Sum of
positives (Ps)','Sum of
negatives (Ns)', '(Ps-Ns)/(Ps+Ns)', 'Count of
positives (Pc)', 'Count of
negatives (Nc)', '(Pc-Nc)/(Pc+Nc)')
for (i in 1:cx) {
spos <- 0
sneg <- 0
cpos <- 0
cneg <- 0
for (j in 1:nx) {
if (!is.na(x[j,i])) {
myx <- as.numeric(x[j,i]) - mymedian
if (myx > 0) {
spos = spos + myx
cpos = cpos + 1
}
if (myx < 0) {
sneg = sneg + abs(myx)
cneg = cneg + 1
}
}
}
myresult[i,1] <- round(mean(as.numeric(x[,i]),na.rm=T)-mymedian,2)
myresult[i,2] <- spos
myresult[i,3] <- sneg
myresult[i,4] <- round((spos - sneg) / (spos + sneg),2)
myresult[i,5] <- cpos
myresult[i,6] <- cneg
myresult[i,7] <- round((cpos - cneg) / (cpos + cneg),2)
}
myresult
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of survey scores (median of Likert score was subtracted)',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Question',header=TRUE)
for (i in 1:7) {
a<-table.element(a,colnames(myresult)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:cx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
for (j in 1:7) {
a<-table.element(a,myresult[i,j],align='right')
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='pearson'),align='right')
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,'Kendall tau rank correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')