Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_surveyscores.wasp
Title produced by softwareSurvey Scores
Date of computationThu, 07 Dec 2017 13:09:42 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/07/t1512649914wtkprt32dd6hicm.htm/, Retrieved Thu, 31 Oct 2024 23:24:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308701, Retrieved Thu, 31 Oct 2024 23:24:20 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsDatabase 1: column AI-AR
Estimated Impact153
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Survey Scores] [Survey Scores Ran...] [2017-12-07 12:09:42] [79eb5143bcf363cf12f20cb866038ece] [Current]
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Dataseries X:
3	5	5	5	5	5	5	5	5	5
5	5	4	4	2	3	5	5	3	5
4	4	4	4	3	4	4	4	4	5
4	4	3	3	4	4	4	4	3	5
5	5	5	4	3	5	3	3	3	4
5	4	4	5	4	5	5	4	4	5
5	5	5	4	2	5	5	5	5	4
5	5	4	5	1	5	5	5	5	4
5	4	4	4	3	4	4	3	4	3
5	4	4	4	2	4	4	4	5	3
4	5	4	4	4	3	4	4	3	4
3	5	3	4	3	4	3	4	4	5
4	4	5	4	4	4	4	3	4	4
5	5	3	4	4	4	4	4	4	4
4	4	3	3	3	4	5	4	5	3
3	4	3	4	4	3	4	3	4	5
5	5	4	4	4	4	4	5	5	5
5	5	5	5	1	5	4	3	3	5
5	5	5	5	5	5	5	5	4	5
3	4	4	4	3	3	3	5	5	3
5	4	3	3	3	4	4	4	4	4
4	4	3	3	3	3	4	3	4	3
5	5	4	4	3	3	3	2	2	3
3	4	5	4	3	2	4	4	5	2
4	4	4	4	5	4	3	4	4	4
4	4	4	4	4	4	4	5	4	4
4	5	5	4	3	5	5	5	3	5
5	5	4	4	2	4	3	3	4	3
5	5	4	4	1	5	4	5	5	4
3	4	4	3	3	4	3	3	4	4
1	4	4	2	2	1	4	4	3	4
5	5	4	5	5	4	5	5	5	4
5	5	5	3	1	5	5	5	5	4
3	5	4	4	5	5	5	2	4	4
5	3	3	3	4	2	4	5	5	5
4	4	4	4	3	4	4	5	3	4
4	4	3	3	3	4	3	3	3	4
4	4	3	3	3	3	3	4	3	3
4	4	4	4	2	3	3	3	4	3
4	4	4	4	4	4	4	3	3	4
5	3	2	4	3	2	5	5	4	3
4	4	3	4	1	4	4	4	5	3
3	5	4	4	2	3	4	4	3	3
5	5	4	5	4	5	4	5	5	5
4	4	4	4	3	4	4	3	4	4
4	4	3	3	2	3	3	2	2	4
5	5	5	4	4	5	4	5	5	4
5	5	5	5	3	5	5	5	4	5
5	5	5	5	4	5	5	5	5	5
3	4	4	4	3	4	4	4	3	3
4	5	4	4	4	4	5	5	5	4
4	4	4	4	4	4	3	3	4	4
4	4	4	4	4	4	4	4	4	4
5	4	4	4	3	4	4	5	5	5
2	4	4	4	3	3	4	4	4	4
4	4	4	5	4	5	4	4	4	4
3	4	3	4	3	4	3	3	3	3
5	5	4	3	4	4	3	4	4	5
5	5	5	4	5	4	3	4	2	4
5	5	5	5	4	5	5	5	5	5
5	4	4	4	4	4	4	3	4	4
4	4	4	4	4	4	4	4	5	4
4	4	4	4	4	4	4	4	5	4
5	4	4	3	3	5	5	4	4	4
4	2	3	4	2	4	1	2	4	4
4	4	4	3	3	4	5	5	5	4
4	4	3	4	1	3	3	2	3	3
4	4	4	4	4	4	4	5	3	4
4	4	4	4	5	5	5	2	2	4
4	4	4	3	2	4	4	4	3	4
4	3	4	4	3	3	4	4	2	4
3	4	5	4	3	4	5	5	5	4
4	4	4	5	2	5	5	5	5	5
4	4	4	4	4	4	5	3	5	4
3	4	4	3	4	4	4	5	5	4
5	5	5	4	2	4	4	4	3	4
4	3	3	3	3	4	3	3	3	3
5	4	5	5	2	4	4	5	5	3
3	3	3	3	3	3	3	3	1	5
5	5	3	3	2	4	3	2	2	4
5	5	5	5	3	4	4	5	5	4
4	4	4	3	4	4	4	1	1	3
3	3	4	4	4	4	3	4	4	4
5	5	5	5	3	5	5	5	5	1
5	4	4	4	4	4	5	5	4	4
5	2	3	3	5	4	2	2	3	5
4	5	4	4	3	5	5	5	5	4
3	4	4	4	3	4	4	4	4	4
4	4	4	4	3	4	5	4	4	4
3	4	4	4	4	4	4	4	4	4
4	4	4	4	3	4	4	4	4	4
5	5	4	5	3	4	5	5	5	4
4	4	4	4	3	4	4	5	4	4
4	4	4	4	4	4	4	4	4	2
4	4	4	4	2	4	3	3	4	5
5	5	5	4	5	5	5	5	4	4
5	5	5	5	5	4	4	4	5	4
4	4	4	4	3	4	3	4	4	3
4	4	4	4	5	3	4	4	3	4
4	4	4	4	3	4	4	4	4	4
5	4	4	4	3	4	4	4	5	3
4	4	4	4	3	3	3	3	3	4
4	4	4	4	2	5	5	5	5	5
4	4	4	4	2	4	4	4	4	4
5	5	4	4	3	4	4	4	4	4
5	5	5	4	2	5	4	4	4	5
4	4	4	4	1	4	4	4	4	4
5	5	5	4	2	4	4	4	5	5
3	3	3	3	3	3	3	3	3	3
4	3	4	4	4	4	4	4	4	4
3	4	3	4	3	3	2	3	3	4
5	4	4	4	4	4	5	4	1	5
4	4	4	3	3	4	2	2	2	4
4	4	4	3	3	4	2	2	2	4
5	4	5	5	5	5	5	5	4	5
5	5	5	5	4	5	5	4	4	4
5	5	4	4	4	4	5	4	4	4
3	2	2	2	2	2	3	2	1	4
5	5	5	5	4	4	3	3	3	5
3	4	3	4	4	4	3	4	3	4
4	4	4	3	3	4	4	4	4	5
4	4	4	4	4	4	4	5	5	4
4	4	3	3	2	3	4	2	2	3
4	3	3	3	3	4	3	2	2	3
4	3	3	3	3	2	2	4	4	4
4	4	3	4	4	3	4	5	5	5
5	4	5	5	3	4	4	4	4	5
5	5	3	3	4	3	3	3	3	4
5	3	2	2	1	4	4	4	4	3
3	4	3	3	3	4	4	4	3	4
4	2	3	3	2	2	4	4	3	2
4	5	4	4	3	4	4	3	3	4
4	4	4	4	4	4	4	4	4	4
4	5	4	4	4	3	3	4	3	3
4	4	4	3	5	3	3	4	4	4
4	4	4	5	3	5	4	1	5	5
5	4	4	4	3	5	5	4	4	4
4	4	3	3	4	3	3	3	3	3
5	3	2	3	3	5	4	3	3	3
5	5	4	3	4	4	4	4	3	4
4	3	3	3	3	3	3	4	4	3
4	4	5	5	2	5	4	2	3	5
3	5	4	3	3	4	4	4	5	4
4	4	4	4	3	4	4	4	4	4
4	4	4	3	3	3	3	3	4	3
3	3	3	3	1	2	2	2	2	3
3	3	2	3	4	2	3	3	3	2
3	4	4	5	5	5	4	4	4	4
4	4	4	4	3	4	4	4	4	4
4	4	4	4	3	4	5	4	3	5
4	4	3	4	4	4	4	4	5	5
4	5	4	4	3	5	5	4	3	4
4	4	4	3	3	4	3	3	4	4
5	5	5	5	5	5	5	3	3	5
5	4	4	4	3	5	5	5	5	4
5	5	5	5	5	4	5	5	3	5
5	4	4	4	3	4	3	3	3	3
5	5	4	4	3	4	5	4	5	4
5	5	4	4	2	4	4	5	5	5
5	5	4	4	3	4	4	4	4	4
3	3	4	3	2	4	3	3	2	3
5	5	4	4	2	4	4	4	4	5
4	3	3	4	2	4	4	3	3	4
4	4	4	4	4	4	3	3	3	3
5	5	5	5	3	3	3	3	3	4
3	4	4	3	3	3	4	2	3	3
4	4	4	4	4	4	4	4	4	4
4	4	4	4	3	4	4	2	3	4
4	4	3	3	2	3	3	3	3	3
4	4	4	3	4	4	3	3	4	4
4	3	2	3	4	4	4	3	4	4
5	4	4	4	5	5	5	4	5	4
4	4	4	3	3	4	3	3	3	4
4	4	4	4	3	4	4	4	4	4
5	5	5	4	4	4	4	4	5	5
4	4	4	4	3	3	4	4	4	4
5	5	4	4	3	4	4	4	4	4
5	4	3	4	2	4	4	4	4	3
4	5	4	4	4	5	5	3	4	4
4	5	5	5	1	4	4	4	5	5
4	4	3	3	3	4	3	4	3	4
4	3	3	3	3	3	4	4	4	4
3	2	2	2	4	3	4	3	4	3
5	5	5	4	4	4	4	4	4	5
5	5	4	4	5	4	4	4	4	4
4	4	3	3	3	4	4	4	4	3
5	5	5	3	3	5	5	3	4	4
4	4	3	4	2	3	5	4	2	4
4	4	5	4	3	3	4	4	4	5
5	3	4	4	3	3	4	5	5	3
3	4	4	4	3	4	4	3	3	4
5	5	4	4	4	4	4	4	4	5
5	4	4	4	3	4	4	4	4	4
3	4	3	4	3	2	1	3	3	3
3	4	4	4	3	3	4	4	3	5
3	3	4	3	3	4	4	3	2	4
3	3	4	4	3	4	3	4	4	4
3	4	3	3	4	4	3	4	3	4
4	5	4	5	4	5	5	3	4	5
3	4	4	4	3	3	3	4	4	4
4	5	5	5	4	3	4	4	5	4
4	3	3	3	2	4	3	2	2	4
5	3	3	3	3	3	3	4	2	3
5	5	5	5	3	5	5	5	5	5
4	4	3	4	5	4	3	3	3	3
5	5	5	4	3	4	4	5	5	5
5	5	4	4	4	4	4	3	4	4
5	3	3	5	3	5	3	4	4	5
5	5	5	5	4	5	5	5	5	5
4	5	5	5	5	3	2	2	4	5
4	5	5	5	5	3	2	2	4	5
3	5	3	2	4	2	3	1	1	2
5	5	4	4	5	5	4	4	3	5
4	4	4	4	3	4	4	4	4	4
5	5	5	3	4	4	3	2	4	4
5	5	4	4	2	4	4	4	4	5
4	5	4	4	4	4	4	2	3	4
5	5	5	5	3	5	5	5	5	4
5	4	1	3	2	1	2	3	3	1
4	4	4	4	2	3	3	3	3	4
4	4	3	4	4	4	3	3	4	4
4	4	4	4	4	4	4	3	3	4
4	4	4	4	4	3	3	4	4	4
4	4	4	4	4	3	4	3	3	4
5	5	4	4	2	4	3	4	4	4
5	5	4	4	2	5	4	4	4	4
5	5	5	4	4	4	5	3	5	5
5	5	5	5	3	4	4	4	5	4
4	4	3	3	3	4	4	3	3	4
5	5	5	5	5	5	5	5	5	5
4	3	3	3	3	3	3	3	3	3
4	4	3	3	3	4	3	4	5	4
4	4	4	4	4	4	3	3	3	4
5	5	5	4	4	4	4	4	5	4
4	4	5	5	4	5	5	4	4	4
4	4	5	5	4	5	5	4	4	4
4	4	5	5	4	5	5	4	4	4
5	5	5	5	4	4	4	5	4	4
5	4	4	3	3	3	3	4	4	3
5	5	5	5	3	5	4	4	4	5
4	4	4	4	4	4	4	4	5	4
4	3	4	4	4	4	5	3	3	3
4	4	5	5	4	5	5	4	5	5
2	4	3	3	2	3	3	3	3	3
4	4	5	4	5	4	5	5	5	5
3	2	3	2	2	2	2	3	3	3
2	2	2	2	1	1	1	1	2	2
2	2	2	2	2	2	3	2	2	2
5	4	4	5	4	4	4	4	4	4
5	5	5	5	5	5	5	3	3	5
3	3	3	3	3	3	3	3	3	3
3	4	3	2	3	3	3	4	2	3
4	4	4	5	5	5	5	4	3	5
3	3	2	3	1	2	2	4	3	3
3	3	3	3	3	3	3	3	3	3
4	4	4	4	4	4	4	5	5	5
3	3	3	3	3	3	3	3	3	3
4	4	3	4	3	3	2	3	3	4
2	2	2	2	2	2	2	2	2	2
4	4	4	4	3	4	2	1	1	4
3	3	3	3	2	3	2	4	3	3
3	3	3	3	3	3	3	3	3	3
4	4	4	4	4	4	4	4	4	4
3	5	4	2	3	4	1	2	4	4
5	4	4	4	2	5	3	2	2	4
4	4	4	4	3	4	4	4	4	4
5	4	4	5	3	3	4	3	3	3
4	4	3	4	2	4	4	4	5	5
5	4	4	4	2	4	3	1	1	5
4	4	4	3	2	3	3	3	3	3
5	4	4	4	2	4	4	3	4	4
4	4	3	3	3	3	3	5	5	3
5	5	4	4	2	5	4	3	3	4
5	4	4	4	3	4	4	4	5	4
4	4	4	4	3	4	4	4	4	5
3	3	4	4	1	3	3	1	5	3
4	3	4	3	2	3	2	2	3	4
4	4	3	4	5	4	3	3	3	4
4	3	3	4	4	4	4	4	5	4
4	3	3	3	3	3	3	3	4	3
5	4	3	3	3	5	3	3	4	5
5	4	4	3	3	4	4	3	5	4
4	4	4	3	3	3	3	3	4	3
5	5	5	5	4	4	3	3	3	3
4	3	4	4	3	3	3	4	5	5
3	3	3	3	2	3	3	4	4	3
3	4	3	3	2	2	2	2	2	2
3	4	3	3	3	3	3	3	3	3
5	5	4	4	2	4	4	3	3	3
3	4	4	3	4	4	3	4	4	5
4	4	4	4	4	4	4	4	4	4
4	4	4	3	3	3	3	3	3	3
4	4	4	4	4	4	3	3	3	5
5	3	3	3	3	4	3	4	4	3
3	3	3	3	3	3	4	3	4	3
5	4	4	4	3	4	4	3	3	3
3	3	3	3	3	3	3	3	3	3
4	2	3	4	3	4	4	4	5	4
5	5	5	5	3	5	5	3	3	5
3	4	4	4	4	4	4	4	4	4
3	3	3	3	2	3	3	4	4	3
4	3	3	3	2	3	3	3	3	3
5	4	4	4	1	4	4	5	5	4
3	3	3	3	3	3	3	3	3	3
4	4	4	5	3	4	4	5	4	4
4	4	4	4	4	4	3	4	4	3
5	4	4	4	3	5	4	3	3	4
3	3	3	3	3	3	3	3	3	3
4	3	4	4	4	3	4	3	3	4
3	4	4	4	1	3	4	3	3	4
3	4	4	4	1	3	3	4	4	4
4	3	3	3	2	4	3	3	4	4
5	4	4	4	3	4	4	3	3	3
3	3	4	4	2	3	3	2	2	3
3	3	3	2	2	3	2	2	4	4
3	4	3	3	3	3	3	2	2	3
4	4	4	4	3	4	4	4	4	4
3	3	4	4	2	3	4	4	4	4
5	4	4	3	2	4	3	3	2	3
5	5	4	4	3	4	3	3	3	4
4	4	4	4	2	4	4	4	4	4
4	3	3	3	3	4	4	4	4	4
4	4	4	4	2	4	3	3	3	3
4	4	3	3	2	4	3	3	3	3
3	3	3	3	4	3	4	3	4	4
3	4	2	3	3	2	2	2	2	3
4	5	4	4	3	4	4	3	3	4
3	4	3	3	2	3	3	3	3	4
4	4	2	2	3	4	3	1	1	3
4	2	3	4	2	3	3	4	4	3
3	3	3	4	3	4	4	4	4	4
3	3	3	3	3	3	3	3	3	4
3	3	4	4	3	3	3	3	3	3
3	3	4	4	2	3	5	4	5	3
4	3	4	3	2	3	2	2	2	3
5	3	4	4	1	4	5	4	4	4
4	4	3	4	4	3	4	4	4	4
5	4	4	3	2	3	3	3	3	3
4	3	3	3	4	3	4	4	3	3
4	4	2	4	3	4	3	2	3	5
4	3	3	3	3	3	3	1	3	3
4	4	3	3	4	2	3	2	2	2
3	2	3	3	3	3	2	2	3	2
3	4	2	3	2	2	2	2	2	4
3	3	3	3	3	3	3	3	3	3
3	4	4	4	4	4	3	3	4	4
4	4	4	4	4	3	3	3	3	3
4	4	4	4	3	3	3	3	3	3
5	4	4	5	1	4	3	4	3	4
5	5	5	5	3	3	3	3	3	5
3	3	3	3	3	3	3	3	3	3
4	4	4	4	3	4	4	4	4	4
4	3	3	3	3	3	3	3	4	3
3	3	2	3	3	3	3	4	4	4
5	4	4	4	2	3	2	2	3	5
5	5	5	5	4	5	4	3	3	4
5	4	3	4	4	4	3	2	2	2
4	4	4	4	3	3	3	3	4	3
3	2	3	3	4	4	2	4	3	3
4	3	4	4	3	4	4	3	4	4
4	3	3	3	3	4	4	4	4	3
3	3	4	4	3	3	4	2	2	3
3	3	3	3	2	4	3	3	4	4
4	2	4	4	2	4	4	5	5	4
3	4	4	4	3	4	2	2	3	3
3	3	2	2	3	3	2	2	2	1
4	3	3	3	2	4	4	4	4	3
3	3	3	4	4	2	4	3	1	3
5	3	4	4	3	4	4	2	3	4
5	4	5	5	3	5	5	5	5	5
3	4	3	3	2	3	3	1	3	2
4	4	4	4	3	4	3	4	4	4
5	5	4	4	3	4	4	2	2	4
4	3	3	3	2	2	3	3	3	3
5	5	5	5	3	5	4	3	3	5
4	5	4	5	2	4	4	3	3	5
3	3	3	3	3	4	4	3	3	2
4	5	5	5	4	5	5	4	5	5
4	3	3	3	3	4	4	4	4	3
4	3	3	3	2	2	3	3	3	3
3	3	3	3	3	3	3	3	4	3
3	3	3	3	3	3	3	2	3	3
5	5	5	5	4	4	4	4	4	4
4	4	5	3	4	4	3	4	4	5
5	5	4	4	2	4	4	4	4	4
3	3	3	3	4	3	3	1	1	3
3	3	3	3	3	3	2	3	3	3
4	4	4	4	2	3	4	4	4	4
4	4	3	2	2	3	3	2	2	4
3	3	3	3	3	3	2	2	4	5
4	4	4	4	4	4	4	4	4	4
3	3	3	3	3	3	3	3	3	3
3	4	3	3	4	4	3	4	4	2
5	3	5	5	3	5	5	3	3	5
3	4	4	4	4	5	4	4	4	4
2	4	1	3	1	2	4	3	4	2
3	4	4	2	1	4	2	1	2	3
4	4	4	3	3	3	3	2	3	2
3	4	3	5	2	3	2	5	5	2
3	3	3	3	3	3	3	3	3	3
3	3	4	4	3	3	4	3	3	3
3	4	3	3	2	2	2	3	3	3
3	4	4	5	3	5	4	5	5	5
5	4	4	4	2	4	4	3	4	3
4	4	4	4	3	3	3	2	3	4
4	4	4	4	3	4	3	4	4	4
3	4	4	2	3	2	2	4	4	3
5	5	4	5	2	4	4	4	4	4
4	3	3	3	3	3	3	3	3	3
5	5	5	5	4	5	5	4	5	5
4	4	4	4	3	4	4	4	4	4
4	4	3	3	3	3	3	4	4	3
4	4	4	3	2	4	2	2	2	3
5	3	4	4	2	4	3	4	5	4
3	3	4	5	4	3	4	5	4	4
4	4	4	4	2	4	4	2	4	3
5	4	4	5	2	4	2	3	4	5
4	4	3	4	3	3	2	4	3	2
4	4	4	4	3	4	4	4	4	4
4	4	4	3	3	4	4	3	3	3
5	2	3	3	2	2	2	1	1	3
4	4	3	4	4	4	5	2	2	3
3	4	5	4	3	3	3	4	4	3
4	3	3	3	3	3	3	2	3	3
4	3	4	4	4	4	4	2	4	4
3	4	4	3	2	3	4	4	3	4
4	3	4	3	4	4	3	4	3	4
3	3	3	3	3	3	3	3	3	3
3	4	4	4	4	4	2	2	2	3
4	4	4	4	4	4	4	4	5	4
5	5	5	5	1	4	2	2	2	5
5	3	3	3	4	4	4	4	5	2
4	4	4	3	4	2	2	2	3	4
4	3	4	4	2	4	2	2	2	2
4	4	5	5	3	4	4	5	4	5
5	3	2	2	1	4	4	4	3	3
4	3	3	4	3	2	3	3	3	2
4	5	3	4	4	4	5	5	5	4
4	4	4	4	3	3	4	4	5	4
5	5	5	5	4	5	4	4	4	5
4	4	3	3	2	3	3	5	5	4
4	3	3	3	2	3	4	4	4	4
4	3	3	4	3	3	4	4	4	3
5	4	5	5	3	4	4	4	4	4
4	3	3	3	3	3	3	3	3	3
4	3	3	3	2	3	4	3	4	3




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308701&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=308701&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308701&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







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)
11.0447480.9733670.96
20.94435150.93330150.91
30.77366220.89294200.87
40.76356180.9286180.88
50.071691360.111421140.11
60.72354330.83287300.81
70.62324480.74257440.71
80.49301840.56239710.54
90.61334620.69251510.66
100.78377280.86291250.84

\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 & 1.04 & 474 & 8 & 0.97 & 336 & 7 & 0.96 \tabularnewline
2 & 0.94 & 435 & 15 & 0.93 & 330 & 15 & 0.91 \tabularnewline
3 & 0.77 & 366 & 22 & 0.89 & 294 & 20 & 0.87 \tabularnewline
4 & 0.76 & 356 & 18 & 0.9 & 286 & 18 & 0.88 \tabularnewline
5 & 0.07 & 169 & 136 & 0.11 & 142 & 114 & 0.11 \tabularnewline
6 & 0.72 & 354 & 33 & 0.83 & 287 & 30 & 0.81 \tabularnewline
7 & 0.62 & 324 & 48 & 0.74 & 257 & 44 & 0.71 \tabularnewline
8 & 0.49 & 301 & 84 & 0.56 & 239 & 71 & 0.54 \tabularnewline
9 & 0.61 & 334 & 62 & 0.69 & 251 & 51 & 0.66 \tabularnewline
10 & 0.78 & 377 & 28 & 0.86 & 291 & 25 & 0.84 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308701&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]1.04[/C][C]474[/C][C]8[/C][C]0.97[/C][C]336[/C][C]7[/C][C]0.96[/C][/ROW]
[ROW][C]2[/C][C]0.94[/C][C]435[/C][C]15[/C][C]0.93[/C][C]330[/C][C]15[/C][C]0.91[/C][/ROW]
[ROW][C]3[/C][C]0.77[/C][C]366[/C][C]22[/C][C]0.89[/C][C]294[/C][C]20[/C][C]0.87[/C][/ROW]
[ROW][C]4[/C][C]0.76[/C][C]356[/C][C]18[/C][C]0.9[/C][C]286[/C][C]18[/C][C]0.88[/C][/ROW]
[ROW][C]5[/C][C]0.07[/C][C]169[/C][C]136[/C][C]0.11[/C][C]142[/C][C]114[/C][C]0.11[/C][/ROW]
[ROW][C]6[/C][C]0.72[/C][C]354[/C][C]33[/C][C]0.83[/C][C]287[/C][C]30[/C][C]0.81[/C][/ROW]
[ROW][C]7[/C][C]0.62[/C][C]324[/C][C]48[/C][C]0.74[/C][C]257[/C][C]44[/C][C]0.71[/C][/ROW]
[ROW][C]8[/C][C]0.49[/C][C]301[/C][C]84[/C][C]0.56[/C][C]239[/C][C]71[/C][C]0.54[/C][/ROW]
[ROW][C]9[/C][C]0.61[/C][C]334[/C][C]62[/C][C]0.69[/C][C]251[/C][C]51[/C][C]0.66[/C][/ROW]
[ROW][C]10[/C][C]0.78[/C][C]377[/C][C]28[/C][C]0.86[/C][C]291[/C][C]25[/C][C]0.84[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308701&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308701&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)
11.0447480.9733670.96
20.94435150.93330150.91
30.77366220.89294200.87
40.76356180.9286180.88
50.071691360.111421140.11
60.72354330.83287300.81
70.62324480.74257440.71
80.49301840.56239710.54
90.61334620.69251510.66
100.78377280.86291250.84







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.969 (0)0.973 (0)
(Ps-Ns)/(Ps+Ns)0.969 (0)1 (0)1 (0)
(Pc-Nc)/(Pc+Nc)0.973 (0)1 (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) & 0.969 (0) & 0.973 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.969 (0) & 1 (0) & 1 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.973 (0) & 1 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308701&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]0.969 (0)[/C][C]0.973 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.969 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.973 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308701&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308701&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)0.969 (0)0.973 (0)
(Ps-Ns)/(Ps+Ns)0.969 (0)1 (0)1 (0)
(Pc-Nc)/(Pc+Nc)0.973 (0)1 (0)1 (0)







Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.867 (0)0.867 (0)
(Ps-Ns)/(Ps+Ns)0.867 (0)1 (0)1 (0)
(Pc-Nc)/(Pc+Nc)0.867 (0)1 (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) & 0.867 (0) & 0.867 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.867 (0) & 1 (0) & 1 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.867 (0) & 1 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308701&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]0.867 (0)[/C][C]0.867 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.867 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.867 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308701&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308701&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)0.867 (0)0.867 (0)
(Ps-Ns)/(Ps+Ns)0.867 (0)1 (0)1 (0)
(Pc-Nc)/(Pc+Nc)0.867 (0)1 (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)
}
print(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')