Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_surveyscores.wasp
Title produced by softwareSurvey Scores
Date of computationSun, 03 May 2020 15:02:56 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/May/03/t1588511357p2nyfzc8piauv56.htm/, Retrieved Wed, 21 Apr 2021 10:27:23 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Wed, 21 Apr 2021 10:27:23 +0200
QR Codes:

Original text written by user:
IsPrivate?This computation is private
User-defined keywords
Estimated Impact0
Dataseries X:
2	2	1	3	3	3	1	2	2	2	2	2	3	2	2	1	1	3	2	2	2	2	2	2	2	1	2	2	2	3	2	2	3	2	3	3	3	3	3	3	2	3	3	2	2	2	3	3	3	3	2	3
4	6	1	6	6	3	2	2	2	NA	4	1	NA	4	5	2	1	4	2	2	6	3	6	6	5	4	5	5	6	5	6	4	6	4	5	5	5	6	6	4	6	4	4	5	5	5	5	6	6	5	5	6
6	6	1	6	6	6	1	6	6	1	6	1	1	5	6	6	3	6	2	2	6	6	6	6	5	6	5	4	5	6	4	5	6	5	5	6	6	6	6	6	6	6	6	4	5	5	5	5	6	5	5	6
6	6	1	6	6	6	1	1	1	1	1	4	1	6	6	1	1	1	1	2	5	1	6	6	6	2	6	1	6	6	6	6	5	5	6	6	6	6	6	5	6	6	6	5	6	6	6	5	6	6	6	6
5	6	1	6	6	6	1	1	1	6	3	2	NA	2	NA	NA	1	6	1	2	6	6	6	6	5	5	6	6	6	6	6	5	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	2	5	6	6	1	1	1	6	6	1	1	1	1	2	6	6	6	6	6	6	1	6	6	6	6	6	6	6	6	6	6	6	5	6	6	6	6	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	5	NA	NA	NA	NA	NA	3	6	NA	1	1	6	1	2	5	6	6	6	4	4	6	6	6	6	5	5	5	5	6	6	6	6	6	6	6	5	5	5	5	5	6	6	6	6	6	6
6	6	1	6	6	6	1	4	4	4	1	1	1	1	5	1	1	5	2	3	6	6	6	6	6	4	4	4	5	6	6	3	6	3	6	6	6	6	6	6	5	4	4	3	4	3	6	6	6	6	6	6
4	6	1	6	6	6	1	1	6	NA	NA	NA	NA	5	5	2	5	2	3	3	6	4	6	6	NA	1	6	6	6	6	5	5	6	5	6	6	6	6	6	6	6	5	6	5	6	6	6	6	6	6	6	6
5	6	1	6	6	6	3	2	2	NA	4	4	5	3	4	2	2	4	3	3	4	3	6	5	5	2	6	4	6	5	6	4	6	6	6	5	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
5	6	1	6	6	6	3	1	3	1	5	2	1	3	6	2	1	4	3	3	5	2	6	6	2	4	4	1	5	6	5	4	5	4	6	6	5	6	6	5	6	2	3	4	5	5	5	6	6	6	5	6
4	6	NA	6	6	3	2	NA	5	NA	NA	3	5	2	3	3	3	3	3	3	5	3	6	5	5	4	6	4	6	4	4	4	3	3	4	5	5	5	6	4	5	3	3	3	3	3	3	5	5	6	5	6
2	3	2	3	3	3	1	1	1	1	1	2	1	1	2	1	1	3	1	3	2	2	2	2	2	2	2	1	2	3	2	1	3	3	3	3	3	3	3	3	3	2	1	1	3	2	3	2	3	3	3	3
1	6	1	6	6	6	1	1	4	4	4	2	1	3	NA	NA	1	6	2	4	6	6	6	6	3	6	6	3	4	6	4	4	4	4	6	6	6	6	6	5	6	6	6	6	6	6	6	6	6	6	6	6
3	4	2	6	6	5	4	3	4	3	5	4	5	4	6	5	3	5	3	4	6	4	5	5	6	5	5	4	5	4	3	2	3	2	4	5	4	6	6	4	5	5	5	6	6	4	5	4	5	6	6	5
6	4	1	6	6	5	1	4	6	6	1	1	2	4	3	3	1	4	3	4	6	4	6	6	5	4	4	6	6	6	5	3	5	5	5	6	5	5	5	5	6	6	6	5	6	5	6	6	6	5	4	6
4	6	1	6	6	6	3	1	3	4	6	2	2	6	6	3	2	5	3	4	6	4	6	5	6	4	6	5	6	6	4	4	5	4	4	5	6	6	6	5	6	1	1	3	4	3	4	4	4	4	3	4
4	6	1	6	6	6	1	2	6	6	2	5	2	2	4	2	2	6	4	4	6	5	6	5	6	5	6	5	5	6	5	5	5	4	6	6	4	6	6	5	6	4	3	5	5	6	6	6	6	6	5	6
4	6	1	6	6	5	1	1	5	5	3	1	2	4	5	1	1	5	5	4	6	4	6	6	4	3	4	3	5	5	3	2	4	4	5	5	5	5	6	4	6	4	4	4	4	4	5	5	5	5	4	5
6	6	1	6	6	6	2	1	5	5	4	2	1	2	6	1	1	6	5	4	6	4	6	5	5	5	6	4	5	3	6	5	6	4	6	6	6	6	6	6	6	1	1	5	5	5	5	5	5	5	5	5
4	6	1	6	6	5	2	NA	5	5	5	1	3	5	5	1	1	6	1	4	5	4	5	5	3	5	3	4	5	4	4	4	4	4	5	6	6	6	6	5	6	3	2	6	5	5	NA	6	6	5	5	5
2	3	1	6	6	4	1	4	1	1	3	3	NA	4	NA	1	1	1	1	4	5	NA	6	6	6	1	4	6	6	6	4	2	6	3	6	6	6	6	6	5	6	5	5	6	6	5	6	6	6	6	5	6
1	6	1	6	6	4	1	1	4	NA	1	3	NA	2	4	1	1	5	NA	4	5	3	6	6	5	4	6	6	6	4	3	3	4	3	4	4	4	5	5	5	6	5	5	4	5	5	5	6	6	5	5	6
4	5	1	6	6	3	2	2	3	3	3	3	6	5	6	NA	NA	6	2	5	6	3	6	6	4	4	3	4	5	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	6	3	5	6	1	1	4	1	6	4	1	6	3	5	6	4	6	6	6	4	4	5	5	5	4	4	5	4	5	6	6	6	6	6	6	4	5	6	6	5	6	6	6	6	6	6
6	1	1	6	6	6	1	1	6	6	2	1	6	1	6	1	1	6	4	5	6	5	6	6	4	4	6	1	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
6	NA	NA	6	6	6	1	1	5	NA	1	1	1	1	6	6	2	6	5	5	6	6	6	6	5	6	1	1	6	6	5	4	6	5	6	6	6	6	6	6	6	5	6	6	6	5	6	6	6	6	6	6
5	6	1	6	6	6	2	2	3	6	2	2	3	1	2	2	3	6	5	5	6	4	6	6	5	3	4	4	6	6	5	5	5	5	6	6	5	6	6	5	5	5	4	6	5	4	6	6	6	5	4	6
4	4	2	4	5	5	2	4	4	NA	3	3	NA	1	NA	1	1	5	5	5	6	NA	6	5	5	3	3	6	6	5	5	5	6	4	6	6	5	6	5	5	6	5	5	5	5	4	5	5	5	6	5	6
6	6	1	6	6	6	1	1	4	5	2	1	1	2	6	2	2	5	6	5	6	5	5	6	5	5	6	5	6	6	6	4	5	5	6	6	6	6	6	5	6	5	5	6	6	5	6	6	6	6	6	6
6	6	1	6	6	6	1	2	2	1	4	3	3	1	5	1	1	6	6	5	6	1	6	6	6	1	6	2	6	3	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	4	5	5	5	5	3	6
3	5	2	6	6	5	2	3	6	2	4	3	2	3	6	6	1	6	6	5	4	4	5	4	4	4	5	4	4	4	4	3	6	5	5	6	6	6	6	5	5	5	5	5	5	6	6	6	6	6	6	6
6	6	1	6	6	6	1	1	5	5	1	2	1	1	5	1	4	6	3	1	6	1	6	6	6	3	6	3	6	6	5	4	6	5	5	6	6	6	6	5	6	6	6	6	6	6	6	6	6	6	6	6
5	6	1	6	6	5	1	2	4	5	4	3	1	4	4	1	1	4	3	1	6	1	6	6	4	3	1	6	6	6	6	4	6	6	6	6	6	6	6	6	6	5	6	6	6	6	6	6	6	6	4	6
2	3	3	NA	NA	2	2	1	2	2	NA	4	1	4	NA	1	1	2	3	1	6	5	5	5	5	3	4	2	6	6	3	NA	5	4	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
4	5	2	6	6	6	2	2	2	1	2	2	6	6	5	1	1	6	3	1	6	5	6	6	6	6	6	3	4	5	4	3	6	6	6	5	4	5	6	5	6	3	3	5	4	4	6	6	6	6	4	6
6	6	1	6	6	6	1	4	4	6	3	1	NA	2	5	1	1	6	1	1	6	6	5	6	NA	3	3	4	6	6	4	5	6	5	6	6	6	6	6	6	6	5	5	6	6	5	6	6	6	6	5	6
6	6	1	6	6	6	1	2	4	6	6	2	1	5	6	6	1	6	1	1	6	4	6	5	5	4	4	2	6	5	5	5	6	4	6	6	6	6	6	6	6	5	5	5	6	6	6	6	6	6	6	6
6	6	1	6	6	6	1	1	6	6	3	3	3	1	1	1	1	6	1	1	6	6	3	6	4	4	1	6	6	6	5	1	3	3	6	6	5	6	6	6	6	4	5	5	6	2	6	6	6	5	5	6
6	6	1	6	6	6	1	1	6	NA	1	1	3	1	2	1	1	1	1	1	6	6	6	6	6	5	6	5	6	6	5	3	5	4	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	1	1	1	3	1	1	1	1	2	1	1	1	1	1	6	6	6	6	6	1	1	6	6	6	6	1	6	2	6	6	6	6	6	6	5	1	3	5	6	5	6	6	6	4	5	6
6	6	1	6	6	5	3	1	1	1	1	1	6	6	6	6	1	6	2	6	6	1	6	6	6	2	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
3	5	1	NA	NA	3	6	5	2	1	1	5	NA	NA	NA	NA	4	2	2	6	5	5	4	5	NA	NA	5	6	6	5	6	6	6	6	6	6	6	6	6	5	5	6	6	6	5	5	6	6	5	6	6	6
6	6	1	6	6	6	1	6	6	6	5	5	6	1	3	2	1	6	3	6	6	5	6	6	6	1	1	6	6	6	5	5	5	4	6	6	6	6	6	6	6	5	2	3	5	5	5	5	5	5	5	5
6	6	2	6	6	6	2	4	4	6	2	2	4	2	6	6	3	6	4	6	6	4	6	6	5	4	4	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	4	6	6	6	6	6	6	4	5	5
3	5	1	6	6	6	1	1	5	NA	6	4	1	2	6	6	NA	6	5	6	5	5	6	6	2	6	6	3	6	5	6	5	6	6	6	6	6	6	6	6	6	5	6	6	6	6	6	6	6	5	6	6
3	6	1	6	6	1	1	1	1	1	6	6	NA	6	6	6	1	6	1	6	6	5	6	6	4	4	6	4	6	6	6	6	6	6	6	6	6	6	6	6	6	4	4	6	6	6	6	6	6	4	4	6
6	6	1	6	6	6	1	1	1	6	6	6	6	6	6	3	1	6	1	6	6	1	6	6	3	6	6	6	6	6	6	3	6	6	6	6	6	6	6	6	6	4	4	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	1	1	2	2	2	1	1	1	NA	NA	1	6	1	6	4	4	4	4	4	4	4	4	4	5	5	4	6	6	5	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
5	6	1	6	6	6	4	1	6	1	1	1	6	1	1	1	1	1	1	6	6	1	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	1	1	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	1	1	6	NA	NA	NA	6	4	2	1	1	6	1	6	6	6	6	6	6	6	6	6	6	6	6	1	5	4	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	6	3	3	3	1	3	5	1	6	6	1	6	6	6	6	6	6	6	6	6	6	5	6	6	6	3	6	6	6	6	6	6	6	6	6	5	6	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	1	NA	6	1	1	1	4	1	6	1	1	6	6	6	6	5	6	6	1	6	2	1	6	2	1	1	6	1	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
5	6	1	6	6	6	6	2	6	6	1	1	6	2	NA	NA	1	6	6	6	6	1	6	6	6	2	3	6	6	6	6	5	6	5	NA	6	6	6	6	6	6	5	4	2	6	6	6	6	6	6	6	6
3	5	1	6	6	6	2	4	6	6	1	2	4	2	6	5	1	6	6	6	6	5	6	6	4	2	2	5	6	6	4	3	4	4	4	5	5	6	5	4	6	5	5	4	4	4	6	6	5	5	5	6
4	6	1	6	6	6	1	1	3	1	5	1	NA	3	6	1	1	6	6	6	6	5	6	6	5	6	5	2	6	6	6	2	6	4	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	5	6
6	6	1	6	6	6	1	3	4	NA	3	2	2	5	6	4	1	6	6	6	6	4	6	6	5	5	6	5	6	6	5	4	6	5	6	6	6	6	6	6	6	5	5	6	6	6	6	6	6	6	6	6
3	6	1	6	6	6	1	1	6	6	1	1	6	5	6	1	1	6	NA	6	6	3	6	6	6	1	6	6	6	6	3	4	5	6	6	6	6	6	6	6	5	3	3	5	6	6	6	6	6	6	5	6
6	6	1	6	6	6	1	4	4	5	4	4	5	1	6	2	1	6	5	NA	6	1	6	6	4	NA	NA	2	6	6	6	4	5	5	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
6	6	1	5	6	6	1	4	4	5	5	5	6	3	NA	NA	6	6	NA	NA	6	1	6	6	1	1	1	6	6	6	6	5	6	5	6	6	6	6	6	6	6	5	NA	6	6	6	5	6	5	6	5	6
5	6	1	6	6	5	1	3	3	5	3	4	3	3	2	1	1	2	2	2	4	4	6	5	6	6	6	4	NA	6	5	4	6	5	6	5	6	6	6	5	5	5	5	5	5	5	5	5	5	6	6	6
4	4	4	6	6	4	4	5	5	5	4	4	4	4	4	4	4	3	3	3	6	4	6	6	6	5	6	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5	5
6	6	1	6	6	6	1	1	3	6	1	1	1	1	1	1	1	6	1	3	6	NA	6	6	6	6	6	2	6	5	5	2	5	4	5	5	5	5	5	5	5	3	4	4	5	4	5	5	5	5	5	5
6	NA	1	6	6	6	6	1	3	3	2	2	NA	2	5	2	1	6	2	1	6	4	6	6	5	6	2	2	5	2	2	4	6	5	4	5	3	6	5	4	6	5	4	6	6	6	6	6	6	6	6	6
6	4	1	6	6	6	1	1	4	4	1	1	1	1	1	1	1	1	3	1	4	4	3	5	5	5	2	1	5	6	6	1	6	3	6	6	5	6	6	6	6	4	5	5	5	5	6	6	6	6	6	6
6	1	1	6	6	6	1	1	3	6	3	3	NA	1	1	1	1	6	1	1	6	5	5	6	2	5	5	1	6	6	5	1	6	5	5	6	1	6	5	5	6	1	4	5	5	6	6	6	6	6	6	6
3	6	1	6	6	6	2	4	4	5	2	4	2	1	2	2	1	6	5	6	5	5	6	6	6	4	3	6	6	6	6	6	5	5	6	6	6	6	5	5	6	4	4	4	6	6	6	6	5	6	6	6
3	6	1	6	6	6	1	1	2	4	1	2	4	1	1	1	1	4	1	2	6	5	6	6	5	3	5	6	6	5	4	2	6	4	6	6	6	6	5	3	6	2	4	5	5	2	6	6	6	6	4	5
4	6	2	6	6	6	1	2	5	6	3	3	4	2	3	1	2	6	2	3	6	4	6	6	3	4	6	3	6	5	4	3	6	5	6	6	6	6	6	6	6	5	5	6	6	6	6	6	6	5	5	6
3	3	3	3	3	3	3	1	3	2	1	1	3	1	1	1	1	3	3	3	2	1	2	2	2	2	2	2	2	3	2	2	3	3	3	3	3	3	3	3	3	3	3	2	3	3	3	3	3	3	3	3
6	6	1	6	6	6	3	1	6	6	1	3	1	4	2	1	1	3	1	4	6	5	6	6	6	4	3	6	6	6	6	6	6	6	6	6	6	6	6	6	6	5	5	6	6	6	6	6	6	6	6	6
4	4	1	6	6	6	4	3	3	4	2	2	6	3	6	2	1	5	3	5	6	5	4	5	5	4	4	4	4	6	5	5	5	5	5	6	6	6	6	6	5	4	3	4	4	4	6	6	6	4	4	6
6	6	1	6	6	6	2	1	3	5	2	5	NA	2	2	2	1	6	4	5	5	3	6	6	5	3	6	4	6	6	5	2	6	4	6	6	6	6	5	5	5	4	6	4	5	5	6	4	6	5	6	6
6	1	6	6	6	6	1	1	1	6	3	3	6	1	1	1	1	5	1	1	6	3	6	6	3	1	4	3	5	6	4	4	5	5	6	5	5	5	4	4	4	3	3	4	4	4	4	4	4	4	3	4
5	6	1	6	6	6	1	3	3	6	2	2	6	3	4	1	3	6	1	3	6	2	6	6	6	1	1	6	6	6	3	3	6	5	6	6	5	6	6	6	5	3	4	5	6	6	6	6	6	6	6	6
4	6	1	6	6	6	2	1	6	3	5	4	3	2	4	1	3	6	2	6	6	3	6	6	4	NA	6	4	6	6	6	4	6	5	6	6	6	6	6	6	6	5	5	6	6	6	6	6	6	6	6	6
4	6	1	6	6	6	4	2	5	5	3	3	3	4	5	5	2	6	4	6	6	5	5	6	5	5	5	4	6	6	4	4	6	6	6	6	6	6	6	6	6	4	4	6	6	6	6	6	6	6	6	6
5	6	1	6	6	6	3	1	4	6	3	3	6	5	5	1	1	6	6	NA	6	4	6	6	6	2	5	1	6	5	4	1	4	4	5	5	5	5	4	4	5	1	1	5	5	4	6	6	6	6	6	6
6	4	1	6	6	4	1	2	2	1	1	5	5	6	5	5	1	4	2	2	6	5	6	6	3	4	6	5	5	3	4	2	5	4	5	6	6	6	5	5	6	5	5	5	6	5	4	5	5	5	4	5
4	4	2	6	6	6	4	1	6	6	3	2	NA	4	6	6	3	6	3	2	6	3	5	6	5	2	5	6	NA	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
4	5	1	6	6	6	2	1	5	5	2	3	4	3	4	2	3	4	4	2	6	4	6	6	2	2	5	5	5	5	5	5	5	5	6	6	6	6	6	6	6	4	5	5	5	5	5	6	6	4	4	5
6	6	1	6	6	6	1	1	3	6	1	1	6	2	2	1	1	6	5	2	6	2	4	6	2	2	4	5	6	6	6	6	6	5	6	6	6	6	6	5	6	6	6	5	6	5	6	6	6	6	5	6
6	6	1	6	6	6	2	6	6	6	1	1	6	5	5	5	1	6	5	2	6	5	6	6	6	6	5	6	6	6	6	3	6	6	6	6	6	6	6	6	6	4	4	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	1	1	1	1	1	3	1	2	1	1	1	1	1	2	6	6	6	6	6	6	6	3	2	6	6	5	6	4	6	6	6	6	6	6	6	2	2	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	2	4	5	1	1	3	1	6	6	2	6	4	1	2	6	6	6	6	6	4	4	5	1	5	5	2	5	4	5	6	6	6	6	6	6	5	4	4	4	4	4	4	4	4	4	4
4	6	NA	6	6	6	2	1	5	6	1	1	6	1	4	3	3	6	3	3	6	3	6	6	4	3	3	6	6	6	6	2	6	5	6	6	6	6	6	6	6	3	6	6	6	6	6	6	6	6	6	6
5	6	1	6	6	5	5	4	4	6	1	1	5	3	3	3	2	6	5	3	5	3	6	6	2	3	3	6	6	6	5	4	6	5	5	5	6	6	5	5	6	4	5	4	5	5	5	5	4	5	5	6
6	6	1	6	6	6	1	1	6	6	1	3	6	3	1	1	1	6	1	3	6	5	6	6	4	4	4	6	6	6	3	3	5	1	3	5	6	6	6	4	6	1	2	6	6	4	6	6	6	6	6	6
5	6	1	6	6	6	2	1	3	5	1	3	5	1	4	2	4	6	3	4	6	5	4	6	4	5	4	1	6	4	2	2	4	2	5	5	5	5	5	5	6	2	3	2	3	3	4	6	6	6	6	5
5	5	1	6	6	6	5	4	5	6	1	1	4	3	4	2	2	4	4	4	6	4	5	6	6	4	1	6	6	6	5	5	5	5	5	6	6	6	6	6	6	6	6	5	6	5	6	6	6	6	6	6
2	4	2	6	6	6	1	3	3	NA	3	3	6	4	5	4	1	6	4	4	6	2	6	6	6	3	6	1	6	5	6	4	6	5	6	6	6	6	6	6	6	3	6	6	6	6	6	6	6	6	6	6
1	1	6	6	6	5	1	3	1	1	1	1	6	6	6	1	1	1	1	4	6	NA	6	5	6	6	NA	NA	NA	4	6	6	6	6	6	6	4	5	6	6	6	6	5	6	5	5	5	6	5	4	3	4
6	6	1	6	6	3	2	1	3	5	1	4	5	1	6	1	1	6	6	4	6	6	4	6	6	6	4	4	5	6	6	6	6	6	6	6	5	6	6	6	6	4	6	6	6	6	6	6	6	6	6	6
1	4	3	6	6	6	6	1	2	4	4	2	2	NA	6	2	6	6	2	5	6	4	5	2	5	6	6	2	2	5	2	2	5	5	6	6	4	6	5	4	6	5	6	6	6	6	6	6	6	6	6	3
5	5	6	6	6	6	3	2	3	2	1	2	4	6	6	5	1	3	4	5	6	5	6	6	6	5	3	6	4	6	6	6	6	5	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	2	NA	NA	NA	5	5	5	4	5	4	1	6	5	5	6	5	6	6	5	4	4	2	NA	5	4	4	5	5	6	6	5	6	6	5	6	3	4	4	6	4	6	6	6	6	5	6
6	6	2	6	6	6	6	4	4	4	4	4	6	5	5	2	1	6	5	5	6	5	6	6	6	6	6	5	5	5	5	4	5	6	6	6	6	6	6	6	6	5	6	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	1	1	5	5	1	1	1	6	6	6	1	6	1	5	6	2	5	5	2	1	1	6	6	6	6	6	6	6	6	6	6	6	6	6	6	5	5	6	6	6	6	6	6	6	6	6
3	4	1	4	5	5	3	1	2	3	2	1	5	5	5	4	1	6	6	5	6	6	6	5	5	5	5	1	2	5	5	5	6	6	6	6	6	6	6	6	6	5	6	6	6	6	6	6	6	6	6	6
3	5	1	6	6	6	2	2	4	6	2	2	NA	5	5	2	NA	6	2	1	6	6	6	6	6	1	2	6	6	5	5	6	6	5	6	6	5	6	6	4	4	3	1	2	6	6	6	5	5	4	2	6
6	6	1	6	6	6	1	1	5	6	1	1	6	1	5	2	3	6	2	1	6	4	5	6	2	2	1	6	6	6	6	5	6	6	6	6	6	6	6	6	6	5	6	6	6	6	6	6	6	5	5	6
6	1	1	6	6	6	1	1	6	6	1	1	1	2	3	1	1	3	3	1	6	6	5	6	6	6	1	2	6	6	6	6	6	5	6	6	6	6	6	6	6	5	5	6	6	6	6	6	6	6	5	6
3	3	1	3	3	3	1	1	3	1	1	1	3	2	2	3	1	3	1	1	2	2	1	2	2	2	1	2	2	3	3	3	3	1	3	3	3	3	3	3	3	2	2	3	3	2	2	3	3	3	3	3
6	6	1	6	6	6	1	2	4	5	2	4	6	1	5	1	1	2	1	1	6	5	6	6	6	6	4	5	5	1	5	2	5	5	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
2	6	1	6	6	6	1	1	5	6	1	1	5	5	6	1	1	5	1	1	6	1	6	6	4	4	6	1	2	6	6	4	6	6	6	6	6	6	6	6	6	4	6	6	6	6	6	6	6	6	6	6
1	3	3	6	6	6	1	1	1	1	1	1	6	1	5	1	1	4	1	1	6	6	NA	6	6	6	1	3	6	6	6	1	6	3	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
6	6	1	6	3	6	1	1	1	6	1	3	5	1	2	1	1	5	1	1	6	1	2	5	2	5	2	3	6	6	6	6	6	6	6	6	6	6	6	6	6	3	3	3	6	5	6	6	6	5	3	6
NA	NA	NA	6	6	6	1	NA	6	6	1	1	NA	1	4	1	1	6	6	1	6	1	6	6	6	3	4	5	6	6	2	3	6	6	6	6	5	6	6	6	6	1	1	6	6	1	6	6	6	6	6	6
3	6	1	5	5	6	1	4	4	6	2	2	5	6	6	2	1	6	2	6	6	5	6	6	5	5	6	3	6	6	5	5	6	5	5	6	5	6	6	5	6	5	5	5	6	6	6	6	6	6	6	6
4	6	NA	6	6	6	2	3	5	6	2	3	6	6	NA	NA	NA	6	3	6	6	5	6	6	6	5	5	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
4	6	1	6	6	6	1	1	5	5	NA	NA	NA	5	6	1	NA	6	4	6	6	3	6	6	6	6	4	NA	6	6	4	4	6	5	6	6	6	6	6	5	6	6	6	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	3	1	6	NA	1	3	3	6	5	2	1	6	4	6	6	NA	6	6	6	6	5	3	6	5	6	5	5	4	6	6	5	6	6	6	6	5	6	6	6	6	6	6	6	6	6	6
6	5	1	6	6	6	1	1	4	6	1	1	6	6	6	1	NA	6	6	6	6	1	6	6	6	4	6	5	5	6	3	3	6	6	6	6	6	6	6	6	6	6	5	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	1	1	6	6	1	2	6	6	6	3	1	6	6	6	6	4	6	6	4	5	4	6	6	6	4	4	5	5	4	6	6	5	6	6	6	5	5	5	6	4	6	6	6	6	6	6
6	6	1	6	6	5	1	1	1	1	1	1	4	6	NA	NA	1	NA	NA	6	6	6	6	6	6	6	1	1	NA	6	6	1	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6	6
6	6	1	6	6	6	NA	NA	6	NA	NA	NA	6	6	6	6	NA	6	NA	6	6	1	6	6	6	5	6	NA	NA	6	5	5	6	6	6	6	5	6	5	5	6	5	5	6	6	6	5	5	5	5	5	6
4	5	1	6	6	6	1	1	4	6	2	3	NA	3	4	NA	NA	6	1	NA	6	4	6	5	5	4	6	NA	NA	6	6	2	5	6	6	6	2	6	6	6	6	1	1	5	5	3	NA	NA	NA	6	2	5




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=&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=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
11.22169.528.50.7191250.57
21.79221170.86102120.79
3-2.188252-0.944108-0.93
42.34271.520.9911140.93
52.342722.50.9811050.91
62.012448.50.93106110.81
7-1.5525205-0.7816100-0.72
8-1.4919.5183.5-0.812189-0.62
90.38106.5630.2669460.2
100.7213562.50.3768330.35
11-1.1632.5160.5-0.662585-0.55
12-1.1322149-0.742290-0.61
130.219978.50.1254450.09
14-0.3678119.5-0.214867-0.17
150.8914147.50.576290.45
16-1.1842168.5-0.62483-0.55
17-1.9311221.5-0.918101-0.85
181.42199.534.50.7193230.6
19-0.5362.5121.5-0.323973-0.3
200.15103.5860.0961520.08
212.18260.560.9511340.93
220.44107.558.50.375370.34
232.04246.59.50.9310970.88
242.132577.50.9411250.91
251.25169.527.50.7293210.63
260.49112560.3376380.33
270.73140.5560.4381340.41
280.6112960.50.3674390.31
291.87220.514.50.8810190.84
301.88229.590.92107100.83
311.3717817.50.82100170.71
320.41104570.2974420.28
331.922283.50.9711070.88
341.23161.5180.8101160.73
352.07242.52.50.9811150.91
362.23262.520.9811340.93
371.992396.50.9511070.88
382.29269.520.9911340.93
392.21260.520.9811340.93
401.922272.50.9811250.91
412.22262.530.9811340.93
420.9114538.50.5888290.5
431.1161.533.50.6691250.57
441.66207.5130.88105120.79
451.98235.540.9711160.9
461.65205.5130.88105120.79
472.122473.50.9711050.91
482.1725530.9811240.93
492.1725420.9811240.93
502.04240.520.9811340.93
511.762158.50.92106110.81
522.192592.50.9811250.91

\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 & 1.22 & 169.5 & 28.5 & 0.71 & 91 & 25 & 0.57 \tabularnewline
2 & 1.79 & 221 & 17 & 0.86 & 102 & 12 & 0.79 \tabularnewline
3 & -2.18 & 8 & 252 & -0.94 & 4 & 108 & -0.93 \tabularnewline
4 & 2.34 & 271.5 & 2 & 0.99 & 111 & 4 & 0.93 \tabularnewline
5 & 2.34 & 272 & 2.5 & 0.98 & 110 & 5 & 0.91 \tabularnewline
6 & 2.01 & 244 & 8.5 & 0.93 & 106 & 11 & 0.81 \tabularnewline
7 & -1.55 & 25 & 205 & -0.78 & 16 & 100 & -0.72 \tabularnewline
8 & -1.49 & 19.5 & 183.5 & -0.81 & 21 & 89 & -0.62 \tabularnewline
9 & 0.38 & 106.5 & 63 & 0.26 & 69 & 46 & 0.2 \tabularnewline
10 & 0.72 & 135 & 62.5 & 0.37 & 68 & 33 & 0.35 \tabularnewline
11 & -1.16 & 32.5 & 160.5 & -0.66 & 25 & 85 & -0.55 \tabularnewline
12 & -1.13 & 22 & 149 & -0.74 & 22 & 90 & -0.61 \tabularnewline
13 & 0.21 & 99 & 78.5 & 0.12 & 54 & 45 & 0.09 \tabularnewline
14 & -0.36 & 78 & 119.5 & -0.21 & 48 & 67 & -0.17 \tabularnewline
15 & 0.89 & 141 & 47.5 & 0.5 & 76 & 29 & 0.45 \tabularnewline
16 & -1.18 & 42 & 168.5 & -0.6 & 24 & 83 & -0.55 \tabularnewline
17 & -1.93 & 11 & 221.5 & -0.91 & 8 & 101 & -0.85 \tabularnewline
18 & 1.42 & 199.5 & 34.5 & 0.71 & 93 & 23 & 0.6 \tabularnewline
19 & -0.53 & 62.5 & 121.5 & -0.32 & 39 & 73 & -0.3 \tabularnewline
20 & 0.15 & 103.5 & 86 & 0.09 & 61 & 52 & 0.08 \tabularnewline
21 & 2.18 & 260.5 & 6 & 0.95 & 113 & 4 & 0.93 \tabularnewline
22 & 0.44 & 107.5 & 58.5 & 0.3 & 75 & 37 & 0.34 \tabularnewline
23 & 2.04 & 246.5 & 9.5 & 0.93 & 109 & 7 & 0.88 \tabularnewline
24 & 2.13 & 257 & 7.5 & 0.94 & 112 & 5 & 0.91 \tabularnewline
25 & 1.25 & 169.5 & 27.5 & 0.72 & 93 & 21 & 0.63 \tabularnewline
26 & 0.49 & 112 & 56 & 0.33 & 76 & 38 & 0.33 \tabularnewline
27 & 0.73 & 140.5 & 56 & 0.43 & 81 & 34 & 0.41 \tabularnewline
28 & 0.61 & 129 & 60.5 & 0.36 & 74 & 39 & 0.31 \tabularnewline
29 & 1.87 & 220.5 & 14.5 & 0.88 & 101 & 9 & 0.84 \tabularnewline
30 & 1.88 & 229.5 & 9 & 0.92 & 107 & 10 & 0.83 \tabularnewline
31 & 1.37 & 178 & 17.5 & 0.82 & 100 & 17 & 0.71 \tabularnewline
32 & 0.41 & 104 & 57 & 0.29 & 74 & 42 & 0.28 \tabularnewline
33 & 1.92 & 228 & 3.5 & 0.97 & 110 & 7 & 0.88 \tabularnewline
34 & 1.23 & 161.5 & 18 & 0.8 & 101 & 16 & 0.73 \tabularnewline
35 & 2.07 & 242.5 & 2.5 & 0.98 & 111 & 5 & 0.91 \tabularnewline
36 & 2.23 & 262.5 & 2 & 0.98 & 113 & 4 & 0.93 \tabularnewline
37 & 1.99 & 239 & 6.5 & 0.95 & 110 & 7 & 0.88 \tabularnewline
38 & 2.29 & 269.5 & 2 & 0.99 & 113 & 4 & 0.93 \tabularnewline
39 & 2.21 & 260.5 & 2 & 0.98 & 113 & 4 & 0.93 \tabularnewline
40 & 1.92 & 227 & 2.5 & 0.98 & 112 & 5 & 0.91 \tabularnewline
41 & 2.22 & 262.5 & 3 & 0.98 & 113 & 4 & 0.93 \tabularnewline
42 & 0.91 & 145 & 38.5 & 0.58 & 88 & 29 & 0.5 \tabularnewline
43 & 1.1 & 161.5 & 33.5 & 0.66 & 91 & 25 & 0.57 \tabularnewline
44 & 1.66 & 207.5 & 13 & 0.88 & 105 & 12 & 0.79 \tabularnewline
45 & 1.98 & 235.5 & 4 & 0.97 & 111 & 6 & 0.9 \tabularnewline
46 & 1.65 & 205.5 & 13 & 0.88 & 105 & 12 & 0.79 \tabularnewline
47 & 2.12 & 247 & 3.5 & 0.97 & 110 & 5 & 0.91 \tabularnewline
48 & 2.17 & 255 & 3 & 0.98 & 112 & 4 & 0.93 \tabularnewline
49 & 2.17 & 254 & 2 & 0.98 & 112 & 4 & 0.93 \tabularnewline
50 & 2.04 & 240.5 & 2 & 0.98 & 113 & 4 & 0.93 \tabularnewline
51 & 1.76 & 215 & 8.5 & 0.92 & 106 & 11 & 0.81 \tabularnewline
52 & 2.19 & 259 & 2.5 & 0.98 & 112 & 5 & 0.91 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]1.22[/C][C]169.5[/C][C]28.5[/C][C]0.71[/C][C]91[/C][C]25[/C][C]0.57[/C][/ROW]
[ROW][C]2[/C][C]1.79[/C][C]221[/C][C]17[/C][C]0.86[/C][C]102[/C][C]12[/C][C]0.79[/C][/ROW]
[ROW][C]3[/C][C]-2.18[/C][C]8[/C][C]252[/C][C]-0.94[/C][C]4[/C][C]108[/C][C]-0.93[/C][/ROW]
[ROW][C]4[/C][C]2.34[/C][C]271.5[/C][C]2[/C][C]0.99[/C][C]111[/C][C]4[/C][C]0.93[/C][/ROW]
[ROW][C]5[/C][C]2.34[/C][C]272[/C][C]2.5[/C][C]0.98[/C][C]110[/C][C]5[/C][C]0.91[/C][/ROW]
[ROW][C]6[/C][C]2.01[/C][C]244[/C][C]8.5[/C][C]0.93[/C][C]106[/C][C]11[/C][C]0.81[/C][/ROW]
[ROW][C]7[/C][C]-1.55[/C][C]25[/C][C]205[/C][C]-0.78[/C][C]16[/C][C]100[/C][C]-0.72[/C][/ROW]
[ROW][C]8[/C][C]-1.49[/C][C]19.5[/C][C]183.5[/C][C]-0.81[/C][C]21[/C][C]89[/C][C]-0.62[/C][/ROW]
[ROW][C]9[/C][C]0.38[/C][C]106.5[/C][C]63[/C][C]0.26[/C][C]69[/C][C]46[/C][C]0.2[/C][/ROW]
[ROW][C]10[/C][C]0.72[/C][C]135[/C][C]62.5[/C][C]0.37[/C][C]68[/C][C]33[/C][C]0.35[/C][/ROW]
[ROW][C]11[/C][C]-1.16[/C][C]32.5[/C][C]160.5[/C][C]-0.66[/C][C]25[/C][C]85[/C][C]-0.55[/C][/ROW]
[ROW][C]12[/C][C]-1.13[/C][C]22[/C][C]149[/C][C]-0.74[/C][C]22[/C][C]90[/C][C]-0.61[/C][/ROW]
[ROW][C]13[/C][C]0.21[/C][C]99[/C][C]78.5[/C][C]0.12[/C][C]54[/C][C]45[/C][C]0.09[/C][/ROW]
[ROW][C]14[/C][C]-0.36[/C][C]78[/C][C]119.5[/C][C]-0.21[/C][C]48[/C][C]67[/C][C]-0.17[/C][/ROW]
[ROW][C]15[/C][C]0.89[/C][C]141[/C][C]47.5[/C][C]0.5[/C][C]76[/C][C]29[/C][C]0.45[/C][/ROW]
[ROW][C]16[/C][C]-1.18[/C][C]42[/C][C]168.5[/C][C]-0.6[/C][C]24[/C][C]83[/C][C]-0.55[/C][/ROW]
[ROW][C]17[/C][C]-1.93[/C][C]11[/C][C]221.5[/C][C]-0.91[/C][C]8[/C][C]101[/C][C]-0.85[/C][/ROW]
[ROW][C]18[/C][C]1.42[/C][C]199.5[/C][C]34.5[/C][C]0.71[/C][C]93[/C][C]23[/C][C]0.6[/C][/ROW]
[ROW][C]19[/C][C]-0.53[/C][C]62.5[/C][C]121.5[/C][C]-0.32[/C][C]39[/C][C]73[/C][C]-0.3[/C][/ROW]
[ROW][C]20[/C][C]0.15[/C][C]103.5[/C][C]86[/C][C]0.09[/C][C]61[/C][C]52[/C][C]0.08[/C][/ROW]
[ROW][C]21[/C][C]2.18[/C][C]260.5[/C][C]6[/C][C]0.95[/C][C]113[/C][C]4[/C][C]0.93[/C][/ROW]
[ROW][C]22[/C][C]0.44[/C][C]107.5[/C][C]58.5[/C][C]0.3[/C][C]75[/C][C]37[/C][C]0.34[/C][/ROW]
[ROW][C]23[/C][C]2.04[/C][C]246.5[/C][C]9.5[/C][C]0.93[/C][C]109[/C][C]7[/C][C]0.88[/C][/ROW]
[ROW][C]24[/C][C]2.13[/C][C]257[/C][C]7.5[/C][C]0.94[/C][C]112[/C][C]5[/C][C]0.91[/C][/ROW]
[ROW][C]25[/C][C]1.25[/C][C]169.5[/C][C]27.5[/C][C]0.72[/C][C]93[/C][C]21[/C][C]0.63[/C][/ROW]
[ROW][C]26[/C][C]0.49[/C][C]112[/C][C]56[/C][C]0.33[/C][C]76[/C][C]38[/C][C]0.33[/C][/ROW]
[ROW][C]27[/C][C]0.73[/C][C]140.5[/C][C]56[/C][C]0.43[/C][C]81[/C][C]34[/C][C]0.41[/C][/ROW]
[ROW][C]28[/C][C]0.61[/C][C]129[/C][C]60.5[/C][C]0.36[/C][C]74[/C][C]39[/C][C]0.31[/C][/ROW]
[ROW][C]29[/C][C]1.87[/C][C]220.5[/C][C]14.5[/C][C]0.88[/C][C]101[/C][C]9[/C][C]0.84[/C][/ROW]
[ROW][C]30[/C][C]1.88[/C][C]229.5[/C][C]9[/C][C]0.92[/C][C]107[/C][C]10[/C][C]0.83[/C][/ROW]
[ROW][C]31[/C][C]1.37[/C][C]178[/C][C]17.5[/C][C]0.82[/C][C]100[/C][C]17[/C][C]0.71[/C][/ROW]
[ROW][C]32[/C][C]0.41[/C][C]104[/C][C]57[/C][C]0.29[/C][C]74[/C][C]42[/C][C]0.28[/C][/ROW]
[ROW][C]33[/C][C]1.92[/C][C]228[/C][C]3.5[/C][C]0.97[/C][C]110[/C][C]7[/C][C]0.88[/C][/ROW]
[ROW][C]34[/C][C]1.23[/C][C]161.5[/C][C]18[/C][C]0.8[/C][C]101[/C][C]16[/C][C]0.73[/C][/ROW]
[ROW][C]35[/C][C]2.07[/C][C]242.5[/C][C]2.5[/C][C]0.98[/C][C]111[/C][C]5[/C][C]0.91[/C][/ROW]
[ROW][C]36[/C][C]2.23[/C][C]262.5[/C][C]2[/C][C]0.98[/C][C]113[/C][C]4[/C][C]0.93[/C][/ROW]
[ROW][C]37[/C][C]1.99[/C][C]239[/C][C]6.5[/C][C]0.95[/C][C]110[/C][C]7[/C][C]0.88[/C][/ROW]
[ROW][C]38[/C][C]2.29[/C][C]269.5[/C][C]2[/C][C]0.99[/C][C]113[/C][C]4[/C][C]0.93[/C][/ROW]
[ROW][C]39[/C][C]2.21[/C][C]260.5[/C][C]2[/C][C]0.98[/C][C]113[/C][C]4[/C][C]0.93[/C][/ROW]
[ROW][C]40[/C][C]1.92[/C][C]227[/C][C]2.5[/C][C]0.98[/C][C]112[/C][C]5[/C][C]0.91[/C][/ROW]
[ROW][C]41[/C][C]2.22[/C][C]262.5[/C][C]3[/C][C]0.98[/C][C]113[/C][C]4[/C][C]0.93[/C][/ROW]
[ROW][C]42[/C][C]0.91[/C][C]145[/C][C]38.5[/C][C]0.58[/C][C]88[/C][C]29[/C][C]0.5[/C][/ROW]
[ROW][C]43[/C][C]1.1[/C][C]161.5[/C][C]33.5[/C][C]0.66[/C][C]91[/C][C]25[/C][C]0.57[/C][/ROW]
[ROW][C]44[/C][C]1.66[/C][C]207.5[/C][C]13[/C][C]0.88[/C][C]105[/C][C]12[/C][C]0.79[/C][/ROW]
[ROW][C]45[/C][C]1.98[/C][C]235.5[/C][C]4[/C][C]0.97[/C][C]111[/C][C]6[/C][C]0.9[/C][/ROW]
[ROW][C]46[/C][C]1.65[/C][C]205.5[/C][C]13[/C][C]0.88[/C][C]105[/C][C]12[/C][C]0.79[/C][/ROW]
[ROW][C]47[/C][C]2.12[/C][C]247[/C][C]3.5[/C][C]0.97[/C][C]110[/C][C]5[/C][C]0.91[/C][/ROW]
[ROW][C]48[/C][C]2.17[/C][C]255[/C][C]3[/C][C]0.98[/C][C]112[/C][C]4[/C][C]0.93[/C][/ROW]
[ROW][C]49[/C][C]2.17[/C][C]254[/C][C]2[/C][C]0.98[/C][C]112[/C][C]4[/C][C]0.93[/C][/ROW]
[ROW][C]50[/C][C]2.04[/C][C]240.5[/C][C]2[/C][C]0.98[/C][C]113[/C][C]4[/C][C]0.93[/C][/ROW]
[ROW][C]51[/C][C]1.76[/C][C]215[/C][C]8.5[/C][C]0.92[/C][C]106[/C][C]11[/C][C]0.81[/C][/ROW]
[ROW][C]52[/C][C]2.19[/C][C]259[/C][C]2.5[/C][C]0.98[/C][C]112[/C][C]5[/C][C]0.91[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
11.22169.528.50.7191250.57
21.79221170.86102120.79
3-2.188252-0.944108-0.93
42.34271.520.9911140.93
52.342722.50.9811050.91
62.012448.50.93106110.81
7-1.5525205-0.7816100-0.72
8-1.4919.5183.5-0.812189-0.62
90.38106.5630.2669460.2
100.7213562.50.3768330.35
11-1.1632.5160.5-0.662585-0.55
12-1.1322149-0.742290-0.61
130.219978.50.1254450.09
14-0.3678119.5-0.214867-0.17
150.8914147.50.576290.45
16-1.1842168.5-0.62483-0.55
17-1.9311221.5-0.918101-0.85
181.42199.534.50.7193230.6
19-0.5362.5121.5-0.323973-0.3
200.15103.5860.0961520.08
212.18260.560.9511340.93
220.44107.558.50.375370.34
232.04246.59.50.9310970.88
242.132577.50.9411250.91
251.25169.527.50.7293210.63
260.49112560.3376380.33
270.73140.5560.4381340.41
280.6112960.50.3674390.31
291.87220.514.50.8810190.84
301.88229.590.92107100.83
311.3717817.50.82100170.71
320.41104570.2974420.28
331.922283.50.9711070.88
341.23161.5180.8101160.73
352.07242.52.50.9811150.91
362.23262.520.9811340.93
371.992396.50.9511070.88
382.29269.520.9911340.93
392.21260.520.9811340.93
401.922272.50.9811250.91
412.22262.530.9811340.93
420.9114538.50.5888290.5
431.1161.533.50.6691250.57
441.66207.5130.88105120.79
451.98235.540.9711160.9
461.65205.5130.88105120.79
472.122473.50.9711050.91
482.1725530.9811240.93
492.1725420.9811240.93
502.04240.520.9811340.93
511.762158.50.92106110.81
522.192592.50.9811250.91







Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.989 (0)0.993 (0)
(Ps-Ns)/(Ps+Ns)0.989 (0)1 (0)0.998 (0)
(Pc-Nc)/(Pc+Nc)0.993 (0)0.998 (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) & 0.989 (0) & 0.993 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.989 (0) & 1 (0) & 0.998 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.993 (0) & 0.998 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]0.989 (0)[/C][C]0.993 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.989 (0)[/C][C]1 (0)[/C][C]0.998 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.993 (0)[/C][C]0.998 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)0.989 (0)0.993 (0)
(Ps-Ns)/(Ps+Ns)0.989 (0)1 (0)0.998 (0)
(Pc-Nc)/(Pc+Nc)0.993 (0)0.998 (0)1 (0)







Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.911 (0)0.918 (0)
(Ps-Ns)/(Ps+Ns)0.911 (0)1 (0)0.942 (0)
(Pc-Nc)/(Pc+Nc)0.918 (0)0.942 (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) & 0.911 (0) & 0.918 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.911 (0) & 1 (0) & 0.942 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.918 (0) & 0.942 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]0.911 (0)[/C][C]0.918 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.911 (0)[/C][C]1 (0)[/C][C]0.942 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.918 (0)[/C][C]0.942 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)0.911 (0)0.918 (0)
(Ps-Ns)/(Ps+Ns)0.911 (0)1 (0)0.942 (0)
(Pc-Nc)/(Pc+Nc)0.918 (0)0.942 (0)1 (0)



Parameters (Session):
Parameters (R input):
par1 = 1 2 3 4 5 6 ;
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')