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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_surveyscores.wasp

Title produced by software

Survey Scores

Date of computation

Fri, 15 Dec 2017 11:28:09 +0100

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/15/t1513333828m0qhkbbxkspnmmd.htm/, Retrieved Wed, 11 Feb 2026 11:43:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309637, Retrieved Wed, 11 Feb 2026 11:43:54 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Info Q + System Q

Estimated Impact

344

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Survey Scores] [Survey Scores Ran...] [2017-12-15 10:28:09] [6a3953600cf19f2574c53feb20fccf09] [Current]

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Dataseries X:

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Histogram

Boxplots

3	3	2	3	3	2	3	2	3	3	3	4	1
5	5	4	4	3	4	4	4	3	4	5	5	5
4	4	4	4	4	4	4	4	4	5	5	5	4
4	4	4	4	4	5	5	4	4	2	3	3	4
3	3	5	5	4	4	4	4	4	5	2	5	5
3	3	4	4	4	4	4	4	5	3	4	5	5
3	4	3	4	4	4	4	5	4	4	4	5	4
3	3	4	3	4	4	4	4	4	4	4	5	4
3	3	2	3	4	3	3	3	3	4	3	4	4
3	4	3	4	4	2	3	5	3	4	5	3	4
3	3	3	3	4	4	3	4	4	3	3	4	4
4	3	3	4	3	4	4	4	4	4	4	5	4
4	3	4	4	4	4	3	4	4	4	3	5	4
4	4	4	5	4	4	4	4	4	4	4	5	4
4	2	4	2	3	3	3	4	3	2	3	3	4
5	4	4	4	4	3	4	3	3	2	5	4	5
2	2	4	4	4	4	4	4	4	4	3	4	3
4	3	4	3	4	4	4	4	4	4	4	3	4
3	3	4	3	5	5	5	5	5	5	5	5	5
3	3	4	4	3	2	2	4	4	2	5	4	4
3	4	4	3	4	3	3	4	4	3	4	4	4
3	2	4	4	3	3	3	3	4	3	2	4	4
2	3	3	3	4	4	3	4	4	5	5	5	5
3	2	4	3	3	4	4	2	5	3	4	3	5
4	4	3	4	4	4	3	4	4	3	1	3	5
3	2	3	2	4	2	2	3	3	3	3	3	4
3	4	4	4	4	3	4	5	4	4	4	3	3
4	3	3	5	4	5	5	5	5	4	4	5	5
3	3	3	3	3	4	3	3	4	4	4	5	5
4	3	3	4	3	3	3	3	4	4	4	4	4
3	5	5	4	4	4	4	4	5	5	5	5	5
2	2	2	4	3	3	3	4	4	4	2	5	3
1	2	3	1	5	1	1	4	1	5	2	3	3
2	1	2	5	5	3	5	5	5	5	5	5	5
4	4	4	4	3	2	2	4	4	4	5	5	3
3	4	4	4	4	3	3	4	3	3	3	4	4
3	3	3	2	3	4	4	3	3	4	4	4	4
4	4	3	3	4	2	2	3	3	3	3	4	4
3	2	3	3	3	3	3	3	3	4	3	4	4
4	4	3	3	3	3	3	3	3	3	3	3	3
4	3	4	4	3	4	4	3	2	3	2	4	3
2	3	2	4	2	4	3	4	4	5	5	5	5
2	2	2	3	3	2	2	3	2	4	4	5	4
3	2	4	4	4	4	4	4	5	5	5	4	5
4	4	4	4	4	3	3	5	4	4	4	3	3
4	2	2	4	4	4	4	5	4	5	5	5	5
4	4	5	5	4	3	4	4	5	4	4	5	5
2	3	4	3	4	4	4	3	3	3	4	5	4
4	5	5	5	4	2	2	4	3	4	4	5	4
4	4	4	4	4	4	4	4	3	4	4	3	4
5	5	4	4	5	5	5	5	4	5	5	5	5
3	2	2	3	3	3	3	4	4	4	4	4	4
3	4	4	3	4	3	3	4	4	4	3	2	3
4	3	4	3	4	4	4	4	3	2	2	3	3
2	3	4	4	4	4	3	4	4	3	4	4	4
3	3	4	3	4	4	4	4	5	4	3	5	5
3	3	4	4	4	4	4	4	3	4	4	3	4
5	3	4	5	4	4	4	3	4	5	5	5	5
2	2	2	4	3	3	2	4	3	2	2	4	2
4	4	4	3	4	4	4	4	4	4	4	5	5
3	3	3	4	3	3	3	4	4	4	3	5	4
4	3	3	3	4	3	3	4	4	4	4	4	4
4	3	3	4	4	4	4	4	4	4	4	4	4
4	3	3	4	4	3	3	4	3	2	4	5	5
2	2	3	3	2	3	3	3	4	2	1	5	5
4	4	4	3	4	3	3	4	4	4	4	5	4
4	3	4	2	3	3	4	3	4	4	4	4	4
4	4	4	4	4	4	4	4	4	4	4	4	4
5	4	4	3	5	4	4	5	5	2	5	5	5
3	4	5	3	3	4	3	5	3	2	2	4	4
3	2	3	2	3	2	2	2	4	4	4	5	5
3	4	3	4	3	3	3	3	4	3	2	3	4
4	3	4	4	5	4	4	5	4	5	5	5	5
4	4	4	4	5	3	3	4	5	5	4	5	4
4	3	4	4	4	4	3	4	4	4	4	4	4
2	3	4	3	3	3	2	4	4	4	3	5	5
3	3	3	2	3	2	3	3	3	3	3	4	3
3	2	3	3	4	4	4	4	4	3	3	4	4
2	4	4	3	3	2	3	4	1	3	3	3	3
3	4	4	5	3	4	4	5	4	4	4	5	5
2	4	3	4	4	2	3	2	3	1	2	4	5
4	4	4	2	3	3	3	4	3	2	4	4	5
3	3	3	3	3	3	3	4	3	3	5	5	4
4	3	3	5	4	3	3	5	5	5	5	5	5
4	4	4	5	4	4	4	4	3	2	4	4	4
4	4	5	3	3	2	2	4	3	4	4	5	4
3	3	4	4	4	4	3	3	4	3	4	4	3
4	3	4	4	3	3	3	4	4	4	4	4	4
3	3	2	4	3	3	2	2	3	4	2	3	2
3	4	4	4	4	4	4	4	4	4	4	5	5
3	4	4	4	4	3	3	4	4	4	4	5	5
3	4	4	3	4	4	3	5	4	4	5	4	4
4	4	4	4	4	3	3	4	5	4	4	5	4
4	3	3	4	4	5	5	4	4	4	4	4	5
2	2	2	3	3	2	2	2	3	5	4	5	5
4	2	3	2	4	4	4	5	5	5	4	4	4
4	2	3	3	5	1	3	4	4	5	4	4	4
4	2	3	3	3	2	2	3	5	2	4	5	5
4	3	3	4	3	3	4	3	4	3	4	4	3
4	4	4	4	4	2	2	4	4	4	4	4	5
2	3	1	2	3	2	2	4	5	4	3	4	4
2	3	3	3	3	2	3	3	4	3	3	3	3
3	3	2	2	4	4	4	3	5	1	4	3	3
2	2	2	2	4	4	4	4	4	4	4	3	3
4	4	4	3	4	4	4	4	5	4	4	4	3
4	4	4	5	5	4	4	4	4	4	4	4	5
3	3	3	3	4	3	3	4	4	4	1	4	4
2	3	4	2	4	2	2	4	5	5	4	5	5
3	3	3	3	3	3	3	3	3	3	3	3	3
4	3	3	4	4	3	4	4	3	2	4	3	4
2	2	3	3	2	3	3	3	2	3	3	4	3
4	2	4	4	3	2	3	4	4	2	4	4	2
2	2	2	2	2	2	2	3	3	3	3	4	5
2	2	2	2	2	2	2	3	3	3	3	4	5
3	4	4	4	3	3	3	3	3	4	4	3	3
2	3	3	4	4	4	3	4	4	5	1	5	5
5	3	4	5	5	5	5	5	4	4	5	4	5
2	2	2	3	3	3	3	2	2	4	2	3	4
2	1	1	4	2	4	4	4	4	4	4	5	5
4	4	4	4	4	3	3	4	4	5	4	4	4
4	4	4	4	4	2	2	4	3	4	2	4	3
4	4	3	4	4	4	4	4	3	2	3	3	3
1	1	2	3	3	3	1	2	3	3	3	4	4
3	2	2	3	3	3	2	3	2	3	3	4	4
3	3	3	3	3	3	2	3	3	4	4	4	4
4	4	4	3	4	3	3	4	4	4	4	4	5
3	4	4	3	3	3	3	3	4	3	4	4	5
3	3	3	2	4	3	3	4	4	4	3	4	5
2	2	2	3	3	2	2	3	2	4	3	5	5
4	3	2	3	2	3	3	4	3	3	2	3	3
2	4	2	2	3	2	4	4	3	3	4	2	4
3	3	4	3	2	2	2	4	4	1	4	4	4
4	4	4	4	4	3	3	4	3	3	4	4	4
2	2	2	4	2	4	3	3	4	5	3	5	5
3	2	4	3	4	3	2	4	4	4	3	5	5
3	1	3	4	4	4	4	5	5	5	2	3	2
3	3	4	3	4	4	4	4	4	5	4	5	5
3	3	2	3	4	3	3	4	4	2	5	4	5
2	3	3	2	2	1	2	4	2	4	2	4	5
3	3	4	3	4	3	3	4	4	4	4	4	5
2	2	2	3	2	3	3	4	3	3	3	4	4
3	2	3	4	4	4	4	3	4	3	3	4	3
2	3	2	5	4	3	3	4	4	4	5	5	3
3	2	3	4	3	1	1	4	4	4	4	4	4
4	3	3	3	4	3	3	3	3	3	3	3	3
1	1	1	3	1	3	3	2	2	3	4	5	5
4	3	2	3	2	1	3	4	3	3	3	3	2
5	5	4	4	3	4	4	4	4	5	4	4	5
4	4	4	4	4	4	4	4	4	4	4	4	4
2	2	4	4	3	4	4	4	3	1	2	4	4
1	2	3	4	3	4	4	2	4	4	4	4	4
4	4	4	4	4	4	4	4	3	1	3	4	3
3	3	3	3	3	3	3	4	4	3	3	4	4
3	3	4	2	4	2	2	3	5	2	3	5	5
4	4	4	3	4	4	3	4	3	4	4	4	3
3	2	2	5	4	4	4	5	5	5	5	5	5
3	4	4	4	4	3	3	3	4	3	4	5	5
3	3	4	3	4	4	3	5	4	4	4	4	4
4	2	4	4	5	5	5	4	4	4	5	5	5
3	3	3	3	2	2	2	3	3	4	3	5	5
4	3	3	4	2	2	3	2	3	3	3	4	2
3	4	3	2	4	3	3	5	3	5	4	5	5
2	3	3	3	3	1	1	2	4	4	3	4	5
2	2	3	2	2	3	3	3	2	3	3	3	4
4	3	3	3	4	3	2	2	3	4	5	4	5
4	3	5	4	4	3	2	5	3	3	5	3	5
4	4	4	4	4	4	4	4	4	4	4	4	4
4	3	3	4	3	4	4	4	3	2	4	5	5
2	2	4	2	3	1	1	4	3	2	2	4	4
4	4	4	4	4	3	3	3	4	4	3	5	4
3	3	4	3	4	3	3	4	3	3	4	4	4
4	3	3	3	3	4	5	5	4	4	5	4	4
3	4	4	4	4	4	4	4	4	4	4	4	4
4	3	4	5	4	4	4	5	3	4	4	4	4
3	3	3	4	4	4	4	3	3	5	4	4	4
2	3	3	2	4	2	2	3	4	2	3	5	5
4	4	4	4	4	3	3	4	4	2	3	4	4
4	3	4	4	4	4	4	4	4	3	4	4	4
4	4	3	4	3	4	4	4	4	4	4	4	4
3	2	4	4	4	4	4	3	5	4	3	5	5
3	4	3	3	4	3	3	4	4	3	3	4	3
2	2	2	2	2	3	3	3	3	3	3	4	5
3	4	1	1	3	1	1	3	3	2	2	5	5
3	4	4	4	4	4	4	4	4	3	4	4	4
4	4	4	3	4	2	3	4	4	4	3	4	4
4	4	4	4	5	4	3	4	4	4	4	4	5
4	4	4	5	4	4	3	4	4	4	5	5	4
4	3	3	3	4	5	3	4	5	4	2	3	3
4	3	4	4	4	3	3	3	3	4	3	4	5
4	4	4	5	4	3	3	4	4	3	4	4	5
2	3	3	3	4	3	3	4	4	3	2	4	4
2	2	3	3	4	5	4	4	3	5	3	5	4
3	3	3	3	3	4	3	3	4	4	5	4	5
3	1	3	3	3	3	3	3	3	4	4	4	4
2	3	3	3	3	2	2	2	3	2	4	3	5
2	3	3	3	3	2	2	3	4	3	4	5	5
4	3	3	5	4	3	3	4	4	5	2	3	3
4	4	4	2	3	4	4	3	3	5	3	4	4
4	2	4	4	5	4	4	5	4	2	4	4	2
3	3	4	4	4	4	4	4	4	3	4	4	4
4	4	4	5	4	4	4	4	4	4	4	4	4
2	2	3	2	3	3	3	3	3	5	2	4	3
4	1	2	4	4	3	2	2	2	4	4	5	5
4	2	3	5	5	4	4	5	5	5	4	2	3
3	3	4	3	3	2	2	4	3	4	4	4	4
4	3	4	4	4	4	4	4	4	3	4	4	4
3	3	4	3	3	4	3	3	4	5	4	4	5
3	4	3	4	4	4	4	3	4	2	4	5	5
4	3	3	4	4	5	5	4	4	3	4	5	3
4	4	2	2	3	4	3	4	4	1	2	4	2
4	4	2	2	3	4	3	4	4	1	2	4	2
2	2	2	3	2	1	1	3	1	5	2	5	5
4	3	4	3	4	3	3	4	4	4	3	4	4
2	2	3	2	4	1	2	4	4	4	4	4	4
2	1	2	1	3	5	5	5	5	5	4	5	5
4	4	4	5	4	4	4	4	3	4	4	4	5
4	4	4	4	3	3	3	3	4	4	4	5	5
2	2	2	3	4	2	2	3	4	5	4	5	5
3	2	4	3	3	4	3	4	3	2	3	5	4
4	3	3	4	4	4	4	4	4	1	4	5	5
3	3	3	4	3	3	3	4	4	5	4	5	5
2	2	2	2	2	2	2	3	4	3	3	4	4
3	2	2	3	2	4	4	4	4	4	4	5	5
3	4	3	4	4	3	3	3	4	4	3	4	4
3	3	3	4	4	4	4	4	4	3	3	4	5
3	2	4	3	3	2	3	4	3	1	4	4	5
3	2	3	4	4	5	5	3	3	3	4	5	5
4	3	4	4	4	4	4	4	4	5	3	4	5
2	3	4	3	3	3	3	4	3	4	4	4	4
5	4	5	5	5	5	5	5	5	5	5	4	5
3	3	3	3	3	3	3	3	3	3	2	3	3
3	3	2	3	3	3	3	3	3	4	4	4	5
3	3	3	4	3	3	3	4	4	4	4	4	4
3	3	3	4	3	4	4	4	4	4	4	4	4
4	4	4	4	4	4	4	4	4	4	4	4	4
4	4	4	4	4	4	4	4	4	4	4	4	4
4	4	4	4	4	4	4	4	4	4	4	4	4
4	4	4	4	4	4	4	4	4	5	4	5	5
3	2	3	3	3	3	3	3	3	4	4	4	5
4	5	5	4	4	2	3	4	4	4	4	4	5
3	3	3	3	4	2	2	4	3	2	3	2	4
1	2	1	2	3	2	2	3	2	3	3	3	5
2	2	3	3	4	2	3	5	5	5	4	3	4
2	2	2	3	2	1	2	2	2	2	2	2	1
5	4	4	5	5	4	5	4	4	5	4	5	4
3	3	1	1	2	1	1	1	2	2	1	2	2
2	2	2	2	2	1	1	3	2	2	3	3	4
2	2	2	2	3	1	2	2	2	2	3	3	4
5	4	4	4	4	4	4	4	4	5	5	4	4
3	4	3	3	5	3	3	4	4	5	4	5	5
3	3	3	3	3	3	3	3	3	3	3	3	3
4	4	3	5	4	4	5	4	4	5	4	5	5
3	2	2	5	5	4	5	5	5	5	2	5	5
1	1	1	1	1	1	1	2	1	3	1	2	4
2	3	3	3	3	4	4	3	4	3	3	4	3
4	4	4	3	4	4	3	4	5	4	4	4	4
3	3	3	3	3	3	3	3	3	3	3	3	3
2	2	3	3	2	2	2	3	2	3	3	3	4
2	2	2	2	2	2	2	2	2	2	4	4	4
2	2	2	2	3	3	3	4	3	3	3	3	4
3	2	3	3	4	2	2	3	3	4	4	3	2
3	3	3	3	3	3	3	3	3	3	3	3	3
4	4	4	4	4	4	4	4	4	4	4	4	3
2	4	4	5	5	5	4	5	4	5	5	5	4
2	5	5	4	4	3	4	4	3	4	5	5	5
4	4	4	3	4	3	3	4	4	4	4	5	4
3	3	2	4	4	4	4	4	3	5	4	4	4
5	4	4	5	3	3	3	4	4	4	5	4	5
5	2	5	5	5	2	2	5	4	1	3	5	5
3	3	3	4	4	4	4	4	4	2	2	4	4
3	4	5	5	4	4	4	4	5	4	4	5	5
5	4	3	4	3	3	3	4	3	4	5	5	4
4	4	5	5	5	4	4	5	4	4	5	5	4
4	4	5	4	4	2	2	5	4	3	5	5	5
5	4	5	4	4	3	3	4	4	3	3	4	5
1	2	3	3	2	3	3	3	3	4	2	4	4
4	4	4	4	4	5	5	4	3	4	5	4	5
4	3	3	4	4	4	4	5	4	2	4	5	5
1	3	3	4	5	3	3	4	5	3	5	5	4
3	3	4	4	4	4	4	4	4	3	4	4	4
2	2	2	3	4	3	3	4	4	2	2	5	5
3	2	3	5	4	4	4	4	3	4	3	4	5
4	4	4	4	4	5	4	5	4	4	4	4	1
3	4	4	5	4	3	3	5	5	5	5	5	5
2	3	3	3	4	3	3	4	3	4	4	5	5
3	3	4	4	4	4	4	4	3	4	5	4	5
3	3	3	3	3	4	4	4	3	2	2	3	3
4	4	4	4	3	4	4	3	4	5	4	5	5
4	3	4	4	4	2	3	5	4	3	5	5	5
4	5	3	4	3	3	4	4	3	4	4	4	3
4	3	4	4	5	4	4	4	4	3	4	4	5
3	4	4	4	5	4	4	5	5	5	5	5	5
4	1	3	5	3	3	2	3	5	2	4	4	2
4	3	3	4	4	3	3	3	4	4	4	3	5
3	4	4	3	3	3	4	3	4	2	2	3	3
3	3	3	5	4	4	4	4	4	2	4	2	4
3	1	3	2	4	2	3	4	2	4	2	4	4
4	4	4	5	3	5	5	4	4	4	4	4	4
4	4	5	4	4	2	3	4	5	3	3	4	5
4	3	3	4	3	3	3	4	4	4	4	4	4
4	4	4	4	3	3	3	3	4	3	3	3	3
3	4	4	5	4	3	3	4	3	4	2	4	5
1	3	3	4	4	4	4	4	2	4	4	4	3
3	3	3	3	3	3	3	3	3	3	3	3	3
4	3	4	3	5	3	3	4	4	3	4	4	5
4	4	3	4	3	4	4	5	4	4	4	5	4
4	5	4	5	4	5	5	5	4	3	4	4	5
4	4	4	4	4	3	3	4	4	4	4	4	4
4	4	4	3	3	3	3	4	4	4	4	4	4
4	2	3	2	3	2	2	4	3	3	2	3	3
3	2	2	4	4	4	4	4	4	4	4	5	5
3	4	3	4	3	4	4	4	2	4	4	4	5
2	3	3	4	4	4	4	4	5	4	4	5	4
4	3	3	4	3	3	3	4	3	2	4	2	2
3	2	4	3	3	4	3	4	2	2	2	4	5
3	3	4	4	3	4	4	4	4	4	3	3	3
4	3	4	4	3	3	4	4	3	4	4	4	4
3	3	3	3	4	3	3	4	5	5	2	1	3
3	4	3	4	4	5	4	5	4	3	5	5	5
5	4	4	5	4	5	5	4	4	5	5	5	5
3	3	3	4	3	4	4	3	4	2	2	4	4
4	3	3	3	3	3	3	4	3	4	4	4	4
4	4	4	4	4	4	4	4	4	4	4	2	4
4	4	3	4	3	3	3	4	2	1	4	4	5
4	3	2	5	2	4	2	2	3	2	1	4	2
4	3	3	3	3	5	4	4	2	3	4	2	2
4	4	4	4	4	3	3	4	4	3	5	5	4
4	4	4	5	4	4	4	4	4	5	4	5	5
4	4	4	3	3	3	3	3	2	3	2	4	4
2	2	3	4	4	2	2	4	3	4	3	4	4
4	4	3	4	3	2	2	4	3	2	2	4	4
4	4	3	3	4	2	2	4	3	3	3	4	3
4	3	4	4	5	3	3	5	4	3	3	4	3
2	4	3	4	5	3	3	5	3	5	5	2	3
3	4	3	2	4	3	3	4	4	3	4	4	4
5	2	3	4	5	3	2	5	3	4	5	4	5
4	4	4	4	4	3	3	4	4	4	4	4	5
5	4	4	4	5	5	5	5	5	5	5	5	5
3	4	4	4	3	3	3	4	3	3	4	4	3
2	2	1	1	2	1	1	4	4	4	2	1	4
2	3	2	2	4	1	1	5	1	4	3	3	4
2	2	3	3	3	3	2	1	2	4	4	3	5
4	4	4	4	2	1	1	2	4	4	2	4	4
2	3	2	2	3	3	3	4	3	4	3	2	4
4	3	3	3	3	2	2	4	3	2	4	4	3
4	4	4	5	4	4	4	4	3	4	4	4	4
4	4	4	4	4	4	4	4	4	4	4	4	4
4	4	4	4	2	1	1	5	3	5	3	5	4
5	5	4	4	4	4	4	5	4	2	3	4	5
4	4	5	5	5	3	3	5	5	1	5	4	5
4	4	5	5	5	3	3	5	5	5	5	3	3
4	4	4	5	4	4	4	4	4	4	5	4	4
3	3	3	4	3	4	4	3	3	4	4	4	4
3	3	3	2	3	3	3	3	3	3	2	2	3
3	3	4	4	4	4	4	5	4	4	2	4	4
5	3	4	5	5	4	4	5	4	4	3	4	5
4	4	4	3	5	2	2	4	3	5	5	5	5
3	4	3	4	4	4	4	4	4	2	4	5	3
3	3	2	1	3	2	3	3	4	3	2	4	4
3	4	3	3	4	4	4	4	4	4	4	4	4
3	3	3	3	3	4	4	4	3	3	4	3	3
3	4	3	4	4	4	3	3	4	2	3	4	4
3	4	3	4	4	4	4	4	4	4	3	5	4
3	2	4	4	2	4	4	4	4	2	5	5	5
3	3	4	3	3	4	5	4	4	4	4	3	3
3	3	3	3	3	2	2	5	2	3	4	4	5
3	2	3	4	4	4	3	3	4	3	4	4	5
4	4	3	3	5	5	5	5	5	3	5	3	3
4	2	5	4	4	4	3	5	5	3	3	5	4
5	4	5	4	5	5	5	5	5	2	2	5	5
4	4	4	4	4	4	4	4	4	4	3	5	5
3	4	4	4	3	4	4	4	3	3	3	4	3
3	5	4	5	4	5	5	3	5	5	5	4	4
5	3	3	4	4	4	5	4	3	4	5	4	5
3	4	3	4	4	4	4	4	4	3	4	4	4
3	4	4	4	4	4	5	5	4	4	5	4	4
3	3	3	4	4	3	4	3	4	2	4	3	5
5	5	4	4	3	5	5	3	5	4	4	5	5
4	4	4	4	3	3	3	4	4	4	2	2	2
5	5	5	4	5	4	4	4	5	5	4	5	5
2	2	2	3	3	2	2	3	3	3	4	2	3
3	3	3	3	3	4	3	3	3	3	2	2	4
4	3	3	3	5	3	3	5	4	4	4	5	5
4	3	4	4	4	4	4	5	4	5	2	5	3
5	4	5	4	4	5	5	4	4	5	4	5	4
4	4	4	4	3	2	2	2	2	3	3	4	4
4	2	3	4	3	3	4	3	3	3	3	3	4
4	3	4	4	4	2	3	4	4	5	4	3	4
4	3	3	4	4	3	3	4	4	2	4	4	4
4	4	3	4	3	3	3	3	3	4	1	5	3
4	4	4	4	3	4	4	3	4	3	4	4	4
5	4	4	4	4	5	5	4	4	3	5	5	5
3	3	4	5	4	4	4	5	4	2	4	3	4
4	4	4	5	5	5	5	5	5	5	5	4	4
4	5	5	5	4	4	4	5	4	4	4	4	4
2	2	3	5	5	4	3	4	3	2	2	4	5
4	4	3	4	3	3	3	2	4	5	2	4	4
4	4	4	4	3	3	3	3	4	4	4	4	5
2	3	3	4	3	3	3	5	3	2	3	4	4
3	3	3	2	3	3	3	3	3	3	3	3	3
3	4	3	4	4	4	3	3	5	4	4	3	4
4	4	3	4	2	2	2	4	2	3	4	4	4
3	4	4	4	4	5	4	5	3	2	2	3	4
4	2	3	3	4	4	4	5	4	4	3	5	5
2	3	3	3	3	2	2	3	3	3	3	4	4
4	4	4	4	4	4	4	4	4	4	4	5	5
4	4	2	3	3	3	2	4	2	5	4	4	4
3	3	5	3	4	4	4	4	4	4	4	4	4
3	3	3	4	3	4	3	3	3	4	3	3	5
4	3	5	4	5	3	4	5	5	5	4	5	4
2	4	3	3	4	2	2	3	3	3	1	2	4
4	3	2	2	3	2	2	3	2	3	2	3	4
2	3	4	4	3	4	3	2	3	4	4	4	4
3	4	5	3	4	1	2	3	4	4	5	4	4
4	4	3	5	3	4	4	5	3	3	5	4	4
3	4	4	3	5	4	4	5	4	5	4	4	5
4	2	4	4	4	5	4	4	2	2	2	4	5
3	3	3	3	4	3	3	4	4	3	4	3	4
2	2	4	2	4	1	2	3	4	4	2	4	4
4	4	4	4	3	3	4	4	4	3	4	4	4
1	2	2	1	5	1	1	3	2	4	4	3	5
3	3	3	5	4	5	4	4	4	2	5	5	5
4	3	4	3	4	3	3	4	4	2	5	5	5
3	3	3	4	3	4	4	4	4	4	4	2	4
4	4	4	4	4	2	2	5	3	2	2	2	4
3	4	4	3	4	4	4	4	3	3	3	4	4
4	4	4	4	4	4	3	3	3	2	4	3	3
3	3	3	4	3	4	4	3	3	3	4	4	3
3	4	4	3	4	4	4	4	3	4	3	3	4
3	4	3	5	4	4	4	4	5	3	4	5	5
5	2	3	5	4	4	4	5	4	4	4	4	4
3	3	2	4	3	3	3	4	4	4	4	5	5
3	4	3	4	3	4	4	3	2	3	2	5	5
4	5	4	4	4	3	3	5	4	2	4	5	5
4	5	5	5	5	5	5	5	4	4	5	5	5
2	3	2	4	5	4	4	5	3	4	3	5	4
3	2	2	3	3	3	3	4	3	3	2	3	3
5	4	3	5	4	5	4	4	4	4	2	5	3
3	3	3	3	4	3	3	4	4	3	4	4	4
3	3	4	3	4	5	5	5	3	3	5	5	5
3	3	3	4	4	2	2	3	4	4	4	4	4
3	4	4	3	4	5	5	5	4	5	4	4	5
3	4	4	4	3	3	3	4	4	3	5	5	5
5	5	4	4	5	4	4	5	4	3	4	4	5
4	4	4	4	4	4	4	4	4	4	4	4	5
4	4	4	4	4	3	3	4	3	3	4	4	4

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 seconds
R Server	Big 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 time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309637&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]

0 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309637&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309637&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 Output	view raw output of R engine
Computing time	0 seconds
R Server	Big Analytics Cloud Computing Center

Summary of survey scores (median of Likert score was subtracted)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	0.31	231	94	0.42	203	84	0.41
2	0.2	199	109	0.29	182	98	0.3
3	0.38	242	73	0.54	215	65	0.54
4	0.57	314	59	0.68	258	51	0.67
5	0.62	311	35	0.8	266	33	0.78
6	0.3	246	110	0.38	210	88	0.41
7	0.28	225	98	0.39	191	83	0.39
8	0.81	391	28	0.87	314	26	0.85
9	0.63	325	43	0.77	274	38	0.76
10	0.53	324	87	0.58	253	75	0.54
11	0.6	345	79	0.63	277	70	0.6
12	1.04	490	24	0.91	352	22	0.88
13	1.13	524	22	0.92	357	19	0.9

\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 & 0.31 & 231 & 94 & 0.42 & 203 & 84 & 0.41 \tabularnewline
2 & 0.2 & 199 & 109 & 0.29 & 182 & 98 & 0.3 \tabularnewline
3 & 0.38 & 242 & 73 & 0.54 & 215 & 65 & 0.54 \tabularnewline
4 & 0.57 & 314 & 59 & 0.68 & 258 & 51 & 0.67 \tabularnewline
5 & 0.62 & 311 & 35 & 0.8 & 266 & 33 & 0.78 \tabularnewline
6 & 0.3 & 246 & 110 & 0.38 & 210 & 88 & 0.41 \tabularnewline
7 & 0.28 & 225 & 98 & 0.39 & 191 & 83 & 0.39 \tabularnewline
8 & 0.81 & 391 & 28 & 0.87 & 314 & 26 & 0.85 \tabularnewline
9 & 0.63 & 325 & 43 & 0.77 & 274 & 38 & 0.76 \tabularnewline
10 & 0.53 & 324 & 87 & 0.58 & 253 & 75 & 0.54 \tabularnewline
11 & 0.6 & 345 & 79 & 0.63 & 277 & 70 & 0.6 \tabularnewline
12 & 1.04 & 490 & 24 & 0.91 & 352 & 22 & 0.88 \tabularnewline
13 & 1.13 & 524 & 22 & 0.92 & 357 & 19 & 0.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309637&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]0.31[/C][C]231[/C][C]94[/C][C]0.42[/C][C]203[/C][C]84[/C][C]0.41[/C][/ROW]
[ROW][C]2[/C][C]0.2[/C][C]199[/C][C]109[/C][C]0.29[/C][C]182[/C][C]98[/C][C]0.3[/C][/ROW]
[ROW][C]3[/C][C]0.38[/C][C]242[/C][C]73[/C][C]0.54[/C][C]215[/C][C]65[/C][C]0.54[/C][/ROW]
[ROW][C]4[/C][C]0.57[/C][C]314[/C][C]59[/C][C]0.68[/C][C]258[/C][C]51[/C][C]0.67[/C][/ROW]
[ROW][C]5[/C][C]0.62[/C][C]311[/C][C]35[/C][C]0.8[/C][C]266[/C][C]33[/C][C]0.78[/C][/ROW]
[ROW][C]6[/C][C]0.3[/C][C]246[/C][C]110[/C][C]0.38[/C][C]210[/C][C]88[/C][C]0.41[/C][/ROW]
[ROW][C]7[/C][C]0.28[/C][C]225[/C][C]98[/C][C]0.39[/C][C]191[/C][C]83[/C][C]0.39[/C][/ROW]
[ROW][C]8[/C][C]0.81[/C][C]391[/C][C]28[/C][C]0.87[/C][C]314[/C][C]26[/C][C]0.85[/C][/ROW]
[ROW][C]9[/C][C]0.63[/C][C]325[/C][C]43[/C][C]0.77[/C][C]274[/C][C]38[/C][C]0.76[/C][/ROW]
[ROW][C]10[/C][C]0.53[/C][C]324[/C][C]87[/C][C]0.58[/C][C]253[/C][C]75[/C][C]0.54[/C][/ROW]
[ROW][C]11[/C][C]0.6[/C][C]345[/C][C]79[/C][C]0.63[/C][C]277[/C][C]70[/C][C]0.6[/C][/ROW]
[ROW][C]12[/C][C]1.04[/C][C]490[/C][C]24[/C][C]0.91[/C][C]352[/C][C]22[/C][C]0.88[/C][/ROW]
[ROW][C]13[/C][C]1.13[/C][C]524[/C][C]22[/C][C]0.92[/C][C]357[/C][C]19[/C][C]0.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309637&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309637&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)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	0.31	231	94	0.42	203	84	0.41
2	0.2	199	109	0.29	182	98	0.3
3	0.38	242	73	0.54	215	65	0.54
4	0.57	314	59	0.68	258	51	0.67
5	0.62	311	35	0.8	266	33	0.78
6	0.3	246	110	0.38	210	88	0.41
7	0.28	225	98	0.39	191	83	0.39
8	0.81	391	28	0.87	314	26	0.85
9	0.63	325	43	0.77	274	38	0.76
10	0.53	324	87	0.58	253	75	0.54
11	0.6	345	79	0.63	277	70	0.6
12	1.04	490	24	0.91	352	22	0.88
13	1.13	524	22	0.92	357	19	0.9

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.942 (0)	0.938 (0)
(Ps-Ns)/(Ps+Ns)	0.942 (0)	1 (0)	0.998 (0)
(Pc-Nc)/(Pc+Nc)	0.938 (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) & 0.942 (0) & 0.938 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.942 (0) & 1 (0) & 0.998 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.938 (0) & 0.998 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309637&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]0.942 (0)[/C][C]0.938 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.942 (0)[/C][C]1 (0)[/C][C]0.998 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.938 (0)[/C][C]0.998 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309637&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309637&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)
mean	1 (0)	0.942 (0)	0.938 (0)
(Ps-Ns)/(Ps+Ns)	0.942 (0)	1 (0)	0.998 (0)
(Pc-Nc)/(Pc+Nc)	0.938 (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)
mean	1 (0)	0.923 (0)	0.935 (0)
(Ps-Ns)/(Ps+Ns)	0.923 (0)	1 (0)	0.961 (0)
(Pc-Nc)/(Pc+Nc)	0.935 (0)	0.961 (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) & 0.923 (0) & 0.935 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.923 (0) & 1 (0) & 0.961 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.935 (0) & 0.961 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309637&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]0.923 (0)[/C][C]0.935 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.923 (0)[/C][C]1 (0)[/C][C]0.961 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.935 (0)[/C][C]0.961 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309637&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309637&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)
mean	1 (0)	0.923 (0)	0.935 (0)
(Ps-Ns)/(Ps+Ns)	0.923 (0)	1 (0)	0.961 (0)
(Pc-Nc)/(Pc+Nc)	0.935 (0)	0.961 (0)	1 (0)

Parameters (Session):

par1 = TRUE ;

Parameters (R input):

par1 = 1 2 3 4 5 ;

R code (references can be found in the software module):

par1 <- '1 2 3 4 5'
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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code