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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

Wed, 23 Oct 2013 07:53:42 -0400

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/2013/Oct/23/t1382529271paxgbu3d0ch6so3.htm/, Retrieved Sat, 27 Apr 2024 19:22:41 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=218828, Retrieved Sat, 27 Apr 2024 19:22:41 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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

-       [Survey Scores] [] [2013-10-23 11:53:42] [86ae564e1d54e2fca6d87caa651728c1] [Current]

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Dataseries X:

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Histogram

Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	11 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.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 Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=218828&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 Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=218828&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=218828&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	11 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

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	0.45	141	41	0.55	120	39	0.51
2	0.68	176	26	0.74	146	24	0.72
3	0.58	167	38	0.63	136	34	0.6
4	0.47	144	39	0.57	125	36	0.55
5	0.76	191	22	0.79	154	20	0.77
6	0.74	194	30	0.73	156	25	0.72
7	0.7	183	28	0.73	147	28	0.68
8	0.98	235	18	0.86	177	15	0.84
9	-0.11	64	88	-0.16	58	73	-0.11
10	0.83	205	20	0.82	158	20	0.78
11	-0.37	68	151	-0.38	53	109	-0.35
12	0.91	219	17	0.86	171	15	0.84
13	1.15	289	34	0.79	187	29	0.73
14	0.5	148	38	0.59	117	35	0.54
15	0.22	90	42	0.36	80	38	0.36
16	-0.59	38	170	-0.63	34	130	-0.59
17	0.41	128	38	0.54	109	36	0.5
18	0.53	156	38	0.61	131	32	0.61
19	0.52	145	30	0.66	124	29	0.62
20	-0.17	75	113	-0.2	68	89	-0.13

\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 & 0.45 & 141 & 41 & 0.55 & 120 & 39 & 0.51 \tabularnewline
2 & 0.68 & 176 & 26 & 0.74 & 146 & 24 & 0.72 \tabularnewline
3 & 0.58 & 167 & 38 & 0.63 & 136 & 34 & 0.6 \tabularnewline
4 & 0.47 & 144 & 39 & 0.57 & 125 & 36 & 0.55 \tabularnewline
5 & 0.76 & 191 & 22 & 0.79 & 154 & 20 & 0.77 \tabularnewline
6 & 0.74 & 194 & 30 & 0.73 & 156 & 25 & 0.72 \tabularnewline
7 & 0.7 & 183 & 28 & 0.73 & 147 & 28 & 0.68 \tabularnewline
8 & 0.98 & 235 & 18 & 0.86 & 177 & 15 & 0.84 \tabularnewline
9 & -0.11 & 64 & 88 & -0.16 & 58 & 73 & -0.11 \tabularnewline
10 & 0.83 & 205 & 20 & 0.82 & 158 & 20 & 0.78 \tabularnewline
11 & -0.37 & 68 & 151 & -0.38 & 53 & 109 & -0.35 \tabularnewline
12 & 0.91 & 219 & 17 & 0.86 & 171 & 15 & 0.84 \tabularnewline
13 & 1.15 & 289 & 34 & 0.79 & 187 & 29 & 0.73 \tabularnewline
14 & 0.5 & 148 & 38 & 0.59 & 117 & 35 & 0.54 \tabularnewline
15 & 0.22 & 90 & 42 & 0.36 & 80 & 38 & 0.36 \tabularnewline
16 & -0.59 & 38 & 170 & -0.63 & 34 & 130 & -0.59 \tabularnewline
17 & 0.41 & 128 & 38 & 0.54 & 109 & 36 & 0.5 \tabularnewline
18 & 0.53 & 156 & 38 & 0.61 & 131 & 32 & 0.61 \tabularnewline
19 & 0.52 & 145 & 30 & 0.66 & 124 & 29 & 0.62 \tabularnewline
20 & -0.17 & 75 & 113 & -0.2 & 68 & 89 & -0.13 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=218828&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]0.45[/C][C]141[/C][C]41[/C][C]0.55[/C][C]120[/C][C]39[/C][C]0.51[/C][/ROW]
[ROW][C]2[/C][C]0.68[/C][C]176[/C][C]26[/C][C]0.74[/C][C]146[/C][C]24[/C][C]0.72[/C][/ROW]
[ROW][C]3[/C][C]0.58[/C][C]167[/C][C]38[/C][C]0.63[/C][C]136[/C][C]34[/C][C]0.6[/C][/ROW]
[ROW][C]4[/C][C]0.47[/C][C]144[/C][C]39[/C][C]0.57[/C][C]125[/C][C]36[/C][C]0.55[/C][/ROW]
[ROW][C]5[/C][C]0.76[/C][C]191[/C][C]22[/C][C]0.79[/C][C]154[/C][C]20[/C][C]0.77[/C][/ROW]
[ROW][C]6[/C][C]0.74[/C][C]194[/C][C]30[/C][C]0.73[/C][C]156[/C][C]25[/C][C]0.72[/C][/ROW]
[ROW][C]7[/C][C]0.7[/C][C]183[/C][C]28[/C][C]0.73[/C][C]147[/C][C]28[/C][C]0.68[/C][/ROW]
[ROW][C]8[/C][C]0.98[/C][C]235[/C][C]18[/C][C]0.86[/C][C]177[/C][C]15[/C][C]0.84[/C][/ROW]
[ROW][C]9[/C][C]-0.11[/C][C]64[/C][C]88[/C][C]-0.16[/C][C]58[/C][C]73[/C][C]-0.11[/C][/ROW]
[ROW][C]10[/C][C]0.83[/C][C]205[/C][C]20[/C][C]0.82[/C][C]158[/C][C]20[/C][C]0.78[/C][/ROW]
[ROW][C]11[/C][C]-0.37[/C][C]68[/C][C]151[/C][C]-0.38[/C][C]53[/C][C]109[/C][C]-0.35[/C][/ROW]
[ROW][C]12[/C][C]0.91[/C][C]219[/C][C]17[/C][C]0.86[/C][C]171[/C][C]15[/C][C]0.84[/C][/ROW]
[ROW][C]13[/C][C]1.15[/C][C]289[/C][C]34[/C][C]0.79[/C][C]187[/C][C]29[/C][C]0.73[/C][/ROW]
[ROW][C]14[/C][C]0.5[/C][C]148[/C][C]38[/C][C]0.59[/C][C]117[/C][C]35[/C][C]0.54[/C][/ROW]
[ROW][C]15[/C][C]0.22[/C][C]90[/C][C]42[/C][C]0.36[/C][C]80[/C][C]38[/C][C]0.36[/C][/ROW]
[ROW][C]16[/C][C]-0.59[/C][C]38[/C][C]170[/C][C]-0.63[/C][C]34[/C][C]130[/C][C]-0.59[/C][/ROW]
[ROW][C]17[/C][C]0.41[/C][C]128[/C][C]38[/C][C]0.54[/C][C]109[/C][C]36[/C][C]0.5[/C][/ROW]
[ROW][C]18[/C][C]0.53[/C][C]156[/C][C]38[/C][C]0.61[/C][C]131[/C][C]32[/C][C]0.61[/C][/ROW]
[ROW][C]19[/C][C]0.52[/C][C]145[/C][C]30[/C][C]0.66[/C][C]124[/C][C]29[/C][C]0.62[/C][/ROW]
[ROW][C]20[/C][C]-0.17[/C][C]75[/C][C]113[/C][C]-0.2[/C][C]68[/C][C]89[/C][C]-0.13[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=218828&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=218828&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	0.45	141	41	0.55	120	39	0.51
2	0.68	176	26	0.74	146	24	0.72
3	0.58	167	38	0.63	136	34	0.6
4	0.47	144	39	0.57	125	36	0.55
5	0.76	191	22	0.79	154	20	0.77
6	0.74	194	30	0.73	156	25	0.72
7	0.7	183	28	0.73	147	28	0.68
8	0.98	235	18	0.86	177	15	0.84
9	-0.11	64	88	-0.16	58	73	-0.11
10	0.83	205	20	0.82	158	20	0.78
11	-0.37	68	151	-0.38	53	109	-0.35
12	0.91	219	17	0.86	171	15	0.84
13	1.15	289	34	0.79	187	29	0.73
14	0.5	148	38	0.59	117	35	0.54
15	0.22	90	42	0.36	80	38	0.36
16	-0.59	38	170	-0.63	34	130	-0.59
17	0.41	128	38	0.54	109	36	0.5
18	0.53	156	38	0.61	131	32	0.61
19	0.52	145	30	0.66	124	29	0.62
20	-0.17	75	113	-0.2	68	89	-0.13

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.968 (0)	0.968 (0)
(Ps-Ns)/(Ps+Ns)	0.968 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.968 (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) & 0.968 (0) & 0.968 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.968 (0) & 1 (0) & 0.999 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.968 (0) & 0.999 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=218828&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]0.968 (0)[/C][C]0.968 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.968 (0)[/C][C]1 (0)[/C][C]0.999 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.968 (0)[/C][C]0.999 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=218828&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=218828&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)	0.968 (0)	0.968 (0)
(Ps-Ns)/(Ps+Ns)	0.968 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.968 (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)
mean	1 (0)	0.918 (0)	0.899 (0)
(Ps-Ns)/(Ps+Ns)	0.918 (0)	1 (0)	0.971 (0)
(Pc-Nc)/(Pc+Nc)	0.899 (0)	0.971 (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) & 0.918 (0) & 0.899 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.918 (0) & 1 (0) & 0.971 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.899 (0) & 0.971 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=218828&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]0.918 (0)[/C][C]0.899 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.918 (0)[/C][C]1 (0)[/C][C]0.971 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.899 (0)[/C][C]0.971 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=218828&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=218828&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)	0.918 (0)	0.899 (0)
(Ps-Ns)/(Ps+Ns)	0.918 (0)	1 (0)	0.971 (0)
(Pc-Nc)/(Pc+Nc)	0.899 (0)	0.971 (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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code