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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

Sun, 07 Sep 2008 07:41:27 -0600

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/2008/Sep/07/t1220794944bzrkmfrlic23vxu.htm/, Retrieved Sat, 18 May 2024 16:53:52 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=14333, Retrieved Sat, 18 May 2024 16:53:52 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

277

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

-       [Survey Scores] [E-Learn 2008 table 2] [2008-09-07 13:41:27] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]

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Dataseries X:

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Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	40 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 40 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14333&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]40 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14333&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14333&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	40 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

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	0.43	116	26	0.63	103	22	0.65
2	1.13	249	13	0.9	168	9	0.9
3	0.43	113	23	0.66	103	19	0.69
4	1.37	295	11	0.93	182	7	0.93
5	0.39	114	33	0.55	100	30	0.54
6	1.32	282	8	0.94	178	7	0.92
7	0.34	103	33	0.51	91	27	0.54
8	1.22	263	10	0.93	173	8	0.91
9	0.62	147	17	0.79	119	16	0.76
10	1.01	221	10	0.91	156	7	0.91
11	0.8	179	13	0.86	134	12	0.84
12	1.17	252	9	0.93	171	8	0.91
13	0.83	187	15	0.85	141	15	0.81
14	0.96	212	12	0.89	151	12	0.85
15	0.45	120	27	0.63	98	24	0.61
16	0.81	184	16	0.84	137	14	0.81
17	0.44	140	49	0.48	116	38	0.51
18	0.66	164	26	0.73	118	22	0.69
19	0.47	142	44	0.53	119	33	0.57
20	0.85	194	18	0.83	145	15	0.81
21	0.15	94	62	0.21	81	50	0.24
22	0.45	136	43	0.52	103	33	0.51
23	0.27	111	54	0.35	96	38	0.43
24	0.85	198	22	0.8	141	15	0.81
25	0.83	179	7	0.92	141	7	0.91
26	1.17	250	6	0.95	171	4	0.95
27	0.87	194	14	0.87	141	12	0.84
28	1.08	232	8	0.93	160	6	0.93
29	0.7	156	11	0.87	130	11	0.84
30	1.12	235	3	0.97	165	3	0.96
31	0.8	178	11	0.88	142	11	0.86
32	1.04	223	7	0.94	163	7	0.92
33	0.38	125	45	0.47	107	36	0.5
34	0.78	187	24	0.77	137	19	0.76
35	0.25	100	49	0.34	87	37	0.4
36	0.66	167	29	0.7	125	22	0.7
37	0.47	134	36	0.58	111	27	0.61
38	0.89	208	22	0.81	150	16	0.81
39	0.07	89	74	0.09	74	60	0.1
40	0.34	130	60	0.37	98	49	0.33
41	0.57	142	23	0.72	116	21	0.69
42	1.06	232	12	0.9	158	10	0.88
43	0.36	105	30	0.56	93	23	0.6
44	0.99	221	16	0.86	154	12	0.86
45	0.89	195	10	0.9	149	10	0.87
46	1.3	273	3	0.98	177	3	0.97
47	0.86	191	13	0.87	136	10	0.86
48	1.21	258	7	0.95	169	5	0.94

\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 & 0.43 & 116 & 26 & 0.63 & 103 & 22 & 0.65 \tabularnewline
2 & 1.13 & 249 & 13 & 0.9 & 168 & 9 & 0.9 \tabularnewline
3 & 0.43 & 113 & 23 & 0.66 & 103 & 19 & 0.69 \tabularnewline
4 & 1.37 & 295 & 11 & 0.93 & 182 & 7 & 0.93 \tabularnewline
5 & 0.39 & 114 & 33 & 0.55 & 100 & 30 & 0.54 \tabularnewline
6 & 1.32 & 282 & 8 & 0.94 & 178 & 7 & 0.92 \tabularnewline
7 & 0.34 & 103 & 33 & 0.51 & 91 & 27 & 0.54 \tabularnewline
8 & 1.22 & 263 & 10 & 0.93 & 173 & 8 & 0.91 \tabularnewline
9 & 0.62 & 147 & 17 & 0.79 & 119 & 16 & 0.76 \tabularnewline
10 & 1.01 & 221 & 10 & 0.91 & 156 & 7 & 0.91 \tabularnewline
11 & 0.8 & 179 & 13 & 0.86 & 134 & 12 & 0.84 \tabularnewline
12 & 1.17 & 252 & 9 & 0.93 & 171 & 8 & 0.91 \tabularnewline
13 & 0.83 & 187 & 15 & 0.85 & 141 & 15 & 0.81 \tabularnewline
14 & 0.96 & 212 & 12 & 0.89 & 151 & 12 & 0.85 \tabularnewline
15 & 0.45 & 120 & 27 & 0.63 & 98 & 24 & 0.61 \tabularnewline
16 & 0.81 & 184 & 16 & 0.84 & 137 & 14 & 0.81 \tabularnewline
17 & 0.44 & 140 & 49 & 0.48 & 116 & 38 & 0.51 \tabularnewline
18 & 0.66 & 164 & 26 & 0.73 & 118 & 22 & 0.69 \tabularnewline
19 & 0.47 & 142 & 44 & 0.53 & 119 & 33 & 0.57 \tabularnewline
20 & 0.85 & 194 & 18 & 0.83 & 145 & 15 & 0.81 \tabularnewline
21 & 0.15 & 94 & 62 & 0.21 & 81 & 50 & 0.24 \tabularnewline
22 & 0.45 & 136 & 43 & 0.52 & 103 & 33 & 0.51 \tabularnewline
23 & 0.27 & 111 & 54 & 0.35 & 96 & 38 & 0.43 \tabularnewline
24 & 0.85 & 198 & 22 & 0.8 & 141 & 15 & 0.81 \tabularnewline
25 & 0.83 & 179 & 7 & 0.92 & 141 & 7 & 0.91 \tabularnewline
26 & 1.17 & 250 & 6 & 0.95 & 171 & 4 & 0.95 \tabularnewline
27 & 0.87 & 194 & 14 & 0.87 & 141 & 12 & 0.84 \tabularnewline
28 & 1.08 & 232 & 8 & 0.93 & 160 & 6 & 0.93 \tabularnewline
29 & 0.7 & 156 & 11 & 0.87 & 130 & 11 & 0.84 \tabularnewline
30 & 1.12 & 235 & 3 & 0.97 & 165 & 3 & 0.96 \tabularnewline
31 & 0.8 & 178 & 11 & 0.88 & 142 & 11 & 0.86 \tabularnewline
32 & 1.04 & 223 & 7 & 0.94 & 163 & 7 & 0.92 \tabularnewline
33 & 0.38 & 125 & 45 & 0.47 & 107 & 36 & 0.5 \tabularnewline
34 & 0.78 & 187 & 24 & 0.77 & 137 & 19 & 0.76 \tabularnewline
35 & 0.25 & 100 & 49 & 0.34 & 87 & 37 & 0.4 \tabularnewline
36 & 0.66 & 167 & 29 & 0.7 & 125 & 22 & 0.7 \tabularnewline
37 & 0.47 & 134 & 36 & 0.58 & 111 & 27 & 0.61 \tabularnewline
38 & 0.89 & 208 & 22 & 0.81 & 150 & 16 & 0.81 \tabularnewline
39 & 0.07 & 89 & 74 & 0.09 & 74 & 60 & 0.1 \tabularnewline
40 & 0.34 & 130 & 60 & 0.37 & 98 & 49 & 0.33 \tabularnewline
41 & 0.57 & 142 & 23 & 0.72 & 116 & 21 & 0.69 \tabularnewline
42 & 1.06 & 232 & 12 & 0.9 & 158 & 10 & 0.88 \tabularnewline
43 & 0.36 & 105 & 30 & 0.56 & 93 & 23 & 0.6 \tabularnewline
44 & 0.99 & 221 & 16 & 0.86 & 154 & 12 & 0.86 \tabularnewline
45 & 0.89 & 195 & 10 & 0.9 & 149 & 10 & 0.87 \tabularnewline
46 & 1.3 & 273 & 3 & 0.98 & 177 & 3 & 0.97 \tabularnewline
47 & 0.86 & 191 & 13 & 0.87 & 136 & 10 & 0.86 \tabularnewline
48 & 1.21 & 258 & 7 & 0.95 & 169 & 5 & 0.94 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14333&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]0.43[/C][C]116[/C][C]26[/C][C]0.63[/C][C]103[/C][C]22[/C][C]0.65[/C][/ROW]
[ROW][C]2[/C][C]1.13[/C][C]249[/C][C]13[/C][C]0.9[/C][C]168[/C][C]9[/C][C]0.9[/C][/ROW]
[ROW][C]3[/C][C]0.43[/C][C]113[/C][C]23[/C][C]0.66[/C][C]103[/C][C]19[/C][C]0.69[/C][/ROW]
[ROW][C]4[/C][C]1.37[/C][C]295[/C][C]11[/C][C]0.93[/C][C]182[/C][C]7[/C][C]0.93[/C][/ROW]
[ROW][C]5[/C][C]0.39[/C][C]114[/C][C]33[/C][C]0.55[/C][C]100[/C][C]30[/C][C]0.54[/C][/ROW]
[ROW][C]6[/C][C]1.32[/C][C]282[/C][C]8[/C][C]0.94[/C][C]178[/C][C]7[/C][C]0.92[/C][/ROW]
[ROW][C]7[/C][C]0.34[/C][C]103[/C][C]33[/C][C]0.51[/C][C]91[/C][C]27[/C][C]0.54[/C][/ROW]
[ROW][C]8[/C][C]1.22[/C][C]263[/C][C]10[/C][C]0.93[/C][C]173[/C][C]8[/C][C]0.91[/C][/ROW]
[ROW][C]9[/C][C]0.62[/C][C]147[/C][C]17[/C][C]0.79[/C][C]119[/C][C]16[/C][C]0.76[/C][/ROW]
[ROW][C]10[/C][C]1.01[/C][C]221[/C][C]10[/C][C]0.91[/C][C]156[/C][C]7[/C][C]0.91[/C][/ROW]
[ROW][C]11[/C][C]0.8[/C][C]179[/C][C]13[/C][C]0.86[/C][C]134[/C][C]12[/C][C]0.84[/C][/ROW]
[ROW][C]12[/C][C]1.17[/C][C]252[/C][C]9[/C][C]0.93[/C][C]171[/C][C]8[/C][C]0.91[/C][/ROW]
[ROW][C]13[/C][C]0.83[/C][C]187[/C][C]15[/C][C]0.85[/C][C]141[/C][C]15[/C][C]0.81[/C][/ROW]
[ROW][C]14[/C][C]0.96[/C][C]212[/C][C]12[/C][C]0.89[/C][C]151[/C][C]12[/C][C]0.85[/C][/ROW]
[ROW][C]15[/C][C]0.45[/C][C]120[/C][C]27[/C][C]0.63[/C][C]98[/C][C]24[/C][C]0.61[/C][/ROW]
[ROW][C]16[/C][C]0.81[/C][C]184[/C][C]16[/C][C]0.84[/C][C]137[/C][C]14[/C][C]0.81[/C][/ROW]
[ROW][C]17[/C][C]0.44[/C][C]140[/C][C]49[/C][C]0.48[/C][C]116[/C][C]38[/C][C]0.51[/C][/ROW]
[ROW][C]18[/C][C]0.66[/C][C]164[/C][C]26[/C][C]0.73[/C][C]118[/C][C]22[/C][C]0.69[/C][/ROW]
[ROW][C]19[/C][C]0.47[/C][C]142[/C][C]44[/C][C]0.53[/C][C]119[/C][C]33[/C][C]0.57[/C][/ROW]
[ROW][C]20[/C][C]0.85[/C][C]194[/C][C]18[/C][C]0.83[/C][C]145[/C][C]15[/C][C]0.81[/C][/ROW]
[ROW][C]21[/C][C]0.15[/C][C]94[/C][C]62[/C][C]0.21[/C][C]81[/C][C]50[/C][C]0.24[/C][/ROW]
[ROW][C]22[/C][C]0.45[/C][C]136[/C][C]43[/C][C]0.52[/C][C]103[/C][C]33[/C][C]0.51[/C][/ROW]
[ROW][C]23[/C][C]0.27[/C][C]111[/C][C]54[/C][C]0.35[/C][C]96[/C][C]38[/C][C]0.43[/C][/ROW]
[ROW][C]24[/C][C]0.85[/C][C]198[/C][C]22[/C][C]0.8[/C][C]141[/C][C]15[/C][C]0.81[/C][/ROW]
[ROW][C]25[/C][C]0.83[/C][C]179[/C][C]7[/C][C]0.92[/C][C]141[/C][C]7[/C][C]0.91[/C][/ROW]
[ROW][C]26[/C][C]1.17[/C][C]250[/C][C]6[/C][C]0.95[/C][C]171[/C][C]4[/C][C]0.95[/C][/ROW]
[ROW][C]27[/C][C]0.87[/C][C]194[/C][C]14[/C][C]0.87[/C][C]141[/C][C]12[/C][C]0.84[/C][/ROW]
[ROW][C]28[/C][C]1.08[/C][C]232[/C][C]8[/C][C]0.93[/C][C]160[/C][C]6[/C][C]0.93[/C][/ROW]
[ROW][C]29[/C][C]0.7[/C][C]156[/C][C]11[/C][C]0.87[/C][C]130[/C][C]11[/C][C]0.84[/C][/ROW]
[ROW][C]30[/C][C]1.12[/C][C]235[/C][C]3[/C][C]0.97[/C][C]165[/C][C]3[/C][C]0.96[/C][/ROW]
[ROW][C]31[/C][C]0.8[/C][C]178[/C][C]11[/C][C]0.88[/C][C]142[/C][C]11[/C][C]0.86[/C][/ROW]
[ROW][C]32[/C][C]1.04[/C][C]223[/C][C]7[/C][C]0.94[/C][C]163[/C][C]7[/C][C]0.92[/C][/ROW]
[ROW][C]33[/C][C]0.38[/C][C]125[/C][C]45[/C][C]0.47[/C][C]107[/C][C]36[/C][C]0.5[/C][/ROW]
[ROW][C]34[/C][C]0.78[/C][C]187[/C][C]24[/C][C]0.77[/C][C]137[/C][C]19[/C][C]0.76[/C][/ROW]
[ROW][C]35[/C][C]0.25[/C][C]100[/C][C]49[/C][C]0.34[/C][C]87[/C][C]37[/C][C]0.4[/C][/ROW]
[ROW][C]36[/C][C]0.66[/C][C]167[/C][C]29[/C][C]0.7[/C][C]125[/C][C]22[/C][C]0.7[/C][/ROW]
[ROW][C]37[/C][C]0.47[/C][C]134[/C][C]36[/C][C]0.58[/C][C]111[/C][C]27[/C][C]0.61[/C][/ROW]
[ROW][C]38[/C][C]0.89[/C][C]208[/C][C]22[/C][C]0.81[/C][C]150[/C][C]16[/C][C]0.81[/C][/ROW]
[ROW][C]39[/C][C]0.07[/C][C]89[/C][C]74[/C][C]0.09[/C][C]74[/C][C]60[/C][C]0.1[/C][/ROW]
[ROW][C]40[/C][C]0.34[/C][C]130[/C][C]60[/C][C]0.37[/C][C]98[/C][C]49[/C][C]0.33[/C][/ROW]
[ROW][C]41[/C][C]0.57[/C][C]142[/C][C]23[/C][C]0.72[/C][C]116[/C][C]21[/C][C]0.69[/C][/ROW]
[ROW][C]42[/C][C]1.06[/C][C]232[/C][C]12[/C][C]0.9[/C][C]158[/C][C]10[/C][C]0.88[/C][/ROW]
[ROW][C]43[/C][C]0.36[/C][C]105[/C][C]30[/C][C]0.56[/C][C]93[/C][C]23[/C][C]0.6[/C][/ROW]
[ROW][C]44[/C][C]0.99[/C][C]221[/C][C]16[/C][C]0.86[/C][C]154[/C][C]12[/C][C]0.86[/C][/ROW]
[ROW][C]45[/C][C]0.89[/C][C]195[/C][C]10[/C][C]0.9[/C][C]149[/C][C]10[/C][C]0.87[/C][/ROW]
[ROW][C]46[/C][C]1.3[/C][C]273[/C][C]3[/C][C]0.98[/C][C]177[/C][C]3[/C][C]0.97[/C][/ROW]
[ROW][C]47[/C][C]0.86[/C][C]191[/C][C]13[/C][C]0.87[/C][C]136[/C][C]10[/C][C]0.86[/C][/ROW]
[ROW][C]48[/C][C]1.21[/C][C]258[/C][C]7[/C][C]0.95[/C][C]169[/C][C]5[/C][C]0.94[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14333&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14333&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	0.43	116	26	0.63	103	22	0.65
2	1.13	249	13	0.9	168	9	0.9
3	0.43	113	23	0.66	103	19	0.69
4	1.37	295	11	0.93	182	7	0.93
5	0.39	114	33	0.55	100	30	0.54
6	1.32	282	8	0.94	178	7	0.92
7	0.34	103	33	0.51	91	27	0.54
8	1.22	263	10	0.93	173	8	0.91
9	0.62	147	17	0.79	119	16	0.76
10	1.01	221	10	0.91	156	7	0.91
11	0.8	179	13	0.86	134	12	0.84
12	1.17	252	9	0.93	171	8	0.91
13	0.83	187	15	0.85	141	15	0.81
14	0.96	212	12	0.89	151	12	0.85
15	0.45	120	27	0.63	98	24	0.61
16	0.81	184	16	0.84	137	14	0.81
17	0.44	140	49	0.48	116	38	0.51
18	0.66	164	26	0.73	118	22	0.69
19	0.47	142	44	0.53	119	33	0.57
20	0.85	194	18	0.83	145	15	0.81
21	0.15	94	62	0.21	81	50	0.24
22	0.45	136	43	0.52	103	33	0.51
23	0.27	111	54	0.35	96	38	0.43
24	0.85	198	22	0.8	141	15	0.81
25	0.83	179	7	0.92	141	7	0.91
26	1.17	250	6	0.95	171	4	0.95
27	0.87	194	14	0.87	141	12	0.84
28	1.08	232	8	0.93	160	6	0.93
29	0.7	156	11	0.87	130	11	0.84
30	1.12	235	3	0.97	165	3	0.96
31	0.8	178	11	0.88	142	11	0.86
32	1.04	223	7	0.94	163	7	0.92
33	0.38	125	45	0.47	107	36	0.5
34	0.78	187	24	0.77	137	19	0.76
35	0.25	100	49	0.34	87	37	0.4
36	0.66	167	29	0.7	125	22	0.7
37	0.47	134	36	0.58	111	27	0.61
38	0.89	208	22	0.81	150	16	0.81
39	0.07	89	74	0.09	74	60	0.1
40	0.34	130	60	0.37	98	49	0.33
41	0.57	142	23	0.72	116	21	0.69
42	1.06	232	12	0.9	158	10	0.88
43	0.36	105	30	0.56	93	23	0.6
44	0.99	221	16	0.86	154	12	0.86
45	0.89	195	10	0.9	149	10	0.87
46	1.3	273	3	0.98	177	3	0.97
47	0.86	191	13	0.87	136	10	0.86
48	1.21	258	7	0.95	169	5	0.94

Pearson correlation matrix of survey scores
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1	0.917819530511028	0.918736694238057
(Ps-Ns)/(Ps+Ns)	0.917819530511028	1	0.994272760888864
(Pc-Nc)/(Pc+Nc)	0.918736694238057	0.994272760888864	1

\begin{tabular}{lllllllll}
\hline
Pearson correlation matrix of survey scores \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 & 0.917819530511028 & 0.918736694238057 \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.917819530511028 & 1 & 0.994272760888864 \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.918736694238057 & 0.994272760888864 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14333&T=2

[TABLE]
[ROW][C]Pearson correlation matrix of survey scores[/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[/C][C]0.917819530511028[/C][C]0.918736694238057[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.917819530511028[/C][C]1[/C][C]0.994272760888864[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.918736694238057[/C][C]0.994272760888864[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14333&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14333&T=2

As an alternative you can also use a QR Code:

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

Pearson correlation matrix of survey scores
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1	0.917819530511028	0.918736694238057
(Ps-Ns)/(Ps+Ns)	0.917819530511028	1	0.994272760888864
(Pc-Nc)/(Pc+Nc)	0.918736694238057	0.994272760888864	1

Kendall tau rank correlation matrix of survey scores
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1	0.816146451901852	0.828931160602788
(Ps-Ns)/(Ps+Ns)	0.816146451901852	1	0.955205363187087
(Pc-Nc)/(Pc+Nc)	0.828931160602788	0.955205363187087	1

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlation matrix of survey scores \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 & 0.816146451901852 & 0.828931160602788 \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.816146451901852 & 1 & 0.955205363187087 \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.828931160602788 & 0.955205363187087 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14333&T=3

[TABLE]
[ROW][C]Kendall tau rank correlation matrix of survey scores[/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[/C][C]0.816146451901852[/C][C]0.828931160602788[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.816146451901852[/C][C]1[/C][C]0.955205363187087[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.828931160602788[/C][C]0.955205363187087[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14333&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14333&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 correlation matrix of survey scores
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1	0.816146451901852	0.828931160602788
(Ps-Ns)/(Ps+Ns)	0.816146451901852	1	0.955205363187087
(Pc-Nc)/(Pc+Nc)	0.828931160602788	0.955205363187087	1

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):

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])
}
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 correlation matrix of survey scores',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,cor(myresult[,1],myresult[,1],method='pearson'))
a<-table.element(a,cor(myresult[,1],myresult[,4],method='pearson'))
a<-table.element(a,cor(myresult[,1],myresult[,7],method='pearson'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,cor(myresult[,4],myresult[,1],method='pearson'))
a<-table.element(a,cor(myresult[,4],myresult[,4],method='pearson'))
a<-table.element(a,cor(myresult[,4],myresult[,7],method='pearson'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,cor(myresult[,7],myresult[,1],method='pearson'))
a<-table.element(a,cor(myresult[,7],myresult[,4],method='pearson'))
a<-table.element(a,cor(myresult[,7],myresult[,7],method='pearson'))
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 correlation matrix of survey scores',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,cor(myresult[,1],myresult[,1],method='kendall'))
a<-table.element(a,cor(myresult[,1],myresult[,4],method='kendall'))
a<-table.element(a,cor(myresult[,1],myresult[,7],method='kendall'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,cor(myresult[,4],myresult[,1],method='kendall'))
a<-table.element(a,cor(myresult[,4],myresult[,4],method='kendall'))
a<-table.element(a,cor(myresult[,4],myresult[,7],method='kendall'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,cor(myresult[,7],myresult[,1],method='kendall'))
a<-table.element(a,cor(myresult[,7],myresult[,4],method='kendall'))
a<-table.element(a,cor(myresult[,7],myresult[,7],method='kendall'))
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