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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, 06 Dec 2017 13:56:58 +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/06/t1512565059ycrl1pxx5z399ka.htm/, Retrieved Tue, 14 May 2024 09:47:04 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308606, Retrieved Tue, 14 May 2024 09:47:04 +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] [Survey scores ran...] [2017-12-06 12:56:58] [dd1b1eac6490c5f5f771b5814b2d0001] [Current]

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Dataseries X:

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Histogram

Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308606&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=308606&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308606&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	1 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	-0.22	25	65	-0.44	25	47	-0.31
2	-0.32	29	86	-0.5	29	64	-0.38
3	-0.06	36	47	-0.13	36	40	-0.05
4	-0.49	19	107	-0.7	19	83	-0.63
5	-0.35	14	76	-0.69	14	59	-0.62
6	-0.31	30	85	-0.48	30	57	-0.31
7	-0.45	38	118	-0.51	38	80	-0.36
8	-0.37	31	96	-0.51	31	75	-0.42
9	-1.43	7	262	-0.95	7	149	-0.91
10	-0.82	7	153	-0.91	7	112	-0.88
11	-0.76	4	139	-0.94	4	106	-0.93
12	-0.78	7	146	-0.91	7	103	-0.87
13	-0.92	5	168	-0.94	5	119	-0.92
14	-0.64	7	121	-0.89	7	88	-0.85
15	-0.54	15	111	-0.76	15	87	-0.71
16	-0.78	7	146	-0.91	7	102	-0.87
17	-0.79	9	149	-0.89	9	109	-0.85
18	-0.25	24	68	-0.48	24	55	-0.39
19	-0.29	19	70	-0.57	19	57	-0.5
20	-0.38	48	115	-0.41	48	66	-0.16
21	-0.16	42	71	-0.26	42	49	-0.08
22	-0.42	33	108	-0.53	33	71	-0.37
23	-0.51	23	114	-0.66	23	80	-0.55
24	-0.33	22	80	-0.57	22	67	-0.51
25	-0.42	28	103	-0.57	28	71	-0.43
26	0.19	65	32	0.34	65	29	0.38
27	-0.3	47	101	-0.36	47	73	-0.22
28	-0.08	50	65	-0.13	50	51	-0.01
29	-0.44	11	89	-0.78	11	72	-0.73
30	-0.34	18	79	-0.63	18	70	-0.59
31	-0.37	28	94	-0.54	28	68	-0.42
32	0.16	63	35	0.29	63	33	0.31
33	0.12	66	44	0.2	66	36	0.29
34	-0.24	25	67	-0.46	25	49	-0.32
35	0.2	67	32	0.35	67	29	0.4
36	0.17	56	26	0.37	56	22	0.44
37	-0.09	32	48	-0.2	32	42	-0.14
38	-0.14	27	52	-0.32	27	49	-0.29
39	-0.79	17	158	-0.81	17	111	-0.73
40	-0.07	36	49	-0.15	36	39	-0.04
41	-0.1	41	58	-0.17	41	50	-0.1
42	-0.21	42	80	-0.31	42	59	-0.17
43	-0.22	45	84	-0.3	45	64	-0.17
44	-0.04	40	47	-0.08	40	41	-0.01

\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 & -0.22 & 25 & 65 & -0.44 & 25 & 47 & -0.31 \tabularnewline
2 & -0.32 & 29 & 86 & -0.5 & 29 & 64 & -0.38 \tabularnewline
3 & -0.06 & 36 & 47 & -0.13 & 36 & 40 & -0.05 \tabularnewline
4 & -0.49 & 19 & 107 & -0.7 & 19 & 83 & -0.63 \tabularnewline
5 & -0.35 & 14 & 76 & -0.69 & 14 & 59 & -0.62 \tabularnewline
6 & -0.31 & 30 & 85 & -0.48 & 30 & 57 & -0.31 \tabularnewline
7 & -0.45 & 38 & 118 & -0.51 & 38 & 80 & -0.36 \tabularnewline
8 & -0.37 & 31 & 96 & -0.51 & 31 & 75 & -0.42 \tabularnewline
9 & -1.43 & 7 & 262 & -0.95 & 7 & 149 & -0.91 \tabularnewline
10 & -0.82 & 7 & 153 & -0.91 & 7 & 112 & -0.88 \tabularnewline
11 & -0.76 & 4 & 139 & -0.94 & 4 & 106 & -0.93 \tabularnewline
12 & -0.78 & 7 & 146 & -0.91 & 7 & 103 & -0.87 \tabularnewline
13 & -0.92 & 5 & 168 & -0.94 & 5 & 119 & -0.92 \tabularnewline
14 & -0.64 & 7 & 121 & -0.89 & 7 & 88 & -0.85 \tabularnewline
15 & -0.54 & 15 & 111 & -0.76 & 15 & 87 & -0.71 \tabularnewline
16 & -0.78 & 7 & 146 & -0.91 & 7 & 102 & -0.87 \tabularnewline
17 & -0.79 & 9 & 149 & -0.89 & 9 & 109 & -0.85 \tabularnewline
18 & -0.25 & 24 & 68 & -0.48 & 24 & 55 & -0.39 \tabularnewline
19 & -0.29 & 19 & 70 & -0.57 & 19 & 57 & -0.5 \tabularnewline
20 & -0.38 & 48 & 115 & -0.41 & 48 & 66 & -0.16 \tabularnewline
21 & -0.16 & 42 & 71 & -0.26 & 42 & 49 & -0.08 \tabularnewline
22 & -0.42 & 33 & 108 & -0.53 & 33 & 71 & -0.37 \tabularnewline
23 & -0.51 & 23 & 114 & -0.66 & 23 & 80 & -0.55 \tabularnewline
24 & -0.33 & 22 & 80 & -0.57 & 22 & 67 & -0.51 \tabularnewline
25 & -0.42 & 28 & 103 & -0.57 & 28 & 71 & -0.43 \tabularnewline
26 & 0.19 & 65 & 32 & 0.34 & 65 & 29 & 0.38 \tabularnewline
27 & -0.3 & 47 & 101 & -0.36 & 47 & 73 & -0.22 \tabularnewline
28 & -0.08 & 50 & 65 & -0.13 & 50 & 51 & -0.01 \tabularnewline
29 & -0.44 & 11 & 89 & -0.78 & 11 & 72 & -0.73 \tabularnewline
30 & -0.34 & 18 & 79 & -0.63 & 18 & 70 & -0.59 \tabularnewline
31 & -0.37 & 28 & 94 & -0.54 & 28 & 68 & -0.42 \tabularnewline
32 & 0.16 & 63 & 35 & 0.29 & 63 & 33 & 0.31 \tabularnewline
33 & 0.12 & 66 & 44 & 0.2 & 66 & 36 & 0.29 \tabularnewline
34 & -0.24 & 25 & 67 & -0.46 & 25 & 49 & -0.32 \tabularnewline
35 & 0.2 & 67 & 32 & 0.35 & 67 & 29 & 0.4 \tabularnewline
36 & 0.17 & 56 & 26 & 0.37 & 56 & 22 & 0.44 \tabularnewline
37 & -0.09 & 32 & 48 & -0.2 & 32 & 42 & -0.14 \tabularnewline
38 & -0.14 & 27 & 52 & -0.32 & 27 & 49 & -0.29 \tabularnewline
39 & -0.79 & 17 & 158 & -0.81 & 17 & 111 & -0.73 \tabularnewline
40 & -0.07 & 36 & 49 & -0.15 & 36 & 39 & -0.04 \tabularnewline
41 & -0.1 & 41 & 58 & -0.17 & 41 & 50 & -0.1 \tabularnewline
42 & -0.21 & 42 & 80 & -0.31 & 42 & 59 & -0.17 \tabularnewline
43 & -0.22 & 45 & 84 & -0.3 & 45 & 64 & -0.17 \tabularnewline
44 & -0.04 & 40 & 47 & -0.08 & 40 & 41 & -0.01 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308606&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]-0.22[/C][C]25[/C][C]65[/C][C]-0.44[/C][C]25[/C][C]47[/C][C]-0.31[/C][/ROW]
[ROW][C]2[/C][C]-0.32[/C][C]29[/C][C]86[/C][C]-0.5[/C][C]29[/C][C]64[/C][C]-0.38[/C][/ROW]
[ROW][C]3[/C][C]-0.06[/C][C]36[/C][C]47[/C][C]-0.13[/C][C]36[/C][C]40[/C][C]-0.05[/C][/ROW]
[ROW][C]4[/C][C]-0.49[/C][C]19[/C][C]107[/C][C]-0.7[/C][C]19[/C][C]83[/C][C]-0.63[/C][/ROW]
[ROW][C]5[/C][C]-0.35[/C][C]14[/C][C]76[/C][C]-0.69[/C][C]14[/C][C]59[/C][C]-0.62[/C][/ROW]
[ROW][C]6[/C][C]-0.31[/C][C]30[/C][C]85[/C][C]-0.48[/C][C]30[/C][C]57[/C][C]-0.31[/C][/ROW]
[ROW][C]7[/C][C]-0.45[/C][C]38[/C][C]118[/C][C]-0.51[/C][C]38[/C][C]80[/C][C]-0.36[/C][/ROW]
[ROW][C]8[/C][C]-0.37[/C][C]31[/C][C]96[/C][C]-0.51[/C][C]31[/C][C]75[/C][C]-0.42[/C][/ROW]
[ROW][C]9[/C][C]-1.43[/C][C]7[/C][C]262[/C][C]-0.95[/C][C]7[/C][C]149[/C][C]-0.91[/C][/ROW]
[ROW][C]10[/C][C]-0.82[/C][C]7[/C][C]153[/C][C]-0.91[/C][C]7[/C][C]112[/C][C]-0.88[/C][/ROW]
[ROW][C]11[/C][C]-0.76[/C][C]4[/C][C]139[/C][C]-0.94[/C][C]4[/C][C]106[/C][C]-0.93[/C][/ROW]
[ROW][C]12[/C][C]-0.78[/C][C]7[/C][C]146[/C][C]-0.91[/C][C]7[/C][C]103[/C][C]-0.87[/C][/ROW]
[ROW][C]13[/C][C]-0.92[/C][C]5[/C][C]168[/C][C]-0.94[/C][C]5[/C][C]119[/C][C]-0.92[/C][/ROW]
[ROW][C]14[/C][C]-0.64[/C][C]7[/C][C]121[/C][C]-0.89[/C][C]7[/C][C]88[/C][C]-0.85[/C][/ROW]
[ROW][C]15[/C][C]-0.54[/C][C]15[/C][C]111[/C][C]-0.76[/C][C]15[/C][C]87[/C][C]-0.71[/C][/ROW]
[ROW][C]16[/C][C]-0.78[/C][C]7[/C][C]146[/C][C]-0.91[/C][C]7[/C][C]102[/C][C]-0.87[/C][/ROW]
[ROW][C]17[/C][C]-0.79[/C][C]9[/C][C]149[/C][C]-0.89[/C][C]9[/C][C]109[/C][C]-0.85[/C][/ROW]
[ROW][C]18[/C][C]-0.25[/C][C]24[/C][C]68[/C][C]-0.48[/C][C]24[/C][C]55[/C][C]-0.39[/C][/ROW]
[ROW][C]19[/C][C]-0.29[/C][C]19[/C][C]70[/C][C]-0.57[/C][C]19[/C][C]57[/C][C]-0.5[/C][/ROW]
[ROW][C]20[/C][C]-0.38[/C][C]48[/C][C]115[/C][C]-0.41[/C][C]48[/C][C]66[/C][C]-0.16[/C][/ROW]
[ROW][C]21[/C][C]-0.16[/C][C]42[/C][C]71[/C][C]-0.26[/C][C]42[/C][C]49[/C][C]-0.08[/C][/ROW]
[ROW][C]22[/C][C]-0.42[/C][C]33[/C][C]108[/C][C]-0.53[/C][C]33[/C][C]71[/C][C]-0.37[/C][/ROW]
[ROW][C]23[/C][C]-0.51[/C][C]23[/C][C]114[/C][C]-0.66[/C][C]23[/C][C]80[/C][C]-0.55[/C][/ROW]
[ROW][C]24[/C][C]-0.33[/C][C]22[/C][C]80[/C][C]-0.57[/C][C]22[/C][C]67[/C][C]-0.51[/C][/ROW]
[ROW][C]25[/C][C]-0.42[/C][C]28[/C][C]103[/C][C]-0.57[/C][C]28[/C][C]71[/C][C]-0.43[/C][/ROW]
[ROW][C]26[/C][C]0.19[/C][C]65[/C][C]32[/C][C]0.34[/C][C]65[/C][C]29[/C][C]0.38[/C][/ROW]
[ROW][C]27[/C][C]-0.3[/C][C]47[/C][C]101[/C][C]-0.36[/C][C]47[/C][C]73[/C][C]-0.22[/C][/ROW]
[ROW][C]28[/C][C]-0.08[/C][C]50[/C][C]65[/C][C]-0.13[/C][C]50[/C][C]51[/C][C]-0.01[/C][/ROW]
[ROW][C]29[/C][C]-0.44[/C][C]11[/C][C]89[/C][C]-0.78[/C][C]11[/C][C]72[/C][C]-0.73[/C][/ROW]
[ROW][C]30[/C][C]-0.34[/C][C]18[/C][C]79[/C][C]-0.63[/C][C]18[/C][C]70[/C][C]-0.59[/C][/ROW]
[ROW][C]31[/C][C]-0.37[/C][C]28[/C][C]94[/C][C]-0.54[/C][C]28[/C][C]68[/C][C]-0.42[/C][/ROW]
[ROW][C]32[/C][C]0.16[/C][C]63[/C][C]35[/C][C]0.29[/C][C]63[/C][C]33[/C][C]0.31[/C][/ROW]
[ROW][C]33[/C][C]0.12[/C][C]66[/C][C]44[/C][C]0.2[/C][C]66[/C][C]36[/C][C]0.29[/C][/ROW]
[ROW][C]34[/C][C]-0.24[/C][C]25[/C][C]67[/C][C]-0.46[/C][C]25[/C][C]49[/C][C]-0.32[/C][/ROW]
[ROW][C]35[/C][C]0.2[/C][C]67[/C][C]32[/C][C]0.35[/C][C]67[/C][C]29[/C][C]0.4[/C][/ROW]
[ROW][C]36[/C][C]0.17[/C][C]56[/C][C]26[/C][C]0.37[/C][C]56[/C][C]22[/C][C]0.44[/C][/ROW]
[ROW][C]37[/C][C]-0.09[/C][C]32[/C][C]48[/C][C]-0.2[/C][C]32[/C][C]42[/C][C]-0.14[/C][/ROW]
[ROW][C]38[/C][C]-0.14[/C][C]27[/C][C]52[/C][C]-0.32[/C][C]27[/C][C]49[/C][C]-0.29[/C][/ROW]
[ROW][C]39[/C][C]-0.79[/C][C]17[/C][C]158[/C][C]-0.81[/C][C]17[/C][C]111[/C][C]-0.73[/C][/ROW]
[ROW][C]40[/C][C]-0.07[/C][C]36[/C][C]49[/C][C]-0.15[/C][C]36[/C][C]39[/C][C]-0.04[/C][/ROW]
[ROW][C]41[/C][C]-0.1[/C][C]41[/C][C]58[/C][C]-0.17[/C][C]41[/C][C]50[/C][C]-0.1[/C][/ROW]
[ROW][C]42[/C][C]-0.21[/C][C]42[/C][C]80[/C][C]-0.31[/C][C]42[/C][C]59[/C][C]-0.17[/C][/ROW]
[ROW][C]43[/C][C]-0.22[/C][C]45[/C][C]84[/C][C]-0.3[/C][C]45[/C][C]64[/C][C]-0.17[/C][/ROW]
[ROW][C]44[/C][C]-0.04[/C][C]40[/C][C]47[/C][C]-0.08[/C][C]40[/C][C]41[/C][C]-0.01[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308606&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308606&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	-0.22	25	65	-0.44	25	47	-0.31
2	-0.32	29	86	-0.5	29	64	-0.38
3	-0.06	36	47	-0.13	36	40	-0.05
4	-0.49	19	107	-0.7	19	83	-0.63
5	-0.35	14	76	-0.69	14	59	-0.62
6	-0.31	30	85	-0.48	30	57	-0.31
7	-0.45	38	118	-0.51	38	80	-0.36
8	-0.37	31	96	-0.51	31	75	-0.42
9	-1.43	7	262	-0.95	7	149	-0.91
10	-0.82	7	153	-0.91	7	112	-0.88
11	-0.76	4	139	-0.94	4	106	-0.93
12	-0.78	7	146	-0.91	7	103	-0.87
13	-0.92	5	168	-0.94	5	119	-0.92
14	-0.64	7	121	-0.89	7	88	-0.85
15	-0.54	15	111	-0.76	15	87	-0.71
16	-0.78	7	146	-0.91	7	102	-0.87
17	-0.79	9	149	-0.89	9	109	-0.85
18	-0.25	24	68	-0.48	24	55	-0.39
19	-0.29	19	70	-0.57	19	57	-0.5
20	-0.38	48	115	-0.41	48	66	-0.16
21	-0.16	42	71	-0.26	42	49	-0.08
22	-0.42	33	108	-0.53	33	71	-0.37
23	-0.51	23	114	-0.66	23	80	-0.55
24	-0.33	22	80	-0.57	22	67	-0.51
25	-0.42	28	103	-0.57	28	71	-0.43
26	0.19	65	32	0.34	65	29	0.38
27	-0.3	47	101	-0.36	47	73	-0.22
28	-0.08	50	65	-0.13	50	51	-0.01
29	-0.44	11	89	-0.78	11	72	-0.73
30	-0.34	18	79	-0.63	18	70	-0.59
31	-0.37	28	94	-0.54	28	68	-0.42
32	0.16	63	35	0.29	63	33	0.31
33	0.12	66	44	0.2	66	36	0.29
34	-0.24	25	67	-0.46	25	49	-0.32
35	0.2	67	32	0.35	67	29	0.4
36	0.17	56	26	0.37	56	22	0.44
37	-0.09	32	48	-0.2	32	42	-0.14
38	-0.14	27	52	-0.32	27	49	-0.29
39	-0.79	17	158	-0.81	17	111	-0.73
40	-0.07	36	49	-0.15	36	39	-0.04
41	-0.1	41	58	-0.17	41	50	-0.1
42	-0.21	42	80	-0.31	42	59	-0.17
43	-0.22	45	84	-0.3	45	64	-0.17
44	-0.04	40	47	-0.08	40	41	-0.01

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.912 (0)	0.913 (0)
(Ps-Ns)/(Ps+Ns)	0.912 (0)	1 (0)	0.991 (0)
(Pc-Nc)/(Pc+Nc)	0.913 (0)	0.991 (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) & 0.912 (0) & 0.913 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.912 (0) & 1 (0) & 0.991 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.913 (0) & 0.991 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308606&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]0.912 (0)[/C][C]0.913 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.912 (0)[/C][C]1 (0)[/C][C]0.991 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.913 (0)[/C][C]0.991 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308606&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308606&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)	0.912 (0)	0.913 (0)
(Ps-Ns)/(Ps+Ns)	0.912 (0)	1 (0)	0.991 (0)
(Pc-Nc)/(Pc+Nc)	0.913 (0)	0.991 (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)	0.858 (0)	0.813 (0)
(Ps-Ns)/(Ps+Ns)	0.858 (0)	1 (0)	0.954 (0)
(Pc-Nc)/(Pc+Nc)	0.813 (0)	0.954 (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) & 0.858 (0) & 0.813 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.858 (0) & 1 (0) & 0.954 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.813 (0) & 0.954 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308606&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]0.858 (0)[/C][C]0.813 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.858 (0)[/C][C]1 (0)[/C][C]0.954 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.813 (0)[/C][C]0.954 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=308606&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308606&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)	0.858 (0)	0.813 (0)
(Ps-Ns)/(Ps+Ns)	0.858 (0)	1 (0)	0.954 (0)
(Pc-Nc)/(Pc+Nc)	0.813 (0)	0.954 (0)	1 (0)

Parameters (Session):

par1 = 10 ; par2 = white ; par3 = TRUE ; par4 = Unknown ;

Parameters (R input):

par1 = 4 ;

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

par1 <- '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