Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

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

Mon, 05 Apr 2010 12:09:34 +0000

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/2010/Apr/05/t12704711313zop8wocl6m9qxl.htm/, Retrieved Wed, 24 Apr 2024 19:04:08 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=74592, Retrieved Wed, 24 Apr 2024 19:04:08 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

Academic Motivation Scale : Vallerand, R. J., Pelletier, L. G., Blais, M. R., Briere, N. M., Senecal, C., & Vallieres, E. F. (1992). The Academic Motivation Scale: A measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 52, 1003-1017.

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 1] [2008-09-07 11:33:54] [b98453cac15ba1066b407e146608df68]
- RMPD    [Survey Scores] [AMS] [2010-04-05 12:09:34] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

7	5	6	4	3	4	6	7	5	7	4	2	5	6	7	6	6	4	2	6	6	7	5	6	5	2	5	6
3	7	6	3	1	6	6	6	7	7	6	1	5	4	5	7	7	5	1	6	6	5	7	6	5	1	7	7
6	7	7	2	1	5	3	7	6	7	3	1	4	3	7	7	7	4	1	7	6	7	7	7	5	1	6	4
5	6	7	3	2	5	1	6	6	7	4	2	4	4	6	5	7	3	1	5	5	7	6	6	3	1	5	6
2	5	6	1	1	2	3	6	2	7	1	1	3	1	3	2	5	1	1	2	1	4	6	7	1	1	1	3
2	6	3	4	2	6	6	5	6	5	5	3	6	4	4	6	5	3	2	4	3	4	6	6	4	1	4	5
5	6	4	2	1	6	7	7	5	6	5	4	6	2	5	6	6	4	1	4	3	6	6	6	4	1	5	7
6	6	6	4	1	5	7	7	5	6	3	1	6	2	6	6	3	3	1	6	5	7	6	6	3	1	4	6
4	6	6	3	1	6	6	5	6	6	4	1	5	4	6	6	6	3	1	5	6	6	6	5	3	1	6	6
5	3	6	5	1	2	7	6	2	6	2	1	5	5	7	6	6	1	1	5	6	7	6	6	2	1	5	7
1	4	5	2	1	2	5	1	5	5	5	1	5	2	3	5	5	2	1	3	4	2	6	6	2	1	3	4
6	5	6	3	2	2	6	3	4	6	2	2	5	5	6	6	5	2	1	4	5	5	5	6	3	1	4	6
7	7	3	1	1	4	7	7	7	7	1	1	5	4	7	7	4	1	1	4	7	7	7	5	1	1	7	7
5	7	6	4	1	6	4	6	6	7	3	2	5	3	5	6	6	4	1	6	5	6	6	6	4	1	6	4
5	3	6	1	1	2	7	6	5	5	1	1	3	5	5	3	5	2	1	5	5	5	4	5	4	1	3	5
5	6	7	4	1	5	6	7	6	7	5	5	6	6	7	6	7	5	1	6	5	5	5	6	4	1	6	6
6	6	7	2	1	4	5	7	6	7	3	1	5	5	6	6	5	2	1	5	1	5	5	6	4	1	4	4
3	6	4	5	1	5	7	6	3	4	3	1	4	2	3	4	6	4	1	3	6	6	7	7	4	1	4	5
6	5	7	4	1	4	5	7	6	7	5	1	4	4	6	6	7	5	1	5	4	6	7	7	5	1	5	5
4	5	6	3	1	3	5	6	6	6	4	2	3	4	5	5	6	5	1	6	6	6	6	7	6	1	5	6
2	5	6	3	1	2	7	7	5	7	3	1	5	3	6	6	6	3	1	5	5	6	4	5	4	1	5	6
5	7	7	6	1	7	5	7	7	7	5	1	7	7	7	7	7	4	1	7	7	7	7	7	5	1	7	5
5	6	6	4	1	5	7	6	5	6	5	1	4	5	5	5	6	4	1	6	6	6	6	7	4	1	4	7
4	5	7	6	1	5	5	5	5	6	5	1	5	4	4	4	5	4	1	4	4	4	7	NA	4	1	5	4
7	7	7	7	1	7	7	5	7	7	7	1	7	5	5	7	7	7	1	7	4	5	7	7	7	1	7	7
5	5	6	5	1	5	4	6	5	7	1	1	3	4	7	6	5	1	1	4	2	7	7	7	4	1	2	3
4	7	7	2	1	3	7	7	3	7	3	1	3	2	6	4	7	3	1	3	7	7	7	7	3	1	3	7
5	6	6	4	1	1	5	6	6	6	4	1	2	5	6	4	5	4	1	3	5	6	6	4	4	1	4	6
4	6	7	3	1	4	6	5	5	7	5	1	4	4	7	7	6	4	1	4	5	6	6	7	4	1	4	4
6	5	6	6	3	3	6	7	4	6	1	4	5	6	7	5	6	2	1	5	5	7	6	6	4	2	5	6
7	4	7	3	1	3	5	7	2	7	2	1	4	3	7	5	6	3	1	2	5	7	7	6	3	1	3	6
5	4	7	3	1	6	6	6	5	6	4	2	6	3	7	5	6	2	1	6	6	6	6	6	2	1	6	6
5	4	5	5	2	3	3	7	4	7	3	1	3	5	7	6	6	2	1	3	5	7	6	6	3	1	5	4
6	6	5	4	2	2	1	1	3	1	1	1	6	5	7	6	5	2	3	5	6	7	5	6	4	2	4	5
5	5	7	4	1	4	6	6	6	7	4	1	5	5	5	7	6	4	1	5	4	4	7	7	5	1	6	6
6	6	7	4	1	5	6	7	4	6	3	1	6	4	6	7	7	4	1	6	3	7	6	6	4	1	5	6
6	6	5	5	1	5	7	7	6	7	5	2	6	7	7	7	7	6	1	6	7	7	7	7	5	1	5	7
6	3	6	2	1	3	4	6	5	6	4	1	4	6	7	6	6	3	1	2	6	6	5	6	2	1	3	6
5	4	7	1	1	3	5	7	2	3	1	1	4	6	7	4	6	1	1	4	3	7	5	6	1	1	2	4
5	7	6	1	1	6	6	6	6	3	6	1	6	1	5	6	5	4	1	5	2	3	6	7	3	1	5	6
6	6	7	5	1	6	7	7	5	7	3	1	6	7	7	6	7	1	1	5	7	7	7	7	2	1	6	7
6	6	7	5	1	6	6	7	6	7	4	3	6	7	7	6	7	3	1	6	7	7	5	7	7	1	5	7
3	5	6	4	3	4	6	7	7	7	1	4	5	6	7	5	3	2	2	6	5	6	6	6	2	2	4	5
4	7	7	7	1	4	6	5	7	6	5	1	4	5	5	6	6	5	1	6	6	5	7	7	6	1	7	6
5	5	6	4	1	4	6	5	5	5	4	1	5	5	5	5	5	4	1	5	6	6	6	6	4	1	6	6
6	6	7	3	1	5	7	7	4	7	2	1	4	2	5	6	6	2	1	2	2	6	6	6	2	1	4	7
3	3	5	4	1	3	6	6	2	4	2	5	5	2	6	3	2	2	2	3	4	6	3	4	4	2	2	6
2	4	6	4	2	2	4	7	6	6	4	3	3	1	2	3	5	3	4	4	2	5	5	5	4	2	3	3
5	4	5	2	1	3	7	7	3	6	3	4	6	6	6	3	6	2	1	4	6	6	5	6	2	1	6	7
6	6	6	4	1	4	6	7	6	6	4	2	4	4	6	6	6	3	1	5	5	7	6	6	4	1	NA	5
6	5	6	4	1	7	5	7	7	6	3	2	6	6	6	6	4	4	1	5	4	7	7	6	5	1	6	6
6	6	7	5	1	6	6	6	5	7	4	1	6	6	6	5	6	5	1	6	6	6	5	6	5	1	6	6
4	5	7	5	1	4	6	5	5	5	4	1	6	6	6	5	4	4	1	6	6	5	4	7	4	1	4	6
3	7	7	6	1	6	6	5	7	7	7	2	5	3	2	6	6	7	1	6	5	2	7	2	7	1	5	5
2	7	6	2	1	5	6	6	6	NA	4	2	5	5	5	5	5	2	1	5	6	6	6	6	4	1	7	7
5	5	4	3	1	5	6	7	5	5	5	2	5	6	7	5	4	4	1	5	7	7	7	7	6	1	5	7
2	5	6	4	1	6	6	5	6	5	3	1	5	5	5	5	6	3	1	5	6	6	5	7	4	1	6	6
5	4	7	2	1	2	6	6	4	7	1	1	2	4	6	1	6	1	1	3	3	6	4	6	1	1	2	2
4	5	6	2	1	4	7	6	3	6	2	1	3	6	7	5	6	2	1	4	6	7	4	6	2	1	4	6
4	7	6	3	1	7	7	7	5	5	5	1	7	4	4	5	6	5	1	7	5	6	5	7	5	1	7	7
4	5	6	4	1	5	5	2	5	7	3	2	4	4	4	6	6	3	1	6	5	5	6	7	3	1	5	5
7	5	7	3	1	1	7	7	3	7	5	1	4	7	7	7	7	7	1	5	7	7	7	7	7	1	7	7
5	5	5	6	1	5	7	6	6	7	4	2	6	6	7	6	7	4	1	6	6	6	5	7	5	1	6	7
5	7	3	5	2	6	5	5	6	4	3	2	5	5	6	5	5	3	2	4	7	5	6	5	5	1	5	6
5	6	7	3	1	2	6	6	5	6	4	1	4	5	6	6	6	4	1	5	6	6	6	7	5	1	5	6
6	6	7	4	1	4	6	6	5	7	4	1	4	7	5	6	6	3	1	6	5	6	6	6	4	1	5	6
3	6	7	4	1	3	6	6	4	7	5	1	5	5	4	6	6	3	1	3	5	5	5	5	3	1	6	6
5	5	6	4	1	4	6	5	5	5	4	1	5	5	5	5	5	4	1	5	6	6	6	6	4	1	6	6
7	6	7	3	1	1	7	7	4	5	5	1	4	4	7	5	5	4	1	6	4	7	5	6	6	1	6	6
7	6	6	3	1	5	6	7	5	6	4	1	5	3	4	4	5	2	1	5	4	6	6	7	3	1	5	6
4	3	6	3	1	2	6	7	4	6	2	1	5	4	5	4	6	2	1	5	6	7	7	6	4	1	6	6
7	4	1	2	1	7	7	7	7	7	1	1	7	7	7	7	7	1	1	4	7	7	7	7	1	1	7	7
6	3	4	3	1	5	7	6	3	7	2	2	5	4	5	3	6	2	1	6	5	5	5	4	3	1	5	7
2	7	5	5	1	2	1	1	7	5	7	1	1	1	1	7	4	6	1	3	1	1	6	4	3	1	1	1
5	4	7	4	1	5	7	6	4	7	5	1	4	6	6	4	6	4	1	6	6	6	5	6	4	1	5	6
3	6	6	4	1	6	6	5	5	6	2	1	6	5	3	5	5	1	1	4	6	3	6	2	3	1	6	7
5	7	7	5	1	5	6	6	6	6	5	1	6	6	6	6	6	5	1	6	6	6	6	6	5	1	6	6
6	4	6	5	2	5	7	6	4	6	3	1	5	7	7	4	6	3	1	4	6	6	5	5	6	1	6	7
6	5	7	4	1	5	6	7	5	7	4	1	5	6	7	6	7	4	1	5	5	6	5	6	4	1	6	6
4	5	7	3	1	6	4	3	5	7	6	1	6	2	5	6	6	4	1	5	3	5	7	7	5	1	6	4
4	5	6	3	1	6	6	6	5	7	3	3	5	1	4	5	5	4	1	4	3	4	4	5	2	1	3	5
5	4	6	4	1	3	5	7	4	7	3	3	3	4	7	4	5	3	1	5	3	7	4	7	4	2	5	5
5	6	6	6	1	5	6	7	7	6	6	1	6	6	7	7	6	6	1	6	6	6	6	5	6	1	5	6
5	4	6	4	1	4	5	7	4	5	4	1	6	4	5	5	3	3	1	4	3	6	5	6	6	1	4	5
4	6	6	4	2	NA	6	5	6	6	4	3	6	4	3	6	4	2	1	6	5	6	6	6	2	1	5	6
5	6	5	5	2	NA	4	5	5	5	4	2	5	5	5	5	5	3	1	5	3	5	5	5	4	1	4	4
6	7	7	4	1	5	7	7	7	7	5	1	5	6	6	7	4	4	1	5	7	6	7	5	3	1	6	7
5	7	6	5	1	6	5	6	6	6	3	1	5	5	6	5	5	4	1	6	5	5	5	6	5	1	5	5
6	5	6	1	2	2	5	6	2	6	2	4	3	6	6	5	6	1	1	4	4	6	5	2	2	1	4	5
5	4	6	4	1	3	5	5	3	6	3	4	3	4	6	4	5	3	1	2	3	5	5	5	2	1	4	5
5	6	7	3	4	3	6	5	4	6	2	6	5	5	4	5	5	3	2	5	7	5	6	6	4	3	5	5
4	3	5	4	6	3	5	5	2	6	1	6	4	3	5	3	5	1	4	4	4	5	3	5	4	3	4	4
3	5	6	3	1	3	6	5	4	6	3	3	4	3	5	5	5	3	1	3	4	5	5	5	4	2	4	5
6	5	6	5	NA	4	7	7	6	6	4	1	5	4	5	6	6	4	1	4	6	6	5	6	4	1	5	7
5	6	4	6	1	6	7	5	6	6	4	4	6	3	6	6	5	6	1	6	4	6	6	5	5	1	6	7
5	6	6	5	1	6	6	6	6	6	4	2	6	5	7	6	6	4	1	6	6	6	6	7	4	1	6	6
6	5	6	5	2	4	6	6	4	5	3	1	4	5	7	5	6	3	1	5	5	6	4	5	5	1	5	7
4	5	5	4	2	3	6	7	4	5	4	1	4	6	6	6	7	4	2	3	5	6	7	6	4	1	3	6
3	3	7	5	1	4	7	7	4	7	3	1	5	5	7	6	7	3	1	6	6	7	6	6	5	1	6	7
5	5	7	6	2	5	5	6	6	6	4	2	6	2	4	6	7	5	1	5	4	6	7	7	5	1	4	5
6	3	6	2	1	4	4	5	4	5	3	1	4	4	5	4	5	2	1	5	3	5	5	6	4	1	4	4
4	5	7	5	1	1	5	6	3	6	3	1	2	2	4	4	6	2	1	4	3	5	6	6	6	1	5	5
5	5	7	4	2	5	6	6	5	6	2	1	2	4	7	5	5	4	1	6	5	6	7	6	5	1	4	5
5	5	6	4	2	4	5	6	5	6	3	4	5	5	6	5	6	4	3	4	5	6	6	6	5	2	4	5
7	5	7	5	1	4	7	7	5	7	3	1	5	6	7	6	6	3	1	6	6	7	7	7	7	1	7	7
6	4	6	5	2	4	6	5	4	5	3	2	5	4	5	4	6	3	2	4	5	5	5	6	4	2	4	5
4	4	6	3	1	4	5	5	4	6	3	1	4	3	5	4	6	3	1	4	5	5	4	6	3	1	3	4
5	6	7	5	1	4	7	6	6	6	5	1	4	6	6	5	6	5	2	6	6	6	6	6	5	1	6	6
6	5	7	5	2	5	5	6	5	6	4	2	6	6	6	5	6	5	2	6	5	7	6	6	5	2	5	6
5	5	7	4	1	5	7	5	6	7	3	1	5	5	5	6	5	3	1	5	4	5	5	6	5	1	5	6
4	5	5	5	2	3	6	5	6	6	6	3	6	3	6	6	5	5	3	5	4	6	6	6	5	2	5	5
7	6	6	4	2	5	7	6	5	6	5	1	5	6	6	5	6	5	1	5	6	6	5	5	5	1	5	7
6	4	7	2	1	4	6	7	5	7	2	1	5	6	7	4	7	1	1	6	6	6	6	7	2	1	6	7
4	3	6	4	3	4	5	7	5	5	4	4	5	6	5	5	5	3	2	4	NA	7	5	5	4	3	5	5
4	3	5	4	1	4	6	6	4	6	4	1	5	5	7	4	5	3	1	4	4	6	5	6	4	1	5	6
2	5	2	4	1	5	6	2	6	7	5	1	7	1	4	6	7	5	1	6	7	1	6	7	5	1	6	7
6	6	7	6	2	5	6	6	7	7	5	2	5	4	7	6	7	4	1	6	6	7	6	6	6	1	7	7
6	7	7	7	1	6	7	7	7	6	4	1	5	5	7	7	7	4	1	5	6	7	7	7	7	1	6	7
7	7	7	6	1	5	7	5	4	7	4	1	6	5	5	6	6	1	1	3	6	6	6	6	3	1	2	6
7	7	6	5	1	7	4	7	6	7	6	1	7	6	7	7	7	5	1	6	6	7	7	7	6	1	6	7
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	5
4	4	5	3	1	2	4	5	5	6	3	1	3	4	4	4	4	3	1	3	4	5	6	7	3	1	4	5
5	5	6	6	1	5	6	6	6	6	6	1	6	1	4	4	4	4	1	4	3	6	6	6	2	1	6	4
5	6	6	7	1	6	7	4	6	7	7	1	6	7	7	7	7	6	NA	6	7	5	7	6	6	1	7	7
5	4	6	2	1	4	5	7	4	6	3	4	5	1	7	5	4	2	1	2	2	6	5	7	1	2	2	4
1	4	6	3	1	4	5	7	6	6	3	3	5	4	7	7	7	1	1	4	4	5	6	6	2	1	5	5
6	6	7	4	2	3	6	7	5	6	4	1	5	6	6	7	7	3	1	5	6	6	6	7	4	1	4	6
7	7	7	1	1	7	7	7	4	7	1	1	7	4	7	7	7	1	1	7	7	7	7	7	1	1	7	7
5	3	6	4	6	1	1	5	3	5	1	2	2	2	4	2	5	2	4	2	3	5	2	3	2	2	1	1
6	6	7	4	1	5	7	7	6	7	3	1	5	7	5	6	5	2	1	5	7	6	6	6	4	1	6	7
5	5	4	4	2	4	6	5	5	6	4	2	5	4	6	5	6	4	2	5	4	6	5	7	4	2	6	7
7	5	7	5	1	7	7	7	5	7	4	1	7	4	5	6	7	3	1	7	5	7	4	7	4	1	5	5
4	5	5	5	2	3	6	5	6	7	3	2	5	5	6	5	6	5	1	5	5	5	6	6	5	1	3	5
7	7	7	7	1	4	5	7	7	7	7	1	4	6	7	7	7	7	1	4	5	7	7	7	7	1	4	5
5	5	6	3	2	4	5	5	5	6	2	2	5	4	6	5	6	2	2	4	3	5	5	6	4	2	5	4
5	5	7	5	1	5	6	7	5	6	4	1	6	6	7	6	6	4	1	6	6	7	6	6	6	1	5	6
5	5	5	3	2	4	5	6	6	6	3	2	5	5	5	5	5	3	1	5	5	5	5	5	4	6	NA	6
5	6	5	6	1	5	6	7	6	7	4	1	6	6	6	6	5	3	1	5	6	6	6	6	4	1	5	6
7	7	7	7	1	7	7	7	7	7	7	7	7	7	7	6	7	7	1	7	7	7	7	7	7	1	7	7
6	4	6	5	2	4	4	5	4	7	4	2	4	3	7	4	5	3	1	3	3	6	5	6	3	2	4	3
1	7	7	4	1	4	4	5	5	7	5	1	5	2	2	2	6	4	1	4	1	1	7	7	4	1	4	1
1	3	1	5	7	5	2	1	3	1	3	7	4	5	2	4	2	4	7	4	3	1	3	5	4	7	4	3
4	3	5	2	1	5	6	7	2	6	3	1	4	5	7	2	6	3	1	6	6	7	4	6	2	1	4	6
5	6	6	6	2	5	6	6	5	5	4	2	5	6	6	5	6	5	2	5	6	6	5	6	5	2	5	5
5	4	5	2	4	5	5	5	4	5	3	2	5	5	6	5	5	NA	3	5	6	6	5	5	5	1	4	6
6	6	7	4	1	4	6	7	6	6	4	1	4	4	7	6	6	4	1	4	5	6	6	6	5	1	5	6
5	5	6	6	1	4	7	6	5	5	3	2	5	5	5	5	5	5	1	5	6	6	6	6	5	1	6	6
2	7	5	4	1	5	7	3	6	6	5	1	6	5	6	6	5	4	1	5	6	3	6	6	5	1	6	7
6	6	6	6	1	6	7	7	7	7	5	1	7	6	7	7	7	7	1	5	7	7	7	7	7	1	6	6
2	4	2	6	3	5	3	2	4	3	3	6	4	4	3	4	4	2	4	3	2	3	4	5	3	5	3	4
6	4	6	5	3	4	4	6	5	5	4	3	5	4	6	5	6	4	4	5	5	6	5	6	4	3	5	5
7	6	2	6	1	7	7	7	7	7	7	1	7	4	6	7	7	6	1	6	7	7	5	6	7	1	6	7
5	4	6	3	1	2	6	7	2	6	2	2	4	5	5	4	6	3	4	4	6	7	4	7	3	2	3	5
7	5	6	2	4	4	7	7	5	6	3	5	2	7	7	3	5	2	3	2	6	7	3	6	3	4	6	7
4	7	6	5	1	5	6	7	5	7	4	1	NA	3	7	5	4	4	1	5	4	7	6	5	4	1	6	7
4	7	7	5	1	6	4	4	7	7	5	1	7	3	4	7	7	6	1	6	4	4	7	6	5	1	7	5
3	4	4	3	4	5	4	3	4	5	4	3	4	5	4	4	3	5	4	3	4	5	5	4	5	4	5	5
4	5	5	4	2	3	5	4	4	5	2	2	3	2	3	3	4	3	2	4	2	4	4	4	2	1	3	3
5	7	4	6	1	5	7	7	6	6	7	1	7	5	7	7	7	6	NA	6	5	7	5	7	5	1	5	7
3	6	7	5	1	7	5	5	6	7	6	1	7	4	3	7	7	5	1	6	2	2	7	7	6	1	7	5
6	5	7	4	2	6	7	7	7	7	5	3	6	6	7	7	7	5	2	5	6	7	7	7	5	NA	5	7
5	6	6	5	1	4	6	7	6	6	5	1	4	5	6	6	6	5	1	6	6	6	6	6	5	1	6	6
3	6	6	5	2	6	6	7	6	5	5	3	4	5	5	6	4	4	2	6	6	7	5	6	5	2	5	6
6	5	6	1	1	4	5	6	4	6	3	1	5	5	6	6	6	3	1	6	5	6	5	6	3	1	4	5
6	5	2	3	5	4	5	6	4	5	5	6	4	1	5	4	2	4	5	4	4	6	4	3	3	4	4	4
3	5	5	3	2	5	5	3	5	4	4	2	5	4	3	5	4	4	2	5	4	3	5	4	5	2	5	3
6	4	6	2	2	3	7	6	4	6	NA	3	3	6	7	5	6	3	1	2	5	6	5	7	3	1	3	7
7	5	7	4	3	4	7	7	4	7	4	4	5	7	7	4	7	4	1	4	7	7	5	5	4	1	4	7
7	5	5	2	1	4	6	5	4	6	3	5	3	4	6	4	6	2	2	5	5	7	5	5	2	2	4	6
4	6	6	6	1	5	6	NA	6	6	5	1	5	5	NA	7	6	4	1	6	4	NA	6	7	6	1	6	7
3	7	6	5	3	7	6	5	7	7	7	3	7	5	6	7	7	5	1	6	4	6	7	6	6	1	7	7
5	6	5	4	1	3	5	5	NA	5	3	1	3	4	5	5	NA	2	1	5	5	5	5	5	2	1	5	5
5	5	6	4	2	4	4	6	5	5	5	2	5	4	5	4	6	4	2	3	5	6	5	6	4	2	4	5
5	5	5	3	1	4	6	6	5	6	4	1	5	5	7	4	6	4	1	4	5	6	6	6	4	1	5	6
3	5	6	3	1	5	5	6	5	5	5	3	4	5	5	4	5	3	4	5	5	6	5	6	5	4	5	6
6	6	5	5	1	5	5	6	6	6	5	2	5	6	6	6	6	5	1	5	6	6	6	6	6	1	6	6
7	7	7	7	1	7	7	7	7	7	1	1	7	7	7	7	7	1	1	7	7	NA	7	7	1	1	7	7
7	6	6	3	1	1	5	7	5	7	3	1	1	5	7	5	6	1	1	3	4	7	5	6	1	1	2	4
4	5	5	5	2	4	4	5	5	6	3	4	4	3	5	5	5	5	3	5	3	5	5	5	5	2	5	5
3	6	4	4	2	4	5	4	5	5	5	1	5	3	5	5	4	3	2	3	4	4	5	5	4	2	5	5
5	3	6	2	1	4	6	6	4	7	2	1	4	3	5	3	6	2	1	4	5	6	4	5	2	1	4	5
5	7	7	6	1	4	7	7	7	6	6	1	6	6	7	7	7	6	1	7	6	7	7	6	6	1	7	7
2	4	5	5	1	4	7	5	5	6	5	1	5	5	5	6	5	3	1	7	7	6	6	5	5	1	4	5
1	6	5	3	6	2	7	6	3	1	1	5	6	7	6	2	5	2	1	6	7	5	5	6	1	1	6	7
6	6	7	4	1	5	6	5	6	7	3	1	4	3	5	6	5	2	1	4	5	6	7	7	3	1	4	4
6	5	5	3	1	2	6	6	5	6	2	1	5	4	7	6	6	2	1	5	5	7	5	5	2	1	6	6
2	2	5	1	2	1	1	2	3	4	NA	2	5	1	2	3	5	1	4	1	4	4	5	6	2	1	2	5
5	5	6	6	2	6	6	6	3	6	2	1	4	6	6	5	6	2	2	6	6	6	4	6	2	1	4	6
6	6	4	5	1	3	6	6	6	5	5	2	6	4	1	6	5	5	1	4	5	5	5	5	2	1	2	5
5	7	7	6	1	6	7	7	7	7	3	1	7	7	7	7	7	6	1	5	5	7	7	7	4	1	7	7
3	5	6	4	1	5	5	6	4	5	3	1	4	6	3	5	4	4	2	5	3	4	5	4	3	1	4	4
2	6	7	5	2	5	5	5	5	6	4	1	5	6	6	5	5	5	1	5	3	6	6	6	4	1	5	5
2	5	6	4	1	6	7	4	6	6	3	1	7	4	5	6	4	3	1	7	5	4	6	6	4	1	6	7
3	4	6	6	1	4	4	6	5	7	5	2	6	3	6	6	7	4	1	5	4	6	7	5	4	1	6	5
5	5	6	6	3	3	5	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4	4	6	6	NA	NA	6	NA	6	6	5	5	5	5	6	4	5	3	2	4	4	NA	6	6	6	2	6	6
5	6	6	4	1	6	7	7	4	6	4	1	5	6	5	6	7	4	1	6	6	6	5	6	5	1	5	6
6	5	7	5	1	6	6	6	5	6	2	1	5	NA	5	6	6	2	1	6	6	3	6	6	5	1	6	6
4	5	3	3	1	3	4	4	5	4	3	1	3	4	4	4	5	4	1	4	5	4	5	5	4	1	4	5
6	3	6	4	1	3	6	6	3	6	3	5	3	4	6	3	6	3	5	4	5	6	5	6	3	4	4	5
5	4	6	4	1	4	6	7	4	5	4	1	4	6	7	5	6	4	1	4	5	7	5	6	4	1	4	5
5	6	7	4	2	5	7	6	5	5	4	2	6	5	4	5	5	3	2	6	5	6	5	4	4	2	6	6
6	6	6	4	2	3	5	6	6	6	4	3	2	5	6	6	6	3	3	5	4	6	6	6	2	2	4	6
6	6	7	4	1	5	5	7	5	7	5	1	5	4	6	6	6	4	1	5	5	7	6	6	4	1	5	5
7	4	6	4	2	4	6	7	4	6	4	2	5	5	6	4	4	3	2	4	4	5	5	4	4	3	5	7
6	5	7	2	1	4	6	7	5	6	5	1	6	6	5	5	6	2	1	5	6	6	6	7	5	1	6	6
4	6	6	6	1	6	6	5	6	6	6	1	6	5	6	6	6	6	1	6	6	6	6	6	6	1	6	6
4	6	4	3	4	4	4	4	6	4	3	5	4	3	4	5	4	3	4	4	4	4	5	4	4	3	4	4
7	5	4	4	2	4	6	7	5	6	4	1	6	6	7	5	2	3	1	5	6	7	5	4	3	1	4	5
7	6	6	5	1	5	5	6	6	7	5	1	5	4	6	6	5	6	1	6	4	6	7	6	6	1	6	4
6	6	6	6	2	5	5	6	6	6	6	3	6	6	6	5	6	5	2	6	6	6	6	6	6	2	6	6
5	6	7	4	1	6	5	4	6	6	5	1	2	7	7	7	7	NA	1	1	2	4	7	7	6	1	5	4
6	4	6	3	2	5	5	6	5	6	3	2	6	6	6	4	6	4	2	5	6	6	4	5	4	2	5	6
5	6	5	2	1	1	6	7	3	4	3	3	2	6	6	3	4	1	3	6	4	6	4	4	2	1	6	6
6	6	7	6	1	5	6	7	5	6	5	2	4	6	6	6	7	4	1	4	6	7	5	7	4	1	6	7
5	4	6	4	2	2	6	6	3	6	2	2	2	6	6	2	6	2	2	2	5	5	6	6	3	2	5	6
7	1	1	1	7	2	1	6	1	4	3	7	2	2	6	1	1	1	6	3	1	6	1	5	1	5	1	1
4	5	5	6	3	4	6	6	4	6	NA	4	NA	3	6	4	5	4	5	4	3	6	5	6	4	3	4	3
3	5	6	4	2	4	6	7	6	7	4	2	5	4	6	7	6	4	1	6	5	6	6	7	5	1	5	6
2	5	5	4	5	4	4	4	4	5	2	1	3	4	7	5	5	2	2	4	4	7	5	6	4	1	4	5
4	4	4	4	4	4	4	4	5	3	5	1	4	4	4	4	4	4	4	4	4	4	4	4	4	1	4	5
7	7	7	6	1	4	7	7	4	7	4	1	4	4	7	7	7	4	1	4	4	7	7	7	4	1	4	4
5	5	6	4	1	3	5	5	5	5	4	2	5	3	4	5	6	3	2	5	3	4	6	6	5	1	3	6
4	7	5	6	1	6	7	5	7	5	4	1	5	5	4	7	6	4	1	4	7	5	6	6	5	1	5	7
6	4	5	4	6	4	4	6	5	5	4	2	4	3	5	5	5	3	2	5	4	5	5	6	4	2	4	5
5	5	5	2	2	4	5	5	5	5	4	2	4	4	6	6	4	3	2	5	5	5	5	5	4	2	3	5
5	5	5	4	2	3	3	5	4	4	3	2	4	4	4	4	3	3	2	5	5	4	4	5	4	2	5	5
2	2	6	4	5	5	7	1	3	3	5	3	1	7	4	2	2	2	7	2	4	2	6	2	2	6	5	2
5	5	5	5	1	5	6	7	5	6	5	1	6	4	7	5	6	5	1	5	4	5	6	6	4	1	5	6
4	5	5	6	3	5	6	5	5	6	5	3	6	4	5	5	7	4	2	4	3	5	5	7	5	2	5	5
6	5	6	5	2	5	5	6	4	5	4	5	6	4	7	5	6	4	6	5	4	6	5	5	4	5	6	5
7	3	4	2	2	3	5	7	2	5	2	3	2	5	6	3	4	2	2	2	5	6	4	4	2	2	3	4
4	5	7	1	1	5	6	7	4	7	4	1	5	2	6	4	6	3	1	3	5	7	4	6	4	1	2	5
5	5	6	4	3	3	3	5	5	5	4	2	3	5	6	5	5	4	3	4	4	5	4	5	3	3	4	4
4	5	4	3	5	4	5	4	5	4	3	5	4	4	6	3	4	5	4	4	4	3	5	3	4	4	3	5
5	5	6	3	3	3	5	6	5	6	4	3	3	5	6	5	6	4	3	5	5	6	6	5	3	2	4	5
6	6	7	4	1	5	7	6	6	7	4	1	6	5	6	6	7	4	1	5	5	6	6	6	4	1	5	7
6	6	5	6	2	3	2	5	6	5	6	2	5	6	6	5	6	5	3	5	6	6	7	5	7	2	6	6
5	7	7	6	1	6	6	4	6	6	5	1	7	1	2	5	4	4	1	7	2	4	6	5	4	1	7	3
2	6	6	6	2	3	6	7	4	6	4	2	4	4	7	5	6	4	2	4	5	6	6	5	4	1	4	6
7	5	3	4	5	4	6	6	3	5	5	2	2	2	5	5	2	4	2	2	2	6	4	5	5	2	3	5
7	7	7	7	1	4	7	7	7	7	7	1	4	7	7	7	7	7	1	7	7	7	7	7	7	1	7	7
5	5	5	4	3	5	5	5	5	6	4	2	5	5	6	5	5	4	1	5	6	6	5	6	4	2	5	6
5	5	7	2	1	5	5	5	3	7	3	1	4	1	3	5	4	3	1	2	3	7	5	4	2	1	3	4
3	4	3	4	1	4	7	7	4	5	5	4	3	4	3	5	7	2	1	6	3	4	6	1	7	2	5	7
2	3	4	5	1	6	6	4	4	3	3	1	7	2	3	5	2	3	1	2	3	4	4	1	3	1	3	4
1	5	5	4	1	3	5	2	4	6	2	1	2	2	3	3	4	4	1	2	2	3	3	3	1	1	4	3
4	4	3	4	4	3	3	3	4	3	5	3	3	4	4	3	4	3	4	4	4	3	3	4	5	4	4	3
2	5	5	4	3	4	7	5	5	4	5	3	5	3	5	4	4	4	4	4	4	4	4	4	4	4	NA	4
3	6	3	6	3	5	3	5	2	5	2	5	5	3	5	2	5	3	5	3	5	3	5	3	2	5	3	5
5	5	4	3	2	5	7	5	5	4	5	3	5	3	5	5	5	5	4	5	6	5	3	5	5	2	5	6
3	5	6	5	1	5	6	7	6	6	4	1	3	4	7	6	6	5	1	4	2	6	6	7	5	1	5	2
NA	5	6	5	7	4	4	7	6	6	5	6	4	7	6	5	5	6	6	5	7	6	5	6	5	6	5	5
6	3	7	1	1	2	3	4	3	7	2	1	3	1	4	3	3	1	1	3	3	NA	5	7	3	1	3	1
6	5	5	2	2	4	6	6	4	5	2	1	4	5	5	5	5	4	1	5	5	6	4	4	3	1	4	4
6	7	7	5	1	6	6	7	6	6	5	1	7	5	6	6	7	4	1	5	6	6	6	7	5	1	6	7
3	5	5	5	2	5	5	4	5	5	2	1	5	3	4	5	5	2	4	4	2	5	5	7	4	1	4	3
6	2	5	2	2	1	7	7	2	4	1	4	2	6	7	3	6	2	1	5	6	7	2	7	1	1	3	7
5	5	6	4	2	4	5	5	6	6	4	3	4	3	5	4	4	4	2	5	5	5	6	5	4	2	5	5
2	3	7	2	1	4	7	7	4	7	2	1	1	1	7	1	5	2	1	1	1	7	6	7	2	1	6	7
7	4	7	4	3	1	7	7	2	7	2	3	4	5	7	2	7	2	2	3	6	7	4	6	3	1	5	7
3	4	2	2	3	3	6	6	6	6	3	5	5	3	6	6	7	3	3	5	6	6	7	3	2	2	6	6
5	5	7	4	1	5	6	7	5	6	5	1	5	4	6	6	6	5	3	6	3	7	6	6	5	1	6	6
6	4	3	1	1	5	7	7	2	6	1	1	7	5	6	5	6	3	2	6	7	6	4	5	2	2	5	6
5	5	6	3	1	5	5	7	5	7	5	1	5	4	6	5	6	5	1	5	5	6	5	6	5	1	4	5
5	5	5	4	2	4	4	5	5	5	4	1	5	3	5	5	5	4	1	5	2	5	5	5	4	1	4	2
3	4	3	4	4	5	4	4	3	4	4	3	3	3	4	3	4	4	4	3	3	2	3	5	3	4	3	3
5	5	7	2	4	2	4	7	4	2	2	5	2	2	7	4	7	2	1	7	5	7	4	4	4	4	4	4
4	4	6	3	1	2	6	6	4	6	2	1	4	3	5	5	5	2	1	4	3	5	5	7	3	1	4	4
5	5	7	6	1	4	6	6	5	6	6	2	5	5	7	6	6	5	1	5	5	6	7	6	6	1	5	5
7	6	7	6	1	6	7	6	6	6	5	1	6	6	6	6	6	6	1	6	6	6	6	6	6	1	6	7
5	3	5	3	1	4	5	6	4	4	2	1	5	5	5	5	5	3	1	5	4	6	4	5	2	1	5	6
5	5	5	4	5	3	6	5	3	5	2	3	4	2	5	4	5	4	2	4	3	5	5	5	5	2	4	6
5	5	6	2	1	5	6	5	4	5	4	2	4	1	4	4	5	3	1	4	2	4	5	5	2	1	3	4
6	5	6	3	1	5	7	6	4	6	3	4	3	4	5	5	6	2	1	2	5	6	5	5	1	2	3	5
4	4	5	5	5	5	5	5	5	5	5	5	5	5	5	4	4	4	4	5	5	5	5	5	5	5	5	5
6	6	5	2	1	5	7	6	6	6	4	1	5	6	5	5	4	1	1	6	5	5	5	6	4	1	6	7
5	5	5	5	1	5	5	5	5	5	4	2	5	5	5	5	5	3	1	5	5	5	5	3	4	1	5	5
7	7	7	7	1	7	7	7	7	7	6	1	7	6	5	7	6	6	1	6	2	7	7	6	6	1	NA	7
7	7	7	4	1	4	5	7	7	7	5	1	4	3	7	7	7	5	1	5	4	7	7	7	4	1	4	4
5	7	6	4	1	5	5	5	6	6	6	2	6	4	6	7	6	6	1	6	5	5	7	6	6	2	6	6
1	6	5	4	1	7	7	6	4	4	2	1	5	2	2	5	5	2	1	5	6	3	4	5	2	1	6	6
3	2	6	5	1	3	6	5	6	6	4	3	6	6	4	4	4	4	1	6	5	4	5	6	5	1	6	6
4	5	5	3	2	3	6	6	4	5	5	4	6	3	6	6	5	4	2	6	6	5	5	5	4	2	6	6
4	4	3	5	3	NA	4	4	6	4	3	4	5	3	4	4	4	3	3	5	4	4	5	4	3	3	4	4
3	5	5	5	2	5	5	4	4	6	4	2	4	4	6	5	5	4	1	4	4	6	5	4	4	1	4	4
6	6	5	5	1	5	5	NA	NA	NA	NA	NA	NA	NA	6	5	6	4	1	6	6	6	6	6	4	1	5	6
4	7	7	6	1	4	6	6	7	6	7	1	7	5	5	7	6	6	1	7	6	5	6	7	6	1	7	6
5	5	6	4	2	4	5	6	4	5	4	1	5	5	5	5	6	5	1	5	5	6	5	5	4	1	4	5
4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	NA	NA	3	5	6	3	2	4	NA	7	1
1	6	6	2	1	7	7	6	4	6	2	1	5	2	2	4	1	1	1	7	1	4	4	6	4	1	NA	6
5	5	5	4	3	3	5	5	4	5	3	5	4	4	5	4	5	4	5	4	5	5	4	4	4	2	4	4
3	6	6	5	1	6	6	5	7	6	5	1	6	4	5	7	6	5	1	6	4	5	6	6	5	1	6	5
2	5	4	2	2	4	5	6	6	6	4	3	4	3	6	6	3	5	2	3	2	5	6	5	5	2	5	3
5	5	6	1	1	4	6	5	4	7	4	1	5	3	5	5	6	3	1	2	3	5	5	7	3	1	4	7
1	4	7	5	1	4	7	6	5	6	4	1	5	5	5	5	6	4	1	5	5	6	5	5	5	1	5	5
7	6	5	6	6	5	6	6	5	6	4	6	5	4	6	5	6	5	4	2	5	6	5	5	5	6	5	6
6	6	7	6	2	6	7	6	6	6	7	6	6	5	6	6	6	7	6	6	6	6	7	6	5	6	6	7
4	5	7	4	1	5	7	6	4	6	5	2	4	6	5	5	6	3	1	4	5	7	6	7	6	1	5	7
5	6	7	4	1	5	7	7	2	7	4	1	5	6	6	5	6	4	1	5	5	6	6	7	5	1	4	6
2	3	4	4	4	4	4	5	4	5	5	4	4	4	5	5	4	4	4	4	5	5	3	5	NA	6	NA	5
5	4	5	2	5	3	3	5	3	5	2	5	2	5	5	3	4	1	2	4	4	5	4	2	2	3	4	5
NA	4	NA	NA	NA	NA	NA	NA	NA	NA	NA	3	NA	NA	NA	NA	3	NA	NA	NA	NA	NA	3	NA	NA	NA	NA	NA
3	4	4	4	5	4	5	4	5	4	5	NA	5	4	5	5	4	4	5	4	5	4	4	5	5	5	4	6
3	6	6	6	2	6	7	6	6	7	5	1	6	6	6	5	6	7	1	6	6	7	6	6	5	1	6	7
5	6	5	4	5	4	4	4	3	3	3	4	NA	4	5	4	4	4	4	5	5	5	4	4	4	5	5	4
3	5	7	5	1	4	7	7	5	7	4	1	5	7	7	4	7	4	1	7	7	7	7	7	4	1	7	7
1	5	6	6	1	5	7	7	5	7	5	1	5	4	5	5	6	4	1	5	6	6	6	6	6	1	5	5
2	3	2	4	4	3	4	4	3	4	3	3	4	3	4	3	3	4	3	4	3	3	3	4	3	3	4	4
7	5	NA	5	6	5	6	5	NA	6	5	NA	4	4	7	6	4	6	6	6	6	7	5	6	5	6	4	4
2	2	3	3	2	3	4	5	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4	4
6	6	6	6	2	5	6	6	6	6	4	2	6	6	5	5	6	3	2	5	6	5	6	6	6	2	5	6
3	7	6	6	1	6	7	5	6	5	4	2	6	4	4	4	5	4	1	5	4	4	5	5	5	1	5	5
7	7	7	5	1	7	7	7	7	7	6	1	7	5	7	7	6	5	1	6	6	6	7	7	6	NA	6	7
1	5	4	6	4	4	5	5	5	5	5	6	5	5	6	4	5	5	5	5	2	5	5	5	5	3	4	4
2	5	6	4	1	5	6	6	5	7	3	2	5	2	6	5	6	4	1	3	1	5	6	6	4	1	5	6
5	5	6	5	6	5	4	5	4	5	5	6	5	4	6	5	5	6	5	4	5	6	5	6	5	5	6	5
7	6	5	5	2	6	6	6	6	7	2	1	6	5	7	7	5	4	1	5	7	7	7	6	2	1	4	6
2	7	1	7	1	5	4	1	7	1	7	4	4	1	1	7	4	6	1	6	4	1	5	4	7	1	7	4
5	7	7	5	1	4	7	7	6	7	5	1	5	5	5	6	5	5	1	6	7	5	5	7	5	1	5	7
5	3	7	4	1	5	7	5	4	7	4	1	5	2	5	4	6	3	1	5	6	6	5	6	4	1	5	6
5	4	6	5	2	5	6	6	5	6	3	1	6	5	6	5	6	3	1	5	5	6	5	6	5	1	5	6
5	5	5	4	1	3	5	5	5	5	4	2	6	6	6	6	6	4	1	5	5	5	5	6	2	1	4	5
4	5	6	5	1	4	7	6	4	6	4	1	5	6	7	5	3	4	1	5	6	7	5	7	4	1	4	6
2	6	4	3	2	5	4	4	6	6	5	2	5	3	5	6	5	5	2	4	3	5	6	5	4	2	6	4
5	5	4	3	4	3	5	5	4	5	3	4	5	5	5	4	4	3	2	4	4	5	4	5	5	3	3	4
2	5	5	4	1	5	6	5	4	5	3	2	4	2	5	5	5	2	1	5	5	5	4	5	3	1	4	6
5	6	7	6	1	3	7	7	3	7	3	5	4	7	7	7	6	3	1	4	7	7	7	7	3	3	6	7
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
7	4	6	2	1	2	6	6	3	6	2	1	6	3	7	2	6	2	1	6	NA	6	2	5	2	1	6	7

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	13 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 13 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74592&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74592&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74592&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	13 seconds
R Server	'George Udny Yule' @ 72.249.76.132

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	0.7	352	121	0.49	208	71	0.49
2	1.16	421	37	0.84	247	30	0.78
3	1.7	593	36	0.89	281	22	0.85
4	0.09	193	164	0.08	126	100	0.12
5	-2.23	34	763	-0.91	21	291	-0.87
6	0.33	230	123	0.3	154	80	0.32
7	1.6	560	32	0.89	275	18	0.88
8	1.73	595	34	0.89	284	17	0.89
9	0.89	349	61	0.7	206	44	0.65
10	1.81	611	22	0.93	290	13	0.91
11	-0.17	146	201	-0.16	104	128	-0.1
12	-1.94	45	679	-0.88	30	271	-0.8
13	0.74	312	73	0.62	201	48	0.61
14	0.4	268	139	0.32	163	82	0.33
15	1.51	532	39	0.86	266	25	0.83
16	1.11	413	50	0.78	237	34	0.75
17	1.43	499	30	0.89	263	19	0.87
18	-0.41	113	247	-0.37	75	149	-0.33
19	-2.32	25	780	-0.94	16	286	-0.89
20	0.72	312	75	0.61	201	50	0.6
21	0.78	350	97	0.57	205	62	0.54
22	1.58	550	37	0.87	273	22	0.85
23	1.43	490	21	0.92	271	16	0.89
24	1.69	576	25	0.92	284	15	0.9
25	0.04	182	169	0.04	123	99	0.11
26	-2.4	26	807	-0.94	17	296	-0.89
27	0.82	325	60	0.69	197	42	0.65
28	1.43	508	40	0.85	257	24	0.83

\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 & 0.7 & 352 & 121 & 0.49 & 208 & 71 & 0.49 \tabularnewline
2 & 1.16 & 421 & 37 & 0.84 & 247 & 30 & 0.78 \tabularnewline
3 & 1.7 & 593 & 36 & 0.89 & 281 & 22 & 0.85 \tabularnewline
4 & 0.09 & 193 & 164 & 0.08 & 126 & 100 & 0.12 \tabularnewline
5 & -2.23 & 34 & 763 & -0.91 & 21 & 291 & -0.87 \tabularnewline
6 & 0.33 & 230 & 123 & 0.3 & 154 & 80 & 0.32 \tabularnewline
7 & 1.6 & 560 & 32 & 0.89 & 275 & 18 & 0.88 \tabularnewline
8 & 1.73 & 595 & 34 & 0.89 & 284 & 17 & 0.89 \tabularnewline
9 & 0.89 & 349 & 61 & 0.7 & 206 & 44 & 0.65 \tabularnewline
10 & 1.81 & 611 & 22 & 0.93 & 290 & 13 & 0.91 \tabularnewline
11 & -0.17 & 146 & 201 & -0.16 & 104 & 128 & -0.1 \tabularnewline
12 & -1.94 & 45 & 679 & -0.88 & 30 & 271 & -0.8 \tabularnewline
13 & 0.74 & 312 & 73 & 0.62 & 201 & 48 & 0.61 \tabularnewline
14 & 0.4 & 268 & 139 & 0.32 & 163 & 82 & 0.33 \tabularnewline
15 & 1.51 & 532 & 39 & 0.86 & 266 & 25 & 0.83 \tabularnewline
16 & 1.11 & 413 & 50 & 0.78 & 237 & 34 & 0.75 \tabularnewline
17 & 1.43 & 499 & 30 & 0.89 & 263 & 19 & 0.87 \tabularnewline
18 & -0.41 & 113 & 247 & -0.37 & 75 & 149 & -0.33 \tabularnewline
19 & -2.32 & 25 & 780 & -0.94 & 16 & 286 & -0.89 \tabularnewline
20 & 0.72 & 312 & 75 & 0.61 & 201 & 50 & 0.6 \tabularnewline
21 & 0.78 & 350 & 97 & 0.57 & 205 & 62 & 0.54 \tabularnewline
22 & 1.58 & 550 & 37 & 0.87 & 273 & 22 & 0.85 \tabularnewline
23 & 1.43 & 490 & 21 & 0.92 & 271 & 16 & 0.89 \tabularnewline
24 & 1.69 & 576 & 25 & 0.92 & 284 & 15 & 0.9 \tabularnewline
25 & 0.04 & 182 & 169 & 0.04 & 123 & 99 & 0.11 \tabularnewline
26 & -2.4 & 26 & 807 & -0.94 & 17 & 296 & -0.89 \tabularnewline
27 & 0.82 & 325 & 60 & 0.69 & 197 & 42 & 0.65 \tabularnewline
28 & 1.43 & 508 & 40 & 0.85 & 257 & 24 & 0.83 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74592&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]0.7[/C][C]352[/C][C]121[/C][C]0.49[/C][C]208[/C][C]71[/C][C]0.49[/C][/ROW]
[ROW][C]2[/C][C]1.16[/C][C]421[/C][C]37[/C][C]0.84[/C][C]247[/C][C]30[/C][C]0.78[/C][/ROW]
[ROW][C]3[/C][C]1.7[/C][C]593[/C][C]36[/C][C]0.89[/C][C]281[/C][C]22[/C][C]0.85[/C][/ROW]
[ROW][C]4[/C][C]0.09[/C][C]193[/C][C]164[/C][C]0.08[/C][C]126[/C][C]100[/C][C]0.12[/C][/ROW]
[ROW][C]5[/C][C]-2.23[/C][C]34[/C][C]763[/C][C]-0.91[/C][C]21[/C][C]291[/C][C]-0.87[/C][/ROW]
[ROW][C]6[/C][C]0.33[/C][C]230[/C][C]123[/C][C]0.3[/C][C]154[/C][C]80[/C][C]0.32[/C][/ROW]
[ROW][C]7[/C][C]1.6[/C][C]560[/C][C]32[/C][C]0.89[/C][C]275[/C][C]18[/C][C]0.88[/C][/ROW]
[ROW][C]8[/C][C]1.73[/C][C]595[/C][C]34[/C][C]0.89[/C][C]284[/C][C]17[/C][C]0.89[/C][/ROW]
[ROW][C]9[/C][C]0.89[/C][C]349[/C][C]61[/C][C]0.7[/C][C]206[/C][C]44[/C][C]0.65[/C][/ROW]
[ROW][C]10[/C][C]1.81[/C][C]611[/C][C]22[/C][C]0.93[/C][C]290[/C][C]13[/C][C]0.91[/C][/ROW]
[ROW][C]11[/C][C]-0.17[/C][C]146[/C][C]201[/C][C]-0.16[/C][C]104[/C][C]128[/C][C]-0.1[/C][/ROW]
[ROW][C]12[/C][C]-1.94[/C][C]45[/C][C]679[/C][C]-0.88[/C][C]30[/C][C]271[/C][C]-0.8[/C][/ROW]
[ROW][C]13[/C][C]0.74[/C][C]312[/C][C]73[/C][C]0.62[/C][C]201[/C][C]48[/C][C]0.61[/C][/ROW]
[ROW][C]14[/C][C]0.4[/C][C]268[/C][C]139[/C][C]0.32[/C][C]163[/C][C]82[/C][C]0.33[/C][/ROW]
[ROW][C]15[/C][C]1.51[/C][C]532[/C][C]39[/C][C]0.86[/C][C]266[/C][C]25[/C][C]0.83[/C][/ROW]
[ROW][C]16[/C][C]1.11[/C][C]413[/C][C]50[/C][C]0.78[/C][C]237[/C][C]34[/C][C]0.75[/C][/ROW]
[ROW][C]17[/C][C]1.43[/C][C]499[/C][C]30[/C][C]0.89[/C][C]263[/C][C]19[/C][C]0.87[/C][/ROW]
[ROW][C]18[/C][C]-0.41[/C][C]113[/C][C]247[/C][C]-0.37[/C][C]75[/C][C]149[/C][C]-0.33[/C][/ROW]
[ROW][C]19[/C][C]-2.32[/C][C]25[/C][C]780[/C][C]-0.94[/C][C]16[/C][C]286[/C][C]-0.89[/C][/ROW]
[ROW][C]20[/C][C]0.72[/C][C]312[/C][C]75[/C][C]0.61[/C][C]201[/C][C]50[/C][C]0.6[/C][/ROW]
[ROW][C]21[/C][C]0.78[/C][C]350[/C][C]97[/C][C]0.57[/C][C]205[/C][C]62[/C][C]0.54[/C][/ROW]
[ROW][C]22[/C][C]1.58[/C][C]550[/C][C]37[/C][C]0.87[/C][C]273[/C][C]22[/C][C]0.85[/C][/ROW]
[ROW][C]23[/C][C]1.43[/C][C]490[/C][C]21[/C][C]0.92[/C][C]271[/C][C]16[/C][C]0.89[/C][/ROW]
[ROW][C]24[/C][C]1.69[/C][C]576[/C][C]25[/C][C]0.92[/C][C]284[/C][C]15[/C][C]0.9[/C][/ROW]
[ROW][C]25[/C][C]0.04[/C][C]182[/C][C]169[/C][C]0.04[/C][C]123[/C][C]99[/C][C]0.11[/C][/ROW]
[ROW][C]26[/C][C]-2.4[/C][C]26[/C][C]807[/C][C]-0.94[/C][C]17[/C][C]296[/C][C]-0.89[/C][/ROW]
[ROW][C]27[/C][C]0.82[/C][C]325[/C][C]60[/C][C]0.69[/C][C]197[/C][C]42[/C][C]0.65[/C][/ROW]
[ROW][C]28[/C][C]1.43[/C][C]508[/C][C]40[/C][C]0.85[/C][C]257[/C][C]24[/C][C]0.83[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74592&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74592&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	0.7	352	121	0.49	208	71	0.49
2	1.16	421	37	0.84	247	30	0.78
3	1.7	593	36	0.89	281	22	0.85
4	0.09	193	164	0.08	126	100	0.12
5	-2.23	34	763	-0.91	21	291	-0.87
6	0.33	230	123	0.3	154	80	0.32
7	1.6	560	32	0.89	275	18	0.88
8	1.73	595	34	0.89	284	17	0.89
9	0.89	349	61	0.7	206	44	0.65
10	1.81	611	22	0.93	290	13	0.91
11	-0.17	146	201	-0.16	104	128	-0.1
12	-1.94	45	679	-0.88	30	271	-0.8
13	0.74	312	73	0.62	201	48	0.61
14	0.4	268	139	0.32	163	82	0.33
15	1.51	532	39	0.86	266	25	0.83
16	1.11	413	50	0.78	237	34	0.75
17	1.43	499	30	0.89	263	19	0.87
18	-0.41	113	247	-0.37	75	149	-0.33
19	-2.32	25	780	-0.94	16	286	-0.89
20	0.72	312	75	0.61	201	50	0.6
21	0.78	350	97	0.57	205	62	0.54
22	1.58	550	37	0.87	273	22	0.85
23	1.43	490	21	0.92	271	16	0.89
24	1.69	576	25	0.92	284	15	0.9
25	0.04	182	169	0.04	123	99	0.11
26	-2.4	26	807	-0.94	17	296	-0.89
27	0.82	325	60	0.69	197	42	0.65
28	1.43	508	40	0.85	257	24	0.83

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.986 (0)	0.989 (0)
(Ps-Ns)/(Ps+Ns)	0.986 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.989 (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) & 0.986 (0) & 0.989 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.986 (0) & 1 (0) & 0.999 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.989 (0) & 0.999 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74592&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]0.986 (0)[/C][C]0.989 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.986 (0)[/C][C]1 (0)[/C][C]0.999 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.989 (0)[/C][C]0.999 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74592&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74592&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)	0.986 (0)	0.989 (0)
(Ps-Ns)/(Ps+Ns)	0.986 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.989 (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)	0.926 (0)	0.925 (0)
(Ps-Ns)/(Ps+Ns)	0.926 (0)	1 (0)	0.985 (0)
(Pc-Nc)/(Pc+Nc)	0.925 (0)	0.985 (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) & 0.926 (0) & 0.925 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.926 (0) & 1 (0) & 0.985 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.925 (0) & 0.985 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=74592&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]0.926 (0)[/C][C]0.925 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.926 (0)[/C][C]1 (0)[/C][C]0.985 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.925 (0)[/C][C]0.985 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=74592&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=74592&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)	0.926 (0)	0.925 (0)
(Ps-Ns)/(Ps+Ns)	0.926 (0)	1 (0)	0.985 (0)
(Pc-Nc)/(Pc+Nc)	0.925 (0)	0.985 (0)	1 (0)

Parameters (Session):

par1 = 1 2 3 4 5 6 7 ;

Parameters (R input):

par1 = 1 2 3 4 5 6 7 ;

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