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

Tue, 04 Dec 2012 10:21:28 -0500

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/2012/Dec/04/t1354634628aanejqf2pukmz2t.htm/, Retrieved Wed, 24 Apr 2024 00:00:46 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=196308, Retrieved Wed, 24 Apr 2024 00:00:46 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

102

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

F     [Bivariate Kernel Density Estimation] [Connected vs Sepa...] [2010-10-04 07:40:49] [b98453cac15ba1066b407e146608df68]
- RMPD    [Survey Scores] [Survey Scores] [2012-12-04 15:21:28] [4289cf790da1cc09a0cb8798de13fde3] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	7 seconds
R Server	'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 7 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196308&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196308&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196308&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	7 seconds
R Server	'George Udny Yule' @ yule.wessa.net

Summary of survey scores (median of Likert score was subtracted)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	2.08	343	6	0.97	147	5	0.93
2	1.84	305	7	0.96	142	6	0.92
3	2.28	373	3	0.98	155	3	0.96
4	2.44	398	3	0.99	156	3	0.96
5	1.54	262	12	0.91	125	10	0.85
6	1.67	285	15	0.9	136	12	0.84
7	1.7	293	17	0.89	130	16	0.78
8	1.62	282	19	0.87	137	15	0.8
9	0.69	149	38	0.59	88	30	0.49
10	0.54	147	59	0.43	88	45	0.32
11	0.27	112	68	0.24	72	49	0.19
12	0.7	163	50	0.53	96	37	0.44
13	2.77	450	1	1	156	1	0.99
14	2.99	486	2	0.99	160	2	0.98
15	2.49	407	3	0.99	155	3	0.96
16	2.78	454	3	0.99	159	2	0.98
17	2.8	456	3	0.99	152	3	0.96
18	1.38	251	27	0.81	119	20	0.71
19	1.86	316	14	0.92	135	12	0.84
20	2.52	415	7	0.97	150	5	0.94
21	1.79	313	23	0.86	134	15	0.8
22	3.08	500	1	1	158	1	0.99
23	2.56	419	4	0.98	153	4	0.95
24	2.96	483	3	0.99	158	2	0.98
25	-1.56	8	260	-0.94	7	148	-0.91
26	-1.33	16	232	-0.87	10	139	-0.87
27	-1.62	8	270	-0.94	7	148	-0.91
28	-1.7	6	281	-0.96	5	154	-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 & 2.08 & 343 & 6 & 0.97 & 147 & 5 & 0.93 \tabularnewline
2 & 1.84 & 305 & 7 & 0.96 & 142 & 6 & 0.92 \tabularnewline
3 & 2.28 & 373 & 3 & 0.98 & 155 & 3 & 0.96 \tabularnewline
4 & 2.44 & 398 & 3 & 0.99 & 156 & 3 & 0.96 \tabularnewline
5 & 1.54 & 262 & 12 & 0.91 & 125 & 10 & 0.85 \tabularnewline
6 & 1.67 & 285 & 15 & 0.9 & 136 & 12 & 0.84 \tabularnewline
7 & 1.7 & 293 & 17 & 0.89 & 130 & 16 & 0.78 \tabularnewline
8 & 1.62 & 282 & 19 & 0.87 & 137 & 15 & 0.8 \tabularnewline
9 & 0.69 & 149 & 38 & 0.59 & 88 & 30 & 0.49 \tabularnewline
10 & 0.54 & 147 & 59 & 0.43 & 88 & 45 & 0.32 \tabularnewline
11 & 0.27 & 112 & 68 & 0.24 & 72 & 49 & 0.19 \tabularnewline
12 & 0.7 & 163 & 50 & 0.53 & 96 & 37 & 0.44 \tabularnewline
13 & 2.77 & 450 & 1 & 1 & 156 & 1 & 0.99 \tabularnewline
14 & 2.99 & 486 & 2 & 0.99 & 160 & 2 & 0.98 \tabularnewline
15 & 2.49 & 407 & 3 & 0.99 & 155 & 3 & 0.96 \tabularnewline
16 & 2.78 & 454 & 3 & 0.99 & 159 & 2 & 0.98 \tabularnewline
17 & 2.8 & 456 & 3 & 0.99 & 152 & 3 & 0.96 \tabularnewline
18 & 1.38 & 251 & 27 & 0.81 & 119 & 20 & 0.71 \tabularnewline
19 & 1.86 & 316 & 14 & 0.92 & 135 & 12 & 0.84 \tabularnewline
20 & 2.52 & 415 & 7 & 0.97 & 150 & 5 & 0.94 \tabularnewline
21 & 1.79 & 313 & 23 & 0.86 & 134 & 15 & 0.8 \tabularnewline
22 & 3.08 & 500 & 1 & 1 & 158 & 1 & 0.99 \tabularnewline
23 & 2.56 & 419 & 4 & 0.98 & 153 & 4 & 0.95 \tabularnewline
24 & 2.96 & 483 & 3 & 0.99 & 158 & 2 & 0.98 \tabularnewline
25 & -1.56 & 8 & 260 & -0.94 & 7 & 148 & -0.91 \tabularnewline
26 & -1.33 & 16 & 232 & -0.87 & 10 & 139 & -0.87 \tabularnewline
27 & -1.62 & 8 & 270 & -0.94 & 7 & 148 & -0.91 \tabularnewline
28 & -1.7 & 6 & 281 & -0.96 & 5 & 154 & -0.94 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196308&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]2.08[/C][C]343[/C][C]6[/C][C]0.97[/C][C]147[/C][C]5[/C][C]0.93[/C][/ROW]
[ROW][C]2[/C][C]1.84[/C][C]305[/C][C]7[/C][C]0.96[/C][C]142[/C][C]6[/C][C]0.92[/C][/ROW]
[ROW][C]3[/C][C]2.28[/C][C]373[/C][C]3[/C][C]0.98[/C][C]155[/C][C]3[/C][C]0.96[/C][/ROW]
[ROW][C]4[/C][C]2.44[/C][C]398[/C][C]3[/C][C]0.99[/C][C]156[/C][C]3[/C][C]0.96[/C][/ROW]
[ROW][C]5[/C][C]1.54[/C][C]262[/C][C]12[/C][C]0.91[/C][C]125[/C][C]10[/C][C]0.85[/C][/ROW]
[ROW][C]6[/C][C]1.67[/C][C]285[/C][C]15[/C][C]0.9[/C][C]136[/C][C]12[/C][C]0.84[/C][/ROW]
[ROW][C]7[/C][C]1.7[/C][C]293[/C][C]17[/C][C]0.89[/C][C]130[/C][C]16[/C][C]0.78[/C][/ROW]
[ROW][C]8[/C][C]1.62[/C][C]282[/C][C]19[/C][C]0.87[/C][C]137[/C][C]15[/C][C]0.8[/C][/ROW]
[ROW][C]9[/C][C]0.69[/C][C]149[/C][C]38[/C][C]0.59[/C][C]88[/C][C]30[/C][C]0.49[/C][/ROW]
[ROW][C]10[/C][C]0.54[/C][C]147[/C][C]59[/C][C]0.43[/C][C]88[/C][C]45[/C][C]0.32[/C][/ROW]
[ROW][C]11[/C][C]0.27[/C][C]112[/C][C]68[/C][C]0.24[/C][C]72[/C][C]49[/C][C]0.19[/C][/ROW]
[ROW][C]12[/C][C]0.7[/C][C]163[/C][C]50[/C][C]0.53[/C][C]96[/C][C]37[/C][C]0.44[/C][/ROW]
[ROW][C]13[/C][C]2.77[/C][C]450[/C][C]1[/C][C]1[/C][C]156[/C][C]1[/C][C]0.99[/C][/ROW]
[ROW][C]14[/C][C]2.99[/C][C]486[/C][C]2[/C][C]0.99[/C][C]160[/C][C]2[/C][C]0.98[/C][/ROW]
[ROW][C]15[/C][C]2.49[/C][C]407[/C][C]3[/C][C]0.99[/C][C]155[/C][C]3[/C][C]0.96[/C][/ROW]
[ROW][C]16[/C][C]2.78[/C][C]454[/C][C]3[/C][C]0.99[/C][C]159[/C][C]2[/C][C]0.98[/C][/ROW]
[ROW][C]17[/C][C]2.8[/C][C]456[/C][C]3[/C][C]0.99[/C][C]152[/C][C]3[/C][C]0.96[/C][/ROW]
[ROW][C]18[/C][C]1.38[/C][C]251[/C][C]27[/C][C]0.81[/C][C]119[/C][C]20[/C][C]0.71[/C][/ROW]
[ROW][C]19[/C][C]1.86[/C][C]316[/C][C]14[/C][C]0.92[/C][C]135[/C][C]12[/C][C]0.84[/C][/ROW]
[ROW][C]20[/C][C]2.52[/C][C]415[/C][C]7[/C][C]0.97[/C][C]150[/C][C]5[/C][C]0.94[/C][/ROW]
[ROW][C]21[/C][C]1.79[/C][C]313[/C][C]23[/C][C]0.86[/C][C]134[/C][C]15[/C][C]0.8[/C][/ROW]
[ROW][C]22[/C][C]3.08[/C][C]500[/C][C]1[/C][C]1[/C][C]158[/C][C]1[/C][C]0.99[/C][/ROW]
[ROW][C]23[/C][C]2.56[/C][C]419[/C][C]4[/C][C]0.98[/C][C]153[/C][C]4[/C][C]0.95[/C][/ROW]
[ROW][C]24[/C][C]2.96[/C][C]483[/C][C]3[/C][C]0.99[/C][C]158[/C][C]2[/C][C]0.98[/C][/ROW]
[ROW][C]25[/C][C]-1.56[/C][C]8[/C][C]260[/C][C]-0.94[/C][C]7[/C][C]148[/C][C]-0.91[/C][/ROW]
[ROW][C]26[/C][C]-1.33[/C][C]16[/C][C]232[/C][C]-0.87[/C][C]10[/C][C]139[/C][C]-0.87[/C][/ROW]
[ROW][C]27[/C][C]-1.62[/C][C]8[/C][C]270[/C][C]-0.94[/C][C]7[/C][C]148[/C][C]-0.91[/C][/ROW]
[ROW][C]28[/C][C]-1.7[/C][C]6[/C][C]281[/C][C]-0.96[/C][C]5[/C][C]154[/C][C]-0.94[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196308&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196308&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	2.08	343	6	0.97	147	5	0.93
2	1.84	305	7	0.96	142	6	0.92
3	2.28	373	3	0.98	155	3	0.96
4	2.44	398	3	0.99	156	3	0.96
5	1.54	262	12	0.91	125	10	0.85
6	1.67	285	15	0.9	136	12	0.84
7	1.7	293	17	0.89	130	16	0.78
8	1.62	282	19	0.87	137	15	0.8
9	0.69	149	38	0.59	88	30	0.49
10	0.54	147	59	0.43	88	45	0.32
11	0.27	112	68	0.24	72	49	0.19
12	0.7	163	50	0.53	96	37	0.44
13	2.77	450	1	1	156	1	0.99
14	2.99	486	2	0.99	160	2	0.98
15	2.49	407	3	0.99	155	3	0.96
16	2.78	454	3	0.99	159	2	0.98
17	2.8	456	3	0.99	152	3	0.96
18	1.38	251	27	0.81	119	20	0.71
19	1.86	316	14	0.92	135	12	0.84
20	2.52	415	7	0.97	150	5	0.94
21	1.79	313	23	0.86	134	15	0.8
22	3.08	500	1	1	158	1	0.99
23	2.56	419	4	0.98	153	4	0.95
24	2.96	483	3	0.99	158	2	0.98
25	-1.56	8	260	-0.94	7	148	-0.91
26	-1.33	16	232	-0.87	10	139	-0.87
27	-1.62	8	270	-0.94	7	148	-0.91
28	-1.7	6	281	-0.96	5	154	-0.94

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.951 (0)	0.964 (0)
(Ps-Ns)/(Ps+Ns)	0.951 (0)	1 (0)	0.998 (0)
(Pc-Nc)/(Pc+Nc)	0.964 (0)	0.998 (0)	1 (0)

\begin{tabular}{lllllllll}
\hline
Pearson correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.951 (0) & 0.964 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.951 (0) & 1 (0) & 0.998 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.964 (0) & 0.998 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196308&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]0.951 (0)[/C][C]0.964 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.951 (0)[/C][C]1 (0)[/C][C]0.998 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.964 (0)[/C][C]0.998 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196308&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196308&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)	0.951 (0)	0.964 (0)
(Ps-Ns)/(Ps+Ns)	0.951 (0)	1 (0)	0.998 (0)
(Pc-Nc)/(Pc+Nc)	0.964 (0)	0.998 (0)	1 (0)

Kendall tau rank correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.871 (0)	0.87 (0)
(Ps-Ns)/(Ps+Ns)	0.871 (0)	1 (0)	0.961 (0)
(Pc-Nc)/(Pc+Nc)	0.87 (0)	0.961 (0)	1 (0)

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations of survey scores (and p-values) \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 (0) & 0.871 (0) & 0.87 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.871 (0) & 1 (0) & 0.961 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.87 (0) & 0.961 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196308&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]0.871 (0)[/C][C]0.87 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.871 (0)[/C][C]1 (0)[/C][C]0.961 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.87 (0)[/C][C]0.961 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196308&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196308&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)	0.871 (0)	0.87 (0)
(Ps-Ns)/(Ps+Ns)	0.871 (0)	1 (0)	0.961 (0)
(Pc-Nc)/(Pc+Nc)	0.87 (0)	0.961 (0)	1 (0)

Parameters (Session):

par1 = 1 2 3 4 5 ;

Parameters (R input):

par1 = 1 2 3 4 5 ;

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

docor <- function(x,y,method) {
r <- cor.test(x,y,method=method)
paste(round(r$estimate,3),' (',round(r$p.value,3),')',sep='')
}
x <- t(x)
nx <- length(x[,1])
cx <- length(x[1,])
mymedian <- median(as.numeric(strsplit(par1,' ')[[1]]))
myresult <- array(NA, dim = c(cx,7))
rownames(myresult) <- paste('Q',1:cx,sep='')
colnames(myresult) <- c('mean','Sum of
positives (Ps)','Sum of
negatives (Ns)', '(Ps-Ns)/(Ps+Ns)', 'Count of
positives (Pc)', 'Count of
negatives (Nc)', '(Pc-Nc)/(Pc+Nc)')
for (i in 1:cx) {
spos <- 0
sneg <- 0
cpos <- 0
cneg <- 0
for (j in 1:nx) {
if (!is.na(x[j,i])) {
myx <- as.numeric(x[j,i]) - mymedian
if (myx > 0) {
spos = spos + myx
cpos = cpos + 1
}
if (myx < 0) {
sneg = sneg + abs(myx)
cneg = cneg + 1
}
}
}
myresult[i,1] <- round(mean(as.numeric(x[,i]),na.rm=T)-mymedian,2)
myresult[i,2] <- spos
myresult[i,3] <- sneg
myresult[i,4] <- round((spos - sneg) / (spos + sneg),2)
myresult[i,5] <- cpos
myresult[i,6] <- cneg
myresult[i,7] <- round((cpos - cneg) / (cpos + cneg),2)
}
myresult
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of survey scores (median of Likert score was subtracted)',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Question',header=TRUE)
for (i in 1:7) {
a<-table.element(a,colnames(myresult)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:cx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
for (j in 1:7) {
a<-table.element(a,myresult[i,j],align='right')
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code