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

Fri, 12 Dec 2014 13:44:11 +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/2014/Dec/12/t1418391882pse3fftcxtq66r8.htm/, Retrieved Tue, 10 Feb 2026 11:46:38 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266697, Retrieved Tue, 10 Feb 2026 11:46:38 +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

348

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

-       [Survey Scores] [] [2014-12-12 13:44:11] [921bde233b8ec180d9061abb09deed53] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

0 0 1 1 0 0 0 1 1 1
1 0 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 1 1 0
0 0 1 1 1 1 0 1 0 0
0 0 1 1 1 1 1 1 1 0
0 1 1 0 0 0 0 0 0 1
0 0 1 1 0 0 0 0 1 1
0 0 1 1 1 0 0 1 0 0
1 1 1 1 1 0 0 1 1 0
0 0 1 1 1 0 0 1 1 1
1 0 1 1 1 0 1 1 0 0
0 0 1 0 0 0 0 1 0 0
0 0 1 0 1 0 0 0 1 1
0 0 1 1 1 0 0 0 1 0
1 0 1 0 1 0 1 0 1 0
0 0 1 1 0 0 0 1 0 0
0 0 1 1 1 1 0 0 0 0
1 1 1 1 1 1 0 1 0 0
0 1 1 1 1 0 0 0 1 0
0 0 1 0 0 0 0 0 1 0
0 0 1 1 0 0 0 1 0 0
0 0 1 1 1 0 1 1 1 0
1 1 1 1 0 0 0 1 1 0
0 0 1 0 0 0 0 0 1 0
0 1 1 1 1 0 0 1 1 1
0 0 1 0 0 0 0 0 0 1
1 1 1 1 1 1 1 1 1 1
0 1 1 1 0 0 0 0 0 1
0 1 1 1 0 0 0 0 1 0
0 0 1 1 0 0 0 0 0 0
0 0 1 1 1 0 0 0 1 0
0 0 1 1 1 0 0 1 0 0
0 0 1 1 1 1 1 0 1 1
0 0 1 1 0 0 0 0 0 0
0 1 1 1 0 1 0 1 1 0
0 0 1 0 1 0 0 0 1 0
0 1 0 1 0 0 0 1 0 0
0 0 1 1 0 0 0 0 0 0
1 0 1 1 0 0 0 0 1 1
0 0 1 1 1 1 1 0 1 1
0 1 1 1 1 0 0 0 1 1
0 1 1 1 0 0 0 0 0 1
0 0 1 1 1 1 1 0 1 0
0 0 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 0 0 1
0 0 1 1 1 1 0 0 1 0
0 0 1 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0
0 0 1 1 0 0 0 1 1 1
0 0 1 1 1 1 1 1 1 0
0 1 1 1 0 0 0 0 1 0
0 0 0 1 0 0 0 1 0 1
0 0 1 0 1 0 0 0 0 0
0 0 1 1 0 1 1 0 1 0
0 0 1 1 0 0 0 1 0 1
0 0 1 1 1 1 0 0 1 1
0 0 1 1 0 0 0 1 1 0
1 1 1 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 0 0
1 0 1 1 1 1 1 1 1 1
1 0 1 1 1 1 1 0 1 1
0 1 1 1 1 1 1 1 1 0
0 0 1 1 0 0 0 0 1 0
0 0 1 0 0 0 0 0 1 0
0 1 1 1 0 0 0 0 1 0
0 0 1 0 0 0 0 0 1 0
0 0 1 1 0 0 0 0 0 0
0 0 1 0 0 0 0 0 0 0
0 1 1 0 0 0 0 0 1 1
0 0 1 1 1 0 0 1 1 0
0 0 1 1 1 1 1 1 1 1
0 0 1 0 1 0 1 0 1 0
0 0 1 1 0 1 0 1 1 1
0 0 1 1 0 1 0 1 0 1
1 0 1 0 0 0 0 0 1 0
0 0 1 1 1 1 1 1 1 1
0 0 1 1 0 0 0 0 1 1
0 0 1 1 1 1 1 0 0 1
0 1 1 1 0 0 0 0 1 0
0 0 1 1 0 0 0 0 1 0
0 0 1 1 1 1 1 1 1 1
0 1 1 0 1 0 0 1 1 1
0 0 1 1 0 0 0 0 0 1
0 0 1 1 1 0 0 1 1 0
0 0 1 1 1 0 0 0 1 0
0 0 1 1 0 0 0 1 0 0
0 0 1 1 1 1 0 1 1 1
0 0 1 0 1 0 0 0 0 0
0 0 1 1 1 1 0 0 0 0
1 1 1 1 0 0 0 1 1 0
0 0 0 1 1 1 1 0 1 1
0 0 1 1 1 0 0 1 1 1
0 0 1 1 1 0 0 1 0 0
0 1 1 1 1 1 1 0 0 0
0 0 1 1 1 1 1 0 0 0
0 1 1 1 0 0 0 0 1 1
1 0 1 1 1 1 0 0 1 0
1 0 1 1 1 1 1 1 1 0
1 0 1 1 0 0 0 1 1 0
1 0 1 0 1 1 0 1 0 1
0 0 1 1 0 0 0 1 1 0
0 0 1 0 0 0 1 1 0 0
0 0 1 1 0 0 0 0 1 0
0 0 1 1 0 0 0 0 0 0
1 1 1 0 0 0 0 0 0 1
0 1 1 1 0 0 0 1 1 0
0 1 1 0 0 0 0 0 0 1
1 0 1 1 0 0 0 0 0 1
0 0 1 1 1 0 1 0 0 1
0 0 1 1 0 0 0 0 0 1
0 0 1 1 0 0 0 1 1 1
0 0 1 1 1 0 0 0 1 0
0 0 1 1 0 0 0 1 1 0
0 0 1 1 1 0 0 1 1 1
0 0 1 1 0 0 0 1 0 0
0 0 1 1 0 0 0 1 1 0
0 0 1 1 0 0 0 0 0 1
1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 0 0 0 0 0
0 1 1 1 1 1 1 1 1 0
0 0 1 1 0 0 0 0 1 0
0 0 1 1 0 0 0 1 1 1
0 0 1 1 0 0 0 1 1 0
0 1 1 1 0 0 0 0 0 0
0 0 1 1 1 0 0 1 1 0
0 1 1 0 0 0 0 0 1 0
0 0 1 1 0 0 0 0 1 0
1 0 0 1 1 0 0 0 1 0
0 0 1 0 1 0 1 0 0 0
1 0 1 1 1 0 0 1 1 0
0 1 1 1 1 1 0 1 0 0
0 0 1 1 0 0 0 0 1 1
0 0 1 1 1 0 0 0 1 0
0 0 1 0 0 0 0 1 1 1
0 0 0 0 0 0 0 1 1 1
0 0 1 1 0 0 0 0 0 0
1 1 1 1 0 0 0 0 0 1
0 0 1 1 0 0 0 0 1 1
0 0 1 0 1 0 0 0 1 1
0 1 1 1 0 0 0 0 1 0
0 0 1 1 0 0 0 0 1 0
0 0 1 1 0 0 0 1 1 0
0 0 1 1 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 1 1 0 1 1 0 0 0
0 0 1 1 1 1 1 0 0 1
0 0 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 1 1 0
1 0 1 1 0 0 0 0 1 0
0 1 0 0 0 0 0 0 0 1
0 1 0 1 0 0 0 1 1 0
0 0 1 1 0 0 0 0 1 0
1 1 1 1 0 0 0 1 1 0
0 1 1 1 1 0 0 0 1 1
0 0 1 1 0 0 0 1 1 0
0 0 1 0 1 0 0 1 1 1
0 0 1 1 0 0 0 1 1 0
1 1 1 1 0 1 1 0 0 0
0 0 1 1 1 1 1 1 0 0
1 0 1 1 1 1 1 1 1 1
0 0 1 1 1 0 0 0 1 0
0 1 1 1 1 1 1 1 1 0
0 0 1 1 0 1 0 0 1 1
0 0 0 1 0 0 0 1 1 1
0 0 1 1 0 0 0 0 1 1
0 0 1 1 1 1 1 1 1 0
0 0 1 1 0 0 0 1 1 0
0 0 1 1 1 1 1 1 1 1
0 0 1 1 0 0 0 1 1 0
0 0 1 1 0 0 0 0 1 0
0 0 1 0 1 1 0 1 1 0
0 1 1 1 1 1 1 0 1 1
0 0 1 1 0 0 0 0 1 1
1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 0 0 0 1 0
0 1 1 1 1 0 0 0 1 0
0 0 1 1 0 0 0 0 1 0
0 0 1 1 0 0 0 1 0 0
0 0 1 1 0 0 0 0 1 0
0 0 1 1 1 0 0 0 1 0
0 0 1 1 0 0 0 1 1 1
0 0 1 1 1 0 0 1 1 0
0 0 1 1 1 0 0 0 1 0
1 0 1 1 1 0 0 1 1 1
0 0 1 1 0 0 0 1 1 1
0 0 1 1 1 0 0 1 0 0
0 0 1 1 1 1 1 1 1 0
0 0 1 1 1 1 1 1 1 0
0 0 1 1 1 1 1 1 1 0
0 0 1 1 1 1 1 1 1 0
1 1 1 0 1 1 0 0 1 1
0 0 1 1 1 0 1 1 1 1
0 0 1 0 0 0 0 0 0 0
0 0 1 0 0 0 0 0 1 0
0 1 1 0 0 0 0 0 1 0
0 0 1 1 1 1 1 0 1 0
0 0 1 1 1 1 1 1 1 1
0 0 1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 0 0 0
0 0 1 0 0 0 0 1 1 0
0 0 1 1 1 1 0 1 1 0
0 0 1 1 1 0 1 0 1 0
0 1 1 1 1 0 0 1 1 1
0 0 1 0 0 0 0 1 1 0
0 0 1 1 1 0 0 0 0 0
0 0 1 0 1 0 0 0 1 1
0 0 1 1 1 0 0 1 0 0
0 0 1 0 0 0 0 0 0 0
0 0 1 1 0 0 0 1 1 1
0 0 0 0 0 0 0 0 0 0
0 0 1 1 0 0 0 1 1 0
0 0 1 1 0 0 1 1 1 1
1 0 1 1 0 0 0 0 1 0
0 0 1 0 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0
0 0 1 1 1 1 0 1 1 1
0 0 1 0 1 0 0 0 1 0
0 0 1 1 0 0 0 1 1 1
0 0 1 1 0 0 0 0 1 0
0 0 1 1 1 1 1 1 0 0
0 1 1 1 1 1 1 1 1 1
0 0 1 1 1 0 0 0 1 0
0 0 0 1 0 0 0 1 0 1
1 1 1 1 1 1 1 0 1 1
0 1 1 0 1 0 0 1 0 1
0 0 1 1 0 0 0 0 0 1
0 0 1 1 1 1 0 0 1 1
0 0 1 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 1
1 0 1 0 1 1 1 0 0 0
0 0 1 1 1 0 0 1 0 0
0 0 0 0 0 0 0 0 0 0
0 0 1 0 1 0 0 0 0 0
0 0 1 1 1 0 0 1 1 0
0 0 0 1 1 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0
0 0 1 1 1 0 0 1 1 0
0 0 1 1 1 1 1 1 0 0
0 0 1 1 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0
1 0 1 1 0 0 0 0 0 0
0 0 1 1 1 1 0 0 1 0
0 0 1 0 0 0 0 1 1 1
0 1 1 1 0 0 0 1 1 0
0 0 1 1 1 1 1 1 1 0
0 1 1 1 1 1 1 0 1 1
0 0 1 1 1 0 0 1 1 1
0 0 1 1 0 0 0 1 1 0
0 1 1 1 1 0 1 0 0 0
0 0 1 1 0 1 1 0 1 0
0 1 1 0 0 0 0 0 0 1
0 0 1 1 1 0 0 1 1 1
0 0 0 1 0 0 0 1 1 0
0 0 1 1 1 0 0 1 1 1
0 0 1 1 0 0 0 1 0 0
0 0 1 1 1 1 1 1 0 1
0 0 1 1 1 1 1 0 1 1
0 0 1 1 1 1 0 1 1 0
0 0 1 1 0 0 0 1 1 1
0 0 1 1 1 1 0 0 1 0
0 1 1 1 0 0 0 0 1 0
0 0 1 1 0 0 0 1 1 0
0 0 1 1 1 1 1 1 1 0
0 0 1 1 0 0 0 0 0 0
0 1 1 1 0 0 0 1 1 0
0 0 1 1 0 0 0 1 1 0
0 0 1 0 0 0 0 0 1 0
0 0 1 1 1 0 0 1 0 1
1 0 1 0 0 0 0 0 1 1
0 0 1 1 1 1 1 0 1 1
0 0 1 1 1 1 1 0 1 0
0 0 1 1 1 0 0 0 1 0
0 1 1 0 0 0 0 1 1 1
0 0 0 0 0 0 0 0 0 0
1 0 1 1 1 0 1 1 1 0
0 0 1 1 1 0 0 0 1 0
1 0 1 1 0 0 0 0 1 1
0 0 1 1 1 0 1 1 0 1
0 0 1 1 1 1 1 1 1 1
1 0 1 1 1 0 0 0 1 0
1 0 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 1 1 1
0 0 1 0 1 0 0 1 1 1
0 0 1 1 1 1 1 1 1 1
0 0 1 1 1 1 1 0 1 1
1 0 1 0 0 0 0 0 0 1
0 0 1 0 1 0 0 0 1 1
0 0 1 1 1 1 0 1 0 0
0 0 1 0 0 0 0 0 0 0
0 1 1 1 0 0 0 1 1 1
0 0 1 1 1 1 1 1 0 1
1 0 1 0 1 0 0 1 1 0
0 0 1 1 1 1 0 1 1 1
0 1 1 1 0 0 0 1 0 1
0 0 1 1 1 0 0 1 0 1
0 0 1 1 0 0 0 0 0 1
1 0 1 1 1 0 1 0 0 0
0 0 1 0 1 1 0 1 1 0
0 0 1 1 0 0 0 0 1 0
0 1 1 1 0 0 0 0 1 1
0 0 1 1 1 1 1 0 1 1
0 0 1 1 0 0 0 0 1 1
0 1 1 1 0 0 0 1 1 0
0 0 1 0 1 0 0 0 1 0
0 0 1 1 0 0 0 1 1 1
0 0 1 1 1 0 1 1 1 1
0 0 1 0 0 0 0 0 0 0
0 1 1 0 1 0 0 0 1 1
0 1 1 1 1 0 0 1 0 0
0 1 1 1 1 1 1 1 1 1
0 1 1 0 0 0 0 0 1 1
0 0 1 1 1 1 0 0 1 0
0 0 1 1 1 0 0 1 1 0
0 0 1 1 0 0 0 1 1 1
0 0 1 0 0 0 0 0 1 0
0 0 1 1 1 0 0 0 0 1
0 0 1 0 0 1 0 0 1 1
0 0 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 0 1 0
1 1 1 1 0 0 0 0 1 1
1 0 1 1 1 0 0 0 0 1
0 1 1 1 0 0 0 1 1 1
1 1 1 1 0 0 0 1 1 1
0 0 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 1 1 0
0 0 1 1 0 0 0 1 1 0
0 0 1 1 1 1 0 1 0 0
0 1 0 0 0 0 0 1 0 0
0 0 1 0 0 0 0 0 1 0
0 0 1 0 0 0 0 1 0 1
0 0 1 1 1 0 1 1 0 1
1 1 1 1 1 1 0 1 0 1
0 0 1 1 1 0 0 1 0 0
0 1 1 0 0 0 0 1 1 1
0 0 1 1 1 1 0 0 1 1
0 0 1 1 0 0 0 0 1 0
0 0 1 1 0 0 0 1 1 0
0 0 1 1 0 0 0 1 1 1
0 0 1 0 1 0 0 1 1 0
0 0 1 1 0 0 0 0 1 0
0 0 1 1 0 0 0 1 1 1
0 1 0 1 1 0 0 1 0 1
0 1 1 1 0 0 0 0 0 0
1 0 1 0 0 0 0 0 1 1
0 1 1 1 0 0 0 0 1 1
0 1 1 1 1 0 0 1 1 1
1 1 1 1 1 1 0 1 1 1
0 1 1 1 1 1 1 0 1 1
0 1 1 1 0 0 0 1 1 1
0 0 1 1 1 0 0 0 0 1
1 1 1 1 1 0 0 1 1 0
0 0 1 0 1 0 0 0 1 0
1 0 1 1 0 0 0 1 1 0
0 0 1 1 1 1 1 0 0 1
0 1 1 1 0 0 0 1 1 1
0 0 1 1 1 0 1 1 1 1
0 0 1 0 0 0 0 0 1 1
1 0 1 1 1 0 1 0 0 1
0 0 1 1 1 0 1 0 1 1
0 0 1 1 0 0 0 1 1 0
0 0 1 0 1 0 0 0 1 1
0 0 1 1 1 0 0 0 1 1
0 0 1 1 0 0 0 0 1 1
0 0 1 1 1 0 0 0 1 1
1 1 1 1 1 1 1 1 0 1
0 0 1 1 1 0 0 1 1 1
1 0 1 1 0 1 0 0 0 0
0 1 1 1 0 0 0 0 1 0
0 0 1 1 0 1 0 0 0 1
0 0 1 1 0 0 0 1 1 1
1 0 1 1 0 1 0 0 1 1
0 0 1 1 0 0 0 0 0 1
1 0 1 1 1 1 1 0 1 1
0 0 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 1 1 0
0 1 1 0 0 0 0 0 1 1
0 1 1 1 0 0 0 1 1 1
0 0 1 1 1 1 1 1 1 1
0 1 1 1 0 0 0 1 1 1
0 0 0 0 1 0 0 0 1 1
0 0 1 1 0 0 0 0 1 1
0 0 1 1 1 0 0 0 1 0
0 1 1 1 1 1 0 0 1 0
0 1 1 1 1 1 1 1 1 1
0 0 1 1 1 1 0 0 1 1
0 0 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 0 1 1
0 1 1 1 0 0 0 1 1 0
0 0 1 1 1 0 1 0 0 0
0 0 1 1 0 0 0 0 0 1
0 1 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 1 0 1
0 0 1 1 1 0 0 1 1 1
0 0 1 1 1 0 0 0 1 1
0 0 1 1 0 0 0 1 0 1
1 1 1 1 1 0 0 1 0 0
0 0 1 1 1 1 1 1 1 1
0 0 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 0 1 1
1 0 1 1 1 1 0 0 1 1
0 0 1 1 1 1 1 1 1 1
1 1 1 1 1 0 0 0 1 1
1 1 1 1 0 0 0 1 0 1
0 0 1 0 1 0 0 0 0 1
0 0 1 0 0 0 0 1 0 0
0 0 1 1 0 0 0 1 1 1
0 0 1 1 1 1 1 0 0 1
0 0 1 1 0 0 0 0 1 1
1 0 1 1 0 0 0 0 1 1
1 0 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 1 0 1
0 0 1 1 0 0 0 0 1 0
0 0 1 1 1 0 1 0 0 1
0 0 1 0 0 0 0 0 1 0
0 0 1 1 1 1 0 1 1 1
0 0 1 1 1 0 1 0 1 0
0 0 1 0 0 0 0 1 1 1
1 0 1 1 1 1 0 1 1 1
0 0 1 1 0 0 0 1 0 0
0 0 1 1 0 0 0 0 0 0
0 0 1 0 1 0 0 0 1 1
0 0 1 0 1 0 0 0 0 1
0 0 1 1 1 0 0 0 1 1
0 0 1 0 1 0 1 0 1 1
0 0 1 1 0 0 0 1 0 0
0 1 1 1 0 1 1 0 1 1
1 0 1 1 0 0 0 1 1 1
0 1 1 1 1 0 0 0 0 0
0 1 1 1 0 0 0 0 1 0
0 1 1 1 1 0 0 0 1 1
0 0 1 1 0 1 1 1 1 1
0 1 1 1 0 0 0 0 1 0
1 1 1 1 0 1 1 1 1 1
0 1 1 1 1 0 0 1 1 1
1 0 1 1 1 0 0 1 1 1
0 0 1 1 1 0 0 1 1 0
1 1 1 1 0 0 0 0 1 0
0 1 1 1 1 0 0 0 0 1
0 0 1 1 1 0 1 1 0 1
0 0 1 0 0 0 1 1 1 0
0 0 1 1 0 0 0 0 1 1
1 0 0 1 1 0 0 1 1 1
0 0 1 1 0 0 0 1 1 0
1 0 1 0 0 0 0 0 1 0
0 0 1 0 0 0 0 1 0 1
0 0 1 0 0 0 0 0 1 0
1 0 1 1 0 0 0 1 1 1
0 0 1 1 0 0 0 0 0 1
0 0 1 0 1 0 0 0 1 1
0 0 1 1 0 0 0 0 1 0
0 0 1 0 1 0 0 0 1 1
1 1 1 1 1 0 0 1 1 1
0 1 1 1 1 0 0 0 0 1
0 0 1 1 0 0 0 1 1 1
0 0 1 1 0 0 0 1 1 1
1 0 1 1 0 0 0 0 1 1
0 0 1 1 1 0 1 1 1 1
0 0 1 0 0 0 0 0 1 1
0 0 1 1 0 0 0 1 1 1
0 0 1 1 0 0 0 1 1 1
0 0 1 1 0 0 0 1 1 1
0 0 1 1 0 0 0 1 1 1
0 0 1 1 0 0 0 1 1 1
0 0 1 1 0 0 0 1 0 1
0 1 1 1 1 1 1 1 1 1
0 0 1 1 1 0 0 1 1 0
0 0 1 1 0 0 0 1 1 0
0 0 1 1 1 1 1 1 1 1
1 0 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 0 0 0
1 0 1 1 0 0 0 0 1 1
0 0 1 1 1 1 0 1 1 1
0 0 1 1 0 0 0 0 0 1
1 0 1 1 1 0 0 0 0 1
0 0 1 1 0 0 0 1 1 1
0 0 1 1 1 0 0 0 0 1
0 0 1 0 0 0 0 0 0 0
0 1 1 1 1 0 1 0 1 0
0 1 1 1 0 0 0 0 1 1
0 0 1 1 0 0 0 1 1 1
0 0 1 1 1 0 0 1 0 0
0 1 1 1 0 0 0 0 0 1
0 0 1 1 0 0 0 1 1 1
0 0 1 1 1 0 0 1 1 0
0 0 1 0 0 0 0 1 1 1
0 0 1 1 1 0 0 0 1 0
1 0 1 1 1 0 0 1 1 1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	5 seconds
R Server	'Gwilym Jenkins' @ jenkins.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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266697&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266697&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266697&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	5 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Summary of survey scores (median of Likert score was subtracted)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	-0.35	37.5	206	-0.69	75	412	-0.69
2	-0.28	53.5	190	-0.56	107	380	-0.56
3	0.45	232.5	11	0.91	465	22	0.91
4	0.31	197	46.5	0.62	394	93	0.62
5	-0.04	112	131.5	-0.08	224	263	-0.08
6	-0.27	55	188.5	-0.55	110	377	-0.55
7	-0.3	48.5	195	-0.6	97	390	-0.6
8	-0.03	114	129.5	-0.06	228	259	-0.06
9	0.2	171.5	72	0.41	343	144	0.41
10	0.01	124	119.5	0.02	248	239	0.02

\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 & -0.35 & 37.5 & 206 & -0.69 & 75 & 412 & -0.69 \tabularnewline
2 & -0.28 & 53.5 & 190 & -0.56 & 107 & 380 & -0.56 \tabularnewline
3 & 0.45 & 232.5 & 11 & 0.91 & 465 & 22 & 0.91 \tabularnewline
4 & 0.31 & 197 & 46.5 & 0.62 & 394 & 93 & 0.62 \tabularnewline
5 & -0.04 & 112 & 131.5 & -0.08 & 224 & 263 & -0.08 \tabularnewline
6 & -0.27 & 55 & 188.5 & -0.55 & 110 & 377 & -0.55 \tabularnewline
7 & -0.3 & 48.5 & 195 & -0.6 & 97 & 390 & -0.6 \tabularnewline
8 & -0.03 & 114 & 129.5 & -0.06 & 228 & 259 & -0.06 \tabularnewline
9 & 0.2 & 171.5 & 72 & 0.41 & 343 & 144 & 0.41 \tabularnewline
10 & 0.01 & 124 & 119.5 & 0.02 & 248 & 239 & 0.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266697&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]-0.35[/C][C]37.5[/C][C]206[/C][C]-0.69[/C][C]75[/C][C]412[/C][C]-0.69[/C][/ROW]
[ROW][C]2[/C][C]-0.28[/C][C]53.5[/C][C]190[/C][C]-0.56[/C][C]107[/C][C]380[/C][C]-0.56[/C][/ROW]
[ROW][C]3[/C][C]0.45[/C][C]232.5[/C][C]11[/C][C]0.91[/C][C]465[/C][C]22[/C][C]0.91[/C][/ROW]
[ROW][C]4[/C][C]0.31[/C][C]197[/C][C]46.5[/C][C]0.62[/C][C]394[/C][C]93[/C][C]0.62[/C][/ROW]
[ROW][C]5[/C][C]-0.04[/C][C]112[/C][C]131.5[/C][C]-0.08[/C][C]224[/C][C]263[/C][C]-0.08[/C][/ROW]
[ROW][C]6[/C][C]-0.27[/C][C]55[/C][C]188.5[/C][C]-0.55[/C][C]110[/C][C]377[/C][C]-0.55[/C][/ROW]
[ROW][C]7[/C][C]-0.3[/C][C]48.5[/C][C]195[/C][C]-0.6[/C][C]97[/C][C]390[/C][C]-0.6[/C][/ROW]
[ROW][C]8[/C][C]-0.03[/C][C]114[/C][C]129.5[/C][C]-0.06[/C][C]228[/C][C]259[/C][C]-0.06[/C][/ROW]
[ROW][C]9[/C][C]0.2[/C][C]171.5[/C][C]72[/C][C]0.41[/C][C]343[/C][C]144[/C][C]0.41[/C][/ROW]
[ROW][C]10[/C][C]0.01[/C][C]124[/C][C]119.5[/C][C]0.02[/C][C]248[/C][C]239[/C][C]0.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266697&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266697&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	-0.35	37.5	206	-0.69	75	412	-0.69
2	-0.28	53.5	190	-0.56	107	380	-0.56
3	0.45	232.5	11	0.91	465	22	0.91
4	0.31	197	46.5	0.62	394	93	0.62
5	-0.04	112	131.5	-0.08	224	263	-0.08
6	-0.27	55	188.5	-0.55	110	377	-0.55
7	-0.3	48.5	195	-0.6	97	390	-0.6
8	-0.03	114	129.5	-0.06	228	259	-0.06
9	0.2	171.5	72	0.41	343	144	0.41
10	0.01	124	119.5	0.02	248	239	0.02

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	1 (0)	1 (0)
(Ps-Ns)/(Ps+Ns)	1 (0)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	1 (0)	1 (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) & 1 (0) & 1 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0) & 1 (0) & 1 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 1 (0) & 1 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266697&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]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]1 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266697&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266697&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)	1 (0)	1 (0)
(Ps-Ns)/(Ps+Ns)	1 (0)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	1 (0)	1 (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)	1 (0)	1 (0)
(Ps-Ns)/(Ps+Ns)	1 (0)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	1 (0)	1 (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) & 1 (0) & 1 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0) & 1 (0) & 1 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 1 (0) & 1 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266697&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]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]1 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266697&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266697&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)	1 (0)	1 (0)
(Ps-Ns)/(Ps+Ns)	1 (0)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	1 (0)	1 (0)	1 (0)

Parameters (Session):

par1 = 0 1 ;

Parameters (R input):

par1 = 0 1 ;

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