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Author

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R Software Module

rwasp_surveyscores.wasp

Title produced by software

Survey Scores

Date of computation

Wed, 10 Dec 2014 12:55:50 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/10/t1418216171lwfrh2y34gqxadr.htm/, Retrieved Sun, 19 May 2024 16:31:46 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265061, Retrieved Sun, 19 May 2024 16:31:46 +0000

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Estimated Impact

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

-     [Survey Scores] [] [2014-12-10 12:34:32] [5efa6717cfe6505454df834acc87b53b]
- R       [Survey Scores] [] [2014-12-10 12:55:50] [4621f922aed0297f88122271e88ec2ef] [Current]
-    D      [Survey Scores] [] [2014-12-10 13:54:16] [5efa6717cfe6505454df834acc87b53b] 
-    D        [Survey Scores] [] [2014-12-10 13:57:46] [5efa6717cfe6505454df834acc87b53b] 

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4 5 1 2 3 4 4 5 2 4 4 4 1 1 1 4 2 2 4 4 1 1 1 4 1 1 4 1 4 4 5 1 2 1 1
4 4 1 3 2 3 4 4 2 4 3 3 4 3 2 3 4 2 2 2 2 2 2 3 2 2 4 3 4 3 4 4 4 2 2
4 3 2 3 3 4 2 4 4 4 5 4 4 2 2 2 4 4 3 5 4 3 2 4 4 3 3 5 1 4 3 2 3 2 4
3 5 2 4 1 2 4 5 2 1 1 2 2 2 2 4 5 2 3 2 2 2 1 3 2 1 5 4 4 3 4 3 4 3 2
4 3 2 3 2 4 3 4 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 3 3 2 3 3 3 3 3 3 3 3
4 4 2 2 2 4 4 4 2 4 4 3 4 4 2 4 2 2 2 2 2 2 2 3 2 4 4 2 4 3 4 4 2 3 2
4 4 4 4 2 4 4 4 4 4 4 4 4 3 3 4 4 4 4 4 3 2 2 4 2 2 4 4 4 4 4 4 4 3 2
2 3 2 2 2 2 3 3 2 2 2 3 2 2 2 3 3 3 3 3 3 4 2 3 1 2 3 2 3 3 3 3 2 3 2
4 4 3 1 4 3 3 4 3 3 2 2 2 2 2 4 4 4 3 3 3 2 2 4 2 2 4 2 4 4 3 4 4 2 2
5 5 2 4 2 2 4 5 2 4 2 5 1 2 1 5 4 2 4 1 3 1 1 4 1 1 2 4 4 4 5 5 5 3 1
2 2 2 2 2 4 2 4 1 2 4 2 1 1 2 4 2 2 2 2 2 2 1 4 2 2 4 2 2 2 2 2 2 2 1
4 2 2 4 2 4 3 4 2 4 2 3 2 2 4 4 4 4 3 4 2 2 2 4 2 2 4 2 3 4 2 2 3 2 2
4 4 2 2 2 4 4 4 2 2 3 3 1 2 2 2 2 2 4 4 2 2 2 2 2 3 4 2 4 2 4 2 3 2 2
1 4 1 2 1 4 4 4 2 4 2 4 4 3 1 3 4 3 4 1 4 1 2 4 2 2 4 4 4 3 4 3 2 2 1
5 4 2 4 2 4 5 5 4 2 4 5 1 2 3 5 4 2 4 5 0 2 4 4 3 2 5 2 5 4 5 4 4 2 2
4 4 5 3 4 4 2 4 3 4 4 4 4 3 5 3 4 4 4 5 3 4 3 4 4 5 4 2 4 4 4 2 4 3 4
3 2 1 4 2 4 4 4 1 4 4 3 2 4 2 4 4 1 3 2 2 4 1 4 2 2 4 3 4 2 3 2 2 2 1
4 4 3 3 2 4 4 4 1 2 4 3 3 2 3 4 3 3 3 3 3 2 1 3 2 3 4 3 3 3 4 3 3 4 3
2 4 3 4 3 4 4 4 4 4 3 3 3 3 2 3 4 3 2 2 2 3 1 3 2 3 4 2 4 3 4 3 3 3 3
3 1 1 4 2 5 4 4 4 4 2 5 3 3 2 4 3 4 4 4 4 2 3 2 2 2 5 2 5 5 4 3 4 1 1
4 2 4 2 2 4 4 3 2 4 4 5 2 1 3 5 5 4 4 4 2 2 2 4 2 3 4 4 4 3 2 2 3 1 1
4 4 3 3 3 4 4 4 3 3 4 3 2 2 3 3 4 2 3 4 2 2 2 3 2 4 4 2 4 3 4 4 4 2 2
2 2 2 4 2 4 4 4 5 5 3 5 3 3 2 4 2 4 4 3 4 2 3 5 4 1 4 4 3 4 3 5 3 3 2
4 4 3 4 3 4 4 4 4 4 4 4 4 3 3 3 4 4 4 3 3 3 3 5 3 3 4 2 4 4 4 3 3 3 3
4 5 3 1 3 4 5 5 4 4 4 4 4 3 4 4 5 3 4 4 4 3 3 4 3 3 5 4 5 4 5 3 3 3 3
2 2 2 2 2 4 3 4 2 4 3 3 2 2 2 3 4 2 4 4 2 2 2 4 2 2 4 3 2 2 2 2 2 2 2
2 4 2 4 4 4 2 4 2 4 2 4 2 2 2 4 4 2 3 2 2 2 2 2 2 2 4 2 4 4 4 4 4 2 4
4 4 1 2 2 4 4 4 1 3 2 3 2 2 2 4 3 3 2 3 2 2 1 2 2 2 4 3 4 3 4 2 2 1 1
4 2 2 2 3 4 4 4 1 1 4 2 1 1 1 4 2 1 2 1 1 1 1 1 1 1 5 1 3 1 2 2 2 1 1
4 4 4 3 2 2 4 4 2 4 4 2 2 2 2 3 4 2 2 4 2 4 2 3 3 4 4 2 3 2 4 2 3 2 4
3 4 3 2 2 2 3 4 2 4 4 3 2 2 2 4 3 2 2 2 2 2 2 2 2 2 4 2 3 3 4 3 2 2 2
5 4 5 5 5 5 4 4 4 3 5 5 1 2 3 3 2 2 2 5 3 5 2 4 3 2 5 2 4 4 3 2 2 2 4
2 4 4 5 2 5 2 4 4 4 4 4 4 2 1 3 4 4 2 1 2 2 4 3 2 2 4 2 3 4 3 2 2 2 2
3 4 2 2 1 2 4 4 2 4 2 2 2 2 2 2 4 4 2 2 4 1 2 1 2 2 4 2 4 2 4 2 4 2 2
5 5 2 4 2 4 4 5 2 4 4 4 1 2 2 4 2 3 4 4 4 1 2 2 4 2 4 2 4 3 4 2 2 3 1
4 4 2 4 1 2 4 4 4 2 4 3 2 3 4 3 3 4 2 2 3 1 3 4 2 2 4 2 4 2 4 2 2 3 2
3 4 2 3 2 4 4 4 3 4 4 3 2 2 2 4 4 3 3 3 2 2 2 3 3 2 4 4 4 4 4 4 3 3 2
2 5 1 3 2 5 4 5 2 4 2 3 3 4 3 3 2 4 4 1 4 1 4 5 4 1 4 4 3 4 3 2 3 3 1
2 3 1 2 2 3 4 4 1 2 3 2 1 1 1 4 2 1 2 3 1 1 1 1 1 1 4 2 3 2 3 2 1 2 1
2 4 2 2 2 4 4 4 2 2 4 4 2 2 2 4 4 2 2 2 2 2 2 2 2 2 4 2 2 2 4 4 4 4 2
5 4 5 4 5 5 5 5 4 2 5 5 3 4 2 5 1 4 4 4 2 3 2 5 3 2 5 2 5 5 5 2 3 3 0
2 4 1 1 2 2 4 4 1 2 4 2 1 2 2 4 2 1 2 2 1 1 1 1 1 1 4 1 3 1 4 1 1 2 1
2 5 2 4 3 4 3 4 4 4 3 3 2 2 2 3 3 2 3 2 3 3 3 4 2 3 4 2 3 2 3 4 4 2 3
5 5 3 3 2 5 3 5 4 4 4 3 2 3 2 4 2 3 3 3 2 2 2 3 2 2 4 2 4 3 4 2 3 2 2
2 4 1 2 2 4 3 4 2 3 2 4 2 2 1 4 4 3 2 2 2 1 2 3 2 1 4 2 4 3 4 2 2 2 1
3 4 1 2 1 3 4 4 2 2 4 3 1 2 2 3 3 2 2 2 2 2 2 4 2 2 4 2 4 4 4 4 4 2 2
5 5 3 5 5 5 5 5 5 5 4 5 5 5 4 4 4 5 5 4 5 3 3 5 5 4 5 5 5 4 5 2 2 5 5
3 4 2 4 3 3 4 4 5 4 4 4 2 2 2 4 4 3 2 2 4 2 3 4 4 2 4 4 4 4 4 4 5 3 2
2 2 2 4 2 2 4 5 4 3 2 5 1 2 1 4 2 2 3 1 4 1 1 4 2 1 5 2 4 3 4 2 2 3 1
2 4 2 3 4 4 3 4 2 3 2 2 2 3 2 3 3 4 2 3 4 3 4 3 4 2 4 3 3 2 2 4 3 2 2
1 3 1 1 1 2 2 2 1 3 3 2 1 1 1 3 3 1 1 1 1 1 1 3 1 3 4 2 3 2 2 2 2 1 2
4 5 1 3 3 4 4 4 2 3 4 4 3 2 1 4 4 3 4 2 2 4 1 3 2 3 5 2 5 3 4 2 4 2 3
2 2 2 1 4 5 4 2 4 2 2 5 2 2 1 5 3 4 5 1 1 1 1 5 1 1 2 1 1 5 2 1 2 3 1
4 5 2 4 2 4 5 5 3 3 2 2 4 4 2 2 5 4 2 2 4 1 2 4 4 1 5 4 4 4 5 2 4 4 1
4 5 3 2 2 4 4 5 1 4 4 3 1 2 2 4 4 3 4 4 4 2 2 4 2 4 4 2 4 3 5 2 2 4 2
2 4 1 2 2 4 4 4 1 3 2 4 1 2 2 4 4 1 2 2 1 1 1 2 2 2 4 5 4 4 4 4 4 2 2
3 4 1 2 3 2 4 4 2 3 2 3 2 2 1 4 2 2 2 1 2 2 2 4 2 2 4 2 4 4 4 2 2 2 2
4 3 4 4 2 4 4 4 3 4 4 3 2 2 2 3 2 2 3 2 4 2 1 4 2 2 4 3 4 2 4 3 4 2 0
2 4 2 2 2 4 3 4 2 4 3 4 2 4 1 4 2 3 2 2 2 1 2 3 2 1 4 2 4 4 3 2 2 2 1
3 5 3 2 1 4 4 5 4 4 5 4 3 2 1 3 4 3 2 2 3 1 2 2 1 1 4 3 4 4 4 3 5 2 1
5 5 3 5 4 5 3 5 5 4 4 3 3 3 3 4 4 5 4 3 4 3 4 3 3 2 5 4 4 4 4 3 4 5 1
2 4 1 2 2 2 3 4 2 2 3 3 1 1 1 4 2 1 2 2 2 1 1 3 2 1 3 2 3 3 4 3 2 2 1
4 4 4 3 2 3 4 4 4 3 4 3 2 3 2 3 3 4 4 3 3 3 3 2 2 2 4 4 3 4 4 3 3 2 2
3 4 1 2 1 3 4 3 1 4 3 3 1 1 1 2 2 1 2 1 1 2 1 3 1 2 3 3 3 2 3 2 2 2 2
2 4 2 2 2 4 5 5 3 2 2 3 2 3 2 4 4 4 4 3 2 3 3 2 2 2 5 3 4 3 5 4 4 2 2
4 5 1 3 1 4 5 5 4 4 2 4 4 3 1 4 4 3 4 1 3 1 3 4 3 2 4 5 5 4 5 4 3 2 1
4 2 1 4 5 3 3 4 1 1 5 3 2 2 2 3 3 1 2 2 4 1 2 2 2 4 3 2 2 4 2 1 2 1 1
2 4 1 4 1 3 4 5 1 1 1 1 1 1 1 3 2 1 1 1 1 1 1 1 1 1 4 2 4 1 4 1 1 1 1
4 5 2 2 2 4 5 5 4 4 4 5 4 3 2 4 4 3 2 2 2 2 3 4 2 2 4 4 4 4 5 4 2 2 2
4 5 4 2 2 4 4 4 2 3 4 3 2 3 1 4 4 4 4 3 2 4 2 4 2 2 3 1 4 3 4 4 2 2 2
3 4 2 2 2 3 4 4 2 3 4 4 2 2 2 4 2 2 2 2 2 2 2 4 2 2 4 3 4 4 4 2 2 2 2
4 4 2 3 2 4 1 3 4 4 5 4 1 1 1 4 4 1 4 1 1 1 1 1 2 1 1 4 2 2 1 3 4 2 1
4 4 3 2 2 4 3 4 2 2 4 4 2 2 1 4 3 2 3 2 3 2 2 4 2 3 4 2 3 4 4 4 3 1 1
3 4 3 3 2 5 4 4 3 4 2 3 4 2 1 2 4 3 3 4 2 1 2 2 2 1 4 4 3 4 3 3 4 1 1
3 4 2 4 2 4 4 4 3 3 4 4 3 3 2 4 3 5 4 3 3 2 2 4 2 2 4 3 4 4 4 3 2 2 2
4 4 2 3 2 2 4 5 3 1 4 3 2 2 1 4 4 2 3 3 1 1 1 4 1 4 4 2 4 4 5 3 2 2 1
3 5 1 3 1 3 4 4 2 3 2 4 1 1 1 3 4 2 2 1 1 1 1 3 1 1 4 3 3 2 4 3 4 1 1
2 5 1 2 1 4 5 5 5 1 2 4 1 1 1 4 1 1 2 1 1 1 1 4 1 1 1 1 5 2 5 2 2 1 1
3 3 2 4 1 4 4 4 3 3 1 4 3 2 1 4 3 3 3 2 2 1 1 3 2 1 4 3 4 4 3 3 3 2 1
2 4 1 3 1 3 3 4 1 2 3 2 2 1 1 3 2 2 3 2 1 1 3 2 2 1 4 2 4 2 4 2 2 3 1
2 4 1 2 2 5 5 5 2 2 5 3 3 4 2 5 2 4 3 2 3 1 2 4 2 2 5 2 5 3 5 2 2 2 2
3 2 3 3 4 3 2 4 2 1 4 3 1 1 3 2 2 3 3 3 3 2 2 4 2 2 3 1 3 3 2 3 2 2 2
1 2 3 3 3 4 3 2 4 4 3 3 4 4 4 4 3 3 3 2 3 4 3 2 3 3 4 4 3 4 4 3 3 3 3
3 4 1 3 2 4 3 4 2 2 4 3 2 2 2 4 3 2 3 2 2 3 2 3 2 3 4 2 3 3 4 2 3 2 2
4 4 2 2 2 4 4 4 1 2 2 2 2 1 2 4 2 2 1 2 2 1 1 4 2 2 4 1 3 4 4 2 2 2 2
4 5 2 4 2 4 5 5 5 2 4 5 3 2 4 3 4 5 5 4 2 5 2 4 3 4 5 4 5 3 5 2 4 2 5
4 4 3 2 1 2 4 4 3 2 4 1 2 2 1 3 2 2 1 2 2 2 1 4 2 4 4 2 4 2 4 3 3 2 1
4 4 1 4 1 3 3 4 4 3 5 4 3 3 1 4 3 4 2 3 3 1 2 3 2 1 4 4 3 3 3 4 4 2 1
2 4 2 3 2 3 4 4 2 3 4 2 2 2 2 3 3 2 2 2 2 2 2 3 2 2 4 2 3 3 4 2 2 2 2
5 2 2 4 2 4 2 3 4 4 4 4 2 2 3 2 4 4 4 3 4 4 3 4 4 2 3 5 2 4 2 4 4 4 4
4 4 3 3 2 4 4 4 2 3 4 4 2 2 2 4 3 2 2 2 2 1 2 4 2 2 4 2 4 3 5 3 2 2 2
3 3 2 3 2 3 3 3 2 2 4 2 2 1 2 4 2 2 2 2 1 2 2 3 1 3 3 2 2 2 3 2 3 2 2
2 4 1 2 1 3 4 4 3 3 2 3 2 2 2 4 2 2 3 3 2 1 1 4 3 2 4 2 4 2 4 2 2 3 2
4 4 1 2 2 3 4 4 2 2 4 2 2 2 2 3 3 2 2 3 2 3 2 2 2 4 4 2 3 2 4 2 2 2 3
4 3 1 4 2 4 4 4 2 4 2 3 1 1 1 4 4 2 2 2 2 2 2 3 2 2 4 2 4 3 3 4 4 3 2
2 2 1 3 2 4 2 3 2 2 2 4 2 2 1 3 4 3 3 2 2 2 2 3 2 2 3 4 3 3 3 2 2 2 2
4 3 1 3 3 4 4 4 4 4 1 2 1 2 1 4 5 2 3 2 4 2 2 3 4 2 4 4 3 3 4 2 2 3 2
4 5 3 3 3 4 5 5 4 4 4 4 3 3 3 4 4 4 4 3 2 4 3 4 2 2 5 3 5 3 5 2 5 4 2
4 4 4 3 3 4 4 5 2 3 5 4 3 3 2 4 2 3 2 2 4 3 3 3 3 3 4 2 4 3 4 2 2 4 3
2 3 2 2 2 3 4 4 2 3 4 2 2 2 2 2 4 2 2 2 2 3 2 2 2 2 4 2 3 2 3 2 2 2 2
4 4 2 3 2 3 4 3 4 5 3 3 2 2 4 4 4 2 1 2 4 2 4 2 4 2 4 2 4 4 3 4 3 4 2
2 4 2 4 1 4 4 5 3 2 2 4 2 2 1 2 2 2 4 2 1 1 1 4 2 2 4 2 2 4 4 4 4 1 1
4 4 3 3 4 4 4 4 4 2 2 3 3 4 4 4 3 4 2 3 4 3 2 4 3 4 4 2 4 3 4 2 2 1 1
3 5 3 4 3 3 3 5 3 3 2 4 3 3 2 3 3 3 3 2 3 2 3 2 2 2 3 3 3 4 3 3 5 1 2
4 4 2 3 2 4 3 4 4 4 4 3 3 3 2 3 2 3 4 4 2 2 3 3 2 2 3 2 3 4 4 3 3 3 2
2 4 1 2 1 4 5 4 2 2 1 2 1 1 1 4 2 1 2 1 2 1 2 2 2 1 5 3 4 2 4 3 4 2 1
3 4 2 3 1 5 4 4 3 4 4 4 3 3 2 4 2 4 3 2 3 1 2 4 2 2 4 3 4 4 4 3 2 3 1
2 4 1 3 1 4 5 4 4 3 2 2 4 4 1 4 4 2 4 1 4 1 2 5 2 1 4 5 5 4 5 1 2 2 2

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265061&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]4 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=265061&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265061&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	4 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	0.23	62	37	0.25	53	34	0.22
2	0.81	104	16	0.73	82	15	0.69
3	-0.88	14	109	-0.77	11	76	-0.75
4	-0.08	37	46	-0.11	33	41	-0.11
5	-0.79	16	101	-0.73	12	80	-0.74
6	0.66	85	14	0.72	73	14	0.68
7	0.73	90	11	0.78	76	10	0.77
8	1.12	124	3	0.95	97	3	0.94
9	-0.29	41	72	-0.27	35	57	-0.24
10	0.07	50	42	0.09	47	35	0.15
11	0.24	67	41	0.24	58	36	0.23
12	0.31	58	25	0.4	46	23	0.33
13	-0.74	17	97	-0.7	16	72	-0.64
14	-0.72	12	90	-0.76	11	72	-0.73
15	-1.04	10	122	-0.85	9	87	-0.81
16	0.57	72	10	0.76	66	10	0.74
17	0.17	54	36	0.2	49	34	0.18
18	-0.29	34	65	-0.31	30	52	-0.27
19	-0.14	36	51	-0.17	33	46	-0.16
20	-0.51	25	80	-0.52	21	63	-0.5
21	-0.53	24	81	-0.54	23	63	-0.47
22	-0.97	13	118	-0.8	11	80	-0.76
23	-0.96	6	110	-0.9	6	81	-0.86
24	0.25	59	32	0.3	52	26	0.33
25	-0.77	13	96	-0.76	12	81	-0.74
26	-0.85	13	105	-0.78	12	80	-0.74
27	0.94	108	7	0.88	91	5	0.9
28	-0.34	33	70	-0.36	27	62	-0.39
29	0.6	77	12	0.73	65	10	0.73
30	0.19	50	30	0.25	47	27	0.27
31	0.73	92	13	0.75	74	12	0.72
32	-0.29	28	59	-0.36	26	53	-0.34
33	-0.13	38	52	-0.16	33	49	-0.2
34	-0.69	12	87	-0.76	10	72	-0.76
35	-1.13	10	132	-0.86	8	90	-0.84

\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 & 0.23 & 62 & 37 & 0.25 & 53 & 34 & 0.22 \tabularnewline
2 & 0.81 & 104 & 16 & 0.73 & 82 & 15 & 0.69 \tabularnewline
3 & -0.88 & 14 & 109 & -0.77 & 11 & 76 & -0.75 \tabularnewline
4 & -0.08 & 37 & 46 & -0.11 & 33 & 41 & -0.11 \tabularnewline
5 & -0.79 & 16 & 101 & -0.73 & 12 & 80 & -0.74 \tabularnewline
6 & 0.66 & 85 & 14 & 0.72 & 73 & 14 & 0.68 \tabularnewline
7 & 0.73 & 90 & 11 & 0.78 & 76 & 10 & 0.77 \tabularnewline
8 & 1.12 & 124 & 3 & 0.95 & 97 & 3 & 0.94 \tabularnewline
9 & -0.29 & 41 & 72 & -0.27 & 35 & 57 & -0.24 \tabularnewline
10 & 0.07 & 50 & 42 & 0.09 & 47 & 35 & 0.15 \tabularnewline
11 & 0.24 & 67 & 41 & 0.24 & 58 & 36 & 0.23 \tabularnewline
12 & 0.31 & 58 & 25 & 0.4 & 46 & 23 & 0.33 \tabularnewline
13 & -0.74 & 17 & 97 & -0.7 & 16 & 72 & -0.64 \tabularnewline
14 & -0.72 & 12 & 90 & -0.76 & 11 & 72 & -0.73 \tabularnewline
15 & -1.04 & 10 & 122 & -0.85 & 9 & 87 & -0.81 \tabularnewline
16 & 0.57 & 72 & 10 & 0.76 & 66 & 10 & 0.74 \tabularnewline
17 & 0.17 & 54 & 36 & 0.2 & 49 & 34 & 0.18 \tabularnewline
18 & -0.29 & 34 & 65 & -0.31 & 30 & 52 & -0.27 \tabularnewline
19 & -0.14 & 36 & 51 & -0.17 & 33 & 46 & -0.16 \tabularnewline
20 & -0.51 & 25 & 80 & -0.52 & 21 & 63 & -0.5 \tabularnewline
21 & -0.53 & 24 & 81 & -0.54 & 23 & 63 & -0.47 \tabularnewline
22 & -0.97 & 13 & 118 & -0.8 & 11 & 80 & -0.76 \tabularnewline
23 & -0.96 & 6 & 110 & -0.9 & 6 & 81 & -0.86 \tabularnewline
24 & 0.25 & 59 & 32 & 0.3 & 52 & 26 & 0.33 \tabularnewline
25 & -0.77 & 13 & 96 & -0.76 & 12 & 81 & -0.74 \tabularnewline
26 & -0.85 & 13 & 105 & -0.78 & 12 & 80 & -0.74 \tabularnewline
27 & 0.94 & 108 & 7 & 0.88 & 91 & 5 & 0.9 \tabularnewline
28 & -0.34 & 33 & 70 & -0.36 & 27 & 62 & -0.39 \tabularnewline
29 & 0.6 & 77 & 12 & 0.73 & 65 & 10 & 0.73 \tabularnewline
30 & 0.19 & 50 & 30 & 0.25 & 47 & 27 & 0.27 \tabularnewline
31 & 0.73 & 92 & 13 & 0.75 & 74 & 12 & 0.72 \tabularnewline
32 & -0.29 & 28 & 59 & -0.36 & 26 & 53 & -0.34 \tabularnewline
33 & -0.13 & 38 & 52 & -0.16 & 33 & 49 & -0.2 \tabularnewline
34 & -0.69 & 12 & 87 & -0.76 & 10 & 72 & -0.76 \tabularnewline
35 & -1.13 & 10 & 132 & -0.86 & 8 & 90 & -0.84 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265061&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]0.23[/C][C]62[/C][C]37[/C][C]0.25[/C][C]53[/C][C]34[/C][C]0.22[/C][/ROW]
[ROW][C]2[/C][C]0.81[/C][C]104[/C][C]16[/C][C]0.73[/C][C]82[/C][C]15[/C][C]0.69[/C][/ROW]
[ROW][C]3[/C][C]-0.88[/C][C]14[/C][C]109[/C][C]-0.77[/C][C]11[/C][C]76[/C][C]-0.75[/C][/ROW]
[ROW][C]4[/C][C]-0.08[/C][C]37[/C][C]46[/C][C]-0.11[/C][C]33[/C][C]41[/C][C]-0.11[/C][/ROW]
[ROW][C]5[/C][C]-0.79[/C][C]16[/C][C]101[/C][C]-0.73[/C][C]12[/C][C]80[/C][C]-0.74[/C][/ROW]
[ROW][C]6[/C][C]0.66[/C][C]85[/C][C]14[/C][C]0.72[/C][C]73[/C][C]14[/C][C]0.68[/C][/ROW]
[ROW][C]7[/C][C]0.73[/C][C]90[/C][C]11[/C][C]0.78[/C][C]76[/C][C]10[/C][C]0.77[/C][/ROW]
[ROW][C]8[/C][C]1.12[/C][C]124[/C][C]3[/C][C]0.95[/C][C]97[/C][C]3[/C][C]0.94[/C][/ROW]
[ROW][C]9[/C][C]-0.29[/C][C]41[/C][C]72[/C][C]-0.27[/C][C]35[/C][C]57[/C][C]-0.24[/C][/ROW]
[ROW][C]10[/C][C]0.07[/C][C]50[/C][C]42[/C][C]0.09[/C][C]47[/C][C]35[/C][C]0.15[/C][/ROW]
[ROW][C]11[/C][C]0.24[/C][C]67[/C][C]41[/C][C]0.24[/C][C]58[/C][C]36[/C][C]0.23[/C][/ROW]
[ROW][C]12[/C][C]0.31[/C][C]58[/C][C]25[/C][C]0.4[/C][C]46[/C][C]23[/C][C]0.33[/C][/ROW]
[ROW][C]13[/C][C]-0.74[/C][C]17[/C][C]97[/C][C]-0.7[/C][C]16[/C][C]72[/C][C]-0.64[/C][/ROW]
[ROW][C]14[/C][C]-0.72[/C][C]12[/C][C]90[/C][C]-0.76[/C][C]11[/C][C]72[/C][C]-0.73[/C][/ROW]
[ROW][C]15[/C][C]-1.04[/C][C]10[/C][C]122[/C][C]-0.85[/C][C]9[/C][C]87[/C][C]-0.81[/C][/ROW]
[ROW][C]16[/C][C]0.57[/C][C]72[/C][C]10[/C][C]0.76[/C][C]66[/C][C]10[/C][C]0.74[/C][/ROW]
[ROW][C]17[/C][C]0.17[/C][C]54[/C][C]36[/C][C]0.2[/C][C]49[/C][C]34[/C][C]0.18[/C][/ROW]
[ROW][C]18[/C][C]-0.29[/C][C]34[/C][C]65[/C][C]-0.31[/C][C]30[/C][C]52[/C][C]-0.27[/C][/ROW]
[ROW][C]19[/C][C]-0.14[/C][C]36[/C][C]51[/C][C]-0.17[/C][C]33[/C][C]46[/C][C]-0.16[/C][/ROW]
[ROW][C]20[/C][C]-0.51[/C][C]25[/C][C]80[/C][C]-0.52[/C][C]21[/C][C]63[/C][C]-0.5[/C][/ROW]
[ROW][C]21[/C][C]-0.53[/C][C]24[/C][C]81[/C][C]-0.54[/C][C]23[/C][C]63[/C][C]-0.47[/C][/ROW]
[ROW][C]22[/C][C]-0.97[/C][C]13[/C][C]118[/C][C]-0.8[/C][C]11[/C][C]80[/C][C]-0.76[/C][/ROW]
[ROW][C]23[/C][C]-0.96[/C][C]6[/C][C]110[/C][C]-0.9[/C][C]6[/C][C]81[/C][C]-0.86[/C][/ROW]
[ROW][C]24[/C][C]0.25[/C][C]59[/C][C]32[/C][C]0.3[/C][C]52[/C][C]26[/C][C]0.33[/C][/ROW]
[ROW][C]25[/C][C]-0.77[/C][C]13[/C][C]96[/C][C]-0.76[/C][C]12[/C][C]81[/C][C]-0.74[/C][/ROW]
[ROW][C]26[/C][C]-0.85[/C][C]13[/C][C]105[/C][C]-0.78[/C][C]12[/C][C]80[/C][C]-0.74[/C][/ROW]
[ROW][C]27[/C][C]0.94[/C][C]108[/C][C]7[/C][C]0.88[/C][C]91[/C][C]5[/C][C]0.9[/C][/ROW]
[ROW][C]28[/C][C]-0.34[/C][C]33[/C][C]70[/C][C]-0.36[/C][C]27[/C][C]62[/C][C]-0.39[/C][/ROW]
[ROW][C]29[/C][C]0.6[/C][C]77[/C][C]12[/C][C]0.73[/C][C]65[/C][C]10[/C][C]0.73[/C][/ROW]
[ROW][C]30[/C][C]0.19[/C][C]50[/C][C]30[/C][C]0.25[/C][C]47[/C][C]27[/C][C]0.27[/C][/ROW]
[ROW][C]31[/C][C]0.73[/C][C]92[/C][C]13[/C][C]0.75[/C][C]74[/C][C]12[/C][C]0.72[/C][/ROW]
[ROW][C]32[/C][C]-0.29[/C][C]28[/C][C]59[/C][C]-0.36[/C][C]26[/C][C]53[/C][C]-0.34[/C][/ROW]
[ROW][C]33[/C][C]-0.13[/C][C]38[/C][C]52[/C][C]-0.16[/C][C]33[/C][C]49[/C][C]-0.2[/C][/ROW]
[ROW][C]34[/C][C]-0.69[/C][C]12[/C][C]87[/C][C]-0.76[/C][C]10[/C][C]72[/C][C]-0.76[/C][/ROW]
[ROW][C]35[/C][C]-1.13[/C][C]10[/C][C]132[/C][C]-0.86[/C][C]8[/C][C]90[/C][C]-0.84[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265061&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265061&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	0.23	62	37	0.25	53	34	0.22
2	0.81	104	16	0.73	82	15	0.69
3	-0.88	14	109	-0.77	11	76	-0.75
4	-0.08	37	46	-0.11	33	41	-0.11
5	-0.79	16	101	-0.73	12	80	-0.74
6	0.66	85	14	0.72	73	14	0.68
7	0.73	90	11	0.78	76	10	0.77
8	1.12	124	3	0.95	97	3	0.94
9	-0.29	41	72	-0.27	35	57	-0.24
10	0.07	50	42	0.09	47	35	0.15
11	0.24	67	41	0.24	58	36	0.23
12	0.31	58	25	0.4	46	23	0.33
13	-0.74	17	97	-0.7	16	72	-0.64
14	-0.72	12	90	-0.76	11	72	-0.73
15	-1.04	10	122	-0.85	9	87	-0.81
16	0.57	72	10	0.76	66	10	0.74
17	0.17	54	36	0.2	49	34	0.18
18	-0.29	34	65	-0.31	30	52	-0.27
19	-0.14	36	51	-0.17	33	46	-0.16
20	-0.51	25	80	-0.52	21	63	-0.5
21	-0.53	24	81	-0.54	23	63	-0.47
22	-0.97	13	118	-0.8	11	80	-0.76
23	-0.96	6	110	-0.9	6	81	-0.86
24	0.25	59	32	0.3	52	26	0.33
25	-0.77	13	96	-0.76	12	81	-0.74
26	-0.85	13	105	-0.78	12	80	-0.74
27	0.94	108	7	0.88	91	5	0.9
28	-0.34	33	70	-0.36	27	62	-0.39
29	0.6	77	12	0.73	65	10	0.73
30	0.19	50	30	0.25	47	27	0.27
31	0.73	92	13	0.75	74	12	0.72
32	-0.29	28	59	-0.36	26	53	-0.34
33	-0.13	38	52	-0.16	33	49	-0.2
34	-0.69	12	87	-0.76	10	72	-0.76
35	-1.13	10	132	-0.86	8	90	-0.84

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.991 (0)	0.99 (0)
(Ps-Ns)/(Ps+Ns)	0.991 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.99 (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) & 0.991 (0) & 0.99 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.991 (0) & 1 (0) & 0.999 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.99 (0) & 0.999 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265061&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]0.991 (0)[/C][C]0.99 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.991 (0)[/C][C]1 (0)[/C][C]0.999 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.99 (0)[/C][C]0.999 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265061&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265061&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)	0.991 (0)	0.99 (0)
(Ps-Ns)/(Ps+Ns)	0.991 (0)	1 (0)	0.999 (0)
(Pc-Nc)/(Pc+Nc)	0.99 (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)	0.931 (0)	0.914 (0)
(Ps-Ns)/(Ps+Ns)	0.931 (0)	1 (0)	0.964 (0)
(Pc-Nc)/(Pc+Nc)	0.914 (0)	0.964 (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) & 0.931 (0) & 0.914 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.931 (0) & 1 (0) & 0.964 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.914 (0) & 0.964 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265061&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]0.931 (0)[/C][C]0.914 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.931 (0)[/C][C]1 (0)[/C][C]0.964 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.914 (0)[/C][C]0.964 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265061&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265061&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)	0.931 (0)	0.914 (0)
(Ps-Ns)/(Ps+Ns)	0.931 (0)	1 (0)	0.964 (0)
(Pc-Nc)/(Pc+Nc)	0.914 (0)	0.964 (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