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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_surveyscores.wasp

Title produced by software

Survey Scores

Date of computation

Fri, 15 Dec 2017 20:57:28 +0100

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/15/t1513368086c6194llxv5ef768.htm/, Retrieved Wed, 15 May 2024 04:26:58 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309812, Retrieved Wed, 15 May 2024 04:26:58 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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

-       [Survey Scores] [Survey Scores –...] [2017-12-15 19:57:28] [228f385b091a4ec8014a0b8722ae7714] [Current]

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Dataseries X:

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Histogram

Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 seconds
R Server	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309812&T=0

[TABLE]
[ROW]

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

Raw Input[/C]

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

Raw Output[/C]

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

Computing time[/C]

0 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309812&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309812&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	0 seconds
R Server	Big Analytics Cloud Computing Center

Summary of survey scores (median of Likert score was subtracted)
Question	mean	Sum ofpositives (Ps)	Sum ofnegatives (Ns)	(Ps-Ns)/(Ps+Ns)	Count ofpositives (Pc)	Count ofnegatives (Nc)	(Pc-Nc)/(Pc+Nc)
1	0.31	231	94	0.42	203	84	0.41
2	0.63	325	43	0.77	274	38	0.76
3	0.53	324	87	0.58	253	75	0.54
4	1.05	487	17	0.93	353	13	0.93
5	0.6	345	79	0.63	277	70	0.6
6	1.04	490	24	0.91	352	22	0.88
7	0.69	356	50	0.75	305	43	0.75

\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 & 0.31 & 231 & 94 & 0.42 & 203 & 84 & 0.41 \tabularnewline
2 & 0.63 & 325 & 43 & 0.77 & 274 & 38 & 0.76 \tabularnewline
3 & 0.53 & 324 & 87 & 0.58 & 253 & 75 & 0.54 \tabularnewline
4 & 1.05 & 487 & 17 & 0.93 & 353 & 13 & 0.93 \tabularnewline
5 & 0.6 & 345 & 79 & 0.63 & 277 & 70 & 0.6 \tabularnewline
6 & 1.04 & 490 & 24 & 0.91 & 352 & 22 & 0.88 \tabularnewline
7 & 0.69 & 356 & 50 & 0.75 & 305 & 43 & 0.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309812&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]0.31[/C][C]231[/C][C]94[/C][C]0.42[/C][C]203[/C][C]84[/C][C]0.41[/C][/ROW]
[ROW][C]2[/C][C]0.63[/C][C]325[/C][C]43[/C][C]0.77[/C][C]274[/C][C]38[/C][C]0.76[/C][/ROW]
[ROW][C]3[/C][C]0.53[/C][C]324[/C][C]87[/C][C]0.58[/C][C]253[/C][C]75[/C][C]0.54[/C][/ROW]
[ROW][C]4[/C][C]1.05[/C][C]487[/C][C]17[/C][C]0.93[/C][C]353[/C][C]13[/C][C]0.93[/C][/ROW]
[ROW][C]5[/C][C]0.6[/C][C]345[/C][C]79[/C][C]0.63[/C][C]277[/C][C]70[/C][C]0.6[/C][/ROW]
[ROW][C]6[/C][C]1.04[/C][C]490[/C][C]24[/C][C]0.91[/C][C]352[/C][C]22[/C][C]0.88[/C][/ROW]
[ROW][C]7[/C][C]0.69[/C][C]356[/C][C]50[/C][C]0.75[/C][C]305[/C][C]43[/C][C]0.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309812&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309812&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	0.31	231	94	0.42	203	84	0.41
2	0.63	325	43	0.77	274	38	0.76
3	0.53	324	87	0.58	253	75	0.54
4	1.05	487	17	0.93	353	13	0.93
5	0.6	345	79	0.63	277	70	0.6
6	1.04	490	24	0.91	352	22	0.88
7	0.69	356	50	0.75	305	43	0.75

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.961 (0.001)	0.949 (0.001)
(Ps-Ns)/(Ps+Ns)	0.961 (0.001)	1 (0)	0.997 (0)
(Pc-Nc)/(Pc+Nc)	0.949 (0.001)	0.997 (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) & 0.961 (0.001) & 0.949 (0.001) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.961 (0.001) & 1 (0) & 0.997 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.949 (0.001) & 0.997 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309812&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]0.961 (0.001)[/C][C]0.949 (0.001)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.961 (0.001)[/C][C]1 (0)[/C][C]0.997 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.949 (0.001)[/C][C]0.997 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309812&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309812&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)	0.961 (0.001)	0.949 (0.001)
(Ps-Ns)/(Ps+Ns)	0.961 (0.001)	1 (0)	0.997 (0)
(Pc-Nc)/(Pc+Nc)	0.949 (0.001)	0.997 (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)	0.905 (0.003)	0.905 (0.003)
(Ps-Ns)/(Ps+Ns)	0.905 (0.003)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	0.905 (0.003)	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) & 0.905 (0.003) & 0.905 (0.003) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.905 (0.003) & 1 (0) & 1 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.905 (0.003) & 1 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309812&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]0.905 (0.003)[/C][C]0.905 (0.003)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.905 (0.003)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.905 (0.003)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309812&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309812&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)	0.905 (0.003)	0.905 (0.003)
(Ps-Ns)/(Ps+Ns)	0.905 (0.003)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	0.905 (0.003)	1 (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)
}
print(myresult)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Summary of survey scores (median of Likert score was subtracted)',8,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Question',header=TRUE)
for (i in 1:7) {
a<-table.element(a,colnames(myresult)[i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:cx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
for (j in 1:7) {
a<-table.element(a,myresult[i,j],align='right')
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Pearson correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='pearson'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='pearson'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations of survey scores (and p-values)',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',header=TRUE)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,docor(myresult[,1],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,1],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,docor(myresult[,4],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,4],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,docor(myresult[,7],myresult[,1],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,4],method='kendall'),align='right')
a<-table.element(a,docor(myresult[,7],myresult[,7],method='kendall'),align='right')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code