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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

Tue, 14 Dec 2010 11:35:06 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/14/t1292326381qfj3ww25f6kpwlm.htm/, Retrieved Thu, 02 May 2024 15:58:58 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109426, Retrieved Thu, 02 May 2024 15:58:58 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

129

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

-     [Survey Scores] [E-Learn 2008 table 1] [2008-09-07 11:33:54] [b98453cac15ba1066b407e146608df68]
F RM D  [Survey Scores] [ATTLES] [2010-04-05 12:47:13] [b98453cac15ba1066b407e146608df68]
- R PD      [Survey Scores] [Survey Scores - G...] [2010-12-14 11:35:06] [e192c8164fa91adb027f71579ac0a49a] [Current]
-             [Survey Scores] [Survey Scores - G...] [2010-12-20 19:44:57] [af8eb90b4bf1bcfcc4325c143dbee260] 

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Dataseries X:

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Histogram

Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 2 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109426&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109426&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109426&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	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

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	0.97	179	38	0.65	110	25	0.63
2	0.82	166	47	0.56	92	38	0.42
3	0.46	122	55	0.38	74	39	0.31
4	1.51	235	15	0.88	124	10	0.85
5	1.28	209	22	0.81	111	16	0.75
6	1.66	265	23	0.84	125	13	0.81
7	0.42	152	90	0.26	83	50	0.25
8	1.05	201	48	0.61	103	28	0.57
9	-0.42	72	134	-0.3	55	74	-0.15
10	0.03	100	96	0.02	65	49	0.14
11	0.6	141	54	0.45	77	33	0.4
12	-0.89	30	160	-0.68	26	86	-0.54
13	-0.73	35	142	-0.6	28	78	-0.47
14	0.28	107	66	0.24	70	40	0.27
15	0.75	151	41	0.57	88	25	0.56

\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 & 0.97 & 179 & 38 & 0.65 & 110 & 25 & 0.63 \tabularnewline
2 & 0.82 & 166 & 47 & 0.56 & 92 & 38 & 0.42 \tabularnewline
3 & 0.46 & 122 & 55 & 0.38 & 74 & 39 & 0.31 \tabularnewline
4 & 1.51 & 235 & 15 & 0.88 & 124 & 10 & 0.85 \tabularnewline
5 & 1.28 & 209 & 22 & 0.81 & 111 & 16 & 0.75 \tabularnewline
6 & 1.66 & 265 & 23 & 0.84 & 125 & 13 & 0.81 \tabularnewline
7 & 0.42 & 152 & 90 & 0.26 & 83 & 50 & 0.25 \tabularnewline
8 & 1.05 & 201 & 48 & 0.61 & 103 & 28 & 0.57 \tabularnewline
9 & -0.42 & 72 & 134 & -0.3 & 55 & 74 & -0.15 \tabularnewline
10 & 0.03 & 100 & 96 & 0.02 & 65 & 49 & 0.14 \tabularnewline
11 & 0.6 & 141 & 54 & 0.45 & 77 & 33 & 0.4 \tabularnewline
12 & -0.89 & 30 & 160 & -0.68 & 26 & 86 & -0.54 \tabularnewline
13 & -0.73 & 35 & 142 & -0.6 & 28 & 78 & -0.47 \tabularnewline
14 & 0.28 & 107 & 66 & 0.24 & 70 & 40 & 0.27 \tabularnewline
15 & 0.75 & 151 & 41 & 0.57 & 88 & 25 & 0.56 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109426&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]0.97[/C][C]179[/C][C]38[/C][C]0.65[/C][C]110[/C][C]25[/C][C]0.63[/C][/ROW]
[ROW][C]2[/C][C]0.82[/C][C]166[/C][C]47[/C][C]0.56[/C][C]92[/C][C]38[/C][C]0.42[/C][/ROW]
[ROW][C]3[/C][C]0.46[/C][C]122[/C][C]55[/C][C]0.38[/C][C]74[/C][C]39[/C][C]0.31[/C][/ROW]
[ROW][C]4[/C][C]1.51[/C][C]235[/C][C]15[/C][C]0.88[/C][C]124[/C][C]10[/C][C]0.85[/C][/ROW]
[ROW][C]5[/C][C]1.28[/C][C]209[/C][C]22[/C][C]0.81[/C][C]111[/C][C]16[/C][C]0.75[/C][/ROW]
[ROW][C]6[/C][C]1.66[/C][C]265[/C][C]23[/C][C]0.84[/C][C]125[/C][C]13[/C][C]0.81[/C][/ROW]
[ROW][C]7[/C][C]0.42[/C][C]152[/C][C]90[/C][C]0.26[/C][C]83[/C][C]50[/C][C]0.25[/C][/ROW]
[ROW][C]8[/C][C]1.05[/C][C]201[/C][C]48[/C][C]0.61[/C][C]103[/C][C]28[/C][C]0.57[/C][/ROW]
[ROW][C]9[/C][C]-0.42[/C][C]72[/C][C]134[/C][C]-0.3[/C][C]55[/C][C]74[/C][C]-0.15[/C][/ROW]
[ROW][C]10[/C][C]0.03[/C][C]100[/C][C]96[/C][C]0.02[/C][C]65[/C][C]49[/C][C]0.14[/C][/ROW]
[ROW][C]11[/C][C]0.6[/C][C]141[/C][C]54[/C][C]0.45[/C][C]77[/C][C]33[/C][C]0.4[/C][/ROW]
[ROW][C]12[/C][C]-0.89[/C][C]30[/C][C]160[/C][C]-0.68[/C][C]26[/C][C]86[/C][C]-0.54[/C][/ROW]
[ROW][C]13[/C][C]-0.73[/C][C]35[/C][C]142[/C][C]-0.6[/C][C]28[/C][C]78[/C][C]-0.47[/C][/ROW]
[ROW][C]14[/C][C]0.28[/C][C]107[/C][C]66[/C][C]0.24[/C][C]70[/C][C]40[/C][C]0.27[/C][/ROW]
[ROW][C]15[/C][C]0.75[/C][C]151[/C][C]41[/C][C]0.57[/C][C]88[/C][C]25[/C][C]0.56[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109426&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109426&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	0.97	179	38	0.65	110	25	0.63
2	0.82	166	47	0.56	92	38	0.42
3	0.46	122	55	0.38	74	39	0.31
4	1.51	235	15	0.88	124	10	0.85
5	1.28	209	22	0.81	111	16	0.75
6	1.66	265	23	0.84	125	13	0.81
7	0.42	152	90	0.26	83	50	0.25
8	1.05	201	48	0.61	103	28	0.57
9	-0.42	72	134	-0.3	55	74	-0.15
10	0.03	100	96	0.02	65	49	0.14
11	0.6	141	54	0.45	77	33	0.4
12	-0.89	30	160	-0.68	26	86	-0.54
13	-0.73	35	142	-0.6	28	78	-0.47
14	0.28	107	66	0.24	70	40	0.27
15	0.75	151	41	0.57	88	25	0.56

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.984 (0)	0.985 (0)
(Ps-Ns)/(Ps+Ns)	0.984 (0)	1 (0)	0.994 (0)
(Pc-Nc)/(Pc+Nc)	0.985 (0)	0.994 (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) & 0.984 (0) & 0.985 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.984 (0) & 1 (0) & 0.994 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.985 (0) & 0.994 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109426&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]0.984 (0)[/C][C]0.985 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.984 (0)[/C][C]1 (0)[/C][C]0.994 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.985 (0)[/C][C]0.994 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109426&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109426&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)	0.984 (0)	0.985 (0)
(Ps-Ns)/(Ps+Ns)	0.984 (0)	1 (0)	0.994 (0)
(Pc-Nc)/(Pc+Nc)	0.985 (0)	0.994 (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)	0.943 (0)	0.924 (0)
(Ps-Ns)/(Ps+Ns)	0.943 (0)	1 (0)	0.981 (0)
(Pc-Nc)/(Pc+Nc)	0.924 (0)	0.981 (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) & 0.943 (0) & 0.924 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.943 (0) & 1 (0) & 0.981 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.924 (0) & 0.981 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109426&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]0.943 (0)[/C][C]0.924 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.943 (0)[/C][C]1 (0)[/C][C]0.981 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.924 (0)[/C][C]0.981 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109426&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109426&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)	0.943 (0)	0.924 (0)
(Ps-Ns)/(Ps+Ns)	0.943 (0)	1 (0)	0.981 (0)
(Pc-Nc)/(Pc+Nc)	0.924 (0)	0.981 (0)	1 (0)

Parameters (Session):

par1 = 1 2 3 4 5 6 7 ;

Parameters (R input):

par1 = 1 2 3 4 5 6 7 ;

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

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

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code