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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 11:31:31 +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/t1292326221gc142bwiz0ipas9.htm/, Retrieved Thu, 02 May 2024 17:42:02 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109420, Retrieved Thu, 02 May 2024 17:42:02 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

135

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 - N...] [2010-12-14 11:31:31] [e192c8164fa91adb027f71579ac0a49a] [Current]
-             [Survey Scores] [Survey Scores - N...] [2010-12-20 19:37:41] [af8eb90b4bf1bcfcc4325c143dbee260] 

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Dataseries X:

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Histogram

Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109420&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109420&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109420&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	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

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	1.29	206	18	0.84	125	11	0.84
2	-1.35	25	222	-0.8	20	109	-0.69
3	0.32	131	85	0.21	80	52	0.21
4	0.53	128	51	0.43	83	30	0.47
5	-0.47	84	153	-0.29	53	79	-0.2
6	0.94	176	40	0.63	103	27	0.58
7	-0.21	95	125	-0.14	55	65	-0.08
8	1.24	205	24	0.79	115	20	0.7
9	0.55	124	43	0.49	90	29	0.51
10	1.05	188	36	0.68	101	21	0.66
11	-0.1	95	110	-0.07	66	54	0.1
12	-0.49	60	132	-0.38	48	76	-0.23
13	1.37	211	11	0.9	123	8	0.88
14	-0.98	41	184	-0.64	28	95	-0.54
15	1.05	160	7	0.92	100	4	0.92

\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 & 1.29 & 206 & 18 & 0.84 & 125 & 11 & 0.84 \tabularnewline
2 & -1.35 & 25 & 222 & -0.8 & 20 & 109 & -0.69 \tabularnewline
3 & 0.32 & 131 & 85 & 0.21 & 80 & 52 & 0.21 \tabularnewline
4 & 0.53 & 128 & 51 & 0.43 & 83 & 30 & 0.47 \tabularnewline
5 & -0.47 & 84 & 153 & -0.29 & 53 & 79 & -0.2 \tabularnewline
6 & 0.94 & 176 & 40 & 0.63 & 103 & 27 & 0.58 \tabularnewline
7 & -0.21 & 95 & 125 & -0.14 & 55 & 65 & -0.08 \tabularnewline
8 & 1.24 & 205 & 24 & 0.79 & 115 & 20 & 0.7 \tabularnewline
9 & 0.55 & 124 & 43 & 0.49 & 90 & 29 & 0.51 \tabularnewline
10 & 1.05 & 188 & 36 & 0.68 & 101 & 21 & 0.66 \tabularnewline
11 & -0.1 & 95 & 110 & -0.07 & 66 & 54 & 0.1 \tabularnewline
12 & -0.49 & 60 & 132 & -0.38 & 48 & 76 & -0.23 \tabularnewline
13 & 1.37 & 211 & 11 & 0.9 & 123 & 8 & 0.88 \tabularnewline
14 & -0.98 & 41 & 184 & -0.64 & 28 & 95 & -0.54 \tabularnewline
15 & 1.05 & 160 & 7 & 0.92 & 100 & 4 & 0.92 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109420&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]1.29[/C][C]206[/C][C]18[/C][C]0.84[/C][C]125[/C][C]11[/C][C]0.84[/C][/ROW]
[ROW][C]2[/C][C]-1.35[/C][C]25[/C][C]222[/C][C]-0.8[/C][C]20[/C][C]109[/C][C]-0.69[/C][/ROW]
[ROW][C]3[/C][C]0.32[/C][C]131[/C][C]85[/C][C]0.21[/C][C]80[/C][C]52[/C][C]0.21[/C][/ROW]
[ROW][C]4[/C][C]0.53[/C][C]128[/C][C]51[/C][C]0.43[/C][C]83[/C][C]30[/C][C]0.47[/C][/ROW]
[ROW][C]5[/C][C]-0.47[/C][C]84[/C][C]153[/C][C]-0.29[/C][C]53[/C][C]79[/C][C]-0.2[/C][/ROW]
[ROW][C]6[/C][C]0.94[/C][C]176[/C][C]40[/C][C]0.63[/C][C]103[/C][C]27[/C][C]0.58[/C][/ROW]
[ROW][C]7[/C][C]-0.21[/C][C]95[/C][C]125[/C][C]-0.14[/C][C]55[/C][C]65[/C][C]-0.08[/C][/ROW]
[ROW][C]8[/C][C]1.24[/C][C]205[/C][C]24[/C][C]0.79[/C][C]115[/C][C]20[/C][C]0.7[/C][/ROW]
[ROW][C]9[/C][C]0.55[/C][C]124[/C][C]43[/C][C]0.49[/C][C]90[/C][C]29[/C][C]0.51[/C][/ROW]
[ROW][C]10[/C][C]1.05[/C][C]188[/C][C]36[/C][C]0.68[/C][C]101[/C][C]21[/C][C]0.66[/C][/ROW]
[ROW][C]11[/C][C]-0.1[/C][C]95[/C][C]110[/C][C]-0.07[/C][C]66[/C][C]54[/C][C]0.1[/C][/ROW]
[ROW][C]12[/C][C]-0.49[/C][C]60[/C][C]132[/C][C]-0.38[/C][C]48[/C][C]76[/C][C]-0.23[/C][/ROW]
[ROW][C]13[/C][C]1.37[/C][C]211[/C][C]11[/C][C]0.9[/C][C]123[/C][C]8[/C][C]0.88[/C][/ROW]
[ROW][C]14[/C][C]-0.98[/C][C]41[/C][C]184[/C][C]-0.64[/C][C]28[/C][C]95[/C][C]-0.54[/C][/ROW]
[ROW][C]15[/C][C]1.05[/C][C]160[/C][C]7[/C][C]0.92[/C][C]100[/C][C]4[/C][C]0.92[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109420&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109420&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	1.29	206	18	0.84	125	11	0.84
2	-1.35	25	222	-0.8	20	109	-0.69
3	0.32	131	85	0.21	80	52	0.21
4	0.53	128	51	0.43	83	30	0.47
5	-0.47	84	153	-0.29	53	79	-0.2
6	0.94	176	40	0.63	103	27	0.58
7	-0.21	95	125	-0.14	55	65	-0.08
8	1.24	205	24	0.79	115	20	0.7
9	0.55	124	43	0.49	90	29	0.51
10	1.05	188	36	0.68	101	21	0.66
11	-0.1	95	110	-0.07	66	54	0.1
12	-0.49	60	132	-0.38	48	76	-0.23
13	1.37	211	11	0.9	123	8	0.88
14	-0.98	41	184	-0.64	28	95	-0.54
15	1.05	160	7	0.92	100	4	0.92

Pearson correlations of survey scores (and p-values)
	mean	(Ps-Ns)/(Ps+Ns)	(Pc-Nc)/(Pc+Nc)
mean	1 (0)	0.992 (0)	0.988 (0)
(Ps-Ns)/(Ps+Ns)	0.992 (0)	1 (0)	0.997 (0)
(Pc-Nc)/(Pc+Nc)	0.988 (0)	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) & 0.992 (0) & 0.988 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.992 (0) & 1 (0) & 0.997 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.988 (0) & 0.997 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109420&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]0.992 (0)[/C][C]0.988 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.992 (0)[/C][C]1 (0)[/C][C]0.997 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.988 (0)[/C][C]0.997 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109420&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109420&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)	0.992 (0)	0.988 (0)
(Ps-Ns)/(Ps+Ns)	0.992 (0)	1 (0)	0.997 (0)
(Pc-Nc)/(Pc+Nc)	0.988 (0)	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)	0.938 (0)	0.938 (0)
(Ps-Ns)/(Ps+Ns)	0.938 (0)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	0.938 (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) & 0.938 (0) & 0.938 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.938 (0) & 1 (0) & 1 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.938 (0) & 1 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109420&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]0.938 (0)[/C][C]0.938 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.938 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.938 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109420&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109420&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)	0.938 (0)	0.938 (0)
(Ps-Ns)/(Ps+Ns)	0.938 (0)	1 (0)	1 (0)
(Pc-Nc)/(Pc+Nc)	0.938 (0)	1 (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