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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_surveyscores.wasp
Title produced by softwareSurvey Scores
Date of computationSat, 23 Feb 2008 04:28:38 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Feb/23/t120376618585cqsbcczjphhg4.htm/, Retrieved Tue, 14 May 2024 08:31:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=8539, Retrieved Tue, 14 May 2024 08:31:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact211

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Survey Scores] [survey scores] [2008-02-23 11:28:38] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4	4	2	2	2	3	3	3	3	2	2	2	2	2	1	1	2	2	2	2	1	2	2	1	2	2	2	2	2	2	2	1	4	3	3	1	NA	NA	2
4	1	2	1	1	1	1	4	2	1	4	2	4	1	1	1	5	1	1	1	1	1	1	1	4	1	1	1	1	1	1	1	1	1	1	4	1	1	2
1	5	NA	4	NA	3	3	3	3	4	2	3	4	3	2	NA	4	1	1	1	1	1	1	1	4	1	1	NA	1	1	1	1	NA	1	1	1	NA	1	NA
1	2	1	2	1	2	1	2	2	2	1	1	1	1	1	NA	2	1	1	2	1	2	2	NA	1	1	1	2	2	2	1	NA	1	1	2	1	1	2	2
1	1	1	1	1	2	1	1	1	1	1	NA	4	1	NA	NA	1	1	1	1	1	1	1	NA	5	1	1	1	1	1	1	NA	NA	1	1	1	1	NA	1
3	5	2	3	2	1	NA	4	3	1	2	3	4	1	1	NA	3	1	1	2	2	NA	2	NA	1	NA	NA	NA	NA	NA	NA	NA	1	1	1	1	NA	3	3
3	4	3	4	4	4	4	4	4	3	1	2	2	2	3	NA	1	2	1	2	2	NA	2	NA	1	1	1	1	2	2	2	NA	NA	NA	NA	NA	NA	NA	NA
2	2	1	2	1	1	NA	4	1	1	1	1	4	NA	NA	NA	2	2	2	NA	NA	1	1	NA	2	NA	NA	NA	NA	NA	2	NA	1	NA	NA	1	1	4	1
3	4	3	4	3	3	NA	4	2	3	3	NA	4	1	NA	NA	3	1	1	NA	NA	NA	2	NA	3	1	1	NA	NA	NA	NA	NA	1	NA	NA	1	NA	NA	NA
1	1	1	1	1	1	1	4	1	1	1	1	1	1	1	1	1	1	1	1	2	2	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1
1	1	NA	NA	NA	NA	NA	2	2	NA	2	NA	NA	NA	NA	NA	2	NA	NA	NA	NA	NA	NA	NA	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	2	NA	NA	NA
1	1	1	1	1	1	NA	4	4	1	1	NA	NA	1	1	NA	1	NA	1	NA	1	4	1	NA	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1
5	5	4	4	4	5	3	4	3	4	4	4	4	2	1	1	3	1	2	3	3	4	3	2	3	2	2	2	3	4	1	2	2	1	1	2	2	3	3
1	1	1	1	1	1	1	1	1	1	1	NA	NA	NA	1	NA	1	1	1	1	NA	NA	NA	NA	1	1	NA	1	NA	1	NA	NA	NA	NA	NA	1	NA	NA	NA
4	3	4	4	4	5	5	5	3	2	4	2	4	3	4	4	2	1	1	2	2	2	1	2	1	NA	NA	3	3	4	NA	NA	3	4	3	1	NA	NA	NA
4	5	3	4	NA	5	NA	4	4	5	4	1	NA	5	NA	NA	1	NA	NA	NA	1	NA	1	NA	1	NA	1	NA	1	NA	1	NA	1	NA	NA	4	4	4	1
2	3	1	1	1	2	1	2	2	2	2	4	4	3	3	NA	3	4	3	3	4	4	3	4	3	3	3	4	3	4	4	3	NA	3	3	1	NA	NA	1
3	4	3	2	2	3	4	NA	NA	3	1	NA	2	2	NA	NA	2	1	1	NA	2	1	2	NA	2	1	1	NA	3	3	2	NA	NA	NA	NA	1	NA	2	2
4	4	4	4	NA	3	4	2	NA	NA	2	NA	NA	3	3	NA	2	2	2	2	2	4	2	2	2	2	2	2	4	4	2	NA	3	3	3	3	3	3	3

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=8539&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=8539&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=8539&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
1-0.47716-0.3969-0.2
2-0.051314-0.04980.06
3-0.82317-0.7310-0.54
4-0.5716-0.39710-0.18
5-1.07319-0.73311-0.57
6-0.44715-0.3649-0.38
7-0.54512-0.4146-0.2
80.171180.161060.25
9-0.59313-0.6239-0.5
10-0.82418-0.64311-0.57
11-0.95422-0.69414-0.56
12-0.83212-0.7128-0.6
130.14970.12950.29
14-1218-0.8111-0.83
15-1.23117-0.8919-0.8
16-1.418-0.7814-0.6
17-0.84319-0.73213-0.73
18-1.56126-0.93115-0.88
19-1.65028-1016-1
20-1.23016-1011-1
21-1.27120-0.9113-0.86
22-0.77414-0.5649-0.38
23-1.35023-1015-1
24-1.25111-0.8317-0.75
25-0.89421-0.68313-0.62
26-1.64023-1013-1
27-1.64023-1013-1
28-1.25116-0.88110-0.82
29-1115-0.8819-0.8
30-0.79415-0.5849-0.38
31-1.43121-0.91113-0.86
32-1.57011-106-1
33-1.33117-0.8919-0.8
34-1.25116-0.8818-0.78
35-1.25015-108-1
36-1.44228-0.87215-0.76
37-1.33113-0.8617-0.75
38-0.73210-0.6726-0.5
39-1.23016-1010-1

\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 & -0.47 & 7 & 16 & -0.39 & 6 & 9 & -0.2 \tabularnewline
2 & -0.05 & 13 & 14 & -0.04 & 9 & 8 & 0.06 \tabularnewline
3 & -0.82 & 3 & 17 & -0.7 & 3 & 10 & -0.54 \tabularnewline
4 & -0.5 & 7 & 16 & -0.39 & 7 & 10 & -0.18 \tabularnewline
5 & -1.07 & 3 & 19 & -0.73 & 3 & 11 & -0.57 \tabularnewline
6 & -0.44 & 7 & 15 & -0.36 & 4 & 9 & -0.38 \tabularnewline
7 & -0.54 & 5 & 12 & -0.41 & 4 & 6 & -0.2 \tabularnewline
8 & 0.17 & 11 & 8 & 0.16 & 10 & 6 & 0.25 \tabularnewline
9 & -0.59 & 3 & 13 & -0.62 & 3 & 9 & -0.5 \tabularnewline
10 & -0.82 & 4 & 18 & -0.64 & 3 & 11 & -0.57 \tabularnewline
11 & -0.95 & 4 & 22 & -0.69 & 4 & 14 & -0.56 \tabularnewline
12 & -0.83 & 2 & 12 & -0.71 & 2 & 8 & -0.6 \tabularnewline
13 & 0.14 & 9 & 7 & 0.12 & 9 & 5 & 0.29 \tabularnewline
14 & -1 & 2 & 18 & -0.8 & 1 & 11 & -0.83 \tabularnewline
15 & -1.23 & 1 & 17 & -0.89 & 1 & 9 & -0.8 \tabularnewline
16 & -1.4 & 1 & 8 & -0.78 & 1 & 4 & -0.6 \tabularnewline
17 & -0.84 & 3 & 19 & -0.73 & 2 & 13 & -0.73 \tabularnewline
18 & -1.56 & 1 & 26 & -0.93 & 1 & 15 & -0.88 \tabularnewline
19 & -1.65 & 0 & 28 & -1 & 0 & 16 & -1 \tabularnewline
20 & -1.23 & 0 & 16 & -1 & 0 & 11 & -1 \tabularnewline
21 & -1.27 & 1 & 20 & -0.9 & 1 & 13 & -0.86 \tabularnewline
22 & -0.77 & 4 & 14 & -0.56 & 4 & 9 & -0.38 \tabularnewline
23 & -1.35 & 0 & 23 & -1 & 0 & 15 & -1 \tabularnewline
24 & -1.25 & 1 & 11 & -0.83 & 1 & 7 & -0.75 \tabularnewline
25 & -0.89 & 4 & 21 & -0.68 & 3 & 13 & -0.62 \tabularnewline
26 & -1.64 & 0 & 23 & -1 & 0 & 13 & -1 \tabularnewline
27 & -1.64 & 0 & 23 & -1 & 0 & 13 & -1 \tabularnewline
28 & -1.25 & 1 & 16 & -0.88 & 1 & 10 & -0.82 \tabularnewline
29 & -1 & 1 & 15 & -0.88 & 1 & 9 & -0.8 \tabularnewline
30 & -0.79 & 4 & 15 & -0.58 & 4 & 9 & -0.38 \tabularnewline
31 & -1.43 & 1 & 21 & -0.91 & 1 & 13 & -0.86 \tabularnewline
32 & -1.57 & 0 & 11 & -1 & 0 & 6 & -1 \tabularnewline
33 & -1.33 & 1 & 17 & -0.89 & 1 & 9 & -0.8 \tabularnewline
34 & -1.25 & 1 & 16 & -0.88 & 1 & 8 & -0.78 \tabularnewline
35 & -1.25 & 0 & 15 & -1 & 0 & 8 & -1 \tabularnewline
36 & -1.44 & 2 & 28 & -0.87 & 2 & 15 & -0.76 \tabularnewline
37 & -1.33 & 1 & 13 & -0.86 & 1 & 7 & -0.75 \tabularnewline
38 & -0.73 & 2 & 10 & -0.67 & 2 & 6 & -0.5 \tabularnewline
39 & -1.23 & 0 & 16 & -1 & 0 & 10 & -1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=8539&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]-0.47[/C][C]7[/C][C]16[/C][C]-0.39[/C][C]6[/C][C]9[/C][C]-0.2[/C][/ROW]
[ROW][C]2[/C][C]-0.05[/C][C]13[/C][C]14[/C][C]-0.04[/C][C]9[/C][C]8[/C][C]0.06[/C][/ROW]
[ROW][C]3[/C][C]-0.82[/C][C]3[/C][C]17[/C][C]-0.7[/C][C]3[/C][C]10[/C][C]-0.54[/C][/ROW]
[ROW][C]4[/C][C]-0.5[/C][C]7[/C][C]16[/C][C]-0.39[/C][C]7[/C][C]10[/C][C]-0.18[/C][/ROW]
[ROW][C]5[/C][C]-1.07[/C][C]3[/C][C]19[/C][C]-0.73[/C][C]3[/C][C]11[/C][C]-0.57[/C][/ROW]
[ROW][C]6[/C][C]-0.44[/C][C]7[/C][C]15[/C][C]-0.36[/C][C]4[/C][C]9[/C][C]-0.38[/C][/ROW]
[ROW][C]7[/C][C]-0.54[/C][C]5[/C][C]12[/C][C]-0.41[/C][C]4[/C][C]6[/C][C]-0.2[/C][/ROW]
[ROW][C]8[/C][C]0.17[/C][C]11[/C][C]8[/C][C]0.16[/C][C]10[/C][C]6[/C][C]0.25[/C][/ROW]
[ROW][C]9[/C][C]-0.59[/C][C]3[/C][C]13[/C][C]-0.62[/C][C]3[/C][C]9[/C][C]-0.5[/C][/ROW]
[ROW][C]10[/C][C]-0.82[/C][C]4[/C][C]18[/C][C]-0.64[/C][C]3[/C][C]11[/C][C]-0.57[/C][/ROW]
[ROW][C]11[/C][C]-0.95[/C][C]4[/C][C]22[/C][C]-0.69[/C][C]4[/C][C]14[/C][C]-0.56[/C][/ROW]
[ROW][C]12[/C][C]-0.83[/C][C]2[/C][C]12[/C][C]-0.71[/C][C]2[/C][C]8[/C][C]-0.6[/C][/ROW]
[ROW][C]13[/C][C]0.14[/C][C]9[/C][C]7[/C][C]0.12[/C][C]9[/C][C]5[/C][C]0.29[/C][/ROW]
[ROW][C]14[/C][C]-1[/C][C]2[/C][C]18[/C][C]-0.8[/C][C]1[/C][C]11[/C][C]-0.83[/C][/ROW]
[ROW][C]15[/C][C]-1.23[/C][C]1[/C][C]17[/C][C]-0.89[/C][C]1[/C][C]9[/C][C]-0.8[/C][/ROW]
[ROW][C]16[/C][C]-1.4[/C][C]1[/C][C]8[/C][C]-0.78[/C][C]1[/C][C]4[/C][C]-0.6[/C][/ROW]
[ROW][C]17[/C][C]-0.84[/C][C]3[/C][C]19[/C][C]-0.73[/C][C]2[/C][C]13[/C][C]-0.73[/C][/ROW]
[ROW][C]18[/C][C]-1.56[/C][C]1[/C][C]26[/C][C]-0.93[/C][C]1[/C][C]15[/C][C]-0.88[/C][/ROW]
[ROW][C]19[/C][C]-1.65[/C][C]0[/C][C]28[/C][C]-1[/C][C]0[/C][C]16[/C][C]-1[/C][/ROW]
[ROW][C]20[/C][C]-1.23[/C][C]0[/C][C]16[/C][C]-1[/C][C]0[/C][C]11[/C][C]-1[/C][/ROW]
[ROW][C]21[/C][C]-1.27[/C][C]1[/C][C]20[/C][C]-0.9[/C][C]1[/C][C]13[/C][C]-0.86[/C][/ROW]
[ROW][C]22[/C][C]-0.77[/C][C]4[/C][C]14[/C][C]-0.56[/C][C]4[/C][C]9[/C][C]-0.38[/C][/ROW]
[ROW][C]23[/C][C]-1.35[/C][C]0[/C][C]23[/C][C]-1[/C][C]0[/C][C]15[/C][C]-1[/C][/ROW]
[ROW][C]24[/C][C]-1.25[/C][C]1[/C][C]11[/C][C]-0.83[/C][C]1[/C][C]7[/C][C]-0.75[/C][/ROW]
[ROW][C]25[/C][C]-0.89[/C][C]4[/C][C]21[/C][C]-0.68[/C][C]3[/C][C]13[/C][C]-0.62[/C][/ROW]
[ROW][C]26[/C][C]-1.64[/C][C]0[/C][C]23[/C][C]-1[/C][C]0[/C][C]13[/C][C]-1[/C][/ROW]
[ROW][C]27[/C][C]-1.64[/C][C]0[/C][C]23[/C][C]-1[/C][C]0[/C][C]13[/C][C]-1[/C][/ROW]
[ROW][C]28[/C][C]-1.25[/C][C]1[/C][C]16[/C][C]-0.88[/C][C]1[/C][C]10[/C][C]-0.82[/C][/ROW]
[ROW][C]29[/C][C]-1[/C][C]1[/C][C]15[/C][C]-0.88[/C][C]1[/C][C]9[/C][C]-0.8[/C][/ROW]
[ROW][C]30[/C][C]-0.79[/C][C]4[/C][C]15[/C][C]-0.58[/C][C]4[/C][C]9[/C][C]-0.38[/C][/ROW]
[ROW][C]31[/C][C]-1.43[/C][C]1[/C][C]21[/C][C]-0.91[/C][C]1[/C][C]13[/C][C]-0.86[/C][/ROW]
[ROW][C]32[/C][C]-1.57[/C][C]0[/C][C]11[/C][C]-1[/C][C]0[/C][C]6[/C][C]-1[/C][/ROW]
[ROW][C]33[/C][C]-1.33[/C][C]1[/C][C]17[/C][C]-0.89[/C][C]1[/C][C]9[/C][C]-0.8[/C][/ROW]
[ROW][C]34[/C][C]-1.25[/C][C]1[/C][C]16[/C][C]-0.88[/C][C]1[/C][C]8[/C][C]-0.78[/C][/ROW]
[ROW][C]35[/C][C]-1.25[/C][C]0[/C][C]15[/C][C]-1[/C][C]0[/C][C]8[/C][C]-1[/C][/ROW]
[ROW][C]36[/C][C]-1.44[/C][C]2[/C][C]28[/C][C]-0.87[/C][C]2[/C][C]15[/C][C]-0.76[/C][/ROW]
[ROW][C]37[/C][C]-1.33[/C][C]1[/C][C]13[/C][C]-0.86[/C][C]1[/C][C]7[/C][C]-0.75[/C][/ROW]
[ROW][C]38[/C][C]-0.73[/C][C]2[/C][C]10[/C][C]-0.67[/C][C]2[/C][C]6[/C][C]-0.5[/C][/ROW]
[ROW][C]39[/C][C]-1.23[/C][C]0[/C][C]16[/C][C]-1[/C][C]0[/C][C]10[/C][C]-1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=8539&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=8539&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of survey scores (median of Likert score was subtracted)
QuestionmeanSum ofpositives (Ps)Sum ofnegatives (Ns)(Ps-Ns)/(Ps+Ns)Count ofpositives (Pc)Count ofnegatives (Nc)(Pc-Nc)/(Pc+Nc)
1-0.47716-0.3969-0.2
2-0.051314-0.04980.06
3-0.82317-0.7310-0.54
4-0.5716-0.39710-0.18
5-1.07319-0.73311-0.57
6-0.44715-0.3649-0.38
7-0.54512-0.4146-0.2
80.171180.161060.25
9-0.59313-0.6239-0.5
10-0.82418-0.64311-0.57
11-0.95422-0.69414-0.56
12-0.83212-0.7128-0.6
130.14970.12950.29
14-1218-0.8111-0.83
15-1.23117-0.8919-0.8
16-1.418-0.7814-0.6
17-0.84319-0.73213-0.73
18-1.56126-0.93115-0.88
19-1.65028-1016-1
20-1.23016-1011-1
21-1.27120-0.9113-0.86
22-0.77414-0.5649-0.38
23-1.35023-1015-1
24-1.25111-0.8317-0.75
25-0.89421-0.68313-0.62
26-1.64023-1013-1
27-1.64023-1013-1
28-1.25116-0.88110-0.82
29-1115-0.8819-0.8
30-0.79415-0.5849-0.38
31-1.43121-0.91113-0.86
32-1.57011-106-1
33-1.33117-0.8919-0.8
34-1.25116-0.8818-0.78
35-1.25015-108-1
36-1.44228-0.87215-0.76
37-1.33113-0.8617-0.75
38-0.73210-0.6726-0.5
39-1.23016-1010-1






Pearson correlation matrix of survey scores
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean10.948717685937550.93108296784099
(Ps-Ns)/(Ps+Ns)0.9487176859375510.982884693820154
(Pc-Nc)/(Pc+Nc)0.931082967840990.9828846938201541

\begin{tabular}{lllllllll}
\hline
Pearson correlation matrix of survey scores \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 & 0.94871768593755 & 0.93108296784099 \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.94871768593755 & 1 & 0.982884693820154 \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.93108296784099 & 0.982884693820154 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=8539&T=2

[TABLE]
[ROW][C]Pearson correlation matrix of survey scores[/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[/C][C]0.94871768593755[/C][C]0.93108296784099[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.94871768593755[/C][C]1[/C][C]0.982884693820154[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.93108296784099[/C][C]0.982884693820154[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=8539&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=8539&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Pearson correlation matrix of survey scores
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean10.948717685937550.93108296784099
(Ps-Ns)/(Ps+Ns)0.9487176859375510.982884693820154
(Pc-Nc)/(Pc+Nc)0.931082967840990.9828846938201541






Kendall tau rank correlation matrix of survey scores
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean10.7763897597924770.725111947751273
(Ps-Ns)/(Ps+Ns)0.77638975979247710.917621968051077
(Pc-Nc)/(Pc+Nc)0.7251119477512730.9176219680510771

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlation matrix of survey scores \tabularnewline
 & mean & (Ps-Ns)/(Ps+Ns) & (Pc-Nc)/(Pc+Nc) \tabularnewline
mean & 1 & 0.776389759792477 & 0.725111947751273 \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.776389759792477 & 1 & 0.917621968051077 \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.725111947751273 & 0.917621968051077 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=8539&T=3

[TABLE]
[ROW][C]Kendall tau rank correlation matrix of survey scores[/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[/C][C]0.776389759792477[/C][C]0.725111947751273[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.776389759792477[/C][C]1[/C][C]0.917621968051077[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.725111947751273[/C][C]0.917621968051077[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=8539&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=8539&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Kendall tau rank correlation matrix of survey scores
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean10.7763897597924770.725111947751273
(Ps-Ns)/(Ps+Ns)0.77638975979247710.917621968051077
(Pc-Nc)/(Pc+Nc)0.7251119477512730.9176219680510771


Figures (Output of Computation)

Input Parameters & R Code

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):
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])
}
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 correlation matrix of survey scores',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,cor(myresult[,1],myresult[,1],method='pearson'))
a<-table.element(a,cor(myresult[,1],myresult[,4],method='pearson'))
a<-table.element(a,cor(myresult[,1],myresult[,7],method='pearson'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,cor(myresult[,4],myresult[,1],method='pearson'))
a<-table.element(a,cor(myresult[,4],myresult[,4],method='pearson'))
a<-table.element(a,cor(myresult[,4],myresult[,7],method='pearson'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,cor(myresult[,7],myresult[,1],method='pearson'))
a<-table.element(a,cor(myresult[,7],myresult[,4],method='pearson'))
a<-table.element(a,cor(myresult[,7],myresult[,7],method='pearson'))
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 correlation matrix of survey scores',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,cor(myresult[,1],myresult[,1],method='kendall'))
a<-table.element(a,cor(myresult[,1],myresult[,4],method='kendall'))
a<-table.element(a,cor(myresult[,1],myresult[,7],method='kendall'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Ps-Ns)/(Ps+Ns)',header=TRUE)
a<-table.element(a,cor(myresult[,4],myresult[,1],method='kendall'))
a<-table.element(a,cor(myresult[,4],myresult[,4],method='kendall'))
a<-table.element(a,cor(myresult[,4],myresult[,7],method='kendall'))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'(Pc-Nc)/(Pc+Nc)',header=TRUE)
a<-table.element(a,cor(myresult[,7],myresult[,1],method='kendall'))
a<-table.element(a,cor(myresult[,7],myresult[,4],method='kendall'))
a<-table.element(a,cor(myresult[,7],myresult[,7],method='kendall'))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')