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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_surveyscores.wasp
Title produced by softwareSurvey Scores
Date of computationTue, 09 Dec 2014 09:55:05 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/09/t1418118974x8mtndb0wx257tz.htm/, Retrieved Thu, 16 May 2024 21:33:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264376, Retrieved Thu, 16 May 2024 21:33:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [Intrinsic Motivat...] [2010-10-12 11:18:40] [b98453cac15ba1066b407e146608df68]
- R PD  [Survey Scores] [] [2011-10-18 12:18:26] [b98453cac15ba1066b407e146608df68]
- RM      [Survey Scores] [Question 1] [2014-10-15 11:59:48] [6795cd14e59cd8fafcdf800c40b889d9]
-   PD      [Survey Scores] [Perfectionisme ] [2014-12-08 21:11:04] [6795cd14e59cd8fafcdf800c40b889d9]
-    D          [Survey Scores] [depression intrin...] [2014-12-09 09:55:05] [a9a71eb17c5e64a5660208fb3c309b9e] [Current]
-    D            [Survey Scores] [DEPRESSION EXTR] [2014-12-09 10:09:21] [6795cd14e59cd8fafcdf800c40b889d9]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264376&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264376&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264376&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 computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






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)
10.84109160.7485150.7
2-0.054046-0.073541-0.08
30.6889140.7376140.69
40.7493110.7978100.77
51.1212730.959930.94
6-0.264372-0.253757-0.21
70.0751430.0948360.14
80.2959270.3747250.31
9-0.741294-0.771175-0.74
100.5875110.7468110.72
110.1455390.1750360.16
12-0.283667-0.33154-0.27
13-0.143853-0.163448-0.17
140.2662330.3154270.33
150.9411170.889350.9
16-0.353473-0.362864-0.39
170.679120.7466100.74
180.1952310.2549280.27
190.7495130.7676120.73
20-0.283061-0.342854-0.32
21-0.134054-0.153550-0.18

\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 & 0.84 & 109 & 16 & 0.74 & 85 & 15 & 0.7 \tabularnewline
2 & -0.05 & 40 & 46 & -0.07 & 35 & 41 & -0.08 \tabularnewline
3 & 0.68 & 89 & 14 & 0.73 & 76 & 14 & 0.69 \tabularnewline
4 & 0.74 & 93 & 11 & 0.79 & 78 & 10 & 0.77 \tabularnewline
5 & 1.12 & 127 & 3 & 0.95 & 99 & 3 & 0.94 \tabularnewline
6 & -0.26 & 43 & 72 & -0.25 & 37 & 57 & -0.21 \tabularnewline
7 & 0.07 & 51 & 43 & 0.09 & 48 & 36 & 0.14 \tabularnewline
8 & 0.29 & 59 & 27 & 0.37 & 47 & 25 & 0.31 \tabularnewline
9 & -0.74 & 12 & 94 & -0.77 & 11 & 75 & -0.74 \tabularnewline
10 & 0.58 & 75 & 11 & 0.74 & 68 & 11 & 0.72 \tabularnewline
11 & 0.14 & 55 & 39 & 0.17 & 50 & 36 & 0.16 \tabularnewline
12 & -0.28 & 36 & 67 & -0.3 & 31 & 54 & -0.27 \tabularnewline
13 & -0.14 & 38 & 53 & -0.16 & 34 & 48 & -0.17 \tabularnewline
14 & 0.26 & 62 & 33 & 0.31 & 54 & 27 & 0.33 \tabularnewline
15 & 0.94 & 111 & 7 & 0.88 & 93 & 5 & 0.9 \tabularnewline
16 & -0.35 & 34 & 73 & -0.36 & 28 & 64 & -0.39 \tabularnewline
17 & 0.6 & 79 & 12 & 0.74 & 66 & 10 & 0.74 \tabularnewline
18 & 0.19 & 52 & 31 & 0.25 & 49 & 28 & 0.27 \tabularnewline
19 & 0.74 & 95 & 13 & 0.76 & 76 & 12 & 0.73 \tabularnewline
20 & -0.28 & 30 & 61 & -0.34 & 28 & 54 & -0.32 \tabularnewline
21 & -0.13 & 40 & 54 & -0.15 & 35 & 50 & -0.18 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264376&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]0.84[/C][C]109[/C][C]16[/C][C]0.74[/C][C]85[/C][C]15[/C][C]0.7[/C][/ROW]
[ROW][C]2[/C][C]-0.05[/C][C]40[/C][C]46[/C][C]-0.07[/C][C]35[/C][C]41[/C][C]-0.08[/C][/ROW]
[ROW][C]3[/C][C]0.68[/C][C]89[/C][C]14[/C][C]0.73[/C][C]76[/C][C]14[/C][C]0.69[/C][/ROW]
[ROW][C]4[/C][C]0.74[/C][C]93[/C][C]11[/C][C]0.79[/C][C]78[/C][C]10[/C][C]0.77[/C][/ROW]
[ROW][C]5[/C][C]1.12[/C][C]127[/C][C]3[/C][C]0.95[/C][C]99[/C][C]3[/C][C]0.94[/C][/ROW]
[ROW][C]6[/C][C]-0.26[/C][C]43[/C][C]72[/C][C]-0.25[/C][C]37[/C][C]57[/C][C]-0.21[/C][/ROW]
[ROW][C]7[/C][C]0.07[/C][C]51[/C][C]43[/C][C]0.09[/C][C]48[/C][C]36[/C][C]0.14[/C][/ROW]
[ROW][C]8[/C][C]0.29[/C][C]59[/C][C]27[/C][C]0.37[/C][C]47[/C][C]25[/C][C]0.31[/C][/ROW]
[ROW][C]9[/C][C]-0.74[/C][C]12[/C][C]94[/C][C]-0.77[/C][C]11[/C][C]75[/C][C]-0.74[/C][/ROW]
[ROW][C]10[/C][C]0.58[/C][C]75[/C][C]11[/C][C]0.74[/C][C]68[/C][C]11[/C][C]0.72[/C][/ROW]
[ROW][C]11[/C][C]0.14[/C][C]55[/C][C]39[/C][C]0.17[/C][C]50[/C][C]36[/C][C]0.16[/C][/ROW]
[ROW][C]12[/C][C]-0.28[/C][C]36[/C][C]67[/C][C]-0.3[/C][C]31[/C][C]54[/C][C]-0.27[/C][/ROW]
[ROW][C]13[/C][C]-0.14[/C][C]38[/C][C]53[/C][C]-0.16[/C][C]34[/C][C]48[/C][C]-0.17[/C][/ROW]
[ROW][C]14[/C][C]0.26[/C][C]62[/C][C]33[/C][C]0.31[/C][C]54[/C][C]27[/C][C]0.33[/C][/ROW]
[ROW][C]15[/C][C]0.94[/C][C]111[/C][C]7[/C][C]0.88[/C][C]93[/C][C]5[/C][C]0.9[/C][/ROW]
[ROW][C]16[/C][C]-0.35[/C][C]34[/C][C]73[/C][C]-0.36[/C][C]28[/C][C]64[/C][C]-0.39[/C][/ROW]
[ROW][C]17[/C][C]0.6[/C][C]79[/C][C]12[/C][C]0.74[/C][C]66[/C][C]10[/C][C]0.74[/C][/ROW]
[ROW][C]18[/C][C]0.19[/C][C]52[/C][C]31[/C][C]0.25[/C][C]49[/C][C]28[/C][C]0.27[/C][/ROW]
[ROW][C]19[/C][C]0.74[/C][C]95[/C][C]13[/C][C]0.76[/C][C]76[/C][C]12[/C][C]0.73[/C][/ROW]
[ROW][C]20[/C][C]-0.28[/C][C]30[/C][C]61[/C][C]-0.34[/C][C]28[/C][C]54[/C][C]-0.32[/C][/ROW]
[ROW][C]21[/C][C]-0.13[/C][C]40[/C][C]54[/C][C]-0.15[/C][C]35[/C][C]50[/C][C]-0.18[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264376&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264376&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)
10.84109160.7485150.7
2-0.054046-0.073541-0.08
30.6889140.7376140.69
40.7493110.7978100.77
51.1212730.959930.94
6-0.264372-0.253757-0.21
70.0751430.0948360.14
80.2959270.3747250.31
9-0.741294-0.771175-0.74
100.5875110.7468110.72
110.1455390.1750360.16
12-0.283667-0.33154-0.27
13-0.143853-0.163448-0.17
140.2662330.3154270.33
150.9411170.889350.9
16-0.353473-0.362864-0.39
170.679120.7466100.74
180.1952310.2549280.27
190.7495130.7676120.73
20-0.283061-0.342854-0.32
21-0.134054-0.153550-0.18






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.989 (0)0.988 (0)
(Ps-Ns)/(Ps+Ns)0.989 (0)1 (0)0.998 (0)
(Pc-Nc)/(Pc+Nc)0.988 (0)0.998 (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) & 0.989 (0) & 0.988 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.989 (0) & 1 (0) & 0.998 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.988 (0) & 0.998 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264376&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]0.989 (0)[/C][C]0.988 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.989 (0)[/C][C]1 (0)[/C][C]0.998 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.988 (0)[/C][C]0.998 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264376&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264376&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 correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.989 (0)0.988 (0)
(Ps-Ns)/(Ps+Ns)0.989 (0)1 (0)0.998 (0)
(Pc-Nc)/(Pc+Nc)0.988 (0)0.998 (0)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.949 (0)0.909 (0)
(Ps-Ns)/(Ps+Ns)0.949 (0)1 (0)0.964 (0)
(Pc-Nc)/(Pc+Nc)0.909 (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) & 0.949 (0) & 0.909 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 0.949 (0) & 1 (0) & 0.964 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 0.909 (0) & 0.964 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264376&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]0.949 (0)[/C][C]0.909 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]0.949 (0)[/C][C]1 (0)[/C][C]0.964 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]0.909 (0)[/C][C]0.964 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264376&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264376&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 correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)0.949 (0)0.909 (0)
(Ps-Ns)/(Ps+Ns)0.949 (0)1 (0)0.964 (0)
(Pc-Nc)/(Pc+Nc)0.909 (0)0.964 (0)1 (0)


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):
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')