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Free Statistics

of Irreproducible Research!

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 computationWed, 10 Dec 2014 12:46:37 +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/10/t14182157426k1kdunc60vdfg0.htm/, Retrieved Thu, 12 Feb 2026 05:32:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265051, Retrieved Thu, 12 Feb 2026 05:32:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact352

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Survey Scores] [Kendall Tau NUMCAL] [2014-12-10 12:46:37] [ddb851b9ced255c1d64c58a7ca49fb28] [Current]
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1 1 0 0 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 0 1 1 1
0 1 1 1 1 0 1 1 1 0 1 1 1 1
1 1 1 0 1 1 1 1 1 1 0 1 1 1
1 1 0 1 1 1 1 1 1 1 1 1 1 1
1 1 0 1 1 1 1 1 1 1 1 1 1 1
0 1 1 0 0 1 1 1 1 1 0 1 1 0
1 1 1 1 0 1 1 1 1 1 0 1 1 1
0 1 1 1 1 1 1 1 1 1 0 1 1 1
1 0 1 1 1 1 1 1 1 1 1 1 1 0
0 1 0 1 1 1 1 1 1 1 1 1 1 1
0 0 1 1 1 1 1 1 1 1 0 1 1 0
0 1 0 0 1 0 1 1 0 1 0 1 1 1
0 1 1 0 1 1 1 1 1 1 1 1 1 0
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 0 0 1 1 1 1 1 1 1 0 1 1 0
0 1 0 1 1 0 0 0 1 0 0 1 1 0
0 1 0 0 0 1 0 0 0 0 0 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 0 0 1 0 1 1 0 1 0 1 1 0
1 1 1 1 1 1 1 1 1 1 0 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 0 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 0 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 0 1 1 0
1 1 1 1 1 1 1 1 0 0 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 0
0 1 1 1 1 1 1 1 1 1 0 1 1 1
1 1 1 1 0 0 1 1 0 1 0 1 1 0
1 1 1 0 1 1 1 1 1 1 1 1 1 0
0 1 1 1 1 0 1 0 1 0 1 1 1 1
0 0 0 1 1 0 1 0 1 1 1 1 1 0
1 0 1 1 1 0 0 0 0 0 1 1 1 0
1 0 0 1 0 1 1 1 1 1 1 1 1 1
0 1 1 1 1 0 1 0 1 1 1 1 1 0
0 0 1 1 1 1 1 1 1 1 1 1 1 0
0 1 0 0 0 1 1 1 1 1 1 1 1 0
0 1 0 0 1 1 1 1 1 1 1 1 1 0
1 0 0 0 0 1 1 1 1 1 1 0 1 0
0 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 0 1 1 0
0 1 1 0 1 0 0 0 1 0 1 1 1 1
0 0 1 0 0 0 0 0 0 0 1 1 1 1
0 0 1 1 1 0 0 1 0 0 0 0 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 0 0 1 1 0 1 1 0 0 0 1 1 1
1 1 0 1 1 1 1 1 1 1 1 1 1 1
1 1 0 0 1 0 1 0 1 1 1 1 1 1
0 1 1 0 0 1 1 1 1 1 0 1 1 0
1 1 1 1 1 0 0 0 0 0 0 1 1 1
1 1 1 0 1 1 1 1 1 1 1 1 1 1
0 0 0 1 0 1 1 1 1 1 0 1 1 1
0 1 0 1 0 0 1 1 0 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 0 0 0 0 0 1 1 0 1 0 1 1 1
1 1 1 0 1 0 0 0 0 0 1 1 1 0
0 1 0 1 1 1 1 1 1 1 1 1 1 0
0 1 0 0 1 0 1 0 1 1 1 1 1 0
0 1 1 1 0 0 0 1 0 0 0 1 1 1
0 0 0 0 0 1 1 1 0 0 1 1 1 1
0 1 1 1 1 1 1 1 1 1 0 1 1 0
1 1 1 1 1 1 1 1 1 1 0 1 1 1
1 1 1 1 1 1 1 1 1 1 0 1 1 1
0 1 1 1 0 0 1 1 0 1 0 1 1 0
1 0 1 1 1 1 1 1 1 1 0 1 1 1
0 0 1 1 1 0 1 0 0 0 1 1 1 0
0 0 0 1 1 0 1 1 0 0 0 1 1 0
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 0 1 1 0 1 1 1 1 0 1 1 1
0 1 1 1 1 1 0 1 0 0 0 1 1 0
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
1 0 0 0 1 1 0 1 0 0 0 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 0 0 0 0 0 0 0 0 0
0 1 1 0 1 1 1 1 0 0 0 1 1 1
0 1 1 0 1 1 1 1 1 1 1 1 0 1
0 1 0 0 0 1 1 1 1 1 1 1 1 0
0 1 1 0 0 0 1 1 0 0 0 1 1 0
0 1 0 0 0 1 0 1 1 0 0 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 0 1 1 1 1 1 1 1 1 1 1 0
1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 0 1 1 1 1 1 1 1 1 1 1
0 0 1 1 1 0 1 0 1 1 1 1 0 0
1 1 1 1 1 1 1 1 1 1 1 1 1 0
1 1 1 1 1 1 1 1 1 1 0 1 1 1
1 1 1 1 1 1 1 1 0 0 1 1 1 1
1 0 1 1 1 1 1 1 1 1 1 1 1 1
0 1 0 1 1 1 1 1 1 1 1 1 1 1
1 0 1 1 1 0 1 1 0 1 0 1 1 0
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 0 1 1 0 0 1 1 1 0
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 0
1 1 1 1 0 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 0
1 1 1 1 1 1 0 1 0 0 0 1 1 0
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 0 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 0 0 1 1 1 1 1 1 1 0 1 1 1
0 0 1 1 1 1 1 1 1 1 0 1 1 1
0 1 1 1 1 1 1 1 0 0 0 1 1 1
0 1 1 1 1 1 1 1 1 1 0 1 1 0
0 0 1 1 1 0 1 0 0 0 1 1 1 0
0 1 1 1 1 0 1 0 1 1 0 1 1 1
0 1 1 1 1 1 1 1 1 1 0 1 1 0
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 0 1 1 1 1 1 1 0 0 0 1 1 0
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 0 1 1 1 1 1 1 1 0 1 1 0
0 0 1 1 1 1 1 1 0 0 1 1 1 1
0 0 0 1 1 1 1 1 1 1 1 1 1 0
0 0 1 0 0 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 0 1 0 1 1 0 1 1 0
1 0 0 1 1 1 1 1 1 1 1 1 1 1
0 1 1 0 1 1 1 1 1 1 1 1 1 1
0 0 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 0 1 0 1 0 0 0 1 1 1 1
0 1 1 1 1 1 1 1 1 1 0 1 1 1
1 0 0 0 0 1 0 1 0 0 1 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 0
0 1 0 1 1 0 1 1 1 0 0 1 1 0
1 0 1 1 1 1 1 1 1 1 0 1 1 1
0 0 1 0 1 1 0 1 1 0 0 1 1 0
1 0 0 1 0 1 0 1 1 0 1 1 1 1
1 0 1 1 1 1 1 1 1 1 0 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 0 1 1 1 1 1 1 1 1 0 1 1 1
0 1 0 1 1 1 1 1 1 1 1 1 1 1
0 0 0 0 0 0 1 0 1 0 1 1 1 0
0 1 0 1 1 1 0 1 1 0 1 1 1 0
0 1 0 1 1 1 1 1 1 1 1 1 1 0
0 1 1 1 1 1 1 1 1 1 0 1 1 1
0 1 1 1 1 1 1 1 1 1 1 0 0 0
0 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 0 0 1 1 1 1 1 1 1 1 1 1 1
0 0 1 0 0 1 0 1 1 0 0 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 0 1 0 1 1 1 1 1 1 1 1 1
0 1 0 1 1 0 1 0 1 0 1 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 0 1 0 0 0 0 1 1 0
1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 0 1 1 1 1 1 1 1 1 1 1
0 0 1 1 1 1 1 1 1 1 1 1 1 0
1 1 1 1 1 1 1 1 0 0 1 1 1 1
0 1 1 1 0 0 1 1 1 0 1 1 1 1
1 1 1 1 1 1 1 1 1 1 0 1 1 0
0 1 0 0 0 0 1 1 0 0 1 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 0
0 1 0 1 1 1 1 1 0 0 0 1 1 0
0 1 0 1 1 0 1 0 1 1 1 1 1 1
1 1 1 1 0 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 0 1 1 0
0 1 1 1 1 1 0 1 1 0 0 1 1 0
0 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 0 1 1 0 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 0 1 1 1 0 1 0 0 0 0 1 1 0
1 1 0 1 1 1 1 1 1 1 1 1 1 0
1 1 1 1 1 1 1 1 1 1 0 1 1 0
1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 0 1 1 1 1 1 1 1 1 1 0
1 1 1 1 1 1 1 1 0 1 1 1 1 0
0 1 0 1 1 0 0 0 0 0 0 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 0 1 1 0
0 0 1 0 0 1 1 1 1 1 1 1 1 1
1 1 1 1 1 0 1 0 0 0 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 0 1 1 1 1 1 1 1 1 1 1
0 1 1 0 1 1 1 1 1 1 0 1 1 1
0 0 0 0 1 1 0 1 1 0 1 0 0 0
1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 0 1 1 0 0 1 0 0 0 1 1 0
0 1 1 1 1 1 1 1 1 1 0 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 0 1 1 1
1 0 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 0 1 1 0 1 0 1 1 0
0 1 1 1 1 0 1 0 0 1 0 1 1 1
0 1 0 1 1 1 1 1 1 1 1 1 1 0
0 0 1 0 1 0 1 1 0 1 0 1 1 0
0 1 0 1 0 1 0 1 1 0 1 1 1 0
1 1 1 1 1 1 1 1 1 1 1 1 1 0
0 1 1 1 1 0 1 0 0 0 1 1 1 0
0 0 1 1 1 0 1 0 1 1 1 1 1 0
1 1 1 1 1 1 1 0 0 0 0 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 0
0 0 1 1 1 0 0 0 0 0 1 1 1 0
1 1 0 1 1 1 1 1 1 1 0 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 0 1 1 0
0 1 1 1 1 1 1 1 1 1 0 1 1 0
0 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 0 1 1 1 1 1 1 0 1 1 0
0 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 0 1 1 1 1 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 0 1 1 1
0 1 1 0 1 1 1 1 1 1 1 1 1 0
0 0 0 0 0 1 1 1 1 1 1 1 1 0
0 1 1 1 1 1 1 1 1 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 0 1 1 1
1 1 1 0 1 0 1 1 0 1 1 1 1 1
0 1 1 1 1 1 1 1 1 1 0 0 0 0

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time20 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 20 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265051&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]20 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265051&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265051&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 time20 seconds
R Server'Gwilym Jenkins' @ jenkins.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)
10.1212.51400.214252800.21
20.28276.5760.575531520.57
30.2426191.50.485221830.48
40.18238114.50.354762290.35
50.36303.5490.72607980.72
60.3730547.50.73610950.73
70.3831042.50.76620850.76
80.4318.5340.81637680.81
90.3630349.50.72606990.72
100.31285.5670.625711340.62
110.24260.5920.485211840.48
120.4734210.50.94684210.94
130.4633913.50.92678270.92
140.25265.5870.515311740.51

\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 & 0.1 & 212.5 & 140 & 0.21 & 425 & 280 & 0.21 \tabularnewline
2 & 0.28 & 276.5 & 76 & 0.57 & 553 & 152 & 0.57 \tabularnewline
3 & 0.24 & 261 & 91.5 & 0.48 & 522 & 183 & 0.48 \tabularnewline
4 & 0.18 & 238 & 114.5 & 0.35 & 476 & 229 & 0.35 \tabularnewline
5 & 0.36 & 303.5 & 49 & 0.72 & 607 & 98 & 0.72 \tabularnewline
6 & 0.37 & 305 & 47.5 & 0.73 & 610 & 95 & 0.73 \tabularnewline
7 & 0.38 & 310 & 42.5 & 0.76 & 620 & 85 & 0.76 \tabularnewline
8 & 0.4 & 318.5 & 34 & 0.81 & 637 & 68 & 0.81 \tabularnewline
9 & 0.36 & 303 & 49.5 & 0.72 & 606 & 99 & 0.72 \tabularnewline
10 & 0.31 & 285.5 & 67 & 0.62 & 571 & 134 & 0.62 \tabularnewline
11 & 0.24 & 260.5 & 92 & 0.48 & 521 & 184 & 0.48 \tabularnewline
12 & 0.47 & 342 & 10.5 & 0.94 & 684 & 21 & 0.94 \tabularnewline
13 & 0.46 & 339 & 13.5 & 0.92 & 678 & 27 & 0.92 \tabularnewline
14 & 0.25 & 265.5 & 87 & 0.51 & 531 & 174 & 0.51 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265051&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]0.1[/C][C]212.5[/C][C]140[/C][C]0.21[/C][C]425[/C][C]280[/C][C]0.21[/C][/ROW]
[ROW][C]2[/C][C]0.28[/C][C]276.5[/C][C]76[/C][C]0.57[/C][C]553[/C][C]152[/C][C]0.57[/C][/ROW]
[ROW][C]3[/C][C]0.24[/C][C]261[/C][C]91.5[/C][C]0.48[/C][C]522[/C][C]183[/C][C]0.48[/C][/ROW]
[ROW][C]4[/C][C]0.18[/C][C]238[/C][C]114.5[/C][C]0.35[/C][C]476[/C][C]229[/C][C]0.35[/C][/ROW]
[ROW][C]5[/C][C]0.36[/C][C]303.5[/C][C]49[/C][C]0.72[/C][C]607[/C][C]98[/C][C]0.72[/C][/ROW]
[ROW][C]6[/C][C]0.37[/C][C]305[/C][C]47.5[/C][C]0.73[/C][C]610[/C][C]95[/C][C]0.73[/C][/ROW]
[ROW][C]7[/C][C]0.38[/C][C]310[/C][C]42.5[/C][C]0.76[/C][C]620[/C][C]85[/C][C]0.76[/C][/ROW]
[ROW][C]8[/C][C]0.4[/C][C]318.5[/C][C]34[/C][C]0.81[/C][C]637[/C][C]68[/C][C]0.81[/C][/ROW]
[ROW][C]9[/C][C]0.36[/C][C]303[/C][C]49.5[/C][C]0.72[/C][C]606[/C][C]99[/C][C]0.72[/C][/ROW]
[ROW][C]10[/C][C]0.31[/C][C]285.5[/C][C]67[/C][C]0.62[/C][C]571[/C][C]134[/C][C]0.62[/C][/ROW]
[ROW][C]11[/C][C]0.24[/C][C]260.5[/C][C]92[/C][C]0.48[/C][C]521[/C][C]184[/C][C]0.48[/C][/ROW]
[ROW][C]12[/C][C]0.47[/C][C]342[/C][C]10.5[/C][C]0.94[/C][C]684[/C][C]21[/C][C]0.94[/C][/ROW]
[ROW][C]13[/C][C]0.46[/C][C]339[/C][C]13.5[/C][C]0.92[/C][C]678[/C][C]27[/C][C]0.92[/C][/ROW]
[ROW][C]14[/C][C]0.25[/C][C]265.5[/C][C]87[/C][C]0.51[/C][C]531[/C][C]174[/C][C]0.51[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265051&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265051&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)
10.1212.51400.214252800.21
20.28276.5760.575531520.57
30.2426191.50.485221830.48
40.18238114.50.354762290.35
50.36303.5490.72607980.72
60.3730547.50.73610950.73
70.3831042.50.76620850.76
80.4318.5340.81637680.81
90.3630349.50.72606990.72
100.31285.5670.625711340.62
110.24260.5920.485211840.48
120.4734210.50.94684210.94
130.4633913.50.92678270.92
140.25265.5870.515311740.51






Pearson correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)1 (0)1 (0)
(Ps-Ns)/(Ps+Ns)1 (0)1 (0)1 (0)
(Pc-Nc)/(Pc+Nc)1 (0)1 (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) & 1 (0) & 1 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0) & 1 (0) & 1 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 1 (0) & 1 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265051&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]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]1 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265051&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265051&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)1 (0)1 (0)
(Ps-Ns)/(Ps+Ns)1 (0)1 (0)1 (0)
(Pc-Nc)/(Pc+Nc)1 (0)1 (0)1 (0)






Kendall tau rank correlations of survey scores (and p-values)
mean(Ps-Ns)/(Ps+Ns)(Pc-Nc)/(Pc+Nc)
mean1 (0)1 (0)1 (0)
(Ps-Ns)/(Ps+Ns)1 (0)1 (0)1 (0)
(Pc-Nc)/(Pc+Nc)1 (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) & 1 (0) & 1 (0) \tabularnewline
(Ps-Ns)/(Ps+Ns) & 1 (0) & 1 (0) & 1 (0) \tabularnewline
(Pc-Nc)/(Pc+Nc) & 1 (0) & 1 (0) & 1 (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265051&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]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Ps-Ns)/(Ps+Ns)[/C][C]1 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[ROW][C](Pc-Nc)/(Pc+Nc)[/C][C]1 (0)[/C][C]1 (0)[/C][C]1 (0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265051&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265051&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)1 (0)1 (0)
(Ps-Ns)/(Ps+Ns)1 (0)1 (0)1 (0)
(Pc-Nc)/(Pc+Nc)1 (0)1 (0)1 (0)


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 1 ;
Parameters (R input):
par1 = 0 1 ;
R code (references can be found in the software module):
par1 <- '1 2 3 4 5 6 7 8 9 10 11 12 13 14'
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')