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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationSat, 08 Dec 2012 08:09:23 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/08/t1354972180qwt3t5zk0nqrpgx.htm/, Retrieved Thu, 28 Mar 2024 12:02:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197574, Retrieved Thu, 28 Mar 2024 12:02:01 +0000
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IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2010-12-05 17:44:33] [b98453cac15ba1066b407e146608df68]
- R PD  [Kendall tau Correlation Matrix] [Workshop 10 Pears...] [2010-12-14 15:02:37] [a9e130f95bad0a0597234e75c6380c5a]
- RM      [Kendall tau Correlation Matrix] [WS 10 - Pearson C...] [2011-12-13 13:12:21] [95a4a8598e82ac3272c4dca488d0ba38]
- R           [Kendall tau Correlation Matrix] [] [2012-12-08 13:09:23] [8202a5611fe794f0e10e9bba0c705a45] [Current]
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Dataseries X:
0 24 14 11 12 24 26
0 25 11 7 8 25 23
0 17 6 17 8 30 25
1 18 12 10 8 19 23
1 18 8 12 9 22 19
1 16 10 12 7 22 29
1 20 10 11 4 25 25
1 16 11 11 11 23 21
1 18 16 12 7 17 22
1 17 11 13 7 21 25
0 23 13 14 12 19 24
0 30 12 16 10 19 18
1 23 8 11 10 15 22
1 18 12 10 8 16 15
1 15 11 11 8 23 22
1 12 4 15 4 27 28
0 21 9 9 9 22 20
1 15 8 11 8 14 12
1 20 8 17 7 22 24
0 31 14 17 11 23 20
0 27 15 11 9 23 21
1 34 16 18 11 21 20
1 21 9 14 13 19 21
1 31 14 10 8 18 23
1 19 11 11 8 20 28
0 16 8 15 9 23 24
1 20 9 15 6 25 24
1 21 9 13 9 19 24
1 22 9 16 9 24 23
1 17 9 13 6 22 23
1 24 10 9 6 25 29
0 25 16 18 16 26 24
0 26 11 18 5 29 18
1 25 8 12 7 32 25
1 17 9 17 9 25 21
1 32 16 9 6 29 26
1 33 11 9 6 28 22
1 13 16 12 5 17 22
1 32 12 18 12 28 22
1 25 12 12 7 29 23
1 29 14 18 10 26 30
1 22 9 14 9 25 23
1 18 10 15 8 14 17
1 17 9 16 5 25 23
0 20 10 10 8 26 23
1 15 12 11 8 20 25
1 20 14 14 10 18 24
1 33 14 9 6 32 24
0 29 10 12 8 25 23
1 23 14 17 7 25 21
0 26 16 5 4 23 24
1 18 9 12 8 21 24
0 20 10 12 8 20 28
1 11 6 6 4 15 16
1 28 8 24 20 30 20
1 26 13 12 8 24 29
0 22 10 12 8 26 27
1 17 8 14 6 24 22
0 12 7 7 4 22 28
1 14 15 13 8 14 16
1 17 9 12 9 24 25
1 21 10 13 6 24 24
1 19 12 14 7 24 28
1 18 13 8 9 24 24
0 10 10 11 5 19 23
0 29 11 9 5 31 30
1 31 8 11 8 22 24
0 19 9 13 8 27 21
1 9 13 10 6 19 25
1 20 11 11 8 25 25
1 28 8 12 7 20 22
0 19 9 9 7 21 23
0 30 9 15 9 27 26
0 29 15 18 11 23 23
0 26 9 15 6 25 25
0 23 10 12 8 20 21
1 13 14 13 6 21 25
1 21 12 14 9 22 24
1 19 12 10 8 23 29
1 28 11 13 6 25 22
1 23 14 13 10 25 27
1 18 6 11 8 17 26
0 21 12 13 8 19 22
1 20 8 16 10 25 24
1 23 14 8 5 19 27
1 21 11 16 7 20 24
1 21 10 11 5 26 24
1 15 14 9 8 23 29
1 28 12 16 14 27 22
1 19 10 12 7 17 21
1 26 14 14 8 17 24
1 10 5 8 6 19 24
0 16 11 9 5 17 23
1 22 10 15 6 22 20
1 19 9 11 10 21 27
1 31 10 21 12 32 26
0 31 16 14 9 21 25
1 29 13 18 12 21 21
0 19 9 12 7 18 21
1 22 10 13 8 18 19
1 23 10 15 10 23 21
0 15 7 12 6 19 21
0 20 9 19 10 20 16
1 18 8 15 10 21 22
1 23 14 11 10 20 29
1 25 14 11 5 17 15
1 21 8 10 7 18 17
1 24 9 13 10 19 15
1 25 14 15 11 22 21
1 17 14 12 6 15 21
1 13 8 12 7 14 19
1 28 8 16 12 18 24
0 21 8 9 11 24 20
1 25 7 18 11 35 17
0 9 6 8 11 29 23
1 16 8 13 5 21 24
1 19 6 17 8 25 14
1 17 11 9 6 20 19
1 25 14 15 9 22 24
1 20 11 8 4 13 13
1 29 11 7 4 26 22
1 14 11 12 7 17 16
1 22 14 14 11 25 19
1 15 8 6 6 20 25
0 19 20 8 7 19 25
1 20 11 17 8 21 23
0 15 8 10 4 22 24
1 20 11 11 8 24 26
1 18 10 14 9 21 26
1 33 14 11 8 26 25
1 22 11 13 11 24 18
1 16 9 12 8 16 21
1 17 9 11 5 23 26
1 16 8 9 4 18 23
0 21 10 12 8 16 23
0 26 13 20 10 26 22
1 18 13 12 6 19 20
1 18 12 13 9 21 13
1 17 8 12 9 21 24
1 22 13 12 13 22 15
1 30 14 9 9 23 14
0 30 12 15 10 29 22
1 24 14 24 20 21 10
1 21 15 7 5 21 24
1 21 13 17 11 23 22
1 29 16 11 6 27 24
1 31 9 17 9 25 19
1 20 9 11 7 21 20
0 16 9 12 9 10 13
0 22 8 14 10 20 20
1 20 7 11 9 26 22
1 28 16 16 8 24 24
1 38 11 21 7 29 29
0 22 9 14 6 19 12
1 20 11 20 13 24 20
0 17 9 13 6 19 21
1 28 14 11 8 24 24
1 22 13 15 10 22 22
0 31 16 19 16 17 20




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197574&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197574&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197574&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Correlations for all pairs of data series (method=pearson)
GenderConcMistakesDoubtsActionsParExpParCritPersonalStandardsOrganisation
Gender1-0.0540.0120.028-0.038-0.033-0.002
ConcMistakes-0.05410.3950.3290.3110.4250.054
DoubtsActions0.0120.39510.0270.154-0.0320.07
ParExp0.0280.3290.02710.5930.244-0.155
ParCrit-0.0380.3110.1540.59310.131-0.203
PersonalStandards-0.0330.425-0.0320.2440.13110.352
Organisation-0.0020.0540.07-0.155-0.2030.3521

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Gender & ConcMistakes & DoubtsActions & ParExp & ParCrit & PersonalStandards & Organisation \tabularnewline
Gender & 1 & -0.054 & 0.012 & 0.028 & -0.038 & -0.033 & -0.002 \tabularnewline
ConcMistakes & -0.054 & 1 & 0.395 & 0.329 & 0.311 & 0.425 & 0.054 \tabularnewline
DoubtsActions & 0.012 & 0.395 & 1 & 0.027 & 0.154 & -0.032 & 0.07 \tabularnewline
ParExp & 0.028 & 0.329 & 0.027 & 1 & 0.593 & 0.244 & -0.155 \tabularnewline
ParCrit & -0.038 & 0.311 & 0.154 & 0.593 & 1 & 0.131 & -0.203 \tabularnewline
PersonalStandards & -0.033 & 0.425 & -0.032 & 0.244 & 0.131 & 1 & 0.352 \tabularnewline
Organisation & -0.002 & 0.054 & 0.07 & -0.155 & -0.203 & 0.352 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197574&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Gender[/C][C]ConcMistakes[/C][C]DoubtsActions[/C][C]ParExp[/C][C]ParCrit[/C][C]PersonalStandards[/C][C]Organisation[/C][/ROW]
[ROW][C]Gender[/C][C]1[/C][C]-0.054[/C][C]0.012[/C][C]0.028[/C][C]-0.038[/C][C]-0.033[/C][C]-0.002[/C][/ROW]
[ROW][C]ConcMistakes[/C][C]-0.054[/C][C]1[/C][C]0.395[/C][C]0.329[/C][C]0.311[/C][C]0.425[/C][C]0.054[/C][/ROW]
[ROW][C]DoubtsActions[/C][C]0.012[/C][C]0.395[/C][C]1[/C][C]0.027[/C][C]0.154[/C][C]-0.032[/C][C]0.07[/C][/ROW]
[ROW][C]ParExp[/C][C]0.028[/C][C]0.329[/C][C]0.027[/C][C]1[/C][C]0.593[/C][C]0.244[/C][C]-0.155[/C][/ROW]
[ROW][C]ParCrit[/C][C]-0.038[/C][C]0.311[/C][C]0.154[/C][C]0.593[/C][C]1[/C][C]0.131[/C][C]-0.203[/C][/ROW]
[ROW][C]PersonalStandards[/C][C]-0.033[/C][C]0.425[/C][C]-0.032[/C][C]0.244[/C][C]0.131[/C][C]1[/C][C]0.352[/C][/ROW]
[ROW][C]Organisation[/C][C]-0.002[/C][C]0.054[/C][C]0.07[/C][C]-0.155[/C][C]-0.203[/C][C]0.352[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197574&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197574&T=1

As an alternative you can also use a QR Code:  

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

Correlations for all pairs of data series (method=pearson)
GenderConcMistakesDoubtsActionsParExpParCritPersonalStandardsOrganisation
Gender1-0.0540.0120.028-0.038-0.033-0.002
ConcMistakes-0.05410.3950.3290.3110.4250.054
DoubtsActions0.0120.39510.0270.154-0.0320.07
ParExp0.0280.3290.02710.5930.244-0.155
ParCrit-0.0380.3110.1540.59310.131-0.203
PersonalStandards-0.0330.425-0.0320.2440.13110.352
Organisation-0.0020.0540.07-0.155-0.2030.3521







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Gender;ConcMistakes-0.0542-0.0791-0.0663
p-value(0.4972)(0.3215)(0.32)
Gender;DoubtsActions0.01220.04070.035
p-value(0.8788)(0.6104)(0.6088)
Gender;ParExp0.02790.01190.0102
p-value(0.7265)(0.8812)(0.8807)
Gender;ParCrit-0.0381-0.055-0.0475
p-value(0.6334)(0.4912)(0.4895)
Gender;PersonalStandards-0.0329-0.0354-0.03
p-value(0.6802)(0.6575)(0.656)
Gender;Organisation-0.00240.02430.0207
p-value(0.9758)(0.7606)(0.7596)
ConcMistakes;DoubtsActions0.39530.39490.3021
p-value(0)(0)(0)
ConcMistakes;ParExp0.32880.28420.2144
p-value(0)(3e-04)(2e-04)
ConcMistakes;ParCrit0.31090.33090.2526
p-value(1e-04)(0)(0)
ConcMistakes;PersonalStandards0.4250.40770.3013
p-value(0)(0)(0)
ConcMistakes;Organisation0.05410.00580.0018
p-value(0.4983)(0.9427)(0.9749)
DoubtsActions;ParExp0.02720.02130.0124
p-value(0.7332)(0.7897)(0.8314)
DoubtsActions;ParCrit0.15430.12050.0884
p-value(0.0521)(0.1304)(0.1357)
DoubtsActions;PersonalStandards-0.03240.00270.002
p-value(0.6847)(0.9734)(0.9724)
DoubtsActions;Organisation0.06980.08150.0587
p-value(0.3817)(0.3068)(0.314)
ParExp;ParCrit0.59320.48210.3775
p-value(0)(0)(0)
ParExp;PersonalStandards0.24360.19870.1512
p-value(0.002)(0.0121)(0.0084)
ParExp;Organisation-0.1549-0.1805-0.1349
p-value(0.0512)(0.0228)(0.0196)
ParCrit;PersonalStandards0.13130.11590.085
p-value(0.099)(0.1459)(0.1439)
ParCrit;Organisation-0.203-0.189-0.1383
p-value(0.0103)(0.0171)(0.0182)
PersonalStandards;Organisation0.35220.3090.2242
p-value(0)(1e-04)(1e-04)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Gender;ConcMistakes & -0.0542 & -0.0791 & -0.0663 \tabularnewline
p-value & (0.4972) & (0.3215) & (0.32) \tabularnewline
Gender;DoubtsActions & 0.0122 & 0.0407 & 0.035 \tabularnewline
p-value & (0.8788) & (0.6104) & (0.6088) \tabularnewline
Gender;ParExp & 0.0279 & 0.0119 & 0.0102 \tabularnewline
p-value & (0.7265) & (0.8812) & (0.8807) \tabularnewline
Gender;ParCrit & -0.0381 & -0.055 & -0.0475 \tabularnewline
p-value & (0.6334) & (0.4912) & (0.4895) \tabularnewline
Gender;PersonalStandards & -0.0329 & -0.0354 & -0.03 \tabularnewline
p-value & (0.6802) & (0.6575) & (0.656) \tabularnewline
Gender;Organisation & -0.0024 & 0.0243 & 0.0207 \tabularnewline
p-value & (0.9758) & (0.7606) & (0.7596) \tabularnewline
ConcMistakes;DoubtsActions & 0.3953 & 0.3949 & 0.3021 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
ConcMistakes;ParExp & 0.3288 & 0.2842 & 0.2144 \tabularnewline
p-value & (0) & (3e-04) & (2e-04) \tabularnewline
ConcMistakes;ParCrit & 0.3109 & 0.3309 & 0.2526 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
ConcMistakes;PersonalStandards & 0.425 & 0.4077 & 0.3013 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
ConcMistakes;Organisation & 0.0541 & 0.0058 & 0.0018 \tabularnewline
p-value & (0.4983) & (0.9427) & (0.9749) \tabularnewline
DoubtsActions;ParExp & 0.0272 & 0.0213 & 0.0124 \tabularnewline
p-value & (0.7332) & (0.7897) & (0.8314) \tabularnewline
DoubtsActions;ParCrit & 0.1543 & 0.1205 & 0.0884 \tabularnewline
p-value & (0.0521) & (0.1304) & (0.1357) \tabularnewline
DoubtsActions;PersonalStandards & -0.0324 & 0.0027 & 0.002 \tabularnewline
p-value & (0.6847) & (0.9734) & (0.9724) \tabularnewline
DoubtsActions;Organisation & 0.0698 & 0.0815 & 0.0587 \tabularnewline
p-value & (0.3817) & (0.3068) & (0.314) \tabularnewline
ParExp;ParCrit & 0.5932 & 0.4821 & 0.3775 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
ParExp;PersonalStandards & 0.2436 & 0.1987 & 0.1512 \tabularnewline
p-value & (0.002) & (0.0121) & (0.0084) \tabularnewline
ParExp;Organisation & -0.1549 & -0.1805 & -0.1349 \tabularnewline
p-value & (0.0512) & (0.0228) & (0.0196) \tabularnewline
ParCrit;PersonalStandards & 0.1313 & 0.1159 & 0.085 \tabularnewline
p-value & (0.099) & (0.1459) & (0.1439) \tabularnewline
ParCrit;Organisation & -0.203 & -0.189 & -0.1383 \tabularnewline
p-value & (0.0103) & (0.0171) & (0.0182) \tabularnewline
PersonalStandards;Organisation & 0.3522 & 0.309 & 0.2242 \tabularnewline
p-value & (0) & (1e-04) & (1e-04) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197574&T=2

[TABLE]
[ROW][C]Correlations for all pairs of data series with p-values[/C][/ROW]
[ROW][C]pair[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]Gender;ConcMistakes[/C][C]-0.0542[/C][C]-0.0791[/C][C]-0.0663[/C][/ROW]
[ROW][C]p-value[/C][C](0.4972)[/C][C](0.3215)[/C][C](0.32)[/C][/ROW]
[ROW][C]Gender;DoubtsActions[/C][C]0.0122[/C][C]0.0407[/C][C]0.035[/C][/ROW]
[ROW][C]p-value[/C][C](0.8788)[/C][C](0.6104)[/C][C](0.6088)[/C][/ROW]
[ROW][C]Gender;ParExp[/C][C]0.0279[/C][C]0.0119[/C][C]0.0102[/C][/ROW]
[ROW][C]p-value[/C][C](0.7265)[/C][C](0.8812)[/C][C](0.8807)[/C][/ROW]
[ROW][C]Gender;ParCrit[/C][C]-0.0381[/C][C]-0.055[/C][C]-0.0475[/C][/ROW]
[ROW][C]p-value[/C][C](0.6334)[/C][C](0.4912)[/C][C](0.4895)[/C][/ROW]
[ROW][C]Gender;PersonalStandards[/C][C]-0.0329[/C][C]-0.0354[/C][C]-0.03[/C][/ROW]
[ROW][C]p-value[/C][C](0.6802)[/C][C](0.6575)[/C][C](0.656)[/C][/ROW]
[ROW][C]Gender;Organisation[/C][C]-0.0024[/C][C]0.0243[/C][C]0.0207[/C][/ROW]
[ROW][C]p-value[/C][C](0.9758)[/C][C](0.7606)[/C][C](0.7596)[/C][/ROW]
[ROW][C]ConcMistakes;DoubtsActions[/C][C]0.3953[/C][C]0.3949[/C][C]0.3021[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]ConcMistakes;ParExp[/C][C]0.3288[/C][C]0.2842[/C][C]0.2144[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](3e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]ConcMistakes;ParCrit[/C][C]0.3109[/C][C]0.3309[/C][C]0.2526[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]ConcMistakes;PersonalStandards[/C][C]0.425[/C][C]0.4077[/C][C]0.3013[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]ConcMistakes;Organisation[/C][C]0.0541[/C][C]0.0058[/C][C]0.0018[/C][/ROW]
[ROW][C]p-value[/C][C](0.4983)[/C][C](0.9427)[/C][C](0.9749)[/C][/ROW]
[ROW][C]DoubtsActions;ParExp[/C][C]0.0272[/C][C]0.0213[/C][C]0.0124[/C][/ROW]
[ROW][C]p-value[/C][C](0.7332)[/C][C](0.7897)[/C][C](0.8314)[/C][/ROW]
[ROW][C]DoubtsActions;ParCrit[/C][C]0.1543[/C][C]0.1205[/C][C]0.0884[/C][/ROW]
[ROW][C]p-value[/C][C](0.0521)[/C][C](0.1304)[/C][C](0.1357)[/C][/ROW]
[ROW][C]DoubtsActions;PersonalStandards[/C][C]-0.0324[/C][C]0.0027[/C][C]0.002[/C][/ROW]
[ROW][C]p-value[/C][C](0.6847)[/C][C](0.9734)[/C][C](0.9724)[/C][/ROW]
[ROW][C]DoubtsActions;Organisation[/C][C]0.0698[/C][C]0.0815[/C][C]0.0587[/C][/ROW]
[ROW][C]p-value[/C][C](0.3817)[/C][C](0.3068)[/C][C](0.314)[/C][/ROW]
[ROW][C]ParExp;ParCrit[/C][C]0.5932[/C][C]0.4821[/C][C]0.3775[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]ParExp;PersonalStandards[/C][C]0.2436[/C][C]0.1987[/C][C]0.1512[/C][/ROW]
[ROW][C]p-value[/C][C](0.002)[/C][C](0.0121)[/C][C](0.0084)[/C][/ROW]
[ROW][C]ParExp;Organisation[/C][C]-0.1549[/C][C]-0.1805[/C][C]-0.1349[/C][/ROW]
[ROW][C]p-value[/C][C](0.0512)[/C][C](0.0228)[/C][C](0.0196)[/C][/ROW]
[ROW][C]ParCrit;PersonalStandards[/C][C]0.1313[/C][C]0.1159[/C][C]0.085[/C][/ROW]
[ROW][C]p-value[/C][C](0.099)[/C][C](0.1459)[/C][C](0.1439)[/C][/ROW]
[ROW][C]ParCrit;Organisation[/C][C]-0.203[/C][C]-0.189[/C][C]-0.1383[/C][/ROW]
[ROW][C]p-value[/C][C](0.0103)[/C][C](0.0171)[/C][C](0.0182)[/C][/ROW]
[ROW][C]PersonalStandards;Organisation[/C][C]0.3522[/C][C]0.309[/C][C]0.2242[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197574&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197574&T=2

As an alternative you can also use a QR Code:  

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

Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Gender;ConcMistakes-0.0542-0.0791-0.0663
p-value(0.4972)(0.3215)(0.32)
Gender;DoubtsActions0.01220.04070.035
p-value(0.8788)(0.6104)(0.6088)
Gender;ParExp0.02790.01190.0102
p-value(0.7265)(0.8812)(0.8807)
Gender;ParCrit-0.0381-0.055-0.0475
p-value(0.6334)(0.4912)(0.4895)
Gender;PersonalStandards-0.0329-0.0354-0.03
p-value(0.6802)(0.6575)(0.656)
Gender;Organisation-0.00240.02430.0207
p-value(0.9758)(0.7606)(0.7596)
ConcMistakes;DoubtsActions0.39530.39490.3021
p-value(0)(0)(0)
ConcMistakes;ParExp0.32880.28420.2144
p-value(0)(3e-04)(2e-04)
ConcMistakes;ParCrit0.31090.33090.2526
p-value(1e-04)(0)(0)
ConcMistakes;PersonalStandards0.4250.40770.3013
p-value(0)(0)(0)
ConcMistakes;Organisation0.05410.00580.0018
p-value(0.4983)(0.9427)(0.9749)
DoubtsActions;ParExp0.02720.02130.0124
p-value(0.7332)(0.7897)(0.8314)
DoubtsActions;ParCrit0.15430.12050.0884
p-value(0.0521)(0.1304)(0.1357)
DoubtsActions;PersonalStandards-0.03240.00270.002
p-value(0.6847)(0.9734)(0.9724)
DoubtsActions;Organisation0.06980.08150.0587
p-value(0.3817)(0.3068)(0.314)
ParExp;ParCrit0.59320.48210.3775
p-value(0)(0)(0)
ParExp;PersonalStandards0.24360.19870.1512
p-value(0.002)(0.0121)(0.0084)
ParExp;Organisation-0.1549-0.1805-0.1349
p-value(0.0512)(0.0228)(0.0196)
ParCrit;PersonalStandards0.13130.11590.085
p-value(0.099)(0.1459)(0.1439)
ParCrit;Organisation-0.203-0.189-0.1383
p-value(0.0103)(0.0171)(0.0182)
PersonalStandards;Organisation0.35220.3090.2242
p-value(0)(1e-04)(1e-04)



Parameters (Session):
par1 = pearson ;
Parameters (R input):
par1 = pearson ;
R code (references can be found in the software module):
panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
rr <- cor.test(x, y, method=par1)
r <- round(rr$p.value,2)
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep='')
if(missing(cex.cor)) cex <- 0.5/strwidth(txt)
text(0.5, 0.5, txt, cex = cex)
}
panel.hist <- function(x, ...)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
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,'Correlations for all pairs of data series with p-values',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
cor.test(y[1,],y[2,],method=par1)
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='')
a<-table.element(a,dum,header=TRUE)
rp <- cor.test(y[i,],y[j,],method='pearson')
a<-table.element(a,round(rp$estimate,4))
rs <- cor.test(y[i,],y[j,],method='spearman')
a<-table.element(a,round(rs$estimate,4))
rk <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,round(rk$estimate,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=T)
a<-table.element(a,paste('(',round(rp$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rs$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rk$p.value,4),')',sep=''))
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')