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Author's title

Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationSun, 26 Dec 2010 09:51:28 +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/2010/Dec/26/t12933570144af5yd19uqn8fiz.htm/, Retrieved Mon, 06 May 2024 15:43:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115491, Retrieved Mon, 06 May 2024 15:43:24 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146
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 18:04:16] [b98453cac15ba1066b407e146608df68]
- R PD    [Kendall tau Correlation Matrix] [Workshop 10 (Kend...] [2010-12-26 09:51:28] [6427096bd21c899f2c90594929aeeec2] [Current]
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Dataseries X:
1	0	2	5	3	4
0	0	2	4	3	4
0	0	4	4	2	5
0	1	2	4	2	3
0	1	3	2	3	4
1	0	4	5	2	3
1	1	3	5	1	4
0	0	3	4	3	3
1	1	3	3	2	2
1	1	2	4	2	4
1	1	4	4	3	2
0	0	4	3	2	2
0	0	3	3	2	2
1	1	3	3	2	1
0	1	4	4	3	4
1	0	4	5	1	4
0	1	3	4	3	2
1	0	3	2	2	2
0	1	3	4	3	3
0	1	4	4	4	3
1	1	2	4	2	3
1	0	5	4	3	4
1	0	4	4	5	3
0	0	2	4	2	2
1	1	3	5	2	2
1	1	4	4	3	4
0	0	4	4	2	4
0	0	3	4	2	3
1	0	4	4	2	4
1	0	4	4	2	2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115491&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115491&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115491&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Correlations for all pairs of data series (method=kendall)
PopGenderStandardsOrganizationMistakesGoals
Pop10.0710.1310.259-0.216-0.041
Gender0.0711-0.22-0.0550.143-0.105
Standards0.131-0.2210.0480.1230.137
Organization0.259-0.0550.0481-0.0810.336
Mistakes-0.2160.1430.123-0.08110.089
Goals-0.041-0.1050.1370.3360.0891

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Pop & Gender & Standards & Organization & Mistakes & Goals \tabularnewline
Pop & 1 & 0.071 & 0.131 & 0.259 & -0.216 & -0.041 \tabularnewline
Gender & 0.071 & 1 & -0.22 & -0.055 & 0.143 & -0.105 \tabularnewline
Standards & 0.131 & -0.22 & 1 & 0.048 & 0.123 & 0.137 \tabularnewline
Organization & 0.259 & -0.055 & 0.048 & 1 & -0.081 & 0.336 \tabularnewline
Mistakes & -0.216 & 0.143 & 0.123 & -0.081 & 1 & 0.089 \tabularnewline
Goals & -0.041 & -0.105 & 0.137 & 0.336 & 0.089 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115491&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Pop[/C][C]Gender[/C][C]Standards[/C][C]Organization[/C][C]Mistakes[/C][C]Goals[/C][/ROW]
[ROW][C]Pop[/C][C]1[/C][C]0.071[/C][C]0.131[/C][C]0.259[/C][C]-0.216[/C][C]-0.041[/C][/ROW]
[ROW][C]Gender[/C][C]0.071[/C][C]1[/C][C]-0.22[/C][C]-0.055[/C][C]0.143[/C][C]-0.105[/C][/ROW]
[ROW][C]Standards[/C][C]0.131[/C][C]-0.22[/C][C]1[/C][C]0.048[/C][C]0.123[/C][C]0.137[/C][/ROW]
[ROW][C]Organization[/C][C]0.259[/C][C]-0.055[/C][C]0.048[/C][C]1[/C][C]-0.081[/C][C]0.336[/C][/ROW]
[ROW][C]Mistakes[/C][C]-0.216[/C][C]0.143[/C][C]0.123[/C][C]-0.081[/C][C]1[/C][C]0.089[/C][/ROW]
[ROW][C]Goals[/C][C]-0.041[/C][C]-0.105[/C][C]0.137[/C][C]0.336[/C][C]0.089[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115491&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115491&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=kendall)
PopGenderStandardsOrganizationMistakesGoals
Pop10.0710.1310.259-0.216-0.041
Gender0.0711-0.22-0.0550.143-0.105
Standards0.131-0.2210.0480.1230.137
Organization0.259-0.0550.0481-0.0810.336
Mistakes-0.2160.1430.123-0.08110.089
Goals-0.041-0.1050.1370.3360.0891







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Pop;Gender0.07140.07140.0714
p-value(0.7076)(0.7076)(0.7005)
Pop;Standards0.14230.13990.1314
p-value(0.4531)(0.4608)(0.4512)
Pop;Organization0.23280.27380.2593
p-value(0.2156)(0.1432)(0.1404)
Pop;Mistakes-0.1608-0.227-0.2159
p-value(0.396)(0.2276)(0.2215)
Pop;Goals-0.0739-0.0446-0.0413
p-value(0.6978)(0.8149)(0.8101)
Gender;Standards-0.2244-0.2346-0.2202
p-value(0.2332)(0.2121)(0.2065)
Gender;Organization-0.0537-0.0583-0.0553
p-value(0.7779)(0.7594)(0.7534)
Gender;Mistakes0.07760.14990.1426
p-value(0.6835)(0.4291)(0.4194)
Gender;Goals-0.134-0.1136-0.1052
p-value(0.4801)(0.5502)(0.5408)
Standards;Organization0.04390.0520.0478
p-value(0.8177)(0.785)(0.7722)
Standards;Mistakes0.18010.14220.1234
p-value(0.3408)(0.4536)(0.4569)
Standards;Goals0.14730.16310.1366
p-value(0.4372)(0.3891)(0.3981)
Organization;Mistakes-0.0945-0.0996-0.0815
p-value(0.6193)(0.6004)(0.6264)
Organization;Goals0.33380.37460.3365
p-value(0.0715)(0.0414)(0.0391)
Mistakes;Goals0.04880.10330.0892
p-value(0.7979)(0.5871)(0.586)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Pop;Gender & 0.0714 & 0.0714 & 0.0714 \tabularnewline
p-value & (0.7076) & (0.7076) & (0.7005) \tabularnewline
Pop;Standards & 0.1423 & 0.1399 & 0.1314 \tabularnewline
p-value & (0.4531) & (0.4608) & (0.4512) \tabularnewline
Pop;Organization & 0.2328 & 0.2738 & 0.2593 \tabularnewline
p-value & (0.2156) & (0.1432) & (0.1404) \tabularnewline
Pop;Mistakes & -0.1608 & -0.227 & -0.2159 \tabularnewline
p-value & (0.396) & (0.2276) & (0.2215) \tabularnewline
Pop;Goals & -0.0739 & -0.0446 & -0.0413 \tabularnewline
p-value & (0.6978) & (0.8149) & (0.8101) \tabularnewline
Gender;Standards & -0.2244 & -0.2346 & -0.2202 \tabularnewline
p-value & (0.2332) & (0.2121) & (0.2065) \tabularnewline
Gender;Organization & -0.0537 & -0.0583 & -0.0553 \tabularnewline
p-value & (0.7779) & (0.7594) & (0.7534) \tabularnewline
Gender;Mistakes & 0.0776 & 0.1499 & 0.1426 \tabularnewline
p-value & (0.6835) & (0.4291) & (0.4194) \tabularnewline
Gender;Goals & -0.134 & -0.1136 & -0.1052 \tabularnewline
p-value & (0.4801) & (0.5502) & (0.5408) \tabularnewline
Standards;Organization & 0.0439 & 0.052 & 0.0478 \tabularnewline
p-value & (0.8177) & (0.785) & (0.7722) \tabularnewline
Standards;Mistakes & 0.1801 & 0.1422 & 0.1234 \tabularnewline
p-value & (0.3408) & (0.4536) & (0.4569) \tabularnewline
Standards;Goals & 0.1473 & 0.1631 & 0.1366 \tabularnewline
p-value & (0.4372) & (0.3891) & (0.3981) \tabularnewline
Organization;Mistakes & -0.0945 & -0.0996 & -0.0815 \tabularnewline
p-value & (0.6193) & (0.6004) & (0.6264) \tabularnewline
Organization;Goals & 0.3338 & 0.3746 & 0.3365 \tabularnewline
p-value & (0.0715) & (0.0414) & (0.0391) \tabularnewline
Mistakes;Goals & 0.0488 & 0.1033 & 0.0892 \tabularnewline
p-value & (0.7979) & (0.5871) & (0.586) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115491&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]Pop;Gender[/C][C]0.0714[/C][C]0.0714[/C][C]0.0714[/C][/ROW]
[ROW][C]p-value[/C][C](0.7076)[/C][C](0.7076)[/C][C](0.7005)[/C][/ROW]
[ROW][C]Pop;Standards[/C][C]0.1423[/C][C]0.1399[/C][C]0.1314[/C][/ROW]
[ROW][C]p-value[/C][C](0.4531)[/C][C](0.4608)[/C][C](0.4512)[/C][/ROW]
[ROW][C]Pop;Organization[/C][C]0.2328[/C][C]0.2738[/C][C]0.2593[/C][/ROW]
[ROW][C]p-value[/C][C](0.2156)[/C][C](0.1432)[/C][C](0.1404)[/C][/ROW]
[ROW][C]Pop;Mistakes[/C][C]-0.1608[/C][C]-0.227[/C][C]-0.2159[/C][/ROW]
[ROW][C]p-value[/C][C](0.396)[/C][C](0.2276)[/C][C](0.2215)[/C][/ROW]
[ROW][C]Pop;Goals[/C][C]-0.0739[/C][C]-0.0446[/C][C]-0.0413[/C][/ROW]
[ROW][C]p-value[/C][C](0.6978)[/C][C](0.8149)[/C][C](0.8101)[/C][/ROW]
[ROW][C]Gender;Standards[/C][C]-0.2244[/C][C]-0.2346[/C][C]-0.2202[/C][/ROW]
[ROW][C]p-value[/C][C](0.2332)[/C][C](0.2121)[/C][C](0.2065)[/C][/ROW]
[ROW][C]Gender;Organization[/C][C]-0.0537[/C][C]-0.0583[/C][C]-0.0553[/C][/ROW]
[ROW][C]p-value[/C][C](0.7779)[/C][C](0.7594)[/C][C](0.7534)[/C][/ROW]
[ROW][C]Gender;Mistakes[/C][C]0.0776[/C][C]0.1499[/C][C]0.1426[/C][/ROW]
[ROW][C]p-value[/C][C](0.6835)[/C][C](0.4291)[/C][C](0.4194)[/C][/ROW]
[ROW][C]Gender;Goals[/C][C]-0.134[/C][C]-0.1136[/C][C]-0.1052[/C][/ROW]
[ROW][C]p-value[/C][C](0.4801)[/C][C](0.5502)[/C][C](0.5408)[/C][/ROW]
[ROW][C]Standards;Organization[/C][C]0.0439[/C][C]0.052[/C][C]0.0478[/C][/ROW]
[ROW][C]p-value[/C][C](0.8177)[/C][C](0.785)[/C][C](0.7722)[/C][/ROW]
[ROW][C]Standards;Mistakes[/C][C]0.1801[/C][C]0.1422[/C][C]0.1234[/C][/ROW]
[ROW][C]p-value[/C][C](0.3408)[/C][C](0.4536)[/C][C](0.4569)[/C][/ROW]
[ROW][C]Standards;Goals[/C][C]0.1473[/C][C]0.1631[/C][C]0.1366[/C][/ROW]
[ROW][C]p-value[/C][C](0.4372)[/C][C](0.3891)[/C][C](0.3981)[/C][/ROW]
[ROW][C]Organization;Mistakes[/C][C]-0.0945[/C][C]-0.0996[/C][C]-0.0815[/C][/ROW]
[ROW][C]p-value[/C][C](0.6193)[/C][C](0.6004)[/C][C](0.6264)[/C][/ROW]
[ROW][C]Organization;Goals[/C][C]0.3338[/C][C]0.3746[/C][C]0.3365[/C][/ROW]
[ROW][C]p-value[/C][C](0.0715)[/C][C](0.0414)[/C][C](0.0391)[/C][/ROW]
[ROW][C]Mistakes;Goals[/C][C]0.0488[/C][C]0.1033[/C][C]0.0892[/C][/ROW]
[ROW][C]p-value[/C][C](0.7979)[/C][C](0.5871)[/C][C](0.586)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115491&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115491&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
Pop;Gender0.07140.07140.0714
p-value(0.7076)(0.7076)(0.7005)
Pop;Standards0.14230.13990.1314
p-value(0.4531)(0.4608)(0.4512)
Pop;Organization0.23280.27380.2593
p-value(0.2156)(0.1432)(0.1404)
Pop;Mistakes-0.1608-0.227-0.2159
p-value(0.396)(0.2276)(0.2215)
Pop;Goals-0.0739-0.0446-0.0413
p-value(0.6978)(0.8149)(0.8101)
Gender;Standards-0.2244-0.2346-0.2202
p-value(0.2332)(0.2121)(0.2065)
Gender;Organization-0.0537-0.0583-0.0553
p-value(0.7779)(0.7594)(0.7534)
Gender;Mistakes0.07760.14990.1426
p-value(0.6835)(0.4291)(0.4194)
Gender;Goals-0.134-0.1136-0.1052
p-value(0.4801)(0.5502)(0.5408)
Standards;Organization0.04390.0520.0478
p-value(0.8177)(0.785)(0.7722)
Standards;Mistakes0.18010.14220.1234
p-value(0.3408)(0.4536)(0.4569)
Standards;Goals0.14730.16310.1366
p-value(0.4372)(0.3891)(0.3981)
Organization;Mistakes-0.0945-0.0996-0.0815
p-value(0.6193)(0.6004)(0.6264)
Organization;Goals0.33380.37460.3365
p-value(0.0715)(0.0414)(0.0391)
Mistakes;Goals0.04880.10330.0892
p-value(0.7979)(0.5871)(0.586)



Parameters (Session):
par1 = kendall ;
Parameters (R input):
par1 = kendall ;
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')