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Author's title

Author*Unverified author*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationMon, 20 Dec 2010 10:28:58 +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/20/t12928408032t3jn1qnsfaq3sk.htm/, Retrieved Fri, 03 May 2024 23:12:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112832, Retrieved Fri, 03 May 2024 23:12:52 +0000
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Estimated Impact163
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-     [Kendall tau Correlation Matrix] [] [2010-12-05 17:44:33] [b98453cac15ba1066b407e146608df68]
F   PD  [Kendall tau Correlation Matrix] [] [2010-12-12 17:09:17] [de55ccbf69577500a5f46ed42a101114]
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Dataseries X:
1	15	15	13	6
2	9	12	11	4
2	12	15	14	6
2	15	12	12	5
2	17	14	12	5
2	14	8	6	4
1	9	11	10	5
1	12	15	11	3
2	11	4	10	2
2	13	13	12	5
1	16	19	15	6
1	16	10	13	6
1	15	15	18	8
2	10	6	11	6
1	16	7	12	3
2	12	14	13	6
2	15	16	14	6
1	13	16	16	7
1	18	14	16	8
2	13	15	16	6
1	17	14	15	7
1	14	12	13	4
2	13	9	8	4
1	13	12	14	2
1	15	14	15	6
1	13	12	13	6
1	15	14	16	6
1	13	10	13	6
1	14	14	12	6
1	13	16	15	7
1	16	10	11	4
1	14	8	14	3
2	12	8	14	3
1	18	12	13	5
1	15	11	13	6
2	9	8	12	4
2	16	13	14	6
1	16	11	13	3
2	17	12	12	3
2	13	16	14	6
1	17	16	15	6
1	15	13	16	6
1	14	14	15	8
2	10	5	5	2
2	13	14	15	6
1	11	13	8	4
1	11	16	16	7
2	16	15	14	6
2	16	15	14	6
1	11	15	16	6
1	15	11	14	5
1	15	15	13	6
1	12	16	14	6
1	17	13	14	5
2	15	11	12	6
2	16	12	13	7
1	14	12	15	5
1	17	10	15	6
1	10	8	13	6
2	11	9	10	4
1	15	12	13	5
2	15	14	14	6
1	7	12	13	6
2	17	11	13	4
2	14	14	18	6
2	18	7	12	4
2	14	16	14	7
1	12	16	16	8
2	14	11	13	6
1	9	16	16	6
1	14	13	15	6
1	11	11	14	5
1	15	11	14	5
1	16	13	13	6
1	17	14	12	6
1	16	15	16	4
2	12	10	9	5
1	15	15	15	8
2	15	11	16	6
1	16	6	11	2
1	16	11	13	2
2	11	12	13	4
2	15	13	14	6
1	12	12	15	6
2	14	8	14	5
1	15	9	12	4
1	17	10	16	4
1	19	16	14	6
1	15	15	13	5
2	16	14	12	6
1	14	12	13	7
1	16	12	12	6
1	15	10	9	4
1	15	12	13	4
2	17	8	10	3
1	12	16	15	8
1	18	11	9	4
1	13	12	13	4
1	14	9	13	5
2	14	14	13	5
2	14	15	15	7
2	12	8	13	4
1	14	12	14	5
2	12	10	11	5
1	15	16	15	8
1	11	17	14	5
2	11	8	15	2
1	15	9	12	5
1	14	8	15	4
2	15	11	14	5
1	16	16	16	7
2	12	13	14	6
1	14	5	12	3
1	14	5	12	3
1	18	15	11	5
1	14	15	13	6
1	13	12	12	5
2	14	12	12	6
1	14	16	16	7
1	17	12	13	6
1	12	10	12	6
1	16	12	14	5
1	15	4	4	4
2	10	11	14	6
2	13	16	15	6
2	15	7	12	3
1	16	9	11	4
2	15	14	12	4
1	14	11	11	4
1	11	10	12	5
2	13	6	11	4
1	17	14	13	6
1	14	11	12	6
1	16	11	12	4
2	15	9	15	7
1	12	16	14	4
2	16	7	12	4
2	8	8	12	4
2	9	10	12	4
1	13	14	13	5
1	19	9	11	4
1	11	13	13	7
2	15	13	12	3
2	11	12	14	5
2	15	11	15	5
2	16	10	15	6
1	15	12	13	5
1	12	14	16	6
2	16	11	17	6
2	15	13	13	3
2	13	14	14	6
1	14	13	13	5
1	11	16	16	8
1	15	13	13	6
1	12	13	13	6
1	16	12	14	4
1	14	9	13	3
1	13	14	14	4
1	15	15	16	7




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=112832&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=112832&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112832&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)
GenderHappinessPopularityLikedCelebrity
Gender1-0.119-0.154-0.117-0.099
Happiness-0.11910.0070.007-0.006
Popularity-0.1540.00710.4230.497
Liked-0.1170.0070.42310.46
Celebrity-0.099-0.0060.4970.461

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Gender & Happiness & Popularity & Liked & Celebrity \tabularnewline
Gender & 1 & -0.119 & -0.154 & -0.117 & -0.099 \tabularnewline
Happiness & -0.119 & 1 & 0.007 & 0.007 & -0.006 \tabularnewline
Popularity & -0.154 & 0.007 & 1 & 0.423 & 0.497 \tabularnewline
Liked & -0.117 & 0.007 & 0.423 & 1 & 0.46 \tabularnewline
Celebrity & -0.099 & -0.006 & 0.497 & 0.46 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112832&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Gender[/C][C]Happiness[/C][C]Popularity[/C][C]Liked[/C][C]Celebrity[/C][/ROW]
[ROW][C]Gender[/C][C]1[/C][C]-0.119[/C][C]-0.154[/C][C]-0.117[/C][C]-0.099[/C][/ROW]
[ROW][C]Happiness[/C][C]-0.119[/C][C]1[/C][C]0.007[/C][C]0.007[/C][C]-0.006[/C][/ROW]
[ROW][C]Popularity[/C][C]-0.154[/C][C]0.007[/C][C]1[/C][C]0.423[/C][C]0.497[/C][/ROW]
[ROW][C]Liked[/C][C]-0.117[/C][C]0.007[/C][C]0.423[/C][C]1[/C][C]0.46[/C][/ROW]
[ROW][C]Celebrity[/C][C]-0.099[/C][C]-0.006[/C][C]0.497[/C][C]0.46[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112832&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112832&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)
GenderHappinessPopularityLikedCelebrity
Gender1-0.119-0.154-0.117-0.099
Happiness-0.11910.0070.007-0.006
Popularity-0.1540.00710.4230.497
Liked-0.1170.0070.42310.46
Celebrity-0.099-0.0060.4970.461







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Gender;Happiness-0.1497-0.1371-0.1188
p-value(0.0597)(0.0849)(0.0849)
Gender;Popularity-0.1879-0.1797-0.1539
p-value(0.0177)(0.0234)(0.0239)
Gender;Liked-0.1338-0.1335-0.1169
p-value(0.0928)(0.0934)(0.0933)
Gender;Celebrity-0.1301-0.1106-0.0991
p-value(0.1022)(0.1651)(0.1644)
Happiness;Popularity0.0710.01610.0072
p-value(0.3737)(0.8399)(0.9035)
Happiness;Liked0.07210.01580.0068
p-value(0.3661)(0.8434)(0.91)
Happiness;Celebrity0.0162-0.008-0.006
p-value(0.8399)(0.9201)(0.9232)
Popularity;Liked0.55460.54020.4227
p-value(0)(0)(0)
Popularity;Celebrity0.6160.60540.4969
p-value(0)(0)(0)
Liked;Celebrity0.5310.56410.46
p-value(0)(0)(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Gender;Happiness & -0.1497 & -0.1371 & -0.1188 \tabularnewline
p-value & (0.0597) & (0.0849) & (0.0849) \tabularnewline
Gender;Popularity & -0.1879 & -0.1797 & -0.1539 \tabularnewline
p-value & (0.0177) & (0.0234) & (0.0239) \tabularnewline
Gender;Liked & -0.1338 & -0.1335 & -0.1169 \tabularnewline
p-value & (0.0928) & (0.0934) & (0.0933) \tabularnewline
Gender;Celebrity & -0.1301 & -0.1106 & -0.0991 \tabularnewline
p-value & (0.1022) & (0.1651) & (0.1644) \tabularnewline
Happiness;Popularity & 0.071 & 0.0161 & 0.0072 \tabularnewline
p-value & (0.3737) & (0.8399) & (0.9035) \tabularnewline
Happiness;Liked & 0.0721 & 0.0158 & 0.0068 \tabularnewline
p-value & (0.3661) & (0.8434) & (0.91) \tabularnewline
Happiness;Celebrity & 0.0162 & -0.008 & -0.006 \tabularnewline
p-value & (0.8399) & (0.9201) & (0.9232) \tabularnewline
Popularity;Liked & 0.5546 & 0.5402 & 0.4227 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Popularity;Celebrity & 0.616 & 0.6054 & 0.4969 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Liked;Celebrity & 0.531 & 0.5641 & 0.46 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112832&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;Happiness[/C][C]-0.1497[/C][C]-0.1371[/C][C]-0.1188[/C][/ROW]
[ROW][C]p-value[/C][C](0.0597)[/C][C](0.0849)[/C][C](0.0849)[/C][/ROW]
[ROW][C]Gender;Popularity[/C][C]-0.1879[/C][C]-0.1797[/C][C]-0.1539[/C][/ROW]
[ROW][C]p-value[/C][C](0.0177)[/C][C](0.0234)[/C][C](0.0239)[/C][/ROW]
[ROW][C]Gender;Liked[/C][C]-0.1338[/C][C]-0.1335[/C][C]-0.1169[/C][/ROW]
[ROW][C]p-value[/C][C](0.0928)[/C][C](0.0934)[/C][C](0.0933)[/C][/ROW]
[ROW][C]Gender;Celebrity[/C][C]-0.1301[/C][C]-0.1106[/C][C]-0.0991[/C][/ROW]
[ROW][C]p-value[/C][C](0.1022)[/C][C](0.1651)[/C][C](0.1644)[/C][/ROW]
[ROW][C]Happiness;Popularity[/C][C]0.071[/C][C]0.0161[/C][C]0.0072[/C][/ROW]
[ROW][C]p-value[/C][C](0.3737)[/C][C](0.8399)[/C][C](0.9035)[/C][/ROW]
[ROW][C]Happiness;Liked[/C][C]0.0721[/C][C]0.0158[/C][C]0.0068[/C][/ROW]
[ROW][C]p-value[/C][C](0.3661)[/C][C](0.8434)[/C][C](0.91)[/C][/ROW]
[ROW][C]Happiness;Celebrity[/C][C]0.0162[/C][C]-0.008[/C][C]-0.006[/C][/ROW]
[ROW][C]p-value[/C][C](0.8399)[/C][C](0.9201)[/C][C](0.9232)[/C][/ROW]
[ROW][C]Popularity;Liked[/C][C]0.5546[/C][C]0.5402[/C][C]0.4227[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Popularity;Celebrity[/C][C]0.616[/C][C]0.6054[/C][C]0.4969[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Liked;Celebrity[/C][C]0.531[/C][C]0.5641[/C][C]0.46[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112832&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112832&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;Happiness-0.1497-0.1371-0.1188
p-value(0.0597)(0.0849)(0.0849)
Gender;Popularity-0.1879-0.1797-0.1539
p-value(0.0177)(0.0234)(0.0239)
Gender;Liked-0.1338-0.1335-0.1169
p-value(0.0928)(0.0934)(0.0933)
Gender;Celebrity-0.1301-0.1106-0.0991
p-value(0.1022)(0.1651)(0.1644)
Happiness;Popularity0.0710.01610.0072
p-value(0.3737)(0.8399)(0.9035)
Happiness;Liked0.07210.01580.0068
p-value(0.3661)(0.8434)(0.91)
Happiness;Celebrity0.0162-0.008-0.006
p-value(0.8399)(0.9201)(0.9232)
Popularity;Liked0.55460.54020.4227
p-value(0)(0)(0)
Popularity;Celebrity0.6160.60540.4969
p-value(0)(0)(0)
Liked;Celebrity0.5310.56410.46
p-value(0)(0)(0)



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')