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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 computationSun, 15 Nov 2009 03:58:06 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/15/t1258282866dzigrg4xnbahiru.htm/, Retrieved Fri, 03 May 2024 09:05:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=57266, Retrieved Fri, 03 May 2024 09:05:17 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [] [2009-11-15 10:58:06] [4d89445a8ea4b299af2ee123046cffa6] [Current]
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Dataseries X:
97.4	106.7	96.7	116.7
97	104.7	94.7	109
105.4	107.4	90.1	119.5
102.7	109.8	87.9	115.1
98.1	103.4	76.3	107.1
104.5	114.8	82.6	109.7
87.4	114.3	81.8	110.4
89.9	109.6	66.2	105
109.8	118.3	97.8	115.8
111.7	127.3	94.7	116.4
98.6	112.3	81.2	111.1
96.9	114.9	70.6	119.5
95.1	108.2	87.6	110.9
97	105.4	89.3	115.1
112.7	122.1	99.6	125.2
102.9	113.5	83.9	116
97.4	110	74.7	112.9
111.4	125.3	91.2	121.7
87.4	114.3	80.8	123.2
96.8	115.6	72.3	116.6
114.1	127.1	99.7	136.2
110.3	123	90.1	120.9
103.9	122.2	83.1	119.6
101.6	126.4	71.9	125.9
94.6	112.7	78.6	116.1
95.9	105.8	87.2	107.5
104.7	120.9	90.6	116.7
102.8	116.3	80	112.5
98.1	115.7	73.1	113
113.9	127.9	85.6	126.4
80.9	108.3	73.8	114.1
95.7	121.1	70.6	112.5
113.2	128.6	91.8	112.4
105.9	123.1	81.3	113.1
108.8	127.7	85.2	116.3
102.3	126.6	69.6	111.7
99	118.4	83.3	118.8
100.7	110	89.8	116.5
115.5	129.6	99.5	125.1
100.7	115.8	78.9	113.1
109.9	125.9	83.8	119.6
114.6	128.4	92	114.4
85.4	114	80.9	114
100.5	125.6	74.6	117.8
114.8	128.5	97.9	117
116.5	136.6	88.3	120.9
112.9	133.1	88.1	115
102	124.6	66.4	117.3
106	123.5	92.3	119.4
105.3	117.2	95.6	114.9
118.8	135.5	99.7	125.8
106.1	124.8	78.9	117.6
109.3	127.8	79.4	117.6
117.2	133.1	87.8	114.9
92.5	125.7	80.5	121.9
104.2	128.4	71.8	117
112.5	131.9	89.2	106.4
122.4	146.3	96.4	110.5
113.3	140.6	83.5	113.6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=57266&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]1 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=57266&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57266&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( TIip , ipv&g )0.601816609482961.85065296420817e-11
tau( TIip , ipk&t )0.4308323563892151.52791462060264e-06
tau( TIip , ipchn )0.2277666086460870.0111445414994655
tau( ipv&g , ipk&t )0.1476706773025370.0992977724538313
tau( ipv&g , ipchn )0.2423712676440510.00690034623549018
tau( ipk&t , ipchn )0.1655417104077230.0650774061001749

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( TIip , ipv&g ) & 0.60181660948296 & 1.85065296420817e-11 \tabularnewline
tau( TIip , ipk&t ) & 0.430832356389215 & 1.52791462060264e-06 \tabularnewline
tau( TIip , ipchn ) & 0.227766608646087 & 0.0111445414994655 \tabularnewline
tau( ipv&g , ipk&t ) & 0.147670677302537 & 0.0992977724538313 \tabularnewline
tau( ipv&g , ipchn ) & 0.242371267644051 & 0.00690034623549018 \tabularnewline
tau( ipk&t , ipchn ) & 0.165541710407723 & 0.0650774061001749 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=57266&T=1

[TABLE]
[ROW][C]Kendall tau rank correlations for all pairs of data series[/C][/ROW]
[ROW][C]pair[/C][C]tau[/C][C]p-value[/C][/ROW]
[ROW][C]tau( TIip , ipv&g )[/C][C]0.60181660948296[/C][C]1.85065296420817e-11[/C][/ROW]
[ROW][C]tau( TIip , ipk&t )[/C][C]0.430832356389215[/C][C]1.52791462060264e-06[/C][/ROW]
[ROW][C]tau( TIip , ipchn )[/C][C]0.227766608646087[/C][C]0.0111445414994655[/C][/ROW]
[ROW][C]tau( ipv&g , ipk&t )[/C][C]0.147670677302537[/C][C]0.0992977724538313[/C][/ROW]
[ROW][C]tau( ipv&g , ipchn )[/C][C]0.242371267644051[/C][C]0.00690034623549018[/C][/ROW]
[ROW][C]tau( ipk&t , ipchn )[/C][C]0.165541710407723[/C][C]0.0650774061001749[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=57266&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57266&T=1

As an alternative you can also use a QR Code:  

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

Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( TIip , ipv&g )0.601816609482961.85065296420817e-11
tau( TIip , ipk&t )0.4308323563892151.52791462060264e-06
tau( TIip , ipchn )0.2277666086460870.0111445414994655
tau( ipv&g , ipk&t )0.1476706773025370.0992977724538313
tau( ipv&g , ipchn )0.2423712676440510.00690034623549018
tau( ipk&t , ipchn )0.1655417104077230.0650774061001749



Parameters (Session):
Parameters (R input):
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='kendall')
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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations for all pairs of data series',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'tau',1,TRUE)
a<-table.element(a,'p-value',1,TRUE)
a<-table.row.end(a)
n <- length(y[,1])
n
cor.test(y[1,],y[2,],method='kendall')
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste('tau(',dimnames(t(x))[[2]][i])
dum <- paste(dum,',')
dum <- paste(dum,dimnames(t(x))[[2]][j])
dum <- paste(dum,')')
a<-table.element(a,dum,header=TRUE)
r <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,r$estimate)
a<-table.element(a,r$p.value)
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable.tab')