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Author

*The author of this computation has been verified*

R Software Module

rwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Tue, 17 Nov 2009 11:58:34 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/17/t1258484402646ygza0791bdo9.htm/, Retrieved Thu, 02 May 2024 04:28:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=57404, Retrieved Thu, 02 May 2024 04:28:22 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

177

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Kendall tau Correlation Matrix] [3/11/2009] [2009-11-02 21:25:00] [b98453cac15ba1066b407e146608df68]
- R  D    [Kendall tau Correlation Matrix] [] [2009-11-17 18:58:34] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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Histogram

Boxplots

267413	294912	95.1	1.6
267366	293488	97	1.3
264777	290555	112.7	1.1
258863	284736	102.9	1.9
254844	281818	97.4	2.6
254868	287854	111.4	2.3
277267	316263	87.4	2.4
285351	325412	96.8	2.2
286602	326011	114.1	2
283042	328282	110.3	2.9
276687	317480	103.9	2.6
277915	317539	101.6	2.3
277128	313737	94.6	2.3
277103	312276	95.9	2.6
275037	309391	104.7	3.1
270150	302950	102.8	2.8
267140	300316	98.1	2.5
264993	304035	113.9	2.9
287259	333476	80.9	3.1
291186	337698	95.7	3.1
292300	335932	113.2	3.2
288186	323931	105.9	2.5
281477	313927	108.8	2.6
282656	314485	102.3	2.9
280190	313218	99	2.6
280408	309664	100.7	2.4
276836	302963	115.5	1.7
275216	298989	100.7	2
274352	298423	109.9	2.2
271311	301631	114.6	1.9
289802	329765	85.4	1.6
290726	335083	100.5	1.6
292300	327616	114.8	1.2
278506	309119	116.5	1.2
269826	295916	112.9	1.5
265861	291413	102	1.6
269034	291542	106	1.7
264176	284678	105.3	1.8
255198	276475	118.8	1.8
253353	272566	106.1	1.8
246057	264981	109.3	1.3
235372	263290	117.2	1.3
258556	296806	92.5	1.4
260993	303598	104.2	1.1
254663	286994	112.5	1.5
250643	276427	122.4	2.2
243422	266424	113.3	2.9
247105	267153	100	3.1
248541	268381	110.7	3.5
245039	262522	112.8	3.6
237080	255542	109.8	4.4
237085	253158	117.3	4.2
225554	243803	109.1	5.2
226839	250741	115.9	5.8
247934	280445	96	5.9
248333	285257	99.8	5.4
246969	270976	116.8	5.5
245098	261076	115.7	4.7
246263	255603	99.4	3.1
255765	260376	94.3	2.6
264319	263903	91	2.3
268347	264291	93.2	1.9
273046	263276	103.1	0.6
273963	262572	94.1	0.6
267430	256167	91.8	-0.4
271993	264221	102.7	-1.1
292710	293860	82.6	-1.7

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=57404&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]0 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=57404&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57404&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Kendall tau rank correlations for all pairs of data series
pair	tau	p-value
tau( werkl_man , werkl_vrouw )	0.701198841733362	0
tau( werkl_man , IndProd )	-0.224886877828054	0.0071536526433773
tau( werkl_man , Nat.consP )	-0.176704436793736	0.0369488037483226
tau( werkl_vrouw , IndProd )	-0.111287041978327	0.183105424496055
tau( werkl_vrouw , Nat.consP )	-0.0247789129525593	0.769809695077727
tau( IndProd , Nat.consP )	0.0858278692998146	0.310888262479083

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( werkl_man , werkl_vrouw ) & 0.701198841733362 & 0 \tabularnewline
tau( werkl_man , IndProd ) & -0.224886877828054 & 0.0071536526433773 \tabularnewline
tau( werkl_man , Nat.consP ) & -0.176704436793736 & 0.0369488037483226 \tabularnewline
tau( werkl_vrouw , IndProd ) & -0.111287041978327 & 0.183105424496055 \tabularnewline
tau( werkl_vrouw , Nat.consP ) & -0.0247789129525593 & 0.769809695077727 \tabularnewline
tau( IndProd , Nat.consP ) & 0.0858278692998146 & 0.310888262479083 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=57404&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( werkl_man , werkl_vrouw )[/C][C]0.701198841733362[/C][C]0[/C][/ROW]
[ROW][C]tau( werkl_man , IndProd )[/C][C]-0.224886877828054[/C][C]0.0071536526433773[/C][/ROW]
[ROW][C]tau( werkl_man , Nat.consP )[/C][C]-0.176704436793736[/C][C]0.0369488037483226[/C][/ROW]
[ROW][C]tau( werkl_vrouw , IndProd )[/C][C]-0.111287041978327[/C][C]0.183105424496055[/C][/ROW]
[ROW][C]tau( werkl_vrouw , Nat.consP )[/C][C]-0.0247789129525593[/C][C]0.769809695077727[/C][/ROW]
[ROW][C]tau( IndProd , Nat.consP )[/C][C]0.0858278692998146[/C][C]0.310888262479083[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=57404&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57404&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
pair	tau	p-value
tau( werkl_man , werkl_vrouw )	0.701198841733362	0
tau( werkl_man , IndProd )	-0.224886877828054	0.0071536526433773
tau( werkl_man , Nat.consP )	-0.176704436793736	0.0369488037483226
tau( werkl_vrouw , IndProd )	-0.111287041978327	0.183105424496055
tau( werkl_vrouw , Nat.consP )	-0.0247789129525593	0.769809695077727
tau( IndProd , Nat.consP )	0.0858278692998146	0.310888262479083

Figure 1

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Postscript link

PDF link

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')

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