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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationWed, 22 Dec 2010 20:28:55 +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/22/t1293049611jy7vp2booj9uw5l.htm/, Retrieved Sun, 05 May 2024 23:48:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114565, Retrieved Sun, 05 May 2024 23:48:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159

Tree of Dependent Computations

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]
- RMPD  [Kendall tau Correlation Matrix] [WS 10 - Pearson c...] [2010-12-10 16:13:49] [033eb2749a430605d9b2be7c4aac4a0c]
-         [Kendall tau Correlation Matrix] [] [2010-12-13 18:15:16] [d7b28a0391ab3b2ddc9f9fba95a43f33]
-           [Kendall tau Correlation Matrix] [] [2010-12-21 18:27:28] [42a441ca3193af442aa2201743dfb347]
-    D        [Kendall tau Correlation Matrix] [] [2010-12-22 16:43:37] [f82dc80ca9fc4fd83b66f6024d510f8c]
-    D            [Kendall tau Correlation Matrix] [] [2010-12-22 20:28:55] [9d4f9c24554023ef0148ede5dd3a4d11] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5	4	3	2	12
4	4	3	2	11
5	5	5	2	15
2	2	2	1	6
4	5	4	2	13
3	3	4	2	10
5	3	4	2	12
5	5	4	2	14
4	3	5	2	12
3	3	NA	2	6
2	4	4	1	10
4	4	4	2	12
4	4	4	1	12
4	3	4	2	11
5	5	5	2	15
5	4	3	1	12
4	4	2	1	10
4	4	4	2	12
4	4	3	1	11
4	4	4	2	12
4	4	3	1	11
4	4	4	2	12
5	4	4	2	13
3	4	4	2	11
5	NA	4	1	9
4	4	5	2	13
4	3	3	1	10
5	5	4	2	14
4	4	4	2	12
3	4	3	1	10
4	4	4	2	12
4	2	2	1	8
4	3	3	2	10
4	4	4	2	12
4	4	4	1	12
2	2	3	1	7
3	NA	3	1	6
4	4	4	1	12
3	4	3	2	10
4	3	3	1	10
2	4	4	1	10
4	4	4	2	12
5	5	5	1	15
4	3	3	1	10
4	4	2	2	10
4	4	4	2	12
5	4	4	2	13
3	4	4	2	11
4	4	3	2	11
4	4	4	1	12
5	5	4	2	14
3	3	4	1	10
4	4	4	1	12
5	4	4	2	13
2	1	2	1	5
2	2	2	2	6
4	4	4	2	12
4	4	4	2	12
4	3	4	1	11
4	3	3	2	10
2	2	3	1	7
4	4	4	1	12
5	5	4	2	14
3	4	4	2	11
4	4	4	2	12
5	4	4	1	13
5	5	4	2	14
4	4	3	1	11
4	4	4	2	12
4	4	4	1	12
2	3	3	1	8
3	4	4	2	11
5	5	4	2	14
4	5	5	1	14
4	4	4	1	12
3	2	4	2	9
4	4	5	2	13
3	4	4	2	11
4	4	4	1	12
4	4	4	1	12
4	4	4	1	12
4	4	4	1	12
4	4	4	2	12
4	4	4	1	12
4	4	3	2	11
3	4	3	2	10
4	3	2	1	9
4	4	4	2	12
4	4	4	2	12
4	4	4	2	12
3	3	3	2	9
5	5	5	2	15
4	4	4	2	12
4	4	4	2	12
4	4	4	2	12
4	4	2	2	10
5	4	4	2	13
4	3	2	2	9
4	4	4	1	12
2	4	4	1	10
5	5	4	2	14
4	4	3	1	11
5	5	5	2	15
4	4	3	1	11
4	4	3	2	11
4	4	4	1	12
4	4	4	2	12
4	4	4	1	12
4	3	4	1	11
2	4	1	2	7
4	4	4	2	12
5	5	4	2	14
4	4	3	2	11
4	3	4	1	11
2	4	4	2	10
5	4	4	1	13
5	5	3	2	13
2	2	4	2	8
4	4	3	2	11
4	4	4	2	12
4	4	3	2	11
5	4	4	2	13
4	4	4	2	12
5	5	4	2	14
5	4	4	2	13
5	5	5	2	15
3	3	4	1	10
4	4	3	2	11
4	3	2	2	9
4	4	3	2	11
3	4	3	1	10
4	4	3	1	11
4	2	2	2	8
4	4	3	1	11
4	4	4	1	12
4	4	4	2	12
4	3	2	1	9
4	4	3	1	11
3	4	3	2	10
2	3	3	2	8
2	3	4	1	9
4	2	2	2	8
2	4	3	1	9
5	5	5	2	15
3	4	4	1	11
2	4	2	2	8
5	4	4	2	13
4	4	4	1	12
4	4	4	1	12
2	3	4	1	9
3	2	2	2	7
5	4	4	2	13
4	2	3	1	9
2	2	2	2	6
2	3	3	2	8
2	3	3	2	8
5	5	5	2	15
2	2	2	2	6
4	3	2	2	9
4	4	3	2	11
2	2	4	2	8
2	3	3	2	8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114565&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114565&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114565&T=0

As an alternative you can also use a QR Code:  
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'RServer@AstonUniversity' @ vre.aston.ac.uk
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.






Correlations for all pairs of data series (method=pearson)
CCSCHCSAORTGPCCS
CCS10.5940.3870.1470.8
CHCS0.59410.5360.1550.856
AORT0.3870.53610.0610.759
G0.1470.1550.06110.163
PCCS 0.80.8560.7590.1631

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & CCS & CHCS & AORT & G & PCCS
 \tabularnewline
CCS & 1 & 0.594 & 0.387 & 0.147 & 0.8 \tabularnewline
CHCS & 0.594 & 1 & 0.536 & 0.155 & 0.856 \tabularnewline
AORT & 0.387 & 0.536 & 1 & 0.061 & 0.759 \tabularnewline
G & 0.147 & 0.155 & 0.061 & 1 & 0.163 \tabularnewline
PCCS
 & 0.8 & 0.856 & 0.759 & 0.163 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114565&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]CCS[/C][C]CHCS[/C][C]AORT[/C][C]G[/C][C]PCCS
[/C][/ROW]
[ROW][C]CCS[/C][C]1[/C][C]0.594[/C][C]0.387[/C][C]0.147[/C][C]0.8[/C][/ROW]
[ROW][C]CHCS[/C][C]0.594[/C][C]1[/C][C]0.536[/C][C]0.155[/C][C]0.856[/C][/ROW]
[ROW][C]AORT[/C][C]0.387[/C][C]0.536[/C][C]1[/C][C]0.061[/C][C]0.759[/C][/ROW]
[ROW][C]G[/C][C]0.147[/C][C]0.155[/C][C]0.061[/C][C]1[/C][C]0.163[/C][/ROW]
[ROW][C]PCCS
[/C][C]0.8[/C][C]0.856[/C][C]0.759[/C][C]0.163[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114565&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114565&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Correlations for all pairs of data series (method=pearson)
CCSCHCSAORTGPCCS
CCS10.5940.3870.1470.8
CHCS0.59410.5360.1550.856
AORT0.3870.53610.0610.759
G0.1470.1550.06110.163
PCCS 0.80.8560.7590.1631






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
CCS;CHCS0.59360.60090.5522
p-value(0)(0)(0)
CCS;AORT0.38710.39060.348
p-value(0)(0)(0)
CCS;G0.14690.16040.1498
p-value(0.0622)(0.0415)(0.0419)
CCS;PCCS 0.80010.80880.7281
p-value(0)(0)(0)
CHCS;AORT0.53650.51290.4727
p-value(0)(0)(0)
CHCS;G0.15490.1680.1582
p-value(0.0504)(0.0337)(0.0341)
CHCS;PCCS 0.85650.81340.7408
p-value(0)(0)(0)
AORT;G0.0610.0840.079
p-value(0.4419)(0.2896)(0.2882)
AORT;PCCS 0.75880.75220.671
p-value(0)(0)(0)
G;PCCS 0.16340.18980.166
p-value(0.0377)(0.0156)(0.016)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
CCS;CHCS & 0.5936 & 0.6009 & 0.5522 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CCS;AORT & 0.3871 & 0.3906 & 0.348 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CCS;G & 0.1469 & 0.1604 & 0.1498 \tabularnewline
p-value & (0.0622) & (0.0415) & (0.0419) \tabularnewline
CCS;PCCS
 & 0.8001 & 0.8088 & 0.7281 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CHCS;AORT & 0.5365 & 0.5129 & 0.4727 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CHCS;G & 0.1549 & 0.168 & 0.1582 \tabularnewline
p-value & (0.0504) & (0.0337) & (0.0341) \tabularnewline
CHCS;PCCS
 & 0.8565 & 0.8134 & 0.7408 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
AORT;G & 0.061 & 0.084 & 0.079 \tabularnewline
p-value & (0.4419) & (0.2896) & (0.2882) \tabularnewline
AORT;PCCS
 & 0.7588 & 0.7522 & 0.671 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
G;PCCS
 & 0.1634 & 0.1898 & 0.166 \tabularnewline
p-value & (0.0377) & (0.0156) & (0.016) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114565&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]CCS;CHCS[/C][C]0.5936[/C][C]0.6009[/C][C]0.5522[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CCS;AORT[/C][C]0.3871[/C][C]0.3906[/C][C]0.348[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CCS;G[/C][C]0.1469[/C][C]0.1604[/C][C]0.1498[/C][/ROW]
[ROW][C]p-value[/C][C](0.0622)[/C][C](0.0415)[/C][C](0.0419)[/C][/ROW]
[ROW][C]CCS;PCCS
[/C][C]0.8001[/C][C]0.8088[/C][C]0.7281[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CHCS;AORT[/C][C]0.5365[/C][C]0.5129[/C][C]0.4727[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CHCS;G[/C][C]0.1549[/C][C]0.168[/C][C]0.1582[/C][/ROW]
[ROW][C]p-value[/C][C](0.0504)[/C][C](0.0337)[/C][C](0.0341)[/C][/ROW]
[ROW][C]CHCS;PCCS
[/C][C]0.8565[/C][C]0.8134[/C][C]0.7408[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]AORT;G[/C][C]0.061[/C][C]0.084[/C][C]0.079[/C][/ROW]
[ROW][C]p-value[/C][C](0.4419)[/C][C](0.2896)[/C][C](0.2882)[/C][/ROW]
[ROW][C]AORT;PCCS
[/C][C]0.7588[/C][C]0.7522[/C][C]0.671[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]G;PCCS
[/C][C]0.1634[/C][C]0.1898[/C][C]0.166[/C][/ROW]
[ROW][C]p-value[/C][C](0.0377)[/C][C](0.0156)[/C][C](0.016)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114565&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114565&T=2

As an alternative you can also use a QR Code:  
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
CCS;CHCS0.59360.60090.5522
p-value(0)(0)(0)
CCS;AORT0.38710.39060.348
p-value(0)(0)(0)
CCS;G0.14690.16040.1498
p-value(0.0622)(0.0415)(0.0419)
CCS;PCCS 0.80010.80880.7281
p-value(0)(0)(0)
CHCS;AORT0.53650.51290.4727
p-value(0)(0)(0)
CHCS;G0.15490.1680.1582
p-value(0.0504)(0.0337)(0.0341)
CHCS;PCCS 0.85650.81340.7408
p-value(0)(0)(0)
AORT;G0.0610.0840.079
p-value(0.4419)(0.2896)(0.2882)
AORT;PCCS 0.75880.75220.671
p-value(0)(0)(0)
G;PCCS 0.16340.18980.166
p-value(0.0377)(0.0156)(0.016)


Figures (Output of Computation)

Input Parameters & R Code

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')