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Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 14 Dec 2010 16:19:31 +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/14/t1292343553tzanliocvqspthz.htm/, Retrieved Thu, 02 May 2024 14:48:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109836, Retrieved Thu, 02 May 2024 14:48:28 +0000
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Original text written by user:
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User-defined keywords
Estimated Impact118
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]
-   PD  [Kendall tau Correlation Matrix] [Pearson correlati...] [2010-12-14 16:08:32] [b3140021f9a1a3896de9ecbfce0f1101]
-    D      [Kendall tau Correlation Matrix] [Pearson correlati...] [2010-12-14 16:19:31] [0605ea080d54454c99180f574351b8e4] [Current]
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Dataseries X:
25	11	7	8	23
17	6	17	8	25
18	8	12	9	19
16	10	12	7	29
20	10	11	4	25
16	11	11	11	21
18	16	12	7	22
17	11	13	7	25
30	12	16	10	18
23	8	11	10	22
18	12	10	8	15
21	9	9	9	20
31	14	17	11	20
27	15	11	9	21
21	9	14	13	21
16	8	15	9	24
20	9	15	6	24
17	9	13	6	23
25	16	18	16	24
26	11	18	5	18
25	8	12	7	25
17	9	17	9	21
32	12	18	12	22
22	9	14	9	23
17	9	16	5	23
20	14	14	10	24
29	10	12	8	23
23	14	17	7	21
20	10	12	8	28
11	6	6	4	16
26	13	12	8	29
22	10	12	8	27
14	15	13	8	16
19	12	14	7	28
20	11	11	8	25
28	8	12	7	22
19	9	9	7	23
30	9	15	9	26
29	15	18	11	23
26	9	15	6	25
23	10	12	8	21
21	12	14	9	24
28	11	13	6	22
23	14	13	10	27
18	6	11	8	26
20	8	16	10	24
21	10	11	5	24
28	12	16	14	22
10	5	8	6	24
22	10	15	6	20
31	10	21	12	26
29	13	18	12	21
22	10	13	8	19
23	10	15	10	21
20	9	19	10	16
18	8	15	10	22
25	14	11	5	15
21	8	10	7	17
24	9	13	10	15
25	14	15	11	21
13	8	12	7	19
28	8	16	12	24
25	7	18	11	17
9	6	8	11	23
16	8	13	5	24
19	6	17	8	14
29	11	7	4	22
14	11	12	7	16
22	14	14	11	19
15	8	6	6	25
15	8	10	4	24
20	11	11	8	26
18	10	14	9	26
33	14	11	8	25
22	11	13	11	18
16	9	12	8	21
16	8	9	4	23
18	13	12	6	20
18	12	13	9	13
22	13	12	13	15
30	14	9	9	14
30	12	15	10	22
24	14	24	20	10
21	13	17	11	22
29	16	11	6	24
31	9	17	9	19
20	9	11	7	20
16	9	12	9	13
22	8	14	10	20
20	7	11	9	22
28	16	16	8	24
38	11	21	7	29
22	9	14	6	12
20	11	20	13	20
17	9	13	6	21
22	13	15	10	22
31	16	19	16	20
24	14	11	12	26
18	12	10	8	23
23	13	14	12	24
15	11	11	8	22
12	4	15	4	28
15	8	11	8	12
20	8	17	7	24
34	16	18	11	20
31	14	10	8	23
19	11	11	8	28
21	9	13	9	24
22	9	16	9	23
24	10	9	6	29
32	16	9	6	26
33	11	9	6	22
13	16	12	5	22
25	12	12	7	23
29	14	18	10	30
18	10	15	8	17
20	10	10	8	23
15	12	11	8	25
33	14	9	6	24
26	16	5	4	24
18	9	12	8	24
28	8	24	20	20
17	8	14	6	22
12	7	7	4	28
17	9	12	9	25
21	10	13	6	24
18	13	8	9	24
10	10	11	5	23
29	11	9	5	30
31	8	11	8	24
19	9	13	8	21
9	13	10	6	25
13	14	13	6	25
19	12	10	8	29
21	12	13	8	22
23	14	8	5	27
21	11	16	7	24
15	14	9	8	29
19	10	12	7	21
26	14	14	8	24
16	11	9	5	23
19	9	11	10	27
31	16	14	9	25
19	9	12	7	21
15	7	12	6	21
23	14	11	10	29
17	14	12	6	21
21	8	9	11	20
17	11	9	6	19
25	14	15	9	24
20	11	8	4	13
19	20	8	7	25
20	11	17	8	23
17	9	11	5	26
21	10	12	8	23
26	13	20	10	22
17	8	12	9	24
21	15	7	5	24
28	14	11	8	24




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=109836&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=109836&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109836&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=pearson)
CMDPEPCO
CM10.3950.3290.3110.054
D0.39510.0270.1540.07
PE0.3290.02710.593-0.155
PC0.3110.1540.5931-0.203
O0.0540.07-0.155-0.2031

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & CM & D & PE & PC & O \tabularnewline
CM & 1 & 0.395 & 0.329 & 0.311 & 0.054 \tabularnewline
D & 0.395 & 1 & 0.027 & 0.154 & 0.07 \tabularnewline
PE & 0.329 & 0.027 & 1 & 0.593 & -0.155 \tabularnewline
PC & 0.311 & 0.154 & 0.593 & 1 & -0.203 \tabularnewline
O & 0.054 & 0.07 & -0.155 & -0.203 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109836&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]CM[/C][C]D[/C][C]PE[/C][C]PC[/C][C]O[/C][/ROW]
[ROW][C]CM[/C][C]1[/C][C]0.395[/C][C]0.329[/C][C]0.311[/C][C]0.054[/C][/ROW]
[ROW][C]D[/C][C]0.395[/C][C]1[/C][C]0.027[/C][C]0.154[/C][C]0.07[/C][/ROW]
[ROW][C]PE[/C][C]0.329[/C][C]0.027[/C][C]1[/C][C]0.593[/C][C]-0.155[/C][/ROW]
[ROW][C]PC[/C][C]0.311[/C][C]0.154[/C][C]0.593[/C][C]1[/C][C]-0.203[/C][/ROW]
[ROW][C]O[/C][C]0.054[/C][C]0.07[/C][C]-0.155[/C][C]-0.203[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109836&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109836&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=pearson)
CMDPEPCO
CM10.3950.3290.3110.054
D0.39510.0270.1540.07
PE0.3290.02710.593-0.155
PC0.3110.1540.5931-0.203
O0.0540.07-0.155-0.2031







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
CM;D0.39530.39490.3021
p-value(0)(0)(0)
CM;PE0.32880.28420.2144
p-value(0)(3e-04)(2e-04)
CM;PC0.31090.33090.2526
p-value(1e-04)(0)(0)
CM;O0.05410.00580.0018
p-value(0.4983)(0.9427)(0.9749)
D;PE0.02720.02130.0124
p-value(0.7332)(0.7897)(0.8314)
D;PC0.15430.12050.0884
p-value(0.0521)(0.1304)(0.1357)
D;O0.06980.08150.0587
p-value(0.3817)(0.3068)(0.314)
PE;PC0.59320.48210.3775
p-value(0)(0)(0)
PE;O-0.1549-0.1805-0.1349
p-value(0.0512)(0.0228)(0.0196)
PC;O-0.203-0.189-0.1383
p-value(0.0103)(0.0171)(0.0182)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
CM;D & 0.3953 & 0.3949 & 0.3021 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CM;PE & 0.3288 & 0.2842 & 0.2144 \tabularnewline
p-value & (0) & (3e-04) & (2e-04) \tabularnewline
CM;PC & 0.3109 & 0.3309 & 0.2526 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
CM;O & 0.0541 & 0.0058 & 0.0018 \tabularnewline
p-value & (0.4983) & (0.9427) & (0.9749) \tabularnewline
D;PE & 0.0272 & 0.0213 & 0.0124 \tabularnewline
p-value & (0.7332) & (0.7897) & (0.8314) \tabularnewline
D;PC & 0.1543 & 0.1205 & 0.0884 \tabularnewline
p-value & (0.0521) & (0.1304) & (0.1357) \tabularnewline
D;O & 0.0698 & 0.0815 & 0.0587 \tabularnewline
p-value & (0.3817) & (0.3068) & (0.314) \tabularnewline
PE;PC & 0.5932 & 0.4821 & 0.3775 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PE;O & -0.1549 & -0.1805 & -0.1349 \tabularnewline
p-value & (0.0512) & (0.0228) & (0.0196) \tabularnewline
PC;O & -0.203 & -0.189 & -0.1383 \tabularnewline
p-value & (0.0103) & (0.0171) & (0.0182) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109836&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]CM;D[/C][C]0.3953[/C][C]0.3949[/C][C]0.3021[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CM;PE[/C][C]0.3288[/C][C]0.2842[/C][C]0.2144[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](3e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]CM;PC[/C][C]0.3109[/C][C]0.3309[/C][C]0.2526[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CM;O[/C][C]0.0541[/C][C]0.0058[/C][C]0.0018[/C][/ROW]
[ROW][C]p-value[/C][C](0.4983)[/C][C](0.9427)[/C][C](0.9749)[/C][/ROW]
[ROW][C]D;PE[/C][C]0.0272[/C][C]0.0213[/C][C]0.0124[/C][/ROW]
[ROW][C]p-value[/C][C](0.7332)[/C][C](0.7897)[/C][C](0.8314)[/C][/ROW]
[ROW][C]D;PC[/C][C]0.1543[/C][C]0.1205[/C][C]0.0884[/C][/ROW]
[ROW][C]p-value[/C][C](0.0521)[/C][C](0.1304)[/C][C](0.1357)[/C][/ROW]
[ROW][C]D;O[/C][C]0.0698[/C][C]0.0815[/C][C]0.0587[/C][/ROW]
[ROW][C]p-value[/C][C](0.3817)[/C][C](0.3068)[/C][C](0.314)[/C][/ROW]
[ROW][C]PE;PC[/C][C]0.5932[/C][C]0.4821[/C][C]0.3775[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PE;O[/C][C]-0.1549[/C][C]-0.1805[/C][C]-0.1349[/C][/ROW]
[ROW][C]p-value[/C][C](0.0512)[/C][C](0.0228)[/C][C](0.0196)[/C][/ROW]
[ROW][C]PC;O[/C][C]-0.203[/C][C]-0.189[/C][C]-0.1383[/C][/ROW]
[ROW][C]p-value[/C][C](0.0103)[/C][C](0.0171)[/C][C](0.0182)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109836&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109836&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
CM;D0.39530.39490.3021
p-value(0)(0)(0)
CM;PE0.32880.28420.2144
p-value(0)(3e-04)(2e-04)
CM;PC0.31090.33090.2526
p-value(1e-04)(0)(0)
CM;O0.05410.00580.0018
p-value(0.4983)(0.9427)(0.9749)
D;PE0.02720.02130.0124
p-value(0.7332)(0.7897)(0.8314)
D;PC0.15430.12050.0884
p-value(0.0521)(0.1304)(0.1357)
D;O0.06980.08150.0587
p-value(0.3817)(0.3068)(0.314)
PE;PC0.59320.48210.3775
p-value(0)(0)(0)
PE;O-0.1549-0.1805-0.1349
p-value(0.0512)(0.0228)(0.0196)
PC;O-0.203-0.189-0.1383
p-value(0.0103)(0.0171)(0.0182)



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')