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Author's title

Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationFri, 10 Dec 2010 13:19:02 +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/10/t12919870274phbsjwdho5rbei.htm/, Retrieved Mon, 29 Apr 2024 16:03:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107656, Retrieved Mon, 29 Apr 2024 16:03:45 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
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] [] [2010-12-10 13:19:02] [8e16b01a5be2b3f7f3ad6418d9d6fd5b] [Current]
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Dataseries X:
356	182	89
386	213	97
444	227	154
387	209	81
327	219	110
448	221	116
225	114	73
182	97	73
460	205	174
411	215	103
342	224	130
361	189	91
377	182	136
331	201	106
428	198	136
340	173	122
352	238	131
461	258	135
221	122	75
198	101	68
422	259	143
329	243	115
320	188	93
375	173	128
364	224	152
351	215	125
380	196	107
319	159	116
322	187	220
386	208	137
221	131	34
187	93	51
344	210	153
342	228	145
365	176	116
313	195	145
356	188	98
337	188	118
389	190	139
326	188	140
343	176	113
357	225	149
220	93	79
218	79	47
391	235	166
425	247	180
332	195	122
298	197	134
360	211	114
336	156	125
325	209	181
393	180	142
301	185	143
426	303	187
265	129	137
210	85	62
429	249	239
440	231	157
357	212	139
431	240	187
442	234	99
442	217	146
544	287	175
420	221	148
396	208	130
482	241	183
261	156	115
211	96	80
448	320	223
468	242	131
464	227	201
425	200	157




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107656&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107656&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107656&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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132







Correlations for all pairs of data series (method=pearson)
VlaanderenWallonieBrussel
Vlaanderen10.8540.671
Wallonie0.85410.724
Brussel0.6710.7241

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Vlaanderen & Wallonie & Brussel \tabularnewline
Vlaanderen & 1 & 0.854 & 0.671 \tabularnewline
Wallonie & 0.854 & 1 & 0.724 \tabularnewline
Brussel & 0.671 & 0.724 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107656&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Vlaanderen[/C][C]Wallonie[/C][C]Brussel[/C][/ROW]
[ROW][C]Vlaanderen[/C][C]1[/C][C]0.854[/C][C]0.671[/C][/ROW]
[ROW][C]Wallonie[/C][C]0.854[/C][C]1[/C][C]0.724[/C][/ROW]
[ROW][C]Brussel[/C][C]0.671[/C][C]0.724[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107656&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107656&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)
VlaanderenWallonieBrussel
Vlaanderen10.8540.671
Wallonie0.85410.724
Brussel0.6710.7241







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Vlaanderen;Wallonie0.85440.75690.5741
p-value(0)(0)(0)
Vlaanderen;Brussel0.6710.59480.4355
p-value(0)(0)(0)
Wallonie;Brussel0.72380.64170.4813
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
Vlaanderen;Wallonie & 0.8544 & 0.7569 & 0.5741 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Vlaanderen;Brussel & 0.671 & 0.5948 & 0.4355 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Wallonie;Brussel & 0.7238 & 0.6417 & 0.4813 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107656&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]Vlaanderen;Wallonie[/C][C]0.8544[/C][C]0.7569[/C][C]0.5741[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Vlaanderen;Brussel[/C][C]0.671[/C][C]0.5948[/C][C]0.4355[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Wallonie;Brussel[/C][C]0.7238[/C][C]0.6417[/C][C]0.4813[/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=107656&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107656&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
Vlaanderen;Wallonie0.85440.75690.5741
p-value(0)(0)(0)
Vlaanderen;Brussel0.6710.59480.4355
p-value(0)(0)(0)
Wallonie;Brussel0.72380.64170.4813
p-value(0)(0)(0)



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')