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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 computationFri, 24 Dec 2010 16:41:33 +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/24/t12932088654rgjkux1qwpb9py.htm/, Retrieved Tue, 30 Apr 2024 06:40:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115189, Retrieved Tue, 30 Apr 2024 06:40:28 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [] [2010-12-24 16:41:33] [95610e892c4b5c84ff80f4c898567a9d] [Current]
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Dataseries X:
1.35	75.53
1.91	75.75
1.31	76.57
1.19	77.59
1.3	77.15
1.14	79.08
1.1	80.29
1.02	79.94
1.11	80.19
1.18	79.70
1.24	79.14
1.36	78.23
1.29	77.16
1.73	76.77
1.41	76.19
1.15	74.83
1.31	74.33
1.15	72.71
1.08	71.32
1.1	71.88
1.14	71.78
1.24	71.77
1.33	72.17
1.49	70.84
1.38	70.64
1.96	70.85
1.36	71.43
1.24	78.52
1.35	81.12
1.23	84.16
1.09	84.36
1.08	84.13
1.33	83.59
1.35	82.13
1.38	83.03
1.5	83.91
1.47	83.01
2.09	82.36
1.52	82.01
1.29	81.83
1.52	80.89
1.27	82.86
1.35	83.28
1.29	82.63
1.41	81.52
1.39	82.20
1.45	81.97
1.53	81.60
1.45	82.36
2.11	82.55
1.53	81.27
1.38	79.89
1.54	74.44
1.35	73.47
1.29	73.16
1.33	73.16
1.47	72.94
1.47	72.89
1.54	73.26
1.59	73.93
1.5	72.58
2	72.00
1.51	72.79
1.4	71.86
1.62	69.74
1.44	69.73
1.29	69.05
1.28	69.63
1.4	70.48
1.39	72.49
1.46	72.66
1.49	74.77




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 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 & 10 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115189&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]10 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=115189&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115189&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 time10 seconds
R Server'George Udny Yule' @ 72.249.76.132







Correlations for all pairs of data series (method=pearson)
tulpolie
tulp1-0.063
olie-0.0631

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & tulp & olie \tabularnewline
tulp & 1 & -0.063 \tabularnewline
olie & -0.063 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115189&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]tulp[/C][C]olie[/C][/ROW]
[ROW][C]tulp[/C][C]1[/C][C]-0.063[/C][/ROW]
[ROW][C]olie[/C][C]-0.063[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115189&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115189&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)
tulpolie
tulp1-0.063
olie-0.0631







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
tulp;olie-0.0627-0.0813-0.0604
p-value(0.6007)(0.4971)(0.4567)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
tulp;olie & -0.0627 & -0.0813 & -0.0604 \tabularnewline
p-value & (0.6007) & (0.4971) & (0.4567) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115189&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]tulp;olie[/C][C]-0.0627[/C][C]-0.0813[/C][C]-0.0604[/C][/ROW]
[ROW][C]p-value[/C][C](0.6007)[/C][C](0.4971)[/C][C](0.4567)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115189&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115189&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
tulp;olie-0.0627-0.0813-0.0604
p-value(0.6007)(0.4971)(0.4567)



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')