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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 computationTue, 14 Dec 2010 18:18:05 +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/t1292350576h1uutlh6b6l7b2i.htm/, Retrieved Thu, 02 May 2024 14:29:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109978, Retrieved Thu, 02 May 2024 14:29:33 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107
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 kendall] [2010-12-14 18:18:05] [09489ba95453d3f5c9e6f2eaeda915af] [Current]
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Dataseries X:
14544.5	94.6	-3.0	14097.8
15116.3	95.9	-3.7	14776.8
17413.2	104.7	-4.7	16833.3
16181.5	102.8	-6.4	15385.5
15607.4	98.1	-7.5	15172.6
17160.9	113.9	-7.8	16858.9
14915.8	80.9	-7.7	14143.5
13768	95.7	-6.6	14731.8
17487.5	113.2	-4.2	16471.6
16198.1	105.9	-2.0	15214
17535.2	108.8	-0.7	17637.4
16571.8	102.3	0.1	17972.4
16198.9	99	0.9	16896.2
16554.2	100.7	2.1	16698
19554.2	115.5	3.5	19691.6
15903.8	100.7	4.9	15930.7
18003.8	109.9	5.7	17444.6
18329.6	114.6	6.2	17699.4
16260.7	85.4	6.5	15189.8
14851.9	100.5	6.5	15672.7
18174.1	114.8	6.3	17180.8
18406.6	116.5	6.2	17664.9
18466.5	112.9	6.4	17862.9
16016.5	102	6.3	16162.3
17428.5	106	5.8	17463.6
17167.2	105.3	5.1	16772.1
19630	118.8	5.1	19106.9
17183.6	106.1	5.8	16721.3
18344.7	109.3	6.7	18161.3
19301.4	117.2	7.1	18509.9
18147.5	92.5	6.7	17802.7
16192.9	104.2	5.5	16409.9
18374.4	112.5	4.2	17967.7
20515.2	122.4	3.0	20286.6
18957.2	113.3	2.2	19537.3
16471.5	100	2.0	18021.9
18746.8	110.7	1.8	20194.3
19009.5	112.8	1.8	19049.6
19211.2	109.8	1.5	20244.7
20547.7	117.3	0.4	21473.3
19325.8	109.1	-0.9	19673.6
20605.5	115.9	-1.7	21053.2
20056.9	96	-2.6	20159.5
16141.4	99.8	-4.4	18203.6
20359.8	116.8	-8.3	21289.5
19711.6	115.7	-14.4	20432.3
15638.6	99.4	-21.3	17180.4
14384.5	94.3	-26.5	15816.8
13855.6	91	-29.2	15071.8
14308.3	93.2	-30.8	14521.1
15290.6	103.1	-30.9	15668.8
14423.8	94.1	-29.5	14346.9
13779.7	91.8	-27.1	13881
15686.3	102.7	-24.4	15465.9
14733.8	82.6	-21.9	14238.2
12522.5	89.1	-19.3	13557.7
16189.4	104.5	-17.0	16127.6
16059.1	105.1	-13.8	16793.9
16007.1	95.1	-9.9	16014
15806.8	88.7	-7.9	16867.9
15160	86.3	-7.2	16014.6
15692.1	91.8	-6.2	15878.6
18908.9	111.5	-4.5	18664.9
16969.9	99.7	-3.9	17962.5
16997.5	97.5	-5.0	17332.7
19858.9	111.7	-6.2	19542.1
17681.2	86.2	-6.1	17203.6
16006.9	95.4	-5.0	16579




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

\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
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109978&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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109978&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109978&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Correlations for all pairs of data series (method=kendall)
uitvoerproductieondernemersvertrouweninvoer
uitvoer10.6250.3580.755
productie0.62510.3230.528
ondernemersvertrouwen0.3580.32310.273
invoer0.7550.5280.2731

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & uitvoer & productie & ondernemersvertrouwen & invoer \tabularnewline
uitvoer & 1 & 0.625 & 0.358 & 0.755 \tabularnewline
productie & 0.625 & 1 & 0.323 & 0.528 \tabularnewline
ondernemersvertrouwen & 0.358 & 0.323 & 1 & 0.273 \tabularnewline
invoer & 0.755 & 0.528 & 0.273 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109978&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]uitvoer[/C][C]productie[/C][C]ondernemersvertrouwen[/C][C]invoer[/C][/ROW]
[ROW][C]uitvoer[/C][C]1[/C][C]0.625[/C][C]0.358[/C][C]0.755[/C][/ROW]
[ROW][C]productie[/C][C]0.625[/C][C]1[/C][C]0.323[/C][C]0.528[/C][/ROW]
[ROW][C]ondernemersvertrouwen[/C][C]0.358[/C][C]0.323[/C][C]1[/C][C]0.273[/C][/ROW]
[ROW][C]invoer[/C][C]0.755[/C][C]0.528[/C][C]0.273[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109978&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109978&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=kendall)
uitvoerproductieondernemersvertrouweninvoer
uitvoer10.6250.3580.755
productie0.62510.3230.528
ondernemersvertrouwen0.3580.32310.273
invoer0.7550.5280.2731







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
uitvoer;productie0.7780.79830.6254
p-value(0)(0)(0)
uitvoer;ondernemersvertrouwen0.5580.52280.3576
p-value(0)(0)(0)
uitvoer;invoer0.9280.91470.755
p-value(0)(0)(0)
productie;ondernemersvertrouwen0.44290.44850.3226
p-value(2e-04)(1e-04)(1e-04)
productie;invoer0.71640.71080.5279
p-value(0)(0)(0)
ondernemersvertrouwen;invoer0.450.41930.2731
p-value(1e-04)(4e-04)(0.001)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
uitvoer;productie & 0.778 & 0.7983 & 0.6254 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
uitvoer;ondernemersvertrouwen & 0.558 & 0.5228 & 0.3576 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
uitvoer;invoer & 0.928 & 0.9147 & 0.755 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
productie;ondernemersvertrouwen & 0.4429 & 0.4485 & 0.3226 \tabularnewline
p-value & (2e-04) & (1e-04) & (1e-04) \tabularnewline
productie;invoer & 0.7164 & 0.7108 & 0.5279 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
ondernemersvertrouwen;invoer & 0.45 & 0.4193 & 0.2731 \tabularnewline
p-value & (1e-04) & (4e-04) & (0.001) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109978&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]uitvoer;productie[/C][C]0.778[/C][C]0.7983[/C][C]0.6254[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]uitvoer;ondernemersvertrouwen[/C][C]0.558[/C][C]0.5228[/C][C]0.3576[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]uitvoer;invoer[/C][C]0.928[/C][C]0.9147[/C][C]0.755[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]productie;ondernemersvertrouwen[/C][C]0.4429[/C][C]0.4485[/C][C]0.3226[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]productie;invoer[/C][C]0.7164[/C][C]0.7108[/C][C]0.5279[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]ondernemersvertrouwen;invoer[/C][C]0.45[/C][C]0.4193[/C][C]0.2731[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](4e-04)[/C][C](0.001)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109978&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109978&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
uitvoer;productie0.7780.79830.6254
p-value(0)(0)(0)
uitvoer;ondernemersvertrouwen0.5580.52280.3576
p-value(0)(0)(0)
uitvoer;invoer0.9280.91470.755
p-value(0)(0)(0)
productie;ondernemersvertrouwen0.44290.44850.3226
p-value(2e-04)(1e-04)(1e-04)
productie;invoer0.71640.71080.5279
p-value(0)(0)(0)
ondernemersvertrouwen;invoer0.450.41930.2731
p-value(1e-04)(4e-04)(0.001)



Parameters (Session):
par1 = kendall ;
Parameters (R input):
par1 = kendall ;
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')