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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 27 Nov 2007 16:52:10 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/28/t11962069389pdn6up83a8nhzl.htm/, Retrieved Thu, 02 May 2024 11:07:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6970, Retrieved Thu, 02 May 2024 11:07:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196

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] [Workshop 4 Q3 (2)] [2007-11-27 23:52:10] [44cf2be50bc8700e14714598feda9df9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15761.3	0.9808	523000	106.5
16943.0	0.9811	519000	112.3
15070.3	1.0014	509000	102.8
13659.6	1.0183	512000	96,5
14768.9	1.0622	519000	101.0
14725.1	1.0773	517000	98.9
15998.1	1.0807	510000	105.1
15370.6	1.0848	509000	103.0
14956.9	1.1582	501000	99.0
15469.7	1.1663	507000	104.3
15101.8	1.1372	569000	94.6
11703.7	1.1139	580000	90.4
16283.6	1.1222	578000	108.9
16726.5	1.1692	565000	111.4
14968.9	1.1702	547000	100.8
14861.0	1.2286	555000	102.5
14583.3	1.2613	562000	98.2
15305.8	1.2646	561000	98.7
17903.9	1.2262	555000	113.3
16379.4	1.1985	544000	104.6
15420.3	1.2007	537000	99.3
17870.5	1.2138	543000	111.8
15912.8	1.2266	594000	97.3
13866.5	1.2176	611000	97.7
17823.2	1.2218	613000	115.6
17872.0	1.2490	611000	111.9
17420.4	1.2991	594000	107.0
16704.4	1.3408	595000	107.1
15991.2	1.3119	591000	100.6
16583.6	1.3014	589000	99.2
19123.5	1.3201	584000	108.4
17838.7	1.2938	573000	103.0
17209.4	1.2694	567000	99.8
18586.5	1.2165	569000	115.0
16258.1	1.2037	621000	90.8
15141.6	1.2292	629000	95.9
19202.1	1.2256	628000	114.4
17746.5	1.2015	612000	108.2
19090.1	1.1786	595000	112.6
18040.3	1.1856	597000	109.1
17515.5	1.2103	593000	105.0
17751.8	1.1938	590000	105.0
21072.4	1.2020	580000	118.5
17170.0	1.2271	574000	103.7
19439.5	1.2770	573000	112.5
19795.4	1.2650	573000	116.6
17574.9	1.2684	620000	96.6
16165.4	1.2811	626000	101.9
19464.6	1.2727	620000	116.5
19932.1	1.2611	588000	119.3
19961.2	1.2881	566000	115.4
17343.4	1.3213	557000	108.5
18924.2	1.2999	561000	111.5
18574.1	1.3074	549000	108.8
21350.6	1.3242	532000	121.8
18840.1	1.3516	526000	109.6
20304.8	1.3511	511000	112.2
21132.4	1.3419	499000	119.6
19753.9	1.3716	555000	103.4
18009.9	1.3622	565000	105.3
20390.4	1.3896	542000	113.5

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6970&T=0

[TABLE]
[ROW][C]Summary of compuational 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]1 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=6970&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6970&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( Belgische_uitvoer , Wisselkoers )0.4087431693989073.24389454542384e-06
tau( Belgische_uitvoer , Werkloosheid )0.08452331750829190.337734763687563
tau( Belgische_uitvoer , Industriële_productie )0.6560963255108348.14903700074865e-14
tau( Wisselkoers , Werkloosheid )0.1119659530629320.204119942998685
tau( Wisselkoers , Industriële_productie )0.1902679343981420.0303373163081324
tau( Werkloosheid , Industriële_productie )-0.005491528766668390.950361807164186

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( Belgische_uitvoer , Wisselkoers ) & 0.408743169398907 & 3.24389454542384e-06 \tabularnewline
tau( Belgische_uitvoer , Werkloosheid ) & 0.0845233175082919 & 0.337734763687563 \tabularnewline
tau( Belgische_uitvoer , Industriële_productie ) & 0.656096325510834 & 8.14903700074865e-14 \tabularnewline
tau( Wisselkoers , Werkloosheid ) & 0.111965953062932 & 0.204119942998685 \tabularnewline
tau( Wisselkoers , Industriële_productie ) & 0.190267934398142 & 0.0303373163081324 \tabularnewline
tau( Werkloosheid , Industriële_productie ) & -0.00549152876666839 & 0.950361807164186 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6970&T=1

[TABLE]
[ROW][C]Kendall tau rank correlations for all pairs of data series[/C][/ROW]
[ROW][C]pair[/C][C]tau[/C][C]p-value[/C][/ROW]
[ROW][C]tau( Belgische_uitvoer , Wisselkoers )[/C][C]0.408743169398907[/C][C]3.24389454542384e-06[/C][/ROW]
[ROW][C]tau( Belgische_uitvoer , Werkloosheid )[/C][C]0.0845233175082919[/C][C]0.337734763687563[/C][/ROW]
[ROW][C]tau( Belgische_uitvoer , Industriële_productie )[/C][C]0.656096325510834[/C][C]8.14903700074865e-14[/C][/ROW]
[ROW][C]tau( Wisselkoers , Werkloosheid )[/C][C]0.111965953062932[/C][C]0.204119942998685[/C][/ROW]
[ROW][C]tau( Wisselkoers , Industriële_productie )[/C][C]0.190267934398142[/C][C]0.0303373163081324[/C][/ROW]
[ROW][C]tau( Werkloosheid , Industriële_productie )[/C][C]-0.00549152876666839[/C][C]0.950361807164186[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6970&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6970&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:

Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( Belgische_uitvoer , Wisselkoers )0.4087431693989073.24389454542384e-06
tau( Belgische_uitvoer , Werkloosheid )0.08452331750829190.337734763687563
tau( Belgische_uitvoer , Industriële_productie )0.6560963255108348.14903700074865e-14
tau( Wisselkoers , Werkloosheid )0.1119659530629320.204119942998685
tau( Wisselkoers , Industriële_productie )0.1902679343981420.0303373163081324
tau( Werkloosheid , Industriële_productie )-0.005491528766668390.950361807164186


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
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='kendall')
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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations for all pairs of data series',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'tau',1,TRUE)
a<-table.element(a,'p-value',1,TRUE)
a<-table.row.end(a)
n <- length(y[,1])
n
cor.test(y[1,],y[2,],method='kendall')
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste('tau(',dimnames(t(x))[[2]][i])
dum <- paste(dum,',')
dum <- paste(dum,dimnames(t(x))[[2]][j])
dum <- paste(dum,')')
a<-table.element(a,dum,header=TRUE)
r <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,r$estimate)
a<-table.element(a,r$p.value)
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable.tab')