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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 computationThu, 29 Nov 2007 04:49:00 -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/29/t1196336338x9xqkezuyrqqme3.htm/, Retrieved Fri, 03 May 2024 12:27:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7442, Retrieved Fri, 03 May 2024 12:27:52 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174

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] [Kendall Tau Corre...] [2007-11-29 11:49:00] [5f37cd8ab253ad45d932eaa1e9b30ad5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
108,9	519	13,0	103,9
108,8	509	10,9	104,5
108,8	512	9,6	106,3
108,8	519	4,0	108,6
108,8	517	-1,1	110,0
108,8	510	-7,7	110,4
108,8	509	-8,9	109,8
108,8	501	-8,0	108,8
108,8	507	-7,1	108,9
108,8	569	-5,3	109,7
108,8	580	-2,5	110,4
108,8	578	-2,4	111,5
108,8	565	-2,9	112,7
108,8	547	-4,8	113,8
109,1	555	-7,2	113,9
113,2	562	1,7	113,4
112,1	561	2,2	113,8
112,1	555	13,4	114,1
116,2	544	12,3	113,5
118,1	537	13,7	113,9
119,2	543	4,4	116,1
119,2	594	-2,5	118,4
119,2	611	-12,2	120,5
120,0	613	-7,0	122,0
121,5	611	-4,1	121,4
123,5	594	0,9	120,5
123,5	595	6,5	120,8
128,3	591	3,7	110,4
126,9	589	-3,9	109,3
122,5	584	-14,4	108,9
119,7	573	-17,1	110,0
122,6	567	-10,0	112,3
123,3	569	-5,2	114,5
123,7	621	2,3	114,8
121,7	629	-4,8	113,3
121,0	628	-2,3	112,2
121,0	612	-5,4	112,8
121,0	595	-7,7	113,8
121,0	597	-5,9	114,2
129,4	593	-4,3	114,7
130,8	590	9,2	115,2
130,8	580	16,9	115,0
129,6	574	18,4	114,9
129,6	573	6,6	114,4
134,7	573	4,1	113,8
131,0	620	1,4	114,5
126,9	626	9,5	116,0
130,4	620	0,7	116,7
130,4	588	1,4	116,4
131,6	566	-1,6	116,0
131,6	557	-0,7	115,9
131,6	561	-7,7	115,4
131,6	549	-15,5	115,2
128,8	532	-19,4	115,8

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7442&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7442&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7442&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( energieprijs , werkloosheid )0.3230671066979480.000834109086143453
tau( energieprijs , aantal-personenwagens )0.07548728309361930.433930237811944
tau( energieprijs , industriële-productie )0.4304841328939778.6625453892264e-06
tau( werkloosheid , aantal-personenwagens )-0.01125574991148210.904931646454918
tau( werkloosheid , industriële-productie )0.3303919960473410.000474657711839077
tau( aantal-personenwagens , industriële-productie )0.05281722883227870.575524203806077

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( energieprijs , werkloosheid ) & 0.323067106697948 & 0.000834109086143453 \tabularnewline
tau( energieprijs , aantal-personenwagens ) & 0.0754872830936193 & 0.433930237811944 \tabularnewline
tau( energieprijs , industriële-productie ) & 0.430484132893977 & 8.6625453892264e-06 \tabularnewline
tau( werkloosheid , aantal-personenwagens ) & -0.0112557499114821 & 0.904931646454918 \tabularnewline
tau( werkloosheid , industriële-productie ) & 0.330391996047341 & 0.000474657711839077 \tabularnewline
tau( aantal-personenwagens , industriële-productie ) & 0.0528172288322787 & 0.575524203806077 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7442&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( energieprijs , werkloosheid )[/C][C]0.323067106697948[/C][C]0.000834109086143453[/C][/ROW]
[ROW][C]tau( energieprijs , aantal-personenwagens )[/C][C]0.0754872830936193[/C][C]0.433930237811944[/C][/ROW]
[ROW][C]tau( energieprijs , industriële-productie )[/C][C]0.430484132893977[/C][C]8.6625453892264e-06[/C][/ROW]
[ROW][C]tau( werkloosheid , aantal-personenwagens )[/C][C]-0.0112557499114821[/C][C]0.904931646454918[/C][/ROW]
[ROW][C]tau( werkloosheid , industriële-productie )[/C][C]0.330391996047341[/C][C]0.000474657711839077[/C][/ROW]
[ROW][C]tau( aantal-personenwagens , industriële-productie )[/C][C]0.0528172288322787[/C][C]0.575524203806077[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7442&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7442&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( energieprijs , werkloosheid )0.3230671066979480.000834109086143453
tau( energieprijs , aantal-personenwagens )0.07548728309361930.433930237811944
tau( energieprijs , industriële-productie )0.4304841328939778.6625453892264e-06
tau( werkloosheid , aantal-personenwagens )-0.01125574991148210.904931646454918
tau( werkloosheid , industriële-productie )0.3303919960473410.000474657711839077
tau( aantal-personenwagens , industriële-productie )0.05281722883227870.575524203806077


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')