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Description of Statistical Computation

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, 23 Dec 2008 11:02:00 -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/2008/Dec/23/t1230055371aky8ly97umxx9cs.htm/, Retrieved Fri, 24 May 2024 05:40:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36368, Retrieved Fri, 24 May 2024 05:40:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact112

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] [] [2008-12-23 17:38:23] [74be16979710d4c4e7c6647856088456]
-   PD    [Kendall tau Correlation Matrix] [] [2008-12-23 18:02:00] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0	1	-1.3	16
0	1.1	0.4	38
0	1.2	-6.3	41
0	0.5	0.4	43
0	-1	-1.3	42
0	-0.8	0.7	40
0	-1.1	-3.5	48
0	-0.4	2	46
0	1.2	3.9	51
0	0.6	7.8	52
0	-0.1	7	55
0	0.3	-0.9	55
0	0.2	3	46
0	-0.2	-0.7	38
0.2	-0.8	8.8	43
4.1	-0.8	-8.1	43
-1	1	2.7	44
0	-0.1	2.5	45
4	-0.8	11.8	35
1.9	0.9	-1.5	36
1.1	1.8	-7.7	36
0	0.1	-13.5	25
0	-0.1	-1.6	31
0.7	-0.8	-1.8	35
1.6	-2.1	2.3	46
2	-0.3	3.1	47
0	1.4	-2.5	40
4.8	-10.8	7.1	29
-1.5	9.4	-7.5	28
-4.4	0.5	-4.8	29
-2.7	1.7	-7.1	29
2.8	1.1	2.7	30
0.7	0	10.5	26
0.4	-2.1	7.6	27
-1.9	-1.7	2.8	18
-0.7	0.4	-5.6	15
0	1.6	-5	1
0	0.5	-2.9	1
0	-0.6	-5.2	2
8.3	0.1	9.7	2
1.4	0	6.9	1
0	-0.6	9.3	-4
-1.2	-1.42	-1.4	1
0	-0.4	1.1	6
5.1	-0.1	-11.2	4
-3.7	1.4	-0.5	-1
-4.1	0.7	-8.9	-3
3.5	-0.9	2.4	-8
0	-1	1.9	-24
1.2	-0.1	0.5	-29
0	0.4	-0.1	-40
0	-0.3	-2.8	-32
0.2	0.2	-1.8	-41
-1.1	0.9	-0.9	-48
-3.9	-0.5	-0.9	-48
0.2	-0.5	1.2	-62
-0.4	0.6	6.6	-74
-0.2	0.8	5.1	-65
-0.7	-0.2	5.6	-61
2.2	-1.42	1.3	-78
2.2	0.2	2.1	-61

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36368&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]1 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=36368&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36368&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 computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( energieprijzen , industriële_productie )-0.2419536027509440.0101176929500789
tau( energieprijzen , nieuwe_personenwagens )0.2044666820144430.0282971388824316
tau( energieprijzen , werkloosheid )0.06258313750339450.503775491712184
tau( industriële_productie , nieuwe_personenwagens )-0.2072125196285450.0197896468264133
tau( industriële_productie , werkloosheid )0.01224281616505700.89092848339952
tau( nieuwe_personenwagens , werkloosheid )0.03360914190675040.704051484710579

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( energieprijzen , industriële_productie ) & -0.241953602750944 & 0.0101176929500789 \tabularnewline
tau( energieprijzen , nieuwe_personenwagens ) & 0.204466682014443 & 0.0282971388824316 \tabularnewline
tau( energieprijzen , werkloosheid ) & 0.0625831375033945 & 0.503775491712184 \tabularnewline
tau( industriële_productie , nieuwe_personenwagens ) & -0.207212519628545 & 0.0197896468264133 \tabularnewline
tau( industriële_productie , werkloosheid ) & 0.0122428161650570 & 0.89092848339952 \tabularnewline
tau( nieuwe_personenwagens , werkloosheid ) & 0.0336091419067504 & 0.704051484710579 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36368&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( energieprijzen , industriële_productie )[/C][C]-0.241953602750944[/C][C]0.0101176929500789[/C][/ROW]
[ROW][C]tau( energieprijzen , nieuwe_personenwagens )[/C][C]0.204466682014443[/C][C]0.0282971388824316[/C][/ROW]
[ROW][C]tau( energieprijzen , werkloosheid )[/C][C]0.0625831375033945[/C][C]0.503775491712184[/C][/ROW]
[ROW][C]tau( industriële_productie , nieuwe_personenwagens )[/C][C]-0.207212519628545[/C][C]0.0197896468264133[/C][/ROW]
[ROW][C]tau( industriële_productie , werkloosheid )[/C][C]0.0122428161650570[/C][C]0.89092848339952[/C][/ROW]
[ROW][C]tau( nieuwe_personenwagens , werkloosheid )[/C][C]0.0336091419067504[/C][C]0.704051484710579[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36368&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36368&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( energieprijzen , industriële_productie )-0.2419536027509440.0101176929500789
tau( energieprijzen , nieuwe_personenwagens )0.2044666820144430.0282971388824316
tau( energieprijzen , werkloosheid )0.06258313750339450.503775491712184
tau( industriële_productie , nieuwe_personenwagens )-0.2072125196285450.0197896468264133
tau( industriële_productie , werkloosheid )0.01224281616505700.89092848339952
tau( nieuwe_personenwagens , werkloosheid )0.03360914190675040.704051484710579


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
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')