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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 computationFri, 06 Nov 2009 02:20:07 -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/2009/Nov/06/t1257499259j9a0kih6v9bdpla.htm/, Retrieved Sun, 28 Apr 2024 06:38:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54230, Retrieved Sun, 28 Apr 2024 06:38:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact234

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] [3/11/2009] [2009-11-02 21:25:00] [b98453cac15ba1066b407e146608df68]
-    D  [Kendall tau Correlation Matrix] [WS 6] [2009-11-05 11:06:22] [eaf42bcf5162b5692bb3c7f9d4636222]
-    D      [Kendall tau Correlation Matrix] [Workshop 6: Kenda...] [2009-11-06 09:20:07] [a5c6be3c0aa55fdb2a703a08e16947ef] [Current]
-   PD        [Kendall tau Correlation Matrix] [Kendall Tau Rank ...] [2009-12-11 11:14:13] [1433a524809eda02c3198b3ae6eebb69]
-    D          [Kendall tau Correlation Matrix] [Kendall Tau Rank ...] [2009-12-11 11:58:45] [1433a524809eda02c3198b3ae6eebb69]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.7461	0.5857	1.2413	8.9	2.86
0.7775	0.5858	1.2758	8.6	2.55
0.7790	0.5717	1.2729	8.3	2.27
0.7744	0.5945	1.2695	8.3	2.26
0.7905	0.5961	1.2858	8.3	2.57
0.7719	0.5973	1.2741	8.4	3.07
0.7811	0.6036	1.2823	8.5	2.76
0.7557	0.6096	1.2588	8.4	2.51
0.7637	0.6315	1.2856	8.6	2.87
0.7595	0.6262	1.2619	8.5	3.14
0.7471	0.6121	1.2590	8.5	3.11
0.7615	0.6326	1.2865	8.5	3.16
0.7487	0.6214	1.2667	8.5	2.47
0.7389	0.6274	1.2505	8.5	2.57
0.7337	0.6175	1.2205	8.5	2.89
0.7510	0.6208	1.2220	8.5	2.63
0.7382	0.6225	1.1990	8.5	2.38
0.7159	0.5889	1.1583	8.5	1.69
0.7542	0.6020	1.1931	8.5	1.96
0.7636	0.5932	1.2028	8.5	2.19
0.7433	0.5841	1.1802	8.6	1.87
0.7658	0.6000	1.2084	8.4	1.6
0.7627	0.5947	1.1996	8.1	1.63
0.7480	0.5891	1.1870	8.00	1.22
0.7692	0.6051	1.2013	8.00	1.21
0.7850	0.5960	1.2120	8.00	1.49
0.7913	0.6012	1.2133	8.00	1.64
0.7720	0.5957	1.1866	7.9	1.66
0.7880	0.5959	1.2067	7.8	1.77
0.8070	0.6049	1.2240	7.8	1.82
0.8268	0.6064	1.2566	7.9	1.78
0.8244	0.6137	1.2608	8.1	1.28
0.8487	0.6311	1.3005	8.00	1.29
0.8572	0.6258	1.2955	7.6	1.37
0.8214	0.6010	1.2500	7.3	1.12
0.8827	0.6232	1.3158	7.00	1.51
0.9216	0.6384	1.3358	6.8	2.24
0.8865	0.6014	1.2817	7.00	2.94
0.8816	0.5980	1.2707	7.1	3.09
0.8884	0.5987	1.2595	7.2	3.46
0.9466	0.6237	1.3182	7.1	3.64
0.9180	0.5813	1.2665	6.9	4.39
0.9337	0.5991	1.2715	6.7	4.15
0.9559	0.6160	1.3041	6.7	5.21
0.9626	0.6096	1.3106	6.6	5.8
0.9434	0.6051	1.2911	6.9	5.91
0.8639	0.5857	1.2233	7.3	5.39
0.7996	0.5565	1.1438	7.5	5.46
0.6680	0.5223	0.9895	7.3	4.72
0.6572	0.5091	1.9903	7.1	3.14
0.6928	0.4919	0.9967	6.9	2.63
0.6438	0.4995	0.9708	7.1	2.32
0.6454	0.5069	0.9946	7.5	1.93
0.6873	0.5190	1.0441	7.7	0.62
0.7265	0.5460	1.0757	7.8	0.6
0.7912	0.5648	1.1461	7.8	-0.37
0.8114	0.5751	1.1749	7.7	-1.1
0.8281	0.5862	1.1926	7.7	-1.68
0.8393	0.5877	1.2109	7.8	-0.78

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54230&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54230&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54230&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'Gwilym Jenkins' @ 72.249.127.135






Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( US_DOLLAR , EURO )0.2316467694903740.00960308512272845
tau( US_DOLLAR , SINGAPORE_DOLLAR )0.4365867913500881.03430459930109e-06
tau( US_DOLLAR , Werkloosheidsgraad_in_% )-0.4586989619953716.13056772784723e-07
tau( US_DOLLAR , Inflatie )0.0713659239339030.424946734316361
tau( EURO , SINGAPORE_DOLLAR )0.4808425366694127.62419760658162e-08
tau( EURO , Werkloosheidsgraad_in_% )0.1677719654719640.0683704086657477
tau( EURO , Inflatie )0.09426229508196720.292344464675358
tau( SINGAPORE_DOLLAR , Werkloosheidsgraad_in_% )-0.0508320749440780.580499330469954
tau( SINGAPORE_DOLLAR , Inflatie )0.2971630275280550.000892874099977625
tau( Werkloosheidsgraad_in_% , Inflatie )-0.04905967221382350.594068135064721

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( US_DOLLAR , EURO ) & 0.231646769490374 & 0.00960308512272845 \tabularnewline
tau( US_DOLLAR , SINGAPORE_DOLLAR ) & 0.436586791350088 & 1.03430459930109e-06 \tabularnewline
tau( US_DOLLAR , Werkloosheidsgraad_in_% ) & -0.458698961995371 & 6.13056772784723e-07 \tabularnewline
tau( US_DOLLAR , Inflatie ) & 0.071365923933903 & 0.424946734316361 \tabularnewline
tau( EURO , SINGAPORE_DOLLAR ) & 0.480842536669412 & 7.62419760658162e-08 \tabularnewline
tau( EURO , Werkloosheidsgraad_in_% ) & 0.167771965471964 & 0.0683704086657477 \tabularnewline
tau( EURO , Inflatie ) & 0.0942622950819672 & 0.292344464675358 \tabularnewline
tau( SINGAPORE_DOLLAR , Werkloosheidsgraad_in_% ) & -0.050832074944078 & 0.580499330469954 \tabularnewline
tau( SINGAPORE_DOLLAR , Inflatie ) & 0.297163027528055 & 0.000892874099977625 \tabularnewline
tau( Werkloosheidsgraad_in_% , Inflatie ) & -0.0490596722138235 & 0.594068135064721 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54230&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( US_DOLLAR , EURO )[/C][C]0.231646769490374[/C][C]0.00960308512272845[/C][/ROW]
[ROW][C]tau( US_DOLLAR , SINGAPORE_DOLLAR )[/C][C]0.436586791350088[/C][C]1.03430459930109e-06[/C][/ROW]
[ROW][C]tau( US_DOLLAR , Werkloosheidsgraad_in_% )[/C][C]-0.458698961995371[/C][C]6.13056772784723e-07[/C][/ROW]
[ROW][C]tau( US_DOLLAR , Inflatie )[/C][C]0.071365923933903[/C][C]0.424946734316361[/C][/ROW]
[ROW][C]tau( EURO , SINGAPORE_DOLLAR )[/C][C]0.480842536669412[/C][C]7.62419760658162e-08[/C][/ROW]
[ROW][C]tau( EURO , Werkloosheidsgraad_in_% )[/C][C]0.167771965471964[/C][C]0.0683704086657477[/C][/ROW]
[ROW][C]tau( EURO , Inflatie )[/C][C]0.0942622950819672[/C][C]0.292344464675358[/C][/ROW]
[ROW][C]tau( SINGAPORE_DOLLAR , Werkloosheidsgraad_in_% )[/C][C]-0.050832074944078[/C][C]0.580499330469954[/C][/ROW]
[ROW][C]tau( SINGAPORE_DOLLAR , Inflatie )[/C][C]0.297163027528055[/C][C]0.000892874099977625[/C][/ROW]
[ROW][C]tau( Werkloosheidsgraad_in_% , Inflatie )[/C][C]-0.0490596722138235[/C][C]0.594068135064721[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54230&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54230&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( US_DOLLAR , EURO )0.2316467694903740.00960308512272845
tau( US_DOLLAR , SINGAPORE_DOLLAR )0.4365867913500881.03430459930109e-06
tau( US_DOLLAR , Werkloosheidsgraad_in_% )-0.4586989619953716.13056772784723e-07
tau( US_DOLLAR , Inflatie )0.0713659239339030.424946734316361
tau( EURO , SINGAPORE_DOLLAR )0.4808425366694127.62419760658162e-08
tau( EURO , Werkloosheidsgraad_in_% )0.1677719654719640.0683704086657477
tau( EURO , Inflatie )0.09426229508196720.292344464675358
tau( SINGAPORE_DOLLAR , Werkloosheidsgraad_in_% )-0.0508320749440780.580499330469954
tau( SINGAPORE_DOLLAR , Inflatie )0.2971630275280550.000892874099977625
tau( Werkloosheidsgraad_in_% , Inflatie )-0.04905967221382350.594068135064721


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')