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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationMon, 09 Nov 2009 16:57:54 -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/10/t1257811112tpnvbe8fl3szlpe.htm/, Retrieved Mon, 06 May 2024 10:35:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55095, Retrieved Mon, 06 May 2024 10:35:05 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173
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]
- R  D    [Kendall tau Correlation Matrix] [WorkShop6 (SHW)] [2009-11-09 23:57:54] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-    D      [Kendall tau Correlation Matrix] [Workshop 6, Deel 7] [2009-11-12 14:55:13] [aba88da643e3763d32ff92bd8f92a385]
-   PD        [Kendall tau Correlation Matrix] [Kendall Tau corre...] [2009-11-13 01:31:54] [100eabcd48fc1a8fabbdc8e8267bd5e3]
-    D      [Kendall tau Correlation Matrix] [Workshop 6] [2009-11-12 14:55:14] [b6394cb5c2dcec6d17418d3cdf42d699]
-    D      [Kendall tau Correlation Matrix] [workshop 6 kendal...] [2009-11-12 14:57:31] [af8eb90b4bf1bcfcc4325c143dbee260]
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Dataseries X:
581000	282965	111632	37391
597000	276610	106707	38540
587000	277838	108827	38022
536000	277051	108413	34470
524000	277026	106249	33227
537000	274960	104861	33411
536000	270073	102382	33616
533000	267063	100320	32618
528000	264916	100228	31759
516000	287182	117089	29951
502000	291109	121523	28022
506000	292223	114948	27823
518000	288109	112831	27730
534000	281400	107605	28472
528000	282579	108928	28468
478000	280113	101993	24910
469000	280331	102850	24312
490000	276759	99925	26180
493000	275139	101536	26121
508000	274275	99450	26696
517000	271234	98305	27206
514000	289725	110159	27210
510000	290649	109483	26646
527000	292223	106810	27441
542000	278429	96279	28143
565000	269749	91982	30134
555000	265784	90276	30393
499000	268957	90999	26203
511000	264099	86622	26374
526000	255121	83117	27182
532000	253276	80367	28060
549000	245980	77550	29175
561000	235295	77443	30522
557000	258479	92844	30083
566000	260916	92175	30713
588000	254586	84822	32013
620000	250566	81632	35395
626000	243345	78872	35816
620000	247028	81485	36057
573000	248464	80651	33169
573000	244962	78192	33792
574000	237003	76844	34412
580000	237008	76335	33935
590000	225477	71415	34500
593000	226762	73899	34286
597000	247857	86822	36007
595000	248256	86371	35701
612000	246892	83469	36830
628000	245021	82662	37250
629000	246186	82880	39284
621000	255688	89406	38192
569000	264242	95378	33347
567000	268270	97657	33357
573000	272969	100247	33654
584000	273886	99180	34390
589000	267353	97493	34715
591000	271916	101628	35377
595000	292633	114585	35415
594000	295804	115669	34718
611000	293222	111311	36021




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=55095&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=55095&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55095&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( WLH_België , WLH_MBEL )-0.3449454526824310.000102362869002922
tau( WLH_België , WLH_MVL )-0.2876564570151070.00119295702448213
tau( WLH_België , WLH_MA )0.7870914867145650
tau( WLH_MBEL , WLH_MVL )0.826787261037260
tau( WLH_MBEL , WLH_MA )-0.2311387489844420.009090663679293
tau( WLH_MVL , WLH_MA )-0.1322033898305080.135585103009819

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( WLH_België , WLH_MBEL ) & -0.344945452682431 & 0.000102362869002922 \tabularnewline
tau( WLH_België , WLH_MVL ) & -0.287656457015107 & 0.00119295702448213 \tabularnewline
tau( WLH_België , WLH_MA ) & 0.787091486714565 & 0 \tabularnewline
tau( WLH_MBEL , WLH_MVL ) & 0.82678726103726 & 0 \tabularnewline
tau( WLH_MBEL , WLH_MA ) & -0.231138748984442 & 0.009090663679293 \tabularnewline
tau( WLH_MVL , WLH_MA ) & -0.132203389830508 & 0.135585103009819 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55095&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( WLH_België , WLH_MBEL )[/C][C]-0.344945452682431[/C][C]0.000102362869002922[/C][/ROW]
[ROW][C]tau( WLH_België , WLH_MVL )[/C][C]-0.287656457015107[/C][C]0.00119295702448213[/C][/ROW]
[ROW][C]tau( WLH_België , WLH_MA )[/C][C]0.787091486714565[/C][C]0[/C][/ROW]
[ROW][C]tau( WLH_MBEL , WLH_MVL )[/C][C]0.82678726103726[/C][C]0[/C][/ROW]
[ROW][C]tau( WLH_MBEL , WLH_MA )[/C][C]-0.231138748984442[/C][C]0.009090663679293[/C][/ROW]
[ROW][C]tau( WLH_MVL , WLH_MA )[/C][C]-0.132203389830508[/C][C]0.135585103009819[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55095&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55095&T=1

As an alternative you can also use a 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( WLH_België , WLH_MBEL )-0.3449454526824310.000102362869002922
tau( WLH_België , WLH_MVL )-0.2876564570151070.00119295702448213
tau( WLH_België , WLH_MA )0.7870914867145650
tau( WLH_MBEL , WLH_MVL )0.826787261037260
tau( WLH_MBEL , WLH_MA )-0.2311387489844420.009090663679293
tau( WLH_MVL , WLH_MA )-0.1322033898305080.135585103009819



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')