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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 computationFri, 13 Nov 2009 11:16:52 -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/13/t12581363791yziogfxm7epxb8.htm/, Retrieved Sun, 05 May 2024 15:05:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=56963, Retrieved Sun, 05 May 2024 15:05:52 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [] [2009-11-13 18:16:52] [0ba0bb061c5f6e19f35882c90a639aa5] [Current]
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Dataseries X:
232	153	252	100
309	142	331	100
308	138	330	100
309	142	332	100
298	129	322	101.1
293	138	315	101.35
290	142	313	101.45
292	122	314	101.49
283	128	304	101.68
269	135	289	101.92
265	139	284	102.04
253	166	271	102.55
236	116	254	104.02
232	153	246	105.41
224	139	237	105.48
222	150	235	105.54
215	161	230	105.16
213	112	228	105.16
211	113	227	105.16
212	133	231	105.16
215	130	231	105.16
214	131	228	105.17
215	142	230	105.17
213	161	228	105.54
212	148	227	106.9
210	167	225	107.27
197	142	210	107.31
190	132	203	107.39
183	203	196	107.41
176	158	189	107.46
169	85	182	113.14
163	149	177	117
160	155	172	119.28
150	162	162	119.39
147	160	159	119.5
150	187	161	119.67
139	185	150	119.67
137	159	148	119.73
136	126	147	119.77
130	116	144	119.77
129	214	143	119.78
134	135	148	119.78
137	170	152	119.78
131	144	145	121.28
133	119	149	122.44
133	134	148	122.72
129	154	144	122.75
129	125	143	122.8
123	177	138	122.81
122	133	136	122.83
123	151	137	122.83
116	176	133	122.83
121	154	136	122.84
121	167	137	122.85
123	204	140	123.61
125	102	141	124.74
122	121	138	125.1
122	167	137	125.29
123	121	136	125.45
121	249	134	125.51
123	185	136	125.55




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=56963&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=56963&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56963&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'Gwilym Jenkins' @ 72.249.127.135







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( vrouw , douane )-0.1873616781407580.0351928669081643
tau( vrouw , VlGw )0.9673153946125820
tau( vrouw , CPI )-0.8915398371371221.31364072914925e-23
tau( douane , VlGw )-0.1919248081175640.0306424293950644
tau( douane , CPI )0.1993908192964070.02488734846233
tau( VlGw , CPI )-0.8945483240786177.62615240061271e-24

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( vrouw , douane ) & -0.187361678140758 & 0.0351928669081643 \tabularnewline
tau( vrouw , VlGw ) & 0.967315394612582 & 0 \tabularnewline
tau( vrouw , CPI ) & -0.891539837137122 & 1.31364072914925e-23 \tabularnewline
tau( douane , VlGw ) & -0.191924808117564 & 0.0306424293950644 \tabularnewline
tau( douane , CPI ) & 0.199390819296407 & 0.02488734846233 \tabularnewline
tau( VlGw , CPI ) & -0.894548324078617 & 7.62615240061271e-24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56963&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( vrouw , douane )[/C][C]-0.187361678140758[/C][C]0.0351928669081643[/C][/ROW]
[ROW][C]tau( vrouw , VlGw )[/C][C]0.967315394612582[/C][C]0[/C][/ROW]
[ROW][C]tau( vrouw , CPI )[/C][C]-0.891539837137122[/C][C]1.31364072914925e-23[/C][/ROW]
[ROW][C]tau( douane , VlGw )[/C][C]-0.191924808117564[/C][C]0.0306424293950644[/C][/ROW]
[ROW][C]tau( douane , CPI )[/C][C]0.199390819296407[/C][C]0.02488734846233[/C][/ROW]
[ROW][C]tau( VlGw , CPI )[/C][C]-0.894548324078617[/C][C]7.62615240061271e-24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56963&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56963&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( vrouw , douane )-0.1873616781407580.0351928669081643
tau( vrouw , VlGw )0.9673153946125820
tau( vrouw , CPI )-0.8915398371371221.31364072914925e-23
tau( douane , VlGw )-0.1919248081175640.0306424293950644
tau( douane , CPI )0.1993908192964070.02488734846233
tau( VlGw , CPI )-0.8945483240786177.62615240061271e-24



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')