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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 computationThu, 12 Nov 2009 07:06:21 -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/12/t12580351882mcj7ss8g0eoa6t.htm/, Retrieved Fri, 03 May 2024 19:18:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=56005, Retrieved Fri, 03 May 2024 19:18:33 +0000
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Original text written by user:Hieruit valt duidelijk af te leiden dat alle vier de tijdreeksen degelijk met elkaar in verband zitten, dat zien we uit de correlatie grafiekjes en uit de cijfers die weergeven dat de kans op vergissing 0,00 is. De histogrammen vertonen wel geen duidelijke normaalverdeling.
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [Kendell tau corre...] [2009-11-12 14:06:21] [bef26de542bed2eafc60fe4615b06e47] [Current]
-   PD    [Kendall tau Correlation Matrix] [] [2010-12-28 20:25:55] [f47feae0308dca73181bb669fbad1c56]
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Dataseries X:
121.6	116.2	91.8	124.1
118.8	111.2	93.2	127.6
114.0	105.8	86.5	110.7
111.5	122.7	98.9	104.6
97.2	99.5	77.2	112.7
102.5	107.9	79.4	115.3
113.4	124.6	90.4	139.4
109.8	115.0	81.4	119.0
104.9	110.3	85.8	97.4
126.1	132.7	103.6	154.0
80.0	99.7	73.6	81.5
96.8	96.5	75.7	88.8
117.2	118.7	99.2	127.7
112.3	112.9	88.7	105.1
117.3	130.5	94.6	114.9
111.1	137.9	98.7	106.4
102.2	115.0	84.2	104.5
104.3	116.8	87.7	121.6
122.9	140.9	103.3	141.4
107.6	120.7	88.2	99.0
121.3	134.2	93.4	126.7
131.5	147.3	106.3	134.1
89.0	112.4	73.1	81.3
104.4	107.1	78.6	88.6
128.9	128.4	101.6	132.7
135.9	137.7	101.4	132.9
133.3	135.0	98.5	134.4
121.3	151.0	99.0	103.7
120.5	137.4	89.5	119.7
120.4	132.4	83.5	115.0
137.9	161.3	97.4	132.9
126.1	139.8	87.8	108.5
133.2	146.0	90.4	113.9
151.1	166.5	101.6	142.0
105.0	143.3	80.0	97.7
119.0	121.0	81.7	92.2
140.4	152.6	96.4	128.8
156.6	154.4	110.2	134.9
137.1	154.6	101.1	128.2
122.7	158.0	89.3	114.8
125.8	142.6	90.0	117.9
139.3	153.4	95.4	119.1
134.9	163.4	100.3	120.7
149.2	167.3	99.5	129.1
132.3	154.8	93.9	117.6
149.0	165.7	100.6	129.2
117.2	144.7	84.7	100.0
119.6	120.9	81.6	87.0
152.0	152.8	109.0	128.0
149.4	160.2	99.0	127.7
127.3	128.3	81.1	93.4
114.1	150.5	81.8	84.1
102.1	117.0	66.5	71.7
107.7	116.0	66.4	83.2
104.4	133.3	86.3	89.1
102.1	116.4	73.6	79.6
96.0	104.0	71.5	62.8
109.3	126.6	87.2	95.1
90.0	92.9	65.3	63.6
83.9	83.6	69.7	61.4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56005&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56005&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56005&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( Promet , Maapwe )0.654216604687661.65867319878998e-13
tau( Promet , Elelap )0.6247522198999591.97641902843770e-12
tau( Promet , Transp )0.5632608880352042.19637863452249e-10
tau( Maapwe , Elelap )0.5131543573515227.2353396607383e-09
tau( Maapwe , Transp )0.4020356394777665.76080017888891e-06
tau( Elelap , Transp )0.6836447048375021.31006316905768e-14

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( Promet , Maapwe ) & 0.65421660468766 & 1.65867319878998e-13 \tabularnewline
tau( Promet , Elelap ) & 0.624752219899959 & 1.97641902843770e-12 \tabularnewline
tau( Promet , Transp ) & 0.563260888035204 & 2.19637863452249e-10 \tabularnewline
tau( Maapwe , Elelap ) & 0.513154357351522 & 7.2353396607383e-09 \tabularnewline
tau( Maapwe , Transp ) & 0.402035639477766 & 5.76080017888891e-06 \tabularnewline
tau( Elelap , Transp ) & 0.683644704837502 & 1.31006316905768e-14 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56005&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( Promet , Maapwe )[/C][C]0.65421660468766[/C][C]1.65867319878998e-13[/C][/ROW]
[ROW][C]tau( Promet , Elelap )[/C][C]0.624752219899959[/C][C]1.97641902843770e-12[/C][/ROW]
[ROW][C]tau( Promet , Transp )[/C][C]0.563260888035204[/C][C]2.19637863452249e-10[/C][/ROW]
[ROW][C]tau( Maapwe , Elelap )[/C][C]0.513154357351522[/C][C]7.2353396607383e-09[/C][/ROW]
[ROW][C]tau( Maapwe , Transp )[/C][C]0.402035639477766[/C][C]5.76080017888891e-06[/C][/ROW]
[ROW][C]tau( Elelap , Transp )[/C][C]0.683644704837502[/C][C]1.31006316905768e-14[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56005&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56005&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( Promet , Maapwe )0.654216604687661.65867319878998e-13
tau( Promet , Elelap )0.6247522198999591.97641902843770e-12
tau( Promet , Transp )0.5632608880352042.19637863452249e-10
tau( Maapwe , Elelap )0.5131543573515227.2353396607383e-09
tau( Maapwe , Transp )0.4020356394777665.76080017888891e-06
tau( Elelap , Transp )0.6836447048375021.31006316905768e-14



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')