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Author*Unverified author*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationThu, 13 Dec 2007 07:32:35 -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/2007/Dec/13/t1197555487bse1nxwvs5kgxxe.htm/, Retrieved Sun, 05 May 2024 09:42:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3570, Retrieved Sun, 05 May 2024 09:42:21 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsalle reeksen
Estimated Impact182
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [kendall tau corel...] [2007-12-13 14:32:35] [a2659e9a411aa0bcc5ca303430cc5df1] [Current]
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Dataseries X:
100,6	115,9	59,7	125
96,1	112,9	58,2	121,7
110	126,3	75,3	134,3
108,2	116,8	69	124,3
106,9	112	66,1	119,1
117,2	129,7	77,5	137,8
105,2	113,6	69,3	120,5
106,3	115,7	70,2	122,7
95,9	119,5	70,2	127,2
107,5	125,8	78,2	133,2
113	129,6	85,4	136,3
111,4	128	82,4	134,9
95,5	112,8	61,2	120,9
90,3	101,6	52,2	109,4
110,8	123,9	85,3	129,6
107,1	118,8	79,9	124,7
101,4	109,1	72,2	114,6
112,9	130,6	85,7	137,4
98,5	112,4	75,5	117,9
100,1	111	69,2	117,4
93,4	116,2	77,6	122
104,4	119,8	85,3	124,8
101,8	117,2	77	123,3
107,9	127,3	89,9	132,8
91,3	107,7	60	115,1
86,6	97,5	54,3	104,2
111,4	120,1	84	125,5
98,4	110,6	69,9	116,8
102,2	111,3	75,1	116,8
103	119,8	81,7	125,5
95,8	105,5	69,9	110,9
96	108,7	68,3	114,9
95,7	128,7	77,3	136,4
106,4	119,5	77,4	125,8
112	121,1	85,3	126,5
116,2	128,4	91	134
93,9	108,8	60,6	116,1
100,5	107,5	57,6	115
112,5	125,6	93,8	130,3
101,2	102,9	78,7	106,5
107,8	107,5	80,3	111,6
114,3	120,4	89,8	125
99,6	104,3	77,5	108,3
98,6	100,6	71,7	105
93,6	121,9	83,2	127,4
99,6	112,7	86,2	116,6
113,1	124,9	100,7	128,6
110,7	123,9	100,8	127,5
88,1	102,2	57,1	108,4
93,1	104,9	62,5	110,8
107,4	109,8	79,7	114,2
99,5	98,9	80,3	101,8
105,6	107,3	92,4	109,8
108,3	112,6	91,8	115,9
99,2	104	85,8	106,9
99,3	110,6	84,2	114,6
107,1	100,8	93,1	105,4
106,9	103,8	101,2	108,1
115,4	117	100,6	118,4
99	108,4	106,7	112,7
100,1	95,5	64	98,4
96,2	96,9	67,5	99,6
96,9	103,9	101	103,9
96,2	101,1	95,5	101,5
91	100,6	97	100,8
99	104,3	103,8	104,5
99	98	95,2	98,2
107,2	99,5	86,7	99,9
110,8	97,4	93,5	97,5
111,1	105,6	102,5	105,7
104,6	117,5	112,3	117,7
94,3	107,4	105,5	107,4
90,7	97,8	75,4	98,4
88,8	91,5	70,4	92
90,9	107,7	108	107,7
90,5	100,1	100	100,2
95,5	96,6	93,3	96,7
103,1	106,8	111,1	106,8
100,6	98	101,1	98
103,1	98,6	98,1	98,6




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3570&T=0

[TABLE]
[ROW][C]Summary of compuational 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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3570&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3570&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Kendall tau rank correlations for all pairs of data series
pairtaup-value
tau( intermediare , consumptiegoed )0.408383696212649.09478434785171e-08
tau( intermediare , duurzaam )0.2387302669978780.00177877145034744
tau( intermediare , niet-duurzaam )0.3687721156036981.37568907643271e-06
tau( consumptiegoed , duurzaam )0.0368020323089740.629798774036173
tau( consumptiegoed , niet-duurzaam )0.896923745300860
tau( duurzaam , niet-duurzaam )-0.06594800585119270.387442778651968

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( intermediare , consumptiegoed ) & 0.40838369621264 & 9.09478434785171e-08 \tabularnewline
tau( intermediare , duurzaam ) & 0.238730266997878 & 0.00177877145034744 \tabularnewline
tau( intermediare , niet-duurzaam ) & 0.368772115603698 & 1.37568907643271e-06 \tabularnewline
tau( consumptiegoed , duurzaam ) & 0.036802032308974 & 0.629798774036173 \tabularnewline
tau( consumptiegoed , niet-duurzaam ) & 0.89692374530086 & 0 \tabularnewline
tau( duurzaam , niet-duurzaam ) & -0.0659480058511927 & 0.387442778651968 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3570&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( intermediare , consumptiegoed )[/C][C]0.40838369621264[/C][C]9.09478434785171e-08[/C][/ROW]
[ROW][C]tau( intermediare , duurzaam )[/C][C]0.238730266997878[/C][C]0.00177877145034744[/C][/ROW]
[ROW][C]tau( intermediare , niet-duurzaam )[/C][C]0.368772115603698[/C][C]1.37568907643271e-06[/C][/ROW]
[ROW][C]tau( consumptiegoed , duurzaam )[/C][C]0.036802032308974[/C][C]0.629798774036173[/C][/ROW]
[ROW][C]tau( consumptiegoed , niet-duurzaam )[/C][C]0.89692374530086[/C][C]0[/C][/ROW]
[ROW][C]tau( duurzaam , niet-duurzaam )[/C][C]-0.0659480058511927[/C][C]0.387442778651968[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3570&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3570&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( intermediare , consumptiegoed )0.408383696212649.09478434785171e-08
tau( intermediare , duurzaam )0.2387302669978780.00177877145034744
tau( intermediare , niet-duurzaam )0.3687721156036981.37568907643271e-06
tau( consumptiegoed , duurzaam )0.0368020323089740.629798774036173
tau( consumptiegoed , niet-duurzaam )0.896923745300860
tau( duurzaam , niet-duurzaam )-0.06594800585119270.387442778651968



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')