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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, 13 Nov 2009 13:31:02 -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/t1258144313r9991kvw6p6o7ss.htm/, Retrieved Sat, 04 May 2024 11:42:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=57107, Retrieved Sat, 04 May 2024 11:42:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128

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] [workshop 6,3] [2009-11-09 20:47:13] [35f0fff14d789f48983afb62e692bd0d]
-    D      [Kendall tau Correlation Matrix] [Workshop 6] [2009-11-13 20:31:02] [ee8fc1691ecec7724e0ca78f0c288737] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
130	87.1	122.6	 100.0 
136.7	110.5	115.4	 120.3 
138.1	110.8	109	 130.5 
139.5	104.2	129.1	 118.4 
140.4	88.9	102.8	 114.7 
144.6	89.8	96.2	 110.2 
151.4	90	127.7	 111.4 
147.9	93.9	128.9	 100.9 
141.5	91.3	126.5	 88.7 
143.8	87.8	119.8	 118.2 
143.6	99.7	113.2	 129.5 
150.5	73.5	114.1	 119.2 
150.1	79.2	134.1	 109.8 
154.9	96.9	130	 117.4 
162.1	95.2	121.8	 143.4 
176.7	95.6	132.1	 162.2 
186.6	89.7	105.3	 148.8 
194.8	92.8	103	 130.5 
196.3	88	117.1	 166.0 
228.8	101.1	126.3	 143.3 
267.2	92.7	138.1	 139.6 
237.2	95.8	119.5	 171.4 
254.7	103.8	138	 164.7 
258.2	81.8	135.5	 166.3 
257.9	87.1	178.6	 156.2 
269.6	105.9	162.2	 170.4 
266.9	108.1	176.9	 161.5 
269.6	102.6	204.9	 184.3 
253.9	93.7	132.2	 164.3 
258.6	103.5	142.5	 175.2 
274.2	100.6	164.3	 173.1 
301.5	113.3	174.9	 132.7 
304.5	102.4	175.4	 136.2 
285.1	102.1	143	 163.3 
287.7	106.9	158.7	 160.3 
265.5	87.3	155.4	 175.5 
264.1	93.1	176.6	 159.1 
276.1	109.1	163.3	 164.9 
258.9	120.3	178.9	 171.7 
239.1	104.9	182.7	 222.1 
250.1	92.6	158.9	 195.7 
276.8	109.8	115.5	 235.2 
297.6	111.4	169.4	 233.4 
295.4	117.9	168	 189.1 
283	121.6	159.8	 230.1 
275.8	117.8	129	 254.1 
279.7	124.2	157.9	 260.2 
254.6	106.8	169.5	 270.3 
234.6	102.7	169.1	 229.6 
176.9	116.8	183.6	 277.6 
148.1	113.6	168.9	 259.0 
122.7	96.1	186.2	 301.3 
124.9	85	227.1	 271.5 
121.6	83.2	126.4	 287.1 
128.4	84.9	169.3	 295.6 
144.5	83	175	 273.8 
151.8	79.6	133.9	 257.9 
167.1	83.2	110.1	 245.6 
173.8	83.8	104.3	 278.5 
203.7	82.8	108.7	 241.5 
199.8	71.4	112.6	 215.5

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=57107&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=57107&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57107&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( prijs , prod )0.356029545714475.09223721041341e-05
tau( prijs , omzet )0.2727521282512720.00190089611306998
tau( prijs , invoer )0.1126298523783490.199853147968291
tau( prod , omzet )0.2504100975699680.00436910154120196
tau( prod , invoer )0.09789445266188960.265293592799992
tau( omzet , invoer )0.2880568568906220.00103976632207359

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( prijs , prod ) & 0.35602954571447 & 5.09223721041341e-05 \tabularnewline
tau( prijs , omzet ) & 0.272752128251272 & 0.00190089611306998 \tabularnewline
tau( prijs , invoer ) & 0.112629852378349 & 0.199853147968291 \tabularnewline
tau( prod , omzet ) & 0.250410097569968 & 0.00436910154120196 \tabularnewline
tau( prod , invoer ) & 0.0978944526618896 & 0.265293592799992 \tabularnewline
tau( omzet , invoer ) & 0.288056856890622 & 0.00103976632207359 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=57107&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( prijs , prod )[/C][C]0.35602954571447[/C][C]5.09223721041341e-05[/C][/ROW]
[ROW][C]tau( prijs , omzet )[/C][C]0.272752128251272[/C][C]0.00190089611306998[/C][/ROW]
[ROW][C]tau( prijs , invoer )[/C][C]0.112629852378349[/C][C]0.199853147968291[/C][/ROW]
[ROW][C]tau( prod , omzet )[/C][C]0.250410097569968[/C][C]0.00436910154120196[/C][/ROW]
[ROW][C]tau( prod , invoer )[/C][C]0.0978944526618896[/C][C]0.265293592799992[/C][/ROW]
[ROW][C]tau( omzet , invoer )[/C][C]0.288056856890622[/C][C]0.00103976632207359[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=57107&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57107&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( prijs , prod )0.356029545714475.09223721041341e-05
tau( prijs , omzet )0.2727521282512720.00190089611306998
tau( prijs , invoer )0.1126298523783490.199853147968291
tau( prod , omzet )0.2504100975699680.00436910154120196
tau( prod , invoer )0.09789445266188960.265293592799992
tau( omzet , invoer )0.2880568568906220.00103976632207359


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')