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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationSun, 16 Dec 2007 09:48:56 -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/16/t11978227530162qyiibh6f1pq.htm/, Retrieved Thu, 02 May 2024 05:48:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=14387, Retrieved Thu, 02 May 2024 05:48:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsgeen differentiatie
Estimated Impact165

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] [Kendall Tau ] [2007-12-16 16:48:56] [64ea87172e043784f189047ac4ee4e00] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
104,3	97,5	0,2	513
103,9	97,1	0,8	503
103,9	97,5	1,2	471
103,9	98,5	4,5	471
108,0	100,5	0,4	476
108,0	102,8	5,9	475
108,0	105,2	6,5	470
108,0	107,4	12,8	461
108,0	108,0	4,2	455
108,0	107,6	-3,3	456
108,0	107,0	-12,5	517
108,0	105,8	-16,3	525
108,0	104,3	-10,5	523
108,0	103,8	-11,8	519
108,0	104,4	-11,4	509
108,0	106,2	-17,7	512
108,0	108,5	-17,3	519
108,0	109,8	-18,6	517
108,0	110,3	-17,9	510
108,0	109,7	-21,4	509
108,0	108,7	-19,4	501
108,0	108,9	-15,5	507
108,0	109,7	-7,7	569
108,0	110,4	-0,7	580
108,0	111,4	-1,6	578
108,0	112,6	1,4	565
108,0	113,6	0,7	547
108,2	113,8	9,5	555
112,3	113,2	1,4	562
111,3	113,6	4,1	561
111,3	113,9	6,6	555
115,3	113,4	18,4	544
117,2	113,8	16,9	537
118,3	116,0	9,2	543
118,3	118,3	-4,3	594
118,3	120,5	-5,9	611
119,0	121,9	-7,7	613
120,6	121,2	-5,4	611
122,6	120,2	-2,3	594
122,6	120,6	-4,8	595
127,4	110,2	2,3	591
125,9	109,2	-5,2	589
121,5	108,7	-10	584
118,8	109,9	-17,1	573
121,6	112,2	-14,4	567
122,3	114,5	-3,9	569
122,7	114,7	3,7	621
120,8	113,2	6,5	629
120,1	112,1	0,9	628
120,1	112,6	-4,1	612
120,1	113,6	-7	595
120,1	114,0	-12,2	597
128,4	114,5	-2,5	593
129,8	115,0	4,4	590
129,8	114,9	13,7	580
128,6	114,8	12,3	574
128,6	114,3	13,4	573
133,7	113,7	2,2	573
130,0	114,5	1,7	620
125,9	116,0	-7,2	626
129,4	116,6	-4,8	620
129,4	116,2	-2,9	588
130,6	115,7	-2,4	566
130,6	115,6	-2,5	557
130,6	115,2	-5,3	561
130,8	115,0	-7,1	549
129,7	115,7	-8	532
125,8	115,9	-8,9	526
126,0	115,6	-7,7	511
125,6	115,9	-1,1	499
125,4	117,0	4	555
124,7	117,9	9,6	565
126,9	118,8	10,9	542
129,1	119,9	13	527

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 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=14387&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]5 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=14387&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14387&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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( energieprijzen , industriële_productie )0.5473564778048613.43036710148681e-11
tau( energieprijzen , nieuwe_personenwagens )0.1368782236558710.0968986781056198
tau( energieprijzen , werkloosheid )0.3969759720907631.54511457983730e-06
tau( industriële_productie , nieuwe_personenwagens )0.1156565777753660.146566867935769
tau( industriële_productie , werkloosheid )0.3815912121389541.74691812637739e-06
tau( nieuwe_personenwagens , werkloosheid )0.02901252118996040.715774150401436

\begin{tabular}{lllllllll}
\hline
Kendall tau rank correlations for all pairs of data series \tabularnewline
pair & tau & p-value \tabularnewline
tau( energieprijzen , industriële_productie ) & 0.547356477804861 & 3.43036710148681e-11 \tabularnewline
tau( energieprijzen , nieuwe_personenwagens ) & 0.136878223655871 & 0.0968986781056198 \tabularnewline
tau( energieprijzen , werkloosheid ) & 0.396975972090763 & 1.54511457983730e-06 \tabularnewline
tau( industriële_productie , nieuwe_personenwagens ) & 0.115656577775366 & 0.146566867935769 \tabularnewline
tau( industriële_productie , werkloosheid ) & 0.381591212138954 & 1.74691812637739e-06 \tabularnewline
tau( nieuwe_personenwagens , werkloosheid ) & 0.0290125211899604 & 0.715774150401436 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=14387&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( energieprijzen , industriële_productie )[/C][C]0.547356477804861[/C][C]3.43036710148681e-11[/C][/ROW]
[ROW][C]tau( energieprijzen , nieuwe_personenwagens )[/C][C]0.136878223655871[/C][C]0.0968986781056198[/C][/ROW]
[ROW][C]tau( energieprijzen , werkloosheid )[/C][C]0.396975972090763[/C][C]1.54511457983730e-06[/C][/ROW]
[ROW][C]tau( industriële_productie , nieuwe_personenwagens )[/C][C]0.115656577775366[/C][C]0.146566867935769[/C][/ROW]
[ROW][C]tau( industriële_productie , werkloosheid )[/C][C]0.381591212138954[/C][C]1.74691812637739e-06[/C][/ROW]
[ROW][C]tau( nieuwe_personenwagens , werkloosheid )[/C][C]0.0290125211899604[/C][C]0.715774150401436[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=14387&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=14387&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( energieprijzen , industriële_productie )0.5473564778048613.43036710148681e-11
tau( energieprijzen , nieuwe_personenwagens )0.1368782236558710.0968986781056198
tau( energieprijzen , werkloosheid )0.3969759720907631.54511457983730e-06
tau( industriële_productie , nieuwe_personenwagens )0.1156565777753660.146566867935769
tau( industriële_productie , werkloosheid )0.3815912121389541.74691812637739e-06
tau( nieuwe_personenwagens , werkloosheid )0.02901252118996040.715774150401436


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
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')