Free Statistics

of Irreproducible Research!

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 computationMon, 13 Dec 2010 21:00:22 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/13/t1292273926kiuw9znbnop5yzl.htm/, Retrieved Mon, 06 May 2024 22:50:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109200, Retrieved Mon, 06 May 2024 22:50:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact188
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2010-12-05 17:44:33] [b98453cac15ba1066b407e146608df68]
F RMPD    [Kendall tau Correlation Matrix] [Kendall] [2010-12-13 21:00:22] [8bf9de033bd61652831a8b7489bc3566] [Current]
Feedback Forum
2010-12-18 12:36:58 [00c625c7d009d84797af914265b614f9] [reply
Dit is een non-parametrische techniek, hiervoor geldt de normaliteits assumptie niet. De correlatie is nog steeds negatief, maar er is wel degelijk een negatief verband tussen de gegevens. De p-waarde is zeer klein, dus de kans dat we ons vergissen bij het verwerpen van de nulhypothese (H0: er is geen verband) is zeer klein.

Post a new message
Dataseries X:
2649.2	31077	
2579.4	31293	
2504.6	30236	
2462.3	30160	
2467.4	32436	
2446.7	30695	
2656.3	27525	
2626.2	26434	
2482.6	25739	
2539.9	25204	
2502.7	24977	
2466.9	24320	
2513.2	22680	
2443.3	22052	
2293.4	21467	
2070.8	21383	
2029.6	21777	
2052 	21928	
1864.4	21814	
1670.1	22937	
1811 	 23595	
1905.4	20830	
1862.8	19650
2014.5	19195	
2197.8	19644	
2962.3	18483	
3047 	 18079	
3032.6	19178	
3504.4	18391	
3801.1	18441	
3857.6	18584	
3674.4	20108	
3721 	20148	
3844.5	19394	
4116.7	17745	
4105.2	17696	
4435.2	17032	
4296.5	16438	
4202.5	15683	
4562.8	15594	
4621.4	15713	
4697 	 15937	
4591.3	16171	
4357 	 15928	
4502.6	16348	
4443.9	15579	
4290.9	15305
4199.8	15648	
4138.5	14954	
3970.1	15137	
3862.3	15839	
3701.6	16050	
3570.12 	15168 	
3801.06 	17064 	
3895.51 	16005 	
3917.96 	14886 	
3813.06 	14931 	
3667.03 	14544 	
3494.17 	13812 	
3364	 13031	
3295.3	12574	
3277.0	11964	
3257.2	11451	
3161.7	11346	
3097.3	11353	
3061.3	10702	
3119.3	10646	
3106.22 	10556 	
3080.58 	10463 	
2981.85 	10407 	




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109200&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109200&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109200&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'George Udny Yule' @ 72.249.76.132







Correlations for all pairs of data series (method=kendall)
Bel20Goudprijs
Bel201-0.291
Goudprijs-0.2911

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Bel20 & Goudprijs \tabularnewline
Bel20 & 1 & -0.291 \tabularnewline
Goudprijs & -0.291 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109200&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Bel20[/C][C]Goudprijs[/C][/ROW]
[ROW][C]Bel20[/C][C]1[/C][C]-0.291[/C][/ROW]
[ROW][C]Goudprijs[/C][C]-0.291[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109200&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109200&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series (method=kendall)
Bel20Goudprijs
Bel201-0.291
Goudprijs-0.2911







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Bel20;Goudprijs-0.5399-0.564-0.2911
p-value(0)(0)(4e-04)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Bel20;Goudprijs & -0.5399 & -0.564 & -0.2911 \tabularnewline
p-value & (0) & (0) & (4e-04) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109200&T=2

[TABLE]
[ROW][C]Correlations for all pairs of data series with p-values[/C][/ROW]
[ROW][C]pair[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]Bel20;Goudprijs[/C][C]-0.5399[/C][C]-0.564[/C][C]-0.2911[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](4e-04)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109200&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109200&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Bel20;Goudprijs-0.5399-0.564-0.2911
p-value(0)(0)(4e-04)



Parameters (Session):
par1 = pearson ;
Parameters (R input):
par1 = kendall ;
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=par1)
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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
cor.test(y[1,],y[2,],method=par1)
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='')
a<-table.element(a,dum,header=TRUE)
rp <- cor.test(y[i,],y[j,],method='pearson')
a<-table.element(a,round(rp$estimate,4))
rs <- cor.test(y[i,],y[j,],method='spearman')
a<-table.element(a,round(rs$estimate,4))
rk <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,round(rk$estimate,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=T)
a<-table.element(a,paste('(',round(rp$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rs$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rk$p.value,4),')',sep=''))
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')