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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Fri, 17 Dec 2010 11:58:58 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/17/t1292587085j8t3ahmu56x15gy.htm/, Retrieved Tue, 07 May 2024 02:18:30 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111403, Retrieved Tue, 07 May 2024 02:18:30 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

159

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Paired and Unpaired Two Samples Tests about the Mean] [Dagelijkse omzet ...] [2010-10-25 11:22:12] [b98453cac15ba1066b407e146608df68]
-   PD  [Paired and Unpaired Two Samples Tests about the Mean] [ws 5 - question 1] [2010-10-29 11:09:06] [ec7b4b7cc1a30b20be5ec01cdf2adbbd]
- RMPD    [Histogram] [paper - histogram] [2010-12-15 15:48:33] [ec7b4b7cc1a30b20be5ec01cdf2adbbd]
- RMPD      [Pearson Correlation] [paper - correlatie] [2010-12-17 11:31:48] [ec7b4b7cc1a30b20be5ec01cdf2adbbd]
- RMPD          [Kendall tau Correlation Matrix] [paper - pearson c...] [2010-12-17 11:58:58] [6ea41cf020a5319fc3c331a4158019e5] [Current]

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Dataseries X:

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Histogram

Boxplots

296,95	17,20
296,84	17,20
287,54	17,20
287,81	17,20
283,99	20,63
275,79	20,63
269,52	20,63
278,35	20,63
283,43	19,32
289,46	19,32
282,30	19,32
293,55	19,32
304,78	12,99
300,99	12,99
315,29	12,99
316,21	12,99
331,79	18,13
329,38	18,13
317,27	18,13
317,98	18,13
340,28	28,37
339,21	28,37
336,71	28,37
340,11	28,37
347,72	24,35
328,68	24,35
303,05	24,35
299,83	24,35
320,04	24,99
317,94	24,99
303,31	24,99
308,85	24,99
319,19	28,84
314,52	28,84
312,39	28,84
315,77	28,84
320,23	37,88
309,45	37,88
296,54	37,88
297,28	37,88
301,39	54,04
306,68	54,04
305,91	54,04
314,76	54,04
323,34	64,93
341,58	64,93
330,12	64,93
318,16	64,93
317,84	71,81
325,39	71,81
327,56	71,81
329,77	71,81
333,29	99,75
346,10	99,75
358,00	99,75
344,82	99,75
313,30	61,25
301,26	61,25
306,38	61,25
319,31	61,25

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111403&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]2 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=111403&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111403&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Correlations for all pairs of data series (method=pearson)
	GemPrijsTicket_$	GemiddeldeOlieprijs_$
GemPrijsTicket_$	1	0.515
GemiddeldeOlieprijs_$	0.515	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & GemPrijsTicket_$ & GemiddeldeOlieprijs_$ \tabularnewline
GemPrijsTicket_$ & 1 & 0.515 \tabularnewline
GemiddeldeOlieprijs_$ & 0.515 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111403&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]GemPrijsTicket_$[/C][C]GemiddeldeOlieprijs_$[/C][/ROW]
[ROW][C]GemPrijsTicket_$[/C][C]1[/C][C]0.515[/C][/ROW]
[ROW][C]GemiddeldeOlieprijs_$[/C][C]0.515[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111403&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111403&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=pearson)
	GemPrijsTicket_$	GemiddeldeOlieprijs_$
GemPrijsTicket_$	1	0.515
GemiddeldeOlieprijs_$	0.515	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
GemPrijsTicket_$;GemiddeldeOlieprijs_$	0.5148	0.4981	0.3491
p-value	(0)	(1e-04)	(1e-04)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
GemPrijsTicket_$;GemiddeldeOlieprijs_$ & 0.5148 & 0.4981 & 0.3491 \tabularnewline
p-value & (0) & (1e-04) & (1e-04) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111403&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]GemPrijsTicket_$;GemiddeldeOlieprijs_$[/C][C]0.5148[/C][C]0.4981[/C][C]0.3491[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111403&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111403&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
pair	Pearson r	Spearman rho	Kendall tau
GemPrijsTicket_$;GemiddeldeOlieprijs_$	0.5148	0.4981	0.3491
p-value	(0)	(1e-04)	(1e-04)

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = pearson ;

Parameters (R input):

par1 = pearson ;

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')

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Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code