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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 14 Dec 2010 10:44:23 +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/14/t1292323352vymjwuuuuw0j70z.htm/, Retrieved Thu, 02 May 2024 20:47:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109377, Retrieved Thu, 02 May 2024 20:47:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact237

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] [] [2010-12-05 17:44:33] [b98453cac15ba1066b407e146608df68]
-   PD  [Kendall tau Correlation Matrix] [WS10 PCM DMA] [2010-12-09 16:41:09] [2099aacba481f75a7f949aa310cab952]
- R  D    [Kendall tau Correlation Matrix] [Workshop 10, Pear...] [2010-12-10 12:51:04] [3635fb7041b1998c5a1332cf9de22bce]
-    D        [Kendall tau Correlation Matrix] [WS10Pearson2] [2010-12-14 10:44:23] [9be3691a9b6ce074cb51fd18377fce28] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2,65	2,89	2,23
2,61	2,55	2,21
2,61	2,47	2,18
2,47	2,24	2,21
2,5	2,26	2,13
2,47	2,33	2,17
2,37	2,3	2,24
2,27	2,28	2,03
2,28	2,26	2,05
2,25	2,23	2,1
2,19	2,31	2,16
2,24	2,24	2,13
2,3	2,07	2,24
2,44	1,98	2,17
2,55	1,93	2,23
2,58	1,96	2,13
2,5	1,99	2,25
2,44	2,01	2,17
2,35	2,11	2,29
2,36	2,26	2,17
2,44	2,39	2,1
2,48	2,63	2,12
2,49	2,73	2,17
2,53	2,87	2,14
2,6	3,01	2,22
2,62	3,18	2,3
2,67	3,24	2,2
2,62	3,06	2,31
2,56	2,94	2,35
2,53	2,85	2,16
2,45	2,84	2,14
2,37	2,73	2,08
2,43	2,42	2,05
2,46	2,14	2,07
2,5	2,03	2,06
2,46	1,98	1,96
2,47	1,9	2,15
2,45	1,88	2,15
2,43	1,87	2,1
2,41	1,83	2,05
2,32	1,82	2,07
2,3	1,83	2,01
2,27	1,83	2,1
2,23	1,82	2,01
2,3	1,84	2,02
2,3	1,87	2,04
2,25	1,87	1,99
2,22	1,87	1,91
2,28	1,84	2,06
2,38	1,81	2,21
2,38	1,78	2,13
2,37	1,79	2,18
2,32	1,79	2,12
2,29	1,8	2,08
2,2	1,82	2,17
2,07	1,94	2,17

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'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=109377&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=109377&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109377&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'George Udny Yule' @ 72.249.76.132






Correlations for all pairs of data series (method=pearson)
SinaasappelenCitroenenBananen
Sinaasappelen10.6310.497
Citroenen0.63110.485
Bananen0.4970.4851

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Sinaasappelen & Citroenen & Bananen \tabularnewline
Sinaasappelen & 1 & 0.631 & 0.497 \tabularnewline
Citroenen & 0.631 & 1 & 0.485 \tabularnewline
Bananen & 0.497 & 0.485 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109377&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Sinaasappelen[/C][C]Citroenen[/C][C]Bananen[/C][/ROW]
[ROW][C]Sinaasappelen[/C][C]1[/C][C]0.631[/C][C]0.497[/C][/ROW]
[ROW][C]Citroenen[/C][C]0.631[/C][C]1[/C][C]0.485[/C][/ROW]
[ROW][C]Bananen[/C][C]0.497[/C][C]0.485[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109377&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109377&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:

Correlations for all pairs of data series (method=pearson)
SinaasappelenCitroenenBananen
Sinaasappelen10.6310.497
Citroenen0.63110.485
Bananen0.4970.4851






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Sinaasappelen;Citroenen0.6310.59240.4296
p-value(0)(0)(0)
Sinaasappelen;Bananen0.49660.51530.3719
p-value(1e-04)(0)(1e-04)
Citroenen;Bananen0.48460.4270.2937
p-value(2e-04)(0.001)(0.0017)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Sinaasappelen;Citroenen & 0.631 & 0.5924 & 0.4296 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Sinaasappelen;Bananen & 0.4966 & 0.5153 & 0.3719 \tabularnewline
p-value & (1e-04) & (0) & (1e-04) \tabularnewline
Citroenen;Bananen & 0.4846 & 0.427 & 0.2937 \tabularnewline
p-value & (2e-04) & (0.001) & (0.0017) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109377&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]Sinaasappelen;Citroenen[/C][C]0.631[/C][C]0.5924[/C][C]0.4296[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Sinaasappelen;Bananen[/C][C]0.4966[/C][C]0.5153[/C][C]0.3719[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Citroenen;Bananen[/C][C]0.4846[/C][C]0.427[/C][C]0.2937[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](0.001)[/C][C](0.0017)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109377&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109377&T=2

As an alternative you can also use a QR Code:  
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
Sinaasappelen;Citroenen0.6310.59240.4296
p-value(0)(0)(0)
Sinaasappelen;Bananen0.49660.51530.3719
p-value(1e-04)(0)(1e-04)
Citroenen;Bananen0.48460.4270.2937
p-value(2e-04)(0.001)(0.0017)


Figures (Output of Computation)

Input Parameters & R Code

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')