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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 computationMon, 19 Nov 2012 06:15:23 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/19/t1353323741totdpg5zeur2tpy.htm/, Retrieved Fri, 01 Nov 2024 00:02:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=190444, Retrieved Fri, 01 Nov 2024 00:02:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact172

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- RMPD    [Kendall tau Correlation Matrix] [WS7] [2012-11-19 11:15:23] [e2ccb4f6662abf6b355cbcf28b97e404] [Current]
- RM        [Kendall tau Correlation Matrix] [] [2013-11-21 01:50:31] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7	7	7	5
5	5	5	5
6	5	4	4
4	5	5	5
5	5	5	5
6	6	6	7
7	4	7	7
6	5	5	6
6	7	7	6
6	5	5	6
5	2	4	6
5	5	6	6
4	5	4	6
6	6	6	6
6	6	7	7
5	5	6	5
3	3	4	3
7	6	6	7
3	5	6	6
5	5	6	6
3	3	4	4
5	5	5	6
2	1	2	2
6	5	6	6
3	4	5	5
6	6	6	7
6	6	6	7
5	4	5	5
5	4	5	6
7	5	5	6
6	4	6	6
5	5	6	6
5	6	5	5
4	3	4	4
4	5	6	5
6	5	5	6
5	3	5	5
5	5	5	5
7	7	7	7
5	6	5	6
5	4	5	4
6	5	7	5
5	5	5	5
6	6	7	6
7	7	6	6
5	3	3	4
5	4	4	4
5	6	6	6
6	5	5	5
2	2	4	5
4	4	4	6
4	4	6	5
6	5	5	6
3	4	4	5
6	6	6	6
6	2	5	5
5	4	5	6
6	6	6	6
1	4	6	3
5	5	6	6
7	6	5	6
4	4	5	5
5	6	5	5
6	6	5	6
4	5	4	4
6	6	5	5
6	6	6	6
5	4	6	6
5	6	5	6
3	3	5	5
5	5	5	6
6	5	6	6
5	5	6	6
6	6	6	6
6	6	6	6
4	4	4	4
4	4	4	4
6	5	5	5
7	6	6	7
4	3	3	5
5	6	7	7
6	2	5	5
6	5	6	6
5	3	6	6
3	4	5	5
7	6	6	6
6	5	6	7
4	4	4	5
4	5	6	4
5	5	5	5
3	4	4	4
7	7	7	6
6	4	6	6
6	6	6	5
4	4	4	4
5	4	5	5
6	6	6	7
5	3	5	6
6	4	4	5
6	7	7	6
4	5	6	6
5	5	5	5
6	6	6	6
5	5	6	6
5	5	5	5
4	4	5	5
4	5	5	4
6	6	5	7
5	5	7	7
6	5	6	5
5	4	7	7
6	4	6	6
5	5	5	5
4	5	4	5
6	6	6	7
4	5	4	5
5	3	3	5
5	5	5	5
6	3	5	5
3	4	5	3
5	4	5	5
4	5	5	5
5	2	5	4
5	5	3	4
7	7	7	7
5	6	6	6
7	6	6	6
5	5	4	6
4	4	4	5
6	6	6	5
4	3	4	5
4	7	6	6
4	3	2	2
4	4	5	5
6	6	5	7
6	5	6	6
5	6	5	5
3	4	4	5
6	6	6	6
5	6	6	6
4	4	5	5
5	5	5	5
2	3	2	2
5	6	6	7
7	5	6	7
4	6	5	5
4	5	6	6
7	6	7	5
6	5	5	6
5	6	5	5
5	5	5	6
5	5	6	6
7	6	7	7
6	5	7	6
6	6	6	6
5	5	5	6
2	4	6	6
4	4	4	4
6	4	6	6
5	5	6	4
5	4	4	5
5	5	5	5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190444&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190444&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190444&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 time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Correlations for all pairs of data series (method=pearson)
Q2Q9Q16Q23
Q210.5430.5320.6
Q90.54310.6010.531
Q160.5320.60110.664
Q230.60.5310.6641

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Q2 & Q9 & Q16 & Q23 \tabularnewline
Q2 & 1 & 0.543 & 0.532 & 0.6 \tabularnewline
Q9 & 0.543 & 1 & 0.601 & 0.531 \tabularnewline
Q16 & 0.532 & 0.601 & 1 & 0.664 \tabularnewline
Q23 & 0.6 & 0.531 & 0.664 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190444&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Q2[/C][C]Q9[/C][C]Q16[/C][C]Q23[/C][/ROW]
[ROW][C]Q2[/C][C]1[/C][C]0.543[/C][C]0.532[/C][C]0.6[/C][/ROW]
[ROW][C]Q9[/C][C]0.543[/C][C]1[/C][C]0.601[/C][C]0.531[/C][/ROW]
[ROW][C]Q16[/C][C]0.532[/C][C]0.601[/C][C]1[/C][C]0.664[/C][/ROW]
[ROW][C]Q23[/C][C]0.6[/C][C]0.531[/C][C]0.664[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190444&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190444&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)
Q2Q9Q16Q23
Q210.5430.5320.6
Q90.54310.6010.531
Q160.5320.60110.664
Q230.60.5310.6641






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Q2;Q90.54290.55620.4828
p-value(0)(0)(0)
Q2;Q160.53240.54690.4771
p-value(0)(0)(0)
Q2;Q230.59960.56990.497
p-value(0)(0)(0)
Q9;Q160.6010.57120.4994
p-value(0)(0)(0)
Q9;Q230.53060.51770.4453
p-value(0)(0)(0)
Q16;Q230.66430.63170.5693
p-value(0)(0)(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Q2;Q9 & 0.5429 & 0.5562 & 0.4828 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Q2;Q16 & 0.5324 & 0.5469 & 0.4771 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Q2;Q23 & 0.5996 & 0.5699 & 0.497 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Q9;Q16 & 0.601 & 0.5712 & 0.4994 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Q9;Q23 & 0.5306 & 0.5177 & 0.4453 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Q16;Q23 & 0.6643 & 0.6317 & 0.5693 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=190444&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]Q2;Q9[/C][C]0.5429[/C][C]0.5562[/C][C]0.4828[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Q2;Q16[/C][C]0.5324[/C][C]0.5469[/C][C]0.4771[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Q2;Q23[/C][C]0.5996[/C][C]0.5699[/C][C]0.497[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Q9;Q16[/C][C]0.601[/C][C]0.5712[/C][C]0.4994[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Q9;Q23[/C][C]0.5306[/C][C]0.5177[/C][C]0.4453[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Q16;Q23[/C][C]0.6643[/C][C]0.6317[/C][C]0.5693[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=190444&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=190444&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
Q2;Q90.54290.55620.4828
p-value(0)(0)(0)
Q2;Q160.53240.54690.4771
p-value(0)(0)(0)
Q2;Q230.59960.56990.497
p-value(0)(0)(0)
Q9;Q160.6010.57120.4994
p-value(0)(0)(0)
Q9;Q230.53060.51770.4453
p-value(0)(0)(0)
Q16;Q230.66430.63170.5693
p-value(0)(0)(0)


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')