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*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

Sun, 29 Nov 2015 22:20:36 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Nov/29/t1448835650y5j36rzb9771mpj.htm/, Retrieved Thu, 16 May 2024 01:57:52 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284547, Retrieved Thu, 16 May 2024 01:57:52 +0000

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Estimated Impact

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

-     [Multiple Regression] [] [2015-11-25 14:21:14] [32b17a345b130fdf5cc88718ed94a974]
- RMPD    [Kendall tau Correlation Matrix] [CM X5] [2015-11-29 22:20:36] [83aba8bbc702c7812e095afce40a5d1d] [Current]

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Dataseries X:

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Histogram

Boxplots

6,8	225	9,2
6,3	180	11,7
6,4	190	15,8
6,2	180	8,6
6,9	205	23,2
6,4	225	27,4
6,3	185	9,3
6,8	235	16
6,9	235	4,7
6,7	210	12,5
6,9	245	20,1
6,9	245	9,1
6,3	185	8,1
6,1	185	8,6
6,2	180	20,3
6,8	220	25
6,5	194	19,2
7,6	225	3,3
6,3	210	11,2
7,1	240	10,5
6,8	225	10,1
7,3	263	7,2
6,4	210	13,6
6,8	235	9
7,2	230	24,6
6,4	190	12,6
6,6	220	5,6
6,8	210	8,7
6,1	180	7,7
6,5	235	24,1
6,4	185	11,7
6	175	7,7
6	192	9,6
7,3	263	7,2
6,1	180	12,3
6,7	240	8,9
6,4	210	13,6
5,8	160	11,2
6,9	230	2,8
7	245	3,2
7,3	228	9,4
5,9	155	11,9
6,2	200	15,4
6,8	235	7,4
7	235	18,9
5,9	105	7,9
6,1	180	12,2
5,7	185	11
7,1	245	2,8
5,8	180	11,8
7,4	240	17,1
6,8	225	11,6
6,8	215	5,8
7	230	8,3

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message	The field 'Names of X columns' contains a hard return which cannot be interpreted. Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
R Framework error message & The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'. \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284547&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284547&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284547&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	1 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net
R Framework error message	The field 'Names of X columns' contains a hard return which cannot be interpreted. Please, resubmit your request without hard returns in the 'Names of X columns'.

Correlations for all pairs of data series (method=pearson)
	X1	X2	X5
X1	1	0.834	-0.069
X2	0.834	1	-0.01
X5	-0.069	-0.01	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & X1 & X2 & X5
 \tabularnewline
X1 & 1 & 0.834 & -0.069 \tabularnewline
X2 & 0.834 & 1 & -0.01 \tabularnewline
X5
 & -0.069 & -0.01 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284547&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]X1[/C][C]X2[/C][C]X5
[/C][/ROW]
[ROW][C]X1[/C][C]1[/C][C]0.834[/C][C]-0.069[/C][/ROW]
[ROW][C]X2[/C][C]0.834[/C][C]1[/C][C]-0.01[/C][/ROW]
[ROW][C]X5
[/C][C]-0.069[/C][C]-0.01[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284547&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284547&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)
	X1	X2	X5
X1	1	0.834	-0.069
X2	0.834	1	-0.01
X5	-0.069	-0.01	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
X1;X2	0.8343	0.8678	0.7122
p-value	(0)	(0)	(0)
X1;X5	-0.0689	-0.1595	-0.0897
p-value	(0.6205)	(0.2492)	(0.3525)
X2;X5	-0.0098	-0.1526	-0.093
p-value	(0.9437)	(0.2707)	(0.3339)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
X1;X2 & 0.8343 & 0.8678 & 0.7122 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X1;X5
 & -0.0689 & -0.1595 & -0.0897 \tabularnewline
p-value & (0.6205) & (0.2492) & (0.3525) \tabularnewline
X2;X5
 & -0.0098 & -0.1526 & -0.093 \tabularnewline
p-value & (0.9437) & (0.2707) & (0.3339) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284547&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]X1;X2[/C][C]0.8343[/C][C]0.8678[/C][C]0.7122[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X1;X5
[/C][C]-0.0689[/C][C]-0.1595[/C][C]-0.0897[/C][/ROW]
[ROW][C]p-value[/C][C](0.6205)[/C][C](0.2492)[/C][C](0.3525)[/C][/ROW]
[ROW][C]X2;X5
[/C][C]-0.0098[/C][C]-0.1526[/C][C]-0.093[/C][/ROW]
[ROW][C]p-value[/C][C](0.9437)[/C][C](0.2707)[/C][C](0.3339)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284547&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284547&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
X1;X2	0.8343	0.8678	0.7122
p-value	(0)	(0)	(0)
X1;X5	-0.0689	-0.1595	-0.0897
p-value	(0.6205)	(0.2492)	(0.3525)
X2;X5	-0.0098	-0.1526	-0.093
p-value	(0.9437)	(0.2707)	(0.3339)

Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I error	Pearson r	Spearman rho	Kendall tau
0.01	0.33	0.33	0.33
0.02	0.33	0.33	0.33
0.03	0.33	0.33	0.33
0.04	0.33	0.33	0.33
0.05	0.33	0.33	0.33
0.06	0.33	0.33	0.33
0.07	0.33	0.33	0.33
0.08	0.33	0.33	0.33
0.09	0.33	0.33	0.33
0.1	0.33	0.33	0.33

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Correlation Tests \tabularnewline
Number of significant by total number of Correlations \tabularnewline
Type I error & Pearson r & Spearman rho & Kendall tau \tabularnewline
0.01 & 0.33 & 0.33 & 0.33 \tabularnewline
0.02 & 0.33 & 0.33 & 0.33 \tabularnewline
0.03 & 0.33 & 0.33 & 0.33 \tabularnewline
0.04 & 0.33 & 0.33 & 0.33 \tabularnewline
0.05 & 0.33 & 0.33 & 0.33 \tabularnewline
0.06 & 0.33 & 0.33 & 0.33 \tabularnewline
0.07 & 0.33 & 0.33 & 0.33 \tabularnewline
0.08 & 0.33 & 0.33 & 0.33 \tabularnewline
0.09 & 0.33 & 0.33 & 0.33 \tabularnewline
0.1 & 0.33 & 0.33 & 0.33 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284547&T=3

[TABLE]
[ROW][C]Meta Analysis of Correlation Tests[/C][/ROW]
[ROW][C]Number of significant by total number of Correlations[/C][/ROW]
[ROW][C]Type I error[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]0.01[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[ROW][C]0.02[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[ROW][C]0.03[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[ROW][C]0.04[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[ROW][C]0.05[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[ROW][C]0.06[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[ROW][C]0.07[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[ROW][C]0.08[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[ROW][C]0.09[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[ROW][C]0.1[/C][C]0.33[/C][C]0.33[/C][C]0.33[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284547&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284547&T=3

As an alternative you can also use a QR Code:

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

Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I error	Pearson r	Spearman rho	Kendall tau
0.01	0.33	0.33	0.33
0.02	0.33	0.33	0.33
0.03	0.33	0.33	0.33
0.04	0.33	0.33	0.33
0.05	0.33	0.33	0.33
0.06	0.33	0.33	0.33
0.07	0.33	0.33	0.33
0.08	0.33	0.33	0.33
0.09	0.33	0.33	0.33
0.1	0.33	0.33	0.33

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):

par1 <- 'pearson'
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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
x <- na.omit(x)
y <- t(na.omit(t(y)))
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
ncorrs <- (n*n -n)/2
mycorrs <- array(0, dim=c(10,3))
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)
for (iii in 1:10) {
iiid100 <- iii / 100
if (rp$p.value < iiid100) mycorrs[iii, 1] = mycorrs[iii, 1] + 1
if (rs$p.value < iiid100) mycorrs[iii, 2] = mycorrs[iii, 2] + 1
if (rk$p.value < iiid100) mycorrs[iii, 3] = mycorrs[iii, 3] + 1
}
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Correlation Tests',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of significant by total number of Correlations',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Type I error',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)
for (iii in 1:10) {
iiid100 <- iii / 100
a<-table.row.start(a)
a<-table.element(a,round(iiid100,2),header=T)
a<-table.element(a,round(mycorrs[iii,1]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,2]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,3]/ncorrs,2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code