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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 computationSun, 14 Dec 2014 17:10:18 +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/2014/Dec/14/t1418577191pzey84ywv1nzaeb.htm/, Retrieved Thu, 16 May 2024 10:51:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=267759, Retrieved Thu, 16 May 2024 10:51:58 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67

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] [] [2014-12-14 17:10:18] [8145b3fe416df466b077d26de89041cd] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
21 4
26 9
22 4
22 5
18 4
23 4
12 9
20 8
22 11
21 4
19 4
22 6
15 4
20 8
19 4
18 4
15 11
20 4
21 4
21 6
15 6
16 4
23 8
21 5
18 4
25 9
9 4
30 7
20 10
23 4
16 4
16 7
19 12
25 4
25 7
18 5
23 8
21 5
10 4
14 9
22 7
26 4
23 4
23 4
24 4
24 4
18 7
23 4
15 7
19 4
16 4
25 4
23 4
17 8
19 4
21 4
18 4
27 4
21 7
13 12
8 4
29 4
28 4
23 5
21 15
19 5
19 10
20 9
18 8
19 4
17 5
19 4
25 9
19 4
22 10
23 4
26 7
14 4
28 6
16 7
24 5
20 4
12 4
24 4
22 4
12 4
22 4
20 6
10 10
23 7
17 4
22 4
24 7
18 4
21 8
20 11
20 6
22 14
19 5
20 4
26 8
23 9
24 4
21 4
21 5
19 4
8 5
17 4
20 4
11 7
8 10
15 4
18 5
18 4
19 4
19 4
23 6
22 4
21 8
25 5
30 4
17 17
27 4
23 4
23 8
18 4
18 7
23 4
19 4
15 5
20 7
16 4
24 4
25 7
25 11
19 7
19 4
16 4
19 4
19 4
23 4
21 4
22 6
19 8
20 23
20 4
3 8
23 6
14 4
23 4
20 7
15 4
13 4
16 4
7 4
24 10
17 6
24 5
24 5
19 4
25 4
20 5
28 5
23 5
27 5
18 4
28 6
21 4
19 4
23 4
27 9
22 18
28 6
25 5
21 4
22 11
28 4
20 10
29 6
25 8
25 8
20 6
20 8
16 4
20 4
20 9
23 9
18 5
25 4
18 4
19 15
25 10
25 9
25 7
24 9
19 6
26 4
10 7
17 4
13 7
17 4
30 15
25 4
4 9
16 4
21 4
23 28
22 4
17 4
20 4
20 5
22 4
16 4
23 12
16 5
0 4
18 6
25 6
23 5
12 4
18 4
24 4
11 10
18 7
14 4
23 4
24 7
29 4
18 4
15 12
29 5
16 8
19 6
22 17
16 4
23 5
23 4
19 5
4 5
20 6
24 4
20 4
4 4
24 6
22 8
16 10
3 4
15 5
24 4
17 4
20 4
27 16
23 4
26 7
23 4
17 4
20 14
22 5
19 5
24 5
19 5
23 7
15 19
27 16
26 4
22 4
22 7
18 9
15 5
22 14
27 4
10 16
20 10
17 5
23 6
19 4
13 4
27 4
23 5
16 4
25 4
2 5
26 4
20 4
23 5
22 8
24 15

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'Sir Ronald Aylmer Fisher' @ fisher.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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267759&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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267759&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267759&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Correlations for all pairs of data series (method=pearson)
NUMERACYTOTAMS.A
NUMERACYTOT10.04
AMS.A0.041

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & NUMERACYTOT & AMS.A \tabularnewline
NUMERACYTOT & 1 & 0.04 \tabularnewline
AMS.A & 0.04 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267759&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]NUMERACYTOT[/C][C]AMS.A[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]1[/C][C]0.04[/C][/ROW]
[ROW][C]AMS.A[/C][C]0.04[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267759&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267759&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)
NUMERACYTOTAMS.A
NUMERACYTOT10.04
AMS.A0.041






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
NUMERACYTOT;AMS.A0.03960.07310.0561
p-value(0.5038)(0.2171)(0.2097)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
NUMERACYTOT;AMS.A & 0.0396 & 0.0731 & 0.0561 \tabularnewline
p-value & (0.5038) & (0.2171) & (0.2097) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267759&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]NUMERACYTOT;AMS.A[/C][C]0.0396[/C][C]0.0731[/C][C]0.0561[/C][/ROW]
[ROW][C]p-value[/C][C](0.5038)[/C][C](0.2171)[/C][C](0.2097)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267759&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267759&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
NUMERACYTOT;AMS.A0.03960.07310.0561
p-value(0.5038)(0.2171)(0.2097)






Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.01000
0.02000
0.03000
0.04000
0.05000
0.06000
0.07000
0.08000
0.09000
0.1000

\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 & 0 & 0 \tabularnewline
0.02 & 0 & 0 & 0 \tabularnewline
0.03 & 0 & 0 & 0 \tabularnewline
0.04 & 0 & 0 & 0 \tabularnewline
0.05 & 0 & 0 & 0 \tabularnewline
0.06 & 0 & 0 & 0 \tabularnewline
0.07 & 0 & 0 & 0 \tabularnewline
0.08 & 0 & 0 & 0 \tabularnewline
0.09 & 0 & 0 & 0 \tabularnewline
0.1 & 0 & 0 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=267759&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[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]0.02[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]0.03[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]0.04[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]0.05[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]0.06[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]0.07[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]0.08[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]0.09[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]0.1[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=267759&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=267759&T=3

As an alternative you can also use a QR Code:  
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 errorPearson rSpearman rhoKendall tau
0.01000
0.02000
0.03000
0.04000
0.05000
0.06000
0.07000
0.08000
0.09000
0.1000


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')
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')