FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationTue, 20 Dec 2016 14:33:54 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/20/t1482240855ywz1tsf0q1asmbi.htm/, Retrieved Sat, 27 Apr 2024 21:13:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301661, Retrieved Sat, 27 Apr 2024 21:13:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56

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] [kendall ith en tvdc] [2016-12-20 13:33:54] [6f830dc7e8de22be3233942ffbe3aaba] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
14	10
19	13
17	14
17	12
15	12
20	13
15	13
19	13
15	13
15	14
19	14
16	12
20	12
18	11
15	12
14	14
20	12
16	11
16	13
16	13
10	12
19	13
19	12
16	13
15	11
18	12
17	12
19	13
17	13
14	10
19	12
20	13
5	13
19	10
16	14
15	12
16	10
18	10
16	14
15	12
17	14
14	10
20	13
19	12
7	12
13	13
16	12
16	10
18	14
18	15
16	14
17	8
19	11
16	10
19	12
13	14
16	12
13	12
12	14
17	13
17	13
17	13
16	12
16	10
14	14
16	11
13	10
16	13
14	12
20	12
12	11
13	10
18	14
14	12
19	13
18	11
14	10
18	14
19	13
15	7
14	13
17	13
19	13
13	15
19	13
18	14
20	12
15	13
15	11
15	12
20	14
15	13
19	14
18	12
18	12
15	13
20	14
17	13
18	13
19	12
20	10
13	12
17	13
15	12
16	13
18	12
18	12
14	12
15	11
12	12
17	9
14	14
18	12
17	13
17	13
20	13
16	11
14	12
15	11
18	12
20	12
17	13
17	12
17	13
17	13
15	12
17	12
18	8
17	12
20	13
15	10
16	8
15	12
18	13
15	12
18	15
20	14
19	10
14	11
16	12
15	10
17	14
18	10
20	15
17	11
18	12
15	9
16	12
11	13
15	12
18	9
17	12
16	14
12	11
19	12
18	14
15	12
17	15
19	11
18	12
19	12
16	10
16	12
16	11
14	11

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301661&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=301661&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301661&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R ServerBig Analytics Cloud Computing Center






Correlations for all pairs of data series (method=kendall)
ITHSUMTVDCSUM-4
ITHSUM10.138
TVDCSUM-40.1381

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & ITHSUM & TVDCSUM-4 \tabularnewline
ITHSUM & 1 & 0.138 \tabularnewline
TVDCSUM-4 & 0.138 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301661&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]ITHSUM[/C][C]TVDCSUM-4[/C][/ROW]
[ROW][C]ITHSUM[/C][C]1[/C][C]0.138[/C][/ROW]
[ROW][C]TVDCSUM-4[/C][C]0.138[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301661&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301661&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=kendall)
ITHSUMTVDCSUM-4
ITHSUM10.138
TVDCSUM-40.1381






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
ITHSUM;TVDCSUM-40.11940.17830.1376
p-value(0.1266)(0.022)(0.0229)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
ITHSUM;TVDCSUM-4 & 0.1194 & 0.1783 & 0.1376 \tabularnewline
p-value & (0.1266) & (0.022) & (0.0229) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301661&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]ITHSUM;TVDCSUM-4[/C][C]0.1194[/C][C]0.1783[/C][C]0.1376[/C][/ROW]
[ROW][C]p-value[/C][C](0.1266)[/C][C](0.022)[/C][C](0.0229)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301661&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301661&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
ITHSUM;TVDCSUM-40.11940.17830.1376
p-value(0.1266)(0.022)(0.0229)






Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.01000
0.02000
0.03011
0.04011
0.05011
0.06011
0.07011
0.08011
0.09011
0.1011

\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 & 1 & 1 \tabularnewline
0.04 & 0 & 1 & 1 \tabularnewline
0.05 & 0 & 1 & 1 \tabularnewline
0.06 & 0 & 1 & 1 \tabularnewline
0.07 & 0 & 1 & 1 \tabularnewline
0.08 & 0 & 1 & 1 \tabularnewline
0.09 & 0 & 1 & 1 \tabularnewline
0.1 & 0 & 1 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301661&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]1[/C][C]1[/C][/ROW]
[ROW][C]0.04[/C][C]0[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.05[/C][C]0[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.06[/C][C]0[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.07[/C][C]0[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.08[/C][C]0[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.09[/C][C]0[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.1[/C][C]0[/C][C]1[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301661&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301661&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
0.03011
0.04011
0.05011
0.06011
0.07011
0.08011
0.09011
0.1011


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = kendall ;
Parameters (R input):
par1 = kendall ;
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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
x <- na.omit(x)
y <- t(na.omit(t(y)))
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
print(n)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$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')