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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, 11 Dec 2016 17:51:10 +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/11/t1481475290nq07s3lus845gyz.htm/, Retrieved Thu, 02 May 2024 12:59:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298832, Retrieved Thu, 02 May 2024 12:59:39 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact61

Tree of Dependent Computations

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

Dataseries X:
Download CSV
Histogram
Boxplots 
13	4	2	3
16	5	3	4
17	4	4	4
15	3	4	3
16	4	4	4
16	3	4	4
17	3	4	3
16	3	4	4
17	4	5	4
17	4	5	4
17	4	4	4
15	4	4	3
16	4	4	3
14	3	3	4
16	4	4	4
17	3	4	4
16	3	4	4
NA	5	5	5
15	5	5	3
17	4	4	4
16	3	4	3
15	4	4	4
16	4	4	4
15	4	4	4
17	4	4	4
15	3	4	4
16	3	4	3
15	4	4	4
16	2	4	4
16	5	4	4
13	4	3	4
15	4	5	4
17	5	4	4
15	4	3	4
13	2	3	4
17	4	5	4
15	3	4	4
14	4	3	3
14	4	3	4
18	4	4	4
15	5	4	4
17	4	5	4
13	3	3	4
16	5	5	3
15	5	4	3
15	4	4	3
16	4	4	4
15	3	5	3
13	4	4	4
NA	2	3	2
17	4	5	4
17	5	5	4
17	5	5	4
11	4	3	4
14	4	3	3
13	4	4	4
15	3	4	3
17	3	4	4
16	4	4	3
15	4	4	4
17	5	5	4
16	2	4	4
16	4	4	4
16	3	4	4
15	4	4	4
12	4	2	4
17	4	4	3
14	4	4	3
14	5	4	3
16	3	4	3
15	3	4	3
15	4	5	5
13	4	4	4
13	4	4	4
17	4	4	5
15	3	4	4
16	4	4	4
14	3	4	3
15	3	3	4
17	4	3	4
16	4	4	4
12	3	3	4
16	4	4	4
17	4	4	4
17	4	4	4
20	5	4	4
17	5	4	5
18	4	4	4
15	3	4	4
17	3	4	4
14	4	2	3
15	4	4	4
17	4	4	4
16	4	4	4
17	4	5	4
15	3	4	3
16	4	4	4
18	5	4	4
18	5	4	5
16	4	5	4
NA	3	4	4
17	5	3	4
15	4	4	4
13	5	4	4
15	3	4	3
17	5	4	5
16	4	4	3
16	4	4	3
15	4	4	4
16	4	4	4
16	3	4	4
13	4	4	4
15	4	4	3
12	3	3	3
19	4	4	3
16	3	4	4
16	4	4	4
17	5	4	5
16	5	4	4
14	4	4	4
15	4	4	3
14	3	4	3
16	4	4	4
15	4	4	4
17	4	5	4
15	3	4	4
16	4	4	3
16	4	4	4
15	3	4	3
15	4	4	3
11	3	2	2
16	4	4	3
18	5	4	3
13	2	4	3
11	3	3	4
16	4	4	3
18	5	5	4
NA	NA	NA	NA
15	4	5	4
19	5	5	5
17	4	5	4
13	4	4	3
14	3	4	4
16	4	4	4
13	4	4	4
17	4	4	4
14	4	4	4
19	5	4	3
14	4	3	4
16	4	4	4
12	3	3	3
16	4	5	4
16	4	4	3
15	4	4	4
12	3	4	3
15	4	4	4
17	5	4	4
13	4	4	4
15	2	3	4
18	4	4	4
15	4	3	3
18	4	4	4
15	4	5	5
15	5	4	4
16	5	4	3
13	3	3	4
16	4	4	4
13	4	4	4
16	2	3	5

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298832&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=298832&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298832&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 time1 seconds
R ServerBig Analytics Cloud Computing Center






Correlations for all pairs of data series (method=pearson)
TVSUMSK1SK2SK4
TVSUM10.3490.4860.242
SK10.34910.2640.162
SK20.4860.26410.186
SK40.2420.1620.1861

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & TVSUM & SK1 & SK2 & SK4 \tabularnewline
TVSUM & 1 & 0.349 & 0.486 & 0.242 \tabularnewline
SK1 & 0.349 & 1 & 0.264 & 0.162 \tabularnewline
SK2 & 0.486 & 0.264 & 1 & 0.186 \tabularnewline
SK4 & 0.242 & 0.162 & 0.186 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298832&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]TVSUM[/C][C]SK1[/C][C]SK2[/C][C]SK4[/C][/ROW]
[ROW][C]TVSUM[/C][C]1[/C][C]0.349[/C][C]0.486[/C][C]0.242[/C][/ROW]
[ROW][C]SK1[/C][C]0.349[/C][C]1[/C][C]0.264[/C][C]0.162[/C][/ROW]
[ROW][C]SK2[/C][C]0.486[/C][C]0.264[/C][C]1[/C][C]0.186[/C][/ROW]
[ROW][C]SK4[/C][C]0.242[/C][C]0.162[/C][C]0.186[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298832&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298832&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)
TVSUMSK1SK2SK4
TVSUM10.3490.4860.242
SK10.34910.2640.162
SK20.4860.26410.186
SK40.2420.1620.1861






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
TVSUM;SK10.34940.35070.2969
p-value(0)(0)(0)
TVSUM;SK20.48620.44090.3833
p-value(0)(0)(0)
TVSUM;SK40.24160.25010.2184
p-value(0.0018)(0.0012)(0.0012)
SK1;SK20.26410.27730.2533
p-value(6e-04)(3e-04)(4e-04)
SK1;SK40.16160.17460.1641
p-value(0.0381)(0.0249)(0.0229)
SK2;SK40.18560.13610.128
p-value(0.017)(0.0813)(0.0806)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
TVSUM;SK1 & 0.3494 & 0.3507 & 0.2969 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
TVSUM;SK2 & 0.4862 & 0.4409 & 0.3833 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
TVSUM;SK4 & 0.2416 & 0.2501 & 0.2184 \tabularnewline
p-value & (0.0018) & (0.0012) & (0.0012) \tabularnewline
SK1;SK2 & 0.2641 & 0.2773 & 0.2533 \tabularnewline
p-value & (6e-04) & (3e-04) & (4e-04) \tabularnewline
SK1;SK4 & 0.1616 & 0.1746 & 0.1641 \tabularnewline
p-value & (0.0381) & (0.0249) & (0.0229) \tabularnewline
SK2;SK4 & 0.1856 & 0.1361 & 0.128 \tabularnewline
p-value & (0.017) & (0.0813) & (0.0806) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298832&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]TVSUM;SK1[/C][C]0.3494[/C][C]0.3507[/C][C]0.2969[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]TVSUM;SK2[/C][C]0.4862[/C][C]0.4409[/C][C]0.3833[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]TVSUM;SK4[/C][C]0.2416[/C][C]0.2501[/C][C]0.2184[/C][/ROW]
[ROW][C]p-value[/C][C](0.0018)[/C][C](0.0012)[/C][C](0.0012)[/C][/ROW]
[ROW][C]SK1;SK2[/C][C]0.2641[/C][C]0.2773[/C][C]0.2533[/C][/ROW]
[ROW][C]p-value[/C][C](6e-04)[/C][C](3e-04)[/C][C](4e-04)[/C][/ROW]
[ROW][C]SK1;SK4[/C][C]0.1616[/C][C]0.1746[/C][C]0.1641[/C][/ROW]
[ROW][C]p-value[/C][C](0.0381)[/C][C](0.0249)[/C][C](0.0229)[/C][/ROW]
[ROW][C]SK2;SK4[/C][C]0.1856[/C][C]0.1361[/C][C]0.128[/C][/ROW]
[ROW][C]p-value[/C][C](0.017)[/C][C](0.0813)[/C][C](0.0806)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298832&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298832&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
TVSUM;SK10.34940.35070.2969
p-value(0)(0)(0)
TVSUM;SK20.48620.44090.3833
p-value(0)(0)(0)
TVSUM;SK40.24160.25010.2184
p-value(0.0018)(0.0012)(0.0012)
SK1;SK20.26410.27730.2533
p-value(6e-04)(3e-04)(4e-04)
SK1;SK40.16160.17460.1641
p-value(0.0381)(0.0249)(0.0229)
SK2;SK40.18560.13610.128
p-value(0.017)(0.0813)(0.0806)






Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.010.670.670.67
0.020.830.670.67
0.030.830.830.83
0.0410.830.83
0.0510.830.83
0.0610.830.83
0.0710.830.83
0.0810.830.83
0.09111
0.1111

\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 & 0.67 & 0.67 & 0.67 \tabularnewline
0.02 & 0.83 & 0.67 & 0.67 \tabularnewline
0.03 & 0.83 & 0.83 & 0.83 \tabularnewline
0.04 & 1 & 0.83 & 0.83 \tabularnewline
0.05 & 1 & 0.83 & 0.83 \tabularnewline
0.06 & 1 & 0.83 & 0.83 \tabularnewline
0.07 & 1 & 0.83 & 0.83 \tabularnewline
0.08 & 1 & 0.83 & 0.83 \tabularnewline
0.09 & 1 & 1 & 1 \tabularnewline
0.1 & 1 & 1 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298832&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]0.67[/C][C]0.67[/C][C]0.67[/C][/ROW]
[ROW][C]0.02[/C][C]0.83[/C][C]0.67[/C][C]0.67[/C][/ROW]
[ROW][C]0.03[/C][C]0.83[/C][C]0.83[/C][C]0.83[/C][/ROW]
[ROW][C]0.04[/C][C]1[/C][C]0.83[/C][C]0.83[/C][/ROW]
[ROW][C]0.05[/C][C]1[/C][C]0.83[/C][C]0.83[/C][/ROW]
[ROW][C]0.06[/C][C]1[/C][C]0.83[/C][C]0.83[/C][/ROW]
[ROW][C]0.07[/C][C]1[/C][C]0.83[/C][C]0.83[/C][/ROW]
[ROW][C]0.08[/C][C]1[/C][C]0.83[/C][C]0.83[/C][/ROW]
[ROW][C]0.09[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.1[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298832&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298832&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
0.010.670.670.67
0.020.830.670.67
0.030.830.830.83
0.0410.830.83
0.0510.830.83
0.0610.830.83
0.0710.830.83
0.0810.830.83
0.09111
0.1111


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