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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareKendall tau Correlation Matrix
Date of computationFri, 07 Dec 2012 08:48:13 -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/Dec/07/t13548881085je34vmj3gc7ypd.htm/, Retrieved Fri, 19 Apr 2024 03:28:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197371, Retrieved Fri, 19 Apr 2024 03:28:13 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116

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] [] [2010-12-05 18:04:16] [b98453cac15ba1066b407e146608df68]
- RMPD  [Kendall tau Correlation Matrix] [] [2011-12-11 12:47:57] [b4c8fd31b0af00c33711722ddf8d2c4c]
-   PD    [Kendall tau Correlation Matrix] [] [2011-12-11 13:35:32] [b4c8fd31b0af00c33711722ddf8d2c4c]
-    D      [Kendall tau Correlation Matrix] [] [2011-12-11 14:09:21] [b4c8fd31b0af00c33711722ddf8d2c4c]
-   PD        [Kendall tau Correlation Matrix] [] [2011-12-12 10:00:02] [74be16979710d4c4e7c6647856088456]
-               [Kendall tau Correlation Matrix] [] [2011-12-12 10:02:56] [74be16979710d4c4e7c6647856088456]
-  M                [Kendall tau Correlation Matrix] [WS 10] [2012-12-07 13:48:13] [f4c84c9faf29e2061c3a475b218c0eb5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197371&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]2 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=197371&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197371&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Correlations for all pairs of data series (method=kendall)
PopGenderTime_RFC_secCompendium_writing_time_sec
Pop10.907-0.091-0.113
Gender0.9071-0.102-0.111
Time_RFC_sec-0.091-0.10210.699
Compendium_writing_time_sec-0.113-0.1110.6991

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Pop & Gender & Time_RFC_sec & Compendium_writing_time_sec \tabularnewline
Pop & 1 & 0.907 & -0.091 & -0.113 \tabularnewline
Gender & 0.907 & 1 & -0.102 & -0.111 \tabularnewline
Time_RFC_sec & -0.091 & -0.102 & 1 & 0.699 \tabularnewline
Compendium_writing_time_sec & -0.113 & -0.111 & 0.699 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197371&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Pop[/C][C]Gender[/C][C]Time_RFC_sec[/C][C]Compendium_writing_time_sec[/C][/ROW]
[ROW][C]Pop[/C][C]1[/C][C]0.907[/C][C]-0.091[/C][C]-0.113[/C][/ROW]
[ROW][C]Gender[/C][C]0.907[/C][C]1[/C][C]-0.102[/C][C]-0.111[/C][/ROW]
[ROW][C]Time_RFC_sec[/C][C]-0.091[/C][C]-0.102[/C][C]1[/C][C]0.699[/C][/ROW]
[ROW][C]Compendium_writing_time_sec[/C][C]-0.113[/C][C]-0.111[/C][C]0.699[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197371&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197371&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)
PopGenderTime_RFC_secCompendium_writing_time_sec
Pop10.907-0.091-0.113
Gender0.9071-0.102-0.111
Time_RFC_sec-0.091-0.10210.699
Compendium_writing_time_sec-0.113-0.1110.6991






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Pop;Gender0.90740.90740.9074
p-value(0)(0)(0)
Pop;Time_RFC_sec-0.1333-0.111-0.0909
p-value(0.0887)(0.157)(0.1563)
Pop;Compendium_writing_time_sec-0.1392-0.1384-0.1134
p-value(0.0754)(0.0773)(0.0773)
Gender;Time_RFC_sec-0.1528-0.1239-0.1015
p-value(0.0509)(0.1138)(0.1136)
Gender;Compendium_writing_time_sec-0.1419-0.1354-0.111
p-value(0.0699)(0.0838)(0.0838)
Time_RFC_sec;Compendium_writing_time_sec0.85950.86060.6986
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
Pop;Gender & 0.9074 & 0.9074 & 0.9074 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Pop;Time_RFC_sec & -0.1333 & -0.111 & -0.0909 \tabularnewline
p-value & (0.0887) & (0.157) & (0.1563) \tabularnewline
Pop;Compendium_writing_time_sec & -0.1392 & -0.1384 & -0.1134 \tabularnewline
p-value & (0.0754) & (0.0773) & (0.0773) \tabularnewline
Gender;Time_RFC_sec & -0.1528 & -0.1239 & -0.1015 \tabularnewline
p-value & (0.0509) & (0.1138) & (0.1136) \tabularnewline
Gender;Compendium_writing_time_sec & -0.1419 & -0.1354 & -0.111 \tabularnewline
p-value & (0.0699) & (0.0838) & (0.0838) \tabularnewline
Time_RFC_sec;Compendium_writing_time_sec & 0.8595 & 0.8606 & 0.6986 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197371&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]Pop;Gender[/C][C]0.9074[/C][C]0.9074[/C][C]0.9074[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Pop;Time_RFC_sec[/C][C]-0.1333[/C][C]-0.111[/C][C]-0.0909[/C][/ROW]
[ROW][C]p-value[/C][C](0.0887)[/C][C](0.157)[/C][C](0.1563)[/C][/ROW]
[ROW][C]Pop;Compendium_writing_time_sec[/C][C]-0.1392[/C][C]-0.1384[/C][C]-0.1134[/C][/ROW]
[ROW][C]p-value[/C][C](0.0754)[/C][C](0.0773)[/C][C](0.0773)[/C][/ROW]
[ROW][C]Gender;Time_RFC_sec[/C][C]-0.1528[/C][C]-0.1239[/C][C]-0.1015[/C][/ROW]
[ROW][C]p-value[/C][C](0.0509)[/C][C](0.1138)[/C][C](0.1136)[/C][/ROW]
[ROW][C]Gender;Compendium_writing_time_sec[/C][C]-0.1419[/C][C]-0.1354[/C][C]-0.111[/C][/ROW]
[ROW][C]p-value[/C][C](0.0699)[/C][C](0.0838)[/C][C](0.0838)[/C][/ROW]
[ROW][C]Time_RFC_sec;Compendium_writing_time_sec[/C][C]0.8595[/C][C]0.8606[/C][C]0.6986[/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=197371&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197371&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
Pop;Gender0.90740.90740.9074
p-value(0)(0)(0)
Pop;Time_RFC_sec-0.1333-0.111-0.0909
p-value(0.0887)(0.157)(0.1563)
Pop;Compendium_writing_time_sec-0.1392-0.1384-0.1134
p-value(0.0754)(0.0773)(0.0773)
Gender;Time_RFC_sec-0.1528-0.1239-0.1015
p-value(0.0509)(0.1138)(0.1136)
Gender;Compendium_writing_time_sec-0.1419-0.1354-0.111
p-value(0.0699)(0.0838)(0.0838)
Time_RFC_sec;Compendium_writing_time_sec0.85950.86060.6986
p-value(0)(0)(0)


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = kendall ;
Parameters (R input):
par1 = kendall ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')