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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, 09 Dec 2012 12:03:13 -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/09/t1355072684gtkfsq0eht3zrp6.htm/, Retrieved Fri, 19 Apr 2024 11:49:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197989, Retrieved Fri, 19 Apr 2024 11:49:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110

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 17:44:33] [b98453cac15ba1066b407e146608df68]
- RMPD  [Kendall tau Correlation Matrix] [] [2011-12-11 11:57:54] [b4c8fd31b0af00c33711722ddf8d2c4c]
-   PD    [Kendall tau Correlation Matrix] [] [2011-12-11 13:31:49] [b4c8fd31b0af00c33711722ddf8d2c4c]
-    D      [Kendall tau Correlation Matrix] [] [2011-12-11 14:05:41] [b4c8fd31b0af00c33711722ddf8d2c4c]
-   PD        [Kendall tau Correlation Matrix] [] [2011-12-12 09:38:14] [74be16979710d4c4e7c6647856088456]
-    D            [Kendall tau Correlation Matrix] [WS10 (1)] [2012-12-09 17:03:13] [6b9eda33bf4cae06c9f9f024b199ddfb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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1	1	201940	93913
1	1	235454	136048
1	1	220801	181248

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'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197989&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197989&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197989&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'Gwilym Jenkins' @ jenkins.wessa.net






Correlations for all pairs of data series (method=pearson)
POPGenderTime_RFC_secCompendium_writing_time_sec
POP10.113-0.0120.035
Gender0.1131-0.048-0.173
Time_RFC_sec-0.012-0.04810.052
Compendium_writing_time_sec0.035-0.1730.0521

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & POP & Gender & Time_RFC_sec & Compendium_writing_time_sec \tabularnewline
POP & 1 & 0.113 & -0.012 & 0.035 \tabularnewline
Gender & 0.113 & 1 & -0.048 & -0.173 \tabularnewline
Time_RFC_sec & -0.012 & -0.048 & 1 & 0.052 \tabularnewline
Compendium_writing_time_sec & 0.035 & -0.173 & 0.052 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197989&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/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]0.113[/C][C]-0.012[/C][C]0.035[/C][/ROW]
[ROW][C]Gender[/C][C]0.113[/C][C]1[/C][C]-0.048[/C][C]-0.173[/C][/ROW]
[ROW][C]Time_RFC_sec[/C][C]-0.012[/C][C]-0.048[/C][C]1[/C][C]0.052[/C][/ROW]
[ROW][C]Compendium_writing_time_sec[/C][C]0.035[/C][C]-0.173[/C][C]0.052[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197989&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197989&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)
POPGenderTime_RFC_secCompendium_writing_time_sec
POP10.113-0.0120.035
Gender0.1131-0.048-0.173
Time_RFC_sec-0.012-0.04810.052
Compendium_writing_time_sec0.035-0.1730.0521






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
POP;Gender0.11320.11320.1132
p-value(0.2478)(0.2478)(0.246)
POP;Time_RFC_sec-0.01220.00340.0028
p-value(0.9015)(0.9725)(0.9723)
POP;Compendium_writing_time_sec0.03540.01260.0104
p-value(0.7186)(0.8977)(0.8969)
Gender;Time_RFC_sec-0.0475-0.0598-0.0491
p-value(0.6286)(0.5424)(0.5399)
Gender;Compendium_writing_time_sec-0.1728-0.2017-0.1654
p-value(0.0766)(0.0382)(0.0388)
Time_RFC_sec;Compendium_writing_time_sec0.05220.05740.0376
p-value(0.5949)(0.5584)(0.5683)

\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 & 0.1132 & 0.1132 & 0.1132 \tabularnewline
p-value & (0.2478) & (0.2478) & (0.246) \tabularnewline
POP;Time_RFC_sec & -0.0122 & 0.0034 & 0.0028 \tabularnewline
p-value & (0.9015) & (0.9725) & (0.9723) \tabularnewline
POP;Compendium_writing_time_sec & 0.0354 & 0.0126 & 0.0104 \tabularnewline
p-value & (0.7186) & (0.8977) & (0.8969) \tabularnewline
Gender;Time_RFC_sec & -0.0475 & -0.0598 & -0.0491 \tabularnewline
p-value & (0.6286) & (0.5424) & (0.5399) \tabularnewline
Gender;Compendium_writing_time_sec & -0.1728 & -0.2017 & -0.1654 \tabularnewline
p-value & (0.0766) & (0.0382) & (0.0388) \tabularnewline
Time_RFC_sec;Compendium_writing_time_sec & 0.0522 & 0.0574 & 0.0376 \tabularnewline
p-value & (0.5949) & (0.5584) & (0.5683) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197989&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]0.1132[/C][C]0.1132[/C][C]0.1132[/C][/ROW]
[ROW][C]p-value[/C][C](0.2478)[/C][C](0.2478)[/C][C](0.246)[/C][/ROW]
[ROW][C]POP;Time_RFC_sec[/C][C]-0.0122[/C][C]0.0034[/C][C]0.0028[/C][/ROW]
[ROW][C]p-value[/C][C](0.9015)[/C][C](0.9725)[/C][C](0.9723)[/C][/ROW]
[ROW][C]POP;Compendium_writing_time_sec[/C][C]0.0354[/C][C]0.0126[/C][C]0.0104[/C][/ROW]
[ROW][C]p-value[/C][C](0.7186)[/C][C](0.8977)[/C][C](0.8969)[/C][/ROW]
[ROW][C]Gender;Time_RFC_sec[/C][C]-0.0475[/C][C]-0.0598[/C][C]-0.0491[/C][/ROW]
[ROW][C]p-value[/C][C](0.6286)[/C][C](0.5424)[/C][C](0.5399)[/C][/ROW]
[ROW][C]Gender;Compendium_writing_time_sec[/C][C]-0.1728[/C][C]-0.2017[/C][C]-0.1654[/C][/ROW]
[ROW][C]p-value[/C][C](0.0766)[/C][C](0.0382)[/C][C](0.0388)[/C][/ROW]
[ROW][C]Time_RFC_sec;Compendium_writing_time_sec[/C][C]0.0522[/C][C]0.0574[/C][C]0.0376[/C][/ROW]
[ROW][C]p-value[/C][C](0.5949)[/C][C](0.5584)[/C][C](0.5683)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197989&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197989&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;Gender0.11320.11320.1132
p-value(0.2478)(0.2478)(0.246)
POP;Time_RFC_sec-0.01220.00340.0028
p-value(0.9015)(0.9725)(0.9723)
POP;Compendium_writing_time_sec0.03540.01260.0104
p-value(0.7186)(0.8977)(0.8969)
Gender;Time_RFC_sec-0.0475-0.0598-0.0491
p-value(0.6286)(0.5424)(0.5399)
Gender;Compendium_writing_time_sec-0.1728-0.2017-0.1654
p-value(0.0766)(0.0382)(0.0388)
Time_RFC_sec;Compendium_writing_time_sec0.05220.05740.0376
p-value(0.5949)(0.5584)(0.5683)


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')
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')