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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 computationWed, 29 Dec 2010 14:35:54 +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/2010/Dec/29/t12936332167ceh8ocda9h5lfv.htm/, Retrieved Fri, 03 May 2024 10:04:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116872, Retrieved Fri, 03 May 2024 10:04:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Multiple Regression] [2010-12-01 14:36:47] [f82dc80ca9fc4fd83b66f6024d510f8c]
- RMPD  [Kendall tau Correlation Matrix] [] [2010-12-21 21:18:05] [4cec9a0c6d7fcfe819c8df12b51eb7f5]
-         [Kendall tau Correlation Matrix] [] [2010-12-21 21:19:40] [f82dc80ca9fc4fd83b66f6024d510f8c]
-             [Kendall tau Correlation Matrix] [] [2010-12-29 14:35:54] [9d4f9c24554023ef0148ede5dd3a4d11] [Current]
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Dataseries X:
9	2	3	3	2	14
9	2	5	4	1	18
9	4	3	2	2	11
9	3	3	2	2	12
9	3	4	4	1	16
9	2	5	4	1	18
9	4	4	4	2	14
9	3	4	4	3	14
9	2	4	3	2	15
9	2	4	3	2	15
9	2	4	5	2	17
9	1	5	4	1	19
9	2	2	2	4	10
9	1	4	3	2	16
9	2	5	5	2	18
9	3	4	4	3	14
9	2	4	3	3	14
9	2	4	4	1	17
9	3	4	2	1	14
9	2	5	3	2	16
9	1	4	4	1	18
9	3	3	2	3	11
9	4	3	5	2	14
9	3	3	3	3	12
9	2	5	4	2	17
9	4	2	3	4	9
9	2	4	4	2	16
9	4	4	4	2	14
9	3	4	4	2	15
9	4	3	2	2	11
9	2	4	4	2	16
9	3	3	4	3	13
9	1	4	4	2	17
9	2	4	3	2	15
9	3	4	4	3	14
9	2	4	4	2	16
9	4	2	3	4	9
9	2	4	3	2	15
9	2	5	4	2	17
9	2	3	4	4	13
9	2	4	4	3	15
9	2	4	4	2	16
9	2	5	4	3	16
9	3	3	4	4	12
9	2	4	NA	2	12
9	4	3	3	3	11
9	2	4	4	3	15
9	2	4	3	2	15
9	3	5	4	1	17
9	4	4	3	2	13
9	2	3	4	1	16
9	2	3	3	2	14
9	4	4	2	3	11
9	2	3	3	4	12
9	3	4	4	5	12
9	2	4	4	3	15
9	2	4	4	2	16
9	2	3	4	2	15
9	3	3	3	3	12
9	4	3	3	2	12
9	5	3	2	4	8
9	3	4	3	3	13
9	5	4	2	2	11
9	3	4	3	2	14
9	3	4	4	2	15
10	4	3	2	3	10




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
R Framework error message & 
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=116872&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=116872&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116872&T=0

As an alternative you can also use a 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'RServer@AstonUniversity' @ vre.aston.ac.uk
R Framework error message
The field 'Names of X columns' contains a hard return which cannot be interpreted.
Please, resubmit your request without hard returns in the 'Names of X columns'.







Correlations for all pairs of data series (method=pearson)
monthIDTHPPTGYWPOPPPS
month10.177-0.127-0.2230.088-0.207
IDT0.1771-0.402-0.4140.292-0.73
HPP-0.127-0.40210.434-0.5060.772
TGYW-0.223-0.4140.4341-0.1980.688
POP0.0880.292-0.506-0.1981-0.684
PPS -0.207-0.730.7720.688-0.6841

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & month & IDT & HPP & TGYW & POP & PPS
 \tabularnewline
month & 1 & 0.177 & -0.127 & -0.223 & 0.088 & -0.207 \tabularnewline
IDT & 0.177 & 1 & -0.402 & -0.414 & 0.292 & -0.73 \tabularnewline
HPP & -0.127 & -0.402 & 1 & 0.434 & -0.506 & 0.772 \tabularnewline
TGYW & -0.223 & -0.414 & 0.434 & 1 & -0.198 & 0.688 \tabularnewline
POP & 0.088 & 0.292 & -0.506 & -0.198 & 1 & -0.684 \tabularnewline
PPS
 & -0.207 & -0.73 & 0.772 & 0.688 & -0.684 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116872&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]month[/C][C]IDT[/C][C]HPP[/C][C]TGYW[/C][C]POP[/C][C]PPS
[/C][/ROW]
[ROW][C]month[/C][C]1[/C][C]0.177[/C][C]-0.127[/C][C]-0.223[/C][C]0.088[/C][C]-0.207[/C][/ROW]
[ROW][C]IDT[/C][C]0.177[/C][C]1[/C][C]-0.402[/C][C]-0.414[/C][C]0.292[/C][C]-0.73[/C][/ROW]
[ROW][C]HPP[/C][C]-0.127[/C][C]-0.402[/C][C]1[/C][C]0.434[/C][C]-0.506[/C][C]0.772[/C][/ROW]
[ROW][C]TGYW[/C][C]-0.223[/C][C]-0.414[/C][C]0.434[/C][C]1[/C][C]-0.198[/C][C]0.688[/C][/ROW]
[ROW][C]POP[/C][C]0.088[/C][C]0.292[/C][C]-0.506[/C][C]-0.198[/C][C]1[/C][C]-0.684[/C][/ROW]
[ROW][C]PPS
[/C][C]-0.207[/C][C]-0.73[/C][C]0.772[/C][C]0.688[/C][C]-0.684[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116872&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116872&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series (method=pearson)
monthIDTHPPTGYWPOPPPS
month10.177-0.127-0.2230.088-0.207
IDT0.1771-0.402-0.4140.292-0.73
HPP-0.127-0.40210.434-0.5060.772
TGYW-0.223-0.4140.4341-0.1980.688
POP0.0880.292-0.506-0.1981-0.684
PPS -0.207-0.730.7720.688-0.6841







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
month;IDT0.17690.17420.1617
p-value(0.1553)(0.1619)(0.1602)
month;HPP-0.127-0.147-0.1389
p-value(0.3095)(0.2389)(0.236)
month;TGYW-0.2227-0.199-0.1874
p-value(0.0746)(0.1121)(0.1115)
month;POP0.08790.11950.1111
p-value(0.483)(0.339)(0.3351)
month;PPS -0.2074-0.1904-0.1643
p-value(0.0948)(0.1257)(0.1248)
IDT;HPP-0.4024-0.4106-0.364
p-value(8e-04)(6e-04)(8e-04)
IDT;TGYW-0.4142-0.367-0.3215
p-value(6e-04)(0.0026)(0.0032)
IDT;POP0.29190.30440.2638
p-value(0.0174)(0.013)(0.0137)
IDT;PPS -0.7296-0.7221-0.6245
p-value(0)(0)(0)
HPP;TGYW0.43440.44190.3955
p-value(3e-04)(2e-04)(4e-04)
HPP;POP-0.5057-0.471-0.4283
p-value(0)(1e-04)(1e-04)
HPP;PPS 0.77220.75120.6649
p-value(0)(0)(0)
TGYW;POP-0.1978-0.2214-0.1933
p-value(0.1142)(0.0764)(0.0772)
TGYW;PPS 0.68780.67470.5751
p-value(0)(0)(0)
POP;PPS -0.6835-0.6684-0.5728
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
month;IDT & 0.1769 & 0.1742 & 0.1617 \tabularnewline
p-value & (0.1553) & (0.1619) & (0.1602) \tabularnewline
month;HPP & -0.127 & -0.147 & -0.1389 \tabularnewline
p-value & (0.3095) & (0.2389) & (0.236) \tabularnewline
month;TGYW & -0.2227 & -0.199 & -0.1874 \tabularnewline
p-value & (0.0746) & (0.1121) & (0.1115) \tabularnewline
month;POP & 0.0879 & 0.1195 & 0.1111 \tabularnewline
p-value & (0.483) & (0.339) & (0.3351) \tabularnewline
month;PPS
 & -0.2074 & -0.1904 & -0.1643 \tabularnewline
p-value & (0.0948) & (0.1257) & (0.1248) \tabularnewline
IDT;HPP & -0.4024 & -0.4106 & -0.364 \tabularnewline
p-value & (8e-04) & (6e-04) & (8e-04) \tabularnewline
IDT;TGYW & -0.4142 & -0.367 & -0.3215 \tabularnewline
p-value & (6e-04) & (0.0026) & (0.0032) \tabularnewline
IDT;POP & 0.2919 & 0.3044 & 0.2638 \tabularnewline
p-value & (0.0174) & (0.013) & (0.0137) \tabularnewline
IDT;PPS
 & -0.7296 & -0.7221 & -0.6245 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
HPP;TGYW & 0.4344 & 0.4419 & 0.3955 \tabularnewline
p-value & (3e-04) & (2e-04) & (4e-04) \tabularnewline
HPP;POP & -0.5057 & -0.471 & -0.4283 \tabularnewline
p-value & (0) & (1e-04) & (1e-04) \tabularnewline
HPP;PPS
 & 0.7722 & 0.7512 & 0.6649 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
TGYW;POP & -0.1978 & -0.2214 & -0.1933 \tabularnewline
p-value & (0.1142) & (0.0764) & (0.0772) \tabularnewline
TGYW;PPS
 & 0.6878 & 0.6747 & 0.5751 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
POP;PPS
 & -0.6835 & -0.6684 & -0.5728 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116872&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]month;IDT[/C][C]0.1769[/C][C]0.1742[/C][C]0.1617[/C][/ROW]
[ROW][C]p-value[/C][C](0.1553)[/C][C](0.1619)[/C][C](0.1602)[/C][/ROW]
[ROW][C]month;HPP[/C][C]-0.127[/C][C]-0.147[/C][C]-0.1389[/C][/ROW]
[ROW][C]p-value[/C][C](0.3095)[/C][C](0.2389)[/C][C](0.236)[/C][/ROW]
[ROW][C]month;TGYW[/C][C]-0.2227[/C][C]-0.199[/C][C]-0.1874[/C][/ROW]
[ROW][C]p-value[/C][C](0.0746)[/C][C](0.1121)[/C][C](0.1115)[/C][/ROW]
[ROW][C]month;POP[/C][C]0.0879[/C][C]0.1195[/C][C]0.1111[/C][/ROW]
[ROW][C]p-value[/C][C](0.483)[/C][C](0.339)[/C][C](0.3351)[/C][/ROW]
[ROW][C]month;PPS
[/C][C]-0.2074[/C][C]-0.1904[/C][C]-0.1643[/C][/ROW]
[ROW][C]p-value[/C][C](0.0948)[/C][C](0.1257)[/C][C](0.1248)[/C][/ROW]
[ROW][C]IDT;HPP[/C][C]-0.4024[/C][C]-0.4106[/C][C]-0.364[/C][/ROW]
[ROW][C]p-value[/C][C](8e-04)[/C][C](6e-04)[/C][C](8e-04)[/C][/ROW]
[ROW][C]IDT;TGYW[/C][C]-0.4142[/C][C]-0.367[/C][C]-0.3215[/C][/ROW]
[ROW][C]p-value[/C][C](6e-04)[/C][C](0.0026)[/C][C](0.0032)[/C][/ROW]
[ROW][C]IDT;POP[/C][C]0.2919[/C][C]0.3044[/C][C]0.2638[/C][/ROW]
[ROW][C]p-value[/C][C](0.0174)[/C][C](0.013)[/C][C](0.0137)[/C][/ROW]
[ROW][C]IDT;PPS
[/C][C]-0.7296[/C][C]-0.7221[/C][C]-0.6245[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]HPP;TGYW[/C][C]0.4344[/C][C]0.4419[/C][C]0.3955[/C][/ROW]
[ROW][C]p-value[/C][C](3e-04)[/C][C](2e-04)[/C][C](4e-04)[/C][/ROW]
[ROW][C]HPP;POP[/C][C]-0.5057[/C][C]-0.471[/C][C]-0.4283[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]HPP;PPS
[/C][C]0.7722[/C][C]0.7512[/C][C]0.6649[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]TGYW;POP[/C][C]-0.1978[/C][C]-0.2214[/C][C]-0.1933[/C][/ROW]
[ROW][C]p-value[/C][C](0.1142)[/C][C](0.0764)[/C][C](0.0772)[/C][/ROW]
[ROW][C]TGYW;PPS
[/C][C]0.6878[/C][C]0.6747[/C][C]0.5751[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]POP;PPS
[/C][C]-0.6835[/C][C]-0.6684[/C][C]-0.5728[/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=116872&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116872&T=2

As an alternative you can also use a 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
month;IDT0.17690.17420.1617
p-value(0.1553)(0.1619)(0.1602)
month;HPP-0.127-0.147-0.1389
p-value(0.3095)(0.2389)(0.236)
month;TGYW-0.2227-0.199-0.1874
p-value(0.0746)(0.1121)(0.1115)
month;POP0.08790.11950.1111
p-value(0.483)(0.339)(0.3351)
month;PPS -0.2074-0.1904-0.1643
p-value(0.0948)(0.1257)(0.1248)
IDT;HPP-0.4024-0.4106-0.364
p-value(8e-04)(6e-04)(8e-04)
IDT;TGYW-0.4142-0.367-0.3215
p-value(6e-04)(0.0026)(0.0032)
IDT;POP0.29190.30440.2638
p-value(0.0174)(0.013)(0.0137)
IDT;PPS -0.7296-0.7221-0.6245
p-value(0)(0)(0)
HPP;TGYW0.43440.44190.3955
p-value(3e-04)(2e-04)(4e-04)
HPP;POP-0.5057-0.471-0.4283
p-value(0)(1e-04)(1e-04)
HPP;PPS 0.77220.75120.6649
p-value(0)(0)(0)
TGYW;POP-0.1978-0.2214-0.1933
p-value(0.1142)(0.0764)(0.0772)
TGYW;PPS 0.68780.67470.5751
p-value(0)(0)(0)
POP;PPS -0.6835-0.6684-0.5728
p-value(0)(0)(0)



Parameters (Session):
par1 = pearson ;
Parameters (R input):
par1 = pearson ; 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')