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R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationMon, 10 Dec 2012 13:50:59 -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/10/t1355165472xtpc8a3h74qgtbh.htm/, Retrieved Fri, 29 Mar 2024 13:01:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198283, Retrieved Fri, 29 Mar 2024 13:01:15 +0000
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Estimated Impact64
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-       [Kendall tau Correlation Matrix] [] [2012-12-10 18:50:59] [26ce3afa84a4087bb435ca409d5552c3] [Current]
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Dataseries X:
6.80	225.00	0.44	0.67	9.20
6.30	180.00	0.44	0.80	11.70
6.40	190.00	0.46	0.76	15.80
6.20	180.00	0.42	0.65	8.60
6.90	205.00	0.45	0.90	23.20
6.40	225.00	0.43	0.78	27.40
6.30	185.00	0.49	0.77	9.30
6.80	235.00	0.47	0.75	16.00
6.90	235.00	0.44	0.82	4.70
6.70	210.00	0.48	0.83	12.50
6.90	245.00	0.52	0.63	20.10
6.90	245.00	0.49	0.76	9.10
6.30	185.00	0.37	0.71	8.10
6.10	185.00	0.42	0.78	8.60
6.20	180.00	0.44	0.78	20.30
6.80	220.00	0.50	0.88	25.00
6.50	194.00	0.50	0.83	19.20
7.60	225.00	0.43	0.57	3.30
6.30	210.00	0.37	0.82	11.20
7.10	240.00	0.50	0.71	10.50
6.80	225.00	0.40	0.77	10.10
7.30	263.00	0.48	0.66	7.20
6.40	210.00	0.48	0.24	13.60
6.80	235.00	0.43	0.73	9.00
7.20	230.00	0.56	0.72	24.60
6.40	190.00	0.44	0.76	12.60
6.60	220.00	0.49	0.75	5.60
6.80	210.00	0.40	0.74	8.70
6.10	180.00	0.42	0.71	7.70
6.50	235.00	0.49	0.74	24.10
6.40	185.00	0.48	0.86	11.70
6.00	175.00	0.39	0.72	7.70
6.00	192.00	0.44	0.79	9.60
7.30	263.00	0.48	0.66	7.20
6.10	180.00	0.34	0.82	12.30
6.70	240.00	0.52	0.73	8.90
6.40	210.00	0.48	0.85	13.60
5.80	160.00	0.41	0.81	11.20
6.90	230.00	0.41	0.60	2.80
7.00	245.00	0.41	0.57	3.20
7.30	228.00	0.45	0.73	9.40
5.90	155.00	0.29	0.71	11.90
6.20	200.00	0.45	0.80	15.40
6.80	235.00	0.55	0.78	7.40
7.00	235.00	0.48	0.74	18.90
5.90	105.00	0.36	0.84	7.90
6.10	180.00	0.53	0.79	12.20
5.70	185.00	0.35	0.70	11.00
7.10	245.00	0.41	0.78	2.80
5.80	180.00	0.43	0.87	11.80
7.40	240.00	0.60	0.71	17.10
6.80	225.00	0.48	0.70	11.60
6.80	215.00	0.46	0.73	5.80
7.00	230.00	0.44	0.76	8.30




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net
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 & 'George Udny Yule' @ yule.wessa.net \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=198283&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]'George Udny Yule' @ yule.wessa.net[/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=198283&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198283&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'George Udny Yule' @ yule.wessa.net
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)
X1X2X3X4X5
X110.8340.493-0.256-0.069
X20.83410.511-0.287-0.01
X30.4930.5111-0.0350.33
X4-0.256-0.287-0.03510.239
X5 -0.069-0.010.330.2391

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & X1 & X2 & X3 & X4 & X5
 \tabularnewline
X1 & 1 & 0.834 & 0.493 & -0.256 & -0.069 \tabularnewline
X2 & 0.834 & 1 & 0.511 & -0.287 & -0.01 \tabularnewline
X3 & 0.493 & 0.511 & 1 & -0.035 & 0.33 \tabularnewline
X4 & -0.256 & -0.287 & -0.035 & 1 & 0.239 \tabularnewline
X5
 & -0.069 & -0.01 & 0.33 & 0.239 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198283&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]X1[/C][C]X2[/C][C]X3[/C][C]X4[/C][C]X5
[/C][/ROW]
[ROW][C]X1[/C][C]1[/C][C]0.834[/C][C]0.493[/C][C]-0.256[/C][C]-0.069[/C][/ROW]
[ROW][C]X2[/C][C]0.834[/C][C]1[/C][C]0.511[/C][C]-0.287[/C][C]-0.01[/C][/ROW]
[ROW][C]X3[/C][C]0.493[/C][C]0.511[/C][C]1[/C][C]-0.035[/C][C]0.33[/C][/ROW]
[ROW][C]X4[/C][C]-0.256[/C][C]-0.287[/C][C]-0.035[/C][C]1[/C][C]0.239[/C][/ROW]
[ROW][C]X5
[/C][C]-0.069[/C][C]-0.01[/C][C]0.33[/C][C]0.239[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198283&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198283&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)
X1X2X3X4X5
X110.8340.493-0.256-0.069
X20.83410.511-0.287-0.01
X30.4930.5111-0.0350.33
X4-0.256-0.287-0.03510.239
X5 -0.069-0.010.330.2391







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
X1;X20.83430.86780.7122
p-value(0)(0)(0)
X1;X30.49270.42590.3207
p-value(2e-04)(0.0013)(0.0011)
X1;X4-0.2564-0.359-0.2721
p-value(0.0613)(0.0077)(0.0053)
X1;X5 -0.0689-0.1595-0.0897
p-value(0.6205)(0.2492)(0.3525)
X2;X30.51090.45760.3451
p-value(1e-04)(5e-04)(5e-04)
X2;X4-0.2871-0.3725-0.2656
p-value(0.0353)(0.0055)(0.0065)
X2;X5 -0.0098-0.1526-0.093
p-value(0.9437)(0.2707)(0.3339)
X3;X4-0.03460.01540.0044
p-value(0.8039)(0.9118)(0.9641)
X3;X5 0.33010.34950.2437
p-value(0.0148)(0.0096)(0.0113)
X4;X5 0.23850.33650.2422
p-value(0.0824)(0.0128)(0.011)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
X1;X2 & 0.8343 & 0.8678 & 0.7122 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X1;X3 & 0.4927 & 0.4259 & 0.3207 \tabularnewline
p-value & (2e-04) & (0.0013) & (0.0011) \tabularnewline
X1;X4 & -0.2564 & -0.359 & -0.2721 \tabularnewline
p-value & (0.0613) & (0.0077) & (0.0053) \tabularnewline
X1;X5
 & -0.0689 & -0.1595 & -0.0897 \tabularnewline
p-value & (0.6205) & (0.2492) & (0.3525) \tabularnewline
X2;X3 & 0.5109 & 0.4576 & 0.3451 \tabularnewline
p-value & (1e-04) & (5e-04) & (5e-04) \tabularnewline
X2;X4 & -0.2871 & -0.3725 & -0.2656 \tabularnewline
p-value & (0.0353) & (0.0055) & (0.0065) \tabularnewline
X2;X5
 & -0.0098 & -0.1526 & -0.093 \tabularnewline
p-value & (0.9437) & (0.2707) & (0.3339) \tabularnewline
X3;X4 & -0.0346 & 0.0154 & 0.0044 \tabularnewline
p-value & (0.8039) & (0.9118) & (0.9641) \tabularnewline
X3;X5
 & 0.3301 & 0.3495 & 0.2437 \tabularnewline
p-value & (0.0148) & (0.0096) & (0.0113) \tabularnewline
X4;X5
 & 0.2385 & 0.3365 & 0.2422 \tabularnewline
p-value & (0.0824) & (0.0128) & (0.011) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198283&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]X1;X2[/C][C]0.8343[/C][C]0.8678[/C][C]0.7122[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X1;X3[/C][C]0.4927[/C][C]0.4259[/C][C]0.3207[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](0.0013)[/C][C](0.0011)[/C][/ROW]
[ROW][C]X1;X4[/C][C]-0.2564[/C][C]-0.359[/C][C]-0.2721[/C][/ROW]
[ROW][C]p-value[/C][C](0.0613)[/C][C](0.0077)[/C][C](0.0053)[/C][/ROW]
[ROW][C]X1;X5
[/C][C]-0.0689[/C][C]-0.1595[/C][C]-0.0897[/C][/ROW]
[ROW][C]p-value[/C][C](0.6205)[/C][C](0.2492)[/C][C](0.3525)[/C][/ROW]
[ROW][C]X2;X3[/C][C]0.5109[/C][C]0.4576[/C][C]0.3451[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](5e-04)[/C][C](5e-04)[/C][/ROW]
[ROW][C]X2;X4[/C][C]-0.2871[/C][C]-0.3725[/C][C]-0.2656[/C][/ROW]
[ROW][C]p-value[/C][C](0.0353)[/C][C](0.0055)[/C][C](0.0065)[/C][/ROW]
[ROW][C]X2;X5
[/C][C]-0.0098[/C][C]-0.1526[/C][C]-0.093[/C][/ROW]
[ROW][C]p-value[/C][C](0.9437)[/C][C](0.2707)[/C][C](0.3339)[/C][/ROW]
[ROW][C]X3;X4[/C][C]-0.0346[/C][C]0.0154[/C][C]0.0044[/C][/ROW]
[ROW][C]p-value[/C][C](0.8039)[/C][C](0.9118)[/C][C](0.9641)[/C][/ROW]
[ROW][C]X3;X5
[/C][C]0.3301[/C][C]0.3495[/C][C]0.2437[/C][/ROW]
[ROW][C]p-value[/C][C](0.0148)[/C][C](0.0096)[/C][C](0.0113)[/C][/ROW]
[ROW][C]X4;X5
[/C][C]0.2385[/C][C]0.3365[/C][C]0.2422[/C][/ROW]
[ROW][C]p-value[/C][C](0.0824)[/C][C](0.0128)[/C][C](0.011)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198283&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198283&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
X1;X20.83430.86780.7122
p-value(0)(0)(0)
X1;X30.49270.42590.3207
p-value(2e-04)(0.0013)(0.0011)
X1;X4-0.2564-0.359-0.2721
p-value(0.0613)(0.0077)(0.0053)
X1;X5 -0.0689-0.1595-0.0897
p-value(0.6205)(0.2492)(0.3525)
X2;X30.51090.45760.3451
p-value(1e-04)(5e-04)(5e-04)
X2;X4-0.2871-0.3725-0.2656
p-value(0.0353)(0.0055)(0.0065)
X2;X5 -0.0098-0.1526-0.093
p-value(0.9437)(0.2707)(0.3339)
X3;X4-0.03460.01540.0044
p-value(0.8039)(0.9118)(0.9641)
X3;X5 0.33010.34950.2437
p-value(0.0148)(0.0096)(0.0113)
X4;X5 0.23850.33650.2422
p-value(0.0824)(0.0128)(0.011)



Parameters (Session):
par1 = pearson ;
Parameters (R input):
par1 = pearson ;
R code (references can be found in the software module):
par1 <- 'pearson'
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')