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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 2011 07:18:49 -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/2011/Dec/11/t132360598881gppchr72n0j4y.htm/, Retrieved Mon, 29 Apr 2024 01:54:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153688, Retrieved Mon, 29 Apr 2024 01:54:56 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact180
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2010-12-05 18:56:24] [b98453cac15ba1066b407e146608df68]
-   PD  [Multiple Regression] [Workshop 10, Mult...] [2010-12-10 13:01:24] [3635fb7041b1998c5a1332cf9de22bce]
- RMPD      [Kendall tau Correlation Matrix] [Kendall Tau Corre...] [2011-12-11 12:18:49] [5959e8d69ed0f77745135d9c4c7e0d16] [Current]
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Dataseries X:
12008.00	4.00
9169.00	5.90
8788.00	7.10
8417.00	10.50
8247.00	15.10
8197.00	16.80
8236.00	15.30
8253.00	18.40
7733.00	16.10
8366.00	11.30
8626.00	7.90
8863.00	5.60
10102.00	3.40
8463.00	4.80
9114.00	6.50
8563.00	8.50
8872.00	15.10
8301.00	15.70
8301.00	18.70
8278.00	19.20
7736.00	12.90
7973.00	14.40
8268.00	6.20
9476.00	3.30
11100.00	4.60
8962.00	7.10
9173.00	7.80
8738.00	9.90
8459.00	13.60
8078.00	17.10
8411.00	17.80
8291.00	18.60
7810.00	14.70
8616.00	10.50
8312.00	8.60
9692.00	4.40
9911.00	2.30
8915.00	2.80
9452.00	8.80
9112.00	10.70
8472.00	13.90
8230.00	19.30
8384.00	19.50
8625.00	20.40
8221.00	15.30
8649.00	7.90
8625.00	8.30
10443.00	4.50
10357.00	3.20
8586.00	5.00
8892.00	6.60
8329.00	11.10
8101.00	12.80
7922.00	16.30
8120.00	17.40
7838.00	18.90
7735.00	15.80
8406.00	11.70
8209.00	6.40
9451.00	2.90
10041.00	4.70
9411.00	2.40
10405.00	7.20
8467.00	10.70
8464.00	13.40
8102.00	18.30
7627.00	18.40
7513.00	16.80
7510.00	16.60
8291.00	14.10
8064.00	6.10
9383.00	3.50
9706.00	1.70
8579.00	2.30
9474.00	4.50
8318.00	9.30
8213.00	14.20
8059.00	17.30
9111.00	23.00
7708.00	16.30
7680.00	18.40
8014.00	14.20
8007.00	9.10
8718.00	5.90
9486.00	7.20
9113.00	6.80
9025.00	8.00
8476.00	14.30
7952.00	14.60
7759.00	17.50
7835.00	17.20
7600.00	17.20
7651.00	14.10
8319.00	10.40
8812.00	6.80
8630.00	4.10




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 0 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153688&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153688&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153688&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 time0 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Correlations for all pairs of data series (method=kendall)
SterftecijfersTemperatuur
Sterftecijfers1-0.525
Temperatuur-0.5251

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Sterftecijfers & Temperatuur \tabularnewline
Sterftecijfers & 1 & -0.525 \tabularnewline
Temperatuur & -0.525 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153688&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Sterftecijfers[/C][C]Temperatuur[/C][/ROW]
[ROW][C]Sterftecijfers[/C][C]1[/C][C]-0.525[/C][/ROW]
[ROW][C]Temperatuur[/C][C]-0.525[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153688&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153688&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=kendall)
SterftecijfersTemperatuur
Sterftecijfers1-0.525
Temperatuur-0.5251







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Sterftecijfers;Temperatuur-0.6712-0.7231-0.5254
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
Sterftecijfers;Temperatuur & -0.6712 & -0.7231 & -0.5254 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153688&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]Sterftecijfers;Temperatuur[/C][C]-0.6712[/C][C]-0.7231[/C][C]-0.5254[/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=153688&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153688&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
Sterftecijfers;Temperatuur-0.6712-0.7231-0.5254
p-value(0)(0)(0)



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