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Author's title

Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 21 Dec 2010 12:06:15 +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/21/t1292933041wmvnw7kxfiosudk.htm/, Retrieved Fri, 17 May 2024 18:51:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113339, Retrieved Fri, 17 May 2024 18:51:58 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153
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]
-   PD    [Kendall tau Correlation Matrix] [] [2010-12-21 12:06:15] [1d208f56d63f78e3037c4c685f0bba30] [Current]
- RM D      [Kendall tau Correlation Matrix] [pearson correlati...] [2010-12-24 10:01:53] [d4d7f64064e581afd5f11cb27d8ab03c]
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Dataseries X:
112.3	112.9	88.7	105.1
117.3	130.5	94.6	114.9
111.1	137.9	98.7	106.4
102.2	115	84.2	104.5
104.3	116.8	87.7	121.6
122.9	140.9	103.3	141.4
107.6	120.7	88.2	99
121.3	134.2	93.4	126.7
131.5	147.3	106.3	134.1
89	112.4	73.1	81.3
104.4	107.1	78.6	88.6
128.9	128.4	101.6	132.7
135.9	137.7	101.4	132.9
133.3	135	98.5	134.4
121.3	151	99	103.7
120.5	137.4	89.5	119.7
120.4	132.4	83.5	115
137.9	161.3	97.4	132.9
126.1	139.8	87.8	108.5
133.2	146	90.4	113.9
151.1	166.5	101.6	142
105	143.3	80	97.7
119	121	81.7	92.2
140.4	152.6	96.4	128.8
156.6	154.4	110.2	134.9
137.1	154.6	101.1	128.2
122.7	158	89.3	114.8
125.8	142.6	90	117.9
139.3	153.4	95.4	119.1
134.9	163.4	100.3	120.7
149.2	167.3	99.5	129.1
132.3	154.8	93.9	117.6
149	165.7	100.6	129.2
117.2	144.7	84.7	100
119.6	120.9	81.6	87
152	152.8	109	128
149.4	160.2	99	127.7
127.3	128.3	81.1	93.4
114.1	150.5	81.8	84.1
102.1	117	66.5	71.7
107.7	116	66.4	83.2
104.4	133.3	86.3	89.1
102.1	116.4	73.6	79.6
96	104	71.5	62.8
109.3	126.6	87.2	95.1
90	92.9	65.3	63.6
83.9	83.6	69.7	61.4
112	112.8	95.5	98.2
114.3	113.2	86.3	95.3
103.6	118.5	81	81.5
91.7	125.5	88.7	85.5
80.8	91.3	71.9	71.1
87.2	105.4	78.6	78.1
109.2	121.3	96	103
102.7	106.9	81.1	86
95.1	109.4	77.5	86.2
117.5	132.6	97.3	105.7
85.1	96.8	78.6	57.2
92.1	100.3	79	73.7
113.5	119.2	93.4	120.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113339&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113339&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113339&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Correlations for all pairs of data series (method=pearson)
X1X2X3X4
X110.8760.8020.859
X20.87610.7440.789
X30.8020.74410.883
X40.8590.7890.8831

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & X1 & X2 & X3 & X4 \tabularnewline
X1 & 1 & 0.876 & 0.802 & 0.859 \tabularnewline
X2 & 0.876 & 1 & 0.744 & 0.789 \tabularnewline
X3 & 0.802 & 0.744 & 1 & 0.883 \tabularnewline
X4 & 0.859 & 0.789 & 0.883 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113339&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][/ROW]
[ROW][C]X1[/C][C]1[/C][C]0.876[/C][C]0.802[/C][C]0.859[/C][/ROW]
[ROW][C]X2[/C][C]0.876[/C][C]1[/C][C]0.744[/C][C]0.789[/C][/ROW]
[ROW][C]X3[/C][C]0.802[/C][C]0.744[/C][C]1[/C][C]0.883[/C][/ROW]
[ROW][C]X4[/C][C]0.859[/C][C]0.789[/C][C]0.883[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113339&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113339&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)
X1X2X3X4
X110.8760.8020.859
X20.87610.7440.789
X30.8020.74410.883
X40.8590.7890.8831







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
X1;X20.87610.87440.6949
p-value(0)(0)(0)
X1;X30.80180.8240.6202
p-value(0)(0)(0)
X1;X40.85910.86750.6833
p-value(0)(0)(0)
X2;X30.74420.76320.5647
p-value(0)(0)(0)
X2;X40.78880.76930.5815
p-value(0)(0)(0)
X3;X40.88260.90110.7263
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
X1;X2 & 0.8761 & 0.8744 & 0.6949 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X1;X3 & 0.8018 & 0.824 & 0.6202 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X1;X4 & 0.8591 & 0.8675 & 0.6833 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X2;X3 & 0.7442 & 0.7632 & 0.5647 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X2;X4 & 0.7888 & 0.7693 & 0.5815 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
X3;X4 & 0.8826 & 0.9011 & 0.7263 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113339&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]0.8761[/C][C]0.8744[/C][C]0.6949[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X1;X3[/C][C]0.8018[/C][C]0.824[/C][C]0.6202[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X1;X4[/C][C]0.8591[/C][C]0.8675[/C][C]0.6833[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X2;X3[/C][C]0.7442[/C][C]0.7632[/C][C]0.5647[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X2;X4[/C][C]0.7888[/C][C]0.7693[/C][C]0.5815[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]X3;X4[/C][C]0.8826[/C][C]0.9011[/C][C]0.7263[/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=113339&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113339&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;X20.87610.87440.6949
p-value(0)(0)(0)
X1;X30.80180.8240.6202
p-value(0)(0)(0)
X1;X40.85910.86750.6833
p-value(0)(0)(0)
X2;X30.74420.76320.5647
p-value(0)(0)(0)
X2;X40.78880.76930.5815
p-value(0)(0)(0)
X3;X40.88260.90110.7263
p-value(0)(0)(0)



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')