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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 computationThu, 22 Dec 2011 13:09:43 -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/22/t13245774337refpmajj17w0h4.htm/, Retrieved Fri, 03 May 2024 06:17:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=159807, Retrieved Fri, 03 May 2024 06:17:06 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
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 18:04:16] [b98453cac15ba1066b407e146608df68]
- RMPD  [Kendall tau Correlation Matrix] [WS 10 kendall's t...] [2011-12-09 12:33:10] [60c0c94f647e2c90e494ab0f2a2f1926]
-   PD    [Kendall tau Correlation Matrix] [WS 10 kendall's t...] [2011-12-09 13:50:14] [60c0c94f647e2c90e494ab0f2a2f1926]
-   PD        [Kendall tau Correlation Matrix] [Paper pearson] [2011-12-22 18:09:43] [7e9b6bd31a62815918579b1facd0f368] [Current]
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Dataseries X:
12	13	6
7	11	4
13	14	6
11	12	5
16	12	5
10	6	4
15	10	5
5	11	3
4	10	2
7	12	5
15	15	6
5	13	6
16	18	8
15	11	6
13	12	3
13	13	6
15	14	6
15	16	7
10	16	8
17	16	6
14	15	7
9	13	4
6	8	4
11	14	2
13	15	6
12	13	6
10	16	6
4	13	6
13	12	6
15	15	7
8	11	4
10	14	3
8	13	5
7	13	6
9	12	4
14	14	6
5	13	3
7	12	3
16	14	6
14	15	6
16	16	6
15	15	8
4	5	2
12	15	6
8	8	4
17	16	7
15	16	6
16	14	6
12	16	6
12	14	5
13	13	6
14	14	6
14	14	5
15	12	6
14	13	7
11	15	5
13	15	6
4	13	6
8	10	4
13	13	5
15	14	6
15	13	6
8	13	4
17	18	6
12	12	4
13	14	7
14	16	8
7	13	6
16	16	6
11	15	6
10	14	5
14	13	6
19	12	6
14	16	4
8	9	5
15	15	8
8	16	6
8	12	6
6	11	2
7	13	2
16	13	4
15	14	6
10	15	6
8	14	5
9	12	4
8	16	4
14	14	6
14	13	5
14	12	6
15	13	7
7	12	6
7	9	4
12	13	4
7	10	3
12	15	8
6	9	4
10	13	4
12	13	5
13	13	5
14	15	7
8	13	4
14	14	5
10	11	5
14	15	8
15	14	5
10	15	2
6	12	5
9	15	4
11	14	5
16	16	7
14	14	6
8	12	3
16	11	5
16	13	6
14	12	5
12	12	6
16	16	7
15	13	6
11	12	6
6	14	5
6	4	4
16	14	6
16	15	6
8	12	3
11	11	4
12	12	4
13	11	4
11	12	5
9	11	4
15	13	6
11	12	6
12	12	4
15	15	7
8	14	4
7	12	4
10	12	4
9	12	4
13	13	5
11	11	4
12	13	7
5	12	3
12	14	5
14	15	5
15	15	6
14	13	5
13	16	6
14	17	6
14	13	3
15	14	6
13	13	5
14	16	8
11	13	6
14	14	4
11	13	3
8	14	4
12	16	7




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159807&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159807&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159807&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 time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Correlations for all pairs of data series (method=kendall)
Knowing_peoplePerceived_likedCelebrity
Knowing_people10.370.45
Perceived_liked0.3710.465
Celebrity0.450.4651

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Knowing_people & Perceived_liked & Celebrity \tabularnewline
Knowing_people & 1 & 0.37 & 0.45 \tabularnewline
Perceived_liked & 0.37 & 1 & 0.465 \tabularnewline
Celebrity & 0.45 & 0.465 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159807&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Knowing_people[/C][C]Perceived_liked[/C][C]Celebrity[/C][/ROW]
[ROW][C]Knowing_people[/C][C]1[/C][C]0.37[/C][C]0.45[/C][/ROW]
[ROW][C]Perceived_liked[/C][C]0.37[/C][C]1[/C][C]0.465[/C][/ROW]
[ROW][C]Celebrity[/C][C]0.45[/C][C]0.465[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=159807&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159807&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)
Knowing_peoplePerceived_likedCelebrity
Knowing_people10.370.45
Perceived_liked0.3710.465
Celebrity0.450.4651







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Knowing_people;Perceived_liked0.49730.47530.3704
p-value(0)(0)(0)
Knowing_people;Celebrity0.55770.56920.4502
p-value(0)(0)(0)
Perceived_liked;Celebrity0.53760.56990.4651
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
Knowing_people;Perceived_liked & 0.4973 & 0.4753 & 0.3704 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Knowing_people;Celebrity & 0.5577 & 0.5692 & 0.4502 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Perceived_liked;Celebrity & 0.5376 & 0.5699 & 0.4651 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=159807&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]Knowing_people;Perceived_liked[/C][C]0.4973[/C][C]0.4753[/C][C]0.3704[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Knowing_people;Celebrity[/C][C]0.5577[/C][C]0.5692[/C][C]0.4502[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Perceived_liked;Celebrity[/C][C]0.5376[/C][C]0.5699[/C][C]0.4651[/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=159807&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=159807&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
Knowing_people;Perceived_liked0.49730.47530.3704
p-value(0)(0)(0)
Knowing_people;Celebrity0.55770.56920.4502
p-value(0)(0)(0)
Perceived_liked;Celebrity0.53760.56990.4651
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')