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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, 14 Dec 2010 07:53:26 +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/14/t1292313105fzgh6axph9zv4q3.htm/, Retrieved Thu, 02 May 2024 20:58:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109247, Retrieved Thu, 02 May 2024 20:58:56 +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]
- R PD    [Kendall tau Correlation Matrix] [] [2010-12-14 07:53:26] [5f45e5b827d1a020c3ecc9d930121b4e] [Current]
-    D      [Kendall tau Correlation Matrix] [] [2010-12-14 08:01:01] [22937c5b58c14f6c22964f32d64ff823]
- RM          [Kendall tau Correlation Matrix] [] [2010-12-14 14:04:12] [f72e5115d7374b3b3f29ba3966e5379d]
-   PD      [Kendall tau Correlation Matrix] [] [2010-12-14 09:05:37] [22937c5b58c14f6c22964f32d64ff823]
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Dataseries X:
2	14	53
2	18	86
2	11	66
1	12	67
2	16	76
2	18	78
2	14	53
2	14	80
2	15	74
2	15	76
1	17	79
2	19	54
1	10	67
2	16	54
2	18	87
1	14	58
1	14	75
2	17	88
1	14	64
2	16	57
1	18	66
2	11	68
2	14	54
2	12	56
1	17	86
2	9	80
1	16	76
2	14	69
2	15	78
1	11	67
2	16	80
1	13	54
2	17	71
2	15	84
1	14	74
1	16	71
1	9	63
1	15	71
2	17	76
1	13	69
1	15	74
2	16	75
1	16	54
1	12	52
2	12	69
2	11	68
2	15	65
2	15	75
2	17	74
1	13	75
2	16	72
1	14	67
1	11	63
2	12	62
1	12	63
2	15	76
2	16	74
2	15	67
1	12	73
2	12	70
1	8	53
1	13	77
2	11	77
2	14	52
2	15	54
1	10	80
2	11	66
1	12	73
2	15	63
1	15	69
1	14	67
2	16	54
2	15	81
1	15	69
1	13	84
2	12	80
2	17	70
2	13	69
1	15	77
1	13	54
1	15	79
1	16	30
2	15	71
1	16	73
2	15	72
2	14	77
1	15	75
2	14	69
2	13	54
2	7	70
2	17	73
2	13	54
2	15	77
2	14	82
2	13	80
2	16	80
2	12	69
2	14	78
1	17	81
1	15	76
2	17	76
1	12	73
2	16	85
1	11	66
2	15	79
1	9	68
2	16	76
1	15	71
1	10	54
2	10	46
2	15	82
2	11	74
2	13	88
1	14	38
2	18	76
1	16	86
2	14	54
2	14	70
2	14	69
2	14	90
2	12	54
2	14	76
2	15	89
2	15	76
2	15	73
2	13	79
1	17	90
2	17	74
2	19	81
2	15	72
1	13	71
1	9	66
2	15	77
1	15	65
1	15	74
2	16	82
1	11	54
1	14	63
2	11	54
2	15	64
1	13	69
2	15	54
1	16	84
2	14	86
1	15	77
2	16	89
2	16	76
1	11	60
1	12	75
1	9	73
2	16	85
2	13	79
1	16	71
2	12	72
2	9	69
2	13	78
2	13	54
2	14	69
2	19	81
2	13	84
2	12	84
2	13	69




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109247&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109247&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109247&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'Gwilym Jenkins' @ 72.249.127.135







Correlations for all pairs of data series (method=pearson)
GenderHappinessBelonging
Gender10.1820.143
Happiness0.18210.286
Belonging0.1430.2861

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Gender & Happiness & Belonging \tabularnewline
Gender & 1 & 0.182 & 0.143 \tabularnewline
Happiness & 0.182 & 1 & 0.286 \tabularnewline
Belonging & 0.143 & 0.286 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109247&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Gender[/C][C]Happiness[/C][C]Belonging[/C][/ROW]
[ROW][C]Gender[/C][C]1[/C][C]0.182[/C][C]0.143[/C][/ROW]
[ROW][C]Happiness[/C][C]0.182[/C][C]1[/C][C]0.286[/C][/ROW]
[ROW][C]Belonging[/C][C]0.143[/C][C]0.286[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109247&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109247&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)
GenderHappinessBelonging
Gender10.1820.143
Happiness0.18210.286
Belonging0.1430.2861







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Gender;Happiness0.18180.16430.1422
p-value(0.0206)(0.0367)(0.0371)
Gender;Belonging0.14340.16890.1409
p-value(0.0687)(0.0317)(0.0321)
Happiness;Belonging0.28560.36180.2635
p-value(2e-04)(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
Gender;Happiness & 0.1818 & 0.1643 & 0.1422 \tabularnewline
p-value & (0.0206) & (0.0367) & (0.0371) \tabularnewline
Gender;Belonging & 0.1434 & 0.1689 & 0.1409 \tabularnewline
p-value & (0.0687) & (0.0317) & (0.0321) \tabularnewline
Happiness;Belonging & 0.2856 & 0.3618 & 0.2635 \tabularnewline
p-value & (2e-04) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109247&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]Gender;Happiness[/C][C]0.1818[/C][C]0.1643[/C][C]0.1422[/C][/ROW]
[ROW][C]p-value[/C][C](0.0206)[/C][C](0.0367)[/C][C](0.0371)[/C][/ROW]
[ROW][C]Gender;Belonging[/C][C]0.1434[/C][C]0.1689[/C][C]0.1409[/C][/ROW]
[ROW][C]p-value[/C][C](0.0687)[/C][C](0.0317)[/C][C](0.0321)[/C][/ROW]
[ROW][C]Happiness;Belonging[/C][C]0.2856[/C][C]0.3618[/C][C]0.2635[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109247&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109247&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
Gender;Happiness0.18180.16430.1422
p-value(0.0206)(0.0367)(0.0371)
Gender;Belonging0.14340.16890.1409
p-value(0.0687)(0.0317)(0.0321)
Happiness;Belonging0.28560.36180.2635
p-value(2e-04)(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')