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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationThu, 13 Dec 2012 12:44:55 -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/13/t1355420769be07eugaxm6jyca.htm/, Retrieved Mon, 29 Apr 2024 06:29:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=199338, Retrieved Mon, 29 Apr 2024 06:29:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Werkeloosheid ver...] [2012-11-15 17:53:40] [8ab8078357d7493428921287469fd527]
- R PD  [Multiple Regression] [] [2012-12-10 12:50:31] [8ab8078357d7493428921287469fd527]
- RMP       [Kendall tau Correlation Matrix] [] [2012-12-13 17:44:55] [eace0511beeaae09dbb51bfebd62c02b] [Current]
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Dataseries X:
277	5	82	98
232	4	84	100
256	3	85	103
242	4	87	100
302	4	91	100
282	4	94	101
288	5	96	100
321	6	97	100
316	5	99	100
396	5	100	102
362	4	102	103
392	3	104	106
414	2	105	108
417	2	107	105
476	2	108	110
488	1	109	110
489	0	110	110
467	0	110	113
460	1	109	111
482	0	109	111
510	1	109	111
493	0	110	111
476	0	110	107
448	1	110	110
410	2	110	104
466	2	107	105
417	3	108	104
387	3	109	106
370	1	109	105
344	2	110	104
396	3	109	104
349	2	110	104
326	4	110	103
303	4	110	104
300	3	110	98
329	3	110	100
304	3	110	103
286	3	109	100
281	5	110	100
377	5	110	101
344	4	112	100
369	3	112	100
390	2	112	100
406	-1	111	102
426	-4	112	103
467	-5	112	106
437	-4	113	108
410	-2	113	105
390	2	113	110
418	2	112	110
398	2	112	110
422	2	111	113
439	3	112	111
419	1	112	111
484	1	113	111
491	-1	113	111




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=199338&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=199338&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199338&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=pearson)
werkeloosheidbbpcpiprijsbouw
werkeloosheid1-0.6540.6290.804
bbp-0.6541-0.507-0.521
cpi0.629-0.50710.484
prijsbouw0.804-0.5210.4841

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & werkeloosheid & bbp & cpi & prijsbouw \tabularnewline
werkeloosheid & 1 & -0.654 & 0.629 & 0.804 \tabularnewline
bbp & -0.654 & 1 & -0.507 & -0.521 \tabularnewline
cpi & 0.629 & -0.507 & 1 & 0.484 \tabularnewline
prijsbouw & 0.804 & -0.521 & 0.484 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199338&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]werkeloosheid[/C][C]bbp[/C][C]cpi[/C][C]prijsbouw[/C][/ROW]
[ROW][C]werkeloosheid[/C][C]1[/C][C]-0.654[/C][C]0.629[/C][C]0.804[/C][/ROW]
[ROW][C]bbp[/C][C]-0.654[/C][C]1[/C][C]-0.507[/C][C]-0.521[/C][/ROW]
[ROW][C]cpi[/C][C]0.629[/C][C]-0.507[/C][C]1[/C][C]0.484[/C][/ROW]
[ROW][C]prijsbouw[/C][C]0.804[/C][C]-0.521[/C][C]0.484[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199338&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199338&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)
werkeloosheidbbpcpiprijsbouw
werkeloosheid1-0.6540.6290.804
bbp-0.6541-0.507-0.521
cpi0.629-0.50710.484
prijsbouw0.804-0.5210.4841







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
werkeloosheid;bbp-0.6543-0.7837-0.6015
p-value(0)(0)(0)
werkeloosheid;cpi0.62940.42470.3237
p-value(0)(0.0011)(8e-04)
werkeloosheid;prijsbouw0.80410.83670.6593
p-value(0)(0)(0)
bbp;cpi-0.5068-0.5584-0.4421
p-value(1e-04)(0)(0)
bbp;prijsbouw-0.5211-0.6937-0.5461
p-value(0)(0)(0)
cpi;prijsbouw0.48390.38350.2952
p-value(2e-04)(0.0035)(0.0034)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
werkeloosheid;bbp & -0.6543 & -0.7837 & -0.6015 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
werkeloosheid;cpi & 0.6294 & 0.4247 & 0.3237 \tabularnewline
p-value & (0) & (0.0011) & (8e-04) \tabularnewline
werkeloosheid;prijsbouw & 0.8041 & 0.8367 & 0.6593 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
bbp;cpi & -0.5068 & -0.5584 & -0.4421 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
bbp;prijsbouw & -0.5211 & -0.6937 & -0.5461 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
cpi;prijsbouw & 0.4839 & 0.3835 & 0.2952 \tabularnewline
p-value & (2e-04) & (0.0035) & (0.0034) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199338&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]werkeloosheid;bbp[/C][C]-0.6543[/C][C]-0.7837[/C][C]-0.6015[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]werkeloosheid;cpi[/C][C]0.6294[/C][C]0.4247[/C][C]0.3237[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0.0011)[/C][C](8e-04)[/C][/ROW]
[ROW][C]werkeloosheid;prijsbouw[/C][C]0.8041[/C][C]0.8367[/C][C]0.6593[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]bbp;cpi[/C][C]-0.5068[/C][C]-0.5584[/C][C]-0.4421[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]bbp;prijsbouw[/C][C]-0.5211[/C][C]-0.6937[/C][C]-0.5461[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]cpi;prijsbouw[/C][C]0.4839[/C][C]0.3835[/C][C]0.2952[/C][/ROW]
[ROW][C]p-value[/C][C](2e-04)[/C][C](0.0035)[/C][C](0.0034)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199338&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199338&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
werkeloosheid;bbp-0.6543-0.7837-0.6015
p-value(0)(0)(0)
werkeloosheid;cpi0.62940.42470.3237
p-value(0)(0.0011)(8e-04)
werkeloosheid;prijsbouw0.80410.83670.6593
p-value(0)(0)(0)
bbp;cpi-0.5068-0.5584-0.4421
p-value(1e-04)(0)(0)
bbp;prijsbouw-0.5211-0.6937-0.5461
p-value(0)(0)(0)
cpi;prijsbouw0.48390.38350.2952
p-value(2e-04)(0.0035)(0.0034)



Parameters (Session):
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')