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workshop 10 pearson

*The author of this computation has been verified*
R Software Module: /rwasp_pairs.wasp (opens new window with default values)
Title produced by software: Kendall tau Correlation Matrix
Date of computation: Mon, 13 Dec 2010 10:41:59 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/13/t1292236957zc87jac16d2bjwb.htm/, Retrieved Mon, 13 Dec 2010 11:42:37 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/13/t1292236957zc87jac16d2bjwb.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
216.234 627 213.586 696 209.465 825 204.045 677 200.237 656 203.666 785 241.476 412 260.307 352 243.324 839 244.460 729 233.575 696 237.217 641 235.243 695 230.354 638 227.184 762 221.678 635 217.142 721 219.452 854 256.446 418 265.845 367 248.624 824 241.114 687 229.245 601 231.805 676 219.277 740 219.313 691 212.610 683 214.771 594 211.142 729 211.457 731 240.048 386 240.636 331 230.580 707 208.795 715 197.922 657 194.596 653 194.581 642 185.686 643 178.106 718 172.608 654 167.302 632 168.053 731 202.300 392 202.388 344 182.516 792 173.476 852 166.444 649 171.297 629 169.701 685 164.182 617 161.914 715 159.612 715 151.001 629 158.114 916 186.530 531 187.069 357 174.330 917 169.362 828 166.827 708 178.037 858 186.413 775 189.226 785 191.563 1006 188.906 789 186.005 734 195.309 906 223.532 532 226.899 387 214.126 991 206.903 841 204.442 892 220.375 782
 
Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk


Correlations for all pairs of data series (method=pearson)
werklozenfaillissementen
werklozen1-0.335
faillissementen-0.3351


Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
werklozen;faillissementen-0.3351-0.2352-0.1583
p-value(0.004)(0.0467)(0.0495)
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/13/t1292236957zc87jac16d2bjwb/173e91292236916.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/13/t1292236957zc87jac16d2bjwb/173e91292236916.ps (open in new window)


 
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')
 





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