| Paper Pearson Correlatie | *The author of this computation has been verified* | R Software Module: Patrick.Wessa/rwasp_pairs.wasp (opens new window with default values) | Title produced by software: Kendall tau Correlation Matrix | Date of computation: Sat, 18 Dec 2010 17:39:49 +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/18/t1292693897yp2qbcd4n4fj1ni.htm/, Retrieved Sat, 18 Dec 2010 18:38:19 +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/18/t1292693897yp2qbcd4n4fj1ni.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 « | 97,06 21.454 631.923 130.678
97,73 23.899 654.294 120.877
98 24.939 671.833 137.114
97,76 23.580 586.840 134.406
97,48 24.562 600.969 120.262
97,77 24.696 625.568 130.846
97,96 23.785 558.110 120.343
98,22 23.812 630.577 98.881
98,51 21.917 628.654 115.678
98,19 19.713 603.184 120.796
98,37 19.282 656.255 94.261
98,31 18.788 600.730 89.151
98,6 21.453 670.326 119.880
98,96 24.482 678.423 131.468
99,11 27.474 641.502 155.089
99,64 27.264 625.311 149.581
100,02 27.349 628.177 122.788
99,98 30.632 589.767 143.900
100,32 29.429 582.471 112.115
100,44 30.084 636.248 109.600
100,51 26.290 599.885 117.446
101 24.379 621.694 118.456
100,88 23.335 637.406 101.901
100,55 21.346 595.994 89.940
100,82 21.106 696.308 129.143
101,5 24.514 674.201 126.102
102,15 28.353 648.861 143.048
102,39 30.805 649.605 142.258
102,54 31.348 672.392 131.011
102,85 34.556 598.396 146.471
103,47 33.855 613.177 114.073
103,56 34.787 638.104 114.642
103,69 32.529 615.632 118.226
103,49 29.998 634.465 111.338
etc... | | 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!
Correlations for all pairs of data series (method=pearson) | | CPI | vacatures | werklozen | inschrijvingen | CPI | 1 | 0.8 | 0.249 | 0.029 | vacatures | 0.8 | 1 | -0.099 | 0.242 | werklozen | 0.249 | -0.099 | 1 | 0.12 | inschrijvingen | 0.029 | 0.242 | 0.12 | 1 |
Correlations for all pairs of data series with p-values | pair | Pearson r | Spearman rho | Kendall tau | CPI;vacatures | 0.8003 | 0.8168 | 0.6207 | p-value | (0) | (0) | (0) | CPI;werklozen | 0.2488 | 0.138 | 0.0887 | p-value | (0.0225) | (0.2107) | (0.2326) | CPI;inschrijvingen | 0.0293 | 0.0399 | 0.0192 | p-value | (0.791) | (0.7189) | (0.7958) | vacatures;werklozen | -0.0991 | -0.1419 | -0.0912 | p-value | (0.3697) | (0.1974) | (0.2193) | vacatures;inschrijvingen | 0.2417 | 0.2591 | 0.1756 | p-value | (0.0267) | (0.0175) | (0.0181) | werklozen;inschrijvingen | 0.1197 | 0.094 | 0.062 | p-value | (0.2781) | (0.3944) | (0.404) |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Dec/18/t1292693897yp2qbcd4n4fj1ni/127va1292693985.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/18/t1292693897yp2qbcd4n4fj1ni/127va1292693985.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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