| 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: Sun, 19 Dec 2010 10:15:21 +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/19/t1292753663ue8ki5674xqc9pg.htm/, Retrieved Sun, 19 Dec 2010 11:14:24 +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/19/t1292753663ue8ki5674xqc9pg.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 « | 62.027 63.152
56.493 60.106
65.566 72.616
62.653 73.159
53.470 68.848
59.600 77.056
42.542 62.246
42.018 60.777
44.038 64.513
44.988 58.353
43.309 56.511
26.843 44.554
69.770 71.414
64.886 65.719
79.354 80.997
63.025 69.826
54.003 65.386
55.926 75.589
45.629 65.520
40.361 59.003
43.039 63.961
44.570 59.716
43.269 57.520
25.563 42.886
68.707 69.805
60.223 64.656
74.283 80.353
61.232 71.321
61.531 76.577
65.305 81.580
51.699 71.127
44.599 63.478
35.221 48.152
55.066 69.236
45.335 57.038
28.702 43.621
69.517 69.551
69.240 72.009
71.525 72.140
77.740 81.519
62.107 73.310
65.450 80.406
51.493 70.697
43.067 59.328
49.172 68.281
54.483 70.041
38.158 51.244
27.898 46.538
58.648 61.443
56.000 62.256
62.381 73.117
59.849 74.155
48.345 65.191
55.376 77.889
45.400 68.688
38.389 59.983
44.098 65.470
48.290 65.089
41.267 54.795
31.238 47.123 | | 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) | | inschrijvingen | aanvragen | inschrijvingen | 1 | 0.864 | aanvragen | 0.864 | 1 |
Correlations for all pairs of data series with p-values | pair | Pearson r | Spearman rho | Kendall tau | inschrijvingen;aanvragen | 0.8638 | 0.8377 | 0.6497 | p-value | (0) | (0) | (0) |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Dec/19/t1292753663ue8ki5674xqc9pg/16s2i1292753719.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/19/t1292753663ue8ki5674xqc9pg/16s2i1292753719.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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