| onderling effect 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, 27 Dec 2010 12:39:51 +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/27/t1293453447k6nnb950yq7t84i.htm/, Retrieved Mon, 27 Dec 2010 13:37:29 +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/27/t1293453447k6nnb950yq7t84i.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 « | 332 5140
369 4749
384 3635
373 4305
378 5805
426 4260
423 3869
397 7325
422 9280
409 6222
430 3272
412 7598
470 1345
491 1900
504 1480
484 1472
474 3823
508 4454
492 3357
452 5393
457 8329
457 4152
471 4042
451 7747
493 1451
514 911
522 -406
490 1387
484 2150
506 1577
501 2642
462 4273
465 8064
454 3243
464 1112
427 2280
460 505
473 744
465 -1369
422 -531
415 1041
413 2076
420 577
363 5080
376 6584
380 3761
384 294
346 5020
389 1141
407 3805
393 2127
346 2531
348 3682
353 3263
364 2798
305 5936
307 10568
312 5296
312 1870
286 4390
324 3707
336 5201
327 3748
302 5282
299 5349
311 6249
315 5517
264 8640
278 15767
278 8850
287 5582
279 6496
324 3255
354 6189
354 6452
360 5099
363 6833
385 7046
412 7739
370 10142
389 16054
395 7721
417 6182
404 6490
456 3704
478 6235
468 4655
437 5072
432 3640
441 5147
449 5703
386 11889
396 15603
394 9589 | | 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) | | werkloosheidstotaal | bevolkingstotaal | werkloosheidstotaal | 1 | -0.403 | bevolkingstotaal | -0.403 | 1 |
Correlations for all pairs of data series with p-values | pair | Pearson r | Spearman rho | Kendall tau | werkloosheidstotaal;bevolkingstotaal | -0.4028 | -0.4372 | -0.2905 | p-value | (1e-04) | (0) | (0) |
| | Charts produced by software: | | http://www.freestatistics.org/blog/date/2010/Dec/27/t1293453447k6nnb950yq7t84i/1qkzk1293453589.png (open in new window) | http://www.freestatistics.org/blog/date/2010/Dec/27/t1293453447k6nnb950yq7t84i/1qkzk1293453589.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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