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Data X:
0 24 14 11 12 24 26 0 25 11 7 8 25 23 0 17 6 17 8 30 25 1 18 12 10 8 19 23 1 18 8 12 9 22 19 1 16 10 12 7 22 29 1 20 10 11 4 25 25 1 16 11 11 11 23 21 1 18 16 12 7 17 22 1 17 11 13 7 21 25 0 23 13 14 12 19 24 0 30 12 16 10 19 18 1 23 8 11 10 15 22 1 18 12 10 8 16 15 1 15 11 11 8 23 22 1 12 4 15 4 27 28 0 21 9 9 9 22 20 1 15 8 11 8 14 12 1 20 8 17 7 22 24 0 31 14 17 11 23 20 0 27 15 11 9 23 21 1 34 16 18 11 21 20 1 21 9 14 13 19 21 1 31 14 10 8 18 23 1 19 11 11 8 20 28 0 16 8 15 9 23 24 1 20 9 15 6 25 24 1 21 9 13 9 19 24 1 22 9 16 9 24 23 1 17 9 13 6 22 23 1 24 10 9 6 25 29 0 25 16 18 16 26 24 0 26 11 18 5 29 18 1 25 8 12 7 32 25 1 17 9 17 9 25 21 1 32 16 9 6 29 26 1 33 11 9 6 28 22 1 13 16 12 5 17 22 1 32 12 18 12 28 22 1 25 12 12 7 29 23 1 29 14 18 10 26 30 1 22 9 14 9 25 23 1 18 10 15 8 14 17 1 17 9 16 5 25 23 0 20 10 10 8 26 23 1 15 12 11 8 20 25 1 20 14 14 10 18 24 1 33 14 9 6 32 24 0 29 10 12 8 25 23 1 23 14 17 7 25 21 0 26 16 5 4 23 24 1 18 9 12 8 21 24 0 20 10 12 8 20 28 1 11 6 6 4 15 16 1 28 8 24 20 30 20 1 26 13 12 8 24 29 0 22 10 12 8 26 27 1 17 8 14 6 24 22 0 12 7 7 4 22 28 1 14 15 13 8 14 16 1 17 9 12 9 24 25 1 21 10 13 6 24 24 1 19 12 14 7 24 28 1 18 13 8 9 24 24 0 10 10 11 5 19 23 0 29 11 9 5 31 30 1 31 8 11 8 22 24 0 19 9 13 8 27 21 1 9 13 10 6 19 25 1 20 11 11 8 25 25 1 28 8 12 7 20 22 0 19 9 9 7 21 23 0 30 9 15 9 27 26 0 29 15 18 11 23 23 0 26 9 15 6 25 25 0 23 10 12 8 20 21 1 13 14 13 6 21 25 1 21 12 14 9 22 24 1 19 12 10 8 23 29 1 28 11 13 6 25 22 1 23 14 13 10 25 27 1 18 6 11 8 17 26 0 21 12 13 8 19 22 1 20 8 16 10 25 24 1 23 14 8 5 19 27 1 21 11 16 7 20 24 1 21 10 11 5 26 24 1 15 14 9 8 23 29 1 28 12 16 14 27 22 1 19 10 12 7 17 21 1 26 14 14 8 17 24 1 10 5 8 6 19 24 0 16 11 9 5 17 23 1 22 10 15 6 22 20 1 19 9 11 10 21 27 1 31 10 21 12 32 26 0 31 16 14 9 21 25 1 29 13 18 12 21 21 0 19 9 12 7 18 21 1 22 10 13 8 18 19 1 23 10 15 10 23 21 0 15 7 12 6 19 21 0 20 9 19 10 20 16 1 18 8 15 10 21 22 1 23 14 11 10 20 29 1 25 14 11 5 17 15 1 21 8 10 7 18 17 1 24 9 13 10 19 15 1 25 14 15 11 22 21 1 17 14 12 6 15 21 1 13 8 12 7 14 19 1 28 8 16 12 18 24 0 21 8 9 11 24 20 1 25 7 18 11 35 17 0 9 6 8 11 29 23 1 16 8 13 5 21 24 1 19 6 17 8 25 14 1 17 11 9 6 20 19 1 25 14 15 9 22 24 1 20 11 8 4 13 13 1 29 11 7 4 26 22 1 14 11 12 7 17 16 1 22 14 14 11 25 19 1 15 8 6 6 20 25 0 19 20 8 7 19 25 1 20 11 17 8 21 23 0 15 8 10 4 22 24 1 20 11 11 8 24 26 1 18 10 14 9 21 26 1 33 14 11 8 26 25 1 22 11 13 11 24 18 1 16 9 12 8 16 21 1 17 9 11 5 23 26 1 16 8 9 4 18 23 0 21 10 12 8 16 23 0 26 13 20 10 26 22 1 18 13 12 6 19 20 1 18 12 13 9 21 13 1 17 8 12 9 21 24 1 22 13 12 13 22 15 1 30 14 9 9 23 14 0 30 12 15 10 29 22 1 24 14 24 20 21 10 1 21 15 7 5 21 24 1 21 13 17 11 23 22 1 29 16 11 6 27 24 1 31 9 17 9 25 19 1 20 9 11 7 21 20 0 16 9 12 9 10 13 0 22 8 14 10 20 20 1 20 7 11 9 26 22 1 28 16 16 8 24 24 1 38 11 21 7 29 29 0 22 9 14 6 19 12 1 20 11 20 13 24 20 0 17 9 13 6 19 21 1 28 14 11 8 24 24 1 22 13 15 10 22 22 0 31 16 19 16 17 20
Names of X columns:
Gender ConcMistakes DoubtsActions ParExp ParCrit PersonalStandards Organisation
Type of Correlation


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R Code
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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Raw Output	view raw output of R engine
Computing time	0 seconds
R Server	Big Analytics Cloud Computing Center