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Data X:
1 41 25 15 9 3 1 38 25 15 9 4 1 37 19 14 9 4 1 42 18 10 8 4 1 40 23 18 15 3 1 43 25 14 9 4 1 40 23 11 11 4 1 45 30 17 6 5 1 45 32 21 10 4 1 44 25 7 11 4 1 42 26 18 16 4 1 32 25 13 11 5 1 32 25 13 11 5 1 41 35 18 7 4 1 38 20 12 10 4 1 38 21 9 9 4 1 24 23 11 15 3 1 46 17 11 6 5 1 42 27 16 12 4 1 46 25 12 10 4 1 43 18 14 14 5 1 38 22 13 9 4 1 39 23 17 14 4 1 40 25 13 14 3 1 37 19 13 9 2 1 41 20 12 8 4 1 46 26 12 10 4 1 26 16 12 9 3 1 37 22 9 9 3 1 39 25 17 9 4 1 44 29 18 11 5 1 38 22 12 10 2 1 38 32 12 8 0 1 38 23 9 14 4 1 33 18 13 10 3 1 43 26 11 14 4 1 41 14 13 15 2 1 49 20 6 8 4 1 45 25 11 10 5 1 31 21 18 13 3 1 30 21 18 13 3 1 38 23 15 10 4 1 39 24 11 11 4 1 40 21 14 10 4 1 36 17 12 16 2 1 49 29 8 6 5 1 41 25 11 11 4 1 42 25 17 14 3 1 41 25 16 9 5 1 43 21 13 11 4 1 46 23 15 8 3 1 41 25 16 8 5 1 39 25 7 11 4 1 42 24 16 16 4 1 35 21 13 12 5 1 36 22 15 14 3 1 48 14 12 8 4 1 41 20 12 10 4 1 47 21 24 14 3 1 41 22 15 10 3 1 31 19 8 5 5 1 36 28 18 12 4 1 46 25 17 9 4 1 44 21 15 8 4 1 43 27 11 16 2 1 40 19 12 13 5 1 40 20 14 8 3 1 46 17 11 14 3 1 39 22 10 8 4 1 44 26 11 7 4 1 38 17 12 11 2 1 39 15 6 6 4 1 41 27 15 9 5 1 39 25 14 14 3 1 40 19 16 12 4 1 44 18 16 8 4 1 42 15 11 8 4 1 46 29 15 12 5 1 44 24 12 13 4 1 37 24 13 11 4 1 39 22 14 12 2 1 40 22 12 13 3 1 42 25 17 14 3 1 37 21 11 9 3 1 33 21 13 8 2 1 35 18 9 8 4 1 42 10 12 9 2 0 36 18 10 14 2 0 44 23 9 14 4 0 45 24 11 14 4 0 47 32 9 14 4 0 40 24 16 9 4 0 49 17 14 14 4 0 48 30 24 8 5 0 29 25 9 10 4 0 45 23 11 11 5 0 29 19 14 13 2 0 41 21 12 9 4 0 34 24 8 13 2 0 38 23 5 16 2 0 37 19 10 12 3 0 48 27 15 4 5 0 39 26 10 10 4 0 34 26 18 14 4 0 35 16 12 10 2 0 41 27 13 9 3 0 43 14 11 8 4 0 41 18 12 9 3 0 39 21 7 15 2 0 36 22 17 8 4 0 32 31 9 11 4 0 46 23 10 12 4 0 42 24 12 9 4 0 42 19 10 13 2 0 45 22 7 7 3 0 39 24 13 10 4 0 45 28 9 11 4 0 48 24 9 8 5 0 28 15 12 14 4 0 35 21 11 9 2 0 38 21 14 16 4 0 42 13 8 11 4 0 36 20 11 12 3 0 37 22 11 8 4 0 38 19 12 7 3 0 43 26 20 13 4 0 35 19 8 20 2 0 36 20 11 11 4 0 33 14 15 10 2 0 39 17 12 16 4 0 32 29 12 12 4 0 45 21 12 8 3 0 35 19 11 10 4 0 38 17 9 11 3 0 36 19 8 14 3 0 42 17 12 10 3 0 41 19 13 12 4 0 47 21 17 11 3 0 35 20 16 11 3 0 43 20 11 14 3 0 40 29 9 16 4 0 46 23 11 9 4 0 44 23 11 11 5 0 35 19 13 9 3 0 29 22 15 14 4
Names of X columns:
Gender StudyForCareer PersonalStandards ParentalExpectation Doubts LeaderPreference
Type of Correlation
pearson
spearman
kendall
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Title:
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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