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Data X:
6 2 1 3 11 16 14 5 4 1 1 1 11 13 11 12 5 1 1 3 15 16 11 11 4 1 1 3 11 6 9 6 4 1 2 3 9 11 11 12 6 1 1 3 14 13 16 11 6 1 1 1 12 15 13 12 4 2 4 3 6 9 11 7 4 1 1 3 4 6 4 8 6 1 1 1 13 11 15 13 4 1 1 1 12 9 13 12 6 1 1 3 10 4 13 13 5 1 1 1 12 8 13 12 4 1 3 3 9 11 11 12 6 2 1 3 16 16 15 11 3 2 1 1 13 5 12 12 5 1 1 1 12 6 14 12 6 1 6 1 11 7 13 12 4 2 1 3 12 16 13 11 6 2 1 1 12 12 12 13 2 1 1 3 11 7 13 9 7 2 1 3 16 13 14 11 5 1 1 1 9 12 13 11 2 2 1 3 8 10 15 11 4 1 1 1 11 12 12 9 4 2 1 4 9 8 10 11 6 2 1 3 16 15 14 12 6 1 1 3 14 15 13 12 5 2 1 3 10 10 11 10 6 1 4 3 14 13 15 12 6 2 1 1 16 16 14 12 4 1 1 3 12 10 13 12 6 2 1 3 13 14 14 9 6 1 1 3 16 16 16 9 6 1 1 3 15 13 13 12 2 2 1 1 5 4 5 14 4 2 1 3 12 7 11 12 5 1 1 1 11 15 10 11 3 1 1 2 15 5 11 9 7 2 1 3 15 14 15 11 5 1 1 1 12 11 15 7 3 1 1 1 5 8 12 15 8 1 1 3 16 14 15 11 8 1 1 3 16 12 15 12 5 2 2 1 12 12 14 12 6 2 1 3 6 15 11 9 3 2 1 3 7 8 12 12 5 2 1 3 14 16 12 11 4 2 2 3 8 9 12 11 5 1 4 3 12 13 13 8 5 2 1 1 10 8 9 7 6 2 4 3 11 15 12 12 5 1 1 2 13 14 14 8 6 1 1 1 15 12 16 10 6 1 2 2 10 11 12 12 4 2 3 3 9 6 8 15 8 1 1 3 16 14 16 12 6 2 2 1 11 8 16 12 4 2 1 3 8 8 13 12 6 2 1 1 14 15 14 12 5 2 1 3 11 14 15 8 5 1 1 3 12 14 14 10 6 2 1 3 14 17 18 14 6 1 1 3 15 16 13 10 6 2 1 3 14 13 13 12 6 2 1 3 11 7 13 14 6 2 1 1 11 14 17 6 6 1 1 3 15 12 13 11 7 2 1 3 12 14 13 10 4 2 1 3 7 12 12 14 4 1 1 1 10 8 11 12 3 2 1 1 13 14 13 13 6 2 1 3 15 17 16 11 5 1 1 3 15 14 13 11 5 1 1 1 13 13 13 12 3 2 2 3 8 7 10 13 5 1 1 1 14 13 13 12 4 2 1 3 11 8 13 8 3 2 1 3 12 7 12 12 7 1 1 3 16 16 16 11 4 2 1 3 8 10 6 10 4 1 1 3 12 14 14 12 5 2 2 7 11 11 14 11 6 1 1 1 13 11 13 12 2 1 1 3 6 6 11 12 2 2 1 1 4 4 10 10 6 1 1 3 11 11 12 12 4 2 1 1 7 7 12 12 5 2 1 3 12 11 12 11 6 1 1 3 12 12 13 10 7 1 1 1 16 16 16 12 8 1 1 1 15 15 15 11 6 1 4 3 13 16 16 12 6 1 1 2 12 10 15 12 3 1 1 1 9 11 13 10 7 1 1 1 16 17 16 11 3 1 1 2 11 5 13 10 6 2 1 2 14 15 14 11 4 2 1 1 10 9 12 11 4 1 1 2 10 8 16 12 6 1 1 3 11 8 12 11 6 1 2 3 16 14 14 11 6 1 1 2 8 4 13 7 4 1 1 3 16 8 14 12 7 1 1 1 12 15 13 8 5 1 1 3 11 12 14 10 7 1 1 2 16 15 15 12 4 1 1 3 9 9 12 11 6 2 1 2 13 15 14 13 6 1 1 3 14 19 12 9 6 1 1 1 10 13 15 11 5 1 1 1 12 14 12 13 5 1 1 3 11 10 14 8 6 1 1 3 12 15 13 12 7 1 1 3 13 12 13 11 4 2 1 1 14 12 12 11 4 1 1 3 12 12 13 12 8 1 1 3 14 10 16 13 6 1 1 1 13 14 13 11 3 1 1 1 8 10 14 10 4 1 4 3 13 8 8 10 5 1 1 1 10 11 12 10 5 2 1 3 8 8 14 12 6 2 1 3 15 13 14 12 8 1 1 3 15 16 18 13 2 1 2 1 12 11 14 11 4 2 1 1 8 10 12 11 7 1 2 3 15 12 16 12 5 1 1 3 9 6 12 9 6 2 1 3 14 14 12 11 6 1 1 3 16 14 14 12 4 1 1 3 14 8 14 12 5 2 1 3 14 13 13 13 6 1 1 3 14 13 12 6 6 1 1 3 14 10 16 11 6 2 1 2 14 12 15 10 6 2 4 3 13 14 14 12 5 1 1 3 12 14 13 11 5 2 5 3 13 7 12 12 6 1 1 1 19 15 15 12 4 1 1 2 8 9 15 7 6 1 1 3 10 5 13 12 3 1 1 1 7 13 12 12 6 1 1 1 12 7 12 9 8 1 1 3 16 14 16 12 4 1 1 3 15 14 16 12
Names of X columns:
Celebrity Gender Raised Marital Popularity KnowingPeople Liked FindingFriends
Type of Correlation
kendall
pearson
spearman
kendall
Chart options
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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