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Data X:
13 53 41 7 2 16 86 39 5 2 19 66 30 5 2 15 67 31 5 1 14 76 34 8 2 13 78 35 6 2 19 53 39 5 2 15 80 34 6 2 14 74 36 5 2 15 76 37 4 2 16 79 38 6 1 16 54 36 5 2 16 67 38 5 1 16 54 39 6 2 17 87 33 7 2 15 58 32 6 1 15 75 36 7 1 20 88 38 6 2 18 64 39 8 1 16 57 32 7 2 16 66 32 5 1 16 68 31 5 2 19 54 39 7 2 16 56 37 7 2 17 86 39 5 1 17 80 41 4 2 16 76 36 10 1 15 69 33 6 2 16 78 33 5 2 14 67 34 5 1 15 80 31 5 2 12 54 27 5 1 14 71 37 6 2 16 84 34 5 2 14 74 34 5 1 7 71 32 5 1 10 63 29 5 1 14 71 36 5 1 16 76 29 5 2 16 69 35 5 1 16 74 37 5 1 14 75 34 7 2 20 54 38 5 1 14 52 35 6 1 14 69 38 7 2 11 68 37 7 2 14 65 38 5 2 15 75 33 5 2 16 74 36 4 2 14 75 38 5 1 16 72 32 4 2 14 67 32 5 1 12 63 32 5 1 16 62 34 7 2 9 63 32 5 1 14 76 37 5 2 16 74 39 6 2 16 67 29 4 2 15 73 37 6 1 16 70 35 6 2 12 53 30 5 1 16 77 38 7 1 16 77 34 6 2 14 52 31 8 2 16 54 34 7 2 17 80 35 5 1 18 66 36 6 2 18 73 30 6 1 12 63 39 5 2 16 69 35 5 1 10 67 38 5 1 14 54 31 5 2 18 81 34 4 2 18 69 38 6 1 16 84 34 6 1 17 80 39 6 2 16 70 37 6 2 16 69 34 7 2 13 77 28 5 1 16 54 37 7 1 16 79 33 6 1 20 30 37 5 1 16 71 35 5 2 15 73 37 4 1 15 72 32 8 2 16 77 33 8 2 14 75 38 5 1 16 69 33 5 2 16 54 29 6 2 15 70 33 4 2 12 73 31 5 2 17 54 36 5 2 16 77 35 5 2 15 82 32 5 2 13 80 29 6 2 16 80 39 6 2 16 69 37 5 2 16 78 35 6 2 16 81 37 5 1 14 76 32 7 1 16 76 38 5 2 16 73 37 6 1 20 85 36 6 2 15 66 32 6 1 16 79 33 4 2 13 68 40 5 1 17 76 38 5 2 16 71 41 7 1 16 54 36 6 1 12 46 43 9 2 16 82 30 6 2 16 74 31 6 2 17 88 32 5 2 13 38 32 6 1 12 76 37 5 2 18 86 37 8 1 14 54 33 7 2 14 70 34 5 2 13 69 33 7 2 16 90 38 6 2 13 54 33 6 2 16 76 31 9 2 13 89 38 7 2 16 76 37 6 2 15 73 33 5 2 16 79 31 5 2 15 90 39 6 1 17 74 44 6 2 15 81 33 7 2 12 72 35 5 2 16 71 32 5 1 10 66 28 5 1 16 77 40 6 2 12 65 27 4 1 14 74 37 5 1 15 82 32 7 2 13 54 28 5 1 15 63 34 7 1 11 54 30 7 2 12 64 35 6 2 8 69 31 5 1 16 54 32 8 2 15 84 30 5 1 17 86 30 5 2 16 77 31 5 1 10 89 40 6 2 18 76 32 4 2 13 60 36 5 1 16 75 32 5 1 13 73 35 7 1 10 85 38 6 2 15 79 42 7 2 16 71 34 10 1 16 72 35 6 2 14 69 35 8 2 10 78 33 4 2 17 54 36 5 2 13 69 32 6 2 15 81 33 7 2 16 84 34 7 2 12 84 32 6 2 13 69 34 6 2
Names of X columns:
Learning Belonging Connected Age Gender
Type of Correlation
kendall
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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