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Data X:
0 0 173326 146283 0 0 133131 98364 0 0 258873 86146 0 0 180083 96933 0 0 324799 79234 0 0 230964 42551 0 0 236785 195663 0 0 135473 6853 0 0 202925 21529 0 0 215147 95757 0 0 344297 85584 0 0 153935 143983 0 0 132943 75851 0 0 174724 59238 0 0 174415 93163 0 0 225548 96037 0 0 223632 151511 0 0 124817 136368 0 0 221698 112642 0 0 210767 94728 0 0 170266 105499 0 0 260561 121527 0 0 84853 127766 0 0 294424 98958 0 0 101011 77900 0 0 215641 85646 0 0 325107 98579 0 0 7176 130767 0 0 167542 131741 0 1 106408 53907 0 1 96560 178812 0 1 265769 146761 0 1 269651 82036 0 1 149112 163253 0 1 175824 27032 0 1 152871 171975 0 1 111665 65990 0 1 116408 86572 0 1 362301 159676 0 1 78800 1929 0 1 183167 85371 0 1 277965 58391 0 1 150629 31580 0 1 168809 136815 0 1 24188 120642 0 1 329267 69107 0 1 65029 50495 0 1 101097 108016 0 1 218946 46341 0 1 244052 78348 0 1 341570 79336 0 1 103597 56968 0 1 233328 93176 1 0 256462 161632 1 0 206161 87850 1 0 311473 127969 1 0 235800 15049 1 0 177939 155135 1 0 207176 25109 1 0 196553 45824 1 0 174184 102996 1 0 143246 160604 1 0 187559 158051 1 0 187681 44547 1 0 119016 162647 1 0 182192 174141 1 0 73566 60622 1 0 194979 179566 1 0 167488 184301 1 0 143756 75661 1 0 275541 96144 1 0 243199 129847 1 0 182999 117286 1 0 135649 71180 1 0 152299 109377 1 0 120221 85298 1 1 346485 73631 1 1 145790 86767 1 1 193339 23824 1 1 80953 93487 1 1 122774 82981 1 1 130585 73815 1 1 112611 94552 1 1 286468 132190 1 1 241066 128754 1 1 148446 66363 1 1 204713 67808 1 1 182079 61724 1 1 140344 131722 1 1 220516 68580 1 1 243060 106175 1 1 162765 55792 1 1 182613 25157 1 1 232138 76669 1 1 265318 57283 1 1 85574 105805 1 1 310839 129484 1 1 225060 72413 1 1 232317 87831 1 1 144966 96971 1 1 43287 71299 1 1 155754 77494 1 1 164709 120336 1 1 201940 93913 1 1 235454 136048 1 1 220801 181248
Names of X columns:
POP Gender Time_RFC_sec Compendium_writing_time_sec
Type of Correlation
pearson
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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Big Analytics Cloud Computing Center
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