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Data X:
0 210907 146283 0 120982 98364 1 176508 86146 0 385534 195663 0 149061 95757 1 165446 85584 1 237213 143983 1 133131 59238 1 324799 151511 0 230964 136368 1 236785 112642 0 135473 94728 0 215147 121527 1 344297 127766 0 153935 98958 1 174724 85646 1 174415 98579 0 225548 130767 1 223632 131741 1 124817 53907 0 210767 146761 0 170266 82036 0 294424 171975 1 325107 159676 1 7176 1929 0 106408 58391 0 96560 31580 1 265769 136815 0 149112 69107 1 175824 50495 0 152871 108016 1 111665 46341 1 362301 79336 0 183167 93176 1 168809 127969 1 24188 15049 1 329267 155135 1 218946 102996 1 244052 160604 1 341570 158051 0 103597 44547 1 256462 174141 0 235800 184301 1 196553 129847 1 174184 117286 0 143246 71180 1 187559 109377 0 187681 85298 1 73566 23824 0 167488 82981 0 143756 73815 0 243199 132190 1 182999 128754 1 152299 67808 1 346485 131722 1 193339 106175 1 122774 25157 0 130585 76669 1 112611 57283 1 286468 105805 1 148446 72413 0 182079 96971 1 140344 71299 1 220516 77494 1 243060 120336 1 162765 93913 1 232138 181248 0 265318 146123 1 85574 32036 0 310839 186646 0 225060 102255 1 232317 168237 0 144966 64219 1 164709 115338 1 220801 84845 0 99466 153197 1 92661 29877 1 133328 63506 1 61361 22445 1 100750 68370 0 102010 42071 1 101523 50517 1 243511 103950 1 22938 5841 1 152474 84396 0 99923 35753 1 132487 55515 0 317394 209056 1 21054 6622 1 209641 115814 0 22648 11609 0 31414 13155 1 46698 18274 1 131698 72875 1 244749 142775 0 128423 20112 0 97839 61023 1 272458 132432 1 108043 45109 0 328107 170875 1 351067 214921 0 158015 100226 1 229242 78876 1 84207 6940 0 120445 49025 0 324598 122037 0 131069 53782 0 204271 127748 0 116048 77395 1 250047 89324 1 299775 103300 0 195838 112283 1 173260 10901 0 254488 120691 1 92499 25899 0 224330 139296 0 135781 52678 1 74408 23853 0 81240 17306 1 181633 89455 1 271856 147866 1 95227 14336 0 98146 30059 0 59194 22097 1 139942 96841 0 118612 41907 1 72880 27080 1 65475 35885 1 71965 28313 0 135131 36134 0 108446 55764 1 181528 66956 1 134019 47487 0 121848 35619 0 81872 45608 0 58981 7721 0 53515 20634 1 56375 31931 1 65490 37754 1 76302 40557 1 104011 94238 0 98104 44197 1 30989 4103 0 135458 44144 1 63123 27640 1 74914 28990 0 31774 4694 1 81437 42648 1 65745 25836 1 56653 22779 1 158399 40820 1 73624 32378 1 91899 39613 1 139526 60865 0 51567 20107 0 102538 48231 1 86678 39725 1 150580 62991 1 99611 49363 0 99373 24552 0 86230 31493 0 30837 3439 1 31706 19555 1 89806 21228 0 64175 28893 0 59382 21425 0 119308 50276 0 76702 37643 1 19764 9927 0 84105 27184 1 64187 18475 1 72535 35873
Names of X columns:
Gender Total_Time_spent_in_RFC_in_seconds Compendium_Writing:total_number_of_seconds
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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Big Analytics Cloud Computing Center
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