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