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Data X:
210907 79 30 26 120982 58 28 31 176508 60 38 27 179321 108 30 0 123185 49 22 0 52746 0 26 0 385534 121 25 0 33170 1 18 0 101645 20 11 0 149061 43 26 27 165446 69 25 0 237213 78 38 23 173326 86 44 0 133131 44 30 27 258873 104 40 0 180083 63 34 0 324799 158 47 17 230964 102 30 25 236785 77 31 27 135473 82 23 0 202925 115 36 0 215147 101 36 0 344297 80 30 26 153935 50 25 0 132943 83 39 0 174724 123 34 23 174415 73 31 27 225548 81 31 0 223632 105 33 20 124817 47 25 25 221698 105 33 0 210767 94 35 0 170266 44 42 0 260561 114 43 0 84853 38 30 0 294424 107 33 24 101011 30 13 0 215641 71 32 0 325107 84 36 0 7176 0 0 0 167542 59 28 0 106408 33 14 23 96560 42 17 20 265769 96 32 25 269651 106 30 0 149112 56 35 26 175824 57 20 26 152871 59 28 20 111665 39 28 21 116408 34 39 0 362301 76 34 28 78800 20 26 0 183167 91 39 26 277965 115 39 0 150629 85 33 0 168809 76 28 0 24188 8 4 0 329267 79 39 23 65029 21 18 0 101097 30 14 0 218946 76 29 30 244052 101 44 12 341570 94 21 35 103597 27 16 25 233328 92 28 0 256462 123 35 0 206161 75 28 0 311473 128 38 0 235800 105 23 0 177939 55 36 0 207176 56 32 0 196553 41 29 25 174184 72 25 0 143246 67 27 18 187559 75 36 0 187681 114 28 0 119016 118 23 0 182192 77 40 0 73566 22 23 0 194979 66 40 0 167488 69 28 20 143756 105 34 24 275541 116 33 0 243199 88 28 0 182999 73 34 26 135649 99 30 0 152299 62 33 30 120221 53 22 0 346485 118 38 23 145790 30 26 0 193339 100 35 27 80953 49 8 0 122774 24 24 26 130585 67 29 13 112611 46 20 18 286468 57 29 27 241066 75 45 0 148446 135 37 0 204713 68 33 0 182079 124 33 31 140344 33 25 28 220516 98 32 28 243060 58 29 29 162765 68 28 29 182613 81 28 0 232138 131 31 0 265318 110 52 0 85574 37 21 23 310839 130 24 0 225060 93 41 28 232317 118 33 0 144966 39 32 0 43287 13 19 0 155754 74 20 0 164709 81 31 20 201940 109 31 0 235454 151 32 0 220801 51 18 24 99466 28 23 21 92661 40 17 30 133328 56 20 25 61361 27 12 22 125930 37 17 0 100750 83 30 23 224549 54 31 0 82316 27 10 0 102010 28 13 0 101523 59 22 26 243511 133 42 23 22938 12 1 0 41566 0 9 0 152474 106 32 32 61857 23 11 0 99923 44 25 26 132487 71 36 18 317394 116 31 0 21054 4 0 0 209641 62 24 0 22648 12 13 12 31414 18 8 0 46698 14 13 0 131698 60 19 34 91735 7 18 0 244749 98 33 33 184510 64 40 0 79863 29 22 0 128423 32 38 28 97839 25 24 26 38214 16 8 0 151101 48 35 0 272458 100 43 24 172494 46 43 24 108043 45 14 25 328107 129 41 23 250579 130 38 0 351067 136 45 24 158015 59 31 0 98866 25 13 0 85439 32 28 0 229242 63 31 22 351619 95 40 0 84207 14 30 0 120445 36 16 24 324598 113 37 30 131069 47 30 24 204271 92 35 0 165543 70 32 0 141722 19 27 0 116048 50 20 27 250047 41 18 28 299775 91 31 31 195838 111 31 19 173260 41 21 29 254488 120 39 21 104389 135 41 0 136084 27 13 0 199476 87 32 0 92499 25 18 29 224330 131 39 25 135781 45 14 17 74408 29 7 0 81240 58 17 0 14688 4 0 0 181633 47 30 29 271856 109 37 0 7199 7 0 0 46660 12 5 0 17547 0 1 0 133368 37 16 0 95227 37 32 0 152601 46 24 0 98146 15 17 27 79619 42 11 0 59194 7 24 17 139942 54 22 0 118612 54 12 27 72880 14 19 0 65475 16 13 25 99643 33 17 0 71965 32 15 0 77272 21 16 0 49289 15 24 0 135131 38 15 0 108446 22 17 14 89746 28 18 0 44296 10 20 0 77648 31 16 0 181528 32 16 27 134019 32 18 22 124064 43 22 0 92630 27 8 0 121848 37 17 27 52915 20 18 0 81872 32 16 0 58981 0 23 29 53515 5 22 22 60812 26 13 0 56375 10 13 26 65490 27 16 0 80949 11 16 0 76302 29 20 25 104011 25 22 22 98104 55 17 23 67989 23 18 0 30989 5 17 0 135458 43 12 0 73504 23 7 0 63123 34 17 21 61254 36 14 0 74914 35 23 0 31774 0 17 25 81437 37 14 31 87186 28 15 0 50090 16 17 0 65745 26 21 27 56653 38 18 28 158399 23 18 23 46455 22 17 0 73624 30 17 26 38395 16 16 0 91899 18 15 0 139526 28 21 0 52164 32 16 0 51567 21 14 0 70551 23 15 0 84856 29 17 0 102538 50 15 23 86678 12 15 13 85709 21 10 0 34662 18 6 0 150580 27 22 22 99611 41 21 25 19349 13 1 0 99373 12 18 16 86230 21 17 12 30837 8 4 0 31706 26 10 0 89806 27 16 0 62088 13 16 0 40151 16 9 0 27634 2 16 0 76990 42 17 0 37460 5 7 0 54157 37 15 20 49862 17 14 0 84337 38 14 0 64175 37 18 20 59382 29 12 23 119308 32 16 23 76702 35 21 0 103425 17 19 0 70344 20 16 0 43410 7 1 0 104838 46 16 0 62215 24 10 0 69304 40 19 0 53117 3 12 0 19764 10 2 0 86680 37 14 0 84105 17 17 24 77945 28 19 0 89113 19 14 0 91005 29 11 0 40248 8 4 0 64187 10 16 24 50857 15 20 0 56613 15 12 0 62792 28 15 0 72535 17 16 0
Names of X columns:
Time_in_rfc blogged_computations compendiums_reviewed TotaleTestScore
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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R Server
Big Analytics Cloud Computing Center
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