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Data X:
41 38 7 53 145 56 39 32 5 86 101 56 30 35 5 66 98 54 31 33 5 67 132 89 34 37 8 76 60 40 35 29 6 78 38 25 39 31 5 53 144 92 34 36 6 80 5 18 36 35 5 74 28 63 37 38 4 76 84 44 38 31 6 79 79 33 36 34 5 54 127 84 38 35 5 67 78 88 39 38 6 54 60 55 33 37 7 87 131 60 32 33 6 58 84 66 36 32 7 75 133 154 38 38 6 88 150 53 39 38 8 64 91 119 32 32 7 57 132 41 32 33 5 66 136 61 31 31 5 68 124 58 39 38 7 54 118 75 37 39 7 56 70 33 39 32 5 86 107 40 41 32 4 80 119 92 36 35 10 76 89 100 33 37 6 69 112 112 33 33 5 78 108 73 34 33 5 67 52 40 31 28 5 80 112 45 27 32 5 54 116 60 37 31 6 71 123 62 34 37 5 84 125 75 34 30 5 74 27 31 32 33 5 71 162 77 29 31 5 63 32 34 36 33 5 71 64 46 29 31 5 76 92 99 35 33 5 69 0 17 37 32 5 74 83 66 34 33 7 75 41 30 38 32 5 54 47 76 35 33 6 52 120 146 38 28 7 69 105 67 37 35 7 68 79 56 38 39 5 65 65 107 33 34 5 75 70 58 36 38 4 74 55 34 38 32 5 75 39 61 32 38 4 72 67 119 32 30 5 67 21 42 32 33 5 63 127 66 34 38 7 62 152 89 32 32 5 63 113 44 37 32 5 76 99 66 39 34 6 74 7 24 29 34 4 67 141 259 37 36 6 73 21 17 35 34 6 70 35 64 30 28 5 53 109 41 38 34 7 77 133 68 34 35 6 77 123 168 31 35 8 52 26 43 34 31 7 54 230 132 35 37 5 80 166 105 36 35 6 66 68 71 30 27 6 73 147 112 39 40 5 63 179 94 35 37 5 69 61 82 38 36 5 67 101 70 31 38 5 54 108 57 34 39 4 81 90 53 38 41 6 69 114 103 34 27 6 84 103 121 39 30 6 80 142 62 37 37 6 70 79 52 34 31 7 69 88 52 28 31 5 77 25 32 37 27 7 54 83 62 33 36 6 79 113 45 37 38 5 30 118 46 35 37 5 71 110 63 37 33 4 73 129 75 32 34 8 72 51 88 33 31 8 77 93 46 38 39 5 75 76 53 33 34 5 69 49 37 29 32 6 54 118 90 33 33 4 70 38 63 31 36 5 73 141 78 36 32 5 54 58 25 35 41 5 77 27 45 32 28 5 82 91 46 29 30 6 80 48 41 39 36 6 80 63 144 37 35 5 69 56 82 35 31 6 78 144 91 37 34 5 81 73 71 32 36 7 76 168 63 38 36 5 76 64 53 37 35 6 73 97 62 36 37 6 85 117 63 32 28 6 66 100 32 33 39 4 79 149 39 40 32 5 68 187 62 38 35 5 76 127 117 41 39 7 71 37 34 36 35 6 54 245 92 43 42 9 46 87 93 30 34 6 82 177 54 31 33 6 74 49 144 32 41 5 88 49 14 32 33 6 38 73 61 37 34 5 76 177 109 37 32 8 86 94 38 33 40 7 54 117 73 34 40 5 70 60 75 33 35 7 69 55 50 38 36 6 90 39 61 33 37 6 54 64 55 31 27 9 76 26 77 38 39 7 89 64 75 37 38 6 76 58 72 33 31 5 73 95 50 31 33 5 79 25 32 39 32 6 90 26 53 44 39 6 74 76 42 33 36 7 81 129 71 35 33 5 72 11 10 32 33 5 71 2 35 28 32 5 66 101 65 40 37 6 77 28 25 27 30 4 65 36 66 37 38 5 74 89 41 32 29 7 82 193 86 28 22 5 54 4 16 34 35 7 63 84 42 30 35 7 54 23 19 35 34 6 64 39 19 31 35 5 69 14 45 32 34 8 54 78 65 30 34 5 84 14 35 30 35 5 86 101 95 31 23 5 77 82 49 40 31 6 89 24 37 32 27 4 76 36 64 36 36 5 60 75 38 32 31 5 75 16 34 35 32 7 73 55 32 38 39 6 85 131 65 42 37 7 79 131 52 34 38 10 71 39 62 35 39 6 72 144 65 35 34 8 69 139 83 33 31 4 78 211 95 36 32 5 54 78 29 32 37 6 69 50 18 33 36 7 81 39 33 34 32 7 84 90 247 32 35 6 84 166 139 34 36 6 69 12 29
Names of X columns:
Connected Separate age beloning totblogs Login
Type of Correlation
6
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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