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Data X:
162.5 98.1 120.3 58.8 237.7 93.8 405.1 141.3 53.2 122.4 113.2 80.1 323.2 111.4 137.7 168 81.2 136.7 74 109.6 117.6 85.7 128.1 129.7 108.5 238.5 148.8 60.3 164.4 55.5 100.4 70.9 132.5 104.8 88.8 328.6 136.9 157.9 75.7 233.7 101.2 131.8 138.7 154.1 75.2 95.3 68.7 43.5 68.8 217.7 62.4 121 118.3 132.2 213.7 113.1 72.8 127.7 203.7 45 136.5 58.9 43.8 155 46.4 77.4 79.3 51.5 74.2 60.3 55.4 80.5 199.3 214.1 174 50.9 164.7 57.2 55.9 115.1 173.3 165.3 93.5 144 75 232.9 76.5 151.4 68.8 82.4 349.4 399.8 124.3 66.2 150.8 72.7 152.4 99.6 109.6 184.1
Data Y:
31.35 16.55 10.27 476.8 161.7 26.75 33.47 20.68 1.26 470.4 28 184.6 51.62 0.76 14.64 97.2 2425 3.65 44.88 174.6 27.98 1.17 114.8 20.65 0.94 36.37 24.27 1542 41.77 7.9 6.56 49.72 0.72 16.8 5.1 19.85 5.74 4.49 9.92 41.22 41.84 14.25 307.2 12.39 206.5 7.83 1.86 1340 2434 91.2 34.82 2.35 2.62 9.72 7.26 712 497 12.15 118.7 200.3 884 50.3 210.6 171.4 246.8 22.45 204.7 268.3 0.22 255 4.53 15650 85.11 130.6 255 1.42 54.05 499.89 309.2 595 21.42 64.7 26.75 193.56 3367 71.04 166.9 2.79 26.51 267.92 6.19 180.2 44.7 1770 894.9 391.5 18.18 3.11 174.6 0.05
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R Code
k <- cor.test(x,y,method='spearman') bitmap(file='test1.png') plot(x,y,main='Scatterplot',xlab=xlab,ylab=ylab) grid() dev.off() bitmap(file='test2.png') plot(rank(x),rank(y),main='Scatterplot of Ranks',xlab=xlab,ylab=ylab) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Spearman Rank Correlation',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'rho',header=TRUE) a<-table.element(a,k$estimate) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'2-sided p-value',header=TRUE) a<-table.element(a,k$p.value) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'S',header=TRUE) a<-table.element(a,k$statistic) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Big Analytics Cloud Computing Center
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