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Data X:
100.7 97.9 96.5 96.6 96.6 95.5 91.8 89.3 87 85.9 88 87.9 89.2 90.9 91.6 90.2 89.1 87.5 86.3 86 84.4 86.1 91 92.7 88 84.3 82.2 80.8 79.4 80.2 82.2 82.2 81.2 82.1 88.1 88.5 92.1 98.6 100.9 100.6 101.1 102.1 103.6 102.8 108.3 104 106.1 106.3 109 111 113.7 112.7 110.3 114.5 119.3 121.8 125.4 129.7 129.4 134.5 141.2 141.4 152.2 167.7 173.3 168.7 172.6 169.8 172 179.4 174.6 172.5 172.6 176.3 178.9 179.6 179.9 180.3 180.9 177.7
Data Y:
100.8 100.8 100.8 90.1 95.7 88.6 93.3 93.3 93.3 93.3 93.3 93.3 88.6 97.4 97.4 102.9 102.9 102.9 105.1 105.1 105.1 105.1 105.1 105.1 96.9 96.9 96.9 96.9 96.9 96.9 96.5 96.5 96.5 96 96 96 96 96 96 105.8 105.8 105.8 105.8 105.8 105.8 105.8 105.8 105.8 123.6 142.2 142.2 141.2 141.2 141.2 124.7 124.7 124.7 122.7 122.7 122.7 123.3 123.3 123.3 127.2 127.2 127.2 140 140 140 140 140 140 139 139 139 147 147 147 147.1 147.1
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R Code
library('Kendall') k <- Kendall(x,y) bitmap(file='test1.png') par(bg=rgb(0.2,0.4,0.6)) plot(x,y,main='Scatterplot',xlab=xlab,ylab=ylab) grid() dev.off() bitmap(file='test2.png') par(bg=rgb(0.2,0.4,0.6)) 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,'Kendall tau Rank Correlation',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Kendall tau',header=TRUE) a<-table.element(a,k$tau) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'2-sided p-value',header=TRUE) a<-table.element(a,k$sl) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Score',header=TRUE) a<-table.element(a,k$S) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Var(Score)',header=TRUE) a<-table.element(a,k$varS) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Denominator',header=TRUE) a<-table.element(a,k$D) 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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