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Data X:
95.1 97.0 112.7 102.9 97.4 111.4 87.4 96.8 114.1 110.3 103.9 101.6 94.6 95.9 104.7 102.8 98.1 113.9 80.9 95.7 113.2 105.9 108.8 102.3 99.0 100.7 115.5 100.7 109.9 114.6 85.4 100.5 114.8 116.5 112.9 102.0 106.0 105.3 118.8 106.1 109.3 117.2 92.5 104.2 112.5 122.4 113.3 100.0 110.7 112.8 109.8 117.3 109.1 115.9 96.0 99.8 116.8 115.7 99.4 94.3
Data Y:
98.2 98.7 113.3 104.6 99.3 111.8 97.3 97.7 115.6 111.9 107.0 107.1 100.6 99.2 108.4 103.0 99.8 115.0 90.8 95.9 114.4 108.2 112.6 109.1 105.0 105.0 118.5 103.7 112.5 116.6 96.6 101.9 116.5 119.3 115.4 108.5 111.5 108.8 121.8 109.6 112.2 119.6 104.1 105.3 115.0 124.1 116.8 107.5 115.6 116.2 116.3 119.0 111.9 118.6 106.9 103.2 118.6 118.7 102.8 100.6
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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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