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Data X:
16.5 9.2 6.2 5.8 15 5.7 6.4 4.3 15.1 0.5 3.7 11.8 0.5 8.6 7.2 1.1 1.9 3.1 27.9 15.6 9.5 1.9 8.4 3.8 9.1 7.6 6 5.3 3.8 3.3 7.4 2.9 7.4 8.3 12.8 11.6 3.3 9 8.4 7.1 6.3 9.4 10.3 12.9 4.6 20.4 2 6.1 9.2 11.4 4.3 5.1 5.1 5.5 10.7 9.2 3.3 11 9.1 3.8 6.7 10.8 5.4 23.8 4.1 27.2 3.1 2.4 6.1 5.2 5.3 3.9 6.1 7.2 17.8 22.2 0.8 23.3 5.8 3.1 4.4 4.7 2 4.4 5.9 6 10.8 7.1 6 2.4 6.6 7.4 15.5 4 1.7 7.9 30.3 3.4 6.7 23.7 4.5 1.9 0.7 3.3 3.3 3.2 2.7 9.9 5.7 4.7 13.1
Data Y:
16.1 19.7 7.1 7.7 18.7 5.8 5.8 5.9 15.6 4.3 4.7 10.9 0.5 7.9 16.5 0.9 3.1 4.5 22.3 21.4 14 2.2 7.5 2.1 12.7 6.4 7.3 3.7 3 2.1 13.1 4.4 11.5 11 14.2 11.9 5 22.2 23.9 6.7 11.1 8.5 9.6 10 4 28.5 3 7 15.7 15.1 9.7 5.3 6.3 5.8 12.7 18.2 2.9 23.9 13.2 3.4 9.1 8.9 11 31.8 3.9 26 3.6 4.3 11.4 5.5 11.5 4.2 3.8 6.1 17.1 26.2 0.9 28 6 1.5 5.8 7.6 3 5.6 5.8 6.4 11.5 5.5 5.5 2.6 8.6 12.5 17.9 1.9 1.9 9.6 32.8 8.5 15.5 27.7 4.7 3.4 0.6 5.6 6.9 4.7 1.9 7.8 11.2 6.2 28.4
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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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