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Data X:
16.3 17.4 18.1 18.0 17.8 17.5 17.4 17.7 18.1 18.5 18.7 18.9 19.5 19.9 20.2 20.2 19.9 19.6 19.4 19.6 19.8 20.1 20.2 20.2 20.8 21.2 21.3 20.9 20.6 20.5 20.8 21.3 21.9 22.3 22.6 22.7 23.7 24.3 24.6 24.5 24.5 24.2 24.4 24.8 25.2 25.6 25.9 25.8 26.7 27.1 27.0 26.6 26.1 25.6 25.6 25.6 25.8 26.0 25.9 25.4 26.0 26.0 25.8 25.1 24.5 23.8 23.7 23.6 23.7 23.9 23.8 23.5 23.9 23.9 23.6 23.0 22.4 21.7 21.2 21.1 21.2 21.6
Data Y:
9.8 10.0 10.2 10.3 10.3 10.4 10.6 11.1 11.3 11.4 11.3 11.5 11.5 11.8 11.8 11.9 11.8 11.9 11.9 12.2 12.2 12.1 12.3 12.4 12.5 12.6 12.7 12.4 12.3 11.9 12.0 12.6 13.2 13.6 14.1 14.7 14.7 15.0 15.3 15.5 15.1 15.0 15.2 15.9 16.2 16.8 17.1 17.6 17.9 17.8 17.6 17.1 16.7 16.1 16.2 15.8 15.7 15.7 15.5 15.4 15.3 15.3 15.0 14.6 14.1 13.8 13.7 13.3 13.3 13.6 13.6 13.9 14.1 13.9 13.4 12.9 12.1 11.9 11.8 12.1 12.4 12.5
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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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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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