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Data X:
12 15 16 6 16 16 16 16 16 17 9 15 14 15 13 16 20 14 12 15 16 11 9 16 14 15 13 13 12 16 14 16 14 15 10 16 16 12 16 15 16 15 13 NA 7 7 17 8 15 16 14 19 11 15 17 9 19 17 16 9 11 14 16 17 15 17 10 16 15 11 16 16 16 14 14 16 16 18 14 20 15 16 16 12 8
Data Y:
7 12 12 6 11 10 13 12 12 10 8 12 9 12 9 11 15 8 8 11 12 8 4 10 7 12 11 9 10 8 8 11 12 10 10 12 11 8 10 9 10 12 8 NA 3 8 12 12 10 9 12 14 8 12 13 7 14 13 12 8 13 9 12 10 10 13 9 11 12 8 12 12 12 9 12 12 11 12 6 7 10 12 10 9 3
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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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