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Data X:
337.701 190.114 602.497 63.709 60.383 144.644 88.493 31.788 43.734 2.918.723 17.866 15.727 14.481 12.996 77.006 56.788 11.692 8.974 71.701 13.571 7.469 6.943 85.481 10.690 5.075 12.324 4.043 25.589 3.078 2.928 1.801 2.239 10.167 1.474 1.300 1.863 966 915 788 701 625 595 20.252 1.590 400 387 358 126 17 4 4.125 2 13.117 58.010 33.316 19.440 28.893 6.161
Data Y:
1 3 3 3 2 1 3 2 2 5 1 5 3 6 3 3 3 4 2 1 2 5 1 4 1 4 4 3 5 5 6 3 4 4 2 5 4 4 4 2 4 6 4 3 5 6 5 3 2 2 4 4 5 3 4 3 4 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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