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Data X:
99.90 99.80 99.80 100.30 99.90 99.90 100.00 100.10 100.10 100.20 100.30 100.60 100.00 100.10 100.20 100.00 100.10 100.10 100.10 100.50 100.50 100.50 96.30 96.30 96.80 96.80 96.90 96.80 96.80 96.80 96.80 97.00 97.00 97.00 96.80 96.90 97.20 97.30 97.30 97.20 97.30 97.30 97.30 97.30 97.30 97.30 98.10 96.80 96.80 96.80 96.80 96.80 96.80 96.80 96.80 96.80 96.80 96.80 96.90 97.10 97.10
Data Y:
109.20 88.60 94.30 98.30 86.40 80.60 104.10 108.20 93.40 71.90 94.10 94.90 96.40 91.10 84.40 86.40 88.00 75.10 109.70 103.00 82.10 68.00 96.40 94.30 90.00 88.00 76.10 82.50 81.40 66.50 97.20 94.10 80.70 70.50 87.80 89.50 99.60 84.20 75.10 92.00 80.80 73.10 99.80 90.00 83.10 72.40 78.80 87.30 91.00 80.10 73.60 86.40 74.50 71.20 92.40 81.50 85.30 69.90 84.20 90.70 100.30
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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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