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Data X:
110.40 96.40 101.90 106.20 81.00 94.70 101.00 109.40 102.30 90.70 96.20 96.10 106.00 103.10 102.00 104.70 86.00 92.10 106.90 112.60 101.70 92.00 97.40 97.00 105.40 102.70 98.10 104.50 87.40 89.90 109.80 111.70 98.60 96.90 95.10 97.00 112.70 102.90 97.40 111.40 87.40 96.80 114.10 110.30 103.90 101.60 94.60 95.90 104.70 102.80 98.10 113.90 80.90 95.70 113.20 105.90 108.80 102.30 99.00 100.70 115.50
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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