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Data X:
103.8 100.8 110.6 104.0 112.6 107.3 98.9 109.8 104.9 102.2 123.9 124.9 112.7 121.9 100.6 104.3 120.4 107.5 102.9 125.6 107.5 108.8 128.4 121.1 119.5 128.7 108.7 105.5 119.8 111.3 110.6 120.1 97.5 107.7 127.3 117.2 119.8 116.2 111.0 112.4 130.6 109.1 118.8 123.9 101.6 112.8 128.0 129.6 125.8 119.5 115.7 113.6 129.7 112.0 116.8 127.0 112.1 113.3 120.5 127.7
Data Y:
101.2 93.1 84.2 85.8 91.8 92.4 80.3 79.7 62.5 57.1 100.8 100.7 86.2 83.2 71.7 77.5 89.8 80.3 78.7 93.8 57.6 60.6 91.0 85.3 77.4 77.3 68.3 69.9 81.7 75.1 69.9 84.0 54.3 60.0 89.9 77.0 85.3 77.6 69.2 75.5 85.7 72.2 79.9 85.3 52.2 61.2 82.4 85.4 78.2 70.2 70.2 69.3 77.5 66.1 69.0 79.2 56.2 64.5 77.4 88.5
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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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Big Analytics Cloud Computing Center
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