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Data X:
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 99.00 100.70 115.50 100.70 109.90 114.60 85.40 100.50 114.80 116.50 112.90 102.00 106.00 105.30 118.80 106.10 109.30 117.20 92.50 104.20 112.50 122.40 113.30 100.00 110.70 112.80 109.80 117.30 109.10 115.90 96.00 99.80 116.80 115.70 99.40 94.30 91.00 93.20 103.10 94.10 91.80 102.70 82.60
Data Y:
8.00 8.10 7.70 7.50 7.60 7.80 7.80 7.80 7.50 7.50 7.10 7.50 7.50 7.60 7.70 7.70 7.90 8.10 8.20 8.20 8.20 7.90 7.30 6.90 6.60 6.70 6.90 7.00 7.10 7.20 7.10 6.90 7.00 6.80 6.40 6.70 6.60 6.40 6.30 6.20 6.50 6.80 6.80 6.40 6.10 5.80 6.10 7.20 7.30 6.90 6.10 5.80 6.20 7.10 7.70 7.90 7.70 7.40 7.50 8.00
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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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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