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Data X:
150.85 147.79 141.96 148.39 147.71 150.6 151.18 152.24 157.19 154.62 157.22 159.7 160.55 149.66 151.69 154.13 151.48 153.34 155.8 158.87 156.09 156.3 156.4 154.09 161.32 160.12 155.17 154.51 151.38 152.59 153.98 154.91 153.01 155.09 155.53 161.86 166.03 164.54 164.33 163.21 159.95 164.18 167.13 166.8 166.29 168.07 167.1 163.53 168.28 169.07 165.84 163.88 157.33 161 163.54 161.21 158.92 160.18 159.9 164.46
Data Y:
128.6 128.9 129.06 129.23 129.27 129.33 129.35 129.31 129.4 129.49 129.47 129.46 129.45 129.28 129.2 129.25 129.14 129.11 129.02 129.08 128.99 129.11 129.08 129.19 129.23 129.25 129.31 129.33 129.39 129.55 129.43 129.45 129.57 129.76 129.92 130.08 130.41 130.84 131.24 131.49 131.74 132.34 133.5 134.43 136.5 137.41 138.02 138.15 138.24 138.2 138.31 138.65 139.3 139.8 140.52 141.57 141.77 141.66 141.36 141.17
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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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