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Data X:
114.08 112.95 135.31 134.31 133.03 140.11 124.69 131.68 150.95 137.26 130.51 143.15 118.01 122.56 147.97 135.74 151.62 154.82 145.59 147.12 175.86 140.66 152.69 154.38 132.45 136.44 153.24 154.11 155.93 142.53 148.73 147.73 166.79 144.30 156.07 161.70 152.10 140.45 155.56 174.53 167.16 159.48 173.22 176.13 180.31 185.84 169.43 195.25 174.99 156.42 182.08 182.00 153.28 136.72 130.19 132.04 143.89 133.38 127.98 150.45 133.55
Data Y:
136.49 142.62 141.71 149.51 147.39 131.96 136.38 127.34 133.85 125.14 141.25 149.32 120.92 134.85 131.93 134.22 143.07 145.37 134.32 126.31 162.21 124.09 153.91 154.34 138.70 150.98 146.39 178.30 168.23 162.52 158.86 152.17 171.01 171.49 189.62 177.46 179.98 156.96 167.89 194.78 192.78 165.06 196.60 151.64 187.02 210.99 219.08 235.68 241.44 187.46 229.57 208.44 215.09 217.00 171.08 178.41 196.34 172.11 154.93 182.26 181.74
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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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