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Data X:
153.24 184.48 191.81 168.19 163.81 190.57 163.81 129.62 173.90 198.76 135.52 179.81 137.05 142.57 187.52 220.48 208.76 210.19 232.57 173.81 218.86 226.76 196.67 237.43 173.14 207.62 234.67 204.10 230.76 210.19 194.76 172.10 221.90 225.24 228.00 198.76 199.05 235.43 270.76 234.10 237.24 239.43 239.24 197.33 217.43 242.19 207.52 232.76 222.10 202.48 228.10 319.52 236.95 252.00 262.29 172.10 243.90 235.62 216.95 236.29
Data Y:
146.54 120.13 131.67 131.97 145.92 177.02 149.56 171.58 173.95 190.39 183.46 165.44 186.32 223.29 198.99 191.05 178.42 187.85 183.51 252.94 213.51 185.53 215.48 214.39 229.21 183.55 206.71 186.23 217.46 214.69 202.06 225.57 220.70 246.32 273.51 220.66 295.88 215.35 230.83 220.00 232.06 237.68 294.39 295.35 267.68 274.12 246.84 249.34 303.25 236.14 233.38 260.96 281.18 281.54 288.95 332.68 345.96 414.96 285.35 288.03
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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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