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Data X:
1.72 0.89 1.17 1.01 1.92 0.91 1.61 1.49 1.79 1.00 1.51 1.19 0.97 1.71 1.04 0.85 1.04 1.17 1.28 1.29 1.17 1.21 0.91 1.93 1.84 1.15 1.03
Data Y:
11.02 0.86 0.95 0.98 1.07 0.98 1.04 1.07 0.96 0.91 0.87 0.83 0.89 1.44 1.10 0.88 0.83 1.26 1.17 0.80 0.90 0.80 1.21 0.80 1.00 0.94 0.91
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R Code
k <- cor.test(x,y,method='spearman') bitmap(file='test1.png') plot(x,y,main='Scatterplot',xlab=xlab,ylab=ylab) grid() dev.off() bitmap(file='test2.png') 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,'Spearman Rank Correlation',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'rho',header=TRUE) a<-table.element(a,k$estimate) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'2-sided p-value',header=TRUE) a<-table.element(a,k$p.value) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'S',header=TRUE) a<-table.element(a,k$statistic) 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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