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Data X:
-999.0 6.3 -999.0 -999.0 2.1 9.1 15.8 5.2 10.9 8.3 11.0 3.2 7.6 -999.0 6.3 8.6 6.6 9.5 4.8 12.0 -999.0 3.3 11.0 -999.0 4.7 -999.0 10.4 7.4 2.1 -999.0 -999.0 7.7 17.9 6.1 8.2 8.4 11.9 10.8 13.8 14.3 -999.0 15.2 10.0 11.9 6.5 7.5 -999.0 10.6 7.4 8.4 5.7 4.9 -999.0 3.2 -999.0 8.1 11.0 4.9 13.2 9.7 12.8 -999.0
Data Y:
5 1 1 2 5 4 1 5 2 1 4 5 1 5 1 2 2 2 2 1 5 5 1 4 3 1 1 3 5 1 5 2 1 1 1 1 1 1 1 1 5 2 4 1 4 5 2 1 1 3 2 2 5 5 2 1 1 1 2 3 1 1
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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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