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Data X:
5.58 9.59 6.01 18.11 25.64 12.46 5.73 19.41 7.79 14.66 11.66 9.20 10.48 19.41 12.80 13.55 22.18 20.41 7.20 8.63 4.94 4.55 4.58 9.21 8.83 4.44 7.03 6.53 7.54 5.60 8.54 7.51 6.61 6.82 4.60 2.40 3.20 5.39 2.87 3.02 5.46 3.74 6.21 2.63
Data Y:
6.72 1.39 1.58 7.92 7.59 3.61 4.38 4.26 3.83 #DIV/0! 5.18 2.96 5.40 4.26 5.77 4.57 3.67 2.58 5.43 6.08 3.49 10.36 6.36 7.96 3.61 11.81 3.02 1.70 5.81 2.31 4.75 5.07 3.95 4.88 5.27 2.67 1.53 2.65 2.39 1.69 5.65 5.18 3.43 1.96
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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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