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Data X:
4.79 5.95 5.46 5.75 5.15 4.96 5.28 5.73 5.75 5.88 6.3 6.74 6.75 7.34 6.64 6.62 6.32 5.32 5.68 6.18 5.02 2.1 4 3 4.73 5.14 5.81 6.24 4.49 4.22 4.88 5.18 5.19 5.06 4.65 4.83 4.6 4.72 4.33 4.97 5.37 4.19 4.54 5.82 5.49 3.28 5.11 6.24 6.41 6.43 8.42 8.23 3.17 2.72 3 3.47 3.88 3.43 4.06
Data Y:
2.86 2.55 2.27 2.26 2.57 3.07 2.76 2.51 2.87 3.14 3.11 3.16 2.47 2.57 2.89 2.63 2.38 1.69 1.96 2.19 1.87 1.6 1.63 1.22 1.21 1.49 1.64 1.66 1.77 1.82 1.78 1.28 1.29 1.37 1.12 1.51 2.24 2.94 3.09 3.46 3.64 4.39 4.15 5.21 5.8 5.91 5.39 5.46 4.72 3.14 2.63 2.32 1.93 0.62 0.6 -0.37 -1.1 -1.68 -0.78
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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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