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Data X:
.81 .81 .79 .75 .73 .81 .75 .79 .81 .76 .59 .85 .94 .71 .81 .89 .88 .91 .76 .86 .93 .66 .90 .65 .84 .84 .56 .79 .73 .93 .83 .84 .81 .86 .91 .81 .86 .80
Data Y:
.44 .37 .37 .36 .36 .40 .38 .35 .38 .49 .38 .42 .43 .33 .44 .41 .35 .36 .43 .39 .48 .49 .44 .42 .42 .42 .39 .46 .38 .36 .36 .41 .38 .41 .45 .37 .41
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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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