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Data X:
3.923198482 3.355352521 3.011684284 4.091213472 4.084557852 3.264489131 3.766129784 3.992770823 -0.54141524 3.112752558 3.171661653 2.462250663 3.070654392 2.235820402 2.725664507 2.336545755 2.220263192 1.620463769 1.533868628 0.978287599 1.476911825 2.268496345 2.792958826 2.095200542 2.120262192 2.607602101 2.635155718
Data Y:
2.436036766 2.506268418 2.098265365 2.124832238 2.517217513 2.461391452 2.315347438 3.204714162 -1.294824902 2.369731394 2.468767432 2.054236524 2.424888321 1.52028568 2.089777283 1.536802397 1.387692825 0.852021492 0.688743986 0.108574911 0.574870836 1.37486412 1.732474185 1.439071701 1.420530401 1.87856963 1.908516226
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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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Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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