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Data X:
412 229 215 196 181 164 131 126 123 119 116 112 111 110 109 107 106 105 104 104 103 102 100 99 98 98 96 95 95 95 92 91 90 85 81 80 79 78 77 77 76 75 75 75 74 74 74 73 73 73 71 71 70 70 69 68 68 67 66 66 64 64 63 63 63 63 62 62 61 60 60 59 59 58 57 57 57 56 55 55 55 55 54 54 54 54 53 53 53 53 52 52 52 52 51 50 50 50 49 49
Data Y:
4.301 2.09 4.301 4.716 4.301 2.09 4.154 7.608 1.939 2.09 4.301 2.09 2.225 4.716 4.716 4.716 4.301 3.161 2.09 1.037 4.301 7.608 2.225 4.301 2.225 4.301 2.225 3.161 1.037 2.225 4.301 2.09 4.716 4.301 2.09 4.301 3.161 2.09 3.377 4.301 4.301 2.09 2.225 3.217 2.384 2.09 4.716 4.716 1.236 2.225 4.716 4.716 2.228 1.518 4.716 2.225 4.716 4.716 2.09 1.834 4.716 4.716 4.154 2.09 2.225 1.959 6.093 3.217 3.161 2.225 2.046 4.301 4.301 1.973 2.09 4.154 7.608 2.09 2.09 2.09 2.09 4.154 3.946 2.225 4.716 4.301 2.09 4.716 1.257 2.576 4.716 2.475 0.716 2.225 4.301 2.225 4.301 1.939 2.09 1.518
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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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