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Data:
72.9 85 98.8 86.3 101.9 95.1 71.6 84.4 97.5 100.7 92.9 74.4 81.4 84 95.9 86.8 98.9 101.3 74.5 86 92.6 103.5 90 68 79.7 81.2 91.8 96.5 93.2 98.9 79.2 79.2 99.4 105 88.3 65.3 78.1 82.3 93.8 96 89.2 99.2 81.7 76 101.1 103.5 84.5 74 78.3 83 100.9 95.4 89 109.5 77.5 83.4 104.6 101.4 93 81.7 80 85.5 95.2 102.7 96.2 113.8 76.8 88.9 109.2 101.4 99.1 84.1 87.9 90 108.5 99.5 111.3 117.5 82.7 94.9 115.2 116.6 110.1 88.5 100.1 102.9 120.1 108.2 114.4 123.5 92.3 101.1 114.8 127 112.4 85.3 109.2 113.7 110.4 127.3 117.4 124.6 100.7 93.5 124.5 121.7 98 81.6 82.7 86.8 104 99.4 94.9 110 85.2 85.7 112.4 110.9 95.7 77.1 80.2 84.5 112.8 107.3 100.6 123 89.1 93.9 115.9 113.1 102.4 77.2 91.7 99.7 120.9 104.7 120.3 112.1 83.7 98.1 119.1 108.5 108.5 86 91.2 92 113.9 100.7 107.3 115 87.6 95.9 106.9 113.9 101.9 75.8 83.6 88.7 97.9 105.6 105.2 111.1 92.5 88.3 107 112.7 95.5 78.7 93.2 91.5 102.8 107 98.5 108.8 90.9 85.6 111.9 111.9 93.3 77.8 88.4 92.7 109.6 103.4 96.5 117.5 90.7 86.7 107.5 109.5 94.7 78.7 89.1 97.3 106.6 106.9 102.7 116.3 84.5 92.9 110.7 104.1 99.1 86.9 88.4 97.9 116.9 100.8 112.8 118.8 84.4 95.5
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R Code
par1 <- as.numeric(par1) (n <- length(x)) (np <- floor(n / par1)) arr <- array(NA,dim=c(par1,np)) j <- 0 k <- 1 for (i in 1:(np*par1)) { j = j + 1 arr[j,k] <- x[i] if (j == par1) { j = 0 k=k+1 } } arr arr.mean <- array(NA,dim=np) arr.sd <- array(NA,dim=np) arr.range <- array(NA,dim=np) for (j in 1:np) { arr.mean[j] <- mean(arr[,j],na.rm=TRUE) arr.sd[j] <- sd(arr[,j],na.rm=TRUE) arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE) } arr.mean arr.sd arr.range (lm1 <- lm(arr.sd~arr.mean)) (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) (lm2 <- lm(arr.range~arr.mean)) bitmap(file='test1.png') plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation') dev.off() bitmap(file='test2.png') plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range') dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Section',header=TRUE) a<-table.element(a,'Mean',header=TRUE) a<-table.element(a,'Standard Deviation',header=TRUE) a<-table.element(a,'Range',header=TRUE) a<-table.row.end(a) for (j in 1:np) { a<-table.row.start(a) a<-table.element(a,j,header=TRUE) a<-table.element(a,arr.mean[j]) a<-table.element(a,arr.sd[j] ) a<-table.element(a,arr.range[j] ) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alpha',header=TRUE) a<-table.element(a,lm1$coefficients[[1]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'beta',header=TRUE) a<-table.element(a,lm1$coefficients[[2]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,2]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,3]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value',header=TRUE) a<-table.element(a,summary(lm1)$coefficients[2,4]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'alpha',header=TRUE) a<-table.element(a,lnlm1$coefficients[[1]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'beta',header=TRUE) a<-table.element(a,lnlm1$coefficients[[2]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,2]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,3]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value',header=TRUE) a<-table.element(a,summary(lnlm1)$coefficients[2,4]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Lambda',header=TRUE) a<-table.element(a,1-lnlm1$coefficients[[2]]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable2.tab')
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