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Data:
99.5 101.6 103.9 106.6 108.3 102 93.8 91.6 97.7 94.8 98 103.8 97.8 91.2 89.3 87.5 90.4 94.2 102.2 101.3 96 90.8 93.2 90.9 91.1 90.2 94.3 96 99 103.3 113.1 112.8 112.1 107.4 111 110.5 110.8 112.4 111.5 116.2 122.5 121.3 113.9 110.7 120.8 141.1 147.4 148 158.1 165 187 190.3 182.4 168.8 151.2 120.1 112.5 106.2 107.1 108.5 106.5 108.3 125.6 124 127.2 136.9 135.8 124.3 115.4 113.6 114.4 118.4 117 116.5 115.4 113.6 117.4 116.9 116.4 111.1 110.2 118.9 131.8 130.6 138.3 148.4 148.7 144.3 152.5 162.9 167.2 166.5 185.6
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R Code
library(MASS) par1 <- as.numeric(par1) if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2) x <- as.ts(x) #otherwise the fitdistr function does not work properly r <- fitdistr(x,'normal') r bitmap(file='test1.png') myhist<-hist(x,col=par1,breaks=par2,main=main,ylab=ylab,xlab=xlab,freq=F) curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Parameter',1,TRUE) a<-table.element(a,'Estimated Value',1,TRUE) a<-table.element(a,'Standard Deviation',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,r$estimate[1]) a<-table.element(a,r$sd[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'standard deviation',header=TRUE) a<-table.element(a,r$estimate[2]) a<-table.element(a,r$sd[2]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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