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122.6 115.4 109 129.1 102.8 96.2 127.7 128.9 126.5 119.8 113.2 114.1 134.1 130 121.8 132.1 105.3 103 117.1 126.3 138.1 119.5 138 135.5 178.6 162.2 176.9 204.9 132.2 142.5 164.3 174.9 175.4 143 158.7 155.4 176.6 163.3 178.9 182.7 158.9 115.5 169.4 168 159.8 129 157.9 169.5 169.1 183.6 168.9 186.2 227.1 126.4 169.3 175 133.9 110.1 104.3 108.7 112.6
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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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