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5.75 6 5.5 5 6 6.75 7 6.75 6 5.75 6 6.75 6.75 7 6.75 5.75 6 7 6.75 6.25 4.75 6 5 7 6.5 5.75 5.75 5 2.75 6 6.25 5.75 4.5 5 5 6 5.75 6.25 7 6.5 6.5 5.75 5.5 6 5.25 5 5.5 5 6.25 5 5.5 5.75 6.25 5.75 5.75 5.5 6 6.25 5.25 3 4.25 5 5.75 5.75 5 7 6 6 6 6 7 6.25 5.25 6.25 6.25 4.5 4.25 6.5 7 5.25 6.75 5.5 5.25 6.25 5.5 5.75 6.5 4.75 6.25 5.25 3.25 6 6.25 6.5 6.25 6.25 5.5 5.25 5.75 6.25 6 5.25 5.25 6.25 5.5 5 5 5.75 7 5.75 7 6 4.5 5 7 5.25 5.25 6.25 4.75 4.5 5.25 5.5 6 3.75 7 6.5 5.75 6.5 5 5.5 5 5.75 5.5 6 5.75 5.5 6.5 5.75 6.75 5.75 5.25 6.5 5.75 5.25 6.75 4.75 5.75 6.25 5.75 5.5 5.5 6.25 6.25 7 7 5 6.25 4.75 6.25 5.5 4.5 5
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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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