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12.9 12.8 7.4 6.7 14.8 13.3 11.1 8.2 11.4 6.4 11.3 10 6.4 10.8 13.8 11.7 13.4 11.7 9 9.7 10.8 12.7 11.8 5.9 11.4 13 11.3 6.7 12.1 13.3 5.7 13.3 7.6 11.1 13 9.9 11.1 4.35 12.7 18.1 12.6 19.1 18.4 14.7 10.6 12.6 16.2 18.9 14.1 16.15 14.75 14.8 12.45 12.65 17.35 18.4 11.6 17.75 15.25 17.65 14.75 9.9 16 13.85 17.1 14.6 15.4 17.6 13.9 16.25 15.65 14.6 11.2 16.35 15.85 7.65 12.35 15.6 13.1 12.85 9.5 11.85 13.6 17.6 16.1 13.35 15.15
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R Code
library(MASS) library(car) 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$estimate[2])^2),min(x),max(x),add=T) dev.off() bitmap(file='test3.png') qqPlot(x,dist='norm',main='QQ plot (Normal) with confidence intervals') grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Parameter',1,TRUE) a<-table.element(a,'Estimated Value',1,TRUE) a<-table.element(a,'Standard Deviation',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,r$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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Big Analytics Cloud Computing Center
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