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5.70 3.40 4.80 6.50 8.50 13.60 15.70 18.80 19.20 12.90 14.40 6.20 2.40 4.60 7.10 7.80 9.90 13.90 17.10 17.80 18.30 14.70 10.50 8.60 4.40 2.30 2.80 8.80 10.70 12.80 19.30 19.50 20.30 15.30 7.90 8.30 4.50 3.20 5.00 6.60 11.10 13.40 16.30 17.40 18.90 15.80 11.70 6.40 2.90 4.70 2.40 7.00 10.60 12.80 17.70 18.20 16.50 16.20 13.90 6.60 3.60 1.40 2.60 4.30 8.80 14.50 16.80 22.70 15.70 18.20 14.20 9.10 5.90 7.00 6.20 7.80 14.30 14.60 17.30 17.10 17.00 13.90 10.30 6.70
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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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