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Data:
120.9 119.6 125.9 116.1 107.5 116.7 112.5 113 126.4 114.1 112.5 112.4 113.1 116.3 111.7 118.8 116.5 125.1 113.1 119.6 114.4 114 117.8 117 120.9 115 117.3 119.4 114.9 125.8 117.6 117.6 114.9 121.9 117 106.4 110.5 113.6 114.2 125.4 124.6 120.2 120.8 111.4 124.1 120.2 125.5 116 117 105.7 102 106.4 96.9 107.6 98.8 101.1 105.7 104.6 103.2 101.6
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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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1 seconds
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Big Analytics Cloud Computing Center
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