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6830.2 4108.8 3131.6 7008 1276.8 6554.6 4387.6 4651.8 6192.2 4645.4 4540 5115.2 6776.2 4455 2579 7855.2 866.6 6406.4 4479.6 5164 6308.2 5124.8 4958.4 5410.8 7570.4 4753.8 3406.2 10495.2 723.6 6954 5429.6 5155.2 6930 6119 4681.2 6040 8226 5075.4 2514.4 9024 1964 7282.4 6287.6 5152.8 7425 6224.6 4824.4 6716.8 9293.2 4561 2848 14370 1855 8104.2 6377.8 5376.8 7959.4 6485.8 5007.8 7307.4 8797.4 5130.2 4127.4 10666.8 3591.6 9218.4 5158.2 6388.4 8356.8 6257.4 5964.4 7934.6 9725.4 4685.4 3553.8 13706.6 5067.2 9975.2 5875.4 7386.4 9005.2 7098.6 6889.6 7477 11208.8 5766 2634.8 14875 4293.4 9927.8 6658 7286.8 9332.8 8138.2 5431.2 9294.2 10176.4 5585.8 2257.6 15553.6 2402.4 8903.4 7680.6 6912 9595.8 7866.4 6397.4 8344.4 12090.2 4442.6 3900.6 13598.6 2402.4 10614.4 7019.6 6943
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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') print(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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