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Data:
-2.344 0.2984 1.134 0.06216 0.2984 0.2984 2.261 0.7043 1.134 1.048 2.167 0.09963 0.6562 -1.702 0.7043 1.511 0.6562 -0.6535 1.261 0.2984 0.01407 0.6562 -0.2957 1.048 -0.8523 -0.1166 -0.0454 0.4915 0.4915 -1.918 -0.2385 1.298 -0.3813 -2.702 1.048 -0.2957 -1.654 -1.296 2.742 -0.2957 1.704 -1.833 0.3839 -0.4888 -0.2957 0.7043 0.4552 -2.296 1.298 2.704 2.491 -4.702 -1.508 -2.509 -0.0454 1.182 0.7043 -0.4032 1.492 0.6562 0.6562 0.5487 -0.7016 -3.21 2.38 -1.344 -1.296 0.9546 -0.3438 -0.3438 -1.043 -2.702 2.491 -0.6161 0.2984 -1.594 -0.9519 1.298 0.6562 -5.296 0.7043 1.917 1.048 4.742 1.704 2.048 -0.9519 1.656 -1.983 0.1674 1.704 0.8974 1.656 -0.9519 0.04809 2.656 2.048 1.312 -2.509 -0.9519 -1.688 -0.2957 1.048 0.2984 0.2412 -0.5085 0.4915 0.2609 -1.045 -0.4888 -3.083 3.704 0.7043 0.04809 1.134 0.04809 -1.451 -0.5085 -1.739 0.6562 -0.7016 0.9315 -0.8663 0.4915 0.7043 -0.7016 -0.8663 -4.508 0.1337 2.704 -2.952 -3.833 2.695 -0.5085 3.656 1.704 -2.509 -1.702 0.1337 -1.986 1.742 -1.508 3.384 -1.508 0.04809 -2.688 0.04809 0.2984 0.2644 -3.702 -0.5085 1.298 -1.952 -0.7391 2.298 -0.2582 2.511 -1.233 -0.5085 0.6562 -1.881 0.4915 -1.045 0.5487
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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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