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Data:
$62.897.210.20 $63.174.413.18 $67.201.224.66 $68.973.979.92 $52.190.577.71 $61.079.762.12 $60.602.326.05 $80.045.781.80 $63.348.002.01 $70.379.096.07 $57.579.682.80 $59.434.016.55 $58.259.927.53 $60.806.054.54 $66.296.678.07 $66.601.187.53 $67.694.923.94 $65.798.390.32 $62.111.206.30 $66.977.264.43 $59.111.920.01 $53.488.848.05 $53.985.223.72 $62.766.088.16 $58.102.681.96 $68.715.070.51 $66.952.517.50 $66.529.466.40 $71.513.797.44 $67.518.599.51 $70.881.629.67 $74.068.747.43 $73.348.701.17 $74.418.791.76 $83.778.135.12 $82.054.671.92 $83.909.739.64 $79.179.168.58 $74.697.490.36 $76.996.320.79 $77.924.713.88 $77.257.423.85 $91.579.952.10 $95.295.918.81 $93.023.164.41 $92.592.734.65 $95.612.377.01 $97.493.588.08 $95.460.766.25 $97.589.841.71 $116.455.733.38 $123.758.776.11
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R Code
library(MASS) library(car) par1 <- as.numeric(par1) if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2) x <- as.ts(x) #otherwise the fitdistr function does not work properly r <- fitdistr(x,'normal') print(r) bitmap(file='test1.png') myhist<-hist(x,col=par1,breaks=par2,main=main,ylab=ylab,xlab=xlab,freq=F) curve(1/(r$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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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