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Data:
9.26 9.27 9.29 9.27 9.29 9.31 9.33 9.35 9.34 9.35 9.38 9.43 9.47 9.5 9.55 9.58 9.61 9.57 9.61 9.65 9.62 9.63 9.62 9.63 9.65 9.72 9.75 9.77 9.78 9.82 9.84 9.9 9.94 9.96 10.03 10.03 10.12 10.12 10.05 10.14 10.17 10.2 10.2 10.35 10.43 10.52 10.57 10.57 10.57 10.65 10.57 10.61 10.63 10.71 10.72 10.77 10.79 10.82 10.9 10.83 10.92 10.91 10.88 10.87 11 10.99 11.03 11.04 10.99 10.9 11 10.99 10.92 10.98 11.15 11.19 11.33 11.38 11.4 11.45 11.56 11.61 11.82 11.77 11.85 11.82 11.92 11.86 11.87 11.94 11.86 11.92 11.83 11.91 11.93 11.99 11.96 12.12 11.85 12.01 12.1 12.21 12.31 12.31 12.39 12.35 12.41 12.51 12.27 12.51 12.44 12.47 12.51 12.58 12.5 12.52 12.59 12.51 12.67 12.64 12.54 12.6 12.67 12.62 12.72 12.85 12.85 12.82 12.79 12.94 12.71 12.56
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R Code
library(Hmisc) m <- mean(x) e <- median(x) bitmap(file='test1.png') op <- par(mfrow=c(2,1)) mydensity1 <- density(x,kernel='gaussian',na.rm=TRUE) plot(mydensity1,main='Density Plot - Gaussian Kernel',xlab='Median (0 -> full line) | Mean (0 -> dashed line)',ylab='density') abline(v=e,lty=1) abline(v=m,lty=5) grid() myseq <- seq(0.01, 0.99, 0.01) hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE) plot(myseq,hd,col=2,main='Harrell-Davis Quantiles',xlab='quantiles',ylab='Median (0 -> full) | Mean (0 -> dashed)') abline(h=m,lty=5) abline(h=e,lty=1) grid() par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Median versus Mean',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,mean(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'median',header=TRUE) a<-table.element(a,median(x)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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