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Data:
15.22 15.27 15.31 15.33 15.42 15.49 15.65 15.67 15.69 15.83 15.92 15.99 15.94 15.96 16.03 16.09 16.04 16.23 16.2 16.2 16.26 16.28 16.27 16.29 16.3 16.37 16.39 16.42 16.43 16.37 16.37 16.39 16.48 16.51 16.5 16.54 16.52 16.56 16.61 16.75 16.75 16.79 16.82 16.84 17.14 17.25 17.28 17.3 17.34 17.44 17.48 17.55 17.59 17.66 17.67 17.64 17.68 17.72 17.78 17.83 17.88 18.11 18.16 18.27 18.29 18.35 18.35 18.38 18.41 18.41 18.42 18.43 18.48 18.54 18.65 18.66 18.69 18.72 18.72 18.73 18.84 18.83 18.91 18.91 18.94 18.97 19 19.08 19.18 19.24 19.23 19.25 19.3 19.33 19.35 19.35 19.31 19.47 19.7 19.76 19.9 19.97 20.1 20.26 20.44 20.43 20.57 20.6 20.69 20.93 20.98 21.11 21.14 21.16 21.32 21.32 21.48 21.58 21.74 21.75 21.81 21.89 22.21 22.37 22.47 22.51 22.55 22.61 22.58 22.85 22.93 22.98
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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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1 seconds
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Big Analytics Cloud Computing Center
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