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Data:
19.4 19.4 19.4 19.5 19.5 19.5 28.7 28.7 28.7 21.8 21.8 21.8 20 20 20 22.6 22.6 22.6 22.4 22.4 22.4 18.6 18.6 18.6 16.2 16.2 16.2 13.8 13.8 13.8 24.1 24.1 24.1 19.9 19.9 19.9 22.3 22.3 22.3 20.9 20.9 20.9 23.5 23.5 23.5 23.1 23.1 23.1 25.7 25.7 25.7 19.7 19.7 19.7 23.1 23.1 23.1 20.7 20.7 20.7 18 18 18 16.9 16.9 16.9 24.4 24.4 24.4 15.5 15.5 15.5 18.4 18.4 18.4 16.2 16.2 16.2 20.6 20.6 20.6 19.8 19.8 19.8
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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
2 seconds
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Big Analytics Cloud Computing Center
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