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Data:
17 16.7 15.4 15.1 16.1 17 16.1 14.3 16.1 14.8 15.9 17.6 15.9 14.8 16.5 15.6 14.6 17.1 15.2 14.8 15.4 16.6 15.1 15.4 15.2 16.6 16.1 15.7 15.8 15.7 16.9 15.9 17.1 17 16.6 17.1 16.6 16.6 16.5 17 15.9 17 16.1 16.1 16.8 16.7 15.7 18.7 16.1 16.3 17.2 16.1 16.5 16.5 15.1 16.7 14.4 16.2 15.9 17.3 15.6 15.6 14.7 15.8 15.8 14.8 16.1 16.3 16.1 17.4 16.7 16.1 15.4 16.9 15.5 17.6 18.4 15.9 15.2 15.5 15.9 15.8 17.6 18.2 15.9 15.7 16.4 15.6 15.8 17 16.8 16.6 17.7 15.7 18 18.2 16.4 18 16.3
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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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