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1.8 2.1 2.2 2.3 2.1 2.7 2.1 2.4 2.9 2.2 2.1 2.2 2.2 2.7 1.9 2 2.5 2.2 2.3 1.9 2.1 3.5 2.1 2.3 2.3 2.2 3.5 1.9 1.9 1.9 1.9 2.1 2 3.2 2.3 2.5 1.8 2.4 2.8 2.3 2 2.5 2.3 1.8 1.9 2.6 2 2.6 1.6 2.2 2.1 1.8 1.8 1.9 2.4 1.9 2 2.1 1.7 1.9 2.1 2.4 1.8 2.3 2.1 2 2.8 2 2.7 2.1 2.9 2 1.8 2.6 2.1 2.3 2.2 2 2.2 2.1 2.1 1.9 2 1.7 2.2 2.2 2.3 2.4 2.1 1.9 1.7 1.8 1.5 1.9 1.9 1.7 1.9 1.9 1.8 2.4 1.8 1.9 1.8 2.1 1.9 2.2 2 1.7 1.7 1.8 1.9 1.8 1 1 4 4 3 2 4 4 4 2 4 1 3 3 4 3 4 3 3 4 3 3 2 2 3 1 4 3 2 4 4 4 4 4 3 3 4 4 4 3 4 4 2 2 4 3 3 2 3 2 4 1 4 1 4 3 3 2 3 3 4 4 4 3 3 4 4 1 2 3 4 3 4 3 3 3 3 1 1 3 2 3 2 2 4 2 2 3 4 2 4 3 4 2 1 1 4 3 1 4 3 2 4 3 3 4 1 3 4 1 3 4 4 1 4 2 3 4 4 4 2 4 2 1 1 4 2 2 3 2 3 4 2 3 4 3 4 4 4 2 2 2 4 3 2 2 3 3 1 2 2 3 3 2 2 3 3 1 3 2 2 3 3 3 3 1
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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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