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Data:
2.17 2.17 2.08 2.12 2.18 2.13 2.21 2.06 1.91 1.99 2.04 2.02 2.01 2.1 2.01 2.07 2.05 2.1 2.15 2.15 1.96 2.06 2.07 2.05 2.08 2.14 2.16 2.35 2.31 2.2 2.3 2.22 2.14 2.17 2.12 2.1 2.17 2.29 2.17 2.25 2.13 2.23 2.17 2.24 2.13 2.16 2.1 2.05 2.03 2.24 2.17 2.13 2.21 2.18 2.21 2.23 2.09 2.16 2.13 2.12 2.04 2.2 2.16 2.14 2.18 2.08 2.1 2.04 1.98 1.99 1.99 2 2.02 2.02 2.03 1.96 1.95 1.94 1.96 2 1.88 1.98 1.99 1.96
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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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