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Data:
10 8 6 10 8 10 7 10 6 7 9 6 7 6 4 6 8 9 8 6 6 10 8 8 7 4 9 8 10 8 6 7 8 5 10 2 6 7 5 8 7 7 10 7 6 10 6 5 8 8 5 8 10 7 7 7 7 2 4 6 7 9 9 4 9 9 8 7 9 7 6 7 2 3 4 5 2 6 8 5 4 10 10 10 9 5 5 7 10 9 8 8 8 8 8 7 6 8 2 5 4 9 10 6 4 10 6 7 7 8 6 5 6 7 6 9 9 7 6 7 7 8 7 8 7 4 10 8 8 2 6 4 4 9 2 6 7 4 10 3 7 4 8 4 5 6 5 9 6 8 4 4 8 4 10 8 5 3 7 6 5 5 9 2 7 7 5 9 4 5 9 7 6 8 7 6 8 6 7
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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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3 seconds
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Big Analytics Cloud Computing Center
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