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Data:
7.5 6 6.5 1 1 5.5 8.5 6.5 4.5 2 5 0.5 5 5 2.5 5 5.5 3.5 3 4 0.5 6.5 4.5 7.5 5.5 4 7.5 7 4 5.5 2.5 5.5 3.5 2.5 4.5 4.5 4.5 6 2.5 5 0 5 6.5 5 6 4.5 5.5 1 7.5 6 5 1 5 6.5 7 4.5 0 8.5 3.5 7.5 3.5 6 1.5 9 3.5 3.5 4 6.5 7.5 6 5 5.5 3.5 7.5 6.5 6.5 6.5 7 3.5 1.5 4 7.5 4.5 0 3.5 5.5 5 4.5 2.5 7.5 7 0 4.5 3 1.5 3.5 2.5 5.5 8 1 5 4.5 3 3 8 2.5 7 0 1 3.5 5.5 5.5 0.5 7.5 9 9.5 8.5 7 8 10 7 8.5 9 9.5 4 6 8 5.5 9.5 7.5 7 7.5 8 7 7 6 10 2.5 9 8 6 8.5 6 9 8 9 5.5 7 5.5 9 2 8.5 9 8.5 9 7.5 10 9 7.5 6 10.5 8.5 8 10 10.5 6.5 9.5 8.5 7.5 5 8 10 7 7.5 7.5 9.5 6 10 7 3 6 7 10 7 3.5 8 10 5.5 6 6.5 6.5 8.5 4 9.5 8 8.5 5.5 7 9 8 10 8 6 8 5 9 4.5 8.5 9.5 8.5 7.5 7.5 5 7 8 5.5 8.5 9.5 7 8 8.5 3.5 6.5 6.5 10.5 8.5 8 10 10 9.5 9 10 7.5 4.5 4.5 0.5 6.5 4.5 5.5 5 6 4 8 10.5 6.5 8 8.5 5.5 7 5 3.5 5 9 8.5 5 9.5 3 1.5 6 0.5 6.5 7.5 4.5 8 9 7.5 8.5 7 9.5 6.5 9.5 6 8 9.5 8 8 9 5
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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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