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Data:
2.32 1.93 0.62 0.6 -0.37 -1.1 -1.68 -0.77 -1.2 -0.97 -0.12 0.26 0.62 0.7 1.65 1.79 2.28 2.46 2.57 2.32 2.91 3.01 2.87 3.11 3.22 3.38 3.52 3.41 3.35 3.68 3.75 3.6 3.56 3.57 3.85 3.48 3.65 3.66 3.36 3.19 2.81 2.25 2.32 2.85 2.75 2.78 2.26 2.23 1.46 1.19 1.11 1 1.18 1.59 1.51 1.01 0.9 0.63 0.81 0.97 1.14 0.97 0.89 0.62 0.36 0.27 0.34 0.02 -0.12 0.09 -0.11 -0.38 -0.65 -0.4 -0.4 0.29 0.56 0.63 0.46 0.91 1.06 1.28 1.52 1.5
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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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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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