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Data:
2.13 1.87 2.23 3 2.12 1.6 1.17 1.02 1.22 1.8 2.13 2.21 2.38 1.99 1.82 2.47 1.94 1.39 1.11 0.97 1.38 2.39 1.88 2.11 2.11 2.17 2.54 3.13 2.25 1.39 1.36 1.33 1.6 1.95 2.23 2.53 2.36 1.95 2.16 2.76 2.09 1.49 1.17 1.3 1.26 2.17 2.03 2.18 2.61 2.58 3.86 3.81 2.41 1.47 1.33 1.38 1.57 2.6 2.18 2.36 2.24 2.41 2.51 2.98 1.87 1.9 1.47 1.45 2.71 2.9 2.11 2.18 2.24 2.05 2.42 2.77 1.99 1.47 1.09 0.93 1.32 2.03 2.04 2.78 2.8 3.03 3.11 2.75 2.78 1.76 1.29 1.28 1.43 1.71 1.89 1.84
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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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