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Data:
2.8 3.08 3.89 3.68 4.62 5.07 5.22 4.94 5.14 4.8 3.89 3.54 3.34 2.8 1.6 1.56 0.68 -0.11 -0.66 -0.2 -0.62 -0.59 -0.3 -0.26 -0.08 0.13 0.94 1.05 1.59 2.03 2.15 2.05 2.56 2.54 2.53 2.6 2.71 2.82 2.92 2.87 2.89 3.27 3.32 3.14 3.04 3.09 3.39 3.24 3.38 3.41 3.14 2.96 2.74 2.21 2.24 2.56 2.39 2.49 2.17 2.16 1.48 1.09 1.25 1.27 1.39 1.69 1.55 1.19 1.08 0.94 0.98 1.01 1.25 1.17 1.02 0.67 0.26 0.14 0.22 0.02 0.03 0.1 -0.01 -0.01
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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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