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Data:
86.9 85.8 84.4 80.4 84.4 90.7 91.6 91.9 92.5 92.5 92 92 94.5 95.5 96.3 100 103.1 109.2 108.7 107.5 104.5 103.8 102.5 100.8 100.7 102.7 106.5 105.5 110.1 110.1 109 106.9 108 106.1 101.7 100.6 102.6 100.5 105.2 104.3 104.1 104.8 105.2 102.7 101 93.9 90.2 92.4 94.4 93.3 93.9 95.1 97.6 99.3 101.1 100.6 99.3 97 96.4 98.7
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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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1 seconds
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Big Analytics Cloud Computing Center
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