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Data:
229.7 231.5 226.4 242.1 228.3 209.9 209.3 220.8 239.6 241.1 241.9 240.8 179.9 190.8 174.2 170 170.3 159.3 147.9 154.2 164.5 173.9 163.6 149.7 128.2 124.7 125.1 120.9 117.5 114 113.4 118.9 121.7 121.9 120.3 115.6 105.7 105.1 104.6 105 104.9 105.1 103.9 101.9 99 97 95.8 94.7 97.6 97.9 99.3 99.7 99.7 100 99.1 98.2 98.1 98.6 100.2 101.9 97.5 97.1 98.1 98.5 98.3 99.3 100.9 100.4 101.7 102 103.2 103.1
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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
2 seconds
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Big Analytics Cloud Computing Center
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