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Data:
16.3 16.37 16.38 16.37 16.42 16.43 16.44 16.53 16.55 16.56 16.6 16.61 16.62 16.64 16.61 16.74 16.87 16.89 16.89 16.99 17.06 17.1 17.11 17.17 17.17 17.21 17.37 17.43 17.44 17.46 17.42 17.47 17.45 17.44 17.46 17.47 17.47 17.56 17.61 17.61 17.6 17.57 17.59 17.59 17.68 17.73 17.75 17.75 17.75 17.85 18.06 18.05 18.16 18.2 18.21 18.33 18.36 18.37 18.4 18.47 18.49 18.5 18.53 18.56 18.6 18.61 18.62 18.61 18.65 18.77 18.78 18.78 18.8 18.85 18.85 18.98 19.06 19.08 19.19 19.21 19.29 19.3 19.36 19.36
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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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Raw Output
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Computing time
2 seconds
R Server
Big Analytics Cloud Computing Center
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