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Data:
1.73 1.75 1.75 1.75 1.73 1.74 1.75 1.75 1.34 1.24 1.24 1.26 1.25 1.26 1.26 1.22 1.01 1.03 1.01 1.01 1 0.98 1 1.01 1 1 1 1.03 1.26 1.43 1.61 1.76 1.93 2.16 2.28 2.5 2.63 2.79 3 3.04 3.26 3.5 3.62 3.78 4 4.16 4.29 4.49 4.59 4.79 4.94 4.99 5.24 5.25 5.25 5.25 5.25 5.24 5.25 5.26 5.26 5.25 5.25 5.25 5.26 5.02 4.94 4.76 4.49 4.24 3.94 2.98 2.61 2.28 1.98 2 2.01 2 1.81 0.97 0.39 0.16 0.15 0.22
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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
R Server
Big Analytics Cloud Computing Center
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