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Data:
25000 25284 12434.5 33955 14980.5 50831 4198.5 34566 35000 11055.5 20807 21887.29 16977.5 19613.5 14570 24416.5 16825.5 13980 21450.5 27239.5 19078.5 20459.1 20373.5 19306.5 16723.16 11638 20917 17903.5 28218.5 15268 21555 23143 16691 17932.5 30512 41931.5 10853.5 25939.5 14900 25127.76 22063.5 25306.5 31217.5 23201.5 38148 26264 16359 27945.5 16218.5 36003.5 20323.5 20100.5 18741 24426.75 19174.5 13766 18999 21745 34469 13248 16218.5 36003.5 20323.5 20100.5 18741 24426.75 19174.5 13766 18999 21745 34469 13248
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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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