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Data:
17.75694444 -10.5625 -10.40277778 -24.45138889 7.798611111 56.28472222 2.743055556 -26.97222222 -5.948611111 -13.34861111 5.718055556 -13.86527778 53.75694444 3.3125 30.80555556 -3.409722222 -22.11805556 -38.67361111 -5.215277778 7.194444444 -0.781944444 16.06805556 -14.44861111 27.13472222 3.715277778 3.854166667 -5.944444444 2.881944444 -17.57638889 -7.215277778 -5.965277778 -4.847222222 -11.49027778 -5.806944444 1.176388889 22.38472222 -27.86805556 26.3125 -5.777777778 6.840277778 3.298611111 0.659722222 29.03472222 22.52777778 18.55138889 8.193055556 2.968055556 -25.07361111 -30.65972222 -19.5625 -3.069444444 6.381944444 20.92361111 4.951388889 -18.67361111 2.444444444 1.718055556 -3.056944444 6.634722222 -8.531944444 -14.24305556 -0.895833333 -3.152777778 14.21527778 10.13194444 -13.54861111 0.534722222 2.111111111
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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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