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760 730 730 680 730 710 800 830 820 770 800 840 800 710 800 780 760 730 770 880 850 810 770 810 890 790 840 830 740 760 630 890 900 820 810 820 890 810 810 840 830 790 610 870 870 820 800 840 860 860 730 850 860 900 610 960 820 860 810 820 820 880 840 910 860 880 620 970 810 880 870 800 740 1010 850 980 880 870 660 940 860 880 1000 840 800 1060 790 930 920 840 690 940 1010 890 1000 820 800 1000 780 1010 950 830 670 1000 960 920 1040 860
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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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2 seconds
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Big Analytics Cloud Computing Center
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