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Data:
12873 12975 13328 13477 13529 13674 14000 14008 14011 14058 14237 14326 14440 14442 14483 14765 14884 14900 14938 15057 15074 15307 15414 15486 15528 15636 15686 15692 15723 15838 15943 15983 15986 16150 16193 16290 16316 16320 16352 16362 16375 16393 16490 16518 16534 16747 16879 16961 16998 17049 17163 17193 17226 17307 17418 17473 17480 17804 17871 17910 18060 18127 18450 18522 18652 18869 18871 18890 18897 19051 19062 19100 19240 19415 19420 19509 19547 19978 20018 20169 20216 20254 21263 21971
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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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