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Data:
42.3 50.8 54.1 38.2 48.4 61.1 54.1 61.4 64.3 57.4 71.7 55.3 55.1 66.8 59.4 64.9 59.2 77.4 75.8 38.3 54 61.8 61.3 104.3 39.7 62.6 50.2 90.9 56.2 50.2 52.8 45.6 69 81.9 73.9 54.9 55.4 64.6 49.6 55.8 44.6 61.5 40.5 48.3 50.9 65.3 56.5 53.2 56.9 79.5 94 68.4 65.9 85.5 77.5 114.8 87.4 107.5 151.7 94.4 67.5 95.2 96.2 70.6 80.1 83.4 115.4 61.5 80.6 94.3 82.6 107.7 79.1 102.8 125.2 106.4 62.3 107.4 67.9 88 76.5 130.5 100.9 85.6
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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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