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Data:
75.99 76.31 76.51 76.75 77.23 77.22 77.25 77.36 77.57 77.88 78.29 78.42 78.96 79.85 80.05 80.16 80.29 80.36 80.48 80.95 82.3 84.81 85.4 86.13 87.02 87.38 87.5 87.91 88.06 88.09 88.16 88.33 88.52 88.96 89.26 89.34 89.09 89.25 89.31 89.28 89.32 89.47 89.59 89.62 89.71 89.9 90.04 90.05 90.18 90.5 90.63 90.75 90.76 90.67 90.5 90.8 91.22 92.19 92.51 92.67 93.75 94.1 94.96 95.21 95.33 95.43 95.44 95.64 95.8 95.87 95.98 96.07 96.23 96.32 96.55 96.73 96.61 96.64 96.86 97.02 97.22 98.1 98.46 98.6 98.78 99.13 99.48 99.62 99.68 99.95 100.12 100.25 100.47 100.7 100.88 100.95 100.92 101.12 101.19 101.28 101.28 101.3 101.3 101.36 101.45 101.58 101.73 101.84 102.01 102.14 102.16 102.32 102.41 102.4 102.43 102.42 102.3 102.65 102.72 102.86
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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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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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