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Data:
84.97 85.57 85.74 85.88 85.88 85.96 85.96 85.99 86.02 86.14 86.3 86.32 86.32 86.77 87.47 87.39 87.3 87.31 87.31 87.38 87.4 87.32 87.37 87.4 87.4 87.89 87.7 87.89 88.02 88.08 88.08 88.15 88.21 88.41 88.39 88.41 88.41 89.1 90.35 90.61 91.18 91.22 91.22 91.4 91.52 91.68 91.71 91.77 91.77 92.16 93.64 93.78 93.96 93.82 93.82 93.89 94.05 94.46 94.62 94.72 94.72 95.76 96.14 97.11 97.19 97.43 97.43 97.56 97.66 97.75 97.82 97.82 97.82 98.35 98.19 98.19 98.21 98.22 98.26 98.23 98.26 98.5 98.51 98.51 98.51 98.89 99.55 99.9 100.12 100.09 100.09 100.09 100.46 100.71 100.79 100.79 100.93 101.15 101.53 101.91 102.18 102.24 102.2 102.32 102.43 102.45 102.84 102.96 102.96 103.1 103.4 103.74 103.97 104.29 104.33 104.46 104.9 105.31 105.63 105.68
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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
2 seconds
R Server
Big Analytics Cloud Computing Center
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