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Data:
36.80 35.40 33.00 28.73 26.70 26.46 24.60 28.00 31.60 33.50 34.50 35.00 34.76 33.50 32.74 34.40 31.93 29.24 25.75 26.03 26.08 23.80 20.61 19.70 18.18 19.60 20.60 20.03 23.00 23.60 22.56 22.55 23.75 24.92 24.50 30.58 28.07 27.70 27.00 25.23 26.86 25.60 24.55 23.96 23.50 23.64 21.55 21.05 21.89 21.98 21.45 22.15 22.58 23.80 23.30 22.38 23.00 21.96 22.40 20.80 20.40 16.00 12.78 9.75 7.50 11.24 12.24 12.75 12.52 14.49 14.21 14.32 22.15 22.58 23.80 23.30 22.38 23.00 21.96 22.40 20.80 20.40 16.00 12.78 9.75 7.50 11.24 12.24 12.75 12.52 14.49 14.21 14.32
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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
R Server
Big Analytics Cloud Computing Center
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