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Data:
18288.3 16049 16764.5 17880.2 16555.9 16087.1 16373.5 17842.2 22321.5 22786.7 18274.1 22392.9 23899.3 21343.5 22952.3 21374.4 21164.1 20906.5 17877.4 20664.3 22160 19813.6 17735.4 19640.2 20844.4 19823.1 18594.6 21350.6 18574.1 18924.2 17343.4 19961.2 19932.1 19464.6 16165.4 17574.9 19795.4 19439.5 17170 21072.4 17751.8 17515.5 18040.3 19090.1 17746.5 19202.1 15141.6 16258.1 18586.5 17209.4 17838.7 19123.5 16583.6 15991.2 16704.5 17422 17872 17823.2 13866.5 15912.8 17870.5 15420.3 16379.4 17903.9 15305.8 14583.3 14861 14968.9 16726.5 16283.6 11703.7 15101.8 15469.7 14956.9 15370.6 15998.1 14725.1 14768.9 13659.6 15070.3 16942.6 15761.3 12083 15023.6 15106.5
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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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