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Data:
498.10 498.76 498.88 498.88 498.88 498.88 499.48 501.21 502.05 502.05 502.05 504.10 506.81 516.88 520.43 520.68 520.68 520.68 521.03 521.25 521.25 521.25 521.65 521.65 522.77 518.72 519.27 519.38 521.29 521.29 521.29 523.47 523.86 524.14 524.14 524.14 534.60 534.99 535.39 535.39 535.39 535.39 535.39 535.64 536.08 537.80 537.80 537.80 537.85 544.39 545.15 544.65 544.65 544.65 545.73 548.94 550.94 551.22 551.22 551.22 553.12 565.37 566.73 566.73 566.78 566.78 566.78 566.78 566.93 566.93 566.93 566.93 574.38 574.40 574.40 574.40 574.40 574.40 574.50 574.50 574.67 574.66 574.66 574.94 576.10 583.38 584.15 584.15 584.15 584.15 585.14 585.14 585.67 586.49 586.81 586.85
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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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Raw Input
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Raw Output
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Computing time
2 seconds
R Server
Big Analytics Cloud Computing Center
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