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Data:
771.28 766.78 757.59 747.73 746.59 744.5 744.29 743.79 738.89 736.74 732.77 731.58 731.48 730.08 724.19 716.81 714.84 713.18 713.16 713.15 713.6 707.08 704.11 704.36 704.36 701.93 696.44 686.58 684.48 683.74 683.7 683.52 678.77 674.71 670.28 668.85 668.85 669.35 672.28 671.6 671.96 671.18 671.18 681.14 682.23 679.98 679.69 679.69 679.7 681.21 672.32 669.98 667.91 666.04 666.04 666.27 664.45 660.76 660.4 660.69 660.69 662.23 661.41 659.02 655.43 652.59 652.59 648.2 645.84 644.67 642.71 640.14 640.14 639.64 630.28 614.57 614.7 615.08 615.08 614.43 604.55 598.98 594.05 593.05 593.05 593.34 584.72 580.7 577.08 569.92 569.92 568.86 559.38 548.22 545.61 545.33
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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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