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Data:
881.2412655 829.3840119 798.245268 860.679742 943.0594116 765.7904298 937.9587876 891.4824678 998.9762094 950.26668 950.818554 1003.009767 860.9661704 923.5955421 916.1714272 949.9833665 988.8452288 946.8919944 984.6924692 978.649437 1117.149061 854.0713256 1044.938733 960.11217 884.6545329 931.3303455 894.2625903 1089.305419 1034.156547 1008.949251 949.7055648 924.1641224 1034.0468 1004.545776 1128.755463 1011.305803 1009.571733 820.6931964 948.5830077 1061.771074 964.8048 858.6926512 824.8851512 716.525568 931.7342515 971.9671671 981.8002545 1103.17256 1148.573047 1028.97457 1298.539846 1096.215765 1071.682067 1215.565735 886.2840744 927.52071 979.8538375 784.032183 736.5133824 842.7949725
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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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