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1394 1570 1657 1746 1754 1787 1819 1828 1832 1846 1851 1852 1853 1855 1878 1898 1947 1954 2040 2057 2058 2063 2069 2069 2072 2072 2074 2085 2093 2113 2137 2139 2150 2154 2155 2160 2164 2172 2187 2194 2201 2214 2218 2226 2251 2260 2260 2266 2267 2276 2277 2280 2282 2289 2295 2299 2311 2318 2333 2351 2355 2360 2368 2379 2408 2411 2442 2450 2456 2467 2479 2498 2521 2533 2539 2540 2546 2548 2565 2570 2628 2669 2678 2695 2725 2798 2799 2825 2842 2844 2920 2930 2947 2981 3016 3249 3336 3440 3595
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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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