Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
24 17 22 15 20 24 15 20 20 17 11 21 28 14 13 12 21 13 19 23 27 25 27 16 20 18 19 17 10 11 16 13 14 12 15 15 14 10 13 21 11 14 20 7 24 16 22 25 5 19 23 13 10 12 21 22 20 17 13 9 22 15 12 25 14 14 17 9 10 15 15 15 14 21 13 20 16 12 20 18 21 23 13 22 14 23 16 14 22 19 23 16 20 8 16 11 16 10 17 16 17 10 15 13 19 14 18 25 10 22 15 18 22 18 15 20 18 6 17 12 12 19 23 26 28 19 16 3 11 15 22 12 21 25 12 14 24 12 13 15 17 12 28 25 14 21 18 23 16 15 5 19 22 19 12 22 18 24 19 4 20 24 26 22 19 9 22 18 16 19 20 21 17 9 26 28 13 16 22 18 21 10 15 15 13 10 23 21 14 17 15 15 17 26 12 14 26 18 17 20 16 19 12 20 19 25 19 15 12
Chart options
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')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
2 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation