Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
22 17 23 23 28 29 21 24 20 7 19 28 18 26 21 19 20 23 24 16 19 24 21 16 16 21 28 16 23 26 29 18 19 19 16 16 16 18 22 14 20 15 22 24 16 19 24 19 15 11 15 17 20 21 16 17 20 15 21 16 18 25 21 21 16 20 24 28 27 22 20 27 17 22 23 15 22 13 21 18 22 19 15 20 17 21 23 20 18 22 24 24 18 27 19 20 15 20 27 20 20 13 21 23 26 24 25 18 21 23 16 19 20 25 22 20 25 27 20 18 26 26 24 27 16 15 25 27 18 16 18 23 21 21 14 24 18 16 25 22 13 20 17 23 22 23 22 23 10 18 25 26 14 23 22 23 19 14 26 24 21 17 16 15 11 19 21 20 16 19 16 11 22 20 26 26 20 24 20 15 23 25 27 23 20 25 24 22 27 20 17 22 26 19 19 24 22 16 22 23 19 20 16 19 20 15 22
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
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation