Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
85.13 85.54 85.47 85.78 86.07 86.05 86.32 86.43 86.41 86.38 86.59 86.68 86.87 87.32 87.13 87.42 87.22 87.17 87.52 87.49 87.53 87.93 88.54 88.96 89.3 90.01 90.52 90.64 91.25 91.59 92.09 91.81 92.03 92.15 91.98 92.11 92.28 92.53 91.97 92.05 91.87 91.49 91.48 91.63 91.46 91.61 91.7 91.87 92.21 92.65 92.83 93.02 93.33 93.35 93.45 93.51 93.8 93.94 94.02 94.26 94.71 95.26 95.54 95.69 96.03 96.4 96.55 96.45 96.65 96.84 97.21 97.31 97.91 98.51 98.54 98.52 98.66 98.53 98.71 98.92 98.96 99.25 99.32 99.41 99.36 99.58 99.77 99.77 100.03 100.2 100.24 100.1 100.03 100.18 100.29 100.41 100.6 100.75 100.79 100.44 100.29 100.34 100.46 100.12 100.06 100.28 100.28 100.4
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