Hi Philip, This may be a starter: attach(airquality) heights <- tapply(Temp,Month,mean) temp_sd<-tapply(Temp,Month,sd) lower <- tapply(Temp,Month,function(v) t.test(v)$conf.int[1]) upper <- tapply(Temp,Month,function(v) t.test(v)$conf.int[2]) library(plotrix) barp(heights,ylim=c(0,100),names.arg=month.abb[5:9], main="Air quality (May-Sep)",xlab="Month",ylab="Temperature") dispersion(1:5,y=heights,ulim=upper,llim=lower,intervals=FALSE) ci95<-seq(-1.96,1.96,length.out=40) norm_curve<-rescale(dnorm(ci95),c(0,0.4)) for(i in 1:5) polygon(c(i-norm_curve,i+norm_curve), c(heights[i]+ci95*temp_sd[i],heights[i]+rev(ci95*temp_sd[i])))
Jim On Sun, Dec 8, 2019 at 8:18 PM <p...@philipsmith.ca> wrote: > >> I want to show little bell curves on my bar chart to illustrate the > >> confidence ranges. The following example from Paul Teetor's "R > >> Cookbook" > >> does what I want, but shows I-beams instead of bell curves. The > >> I-beams > >> suggest uniform, rather than normal distributions. So I am looking > >> for a > >> way to plot normal distribution curves instead. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
