Plotting confidence intervals

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

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.