Best way to put two histograms on same scale? Let's say I have two distributions I want to compare in detail, i.e. in a way that makes shape, scale and shift easily visible.  One good way to do this is to plot a histogram for each distribution, put them on the same X scale, and stack one underneath the other.  
When doing this, how should binning be done?  Should both histograms use the same bin boundaries even if one distribution is much more dispersed than the other, as in Image 1 below?  Should binning be done independently for each histogram before zooming, as in Image 2 below?  Is there even a good rule of thumb on this?


 A: I think you need to use the same bins.  Otherwise the mind plays tricks on you. Normal(0,2) looks more dispersed relative to Normal(0,1) in Image #2 than it does in Image #1.  Nothing to do with statistics.  It just looks like Normal(0,1) went on a "diet".
-Ralph Winters
Midpoint and histogram end points can also alter perception of the dispersion.
Notice that in this applet a maximum bin selection implies a range of >1.5 - ~5 while a minimum bin selection implies a range of <1 - > 5.5
http://www.stat.sc.edu/~west/javahtml/Histogram.html
A: Another approach would be to plot the different distributions on the same plot and use something like the alpha parameter in ggplot2 to address the overplotting issues. The utility of this method will be dependent on the differences or similarities in your distribution as they will be plotted with the same bins. Another alternative would be to display smoothed density curves for each distribution. Here's an example of these options and the other options discussed in the thread:
library(ggplot2)

df <- melt(
    data.frame( 
        x = rnorm(1000)
        , y = rnorm(1000, 0, 2)
    )
)


ggplot(data = df) + 
#   geom_bar(aes(x = value, fill = variable), alpha = 1/2)
#   geom_bar(aes(x = value)) + facet_grid(variable ~ .)
#   geom_density(aes(x = value, colour = variable))
#   stat_qq(aes(sample = value, colour = variable))

A: So it's a question of maintaining the same bin size or maintaining the same number of bins? I can see arguments for both sides. A work-around would be to standardize the values first. Then you could maintain both.
