"A new technique is presented for illustrating several probability
distributions on the same axes. The density strip is a shaded
monochrome strip whose darkness at a point is proportional to
the probability density of the quantity at that point. These are
ideal for comparing distributions arising from parameter estimation,
such as posterior distributions from Bayesian multiple
regression or meta-analysis. Such distributions are more commonly
illustrated as a point and line representing point and
interval estimates. This may give the false perception that all
points within the line are equally likely, and that points outside
the line are impossible. The density strip represents the entire
distribution in one dimension, giving a fuller description of the
uncertainty surrounding the quantity. The strips fade gradually
to white in the tails of a typical distribution, in contrast with line
plots and strips whose thickness is proportional to the density,
which terminate at a clear limit. This discourages casual significance
testing based on comparing an arbitrary point in the
tail of the distribution to a threshold. Shaded strips can also be
generalized to shaded regions, which illustrate the uncertainty
surrounding a continuously varying unknown quantity, such as
a survival curve or a forecast from a time series."