  Bayesian data analysis is about more than just computing a posterior
distribution, and Bayesian visualization is about more than trace plots of
Markov chains. Practical Bayesian data analysis, like all data analysis, is an
iterative process of model building, inference, model checking and evaluation,
and model expansion. Visualization is helpful in each of these stages of the
Bayesian workflow and it is indispensable when drawing inferences from the
types of modern, high-dimensional models that are used by applied researchers.
