[peatmoss]

I think this is an important point. Having worked in / proximate to public policy kinds of problems, Bayesian methods have some really great properties:

1. easier interpretation of results than frequentist methods for lay people (business strata, elected officials, or other decision makers)

2. Uncertainty can be quantified and visualized reasonably well, which helps decision makers not think of stats as a magic box that produces a single answer.

3. Sensitivity analysis can be placed right up front: selection of priors representative of the beliefs of differing opinions / ideologies can inform decision makers of when they should consider changing their minds, and when they might still hold out.

Downsides of Bayesian methods:

1) Conceptually more involved than typical maximum likelihood estimation methods

2) Computationally expensive

3) Methods might not be as well known to a nominally stats-savvy audience.