Supporting Bayesian Analysis

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At the risk of oversimplification, it may be said that in the old days our conceptual universe included i) facts or observations, ii) assumptions, and iii) conclusions or results, with all of these things often treated as certainties or as optima. This way of looking at things is still deeply embedded in the language and forms of science, but our conceptual universe is much more nuanced now. Instead of certainties we have inferences with explicit reliabilities; instead of alleged optima we have entire distributions; and so on. How do build an infrastructure to confront the true complexity of inference, i.e., to embrace uncertainty rather than trying to push it out of view?

Analysis of current challenges

Current status

(how is this need being met today? what resources, tools are available?)

Problems and projected difficulties

(what is missing? what challenges are coming up?)

Related or overlapping projects

(who else is working on this? what are they doing?)

Goals for the working group

(specific goals for this topic)

Strategy for achieving goal

(be sure to include specific deliverables or milestones)

Progress in achieving goals

(give dates and provide links to outputs)