The Azimuth Project
Bayesian statistical decision theory (Rev #2, changes)

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The idea

Bayesian statistical decision theory is a formal approach to making decisions under uncertainty. The big picture looks like this.

Bayesian statistical decision theory: the big picture

The model is at the heart of the framework. Typically it is based on scientific theory concerning some aspect of the real world. It is a stochastic model with some adjustable parameters which can be used to calculate the probability of observing particular outcomes.

The prior is a probability distribution which represents what assumed about the value of the parameters before the data is seen.

The utility function, or loss function evaluates the consequences of taking possible actions, given parameter values.