Statistics ·
Bayesian Modelling
A brief note on separating a likelihood, prior, and scientific target.
Structure
Bayesian inference updates a prior through a likelihood: $p(\theta\mid y) \propto p(y\mid\theta)p(\theta)$. The model’s assumptions deserve at least as much attention as its posterior summaries.