Bayesian statistics is an approach to data analysis and parameter estimation based on Bayes’ Theorem. This Primer describes the stages involved in Bayesian analysis, from specifying the prior and data models, to deriving inference, model checking and refinement. Bayesian analysis has been successfully employed across a variety of research fields, including social sciences, ecology, genetics, medicine, and more. We discuss these applications and propose strategies for reproducibility and reporting standards. Finally, we outline the impact of Bayesian analysis in artificial intelligence, a major goal in the next decade.
|Number of pages||60|
|Journal||Nature Reviews Methods Primers|
|Publication status||Accepted/In press - 21 Oct 2020|