Many would probably be content to use Bayesian methodology for hypothesis testing, if it was easy, objective and with trustworthy assumptions. The Bayesian information criterion and some simple bounds ...

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

Bayesian inference in phylogenetic dynamics integrates genetic data with models of evolutionary and population processes to reconstruct the history and tempo of lineage diversification. By combining ...

The "replication crisis" refers to a problem in the sciences where findings from previous experiments don't hold up when studies are repeated. It is a particular issue for those in the behavioral ...

This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...

Among the books in my 'to-read' pile that I don't remember when I added, there was a book called 'The Grand Unified Theory of ...

A Bayesian re-analysis of hundreds of published clinical trials shows that statistically negative studies can hide strong ...

The Frontier of Avian Observation Data and Probabilistic Machine Learning—From Hierarchical Bayes to Causal, Geometric, ...