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 ...

Understanding Bayesian inference through a drinking invitationHow does probability change with new information?Today's goal:Understand Bayesian inference using familiar problems and connect it to ...

Part I: Fundamentals of Bayesian inference. Probability and inference -- Single-parameter models -- Introduction to multiparameter models -- Asymptotics and connections to non-Bayesian approaches -- ...

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 ...

A methodological commentary questions the Bayesian modelling, self-reported outcomes and causal interpretations in a recent ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

The statistical architecture behind the new analysis deserves attention because it differs meaningfully from the ...