Statistical Rethinking 2023 - Markov Chain Monte Carlo

Dive into the world of Markov Chain Monte Carlo (MCMC) in this comprehensive lecture from Richard McElreath's Statistical Rethinking 2023 series. Begin with an introduction to the topic, then explore the concept of King Markov and its relevance to statistical analysis. Delve into the intricacies of MCMC methods, followed by an in-depth look at Hamiltonian Monte Carlo. After a brief pause, learn about the New Jersey Wine example and its application to MCMC. Examine various MCMC diagnostics to ensure the reliability of your results. Investigate the use of Item Response Theory (IRT) in analyzing judges' decisions. Conclude with a summary and outlook on the future of MCMC in statistical analysis. Access additional course materials through the provided GitHub repository and enhance your understanding of this powerful statistical technique.

Introduction
King Markov
MCMC
Hamiltonian Monte Carlo
Pause
New Jersey Wine
MCMC diagnostics
Judges and IRT
Summary and outlook