Statistical Rethinking | Bayesian Modeling | Richard McElreath
Richard McElreath
Comprehensive introduction to Bayesian statistical modeling, covering probability theory, MCMC, and practical applications. Taught by renowned statistician Richard McElreath.
University CoursesMachine LearningR
Introduction
This course, "Statistical Rethinking Winter 2015" by Richard McElreath, provides a comprehensive introduction to Bayesian statistical modeling. The course covers a wide range of topics, including probability theory, Markov Chain Monte Carlo (MCMC) methods, and the application of Bayesian techniques to real-world problems.
Highlights
Comprehensive coverage of Bayesian statistical modeling
Hands-on demonstrations and examples using the R programming language
Emphasis on practical applications and problem-solving
Taught by renowned statistician Richard McElreath
Recommendation
This course is highly recommended for anyone interested in learning Bayesian statistics and its practical applications. It is suitable for students, researchers, and professionals in fields such as social sciences, biology, and data science who want to deepen their understanding of statistical modeling and inference.
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