Statistical Rethinking Fall 2017

Explore Bayesian statistical methods through this comprehensive lecture series delivered by Richard McElreath at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany during Fall and Winter 2017/2018. Master the fundamentals of statistical rethinking by learning how to approach data analysis from a Bayesian perspective, moving beyond traditional frequentist methods to develop a deeper understanding of uncertainty, probability, and causal inference. Discover how to build and interpret statistical models that reflect the complexity of real-world phenomena while avoiding common pitfalls in statistical reasoning. Work through practical examples and applications that demonstrate how Bayesian thinking can transform your approach to scientific inquiry and data analysis. Gain proficiency in modern statistical techniques including multilevel modeling, model comparison, and causal inference through 19 structured lectures that systematically build your understanding from basic probability concepts to advanced modeling strategies. Learn to think critically about statistical assumptions, interpret results more meaningfully, and communicate findings with appropriate uncertainty. These lectures serve as the perfect companion to the "Statistical Rethinking" textbook, providing visual explanations and detailed walkthroughs of key concepts that will reshape how you understand and practice statistics in research and applied settings.