Bayesian Workflow: New Book by Gelman, Vehtari and McElreath

📚 Bayesian Workflow — A New Book Is Coming!

Andrew Gelman, Aki Vehtari and Richard McElreath, three major figures in modern statistics, are publishing a book dedicated to Bayesian workflow, with contributions from several co-authors and half of the chapters focused on real case studies.

🔵 What is Bayesian workflow? It is an iterative process for building, evaluating, and improving statistical models using the Bayesian probability framework. It includes prior selection, model checking, and result analysis.

📊 The authors:

• 🎓 Andrew Gelman — Columbia University, co-author of Bayesian Data Analysis.
• 🧮 Aki Vehtari — Aalto University, expert in computational Bayesian inference.
• 📖 Richard McElreath — author of the widely-read Statistical Rethinking.

🧑‍💻 Related tools: Stan, BRMS, PyMC, ArviZ.

💡 Explanation in a nutshell

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Bayesian statistics is a way of reasoning under uncertainty. Unlike traditional methods, it incorporates prior knowledge and updates it with data. This book teaches how to carry out that process in a systematic and reproducible way, from model construction to communicating results.

More information at the link 👇

Bayesian Workflow [cover] | R-bloggers

Ah great, the new book on Bayesian workflow by Andrew Gelman, Aki Vehtari, Richard McElreath I knew they were working on is about to appear! …

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