--- product_id: 181027572 title: "Statistical Rethinking: A Bayesian Course with Examples in R and STAN (Chapman & Hall/CRC Texts in Statistical Science)" price: "€ 239.78" currency: EUR in_stock: true reviews_count: 8 url: https://www.desertcart.be/products/181027572-statistical-rethinking-a-bayesian-course-with-examples-in-r-stan store_origin: BE region: Belgium --- # Statistical Rethinking: A Bayesian Course with Examples in R and STAN (Chapman & Hall/CRC Texts in Statistical Science) **Price:** € 239.78 **Availability:** ✅ In Stock ## Quick Answers - **What is this?** Statistical Rethinking: A Bayesian Course with Examples in R and STAN (Chapman & Hall/CRC Texts in Statistical Science) - **How much does it cost?** € 239.78 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.be](https://www.desertcart.be/products/181027572-statistical-rethinking-a-bayesian-course-with-examples-in-r-stan) ## Best For - Customers looking for quality international products ## Why This Product - Free international shipping included - Worldwide delivery with tracking - 15-day hassle-free returns ## Description desertcart.com: Statistical Rethinking: A Bayesian Course with Examples in R and STAN (Chapman & Hall/CRC Texts in Statistical Science): 9780367139919: McElreath, Richard: Books Review: The Only readable Bayesian Analysis book I own - Over the years I've bought many Bayesian Analysis textbooks, the reason being I knew from ML academics that working with distributions is the "true" way of doing ML instead of just point estimates like in industrial ML. Before picking up this book I had given up on ever finding a real use-case for Bayesian ML because most of the other often recommended textbooks I owned were happy with long tedious mathematical derivations that wouldn't even bother explaining why a technique is important or how to implement it. This book is exceptional in that it gives you the historical context behind how certain techniques were evolved and an excellent intuition for how they work. The book also comes with an R Bayesian Analysis library which also has excellent ports in Julia and Python on Github. In the case where you don't have gigantic amounts of data and where you'd like to question assumptions that you have about data, this book will teach you a way of how to think about data that is sorely lacking in any sort of Deep Learning text. All of the algorithms in this book have stood the test of time and will continue to be relevant for the foreseeable future, thankfully this book exists to make these algorithms understandable. Review: Excellent course in Bayesian statistics - I must confess that I was quite hesitant to pick this book up when I first encountered the strong recommendations of experienced Bayesian practitioners. The 'cutesy' chapter titles and topics really threw me off, and as someone who actively uses Bayesian stats I was sure there would not be much for me to learn from this book. Well, I was quite wrong. This is one of the most enjoyable technical books I have read in a long time and it really helped focus my skills and put the tools of Bayesian stats in perspective. Highly recommended to even experienced data scientists... even when he is covering ground you know well, it gives you a new way to think and communicate it to others. ## Technical Specifications | Specification | Value | |---------------|-------| | Best Sellers Rank | #75,231 in Books ( See Top 100 in Books ) #8 in Mathematical & Statistical Software #19 in Sociology Research & Measurement #46 in Probability & Statistics (Books) | | Customer Reviews | 4.8 out of 5 stars 376 Reviews | ## Images ![Statistical Rethinking: A Bayesian Course with Examples in R and STAN (Chapman & Hall/CRC Texts in Statistical Science) - Image 1](https://m.media-amazon.com/images/I/81cEpsiTCFL.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ The Only readable Bayesian Analysis book I own *by M***M on June 15, 2020* Over the years I've bought many Bayesian Analysis textbooks, the reason being I knew from ML academics that working with distributions is the "true" way of doing ML instead of just point estimates like in industrial ML. Before picking up this book I had given up on ever finding a real use-case for Bayesian ML because most of the other often recommended textbooks I owned were happy with long tedious mathematical derivations that wouldn't even bother explaining why a technique is important or how to implement it. This book is exceptional in that it gives you the historical context behind how certain techniques were evolved and an excellent intuition for how they work. The book also comes with an R Bayesian Analysis library which also has excellent ports in Julia and Python on Github. In the case where you don't have gigantic amounts of data and where you'd like to question assumptions that you have about data, this book will teach you a way of how to think about data that is sorely lacking in any sort of Deep Learning text. All of the algorithms in this book have stood the test of time and will continue to be relevant for the foreseeable future, thankfully this book exists to make these algorithms understandable. ### ⭐⭐⭐⭐⭐ Excellent course in Bayesian statistics *by D***Y on March 20, 2022* I must confess that I was quite hesitant to pick this book up when I first encountered the strong recommendations of experienced Bayesian practitioners. The 'cutesy' chapter titles and topics really threw me off, and as someone who actively uses Bayesian stats I was sure there would not be much for me to learn from this book. Well, I was quite wrong. This is one of the most enjoyable technical books I have read in a long time and it really helped focus my skills and put the tools of Bayesian stats in perspective. Highly recommended to even experienced data scientists... even when he is covering ground you know well, it gives you a new way to think and communicate it to others. ### ⭐⭐⭐⭐⭐ Get this now *by A***R on December 29, 2024* This book was recommended from a colleague who is a former AWS Cloud Engineer, and another who is a fantastic Statistician. Both have said this is the book to read if you want to understand Bayesian statistics, but does not cover how and why it is superior to frequentist. This is not a basic statistics book and does not cover p-values. Recommend for MS or PhD students with a strong math background ## Frequently Bought Together - Statistical Rethinking: A Bayesian Course with Examples in R and STAN (Chapman & Hall/CRC Texts in Statistical Science) - Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science) - Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan --- ## Why Shop on Desertcart? - 🛒 **Trusted by 1.3+ Million Shoppers** — Serving international shoppers since 2016 - 🌍 **Shop Globally** — Access 737+ million products across 21 categories - 💰 **No Hidden Fees** — All customs, duties, and taxes included in the price - 🔄 **15-Day Free Returns** — Hassle-free returns (30 days for PRO members) - 🔒 **Secure Payments** — Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** — Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.be/products/181027572-statistical-rethinking-a-bayesian-course-with-examples-in-r-stan](https://www.desertcart.be/products/181027572-statistical-rethinking-a-bayesian-course-with-examples-in-r-stan) --- *Product available on Desertcart Belgium* *Store origin: BE* *Last updated: 2026-04-27*