--- product_id: 62842939 title: "DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial" price: "G$44415" currency: GYD in_stock: true reviews_count: 13 url: https://guyana.desertcart.com/products/62842939-data-analysis-bayesian-tutorial-2e-paper-a-bayesian-tutorial store_origin: GY region: Guyana --- # DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial **Price:** G$44415 **Availability:** ✅ In Stock ## Quick Answers - **What is this?** DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial - **How much does it cost?** G$44415 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [guyana.desertcart.com](https://guyana.desertcart.com/products/62842939-data-analysis-bayesian-tutorial-2e-paper-a-bayesian-tutorial) ## 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 Buy DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial 2 by SIVIA, Devinderjit (ISBN: 9780198568322) from desertcart's Book Store. Everyday low prices and free delivery on eligible orders. Review: the best introduction to practical Bayesian inference that exists - I rarely write reviews on desertcart but I have to say here that of the many, many books on Bayesian theory and practice that I have read over 20 years of running a consultancy which specialises in the use of these techniques, this is certainly the best as an introduction to the modern approach to Bayesian thinking in scientific problems. After the first chapter shows why the ideas are important and where they came from, it exudes practical advice rather then unnecessary theory and continues in a carefully-considered fashion developing the complexity and background until at the end we are exposed to some pretty advanced ideas where the appropriate level of theory is then injected. Once you have absorbed the various messages thoroughly including e.g. - the caveats - how to specify realistic prior knowledge - where approximations are useful and when they are not you will be armed to use your own expert knowledge to attack problems which - although they may at first seem to be unmanageable - will be forced to yield to the subtlety and power of probability theory via Bayes' theorem if you can collect enough data of useful quality. I disagree strongly with one of the other reviewers here who likes everything except the section on Nested Sampling by John Skilling at the end. It may be a little different in tone but the technique is sound, important and rather easy to implement, and variations have been making waves in difficult high-dimensional problems in areas such as astrophysics for years now. It has a bright future and this is an excellent introduction to it. If you are interested in the modern Bayesian perspective and want real gravity, rigour and depth (along with long-winded bluster, humour and personal attacks on critics) then go for Jaynes' "Probability Theory: the Logic of Science" Probability Theory: The Logic of Science: Principles and Elementary Applications Vol 1 which is the 'reference book' (though untypical in form & slightly unfinished) to support this excellent practical introduction. Review: Five Stars - Good introductory book an Bayesian statistics. Concise and quite complete, requires some background in calculus but very accessible book. ## Technical Specifications | Specification | Value | |---------------|-------| | Best Sellers Rank | 820,298 in Books ( See Top 100 in Books ) 714 in Engineering Physics 859 in Higher Education of Engineering 981 in Higher Mathematical Education | | Customer reviews | 4.6 4.6 out of 5 stars (80) | | Dimensions | 23.22 x 19.2 x 1.45 cm | | Edition | 2nd | | ISBN-10 | 0198568320 | | ISBN-13 | 978-0198568322 | | Item weight | 408 g | | Language | English | | Print length | 246 pages | | Publication date | 1 Jun. 2006 | | Publisher | Oxford University Press | ## Images ![DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial - Image 1](https://m.media-amazon.com/images/I/61QffpXFLhL.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ the best introduction to practical Bayesian inference that exists *by M***S on 13 April 2012* I rarely write reviews on Amazon but I have to say here that of the many, many books on Bayesian theory and practice that I have read over 20 years of running a consultancy which specialises in the use of these techniques, this is certainly the best as an introduction to the modern approach to Bayesian thinking in scientific problems. After the first chapter shows why the ideas are important and where they came from, it exudes practical advice rather then unnecessary theory and continues in a carefully-considered fashion developing the complexity and background until at the end we are exposed to some pretty advanced ideas where the appropriate level of theory is then injected. Once you have absorbed the various messages thoroughly including e.g. - the caveats - how to specify realistic prior knowledge - where approximations are useful and when they are not you will be armed to use your own expert knowledge to attack problems which - although they may at first seem to be unmanageable - will be forced to yield to the subtlety and power of probability theory via Bayes' theorem if you can collect enough data of useful quality. I disagree strongly with one of the other reviewers here who likes everything except the section on Nested Sampling by John Skilling at the end. It may be a little different in tone but the technique is sound, important and rather easy to implement, and variations have been making waves in difficult high-dimensional problems in areas such as astrophysics for years now. It has a bright future and this is an excellent introduction to it. If you are interested in the modern Bayesian perspective and want real gravity, rigour and depth (along with long-winded bluster, humour and personal attacks on critics) then go for Jaynes' "Probability Theory: the Logic of Science" Probability Theory: The Logic of Science: Principles and Elementary Applications Vol 1 which is the 'reference book' (though untypical in form & slightly unfinished) to support this excellent practical introduction. ### ⭐⭐⭐⭐⭐ Five Stars *by Z***G on 1 November 2016* Good introductory book an Bayesian statistics. Concise and quite complete, requires some background in calculus but very accessible book. ### ⭐⭐⭐⭐⭐ Great book for applied Bayesian *by A***R on 24 October 2016* One of the best books in practical application of Bayesian statistics. It has clear examples and solutions applied. --- ## 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://guyana.desertcart.com/products/62842939-data-analysis-bayesian-tutorial-2e-paper-a-bayesian-tutorial](https://guyana.desertcart.com/products/62842939-data-analysis-bayesian-tutorial-2e-paper-a-bayesian-tutorial) --- *Product available on Desertcart Guyana* *Store origin: GY* *Last updated: 2026-06-03*