Bayesian Core: A Practical Approach to Computational Bayesian Statistics eBook

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Bayesian Core: A Practical Approach to Computational Bayesian Statistics
After that, it was down to attitude. —Ian Rankin, Black & Blue. — The purpose of this book is to provide a self-contained (we insist!) entry into practical and computational Bayesian statistics using generic examples from the most common models for a class duration of about seven blocks that roughly correspond to 13 to 15 weeks of teaching (with three hours of lectures per week), depending on the intended level and the prerequisites imposed on the students. (That estimate does not include practice—i. e. , programming labs—since those may have a variable duration, also depending on the s- dents’ involvement and their programming abilities. ) The emphasis on practice is a strong feature of this book in that its primary audience consists of gr- uate students who need to use (Bayesian) statistics as a tool to analyze their experiments and/or datasets. The book should also appeal to scientists in all ?elds, given the versatility of the Bayesian tools. It can also be used for a more classical statistics audience when aimed at teaching a quick entry to Bayesian statistics at the end of an undergraduate program for instance. (Obviously, it can supplement another textbook on data analysis at the graduate level.

This is a digital product.

Bayesian Core: A Practical Approach to Computational Bayesian Statistics is written by Jean-Michel Marin; Christian Robert and published by Springer. The Digital and eTextbook ISBNs for Bayesian Core: A Practical Approach to Computational Bayesian Statistics are 9780387389837, 0387389830 and the print ISBNs are 9780387389790, 0387389792.