000			01759nam a22001817a 4500
020			_a9781473916364
082	0	4	_a519.542 _bLAM/S
100	1		_aLambert, Ben,
245	1	2	_aA Student's Guide to Bayesian statistics
246			_aStudent's Guide to Bayesian statistics
260			_aLondon _bSage Publishers _c2018
300			_axx, 498 p.
505	0		_aAn introduction to Bayesian inference -- Understanding the Bayesian formula -- Analytic Bayesian methods -- A practical guide to doing real-life Bayesian analysis: Computational Bayes -- Hierarchical models and regression.
520			_a"Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first student-focused introduction to Bayesian statistics. Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, student-friendly language to provide approachable instruction perfectly aimed at statistics and Bayesian newcomers. Through a logical structure that introduces and builds upon key concepts in a gradual way and slowly acclimatizes students to using R and Stan software, the book covers: An introduction to probability and Bayesian inference, Understanding Bayes' rule, Nuts and bolts of Bayesian analytic methods, Computational Bayes and real-world Bayesian analysis, Regression analysis and hierarchical methods. This unique guide will help students develop the statistical confidence and skills to put the Bayesian formula into practice, from the basic concepts of statistical inference to complex applications of analyses." --
650		0	_aBayesian statistical decision theory.
650		7	_aBayesian statistical decision theory.
942			_cBK
999			_c2657 _d2657