# A Student’s Guide to Bayesian Statistics

- Ben Lambert - Imperial College London (London, United Kingdom)

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.

### Supplements

https://study.sagepub.com/lambert

Hands down the best introduction to Bayesian approaches. Unlike other "introductions", Lambert doesn't assume an acquaintance with integral calculus and helps the student instead to build an intuition about Bayesian approaches (and their distinction from frequentist approaches). I'm sure this will take its place alongside Field's book on SPSS as a must-have for psychology undergraduates and post-graduates.

**Clinical, Educational and Health Psychology, University College London**

Probably the best introductory textbook for bayesian statistics. - In particular, it is very applied, provides a modern and up-to-date introduction, as well as clear guides how to best use the book.

**Department of Social Policy and Intervention, University of Oxford**

very essential has to my lectures

**Faculty of Engineering & Science, Greenwich University**

there aren't many students doing Bayesian Statistics analysis in dissertation this year so we don't provide such course unit. This book is a really helpful supplementary material for the students.

**School of Planning and Landscape, Manchester University**

A very useful reference with good examples, well-structured and progressive.

**International Finance and Management, Pyongyang University of Science And Technology**

Clear and useful guide

**Warwick Business School, Warwick University**