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This book was used as essential reading throughout my module (on an MSc level) not just for learning the “what”, “why” and “how” about the key principles and theory behind Bayesian statistics; but for understanding the practical component for implementing statistical analysis the Bayesian way using Stan interfaced with RStudio through RStan package, as well as for learning the Stan and RStan coding etiquettes for implementing Bayesian modelling and gaining its mastery in Stan and RStudio.
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.
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.
very essential has to my lectures
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.
A very useful reference with good examples, well-structured and progressive.
Clear and useful guide
