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This book is a treasure for both instructors and students. It is written by a master, award-winning teacher with an unparalleled expertise of getting difficult concepts across in a deceptively simple fashion. Written in clear functional English, it both teaches the usual applied statistical methods, as well as provides a gentle introduction to Bayesian methods throughout the book. This is, in essence, more of a new book than just a new edition of an existing one.
Introduction to statistics is a busy field, and Stinerock explains the subject in a careful and friendly manner. The inclusion of Bayesian methods in the second edition is an important contribution — when it is encountered at the beginning of the statistical journey, it allows the reader to appreciate the richness of the Bayesian approach without dealing with the analytical and computational complexities of the subject.
This book is a wonderful primer for learning both statistics and introductory R programming. It is clearly written, provides straightforward explanations of traditional and Bayesian methods, has a lot of supporting material for instructors and students including numerous practice data sets and solved exercises.
A reading list document with clear guidance to support students working on their individual student projects at MA level- clearly written with relevant examples to support.
This is a really useful book and will be useful as a teaching resource for myself as a lecturer. It would be useful for MSc students but I think might be a little confusing for my BSc cohort
This is a perfect book for R education. Thank you.
Too advanced for my students. Need something simpler.
Not as basic as I would have liked.
Useful book, but perhaps not aimed at the total beginner students I am working with. This seems more directed for those working in social statistics - which would be well placed
Due to its contents and the clarity of the presentations.
