Statistical modeling with R: a dual frequentist and Bayesian approach for life scientists
这本书面向生命科学领域的研究生，用通俗易懂的方式讲解频率学派和贝叶斯统计的基础，涵盖线性与广义线性混合模型，并配有R代码和数据集，适合应用统计课程。
This book is excellent for students in statistics towards the end of their undergraduate studies but even more so for graduate students in life sciences working with applied statistics.It covers the basics of frequentist and Bayesian statistics, and also likelihood theory in a simple but thorough way, without going into any great mathematical detail.The most common MCMC algorithms are presented accessibly and the book covers essential topics on linear and generalized linear mixed models with several extensions.It summarizes key papers and books and connects well to previous literature on statistical modelling.For several years, I gave a course on Controversies in statistics for doctoral students in microdata analysis at Dalarna University.The students had a variety of backgrounds from their undergraduate studies, economics, computer science, biology, and a few with a background in statistics.The course also covered linear and generalized linear mixed models with applications in R. If this book had been available at the time, I would definitely have used it.Especially since all pieces of R code and data to run the examples in the book are available on a well-structured companion website.It would have been the perfect book for the course.A reader expecting a condensed textbook on mathematical statistics will be disappointed though.The author has put a rather personal touch to it with elaborate texts explaining different concepts in a familiar, comprehensible, and attainable way.The preface is quite extensive and covers several matters not connected to statistics.Here, I disagree with the author.Pineapple on pizza is an excellent mix!I believe the author uses the possibility that a preface offers to lower the threshold of the topic for students that do not have a strong background in statistics.It does indeed give a smooth introduction to the book letting the reader get acquainted with the author's style of writing.The book is a novel contribution to the literature on statistical modelling, it has my highest endorsement, and I look forward to using it in future graduate courses on applied statistics.