“A wonderful and highly readable text that has the potential to have a great impact on the early training of biology students. . . . Quantifying Life is the best source for biology students to begin their study of quantitative modeling. The strengths of Quantifying Life are its size, choice of content, accessibility, price, and perhaps above all its approach to computing. I am also very excited about the use of the R language over other software or programming languages. . . . If you are a serious student of biology, then I strongly recommend to you to read Quantifying Life. I also believe that this book is a valuable resource for mathematicians and other quantitative scientists that find themselves working with biologists. It may prove very helpful in communicating with their collaborators in the life sciences.”

Jason M. Graham, University of Scranton | MAA Reviews

“Quantifying Life . . . is an intriguing addition to the literature because of its hybrid nature: it combines some approaches to study data typically addressed in textbooks of biostatistics with others that are usually found in textbooks of mathematical biology. This approach is useful because it allows students to understand links between issues that are generally discussed in separate courses and to develop a more open mind in the numerical analysis of biological data. . . . This book deserves a space in the bookcase of people that want an introductory text to mathematical modelling in life sciences.”

SimoneFattorini, University of L'Aquila, Italy | Biological Conservation

“The book has seventeen short chapters, each of which is meant to represent a week’s worth of material. Thus a big fraction of the book could be covered in a semester. Each chapter includes a bit of mathematics, necessarily quite elementary, some simple biological applications, and some computing exercises in R. The author is adamant that pencil-and-paper exercises are not enough; there has to be some computing. The students are not expected to know anything about R initially. The first exercises are extremely simple, and the complexity grows gradually as the students proceed through the book. By the end of the semester they should know a fair amount, which ought to serve them well in the future. . . . This looks to me like an improvement on the bio-calculus approach to educating biology students, and I hope this book proves to be a success.”

David S. Watkins, Washington State University | SIAM Reviews

“Taking a rare modeling approach, Kondrashov covers all of the mathematics and computation that biology students need, simultaneously introducing readers to programming in R (or any language really) and focusing on computational examples. And the writing is outstanding, the best I’ve seen in a mathematics text. I love this book—I will use pieces of it in every class I teach.”

Sarah Hews, Hampshire College

“Very exciting, especially for life science students and those who teach biology. There is a growing need for more quantitative understanding among life scientists, and the concepts and tools provided in Quantifying Life are exactly the types of tools the field needs. It includes many of the standard tools of modeling but places an emphasis on stochastic processes and computation, two topics less common to many introductory modeling texts. It is unique in its inclusion of Bayesian analysis, Markov models, the use of linear algebra techniques in modeling, and a strong programming component, all designed for students with very little mathematical background. Further, the exercises place a much-needed importance on analysis of results and not just memorization of facts. The conversational style, use of real-world and modern data and examples, and hands-on approach mixing biological and mathematical background with programming in R are fantastic.”

Hannah Callender, University of Portland