Statistical methods are a key tool for all scientists working with data, but learning the basics continues to challenge successive generations of students. This accessible textbook provides an up-to-date introduction to the classical techniques and modern extensions of linear model analysis-one of the most useful approaches for investigating scientific data in the life and environmental sciences. While some of the foundational analyses (e.g. t tests, regression, ANOVA) are as useful now as ever, best practice moves on and there are many new general developments that offer great potential. The book emphasizes an estimation-based approach that takes account of recent criticisms of over-use of probability values and introduces the alternative approach that uses information criteria. This new edition includes the latest advances in R and related software and has been thoroughly “road-tested” over the last decade to create a proven textbook that teaches linear and generalized linear model analysis to students of ecology, evolution, and environmental studies (including worked analyses of data sets relevant to all three disciplines). While R is used throughout, the focus remains firmly on statistical analysis. The New Statistics with R is suitable for senior undergraduate and graduate students, professional researchers, and practitioners in the fields of ecology, evolution and environmental studies.

"Review from previous edition The book is suitable for undergraduate and graduate students, researchers and practitioners in biological sciences. I found it refreshing and worthy of wide use." - Basil Jarvis, The Biologist

"[T]his book is of great interest ... it is important to evaluate its value as a teaching tool for R for biologists. ... [T]he book's strength is that it takes an applied scientist through the necessary basic statistics, and shows step by step how to work with real data. The New Statistics with R is, furthermore, a great textbook for computer exercise sessions in any introductory statistical class (especially for the life sciences). With its help, one should be able to design a very attractive course for both applied and more theoretical students." - Krzysztof Bartoszek, Systematic Biology

"... overall the book gives useful, ecumenical, and reliable statistical advice. I would recommend it for courses that are trying to equip students who already know elementary statistics with the basic tools they need to understand and perform analyses of real, messy data." - Ben Bolker, Quarterly Review of Biology