Over the past few decades, the life sciences have experienced an analytical revolution. With powerful computers now widely available, students and researchers are expected to perform increasingly advanced statistical analyses--previously the domain of only statistical experts. However, most undergraduate and graduate students still lack the proper formal training needed to succeed. Regardless of your experience level, this book will teach you in an efficient, accessible, and occasionally humorous manner, ensuring you understand how and when to perform your analyses.The book uses the statistical language R, which is the choice of ecologists worldwide and is rapidly becoming the 'go-to' stats program throughout the life sciences. By using a single, real-world dataset throughout the book, readers will become deeply familiar with an imperfect but realistic set of data. Early chapters are designed to teach basic data manipulation skills and build good habits in preparation for learning more advanced analyses. This approach demonstrates the importance of viewing data through different lenses, facilitating an easy and natural progression from linear and generalized linear models through to mixed effects versions of those same analyses. Readers will also learn advanced plotting and data-wrangling techniques and gain an introduction to writing their own functions.Applied Statistics with R is suitable for senior undergraduate and graduate students, professional researchers, and practitioners throughout the life sciences, whether in the fields of ecology, evolution, environmental studies, psychology, or neuroscience.