The chapter introduces the book "Ecological Models and Data in R" by Ben Bolker, providing an overview of the content and scope. It acknowledges the contributions of various individuals and institutions that supported the author's work. The chapter also outlines the structure of the book, which covers topics such as exploratory data analysis, deterministic and stochastic functions, likelihood and power analysis, optimization, and dynamic models. It emphasizes the importance of combining models with data to answer ecological questions and highlights the need for a solid understanding of statistics, computer skills, and ecological concepts. The chapter concludes with a discussion on the different frameworks for modeling, including theoretical and applied models, and the distinction between deterministic and stochastic approaches. It also touches on the philosophical differences between frequentist, likelihood-based, and Bayesian statistical methods, using a seed predation example to illustrate these concepts.The chapter introduces the book "Ecological Models and Data in R" by Ben Bolker, providing an overview of the content and scope. It acknowledges the contributions of various individuals and institutions that supported the author's work. The chapter also outlines the structure of the book, which covers topics such as exploratory data analysis, deterministic and stochastic functions, likelihood and power analysis, optimization, and dynamic models. It emphasizes the importance of combining models with data to answer ecological questions and highlights the need for a solid understanding of statistics, computer skills, and ecological concepts. The chapter concludes with a discussion on the different frameworks for modeling, including theoretical and applied models, and the distinction between deterministic and stochastic approaches. It also touches on the philosophical differences between frequentist, likelihood-based, and Bayesian statistical methods, using a seed predation example to illustrate these concepts.