This book, "Modern Applied Statistics with S," is the fourth edition of a widely used text for statistical analysis using the S programming language. It is intended for both introductory users of S and for classroom use. The book covers modern statistical methods and focuses on using the current S environments, such as S-PLUS and R, for data analysis. It includes a companion volume that provides a more in-depth discussion of programming in S. The book is structured into chapters that cover various statistical topics, including data manipulation, the S language, graphics, univariate statistics, linear statistical models, generalized linear models, non-linear and smooth regression, tree-based methods, random and mixed effects, exploratory multivariate analysis, classification, survival analysis, time series analysis, spatial statistics, and optimization. Each chapter provides a summary of the methods discussed, along with examples and exercises. The book is not a text in statistical theory but rather a practical guide to applying statistical methods using S. It emphasizes the use of S for data analysis and the graphical capabilities of the software. The authors acknowledge the contributions of the S environment's developers and the many individuals who have contributed to the software's development and testing. The book includes typographical conventions for setting apart S language constructs and commands, as well as notes specific to different S environments. It also provides references and an index for further reading. The authors welcome feedback and corrections from readers.This book, "Modern Applied Statistics with S," is the fourth edition of a widely used text for statistical analysis using the S programming language. It is intended for both introductory users of S and for classroom use. The book covers modern statistical methods and focuses on using the current S environments, such as S-PLUS and R, for data analysis. It includes a companion volume that provides a more in-depth discussion of programming in S. The book is structured into chapters that cover various statistical topics, including data manipulation, the S language, graphics, univariate statistics, linear statistical models, generalized linear models, non-linear and smooth regression, tree-based methods, random and mixed effects, exploratory multivariate analysis, classification, survival analysis, time series analysis, spatial statistics, and optimization. Each chapter provides a summary of the methods discussed, along with examples and exercises. The book is not a text in statistical theory but rather a practical guide to applying statistical methods using S. It emphasizes the use of S for data analysis and the graphical capabilities of the software. The authors acknowledge the contributions of the S environment's developers and the many individuals who have contributed to the software's development and testing. The book includes typographical conventions for setting apart S language constructs and commands, as well as notes specific to different S environments. It also provides references and an index for further reading. The authors welcome feedback and corrections from readers.