The book "Smoothing Methods in Statistics" by Jeffrey S. Simonoff is part of the Springer Series in Statistics. It covers a wide range of smoothing methods used in statistical analysis, emphasizing practical applications over theoretical details. The author aims to highlight methods that work well in real-world data analysis, rather than focusing on the elegance of statistical theory. The book is designed for data analysts and statisticians interested in smoothing methods, providing a comprehensive overview of univariate and multivariate density estimation, nonparametric regression, and smoothing techniques for categorical data. Each chapter includes background material, computational issues, and exercises, making it suitable for both undergraduate and graduate courses. The book also provides references to original research and code for implementing the methods discussed. Despite its broad coverage, the book omits certain topics due to space constraints. The author acknowledges the contributions of numerous colleagues and students who helped shape the content.The book "Smoothing Methods in Statistics" by Jeffrey S. Simonoff is part of the Springer Series in Statistics. It covers a wide range of smoothing methods used in statistical analysis, emphasizing practical applications over theoretical details. The author aims to highlight methods that work well in real-world data analysis, rather than focusing on the elegance of statistical theory. The book is designed for data analysts and statisticians interested in smoothing methods, providing a comprehensive overview of univariate and multivariate density estimation, nonparametric regression, and smoothing techniques for categorical data. Each chapter includes background material, computational issues, and exercises, making it suitable for both undergraduate and graduate courses. The book also provides references to original research and code for implementing the methods discussed. Despite its broad coverage, the book omits certain topics due to space constraints. The author acknowledges the contributions of numerous colleagues and students who helped shape the content.