The book <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SAR Image Analysis—A Computational Statistics Approach: With R Code, Data, and Applications</i> stands out as an exceptional resource dedicated to statistical methodologies to extract information from synthetic aperture radar (SAR) imagery, all within a computational framework using R programming language. The book covers a wide range of topics in 183 pages and seven chapters, including a detailed overview of SAR data acquisition and its strong connection with specific concepts of non-Gaussian statistical models due to the physical properties of the scene. Its primary objective is to consolidate a comprehensive repository about well-established and state-of-the-art parametric models utilized in SAR image processing. It also addresses the critical task of parameter estimation, which is essential for extracting valuable information from the data. Moreover, all of the R codes and datasets are available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">www.wiley.com/go/frery/sarimageanalysis</uri> , allowing readers to directly apply the concepts discussed and see their practical implications, making the learning experience more engaging as it bridges the gap between theory and practice.