The book "Hierarchical Cluster Analysis and Conformity", written by the author's team as part of Michel Jambiu, B. G. Mirkina and S. A. Aivazian is a fascinating and deep dive into the world of statistical methods, which are becoming increasingly relevant in the modern information society. This work not only illuminates the theoretical foundations and practical aspects of hierarchical cluster analysis. but also offers readers unique approaches to interpreting data, which makes it an indispensable aid for students, Researchers and practitioners in the field of statistics, Sociology , Marketing and other related disciplines . The book begins with the basics, explaining what cluster analysis is and how it is used to group objects based on their similarity. The authors share their knowledge of various methods of hierarchical cluster analysis, such as the nearest neighbor method, the centroid method, and others, which allows the reader not only to understand the theory, but also to see how these methods are applied in practice. An important part of the book is a section devoted to data visualization, where the authors demonstrate how to correctly interpret the results and present them in a visual form. Readers interested in statistics, data analytics and machine learning will find in this book many useful examples and tasks that will help consolidate the knowledge they have gained. Students, graduate students and practitioners in the field of analytics will be able to use this work as a reference and source of inspiration for their own research. The book will also be of interest to those working in the field of marketing and sociology, since hierarchical cluster analysis allows you to identify hidden patterns and segment the audience. The topics raised in the book cover a wide range of issues, including methods of data processing, analysis of large amounts of information and the application of statistical models in real-world conditions. The authors emphasize the importance of choosing the right methods of analysis depending on the tasks, which makes their approach universal and applicable in various fields. Discussing practical case studies and real-life examples helps readers better understand how to use hierarchical cluster analysis to solve specific problems. The style of the authors is distinguished by clarity and accessibility, which makes complex concepts understandable even for those who are just beginning to get acquainted with the world of statistics. Michelle Jambiu, B. G. Mirkin and S. A. Aivazyan are experienced specialists in their fields, and their joint work reflects the rich experience and deep knowledge that they are ready to convey to readers. Their previous publications are also noteworthy, as they cover various aspects of statistics and data analysis, which emphasizes their expertise and authority in the field. “Hierarchical cluster analysis and compliance” is not just a textbook, but a real find for all who seek to deepen their knowledge in the field of data analysis. This book will be a reliable companion on the way to mastering complex methods of statistics and will help readers to unlock the potential of the data that surrounds them. If you are looking for a quality, informative and practical guide to hierarchical cluster analysis, then this book is your ideal choice.