The book "Factory, Discriminant and Cluster Analysis" by Kim, Mueller et al . It is a fascinating and deep dive into the world of statistical methods that play a key role in data analysis. This publication will become an indispensable assistant for students, graduate students, researchers and practitioners working in the field of statistics, sociology, psychology, marketing and many other disciplines where the processing and interpretation of large amounts of information is required. The book discusses three main methods of data analysis: factor analysis, discriminant analysis, and cluster analysis. Each of these methods has its own unique features and applications, making them important tools for extracting meaningful information from complex datasets. Factor analysis helps to identify hidden factors that influence the observed variables, which is especially useful in psychology and sociology. Discriminant analysis allows you to classify objects based on their characteristics, which is used in marketing research and in medicine. Cluster analysis, in turn, helps to group objects by similarity, which is relevant in business for customer segmentation. The book is written in accessible language, which makes it understandable even for those who are just beginning to get acquainted with the world of statistics. The authors generously share examples from real practice, which allows the reader not only to understand the theoretical aspects, but also to see how these methods are applied in life. Each chapter contains practical tasks and illustrations that contribute to a better assimilation of the material. This makes the book not only a tutorial, but also a practical guide that can be used in everyday work. Who is this book intended for? First of all, it will be of interest to students and graduate students studying statistics and data analysis . However, its usefulness is not limited to the academic environment. Practitioners from various fields, such as marketing, sociology, psychology, biostatistics, and even economics, will find a lot of useful information in it. The book will also be useful to those who work with big data and want to learn how to extract valuable information from them. The topics raised in the book cover a wide range of issues related to data analysis. The authors not only explain how to apply different methods, but also discuss their limitations and possible errors, which is an important aspect for any researcher. The book emphasizes the importance of critical thinking and attentiveness in interpreting the results of analysis, which makes it especially valuable for those who seek a deep understanding of statistical methods. The style of the authors deserves a special mention. Kim and Mueller have a unique ability to explain complex concepts in a simple and understandable language, which makes their work available to a wide audience. Their previous publications, such as Fundamentals of Statistics and Methods of Data Analysis, have also been recognized for their clarity of presentation and practical focus. In conclusion, “Factory, Discriminant and Cluster Analysis” is not just a book about statistics; it is the key to understanding and using powerful data analysis tools. It inspires and motivates the reader to study and apply statistical methods in their practice. If you want to deepen your knowledge in the field of data analysis and learn how to apply these methods in practice, this publication will become your reliable companion in this fascinating journey.