Probability and Statistics in Examples and Tasks . Volume 3. The Theory of Information and Coding by Kelbert M. I. and Suhova Y. M. It is a unique publication that immerses the reader in the world of information theory and coding, revealing complex concepts in an accessible and understandable language. This volume completes a trilogy devoted to probability and statistics, and offers readers not only theoretical foundations, but also practical tasks that will help to consolidate the knowledge gained. If you are a student studying mathematics, statistics or computer science, or a professional working in the field of data analysis, information theory or telecommunications, this book will become an indispensable assistant for you. It is suitable for both beginners and more experienced readers seeking to deepen their knowledge in the field of encoding and transmitting information. It will also be of interest to teachers who are looking for quality materials to prepare for classes . In the third volume, the authors consider such important topics as entropy, mutual information, coding sources and channels, as well as various methods of data compression. Each chapter is filled with examples from real life, which makes the material more accessible and understandable. The reader will be able to see how theoretical concepts are applied in practice, which, of course, contributes to better assimilation of information. Kelbert and Sukhov use their unique style, which combines the rigor of the scientific approach and the accessibility of the presentation. They not only represent formulas and theorems, but also explain their meaning by showing how they can be used in various fields. This approach makes the book not just a textbook, but a real tool for self-development and professional growth. The topics raised in the book cover a wide range of issues related to the processing and transmission of information. In today's world, where data is becoming the main resource, knowledge of information theory and coding is becoming especially relevant. The book will help the reader understand how information is encoded, transmitted, and processed, which is a key aspect in areas such as computer science, telecommunications, and even artificial intelligence. In addition, "Probability and Statistics in Examples and Tasks. Volume 3" will be an excellent addition to the library of any researcher or practitioner. In it you will find not only theoretical calculations, but also a lot of tasks for self-solution, which will allow you to test your knowledge and skills. This makes the book not just a source of information, but also a tool for the practical application of the material studied. If you are looking for similar books, then you may be interested in publications such as Claude Shannon's Theory of Information or John D.'s Statistics for Researchers. Cooks. These books, as well as the work of Kelbert and Sukhov, offer an in-depth understanding of statistical methods and information theory. In conclusion, "Probability and statistics in examples and tasks. Volume 3. Information Theory and Coding” is not just a textbook, but a whole world of knowledge that will help you understand the complex issues of information theory and coding. This book will be your reliable companion on the way to understanding and mastering one of the most interesting and relevant areas in science. Do not miss the opportunity to expand your horizons and deepen your knowledge with this wonderful publication!