The book "Processing the results of multiple measurements. Criteria for elimination of gross errors. Methodological recommendations” is an indispensable work for all those engaged in scientific research, engineering development or any other activity related to accurate measurements. The authors, combining their knowledge and experience, offer readers a deep immersion in the world of statistics, data processing and error analysis, which makes this book relevant for both students and experienced professionals. The focus of the book is the most important task - processing multiple measurements. Anyone who has ever conducted experiments or collected data knows how critical it is to interpret the results. The book offers the reader not only theoretical foundations, but also practical methodological recommendations to eliminate gross errors, which allows to significantly increase the accuracy and reliability of the data received. This is especially important in areas such as physics, chemistry, biology, engineering and many others, where the slightest deviations can lead to serious consequences. Who will be interested in this book? First of all, it is addressed to students and graduate students of technical and natural sciences specialties who seek to deepen their knowledge in the field of statistics and data processing . The book will also be useful to practicing engineers, researchers and analysts working with experimental data and seeking to improve the quality of their research. It is important to note that even those who do not have in-depth knowledge of statistics will find available explanations and examples in the book, making it suitable for a wide audience. The topics raised in the book cover a wide range of issues related to data processing. The authors discuss in detail the methods of statistical analysis, including the criteria for eliminating gross errors, which allows the reader not only to understand how to identify and eliminate errors, but also to develop critical thinking in the process of data analysis. In today's world, where information is increasingly available, the ability to interpret data correctly and make informed decisions based on the information received becomes a necessary skill. The style of the authors is clear and structured, which makes the material easy to perceive. Each chapter of the book follows logically from the previous one, creating a holistic view of the data processing process. The authors use many examples and illustrations, which allows the reader not only to learn the theoretical aspects, but also to apply them in practice. This special attention to detail and the desire for accessibility make the book not only a tutorial, but also a reference book for everyone who works with data. If you are looking for literature that will help you better understand how to work with multiple dimensions and avoid gross errors, this book will be an excellent choice. It can become a basis for further study of statistics and data analysis, as well as a source of inspiration for new research. Do not miss the opportunity to enrich your knowledge and skills by immersing yourself in the world of accurate measurements and statistical analysis that this book opens before you.