Statistical Theory: A Concise Introduction

Designed for a one-semester advanced undergraduate or graduate statistical theory course, Statistical Theory: A Concise Introduction, Second Edition, provides a clear and concise explanation of major statistical concepts, including parameter estimation, confidence intervals, hypothesis testing, asymptotic analysis, Bayesian inference, linear models, nonparametric statistics, and decision theory. It uses illustrative examples and self-contained chapters to balance clarity and rigor, with a focus on practical applications. The primary audience is students who want to understand the theoretical basis of mathematical statistics, and it will also be an excellent reference for researchers.

Format: Hardback
Length: 222 pages
Publication date: 23 December 2022
Publisher: Taylor & Francis Ltd

Designed for a one-semester advanced undergraduate or graduate statistical theory course, Statistical Theory: A Concise Introduction, Second Edition, offers a comprehensive and accessible introduction to the fundamental concepts, mathematics, and principles of statistical theory. Written with clarity and rigor, this textbook provides a solid foundation for students seeking to understand the theoretical basis of mathematical statistics, whether at the undergraduate or graduate level.

The book is organized into nine chapters, each covering a different aspect of statistical theory. The first chapter provides an overview of the field, introducing key concepts such as random variables, probability distributions, and statistical inference. Subsequent chapters delve into more detailed topics, including parameter estimation, confidence intervals, hypothesis testing, asymptotic analysis, Bayesian inference, linear models, nonparametric statistics, and decision theory.

To enhance understanding, the book employs a variety of pedagogical tools. Illustrative examples are used throughout to demonstrate the practical applications of statistical concepts, while formal definitions, theorems, and proofs provide a solid theoretical foundation. In some cases, a sketched version of a proof is presented, explaining the main ideas rather than delving into detailed technical mathematical and probabilistic arguments. This approach helps maintain a proper balance between clarity and rigor of exposition.

The second edition of the book has been extensively updated to reflect recent developments in the field. A new chapter on nonparametric estimation has been added, providing students with an introduction to this important topic. The chapter on statistical decision theory has also been significantly revised, with a focus on modern applications and computational methods. Other updates have been made throughout the text to ensure that it remains current and relevant.

One of the key features of the book is its accessibility. No prior knowledge of heavy calculus is required, and simple questions are scattered throughout the text to help students check their understanding of the material. Each chapter also includes a set of exercises that range in difficulty, allowing students to gradually build their skills and knowledge. Chapters and sections marked by asterisks contain more advanced topics and may be omitted depending on the student's background and interests.

The primary audience for the book is students who want to understand the theoretical basis of mathematical statistics. It is suitable for advanced undergraduate students who have completed a course in probability theory and statistics, as well as for graduate students who are embarking on a research career in statistical science. The book's concise and clear writing style makes it accessible to a wide range of students, and its emphasis on practical applications and real-world examples helps to reinforce the theoretical concepts.

In conclusion, Statistical Theory: A Concise Introduction, Second Edition, is an excellent textbook for students seeking to understand the theoretical basis of mathematical statistics. With its comprehensive coverage of key topics, clear explanations, and engaging pedagogy, this book provides a solid foundation for students embarking on a research career in statistical science or pursuing advanced studies in the field. Whether you are a novice or an experienced statistical practitioner, this book will be a valuable resource for your academic journey.

Weight: 600g
Dimension: 254 x 178 (mm)
ISBN-13: 9781032007458
Edition number: 2 ed