WINNER OF THE 2005 DEGROOT PRIZE! This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. This book covers a much wider range of topics than a typical introductory...(展开全部)

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mat...(展开全部)

WINNER OF THE 2005 DEGROOT PRIZE! This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. This book covers a much wider range of topics than a typical introductory...(展开全部)

Causality is central to the understanding and use of data. Without an understanding of cause effect relationships, we cannot use data to answer questions as basic as, “Does this treatment harm or help patients?” But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding...(展开全部)

Algebraic topology is a basic part of modern mathematics and some knowledge of this area is indispensable for any advanced work relating to geometry, including topology itself, differential geometry, algebraic geometry and Lie groups. This book provides a treatment of algebraic topology both for teachers of the subject and for advanced graduate students in mathematics either sp...(展开全部)

Going beyond traditional textbook topics, 'A Modern Course in Statistical Physics' incorporates contemporary research in a basic course on statistical mechanics. From the universal nature of matter to the latest results in the spectral properties of decay processes, this book emphasizes the theoretical foundations derived from thermodynamics and probability theory underlying al...(展开全部)

This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. Intended for first-year graduate students, this book can be use...(展开全部)

This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. Intended for first-year graduate students, this book can be use...(展开全部)

Casella 在福特汉姆大学完成了他的本科教育，在普渡大学完成了研究生教育。他曾在罗格斯大学、康奈尔大学和佛罗里达大学任教。他的贡献集中在统计学领域，包括蒙特卡洛方法、模型选择和基因组分析。他在贝叶斯和经验贝叶斯方法方面特别活跃，其作品与斯坦因现象相联系，涉及评估和加速马尔科夫链蒙特卡洛方法的收敛性，如他的Rao-Blackwellisation技术，以及将拉索重塑为具有独立拉普拉斯先验的贝叶斯后验模式估计。 Casella于1988年被任命为美国统计学会和数学统计研究所的研究员，并于1989年成为国际统计学会的当选研究员。2009年，他被任命为西班牙皇家科学院外籍院士。 Roger Lee Berger 是美国统计学家和教授，与合作者 George Casella 于1990年首次出版《Statistical Inference》一书。