Statistical Inference 2nd edition

Intended for first-year graduate students specializing in statistics, this textbook seeks to build theoretical statistics from the first principles of probability theory. It covers the basics of probability theory and details major statistical principles, including sufficiency, likelihood, and invariance. It then outlines the methods of inference, estimation, and hypothesis testing. Special topics like asymptotic evaluations, analysis of variance and regression, and regression models are also discussed. Casella teaches at the University of Florida. Berger teaches at North Carolina State University. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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 used for students majoring in statistics who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.