Mathematical Statistics

by Jun Shao

This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics. This new edition has been revised and updated and in this fourth printing, errors have been ironed out. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are useful in statistics. The second chapter introduces some fundamental concepts in statistical decision theory and inference. Subsequent chapters contain detailed studies on some important unbiased estimation, parametric estimation, nonparametric estimation, hypothesis testing, and confidence sets. A large number of exercises in each chapter provide not only practice problems for students, but also many additional results.

Genres: Mathematics

608 pages, Hardcover

First published January 1, 1999

Reviews

[Joe Cole · Rating 5 out of 5]

I'm very impressed with the author! For if a textbook is a reflection of what an author knows about some subject, then Shao represents a treasure trove of knowledge that is so eloquently shared in this book. Anyone serious about doing graduate-level reasearch in statistics should invest a year of studying this book. But be forwarned that most likely one will find this, due to the onslaught of measure theoretic analysis, one of the more challenging books to makes its way on the book shelf.

[Jette Stuart · Rating 3 out of 5]

This is great supplemental material to any undergraduate text in mathematical statistics.

[Mikoto · Rating 3 out of 5]

Frequently leaving key statements as exercise or referring to other books breaks the flow of the content. I would recommend the book by Schervish which covers similar topics but is more self-contained.