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Mathematical Statistics
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Binding: Hardcover
Dewey Decimal Number: 519.5
EAN: 9780387953823
Edition: 2nd
ISBN: 0387953825
Label: Springer
Manufacturer: Springer
Number Of Items: 1
Number Of Pages: 520
Publication Date: October 05, 2007
Publisher: Springer
Studio: Springer
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Editorial Review:
This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are usefulin statistics. The second chapter introduces some fundamental concepts in statistical decision theory and inference. Chapters 3-7 contain detailed studies on some important topics: 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. In addition to the classical results that are typically covered in a textbook of a similar level, this book introduces some topics in modern statistical theory that have been developed in recent years, such as Markov chain Monte Carlo, quasi-likelihoods, empirical likelihoods, statistical functionals, generalized estimation equations, the jackknife, and the bootstrap. Jun Shao is Professor of Statistics at the University of Wisconsin, Madison. Also available: Jun Shao and Dongsheng Tu, The Jackknife and Bootstrap, Springer- Verlag New York, Inc., 1995, Cloth, 536 pp., 0-387-94515-6.
Customer Reviews
Average Rating: 
Rating:  - Has everything you need, if you can read and understand it.
I don't know if statistics are just that difficult a subject or statistics writers just aren't good. Either way I have not found a satisfactory statistics book that treats the subject rigorously, but still readable. This book is an excellent reference. However, it's notation is cumbersome, if you're not used to it.
Before I started taking the class that uses this book, I took four undergraduate probability and statistics classes, as well as studied advanced topics such as measure ... Read More
Rating: - Good reference
This book, coupled with its accompanying exercises volume is a good source for beginning graduate level statistics.
Rating:  - Excellent, very clear, accurate notations
I know it must be a sign of extreme geekyness to be reviewing statistics books... but it happens to be one of my passions (so that proves it takes all kinds of people to make the world go around). I find this book to be unusually clear. Printing is also of high quality and I did not spot sloppy notation errors (though I was not looking intensely). I would judge the level to be about first of second year graduate level. First chapter lays out probability theory very well and introduces the more standard ... Read More
Rating: - Great book, not for kids
Don't waste your time: this is a rigorous book on mathematical statistics, done right, for mathematically mature readers.
If you want a plug and chug manual, buy something else. If you want precision and rigor, buy this.
Rating: - Worth the time reading
Very readible, precise and concise treatment of statistics. Requires mathematical maturity. Although it doesn't require a background in measure theory, some familiarity (or willingness to learn) would be really helpful (Ch. 1 provides an overview of measure-theoretic probability). I read the first half of it in a PhD level statics class. I found its approach refreshing after taking an engineering oriented senior level/grad statistics class. I still frequently consult it.
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