Description
Book SynopsisThis graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are useful in statistics.
Trade ReviewFrom the reviews of the second edition:
"The second edition of Mathematical Statistics continues to hold its identity among many other available books on mathematical statistics...The revised and updated version remains of high quality, and I recommend it for use as a text or reference book in a graduate statistics program." Journal of the American Statistical Association, September 2004
"The first edition of this book was published in 1999 … . The main changes include addition of new material in Chapter 1, addition and deletion of a number of exercises, addition of two new sub-sections … . The book remains valuable to instructors and graduate students of traditional mathematical statistics courses, specially for its large collection of problems and for its rigourous presentation." (Arup Bose, Sankhya: The Indian Journal of Statistics, Vol. 65 (3), 2003)
"This book is intended for an advanced postgraduate course in Mathematical Statistics, offered in a mathematically rigorous fashion. … in order to get to grips with rigorous mathematical statistics, this is an ideal book. Also, as a reference book, it is ideally suited. … Two particularly attractive features of the book are the large number of exercises at the end of each chapter – well over a hundred in each chapter, and the fact that asymptotic theory is studied throughout the book … ." (Tertius de Wet, SASJ – South African Statistical Journal, March, 2004)
Table of ContentsProbability Theory * Fundamentals of Statistics * Unbiased Estimation * Estimation in Parametric Models * Estimation in Nonparametric Models * Hypothesis Tests * Confidence Sets
